In today's low-growth business environment, efficiency management is becoming more important to improve corporate sustainability. In a chain store, the efficiency of individual stores must be well managed to improve the efficiency of the entire enterprise. To do this, it is important to measure the efficiency of individual stores and to find factors that affect efficiency. The main purpose of this study is to find out the factors affecting the efficiency of chain stores and to analyze the results to find out the implications that contribute to an improvement in efficiency. We measured the relative efficiency of individual stores using data envelopment analysis (DEA) and analyzed the factors that affect efficiency with the Tobit regression model. As a result, we found that the number of items per employee and a competitive environment influence the efficiency of stores. An excessive number of items may cause efficiency to be lowered. Therefore, it is necessary to manage the life cycle of the product, considering the trade-off between assortment and efficiency. Competition helps to improve efficiency to some extent, but too much competition can reduce efficiency.

Abstract:The purpose of this paper is to study consumer acceptance of the Home Energy Management System, which is the next generation electronic management system that the Korean government plans to implement in households. The Home Energy Management System is a critical device in maximizing the efficiency of electric energy consumption for each household by using a smart grid. Because it can visualize real-time price information on the electricity, households can easily monitor and control the amount of electricity consumption. With this feature, the Home Energy Management System can contribute to consumers' total energy savings. This is a major reason why the Korean government wishes to implement it nationwide. Since the Home Energy Management System is a product that applies new technology that has not yet been directly encountered by consumers, there may be a difference in the level of public perception of the Home Energy Management System. Therefore, the impact of consumers' awareness of the Home Energy Management System on their intention to use is important. To do this, the Technology Acceptance Model is utilized in this study. Traditional research on the Technology Acceptance Model includes awareness of usefulness and ease of use as well as intention to use. In contrast, in this research, an extended Technology Acceptance Model with four additional factors-economic benefit, social contribution, environmental responsibility, and innovativeness-that may affect the consumer's awareness of usefulness and ease of use, is proposed. To collect the data, the survey was conducted with 287 respondents. As a result, the proposed model proved to be suitable in explaining the intention to use with a 70.3% explanation power. It is found that economic benefit (0.231) and innovativeness (0.259) impact on usefulness of the Home Energy Management System. Moreover, usefulness (0.551) has a bigger effect on intention to use than ease of use (0.338) does. Based on this, it is desirable for the Korean government to pursue a public relations strategy that emphasizes the economic benefits, social contributions, and environmental responsibility that will be gained when introducing the Home Energy Management System. It is effective to focus on consumers who are inclined to accept innovation. In addition, more effective results can be obtained by referring to the usefulness of the Home Energy Management System rather than referring to ease of use.

This paper analyzes the operational efficiency of 91 individual retail stores in Seoul by a two-step procedure.In the first step, a data envelopment analysis (DEA) model is used to identify the efficiency scores. Three inputs (store size, number of items, and number of employees) and two outputs (sales and number of customers) are used for the efficiency measurement. In the second step, a Tobit regression model is used to identify the drivers of efficiency. DEA efficiency scores are used to test hypotheses on the impact of five independent variables, namely store age, number of items per store size, number of items per employee, trade area index, and number of competitors.Results of the Tobit analysis show that number of items per store size, number of items per employee, and number of competitors play a significant role in influencing the operational efficiency of retail stores. Managerial implications of the study are discussed.