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This research aims to explore how policymakers manage the information and communication of green behavior on social platforms to support their growth in corporate social responsibility (CSR). Social platforms play a strategic and interactive role through electronic word-of-mouth (eWOM), which brings unprecedented green purchase opportunities.

Based on stakeholder theory, a conceptual framework is designed to investigate the influence of green behavior interactions (GBIs) on CSR under the mediating effects of eWOM subfactors (eWC = eWOM communication, eWIA = eWOM information adoption and eWSC = eWOM source credibility). Data from 414 regular stakeholders of logistics firms were analyzed via structural equation modeling.

The results reveal positive influences of the GBI on eWC, eWIA, eWSC and CSR, with path coefficients of 0.329, 0.713, 0.809 and 0.316, respectively. The mediating effects of eWC and eWSC from the GBI to CSR were discovered with path coefficients of 0.105 and 0.226, respectively. Coincidentally, the mediating role of eWIA was positive but not supported. The outcomes of this study indicate that the administration of GBI and eWOM from a green purchase perspective is essential for a firm. The CSR practices of green logistics firms can be successfully supported by the administration of the GBI and eWOM indicators.

This study develops a novel multidimensional framework that illustrates the impact of eWOM on reducing information asymmetry, enhancing credibility, supporting informed decision-making and improving green consumer behavior. By amplifying positive reviews, increasing engagement and establishing a feedback loop, this framework aims to provide comprehensive insights into the efficacy of eWOM for firms’ products and services.

This study aims to apply Benford’s law to examine the earnings management of companies listed in emerging ASEAN-5 countries: Indonesia, Malaysia, Philippines, Thailand and Vietnam.

The authors follow Amiram et al. (2015) to measure deviations from Benford’s law of the first digits of numbers reported in financial statements. The authors use the Jones-modified performance-match model (Jones, 1991; Dechow et al., 1995; Kothari et al., 2005) to estimate accrual earnings management. The authors use a sample of 47,389 observations of listed companies in ASEAN-5 countries from 2006 to 2019. The authors also run ordinary least squares (OLS) regressions to test the hypotheses.

The authors find that the first digits of numbers reported in the financial statements of companies in the sample closely conform to Benford’s law. Further evidence shows that the deviation from Benford’s law is positively related to abnormal accruals. The relationship between deviation from Benford’s law and abnormal accruals is more pronounced for the post-international financial reporting standards adoption period. The results survive for some robustness checks.

The authors show that Benford’s law holds for financial statements of companies listed in the emerging ASEAN-5 countries.

Auditors could use Benford’s law as an analytical procedure to assess the risks of material misstatements. Also, other users could apply Benford’s law on audited financial statements to foresee undetected misstatements.

The authors provide original evidence that financial statements of ASEAN-5 countries follow Benford’s law. The evidence supports the usefulness of Benford’s law in developing markets.

The purpose of the study is to analytically as well as numerically investigate the weight of throughflow on the onset of Casson nanofluid layer in a permeable matrix. This study examines both the marginal and over stable kind of convective movement in the system.

A double-phase model is used for Casson nanofluid, which integrates the impacts of thermophoresis and Brownian wave, whereas for flow in the porous matrix the altered Darcy model is occupied under the statement that nanoparticle flux is disappear on the boundaries. The resultant eigenvalue problem is resolved analytically as well as numerically with the help of Galerkin process with the Casson nanofluid Rayleigh–Darcy number as the eigenvalue.

The findings revealed that the throughflow factor postpones the arrival of convective flow and reduces the extent of convective cells, whereas the Casson factor, the Casson nanoparticle Rayleigh–Darcy number and the reformed diffusivity ratio promote convective motion and also decrease the extent of convective cells.

Controlling the convective movement in heat transfer systems that generate high heat flux is a real mechanical challenge. The proposed framework proved that the use of throughflow is one of the most important ways to control the convective movement in Casson nanofluid. To the best of the authors’ knowledge, no inspection has been established in the literature that studies the outcome of throughflow on the Casson nanofluid convective flow in a porous medium layer. However, the convective flow of Casson nanofluid finds many applications in improving heat transmission and energy efficiency in a range of thermal systems, such as the cooling of heat-generating elements in electronic devices, heat exchangers, pharmaceutical practices and hybrid-powered engines, where throughflow can play a significant role in controlling the convective motion.

The purpose of this paper is to explore the domain of metaverse commerce and conduct a thorough examination of the complex dynamics that contribute to impulsive purchasing behavior. This study aims to examine the impact of vividness, interactivity and effectiveness on social presence and telepresence within the metaverse, a digital landscape. Specifically, it seeks to understand how these factors influence consumers' impulsive buying behavior.

The methodology used in this study consisted of distributing self-administered questionnaires via a survey. Data collection was conducted among a targeted sample of 348 participants in Vietnam who had direct experience with metaverse commerce services. Then, the collected data was subjected to analysis using two distinct methodologies: partial least squares structural equation modeling and artificial neural networks.

The findings of this study provide significant insights into the correlation between social presence, telepresence and impulsive buying behavior within the field of metaverse commerce. The research findings also indicate that the impact of social presence and telepresence on impulsive purchasing behavior is contingent upon the enhanced vividness, effectiveness and interactivity of the virtual environment.

The present investigation unveiled a range of linear and non-linear mechanisms that elucidate the functions of effectiveness, vividness and interactivity in facilitating the complex interplay between social presence, telepresence and impulsive buying behavior in the context of metaverse commerce. The study provides both theoretical and practical contributions to the existing body of literature on Metaverse commerce.

This paper aims  to examine the dynamic spillovers of Federal Reserve’s monetary policy shocks on real house price indices in nine emerging economies, namely China, Brazil, Thailand, Chile, Peru, Mexico, Malaysia, Indonesia and South Africa.

The authors use the local projection method with a panel data set of these countries spanning from 2005Q3 to 2019Q4 to estimate local projections at each period rather than extrapolating into distant periods from a given model.

A pure tightening monetary policy shock is associated with a decline in housing prices in the nine emerging markets. However, the optimistic information about the US macro-economic fundamentals that is embedded in the tightening announcement would increase housing prices. Therefore, the net transmission effects of the US policy rate shocks may be smaller than what previous studies reported. In addition, the authors also find that capital control actions executed by emerging countries are effective in mitigating the spillovers of the US monetary policy.

First, the paper aims to investigate the effects of US monetary policy shocks on housing prices in emerging economies which have not received sufficient scholarly attention. Second, the analysis focuses on both pure monetary policy shocks and the Federal Reserve's information on economic fundamentals contained in its rate announcements. Third, the authors also assess the effectiveness of capital controls imposed by policymakers in emerging countries in mitigating the spillovers of US policy rate shocks on housing prices in emerging markets.

This study combines the TAM and UGT frameworks to investigate how Vietnamese students' views of ChatGPT and intrinsic needs affect their intentions to use it for education (via variables including perceived ease of use, perceived usefulness, novelty, information seeking and academic content creation). We will employ TAM theory (Davis, 1989) and UGT theory to elucidate university students' motivations for utilising ChatGPT in Vietnam. Simultaneously, we aim to address the limitation stemming from data uniformity. Our research will make a substantial contribution to the understanding of researchers regarding the use of ChatGPT and its varied consequences as it grows and develops.

This study was conducted at a private university in Vietnam with an estimated population of 15,000 students. One of Vietnam’s top private information technology institutions requires its students to use a variety of information and communication technologies (ICTs) on a regular basis to facilitate and enjoy their academic pursuits (Ngo, 2024; Nguyen). Students who are familiar with ChatGPT and have access to it for educational purposes are the ones that were chosen. This research is a quantitative study that utilises primary data through a survey method. Participants answered a questionnaire online through the Google Form platform sharing via social media platforms from October to December 2023. The questionnaire was divided into two sections: the first contained screening questions and demographic information and the second had five-point Likert-scale questions that measured the study’s components. Two screening questions are used to separate out the intended responders. (i.e. “I have heard the name ChatGPT” and “I know about ChatGPT”) were set to find whether the participants had any knowledge of ChatGPT. If participants were unaware of ChatGPT, their responses were not included in the study. A total of 283 responses were received. The participant’s demographic information is shown in Table 1. It is believed that a sample size of more than 200 provides adequate statistical power for data analysis in structural equation modelling. It is evident that the 283-sample size in this study is adequate to evaluate the research hypothesis and the fitting model. 42.9% of the 283 research samples were made up of men, while 57.1% were women. Business administration accounted for 40.1% of survey respondents, followed by information technology (25.2%) and English language (14.5%). The average ChatGPT usage time of respondents was 56 min in a single use. The study sample’s average age is 20–72 years old.

The present study contributes to the existing AI chatbot literature in the educational industry in several ways. First, this study addresses a gap in the literature by investigating the factors that influence students’ ITU ChatGPT for educational purposes in Vietnam. Using the extended model, we investigated factors influencing students’ intentions to use ChatGPT. It integrates three motive factors of the UGT (ACT, IS and N) with the core factors of TAM (PeoU and PU). The integrated framework’s findings indicate that in a Vietnamese educational setting, ChatGPT is a novel technology that should be considered in conjunction with PU and PEoU.

First, only Vietnamese students make up the research sample. To increase the relevance of the findings, it is advised that future research look at the study model in various geographic regions. Second, the present investigation’s constraints arise from the lack of clarity about the Chat GPT version utilised by the respondents, specifically whether it was the free or premium edition. Furthermore, the limited duration of the survey presents an obstacle to gathering thorough data. Due to their reliance on the particular features and functionalities of the Chat GPT version used, these restrictions may have an effect on the researcher’s objectivity. Furthermore, the limited survey time may curtail the coverage of the collected answers, particularly considering that our survey predominantly focuses on business administration students, thus limiting the diversity and richness of the gathered data. We recommend that future studies should conduct comparative research between different versions of GPT Chat, including free and paid variants that can provide valuable insights into potential differences in performance and results. Such analysis can provide a deeper understanding of the strengths and limitations of different GPT Chat versions. Third, because the study focused on behavioural intention, actual usage and post-usage behaviour may not be covered by the findings. To gain a deeper understanding of users' actual behaviour, we suggest doing research on their usage and post-usage behaviours.

The findings will assist service providers and legislators in determining critical variables and influencing students' incentives to use ChatGPT in educational settings that use constructivist teaching methods. As a result, the information will assist service providers in creating AI chatbots that are more user-friendly, visually appealing, efficient, safe and convenient for education. Governments, in conjunction with service providers, have the potential to significantly accelerate the adoption of AI-based chatbots by highlighting their ethical and sustainable use. The findings demonstrate that students' ITU towards ChatGPT is substantially impacted by PU and PEoU. It is recommended that service providers emphasize the advantages and ease of use of AI chatbots in order to draw new clients. Additionally, in order to promote ChatGPT or related technologies, marketers should concentrate on raising the technology’s perceived novelty value. This is because people are open to new technologies as long as they believe they are interesting and innovative.

ChatGPT is an advanced AI-powered chatbot that has the potential to advance and revolutionize the learning and teaching process. This study attempted to look at the elements that lead students to want to use ChatGPT from an academic standpoint by combining the UGT and TAM. For practitioners, academics and educators, the findings provide a solid knowledge of and encouragement for the sustainable use of such AI tools. Despite having important practical consequences, the study contains a number of limitations that indicate possible research gaps that should be filled by further investigation.

This study investigates the impact of human capital (managers' capital, employees' capital) and orientation (market orientation, entrepreneurial orientation) for accelerating the digitalization process and improving the firm performance. It also studies the role of supply chains as both direct and indirect mediators of the correlation between digitalization and business performance.

This article aims to develop an empirical study using a random sampling technique and survey data collected from 368 managers and owners of different food enterprises in Vietnam. The study adopted a methodological approach quantitatively. Analysis of the relationships and confirmatory factors was performed using structural equation modeling (SEM), a technique to evaluate the proposed relationships.

In line with expectations, the findings emphasize the impact of human capital (managers' capital, employees' capital) and orientation (market orientation, entrepreneurial orientation) for accelerating the digitalization process and the role of supply chains as both direct and indirect mediators of the correlation between digitalization and improving the firm performance, in the context of emerging markets.

This is an important investigation, according to the authors' knowledge, regarding the role of developing human capital (managers' capital, employees' capital) and orientation (market orientation, entrepreneurial orientation) as a key strategy for accelerating the digitalization process and improving the firm performance. Further, the study's novelty reinforces the role of supply chains as both direct and indirect mediators of the correlation between digitalization and business performance in the Vietnamese food companies, where a market economy is emerging.

Artificial intelligence (AI) customer service has grown rapidly in recent years due to the emergence of COVID-19 and the growth of the e-commerce industry. Therefore, this study employs the integration of the stimuli–organism–response (SOR) and the task-technology fit (TTF) frameworks to understand the factors that affect individuals’ intentions towards AI customer service adoption in Malaysia.

The study utilised a survey-based research approach to investigate the factors that affect individuals’ intentions towards AI customer service adoption in Malaysia. The data were collected by conducting an online survey targeting individuals aged 18 or above who had prior customer service interaction experience with human service agents but had not yet adopted AI customer service. A sample of 339 respondents was used to evaluate the hypotheses, adopting partial least squares structural equation modelling as a symmetric analytic technique.

The PLS-SEM analysis revealed that social influence and anthropomorphism have a positive direct relationship with emotional trust. Furthermore, communicative competence, technology characteristics and perceived intelligence were positively correlated with TTF. Moreover, emotional trust significantly impacts AI customer service adoption. In addition, AI readiness positively moderates the association between task technology fit and AI customer service adoption.

The study provides insights to individuals, organisations, the government and educational institutions to improve the features of AI customer service and its development in Malaysia.

The originality of this study is found in its adoption of the SOR theory and TTF to understand the factors affecting AI customer service adoption. Additionally, it incorporates moderating variables during the analysis, adding depth to the findings. This approach introduces a new perspective on the factors that impact the adoption of AI customer service and offers valuable insights for practitioners seeking to formulate effective strategies to promote its adoption.

This study introduces a multi-vaccine multi-echelon supply chain (MVMS) framework designed to ensure sustainable vaccine distribution during outbreaks. The framework aims to minimize the total costs of vaccine distribution and reduce greenhouse gas (GHG) emissions to mitigate environmental impacts while maximizing job opportunities within the network.

Our proposed appraoch employs a multi-objective mixed-integer linear programming model.

The findings indicate that incorporating uncertainties related to demand and inspection errors significantly facilitates timely responses to unexpected shortages, fulfills the requirements of healthcare facilities, and enhances the supply chain’s resilience against future uncertainties. This study also explores managerial implications and suggests avenues for future research to further advance this field.

Existing literature on MVMS often relies on simplifying assumptions of perfect vaccines and primarily focuses on demand uncertainty. However, real-world supply chains are typically marked by imperfections, disruptions, and a variety of uncertainties beyond demand. In this work, we address several sources of parameter uncertainty, including demand variability, inspection errors, vaccine waste, and defective treatments rates to enhance the robustness of our model.

This study aims to explore the potential of artificial intelligence with AI-powered humanoid Chatbots (AIPHC) as transformative tools to improve customer service quality in the insurance sector. The usability and efficiency of integrating advanced AI chatbots that can replicate human-like interactions in insurance services will be examined by taking into consideration customers’ technological readiness and chatbots’ anthropomorphism.

This empirical study analysed 688 customer responses collected through purposive sampling using structural equation modelling. With the help of SmartPLS 4.0, the study determines whether anthropomorphism, that is AIPHC system-specific and customer personality-specific dimensions, can influence the acceptance of AIPHC in the insurance sector.

The results show that the chatbot’s anthropomorphism positively influenced customers’ optimism and innovativeness but negatively impacted discomfort and security. Further optimism and innovativeness favourably impact AIPHC adoption. Insecurity had a significant negative impact, while discomfort was insignificant for AIPHC adoption.

The study determines how people will react to AI-powered information systems. The results could help us better understand how the technological readiness of customers can be used in emphasizing the significance of system-specific theories like anthropomorphism in sectors like insurance, where customer interactions and delivery of quality services are important.

The results highlight chatbots’ potential to raise the quality of service, simplify processes and enhance customers’ overall experiences in the insurance sector. This study contributes to the continuing discussion on using AI technologies in customer service by considering the interplay between technology readiness and anthropomorphism. It also provides insightful information for insurance professionals and technology developers.

Anthropomorphic humanoid chatbots can increase the availability, affordability and accessibility of essential services. They have the potential to increase users’ competence, autonomy and—possibly counterintuitively social relatedness.

This empirical research explores the link between anthropomorphism and technology readiness to enhance service quality provided by AI powered chatbots in the insurance sector.