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Data Mining Approach to Assessment of the ERP System from the Vendor’s Perspective

  • Conference paper
Information Technology for Management

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 243))

Abstract

The paper presents an approach to analysis and assessment of benefits brought by an implementation of an Enterprise Resource Planning system. The research has been conducted on a sample of 10 Polish companies using the Xpertis software, which is one of the popular applications for supporting the business activities of small and medium companies. The approach presented hereby aims at elaboration of the assessment method which can be easily applied by the software vendor, moreover it is acceptable by the customers because it does not disclose the confidential business information and still gives the results informative enough to be valuable as well for the software company as for its customers. Analysis conducted through the Orange Data Mining tool was described. The comparative study of the Xpertis ERP features and the customers’ characteristics has been briefly presented and the directions of the future development of the considered software have been proposed.

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Notes

  1. 1.

    Software developed by Bioinformatics Lab at University of Ljubljana, Slovenia, in collaboration with open source community http://orange.biolab.si/.

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Acknowledgments

The survey prepared is a collaborative effort. Therefore the author thanks Cezary Stępniak, Częstochowa University of Technology, Poland, for the idea of the research and cooperation on preparation of the survey questionnaire. The author would like to thank Janusz Jakóbczak consultant to the Management Board of Macrologic Inc. for consulting the survey questionnaire, gathering data and his comments to the draft of the paper.

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Correspondence to Ilona Pawełoszek .

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Pawełoszek, I. (2016). Data Mining Approach to Assessment of the ERP System from the Vendor’s Perspective. In: Ziemba, E. (eds) Information Technology for Management. Lecture Notes in Business Information Processing, vol 243. Springer, Cham. https://doi.org/10.1007/978-3-319-30528-8_8

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  • DOI: https://doi.org/10.1007/978-3-319-30528-8_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30527-1

  • Online ISBN: 978-3-319-30528-8

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