Analyzing enterprise information system’s feature use: a data-driven perspective

Abstract

Purpose

The purpose of this study is to propose a data-driven perspective to analyze enterprise information system (EIS) feature use for understanding what and how the system features are actually used in the organization.

Design/methodology/approach

An empirical study was conducted by analyzing information system (IS) log data collected from a well-known shipbuilding manufacturer in China. The multiple analytical approach employed in this study includes social network analysis, association rules learning and human dynamics.

Findings

This study first classified IS users into 41 core users and 325 general users. Then 24 core modules and 54 general modules were identified by social network analysis, and the correlation between them was analyzed. Finally, we found that the IS use time intervals for different user groups followed a power-law distribution, and IS use displayed strong burstiness and weak memory.

Originality/value

This study proposes a data-driven perspective to investigate how the system features are actually used in the organization. This study contributes to the literature and opens a new avenue for future IS use research. Furthermore, this study informs managers how to diagnose, maintain and optimize the implemented IS in order to maximize IS benefits.

Citation

Jia, Y., Ge, S. and Wang, N. (2021), "Analyzing enterprise information system’s feature use: a data-driven perspective", Information Technology & People, Vol. 34 No. 1, pp. 375-398. https://doi.org/10.1108/ITP-05-2019-0254