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1 – 10 of over 2000Cinzia Calluso and Maria Giovanna Devetag
This study aims to investigate some individual factors that may positively/negatively impact upon the willingness to use AI-assisted hiring procedures (AI-WtU). Specifically, the…
Abstract
Purpose
This study aims to investigate some individual factors that may positively/negatively impact upon the willingness to use AI-assisted hiring procedures (AI-WtU). Specifically, the authors contribute to the ongoing discussion by testing the specific role of individuals’ personality traits and their attitude toward technology acceptance.
Design/methodology/approach
Data have been collected from a cohort of workers (n = 157) to explore their individual level of AI-WtU, their personality traits and level of technology acceptance, along with a series of control variables including age, gender, education, employment status, knowledge and previous experience of AI-assisted hiring.
Findings
The results obtained show the significant role played by a specific personality trait –conscientiousness – and technology acceptance in shaping the level of AI-WtU. Importantly, technology acceptance also mediates the relationship between AI-WtU and conscientiousness, thus suggesting that conscientious people may be more willing to engage in AI-assisted practices, as they see technologies as means of improving reliability and efficiency. Further, the study also shows that previous experience with AI-assisted hiring in the role of job applicants has a negative effect on AI-WtU, suggesting a prevailing negative experience with such tools, and the consequent urge for their improvement.
Originality/value
This study, to the best of the authors’ knowledge, is the first to test the potential role of personality traits in shaping employees AI-WtU and to provide a comprehensive understanding of the issue by additionally testing the joint effect of technology acceptance, age, gender, education, employment status and knowledge and previous experience of AI-assisted hiring in shaping individual AI-WtU.
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Jia Li, Wenxiang Xu and Xiaohua Zhao
Connected vehicle-based variable speed limit (CV-VSL) systems in fog area use multi-source detection data to indicate drivers to make uniform change in speed when low visibility…
Abstract
Purpose
Connected vehicle-based variable speed limit (CV-VSL) systems in fog area use multi-source detection data to indicate drivers to make uniform change in speed when low visibility conditions suddenly occur. The purpose of the speed limit is to make the driver's driving behavior more consistent, so as to improve traffic safety and relieve traffic congestion. The on-road dynamic message sign (DMS) and on-board human–machine interface (HMI) are two types of warning technologies for CV-VSL systems. This study aims to analyze drivers’ acceptance of the two types of warning technologies in fog area and its influencing factors.
Design/methodology/approach
This study developed DMS and on-board HMI for the CV-VSL system in fog area on a driving simulator. The DMS and on-board HMI provided the driver with weather and speed limit information. In all, 38 participants participated in the experiment and completed questionnaires on drivers’ basic information, perceived usefulness and ease of use of the CV-VSL systems. Technology acceptance model (TAM) was developed to evaluate the drivers’ acceptance of CV-VSL systems. A variance analysis method was used to study the influencing factors of drivers’ acceptance including drivers’ characteristics, technology types and fog density.
Findings
The results showed that drivers’ acceptance of on-road DMS was significantly higher than that of on-board HMI. The fog density had no significant effect on drivers’ acceptance of on-road DMS or on-board HMI. Drivers’ gender, age, driving year and driving personality were associated with the acceptance of the two CV-VSL technologies differently. This study is beneficial to the functional improvement of on-road DMS, on-board HMI and their market prospects.
Originality/value
Previous studies have been conducted to evaluate the effectiveness of CV-VSL systems. However, there were rare studies focused on the drivers’ attitude toward using which was also called as acceptance of the CV-VSL systems. Therefore, this research calculated the drivers’ acceptance of two normally used CV-VSL systems including on-road DMS and on-board HMI using TAM. Furthermore, variance analysis was conducted to explore whether the factors such as drivers’ characteristics (gender, age, driving year and driving personality), technology types and fog density affected the drivers’ acceptance of the CV-VSL systems.
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Johnson Adetooto, Abimbola Windapo, Francesco Pomponi, Fabio Companie, Kehinde Alade and Amanda Mtya
Sandbag building technologies (SBTs) have been offered as a cost-effective and sustainable alternative building technology (ABT) capable of accelerating house construction in…
Abstract
Purpose
Sandbag building technologies (SBTs) have been offered as a cost-effective and sustainable alternative building technology (ABT) capable of accelerating house construction in South Africa, but its acceptance remains low. However, knowledge about how to effectively improve SBT social acceptance is limited. This study aims to develop and prioritise SBT social acceptability strategies towards providing a comprehensive framework for the successful deployment and widespread adoption of sandbag technology.
Design/methodology/approach
This study used a quantitative research strategy that included a literature review and a structured questionnaire survey of 228 ABT professionals and stakeholders in the South African housing industry. The study statistically analysed 13 strategies for the social acceptance of SBT.
Findings
The analysis showed that the top three strategies include the availability of sandbag demonstration projects in all provinces, the approval of a sandbag building code and the availability of standard design methods for earthbags. A factor analysis clustered the 13 strategies into Stakeholders integration and policy formation, Effective education and knowledge sharing and Grassroots advocacy and incentives.
Practical implications
The current study’s findings provide a broad framework for the effective implementation and wide acceptance of sandbag technology in housing projects. It offered certain best practices that policymakers and practitioners might use to promote ABT and SBT societal acceptability.
Originality/value
To the best of the authors’ knowledge, the study represents the first and only attempt to investigate the viewpoints of experts and housing market stakeholders in South Africa regarding sandbag technology social acceptance strategies and contributes to the social acceptance body of knowledge in ABT and SBT.
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The study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt…
Abstract
Purpose
The study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt m-learning in teaching and learning, including its acceptance.
Design/methodology/approach
A structured questionnaire was administered to open and distance learning (ODL) students in Odisha, India, to assess their readiness and acceptance of m-learning. 665 valid responses were collected, and collected data was analysed using statistical packages for social sciences (SPSS) and SmartPLS.
Findings
The findings of the study reveal that optimism contributes positively to perceived ease of use (PEOU) and perceived usefulness (PU) of m-learning (β = 7.921, p < 0.001; β = 2.123, p < 0.05), whereas innovativeness positively contributes to PEOU of m-learning (β = 2.227, p < 0.05), but not PU of m-learning. ODL student's optimism improves his/her PEOU and PU of m-learning, but innovativeness improves only his/her PEOU. Further, the impact of innovativeness is higher than that of optimism in the TRAM and innovativeness is the strong predictor to adopt m-learning. It also shows that the PU of m-learning positively influences behavioural intention to use m-learning (β = 4.757, p < 0.001). Integrating technology readiness (TR) with technology acceptance model (TAM) to predict students' acceptance of m-learning is very useful.
Practical implications
The paper will help decision-makers to adopt and use m-learning in higher educational institutions.
Originality/value
This paper is the first to explore the readiness and acceptance of m-learning in higher education in India.
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Marie Molitor and Maarten Renkema
This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the…
Abstract
This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the smart industry context showed that there is limited research on HRC in hybrid teams and even less on effective management of these teams. This book chapter addresses this issue by investigating factors affecting intention to collaborate with a robot by conducting a vignette study. We hypothesized that six technology acceptance factors, performance expectancy, trust, effort expectancy, social support, organizational support and computer anxiety would significantly affect a users' intention to collaborate with a robot. Furthermore, we hypothesized a moderating effect of a particular HR system, either productivity-based or collaborative. Using a sample of 96 participants, this study tested the effect of the aforementioned factors on a users' intention to collaborate with the robot. Findings show that performance expectancy, organizational support and computer anxiety significantly affect the intention to collaborate with a robot. A significant moderating effect of a particular HR system was not found. Our findings expand the current technology acceptance models in the context of HRC. HRM can support effective HRC by a combination of comprehensive training and education, empowerment and incentives supported by an appropriate HR system.
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Marco Hubert, Markus Blut, Christian Brock, Ruby Wenjiao Zhang, Vincent Koch and René Riedl
This study aims to develop a comprehensive adoption model that combines constructs from various theories and tests these theories against each other. The study combines a…
Abstract
Purpose
This study aims to develop a comprehensive adoption model that combines constructs from various theories and tests these theories against each other. The study combines a technology acceptance model, innovation diffusion theory and risk theory. It develops this model in a smart home applications context.
Design/methodology/approach
The study is based on an online survey consisting of 409 participants, and the data are analyzed using structural equation modeling.
Findings
Each theory provides unique insights into technology acceptance and numerous constructs are interrelated. Predictors from innovation diffusion and risk theory often display indirect effects through technology acceptance variables. The study identifies risk perception as a major inhibitor of use intention, mediated through perceived usefulness. Results reveal that the most important determinants of use intention are compatibility and usefulness of the application.
Research limitations/implications
Studies which do not examine different theories together may not be able to detect the indirect effects of some predictors and could falsely conclude that these predictors do no matter. The findings emphasize the crucial role of compatibility, perceived usefulness and various risk facets associated with smart homes.
Originality/value
This study broadens the understanding about the necessity of combining acceptance and adoption drivers from several theories to better understand the usage of complex technological systems such as smart home applications.
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This study identifies key facets leading to consumers' Internet of Things (IoT) adoption intention.
Abstract
Purpose
This study identifies key facets leading to consumers' Internet of Things (IoT) adoption intention.
Design/methodology/approach
Applying four technology acceptance theories (theory of planned behavior, technology acceptance model, pleasure-arousal-dominance theory and technology readiness index), the author uses deductive quantitative research to develop a model, explaining IoT adoption intentions. Administrated questionnaires are distributed in Egypt among generation-Z and millennials in malls. A total of 400 questionnaires are used for hypotheses testing, applying structural equation modeling (SEM) path coefficient analysis.
Findings
Results of this study show that attitude, dominance, perceived usefulness, innovativeness and insecurity impact consumers' IoT adoption intentions; subjective norms, perceived behavior control, pleasure, arousal, perceived ease, optimism and discomfort hold insignificant impact on consumers' IoT adoption intentions.
Research limitations/implications
Exploring IoT facets and how these facets impact consumers' adoption intentions, this study helps grasp technology acceptance in theory and practice, guiding scholar and practitioners (e.g. IoT developers, retailers, marketers and other field experts) to consider consumers' mindset when developing, improving and marketing IoT.
Originality/value
The contribution stems from the incorporation of various frameworks used to explain technology acceptance. By studying several theories jointly, the research extracts and identifies a significant set of facets (technical and psychological) to build a comprehensive theory of IoT acceptance, showing consumers' IoT adoption is not entirely similar to adoption of other past innovations. This understanding allows marketers to focus on content that needs to be promoted to boost consumers' IoT purchase plans. Future researchers could replicate the results to IoT categories (e.g. home appliances, cars, healthcare, education, sportswear, etc.) to improve external validity of the findings, among other future research opportunities.
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Desirée H. van Dun and Maneesh Kumar
Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech…
Abstract
Purpose
Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech initiatives is key to successful Industry 4.0 technology adoption, but few studies have examined the determinants of employee acceptance. This study, therefore, aims to explore how managers affect employees' acceptance of Industry 4.0 technology, and, in turn, Industry 4.0 technology adoption.
Design/methodology/approach
Rooted in the unified theory of acceptance and use of technology model and social exchange theory, this inductive research follows an in-depth comparative case study approach. The two studied Dutch manufacturing firms engaged in the adoption of Industry 4.0 technologies in their primary processes, including cyber-physical systems and augmented reality. A mix of qualitative methods was used, consisting of field visits and 14 semi-structured interviews with managers and frontline employees engaged in Industry 4.0 technology adoption.
Findings
The cross-case comparison introduces the manager's need to adopt a transformational leadership style for employees to accept Industry 4.0 technology adoption as an organisational-level factor that extends existing Industry 4.0 technology user acceptance theorising. Secondly, manager's and employee's recognition and serving of their own and others' emotions through emotional intelligence are proposed as an additional individual-level factor impacting employees' acceptance and use of Industry 4.0 technologies.
Originality/value
Synthesising these insights with those from the domain of Organisational Behaviour, propositions were derived from theorising the social aspects of effective Industry 4.0 technology adoption.
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Shinta Rahma Diana and Farida Farida
Technology acceptance is a measure of that technology’s usefulness. Oil palm is one of the biggest contributors to Indonesia’s revenues, thus fueling its economy. Using remote…
Abstract
Purpose
Technology acceptance is a measure of that technology’s usefulness. Oil palm is one of the biggest contributors to Indonesia’s revenues, thus fueling its economy. Using remote sensing would allow a plantation to monitor and forecast its production and the amount of fertilizer used. This review aims to provide a policy recommendation in the form of a strategy to improve the added value of Indonesia’s oil palm and support the government in increasing oil palm production. This recommendation needs to be formulated by determining the users’ acceptance of remote sensing technology (state-owned plantations, private plantation companies and smallholder plantations).
Design/methodology/approach
This review’s methodology used sentiment analysis through text mining (bag of words model). The study’s primary data were from focus group discussions (FGDs), questionnaires, observations on participants, audio-visual documentation and focused discussions based on group category. The results of interviews and FGDs were transcribed into text and analyzed to 1) find words that can represent the content of the document; 2) classify and determine the frequency (word cloud); and finally 3) analyze the sentiment.
Findings
The result showed that private plantation companies and state-owned plantations had extremely high positive sentiments toward using remote sensing in their oil palm plantations, whereas smallholders had a 60% resistance. However, there is still a possibility for this technology’s adoption by smallholders, provided it is free and easily applied.
Research limitations/implications
Basically, technology is applied to make work easier. However, not everyone is tech-savvy, especially the older generations. One dimension of technology acceptance is user/customer retention. New technology would not be immediately accepted, but there would be user perceptions about its uses and ease. At first, people might be reluctant to accept a new technology due to the perception that it is useless and difficult. Technology acceptance is the gauge of how useful technology is in making work easier compared to conventional ways.
Practical implications
Therefore, technology acceptance needs to be improved among smallholders by intensively socializing the policies, and through dissemination and dedication by academics and the government.
Social implications
The social implications of using technology are reducing the workforce, but the company will be more profitable and efficient.
Originality/value
Remote sensing is one of the topics that people have not taken up in a large way, especially sentiment analysis. Acceptance of technology that utilizes remote sensing for plantations is very useful and efficient. In the end, company profits can be allocated more toward empowering the community and the environment.
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Nannan Xi, Juan Chen, Filipe Gama, Henry Korkeila and Juho Hamari
In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in…
Abstract
Purpose
In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.
Design/methodology/approach
This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.
Findings
Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.
Originality/value
This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.
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