Assessing variations among strategic alignment factors based on industry type: Correlational and comparative study

by Matahen, Nicholas, Ph.D., CAPELLA UNIVERSITY, 2016, 136 pages; 10239954

Abstract:

Attaining the concept of fit in IT-Business strategic management has become increasingly critical as advancements in technology are forcing organizations to continuously change and transform in order to maintain competitive edge. We live in a time when technology is impacting, and transforming every industry. Organizations rely on Information Technology as an enabler to reach their business objectives. To meet these goals and objectives, organizations adopt strategic plans and recommended practices. IT-Business strategic management and alignment has been a top concern for many organizations. The main purpose of this nonexperimental quantitative research study was to investigate the relationship between strategic alignment of Information Technology (IT) and Business, and the influence of industry type on strategic alignment. The IT-Business alignment challenge remains a crucial subject to explore. This is verified by many research studies over a period of thirty years where they have repeatedly identified the lack IT-Business alignment as a ubiquitous and continuing problem. This dissertation explored two research questions, the first of which was “To what extent do communications, competency, IT governance, partnership, IT infrastructure, and skills predict the level of strategic alignment?” and the second of which was “To what extent do the relationships between communication, competency, IT governance, partnership, IT infrastructure, skills, with strategic alignment differ, based on industry type?” Within this study, the researcher assessed the predictive relationship between the indicated factors and the level of strategic alignment, and the influence of industry type on strategic alignment. The results of the ordinal logistic regression for all six predictor variables predicted level of strategic alignment. The results of the stepwise regression confirmed that all six predictor variables significantly contribute to the dependent variable and are included in the most optimal predictive model. The industry type variable was assessed using the differences in the subscale scores and showed no statistically significant differences for competency, IT governance, partnership, IT infrastructure, and skills. However, the results of the Kruskal-Wallis test for communications variable was significant.

AdviserLawrence R. Ness
SchoolCAPELLA UNIVERSITY
Source TypeDissertation
SubjectsManagement; Information technology; Computer science
Publication Number10239954

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