Evaluating performance of white goods services using DEA, beta regression, and cluster analysis

Gültekin Çağıl; Tuğba Şahin

doi:10.35860/iarej.1722670

Evaluating performance of white goods services using DEA, beta regression, and cluster analysis

Abstract

This study adopts an integrated quantitative framework that combines Data Envelopment Analysis (DEA), bootstrap methods, beta regression, and cluster analysis to assess the performance of authorized service centers in the white goods industry. Initially, traditional DEA was applied to estimate relative efficiency levels, after which a bootstrap-enhanced DEA was utilized to improve the robustness of the efficiency measures by mitigating sample sensitivity. Given that the efficiency outcomes followed a continuous distribution between 0 and 1, beta regression was employed as a suitable modeling technique to identify and evaluate the determinants of service performance, yielding statistically significant insights while effectively addressing issues such as heteroscedasticity and skewness that often challenge linear models. Building on these results, cluster analysis was conducted to classify service centers into groups with similar performance profiles, highlighting meaningful distinctions among clusters in areas such as strategic planning, resource utilization, and service quality. The findings from the clustering and determinant analysis offer actionable managerial recommendations, suggesting that high-performing clusters should be benchmarked for resource optimization and targeted quality improvement initiatives.

Keywords

References

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Details

Primary Language

English

Subjects

Industrial Engineering

Journal Section

Research Article

Authors

Gültekin Çağıl
0000-0001-8609-6178
Türkiye

Tuğba Şahin ^*
0009-0007-2271-2825
Türkiye

Publication Date

April 20, 2026

Submission Date

June 18, 2025

Acceptance Date

February 16, 2026

Published in Issue

Year 2026 Volume: 10 Number: 1

DOI

https://doi.org/10.35860/iarej.1722670

IZ

https://izlik.org/JA52SS55LN

Cite

RIS / Bibtex

APA

Çağıl, G., & Şahin, T. (2026). Evaluating performance of white goods services using DEA, beta regression, and cluster analysis. International Advanced Researches and Engineering Journal, 10(1), 61-74. https://doi.org/10.35860/iarej.1722670

AMA

1.Çağıl G, Şahin T. Evaluating performance of white goods services using DEA, beta regression, and cluster analysis. Int. Adv. Res. Eng. J. 2026;10(1):61-74. doi:10.35860/iarej.1722670

Chicago

Çağıl, Gültekin, and Tuğba Şahin. 2026. “Evaluating Performance of White Goods Services Using DEA, Beta Regression, and Cluster Analysis”. International Advanced Researches and Engineering Journal 10 (1): 61-74. https://doi.org/10.35860/iarej.1722670.

EndNote

Çağıl G, Şahin T (April 1, 2026) Evaluating performance of white goods services using DEA, beta regression, and cluster analysis. International Advanced Researches and Engineering Journal 10 1 61–74.

IEEE

[1]G. Çağıl and T. Şahin, “Evaluating performance of white goods services using DEA, beta regression, and cluster analysis”, Int. Adv. Res. Eng. J., vol. 10, no. 1, pp. 61–74, Apr. 2026, doi: 10.35860/iarej.1722670.

ISNAD

Çağıl, Gültekin - Şahin, Tuğba. “Evaluating Performance of White Goods Services Using DEA, Beta Regression, and Cluster Analysis”. International Advanced Researches and Engineering Journal 10/1 (April 1, 2026): 61-74. https://doi.org/10.35860/iarej.1722670.

JAMA

1.Çağıl G, Şahin T. Evaluating performance of white goods services using DEA, beta regression, and cluster analysis. Int. Adv. Res. Eng. J. 2026;10:61–74.

MLA

Çağıl, Gültekin, and Tuğba Şahin. “Evaluating Performance of White Goods Services Using DEA, Beta Regression, and Cluster Analysis”. International Advanced Researches and Engineering Journal, vol. 10, no. 1, Apr. 2026, pp. 61-74, doi:10.35860/iarej.1722670.

Vancouver

1.Gültekin Çağıl, Tuğba Şahin. Evaluating performance of white goods services using DEA, beta regression, and cluster analysis. Int. Adv. Res. Eng. J. 2026 Apr. 1;10(1):61-74. doi:10.35860/iarej.1722670