An examination of the existing literature shows that venture capital has become a global practice. Venture capitalists make widespread investments outside domestic markets (Wright et al. 2005). It is likely that a new firm will be encouraged to internationalize when the venture capital firm financing it has a high level of international knowledge/expertise. Along these lines, prior studies have investigated how greater ownership among external investors results in higher rates of ventures’ activities in foreign markets (George et al. 2005). We build on these studies by suggesting that venture capital firms aid in the internationalization process of entrepreneurial ventures by providing them with international knowledge. Of course, the impact of venture capital firms’ knowledge in this context varies depending on the extent of their international experience (Fernhaber et al. 2009).
Proximal Firms
Research on knowledge spillovers has argued that firms can profit from other firms’ knowledge through informal interactions. This research has highlighted the importance of geographic proximity to one another for effective knowledge transfer to occur (Audretsch and Feldman 1996). As Saxenian (1990: 97) explained, people “meet at trade shows, industry conferences, and the scores of seminars, talks, and social activities organized by local business organizations and trade associations. In these forums, relationships are easily formed and maintained, technical and market information is exchanged, business contacts are established, and new enterprises are conceived.” A particularly good illustration of the value of knowledge spillovers can be seen in industries characterized by intense research and development (R&D). Many multinational corporations, for instance, have built their R&D labs in specific locations based on the likelihood that spillovers of knowledge occur (Feinberg and Gupta 2004). The degree to which knowledge from one firm spills over to other firms is partially determined by the presence (or lack) of the relevant industry in the firm’s specific geographic area. For instance, while Silicon Valley is the most renowned area for the development of new software, other top tech regions in the United States, such as San Francisco, Boston, and Austin, also represent regions in which knowledge spillovers can advance entrepreneurial firms depending on their industry presence. The notion of knowledge spillovers is usually associated with technological knowledge; however, knowledge spillovers are likely to also occur for international knowledge (Fernhaber et al. 2009). If many of the firms physically surrounding a new venture are international, the likelihood of international knowledge from these firms spilling over and influencing the new firm is greater (Fernhaber et al. 2008).
Internal and External Sources of Knowledge About International Markets
As we addressed above, alliance partners, venture capital firms, and proximal firms can provide entrepreneurial ventures with international knowledge. This knowledge is not usually an element of a formal exchange of resources per se; instead, it is a secondary benefit a new venture can exploit from this relationship. While we believe these external international knowledge sources will directly influence new ventures’ international activities, it is also probable that the international knowledge possessed by the TMT of an entrepreneurial firm will impact the degree to which the firm accepts and capitalizes on these knowledge sources from outside.
One may assume that new ventures that have TMTs with greater international experience are more capable at identifying the worth of their networks’ international knowledge and applying that knowledge when internationalizing. However, my (Dean) colleagues and I (Fernhaber et al. 2009a, b) found that new ventures having TMTs with limited or lacking international knowledge are more likely to take advantage of external knowledge sources. More specifically, new ventures generally have a “high ratio of assumption to knowledge” (McGrath and MacMillan 1995: 4), often motivating them to find external sources to confirm they are taking the right course of action and enhance their odds of success. These external knowledge sources are valuable because they compensate for—and sometimes even replace—new ventures’ limited collection of internal knowledge sources. Indeed, as Stinchcombe and March (1965) described, new ventures’ dependence on social networks for survival is one of the main elements of the liability of newness. This notion implies that when new ventures have inadequate internal international knowledge, they must depend on external international knowledge sources more heavily when making strategic decisions. That is, new ventures with limited knowledge about foreign markets are more likely to be motivated to seek out and actively exploit this knowledge in the outside environment. Entrepreneurial ventures that have TMTs with more international knowledge, on the other hand, will to a limited extent rely on outside knowledge sources (even though they will still benefit from these sources) for recognizing new opportunities in international markets.
Neo-institutional theory corroborates these assertions, demonstrating that during times of uncertainty, firms are more likely to seek out and compare themselves to similar firms in their environment to understand their own situation and adjust their behavior if necessary (Haunschild and Miner 1997). In general, uncertainty can be connected to being new and/or lacking experience (Shepherd et al. 2000). For instance, studying how Japanese firms make decision about their mode of foreign entry, Lu (2002) showed that experience moderates the impact of firms’ isomorphic behavior on their mode of entry decision. Firms with weaker experience in foreign entries generally draw to a greater extent on other firms’ previously used entry modes. Similarly, entrepreneurial firms with weaker international experience tend to confront higher uncertainty and thus to a greater extent depend on outside firms’ international knowledge for opportunity recognition.
In addition, entrepreneurial ventures’ TMTs with weaker international experience tend to profit more from outside international knowledge sources since they have a larger knowledge gap that needs to be filled. Indeed, new ventures sometimes deliberately choose to exploit external knowledge when seeking international opportunities because they recognize a shortage in their own knowledge. However, this exploitation can also occur inadvertently. For instance, a new venture may enter international markets because its partners wanted to or because a particularly valuable opportunity required such entry. An absence of international experience often increases the TMT’s awareness of and openness to accept knowledge from outside sources. Indeed, in my (Dean) study on new venture internationalization with colleagues (Fernhaber et al. 2009), we showed that the association between the international knowledge of an entrepreneurial firm’s external knowledge sources and the firm’s internationalization is more positive when there is less international knowledge within the TMT than when there is more international knowledge within the TMT.
Knowledge, Cognitive Processes, and Opportunity Identification
Previous research has shown that when firms perceive discrepancies between their prior assumptions and environmental signals, a “trigger” is activated that concentrates their attention on the interpretation of the signals and prompts the development and pursuit of a response by the organization (Dutton and Jackson 1987). However, while we know what factors influence managerial perceptions of environmental signals within organizations (Kaplan 2008; Ocasio 1997), our understanding of perceptions of opportunities is incomplete. That is, compared to perceptions of threat, we know less about the processes individuals use to identify opportunities. However, we do know, as Baron (2006: 104) argued, that opportunity identification requires pattern recognition, or the ability to “‘connect the dots between changes in technology, demographics, markets, government policies and other factors.” Indeed, Baron and Ensley (2006) found that experts’ opportunity prototypes show higher complexity levels than prototypes of novice entrepreneurs and highlight different characteristics of both the opportunity and the business.
Although these studies are a considerable step toward understanding opportunity identification, numerous conceptual issues and empirical difficulties still hinder research in this area. Some studies, for example, investigate opportunities t
hat were identified in the past, thus leading to limitations caused by biases due to retrospection and success (Golden 1992; Huber and Power 1985). Consequently, it continues to be challenging to uncover precisely how attention to environmental signals fosters opportunity identification (Ocasio 1997; Shepherd et al. 2007, 2017); what the perceived features of the signals are (Jackson and Dutton 1988; Julian and Ofori-Dankwa 2008); what information-processing abilities individuals have (Kuvaas 2002; Milliken 1990); what crucial resources, resource slack, or strategies firms have (Chattopadhyay et al. 2001; Thomas and McDaniel 1990); or how prior knowledge (Dimov 2007b; Shane 2000; Shepherd and DeTienne 2005) and other capabilities and resources at the individual or organizational level are utilized (Barnett 2008; Cattani and Ferriani 2008). Thus, numerous unanswered questions remain surrounding what factors facilitate opportunity recognition as well as how and why these factors are so crucial.
To shed light on these issues, my (Dean) colleagues and I (Grégoire et al. 2010) explored the reasoning strategies individuals utilize to identify opportunities. More specifically, the study investigated two previously unaddressed questions: what cognitive process facilitates individuals’ opportunity recognition, and what particular role does the individual’s prior knowledge play in this process? To this end, we created a model of opportunity identification as a cognitive process of structural alignment (Gentner 1983, 1989). Next, we carried out exercises with founders to document their think-aloud articulations during their attempts to identify new technological opportunities. An analysis of these articulations determined the degree to which entrepreneurs utilize structural-alignment processes when identifying new technological opportunities as well as the impact prior knowledge has in these processes.
These findings of structural-alignment processes have broader implications for research on organizations. Crossan et al. (1999) showed that for organizational learning, opportunity recognition is based on mechanisms at the inter-individual, team, organization, and society levels (Davidsson 2003; Dimov 2007a); however, there are also many poorly understood individual processes at the center of this multilevel phenomenon. Moreover, opportunity recognition is a prerequisite to opportunity evaluation and pursuit by both individuals and organizations (McMullen and Shepherd 2006). Thus, individual opportunity-recognition processes are crucial not only for entrepreneurial firm foundation but also for learning, adaptation, renewal, and strategy formulation more generally within organizations (Crossan and Berdrow 2003; Zott and Amit 2007).
There is a recurrent discussion among scholars about the ontological nature of opportunities. That is, do opportunities come into being as objective artifacts waiting for predisposed individuals to “discover” them, or do they come into being out of these individuals’ subjective interpretations and creative behavior? This discussion has received a great deal of attention (Davidsson 2003; McMullen et al. 2007), but it is our opinion that in its current form, this debate has led to a stalemate that impedes research on one of the most relevant phenomena for organization scholars; that is, it impedes research on the processes individuals and organizations use to identify and then exploit potential opportunities (Grégoire et al. 2010; McMullen and Shepherd 2006; Shepherd et al. 2007; Shepherd 2015).
Rather than focusing on the philosophical foundations of the nature of opportunities, it may be more beneficial to examine research suggesting that opportunities stem from changes, such as changes associated with new organizational or individual knowledge, changes in the actions of important players in the economy (e.g., customers, suppliers, competitors), or widespread changes in the macro-environment (e.g., new regulations , economic cycles) (Grégoire et al. 2010; see also Shepherd et al. 2007, 2017). However, while changes like these may make existing routines and processes less optimal, they do not represent opportunities in and of themselves. As an example, take an inventor developing a new technology. While this new technology may create an objectively distinguishable environmental change, he or she does not already “have” an opportunity. Further, the new technology itself does not signify an opportunity because opportunities are associated with action targeted at reaping benefits from these changes (Grégoire et al. 2010; Grégoire and Shepherd 2012). In the entrepreneurial context, for example, new technological opportunities would stem from applying the technology in a specific market context (see Venkataraman and Sarasvathy 2001: 652; Eckhardt and Shane 2003).
Yet, the appropriateness of using a new technology in a specific market context is uncertain from the beginning (Knight 1921; McMullen and Shepherd 2006) due to unbalanced knowledge diffusion (Hayek 1945) and restrictions to the rationality of the person (Simon 1957), including narrow attention (Ocasio 1997; Shepherd et al. 2007, 2017); this appropriateness can only be examined in hindsight. Thus, we can conclude that the opportunity-identification process has both objective and subjective dimensions: there is the objective reality of an individual’s environment and then his or her subjective interpretation of this environment and of his or her role in that environment before any objective facts become available (McMullen and Shepherd 2006).
As such, research has focused on the difference between two interdependent phases of entrepreneurial action (McMullen and Shepherd 2006; Shepherd et al. 2017). The first phase deals with the emergence of subjective individual beliefs about the existence of an opportunity for somebody who possesses the capabilities/skills necessary for exploitation (2006: 137). The second deals with individuals’ assessment of the opportunity for themselves or their organization—namely, whether they have the capabilities and motivation necessary for exploitation. Thus far, the majority of work on opportunity identification has either not distinguished between the two opportunity-process phases (e.g., Baron and Ensley 2006) or has concentrated on the assessment phase (e.g., Chattopadhyay et al. 2001; Krueger and Brazeal 1994; Sarasvathy 2001; Thomas and McDaniel 1990). Yet, to advance knowledge of the underlying mechanisms that lead individuals and organizations to pursue potential opportunities, research has also focused on the first phase—the process of identifying opportunities orefforts to make sense of signals of change (e.g., new information about new conditions) to form beliefs regarding whether or not enacting a course of action to address this change could lead to net benefits (for instance, in terms of profits, growth, competitive jockeying and/or other forms of individual or organizational gains). (Grégoire et al. 2010: 415)
Structural Alignment Connecting the Novel to the Known
We believe that the solution to this puzzle lies partly in examining the cognitive processes people use to make sense of new information. It is well documented that individuals mentally compare new information to their prior knowledge in order to understand it. With this perspective, being able to identify opportunity-relevant patterns requires individuals to put forth cognitive effort to see “resemblances” between what happens in the world (such indications of possible environmental changes) and their mental models of circumstances that are pertinent to understanding the new information as well as to (in the case of opportunity identification) recognizing a plan to potentially benefit from these changes.
However, how does this comparison and sensemaking occur in the real world? What cognitive processes do individuals use to evaluate resemblances between new information and their prior knowledge? This issue of resemblance is the focus of cognitive research on perceptions of similarity and the utilization and outcomes of similarity considerations across a large variety of reasoning tasks (cf. Holyoak and Thagard 1996). Research in this area emphasizes that similarity perceptions regarding two or more items of interest depend on individuals’ alignment of mental representations of these items (Day and Gentner 2007; Keane et al. 1994). Following on this research stream, the cognitive process of structural alignment (Gentner 1983, 1989) can serve as a valuable foundation to explore opportunity recognition. Structural alignment represents a cognitive “tool” individuals use to compare objects. Based on this comparison, the individual then derives implications o
r generates new insights. When individuals come across a new object, for example, they tend to instinctively question if anything in the new object is similar to anything they have encountered previously. Based on identified similarities, individuals then make efforts to more fully make sense of the new object. As cognitive scientists have illustrated, these considerations and the associated structural-alignment mechanism take a vital role in how individuals understand new information, learn novel ideas, and create new categories (see Holland et al. 1986). These processes include scientific innovation, the development of new product ideas, strategy development (Gavetti and Rivkin 2005, 2007), and other tasks that require creativity (Dahl and Moreau 2002; Ward 1995).
A main finding of this literature is that alignment occurs at two levels. One level centers on superficial features, while the other level centers on structural relationships (Gentner 1983, 1989). Specifically, superficial features are a mental representation’s basic “parts” in addition to its characteristics and attributes (Gentner et al. 1995: 271). Structural relationships, on the other hand, are the links connecting various superficial features as part of a mental representation. Further, research has found that there are two types of structural relationships. The first type are first-order structural relationships, which denote one-to-one functional relationships between superficial features. These superficial features can include direct effects and action verbs. The second type are higher-order relationships, which are “relationships between relationships” and are therefore more abstract. Higher-order relationships include goal statements, causal chains, and conditional rules (Gentner et al. 1993; Holyoak 1985).
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