Pakistan Journal of Commerce and Social Sciences
Mission Statement Pakistan Journal of Commerce and Social Sciences (PJCSS) is a peer reviewed journal started in 2008 with the mission of providing high quality scientific content to academic researchers and business practitioners. It focuses to provide intellectually stimulating forum where researchers can share their ideas, experiments, commerce related themes and topics in a friendly, supportive and thought provoking environment. The editorial board of PJCSS is committed to promote the journal as one of the leading and globally reputable essential reading in contemporary commerce during the next five years to come.
Building Digital Bonds: The Impact of AI-Driven Personalization on Customer Experience and AI Relationship Quality
This study aims to examine the impact of AI-driven personalization on AI-enabled customer experience and perceived AI relationship quality. It further investigates the mediating roles of trust in AI and perceived personal relevance, as well as the moderating effects of privacy concern and technology readiness within an integrated conceptual framework. A quantitative, cross-sectional research design was employed. Data were collected from 330 users who had prior experience with at least one of three specified AI-enabled digital platform categories: e-commerce recommendation platforms (e.g., online retail sites), streaming services (e.g., video or music platforms), and fintech applications (e.g., digital banking or payment apps). Respondents were screened using platform-specific filter questions to reduce heterogeneity. The proposed model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS. Reliability, validity, mediation, and moderation effects were evaluated using bootstrapping techniques. To address potential common method bias arising from single-source self-reported data, Harman's Single-Factor test was conducted. The test confirmed that no single factor accounted for the majority of variance, suggesting that CMB does not critically threaten the validity of the findings. The main finding is that AI-driven personalization significantly enhances AI-enabled customer experience (β = 0.684, p < 0.001), with Trust in AI emerging as the primary psychological mediator of both experiential and relational outcomes. Perceived personal relevance provided a complementary mediation pathway. Privacy concern and technology readiness acted as modest boundary conditions on the personalization–mediator relationships. Additionally, privacy concern and technology readiness were found to act as boundary conditions that modestly moderated the personalization–mediator relationships, consistent with Privacy Calculus Theory and Technology Readiness Theory respectively. This study provides a comprehensive model integrating experiential, relational, and individual-difference perspectives in AI-enabled services. The findings offer theoretical advancement and practical insights for designing transparent, user-centric, and trust-enhancing AI personalization strategies.
AI-driven personalization, AI-enabled customer experience, perceived AI relationship quality, trust in AI, perceived personal relevance, privacy concerns, technology readiness.
Copyright (c) 2026 Pakistan Journal of Commerce and Social Sciences
Climate Resilience, Green Finance and Sustainable Economic Development: An Evidence from High and Upper-Middle-Income Countries
The study provides a comprehensive analysis of the impact of green finance and climate resilience on sustainable economic development. The annual data utilized by the study covers 38 high and upper-middle-income countries during the time-period of 2011 and 2019. This study employs an augmented system GMM estimator to address the issues of endogeneity, dynamic dependence, and simultaneity. The findings show that both climate resilience and green finance have combined and significant impact on sustainable economic development. The results of the study clearly indicate that renewable energy transitions, clean and green infrastructure, and low carbon technologies has significant positive contribution in sustainable development. Green investments offer a pathway for environmental improvements, encourages innovation, and reallocation of financial flows on the way to sustainable sectors. The findings of this study show that there is a significant negative relation between green finance and climate resilience. The findings of the study suggest that both climate resilience and green finance are significant important, but their combined impact should be managed carefully. The study implies that nations with high investment in green finance and climate control projects can enjoy relatively more sustainable economic development. Policymakers should account for fiscal capacity, avoid policies which overlapped and prioritize the integration except duplication.
climate resilience, green finance, sustainable economic development, ND-GAIN INDEX.
Environmental Performance in the Artificial Intelligence Era: Green HRM Mediation and Green Culture Moderation with Importance-Performance Map Analysis
This study aims to investigate the function of artificial intelligence (AI) in supporting green human resource management (GHRM) practices for improving environmental performance, as well as exploring the reinforcing impact of green culture based on dynamic capability theory insights. Data collection was conducted using structured questionnaires administered to 467 managers working in the palm oil business in West Sumatra, Indonesia with a convenience sampling approach. Partial Least Squares–Structural Equation Modelling (PLS-SEM) and importance–performance map analysis (IPMA) was used to investigate the data. The results suggest that AI significantly improves environmental performance and GHRM, while GHRM also positively affects environmental performance. GHRM mediates the relationship between AI and environmental performance. Green culture strengthens the AI effect on environmental performance but does not significantly moderate the AI and GHRM connection, nor does it produce a significant moderate mediation effect. The proposed model demonstrates that GHRM has moderate explanatory power (R2 = 0.610) and environmental performance has weak explanatory power (R2 = 0.290). AI has a moderate effect on GHRM (f2 = 0.313), whereas the remaining direct effects and other interactions are relatively small. In addition, the model exhibits positive predictive relevance for GHRM (Q2 = 0.07) and environmental performance (Q2 = 0.08), although its predictive capability remains relatively limited. The findings highlight the strategic role of AI in enhancing environmental performance both direct and indirect effect via GHRM. A strong green culture further amplifies this effect. This research adds to the integration of AI, GHRM, and green culture within the dynamic capability perspective and provides practical insights relevant to managers and policymakers, to optimize AI-driven HR practices and organizational culture for improved environmental performance.
AI, green HRM, green culture, environmental performance, palm oil industry, dynamic capability theory.
Climate Finance as a Catalyst for Energy Security Transitions: The Conditional Role of Natural-Resource Dependence in Developing Economies
This study examines whether international climate finance advances electricity-sector energy-security transitions in developing economies and whether natural-resource dependence conditions that relationship. Using country-year panel data for the period 2000-2023, across 118 developing economies, the paper estimates two-way fixed-effects models, moderation models, nonlinear specifications, robustness checks, marginal effects, and three-dimensional response surfaces. The results indicate that climate finance is most robustly associated with electricity-sector outcomes: higher finance exposure is linked to stronger renewable-electricity performance, lower fossil-electricity dependence, and lower energy-import exposure. However, the finance-transition relationship is conditional rather than automatic. Natural-resource rents weaken the marginal effect of climate finance, indicating that fossil-fuel lock-in and resource-rent incentives can reduce the effectiveness of external finance. Governance quality also matters because climate finance must pass through public investment systems, utilities, regulators, procurement agencies, and monitoring institutions before it becomes implemented transition capacity. The results indicate that climate finance is positively associated with renewable electricity (beta = 0.5884, p < 0.10). The study contributes to recent green-development debates by linking climate finance to energy security, locating resource dependence as a boundary condition, and presenting coefficient, marginal-effect, and surface-response evidence that can guide policy design.
climate finance, energy security, renewable electricity, fossil-fuel lock-in, natural resource rents, governance quality, developing economies
Economic Growth and Environmental Sustainability in Romania: The Role of Renewable Energy and Carbon Emissions
Carbon emissions constitute one of the most urgent environmental challenges of the 21st century. This study investigates the relationship between economic growth and carbon emissions in Romania, an emerging economy in Eastern Europe. Drawing on annual time series data from 1991 to 2024, the analysis explores how carbon emissions are influenced by key factors such as GDP growth and renewable energy consumption. To examine the long-term interactions among these variables, the Autoregressive Distributed Lag (ARDL) Bounds testing approach for co-integration was employed. The empirical results reveal a significant long-run relationship among the variables. Specifically, economic growth exerts a statistically significant positive impact on carbon emissions, highlighting the environmental cost of Romania’s economic expansion. In contrast, renewable energy consumption demonstrates a statistically significant negative impact on carbon emissions, which shows that with the increase in the renewable energy consumption the carbon emissions would decrease considerably in Romania. This study contributes to the literature by providing one of the few country-specific ARDL co-integration analyses of Romania over the post-transition period (1992–2024), simultaneously examining the long-run effects of economic growth and renewable energy consumption on carbon emissions to generate evidence tailored to Romania’s sustainable development pathway. These findings carry important policy implications like achieving a sustainable balance between economic development and environmental protection. It is imperative to enhance investment in and the adoption of renewable energy technologies; also there is need of decarbonizing transport through using green transport or reducing fossil fuel use in residential heating in Romania.
economic growth, carbon emissions, renewable energy, environmental sustainability, Romania.
Generative Artificial Intelligence in Tourism: The Roles of Perceived Usefulness, Trust in AI-Generated Content and Perceived AI Control among International Tourists
The rapid rise of generative artificial intelligence (GenAI) is fundamentally changing the way tourists search for information, plan their trips, experience their trips, and share information after their trips. While the Technology Acceptance Model (TAM) considers perceived usefulness and perceived ease of use as central factors, this study extends the theoretical framework by incorporating two additional constructs: trust in AI-generated content and perceived AI control. This study examines GenAI usage behavior using survey data from 541 international tourists in Ho Chi Minh City. The PLS-SEM results show that perceived usefulness is the strongest driver of GenAI usage behavior and the main antecedent of trust in AI-generated content. Trust has a significant but secondary effect, functioning as a credibility mechanism that strengthens tourists’ confidence in useful AI-generated travel support. At the same time, perceived AI control has a direct and independent effect, highlighting the importance of tourists’ ability to guide, adjust, and redirect AI-generated recommendations. Notably, perceived ease of use does not directly influence usage behavior or trust, although it has a weak positive effect on perceived usefulness. This study refines TAM by showing that perceived usefulness remains the dominant driver of GenAI usage behavior, while trust serves as a complementary credibility mechanism and perceived AI control acts as an independent usage driver. Practically, it suggests that tourism GenAI applications should prioritize concrete travel value, controllability, and locally credible information for international tourists.
AI adoption, GenAI usage behavior, generative AI, trust in AI-generated content, perceived AI control, ˙perceived usefulness.
Short- and Long-Run Drivers of CO₂ Emissions in the Top Ten CO₂ -Emitting Economies: Evidence from Decoupling and Nonlinear Dynamics
This study employs a multi-stage STIRPAT-based framework by combining decoupling analysis, cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model and panel threshold model to examine economic growth (GDP), population (POP), energy efficiency (EE), decarbonization (DEC) and renewable energy (REN) as drivers of CO2 emissions in the top ten CO₂-emitting economies from 1990 to 2024 using World Bank data. The decoupling analysis reveals heterogeneous performance, either strong decoupling or weak decoupling during the sampled period. No country falls within the expansive coupling or negative decoupling categories. The CS-ARDL estimates show that GDP consistently raises emissions both in the short and long run, while POP exerts significant environmental pressure in the long run. In contrast, EE, DEC and REN reduce emissions, with their effects becoming stronger over time. In the panel threshold regression, EE (output per unit of energy used) and DEC (reciprocal of the CO2 produced per unit of energy used) are used as threshold variables. The threshold analysis confirms significant nonlinear effects of EE and DEC on carbon emissions, with threshold values estimated at 2.904 and 0.219, respectively. The findings reveal that economic growth increases CO₂ emissions across all regimes; however, the magnitude of this effect declines after the threshold levels are exceeded, indicating that higher EE and stronger decarbonization efforts help mitigate environmental degradation. Additionally, POP effects vary across regimes, suggesting the presence of heterogeneous environmental impacts under different efficiency and decarbonization conditions. Overall, the findings demonstrate that combining decoupling analysis with short- and long-run elasticity estimation and nonlinear threshold modelling provides a coherent and policy-relevant understanding of emissions dynamics in major polluting economies.
CO₂ emissions, energy efficiency, decarbonization, renewable energy, economic growth.
From Bonding to Backlash: The Interplay of Social Comparison, Secrecy, and Jealousy in Organizational Politics
This study discusses the possible effects of good professional relationships on emotional and behavioral behaviors, such as political activity, social comparison, and jealousy. The total number of participants across four research studies is 1,094, and a between-subjects experimental design has been used. The participants were randomly assigned to a setting in which either a close coworker or an acquaintance of these coworkers was either very successful, routinely appreciated, or received concrete rewards. The study compared non-destructive and destructive social comparison, as well as politically-oriented workplace intentions, with depression and tested for mediation and moderation using ANOVA and regression-based methods. An interesting result was that jealousy was even more intense when they saw extraordinary success among close work friends than when they saw ordinary success or material gain. This relationship was mediated by social comparison, with secrecy further intensifying it. Furthermore, feelings of jealousy were found to increase politically directed self-serving behavior within the workplace. The results generally show that stronger interpersonal relationships are associated with greater emotional and behavioral responses in a politically oriented workplace. Including emotions adds a fresh perspective to the study of organizational politics and shows how achievement and appreciation might, in organizational contexts, unintentionally compromise peer relationships, hence highlighting the necessity of openness and the just sharing of appreciation.
organizational politics, workplace friendship, social comparison, jealousy, secrecy, workplace friendships, political behavior.
Predictive AI Crowd-Management Messaging and Its Influence on Perceived Control, Stress Reduction, Temporal Satisfaction, and Destination Loyalty
This study investigates the influence of predictive AI crowd-management messaging on tourists’ psychological and behavioral responses in crowded destinations. Drawing on the Stimulus–Organism–Response (S–O–R) framework, the study examines how predictive and data-driven crowd-management messages shape perceived control, stress reduction, temporal satisfaction, and destination loyalty. A quantitative cross-sectional design was employed using purposive sampling. Data were collected from 265 tourists who had recently visited destinations offering digital or smart tourism information services. The respondents were selected from tourism destinations utilizing AI-enabled crowd-management and informational systems. Established measurement scales adopted from prior studies were used, and data were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS. The findings reveal that predictive AI crowd-management messaging significantly enhances tourists’ perceived control, which subsequently reduces stress and improves temporal satisfaction. Temporal satisfaction emerged as a strong predictor of destination loyalty. Furthermore, the results support a serial mediation mechanism in which predictive AI crowd-management messaging enhances perceived control, leading to stress reduction, which subsequently increases temporal satisfaction and ultimately strengthens destination loyalty. The study extends smart tourism literature by integrating AI-based crowd-management communication with tourists’ cognitive, emotional, and evaluative processes. The findings suggest that destinations can leverage predictive AI communication to enhance tourists’ sense of control, reduce stress, improve time-related experiences, and foster long-term destination loyalty.
Predictive AI, crowd management, perceived control, stress reduction, temporal satisfaction, destination loyalty.
Enhancing Online Impulse Buying through Artificial Intelligence Stimuli and Social Stimuli in Generation Z: The Mediating Role of Brand Trust
The purpose of this research is to investigate and explain the extent to which artificial intelligence stimuli and social behavior determinants influence online impulse buying in Pakistan’s e-retail sector positioning brand trust as central pathway mechanism among generation Z. Drawing on the integrated Stimulus-Organism-Response (SOR) framework and Technology Acceptance Model (TAM), study specified three stimuli factors AI exposure, AI accuracy perception, and recommended product, while buying impulsiveness and subjective norms were incorporated as behavioral constructs to predict impulse buying behavior mediated by the brand trust. Data were collected from generation Z and broader adult cohort via cross-sectional Google Survey yielding 508 valid responses. Partial-Least-Square, structural equation modeling (SmartPLS-4.0) was used to test the hypothesized relationship of the variables. Findings of the study revealed AI accuracy perception and subjective norms exhibited strong mediating effect through brand trust on impulse buying as compared to AI exposure, recommended product, and buying impulsiveness. Overall, the model explained 57.0% effect on brand trust and 35.8% was recorded on impulse buying with satisfactory predictive relevance and effect size. AI accuracy perception and subjective norms are strong calibration with brand trust; where effect size indicates larger trust leads to influence impulse buying significantly.
AI recommendation accuracy, brand trust, online impulse buying, e-commerce, generation Z, subjective norms, consumer impulsiveness, Pakistan.
Copyright (c) 2026 Pakistan Journal of Commerce and Social Sciences (ISSN 1997-8553)
Digital Trade and Global Environmental Quality: The Moderating Role of Energy Justice
The potential of digital trade (DTE) and energy justice (EJ) to support environmental quality requires in-depth exploration because the environmental gains of DTE can be compromised in economies where EJ is not ensured. This study explores the environmental effects of DTE and EJ on ecological footprint (EF) utilizing panel data from 147 economies from 2005 to 2023. The empirical results are estimated using panel data estimators namely fixed effects, random effects, the system generalized method of moments (GMM) and the method of moments quantile regression (MMQR). The GMM estimates suggest that DTE exerts a positive and significant influence on the environment. However, the MMQR results demonstrate that the effect of DTE on EF varies in sign and magnitude across quantiles. The positive effect is observed in median and higher quantiles while the negative effect is noted in lower quantiles. Finally, the results suggest a moderating role of EJ in the environmental effect of DTE. That is, the interactive effect of DT with EJ exerts a significantly positive effect on environmental quality. This finding suggests that ensuring EJ in home economies strengthens the environmental benefits of digital trade integration. These findings offer important policy implications for advancing digitalization strategies along with ensuring EJ to promote global environmental sustainability.
Digital trade, energy justice, environmental quality, resource endowment, ecological footprint.
Board Characteristics, Firm Performance, and Institutional Ownership: Evidence from Listed Companies of Pakistan
This study endeavors to scrutinize the impact of board characteristics on firm performance directly as well as through the moderating influence of institutional ownership. Tobin’ Q and market-to-book ratio are the proxies of firm performance as dependent variable. The analytical approach involves unbalanced panel data comprising 883 firm year observations of 75 textile manufacturing firms listed on Pakistan Stock Exchange from 2012 – 2023 by using fixed effect regression and system GMM estimation techniques through STATA software. Notably, findings indicate that board size and female directors demonstrate significant positive influence, whereas, outside directors and director ownership shows significant negative influence on firm performance. Furthermore, findings also indicate that institutional ownership has a significant positive moderating influence on the relationship between board characteristics and firm performance. This contribution to the scholarly literature provides certain important theoretical insights and practical implications for practitioners and policy makers.
Board characteristics, ownership structure, institutional ownership, firm performance, Pakistan Stock Exchange.
Drivers and Barriers of ChatGPT Adoption in Higher Education: Insights from Multiple Theories
This study aims to discuss the driving forces and obstacles that influence the usage of ChatGPT among higher education postgraduate research scholars. The data analysis was conducted using the partial least squares structural equation modeling (PLS-SEM) with the consideration of 436 valid responses which were collected from post graduate research scholars in Pakistan. The study relies on the behavioral reasoning theory (BRT), the technology acceptance model (TAM-2), and the theory of innovation resistance (IRT) to explain determinants that facilitate and hinder the use of technology. The findings confirmed that perceived ease of use, perceived usefulness, and social influence (reason for) are positively related. Tradition, risk, and usage barriers (reasons against), on the other hand, have a negative relationship with the intention of the users to use ChatGPT. These results indicate that adoption drivers and resistance factors influence simultaneously the usage of ChatGPT in academic context. In addition to integrating three prominent theoretical perspectives on technology adoption and resistance, this study contributes to the literature on AI-based technology adoption and advances understanding of the behavioral mechanisms underlying ChatGPT usage. This study also has practical implications to the institutions of higher learning and policymakers on how to effectively and responsibly integrate the use of generative AI tools in higher learning institutions.
Behavioral reasoning theory, technology acceptance model, innovation resistance theory, perceived usefulness, perceived ease of use, social influence, attitude towards ChatGPT, intention to use ChatGPT.
The impact of Foreign Direct Investment, Institutional Quality, and Industrialization on Carbon Emissions: Evidence from High-Income and Upper-Middle-Income Countries
This study investigates the relationship between foreign direct investment (FDI), institutional quality, industrialization, and carbon emissions across 48 high-income and 37 upper-middle-income countries for the years 2002 to 2022 by employing panel quantile regression analysis using R software. The results show that inward FDI has increased pollution in high-income countries by the coefficient of 0.016 to 0.026 while it has reduced carbon emissions in upper-middle-income countries by the coefficient of -0.012 to 0.01. In outward FDI, although it is expected that upper-middle income countries will end up with low carbon emissions, the results show that carbon emissions increase in these countries by the coefficient of -0.025 to 0.08. Industrialization has significantly raised pollution in both groups, while institutional quality has a positive impact in high-income countries and a negative influence in upper-middle-income nations, implying the mixed impact of good governance in environmental management. The findings highlight the dual effect of FDI on carbon emissions, indicating that its environmental impact varies according to the extent of policy interventions, i.e. carbon taxation, environmental regulation, designed to balance economic growth with environmental protection. The results offer valuable insights for companies and policymakers seeking to align economic growth with environmental sustainability across different stages of economic development.
Foreign direct investment, carbon emissions, industrialization, institutional quality.
Digital Trade Integration and the Green Transition: The Moderating Role of Energy Equity in a Global Panel Analysis
In recent years, digital trade integration has emerged as a potentially important factor influencing the global green transition through the cross-border diffusion of renewable technologies and smart energy systems. Nevertheless, its usefulness in expediting the adoption of renewable energy is still unclear, especially at a time when the world is facing increasing electricity needs to support digital infrastructure and address long-range energy inequities. This study examines whether the environmental effects of digital trade integration depend on energy equity using a balanced panel of 71 economies from 2002 to 2023. The analysis employs several panel econometric techniques, including fixed effects, FMOLS, DOLS, System GMM, and the Dumitrescu–Hurlin panel causality test. The findings indicate (i) a Granger-causality relationship between digital trade integration and the green transition; (ii) a significant positive interaction effect, suggesting a “justice threshold” where higher energy equity strengthens the impact of digital trade on renewable energy adoption; and (iii) much stronger synergies in the middle and low-income economies, which supports a leapfrog hypothesis. These outcomes indicate that digital trade may speed up the adoption of renewable energy in case of fair access to energy. To ensure that the global green transition occurring in digital trade systems is inclusive and just, the paper can give viable policy suggestions to the implementation of energy equity.
Digital trade integration, energy equity, green transition, renewable energy, financial development, natural resource rents.
Role of External Corporate Social Responsibility towards Task Performance: Unveiling Serial Mediation of Organizational Pride and Affective Commitment
The importance of CSR is undeniable—it serves as a powerful driver that boosts both employee performance and overall organizational success. Extensive research is found in literature on CSR and its several dynamics related to the performance. Therefore, the objective of the study is to investigate how employees’ external CSR perception influences the task performance of the employees. Based on the social identity theoretical lens, this study drives the research framework of CSR and performance with potential mediating effect of organizational pride and effective commitment. The data was collected from a sample of 372 employees working in private organizations of service sector. For data analysis, PLS-SEM was utilized which validates the hypothesized relationships between variables. The results of this study lend support for hypothesized model. Additionally, it is exhibited that organizational pride and affective commitment sequentially mediate the relationship between employee’s external CSR perception and task performance. The findings of this study contributed to the existing literature by explaining the CSR and task performance in the different context that has not been explored yet. Moreover, this study also discussed the robust theoretical contributions and practical implications of the results.
External CSR, task performance, organizational pride, affective commitment, service sector, Pakistan.
Equity Crowdfunding Success in Malaysia: The Role of Crowd Investors, Campaign Disclosure and Valuation Disclosure
This study examines the determinants of equity crowdfunding (ECF) campaign success in Malaysia through the lens of quality signaling theory and behavioral herding dynamics. Using a manually collected dataset of 335 completed campaigns launched on pitchIN, MyStartr, and AtaPlus between 2016 and 2025. The study investigates how firm-level and campaign-level signals influence fundraising outcomes in a regulated digital financing environment. Binary logistic regression is employed as the primary analytical method, with probit regression used for robustness testing. The findings show that the number of investors has a significant and positive relationship with campaign success, underscoring the importance of social proof and herding behavior in reducing information asymmetry. Valuation disclosure significantly increases the likelihood of success by enhancing transparency and investor confidence, while company age displays a negative effect, indicating investor preference for younger and growth-oriented ventures. In contrast, campaign duration and industry sector do not significant influence once credible signals are considered. The study contributes to the entrepreneurial finance literature by cooperatively modelling behavioral crowd signals and firm-level quality signals using real-market data from Malaysia, and offers practical insights for entrepreneurs, platform operators, and policymakers seeking to strengthen transparency, investor engagement, and digital financing effectiveness.
Equity crowdfunding, signaling theory, information asymmetry, campaign success, campaign duration, valuation disclosure, Malaysia.
Influence of Environmental Stimuli on Impulsive Buying Behavior in Online Livestream Commerce: The Moderating Role of Livestream Viewing Frequency and Livestream Shopping Experience
The impact of environmental factors on consumer impulsive buying behavior in the context of e-commerce live streaming: Role of celebrity endorsements and moderating effects of live streaming frequency and shopping experience This study examined the effect of environmental factors like perceived scarcity, perceived discount, time pressure, social pressure and celebrity endorsement on the emotional arousal of online consumers, which further affects their impulse buying. Additionally, the study shed light on the role of two emerging consumer behavioral variables, namely the frequency of watching live streaming videos and live streaming shopping experience. Based on a survey conducted from an online panel of 575 consumers, partial least squares structural equation modeling (PLS-SEM) was used for empirical verification. The results confirmed that the frequency of watching live streaming videos and live streaming shopping experience are significant moderators that decrease the influence of emotional arousal on impulse buying in a statistically significant manner. These results indicated the mediating role of emotional arousal towards the relationship between environmental factors and impulse buying, however consumers having a higher live streaming shopping experience and greater exposure to live streaming videos tend to be more rational, capable of learning and thereby refraining from their impulsive buying behavior. This contributes to a better understanding of how consumers learn to restrain their impulse buying in the era of e-commerce live streaming and sheds new light in the existing theories regarding online consumer behaviors in the livestream commerce context.
Impulsive buying, livestream viewing frequency, livestream shopping experience, e-commerce, emotional arousal, celebrity endorsement, social influence.
The Spillover Impact of Green HRM on Non-Green Outcomes in Logistics Industry: Mediating Role of Organization Pride and Moderating Role of Ethical Leadership Style and Psychological Empowerment
This study examines the direct and indirect effects of green human resource management (GHRM) on job satisfaction, with organizational pride as a mediator and ethical leadership and psychological empowerment as moderators. Data were collected in three waves from 308 respondents in Pakistan’s logistics industry, with hypotheses tested using PLS-SEM through SmartPLS. Findings reveal that GHRM positively influences employee job satisfaction, with organizational pride playing a significant mediating role. Ethical leadership further strengthens the GHRM-job satisfaction link by amplifying the positive effects of organizational pride, while psychological empowerment enhances the pride-satisfaction relationship, underscoring the importance of an empowering workplace culture. This research contributes to GHRM literature by addressing its less-discussed non-green outcomes, particularly in the logistics sector. By integrating organizational pride, ethical leadership, and psychological empowerment, the study provides a comprehensive understanding of factors influencing GHRM’s effectiveness. These insights help organizations balance sustainability goals with employee-centric approaches, offering actionable strategies to benchmark practices and gain a competitive edge in fostering both environmental responsibility and employee well-being. For policy makers, the findings suggest that promoting GHRM frameworks in logistic industries, particularly in the vulnerable developing countries not only advances environmental goals but also improves employees’ well-being.
Green HRM, job satisfaction, ethical leadership style, organizational pride, psychological empowerment, social exchange theory, logistic industry, Pakistan.
The Load Capacity Curve Hypothesis: Natural Resource Rent, Financial Inclusion, and the Pathways to Global Environmental Sustainability
The load capacity factor (LCF) hypothesis extends the environmental Kuznets curve (EKC) framework by incorporating both the demand and supply sides of natural resources. This study investigates the LCF hypothesis and the environmental impacts of the natural resources, financial inclusion, population density, and energy consumption on LCF globally and across income groups. The Driscoll-Kraay standard error approach is employed on the panel data from 1995 to 2021. For robustness analysis, the system GMM estimation approach is also utilized. The results reveal the validity of the LCF hypothesis. Natural resource rent negatively affects LCF across all panels except the low-income group, where an insignificant relationship is observed. Financial inclusion reveals mixed findings; it improves LCF in high-income and high-middle-income economies whereas reducing LCF in low-middle-income economies. Comparatively, financial inclusion measures reflect mixed effects. An increase in domestic credit and bank branches leads to environmental degradation by reducing LCF across all panels. The proliferation of ATMs tends to improve LCF in global, high-income, and upper-middle-income economies, whereas diminishing it in low-middle-income and low-income economies. This research suggests the importance of developing an inclusive financial system, along with adopting cleaner energy technologies to improve the load capacity of the planet.
Energy consumption, natural resource rent, financial inclusion, load capacity factor.
Copyright (c) 2025 Pakistan Journal of Commerce and Social Sciences (ISSN 1997-8553)
Do Institutional Investors Mitigate Costly Restructuring? Dynamic Evidence from the Globe
This research aims to comprehensively examine the impacts of various levels of the life cycle stages of firms (LCSF) on restructuring charges and to investigate the impact of institutional ownership on the correlation between LCSF and restructuring charges. This study employs panel data that is run using a two-step system GMM. The dataset covers the years 2000 to 2023 and consists of 7,570 observations of firm-year of non-utility and non-financial companies. The results show that the charges of restructuring have the propensity to rise (or fall) as a firm moves to either growth or maturity (or introduction or decline) stage. Also, under institutional ownership, a firm changing to growth or maturity (or introduction or decline) stage leads to a significant increase (or minor decrease) in restructuring charges. The information on the correlation between LCSF and restructuring charges will assist the investors in forecasting the alterations in the restructuring costs as firms cross the various stages of their life cycles. Moreover, the effects of institutional ownership on this relationship will be useful in informing investors on how to best invest in stocks. To the best of our knowledge, no previous study has investigated the effects of LCSF on restructuring charges and the moderating effect of institutional ownership in the relationship. This research paper is aimed at filling this gap and offering new information.
Restructuring charges, firm life cycle stages, institutional ownership, large firms, and small firms
The Impact of Netflix’s AI Powered Recommendation System on Consumers’ Behavioral Intentions
Current studies primarily focus on the recommender systems (RSs) through the algorithmic accuracy, and which insufficient to fully measure accurately the practical effectiveness of the RSs and understand user experience. There is an urge examine the dynamic interactions on the critical user context of "beyond accuracy" features such as diversity, novelty, and serendipity to understand RS’s value creation mechanism holistically. The aim of the study is to explore the multidimensional effects of key features (Stimuli) of artificial intelligence (AI)-RSs on consumer behavior (Response) based on the Stimulus-Organism-Response (S-O-R) theoretical framework which is a gap in the literature. The study was modeled four key features of RSs (accuracy, diversity, novelty, serendipity) as stimuli, user engagement, satisfaction, and perceived risk as organism (mediating constructs), and behavioral intentions as the response. Data was collected from 437 participants, and analyses were conducted using the covariance-based structural equation modeling (CB-SEM) by AMOS 24.0 and SPSS 25.0 statistical programs. The findings explains that the empirical assumptions of the S-O-R model were met to a high degree, successfully explaining 61% of the variance in behavioral intentions. Specifically, satisfaction and engagement have strongest positive effects on behavioral intentions. The findings suggest that the effectiveness of AI-RSs should no longer be evaluated solely through algorithmic accuracy, but rather through the dynamics of user-centered value creation (satisfaction, engagement, and risk management). Furthermore, serendipity have the strongest direct effect on engagement, highlighting the importance of “beyond-accuracy objectives” that trigger curiosity. Accuracy and diversity significantly and negatively reduce risk, demonstrating a critical role in increasing system trustworthiness. Contrary to the accuracy-diversity trade-off problem, a strong positive relationship exists between accuracy and diversity, suggesting that these multiple goals reinforce each other in the context of user perception. These results provide important theoretical and practical consequences for the design of multi-objective recommender systems (MORS).
AI-Powered Recommendation Systems, Accuracy, Novelty, Diversity, Serendipity, Engagement, Satisfaction, Perceived Risk, Netflix viewers, Türkiye.
Estimation of Parameters of the Beta-Extreme Value Distribution
In this research paper The Beta Extreme Value Type (III) distribution which is developed by Zafar and Aleem (2007) is considered and parameters are estimated by using moments of the Beta-Extreme Value (Type III) Distribution when the parameters ‘m’ & ‘n’ are real and moments of the Beta-Extreme Value (Type III) Distribution when the parameters ‘m’ & ‘n’ are integers and then a Comparison between rth moments about origin when parameters are ‘m’ & ‘n’ are real and when parameters are ‘m’ & ‘n’ are integers. At the end second method, method of Maximum Likelihood is used to estimate the unknown parameters of the Beta Extreme Value Type (III) distribution.
Copyright (c) 2008 Pakistan Journal of Commerce and Social Sciences (ISSN 1997-8553)
Burnout in Customer Service Representatives
The purpose and aim of this research was to (1) identify the factors that contributes towards job burnout in sales service representative (2) What are the relationships of these factors (3) To empirically test the relationships of the determinants relating to burnout in customer service representatives. Based on literature survey six different variables related to burnout were identified. The variables were (1) Emotional exhaustion.(2) Reduced personal accomplishment.(3) Job induced tension.(4) Job satisfaction.(5) Workload (6) Job satisfaction. Each of the variables contained 3 sub-variables. Five different hypotheses were developed and tested through techniques such as Z-test, F-test and regression analysis. The questionnaire administered for the study contained 15 questions including personal data. The subject was Moblink company customers sales service representative in Karachi.The valid sample size was 98 drawn through multi-cluster technique. Techniques such as measure of dispersion and measure of central tendencies were used for analyzing the data. Regression, Z-test, and F-test were used for testing the developed hypothesis. According to the respondents’ opinions, the reduced personal accomplishment had a high rating with a mean of 3.75 and job induced tension has the lowest mean of 3.58. The standard deviation of respondents’ opinions was highest for dimension depersonalization and least for dimension work load. This indicates that there is a high polarization of the respondents’ opinions on the dimension depersonalization moral and least on the dimension work load. The Skew nesses for all the dimensions were in negative except the determinants emotional exhaustion and workload. This indicates that the majority of respondents’ opinions on all the dimensions were below the mean except in the case of emotional exhaustion and workload. Five hypotheses were developed and tested: a) The hypothesis relating to low level of burnout in customers service representative was rejected. b) The hypothesis relating to no significant difference in the burnout levels of younger age group and older age group was accepted. c) The hypothesis relating to higher level of burnout in the single customers sales representatives as compared to married ones was accepted. d) Alternative hypothesis of relationship between independent variable “Job satisfaction” and dependent variable “Burnout”” was accepted. e) Alternative hypothesis of relationship between independent variable “Work load” and dependent variable “Burnout”” was accepted.
Education, Underemployment, and Job Satisfaction
Education is an effective vehicle for producing the required skills to maintain economic growth. The benefits of education range from human to economic, social and cultural. In Pakistan, there is significant rise in the average level of education, but over time, more and more workers incapable to use their educational background on the job. Supply of labor may have outstripped the demand of labor in some professions, and high qualified peoples taking job on low positions. Such underemployment/overeducation has not been fully explored in Pakistan. The theme of paper is “underemployment symbolizes an inefficient usage of human resources and lost output for society”. The research is based on case study on clerical workers of SNGPL. By comparing their educational backgrounds with their nature of job, this paper examines the impact of overeducation on job satisfaction. Our results show that underemployment/overeducation is correlated with higher level of job dissatisfaction, reduced job involvement, impaired co-worker relationship, and more emphasis on future aspirations.
Sui Northern Gas Pipeline Limited (SNGPL), Job satisfaction, Underemployment, overeducated clerical workers.
Growth and Efficiency of Small Scale Industry and its Impact on Economic Development of Sindh
The purpose of this study is to analyze the growth, efficiency, causes of sickness of small scale industry, emergence of entrepreneur and competencies of entrepreneurs at Larkana estate area of Sindh Province. The study examines the educational background of the entrepreneurs of small scale industry who are the helm of affairs and its impact on the growth of sales of the every year. Strong evidence emerges that owners of small industrial units are family concern and having a low educational background, lack of managerial knowledge and conservation-oriented attitude results in under utilization of capacity and low growth of units established every year. This research paper provides a survey of the theoretical and empirical literature relating to promote the small scale industry in the Larkana region. This study indicates effective policy measures to promote the small scale industry particularly in Larkana region and generally in Pakistan.
Small scale industry, Skilled entrepreneurs, Sindh, Larkana.
Dynamic Supply Response Analysis of Pakistani Rice Growers
Alternative specifications of model of supply response of Pakistani rice growers and their economic implications are considered in terms of the existences and nature of production lags, and the choice between expected price and gross returns as the preferred explanatory of producer's response to changing economic condition. The analysis indicates that there are lags which are due primarily to the difficulties and cost of rapid adjustment rather than to the time required to revise expectations. The statistical results were similar for the alternative specification of gross margins and prices as the economic decision available. However, the price elasticities derived using the gross margins specification were about a third of those using the prices specification. The gross margin specification yielded additional information in the form of yield and input cost elasticities.
Supply response analysis, Rice growers, Pakistan.
Problems and Challenges in Human Resource Management: A Case of Large Organization in Pakistan
This paper critically analyzes the work culture for a mainstream financial organization operating within Pakistan, while drawing a specific example to elucidate certain dilemmas that impede the potential growth for the financial sector and its constituent workforce, besides hampering the performance of the organizations. The case study is related to an organization in financial sector which conducts a Management Trainee Program with the purpose to select, train and develop a high-potential pool of talent into future leaders and fore-runners of the organization. This paper critically analyzes several inherent problems that face the successful implementation of the trainee program under the frameworks of various theories of organizational management. To solve these problems, this article presents a detailed diagnosis of the management shortcomings to improve the firm‟s corporate culture, work ethics and employee handling strategy and mechanism. Recommendations are also made to minimize the problems and maximize the success of the Management Trainee Program in the case study organization.
Human resource management, management trainee program, problems, challenges, motivation.
Working Capital Approaches and Firm’s Returns in Pakistan
This study investigates the relationship between the aggressive/conservative working capital policies for seventeen industrial groups of public limited companies listed at Karachi Stock Exchange for a period of 1998-2003. The ordinary least square regression model has been used to investigate into the relationship of working capital approaches and the returns of firms. The study found significant differences among their working capital investment and financing policies across different industries. Moreover, these significant differences are remarkably stable over the period of six years. The aggressive investment working capital policies are accompanied by aggressive working capital financing policies. Finally, we found a negative relationship between the profitability measures of firms and degree of aggressiveness of working capital investment and financing policies. The study would contribute a better understanding of working capital management policies in an emerging market like Pakistan.
Working capital, Aggressive working capital policy, Aggressive financing policy.
Determinants of Corporate Philanthropy in Pakistan
The importance of corporate philanthropy and its related philosophy of corporate social responsibility have captured the attention of researchers and humanitarian groups in WTO era. Corporate donations have been considered as a critical tool to improve corporate image in a highly competitive environment. This paper explores the determinants of corporate donations based on LSE-25 index companies over the five year period 2002-06. Multiple regression techniques have been used for gauging the determinants of corporate philanthropy after collecting data from audited financial reports of companies. The study is a pioneering attempt in measuring the determinants of philanthropy in corporate sector of Pakistan.
corporate philanthropy, charitable contributions, LSE-25, corporate donations.