• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1047-1058
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• 2008

Prediction of total sales in information security industry is considered. Exponential smoothing and spline smoothing is applied to the time series of annual sales data. Due to the different survey items of every year, we recollect the original survey data by some basic criterion and predict the sales to 2014. We show the total sales in infonnation security industry are increasing gradually by year.

• 대한지역사회영양학회지
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• 제18권5호
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• pp.505-514
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• 2013

Effect of Menu Calorie Labels on Menu Sales and Consumer's Recognition at a Korean Restaurant in a Hotel The role of calorie information is to help consumers make healthier food choices. However, calorie information is generally unavailable in restaurants. Even in high-end hotel restaurants, which try to provide high quality foods and service, calorie labeling is not mandatory. Therefore, the purpose of this study was to evaluate the effect of calorie labeling on menu sales and consumer's recognition at a Korean restaurant in Kangwonland hotel. The calorie contents of 10 dishes sold in the restaurant were calculated using the food composition table. After making a new menu plate displaying calorie information, the new menu plate and old menu plate were provided every other week for 4 weeks. When we compared the sales between the periods of calorie labeled and calorie unlabeled, sales of 4 items among the 5 food items providing less than 1000 kcal, increased, however the 3 items among the menu providing more than 1000 kcal decreased. As the survey results of total 405 consumers (male n = 232, female n = 173) showed the new menu plate, 68.2% of subjects recognized calorie labeling on the menu plate. Among the subjects who recognized calorie labeling, 58.3% answered that calorie information affected their food choices. And most of them answered that they chose lower calorie foods based on the information provided. The results suggest that displaying calorie information on the menu plate at a Korean restaurant was effective in changing consumer's food choices.

• 유통과학연구
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• 제14권11호
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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.

• 지능정보연구
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• 제16권3호
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• pp.163-179
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• 2010

최근 패션산업에서는 고객의 니즈가 다양해지고 공급 리드타임이 크게 단축됨에 따라 최신 유행을 즉각 반영한 디자인, 빠른 상품 회전율로 승부하는 패스트 패션이 각광받고 있다. 또한, 기업간 경쟁도 심화되면서 얼마나 신속하게 효율적으로 고객의 니즈를 만족시킬 것인가가 패션산업의 중요한 성공요인으로 강조되고 있다. 따라서, 다품종 소량 신속생산이 강조되는 패스트 패션 산업에서는 트랜드 변화에 신속 대응을 지원하는 지능형 신속대응시스템(Intelligent Quick Response System : IQRS) 구축 및 지원을 절실히 요구하고 있다. 본 논문은 패스트 패션 산업 IQRS 구축에서 요구되는 신속대응 프로세스 수립, 지능적 판단을 지원하는 신속대응 기준 및 실행, 신속대응 물량 산정 및 시기 의사결정 모델을 제시하였다. 또한, 신속대응 의사결정의 합리성을 검증할 수 있는 KPI(Key Performance Indicator)를 설계하여 모델의 신뢰도를 향상시켰다. 제시된 각 모델은 A사의 ERP 구현사례를 통해 실용성을 검증하였다.

• 디지털융복합연구
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• 제10권7호
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• pp.85-92
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• 2012

IT 장비의 발전에 따라 온라인 쇼핑도 데스크 톱 환경에서 스마트폰에 이르기까지 다양한 형태로 이루어지고 있으며, 판매 품목도 다양하게 진행되고 있다. 뿐만 아니라, 판매 형식도 하루에 한 종목만을 판매하는 형태 등 오프라인에서 볼 수 없는 형태의 온라인 판매 형식이 다양하게 나타나고 있다. 이러한 판매 형태에서도 경쟁은 매우 심화되고 있으며, 이들 가운데에서도 차별화된 특징이 경쟁력을 도모할 수 있게 되었다. 이에 본 연구에서는 하루 한 종류의 상품만을 온라인 마케팅에 활용하여 일일 상품에 대한 기대치를 높임으로서 매출 향상을 목적으로 기획 및 구현된 사이트 개발을 목표로 하고 있다. 이를 위해서 기존 상업 사이트들에 대해 일일 상품 사이트 기획들에 대한 분석을 기반으로 평소 관심을 갖지 않던 품목에 대한 관심을 증대시킬 수 있으며, 고객들이 사이트 방문 시 마케팅 기획과 정보 배치를 중심으로 강조된 사이트를 구축하였다. 이를 통해 특정 품목에 대한 일부 고객층 대상으로 일일 품목 홍보 효과 증대와 매출 증대를 도모할 수 있을 것으로 기대된다.

• Asia pacific journal of information systems
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• 제14권4호
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• pp.87-97
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• 2004

One of the most fundamental problems in business is ranking items with respect to profit based on historical transactions. The difficulty is that the profit of one item comes from its influence on the sales of other items as well as its own sales, and that there is no well-developed algorithm for estimating overall profit of selected items. In this paper, we developed a product network based on association rule and an algorithm for profit estimation and item selection using the estimated profit ranking(EPR). As a result of computer simulation, the suggested algorithm outperforms the individual approach and the hub-authority profit ranking algorithm.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2002년도 추계정기학술대회
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• pp.241-249
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• 2002

Making traditional plan of target marketing based on Association Rule has brought restriction to obtain the target of marketing. This paper is to present Inverse Association Rule as a new association rule for target marketing. Inverse Association Rule does not use information about relation between items that customers purchase like Association Rule, but use information about relation between items that customers do not pruchase. By adding Inverse Association Rule to target marketing, we generate new marketing rule to look for new target of marketing. From new marketing rule, this paper is to show direct marketing about target item and indirect marketing about another item associated with target item to sell target item. The reason is that sales of the item associated with target item have an influence on sales of target item.

• 한국의상디자인학회지
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• 제16권1호
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• pp.41-52
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• 2014

The purposes of this study were to explore differences in utilization of information sources depending on the length of buyers' career and annual sales volume of stores where buyers work for. The questionnaire was prepared by the researcher and was answered by 200 buyers who purchase their items from Dondaemun market. The researcher analyzed the data using both ANOVA and Tukey's test as a post-hoc test. The conclusion of this study is summarized below. First, there were significant differences in utilization of information sources among buyer groups depending on the length of buyers' career. The buyers with more than 10 years career showed more effective utilization of information source such as resident buying offices, manufacturers, trade publications, trade associations, fashion reports, celebrities, window shopping, professional magazines, and advice from others. Second, there were significant differences in utilization of information sources among buyer groups depending on annual sales volume of the stores where the buyers work for. The buyer who work for the store with its annual sales volume in excess of 2 billion won showed more effective utilization of information source such as trade association, professional magazines, sales record, want slips, advertising results, sales trends, customer surveys, sales meetings, customer advisory panel, in-store merchandising bureau and advice from other experienced buyers. However, buyers of the store with its annual sales volume lower than 100 million won showed different pattern utilization of information sources such as vendors, trade publication, celebrities and advice from others.

• Journal of Information Technology Applications and Management
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• 제23권2호
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• pp.113-141
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• 2016

This study identifies and validates the factors that affect sales performance of salespersons in the business software industry. In the study, in order to measure the dependent variable (performance of the salesperson) more comprehensively, multiple items are utilized and both outcome and behavior indicators are used. Independent variables are identified based on the classification of Verbeke et al. [(2011] including sales related knowledge, degree of adaptiveness, role ambiguity, and work engagement. Results of the hypotheses testing show that 'sales related knowledge' and 'work engagement' are statistically significant factors, but 'degree of adaptiveness' and 'role ambiguity' are not. This study has a few limitations and future research direction to overcome the limitation is suggested : use of both perceptions of the salesperson and objective measures in measuring the related variables; study including cognitive ability; analyses of the factors across various types of software companies; and analyses of the factors on the team level.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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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.