Purpose The purpose of this paper is to examine the determinants of user adoption of smartphone fitness apps in context of an emerging economy. Design/methodology/approach The present study uses the extended unified theory of acceptance and use of technology (UTAUT2) as the base model along with two additional constructs, i.e. self-efficacy and personal innovativeness. The data collection was done through an online survey, wherein a total of 324 valid responses were obtained for the statistical analysis. All the hypothesized relationships were tested through partial least square structural equation modelling (PLS-SEM) using an open source programming language and software environment, i.e. R Software along with plspm-package. Findings Significant predictors of smartphone fitness app adoption intention include effort expectancy, social influence, perceived value, habit and personal innovativeness. Further, this study confirms significant relationship between personal innovativeness and habit, self-efficacy and effort expectancy and effort expectancy and performance expectation. This study reveals that personal innovativeness is the strongest predictor of behavioural intention. Contrary to the expectations, factors like performance expectancy, facilitating conditions and hedonic motivation did not influence behavioural intention. Practical implications This study gives significant clues to app developers that can drastically influence the adoption of fitness apps. The findings suggest that marketers should focus on users with high personal innovativeness that can further act as role models and significantly influence their social circle. Interestingly, the findings suggest that fitness apps, as compared to other apps, should not emphasize much on the hedonic value of their offerings. Originality/value This study is one of the few studies to examine the adoption of smartphone fitness apps in an emerging economy context by using extended version of UTAUT2 model. Further, this study shows how new endogenous and exogenous variables (i.e. self-efficacy and personal innovativeness) contribute to better explanatory power of the UTAUT2 framework.

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The recent rise of consumer happiness research in marketing literature is noticeable. This article presents a systematic review of consumer happiness research from 1991 to 2020. From an initial pool of 600 articles on consumer happiness from 158 marketing journals in the ABS and ABDC lists, 71 articles were selected. The procedure was as follows: (1) search of articles, (2) quality assessment, (3) extraction of data from articles, and (4) thematic synthesis. The review concluded that the term “consumer happiness” does not have a standardized definition in the existing literature. However, happiness has been studied in a variety of contexts, and consumer research is one of these contexts. Further, the review concluded that consumer happiness research is largely segregated across three themes: marketing beyond satisfaction, marketing for health and mind, and digital felicity. Seven areas of future research on consumer happiness are also proposed. The authors present academic and managerial contributions with scholarly implications for the literature in the areas of consumer well-being, the role of marketing/interactive marketing, and the positive side of marketing. The authors also suggest that marketers not only seek consumers’ need fulfillment and satisfaction from their product or service consumption but also try to elicit hedonic associations with their products or services.

Purpose The present study aims to probe into the determinants of mobile wallet adoption by millennials with the assistance of extended technology acceptance model. Design/methodology/approach The data was collected from the students studying professional courses in leading private universities in the north region of India. Keeping in view of the objective and hypotheses, the Partial Least Square Structural Equation Modeling (PLS -SEM) technique was used to test the proposed model. Findings The tested model brings into notice the imperative observation, which clearly outlines that there are all significant relationships, which can be observed herein. To explicitly state: perceived ease of use (PEOU) has a significant positive relationship with the perceived usefulness followed by PEOU also shares a significant positive relationship with the behavioral intention, and lastly trust as a variable under study establishes a significant positive relationship with actual use (AU). Research limitations/implications Implications for the banking industry are to ensure the safety and privacy (financial information) confidential. Originality/value The present study contributes to the literature of mobile wallet in the developing nations.

Purpose 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. Design/methodology/approach 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. Findings 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. Practical implications 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. Originality/value 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.