AI Recruitment: Explaining job seekers’ acceptance of automation in human resource management

Ochmann, Jessica; Laumer, Sven

doi:10.30844/wi_2020_q1-ochmann

Cited by 10 publications

(8 citation statements)

References 42 publications

(62 reference statements)

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“…Social Influence refers to how much people believe that significant individuals in their lives, such as family and friends, think they should utilize a specific technology [32,67]. It's noted that social influence holds a vital role in technology use across different areas including mobile technology in healthcare [59], AI based talent acquisition in the view of job applicants [68] and adopting ERP in the corporates [62]. Based on the earlier research, HR and recruiting professionals can gain access to guidance, advice, and valuable information regarding AI software in recruitment, enhancing their confidence in making decisions to use the system, thereby assessing the hypothesis.…”

Section: Social Influencementioning

confidence: 99%

An Extended UTAUT Model for Analyzing Users’ Acceptance Factors for Artificial Intelligence Adoption in Human Resource Recruitment: A Case Study of Thailand

Wongras,

Tanantong

2023

Preprint

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Recruitment is a fundamental aspect of Human Resource Management to drive organizational performance. Traditional recruitment processes, with manual stages, are time-consuming and inefficient. Artificial Intelligence (AI), which demonstrates its potential in various sectors such as healthcare, education and notable cases of ChatGPT, is currently reshaping recruitment by automating tasks to improve efficiency. However, in Thailand, where there is a growing demand for talents, the application of AI in recruitment remains relatively limited. This research focuses on human resources (HR) and recruitment professionals in Thailand, aiming to understand their perspectives on the integration of AI in recruitment. It extended the Unified Theory for Acceptance and Use of Technology (UTAUT) model, customized to suit the specific requirements of Thai recruitment practices. The study explores the factors influencing users' intention to adopt AI in recruitment. Survey questionnaire items were created based on prior literatures and refined with insights from HR and recruitment experts to ensure applicability in the context of recruitment in Thailand. A survey involving 364 HR and recruiting professionals in Bangkok metropolitan area supplied comprehensive responses. The research reveals that several factors, including Perceived Value, Perceived Autonomy, Effort Expectancy, and Facilitating Conditions, significantly impact the intention to adopt AI for recruitment. While Social Influence and Trust in AI Technology do not have a direct influence on intention, Social Influence directly affects Perceived Value. Trust in AI Technology positively influences Effort Expectancy. This study provides valuable benefits for HR and recruitment professionals, organizations and AI developers by offering insights into AI adoption and sustainability, enhancing recruitment processes and promoting the effective use of AI tools in this sector.

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Section: Social Influencementioning

confidence: 99%

An Extended UTAUT Model for Analyzing Users’ Acceptance Factors for Artificial Intelligence Adoption in Human Resource Recruitment: A Case Study of Thailand

Wongras,

Tanantong

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Three different types of AI-based systems are discussed in the recruiting context depending on whether the use of AI supports the employee or the applicant [11]. For the first type, the AI job recommender systems match a candidate profile and the available job opportunities, and then prioritize job opportunities for the candidate [12].…”

Section: Types Of Ai Used In Recruitmentmentioning

confidence: 99%

Computer, Whom Should I Hire? – Acceptance Criteria for Artificial Intelligence in the Recruitment Process

Laurim¹,

Arpaci²,

Prommegger³

et al. 2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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In the war for talents, the need for appropriate tools to fill open positions with the right talents is becoming increasingly important for employers. AI-based technologies simplify recruiters' daily work and increase the efficiency of the recruitment process by replacing time-consuming approaches. However, little is known about the reactions of stakeholders to AI-based recruiting. Thus, this paper aims to identify personal and contextual factors that influence the acceptance of AI-based technologies in the recruitment process. Based on the interviews with recruiters, managers, and applicants involved in the recruitment process, we present that transparency, complementary features of the AI tools, and a sense of control play key roles in the acceptance of AI-based technology when used for recruiting. The findings contribute to research on the adoption of AI in the recruitment process and provide recommendations on the use of AI technologies when hiring talents.

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“…The UTAUT-based model has been widely used in diverse research domains, covering the adoption of various technologies like mobile technology services [63][64][65], medical technology [66], corporate ERP management [67], education technology [68], IoT adoption [69], AI-driven customer relationship management systems [70], AI-powered intelligent products [71], AI in public technology services [72], and AI in HR and recruitment areas [39,[73][74][75]. Consequently, the UTAUT was chosen as the foundational model for this study.…”

Section: Development Of Influencing Factors Toward the Intention To U...mentioning

confidence: 99%

A UTAUT-Based Framework for Analyzing Users’ Intention to Adopt Artificial Intelligence in Human Resource Recruitment: A Case Study of Thailand

Tanantong,

Wongras

2024

Systems

View full text Add to dashboard Cite

Recruitment is a fundamental aspect of Human Resource Management to drive organizational performance. Traditional recruitment processes, with manual stages, are time-consuming and inefficient. Artificial Intelligence (AI), which demonstrates its potential in various sectors such as healthcare, education, and notable cases of ChatGPT, is currently reshaping recruitment by automating tasks to improve efficiency. However, in Thailand, where there is a growing demand for talents, the application of AI in recruitment remains relatively limited. This study focuses on human resources (HR) and recruitment professionals in Thailand, aiming to understand their perspectives on the integration of AI in recruitment. It utilized the Unified Theory for Acceptance and Use of Technology (UTAUT) model, customized to suit the specific requirements of Thailand recruitment practices. The study explores the factors influencing users’ intention to adopt AI in recruitment. Survey questionnaire items were created based on prior literature and refined with insights from HR and recruitment experts to ensure applicability in the context of recruitment in Thailand. A survey involving 364 HR and recruiting professionals in the Bangkok metropolitan area supplied comprehensive responses. The study reveals that several factors, including perceived value, perceived autonomy, effort expectancy, and facilitating conditions, significantly impact the intention to adopt AI for recruitment. While social influence and trust in AI technology do not have a direct influence on intention, social influence directly affects perceived value. Trust in AI technology positively influences Effort Expectancy. This study provides valuable benefits for HR and recruitment professionals, organizations, and AI developers by offering insights into AI adoption and sustainability, enhancing recruitment processes and promoting the effective use of AI tools in this sector.

show abstract

AI Recruitment: Explaining job seekers’ acceptance of automation in human resource management

Cited by 10 publications

References 42 publications

An Extended UTAUT Model for Analyzing Users’ Acceptance Factors for Artificial Intelligence Adoption in Human Resource Recruitment: A Case Study of Thailand

An Extended UTAUT Model for Analyzing Users’ Acceptance Factors for Artificial Intelligence Adoption in Human Resource Recruitment: A Case Study of Thailand

Computer, Whom Should I Hire? – Acceptance Criteria for Artificial Intelligence in the Recruitment Process

A UTAUT-Based Framework for Analyzing Users’ Intention to Adopt Artificial Intelligence in Human Resource Recruitment: A Case Study of Thailand

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