Combining Grey Theory and Data Envelopment Analysis to Evaluate the Business Performance of the Vietnamese Seafood Industry

(Pages 237-245)

Dac Hung Nguyen1, Xuan Huynh Nguyen2, and Thi Kim Lien Nguyen3,*
1Department of Economics, Hung Yen University of Technology and Education, Hung Yen Province 160000, Vietnam.
2Hanoi School of Business & Management, Vietnam National University, Hanoi 100000, Vietnam.
3Department of Economics-Business Administration, Thanh Dong University, Hai Duong, Hai Duong Province 171960, Vietnam


In recent years, the Vietnamese seafood industry is sharply growing up and being exported to many countries over the world. The purpose of this study is to evaluate the efficiency of Vietnamese Seafood companies, from past to future, by integration of the grey first-order single variables GM(1,1) model) using the grey theory method and the super slacked-based measure (SBM) model in the data envelopment analysis (DEA) method. First, the GM(1,1) model is used to estimate the future values of input and output variables during the period of 2021–2024. Second, the super-SBM model is implemented to discover the efficiency and position of Seafood companies from past to future. The main findings indicate that six Vietnamese seafood companies, including ABT, BLF, FMC, KHS, SJ1, and VHC obtain an efficiency score in both historical and future terms. Empirical results develop an overall picture of the seafood industry in Vietnam by means of a measurement of the operational process.


Grey first-order single variable (GM,1,1) model; Super-SBM model; Data envelopment analysis; Seafood industry; efficiency scoring.

JEL Classification:

C02- Mathematical Methods; F37 - International Finance Forecasting and Simulation: Models and Applications; L1 - Market Structure, Firm Strategy, and Market Performance.

How to Cite:

Dac Hung Nguyen, Xuan Huynh Nguyen, and Thi Kim Lien Nguyen. Combining Grey Theory and Data Envelopment Analysis to Evaluate the Business Performance of the Vietnamese Seafood Industry. [ref]: vol.19.2021. available at:

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