환경서비스업과 물류서비스업의 예측 및 인과성 검정 (Prediction and Causality Examination of the Environment Service Industry and Distribution Service Industry)

서지정보

· 발행기관 : 한국유통과학회
· 수록지 정보 : 유통과학연구 / 12권 / 6호 / 49 ~ 57페이지
· 저자명 : 선일석, 이충효

초록

Purpose - The world now recognizes environmental disruptionas a serious issue when regarding growth-oriented strategies;therefore, environmental preservation issues become pertinent.
Consequently, green distribution is continuously emphasized.
However, studying the prediction and association of distributionand the environment is insufficient. Most existing studies aboutgreen distribution are about its necessity, detailed operationmethods, and political suggestions; it is necessary to study thedistribution service industry and environmental service industrytogether, for green distribution.
Research design, data, and methodology - ARIMA (auto-regressivemoving average model) was used to predict the environmentalservice and distribution service industries, and theGranger Causality Test based on VAR (vector auto regressive)was used to analyze the causal relationship. This study used 48quarters of time-series data, from the 4th quarter in 2001 to the3rd quarter in 2013, about each business type’s production index,and used an unchangeable index. The production indexabout the business type is classified into the current index andthe unchangeable index. The unchangeable index divides thecurrent index into deflators to remove fluctuation. Therefore, it iseasy to analyze the actual production index. This study usedthe unchangeable index.
Results – The production index of the distribution service industryand the production index of the environmental service industryconsider the autocorrelation coefficient and partial autocorrelationcoefficient; therefore, ARIMA(0,0,2)(0,1,1)4 andARIMA(3,1,0)(0,1,1)4 were established as final prediction models,resulting in the gradual improvement in every production indexof both types of business. Regarding the distribution service in-dustry’s production index, it is predicted that the 4th quarter in2014 is 114.35, and the 4th quarter in 2015 is 123.48.
Moreover, regarding the environmental service industry’s productionindex, it is predicted that the 4th quarter in 2014 is110.95, and the 4th quarter in 2015 is 111.67.
In a causal relationship analysis, the environmental service industryimpacts the distribution service industry, but the distributionservice industry does not impact the environmentalservice industry.
Conclusions - This study predicted the distribution service industryand environmental service industry with the ARIMA model,and examined the causal relationship between them throughthe Granger causality test based on the VAR Model. Predictionreveals the seasonality and gradual increase in the twoindustries. Moreover, the environmental service industry impactsthe distribution service industry, but the distribution service industrydoes not impact the environmental service industry. Thisstudy contributed academically by offering base line data neededin the establishment of a future style of management andpolicy directions for the two industries through the prediction ofthe distribution service industry and the environmental serviceindustry, and tested a causal relationship between them, whichis insufficient in existing studies. The limitations of this study arethat deeper considerations of advanced studies are deficient,and the effect of causality between the two types of industrieson the actual industry was not established.

영어초록

Purpose - The world now recognizes environmental disruptionas a serious issue when regarding growth-oriented strategies;therefore, environmental preservation issues become pertinent.
Consequently, green distribution is continuously emphasized.
However, studying the prediction and association of distributionand the environment is insufficient. Most existing studies aboutgreen distribution are about its necessity, detailed operationmethods, and political suggestions; it is necessary to study thedistribution service industry and environmental service industrytogether, for green distribution.
Research design, data, and methodology - ARIMA (auto-regressivemoving average model) was used to predict the environmentalservice and distribution service industries, and theGranger Causality Test based on VAR (vector auto regressive)was used to analyze the causal relationship. This study used 48quarters of time-series data, from the 4th quarter in 2001 to the3rd quarter in 2013, about each business type’s production index,and used an unchangeable index. The production indexabout the business type is classified into the current index andthe unchangeable index. The unchangeable index divides thecurrent index into deflators to remove fluctuation. Therefore, it iseasy to analyze the actual production index. This study usedthe unchangeable index.
Results – The production index of the distribution service industryand the production index of the environmental service industryconsider the autocorrelation coefficient and partial autocorrelationcoefficient; therefore, ARIMA(0,0,2)(0,1,1)4 andARIMA(3,1,0)(0,1,1)4 were established as final prediction models,resulting in the gradual improvement in every production indexof both types of business. Regarding the distribution service in-dustry’s production index, it is predicted that the 4th quarter in2014 is 114.35, and the 4th quarter in 2015 is 123.48.
Moreover, regarding the environmental service industry’s productionindex, it is predicted that the 4th quarter in 2014 is110.95, and the 4th quarter in 2015 is 111.67.
In a causal relationship analysis, the environmental service industryimpacts the distribution service industry, but the distributionservice industry does not impact the environmentalservice industry.
Conclusions - This study predicted the distribution service industryand environmental service industry with the ARIMA model,and examined the causal relationship between them throughthe Granger causality test based on the VAR Model. Predictionreveals the seasonality and gradual increase in the twoindustries. Moreover, the environmental service industry impactsthe distribution service industry, but the distribution service industrydoes not impact the environmental service industry. Thisstudy contributed academically by offering base line data neededin the establishment of a future style of management andpolicy directions for the two industries through the prediction ofthe distribution service industry and the environmental serviceindustry, and tested a causal relationship between them, whichis insufficient in existing studies. The limitations of this study arethat deeper considerations of advanced studies are deficient,and the effect of causality between the two types of industrieson the actual industry was not established.

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