Implementation and user acceptance of research information systems: An empirical survey of German universities and research organisations

Abstract

Purpose

The purpose of this paper is to present empirical evidence on the implementation, acceptance and quality-related aspects of research information systems (RIS) in academic institutions.

Design/methodology/approach

The study is based on a 2018 survey with 160 German universities and research institutions.

Findings

The paper presents recent figures about the implementation of RIS in German academic institutions, including results on the satisfaction, perceived usefulness and ease of use. It contains also information about the perceived data quality and the preferred quality management. RIS acceptance can be achieved only if the highest possible quality of the data is to be ensured. For this reason, the impact of data quality on the technology acceptance model (TAM) is examined, and the relation between the level of data quality and user acceptance of the associated institutional RIS is addressed.

Research limitations/implications

The data provide empirical elements for a better understanding of the role of the data quality for the acceptance of RIS, in the framework of a TAM. The study puts the focus on commercial and open-source solutions while in-house developments have been excluded. Also, mainly because of the small sample size, the data analysis was limited to descriptive statistics.

Practical implications

The results are helpful for the management of RIS projects, to increase acceptance and satisfaction with the system, and for the further development of RIS functionalities.

Originality/value

The number of empirical studies on the implementation and acceptance of RIS is low, and very few address in this context the question of data quality. The study tries to fill the gap.

Citation

Schöpfel, J., Azeroual, O. and Saake, G. (2020), "Implementation and user acceptance of research information systems: An empirical survey of German universities and research organisations", Data Technologies and Applications, Vol. 54 No. 1, pp. 1-15. https://doi.org/10.1108/DTA-01-2019-0009