The application of hybrid Partial-Least-Square-Structural-Equation-Modeling-Artificial-Neural-Network in Information Systems (IS) research has surged over the years. Grounded on a systematic literature review from the list of premier and other promising IS journals, we found several concerns and issues. Hitherto, there are no guidelines for IS researchers for the hybrid PLS-SEM-ANN approach. We unlocked the potential of the hybrid PLS-SEM-ANN in providing better insight and understanding for IS researchers. In addition, best practices and recommendations for the adoption of PLS-SEM-ANN are discussed. The study contributes to advancing IS research by conducting a systematic literature review with Biblioshiny apps from the R studio’s Bibliometrix package and then proposing a comprehensive and robust approach to address the duality nature through the linear-nonlinear and compensatory-non-compensatory relationships. We proposed a guideline and suggested the minimum sample size, best practices and recommendations for reporting the results. We discuss the opportunities and prospects of the hybrid approach.

In a short span of time since its introduction, generative artificial intelligence (AI) has garnered much interest at both personal and organizational levels. This is because of its potential to cause drastic and widespread shifts in many aspects of life that are comparable to those of the Internet and smartphones. More specifically, generative AI utilizes machine learning, neural networks, and other techniques to generate new content (e.g. text, images, music) by analyzing patterns and information from the training data. This has enabled generative AI to have a wide range of applications, from creating personalized content to improving business operations. Despite its many benefits, there are also significant concerns about the negative implications of generative AI. In view of this, the current article brings together experts in a variety of fields to expound and provide multi-disciplinary insights on the opportunities, challenges, and research agendas of generative AI in specific industries (i.e. marketing, healthcare, human resource, education, banking, retailing, the workplace, manufacturing, and sustainable IT management).

The concept of the Metaverse, an immersive simulated world with parallels to reality, has gained significant prominence in recent times. Initially popularized through gaming, the Metaverse is now poised to infiltrate various aspects of human life. Intelligent transportation systems represent a promising yet challenging domain for Metaverse integration. Alternative implementations can create challenges in different dimensions. A comprehensive evaluation that takes challenges and opportunities for the different dimensions into account is required in decision making process of choosing the best implementation method. This study presents the development of a novel evaluation model, the Fermatean Fuzzy Operational Competitiveness Rating (OCRA) model, which incorporates the Fermatean Fuzzy Distance Measure (FF-DM) and Relative Closeness Coefficient (FF-RCC) techniques. The model is tested in a case to rank three alternative approaches, considering criteria of four key dimensions: managerial, safety, user, and urban mobility. In the first stage, the FF-DM and FF-RCC-based tool is employed to determine the criteria weights. In the second stage, an enhanced version of the Fermatean Fuzzy OCRA model, utilizing FF-DM and FF-RCC, is employed to rank the alternatives. The findings indicate that policymakers' decisions in traffic management hold the potential to shape the trajectory of the Metaverse movement, representing an unparalleled opportunity with implications that extend beyond our current comprehension.

This study is one of the few studies that aimed to examine, first, the effect of social media usage for news consumption on users’ cognitive notions in terms of focal and affiliate social media trust, and second, the effect of social media trust, news-finds-me perception (NFMP), and fake news’ deception detection self-efficacy (DDSE) on news credibility, brand (dis)trust, and consumers’ propensity to believe and act on fake news. The analysis findings indicated that: (i) social media usage induces focal and affiliate social media trust, (ii) NFMP and DDSE influence news credibility, which in turn determines brand (dis)trust and the propensity to believe in and act on fake news, and (iii) the impact of focal and affiliate social media trust on news credibility is moderated by persuasive knowledge. The present study’s findings contribute to the existing consumer behavior literature by offering insights to counteract the impact of fake news on brands.

Mobile grocery shopping has gained traction recently due to the COVID-19 pandemic. Hence, this study aims to investigate the antecedents that influence consumers’ buying intention through mobile grocery shopping. This was achieved through the use of a multi-perspective research model that includes the consumers’ positive and negative valences as well as consumer characteristics. Data was collected from 400 Malaysian consumers and analyzed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) analysis. The finding of the study indicated the significant effects of positive valences (e.g., hedonic and utilitarian value) but not negative valences (e.g., privacy concern and security risk) on consumer buying intention through mobile grocery shopping. This study among the first to examine the intricacies of varying consumer characteristics in the context of mobile grocery shopping. The implications derived from the findings of this study are discussed.

The term metaverse is described as the next iteration of the Internet. Metaverse is a virtual platform that uses extended reality technologies, i.e. augmented reality, virtual reality, mixed reality, 3D graphics, and other emerging technologies to allow real-time interactions and experiences in ways that are not possible in the physical world. Companies have begun to notice the impact of the metaverse and how it may help maximize profits. The purpose of this paper is to offer perspectives on several important areas, i.e. marketing, tourism, manufacturing, operations management, education, the retailing industry, banking services, healthcare, and human resource management that are likely to be impacted by the adoption and use of a metaverse. Each includes an overview, opportunities, challenges, and a potential research agenda.

Although mobile payment services are unlikely to become obsolete, their market dominance has been challenged following the intensified market competition. A research model is developed to uncover the drivers of users’ hedonic and utilitarian motivations (i.e., application, marketing, and internal stimuli) as the key to fostering satisfaction and commitment toward mobile payment services. Data were gathered from a survey and analyzed via the dual-stage Structural Equation Modeling-Artificial Neural Network (SEM-ANN) technique to capture both linear and non-linear relationships. The findings suggested that information value, monetary value, self-congruence, and reward and recognition drive hedonic and/or utilitarian motivations, which in turn promote users’ satisfaction and commitment toward mobile payment services. The ANN analysis reveals the existence of a non-linear hidden attribute. The research provides theoretical insights and practical implications for the field of mobile payment services.

Wearable payment, which is the use of wearable technology to make payment, is anticipated to be the future of proximity mobile payment. However, the acceptance and use of wearable payment in Malaysia leave much to be desired. Additionally, this area of research is currently under-addressed. Thus, this study looks into the elements that influence the intention to adopt wearable payment in Malaysia. The results are robustly insightful in revealing the intention to adopt wearable payment in Malaysia. Hence, there are numerous implications to wearable technology companies, wearable payment system designers, merchants and other stakeholders. Overall, this research is anticipated to serve as one of the pioneering research for future studies related to this area.

This paper looks to determine the antecedents of Near Field Communication (NFC) mobile payment from a developing country’s perspective. This was done with the use of a conceptual framework based on the Mobile Technology Acceptance Model (MTAM) that consists of mobile usefulness (MU), mobile ease of use (MEU) while integrating mobile self-efficacy (MSE), and system and service quality (SSQ). A self-administered questionnaire developed from measurement items adapted from past studies yielded 352 usable responses from smartphone users who were patronizing popular shopping malls in the Klang Valley region. The analysis was done using SmartPLS 3.0 which found that other than MSE, all other independent variables were significant determinants of the intention to adopt mobile payment. Moreover, MSE and SSQ have significantly positive relationships with MU and MEU. This study successfully applied the MTAM model as 72% of the intention to adopt mobile payment can be explained by all factors in the research model.

Tourism shopping via mobile applications has revolutionized the tourism industry. The research examined the antecedents to the adoption of mobile tourism shopping (MTS) via an integrated model, consisting of the Mobile Technology Acceptance Model, consumer perception of merchant ethics, consumer decision-making styles, and characteristics of mobile applications. The results were empirically validated via the PLS-SEM-ANN method. The findings indicated that mobile usefulness, mobile ease of use, application quality, and service quality have significant positive correlations with the intention to use MTS, whereas privacy concern has displayed a significant negative relationship. Moreover, source reliability, application reputation, perfectionism, and novelty-fashion consciousness were revealed to be statistically insignificant to the development of adoption intention toward MTS. Furthermore, the ANN results have indicated the existence of a non-linear hidden attribute in the prediction of ANN Model A. The research has generated valuable theoretical implications and practical insights. For one, the advantages that come with the adoption of MTS and the security measures taken by the service providers should be highlighted to the prospects via effective marketing messages to nurture confidence, which can subsequently drive adoption.

The growth of a country is heavily depending on its investment over science and technology. In fact, the progress in computer science research serves as a vital factor in the development of a country. Interestingly, despite that the Association of Southeast Asian Nations (ASEAN) is located near each other, they do not share a similar level of ICT development, which leads to a digital divide among them. Thus, it is crucial to bibliometrically evaluate and compare the computer science research output over the latest decade (i.e., 2009 to 2018) among these countries. With the data gathered from the Web of Science, this study seeks to uncover the research focus of all ASEAN countries over the latest decade by analyzing the author keywords. Majority of the ASEAN was having a different research focus, explaining the varied levels of ICT development. Practical and theoretical implications are then offered accordingly.

Cyberbullying on social media has become a serious matter and is the most rampant form of bullying among students nowadays. Accordingly, this study examines mobile social cyberbullying perpetration, a new form of cyberbullying perpetration that is conducted over mobile social media, through the theoretical lenses of Barlett and Gentile Cyberbullying Model (BGCM) and Mobile Technology Acceptance Model (MTAM). The Partial Least Squares Structural Equation Modeling analysis was performed on the 489 samples gathered from university students in order to obtain inferential statistics. Perceived anonymity and belief in the irrelevance of muscularity from the BGCM are positively related to mobile usefulness and mobile ease of use from the MTAM, while all of them are reported to have a positive association with the positive cyberbullying attitudes, which ultimately explain mobile social cyberbullying perpetration. From the results, it is ascertained that the well-founded integrated model has made a novel contribution toward the current literature of cyberbullying perpetration, particularly the rarely studied mobile social cyberbullying perpetration. Several suggestions on reducing the mobile social cyberbullying perpetration are then made to the practitioners, especially the government policymakers and mobile social media service providers.

The emergences of Web 2.0 and cloud computing have contributed greatly to the prevalence of electronic Word-of-Mouth (eWoM). Unlike most of the existing studies which have used linear models, nonlinear relationships were discovered in hotel booking intention. So far, the effects of elaboration-likelihood model (ELM) and demographics have been largely overlooked, though studies have shown that ELM may explain consumers’ perception, behavior, and IS acceptance. Data were gathered from 497 patrons of 10 hotels in Golden Triangle, Kuala Lumpur, Malaysia. Using artificial neural network (ANN), we found that user involvement, positive eWoM, user expertise, perceived credibility, education, negative eWoM, and income are among the important predictors explaining 81% of variance in booking intention. The theoretical implications may further advance eWoM and ELM literatures, while the managerial implications may provide novel understandings to hotel operators, advertisers, and relevant hospitality policy makers in formulating effective decision making.

This study aims to understand users’ motivations to adopt mobile entertainment (m-entertainment). Extending the Technology Acceptance Model (TAM), this study examined the effects of trust, perceived financial cost (PFC), and quality of the service on consumers’ decision in adopting the m-entertainment. Survey data were collected from 524 mobile users and analyzed using both structural equation modeling (SEM) and neural network (NN) . The result showed that perceived usefulness (PU), perceived ease of use (PEOU), and quality of service (QS) are important predictors of m-entertainment adoption. The study contributes to the existing literature by extending the TAM model as well as examining m-entertainment, an important and emerging business model in mobile commerce. A new analytical approach using both SEM and NN was also employed in this study.