• Journal of Distribution Science
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• v.12 no.4
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• pp.23-30
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• 2014

Purpose - The purpose of this study is to analyze the efficiency of retail businesses by dividing domestic retailers into discount stores, super supermarkets (SSMs), and department stores. It suggests retail-business investment strategies by using data environment analysis (DEA) to analyze how input elements such as store area, parking lot area, number of employees, and sales management expenses for the convenience of customers positively affect business performance measurements such as sales and visiting customers per day. Research Design, Data, and Methodology - The DEA model calculates a ratio of the weighted mean of various inputs to the weighted mean of various outputs and measures the efficiency of a specific decision making unit (DMU). The study included 19 companies (five discount store DMUs, ten SSM DMUs, and four department store DMUs). Because the business elements and sizes of retail store DMUs used in this analysis are different, average per-store input and output variables were used. Data were collected from "The Yearbook of Retail Industry in Korea (2012)." DEA analysis was used to determine differences in efficiency among discount stores, SSMs, and department stores in terms of the business elements of each retail business. It was also used to determine what business elements were excessively invested in by comparing and analyzing efficiency by business elements using SPSS software's ANOVA (Analysis of Variance). Results - The CCR and BCC efficiency analysis found that the efficiency of discount stores is low. We believe that the saturation state of discount stores is a major factor. The ANOVA analysis confirms the VRS hypothesis with a statistically significant difference among the three groups, based on an analysis confidence interval of 95%. CRS and SE were not found to be significantly different among the three groups. As for the post hoc test, which concretely shows differences by group, the Scheffe's multiple comparison analysis test found the average differences between group 1 (discount stores) and group 2 (SSM) to be statistically significant. Conclusions - The DEA efficiency analysis implies that investment in input elements, including store area, parking lot area, and sales management expenses, were excessive in the case of discount stores, while SSMs need to invest more in promotion activities such as gifts, events, and coupons for customer management. Department stores have found that small companies invest excessively in input elements. Department stores need to invest in differentiated shopping mall complexes. This study was limited in acquiring statistical data; various input variables which might have shown more secure customer management and promotional expenses could not be applied. As the study was limited in various aspects of the efficiency analyses because financial analyses of the companies and of causal relationships, including satisfaction and loyalty of visiting customers, were not done, these aspects will be examined in the next study.

• 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.