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Driven by advanced voice interaction technology, the voice-user interface (VUI) has gained popularity in recent years. VUI has been integrated into various devices in the context of the smart home system. In comparison with traditional interaction methods, VUI provides multiple benefits. VUI allows for hands-free and eyes-free interaction. It also enables users to perform multiple tasks while interacting. Moreover, as VUI is highly similar to a natural conversation in daily lives, it is intuitive to learn. The advantages provided by VUI are particularly beneficial to older adults, who suffer from decreases in physical and cognitive abilities, which hinder their interaction with electronic devices through traditional methods. However, the factors that influence older adults’ adoption of VUI remain unknown. This study addresses this research gap by proposing a conceptual model. On the basis of the technology adoption model (TAM) and the senior technology adoption model (STAM), this study considers the characteristic of VUI and the characteristic of older adults through incorporating the construct of trust and aging-related characteristics (i.e., perceived physical conditions, mobile self-efficacy, technology anxiety, self-actualization). A survey was designed and conducted. A total of 420 Chinese older adults participated in this survey, and they were current or potential users of VUI. Through structural equation modeling, data were analyzed. Results showed a good fit with the proposed conceptual model. Path analysis revealed that three factors determine Chinese older adults’ adoption of VUI: perceived usefulness, perceived ease of use, and trust. Aging-related characteristics also influence older adults’ adoption of VUI, but they are mediated by perceived usefulness, perceived ease of use, and trust. Specifically, mobile self-efficacy is demonstrated to positively influence trust and perceived ease of use but negatively influence perceived usefulness. Self-actualization exhibits positive influences on perceived usefulness and perceived ease of use. Technology anxiety only exerts influence on perceived ease of use in a marginal way. No significant influences of perceived physical conditions were found. This study extends the TAM and STAM by incorporating additional variables to explain Chinese older adults’ adoption of VUI. These results also provide valuable implications for developing suitable VUI for older adults as well as planning actionable communication strategies for promoting VUI among Chinese older adults.

Under the uncertainty of conservation tillage on output, technology demonstration, as an information disclosure mechanism, is very worthy of attention for its effects on rural households' conservation tillage adoption. This study constructs a three-stage technology adoption model to discuss the theoretical relationship between technology demonstration and rural households' conservation tillage adoption decision, and then empirical analyzed it using a sampling rural household data from six provinces in the main grain-producing areas of China. The results show that: First, the cognition of conservation tillage is the pre-determined stage for the adoption and its intensity. Second, technology demonstration has significant positive effect on rural households' cognition of conservation tillage, but it strongly negative related to the adoption and adoption intensity. Third, extending the technology demonstration time cannot change the rural households' adoption decision. Fourth, the technological demonstration has similar effects on the conservation tillage adoption of small-scale and large-scale farmers. Fifth, increasing land size helps rural households to adopt conservation tillage, while land fragmentation hinders their adoption.

Blockchain technologies have received considerable attention from academia and industry due to their distinctive characteristics, such as data integrity, security, decentralization, and reliability. However, their adoption rate is still scarce, which is one of the primary reasons behind conducting studies related to users’ satisfaction and adoption. Determining what impacts the use and adoption of Blockchain technologies can efficiently address their adoption challenges. Hence, this systematic review aimed to review studies published on Blockchain technologies to offer a thorough understanding of what impacts their adoption and discuss the main challenges and opportunities across various sectors. From 902 studies collected, 30 empirical studies met the eligibility criteria and were thoroughly analyzed. The results confirmed that the technology acceptance model (TAM) and technology–organization–environment (TOE) were the most common models for studying Blockchain adoption. Apart from the core variables of these two models, the results indicated that trust, perceived cost, social influence, and facilitating conditions were the significant determinants influencing several Blockchain applications. The results also revealed that supply chain management is the main domain in which Blockchain applications were adopted. Further, the results indicated inadequate exposure to studying the actual use of Blockchain technologies and their continued use. It is also essential to report that existing studies have examined the adoption of Blockchain technologies from the lens of the organizational level, with little attention paid to the individual level. This review is believed to improve our understanding by revealing the full potential of Blockchain adoption and opening the door for further research opportunities.

Intelligent information technology (IIT) based on AI and intelligent network communication technology is rapidly changing the social structure and the personal lives. However, IIT acceptancefrom various perspectives still requires extensive research. The research question in this paper examines how five factors—psychological, technological, resource, risk perception, and value factors—influence IIT acceptance. Based on an analysis of survey data, it was first found that the acceptance rate of IIT itself was generally very high. Second, in terms of IIT acceptance, among twenty-five predictors, voluntariness (+), positive image of technology (+), performance expectancy (+), relative advantage (+), radical innovation (+), and experience of use (+) were found to have significant effects on the IIT acceptance. Third, in addition to technological factors, psychological factors and risk perception factors also played an important role in individuals’ decisions regarding IIT acceptance.

Blockchain overcomes numerous complicated problems related to confidentiality, integrity, availability of fast and secure distributed systems. Using data from a cross-sectoral survey of 449 industries, we investigate factors that hinder or facilitate blockchain adoption in supply chains. To capture the most vital aspects of blockchain adoption in supply chains, our conceptual model integrates the unified theory of acceptance and use of technology (UTAUT) model with the task-technology fit (TTF) and information system success (ISS) models, with trust-based information technology innovation adoption constructs. Using structural equation modelling, we find that the ISS, TTF, and UTAUT models positively influence the key factors affecting supply chain employees’ willingness to adopt blockchain. Our results show that the UTAUT’s social influence factor has no significant effect on the intention to adopt blockchain, while inter-organisational trust has a significant effect on the relationship between the UTAUT dimension and intention to adopt blockchain.

This study explores the adoption of blockchain technology within the Ethiopian National Quality Infrastructure (NQI). Data from 178 professionals representing various organizations and roles were collected to investigate key adoption factors. By integrating the Technology Acceptance Model (TAM) and the Technology-Organization-Environment (TOE) framework, external factors (Technology Compatibility, Relative Advantage, Government Support, and Policy) and internal factors (perceived usefulness, perceived ease of use, and intention to use) were examined. A dual-stage analytical approach involving partial least square-based structural equation model (PLS-SEM) and artificial neural network (ANN) analyses was employed. The findings emphasize the significance of technological compatibility, perceived usefulness, and top management support as determinants of blockchain adoption in the NQI. Particularly, the compatibility of the existing system emerges as the most influential factor in adopting blockchain technology within the Ethiopian NQI. This study enhances the understanding of blockchain adoption within the NQI context, providing valuable insights for successful implementation. It contributes to the existing knowledge in this area and offers practical implications for quality infrastructure management.

In the light of several national advanced manufacturing strategies such as Industry 4.0 in Germany or the Made in China 2025 initiative in China, this article examines the challenges of Industry 4.0 adoption of Japanese small and medium-sized manufacturing firms. A technology adoption model for Industry 4.0 is developed and empirically tested with 38 manufacturing companies. The results yield that the market uncertainty of the firm’s business is a significant driver for adoption in the short, medium, and long-term. Relative competitive advantage matters in the short term and top management support in the long-term. No support has been identified concerning advanced manufacturing complexity and market transparency of Industry 4.0 solutions.

Purpose This paper aims to investigate and comprehend the nature of the relationship between e-government development and the digital economy. Design/methodology/approach A multidimensional research paradigm is developed on the basis of the technology adoption model and Fountain’s technology enactment theory. The model is empirically examined using a regional study of 20 Asian countries. Findings A positive two-way relationship between e-government development and the digital economy has been indicated by the findings. Moreover, along with social, economic, political, technological and demographic factors, certain national cultural characteristics have significant effects on the digital economy and e-government development. Research limitations/implications One of the key limitations of the study is that it is based on publicly available secondary data. Therefore, some degree of caution should be kept in mind when making generalisations about the findings of this study. Originality/value The contribution of this study is that it provides a more accurate and comprehensive understanding of the dynamic association between e-government development and the digital economy by providing aid to policymakers in understanding the nature of dynamic relationships between the digital economy, government organisations and citizens’ adoption of technologies.

While wearable healthcare technologies (WHTs) are rapidly gaining acceptance, it is crucial to analyze the reasons contributing to the continued use of these technologies since many customers tend to abandon their devices after a short usage period. This study proposes and empirically tests a framework that augments the technology acceptance model (TAM) with extra explanatory power gained by integrating the investment model (IM) and the task-technology fit (TTF) model. The framework suggests explaining users’ intention to keep using WHTs by four key constructs extracted from the three models, namely ease of use, usefulness, commitment level, and task-technology fit. Structural equation modeling was used to analyze 431 valid responses. The findings showed that usefulness, commitment level, and task-technology fit had a significant direct effect on users’ intention to keep using their current WHTs, while ease of use had an insignificant effect. Furthermore, the findings showed that integrating TAM, IM, and TTF provided more insights into the contributing factors that drive the intention to keep using the current WHTs. Additionally, the findings emphasize the impact of the wearables’ technological features on users’ intentions to continue using the devices. The integration of the three models provided complementary explanatory power and illustrated how better insights, regarding users’ technology acceptance, could be gained by integrating three well-established theories, namely TAM, IM, and TTF.

Artificial intelligence (AI) has recently been introduced as a new way of analyzing and predicting sport consumer behavior. The goal of this study was to investigate the relationships among the perceived usefulness, perceived ease of use, the importance of exercise, attitudes towards use, and the behavioral intention to use AI services based on the technology adoption model. The authors recruited 408 participants who participated in an experiment designed to provide a deeper understanding of AI fitness services. After screening, the collected data were screened through assumption tests, and we conducted a confirmatory factor analysis and structural equation modeling to analyze research hypotheses. The results indicated that three types of consumer evaluations (i.e., perceived usefulness, perceived ease of use, and importance of exercise) positively influence their attitudes toward AI fitness services. In addition, the positive attitudes regarding AI services positively influenced the intention to use AI services. The results of this research contribute to our knowledge of the consumers’ attitudes and behaviors toward AI services in the sport industry based on the technology acceptance model. Furthermore, this study provided the empirical evidence critically needed to increase our understanding of AI in the sport industry and offered new insights into how sport facility managers can predict their consumers’ intention to use AI services.