Article Preview
Top1. Introduction
Private equity financing is critical for new ventures to enhance their likelihood of survival and success, particularly in the early stages of their life cycle (Bruton et al., 2010; Cavallo et al., 2019; Pan et al., 2020; Tian et al., 2019). It is critical because new ventures often face the liability of “newness”; in general, they also have limited financial capital resources, which constrains their operations and development (Stinchcombe, 1965; Tian et al., 2019). However, new ventures can experience challenges when seeking to obtain financial support from private equity investors (Becker-Blease & Sohl, 2015). One key reason for these challenges is that new ventures often face an information asymmetry problem caused by the lack of a credible operational track record (Fisher et al., 2016; Wang et al., 2019). In the absence of information regarding a venture’s quality, entrepreneurial signaling information management have been identified as a key mechanism that enables new ventures to communicate their unobservable quality and potential value to investors, enabling them to secure private equity funding (e.g., Certo, 2003; Plummer et al., 2016).
Research based on signaling theory has revealed that new ventures make frequent use of multiple signal types in their pursuit of private equity financing (Drover et al., 2017; Vergne et al., 2018). These signals relate to several factors, such as the educational background and prior experience of entrepreneurs (e.g., Park et al., 2016); a venture’s innovative product lines (e.g., Hoenig & Henkel, 2015); and a venture’s participation in strategic alliances (e.g., Pollock et al., 2010). However, the literature presents inconsistent findings regarding the effect of different signals on securing equity financing (Ko & McKelvie, 2018). One important reason for these inconsistent findings is that studies have predominantly focused on new ventures as signalers to explore the effects of signals; it is generally assumed that signals are received and understood equally by all investors who are the signal receivers (Drover et al., 2017). However, financing decisions are made by an investor’s determination of a signal’s effectiveness (Bitektine, 2011), and investors’ interpretation of signals may differ (Connelly et al., 2011). Moreover, different investor types, such as angel and venture capital (VC) investors, who have diverse priorities and focuses, may also interpret the same signal sent by ventures differently (Fisher et al., 2016). In summary, it is important to explore the process of how different equity investors interpret the signals sent by new ventures.
Therefore, to address knowledge gaps and further advance the new venture signaling literature, this study adopts an integrated signaling and screening framework to explore how different investors interpret the multiple types of signals from new ventures at different growth stages. Further, it uses data on signaler‒receiver pairs in this framework. Adopting an inductive case study approach (Eisenhardt, 1989), the study investigates 16 new venture cases in the high-technology industry and their corresponding angel investors and venture capitalists. The high-technology industry provides a useful study context for two reasons. First, the complexity of high technology means that it is difficult for equity investors to assess new ventures; thus, information asymmetry is typically severe in this sector (Cannizzaro & Weiner, 2018). Second, the development of technology-intensive products and services involves significant resource consumption and uncertainty, which means that securing external financing is often critical to a new venture’s survival and development (Colombo & Grilli, 2009; Gimmon & Levie, 2010). Consequently, this research setting is ideal for examining the dynamic of multiple signals in the financing acquisition of new ventures.