Emerging entrepreneurial firms rely on network ties “embedded” within social relationships. This theory-building study addresses the research questions of: 1) What are the social qualities of embedded network ties? and 2) To what extent do qualities of the social relationships create different types of embeddedness? Using case study method, network data from eight emerging entrepreneurial firms in the computer industry was collected through semistructured interviews, archival data, and network modeling. Embedded network relationships demonstrated social qualities aggregating into three social components: personal relationship, dyadic interaction and social capital.  Seven types of embeddedness emerged facilitating a more useful construct of embeddedness for future research. Finally, implications of different types of embedded network ties are addressed.

Emerging entrepreneurial firms face the central challenge of obtaining resources for successful firm survival and performance (Aldrich & Zimmer, 1986; Barney, 1991; Peteraf, 1993), particularly given that most emerging firms are internally resource poor due to liabilities of newness and smallness (Baum, 1996; Jarillo, 1989; Stinchcombe, 1965). Therefore, emerging firms typically find critical resources within their social networks (Jarillo, 1989; Larson & Starr, 1993). These network ties are often “embedded” within social relationships that influence the economic actions of the firm (Uzzi, 1996) and are governed through mechanisms of trust and relational contracting (Dyer & Singh, 1998; Granovetter, 1985; Uzzi, 1996, 1997). However, these embedded network ties, and the social relationships upon which they are built, are complex and ambiguous (Bradach & Eccles, 1991; Uzzi, 1996) and demonstrate a variety of social characteristics that may differentially influence trust and resource acquisition.

This research closely examines the qualities of embedded network relationships focusing on the following research questions: 1)What are the qualities of embedded network ties? and 2) To what extent do the qualities of embedded network ties create different types of embeddedness? These research questions address the call for clarification of the qualities of embeddedness and the role of social relationships in economic exchange (Madhok, 1997; Uzzi, 1996), particularly for emerging entrepreneurial firms. This study further “unpacks” the concept of embeddedness (Uzzi, 1996) through a study of the qualities of embedded network ties within emerging entrepreneurial firms in the computer industry. Propositions are presented regarding embeddedness and its qualities. This research also lays theoretical groundwork for future work on embeddedness and firm emergence.

An entrepreneur’s external relationship with another individual or firm creates a dyadic tie. This dyadic tie is the basic building block of the external network and represents the level of analysis for this study. In the case of emerging firms, the social network of the entrepreneur is virtually synonymous with the firm’s network, as network ties initially exist on the interpersonal level (Bhide, 1999; Hite & Hesterly, 1999; Zaheer, McEvily & Perrone, 1998). Thus, during the early stages of emerging firms, both levels of network analysis are often simultaneously at play given that the set of the entrepreneur’s direct dyadic ties, and the relationships between those ties, in turn, creates an egocentric network that can be used for the benefit of the firm (Powell & Smith-Doerr, 1994; Wasserman & Faust, 1994). This research, then, is simultaneously focused on both the individual entrepreneur’s and the firm’s dyadic relationships as these ties directly influence the flow of resources across firm boundaries. Networking through dyadic ties provides the emerging firm with critical avenues to access necessary external resources, bridges to other firms and individuals, and conduits for reciprocal patterns of communication and exchange (Jarillo, 1989; Starr & MacMillan, 1990), Thus, the external network enables resources to cross the firm’s boundary and facilitates emergence of the firm as it borrows, leverages, influences and controls resources not currently owned by the firm (Hite & Hesterly, 1999; Jarillo, 1989).

When network ties are embedded within social relationships that influence the economic actions of the firm, they are embedded network ties (Granovetter, 1985, 1992; Uzzi, 1996). Indeed, Staber & Aldrich (1995) indicate that “sociologists now take as axiomatic the proposition that economic action, including entrepreneurial behavior, is embedded in interpersonal social networks” (p. 442). However, the literature, with the exception of Uzzi (1996, 1997), has generally approached the concept of embeddedness with assumptions of homogeneity across embedded network ties. Yet, important social and strategic differences may exist between embedded network ties as evidenced by the variety of advantages and disadvantages of resource exchange through embedded ties (e.g. Uzzi, 1996, Portes & Sensenbrenner, 1993). Specifically, the social characteristics of these embedded network ties have not previously been well specified. Therefore, if emerging entrepreneurial firms assume that their embedded network ties are similar and, yet the ties are indeed heterogeneous along critical dimensions, the firm may encounter both governance and resources acquisition difficulties that may inhibit successful emergence (Jarillo, 1989). The following section describes this study’s methods of identifying the social qualities of embedded network ties, and the resulting types of embeddedness, of emerging entrepreneurial firms.

 With the goal of theory building, this study utilized a post-positivist paradigm, grounded theory and a case study method (Glaser & Strauss, 1967; Strauss & Corbin, 1994; Miles & Huberman, 1994; Yin, 1994). As such, the findings were grounded in the data (Eisenhardt, 1989; Glaser & Strauss, 1967; Strauss & Corbin, 1994), and the data and theory were continually revisited in a research model that is “conceived [of] as spiraling rather than linear in its progression” (Berg, 1995, p. 16). Given that it is “pointless to seek to explain what we have not described with a reasonable degree of precision” (King, Keohane & Verba, 1994, p. 44), the underlying aim of the research was to gather thick descriptions of embeddedness and to identify the convergence of common themes and patterns across the cases (Glaser & Strauss, 1967; Huberman & Miles, 1994; King et al., 1994; Miles & Huberman, 1994; Schein, 1987; Yin, 1994).

Case Study Design

Case study methods and qualitative approaches are increasingly being advocated as research methods in strategic management, entrepreneurship and network research, particularly for early theory development (e.g., Eisenhardt, 1989, 1991). Based upon theoretical sampling (Erlandson, Harris, Skipper & Allen, 1993; Yin, 1994), eight emerging entrepreneurial firms were selected from the computer industry within the same county of a western US state. This county recently experienced an employment upheaval within the computer industry suggesting the area may be prime for the emergence of new, entrepreneurial firms with high potential for networking activity (Saxenian, 1990) and that new firms may attempt to reestablish equilibrium in the local industry (Kirzner, 1973, 1997). In addition to industry and geographical location, the range in the number of entrepreneurial founders in the firm was another theoretical sampling criteria given that the number and skills of entrepreneurial partners in the firm influences firm strategy (Chandler & Hanks, 1998). In addition, given the focus on emerging firms, case firms were selected that had been licensed within 18 and 24 months to ensure locating firms within the emergence stage.  The firms were identified using lists of new business licenses obtained from July to December 1996. These lists provided the potential pool of firms ages 18-24 months old at the time of data collection (July–September 1998).  An initial screening of these firms indicated 80 out of 982 firms (8%) were specifically emerging in the computer industry.

Sampling parameters also required that firms meet further eligibility criteria (Fink, 1995) to identify whether the firm actually belonged to the population under study, e.g., is the respondent an entrepreneur of an emerging firm? Eligibility criteria were based upon the working definition of an entrepreneur as the founder/owner/manager of a private firm. Telephone screening of the 80 firms determined which firms met the eligibility criteria. From the qualified firms, cases were chosen to fill the theoretical sampling case design based on the number of entrepreneurial partners and willingness to participate. Six (6) emerging entre-preneurial firms were initially identified; two additional cases were added in the process of reaching theoretical saturation (Eisenhardt, 1989; Glaser & Strauss, 1967; Gummesson, 1991; Strauss, 1987). The final eight cases of emerging entrepreneurial firms represented 17 entrepreneurs. Two firms had solo entrepreneurs, three firms had two partners, and three firms had three partners. Thus, the design controlled for industry, location, entrepreneurial team structure and firm age.

Data Collection

The first of two data collection phases entailed an in-depth, open-ended interview with each entrepreneur to understand the history of the firm, the firm’s overall network structure, and the entrepreneur’s direct dyadic network tie relationships in terms of their history, experiences and exchanges with these network ties. This phase also included a review of relevant archival data (e.g. Rolodex lists, email address lists, supplier and customer files). Based on the first interview and archival data, graphical maps were created of each firm’s network. The second phase of data collection entailed a follow-up interview to further explore relationships with network ties, to clarify ambiguous relationships, to conduct a member check with each entrepreneur to confirm the accuracy of the graphical network map (Miles & Huberman, 1994), and to allow the informant to review network relationships for a second time.  In sum, the research data consisted mainly of transcribed text interviews, graphical network maps, researcher observations, and the researcher’s field journal.

Data Analysis

The data analysis was iterative with data collection and facilitated the generation of themes, patterns and theoretical models from the data that were continually being modified to incorporate new data, new themes as well as the researcher’s emergent ideas (Miles & Huberman, 1994). In all, over 300 dyadic network ties were identified by the entrepreneurs, of which 160 had sufficient information to support an initial screening for characteristics of embeddedness based on two criteria: 1) the influence of the social relationship upon economic actions and decisions of the firm (Uzzi, 1996); and 2) evidence of relational contract (as opposed to traditional market contracting) (Dyer & Singh, 1998; Williamson, 1985). Of these 160 ties, 66 embedded network ties emerged (41%) and became the focus of further data analysis. Computer analysis of both the textual and network data was facilitated through the use of NUD*IST, WordPerfect, Krackplot and MacFlow software. Data analysis included within-case, within-group, across-case and across-group pattern matching (Denzin & Lincoln, 1994; Miles & Huberman, 1994). Using NUD*IST to code the interview text for descriptions of characteristics of embedded network ties, over 100 characteristics initially emerged. Through data reduction, tie characteristics were iteratively organized into an hierarchical tree structure where some emerged as superordinate and others emerged as subordinate.

Several social components of embedded network ties emerged from the data that further clarify the qualities of embeddedness. Overarching patterns emerged that included trust, as expected, and three main components of the social relationship. These three main components were composed of 11 attributes at the secondary level and over 100 elements at the third level. The next three sections will describe the social components found in the embedded network ties, namely: personal relationship, dyadic interaction and social capital. Table 1 identifies these three superordinate components of embedded relationships, along with their subordinate attributes and elements. The fourth section will then briefly address the issue of embeddedness and trust which was also an important quality of embeddedness, as expected from previous research (Good, 1988; Granovetter, 1985; Powell & Smith-Doerr, 1994; Uzzi, 1996, 1997).

Personal Relationship

Having a personal relationship with a dyadic network tie represented a pervasive thread which ran, not unexpectedly, throughout the data. Concrete personal relations are a critical element of social relationships within embedded network ties (Coleman, 1988; Granovetter, 1985; Uzzi, 1996). While the personal relationship, alone, is often considered to be the equivalent of the social relationship, in this data, the personal relationship represented just one component of the social relationship. The descriptions of the personal relationships with their embedded network ties entailed three main attributes—Knows Well, Affect, and Sociality. These attributes are also reflected in previous research on personal ties (Burt, 1997; Krackhardt, 1992) providing additional construct validity to the face validity of these attributes. Knowing well is the extent to which the dyadic partners are aware of each other’s persona, needs and interests, e.g. “They know my personality. They can cut to the quick on me and read me and I can read them” (Case 6-4, 6-5: 3828). Affect is represented in the extent to which feelings and emotions are an integral part of the dyadic relationship (Krackhardt, 1992), e.g. “definitely goes a lot deeper than just business” (Case 3-1:4501). Sociality, or the degree to which the dyadic interaction takes on a social and personal nature, was demonstrated in knowing about the dyadic partner’s personal life and family as well as engaging in social activities together, e.g., “We get together and talk for like an hour just to catch up on how his life is” (Case 4-4:1959).  Thus, genuine and sincere sociality provided an important foundation for the personal relationship within embedded relationships. Therefore, an essential component of the social relationship of an embedded network tie is the personal relationship that exists between the dyadic partners. Thus, the data supports the following proposition:

Proposition 1: The greater the personal relationship within a dyadic network tie, in terms of knowing well, affect and sociality, the greater the likelihood that the tie will be an embedded network tie.

Dyadic Interaction

The interaction between the dyadic partners, within the context of the business relationship, represented a second component of the embedded network ties. Dyadic interaction is based upon the history of exchange relations between partners (Emerson, 1976). Interaction, in this sense, does not entail characteristics of the specific transactions or the contractual bases for exchange but, rather, is reflected in the history of interaction attributes that develop between the two dyadic partners. Indeed, “the result of the various kinds of exchanges . . . that actors engage in to achieve their interest is . . . the formation of social relationships having some persistence overtime” (Coleman, 1990, p. 300). Based upon the data, four attributes of dyadic interaction emerged: extent, effort, ease and quality.

Interaction extent entailed the range, scope and comprehensiveness of the partners of exchange between dyadic partners and was composed of frequency, amount, intensity, reciprocal interdependence, multiplexity and duration. For example, one informant described the multiplexity and reciprocal interdependence of his embedded tie: “I’m selling my products through them. But I’m also doing work for them. So it kind of goes both ways. . . . In this whole relationship, they are actually every single one of these that I can think of [supplier, customer, vendor, broker, previous employer]” (Case 3-2:1585, 5404).

Interaction effort is the level of expenditure of energy and resources of one dyadic partner on behalf of the other dyadic partner, specifically that which is beyond what is due, usual or expected; e.g., “I really went out of my way to help her” (Case 3-1:6206). This extra effort represents asymmetrical investments that maintained the dyadic interaction and functioned as the glue motivating continuing interaction. This asymmetry of effort was often displayed under scenarios of problem solving (Uzzi, 1996). Interaction effort was displayed as working for the partner, education, responsiveness, helpfulness, and problem solving.

Interaction ease acts as the lubricant for the wheels of the interaction. Five elements of ease emerged, namely proximity, technological compatibility, goal congruence, convenience and communication quality. Interaction ease reduced stress, tension and difficulty and, thus, increased the likelihood of continuing a relationship which required less effort and created less friction. Interaction ease reflects the comfort of the dyadic interaction, often as a function of the history and familiarity of the interaction. One informant describes this ease as:

Once you develop a good relationship with a client, then it’s going to take a tremendous amount of bad experiences for them to turn away from you. Once they become familiar and comfortable, then that’s a part of their business they no longer have to worry about. It’s like a channel. Once they get down in that, then actually getting up and out and going to find somebody else is a huge amount of work and a lot of risk. And so once you get that established, then you’re home free with them. (Case 5:3404)

Interaction quality is the degree of excellence, merit or superiority of the dyadic interaction. As such, this attribute takes on a subjective nature wherein the entrepreneur is continually evaluating and comparing the dyadic interaction with other network ties, in terms of extent, effort, and ease. The informants described the attributes of quality as knowledge of business needs, being a known entity, understanding, working well together, satisfaction, loyalty to interaction, anticipation of future interaction and synergy. High interaction quality with embedded network ties was described as having “that magic” (4-21:4381). Indeed, outcomes such as commitment and coordinated adaptation are increased under conditions of high interaction quality (Jones & Hesterly, 1995; Podolny, 1994). As such, interaction quality also leads to the positive desire to continue the relationship. Based on the data, embedded ties demonstrated greater dyadic interaction than arm’s length ties, particularly in areas of extent, ease, effort and quality.  Thus, the data support the following proposition:

Proposition 2: The greater the dyadic interaction within a network tie, in terms of extent, ease, effort and quality, the greater the likelihood that the tie will be an embedded network tie.

Social Capital

A third component of embeddedness was the presence of social capital. Embedded network ties manifested four main attributes of social capital. The first two attributes, obligation and resource accessibility (Coleman, 1988), focused on the dyadic relationship. At this level, social capital resides in the relationship between the dyadic partners (Coleman, 1990) and “inheres in the structure of relations between actors,...[and] constitutes a particular kind of resource available to an actor . . . [making] possible the achievement of certain ends that in its absence would not be possible” (Coleman, 1988, p. 98).  Obligations, represented by the extent of social indebtedness which binds or constrains the course of interaction between dyadic partners, manifested three main elements: asymmetry (which included gift giving), expectations and norms, e.g. “I killed myself after hours trying to get as much as I could done...and that bought me a lot of points“ (Case 5-8:1168). Resource accessibility was the extent to which dyadic partners could access the available resources from one another other (Nahapiet & Ghoshal, 1998), e.g. “they could call [us] at anytime if they had any problems” (Case 3-8:883). In addition, two attributes of social capital, brokering and structural embeddedness, touched on the broader network level of analysis (Granovetter, 1985, 1992; Uzzi, 1996; 1997). Brokering involved a dyadic partner connecting the emerging firm with a third party, e.g. “we stay with Steve because nobody knows us at the [new] bank. . . . Steve can help us at the next bank. . . . He bridges relationships and things with the other people we don’t even know“ (Case 6-7:1107,1637). Embedded network ties also displayed structural embeddedness due to common ties providing information flow and created greater redundancy within the network, e.g.,

We all worked together at Frameworks and now everyone is spread out all over. . . . So we have a personal relationship with these folks that allows us to kind of seed around in other places. . . . [Also] Frameworks has developed a whole channel of vendors... I know the people in that channel. So they become my channel . . . now I just go directly to them. (Case 3-2:6403,1573, 1582,6388)

Thus, social capital was demonstrated at both the individual and network levels (Coleman, 1988; Emerson, 1976). Thus, the data support the following proposition:

Proposition 3: The greater the social capital within a network tie, in terms of obligations, resource accessibility, brokering, structural embeddedness,, the greater the likelihood that the tie will be an embedded network tie.

Embedded network relationships, then, are composed of different combinations of these three social components. Based upon the potential combinations of these three components, seven types or patterns of embeddedness emerged among the 66 embedded network ties (see Figure 1). For example, an embedded network tie may have high degrees of personal relationship and dyadic interaction. Another embedded tie may have high degrees of social capital, without the supporting high levels of personal relationship or dyadic interaction. These two social relationships may both develop trust and embeddedness, wherein the social relationship influences the firm’s economic actions (Uzzi, 1996); yet, they may have different strengths and vulnerabilities in terms of resource accessibility and governance controls. This typology, then, provides a foundation for addressing the question of what kind of social relationship, and thus embeddedness, exists within a specific network tie. Each of the seven types of embedded ties indicated in Figure 1 were found within the cases. This section describes each of the seven types of embeddedness, beginning with those that were unidimensionally embedded. Unidimensional ties, representing 9% of the embedded network ties, demonstrated personal, competent or hollow embeddedness.

Personal Embeddedness

Personal embeddedness is built purely upon the affect, knowing well, or sociality of the personal relationship. The tie with personal embeddedness represents the classic example of bringing a friend into the business without direct knowledge or experience of his or her competency or dyadic interaction. In this case, maintaining the personal relationship may be more salient than the economic exchange causing the entrepreneur to make inefficient and ineffective economic decisions. If the tie is not competent, then the entrepreneur may attempt to drop the tie from the business network if they can to avoid experiencing the dark side of embeddedness (Coleman, 1988; Dubini & Aldrich, 1991; Granovetter, 1985; Hesterly et al, 1998; Portes & Sensenbrenner, 1993).

Competency Embeddedness

Competency embeddedness is built over a previous history of dyadic interaction. In this situation, a high degree of interaction extent, effort, ease and/or quality exists, the tie provides business value, and the interaction is comfortable and familiar with routines having become known and stabilized. As a result, the entrepreneur is loyal to the dyadic interaction over time. However, the danger is that with this social relationship, moral controls may not have much sway. Competency embeddedness may also develop as a result of a long history of interaction with the same market or arm’s length ties.

Hollow Embeddedness

Hollow embeddedness are built upon social capital alone.  Thus, the entire relationship is founded upon either asymmetry or the recommendation of a third party. This type of embedded tie influences the economic action of the firm either through common network ties or through the sense of obligation is instilled in the relationship. As a result, the entrepreneur may be obligated to remain in a relationship even when preferring otherwise. Thus, hollow embeddedness may provide little perceived business value, does not necessarily engender significant trust and, therefore, is hollow. In addition to the unidimensionally embedded ties, 47% of the embedded network ties exhibited high degrees of two social components and are, thus, bidimensionally embedded. As illustrated in Figure 1, three types of bidimensional embeddedness are possible: functional, isolated and latent.

Functional Embeddedness

Functional embeddedness, demonstrated by 11% of the embedded network ties, across five cases, are built upon dyadic interaction and social capital. Although these ties do not rely upon high degrees of personal relationship, they function very well as a business tie. These relationships clearly demonstrated embeddedness in that the social relationship, built upon the history of dyadic interaction and social capital, influenced the firm’s economic actions. Yet, without the personal relation-ship component, such embeddedness may easily be overlooked in the research.

Isolated Embeddedness

Isolated embeddedness was characterized by high degrees of both personal goodwill and personal economic trust. Although demonstrated by only 5% of the network ties, this type of embeddedness was discussed by all eight cases. Isolated embeddedness demonstrated high levels of loyalty both to the tie and to the interaction, likely given the internal focus of the relationship. However, these ties are not well connected to each other’s networks. Given that isolated embeddedness reflects such an isolated dyad, the low frequency is actually not surprising.

Latent Embeddedness

Latent embeddedness was the most common form of bidimensionally embedded ties (31%) and were found across 7 cases. Latent embeddedness suggests that although the network tie may be perceived to be in the business network, the relationship is actually characterized by every low levels of current dyadic interaction. These ties may have once been more involved in the firm or stand waiting in the wings for potential future involvement. Latent embedded ties had the highest number of family members. This finding reflects the intuitive expectation that entrepreneurs use family and friends in the business network. Yet, while the entrepreneur may be willing to work with the network tie, either as a friend or as “favor,” the competency and value of the tie are yet still unproven.

Full Embeddedness

As illustrated in Figure 1, network ties that were fully embedded in the social relationship demonstrated high degrees of all three social components. Full embeddedness represented the most common type of embedded network ties (44%). These ties clearly demonstrated qualities of personal relationship, dyadic interaction and social capital. Many of these ties were built from the pre-existing network ties of the entrepreneur. The fully embedded tie likely represents the stereotypical perspective of embeddedness.

However, fully embedded ties represented only half of the embedded network ties; thus, the other types of embeddedness represent critical dimensions of this construct (Hite, 1999). They also resulted in trust, relational contracting and the influence of the social relationship upon the economic actions of the firm. Indeed, the variety of social relationships within embedded ties was the impetus for this study. Based on the data, the sources of this variety within embeddedness become more clear as a function of the number of different social components that currently exist within the dyadic relationship. As a result, with more social components, embeddedness increases and the social relationship becomes better positioned to have a greater influence on the economic behavior of the firm.

An overall pattern emerged of the governance of embedded network ties as, indeed, built upon trust (Uzzi, 1996). Indeed, various types of social relationships demonstrated varying types of trust (Coleman, 1988; Hesterly, Jones & Madhok, 1998). In this data, the three main components of the social relationships of embedded network ties, personal relationship, dyadic interaction and social capital, served to support the development of personal goodwill trust, personal economic or competency trust and social trust, respectively (Hesterly et al., 1998; Larson, 1992). The implication is that fully-embedded ties exhibit a balance of all three types of trust, like a three-legged stool, whereas other embedded ties may lack of one or more trust types. Thus, the fully embedded network tie is well aligned to be effectively governed by relational contracting given its protection by the full range of both social and personal trust. Yet, if one or more types of trust are lacking for unidimensionally and bi-dimensionally embedded ties, then other governance measures may need to be put in place. The reliance of emerging entrepreneurial firms solely on the limited trust within non-fully embedded ties as the sole governance mechanism may represent an unreliable safeguard. The emerging entrepreneurial firm will be in a better position to take advantage of both the cost minimizing and value maximizing aspects of embedded network ties (Dyer & Singh, 1998) under conditions of full embeddedness.

The distinctions between types of embeddedness may be crucial to the effective governance of the network relationships of emerging entrepreneurial firms. Building upon and adding to previous research, this study implies that the types of social relationships within embedded network ties may influence the types of trust available (Granovetter, 1985; Hesterly et al., 1998; Jones, Hesterly & Borgatti, 1997; Powell & Smith-Doerr, 1994; Uzzi, 1996).

The goal of the study was to further “unpack the concept [of embeddedness] to discover what components of social organization contribute to the value produced” (Coleman, 1988, p. 101). Theoretically positioned at the confluence of strategic, entrepreneurial and network theory, this study identifies qualities of embedded network ties within emerging entrepreneurial firms. The findings provide a better understanding of embeddedness and facilitate a clearer and more useful construct of embeddedness for future research. Given that different types of embeddedness exist, based upon different combinations of social components, then indeed embedded network ties are not all alike.

The lack of homogeneity within embeddedness suggests that emerging entrepreneurial firms may be well served to identify the social components and types of embeddedness within their network relationships. As a result, firms may be able to strategically manage more effective governance of their embedded ties. The mismatch between governance controls and type of embeddedness may create vulnerabilities for the emerging firm. Thus, this research suggests that the governance mode is effectively chosen through consideration of not only of the characteristics of the transaction (Williamson, 1985), but also the characteristics of the dyadic relationship. These findings may also challenge the notion that relational contracting based upon trust is equally effective, or is the most appropriate governance, for all embedded network ties. Based on this understanding, emerging entrepreneurial firms may be able to better recognize, analyze and manage the embeddedness of their dyadic network ties and better ensure successful firm emergence, growth and performance.

CONTACT: Julie M. Hite, Management Department, David Eccles School of Business, University of Utah, 1645 E. Campus Center Dr., Rm 101, Salt Lake City, UT 84112-9301; (T) 801-585-6754; (F) 801-581-7214; mgtjh@business.utah.edu

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