• Journal of Digital Convergence
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• v.18 no.1
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• pp.35-44
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• 2020

The purpose of this paper is to investigate various factors affecting the efficiency of China IC industry, reflecting the resource utilization and overall development level of China IC industry. In this paper, three input indicators (R&D Expenditure, Cash paid to and for employees, Total fixed assets) and two output indicators (Net profit, Sales revenue) were selected for 17 listed companies in the IC industry with operating profit of less than 1 billion yuan in 2018 and applied the technology efficiency theory and DEA analysis method to analyze the relative efficiency of the output base. The study found that one of the 17 companies analyzed was efficient, two were inefficient on an inadequate scale, and the rest were inefficient due to insufficient production technology, scale and management level. This study argues that enterprises should reduce resource input appropriately and strengthen scientific and technological innovation management to maximize resource utilization efficiency. Therefore, this study has important practical significance for improving the efficiency of IC enterprises. The Malmquist method will be used to study the total factor productivity of small and Medium-sized companies in IC industry.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.4
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• pp.71-102
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• 2007

There were many comprehensive analyses conducted within the existing research activities wherein factors affecting technology progress including investment in R&D vis-${\Box}$-vis their influences act as the determinants of TFP. Note, however, that there were few comprehensive analysis in the industrial research performed regarding the impact of the economy of scale as it affects TFP; most of these research studies dealt with the analysis of the non -parametric Malmquist productivity index or used the stochastic frontier production function models. No comprehensive analysis on the impacts of individual independent variables affecting TFP was performed. Therefore, this study obtained the TFP increase rate of each industry by analyzing the factors of the existing growth accounting equation and comprehensively analyzed the TFP determinants by constructing a comprehensive analysis model considering the investment in R&D and economy of scale (smallness by industry) as the influencers of TFP by industry. First, for the TFP increase rate of the 15 industries as a whole, the annual average increase rate for 1993${\sim}$ 1997 was approximately 3.8% only; during 1999${\sim}$ 2000 following the foreign exchange crisis, however, the annual increase rate rose to approximately 7.8%. By industry, the annual average increase rate of TFP between 1993 and 2000 stood at 11.6%, the highest in the electrical and electronic equipment manufacturing business and IT manufacturing sector. In contrast, a -0.4% increase rate was recorded in the furniture and other product manufacturing sectors. In the case of the service industry, the TFP increase rate was 7.3% in the transportation, warehousing, and communication sectors. This is much higher than the 2.9% posted in the electricity, water, and gas sectors and -3.7% recorded in the wholesale, food, and hotel businesses. The results of the comprehensive analysis conducted on the determinants of TFP showed that the correlations between R&D and TFP in general were positive (+) correlations whose significance has yet to be validated; in the model where the self-employed and unpaid family workers were used as proxy variables indicating the smallness of industry out of the total number of workers, however, significant negative (-) correlations were noted. On the other hand, the estimation factors of variables surrogating the smallness of scale in each industry showed that a consistently high "smallness of scale" in an industry means a decrease in the increase rate of TFP in the same industry.