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This paper aims to investigate the key enablers and inhibitors that influence the intention to use fitness wearables using the value-based adoption model (VAM).

Data were collected using a structured online questionnaire from 323 respondents who had never used fitness wearables. A purposive sampling technique was used in this study. Smart PLS was employed to test the research framework and hypotheses using a two-step approach.

The findings support some of the hypotheses developed with R² values of 0.622 for perceived value (PV) and 0.567 for intention to use fitness wearable. Perceived enjoyment, perceived social image and perceived usefulness had a positive effect on PV. In addition, health information sensitivity (HIS) was positively related to perceived privacy risk and health information accuracy was positively related to perceived usefulness. Surprisingly, this study did not find any significant relationship between perceived fee, perceived privacy risk, perceived health increase and perceived design aesthetics with PV.

This study's findings can help designers and manufacturers design fitness wearables by considering factors that users find valuable, thus satisfying consumers' needs.

This study tries to model behavioural intention of fitness wearable usage of individual users by using the VAM with the addition of two new antecedences, HSI and health information accuracy, to better explain the behaviour.

Because the success of m-payment services depends on the enablers and barriers that affect user satisfaction, the present research explores the effects of perceived value and sacrifices on users' satisfaction with m-payment services. The predicted relationships among perceived value, perceived sacrifices, users' satisfaction, continuance intention, word-of-mouth (WOM), shopping effectiveness, quality of life (QOL) and stickiness were established based on the mobile technology acceptance model (MTAM) and the value-based adoption model (VAM).

A representative data sample of 430 Egyptian banking clients was analyzed to test the hypotheses using partial least squares-structural equation modeling (PLS-SEM).

The findings revealed that all perceived value constructs significantly positively affect users' satisfaction. Moreover, all perceived sacrifice constructs significantly negatively affect users' satisfaction. Users' satisfaction, in turn, has a significant positive effect on continuance intention, WOM, shopping effectiveness, QOL and stickiness with m-payment services.

This is the first study to examine several levels of m-payment outcomes, including m-payment, consumer and bank outcomes, based on the integration of MTAM and VAM models.

The purpose of our study was two-fold: (1) to examine the effect of perceived value derived from perceived benefits and sacrifices in the adoption of artificial intelligence (AI) in talent acquisition and (2) to investigate the moderating role of human resource (HR) readiness in the association between perceived value and AI adoption intention.

A structured questionnaire was administered to 198 talent acquisition executives and HR professionals of Indian IT companies based on a purposive sampling technique. Partial least squares structural equation modeling (PLS-SEM) was used on the Smart PLS 2.0 platform to analyse the data and test the model.

Results revealed that perceived benefits and sacrifices significantly predict perceived value which significantly affects the HR professional’s AI adoption intention. The study further found that HR readiness moderates the link between perceived value and the intention of HR professionals to adopt AI in the talent acquisition process in the Indian IT industry.

IT companies are advised to continuously monitor and evaluate the performance of AI tools to ensure that they are meeting the recruitment process needs to leverage AI’s benefits in talent acquisition. This study seeks to provide the impetus for a planned AI adoption in talent acquisition.

This research provides ample evidence for the existing technology adoption theories. It explored the predictors of adoption by validating the value-based adoption model in the Indian context. It provides valuable insights into the practice of acquiring talents in the IT sector using artificial intelligence.

Grounded on the value-based adoption model and innovation diffusion theory, this study examined consumer purchase decisions of mobile Global Positioning System (GPS) navigation apps. In addition, this study also investigated the moderating role that perceived availability of free substitutes (PAFS) plays in the relationship between perceived value and purchase intention. The paper aims to discuss these issues.

Data collected from 219 mobile users were analyzed against the research model using the partial least squares approach.

The results showed that compatibility, relative advantage, perceived enjoyment, perceived cost (positively), and complexity (negatively) influenced these users’ value perceptions and purchase decisions. Furthermore, PAFS significantly weakened the positive relationship between perceived value and purchase intentions.

Based on these findings, the authors provide practical suggestions for mobile app developers to increase mobile app sales. This study also helps advance knowledge of mobile internet marketing.

This study is a pioneering effort in explaining consumer purchase intentions in the context of mobile GPS navigation app.

The blockchain technology is based on distributed ledger. Many stakeholders, such as developers, entrepreneurs and technology lovers, consider the blockchain as an economic and business re-creation that is faced with numerous challenges in its application. Blockchain technology is the backbone of many digital currencies, i.e. Bitcoin and Ethereum. Although presently digital currencies are recognized as payment and exchange instruments in many countries, the economic sanctions imposed on some countries have restricted the possibility of the trading. So, this study seeks to evaluate the adoption of blockchain for digital currency use in Iran in the shadow of economic sanctions.

The developed value-based technology adoption model and smart PLS software have been used in this research. The statistical population of the study was people active in the Iranian stock market; the purpose for this selection was their familiarity with financial and digital currency issues.

The results show that the terms of sanctions, usage and facilitating conditions are directly related to users' perceived value of digital currency and its use; As a result, in a sanctioned country like Iran, the use of digital currencies is being accepted as a way of rolling out economic sanctions and thus making commercial payments.

As well as the fact that evaluating the adoption of the blockchain technology in a sanctioned country like Iran is considered as the originality aspect of the research, applying an extended model in the technology adoption is also the research innovation.

Consumers' perceptions of product intelligence affect their willingness to accept smart offerings. This paper explores how people perceive various smart products based on their smartness profiles, composed of five distinct smartness facets. Additionally, the study investigates how these perceptions of product intelligence impact consumers' evaluation of factors that either promote or impede the adoption of smart products. These factors are examined as potential mediators in the adoption process. This paper aims to determine if the value-based adoption model can be applied to a broad range of smart service systems.

Consumers assessed one of 28 smart products in a scenario-based quantitative study. Multilevel structural equation modeling (SEM) is used to test the conceptual model, taking the nested data structure into account.

The findings show that product smartness essentially enhances usage intention via adoption drivers (enjoyment and usefulness) and reduces usage intention via adoption barriers (intrusiveness). In particular, the ability to interact in a humanlike manner increases the benefits consumers perceive, which in turn increases consumer acceptance. Only the smartness characteristic of awareness impairs usage intention, mediated by the perceived benefits of enjoyment and usefulness.

In contrast to previous research, which usually focuses on single smart products, this work examines a variety of different products, which allows for better transferability of the results to other smart offerings. Furthermore, prior research has mainly focused on single facets of product smartness or researched smartness on an aggregated level. By considering the consumer perception of each smartness facet, the authors gain deeper insights into the perceptual differences regarding product smartness and how this affects technology adoption via conflicting key acceptance drivers and barriers.

This paper aims to investigate what motivates consumers to adopt one of the emerging mobile applications of the sharing economy, ridesharing application. Using social cognitive theory as the theoretical framework, this study develops a value adoption model to illustrate important factors that influence adoption of ridesharing applications.

Based on prior literature, a quantitative methodology was adopted using a survey questionnaire that allows for the measurement of the nine constructs contained in the hypothesized theoretical model. Data collected from a sample of 314 respondents in Beijing, China provided the foundation for the examination of the proposed relationships in the model.

First, the results indicate that self-efficacy is a fundamental factor that has a direct effect on consumers’ perceptions of value and an indirect effect on behavioral intentions. Second, the study demonstrates that functional value, emotional value and social value are critical antecedents of overall perceived value of ridesharing applications. On the other hand, learning effort and risk perception are not significant perceived costs for consumers in adopting ridesharing applications.

Although typical adopters of internet applications constitute a significant portion of younger consumers, the use of a college student sample in this study may affect the generalizability of the results.

The findings provide critical insight into consumer motivations behind adoption of ridesharing applications specifically, and for sharing economy platforms in general.

This study provides important theoretical implications for innovation adoption research through an empirical examination of the relationship between personal, environmental and behavioral factors in a framework of social cognitive theory.

Pro-poor innovations are innovations targeted at economically poor consumers. These innovations have the potential to improve consumer wellbeing. However, while take up of some such innovations has been rapid (e.g., mobile phones) take up of others has been slower (e.g., fuel efficient stoves). What explains why some pro-poor innovations fail and some succeed? While the literature on consumer innovation adoption in economically wealthy countries is vast, there is very little literature in the context of the “bottom-of-the-pyramid” (BoP) and subsistence marketplaces. This chapter aims to begin answering this question through a review of the extant literature in the area of consumer innovation adoption, which is integrated with literature in the area of consumption within subsistence marketplaces and the BoP. A conceptual model is proposed which outlines key parameters for marketers and managers. The chapter closes by outlining implications and a future research agenda.

Robots, as the crystallization of new artificial intelligence, are being applied in various fields, especially the hotel industry. They are seizing the opportunities, using technology to improve the overall quality and comprehensive competitiveness. However, they also cause many problems due to practical limitations. The purpose of this paper is to study customers' recognition and acceptance of hotel service robots to guide the successful promotion of this technology.

This paper proposed a comprehensive model based on the theory of planned behavior, the technology acceptance model and then the perceived value-based acceptance model. Exploratory factor analysis, confirmatory factor analysis, grouped regression analysis and path analysis was adopted to validate the impacts of each variable to obtain the final reliable model using data collected from hotel guests using a self-designed questionnaire.

The empirical research based on the theoretical model shows that the constructed conceptual model can thoroughly explain the influencing factors of hotel robot acceptance, enrich the acceptance theory and provide academic support for the use and popularization of hotel service robots. Among all variables, attitude, usefulness and perceived value are the factors that have the greatest impact on acceptance. They have significant differences in the effects of adjustment variables such as gender, educational level, whether hotel robots have been used, and whether other robot services have been experienced on different paths in the model.

This paper explored the customer acceptance of service robots in hotels, helped to understand the process of decision-making on service robot selection and contributed to the theoretical extension of the hospitality industry. The work guides hotel management to promote better-personalized products and services of robot technology in the hospitality industries.

The acceptance study on hotel service robots provides insight into the hotel industry to understand customers' attitudes and acceptance of emerging technology.

With the advent of the digital era, the internet has gradually become an essential factor in people’s lives. Its increasing popularity has also caused e-commerce to thrive, and has increased the power of online marketing. In recent years, social commerce has emerged as a new mode of operation which can be distinguished from traditional e-commerce. The paper aims to discuss these issues.

The main purpose of this study is to determine which factors influence a consumer’s behavioral intention in the context of social commerce websites, and to explore overall purchase intentions based on the consumer’s cognitive evaluation. The examination reveals that consumers’ multidimensional perceptions influence both their perceptions of value and their purchase intentions. Other related social awareness factors explored by this study are also shown to influence customers’ purchase intentions.

In summary, the results show that perceived value and social awareness factors influence customers’ purchasing decisions and behavioral intentions for different gender. These findings have significant theoretical and managerial implications.

Social commerce is a subset of e-commerce brought about by the development of social networking. Activities conducted on social networking websites can be considered as a form of social commerce. In Taiwan, social commerce is still in the early stages of development.