• Journal of the Ergonomics Society of Korea
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• v.26 no.1
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• pp.79-85
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• 2007

Demand forecasting methods for a consumer product such as TV or refrigerator are widely known. However, sales forecast for a brand new product cannot be estimated using conventional forecasting methods. This study proposes a five-step procedure in forecasting a newly developed product. Step one defines functions in a High Touch product in order to estimate relative attraction of the product to consumer group. In step two, for a comparison purpose, a compatible product that is successfully penetrated into market is selected. Step three breaks a target population into many segments based on demography. Step four calculates relative attraction between the High Touch product and the compatible product. Finally, market penetration rate of the High Touch product is estimated using a bell-shaped diffusion curve of the compatible product. The process offers a method to estimate potential demand and growth pattern of the new High Touch product.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.339-348
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• 2007

Since the 1980s, the marketing paradigm has rapidly changed from product-driven marketing to customer-driven marketing. Recently, due to an increase in the amount of information, customer-differentiation strategies have been emphasized more than product-differentiation strategies. This paper suggests a methodology for new customer segmentation and purchase forecasting using changes in customer behavior. This methodology includes a segmentation method for new customers using existing customer's characteristics and a purchase-forecasting system using the purchase-behavior patterns of existing customers. The proposed methodology not only provides differential services from a segmentation system but also recommends differential items from the purchase forecasting system for new and existing customers.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.1
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• pp.45-59
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• 2013

A long-term forecasting method for a new product in early stage of diffusion is proposed. The method includes a constrained non-linear least square estimation with the logistic diffusion model. The constraints would be critical market informations such as market potential, peak point, and take-off. Findings on 20 cases having almost full life cycle are that (i) combining any market information improves the forecasting accuracy, (ii) market potential is the most stable information, and (iii) peak point and take-off information have negative effect in case of overestimation.

• Journal of the Korean Operations Research and Management Science Society
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• v.10 no.1
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• pp.65-78
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• 1985

In this paper, the approach getting a total demand by forecasting the new demand and the replacement demand separately and adding them is used for long term forecasting of durable goods. Cross country analysis using the income as an independent variable and S-shaped growth curve as a fitting model is developed as a method of forecasting new demand. To get the replacement demand the methods using the number of ownership and the replacement rate and the methods using the past demand and the distribution of the product life are proposed. And the theoretical explannation for product life cycle's diversity, which is the one of the major considerations in the long term forecasting, is attempted by the combination of the new demand and the replacement demand patterns. This is applicated the long term forecasting of Korean passenger cars.

• Archives of design research
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• v.14 no.1
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• pp.93-101
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• 2001

This study suggested how to apply it decision-making of product development rapidly by design evaluation process to objectify and the result to quantify with viewpoint of design evaluation sets to marketability. Coverage of this method limited to the evaluation stage of design concept. The procedure of study, first of all, referred to some type of design evaluation method and their feature. And next, referred to some kinds of demand forecasting for marketing. Above an, this study focused on the method of demand forecasting by buying intentions surveys proper to the marketability evaluation of new product design. On a case study, I had investigated preference survey and buying intentions surveys about the design proposal of "language master audio". I selected the best design proposal through the conjoint analysis and also investigated demand forecasting. First, on the basis of buying intentions surveys, choose population and had produced buying demand, awareness demand, potential demand. I could estimate some profit to take out expense and cost from the buying demand. This estimated profit is marketability judgement data of product design at the design concept stage and can be utilized to measurable data for decision-making of product development. Through the case study, this method could forecast a target demand, and even if it is some difference between real sales volume, but the case study could verified that this method is effective to the evaluation of marketability in case of completely new product got on the typical category and the product category could be set up the population clearly.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.355-364
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• 1990

In the classical research, technological forecasting was used in the field of substitution of a new technology product for a old in the developed countries. But in the developing or underdeveloped countries, more interested in the forecasting of technological level in certain industry than technological forecasting in certain product. This article shows the forecasting method of technological level by using a procedure of AHP(Analytical Hierarchy Process). With the historical data of the technological levels in the Korean Civil Aerospace(KCA) industry using AHP questionaire, the Gompertz curve was used to forecast the technological levels of KCA industry.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.51-63
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• 1992

It is commonly accepted that the demand forecasting data play a vital role in deciding strategic variables such as the optimal market entry time, the price structure and the production capacity etc. In case of the new product, however, it is hard to apply the well known regression-type methodologies. In this study, we survey the characteristics of various types of new product demand forecasting(NPDF) methodologies which are useful in case the historical data are not available. Further, we explore the possibility of incorporating the NPDF methodologies and develope the unified infra-structure of the NPDF methodologies. Finally we propose an integrated prototype of the NPDF model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.35-38
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• 1996

It's a rather difficult for new product launch strategy establishment to be settled down because we must know the correlation between the quantitative and the qualitative information. Therefore, we introduce you case-based reasoning system that use its correlation and new product launch's experience in the past. Using the real cases, this system evaluates the performance as we compare human expert's new product sales forecasting with system's.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2490-2495
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• 2005

The scheduling of plant should be determined based on the product demands correctly forecasted by reasonable methods. However, because most existing forecasting packages need user's knowledge about forecasting, it has been hard for plant engineers without forecasting knowledge to apply forecasted demands to scheduling. Therefore, a forecasting module has been developed for plant engineers without forecasting knowledge. In this study, for the development of the forecasting module, an automatic method using the ARIMA model that is framed from the modified Box-Jenkins process is proposed. And a new method for safety inventory determination is proposed to reduce the penalty cost by forecasting errors. Finally, using the two proposed methods, the web-based automatic module has been developed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.137-145
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• 2020

Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.