Selection Tool Use: A Focus on Personality Testing in Canada, the United States, and Germany

Risavy, Stephen D.; Fisher, Peter A.; Robie, Chet; König, Cornelius J.

doi:10.25035/pad.2019.01.004

Cited by 15 publications

(26 citation statements)

References 20 publications

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“…So, although there exist robust research findings on evidence-based selection and decision making (e.g., Kuncel et al, 2013), our knowledge on how information is combined in practice is scarce and outdated or primarily anecdotal (Grove & Meehl, 1996;Ryan & Sackett, 1987). This is surprising, given that surveys on what assessment instruments are used to collect information are abundant (Furnham, 2008;Jackson et al, 2018;König et al, 2010;Mann & Chowhan, 2011;Piotrowski & Armstrong, 2006;Risavy et al, 2019;Taylor et al, 2002;Zibarras & Woods, 2010).…”

Section: The Prevalence Of Holistic and Mechanical Prediction In Prac...mentioning

confidence: 99%

Holistic and mechanical combination in psychological assessment: Why algorithms are underutilized and what is needed to increase their use

Neumann¹,

Niessen²,

Hurks³

et al. 2022

Preprint

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Although mechanical combination results in more valid judgments and decisions than holistic combination, existing publications suggest that mechanical combination is rarely used in practice. Yet, these publications are either descriptions of anecdotal experiences or outdated surveys. Therefore, in several Western countries, we conducted two surveys (total N = 323) and two focus groups to investigate (1) how decision makers in psychological and HR practice combine information, (2) why they do (not) use mechanical combination, and (3) what may be needed to increase its use in practice. Many participants reported mostly using holistic combination, usually in teams. The most common reasons for not using mechanical combination were that algorithms are unavailable in practice and that stakeholders do not accept their use. Furthermore, decision makers do not quantify information, do not believe in research findings on evidence-based decision making, and think that combining holistic and mechanical combination results in the best decisions. The most important reason why mechanical combination is used was to increase predictive validity. To stimulate the use of mechanical combination in practice, our results suggest that decision makers should receive more training on evidence-based decision making, and decision aids supporting the use of mechanical combination should be developed.

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Section: The Prevalence Of Holistic and Mechanical Prediction In Prac...mentioning

confidence: 99%

Holistic and mechanical combination in psychological assessment: Why algorithms are underutilized and what is needed to increase their use

Neumann¹,

Niessen²,

Hurks³

et al. 2022

Preprint

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“…Specifically, tech companies may exhibit a gap similar to other industries (e.g., Fisher et al, in press) or, because tech professionals are more likely to have technical backgrounds (e.g., Gorman, 2011), they may be more likely to use data when making decisions, including hiring decisions. 1 In the current research, we compare the findings from a tech-specific sample with the selection practices of companies in general (Risavy et al, 2019).…”

Section: Selection Practices In Tech Companiesmentioning

confidence: 99%

“…In Study 1 we sought to assess the selection practices of tech companies through the quantitative approach of comparing the use of selection tools in tech companies with existing research that has assessed the selection practices of companies in general (Risavy et al, 2019). In Study 2 we sought to understand the reasons tech companies are using their current selection practices through the qualitative approach of interviewing tech company representatives who are knowledgeable about the hiring process at their company (e.g., HR professionals, CEOs, COOs).…”

Section: The Current Researchmentioning

confidence: 99%

Selection tool use in Canadian tech companies: Assessing and explaining the research–practice gap.

Risavy

Robie

Fisher

et al. 2021

Canadian Journal of Behavioural Science / Revue canadienne des

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Hiring the right people at the right time is essential for the successful growth of any organization. Although organizational researchers have identified the most reliable and valid methods for selecting employees, many companies are not following these recommendations and are missing out on top talent as a result. In the present research we focus on the selection methods of tech companies using a two-study, mixed-methods design. In Study 1 we surveyed 120 tech company representatives who were knowledgeable about their company's hiring practices (e.g., HR professionals, CEOs, COOs). It was found that tech companies are far behind the science and tend to use selection practices known to be poor predictors of performance. In Study 2 we interviewed 18 tech company representatives (17 of which were from organizations that participated in Study 1) about the reasons their company uses their selection practices. We found that tech companies are not particularly concerned with reliability or validity and, instead, value efficiency and maintaining the status quo. Future research directions and practical advice to help tech companies better acquire talent are provided. Public Significance Statement(a) There is a substantial gap between the practices that tech companies are using to hire employees and the best available advice from the research literature; (b) tech companies can likely increase their chances of surviving and thriving by adopting more evidence-based selection tools and methods; and (c) many of the reasons that tech company representatives provide for using their chosen selection devices may be preventing them from seeking out better practices.

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“…Instead, practitioners primarily consider personality and applied social skills rather than cognitive abilities to be the most important constructs (Fisher et al, 2020;Ryan et al, 2015;Sackett & Walmsley, 2014).With regard to assessment instruments, scientific evidence showed that scores on cognitive ability tests, assessment centers, work sample tests, and structured interviews are valid predictors of job performance (Huffcutt et al, 2014;Ones et al, 2010;Roth et al, 2005;Sackett, Shewach, & Keiser, 2017). However, less valid instruments such as analyses of CV's and cover letters, and unstructured interviews are prevalent in practice (König et al, 2010;Lievens & De Paepe, 2004;Risavy et al, 2019;Zibarras & Woods, 2010).…”

Section: The Science-practice Gapmentioning

confidence: 99%

“…Based on both reviews, we (1) give practical recommendations about effective interventions to establish evidence-based assessment, (2) discuss the most promising theoretical frameworks that were used in these studies, and (3) provide an agenda for future research. We chose to focus on personnel-and educational selection because these fields are both concerned with human performance prediction, often use similar predictors (Michel et al, 2019;Risavy et al, 2019), and findings on evidence-based assessment are comparable across both fields (Kuncel et al, 2013).…”

mentioning

confidence: 99%

Implementing evidence-based assessment and selection in organizations: A review and an agenda for future research

Neumann¹,

Niessen²,

Meijer³

2020

Organizational Psychology Review

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In personnel- and educational selection, a substantial gap exists between research and practice, since evidence-based assessment instruments and decision-making procedures are underutilized. We provide an overview of studies that investigated interventions to encourage the use of evidence-based assessment methods, or factors related to their use. The most promising studies were grounded in self-determination theory. Training and autonomy in the design of evidence-based assessment methods were positively related to their use, while negative stakeholder perceptions decreased practitioners’ intentions to use evidence-based assessment methods. Use of evidence-based decision-making procedures was positively related to access to such procedures, information to use it, and autonomy over the procedure, but negatively related to receiving outcome feedback. A review of the professional selection literature showed that the implementation of evidence-based assessment was hardly discussed. We conclude with an agenda for future research on encouraging evidence-based assessment practice.

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Selection Tool Use: A Focus on Personality Testing in Canada, the United States, and Germany

Cited by 15 publications

References 20 publications

Holistic and mechanical combination in psychological assessment: Why algorithms are underutilized and what is needed to increase their use

Holistic and mechanical combination in psychological assessment: Why algorithms are underutilized and what is needed to increase their use

Selection tool use in Canadian tech companies: Assessing and explaining the research–practice gap.

Implementing evidence-based assessment and selection in organizations: A review and an agenda for future research

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