Intelligent recruitment: How to identify, select, and retain talents from around the world using artificial intelligence

Allal‐Chérif, Oihab; Aránega, Alba Yela; Sánchez, Rafael Castaño

doi:10.1016/j.techfore.2021.120822

Cited by 60 publications

(13 citation statements)

References 27 publications

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“…Artificial intelligence (AI) is undoubtedly one of the most epoch-making innovations in contemporary history; it has probably contributed more than expected and accelerated the development of other industries and fields [6,7,21]. Artificial intelligence (AI) is intelligence that is performed by machines or software by thinking and behaving intelligently like humans [3,4,22].…”

Section: What Is Artificial Intelligence (Ai)?mentioning

confidence: 99%

“…In recent years, with the further development of artificial intelligence, we have also witnessed and been surprised at how AI has become part of our popular culture. Especially since 1997, when International Business Machine Corporation (IBM)'s Deep Blue defeated Garry Kasparov, the world chess champion, people have gained a deeper understanding of AI [6][7][8]. Nowadays, intelligent personal assistants (IPAs) have become popular and common among premiumtier smartphones.…”

Section: Introductionmentioning

confidence: 99%

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Analyzing Determinants for Adoption of Intelligent Personal Assistant: An Empirical Study

Sun

2021

Applied Sciences

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With the accelerating advances in artificial intelligence (AI) technologies, the rising demand for the intelligent personal assistant is expected to rapidly increase in the following decades. As customer loyalty has become a critical element in gaining a competitive advantage and many marketers pay great attention to it, this research aims to explore the factors that directly affect customer loyalty toward the intelligent personal assistant. The main motivation is to investigate and identify the direct effects that variables such as customer innovativeness and perceived value have on customer loyalty. Additionally, both product knowledge and corporate image will be examined as moderators. The results obtained demonstrate that perceived value has a positive influence on customer loyalty. Furthermore, product knowledge moderates the influence of functional and hedonic innovativeness on customer satisfaction. The study’s main contributions provide a better understanding of customer loyalty. This research aims to be viewed as a specific guide to provide effective practices that companies should implement to help them reallocate resources appropriately and enhance customer value creation. The results indicate that the higher the level of customer perceived value, the better the customer loyalty will be. The findings represent that corporate image has a positive moderating effect on the influence of customer innovativeness on perceived value. This study draws on the outcomes of administrative suggestions and recommends a few observational strategies to improve the monetary administration in the intelligent personal assistant industry.

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Section: What Is Artificial Intelligence (Ai)?mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analyzing Determinants for Adoption of Intelligent Personal Assistant: An Empirical Study

Sun

2021

Applied Sciences

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“…Recruiters check the candidate’s SM before recruiting (Allal-Chérif et al , 2021), indicating that they should receive this automated, evidence-based solution. Choosing candidates that present ethical, political, social and other values aligned with the values and vision of the institution will lead to the optimisation of time and costs, as well as the acquisition of new perspectives, a better understanding of morals, manners and thoughts (Boudlaie et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

AI and public contests: a model to improve the evaluation and selection of public contest candidates in the Police Force

Goncalves

Anastasiadou

Santos

2022

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Purpose The number of candidates applying to public contests (PC) is increasing compared to the number of human resources employees required for selecting them for the Police Force (PF). This work intends to perceive how those public institutions can evaluate and select their candidates efficiently during the different phases of the recruitment process. To achieve this purpose, artificial intelligence (AI) was studied. This paper aims to focus on analysing the AI technologies most used and appropriate to the PF as a complementary recruitment strategy of the National Criminal Investigation police agency of Portugal – Polícia Judiciária. Design/methodology/approach Using design science research as a methodological approach, the authors suggest a theoretical framework in pair with the segmentation of the candidates and comprehend the most important facts facing public institutions regarding the usage of AI technologies to make decisions about evaluating and selecting candidates. Following the preferred reporting items for systematic reviews and meta-analyses methodology guidelines, a systematic literature review and meta-analyses method was adopted to identify how the usage and exploitation of transparent AI positively impact the recruitment process of a public institution, resulting in an analysis of 34 papers between 2017 and 2021. Findings Results suggest that the conceptual pairing of evaluation and selection problems of candidates who apply to PC with applicable AI technology such as K-means, hierarchical clustering, artificial neural network and convolutional neural network algorithms can support the recruitment process and could help reduce the workload in the entire process while maintaining the standard of responsibility. The combination of AI and human decision-making is a fair, objective and unbiased process emphasising a decision-making process free of nepotism and favouritism when carefully developed. Innovative and modern as a category, group the statements that emphasise the innovative and contemporary nature of the process. Research limitations/implications There are two main limitations in this study that should be considered. Firstly, the difficulty regarding the timetable, privacy and legal issues associated with public institutions. Secondly, a small group of experts served as the validation group for the new framework. Individual semi-structured interviews were conducted to alleviate this constraint. They provide additional insights into an interviewee’s opinions and beliefs. Social implications Ensure that the system is fair, transparent and facilitates their application process. Originality/value The main contribution is the AI-based theoretical framework, applicable within the analysis of literature papers, focusing on the problem of how the institutions can gain insights about their candidates while profiling them, how to obtain more accurate information from the interview phase and how to reach a more rigorous assessment of their emotional intelligence providing a better alignment of moral values. This work aims to improve the decision-making process of a PF institution recruiter by turning it into a more automated and evidence-based decision when recruiting an adequate candidate for the job vacancy.

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“…E-recruitment and more specifically the use of AI in conjunction with the analysis of employee performance resulted from adopting chatbots in recruitment, is the subject of very limited literature. This area is not mature, evolving quickly, and relatively unstable (Allal-Chérif et al, 2021). For this reason, this paper tries to analyse the current situation of chatbots' implementation in recruiting and the reflection of this technology on employee's performance.…”

Section: Introductionmentioning

confidence: 99%

“…These tasks extend to covering data mining in recruitment and selection (Allal-Chérif et al, 2021), employee turnover and data extraction, with an emphasis placed on employee performance and productivity (Arslan et al,2021). For instance, IBM and…”

Section: Introductionmentioning

confidence: 99%

Adoption Factors of Artificial intelligence in Human Resource Management

Tuffaha¹

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The world is witnessing new technological advancements, which significantly impacts organizations across different departments. Artificial intelligence (AI) is one of these advancements that is widely heralded as a revolutionary technology in Human Resource Management (HRM). Professionals and scholars have discussed the bright role of AI in HRM. However, deep analysis of this technology in the HR process is still scarce.Therefore, the main goal of this thesis is to investigate the status of AI in HRM and derive concrete implementation key factors. Through, first, building an academic framework for AI in HRM; second, analyzing the most commonly used AI applications in HR process; third, identifying the optimal ways to transfer the knowledge of AI implementation processes.The methodology used for the investigation combines a systematic literature review and a qualitative research technique. As a basis and preparatory measure to address the research questions, an extensive literature analysis in the AI-HRM field was carried out, with a particular focus on publications of AI in HRM, HR-Big data analysis, AI applications/solutions in HRM and AI implementation. Along similar lines, the author published papers in several conference proceedings to improve the maturity of research questions.Based on this work, the published studies illustrate the gap between the promise and reality of AI in HRM, taking into account the requirements of AI implementation as well as the applications and limitations. Subsequently, HR experts and AI consultants, who had already gained first-hand experience with HR processes in an AI environment, were interviewed to find out the truth of the dominant AI's application in HR process.The main findings of this thesis are the derivation of a complete definition of AI in HRM as well as the status of the adoption strategies of AI applications in HRM. As a further result, it explores the usefulness and limitations of chatbots in the recruitment processes in India. In addition, derived the key factors to transfer the knowledge of AI implementation process to HR managers and employees. Challenges associated with AI implementation in the HR process and the impact of COVID-19 on AI implementation were also concluded.

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Intelligent recruitment: How to identify, select, and retain talents from around the world using artificial intelligence

Cited by 60 publications

References 27 publications

Analyzing Determinants for Adoption of Intelligent Personal Assistant: An Empirical Study

Analyzing Determinants for Adoption of Intelligent Personal Assistant: An Empirical Study

AI and public contests: a model to improve the evaluation and selection of public contest candidates in the Police Force

Adoption Factors of Artificial intelligence in Human Resource Management

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