JOURNAL OF SOCIAL SCIENCES DEVELOPMENT

DIGITAL CAPABILITIES AND INNOVATION PERFORMANCE IN PAKISTAN: THE ROLE OF EMPLOYEE ENGAGEMENT

Muhammad Usman, Inam Ullah Khan, Umar Farooq — Sat, 02 May 2026 00:00:00 +0000

The increasing pace of technological advancement and globalization has compelled organizations to develop strong digital capabilities to remain competitive in today's business environment. Digital capabilities refer to an organization's ability to acquire, integrate, and utilize digital technologies, resources, and competencies to improve business processes and create value. The study examines how digital capabilities (Cloud Computing Adoption (CCA), Cybersecurity Capability (CC), AI-based Decision Support Systems (ADSS), and Digital Transformation (DT) affect the Innovation Performance (IP) in organizations in Pakistan. The research uses quantitative method, and 350 employees were the subjects. Data was analyzed using PLS-SEM and examined with mediation of Employee Engagement (EE) and moderation of Organizational Digital Culture (ODC). All digital capabilities were found to positively influence innovation performance both directly and indirectly, via employee engagement. Organizational digital culture plays significant moderating role between employee engagement & innovative performance. The results indicate that technological integration should go hand-in-hand with human-centered engagement and positive digital culture to maximize innovative outcomes.

FAMILY CONFLICT, EMOTIONAL REGULATION, SOCIAL SUPPORT & TREATMENT ADHERENCE IN ADULTS WITH SUBSTANCE USE DISORDER

Kousar Tariq, Shagufta Bibi, Muhammad Luqman Khan — Tue, 05 May 2026 00:00:00 +0000

The substance use disorder (SUD) represents a significant psychological and public health issue that adversely impacts the individuals' emotional well- being, familial relationships, and treatment outcomes. This study aimed to investigate the connections between social support, emotional regulation, family conflict, and treatment adherence in adults with the substance use disorder, particularly emphasizing mediating role of social support. Also, variations based on marital status were examined. The sample comprised 200 adult males diagnosed with substance use disorder, recruited through convenience sampling from rehabilitation centers and treatment facilities. Data collection involved standardized self-report instruments, including the Multidimensional Scale of Perceived Social Support (MSPSS), Emotion Regulation Questionnaire (ERQ), Family Conflict Scale (FCS) & Medication Adherence Rating Scale (MARS-10). Analysis of data was conducted using the descriptive statistics, Pearson product-moment correlation, independent sample t-test & mediation analysis via SPSS. The results indicated significant positive correlations amid social support, emotional regulation & treatment adherence, while family conflict exhibited significant negative correlations with these variables.

THE IMPACT OF ARTIFICIAL INTELLIGENCE TOOLS USAGE ON UNIVERSITY STUDENTS’ ACADEMIC INTEGRITY AND PERFORMANCE

Hunaiza Sabir, Shazia Malik — Fri, 08 May 2026 00:00:00 +0000

The widespread use of AI tools among university students has created both opportunities and challenges in higher education. As a result, students are increasingly integrating AI tools into their learning processes to support coursework, assignments, and exam preparation. In this research, impacts of use of AI applications on academic integrity and academic performance of PhD Education and MPhil Education students enrolled at University of the Punjab were explored. The research adopted a quantitative correlational design in which a sample of 200 postgraduate students was selected through convenience sampling technique. Data were collected using standardized questionnaire comprising 44 questions, which had a reliability index of the Cronbach Alpha = .85. Data analysis techniques used included descriptive statistics, correlation, regression, t-test & ANOVA. The findings revealed that students used AI technology such as ChatGPT, Grammarly, DeepSeek, and QuillBot to assist their writing and research processes. Regression analysis showed that both were positively and significantly predicted by the use of AI. Thus, this study therefore advocates for urgent actions on the part of universities to establish ethical policies, raise awareness & provide training on the AI usage.

ALGORITHMIC TRANSPARENCY, PERCEIVED FAIRNESS & EMPLOYEE TRUST IN AI-DRIVEN HR DECISIONS: A MEDIATION MODEL

Muhammad Farhan Khan, Irfan Ullah Khan — Thu, 14 May 2026 00:00:00 +0000

The algorithmic transparency in AI-driven HR decisions helps employees understand how decisions are made, reducing uncertainty and increasing perceptions of procedural fairness. Perceived fairness acts as a key mediator by translating the transparent AI processes into stronger employee trust in automated recruitment, evaluation, promotion, and reward decisions. This study examines whether algorithmic transparency builds employee trust in AI-driven HR decisions directly or indirectly through perceived fairness. Drawing on organizational justice theory and trust-in-automation theory, a cross-sectional survey of 322 mid-to-senior managers at the multinational corporations in Pakistan was analyzed using Hayes' PROCESS Macro (Model 4) with 5,000 bootstrap resamples. Transparency was positively associated with both trust (β = 0.217, p < .001) and perceived fairness (β = 0.351, p < .001), and fairness was positively associated with trust (β = 0.295, p < .001). The indirect effect of transparency on trust through fairness was significant (β = 0.103, 95% CI (0.067, 0.142), with the direct effect remaining significant, signifying partial mediation. Results show transparency alone is insufficient to secure the employee trust; its impact depends on whether decisions are perceived as fair, with the implications for designing more trustworthy AI- driven HR systems.

AI-TECHNOLOGY TRUST AS MEDIATOR IN LINKING PERCEIVED CHANGES IN HR FUNCTIONS AND EMPLOYEE ADOPTION INTENTIONS

Muhammad Irfan, Muhammad Ilyas — Mon, 18 May 2026 00:00:00 +0000

The study explores how perceived changes in human resource (HR) function relate to employee intentions to adopt artificial intelligence (AI) in the workplace in context of multinational companies (MNCs) in Pakistan and how trust in AI technology mediates this relationship. A quantitative, cross- sectional design was employed and data was analyzed using the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of the Technology (UTAUT), to attain desired outcomes. Mayer (1995) integrative trust model and organizational justice theory as constructs. The results of statistical analysis conducted using SPSS and Hayes PROCESS (Model 4) indicated that perceived changes in HR functions statistically significantly affect the intention to adopt AI technology by employee and the employee's perception of AI-technology trust. Moreover, paths between the perceived HR function changes, adoption intentions are partially mediated by trust in the AI-technology. The results show that technological implementation is not enough for system acceptance; building affective trust depending on the perceived algorithmic ability, benevolence as well as procedural integrity is vital for reducing vulnerability & increasing continued use in AI-supported HRM systems.