• Journal of Distribution Research
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• v.15 no.5
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• pp.103-126
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• 2010

The development of an industry including distribution sector is influenced by not only government policy but the related firms' behaviors. Recently the large-scale retailers have had more enormous channel power than any other distributors including monopolistic makers. Now is the time for government to prepare some policies against the unfair transaction behaviors by large-scale retailers. In this paper I tried to inquire into the distribution competition policy from a political correspondent point of view related with the transition of distribution system. For the purpose of this article I compared the case of Korea with Japan. According to the results so far inquired, there are some commons and differences in the cases of the two. Some suggestions are as follows. Considering the predominant position the concept of large-scale retailers is to be extended from a single store to numerous chain stores in the political level. Government needs to examine the standard propriety for large-scale retailer; the size of selling area and amount of sales a year. When a large-scale retailer store is to be established, it need to be taken a permit or a pre-inspection. The Fair Trade Commission have to secure the neutrality from Government's strategies. And government should find out the examples of unfair transaction behavior types and prepare some proper guidelines continually. For the last time statistical data by distributors are to be fitted out and the actual investigations for estimating the effects of government policies need to be enforced.

• Journal of Distribution Science
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• v.11 no.10
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• pp.107-116
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• 2013

Purpose - Eggs are nutritionally complete and one of the most popular natural foods. Moreover, the poultry industry is one of the important food industries. However, early industrialization of the poultry industry on its own did not lead to further development compared to other livestock industries. In this study, we investigate what factors influence consumers' behavior and how consumers' understanding of retail business affects their propensity to consume. This study is different from other studies as it analyzes how the brand names of manufacturers and distribution companies affect the purchasing characteristics or actual purchase behavior of consumers in order to suggest how these manufacturers and distribution companies can increase their competitiveness. Research design, data, methodology - This study conducted a survey of 250 randomly selected egg purchasers in discount stores from January to April 2013. Consumers' purchase tendencies were calculated through frequency analysis. This result was then utilized using cluster analysis to draw a conclusion about which purchase tendency influenced consumers buying three different brands of eggs or whether this tendency really affected consumers. As a result, the outcomes of Hypotheses 2 and 3 were not clear so we drew a conclusion with our analysis of Hypothesis 1. Results - While the outcomes of Hypotheses 2 and 3 did not clearly indicate whether purchasing tendencies affected consumers when buying eggs, our analysis of Hypothesis 1 indicated that consumers were affected by the quality of the eggs rather than exterior factors such as the brand name. Thus, we concluded that it is important to promote the excellence of the quality of the eggs. Usually firms buy eggs from farms and repackage them in order to sell them. In this sense, if consumers were aware of this egg production process, and eggs were fairly distributed to retailers, large retail PB businesses would also be able to enhance their competitiveness. Conclusions - The brand, packaging, retail outlet, and other external features influenced the purchase of eggs to a certain degree, while shelf life, grade of the eggs, cleanliness, and other intrinsic characteristics had more influence. In particular, shelf life was the most important factor influencing purchase. Consumers were influenced not only by intrinsic characteristics of the eggs but also by large-scale producers' brands. Consumers relied upon the brand despite reduced competition because they found it difficult to identify shelf life and/or cleanliness. Small businesses and/or large-scale retailers can remain competitive by maintaining the freshness and cleanliness of the eggs. Further studies need to investigate areas in which consumers' cognition of the product is poor and/or the purchase inclination with regard to less developed industries such as eggs. In this study, the greatest problem was that consumers did not consume in accordance with the current situation as consumers have preferred fresh and clean eggs for a long time compared to purchase decisions based on external brands and/or packaging.

• 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.17 no.5
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• pp.95-102
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• 2019

Purpose - The purpose of the research is to identify the demographic characteristics of the customers with high private label purchase intention. According to the previous research demographics such as gender, age, income, and residence type affect private label purchase intention indirectly through psychographics rather than directly. For instance, higher income group is time pressured, price-insensitive, quality-sensitive, less likely to enjoy shopping utilitarian products, and less likely to be variety-seeking. The main contribution of this research is to verify the results found in the previous empirical foreign research using scanner data and to investigate the differences of the characteristics of private label users between Korea and the foreign countries. Research design, data, and methodology - In order to empirically test the proposed hypotheses, scanner data of a Korean major super center was analyzed. Results - Empirical results show that private labels are more favored by old people over 50s, dwellers in individual house, lower income group, and frequent store visitors. Age of 30s, dwellers in the apartment of 30 pyung, higher income group, and consumers who purchased a large amount are less likely to purchase private labels. Gender turned out not to affect private label purchase. It should be noted that there is a significant multicollinearity among independent variables. Conclusions - The research findings provide managerial implication for retailers' private label strategy. In general, retailers heavily send private label coupons to the customers with high purchase volume. According to the research, however, store visit frequency is much more positively associated with private label purchase than purchase amount. The study has some limitations. The samples are only consumers with private label purchase experience. The data were drawn from one store and only 8 commodity products were used for the analysis. Also, if more demographics were available, a more complete description on the private brand users' profile could have been derived. We propose the following future research. Research using the data including consumers without private label experience, research investigating direction of causality between private label loyalty and store loyalty, and research using hedonic private label products such as TV and PC could be promising.

• Nutrition Research and Practice
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• v.15 no.sup1
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• pp.94-109
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• 2021

BACKGROUND/OBJECTIVES: The coronavirus disease 2019 (COVID-19) outbreak has dramatically changed nearly every aspect of our lives. Although Dietary lifestyle includes attitudes and behaviors to meet their most basic needs, but few studies have examined the pattern of changes in dietary lifestyle driven by COVID-19. This study explores changes in dietary attitudes and behaviors among Korean consumers after COVID-19. SUBJECTS/METHODS: An online survey was conducted with 549 Korean adults aged 20 and older to identify general demographics and changes in dietary attitudes and behaviors. Data were collected from Oct 12 to Oct 18, 2020. Frequency, percentage, and mean values were calculated and a K-means cluster analysis was performed to categorize consumers based on the 5S of dietary attitudes (i.e., savor-oriented, safety-oriented, sustainability-oriented, saving-oriented, and socializing-oriented). RESULTS: Findings indicate consumers considered safety, health, and freshness to be most important when choosing groceries and prepared meal such as home meal replacement and delivery food. Among the types of services, a large proportion of consumers increased their delivery and take-out services. Regarding retail channels, the increase in the use of online retailers was remarkable compared to offline retailers. Finally, consumers were classified into four segments based on changes in dietary attitudes: "most influenced," "seeking safety and sustainability," "abstaining from savor and socializing," and "least influenced." Each type of consumer exhibited statistically significant differences by sex, age, household composition, presence of disease, and perceived risk of COVID-19. CONCLUSIONS: This exploratory study provides initial insights for future research by identifying various aspects of dietary attitudes and behaviors among Korean consumers after COVID-19.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.29-49
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• 2022

Consumers are now no longer satisfied with using a single channel to shop and then desire a smooth and consistent purchasing experience across channels. By integrating different channels and services, an omni-channel strategy allows consumers to choose their preferred channel to complete their shopping tasks. Therefore, large retailers in China have recently been transforming into omni-channel retail formats to secure their competitive advantage. To better implement this strategy and optimize its effectiveness, it is important to understand how consumers respond to the quality of channel integration. Based on social exchange theory (SET), the main purposes of this study are to explore the impact of channel integration quality on consumer engagement in the Chinese omni-channel retailing environment and to further examine whether there is a moderating effect of consumer empowerment on this relationship. To test this research model, we collected data from 330 respondents by conducting an online questionnaire in China. The results indicated that the two dimensions of channel integration (breadth of channel-service choice and transparency of channel-service configuration) positively affected two dimensions of customer engagement (conscious attention and enthusiastic participation), respectively. The findings also show that consumer empowerment only positively moderates the relationship between breadth of channel service choice and conscious attention, whereas it negatively moderates the relationship between transparency of channel-service configuration and conscious attention/enthusiastic participation. Given these results, this study deepens our understanding of the impact of the quality of channel integration on customer engagement in the context of omni-channel retailing in China and sheds light on how retailers can attract consumers with different levels of empowerment.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Journal of Distribution Research
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• v.17 no.5
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• pp.113-128
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• 2012

The growth of market share of distributors' brands, also known as private brand, has accelerated in recent years. Sales volumes and market shares of private brands, as well as their appeal to consumers have steadily increased. Carrying private brands comes with numerous advantages, one of which is the relatively high gross margin, which can be 20 - 30% higher compared to manufacturer brands. Recently, many big discount stores are expanding private brand for higher sales volume. Thus, private brands play an important strategic role for retailers. The tendency of growing private brand will decrease sales revenue of both channel members, distributer and manufacturer. The disadvantage for manufacturer is obvious, especially for the manufactures who not only produce their own brands but also retailer brands competing against their own. There are also possible to weaken the brand awareness of manufacturer's brand. The purpose of this study is to explore the perception gap between retailers and manufacturers. we investigated to identify how consumers perceive private brand. In other to study the impact of private brands on distributors, we surveyed the actual condition of private brand and perception towards private brands among consumers, retailers and manufacturers. Based these analysis, we recommended proposal for private brand policies as follows: First, it need to correct imbalance between large retailer and manufacturer. second, we suggest "win-win growth policy", Third, by registering trademark right of national brand, manufacturers have a way of protecting their brands. Forth, manufacturers are encouraged to produce PNB(Private National Brand).

• Journal of Distribution Science
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• v.14 no.6
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• pp.65-73
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• 2016

Purpose - Recently, the management conditions of small independent retailers are getting worse everyday as large-scale marts and franchised convenience stores are increasing. The objective of this research is to find out the antecedents and consequences of cooperation in voluntary chain in order to enhance small independent retailer's competitiveness. Voluntary chains, also called affiliation or symbol groups, or allied group represent a high market shared in some European countries like Italy, France, and Germany. Nevertheless, there are still limitations in this research from academic fields. Drawing from network theory, the author investigates the relationship between antecedent factors in voluntary chain cooperation, such as participation benefits, justice of compensation, and autonomy in voluntary chain, and relationship specific asset. The author also attempts to examine the relationship between the relationship specific asset and cooperation of voluntary chain member shop and cooperation and consequence factors of voluntary chain cooperation, such as efficiency, group cohesiveness, and long-term relationship. Research design, data, and methodology - The author presented conceptual framework integrating the major antecedents and consequences of voluntary chain cooperation. The data were collected from 174 independent small retailers who joined K-voluntary chain. K-voluntary chain consists of small independent retailers. In accordance with their status, each entrepreneur associated with the voluntary group can own one or more outlets and can be a part of the life and the decision-making process of the group. This participation is not based on company turnover or on the number of outlets, but based on a one member, one vote system. To verify the research model and test hypotheses, the author carefully investigated the reliability, content validity, convergent validity, and discriminant validity of the proposed model. The data were analyzed by using SPSS 18.0 and AMOS structural equation modeling program. Results - The results of this study are as follows. First, as antecedent variables, participation benefits and justice of compensation have positive effect on the relationship specific assets of voluntary chain members. Second, voluntary chain members' relationship specific asset also directly related to the level of its cooperation to chain headquarter. Third, cooperation of voluntary chain member shop facilitates efficiency, group cohesiveness, and long-term relationship. Unexpectedly, there are no effect autonomy in voluntary chain to relationship specific asset. Conclusions - This research shows several theoretical and practical implications to both marketing scholars and marketers. In terms of theoretical implications, this study applies to network theory and network theory variables to explain the antecedent and consequence factors of cooperation in voluntary chain. From the point of view from business management, most of all, this study shows the way how to reinforce competitiveness of voluntary chain. Specifically, it is necessary for voluntary chain headquarter to give higher level of participation benefit and justice of compensation to its members. Second, the results also indicate what the consequence factors of cooperation in voluntary chain. In other words, to increase the level of marketing efficiency, group cohesiveness, long-term orientation in retail voluntary chain, and chain headquarter need to facilitate participants' cooperation.