Abstract
In order to be able to optimise the usage of IS/IT services within an organization, the Business Information Management (BIM) role is pivotal. Many organizations struggle to determine what the required number of staff for the BIM department should be. In earlier research a preliminary model to determine the required capacity of BIM was designed. In this paper the model is validated within a specific industry: the agricultural sector. From a sense that quality of IS/IT services might influence the relationship between the determining factors in the model and the required capacity for BIM, also research is conducted to analyse if quality of IS/IT service interferes with determining the required BIM capacity. As part of a literature study seven aspects of quality were found which provide a good overview of the quality of the IS/IT service within an organization. These seven aspects were included in a survey which had 37 respondents from organizations within the agricultural sector. Data was collected about a set of eight determining factors that were taken from prior research and about quality of IS/IT. Based upon these data correlations were tested. The first connections were tested by using Pearson’s product-moment correlation coefficient which showed a significant correlation between several factors and the number of FTEs. After which a multiple regression-analysis was done to check if the number of FTEs for the executive processes would increase or decrease when the number of business processes increases or decreases. The quality of the IS/IT service doesn’t seem to influence the relationship between the several factors and the number of FTEs investigated in this research. This research shows that the quality of IS/IT service has no influence on determining the required capacity of a BIM department.
Recommended Citation
Hartsink, Melissa; van Outvorst, Frank; ter Braak, Matthijs; and de Waal, Benny ME, "Does Quality Influence the Required Capacity of Business Information Management? The Case of Agriculture" (2019). BLED 2019 Proceedings. 11.
https://aisel.aisnet.org/bled2019/11