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).

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.

Despite the high utilization of mobile payment during the COVID-19 pandemic, this situation may change in the post-pandemic era. Therefore, great value can be derived from determining the significant antecedents of mobile payment continuance intention. This study looks to do so by introducing a Multi-Dimensional Nomological Network of Mobile Payment Continuance. A two-stage Partial Least Square-Structural Equation Modeling and Artificial Neural Network was utilized for the data analysis. The results provided empirical support to establish the overall nomological network. In addition, more than 70% of the variance in continuance intention was captured. Overall, this study provides practitioners with detailed insights to develop strategies for sustainable utilization and academics with a dynamic framework to look into users’ mobile payment continuance intention.

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.

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.