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The Moldoveanu, Baum & Rowley approach highlights the importance of developing a multi-level theory of network evolution that explicitly accounts for strategic agency and (bounded) rationality. I discuss intriguing questions raised by their model about structure vs. topology, feedback loops in evolution, and network resources other than information.

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).

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.

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.

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.

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.

This article is premised on the idea that social networks represent an important, but often overlooked, unit of analysis in management and entrepreneurship studies. The concept of embeddedness, emphasizing the significance of social relationships, is of particular relevance as more and more frequently minorities and immigrants engage in small businessownership. This article borrows from the ethnicity and social network traditions, and offers that an analysis of the ethnic homogeneity of an entrepreneur's strong and weak social ties would be fruitful in gauging entrepreneurial success.

The purpose of this study is to focus on a growing strategic approach in global industries: the coopetition. Cooperation among competitors, namely, coopetition, is a strategic guideline in many global industries affected by technological innovation. This study discussed the effect of firm-, inter-firm- and industry-level drivers leading to coopetitive agreements in global industries affected by technological innovation.

By using an event history analysis, the authors develop a framework on firm-, inter-firm- and industry-level drivers on the likelihood of each competitor in the industry entering into coopetitive agreements in global competitive contexts. Empirical data are analyzed in five global industries: car industry, telecommunication industry, air transportation industry, bank industry and computer programming services industry.

The results of this study suggest that firms’ experience in cooperation (H1) predicts whether a firm will enter a coopetitive agreement. Moreover, the cultural similarity among competitors (H2) predicts whether a firm will enter a coopetitive agreement with a culturally similar competitor, while the total number of competitors already involved in coopetitive agreements (H3) has a low positive effect on the likelihood of a firm to coopete. Finally, the speed of agreements among competitors (H4) and the total number of coopetitive agreements in the industry (H5) (only in the car industry and software industry) are positively related to the chance of a firm entering into a coopetitive agreement.

First, the authors identified and tested specific drivers of coopetition as a result of the literature review and data accessibility. The results may have omitted some variables able to further explain the event of coopetition. Second, the results of cultural distance versus cultural similarity revealed differences on firms’ behavior according to their different nationality. Chinese firms were the most oriented to deal coopetitive agreements with other Chinese firms, while firms from other countries were progressively less oriented by cultural similarity. These results may lead to studies of the “country of origin effect” on which partners to include in coopeititve agreements or which network of partners to join. Finally, the findings of this study are based on five industries over a specific ten years period of time. Consequently, the results certainly reflect the evolution of these industries over the time period considered.

The empirical investigation clarifies the relationship between decisions on strategy and competitive dynamics with the decision-making option to coopete. While managers take into account strategic moves against competitors, according to the authors’ investigation, it is valuable to consider coopetitive actions, especially when other competitors are involved in coopetitive agreements and the industry is affected by technological innovation. Moreover, the knowledge of drivers at the firm, inter-firm and industry level affecting coopetition is helpful to identify the weak or strong signals that show the rise and proliferation of coopetition in an industry.

This study highlights the relevance of coopetition as an emerging approach in the competition among firms for developing or exploiting technological innovations. This approach can improve results in technological innovations that can have an impact in sustainability as well as new innovative solutions for social progress.

In literature, attention has been focused on drivers explaining the growing number of coopetitive agreements in several industries. Some contributions already discussed this topic from the perspective of costs and benefits for players. This study tries to continue to fill this research gap by studying, at firm, inter-firm and industry level, drivers of the likelihood of each competitor in the industry entering into coopetitive agreements in global competitive contexts.