Journal article
Understanding Software Operations Support Expertise: A Revealed Causal Mapping Approach
MIS quarterly, v 24(3), pp 475-507
01 Sep 2000
Abstract
This paper utilizes a qualitative methodology, revealed causal mapping (RCM), to investigate the phenomenon of software operations support expertise. Software operations support is a large portion of the IS work performed in organizations. While we as researchers have access to generalized theories and frameworks of expertise, very little is known about expertise in this critical area. To understand software operations support expertise, a mid-range theory is evoked from interviews with experts and the construction of RCMs from those interviews. The results of this study indicate that software operation support expertise is comprised of five major constructs: personal competencies, environmental factors, support personnel motivation, IS policies, and support personnel outcomes. Additionally, this study revealed that these constructs interact differently in contexts where software support is the main activity versus contexts where the focus is development. This study demonstrates that the use of the RCM methodology yields constructs of software operations support expertise that are not suggested by generalized theory. In addition, the use of RCM as an evocative, qualitative methodology reveals the interaction and linkages between these constructs. This paper also provides a history of and tutorial to the RCM methodology for use by the research community.
Metrics
Details
- Title
- Understanding Software Operations Support Expertise: A Revealed Causal Mapping Approach
- Creators
- Kay M. NelsonSucheta NadkarniV. K. NarayananMehdi Ghods
- Publication Details
- MIS quarterly, v 24(3), pp 475-507
- Publisher
- The Society for Information Management and The Management Information Systems Research Center of the University of Minnesota, and The Association for Information Systems
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Management
- Web of Science ID
- WOS:000089487800007
- Scopus ID
- 2-s2.0-0010597854
- Other Identifier
- 991021882960704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Industry collaboration
- Domestic collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Information Science & Library Science
- Management