Join thousands of book lovers
Sign up to our newsletter and receive discounts and inspiration for your next reading experience.
By signing up, you agree to our Privacy Policy.You can, at any time, unsubscribe from our newsletters.
During the last decades, a considerable amount of research has been directed towards explaining the concept of Digital Human Resource Management (DHRM). Yet, a holistic assessment of DHRM antecedents and consequences with respect to possible contextual contingencies is still missing. To this end, this thesis introduces a research framework illuminating the multifaceted phenomenon of DHRM from various perspectives. An exploratory four-step meta-analytic structural equation modelling (E-MASEM) approach tailored to address the domain-specific challenges of DHRM is introduced and applied. Results identify 32 constructs associated with the DHRM usage phenomenon which are categorized into DHRM antecedents and DHRM consequences. Findings reveal that user perceptions, expectations, attitudes, and intentions are essential in predicting DHRM usage while HRM service quality and user satisfaction are found crucial in explaining other DHRM consequences. Further, practitioners are informed about therelative importance of factors for both facilitating DHRM adoption and measuring DHRM success. Lastly, this thesis also contributes to the MASEM methodology by outlining a new approach to summarize statistical inferences from multiple moderator tests.
Sign up to our newsletter and receive discounts and inspiration for your next reading experience.
By signing up, you agree to our Privacy Policy.