Hoang Van Hung
Hung Yen University of Technology and Education (UTEHY), Hung Yen, VietnamEmail: davidhoang8585@gmail.com
Nguyen Van Huong
Hung Yen University of Technology and Education (UTEHY), Hung Yen, VietnamEmail: Vanhuong75hy@gmail.com
Le Thi Thuong
Hung Yen University of Technology and Education (UTEHY), Hung Yen, VietnamEmail: lethuongkt.utehy@gmail.com
Thai Thi Kim Oanh
Vinh University (VU), Vinh City, VietnamEmail: thaithikimoanhkt@gmail.com
Nguyen Van Chuong
University of Financial – Business Administration (UFBA), Hung Yen, Viet NamEmail: nguyenchuong.edu@gmail.com
Nguyen Cong Tiep
Viet Nam National University of Agriculture (VNUA), Ha Noi, Viet NamEmail: nctiep@vnua.edu.vn
Thai Van Ha
Ha Noi University of Business and Technology (HUBT), Vinh Tuy, Hai Ba Trung, Ha NoiEmail: vanha280182@gmail.com
Nguyen Thi Luong
Can Tho University (CTU), Can Tho City, Viet NamEmail: ntluong@ctu.edu.vn
Abstract:
Bananas are considered one of the leading trading crops due to their high demand all over the globe. Since the increasing demand leads to the expansion of global import, the existing literature is in dire need of updating, especially from the producing economies that fall in the category of developing nations. The study, thus, intends to estimate the critical efficiency of said area. Along with it, the study aims to determine the elements of banana production in the context of Vietnam using a stochastic frontier approach and technical efficiency technique. The sample of the study is the province of Vietnam named Hung Yen, and it made sure to collect the data from 160 farmers in 2022. Results of the study reveal that the farmers' technical efficiency fluctuates between the range of 89.68- 97.81%. However, the average technical efficiency of banana farmers was reported to be 95.92%. From the result, it is gauged that factors such as potassium, manure, distance, capital, and training showed positive signs at a 0.01 significance level. Also, the education and area coefficient show a positive sign at a 0.05 significance level. Finally, distance and district variables, which were the dummy variable, show a negative sign at 0.01 and 0.05 significance levels, respectively.
Keywords:Technical efficiency, productivity, and Stochastic Frontier Production Function.