On exposing strategic and structural mismatches between business and information systems: misalignment symptom detection based on enterprise architecture model analysis = Stratégiai és strukturális összehangolási zavarok feltárása az üzleti és informatikai területek között: összehangolási zavarok tüneteinek azonosítása vállalati architektúra modellek elemzésével

Őri, Dóra (2017) On exposing strategic and structural mismatches between business and information systems: misalignment symptom detection based on enterprise architecture model analysis = Stratégiai és strukturális összehangolási zavarok feltárása az üzleti és informatikai területek között: összehangolási zavarok tüneteinek azonosítása vállalati architektúra modellek elemzésével. PhD thesis, Budapesti Corvinus Egyetem, Gazdaságinformatika Doktori Iskola. DOI 10.14267/phd.2017029

[img]
Preview
PDF : (dissertation in English)
6MB
[img]
Preview
PDF : (draft in English)
1MB
[img]
Preview
PDF : (az értekezés tézisei magyar nyelven)
1MB

Abstract

One of the most important issues on information systems (IS) research is the need to align business with information systems and information technology (IT). Since information systems facilitate the success of business strategies, the importance of business-IT (or strategic) alignment is unquestionable. While organisations address alignment achievement, they are continually suffering from misalignments. These difficulties (the misalignments) encumber the achievement of alignment, and lead us to the phenomenon of misalignment. This Ph.D. dissertation deals with the concept of misalignment, with special attention on enterprise architecture (EA)-based analytical potential. The main purpose of the proposed research is to analyse strategic misalignment between the business dimension and the information systems dimension. The problem of business-IT alignment is translated into the aspects of enterprise architecture. The study aims to accomplish an EA-based, systematic analysis of mismatches between business and information systems.

Item Type:Thesis (PhD thesis)
Supervisor:Szabó Zoltán
Subjects:Knowledge economy, innovation
ID Code:964
Date:23 May 2017
DOI:10.14267/phd.2017029
Deposited On:17 May 2017 11:25
Last Modified:12 Jul 2017 11:13

Repository Staff Only: item control page

Downloads

Downloads per month over past two year

View more statistics