GPT-Anwendungen in Industrieunternehmen: Eine Untersuchung der Akzeptanz und Nutzung durch Angestellte

Abstract

This study analyzes the acceptance and use of the in-house GPT application AIA, which
has been implemented in an Austrian industrial company. Only a comprehensive and
active use of the AI application by employees ensures an efficient use of the invested
resources and provides the company with a competitive advantage. Therefore, this study
focuses on the factors that positively influence the acceptance and use of GPT
applications by employees. The findings are intended to serve as a framework for
developing a training strategy for dealing with AI applications in everyday work.
The Technology Acceptance Model 2 (TAM2) and selected constructs from the Unified
Theory of Acceptance and Use of Technology (UTAUT) were used for the analysis. The
empirical study was conducted at the Austrian sites of a manufacturing company and
included 256 participants from the white-collar sector. An online questionnaire was used
for data collection. In addition to correlations between TAM2 and UTAUT constructs,
reasons for not using the GPT application and information about previous training were
collected.
The results of the study show that Perceived Usefulness has the greatest impact on
employees' Behavioral Intentions and thus on the Actual Use of the GPT application. Job
Relevance, Output Quality and Result Demonstrability are significant determinants of
Perceived Usefulness, with Job Relevance being the strongest predictor. The positive
effect of Subjective Norm decreases with increasing experience. On the other hand,
Perceived Ease of Use and Image show no significant effects. With regard to the UTAUT
constructs that were examined, Social Influence shows no significant effect. Although
facilitating conditions have a positive effect on Behavioral Intention, the effect of
Perceived Usefulness is significantly greater.
To promote the active use of the company's GPT application and future AI technologies
in the company, training measures on the use of AI aimed at employees should focus
primarily on the benefits of the application and its relevance in the respective work
context, as well as on improving skills for assessing the quality of the results.

Date of Award	2024
Original language	German (Austria)
Supervisor	Tanja Jadin (Supervisor)