Pakistan Journal of Commerce and Social Sciences (ISSN 1997-8553)
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Empowering Leadership Navigating the Employees Entrepreneurial Orientation Through Work Uncertainty: Evidence from Tourism and Hospitality Industry
Full text linkThis research investigates the impacts of empowering leadership (EL) on work uncertainty (WU) and employees entrepreneurial orientation (EO) and its dimensions (risk-taking, pro-activeness, and innovativeness). Furthermore, this study also exploring the intervening role of work uncertainty in the connection between empowering leadership and entrepreneurial orientation and its dimension. The data (n=271) were gathered from individuals employing in hospitality and tourism industry of Pakistan by utilizing a timelag research approach. Using AMOS software for data analysis, findings suggested that empowering leadership is meaningfully related with work uncertainty and individuals entrepreneurial orientation. Similarly, work uncertainty mediates the relationship between empowering leadership and entrepreneurial orientation and its dimensions. This study suggests that empowering leadership can be an effective tool for encouraging employees entrepreneurial orientation. Therefore, managers and leaders of hospitality and tourism sector, who aim to achieve employees entrepreneurial orientation need to induce empowering leadership in their organization. The article bridges the gap relating to factors and antecedents that impact individuals entrepreneurial orientation in a time lag research design. This research is one of the pioneer studies which examining, how empowered leadership affects entrepreneurial orientation, with employing work uncertainty as a mediating role. The practitioners of tourism and hospitality industry such as investors, managers, employees and other stakeholders, will find this study quite useful as well
Measuring the Long-run Effect of Economic Growth, Population Aging, and Unemployment on Carbon Emissions in South Asia
Full text linkDuring the last two decades, South Asia has faced extreme climate change events of heatwaves, floods, storms, droughts, and fires, affecting economies and millions of people. Meantime, the region has also experienced a notable change in economic growth, population aging, and unemployment rate. However, the carbon implications of these factors are still limited, and it requires further exploration to understand their association with carbon emissions for environmental sustainability. Thus, the prime aim of this study is to empirically evaluate the effect of economic growth, population aging, and unemployment on carbon emissions in South Asia by controlling trade and renewable energy. For this, panel data from 1996 to 2020 for Bangladesh, India, Nepal, Pakistan, and Sri Lanka have been used for empirical analysis. The study employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) estimation techniques using Stata and EViews software. Economic growth, population aging, and trade openness increase carbon emissions while unemployment and renewable energy reduce them. This study also confirms an inverted U-shaped association between income and carbon emissions in South Asia
Impact of Product Assortment, Perceived Service Quality, Website Quality, and Customer Reviews on Customer Happiness and Word of Mouth
Full text linkThe main aim of this paper focuses on examining the effect of website quality, product assortment, customer reviews, and perceived service quality on customer happiness and word of mouth. The data for this research was gathered from online shoppers of retail stores in United Arab Emirates. Data was analyzed using partial least square based structural equation modeling through SmartPLS software in order to verify research hypotheses and draw conclusions. The findings also showed that website quality, customer reviews and perceived service quality have positive effects on customer happiness and word of mouth. Finally, the results revealed that product assortment positively affects word of mouth, while its effect on customer happiness is insignificant. This research builds upon the existing literature by demonstrating the effect of selected factors on customer happiness and word of mouth, considering that only limited studies were conducted in the past about these variables in the Middle East region
Mediating role of AI adoption between the relationship of leadership vision, change management capability, competitive pressure, trading partnerships, and SME performance
Full text linkThis study investigates the critical drivers of artificial intelligence (AI) adoption in SMEs. The mediating role of AI adoption on the relationship between leadership vision, change management capability, competitive pressure, trading partnerships, and SME performance is also investigated. This research employs a quantitative methodology, collecting data through structured questionnaires from senior and middle-level managers of manufacturing SMEs in Pakistan. Data were analyzed using the software SmartPLS for partial least squares structural equation modeling (PLS-SEM). The results reveal that trading partnerships are the most critical drivers of AI adoption in SMEs within an emerging economy, followed by change management capabilities and leadership vision. These factors contribute to improving SME performance in competitive and resource-constrained markets, aligning with Sustainable Development Goal 9 (industry, innovation, and infrastructure). Additionally, AI adoption mediates the relationship between trading partnerships, competitive pressure, and SME performance. This research uncovers unique insights by integrating the technology-organization-environment (TOE) framework, Resource-based view theory, and diffusion of innovations theory simultaneously in a proposed research framework that tests the critical drivers of AI adoption in SMEs within an emerging economy
The Effects of Cause-Related Marketing on Consumer Repurchase Intentions Through Brand Resonance: Moderating Effects of News Articles and Advertising
Full text linkThe increasing reliance on news articles and advertising to communicate cause-related marketing (CRM) initiatives highlights a critical gap in understanding their effects on brand equity, especially post-natural disasters. This study investigates the role of brand resonance as a mediator and media coverage (news articles and advertising via newspapers) as a moderator in the relationship between CRM and consumer repurchase intention (CRI). Despite widespread discussions about the impact of paid media on brand equity, the intricate interactions between CRM message framing, the medium of dissemination, and their collective influence on brand resonance during crises still need to be fully explored. Utilizing attribution theory and signaling theory, this research aims to bridge these gaps by examining how different media types affect the effectiveness of CRM activities. This study used an accidental sampling technique to collect data from 410 respondents and applied PROCESS Macro v4.0 to test the research hypotheses. The findings extend the existing literature by providing empirical evidence on how CRM, when mediated by brand resonance and moderated by media coverage, shapes corporate reputation. This research not only deepens the theoretical understanding but also offers practical insights for optimizing media strategies to enhance brand resonance and consumer satisfaction in the aftermath of natural disasters
The Role of Digitalization in Driving Green Growth: A Global Panel Data Perspective
Full text linkThis paper analyzes the green growth (GG) effects of digitalization using panel data from 164 countries spanning the period from 1990 to 2023. The study uses four measures of digitalization: internet users, broadband, mobile cellular, and fixed telephone subscriptions. The empirical results are estimated employing pooled ordinary least squares, fixed effects, random effects, system generalized method of moments, and panel quantile regression estimation approaches. STATA software is used to analyze the data. The results suggest that the proliferation of digitalization measures tends to boost GG. The results based on principal component analysis also confirm the positive impact of digitalization on GG. Furthermore, the GG-improving influence of digitalization remains robust across all quantiles. The role of renewable energy also turns out to be conducive to improving GG prospects. However, the roles of financial development and trades are not robust in influencing GG. The GG effects of financial development vary from a positive influence at lower quantiles to a negative influence at higher quantiles. Conversely, the GG effect of trade varies from a negative influence at lower quantiles to a positive influence at higher quantiles
Unravelling Crash Risk Transmission: Cryptocurrency Impact on Stock Markets in G-7 and China
Full text linkIn this paper, we use the Empirical Bayes estimation and multiple linear regression approach to examine the impact of the top 5 cryptocurrencies’ crash risks on the G-7 and China equity markets’ crash risks. MATLAB was used to calculate the crash risks, while Stata software was employed for the econometric analysis. Three crash risk measures are used to validate the robustness of the results: (i) the relative frequency of the number of crash days in the market, (ii) the monthly returns’ skewness, and (iii) the down-to-up volatility. Our findings indicate that overall crash risks of the top 5 cryptocurrencies are positively related with G-7 and Chinese stock markets’ crash risk. This suggests that the crash risk transmits from the crypto to the equity markets and the crashes in crypto can serve as a predictor in the stock markets. Furthermore, there is a negative correlation between the historical crash risks of the G-7 stock market and the present crash risks of the same stock market. This suggests that past stock market crashes can serve as a predictive factor for assessing the current risk of a stock market crash
Translation of Green Supply Chain Management to Environmental Performance via Green Process Innovation and the Moderation of Managers’ Job Satisfaction and Top Management Commitment
Full text linkThis paper investigates the effects of green strategy and design (i.e., two important facets of green supply chain management) on firms’ environmental performance through the mediating role of green process innovation. In addition, the moderation of two management attitudes (managers’ job satisfaction and top management commitment) are tested as the boundary conditions of the proposed relationships. A time-lag design was used to collect data from 279 managers of 31 manufacturing firms in Jordan. SPSS and PROCESS macro were utilized to test hypothesized relationships. All hypothesized mediation and moderation relations were supported, except the moderation of top management commitment to the green design-green process innovation relationship. These findings provide managers with evidence to proactively implement and invest in green strategy and green design facets because such facets will not only positively affect their environmental performance but enhance other performances and help achieve a competitive advantage for the firm. Our findings expand the literature on green strategy and design facets. It is among the few studies that have explored the link between green strategy and environmental performance, the underlying process, and introducing two managerial attitudes (middle manager job satisfaction and top management commitment) as boundary conditions in a single study. The testimony from the Jordanian manufacturing sector is another unique contribution to this study
A Machine Learning Approach to Predict Bankruptcy in Chinese Companies with ESG Integration
Full text linkIn this scholarly investigation, we meticulously assess the effectiveness of Environmental, Social, and Governance (ESG) metrics in predicting financial hardship across a cohort of 3,111 publicly traded companies on the Chinese stock exchange from 2012-2022. This study employs Python software for comprehensive data analysis to process and interpret large datasets efficiently. Our empirical findings robustly validate that incorporating ESG metrics significantly enhances the predictive prowess of our model, thereby elevating precision in discerning instances of financial distress. A striking feature in the process is that the chance of incorrectly identifying the distressed or defaulting firms as sound business enterprises due to the implementation of ESG is impossible.
The foundation of our predictive model, bonded by a strong methodology, includes integrating various tools such as classical statistics methods and state-of-the-art new machine learning models. For a comparative analysis seven machine learning models have been employed, such as Logistic Regression, Decision Trees, Support Vector Machines, Random Forest, Naïve Bayes, AdaBoost, and Gradient Boosting. To interpret the results, three performance parameters have been used which are sensitivity (Se), Area Under the Curve (AUC), and F1 score. Among all the models Random Forest Model stands out as the most stable model, which shows 100% accuracy in all the parameters, with and without the inclusion of ESG Scores. The implications of our work also affect the market scene, making an impact through prospective investors, policymakers, and financial parties affiliated with the forefront companies. Additionally, the present contribution develops the existing literature on distress prediction, as it helps to understand which sustainability factors work best for a comprehensive analysis of the company\u27s problems
Examining Loyalty of Social Media Influencers - The Effects of Self-Disclosure and Credibility
Full text linkThis paper examines the mechanism by which followers become loyal to social media influencers. The study proposes that self-disclosure is a distinct element of influencer brands and has a positive effect on credibility, emotional attachment, and brand trust. A cross-sectional study was designed in which 341 social media users participated. Structural equation modelling (AMOS 22), was used to examine the relationships between variables. Results showed that self-disclosure had a positive relationship with credibility and emotional attachment while the brand trust was increased due to their credibility. Furthermore, it provided evidence of how emotional attachment toward the influencer\u27s brand led to loyalty towards influencer brand through trust. This study is pioneering attempt as it conceptualized the influencer brand’s self-disclosures and establishes a link between influencer credibility and followers™ conception of their brand. The findings offer valuable insights into developing effective influencer marketing strategies and enhancing influencer brand equity