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Scale directional distance function and its application to the measurement of eco-efficiency in the manufacturing sector

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  • Noor Ramli
  • Susila Munisamy
  • Behrouz Arabi

Abstract

Directional distance function (DDF) is a recognized technique for measuring efficiency while incorporating undesirable outputs. This approach allows for desirable outputs to be expanded while undesirable outputs are contracted simultaneously. A drawback of the DDF approach is that the direction vector to the production boundary is fixed arbitrarily, which may not provide the best efficiency measure. Therefore, this study extends the previous framework of efficiency analysis to introduce a new slacks-based measure of efficiency called the scale directional distance function (SDDF) approach. This new approach determines the optimal direction to the frontier for each unit of analysis and provides dissimilar expansion and contraction factors to achieve a more reasonable eco-efficiency score. This new approach is employed to measure the eco-efficiency of the Malaysian manufacturing sector. In addition, the paper demonstrates the use of the new approach to establish target values for the reduction/expansion of outputs in order for the inefficient DMUs to achieve full eco-efficiency. The results indicate that Melaka, Pulau Pinang, Negeri Sembilan, Sabah, Sarawak and Labuan have attained full eco-efficiency while Terengganu is the least eco-efficient. The overall eco-efficiency of the manufacturing sector in Malaysia is 80.5 % with wide variations across the states. Copyright Springer Science+Business Media New York 2013

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  • Noor Ramli & Susila Munisamy & Behrouz Arabi, 2013. "Scale directional distance function and its application to the measurement of eco-efficiency in the manufacturing sector," Annals of Operations Research, Springer, vol. 211(1), pages 381-398, December.
    • Handle: RePEc:spr:annopr:v:211:y:2013:i:1:p:381-398:10.1007/s10479-013-1441-1
    DOI: 10.1007/s10479-013-1441-1
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    1. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency: Some clarifications," European Journal of Operational Research, Elsevier, vol. 206(3), pages 702-702, November.
    2. Arocena, Pablo & Waddams Price, Catherine, 2002. "Generating efficiency: economic and environmental regulation of public and private electricity generators in Spain," International Journal of Industrial Organization, Elsevier, vol. 20(1), pages 41-69, January.
    3. Lu, Wen-Min & Lo, Shih-Fang, 2007. "A closer look at the economic-environmental disparities for regional development in China," European Journal of Operational Research, Elsevier, vol. 183(2), pages 882-894, December.
    4. Fare, Rolf & Grosskopf, Shawna & Weber, William L., 2006. "Shadow prices and pollution costs in U.S. agriculture," Ecological Economics, Elsevier, vol. 56(1), pages 89-103, January.
    5. Jaraitė, Jūratė & Di Maria, Corrado, 2012. "Efficiency, productivity and environmental policy: A case study of power generation in the EU," Energy Economics, Elsevier, vol. 34(5), pages 1557-1568.
    6. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    7. Gongbing Bi & Yan Luo & Jingjing Ding & Liang Liang, 2015. "Environmental performance analysis of Chinese industry from a slacks-based perspective," Annals of Operations Research, Springer, vol. 228(1), pages 65-80, May.
    8. Riccardi, R. & Oggioni, G. & Toninelli, R., 2012. "Efficiency analysis of world cement industry in presence of undesirable output: Application of data envelopment analysis and directional distance function," Energy Policy, Elsevier, vol. 44(C), pages 140-152.
    9. Joseph Sarkis & Srinivas Talluri, 2004. "Ecoefficiency Measurement Using Data Envelopment Analysis: Research And Practitioner Issues," Journal of Environmental Assessment Policy and Management (JEAPM), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 91-123.
    10. Wu, Jie & An, Qingxian & Xiong, Beibei & Chen, Ya, 2013. "Congestion measurement for regional industries in China: A data envelopment analysis approach with undesirable outputs," Energy Policy, Elsevier, vol. 57(C), pages 7-13.
    11. Aiken, Deborah Vaughn & Pasurka, Carl Jr., 2003. "Adjusting the measurement of US manufacturing productivity for air pollution emissions control," Resource and Energy Economics, Elsevier, vol. 25(4), pages 329-351, October.
    12. Watanabe, Michio & Tanaka, Katsuya, 2007. "Efficiency analysis of Chinese industry: A directional distance function approach," Energy Policy, Elsevier, vol. 35(12), pages 6323-6331, December.
    13. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    14. Wu, F. & Fan, L.W. & Zhou, P. & Zhou, D.Q., 2012. "Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis," Energy Policy, Elsevier, vol. 49(C), pages 164-172.
    15. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Slacks-based efficiency measures for modeling environmental performance," Ecological Economics, Elsevier, vol. 60(1), pages 111-118, November.
    16. Ball, V. Eldon & Lovell, C.A. Knox & Luu, H. & Nehring, Richard F., 2004. "Incorporating Environmental Impacts in the Measurement of Agricultural Productivity Growth," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(3), pages 1-25, December.
    17. Jajri, Idris & Ismail, Rahmah, 2006. "Technical efficiency, technological change and total factor productivity growth in Malaysian manufacturing sector," MPRA Paper 1956, University Library of Munich, Germany.
    18. Timo Kuosmanen, 2005. "Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1077-1082.
    19. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    20. Kumar Mandal, Sabuj & Madheswaran, S., 2010. "Environmental efficiency of the Indian cement industry: An interstate analysis," Energy Policy, Elsevier, vol. 38(2), pages 1108-1118, February.
    21. Joseph Sarkis, 2006. "The adoption of environmental and risk management practices: Relationships to environmental performance," Annals of Operations Research, Springer, vol. 145(1), pages 367-381, July.
    22. Dyckhoff, H. & Allen, K., 2001. "Measuring ecological efficiency with data envelopment analysis (DEA)," European Journal of Operational Research, Elsevier, vol. 132(2), pages 312-325, July.
    23. Wei, Quanling & Yan, Hong, 2004. "Congestion and returns to scale in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 153(3), pages 641-660, March.
    24. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    25. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    26. Elsadig Musa Ahmed, 2007. "The Impact of Biochemical Oxygen Demand Emissions on Malaysia's Manufacturing Productivity Growth," Global Economic Review, Taylor & Francis Journals, vol. 36(4), pages 305-319.
    27. Zbigniew Nahorski & Hans Ravn, 2000. "A review of mathematical models in economic environmental problems," Annals of Operations Research, Springer, vol. 97(1), pages 165-201, December.
    28. Wang, Qunwei & Zhou, Peng & Zhou, Dequn, 2012. "Efficiency measurement with carbon dioxide emissions: The case of China," Applied Energy, Elsevier, vol. 90(1), pages 161-166.
    29. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
    30. Sueyoshi, Toshiyuki & Goto, Mika & Ueno, Takahiro, 2010. "Performance analysis of US coal-fired power plants by measuring three DEA efficiencies," Energy Policy, Elsevier, vol. 38(4), pages 1675-1688, April.
    31. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    32. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    33. Pittman, Russell W, 1983. "Multilateral Productivity Comparisons with Undesirable Outputs," Economic Journal, Royal Economic Society, vol. 93(372), pages 883-891, December.
    34. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    35. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "Economic growth and environmental efficiency: Evidence from US regions," Economics Letters, Elsevier, vol. 120(1), pages 48-52.
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