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Wearable medical devices (WMDs) are improving people’s health and well-being in a noble way, as these aid in effective personal health monitoring, remote surveillance and overall illness management. Despite its wider applicability and usage, it is prevalent that users discontinue its usage, which presents an obstacle in the proliferation of such vital innovations among the masses. Therefore, relying on the expectation-confirmation model (ECM), this study aims to delve deeper to explain the factors that motivate users to continually use WMDs by incorporating novel variables, namely, health belief, health information accuracy and privacy protection.

The study proposes and tests an extended ECM perspective to predict the continuance intention (CI) of WMDs among users. By using structural equation modelling using SmartPLS, the authors tested the model on Indian people (n = 451) who had an erstwhile experience of using WMDs.

The study results show that confirmation of users’ expectations positively impacts their usefulness and satisfaction towards WMDs. Moreover, satisfaction towards WMDs is the strongest predictor of users’ CI, followed by perceived usefulness. Interestingly, personal factor such as health beliefs reveals a greater influence on perceived usefulness than technological factors like health information accuracy and privacy protection.

The study findings demonstrate the significance of using the expectation-confirmation perspective in technology-based studies in general and WMDs, in particular. This study aids by offering an integrated model of WMD’s continued usage intention for the users, in addition to practical implications for marketers and policymakers.

A paucity of research exists when understanding the predictors of CI for WMDs. This study fills this gap and adds to behavioural literature by offering a noble viewpoint involving an extended ECM perspective.

Despite the proliferation of service chatbots in the tourism industry, the question on its continuance intentions among customers has largely remain unanswered. Building on an integrated framework using the task–technology fit theory (TTF) and the expectation–confirmation model (ECM), the present study aims to settle this debate by investigating the factors triggering customers to continue to use chatbots in a travel planning context.

The research followed a quantitative approach in which a survey of 322 chatbot users was undertaken. The model was empirically validated using the structural equation modelling approach using AMOS.

The results reveal that users’ expectations are confirmed when they believe that the technological characteristics of chatbots satisfy their task-related characteristics. Simply, the results reveal a significant and direct effect of TTF on customers’ confirmation and perceived usefulness towards chatbots. Moreover, perceived usefulness and confirmation were found to positively impact customers’ satisfaction towards chatbots, in which the former exerts a relatively stronger impact. Not surprisingly, customers’ satisfaction with the artificial intelligence(AI)-based chatbots emerged as a predominant predictor of their continuance use.

The findings have various practical ramifications for developers who must train chatbot algorithms on massive data to increase their accuracy and to answer more exhaustive inquiries, thereby generating a task–technology fit. It is recommended that service providers give consumers hassle-free service and precise answers to their inquiries to guarantee their satisfaction.

The present work attempted to empirically construct and evaluate the combination of the TTF model and the ECM, which is unique in the AI-based chatbots available in a tourism context. This research presents an alternate method for understanding the continuance intentions concerning AI-based service chatbots.

The purpose of this paper is to examine the existence and profile consumer segments based on dissonance in Indian apparel fashion retail market.

This study is based on cognitive dissonance theory (CDT) and analyses data using cluster and discriminant analysis on a sample (n = 354) from India.

The findings revealed three dissonance segments among consumers based on the intensity of dissonance experienced. This study also validated the clusters and profiled each segment. In doing so, the three clusters exhibited unique differences with respect to purchase and socio-demographic characteristics. Moreover, high dissonance segments were found to inversely impact customer’s satisfaction, loyalty and overall perceived value and positively impact tendency to switch.

Understanding the existence of cognitive dissonance (CD) patterns among consumers is critical for fashion apparel retailers. This paper offers unique insights into the specialties of each dissonance segment that assists the marketers to frame appropriate strategies to target them.

This paper advances knowledge on consumer behavior by highlighting the significance of CD.

This paper aims to explore the determinants of intention towards the use of agro-advisory mobile applications by extending the technology acceptance model (TAM) with addition of the following constructs: result demonstrability (RD), trust, self-efficacy (SE) and mobile usage proficiency (MUP).

The study employed a survey on farmers (n = 446), which was analysed through structural equation modelling using Analysis of Moment Structures (AMOS).

The results show that RD and farmer's trust on agro-advisory mobile apps (AAMA) positively impact their perceptions of usefulness. Also, farmer's SE and MUP positively affect their perceptions of ease of using AAMA. Further, interestingly, farmer's attitude towards the AAMA fully mediates the relationship between perceived usefulness and perceived ease of use on intention to use them.

Understanding the antecedents of agro-advisory mobile application offers a unique contribution to policymakers, private firms, and non-government organizations by proving key insights on the acceptance of agriculture based mobile technologies in context of developing nations.

To the best of author's knowledge, this is one of the first research enquiries on the adoption of agro-advisory mobile applications. The new theoretical framework adds to the original TAM and offers novel insights that are helpful in augmenting the current understanding on AAMA and their acceptance by the beneficiaries.