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Business and Management
Information Systems and Management

Adoption and Use of AI Tools: A Research Agenda Grounded in UTAUT

Profile image of Viswanath VenkateshViswanath Venkatesh

2021, Annals of Operations Research

https://doi.org/10.1007/S10479-020-03918-9
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21 pages

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Abstract

This paper is motivated by the widespread availability of AI tools, whose adoption and consequent benefits are still a question mark. As a first step, some critical issues that relate to AI tools in general, humans in the context of AI tools, and AI tools in the context of operations management are identified. A discussion of how these issues could hinder employee adoption and use of AI tools is presented. Building on this discussion, the unified theory of acceptance and use of technology (UTAUT) is used as a theoretical basis to propose individual characteristics, technology characteristics, environmental characteristics and interventions as viable research directions that could not only contribute to the adoption literature, particularly as it relates to AI tools, but also, if pursued, such research could help organizations positively influence the adoption of AI tools.

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    Ismi Rajiani

    Administrative Sciences

    The Internet of things (IoT) has oriented organisations digitally in administrating human resources. In line with this trend, Indonesian public sectors are adopting Human Resources Information Systems (HRIS) to boost employee innovation outcomes. However, coercive pressure to implement HRIS has only resulted in fiascos for the technology, which cannot be fully considered to eliminate long, ineffective, and inefficient practices. This study examines the instrumental adoption factors to adopt HRIS in boosting employee innovation outcomes from technological, organisational, people, and social outlooks. The empirical data consisting of 500 valid datasets were obtained from public servants in Indonesia via web-based questionnaires. structural equation modelling (SEM), which was used to examine the relationship among constructs. Technology fit, organisational resources, knowledge, and social influences have positive impacts on technology adoption. However, when treated as a mediation, the...

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    The Collaborative Effort and Efficiency of Inquiry-Based Learning
    Mohammad Amzad Hossain, Dr. Mohammad Tariq Hasan

    International Journal of Online Pedagogy and Course Design

    This study investigates the effect on the teacher's performance of collaborative effort and efficiency of inquiry-based learning. It also determines the impact of the mediating role of student performance. The research framework was constructed based on the unified technology acceptance and use of technology theory. A quantitative analysis was done with surveys to collect primary data from the teacher and lecturers of Malaysia. The researcher used a Likert scale of 7 to evaluate elements of the building. This study focuses on the top 10 public university students in Malaysia. The universities are University Malaya (UM), University Kembangan Malaysia, University Putra Malaysia (UPM), University Since Malaysia (USM), University Technology Malaysia (UTM), Universiti Utara Malaysia (UUM), International Islamic University Malaysia (IIUM), University Technology Mara (UiTM), University Malaysia Perlis (UniMap), and University Tun Hossain (UTHM). Finally, researchers selected the total ...

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    Predicting the Intention to Adopt Innovation in Supply Chain Finance
    Ronnie Figueiredo

    Journal of Organizational and End User Computing

    Based on the mixed model unified technology acceptance and utilization theory (UTAUT) and spinner innovation model (SPINNER), a theoretical model is suggested to explain the determinant of behavioral intention to predict innovation in the context of a financial sector firm. A questionnaire was developed to collect primary data, which was subsequently processed through the artificial intelligence technique (deep learning). The constructs (performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, public knowledge, private knowledge, and innovation) supported the model, including mediating hypotheses. It was observed that the mixed methodological approach (SEM and ANN) can help to find the linear and non-linear relationships better, being that the error of the predicted model is 0.104, that is, 10.4% relatively low, which evidences that ANN can be used to predict the dependent variable innovation safely.

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