• The Journal of Information Systems
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• v.26 no.4
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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.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.15-24
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• 2019

The development of "New Retailing" is still in its infancy. Theoretical research has just begun, showing the characteristics of practice leading theoretical research, that is, there is more practical exploration but relatively insufficient theoretical research. At present, the theoretical research and practice development of "New Retailing" is gradually clear. The future development trend is large-scale, no boundaries, and wisdom. The academic community should further study in depth with theory and practice, focusing on the deep integration of online and offline, the new logistics under "New Retailing", and the research direction of "New Retailing" driving supply chain transformation and reconstruction so as to better guide the development of "New Retailing". The purpose of the research is to sort out the research status and theoretical situation of "new retailing", so as to provide references for further research on "new retail" and guidance for practical development.

• Management & Information Systems Review
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• v.30 no.3
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• pp.191-215
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• 2011

Retailing service companies need to manage customer's behavior participating in service production and delivery process, while trying to differentiate from competitors with customer services. They also need to know the level of customer participation to make good use of customer participation in retailing service delivery process. Therefore, this paper expects to show the level of customer participation in domestic primary retailing service types. In details, this paper empirically identifies how different the level of customer participation is in four retailing service types-family restaurant, hair service, hospital service, educational service. As results, activity effort, communication effort, and compliance effort variables of customer participation were significantly in different level. But, sympathy effort variable of customer participation was not identified on the level of difference in four retailing service types. Additionally, hospital service showed the highest level of customer participation in four retailing service types, then family restaurant, education service, and hair service were in order. Judging these results, this paper suggests that the level of customer participation according to retailing service types would be different empirically. Also, this paper provides the opportunities to make properly good use of customer participation suitable to individual retailing type.

• Journal of Distribution Research
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• v.17 no.2
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• pp.93-115
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• 2012

This study empirically examines the impact of changes in market shares among retailing types on the price index. The retailing type is classified into 6 groups: department store, big mart, super market, convenient store, specialty merchant, and on-line store. The market shares of retailing types are calculated by the ratio of each retailing type monthly sales to total monthly retailing sales in which total retailing sales is the sum of each retailing type sales. We employed several price indices: consumer price index (CPI), CPI for living necessaries, and fresh food price index. In addition, this study used fundamental price indices based on 25 product families as well as 42 representative products. The empirical model also included several variables in order to control for the macroeconomic effects and those variables are the exchange rate, M1, an oil price, and the industrial production index. The data is monthly time-series data spanning over the period from January 2000 to December 2010. In order to test for the stability of data series, we conducted ADF test and PP test in which the model and length of lag were determined by the relevant previous literature and based on the AIC. The empirical results indicate that changes in market shares among retailing types have impacts on the price index. Table A shows that impacts differ as to which price index to use and which product families and products to use. For department store, it lowers the price of food and non-alcoholic beverages, home appliances, fresh food, fresh and vegetables, but it keeps the price high for fresh fruit. The big mart retailing type has a positive impact on the price of food, nut has a negative effect on clothing and foot wear, non-food, and fresh fruit. For super market, it has a positive impact on food and non-alcoholic beverages, fresh food, fresh shellfishes, but increases the price of CPI for living necessaries and non-food. The specialty merchant retailing type increases the price level of CPI for living necessaries and fresh fruit. For on-line store type, it keeps the price high for CPI for living necessaries and non-food as well as fresh fruit. For the analysis based on 25 product families shows that changes in market shares among retailing types also have different effects on the price index. Table B summarizes the different results. The 42 representative product level analysis is summerized in Table C and it indicates that changes in market shares among retailing types have different effects on the price index. The study offers the theoretical and practical implication to these findings and also suggests the direction for the further analysis.

• Fashion, Industry and Education
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• v.14 no.1
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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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• v.7 no.4
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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.

• The Journal of Information Systems
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• v.6 no.1
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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.

• Journal of Distribution Science
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• v.20 no.8
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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.

• Fashion & Textile Research Journal
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• v.12 no.3
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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.

• Korean Journal of Human Ecology
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• v.20 no.6
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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.