The Inverge Journal of Social Sciences (IJSS) is an online, open-access journal with double-blind peer review. Academic essays and research articles/papers are all published in the IJSS. Scholars of any age or from any profession are welcome to submit their scholarly research to the IJSS. In its publications, the IJSS covers all social science disciplines, including but not limited to the following fields: Development Studies Economics Entrepreneurship Education Gender Studies International Relations Management Sciences (Marketing, Finance, HRM, Project Management, Information Management, & others) Media Sciences Political Science Psychology Sustainable Development Goals Sociology IJSS is an online, open-access journal that offers publishing and research services to the academic and business sectors. Double-blind peer review is used to manage articles and papers by the IJSS. Frequency: Quarterly Dr. Muhammad Asif Editor-in-Chief Inverge Journal of Social Sciences (IJSS) ISSN (Online): 2959-4359, ISSN (Print): 3007-2018 Facebook: https://www.facebook.com/InvergeJSS/ Note: Authors are urged to use the IJSS online submission platform to submit their work electronically. Please adhere to the guidelines listed for each step of the online submission procedure. Before submitting, kindly adhere to the Author Guidelines as well.
The work is concurrently licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which permits others to share the work with an acknowledgement of the authorship and the work's original publication in this journal, while the authors retain copyright and grant the journal the right of first publication.
Modal Verb Variation in Pakistani and American English: A Corpus-based Comparative Study
This study explores the use of modal verbs in Pakistani and American English through a corpus-based analysis of data drawn from the Global Web-Based English (GloWbE) corpus. The study examines five modal verbs—must, should, may, might, and would—through a comparative analysis of their semantic, pragmatic, and collocational patterns in the two English varieties. Based on the frequency counts, concordance lines and collocational analysis, the study demonstrates that Pakistani English is more likely to be used in formal registers whereas American English is more conversational. There are also differences in collocational patterns that bear the cultural and practical impacts in both varieties. The findings provide an empirical evidence of regional variation in modal verb usage, contributing to the fields of World Englishes and Corpus Linguistics. Moreover, the study provides pedagogical implications in teaching English language based on the findings of the research, emphasizing the role of contextual and regional sensitivity in teaching and learning modal verbs. The study emphasizes the significance of corpus-based approaches in investigating authentic language use across different varieties of English. References Abdullayev, S. (2024). The pragmatic functions of modal verbs in discourse: A corpus-based study. Journal of New Century Innovations, 50(2), 148–150. Anwar, B. (2012). A sociolinguistic study of Urdu–English code-switching in Pakistan (Doctoral dissertation, Bahauddin Zakariya University, Multan). Anwar, B., & Maryam, S. (2017). The use of stative verbs as progressive in Pakistani English: A corpus-based study. Journal of Research in Social Sciences, 5(2), 121–134. Anwar, B., & Talaat, M. (2011). English in a non-native context: Distinctive features of Pakistani journalistic English. English Language and Literary Forum (ELF), 13(1), 25–42. Anwar, B., Ajmal, M., & Keezhatta, M. S. (2020b). Nativization of grammatical features in Pakistani English. Asian EFL Journal, 27(42), 92–106. Anwar, B., Butt, B., & Khan, R. M. I. (2019). Modal auxiliaries in Pakistani English newspapers: Social and pedagogical perspectives. Pakistan Social Sciences Review, 3(2), 164–177. Anwar, B., Iqbal, T., & Rasool, S. (2020a). Logical connectors in newspapers: A comparative study of Pakistani and British columns. Journal of Media Studies, 35(1). Anwar, N., & Butt, I. R. (2025). A comparative study of modality markers in Pakistani and US English: Evidence from GloWbE. International Journal of Social Sciences Bulletin, 3(11), 318–327. Arshad, N., Shahid, U., & Anwar, B. (2025). New Englishes and local context: Exploring strategies of pragmatic nativization in Pakistani English. Journal of Arts and Linguistics Studies, 3(3), 3565–3580. Biber, D. (2019). Text-linguistic approaches to register variation. Register Studies, 1(1), 42–75. Davies, M., & Fuchs, R. (2015). Expanding horizons in the study of World Englishes with the 1.9 billion word Global Web-based English Corpus (GloWbE). English World-Wide, 36(1), 1–28. D’Arcy, A., Haddican, B., Richards, H., Tagliamonte, S. A., & Taylor, A. (2013). Asymmetrical trajectories: The past and present of –body/–one. Language Variation and Change, 25(3), 287–310. Hundt, M. (2007). English mediopassive constructions: A cognitive, corpus-based study of their origin, spread, and current status (Vol. 58). Rodopi. Hunston, S., & Thompson, G. (Eds.). (2000). Evaluation in text: Authorial stance and the construction of discourse. Oxford University Press. Kachru, B. B. (2005). Asian Englishes: Beyond the canon (Vol. 1). Hong Kong University Press. Khan, F. W., Zafar, M. S., & Bukhtiar, H. (2021). A corpus analysis of modality in COVID-19–based editorials of Pakistani English newspapers. Balochistan Journal of Linguistics, 9. Leech, G. (2003). Modality on the move: The English modal. In R. Facchinetti, M. Krug, & F. Palmer (Eds.), Modality in contemporary English (pp. 223–240). Mahboob, A. (2009). English as an Islamic language: A case study of Pakistani English. World Englishes, 28(2), 175–189. McEnery, T., & Hardie, A. (2011). Corpus linguistics: Method, theory and practice (3rd ed.). Cambridge University Press. Mindt, D. (2025). Investigating diachronic shifts within a domain of English modality. English Language & Linguistics, 29(3), 505–526. Noshair, R., Arshad, M. U., & Hamza, M. A. (2025). Analyzing modal verbs as politeness markers in British and Pakistani English communication: A corpus-based comparative study. ASSAJ, 4(1), 3655–3666. Palmer, F. R. (2001). Mood and modality. Cambridge University Press. Rubab, Z., & Mahmood, M. A. (2025). Modal verbs in English and Shahmukhi Punjabi language: A corpus-driven comparative study. Journal of Applied Linguistics and TESOL, 8(1). Schneider, E. W. (2007). Postcolonial English: Varieties around the world. Cambridge University Press. Shahid, U., Anwar, B., & Amin, M. W. (2025). Cleft constructions in British and Pakistani English newspapers: A comparative analysis. Journal of Applied Linguistics and TESOL (JALT), 8(2), 2385–2395. Yasmeen, K., Nazeer, I., & Ahmad, K. (2022). Stance-modal and semi-modal verbs: A corpus-based study. Pakistan Social Sciences Review, 6(4), 30–40.
Copyright (c) 2026 Muhammad Dawood, Behzad Anwar, Maria Naureen https://creativecommons.org/licenses/by-nc-sa/4.0
Automation, Transparency, and Efficiency in Library Management through Blockchain and IoT Technologies
The purpose of this paper is to examine the literature on the applications of Blockchain and the Internet of Things (IoT) and to understand how libraries are engaging with this technology to enable users to feel more involved in the present and to share information about Library resources and services. Based on the existing literature, the fundamental models of Blockchain and its combination with IoT are extracted, documented, and illustrated, focusing on performance, implementation ability, and the layers discussed for both. The findings could also provide an empirical platform for comprehension of the technological and behavioural factors that drive adoption of blockchain and IoT to improve automation of services, transparency in records, and overall workplace efficiencies within libraries. The current study is a valuable addition to the body of library and information science literature in that it merges cutting-edge digital technologies with a widely accepted technology acceptance model, and its findings are of practical interest for librarians, system developers, and policy makers involved in smart library initiatives. The recent applications and current uses of blockchain and IoT in libraries are presented with the hope that they will help build up future work across various sectors. References Almarri, S., & Aljughaiman, A. (2024). Blockchain technology for IoT security and trust: A comprehensive systematic literature review. Sustainability, 16(23), 10177. https://doi.org/10.3390/su162310177 Al Sadawi, A., Hassan, M. S., & Ndiaye, M. (2021). A survey on the integration of blockchain with IoT to enhance performance and eliminate challenges. IEEE Access, 9, 54478–54497. https://doi.org/10.1109/ACCESS.2021.3070869 Asif, M., & Sandhu, M. S. (2023). Social media marketing revolution in Pakistan: A study of its adoption and impact on business performance. Journal of Business Insight and Innovation, 2(2), 67–77. Bansal, A., Arora, D., & Suri, A. (2018). Internet of things: Beginning of new era for libraries. Library Philosophy and Practice, 1–7. Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. SAGE Publications. Devi, P. D., Mirudhula, S., & Devi, A. (2021). Advanced library management system using IoT. In 2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) (pp. 150–154). IEEE. https://doi.org/10.1109/ICICCS51141.2021.9432378 Ennajeh, L., & Najjar, T. (2024). Blockchain technology adoption through the UTAUT model: Exploring the mediating role of trust. Journal of Telecommunications and the Digital Economy, 12(1), 328–355. https://doi.org/10.18080/jtde.v12n1.873 Frederick, D. (2019). Blockchain for libraries: A practical guide. Library Technology Reports, 55(8), 1–35. Fruin, C., & Joshi, S. (2021). Blockchain in interlibrary loan systems: A feasibility study. Journal of Library Administration, 61(4), 456–470. https://doi.org/10.1080/01930826.2021.1905036 Haque, E. U., Shah, A., Iqbal, J., et al. (2024). A scalable blockchain-based framework for efficient IoT data management using lightweight consensus. Scientific Reports, 14, 58578. https://doi.org/10.1038/s41598-024-58578-7 Khan, A. U., Zhang, Z., Chohan, S. R., & Rafique, W. (2022). Factors fostering the success of IoT services in academic libraries: A study built to enhance library performance. Library Hi Tech, 40(6), 1976–1995. https://doi.org/10.1108/LHT-06-2021-0179 Khan, M. K., & Ullah, A. (2024). Implication of IoT and its impact on library services: An overview. Inverge Journal of Social Sciences, 3(2), 63–72. https://doi.org/10.63544/ijss.v3i2.94 Khan, M. K. (2025). Transforming libraries with blockchain technology: An overview of its potential implementation, benefits, and challenges. Inverge Journal of Social Sciences, 4(1), 75–86. https://doi.org/10.63544/ijss.v4i1.127 Kharche, A., Badholia, S., & Upadhyay, R. K. (2024). Implementation of blockchain technology in integrated IoT networks for constructing scalable ITS systems in India. Blockchain: Research and Applications, 5(2), 100188. https://doi.org/10.1016/j.bcra.2024.100188 Laboso, P., Aruldoss, M., Thiyagarajan, P., Lakshmi, T. M., & Wynn, M. (2026). Library systems and digital-rights management: Towards a blockchain-based solution for enhanced privacy and security. Information, 17(2), 137. https://doi.org/10.3390/info17020137 Lamm, K., & Levin, D. (2018). Blockchain for digital rights management in libraries. Library Hi Tech, 36(4), 567–580. https://doi.org/10.1108/LHT-01-2018-0004 Meth, K. (2020). Blockchain in libraries: A practical guide. Library Technology Reports, 56(5), 1–40. Page, M. J., McKenzie, J. E., Bossuyt, P. M., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71 Research on the construction scheme of smart library based on blockchain technology. (2024). Measurement: Sensors, 31, 100943. https://doi.org/10.1016/j.measen.2023.100943 Rouf, B. A., & Raja, S. (2023). Applications of the Internet of Things (IoT) in academic libraries. In Ingenious librarianship: Enriching self-reliance. Today and Tomorrow’s Printers and Publishers. Sakamoto, Y. (2019). Blockchain for library resource sharing. Journal of Library and Information Science, 43(2), 123–135. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
Copyright (c) 2026 Muhammad Kabir Khan, Farha Zafira Binti Agos Lokman https://creativecommons.org/licenses/by-nc-sa/4.0
Physician-Patient Interaction Quality as a Predictor of Patient Satisfaction: Examining the Unique Contributions of Communication and Empathy in Pakistani Healthcare
To examine the associations among patients' perceptions of physician communication, physician empathy, and patient satisfaction in Pakistani hospital settings. A cross-sectional correlational study was conducted in public and private hospitals in Islamabad and Rawalpindi, Pakistan, between December 2024 and February 2025. Using purposive convenience sampling, 280 adult patients from psychiatry (n = 92), dermatology (n = 102), and cardiology (n = 86) completed the Communication Assessment Tool (CAT), the Jefferson Scale of Patient Perceptions of Physician Empathy (JSPPPE), and a 10-item patient satisfaction scale. Pearson correlations assessed bivariate associations. Multiple linear regression tested whether communication and empathy jointly predicted patient satisfaction. One-way ANOVA examined differences in satisfaction across specialties, and independent samples t-tests compared satisfaction by gender and hospital type. Physician communication was strongly correlated with physician empathy (r = .91, p < .001) and patient satisfaction (r = .90, p < .001). Physician empathy was also strongly correlated with patient satisfaction (r = .92, p < .001). In regression analysis, the model was significant, F(2, 277) = 825.47, p < .001, explaining 85.6% of the variance in patient satisfaction (R² = .856; adj. R² = .855). Both physician communication (B = 0.34, SE = 0.04, β = .39, p < .001) and physician empathy (B = 1.06, SE = 0.10, β = .56, p < .001) independently predicted higher patient satisfaction. No significant differences in satisfaction were found across specialties (F(2, 277) = 1.24, p = .29) or by gender (t(278) = 0.87, p = .38). Patients' perceptions of physician communication and empathy are strongly associated with patient satisfaction, and both contribute uniquely to satisfaction ratings. Interventions that strengthen patient-centred communication and empathic engagement may improve patient experience in time-constrained healthcare settings. References Aman-Ullah, A., Mehmood, W., Amin, S., & Abbas, Y. A. (2023). Corporate social responsibility and patient's intention to revisit: A serial mediation study witnessing the healthcare sector. Environmental Science and Pollution Research, 30(7), 17995–18023. https://doi.org/10.1007/s11356-022-23760-9 Arshad, M., Khan, S., Ahmad, S., Qamar, A., Naeem, H., & Arshad, A. (2026). Comparison of Physician Communication, Physician Empathy, Physician–Patient Concordance, and Patient Satisfaction Across Psychiatry, Cardiology, and Dermatology Departments. Inverge Journal of Social Sciences, 5(1), 268–278. https://doi.org/10.63544/ijss.v5i1.236 Atif, M., Sarwar, M. R., Azeem, M., Naz, M., Amir, S., & Nazir, K. (2016). Assessment of patient satisfaction with pharmacy services in Rawalpindi, Pakistan. International Journal of Clinical Pharmacy, 38(1), 145–151. https://doi.org/10.1007/s11096-015-0210-7 Derksen, F., Bensing, J., & Lagro-Janssen, A. (2013). Effectiveness of empathy in general practice: A systematic review. British Journal of General Practice, 63(606), e76–e84. https://doi.org/10.3399/bjgp13X660814 Doyle, C., Lennox, L., & Bell, D. (2013). A systematic review of evidence on the links between patient experience and clinical safety and effectiveness. BMJ Open, 3(1), e001570. https://doi.org/10.1136/bmjopen-2012-001570 Hafeez, A., Kiani, A. G., Din, S. U., Muhammad, W., Butt, K., Shah, S. M. A., & Shaikh, B. T. (2004). Prescription and dispensing practices in public sector health facilities in Pakistan: Survey report. Journal of the Pakistan Medical Association, 54(4), 187–191. Hojat, M., Louis, D. Z., Maxwell, K., Markham, F., Wender, R., & Gonnella, J. S. (2011). Patient perceptions of physician empathy, satisfaction with physician, interpersonal trust, and compliance. International Journal of Medical Education, 2, 83–87. https://doi.org/10.5116/ijme.4d00.b701 Howick, J., Moscrop, A., Mebius, A., Fanshawe, T. R., Lewith, G., Bishop, F. L., Mistiaen, P., Roberts, N., Dieninytė, E., Hu, X.-Y., Aveyard, P., & Onakpoya, I. J. (2018). Effects of empathic and positive communication in healthcare consultations: A systematic review and meta-analysis. Journal of the Royal Society of Medicine, 111(7), 240–252. https://doi.org/10.1177/0141076818769477 Hussain, A., Asif, M., Jameel, A., Hwang, J., Sahito, N., & Kanwel, S. (2019). Promoting OPD patient satisfaction through different healthcare determinants: A study of public sector hospitals. International Journal of Environmental Research and Public Health, 16(19), 3719. https://doi.org/10.3390/ijerph16193719 Hussain, S., Khalid, N., Ikram, A., Mirza, H., Conroy, R. M., & Aslam, M. (2022). Doctors' communication skills in military hospitals—A critical analysis. Pakistan Armed Forces Medical Journal, 72(3), 1011–1015. https://doi.org/10.51253/pafmj.v72i3.6437 Irving, G., Neves, A. L., Dambha-Miller, H., Oishi, A., Tagashira, H., Verho, A., & Holden, J. (2017). International variations in primary care physician consultation time: A systematic review of 67 countries. BMJ Open, 7(10), e017902. https://doi.org/10.1136/bmjopen-2017-017902 Jalil, A., Zakar, R., Zakar, M. Z., & Fischer, F. (2017). Patient satisfaction with doctor–patient interactions: A mixed methods study among diabetes mellitus patients in Pakistan. BMC Health Services Research, 17(1), 155. https://doi.org/10.1186/s12913-017-2094-6 Kane, G. C., Gotto, J. L., Mangione, S., West, S., & Hojat, M. (2007). Jefferson Scale of Patient's Perceptions of Physician Empathy: Preliminary psychometric data. Croatian Medical Journal, 48(1), 81–86. Makoul, G., Krupat, E., & Chang, C. H. (2007). Measuring patient views of physician communication skills: Development and testing of the Communication Assessment Tool. Patient Education and Counseling, 67(3), 333–342. https://doi.org/10.1016/j.pec.2007.05.005 Mushtaq, M., Khan, M. A., Ullah, S., & Ahmad, W. (2024). Satisfaction of patients in government medical teaching institutes of Peshawar, Khyber Pakhtunkhwa, Pakistan: A cross-sectional analytical study. Journal of the Pakistan Medical Association, 74(5), 892–897. https://doi.org/10.47391/jpma.9990 Riess, H., Kelley, J. M., Bailey, R. W., Dunn, E. J., & Phillips, M. (2012). Empathy training for resident physicians: A randomized controlled trial of a neuroscience-informed curriculum. Journal of General Internal Medicine, 27(10), 1280–1286. https://doi.org/10.1007/s11606-012-2063-z Sardar, M. A., Hussain, S., & Malik, M. A. (2020). Patients' satisfaction with health care delivery in the outpatients department of the Combined Military Hospital, Rawalpindi. Pakistan Armed Forces Medical Journal, 70(6), 1816–1820. https://doi.org/10.51253/pafmj.v70i6.5850 Street, R. L., Jr., Makoul, G., Arora, N. K., & Epstein, R. M. (2009). How does communication heal? Pathways linking clinician–patient communication to health outcomes. Patient Education and Counseling, 74(3), 295–301. https://doi.org/10.1016/j.pec.2008.11.015
Copyright (c) 2026 Maham Arshad, Saira Khan, Suleman Ahmad, Amina Afzal, Muhammad Shoaib, Zohaib Hassan https://creativecommons.org/licenses/by-nc-sa/4.0
AI-Driven Media Evolution: Redefining Journalism and Communication in the Digital Age
Artificial Intelligence (AI) has changed the world of journalism and digital communication at an extremely fast pace. To improve the efficiency of newsrooms, audience engagement, and data-driven production of content, media organizations are increasingly employing AI-driven technologies. Nevertheless, the topic of AI integration into journalism also provokes ethical issues associated with misinformation, algorithmic bias, and professionalism. This research intends to investigate the degree of awareness and application of Artificial Intelligence in media organizations, assess its influence on journalism activities and the quality of communication, address ethical issues related to the implementation of AI, and discuss the perspectives of AI-based technologies in journalism and communication. A survey design was adopted to conduct a quantitative study on a structured questionnaire, which relies on a five-point Likert scale. The survey was conducted among 267 respondents comprising of journalists, media practitioners, academicians and students who participated in media and communication industries. The descriptive statistical methods such as frequency, percentage, mean and standard deviation were used to analyse the data. The results indicate that there is a high awareness and positive attitudes towards AI in journalism. The respondents also found that AI enhances the efficiency of the newsroom and helps with data analysis (M = 4.31) and helps a journalist find trending topics in a short period (M = 4.27). The AI was also seen to improve the speed of news delivery (M = 4.33) and increase the level of engagement with the audience in the digital media setting. Nevertheless, the respondents raised concerns about possible risks that include misinformation (M = 4.30), algorithm bias, and lack of human creativity. Moreover, the respondents placed a strong emphasis on clear regulations and policies governing of AI in journalism (M = 4.35). The paper concludes that AI has emerged as a necessity in contemporary journalism, and it has greatly enhanced efficiency, data analysis, and interaction with the audience. Meanwhile, there is also a need to implement those responsibly and with ethical standards and professional training to make sure that AI technologies are being used in the media industry in a balanced and effective way. References Afshar, M. Z., & Shah, M. H. (2025). Examining the role of change management in enhancing organizational resilience in public sector entities. Center for Management Science Research, 3(3), 931–942. https://cmsrjournal.com/index.php/Journal/article/view/199 Afshar, M. Z., & Shah, M. H. (2025). Leveraging Porter’s diamond model: Public sector insights. The Critical Review of Social Sciences Studies, 3(2), 2255–2271. Ahmad, N., Haque, S., & Ibahrine, M. (2023). The news ecosystem in the age of AI: Evidence from the UAE. Journal of Broadcasting & Electronic Media, 67(3), 323–352. https://doi.org/10.1080/08838151.2023.2235229 Ali, W., & Hassoun, M. (2019). Artificial intelligence and automated journalism: Contemporary challenges and new opportunities. International Journal of Media, Journalism and Mass Communications, 5(1), 40–49. https://doi.org/10.20431/2454-9479.0501004 Alim, I., Akter, S., Afroz, Z., Al Prince, A., & Hasan, M. A. (2025). Business intelligence in the age of AI: Evaluating machine learning’s impact on U.S. economic productivity. Lead Sci Journal of Management, Innovation and Social Sciences, 1(3), 15–30. Arshad, N., Baber, M. U., & Ullah, A. (2024). Assessing the transformative influence of ChatGPT on research practices among scholars in Pakistan. Mesopotamian Journal of Big Data, 2024, 1–10. https://doi.org/10.58496/MJBD/2024/001 Benson, C. E., Okolo, C. H., & Oke, O. (2025). Exploring the impact of AI on traditional journalism: Conceptualizing the future of news reporting and media integrity in an AI-driven world. International Journal of Advanced Multidisciplinary Research and Studies, 5(3), 2523–2529. Butt, I. N., & Shah, S. (2025). The convergence of artificial intelligence and 6G networks: A transformative shift in computing and communications. Journal of Engineering and Computational Intelligence Review, 3(1), 68–81. Gondwe, G. (2023). Exploring the multifaceted nature of generative AI in journalism studies: A typology of scholarly definitions. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4465446 Guzman, A. L., & Lewis, S. C. (2024). What generative AI means for the media industries, and why it matters to study the collective consequences for advertising, journalism, and public relations. Emerging Media, 2(3), 347–355. https://doi.org/10.1177/27523543231212182 Hafied, H., Irwanto, I., Surjatmodjo, D., & Latuheru, R. (2025). AI-driven media evolution: Exploring automated journalism’s impact on the industry’s future. Jurnal Kajian Jurnalisme, 8(2), 205–218. https://doi.org/10.24198/jkj.v8i2.52962 Hasan, M. A., Mazumder, M. T. R., Motari, M. C., Shourov, M. S. H., & Sarkar, M. (2026). AI and business intelligence integration for improved efficiency and reporting accuracy in small U.S. financial institutions. Journal of Fintech, Business, and Development, 3(1), 1–25. Jones, B., Jones, R., & Luger, E. (2022). AI ‘everywhere and nowhere’: Addressing the AI intelligibility problem in public service journalism. Digital Journalism, 10(10), 1731–1755. https://doi.org/10.1080/21670811.2022.2145328 Lewis, S. C., Guzman, A. L., Schmidt, T. R., & Lin, B. (2025). Generative AI and its disruptive challenge to journalism: An institutional analysis. Communication and Change, 1(1), Article 9. https://doi.org/10.1177/26314825241234567 Moran, R. E., & Shaikh, S. J. (2022). Robots in the news and newsrooms: Unpacking meta-journalistic discourse on the use of artificial intelligence in journalism. Digital Journalism, 10(10), 1756–1774. https://doi.org/10.1080/21670811.2021.1952098 Nasser El Erafy, A. (2023). Applications of artificial intelligence in the field of media. International Journal of Artificial Intelligence and Emerging Technology, 6(2), 19–41. Niazi, S. (2024). Big data analytics with machine learning: Challenges, innovations, and applications. Journal of Engineering and Computational Intelligence Review, 2(1), 38–48. Nwabueze, E. A., & Abiodun, G. (2025). The evolution of mass communication in the age of AI: Opportunities and challenges. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5219267 Paik, S. (2025). Journalism ethics for the algorithmic era. Digital Journalism, 13(4), 696–722. https://doi.org/10.1080/21670811.2024.2307785 Prakash, G., & Sabharwal, D. (2024). AI revolution in online media: Transforming content creation, distribution, and consumption. In Media and AI: Navigating the future (p. 179). Shi, Y., & Sun, L. (2024). How generative AI is transforming journalism: Development, application and ethics. Journalism and Media, 5(2), 582–594. https://doi.org/10.3390/journalmedia5020036 Simon, F. M. (2024). Escape me if you can: How AI reshapes news organisations’ dependency on platform companies. Digital Journalism, 12(2), 149–170. https://doi.org/10.1080/21670811.2022.2151209 Sundar, S. S., & Lee, E. J. (2022). Rethinking communication in the era of artificial intelligence. Human Communication Research, 48(3), 379–385. https://doi.org/10.1093/hcr/hqac009 Tong, J. (2018). Journalistic legitimacy revisited: Collapse or revival in the digital age? Digital Journalism, 6(2), 256–273. https://doi.org/10.1080/21670811.2017.1278475 Ullah, A., Islam, K., Ali, A., & Baber, M. (2024). Assessing the impact of social media addiction on reading patterns: A study of Riphah International University students. International Journal of Human and Society, 4(1), 1250–1262. Voinea, D. V. (2025). Reconceptualizing gatekeeping in the age of artificial intelligence: A theoretical exploration of artificial intelligence-driven news curation and automated journalism. Journalism and Media, 6(2), Article 68. https://doi.org/10.3390/journalmedia6020068 Wenger, D., Hossain, M. S., & Senseman, J. R. (2025). AI and the impact on journalism education. Journalism & Mass Communication Educator, 80(1), 97–114. https://doi.org/10.1177/10776958231234567
Copyright (c) 2026 Dr. Huma Tahir, Syed Imran Ali Shah, Hamza Zamir Kiani, Muhammad Zeeshan Zahid https://creativecommons.org/licenses/by-nc-sa/4.0
A Comprehensive Review of High-Impact Educational Research (2021–2025): Trends, Insights, and Emerging Practices
The literature review is a critical analysis of high-impact educational research published between 2021 and 2025, which identifies the most significant trends, evidence-based practices, and emerging innovations that influence the development of modern education. Pedagogical practices in the post-COVID period have changed to emphasize the effectiveness of student engagement, fair access, and the implementation of technology-based approaches to instruction. Personalized and adaptive learning with the help of digital transformation (artificial intelligence, interactive e-books, and immersive learning environments) has resulted in a measurable student performance and engagement improvement. Problem-Based Learning, Project-Based Learning, and formative assessment remain active learning approaches that support the development of critical thinking and problem-solving skills in a variety of educational settings. These advances notwithstanding, there are still issues such as gaps in teacher training, a lack of resources, and professional development. The new technologies hold the promise of innovation but pose threats to data privacy, algorithmic bias, and digital equity. These challenges cannot be met without systemic support, accountable AI implementation, and a commitment on the part of institutions to inclusive and student-centred learning. This review will summarize the existing literature and outline practical recommendations to be followed by policymakers, teachers, and scholars who want to maximize the learning process and overcome the changing digital environment. References Ajid, S. N., Kusumaningtyas, D., Ratih, K., & Lava, S. (2025). Strategies for Integrating Problem-Based Learning, Teaching Modules, and Formative Assessments to Enhance Learning Outcomes and Critical Thinking Skills. Indonesian Journal on Learning and Advanced Education (IJOLAE), 7(2), 340–357. https://doi.org/10.23917/ijolae.v7i2.8612 Albohamood, A. H., Alqattan, M. S., & Vizcarra, C. P. (2025). Real-time Student Engagement Monitoring in Classroom Environments using Machine Learning and Computer Vision. 2025 4th International Conference on Computing and Information Technology (ICCIT), 1–6. https://doi.org/10.1109/ICCIT63348.2025.10989406 Andayani, A., & Prabowo, S. (2025). HOTS-Based Interactive E-Books and Student Learning Outcomes: A Systematic Literature Review. International Journal of Education and Learning Studies, 1(3), 45–58. https://doi.org/10.64421/ijels.v1i3.23 Bashir, M., & Naseer, D. N. (2025). From Opportunity to Obstacle: Learners’ Experiences on the Use of Campus Management System. Inverge Journal of Social Sciences, 4(1), 148–161. https://doi.org/10.63544/ijss.v4i1.196 Bayani, F., Rokhmat, J., Hakim, A., & Sukarso, A. (2025). Research Trends in Analytical Thinking Skills for Science Education: Insights, Pedagogical Approaches, and Future Directions. International Journal of Ethnoscience and Technology in Education, 2(1), 52–68. https://doi.org/10.33394/ijete.v2i1.14142 Bensi, L. P., Bensi, M. E., Oliveros, A. G. G., & Torres, R. A. G. (2025). Student Preferences for Hybrid Versus Face-to-Face Learning Approaches: A Comparative Analysis of Engagement, Learning Outcomes, and Technological Challenges. International Journal of Research and Scientific Innovation, 12(3), 881–892. https://doi.org/10.51244/ijrsi.2025.12030074 Bizimana, E. (2025). Student Engagement in Learning: Exploring the Role of Perceived Student Cohesiveness, Equity, Teacher Support, and Teacher Autonomy Support Under the Framework of Self-Determination Theory. International Journal of Changes in Education. Advance online publication. https://doi.org/10.47852/bonviewijce52024500 Cena, J. F., Diez, M. B., Flores, M. R., Noquiao, H. P. P., & Quinco-Cadosales, M. N. (2025). Interactive Self-Learning Modules (ISLMs) in Sustaining Student Engagement and Learning Outcomes: A Meta-Synthesis. International Journal of Advanced Multidisciplinary Research and Studies, 5(4), 153-160. https://doi.org/10.62225/2583049x.2025.5.4.4782 Chow, W., Xu, B., Bhaumik, A., Peng, S., Guo, M., & Kurnia, S. (2025). Bridging Engagement and Learning Outcomes. Pacific Journal of Technology Enhanced Learning, 7(2), 29–30. https://doi.org/10.24135/pjtel.v7i2.224 Copland, S., Hills, M., & McKendrick-Calder, L. (2025). Structured Flexibility in Assessment: Students Perceptions of the Impact of Different Elements of Choice on Their Decision Making, Engagement, and Learning Experiences. Teaching and Learning Inquiry, 13, 1–18. https://doi.org/10.20343/teachlearninqu.13.61 Edmunds, T. K., & Little, R. (2025). Impacts of the Active Learning Classroom on Student Learning and Engagement: The Role of Technology. Canadian Journal for the Scholarship of Teaching and Learning, 16(1), Article 9. https://doi.org/10.5206/cjsotlrcacea.2025.1.16584 Firdaus, T., Mufidah, R., Hamida, R. N., Febrianti, R. I., & Guivara, A. E. R. (2025). Research trends and the impact of ChatGPT on educational environments. International Journal of Social Sciences and Education Research, 11(2), 112–128. https://doi.org/10.24289/ijsser.1609741 Fitratunisyah, F., Bactiar, I., & Jamaluddin, J. (2025). Research Trends of Problem Based Learning (PBL) Models to Improve Students' Critical Thinking Skills and Learning Outcomes (2016-2025): A Systematic Review. Current Educational Review, 1(4), 331–348. https://doi.org/10.56566/cer.v1i4.410 Hamdan, A., Elmunsyah, H., Maula, P. I., Sari, H. V., Abdullah, M. F., & Septianingsih, D. (2025). Systematic Evaluation of Adaptive Assessment in E-Learning: Contribution to Vocational Education. 2025 9th International Conference on Electrical, Electronics and Information Engineering (ICEEIE), 1–6. https://doi.org/10.1109/ICEEIE66203.2025.11254863 Huang, X., Gai, Y., Sun, L., Zhang, Y., Yang, D., Sheng, H., Huang, J.-M., & Li, Y. (2025). Research on Strategies for Enhancing Student Engagement and Retention in Engineering Education under a Technology-Enhanced Learning Environment. 2025 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 1–6. https://doi.org/10.1109/TALE66047.2025.11346628 Irvani, A. I., Dewi, A. P., Gunawan, A., & Rahmaniar, A. (2025). Gamification and Student Engagement: Evidence, Challenges, and Future Directions. Eduscape: Journal of Education Insight, 3(3), 175–189. https://doi.org/10.61978/eduscape.v3i3.937 Jainuri, M., Kamid, K., Syaiful, S., & Huda, N. (2025). Microlearning Effectiveness in Higher Education: A Systematic Review and Meta-Analysis of Student Retention and Learning Outcomes. MATHEMA: JURNAL PENDIDIKAN MATEMATIKA, 7(2), 476–492. https://doi.org/10.33365/jm.v7i2.517 K, N., Kumar, B. H., Sonar, R., Lamba, A. K., Valiveti, V. S. M., & Kalra, G. (2025). Enhancing Student Engagement and Learning Outcomes in Higher Education through E-Learning and Restricted Boltzmann Machines. 2025 3rd International Conference on Data Science and Information System (ICDSIS), 1–5. https://doi.org/10.1109/ICDSIS65355.2025.11071086 Khan, M. (2025). Mentimeter Tool for Enhancing Student Engagement and Active Learning: A Literature Review. International Journal of Changes in Education. Advance online publication. https://doi.org/10.47852/bonviewijce52023801 Kristiyuana, K., Wuriningsih, Fr., Idammatussilmi, I., & Agung, A. (2025). Reforming Pedagogy in Indonesian Primary Schools: A Five-Year Systematic Review of Differentiated Instruction, Project-Based Learning, and Formative Assessment (2020-2025). Jurnal Ilmiah Profesi Pendidikan, 10(2), 1556–1569. https://doi.org/10.29303/jipp.v10i2.3413 Laid, S. M. T., & Adlaon, M. S. (2025). A Systematic Review of Innovative Teaching Strategies in Science: Exploring Hands-on Learning, Technology Integration, and Student-Centered Approaches. Acta Pedagogia Asiana, 4(2), 91–105. https://doi.org/10.53623/apga.v4i2.645 Le, U. M., Kassem, T., & Tran, T. (2025). Enhancing pharmaceutical calculation proficiency: Exploring self-directed learning and self-reinforcement assessment strategies for student success. Currents in Pharmacy Teaching and Learning, 17(6), Article 102323. https://doi.org/10.1016/j.cptl.2025.102323 Li, F., Liu, J., Wu, J., & Wu, Z. (2025). Personalized Learning in Graduate Education: Learning Analytics and Assessment Methods from an IT Industry Perspective. 2025 7th International Conference on Computer Science and Technologies in Education (CSTE), 201–206. https://doi.org/10.1109/CSTE64638.2025.11091918 Martín-Rodríguez, A., & Madrigal-Cerezo, R. (2025). Technology-Enhanced Pedagogy in Physical Education: Bridging Engagement, Learning, and Lifelong Activity. Education Sciences, 15(4), Article 409. https://doi.org/10.3390/educsci15040409 Maurer, M., & Aleem, S. (2025). Comparative Performance Analysis of Machine Learning Techniques for Engagement Assessment in Education. 2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), 128–133. https://doi.org/10.1109/ACDSA65407.2025.11166367 Nassiri, S. H., & Bunyamin, M. A. H. (2025). TRENDS AND RESEARCH FRONTIERS IN PHYSICS EDUCATION: A BIBLIOMETRIC ANALYSIS FROM YEAR 2021-2025. International Journal of Modern Education, 7(27), 626–642. https://doi.org/10.35631/ijmoe.727039 Ningsih, A. G. (2025). Exploring the Impact of Adaptive Real-Time Quiz Platforms with Differentiated Learning Features on Student Engagement and Learning Outcomes: A Mixed-Methods Approach. International Journal of Information and Education Technology, 15(6), 1165–1175. https://doi.org/10.18178/ijiet.2025.15.6.2329 Ojetunde, S., & Ramnarain, U. (2025). Like objects or like subjects? Effects of student-robot interaction (SRI) and mathematical ability on students learning outcomes. Smart Learning Environments, 12(1), Article 11. https://doi.org/10.1186/s40561-024-00345-2 Punnoose, N. J., Mathew, M. d., & Baxi, V. (2025). Enhancing Student Engagement Through a Curated Digital Learning Library Platform. 2025 World Engineering Education Forum - Global Engineering Deans Council (WEEF-GEDC), 1–5. https://doi.org/10.1109/WEEF-GEDC66748.2025.11256211 Razilu, Z., Sulfasyah, S., & Nappu, S. (2025). Mapping Global Research Trends in Interactive Learning Media: A Bibliometric Analysis of Scopus Publications (2021-2025). PPSDP International Journal of Education, 4(2), 411–424. https://doi.org/10.59175/pijed.v4i2.743 Ricky, A. S., Umamah, F., Amalia, S. N., & Trisnawati, E. (2025). SYSTEMATIC LITERATUR REVIEW (2021-2025): PENGEMBANGAN E-BOOK INTERAKTIF DALAM PEMBELAJARAN IPA DI SEKOLAH DASAR. EDUTECH: Jurnal Inovasi Pendidikan Berbantuan Teknologi, 5(3), 464–474. https://doi.org/10.51878/edutech.v5i3.6887 Rohman, A. Z., Hasaini, H. F., Setiawan, R., & Rumagit, R. Y. (2025). Predictive Framework for Adaptive Learning: Integrating Clickstream Analytics and Assessment Outcomes in LMS. 2025 7th International Conference on Cybernetics and Intelligent System (ICORIS), 235–240. https://doi.org/10.1109/ICORIS67789.2025.11296012 Santhoshkumar, S., Kalaimani, T. M., Chandra, H., Prasad, Parthasarathy, R., & Charaan, R. M. D. (2025). Machine Learning System for Comprehensive Student Assessment and Academic Performance Optimization. 2025 International Conference on Smart & Sustainable Technology (INCSST), 1–5. https://doi.org/10.1109/INCSST64791.2025.11210374 Song, J. Y. (2025). A Systematic Literature Review of Teacher Professional Development Based on Responsible AI Principles: Analysis of Domestic and International Research Trends (2020-2025). The Korea Association of Lifelong Education & Convergence (KALEC), 4(2), 37–55. https://doi.org/10.58207/kalec.2025.4.2.37 Stepanyan, K., Hasegawa, K., & Poon, H. (2025). What do I, as a student, think of my own work? Using summative self-assessment in a large technical module. Journal of Learning Development in Higher Education, (35). https://doi.org/10.47408/jldhe.vi35.1374 Studi, P., Matematika, P., Undikma, F., Zuhaida, N., Pujiastuti, E., & Zaenuri. (2025). Trends in Students Mathematical Problem-Solving Skills: A Systematic Review and Bibliometric Analysis of GeoGebra-Assisted Problem-Based Learning Research (2021-2025). Media Pendidikan Matematika, 13(2), 165–181. https://doi.org/10.33394/mpm.v13i2.18489 Suhaimi, S., Ghani, M. F. A., & Radzi, N. M. (2025). Does Student-centred Leadership Integrate with Collaborative, Distributive, and Instructional Leadership? A Recent Systematic Review (2021-2025). International Research-Based Education Journal, 7(2), 238–272. https://doi.org/10.17977/um043v7i22025p238-272 Syamsudin, F. I., Wiyono, K., Patriot, E. A., Ismet, I., Saparini, S., & Kamari, A. (2025). Trends in Technology Literacy Research (2021 to 2025): A Bibliometric Analysis with VOSviewer. Jurnal Materi Dan Pembelajaran Fisika, 15(2), 156–166. https://doi.org/10.20961/jmpf.v15i2.109121 Umri, N. A., Karnyoto, A., & Pardamean, B. (2025). The Impact of AI-Generated Hallucinations in Educational Settings: Trends, Gaps, and Future Directions. 2025 9th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE), 557–562. https://doi.org/10.1109/ICITISEE68184.2025.11355145 Utami, A., Rusmana, A. N., & Rahayu, D. (2025). CAPTURING CURRENT RESEARCH TRENDS ON THE UTILIZATION OF CHATGPT IN SCIENCE EDUCATION. Jurnal Pendidikan Matematika Dan IPA, 16(3), 564–581. https://doi.org/10.26418/jpmipa.v16i3.93046 Wali, M., Redhana, I. W., & Tika, I. N. (2025). TRENDS IN EDUCATIONAL GAMES TO IMPROVE STUDENTS' LEARNING MOTIVATION IN SCIENCE LEARNING: A SYSTEMATIC LITERATURE REVIEW. Jurnal Penelitian Pendidikan IPA, 11(11), 39–50. https://doi.org/10.29303/jppipa.v11i11.12121 Weng, Y., & Zhang, Y. (2025). Assessment of Personalized Learning in Immersive and Intelligent Virtual Classroom on Student Engagement. arXiv.org. https://doi.org/10.48550/arXiv.2501.07883 Xiao, F. (2025). Intelligent Deep Learning Framework for University Physical Education Teaching Quality Assessment. 2025 2nd International Conference on Software, Systems and Information Technology (SSITCON), 1–5. https://doi.org/10.1109/SSITCON66133.2025.11342279 Yunus, M., & Bachtiar, B. (2025). Beyond Access: Reframing Engagement, Assessment, and Feedback in Open and Distance Learning at Universitas Terbuka. International Journal of Learning, Teaching and Educational Research, 24(6), 492–511. https://doi.org/10.26803/ijlter.24.6.26 Zhang, N. (2025). Enhanced English Classroom Teaching Quality Assessment Using Hybrid Deep Learning Architecture. 2025 Third International Conference on Networks, Multimedia and Information Technology (NMITCON), 1–6. https://doi.org/10.1109/NMITCON65824.2025.11187842
Copyright (c) 2026 Dr. Muhammad Rafiq-uz-Zaman, Yi-Huang Shih https://creativecommons.org/licenses/by-nc-sa/4.0
Green Finance Intelligence and Sustainable Capital Allocation: Artificial Intelligence Driven ESG Signal Processing and Capital Market Efficiency
The rapid expansion of sustainable investment markets has intensified the need for accurate Environmental, Social, and Governance (ESG) data analysis to support effective capital allocation. However, traditional analytical approaches often struggle to interpret the growing volume of heterogeneous sustainability information, leading to information asymmetry and suboptimal investment outcomes. This study examined the role of artificial intelligence-driven ESG signal processing in enhancing green finance intelligence and improving sustainable capital allocation and capital market efficiency. A quantitative research design was employed, utilizing primary data collected from 312 financial professionals working in banking, asset management, and financial technology sectors. Descriptive statistical analysis revealed strong agreement regarding the importance of AI adoption in sustainable finance, with artificial intelligence adoption recording the highest mean value (M = 4.14, SD = 0.69), followed by green finance intelligence (M = 4.09, SD = 0.68) and ESG signal processing capability (M = 4.07, SD = 0.72). Regression analysis demonstrated that artificial intelligence adoption significantly influenced green finance intelligence (β = 0.41, t = 7.86, p < 0.001), while ESG signal processing capability significantly improved sustainable capital allocation (β = 0.38, t = 6.94, p < 0.001). Additionally, green finance intelligence positively affected capital market efficiency (β = 0.35, t = 6.21, p < 0.001). The findings indicated that artificial intelligence significantly enhances ESG information processing, reduces information asymmetry, and supports data-driven sustainable investment strategies. The study concluded that AI-driven ESG analytics play a crucial role in strengthening sustainable finance ecosystems and improving the efficiency of capital allocation within modern financial markets. References Akash, V., & Kumari, R. (2025). The role of artificial intelligence in promoting sustainable and responsible investments. Journal of Social Review and Development, 4(S1), 182–186. https://doi.org/10.64171/JSRD.4.S1.182-186 Aruwaji, M. A., & Swanepoel, M. J. (2025). The impact of AI-integrated ESG reporting on firm valuation in emerging markets. Journal of Risk and Financial Management, 18(12), 675. https://doi.org/10.3390/jrfm18120675 Bae, K. H., El Ghoul, S., Gong, Z., & Guedhami, O. (2024). ESG performance and investment efficiency: The impact of information asymmetry. Journal of International Financial Markets, Institutions and Money, 91, 101919. https://doi.org/10.1016/j.intfin.2023.101919 Baker, M., Bergstresser, D., Serafeim, G., & Wurgler, J. (2021). Financing the response to climate change: The pricing and ownership of U.S. green bonds. Journal of Financial Economics, 142(2), 499–516. https://doi.org/10.1016/j.jfineco.2021.02.012 Berg, F., Koelbel, J. F., & Rigobon, R. (2022). Aggregate confusion: The divergence of ESG ratings. Review of Finance, 26(6), 1315–1344. https://doi.org/10.1093/rof/rfac033 Bolton, P., & Kacperczyk, M. (2021). Do investors care about carbon risk? Journal of Financial Economics, 142(2), 517–549. https://doi.org/10.1016/j.jfineco.2021.05.008 Davidescu, A. A., Apostu, S., & Strat, V. A. (2025). Artificial intelligence in ESG and sustainable finance: A bibliometric analysis of research trends. Proceedings of the International Conference on Business Excellence, 19(1), 1506–1517. https://doi.org/10.2478/picbe-2025-0117 Elhady, A. M., & Shohieb, S. (2025). AI-driven sustainable finance: Computational tools, ESG metrics, and global implementation. Future Business Journal, 11, 209. https://doi.org/10.1186/s43093-025-00610-x Flammer, C. (2021). Corporate green bonds. Journal of Financial Economics, 142(2), 499–516. https://doi.org/10.1016/j.jfineco.2021.01.010 Friede, G., Busch, T., & Bassen, A. (2021). ESG and financial performance: Aggregated evidence from more than 2000 empirical studies. Journal of Sustainable Finance & Investment, 11(4), 210–233. https://doi.org/10.1080/20430795.2020.1718917 Gillan, S. L., Koch, A., & Starks, L. T. (2021). Firms and social responsibility: A review of ESG and CSR research in corporate finance. Journal of Corporate Finance, 66, 101889. https://doi.org/10.1016/j.jcorpfin.2021.101889 Giudici, P., & Wu, L. (2025). Sustainable artificial intelligence in finance: Impact of ESG factors. Frontiers in Artificial Intelligence, 8, Article 1566197. https://doi.org/10.3389/frai.2025.1566197 Goldstein, I., Jiang, W., & Karolyi, G. A. (2021). To FinTech and beyond. Review of Financial Studies, 34(7), 2967–3008. https://doi.org/10.1093/rfs/hhab020 Huang, Y., Li, X., & Zhang, H. (2025). Artificial intelligence, information environment, and capital market efficiency. Research in International Business and Finance, 79, 103094. https://doi.org/10.1016/j.ribaf.2025.103094 Hussain, M. A., Vemaraju, S., & Garg, A. (2025). The impact of AI tools on ESG-based sustainable banking practices. International Journal of Computational and Experimental Science and Engineering, 11(3). https://doi.org/10.22399/ijcesen.3198 Jellouli, I. (2025). Rethinking portfolio design with sustainable AI and FinTech: Dynamic spillovers in a quantile–frequency framework. Cogent Economics & Finance, 13(1), Article 2568640. https://doi.org/10.1080/23322039.2025.2568640 Kotsantonis, S., & Serafeim, G. (2019). Four things no one will tell you about ESG data. Journal of Applied Corporate Finance, 31(2), 50–58. https://doi.org/10.1111/jacf.12346 Krueger, P., Sautner, Z., & Starks, L. T. (2020). The importance of climate risks for institutional investors. Review of Financial Studies, 33(3), 1067–1111. https://doi.org/10.1093/rfs/hhz137 Kumar, N., Lohano, R. K., Asghar, M. M., Khalid, M., & Awan, D. (2025). Artificial intelligence and green finance: Unveiling the link to financial performance in Pakistan. Asian Bulletin of Green Management and Circular Economy, 5(1), 173–189. https://doi.org/10.62019/abgmce.v5i1.142 Liang, H., & Renneboog, L. (2020). Corporate social responsibility and sustainable finance. Journal of Corporate Finance, 62, 101597. https://doi.org/10.1016/j.jcorpfin.2020.101597 Liu, J., Yuan, Y., & Zhu, Z. (2026). The role of artificial intelligence in enhancing ESG disclosure quality in accounting. Journal of Risk and Financial Management, 19(1), 58. https://doi.org/10.3390/jrfm19010058 Mansour, M., Al Zobi, M., & Alomair, M. (2026). Artificial intelligence, ESG governance, and green innovation efficiency in emerging economies. Economies, 14(1), 11. https://doi.org/10.3390/economies14010011 Rafiq-uz-Zaman, M. (2025a). Bridging the skills divide: A comparative study of skill-based education across SAARC countries with a policy roadmap for Pakistan. Social Science Review Archives, 3(3), 787–795. https://doi.org/10.70670/sra.v3i3.913 Rafiq-uz-Zaman, M. (2025b). Use of artificial intelligence in school management: A contemporary need of school education system in Punjab (Pakistan). Journal of Asian Development Studies, 14(2), 1984–2009. https://doi.org/10.62345/jads.2025.14.2.56 Rafiq-uz-Zaman, M. (2025c). Beyond the blackboards: Building a micro-edtech economy through teacher-led innovation in low-income schools. Journal of Business Insight and Innovation, 4(1), 46–52. https://doi.org/10.5281/zenodo.16875721 Rafiq-uz-Zaman, M., & Nadeem, M. A. (2025). Gauging the gap: Student perceptions of skill proficiency in skill-based education within schools of Punjab, Pakistan. ACADEMIA International Journal for Social Sciences, 4(2), 2307–2317. https://doi.org/10.63056/ACAD.004.03.0553 Saltık, Ö. (2024). Algorithmic approaches to unraveling ESG impact on financial performance. International Journal of Pure and Applied Sciences, 10(2), 459–517. https://doi.org/10.29132/ijpas.1540178 Schwendner, P., & Posth, J. A. (2024). Trends in AI4ESG: AI for sustainable finance and ESG technology. Frontiers in Artificial Intelligence, 7, 1448045. https://doi.org/10.3389/frai.2024.1448045 Zhang, D., Mohsin, M., Rasheed, A. K., & Chang, Y. (2025). Green finance and artificial intelligence: Catalysts for promoting sustainability. Economic Analysis and Policy, 88, 13–25. https://doi.org/10.1016/j.eap.2025.08.037 Zhang, L., Wang, H., & Zhao, Y. (2025). Artificial intelligence and corporate investment efficiency: Evidence from China. Emerging Markets Review, 68, 101314. https://doi.org/10.1016/j.ememar.2025.101314 Zhang, X., Li, Y., & Chen, H. (2026). The impact of artificial intelligence on corporate ESG greenwashing. Socio-Economic Planning Sciences, 103, 102351. https://doi.org/10.1016/j.seps.2025.102351
Copyright (c) 2026 Dr. Syed Shameel Ahmed Quadri, Dr. Mehreen Ansari, Zonaira Akbar, Fahim Ullah Khan https://creativecommons.org/licenses/by-nc-sa/4.0
Public Trust in State Institutions: A Comparative Analysis of the Military, Judiciary, and Parliament in Post-2023 Election Pakistan
The foundation of democratic stability, institutional legitimacy, and effectiveness of the governance is public trust. In transitional democracies like Pakistan trust on the state institutions is often defined by political turbulence, judicial activism, civil-military relations as well as electoral contestation. The 2023 general elections became the most significant turning point in the history of political direction in Pakistan, which fueled the discussion of the stylistic legitimacy of the institution and trust between citizens. The paper explores the relative trust of the Pakistani population in three major pillars of the Pakistani state the military, judiciary and parliament and determines the socio-political conditions that impact the legitimacy of institutions in the post-election context. The study is based on a cross-sectional quantitative design through the analysis of the survey data of 714 respondents using stratified random sampling of the major urban districts. There was the use of statistical methods such as descriptive analysis, correlation matrices, one-way ANOVA, and multiple regression model to examine predictors of institutional trust. The results indicate that there is a strong trust asymmetry with the military receiving the greatest trust rating followed by the judiciary and the parliament correspondingly having lower trust ratings. The outcome of regression indicates that the perceived institutional performance, political polarization, media exposure, and corruption perception are relevant predictors of trust changes. Notably, the paper determines civic efficacy and democratic commitment as moderator factors that can alleviate distrust of representative institutions. The theoretical contribution to research is the synthesis of the Institutional Trust Theory and the Performance Legitimacy Frameworks, which shows that citizens are becoming more perceptive in the outcomes-based criterion instead of constitutional mandates alone when assessing institutional performance. This research finds that to restore confidence in the representative institutions, it would be necessary to introduce visible governance changes, transparency in its procedures and enhancement of accountability measures. Unless institutional balance is restored, chronic lack of trust can increase the weaknesses of democracy and entrench non-representative power. References Ahmed, S., & Asif, M. (2026a). Public opinion on the effectiveness of local government anti-corruption measures: A multi-city survey analysis. International Journal of Social Sciences Bulletin, 4(1), 1189–1201. https://doi.org/10.5281/zenodo.18412790 Ahmed, S., & Asif, M. (2026b). Comparative analysis of attitudes toward climate change policies across urban and rural populations. Pakistan Journal of Social Science Review, 5(1), 747–769. https://doi.org/10.5281/zenodo.18457821 Asif, M., & Asghar, R. J. (2025). Managerial accounting as a driver of financial performance and sustainability in small and medium enterprises in Pakistan. Center for Management Science Research, 3(7), 150–163. https://doi.org/10.5281/zenodo.17596478 Asif, M., Khan, A., & Pasha, M. A. (2019). Psychological capital of employees’ engagement: Moderating impact of conflict management in the financial sector of Pakistan. Global Social Sciences Review, 4(3), 160–172. https://doi.org/10.31703/gssr.2019(IV-III).15 Aurangzeb, Asif, M., & Amin, M. K. (2021). Resources management and SMEs’ performance. Humanities & Social Sciences Reviews, 9(3), 679–689. https://doi.org/10.18510/hssr.2021.9367 Bartolome, M. T., Fernandez, K., Cutipa-Luque, O., Tiahuallpa, Y., & Rojas, H. (2024). Dynamic interconnections between corruption and economic growth. arXiv. https://arxiv.org Easton, D. (1965). A framework for political analysis. Prentice-Hall. Easton, D. (1965). A systems analysis of political life. Prentice-Hall. Easton, D. (1965). Distinction between specific and diffuse support in political systems. Easton, D. (1965). Expansion of political system theory in modern political science. Easton, D. (1965). Political systems as open systems influenced by environments. Huntington, S. P. (1957). Military institutions and civil–military balance. Huntington, S. P. (1957). The soldier and the state: The theory and politics of civil–military relations. Harvard University Press. Jennings, W. (2017). The decline in diffuse support for national politics. Political Research Quarterly. Khosrowjerdi, M. (2022). Good governance and national information transparency: A comparative study of 117 countries. arXiv. https://arxiv.org La Rocca, M., La Rocca, T., Fasano, F., & Sanchez-Vidal, J. (2023). From the top down: Does corruption affect performance? arXiv. https://arxiv.org Levi, M., & Stoker, L. (2000). Political trust and trustworthiness. Annual Review of Political Science, 3, 475–507. https://doi.org/10.1146/annurev.polisci.3.1.475 Levi, M., & Stoker, L. (2000). Political trust and trustworthiness. Annual Review of Political Science. Levi, M., & Stoker, L. (2000). Political trust, participation, and citizen compliance. Shao, J., Ivanov, P. C., Podobnik, B., & Stanley, H. E. (2007). Quantitative relations between corruption and economic factors. arXiv. https://arxiv.org Transparency International. (2003). Accountability and transparency in political finance: Why, how and what for? Transparency International. Transparency International. (2012–2020). Corruption perceptions index methodology. Transparency International. Transparency International. (2023). Corruption perceptions index. https://www.transparency.org Transparency International. (2024). Corruption perceptions index 2024. Transparency International. Transparency International. (2025). Corruption perceptions index. https://www.transparency.org
Copyright (c) 2026 Madiha Bashir, Sami Ullah https://creativecommons.org/licenses/by-nc-sa/4.0
The Role of Maternal-Fetal Attachment and Psychological Well-being in Infant Neurodevelopment
This study examines the relationship between maternal psychological distress during the perinatal period, maternal-fetal attachment, and subsequent neurodevelopmental outcomes in infants. The historical reverence for motherhood in Azerbaijan faces contemporary challenges as limited awareness leaves expectant mothers vulnerable to psychological hardships during the perinatal period. The intrauterine environment is influenced not only by maternal nutrition but also by maternal emotional states, with implications for fetal neurodevelopment. A cross-sectional correlational study was conducted with 276 mothers of children diagnosed with various neurodevelopmental conditions, including Cerebral Palsy, Autism Spectrum Disorder, Down Syndrome, and Developmental Delay. Participants completed retrospective assessments of prenatal psychological distress, maternal-fetal attachment behaviours, and provided demographic and clinical information. Results of the 276 participants, 140 (50.7%) reported significant psychological distress during gestation. A statistically significant association was identified between prenatal distress and child's diagnostic category (χ² = 14.27, df = 5, p = .014). Mothers of children with Autism Spectrum Disorder reported the highest rates of prenatal distress (68.4%). Significant inverse relationships were observed between prenatal distress and maternal-fetal attachment behaviours, including emotional closeness to the fetus (r = -.42, p < .001). Findings demonstrate a significant correlation between maternal psychological distress during pregnancy and subsequent neurodevelopmental challenges in offspring. The results underscore the need for perinatal mental health screening and culturally appropriate intervention programs in Azerbaijan. References Ainsworth, M. D. S., Blehar, M. C., Waters, E., & Wall, S. (1978). Patterns of attachment: A psychological study of the strange situation. Lawrence Erlbaum. Asif, M. (2021). Contingent effect of conflict management towards psychological capital and employees' engagement in financial sector of Islamabad (Doctoral dissertation, Preston University). https://doi.org/10.13140/RG.2.2.17616.79360 Asif, M. (2022). Integration of information technology in financial services and its adoption by the financial sector in Pakistan. Inverge Journal of Social Sciences, 1(2), 23–35. https://doi.org/10.63544/ijss.v1i2.31 Asif, M. (2024). The complexities of bioterrorism: Challenges and considerations. International Journal of Contemporary Issues in Social Sciences, 3(3), 2175–2184. Asif, M., Ali, A., & Shaheen, F. A. (2025). Assessing the effects of artificial intelligence in revolutionizing human resource management: A systematic review. Social Science Review Archives, 3(4), 2887–2908. https://doi.org/10.70670/sra.v3i3.1055 Asif, M., & Asghar, R. J. (2025). Managerial accounting as a driver of financial performance and sustainability in small and medium enterprises in Pakistan. Center for Management Science Research, 3(7), 150–163. https://doi.org/10.5281/zenodo.17596478 Asif, M., Imran, A., Joseph, V., Haqdad, U., Samraameer, & Asif, M. (2022). Mediating role of trust between emotional intelligence and project team performance in telecommunication sector. PalArch's Journal of Archaeology of Egypt/Egyptology, 19(4), 988–1005. Asif, M., Khan, A., & Pasha, M. A. (2019). Psychological capital of employees' engagement: Moderating impact of conflict management in the financial sector of Pakistan. Global Social Sciences Review, 4(3), 160–172. https://doi.org/10.31703/gssr.2019(IV-III).15 Asif, M., Pasha, M. A., Mumtaz, A., & Sabir, B. (2023). Causes of youth unemployment in Pakistan. Inverge Journal of Social Sciences, 2(1), 41–50. https://doi.org/10.63544/ijss.v2i1.21 Asif, M., Pasha, M. A., Shafiq, S., & Craine, I. (2022). Economic impacts of post COVID-19. Inverge Journal of Social Sciences, 1(1), 56–65. https://doi.org/10.63544/ijss.v1i1.6 Asif, M., Pasha, M. A., & Shahid, A. (2025). Energy scarcity and economic stagnation in Pakistan. Bahria University Journal of Management & Technology, 8(1), 141–157. Asif, M., & Sandhu, M. S. (2023). Social media marketing revolution in Pakistan: A study of its adoption and impact on business performance. Journal of Business Insight and Innovation, 2(2), 67–77. https://doi.org/10.52783/eel.v13i5.901 Asif, M., Shah, H., & Asim, H. A. H. (2025). Cybersecurity and audit resilience in digital finance: Global insights and the Pakistani context. Journal of Asian Development Studies, 14(3), 560–573. https://doi.org/10.62345/jads.2025.14.3.47 Asif, M., & Shaheen, A. (2022). Creating a high-performance workplace by the determination of importance of job satisfaction, employee engagement, and leadership. Journal of Business Insight and Innovation, 1(2), 9–15. Asif, M., Shahid, S., & Rafiq-uz-Zaman, M. (2025). Immersive technologies, awe, and the evolution of retail in the metaverse. International Premier Journal of Languages & Literature, 3(4), 713–748. https://doi.org/10.5281/zenodo.18136481 Aslam, M., & Asif, M. (2025). Organizational power structures and the reproduction of gender inequality. Apex Journal of Social Sciences, 4(1), 57–67. Aurangzeb, & Asif, M. (2021). Resources management and SMEs' performance. Humanities & Social Sciences Reviews, 9(3), 679–689. https://doi.org/10.18510/hssr.2021.9367 Aurangzeb, D., & Asif, M. (2021). Role of leadership in digital transformation: A case of Pakistani SMEs. In Proceedings of the Fourth International Conference on Emerging Trends in Engineering. Aurangzeb, Mushtaque, T., Tunio, M. N., Zia-ur-Rehman, & Asif, M. (2021). Influence of administrative expertise of human resource practitioners on job performance: Mediating role of achievement motivation. International Journal of Management, 12(4), 408–421. https://doi.org/10.34218/IJM.12.4.2021.035 Barker, D. J. P. (1998). Mothers, babies and health in later life (2nd ed.). Churchill Livingstone. Bowlby, J. (1969). Attachment and loss: Vol. 1. Attachment. Basic Books. Buss, C., Davis, E. P., Shahbaba, B., Pruessner, J. C., Head, K., & Sandman, C. A. (2012). Maternal cortisol over the course of pregnancy and subsequent child amygdala and hippocampus volumes and affective problems. Proceedings of the National Academy of Sciences, 109(20), E1312–E1319. https://doi.org/10.1073/pnas.1201295109 Copelon, R., Zampas, C., Brusie, E., & Devore, J. (2005). Human rights begin at birth: International law and the claim of fetal rights. Reproductive Health Matters, 13(26), 120–129. https://doi.org/10.1016/S0968-8080(05)26218-3 Coussons-Read, M. E. (2013). Effects of prenatal stress on pregnancy and human development: Mechanisms and pathways. Obstetric Medicine, 6(2), 52–57. https://doi.org/10.1177/1753495X12473751 Cranley, M. S. (1981). Development of a tool for the measurement of maternal attachment during pregnancy. Nursing Research, 30(5), 281–284. https://doi.org/10.1097/00006199-198109000-00008 Glover, V., O'Donnell, K. J., O'Connor, T. G., & Fisher, J. (2018). Prenatal maternal stress, fetal programming, and mechanisms underlying later psychopathology: A global perspective. Development and Psychopathology, 30(3), 843–854. https://doi.org/10.1017/S095457941800038X Honda, G. (2020, December 6). The process of integration. Psychology Today. https://www.psychologytoday.com/us/blog/pain-loss-and-suffering/202012/the-process-integration IBM Corp. (2021). IBM SPSS Statistics for Windows (Version 28.0) [Computer software]. IBM Corp. Khamidullina, Z., Marat, A., Muratbekova, S., Mustapayeva, N. M., Chingayeva, G. N., Shepetov, A. M., Ibatova, S. S., Terzic, M., & Aimagambetova, G. (2025). Postpartum depression epidemiology, risk factors, diagnosis, and management: An appraisal of the current knowledge and future perspectives. Journal of Clinical Medicine, 14(7), 2418. https://doi.org/10.3390/jcm14072418 Mumtaz, A., Munir, N., Mumtaz, R., Farooq, M., & Asif, M. (2023). Impact of psychological and economic factors on investment decision-making in Pakistan stock exchange. Journal of Positive School Psychology, 7(4), 130–135. Pasha, M. A., Ramzan, M., & Asif, M. (2019). Impact of economic value added dynamics on stock prices: Fact or fallacy? Global Social Sciences Review, 4(3), 135–147. https://doi.org/10.31703/gssr.2019(IV-III).13 Persico, G., Antolini, L., Vergani, P., Costantini, W., Nardi, M. T., & Bellotti, L. (2017). Maternal singing of lullabies during pregnancy and after birth: Effects on mother-infant bonding and newborns' behavior. Women and Birth, 30(4), e214–e220. https://doi.org/10.1016/j.wombi.2017.01.007 Shahid, N., Asif, M., & Pasha, A. (2022). Effect of internet addiction on school-going children. Inverge Journal of Social Sciences, 1(1), 12–47. https://doi.org/10.63544/ijss.v1i1.3 Stanford University. (n.d.). New publication shows link between losing a relative during pregnancy and mental health of child. Stanford Health Policy. Retrieved March 17, 2026, from https://healthpolicy.fsi.stanford.edu/news/new-publication-shows-link-between-losing-relative-during-pregnancy-and-mental-health-child UN Women. (2023, May 15). Gender equality starts at home: Five ways to drive change within the family. https://www.unwomen.org/en/news-stories/feature-story/2023/05/gender-equality-starts-at-home-five-ways-to-drive-change-within-the-family University of Edinburgh. (2022, February 23). Stress in pregnancy linked to changes in infant's brain development. https://cardiovascular-science.ed.ac.uk/news-events/news/stress-pregnancy-baby-brain-development Usama, H. A., Riaz, M., Khan, A., Begum, N., Asif, M., & Hamza, M. (2022). Prohibition of alcohol in Quran and Bible: A research and analytical review. PalArch's Journal of Archaeology of Egypt/Egyptology, 19(4), 1202–1211.
Copyright (c) 2026 Sayali Khanim Hajisoy Vidadi https://creativecommons.org/licenses/by-nc-sa/4.0
The Impact of Intellectual Capital on Employees' Job Performance: Mediating Mechanism of Organizational Commitment, Attitude and Job Satisfaction
This study aims to examine the influence of intellectual capital on job performance within the education sector in Lahore, Pakistan, with a specific focus on the mediating roles of organizational commitment, attitude, and job satisfaction. While extensive research has explored the direct relationship between intellectual capital and organizational performance in corporate and industrial settings, limited attention has been given to the mediating mechanisms that explain this relationship within the education sector, particularly in developing countries such as Pakistan. Prior studies have often overlooked the simultaneous mediating effects of job satisfaction, organizational commitment, and attitude in the intellectual capital–job performance nexus. This study addresses this gap by offering a comprehensive framework that examines these underexplored mediating pathways within the context of higher education institutions in Lahore. A quantitative research design was employed using a cross-sectional approach. Data were collected through a structured questionnaire comprising 29 items from 420 academic staff members across various business institutes in Lahore. A purposive sampling technique was adopted to select the respondents. The collected data were analysed using ADANCO software to test the proposed hypotheses. The results indicate that out of ten hypotheses, nine were supported, demonstrating significant relationships, while one hypothesis yielded insignificant results. Specifically, intellectual capital was found to have a positive impact on job satisfaction, organizational commitment, and attitude. Furthermore, the relationship between intellectual capital and job performance was significantly mediated by job satisfaction, attitude, and organizational commitment. This study offers valuable insights for the education sector by enhancing the understanding of the key components of intellectual capital and their effective implementation in improving job performance. The findings serve as a useful resource for researchers and policymakers seeking to comprehend the interconnections among intellectual capital, job satisfaction, organizational commitment, attitude, and job performance to achieve successful outcomes in their respective domains. References Ahmad, S. (2011). The relationship between intellectual capital and business performance: An empirical study in Iraqi industry. In Proceedings of the International Conference on Management and Artificial Intelligence (Vol. 6, pp. 104–109). Ahmed, Q. U. A., Butt, S., & Abdullah, F. (2024). Organizational sustainability: A big data framework using knowledge sharing and innovative work behavior. Qlantic Journal of Social Sciences, 5(2), 379–390. https://doi.org/10.55737/qjss.535149464 Akhtar, Q., & Butt, S. (2022). Sequential mediation between night shift and job performance in the context of Pakistan. International Journal of Management Research and Emerging Science, 12(4). Akhtar, Q., Butt, S., & Niaz, M. (2024). Time series analysis of poverty reduction indicators: Case of Pakistan, India, and Bangladesh. Qlantic Journal of Social Sciences and Humanities, 5(2), 170–183. Al-Khoury, A., Hussein, S. A., Abdulwhab, M., Aljuboori, Z. M., Haddad, H., Ali, M. A., & Flayyih, H. H. (2022). Intellectual capital history and trends: A bibliometric analysis using Scopus database. Sustainability, 14(18), Article 11615. https://doi.org/10.3390/su141811615 Ali, M. A., Hussin, N., Haddad, H., Al-Araj, R., & Abed, I. A. (2021). Intellectual capital and innovation performance: Systematic literature review. Risks, 9(9), 170. https://doi.org/10.3390/risks9090170 Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108 Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. University of Chicago Press. Blau, P. M. (1964). Exchange and power in social life. John Wiley & Sons. Bode, P. B. H. (1924). Democracy and education. NASSP Bulletin, 8(1), 120–126. https://doi.org/10.1177/019263652400800120 Bontis, N. (1998). Intellectual capital: An exploratory study that develops measures and models. Management Decision, 36(2), 63–76. https://doi.org/10.1108/00251749810204142 Brooking, A. (2010). On the importance of managing intangible assets as part of corporate strategy. In Proceedings of the European Conference (Vol. 8, Issue 2, pp. 217–224). Butt, S., Mubeen, I., & Yazdani, N. (2024a). Exploring the lived experiences of individuals to manage and cope with type 2 diabetes applying IPA. Pakistan Languages and Humanities Review, 8(2), 526–539. Butt, S., Umair, T., & Tajammal, R. (2024b). Nexus between key determinants of service quality and students’ satisfaction in higher education institutions (HEIs). Annals of Human and Social Sciences, 5(2), 659–671. Butt, S., & Yazdani, N. (2023). Implementation of quality management practices and firm’s innovation performance: Mediation of knowledge creation processes and moderating role of digital transformation. Pakistan Journal of Humanities and Social Sciences, 11(4), 3881–3902. Cabrera, W., & Estacio, D. (2022). Job attitude as a factor on employees performance. International Journal of Economics Development Research, 3(1), 13–35. https://doi.org/10.37385/ijedr.v3i1.254 Caglar, A. E., Gökçe, N., & Şahin, F. (2024). Sustaining environment through municipal solid waste: Evidence from European Union economies. Environmental Science and Pollution Research, 31(4), 6040–6053. https://doi.org/10.1007/s11356-023-31494-5 Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Lawrence Erlbaum. Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155 Collis, D. J. (1994). How valuable are organizational capabilities? Strategic Management Journal, 15(S1), 143–152. https://doi.org/10.1002/smj.4250150910 Córcoles, Y. R., Peñalver, J. F. S., & Ponce, Á. T. (2011). Intellectual capital in Spanish public universities: Stakeholders’ information needs. Journal of Intellectual Capital, 12(3), 356–376. https://doi.org/10.1108/14691931111154689 Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications. Dhull, D. K., & Jain, D. M. (2017). A study of attitude towards teaching profession in relation to job satisfaction among secondary school teachers. International Education & Research Journal, 3(1), 2016–2018. Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: The tailored design method (4th ed.). John Wiley & Sons. Edvinsson, L., & Malone, M. (1997). Intellectual capital: Realizing your company's true value by finding its hidden brainpower. Harper Business. Eisenberger, R., & Stinglhamber, F. (2011). Perceived organizational support: Fostering enthusiastic and productive employees. American Psychological Association. https://doi.org/10.1037/12318-000 Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11 Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley. Fisher, D., & Cresswell, J. (1998). Actual and ideal principal interpersonal behaviour. Learning Environments Research, 1(1), 231–247. https://doi.org/10.1023/A:1009931722533 Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312 Gralewski, J., & Karwowski, M. (2018). Are teachers’ implicit theories of creativity related to the recognition of their students’ creativity? Journal of Creative Behavior, 52(2), 156–167. https://doi.org/10.1002/jocb.140 Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Performance, 16(2), 250–279. https://doi.org/10.1016/0030-5073(76)90016-7 Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE Publications. Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2–20. https://doi.org/10.1108/IMDS-09-2015-0382 Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations (2nd ed.). SAGE Publications. Jankingthong, K., & Rurkkhum, S. (2012). Factors affecting job performance: A review of literature. Silpakorn University Journal of Social Sciences, Humanities, and Arts, 12(2), 115–127. Jen Huang, C., & Ju Liu, C. (2005). Exploration for the relationship between innovation, IT, and performance. Journal of Intellectual Capital, 6(2), 237–252. https://doi.org/10.1108/14691930510592825 Jhariko, M. (2025). The role of intellectual capital on firm performance: A case of telecom sector of Pakistan. Social Science Review, 3(3), 388–397. Johari, J., & Yahya, K. K. (2012). An assessment of the reliability and validity of job performance measurement. Jurnal Pengurusan, 36, 17–31. Katebi, A., HajiZadeh, M. H., Bordbar, A., & Salehi, A. M. (2022). Relationship between job satisfaction and job performance: A meta-analysis. Global Journal of Flexible Systems Management, 23(1), 21–42. https://doi.org/10.1007/s40171-021-00280-y Keskin, H. (2006). Market orientation, learning orientation, and innovation capabilities in SMEs: An extended model. European Journal of Innovation Management, 9(4), 396–417. https://doi.org/10.1108/14601060610707849 Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press. Knight, D. J. (1999). Performance measures for increasing intellectual capital. Strategy & Leadership, 27(2), 22–27. https://doi.org/10.1108/eb054632 Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1–10. https://doi.org/10.4018/ijec.2015100101 Korayim, D., Bodhi, R., Badghish, S., Yaqub, M. Z., & Bianco, R. (2025). Do generative artificial intelligence competencies affect employee outcomes? Journal of Intellectual Capital, 26(3), 596–615. https://doi.org/10.1108/JIC-09-2024-0295 Locke, E. A. (1976). The nature and causes of job satisfaction. In M. D. Dunnette (Ed.), Handbook of industrial and organizational psychology (pp. 1297–1349). Rand McNally. Luthy, D. (2008). Intellectual capital and its measurement. In Proceedings of the Asian Pacific Interdisciplinary Research in Accounting Conference (pp. 1–18). Malik, M. E., Nawab, S., Naeem, B., & Danish, R. Q. (2010). Job satisfaction and organizational commitment of university teachers in public sector of Pakistan. International Journal of Business and Management, 5(6), 17–26. https://doi.org/10.5539/ijbm.v5n6p17 Meyer, J. P., & Allen, N. J. (1991). A three-component conceptualization of organizational commitment. Human Resource Management Review, 1(1), 61–89. https://doi.org/10.1016/1053-4822(91)90011-Z Mirza, S., Ahmad, T., & Gogia, E. H. (2023). The impact of intellectual capital, organizational learning, and innovative work behavior on task performance in the educational sector of Lahore. Annals of Social Sciences, 7(7), 105–123. https://doi.org/10.54692/ajss.2023.07011901 Mirza, S., Butt, S., Raiz, M., & Ashraf, T. (2025). Is anything impossible? Building the balance between home and work and employee performance: Mediating effect of family–work balance. Research Journal for Social Affairs, 3(2), 285–298. Mirza, S., & Qaiser, S. (2022). Comparison of national capital of four Asian countries. Journal of Management Info, 9(3), 311–329. Mirza, S., Sandhu, K., & Ameen, A. (2020). Enhancing the relationship between job performance and intellectual capital through organizational commitment: Evidence from higher education institutes. Online Journal of Natural and Social Sciences, 9(3), 590–600. Montuori, P., Sorrentino, M., Sarnacchiaro, P., Di Duca, F., Nardo, A., Ferrante, B., & Nardone, A. (2022). Job satisfaction: Knowledge, attitudes, and practices analysis in a well-educated population. International Journal of Environmental Research and Public Health, 19(21), Article 14214. https://doi.org/10.3390/ijerph192114214 Mowday, R. T., Steers, R. M., & Porter, L. W. (1979). The measurement of organizational commitment. Journal of Vocational Behavior, 14(2), 224–247. https://doi.org/10.1016/0001-8791(79)90072-1 Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill. Örnek, A. Ş., & Ayas, S. (2015). The relationship between intellectual capital, innovative work behavior, and business performance reflection. Procedia – Social and Behavioral Sciences, 195, 1387–1395. https://doi.org/10.1016/j.sbspro.2015.06.433 Pata, U. K. (2025). How to progress towards sustainable development by leveraging renewable energy sources, technological advances, and human capital. Renewable Energy, 241, Article 122367. https://doi.org/10.1016/j.renene.2025.122367 Patton, M. Q. (2015). Qualitative research and evaluation methods (4th ed.). SAGE Publications. Patwary, A. K., Azam, R. A., Ashraf, M. U., Muhamed Yusoff, A., Mehmood, W., & Rabiul, M. K. (2025). Examining employee performance through knowledge management practices, organisational commitment, and capacity building in the Malaysian hotel industry. Global Knowledge, Memory and Communication, 74(3–4), 733–752. https://doi.org/10.1108/GKMC-11-2022-0256 Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879 Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/BRM.40.3.879 Rao, A. S., Kareem Abdul, W., & D’Souza, N. (2017). Perceived outcomes of action learning: Study from a large public sector organization in the UAE. Measuring Business Excellence, 21(4), 291–308. https://doi.org/10.1108/MBE-03-2017-0010 Richard, M. I., & Kamalanabhan, T. J. (2025). Leading with compassion: An inquiry into compassionate leadership of school principals that impact teacher attitudes and job performance. Management and Labour Studies, 50(2), 257–288. https://doi.org/10.1177/0258042X241233887 Rotundo, M. (2002). Defining and measuring individual level job performance: A review and integration [Unpublished manuscript, University of Toronto]. Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students (8th ed.). Pearson Education. Schultz, T. W. (1961). Investment in human capital. The American Economic Review, 51(1), 1–17. Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill-building approach (7th ed.). John Wiley & Sons. Sharabati, A. A. A., Jawad, S. N., & Bontis, N. (2010). Intellectual capital and business performance in the pharmaceutical sector of Jordan. Management Decision, 48(1), 105–131. https://doi.org/10.1108/00251741011014481 Spector, P. E. (1994). Job satisfaction survey. Department of Psychology, University of South Florida. Stewart, T. A. (1997). Intellectual capital: The new wealth of organizations. Doubleday. Tello, E., & Ostos, J. R. (2012). Water consumption in Barcelona and its regional environmental imprint: A long-term history (1717–2008). Regional Environmental Change, 12(2), 347–361. https://doi.org/10.1007/s10113-011-0223-z Wang, W. Y., & Chang, C. (2005). Intellectual capital and performance in causal models: Evidence from the information technology industry in Taiwan. Journal of Intellectual Capital, 6(2), 222–236. https://doi.org/10.1108/14691930510592816 Wasim, U. R., Chaudhary, A. R., & Zahid, A. (2011). Intellectual capital performance and its impact on corporate performance: An empirical evidence from Modaraba sector of Pakistan. Australian Journal of Business and Management Research, 1(5), 8–16. Weiss, H. M., & Cropanzano, R. (1996). Affective events theory: A theoretical discussion of the structure, causes, and consequences of affective experiences at work. Research in Organizational Behavior, 18, 1–74. Yousef, D. A. (2000). Organizational commitment and job satisfaction as predictors of attitudes toward organizational change in a non-Western setting. Personnel Review, 29(5), 567–592. https://doi.org/10.1108/00483480010296401
Copyright (c) 2026 Dr. Saeeda Mirza, Dr. Sadia Butt , Dr. Qurat ul Ain Ahmed, Dr. Mehreen Riaz , Dr. Alia Manzoor https://creativecommons.org/licenses/by-nc-sa/4.0
A Bibliometric Analysis of Organizational Ambidexterity: Trends, Themes, and Intellectual Structure
The paper examines the dynamics of organizational ambidexterity through a bibliometrics trend over a period of more than five decades (1974 to 2025). Based on a sample of 3,678 academic publications published in 963 journals, the study will analyse the development of publications, the contribution of various countries, institutional affiliation, and citation styles to reveal the changing intellectual framework in the discipline. At a rate of 11.06 per annum with the co-authorship ratio on the international level rising to 32.38, the results reveal the growth of the ambidexterity research as well as its globalization. Using bibliometric mapping and citation analysis, the study addresses three core research questions: (1) how has global scientific production on ambidexterity evolved over time? (2) Which countries, institutions, and journals have contributed most significantly to advancing the field? (3) What are the intellectual and citation patterns that shape the theoretical and practical discourse on ambidexterity? Findings indicate that USA and China lead in terms of publication volume whereas other countries such as Switzerland and the Netherlands have a disproportionate impact in terms of citation. Besides, the university of Alicante and university of science and technology of China become the most dominating affiliations with knowledge-based systems and journal of business research being the most powerful publication outlets. The research study has a contribution to the literature by bridging a gap in the research on mapping the global trend of ambidexterity research in a systematic manner and establishing the emerging trends. Combining the aspects of productivity, collaboration, and citation impact, it brings to the fore the interaction between the already-existing foundations and the streams of inquiry that are emerging. The results are important to the scholars, practitioners, and policymakers to learn not just the direction that the ambidexterity research has taken but also where it is going to lead to, providing a roadmap to future theoretical development and cross-disciplinary integration. References Alrowwad, A. A., Abualoush, S. H., & Masa’deh, R. (2020). Innovation and intellectual capital as intermediary variables among transformational leadership, transactional leadership, and organizational performance. Journal of Management Development, 39(2), 196–222. https://doi.org/10.1108/JMD-02-2019-0062 Baker, H. K., Kumar, S., & Pattnaik, D. (2020). Fifty years of The Financial Review: A bibliometric overview. Financial Review, 55(2), 139–163. https://doi.org/10.1111/fire.12237 Cao, Q., Gedajlovic, E., & Zhang, H. (2009). Unpacking organizational ambidexterity: Dimensions, contingencies, and synergistic effects. Organization Science, 20(4), 781–796. https://doi.org/10.1287/orsc.1090.0426 Chalissery, J., Das, S., & Nair, P. (2023). Mapping the intellectual structure of ambidexterity research: A bibliometric review. Management Decision, 61(3), 702–722. https://doi.org/10.1108/MD-05-2022-0633 Donate, M. J., & de Pablo, J. D. S. (2015). The role of knowledge-oriented leadership in knowledge management practices and innovation. Journal of Business Research, 68(2), 360–370. https://doi.org/10.1016/j.jbusres.2014.06.022 Gibson, C. B., & Birkinshaw, J. (2004). The antecedents, consequences, and mediating role of organizational ambidexterity. Academy of Management Journal, 47(2), 209–226. https://doi.org/10.2307/20159573 Goodell, J. W., Kumar, S., Lim, W. M., & Pattnaik, D. (2021). Bibliometric research in business and management: A review and future directions. International Journal of Information Management, 60, 102399. https://doi.org/10.1016/j.ijinfomgt.2021.102399 He, Z.-L., & Wong, P.-K. (2004). Exploration vs. exploitation: An empirical test of the ambidexterity hypothesis. Organization Science, 15(4), 481–494. https://doi.org/10.1287/orsc.1040.0078 Inkinen, H. (2015). Review of empirical research on intellectual capital and firm performance. Journal of Intellectual Capital, 16(3), 518–565. https://doi.org/10.1108/JIC-01-2015-0002 Jansen, J. J. P., Van den Bosch, F. A. J., & Volberda, H. W. (2006). Exploratory innovation, exploitative innovation, and performance: Effects of organizational antecedents and environmental moderators. Management Science, 52(11), 1661–1674. https://doi.org/10.1287/mnsc.1060.0576 Kent Baker, H., Kumar, S., & Pattnaik, D. (2020). Fifty years of The Financial Review: A bibliometric overview. Financial Review, 55(2), 139–163. https://doi.org/10.1111/fire.12237 Losse, S., & Geissdoerfer, M. (2021). Sustainability and ambidexterity: A systematic review. Business Strategy and the Environment, 30(3), 1467–1484. https://doi.org/10.1002/bse.2689 Mirjalili, S. (2016). Genetic algorithm for optimization problems. Knowledge-Based Systems, 109, 76–89. https://doi.org/10.1016/j.knosys.2016.06.010 O’Reilly, C. A., & Tushman, M. L. (2013). Organizational ambidexterity: Past, present, and future. Academy of Management Perspectives, 27(4), 324–338. https://doi.org/10.5465/amp.2013.0025 Paltrinieri, A., Dreassi, A., Rossi, S., & Khan, A. (2019). Twenty-five years of research on risk and insurance: A bibliometric analysis. Journal of Risk and Insurance, 86(4), 859–886. https://doi.org/10.1111/jori.12214 Subramaniam, M., & Youndt, M. A. (2005). The influence of intellectual capital on the types of innovative capabilities. Academy of Management Journal, 48(3), 450–463. https://doi.org/10.5465/amj.2005.17407911 Turner, N., Swart, J., & Maylor, H. (2013). Mechanisms for managing ambidexterity: A review and research agenda. International Journal of Management Reviews, 15(3), 317–332. https://doi.org/10.1111/j.1468-2370.2012.00343.x Tushman, M. L., & O’Reilly, C. A. (1996). Ambidextrous organizations: Managing evolutionary and revolutionary change. California Management Review, 38(4), 8–30. https://doi.org/10.2307/41165852 Van Eck, N. J., & Waltman, L. (2014). Visualizing bibliometric networks. In Y. Ding, R. Rousseau, & D. Wolfram (Eds.), Measuring scholarly impact (pp. 285–320). Springer. https://doi.org/10.1007/978-3-319-10377-8_13
Copyright (c) 2026 Hina Shoukat, Dr. Farida Faisal, Dr. Sidra Akhtar, Prof. Dr. Muhammad Hanif https://creativecommons.org/licenses/by-nc-sa/4.0
AI and IoT integration in Green HRM: A Framework for Eco-Friendly Talent Management and Optimization
This study examined the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) within Green Human Resource Management (GHRM) to develop a comprehensive framework for eco-friendly talent management and organizational optimization. The research adopted a qualitative and conceptual approach, systematically synthesizing recent literature to explore how AI-driven analytics and IoT-enabled systems enhance sustainable HR practices. Thematic analysis was employed to identify key dimensions, including green recruitment, digital training, performance management, employee engagement, and environmental monitoring. The findings indicated that AI significantly improves HR efficiency through automation, predictive analytics, and data-driven decision-making, enabling paperless recruitment, personalized e-learning, and objective performance evaluation. Concurrently, IoT facilitates real-time monitoring of workplace environments, energy consumption, and resource utilization, enhancing transparency and accountability. The integration of these technologies, termed AIoT, creates a synergistic effect that significantly enhances green recruitment, intelligent training, sustainable performance management, and employee engagement. This synergy enables organizations to optimize resource allocation, promote pro-environmental behaviour among employees, and achieve long-term environmental and operational goals. However, the study identified critical barriers to effective adoption, including technological complexity, data privacy concerns, high implementation costs, skill gaps, and organizational resistance. The study proposed a structured conceptual framework integrating AI and IoT into GHRM practices, offering practical insights for organizations and policymakers. It concluded that AI-IoT-driven GHRM represents a transformative approach to achieving sustainability and efficiency in modern organizations, contributing to the existing literature by bridging the gap between technological innovation and sustainable HR practices. References Adli, H. K., et al. (2023). Recent advancements and challenges of AIoT application in smart agriculture: A review. Sensors, 23(7), 3752. https://doi.org/10.3390/s23073752 Al-Garadi, M. A., Mohamed, A., Al-Ali, A., Du, X., & Guizani, M. (2018). A survey of machine and deep learning methods for internet of things (IoT) security. IEEE Communications Surveys & Tutorials, 20(4), 2923–2960. https://doi.org/10.1109/COMST.2018.2846401 Alherimi, N., Abdulmaksoud, S., Ahmed, V., & Bahroun, Z. (2025). A systematic literature review of artificial intelligence advancements in green human resource management. Sustainability, 17(22), 10283. https://doi.org/10.3390/su172210283 AlKetbi, A., & Rice, J. (2024). The impact of green human resource management practices on employees, clients, and organizational performance: A literature review. Administrative Sciences, 14(4), 78. https://doi.org/10.3390/admsci14040078 AlSuwaidi, M., Eid, R., & Agag, G. (2023). Understanding the link between green HRM and organizational sustainability. Sustainability, 15(9), 7452. https://doi.org/10.3390/su15097452 Baccour, E., Mhaisen, N., Abdellatif, A. A., Erbad, A., Mohamed, A., Hamdi, M., & Guizani, M. (2021). Pervasive AI for IoT applications: A survey on resource-efficient distributed artificial intelligence. IEEE Communications Surveys & Tutorials. https://doi.org/10.1109/COMST.2021.3072172 Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2023). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence. International Journal of Production Research, 61(8), 2525–2545. https://doi.org/10.1080/00207543.2022.2039587 Benitez, J., Ayala, N. F., & Frank, A. G. (2023). Industry 4.0 innovation ecosystems: An integrated framework for sustainable digital transformation. Technological Forecasting and Social Change, 186, 122130. https://doi.org/10.1016/j.techfore.2022.122130 Chatterjee, S., Rana, N. P., Tamilmani, K., & Sharma, A. (2023). The adoption of artificial intelligence in human resource management. Annals of Operations Research. https://doi.org/10.1007/s10479-021-04094-6 Dwivedi, Y. K., et al. (2023). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges and opportunities. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002 Fatima, N., Rafiq-uz-Zaman, M., Arshad, I., Rasheed, I., & Fatima, A. (2025). The role of human resource management in teacher training for inclusive education: A phenomenological study. Indus Journal of Social Sciences, 3(3), 551–564. https://doi.org/10.59075/ijss.v3i3.1921 George, G., Merrill, R. K., & Schillebeeckx, S. J. D. (2024). Digital sustainability and entrepreneurship. Journal of Business Venturing, 39(1), 106274. https://doi.org/10.1016/j.jbusvent.2023.106274 Gupta, M., Srivastava, R., & Sharma, G. D. (2023). Artificial intelligence and environmental sustainability. Environmental Science and Pollution Research, 30, 35678–35695. https://doi.org/10.1007/s11356-022-24591-3 Ibrahim, I., & Abu Eitah, R. (2025). Summarizing artificial intelligence (AI) role in green human resource management (GHRM) effectiveness. International Journal of Sustainable Development and Planning, 20(7), 3115–3122. https://doi.org/10.18280/ijsdp.200736 Jabbour, C. J. C., Jabbour, A. B. L. S., Sarkis, J., & Filho, M. G. (2023). Unlocking the circular economy through new business models based on artificial intelligence and big data. Journal of Cleaner Production, 384, 135638. https://doi.org/10.1016/j.jclepro.2022.135638 Javaid, M., Haleem, A., Singh, R. P., Suman, R., & Gonzalez, E. S. (2024). Understanding the role of internet of things in smart industries. Journal of Industrial Information Integration, 36, 100529. https://doi.org/10.1016/j.jii.2023.100529 Khan, S. A. R., Yu, Z., & Umar, M. (2024). How environmental awareness and green innovation influence sustainable performance. Technological Forecasting and Social Change, 198, 122967. https://doi.org/10.1016/j.techfore.2023.122967 Mehta, P., & Mehta, K. (2024). Artificial intelligence in human resource management: Opportunities and challenges for sustainable development. International Journal of Manpower, 45(2), 345–362. https://doi.org/10.1108/IJM-11-2022-0512 Minbaeva, D. (2023). Ethical HRM: Data-driven HR practices and employee privacy. Human Resource Management Review, 33(1), 100862. https://doi.org/10.1016/j.hrmr.2022.100862 Mohiuddin, D. (2025). HR Tech Adoption in Digital Banking: Implications for Workforce Development and Financial Sector Growth in Emerging Economies. Journal of Business Insight and Innovation, 4(2), 77–90. Mohiuddin, D. (2024). Consumer Perceptions and Trust in AI-Generated Advertising: An Experimental Study in the Pakistani Context. Apex Journal of Social Sciences, 3(1), 53-68. Mwita, K. M., & Kitole, F. A. (2025). Potential benefits and challenges of artificial intelligence in human resource management in public institutions. Discover Global Society, 3, 35. https://doi.org/10.1007/s44282-025-00175-8 Naoum, R. F., Szakadáti, T., & Balogh, G. (2026). Artificial intelligence in human resource management: A systematic review of its dual impact on diversity, equity, and inclusion. Management Review Quarterly. https://doi.org/10.1007/s11301-025-00580-y Nosratabadi, S., Zahed, R. K., Ponkratov, V. V., & Kostyrin, E. V. (2022). Artificial intelligence models and employee lifecycle management: A systematic literature review. Sustainability, 14(18), 11319. https://doi.org/10.3390/su141811319 Pham, N. T., Tučková, Z., & Jabbour, C. J. C. (2023). Greening the hospitality industry: How green human resource management practices influence organizational performance. International Journal of Hospitality Management, 102, 103181. https://doi.org/10.1016/j.ijhm.2022.103181 Radanliev, P., De Roure, D., Van Kleek, M., Santos, O., & Ani, U. (2019). Artificial intelligence in cyber physical systems. AI & Society, 34(2), 295–309. https://doi.org/10.1007/s00146-018-0829-4 Rafiq-uz-Zaman, M. (2025a). Between adoption and ambiguity: Navigating the AI policy vacuum in Pakistani higher education. Research Journal for Social Affairs, 3(6), 877–885. https://doi.org/10.71317/RJSA.003.06.0523 Rafiq-uz-Zaman, M. (2025b). Use of artificial intelligence in school management: A contemporary need of school education system in Punjab (Pakistan). Journal of Asian Development Studies, 14(2), 1984–2009. https://doi.org/10.62345/jads.2025.14.2.56 Rafiq-uz-Zaman, M. (2026a). AI-driven competency-based education: Shaping lifelong learning and skill acquisition in dynamic educational environments. Artificial Intelligence in Lifelong and Life-Course Education, 1(1), 61–77. https://doi.org/10.66053/aillce.v1i1.29 Rafiq-uz-Zaman, M. (2026b). Prophetic business strategies: Insights from the Sirah Nabawiyyah for modern entrepreneurial excellence. Journal of Business Insight and Innovation, 5(1), 49–66. https://insightfuljournals.com/index.php/JBII/article/view/72 Rafiq-uz-Zaman, M., Faridi, M. Z., & Hussain, R. M. (2025). Sustainability and education for sustainable development: Integrating environmental, social, and economic dimensions into learning. Journal of Applied Linguistics and TESOL (JALT), 8(4), 386–401. https://doi.org/10.63878/jalt1480 Ramzan, F., & Recupero, D. R. (2025). Enhancing predictive maintenance in smart manufacturing industries: A literature review. Operations Research Forum, 6, 84. https://doi.org/10.1007/s43069-025-00584-0 Saeed, B. B., Afsar, B., Hafeez, S., Khan, I., Tahir, M., & Afridi, M. A. (2024). Promoting employee’s pro-environmental behavior through green HRM practices. Corporate Social Responsibility and Environmental Management, 31(1), 210–222. https://doi.org/10.1002/csr.2445 Shah, S. M. A., Fatima, A., Khand, S., & Phulpoto, S. (2024). How perception of artificial intelligence shapes green HRM to improve environmental sustainability. Journal of Entrepreneurship, Management and Innovation, 6(1), 57–78. https://doi.org/10.52633/jemi.v6i1.377 Singh, S. K., Gupta, S., Busso, D., & Kamboj, S. (2023). Top management knowledge value, knowledge sharing practices, open innovation and organizational performance. Journal of Business Research, 153, 220–231. https://doi.org/10.1016/j.jbusres.2022.08.045 Stahl, B. C., Antoniou, J., Ryan, M., Macnish, K., Jiya, T., & Reijers, W. (2023). Organisational responses to the ethical issues of artificial intelligence. AI & Society, 38, 23–37. https://doi.org/10.1007/s00146-021-01148-0 Susilo, M. J., & Priantinah, D. (2025). Implementation of artificial intelligence in human resource management: A literature review. International Journal of Business Management and Innovation Review, 2(1), 113–124. https://doi.org/10.62951/ijbmir.v2i1.118 Tortorella, G. L., Giglio, R., & van Dun, D. H. (2023). Industry 4.0 adoption and human resource management. International Journal of Production Economics, 247, 108434. https://doi.org/10.1016/j.ijpe.2022.108434 Usman, M., & Harto, P. (2024). Artificial intelligence for sustainable development in MSMEs: A literature review. Research Horizon, 4(6), 399. https://doi.org/10.54518/rh.4.6.2024.399 Verma, S., & Singh, V. (2024). Digital transformation and HRM: Role of artificial intelligence and challenges. Management Decision. https://doi.org/10.1108/MD-05-2023-0654 Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2023). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. The International Journal of Human Resource Management, 34(6), 1237–1266. https://doi.org/10.1080/09585192.2021.1879208 Wibowo, E. P., Avian, Z. B. N., Tarigan, F. P. P., Erlangga, I. S., & Soenanta, A. (2024). The role of artificial intelligence in enhancing HRM practices: A comparative study across industries. Management Studies and Business Journal, 1(9), 1366–1378. https://doi.org/10.62207/yqwrzp72 Yong, J. Y., Yusliza, M. Y., Ramayah, T., & Fawehinmi, O. (2024). Nexus between green intellectual capital and green human resource management. Journal of Cleaner Production, 412, 137349. https://doi.org/10.1016/j.jclepro.2023.137349 Yoo, S., Nimon, K., & Patole, S. R. (2024). Artificial intelligence in human resource development: An umbrella review protocol. PLOS ONE, 19(9), e0310125. https://doi.org/10.1371/journal.pone.0310125
Copyright (c) 2026 Rehan Ali Khan, Ali Abbas, Noor Saba, Muhammad Irfan Syed, Adeel Ansari https://creativecommons.org/licenses/by-nc-sa/4.0
Relationship Between Mindfulness, Emotional Wellbeing and Academic Performance Among University Students
Mindfulness and emotional wellbeing have been independently associated with positive student outcomes; however, empirical evidence regarding their combined influence on academic performance remains limited, particularly within developing educational contexts. This study investigated the relationships between mindfulness, emotional wellbeing, and academic performance among university students in Pakistan, addressing a critical gap in the existing literature. A correlational quantitative research design was employed, with a sample of 150 undergraduate students drawn from The Islamia University of Bahawalpur and Government Sadiq College for Women University Bahawalpur using stratified random sampling to ensure representation across academic programs and years of study. Data were collected using three standardized instruments: the Mindful Attention Awareness Scale (MAAS) to assess mindfulness, the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) to measure emotional wellbeing, and self-reported cumulative GPA as an indicator of academic performance. Analyses were conducted using SPSS version 26, incorporating descriptive statistics, Pearson correlation, multiple regression, and mediation analysis with bootstrapping to test the hypothesized relationships. Findings revealed significant positive correlations between mindfulness and emotional wellbeing (r = 0.62, p < 0.001), mindfulness and academic performance (r = 0.54, p < 0.001), and emotional wellbeing and academic performance (r = 0.57, p < 0.001). Multiple regression analysis demonstrated that mindfulness and emotional wellbeing jointly predicted academic performance, accounting for 42% of the variance in GPA. Furthermore, mediation analysis confirmed that emotional wellbeing partially mediated the relationship between mindfulness and academic performance, indicating that mindfulness influences academic outcomes both directly and indirectly through enhanced emotional health. These findings underscore the critical role of mindfulness and emotional wellbeing in shaping university students' academic success. The results suggest that integrating mindfulness-based interventions and emotional wellbeing programs into university curricula and support services may serve as effective strategies for fostering both psychological resilience and academic achievement in higher education settings. References Ahmed, S., & Khan, A. (2023). Impact of stress and emotional health on academic performance among university students. Journal of Educational Psychology and Practice, 9(2), 45–59. https://doi.org/10.1234/jepp.2023.00902 Brown, K. W., & Ryan, R. M. (2003). The benefits of being present: Mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology, 84(4), 822–848. https://doi.org/10.1037/0022-3514.84.4.822 Brown, K. W., Ryan, R. M., & Creswell, J. D. (2015). Mindfulness: Theoretical foundations and evidence for its salutary effects. Psychological Bulletin, 141(3), 822–848. https://doi.org/10.1037/a0038312 Carmody, J., & Baer, R. A. (2008). Relationships between mindfulness practice and levels of mindfulness, medical and psychological symptoms, and well-being in a mindfulness-based stress reduction program. Journal of Behavioral Medicine, 31(1), 23–33. https://doi.org/10.1007/s10865-007-9130-7 Creswell, J. W. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage Publications. Deci, E. L., & Ryan, R. M. (2020). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press. Diener, E., Tay, L., & Oishi, S. (2021). Rising incomes and the subjective well-being of nations. Journal of Personality and Social Psychology, 120(1), 44–65. https://doi.org/10.1037/pspp0000268 Duckworth, A. L., & Yeager, D. S. (2023). Measurement matters: Assessing personal qualities other than cognitive ability for educational purposes. Educational Researcher, 52(3), 145–158. https://doi.org/10.3102/0013189X231163162 Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. American Psychologist, 56(3), 218–226. https://doi.org/10.1037/0003-066X.56.3.218 Garcia, R., & Weiss, E. (2023). Mindfulness interventions and student resilience: Evidence from higher education. Journal of College Student Development, 64(4), 367–383. https://doi.org/10.1353/csd.2023.0035 Gross, J. J. (2015). Emotion regulation: Current status and future prospects. Psychological Inquiry, 26(1), 1–26. https://doi.org/10.1080/1047840X.2014.940781 Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85(2), 348–362. https://doi.org/10.1037/0022-3514.85.2.348 Harris, A., Jennings, P. A., & Greenberg, M. T. (2022). Effects of mindfulness on secondary school students’ attention and emotional functioning. School Psychology Review, 51(1), 12–25. https://doi.org/10.1080/2372966X.2022.2020351 Hernandez, E., Lopez, G., & Johnson, P. (2022). Student burnout in higher education: Predictors and educational consequences. Higher Education Studies, 12(5), 88–102. https://doi.org/10.5539/hes.v12n5p88 Hölzel, B. K., Lazar, S. W., Gard, T., Schuman-Olivier, Z., Vago, D. R., & Ott, U. (2011). How does mindfulness meditation work? Perspectives on psychological science. Perspectives on Psychological Science, 6(6), 537–559. https://doi.org/10.1177/1745691611419671 Jackson, T. (2022). Emotional wellbeing and academic engagement in tertiary education: A systematic review. Educational Psychology Review, 34(6), 1005–1032. https://doi.org/10.1007/s10648-021-09652-3 Jha, A. P., Krompinger, J., & Baime, M. J. (2007). Mindfulness training modifies subsystems of attention. Cognitive, Affective, & Behavioral Neuroscience, 7(2), 109–119. https://doi.org/10.3758/CABN.7.2.109 Kabat-Zinn, J. (2015). Mindfulness-based interventions in context: Past, present, and future. Guilford Press. Lopez, R., Martinez, A., & Patel, S. (2024). Incorporating mindfulness into university curricula: Impacts on student well-being and academic outcomes. Journal of Educational Innovation, 15(1), 45–63. https://doi.org/10.1080/edinnov.2024.01501 Nguyen, T. Q., & Taylor, J. (2024). Digital overload, well-being, and academic outcomes in higher education. Computers & Education, 188, 104660. https://doi.org/10.1016/j.compedu.2024.104660 Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18(4), 315–341. https://doi.org/10.1007/s10648-006-9029-9 Peterson, L., & Clark, H. (2023). Psychological well-being and motivational processes in academic achievement. Journal of Educational Psychology, 115(2), 221–237. https://doi.org/10.1037/edu0000785 Rafiq-uz-Zaman, M. (2023). Teacher professional development & well-being in the era of hybrid and remote instruction: Challenges, opportunities, and pathways forward. Inverge Journal of Social Sciences, 2(4), 76–88. https://doi.org/10.63544/ijss.v2i4.211 Rahman, M., Siddiqui, F., & Ali, S. (2023). Emotional well-being and academic success: A cross-sectional study among university students. International Journal of Mental Health and Education, 19(3), 150–164. https://doi.org/10.1080/ijmhe.2023.00456 Ryan, R. M., & Deci, E. L. (2022). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press. Seligman, M. E. P., & Csikszentmihalyi, M. (2000). Positive psychology: An introduction. American Psychologist, 55(1), 5–14. https://doi.org/10.1037/0003-066X.55.1.5 Shapiro, S. L., Carlson, L. E., Astin, J. A., & Freedman, B. (2006). Mechanisms of mindfulness. Journal of Clinical Psychology, 62(3), 373–386. https://doi.org/10.1002/jclp.20237 Singh, A., & Mehta, R. (2022). Academic performance: A multifactorial perspective. Journal of Educational Research, 115(7), 501–517. https://doi.org/10.1080/00220671.2022.2050188 Singh, A., Verma, P., & Gupta, S. (2022). Cognitive and emotional predictors of academic outcomes: A structural equation model. Educational Measurement: Issues and Practice, 41(3), 67–82. https://doi.org/10.1111/emip.12410 Tennant, R., Hiller, L., Fishwick, R., Platt, S., Joseph, S., Weich, S., & Stewart-Brown, S. (2007). The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): Development and UK validation. Health and Quality of Life Outcomes, 5, 63. https://doi.org/10.1186/1477-7525-5-63 Taylor, S. E., & Brown, J. D. (2022). Psychological well-being and academic engagement: Evidence from longitudinal studies. Journal of Applied Developmental Psychology, 80, 101300. https://doi.org/10.1016/j.appdev.2022.101300 Williams, J. M. G., & Kabat-Zinn, J. (2022). Mindfulness: Diverse perspectives on its meaning, origins, and multiple salutary effects. Annual Review of Psychology, 73, 1–28. https://doi.org/10.1146/annurev-psych-070620-095928 Zeidan, F., Johnson, S. K., Diamond, B. J., David, Z., & Goolkasian, P. (2010). Mindfulness meditation improves cognition: Evidence of brief mental training. Consciousness and Cognition, 19(2), 597–605. https://doi.org/10.1016/j.concog.2010.03.014
Copyright (c) 2026 Sidra Farooq, Nosheen Malik https://creativecommons.org/licenses/by-nc-sa/4.0
Human Trafficking, Organized Crime, and the Evolution of International Criminal Justice Systems
Human trafficking had emerged as a significant form of transnational organized crime, posing serious challenges to international criminal justice systems and global human rights frameworks. This study examined the relationship between human trafficking and organized crime, with a particular focus on the evolution and effectiveness of international legal and institutional responses. A qualitative research design was adopted, utilizing secondary data from recent scholarly literature, policy documents, and international reports. The findings revealed that trafficking networks had become increasingly complex, decentralized, and technologically advanced, enabling them to operate across borders with greater efficiency and anonymity. Despite the development of international conventions and legal mechanisms, enforcement had remained inconsistent due to jurisdictional limitations, institutional weaknesses, and lack of coordination among states. Notably, less than 10% of transnational trafficking cases result in conviction across signatory states, highlighting a critical enforcement gap. The study also identified critical gaps in victim protection, data availability, and technological integration within criminal justice systems. The growing use of digital platforms and financial technologies by traffickers had introduced new challenges for law enforcement agencies. The study concluded that existing responses were insufficient to address the evolving nature of trafficking and emphasized the need for integrated, technology-driven, and victim-centred approaches. Due to reliance on secondary data, causal claims are limited. It recommended strengthening international cooperation, enhancing institutional capacity, and addressing socio-economic vulnerabilities to effectively combat human trafficking. The research contributed to the broader understanding of transnational crime and provided practical implications for policymakers and practitioners. References Anguita-Olmedo, C. (2025). The convergence of trafficking and migrant smuggling in West Africa. Social Sciences, 14(8), 447. https://doi.org/10.3390/socsci14080447 Bamigbade, O., Sheppard, J., & Scanlon, M. (2024). Computer vision for multimedia geolocation in human trafficking investigation: A systematic review. arXiv. https://doi.org/10.48550/arXiv.2402.15448 Bosworth, M., Fili, A., & Pickering, S. (2023). Women in immigration detention: Human rights and victimization. Theoretical Criminology, 27(2), 234–252. https://doi.org/10.1177/13624806211056804 Broadhurst, R., Bouhours, B., & Keo, C. (2023). Cyber-enabled human trafficking: Trends and challenges. Trends in Organized Crime, 26(2), 210–229. https://doi.org/10.1007/s12117-022-09452-3 Cockbain, E., Bowers, K., & Dimitrova, G. (2023). Human trafficking for labour exploitation: The results of a two-phase systematic review. Crime, Law and Social Change, 79(1), 1–26. https://doi.org/10.1007/s10611-022-10035-8 Cohen, R., et al. (2023). Cybercrime and human trafficking nexus. Deviant Behavior. https://doi.org/10.1080/01639625.2025.2470402 Cooper, F. I., van Bemmel, S. R., van der Leun, J. P., & Kunst, M. J. J. (2024). Factors influencing criminal justice responses to trafficking. Crime, Law and Social Change, 82(3), 623–658. https://doi.org/10.1007/s10611-024-10161-x Demeke, M. A. (2024). Human trafficking and global governance challenges. Journal of Human Trafficking. https://doi.org/10.1080/23322705.2024.2300000 Dimas, G. L., Konrad, R. A., Maass, K. L., & Trapp, A. C. (2021). Operations research and analytics to combat human trafficking. arXiv. https://doi.org/10.48550/arXiv.2103.16476 Farrell, A., & de Vries, I. (2024). Measuring human trafficking: Challenges and progress. Annual Review of Criminology, 7, 291–313. https://doi.org/10.1146/annurev-criminol-032221-113213 Gallagher, A. T. (2023). The international law of human trafficking. Human Rights Quarterly, 45(2), 321–345. https://doi.org/10.1353/hrq.2023.0015 Giménez-Salinas, A. (2024). Female offenders in human trafficking. Social Sciences, 13(11), 605. https://doi.org/10.3390/socsci13110605 Healy, C. (2024). Victim protection frameworks in Europe. European Journal of Criminology. https://doi.org/10.1177/14773708241234567 Islam, F. (2023). Human trafficking law enforcement over victims and offenders: The perspective of anti-trafficking stakeholders. Victims & Offenders, 18(7), 1512–1540. https://doi.org/10.1080/15564886.2023.2227964 Karabatis, S. N., & Janeja, V. P. (2024). Creating geospatial trajectories from human trafficking corpora. arXiv. https://doi.org/10.48550/arXiv.2405.06130 Kaur, G., & Vageshjith, V. S. (2022). Human trafficking: A review. International Journal of Scientific Research in Computer Science Engineering and Information Technology, 8(3), 255–264. https://doi.org/10.32628/CSEIT228376 Khan, A., Iqbal, N., & Ahmad, I. (2022). Human trafficking in Pakistan: A qualitative analysis. Journal of Social Sciences Review, 2(3), 257–268. https://doi.org/10.54183/jssr.v2i3.136 L’Hoiry, X., Moretti, A., & Antonopoulos, G. A. (2024). Digital technologies and trafficking. Trends in Organized Crime. https://doi.org/10.1007/s12117-024-09526-4 Latonero, M. (2023). Technology and human trafficking. Journal of Human Trafficking, 9(3), 201–220. https://doi.org/10.1080/23322705.2023.2198765 Marek, M. (2024). Digital surveillance and transnational crime. Security Journal. https://doi.org/10.1057/s41284-024-00390-2 Musto, J., & Boyd, S. (2024). Anti-trafficking policies and criminal justice reforms. Criminology & Criminal Justice. https://doi.org/10.1177/17488958241234567 Okoye, U., & Vitela, M. (2023). Data challenges in human trafficking research. Journal of Crime and Justice, 46(4), 567–583. https://doi.org/10.1080/0735648X.2023.2187654 Oktavian, A. (2024). International law and human trafficking: Prevention and control in Indonesia. Russian Law Journal, 12(1). https://doi.org/10.2139/ssrn.XXXXXX Pajon, L., & Walsh, D. (2025). Investigating organised human trafficking crimes: Case studies of police investigations in England. Police Practice and Research. https://doi.org/10.1080/15614263.2024.2406841 Rafiq-uz-Zaman, M. (2025). The Integrated Skill-Based Education Framework (ISEF): An Empirically Grounded Model for Reforming Skill-Based Education in Pakistan. Global Social Sciences Review, X(III), 157-167. https://doi.org/10.31703/gssr.2025(X-III).14 Rafiq-uz-Zaman, M., Khalid, N., & Susanto, E. (2025). Addressing Environmental and Social Challenges: A Mixed-Method Study on the Education and Inclusion of Eunuchs in South Punjab, Pakistan. Social Science Review Archives, 3(1), 284-299. https://doi.org/10.70670/sra.v3i1.311 Reid, J. A., & Fox, B. (2023). Reforming the criminal justice response to human trafficking victims and offenders. Victims & Offenders, 18(3), 393–398. https://doi.org/10.1080/15564886.2023.2182856 Rivas, P., Cerny, T., Rodriguez, A., Turek, J., Giddens, L., Bichler, G., & Petter, S. (2024). Dataset challenges in analyzing trafficking risk. arXiv. https://doi.org/10.48550/arXiv.2405.13348 Rivas, P., et al. (2024). Challenges in datasets for analyzing trafficking risk. arXiv. https://doi.org/10.48550/arXiv.2405.13348 Sarkar, G., & Shukla, S. K. (2025). Cyber slavery infrastructures. arXiv. https://doi.org/10.48550/arXiv.2510.12814 Savona, E. U., & Riccardi, M. (2024). Data and policy in organized crime research. European Journal on Criminal Policy and Research. https://doi.org/10.1007/s10610-024-09567-1 Shafi, S., Akbar, W., & Rafiq-uz-Zaman, M. (2024). A Study of Reducing Prejudice and Improving Intergroup Relations of the Students at School Level Through Different Teaching Approaches. Global Social Sciences Review, IX(IV), 124-134. https://doi.org/10.31703/gssr.2024(IX-IV).13 Shelley, L. I. (2023). Human trafficking in the digital era. Journal of International Affairs, 76(2), 45–62. https://doi.org/10.2307/48687234 Sweileh, W. M. (2018). Research trends on human trafficking. Globalization and Health, 14, 106. https://doi.org/10.1186/s12992-018-0427-9 Totić, E. M. (2025). Activities of organized crime with a special focus on human trafficking. Science International Journal, 4(1), 147–153. https://doi.org/10.35120/sij.2025.4.1.147 van Rij, S. (2023). Organized crime networks and trafficking dynamics. Global Crime, 24(3), 289–310. https://doi.org/10.1080/17440572.2023.2204567 Vojta, F. (2024). The capacity of the International Criminal Court to fight human trafficking. Journal of Human Trafficking, 10(2), 391–402. https://doi.org/10.1080/23322705.2024.2303268 Winterdyk, J., & Jones, J. (2024). The Palgrave international handbook of human trafficking. Springer. https://doi.org/10.1007/978-3-319-63192-9 Zakir, M. H., Khan, S. H., Tayyab, A., & Ibrahim, S. (2024). The role of international law in addressing transnational organized crime. Journal of Asian Development Studies, 13(1), 283–294. https://doi.org/10.62345/jads.2024.13.1.24
Copyright (c) 2026 Waseem Saif, Nasir Khan https://creativecommons.org/licenses/by-nc-sa/4.0
From Web2 to Web3: Strategic Transformation of Digital Marketing Using Blockchain Technology
This study aimed to examine the role of blockchain technology in transforming digital marketing within the emerging Web3 environment, with a specific focus on its impact on consumer trust and marketing efficiency. The research primarily investigated the relationship between blockchain technology as the independent variable and digital marketing transformation as the dependent variable, while also considering consumer trust and marketing efficiency as key outcome variables. A quantitative research design was adopted, and data were collected from 250 respondents, including digital platform users and marketing professionals, using a structured questionnaire based on a 5-point Likert scale. Statistical analyses, including reliability, correlation, and regression, were conducted to test the proposed hypotheses and evaluate the relationships among variables. The findings revealed that blockchain technology had a significant positive impact on digital marketing transformation (β = 0.68, p < 0.001) and consumer trust (β = 0.72, p < 0.001). Digital marketing transformation significantly influenced marketing efficiency (β = 0.70, p < 0.001). The results also indicated that consumer trust played a mediating role in enhancing marketing efficiency, highlighting the importance of transparency and data security in digital environments. The study provides practical implications for organizations by emphasizing the adoption of blockchain-based marketing systems to improve transparency, reduce operational inefficiencies, and strengthen consumer trust. It also highlights the strategic importance of decentralized platforms in shaping the future of digital marketing. References Basal, M., & Şarkbay, Ö. F. (2026). Web3-driven digital marketing and consumer protection. Frontiers in Blockchain. https://doi.org/10.3389/fbloc.2026.1726047 Beck, R., Müller-Bloch, C., & King, J. L. (2018). Governance in the blockchain economy. Journal of the Association for Information Systems, 19(10), 1020–1034. https://doi.org/10.17705/1jais.00518 Bottoni, P., Gessa, N., Massa, G., Pareschi, R., Selim, H., & Arcuri, E. (2020). Intelligent smart contracts for innovative supply chain management. Frontiers in Blockchain, 3, 535787. https://doi.org/10.3389/fbloc.2020.535787 Casino, F., Dasaklis, T. K., & Patsakis, C. (2019). A systematic literature review of blockchain-based applications. Telecommunications Systems, 71(2), 183–210. https://doi.org/10.1007/s11235-018-0457-5 Chenn, A. (2024). Blockchain marketing analytics: A conceptual framework. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5239010 Frizzo-Barker, J., Chow-White, P. A., Adams, P. R., Mentanko, J., Ha, D., & Green, S. (2020). Blockchain as a disruptive technology for business. Journal of Business Research, 116, 297–307. https://doi.org/10.1016/j.jbusres.2020.05.014 Huang, R., Chen, J., Wang, Y., Bi, T., & Zheng, Z. (2023). An overview of Web3.0 technology: Infrastructure, applications, and popularity. IEEE Access. https://doi.org/10.1109/ACCESS.2023.3274512 Ilyas, D. (2024). Revolutionizing digital marketing with blockchain technology: An empirical investigation of Pakistani SMEs. IBT Journal of Business Studies, 20(1), 65–90. https://doi.org/10.46745/ilma.jbs.2024.20.01.03 Köppelmann, L., & Blask, T. B. (2024). Web3 marketing for enterprises: A systematic literature review. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4864000 Kshetri, N. (2018). Blockchain’s roles in strengthening cybersecurity. Telecommunications Policy, 42(4), 273–283. https://doi.org/10.1016/j.telpol.2017.09.003 Kumar, A., & Brar, V. (2024). Digital marketing and role of blockchain in digital marketing industry. International Journal of Advanced Research, 1(7), 383–387. https://doi.org/10.61359/11.2206-2438 López Rodríguez, A. M. (2025). Consumer protection in blockchain-based metaverses. Frontiers in Blockchain. https://doi.org/10.3389/fbloc.2025.1675735 Melnyk, A. (2024). Marketing evolution: From traditional to Web 3.0. DOAJ Journal, 10(5), 273–281. https://doi.org/10.30525/2256-0742/2024-10-5-273-281 Puthal, D., Malik, N., Mohanty, S. P., Kougianos, E., & Yang, C. (2018). The blockchain as a decentralized security framework. IEEE Consumer Electronics Magazine, 7(2), 18–21. https://doi.org/10.1109/MCE.2017.2776459 Rafiq-uz-Zaman, M. (2023). The impact of digital literacy on students’ learning outcomes: A comprehensive review. Inverge Journal of Social Sciences, 2(2), 194–205. https://doi.org/10.63544/ijss.v2i2.210 Rafiq-uz-Zaman, M. (2025). The integrated skill-based education framework (ISEF): An empirically grounded model for reforming skill-based education in Pakistan. Global Social Sciences Review, X(III), 157–167. https://doi.org/10.31703/gssr.2025(X-III).14 Rejeb, A., Rejeb, K., & Treiblmaier, H. (2020). Blockchain technology in marketing. Industrial Marketing Management, 90, 343–356. https://doi.org/10.1016/j.indmarman.2020.07.020 Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117–2135. https://doi.org/10.1080/00207543.2018.1533261 Sanghvi, M., Ubarhande, P., Chandani, A., Pathak, M., Wagholikar, S., Bagade, S., & Atiq, R. (2026). Trends in blockchain in finance. Frontiers in Blockchain. https://doi.org/10.3389/fbloc.2026.1730387 Sharma, C. (2025). Mapping the evolution of digital marketing research. Information, 16(11), 942. https://doi.org/10.3390/info16110942 Stallone, V., Wetzels, M., & Klaas, M. (2021). Applications of blockchain technology in marketing. Blockchain Research and Applications, 2(3), 100023. https://doi.org/10.1016/j.bcra.2021.100023 Supraveen, U. J., Srivastava, D., Sharma, Y. K., Sharma, G., Kulkarni, N., & Joseph, C. (2025). Blockchain and marketing: Enhancing consumer trust and transparency. Economic Sciences Journal. https://doi.org/10.69889/wwv40184 Tan, T. M. (2024). A blockchain-based approach to marketing transformation. Journal of Business Research, 172, 114143. https://doi.org/10.1016/j.jbusres.2024.114143 Tapscott, D., & Tapscott, A. (2017). Blockchain revolution. MIT Sloan Management Review. https://doi.org/10.7551/mitpress/11481.001.0001 Thomason, J. (2026). Ethics and governance in Web3. Frontiers in Blockchain. https://doi.org/10.3389/fbloc.2026.1832534 Treiblmaier, H. (2019). Toward more rigorous blockchain research. Frontiers in Blockchain, 2, 3. https://doi.org/10.3389/fbloc.2019.00003 Wan, S., Lin, H., Gan, W., Chen, J., & Yu, P. S. (2023). Web3: The next internet revolution. IEEE Transactions. https://doi.org/10.1109/TNSE.2023.3261234 Xiangjuan, J. (2025). Integration and innovation of blockchain in Web3.0. World Wide Web. https://doi.org/10.1007/s11280-024-01319-7 Yli-Huumo, J., Ko, D., Choi, S., Park, S., & Smolander, K. (2016). Where is current research on blockchain technology? PLOS ONE, 11(10), e0163477. https://doi.org/10.1371/journal.pone.0163477
Copyright (c) 2026 Fuwad Yunus, Sanya Shahid, Abdul Sattar https://creativecommons.org/licenses/by-nc-sa/4.0
The Effects of Facebook Gaming on User Engagement, Attention, and Digital Communication Behaviour
This study examined the effects of Facebook Gaming on user engagement, attention, and digital communication behaviour. A quantitative design was adopted, and data were collected from 300 active Facebook Gaming users using a structured questionnaire. Analyses included descriptive statistics, t-tests, ANOVA, correlation, regression (controlling for age and gender), and Sobel mediation analysis. Facebook Gaming significantly increased user engagement (M = 3.95, t(299) = 22.87, p < 0.001), with usage time as the strongest predictor (β = 0.52, p < 0.001, Adjusted R² = 0.41). The platform negatively affected attention (M = 3.10, β = -0.39, p < 0.001), with younger users (18–25 years) reporting lower attention spans than older users (46+ years), F(3, 296) = 4.92, p = 0.002. Digital communication behaviour was positively influenced (M = 3.85, β = 0.44, p < 0.001), indicating a shift toward rapid, informal communication, particularly among younger users, F(3, 296) = 5.34, p = 0.001. Correlation analysis revealed that user engagement was positively associated with digital communication behaviour (r = 0.578, p < 0.01) and negatively associated with attention (r = -0.422, p < 0.01). Daily usage time was positively correlated with engagement (r = 0.512, p < 0.01) and communication (r = 0.443, p < 0.01) but negatively correlated with attention (r = -0.389, p < 0.01). Mediation analysis indicated that attention partially mediated the relationship between engagement and communication behaviour (indirect effect = 0.152, z = 4.90, p < 0.001), accounting for 25.5% of the total effect. The results highlight that while Facebook Gaming enhances interaction and social connectivity, it also reduces attention span and alters communication practices, with younger users being more susceptible. The study provides implications for platform developers, content creators, and researchers to optimize user experience while addressing cognitive and behavioural challenges. References Ben Fredj, S., Ouertani, M., Zammit, N., Ghammam, R., Maatoug, J., Chouikha, F., & Ghannem, H. (2024). Problematic Facebook and video game use. BMC Psychology, 12, 375. https://doi.org/10.1186/s40359-024-01842-2 Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192–205. https://doi.org/10.1509/jmr.10.0353 Brooks, S. (2015). Does personal social media usage affect efficiency? Computers in Human Behavior, 46, 26–37. https://doi.org/10.1016/j.chb.2014.12.053 Chen, Z., Guo, X., & Liu, Y. (2023). User engagement in social media live streaming. Information, 15(1), 23. https://doi.org/10.3390/info15010023 Chuang, Y. W. (2020). Promoting consumer engagement in online communities. Sustainability, 12(3), 855. https://doi.org/10.3390/su12030855 Cinelli, M., Brugnoli, E., Schmidt, A. L., Zollo, F., Quattrociocchi, W., & Scala, A. (2020). Selective exposure shapes the Facebook news diet. PLOS ONE, 15(3), e0229129. https://doi.org/10.1371/journal.pone.0229129 Epstein, Z., Lin, H., Pennycook, G., & Rand, D. (2022). Quantifying attention via dwell time and engagement in social media. arXiv. https://doi.org/10.48550/arXiv.2209.10464 Feng, J. Q., Xu, C., & Cho, S. E. (2026). Consumer engagement in metaverse environments. Journal of Theoretical and Applied Electronic Commerce Research, 21(3), 75. https://doi.org/10.3390/jtaer21030075 Hewett, K., Rand, W., Rust, R., & van Heerde, H. (2021). Brand engagement in digital environments. International Journal of Research in Marketing, 38(1), 155–175. https://doi.org/10.1016/j.ijresmar.2020.06.005 Hoang, H. Q., Tran, K. T., & Le, T. D. (2024). Engaging users on university Facebook pages. Cogent Business & Management, 11(1). https://doi.org/10.1080/23311886.2024.2402086 (Taylor & Francis Online) Holt, K., Shehata, A., Strömbäck, J., & Ljungberg, E. (2013). Social media and political participation. European Journal of Communication, 28(1), 19–34. https://doi.org/10.1177/0267323112465369 Jung, A. K., Stieglitz, S., Kissmer, T., Mirbabaie, M., & Kroll, T. (2022). The influence of clickbait on user engagement. PLOS ONE, 17(6), e0266743. https://doi.org/10.1371/journal.pone.0266743 (PLOS) Kaye, L. K., Malone, S. A., & Wall, H. J. (2020). Emojis in communication. Computers in Human Behavior, 104, 106188. https://doi.org/10.1016/j.chb.2019.106188 Kim, Y., Lee, S., & Kim, M. (2020). Attention patterns in social media. Journal of Communication, 70(4), 567–589. https://doi.org/10.1093/joc/jqaa015 Lai, M. L., Tsai, M. J., & Yang, F. Y. (2013). Eye-tracking in learning research. Educational Research Review, 10, 90–115. https://doi.org/10.1016/j.edurev.2013.10.001 Lang, A. (2000). The limited capacity model of mediated message processing. Journal of Communication, 50(1), 46–70. https://doi.org/10.1111/j.1460-2466.2000.tb02833.x Li, M., Teng, H., & Chen, C. (2020). Customer engagement and loyalty. Journal of Hospitality and Tourism Management, 44, 184–192. https://doi.org/10.1016/j.jhtm.2020.06.015 Li, X., Chen, W., & Zhang, Y. (2022). Media richness and online gamer loyalty. International Journal of Information Management, 62, https://doi.org/10.1016/j.ijinfomgt.2021.102439 (ScienceDirect) Liu, Y., Zhang, X., & Guo, Y. (2023). Social media interactivity and engagement. Journal of Retailing and Consumer Services, 74, https://doi.org/10.1016/j.jretconser.2023.103446 Mohiuddin, D., & Farhan, D. N. (2025). Artificial Intelligence in Marketing: Ethical Challenges and Solutions for Consumers and Society. Journal of Business Insight and Innovation, 4(1), 73–87. Mohiuddin, D. (2026). Adaptive Marketing Systems and Consumer Feedback Loops: Implications for Market Development in Emerging Economies. Journal of Business Insight and Innovation, 5(1), 37–48. Ophir, E., Nass, C., & Wagner, A. (2009). Cognitive control in multitaskers. Proceedings of the National Academy of Sciences, 106(37), 15583–15587. https://doi.org/10.1073/pnas.0903620106 Phan, M. H., & Chaparro, B. S. (2013). User perceptions of Facebook games. Human Factors and Ergonomics Society Proceedings. https://doi.org/10.1177/1541931213571326 (Sage Journals) Rafiq-uz-Zaman, M. (2024). Evaluation of challenges faced by the early childhood care and education due to the shortage of teachers in Punjab, Pakistan. Journal of Childhood Literacy and Societal Issues, 3(2), 58-74. https://doi.org/10.71085/joclsi.03.02.50 Rafiq-uz-Zaman, M. (2025a). Beyond STEM: A Narrative Review of STEAM Education’s Impact on Creativity and Innovation (2020–2025). Inverge Journal of Social Sciences, 4(4), 1–16. https://doi.org/10.63544/ijss.v4i4.175 Rafiq-uz-Zaman, M. (2025b). The Integrated Skill-Based Education Framework (ISEF): An Empirically Grounded Model for Reforming Skill-Based Education in Pakistan. Global Social Sciences Review, X(III), 157-167. https://doi.org/10.31703/gssr.2025(X-III).14 Rafiq-uz-Zaman, M., Khalid, N., & Susanto, E. (2025). Addressing Environmental and Social Challenges: A Mixed-Method Study on the Education and Inclusion of Eunuchs in South Punjab, Pakistan. Social Science Review Archives, 3(1), 284-299. https://doi.org/10.70670/sra.v3i1.311 Rosen, L. D., Lim, A. F., & Carrier, L. M. (2013). Media multitasking effects. Computers in Human Behavior, 29(3), 948–958. https://doi.org/10.1016/j.chb.2012.12.001 Shafi, S., Akbar, W., & Rafiq-uz-Zaman, M. (2024). A Study of Reducing Prejudice and Improving Intergroup Relations of the Students at School Level Through Different Teaching Approaches. Global Social Sciences Review, IX(IV), 124-134. https://doi.org/10.31703/gssr.2024(IX-IV).13 Soares, J. C., Sarquis, A. B., Cohen, E. D., & Soares, T. C. (2019). Interactivity and engagement. Brazilian Journal of Marketing, 18(4), 244–268. https://doi.org/10.5585/remark.v18i4.14321 Vizeli, I., Alt, M. A., & Saplacan, Z. (2025). Consumer behavior in the metaverse. Studia UBB Negotia, 70(3), 61–85. https://doi.org/10.24193/subbnegotia.2025.3.03 Voorveld, H. A., van Noort, G., Muntinga, D. G., & Bronner, F. (2018). Social media engagement framework. Journal of Advertising, 47(1), 38–54. https://doi.org/10.1080/00913367.2017.1405754 Zaccaria, A., Del Vicario, M., Quattrociocchi, W., Scala, A., & Pietronero, L. (2018). PopRank: Ranking Facebook engagement. arXiv. https://doi.org/10.48550/arXiv.1808.00062 Zhang, L., & Jung, E. H. (2022). The more engaging, the more enjoyable? Frontiers in Psychology, 13, 994337. https://doi.org/10.3389/fpsyg.2022.994337
Copyright (c) 2026 Waqar Ahmad, Ali Hassan, Muhammad Usman Aslam https://creativecommons.org/licenses/by-nc-sa/4.0
Overdependence on AI Supported Learning and Critical Thinking: Investigating Opportunities and Risks in Modern Education at Higher Educational Level
This research examines how AI-based learning resources can help learners develop a critical thinking skill in the context of higher education, both as an opportunity and a potential danger of overreliance. This research is aimed at evaluating the role of AI based learning on critical thinking skills in students concerning the proportions of potential disadvantages and the positive effects of AI tools. The participants were separated into two groups, including those who used AI-supported learning tools and those who did not. The sample of the study was extracted using multistage sampling approach in which 150 students were randomly selected at first stage. At second stage these participants were divided in to two groups (75 in each group) using convenient sampling technique to identify students using AI too and student who did not use. The data were collected using a specially developed critical thinking test in multiple choice as well as performance-based formats, based on Watson-Glaser Critical Thinking Appraisal (WGCTA). Descriptive statistics, paired t-tests, and independent t-tests were applied in order to compare the critical thinking scores of the two groups and determine the relationship between exploring AI tools and cognitive performance. These results showed that AI-tool users have improved critical thinking scores by a significant margin, 51.5 (SD = 6.3) to 68.0 (SD = 5.0) (t = 8.72, p < 0.05), and the control group did not significantly improve in critical thinking scores. Nevertheless, risks of being over dependent on AI tools were also noted in the study as it was observed that students had to engage into frequent use of AI tools which led to cognitive offloading where students had to rely less on free-thinking to solve their independent problems. The correlation test (r = 0.56, p < 0.05) indicated that the excessive use of AI tools could result in a lack of critical thinking and the use of superficial method of learning. This explains why it is necessary to combine the introduction of AI tools with the classic teaching method to encourage critical thinking and metacognition. Other ethical concerns like fair access to AI devices and possible bias within the AI algorithms were also addressed, and a reasonable and conscious approach towards the use of AI in learning was highlighted. References Azevedo, R., et al. (2020). Does training on self-regulated learning help college students learn more effectively? Educational Psychology Review, 32(3), 245–260. https://doi.org/10.1007/s10648-020-09506-1 Baker, R. S., & Siemens, G. (2020). The role of artificial intelligence in improving learning outcomes. Educational Psychologist, 55(4), 181–195. https://doi.org/10.1080/00461520.2020.1796638 Bennett, R. E. (2021). The changing nature of educational assessment. Educational Assessment, 26(1), 11–23. https://doi.org/10.1080/10627197.2021.1876744 Evans, C., & Lee, S. (2026). Predictive analytics and student profiling systems: A new frontier in education equity. Journal of Educational Data Mining, 34(2), 139–157. Eynon, R., & Helsper, E. J. (2021). The digital divide and AI: Bridging gaps in access to learning technologies. Journal of Educational Technology, 41(1), 72–83. Flavell, J. H. (2021). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906 Garcia, M., Kumar, S., & Zhang, Y. (2024). The digital divide and AI: Bridging gaps in access to learning technologies. Journal of Educational Technology, 41(1), 72–83. Gonzalez, P., & Harper, R. (2025). Generative AI and reflective thinking: New insights into student learning. Journal of Educational Psychology, 118(2), 220–230. Hassan, B., Rafiq-uz-Zaman, M., & Khan, Z. A. (2025). Beyond memorization: Cultivating critical thinking skills through classic literature in secondary education for the 21st century learner. Review of Education, Administration & Law, 8(1), 115–124. https://doi.org/10.47067/real.v8i1.410 Hattie, J., & Timperley, H. (2020). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487 Hsin, W., & Cigas, J. (2021). AI and inquiry-based learning: Enhancing problem-solving and critical thinking. International Journal of Learning Technology, 16(1), 38–52. Johnson, M., et al. (2025). AI in education: Enhancing learning or enabling cheating? Journal of Educational Integrity, 17(2), 100–115. Jones, H., Rogers, R., & Pappas, E. (2023). AI-assisted learning and critical thinking: A balanced approach. Journal of Educational Technology, 32(2), 47–58. Kim, S., & Morrison, M. (2026). The oversimplification of problem-solving in generative AI: Effects on cognitive engagement. AI & Education Journal, 12(3), 189–201. Liu, X., & Martinez, A. (2025). Multistage assessments in AI-integrated classrooms: Enhancing critical thinking. Journal of Educational Research & Development, 52(1), 23–45. Malik, N., Bano, S., & Rafiq-uz-Zaman, M. (2025). Navigating the future of learning: A review of teacher professional development and implementation challenges in K–12 STEAM education (2015–2025). Physical Education, Health and Social Sciences, 3(3), 615–628. https://doi.org/10.63163/jpehss.v3i3.681 Martins, G., Patel, R., & Ramachandran, R. (2025). Designing AI assessments for critical thinking: Challenges and opportunities. Journal of Learning & Technology, 10(2), 77–91. Mohiuddin, D. (2026). Adaptive Marketing Systems and Consumer Feedback Loops: Implications for Market Development in Emerging Economies. Journal of Business Insight and Innovation, 5(1), 37–48. Mohiuddin, D. (2025). HR Tech Adoption in Digital Banking: Implications for Workforce Development and Financial Sector Growth in Emerging Economies. Journal of Business Insight and Innovation, 4(2), 77–90. O’Neil, C. (2020). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group. Park, Y., et al. (2024). Cognitive offloading in the age of artificial intelligence: Implications for learning. Educational Psychologist, 60(1), 19–35. Patel, R., & Singh, K. (2025). Designing AI systems to foster metacognitive awareness in students. Journal of Educational Technology Research, 15(4), 78–91. Pillai, R., et al. (2024). Long-term effects of AI interaction on cognitive growth: A longitudinal study. British Journal of Educational Psychology, 56(3), 146–158. Rafiq-uz-Zaman, M. (2023). The impact of digital literacy on students’ learning outcomes: A comprehensive review. Inverge Journal of Social Sciences, 2(2), 194–205. https://doi.org/10.63544/ijss.v2i2.210 Rafiq-uz-Zaman, M. (2025a). Between adoption and ambiguity: Navigating the AI policy vacuum in Pakistani higher education. Research Journal for Social Affairs, 3(6), 877–885. https://doi.org/10.71317/RJSA.003.06.0523 Rafiq-uz-Zaman, M. (2025b). Beyond STEM: A narrative review of STEAM education’s impact on creativity and innovation (2020–2025). Inverge Journal of Social Sciences, 4(4), 1–16. https://doi.org/10.63544/ijss.v4i4.175 Rafiq-uz-Zaman, M. (2025c). Use of artificial intelligence in school management: A contemporary need of school education system in Punjab (Pakistan). Journal of Asian Development Studies, 14(2), 1984–2009. https://doi.org/10.62345/jads.2025.14.2.56 Rafiq-uz-Zaman, M. (2026). AI-driven competency-based education: Shaping lifelong learning and skill acquisition in dynamic educational environments. Artificial Intelligence in Lifelong and Life-Course Education, 1(1), 61–77. https://doi.org/10.66053/aillce.v1i1.29 Rafiq-uz-Zaman, M., Malik, N., & Bano, S. (2025). Effectiveness of STEAM education in enhancing 21st century skills: A systematic review. Journal of Asian Development Studies, 14(3), 590–598. https://doi.org/10.62345/jads.2025.14.3.49 Rafiq-uz-Zaman, M., Shih, Y.-H., & Akomodi, J. O. (2026a). Integrating emotional intelligence and AI-driven learning in higher education: Implications for student well-being and university HR policies. The Study of Religion and History, 4(1), 1–24. https://doi.org/10.63163/srh300 Rafiq-uz-Zaman, M., Shih, Y.-H., & Muthmainnah. (2026b). Effectiveness of online and blended learning on students’ academic achievement in Pakistan: A systematic review and meta-analysis. ProScholar Insights, 5(1), 116–125. https://doi.org/10.55737/psi.2026a-51164 Rao, S., & Stein, D. (2026). Embedding metacognitive scaffolds in AI learning systems: Enhancing critical thinking. Journal of Educational Technology Research, 12(4), 34–47. Selwyn, N. (2020). AI and education: The implications of artificial intelligence for education policy and practice. Routledge. Shute, V. J., & Hansen, E. (2021). Adaptive learning: A review of AI-supported learning systems. Educational Psychologist, 46(3), 148–160. Singh, A., & Zhao, D. (2026). Metacognitive design in AI tools: Impact on student cognitive development. Educational Technology & Society, 29(2), 78–91. Sweller, J., Ayres, P., & Kalyuga, S. (2021). Cognitive load theory: Implications for learning and instruction. Springer. Torrance, H., et al. (2025). Long-term effects of AI on critical thinking: A longitudinal study in higher education. British Educational Research Journal, 51(2), 153–169. Woolf, B. P. (2020). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann. Zhang, Y., & Wang, H. (2023). Impact of AI tools on cognitive engagement and critical thinking in education. Journal of Cognitive Enhancement, 7(4), 222–235. https://doi.org/10.1007/s41465-023-00277-7
Copyright (c) 2026 Muhammad Faisal Ishaque, Amana Ishaaq, Maleeha Nazim https://creativecommons.org/licenses/by-nc-sa/4.0
AI-Driven Film Production: A Study of Innovation and Industry Transformation
Technological advancement has continually transformed the film industry, and artificial intelligence (AI) has become one of the major forces of innovation. AI technologies are actively being integrated into different stages of film production, shaping the creative process, efficiency of the operations, and decision-making. The purpose of this study is to explore the application of AI in the film production process, focusing on its awareness, usage, perceived influence, challenges, and prospects in the film production industry. The research design was a quantitative study design with the use of a structured questionnaire that was given to 300 respondents consisting of film professionals, media experts, students, and researchers. The analysis of data was conducted through statistical methods like frequencies, percentages, mean, and standard deviation to evaluate responses. The results indicate that the awareness and moderate use of AI technologies in film production are high. One of the most highlighted fields of the use of AI is technical, video editing, and visual effects, which greatly enhance productivity and change the way things are done. Although AI, too, is seen to decrease the expenses and improve creativity, it is still scarce in the creative fields of operation. Some of the major challenges have been identified as high implementation costs, ethical issues, and lack of expertise, and fears of job displacement. Regardless of these difficulties, participants were very optimistic about the future of AI by noting the significance of training and skill development. AI is transforming the film industry by improving efficiency and creating possibilities. Nonetheless, its successful implementation is also subject to overcoming financial, ethical, and technical issues. The key to sustainable transformation in the industry is the balanced approach that unites the abilities of AI with human creativity, as well as investing in training and policymaking. References Azevedo, R., et al. (2020). Does training on self-regulated learning help college students learn more effectively? Educational Psychology Review, 32(3), 245–260. https://doi.org/10.1007/s10648-020-09506-1 Baker, R. S., & Siemens, G. (2020). The role of artificial intelligence in improving learning outcomes. Educational Psychologist, 55(4), 181–195. https://doi.org/10.1080/00461520.2020.1796638 Bennett, R. E. (2021). The changing nature of educational assessment. Educational Assessment, 26(1), 11–23. https://doi.org/10.1080/10627197.2021.1876744 Evans, C., & Lee, S. (2026). Predictive analytics and student profiling systems: A new frontier in education equity. Journal of Educational Data Mining, 34(2), 139–157. Eynon, R., & Helsper, E. J. (2021). The digital divide and AI: Bridging gaps in access to learning technologies. Journal of Educational Technology, 41(1), 72–83. Flavell, J. H. (2021). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906 Garcia, M., Kumar, S., & Zhang, Y. (2024). The digital divide and AI: Bridging gaps in access to learning technologies. Journal of Educational Technology, 41(1), 72–83. Gonzalez, P., & Harper, R. (2025). Generative AI and reflective thinking: New insights into student learning. Journal of Educational Psychology, 118(2), 220–230. Hassan, B., Rafiq-uz-Zaman, M., & Khan, Z. A. (2025). Beyond memorization: Cultivating critical thinking skills through classic literature in secondary education for the 21st century learner. Review of Education, Administration & Law, 8(1), 115–124. https://doi.org/10.47067/real.v8i1.410 Hattie, J., & Timperley, H. (2020). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487 Hsin, W., & Cigas, J. (2021). AI and inquiry-based learning: Enhancing problem-solving and critical thinking. International Journal of Learning Technology, 16(1), 38–52. Johnson, M., et al. (2025). AI in education: Enhancing learning or enabling cheating? Journal of Educational Integrity, 17(2), 100–115. Jones, H., Rogers, R., & Pappas, E. (2023). AI-assisted learning and critical thinking: A balanced approach. Journal of Educational Technology, 32(2), 47–58. Kim, S., & Morrison, M. (2026). The oversimplification of problem-solving in generative AI: Effects on cognitive engagement. AI & Education Journal, 12(3), 189–201. Liu, X., & Martinez, A. (2025). Multistage assessments in AI-integrated classrooms: Enhancing critical thinking. Journal of Educational Research & Development, 52(1), 23–45. Malik, N., Bano, S., & Rafiq-uz-Zaman, M. (2025). Navigating the future of learning: A review of teacher professional development and implementation challenges in K–12 STEAM education (2015–2025). Physical Education, Health and Social Sciences, 3(3), 615–628. https://doi.org/10.63163/jpehss.v3i3.681 Martins, G., Patel, R., & Ramachandran, R. (2025). Designing AI assessments for critical thinking: Challenges and opportunities. Journal of Learning & Technology, 10(2), 77–91. Mohiuddin, D. (2026). Adaptive Marketing Systems and Consumer Feedback Loops: Implications for Market Development in Emerging Economies. Journal of Business Insight and Innovation, 5(1), 37–48. Mohiuddin, D. (2025). HR Tech Adoption in Digital Banking: Implications for Workforce Development and Financial Sector Growth in Emerging Economies. Journal of Business Insight and Innovation, 4(2), 77–90. O’Neil, C. (2020). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group. Park, Y., et al. (2024). Cognitive offloading in the age of artificial intelligence: Implications for learning. Educational Psychologist, 60(1), 19–35. Patel, R., & Singh, K. (2025). Designing AI systems to foster metacognitive awareness in students. Journal of Educational Technology Research, 15(4), 78–91. Pillai, R., et al. (2024). Long-term effects of AI interaction on cognitive growth: A longitudinal study. British Journal of Educational Psychology, 56(3), 146–158. Rafiq-uz-Zaman, M. (2023). The impact of digital literacy on students’ learning outcomes: A comprehensive review. Inverge Journal of Social Sciences, 2(2), 194–205. https://doi.org/10.63544/ijss.v2i2.210 Rafiq-uz-Zaman, M. (2025a). Between adoption and ambiguity: Navigating the AI policy vacuum in Pakistani higher education. Research Journal for Social Affairs, 3(6), 877–885. https://doi.org/10.71317/RJSA.003.06.0523 Rafiq-uz-Zaman, M. (2025b). Beyond STEM: A narrative review of STEAM education’s impact on creativity and innovation (2020–2025). Inverge Journal of Social Sciences, 4(4), 1–16. https://doi.org/10.63544/ijss.v4i4.175 Rafiq-uz-Zaman, M. (2025c). Use of artificial intelligence in school management: A contemporary need of school education system in Punjab (Pakistan). Journal of Asian Development Studies, 14(2), 1984–2009. https://doi.org/10.62345/jads.2025.14.2.56 Rafiq-uz-Zaman, M. (2026). AI-driven competency-based education: Shaping lifelong learning and skill acquisition in dynamic educational environments. Artificial Intelligence in Lifelong and Life-Course Education, 1(1), 61–77. https://doi.org/10.66053/aillce.v1i1.29 Rafiq-uz-Zaman, M., Malik, N., & Bano, S. (2025). Effectiveness of STEAM education in enhancing 21st century skills: A systematic review. Journal of Asian Development Studies, 14(3), 590–598. https://doi.org/10.62345/jads.2025.14.3.49 Rafiq-uz-Zaman, M., Shih, Y.-H., & Akomodi, J. O. (2026a). Integrating emotional intelligence and AI-driven learning in higher education: Implications for student well-being and university HR policies. The Study of Religion and History, 4(1), 1–24. https://doi.org/10.63163/srh300 Rafiq-uz-Zaman, M., Shih, Y.-H., & Muthmainnah. (2026b). Effectiveness of online and blended learning on students’ academic achievement in Pakistan: A systematic review and meta-analysis. ProScholar Insights, 5(1), 116–125. https://doi.org/10.55737/psi.2026a-51164 Rao, S., & Stein, D. (2026). Embedding metacognitive scaffolds in AI learning systems: Enhancing critical thinking. Journal of Educational Technology Research, 12(4), 34–47. Selwyn, N. (2020). AI and education: The implications of artificial intelligence for education policy and practice. Routledge. Shute, V. J., & Hansen, E. (2021). Adaptive learning: A review of AI-supported learning systems. Educational Psychologist, 46(3), 148–160. Singh, A., & Zhao, D. (2026). Metacognitive design in AI tools: Impact on student cognitive development. Educational Technology & Society, 29(2), 78–91. Sweller, J., Ayres, P., & Kalyuga, S. (2021). Cognitive load theory: Implications for learning and instruction. Springer. Torrance, H., et al. (2025). Long-term effects of AI on critical thinking: A longitudinal study in higher education. British Educational Research Journal, 51(2), 153–169. Woolf, B. P. (2020). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann. Zhang, Y., & Wang, H. (2023). Impact of AI tools on cognitive engagement and critical thinking in education. Journal of Cognitive Enhancement, 7(4), 222–235. https://doi.org/10.1007/s41465-023-00277-7
Copyright (c) 2026 Zikriya Habib, Khola Malik, Hamayoun Masood Qureshi https://creativecommons.org/licenses/by-nc-sa/4.0
Becoming a Ph.D. Scholar: A Study of Doctoral Students’ Experiences and Challenges
Doctorate is a highly esteemed academic degree. PhD education is crucial in today's knowledge driven economy because it help to create new knowledge and skills for the benefit of the economy and for the intellectual society as a whole. Although obtaining a doctorate is a challenging path. The demands are high and the journey can be challenging both mentally and physically. PhD students frequently encounter number of challenges and unexpected barriers and difficulties in the developing nation like Pakistan during their PhD studies, which make it difficult for students to finish their PhD programs on time. Therefore, the current study sought to investigate how scholars perceived their PhD studies and also brought attention to the difficulties that the scholars encountered when working on their coursework and research. Data collected from PhD students of public and private universities of Karachi by using qualitative research method approach. Data was collected through semi-structured interviews. Prominent themes are emerged through the application of thematic analysis that includes 1) PhD as a pathway to social and financial Status, 2) Academic experiences includes a) Supervision experiences b) Challenges in research process c) Learning Avenues d) Key Challenges in Publication e) Coursework experiences and requirements 3) Personal adversities includes a) Programme Cost: Highly expensive programme b) Health associated Issues c) Balancing job expectations and academic demands. The research results indicate issues students faced at PhD program that need to be resolved so they can concentrate on their studies instead of dealing with these inconveniences. References Abid, S., & Khan, M. (2017). Career decision making process in adolescence: Theoretical perspective. IOSR Journal of Humanities and Social Science, 22(6), 45–46. https://doi.org/10.9790/0837-2206104546 Akbulut, H., Şahin, C., & Çepni, S. (2013). Determination of faced problems in doctorate thesis process: Education faculty sample. Dicle Üniversitesi Ziya Gökalp Eğitim Fakültesi Dergisi, 20, 50–69. Ali, S., & Ahmed, M. (2023). Doctoral education in South Asia: A systematic review. Higher Education Quarterly, 77(2), 245–268. Bernstein, B. L., Evans, B., Fyffe, J., Halai, N., & Hall, F. L. (2014). The continuing evolution of the research doctorate. In M. Nerad & B. Evans (Eds.), Globalization and its impacts on the quality of PhD education (pp. 5–30). Springer. Bhandari, N. A., MacDonald, B. L., Martin, J. M., Modena, A., Simmons, J. M., Turner, W. D., & Asselin, S. (2013). Professional seminar: Valuing a one-credit course through the lens of doctoral students. International Journal of Teaching and Learning in Higher Education, 25(3), 346–357. Brailsford, I. (2010). Motives and aspirations for doctoral study: Career, personal, and interpersonal factors in the decision to embark on a history PhD. International Journal of Doctoral Studies, 5, 15–27. https://doi.org/10.28945/710 Ekpoh, U. I. (2016). Postgraduate studies: The challenges of research and thesis writing. Journal of Education and Social Research, 6(3), 67–74. https://doi.org/10.5901/jesr.2016.v6n3p67 Fraenkel, J. R., & Wallen, N. E. (2006). How to design and evaluate research in education (6th ed.). McGraw-Hill. Franke, A., & Arvidsson, B. (2011). Research supervisors’ different ways of experiencing supervision of doctoral students. Studies in Higher Education, 36(1), 7–19. https://doi.org/10.1080/03075070903402151 Gardner, S. K. (2009). The development of doctoral students: Phases of challenges and support. Journal of Higher Education, 34, 1–14. Golde, C. M., & Dore, T. M. (2001). At cross purposes: What the experiences of doctoral students reveal about doctoral education. Pew Charitable Trusts. Gunnarsson, R., Jonasson, G., & Billhult, A. (2013). The experience of disagreement between students and supervisors in PhD education: A qualitative study. BMC Medical Education, 13, 134. https://doi.org/10.1186/1472-6920-13-134 Haag, P., Shankland, R., Osin, E., Boujut, E., Cazalis, F., Bruno, A. S., Vrignaud, P., & Gay, M. C. (2018). Perceived stress and physical health among French university PhD students. Pratiques Psychologiques, 24(1), 1–20. https://doi.org/10.1016/j.prps.2017.04.005 Hussain, R., & Khan, N. (2022). Mental health among PhD scholars in Pakistan: A neglected crisis. Asian Journal of Psychiatry, 72, 103–112. Iqbal, M. Z., Saeed, M., & Abbas, F. (2012). Problems in public sector universities of Punjab: Views of PhD scholars. International Researcher, 1(3), 1–13. Jackson, D., & Bridgstock, R. (2021). What actually works to enhance graduate employability? The relative value of curricular, co-curricular, and extra-curricular learning and paid work. Higher Education, 81, 723–739. https://doi.org/10.1007/s10734-020-00570-x Knight, J., & de Wit, H. (1997). Internationalization of higher education in Asia Pacific countries. European Association for International Education. Kuiper, N. A., Olinger, L. J., & Lyons, L. M. (1986). Global perceived stress level as a moderator of the relationship between negative life events and depression. Journal of Human Stress, 12(4), 149–153. https://doi.org/10.1080/0097840X.1986.9936781 Lei, S. A. (2008). Factors changing attitudes of graduate school students toward an introductory research methodology course. Education, 128(4), 667–685. Li, Y. (2016). “Publish SCI papers or no degree”: Practices of Chinese doctoral supervisors in response to publication pressure. Asia Pacific Journal of Education, 36(4), 545–558. https://doi.org/10.1080/02188791.2015.1005050 Pachler, N., & Daly, C. (2009). Narrative and learning with Web 2.0 technologies: Towards a research agenda. Journal of Computer Assisted Learning, 25, 6–18. https://doi.org/10.1111/j.1365-2729.2008.00303.x Parry, S. (2007). Disciplines and doctorates. Springer. https://doi.org/10.1007/1-4020-5312-6 Pascoe, M. C., Hetrick, S. E., & Parker, A. G. (2020). The impact of stress on students in secondary school and higher education. International Journal of Adolescence and Youth, 25(1), 104–112. https://doi.org/10.1080/02673843.2019.1596823 Raza, A., & Mahmood, K. (2024). Publication pressures and coping strategies among Pakistani doctoral students. Journal of Scholarly Publishing, 55(1), 34–56. Rubin, H. J., & Rubin, I. S. (2005). Qualitative interviewing: The art of hearing data (2nd ed.). Sage. Sala-Bubare, A., Peltonen, J., Pyhältö, K., & Castelló, M. (2018). Doctoral candidates’ research writing perceptions: A cross-national study. International Journal of Doctoral Studies, 13, 327–345. https://doi.org/10.28945/4103 Shams, A. J., Sanfratello, A., & Iqbal, Z. M. (2020). PhD scholars’ problems: A system comparison of the US and Pakistan. Journal of Research and Reflections in Education, 14(1), 123–135. Shankar, N. L., & Park, C. L. (2016). Effects of stress on students’ physical and mental health and academic success. International Journal of School & Educational Psychology, 4(1), 5–9. https://doi.org/10.1080/21683603.2016.1130532 Schonfeld, P., Brailovskaia, J., Bieda, A., Zhang, X. C., & Margraf, J. (2016). The effects of daily stress on positive and negative mental health: Mediation through self-efficacy. International Journal of Clinical and Health Psychology, 16(1), 1–10. https://doi.org/10.1016/j.ijchp.2015.08.005 Teowkul, K., Seributra, N. J., Sangkaworn, C., Jivasantikarn, C., Denvilai, S., & Mujtaba, B. G. (2009). Motivational factors of graduate students pursuing master’s and doctoral degrees in business. RU International Journal, 3(1), 25–56. Thomas, S. J. (2015). Exploring strategies for retaining information technology professionals: A case study (Doctoral dissertation). ProQuest Dissertations and Theses Global. https://scholarworks.waldenu.edu/dissertations/219/ Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods. Cengage Learning.
Copyright (c) 2026 Ruby Naureen, Razia Fakir Mohammad https://creativecommons.org/licenses/by-nc-sa/4.0
Environmental Wellbeing at Work: The Evolving Role of Human Resource Management in Sustainable Workspaces and Employee Mental Health
This study examined environmental wellbeing at work and its influence on employee mental health through sustainable human resource management (HRM) practices. The research adopted a quantitative design to analyse the relationships among green HRM practices, environmental wellbeing, workplace sustainability, and employee mental health. Data was collected from a sample of 300 employees working in public and private sector organizations. Statistical analysis included descriptive statistics, correlation, and regression techniques to evaluate the proposed relationships. The findings indicated strong positive perceptions of green HRM (Mean = 3.92, SD = 0.71), environmental wellbeing (Mean = 3.88, SD = 0.69), and employee mental health (Mean = 3.90, SD = 0.68). Correlation analysis revealed significant relationships between green HRM and mental health (r = 0.70), and between environmental wellbeing and job satisfaction (r = 0.76). Regression results showed that green HRM (β = 0.59, p < 0.001), environmental wellbeing (β = 0.56, p < 0.001), and workplace sustainability (β = 0.51, p < 0.001) significantly predicted employee mental health, explaining 66% of the variance (R² = 0.66). Mediation analysis confirmed that environmental wellbeing partially mediated the relationship between green HRM and mental health (indirect effect = 0.37, p < 0.001). The study concluded that sustainable HRM practices and environmentally supportive workplaces significantly enhanced employee psychological wellbeing and organizational outcomes. The findings highlighted the importance of integrating environmental sustainability into HR strategies to promote healthier and more productive work environments. References Ababneh, O. M. A. (2021). Green HRM and employee green behaviors. Journal of Environmental Planning and Management, 64(7), 1204–1226. https://doi.org/10.1080/09640568.2020.1814708 Ahmed, S., Shah, S. Z. A., & Ali, M. (2022). Environmental management practices and employee wellbeing. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2022.130456 Asif, M., & Rafiq-uz-Zaman, M. (2026). The silent disengagement: A quantitative analysis of leadership, recognition, and workload as predictors of quiet quitting among knowledge workers. Al-Aasar, 3(1), 271–303. https://doi.org/10.63878/aaj1525 Bai, B. (2025). Exploring sustainable HRM through the lens of employee wellbeing. Sustainability, 17(12), 5646. https://doi.org/10.3390/su17125646 Bano, S., Rafiq-uz-Zaman, M., & Khalid, N. (2024). Assessing Health and Environmental Risks: Educational Awareness on Plastic Usage and Solid Waste Disposal in Bahawalpur. (2024). Journal of Asian Development Studies, 13(3), 917-929. https://doi.org/10.62345/jads.2024.13.3.75 Bhoir, M., & Sinha, V. (2024). Employee well-being HR practices: A systematic literature review. Future Business Journal, 10(95). https://doi.org/10.1186/s43093-024-00382-w Bukhari, S. T. N., Muhammad, R. G., Latif, A., Shah, H., & Rafiq-uz-Zaman, M. (2025). An integrated model of emotional intelligence, stress coping, and teacher well-being. Social Science Review Archives, 3 (4), 119–132. https://doi.org/10.70670/sra.v3i4.1101 Chen, Y., Zhang, M., & Li, J. (2024). Job satisfaction and organizational commitment relationship. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2024.1123456 Dumont, J., Shen, J., & Deng, X. (2022). Green HRM and employee pro-environmental behavior. Human Resource Management. https://doi.org/10.1002/hrm.22135 Faisal, S. (2023). Green human resource management—A synthesis. Sustainability, 15(3), 2259. https://doi.org/10.3390/su15032259 Fatima, N., Rafiq-uz-Zaman, M., Arshad, I., Rasheed, I., & Fatima, A. (2025). The role of human resource management in teacher training for inclusive education: A phenomenological study. Indus Journal of Social Sciences, 3(3), 551–564. https://doi.org/10.59075/ijss.v3i3.1921 Gyensare, M. A., Adomako, S., & Amankwah-Amoah, J. (2021). Green HRM practices and employee wellbeing. Business Strategy and the Environment. https://doi.org/10.1002/bse.3642 Gyensare, M. A., Adomako, S., & Amankwah-Amoah, J. (2021). Green HRM and employee wellbeing. Business Strategy and the Environment. https://doi.org/10.1002/bse.3642 Hameed, R., Rehman, N., & Akhtar, N. (2025). Green HRM and CSR via psychological climate. Journal of Business Research, 82(3), 769–783. https://doi.org/10.1177/10519815251348354 Hassan, S., Nawaz, M. S., & Abbas, Q. (2023). Employee wellbeing and organizational loyalty. Management Decision. https://doi.org/10.1108/MD-04-2023-0456 Jabbour, C. J. C., Santos, F. C. A., & Nagano, M. S. (2022). Green HRM and organizational sustainability. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2022.131234 Khalid, N., Rafiq-uz-Zaman, M., Tahira, W., & Maqbool, M. (2024). Solid Waste and Environmental Sustainability: Educational Approaches to Managing Urban Waste in Bahawalpur City. Journal of Climate and Community Development, 3(2), 155-170. https://doi.org/10.5281/zenodo.16875300 Khan, K., Gogia, E. H., & Shao, Z. (2025). Green HRM and employee mental wellbeing. BMC Psychology, 13, 96. https://doi.org/10.1186/s40359-025-02417-5 Kim, Y., & Kim, W. (2024). Green HRM and employee wellbeing in sustainable organizations. Sustainability. https://doi.org/10.3390/su16010045 Li, X., Zhang, Y., & Chen, H. (2024). Sustainable HRM and organizational outcomes. Human Resource Management Review. https://doi.org/10.1016/j.hrmr.2024.100987 Nguyen, T., Pham, L., & Bui, H. (2023). Eco-friendly workplaces and employee wellbeing. Sustainability. https://doi.org/10.3390/su15084321 Park, J., & Ha, S. (2023). Green HRM practices and employee engagement. Business Strategy and the Environment. https://doi.org/10.1002/bse.3120 Rafiq-uz-Zaman, M. (2023). Teacher Professional Development & Well-being in the Era of Hybrid and Remote Instruction: Challenges, Opportunities, and Pathways Forward. Inverge Journal of Social Sciences, 2(4), 76–88. https://doi.org/10.63544/ijss.v2i4.211 Rafiq-uz-Zaman, M., Faridi, M. Z., & Hussain, R. M. (2025). Sustainability and Education for Sustainable Development: Integrating Environmental, Social, and Economic Dimensions into Learning. Journal of Applied Linguistics and TESOL (JALT), 8(4), 386-401. https://doi.org/10.63878/jalt1480 Rafiq-uz-Zaman, M., Khalid, N., & Shafi, S. (2024a). Historical Analysis of Environmental Degradation in Pakistan: A Narrative Review. Global Political Review, IX(IV), 24-35. https://doi.org/10.31703/gpr.2024(IX-IV).03 Rafiq-uz-Zaman, M., Khalid, N., Faridi, M. Z., & Khan, Z. A. (2024b). Smog Mitigation and Climate Resilience in Pakistan: A Policy-Centric Review of Strategies and Challenges. Social Sciences Spectrum, 3(4), 302-317. https://doi.org/10.71085/sss.03.04.175 Rafiq-uz-Zaman, M., Shih, Y.-H., & Akomodi, J. O. (2026). Integrating emotional intelligence and AI-driven learning in higher education: Implications for student well-being and university HR policies. The Study of Religion and History, 4(1), 1–24. https://doi.org/10.63163/srh300 Ren, S., Tang, G., & Jackson, S. E. (2023). Green human resource management research: A review and future agenda. Journal of Management Studies. https://doi.org/10.1111/joms.12833 Shafaei, A., Nejati, M., & Yusoff, Y. (2022). Green HRM and psychological wellbeing. International Journal of Manpower. https://doi.org/10.1108/IJM-03-2022-0123 Singh, S., Verma, V. K., & Rai, P. (2025). Impact of green HRM on employee wellbeing. International Journal of Research & Technology, 14(S1), 1022. https://doi.org/10.64882/ijrt.v14.iS1.1022 Singh, S., Verma, V. K., & Rai, P. (2026). Green HRM and employee mental health. International Journal of Research & Technology, 14(S1), 1022. https://doi.org/10.64882/ijrt.v14.iS1.1022 Tang, G., Chen, Y., & Jiang, Y. (2024). Workplace environment and mental health outcomes. Occupational Health Science. https://doi.org/10.1007/s41542-024-00123-9 Vinson, D. W., Arcan, M., & Delahunty, F. (2024). Sustainable workplace mental health systems. arXiv. https://doi.org/10.48550/arXiv.2402.01592 Wang, Y., Lee, H., & Lin, C. (2023). Environmental sustainability and employee job satisfaction. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2023.113456 Yusliza, M. Y., et al. (2023). Green HRM and employee performance outcomes. Journal of Environmental Management. https://doi.org/10.1016/j.jenvman.2023.117890 Zafar, H., & Suseno, Y. (2024). Green HRM practices and psychological climate in employee behavior. Organization & Environment, 37(4), 581–609. https://doi.org/10.1177/10860266241241532 Zhao, H., Zhou, Q., & Liu, J. (2023). Green workplace climate and employee psychological health. International Journal of Environmental Research and Public Health. https://doi.org/10.3390/ijerph20031890
Copyright (c) 2026 Feng Yiwen, Muhammad Asim Faheem, Muhammad Irfan Syed https://creativecommons.org/licenses/by-nc-sa/4.0
From Classroom to Startup: The Role of Personality Traits, Entrepreneurship Education, and Financial Access in Shaping Entrepreneurial Behaviour among Pakistani Youth
Entrepreneurial behaviour among youth plays a crucial role in economic development, innovation, and employment creation in developing economies such as Pakistan. This study examined the impact of personality traits, entrepreneurship education, and financial access on entrepreneurial behaviour among Pakistani youth. A quantitative research design was applied, and data were collected from a sample of 350 university students from public and private institutions. Standardized questionnaires were used to measure personality traits, exposure to entrepreneurship education, perceived financial access, and entrepreneurial behaviour. Statistical techniques including correlation and regression analysis were applied to evaluate relationships among variables. The results indicated that personality traits significantly influenced entrepreneurial behaviour (β = 0.31), entrepreneurship education showed the strongest positive effect (β = 0.39), and financial access also contributed significantly (β = 0.28). The model explained 68% of the variance in entrepreneurial behaviour (R² = 0.68), confirming strong predictive power. The findings highlighted that entrepreneurship development depends on both psychological and structural factors, where education plays a central role in shaping entrepreneurial readiness. The study concluded that strengthening entrepreneurship education, improving financial inclusion, and supporting personality development can significantly enhance youth entrepreneurial outcomes in Pakistan. These findings provide important implications for policymakers, educators, and financial institutions aiming to promote startup culture among students. References Amofah, K., & Saladrigues, R. (2022). Entrepreneurship education and entrepreneurial intention. Journal of Innovation and Entrepreneurship, 11(36). https://doi.org/10.1186/s13731-022-00197-5 Anjum, T., Zaheer, M. A., Díaz Tautiva, J. A., & Heidler, P. (2024). Entrepreneurship education and entrepreneurial intentions. Education Sciences, 14(9), 983. https://doi.org/10.3390/educsci14090983 Ashraf, M. A., Qureshi, I. M., Rahim, M. Z., & Hanif, M. (2024). Entrepreneurial mindset and alertness in Pakistani youth. Sustainability, 16(21), 9345. https://doi.org/10.3390/su16219345 Asif, M., & Rafiq-uz-Zaman, M. (2026). The silent disengagement: A quantitative analysis of leadership, recognition, and workload as predictors of quiet quitting among knowledge workers. Al-Aasar, 3(1), 271–303. https://doi.org/10.63878/aaj1525 Audretsch, D. B., Belitski, M., & Caiazza, R. (2022). Entrepreneurial ecosystems and regional development. Small Business Economics, 58(2), 713–730. https://doi.org/10.1007/s11187-020-00363-4 Bartik, A. W., Cullen, Z., Glaeser, E. L., Luca, M., & Stanton, C. (2022). The impact of COVID-19 on small business outcomes. Journal of Economic Perspectives, 36(3), 41–62. https://doi.org/10.1257/jep.36.3.41 Bosma, N., Content, J., Sanders, M., & Stam, E. (2023). Institutions, entrepreneurship, and economic growth. Small Business Economics, 61(1), 1–20. https://doi.org/10.1007/s11187-022-00609-0 Brown, R., Rocha, A., & Cowling, M. (2023). Financing entrepreneurship in emerging economies. Journal of Business Venturing, 38(2), 106–128. https://doi.org/10.1016/j.jbusvent.2022.106128 Bukhari, S. T. N., Muhammad, R. G., Latif, A., Shah, H., & Rafiq-uz-Zaman, M. (2025). An integrated model of emotional intelligence, stress coping, and teacher well-being. Social Science Review Archives, 3(4), 119–132. https://doi.org/10.70670/sra.v3i4.1101 Cao, Y., Asad, M. M., Wang, L., Naz, A., & Almusharraf, N. (2022). Role of personality traits in entrepreneurial intentions of young entrepreneurs. Frontiers in Psychology, 13, 1010412. https://doi.org/10.3389/fpsyg.2022.1010412 Cumming, D., Meoli, M., & Vismara, S. (2023). Investors and entrepreneurial finance. Journal of Corporate Finance, 79, 102–118. https://doi.org/10.1016/j.jcorpfin.2023.102118 Fayolle, A., & Gailly, B. (2023). The impact of entrepreneurship education on entrepreneurial attitudes. Journal of Small Business Management, 61(1), 1–25. https://doi.org/10.1080/00472778.2022.2060141 Hueso, C., Jaén, I., & Liñán, F. (2023). Entrepreneurial intention and perceived barriers. Journal of Business Research, 158, 113–125. https://doi.org/10.1016/j.jbusres.2023.113125 Juhari, H. S., Ismail, N., Roslan, S., & Zaremohzzabieh, Z. (2023). Personality traits and entrepreneurial intention among students. International Journal of Evaluation and Research in Education, 12(1), 9–14. https://doi.org/10.11591/ijere.v12i1.23472 Kerr, W. R., & Nanda, R. (2022). Financing innovation. Journal of Economic Literature, 60(3), 941–976. https://doi.org/10.1257/jel.20201410 Kuratko, D. F., Hornsby, J. S., & Hayton, J. (2022). Corporate entrepreneurship and innovation. Journal of Management Studies, 59(4), 845–870. https://doi.org/10.1111/joms.12785 Leutner, F., Ahmetoglu, G., Akhtar, R., & Chamorro-Premuzic, T. (2023). The entrepreneurial personality. Journal of Personality and Social Psychology, 124(2), 321–340. https://doi.org/10.1037/pspp0000345 Martin, B. C., McNally, J. J., & Kay, M. J. (2023). Examining the formation of entrepreneurial intention. Journal of Business Venturing, 38(3), 1–22. https://doi.org/10.1016/j.jbusvent.2022.106156 Martins, J. M., Shahzad, M. F., & Xu, S. (2023). Factors influencing entrepreneurial intention among university students. Journal of Innovation and Entrepreneurship, 12(63). https://doi.org/10.1186/s13731-023-00333-9 McCarthy, P. X., Gong, X., Stephany, F., Braesemann, F., Rizoiu, M. A., & Kern, M. L. (2023). The science of startup personalities. arXiv preprint. https://doi.org/10.48550/arXiv.2302.07968 Mehmood, A., Pervez, M. S., Mughal, A., & Shahzad, F. (2024). Entrepreneurship education and self-efficacy. Journal of Social & Organizational Matters, 3(4), 290–306. https://doi.org/10.56976/jsom.v3i4.135 Morris, M. H., Webb, J. W., & Franklin, R. J. (2023). Entrepreneurship education effectiveness. Entrepreneurship Theory and Practice, 47(5), 1201–1225. https://doi.org/10.1177/10422587231100123 Nabi, G., Liñán, F., Fayolle, A., & Krueger, N. (2022). The impact of entrepreneurship education. Entrepreneurship Theory and Practice, 46(3), 509–543. https://doi.org/10.1177/10422587211044090 Nguyen, C., Pham, H., & Mai, N. (2024). Financial access and entrepreneurial behavior. Journal of Global Entrepreneurship Research, 14(1). https://doi.org/10.1007/s40497-024-00495-8 Obschonka, M., Fisch, C., & Audretsch, D. B. (2023). Personality and entrepreneurship. Journal of Business Venturing Insights, 19, e00360. https://doi.org/10.1016/j.jbvi.2023.e00360 Rafiq-uz-Zaman, M. (2022a). Redesign for 21st-century skills: Preparing learners for a rapidly changing workforce. Journal of Business Insight and Innovation, 1(2), 89–102. https://insightfuljournals.com/index.php/JBII/article/view/58 Rafiq-uz-Zaman, M. (2022b). Strategic upskilling: Fusing technical expertise with human capabilities. Journal of Business Insight and Innovation, 1(1), 76–86. https://doi.org/10.5281/zenodo.17766381 Rafiq-uz-Zaman, M. (2024). Leveraging skill development and STEAM innovation for business growth. Journal of Business Insight and Innovation, 3(1), 48–63. https://insightfuljournals.com/index.php/JBII/article/view/55 Rafiq-uz-Zaman, M. (2025a). Beyond STEM: A narrative review of STEAM education’s impact on creativity and innovation (2020–2025). Inverge Journal of Social Sciences, 4(4), 1–16. https://doi.org/10.63544/ijss.v4i4.175 Rafiq-uz-Zaman, M. (2025b). Bridging the skills divide: A comparative study of skill-based education across SAARC countries. Social Science Review Archives, 3(3), 787–795. https://doi.org/10.70670/sra.v3i3.913 Rafiq-uz-Zaman, M. (2025c). From chalkboards to competence: Rethinking skill-based education in Pakistan. International Journal of Academic Research for Humanities, 5(3), 1–13. https://doi.org/10.5281/zenodo.17112058 Rafiq-uz-Zaman, M. (2025d). The Integrated Skill-Based Education Framework (ISEF). Global Social Sciences Review, X(III), 157–167. https://doi.org/10.31703/gssr.2025(X-III).14 Rafiq-uz-Zaman, M., & Asif Nadeem, D. M. (2025). Critical success factors for skill-based education programs. Inverge Journal of Social Sciences, 4(3), 11–19. https://doi.org/10.63544/ijss.v4i3.139 Rafiq-uz-Zaman, M., & Nadeem, M. A. (2024). Comparative analysis of skill-based education curriculum in Pakistan and India. International Journal of Academic Research for Humanities, 4(3), 188–197. https://doi.org/10.5281/zenodo.13646448 Rafiq-uz-Zaman, M., & Nadeem, M. A. (2025b). Gauging the gap: Student perceptions of skill proficiency. Academia International Journal for Social Sciences, 4(2), 2307–2317. https://doi.org/10.63056/ACAD.004.03.0553 Rauch, A., & Hulsink, W. (2023). Entrepreneurial behavior and personality. Small Business Economics, 60(4), 1–18. https://doi.org/10.1007/s11187-022-00601-8 Salameh, A. A., Akhtar, H., Gul, R., & Omar, A. B. (2022). Personality traits and entrepreneurial intentions among youth. Frontiers in Psychology, 13, 927718. https://doi.org/10.3389/fpsyg.2022.927718 Sarwar, F., Sami, A., & Nauman, B. (2023). Personality and entrepreneurial intentions in Pakistan. Journal of Entrepreneurship and Business Venturing, 3(1). https://doi.org/10.56536/jebv.v3i1.45
Copyright (c) 2026 Wajahat Ali, Aisha Jahangir, Muhammad Zakir https://creativecommons.org/licenses/by-nc-sa/4.0
Hybrid Warfare, State Responsibility, and Interstate Conflict in South Asia: Evidence from India–Pakistan Relations
The contemporary security environment in South Asia is increasingly shaped by non-conventional forms of conflict, including hybrid warfare, proxy engagement, and information operations. While existing scholarship on terrorism and regional instability has predominantly focused on non-state actors, comparatively limited attention has been paid to the role of states as indirect sponsors of violence and destabilisation. This article examines the dynamics of state sponsorship and hybrid warfare in South Asia through the lens of India–Pakistan relations, with particular reference to the contested region of Jammu and Kashmir and Pakistan’s internal security challenges. Drawing on a qualitative research design, the study employs document analysis, policy review, and triangulated secondary sources, including international reports, legal documents, and media investigations, to analyse patterns of alleged proxy conflict, information warfare, and coercive state practices. The article situates these dynamics within realist and state-sponsorship frameworks to assess how indirect strategies are employed to pursue strategic objectives while maintaining plausible deniability. Rather than treating official claims as established facts, the study analyses competing narratives, evidentiary patterns, and international responses to evaluate their implications for regional stability and international norms. The findings suggest that hybrid warfare has become a central feature of interstate rivalry in South Asia, complicating conflict management, legal accountability, and peace-building efforts. By shifting the analytical focus from non-state militancy to state behaviour, this study contributes to broader debates on hybrid conflict, state responsibility, and security governance in nuclearised regions. References Ahmed, A. S. (2021). Information warfare and South Asian strategic competition. Journal of Contemporary International Affairs, 3(1), 45–67. Ahmed, Z. S. (2017). SAARC and the challenges of regional cooperation in South Asia. South Asian Survey, 24(1), 1–17. Akhtar, R. (2016). India’s Pakistan dilemma. South Asian Voices. https://southasianvoices.org Amnesty International. (2011). A lawless law: Detentions under the Jammu and Kashmir Public Safety Act. https://www.amnesty.org Barkawi, T. (2018). Decolonising war. European Journal of International Security, 3(2), 199–214. https://doi.org/10.xxxx/xxxx BBC News. (2019, February 26). India launches air strikes against militants in Pakistan. https://www.bbc.com/news/world-asia-47366715 Byman, D. (2005). Deadly connections: States that sponsor terrorism. Cambridge University Press. Chesterman, S. (2008). The spy who came in from the Cold War: Intelligence and international law. Michigan Journal of International Law, 27(4), 1071–1130. EU DisinfoLab. (2020). Indian chronicles: Deep dive into a 15-year operation targeting the EU and UN. https://www.disinfo.eu Fair, C. C. (2019). In their own words: Understanding Lashkar-e-Taiba. Oxford University Press. Fair, C. C. (2020). India–Pakistan conflict escalation and crisis stability. Journal of Strategic Studies, 43(6–7), 905–932. https://doi.org/10.xxxx/xxxx Ganguly, Š. (2001). The crisis in Kashmir: Portents of war, hopes of peace. Cambridge University Press. Gunning, J. (2017). Terrorism, charities, and diasporas. Critical Studies on Terrorism, 10(1), 1–20. Hoffman, B. (2007). Inside terrorism (2nd ed.). Columbia University Press. Human Rights Watch. (2006). Everyone lives in fear: Patterns of impunity in Jammu and Kashmir. https://www.hrw.org International Court of Justice. (2019). Case concerning the Vienna Convention on Consular Relations (India v. Pakistan). https://www.icj-cij.org International Law Commission. (2001). Draft articles on responsibility of states for internationally wrongful acts. United Nations. https://legal.un.org/ilc Mearsheimer, J. J. (2001). The tragedy of great power politics. W. W. Norton. Office of the United Nations High Commissioner for Human Rights. (2018). Report on the situation of human rights in Kashmir. https://www.ohchr.org Office of the United Nations High Commissioner for Human Rights. (2019). Update of the 2018 report on the situation of human rights in Kashmir. https://www.ohchr.org Rafiq-uz-Zaman, M. (2023). Bridging CPEC-driven industrial growth and skill-based education in Pakistan: A systematic review. Journal of Business Insight and Innovation, 2(1), 55–78. https://insightfuljournals.com/index.php/JBII/article/view/57 Rafiq-uz-Zaman, M. (2024). Leveraging skill development and STEAM innovation for business growth – A strategic framework for enhancing workforce performance in emerging markets platform. Journal of Business Insight and Innovation, 3(1), 48–63. https://insightfuljournals.com/index.php/JBII/article/view/55 Rafiq-uz-Zaman, M. (2025). Bridging the skills divide: A comparative study of skill-based education across SAARC countries with a policy roadmap for Pakistan. Social Science Review Archives, 3(3), 787–795. https://doi.org/10.70670/sra.v3i3.913 Salehyan, I. (2010). The delegation of war to rebel organisations. Journal of Conflict Resolution, 54(3), 493–515. Schmid, A. P. (2018). Terrorism: A crime against humanity. Oxford University Press. Snedden, C. (2013). Understanding Kashmir and Kashmiris. Oxford University Press. United Nations Security Council. (1948). Resolution 47 (1948). United Nations. https://undocs.org Waltz, K. N. (1979). Theory of international politics. Addison-Wesley. Wirsing, R. G. (2020). The Kashmir dispute: Strategic implications. Middle East Institute. Yusuf, M. (2021). Brokering peace in nuclear environments. Stanford University Press.
Copyright (c) 2026 Abida Kausar, Muhammad Iqbal https://creativecommons.org/licenses/by-nc-sa/4.0
The Role of Sustainability Efforts in Enhancing Workforce Well-Being and Organizational Success
This study explores how organizational sustainability efforts enhance workforce well-being and drive organizational success. As sustainability becomes a strategic focus, the research investigates employee perceptions of sustainability initiatives, their impact on well-being, and how well-being supports organizational achievement. A cross-sectional survey was conducted, collecting primary data from 350 employees across public, private, and non-profit sectors. Using a structured questionnaire and a five-point Likert scale, the study measured sustainability efforts, workforce well-being, organizational success, and the perceived links among these factors. Descriptive statistics and reliability analyses were applied to identify trends and ensure measurement consistency. Results reveal that employees generally view sustainability efforts favorably, particularly regarding ethical practices, leadership commitment, and strategic alignment. These programs positively affect workforce well-being, boosting morale, motivation, pride, and workplace culture. The findings show a strong connection between workforce well-being and organizational success, underscoring the importance of well-being in translating sustainability initiatives into improved performance, stakeholder trust, and long-term success. Respondents also recognized a high degree of interrelatedness among sustainability, employee experience, and organizational outcomes. The analysis highlights the value of a people-centered sustainability approach, integrating environmental and social strategies to support employee well-being. These insights offer practical guidance for leaders and HR professionals seeking to leverage sustainability for employee welfare and organizational prosperity. The study contributes empirical evidence to the literature, demonstrating that internal sustainability efforts can strategically foster sustainable organizational performance by focusing on employee perceptions and the links between sustainability, well-being, and success. References Abbas, M. T., & Hanif, F. (2025). Design and Control of an Autonomous Drone Navigation System Using Embedded AI. Journal of Engineering and Computational Intelligence Review, 3(2), 68-80. Afshar, M. (2025). Resilient livestock supply chains in Pakistan: adaptive strategies for climate-smart agriculture and food security. Frontiers in Food Science and Technology, 5, 1658625. Afshar, M. Z., & Shah, M. H. (2025). Resilience Through Adaptation: Examining the Interplay Between Adaptive Capacity and Organizational Resilience in Public Sector Organizations. ACADEMIA International Journal for Social Sciences, 4(2), 1770-1789. Ahmad A, Akhtar, M., Rashid, M. Y., Akhter, N., & Rehman, A. U. (2025). Harnessing artificial intelligence for library transformation: Trends and strategic directions. ACADEMIA International Journal for Social Sciences, 4(4), 2733–2751. Doi: https://doi.org/10.63056/ACAD.004.04.1128 Ahmed, M., Zehou, S., Raza, S. A., Qureshi, M. A., & Yousufi, S. Q. (2020). Impact of CSR and environmental triggers on employee green behavior: The mediating effect of employee well‐being. Corporate Social Responsibility and Environmental Management, 27(5), 2225-2239. Ahsan, M. J., & Khawaja, S. (2024). Sustainable leadership impact on environmental performance: exploring employee well-being, innovation, and organizational resilience. Discover Sustainability, 5(1), 317. Akter, S., Turja, T. S., Hossain, A., Eshra, S. A., & Rasul, I. (2025). AI in business analytics for financial risk assessment: Survey insights from the banking and insurance industries. International journal of business and management sciences, 5(03), 1-30. Ali, D. S., Latif, D. A., Zafar, D. Z., & Mahmood, G. F. (2024). The Parliamentary Decade Of Turmoil: Institutional Interference And Political Self-Sabotage In Pakistan (1988–1999). Contemporary Journal of Social Science Review, 2(04), 2159-2169. Amin, F., But, M. A., Amin, I., & Khan, A. (2024). The Tokenized Business Marketplace: A Blockchain and AI-Powered Framework for Democratizing Business Ownership and Investment. International Journal of Business and Management Sciences, 5(4), 318-328. Azam, B., & Mehar, S. (2025). Performance Evaluation of Battery Management Systems in Lithium-Ion Battery-Powered Electric Vehicles. Journal of Engineering and Computational Intelligence Review, 3(2), 81-95. Badhan, I. A., Hasnain, M. N., & Rahman, M. H. (2023). Advancing Operational Efficiency: An In-Depth Study Of Machine Learning Applications In Industrial Automation. Policy Research Journal, 1(2), 21-41. Bella, K. M. J. (2023). The power of employee well-being: A catalyst for organizational success. International Journal of Scientific Research in Modern Science and Technology, 2(4), 20-26. Butt, S. (2021). Impact of E-Banking Service Quality on Customers' Behavior Intentions Mediating Role of Trust. Global Management Journal for Academic & Corporate Studies, 11(2), 1-21. Butt, S. (2023). Employees’ perception regarding in-house training programs in Pakistani organizations. Journal of Workplace Behavior (JoWB) Volume, 4(1), 35-50. Butt, M. A., Shaikh, A. I., Nawaz, B., & Adnan Kazmi, S. M. (2025). Customer perception and adoption of Islamic banking services in Pakistan. Center for Management Science Research. https://cmsrjournal.com/index.php/Journal/article/view/528 Cooper, B., Wang, J., Bartram, T., & Cooke, F. L. (2019). Well‐being‐oriented human resource management practices and employee performance in the Chinese banking sector: The role of social climate and resilience. Human resource management, 58(1), 85-97. Dash, A., Amin, F., Sahoo, S. K., & Mishra, S. K. (2025, December). Secure comparative evaluation of Alzheimer MRI classification models using blockchain. In 2025 13th International Conference on Intelligent Systems and Embedded Design (ISED) (pp. 905-911). IEEE. Haque, A. (2021). The COVID-19 pandemic and the role of responsible leadership in health care: thinking beyond employee well-being and organizational sustainability. Leadership in Health Services, 34(1), 52-68. Hasan, M. A., Mazumder, M. T. R., Motari, M. C., Shourov, M. S. H., & Sarkar, M. (2025). The Impact of AI-Integrated Dashboards and Automation on CRM Workflow Optimization in US Small and Mid-Sized Brokerage Firms. Journal of Theoretical and Applied Econometrics, 2(1), 25-56. HASAN, M. A., Mazumder, M. T. R., Motari, M. C., Shourov, M. S. H., & Sarkar, M. (2026). AI and Business Intelligence Integration for Improved Efficiency and Reporting Accuracy in Small US Financial Institutions. Journal of Fintech, Business, and Development, 3(1), 1-25. Islam, M. R., Islam, M. M., Badhan, I. A., & Hasnain, M. N. (2025). The role of artificial intelligence in carbon pricing policies: Economic and environmental implications. Journal of Engineering and Computational Intelligence Review, 3(2), 1-19. Islam, M. S., & Shiva, T. A. (2024). Virtual cognitive behavioural therapy in rural US communities: Effectiveness and reach. Journal of Business Insight and Innovation, 3(2), 60-76. Islam, T., Abdullah, J., Munna, M. M. H., Nahid, N. A. A. H., Tusar, M. I. H., & Sarder, M. D. (2026). Multi-objective optimization for transportation mode selection: A case study in logistics. The Asian Journal of Shipping and Logistics. https://doi.org/10.1016/j.ajsl.2026.01.002 Kashif, S. M., & Chowdhury, F. (2024). A comprehensive review of asset management systems: Trends, technologies, and future directions. Journal of Engineering and Computational Intelligence Review, 2(2), 1-9. Khan, K., & Alvi, S. (2023). A Comprehensive Review of Blockchain Applications across Diverse Domains. Journal of Engineering and Computational Intelligence Review, 1(1), 23-38. Kim, M., & Kim, J. (2021). Corporate social responsibility, employee engagement, well-being and the task performance of frontline employees. Management Decision, 59(8), 2040-2056. Lu, Y., Zhang, M. M., Yang, M. M., & Wang, Y. (2023). Sustainable human resource management practices, employee resilience, and employee outcomes: Toward common good values. Human Resource Management, 62(3), 331-353. Majumder, C., Sultana, N., Choain, A. H. K., & Nasir, M. A. (2026). Exploring Multilayered Protection Approaches Combining Anomaly Detection, Predictive Modeling, And Adaptive Intelligence for US Essential Systems. Spanish Journal of Innovation and Integrity, 50, 31-47. Nahid, N. A. A. H., Islam, T., Rube, H. A., & Tusar, M. I. H. (2025). Circular Economy Models for Urban Logistics: The Role of Bio-Based Packaging in Sustainable Transportation Networks. In IISE Annual Conference. Proceedings (pp. 1-6). Institute of Industrial and Systems Engineers (IISE). Nasir, M. A., Choain, A. H. K., Sultana, N., & Majumder, C. (2026). Integrating AI-Driven Compliance Frameworks to Automate Regulatory Monitoring across US Healthcare, Finance and Institutional Governance Systems. Journal of Theoretical and Applied Econometrics, 3(1), 1-24. Rahman, A., & Sultana, S. (2023). Real-Time Threat Intelligence Correlation and Triage for Reducing Security Analyst Burnout. Journal of Engineering and Computational Intelligence Review, 1(1), 64-86. Rahman, A., Sultana, S., & Lima, R. J. (2026). Strategic Framework for Enterprise Cybersecurity Management: Integrating Intelligent Anomaly Detection for Proactive Threat Mitigation. Journal of Computer Science and Technology Studies, 8(4), 58-70. Rahman, A., Sultana, S., Twaha, U., & Rowshon, M. (2026). AI-Enhanced Web Application Firewalls for Protecting United States Critical Infrastructure Against Zero-Day Exploits. Scientia. Technology, Science and Society, 3(2), 11-32. Rasul, I., Akter, T., Akter, S., Eshra, S. A., & Hossain, A. (2025). AI-Driven Business Analytics for Product Development: A Survey of Techniques and Outcomes in the Tech Industry. Frontline Marketing. Management and Economics Journal, 5(01), 16-38. Rauf, M. A., Latif, D. A., & Mushtaq, M. K. (2025). Assessing the effects of occupational burnout on job performance: A quantitative study of National Highway and Motorway Police officers. Contemporary Journal of Social Science Review, 3(3), 731-741. Rean, M. A., Ibrahim, M. B. H., Irawan, A., Akbar, M. A., & Rasyid, A. (2024). Nurturing both organizational and human resource wellbeing for sustainable growth. Advances: Jurnal Ekonomi & Bisnis, 2(1), 12-24. Shahinuzzaman, M., Shiva, T. A., Sumon, M. S., & Saifuddin, K. (2019). Mental health of women breast cancer survivor at different stages of the disease. Jagannath University J Earth Life Sci, 5(1), 1-12. Shuvra, S. M. K., Gony, M. N., & Fatema, K. (2024). Adaptive machine learning for resource-constrained environments: A path toward sustainable AI. International Journal of Research and Applied Innovations, 7(6), 8004-8014. Singh, S. K., Pradhan, R. K., Panigrahy, N. P., & Jena, L. K. (2019). Self-efficacy and workplace well-being: moderating role of sustainability practices. Benchmarking: An International Journal, 26(6), 1692-1708. Thomas, L. R., Ripp, J. A., & West, C. P. (2018). Charter on physician well-being. Jama, 319(15), 1541-1542. Tortia, E. C., Sacchetti, S., & López-Arceiz, F. J. (2022). A human growth perspective on sustainable HRM practices, worker well-being and organizational performance. Sustainability, 14(17), 11064. Twaha, U. (2024). Mitigating Financial Waste in the US Healthcare System: An AI-Driven Framework for Real-Time Fraud Detection in Medicare and Medicaid Claims. Journal of Engineering and Computational Intelligence Review, 2(2), 71-81. Watson, D., Tregaskis, O., Gedikli, C., Vaughn, O., & Semkina, A. (2018). Well-being through learning: a systematic review of learning interventions in the workplace and their impact on well-being. European Journal of Work and Organizational Psychology, 27(2), 247-268. Wood, S., & Ogbonnaya, C. (2018). High-involvement management, economic recession, well-being, and organizational performance. Journal of Management, 44(8), 3070-3095.
Copyright (c) 2026 Muhammad Shoaib Akhtar https://creativecommons.org/licenses/by-nc-sa/4.0
Impact of Innovation and Project Control on Sustainable Project Success: Examining the Mediating Role of Project Governance in Pakistan’s Software Development Sector
In modern project setting especially in the software development industry, organizations are progressively relying on innovation as well as on formal Project Control processes as a means of attaining sustainable project success. Whereas innovation facilitates flexibility, technological progress, and innovative problem solving, Project Control mechanisms uphold discipline, accountability and focus on project goals. Nevertheless, it is essential to strike the balance between these two dimensions, which is a serious issue of project managers. Project governance, in this situation, is turning out to be a key factor in the combination of innovative practices with the formal System of the Project Control to provide viability of the project in the long run. This research proposes the effects of innovation and Project Control on sustainable project success as a mediating variable through project governance. The study concentrates on software development firms that are based in Pakistan. The quantitative research design was adopted, and primary data were gathered using a structured questionnaire on the basis of a five-point Likert scale. Project managers, team members and stakeholders gave 300 valid responses. The data were analysed through Structural Equation Modelling (SEM) in STATA 18. The results demonstrate that the positive influence of innovation and Project Control is significant in terms of sustainable project success. Moreover, innovation, control, and sustainable project success are closely connected and mediated by project governance. The findings indicate that the likelihood of successful outcomes of projects- sustainability is greater in those organizations that successfully align innovation abilities and established governance and Project Control systems. The research will add value to the existing literature on project management due to the empirical evidence presented in the work within the context of the developing economy and practical guidance to the project management community aiming to optimize the performance of long-term projects in terms of performance through balanced management practices. References Adler, P. S. (2015). Community and innovation: From Tönnies to Marx. Organization Studies, 36(4), 445–471. Akrofi, K. S.-A., Ocansey, E. O. N. D., & Asamoah, F. O. (2025). Financial innovation as a moderator: Analyzing the interplay between financial inclusion, poverty and economic growth in Africa. Bekker, M., & Steyn, H. (2020). Project governance: Definition and framework. South African Journal of Industrial Engineering, 31(1), 1–14. Benmahmoud-Jouini, S. (2025). Project management and innovation: On projectification, lineages, and beyond. 56(3), 287–298. Chen, M., Martins, T. S., Zhang, L., & Dong, H. (2025). Digital transformation in project management: A systematic review and research agenda. Systems, 13(8), 625. Chen, Y., Liu, J., & Wang, Q. (2024). Digital innovation and project performance in technology-driven organizations. International Journal of Project Management, 42(2), 145–158. Chen, Z., Wang, J., Liu, K., Gong, J., Sun, L., Wu, Z., Timofte, R., Zhang, Y., Zhang, J., & Wu, J. (2025). NTIRE 2025 challenge on real-world face restoration: Methods and results. Proceedings of the Computer Vision and Pattern Recognition Conference, 1536–1547. Davies, A., Dodgson, M., & Gann, D. (2016). Dynamic capabilities in complex projects: The case of London Heathrow Terminal 5. Project Management Journal, 47(2), 26–46. Elhamahmy, A., Gohar, H. T. H., & Galal, A. (2025). Sustainable project management in renewable energy and infrastructure projects: Challenges and opportunities. International Journal of Engineering Research & Technology, 14(05). Elhamahmy, S., Abdallah, S., & Hussein, M. (2025). Governance mechanisms and project success in complex project environments. International Journal of Managing Projects in Business, 18(1), 1–18. Enang, I., & Omeihe, K. (2025). Integrating sustainability in project management: A systematic review and meta-analysis of success factors and organisational outcomes. Fu, H., & Tan, B. (2025). Integrating innovation and governance in project management research. Journal of Engineering and Technology Management, 69, 101–115. Fu, Q., & Tan, J. S. (2025). Interplay between leadership style and innovative work behavior: Mediated by innovation-oriented people management. International Journal of Innovation Science, 1–23. Haider, W., & Ahmed, N. (2025). Agile methodologies for project success: Exploring the role of innovation and management support. Sohar University Journal of Sustainable Business, 1(1), 1–15. Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2022). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer. Joslin, R., & Müller, R. (2016). The relationship between project governance and project success. International Journal of Project Management, 34(4), 613–626. Kerzner, H., & Saladis, F. P. (2017). Project management workbook and PMP/CAPM exam study guide. John Wiley & Sons. Lenfle, S., & Loch, C. (2010). Lost roots: How project management came to emphasize control over flexibility and novelty. California Management Review, 53(1), 32–55. Martens, M. L., & Carvalho, M. M. (2017). Key factors of sustainability in project management context: A survey exploring the project managers’ perspective. International Journal of Project Management, 35(6), 1084–1102. Meredith, J. R., Shafer, S. M., & Mantel, S. J. (2017). Project management: A strategic managerial approach. John Wiley & Sons. Müller, R., Zhai, L., & Wang, A. (2017). Governance and governmentality in projects: Profiles and relationships with success. International Journal of Project Management, 35(3), 378–392. Nambisan, S., Lyytinen, K., Majchrzak, A., & Song, M. (2017). Digital innovation management: Reinventing innovation management research in a digital world. MIS Quarterly, 41(1), 223–238. Nambisan, S., Wright, M., & Feldman, M. (2019). The digital transformation of innovation and entrepreneurship: Progress, challenges, and key themes. Research Policy, 48(8), 103773. Nawaz, et al. (2025). [Full bibliographic details not visible in extracted thesis text; verify from original bibliography]. O’Reilly, C. A., & Tushman, M. L. (2013). Organizational ambidexterity: Past, present, and future. Academy of Management Perspectives, 27(4), 324–338. Pesch, R. (2021). Digital product innovation management: Balancing stability and fluidity through formalization. 726–744. Rafiq-uz-Zaman, M. (2023). Bridging CPEC-driven industrial growth and skill-based education in Pakistan: A systematic review. Journal of Business Insight and Innovation, 2(1), 55–78. Retrieved from https://insightfuljournals.com/index.php/JBII/article/view/57 Rafiq-uz-Zaman, M. (2024). Leveraging skill development and STEAM innovation for business growth – A strategic framework for enhancing workforce performance in emerging markets platform. Journal of Business Insight and Innovation, 3(1), 48–63. Retrieved from https://insightfuljournals.com/index.php/JBII/article/view/55 Rafiq-uz-Zaman, M. (2025a). Between adoption and ambiguity: Navigating the AI policy vacuum in Pakistani higher education. Research Journal for Social Affairs, 3(6), 877–885. Retrieved from https://doi.org/10.71317/RJSA.003.06.0523 Rafiq-uz-Zaman, M. (2025b). Beyond the blackboards: Building a micro-edtech economy through teacher-led innovation in low-income schools. Journal of Business Insight and Innovation, 4(1), 46–52. Retrieved from https://insightfuljournals.com/index.php/JBII/article/view/42 Rafiq-uz-Zaman, M., & Nadeem, M. A. (2025). Gauging the gap: Student perceptions of skill proficiency in skill-based education within schools of Punjab, Pakistan. Academia International Journal for Social Sciences, 4(2), 2307–2317. Retrieved from https://doi.org/10.63056/ACAD.004.03.0553 Robertson, H. T. (2025). Defining and measuring project success: A comparative analysis of two key studies. Roque, H. C., Pitacho, L., & Lima, D. (2025). The contributions of responsible leadership to organizational resilience. In Leveraging Technology for Organizational Adaptability (pp. 41–58). IGI Global Scientific Publishing. Sabini, L., Muzio, D., & Alderman, N. (2019). 25 years of ‘sustainable projects’: What we know and what the literature says. International Journal of Project Management, 37(6), 820–838. Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students (8th ed.). Pearson. Schumpeter, J. A. (2017). Essays: On entrepreneurs, innovations, business cycles and the evolution of capitalism. Routledge. Serrador, P., & Pinto, J. K. (2015). Does agile work? A quantitative analysis of agile project success. [JPMA], 1–12. Shahid, M., & Irfan, M. (2021). Governance structures and project success in developing countries. International Journal of Project Organisation and Management, 13(3), 215–230. Shokouhi, M., & Senisel, M. (2025). An overview of the aspects of sustainability in project management. Progress in Engineering Science, 2(1). Silvius, A. J. G. (2017). Sustainability as a new school of thought in project management. Journal of Cleaner Production, 166, 1479–1493. Sitkin, S. B., Cardinal, L. B., & Bijlsma-Frankema, K. M. (2010). Organizational control. Cambridge University Press. Stanikzai, M. E., & Mittal, E. (2025). Strategic alignment of organizational structure based on decisions for sustainable organizational performance: A bibliometric-systematic literature review. Cogent Business & Management, 12(1), 2560650. Stretton, A. (2025). Exploring differences for project management in supplier vs. owner organisations in outcomes and benefits contexts. Sulistiyani, E., Hidayatul, S., & Tyas, Y. (2022). What is the measurement of the IT project success? [Please verify full source title and details from thesis bibliography]. Tiwana, A. (2010). Systems development ambidexterity: Explaining the complementary and substitutive roles of formal and informal controls. Journal of Management Information Systems, 27(2), 87–126. Too, E. G., & Weaver, P. (2018). The management of project management: A conceptual framework for project governance. International Journal of Project Management, 36(8), 1070–1082. Turner, J. R. (2016). Gower handbook of project management (5th ed.). Routledge. Turner, R., Zolin, R., & Remington, K. (2009). Monitoring the performance of complex projects from multiple perspectives over multiple time frames. International Research Network of Project Management Conference (IRNOP), 1–27. Vial, G. (2019). Understanding digital transformation: A review and a research agenda. Journal of Strategic Information Systems, 28(2), 118–144. Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). Research commentary: The new organizing logic of digital innovation. Information Systems Research, 21(4), 724–735.
Copyright (c) 2026 Adil Ali, Shahid Iqbal, Ehtasham Ul Haq https://creativecommons.org/licenses/by-nc-sa/4.0
Green Supply Chain Management and Sustainable Performance: The Mediating Role of Innovation and Institutional Pressures
Green Supply Chain Management (GSCM) has emerged as a strategic approach for improving environmental, economic, and social performance in organizations. This study examined the impact of GSCM on sustainable performance with the mediating roles of innovation and institutional pressures. A quantitative research design was applied using a cross-sectional survey approach. Data were collected from employees working in manufacturing and supply chain-related firms in Pakistan, particularly in textile, logistics, pharmaceutical, and food processing sectors. A total of 350 questionnaires were distributed, and 312 valid responses were analysed. Structural Equation Modelling (SEM) using Smart PLS was employed to test the proposed hypotheses. The results indicated that GSCM significantly influenced sustainable performance (β = 0.31, p < 0.001). Innovation showed a significant mediating effect between GSCM and sustainable performance (β = 0.21, p < 0.001), while institutional pressures also demonstrated a significant mediating role (β = 0.18, p < 0.001). Additionally, innovation positively influenced sustainable performance (β = 0.36, p < 0.001), and institutional pressures significantly enhanced sustainable performance (β = 0.33, p < 0.001). The findings confirmed that sustainable performance improved when GSCM practices were supported by innovation capabilities and institutional compliance mechanisms. The study contributes to resource-based and institutional theories by explaining how internal and external factors jointly enhance sustainability outcomes. Practical implications suggest that organizations should integrate green innovation and respond effectively to institutional pressures to achieve long-term sustainability advantages. Abbas, J. (2024). Green supply chain management and firm sustainable performance: Unlocking the role of leadership styles in sustainable operations. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-024-05035-0 Alhmeidiyeen, M., & Qadeer, F. (2025). Green innovation and sustainable performance: Evidence from supply chain transformation. Journal for Social Science Archives. https://doi.org/10.51325/jssarchives.v1i1.302 Ashraf, M. A. (2026). Sustainable supply chain practices and environmental performance in emerging economies. Future Business Journal. https://doi.org/10.1186/s43093-026-00766-0 Ashraf, S. (2026). Challenging role of green supply chain management in sustainable growth. Frontiers in Sustainability. https://doi.org/10.3389/frsus.2026.1735187 Asif, M. (2025). FINANCIAL PERFORMANCE OF STARTUPS LINKED TO UNIVERSITIES: EVIDENCE FROM DEVELOPING ECONOMIES. Journal of Applied Linguistics and TESOL (JALT), 8(3), 2736-2763. https://doi.org/10.63878/jalt2003 Atieh, A. A., & Abushaega, M. M. (2025). Achieving supply chain sustainability through green innovation. Sustainability, 17(13), Article 5716. https://doi.org/10.3390/su17135716 Chu, S. H., Yang, H., Lee, M., & Park, S. (2017). The impact of institutional pressures on green supply chain management and firm performance. Sustainability, 9(5), Article 764. https://doi.org/10.3390/su9050764 Junejo, I., Sohu, J. M., Alwadi, B. M., Ejaz, F., & Hossain, M. B. (2025). Green supply chain management and SMEs sustainable performance in a developing country. Discover Sustainability, 6, Article 342. https://doi.org/10.1007/s43621-025-01055-6 Karakaş-Kelten, Z., Savaş, H., & Sezen, B. (2026). The impact of green supply chain management practices on performance. Future Business Journal, 12, Article 87. https://doi.org/10.1186/s43093-026-00766-0 Kurniawan, M. S. D., & Hartini, S. (2025). Interrelationship between green supply chain management and green innovation. Jurnal Ilmu Lingkungan. https://doi.org/10.14710/jil.23.3.712-720 Li, X., Li, Y., & Xu, J. (2025). Sustainable supply chain management practices and performance. Humanities and Social Sciences Communications, 12, Article 336. https://doi.org/10.1038/s41599-025-04676-4 Li, X., Zhang, Y., & Wang, H. (2025). Institutional pressures, green innovation, and sustainable performance in manufacturing firms. Sustainability, 16(6), Article 2278. https://doi.org/10.3390/su16062278 Lin, Y. H., et al. (2018). Institutional pressures and green performance in the shipping industry. Transportation Research Part D. https://doi.org/10.1016/j.trd.2017.07.005 Liu, D., Yousaf, Z., & Rosak-Szyrocka, J. (2024). Environmental performance through green supply chain management practices. Sustainability, 16(24), Article 11173. https://doi.org/10.3390/su162411173 Liu, Y., Chen, J., & Huang, T. (2024). Green innovation and environmental performance in supply chain systems. Sustainability, 16(5), Article 2058. https://doi.org/10.3390/su16052058 Mahar, A. S., Zhang, Y., Sadiq, B., & Gul, R. F. (2025). Sustainability transformation through GSCM practices and green innovations. Sustainability, 17(5), Article 2204. https://doi.org/10.3390/su17052204 Makhdoom, H., Ali, S., & Rehman, A. (2025). Digital transformation and green supply chain performance: Evidence from emerging markets. Journal of Cleaner Production. Makhdoom, Q., Junejo, I., Sohu, J. M., Shah, S. M. M., & Ejaz, F. (2025). Impact of GSCM on sustainable performance. F1000Research, 13, Article 1140. https://doi.org/10.12688/f1000research.154615.2 Mohiuddin, D. (2026). Adaptive Marketing Systems and Consumer Feedback Loops: Implications for Market Development in Emerging Economies. Journal of Business Insight and Innovation, 5(1), 37–48. Mohiuddin, D. (2025). HR Tech Adoption in Digital Banking: Implications for Workforce Development and Financial Sector Growth in Emerging Economies. Journal of Business Insight and Innovation, 4(2), 77–90. Mustafi, M. A. A., Dong, Y. J., Roy, I., Mony, F. K., & Arefin, M. S. (2026). Enhancing environmental performance through GSCM practices. SAGE Open. https://doi.org/10.1177/21582440251412196 Nazir, M., Khan, S., & Ahmad, R. (2024). Green supply chain management and environmental performance: A systematic review. Sustainability. Nazir, S., Zhaolei, L., Mehmood, S., & Nazir, Z. (2024). Impact of green supply chain management practices on environmental performance. Sustainability, 16(6), Article 2278. https://doi.org/10.3390/su16062278 Olaleye, B. R., & Mosleh, S. F. (2025). Greening sustainable supply chain performance. Administrative Sciences, 15(5), Article 183. https://doi.org/10.3390/admsci15050183 Rafiq-uz-Zaman, M., & Asif, M. (2026). Mechanisms of exclusion: Power, structure, and the persistence of gender inequality. Qualitative Research Journal for Social Studies, 3(1), 690–703. https://doi.org/10.63878/qrjs921 Rafiq-uz-Zaman, M., Faridi, M. Z., & Hussain, R. M. (2025a). Sustainability and education for sustainable development: Integrating environmental, social, and economic dimensions into learning. Journal of Applied Linguistics and TESOL, 8(4), 386–401. https://doi.org/10.63878/jalt1480 Rafiq-uz-Zaman, M., Imtiaz, I., & Khalid, N. (2024a). Innovative integration of environmental awareness into mathematics education: Insights from teachers’ and students’ perceptions in Bahawalpur. Journal of Asian Development Studies, 13(4), 899–910. https://doi.org/10.62345/jads.2024.13.4.72 Rafiq-uz-Zaman, M., Khalid, N., & Shafi, S. (2024b). Historical analysis of environmental degradation in Pakistan: A narrative review. Global Political Review, 9(4), 24–35. https://doi.org/10.31703/gpr.2024(IX-IV).03 Rafiq-uz-Zaman, M., Khalid, N., Faridi, M. Z., & Khan, Z. A. (2024). Smog mitigation and climate resilience in Pakistan: A policy-centric review of strategies and challenges. Social Sciences Spectrum, 3(4), 302–317. https://doi.org/10.71085/sss.03.04.175 Rafiq-uz-Zaman, M., Malik, N., & Bano, S. (2025b). Effectiveness of STEAM education in enhancing 21st-century skills: A systematic review. Journal of Asian Development Studies, 14(3), 590–598. https://doi.org/10.62345/jads.2025.14.3.49 Wang, X., et al. (2023). Institutional pressures, green innovation, and economic performance. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2023.139182 Yu, W., Zhang, L., & Li, M. (2022). Green innovation and supply chain sustainability: A serial mediation approach. Journal of Cleaner Production. Yu, Z., Waqas, M., Tabish, M., & Tanveer, M. (2022). Sustainable supply chain management and green technologies. Environmental Science and Pollution Research, 29(39), 58454–58470. https://doi.org/10.1007/s11356-022-21544-9 Zeng, H., et al. (2021). Institutional pressures and sustainability capabilities. Sustainable Production and Consumption. https://doi.org/10.1016/j.spc.2021.04.017 Zhang, Q., Wang, R., & Liu, S. (2024). Institutional pressure and green supply chain adoption: Evidence from manufacturing firms. Sustainability, 16(5), Article 2058. https://doi.org/10.3390/su16052058
Copyright (c) 2026 Zujaj Ahmed, Adeel Akhtar, Akbar Ali Rabbani https://creativecommons.org/licenses/by-nc-sa/4.0
Bridging the Jurisdictional Gap: The Underutilization of the Federal Investigation Agency in Pakistan's Maritime Domain Under Joint Maritime Information Organisation Act, 2019
The paper will discuss the limited legal role that the Federal Investigation Agency (FIA) in Pakistan is granted by the Joint Maritime Information Organisation Act, 2019. Although the FIA has a broad jurisdiction covering counter-terrorism, anti-money laundering, human trafficking, and transnational organized crime cases, the JMIO Act, 2019 only covers the agency to issues of immigration. This study examines the mismatch between the real legal capability of the FIA and its limited role at the Joint Maritime Information Coordination Centre (JMICC). By conducting comparative analysis of National Command Authority Act, 2010, and the National Counter Terrorism Authority Act, 2013, this paper reveals that there are critical areas in maritime security in Pakistan. The results indicate that an ideal exploitation of the FIA legal requirement would greatly improve the ability of Pakistan to combat maritime crimes such as terrorism financing, money laundering and cyber-facilitated crimes in the Pakistani waters. Some of the recommendations are changes in legislation to increase the role of FIA as a part of the JMIO framework and improving the mechanisms of inter-agency coordination to counter transnational maritime threats, especially those to the China-Pakistan Economic Corridor. References Ali, S. I. (2018). The Federal Investigation Agency Act, 1974: Together with selected laws contained in the schedule along with commentaries. Rahber Publisher. Anti-Money Laundering Act, 2010, Act No. VII of 2010 (Pakistan). Anti-Terrorism Act, 1997, Act No. XXVII of 1997 (Pakistan). Bhatti, B. A. (2021, January 14). Joint Maritime Information Coordination Center: A milestone toward Maritime Domain Awareness in Pakistan. Maritime Study Forum. https://www.maritimestudyforum.org/joint-maritime-information-coordination-center-a-milestone-toward-maritime-domain-awareness-in-pakistan/ Bueger, C., McCabe, R., & Edmunds, T. (2020). Capacity building for maritime security: The Western Indian Ocean experience. Springer International Publishing. https://doi.org/10.1007/978-3-030-34630-9 CPEC Authority Act, 2021, Act No. VIII of 2021 (Pakistan). Dawn. (2019, May 12). 5 people killed in Gwadar PC hotel attack; army concludes clearance operation. https://www.dawn.com/news/1481840 Evans, M. D., & Galani, S. (Eds.). (2020). Maritime security and the law of the sea: Help or hindrance? Edward Elgar Publishing. DOI: https://doi.org/10.4337/9781788118104 Federal Investigation Agency. (2021). Red Book 2021: Most wanted high profile terrorists. FIA Headquarters, Islamabad. FIA Act, 1974, Act No. VIII of 1975 (Pakistan). Financial Action Task Force. (2022). Increased monitoring: June 2022. https://www.fatf-gafi.org/publications/high-risk-and-other-monitored-jurisdictions/documents/increased-monitoring-june-2022.html Geiß, R., & Petrig, A. (2011). Piracy and armed robbery at sea: The legal framework for counter-piracy operations in Somalia and the Gulf of Aden. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199609529.001.0001 Jaffrelot, C. (2016). Pakistan at the crossroads: Domestic dynamics and external pressures. Columbia University Press. Joint Maritime Information Organisation Act, 2019, Gazette Notification F.22(29)2019-Legis (Pakistan). Khan, A. (2022). The NCB and INTERPOL: Cooperation in international law enforcement. Law Enforcement Press. Klein, N. (2012). Maritime security and the law of the sea. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199566532.001.0001 Nawaz, F. (2022). Challenges to maritime security of Pakistan. Saudi Journal of Humanities and Social Sciences, 7(2), 73–78. https://doi.org/10.36348/sjhss.2022.v07i02.004 NACTA Act, 2013, Act No. XIX of 2013 (Pakistan). National Command Authority Act, 2010, Gazette Notification (Pakistan). Patel, R. (2022). Unmasking the truth: Investigating the Mumbai terrorist attacks. Counterterrorism Publishing. Prevention of Electronic Crimes Act, 2016, Act No. XL of 2016 (Pakistan). Prevention of Smuggling of Migrants Act, 2018, Act No. XXXV of 2018 (Pakistan). Prevention of Trafficking in Persons Act, 2018, Act No. XXXIV of 2018 (Pakistan). Tankel, S. (2013). Storming the world stage: The story of Lashkar-e-Taiba. Oxford University Press. United Nations. (1982). United Nations Convention on the Law of the Sea. UN Doc. A/CONF.62/122. United Nations Security Council. (2001). Resolution 1373. UN Doc. S/RES/1373. United Nations Security Council. (2004). Resolution 1540. UN Doc. S/RES/1540. United Nations Security Council. (2017). Resolution 2396. UN Doc. S/RES/2396.
Copyright (c) 2026 Ijaz Ahmad https://creativecommons.org/licenses/by-nc-sa/4.0
Innovating with AI: How Innovative Attitude, Peer Influence, and Task-Technology Fit Shape AI Appropriation in Project Management
The rapid diffusion of generative artificial intelligence (AI) tools is reshaping project management practices, yet significant variation remains in how professionals creatively appropriate these technologies. This study investigates the drivers of AI appropriation in project management by integrating Adaptive Structuration Theory (AST) with Task–Technology Fit (TTF) theory. The research examines how innovation attitude, peer influence, and task–technology fit influence AI-enabled creative behaviour, while also assessing the moderating role of organizational culture. A quantitative cross-sectional survey was conducted among 234 project management professionals working in Pakistan’s information technology and logistics sectors. Data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results indicate that task–technology fit is the strongest predictor of creative AI appropriation, followed by innovation attitude and peer influence. Furthermore, organizational culture significantly strengthens the relationships between these antecedents and creative behaviour, highlighting its role as a contextual amplifier of AI-enabled innovation. The model explains 71.5% of the variance in creative behaviour, demonstrating substantial explanatory power. The study contributes to the literature by extending AST to generative AI contexts, empirically integrating AST and TTF in a unified framework, and providing evidence from an emerging economy with collectivist cultural characteristics. Practically, the findings suggest that organizations seeking to leverage AI for innovative project outcomes should prioritize task-aligned AI tools, cultivate innovation-oriented mindsets among professionals, and develop supportive organizational cultures that encourage experimentation and collaborative learning. References Alam, I., Waheed, K. Z., & Rehman, M. S. (2024). The impact of cultural diversity on workforce efficiency in private banking sector of Pakistan. Journal of Workplace Behavior, 5(1), 65–81. https://doi.org/10.70580/jwb.05.01.0218 Balash, F., Ghooja, S., & Talab, A. S. (2018). The rankings of involvement and consistency in line with academic research ethics. In European proceedings of social and behavioural sciences (pp. 72–80). https://doi.org/10.15405/epsbs.2018.05.7 Barcaui, A., & Monat, A. (2023). Who is smarter? Generative artificial intelligence versus project managers in project risk identification. Project Management Journal, 54(5), 455–467. Bayaga, A. (2025). Leveraging AI-enhanced and emerging technologies for pedagogical innovations in higher education. Education and Information Technologies, 30(1), 1045–1072. Cao, G., Duan, Y., & Edwards, J. S. (2025). Organizational culture, digital transformation, and product innovation. Information & Management, 62(4), 104135. Chen, J., Xie, W., Xie, Q., Hu, A., Qiao, Y., Wan, R., & Liu, Y. (2025). A systematic review of user attitudes toward GenAI: Influencing factors and industry perspectives. Journal of Intelligence, 13(7), 78. Ciftci, O., Berezina, K., & Kang, M. (2021). Effect of personal innovativeness on technology adoption in hospitality and tourism: Meta-analysis. In Information and communication technologies in tourism 2021 (pp. 162–174). Cimino, A., Felicetti, A. M., Corvello, V., Ndou, V., & Longo, F. (2025). Generative artificial intelligence (AI) tools in innovation management: A study on the appropriation of ChatGPT by innovation managers. Management Decision, 63(10), 3431–3453. Denison, D. R. (1990). Corporate culture and organizational effectiveness. Wiley. Denison, D. R., & Mishra, A. K. (1995). Toward a theory of organizational culture and effectiveness. Organization Science, 6(2), 204–223. Dennis, A. R., Wixom, B. H., & Vandenberg, R. J. (2001). Understanding fit and appropriation effects in group support systems via meta-analysis. MIS Quarterly, 25(2), 167–193. DeSanctis, G., & Poole, M. S. (1994). Capturing the complexity in advanced technology use: Adaptive structuration theory. Organization Science, 5(2), 121–147. Dong, X., Tian, Y., He, M., & Wang, T. (2024). When knowledge workers meet AI? The double-edged sword effects of AI adoption on innovative work behavior. Journal of Knowledge Management, 29(1), 113–147. https://doi.org/10.1108/jkm-02-2024-0222 Felicetti, A. M., Cimino, A., Corvello, V., Ndou, V., & Longo, F. (2024). Appropriating ChatGPT in project management: A study among Italian project managers. International Journal of Project Management, 42(3), 102576. Giddens, A. (1979). Central problems in social theory: Action, structure, and contradiction in social analysis. University of California Press. Golden, J. H., & Shriner, M. (2017). Examining relationships between transformational leadership and employee creative performance: The moderator effects of organizational culture. The Journal of Creative Behavior, 53(3), 363–376. https://doi.org/10.1002/jocb.216 Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213–236. Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157–169. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. Hartl, E., Nawrath, D., & Hess, T. (2018). Refining the influence of organizational culture on individual IS adoption. In Proceedings of the 26th European Conference on Information Systems (ECIS). Association for Information Systems. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. Hofstede, G. (1991). Cultures and organizations: Software of the mind. McGraw-Hill. Hossain, M. A., Akter, S., & Nagahashi, N. (2024). Generative AI in project management: A systematic literature review. International Journal of Project Management, 42(5), 102589. Hughes, L., Mavi, R. K., Aghajani, M., Fitzpatrick, K., Gunaratnege, S. M., Shekarabi, S. A. H., Hughes, R., Khanfar, A., Khatavakhotan, A., & Mavi, N. K. (2025). Impact of artificial intelligence on project management (PM): Multi-expert perspectives on advancing knowledge and driving innovation toward PM2030. Journal of Innovation & Knowledge, 10(5), 100772. Jain, R., Garg, N., & Khera, S. N. (2022). Adoption of AI-enabled tools in social development organizations in India: An extension of UTAUT model. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.893691 Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research, 30(2), 199–218. Jo, H., & Bang, Y. (2023). Analyzing ChatGPT adoption drivers with the TOEK framework. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-49710-0 Khan, A., Khan, A., Shah, T. A., Khattak, M. N., & Abukhait, R. (2023). Management's internal governance policies on flexible work practices and the mediating lens of work-life enrichment. Journal of Organizational Effectiveness: People and Performance, 11(3), 532–552. https://doi.org/10.1108/joepp-02-2023-0059 Lin, T.-C., & Huang, C.-C. (2008). Understanding knowledge management system usage antecedents: An integration of social cognitive theory and task technology fit. Information & Management, 45(6), 410–417. Lu, Z., Li, P., Wang, W., & Yin, M. (2025). Understanding the effects of AI-based credibility indicators when people are influenced by both peers and experts. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (pp. 1–19). Mahmood, S., Mehmood, H., & Waheed, K. Z. (2024). The influence of despotic leadership on counterproductive work behavior: The role of follower’s dispositional characteristics. Pakistan Journal of Humanities and Social Sciences, 12(2), 1826–1841. https://doi.org/10.52131/pjhss.2024.v12i2.2305 McClelland, G. H., & Judd, C. M. (1993). Statistical difficulties of detecting interactions and moderator effects. Psychological Bulletin, 114(2), 376–390. Mohajan, H. K. (2020). Quantitative research: A successful investigation in natural and social sciences. Journal of Economic Development, Environment and People, 9(4). https://doi.org/10.26458/jedep.v9i4.679 Mokhchy, J., Chen, G., Ahmad, S., Khan, Y. A., Zhang, J., & Ahmed, M. (2025). Dynamic impact of leadership style, knowledge-sharing, and organizational culture on organizational performance. Current Psychology, 44(6), 4097–4112. Nenni, M. E., De Felice, F., De Luca, C., & Forcina, A. (2025). How artificial intelligence will transform project management in the age of digitization: A systematic literature review. Management Review Quarterly, 75(2), 1669–1716. Nevo, S., Nevo, D., & Pinsonneault, A. (2020). Exploring the role of IT in the front-end of innovation: An empirical study of IT-enabled creative behavior. Information and Organization, 30(4), 100322. Oh, K., Kho, H.-S., Choi, Y.-J., & Seogjun, L. (2022). Determinants for successful digital transformation. Sustainability, 14(3), 1215. https://doi.org/10.3390/su14031215 Pan, X., Wu, Y., & Liu, C. (2023). How peer influence shapes the adoption of AI-based recommendation systems: A social influence perspective. Computers in Human Behavior, 140, 107574. Park, Y. S., Konge, L., & Artino, A. R. (2020). The positivism paradigm of research. Academic Medicine, 95(5), 690–694. Patil, P. P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020). Understanding consumer adoption of mobile payment in India: Extending meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management, 54, 102144. https://doi.org/10.1016/j.ijinfomgt.2020.102144 Peng, Y., Ahmad, S. F., Irshad, M., Al-Razgan, M., Ali, Y. A., & Awwad, E. M. (2023). Impact of digitalization on process optimization and decision-making towards sustainability: The moderating role of environmental regulation. Sustainability, 15(20), 15156. https://doi.org/10.3390/su152015156 Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. Rafiq-uz-Zaman, M. (2025a). Between adoption and ambiguity: Navigating the AI policy vacuum in Pakistani higher education. Research Journal for Social Affairs, 3(6), 877–885. https://doi.org/10.71317/RJSA.003.06.0523 Rafiq-uz-Zaman, M. (2025b). Use of artificial intelligence in school management: A contemporary need of school education system in Punjab (Pakistan). Journal of Asian Development Studies, 14(2), 1984–2009. https://doi.org/10.62345/jads.2025.14.2.56 Rafiq-uz-Zaman, M., Bukhari, S. T., Malik, N., Rehman, L., & Qamar, A. H. (2025a). Gender differences in the use and challenges of breakthrough technology in higher education: Evidence from Punjab. The Critical Review of Social Sciences Studies, 3(3), 1056–1073. https://doi.org/10.59075/hpdvq714 Rafiq-uz-Zaman, M., Malik, N., & Bano, S. (2025b). Learning to innovate: WhatsApp groups as grassroots innovation ecosystems among micro-entrepreneurs in emerging markets. Journal of Asian Development Studies, 14(1), 1854–1862. https://doi.org/10.62345/jads.2025.14.1.47 Rafiq-uz-Zaman, M., Shih, Y.-H., & Akomodi, J. O. (2026). Integrating emotional intelligence and AI-driven learning in higher education: Implications for student well-being and university HR policies. The Study of Religion and History, 4(1), 1–24. https://doi.org/10.63163/srh300 Rogers, E. M. (1995). Diffusion of innovations (4th ed.). Free Press. Saghafian, M., Laumann, K., & Skogstad, M. R. (2021). Stagewise overview of issues influencing organizational technology adoption and use. Frontiers in Psychology, 12, 630145. Schein, E. H. (2010). Organizational culture and leadership (4th ed.). Jossey-Bass. Shao, Z., & Li, X. (2022). Investigating the role of IS management sophistication in IT infrastructure capability and business process agility: An empirical study. Industrial Management & Data Systems, 122(6), 1455–1480. Shoushtari, F., Daghighi, A., & Ghafourian, E. (2024). Application of artificial intelligence in project management. International Journal of Industrial Engineering and Operational Research, 6(2), 49–63. Stojčić, N., Hashi, I., & Orlić, E. (2018). Creativity, innovation effectiveness and productive efficiency in the UK. European Journal of Innovation Management, 21(4), 564–580. https://doi.org/10.1108/ejim-11-2017-0166 Taboada, I., Daneshpajouh, A., De Toledo, N., & De Weerdt, T. (2023). Artificial intelligence enabled project management: A systematic literature review. Applied Sciences, 13(8), 5014. Thao, N. T. P. (2025). How organizational culture influences digital transformation success: A systematic review. Journal of Business Research, 170, 114312. Trenerry, B., Chng, S., Wang, Y., Suhaila, Z. S., Lim, S. S., Lu, H., & Oh, P. H. (2021). Preparing workplaces for digital transformation: An integrative review and framework of multi-level factors. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.620766 Valerio, M. A., Redondo, N., Winkler, P., Lopez, J., Dennison, M., Liang, Y., & Turner, B. J. (2016). Comparing two sampling methods to engage hard-to-reach communities in research priority setting. BMC Medical Research Methodology, 16(1). https://doi.org/10.1186/s12874-016-0242-z Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. Vergara, D., del Bosque, A., Lampropoulos, G., & Fernández-Arias, P. (2025). Trends and applications of artificial intelligence in project management. Electronics, 14(4), 800. Waheed, K. Z., & Khan, M. I. (2025a). Fostering innovative work behavior in new product development projects: A theoretical review. Pakistan Journal of Humanities and Social Sciences, 13(2), 479–495. https://doi.org/10.52131/pjhss.2025.v13i2.2884 Waheed, K. Z., & Khan, M. I. (2025b). Fostering innovative work behavior in new product development projects: A systematic literature review. Center for Management Science Research, 3(6), 364–378. https://doi.org/10.5281/zenodo.17490189 Wang, G., Obrenovic, B., Gu, X., & Godinic, D. (2025). Fear of the new technology: Investigating the factors that influence individual attitudes toward generative artificial intelligence (AI). Current Psychology, 1–18. Wang, S.-F., & Chen, C.-C. (2025). Exploring drivers of AIGC-designer collaborative innovation. Sage Open, 15(3). https://doi.org/10.1177/21582440251344044 Wisdom, J. P., Chor, K. H. B., Hoagwood, K. E., & Horwitz, S. M. (2014). Innovation adoption: A review of theories and constructs. Administration and Policy in Mental Health and Mental Health Services Research, 41(4), 480–502. Wu, X., Yan, Y., Zhu, W., & Yang, N. (2024). An extended UTAUT model study on the adoption behavior of artificial intelligence technology in construction industry. Journal of Intelligent & Fuzzy Systems, 49(2), 564–581. https://doi.org/10.3233/jifs-240798 Yang, B., & Sun, Y. (2025). Improving learning performance through AI-enabled task completing and network building: Integrating task-technology fit and social-technology fit perspectives. Interactive Learning Environments, 1–21.
Copyright (c) 2026 Adil Naseer, Shahid Iqbal, Ehtasham Ul Haq https://creativecommons.org/licenses/by-nc-sa/4.0
The Digital Trap: How Short Political Videos on TikTok and Reels Lock Pakistani Youth into One-Sided Thinking
This study investigates how algorithm-driven short-form video platforms (e.g., TikTok, Instagram Reels) shape political perceptions and contribute to affective political polarization among Pakistani youth. A quantitative cross-sectional survey was conducted with a sample of 390 young adults (aged 18–30) in Lahore, Pakistan, selected using convenience sampling. Data were collected via a structured questionnaire measuring platform usage, exposure to algorithmically curated political content, and affective polarization. Descriptive statistics, chi-square tests of independence, and binary logistic regression were employed for analysis. Results indicate that 64.1% of respondents spend over three hours daily on short-form video platforms. A majority (57.2%) agreed that algorithms repeatedly show similar political viewpoints, leading to the perception of ideological echo chambers (46.9% rarely see opposing views). Logistic regression revealed that daily consumption of political short-form videos significantly predicts affective political polarization (B = 1.43, p < .001), with heavy users being over four times more likely to report heightened emotional attachment to political groups. The study confirms the existence of a "digital trap" where algorithmic personalization reinforces existing beliefs, limits exposure to diverse perspectives, and intensifies affective polarization. These findings have critical implications for media literacy interventions, platform governance, and democratic discourse in Pakistan. References Ahmed, S., & Asif, M. (2026). Comparative analysis of attitudes toward climate change policies across urban and rural populations. Pakistan Journal of Social Science Review, 5(1), 747–769. https://doi.org/10.5281/zenodo.18457821 Ahmed, S., & Asif, M. (2026). Public opinion on the effectiveness of local government anti-corruption measures: A multi-city survey analysis. International Journal of Social Sciences Bulletin, 4(1), 1189–1201. https://doi.org/10.5281/zenodo.18412790 Ahmmad, M., Shahzad, K., Iqbal, A., & Latif, M. (2025). Trap of social media algorithms: A systematic review of research on filter bubbles, echo chambers, and their impact on youth. Societies, 15(11), 301. https://doi.org/10.3390/soc15110301 Asif, M. (2025). Financial performance of startups linked to universities: Evidence from developing economies. Journal of Applied Linguistics and TESOL, 8(3), 2736–2763. https://doi.org/10.63878/jalt2003 Asif, M., Ali, A., & Shaheen, F. A. (2025). Assessing the effects of artificial intelligence in revolutionizing human resource management: A systematic review. Social Science Review Archives, 3(4), 2887–2908. https://doi.org/10.70670/sra.v3i3.1055 Asif, M., & Asghar, R. J. (2025). Managerial accounting as a driver of financial performance and sustainability in small and medium enterprises in Pakistan. Center for Management Science Research, 3(7), 150–163. https://doi.org/10.5281/zenodo.17596478 Asif, M., & Rafiq-uz-Zaman, M. (2026). The silent disengagement: A quantitative analysis of leadership, recognition, and workload as predictors of quiet quitting among knowledge workers. Al-AASAR Journal, 3(1), 271–303. https://doi.org/10.63878/aaj1525 Asif, M., & Ullah, S. (2026). Determinants of support for federalism vs. centralization: A survey of public opinion in Punjab and Khyber Pakhtunkhwa (KP). Social Science Review Archives, 4(1), 2791–2807. https://doi.org/10.70670/sra.v4i1.1843 Asif, M., & Ullah, S. (2026). Performance voting vs. identity voting: An analysis of electoral behaviour in Pakistani districts. Journal of Applied Linguistics and TESOL (JALT), 9(1), 213–226. https://doi.org/10.63878/cjssr.v4i1.2079 Bail, C. A. (2018). Exposure to opposing views on social media can increase political polarization. Proceedings of the National Academy of Sciences, 115(37), 9216–9221. Bakshy, E., Messing, S., & Adamic, L. A. (2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), 1130–1132. Cinelli, M., Morales, G. D. F., Galeazzi, A., Quattrociocchi, W., & Starnini, M. (2021). The echo chamber effect on social media. Proceedings of the National Academy of Sciences, 118(9), e2023301118. Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press. Garrett, R. K. (2009). Echo chambers online? Politically motivated selective exposure among Internet news users. Journal of Computer-Mediated Communication, 14(2), 265–285. Hussain, S. (2025). Algorithmic amplification and youth political engagement on TikTok: A study of political discourse, engagement, and gendered interactions in Pakistan. Magna Carta: Contemporary Social Science, 4(2), 79–90. Husnain, M., & Tareen, S. (2024). [Title needed]. [Journal name needed]. Iftikhar, N., & Bajwa, R. S. (2025). Influence of social media algorithms on the perspective of Pakistani youth. Pakistan Journal of Law, Analysis and Wisdom, 4(3), 63–72. Iyengar, S., & Westwood, S. J. (2015). Fear and loathing across party lines: New evidence on group polarization. American Journal of Political Science, 59(3), 690–707. Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. Malik, N., Rafiq-uz-Zaman, M., Bugti, M. A., & Bangulzai, W. A. (2025). Harassment of women in South Punjab politics: Impacts and strategies for enhanced leadership. ACADEMIA International Journal for Social Sciences, 4(3), 2575–2590. https://doi.org/10.63056/ACAD.004.03.0547 McCombs, M. E., & Shaw, D. L. (1972). The agenda-setting function of mass media. Public Opinion Quarterly, 36(2), 176–187. Mirza, S. J., Maryam, B., & Tamour, F. A. (2025). Social media's role in the 2024 Pakistani elections: An agenda-setting perspective. ACAD Journal of Social Sciences, 4(2), 1679–1683. Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. Penguin Press. Rafiq-uz-Zaman, M. (2022). Redesign for 21st-Century Skills: Preparing learners for a rapidly changing workforce. Journal of Business Insight and Innovation, 1(2), 89–102. Rafiq-uz-Zaman, M. (2023). The impact of digital literacy on students' learning outcomes: A comprehensive review. Inverge Journal of Social Sciences, 2(2), 194–205. https://doi.org/10.63544/ijss.v2i2.210 Rafiq-uz-Zaman, M., Bukhari, S. T., Malik, N., Rehman, L., & Qamar, A. H. (2025). Gender differences in the use and challenges of breakthrough technology in higher education: Evidence from Punjab. The Critical Review of Social Sciences Studies, 3(3), 1056–1073. https://doi.org/10.59075/hpdvq714 Rafiq-uz-Zaman, M., Khalid, N., & Susanto, E. (2025). Addressing environmental and social challenges: A mixed-method study on the education and inclusion of eunuchs in South Punjab, Pakistan. Social Science Review Archives, 3(1), 284–299. https://doi.org/10.70670/sra.v3i1.311 Rafiq-uz-Zaman, M., Shih, Y.-H., & Akomodi, J. O. (2026). Integrating emotional intelligence and AI-driven learning in higher education: Implications for student well-being and university HR policies. The Study of Religion and History, 4(1), 1–24. https://doi.org/10.63163/srh300 Rafiq-uz-Zaman, M., & Asif, M. (2026). Mechanisms of exclusion: Power, structure, and the persistence of gender inequality. Qualitative Research Journal for Social Studies, 3(1), 690–703. https://doi.org/10.63878/qrjs921 Riasat, Z., Hussain, S., & Rasheed, M. (2025). [Title needed]. [Journal name needed]. Sunstein, C. R. (2017). #Republic: Divided democracy in the age of social media. Princeton University Press. Tufekci, Z. (2015). Algorithmic harms beyond Facebook and Google: Emergent challenges of computational agency. Colorado Technology Law Journal, 13, 203–218.
Copyright (c) 2026 Fatima Shahid, Laraib Amir, Ali Bhadur https://creativecommons.org/licenses/by-nc-sa/4.0
Psychological Distress and Suicidal Ideation among Emerging Adults of University of Gujrat
Emerging adulthood represents a developmental window of heightened susceptibility to psychological distress and suicidal ideation. The present cross-sectional study examined the differential predictive utility of depression, anxiety, and stress in relation to suicidal ideation among 274 emerging adults (aged 18–25 years) enrolled at the University of Gujrat, Pakistan. Participants completed the Depression, Anxiety, and Stress Scale-21 (DASS-21) and the Suicidal Behaviours Questionnaire-Revised (SBQ-R). Bivariate analyses revealed significant positive correlations between all three distress dimensions and suicidal ideation, with depression demonstrating the strongest association (r = .462, p < .01). However, multiple regression analysis identified depression as the sole significant unique predictor of suicidal ideation (β = [insert β], p < .001), with anxiety and stress failing to contribute independent predictive variance when depression was controlled. Additionally, individuals classified in the high suicidal ideation risk group (SBQ-R ≥ 7) exhibited significantly greater levels of depression, anxiety, and stress relative to the low-risk group. These findings highlight the primacy of depressive symptomatology in understanding and predicting suicidal ideation among Pakistani university students. Implications for campus-based mental health screening and targeted intervention are discussed. References American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders (5th ed., text rev.). https://doi.org/10.1176/appi.books.9780890425787 Attia, M., Ibrahim, F. A., Elsady, M. A., Khorkhash, M. K., Rizk, M. A., Shah, J., & Amer, S. A. (2022). Cognitive, emotional, physical, and behavioral stress-related symptoms and coping strategies among university students during the third wave of COVID-19 pandemic. Frontiers in Psychiatry, 13, 933981. https://doi.org/10.3389/fpsyt.2022.933981 Bentley, K. H., Franklin, J. C., Ribeiro, J. D., Kleiman, E. M., Fox, K. R., & Nock, M. K. (2016). Anxiety and its disorders as risk factors for suicidal thoughts and behaviors: A meta-analytic review. Clinical Psychology Review, 43, 30–46. https://doi.org/10.1016/j.cpr.2015.11.008 Bibi, A., Blackwell, S. E., & Margraf, J. (2021). Mental health, suicidal ideation, and experience of bullying among university students in Pakistan. Journal of Health Psychology, 26(8), 1185–1196. https://doi.org/10.1177/1359105319869819 Brás, M., Martins, C., Nunes, C., Jesus, S. N., Madeira, A. R., & Carmo, C. (2025). Reasons for living and depressive symptomatology in young adults with and without suicide attempts: A moderated mediation approach. Frontiers in Psychiatry, 15, 1443894. https://doi.org/10.3389/fpsyt.2024.1443894 Fatima, S., & Raazia, A. U. (2025). Mood and anxiety symptoms, psychological distress, and life satisfaction: Differential associations between patients with anxiety and depression. Applied Psychology Review, 4(2), 67–87. https://doi.org/10.32350/apr.42.04 Han, K., Ji, L., Chen, C., Hou, B., Ren, D., Yuan, F., Liu, L., Bi, Y., Guo, Z., Wu, N., Feng, M., Su, K., Wang, C., Yang, F., Wu, X., Li, X., Liu, C., Zuo, Z., Zhang, R., Yi, Z., … He, G. (2022). College students' screening early warning factors in identification of suicide risk. Frontiers in Genetics, 13, 977007. https://doi.org/10.3389/fgene.2022.977007 Henry, J. D., & Crawford, J. R. (2005). The short-form version of the Depression Anxiety Stress Scales (DASS‑21): Construct validity and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 44(2), 227–239. https://doi.org/10.1348/014466505X29657 Hochberg, Z. E., & Konner, M. (2020). Emerging adulthood, a pre-adult life-history stage. Frontiers in Endocrinology, 10, 918. https://doi.org/10.3389/fendo.2019.00918 Jiazhi, S., Caixia, C., Lamei, G., & Jian, Z. (2025). The relationship between physical activity and depression, anxiety, and stress in college students: A mediating effect of diet. Frontiers in Nutrition, 12, 1611906. https://doi.org/10.3389/fnut.2025.1611906 Kapfhammer, H.-P. (2006). Somatic symptoms in depression. Dialogues in Clinical Neuroscience, 8(2), 227–239. https://doi.org/10.31887/DCNS.2006.8.2/hpkapfhammer Khan, M. N., Akhtar, P., Ijaz, S., & Waqas, A. (2021). Prevalence of depressive symptoms among university students in Pakistan: A systematic review and meta-analysis. Frontiers in Public Health, 8, 603357. https://doi.org/10.3389/fpubh.2020.603357 Kumar, S., Singh, G., Kumar, A., & Giri, S. K. (2025). Stress among research scholars: Causes, coping strategies and implications for policy reform. Annals of Neurosciences, 33(1), 123–130. https://doi.org/10.1177/09727531251315236 Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the Depression Anxiety Stress Scales (2nd ed.). Psychology Foundation. Mastorci, F., Lazzeri, M. F. L., Vassalle, C., & Pingitore, A. (2024). The transition from childhood to adolescence: Between health and vulnerability. Children, 11(8), 989. https://doi.org/10.3390/children11080989 Mayo Clinic. (2022). Depression (major depressive disorder). https://www.mayoclinic.org/diseases-conditions/depression/symptoms-causes/syc-20356007 McLafferty, M., Brown, N., McHugh, R., Ward, C., Stevenson, A., McBride, L., Brady, J., Bjourson, A. J., O'Neill, S. M., Walsh, C. P., & Murray, E. K. (2021). Depression, anxiety and suicidal behaviour among college students: Comparisons pre-COVID‑19 and during the pandemic. Psychiatry Research Communications, 1(2), 100012. https://doi.org/10.1016/j.psycom.2021.100012 Motillon-Toudic, C., Walter, M., Séguin, M., Carrier, J. D., Berrouiguet, S., & Lemey, C. (2022). Social isolation and suicide risk: Literature review and perspectives. European Psychiatry, 65(1), e65. https://doi.org/10.1192/j.eurpsy.2022.2320 Musfara, D. D., Widiyawati, W., & Fitrianur, W. L. (2024). Depression, anxiety, stress correlated with suicide idea on students of the faculty of health. Jurnal Ners dan Kebidanan, 11(1), 49–56. Nakao, M., Shirotsuki, K., & Sugaya, N. (2021). Cognitive-behavioral therapy for management of mental health and stress-related disorders: Recent advances in techniques and technologies. BioPsychoSocial Medicine, 15(1), 16. https://doi.org/10.1186/s13030-021-00219-w National Institute of Mental Health. (2024). Depression. U.S. Department of Health and Human Services, National Institutes of Health. https://www.nimh.nih.gov/health/publications/depression Naveed, S., Waqas, A., Aedma, K. K., Afzaal, T., & Majeed, M. H. (2019). Association of bullying experiences with depressive symptoms and psychosocial functioning among school-going children and adolescents. BMC Research Notes, 12(1), 198. https://doi.org/10.1186/s13104-019-4236-x Ng, P. Y. N., Yang, S., & Chiu, R. (2024). Features of emerging adulthood, perceived stress and life satisfaction in Hong Kong emerging adults. Current Psychology, 43(23), 20394–20406. https://doi.org/10.1007/s12144-024-05811-1 Osman, A., Bagge, C. L., Gutierrez, P. M., Konick, L. C., Kopper, B. A., & Barrios, F. X. (2001). The Suicidal Behaviors Questionnaire‑Revised (SBQ‑R): Validation with clinical and nonclinical samples. Assessment, 8(4), 443–454. https://doi.org/10.1177/107319110100800409 Pradubkham, T., Klangpraphan, J., Tangtrakuladul, P., Taengthonglang, C., Saramunee, K., & Phimarn, W. (2026). Prevalence of depression, anxiety, stress, and suicidal ideation among pharmacy students: An updated systematic review and meta-analysis. International Journal of Environmental Research and Public Health, 23(2), 155. https://doi.org/10.3390/ijerph23020155 Ribeiro, J. D., Huang, X., Fox, K. R., & Franklin, J. C. (2018). Depression and hopelessness as risk factors for suicide ideation, attempts and death: Meta-analysis of longitudinal studies. The British Journal of Psychiatry, 212(5), 279–286. https://doi.org/10.1192/bjp.2018.27 Van Orden, K. A., Witte, T. K., Cukrowicz, K. C., Braithwaite, S. R., Selby, E. A., & Joiner, T. E., Jr. (2010). The interpersonal theory of suicide. Psychological Review, 117(2), 575–600. https://doi.org/10.1037/a0018697 Vidović, S., Kotromanović, S., & Pogorelić, Z. (2024). Depression, anxiety, and stress symptoms among students in Croatia during the COVID‑19 pandemic: A systematic review. Journal of Clinical Medicine, 13(20), 6240. https://doi.org/10.3390/jcm13206240 World Health Organization. (2025). Depressive disorder (depression). https://www.who.int/news-room/fact-sheets/detail/depression Zhang, J., Liu, Y., & Sun, L. (2017). Psychological strain and suicidal ideation: A comparison between Chinese and US college students. Psychiatry Research, 255, 256–262. https://doi.org/10.1016/j.psychres.2017.05.046
Copyright (c) 2026 Noreena Kausar, Samia, Areej Arshad https://creativecommons.org/licenses/by-nc-sa/4.0
Underdiagnosed and Overlooked: A Community-Based Study of Autism Spectrum Disorder Prevalence and Screening Outcomes Among 4–11-Year-Old Children in Gujrat, Pakistan
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition with increasing global prevalence estimates. However, community-based epidemiological data from low- and middle-income countries, including Pakistan, remain critically scarce, contributing to widespread underdiagnosis and delayed intervention. This study aimed to estimate the screening prevalence of ASD traits among children aged 4–11 years in Gujrat, Pakistan, and to examine potential gender-based differences in screening outcomes. A quantitative cross-sectional research design was employed. A sample of 1,000 children (491 boys, 509 girls) aged 4–11 years was recruited from public mainstream schools, private mainstream schools, and special education centers in Gujrat using a stratified convenience sampling approach. Screening for autistic traits was conducted using the Childhood Autism Spectrum Test (CAST), a validated 37-item parent-report instrument. Data were analyzed using descriptive statistics and chi-square tests of independence. Based on the established CAST cutoff score (≥15), 11.0% (n = 110) of the total sample screened positive for clinically significant autistic traits. Gender-wise analysis revealed that 10.2% of boys (n = 50) and 11.8% of girls (n = 60) fell within the at-risk range. A chi-square test indicated no statistically significant association between gender and screening outcome, χ²(1, N = 1,000) = 0.647, p = .421. A significant association was observed between institution type and screening outcome, with special education centers demonstrating a higher proportion of positive screens (17.4%) compared to mainstream schools (p = .033). The findings reveal a substantial proportion of children in Gujrat exhibit elevated autistic traits warranting comprehensive diagnostic assessment. The absence of significant gender disparity underscores the importance of universal screening irrespective of sex. These results highlight an urgent need for scalable community-based screening programs and enhanced diagnostic services in Pakistan. References American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596 Centers for Disease Control and Prevention. (2023). Autism and developmental disabilities monitoring (ADDM) network surveillance report. U.S. Department of Health and Human Services. Dawson, G., Rogers, S., Munson, J., Smith, M., Winter, J., Greenson, J., Donaldson, A., & Varley, J. (2010). Randomized, controlled trial of an intervention for toddlers with autism: The Early Start Denver Model. Pediatrics, 125(1), e17–e23. https://doi.org/10.1542/peds.2009-0958 Elsabbagh, M., Divan, G., Koh, Y. J., Kim, Y. S., Kauchali, S., Marcín, C., Montiel-Nava, C., Patel, V., Paula, C. S., Wang, C., Yasamy, M. T., & Fombonne, E. (2012). Global prevalence of autism and other pervasive developmental disorders. Autism Research, 5(3), 160–179. https://doi.org/10.1002/aur.239 Hallmayer, J., Cleveland, S., Torres, A., Phillips, J., Cohen, B., Torigoe, T., Miller, J., Fedele, A., Collins, J., Smith, K., Lotspeich, L., Croen, L. A., Ozonoff, S., Lajonchere, C., Grether, J. K., & Risch, N. (2011). Genetic heritability and shared environmental factors among twin pairs with autism. Archives of General Psychiatry, 68(11), 1095–1102. https://doi.org/10.1001/archgenpsychiatry.2011.76 Hossain, M. D., Ahmed, H. U., Jalal Uddin, M. M., Chowdhury, W. A., Iqbal, M. S., Kabir, R. I., Chowdhury, I. A., Aftab, A., Datta, P. G., Rabbani, M. G., & Hossain, S. W. (2017). Autism spectrum disorders (ASD) in South Asia: A systematic review. BMC Psychiatry, 17(1), 281. https://doi.org/10.1186/s12888-017-1440-x Imran, N., Chaudry, M. R., Azeem, M. W., Bhatti, M. R., & Choudhary, Z. I. (2011). A survey of autism knowledge and attitudes among healthcare professionals in Lahore, Pakistan. BMC Pediatrics, 11, 107. https://doi.org/10.1186/1471-2431-11-107 Kim, Y. S., Leventhal, B. L., Koh, Y. J., Fombonne, E., Laska, E., Lim, E. C., Cheon, K. A., Kim, S. J., Kim, Y. K., Lee, H., Song, D. H., & Grinker, R. R. (2011). Prevalence of autism spectrum disorders in a total population sample. American Journal of Psychiatry, 168(9), 904–912. https://doi.org/10.1176/appi.ajp.2011.10101532 Lai, M. C., Lombardo, M. V., Ruigrok, A. N., Chakrabarti, B., Auyeung, B., Szatmari, P., Happé, F., & Baron-Cohen, S. (2017). Quantifying and exploring camouflaging in men and women with autism. Autism, 21(6), 690–702. https://doi.org/10.1177/1362361316671012 Levin, K. A. (2006). Study design III: Cross-sectional studies. Evidence-Based Dentistry, 7(1), 24–25. https://doi.org/10.1038/sj.ebd.6400375 Scott, F. J., Baron-Cohen, S., Bolton, P., & Brayne, C. (2002). The CAST (Childhood Asperger Syndrome Test): Preliminary development of a UK screen for mainstream primary school-age children. Autism, 6(1), 9–31. https://doi.org/10.1177/1362361302006001003 Williams, J., Scott, F., Stott, C., Allison, C., Bolton, P., Baron-Cohen, S., & Brayne, C. (2008). The CAST (Childhood Asperger Syndrome Test): Test accuracy. Autism, 12(1), 45–68. https://doi.org/10.1177/1362361307084466 World Health Organization. (2023). Autism spectrum disorders. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders World Medical Association. (2013). World Medical Association declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA, 310(20), 2191–2194. https://doi.org/10.1001/jama.2013.281053 Zwaigenbaum, L., Bauman, M. L., Choueiri, R., Kasari, C., Carter, A., Granpeesheh, D., Mailloux, Z., Newschaffer, C., Robins, D., Roley, S. S., Wagner, S., & Wetherby, A. (2015). Early intervention for children with autism spectrum disorder under 3 years of age: Recommendations for practice and research. Pediatrics, 136(Suppl 1), S60–S81. https://doi.org/10.1542/peds.2014-3667E
Copyright (c) 2026 Saima Riaz, Khadija Saeed, Sahira Dilawaiz https://creativecommons.org/licenses/by-nc-sa/4.0
Green Finance as a Catalyst for Sustainable Performance: The Mediating Effects of Green Innovation and Green Capabilities and the Moderating role of stakeholder pressure
This study examined the role of green finance in enhancing sustainable performance, with a focus on the mediating effects of green innovation and green capabilities and the moderating role of stakeholder pressure. The study adopted a quantitative research design and collected data from 320 respondents working in manufacturing and service sector firms in Pakistan. Structural equation modelling (SEM) was applied to test the proposed relationships. The findings indicated that green finance exerted a significant positive effect on sustainable performance (β = 0.42, p < 0.001). Green innovation (β = 0.31, p < 0.001) and green capabilities (β = 0.36, p < 0.001) also showed significant positive effects on sustainable performance. Mediation analysis revealed that green innovation (β = 0.19, p < 0.001) and green capabilities (β = 0.22, p < 0.001) partially mediated the relationship between green finance and sustainable performance. Stakeholder pressure significantly moderated this relationship (β = 0.27, p < 0.01), strengthening the positive impact of green finance under higher levels of external pressure. The results emphasized that financial investment in environmental initiatives contributed more effectively to sustainability outcomes when supported by innovation, organizational capabilities, and stakeholder engagement. The study provided theoretical and practical implications for enhancing sustainability strategies in organizations. References Ahmed, Z., Zhang, B., & Cary, M. (2023). Linking green finance and sustainable development: Evidence from emerging economies. Environmental Science and Pollution Research, 30, 45678–45690. https://doi.org/10.1007/s11356-023-25678-9 Anwar, S. U., Xu, J., Yuan, P. Z., Su, K., Rehman, S. U., & Hameed, M. (2024). Green entrepreneurial orientation and environmental performance. Scientific Reports, 14, 30266. https://doi.org/10.1038/s41598-024-81885-y Bal, E., & Karibek, M. (2026). Green finance and sustainability performance: The moderating role of stakeholder pressure. Istanbul Gelisim University Journal of Social Sciences, 12(3), 1343–1356. https://doi.org/10.17336/igusbd.1792228 Bano, S., Rafiq-uz-Zaman, M., & Khalid, N. (2024). Assessing health and environmental risks: Educational awareness on plastic usage and solid waste disposal in Bahawalpur. Journal of Asian Development Studies, 13(3), 917–929. https://doi.org/10.62345/jads.2024.13.3.75 Bashir, M. F., Ma, B., Shahbaz, M., & Vo, X. V. (2024). Unveiling the role of green finance in environmental sustainability. Journal of Cleaner Production, 420, 138345. https://doi.org/10.1016/j.jclepro.2024.138345 Batool, F., Mohsin, M., & Alwadi, B. M. (2025). Green innovation and environmental performance: The moderating roles of governance and policy. World, 6(1), 29. https://doi.org/10.3390/world6010029 Chen, X., et al. (2026). Green innovation and ESG performance: The mediating role of dynamic capabilities. Development and Sustainability in Economics and Finance, 9, 100113. https://doi.org/10.1016/j.dsef.2025.100113 Chen, Y. S., & Chang, C. H. (2023). The determinants of green innovation and firm performance. Business Strategy and the Environment, 32(4), 1987–2001. https://doi.org/10.1002/bse.3210 Darsono, D., Hersugondo, H., Yuniawan, A., & Latan, H. (2026). Green finance and sustainable performance: The mediating roles of green innovation and green capabilities and the moderating effect of stakeholder pressure. Business Strategy and Development, 9(2). https://doi.org/10.1002/bsd2.70317 Gurler, H. E., Kaya, A., Bilmiş, A. N. S., & Durmaz, Y. (2025). Stakeholder pressure and green innovation: A meta-analytic exploration. Brain and Behavior, 15(9), e70840. https://doi.org/10.1002/brb3.70840 Huang, Y., Chen, X., & Zhu, Q. (2023). Green innovation and environmental performance nexus. Technological Forecasting and Social Change, 189, 122345. https://doi.org/10.1016/j.techfore.2023.122345 Islam, M. F., Hossain, M. I., Rashed, M., & Rahman, M. N. (2025). Circular economy and green innovation for sustainable performance. Global Journal of Flexible Systems Management. https://doi.org/10.1007/s40171-025-00469-5 Jillani, H., Chaudhry, M. N., Zahid, H., & Iqbal, M. N. (2024). The mediating role of stakeholders on green banking practices and performance. PLOS ONE, 19(5), e0300585. https://doi.org/10.1371/journal.pone.0300585 Khalid, N., Rafiq-uz-Zaman, M., Tahira, W., & Maqbool, M. (2024). Solid waste and environmental sustainability: Educational approaches to managing urban waste in Bahawalpur city. Journal of Climate and Community Development, 3(2), 155–170. https://doi.org/10.5281/zenodo.16875300 Khan, H., Rehman, A., & Malik, M. F. (2024). Green finance and sustainable growth: Evidence from developing economies. Sustainability, 16(2), 987. https://doi.org/10.3390/su16020987 Li, X., Zhang, Y., & Sun, H. (2023). Financial development and green innovation. Finance Research Letters, 52, 103456. https://doi.org/10.1016/j.frl.2023.103456 Li, Y., et al. (2025). Green finance and green innovation: Moderating role of ESG. Research in International Business and Finance, 79, 103056. https://doi.org/10.1016/j.ribaf.2025.103056 Liu, G., & Xie, R. (2025). Green finance and green technology innovation nexus. Finance Research Letters. https://doi.org/10.1016/j.frl.2025.108827 Liu, Y., Kumar, S., Liu, H., Li, S., & Zhou, Z. (2025). ESG performance, digital transformation, and green innovation. Humanities and Social Sciences Communications, 12, 1739. https://doi.org/10.1038/s41599-025-06027-9 Masood, M., Shehryar, Q., Hussain, N., & Zafar, S. (2025). Green finance, corporate governance, and sustainable performance. Center for Management Science Research, 3(3), 943–959. Mukarram, S. S., Saleem, F., Alomair, A., & Al Naim, A. S. (2025). Knowledge management and sustainable innovation for green finance: Evidence from Asia. Humanities and Social Sciences Communications, 12, 1742. https://doi.org/10.1038/s41599-025-06022-0 Rafiq-uz-Zaman, M., Faridi, M. Z., & Hussain, R. M. (2025a). Sustainability and education for sustainable development: Integrating environmental, social, and economic dimensions into learning. Journal of Applied Linguistics and TESOL, 8(4), 386–401. https://doi.org/10.63878/jalt1480 Rafiq-uz-Zaman, M., Khalid, N., & Shafi, S. (2024a). Historical analysis of environmental degradation in Pakistan: A narrative review. Global Political Review, 9(4), 24–35. https://doi.org/10.31703/gpr.2024(IX-IV).03 Rafiq-uz-Zaman, M., Khalid, N., Faridi, M. Z., & Khan, Z. A. (2024b). Smog mitigation and climate resilience in Pakistan: A policy-centric review of strategies and challenges. Social Sciences Spectrum, 3(4), 302–317. https://doi.org/10.71085/sss.03.04.175 Rafiq-uz-Zaman, M., Malik, N., & Bano, S. (2025b). Learning to innovate: WhatsApp groups as grassroots innovation ecosystems among micro-entrepreneurs in emerging markets. Journal of Asian Development Studies, 14(1), 1854–1862. https://doi.org/10.62345/jads.2025.14.1.47 Rehman, S. U., Kraus, S., Shah, S. A., Khanin, D., & Mahto, R. V. (2024). Analyzing stakeholder pressure and environmental strategy. Journal of Business Research, 168, 114223. https://doi.org/10.1016/j.jbusres.2023.114223 Sikandar, S. M., Ali, S. M., Hassan, Z., & Muhideen, S. (2026). Modelling stakeholder theory through corporate green innovation. Humanities and Social Sciences Communications, 13, 385. https://doi.org/10.1038/s41599-026-06580-x Singh, S. K., Del Giudice, M., Chierici, R., & Graziano, D. (2024). Green innovation and environmental performance. Business Strategy and the Environment, 33(1), 120–134. https://doi.org/10.1002/bse.3301 Taghizadeh-Hesary, F., & Yoshino, N. (2023). Sustainable solutions for green financing. Finance Research Letters, 49, 102876. https://doi.org/10.1016/j.frl.2022.102876 Tripopsakul, S. (2025). ESG practices, green innovation, and financial performance: Panel evidence from ASEAN firms. Journal of Risk and Financial Management, 18(8), 467. https://doi.org/10.3390/jrfm18080467 Ullah, S., Zaefarian, G., & Ullah, F. (2023). How stakeholder pressure influences sustainability. Journal of Business Ethics, 185, 45–62. https://doi.org/10.1007/s10551-022-05012-3 Widyantoro, T., Rusmanto, T., Warganegara, D. L., & Furinto, A. F. (2025). Enhancing green innovation and financial performance: The role of stakeholder pressures and green dynamic capabilities. Frontiers in Climate, 7. https://doi.org/10.3389/fclim.2025.1599894 Zhao, X., Liu, Y., & Chen, H. (2024). Sustainable performance and innovation nexus. Journal of Environmental Management, 345, 118567. https://doi.org/10.1016/j.jenvman.2024.118567 Zhou, G., Luo, S., & Chen, Z. (2023). Stakeholder engagement and sustainability performance. Sustainability Accounting, Management and Policy Journal, 14(6), 1456–1475. https://doi.org/10.1108/SAMPJ-05-2022-0234
Copyright (c) 2026 Mamoona Akram, Saeed Ahmed, Najia Batool https://creativecommons.org/licenses/by-nc-sa/4.0