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

Year 2026, Volume: 10 Issue: 1 , 61 - 74 , 20.04.2026

Gültekin Çağıl , Tuğba Şahin

https://izlik.org/JA52SS55LN

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

Authorized service centers , Beta regression , Bootstrap DEA , Cluster analysis , Data envelopment analysis

References

• 1. Charnes, A., W.W. Cooper and E. Rhodes, Measuring the Efficiency of Decision Making Units, European Journal of Operational Research, 1978. 2(6).
• 2. Selim, S. and S.A. Bursalıoğlu, Efficiency of Higher Education in Turkey: A Bootstrapped Two-Stage DEA Approach, International Journal of Statistics and Applications, 2015. 5(2).
• 3. CHAABOUNI, Sami. China's regional tourism efficiency: A two-stage double bootstrap data envelopment analysis. Journal of destination marketing & management, 2019. 11: 183-191.
• 4. Varabyova, Y. and J. Schreyögg, International Comparisons of the Technical Efficiency of the Hospital Sector: Panel Data Analysis of OECD Countries Using Parametric and Non-Parametric Approaches, Health Policy, 2013. 112(1–2).
• 5. Simar, L. and P.W. Wilson, Estimation and Inference in Two-Stage, Semi-Parametric Models of Production Processes, Journal of Econometrics, 2007. 136(1).
• 6. Danquah, R., S.K. Nelson, C.N. Nweze, P.D. Sumo, L.O. Achaa and I. Arhin, Performance of the African Stock Market Amid COVID-19 Global Health Crisis: Empirical Analysis Using Four Events, Global Business and Economics Review, 2023. 28(2).
• 7. ALSAYEGH, Maha Faisal; ABDUL RAHMAN, Rashidah; HOMAYOUN, Saeid. Corporate sustainability performance and firm value through investment efficiency. Sustainability, 2022. 15(1): 305.
• 8. WANKE, Peter; BARROS, C. P.; FIGUEIREDO, Otávio. Efficiency and productive slacks in urban transportation modes: A two-stage SDEA-Beta Regression approach. Utilities Policy, 2016. 41: p. 31-39.
• 9. ABLANEDO-ROSAS, Jose Humberto, et al. Operational efficiency of Mexican water utilities: Results of a double-bootstrap data envelopment analysis. Water, 2020. 12(2): 553.
• 10. KOUNETAS, Kostas; PAPATHANASSOPOULOS, Fotis. How efficient are Greek hospitals? A case study using a double bootstrap DEA approach. The European Journal of Health Economics, 2013. 14: p. 979-994.
• 11. LI, Yang, et al. Bootstrapped DEA and clustering analysis of eco-Efficiency in China’s hotel industry. Sustainability, 2022. 14(5): 2925.
• 12. FUKUYAMA, Hirofumi; TSIONAS, Mike; TAN, Yong. Dynamic network data envelopment analysis with a sequential structure and behavioural-causal analysis: application to the Chinese banking industry. European Journal of Operational Research, 2023. 307(3): p. 1360-1373.
• 13. YEN, Barbara TH; MULLEY, Corinne; YEH, Chia-Jung. Performance evaluation for demand responsive transport services: A two-stage bootstrap-DEA and ordinary least square approach. Research in Transportation Business & Management, 2023. 46: 100869.
• 14. WOHLGEMUTH, Murilo, et al. Assessment of the technical efficiency of Brazilian logistic operators using data envelopment analysis and one inflated beta regression. Annals of Operations Research, 2020. 286(1): p. 703-717.
• 15. DIA, Mohamed; TAKOUDA, Pawoumodom M.; GOLMOHAMMADI, Amirmohsen. Assessing the performance of Canadian credit unions using a three-stage network bootstrap DEA. Annals of Operations Research, 2022, 311.2: 641-673.
• 16. Ablanedo-Rosas, J. H., & Guerrero Campanur, A. Operational efficiency of Mexican water utilities: Results of a double-bootstrap DEA analysis. Water, 2020. 12(2): 553.
• 17. Benito, B., & Solana, J. . Determinants of Spanish regions' tourism performance: A two-stage, double-bootstrap DEA analysis. Tourism Economics, 2014 20(5): p. 987–1004.
• 18. Dikgang, J., Mahabir, J., & Samkange, C. . Efficiency of South African water utilities: A double bootstrap DEA analysis. Economic Research Southern Africa, 2019. 794.
• 19. Dey, B. K., Paul, U. K., & Das, G. . Are handloom micro-enterprises in India efficient? Estimation based on DEA and bootstrap truncated regression approach. Research Journal of Textile and Apparel, 2023. 27(2): p. 167–183.
• 20. Fries, C. E., & Sant’Anna, Â. M. O. . Assessment of the technical efficiency of Brazilian logistic operators using DEA and one-inflated beta regression. Annals of Operations Research, 202. 287(1–2): p.393–415.
• 21. Kang, I. G. . Classification and performance analysis of innovation in Korean service enterprises using clustering and DEA. Journal of Service Science, 2021. 13(2): p. 25–40.
• 22. Li, Y., Liu, A. C., Wang, S. M., Zhan, Y., Chen, J., & Hsiao, H. F. . A study of total-factor energy efficiency for regional sustainable development in China: An application of bootstrapped DEA and clustering approach. Energies, 2022. 15(9): 3093.
• 23. Li, Y., Liu, A. C., Yu, Y. Y., Zhang, Y., Zhan, Y., & Lin, W. C. . Bootstrapped DEA and clustering analysis of eco-efficiency in China’s hotel industry. Sustainability, 2022. 14(5): 2925.
• 24. Liu, Y., & Zhou, X. . Cluster-based efficiency analysis using bootstrapped DEA in manufacturing industries. Journal of Cleaner Production, 2021. 297: 126627.
• 25. Samkange, C. M. . Efficiency of water service providers in South Africa: A double-bootstrap DEA analysis. Doctoral dissertation, University of Johannesburg, 2019.
• 26. Wong, K., & Chen, H. . Two-stage DEA and clustering for service innovation efficiency: Evidence from Asian financial services. Journal of Productivity Analysis, 2023. 59(2): p. 183–204.
• 27. Singh, H. P., et al. . Bias-corrected DEA efficiency and environmental performance: Evidence from Asian economies. Environmental Economics and Policy Studies, 2020. 22(3): p. 427–449.
• 28. Shafi, I., Chaudhry, M., Montero, E. C., & Alvarado, E. S. A review of approaches for rapid data clustering: Challenges, opportunities and future directions. IEEE Access, 2024. 12: p. 12456–12480.
• 29. Paparrizos, J., Yang, F., & Li, H. . Bridging the gap: A decade review of time-series clustering methods. arXiv preprint arXiv, 2024. 2412.20582.
• 30. Nezamabadi, K., Sardaripour, N., & Haghi, B. Unsupervised ECG analysis: A review. IEEE Reviews in Biomedical Engineering, 2022. 15: p. 1–18.
• 31. Chaudhry, M., Shafi, I., Mahnoor, M., & Vargas, D. L. R. . A systematic literature review on identifying patterns using unsupervised clustering algorithms: A data mining perspective. Symmetry, 2023. 15(9): 1679.
• 32. Lyeonov, S., Podosynnikov, S., & Strielkowski, W. . Does a reliable electricity grid connection matter for the development of European renewable energy startups? Energy Policy, 2025. 192: 113243.
• 33. Cribari-Neto, F., & Zeileis, A. . Beta regression in R. Journal of Statistical Software, 2010. 34(2): p. 1–24. 34. Prasetyo, R. B., Kuswanto, H., Iriawan, N., & Ulama, B. S. S. . Binomial regression models with a flexible generalized logit link function. Symmetry, 2020. 12(2): 221.