• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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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.

• Korean Journal of Community Nutrition
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• v.18 no.5
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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.

• 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.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.85-92
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• 2012

To the development of IT technologies, online shopping is implemented in various forms ranging from desktop environment to smartphone, and also variety of items are being sold. In addition, various type of online sales from that can not seen in offline like sales a one products per one day. In this type of sales, competition is extremely intensified and among those in the differentiated features are hold competitiveness. In this paper, we design and develop the site that adopts the online marketing technique - sale only one kind of product a day for increasing the sales revenue. To do this, in traditional commercial sites, we develop the marketing strategy, and information placement is emphasized site based on analysis of the daily product site planning and so that costumers are concentrated the products that did not interested. Though which customers to target specific items one day for some items and increasing publicity would help the sales increase is expected.

• Asia pacific journal of information systems
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• v.14 no.4
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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.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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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.

• Journal of the Korea Fashion and Costume Design Association
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• v.16 no.1
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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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• v.23 no.2
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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.

• 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.