Efficiency benchmarking based on data envelopment analysis: a case for Turkish textile sector

Erdumlu, Nazan

doi:10.1080/00405000.2015.1061737

Cited by 7 publications

(3 citation statements)

References 17 publications

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“…This approach reduced the efficiency scores of DMUs. Erdumlu [16] compared the profitability and marketability efficiency of Turkish textile, apparel and leather sector with food, beverages and tobacco, and chemicals, petroleum, rubber and plastics using DEA. Lin and Yahalom [17] used DEA with Slacks-Based Measure (SBM) model to analyze the efficiency of 46 textile firms trading in the Taiwan stock market before the 2007 financial crisis firms' operating performance and they offered about improvement areas for the firms.…”

Section: Literature Reviewmentioning

confidence: 99%

Analyzing Efficiency and Productivity Changes of Turkish Textile Firms

AVŞAR¹,

Belgin²

2023

Teksti̇l Ve Konfeksi̇yon

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This study addresses the analyzing of efficiency and productivity change of 19 Turkish textile firms for the period 2014-2020 which are quoted to stock market. For the efficiency analysis super-efficiency DEA model is employed which contains three inputs and two outputs. The efficiency results are given in yearly base. For productivity analysis stage Malmquist Productivity Index is used including TECI, TCI and TFPI values. According to results, none of the firms increased their total factor productivity through 2014 to 2020. Furthermore, there isn’t any significant difference between the average of efficiency, TECI, TCI and TFPI values before and during COVID-19 pandemic. This study contributes to the literature with covering seven-year period including COVID-19 pandemic period in the analyses.

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Section: Literature Reviewmentioning

confidence: 99%

Analyzing Efficiency and Productivity Changes of Turkish Textile Firms

AVŞAR¹,

Belgin²

2023

Teksti̇l Ve Konfeksi̇yon

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“…In the studies using DEA, which were mainly concentrated on the performance evaluation of textile, apparel, and apparel retail companies, the efficiencies were usually calculated by using some financial ratios or default parameters such as "capital" and "amount of sales" as the input and output parameters respectively. 10,[53][54][55][56] The other studies investigating specific issues, such as the efficiencies of production, operational practices, and marketing activities, involved parameters that were purposefully selected to have tangible aspects. 9,12,34,57 Among a diverse set of quantitative input and output parameters, the ones regarding the assets of the suppliers, such as "number of employees," "total intangibles," and "total inventory" became the most preferred input parameters.…”

Section: Literature Reviewmentioning

confidence: 99%

An integrated framework for supplier selection and performance evaluation for apparel retail industry

Sarıçam

Yilmaz

2021

Textile Research Journal

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Supplier evaluation, including supplier selection and performance evaluation, has become a critical issue for apparel retailers within the apparel supply chain dealing with severe competition in the global market. An effective evaluation of suppliers requires considering both the quantitative and qualitative performance aspects and integrating the efficiency measurement. In an attempt to address this issue, this study proposes an integrated framework that can handle supplier selection and overall performance evaluation in a comprehensive but feasible manner. The proposed integrated framework customized for apparel retailers combines the current techniques having specific capabilities: data envelopment analysis (DEA), analytical hierarchy process (AHP), and the technique for order preference by similarity to ideal solution (TOPSIS). DEA has been used to make the overall performance evaluation, whereas AHP and TOPSIS have been used in combination to provide the quantitative data required by DEA. The proposed integrated framework was implemented and verified using numerical data gathered from a global apparel retailer. The findings revealed that suppliers can be more successful when they put a balanced effort into improving their performance in regards to the important criteria instead of concentrating on only the most important criterion. Moreover, the overall performance evaluation can be much more convenient and rewarding for apparel retailers in terms of finding out the true potential of suppliers when quantitative and qualitative data and efficiency measurements are taken into account at the same time.

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“…Gambhir and Sharma [15] used firm-level panel data about 160 companies from 2007-2008 to 2012-2013 to analyze the productivity performance of Indian textile manufacturing industries using DEA. Erdumlu [16] evaluated the efficiency of the Turkish apparel, textile, and leather sector using measure-specific DEA. Raheli et al [17] presented a two-stage nonparametric DEA model to evaluate the sustainability and energy efficiency of tomato production.…”

Section: Introductionmentioning

confidence: 99%

Productivity Benchmarking Using Analytic Network Process (ANP) and Data Envelopment Analysis (DEA)

Mazumder

Kabir

Hasin

et al. 2018

BDCC

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Measuring productivity is the systematic process for both inter- and intra-organizational comparisons. The productivity measurement can be used to control and facilitate decision-making in manufacturing as well as service organizations. This study’s objective was to develop a decision support framework by integrating an analytic network process (ANP) and data envelopment analysis (DEA) approach to tackling productivity measurement and benchmarking problems in a manufacturing environment. The ANP was used to capture the interdependency between the criteria taking into consideration the ambiguity and vagueness. The nonparametric DEA approach was utilized to determine the input-oriented constant returns to scale (CRS) efficiency of different value-adding production units and to benchmark them. The proposed framework was implemented to benchmark the productivity of an apparel manufacturing company. By applying the model, industrial managers can gain benefits by identifying the possible contributing factors that play an important role in increasing the productivity of manufacturing organizations.

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Efficiency benchmarking based on data envelopment analysis: a case for Turkish textile sector

Cited by 7 publications

References 17 publications

Analyzing Efficiency and Productivity Changes of Turkish Textile Firms

Analyzing Efficiency and Productivity Changes of Turkish Textile Firms

An integrated framework for supplier selection and performance evaluation for apparel retail industry

Productivity Benchmarking Using Analytic Network Process (ANP) and Data Envelopment Analysis (DEA)

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