Measuring efficiency in the Chilean wine industry: a robust DEA approach

ABSTRACT

The Chilean wine industry has been quite innovative in terms of winemaking and trading. Yet, to survive in this competitive industry, wine managers should be aware of the relevance of monitoring their performance. In this paper, we assess how the five wineries listed on the Santiago Stock Exchange of Chile are efficient while using their critical resources for making profits. Particularly, we apply data envelopment analysis (DEA) to benchmark and rank these wineries’ technical efficiency based on four inputs and one output. We use data gathered from consolidated financial statements that are prepared using estimates, judgements, and assumptions. To account for some level of ex-post adjustments in data, we evaluate these wineries’ relative efficiency using a robust DEA model, which deals with ambiguous, imprecise, and uncertain input-output parameters. We analyse several levels of variability suitable for this data source, and we evaluate how changing the conservatism level affects technical efficiency and the rankings of the wineries. We also conduct a comparison between the five Chilean wineries and nine others from the New World. As the main conclusion, we found that Chilean wineries keep their efficiency level when including international firms in the analysis.

KEYWORDS:

• Wine Industry
• data Envelopment Analysis
• robust Optimization
• monte-Carlo Simulation
• case study

JEL CLASSIFICATION:

• C15
• C61
• D81
• C14

Acknowledgments

We would like to sincerely thank the reviewers and the editor for their valuable suggestions that allowed us to improve a preliminary version of this work considerably. We also gratefully acknowledged all financial support. Mauricio Varas acknowledges the support from FONDECYT through grant 11190892. Franco Basso acknowledges the support by the Complex Engineering Systems Institute through grant CONICYT PIA/BASAL AFB180003. Raúl Pezoa thanks doctoral scholarship to CONICYT-PFCHA/Doctorado Nacional/2018-21181528.

Data availability statement

The data that support the findings of this study are available from the corresponding author, Mauricio Varas, upon email request.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Comisión Nacional de Investigación Científica y Tecnológica [2018-21181528,AFB180003]; Fondo Nacional de Desarrollo Científico y Tecnológico [11190892].