• Title/Summary/Keyword: Multi-Period Input-Output Analysis

Search Result 13, Processing Time 0.02 seconds

Evaluating the Multi-Period Management Efficiency of Domestic Online-Shopping Companies (DEA와 Malmquist 생산성지수를 이용한 우리나라 온라인쇼핑업체의 다기간 경영 효율성 분석)

  • Ma, Jin-Hee;Ja, Yoon-Ho;Ahn, Young-Hyo
    • Journal of Distribution Science
    • /
    • v.13 no.4
    • /
    • pp.45-53
    • /
    • 2015
  • Purpose - Online shopping enables consumers to conveniently purchase products irrespective of the time and place. As a result, several online shopping companies have emerged to cater to this growing market and, therefore, the competition among them has become increasingly intense. This paper evaluates the comparative efficiency of online shopping companies for a multi-year period (2009-2013), in order to help online shopping managers identify major drivers for enhancing management efficiency and the subsequent competitiveness. Research design, data, and methodology - The researchers collected the data from 2009 to 2013 from the distribution yearbook. This paper analyzes the marketability (sales figures), profitability (business profits), and management conditions (net profits) of domestic online shopping enterprises by incorporating information on human resources (number of employees) and material resources (total assets and capital). Therefore, the number of employees, total assets, and capital are selected as input variables, and sales figures, business profits, and net profits as the output variables. In this study, Data Envelopment Analysis (DEA) was used to measure the comparative efficiency of domestic online shopping companies. In addition, the Malmquist Productivity Index was used to evaluate the trend of change of Decision Making Units' (DMUs') efficiency for a multi-year period. Results - First, as of 2013, Interpark (2.415) was found to be the most efficient online shopping enterprise, followed by Aladdin Communications (2.117), Hyundai Home shopping (1.867), Home&Shopping (1.176), NS Home shopping (1.170), Commerce Planet (1.126), CJ O Shopping (1.105), Ebay Korea (1.088), and GS Home Shopping (1.051). Second, this study recognizes how the management efficiency has changed for the period 2009-2013. Third, the lesser the capital and employees, the more are the net profits, and the better is the management efficiency of domestic online shopping companies. Lastly, the productivity of such companies is influenced by endogenous factors rather than exogenous factors such as shifts in business environment and technological advances. Conclusions - DHC Korea influenced various distribution channels to reach customers through the Internet. Consequently, this helped in increasing the awareness about its products, in addition to an increase in sales. These achievements can be attributed to the characteristics of online shopping companies. Although it is easy for these companies to suggest goods for one-off purchases, they however have difficulties in retaining customers. Overcoming this challenge can be one of the ways to benchmark a successful case of an efficient company. For example, an online shopping company can attract customers by developing a corresponding mobile application as a convenient way to shop online. Additionally, they can satisfy customers by quick delivery of purchased products, which is possible by building an effective logistics network. Our study indicates that the productivity of an online shopping company was influenced by endogenous factors driven by improvements in managerial practices rather than exogenous factors. Accordingly, online shopping companies should adopt strategies to improve their operational efficiency rather than sales volume-oriented management.

Comparative Analysis on Efficiency and Productivity for Korea, Japan and Global Parcel Delivery Companies (한국, 일본, 글로벌 택배기업의 효율성 및 생산성 비교 분석)

  • Ma, Jin-Hee;Ahn, Young-Hyo
    • Journal of Distribution Science
    • /
    • v.14 no.3
    • /
    • pp.73-83
    • /
    • 2016
  • Purpose - The parcel delivery service(courier) industry all over the world has been expanding its market so far, but its growth has been declining in recent years. In this situation, most parcel delivery companies are having trouble with managing themselves because of the pressure from the customer to increase service level and decrease the rate. The purpose of this study is to provide ways to improve competitive advantages of the parcel delivery service industry by evaluating the multi-period operating efficiency of Korea, Japan and global service providers. Research design, data, and methodology - The data for the period of 2011 to 2014 were collected from the annual reports published by parcel delivery companies. In this study, we analyze the marketability (revenue), profitability (operating profits), and management conditions (net profits) of parcel service companies by combining information on human resources (number of employees) and material resources (total assets and equity). Therefore, the number of employees, total assets, and equity are selected as input variables, and revenue, operating profits, and net profits as the output variables. In this study, DEA (Data Envelopment Analysis) is used to measure the comparative efficiency and MPI (Malmquist Productivity Index) is used to analyze the trend of change of the efficiency for a multi-year period. Results - The operational efficiency scores of medium-sized parcel delivery companies in Korea are higher than other larger competitors such as Korean, Japan and Global larger companies. As of 2014, Logen(1.878) was found to be the most efficient parcel delivery enterprise, followed by KGB (1.224), and Kyoungdong(1.002). Otherwise, Hanjin(0.235), CJ(0.262), Hyundai Logistics(0.657), DHL(0.611), UPS(0.766), FedEx(0.498), TNT(0.350), Yamato(0.762) and Sagawa(0.520), larger sized companies, were done inefficiently. The productivity of parcel delivery companies is influenced by endogenous factors as well as exogenous ones such as changes in business environment and technological advances. Conclusions - Korean medium-sized companies have relatively high efficiency scores in operation. That is why they still survive the competitive market in Korea where market restructuring on the industry has been expected to be conducted for many years. The reason why medium-sized couriers had higher efficient scores than larger couriers is that most of couriers spend more operating expenses versus unit price of delivery which is the amount of money that is needed in order to send a package by parcel service. So the delivery unit price must be taken into account by all the expenses associated with the cost of fuel, labor and maintenance expenses for facilities, etc. therefore, the unit price must be increased to strengthen business competitive power. In order for the industry to have more competitive advantage, the companies need to make profits by increasing demand volume and raising the delivery rate to provide high-quality delivery service to customers. And both endogenous and exogenous change must take precedence in order to strengthen their competitiveness.

Application of recurrent neural network for inflow prediction into multi-purpose dam basin (다목적댐 유입량 예측을 위한 Recurrent Neural Network 모형의 적용 및 평가)

  • Park, Myung Ky;Yoon, Yung Suk;Lee, Hyun Ho;Kim, Ju Hwan
    • Journal of Korea Water Resources Association
    • /
    • v.51 no.12
    • /
    • pp.1217-1227
    • /
    • 2018
  • This paper aims to evaluate the applicability of dam inflow prediction model using recurrent neural network theory. To achieve this goal, the Artificial Neural Network (ANN) model and the Elman Recurrent Neural Network(RNN) model were applied to hydro-meteorological data sets for the Soyanggang dam and the Chungju dam basin during dam operation period. For the model training, inflow, rainfall, temperature, sunshine duration, wind speed were used as input data and daily inflow of dam for 10 days were used for output data. The verification was carried out through dam inflow prediction between July, 2016 and June, 2018. The results showed that there was no significant difference in prediction performance between ANN model and the Elman RNN model in the Soyanggang dam basin but the prediction results of the Elman RNN model are comparatively superior to those of the ANN model in the Chungju dam basin. Consequently, the Elman RNN prediction performance is expected to be similar to or better than the ANN model. The prediction performance of Elman RNN was notable during the low dam inflow period. The performance of the multiple hidden layer structure of Elman RNN looks more effective in prediction than that of a single hidden layer structure.