Search results

Although affective accounts of organizational justice theory have been offered, suggesting a role played by trait affectivity dimensions – trait positive affectivity (TPA) and trait negative affectivity (TNA) - in shaping applicant reactions to selection procedures, research in this area relies on cognitive information processing accounts of justice perceptions. Thus, the role played by TPA and TNA in shaping applicant reactions is an underexplored area. This study explicates and tests the role of TPA and TNA in shaping reactions.

The authors carried out a three-wave field study of police job applicants, measuring TPA and TNA before testing and applicant justice perceptions and recommendation intentions pre-feedback and post-feedback.

TPA, but not TNA, was positively associated with justice perceptions and recommendation intentions. Mediation analyses suggested that the TPA-recommendation intentions relationship was mediated through justice perceptions.

Recruiting high TPA applicants can benefit future applicant pools due to enhanced recommendation intentions. High TPA applicants react more favorably to positive features; thus, procedures should conform to procedural justice rules so that favorable aspects exist for high TPA applicants to respond favorably towards.

The authors’ work is the first to integrate affective accounts of the justice perception formation process into applicant reactions research. Their work supports a role served by affect in shaping applicant fairness perceptions and provides novel and important insights for both theory and practice.

Automatic evaluation of job interviews has become an alternative for assessing interviewees. Therefore, questions arise regarding applicant reactions and behavior when algorithms automatically evaluate applicants' interview responses. This study tests arguments from previous research suggesting that applicants whose interviews will be automatically evaluated may use less impression management (IM), but could react more negatively to the interview.

Participants (N = 124; primarily German students) took part in an online mock interview where they responded to interview questions via voice recordings (i.e. an asynchronous interview). Prior to the interview, half of them were informed that their answers would be evaluated automatically (vs by a human rater). After the interviews, participants reported their honest and deceptive IM behavior as well as their reactions to the interview.

Participants in the automatic evaluation condition engaged in less deceptive IM, felt they had fewer opportunities to perform during the interview, and provided shorter interview answers.

The findings of this study suggest a trade-off between IM behavior and applicant reactions in technologically advanced interviews. Furthermore, the results indicate that automatically evaluated interviews might affect interview validity (e.g. because of less deceptive IM) and influence interviewees' response behavior.

Hiring managers might hope that automatically evaluated interviews decrease applicants' use of deceptive IM. However, the results also challenge organizations to pay attention to negative effects of automatic evaluation on applicant reactions.

This study is the first empirical study investigating the impact of automatically evaluated interviews on applicant behavior and reactions.

The aim of this article is to identify recent developments in personnel selection and to review existing research with regard to these recent developments. To this end, 26 human resource representatives were asked to list current or future trends in personnel selection. In addition, existing academic reviews of recent research in personnel selection were scrutinized. As a result, the following four main trends are identified: labour market shortages, technological developments, applicant perceptions of selection procedures, and construct‐driven approaches. Per trend, relevant existing research is reviewed and avenues for future research are discussed.

The use of game-based assessments (GBAs) is growing in selection contexts, yet test-takers have varying reactions to such assessments, which have important implications for applicant behavior. This paper reviews the literature on applicant reactions and explores classic assessment models in the context of GBAs, identifying best practice recommendations and pitfalls for enhancing the candidate experience.

A sample of 374 participants from MTurk completed cognitive GBAs and questionnaires regarding test-taker reactions (job-relatedness, perceived opportunity to perform, provision of selection information, face validity, task engagement, task motivation and willingness to refer others to the company), technology self-efficacy, and game/technology experience.

Fairness mediated the relationship between procedural justice rules and willingness to recommend the company to others. Technology self-efficacy was significantly related to fairness perceptions and procedural justice perceptions. Males had significantly higher procedural justice perceptions of GBAs than females.

The study underscores the importance of considering fairness perceptions and individual differences in reactions to GBAs. Future research should study participants within high-stakes hiring situations and examine other individual difference factors such as ethnicity.

GBAs are a viable assessment method for personnel selection, yet organizations must recognize that individuals are more likely to respond positively to GBAs if they perceive such assessments as fair and job-related, and perceive themselves as capable of performing well on the assessment.

This study tests a classic model of procedural fairness in a novel and timely assessment context.

It is widely established that many hiring managers view social networking websites (SNWs) such as LinkedIn and/or Facebook in the employment selection process, leading to the acceptance or rejection of job applicants. Due to the rapid evolution of social media, scientific study of SNWs has been substantially outpaced by organizational practice. This chapter focuses on a wide range of issues related to SNW screening relevant to research and practice.

The chapter: (1) reviews the current state of SNW screening practices, (2) describes a wide range of HR issues that should be considered such as privacy, discrimination, negligent hiring, validity, reliability, generalizability, impression management, applicant reactions, and utility, (3) draws connections to related issues already addressed by established employment selection methods to inform SNW screening, (4) discusses pros and cons of potential SNW screening approaches, and (5) provides a framework of best practices that should be incorporated into social network screening policies.

As an emerging employment selection approach, SNW screening demonstrates potential as a rich source of applicant information, but includes numerous legal and ethical issues. Further, these potential benefits and risks vary widely depending on the approaches used.

Provides HR practitioners with a wide range of information necessary to develop an effective social network screening policy, while making the case for academics to pursue research in this nascent area.

The purpose of this paper is to examine Chinese traditionality as a predictor of applicants' procedural fairness perceptions in selection, and both its direct and indirect relationship with applicants' recommending behavior, job performance and turnover intention three to four months post hire. Traditionality, as a moderator of perceptions‐outcomes relationships, is also tested.

Survey data of 218 supervisor‐subordinate dyads were collected from Mainland Chinese organizations. Data were gathered in two waves, with demographic and traditionality measures taken at time 1, and supervisory ratings of performance, recommending behavior and intention to turnover taken at time 2.

One component of traditionality alone (Respect for Authority) positively predicted applicants' procedural fairness perceptions. These perceptions, in turn, predicted recommending behavior (+), job performance (+) and turnover intentions (−). There were also direct relationships between Respect for Authority and both job performance (+) and turnover intention (−). The data failed to support the moderating effect of Chinese traditionality on the relationships between procedural fairness perceptions and outcome variables.

Despite the methodological strengths of this study, the study is cross‐sectional in nature which weakens causal inferences regarding the relationships in the theoretical model. Moreover, the paper does not investigate empirically the concrete mechanisms from Chinese traditionality to fairness perceptions and from fairness perceptions to outcome variables, since its foci are the predicting and moderating roles of Chinese traditionality.

The paper's findings underscore the importance of Respect for Authority as the key and only component of Chinese traditionality that predicts procedural justice perceptions and worker outcomes.

Over the past decade, the rapid evolution of social media has impacted the field of human resource management in numerous ways. In response, scholars and practitioners have sought to begin an investigation of the myriad of ways that social media impacts organizations. To date, research evidence on a range of HR-related topics are just beginning to emerge, but are scattered across a range of diverse literatures. The principal aim of this chapter is to review the current literature on the study of social media in HRM and to integrate these disparate emerging literatures. During our review, we discuss the existent research, describe the theoretical foundations of such work, and summarize key research findings and themes into a coherent social media framework relevant to HRM. Finally, we offer recommendations for future work that can enhance knowledge of social media’s impact in organizations.

The purpose of this paper is to pursue several goals: first, what is the relationship between perceived respect for privacy and potential job pursuit of student applicants in a hypothetical application scenario which includes social media screening as part of the selection process? Second, if the job involves vulnerable others, what are the implications for privacy perceptions? And third, to what extent does the use of social media for non-work purposes relate to perceived respect for privacy?

Using a cross-sectional sampling approach, data were collected from 388 student participants in two different data collection rounds via an online survey.

Perceived respect for privacy was positively correlated, and information privacy concern was negatively correlated, with job pursuit intention. However, perceived respect for privacy differed across the different jobs. Specifically, respect for privacy was higher when the employer screened social media for jobs involving explicit work with children. Social media use and content effects also emerged. Those who either observed others online or interacted with others online to socialize reported lower respect for privacy. Participants with more sensitive content online and content they would be unwilling to share also reported lower scores for privacy.

The results were based on cross-sectional data, correlational analyses and hypothetical job scenarios due to ethical considerations and causal restrictions in what may be bi-directional effects.

The current study adds to the limited research on the negative effects of social media screening by employers on applicant reactions and the role of job-specifics on how applicant may react to screening.

In 2018, an artificial intelligence (AI) interview platform was introduced and adopted by companies in Korea. This study aims to explore the perspectives of applicants who have experienced an AI-based interview through this platform and examines the opinions of companies, a platform developer and academia.

This study uses a phenomenological approach. The participants, who had recent experience of AI video interviews, were recruited offline and online. Eighteen job applicants in their 20s, two companies that have adopted this interview platform, a software developer who created the platform and three professors participated in the study. To collect data, focus group interviews and in-depth interviews were conducted.

As a result, all of them believed that an AI-based interview was more efficient than a traditional one in terms of cost and time savings and is likely to be adopted by more companies in the future. They pointed to the possibility of data bias requiring an improvement in AI accountability. Applicants perceived an AI-based interview to be better than traditional evaluation procedures in procedural fairness, objectivity and consistency of algorithms. However, some applicants were dissatisfied about being assessed by AI. Digital divide and automated inequality were recurring themes in this study.

The study is important, as it addresses the real application of AI in detail, and a case study of smart hiring tools would be valuable in finding the practical and theoretical implications of such hiring in the fields of employment and AI.