• 한국정보시스템학회지:정보시스템연구
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• 제26권4호
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• pp.17-37
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• 2017

Purpose Customer Loyalty is the most important factor of customer relationship management (CRM). Especially in retailing industry, where customers have many options of where to spend their money. Classifying loyal customers through customers' data can help retailing companies build more efficient marketing strategies and gain competitive advantages. This study aims to construct classification models of distinguishing the loyal customers within a Korean retailing company using data mining techniques with R language. Design/methodology/approach In order to classify retailing customers, we used combination of support vector machines (SVMs) and other classification algorithms of machine learning (ML) with the support of recursive feature elimination (RFE). In particular, we first clean the dataset to remove outlier and impute the missing value. Then we used a RFE framework for electing most significant predictors. Finally, we construct models with classification algorithms, tune the best parameters and compare the performances among them. Findings The results reveal that ML classification techniques can work well with CRM data in Korean retailing industry. Moreover, customer loyalty is impacted by not only unique factor such as net promoter score but also other purchase habits such as expensive goods preferring or multi-branch visiting and so on. We also prove that with retailing customer's dataset the model constructed by SVMs algorithm has given better performance than others. We expect that the models in this study can be used by other retailing companies to classify their customers, then they can focus on giving services to these potential vip group. We also hope that the results of this ML algorithm using R language could be useful to other researchers for selecting appropriate ML algorithms.

• 한국융합학회논문지
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• 제10권6호
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• pp.15-24
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• 2019

본 연구에서는 "신소매(新零售)"에 대한 연구의 참고자료와 실용적 개발을 위한 지침을 제공하기 위해 "신소매"의 연구현황과 이론적 상황을 정리하였다. "신소매"의 발전은 아직 걸음마 단계에 있다. 이론 연구는 이제 막 시작되어, 보다 실용적인 탐구는 있지만 상대적으로 이론적 연구가 부족한 상황이다. 현재, "신소매"의 이론적 연구와 실천적 발전이 점차 명확해지고 있다. 신소매의 급속한 발전은 신소매에 대한 이론적 연구가 강하게 요구되고 있다. "신소매"의 발전 추세는 대규모화, 경계가 없어지며, 지능화 되고 있다. 연구 결과 "신소매" 하에서의 온라인과 오프라인의 심층적 통합, 새로운 물류체계 및 공급망의 전환과 재편을 가속화 되는 것을 알 수 있었다. '신소매업'의 연구방향에 초점을 맞춰 이론과 실천을 더욱 깊이 연구할 필요가 있다.

• 경영과정보연구
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• 제30권3호
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• pp.191-215
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• 2011

소매서비스업은 고객서비스의 제공을 통해 차별화를 시도하면서도 서비스의 생산 및 전달과정에 참여하는 고객의 행동을 관리할 필요가 있다. 소매서비스업에서 고객참여행동을 적절히 활용하기 위해서는 소매서비스업에 따른 고객참여행동의 수준을 보다 면밀히 파악하고 알아야 할 필요가 제기된다. 본 연구에서는 국내의 주요한 소매서비스업을 선별하여 고객참여행동의 수준을 파악해 보고자 한다. 4가지 소매서비스업 유형(접촉의 정도와 참여행동 수준의 정도에 따라 구분된 패밀리 레스토랑, 미용서비스, 병원서비스, 교육서비스)에 따라 고객참여행동의 하위차원 (적극성, 소통성, 교감성, 순응성)이 어떤 수준의 차이를 보이는 지를 실증적으로 확인하고자 한다. 연구의 결과, 적극성과 소통성에 있어서는 소매서비스 유형별로 유의하게 차이가 있는 것으로 나타났으나, 교감성의 경우에는 집단 간의 차이가 유의하지 않았고, 순응성의 경우에는 한계수준에서 집단 간의 차이를 확인할 수 있었다. 네 가지 소매서비스 유형중 가장 고객참여행동의 수준이 높은 소매서비스는 병원서비스이며, 다음으로 패밀리레스토랑, 교육서비스, 그리고 미용실서비스로 나타났다. 이로써, 본 연구는 소매서비스업 유형에 따라 고객참여행동의 내용과 양이 다르다는 것을 실증하였으며, 소매서비스업 유형별 고객참여행동의 수준을 확인하고 이를 고객참여행동 유도전략에 활용할 수 있는 계기를 마련하였다.

• 한국유통학회지:유통연구
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• 제17권2호
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• pp.93-115
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• 2012

본 연구의 목적은 국내 소매업태간 시장점유율 변화가 소비자 물가에 미친 영향을 실증하는데 있다. 소매업태는 백화점, 대형마트, 슈퍼마켓, 편의점, 전문상품소매점, 무점포판매로 분류하였다. 소매업태간 시장점유율은 매월 각 소매업태별 판매액을 합산하여 월별 총소매판매액을 계산한 후, 각 소매업태의 판매액이 총소매판매액에서 차지하는 비율로 측정하였다. 물가지수는 소비자물가지수, 생활물가지수, 신선식품물가지수가 고려되었으며, 아울러 소비자물가지수의 기본분류에 의한 25종류의 제품군별 물가지수와 이들 제품군을 대표할 수 있는 개별 품목 42개가 고려되었다. 통제변수로 환율, M1, 원유가격, 산업생산지수와 같은 거시경제변수가 모형에 추가되어 분석되었다. 자료의 분석기간은 2000년 1월부터 2010년 12월까지이며, 월별자료가 시계열 분석에 이용되었다. 실증분석에 앞서 본 연구에서는 ADF 검정법과 PP검정법을 이용하여 시계열자료의 안정성을 검증하였으며, 단위근 검정에 필요한 모형의 선택과 시차의 선택은 선행연구와 AIC의 기준에 의해 선택하였다. 분석결과, 소매업태간 시장점유율 변화는 물가에 영향을 미치고 있는 것으로 나타났으며, 소매업태별로 소비자물가지수, 생활물가지수, 신선식품물가지수 증감에 미치는 영향력이 차별적으로 나타났다. 또한 25개의 기본 제품군과 각 제품군에서 42개의 대표적인 품목을 추출하여 분석한 결과에서도 소매업태별 시장점유율 변화는 제품군 및 개별 품목의 물가 증감에 유의하게 영향을 미친 것으로 나타났다. 이러한 결과에 대한 이론적 및 실무적 시사점과 향후 연구 영향이 제시되었다.

• Fashion, Industry and Education
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• 제14권1호
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• pp.50-58
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• 2016

Passive learning attitudes and lack of enthusiasm in a retailing math course is quite common and a significant number of students do express their frustrations and struggles by seeking extra help outside the classroom. In order to promote students' active participation in class and to improve their performance and overall satisfaction with the course, a modified team-based learning (TBL) method was implemented in a retailing math course in two consecutive semesters. Implementing TBL into a retailing math course would improve students' accountability for their own learning, increase student interactions and engagement, and develop teamwork and collaboration skills. The scores on the midterm and final tests indicated that students' performance improved especially for the students who scored below 80% on each test when TBL was implemented. Students' reflection on the TBL activities done in class throughout the semester indicated that these TBL activities help them solidify the concepts taught in class better. They were able to realize their own mistakes and other group members who got the question right helped them understand. To maximize the benefit of TBL, it is suggested to implement TBL within the flipped classroom. Further research is called for to evaluate the effect of TBL on long-term knowledge retention among college students.

• Asian Journal of Business Environment
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• 제7권4호
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• pp.35-41
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• 2017

Purpose - This paper aims to examine several time series models to predict sales of department stores and discount store markets in South Korea, while other previous trial has performed sales of convenience stores and supermarkets. In addition, optimal predicted values on the underlying model can be got and be applied to distribution industry. Research design, data, and methodology - Two retailing types, under investigation, are homogeneous and comparable in size based on 86 realizations sampled from January 2010 to February in 2017. To accomplish the purpose of this research, both ARIMA model and exponential smoothing methods are, simultaneously, utilized. Furthermore, model-fit measures may be exploited as important tools of the optimal model-building. Results - By applying Holt-Winters' additive seasonality method to sales of two large-scale retailing types, persisting increasing trend and fluctuation around the constant level with seasonal pattern, respectively, will be predicted from May in 2017 to February in 2018. Conclusions - Considering 2017-2018 forecasts for sales of two large-scale retailing types, it is important to predict future sales magnitude and to produce the useful information for reforming financial conditions and related policies, so that the impacts of any marketing or management scheme can be compared against the do-nothing scenario.

• 한국정보시스템학회지:정보시스템연구
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• 제6권1호
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• pp.223-256
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• 1997

Since the business scales of retailing companies become to be very large and the number of items dealt increases explosively, automation of inventory management becomes one of the most important issues to solve in retailing industry. In order to accomplish this automation of inventory management, there must be a great need to a method which can perform real-time decision making on inventory control in an automatic fashion, while communicating with inventory information systems like POS system and automatic warehousing system. But even in this circumstance, there are also many obstructions to such automation like varying demands, limited capacity of warehouse and exhibition room, need for strategic consideration on inventory control, etc., in a real sense. Due to these reasons, it seems very difficult that most large-scaled retailing companies get fully automated inventory management system. To overcome those difficulties and reflect them into inventory control, we propose a automated inventory control methodology for retailing industry based on neural network and policy model. Especially, policy model is devised to deal with dynamic varying demands and using this model, strategic goals on inventory can be considered into inventory control mechanism. Our proposed approach is implemented in workstation and its performance is also empirically verified also against to real case of one of the major retailing firm in Korea.

• 유통과학연구
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• 제20권8호
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• pp.21-31
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• 2022

Purpose: This study aims to enrich the literature related on Patronage intention in the context of omnichannel in Tunisia. It reveals the determinants of Patronage intention in the fashion retailer context by examining the roles of omnichannel integration quality (IQ), omnichannel perceived value (PV), flexibility, operational logistics service quality (OLSQ) and customer satisfaction. Research design and methodology: A quantitative online survey with 400 customers of fashion retailers was executed. A structural equation modeling approach was applied to test the research hypotheses using AMOS 25 and SPSS 25 software. Results: The findings show that the omnichannel integration quality, omnichannel perceived value, and operational logistics service quality affect play crucial roles in customer satisfaction. A positive relationship between flexibility and operational logistics service quality was also highlighted. And it is also found that a higher omnichannel integration quality led to a higher omnichannel perceived value in the omnichannel retailing context. Furthermore, customer satisfaction within omnichannel retailing can enhance patronage intention. Conclusions: This research adds to the body of knowledge in omnichannel retailing and presents a comprehension of the omnichannel system from the customer's point of view. In addition, this study provides practical implications for omnichannel retailers to improve customer satisfaction and patronage intention.

• 한국의류산업학회지
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• 제12권3호
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• pp.318-326
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• 2010

The advantages of the multi-channel retailing have been widely discussed but empirical research on fashion multi-channel retailing has been limited. In this study, multi-channel concept was discussed and then, channel choosing condition of apparel shopper and channel choosing criteria for information search and buying were investigated as a empirical study. Drawing on a sample of 298 customers of apparel products in Korea, the result demonstrated that some differences in the perception of experience goods and search goods among apparel products. And, according to buying channel, consumers were different from each other in information search time and clothing expenses. Some suggestion for the future research of multi-channel retailing was given.

• 한국생활과학회지
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• 제20권6호
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• pp.1185-1198
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• 2011

This research explores the consumers' experience in retailing channel(offline channel and online channel) using the critical incident technique. This research aims to clarify the common incidents within retailing channels which implies decisive factors over the channels, and to clarify the contrasts between channels to compare advantages and disadvantages. Therefore, the research is designed to collect the consumers' narrative of those who have used both channels in 3 months. Classifications are conducted with other researchers majoring consumer science. The results address how impressive experiences are constructed on each channel in three dimensions: product, information search, and the purchase-service dimension. These results are able to provide implications for offline and online retailers and directions for future research.