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The purpose of this study is to investigate the key predictors and outcomes of task–technology fit (TTF) of facial recognition payment systems with the moderating role of cultural differences in the restaurant industry.

The survey responses were collected from 336 South Korean and 336 US restaurant customers.

The results revealed that function significantly affected TTF in both groups. Unique to the Korean sample, emotion was found to be a significant determinant of TTF, whereas convenience and social influence were key predictors of TTF only for the US sample. TTF had significant and positive effects on the three dimensions of behavioral intentions in both groups. The result of multi-group analysis showed that cultural differences moderated the effect of convenience on TTF and the effect of emotion on TTF.

The authors provided recommendations for restaurant operators and technology companies seeking to improve customer TTF and acceptance of facial recognition payment systems for the first time.

本研究旨在调查面部识别支付系统任务技术匹配（TTF）的关键前置因素和影响, 以文化差异为调节变量, 研究其在餐饮行业的应用。

我们收集了来自336名韩国和336名美国餐厅顾客的调查回答。

结果显示, 在两组中, 功能显著影响TTF。对于韩国样本来说, 情感被发现是TTF的重要决定因素, 而对于美国样本来说, 方便性和社会影响是TTF的关键预测因素。在两组中, TTF对行为意向的三个维度均产生了显著且积极的影响。多组分析结果显示, 文化差异在方便性对TTF的影响以及情感对TTF的影响中起到了调节作用。

我们首次为寻求改善顾客TTF和接受面部识别支付系统的餐厅经营者和技术公司提供了建议。

Transference-based trust (TBT) via referral sources is a cognitive process where trust in third-party information about an individual transfers to trust in the individual. TBT via referral sources can have significant effects on early trust development in a virtual team (VT). This study aims to examine the potential influence of Hofstede’s (1980) cultural variables and two proposed combinations of these cultural variables on early trust development in VT, including the effects of referral source.

This study adopted multigroup analysis partial least squares structural modeling to examine potential cultural differences in the responses of 357 university students from 51 different countries to understand early trust development in VT.

TBT via referral sources as in interpersonal construct has a positive, direct impact on early trust development. TBT mediated the individual and organizational model constructs. There were significant differences in the high/low values of 3 of the 56 tested cultural dimensions.

Reaffirmed the validity of cognitive-based trust models in understanding early trust development in VTs TBT as an interpersonal construct and has a significant influence on early trust development in VTs. TBT via referral sources mediated the individual and organizational constructs of the model. There were significant differences in the high/low measures of three cultural dimensions (i.e. IV, M and the combination of IV-M-LT) in the relationship of early trusting beliefs to early trusting intensions.

To positively influence interpersonal and organizational aspects of trust development, managers should ensure that the early phases of VTs, before actual implementation begins, are well organized. Managers could make VT members fully aware of how referral sources can influence early trust development. Managers could encourage individuals to have open access to relevant social media accounts for other VT members and encourage individuals to research referral sources on other VTs members. The implication for managers of culturally diverse VT is that the development of early trust is largely by individual choice, rather than differences in national culture.

People need to maintain and actively manage their online presence, ensuring that online information about them is accurate and updated. Referral sources could help VT members learn about one another, which might in turn help foster early trust in their online teams.

Although some studies have found significant cultural differences in early trust development, other studies, including a meta-analysis of 43 studies, found no significant cultural differences in early trust development. This study confirmed the results of the meta-analysis.

Two-sided messages in advertising, which contain both negative and positive information, can have varying effects on persuasion. Thus, it is crucial to understand the conditions under which such messages are more or less effective compared to one-sided messages that only contain positive information. This research investigates the moderating role of the visual angle (close-up vs. long shot) of an image by drawing upon construal level theory.

This research reports two experimental studies employing a 2 (message: two-sided [positive and negative information], one-sided [positive information as a control condition]) × 2 (visual angle: near [close-up], distant [long shot]) between-subjects design.

The results demonstrate that two-sided messages paired with a close-up image decrease positive electronic word of mouth (eWOM) due to increased feelings of ambivalence, while two-sided messages paired with a long-shot image increase positive eWOM due to increased perceived authenticity.

These findings provide insight into the impact of two-sided messages on advertising persuasion and provide guidance for marketers in developing effective communication strategies to leverage positive eWOM.

The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners.

Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses.

The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners’ intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners’ intentions to use IoT.

These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners’ intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field.

This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector.

This study examined how likeminded Facebook comments with incivility and without supporting evidence influence readers' evaluations of the commenter and online political participation intention. This study also investigated whether the indirect effect of exposure to uncivil comments and comments without evidence on online political participation through evaluations of the commenters is contingent on the strength of partisanship.

The study used a 2 (uncivil comments vs civil comments) × 2 (comments without supporting evidence vs comments with supporting evidence) factorial design with a scenario about reading similar viewpoints about the gun control issue in Facebook comments.

The results showed that compared to exposure to civil agreeing comments, exposure to uncivil likeminded comments resulted in higher levels of negative evaluations of the commenters, which in turn decreased willingness to participate in political activities online. Exposure to comments without evidence led to more negative evaluations of the commenters, but it did not significantly influence online political participation. In addition, the strength of partisanship did not significantly moderate the indirect effect of exposure to uncivil comments and comments without evidence on online political participation through evaluations of the commenters.

Although previous studies have demonstrated the significant effects of incivility and reasoned argument, little is known about whether and how people evaluate ingroup members' comments that are uncivil and lacking reasoned arguments. Most of these studies have examined incivility in political contexts, but few have extended the context to the effect of likeminded comments, especially when the comments are uncivil and lack supporting evidence. The current study aims to fill this gap in the literature.

Considering the growth of the at-home smart technology industry and the increasing power of social media influencers, this study aims to examine how influencer endorsements affect individuals’ attitudes and trial intentions toward smart technology products.

An online experiment was conducted to investigate the impact of follower number and expertise domain of influencers and the trust propensity of individuals on their attitudinal and behavioral responses to influencer endorsements of smart technology products. The moderated mediation effect of perceived credibility was further examined.

The results demonstrated that individuals with lower trust propensity responded more positively to a microinfluencer with fewer followers and a specific area of expertise, which led to favorable attitudes and increased intention to try a smart technology product. However, the expertise domain was not a significant factor for the megainfluencer condition with a more extensive follower base. Interestingly, the interaction effects were not observed for individuals with higher trust propensity.

The results of this research provide practical implications for marketers who look for effective strategies for influencer marketing by demonstrating the significant impact of source-related cues, including follower number and expertise domain.

Based on the modality, agency, interactivity and navigability; source credibility; and persuasion knowledge models, this research explains how source-related cues of influencers affect credibility judgment, attitude formation and trial intentions for new technology products and how trust propensity as a personal dispositional factor varies the relationship.

The coronavirus disease 2019 (COVID-19) pandemic has had a big impact on organisations globally, leaving organisations with no choice but to adapt to the new reality of remote work to ensure business continuity. Such an unexpected reality created the conditions for testing new applications of smart home technology whilst working from home. Given the potential implications of such applications to improve the working environment, and a lack of research on that front, this paper pursued two objectives. First, the paper explored the impact of smart home applications by examining the factors that could contribute to perceived productivity and well-being whilst working from home. Second, the study investigated the role of productivity and well-being in motivating the intention of remote workers to use smart home technologies in a home-work environment in the future.

The study adopted a cross-sectional research design. For data collection, 528 smart home users working from home during the pandemic were recruited. Collected data were analysed using a structural equation modelling approach.

The results of the research confirmed that perceived productivity is dependent on service relevance, perceived usefulness, innovativeness, hedonic beliefs and control over environmental conditions. Perceived well-being correlates with task-technology fit, service relevance, perceived usefulness, perceived ease of use, attitude to smart homes, innovativeness, hedonic beliefs and control over environmental conditions. Intention to work from a smart home-office in the future is dependent on perceived well-being.

The findings of the research contribute to the organisational and smart home literature, by providing missing evidence about the implications of the application of smart home technologies for employees' perceived productivity and well-being. The paper considers the conditions that facilitate better outcomes during remote work and could potentially be used to improve the work environment in offices after the pandemic. Also, the findings inform smart home developers about the features of technology which could improve the developers' application in contexts beyond home settings.

Driven by Davis’s (1989) technology acceptance model (TAM) and Westaby’s (2005) behavioral reasoning theory (BRT), the purpose of this study is to develop and test a conceptual model and examine consumers’ acceptance of artificial intelligence (AI) chatbots for apparel shopping.

Data from 353 eligible US respondents was collected through a self-administered questionnaire distributed on Amazon Mechanical Turk, an online panel. Confirmatory factor analysis and path analysis were used to test all hypothesized relationships using the structural equation model.

The results show that optimism and relative advantage of “reasons for” dimensions have a positive and significant influence on perceived ease of use (PEU), while innovativeness and relative advantage have a positive and significant influence on perceived usefulness (PUF). Discomfort and insecurity have no significant impact on PEU and PUF. However, complexity has a negative and significant impact on PEU but not on PUF. Additionally, PEU has a positive influence on PUF. Both PEU and PUF have a positive and significant influence on consumers’ attitudes toward using AI chatbots, which, in turn, affects the intention to use AI chatbots for apparel shopping. Overall, this study identifies that optimism, innovativeness and relative advantage are enablers and good reasons to adopt AI chatbots. Complexity is a prohibitor, making it the only reason against adopting AI chatbots for apparel shopping.

This study contributes to the literature by integrating TAM and BRT to develop a research model to understand what “reasons for” and “reasons against” factors are enablers or prohibitors that significantly impact consumers’ attitude and intention to use AI chatbots for apparel shopping through PEU and PUF.