Modelling continued use of information systems from a forward-looking perspective: Antecedents and consequences of hope and anticipated regret

Does AI-Driven Technostress Promote or Hinder Employees' Artificial Intelligence Adoption Intention? A Moderated Mediation Model of Affective Reactions and Technical Self-Efficacy

PURPOSE

The increasing integration of Artificial Intelligence (AI) within enterprises is generates significant technostress among employees, potentially influencing their intention to adopt AI. However, existing research on the psychological effects of this phenomenon remains inconclusive. Drawing on the Affective Events Theory (AET) and the Challenge-Hindrance Stressor Framework (CHSF), the current study aims to explore the "black box" between challenge and hindrance technology stressors and employees' intention to adopt AI, as well as the boundary conditions of this mediation relationship.

METHODS

The study employs a quantitative approach and utilizes three-wave data. Data were collected through the snowball sampling technique and a structured questionnaire survey. The sample comprises employees from 11 distinct organizations located in Guangdong Province, China. We received 301 valid questionnaires, representing an overall response rate of 75%. The theoretical model was tested through confirmatory factor analysis and regression analyses using Mplus and the Process macro for SPSS.

RESULTS

The results indicate that positive affect mediates the positive relationship between challenge technology stressors and AI adoption intention, whereas AI anxiety mediates the negative relationship between hindrance technology stressors and AI adoption intention. Furthermore, the results reveal that technical self-efficacy moderates the effects of challenge and hindrance technology stressors on affective reactions and the indirect effects of challenge and hindrance technology stressors on AI adoption intention through positive affect and AI anxiety, respectively.

CONCLUSION

Overall, our study suggests that AI-driven challenge technology stressors positively impact AI adoption intention through the cultivation of positive affect, while hindrance technology stressors impede AI adoption intention by triggering AI anxiety. Additionally, technical self-efficacy emerges as a crucial moderator in shaping these relationships. This research has the potential to make a meaningful contribution to the literature on AI adoption intention, deepening our holistic understanding of the influential mechanisms involved. Furthermore, the study affirms the applicability and relevance of Affective Events Theory (AET) and the Challenge-Hindrance Stressor Framework (CHSF). In practical terms, the research provides actionable insights for organizations to effectively manage employees' AI adoption intention.

Fake news believability: The effects of political beliefs and espoused cultural values

Fake news has led to a polarized society as evidenced by diametrically opposed perceptions of and reactions to global events such as the Coronavirus Disease 2019 (COVID-19) pandemic and presidential campaigns. Popular press has linked individuals’ political beliefs and cultural values to the extent to which they believe in false content shared on social networking sites (SNS). However, sweeping generalizations run the risk of helping exacerbate divisiveness in already polarized societies. This study examines the effects of individuals’ political beliefs and espoused cultural values on fake news believability using a repeated-measures design (that exposes individuals to a variety of fake news scenarios). Results from online questionnaire-based survey data collected from participants in the US and India help confirm that conservative individuals tend to exhibit increasing fake news believability and show that collectivists tend to do the same. This study advances knowledge on characteristics that make individuals more susceptible to lending credence to fake news. In addition, this study explores the influence exerted by control variables (i.e., age, sex, and Internet usage). Findings are used to provide implications for theory as well as actionable insights.

The role of affect in international opportunity recognition and the formation of international opportunity beliefs

Despite the significance of individual factors in how entrepreneurs recognize international opportunities either by active search or passive discovery, prior research has typically focused on cognitive aspects overlooking affect as a critical driver of this process. Drawing upon broaden-and-build and affect-as-information theories, we explore how courage, hope, fear of failure, and anticipated regret, as stable affective dispositions, can influence entrepreneurs’ active and passive international opportunity recognition (IOR). Also, based on the mental model theory, we examine whether both processes can lead entrepreneurs to differently form opportunity desirability and feasibility beliefs to judge the opportunities recognized in the foreign market. Based on data from a sample of 172 international entrepreneurs, we find that hope and anticipated regret are positively related to active IOR. Hope and courage are positively related to passive IOR, and fear of failure and anticipated regret are negatively related to passive IOR. Moreover, active IOR better informs opportunity desirability and feasibility beliefs than passive IOR, which indeed only predicts feasibility. These findings are original and novel and thus add value to the flourishing literature on the individual-level factors that influence IOR processes and the emerging literature on how international opportunity desirability and feasibility beliefs are formed to evaluate IOs.

Users’ Evaluation of a New Web Browser Payment Interface for Facilitating the Use of Multiple Payment Systems

The availability of multiple (mobile) electronic payment systems ((M)EPS) has led to the development of web browser payment interfaces that support various payment systems, facilitate the transaction, the choice of the payment system, and perform the payment. However, so far, no in-depth study on user satisfaction determinants with these interfaces has been conducted. Our work aims to cope with this issue. Thus, based on the analysis of payment literature and Google Chrome web browser (GCWB) payment interface, we propose a new web browser payment interface that considers users’ preferences to support multiple payment systems. Furthermore, we have developed a theoretical model to determine users’ preferences to support multiple payment systems. Our model is based on the extension of technology acceptance models. Finally, we evaluated both the theoretical and proposed payment interface through a survey research approach (n = 266); data were collected, and the hypotheses were tested via statistical analysis (chi-square test, regression coefficients). Our experimental results revealed that our proposed interface is accepted, easy to use, and satisfies users’ needs. The key factors for accepting a new web browser payment interface are ease of use, usefulness, security, confidentiality, privacy, payment method preferences, visual interface design, and credibility.

Assessing the Role of Simplicity in the Continuous Use of Mobile Apps

The proliferation of smartphones has provided a huge market for mobile apps and created a massive industry for developers/designers creating various mobile apps for use in our daily activities. However, with many mobile apps competition for users attention, the continued use of these apps has become a growing concern as users easily dump one app for another even after just a single use. This study examined the role of simplicity in the continuance use of mobile apps. The study extended the ECM with simplicity and showed that simplicity had a significant direct positive influence on confirmations, perceived usefulness, and satisfaction as well as a significant total indirect effect on continuance intentions. Additionally, all the ECM proposed relationships were confirmed. The study extends the current literature on continuance use of mobile apps by demonstrating the relevance of a concrete factor that developers/designs can manipulate to improve the continuance use for their mobile apps.

Dual paths to continuous online knowledge sharing: a repetitive behavior perspective

Purpose

Continuous knowledge sharing by active users, who are highly active in answering questions, is crucial to the sustenance of social question-and-answer (Q&A) sites. The purpose of this paper is to examine such knowledge sharing considering reason-based elaborate decision and habit-based automated cognitive processes.

Design/methodology/approach

To verify the research hypotheses, survey data on subjective intentions and web-crawled data on objective behavior are utilized. The sample size is 337 with the response rate of 27.2 percent. Negative binomial and hierarchical linear regressions are used given the skewed distribution of the dependent variable (i.e. the number of answers).

Findings

Both elaborate decision (linking satisfaction, intentions and continuance behavior) and automated cognitive processes (linking past and continuance behavior) are significant and substitutable.

Research limitations/implications

By measuring both subjective intentions and objective behavior, it verifies a detailed mechanism linking continuance intentions, past behavior and continuous knowledge sharing. The significant influence of automated cognitive processes implies that online knowledge sharing is habitual for active users.

Practical implications

Understanding that online knowledge sharing is habitual is imperative to maintaining continuous knowledge sharing by active users. Knowledge sharing trends should be monitored to check if the frequency of sharing decreases. Social Q&A sites should intervene to restore knowledge sharing behavior through personalized incentives.

Originality/value

This is the first study utilizing both subjective intentions and objective behavior data in the context of online knowledge sharing. It also introduces habit-based automated cognitive processes to this context. This approach extends the current understanding of continuous online knowledge sharing behavior.