The role of network density and betweenness centrality in diffusing new venture legitimacy: an epidemiological approach | SpringerLink

We began by asking the question of what happens after new venture legitimacy is established. Researchers have explored how organizations in general, and new ventures in particular, have sought and been judged to be legitimate. This is a valuable endeavor, but it only provides a beginning for identifying how new ventures are judged to be legitimate by groups of stakeholders. Conceptualizing the new venture legitimation process from individual to collective levels (and back) had not been accomplished. By relying on epidemiological principles, we believe that our effort here has made headway in the linking of individual and collective levels of the legitimation process for new ventures. We also believe that understanding the diffusion of new venture legitimacy is critical to researchers and practitioners because diffusion is an essential element of the growth and success of new ventures.

To address our research question, we developed a model and propositions that describe new venture legitimacy diffusion. We used network density and betweenness centrality to explain how the social context affects the diffusion process. We realize that other aspects of the social context need to be explored to continue to enhance understanding of the diffusion process. But, this first step was important because it extends the work of others on initial legitimacy judgments of new ventures. In advancing this line of research we used epidemiology as a guide and had to integrate multiple streams of research involving the areas of legitimation, network density, new venture legitimacy evaluation processes and judgments, collective level legitimacy, and diffusion. By organizing these research areas around individual and collective processes we constructed a model of new venture legitimacy diffusion that identifies different diffusion paths that stem from different social contexts that a new venture may seek out. This not only provides an explanation of how the process unfolds, but it points to the potential for entrepreneurs to influence their venture’s legitimation process beyond the initial act of legitimacy-seeking via selection of legitimacy acquisition strategies (Zimmerman and Zeitz 2002).

Theoretical implications

There are two primary conceptual insights that arise from this work. The first is that the social structure of the potential stakeholders of the new venture may affect the type of legitimacy judgment process that occurs. We examined how the density and betweenness centrality of the network of stakeholders could influence the judgment process. We argued that a reliance on normative or pragmatic processes would stem from the existence of high- and low-density (and betweenness centrality) networks respectively. This gives rise to the idea that potential stakeholders do not have complete flexibility in how they evaluate new ventures. Their judgment process may be strongly influenced by their social context. This, of course, points to the likelihood that other aspects of the social context may influence the legitimacy judgment process, and these will also need to be examined.

The second conceptual insight is that the type of judgment process, normative or pragmatic, used may affect the rate and extent of legitimacy judgments. This effect occurs at both the individual and collective levels within a social context such as a network. Our logic and arguments directed us toward the idea that normative legitimacy judgment processes would be less likely to judge new ventures as legitimate initially, but if legitimacy judgments begin to be made by members of the network they would occur faster and more extensively than found in a pragmatic legitimacy judgment process.

These two conceptual insights extend the extant research focus that has primarily looked at identifying different types of legitimacy and possible strategies for new ventures to gain legitimacy. We add to these initial efforts by suggesting that the networks that new ventures try to gain legitimacy from have characteristics that will likely influence the type of legitimacy judgment process that will be used. Based on the process used, these networks will also likely vary in how quickly and extensively they may judge the new venture as legitimate. Thus, new venture growth and success may be closely tied to the types of networks in which they attempt to enter, rather than tied to particular firms in isolation.

In addition to these conceptual insights, an implication of our focus on network density and betweenness centrality is it highlights the lack of attention paid to network membership, structure, and boundaries. Our working assumption has been that networks are identifiable, but this is not always the case. Networks often contain members with various types of connections (i.e. multiplex (Burt 1980)), which means they are not all attached to the same degree. For example, in a supply chain network some network members are customers while others are suppliers depending on their location in the supply chain. Within a supply chain network, new ventures judged as legitimate by members at one level of the supply chain may not be judged as legitimate at another level. For example, if customers view a new manufacturer as pragmatically legitimate, in part, because they like the lower prices offered, suppliers to the new manufacturer might believe the low prices are not sustainable and the manufacturer will not last. Thus, the basic ideas of network membership need to take into account their potential fluidity.

Continuing with the idea that entrepreneurs may need to better plan out their legitimacy seeking efforts, the current research also informs stage and process models of entrepreneurship (e.g. Bhave 1994; Hanks et al. 1993). Researchers have noted the varying importance of networks during different entrepreneurial stages (e.g. Martinez and Aldrich 2011). Identifying what needs to be done at various stages of the entrepreneurship lifecycle often involves backing up from a predetermined completion point based on how long an activity requires (Fisher et al. 2015). Researchers interested in examining the benefits and drawbacks of entrepreneurs engaging in certain activities during particular stages may profit from a better understanding of the effects of the social context (Bloodgood et al. 1995). Some activities associated with gaining legitimacy and accessing resources or building external relationships may have to transpire in an earlier stage than previously thought. For example, a new venture in need of supplier-partners may have to start this process earlier when pursuing organizations in a dense or high betweenness centrality network. These same actions may not be necessary until a later stage if organizations in a less dense or low betweenness centrality network are the focus.

Similar to stages, geographic levels should also be considered. Older stage models tended to view a new venture as developing locally first and then expanding regionally, nationally, and then globally. Although some ventures continue to follow this path, some new ventures start out globally. These are termed international new ventures (INVs) and are seen as marketing to or integrating resources from multiple parts of the world and gaining a competitive advantage using a product differentiation or low cost strategy (Bloodgood et al. 1996). From a legitimacy diffusion standpoint, each type of geographic expansion could benefit from a different approach. For instance, new ventures starting out locally or regionally may want to utilize local networks to a higher degree than would INVs because the networks might be more open to accepting the new venture.

Research opportunities

Legitimacy-related actions can influence performance (Khaire 2010; Rao et al. 2008). Thus, it is important to understand how legitimacy operates within networks. Our model offers several opportunities for future research. One opportunity is to examine if network density and betweenness centrality influence the type of legitimacy judgment process used by stakeholders. We argued that this influence occurs through the extent of internal network contact and influence. Empirical examination could be performed by measuring the density, betweenness centrality, extent of internal contact and influence of the networks where new ventures seek legitimacy judgments. Network members could be surveyed about how they specifically evaluate new ventures. This could determine the appropriateness of our model and help identify additional contextual factors that may influence the process. A second opportunity is to determine if initial legitimacy judgments are made more quickly in pragmatic judgment processes than they are in normative processes. Also, not all new venture efforts will be equally proactive in trying to obtain legitimacy judgments, so additional measures would need to account for this.

Another consideration is that the definition of legitimacy used within networks may vary and this might affect the attainment of legitimacy thresholds. Thus a third research opportunity is to see if rates of legitimacy attainment increase at different times for normative and pragmatic legitimacy processes. We have not explicitly theorized any differences. However, our implicit assumption that both processes would end up accumulating legitimacy judgments at certain rates would need to be confirmed.

A fourth opportunity is to determine if attaining normative-based legitimacy leads to quicker and more extensive diffusion than it does with pragmatic-based legitimacy. Although we conveyed a strong theoretical logic for why this would be the case, there could be reasons why it may not occur. Intervening variables may interfere with this effect. For example, a dense network that is facing significant technological change may find its members moving more toward a pragmatic evaluation process because of future uncertainties that outweigh social pressures. The opposite effect might also occur if network members lean on one another’s views more because of uncertainties like technological change.

A fifth opportunity is to examine how venture characteristics affect the legitimacy judgment process. For example, the stage of venture development may be important for researchers to identify as it can significantly affect perceptions, behaviors, and outcomes for all organizations within a network. Ventures can be at various stages of development when they attempt to access networks and this may influence the typical processes used for evaluation. More developed ventures may be easier for network members to judge as legitimate which may affect the evaluation process and/or the diffusion rate.

Teasing out explanations for legitimation in any given situation is difficult (Green et al. 2009). For example, imitation stemming from normative legitimacy through contact and imitation arising from structural equivalence can be similar in effect, but very different in causality (Brass et al. 1998; Scott 1995). This provides opportunities for identifying specific causal mechanisms for various types of legitimacy judgment and diffusion in networks. For example, economic-based processes that are consciously performed, such as gap analysis, may enable researchers examine the interaction of social and non-social methods of determining organizational behavior (Seo and Creed 2002).

Additionally, the relationship between entrepreneurial experience and legitimacy diffusion in high- and low-density and betweenness centrality networks needs to be researched. Serial entrepreneurs may possess social capital that enhances legitimacy (Newbert and Tornikoski 2013). The entrepreneur’s previous successes should mitigate resistance by dense or high betweenness centrality networks to judge a new venture as legitimate. In addition, researchers will also need to investigate how network density and betweenness centrality affect mediocre and inferior new ventures. Our focus was on potentially valuable new ventures, which are likely to have some merit-based acceptance. Inferior new ventures may be less likely to be accepted by each type of network. The extent of this acceptance, however, needs evaluation.

Related to the above point, tie strength between entrepreneurs and network members was not specifically addressed in the current research. Prior efforts by serial entrepreneurs are likely to create relationships that could contain a variety of tie strengths and these ties could influence views of legitimacy. Moreover, the tie strength can vary among network members in both dense and less-dense networks, and the tie strength could influence the transmissibility of legitimacy views. We strongly encourage future researchers to examine tie strength in both types of relationships to improve our understanding of new venture legitimacy diffusion. In addition, transmissibility of legitimacy views between networks can also be a critical factor in how diffusion occurs. Here we have focused on diffusion within a network, but diffusion throughout a population will likely involve many networks and the likelihood is great that this does not occur simultaneously. Instead, the sequential nature of some of the diffusion may identify the role that legitimacy views of one network can have on other networks.

Finally, although most of the research in the area of new venture legitimation has focused on judgments of legitimacy, judgments of illegitimacy are also important. Our model implicitly assumes that ventures can move from “not legitimate” to legitimate. However, they can also go from “not legitimate” to illegitimate; making it extremely difficult for a new venture to survive and grow. We did not address them in our model because illegitimacy has been insufficiently investigated. The lack of understanding in that area would make our model potentially cumbersome and imprecise. Our general view, however, is that illegitimacy judgments and diffusion are likely to follow a similar pattern to that of legitimacy. Thus, in a normative judgment process, if stakeholders start to judge a new venture as illegitimate, not just “not legitimate,” the illegitimacy would diffuse quickly and extensively upon reaching an illegitimacy threshold relative to a pragmatic process. Given that illegitimacy has not been developed as much as legitimacy in the literature, we are not sufficiently confident to portray this in our model.

Practical implications

New ventures can enhance their chances for success by molding their strategy to the environment (Romanelli 1989; Venkatraman and Camillus 1984). In recognition of the conformance pressures that guide behaviors within networks, new ventures should consider actions to improve their chances for obtaining legitimacy within a network. New ventures do not have complete freedom to choose networks, and there is likely to be variance in even defining those networks (Mandják et al. 2011). Thus, they may not always be able to select the specific network that would be most beneficial to them. However, understanding the density and betweenness centrality of networks can guide new ventures as they develop relationships. Networks provide valuable resources and help (Hansen 1995; Shane and Cable 2002), but networking efforts take valuable time (Bloodgood et al. 1995) and are not always beneficial (Park et al. 2010). New ventures with limited knowledge and experience may use a “shotgun approach” for targeting networks. Take for instance the search for venture funding. After initially exploiting the friends and family network, ventures must penetrate the financial networks of banks and venture capitalists. Since these networks tend to be dense and hard to penetrate, many ventures pitch to all who will listen often resulting in unsatisfactory results. A more strategic initial approach of focusing on one member of the network could be very beneficial to overall legitimacy diffusion and venture acceptance. Depending on the current stage of legitimacy diffusion, a new venture may target networks that are high or low in density or betweenness centrality to hasten or enhance diffusion.

The following recommendations can assist new ventures that are free to choose their networks, and in preparation for how to deal with all networks — whether high or low density and betweenness centrality. First, new ventures should assess the density and betweenness centrality in a network. While networks that possess both either high or low density and betweenness centrality can be initially accessed by attempts at achieving pragmatic legitimacy, low-density and low-betweenness centrality networks provide an easier environment for initial legitimacy judgments of new ventures than do high-density and high-betweenness centrality networks because of independence among network members and limited concern about legitimacy (D’Aunno et al. 2000). Thus, in these networks a new venture may initially have an easier time forming relationships with some of these organizations because they are more receptive to economic-based logic or change that could enhance their performance. In high-density and high-betweenness centrality networks, social pressures from other network members tend to hurt new venture efforts toward achieving pragmatic legitimacy. This slower initial acceptance is important for new ventures to understand so they can plan more effectively. For instance, because different entrepreneurial behaviors are vital before and after achieving legitimacy (Rutherford and Buller 2007), new ventures may be able to shift their behaviors to those more conducive to growth rather than obtaining legitimacy. An understanding by new ventures of the role that social pressures will play in some networks may also help the new venture contest those pressures and improve its chances for initial legitimacy.

Low-density and low-betweenness centrality networks provide an environment that is initially less contentious and disapproving of new ventures. Since time is often critical to new ventures (Choi and Shepherd 2004; Starr and Macmillan 1990), strategies that speed up acceptance are likely to improve performance. However, for new ventures that require high degrees of diffusion, those that need significant time may be better off focusing on dense or high-betweenness centrality networks as they offer the best chance for very high levels of diffusion. If this strategy is followed, the new venture may benefit from concentrating its efforts on key network members who, once they judge the new venture to be legitimate may trigger other network members to legitimate it (Rutherford and Buller 2007).

Another action for new ventures to consider is to forecast the future state of social pressure within networks of interest. Legitimacy varies over time (Dacin 1997) because interorganizational ties evolve continually, and this can affect the ongoing status of various elements of relationships, such as trust (Hite 2005). Trust in turn can influence the institutional forces that create and maintain social pressures. One factor that directly affects these ties is the turnover among boundary spanners. These individuals develop relationships between organizations (Gulati and Garguilo 1999), hence their entry and exit disrupts connections between organizations (Broschak 2004; Seabright et al. 1992).

Epidemiology and entrepreneurship research

We utilized epidemiological constructs and relationships to construct relationships involving networks of interest for new ventures. This effort informed and expanded new venture legitimacy beyond the stage of initial attainment. There is much more that can be done, of course. The two general factors of epidemiology that were not evaluated, but were controlled for instead, were the probability of infection if contact is made, and the duration of infectiousness (Anderson and May 1991). These also can be sources of guidance to researchers in entrepreneurship. Epidemiology suggests that certain characteristics of some diseases make them particularly infectious (e.g. spreadable through the air). Some business plans that are presented to interested stakeholders may be simple and appealing enough to be understood and spread easily while other plans may be complex and difficult to understand and spread. Researchers could examine the degree of stakeholder buy-in (disease transmission) among various types of business plans and the approach entrepreneurs use to present them. As far as the duration of infectiousness, researchers could investigate how long stakeholders remain interested in pursuing entrepreneurs once a stakeholder has accepted the premise of the new venture. If an entrepreneur’s vision requires lengthy upfront investment and development before positive results appear, they may be better off constructing business plans that contain exponentially growing benefits that maintain interest among “infected” stakeholders even though the benefits will be undetectable for a long time. Researchers could investigate the degree of stakeholder withdrawal from new ventures to identify what types of benefits maintain the longest appeal.

In addition, although we focused on diffusion within certain types of networks, epidemiology also deals with how diseases move beyond a specific network. We proposed that new venture legitimacy would initially be harder to garner within a dense or high betweenness centrality network, but if a new venture begins to be perceived as legitimate within these types of networks the legitimacy will diffuse faster and more thoroughly than in low-density or low-betweenness centrality networks. What happens beyond the network is also of great interest to researchers and entrepreneurs. It seems logical that legitimacy diffusion within a dense or high-betweenness centrality network would influence the spread of diffusion beyond the network less than it would when the diffusion occurs in an open network. This could be examined using an epidemiological approach, whereby the degree of interaction between networks and the degree of similarity of the adjacent networks would be brought into the analyses. Thus, there is much more that epidemiologically-based analysis offers to the study of new venture growth.

Limitations

We must recognize some limitations of using an epidemiological approach to help explain new venture legitimacy diffusion. Above, we mentioned that the network to network spread of the legitimacy could also be investigated. We have focused on the spread of diffusion within a network, but epidemiology actually focuses on populations. This has been simplified in the model presented here, with an implicit understanding that the term “network” is not always clear cut. A population may not always be a set of distinct of networks. Rather, organizations in the population can be part of a number of networks and these networks can be based on a wide variety of commonalities and connections. It is hard to say where one network starts and another one ends. Even though there can be ambiguity surrounding the boundaries of networks in a population, it is still important to address this issue since it raises research questions concerning how networks overlap, interact, and how brokerage occurs between them.

An additional issue that is raised by the application of epidemiology is the use of a binary legitimate/not legitimate decision by network members. Epidemiology tends to focus on getting a disease or not getting a disease (although there can be variations), and we used this approach because it has support in the legitimacy literature. However, the decision to view a new venture as legitimate or not may not always be appropriate. There may be degrees of legitimacy in some situations. The simplistic model used here to examine the applicability of using epidemiological constructs to help explain new venture legitimacy diffusion, is only meant to be a start. Future research could investigate how degrees of legitimacy may affect the model.

Another issue is the potential for new ventures to be evaluated by network members can be much more complex that a general assessment of legitimacy. There can be a variety of dimensions that new ventures are evaluated on and the evaluations may be positive on some dimensions and negative or neutral on others. This was not captured in full in the model used here. An assumption is made that any specific dimensions of interest are evaluated simultaneously as part of the overall evaluation of legitimacy. This may not always be an accurate portrayal of legitimacy evaluations, and future research should take this into consideration. Some dimensions may be more or less important to different network members, and this can affect the socialization proposed here.

Our model has assumed a set of new ventures that are sufficiently different from network members such that they are not cognitively legitimated, but similar enough that they offer a potential, positive benefit to network members (in order to have a reasonable chance for gaining legitimacy). The degree of difference between a new venture and a network and its members could certainly influence the likelihood of new venture legitimacy diffusion, and these differences could be examined in future studies. There may even be an avenue to address this using epidemiology in the sense that disease transmission may depend on characteristics of the disease and certain physical or other characteristics of persons that could potentially be infected.

Finally, while the relationships posited here are focused on a few variables, we recognize that a variety of other factors may influence these relationships. Some of these factors could play a direct role in the model we present while others could play a moderating role. For example, issues of stage of development, geographic expansion, symmetry and directionality, and network types could significantly influence the degree to which density and betweenness centrality affect legitimacy evaluation processes used by network members.