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As businesses keep investing substantial resources in developing business analytics (BA) capabilities, it is unclear how the performance improvement transpires as BA affects performance in many different ways. This paper aims to analyze how BA capabilities affect firms’ agility through resources like information quality and innovative capacity considering industry dynamism and the resulting impact on firm performance.

This paper tested the research hypothesis using primary data collected from 192 companies operating in Bangladesh. The data were analyzed using partial least squares-based structural equation modeling.

The results indicate that BA capabilities improve business resources like information quality and innovative capacity, which, in turn, significantly impact a firm’s agility. This paper also found out that industry dynamism moderates the firms’ agility and, ultimately, firms’ performance.

The contribution of this work provides insight regarding the role of business analytics capabilities in increasing organizational agility and performance under the moderating effects of industry dynamism.

The present research is to the best of the authors’ knowledge among the first studies considering a firm’s agility to explore the impact of BA on a firm’s performance in a dynamic environment. While previous researchers discussed resources like information quality and innovative capability, current research theoretically argues that these items are a leveraging point in a BA context to increase firm agility.

A major portion of our social interaction now occurs online, facilitated by social networking sites (SNSs) that enable people to connect and communicate at will. However, the characteristics of SNS communication can introduce problematic outcomes on otherwise healthy processes, one of which is social comparison. In this work, we investigate whether compulsive SNS use could be driven by two phenomena related to social comparison: the fear of missing out (FoMO) and envy.

Using the stimulus-organism-response framework, we developed a model that was tested with data from a sample of SNS users (N = 330) based in the United States. The analysis was done through partial least squares structural equation modeling.

Our findings show FoMO's association with the two forms of dispositional experienced envy, benign and malicious, as well as expected envy of others (expected envy). Interestingly, benign and expected envy were associated with SNS stalking and self-disclosure, but malicious envy had non-significant associations. Finally, both SNS stalking and self-disclosure were linked to compulsive SNS use.

We study the nuanced ways in which the two forms of experienced envy and expected envy can be triggered by FoMO and result in users' engagement with problematic SNS use. Our research provides evidence that, in addition to benign envy being an antecedent of compulsive SNS use, the wish to invoke envious feelings in others can also significantly drive compulsive use.

There is little empirical evidence on how blockchain affordances may encourage consumers to make sustainable choices. Thus, this paper examines how blockchain affordances affect consumers’ sustainable consumption.

We focus on three blockchain affordances: transparency, traceability, and immutability in this paper. By integrating the affordance lens and theory of consumption values (TCV), we develop a research model wherein we posit that blockchain affordances influence several consumption values, which then affect consumers’ intention to purchase sustainable products. In the study, we designed a scenario and user interface for a novel blockchain-based app for sustainable consumption in the context of the fashion industry and surveyed 295 European consumers to examine the study’s research model. We then analyzed the collected data using the partial least squares technique.

The results show that blockchain affordances positively affect consumption values, including efficiency, social impression, trust, and sustainability information clarity. In turn, these values influence the consumers’ purchase intention of sustainable products. Additionally, our post hoc analysis shows that these consumption values fully mediate the effect of blockchain affordances on consumers’ purchase intention, where trust and sustainability information clarity is found to have a higher impact.

Empirical research studies focusing on understanding blockchain’s effect on sustainable consumption values have been limited in prior literature. This study, drawing on the affordance lens, proposes distinct blockchain affordances and empirically validates their impact on consumers’ sustainable purchase intention. By integrating TCV, it highlights the mediating mechanism that drives blockchain’s impact on consumers’ purchase intention. We empirically identify the values that mediate the effects of blockchain affordances on consumers’ purchase intention; further, we discuss implications for research and practice based on the study findings.

Against the backdrop of dynamic capabilities theory, this research examines the relationship between knowledge and marketing agility in the context of big data marketing analytics (BDMA). The relevant knowledge constructs under investigation are business/marketing, relational, technological and technology management. The level of BDMA deployment is also examined to determine its impact on these relationships.

A survey was used to gather data from marketing professionals working in firms with at least limited experience in big data (BD) deployment in the United States and Canada. The results were analyzed using partial least squares structural equation modeling (PLS-SEM) with a sample of 236 responses.

The results indicate that marketing professionals perceived the knowledge and marketing agility constructs differently than the previous research on IT professionals. The knowledge construct was perceived as a two-dimensional construct consisting of broad knowledge skills and specific technical knowledge skills. Only the broad knowledge skills construct was significantly related to the marketing agility construct, with progressively high predictive validity and relevance when the deployment of BDMA progresses.

The paper's originality stems from the different conceptualizations of the knowledge and marketing agility constructs due to the use of a novel sample of marketing professionals in this study. The research also contributes to the dynamic capabilities theory by emphasizing the critical role of vital knowledge when aiming to enhance marketing agility.

For undergraduate and graduate students in universities, social media are playing an important role in their study/research because a large amount of academic information has been accumulated on social media. Indeed, social media are complementing university libraries. Given that intelligent recommender systems have been widely implemented on social media, this paper aims to examine the adoption mechanism of intelligently recommended information by university students in their study/research.

Building upon the updated information system success model and herding theory, this study developed a research model to examine the determinants of recommended information adoption in mobile applications for social media. Data were collected through an online questionnaire and analyzed with partial least squares structural equation modelling.

The results suggest that herding belief is a valid second-order construct, comprising two first-order dimensions of imitating others and discounting their own information. Information quality, system quality and service quality directly impact satisfaction with the intelligent recommender system. Furthermore, satisfaction with the intelligent recommender system and herding belief directly impact recommended information adoption by university students in their study/research.

This study draws on the updated information system success model and incorporates herding belief as an extended component to investigate recommended information adoption, providing a new lens for understanding recommended information adoption by university students in their study/research.

The purpose of this study is to examine how the interplay of stressor (e.g. fear of missing out, FoMO) and strains (e.g. perceived social overload, communication overload, information overload and system feature overload) in social networking sites (SNS) use can contribute to users’ SNS fatigue from a configurational view.

Data were collected among 363 SNS users in China via an online survey, and fuzzy-set qualitative comparative analysis (fsQCA) was applied in this study to scrutinize the different combinations of FoMO and overload that contribute to the same outcome of SNS fatigue.

Six combinations of casual conditions were identified to underlie SNS fatigue. The results showed that FoMO, perceived information overload and system feature overload are the core conditions that contribute to SNS fatigue when combined with other types of overloads.

The current work supplements the research findings on SNS fatigue by identifying the configurations contributing to SNS fatigue from the joint effects of stressor (FoMO) and strain (perceived social overload, communication overload, information overload and system feature overload) and by providing explanations for SNS fatigue from the configurational perspective.

This study uses a participatory action research (PAR) approach to evaluate the implementation and impact of the government of Tanzania health operation management information system (GoTHOMIS) on healthcare services in Tanzania. The primary objective is to assess the strengths, weaknesses and overall impact of GoTHOMIS.

The research uses a PAR methodology, involving active engagement with stakeholders from healthcare facilities, administrators and information technology experts. Data collection methods consist of key informant interviews and document analysis. The study strategically examines various aspects, including pre-implementation planning, challenges during implementation, system features and the strengths and weaknesses of GoTHOMIS. Furthermore, the focus extends to understanding the impact of GoTHOMIS on healthcare services.

The findings underscore critical areas for improvement, particularly in the pre-implementation planning stage. The study reveals issues related to a top-down approach and insufficient user participation, hindering the successful implementation of GoTHOMIS. Challenges such as inadequate infrastructure, power outages, missing diagnostic codes and compatibility issues with peripheral devices are identified. Despite these hurdles, GoTHOMIS exhibits strengths like improved accessibility, integration with the reporting system by the MTUHA government and automation of clinical tasks.

The study’s originality lies in applying a PAR approach to assess GoTHOMIS. This methodology provides valuable insights into the implementation challenges and suggests potential improvements. The study contributes to the existing body of knowledge by offering a detailed understanding of GoTHOMIS’s strengths and weaknesses, enhancing the potential for effective health management information systems.

On the basis of the conservation of resources theory (CORT), this study investigates the relationship between social overload and users’ withdrawal intention from social communities on social networking sites (SNSs), with the serial mediating mechanisms of social-psychological distance and emotional exhaustion and the moderating mechanism of (similar) linguistic style.

Data were collected from 489 users in different social communities on SNSs in an emerging market. Structural equation modeling was used to analyze the sample data and test the hypotheses.

Results show that social overload has a positive influence on withdrawal intention from social communities on SNSs. Furthermore, social-psychological distance and emotional exhaustion have a serial mediating effect in this relationship. In addition, (similar) linguistic style negatively moderates the link between social overload and emotional exhaustion and that between social overload and withdrawal intention.

This study extends CORT to propose and test a unique research model that clarifies the mechanisms leading to users’ withdrawal behavior from social communities on SNSs. The findings of this study provide implications for researchers, individual users, administrators/managers of social communities, and SNS providers to understand and make better decisions to retain member users.

Prior research has extensively examined how bringing technology from work into the non-work life domain creates conflict, yet the reverse pathway has rarely been studied. The purpose of this study is to bridge this gap and examine how the non-work use of smartphones in the workplace affects work–life conflict.

Drawing from three literature streams: technostress, work–life conflict and role boundary theory, the authors theorise on how limiting employees' ability to integrate the personal life domain into work, by means of technology use policy, contributes to stress and work–life conflict. To test this model, the authors employ a natural experiment in a company that changed its policy from fully restricting to open smartphone access for non-work purposes in the workplace. The insights gained from the experiment were explored further through qualitative interviews.

Work–life conflict declines when a ban on using smartphones for non-work purposes in the workplace is revoked. This study's results show that the relationship between smartphone use in the workplace and work–life conflict is mediated by sensed stress. Additionally, a post-hoc analysis reveals that work performance was unchanged when the smartphone ban was revoked.

First, this study advances the authors' understanding of how smartphone use policies in the workplace spill over to affect non-work life. Second, this work contributes to the technostress literature by revealing how, in specific situations, engagement with ICT can reduce distress and strain.

Artificial intelligence (AI) has received much attention due to its promethean-like powers to transform the management and delivery of public sector services. Due to the proliferation of research articles in this context, research to date is fragmented into research streams based on different types of AI technologies or a specific government function of the public sector (e.g. health, education). The purpose of this study is to synthesize this literature, identify challenges and opportunities, and offer a research agenda that guides future inquiry.

This paper aggregates this fragmented body of knowledge by conducting a systematic literature review of AI research in public sector organisations in the Chartered Association of Business Schools (CABS)-ranked journals between 2012 and 2023.

The search strategy resulted in the retrieval of 2,870 papers, of which 61 were identified as primary papers relevant to this research. These primary papers are mapped to the ten classifications of the functions of government as classified by the Organisation for Economic Co-operation and Development (OECD), and the reported challenges and benefits aggregated.

This study advances knowledge by providing a state-of-the-art of AI research based the OECD classifications of government functions, reporting of claimed benefits and challenges and providing a research agenda for future research.