Name
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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1108/ITP-05-2019-0254 | INFORMATION TECHNOLOGY & PEOPLE |
Keywords | DocType | Volume |
IS feature use, IS use behavior, Time characteristics, Data-driven perspective, Multiple analytical approach | Journal | 34 |
Issue | ISSN | Citations |
1 | 0959-3845 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Jia | 1 | 0 | 0.34 |
| Shilun Ge | 2 | 0 | 0.68 |
| Nianxin Wang | 3 | 0 | 0.68 |