The research aimed to measure the efficiency of using multi stores in a foodservice company using by DEA (data envelopment analysis) which is a new management science technique. The study also attempted to identify relevant variables affecting DEA efficiency in order to suggest methods for improving efficiency. The data were collected from 148 contract foodservice operations, which were operated in similar fashion in October 2009. The DEA efficiency was calculated as an output-oriented BCC Model. Sales, and CSI (customer satisfaction index) were used as output variables whereas food cost, labor cost, and management expense were used as input variables to calculate the DEA efficiency. Operation process variables of the unit consisted of the were consist of ratio of regular employee, ratio of housekeeper, meal counts, meal price, food cost per meal, contract period, number of menu items, forecasting accuracy, order accuracy, inventory turnover, use of processed food, deviation of food cost, number of new menus, and number of events. According to the BCC score and profitability, units were classified into four groups: High efficiency-high profitability (HEHP), High efficiency-low profitability (HELP), Low efficiency-high profitability (LEHP), and Low efficiency-low profitability (LELP). The HEHP group contained 54 units, which mostly contracted management fee type and had a high meal price. The units were also very large and, served three meals. Twenty of the units were operated with high labor cost: most of these were factories and hospitals. The LEHP group contained 20 units, that were mainly office stores of large scale and medium price. Fifty-four LELP group had a low meal price. A high performance group must have high efficiency, profitability, and satisfaction. The BCC score was over 0.969, the meal price was over 4,116 won, the food cost was over 2,077 won, and meal counts per month were over 10,212 meals.
The purpose of this study is to analyze the technical efficiency and its determinants for Korean Apiculture farming by using from door to door and e-mail inquiry data. The analysis was implemented through the Cobb-Douglas stochastic frontier production function (SFPF) model including the technical inefficiency effect model for cross-sectional data. To measure the SFPF model, honey production was used for a dependent variable, and for input variables labor cost, preventive cost, material cost, feeding cost, depreciation cost were used. Farmer's age, farmer's career, farming scale, full-time or half-time firm and movement or fixed firm variables were used to measure the inefficiency effect model. The average technical efficiency on apiculture farming in Korea is estimated to be 0.8112. It means that there were technical inefficiency of about 18.88% in Korea apiculture farming. In this study there are some suggestions which could increase the technical efficiency of Korean apiculture farming.
We investigate the effect of introduction of the bancassurance system on cost efficiency in the Korean insurance industry between 1997 and 2012. Our estimation results indicate that introduction of this system contributed positively to efficiency of life insurance companies in Korea. Increase in a one standard deviation of bancassurance increases cost efficiency by 0.08 which is equivalent to 12 percent of mean cost efficiency. Recognising that the bancassurance system is a relatively new concept, our results indicate that the bancassurance system can be a policy measure to improve productivity in an emerging insurance market. The results illustrate that positive effects have accrued particularly to medium-sized companies and domestic companies, contrary to the prevailing perception that increased competition through bancassurance is more beneficial to large companies and foreign companies.
Purpose - Despite the importance of price, many companies do not implement pricing policies smoothly, because typical price management strategies insufficiently consider logistics efficiency and an increase in logistics costs due to logistics waste. This study attempts to examine the effect of product line pricing, which corresponds to product mix pricing, on logistics efficiency in the case of manufacturer A, and analyzes how logistics performance changes in response to these variables. Research design, data, and methodology - This study, based on the case of manufacturer A, involved research through understanding the current status, analyses, and then proposing improvement measures. Among all the products of manufacturer A, product group B was selected as the research object, and its distribution channel and line pricing were examined. As a result of simulation, for products with low loading efficiency, improvement measures such as changing the number of bags in the box were suggested, and a quantitative analysis was conducted on how these measures influence logistics costs. The TOPS program was used for the Pallet loading efficiency simulation tool in this study. To prevent products from protruding out of the pallet, the maximum measurement was set as 0.0mm, and loading efficiency was based on the pallet area, and not volume. In other words, its size (length x width) was focused upon, following the purpose of this study and, then, the results were obtained. Results - As a result of the loading efficiency simulation, when the number of bags in the box was changed for 36 products with low average loading efficiency of 73.7%, as shown in