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The purpose of this paper is to empirically determine the key factors influencing the US consumers’ intentions to use apparel m-commerce.

An enhanced consumer’s apparel m-commerce adoption model was developed through integrating the existing e-commerce/m-commerce theories (i.e. theory of reasoned action, Technology acceptance model and diffusion of innovation theory). The investigated factors included nine independent variables – perceived usefulness (PU), perceived ease-of-use, subjective norm (SN), personal innovativeness traits, security and privacy concerns, compatibility, observability, trust and past non-store shopping experience (PE), and five control variables – age, gender, education level, income level and ethnicity. The dependent factor is consumer’s intention to use (IU) apparel m-commerce. The primary data were gathered by an online survey of US consumers via Amazon Mechanical Turk. In total, 317 eligible responses were received. The applied statistical techniques were factor analysis and multiple regression analysis.

The results show that the US consumer’s IU apparel m-commerce is significantly affected by PU, SN, compatibility and PE and education level. Overall, 67.3 percent of variation in the US consumer’s IU apparel m-commerce is explained by the developed model, which suggests a high explanatory power.

Companies should provide those functions and features on their mobile websites that enable consumers to easily find the products wanted and complete transactions efficiently. Companies should particularly target the consumers with innovativeness traits and/or those having prior non-store shopping experience. Enhancing the trust in m-commerce among the US consumers with higher education level could help companies attract more potential users. Elderly, female or lower income consumers could be the next business opportunities for apparel e-tailers.

As one of the first efforts made to understand the emerging apparel m-commerce phenomenon, this study empirically determined the key factors influencing the US consumer’s IU apparel m-commerce.

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.

Mobile e-commerce has brought convenience to consumers. But for goods such as shoes, mobile e-commerce has failed to provide the same experience as consumers would have in physical stores, and that also causes problems for online merchants, such as high return rates. As a result, the augmented reality (AR) virtual shoe-try-on function appeared. The way that AR virtual shoe-try-on study different from other AR virtual try-on studies is that AR virtual shoe-try-on study only satisfies consumers' visual experience and consumers cannot judge whether the shoes are comfort or not. Whether consumers would accept AR virtual try-on function to help them make purchase decision due to the visual experience provided by AR virtual try-on function is worth discussion. Measuring users' perceptions and preferences can help companies design AR shoe-trying functions and provide services more cost-effectively.

To promote the continuous use and better development of such mobile e-commerce based on the technology acceptance model (TAM), this study explored the influencing factors for users' intentions to continue using the AR virtual shoe-try-on function, including the perceived usefulness, perceived ease of use, system quality, perceived playfulness and attitude.

The results of this study showed that TAM is a powerful theoretical tool of the new technology in mobile e-commerce and that the system quality and perceived playfulness also have a positive impact on the original variables of TAM. System quality and perceived playfulness are important predictors of users' continuance intentions to use the AR virtual shoe-try-on function.

The main contribution of this study to model iteration and theoretical update is to verify the applicability of the TAM in the AR shoe-try-on function and to expand TAM model with system quality and perceived playfulness. The authors' results will help shoe enterprises win users' recognition through AR shoe-try-on function and improve users' continuance intention of use.

Although East Asia and South East Asia have seen growth in mobile commerce activities, the uptake of such activities in Central Asia has been relatively low. For insight, the purpose of this paper is to investigate the impact of culture, innovation characteristics and concerns about order fulfillment on mobile commerce (shopping) intention in Central Asia.

In total, 779 questionnaires were collected (via mall-intercept method) from cities in Kazakhstan, Kyrgyzstan and Uzbekistan. The data were then subjected to two-step structural equation modeling procedures (using SPSS AMOS V.25) for hypothesis testing.

This study revealed that innovation characteristics, system-based trust (trust in mobile technology), and concerns about order fulfillment affected mobile commerce intention in Central Asia. The strong uncertainty avoidance characteristics of societies in the region mean potential adoptee place great emphasis on trialability and security of mobile commerce. Uncertainty avoidance correlated strongly with concerns about order fulfillment, thereby significantly impacting mobile commerce intention. Power distance and collectivism correlated with observability as factors affecting mobile commerce intention. The innovation characteristics of compatibility, complexity and relative advantage directly impact mobile commerce intention in Central Asia.

There are several limitations in this paper. First, the data in this study are limited to Kazakhstan, Kyrgyzstan and Uzbekistan. This might affect the generalization of this study’s findings across the whole Central Asia region. Second, the respondents in this study are exposed to mobile shopping for less than 30 min before been asked to complete the survey. This might affect respondent’s confidence in mobile commerce. Future study might involve the rest of Central Asia (Tajikistan, Afghanistan and Turkmenistan). Future study might also want to investigate the impact of Web assurance seal on mobile commerce intention in Central Asia.

Managerial/marketing implications and recommended strategies in this study would be useful for businesses (aspirant e-vendors) in Central Asia.

There is limited study about mobile commerce in Central Asia. Furthermore, extant literature on mobile commerce in the region lacked age varieties or lacked multi-national and logistical perspective. This is important given the wide geographical spread of the region. This study addressed these gaps by collecting data from all segments of society in Kazakhstan, Kyrgyzstan and Uzbekistan to test propositions regarding innovation characteristics, culture, and concerns about order fulfillment as factors impacting mobile commerce intention in Central Asia.

The purpose of this paper is to examine the impact of social commerce (s-commerce) cues (i.e. trust, compatibility, reliability and responsiveness) on repurchase intention in apparel s-commerce along with the mediating effect of customer engagement and the moderating effect of s-commerce navigation.

Using the purposive sampling technique, face-to-face survey was administered to Gen-Y social media users in Malaysia. Subsequently, 384 respondents were sampled. Partial least squares-structural equation modeling was used to perform the analyses.

S-commerce cues have a positive effect on customer engagement, which in turn leads to repurchase intention of apparel among Gen-Y. Particularly, customer engagement also mediates the relationship between s-commerce cues and repurchase intention. S-commerce navigation is found to moderate the effect of engagement on repurchase intention.

The findings are derived from the perception of Gen-Y in Malaysia and do not represent the entire population. Future research could investigate the same phenomena across generations and consider heterogeneity issues to provide more insights.

Apparel s-commerce retailers are suggested to engage with customers more in the e-retail environment to build a lasting relationship. Contextual factors such as ease of navigation should be observed to enhance the desired response of diverse customers today.

This study adds to the growing body of knowledge on relationship marketing by assessing the impact of customer engagement and navigation on the relationships between s-commerce cues and repurchase intention in the contemporary setting.

This research investigates apparel consumers' psychological and behavioral responses to omnichannel (OC) integration. Specifically, the study applies the cognitive–affective–conative (CAC) model to reveal consumers' decision-making process under the impact of channel integration quality (CIQ), perceived fluency (PF) and cognitive and affective trust (AT).

Primary data were collected through an online survey. In total, 657 eligible responses were received. This study applied partial least square structural equation modeling for data analysis.

The findings demonstrate that the extrinsic cognitive factor, CIQ, substantially affects consumers' intrinsic cognition (cognitive trust [CT] and PF), which consequently fosters consumers' AT and shopping intentions. Specifically, integrated promotion and transaction information positively affects CT, while integrated product and price and information access negatively impact CT. All the dimensions of CIQ, except integrated promotion (IP), significantly affect PF. CT and AT exhibit mediation effects in the CAC model.

Apparel brands and retailers may apply the findings to effectively design their retail channels and implement channel integration to boost consumers' shopping intentions and trust.

This study is one of the pioneering studies applying the CAC model to empirically examine OC consumers' decision-making process. It is also among the first to determine that cognitive and AT have theoretical distinctions in the OC retailing setting.

This study investigates the factors influencing re-usage intention of online and mobile grocery shopping among young adult consumers in South Africa.

Data were collected from selected young adult participants using a stratified probability sampling strategy. Smart PLS was used to analyse the data.

The findings of the study indicate that perceived usefulness (PU), peer review (PR) and attitude (ATT) positively influence continuance intention (CI).

In line with the available literature, there are few prior post-adoption studies that delineate the influence of individual characteristics on digital commerce usage activities. There is high mobile penetration as a result of positive digital commerce and mobile application usage and adoption, creating the need to investigate and better understand the drivers behind, not just adoption and usage, but continued use of digital commerce platforms and applications. Since the sample size is relatively small, further future research studies can test the same model with bigger sample sizes to assess generalisability of the results in different locations.

This study adds to the current literature by concentrating on the extent to which systems and marketing elements influence young adult customers' intention to continue using online and mobile grocery shopping platforms in South Africa.

The study adds value from a theoretical standpoint, contributing to the antecedent factors of the technology acceptance model (TAM), theory of reasoned action (TRA) and stimulus-organism-response (S-O-R) model and giving marketing academics insights into what aspects drive re-use of online and mobile grocery shopping and on what should be the focus.

The aim of this research work is to examine the originator which is affecting in Thailand the adoption of m-commerce (based on the behavioural intention). The usage of m-commerce has faced reluctance by the subscribers of mobile phone, which is in general the most anticipated challenge among both the developing and developed countries. Similarly, there are restricted empirical research work regarding to the m-commerce in Thailand. As a result, in the situation of developing countries (for instance, Thailand specially), very less numbers of research exist for the recognition of important variables for the m-commerce installation or estimating the m-commerce adoption variables. For explaining the behavioural targets of subscribers and for estimation generally the model that has been used is referred to as technology acceptance model (TAM). First, the factor subjective norms by the region of technology acceptance had contradictory outcomes and inconsistency to the behavioural target. In this study, we employed the Smart Partial Least Square Structural Equation Modelling version 3.2.6 as a data analysis technique. The response rate of the current study is 81%. The results have certainty that has established the presence of these associations between the users which implicated the significance of subjective norms in Thailand which were recognized. The personal opinion of usefulness, perceptions of attitude and easy usage to m-commerce are the important features towards the subjective norms which are the social impacts.

Purpose: The main purpose of this study is to test the effect of consumers’ readiness level to use new technology on their intention to use mobile payment applications based on the technology readiness and acceptance model (TRAM). In detail, it examines how the dimensions of TR as ‘optimism, innovativeness, discomfort, and insecurity’ affect consumers’ intention to utilise mobile payment applications. Moreover, the effect of the technology-accepting behaviour measured by two major factors as ‘perceived usefulness’ and ‘perceived ease of use’ on the intention to use mobile payment applications is also examined.

Need for the study: The existence of a mobile system alone is not enough to attract consumers with no user experience to these applications. The user-centred attribute in the usage of these applications, which involves the influence of technology readiness (TR), has been largely ignored especially in developing countries. By focussing on this area, it is expected to fill the gap that has not been sufficiently handled in the developing country settings and, particularly in Turkey.

Methodology: The study population consists of the consumers who live in İstanbul who is aged 18 and over and use mobile payment technology at least once. After collecting data, confirmatory factor analysis was applied to validate the measurement model. Afterward, the structural model was tested by the Maximum Likelihood-MI estimation method, and the bootstrap samples were stated as 5,000.

Findings: When the results of the study are examined, it is seen that optimism has a significant influence on the perceived usefulness and perceived ease of use dimensions of the technology acceptance model, while innovativeness is significant only on the perceived ease of use. This study results also show that discomfort and insecurity don’t significantly influence the perception of usefulness and easy-to-use mobile payment applications as perceived by individuals. Perceived ease of use is to positively affect the perceived usefulness. Additionally, the perceived ease of use and the perceived usefulness are strong predictors of intention to use mobile payment applications.

Practical implications: Findings of this study demonstrate the validity of the technology readiness and acceptance model for explaining the intention of using mobile payment applications in Turkey. To improve consumers’ intent in the usage of m-payment apps, their level of technological readiness towards technology should be determined and the factors that affect the formation of insecurity and discomfort attitudes of individuals should be emphasised.

As satisfaction is one of the most important conditions for loyalty, this study aims to investigate the main factors affecting online satisfaction for buying clothes from the internet. In this research, the authors followed two main objectives: (1) to identify factors influencing online satisfaction and (2) to determine the importance of the main determinants that explain online satisfaction in the retailing clothing sector.

The research combines qualitative and quantitative research methods. The authors used the focus group technique and a survey based on a questionnaire. For the first exploratory phase of the research, we conducted four focus groups with 21 women, 18–39 years old, who have at least two years experiences as online buyers and who made at least two acquisitions for clothing products in the past six months, from the same website. The purpose of this qualitative method was to understand the young women's perception about online satisfaction and to collect items to be included in the questionnaire. For the second quantitative phase of this study, the sample consisted of 241 participants. To analyse the data, two different types of inferential analysis were used: factor analysis (for identifying the factors that compose online customer satisfaction) and analysis of regression (to determine the most important factors that determine and predict online buyers' satisfaction).

The main results indicate that the significant factors determining a satisfactory experience in an e-retailing market are: good deal (savings), product expectations, customer service and website reputation.

The study is more relevant in the current pandemic context, when the consumer’s behaviour has changed and online shopping has substantially increased. The research can be used by companies that sell clothing on the internet and are interested in increasing their financial results and also their customers' satisfaction.