The perceptions of employees from Romanian companies on adoption of artificial intelligence in recruitment and selection processes

Năstase, Marian; Croitoru, Gabriel; Valentina, Florea Nicoleta; Cristache, Nicoleta; Lile, Ramona Article The perceptions of employees from Romanian companies on adoption of artificial intelligence in recruitment and selection processes Amfiteatru Economic Journal Provided in Cooperation with: The Bucharest University of Economic Studies Suggested Citation: Năstase, Marian; Croitoru, Gabriel; Valentina, Florea Nicoleta; Cristache, Nicoleta; Lile, Ramona (2024) : The perceptions of employees from Romanian companies on adoption of artificial intelligence in recruitment and selection processes, Amfiteatru Economic Journal, ISSN 2247-9104, The Bucharest University of Economic Studies, Bucharest, Vol. 26, Iss. 66, pp. 421-439, https://doi.org/10.24818/EA/2024/66/421 This Version is available at: https://hdl.handle.net/10419/300602 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Innovative Application of AI in Business Impacting Socio-Economic Progress AE Vol. 26 • No. 66 • May 2024 421 THE PERCEPTIONS OF EMPLOYEES FROM ROMANIAN COMPANIES ON ADOPTION OF ARTIFICIAL INTELLIGENCE IN RECRUITMENT AND SELECTION PROCESSES Marian Năstase1, Gabriel Croitoru2, Nicoleta Valentina Florea3, Nicoleta Cristache4 and Ramona Lile5 1) Bucharest University of Economic Studies, Bucharest, Romania. 2)3) Valahia University of Targoviste, Targoviste, Romania. 4) Dunarea de Jos University of Galati, Galati, Romania. 5) Aurel Vlaicu University of Arad, Arad, Romania. Please cite this article as: Năstase, M., Croitoru, G., Florea, N.V., Cristache, N. and Lile, R., 2024. The Perceptions of Employees from Romanian Companies on Adoption of Artificial Intelligence in Recruitment and Selection Processes. Amfiteatru Economic, 26(66), pp. 421-439. DOI: https://doi.org/10.24818/EA/2024/66/421 Article History Received: 28 December 2023 Revised: 27 February 2024 Accepted: 29 March 2024 Abstract Managers increasingly want to improve the efficiency of human resources processes, and a solution with real results is Artificial Intelligence (AI), which provides real results in a virtual world for human resources managers, for companies, and also for candidates. The purpose of this article is to investigate the perception of employees in Romanian companies to adopt and use AI in recruitment and selection processes, analysing the factors that influence this acceptance intention using Technology Acceptance Model (TAM). The study aimed to determine the benefits of AI adoption in recruitment and selection processes, the perceived usefulness of adoption, and the ease of use in these processes. The results obtained showed that almost all the variables proposed for the model positively influenced the intention to accept and use AI in the recruitment and selection process. Non-discrimination and the utility of using (PU) AI in recruitment and selection had little influence. The findings should contribute to understanding the acceptance of artificial intelligence in the two processes proposed for analysis and observe its impact on its adoption among employees in different fields. Keywords: artificial intelligence, human resources, Romanian companies, recruitment, selection, efficiency. JEL Classification: O15, P42, C52. Corresponding author, Marian Năstase – e-mail: [email protected] This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2023 The Author(s). AE The Perceptions of Employees from Romanian Companies on Adoption of Artificial Intelligence in Recruitment and Selection Processes 422 Amfiteatru Economic Introduction Due to globalisation, the increased use of technology, business complexity, IT-based technologies, and artificial intelligence (AI) is increasingly used in various fields of activity. AI is used in human resources (HR) processes such as: recruitment (Horodyski, 2023) and acquisition of new talent (Madeline Laurano, Co-founder & Chief Research Office), selection and interviewing (Gheeta and Bhanu Sree Reddy, 2018), processes employment (Kelan, 2023), training and communication (Ore and Sposato, 2021), improving the work climate (De Obesso Arias, Pérez Rivero and Carrero Márquez, 2023), bringing various benefits (Yadav and Kapoor, 2023). Almost 30% of companies use AI for the recruitment process to reduce time and bring the right employee with the right talent to the right place at the right cost: reduce time-consuming activities, automate CV evaluation, match candidate skills to job requirements, eliminate pauses between processes, make decisions much easier using big data, predict future results, easily connect candidates with specialists, easily manage candidate files or quickly extract key information about candidates. Many companies have already implemented AI in these processes and are measuring its acceptance among their future employees (Vedapradha, Hariharan and Shivakami, 2019). AI is about thinking quickly and logically based on a lot of knowledge at its disposal (Geetha and Bhanu Sree Reddy, 2018), reducing time and cost in meeting the right candidate with the vacancy. In the pandemic and post-pandemic period, AI in recruitment and selection increased in utility for individuals and also for specialists who want a more competitive profile of the candidate (Anghel, 2023). Machines have already changed many contents of jobs, but now a human-technology cooperation is being established based on natural language processing (NLP), voice recognition (VR), machine learning process, deep learning, neural networks (Eurbanks, 2018), problem solving, automation of recruitment and selection (Ore and Sposato, 2021). All these benefits are making AI attractive for organisations who look for talented multi-skills employees. AI was used for the first time in 1956 by the father of AI, John McCarthy, and now AI has offered the opportunity to use recruitment and selection functions as being conducted in smart ways (Ore and Sposato, 2021), bringing new opportunities and challenges, and achieving important objectives. However, even if enterprises use AI in many processes, the human element will remain a vital component of the process. The study is structured as follows: in Section 1 is the literature review is presented, along with some important advantages of recruitment and selection processes based on using AI. Moreover, the research hypothesis and the conceptual model of the analysis also are established. In Section 2 the research methodology is presented, with a focus on research design and context, consisting in the process of data collection and analysis. The results and research discussion are presented in Section 3, which contains, in the final part, the theoretical and managerial contributions of the article; the limitations and future research proposals are also presented. Innovative Application of AI in Business Impacting Socio-Economic Progress AE Vol. 26 • No. 66 • May 2024 423 1. Literature review and research hypothesis 1.1. AI and recruitment process According to Upadhyay and Khandelwal (2018), the application of AI in HR management has been one of the most notable trends among recruitment professionals. There are many advantages of using AI in the recruitment process, so we mention only a few, based on which some research hypotheses have been established. These advantages mainly refer to the reduced time, where the software used in today's recruitment markets uses AI to scan the best possible candidates in a short time (Collins, 2018), providing a shortlist and a ranking of the most promising candidates (Fernández and Fernández, 2019). Another advantage would be the low cost and easy ranking of the candidates. There are many applications for finding a job, but using AI companies can easily rank candidates or shorten the hiring process (Faliagka et al., 2012), ranking candidates and recognising candidates with the best scores and reducing environmental impact (Lepri et al., 2018). Improved speed using AI makes recruitment faster (Collins, 2018), becoming attractive and more cost-effective and performed at high speed (van Esch and Black, 2019) and efficiently (Lamikanra and Obafetni-Ajayi, 2023). The "anywhere anytime" principle and the website can provide different information, anytime it can be accessed from anywhere, and create the ability to attract and retain the right people (Cohen, 2001), providing 24/7/365 accessibility based on just-in-time systems to attract new candidates (Nawaz and Gomes, 2019) considered an asset in today's "talent war" (Leicht-Deobald et al., 2019). Using AI in R&D provides equal opportunities and non-discrimination. Using AI, resumes are screened fairly, giving equal chances to all candidates (Upadhyay and Khandelwal, 2018). Thus, non-discrimination is reduced (Kelan, 2023) and ethics-based vision increases (Tambe, Cappelli and Yakubovich, 2019). Work diversity and reliability are other perks that talented employees want. Non-judgmental is the biggest advantage (Horodisky, 2023), AI ignores the background of candidates and helps to find the right talent, better evaluations, diversify the employee portfolio and a greater diversity of candidates (Lewis, 2018), or an inclusion more effective socio-economic of future employees. Focusing on skills and extracting information makes the process of scanning data on skills and knowledge a beneficial process, and by detecting and collecting them (Stuart and Norvig, 2016), they lead to an effective recruitment process. CV updating using AI provides the possibility to check the skills of the employees and also provides the possibility to update the data for other jobs (Gheeta and Bhanu Sree Reddy, 2018). Thus, we can develop the following research hypotheses: H1Recruitment process based on AI has a positive effect on Intention to adopt AI in R&S processes and also other hypothesis as: H1a-H1jTime saving/ cost saving/ speed/ anywhere/ anytime/ equal chances/ nondiscrimination/ work diversity/ focus on competency/ continuous CV updating have a positive impact on Intention to adopt AI in recruitment processes. 1.2. AI and selection process The literature on AI and the selection process has already been analysed since the early 2000s, and the perceptions of the use of new technologies in the selection process and the job interview have offered numerous advantages. Reducing the costs of interviewing using AI is a real benefit: the amount of manual work decreases and the time to focus on the right candidates increases (Guchait et al., 2014), recruiters can instantly relate to talented AE The Perceptions of Employees from Romanian Companies on Adoption of Artificial Intelligence in Recruitment and Selection Processes 424 Amfiteatru Economic candidates (Leong, 2018), using interviews at distance that are very effective in helping to achieve specific goals through flexible adaptation. Data privacy becomes very important, and data mining must be done based on AI regulations, and data protection must be perceived as an ethical issue (Oswald et al., 2020), according to the European General Data Protection Regulation (GDPR). Using data mining and AI, predictions can be made and decisions can be made (Hmoud and Laszlo, 2019), or information can be extracted based on CV scanning, but based on data confidentiality. Data security, using AI provides a safe environment (Tilmes, 2022), where candidates can, for example, have different questions and answers in a secure platform, regarding benefit coverage, vacation leave, or pay level evaluation. AI handles all types of query using chat box, email form, or a virtual conversation in a meeting room (Gheeta and Bhanu Sree Reddy, 2018). Quick feedback leads to a quick response for candidates because automated emails are used, so the relationship with the candidate is quick and the response is time and cost efficient (Gheeta and Bhanu Sree Reddy, 2018). AI enables rapid feedback about a candidate's rejection, his training programmes, knowledge and skills that an employee can develop in the future (Upadhyay and Khandelwal, 2018). Thus, AI facilitates rapid communication as the Web, social media, or mobile communications are used (Upadhyay and Khandelwal, 2018). By reducing favouritism using AI in the selection process, many advantages can be achieved: less nepotism and favouritism (Langer et al., 2019; Langer, König and Papathanasiou, 2019; Langer, König and Hemsing, 2020; Suen, Chen and Lu, 2019), highly qualified candidates (Persson, 2016), process correctness and precision due to prediction algorithms (Polli, 2019) and variables that do not need to be predefined by RU specialists (Polli, 2019). By screening candidates, companies can easily check candidate skills and knowledge (Forbes, June, 2018), and using the chat box, they can interact with candidates by helping answer questions or providing feedback and requested information (Gheeta and Bhanu Sree Reddy, 2018). Chatbots, as AI tools, help in screening and updating the candidate base using chat, email, or text messages (Upadhyay and Khandelwal, 2018). Job skill matching leads to an efficient AI-based selection process and is when a suitable candidate is found based on the matching principle and less paper is used (Dickson and Nusair, 2010). A rapid assessment using AI of the candidate is based on the data posted on social media, so the selection specialists have access to their values, attitudes, and personality traits (Upadhyay and Khandelwal, 2018). The video interview is very popular, uses a short set of predetermined questions, and can analyse the candidate's competences, skills, but also non-verbal communication, such as body language, facial expressions, or voice (inflection, tone, rhythm, speed) (Tambe, Cappelli and Yakubovich, 2019; van Esch and Black, 2019). The application compares each interviewed candidate with the most talented employees in the company, and then the best one is suggested (HireVue, 2018). Rapid assessment of the right candidate consists of pre-screening and sorting CVs and then matching them to vacancies. The managers' task is now to find qualified candidates based on increased speed and efficiency (Dickson and Nusair, 2010). A rapid assessment of their skills and knowledge is used based on AI (Faliagka et al. 2012). When we talk about talent management, we are talking about a system that can support the organisation's objectives and that facilitates the development of a system of control and measurement of results and that reveals the strong correlations between efforts and performances (Sitnikov, Mihalcea and Romanescu, 2023). By mining data, the system may Innovative Application of AI in Business Impacting Socio-Economic Progress AE Vol. 26 • No. 66 • May 2024 425 gather information related to availability, contact information, skills, knowledge, attitudes, training programmes, and experiences, residency or net salary expectations. Thus, AI can provide the ability to book a meeting, schedule one, or order food without the involvement of a recruitment specialist (Gheeta and Bhanu Sree Reddy, 2018). Thus, the following hypotheses were developed: H2Selection process based on AI has a positive effect on Intention to adopt AI in R&S processes and also: H2a-H2jReduced costs/ privacy/ security/ instant feedback/ lack of favouritism/ rapid screening/ match skills and job/ efficient video interviewing/ quick evaluation/ data extraction have a positive impact on intention to adopt AI in selection processes. 1.3. Technology Acceptance Model (TAM) The technology acceptance model (TAM) proposed by Davis is explaining the impact factors necessary for adoption of new technologies (Davis, 1989) and is very used in information systems research. The TAM relies on two factors: perceived usefulness (PU) and perceived ease of use (PEU). PU refers to the increase in performance based on the use of new technologies and PEU to the acceptance of new technologies without much effort (Na et al., 2022). TAM is a model that measures the degree of acceptance and use of technology in humancomputer interaction (Grani and Maranguni, 2019) and is considered a very important model used to determine the degree of adoption of its use in various fields of innovative activity (Lai, 2017). The main idea of this model is to analyse the user's current relationships, behaviour, intentions, attitudes, beliefs, and norms. In 1993 it was rethought to understand its utility and acceptance of IT systems used in certain processes (Chen et al., 2016). Many researchers use TAM, adding various other variables such as gender, educational level, or participation in various training programs (Martono et al., 2020); therefore, in addition to researchers who used it in recruitment and selection processes, it was also used in this study precisely to highlight the role, importance, and benefits brought by the use of AI in the recruitment and selection processes among employees in Romanian companies. The model states that a person's attitude towards using technology in certain processes is influenced by their perception of the ease and usefulness of using technology (Byun, 2018). Perceived usefulness (PU). Studies determined that AI is used in recruitment because it is friendly and fun and is used to attract the intention of job seekers (Brahmana and Brahmana, 2013) and offer control (Lin, 2010). PU and attitude fully mediate the relationship between e-WOM from e-recruitment and the behavioural intentions of job seekers (Kaur and Kaur, 2023). Therefore, the following hypothesis was proposed. H3PU has a positive effect on intention to adopt AI in R&S processes. Perceived ease of use (PEU). PEU has a direct impact on attitude to use e-recruitment; results indicated that job seekers adopt e-recruitment when it is user-friendly and when help them to accomplish their tasks easily and efficiently (Kaur and Kaur, 2023), when website is interesting, when e-recruitment is creating the desire to choose the company as a potential employer or when is creating the desire to promptly apply for a job, when website is playful, offer e-trust or create a positive relationship (Priyadarshini, Sreejesh and Anusree, 2017), or AE The Perceptions of Employees from Romanian Companies on Adoption of Artificial Intelligence in Recruitment and Selection Processes 426 Amfiteatru Economic offers control for job seeker (Lin, 2010). Therefore, the following research hypothesis was developed. H4PEU has a positive effect on the intention to adopt AI in R&S processes. Based on the literature review and TAM, we developed the conceptual model (Figure no. 1), where AI used in recruitment and selection processes (Parikh, Patel and Jaiswal, 2021) has an important impact on the intention to adopt AI in these processes, and PU (Lin, 2010; Brahmana and Brahmana, 2013) and PEU (Lin, 2010; Priyadarshini, Sreejesh and Anusree, 2017; Kaur and Kaur, 2023) have an influence on the intention to adopt AI in R&S processes. Figure no. 1. Structural model Source: authors' processing 2. Research Methodology The goal of this paper is to investigate the impact of recruitment and selection processes based on AI on the intention to adopt AI in these processes, and also the influence of PU and PEU on the intention to use AI in these analysed processes. In our study, TAM was used, Innovative Application of AI in Business Impacting Socio-Economic Progress AE Vol. 26 • No. 66 • May 2024 427 which provides a clear framework that helps organisations to evaluate their behavioural intention to adopt technology in R&S processes. Other research objectives would be to determine the benefits of using AI in the recruitment and selection processes that each candidate enjoyed, the perceived usefulness of adopting AI in the recruitment and selection processes, the perceived ease of use of AI in these processes, and the degree of adoption in the future period of AI within these processes. In our research, a quantitative study was used, based on the determination of the relationships developed and as research hypotheses. A face-to-face and online questionnaire was used, developed, and applied in November 2023. A total of 250 questionnaires were distributed to respondents who were recruited and selected using AI. These were obtained from contract workers in Romania, who were recruited and selected using AI before being hired. Of the total, 56% of the respondents are male, 68% of the respondents are from urban areas, almost 38% have master's and doctorate degrees, and 27% are from the 36-45 age group, and 74% hold an executive position. A percentage of 43.2% were in manufacturing, 34% in education, 27% in IT, 22% in finance and banking and 8% in health. Related to the two variables analysed, regarding the use of AI in recruitment, 13.6% used recruitment agency portals, 38% the company website, 35.6 LinkedIn, and 12.8% other media sites; and in the selection, 69.2% were subjected to an online interview, 26.8% to online tests, and 10% to a video interview. The demographics of the respondents are shown below (Table 1). Table no. 1. Demographic characteristics of the respondents Characteristic N % Characteristic N % Characteristic N % Gender Male Female Residence Urban Rural Field of activity Production Education Finance and Banking IT/Technology Health 140 110 170 80 108 85 22 27 8 56 44 68 32 43.2 34 8.8 10.8 3.2 Education College Bachelor’s degree Master’s degree Doctorate Functions Management Execution Selection using AI Online interview Online tests The video interview 32 82 94 42 65 185 173 67 10 12.8 32.8 37.6 16.8 26 74 69.2 26.8 4 Age < 25 years 26-35 years 36-45 years 46-54 years > 55 years Recruitment using AI Agency portals Company website LinkedIn Other media sites 30 60 68 65 27 34 95 89 32 12 24 27.2 26 10.8 13.6 38 35.6 12.8 Source: authors' processing 3. Results and discussions The questionnaire (Table no. 2) was developed using a five-point Likert scale (1strongly disagree and 5strongly agree). AE The Perceptions of Employees from Romanian Companies on Adoption of Artificial Intelligence in Recruitment and Selection Processes 428 Amfiteatru Economic The structural model examined respondents' perceptions of the intention to adopt R&D processes based on the use of AI. Focusses on factors such as recruitment, selection, perceived ease of use, perceived usefulness, and actual use of technology. Table no. 2. Confirmatory Factor Analysis and Descriptive statistics Construct Item Measure Mean VIF Loading (St.Est.) Chro alpha AVE CR 1. AI and R&S processes 1.1. AI and recruitment process AIR01 Time saving 4.70 3.026 0.873 0.842 0.682 0.792 AIR02 Cost saving 4.38 3.296 0.807 AIR03 Increased speed 4.31 1.954 0.702 AIR04 Apply from anywhere 4.20 3.397 0.744 AIR05 Apply any moment 4.30 1.240 0.798 AIR06 Equal chances for candidates 3.90 2.239 0.740 AIR07 Discrimination is eliminated 3.70 1.127 0.853 AIR08 A more diverse workforce 3.80 1.392 0.926 AIR09 Focus is on competency 4.00 2.370 0.876 AIR10 Improve continuous and update CVs 4.20 1.275 0.750 1.2. AI and selection process AIS01 Reduced costs 4.60 2.682 0.800 0.796 0.676 0.847 AIS02 Offer privacy 3.80 1.279 0.888 AIS03 Offer security 3.40 1.021 0.740 AIS04 Offer instant feedback 4.20 2.341 0.709 AIS05 Reduce favouritism 3.80 1.642 0.830 AIS06 Efficient and rapid screening 4.49 2.265 0.783 AIS07 Match between employees skills and job vacancy 4.44 2.089 0.867 AIS08 Video interviewing allows to detect non-verbal language 4.64 2.352 0.728 AIS09 Offer quick evaluation responses 4.60 1.785 0.750 AIS10 Use information extraction for candidates skills 4.30 2.580 0.734 Innovative Application of AI in Business Impacting Socio-Economic Progress AE Vol. 26 • No. 66 • May 2024 435 References Abousetta, A., El Kholy, W., Hegazy, M., Kolkaila, E., Emara, A., Serag, S., Fathalla, A. and Ismail, O., 2023. A scoring system for cochlear implant candidate selection using artificial intelligence. Hearing, Balance and Communication, 21(2), pp. 114-121. https://doi.org/10.1080/21695717.2023.2165371. 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