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).

Despite the risks associated with generative AI (GenAI) chatbots, people increasingly use these technologies, which may seem contradictory. This study identified and explored factors and risks related to trust, perceived values, satisfaction, and sustainable use of GenAI chatbots. Relying on IS theories to build a stimulus-organism-response model, the authors tested a model using PLS-SEM with data from 393 ChatGPT users. The results show that user competence and autonomy dramatically increase a user's trust in ChatGPT, and trust improves hedonic value (HV), utilitarian value (UV), value-in-use, perceived task-technology fit (TTF), information accuracy, knowledge acquisition, perceived informativeness, and user satisfaction. In addition to trust, user satisfaction depends on HV, UV, and TTF. The sustainability use of ChatGPT depends on HV and satisfaction. However, perceived privacy concerns, perceived privacy risks, and privacy awareness do not affect consumer trust. There is a complete mediation between trust and sustainability, as well as HV and sustainability.

This study examines the use of information and communications technology (ICT) in remote work practice during the COVID-19 pandemic by integrating task-technology fit theory and the post-acceptance model of IS continuance into a research framework. In addition, it operationalizes the technological characteristics of TTF (task-technology fit) with the technology acceptance model (TAM) and the diffusion of innovation (DOI) theory. The methodology to test the research model takes support from the partial least squares structural equation modeling (PLS-SEM) method using a sample of 320 employees. The results show that TAM significantly explains TTF. Furthermore, there is a positive impact of ICT use on individual and organizational performance. User satisfaction has the most significant effect on individual performance, organizational performance, and IS continuance intention. The authors provide some managerial implications for addressing the challenges of remote work related to ICT disruptions for the post-COVID-19 period.

In light of the controversies surrounding COVID-19 vaccines, this study explored vaccine adoption through a theoretical model, focusing on France (n=2001) and South Africa (n=1107). Analysis using structural equation modelling and hierarchical cluster analysis revealed that social influences, personal opinions on vaccines, perceived severity of the pandemic, and perceived benefits of vaccination were primary drivers of adoption in both countries. Belief in conspiracy theories and perceptions of social distancing and stay-at-home measures had no influence on acceptance. Trust significantly influenced adoption intentions only in South Africa. Cluster analysis revealed four distinct opinion groups—“enthusiasts,” “doubters,” “followers,” and “conspirationists”—each preferring different health information sources and technologies, with a common preference for traditional media over social media. These findings have implications for developing targeted health policies, communication, and trust-building strategies.

Traditionally measurements of service quality have followed the expectation-disconfirmation approach. Further, previous studies have shown that negative disconfirmation is more influential than positive disconfirmation. In this research, we hypothesized information systems(IS) service quality scales based on the dimensionality of the expectation-disconfirmation (ED) and desire-disconfirmation (DD) approach. Using the SERVQUAL+ instrument and data collected from 321 IS users, we developed ED and DD based IS service quality scales using contemporary methods, such as LISREL-based CFA. We have proposed and empirically validated the following two new IS service quality constructs: Service Adequacy (difference of expected service and perceived service) and Service Superiority (difference of desired service and perceived service). Our results indicate that both measures have shown better predictive power than earlier scales like SERVQUAL+ and the IS ZOT scales. We have outlined several implications of ED and DD scales to practice and research.

Self-tracking (ST) technologies offer an unlimited number of opportunities to improve human life, especially health and well-being. Many scholars have been interested in this technology because of its worldwide spread but have not emphasized the benefits versus ST practices risks. This paper presents a literature review of the benefits and risks of ST practices to close this gap. It also develops a multidisciplinary research model based on the extended valence framework. This model offers five hypotheses highlighting the importance of considering technological, social, and health factors when measuring ST adoption. The results show that the perceived benefits outweigh the risks. Health is paramount in the perception of benefits. These results lead us to make a few recommendations for practitioners.

To revamp with new creative age characterized by ongoing digital transformation, more and more industries are capitalizing on digital innovation for their sustainable business growth. Drawing on a systematic literature review, thematic analysis, and using the theories of dynamic capabilities and market orientation, this research scrutinizes a systematic process for developing analytics-based data-driven innovation (DDI). Findings suggest a standardized seven-step process for DDI, including product conceptualization, data acquisition, data refinement, data storage and retrieval, distribution, presentation, and market feedback.

Vaccination is nowadays the most used option to stem the covid-19 pandemic. The global impact of the pandemic has triggered an unprecedented frenzy for research axis related to COVID-19 vaccine. Since 2019, the volume of publications related to COVID-19 vaccines has swollen significantly. In this very dynamic context, it can be difficult to quickly access the state and orientations of the researches. Thus, the goal of this paper is to provide a quick, fast comprehensive science mapping of these researches through an information management bibliometric approach. We extracted 8 246 publications (up to July 08th 2021) related to COVID-19 and vaccination from a world-leading publisher-independent global citation database (Scopus). The Bibliometrix package was then used to perform a bibliometric review of all these documents. The most important connections between the main themes, publications, authors, institutions, countries, collaborations, and journals are being highlighted. Main implications for the Information System along with some future research directions are also presented.

Financial inclusion is a vital development priority for countries worldwide. Mobile wallet (m-wallet) is considered as a disruptive payment method that will substitute the traditional physical wallet to achieve the so-called cashless society and enables financial inclusion. This study aims at developing and testing a research model that integrates a set of technology factors (perceived usefulness, perceived ease of use, fun to use, monetary value), external factors (peer influence and perceived status benefit), and cultural factors (humane orientation and societal collectivism) to assess the intention to adopt and use m-wallet, for financial inclusion, in a developing country. The proposed conceptual model is tested using data collected from 621 m-wallet users in Cameroon. The model explains 47.5% of the variance of the actual use of m-wallet and 32.90% of the variance of financial inclusion. Eight out of the 10 proposed hypotheses were supported. Finally, implications for research and practice are discussed.

This article aims to identify differences in the impact of Self-connectivity and the variables of the technological acceptance model (TAM) on smartwatch adoption in developed countries. The countries involved in the data collection were the United States of America, the United Kingdom, Germany, and France. A sample of 1,197 respondents was used. The study identifies distinct adoption behaviours of smartwatch users in these countries and the moderating impacts of age and gender. The study's results confirm that perceived ease-of-use has no impact on attitude-toward-using the smartwatch and its findings emphasize the key role of perceived-connectivity and the moderating effect of culture on the adoption of innovative products.

The use of RFID tags in healthcare applications has been gaining momentum over the past decade. This is partly due to recent advances in information technology and the need to reduce errors while simultaneously improving the efficiency of the system. We, at the RFID European Lab, have been studying various aspects of RFID implementations in healthcare environment over the past several years. The potential for RFID implementations in healthcare environment is enormous. We consider several such opportunities and identify possible extensions.

In the growing literature on RFID and other network technologies, the importance of organizational transformation at the supply chain level has been recognized. However, the literature lacks conceptual model development and salient mechanisms for achieving the level of organizational transformation required for stakeholders to realize the full business benefits from RFID projects. Furthermore, the RFID adoption, use, and impact studies to date largely focus on a single firm setting and on the retail sector. Therefore, this study intends to fill this knowledge gap in the literature, and develops a contingency model for creating value from RFID supply chain projects in logistics and manufacturing environments. For our model development, we draw upon extant diverse literatures, particularly the framework for IT-enabled business transformation, and leadership and organizational learning. The framework postulates a positive relationship between the level of organizational transformation effected by the use of information technology (IT) and the level of business benefits realized from IT. The contingency model draws on the framework, and explicates five contingency factors influencing value creation from RFID supply chain projects: environmental upheaval; leadership; second-order organizational learning; resources commitment; and organizational transformation. Using the contingency model as a conceptual guide, we also perform an analysis of longitudinal real-world case data from a Canadian third-party logistics service firm's seven-layer supply chain RFID projects. The case study analysis provides evidence for the imperative of the contingency factors identified in the model for creating value from the RFID projects. Furthermore, it also reveals the differential costs for the focal firm and the up-stream manufacturing as a key barrier to realizing the full RFID benefits at the supply chain level.