Valente, T. (1995)
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Archives: Literature
Liu, B., Madhavan, R., Sudharshan, D. (2005)
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Research Paper
Abstract: 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.
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<1 min
Valente, T. (1996)
Abstract: Threshold models have been postulated as one explanation for the success or failure of collective action and the diffusion of innovations. The present paper creates a social network threshold model of the diffusion of innovations based on the Ryan and Gross (1943) adopter categories: (1) early adopters; (2) early majority; (3) late majority; (4) laggards. This new model uses social networks as a basis for adopter categorization, instead of solely relying on the system-level analysis used previously. The present paper argues that these four adopter categories can be created either with respect to the entire social system, or with respect to an individual’s personal network. This dual typology is used to analyze three diffusion datasets to show how external influence and opinion leadership channel the diffusion of innovations. Network thresholds can be used (1) to vary the definition of behavioral contagion, (2) to predict the pattern of diffusion of innovations, and (3) to identify opinion leaders and followers in order to understand the two-step flow hypothesis better.
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<1 min
Kernaghan, S. (2016)
An interesting read on the social acceptance of Google Glass (v1). Includes a deep trawl through what "social acceptance" means, which adds to the story of innovation resistance. Also proposes addition to the Technology Adoption Model 2 (TAM-2).
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<1 min
Govindarajan, V., Trimble, C. (2012)
Mentioned in this article: https://solvinnov.com/resistance-of-innovation/
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Ram, S. (1987)
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Research Paper
“Adoption begins only after the initial resistance offered by the consumers is overcome” plus an interesting model of resistance and attributes
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Sanchez, I., Williams, A., García-Andreu, H. (2019)
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Research Paper
Abstract: Customer resistance is the greatest risk to innovation for the entrepreneur. The aim of this exploratory study is to provide insights into this underdeveloped area in the tourism innovation literature. A qualitative approach is adopted to understand the resistance experienced by 57 entrepreneurs when introducing their innovations into the market, the causes and the actions taken to minimise resistance. Findings indicate that most entrepreneurs often encounter resistance from sceptical customers, satisfied with their status quo and with no or low appetites for innovation. The analysis reveals two main sources of resistance: the association of the innovations with particular risks, and the customers' lack of understanding of the innovation value. Communication strategies are crucial to decrease the associated risks and for trust building. The paper provides a critical perspective on the challenges faced by innovators, challenges which are often overlooked given the near-iconic status of innovation in studies of economic development.
Looks at 57 entrepreneurs and resistance to innovation in the tourism industry. Includes a conceptual model on what to do in the face of postponement, rejection and opposition
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<1 min
Bass, F., Bass, P. I. (2011)
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Research Paper
Abstract: This paper explores multiple-generation demand dynamics of “fast-tech” products, which we define as durable technological products and technology-based services where repeat purchases are motivated by user-perceived functionality increases that trigger generational transitions. Examples of fast-tech products include: personal computers (PCs), DRAMs, printers and wireless telephone services. In management of fast-tech products, special attention must be paid to the different needs of adopters and repeaters, which may require different product, advertising and distribution-channel strategies. We develop a model of multiple-generation product diffusion in which sales are constructed as the sum of adoption sales and repeat sales thus, for the first time, separately identifying first-time purchases and repeat purchases. The model also identifies (1) the potential market for each generation, (2) total systems in use (subscribers if a service market) by time period and (3) systems-in-use (installed-base) mix by product/service generation for each time period. The model reduces to the basic Bass model (1969) in the case of a single generation. We use two sets of empirical data (eight DRAM generations and nine PC generations) to demonstrate that the model provides an excellent fit to historical data. We also provide support for the Norton-Bass Model by fitting it to these same data.
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Bass, F., Krishnan, T., Jain, D. (2000)
In V Mahajan,E Muller and Y. Wind (eds.) NEW-PRODUCT DIFFUSION MODELS Absftact. Following the publication of the Bass model in 1969 in Management Scienceth, e earliestattempt to modify this model to include decision variableswasan often-cited 1975 paper by Robinson and Lakhani thar was also published inManagemenSt cierceI.n the ensuingyearsnumerous modifications and extensionsofthe Bassmodel havebeenproposedto […]
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Bass, F., Krishnan, T., Jain, D. (1994)
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Research Paper
Describes a Generalised Bass Model (GBM) that takes account of price changes or advertising efforts etc. These are defined as decision variables and the paper describes a model to handle them.
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<1 min