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1.Objectives of the paper
This study was motivated by two important limitations of existing CVC research. First, we did not find any papers that exclusively focused on CVC investment strategies after the IT bubble burst in 2001. Prior studies include data from the 1990s, which generally constitute more than 70% of the sample's information. In addition, as the vast majority of industrial firms embedded in VC networks during the 1990s have since withdrawn, pretending that their CVC investments strategies were successful is seemingly difficult. Second, according to social network theory (e.g., Powell 1990; Gulati et al. 2000; Sorenson and Stuart 2001), industrial firms should rely on the most central investors in VC networks to glean information about marketable innovations. However, as the industrial firms join the syndications at the VClists' invitation (Hochberg et al. 2007), this optimum strategy is by no means assured. Consequently, industrial firms not pursue this optimum strategy and focus on a second-best strategy, i.e., multiplying their relationships with VClists. To the best of our knowledge, no paper has attempted to determine whether industrial firms pursue an optimum or second-best strategy when they join VC networks.
Moreover, except for Keil et al. (2010), who encounter some limitations that we have outlined above, we have not found any study that uses the GMM system to elucidate the annual revision process of industrial firms operating within VC networks. From an epistemological perspective, this sophisticated auto-regressive model allows us to consider the effect of past decisions on future choices with regard to the same variable. Therefore, the GMM system fits well with the analysis of firms' strategic decisions in uncertain environments or when they are compelled to adopt a trial-and-error process.
2.Methods
2.1. Sample
The data for our analysis come from the Securities Data Corporation (SDC) Venture Economics database, and we have also gathered accounting information on CVC firms from Orbis (BVD).
As calculating network positions requires ample data, we choose to focus our study on the IT industry and select only the industrial firms that finance startups in this industry. Moreover, the IT startup financing led to the swelling of a speculative bubble, starting in the second half of the 1990s. The bursting of this bubble in 2001 led to the withdrawal of investors...