A New Framework for Industrial Benchmarking

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Author(s): Gürdal Ertek (Sabanci University, Turkey), Mete Sevinç (Sabanci University, Turkey), Firdevs Ulus (Sabanci University, Turkey), Özlem Köse (Sabanci University, Turkey)and Güvenç Şahin (Sabanci University, Turkey)
Copyright: 2017
Pages: 16
Source title: Decision Management: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-1837-2.ch108

Keywords: Business & Management / Decision Support Systems / Information Science Reference

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Abstract

The authors present a benchmarking study on the companies in the Turkish food industry based on their financial data. The aim is to develop a comprehensive benchmarking framework using Data Envelopment Analysis (DEA) and information visualization. Besides DEA, a traditional tool for financial benchmarking based on financial ratios is also incorporated. The consistency/inconsistency between the two methodologies is investigated using information visualization tools. In addition, k-means clustering, a fundamental method from machine learning, is applied. Finally, other relevant data, apart from the financial data, is introduced to the analysis through information visualization to discover new insights into DEA results. The results show that the framework developed is a comprehensive and effective strategy for benchmarking; it can be applied in other industries as well. The study contributes to the literature with a novel methodology that integrates the various benchmarking methods from the fields of operations research, machine learning, and financial analysis.

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