Machine Learning Approach to the Effects of the Superstore Mandatory Closing Regulation

@article{ART002558517},
author={ 안지영 and Heedae PARK },
title={Machine Learning Approach to the Effects of the Superstore Mandatory Closing Regulation},
journal={유통과학연구},
issn={1738-3110},
year={2020},
volume={18},
number={2},
pages={69-77},
doi={10.15722/jds.18.2.202002.69},
url={http://dx.doi.org/10.15722/jds.18.2.202002.69}

TY - JOUR
AU - 안지영
AU - Heedae PARK
TI - Machine Learning Approach to the Effects of the Superstore Mandatory Closing Regulation
T2 - 유통과학연구
PY - 2020
VL - 18
IS - 2
PB - 한국유통과학회
SP - 69-77
SN - 1738-3110
AB - Purpose – This paper is aimed to analyze the effects of the mandatory closing regulation targeting large retailers, which has been implemented since 2012 to protect small retailers. We examine the changes in consumers' choice of retailers and their purchasing patterns of agri-food following the implementation of such regulation. Research design, data, and methodology – Household spending patterns were identified through the historical data of household food purchase, consumer panel provided by the Rural Development Administration. Clustering was employed to determine the household spending patterns. Moreover, the different household spending patterns before and after the regulation were comparatively studied. The patterns of consumers' choice of retail stores and shopping baskets by the type of retailers, derived from the respective datasets before and after the regulation, were compared to analyze the effects of the regulation. Results –After the regulation, some consumers who used to shop at large retailers before the regulation changed their shopping places to small retailers. However, the product categories that consumers had mainly purchased before the regulation were rarely changed even after the regulation. Conclusions – Although the regulation helped migrate some of the consumers to small retailers, the regulation seemed to have failed to stimulate consumers to purchase the goods, normally bought at large retailers, from traditional markets. In other words, traditional markets are not effective substitutes for regulation-affected retailers.
KW - Superstore Mandatory Closing Regulation, Retail Industry, Consumer Behavior, Machine Learning, Clustering
DO - 10.15722/jds.18.2.202002.69
UR - http://dx.doi.org/10.15722/jds.18.2.202002.69
ER -

안지영 and Heedae PARK (2020). Machine Learning Approach to the Effects of the Superstore Mandatory Closing Regulation. 유통과학연구, 18( 2), 69- 77.

안지영 and Heedae PARK . 2020, “Machine Learning Approach to the Effects of the Superstore Mandatory Closing Regulation”, 유통과학연구, vol. 18, no. 2, pp. 69-77. Available from: doi:10.15722/jds.18.2.202002.69

안지영 Heedae PARK et al. “Machine Learning Approach to the Effects of the Superstore Mandatory Closing Regulation” 유통과학연구 18.2 pp. 69-77 (2020): 69.

안지영 , Heedae PARK . Machine Learning Approach to the Effects of the Superstore Mandatory Closing Regulation 유통과학연구 [Internet]. 2020; 18( 2), : 69-77. Available from: doi:10.15722/jds.18.2.202002.69

안지영 and Heedae PARK . “Machine Learning Approach to the Effects of the Superstore Mandatory Closing Regulation” 유통과학연구 18, no.2 (2020): 69-77. doi: 10.15722/jds.18.2.202002.69

홈 권호 목록 논문 목록 논문 상세

Machine Learning Approach to the Effects of the Superstore Mandatory Closing Regulation

유통과학연구

약어 : JDS

2020, vol.18, no.2, pp.69 - 77

DOI : 10.15722/jds.18.2.202002.69

발행기관 : 한국유통과학회

연구분야 : 경제학

안지영¹ , Heedae PARK²

¹Housing Finance Research Institute

²Korea Maritime Institute

인용한 논문 수 : 2 서지 간략 보기

초록

Purpose – This paper is aimed to analyze the effects of the mandatory closing regulation targeting large retailers, which has been implemented since 2012 to protect small retailers. We examine the changes in consumers' choice of retailers and their purchasing patterns of agri-food following the implementation of such regulation. Research design, data, and methodology – Household spending patterns were identified through the historical data of household food purchase, consumer panel provided by the Rural Development Administration. Clustering was employed to determine the household spending patterns. Moreover, the different household spending patterns before and after the regulation were comparatively studied. The patterns of consumers' choice of retail stores and shopping baskets by the type of retailers, derived from the respective datasets before and after the regulation, were compared to analyze the effects of the regulation. Results –After the regulation, some consumers who used to shop at large retailers before the regulation changed their shopping places to small retailers. However, the product categories that consumers had mainly purchased before the regulation were rarely changed even after the regulation. Conclusions – Although the regulation helped migrate some of the consumers to small retailers, the regulation seemed to have failed to stimulate consumers to purchase the goods, normally bought at large retailers, from traditional markets. In other words, traditional markets are not effective substitutes for regulation-affected retailers.

키워드

Superstore Mandatory Closing Regulation, Retail Industry, Consumer Behavior, Machine Learning, Clustering

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