Al-enabled biometrics in recruiting: Insights from marketers for managers

Abstract

Both researchers and practitioners are only in the early stages of examining and understanding the application of artificial intelligence (AI) in terms of marketing themselves as employers or the open jobs they have. AI has the potential to significantly affect how firms reach, identify, attract, and select human capital. We examine factors that can influence a job candidate's intent to complete AI-enabled recruiting processes, especially the influence of a firm's use of biometrics in that process. The results show that (1) social media can increase technology use motivation and AI-enabled recruiting with (2) trendiness as a first stage boundary condition and (3) biometrics as a second stage boundary condition. We contribute to marketing knowledge by identifying that for managers wanting to influence job seekers’ technology use motivation in order to increase their participation in AI-enabled recruiting; they must focus on the indirect effects of trendiness, biometrics, and their social media usage.

Reading Between the Lines: Understanding Customer Experience With Disruptive Technology Through Online Reviews

“…As an antecedent to brand engagement (Hollebeek et al, 2014), customer experience has become a key strategic objective for many organizations (Bilgihan et al, 2016;Brodie et al, 2011;Chen et al, 2018;Johnston & Kong, 2011). In recent times, continuous technological developments, such as social media (Kietzmann et al, 2011), virtual or augmented reality (Farshid et al, 2018), artificial intelligence (AI) (Kietzmann et al, 2018;Mogaji et al, 2020;van Esch et al, 2019van Esch et al, , 2020, and robotics Feng et al, 2020;Huang & Rust, 2018), have been augmenting the capabilities of organizations to understand and transform customer experiences (Bolton et al, 2018;Breidbach et al, 2018;Van Doorn et al, 2017;Xu et al, 2020).…”

AI auditing and impact assessment: according to the UK information commissioner’s office

“…Transparency Building upon a discussion of special category data and discrimination, the guidance explores mitigation of such risks. The overarching theme here is the need for transparency, which is that the purposes 'intention' [6, p. 60] is made clear with respect to why the system is being developed and deployed [24]. This should be done right from the beginning (design phase), with clear policies and good practice regarding procurement and lawful processing of data, including robust testing of any anti-discriminatory measures and monitoring of performance, and with senior management being responsible for signing off the chosen approach.…”

Stimulating or Intimidating: The Effect of AI-Enabled In-Store Communication on Consumer Patronage Likelihood

“…AI has begun to influence our lives profoundly as manifested through its use in innumerable products and services we have come to use daily (e.g., streaming services like Netflix, gaming services like AlphaGo, transportation products like Tesla's autonomous vehicles, health care companies' search for disease prevention and detection using AI, organizations using AI-enabled recruitment and product recommendations enabled by AI;van Esch et al 2020;Topol 2019;van Esch, Black, and Ferolie 2019;Kumar et al 2019). These examples represent the proverbial tip of the iceberg, and it is somewhat self-evident that AI's scope and presence will continue to expand in the near and distant future.…”