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This study examines the effect of crucial factors (benefits and sacrifices) influencing employees' perceived values (hedonic and utilitarian) towards metaverse meeting platforms. Further, the study investigates the impact of employees' perceived values (hedonic and utilitarian values) on behavioral intention to use metaverse meeting platforms. The study also examines how behavioral intention to use metaverse meeting platforms influences organizational SDG achievement. Finally, the authors analyzed the moderating impact of employee creativity.

Data were collected from 228 participants through structured questionnaires, and the hypotheses were examined using the structural equation modeling approach.

Social presence and technostress are significantly associated with perceived hedonic value. Further, social presence, exhaustion and technostress are significantly associated with perceived utilitarian value. Similarly, perceived hedonic and utilitarian value is significantly associated with behavioral intention to use metaverse meeting platforms. Further, behavioral intention to use metaverse meeting platforms is also significantly associated with SDG achievement.

The study enriches the existing literature pertaining to the metaverse, strategic human resources, sustainability, employee creativity and technology adoption. The research also enriches the value-based adoption (VAM) and stimulus-organism-response (SOR) theories.

This research focuses on developing and testing a conceptual model that explores customer behavioural responses (engagement, experience and recommendation) towards generative artificial intelligence (AI)-enabled chatbots. It highlights the significant influence of anthropomorphic characteristics in enhancing perceptions of competence and warmth, further enhancing perceived authenticity. In addition, this study aims to investigate how the need for social interactions moderates these relationships.

This study used a self-administered questionnaire distributed on Prolific Academic to gather data from 282 eligible participants worldwide. This study uses a structural equation modelling approach to answer the research questions.

The findings reveal that anthropomorphic characteristics of generative AI-enabled chatbots are positively associated with perceived competence. Moreover, the findings show that the perceived competence and warmth of generative AI-enabled chatbots are significantly associated with perceived authenticity. Furthermore, the results highlight that the perceived authenticity of generative AI-enabled chatbots is positively associated with customer engagement, experience and recommendation. Finally, the results illustrate that the impact of anthropomorphic characteristics on perceived warmth is significantly moderated by the need for social interaction.

This study enriches the generative AI literature and guides organizations in understanding consumer interactions for leveraging generative AI-enabled chatbots. Furthermore, this study contributes to the social response theory literature as this study investigates how user behavioural intentions towards generative AI-enabled chatbots are influenced by their perceived level of anthropomorphic characteristics.

This study aims to dissect and understand the latent themes of Islamic work ethic (IWE) and explore the driving factors of IWE research.

Structural topic modeling (STM), a sophisticated machine learning technique, was used to analyze a corpus of 205 articles sourced from the Scopus database. These articles cover the 36 years of research on IWE, from 1988 to 2024. Moreover, negative binomial regression was applied to examine the driving factors of IWE research.

The STM analysis unfolds ten topics in conjunction with IWE including individual success, workplace dynamics, organizational work ethics, knowledge management, employee citizenship behavior, financial ethics, job satisfaction, organizational commitment, performance enhancement and leadership. The further STM outputs included word clouds, prevalence proportions, correlation matrix, heatmap, relationship of topics with metadata, topic prominence in the publishing journals and, finally, illustrating trends and future prospects of research on IWE. The results of negative binomial regression reveal that number of authors, article age, journal indexing, authors from multiple countries and number of references are strong drivers of fostering research in IWE, by having significant positive impacts on total citations.

The insights from this study provide valuable guidance for businesses and organizations looking to integrate IWE principles into their operations. By promoting values such as fairness, hard work and ethical behavior, organizations can foster a more inclusive and morally grounded workplace culture. This, in turn, may lead to enhanced employee satisfaction, greater organizational commitment and improved overall performance. Additionally, the emphasis on ethical practices can contribute to broader societal benefits, such as increased trust in business practices and a stronger alignment with social responsibility initiatives.

This is a unique study that explores the latent themes and characteristics of the IWE literature through STM and provides insights on the future research directions. In addition, this study also examines the driving factors of IWE research.

The complexity of citizenship behavior in organizations has long been a focus of research. Traditional methodologies have been predominantly used to address this complexity. This paper aims to tackle the problem using a cutting-edge technological tool: business process mining. The objective is to enhance citizenship behaviors by leveraging primary data collected from 326 white-collar employees in the Indian service industry.

The study focuses on two main processes: training and creativity, with the ultimate goal of fostering organizational citizenship behavior (OCB), both in its overall manifestation (OCB-O) and its individual components (OCB-I). Seven different machine learning algorithms were used: artificial neural, behavior, prediction network, linear discriminant classifier, K-nearest neighbor, support vector machine, extreme gradient boosting (XGBoost), random forest and naive Bayes. The approach involved mining the most effective path for predicting the outcome and automating the entire process to enhance efficiency and sustainability.

The study successfully predicted the OCB-O construct, demonstrating the effectiveness of the approach. An optimized path for prediction was identified, highlighting the potential for automation to streamline the process and improve accuracy. These findings suggest that leveraging automation can facilitate the prediction of behavioral constructs, enabling the customization of policies for future employees.

The findings have significant implications for organizations aiming to enhance citizenship behaviors among their employees. By leveraging advanced technological tools such as business process mining and machine learning algorithms, companies can develop more effective strategies for fostering desirable behaviors. Furthermore, the automation of these processes offers the potential to streamline operations, reduce manual effort and improve predictive accuracy.

This study contributes to the existing literature by offering a novel approach to addressing the complexity of citizenship behavior in organizations. By combining business process mining with machine learning techniques, a unique perspective is provided on how technological advancements can be leveraged to enhance organizational outcomes. Moreover, the findings underscore the value of automation in refining existing processes and developing models applicable to future employees, thus improving overall organizational efficiency and effectiveness.

This study aims to better understand the influence of various post-treatments on the microstructure and mechanical properties of additively manufactured parts for critical applications.

In this study, Laser Powder Bed Fusion (LPBF) fabricated Inconel 718 (IN718) samples were subjected to various heat treatments, namely homogenization, solution heat treatment and double aging, to investigate their influence on the microstructure, mechanical properties and fracture mechanism at an elevated temperature of 650 °C. Homogenization treatment was performed at 1080 °C for durations ranging from 1–8 h. The solution treatment temperature varied from 980 °C to 1140 °C for 1 h, followed by double aging treatment.

At 650 °C, the as-built sample showed the minimum strength but demonstrated the maximum elongation to failure compared to the heat-treated samples. The strength of the IN718 superalloy increased by 20.26% to 34.81%, while ductility significantly reduced by 65.26% to 72.89% after various heat treatments compared to the as-built state. This change is attributed to the enhancement in grain boundary strength resulting from the pinning effect of the intergranular δ-phase.

The study observed that the variations in the fracture mechanism of LPBF fabricated IN718 depend on the duration and temperature of heat treatment. This research provides a thorough overview of the high-temperature mechanical properties of LPBF fabricated IN718 subjected to different homogenization times and solution treatment temperatures, correlating these effects to the corresponding changes in microstructure.

This research aims to identify and model metrics and sub-metrics that enhance sustainable performance measurement in agri-food supply chains.

The study evaluates five key metrics and 18 sub-metrics critical to this industry, establishing interrelationships among them to ensure a successful sustainable performance measurement system. The decision-making trial and evaluation laboratory technique was employed, integrated with fuzzy theory and expert opinions.

The findings suggest that metrics like information technology and organizational productivity, alongside the sub-metric of information integration, significantly contribute to sustainable supply chain performance.

This study proposes a performance measurement system that enables organizations to achieve optimal performance levels through a sustainable supply chain (SCC) and supply chain agility (SCA) framework, supported by digital technologies.

This study aims to explore the extent to which micro, small and medium-sized enterprises (MSMEs) in Saudi Arabia are adopting cloud-based accounting systems, what cloud accounting technologies MSMEs are using and the factors that affect cloud accounting system adoption. The technology, organizational and environmental model was used to assess the factors that affect the adoption of cloud accounting systems.

Data were collected via a survey distributed to MSME owners, directors and chief executives in Saudi Arabia. The final sample comprised 174 participants. Descriptive statistics, multiple response analysis and logistic regression were used to analyze the data.

This study’s findings show that many MSMEs currently do not use cloud accounting. The findings also show that Sage One and Xero Accounting are the main cloud accounting technologies MSMEs use. Perceived benefits, security concerns, organizational readiness, government support and vendor support were found to significantly influence the adoption of cloud accounting systems, while compatibility, firm size, top management support and intensity of the competition were not found to affect MSMEs adoption of cloud accounting technologies.

To the best of the authors’ knowledge, this study is the first to explore cloud accounting adoption by MSMEs in Saudi Arabia. It empirically shows the extent to which cloud-based accounting systems are used in MSMEs and the significant factors influencing the adoption of these systems.

A critical factor to the success of IPOs is investor demand, which can be observed from the IPO subscription pattern. Therefore, the objective of this study is to review the studies on the demand of IPOs, including empirical and theoretical literature, due to the substantial growth of IPOs over the last two decades.

This study extracted secondary data regarding IPO demand published from 1988 to 2022 from the Scopus database. We conducted a meta-literature review for qualitative and quantitative methods on the resulting 284 articles using citation analysis (Harzing’s Publish or Perish and VOS viewer software) and content analysis.

The findings revealed significant elements of the literature, including countries, institutions, journals, authors, articles and topics. Based on the IPO literature review and analyses, this paper developed future research questions to facilitate an extension of the research. Additionally, this paper developed a dual perspective of the present state of IPO research. First, it asserts that the demand for IPOs is not limited to certain countries, jurisdictions or vintages. Second, there are very few studies on demand for IPOs available despite IPOs’ economic worth.

To the best of the authors’ knowledge, this is the first study of its kind to present an empirical evaluation of demand for IPOs using inclusive mapping.

This study aims to examine the effects of religiosity, ethical leadership and local wisdom on the relationship between fraud risk management and asset misappropriation in Indonesia.

Data were collected using a set of questionnaire surveys administered to the head office, local government internal auditors (inspectorate) and local government employees in Indonesia. Sample selection used purposive techniques and obtained 151 respondents who became research data. The dependent variable was asset misappropriation. The independent variable was fraud risk management. The moderating variables for this study were religiosity, leader ethics and local wisdom. The analysis technique applied the structural equation model-partial least square (SEM-PLS).

Fraud risk management has a significant negative effect on asset misappropriation. In addition, this study finds evidence that religiosity, ethical leadership and local wisdom increase fraud risk management against asset misappropriation.

This study proposes an integrative model that enables local governments to understand fraud risk management. By integrating religiosity, ethical leadership and local wisdom, managers can design strategies to prevent asset misappropriation.

This research has the advantage of proposing an integrative model for mitigating asset misappropriation. Research on asset misappropriation is limited. Therefore, this study provides insights into fraud risk management, particularly in Indonesia’s local governments. In addition, this study adds ethical aspects such as religiosity, leadership and local wisdom to complement the weaknesses of fraud risk management and reduce the potential for asset misappropriation.

The Indian government is grappling in generating sufficient revenue resources through taxation to meet their expenditure on public goods and services. Therefore, the government authorities must possess adequate information on factors affecting the taxation revenue of the country to craft and execute policies effectively. Hence, this study endeavors to explore the determinants of tax revenue by incorporating conventional, economic policy and institutional factors.

The study employed the Auto Regressive Distributed Lag (ARDL) modeling by using the data set from 1991 to 2022 according to the availability of the data.

The findings illustrate that trade openness, life expectancy, value added by the manufacturing sector and per capita GDP (Gross domestic Product) positively affect the tax efforts of the government in the conventional determinants. Similarly, in economic policy factors, the financial deepening also exhibits a favorable effect. Conversely, the inflation rate positively boosts the tax efforts in the short run, but it ultimately erodes the tax effort of the government in the long run. In the institutional factors, the official development assistance also illustrates a positive effect.

The findings assert that the Indian government should devise better macro-economic and foreign trade policies with expediting the economic restructuring and bolstering their ability to manage and utilize the foreign aid assistance to boost the tax revenue of the country.

To the authors’ knowledge, this is the first study to incorporate these factors in the Indian context.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2024-0314