Hyping Diffusion: All Adopters Are Not Equal

2010

Journal of Product Innovation Management, 2010

Innovations usually have an initial impact on very few people. The period of learning or early evaluation precedes the diffusion of the technology into the wider addressed population. More than a transfer, this is best characterized as communication of benefits, costs, and compatibility with earlier technologies and a relative assessment of the new state of the art. Innovation development by an organization or individual creates not just a device (i.e., process or tacit knowledge) but concomitantly a capacity on the part of other organizations or persons to use, adopt, replicate, enhance, or modify the technology, skills, or knowledge for their own purposes. How innovations actually diffuse is to understand the communication of progress, and this framing helps one to design innovations and also design the marketing and testing programs to ready innovations for market and launch them efficiently. Diffusion theory's main focus is on the flow of information within a social system, such as via mass media and word-of-mouth communications. This theory presents often in the form of mathematical models of innovation and imitation. Distinct from classical diffusion models, however, consumers are not all identical in how they connect to others within a market or how they respond to information. We examine the effects of various network structures and relational heterogeneity on innovation diffusion within market networks. Specifically, network topology (the structure of how individuals in the market are connected) and the strength of communication links between innovator and follower market segments (a form of relational heterogeneity) are studied. Several research questions concerning network heterogeneity are addressed with an agent-based modeling approach. The present study's findings are based on simulation results that show important effects of network structure on the diffusion process. The ability to speed diffusion varies significantly according to within-and cross-segment communications within a heterogeneous network structure. The implications of the present approach for new product diffusion are discussed, and future research directions are suggested that may add useful insights into the complex social networks inherent to diffusion. A simple summary is that discovery of significant prime communicator nodes in a network allows innovation development practices to be better calibrated to realistically multiple market segments.

The paper investigates actual directions in diffusion research focusing on simple diffusion models incorporating price effect. We review main papers on diffusion research of the last decade and identify the role and position of diffusion modeling in marketing research. We also perform an empirical analysis of the Bass model and its extensions including price variable. We have four main results. (1) We prove the existence of non-linear correlation between the number of adoptions of LCD televisions and the cumulative sales of the product. (2) There is an evident dominance of the imitation behavior of Slovak consumers driving the first purchase of LCD television. (3) The price decrease of LCD televisions has a positive influence on the imitative behavior of Slovak consumers. (4) Slovak consumers do not consider the initial price of LCD televisions as the reference point when deciding about the first purchase. We calculated the peak sales rate and forecasted the timing of peak sales for the year 2013. In addition, this study should serve as a research proposition to marketing scholars and practitioners for a simpler application of diffusion models.

The paper reviews main shifts in diffusion theory concerning fields of marketing and offers research propositions for applying the model approach. We present empirical results to prove the validity of Bass first-purchase model and its alternative model incorporating the price variable. As research object, we choose the product category of liquid crystal televisions which has been recently introduced as a high-tech and durable commodity on the Slovak market. Application of the two models exhibited that imitation coefficient is much greater than innovation behaviour on the Slovak market of LCD televisions. In addition, in the model incorporating price effect, the imitating behaviour increases with the price decline of LCD TVs.

In this paper, we proposed a three compartment model consisting of non-adopter, adopter and frustrated classes of population to discuss the influence of media coverage in spreading and controlling of adopter of a particular product in a region. The model exhibits two equilibria:(i) a adopter-free and (ii) unique interior equilibrium. Stability analysis of the model shows that the adopter-free equilibrium is always locally asymptotically stable if the influence number of adopter (R 0), which depends on parameters of the system is less than unity. Otherwise if R 0 > 1, a unique interior equilibrium exists, it is locally asymptotically stable under some set of conditions. Further analytically and numerically it is observed that the region for backward bifurcation of adopter population increases with the decrease of the valid contact rate before media alert. Finally, numerically experimentation are presented to establish the effect of different media alert rate on adopter and non adopter population.

2001

This paper takes a contingency view to investigate how the role of early adopters (EAs) in the diffusion process changes between platform and nonplatform innovations, what launch decisions firms take to leverage the role of EAs, and how these decisions change between platform and nonplatform innovations. Relying on an exploratory multiple case study of eight industrial product innovations launched in Italy in the 2000s, the paper suggests that the EAs of these innovations play two distinct roles in the diffusion process. The first role, called dissemination, sees EAs triggering and bolstering the propagation of information regarding their opinion about the value for money, properties, advantages, and disadvantages of the new product after they have bought and applied it in their operations. The second role, labeled imitation, consists of EAs inadvertently communicating to later buyers the fact that they have bought the new product, which propels imitative behavior and thus subsequent adoption. A key finding of the paper, which supports a contingency view of innovation diffusion, is that the dissemination role played by EAs has an impact on the adoption of platform innovations, whereas the imitation one is the mechanism through which EAs stimulate subsequent adoption in the case of nonplatform new products. Furthermore, the paper's results point to a constructive view of the process of launching an innovation, whereby firms target at launch different segments of EAs, whose identity is shaped depending on the platform versus nonplatform nature of the innovation and thus on the role they are expected to play in the diffusion process. Concerning managerial implications, this study provides a first tentative understanding of the launch decisions that product and marketing managers may use to target the most appropriate segments of EAs, to leverage their roles and ultimately to favor diffusion. As regards platform innovations, targeting decisions should be driven by the goal to improve the chances that EAs will be willing to disseminate their experience and opinion regarding the new product. As regards instead nonplatform innovations, firms should target EAs whose specific characteristics increase the likelihood of an imitative reaction by later buyers that fear to suffer a competitive disadvantage if they do not conform to EAs' behavior.

European Journal of Innovation Management, 2005

Purpose -To provide an explicit model to address the relationships between the structural characteristics of a network and the diffusion of innovations through it. Further, based on the above relationships, this research tries to provide a way to infer diffusion curve parameters (innovation coefficient and imitation coefficient) from network structure (e.g. centralization). Design/methodology/approach -Based on the network and innovation literatures, we develop a model explicitly relating the structural properties of the network to its innovation and imitation potential, and in turn to the observed diffusion parameters (innovation and imitation coefficients). We first employ current theoretical and empirical results to develop postulates linking six key network properties to innovation and imitation outcomes, and then seek to model their effects in an integrative manner. We argue that the innovation and imitation potentials of a network may be increased by strategically re-designing the underlying network structure. We validated the model by searching the published empirical literature for available published data on network properties and innovation and imitation coefficients. Findings -We validated the model by searching the published empirical literature for available published data on network properties and innovation and imitation coefficients. The results reported from various relevant research papers support our model. Practical implications -This research shows that the innovation and imitation potentials of a network may be increased by strategically re-designing the underlying network structure; hence, provide guidelines for new product managers to enhance the performance of innovative products by re-design the underlying network structure. Originality/value -The model developed in this paper is a breaking through result of synthesizing various traditions of diffusion research, ranging from anthropology and economics to marketing which were developed independently. The research explicitly modeled the diffusion process in terms of the underlying network structure of the relevant population allowing managers and researchers to directly link the diffusion parameters to the structural properties of the network. By doing so, it added value by making it possible to infer diffusion potential from directly measurable network properties. Vis-à-vis the network diffusion literature in particular, we added value by "unpacking" the diffusion process into innovation and imitation processes that form the building blocks of contagion. Moreover, we developed a holistic structural model of network diffusion which integrates the several network properties that have hitherto been studied separately. Paper type Research paper impact of word-of-mouth communication . Against this background, we propose that explicitly modeling the diffusion process in terms of the underlying network structure of the relevant population will allow us to directly link the diffusion parameters to the structural properties of the network. Drawing on the rich diffusion literature in structural sociology and related disciplines , we address the following research question: What are the relationships between the structural characteristics of a network and the diffusion of innovations through it? Further, given the above relationships, how can we infer diffusion curve parameters (innovation coefficient and imitation coefficient) from network structure (e.g. centralization)?

We present a heterogeneous networks model with the awareness stage and the decision-making stage to explain the process of new products diffusion. If mass media is neglected in the decision-making stage, there is a threshold whether the innovation diffusion is successful or not, or else it is proved that the network model has at least one positive equilibrium. For networks with the power-law degree distribution, numerical simulations confirm analytical results, and also at the same time, by numerical analysis of the influence of the network structure and persuasive advertisements on the density of adopters, we give two different products propagation strategies for two classes of nodes in scale-free networks.

Journal of Product Innovation Management, 2010

Innovation diffusion theory suggests that consumers differ concerning the number of contacts they have and the degree and the direction to which social influences determine their choice to adopt. To test the impacts of these factors on innovation diffusion, in particular the occurrence of hits and flops, a new agent-based model for innovation diffusion is introduced. This model departs from existing percolation models by using more realistic agents (both individual preferences and social influence) and more realistic networks (scale free with cost constraints). Furthermore, it allows consumers to weight the links they have, and it allows links to be directional. In this way this agent-based model tests the effect of VIPs who can have a relatively large impact on many consumers. Results indicate that markets with high social influence are more uncertain concerning the final success of the innovation and that it is more difficult for the innovation to take off. As consumers affect each other to adopt or not at the beginning of the diffusion, the new product has more difficulties to reach the critical mass that is necessary for the product to take off. In addition, results of the simulation experiments show under which conditions highly connected agents (VIPs) determine the final diffusion of the innovation. Although hubs are present in almost any network of consumers, their roles and their effects in different markets can be very different. Using a scale-free network with a cut-off parameter for the maximum number of connections a hub can have, the simulation results show that when hubs have limits to the maximum number of connections the innovation diffusion is severely hampered, and it becomes much more uncertain. However, it is found that the effect of VIPs on the diffusion curve is often overestimated. In fact when the influence of VIPs on the decision making of the consumers is strengthened compared with the influence of normal friends, the diffusion of the innovation is not substantially facilitated. It can be concluded that the importance of VIPs resides in their capacity to inform many consumers and not in a stronger persuasive power.