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Blockchain can track the material from the manufacturer to the end customers. Therefore, it can ensure the product's authenticity, transparency and trust in the retail supply chain (SC). There is a need to trace and track the retail products before it reaches the customers to check the quality of the products so that expired products can be recycled and reused, which in turn will help gain customers' trust. This research aims to investigate retail employees' behavioural intention to adopt blockchain in the retail SC.

To examine the behavioural intention of employees in the retail SC, the research uses three theories – the technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour. The technology acceptance model measures the employee's acceptance of blockchain in the retail SC. The unified theory of acceptance is used in this research to measure how blockchain adoption will improve the performance of the employees. The theory of planned behaviour is used in this research to measure whether the employees intend to adopt blockchain. A survey was carried out in the retail stores of India. Exploratory factor analysis and structural equation modelling were used for data analysis.

This study found that the employees of the retail stores have a positive intention and attitude to adopt blockchain technology. Further, it was found that perceived behavioural control and effort expectancy was not promoting blockchain adoption in the retail sector.

This study will help the retail stores' employees understand the blockchain in their operations and will motivate the top management of the retail companies to adopt this technology. The study is limited to the retail SC in India only.

This study uses three theories technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour, which were not used in earlier studies of blockchain adoption in the retail SC.

The present study identifies the factors that impact behavioral intentions to adopt solar water heaters (SWHs) and examines their relationship with behavioral intentions using an extended “Unified Theory of Acceptance and Use of Technology” (UTAUT) model.

The study used a primary survey to collect data from 423 respondents across seven Indian states selected through purposive sampling. The collected data was analyzed using IBM SPSS software and “Structural Equation Modeling” (SEM) was performed using SmartPLS 3.5.5.

The results suggest that social influence is the most significant factor affecting SWH adoption, followed by effort, performance expectancy and facilitating conditions. The perceived cost negatively affects behavioral intentions and social influence on behavioral intentions is partially mediated by facilitating conditions. People prefer SWHs if they are easy to install and compatible with other home appliances. Positive perception of friends and family, easy access and government incentives contribute to SWH adoption.

SWH adoption can be promoted by designing sector-specific programs and improving ease of installation, operation, maintenance and after-sale services.

This study explores the behavioral intentions of individuals in India to adopt SWHs. India is a developing tropical country with a high potential for SWH adoption but has not received much attention. Further, the research integrates the perceived cost construct in the UTAUT model and examines the partial mediation impact of facilitating conditions to improve the model’s comprehensibility.

The purpose of this study is to investigate the factors, which drive teenagers’ behavioural intention to adopt wearable technologies and their behavioural intention to recommend others.

This study proposes a new adoption model combining two different models including the extended unified theory of acceptance and use of technology and the theory of planned behaviour, which provided relevant contributions for understanding the adoption of wearable technologies. A structural equation modelling approach using analysis of a moment structures 23 software was used to analyse the data collected from 318 respondents.

Findings of this study reveals that performance expectancy (β = 0.28; t = 2.049), facilitating conditions (β = 0.28; t = 1.989), social influence (β = 0.23; t = 3.150) and attitude (β = 0.18; t = 3.246) have a statistically significant impact on behavioural intention. Additionally, behavioural intention (β = 0.15; t = 2.543) and attitude (β = 0.15; t = 3.261) have a statistically significant impact on intention to recommend others. However, effort expectancy, price value, hedonic motivation and habit did not have a significant influence on behavioural intention.

In this study, the understanding of the determinants contributing to teenagers’ behavioural intention to use wearable technologies and driving their intention to recommend others to adopt these devices will provide insights to practitioners and decision makers to customize the features of wearable devices to promote sustainable use of these technologies.

This study is among the first to investigate wearable technologies from behavioural perspectives especially on teenagers in Bangladesh. Hence, the findings of this study will help to comprehensively explain teenagers’ behavioural intention to adopt wearable technologies and their intention to recommend others.

This study aims to examine the factors (Stimuli) enhancing perceived utilitarian, social and conditional values (Organisms) of social commerce (s-commerce) platforms and their impact on small and medium enterprises’ (SMEs’) behavioral intention (Response) to adopt s-commerce.

Survey data were gathered from 304 Indian SMEs using s-commerce platforms. Data were analyzed using SmartPLS 3 software.

The results indicated that perceived values significantly impact SMEs’ behavioral intention to adopt s-commerce. Among conditional, utilitarian and social values, the conditional value of s-commerce sites was found to be the strongest motivator for SMEs to adopt s-commerce.

This research contributes to the growing literature on s-commerce, explaining how perceived value influences the decision of SMEs to adopt s-commerce platforms.

Among the significant influencers, perceived usefulness and perceived reputation were found to be the most effective triggers that stimulate perceived values of s-commerce sites. The findings draw due attention from policymakers toward environmental cues such as the legal and regulatory environment, which are instrumental in creating the most important perceived value for SMEs, i.e. conditional value.

By employing the inputs from the theory of consumption values and the Stimulus-Organism-Response framework, this original study looked beyond the technology factors and examined the role of perceived values of s-commerce platforms in shaping SMEs’ behavioral intention to adopt.

Financial technology innovation within the developed world is driving financial markets, yet its adoption is lagging among consumers in emerging markets. At the same time, most African economies continue to be at the tail end of global financial innovations adoption. Given lagging consumer adoption of cryptocurrency in South Africa, the purpose of this paper is to apply the theory of planned behaviour (TPB) to predict behavioural intention to adopt cryptocurrency.

A survey instrument based on the TPB was used to collect quantitative data for predicting adoption from adult distance students at the Mancosa, Cape Town campus. For data analysis, the two-step structural equation modelling approach was used.

The findings indicate that attitude and perceived behavioural control positively impact the intention to adopt cryptocurrency. Subjective norm showed a negative non-significant influence. Overall, the results of the study show that the model has a good model fit and can be used to explain the theory.

The results of this study may not be generalisable to the wider population as it is only based on a cross-sectional study of a sample of adult students at a single institute in South Africa.

The contribution of this paper is threefold: it is one of a few studies on the behavioural intention to adopt cryptocurrency in South Africa using the TPB model, it contributes towards the use of predictive behavioural economics models in understanding consumer behaviour critical to accelerating the adoption of financial innovations, and the results of the study also inform behaviour change strategies that can be applied by practitioners or policymakers to improve adoption. Studies of this nature may lead to the development of financial innovation in emerging markets through a nuanced understanding of consumer behaviour.

This study examines the predictors of behavioral intention of farmers to adopt a mobile agricultural finance application called e-AgriFinance using the Unified Theory of Acceptance and Use of Technology (UTAUT) and perceived cost as an additional predictor.

Using a questionnaire survey, data are collected from 337 farmers in Sarawak, Malaysia. The collected data are analyzed using partial least squares structural equation modelling (PLS-SEM).

The research finds that performance expectancy, effort expectancy, social influence and facilitating conditions are positively related to behavioral intention to adopt the e-AgriFinance app, with social influence being the strongest predictor. Perceived cost is also found to be positively related to behavioral intention which contradicts the prediction of the model.

This study contributes to the use of UTAUT in predicting the adoption of mobile agricultural finance applications among farmers.

For practice, this study provides implications for the Sarawak government to promote digital and financial inclusivity for all communities. This study also provides insights into important features of the e-AgriFinance app for digital finance providers to develop the apps that will be well accepted by farmers in the future.

This research is one of the few studies that focused on farmers' mobile technology adoption in agribusiness from the perspective of an emerging economy.

This study examines the main factors influencing banking customers' behavior toward smart banking services (SBS) adoption in Pakistan. This study extends the unified theory of acceptance and use of technology (UTAUT2) by integrating information privacy concern and big brother effect into an overarching conceptualization.

This study adopts theoretical constructs from the related literature and develops hypotheses. An analysis of 385 banking customers was performed using partial least squares structural equation modeling (PLS-SEM).

The results show that most predictors of behavioral intention, including facilitating conditions, effort expectancy, habit, performance expectancy, hedonic motivation (except for social influence and price value), big brother effect and perceived information privacy concern are significant. Indeed, all predictors of use behavior are also significant. Gender and age differences between individuals further moderate the relationship between UTAUT2 constructs. Moreover, information privacy concern mediates the relationship between big brother effect and behavioral intention.

This cross-sectional study focused only on Pakistan as a developing country, which limits the generalizability of the results.

The roles of social influence and price value must be strengthened by employing marketing strategies and personalized communication. Banks should offer incentives and rewards to customers who recommend SBS to friends and family members. In addition, banks must consider the price factor when offering these services to increase their market share.

This study contributes to the field of technology adoption by providing a unique perspective of SBS adoption in Pakistan. This empirical study is the first to extend the UTAUT2 model by integrating information privacy concern and big brother effect to assess SBS acceptance and use behavior. This study examines SBS adoption issues at the national level, especially in Pakistan.

The main objective of this study is to investigate the factors that influence the adoption intention of cloud computing services among individual users using the extended theory of planned behavior.

A purposive sampling technique was used to collect a total of 339 data points, which were analyzed using SmartPLS to derive variance-based structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA).

The results obtained from PLS-SEM indicate that attitude towards cloud computing, subjective norms, perceived behavioral control, perceived security, cost-effectiveness, and performance expectancy all have a positive and significant impact on the adoption intention of cloud computing services among individual users. On the other hand, the findings from fsQCA provide a clear interpretation and deeper insights into the adoption intention of individual users of cloud computing services by revealing the complex relationships between multiple combinations of antecedents. This helps to understand the reasons for individual users' adoption intention in emerging countries.

This study offers valuable insights to cloud service providers and cyber entrepreneurs on how to promote cloud computing services to individual users in developing countries. It helps these organizations understand their priorities for encouraging cloud computing adoption among individual users from emerging countries. Additionally, policymakers can also understand their role in creating a comfortable and flexible cloud computing access environment for individual users.

This study has contributed to the increasingly growing empirical literature on cloud computing adoption and demonstrates the effectiveness of the proposed theoretical framework in identifying the potential reasons for the slow growth of cloud computing services adoption in the developing world.

This study aims to explore the factors that could affect consumers’ adoption of augmented reality (AR) and investigate the interaction between gender and educational level on intention to adopt AR in developing countries as demonstrated here by Saudi Arabia.

The examined constructs were developed by integrating factors from the unified theory of acceptance and the use of technology (UTAUT2), including performance expectancy, expectancy effort, social influence, facilitating conditions, hedonic motivation and habit. Price value was eliminated and innovativeness was added to the examined constructs. Data were collected from 673 Saudi consumers through an online survey by implementing a convenience sampling. Furthermore, the effect of gender and education level on behavioral intention to adopt AR by consumers was examined.

The results of the regression analysis showed that the independent variables statistically significantly predict the consumers’ behavioral intention toward AR adoption with all the examined constructs. The proposed model was able to explain 84% of the variance of behavioral intention. Furthermore, there was a statistically significant interaction between the effects of gender and educational level on intention to adopt AR.

This study will clarify the relatively low diffusion rate of AR adoption in Saudi Arabia, which will help business owners and marketers to develop the right strategies, especially strategies that are associated to marketing and developing mobile applications by incorporating AR technologies, which will attract the attention of many users.

This is one of the few studies that has explored the intention to adopt AR by consumers by examining the UTAUT2 constructs in the Middle Eastern cultural contexts, in contrast to previous studies, specifically Saudi Arabia. This study further investigated the interaction between the effects of gender and educational level on intention to adopt AR.

The purpose of this paper was to examine the intention to adopt mobile banking services among Generation Y consumers using the unified theory of acceptance and use of technology Unified Theory of Acceptance and Use of Technology (UTAUT) model.

The paper investigated responses from a particular sub-group of Generation Y consumers that is college or university students. The final sample collected was 347 cases, representing a response rate of 90.4 per cent. Two sets of analyses were performed: multiple regression analyses testing the extended UTAUT model and a mediated regression analysis testing the intervening effect of performance expectancy (PE) on the relationship between effort expectancy (EE) and behavioural intention.

Multiple regression analysis revealed PE as the strongest predictor, followed by EE, perceived risk and social influence. The prediction model explained 68.3 per cent of the variance in intention to adopt mobile banking. Mediation analysis supported a partial mediation effect of PE on the relationship between EE and intention to adopt mobile banking.

This study examined respondents’ intention to adopt mobile banking instead of their actual behaviour. Understanding behavioural intention is essential, but it may not accurately represent actual behaviour. In addition, results from this study may not be generalisable to the whole population of Generation Y college or university students due to selection bias and a lack of information concerning the sampling frame.

This research identifies the factors that affect the intention to adopt mobile banking among the Generation Y college or university students. Bank operators can use the findings to improve their marketing strategies and services offered to make them more attractive and competitive to students to speed up the mobile banking adoption rate.

This study is one of the few local studies that introduce a practical model of extended UTAUT by including perceived risk to understand the mobile banking adoption intention among millennial generation.