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This study pinpoints the critical factors influencing the acceptance of blockchain technology in supply chain management in the light of the extended unified theory of acceptance and use of technology (UTAUT2) with additional factors personal innovativeness in technology and user's self-efficacy.

The questionnaire-based data was obtained from SC professionals in China (Beijing). The essential factors influencing it are evaluated through structural equation modeling (SEM), using AMOS software.

The empirical findings specify that performance expectancy, facilitating conditions, price value, hedonic motivation, user self-efficacy, and personal innovativeness are positively influencing user satisfaction. User satisfaction has a substantial progressive effect on habit. Furthermore, facilitating conditions, price value, habit, user self-efficacy, personal innovativeness, and user satisfaction have a progressive impact on continued intention to use blockchain technology in supply chain management.

Although numerous studies investigated the influencing factors of blockchain technology adoption in supply chain management, no study examined the determinants of UTAUT2. However, this study not only empirically studied the UTAUT2 model but also extended it with the most influencing elements such as personal innovativeness in technology and user's self-efficacy. Furthermore, this study contributes to the BT-enabled SCM literature by studying the continued use and acceptance, rather than testing behavioral intention and initial adoption which is common in previous studies of BT-enabled SCM. Finally, this study discusses the limitations, future directions, and managerial implications of the results so that supply chain professionals can deliver what supply chain stakeholders require.

The existing technology acceptance models have not yet investigated functional and motivational factors impacting trust in and use of conversational artificial intelligence (AI) by integrating the feedback and sequential updating mechanisms. This study challenged the existing models and constructed an integrated longitudinal model. Using a territory-wide two-wave survey of a representative sample, this new model examined the effects of hedonic motivation, social motivation, perceived ease of use, and perceived usefulness on continued trust, intended use, and actual use of conversational AI.

An autoregressive cross-lagged model was adopted to test the structural associations of the seven repeatedly measured constructs.

The results revealed that trust in conversational AI positively affected continued actual use, hedonic motivation increased continued intended use, and social motivation and perceived ease of use enhanced continued trust in conversational AI. While the original technology acceptance model was unable to explain the continued acceptance of conversational AI, the findings showed positive feedback effects of actual use on continued intended use. Except for trust, the sequential updating effects of all the measured factors were significant.

This study intended to contribute to the technology acceptance and human–AI interaction paradigms by developing a longitudinal model of continued acceptance of conversational AI. This new model adds to the literature by considering the feedback and sequential updating mechanisms in understanding continued conversational AI acceptance.

Discusses chronic fatigue syndrome (CFS), which is a “contested disease”, that is, it is not recognized by the medical profession as a legitimate illness and, consequently, people suffering from the illness are not eligible for support/aid. Explores what this non‐recognition means and the impact it has on both the sufferers and their families. Refers to repetitive strain injury and Alzheimer’s disease – neither of which were recognized by medical professionals until recent times – as examples of illnesses that have gained medical legitimacy. Reports that sufferers of CFS, who did not receive an adequate medical diagnosis, were under pressure to become active again, whereas sufferers who received a diagnosis of persistent fatigue gained a lot more support from family and friends. Investigates also the strains involved in coping with a family member with an illness such as Alzheimer’s disease or CFS – as ever economic resources figure prominently. Raises the issue of management of illness in modern society. Recommends that, as health care is pushed ever more onto families and the community, so they should be the recipients of financial support.

This paper aims to propose and test a modified technology acceptance model for the social media networks (SMNs) in the luxury hotel context, integrating satisfaction and continued usage intention, using a mixed-method approach. SMNs have revolutionized the way people communicate, search for information and share experiences. The technology acceptance model is the predominant theory for researching technology acceptance; however, there is a gap in identifying and testing context-specific constructs.

This paper uses a mixed-method approach. The researchers conducted 16 interviews and 258 questionnaires with luxury hotel guests. Following the collection of data, interviews and questionnaires were analyzed using thematic and partial least square analysis.

Findings show that accessibility, trust, social influence and perceived benefits influence perceived ease of use and perceived usefulness, which affect attitude and satisfaction and ultimately continued usage intentions. Findings also reveal that enjoyment, although qualitatively proposed, does not influence luxury hotel guests’ SMNs continued usage intention.

This study suggests that hotel managers have to concentrate their marketing efforts in enhancing SMN’s interaction and increasing the number of positive reviews to retain current customers and acquire new ones. Hotels should also develop effective mobile strategies by adopting mobile social network webs and applications, as accessibility becomes more important in today’s marketplace.

Former scholars adopted the approach of proposing external dimensions based on previous research and, thus, did not integrate up-to-date and context-specific variables. Therefore, the present paper uses a new approach by exploring SMN-specific dimensions and testing them in the luxury hotel context.

Wearable health technologies (WHTs) show promise in improving the health and well-being of the aging population because they promote healthy lifestyles. They can be used to collect health information from users and encourage them to be physically active. Despite potential benefits of WHTs, recent studies have shown that older people have low continued use intention toward WHTs. Previous work on this topic is disjointed, and new theoretical viewpoints are required.

The authors propose an enablers and inhibitors perspective to model factors influencing continued use intention of WHTs among the elderly. To test the model, we collected data from Chinese elderly (N = 295) who had prior experience using WHTs.

The study results show that social value is the strongest enabler of continued WHT use, and emotional and epistemic values and device quality also increase use continuance. Inertia and technology anxiety were identified as significant inhibitors. A post hoc importance performance map analysis revealed that while emotional value is a highly significant predictor of continued WHT use, existing WHTs do not stimulate such value in our sample.

The research findings illustrate the importance of incorporating user resistance in technology acceptance studies in general and WHT usage studies in particular. This study contributes by providing an integrative model of technology continued use intention for the elderly along with practical implications for policymakers.

A limited number of prior studies have taken both enablers and inhibitors into account when explaining continued WHT use intention among the elderly. This paper fills this research gap and contributes to the WHT literature by considering both enablers and inhibitors in the same model. Moreover, this study contributes to the ongoing research on WHT, and more broadly, gerontechnology use among the elderly.

This study aims to understand the learner behaviour of millennials for Massive Open Online Courses (MOOCs) in the post-adoption stage by extending the theory of Unified Theory of Acceptance and User Technology 2 (UTAUT2) with expectancy confirmation model (ECM) along with personal innovativeness as the exogenous, satisfaction as a mediating and continued intention as an endogenous construct.

This study applied a cross-sectional research design by using a survey method to collect primary data with a structured questionnaire. Convenience sampling was used to collect data from millennial MOOC users, and partial least square structural equation modelling method was applied for data analysis.

The results indicate that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation influence satisfaction. Similarly, performance expectancy, hedonic motivation, personal innovativeness and satisfaction influence the continued intention for MOOCs.

In terms of limitations, the study applied a cross-sectional research design that could lead to data collection bias. Similarly, the study used convenience sampling as the authors did not have access to the participant list of users from MOOC platforms.

The research highlights various insights to all the stakeholders on improving MOOC satisfaction and enhance the continued intention for millennial learners.

The findings of this research bridge this gap by examining the post-adoption usage behaviour of MOOCs by extending the baseline model of UTAUT2 with personal innovativeness and integrating it with ECM.

The purpose of this paper is to explore the key antecedents of organizational users’ continuance intention of cloud enterprise resource planning (ERP) by the integration of constructs from the expectation–confirmation model (ECM), technology acceptance model (TAM), theory of planned behavior (TPB), task-technology fit and TAM2.

Sample data for this study were collected from end users of cloud ERP working in companies in Taiwan. A total of 560 questionnaires were distributed in the 56 sample companies, and 395 (70.5 percent) usable questionnaires were analyzed using structural equation modeling in this study.

Findings show that while compatibility and output quality are key antecedents of confirmation of expectations toward cloud ERP, compatibility still reveals overwhelming and more indirect impacts on users’ continuance intention of cloud ERP than output quality because output quality has significant but evidently lesser effects on perceived usefulness and perceived ease of use than compatibility.

First, this study contributes to the identification of compatibility and output quality that may reveal deep insights to the task-related factors in understanding users’ cloud ERP continuance greatly driven by their confirmation of expectations toward cloud ERP. Next, the empirical evidence on capturing the ECM, TAM and TPB for completely explaining the antecedents of users’ continued cloud ERP usage intention is well documented. Hence, this study’s findings have significantly shed light on the possible formulation of a richer post-adoption model.

Wearable health devices (WHDs) have demonstrated significant potential in assisting elderly adults with proactive health management by utilizing sensors to record and monitor various aspects of their health, including physical activity, heart rate, etc. However, limited research has systematically explored older adults’ continued usage intention toward WHD. By utilizing the extended unified theory of acceptance and use of technology (UTAUT2), this paper aims to probe the precursors of elderly adults’ continuance intention to use WHD from an enabler–inhibitor perspective.

The research model was developed based on UTAUT2 and examined utilizing the partial least squares technique (PLS). The research data were collected through in-person meetings with older people (n = 272) in four cities in China.

Results reveal that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic values and perceived complexity are the positive predictors of elderly adults’ continuance intention to use WHDs. Technology-related anxiety and usage cost negatively influence the formation of older people’s continuance intention.

This work is an original empirical investigation that draws on several theories as guiding frameworks. It adds to the existing literature on the usage of wearable technologies and offers insights into how the elderly’s intentions to continue using WHDs can be developed. This study broadens the scope of the UTAUT2 application and presents an alternative theoretical framework that can be utilized in future research on the usage behavior of wearable devices by individuals.

The purpose of this paper is to identify the antecedents of continued usage intentions in the connected devices ecosystem in health care by analyzing the users' and physicians' expectations in a new ecosystem where one prefers to connect digitally rather than physically.

This is a unique study in which data was collected from 242 doctors and 215 end-users to gauge the expectations from the connected devices in health care. Further, these responses were hypothesised using UTAUT-2 and ECT theories to analyze general users’ and professional users’ or doctors’ expectations for continued usage in connected devices ecosystem in the health-care ecosystem.

Performance expectancy, social influence, facilitating conditions and price value emerged as significant predictors of satisfaction in both user groups. But habit and hedonic motivation reflected an insignificant impact on user satisfaction. Surprisingly, effort expectancy emerged as a significant factor for end-user satisfaction, and this became insignificant for professional user satisfaction. Satisfaction was positively related to continued usage for both user groups, and app quality has a positive impact on all the predictors.

To the best of the authors’ knowledge, this is the first comparative study to understand the factors which influence consumer behavior leading to a holistic model and can be imbibed for creating a better customer experience in an era where we are more comfortable connecting digitally rather than physically.

This study has used the Unified Theory of Acceptance and Use of Technology-2 model and expectation confirmation theory to analyze the key factors influencing the intentions for continued usage of devices in the Internet of Medical Devices setup.

Technology has revolutionized banking, and “green banking” has been the most recent phenomenon to have caught the financial world's attention. In this paper, the authors look at how personality traits of individuals influence their adoption and continued use of green banking channels. The authors also propose a comprehensive model integrating the “big five” personality traits (conscientiousness, agreeableness, extraversion, openness and neuroticism) into the Technology Acceptance Model (TAM), along with expectation confirmation theory. The integrated proposed model is used in this longitudinal study to predict the continued use of green banking channels once adopted.

The authors collected data during two time periods about 24 weeks apart from 826 green banking channel users from different regions in India. The data were analyzed using Structural Equation Modeling.

The authors found that traits of agreeableness, conscientiousness and extraversion favor an individual adopting green banking channels, while conscientiousness and openness were only associated with its perceived usefulness (PU).

The results offer valuable insights for understanding the adoption and use behavior of people regarding green banking channels. This study would help develop effective segmentation strategies for promoting green banking channels.

By incorporating the big five, along with TAM and Expectation Confirmation Model (ECM), coupled with “trust” as an additional construct, we believe that our study enlarges the boundaries of Information Technology (IT) theories, especially in the context of green banking channels. This study also contributes to advancing the personality theory by exploring how personality traits significantly relate to adopting and using green banking channels.