• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.6
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• pp.1053-1069
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• 2020

This study examined the sales pattern relationship with respect to product attributes to propose sales forecasting for fashion products. We analyzed 537 SKU sales data of T-shirts in the domestic sports brand using SAS program. The sales pattern of fashion products fluctuated and were influenced by exogenous factors; therefore, we removed the influence of exogenous factors found to be price discounts and holiday effects as a result of regression analysis. In addition, it was difficult to predict sales using the sales patterns of the same product since fashion products were released as new products every year. Therefore, the forecasting model was proposed using sales patterns of related product attributes when attributes were considered descriptive variables. We classified sales patterns using K-means clustering in order to explain the relationship between sales patterns and product attributes along with creating a decision tree classifier using attributes as input and sales patterns as output. As a result, the sales patterns of T-shirts were clustered into six types that featured the characteristic shape of peak and slope. It was also associated with the combination of product attributes and their values in regards to the proposed sales pattern prediction model.

• Fashion & Textile Research Journal
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• v.23 no.4
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• pp.480-490
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• 2021

Sales forecasting is crucial for many retail operations. For apparel retailers, accurate sales forecast for the next season is critical to properly manage inventory and plan their supply chains. The challenge in this increases because apparel products are always new for the next season, have numerous variations, short life cycles, long lead times, and seasonal trends. In this study, a sales forecasting model is proposed for apparel products using machine learning techniques. The sales data pertaining to outerwear items for four years were collected from a Korean sports brand and filtered with outliers. Subsequently, the data were standardized by removing the effects of exogenous variables. The sales patterns of outerwear items were clustered by applying K-means clustering, and outerwear attributes associated with the specific sales-pattern type were determined by using a decision tree classifier. Six types of sales pattern clusters were derived and classified using a hybrid model of clustering and decision tree algorithm, and finally, the relationship between outerwear attributes and sales patterns was revealed. Each sales pattern can be used to predict stock-keeping-unit-level sales based on item attributes.

• The Research Journal of the Costume Culture
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• v.14 no.6
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• pp.887-899
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• 2006

In this study the preference degree of a Dangcho pattern with priority given to demographic variables was examined. The results was that demographic variables have influence on the preference degree of a Dangcho pattern. The continual arrangement pattern of a stylistic type was shown as the pattern that men in their 40s and over most prefer. The continual arrangement pattern of a realistic type was shown as the pattern that men in their 40s and over and women in their 50s and over most prefer. The continual arrangement pattern of a geometrical type was shown as the pattern that men working on a sales, service, production position and women in their 50s most prefer. The single arrangement pattern of a stylistic type was shown as the pattern that college men in their 20s, men in their 50s and women working on a sales, production, service position most prefer. The single arrangement pattern of a stylistic type of a realistic type was shown as the pattern that men in their 40s working on a sales, service, production position and college women in their 20s most prefer. The single arrangement pattern of a geometrical type was shown as the pattern that most of people prefer.

• Spatial Information Research
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• v.12 no.2
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• pp.211-228
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• 2004

The purpose of this study is to analyze the sales area of gas stations to see the quality and the efficiencies of spatial distribution structure for petroleum products in Tae-jeon City. Location pattern of gas station is classified by factors of competitive facilities, transportation, population and landuse in Tae-jeon City. As a result, High profit pattern and low profit pattern is classified. The characteristics of the distribution pattern of gas station are that the while densely populated has a small sales area, the thinly populated region has huge ones. Location-allocation model is used in order to minimize the travel distance from consumer location to gas station and balance the spatial distribution of gas station in case studies. The result reveals that the model-based locations of gas stations are more dispersed and balanced in the whole Tae-jeon City compared with the actual location of gas stations. This study shows the characteristics and spatial distribution patterns of sales area and location in petroleum products distribution facilities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1232-1245
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• 2021

In this study, prediction of product sales as they relate to changes in temperature is proposed. This model uses long short-term memory (LSTM), which has shown excellent performance for time series predictions. For verification of the proposed sales prediction model, the sales of short pants, flip-flop sandals, and winter outerwear are predicted based on changes in temperature and time series sales data for clothing products collected from 2015 to 2019 (a total of 1,865 days). The sales predictions using the proposed model show increases in the sale of shorts and flip-flops as the temperature rises (a pattern similar to actual sales), while the sale of winter outerwear increases as the temperature decreases.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.904-913
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• 2005

This paper deals with an integrated problem of inventory control and dynamic pricing strategies for a commodity with price and sales-period dependent demand pattern, where a seller and customers have complete information of each other. The problem consists of two parts; one is each buyer's benefit problem which makes the best decision on price and time for buyer to purchase items, and the other one is a seller's profit problem which decides an optimal sales strategy concerned with inventory control and discount schedule. The seller's profit function consists of sales revenue and inventory holding cost functions. The two parts are closely related into each other with some related variables, so that any existing general solution methods can not be applied. Therefore, a simplified model with single seller and two customers in considered first, where demand for multiple units is allowed to each customer within a time limit. Therewith, the model is generalized for a n-customer-classes problem. To solve the proposed n-customer-set problem, a dynamic programming algorithm is derived. In the proposed dynamic programming algorithm, an intermediate profit function is used, which is computed in case of a fixed initial inventory level and then adjusted in searching for an optimal inventory level. This leads to an optimal sales strategy for a seller, which can derive an optimal decision on both an initial inventory level and a discount schedule, in $O(n^2)$ time. This result can be used for some extended problems with a small customer set and a short selling period, including sales strategy for department stores, Dutch auction for items with heavy holding cost, open tender of materials, quantity-limited sales, and cooperative buying in the on/off markets.

• Journal of Korean Institute of Industrial Engineers
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• v.1 no.1
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• pp.41-56
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• 1975

In the past the pattern of business down-trend usually appeared in the form of, first, decrease in facility investment, then decrease in inventory level, followed by reduced level of consumption. But the pattern nowadays is becoming just the opposite, that is, first, consumption decrease, then inventory level increase, followed by restriction of facility investment. Also in the past, the greater effort was placed in strengthening of hardware areas through optimization and modernization of production means on the premise of sales. But lately software areas take most of the main effort to establish production mean with sales as its objective. Under these circumstances one of the real problems facing production activities today is the conflicting relationship between sales and production functions. This occurs due to differences of their view points. Then, in order to achieve maximum profit at the least cost, which is the ultimate objective of a production activity, the need arises to effectively coordinate sales demand and plant production capacity. For this purpose strong control means and function must be devised. In our case study example we illustrate a management technique for a combined planning function, of optimal coordination of product mixes utilizing a computerized linear programming model as control means of attaining maximum profit. It is hoped that this example help achieve some of corporate objectives.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.169-177
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• 2020

The purpose of this study is to forecast the sales of convenience store flagship products with nonlinear characteristics and time series characteristics. According to the results, the sales of 'Ice Cup' began to increase from March, reached the highest value in summer, especially July and August, and then decreased, revealing a seasonal pattern. Cigarettes showed a seasonal pattern of higher sales in summer and lower sales in winter and was predicted to decrease in sales in the future. This study provides an academic implication in that it focused on the top-selling products that affected an increase in financial performance in a specific convenience store, a method that has been hardly adopted by the existing studies.

• 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.

• Journal of Korea Technology Innovation Society
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• v.8 no.1
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• pp.116-134
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• 2005

This paper investigates the relationships between export and firm characteristics, focusing on technology factors. It is based on a longitudinal data covering listed firms in the Korean manufacturing industry. A regression model for the determinant of export/sales ratio including dynamic adjustment process is tested on a cross-section sample of the year 2001. Empirical findings suggest that there is no significant relationship between export/sales ratio and firm's technological level. The hypotheses concerning human capital intensity and physical capital intensity are also rejected. But we found a positive and inversely U-shaped relationship between firm size and export/sales for basic material and capital good industry. As a dynamic aspect, we found that the pattern of export/sales ratio changed unstably over the last decade. Finally, some policy implications are presented.