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This paper aims to empirically examine the influence of macroeconomic and socioeconomic factors on improving financial inclusion in India, with a specific focus on two distinct indicators of financial inclusion.

This study has used a time-series data set covering the years 1996 to 2022, using a nonlinear autoregressive distributed lag methodology. This approach allows for the examination of both short- and long-run effects of key macroeconomic and socio-economic indicators, including GDP per capita growth, remittance inflows and the income share held by the lowest 20% of the population on the growth of two financial inclusion indicators: the number of commercial bank branches and ATMs per 100,000 adults.

Model-1 investigates how commercial bank branch growth affects financial inclusion. Positive remittance inflow growth and a rise in the income share of the bottom 20% both lead to increased financial inclusion in both the short and long term, with the effects being more pronounced in the long run. Conversely, negative effects of remittance inflow growth and a decline in GDP per capita growth lead to reduced financial inclusion, primarily affecting the long run. Focusing on ATM growth, Model-2 reveals that positive remittance inflow growth has the strongest impact on financial inclusion in the short term. While income share growth for the bottom 20% and GDP growth also positively influence financial inclusion, their effects become significant only in the long run. Conversely, a decline in GDP per capita growth hinders financial inclusion, primarily affecting the short run.

This study fills a gap in research on macroeconomic and socioeconomic factors influencing financial inclusion in India by examining the impact of GDP per capita growth, remittance inflows and the income share held by the lowest 20% of the population, an area relatively unexplored in the Indian context. Second, the study provides comprehensive distinct results for different financial inclusion indicators, offering valuable insights for policymakers. These findings are particularly relevant for policymakers working toward Sustainable Development Goal 8.10.1, as they can use the results to tailor policies that align with SDG objectives. Additionally, policymakers in other developing nations can benefit from this study’s findings to enhance financial inclusion in their respective countries.

This study aims to examine the influence of global and local structural factors on reducing poverty.

The research uses data spanning from 1996–2022 and uses the nonlinear autoregressive distributed lag model. This model allows for the assessment of the short and long-term effects of remittance inflow (RI) growth, control on corruption and employment rate (ER) on poverty reduction in India.

The research findings indicate that in the short run, an increase in international RIs, a higher control of corruption and a greater ERare associated with a decrease in poverty in India. Specifically, a positive change in RIs and control of corruption significantly reduces poverty, while an increase in the ERhas a substantial impact. However, in the long run, only a positive change in RIs and a higher control of corruption continue to significantly reduce poverty.

This study makes several significant contributions to the existing literature. First, it examines the simultaneous impact of three structural factors on poverty, offering insights into their combined long-term effects on the economy. Second, unlike previous studies, this research investigates the nonlinear effects on poverty, which is particularly relevant for developing nations. Lastly, this study aligns with the United Nations’ Sustainable Development Goal 1, which aims to end poverty in all its forms everywhere. The findings of this study are expected to assist Indian policymakers in formulating effective poverty eradication strategies and provide guidance for other developing nations facing similar challenges.

This study aims to investigate the impact of dividend policy on a firm’s participation in corporate social responsibility (CSR)-related activities in the context of Pakistani firms. Furthermore, the role of the board governance mechanism in dividend policy-CSR is investigated.

The study’s sample consists of 115 nonfinancial Pakistan Stock Exchange-listed firms from 2010 to 2021. A multidimensional financial method is used to assess the firm’s CSR engagement, and dividend policy is assessed using the dividend payout ratio and dividend yield. The authors used the fixed effect model and the random effect model to fulfill the study’s objectives. Furthermore, the system-generalized method of moment estimation technique is used to test the robustness of the result. In addition, the authors perform reverse causality analysis and investigate the effect of financial constraints on the dividend policy–CSR relationship.

The authors find that dividend policy has a significant positive impact on CSR. The authors also find that dividend policy is significantly positively associated with components of CSR, i.e. donation, employee welfare and research and development. Furthermore, the authors find that the board governance mechanism strengthens this positive relationship between dividend policy and CSR.

The government and authorities must mandate or at least encourage enterprises to pay dividends as doing so not only keeps shareholders happy but also encourages firms to make CSR initiatives to balance stakeholders. Furthermore, the regulator should take steps to strengthen the board governance structure as it strengthens the positive dividend policy–CSR relationship.

Although little previous research has focused on the CSR-dividend policy link, the authors believe that this is the first study to look at the influence of dividend policy on CSR and the moderating impact of board governance mechanisms in an emerging country, namely, Pakistan.

Mega-infrastructure development plans pave the way for policies to upgrade the infrastructure, environmental management and different aspects of locals’ well-being. These developmental dynamics can positively affect rural tourism including heritage sites destinations. The quality of life of local people can be linked to this positive developmental change through long-term and sustainable economic revitalization projects. In terms of this process, developing large-scale infrastructure and incorporating tourism sustainability can improve the quality of life-related to different dimensions that are critical to the community's well-being. Therefore, researchers have attempted to address this issue.

Data were collected between September and October 2020. The study sample size was the residents of Zhabagly village, including Zhabagaly, Abaiyl and 115 Railway settlements. Moreover, the residents were older than 18 years. A systematic random sampling technique was utilised to reach the targeted sample size and the researchers received 243 responses from the locals. Structural equation modelling (SEM) was used for analysis.

The findings from the structural equation modelling suggest that sustainable tourism increases due to the positive effect of mega-infrastructure development and positively impacts the locals' quality of life. Notably, no direct effect of mega-infrastructure development on quality of life reveals the pivotal role of sustainable tourism. Therefore, during the COVID-19 period, the dimensions of sustainable tourism – economic, market, socio-cultural and environmental – played a role in securing the positive impact of mega-infrastructure development on the locals’ quality of life.

This research highlighted the fact that when infrastructure projects are implemented to their full potential, they will generate sustainable tourism activities, provide eco-adventure activities, relax, treat signatories and boost the economy of all stakeholders. The study used AMOS to test the hypotheses. Qualitative research methods, including interviews with citizens, government officials and tourism managers, require further study.

The infrastructural development on a mega-scale means building an upscaling tourism ecosystem. This ecosystem is marked by the availability of drinking water, waste and energy management facilities that support the elevation of living material, community, health, safety and emotional well-being. It reflects the policy-level implications for future Belt and Road initiatives (BRIs). The tourism industry's resilience during COVID-19 has practical lessons for other industries.

Large-scale infrastructure construction must create favourable conditions for the rapid development of tourism. The availability of clean water, waste and energy management facilities contributes to the food production, social cohesion, physical and mental health and general well-being of the ecosystem. This is one of the few studies that used sustainable tourism as a mediator between the impact of large infrastructure projects and their impact on the quality of life of locals during the COVID-19 pandemic. Aksu-Zhabagly, a World Heritage Site in Kazakhstan, was the site of this field study.

This study explores the factors that contribute to fan loyalty for a losing sports team, with a specific focus on the Karachi Kings in the Pakistan Super League. The research aims to uncover the motives that influence fans’ unwavering support for a team that consistently underperforms.

A qualitative research design was utilized, involving semi-structured interviews with a diverse sample of Karachi Kings fans. Data were analyzed using grounded theory principles to uncover key themes. This approach allowed for an in-depth understanding of the underlying psychological and sociocultural factors. Grounded theory was chosen to systematically generate insights from data, particularly because fan loyalty in current contexts remains underexplored.

The research identified five main themes that influence fan loyalty: identity integration, emotional attachment, cognitive coherence, behavioral consistency and social connectivity. Fans exhibited a strong psychological connection to the Karachi Kings, fueled by regional pride, shared experiences and a sense of community. The findings emphasize the importance of creating a strong fan community and nurturing emotional bonds through consistent engagement and shared experiences.

This study demonstrated how psychological and sociocultural factors combine to sustain support for a losing team. It broadens the understanding of sports fandom by emphasizing that fan loyalty extends beyond a team’s success or failure, being deeply rooted in identity, emotions and social connections. This research offers a nuanced view of fan behavior in a non-Western context and provides valuable insights for developing marketing strategies and fostering community engagement in sports management.

This paper examines the impact of green human resource management (GHRM) practices on employees’ pro-environmental behavior in Pakistan’s hospitality industry. It attempts to identify the critical success factors involved in promoting GHRM and pro-environmental behaviors at the workplace using Interpretive Structural Modeling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) approaches. Later, based on the ability-motivation-opportunity (AMO) model, the study also categorizes the identified critical factors into three categories: ability, motivation and opportunity.

The ISM approach was applied to determine the contextual relationship among the identified critical success factors responsible for promoting GHRM. MICMAC, a structural technique to analyze and validate the ISM-based model, was used to determine the autonomous, dependent, linkage and independent factors based on expert opinions and judgments. The goal was to determine the role of GHRM in transforming the pro-environmental behavior of employees.

The study’s findings show that the proper integration of effective GHRM practices significantly impacts pro-environmental employee behavior. The hierarchical model introduces innovation in the field of GHRM because ISM-based hierarchical models are flexible enough to include or exclude practices according to the green organizational objectives in the hospitality industry within the context of Pakistan. The results offer a comprehensive illustration of the importance of GHRM practices in facilitating, encouraging and promoting employees to take green initiatives and achieve business sustainability.

The study utilizes the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique to identify key success criteria for GHRM, while the innovative approaches of ISM and MICMAC techniques were used to investigate employee pro-environmental behaviors. This novel method gives GHRM research an analytical direction by providing an organized framework for evaluating the impact of GHRM initiatives on environmental outcomes. Additionally, by focusing on developed economies rather than emerging ones, our study within Pakistan’s hospitality sector fills a knowledge vacuum on the dynamics of GHRM in a developing nation.

This study highlights the significance of managers in the hospitality sector serving as role models for implementing GHRM practices to encourage pro environmental behavior among employees. Prioritizing green structural capital, establishing standard environmentally friendly criteria for hiring and evaluating prospective employees and initiating green projects to promote a psychologically green environment are some of the key recommendations. Improving environmental performance, employee satisfaction and loyalty in the hotel industry requires constant communication, training and employee participation in sustainability decision-making.

The GHRM practices have been extensively discussed by academics and researchers. However, there is a notable absence of discussion on the key factors that play a role in transforming employees’ attitudes and behaviors.

This research examines the influence of the digital voice of consumers (DVoC) on the resilience of supply chains (SCR) within the renewable energy sector. The main goal is to identify and highlight the crucial aspects that enable the examination of this impact.

A comprehensive literature analysis was performed utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach to ascertain pertinent factors. This research utilizes a comprehensive methodology that merges interpretive structural modeling (ISM) with Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis to assess the discovered variables.

The study identified 16 factors that contribute to both DVoC and SCR. Key influential factors include top management support, collaboration, feedback influence and flexibility. These factors play a significant role in enhancing SCR by facilitating better adaptation and response to disruptions.

The study is confined to the renewable energy sector and may lack generalizability to other businesses without additional validation. Subsequent studies ought to investigate the implementation of these findings across various industrial contexts to enhance comprehension of DVoC’s influence on SCR.

This study presents a new integrated framework for comprehending the function of DVoC in improving SCR. It presents significant practical consequences for stakeholders in the renewable energy sector, such as researchers, regulators, manufacturers and consumers, highlighting the necessity for a resilient and flexible supply chain.

Nanofluids are used in technology, engineering processes and thermal exchanges. In thermal transfer processing, these are used for the smooth transportation of heat and mass through various mechanisms. In the current investigation, we have examined multiple effects like activation energy thermal radiation, magnetic field, external heat source and especially slippery effects on a bioconvective Casson nanofluid flow through a stretching cylinder.

Several studies used non-Newtonian fluid models to study blood flow in the cardiovascular system. In our research, Lewis numbers for bioconvection and the influence of important parameters, such as Brownian diffusion and thermophoresis effects, are also considered. This system is developed as a partial differential equation for the mathematical treatment. Well-defined similarity transformations convert partial differential equation systems into ordinary differential equations. The resultant system is then numerically solved using the bvp4c built-in function of MATLAB.

After utilizing the numerical approach to the system of ordinary differential equations (ODEs), the results are generated in the form of graphs and tables. These generated results show a suitable accuracy rate compared to the previous results. The consequence of various parameters under the assumed boundary conditions on the temperature, motile microorganisms, concentration and velocity profiles are discussed in detail. The velocity profile decreases as the Magnetic and Reynolds number increases. The temperature profile exhibits increasing behavior for the Brownian motion and thermal radiation count augmentation. The concentration profile decreased on greater inputs of the Schmidt number and magnetic effect. The density of motile microorganisms decreases for the increased value of the bio-convective Lewis number.

The numerical analysis of the flow problem is addressed using graphical results and tabular data; our reported results are refined and novel based on available literature. This method is useful for addressing such fluidic flow efficiently.

This study aims to examine the impact of using ChatGPT on the Halal tourism experience. It examines the relationships among Halal-friendly travel motivations and satisfaction, revisit intention and electronic word-of-mouth (e-WoM) while testing the moderating effect of ChatGPT on the relationship between satisfaction and revisit intention.

This study employed a quantitative methodology. Using purposive sampling techniques, it approached about 800 tourists (from November 2023 to January 2024) from several halal tourism destinations in Indonesia. A total of 395 usable surveys were analyzed to test the relationships and moderation effects by SEM.

The study indicates that Halal-friendly travel motivations positively impact Muslim tourist satisfaction, which in turn influences e-WoM and revisit intention. Importantly, ChatGPT significantly moderates the relationship between satisfaction and revisit intention, thereby strengthening tourist loyalty for those using the AI tool.

The study’s findings provide practical guidelines for halal tourism providers to enhance Halal-compliant services and incorporate ChatGPT as an AI tool to boost Muslim travelers’ satisfaction, drive e-WoM and increase revisit intentions. AI technology gives Halal tourism companies an advantage in offering customized, immediate support, which leads to Muslim visitors becoming loyal.

The study fills a significant gap in the Halal tourism literature by examining AI’s impact on the market. It expands the Expectation-Confirmation Theory (ECT), the push-pull theory and word-of-mouth models in Halal tourism. It also contributes to AI adoption in Halal tourism by addressing how modern AI tools can influence tourist behaviors, improve satisfaction and encourage repeat visits.

This study examines direct effect of leader-member exchange (LMEX) and learning orientation (LEOR) on workplace innovation (WPIN) and indirect effect between underline relationships in presence of mediators such as creative self-efficacy (CRSE), thrive at work (THAW), task interdependence (TAIN) work significance (WOSI) and creative performance (CRPE). Moreover, this study investigates the serial mediating effect of CRSE, WOSI, THAW, TAIN and CRPE between LMEX, LEOR and WPIN in entrepreneurial small and medium-sized enterprises (SMEs).

This study collected a total of 286 usable responses from entrepreneurial SMEs in three major business cities in Pakistan. In this cross-sectional study, data were gathered through self-administered surveys using purposive sampling approach and tested hypotheses using structural equation modeling (SEM).

The findings suggested insignificant direct effect of LMEX and LEOR on WPIN in the presence of mediators. Interestingly, CRSE, THAW, TAIN and CRPE were identified as significant mediators between LMEX, LEOR and WPIN. However, WOSI was found to be an insignificant mediator in the observed context. Moreover, the results revealed significant serial mediating effect of CRSE and CRPE with work context elements such as THAW and TAIN between LMEX, LEOR and WPIN, while serial mediating effect of WOSI in underline relationships found insignificant.

The study emphasizes that chief executive officers (CEOs) of entrepreneurial SMEs should prioritize individual, team and organizational factors to improve WPIN for competitiveness. Entrepreneurial management should focus on building strong relationships with employees to foster creativity and create a learning-oriented work environment that improves motivation and collaboration, thereby boosting employees' CRSE and CRPE, leading to enhanced WPIN.

This research offered a novel research framework and identified critical mediators and serial mediators between LMEX, LEOR and WPIN for entrepreneurial SMEs in developing countries, a domain grossly underrepresented in the literature.