• The Research Journal of the Costume Culture
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• v.25 no.2
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• pp.117-129
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• 2017

The purpose of this study was to investigate meteorological factors' effects on clothing sales based on empirical data from a leading apparel company. The daily sales data were aggregated from "A" company's store records for the Fall/Winter season from 2012 to 2015. Daily weather data corresponding to sales volume data were collected from the Korea Meteorological Administration. The weekend effect and meteorological factors including temperature, wind, humidity, rainfall, fine dust, sea level pressure, and sunshine hours were selected as independent variables to calculate their effects on A company's apparel sales volume. The analysis used a SAS program including correlation analysis, t-test, and multiple-regression analysis. The study results were: First, the weekend effect was the most influential factor affecting sales volume, followed by fine dust and temperature. Second, there were significant differences in the independent variables'effects on sales volume according to the garments' classification. Third, temperature significantly affected outer garments'sales volume, while top garments' sales volume was not influenced significantly. Fourth, humidity, sea level pressure and sunshine affected sales volume partly according to the garments' item. This study can provide proof of significant relationships between meteorological factors and the sales volume of garments, which will serve well to establish better inventory strategies.

• Fashion & Textile Research Journal
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• v.19 no.4
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• pp.434-447
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• 2017

This study investigated the effects of influencing factors on the sales volume of apparel products. Based on previous studies, weekend effect, discount rate, and meteorological factors including daily average temperature, rainfall, sea level pressure, and fine dust were selected as independent variables to calculate their effects on sales quantity of apparel products. The daily sales data during 2015 - 2016 were collected from casual brands and outdoor brands which "A" apparel manufacturing company had operated. The actual data of "A" company were analyzed using SAS(R) 9.4 and SAS(R) Enterprise Miner 14.1. The results of this study were as follows: First, the influencing factors on total sales volume of apparel products were proved to be the weekend effect, discount rate, and fine dust. Second, the analysis of influencing factors on sales volume of apparel products according to season showed: 1) In casual brands, the average temperature had a significant influence on the sales volume of spring/summer products, and the sea level pressure affected the sales volume of summer/fall/winter products significantly. 2) In outdoor brands, the average temperature and the fine dust had a significant influence on the sales volume of all season's products. The sea level pressure affected the sales volume of summer/fall/ winter products significantly. The weekend effect and the discount effect affected the sales volume of apparel products partly. Third, the effect of rainfall was not proven significant, which was different from the results of past studies.

• Culinary science and hospitality research
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• v.4
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• pp.295-315
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• 1998

This paper attempts to examine the degree of chef's satisfaction on food purchasing in 5-star hotel in Seoul. Nowadays, hotel industry in Korea is becoming more and more competitive and the hotel products higher education. Among a range of divisions in deluxe hotel in Seoul, in particular, a F&B division has been more profitable than the others. It is widely accepted that the proportion of revenue obtained from F&B sales is higher than that of revenue from room sales. However, under the IMF intervention, hotels in Korea trend to depend on room sales rather than F&B sales in terms of profit. In such a environment, it is essential that F&B division should carefully seek for an appropriate purchasing procedure which will affect an organizational structure and allow the company to fulfill its goals. Moreover, it is timely their performance and quality of services through ideal food purchasing procedure. In this paper, the author uses a survey technique distributed to approximately 200 chefs who work at 5-stars hotel in Seoul. The author expects that this paper will contribute to the researchers or practitioners who might need a reference on the food purchasing system.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.270-283
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• 2021

The achievement of the long-term relationship is commonly executed by a salesperson that is eventually very crucial to enhance the customer retention in the insurance industry. It indicates there is an urgency to improve the competence of salesperson and organization support to build and maintain bonds of long-lasting loyalty with the individual customers. Therefore, this research aims to analyze the influence of planner's competency and organizational support on sales performance, and to verify empirically whether MDRT goal orientation mediating role between competency, organizational support and sales performance. The results of this research are as follows: firstly, product and customer competence, digital competence, network competence positively affect sales performance. Secondly, sales support positively affect sales performance. Thirdly, meditating effect of MDRT goal orientation were significant found between the planner's competency and sales performance. Moreover, in the relationship between sales support and sales performance, MDRT goal orientation have a fully mediated effect. This means customer management through excellent competency, organization support to insurance trend change, and competence development through MDRT goal orientation positively affect sales performance.

• The Korean Journal of Food And Nutrition
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• v.33 no.1
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• pp.111-115
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• 2020

The purpose of this study is an application of Lee's Menu Engineering (LME) method for menu analysis on the eight kinds of pizza selected from 17 kinds of pizza served by an Italian restaurant near by the Keimyung College University campus. The eliminated nine items were in the third quadrant or below the trend line. The LME method is more efficient than generally used methods such as the Miller, Kasavana & Smith, Uman, Pavesic and Merricks & Jones method. The LME method comprises reference lines and four quadrants created by x, y axes and its average values. The x and y axes comprise the sales ratio (MM%, percentage of the Menu Mix) and the weighted contribution margin (WCM%, percentage of the Weighted Contribution Margin) respectively. The obtained results are such that total sales increased by 1.59% from 58,747,200 won to 59,684,000 won, despite the decrease in sales volume. Total contribution margin also increased from 35,248,320 won to 35,810,400 won. The trend line also shows from y=0.9147x (R²=0.703) to y=0.9944x (R²=0.9893). These results indicate that the LME method is superior in practical applications.

• The Journal of Economics, Marketing and Management
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• v.11 no.1
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• pp.21-30
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• 2023

Purpose: As one of the ongoing studies on the distribution industry, the purpose of this study is to identify the research trends on online shopping so far to propose not only the development of online shopping companies but also the possibility of coexistence between online and offline retailers and the development of the distribution industry. Research design, data and methodology: In this study, the English abstracts of 645 papers on online shopping registered in scienceON were obtained. For the analysis through BERTopic and LDA using Python 3.7 and identifying which topics were interesting to researchers. Results: As a result of word frequency analysis and co-occurrence analysis, it was found that studies related to online shopping were frequently conducted on factors such as products, services, and shopping malls. As a result of BERTopic, five topics such as 'service quality' and 'sales strategy' were derived, and as a result of LDA, three topics including 'purchase experience' were derived. It was confirmed that 'Customer Recommendation' and 'Fashion Mall' showed relatively high interest, and 'Sales Strategy' showed relatively low interest. Conclusions: It was suggested that more diverse studies related to the online shopping mall platform, sales content, and usage influencing factors are needed to develop the online shopping industry.

• Journal of Fashion Business
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• v.13 no.4
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• pp.85-98
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• 2009

Advance development of the internet has brought significant changes to the distribution structure of the fashion industry, resulting in decreased sales in Road shops and sudden growth of online fashion specialty shopping malls. As detailed analysis on internet fashion shopping malls is necessary in order to make a future projection on changes in the fashion industry, this thesis aims to study the color, fabric / pattern, silhouette, item / detail, image, etc of 2008 S/S apparel fashion style sold in the top ten shopping malls, selected in terms of sales volume and awareness. The results were further analyzed to characterize each individual shopping malls, upon which the design was compared with the five main trends for the season provided by three fashion research agencies in order to study the level of trend acceptance. Studies showed that 'Romantic Sake' trend was most widely accepted, followed by 'Eco Nature' which most reflected the characteristics of Spring. 'Modern Ethenic' trend was most aggressively accepted at more upscale shopping malls targeting older demographic, while " Play Urban' was highly accepted by shopping malls specializing in young casual. Due to the disadvantage of not being able to try on the items before purchase, styles following the 'City Luxe' trend featuring fitted suits showed the lowest trend acceptance. Amongst the design elements, color was most widely accepted.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.329-338
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• 2017

This study attempts to classify 1008 alley markets in Seoul through cluster analysis using Dynamic Time Warping, one of the methods used to analyze the similarity of time series, and evaluate the possibility of opening new stores. The sequence of the gross sales of an alley market and that of gross sales per store stand for the potential of growth and profitability of the market, respectively and are used as variables for cluster analysis. Five clusters are obtained for the gross sales and four clusters for the gross sales per store. These two types of clusters are again classified as rising and falling trends, respectively, and the combination of these trends produces four categories. These categories are used to evaluate the possibility of opening new stores in alley markets. The results show that the southeast which is relatively wealthy inferior to other regions in opening new stores. Alley markets in the northeast and the southwest are better than other regions such that opening a new store is justified. In the northwest, there are many markets with trend of gross sales and that of gross sales per store moving in opposite directions, and new store openings in these markets should be postponed.

• 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 Distribution Science
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• v.14 no.11
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• pp.83-90
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• 2016

Purpose - During the last two years, convenient stores (CS) are emerging as one of the most fast-growing retail trades in Korea. The goal of this work is to forecast and to analyze sales at CS using ARIMA-Intervention model (IM) and exponential smoothing method (ESM), together with sales at supermarkets in South Korea. Considering that two retail trades above are homogeneous and comparable in size and purchasing items on off-line distribution channel, individual behavior and characteristic can be detected and also relative superiority of future growth can be forecasted. In particular, the rapid growth of sales at CS is regarded as an everlasting external event, or step intervention, so that IM with season variation can be examined. At the same time, Winters ESM can be investigated as an alternative to seasonal ARIMA-IM, on the assumption that the underlying series shows exponentially decreasing weights over time. In case of sales at supermarkets, the marked intervention could not be found over the underlying periods, so that only Winters ESM is considered. Research Design, Data, and Methodology - The dataset of this research is obtained from Korean Statistical Information Service (1/2010~7/2016) and Survey of Service Trend of Korea Statistics Administration. This work is exploited time series analyses such as IM, ESM and model-fitting statistics by using TSPLOT, TSMODEL, EXSMOOTH, ARIMA and MODELFIT procedures in SPSS 23.0. Results - By applying seasonal ARIMA-Intervention model to sales at CS, the steep and persisting increase can be expected over the next one year. On the other hand, we expect the rate of sales growth of supermarkets to be lagging and tied up constantly in the next 2016 year. Conclusions - Based on 2017 one-year sales forecasts for CS and supermarkets, we can yield the useful information for the development of CS and also for all retail trades. Future study is needed to analyze sales of popular items individually such as tobacco, banana milk, soju and so on and to get segmented results. Furthermore, we can expand sales forecasts to other retail trades such as department stores, hypermarkets, non-store retailing, so that comprehensive diagnostics can be delivered in the future.