Shaha Faisal

This study examines the Green Vision of Saudi Arabia and its efforts towards achieving sustainability in various domains such as energy, economy, tourism, and carbon emissions. The research uses time-series data from 2002 to 2020 to analyze the dynamic impacts of these variables. To achieve this, it employs a co-integration regression test, Granger causality relationships, and one-way and two-way causal effects between carbon emissions, tourism, economic growth, and energy use. The findings of the study provide valuable insights into the challenges and opportunities for sustainability in the kingdom, considering the goals of SDGs 8 and 13. This research contributes to the ongoing discourse on sustainable development in Saudi Arabia and offers significant insights for lawmakers, entrepreneurs, and researchers to influence the country's future direction. The research aims to guide strategic decision-making in line with Saudi Arabia's commitment to achieving a sustainable and resilient future by examining the interconnections between energy, economic growth, tourism, and carbon emissions.

The rise in talent management complications led organizations to rely on the latest technologies to automate their routine HRM tasks through AI. This study proposed to examine fundamental aspects of AI in talent acquisition (cost-benefit, opportunities, and risk factors) from the context of strategic analysis and decision-making. 52 respondents from HRM and the information technology departments from fifteen large dairy enterprises, each with more than one thousand employees, were included in the focus group discussion. Both departments were included in the focus group discussion as they heavily employ AI in talent acquisition. The opinions were collected in multiple rounds based on the cost, benefit, opportunity, and risk criteria using the analytical hierarchy process, a multi-criteria decision-making framework. The findings demonstrated that most respondents opinioned AI supports talent acquisition with many opportunities (38.7%) that involve the identification of the best applicants (18.7%) and different benefits (33.2%) to the organization in the form of saving time and cost (16.1%) leading to higher efficacy. The study infers that the application of AI in HRM significantly contributes to talent acquisition, streamlining processes, improving efficiency, and enhancing decision-making. The study recommends that implementing AI in talent acquisition requires a strategic approach, and organizations need to consider factors such as data privacy, ethical use of AI, and ongoing training to ensure successful integration into their hiring processes. Additionally, regular monitoring and adjustments are essential to optimize the effectiveness of AI tools in talent acquisition. AcknowledgmentThe authors of this article would like to thank Prince Sultan University for its financial and academic support for this publication.

The study aims to analyze the factors that influence customers’ inclination to utilize chatbots in banking services. The paper employed the technology acceptance model and utilized structural equation modeling to examine the factors affecting consumers’ willingness to embrace chatbot services. The survey evaluated various determinants, including perceived usefulness, perceived ease of use, trust, privacy concerns, and customer satisfaction. Data were collected from 250 bank customers in the Bombay region of India through an online survey employing a random sampling method. The collected data were analyzed using IBM SPSS AMOS. This study identifies the aspects of chatbot technology in the banking sector, such as user interface, content, security, and convenience, that influence customers’ decisions to adopt this innovative technology. The results of the analysis revealed path coefficients indicating a significant relationship between information security and perceived usefulness (β = 0.286; p = 0.005) and between perceived usefulness and intention to use (β = 0.489; p < 0.001). Additionally, the path coefficients for design, security, and facilitating conditions were β = 0.281, β = 0.193, and β = 0.136, respectively, all of which held nearly equal significance in the study. The inter-correlations among the variables ranged from 0.346 to 0.854 and were statistically significant. In the banking sector, customers’ intention to use chatbots is influenced by convenience, efficiency, trust, and personalized experiences. Customers are more likely to embrace chatbots when they provide seamless support and tailored solutions, ultimately enhancing customer satisfaction and engagement. AcknowledgmentThis study is supported via funding from Prince Sattam Bin Abdulaziz University project number (PSAU/2023/R/1445).

Sustainability is gaining acceptance worldwide, and HRM is also influenced by it. Researchers globally are also exploring sustainable human resource management which creates a direct link between HRM and sustainability. Bibliometric analysis examined 247 documents on sustainable human resource management from 2003 to 2022. This study aimed to analyze the research trend, global distribution, contributory journals, leading authors, and contributing nations in sustainable HRM. In this bibliometric analysis, 247 documents have been analyzed. The review revealed that sustainable HRM is still an emerging concept worldwide; more researchers from European and Asian countries dominate this field. The present review will be helpful for academicians, practitioners, and researchers in this field. The study also presents interesting results that could help line managers and top managers to formulate ideas for sustainable HRM practices in their own companies.

Green HRM involves a variety of organizational policies, practices, and processes that encourage the use of environmentally friendly methods that could be advantageous to the individual, business, and the environment. Based on the systematic review of empirical articles collected from Scopus, the study identified and analyzed 31 empirical studies published since 2010. The current study was undertaken to identify various factors and measuring tools of GHRM. Based on the Ability–Motivation–Opportunity (AMO) theory and the review methodology, the study identified various factors and measuring tools of GHRM. A few identified factors include Green Recruitment and selection, Green Training and Development, Green compensation management, Green performance management, Green Employee empowerment and participation, and Green Employee relations. The present research has thus opened fresh avenues for future studies. In addition, the study presents different perspectives and suggestions for future research that could facilitate the inclusion of sustainability initiatives in the organizational agenda.

Job embeddedness and person-organization fit are two constructs that reflect employees’ attachment toward their organizations. While job embeddedness enhances employees’ affection, person-organization fit involves the value convergence with the organization. Therefore, the two constructs facilitate continuance in employment. The study attempted to identify the relationship between job embeddedness, person-organization fit, and human capital among the Saudi workforce. Data for the study were collected from 190 full-time employees employed in various organizations in Saudi Arabia. Convenient sampling was used to collect data. The respondents belong to different demographic categories. The data were analyzed using SPSS and structural equation modeling (SEM) techniques. Three hypotheses were formulated for the study to denote the relationships between the variables. For all the hypotheses formulated in the study, t-values (0.71, 0.88, and 0.84) showed a five percent level of significance. The research results thus indicated a significant positive relationship between job embeddedness, person-organization fit, and human capital. The relationship between the constructs and demographic variables was also examined. The findings are significant as the identified constructs help dealing with turnover intention, which is a bane for any organization. Therefore, the results could be used to identify retention strategies. AcknowledgmentsThis publication was supported by the Deanship of Scientific Research at Prince Sattam Bin Abdulaziz University, Alkharj, Saudi Arabia, under the Specialized Research Grant program with Grant No- 2020/02/17318.

Employee turnover is a major concern for organizations. Specifically, among private business schools, it is proved to be one of the major impediments in carrying out academic activities. This phenomenon creates a conundrum for both college administrations and students. Therefore, each academic unit must work to minimize employee turnover. This study aims to identify the elements that influence academicians’ turnover intentions and the ways to negate them. It used a random sample of 236 academicians (professors, assistant professors, associate professors, and lecturers) from various business schools in India. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to analyze the sample. In addition, the structural equation modeling (SEM) approach was used to examine the hypotheses. All variables studied had high loadings of 0.50 or more in CFA. The research model was shown to be fit on three important absolute fit indices: absolute, incremental, and parsimonious. The regression weights of hypotheses were also determined to be significant. The findings indicate that organizational support, compensation, and personnel management had a detrimental effect on turnover intentions at business schools. These results can be used by college administration and management in devising interventions that will assist them in retaining existing talented staff and avoiding the negative repercussions of future turnover.

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