• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.1
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• pp.117-129
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• 2009

The bullwhip effect is known as the significant factor which causes unnecessary inventory, lost sales or cost increase in supply chains. Therefore, the causes of the bullwhip effect must be examined and removed. In this paper, we develop two analytical tools for the bullwhip effect control in supply chains. First, we develop the quantitative models for computing the bullwhip effect in a three-stage supply chain consisted of a single retailer, a single distributor and a single manufacturer when the fixed-interval replenishment policy is applied at each stage. The quantitative models are developed under the different conditions for the demand forecasting and share of customer demand information. They are validated through the computational experiments. Second, we develop a simulation-based decision support system for the bullwhip effect control in a more diverse dynamic supply chain environment. The system includes a what-if analysis function to examine the effects of varying input parameters such as operating policies and costs on the bullwhip effect.

• Environmental and Resource Economics Review
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• v.22 no.1
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• pp.3-29
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• 2013

The purpose of this study is to estimate consumer preferences on hybrid cars and electric cars by employing a choice experiment reflecting the various market conditions, such as different projected market shares of green vehicles and $CO_2$ emission regulations. Depending on different market scenarios, we examine as to which attribute and individual characteristic affect the preferences of potential consumers on green vehicles and further, forecast the potential market shares of green cars. The primary results, estimated by a conditional logit and panel probit models, indicate that sales price, fuel cost, maximum speed, emission of air pollutants, fuel economy, and distance between fuel stations can significantly affect consumer's choice of environment-friendly cars. The second finding is that the unique features of electric cars might better appeal to consumers as the market conditions for electric cars are improved. Third, education, age, and gender can significantly affect individual preferences. Finally, as the market conditions become more favorable toward green cars, the forecasted market shares of hybrid and electric vehicles will increase up to 67% and 14%.

• Journal of the Korean housing association
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• v.14 no.6
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• pp.1-13
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• 2003

Housing supply ratio in Ulsan area has soared up to 91% recently. Therefore, developing a successful marketing strategy is an essential part of apartment sales success in Ulsan area. The purpose of this study is identifying the status of satisfaction level, moving motivation, the level of housing choosing behavior, and housing needs of the apartments for making a marketing strategy. The survey uses questionnaires which are delivered to the 545 housewives who live in 20 pyoung or 30 pyoung apartment in Ulsan area. The research uses a survey questionnaire for gathering a set of statistically-reasonable number of data among one million population of Ulsan metropolitan area. The frequency test and F-test are used for the analysis of the results. The results of empirical analyses provide the following major findings： 1) housing satisfaction of Buk-ku residents is higher than that of the residents of the other area, 2) neighborhood environment improvement and physical environment improvement are important factors of housing moving motivations, 3) view and lighting are important requirements of the housing, 4) the level of housing choosing efforts are more active in the residents of Joong-ku and Dong-ku than those of Nam-ku and Buk-ku.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.134-146
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• 2011

This paper suggests the product supply process model based on the store and production capacity, assortment planning and quick response for fast fashion retailers with BPMN. In the fast fashion industry, the standardized business process model is required to respond quickly market trends and customer requirements based on the quantitative and qualitative criteria. Thus we define the product supply processes which incorporate forecasting and assortment plan, cost and profitability of the production, store capacity based on the visual merchandising, and production capacity of the fast fashion retailers. Also we design the key performance indicators to evaluate the effectiveness of these product supply processes. The product supply process model for the fast fashion has great significance in embracing the fast fashion product development process because it presents the holistic view of the product supply process of the fast fashion and provides a performance evaluation mechanism. A case study shows that adopting the processes, a Korean fast fashion company achieves improvement in various performance indicators.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.4
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• pp.111-135
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• 2011

While previous studies and publications all assert a strong correlation between company's business plan and performance, very few have actually conducted practical analyses to support that. This study takes a practical approach in its analysis of Korean small and mid-sized enterprises(SME) with the view to finding an answer to the question. In addition, with the considerations of entrepreneur type and company's development stage, I analyzed the differences of business plan components' effects on performances. I selected business plan's components, which have been suggested only in theory and in concept, through the literature review and preliminary examination. Corporate performances were the recent improvements of ROS, ROA, market share and the number of employees to measure how greatly each is impacted by the components of a business plan. Results show that business plan components have influenced upon the number of employees. The business plan components discriminated superior company group and inferior company group properly. Especially, finance & related system and advertising & distribution factors showed statistically significant classification forecasting power. Technical/Craftsman evaluated the effects of producing & sales and profit & quality factors high and General/Opportunistic evaluated the effects of finance & related system, advertising & distribution, corporate mission factors high. The effect of corporate mission was highest among company development stages. Finance & related system and advertising & distribution factors showed the statistically significant difference in entrepreneur type and company development stages.

• Journal of the Korean Geographical Society
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• v.49 no.6
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• pp.917-934
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• 2014

Geographically weighted regression(GWR) model has been widely used to estimate spatially heterogeneous real estate prices. The GWR model, however, has some limitations of the selection of different price determinants over space and the restricted number of observations for local estimation. Alternatively, the geographically weighted LASSO(GWL) model has been recently introduced and received a growing interest. In this paper, we attempt to explore various local price determinants for the real estate by utilizing the GWL and its applicability to forecasting the real estate price. To do this, we developed the three hedonic models of OLS, GWR, and GWL focusing on the sales price of apartments in Seoul and compared those models in terms of model fit, prediction, and multicollinearity. As a result, local models appeared to be better than the global OLS on the whole, and in particular, the GWL appeared to be more explanatory and predictable than other models. Moreover, the GWL enabled to provide spatially different sets of price determinants which no multicollinearity exists. The GWL helps select the significant sets of independent variables from a high dimensional dataset, and hence will be a useful technique for large and complex spatial big data.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.181-200
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• 2020

This study used the OLS model to estimate the determinants affecting the tenure of a home and then compared the predictive power of each model with SVM, Decision Tree, Random Forest, Gradient Boosting, XGBooest and LightGBM. There is a difference from the preceding study in that the Stacking model, one of the ensemble models, can be used as a base model to establish a more predictable model to identify the volume of housing transactions in the housing market. OLS analysis showed that sales profits, housing prices, the number of household members, and the type of residential housing (detached housing, apartments) affected the period of housing ownership, and compared the predictability of the machine learning model with RMSE, the results showed that the machine learning model had higher predictability. Afterwards, the predictive power was compared by applying each machine learning after rebuilding the data with the influencing variables, and the analysis showed the best predictive power of Random Forest. In addition, the most predictable Random Forest, Decision Tree, Gradient Boosting, and XGBooost models were applied as individual models, and the Stacking model was constructed using Linear, Ridge, and Lasso models as meta models. As a result of the analysis, the RMSE value in the Ridge model was the lowest at 0.5181, thus building the highest predictive model.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.295-303
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• 2008

With universality of e-commerce through internet, smaller online shopping malls are increased. A Smaller online shopping mall by nature lacks an extra space to load many inventory quantities. Therefore, it is difficult to response immediately with client request with traditional inventory management method. VMI has a character that supplier can control volume of inventory according to sales of seller. This paper proposes SOHO-VMI that is applied VMI into smaller online shopping mall. Proposed SOHO-VMI supports M $\times$ N structure can interact with multiple suppliers and sellers. And it uses XML/EDI for interaction with EDI documents use to legacy system. Also, This paper proposes logistics statistic prediction algorithm can adjust production and distribution volumes to supplier considering seller's product distribution information and seasonal factor.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.2
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• pp.239-250
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• 2002

The purpose of the study was to explore the information activities of wedding dress shops and how companies' characteristics (the number of business year and the location of shops) and information users'characteristics (the year of career) influenced on utilization of information (fashion information, market information and internal information). In addition, the study was to investigate ratings of the importance of the competitive means. The questionnaire was revised by the researchers on the base of preceding research studies after interviewing wedding dress industry workers and performing a pilot survey. The total l10 copies were distributed to the workers of the wedding shops located in the city of seoul. Fifty six copies from the shops in Kangnam area were returned, and 38 copies at Kangbuk area. For statistical analysis, one-way ANOVA and Duncan's tests were used. The results from the study are follow. 1. The heavily utilized fashion information was collected from international and domestic wedding magazine by the respondents for their merchandise and design planning. 2. According to the companies'characteristics (the number of business year and the location of shop), the 50∼10 year-old companies collected fashion information from international fashion shows, domestic wedding/fashion magazine reporters, and utilized sales data as internal information sources than any other companies. The shops in Kangnam area used international fashion information and market information on popular/unpopular goods more than other shops. 3. According to information users'characteristics (the year of career), the 3-5 year-experienced workers utilized domestic fabric converters as an information source, lists of popular/unpopular goods as well as future forecasting information as internal information more any other workers. 4. Dress design, fabrics and customer service before wedding were considered as very important competitive power by wedding shop workers.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.1 s.149
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• pp.1-11
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• 2006

The purpose of this study was to analyze the current CRM situation in Korean apparel industry. Specifically, research purposes were 1) to examine the concepts and benefits of CRM, 2) to examine CRM strategies, 3) to analyze CRM system(i.e., customer relationship management service, customer segmentation criteria, DB management system), and 4) to analyze the potential problems and CRM adoption plan. The subjects for this research were thirty CRM managers in Korean apparel firms classified by the company type(woman's wear, man's wear, casual wear, children's wear, retailer) interviewed from December 2003 to March 1004. The results of this study were as follows: First, the concept of CRM represented the prime customer relationship, continuous consideration, and customer management system. The benefits of CRM reflected re-sales, improvement of profit share, and acquisition of customer's data base. Second, concerning the CRM strategies, most companies focused on persistent customer management through mileage program, membership cards and also implemented product strategies such as demand forecasting, customization based on customer data analysis. We also found that industry preferred to use pricing strategies, for example, segmentation of customer through discrepancies of price in which customers are provided by discount and gift voucher services. Regarding distribution strategy, channel diversification, localized service, and convenient delivery system were used. As promotion strategies, they chose celebrating customers' personal events and promoting cultural events and issuing coupons. Third, regarding CRM system, information service was the most frequently adopted, important and highly beneficial category. Also POS/web-POS, homepage were main sources of information. RFM is the mostly commonly used customer segmentation criteria. Fourth, potential problems in CRM adoption were lack of CRM knowledge and performance measurement of CRM. Future CRM adoption plan included CRM education and development of CRM performance measures.