• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.149-158
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• 1987

The Adoption/Diffusion of Innovations(New Product), a topic of study and research that has frown rapidly in the past few decades, deals with how a new product is adopted in a society. It is of high importance to marketing organizations because New Products must be brought out continuously in order to service. The purpose of this paper is to examine the Adoption/Diffusion Models for New product which will help to analyze the Adoption/Diffusion process of Adopters. There are a number of models that, with varying degrees of success, have been used to predict market acceptance of new product. In this paper, following types of new product Adoption/Diffusion Models was suggested. (1) Adoption Models : The Alternative Models of Adoption. The Rogers Model of the Innovation Decision Process. (2) Diffusion Models : First Purchase Models(Basic Models, Extension of the Basic Models), Repeat Purchase Models

• IE interfaces
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• v.23 no.4
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• pp.337-348
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• 2010

The Bass model is the most widely used model in research of new product diffusion because it presents a nice explanation on the diffusion process of new products. However, it has a limitation that its performance of fitness is lower as the available data become less and also, the diffusion curve is bell-shape and so, it can not represent the various diffusion patterns. Recently, a two-pieces Bass model is developed and applied to analyze diffusion of 10 products. The results are encouraging in terms of fitness. However, diffusion pattern is not dealt with in the paper. In this paper, analysis of diffusion pattern is in depth addressed in two-pieces Bass model. It is shown that the diffusion curves are divided into 3 types with respect to the peak adoption rate and each type is divided into 2 types further. Takeoff time of a diffusion process is analyzed by using the inflection point and regime-change time where it represents the point that imitation and innovation parameters change. Empirical studies for 68 products(28 domestic products and 40 USA products) are performed to analyze the diffusion pattern. Findings are that diffusion patterns of all products except 1 USA product show type I and regime-change time becomes shorter as the introduction time of the product is later in domestic products and regime-change time can be regarded as a takeoff time in 47% of total 68 products.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.23-31
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• 2000

Many studies in marketing and economics have attempted to model price and sales path under the dynamic diffusion process. Most of these models have been based on a fixed product lifetime. The current business climate requiring intensive development of new products however affects the diffusion of new products and their lifetime. Many products have not enjoyed the expected life cycle at the launching stage due to intense technical development competitive reactions, and financial problems. Most diffusion models however have not taken account of the lifetime uncertainty of new product. If the products do not last over the planning horizon set by those models. the optimal price derived from them could be futile. Therefore we had better take such lifetime uncertainty into consideration when developing diffusion models, In this paper we study the impact of uncertain product lifetime on its optimal pricing path in non-competitive market. We develop an optimal pricing model under uncertain product lifetimes and conduct a simulation study to investigate their effects on the optimal pricing and corresponding sales paths. The simulation study provides some interesting findings on optimal pricing policy under uncertain product lifetime. This study could be a stepping stone for the further extended study of optimal pricing strategy with uncertain product lifetime.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.149-158
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• 2015

The purpose of this paper is to investigate the determinants of new product diffusion. We seek to document and explain systematic features of product diffusion. In this essay, we examine the well-documented empirical regularity that the speed of diffusion has accelerated during the twentieth century. The empirical results show that the main source of acceleration are faster declines in prices. Faster price declines make the product affordable to more consumers within a given period of time. Based on theories of intertemporal price discrimination and learning-by-doing, the association between the speed of adoption and the speed of price decline was explained. Faster price declines are attributed to several product characteristics as well as changes in income distribution. Above all, the introduction of consumer electronic products in more recent years can be regarded as the most important factor in accelerating price declines. Consumer electronic products are technologically different from non-electronic goods, in that semiconductors are important components. As the price of semiconductors has dropped rapidly, the falling production costs can be rapidly incorporated to the price of consumer electronic goods. Furthermore, most of the recently introduced consumer electronic products have network externalities, and many products with network externalities require complementary products. A complementary product becomes more readily or cheaply available as more people have the main product. One major difference between previous studies and this study is that the former focuses only on the factors that operate directly on the speed of adoption, while this study incorporated factors that work through price changes as well as the factors that work directly on the speed of adoption.

• ETRI Journal
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• v.31 no.2
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• pp.215-224
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• 2009

Analyzing the diffusion of a convergence product is a new and challenging research field. It is very difficult to find research dealing with this issue due to the inherent complexity and lack of data. In analyzing the diffusion of a convergence product, we should simultaneously take into account its relationship with related single-function products because of their similarities in terms of technology and functionality. In this study, we empirically analyze the diffusion of the convergence mobile phones in South Korea and find that the convergence products can affect the diffusion of MP3 players and digital cameras positively or negatively. This research may be significant for business strategies in technology management and product development.

• 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.

• Korean small business review
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• v.32 no.1
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• pp.65-87
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• 2010

With the advent of knowledge-based society, the revitalization of technological innovation type SMEs, termed "inno-biz" hereafter, has been globally recognized as a government policymakers' primary concern in strengthening national competitiveness, and much effort is being put into establishing polices of boosting the start-ups and innovation capability of SMEs. Especially, in that the inno-biz enables national economy to get vitalized by widening world markets with its superior technology, and thus, taking the initiative of extremely competitive world markets, its growth and development has greater significance. In the case of Korea, the government has been maintaining the policies since the late 1990s of stimulating the growth of SMEs as well as building various infrastructures to foster the start-ups of the SMEs such as venture businesses with high technology. In addition, since the enactment of "Innovation Promotion Law for SMEs" in 2001, the government has been accelerating the policies of prioritizing the growth and development of inno-biz. So, for the sound growth and development of Korean inno-biz, this paper intends to offer effective management strategies for SMEs and suggest proper policies for the government, by researching into the effect of technological innovation capability and technology commercialization capability as the primary business resources on business performance in Korean SMEs in the light of market information orientation. The research is carried out on Korean companies characterized as inno-biz. On the basis of OSLO manual and prior studies, the research categorizes their status. R&D capability, technology accumulation capability and technological innovation system are categorized into technological innovation capability; product development capability, manufacturing capability and marketing capability into technology commercialization capability; and increase in product competitiveness and merits for new technology and/or product development into business performance. Then the effect of each component on business performance is substantially analyzed. In addition, the mediation effect of technological innovation and technology commercialization capability on business performance is observed by the use of the market information orientation as a parameter. The following hypotheses are proposed. H1 : Technology innovation capability will positively influence business performance. H1-1 : R&D capability will positively influence product competitiveness. H1-2 : R&D capability will positively influence merits for new technology and/or product development into business performance. H1-3 : Technology accumulation capability will positively influence product competitiveness. H1-4 : Technology accumulation capability will positively influence merits for new technology and/or product development into business performance. H1-5 : Technological innovation system will positively influence product competitiveness. H1-6 : Technological innovation system will positively influence merits for new technology and/or product development into business performance. H2 : Technology commercializing capability will positively influence business performance. H2-1 : Product development capability will positively influence product competitiveness. H2-2 : Product development capability will positively influence merits for new technology and/or product development into business performance. H2-3 : Manufacturing capability will positively influence product competitiveness. H2-4 : Manufacturing capability will positively influence merits for new technology and/or product development into business performance. H2-5 : Marketing capability will positively influence product competitiveness. H2-6 : Marketing capability will positively influence merits for new technology and/or product development into business performance. H3 : Technology innovation capability will positively influence market information orientation. H3-1 : R&D capability will positively influence information generation. H3-2 : R&D capability will positively influence information diffusion. H3-3 : R&D capability will positively influence information response. H3-4 : Technology accumulation capability will positively influence information generation. H3-5 : Technology accumulation capability will positively influence information diffusion. H3-6 : Technology accumulation capability will positively influence information response. H3-7 : Technological innovation system will positively influence information generation. H3-8 : Technological innovation system will positively influence information diffusion. H3-9 : Technological innovation system will positively influence information response. H4 : Technology commercialization capability will positively influence market information orientation. H4-1 : Product development capability will positively influence information generation. H4-2 : Product development capability will positively influence information diffusion. H4-3 : Product development capability will positively influence information response. H4-4 : Manufacturing capability will positively influence information generation. H4-5 : Manufacturing capability will positively influence information diffusion. H4-6 : Manufacturing capability will positively influence information response. H4-7 : Marketing capability will positively influence information generation. H4-8 : Marketing capability will positively influence information diffusion. H4-9 : Marketing capability will positively influence information response. H5 : Market information orientation will positively influence business performance. H5-1 : Information generation will positively influence product competitiveness. H5-2 : Information generation will positively influence merits for new technology and/or product development into business performance. H5-3 : Information diffusion will positively influence product competitiveness. H5-4 : Information diffusion will positively influence merits for new technology and/or product development into business performance. H5-5 : Information response will positively influence product competitiveness. H5-6 : Information response will positively influence merits for new technology and/or product development into business performance. H6 : Market information orientation will mediate the relationship between technology innovation capability and business performance. H7 : Market information orientation will mediate the relationship between technology commercializing capability and business performance. The followings are the research results : First, as for the effect of technological innovation on business performance, the technology accumulation capability and technological innovating system have a positive effect on increase in product competitiveness and merits for new technology and/or product development, while R&D capability has little effect on business performance. Second, as for the effect of technology commercialization capability on business performance, the effect of manufacturing capability is relatively greater than that of merits for new technology and/or product development. Third, the mediation effect of market information orientation is identified to exist partially in information generation, information diffusion and information response. Judging from these results, the following analysis can be made : On Increase in product competitiveness, directly related to successful technology commercialization of technology, management capability including technological innovation system, manufacturing capability and marketing capability has a relatively strong effect. On merits for new technology and/or product development, on the other hand, capability in technological aspect including R&D capability, technology accumulation capability and product development capability has relatively strong effect. Besides, in the cast of market information orientation, the level of information diffusion within an organization plays and important role in new technology and/or product development. Also, for commercial success like increase in product competitiveness, the level of information response is primarily required. Accordingly, the following policies are suggested : First, as the effect of technological innovation capability and technology commercialization capability on business performance differs among SMEs; in order for SMEs to secure competitiveness, the government has to establish microscopic policies for SMEs which meet their needs and characteristics. Especially, the SMEs lacking in capital and labor are required to map out management strategies of focusing their resources primarily on their strengths. And the government needs to set up policies for SMEs, not from its macro-scaled standpoint, but from the selective and concentrative one that meets the needs and characteristics of respective SMEs. Second, systematic infrastructures are urgently required which lead technological success to commercial success. Namely, as technological merits at respective SME levels do not always guarantee commercial success, the government should make and effort to build systematic infrastructures including encouragement of M&A or technology trade, systematic support for protecting intellectual property, furtherance of business incubating and industrial clusters for strengthening academic-industrial network, and revitalization of technology financing, in order to make successful commercialization from technological success. Finally, the effort to innovate technology, R&D, for example, is essential to future national competitiveness, but its result is often prolonged. So the government needs continuous concern and funding for basic science, in order to maximize technological innovation capability. Indeed the government needs to examine continuously whether technological innovation capability or technological success leads satisfactorily to commercial success in market economic system. It is because, when the transition fails, it should be left to the government.

• Journal of Technology Innovation
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• v.13 no.1
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• pp.113-139
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• 2005

The purpose of this study is to analyse the diffusion process of personal computer (PC) in Korea during the 1990's. To achieve the goal, five research steps have been done such as the literature survey of diffusion theory, set-up of theoretic equilibrium model of supply and demand, derivation of an equilibrium path using Hamiltonian, and empirical analysis. The empirical analysis has been performed based on that equilibrium path. The results can be summarized as follows : First, technological attribute of diffusing product influences the diffusion speed of Product. It has been proven that the size of the network has a significant effect on the diffusion of PC in empirical study Second, supply factors have an important role in the diffusion process. According to the empirical analysis, decreasing cost of production as a result of technological advance promotes the speed of diffusion. This point seems to be manifest theoretically, but existing empirical models have not included supply factors explicitly, Third, it has been found out that expectation of decreasing cost would influence the speed of diffusion negatively as expected ex ante. Theoretically this result is supported by arbitrage condition of purchasing timing.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.267-273
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• 2001

While forecasting sales of a new product is very difficult, it is critical to market success. This is especially true when other products have a highly negative influence on the product because of competition effect. In this paper, we develop a choice-based competitive diffusion model and apply to the case where two digital mobile telecommunication services, that is, digital cellular and PCS services, compete. The basic premise is that demand patterns result from choice behavior, where customers choose a product to maximize their utility. In comparison with Bass-type competitive diffusion models, our model provides superior fitting and forecasting performance. The choice-based model is useful in that it enables the description of such competitive environments and provides the flexibility to include marketing mix variables such as price and advertising.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.1
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• pp.25-29
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• 1987

When the historical data are available, the diffusion model, which describes the time pattern of the adoption process of a new product or technology or service, has been used as a reasonable predictor in the telecommunication demand forecasting area. This paper shows that the diffusion model is applicable when the historical data are not available. The model used is in the form of a "logistic" function. The parameters of the function are estimated using the questionnaire and the historical data of reference products. From the questionnaire, an initial and an upper limit long run value of the market share are estimated, and the diffusion time to the upper limit value is determined by the relation between the investment and the utility.