A new framework for industrial benchmarking

Gürdal Ertek, Mete Sevinç, Firdevs Ulus, Özlem Köse, Güvenç Sahin

Research output: Chapter in Book/Report/Conference proceedingChapter

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.

Original languageEnglish
Title of host publicationDecision Management
Subtitle of host publicationConcepts, Methodologies, Tools, and Applications
PublisherIGI Global
Pages2299-2314
Number of pages16
Volume4-4
ISBN (Electronic)9781522518389
ISBN (Print)1522518371, 9781522518372
DOIs
Publication statusPublished - Jan 30 2017
Externally publishedYes

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)

Fingerprint

Dive into the research topics of 'A new framework for industrial benchmarking'. Together they form a unique fingerprint.

Cite this