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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.

Electric cars have very little market share in developing countries despite their environmental benefits. Thus, governments have started promoting electric cars by providing financial incentives to consumers. The current article aims to examine the direct and indirect effects of government financial incentives on consumer electric car adoption in India.

The study followed a quantitative research method that employed a self-administered survey questionnaire. Structural Equation Modelling and Multi-Group Analysis were followed for data analysis.

The study revealed that financial incentives have an indirect effect on electric car adoption intention rather than a direct effect. In addition, financial incentives were found to have a direct effect on attitude and Perceived Behavioural Control (PBC). Attitude and PBC positively influenced consumer adoption intention.

The insights and implications from the present study would help policymakers and marketers to formulate better incentive policies and market strategies to increase consumer acceptance of electric cars in developing countries.

The study contributes to the literature by analysing the underlying mechanism that links government financial incentives to electric car adoption intention. This study also explored the direct effect of financial incentives on attitude and PBC, which are less investigated in electric vehicle literature. In addition, the present article also assessed the moderating role of age in electric car adoption, which has mixed evidence in the literature, and such studies are scarce in the Indian context.

This study aims to investigate the factors influencing the adoption of online pharmacies in Qatar using the unified theory of acceptance and use of technology-2 (UTAUT-2) framework. Specifically, this study examines the impact of performance expectancy, effort expectancy, social influence, hedonic motivation, habit, technology trust, perceived risk and users’ level of awareness of behavioral intention, which in turn affects the adoption of online pharmacies. Furthermore, this study explores the moderating role of word-of-mouth (WOM) recommendations on the relationship between behavioral intention and online pharmacy adaptation.

This study adopted a descriptive, quantitative approach to investigate the UTAUT-2 model in the context of consumers’ adoption of e-pharmacy in Qatar. Through convenience sampling, 455 responses were collected from regular customers accessing online pharmacy services. The data were analyzed using Smart-PLS 3.2 software to examine the hypothesized relationships.

The results showed that WOM recommendations significantly enhanced the relationship between behavioral intention and adopting online pharmacies in Qatar. This study identified the factors that may hinder or enable the adoption of online pharmacies, including performance expectancy, effort expectancy, social influence, hedonic motivation, habit, technology trust, perceived risk and users’ level of awareness.

This study contributes to the existing literature on technology acceptance by extending the UTAUT-2 model and recognizing three additional variables (perceived risk, technology trust and technology awareness). These need to be investigated against UTAUT-2 variables to detect the significance of their impact on adapting the e-health concept in Qatar. The potential for cultural change to accelerate the adoption of online pharmacies is highlighted. Future research should explore the role of moral and cultural factors in technology adoption.

The results underscore the economic and social significance of e-pharmacy adoption, particularly within the context of a developing country. Considering the positive intentions expressed by individuals toward e-pharmacy, it becomes crucial for managers and decision-makers to make strategic choices to address any challenges that may arise. Policymakers are encouraged to enhance their services and implement various development initiatives to expand e-pharmacy accessibility and availability.

This study builds upon previous research on e-commerce in the pharmaceutical industry and provides a comprehensive understanding of customers in developing countries. Extending the UTAUT-2 model and identifying additional variables contributes to the knowledge of e-health concepts in Qatar. The findings have practical implications for developing strategies to promote online pharmacy adoption in Qatar and other countries.

Recently, the Government of India has emphasized digital financial inclusion for promoting cashless transactions with a vision to transform India from a traditional cash-based economy into a cashless economy. Technology-driven payment apps are facilitated greater access to cashless financial services and improve the speed, efficiency, accuracy and effectiveness of financial transactions. This study aims to explore the determinants of quick response (QR) code mobile payment (m-payment) adoption intention among marginalized street vendors in India.

The proposed research model was tested using 320 responses from QR code m-payment users. An interview schedule was performed using the structured questionnaire from marginalized street vendors by adopting a purposive sampling technique. The proposed research framework of this study developed on the Unified Theory of Acceptance and Use of Technology (UTAUT). In addition to the existing variables proposed in the UTAUT model, three more variables have been added, namely, digital financial literacy (DFL), personal innovativeness (PI) and perceived trust (PT). Besides, the study used confirmatory factor analysis and structural equation modeling techniques to analyze the data.

This study confirms that factors such as performance expectancy, effort expectancy, facilitating conditions, PT and customers’ DFL are significant determinants of street vendors’ intention to use QR code m-payment services. However, social influence and PI have shown an insignificant relationship with adopting a QR code m-payment system.

The results provide insights for policymakers and service providers. Specifically, government and bankers design promotional campaigns emphasizing the ease of use, perceived benefits, security and faster business transactions to accept and use the QR code m-payment system to encourage prospective users to achieve a cashless economy.

Many prior studies have widely concentrated on m-payment adoption intention in India. However, only a few studies have attempted to examine the factors influencing the adoption of QR code m-payment services among merchants from emerging economies. There is a dearth of studies on QR code adoption from an unorganized sector perspective, specifically marginalized street vendors. Therefore, this study explicitly examines the extent to which the determinants of adoption intention toward QR code-based m-payment services among marginalized street vendors within the framework of the extended UTAUT model by incorporating DFL, PI and PT. The findings of this study contribute, theoretically and practically, to the existing literature.

The primary objective of this study is to explore consumers' non-adoption intentions towards meta-commerce (or metaverse retailing). Utilizing the Innovation Resistance Theory (IRT) as the theoretical foundation, this study investigates the impact of diverse barriers on non-adoption intentions within the meta-commerce context.

A total of 356 responses were gathered to test the proposed hypotheses. Structural Equation Modelling (SEM) with SmartPLS 4 software was used to examine these hypotheses.

The findings of this study show that perceived cyber risk, perceived regulatory uncertainty, perceived switching cost and perceived technical uncertainty are significantly linked to non-adoption intention towards meta-commerce. Furthermore, the study suggests that the moderating influence of technostress on these connections is more pronounced for consumers with high technostress compared to those with low technostress.

This study makes a significant contribution to the current body of literature by providing valuable insights into the fundamental barriers that consumers encounter when contemplating the adoption of meta-commerce. This contribution is particularly noteworthy as it fills a gap in the existing literature, as no prior study has comprehensively examined the primary obstacles that shape consumer intentions towards meta-commerce adoption. This novel perspective offers scholars, businesses and policymakers a foundation for developing strategies to address these barriers effectively.

This study aims to investigate the factors influencing the adoption intention of artificial intelligence (AI) by micro, small and medium enterprises (MSMEs) in Jordan.

The study adopts the technology–organization–environment (TOE) model. It examines the moderating effects of innovation culture, employee digital skill level and market competition on the relationships between the independent and dependent variables. A survey was utilized to collect data from 537 MSME owners or managers in Jordan and employed partial least squares structural equation modeling to test the hypotheses.

The results of the study support seven out of eight hypotheses. Business innovativeness, management support, perceived benefits and technological infrastructure have positive and significant effects on AI adoption intention, while perceived costs have no significant effect. However, the innovation culture, employee digital skill level and market competition were found to moderate the relationships between some of the independent variables and dependent variables.

The study provides valuable insights and recommendations for MSME owners, managers, employees, policymakers, educators and researchers interested in promoting and facilitating AI adoption by MSMEs in Jordan.

The current attempt extends the TOE framework by adding significant constructs representing the three contexts. Moreover, it is one of the few studies that analyzed the factors influencing the adoption intention of AI by MSMEs in Jordan, which are significant to the Jordanian economy and represent 99.5% of enterprises.

Developing green innovative services is critical to the restaurant industry to achieve significant benefits as well as environmental sustainability. This study aims to explore the mechanisms through which employees’ green involvement can foster green service innovation behavior.

The data set garnered from employees who worked in restaurants was used to test these mechanisms. A partial least square technique was conducted on this data set.

The results revealed the employees’ green involvement significantly influences their green service innovation intention, which subsequently influences their green service innovation behavior. Furthermore, information technology (IT) adoption was found to fortify the linkage of employee green involvement with green service innovation intention.

The results suggest to the restaurant industry that awareness of green service innovation and IT adoption practices can help restaurants to develop effective sustainability work practices and meet societal expectations.

This study extends the restaurant management literature by linking the green involvement of restaurant employees to green service innovation intention as well as identifying the moderating role of IT adoption underlying this link.

This study aims to examine the key antecedents influencing the private firm’s intention to adopt big data analytics (BDA) in developing economies. To do so, the study follows the sequential explanatory approach.

To test the hypothesized model that draws on the technology–organization–environment (TOE) framework paired with the diffusion of innovation (DOI) theory, a purposive sampling technique was applied to gather data from 156 IT and management domain experts from the private firms that intend to adopt BDA and operate in Pakistan’s service industry, including telecommunication, information technology, agriculture, and e-commerce. The data were analysed using the partial least squares structural equations modelling (PLS-SEM) technique and complemented with qualitative analysis of 10 semi-structured interviews in NVIVO 12 based on grounded theory.

The empirical findings revealed that the two constructs – perceived benefits and top management support – are the powerful drivers of a firm’s intention to adopt BDA in the private sector, whereas IT infrastructure, data quality, technological complexity and financial readiness, along with the moderators, BDA adoption of competitors and government policy and regulation, do not significantly influence the intention. In addition, the qualitative analysis validates and further complements the SEM findings.

Unlike the previous studies on technology adoption, this study proposed a unique research model with contextualized indicators to measure the constructs relevant to private firms, based on the TOE framework and DOI theory, to investigate the causal relationship between drivers and intention. Furthermore, the findings of PLS-SEM were complemented by qualitative analysis to validate the causation. The findings of this study have both theoretical and practical implications.

This study aims to examine the mechanisms underlying social media commerce by investigating the interplay between platforms, people and information. Drawing upon trust transfer theory, the research model proposes that the platform’s information provision enhances the credibility of the information source, leading to increased information usefulness, adoption and sharing, ultimately influencing purchase intention.

The research design used in this study was a quantitative approach using a cross-sectional survey method. The study developed a research model based on trust transfer theory and hypothesized relationships between the platform’s information provision, information source credibility, information-related responses and purchase intention. Structural equation modeling was used to analyze the collected data and test the research hypotheses.

The findings supported most of the hypotheses and provided valuable insights into the role of information credibility in shaping consumers’ purchase intentions. Specifically, the study revealed that the platform’s information provision enhances the credibility of the information source, leading to increased information usefulness, adoption and sharing. Furthermore, information usefulness and adoption mediate the relationship between information source credibility and purchase intention.

The limitations of this research include the use of convenience sampling, which may not represent the broader population, and the cross-sectional design, which does not provide an in-depth understanding of the adoption process. The reliance on self-reported data and the limited scope of investigation with only six constructs are additional limitations. Future studies should consider national random sampling, longitudinal designs, multiple data sources and explore negative effects and other potential mediating variables. Despite these limitations, this research contributes to the understanding of social media commerce mechanisms and provides valuable insights for practitioners in the field.

The findings of this study provide valuable insights for platform providers and marketers in the social media commerce environment. First, the study emphasizes the importance of effective messaging in improving information credibility. Platform providers should focus on delivering accurate and trustworthy information to enhance consumers’ perceptions of product quality and increase purchase intentions. Second, marketers can leverage the information-related factors identified in this study, such as information usefulness and adoption, to optimize their marketing efforts. By understanding how consumers perceive and interact with information on social media platforms, marketers can tailor their strategies to effectively engage and influence potential customers. Overall, these practical implications can enhance success in the competitive social media commerce landscape.

The social implications of this study are significant for social media commerce practitioners. The findings highlight the importance of effective messaging and information provision on social media platforms in improving information credibility, thereby enhancing purchase intention. By understanding the mechanisms that drive consumer behavior in the context of social media commerce, platform providers and marketers can optimize their marketing efforts. This includes focusing on delivering trustworthy and useful information, fostering information adoption and sharing among users and ultimately increasing the likelihood of successful transactions. These insights provide valuable guidance for practitioners to navigate the competitive landscape of social media commerce and enhance their chances of success.

The originality of this research lies in its application of trust transfer theory to investigate the mechanisms driving social media commerce. By examining the interplay between platform, people and information, the study specifically focuses on the role of the platform’s information provision in enhancing information credibility and its impact on information-related responses and purchase intentions. This study extends the understanding of the trust transfer mechanism between customers and sellers/brands in customer-to-customer social commerce by emphasizing the importance of effective messaging and information credibility in shaping consumer behavior. The empirical findings contribute to the understanding of information trust transfer and provide a unique perspective on the underlying mechanisms that drive social media commerce.

The purpose of this study is twofold. The first objective is to identify the factors that affect Gen Z tourists' M-payment behaviour. Next, this study investigates the inter-relationship between Gen Z tourist’s perception of M-payment benefits, adoption behaviour, usage risk and future usage intention.

The sample comprised Malaysian Gen Z individuals (n = 326) who had experience using M-payment methods while travelling outbound. Given the complex nature of the model and the goal to predict and explain relationships within Gen Z's M-payment usage, partial-least square-structural equation modelling was used to assess the study framework and test the proposed relationships.

This study reveals significant influences on Gen Z tourists' behavioural intentions towards M-payment usage. Perceived benefits, performance expectancy, social influence and perceived trust positively impact behavioural intentions, while effort expectancy exhibits no significant effect. Furthermore, perceived trust is strongly influenced by perceived security, which also positively influences behavioural intentions. A mediated relationship is evident as trust mediating the effect of perceived security on behavioural intentions.

This study’s findings contribute to understanding the intricate relationships influencing Gen Z's M-payment behaviour and underscore trust's pivotal role in mediating the security–behavioural intention relationship.

This study is among the first to consider Mental Accounting Theory and the Unified Theory of Acceptance and Use of Technology as crucial underpinning theories in comprehending the intricate relationships that influence Gen Z travellers' perceptions and behaviours concerning M-payment systems.