Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/4763
Title: An Application for Selecting and Evaluating Organization Based KPIs with Fuzzy MCDM in a Large-Scale Organization Operating in the IT Sector
Authors: Yel, İ.
Baysal, M.E.
Sarucan, A.
Keywords: Fuzzy MCDM
IT Organizations
KPI Selection
Benchmarking
Information systems
Information use
Expert opinion
Fuzzy MCDM
Information technology departments
Information technology industry
Information technology organization
Information technology sector
KPI selection
Large-scales
Literature reviews
Multidimensional problems
Human resource management
Publisher: Springer Science and Business Media Deutschland GmbH
Abstract: In today's world, where many people use the outputs of the Information Technologies (IT) industry, it has become a problem for large-scale organizations to compare their IT departments objectively. The use of fuzzy MCDM methods for such a multidimensional problem is evaluated within the scope of this study. As a first step, twenty KPIs were determined by literature review and expert opinion to evaluate organizational units. Subsequently, KPI selection criteria were defined based on the opinions of ten expert personnel working in Architecht Information Systems for the selection of the most appropriate KPIs. These criteria are weighted by the fuzzy AHP method. Eight of the KPIs over the Neutrosophic Z Number (NZN) sets were selected for comparison by the same experts. Four different organizations were ranked by scoring over eight KPIs. It has been confirmed that the results of objective evaluations, instead of subjective evaluations, are more embraced by employees and managers, according to the outputs of the common sense and the infrastructural suitability of the institution. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Description: Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference -- 22 August 2023 through 24 August 2023 -- -- 299549
URI: https://doi.org/10.1007/978-3-031-39777-6_53
https://hdl.handle.net/20.500.13091/4763
ISBN: 9783031397769
ISSN: 2367-3370
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections

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