Measuring technical efficiency of Thai rubber production using the three-stage data envelopment analysis

https://doi.org/10.17221/19/2016-AGRICECONCitation:Parichatnon S., Maichum K., Peng K. (2018): Measuring technical efficiency of Thai rubber production using the three-stage data envelopment analysis. Agric. Econ. – Czech, 64: 227-240.
download PDF

The study investigated the technical efficiency of rubber production in Thailand. Secondary data were collected from the Thai rubber plantations in four regions from 2005 to 2014 by using a three-stage data envelopment analysis (DEA) model. The DEA was used to evaluate the technical efficiency levels and to remove undesirable environmental impacts. Furthermore, the Malmquist productivity index was used to measure the changes in the rubber production efficiency and estimate the rubber productivity trend. The findings indicate that the efficiency scores obtained using adjusted inputs in stage 3 of the DEA approach were higher than the efficiency scores in stage 1 of the DEA approach. Moreover, the results also showed that the Northern region has the worst scores of technical efficiency and declination of productivity among the four regions. However, the technical performance of the Thai rubber production has shown a good performance, an upward productivity trend, and has demonstrated the advantages of the method used. Findings from the study could provide crucial information to farmers, the Thai government, and agricultural planners for formulating effective strategies or plans to improve their technology and efficiency levels.

 

References:
Aigner Dennis, Lovell C.A.Knox, Schmidt Peter (1977): Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6, 21-37  https://doi.org/10.1016/0304-4076(77)90052-5
 
Amini S., Kazemi N., Marzban A. (2015): Evaluation of energy consumption and economic analysis for traditional and modern farms of broiler production. Biological Forum, Research Trend, 7: 905–911.
 
Areetrakul Prapawarin, Wongchai Anupong (2015): Project Analysis of the Rubber Purchasing Center in Chiang Rai. Applied Mechanics and Materials, 799-800, 1445-1449  https://doi.org/10.4028/www.scientific.net/AMM.799-800.1445
 
Asmild Mette, Paradi Joseph C., Aggarwall Vanita, Schaffnit Claire (2004): Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry. Journal of Productivity Analysis, 21, 67-89  https://doi.org/10.1023/B:PROD.0000012453.91326.ec
 
Assaf A. George, Barros Carlos Pestana, Managi Shunsuke (2011): Cost efficiency of Japanese steam power generation companies: A Bayesian comparison of random and fixed frontier models. Applied Energy, 88, 1441-1446  https://doi.org/10.1016/j.apenergy.2010.09.022
 
Avkiran Necmi K. (2009): Opening the black box of efficiency analysis: An illustration with UAE banks. Omega, 37, 930-941  https://doi.org/10.1016/j.omega.2008.08.001
 
Banker R. D., Charnes A., Cooper W. W. (1984): Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 30, 1078-1092  https://doi.org/10.1287/mnsc.30.9.1078
 
Banker Rajiv D., Morey Richard C. (1986): Efficiency Analysis for Exogenously Fixed Inputs and Outputs. Operations Research, 34, 513-521  https://doi.org/10.1287/opre.34.4.513
 
Barros Carlos Pestana, Leach Stephanie (2006): Performance evaluation of the English Premier Football League with data envelopment analysis. Applied Economics, 38, 1449-1458  https://doi.org/10.1080/00036840500396574
 
Caves Douglas W., Christensen Laurits R., Diewert W. Erwin (1982): Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers. The Economic Journal, 92, 73-  https://doi.org/10.2307/2232257
 
Chang Young-Tae, Zhang Ning, Danao Denise, Zhang Nan (2013): Environmental efficiency analysis of transportation system in China: A non-radial DEA approach. Energy Policy, 58, 277-283  https://doi.org/10.1016/j.enpol.2013.03.011
 
Charnes A., Cooper W.W., Lewin A.Y., Seiford L.M. (2013): Data Envelopment Analysis: Theory, Methodology, and Applications. Springer Science and Business Media.
 
Charnes A., Cooper W.W., Rhodes E. (1978): Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429-444  https://doi.org/10.1016/0377-2217(78)90138-8
 
Charnes A., Cooper W. W., Rhodes E. (1981): Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through. Management Science, 27, 668-697  https://doi.org/10.1287/mnsc.27.6.668
 
Chen Po-Chi, Yu Ming-Miin, Chang Ching-Cheng, Hsu Shih-Hsun (2007): Productivity change in Taiwan's farmers' credit unions: a nonparametric risk-adjusted Malmquist approach. Agricultural Economics, 36, 221-231  https://doi.org/10.1111/j.1574-0862.2007.00200.x
 
Chung William (2011): Review of building energy-use performance benchmarking methodologies. Applied Energy, 88, 1470-1479  https://doi.org/10.1016/j.apenergy.2010.11.022
 
Coelli T. (1996): A Guide to DEAP Version 2.1: A Data Envelopment Analysis (Computer Program). Department of Econometrics, University of New England, Armidale, Australia.
 
Coelli T.J., Rao D.S.P., O’Donnell C.J., Battese G.E. (2005): An Introduction to Efficiency and Productivity Analysis. Springer Science and Business Media.
 
Coelli Tim J., Rao D. S. Prasada (2005): Total factor productivity growth in agriculture: a Malmquist index analysis of 93 countries, 1980-2000. Agricultural Economics, 32, 115-134  https://doi.org/10.1111/j.0169-5150.2004.00018.x
 
Cook Wade D., Seiford Larry M. (2009): Data envelopment analysis (DEA) – Thirty years on. European Journal of Operational Research, 192, 1-17  https://doi.org/10.1016/j.ejor.2008.01.032
 
Cooper W.W., Seiford L.M., Tone K. (2006): Introduction to Data Envelopment Analysis and its Uses: With DEA-Solver Software and References. Springer Science and Business Media.
 
Cui Qiang, Li Ye (2014): The evaluation of transportation energy efficiency: An application of three-stage virtual frontier DEA. Transportation Research Part D: Transport and Environment, 29, 1-11  https://doi.org/10.1016/j.trd.2014.03.007
 
De Koeijer T.J., Wossink G.A.A., Struik P.C., Renkema J.A. (2002): Measuring agricultural sustainability in terms of efficiency: the case of Dutch sugar beet growers. Journal of Environmental Management, 66, 9-17  https://doi.org/10.1006/jema.2002.0578
 
Estache Antonio, de la Fé Beatriz Tovar, Trujillo Lourdes (2004): Sources of efficiency gains in port reform: a DEA decomposition of a Malmquist TFP index for Mexico. Utilities Policy, 12, 221-230  https://doi.org/10.1016/j.jup.2004.04.013
 
Fare R., Grosskopf S., Norris M., Zhang Z. (1994): Productivity growth, technical progress, and efficiency change in industrialized countries. American Economic Review, 84: 66–83.
 
Ferrier Gary D., Lovell C.A.Knox (1990): Measuring cost efficiency in banking. Journal of Econometrics, 46, 229-245  https://doi.org/10.1016/0304-4076(90)90057-Z
 
Fried H.O., Lovell C.K., Schmidt S.S., Yaisawarng S. (2002): Accounting for environmental effects and statistical noise in data envelopment analysis. Journal of Productivity Analysis, 17: 157–174. https://doi.org/10.1023/A:1013548723393
 
Fried H.O., Schmidt S.S., Yaisawarng S. (1999): Incorporating the operating environment into a nonparametric measure of technical efficiency. Journal of Productivity Analysis, 12: 249–267. https://doi.org/10.1023/A:1007800306752
 
Fuentes Ramón, Fuster Begoña, Lillo-Bañuls Adelaida (2016): A three-stage DEA model to evaluate learning-teaching technical efficiency: Key performance indicators and contextual variables. Expert Systems with Applications, 48, 89-99  https://doi.org/10.1016/j.eswa.2015.11.022
 
Gorman Michael F., Ruggiero John (2008): Evaluating US state police performance using data envelopment analysis. International Journal of Production Economics, 113, 1031-1037  https://doi.org/10.1016/j.ijpe.2007.12.011
 
He Feng, Zhang Qingzhi, Lei Jiasu, Fu Weihui, Xu Xiaoning (2013): Energy efficiency and productivity change of China’s iron and steel industry: Accounting for undesirable outputs. Energy Policy, 54, 204-213  https://doi.org/10.1016/j.enpol.2012.11.020
 
Ji X., Wu J., Zhu Q. (2015): Eco-design of transportation in sustainable supply chain management: a DEA-like method. Transportation Research Part D: Transport and Environment, 48: 451–459.
 
Kočišová K. (2016): Application of the DEA on the measurement of efficiency in the EU countries. Agricultural Economics (Zemědělská ekonomika), 61, 51-62  https://doi.org/10.17221/107/2014-AGRICECON
 
Kumarasinghe H., Edirisinghe J.C., Patalee M.A.B. (2012): Role of human capital in efficiency increases: evidence from a data envelopment analysis of rubber smallholdings in Gampaha district. Journal of the Rubber Research Institute of Sri Lanka, 92: 12–21.
 
Lee Boon L., Worthington Andrew C. (2016): A network DEA quantity and quality-orientated production model: An application to Australian university research services. Omega, 60, 26-33  https://doi.org/10.1016/j.omega.2015.05.014
 
Lee Jun-Yen (2007): Application of the three-stage DEA in measuring efficiency – an empirical evidence. Applied Economics Letters, 15, 49-52  https://doi.org/10.1080/13504850600675435
 
Liu John S., Lu Louis Y.Y., Lu Wen-Min, Lin Bruce J.Y. (2013): Data envelopment analysis 1978–2010: A citation-based literature survey. Omega, 41, 3-15  https://doi.org/10.1016/j.omega.2010.12.006
 
Liu Yuhang, Mu Cheng, Jiang Kui, Zhao Jingbo, Li Yunke, Zhang Lu, Li Zhengke, Lai Joshua Yuk Lin, Hu Huawei, Ma Tingxuan, Hu Rongrong, Yu Demei, Huang Xuhui, Tang Ben Zhong, Yan He (2015): A Tetraphenylethylene Core-Based 3D Structure Small Molecular Acceptor Enabling Efficient Non-Fullerene Organic Solar Cells. Advanced Materials, 27, 1015-1020  https://doi.org/10.1002/adma.201404152
 
Longpichai Onanong, Perret Sylvain Roger, Shivakoti Ganesh Prasad (2012): Role of Livelihood Capital in Shaping the Farming Strategies and Outcomes of Smallholder Rubber Producers in Southern Thailand. Outlook on Agriculture, 41, 117-124  https://doi.org/10.5367/oa.2012.0085
 
Lygnerud Kristina, Peltola-Ojala Päivi (2010): Factors impacting district heating companies’ decision to provide small house customers with heat. Applied Energy, 87, 185-190  https://doi.org/10.1016/j.apenergy.2009.05.007
 
Meeusen W., van den Broeck J. (1977): Technical efficiency and dimension of the firm: Some results on the use of frontier production functions. Empirical Economics, 2, 109-122  https://doi.org/10.1007/BF01767476
 
Mesike C. S., Esekhade T. U. (2014): Rainfall variability and rubber production in Nigeria. African Journal of Environmental Science and Technology, 8, 54-57  https://doi.org/10.5897/AJEST2013.1593
 
Mustapha N.H.N. (2011): Technical efficiency for rubber smallholders under RISDA’s supervisory system using stochastic frontier analysis. Journal of Sustainability Science and Management, 6: 156–168.
 
National Statistical Office (2016): Statistical Yearbook Thailand. National Statistical Office, Office of the Prime Minister, Bangkok, Thailand.
 
Nguyen Binh Thanh, Dang Mui Kim (2016): Temperature dependence of natural rubber productivity in the southeastern Vietnam. Industrial Crops and Products, 83, 24-30  https://doi.org/10.1016/j.indcrop.2015.12.019
 
Nomikos Nikos K., Pouliasis Panos K. (2011): Forecasting petroleum futures markets volatility: The role of regimes and market conditions. Energy Economics, 33, 321-337  https://doi.org/10.1016/j.eneco.2010.11.013
 
Nowak A., Kijek T., Domanska K. (2015): Technical efficiency and its determinants in the European Union agriculture. Agricultural Economics – Czech, 6: 275–283.
 
Odeck James (2009): Statistical precision of DEA and Malmquist indices: A bootstrap application to Norwegian grain producers. Omega, 37, 1007-1017  https://doi.org/10.1016/j.omega.2008.11.003
 
Portela M C A Silva, Thanassoulis E, Simpson G (2017): Negative data in DEA: a directional distance approach applied to bank branches. Journal of the Operational Research Society, 55, 1111-1121  https://doi.org/10.1057/palgrave.jors.2601768
 
Reig-Martı́nez Ernest, Picazo-Tadeo Andrés J (2004): Analysing farming systems with Data Envelopment Analysis: citrus farming in Spain. Agricultural Systems, 82, 17-30  https://doi.org/10.1016/j.agsy.2003.12.002
 
Rho Sangkyu, An Jungnam (2007): Evaluating the efficiency of a two-stage production process using data envelopment analysis. International Transactions in Operational Research, 14, 395-410  https://doi.org/10.1111/j.1475-3995.2007.00597.x
 
Rubber Research Institute of Thailand (2016): Thai Rubber Statistics. Ministry of Agriculture and Cooperative, Bangkok, Thailand. Available at http://www.thainr.com/en/index.php (accessed July, 2016).
 
Rubber Research Institute of Thailand (2005): Natural Rubber in Thailand. Presentation Held in the Appraisal Meeting on Improving the Productivity of Rubber Smallholdings through Rubber Agroforestry Systems, Hat Yai, Thailand.
 
Sahin Guller, Gokdemir Levent, Ozturk Dogan (2016): Global Crisis and its Effect on Turkish Banking Sector: A Study with Data Envelopment Analysis. Procedia Economics and Finance, 38, 38-48  https://doi.org/10.1016/S2212-5671(16)30174-5
 
Sdoodee S., Rongsawat S. (2012): Impact of Climate Change on Smallholders’ Rubber Production in Songkhla Province, Southern Thailand. In: Proceedings International and National Conference for the Sustainable Community Development of Local Community: The Foundation of Development in the ASEAN Economic Community (AEC).
 
Shang Jui-Kou, Hung Wei-Ting, Wang Fei-Ching (2008): Service outsourcing and hotel performance: three-stage DEA analysis. Applied Economics Letters, 15, 1053-1057  https://doi.org/10.1080/13504850600993523
 
Shrestha R.B., Huang W.-Ch., Gautam S., Johnson T.G. (2016): Efficiency of small scale vegetable farms: policy implications for the rural poverty reduction in Nepal. Agricultural Economics (Zemědělská ekonomika), 62, 181-195  https://doi.org/10.17221/81/2015-AGRICECON
 
Shwartz Michael, Burgess James F., Zhu Joe (2016): A DEA based composite measure of quality and its associated data uncertainty interval for health care provider profiling and pay-for-performance. European Journal of Operational Research, 253, 489-502  https://doi.org/10.1016/j.ejor.2016.02.049
 
Silva E., Arzubi A., Berbel J. (2013): An Application of DEA in Azores Dairy Farms. In Efficiency Measures in the Agricultural Sector, Springer Netherlands.
 
Stewart Chris, Matousek Roman, Nguyen Thao Ngoc (2016): Efficiency in the Vietnamese banking system: A DEA double bootstrap approach. Research in International Business and Finance, 36, 96-111  https://doi.org/10.1016/j.ribaf.2015.09.006
 
Tavana Madjid, Khalili-Damghani Kaveh (2014): A new two-stage Stackelberg fuzzy data envelopment analysis model. Measurement, 53, 277-296  https://doi.org/10.1016/j.measurement.2014.03.030
 
Torres-Jiménez Mercedes, García-Alonso Carlos R., Salvador-Carulla Luis, Fernández-Rodríguez Vicente (2015): Evaluation of system efficiency using the Monte Carlo DEA: The case of small health areas. European Journal of Operational Research, 242, 525-535  https://doi.org/10.1016/j.ejor.2014.10.019
 
Tsay W.J., Huang C.J., Fu T.T., Ho I.L. (2009): Maximum Likelihood Estimation of Censored Stochastic Frontier Models: An Application to the Three-Stage DEA Method. Institute of Economics, Academia Sinica, Taipei, Taiwan.
 
Tsolas Ioannis E., Charles Vincent (2015): Incorporating risk into bank efficiency: A satisficing DEA approach to assess the Greek banking crisis. Expert Systems with Applications, 42, 3491-3500  https://doi.org/10.1016/j.eswa.2014.12.033
 
Van Passel Steven, Van Huylenbroeck Guido, Lauwers Ludwig, Mathijs Erik (2009): Sustainable value assessment of farms using frontier efficiency benchmarks. Journal of Environmental Management, 90, 3057-3069  https://doi.org/10.1016/j.jenvman.2009.04.009
 
Waduge T D, Edirisnghe J C, Fernando A P S, Herath H M L K, Jayasinghe-Mudalige U K (2015): Labour and weather related risks in smallholder rubber production: evidence from Kalutara district. Tropical Agricultural Research and Extension, 16, 88-  https://doi.org/10.4038/tare.v16i3.5281
 
Wei Yi-Ming, Liao Hua, Fan Ying (2007): An empirical analysis of energy efficiency in China's iron and steel sector. Energy, 32, 2262-2270  https://doi.org/10.1016/j.energy.2007.07.007
 
Xue Xiaolong, Shen Qiping, Wang Yaowu, Lu Jinfeng (2008): Measuring the Productivity of the Construction Industry in China by Using DEA-Based Malmquist Productivity Indices. Journal of Construction Engineering and Management, 134, 64-71  https://doi.org/10.1061/(ASCE)0733-9364(2008)134:1(64)
 
Yu Haiying, Hammond Jim, Ling Shenghai, Zhou Shuangxi, Mortimer Peter Edward, Xu Jianchu (2014): Greater diurnal temperature difference, an overlooked but important climatic driver of rubber yield. Industrial Crops and Products, 62, 14-21  https://doi.org/10.1016/j.indcrop.2014.08.001
 
Zamanian G.R., Shahabinejad V., Yaghoubi M. (2013): Application of DEA and SFA on the measurement of agricultural technical efficiency in MENA countries. International Journal of Applied Operational Research, 3: 43–51.
 
download PDF

© 2021 Czech Academy of Agricultural Sciences | Prohlášení o přístupnosti