Success of Data Resource Management in Distributed Environments: An Empirical Investigation
The trend toward distributed processing has significantly increased the awareness of data as a key corporate resource and underscored the importance of its management. In spite of this, there is a lack of empirical investigation of issues related to data resource management (DRM) in distributed processing environments. Being perhaps the first empirical attempt, this exploratory study identifies four information systems (IS) variables related to DRM in a distributed environment. It also seeks to examine the notion of gestalt fit to describe the nature of the relationships among these variables. In addition, the study evaluates whether internally congruent groups outperform their opposites in realizing DRM success. The results of cluster analysis support the view of gestalt fit by identifying five clusters. The results also suggest that organizations represented by a well-blended configuration of high intersite data dependence, high centralization of IS decisions, high concentration IS resources at the central site, and low DRM- related autonomy granted to local sites appear to realize a greater degree of DRM success than the other groups. The implications of the study are discussed, and further research directions are proposed.
|Author||Hemant Jain, K. Ramamurthy, Hwa-Suk Ryu, and Masoud Yasai-Ardekani|
|Keywords||Data resource management, distributed pr ocessing, distributed databases, gestalt fit, cluster analysis, autonomy, centralization, intersite data dependence|