Separating early-adopters from the majority: The case of Broadband Internet access in Korea

This paper examines key static determinants and dynamic diffusion processes to develop a diffusion model of network products from the case of rapid growth of Broadband Internet in Korea. In the competitive environment of shortening product life cycle, there have been few studies on the key factors affecting the rapid and dynamic diffusion of network products. This paper identifies that market and technological factors have had a great impact on the explosive diffusion speed, while government and socio-cultural factors moderately contributed to the rapid diffusion. This paper also explores the dynamic diffusion processes: diffusion for the early-adopter and diffusion for the majority. Finally, theoretical propositions are developed on the diffusion of innovation for network products and practical implications for expediting the diffusion of emerging technologies are discussed.     

竞争性技术创新扩散模型及其应用

基于竞争性技术创新扩散系统的定义及假设,提出了多项竞争性技术创新扩散系统的动力学模型,并将多智能体的建模理论与方法应用到竞争性技术创新扩散的分析中。通过大量仿真实验,将动力学模型、多智能体模型的预测结果和实际数据进行了对比分析,对未来的手机用户扩散数量进行了预测。分析结果认为,一项创新技术只有借助扩散,其潜在经济效益才能被最大限度地发挥。同时,分析结果也验证了该模型在实践中的可行性和有效性。     

Innovation diffusion with generation substitution effects

Markets of high technology products and services, such as telecommunications, are described by fast technological changes and rapid generational substitutions. Since the conventional modeling approaches that are based on diffusion models do not usually incorporate this important aspect into their formulations, the accuracy of the provided forecasts is consequently affected. The work presented in this paper is concerned with the development of a methodology for describing innovation diffusion, in the context of generation substitution. For this purpose, a dynamic diffusion model is developed and evaluated, based on the assumption that the saturation level of the market does not remain constant throughout the diffusion process but is affected by the diffusion of its descendant generation, as soon as the latter is introduced into the market. In contradiction to the conventional diffusion models, which assume static saturation levels, the proposed approach incorporates the effects of generation substitution and develops a diffusion model with a dynamic ceiling. The importance of such an approach is especially significant for markets characterized by rapid technological and generational changes. Evaluation of the proposed methodology was performed over 2G and 3G historical data and for a number of European countries, providing quite accurate estimation and forecasting results, along with important information regarding the rate of generation substitution.     

高技术产业集群中技术创新与扩散的系统基模分析与政策解析

技术扩散(或知识溢出)是企业集群发展的一个主要诱因,但是技术扩散(或知识溢出)的微观过程依然是一个"黑箱"。将高技术产业集群看成一个系统,应用系统动力学的方法,建立了技术创新动力成长上限基模、技术扩散动力成长上限基模、知识生产与搭便车者两败俱伤基模、知识生产富者愈富基模、集群成长与投资不足基模、集群创新舍本逐末基模、集群发展饮鸩止渴基模共7个系统基模,用以揭示高技术产业集群中技术创新、技术扩散、知识生产、集群成长与集群发展之间因果关系的作用机理及运作机制,并对基模根本解作了政策解析。     

A dynamic diffusion model for managing customer's expectation and satisfaction

The paper aims at answering the generic question on how suppliers make the suitable and well-timed decisions in diffusing new technology effectively to adopters. Three major attempts are made for the study: First, investigating the entire process of the adoption and diffusion of technology innovation with reasonably well-accepted models in each areas. Second, proposing an integrated model by concatenating in structured manner the three prominent models for the management of technology innovation such as diffusion model, adoption model, and customer satisfaction model. Third, exploring the dynamic mechanism underlying outward behaviors of the integrated model proposed in the study which depicts the causal relationships that influence technology adoption and diffusion behaviors. An exploration of the dynamic mechanism underlying outward behaviors of the integrated model is presented in the study by introducing the system dynamics simulation technique. These attempts made for the study and the results perhaps allow both researchers and practitioners to gain insight into the causal factors influencing customers' adoption decision making processes and thereby into the potential diffusion patterns resulting from those adoption processes.     

Word-of-mouth reputations in auto insurance markets

A model is developed of the diffusion of information concerning stochastic quality levels of firms under assumptions of highly imperfect consumer knowledge. An equilibrium analysis finds that an increase in the rate of diffusion of information results in a decline in the elasticity of demand with respect to quality. A dynamic analysis indicates, however, that under certain conditions short-term elasticity increases with an increased rate of diffusion of information. The importance of dynamic analysis is underscored by the length of time often required for convergence to the steady state.     

Forecasting future demand for large-screen television sets using conjoint analysis with diffusion model

The methodological framework proposed in this paper addresses two limitations of the basic Bass diffusion model: that it does not reflect competition among products nor does it forecast demand for products that do not exist in the marketplace. The model consists of four steps. First, to investigate consumer preferences for product attributes, we use conjoint analysis to estimate the utility function of consumers. Next we estimate the dynamic price function of each competing product to reflect technological changes and the evolving market environment. Then we derive dynamic utility function by combining the static utility function and the price function. Finally, we forecast the sales of each product using estimated market share and sales data for each period, which are derived from the dynamic utility function and from the Bass diffusion model, respectively.We apply this model to South Korea's market for large-screen televisions. The results show that (1) consumers are sensitive to picture resolution and cost and (2) in the near future, should the market see the introduction of liquid crystal display (LCD) TVs with screens larger than 50 inches, the high resolution and steep price drop of LCD will lead LCD TVs to capture a larger market share than TVs with other display types. Finally, our results show that TVs with 40-inch screens are preferred over TVs with larger screens.     

STRUCTURAL CHANGE AND THE GROWTH OF INDUSTRIAL SECTORS: EMPIRICAL TEST OF A GPT MODEL

This paper investigates the empirical relevance of a model of structural change and the growth of industrial sectors. The model analyzes the process of diffusion of general‐purpose technologies (GPTs) and how this affects the dynamic performance of manufacturing and service industries. The empirical analysis studies the dynamics and the determinants of labor productivity growth for a large number of sectors in 18 OECD countries over the period 1970–2005. The results of dynamic panel data and cross‐sectional analysis provide support for the empirical validity of the model. Industries that are close to the core of ICT‐related GPTs are characterized by greater innovative capabilities and have recently experienced a more dynamic performance. Relatedly, countries that have been able to shift their industrial structure toward these high‐opportunity manufacturing and service industries have grown more rapidly.     

技术创新扩散动力机制及测度研究

本文基于技术创新扩散传播和驱动的双重视角下研究技术创新扩散的动力机制。首先,围绕创新主体和创新客体基于技术创新扩散方式的视角提出了技术创新扩散传播机制,并应用Bass模型对其传播机制进行测度;围绕创新主体、创新客体和创新中介基于技术创新扩散驱动要素的视角提出了技术创新扩散的驱动机制,并应用空间计量模型对其驱动机制进行测度。其次,运用2001-2018年中国五类城市(288个地级以上城市)的ICT数据对其创新扩散传播机制和驱动机制进行实证分析。结果表明：Bass模型能够有效测度五类城市ICT创新扩散的传播机制,且五类城市之间存在显著差异;面板数据固定效应动态SAR模型能够更全面测度五类城市ICT创新扩散驱动机制,时间、空间和时空滞后效应驱动显著,同时从宏观、中观和微观等视角测度并分析了对五类城市的驱动效果,得出一系列有价值的研究结论。     

Wind Power in Europe: A Simultaneous Innovation–Diffusion Model

The purpose of this paper is to provide a quantitative analysis of innovation and diffusion in the European wind power sector. We derive a simultaneous model of wind power innovation and diffusion, which combines a rational choice model of technological diffusion and a learning curve model of dynamic cost reductions. These models are estimated using pooled annual time series data for four European countries (Denmark, Germany, Spain and the United Kingdom) over the time period 1986–2000. The empirical results indicate that reductions in investment costs have been important determinants of increased diffusion of wind power, and these cost reductions can in turn be explained by learning activities and public R&D support. Feed-in tariffs also play an important role in the innovation and diffusion processes. The higher is the feed-in price the higher is, ceteris paribus, the rate of diffusion, and we present some preliminary empirical support for the notion that the impact on diffusion of a marginal increase in the feed-in tariff will differ depending on the support system used. High feed-in tariffs, though, also have a negative effect on cost reductions as they induce wind generators to choose high-cost sites and provide fewer incentives for cost cuts. This illustrates the importance of designing an efficient wind energy support system, which not only promotes diffusion but also provides continuous incentives for cost-reducing innovations.      

Innovation and imitation as an interactive process

This article deals with the problem of the coexistence of innovators and imitators in a competitive market. The study proposes a model of innovation and diffusion of productive knowledge as an interactive process between innovators and imitators under conditions of dynamic uncertainty. The process can be modelled as a Stackelberg game, where the innovator acts as a leader in choosing whether to share knowledge or set up private protection and the imitator as a follower in choosing when becoming active. Under these conditions, activation thresholds are derived for both innovators and imitators. If protection policies are effective, the imitator can be trapped into an inaction region by the innovator. Thus, there will be two regimes without and with diffusion, according to whether the inaction region is enacted or not. Under these conditions, discovery and diffusion appear to be dynamic complements, as a higher speed of activation of innovating firms is favoured by a higher level of imitation and a higher speed of activation of imitating firms is favoured by a higher level of discoveries. In order to explore some of the quantitative implications of these results, the paper also proposes an application of the model to four European countries.     

Basic Stochastic Dynamic Systems of Growth and Trade

Uncertainties are intrinsic features of dynamic economic systems, and this paper considers the dynamic implications of factor endowment (labor, capital) uncertainties for a small growing trading economy. The stochastic growth models presented extend the open neoclassical two-sector growth model (Deardorff) to a stochastic environment in continuous time, and extend the diffusion dynamics of one-sector growth models (Merton; Bourguignon) to a trading two-sector economy. It is demonstrated that the basic propositions of deterministic steady-state growth and endogenous growth theory, under some specifications and certain parametric restrictions, are preserved within a stochastic framework.     

Exploratory analysis of the impact of information dynamics on innovation diffusion

Understanding the dynamic nature of innovation diffusion processes, and mechanisms underlying these dynamics is crucial, since such an understanding is potentially very important in designing effective innovation support policies and developing better diffusion forecasts. The role of information diffusion in conditioning the diffusion dynamics of an innovation is the locus of this study. In order to investigate this, a simulation model that distinguishes between the real attributes of the innovation and their perceived levels by the user groups has been developed. The model makes it possible to separately trace the diffusion dynamics of innovation and the information about an innovation. Additionally, the formulation of the model enables the message broadcasted via word-of-mouth to change in nature from positive to negative, or vice versa. This generic model is used in an exploratory way, which is discussed as a novel approach for conducting a simulation-based analysis. Such an exploration covers a wide range of plausible diffusion behaviors, and aims to demonstrate the extent to which information imperfections and dynamics may influence the diffusion process. During experiments it is observed that information imperfections as well as the pace of learning processes may yield significant changes in the diffusion patterns. These changes may be in the form of altering the basic characteristics of the well-known S-shaped diffusion curve, as well as stopping the diffusion at much lower levels than full adoption. The analysis presented in the article shows that exploratory analysis is a promising way to utilize simulation models for developing general insights about dynamics processes.     

The dynamic effects of general purpose technologies on Schumpeterian growth

General purpose technologies (GPTs) are drastic innovations characterized by pervasiveness in use and innovational complementarities. The dynamic effects of a GPT are analyzed within a quality-ladders model of scale-invariant Schumpeterian growth. The diffusion path of a GPT across a continuum of industries is governed by S-curve dynamics. The model generates a unique, saddle-path long-run equilibrium. Along the transition path, the measure of industries that adopt the new GPT increases, consumption per capita falls, and the interest rate rises. The growth rate of the stock market depends negatively on the rate of GPT diffusion and the magnitude of the GPT-ridden R&D productivity gains; and positively on the rate of population growth. It also follows a U-shaped path during the diffusion process of the new GPT. Finally, the model generates transitional growth cycles of per capita GNP.JEL Classification: E3, O3, O4I would like to thank Elias Dinopoulos for encouragement, and for constructive comments and suggestions. I would also like to thank David Figlio, Douglas Waldo, Steven Slutsky and participants in the 9th Biennial Congress of the International Schumpeter Society for useful discussions and suggestions. Any remaining errors are my own responsibility.     

Knowledge diffusion and knowledge transfer revisited: two sides of the medal

Understanding the way in which knowledge is interpersonally transferred and how it diffuses over time is of exceptional importance for the economic performance of a society. Although this insight is not new, the link between knowledge transfer and knowledge diffusion so far has not been picked out as a central theme in the relevant research field but instead it seems that it has been treated as a theme on the fringes yet. This paper mainly argues, first, that the speed of knowledge diffusion as well as the shape of the cumulative knowledge diffusion function is governed in most instances by knowledge transfer mechanisms. Second, these knowledge transfer mechanisms differ within and between heterophilic groups who participate in the knowledge transfer process. By perfectly disentangling between and within knowledge transfer mechanisms, the paper in general tries to uncover the link between knowledge diffusion and knowledge transfer within a dynamic model which is embedded in a stochastic environment. The model is able to replicate both, symmetric as well as asymmetric cumulative knowledge diffusion patterns. This is certainly an appealing attribute of the model, because from an empirical point of view there is no clear evidence for the existence of purely symmetric cumulative knowledge diffusion curves. Further, the model can be used directly for empirical investigations.     

产业集群内基于时间和距离的技术创新扩散模型研究

以创新和扩散为导向的集群经济效益已成为产业集群的竞争优势所在。基于时间和空间距离因素,构建了产业集群内的技术创新空间扩散模型,应用数据仿真实验,分析了在集群内进行技术创新空间扩散的动态过程,探讨了模型参数变化对技术创新扩散的影响,并着重分析了空间距离对技术创新扩散的影响。结果表明,产业集群内的技术创新扩散是典型的时空统一扩散过程,空间距离会阻碍技术创新的扩散,而且集群内采用技术创新的企业数量与距离因素呈负指数关系,为客观地预测和控制产业集群内时空统一的技术创新扩散过程提供了理论依据。     

Market penetration of new products in segmented populations: A system dynamics simulation with fuzzy sets

The application of system dynamics methodology to the study of market penetration (diffusion) of new products offers considerable flexibility. The differential equations representing total (cumulative) sales need not be that restrictive as in those instances where solely mathematical tools are applied for their solutions. This paper first develops a mathematical formulation of “dynamic diffusion phenomena,” where the target population is not assumed to be constant in time. Besides incorporating the “marketing efforts” of the producer as an explicit variable, the model also gives due importance to the population characteristics affecting the diffusion phenomena. This is achieved by representing all variables and parameters in the differential equations as higher dimensional arrays. Then some basic properties of “fuzzy sets” are exploited to assign numerical values to the parameters. At the end, the problem is cast in a system dynamics setup for its solution. A computer solution with the help of a DYNAMO compiler for a hypothetical case is added to demonstrate the applicability of the ideas developed.     

Modelling a dynamic market potential: A class of automata networks for diffusion of innovations

Innovation diffusion processes are generally described at aggregate level with models like the Bass Model (BM) and the Generalized Bass Model (GBM). However, the recognized importance of communication channels between agents has recently suggested the use of agent-based models, like Cellular Automata. We argue that an adoption or purchase process is nested in a communication network that evolves dynamically and indirectly generates a latent non-constant market potential affecting the adoption phase.Using Cellular Automata we propose a two-stage model of an innovation diffusion process. First we describe a communication network, an Automata Network, necessary for the “awareness” of an innovation. Then, we model a nested process depicting the proper purchase dynamics. Through a mean field approximation we propose a continuous representation of the discrete time equations derived by our nested two-stage model. This constitutes a special non-autonomous Riccati equation, not yet described in well-known international catalogues. The main results refer to the closed form solution that includes a general dynamic market potential and to the corresponding statistical analysis for identification and inference. We discuss an application to the diffusion of a new pharmaceutical drug.     

Technological substitution in the United States pulp and paper industry: The sulfate pulping process

This paper presents an econometric analysis of the diffusion of the sulfate pulping process throughout the U.S. pulp and paper industry. A dynamic equilibrium, Gompertz diffusion function is employed to derive a multivariate estimation model which incorporates more information than the traditional approach of estimating the growth rate function alone. The empirical results suggest that the econometric approach provides a useful integration of the technological diffusion process and the comparative static theory of demand. The sulfate pulping process is projected to continue capturing market share at a relatively rapid rate, and could account for 90% or more of total U.S. woodpulp production by the year 2000.     

Evaluating the potentials of technical cooperation among developing countries

The main purpose of this article is to show that “there are optimal partners for technology transfer to be most effective,” and for many countries this may, in fact, mean looking for “technical cooperation among developing countries (TCDC).” In this article a technology transfer model has been presented, in relatively simple mathematical form, which incorporates both the dynamic and the spatial aspects of the innovation diffusion process. The existing models of technological change at a particular location, i.e., technological substitution, are shown to be special cases of the developed time-level model of technology transfer. The model has been applied to evaluate the international transfer potentials of the “computerization” technology. Optimal partners are identified and the prospects for TCDC has been evaluated. Model usefulness and related policy implications have been discussed in detail.