Electronic word-of-mouth via employer review sites – the effects on organizational attraction

Can I show my skills? Affective responses to artificial intelligence in the recruitment process

Companies increasingly use artificial intelligence (AI) and algorithmic decision-making (ADM) for their recruitment and selection process for cost and efficiency reasons. However, there are concerns about the applicant’s affective response to AI systems in recruitment, and knowledge about the affective responses to the selection process is still limited, especially when AI supports different selection process stages (i.e., preselection, telephone interview, and video interview). Drawing on the affective response model, we propose that affective responses (i.e., opportunity to perform, emotional creepiness) mediate the relationships between an increasing AI-based selection process and organizational attractiveness. In particular, by using a scenario-based between-subject design with German employees (N = 160), we investigate whether and how AI-support during a complete recruitment process diminishes the opportunity to perform and increases emotional creepiness during the process. Moreover, we examine the influence of opportunity to perform and emotional creepiness on organizational attractiveness. We found that AI-support at later stages of the selection process (i.e., telephone and video interview) decreased the opportunity to perform and increased emotional creepiness. In turn, the opportunity to perform and emotional creepiness mediated the association of AI-support in telephone/video interviews on organizational attractiveness. However, we did not find negative affective responses to AI-support earlier stage of the selection process (i.e., during preselection). As we offer evidence for possible adverse reactions to the usage of AI in selection processes, this study provides important practical and theoretical implications.

Employer Ratings through Crowdsourcing on Social Media: An Examination of U.S. Fortune 500 Companies

The aims of this study are to examine the effect of crowdsourced employer ratings and employee recommendations of an employer as an employer of choice, to examine which employer ratings that represent different employee value propositions can predict the overall employer rating through crowdsourcing, to examine whether the Fortune 500 ranking can also influence overall employer ratings, and to mine which keywords are popularly used when employees post a comment about the pros and cons of their employers on a crowdsourced employer branding platform. The study collected crowdsourced employer review data from Glassdoor based on 2019 Fortune 500 companies, and the results found that crowdsourced employer ratings are positively associated with “recommend to a friend,” while culture and values predominantly influence overall employer ratings. The rank of Fortune 500 has less predictive power for overall employer ratings than for other specific employer ratings, except for business outlook. The most popular keywords of Pros on Glassdoor are work–life balance and pay and benefits, whereas the most popular keywords of Cons on Glassdoor are work–life balance and upper management.