Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/3927
Title: Integrated performance evaluation method study and performance based department ranking: a case study
Authors: Şenel, Uğur Tahsin
Daneshvar Rouyendegh (B. Erdebilli), Babak
Tekin, Salih
Keywords: Performance evaluation
Balanced scorecard
Data envelopment analyze
Clustering analyze
Publisher: Springer
Source: Şenel, U. T., Rouyendegh, B. D., & Tekin, S. (2020). Integrated performance evaluation method study and performance based department ranking: a case study. SN Applied Sciences, 2(2), 281.
Abstract: Enterprise companies, which make future strategic plan, need to view overall performance. In this direction, monitoring decision-making unit (DMU) performances is a critical issue. Therefore, it should be fair and consistent performance evaluation and prepared open and clear reports. To handle with these requirements, this study focusses on establishing a comprehensive method of performance evaluations (PE). Five main stages exist as a framework of the study. Firstly, right PE tool are selected in terms of strategic frame of companies. In this study, we examine balanced scorecard (BSC) approach that considers not only financial but also non-financial topics to watch overall performance. BSC has key performance indicators (KPI) that show objectives and actualizations belonging to related DMU, and BSC also provides proper and summary reports including different perspectives. The next step is determination of KPI's weights. Analytic hierarchy process (AHP) is applied to determine KPI priorities. Because BSC evaluates DMU'S separately, it does not provide satisfied comparison among different DMU's. In here, we propose data envelopment analyses (DEA) that is linear program based non-parametric approach. However, DEA works correctly for only homogeneous DMU's. As a third step, classification process is applied to ensure homogeneity. Then, using BSC KPI's as outputs and DMU budgets as input, DEA model is run for each class. As a last step, we separate DMUs into categories using efficiency score obtained from fourth stage. To determine category numbers, Hierarchical Clustering Analyze (AHCA) method is used and group elements are selected with applying K-Means Clustering Analyze technique. At the end, a case study is given to show how developed model is applied within a company that uses only BSC tool for PE currently. It could be said that this integrated methodology is more efficient and reliable for decision-making process.
URI: https://hdl.handle.net/20.500.11851/3927
https://doi.org/10.1007/s42452-020-2092-x
ISSN: 2523-3963
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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