Acceptance of recruiting chatbots: an empirical study on the recruiters' perspective
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2022
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2565
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eng
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361 leaves
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b215412
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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National Institute of Development Administration. Library and Information Center
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Drebert, Judith (2022). Acceptance of recruiting chatbots: an empirical study on the recruiters' perspective. Retrieved from: https://repository.nida.ac.th/handle/662723737/6480.
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Acceptance of recruiting chatbots: an empirical study on the recruiters' perspective
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Abstract
In economic history, there have always been changes and disruptions within market structures and established infrastructure. One eruptive technological development is the automation of business processes. Chatbots offer a way to automate processes in an interactive-laden way via dialogues with the human inquirer. The study at hand investigates factors influencing recruiter-sided chatbot acceptance within the recruiting process. The recruiting process step of candidate interviewing serves as a high-involvement use case for the target group of the quantitative survey: Participants are recruiters in human resource departments in companies from Germany (main focus), Austria and Switzerland with candidate interviews in their recruiting processes. The first chapter contains an introduction to the topic, states the objective of the study and shows the structure of the dissertation. In the second chapter, the recruiting process is being outlined and brought together with the aspect of digitization and automation before regarding the role of chatbots in recruiting. Acceptance research and the topic of chatbot acceptance are presented in the third chapter. The fourth chapter is about the formation of the research model: Based on research on acceptance and specifically the technology acceptance model (TAM), the Human-Robot Collaboration Model (HRCAM) is transformed into the novel Human-Chatbot Collaboration Model (HCCAM) for the non-physical case of chatbots and expanded via the chatbot-relevant constructs of perceived system transparency and inertia regarding chatbot technology. Main focus of the quantitative recruiter survey is the investigation of the antecedents of recruiting chatbot acceptance according to the HCCAM model, specifically regarding job-related automation concerns. It incorporates (1) the validated TAM2 (Venkatesh & Davis, 2000) items subjective norm, job relevance, result demonstrability, and output quality, (2) the validated TAM3 (Venkatesh & Bala, 2008) items self-efficacy, perceptions of external control, and chatbot anxiety, (3) the ethical, legal and social implications (ELSI) and technology affinity items as introduced by Bröhl et al. (2019), (4) perceived system transparency (e.g., Peters et al., 2020) as well as (5) inertia (e.g., Polites & Karahanna, 2012) items adapted from related literature. The fifth chapter is about the quantitative survey for assessing the factors related to recruiters’ chatbot acceptance presenting the methodological approach. Subsequently, the empirical study results are presented in the sixth chapter. Subjective norms and perceived usefulness are found as most relevant significant acceptance criteria for chatbots in recruiting. Overall, 13 significantly influencing factors are yielded, amongst them perceived system transparency and inertia. The dissertation concludes with a discussion of the findings, a display of the theoretical and practical contributions, a conclusion section, an examination of the limitations of the study, and an outlook on future research.
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Thesis (Ph.D. (Management))--National Institute of Development Administration, 2022