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The purpose of this paper is to help understand consumer acceptance of online health information services by integrating the health belief model and extended valence framework.

A laboratory-based, experimental-scenarios research design is used to collect data, and the structural equation modeling technique is used to test the research model.

The model explains 47.6 percent of the variance in intentions to use online health information services. Trust appeared to have the strongest effect on acceptance. Perceived risk also had a significant impact on acceptance. Furthermore, health belief variables are confirmed as important factors for consumer acceptance. Self-efficacy was found to moderate the effect of perceived severity on acceptance.

This study helped identify the relative salience of the health belief model and extended valence framework in consumer acceptance of online health information services.

This study can help practitioners better understand the development of trust and the profiles of consumers who may browse their sites. When online health service providers promote their information to encourage potential online health information seekers, they should use countermeasures against risk perceptions.

This study attempted to extend the valence framework to the non-commercial service context. Moreover, health beliefs and the valence framework are two fundamental aspects that health information seekers consider when making decisions about online health services.

The purpose of this paper is to examine the effects of inhibiting, motivating, and technological factors on users’ intention to participate in the sharing economy.

A self-reported online survey was conducted among Uber users in Hong Kong. A total of 295 valid responses were collected. The research model was empirically tested using the structural equation modeling technique.

The results suggested that perceived risks, perceived benefits, trust in the platform, and perceived platform qualities were significant predictors of users’ intention to participate in Uber.

This study bridged the research gaps in the sharing economy literature by examining the effects of perceived risks, perceived benefits, and trust in the platform on users’ intention to participate in the sharing economy. Moreover, this study enriched the extended valence framework by incorporating perceived platform qualities into the research model, responding to the calls for the inclusion of technological variables in information systems research.

The findings provided practitioners with insights into enhancing users’ intention to participate in the sharing economy.

This study presented one of the first attempts to systematically examine the effects of inhibiting, motivating, and technological factors on users’ intention to participate in the sharing economy.

Artificial intelligence (AI) fosters economic growth and opens up new directions for innovation. However, the diffusion of AI proceeds very slowly and falls behind, especially in comparison to other technologies. An important path leading to better adoption rates identified is trust-building. Particular requirements for trust and their relevance for AI adoption are currently insufficiently addressed.

To close this gap, the authors follow a qualitative approach, drawing on the extended valence framework by assessing semi-structured interviews with experts from various companies.

The authors contribute to research by finding several subcategories for the three main trust dimensions ability, integrity and benevolence, thereby revealing fundamental differences for building trust in AI compared to more traditional technologies. In particular, the authors find access to knowledge, transparency, explainability, certification, as well as self-imposed standards and guidelines to be important factors that increase overall trust in AI.

The results show how the valence framework needs to be elaborated to become applicable to the AI context and provide further structural orientation to better understand AI adoption intentions. This may help decision-makers to identify further requirements or strategies to increase overall trust in their AI products, creating competitive and operational advantage.

This study aims to examine factors affecting restaurant customers’ intention to use near field communication (NFC)-based mobile payment (MP) technology. More specifically, based on the valence theory, this paper examined the impacts of users’ negative valence (perceived risk and privacy concern) and positive valence (utilitarian value and convenience) perceptions toward their NFC-MP technology acceptance. Furthermore, the impacts of individual difference variables (smartphone affinity and compatibility) on users’ negative and positive valences and on their behavioral intentions were analyzed.

A self-administered online questionnaire was used to collect the data of the study from 412 restaurant customers. A confirmatory factor analysis (CFA) was used to validate the measurement model. To test the hypothesized model, structural equation modeling (SEM) was used.

The study findings demonstrated that privacy concern, utilitarian value and convenience significantly affected individuals’ NFC-MP technology acceptance. In addition, compatibility significantly influenced negative and positive valance constructs and smartphone affinity had a positive impact on positive valance constructs only.

This study provides valuable practical implications for restaurant operators and hospitality technology vendors in the context of mobile payment systems.

This study successfully extended the valence framework by adding individual difference constructs to it.

The purpose of this paper is to develop and test a model of the uncertainties and benefits influencing the repurchase intentions of buyers in cross-border e-commerce (CBEC).

The authors draw on the valence framework to hypothesize effects of positive valences (utilitarian benefits) along with negative valences (pre- and post-contractual uncertainties) on buyers’ repeat purchase intentions. Data were collected using an online survey from 378 international B2C buyers on a CBEC platform in China.

Results explain 51.4 percent of the variance and reveal that overall value, as determined by monetary saving, convenience and product offerings as positive valences, exerts the strongest effect on repeat purchase intention. However, negative valences remain significant, and are particularly salient for female shoppers.

The authors extend the valence theory into the study of repeat purchase behavior and contribute to much needed literature on why consumers return to repurchase from a CBEC platform.

Repeat purchase and loyalty of online consumers is essential for success of e-commerce providers. The results help online providers competing in international markets understand how buyers form repurchase intentions based on their evaluations of both value and uncertainty.

Buyer behavior in CBEC has received relatively less attention than domestic e-commerce. This paper is among the first to examine how both positive and negative valences combine to effect repurchase intention of international buyers in CBEC.

Facial recognition payment (FRP) has been attracting attention as an alternative payment mode. This research aims to investigate the future use of FRP for both mobile payment and point of sale payment.

The body of information on this topic is promoted by proposing the valence framework, where the authors used relative advantage, initial trust, perceived playfulness and need for uniqueness as positive valence, and perceived risk, technophobia and perceived complexity as negative valence. This study also investigated the moderating effect of personal innovativeness on consumers' behavioral intention to use FRP-based payments. The authors collected data from 392 FRP users from China to test the model. The authors used structural equation modeling (SEM) to evaluate the significant determinants influencing FRP use.

The authors found that relative advantage and privacy risk are the two most influential predictors of FRP use. The findings indicate that personal innovativeness acts as a moderator between negative valence and behavioral intention. This study provides valuable policy guidelines for the mobile or point of sale (POS) payment companies for adding FRP service into their default payment method.

FRP is a relatively new technology that has not received much research attention in information system (IS) literature. Most studies on payment investigated enablers, and less effort has been given to study both enablers and inhibitors together. Furthermore, the authors employed SEM-based analysis to identify the most important factors influencing consumers' future use decisions.

This paper hypothesized that perceived relative advantage and perceived compatibility would have a positive effect on merchants' intention to accept payments via P2P mobile payment services, while perceived financial risks and perceived costs would have a negative effect. The study also explored the differences in gender, age and experience.

The proposed model is based on the valence framework, where positive utility is represented by relative advantage and perceived compatibility, while negative utility is represented by perceived risks and perceived costs. The data for this study were collected from small business owners (merchants) at the largest public market in the Center Department of Mirebalais, Haiti, using a purposive sampling method.

The results of a structural equation modeling on a sample of 339 merchants only confirmed the effect of both perceived comparative advantage and perceived compatibility. Furthermore, the multigroup analysis revealed that the perceived comparative advantage is stronger for female merchants, older age groups and merchants who frequently used P2P m-payment for the transfer of remittances. Perceived compatibility is stronger for male merchants, younger age groups and merchants who occasionally used P2P m-payment for the transfer of remittances.

This study was conducted in the economic context of Haiti, where P2P m-payments are commonly used for transferring remittances. Since there are limited studies that examine P2P m-payment acceptance from the perspective of merchants, this study offers valuable insights.

Facial recognition payment is an emerging mobile payment method that uses human biometrics for personal identification. The purpose of this study is to examine how users' salient beliefs regarding the technology–organization–environment–individual (TOE–I) dimensions affect their attitudes and how attitudes subsequently influence the intention to use facial recognition payment in offline contactless services.

This study comprehensively investigates customers' decision-making psychological mechanism of using facial recognition payment by integrating the belief–attitude–intention (B–A–I) model and the extended TOE–I framework. Data from 420 valid samples were collected through an online survey and analyzed using partial least squares structural equation modeling.

Research results indicate that convenience and perceived herd exert positive effects on trust and satisfaction. Meanwhile, familiarity has a significantly positive effect only on trust but not on satisfaction. In contrast, perceived privacy risk exhibits a negative effect on both trust and satisfaction. Trust and satisfaction positively influence the intention to use facial recognition payment. Unexpectedly, self-awareness negatively moderates the effect of satisfaction on intention to use, but its effect on the relationship between trust and intention to use is non-significant.

To the best of the authors’ knowledge, this study is one of the early studies that explicate customers' psychological mechanism in facial recognition payment in offline contactless services through an understanding of the B–A–I causal linkages with the identification of users' perceptions from a comprehensive context-specific perspective. This study enriches the literature on facial recognition payment and explores the moderating role of self-awareness in the relationship between users' attitudes and intention to use, thereby revealing a complex psychological process in the usage of offline facial recognition payment systems.

In recent years, short-term sharing accommodation platforms such as Airbnb have made rapid forays in populous cities worldwide, impacting neighborhoods profoundly. Emerging work has focused on demand-side motivations to engage in the sharing economy. The purpose of this paper is to analyze rarely examined supply-side motivations of providers.

To address this gap and to illuminate understanding of how Airbnb supply is configured and influenced, this study examines spatial patterns and socioeconomic influences on participation in the sharing accommodation economy by Airbnb hosts in New York City (NYC). An exploratory conceptual model of host participation is induced, which posits associations of demographic, economic, employment, social capital attributes, and attitudes toward trust and sustainability with host participation, measured by Airbnb property density in neighborhoods. Methods employed include ordinary least squares (OLS) regression, k-means cluster analysis and spatial analytics.

Spatially, clusters of high host densities are in Manhattan and northern Brooklyn and there is little proportionate change longitudinally. OLS regression findings reveal that gender ratio, black race/ethnicity, median household income, and professional, scientific, and technical occupation, and attitudes toward sustainability for property types are dominant correlates of property density, while host trust in customers is not supported.

These results along with differences between Queens and Manhattan boroughs have implications for hosts sharing their homes and for city managers to formulate policies and regulate short-term rental markets in impacted neighborhoods.

The study is novel in conceptualizing and analyzing the supply-side provider motivations of the sharing accommodation economy. Geostatistical analysis of property densities to gauge host participation is novel. Value stems from new insights on NYC’s short-term homesharing market.

Financial technology (FinTech) is undergoing a transformation as a result of robotics and artificial intelligence. FinTech service providers are embracing contactless technology, including the development and widespread adoption of innovative payment service. Among the many types of contactless payment services, facial recognition payment (FRP) has gained in popularity. To capitalize on this rising popularity, comprehending the mechanisms underlying continuous usage intention toward FRP is essential. Drawing from the stimulus–organism–response (S-O-R) model, this study investigates how FRP attributes facilitate continuous usage intention.

In total, 321 Chinese FRP users completed an online survey. Partial least squares structural equation modeling analyzed the results of the survey.

The results reveal that relative advantage and compatibility, user-interface attractiveness and perceived security (stimuli) promote performance expectancy, effort expectancy and positive emotion (organism), which in turn foster FRP continuous usage intention (response).

This research presents an S-O-R model that incorporates several attributes from DOI theory, the UTAUT model and the AIDUA framework to elucidate the antecedents of consumers' continuous usage intention toward FRP. The findings corroborate the significance of the S-O-R mechanism in FRP, setting the groundwork for the acceptance and development of biometric authentication technologies in service contacts and banks. In addition, the study highlights opportunities and essential aspects for FinTech service developers and providers to consider in terms of their practical significance.