Enterprise architecture (EA) may be considered an organizational blueprint that helps experts manage organizational complexity. In this regard, EA analysis is an emerging field gaining greater attention, and considering EA as an intertwined system of components and relationships and performing EA analysis from a structural perspective are promising areas of research. This paper analyzes EA data from a German commercial vehicle manufacturer, modeling a subset of its EA with the help of design structural and domain mapping matrices. Thus, we propose an analysis approach based on network measures that uses structural knowledge generated by the network analysis to validate or refine experts’ tacit knowledge about EA key components from different layers. We refer to this approach as the diagnosis analysis method. Based on our results, we successfully combine the structural knowledge with expert knowledge and provide useful validations for experts.
%0 Conference Paper
%1 santana2016empirical
%A Santana, Alixandre
%A Kreimeyer, Matthias
%A Clo, Pascal
%A Fischbach, Kai
%A de Moura, Hermano
%B 18th International Dependency and Structural Modeling Conference (DSM)
%D 2016
%K 2016 IKTD PUK Tagungsbeitrag
%P 46-56
%R 10.19255/JMPM-DSM2016
%T An Empirical Investigation of Enterprise Architecture Analysis Based on Network Measures and Expert Knowledge: A Case from the Automotive Industry
%X Enterprise architecture (EA) may be considered an organizational blueprint that helps experts manage organizational complexity. In this regard, EA analysis is an emerging field gaining greater attention, and considering EA as an intertwined system of components and relationships and performing EA analysis from a structural perspective are promising areas of research. This paper analyzes EA data from a German commercial vehicle manufacturer, modeling a subset of its EA with the help of design structural and domain mapping matrices. Thus, we propose an analysis approach based on network measures that uses structural knowledge generated by the network analysis to validate or refine experts’ tacit knowledge about EA key components from different layers. We refer to this approach as the diagnosis analysis method. Based on our results, we successfully combine the structural knowledge with expert knowledge and provide useful validations for experts.
%@ 978-85-63710-01-7
@inproceedings{santana2016empirical,
abstract = {Enterprise architecture (EA) may be considered an organizational blueprint that helps experts manage organizational complexity. In this regard, EA analysis is an emerging field gaining greater attention, and considering EA as an intertwined system of components and relationships and performing EA analysis from a structural perspective are promising areas of research. This paper analyzes EA data from a German commercial vehicle manufacturer, modeling a subset of its EA with the help of design structural and domain mapping matrices. Thus, we propose an analysis approach based on network measures that uses structural knowledge generated by the network analysis to validate or refine experts’ tacit knowledge about EA key components from different layers. We refer to this approach as the diagnosis analysis method. Based on our results, we successfully combine the structural knowledge with expert knowledge and provide useful validations for experts.},
added-at = {2022-02-05T22:11:13.000+0100},
author = {Santana, Alixandre and Kreimeyer, Matthias and Clo, Pascal and Fischbach, Kai and de Moura, Hermano},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2de3ea6e9b5d34cd7d786354182b50b85/iktd_group},
booktitle = {18th International Dependency and Structural Modeling Conference (DSM)},
doi = {10.19255/JMPM-DSM2016},
eventdate = {29-30},
interhash = {682866d21e6e512c2845b0b7cd1a60ee},
intrahash = {de3ea6e9b5d34cd7d786354182b50b85},
isbn = {978-85-63710-01-7},
keywords = {2016 IKTD PUK Tagungsbeitrag},
language = {Englisch},
month = {August },
pages = {46-56},
timestamp = {2022-02-05T22:31:25.000+0100},
title = {An Empirical Investigation of Enterprise Architecture Analysis Based on Network Measures and Expert Knowledge: A Case from the Automotive Industry},
venue = {Sao Paulo, Brazil},
year = 2016
}
