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Please use this identifier to cite or link to this item: http://hdl.handle.net/10484/1170

Title: Application of Strategic Institutional-Information Technology Alignment Model in Four-Year Institutions of Higher Education
Authors: Lach-Smith, Barbara
Issue Date: 22-Sep-2010
Abstract: This study examined an existing corporate model of business-information technology alignment for application in higher education and tested the findings by surveying executive and technology leaders in higher education. The purpose of this study was to gain a better understanding of the factors that impact alignment between institutional strategic planning and information technology strategy in higher education. The existing alignment model was examined in the context of mid-size four-year colleges and universities. This study used a combination of Delphi technique and a survey process. The sequence followed was to examine an existing theoretical model for its applicability to higher education by a Delphi expert panel, to pilot test the results of the Delphi in a survey of mid-size four-year institutions of higher education and to analyze the results. In the first phase, the Delphi method was used in two rounds to examine the Strategic Alignment Model (SAM) for application in higher education. An assembled panel of experts examined SAM, its components and questionnaire instrument, and reached a consensus after two rounds about the model’s applicability to higher education. The second phase of the study tested the Delphi panel’s findings by asking Chief Information Officers and Chief Executive Officers from four-year U.S. institutions of higher education to complete SAM’s instrument that was modified by the Delphi. The Delphi panel findings supported the use of the Strategic Alignment Model in higher education with some revisions of its terms to reflect the higher education environment more accurately. Several factors affecting institutional-IT alignment in higher education were identified. Factors associated with domain components of the SAM model as well as factors relating to bivariate linkages between the components of the model were revealed.
URI: http://hdl.handle.net/10484/1170
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