Search results

This study aims to investigate the influence of environmental factors on individual personality traits associated with mobile paymens (MP) adoption using the technological personal environment (TPE) theory as a framework for the proposed theoretical model.

A total of 736 feedback from respondents was used to validate the proposed model using structural equation modeling. The model comprises Trust and Self-efficacy to explain MP adoption from a personal trait perspective. Meanwhile, environmental aspects are represented by social influence, vendor regulations and network externalities.

The result indicates that self-efficacy has the most significant direct effect on user intention to use MP, followed in decreasing order of significance by social influence, trust, vendor regulations and network externalities. Furthermore, social influence is the most contributing aspect from the environmental area that influences user intention directly and indirectly through trust and self-efficacy as mediators. Meanwhile, the moderating effect analysis also found that gender moderates the effect of user self-efficacy on MP adoption.

This study fills the gap by comparing trust and self-efficacy and exploring how those factors are developed and affected by the environmental aspect of MP usage. It was discovered that self-efficacy was the most influential construct influencing the adoption of MP. Social influence was identified as the primary environmental factor that directly impacts user intention regarding MP usage. Furthermore, gender was shown as a moderator, as males place a higher value on self-efficacy as a factor affecting their intention to embrace MP in comparison to females.

This study aims to construct an appropriate framework by incorporating essential components from the most renowned theories to investigate the variables that impact behavioural intentions towards embracing cashless transactions (CLT).

A survey was conducted to ascertain the users’ intention to adopt CLT in Chennai, Tamil Nadu, India. Further, this study used a “partial least squares-based structural equation modelling” technique to analyse the relationships between latent factors.

The results of the proposed model revealed that 11 independent variables together explain the intention to use CLT with a 60.5% explanatory power. Further, perceived usefulness is the most influential factor in predicting users’ willingness to adopt CLT, followed by social influence, perceived costs, attitude, trust and device barriers. Finally, the findings of moderator effects indicate that income and experience interact positively and strongly with behavioural intention to adopt CLT. It indicates that high-income, experienced users are more likely to convert their intentions into actions.

This study integrated critical elements from the major theories, such as Theory of Reasoned Action, Technology Acceptance Model, Decomposed Theory of Planned Behaviour, the unified theory of acceptance and use of technology (UTAUT) model and UTAUT2, to investigate the adoption of CLT. As a result, 11 crucial factors were identified from the existing literature that impacts CLT adoption without overlapping. Consequently, the model presented in this study provides a more profound understanding than previous research regarding why individuals adopt CLT systems. Accordingly, these results could aid policymakers in addressing people’s concerns and facilitating a seamless transition to a cashless society.

This research was motivated by the recognition that the use of mobile-based agricultural extension services (AES) applications has become increasingly popular among the bottom of the pyramid segment in recent years. However, users’ adoption is determined not only by their perception of the technology but also by its perceived wealth. In other words, even though a technology may be perceived as advanced, if it does not fit users’ wealth perception benefits, they may not adopt it. Using an extended unified theory of acceptance and use of technology (UTAUT) perspective, this study aims to explore potential predictors of behavioral intention toward AES such as effort expectancy, performance expectancy, customer wealth (CW), social influence and perceived characteristics of innovation.

Potential causal connections between key UTAUT factors and users’ intentions to use the services are hypothesized. An integrated theoretical model was developed and tested against the empirical data collected from 336 AES users. A measurement model and structural equation model were tested using AMOS 22.0 and confirmed all 14 hypothesized relationships.

The results were consistent with the recent literature on mobile technology acceptance, confirming an unmoderated relationship between CW and the adoption of mobile-based AES. This research proposes a mobile AES user adoption model by integrating CW with the unified theory of acceptance and usage of technology (UTAUT).

This study establishes CW as an outcome of various relationships.

The exponential growth of the construction sector exerts considerable pressure on the environment, and the circular economy (CE) concept has recently gained traction as a means of alleviating such environmental issues. In order to propose solutions to the phenomenon of contractors being hesitant to participate in CE implementation in developing countries, this paper aims to comprehensively explore the enabling factors that motivate contractors to implement CE.

This study is based on the push-pull-mooring (PPM) theory and extends it by introducing information provision (IP) as a trigger on contractors’ intrinsic subjective initiative states on CE implementation. The study considers what and how positive pull, negative push and neutral mooring factors influence the contractors’ CE transition. The framework was validated by questionnaires collected from contractors in China, and the data were analyzed using the structural equation modeling method.

The findings indicate that all factors from the PPM framework exert a positive influence on CE intention, with push factors demonstrating a greater average impact. Furthermore, this study confirms the influence of the IP on contractors’ CE intentions by influencing their intrinsic status. The impact of the IP is most pronounced in terms of contractors’ perceived usefulness and environmental concerns.

This study contributes to the existing body of knowledge in the CE transition studies by extending the PPM theory into the construction industry through the lenses of contractors in developing countries. The results highlight the trigger impacts of the IP on contractors’ psychological status regarding CE transition. Furthermore, it offers insights into government management in the CE transition by providing the government with novel approaches to facilitate the CE transition in the construction sector.

Due to increasing interest in sustainability, consumers prioritize environmentally friendly consumption across various service sectors. This study aims to examine how environment-related attributes of food delivery services affect customer behavior. Specifically, the authors use the stimulus-organism-response framework to explore how environmentally friendly food packages correlate with customers’ environmental support and patronage behavior.

The authors collected data from US food delivery service customers. To test the hypotheses, the authors used partial least squares structural equation modeling.

The authors find that customers’ perceptions of the environmental friendliness of food packages influence their satisfaction and trust, which in turn affect their environmental support and patronage behaviors. Also, customers’ trust and satisfaction mediate the relationship between their food consumption experience and its outcomes. The authors further explore demographic factors that influence the proposed relationships.

Due to the popularity of food delivery services, this study has theoretical and practical implications for restaurant service providers and highlights the potential of environmentally friendly packaging to increase both environmental support and loyal behavior.

Mobile payment (or m-payment), a relatively new digital banking system targeting Pakistani customers, is rapidly expanding. This study aims to explore the elements that impact customer behaviour and encourage the adoption of m-payment in Pakistan.

This study used a quantitative research design, surveying 315 m-payment users residing in three Pakistani cities. A conceptual framework was developed by extending the meta-unified theory of acceptance and use technology (meta-UTAUT) model to incorporate institutional privacy concerns (IPC) and institutional source reliability (ISR). Data analysis was conducted using partial least squares structural equation modelling via Smart PLS 4.0 software.

This study’s results indicate that behavioural intention (BI) is the primary driver ofm-payment use behaviour. The findings also reveal that attitude (AT), performance expectancy (PE), facilitating conditions (FC), social influence (SI), effort expectancy (EE), IPC and ISR significantly influence BI. Notably, PE and FC are positively associated with AT, while EE and SI have no significant impact on AT.

This study has two key limitations. First, its focus on only Pakistani m-payment users limits the broader applicability of the results. Second, the cross-sectional design overlooks potential longitudinal changes in users’ attitude. Future research should aim to recruit diverse country samples and conduct comparative studies, thereby enhancing the understanding of m-payment adoption.

This study provides insights for service providers and marketers, identifying key factors that influence m-payment adoption. Convenience emerges as a critical consideration, suggesting it may drive customer behaviour.

This research significantly advances the field of m-payment studies by investigating the key factors influencing Pakistani consumers’ adoption of m-payment, extending the meta-UTAUT model to include IPC and ISR. By applying this extended framework to the context of Pakistani consumers’ acceptance and use of m-payment, this study provides new insights into the complex factors driving m-payment adoption in developing Asian countries like Pakistan, addressing a significant research gap and paving the way for future studies.

This study proposes a theoretical model to explain user intention to continue engaging with Social Commerce (SC) from a habit perspective. The research uses social impact theory, user personal traits, and SC quality to explain how user habits are formed in SC, leading to continued usage.

The study collected data from 868 Indonesian respondents using a cross-sectional field design. SEM analysis confirmed the proposed theoretical model, calculating direct, indirect, and moderating effects.

The results showed that the social aspect is the dominant construct influencing users’ habit of using SC. Further, the outcome indicates that habit significantly predicts Continuity usage. Profoundly, subjective norms are the most significant predictors of habit, followed by self-efficacy, content quality, and herd behavior. Meanwhile, Trust and Social Support only indirectly affect Habit through self-efficacy and content quality, respectively, as mediators. Additionally, the moderating effect analysis revealed that age and gender play a role in habit formation.

This study specifically explores the factors affecting the development of habits in SC usage, leading to repeated behaviors. This area has not been thoroughly examined in previous research. Therefore, this study seeks to address this gap by investigating how habits are formed through social interactions on SC platforms. Understanding habit formation provides an alternative way of comprehending the continued use of SC, as it is considered a significant factor that leads to continued intention.

Our research investigated how the perceived effectiveness of privacy, perceived privacy risk, and perceived security influenced consumers' behavioral intention to use mobile payment applications during the COVID-19 pandemic.

We applied a quantitative method using a cross-sectional online survey conducted over three years. We collected a sample of 1,471 survey responses focused on ages 18–39. Using descriptive statistics, confirmatory factor analysis, and structural equation modeling, we tested our hypotheses with SPSS 27 and AMOS 27.

Results of the study indicate that the perceived effectiveness of privacy positively influences perceived privacy risk, perceived security, and behavioral intention. Moreover, perceived privacy risk has a positive effect on perceived security. We found no significant relationship between perceived privacy risk and behavioral intention, although perceived security has a positive effect on behavioral intention. Further mediation analyses showed that perceived privacy risk and perceived security mediate the relationship between the perceived effectiveness of privacy and behavioral intention.

This research sheds new light on the role of perceived privacy effectiveness in mobile payment adoption in Hungary, particularly during the COVID-19 pandemic. Our research also explains why and how perceived privacy effectiveness influences consumers' perceived privacy risk, perceived security, and behavioral intention.

This study aims to explore both the drivers (performance expectancy and perceived usefulness of ChatGPT) and the barrier (effort expectancy) that Indonesian youth encounter when adopting generative AI technology, such as ChatGPT, as they pursue digital entrepreneurship.

This study utilizes Hayes' Process Model to evaluate the proposed hypotheses through survey data collected from 518 Indonesian youth.

This study's findings highlight a paradoxical relationship that emerges when effort expectancy intersects with performance expectancy and perceived usefulness of ChatGPT. Specifically, we discovered that when young individuals perceive the adoption of generative AI technology as requiring significant effort, their motivation to engage in digital entrepreneurship is significantly enhanced if they also view the tool as highly useful and beneficial to their future business endeavors.

The findings provide valuable insights for educators and policymakers focused on advancing digital entrepreneurship in developing nations through the integration of generative AI technology.

Our study enriches an underexplored niche within the field of entrepreneurship by examining the intersection of Indonesian youth, generative AI technology and digital entrepreneurship. By incorporating the Expectancy-Value Theory, it brings a fresh perspective to the study of paradoxical relationships in contemporary research in this domain.

This study aims to focus on exploring the role of fear of missing out (FOMO) in the technology adoption context, whereby the bottom-of-the-pyramid (BOP) segment was studied to explore the factors responsible for the development of behavioural intentions (BI) to use unified payments interface (UPI), a disruptive technological phenomenon in the mobile payment systems field.

A mixed-method research approach involving both qualitative and quantitative methods was used. Initially, qualitative data obtained through interviews with UPI’s BOP users were subjected to thematic analysis, leading to the identification of eight factors and the construction of a conceptual model. Subsequently, 354 responses were gathered, and empirical analysis was conducted using structural equation modelling in AMOS 23.0.

Eight factors, including personal and social benefits, perceived security risk, socio-cultural influences, governmental influence, usability, psychological inertia, perceived value (PV) and FOMO, were discovered. The quantitative examination confirmed the validity of the conceptual model in the BOP context, explaining 51% of the variance in BI. FOMO and PV emerged as robust indicators of UPI adoption, with PV significantly regulating the impact of FOMO.

To the best of the author’s knowledge, this study is one of the first to explore what drives BOP users in an emerging economy to adopt UPI. The conceptual model it presents contributes to the advancement of technology adoption literature by incorporating FOMO alongside newly identified BOP-specific factors.