Innovation efficiency of semiconductor industry in China: A new framework based on generalized three-stage DEA analysis
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DOI: 10.1016/j.seps.2018.07.007
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- Wang, Eric C. & Huang, Weichiao, 2007. "Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach," Research Policy, Elsevier, vol. 36(2), pages 260-273, March.
- Li, Ke & Lin, Boqiang, 2016. "Impact of energy conservation policies on the green productivity in China’s manufacturing sector: Evidence from a three-stage DEA model," Applied Energy, Elsevier, vol. 168(C), pages 351-363.
- Patricia Renou-Maissant & Mathilde Aubry, 2014. "Semiconductor Industry Cycles: Explanatory Factors and Forecasting," Post-Print hal-02562533, HAL.
- Hye-Seon Moon & Jeong-Dong Lee, 2005. "A fuzzy set theory approach to national composite S&T indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(1), pages 67-83, July.
- Pérez-López, Gemma & Prior, Diego & Zafra-Gómez, José L., 2018. "Temporal scale efficiency in DEA panel data estimations. An application to the solid waste disposal service in Spain," Omega, Elsevier, vol. 76(C), pages 18-27.
- Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2005. "Returns to scale in dynamic DEA," European Journal of Operational Research, Elsevier, vol. 161(2), pages 536-544, March.
- Chen, Chien-Ming & van Dalen, Jan, 2010. "Measuring dynamic efficiency: Theories and an integrated methodology," European Journal of Operational Research, Elsevier, vol. 203(3), pages 749-760, June.
- repec:fth:harver:1473 is not listed on IDEAS
- Wang, Qunwei & Hang, Ye & Sun, Licheng & Zhao, Zengyao, 2016. "Two-stage innovation efficiency of new energy enterprises in China: A non-radial DEA approach," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 254-261.
- Bi-Huei Tsai & Huang Wen Chen, 2013. "Innovation Characteristics, Industrial Clusters, And Intra-Industry Spillover Effects In Integrated Circuit Industry," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 10(04), pages 1-20.
- Yang, Wei & Shi, Jinfeng & Qiao, Han & Shao, Yanmin & Wang, Shouyang, 2017. "Regional technical efficiency of Chinese Iron and steel industry based on bootstrap network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 57(C), pages 14-24.
- Song, Malin & Ai, Hongshan & Li, Xie, 2015. "Political connections, financing constraints, and the optimization of innovation efficiency among China's private enterprises," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 290-299.
- H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
- Zvi Griliches, 1998.
"Patent Statistics as Economic Indicators: A Survey,"
NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 287-343,
National Bureau of Economic Research, Inc.
- Griliches, Zvi, 1990. "Patent Statistics as Economic Indicators: A Survey," Journal of Economic Literature, American Economic Association, vol. 28(4), pages 1661-1707, December.
- Zvi Griliches, 1990. "Patent Statistics as Economic Indicators: A Survey," NBER Working Papers 3301, National Bureau of Economic Research, Inc.
- Hagedoorn, John & Cloodt, Myriam, 2003. "Measuring innovative performance: is there an advantage in using multiple indicators?," Research Policy, Elsevier, vol. 32(8), pages 1365-1379, September.
- Zoltan J. Acs & Luc Anselin & Attila Varga, 2008.
"Patents and Innovation Counts as Measures of Regional Production of New Knowledge,"
Chapters, in: Entrepreneurship, Growth and Public Policy, chapter 11, pages 135-151,
Edward Elgar Publishing.
- Acs, Zoltan J. & Anselin, Luc & Varga, Attila, 2002. "Patents and innovation counts as measures of regional production of new knowledge," Research Policy, Elsevier, vol. 31(7), pages 1069-1085, September.
- Samuel Kortum & Josh Lerner, 2000. "Assessing the Contribution of Venture Capital to Innovation," RAND Journal of Economics, The RAND Corporation, vol. 31(4), pages 674-692, Winter.
- 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.
- Kapoor, Rahul & McGrath, Patia J., 2014. "Unmasking the interplay between technology evolution and R&D collaboration: Evidence from the global semiconductor manufacturing industry, 1990–2010," Research Policy, Elsevier, vol. 43(3), pages 555-569.
- Staub, Roberta B. & da Silva e Souza, Geraldo & Tabak, Benjamin M., 2010.
"Evolution of bank efficiency in Brazil: A DEA approach,"
European Journal of Operational Research, Elsevier, vol. 202(1), pages 204-213, April.
- Roberta B. Staub & Geraldo Souza & Benjamin M. Tabak, 2009. "Evolution of Bank Efficiency in Brazil: A DEA Approach," Working Papers Series 200, Central Bank of Brazil, Research Department.
- Wang, Chi-Tai & Chiu, Chui-Sheng, 2014. "Competitive strategies for Taiwan's semiconductor industry in a new world economy," Technology in Society, Elsevier, vol. 36(C), pages 60-73.
- Wang, Chun-Hsien & Lu, Yung-Hsiang & Huang, Chin-Wei & Lee, Jun-Yen, 2013. "R&D, productivity, and market value: An empirical study from high-technology firms," Omega, Elsevier, vol. 41(1), pages 143-155.
- Wu, Chiu-Hui & Ding, Cherng G. & Jane, Ten-Der & Lin, Hang-Rung & Wu, Cheng-Ying, 2015. "Lessons from the global financial crisis for the semiconductor industry," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 47-53.
- Zhong, Wei & Yuan, Wei & Li, Susan X. & Huang, Zhimin, 2011. "The performance evaluation of regional R&D investments in China: An application of DEA based on the first official China economic census data," Omega, Elsevier, vol. 39(4), pages 447-455, August.
- Rajah Rasiah & Yap Xiao Shan, 2016.
"Institutional support, technological capabilities and domestic linkages in the semiconductor industry in Singapore,"
Asia Pacific Business Review, Taylor & Francis Journals, vol. 22(1), pages 180-192, January.
- Rajah Rasiah & Yap Xiao SHAN, 2015. "Institutional Support, Technological Capabilities and Domestic Linkages in the Semiconductor Industry in Singapore," Working Papers DP-2015-17, Economic Research Institute for ASEAN and East Asia (ERIA).
- Li, Lan-bing & Liu, Bing-lian & Liu, Wei-lin & Chiu, Yung-Ho, 2017. "Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 24-33.
- Aubry, Mathilde & Renou-Maissant, Patricia, 2014. "Semiconductor industry cycles: Explanatory factors and forecasting," Economic Modelling, Elsevier, vol. 39(C), pages 221-231.
- R G Dyson & E A Shale, 2010. "Data envelopment analysis, operational research and uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 25-34, January.
- Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
- Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Xiao, Xing-Zhi & Tian, Zhen-Zhen & Yang, Xiao-Yuan & Wang, Jian-Lin, 2016. "Cost efficiency of electric grid utilities in China: A comparison of estimates from SFA–MLE, SFA–Bayes and StoNED–CNLS," Energy Economics, Elsevier, vol. 55(C), pages 272-283.
- Li, Ming-Jia & He, Ya-Ling & Tao, Wen-Quan, 2017. "Modeling a hybrid methodology for evaluating and forecasting regional energy efficiency in China," Applied Energy, Elsevier, vol. 185(P2), pages 1769-1777.
- Seema Sharma & V. J. Thomas, 2008. "Inter-country R&D efficiency analysis: An application of data envelopment analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 483-501, September.
- William W. Cooper & Kyung Sam Park & Gang Yu, 2001. "An Illustrative Application of Idea (Imprecise Data Envelopment Analysis) to a Korean Mobile Telecommunication Company," Operations Research, INFORMS, vol. 49(6), pages 807-820, December.
- Rasiah, Rajah & Shahrivar, Rafat Beigpoor & Yap, Xiao-Shan, 2016. "Institutional support, innovation capabilities and exports: Evidence from the semiconductor industry in Taiwan," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 69-75.
- Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
- Liadaki, Aggeliki & Gaganis, Chrysovalantis, 2010. "Efficiency and stock performance of EU banks: Is there a relationship?," Omega, Elsevier, vol. 38(5), pages 254-259, October.
- Tser‐Yieth Chen & Ling‐hua Chen, 2007. "DEA performance evaluation based on BSC indicators incorporated," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 56(4), pages 335-357, May.
- Miki Tsutsui & Kaoru Tone, 2008. "Dynamic DEA: A slacks-based measure approach," GRIPS Discussion Papers 08-13, National Graduate Institute for Policy Studies.
- Chow, Hwee Kwan & Choy, Keen Meng, 2006. "Forecasting the global electronics cycle with leading indicators: A Bayesian VAR approach," International Journal of Forecasting, Elsevier, vol. 22(2), pages 301-315.
- Li, Xibao, 2009. "China's regional innovation capacity in transition: An empirical approach," Research Policy, Elsevier, vol. 38(2), pages 338-357, March.
- Jiancheng Guan & Kaihua Chen, 2010. "Modeling macro-R&D production frontier performance: an application to Chinese province-level R&D," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 165-173, January.
- Charoenrat, Teerawat & Harvie, Charles, 2014. "The efficiency of SMEs in Thai manufacturing: A stochastic frontier analysis," Economic Modelling, Elsevier, vol. 43(C), pages 372-393.
- Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
- Cook, Wade D. & Zhu, Joe, 2007. "Classifying inputs and outputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 180(2), pages 692-699, July.
- Mathilde Aubry & Patricia Renou-Maissant, 2014. "Semiconductor industry cycles: Explanatory factors and forecasting," Post-Print halshs-01101975, HAL.
- Liu, Fuh-Hwa Franklin & Wang, Peng-hsiang, 2008. "DEA Malmquist productivity measure: Taiwanese semiconductor companies," International Journal of Production Economics, Elsevier, vol. 112(1), pages 367-379, March.
- Wang, Chun-Chieh & Sung, Hui-Yun & Chen, Dar-Zen & Huang, Mu-Hsuan, 2017. "Strong ties and weak ties of the knowledge spillover network in the semiconductor industry," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 114-127.
- Timo Kuosmanen & Mika Kortelainen, 2012. "Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints," Journal of Productivity Analysis, Springer, vol. 38(1), pages 11-28, August.
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Keywords
Technological innovation efficiency; Generalized three-stage DEA; Projection analyses; Disparity;All these keywords.
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