IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v86y2023ics0038012122002816.html
   My bibliography  Save this article

Dynamically evaluating the comprehensive efficiency of technological innovation and low-carbon economy in China's industrial sectors

Author

Listed:
  • Jin, Baoling
  • Han, Ying
  • Kou, Po

Abstract

Technological innovation and low-carbon economy are significant for the high-quality development of China's industrial sectors. However, few scholars combine the two stages closely and discuss their coordinated development. This paper establishes an evaluation index system of technological innovation and low-carbon economy in China's industrial sectors. The technological innovation efficiency, low-carbon economy efficiency, and comprehensive efficiency of technological innovation and low-carbon economy are dynamically investigated by the two-stage data envelopment analysis (DEA) model and the DEA window analysis with 35 subsectors panel data during 1996–2018. The inter-industrial differences in the technological innovation efficiency and low-carbon economy efficiency are considered, and the influencing factors of the comprehensive efficiency of technological innovation and low-carbon economy are studied by the bootstrap truncation regression. The results show that: (1) The development of the technological innovation and low-carbon economy is uncoordinated, and the low-carbon economy efficiency needs improvement; (2) There is heterogeneous of the technological innovation efficiency and low-carbon economy efficiency in the 35 subsectors; (3) The density of science and technology institutions, and the average enterprises scale are positive to the comprehensive efficiency of technological innovation and low-carbon economy, while excessive reliance on technology introduction has a negative impaction. The corresponding suggestions are provided for promoting technological innovation efficiency and low-carbon economy efficiency of industrial sectors.

Suggested Citation

  • Jin, Baoling & Han, Ying & Kou, Po, 2023. "Dynamically evaluating the comprehensive efficiency of technological innovation and low-carbon economy in China's industrial sectors," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:soceps:v:86:y:2023:i:c:s0038012122002816
    DOI: 10.1016/j.seps.2022.101480
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012122002816
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2022.101480?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sun, Huaping & Edziah, Bless Kofi & Kporsu, Anthony Kwaku & Sarkodie, Samuel Asumadu & Taghizadeh-Hesary, Farhad, 2021. "Energy efficiency: The role of technological innovation and knowledge spillover," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    2. Chen, Shiyi & Golley, Jane, 2014. "‘Green’ productivity growth in China's industrial economy," Energy Economics, Elsevier, vol. 44(C), pages 89-98.
    3. Ming Meng & Yanan Fu & Tianyu Wang & Kaiqiang Jing, 2017. "Analysis of Low-Carbon Economy Efficiency of Chinese Industrial Sectors Based on a RAM Model with Undesirable Outputs," Sustainability, MDPI, vol. 9(3), pages 1-18, March.
    4. Guo, Chuanyin & Abbasi Shureshjani, Roohollah & Foroughi, Ali Asghar & Zhu, Joe, 2017. "Decomposition weights and overall efficiency in two-stage additive network DEA," European Journal of Operational Research, Elsevier, vol. 257(3), pages 896-906.
    5. Zhang, Xing-Ping & Cheng, Xiao-Mei, 2009. "Energy consumption, carbon emissions, and economic growth in China," Ecological Economics, Elsevier, vol. 68(10), pages 2706-2712, August.
    6. Li, Xibao, 2011. "Sources of External Technology, Absorptive Capacity, and Innovation Capability in Chinese State-Owned High-Tech Enterprises," World Development, Elsevier, vol. 39(7), pages 1240-1248, July.
    7. George E. Halkos & Nickolaos G. Tzeremes & Stavros A. Kourtzidis, 2016. "Measuring Sustainability Efficiency Using a Two-Stage Data Envelopment Analysis Approach," Journal of Industrial Ecology, Yale University, vol. 20(5), pages 1159-1175, October.
    8. Qiu, Yueming & Ortolano, Leonard & David Wang, Yi, 2013. "Factors influencing the technology upgrading and catch-up of Chinese wind turbine manufacturers: Technology acquisition mechanisms and government policies," Energy Policy, Elsevier, vol. 55(C), pages 305-316.
    9. Rubashkina, Yana & Galeotti, Marzio & Verdolini, Elena, 2015. "Environmental regulation and competitiveness: Empirical evidence on the Porter Hypothesis from European manufacturing sectors," Energy Policy, Elsevier, vol. 83(C), pages 288-300.
    10. Ray, Subhash C & Desli, Evangelia, 1997. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries: Comment," American Economic Review, American Economic Association, vol. 87(5), pages 1033-1039, December.
    11. Wang, Miao & Feng, Chao, 2018. "Using an extended logarithmic mean Divisia index approach to assess the roles of economic factors on industrial CO2 emissions of China," Energy Economics, Elsevier, vol. 76(C), pages 101-114.
    12. Lin, Shoufu & Lin, Ruoyun & Sun, Ji & Wang, Fei & Wu, Weixiang, 2021. "Dynamically evaluating technological innovation efficiency of high-tech industry in China: Provincial, regional and industrial perspective," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    13. Alois Kneip & Léopold Simar & Paul Wilson, 2011. "A Computationally Efficient, Consistent Bootstrap for Inference with Non-parametric DEA Estimators," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 483-515, November.
    14. Wu, Jie & Li, Mingjun & Zhu, Qingyuan & Zhou, Zhixiang & Liang, Liang, 2019. "Energy and environmental efficiency measurement of China's industrial sectors: A DEA model with non-homogeneous inputs and outputs," Energy Economics, Elsevier, vol. 78(C), pages 468-480.
    15. Xian’En Wang & Shimeng Wang & Xipan Wang & Wenbo Li & Junnian Song & Haiyan Duan & Shuo Wang, 2019. "The Assessment of Carbon Performance under the Region-Sector Perspective based on the Nonparametric Estimation: A Case Study of the Northern Province in China," Sustainability, MDPI, vol. 11(21), pages 1-23, October.
    16. Ru, Peng & Zhi, Qiang & Zhang, Fang & Zhong, Xiaotian & Li, Jianqiang & Su, Jun, 2012. "Behind the development of technology: The transition of innovation modes in China’s wind turbine manufacturing industry," Energy Policy, Elsevier, vol. 43(C), pages 58-69.
    17. Stefan Nabernegg & Birgit Bednar-Friedl & Fabian Wagner & Thomas Schinko & Janusz Cofala & Yadira Mori Clement, 2017. "The Deployment of Low Carbon Technologies in Energy Intensive Industries: A Macroeconomic Analysis for Europe, China and India," Energies, MDPI, vol. 10(3), pages 1-26, March.
    18. Huangxin Chen & Hang Lin & Wenjie Zou, 2020. "Research on the Regional Differences and Influencing Factors of the Innovation Efficiency of China’s High-Tech Industries: Based on a Shared Inputs Two-Stage Network DEA," Sustainability, MDPI, vol. 12(8), pages 1-15, April.
    19. Siran Fang & Xiaoshan Xue & Ge Yin & Hong Fang & Jialin Li & Yongnian Zhang, 2020. "Evaluation and Improvement of Technological Innovation Efficiency of New Energy Vehicle Enterprises in China Based on DEA-Tobit Model," Sustainability, MDPI, vol. 12(18), pages 1-22, September.
    20. Zuchang Zhong & Fanchao Meng & Yuanbing Zhu & Gang Wang, 2020. "Research on the Technological Innovation Efficiency of China’s Strategic Emerging Industries Based on SBM: NDEA Model and Big Data," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-11, May.
    21. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    22. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    23. He, Yong & Fu, Feifei & Liao, Nuo, 2021. "Exploring the path of carbon emissions reduction in China’s industrial sector through energy efficiency enhancement induced by R&D investment," Energy, Elsevier, vol. 225(C).
    24. Oh, Dong-hyun & Heshmati, Almas, 2010. "A sequential Malmquist-Luenberger productivity index: Environmentally sensitive productivity growth considering the progressive nature of technology," Energy Economics, Elsevier, vol. 32(6), pages 1345-1355, November.
    25. Lin, Boqiang & Du, Zhili, 2017. "Promoting energy conservation in China's metallurgy industry," Energy Policy, Elsevier, vol. 104(C), pages 285-294.
    26. 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.
    27. Yi-Chieh Chen & Lin-Huan Hu & Wan Chen Lu & Jei-Zheng Wu & Jiun-Jen Yang, 2021. "Multiple Criteria Decision-Making for Developing an International Game Participation Strategy: A Novel Application of the Data Envelopment Analysis (DEA) Two-Stage Efficiency Process," Mathematics, MDPI, vol. 9(14), pages 1-16, July.
    28. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    29. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    30. Weijuan Li & Pengcheng Zhang, 2021. "Investigating the transformation efficiency of scientific and technological achievements in China’s equipment manufacturing industry under the low-carbon economy [Environment policy and technologic," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 16(1), pages 135-145.
    31. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    32. Tie Liu & Xu Yang & Yu Guo & Wei Zhang, 2021. "Research on Influencing Factors of Technological Independent Innovation of Equipment Manufacturing Enterprises from the Perspective of Iceberg Theory," Complexity, Hindawi, vol. 2021, pages 1-14, October.
    33. Despotis, Dimitris K. & Koronakos, Gregory & Sotiros, Dimitris, 2016. "The “weak-link” approach to network DEA for two-stage processes," European Journal of Operational Research, Elsevier, vol. 254(2), pages 481-492.
    34. Liu, Hui-hui & Yang, Guo-liang & Liu, Xiao-xiao & Song, Yao-yao, 2020. "R&D performance assessment of industrial enterprises in China: A two-stage DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    35. Yang, Zhenbing & Shao, Shuai & Yang, Lili & Liu, Jianghua, 2017. "Differentiated effects of diversified technological sources on energy-saving technological progress: Empirical evidence from China's industrial sectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1379-1388.
    36. Jingwen Yi & Yuchen Zhang & Kaicheng Liao, 2021. "Regional Differential Decomposition and Formation Mechanism of Dynamic Carbon Emission Efficiency of China’s Logistics Industry," IJERPH, MDPI, vol. 18(24), pages 1-25, December.
    37. Zaim, Osman, 2004. "Measuring environmental performance of state manufacturing through changes in pollution intensities: a DEA framework," Ecological Economics, Elsevier, vol. 48(1), pages 37-47, January.
    38. Wang, Yun & Sun, Xiaohua & Guo, Xu, 2019. "Environmental regulation and green productivity growth: Empirical evidence on the Porter Hypothesis from OECD industrial sectors," Energy Policy, Elsevier, vol. 132(C), pages 611-619.
    39. Coccia, Mario, 2014. "Driving forces of technological change: The relation between population growth and technological innovation," Technological Forecasting and Social Change, Elsevier, vol. 82(C), pages 52-65.
    40. Du, Kerui & Li, Jianglong, 2019. "Towards a green world: How do green technology innovations affect total-factor carbon productivity," Energy Policy, Elsevier, vol. 131(C), pages 240-250.
    41. Kao, Chiang, 2014. "Efficiency decomposition in network data envelopment analysis with slacks-based measures," Omega, Elsevier, vol. 45(C), pages 1-6.
    42. Albrizio, Silvia & Kozluk, Tomasz & Zipperer, Vera, 2017. "Environmental policies and productivity growth: Evidence across industries and firms," Journal of Environmental Economics and Management, Elsevier, vol. 81(C), pages 209-226.
    43. Li, Xiaoyan & Xu, Hengzhou, 2020. "The Energy-conservation and Emission-reduction Paths of Industrial sectors: Evidence from Chinas 35 industrial sectors," Energy Economics, Elsevier, vol. 86(C).
    44. Mette Asmild & Joseph Paradi & Vanita Aggarwall & Claire Schaffnit, 2004. "Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry," Journal of Productivity Analysis, Springer, vol. 21(1), pages 67-89, January.
    45. Lin, Tzu-Yu & Chiu, Sheng-Hsiung & Yang, Hai-Lan, 2022. "Performance evaluation for regional innovation systems development in China based on the two-stage SBM-DNDEA model," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    46. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    47. Han, Yonghui & Zhang, Fan & Huang, Liangxiong & Peng, Keming & Wang, Xianbin, 2021. "Does industrial upgrading promote eco-efficiency? ─A panel space estimation based on Chinese evidence," Energy Policy, Elsevier, vol. 154(C).
    48. Miao, Chenglin & Fang, Debin & Sun, Liyan & Luo, Qiaoling, 2017. "Natural resources utilization efficiency under the influence of green technological innovation," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 153-161.
    49. Wang, Ke & Wei, Yi-Ming & Zhang, Xian, 2012. "A comparative analysis of China’s regional energy and emission performance: Which is the better way to deal with undesirable outputs?," Energy Policy, Elsevier, vol. 46(C), pages 574-584.
    50. Li, Yongjun & Chen, Yao & Liang, Liang & Xie, Jianhui, 2012. "DEA models for extended two-stage network structures," Omega, Elsevier, vol. 40(5), pages 611-618.
    51. Po-Yuan Shih & Cheng-Ping Cheng & Dong-Her Shih & Ting-Wei Wu & David C. Yen, 2022. "Who Is the Most Effective Country in Anti-Corruption? From the Perspective of Open Government Data and Gross Domestic Product," Mathematics, MDPI, vol. 10(13), pages 1-20, June.
    52. Feng Ren & Xin Yu & Quan Li, 2020. "Study on ETFEE in the BTH Region Based on the Window-SBM-Undesirable Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-10, October.
    53. Shoufu Lin & Ji Sun & Shanyong Wang, 2019. "Dynamic evaluation of the technological innovation efficiency of China’s industrial enterprises," Science and Public Policy, Oxford University Press, vol. 46(2), pages 232-243.
    54. Liang Liang & Wade D. Cook & Joe Zhu, 2008. "DEA models for two‐stage processes: Game approach and efficiency decomposition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 643-653, October.
    55. Zhai, Xueqi & An, Yunfei, 2021. "The relationship between technological innovation and green transformation efficiency in China: An empirical analysis using spatial panel data," Technology in Society, Elsevier, vol. 64(C).
    56. Junzhong Zou & Wei Chen & Nan Peng & Xuan Wei, 2020. "Efficiency of Two-Stage Technological Innovation in High Patent-Intensive Industries That Considers Time Lag: Research Based on the SBM-NDEA Model," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-9, May.
    57. Yu-Ying Lin, Eugene & Chen, Ping-Yu & Chen, Chi-Chung, 2013. "Measuring green productivity of country: A generlized metafrontier Malmquist productivity index approach," Energy, Elsevier, vol. 55(C), pages 340-353.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Guoli & Qian, Zhe & Bolatbek, Botagoz & Na, Liu, 2024. "A comparative study of the nexus of natural resource investment in national economies: Effects on cultural communication and economic growth," Resources Policy, Elsevier, vol. 94(C).
    2. Feng, Xinhui & Lin, Xinle & Li, Yan & Yang, Jiayu & Yu, Er & Lei, Kaige, 2024. "Spatial association network of carbon emission performance: Formation mechanism and structural characteristics," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    3. Yin, Lei & Du, Shanxing & Chen, Ge, 2024. "The influence of the bank–firm relationship on enterprises’ technological innovation efficiency: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1583-1600.
    4. Liu, Hongwei & Shao, Liangyu & Min, Jie & Ji, Xiang, 2024. "Regional differences and determinants of environmental efficiency in China's road transportation industry," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 931-946.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Ya & Li, Yongjun & Liang, Liang & Salo, Ahti & Wu, Huaqing, 2016. "Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures," European Journal of Operational Research, Elsevier, vol. 250(2), pages 543-554.
    2. Tatiana Bencova & Andrea Bohacikova, 2022. "DEA in Performance Measurement of Two-Stage Processes: Comparative Overview of the Literature," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 111-129.
    3. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    4. Lim, Dong-Joon & Kim, Moon-Su, 2022. "Measuring dynamic efficiency with variable time lag effects," Omega, Elsevier, vol. 108(C).
    5. Zhang, Linyan & Chen, Kun, 2019. "Hierarchical network systems: An application to high-technology industry in China," Omega, Elsevier, vol. 82(C), pages 118-131.
    6. Eucabeth Majiwa & Boon L. Lee & Clevo Wilson & Hidemichi Fujii & Shunsuke Managi, 2018. "A network data envelopment analysis (NDEA) model of post-harvest handling: the case of Kenya’s rice processing industry," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(3), pages 631-648, June.
    7. Lee, Boon L. & Worthington, Andrew C., 2016. "A network DEA quantity and quality-orientated production model: An application to Australian university research services," Omega, Elsevier, vol. 60(C), pages 26-33.
    8. Liu, Yin & Alnafrah, Ibrahim & Zhou, Yaying, 2024. "A systemic efficiency measurement of resource management and sustainable practices: A network bias-corrected DEA assessment of OECD countries," Resources Policy, Elsevier, vol. 90(C).
    9. Xiao, Huijuan & Wang, Daoping & Qi, Yu & Shao, Shuai & Zhou, Ya & Shan, Yuli, 2021. "The governance-production nexus of eco-efficiency in Chinese resource-based cities: A two-stage network DEA approach," Energy Economics, Elsevier, vol. 101(C).
    10. Chen, Kuan-Chen & Lin, Sun-Yuan & Yu, Ming-Miin, 2022. "Exploring the efficiency of hospital and pharmacy utilizations in Taiwan: An application of dynamic network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    11. Koronakos, Gregory & Sotiros, Dimitris & Despotis, Dimitris K. & Kritikos, Manolis N., 2022. "Fair efficiency decomposition in network DEA: A compromise programming approach," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    12. Kao, Chiang, 2016. "Efficiency decomposition and aggregation in network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 255(3), pages 778-786.
    13. Wen-Min Lu & Qian Long Kweh & Kai-Chu Yang, 2022. "Multiplicative efficiency aggregation to evaluate Taiwanese local auditing institutions performance," Annals of Operations Research, Springer, vol. 315(2), pages 1243-1262, August.
    14. Suvvari Anandarao & S. Raja Sethu Durai & Phanindra Goyari, 2019. "Efficiency Decomposition in two-stage Data Envelopment Analysis: An application to Life Insurance companies in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 271-285, June.
    15. Avkiran, Necmi Kemal, 2015. "An illustration of dynamic network DEA in commercial banking including robustness tests," Omega, Elsevier, vol. 55(C), pages 141-150.
    16. Chen, Zhongfei & Wanke, Peter & Antunes, Jorge Junio Moreira & Zhang, Ning, 2017. "Chinese airline efficiency under CO2 emissions and flight delays: A stochastic network DEA model," Energy Economics, Elsevier, vol. 68(C), pages 89-108.
    17. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    18. Sotiros, Dimitris & Koronakos, Gregory & Despotis, Dimitris K., 2019. "Dominance at the divisional efficiencies level in network DEA: The case of two-stage processes," Omega, Elsevier, vol. 85(C), pages 144-155.
    19. Ramin Gharizadeh Beiragh & Reza Alizadeh & Saeid Shafiei Kaleibari & Fausto Cavallaro & Sarfaraz Hashemkhani Zolfani & Romualdas Bausys & Abbas Mardani, 2020. "An integrated Multi-Criteria Decision Making Model for Sustainability Performance Assessment for Insurance Companies," Sustainability, MDPI, vol. 12(3), pages 1-24, January.
    20. Ming-Fu Hsu & Ying-Shao Hsin & Fu-Jiing Shiue, 2022. "Business analytics for corporate risk management and performance improvement," Annals of Operations Research, Springer, vol. 315(2), pages 629-669, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:soceps:v:86:y:2023:i:c:s0038012122002816. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.