Organizational forms for knowledge management in photovoltaic solar energy industry
Introduction
Photovoltaic (PV) solar energy industry is one of the most booming industries in the world. The main advantage of PV solar cell system is its accessibility of clean and environmentally friendly electricity without consuming fossil fuel. In recent years, many countries have contributed their efforts into the target of zero carbon emission. As a result, the application of PV solar cell system has been strongly promoted in many countries, including Germany, Japan, and USA. The Europe region leads the first among a great number of countries with most PV solar systems installed, and then is followed by countries like Japan, USA, and China in the Asia and Pacific region. With continuously increasing demand for PV solar cell systems, it is not hard to forecast the exponential growth of PV solar energy industry in the near future. For example, the global production capacity of silicon solar cell was 52 MWp and 740 MWp in 2000 and 2003, respectively. However, it reached 4.6 GWp, 6.3 GWp, 9.1 GWp, and 12.0 GWp in the years of 2005, 2006, 2007 and 2008, respectively [1], [2]. The PV solar market increased sharply from 2001 to 2006, at a growth rate of 38.4% according to the survey carried out by the International Energy Agency (IEA). Revenues generated from the PV solar energy industry grew from US$14.5 billion in 2006 to US$18.6 billion in 2007. Based on this strong growth, it is highly possible that its revenue will achieve US$36.4 billion in 2010 and reach over US$100.0 billion before 2020 [3].
The most commonly used PV solar cell today is made from crystalline silicon, but the main trend of PV solar energy industry is toward the PV silicon thin-film solar cell because of its potential reduction of production costs, low material consumption, lower energy consumption and a shorter energy payback time. The crystalline silicon material and energy consumption for making PV silicon thin-film solar cell is only 1/10 of those for traditional solar cell. However, solar radiation conversion efficiency, product stability, and lifetime all need to be improved [4], [5], [6]. As continual cost reduction of chip and flat panel display (FPD) has created a huge consumer market in China, the same trend can apply to PV solar energy industry. Meanwhile, the embedded characteristics such as global logistics, extensible capability, and marketing management may provide the best basis for the development of PV solar energy industry in China. The technologies in chip and FPD industries including deposition, etching, and deep engineering expertise in materials, chemistry and process technology may immediately be applicable to making PV solar cells in volume production. These companies also have extensive R&D infrastructures which may be utilized for advanced solar technology development. The booming investment in China has resulted in expansion of production and growth of revenues.
In recent years, China has taken efforts to combat against global warming and to reach the goal of zero carbon emission. However, compared with Japan and Germany, China is under high pressure to prosper its PV solar energy industry since its technologies are still far behind those countries. Then, a strategic policy to facilitate knowledge distribution, knowledge absorption, and knowledge creation, and then to obtain competitive advantages for PV solar energy industry in China is essential to be proposed. Knowledge management (KM) is the ability to acquire, maintain, disseminate, and create knowledge among firms or within a firm. However, only a small amount of literature examines the importance of learning through collaborations [7], [8], [9]. Especially, suitable forms of organization for KM related to the above issue are critical and have not been comprehensively addressed in existing research literature [10], [11], [12]. In order to challenge the vacancy, a conceptual model is proposed. First, the proposed model examines critical characteristics of successful PV solar energy industry in China. Second, a fuzzy analytic network process is developed to analyze suitable forms of organization for KM in order to distribute existing knowledge, and to create new knowledge.
The rest of this paper is organized as follows: critical characteristics of PV solar energy industry are summarized in Section 2 and main tasks of knowledge management activities are examined in Section 3. A conceptual model using fuzzy analytic network process and considering confidence level and risk index is constructed in Section 4. Suitable forms of organization for KM at different stages are examined and analyzed in Section 5. Discussions and conclusions are provided in the last two sections.
Section snippets
Critical characteristics for successful PV solar energy industry
There are many types of PV solar cells: crystalline silicon cell technology is subdivided into mono-crystalline silicon and multi-crystalline types; thin-film solar cells utilize a thin layer of photo-electrically active material deposited on a substrate. There are several main materials for making thin-film solar cells: amorphous silicon (a-Si), cadmium-telluride (Cd-Te) and copper–indium–selenide (CIS) are the primary commercial technologies. Key factors required by cost reduction include
Main tasks of knowledge management activities
The booming investment for PV solar energy industry in China has resulted in quick expansion of production capacity. However, securing the supply of silicon, improving cell efficiency, and reassuring local supply of equipments for conventional silicon and thin film production are still remained to be solved to meet the requirement of global market and competitive industry [30]. Their gaps and possible solutions in supply chain of PV solar energy industry are described as follows.
A fuzzy analytic network process model
In an analytic hierarchy process (AHP), a decision is pursued using a unidirectional hierarchical relationship among the decision levels [35], whereas an analytic network process (ANP) is used to assess a dynamic multi-directional relationship among the decision attributes [36], [37], [38].
In addition, an assumption of AHP and ANP is consistency or transitivity of preference. However, this may not always be true in real life [39]. In this case, the use of fuzzy numbers may be more suitable.
Suitable forms of organization for KM at different stages
In order to analyze and select suitable forms of organization at different stages of new product development, upstream supply chain of PV solar energy industry in China is used as an example. To simplify the complexity of the environment for our analysis, this paper is based on the following assumptions: the firms try to select suitable forms of organization from five alternatives, A, B, C, D and E; and the development activities of new product are categorized into three sequential stages as
Discussion
We can rank the suitable forms of organization for KM through their fuzzy triangular numbers by selecting the one with a higher mean value and lower spread as most suitable. However, a further analysis should be processed if the fuzzy number does not simultaneously possess a higher mean value and lower spread. Thus, the paper develops a fuzzy ANP model associated with confidence level and risk level to evaluate the best forms of organization. After extensive calculation, it is concluded that
Conclusion
From a managerial point of view, a comprehensive and hierarchical form of organization for KM suitable for most cases, should be proposed and shown in Fig. 3. The centralized KM structure at the highest level provides the strongest guidance between strategic policy and KM initiatives, the best communication and coordination of KM activities, and the clearest understanding of responsibilities by participants. These factors will result in strong commitment from participants to KM initiatives and
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