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

Annals of Operations Research

Volumn 211, Issue 1, 2013, Pages 381-398

  Ramli, Noor Asiah ^a,b   Munisamy, Susila ^a   Arabi, Behrouz ^a  

^a UNIVERSITY OF MALAYA   (Malaysia)

^b UNIVERSITI TEKNOLOGI MARA   (Malaysia)

Author keywords

Data envelopment analysis (DEA); Directional distance function (DDF); Eco efficiency; Scale directional distance function (SDDF); Undesirable output

Indexed keywords

EID: 84890125110     PISSN: 02545330     EISSN: 15729338     Source Type: Journal    
DOI: 10.1007/s10479-013-1441-1     Document Type: Article

References (61)

1. Ahmed, E. M. (2006). Carbon dioxide emissions, impact on Malaysia's manufacturing productivity growth. World Review of Science, Technology and Sustainable Development, 3, 58-69.
2. Ahmed, E. M. (2007). The impact of biochemical oxygen demand emissions on Malaysia's manufacturing productivity growth. Global Economic Review, 36, 305-319.
3. Aiken, D. V., & Pasurka, C. A. (2003). Adjusting the measurement of US manufacturing productivity for air pollution emissions control. Resource and Energy Economics, 25, 329-351.
4. Arocena, P., & Waddams Price, C. (2002). Generating efficiency: economic and environmental regulation of public and private electricity generators in Spain. International Journal of Industrial Organization, 20, 41-69.
5. Ball, V. E., Lovell, C. A. K., Luu, H., & Nehring, R. (2004). Incorporating environmental impacts in the measurement of agricultural productivity growth. Journal of Agricultural and Resource Economics, 29, 436.
6. Beltrán-Esteve, M., Gómez-Limón, J. A., Picazo-Tadeo, A. J., & Reig-Martínez, E. (2013). A metafrontier directional distance function approach to assessing eco-efficiency. Journal of Productivity Analysis. doi: 10. 1007/s11123-012-0334-7.
7. Bi, G., Luo, Y., Ding, J., & Liang, L. (2012). Environmental performance analysis of Chinese industry from a slacks-based perspective. Annals of Operations Research. doi: 10. 1007/s10479-012-1088-3.
8. Bian, Y. (2008). Efficiency evaluation with undesirable factors based on DEA. In 4th international conference on wireless communications, networking and mobile computing (pp. 1-5).
9. Borhan, H., & Ahmed, E. M. (2012). Green environment: assessment of income and water pollution in Malaysia. Procedia-Social and Behavioral Sciences, 42, 166-174.
10. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2, 429-444.
11. 2 emissions in China: a slacks-based efficiency measure. Applied Energy, 98, 198-208.
12. Chung, Y. H., Färe, R., & Grosskopf, S. (1997). Productivity and undesirable outputs: a directional distance function approach. Journal of Environmental Management, 51, 229-240.
13. Coli, M., Nissi, E., & Rapposelli, A. (2011). Monitoring environmental efficiency: an application to Italian provinces. Environmental Modelling & Software, 26(1), 38-43.
14. Debreu, G. (1951). The coefficient of resource utilization. Econometrica: Journal of the Econometric Society, 19(3), 273-292.
15. Department of Statistics, Malaysia (2008). Compendium of environment statistics. Putrajaya: Department of Statistics Malaysia.
16. Dyckhoff, H., & Allen, K. (2001). Measuring ecological efficiency with data envelopment analysis (DEA). European Journal of Operational Research, 132, 312-325.
17. Eggleston, S., Buendia, L., Miwa, K., Ngara, T., & Tanabe, K. (2006). IPCC guidelines for national greenhouse gas inventories. Genova: Intergovernmental Panel on Climate Change.
18. Färe, R., & Grosskopf, S. (2005). New directions: efficiency and productivity. Berlin: Springer.
19. Färe, R., & Grosskopf, S. (2010a). Directional distance functions and slacks-based measures of efficiency. European Journal of Operational Research, 200, 320-322.
20. Färe, R., & Grosskopf, S. (2010b). Directional distance functions and slacks-based measures of efficiency: some clarifications. European Journal of Operational Research, 206, 702.
21. Färe, R., Grosskopf, S., Lovell, C. A. K., & Pasurka, C. (1989). Multilateral productivity comparisons when some outputs are undesirable: a non-parametric approach. Review of Economics and Statistics, 71, 90-98.
22. Färe, R., Grosskopf, S., Noh, D.-W., & Weber, W. (2005). Characteristics of a polluting technology: theory and practice. Journal of Econometrics, 126, 469-492.
23. Färe, R., Grosskopf, S., & Weber, W. L. (2006). Shadow prices and pollution costs in U. S. agriculture. Ecological Economics, 56, 89-103.
24. Färe, R., & Primont, D. (1995). Multi-output production and duality: theory and applications. Berlin: Springer.
25. Halkos, G. E., & Tzeremes, N. G. (2013). Economic growth and environmental efficiency: evidence from US regions. Economics Letters, 120, 48-52.
26. Hua, Z., & Bian, Y. (2007). Modeling data irregularities and structural complexities in data envelopment analysis. Berlin: Springer.
27. International Energy Agency (2009). Key world energy statistics. Paris: International Energy Agency.
28. Ismail, R. (2009). Technical efficiency, technical change and demand for skills in Malaysian food-based industry. European Journal of Social Sciences, 9, 504-515.
29. Jajri, I., & Ismail, R. (2007). Technical efficiency, technological change and total factor productivity in Malaysian manufacturing sector. The ICFAI Journal of Industrial Economics, 4, 63-75.
30. Jaraitėa, J., & Maria, C. D. (2012). Efficiency, productivity and environmental policy: a case study of power generation in the EU. Energy Economics, 34(5), 1557-1568.
31. Koopmans, T. C. (1957). Three essays on the state of economic science. New York: McGraw-Hill.
32. Kuosmanen, T. (2005). Weak disposability in nonparametric production analysis with undesirable outputs. American Journal of Agricultural Economics, 87, 1077-1082.
33. Liu, W., Meng, W., Li, X., & Zhang, D. (2010). DEA models with undesirable inputs and outputs. Annals of Operations Research, 173, 177-194.
34. Lu, W.-M., & Lo, S.-F. (2007). A closer look at the economic-environmental disparities for regional development in China. European Journal of Operational Research, 183, 882-894.
35. Mahadevan, R. (2002). A DEA approach to understanding the productivity growth of Malaysia's manufacturing industries. Asia Pacific Journal of Management, 19, 587-600.
36. Malaysia Productivity Corporation (2011). Productivity Report 2010/2011. Malaysia Productivity Corporation.
37. Mandal, S. K., & Madheswaran, S. (2010). Environmental efficiency of the Indian cement industry: an interstate analysis. Energy Policy, 38, 1108-1118.
38. Mohamad, N. H., & Said, F. (2010). Decomposing productivity growth in Malaysian food manufacturing industry. African Journal of Business Management, 4, 3522-3529.
39. Murty, M. N., & Kumar, S. (2003). Win-win opportunities and environmental regulation: testing of porter hypothesis for Indian manufacturing industries. Journal of Environmental Management, 67, 139-144.
40. Nahorski, Z., & Ravn, H. F. (2000). A review of mathematical models in economic environmental problems. Annals of Operations Research, 97, 165-201.
41. Picazo-Tadeo, A. J., & Prior, D. (2009). Environmental externalities and efficiency measurement. Journal of Environmental Management, 90, 3332-3339.
42. Piot-Lepetit, I. (2010). Technological externalities and environmental policy. How to simulate manure management regulation within a DEA framework. Annals of Operations Research. doi: 10. 1007/s10479-010-0744-8.
43. Pittman, R. W. (1983). Multilateral productivity comparisons with undesirable outputs. Economic Journal, 93, 883-891.
44. 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, 44, 140-152.
45. Sarkis, J. (2006). The adoption of environmental and risk management practices: relationships to environmental performance. Annals of Operations Research, 145, 367-381.
46. Sarkis, J., & Talluri, S. (2004). Ecoefficiency measurement using data envelopment analysis: research and practitioner issues. Journal of Environmental Assessment Policy & Management, 6, 91-123.
47. Seiford, L. M., & Zhu, J. (2002). Modeling undesirable factors in efficiency evaluation. European Journal of Operational Research, 142, 16-20.
48. Song, M., An, Q., Zhang, W., Wang, Z., & Wu, J. (2012). Environmental efficiency evaluation based on data envelopment analysis: a review. Renewable and Sustainable Energy Reviews, 16, 4465-4469.
49. Sueyoshi, T., Goto, M., & Ueno, T. (2010). Performance analysis of US coal-fired power plants by measuring three DEA efficiencies. Energy Policy, 38, 1675-1688.
50. Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130, 498-509.
51. Tone, K., & Tsutsui, M. (2011). Applying an efficiency measure of desirable and undesirable outputs in DEA to US electric utilities. Journal of CENTRUM Cathedra, 4, 236-249.
52. Tyteca, D. (1996). On the measurement of the environmental performance of firms-a literature review and a productive efficiency perspective. Journal of Environmental Management, 46, 281-308.
53. Wang, Q. W., Zhou, P., Shen, N., & Wang, S. S. (2013). Measuring carbon dioxide emission performance in Chinese provinces: a parametric approach. Renewable and Sustainable Energy Reviews, 21, 324-330.
54. Wanga, Q., Zhou, P., & Zhou, D. (2012). Efficiency measurement with carbon dioxide emissions: the case of China. Applied Energy, 90, 161-166.
55. Watanabe, M., & Tanaka, K. (2007). Efficiency analysis of Chinese industry: a directional distance function approach. Energy Policy, 35, 6323-6331.
56. Wei, Q. L., & Yan, H. (2004). Congestion and returns to scale in data envelopment analysis. European Journal of Operational Research, 153, 641-660.
57. 2 emissions in China: a nonparametric analysis. Energy Policy, 49, 164-172.
58. Wu, J., An, Q., Xiong, B., & Chen, Y. (2013). Congestion measurement for regional industries in China: a data envelopment analysis approach with undesirable outputs. Energy Policy, 57, 7-13.
59. Yu-Ying Lin, E., Chen, P. Y., & Chen, C. C. (2013). Measuring the environmental efficiency of countries: a directional distance function metafrontier approach. Journal of Environmental Management, 119, 134-142.
60. Zhou, P., Ang, B. W., & Poh, K. L. (2006). Slacks-based efficiency measures for modeling environmental performance. Ecological Economics, 60, 111-118.
61. 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, 189, 1-18.