Barriers Impeding the Large-Scale Adoption of People Analytics: A Technology-Organization-Environment Approach - Biba, Sindi; Brechtelsbauer, Bastian (ICIS 2024 TREOS, 2024)

Explaining the Adoption of People Analytics in European Companies: An Extension of the Technology-Organization-Environment Framework - Biba, Sindi; Brechtelsbauer, Bastian; Laumer, Sven (ECIS 2025 Proceedings, 2025)

Generative AI as Job Demand and Resource: First Results of an Empirical Study - Biba, Sindi; Laumer, Sven (DIGIT 2024, 2025)
Nowadays the volume and pace of information is overwhelming, and processing vast amounts of data to make decisions and solve problems requires significant time, effort, and cognitive resources. This can often lead to mental strain for decision-makers. Therefore, to address this challenge, researchers advocate for integrating human and machine intelligence, creating a hybrid system that combines complementary strengths. Generative AI (GenAI) has the ability to process large volumes of information at speeds beyond human capacity and can generate novel ideas to support decision-making. However, decision-makers need training not only to write effective prompts but also to engage in deeper inquiry and reflection. Hence, in this paper, we introduce a new theoretical model, where GenAI is depicted as both a job demand and a job resource. Drawing on the Job Demands-Resources (JD-R) model, we propose that the capacity of a GenAI agent to process large datasets and assist with problem-solving renders it a job resource, while the requirement to acquire new skills to use it effectively constitutes a job demand. Our PLS-SEM analysis supports the hypothesis that GenAI, as a job resource, is positively associated with engagement and negatively associated with burnout in the workplace. However, our findings reveal that GenAI, as a job demand, is not positively associated with burnout; rather, it is positively associated to engagement. Hence, acquiring new skills does not appear to be perceived as a burden by employee
Keywords: GenAI; JD-R model; human-AI collaboration; employee implications

People Analytics as a Job Demand or Resource - Biba, Sindi; Laumer, Sven (European Conference on Information Systems, 2024)
Considering the potential that People Analytics has on influencing business outcomes, but at the same time the requirement that it poses for HR professionals to have a variety of skills in order to successfully make use of PA, we introduce a theoretical model, that in addition to the job demands and resources of the JD-R model, presents a third component, the PA as both a job resource and a job demand. Preliminary results of the survey reveal that HR professionals perceive People Analytics as a resourc
Keywords: People Analytics; JD-R model; PA job demands; PA job resources.