8 resultados para Automobile Industry, Quality Change, Innovation, and Hedonic Prices.

em Academic Research Repository at Institute of Developing Economies


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This paper proposes a flowchart approach to the automobile industry cluster policy and the hi-technology industry cluster policy to prioritize policy measures. First, in the automobile industry cluster, suppliers of parts and components to anchor firms such as Honda, Nissan and Toyota of Japanese assembly makers in Guangzhou, China, can innovate partly because the suppliers have become independent of their anchor firms in the Japanese Keiretsu system. Second, concerning the hi-technology industry clustering in Beijing, we show that the existence of universities is a precondition for the industrial cluster policy and that the leadership of the Zhongguancun Science Park Management Committee of Beijing Municipality is crucial to the success of the industrial cluster policy. The flowchart for the hi-technology industry is different from the one for the automobile industry cluster.

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In India, as the production of passenger cars increased, many local small and medium enterprises (SMEs) entered the parts and components manufacturing sector. The sources of knowledge for large enterprises and SMEs are different. Naturally, spillover effects among large enterprises and between large enterprises and SMEs are different. This paper focuses on knowledge spillover among large enterprises and from large enterprises to SMEs. Subcontractor can absorb relation-specific skills through repeated interaction with parent company. The results of field survey emphasizes that relation-specific skills are a determinant factor of spillover effects from assemblers and large auto component manufacturers to SMEs. Econometric analysis shows that spillover effects among medium and large automobile units and from medium and large automobile units to small units went beyond boundary of cluster.

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This paper proposes a general model of the flowchart approach to industrial cluster policy and applies this model to Guangzhou's automobile industry cluster. The flowchart approach to industrial cluster policy is an action plan for prioritizing policy measures in a time-ordered series. We reached the following two conclusions. First,we clarified the effects of Honda, Nissan, and Toyota on agglomeration in Guangzhou's automobile industry cluster. Second, we established that local governments play a crucial role in successful industrial cluster policy, and that the mayor of the local government should be offered incentives in order to target industrial clustering and implement cluster policy.

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In this paper, we apply a flowchart approach to investigate Malaysia's automobile cluster policy. We investigate whether the industrial cluster policy has been successful or not, suggest policy prescriptions, and propose a way to prioritize policy measures. Our flowchart approach leads to the following three policy prescriptions: (1) Malaysian firms should establish sites for exporting compact cars with automatic transmissions; (2) actors in the public, semi-public and private sector should work to upgrade skilled labor; and (3) the central government should promote liberalization and deregulation to attract foreign firms into the supporting industries.

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This study aims to examine the international value distribution structure among major East Asian economies and the US. The mainstream trade theory explains the gains from trade; however, global value chain (GVC) approach emphasises uneven benefits of globalization among trading partners. The present study is mainly based on this view, examining which economy gains the most and which the least from the East Asian production networks. Two key industries, i.e., electronics and automobile, are our principle focus. Input-output method is employed to trace the creation and flows of value-added within the region. A striking fact is that some ASEAN economies increasingly reduce their shares of value-added, taken by developed countries, particularly by Japan. Policy implications are discussed in the final section.

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This paper proposes a mechanism that links industry’s technological characteristics (i.e. quality of non-labor inputs, which is proxied by the length of industry production chains), industry-specific skill wage premium, and skill sorting across industries. It is hypothesized that high-skilled workers are sorted into industries where they can receive a higher skill wage premium, by working with better quality non-labor input. The quality of non-labor inputs is assumed to be worse in industries with longer production chains due to the increased involvement of low-skilled labor and poor infrastructure over the sequential production. By examining Indian wage and employment data for 1999-2000, empirical evidence to support this mechanism can be obtained: First, the skill wage premium is lower [higher] in industries with longer [shorter] production chains. Second, the skill wage premium is lower [higher] in industries with a higher [lower] proportion of low-skilled workers producing inputs outside their own industry. Third, the proportion of high-skilled workers is larger in industries with shorter production chains and lower ratio of low-skilled labor involved, i.e., a skill sorting trend can be observed.

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The paper examines the development and restructuring of the iron and steel industry in Asian countries. Studying countries that have integrated steelworks with large blast furnaces (South Korea, Taiwan, China and India) and countries without (Thailand, Indonesia and Malaysia), the paper shows the difference in the development processes across the countries and across time, and points to the diversity of the development experience of these countries. The paper argues that significant differences in steel production technologies in terms of initial investment and minimum-efficient scale, the changing role of the state, and shifting demand structures in the domestic steel markets of each country have been the important factors that led to the differences in the development path of the steel industry in each country.