Next Article in Journal
Regional Inequality in Underdeveloped Areas: A Case Study of Guizhou Province in China
Next Article in Special Issue
Using Goal-Programming to Model the Effect of Stakeholder Determined Policy and Industry Changes on the Future Management of and Ecosystem Services Provision by Ireland’s Western Peatland Forests
Previous Article in Journal
De-[Constructing] Growth
Previous Article in Special Issue
Assessing Urban Forest Structure, Ecosystem Services, and Economic Benefits on Vacant Land
Article Menu

Export Article

Open AccessArticle
Sustainability 2016, 8(11), 1139; doi:10.3390/su8111139

Applying Data Envelopment Analysis and Grey Model for the Productivity Evaluation of Vietnamese Agroforestry Industry

1
Department of Industrial Engineering and Management, Fortune University, Kaohsiung 83158, Taiwan
2
Department of Industrial Engineering and Management, National Kaohsiung University of Applied Sciences, Kaohsiung 80778, Taiwan
3
Department of Supply Chain Management, National Kaohsiung Marine University, Kaohsiung 80778, Taiwan
4
Department of Management Information Systems, National Chengchi University, Taipei 11605, Taiwan
*
Authors to whom correspondence should be addressed.
Academic Editor: Marc A. Rosen
Received: 12 June 2016 / Revised: 10 October 2016 / Accepted: 1 November 2016 / Published: 5 November 2016
(This article belongs to the Special Issue Decision Support for Forest Ecosystem Management Sustainability)
View Full-Text   |   Download PDF [1592 KB, uploaded 8 November 2016]   |  

Abstract

Agriculture and forestry play important roles in Vietnam, particularly as they contribute to the creation of food, conservation of forest resources, and improvement of soil fertility. Therefore, understanding the performances of relevant enterprises in this field contributes to the sustainable development of this country’s agroforestry industry. This research proposes a hybrid model, which includes a grey model (GM) and a Malmquist productivity index (MPI), to assess the performances of Vietnamese agroforestry enterprises over several time periods. After collecting the data of selected input and output variables for 10 Vietnam agroforestry enterprises in the period of 2011–2014, GM is used to forecast the future values of these input and output variables for the 10 agroforestry enterprises in 2015 and 2016. Following the results of GM, the MPI is used to measure the performance of these enterprises. The MPI scores showed some enterprises will become more efficient, while others will become less efficient. The proposed model gives past–present–future insights in order for decision-makers to sustain agroforestry development in Vietnam. This hybrid approach can be applied to performance analysis of other industries as well. View Full-Text
Keywords: DEA; MPI; GM; performance; agroforestry DEA; MPI; GM; performance; agroforestry
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Wang, C.-N.; Lin, H.-S.; Hsu, H.-P.; Le, V.-T.; Lin, T.-F. Applying Data Envelopment Analysis and Grey Model for the Productivity Evaluation of Vietnamese Agroforestry Industry. Sustainability 2016, 8, 1139.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top