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Empirical Results for Application Landscape Complexity

Schneider, Alexander W. and Reschenhofer, Thomas and Schütz, Alexander and Matthes, Florian (2015):
Empirical Results for Application Landscape Complexity.
In: 48th Hawaii International Conference on System Science (HICSS), Kauai, USA, January 5-8, 2015, [Conference or Workshop Item]

Abstract

The complexity of application landscapes (AL) has been identified as one of the major challenges in enterprise architecture (EA) management for quite some time. Since there is no agreed upon definition of the term complexity in general or in the context of EA management in particular, literature offers a broad variety of concepts and measurements. Therefore, the main purpose of this paper is to (1) provide an overview about metrics to quantify the complexity of ALs proposed in literature, (2) identify metrics currently used in practice to measure AL complexity, and (3) compare empirical results and assess the metrics’ applicability with industry experts. By the assessment of four different ALs from the financial sector, we are able to derive various strengths and weaknesses for the different metrics as well as open issues for future research on quantitative EA models.

Item Type: Conference or Workshop Item
Erschienen: 2015
Creators: Schneider, Alexander W. and Reschenhofer, Thomas and Schütz, Alexander and Matthes, Florian
Title: Empirical Results for Application Landscape Complexity
Language: English
Abstract:

The complexity of application landscapes (AL) has been identified as one of the major challenges in enterprise architecture (EA) management for quite some time. Since there is no agreed upon definition of the term complexity in general or in the context of EA management in particular, literature offers a broad variety of concepts and measurements. Therefore, the main purpose of this paper is to (1) provide an overview about metrics to quantify the complexity of ALs proposed in literature, (2) identify metrics currently used in practice to measure AL complexity, and (3) compare empirical results and assess the metrics’ applicability with industry experts. By the assessment of four different ALs from the financial sector, we are able to derive various strengths and weaknesses for the different metrics as well as open issues for future research on quantitative EA models.

Divisions: 01 Department of Law and Economics
01 Department of Law and Economics > Betriebswirtschaftliche Fachgebiete
01 Department of Law and Economics > Betriebswirtschaftliche Fachgebiete > Information Systems
01 Department of Law and Economics > Betriebswirtschaftliche Fachgebiete > Fachgebiet Software Business & Information Management
Event Title: 48th Hawaii International Conference on System Science (HICSS)
Event Location: Kauai, USA
Event Dates: January 5-8, 2015
Date Deposited: 09 Oct 2014 09:24
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