Saija Mauno, Bettina Kubicek, Jaana Minkkinen and Christian Korunka
In order to understand the driving forces behind intensified job demands (IJDs), the purpose of this paper is to examine demographic factors, structural work-related factors…
Abstract
Purpose
In order to understand the driving forces behind intensified job demands (IJDs), the purpose of this paper is to examine demographic factors, structural work-related factors, personal and job resources as antecedents of IJDs.
Design/methodology/approach
The study is based on cross-sectional (n=4,963) and longitudinal (n=2,055) quantitative data sets of Austrian employees. Data sets were analyzed via regression analyses.
Findings
The results showed that IJDs, as assessed through five sub-dimensions: work intensification, intensified job-related, career-related planning and decision-making demands, intensified demands for skills and for knowledge-related learning, remained fairly stable overtime. The most consistent antecedents of IJDs were personal initiative and ICT use at work. Job resources, e.g. variety of tasks and lacking support from supervisor, related to four sub-dimensions of IJDs.
Research limitations/implications
The findings suggest that personal (being initiative) and job resources (task variety) may have negative effects as they associated with IJDs. Moreover, supervisors’ support is crucial to counteract IJDs.
Practical implications
Employers should recognize that certain personal (e.g. personal initiative) and job-related resources (e.g. lacking supervisory support) might implicate higher IJDs, which, in turn, may cause more job strain as IJDs can be conceived as job stressors.
Originality/value
IJDs have received very little research attention because they are new job demands, which however, can be expected to increase in future due to faster technological acceleration in working life. The study has methodological value as longitudinal design was applied.
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Keywords
Christine Dagmar Malin, Jürgen Fleiß, Isabella Seeber, Bettina Kubicek, Cordula Kupfer and Stefan Thalmann
How to embed artificial intelligence (AI) in human resource management (HRM) is one of the core challenges of digital HRM. Despite regulations demanding humans in the loop to…
Abstract
Purpose
How to embed artificial intelligence (AI) in human resource management (HRM) is one of the core challenges of digital HRM. Despite regulations demanding humans in the loop to ensure human oversight of AI-based decisions, it is still unknown how much decision-makers rely on information provided by AI and how this affects (personnel) selection quality.
Design/methodology/approach
This paper presents an experimental study using vignettes of dashboard prototypes to investigate the effect of AI on decision-makers’ overreliance in personnel selection, particularly the impact of decision-makers’ information search behavior on selection quality.
Findings
Our study revealed decision-makers’ tendency towards status quo bias when using an AI-based ranking system, meaning that they paid more attention to applicants that were ranked higher than those ranked lower. We identified three information search strategies that have different effects on selection quality: (1) homogeneous search coverage, (2) heterogeneous search coverage, and (3) no information search. The more applicants were searched equally often (i.e. homogeneous) as when certain applicants received more search views than others (i.e. heterogeneous) the higher the search intensity was, resulting in higher selection quality. No information search is characterized by low search intensity and low selection quality. Priming decision-makers towards carrying responsibility for their decisions or explaining potential AI shortcomings had no moderating effect on the relationship between search coverage and selection quality.
Originality/value
Our study highlights the presence of status quo bias in personnel selection given AI-based applicant rankings, emphasizing the danger that decision-makers over-rely on AI-based recommendations.
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Christian Korunka, Bettina Kubicek, Matea Paškvan and Heike Ulferts
Increasing speed in many life domains is currently being discussed under the term “social acceleration” as a societal phenomenon which not only affects western societies, but may…
Abstract
Purpose
Increasing speed in many life domains is currently being discussed under the term “social acceleration” as a societal phenomenon which not only affects western societies, but may also lead to job demands arising from accelerated change. Demands such as work intensification and intensified learning and their changes over time may increase emotional exhaustion, but may also induce positive effects. The purpose of this paper is to examine how increases in demands arising from accelerated change affect employee well-being.
Design/methodology/approach
A total of 587 eldercare workers provided data on work intensification and intensified learning as well as on exhaustion and job satisfaction at two points in time.
Findings
Work intensification was negatively related to future job satisfaction and positively related to future emotional exhaustion, whereas intensified learning was positively associated with future job satisfaction and negatively with future emotional exhaustion.
Social implications
Intensified demands represents a growing social as well as work-specific challenge which needs to be addressed by practitioners.
Originality/value
Using a longitudinal perspective this study is the first to examine the relationship of increases in work intensification and intensified learning with job satisfaction and emotional exhaustion at work.