The present research aims to highlight the underlying factors that drive students’ adoption of the ChatGPT chatbot in higher education. This study extends the meta-UTAUT framework by including additional exogenous factors of anthropomorphism, trust, design novelty, and institutional policy. Empirical examination with Structural Equation Modelling among 355 students in Dutch higher education institutions revealed attitude and behavioural intention as significant positive predictors of students’ ChatGPT use behaviour. Institutional policy negatively moderated the effect of behavioural intention on use behaviour. Behavioural intention was significantly and positively influenced by attitude, performance expectancy, social influence, and facilitating conditions. Anthropomorphism, design novelty, trust, performance expectancy, and effort expectancy were unveiled as significant positive antecedents of attitude. The central theoretical contributions of this research include investigating students’ use behaviour instead of behavioural intention, establishing attitude as a core construct, underlining additional antecedents of attitude, and highlighting the importance of institutional policy. The present study contributes to prior research on technology adoption, especially in the area of artificial intelligence in education. The findings yield valuable insights for chatbot designers, product managers, and higher education policy writers.

@en

Purpose
The objective is to identify the effects of suspicion as well as knowledge gaps, especially in non-interpersonal contexts. This study aims to propose a robust framework for future research. The overarching goal is to foster a comprehensive understanding of consumer suspicion, its implications and its potential avenues in the ever-evolving field of consumer behavior.

Design/methodology/approach
Based on a focused review of the literature, this study synthesizes the effects of suspicion in interpersonal and non-interpersonal contexts to unveil its importance for consumer behavior.

Findings
The cognitive, affective and behavioral effects of suspicion are identified. Furthermore, a discernible imbalance is observed, as the predominant focus on interpersonal consumer contexts leaves a significant gap in the comprehension of how consumers navigate and perceive suspicion in noninterpersonal interactions. This topic is important especially in an era dominated by complex brand interrelationships and digital touchpoints. Also, the operationalization of the suspicion construct in a plethora of studies seems to be suboptimal, suggesting a need for improvements with respect to its dynamic nature. In this regard, this review provides insightful directions to advance research in the abovementioned domains.

Research limitations/implications
The synthesis of the findings of the empirical articles did not focus on variations in consumer suspicion across different cultures or regions. In addition, the dynamic nature of suspicion and the evolving landscape of consumer behavior mean that findings and implications may require periodic reassessment to maintain relevance. Also, this review did not delve into the methodological diversities across the studies examined.

Practical implications
This review offers marketers and businesses critical insights into the consumer suspicion dynamics. By understanding these nuances, companies can tailor strategies to mitigate suspicion and optimize consumer relationships.

Originality/value
Through synthesizing the effects of suspicion and providing avenues for future research, this study significantly contributes to consumer behavior literature.@en

While the rise of artificial intelligence (AI) tools holds promise for delivering benefits, it is important to acknowledge the associated risks of their deployment. In this article, we conduct a focused literature review to address two central research inquiries concerning ChatGPT and similar AI tools. Firstly, we examine the potential pitfalls linked with the development and implementation of ChatGPT across the individual, organizational, and societal levels. Secondly, we explore the role of a multi-stakeholder responsible research and innovation framework in guiding chatbots’ sustainable development and utilization. Drawing inspiration from responsible research and innovation and stakeholder theory principles, we underscore the necessity of comprehensive ethical guidelines to navigate the design, inception, and utilization of emerging AI innovations. The findings of the focused review shed light on the potential perils of ChatGPT implementation across various societal levels, including issues such as devaluation of relationships, unemployment, privacy concerns, bias, misinformation, and digital inequities. Furthermore, the proposed multi-stakeholder Responsible Research and Innovation framework can empower AI stakeholders to proactively anticipate and deliberate upon AI’s ethical, social, and environmental implications, thus substantially contributing to the pursuit of responsible AI implementation.

@en

As the field of artificial intelligence (AI) continues to progress, the use of AI-powered chatbots, such as ChatGPT, in higher education settings has gained significant attention. This paper addresses a well-defined problem pertaining to the critical need for a comprehensive examination of students' ChatGPT adoption in higher education. To examine such adoption, it is imperative to focus on measuring actual user behavior. While measuring students' ChatGPT usage behavior at a specific point in time can be valuable, a more holistic approach is necessary to understand the temporal dynamics of AI adoption. To address this need, a longitudinal survey was conducted, examining how students' ChatGPT usage behavior changes over time among students, and unveiling the drivers of such behavior change. The empirical examination of 222 Dutch higher education students revealed a significant decline in students' ChatGPT usage behavior over an 8 month period. This period was defined by two distinct data collection phases: the initial phase (T1) and a follow-up phase conducted 8 months later (T2). Furthermore, the results demonstrate that changes in trust, emotional creepiness, and Perceived Behavioral Control significantly predicted the observed change in usage behavior. The findings of this research carry significant academic and managerial implications, as they advance our comprehension of the temporal aspects of AI adoption in higher education. The findings also provide actionable guidance for AI developers and educational institutions seeking to optimize student engagement with AI technologies.@en

This report provides an overview of the individual and contextual factors that have been found to influence households’ recycling and sorting of their waste, including recycling of plastic waste. It also unveils a comprehensive overview on how specific intervention strategies could encourage households to recycle more frequently and effectively. Finally, the academic report includes guidelines that can help foster households’ recycling and sorting behaviour@en

Consumers have a positive attitude towards products made from recycled materials; however, they frequently end up not purchasing them. To shed light on the factors that influence consumer preferences and acceptance of products made from recycled materials, a scoping review was conducted with the following objectives: (1) to explore which factors are drivers of the acceptance of products made from recycled materials, (2) to identify and analyse potential barriers for their adoption, and (3) to formulate recommendations for future research in order to further enhance choices of alternatives made from recycled materials. The review of the results from 46 articles demonstrated that factors such as environmental benefits, perceived quality, safety, risks, emotions, and individual differences influence consumer acceptance of products made from recycled materials. The present review presents the state-of-the-art of the existing literature and future potential directions that can be fruitful for academics and practitioners interested in the topic.

@en

The circular economy can reduce the environmental footprint of today’s consumption and close the resource loop through circular material flows. Companies are encouraged to fol- low circular principles, such as using more recycled plastic materials. This initiative seems promising; however, it will only be successful if consumers are willing to adopt productsthat are made from recycled plastics. Consumers often have a positive image of products made from recycled plastics; however, they are also concerned about the perceived product risks. How can companies increase the appeal of recycled plastics to consumers? In this paper, we propose a set of seven guidelines intended to highlight the value of products
made from recycled plastics, tackle any perceived risks, and thereby enhance consumer acceptance of such products. Specifically, we highlight how aspects related to product design, marketing elements and business models, can increase consumer evaluations and adoption of products made from recycled plastics. The proposed guidelines provide future directions that could be inspiring for both academics and managers interested in the topics of consumer behaviour, circular economy, and sustainability@en

The impact of incidental emotions on decision making is well established. Incidental emotions can be differentiated on several appraisal dimensions, including certainty–uncertainty. The present research investigates the effect of certainty–uncertainty of incidental emotions on hedonic forecasting. The results of four experimental studies indicate that uncertainty-associated incidental emotions, such as fear and hope, compared with certainty emotions, such as anger and happiness, amplify predicted utility. This amplification effect is confirmed for opposite utility types; uncertainty-associated emotions, when compared with their certainty counterparts, lead to an overprediction of positive utilities and to an underprediction of negative utilities. This effect is mediated by the prediction task uncertainty, providing evidence for a carryover process of the incidental emotion. The effect of task uncertainty on predicted utility is, in turn, partly mediated by attention to the task, suggesting that an affective adaptation process lies behind the amplification of forecasts. Taken together, these findings extend the impact of certainty–uncertainty to the context of hedonic forecasting and further corroborate the impact of incidental emotions in judgment and decision making.

@en