Polynomial innovation diffusion models

In an earlier paper [42] the authors presented a comprehensive evaluation and extensions of available causal models of “binomial type” for describing the time pattern of the innovation diffusion processes. The binomial models are based on the assumption that the entire population can be divided into two groups—adopters of an innovation and the potential adopters—such that eventually everyone adopts the innovation and an innovation once adopted is never rejected. However, many examples can be cited where this assumption is unrealistic. Therefore this paper presents some polynomial innovation diffusion models that are less restrictive compared with the binomial models. The paper also shows the link between the polynomial diffusion process and the multilevel technological substitution process.     

创新扩散时间形态的S型曲线研究

创新扩散是创新通过某种渠道随着时间在社会系统成员间传播的过程。创新扩散S型规则由两条曲线组成：一条被称为累积采用曲线,即S型曲线;另一条被称为单位时间采用量曲线,即钟形曲线。创新扩散率主要受创新特点、创新者特点和环境因素的影响。从创新扩散S型曲线的由来看,其发端于人口增长模型中的增长曲线,后由Tarde提出S型曲线规则,最后Ryan和Gross促使其成为一种研究范式。从创新扩散S型曲线成因看,“波浪效应”和“阈值模型”是两种典型的解释模型：“波浪效应”是指创新扩散过程就像波浪一样,由创新中心点向四周扩散;“阈值模型”探讨了在个人参与某项活动之前,参与该活动的其他个体必须达到的人数。未来重点围绕3个方面进行深化研究：①进一步验证S型曲线;②验证创新扩散S型曲线中的数理模型;③结合创新扩散影响因素与扩散形态,将模型应用到创新扩散预测方面。     

It’s a match! Simulating compatibility-based learning in a network of networks

In this article, we develop a new way to capture knowledge diffusion and assimilation in innovation networks by means of an agent-based simulation model. The model incorporates three essential characteristics of knowledge that have not been covered entirely by previous diffusion models: the network character of knowledge, compatibility of new knowledge with already existing knowledge, and the fact that transmission of knowledge requires some form of attention. We employ a network-of- networks approach, where agents are located within an innovation network and each agent itself contains another network composed of knowledge units (KUs). Since social learning is a path-dependent process, in our model, KUs are exchanged among agents and integrated into their respective knowledge networks depending on the received KUs’ compatibility with the currently focused ones. Thereby, we are also able to endogenize attributes such as absorptive capacity that have been treated as an exogenous parameter in some of the previous diffusion models. We use our model to simulate and analyze various scenarios, including cases for different degrees of knowledge diversity and cognitive distance among agents as well as knowledge exploitation vs. exploration strategies. Here, the model is able to distinguish between two levels of knowledge diversity: heterogeneity within and between agents. Additionally, our simulation results give fresh impetus to debates about the interplay of innovation network structure and knowledge diffusion. In summary, our article proposes a novel way of modeling knowledge diffusion, thereby contributing to an advancement of the economics of innovation and knowledge.     

小世界网络下用户创新扩散效果分析

本文对用户创新的概念及相关研究成果进行了阐述,分析了用户创新扩散的特性;运用WS小世界网络模型构建了用户创新扩散的网络模型,并对扩散效果进行了模拟分析。结果表明:用户创新扩散在不同的网络结构下呈现出不同的结果;创新采纳比例在小世界区间达到最大;随着网络随机化程度的加大,平均创新知识水平变得更高,知识的均匀扩散能够更快实现。最后进行了案例分析。     

Contagion effects of national innovative capacity: Comparing structural equivalence and cohesion models

The effective promotion of national innovation performance is a crucial component of national innovation policy. This study examines network contagion effects of national innovative capacity via the international diffusion of embodied and disembodied technology by two different social network models: the cohesion model, based on diffusion by direct communication, and the structural equivalence model, based on diffusion by network position similarity. This investigation then utilizes data of 42 countries during 1997 to 2002 to empirically examine their network relationship. The analytical results demonstrate that international technology diffusion influences national innovation performance through contagion effects, but that the international similarity of national innovative capacity performance is more accurately predicted by network position than by interactions with others; and this study result provides a new perspective for science and technology policy makers.     

Contagion effects of electronic commerce diffusion: Perspective from network analysis of industrial structure

This study presents a quantitative method for investigating the diffusion of e-commerce adoption using social network analysis methodologies. The contagion effects on innovation diffusion are examined by two different social network models: the cohesion model, which is based on diffusion by direct communication, and the structural equivalence model, which is based on diffusion by similarity of network position. This study then empirically examines a sample of e-commerce diffusion taken from the Taiwan's industrial structure in 2001. The analytical results show that e-commerce diffusion among firms in Taiwan exhibits both contagion effects, but that the mimetic behavior is predicted better by network position than by interactions with others.     

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.     

考虑负面口碑的竞争性创新扩散研究：概念框架与仿真分析

创新往往以市场扩散失败而告终,但当前研究常常围绕成功的创新扩散展开。创新扩散存在多层意义,而不仅仅体现在扩散数量上。在Bass扩散模型的基础上,构造考虑竞争与负面口碑影响的多状态创新扩散模型,利用系统动力学方法探讨不同情境下的创新扩散。仿真结果显示,竞争与负面口碑将从数量和价值角度影响创新扩散过程与结果;同时,作为一种复杂系统,影响因素在类别与品牌层面上的效果并不一致。     

复杂网络下产业转移与区域技术创新扩散影响关系研究

在对产业转移与区域技术创新扩散的复杂网络结构进行分析的基础上,结合复杂网络和采纳阈值模型等相关理论,以技术类型为调节变量,构建了基于产业转移的区域技术创新扩散仿真模型,并借助Netlogo仿真平台进行了仿真分析。结果表明,产业转移规模、创新程度及信息整合与技术创新扩散速度均呈正向相关关系,但在技术创新扩散深度上,受阈值机制的影响,二者关系呈现阶段性变化规律,且在不同的技术类型情况下,转移产业规模、创新程度及信息整合对技术创新扩散深度的影响也存在差异性特征。最后为产业转移和区域经济管理者提出了相关对策建议。     

Issues in modelling innovation intense environments: The importance of the historical and cultural context

Since the 1970s the number of developments labelled as innovation intense environments has increased at an exponential rate. Innovation intense environments are defined here as those spaces that are purported to accelerate the rate of innovation and the proliferation of high technology industries. A number of academic fields now study existing innovation intense environments like Silicon Valley, in order to explain how they are constituted and how they can be replicated.

 Over the years a wide variety of model innovation intense environments has been proposed including: science park, technopolis, information city, milieu, industry cluster and regional innovation system. These different models are compared and analysed in terms of their portrayal of appropriate form, core innovation dynamics and policy recommendations. The discussion of models is then placed within the post-war history of the most famous innovation intense environment—Silicon Valley. It is concluded that such models must be well grounded within a specific historic and cultural context in order to function as useful analytic tools.     

On the combination of exponential smoothing and diffusion forecasts: An application to broadband diffusion in the OECD area

The innovation diffusion literature has established that the spread of a successful innovation over time typically follows a sigmoid curve. Therefore, the forecasting in this area has been monopolized by the use of well known aggregate diffusion models. Time series forecasting has been surprisingly neglected, as it provides mainly accurate short term forecasts. In this work, a method of exponential smoothing, the Holt's damped trend with a modification, is applied in recent broadband diffusion data of two large regions after the reach of the inflection point. As validated with holdback sample data ranging from 6 up to 30 months, the key for successful forecasting is the use of the estimated saturation level calculated from a diffusion model, in order to specify the appropriate trend. The results indicate improved predictions compared to two popular diffusion models, the Gompertz and the Linear Logistic model. The paper concludes with the application of the proposed method in a 48-month forecasting horizon, as well as the suggestions for further research.     

Agent-based modeling of the diffusion of environmental innovations — An empirical approach

This paper presents an agent-based model of the diffusion of water-saving innovations. The empirical foundation of this model is a study, which was carried out for that specific purpose. As an example case, the diffusion of three water-related innovations in Southern Germany was chosen. The model represents a real geographic area and simulates the diffusion of showerheads, toilet flushes, and rain-harvesting systems. Agents are households of certain lifestyles, as represented by the Sinus-Milieus® from commercial marketing. Agents use two different kinds of decision rules to decide upon adoption or rejection of the modeled innovations: A cognitively demanding deliberate decision rule and a very simple decision heuristic. Thus, the model integrates concepts of bounded rationality. The overall framework for decision-making is the Theory of Planned Behavior, which has been elaborated using innovation characteristics from diffusion research. The model was calibrated with empirical data stemming from a questionnaire survey and validated against independent data. Scenarios for the nearer future show that water-saving innovations will diffuse even without further promotion, and different promotion strategies that relate specifically to both innovations and lifestyles can be pointed out.     

产业共性技术扩散三阶段模型构建与仿真研究

结合产业共性技术相关理论与技术扩散模型，以政府作用为调节变量，构建产业共性技术扩散的三阶段仿真模型，对产业共性技术扩散三阶段演化特征进行探讨，借助Matlab平台对主体采纳行为和共性技术扩散速度进行仿真，并以我国新能源汽车产业共性技术扩散为例对仿真结果进行实证检验。研究结果表明：产业共性技术扩散先后经历了权威决策、二次创新以及附随扩散3个阶段;产业共性技术扩散的企业采纳比例遵循“S”型曲线规律，而产业共性技术扩散速度出现了“上升-下降-再上升”的“N”型走势;直接采纳二次研发成果的企业，对产业共性技术扩散影响较大;政府在整个产业共性技术扩散过程中发挥关键作用，但在扩散不同阶段政府介入方式与程度会有所差异;二次创新投入比例与成功率影响产业共性技术扩散规模和速度;只有将产业共性技术转化成专有技术或新产品，才能实现共性技术有效扩散。     

Generalized least squares and maximum likelihood estimation of the logistic function for technology diffusion

Given a simple stochastic model of technology adoption, we derive a function for technological diffusion that is logistic in the deterministic part and has an error term based on the binomial distribution. We derive two estimators—a generalized least squares (GLS) estimator and a maximum likelihood (ML) estimator—which should be more efficient than the ordinary least squares (OLS) estimators typically used to estimate technological diffusion functions. We compare the two new estimators with OLS using Monte-Carlo techniques and find that under perfect specification, GLS and ML are equally efficient and both are more efficient than OLS. There was no evidence of bias in any of the estimators. We used the estimators on some example data and found evidence suggesting that under conditions of misspecification, the estimated variance-covariance of the ML estimator is badly biased. We verified the existence of the bias with a second Monte-Carlo experiment performed with a known misspecification. In the second experiment, GLS was the most efficient estimator, followed by ML, and OLS was least efficient. We conclude that the GLS estimator of choice.     

Modelling the faddish, fashionable and efficient diffusion of agricultural technologies: A case study of the diffusion of wool testing technology in Australia

This study investigates the nature of innovation diffusion in an agricultural context. The dominant agricultural diffusion models assume that an economically rational choice is made to adopt or reject agricultural technologies. However, recent studies of agricultural innovation highlight the ‘irrational’ and potentially ‘inefficient’ nature of the diffusion in this context. To investigate how and why agricultural technologies are adopted or rejected, we examine the diffusion of wool testing technologies in the Australian wool industry using the Bass diffusion model and Abrahamson's diffusion and rejection typology. The results show that diffusion of agricultural innovation is not simply an efficient choice made to close observable performance gaps. The findings suggest that the adoption of inefficient innovations and the rejection of efficient innovations can be driven by an adopter's social context, powerful external influences and imitation within an adopter group and that these drivers change over time, suggesting an evolutionary social process underlies the diffusion of agricultural technologies.     

A non-homogeneous non-uniform influence model of innovation diffusion

A model of innovation diffusion which gives unequal weightage to the adopters of different temporal stages and captures commonly observed ups and downs in new product diffusion is proposed. It is shown that our model possesses features of the existing flexible diffusion models and shows better fit which is indicated by the values of R²_adj, mean absolute deviation, and mean percentage error and estimates a larger market potential, M. It has an interesting feature of conversion factors, first increasing then vanishing, much before we approach market saturation, implying that there is a scope of new thrust in converting remaining potential adopters.     

基于多主体仿真的创新扩散模型研究——对企业创新产品营销战略的探讨

区别于现有创新扩散模型,本文提出的基于multi-agent仿真方法的模型,考虑了个体异质性及移动性的特征。模型认为个体在决策是否接受一项创新产品时,主要考虑两方面的因素:一是衡量产品质量是否达到要求;二是衡量周围与其相联结的社会网络中人群的影响。模型用NetLogo仿真软件运行,其仿真结果论证了产品刚刚投放市场时应适当加大广告强度,而随着市场占有率的增加可以适当降低广告强度。同时,本文也讨论了人口密集度、产品特性和个体的社会影响阈值等因素对创新扩散的影响,并提出了相应的营销策略。     

Binomial innovation diffusion models with dynamic potential adopter population

Models for describing the time pattern of the diffusion processes for innovations are used by researchers in various disciplines. These models are in general binomial models—binomial in the sense that they focus their attention on two causal variables: 1) that part of the population who have already adopted the innovation, and 2) the rest of the population who are potential adopters. However, these models have a serious limitation in that the potential adopter population is assumed to remain constant over time. This paper presents some modified binomial innovation diffusion models that incorporate dynamic potential adopter populations. Moreover, the developed models are applied to some case studies, and their superiority in forecasting the time pattern of diffusion is also included in this presentation.     

Technological innovation, organizational linkages and strategic degrees of freedom

This paper draws on case studies of seuen LK-based multinational companies to examine the relationship between different types of technological innovation, internal and external organizational linkages and technology strategy. A model of technological innovation is deueloped to help explore this relationship. The model consists of three dimensions—technology, component and product—linked by four modes of innovation—incremental, architectural, fusion and breakthrough. The findings support the contingency theory, where different organizational structures and processes are consistent with dgerent contingency theoy, where diffrent organizational structures and processes are consistent with development.     

Does organizational innovation moderate technical innovation directly or indirectly?

We find a divergence in the literature regarding the treatment of how organizational innovation affects innovation and performance. One point of view suggests that organizational innovation impacts performance only, while the other suggests that it impacts technical innovation and firm performance. We use the framework of Crepon-Duguet-Mairesse (CDM) to control for endogeneity; we also use two different measures for organizational innovation. Our contributions to the literature are: the CDM framework in this context is novel; prior research either did not/could not control for endogeneity whereas the CDM framework mitigates this. To discriminate between the direct and indirect approach, we implemented AIC and BIC tests. We find that for the innovation equations in all cases and regardless of which organizational innovation variable is used the direct model is preferable. In contrast, for the productivity equations, we find that in all cases the indirect model is preferable. Thus we do not have a definitive statistical test for which model is superior. Yet, it is our contention that organizational innovation is a new routine within the firm that should impact technical innovation. Furthermore, organizational design theories deduce that organizational innovation should impact technical innovation-implying that the direct model is indeed preferable.