• 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 the Korean Geographical Society
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• v.31 no.1
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• pp.19-37
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• 1996

This paper aims at examining the regional difference of changes in the business organization of retailing in the Seoul metropolitan areas, as an attempt to understand regional structure of retailing within metropolitan areas showing the trend of suburbanization. On the national level, retail sales have concentrated on the large metropolitan areas, especially on the Seoul metropolitan area, with the concentration of population and income. Within metropolitan areas, the suburbanization of retailing has made the larger structure of retail and multi-store retail appeared. In order to confirm such phenomenon, this paper is to analyze and to compare the industrial composition of retailing using industry data of 1979 and 1991. And this paper is to analyze the regional changes in the characteristics of business organization of retailing, with the index including the percentages of establishments with less than under four employees, juridical establishments, employees of ordinary times, and the annual sales per establishment of detailing. The characteristics of business organization of retailing in analyzed by principal components analysis, and the types with component in each district (city, county, ward) is analyzed by cluster analysis(Ward method). The data of 1979 were obtained from the statistics in the Census of Wholesale and Retail Trade published by the National Bureau of Statistics of Economic Planning Board, and that of 1991 were obtained from the statistics in the Report on Establishment Census (Vol.3 Wholesale and Retail Trade) published by the National Statistics Office. The following are resultant findings. 1. In Seoul metropolitan area, changes in the industrial composition of retailing with annual sales from, 1979 to 1991 show very higher composition rates of 'general merchandise stores' and 'retailing of personal transport equipment and gasoline service stations', but comparatively lower composition rates of 'retailing of food, beverages and tobacco', 'retailing of textiles, clothing, footwear and apparel accessaries', 'general retail trade, n.e.c.',and 'retailing of household fuel'. 2. The characteristics of business organization of retailing in Seoul metropolitan area presents the prevailence of small, personal business organization and especially larger employees of ordinary times. 3. Business components of retailing by principal components analysis in Seoul metropolitan area are follows: 1 All retaining industries are larger business scale. 2. Larger business take the 'retailing of taxtiles, clothing, footwear and apparel accessories', 'retailing of furniture, home furnishing and equipment', and 'retailing of jewellery and watches' is main characteristic legal organization and employees of ordinary times. 4. Types changes in business organization of retailing in Seoul metropolitan area represent legal organization and employees of ordinary times taking the 'retailing of textiles, clothing, footwear and apparel accessories', 'retailing of furniture, home furnishing and equipment',and 'retailing of jewellery and equipment', and 'retailing of jewellery and watches', and legal organization taking 'general retail trade, n.e.c.' in 1979. All retailing industries are changed into larger business scale, in 1991. These phenomena of business changes appeared southeastern regions in Kyunggi-do(province). And larger business scale taking the 'retailing of textiles, clothing, footwear and apparel accessories', 'retailing of jewellery and watches', and 'general retail trade, n.e.c.; are appeared in the legal organization in 1979. 'Retailing of personal transport equipment and gasoline service stations' are appeared in employees of ordinary times in 1991. These phenomena of business changes in appeared in eastern and northern regions in Kyunggi-do. 5. Changes in the business organization of retailing in Seoul metropolitan area is appeared in legal organization and employees of ordinary times for some industries in 1979, larger business scale of retailing and employees of ordinary times in 'retailing of personal transport equipment and gasoline service stations' are the characteristics in 1991.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.97-121
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• 2001

Until now, we have believed that one of advantages of cyber market is that it can virtually display and sell goods because it does not necessary maintain expensive physical shops and inventories. But, in a highly competitive environment, business model that does away with goods in stock must be modified. As we know in the case of AMAZON, leading companies already consider merchandise management as a critical success factor in their business model. That is, a solution to compete against one's competitors in a highly competitive environment is merchandise management as in the traditional retail market. Cyber market has not only past sales data but also web log data before sales data that contains information of path that customer search and purchase on cyber market as compared with traditional retail market. So if we can correctly analyze the characteristics of before sales patterns using web log data, we can better prepare for the potential customers and effectively manage inventories and merchandises. We introduce a systematic analysis method to extract useful data for merchandise management - demand forecasting, evaluating & selecting - using web mining that is the application of data mining techniques to the World Wide Web. We use various techniques of web mining such as clustering, mining association rules, mining sequential patterns.

• Korea Journal of Hospital Management
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• v.22 no.4
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• pp.16-23
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• 2017

Purposes: Despite the positive health effects of both smokers and non-smokers, the non-smoking area policy is being negatively evaluated because of the vague fears of declining restaurant sales. The purpose of this study is to analyze the changes in sales of general restaurants(including liquor stores) and other restaurants that are considered to have the most applications of smoking cessation policy among the smoking facilities, and to examine the economic impact of the designation and expansion policies of non-smoking areas. Methodology: This study used the wholesale and retail trade survey data of the Korea National Statistical Office from 2011 to 2014 and analyzed 31,577 restaurants excluding missing values. For statistical analysis, t-test, ANOVA and Difference-in-differences(DID) models were used and the interaction term of area and year was entered. Findings: As the non-smoking area policy had been designated and expanded from December 2012 to December 31 2013, high restaurant sales in 2012 declined sharply in 2013. However, despite the expanding of the no-smoking area from January 1 2014 through December 31 2014, restaurant sales slightly recovered in 2014. In the case of other restaurants, there is no significant change in sales since the start of the policy in 2013. Practical Implications: The decline in restaurant sales due to the designation and expansion of non-smoking areas is temporary and can not be sustained over the long term. This result can be used to positively suggest negative perceptions of the designation and expansion policy of non-smoking areas. Also, this result can contribute to health promotion and smoking cessation policies by protecting non-smokers from the risk of secondhand smoking exposure and inducing smokers to decrease smoking rate and smoking amount.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.137-145
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• 2023

E-Commerce is a buzzword well known for electronic commerce activities including but not limited to the online shopping, digital payment transactions, and B2B online trading. In today's digital age, e-commerce has been playing a very important and vital role in areas such as retail shopping, sales automation, supply chain management, marketing and advertisement, and payment services. With a huge amount of data been collected from various e-commerce services available, there are multiple opportunities to use that data to analyze graphs and trends. Strategize profitable activities, and forecast future trade. This paper explains a contemporary approach for collecting key data metrics and implementing cost-effective automation that will support in improving conversion rates and sales performance of the e-commerce websites resulting in increased profitability.

• Journal of Distribution Research
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• v.4 no.3
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• pp.65-86
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• 2000

From the perspective of relationship marketing, salespeople acts important role by creating values and developing, establishing long-term relationship with customers. This study is designed to suggest validated measure of evaluating retail salespeople in department store setting in an effort to facilitate active future studies. For this purpose, this study investigated attributes of retail salespeople based on series of personal interviews and literature reviews, and validated its measurement via exploratory and confirmatory factor analysis. In addition, this study explored consumers' rating of the importance of attributes related to some selected consumer variables (consumer knowledge, product involvement, and demographic variables). The findings of this study revealed five dimensions of retail salespeople attributes: Service Mind, Sales Efforts, Product Knowledge, Comfortable Impression and Sale Inducing Skill. Customers of department stores put importance of salespeople attributes in this order. Some dimensions of consumer knowledge and product involvement do affect consumers' rating of retail salespeople attributes. Theoretical and managerial implications were suggested based on empirical results.

• Asia Marketing Journal
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• v.15 no.1
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• pp.23-42
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• 2013

To overcome the profitability challenge these days, many global banks are increasingly focusing on cost efficiency through more efficient banking processes, such as online and mobile banking, whereas a number of other banks choose to differentiate their services for retaining and attracting the most valuable customer segment (Deloitte, 2011). While global banks in the retail banking industry are adopting either of these two business models as a strategic choice for their long-term growth, KB Kookmin Bank, one of the leading retail banks in South Korea, has begun to operate 'KB Rockstar' as a strategic channel, particularly designed to target college students in the youth market. The new marketing strategy has resulted in a positive impact on its brand image in customers' perception as well as a drastic increase in the number of youth customers. In this study, we analyze the case of 'KB Rockstar' and summarize the key factors for its success from a marketing perspective. First, 'KB Rockstar' is not simply a good channel strategy, but an innovative marketing strategy that aligns place, product and promotion together in order to create a synergy effect, resulting in the successful implementation of the bank's targeting strategy. Second, the strategy effectively establishes 'KB Rockstar' as a brand targeted to youth customers while also competently strengthening the image of the corporate brand, KB Kookmin Bank. The skillful implementation of organically combined marketing mix strategies has enabled the successful launch of the bank's sub-brand. Third, the strategy considers a retail bank branch as not only the place that makes sales transactions in order to generate short-term profits, but also the place that builds a long-term relationship with customers in order to maximize their lifetime values in the long run.

• Asian Journal of Business Environment
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• v.7 no.1
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• pp.13-23
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• 2017

Purpose - Pleasing ambient colors, music, scent, layout and salespeople are hypothesized to positively impact shoppers' perceptions about the atmosphere of a store. Few studies on the interactive effect of these atmospheric factors have earlier been undertaken. This paper looks at the interactive effect of color on the other predictor variables. Research design, data, and methodology - This study is from field locations in the shopping malls located in Delhi NCR. A descriptive study was undertaken to decipher the interactive effect of color with music, scent, layout and salespeople. Moderation of color on music, scent, layout and salespeople is regressed on store atmospherics. The authors investigate the effects of color, light, music, scent, layout and salespeople on store atmospherics in a retail context. They also study the interactive effect of color with predictor variables which significantly influence the perception of store atmospherics. Results - The paper reveals that music, scent, layout and salespeople influence customer's perception about store atmospherics. The interactive effect of color with scent, layout and sales people influence customer's perception about store atmospherics significantly. It does not moderate with layout and music. Conclusions - Store color is important in predicting store atmospherics. Care is needed to ensure that the effects of different environmental stimuli match.

• International Journal of Advanced Culture Technology
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• v.9 no.2
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• pp.91-99
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• 2021

In Korea, some pharmaceutical companies and agricultural machine manufacturers associate the length of the credit period with the retailer's order size. This kind of commercial practice is based on the principle of economy of scale from the supplier's point of view and tends to make retailer's order size large enough to qualify a certain credit period break. Also, the credit period allowed by the supplier makes it possible to reduce the retail price expecting that the retailer can earn more profits by the stimulating the customer's demand. Since the retailer's order size is affected by the end customer's demand, it is reasonable to determine the retail price and the order size simultaneously. In this regard, this paper analyzes the retailer's problem who has to decide his sales price and order quantity from a supplier who offers different credit periods depending on his order size. And we show that the retailer's order size large enough to qualify a certain credit period break. Also, it is assumed that the end customer's demand rate is represented by a linear decreasing function of the retail price.

• Journal of Distribution Science
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• v.19 no.7
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• pp.87-100
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• 2021

Purpose: This paper examined the role of conditional value in the green automotive industry. The relationships of conditional value's four factors, consumers' attitudes and consumers' intention to purchase green cars were investigated. The conditional value was extended by examining the effect of fuel prices. Research design, data, and methodology: This study is quantitatively designed. All variables were measured using a 7-point Likert-scale; 425 questionnaires were collected from the respondents in Malaysia. SmartPLS was utilized to examine the proposed nine hypotheses. Result: The results demonstrate a positive relationship between attitude and intention toward green cars. Additionally, the results of the relationships were as follows: fuel prices was the most significant predictor of Malaysian consumers' attitudes and consumers' intention to purchase green cars, followed by environmental consequences and government policy. However, retail sales promotions did not show a significant effect on both consumers' attitudes and intentions. Conclusion: The study's findings suggest that the Malaysian government should implement an integrated package that includes a fuel pricing policy that restricts the purchase of non-green cars, as well as a set of financial incentives for purchasing green cars. Moreover, it is valuable to conduct public awareness campaigns about the negative consequences of current consumption patterns.