Factors driving the adoption of smart home technology: An empirical assessment

Factors impacting the adoption of big data in healthcare: A systematic literature review

BACKGROUND

The term "big data" refers to the vast volume, variety, and velocity of data generated from various sources-e.g., sensors, social media, and online platforms. Big data adoption within healthcare poses an intriguing possibility for improving patients' health, increasing operational efficiency, and enabling data-driven decision-making. Despite considerable interest in the adoption of big data in healthcare, empirical research assessing the factors impacting the adoption process is lacking. Therefore, this review aimed to investigate the literature using a systematic approach to explore the factors that affect big data adoption in healthcare.

METHODS

A systematic literature review was conducted. The methodical and thorough process of discovering, assessing, and synthesizing relevant studies provided a full review of the available data. Several databases were used for the information search. Most of the articles retrieved from the search came from popular medical research databases, such as Scopus, Taylor & Francis, ScienceDirect, Emerald Insights, PubMed, Springer, IEEE, MDPI, Google Scholar, ProQuest Central, ProQuest Public Health Database, and MEDLINE.

RESULTS AND CONCLUSION

The results of the systematic literature review indicated that several theoretical frameworks (including the technology acceptance model; the technology, organization, and environment framework; the interactive communication technology adoption model; diffusion of innovation theory; dynamic capabilities theory; and the absorptive capability framework) can be used to analyze and understand technology acceptance in healthcare. It is vital to consider the safety of electronic health records during the use of big data. Furthermore, several elements were found to determine technological acceptance, including environmental, technological, organizational, political, and regulatory factors.

Smart home adoption factors: A systematic literature review and research agenda

Smart homes represent the complement of various automation technologies that together make up a network of devices facilitating the daily tasks of residents. These technologies are being studied for their application from different sectors, including the projection of their use to improve energy consumption planning and health care management. However, technology adoption depends on social awareness within the scope of cognitive advantages and innovations compared to perceived risk because although there are multiple benefits, potential users express fears related to the loss of autonomy and security. This study carries out a systematic literature review based on PRISMA in order to analyze research trends and literary evolution in the technological adoption of smart homes, considering the main theories and variables applied by the community. In proposing a research agenda in accordance with the identified gaps and the growing and emerging themes of the object of study, it is worth highlighting the growing interest in the subject, both for the present and its development in the future. Until now, adoption factors have been attributed more to the technological acceptance model and the diffusion of innovation theory, adopting components of the Theory of Planned Behavior; therefore, in several cases, the attributes of different theories are merged to adapt to the needs of each researcher, promoting the creation of empirical and extended models.

Analysis of Driving Factors in the Intention to Use the Virtual Nursing Home for the Elderly: A Modified UTAUT Model in the Chinese Context

As a unique form of mobile health service (m-Health) for elderly care in China, the virtual nursing home is considered a reliable alternative to the traditional model of home-based care, but services from virtual nursing homes are infrequently used by the elderly in practice. Thus, this study aims to measure the driving factors affecting the behavioral intention to use the virtual nursing home by designing a research framework that combined the unified theory of acceptance and use of technology (UTAUT) with the technology acceptance model (TAM). Furthermore, a new variable, conformist mentality, is proposed as a moderator. In order to validate the model, a well-structured questionnaire using mature scales was used, and the linear regression analysis method was conducted on 200 valid data samples collected during a field study in Harbin, China. The results show that performance expectancy, effort expectancy, and social influence significantly affect behavioral intention. However, the effect of facilitating conditions is not significant. Moreover, performance expectancy and effort expectancy have a positive effect on attitude toward use, and attitude toward use not only affects behavioral intention but also plays a mediating role in the effect of performance expectancy and effort expectancy on behavioral intention. This study also innovatively proposes and confirms conformist mentality as a moderator to strengthen the driving effect of social influence on behavioral intention. This is the first time that conformist mentality is introduced as a moderator in a study on the behavioral perception and acceptance of virtual nursing homes among Chinese older adults. Based on these findings, this study offers theoretical contributions and management implications that are conducive to the sustainable development of virtual nursing homes, thereby making extensive contributions to this field. Additionally, it also aids in the contextual expansion of the UTAUT model.

Factors that predict the acceptance and adoption of smart home technology by seniors in Australia: a structural equation model with longitudinal data

Smart Home Technology presents an exciting opportunity to support seniors living independently in their homes. Despite widespread interest in Smart Homes, seniors' readiness to adopt Smart Home Technology is low. To determine the factors underpinning Australian seniors' acceptance and adoption of Smart Home Technology using an extended UTAUT model that includes Trust, Resistance to Change and Technology Anxiety. A longitudinal study was conducted to validate the proposed model prior to and after the implementation of a pilot Smart Home Modification program for seniors. Structural Equation Modeling has been applied to test the proposed hypotheses using a sample of 60 seniors in regional Australia. Perceived Usefulness is an important predictor of Smart Home Technology adoption by seniors. Trust was found to indirectly predict adoption of Smart Home Technology via Perceived Usefulness. This study showed that Perceived Usefulness and Trust are critical factors for the acceptance and use of SHT by seniors, validating the extension of UTAUT with a Trust factor. This makes a unique theoretical contribution to the literature with implications for aged care providers and policymakers to consider seniors' perceived usefulness and trust in the design, development, and implementation of Smart Home solutions.

Usage and impact of the internet-of-things-based smart home technology: a quality-of-life perspective

The aim of this paper is to explore the usage and impact of the Internet-of-Things-based Smart Home Technology (IoT-SHT) in Malaysia. Face-to-face interviews were conducted with a total of eleven IoT-SHT users who had a minimum of 2-year usage experience. The semi-structured interview consisted of six questions which were compartmentalised into two sections. Common themes were identified through constant comparison of the inductive data in the coding process. The in-depth interview uncovered six uses of IoT-SHT. Mainly, it was used for real-time remote control, surveillance, sensing, home automation, entertainment, and family communication. It seems clear that the IoT-SHT helped people to save time, changed their lives, improved security, safety, environment condition, fun, convenience, and comfort within the home ground. It also facilitated better health tracking, family care, and energy conservation. Psychologically, the IoT-SHT also enhanced one's image, offered better companionship, and improved the sense of belongingness, and closeness within the family. This study fills the research gap by providing insights into how the IoT-SHT was used, thereby benefiting users in Malaysia. With the arrival of industrial revolution 4.0, a comprehensive knowledge on the usage of IoT is pertinent. The findings of this study may also serve as a foundation for future research in IoT-SHT adoption. Practically, this study accelerates IoT-SHT diffusion by providing insights to vendors in designing better IoT products and services, based on the popular usages and impactful benefits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10209-022-00937-0.

An empirical assessment of a modified artificially intelligent device use acceptance model—From the task-oriented perspective

Artificial intelligence (AI) is a cutting-edge technology that has been widely applied in tourism operations. To enhance tourists' experience, many tourism suppliers introduced AI devices to interact with tourists. Previous studies classified AI devices as task- and social- oriented based on their functions; however, current models that explain customers' intention to use AI devices did not reflect the discrepancy between the two different types. Therefore, this paper attempts to fill this gap by proposing a theoretical model for the use of task-oriented AI devices. Based on the multi-stage appraisal framework and the Structural Equation Modeling analysis, this paper presents the following findings: (1) utilitarian motivation, interaction convenience, and task-technology fit are the factors appraised in the first stage; (2) perceived competence and flow experience are the factors appraised in the second stage; (3) utilitarian motivation, interaction convenience, and task-technology fit are positively associated with perceived competence. (4) Perceived competence positively influences flow experience, which further affects customers' switching intention from task-oriented AI devices to human service; (5) the serial mediating effect of perceived competence and flow experience between the stimulus mentioned in the first appraisal stage and the switching intention is confirmed. This study reveals the underlying psychological mechanism when customers use task-oriented AI devices, and it provides a theoretical framework for task-oriented AI device adoption.

Identifying the Key Drivers and Barriers of Smart Home Adoption: A Thematic Analysis from the Business Perspective

Smart homes embrace advanced technologies and the connectedness of devices that aim to increase consumers’ life quality. They are based on data integration over shared platforms collected via sensors and wireless networks. However, although consumers’ current and potential adoption of smart homes have received some research interest, there is a low number of studies considering the foreseeable future of smart homes from the business perspective. To fulfill this gap in the literature, this study presents the results of an exploratory research attempting to reveal the foresight of the business side regarding the penetration of smart home technologies (SHTs) into consumers’ lives. Based on the opinions of industry experts collected through 13 semistructured in-depth interviews, numerous drivers of and barriers to SHT adoption are uncovered and displayed in their intertwined relationship in a thematic map. In creating this map, the qualitative data gathered through the interviews are integrated with widely used theories/models of technology adoption in the literature to develop a full-fledged set of determinants. As a result, drivers of SHT adoption (five sub-themes) and barriers that hinder smart home penetration (eight subthemes) were determined. Drivers consist of relative advantage, enjoyment, image enhancement, modern and multifunctional design, and consumers’ technology innovativeness. In contrast, the main barriers are high cost, complexity, lack of compatibility, lack of trialability, lack of observability, lack of a trusted brand in the market, lack of facilitating conditions and support services, and consumers’ technology anxiety. This rich set of SHT adoption determinants can be used in future studies to examine their relative impact on consumers’ adoption of SHT.

Factors Affecting the Adoption of IoT-Based Smart Campus: An Investigation Using Analytical Hierarchical Process (AHP)

The advancement of technology is making university campuses smarter every single day. Despite the benefits of these advanced technologies, the literature concerning the adoption of smart campuses is significantly lacking increased knowledge to provide effective smart campus solutions. This study aims to prioritize the adoption factors of an IoT-based smart campus. The study applied an analytical hierarchical process (AHP) on 25 factors drawn from the literature. The factors were classified into technology specific factors (TSF), organizational specific factors (OSF), environmental specific factors (ESF), and end-user specific factors (USF). Based on the results obtained, the most significant contributing factors were government support, privacy concerns, social influence, facilitating conditions, and service collaboration, whereas the least significant contributing factors were enjoyment, availability, reliability, mobility, and compatibility. Moreover, based on the global ranking computation, 12 factors from the OSF, ESF, and USF categories appeared to be more significant than TSF. The findings of this study could help university administrators, manufacturers, and policy-makers to understand the critical factors of smart campuses in order to improve the adoption and utilization of these solutions effectively.

Innovation Environment’s Role in Supporting Industry 4.0 Technology Adoption to Address Effects of COVID-19

Health systems were severely strained at the start of the COVID-19 pandemic, where the demand for personal protection equipment (PPE) could not be met. The challenge faced by many countries was how to innovate quickly to create PPE and other needed solutions. The subsequent research gap identified was a lack of practical insights on how to support such novel technology adoption, particularly those that stem from Industry 4.0 (I4.0) within a developing world context. To address this previous literature on I4.0 technology, the role of innovation environments and theoretical principles of technology adoption was reviewed. A practical case from an academic makerspace based in a South African university was then assessed. It was selected due to its direct role in rapid solutions development of PPE using additive manufacturing (AM) until such a time that manufacturers could set up production on a larger scale. It was found that AM and other novel technologies have facilitated innovative solutions to address the significant impacts of the pandemic. Key to which were practices identified of an innovation environment that supported early-stage adoption of AM to achieve this even in a developing country context. The findings imply that innovation environments offer an agile platform to leverage innovation by streamlining certain critical success factors of I4.0 technology adoption, which is presented in a model. However, individual skills developed by such environments to enhance innovation capabilities within this paradigm require further research.

An Integrated Success Model of Internet of Things (IoT)-Based Services in Facilities Management for Public Sector

The rapid growth of the Internet of Things (IoT) has vigorously affected government by enhancing quality and efficiency of public services. However, the application of IoT-based services in public sectors is slow, despite its benefits to citizens. Research is needed to deepen understanding of the factors that influence the successful implementation of facilities management as the Internet-of-Things-based services in public sectors. An integrated model is developed and validated to extend the DeLone and McLean IS success model by including technology readiness and other identified factors which impact the use of facilities management of IoT-based services in public sectors from the perspective of employees. An online questionnaire was developed and distributed to employees from all local authorities throughout Malaysia, and 187 usable responses were collected. The partial least squares structural equation modelling approach was used to test the model, with 90.8% of the variance in IoT-based services, suggesting an acceptable model fit with seven out of nine hypotheses were supported. Thus, the empirical evidence exerts significant effects of technology readiness towards the success of IoT-based facility management in the public sector.

Revising Technology Adoption Factors for IoT-Based Smart Campuses: A Systematic Review

Smart education and the sustainable development of smart campuses have drawn significant research attention. This is enabled by intelligent devices that are widely attracting massive applicability in personal and big business contexts and can increase efficiency and convenience. This paper aims to present a solution to address the lack of a proper adoption model for smart campus initiatives. The evaluation and synthesis of the literature were conducted by following the systematic literature review (SLR) procedure. The study’s findings revealed the taxonomy and IoT technologies leading to the wide adoption of IoT-based smart campuses. The technology adoption models and their corresponding variables help the authors identify and classify a suitable adoption framework for smart campuses. The limitations and challenges of adoption theories as they pertain to smart campuses are discussed. Finally, the study adapts perceived scalability, perceived replicability, perceived reliability, perceived privacy and security, perceived trust, the cost of deployment, usefulness, enjoyment, and technicality as adoption factors of sustainable smart campuses. This study offers practical and theoretical implications regarding the adoption and propagation of emerging smart campuses.

An Empirical Investigation of Reasons Influencing Student Acceptance and Rejection of Mobile Learning Apps Usage

Sustainable learning and education (SLE) is a relatively new ideology based on sustainability principles and developed in response to the United Nations’ recently proclaimed Sustainable Development Goals (SDGs). As a result, technologies should be adopted to equip educational institutions with the tools necessary to attain SLE. Recently, the coronavirus (COVID-19) pandemic has affected educational systems globally, leading them to embrace more innovative technological methods to meet academic demands while maintaining SLE principles. Mobile learning apps (MLA) refers to using the unique capabilities of mobile apps to engage and collaborate towards establishing robust online learning. However, the effectiveness of MLA depends on learners’ acceptance. Therefore, the purpose of this study is to investigate the factors that could affect MLA acceptance. In order to analyze the collected data from 415 Jordanian students among schools and universities, structural equation modeling (SEM) was used. The empirical findings confirm that perceived usefulness and perceived ease of use are significantly influenced by self-efficacy and perceived compatibility. Furthermore, perceived usefulness is significantly influenced by perceived convenience and perceived ease of use. Additionally, perceived enjoyment significantly influences the behavioral intention to use MLA. On the other hand, perceived compatibility has no significant influence on perceived enjoyment. Finally, perceived ease of use, perceived usefulness, and perceived compatibility have no significant effect on behavioral intention to use MLA. This study addresses a critical research gap in the distance learning acceptance literature by proposing an exhaustive model in the post-COVID-19 era that can help to improve students’ performance and outcomes in Jordanian schools and universities.

Key factors driving the adoption of behavioral biometrics and continuous authentication technology: an empirical research

Purpose

For the success of future investments in the implementation of continuous authentication systems, we should explore the key factors that influence technology adoption. The authors investigate the effect of various factors of behavioral intention through the new incorporation of a modified technology acceptance model (TAM) and diffusion of innovation theory (DOI). Also, the authors have created a new theoretical framework with constructs such as security and privacy risks (SPR), biometrics privacy concerns (BPC) and perceived risk of using the technology (PROU). In this paper, the authors conducted a structural equation modeling empirical research. This research is designed in such a way to respond to the trade-off between users’ concern for the protection of their biometrics privacy and their protection from risks.

Design/methodology/approach

The authors provide an extensive conceptual framework for both existing models (TAM and DOI) and the new constructs that the authors have added to the model. In addition, this research explores external factors, such as trust in technology (TT) and innovativeness (Innov). In addition, the authors have introduced significant constructs, to overcome the limitations of the TAM and to adapt it to the needs of the present research. The new theoretical framework the authors introduce in the present research concerns the constructs SPR, BPC and PROU.

Findings

The authors found that the main facilitators of behavioral intention to adopt the technology (BI) are TT, followed by compatibility (COMP), perceived usefulness (PU) and Innov. This research also shows that individuals are less interested in the ease of use of the technology and are willing to sacrifice it to achieve greater security. COMP and Innov also play a significant role. Individuals who believe that the usage of the behavioral biometrics continuous authentication (BBCA) technology would fit into their lifestyle and would like to experiment with new technologies have a positive intention to adopt the BBCA technology. The new constructs the authors have added are SPR, BPC and PROU. The authors’ results support the hypotheses that SPR is a facilitator to PU and PU acts as a facilitator to BI. Consequently, the hypothesis that individuals do not feel adequately protected by classical methods will consider the usefulness of the BBCA as a technology for their extra protection against risks is confirmed by the model. Also, with the constructs BPC and PROU, the authors examined if individuals’ concerns regarding their biometrics privacy act as inhibitors in the BI. The authors concluded that individuals consider that the benefits of using BBCA technology are much more important than the risks for their biometrics privacy since the hypothesis that the major inhibitor of BI is PROU is not supported by the model.

Originality/value

To the best of the authors’ knowledge, this research is among the first in the field that examines the factors that influence the individuals’ decision to adopt BBCA technology.

Enhancing Smart System Platforms

Smart systems are going to transform the social life of modern society. Notwithstanding the benefits of these systems, its use is still low in developing world including Jordan. This study aims to construct a novel model to identify the factors that affect people’s intention to use smart systems in their homes. A survey was conducted on 650 individuals among which 550 valid questionnaires were considered in Jordan. The collected data were analyzed for descriptive analysis and further to valid the hypothesis using Structural Equation Modeling. The findings showed that there is a significant relationship between individuals’ attitudes related to PU and PEOU with their intention toward using smart systems in their lifestyle. It indicated that the research model explains 68.6% of the variance in the individual’s intention to use smart systems in their residence. Practically, it fruitful to the top management of IT companies that offers smart systems. Moreover, enhancing the current systems and organizing a strategic plan for implementation within best practice.

Bringing Smart Home Technology to Peer-to-Peer Accommodation: Exploring the Drivers of Intention to Stay in Smart Accommodation

COVID-19 has caused disruptions in the sharing economy for both platforms and owners, who are typically micro-businesses. Lower demand and ample supply means that users have a great deal of choice. Finding ways for properties to differentiate themselves has been a pressing need. Against this background, this paper pursued two objectives: firstly to explore the perceived functional and emotional value of smart accommodation and the factors contributing to this by adopting the Theory of Consumption Values, and secondly to examine the role of perceived value in driving intention to stay in smart accommodation in the future. 430 responses were collected to analyse the relationships among antecedents, value and intention. The results showed that the functional value of smart accommodation is associated with the perception that such accommodation represents good value for the price, smart devices are useful, they can enhance control of stay experiences, and there are resources and opportunities facilitating the use of technology. Emotional value is determined by the perception that staying in smart accommodation represents sustainable behaviour, the integration of smart home technologies offers control over the stay experience, improves the entertainment experience, aesthetics and playfulness of using technology. Emotional values are inhibited by the perception of surveillance in smart accommodation. Also, the study offers evidence of the correlation of intention with functional and emotional value. The evidence contributes to the literature by explaining the potential implications of innovative technologies for business recovery in the post-pandemic reality, exploring the applications of smart technologies in delivering tourism services, and identifying the factors in the adoption of smart homes in the hospitality sector. The findings provide practical implications for facilitating the applications of innovative technology and its adoption in home and non-home environments.

Smart Home Adoption: The Impact of User Characteristics and Differences in Perception of Benefits

Despite the various benefits offered by smart homes, they have not yet been widely adopted by mainstream users. This study was designed to identify user perceptions in the association between smart home service preference and adoption and to identify factors affecting the adoption and service preferences of smart homes. In order to achieve the goal of the study, an online survey was conducted among 400 potential users in the Republic of Korea. The main findings are as follows: First, there were considerable needs for the services that can support the independent lives of residents, such as safety and convenience services, among all age groups. Second, the study findings suggested that those who preferred environmental control service most were more likely to become relatively active adopters. Third, a significant association between the preference for smart home services and the intention to use was identified. Finally, the study findings suggested that the number of service preferences and adoption was not directly proportional. The findings reported in this study can improve the overall understanding of the process of adopting smart homes, and can provide important insights into user-centered strategies to promote the adoption of smart home services.

Validating the Adoption of Heterogeneous Internet of Things with Blockchain

Emerging technologies such as Internet of Things (IoT) and blockchain have affected the digital transformation. Blockchain, on the one hand, was initially developed for the purpose of financial trading due to its robustness especially for fault tolerance and cryptographic security in addition to its decentralized architecture. IoT, on the other hand, is an open interconnected network of smart devices able to communicate simultaneously. This arises a challenge in privacy and security, specifically for the data being exchanged. To overcome this, studies have focused on the blockchain to resolve the security and privacy issues of IoT. Indeed, limited studies have proposed to assess blockchain’s viability for IoT and the associated challenges. In this paper, a conceptual model has proposed to identify the crucial factors affecting the adoption of blockchain in IoT. The model consists of four dimensions of factors that we assume will affect the adoption of the two technologies. The dimensions are: attitude-related factors, social influence related factors, data-related factors, and security-related factors. This model is validated through a survey that was distributed between professionals in blockchain and IoT. The findings show a significant impact of data-related factors on the adoption of blockchain in IoT and the intention to use them. The model can play an important role in the development of strategies, standards, and performance assessment.

Consumer Innovativeness: a Literature Review

This paper reports the results of a systematic review of recent literature on consumer innovativeness. The main purpose of the research is to identify the current research themes, understand emerging themes, and predict future directions in consumer innovativeness research. Previous reviews were either narrowly scoped or needed to be updated. Accordingly, the current literature review may fill this gap in the literature. The study sample is 188 articles published in journals indexed in the Web of Science database in the last decade. Content analysis was employed by using quantitative and narrative approaches. Based on the content analysis, these articles were assigned to five research themes as follows: 1) consequences of consumer innovativeness; 2) antecedents of consumer innovativeness; 3) the moderating role of consumer innovativeness; 4) the mediating role of consumer innovativeness; 5) measurement of consumer innovativeness. The findings showed that the highest proportion of articles reviewed in this study involve research that examines the consequences of consumer innovativeness. New product adoption is the most commonly identified consequence of consumer innovativeness. The next most common research themes were the moderator role and antecedents of consumer innovativeness. Articles in the measurement of consumer innovativeness were relatively rare. The fewer number of articles in the research theme indicates that measurement of consumer innovativeness has been well identified in the previous studies. The mediator role of consumer innovativeness was not common in the last decade. The research themes were examined in detail by providing the variables included in the previous studies and the study findings, as well. The research confirms the crucial role of consumer innovativeness in adoption. Besides, the findings indicated the augmented role of consumer innovativeness in consumer behaviour literature. The results of the research can be useful for guiding future research. Keywords antecedents of consumer innovativeness, consumer innovativeness, content analysis systematic literature review, consequences of consumer innovativeness.