دانلود رایگان مقاله لاتین نوآوری دو مرحله ای شرکت انرژی از سایت الزویر
عنوان فارسی مقاله:
بازده نوآوری دو مرحله ای شرکت های انرژی جدید در چین: رویکرد DEA غیر رادیال
عنوان انگلیسی مقاله:
Two-stage innovation efficiency of new energy enterprises in China: A non-radial DEA approach
سال انتشار : 2016
برای دانلود رایگان مقاله نوآوری دو مرحله ای شرکت انرژی اینجا کلیک نمایید.
بخشی از مقاله انگلیسی:
2. Literature review
To measure innovation efficiency, researchers previously often used a ratio of single input to single output as an efficiency value. This method is intuitive and simple, but cannot address multiple inputs or outputs, and fails to detect sources of inefficiency. As efficiency calculation methods have improved, researchers have started to use tools that apply a frontier analysis approach, such as stochastic frontier analysis (SFA) and DEA. These tools have become mainstream methods to calculate innovation efficiency (Guan and Chen, 2010a, 2010b). SFA is a parametric analysis method proposed by Aigner et al. (1977). It assumes a specific form in the relationship between the input and output functions, and applies econometric techniques to estimate unknown parameters to identify the frontier. The SFA method has been used to conduct efficiency assessments in manufacturing, banking, and other domains (Liadaki and Gaganis, 2010; Charoenrat and Harvie, 2014). Using SFA, Wang and Huang (2007) calculated innovation effi- ciencies in 30 countries, accounting for environmental factors, and exploring the relationship between R&D efficiency and income levels. Li (2009) used an SFA method proposed by Battese and Coelli (1995) to measure regional innovation performance and capabilities in China's 30 provinces between 1998 and 2005. SFA methods account for the in- fluence of random factors on output (Aigner et al., 1977); however, they are not best for addressing scenarios with multiple outputs (Guan and Chen, 2010a). In contrast, the DEA method accommodates data from multiple inputs and multiple outputs, without setting a particular functional form in advance (Guan and Chen, 2012). As such, the DEA method is more widely used to measure efficiency, and many innovation efficiency studies using DEA are found in the literature. Chen et al. (2006) used DEA to measure the performance of six high-tech industries in Taiwan from 1991 to 1999. Hashimoto and Haneda (2008) analyzed the research and innovation efficiency of the Japanese pharmaceutical industry between 1983 and 1992, using the DEA-Malmquist method. Building on the super-efficiency DEA method, Schmidt-Ehmcke and Zloczysti (2011) calculated and compared the innovation efficiency of 13 industries from 17 countries, including Germany, U.S., and Denmark, identifying a number of cutting-edge, technically efficient industries. The studies described above measure innovation efficiency using different DEA methods, but all view the enterprise's innovation process as a black box, where the innovation process is a “single stage” process of converting input to output. These kinds of study do not assess the innovation system's internal mechanics, and do not address how internal operational systems and processes associated with innovation impact integrated innovation efficiency (Wang et al., 2013a, 2013b). “Single stage” innovation processes do not reflect production practice. In fact, innovation processes in typical high-tech industries or businesses include two phases: upstream technology development and downstream economic transformation (Moon and Lee, 2005; Sharma and Thomas, 2008). For this reason, some scholars have applied a two-stage DEA model to evaluate innovation efficiency. Guan and Chen (2010a) used the relational network DEA model to compare the innovation efficiencies of high-tech industries in China's 26 provinces between 2002 and 2003. They found that the commercial efficiency is better than the R&D efficiency; and the overall innovation efficiency is more closely related to commercial efficiency. A later study measured innovation efficiency of a national level, examining upstream knowledge production processes and downstream knowledge commercialization processes in 30 countries (Guan and Chen, 2012). Cullmann et al. (2012) empirically studies industrial innovation efficiency in Organization for Economic Co-operation and Development (OECD) countries, using a two-stage semi-parameter DEA method; this study improved measures for optimizing resource allocation. Wang et al. (2013a, 2013b) divided the first phase of the innovation process into “Basic production” and “R&D efforts,” and then estimated the profitability and marketability efficiencies of Taiwan's 65 high-tech enterprises between 2006 and 2007. This study generated an R&D decision matrix to identify sources of operational and R&D effi- ciency for high-technology firms. The two-stage DEA method has been applied to study commercial banks (Seiford and Zhu, 1999; Chiu et al., 2016), insurance (Wanke and Barros, 2016), and industrial systems (Bian et al., 2015).
برای دانلود رایگان مقاله نوآوری دو مرحله ای شرکت انرژی اینجا کلیک نمایید.
کلمات کلیدی:
PPT]Download - Europa EU https://europa.eu/capacity4dev/file/29442/download?token=LiZmj_9d UNIDO Industrial Energy Efficiency Programme ... Support innovative business models to promote renewable energy in the ... Renewable energy enterprises. LTLGB 2012: Proceedings of International Conference on Low-carbon ... https://books.google.com/books?isbn=3642346510 Feng Chen, Yisheng Liu, Guowei Hua - 2014 - Business & Economics ... also needed to encourage enterprises improving energy efficiency continuously. ... New. Energy. Core. Technology,. Promote. Independent. Innovation. Ability. Frontiers of Energy and Environmental Engineering https://books.google.com/books?isbn=0415661595 Wen-Pei Sung, Jimmy C.M. Kao, Ran Chen - 2012 - Nature different new energy industry subdivision industries competition, supply and demand, ... and radio activeness of the enterprise Although the new energy industry has ... An efficient way to accomplish regional innovation network system is the ... energy issues in the developing world - Page 7 - Google Books Result https://books.google.com/books?id=XKCKegUCtisC For example, the amount of new energy investment required to support a 4% growth ... place more emphasis on innovative financing schemes, efficiency pricing, ... of energy resources and for efficient management of energy enterprises, and ... Financial innovation is the next big thing in clean energy and efficiency www.zdnet.com/.../financial-innovation-is-the-next-big-thing-in-clean-energy-and-eff... Nov 10, 2013 - A new wave of investment in renewable energy and efficiency upgrades is being driven by innovation in finance -- not in technology, policy or ...
