[논문]Analysis on Logistics Efficiency of China's Agricultural Products Cold Chain from the Green Perspective

Qi, Lu; Chung, Gi-Young; Kim, Hyung-Ho

doi:10.17703/ijact.2020.8.2.192

Analysis on Logistics Efficiency of China's Agricultural Products Cold Chain from the Green Perspective 원문보기

The International journal of advanced culture technology, v.8 no.2, 2020년, pp.192 - 203

Qi, Lu (Dept. of Marketing Management, Jilin Engineering Normal University) , Chung, Gi-Young (Dept. of Business Management, Sehan University) , Kim, Hyung-Ho (Dept. of Air Transport and Logistics, Sehan University)

Abstract ▼ AI-Helper

Although the market demand for cold-chain logistics of agricultural products in China is growing rapidly, the technology and scale of cold-chain logistics in China still lag behind the developed countries, resulting in large energy consumption. In our country, many authors have studied the efficiency of cold-chain logistics by using analytic hierarchy process and data envelopment method, but they haven't eliminated the influence of environmental factors and random error factors on the efficiency of cold-chain logistics, and most of them are limited to regional research. Therefore, in this paper, the three-stage DEA method is used. Based on the green logistics idea, firstly, the efficiency of 29 listed logistics enterprises in China is analyzed. Secondly, this paper uses SFA model to exclude the influence of environment and error factors on the analysis results, taking the enterprise's operating years, local GDP and the proportion of cold chain assets as environmental variables. Finally, this paper estimates the efficiency value again by adjusting the input value. The results are as follows: the main reason of high efficiency enterprises is to achieve scale efficiency. So the scale of assets should be maintained or appropriately expanded. At the same time, the economic development and the number of years of enterprise establishment will significantly affect the efficiency of cold-chain logistics. The influence of these environmental variables on the accuracy of the analysis conclusion should be fully considered.

주제어

표/그림 (6)

표 Table 1. Input and output indicators in related research
표 Table 2. Statistical table of expert questionnaire on performance evaluation indicators
표 Table 3. Input-output index correlation test
표 Table 4. Statistics on Input/Output Data
표 Table 5. Results of SFA regression analysis in the second stage
표 Table 6. Results of DEA analysis in the third stage

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제안 방법

Based on this, this paper tries to build a cold-chain logistics enterprises based on green logistics system efficiency evaluation, and using the three stage DEA model to analyze China's cold chain logistics enterprise efficiency problems, aim to fill the blank of the relevant theoretical research in the field of, at the same time for the construction of ecological civilization under the background of China's cold chain logistics enterprise efficiency to provide a new train of thought.
The selection of input-output indicators directly affects the analysis results of logistics efficiency. In order to select the most representative input-output variables to evaluate the efficiency of cold chain logistics enterprises, the author sorted out the selection of indicators with high frequency in relevant research results at home and abroad, as shown in table 1.
In view of the above indicators, the author specially sent questionnaires to 23 experts in the field of agricultural products cold chain logistics, and asked them to judge the importance of each performance indicator, and the importance degree was divided into five levels. A total of 23 questionnaires were distributed and 23 were returned, among which 19 were valid, with the effective recovery rate of 82.
The basic idea is as follows: firstly, the traditional DEA model is used to analyze the relationship between input data and output data to obtain the difference between the enterprise's efficiency value and input value.
The first step on the right of the above formula is to adjust the selected analysis samples to the common operating environment, and set all the enterprises to the same environment variables. The second step is to set the natural state of all enterprises as the most unfavorable operating opportunity state, so as to make each sample DMU face the same operating environment and natural state, so as to analyze the efficiency problem more objectively.
The basic idea is as follows: firstly, the traditional DEA model is used to analyze the relationship between input data and output data to obtain the difference between the enterprise's efficiency value and input value. Then, the influence of selected environmental variables on the difference value was analyzed, and the SFA model was used to adjust the input items of sample enterprises, in order to eliminate the error caused by the influence of environmental and error factors on the analysis results. Finally, DEA model is used to analyze the adjusted input data and the original output data.
Since the input-oriented DEA model was adopted in the first stage, three factors, namely environmental impact, management inefficiency and statistical noise, would affect the input variables and thus affect the output. Therefore, it is necessary to further analyze the difference between the ideal input and the actual input in order to further adjust the input value and re-estimate the efficiency value which is not affected by environmental factors and random errors.
In terms of logistics efficiency evaluation, input variables are the basic variables of decision-making, which are easy to control, while output variables are relatively difficult to control. Therefore, this paper chooses the investment-oriented BCC model for the first stage analysis. The comprehensive efficiency, pure technical efficiency and scale efficiency of the selected 29 logistics enterprises were calculated by using DEA software Dea-Solver8.

성능/효과

In view of the above indicators, the author specially sent questionnaires to 23 experts in the field of agricultural products cold chain logistics, and asked them to judge the importance of each performance indicator, and the importance degree was divided into five levels. A total of 23 questionnaires were distributed and 23 were returned, among which 19 were valid, with the effective recovery rate of 82.61%. The results of the questionnaire survey are shown in table 2.
Proportion of cold chain assets: The analysis results show that the regression coefficient of the proportion of cold chain assets of logistics enterprises is positive to the net value of fixed assets, employees' salary, investment rate of cold chain technology and investment rate of environmental protection, indicating that the increase of cold chain business will cause the efficiency of these inputs to decrease, such as it will cause too much investment in cold chain technology and form waste.
This paper USES the three-stage DEA model to make an empirical analysis of the efficiency of 29 cold chain logistics enterprises in China in 2018. The conclusions are as follows: first, the inefficiency of inefficient enterprises in Chinese logistics enterprises mainly comes from the inefficiency of scale, and the main reason for the inefficiency of scale is that these cold chain logistics enterprises are relatively small in scale. Second, more than half of the selected cold-chain logistics enterprises have acceptable efficiency, the main reason is to achieve scale efficiency, these enterprises should maintain or moderately expand the scale of assets, give play to the advantages of economies of scale.
Guo studied and analyzed the efficiency of green logistics in Guangdong province as a whole and in all prefect-level cities by combining with DEA method. The research results show that: the overall efficiency of Guangdong province fluctuates greatly, while the green efficiency of logistics industry in prefecture-level cities fluctuates little and is in a process of benign development^[6]. Z.

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