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Medical mistrust, clinical trial knowledge, and clinical trial risk impact research participation, yet are rarely studied among racial and ethnic groups. Data were from a cross-sectional survey ( n  = 1,794). Multinomial logistic regression models examined associations of medical mistrust, clinical trial knowledge, and clinical trial risk with willingness to participate in health research (Yes, No, Unsure) among Chinese, Korean, South Asian, Haitian, North American Latiné, South American Latiné, and Southwest Asian and North African (SWANA) NYC residents with one model per group. Overall, 46.0% of participants reported willingness to participate, ranging from 35.8% (Chinese participants) to 58.7% (South Asian participants). Increased mistrust was associated with less willingness among Chinese (OR: 1.06, 95%CI: 1.00, 1.12) and South American Latiné (OR: 1.15, 95%CI: 1.02, 1.30) participants; more willingness among Haitian participants (OR: 0.87, 95%CI: 0.81, 0.94); more uncertainty among Korean (OR: 1.13, 95%CI: 1.05, 1.22), South Asian (OR: 1.06 95%CI: 1.01, 1.12), and North American Latiné (OR: 1.18, 95%CI: 1.10, 1.28) participants; and less uncertainty among Haitian (OR: 0.91, 95%CI: 0.84, 0.99) and SWANA (OR: 0.91, 95%CI:0.86, 0.97) participants. Knowledge was associated with more willingness for Haitian participants (OR: 2.77, 95%CI: 1.15, 6.65), less willingness for Chinese participants (OR: 0.55, 95%CI: 0.34, 0.88), and more uncertainty among South Asian (OR: 2.09, 95%CI: 1.07, 4.07) and SWANA (OR: 2.71, 95%CI: 1.21, 6.03) participants. Some risk and more willingness were linked for South American Latiné participants (OR: 0.13, 95%CI: 0.02, 0.82). Associations varied by group. Studying multiple racial and ethnic groups advances equitable research representation.

Purpose The purpose of this paper is to examine the effects of perceived benefits, i.e. utilitarian value, hedonic value and social value, as well as perceived risk, on purchase intention in social commerce context. Design/methodology/approach To cast light on the factors motivating users’ intention to purchase in the context of social commerce, data of 277 users of social commerce in China were collected via an online survey. Findings Results show that satisfaction significantly and positively affects users’ purchase intention in social commerce context. In addition, utilitarian, hedonic and social values have significant and positive impacts on satisfaction and purchase intention; and utilitarian value is found to be the most salient factor influencing purchase intention, while hedonic value has the greatest effect on satisfaction. Moreover, perceived risk significantly and negatively affects satisfaction. Originality/value Extant research on social commerce has mainly focused on investigating how the general perceived value affects user behavior, but has less considered different dimensions of perceived value. Moreover, prior studies have explored the roles of utilitarian and hedonic values on user behavior; however, there is a lack of research on the effect of social value. The current study attempts to fill these research gaps.

Purpose The purpose of this paper is to examine the factors that influence the adoption of mobile technology by considering the information technology (IT) managers’ perception. The research identified the key challenges managers faced and whether management would adopt mobile technology or not. Design/methodology/approach A quantitative approach was used for this research, whereby an explanatory research was utilised. Questionnaires were developed and distributed to respondents who were in management and leadership positions and who were responsible for IT within their organisations. Demographic variables of age, gender differences, level of education, level of experience and culture were tested for association to the perceived factors and adoption. A χ2 of association was used to test the association between demographic variables and mobile technology adoption. Findings The results found that perceived ease of use, perceived usefulness, perceived complexity and perceived cost are important factors for adoption. However, perceived risk was a key factor in the adoption of mobile technology. Mobile strategy adoption must consider perceived risk factors central to the adoption. The younger generation (20 to 40) years found it easier to adopt technology than the older generation of 41 years and older. Individuals with a post matriculation level of education understood the importance of risk and cost required for adoption. Research limitations/implications Purposive sampling from a single industry (Life Insurance) was used. Limited literature was available regarding managers perception of mobile technology adoption in the Life Insurance industry. Practical implications The research offers managers insight into the important factors that need to be considered in adopting mobile technology. Originality/value With mobile technology being pervasive, the research seeks to provide managers with the insight in managing the adoption of the technology.

The use of artificial intelligence (AI) in the healthcare field is gaining popularity. However, it also raises some concerns related to privacy and ethical aspects that require the development of a responsible AI framework. The principle of responsible AI states that artificial intelligence-based systems should be considered a part of composite societal and technological systems. This study attempts to establish whether AI risks in digital healthcare are positively associated with responsible AI. The moderating effect of perceived trust and perceived privacy risks is also examined. The theoretical model was based on perceived risk theory. Perceived risk theory is important in the context of this study, as risks related to uneasiness and uncertainty can be expected in the development of responsible AI due to the volatile nature of intelligent applications. Our research provides some interesting findings which are presented in the discussion section.

Scarcity cues are increasingly being employed as marketing tactics. However, it remains unclear whether and how supply-led and demand-led scarcity cues differentially affect purchase decisions for art-infused products. Building on the literatures of scarcity and the art infusion effect, the present research shows that supply-led scarcity cues enhance consumers’ likelihood of purchasing art-infused products, while demand-led scarcity cues work better for their non-art counterparts. Perceived prestige and perceived risk, respectively, underlie these effects. Further, regulatory focus and social visibility moderate the effects. The empirical investigation comprises eight studies—in field, lab, and online settings. The findings of this research extend theoretical insights in the literature on scarcity and the art infusion effect and provide relevant managerial implications.

Electric vehicles (EVs) are known to be effective in reducing dependence on fossil fuels, in turn reducing the emission of greenhouse gas and other pollutants. To promote EVs, considerable efforts and measures have been taken. However, the public’s awareness and acceptance of EVs are still low, which has affected the diffusion of EVs in the market. Based on the stimulus-organism-response (SOR) framework, this research aims to explore how consumers’ EV driving experience (S) affects their emotions and cognitions regarding EVs (O: perceived relative advantage, perceived ease of use, and perceived risk of EVs) and then activates their intentions to adopt EVs (R). Based on survey data from 692 respondents, the results suggested that consumers’ EV driving experience has a significantly positive effect on perceived relative advantage and perceived ease of use, and then perceived relative advantage and perceived ease of use positively affect consumers’ intentions to adopt EVs. The EV driving experience negatively affects perceived risk, and perceived risk is also negatively associated with EV adoption intentions. Furthermore, consumers’ EV driving experience also has a significant direct effect on EV adoption intentions. Based on the research results, relevant recommendations and suggestions have been proposed to promote EVs from the government and enterprise perspectives.

Purpose The purpose of this study is to develop a conceptual framework which takes into account the perceived risk (PR) and the perceived benefits (PB) of using mobile payment systems (MPS) in the context of COVID-19 pandemic. Design/methodology/approach The study proposes a conceptual framework incorporating the uncertainties/risks associated with MPS like perceived technology uncertainty (PTU), perceived regulatory uncertainty (PRU), perceived service intangibility (PSI) and perceived information asymmetry (PIA), along with the benefits of using MPS such as trust, mobility, health consciousness (HC) and fear of Coronavirus (FOC). A survey comprising 1,253 participants was conducted in India. The proposed model was empirically examined through partial least square structural equation modelling. Findings The outcomes of the study revealed a significant positive influence of PTU, PRU, PIA and PSI on PR. On the other hand, HC and FOC were identified as the major antecedents having a significant positive influence on PB. Both PR and PB had a significant influence on the intention to adopt MPS, but the influence of PB was greater than the influence of PR. Practical implications The enablers and inhibitors play a crucial role in understanding the intention to adopt MPS. HC and fear of acquiring Coronavirus can be aggressively marketed by the government and service providers as a strategy to maintain social distancing. Government should address the regulatory concerns associated with the usage of MPS so as to alleviate any negative perception among the general public. Originality/value The current study is a novel attempt to understand the intention to adopt MPS in India as precautionary health behaviour to curb the transmission of Coronavirus pandemic. The study uses two constructs, HC and FOC, to better understand the behaviour of the people and explain the intention to adopt MPS during the COVID-19 pandemic.

The emergence of high-speed internet (5G) services and the demonetization of the Indian currency by the Government of India in the year 2016 served as catalysts for the growth of banking services, such as internet/mobile banking. The main objective of the study was to investigate the role of perceived financial cost, perceived risk, and trust in the adoption of mobile banking services by users. The study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) to explain the adoption of mobile banking services by young Indian customers. The data from 253 users of age between 18–30 years were collected through a survey questionnaire and were analyzed using structural equation modeling with Amos 22.0. The results revealed that performance expectancy, effort expectancy, social influence, and perceived financial cost exhibited a significant positive influence on behavioral intentions. However, the facilitating conditions were found to exert no effect on actual use. In addition, the results demonstrate that both perceived risk and perceived trust moderate the relationship between behavioral intention and the actual use of mobile banking. The results of the study provide some novel insights into how perceived risk and perceived trust shape the interplay between behavioral intention and the actual use of mobile banking services. The inferences drawn from the study may enhance the understanding of the transformation of behavioral intention into the adoption and actual use of mobile banking services.

The paper explores the influence of greenwash on green trust and discusses the mediation roles of green consumer confusion and green perceived risk. The research object of this study focuses on Taiwanese consumers who have the purchase experience of information and electronics products in Taiwan. This research employs an empirical study by means of the structural equation modeling. The results show that greenwash is negatively related to green trust. Therefore, this study suggests that companies must reduce their greenwash behaviors to enhance their consumers’ green trust. In addition, this study finds out that green consumer confusion and green perceived risk mediate the negative relationship between greenwash and green trust. The results also demonstrate that greenwash is positively associated with green consumer confusion and green perceived risk which would negatively affect green trust. It means that greenwash does not only negatively affect green trust directly but also negatively influence it via green consumer confusion and green perceived risk indirectly. Hence, if companies would like to reduce the negative relationship between greenwash and green trust, they need to decrease their consumers’ green consumer confusion and green perceived risk.

Background Several studies highlight the effects of artificial intelligence (AI) systems on healthcare delivery. AI-based tools may improve prognosis, diagnostics, and care planning. It is believed that AI will be an integral part of healthcare services in the near future and will be incorporated into several aspects of clinical care. Thus, many technology companies and governmental projects have invested in producing AI-based clinical tools and medical applications. Patients can be one of the most important beneficiaries and users of AI-based applications whose perceptions may affect the widespread use of AI-based tools. Patients should be ensured that they will not be harmed by AI-based devices, and instead, they will be benefited by using AI technology for healthcare purposes. Although AI can enhance healthcare outcomes, possible dimensions of concerns and risks should be addressed before its integration with routine clinical care. Methods We develop a model mainly based on value perceptions due to the specificity of the healthcare field. This study aims at examining the perceived benefits and risks of AI medical devices with clinical decision support (CDS) features from consumers’ perspectives. We use an online survey to collect data from 307 individuals in the United States. Results The proposed model identifies the sources of motivation and pressure for patients in the development of AI-based devices. The results show that technological, ethical (trust factors), and regulatory concerns significantly contribute to the perceived risks of using AI applications in healthcare. Of the three categories, technological concerns (i.e., performance and communication feature) are found to be the most significant predictors of risk beliefs. Conclusions This study sheds more light on factors affecting perceived risks and proposes some recommendations on how to practically reduce these concerns. The findings of this study provide implications for research and practice in the area of AI-based CDS. Regulatory agencies, in cooperation with healthcare institutions, should establish normative standard and evaluation guidelines for the implementation and use of AI in healthcare. Regular audits and ongoing monitoring and reporting systems can be used to continuously evaluate the safety, quality, transparency, and ethical factors of AI-based services.