This conceptual study reviews and synthesizes the existing literature to explore the impact of agentic artificial intelligence (AI) on market efficiency. The existing studies have well established the benefits of AI in improving information processing, price discovery, and liquidity. The transition from AI to autonomously driven agentic systems has additional benefits, along with introducing new challenges and risks such as volatility and systemic instability. This study examines two key dimensions: (1) how agentic AI contributes to the broader market efficiency; (2) the risks agentic systems pose to stability and volatility in the market. Our discussion posits that while agentic AI holds significant promise, structured governance frameworks, including human in the loop oversight, would be critical to its success. The study’s originality lies in framing a comprehensive conceptual understanding of how agentic AI simultaneously drives efficiency and presents challenges within financial markets. As a conceptual paper, the study is limited by the absence of empirical analysis, relying instead on secondary sources. However, the study identifies critical gaps, particularly in exploring how agentic AI influences cross market spill overs, governance mechanisms, and investor behaviour. This paper provides a valuable foundation for academicians and policymakers navigating the evolving intersection of AI and financial systems.

As an emerging technology, Generative Artificial Intelligence holds immense potential for application across various levels of business and management. The advancements in Gen AI have transcended traditional AI systems. Few studies exist discussing the potential of the technology, though there is a dearth of studies that empirically examine the factors associated with the corresponding user experience. A total of 30,000 critical user reviews were obtained from seven different Generative artificial intelligence applications and subjected to text analytics procedures to uncover key themes and constructs that drive user engagement. The findings highlighted key dimensions that reflect positive user experiences. Moreover, the Net Promotion score of the reviews calculated reflects a high level of user experience.

With the spread of generative AI, non-technology companies are also adopting it at a faster rate. Therefore, this study aims to study the appropriation of Generative AI to create value to non-technology businesses through a knowledge based view of the firm. To achieve this objective, we followed a semi-structured interview schedule, where 98 qualitative data points were collected and analysed. We follow open, axial and selective coding along with Gioia methodology for analysis. Findings indicate that companies employ Generative AI for risk management, where potential threats, impact of possible hazards and degree of uncertainty in the business environment are considered in decision-making. Generative AI also helps in knowledge integration, where assimilation, adaptation, application and implementation are achieved. Findings also suggest that an improved business outlook can be achieved regarding accurate demand forecasting, real-time insights, contextual understanding and alignment to the vision through Generative AI. It is also observed that companies are investing in Generative AI to achieve competitive advantage and greater significance. The contribution of this study lies in the development of four propositions and a framework for generative AI-driven value for non-technology companies. The framework also uncovers the internal flow among key elements from risk identification to integration to developing the outlook and driving utility.

The growing adoption of Metaverse offers an exciting opportunity to connect stakeholders on these technology platforms across industries. These platforms offer capabilities to interact, engage, transact and create different user experiences and functional values for users onboarded. The research on Metaverse is still at a nascent stage and our editorial provides research directions in Metaverse as a unique IT artefact. The current editorial is the second part of the special issue on Metaverse and introduces 8 new articles. We further synthesize all the empirical evidences in Metaverse in this special issue. Subsequently we propose a conceptual layered framework for future researchers to extend when they work on Metaverse platforms. Here the bottom layer starts with the technology artifacts and gradually showcase techno-functional features, before guiding the users towards the adoption and appropriation of Metaverse platforms which further shapes impacts on individuals, organizations and societies.

The emergence of AI agents and agentic systems represents a significant milestone in artificial intelligence, enabling autonomous systems to operate, learn, and collaborate in complex environments with minimal human intervention. This paper, drawing on multi-expert perspectives, examines the potential of AI agents and agentic systems to reshape industries by decentralizing decision-making, redefining organizational structures, and enhancing cross-functional collaboration. Specific applications include healthcare systems capable of creating adaptive treatment plans, supply chain agents that predict and address disruptions in real-time, and business process automation that reallocates tasks from humans to AI, improving efficiency and innovation. However, the integration of these systems raises critical challenges, including issues of attribution and shared accountability in decision-making, compatibility with legacy systems, and addressing biases in AI-driven processes. The paper concludes that while agentic systems hold immense promise, robust governance frameworks, cross-industry collaboration, and interdisciplinary research into ethical design are essential. Future research should explore adaptive workforce reskilling strategies, transparent accountability mechanisms, and energy-efficient deployment models to ensure ethical and scalable implementation.

The increased prevalence of Autism Spectrum Disorder (ASD) and the urgent need for personalized treatment have highlighted the role of data science in enhancing clinicians’ capacity and treatment quality. Application of Natural Language Processing (NLP) has created new paradigms by analyzing and finding similarities between the treatment prescriptions extracted from Electronic Health Records (EHRs). Social Network Analysis (SNA) and centrality computation methods have opened new avenues to identify behavior patterns and mental health symptoms, forecasting therapy progression and personalization trajectories. In this paper, we develop a novel SNA graph model by preprocessing longitudinal Applied Behavior Analysis (ABA) treatment data of 29 patients using NLP methods and computing various centrality scores. We perform community detection at various temporal points during the six-month intervention duration and find patient similarity based on prescription and socio-demographic similarity-building edge weights. We develop a treatment recommendation model and match its outcome on recommendation and effectiveness measures with the ground truth. Our contribution explores novel approaches in determining the node influence of centrality measures on patient-level skill acquisition and treatment recommendation.

Students' acceptance of various technologies in their learning process has long been of interest to academics and practitioners. Amongst other models, the Technology Acceptance Model (TAM) has predominated in this area. Nevertheless, there has not been a single empirical study that has analyzed and compiled the results of all these TAM-based studies. As a result, we perform a comprehensive meta-analysis and apply Meta-Analytic Structural Equation Modelling (MASEM) for a conceptual framework to assess an effect size of 2,462 and a total sample size of 158,096 from 299 primary studies. Our findings reveal that enjoyment is the most prominent antecedent of TAM that plays a critical role in students’ technology acceptance behavior. Further, several methodological, cultural, and contextual moderators were confirmed. We then address the implications of these findings for both research and practice

Customers of various services have ever-changing expectations from service providers, placing critical pressure on providers to develop a synchronous, quick system that positively impacts user experiences while ensuring that providers are efficient, like ridesharing, home care, vehicle repairing, etc. To serve customers seamlessly and offer enhanced experience, businesses are turning to generative AI. Hence, this study conceptualizes an AI-enabled generative Cyber-Physical Servicescape (CPSC) structure and how different elements are related. This study adopted a grounded theory approach and used semi-structured interviews to collect data from 30 industry experts. First-order concepts, second-order themes, and aggregate dimensions are developed based on the interview data. This analysis further led to the emergence of four core elements of an AI-enabled generative CPSC: user interface, cybercore, servicescape design, and AI-based CPS servicescape. This study contributes to theory by developing four propositions and a framework that indicates the relationship between the four emerging elements of an AI-enabled generative CPSC. This study offers implications for theory and practice that can be considered when developing cyber-physical service systems in services and employing generative AI for best customer service.

In today's digital environment, organizations face security challenges like intentional breaches influenced by their specific policies and structures. As emerging technologies like Generative Artificial Intelligence (GAI) become more integrated into organizational processes, the adoption of GAI moderates organizational contextual conditions and rule characteristics, which affects the perceived risk of violating security rules. We extend the SOIPSV model to analyze cybersecurity practices and the strategic use of GAI in enhancing organizational resilience against security breaches. We establish the direct and moderating impacts of contextual conditions and rule characteristics, along with interactions in complex organizational cyber security. Our first study uses text mining for inferential and configurational analysis. Our second qualitative study explained the model of dynamic interplay between GAI and organizational factors. Our findings have implications for perceived risk management and managers redesigning business processes to manage security breaches.

Governments worldwide are investing many resources in developing digital government infrastructure and networks. Government webpages and supersites are substituting for their brick-and-mortar offices and physical state-citizen communication. This shift is transforming the administration and the process of digital government. We also see a growing push for expanding the role of citizens as participants and co-creators of policy and programs for establishing a collaborative digital government. This study examines the Indian e-government setup to explain how governments can ensure ‘accountability by policy design,’ or Digital Accountability (DA), on e-government service (eGS) websites. A mixed-method research design is used to uncover the critical design factors that can help build and maintain accountability on any government service (eGS hereafter) website. Our results show that Transparency remains the most important dimension, but concerns about security and privacy have also become foundational to the conceptualisation of accountability. Another important finding shows that building accountability is meaningful only if there is responsiveness and a sense of user control over the services. The findings also establish an explicit requirement to establish liability for service quality and effectively enforce a sense of accountability in modern eGS. We believe our findings can help improve the theoretical understanding of accountability in eGS while providing actionable insights to practitioners and policymakers to ensure accountable services in the digital age.

This study aims to explore how CSR-related messages posted by CEOs on social media are beneficial in fostering social capital, which in turn impacts the FP and online reputation of the firm. The study also examines whether there is any difference in FP due to sharing of CSR-related messages by CEOs before and during the pandemic. Hierarchical regression is used to examine the influence of CEOs CSR related tweets on FP and online reputation. The study reveals that by posting CSR-related messages on Twitter, CEOs can build social capital available on social media, which leads to better FP and online reputation. Findings also indicate that there is no statistically significant difference in FP and online reputation of the firm due to sharing of CSR-related messages by CEOs before and during the pandemic. Our research makes a significant addition to the empirical studies of CSR, social media and social capital theory.

In the digital era, governance is undergoing a transformation, moving state-citizen engagement into online realms, where citizens serve as users and collaborators in shaping services and policies. Empowering citizens to act as social innovators on issues affecting their lives and local communities is the key to facilitate this transition. As interactions between the state and citizens become more convenient, governments are increasingly focusing on digital citizen empowerment (DCE) to improve the life of their populace. Our study aims to understand the different dimensions of DCE and how it leads to better participation. It also aims to study the role of people's perception towards accountability mechanisms in place and how they can pave the way to enhanced participation behaviour. Employing a mixed-method approach, the study utilises structural equation modelling to examine the relation among e-participation, DCE, and public and social accountability. The results conceptualise DCE, identifying its four dimensions: emotional, cognitive, relational, and behavioural. Furthermore, it underscores the significance of citizens' perceptions of governmental and social accountability in fostering eparticipation. These findings are subsequently validated through a focus group discussion involving specialists from relevant fields. The results indicate that behavioural empowerment stands out as the most crucial aspect of DCE and that DCE enhances the quality of participation, with accountability mechanisms playing a pivotal role in achieving this outcome. Additionally, the findings reveal public disenchantment with e-government initiatives due to perceived administrative unresponsiveness. By pinpointing specific dimensions of individual empowerment, this study provides insights for policymakers to deliver accountable e-government services that promote enhanced e-participation.

Generative Artificial Intelligence (GAI) is witnessing a lot of adoption across industries, but literature is yet to fully document the nuances of these applications. We develop a comprehensive framework for understanding the factors that affect trust in online grocery shopping (OGS) using GAI chatbots. Our exploratory study was conducted via interviews, which helped to build our model. We integrate the Elaboration Likelihood Model (ELM) and Status Quo Bias (SQB) theory to develop the Unified Framework for Trust on Technology Platforms. In our confirmatory study, by analyzing 372 responses from users, using structural equation modelling (SEM), we initially validate our path model. Subsequently, we used fuzzy set qualitative comparative analysis (fsQCA) to check the causal combinations to explain different trust levels. Apart from perceived regret avoidance, all of the other factors had a significant effect on attitude and trust. Perceived anthropomorphism moderated the associations between interaction quality, credibility, threat, and attitude.

People with low or no digital literacy may not receive the digital transformation benefits. There are no-cost digital literacy programs to address this gap, whose outcomes need to be studied. Using survey data of 6989 unemployed females living below the poverty line in India, the present paper examines the linkage between the digital skills training program and empowerment. Economic empowerment measured through employment, education and entrepreneurship-seeking behavior, and psychological empowerment are studied. It also assesses the moderating role of perceived value derived from the training and the mediating role of actual skill usage in understanding the linkage. Results show that the moderating role of perceived value is important for economic empowerment and the mediating role of actual usage of learned digital skills is relevant for psychological empowerment. The paper contributes to the ICTD domain by highlighting that digital literacy training may lead to empowerment for poor women.

As Big Data applications become popular, firms harness their Big Data analytics capabilities for environmental insights. Literature suggests a positive correlation between these capabilities and firm performance, with dynamic capability potentially mediating this relationship. However, the mechanism by which Big Data analytics capabilities transform into dynamic capabilities remains underexplored. Additionally, the role of information technology (IT)-business strategic alignment as a boundary condition is not well-defined. We aim to address these gaps by exploring the impact of Big Data analytics capabilities on firm performance, the mediating function of dynamic capability, and the moderating influence of IT-business strategic alignment. A survey of 352 firms was conducted. Findings revealed a positive impact of Big Data analytics capabilities on firm performance with dynamic capability mediating this effect. IT-business strategic alignment was found to enhance the relationship between Big Data analytics capabilities and dynamic capability, thereby influencing firm performance. We contribute in Big Data analytics capabilities and dynamic capabilities by revealing that consensus problems within multiagent system or Big Data analysis platforms impede the effective transformation of Big Data analytics capability into organizational capabilities. Besides, this article incorporates insights from dynamic capability theory by exploring key predictors of IT-business strategic alignment in overcoming consensus problems and improving the likelihood of success.

Research questionThis study investigates the impact of fantasy sport on online sport fan identities. It explores the socio-psychological outcomes experienced by sport fans participating in fantasy sport and investigates their collaborative value co-creation practices.Research methodsWe use netnography to collect user comments across relevant subreddits. We further employ content analysis to identify the socio-psychological outcomes experienced by sport fans participating in fantasy sport and to gain insights into value co-creation practices within the fantasy sport community.FindingsThis study presents three significant findings. Firstly, it delineates BIRGing as celebration and trash talk and CORFing as disappointment, contemplation, and avoidance. Secondly, it introduces two new socio-psychological outcomes - FAGing and FARDing - encapsulating the dual identity of sport fans participating in fantasy sport. Third, it identifies three unique co-creation practices observed in fantasy sport communities - favoritism and subgrouping; sharing, supporting, and strategizing; and bragging.ImplicationsThis study contributes to our understanding of the impact of fantasy sport on the fan - team dynamic and the emergence of distinctive co-creation practices among evolved fans. From a practical perspective, the research has implications for sport managers and fantasy sport platforms, as fantasy sport serves as a powerful tool for engaging audiences of professional sport leagues.

The demand for skills in emerging technologies has recently surged among professionals. To meet this demand, the implementation of professional skilling programs on education technology platforms (PSPETPs) is necessary. However, there is still a significant gap in understanding the combined motivating and hindering factors underlying the intention to upskill in emerging technologies. This study aims to address this gap by proposing and empirically validating the enablers and barriers that impact the intention to purchase PSPETPs. Additionally, it seeks to verify the moderating effect of visibility in this context. The study is conducted in two phases. The first phase explores the critical dimensions, relying on online reviews on social media platforms. Then, in the second phase, online survey responses from a total of 429 PSPETP users are gathered. The moderating effect of visibility on the relationships and the mediating effect of purchase intention (PRI) between word-of-mouth communications are also tested. The findings suggest that barriers related to image, instruction quality, content quality, and word-of-mouth communication significantly impact PRI, which in turn affects purchase behavior. Besides broadening the innovation diffusion theory and dual-factor theory within the stimulus-organism-response framework, the findings offer practical directions for PSPETP businesses to improve their service offerings and provide additional value for users.

Purpose Digital platforms (DP) are transforming service delivery and affecting associated actors. The position of DPs is impacted by the regulations. However, emerging economies often lack the regulatory environment to support DPs. This paper aims to explore the regulatory developments for DPs using the multi-level perspective (MLP). Design/methodology/approach The paper explores regulatory developments of ride-hailing platforms (RHPs) in India and their impacts. This study uses qualitative interview data from platform representatives, bureaucrats, drivers, experts and policy documents. Findings Regulatory developments in the ride-hailing space cannot be explained as a linear progression. The static institutional assumptions, especially without considering the multi-actors and multi-levels in policy formulation, do not serve associated actors adequately in different times and spaces. The RHPs regulations must consider the perspective of new RHPs and the support available to them. Non-consideration of short- and long-term perspectives of RHPs may have unequal outcomes for established and new RHPs. Research limitations/implications This research has implications for the digital economy regulatory ecosystem, DPs and implications for policymakers. Though the data from legal documents and qualitative interviews is adequate, transactional data from the RHPs and interviews with judiciary actors would have been insightful. Practical implications The study provides insights into critical aspects of regulatory evolution, governance and regulatory impact on the DPs’ ecosystem. The right balance of regulations according to the business models of DPs allows DPs to have space for growth and development of the platform ecosystem. Social implications This research shows the interactions in the digital space and how regulations can impact various actors. A balanced policy can guide the paths of DPs to have equal opportunities. Originality/value DP regulations have a complex structure. The paper studies regulatory developments of DPs and the impacts of governance and controls on associated players and platform ecosystems.