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“Academic values” is one of the most popular terms used in the higher education literature. But how do we study academic values? Besides autonomy, freedom, and collegiality, the “values” in “academic values” often remains implicit, leaving a conceptual gap in the literature. Moreover, autonomy, freedom, and collegiality may reflect the shared normative expectations as part of the value system of a profession, rather than the value orientation at the individual level. To examine the latter, this chapter proposes a conceptual framework adapted from the studies of work values in applied psychology. As a heuristic device, the academic work value framework consists of six ideal-typical value orientations belonging to three dimensions: work autonomy, social orientation, and value of knowledge. The framework's relevance and usefulness are evaluated by revisiting relevant literature on academic orientations. The result shows a spectrum of value positions in academic work, from the “old school” values to the “entrepreneurial” ones to the hybrid orientations. Overall, this framework provides a potential approach to operationalize the concept of academic values for empirical research. At the same time, as a heuristic device, it is open for reflection, critique, and further development.

This study aims to understand a customer-purchase mechanism in the artificial intelligence (AI)-powered chatbot context based on the elaboration likelihood model (ELM) and technology acceptance model (TAM). The first objective is to examine how to boost chatbot adoption. The second objective is to investigate the role of information characteristics, technology-related characteristics and attitude toward AI in purchase intention.

Data was collected from a sample of 492 users in Vietnam, who are potential customers of chatbots for purchase. Structural equation modeling was applied for data analysis.

Results illustrate that chatbot adoption is significantly influenced by information credibility, technology-related factors (i.e. interactivity, relative advantage and perceived intelligence), attitude toward AI and perceived usefulness. Moreover, information quality and persuasiveness motivate information credibility. Information credibility and attitude toward AI are the essential motivations for perceived usefulness. Finally, chatbot adoption and information credibility determine purchase intention.

The results are insightful for practitioners to envisage the importance of chatbot use for customer purchase in the AI scenario. Additionally, this research offers a framework to practitioners for shaping customer engagement in chatbots.

The value of this work lies in the incorporation of technology-related characteristics into the two well-established theories, the ELM and TAM, to identify the importance of AI and its applications (i.e. chatbots) for purchase and to understand the formation of perceived usefulness and chatbot use through information credibility and attitude toward AI.

Looks at consumer research in Greater China including Mainland China, Hong Kong and Taiwan. Maps out the contributions within this area and guides future research. Examines the state of the art over the 1979‐97 period, with particular emphasis on the topics that have been researched, the extent of the theory development in the field and the methodologies used in conducting research. Uses content analysis to review 75 relevant articles. Suggests that, while a considerable breadth of topics have been researched, there remains much to be done, there is further room for theoretical development in Chinese consumer behaviour studies; and the methodologies used need improvement and further refinement.

Artificial intelligence (AI) has a significant impact on value co-creation (VCC). However, a study providing a comprehensive summary of the current state of the art and common ground of the two fields is missing. The current study aims to fill this gap by conceptualizing the role of AI in VCC and customer decision-making.

The study reviews literature on VCC and AI together, including a total of 108 articles. To bring the literature together, the authors adopted the antecedents-mediators-outcomes framework and narrative approach that helped them develop a framework by integrating the antecedents, mediators and outcomes of AI-facilitated VCC. Furthermore, the authors also operationalized existing literature to facilitate an understanding of the role of AI in customer decision-making.

The study, in addition to identifying the common theoretical grounds of VCC and AI (human behavior, cognition and social interactions), operationalizes AI functionality, its characteristics and customer characteristics as the antecedents of AI-facilitated VCC. Moreover, based on literature, on the continuum of low-to-high involvement, four types of decision-making were identified as mediator of the relationship between AI characteristics, customer characteristics and VCC. Additionally, the authors found different categorizations of AI in literature as archetypes to support various forms of VCC.

The study contributes to the literature of VCC and AI by construing a comprehensive framework for analyzing AI's impact on VCC, envisioning customer–AI interaction as continual exchange of advantages in which characteristics of AI and customers play a critical role in customer decision-making and shaping VCC.

The recent progress of digital accounting has significantly affected businesses’ sustainable production process. Businesses generally use digital accounting applications to automate their operational procedures and increase their corporate efficiencies through improved output quality and sustainability. Consequently, the purpose of this study is to look into the antecedent factors that directly and indirectly influence blockchain technology adoption in the context of digital accounting systems.

The data of the current study were obtained from 346 accountants working in information technology companies. Partial least squares structural equation modeling was used to test the research proposal model.

The empirical results confirmed that the adoption of blockchain technology is most considerably impacted by perceived usefulness, whereby it was also revealed that perceived ease of use has a direct and indirect effect on blockchain technology adoption.

According to the researchers’ knowledge, this study addresses a vital research gap in the literature by suggesting a comprehensive research model that can help garner enhanced usage of blockchain technology and its implications in digital accounting systems in the Jordanian context.

AI-based chatbots are revamping employee communication in organizations. This paper examines the adoption of AI-based employee experience chatbots by employees.

The proposed model is developed using behavioral reasoning theory and empirically validated by surveying 1,130 employees and data was analyzed with PLS-SEM.

This research presents the “reasons for” and “reasons against” for the acceptance of AI-based employee experience chatbots. The “reasons for” are – personalization, interactivity, perceived intelligence and perceived anthropomorphism and the “reasons against” are perceived risk, language barrier and technological anxiety. It is found that “reasons for” have a positive association with attitude and adoption intention and “reasons against” have a negative association. Employees' values for openness to change are positively associated with “reasons for” and do not affect attitude and “reasons against”.

This is the first study exploring employees' attitude and adoption intention toward AI-based EEX chatbots using behavioral reasoning theory.

Technology is widely recognised to be revolutionising the accounting profession, allowing accountants to focus on professional skills and technical knowledge that deliver value for organisational success. Despite the known benefits, it is reported that accountants are not fully leveraging the potential value of certain technologies. To understand why, this study aims to draw on the technology adoption model (TAM) and investigates accounting professionals’ perceptions towards technology, and how these may influence adoption at work.

The study gathered online survey data from 585 accounting managers from organisations of varying sizes and in different sectors in Australia and parts of Southeast Asia. Qualitative data were thematically analysed, and quantitative data were analysed using both descriptive and multivariate techniques.

The study highlighted the pivotal role of staff perceptions on the importance and ease of using technology on the uptake and successful usage. Findings emphasised important opportunities for organisations to educate accounting staff on the value of technology and optimise their confidence and skills through training and support initiatives, particularly smaller businesses. Marked differences in the orientation towards technology among Australian and Southeast Asian participants illuminate how national work culture and practice can influence technology adoption.

The study makes a practical contribution by advancing the understanding of the relative importance and value of certain technologies in different regions and organisation types in the accounting profession. It extends the theoretical understanding of the role of TAM’s core elements to the accounting context, exploring staff’s notions of perceived usefulness and perceived ease of use from the manager’s perspective.

The purpose of this paper is to investigate students' adoption intention (ADI) and actual usage (ATU) of artificial intelligence (AI)-based teacher bots (T-bots) for learning using technology adoption model (TAM) and context-specific variables.

A mixed-method design is used wherein the quantitative and qualitative approaches were used to explore the adoption of T-bots for learning. Overall, 45 principals/directors/deans/professors were interviewed and NVivo 8.0 was used for interview data analysis. Overall, 1,380 students of higher education institutes were surveyed, and the collected data was analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique.

The T-bot's ADI’s antecedents found were perceived ease of use, perceived usefulness, personalization, interactivity, perceived trust, anthropomorphism and perceived intelligence. The ADI influences the ATU of T-bots, and its relationship is negatively moderated by stickiness to learn from human teachers in the classroom. It comprehends the insights of senior authorities of the higher education institutions in India toward the adoption of T-bots.

The research provides distinctive insights for principals, directors and professors in higher education institutes to understand the factors affecting the students' behavioral intention and use of T-bots. The developers and designers of T-bots need to ensure that T-bots are more interactive, provide personalized information to students and ensure the anthropomorphic characteristics of T-bots. The education policymakers can also comprehend the factors of T-bot adoption for developing the policies related to T-bots and their implications in education.

T-bot is a new disruptive technology in the education sector, and this is the first step in exploring the adoption factors. The TAM model is extended with context-specific factors related to T-bot technology to offer a comprehensive explanatory power to the proposed model. The research outcome provides the unique antecedents of the adoption of T-bots.

Artificial intelligence (AI) is a powerful and promising technology that can foster the performance, and competitiveness of micro, small and medium enterprises (MSMEs). However, the adoption of AI among MSMEs is still low and slow, especially in developing countries like Jordan. This study aims to explore the elements that influence the intention to adopt AI among MSMEs in Jordan and examines the roles of firm innovativeness and government support within the context.

The study develops a conceptual framework based on the integration of the technology acceptance model, the resource-based view, the uncertainty reduction theory and the communication privacy management. Using partial least squares structural equation modeling – through AMOS and R studio – and the importance–performance map analysis techniques, the responses of 471 MSME founders were analyzed.

The findings reveal that perceived usefulness, perceived ease of use and facilitating conditions are significant drivers of AI adoption, while perceived risks act as a barrier. AI autonomy positively influences both firm innovativeness and AI adoption intention. Firm innovativeness mediates the relationship between AI autonomy and AI adoption intention, and government support moderates the relationship between facilitating conditions and AI adoption intention.

The findings provide valuable insights for policy formulation and strategy development aimed at promoting AI adoption among MSMEs. They highlight the need to address perceived risks and enhance facilitating conditions and underscore the potential of AI autonomy and firm innovativeness as drivers of AI adoption. The study also emphasizes the role of government support in fostering a conducive environment for AI adoption.

As in many emerging nations, the AI adoption research for MSMEs in Jordan (which constitute 99.5% of businesses), is under-researched. In addition, the study adds value to the entrepreneurship literature and integrates four theories to explore other significant factors such as firm innovativeness and AI autonomy.