The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Measuring the Performance of Information Systems: A Functional Scorecard
Abstract
This study develops an instrument that may be used as an information systems (IS) functional scorecard (ISFS). It is based on a theoretical input-output model of the IS function's role in supporting business process effectiveness and organizational performance. The research model consists of three system output dimensions--systems performance, information effectiveness, and service performance. The "updated paradigm" for instrument development was followed to develop and validate the ISFS instrument. Construct validation of the instrument was conducted using responses from 346 systems users in 149 organizations by a combination of exploratory factor analysis and structural equation modeling using LISREL. The process resulted in an instrument that measures 18 unidimensional factors within the three ISFS dimensions. Moreover, a sample of 120 matched-paired responses of separate CIO and user responses was used for nomological validation. The results showed that the ISFS measure reflected by the instrument was positively related to improvements in business processes effectiveness and organizational performance. Consequently, the instrument may be used for assessing IS performance, for guiding information technology investment and sourcing decisions, and as a basis for further research and instrument development.
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Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
A Paradigm for Developing Better Measures of Marketing Constructs
Churchill, G. A. (1979) · Journal of Marketing Research · doi:10.1177/002224377901600110 · Cited by 16,549
Estimating Nonresponse Bias in Mail Surveys
Armstrong, J. S., & Overton, T. S. (1977) · Journal of Marketing Research · doi:10.2307/3150783 · Cited by 12,222
The DeLone and McLean Model of Information Systems Success: A Ten-Year Update
(2003) · Journal of Management Information Systems · doi:10.1080/07421222.2003.11045748 · Cited by 11,791
Construct validity in psychological tests.
Cronbach, L. J., & Meehl, P. E. (1955) · Psychological Bulletin · doi:10.1037/h0040957 · Cited by 11,195
Information Systems Success: The Quest for the Dependent Variable
DeLone, W. H., & McLean, E. R. (1992) · Information Systems Research · doi:10.1287/isre.3.1.60 · Cited by 10,697
Estimating nonresponse bias in mail surveys
Armstrong, J. S., & Overton, T. S. (1977) · Journal of Marketing Research · doi:10.1177/002224377701400320 · Cited by 10,390
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
Task-Technology Fit and Individual Performance
Goodhue, D. L., & Thompson, R. L. (1995) · MIS Quarterly · doi:10.2307/249689 · Cited by 6,006
Dess, G. G., & Robinson, R. B. (1984) · Strategic Management Journal · doi:10.1002/smj.4250050306 · Cited by 3,337
The productivity paradox of information technology
Brynjolfsson, E. (1993) · Communications of the ACM · doi:10.1145/163298.163309 · Cited by 2,604
Assessing the Validity of IS Success Models: An Empirical Test and Theoretical Analysis
Rai, A., Lang, S. S., & Welker, R. B. (2002) · Information Systems Research · doi:10.1287/isre.13.1.50.96 · Cited by 1,611
Anchoring Data Quality Dimensions in Ontological Foundations
Wand, Y., & Wang, R. Y. (1996) · Communications of the ACM · doi:10.1145/240455.240479 · Cited by 1,479
Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics
Devaraj, S., Fan, M., & Kohli, R. (2002) · Information Systems Research · doi:10.1287/isre.13.3.316.77 · Cited by 1,205
Chatterjee, D., Grewal, R., & Sambamurthy, V. (2002) · MIS Quarterly · doi:10.2307/4132321 · Cited by 945
Investment in Enterprise Resource Planning: Business Impact and Productivity Measures
Hitt, L. M., Wu, D. J., & Zhou, X. (2002) · Journal of Management Information Systems · doi:10.1080/07421222.2002.11045716 · Cited by 877 · cited 1×
“…most of the prior instruments were developed prompted the inclusion of new items to measure the IS function’s performance in seven new areas: ERP [51], knowledge management [45, 64, 97], electronic business [9, 55], customer relationship management [39], supply chain management [37], electronic…”
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Cited by
Evaluating E-learning systems success: An empirical study
Al-Fraihat, D., Joy, M., Masa'deh, R., & Sinclair, J. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2019.08.004 · Cited by 1,350
Corporate Sustainable Development: Testing a New Scale Based on the Mainland Chinese Context
Chow, W. S., & Chen, Y. (2012) · Journal of Business Ethics · doi:10.1007/s10551-011-0983-x · Cited by 265
Mishra, D., Luo, Z., Hazen, B., Hassini, E., & Foropon, C. (2019) · Management Decision · doi:10.1108/md-03-2018-0324 · Cited by 87
Metadata
- Authors
- CHANG, J. C.-J., & KING, W. R.
- Venue
- Journal of Management Information Systems
- Publisher
- Informa UK Limited
- Published
- 2005-04
- Volume
- 22
- Issue
- 1
- Pages
- 85-115
- ISSN
- 0742-1222 (ISSN-L)
- 1557-928X
- OpenAlex
- W1574731927
- Cited by
- 267
- References
- 17
- FWCI
- 17.08
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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