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Wearable health devices (WHDs) have demonstrated significant potential in assisting elderly adults with proactive health management by utilizing sensors to record and monitor various aspects of their health, including physical activity, heart rate, etc. However, limited research has systematically explored older adults’ continued usage intention toward WHD. By utilizing the extended unified theory of acceptance and use of technology (UTAUT2), this paper aims to probe the precursors of elderly adults’ continuance intention to use WHD from an enabler–inhibitor perspective.

The research model was developed based on UTAUT2 and examined utilizing the partial least squares technique (PLS). The research data were collected through in-person meetings with older people (n = 272) in four cities in China.

Results reveal that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic values and perceived complexity are the positive predictors of elderly adults’ continuance intention to use WHDs. Technology-related anxiety and usage cost negatively influence the formation of older people’s continuance intention.

This work is an original empirical investigation that draws on several theories as guiding frameworks. It adds to the existing literature on the usage of wearable technologies and offers insights into how the elderly’s intentions to continue using WHDs can be developed. This study broadens the scope of the UTAUT2 application and presents an alternative theoretical framework that can be utilized in future research on the usage behavior of wearable devices by individuals.

In keeping with global developments rendering online shopping as an emerging trend among consumers, the present study extends the unified theory of use and acceptance of technology (UTAUT2) comprising the digital payment mode (DPM) as a new driver of online shopping and with the mediation of attitudes toward technology (ATTs) to gauge a better and deeper understanding of behavioral intention (BI).

This study used a survey instrument with snowball sampling from 600 consumers in northern India. Partial least squares structural equation modeling was used to find the association between drivers using UTUAT2, along with DPM and ATTs. The data were divided into a test group (20%) and validated through a training group (80%).

DPM was shown to be directly associated with BI. The mediation of ATTs was also validated through the model. The predictability of the model was 67.5% for the test group (20%) and 69.6% for the training group (80%). The results also indicated that facilitating conditions is a critical driver of BI.

This study enhances the understanding of the roles that DPM and ATTs play in BI during online shopping, suggesting that Indian managers need to adopt DPM as a support service to make online shopping a worthwhile experience.

E-procurement has the advantage of improving the overall performance of construction project delivery. The purose of this study is to uncover the factors influencing e-procurement acceptance in the public sector of Ghana’s construction industry (GCI). Using an extended unified theory of acceptance and use of technology (UTAUT 2), variables that promote the acceptance of e-procurement in GCI were explored.

Data was collected using a mixed method strategy. In the first stage, a semi-structured interview was used to collect, assess and optimize the UTAUT2 model. Thematic analysis was used on the qualitative data, leading to modification of the proposed UTAUT2 model. The study subsequently used a questionnaire survey using the extended UTAUT2 model. Survey data was analyzed using structural equation modelling (SEM), leading to the identification and validation of factors that facilitate e-procurement acceptance in Ghanaian construction as well as the impact of these factors.

The findings of the study reveal that five independent constructs of the proposed UTAUT2 model significantly affects the behavioural intention of practitioners to accept and use e-procurement in the construction industry in Ghana.

The study will be of utility to government agencies, contracting organizations and other construction stakeholders in developing policy and programmes to support e-procurement acceptance within the sector.

This is a new extended UTAUT2 model that is applicable to technology acceptance within the public sector in sub-Saharan Africa.

The study aimed to investigate the relationship between the intention to avoid food waste (IAFW) and the use of food-sharing technologies, such as internet platforms and mobile applications. The study utilized a model based on the theory of planned behavior (TPB) as an extension of the unified theory of acceptance and use of technology (UTAUT2).

An online platform tool (Prolific), and online self-report questionnaires were used to gather empirical data on 309 individuals. These data were then analyzed using two-step structural equation modeling.

The model explained 76% of the variance in user adoption of food-sharing mobile applications and internet platforms, supporting seven out of the nine tested hypotheses. Effort expectancy, social influence and IAFW were found to be the significant determinants of the behavioural intention to use food-sharing mobile applications and internet platforms (BITA). IAFW partially mediated the relationship between perceived behavior control and BITA. Age played a moderator role between the adoption of food-sharing mobile applications and internet platforms. However, IAFW did not play a mediating role between environmental concerns and BITA. The facilitating condition construct had an insignificant impact on BITA.

The current study was affected by some limitations. First, the data may not be considered as statistically representative because they were gathered online. However, the varied sociodemographic backgrounds of the respondents would boost the reliability of the findings. However, it would be prudent to use caution when extrapolating these findings to other contexts and cultures. Second, environmental concerns and perceived behavior control related to the avoidance of food waste behavior, as well as other factors that affect technology acceptance, may alter with time. Data from cross-sections may cause difficulties in following such changes. Thus, we recommend that longitudinal research studies aimed at building on our findings should be conducted. A qualitative study may help gain deeper insights into the relationship between IAFW related behavior and the adoption of various technologies to share leftover food, thereby revealing further details regarding different perspectives held by various respondents.

The positive relationship between environmental concerns and IAFW underlines the significance of investing in this area to raise social awareness and public concern for environmental safety. Additional initiatives aimed at increasing public concern regarding environmental issues may increase the overall IAFW. Instead of concentrating on a single source pertaining to the avoidance of food waste, the government and policy regulations should focus on regulating and eliminating waste from all sources that generate waste. The adoption of technology to share leftover meals may be influenced by social factors. Increased advertising for food-sharing mobile apps and online platforms may persuade more users to join. Additionally, building additional platforms and mobile apps in these fields with friendlier interactions may improve the cyber environment, making it easier for people to use them. By providing information, tools and assistance to promote the reduction of food wastage, policymakers may create interventions that enhance public perception and behavior toward the reduction of food waste. In conclusion, the findings of our study indicated that the social impact and ease of use are important factors in determining the adoption of food-sharing technology. Cooperation with social influencers, policymakers and developers may lead to the development of user-friendly technology that may improve accessibility to food-sharing technology.

In order to encourage the adoption of food-sharing technology among various age groups, policymakers may create initiatives that take the specific requirements and traits of each group into consideration. Policymakers and governments may also create legislation and regulations that are tailored to guarantee food safety and health security for users of food-sharing technology, such as instructions for handling and storing food as well as safeguards against food fraud and contamination.

This study addressed practical issues related to managing and reducing household food wastage through social sharing via mobile applications and internet platforms. The proposed model, which integrated TPB with UTAUT2 in the context of food wastage and technology acceptance, contributes to the current body of knowledge.

Perceived risk and benefits have been proposed as crucial elements in consumers’ technology adoption intention. Therefore, this study aims to use the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, with perceived risks and benefits, to explore how they affect consumers’ Buy-Now-Pay-Later (BNPL) behavioural intention.

An online survey was conducted among 537 users of BNPL. Partial least square structural equation modelling analysis was performed to examine the hypothesized relationships.

The study found that perceived benefits, performance expectancy, effort expectancy, habit and social influence increase consumers’ behavioural intention towards BNPL. In contrast, perceived risk reduces the consumer’s intention to use. Additionally, the study revealed that consumers’ intention towards BNPL services positively affects their usage.

The lack of information makes consumers hesitant to use BNPL. Therefore, marketers should optimize facilitating conditions, such as user-friendly interfaces, accessible resources and efficient customer support, which should be the business strategy of BNPL service providers to ensure a seamless user experience.

The research empirically investigates the effect of perceived benefits on consumer behavioural intention. This contribution is crucial because while there was speculation about benefits as a driving force to consumers’ adoption intention, there was a lack of sufficient empirical evidence to support it.

The proliferation of smartwatches in the digital age has radically transformed health and fitness management, offering users a multitude of functionalities that extend beyond mere physical activity tracking. While these modern wearables have empowered users with real-time data and personalized health insights, their environmental implications remain relatively unexplored despite a growing emphasis on sustainability. To bridge this gap, this study extends the UTAUT2 model with smartwatch features (mobility and availability) and perceived security to understand the drivers of smartwatch usage and its consequent impact on environmental sustainability.

The proposed theoretical model is evaluated based on data collected from 303 smartwatch users using a hybrid structural equation modeling–artificial neural network (SEM-ANN) approach.

The PLS-SEM results supported smartwatch features’ effect on performance and effort expectancy. The results also supported the role of performance expectancy, social influence, price value, habit and perceived security in smartwatch usage. The use of smartwatches was found to influence environmental sustainability significantly. However, the results did not support the association between effort expectancy, facilitating conditions and hedonic motivation with smartwatch use. The ANN results further complement these outcomes by showing that habit with a normalized importance of 100% is the most significant factor influencing smartwatch use.

Theoretically, this research broadens the UTAUT2 by introducing smartwatch features as external variables and environmental sustainability as a new outcome of technology use. On a practical level, the study offers insights for various stakeholders interested in smartwatch use and their environmental implications.

The global automobile industry is striving towards a sustainable future. Emerging countries including India are gearing up for the revolution. Considering the key role of customer acceptance in the success of any technological shift, the study endeavors to ascertain the catalysts accelerating the adoption of Electric Two-Wheelers (E2W) in India by leveraging an extended Unified Theory of Acceptance and Use of Technology-2 model. The same would assist Electric Vehicle (EV) stakeholders in directing their efforts toward pivotal aspects having the potential to significantly bolster E2W penetration.

Data was collected using convenience sampling technique from 1,254 electric two-wheeler owners across four Indian states and analyzed using Structural Equation Modelling.

Performance Expectancy, Price Value and Hedonic Motivation have a significant influence on purchase intention leading to actual buying behavior. Effort Expectancy, Social Influence, habit value and facilitating conditions were insignificant. Pro-Environmental Approach and Government Support significantly impact adoption intention and behavior respectively in addition to model predictors thus supporting the study’s novelty. Purchase intention proved to influence Actual Buying Behavior. Synergized efforts of EV stakeholders towards performance innovation, cost-effectiveness, improved infrastructure and information diffusion on sustainability and user-friendliness could aid in achieving transition to green mobility.

The study predominantly intends to address the intention–behavior gap related to electric two-wheelers in India. Also, two additional constructs, government support and pro-environmental approach, were incorporated resulting in a novel research framework that aims to test their nuanced ability to impact the model predictors.

This study embarks on a comprehensive investigation into the intricate relationship between consumer trust in e-commerce platforms and the adoption of Green Supply Chain Management (GSCM). It delves into a multifaceted analysis of how these dynamics influence the landscape of online shopping, with a specific focus on four critical dimensions: the efficiency of online purchasing processes, the fulfillment of product delivery commitments, the convenience associated with e-platform utilization, and the safeguarding of consumers' personal information.

This research employs sophisticated Structural Equation Modeling (SEM) techniques, facilitated by SPSS and SmartPLS software, to meticulously analyze the amassed data and subject the formulated hypotheses to rigorous testing. The empirical foundation of this study draws from a sample of 377 randomly selected online shoppers, providing a robust basis for its insights.

At its core, this research is squarely focused on unraveling the dynamics of consumer trust within e-commerce platforms and highlighting the pivotal role played by GSCM in making online shopping more ecologically responsible and sustainable. Of paramount importance is the novel dimension introduced by this study the integration of trust in e-commerce platforms, GSCM practices, and the multifarious dimensions of online shopping all within a unified conceptual framework. Trust on e-commerce platforms leads to GSCM. GSCM determines online shopping satisfaction, i.e. efficiency, fulfillment, convenience, and privacy. Finally, GSCM mediates between trust on e-commerce platforms and online shopping satisfaction.

This holistic approach represents a ground-breaking contribution to the existing body of literature. It presents a fresh perspective on the intricate interactions that define the contemporary e-commerce landscape.

This initial research integrates trust in e-commerce platforms, GSCM, and online shopping in a single framework through UTAUT2.

User acceptance is a necessary precondition to implementing self-driving buses as a solution to public transport challenges. Focusing on potential users in a real-life setting, this paper aims to analyze the factors that affect their willingness to use public autonomous shuttles (PASs) as well as their word-of-mouth (WOM) intentions.

Grounded on Unified Theory of Acceptance and Use of Technology (UTAUT2), the study was carried out on a sample of 318 potential users in a real-life setting. The hypothesized relationships were tested using partial least squares structural equation modeling (PLS-SEM).

The study reveals that performance expectancy, facilitating conditions, hedonic motivation and trust are significant predictors of PAS usage intention, which is, in turn, related to WOM communication. Additionally, the factors that impact the intention to use a PAS are found to exert an indirect effect on WOM, mediated by usage intention.

This study includes practical insights for transport decision-makers on PAS service design, marketing campaigns and WOM monitoring.

While extant research focuses on passengers who have tried autonomous shuttles in experimental settings, this article adopts the perspective of potential users who have no previous experience with these vehicles and identifies the link between usage intention and WOM communication in a real-life traffic environment.

若要引入自動駕駛巴士來解決公共交通的問題和挑戰,一個必不可少的先決條件是得到用戶的認可。本研究透過重點分析活在真實生活環境中的潛在用戶,來探討影響他們使用公共自動交通工具的意願和口碑動機的各個因素。

本研究以延伸整合型科技接受模式為基礎,對一個涵蓋處身於真實生活環境中318名潛在用戶的樣本進行分析和探討。研究人員以偏最小平方法的結構方程模型 (PLS-SEM), 去測試各個被假設的關聯。

研究結果顯示,績效期望、有利條件、享樂動機和信任均明顯能夠預測人們使用公共自動交通工具的意願,而人們使用公共自動交通工具的意願又反過來與口碑溝通有所相關。另外,研究人員發現,影響人們使用公共自動交通工具意願的各個因素,對口碑會產生間接的影響,而使用意願是會起著調節作用的。

現存的學術研究均聚焦分析那些曾於實驗設置下坐過自動交通工具的人士,而本研究卻採用從未坐過自動交通工具人士的角度來進行分析與探討,並且找出了於實際的交通環境裡、使用意願與口碑溝通之間的關聯。

本研究提供的啟示,對有關公共自動交通工具服務設計、市場營銷活動和口碑監督工作的運輸決策者來說頗具實務意義。

Recently, autonomous vehicles (AV) acceptance has been studied intensively. This paper aims to map and analyze the bibliometric characteristics of AV acceptance literature. Furthermore, this research aims to identify research gaps and propose future research opportunities.

The bibliometric analysis was performed. Scopus database was used as the source of the literature. This study selected and analyzed 297 AV acceptance papers. The performance and science mapping analysis were performed.

The developed countries tended to dominate the topic. The publication outlet tended to be in transportation or technology journals. There were four research themes in existing literature. Technology acceptance model (TAM) and UTAUT2 tended to be used for explaining AV acceptance. AV acceptance studies tended to use two types of psychological concepts for understanding AV acceptance, namely risk related concepts and functional utilitarian benefit related concepts. In the context of research design, quantitative approach tended to be used. Self-driving feature was the most exploited feature of AV in the existing literature. Three research gaps were mapped and future research opportunities were proposed.

This paper provided a comprehensive information that allowed scientists to develop future research on AV acceptance.

There is lack of paper that discussed the bibliometric characteristics of AV acceptance literature. This paper fulfilled the gap.