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Enterprise architecture management for small and medium sized enterprises: a case study and tool support

Author

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  • M. BERNAERT

    ()

  • D. VAN DEN POEL

    ()

Abstract

Enterprise architecture (EA) is used as a holistic approach to keep things aligned in a company. Some emphasize the use of EA to align IT with the business, others see it broader and use it to also keep the processes aligned with the strategy. Enterprise architecture management (EAM) enables companies to keep up with a rapidly changing business environment. Although a lot of research is being done on EA and EAM, still hardly anything is known about their use in the context of a small and medium sized enterprise (SME). Because of some specific characteristics of SMEs, it is interesting to look how EA and its management can be applied in a SME. In this paper, the authors present an approach for EA and EAM for SMEs, which combines four dimensions to get a holistic overview, while keeping things aligned. The approach is developed with special attention towards the characteristics of SMEs. A case study in a Belgian SME is used to ground and apply the presented approach. With this case study, the authors show how EA can be applied and managed in a SME. A tool is presented which can be used to implement the approach. The tool enables the EA model to be developed, to be kept up-to-date, and to be used to make analyses.

Suggested Citation

  • M. Bernaert & D. Van Den Poel, 2012. "Enterprise architecture management for small and medium sized enterprises: a case study and tool support," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/789, Ghent University, Faculty of Economics and Business Administration.
  • Handle: RePEc:rug:rugwps:12/789
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    File URL: http://wps-feb.ugent.be/Papers/wp_12_789.pdf
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    References listed on IDEAS

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    1. Bart J. Bronnenberg & Vijay Mahajan, 2001. "Unobserved Retailer Behavior in Multimarket Data: Joint Spatial Dependence in Market Shares and Promotion Variables," Marketing Science, INFORMS, vol. 20(3), pages 284-299, October.
    2. P. Baecke & D. Van Den Poel, 2010. "Improving purchasing behavior predictions by data augmentation with situational variables," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 10/658, Ghent University, Faculty of Economics and Business Administration.
    3. D. Thorleuchter & D. Van Den Poel & A. Prinzie, 2011. "Analyzing existing customers’ websites to improve the customer acquisition process as well as the profitability prediction in B-to-B marketing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/733, Ghent University, Faculty of Economics and Business Administration.
    4. Wagner Kamakura & Carl Mela & Asim Ansari & Anand Bodapati & Pete Fader & Raghuram Iyengar & Prasad Naik & Scott Neslin & Baohong Sun & Peter Verhoef & Michel Wedel & Ron Wilcox, 2005. "Choice Models and Customer Relationship Management," Marketing Letters, Springer, vol. 16(3), pages 279-291, December.
    5. Sangkil Moon & Gary J. Russell, 2008. "Predicting Product Purchase from Inferred Customer Similarity: An Autologistic Model Approach," Management Science, INFORMS, vol. 54(1), pages 71-82, January.
    6. Coussement, Kristof & Benoit, Dries Frederik & Van den Poel, Dirk, 2009. "Improved Marketing Decision Making in a Customer Churn Prediction Context Using Generalized Additive Models," Working Papers 2009/18, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
    7. Kuenzel, Johanna & Musters, Pieter, 2007. "Social interaction and low involvement products," Journal of Business Research, Elsevier, vol. 60(8), pages 876-883, August.
    8. P. Baecke & D. Van Den Poel, 2009. "Data Augmentation by Predicting Spending Pleasure Using Commercially Available External Data," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/596, Ghent University, Faculty of Economics and Business Administration.
    9. Bearden, William O & Etzel, Michael J, 1982. " Reference Group Influence on Product and Brand Purchase Decisions," Journal of Consumer Research, Oxford University Press, vol. 9(2), pages 183-194, September.
    10. David Bell & Sangyoung Song, 2007. "Neighborhood effects and trial on the internet: Evidence from online grocery retailing," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 361-400, December.
    11. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    12. repec:cai:popine:popu_p1998_10n1_0071 is not listed on IDEAS
    13. Eric Bradlow & Bart Bronnenberg & Gary Russell & Neeraj Arora & David Bell & Sri Duvvuri & Frankel Hofstede & Catarina Sismeiro & Raphael Thomadsen & Sha Yang, 2005. "Spatial Models in Marketing," Marketing Letters, Springer, vol. 16(3), pages 267-278, December.
    14. Thomas J. Steenburgh & Andrew Ainslie & Peder Hans Engebretson, 2003. "Massively Categorical Variables: Revealing the Information in Zip Codes," Marketing Science, INFORMS, vol. 22(1), pages 40-57, August.
    15. K. Coussement & D.F. Benoît & D. Van den Poel, 2010. "Improved marketing decision making in a customer churn prediction context using generalized additive models," Post-Print halshs-00581701, HAL.
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    Keywords

    Enterprise architecture management Small and medium sized enterprises Business architecture CHOOSE;

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