Network Learning

Network relationships are an important aspect of a firm’s social capital that determine the firm’s ability to create value and achieve economic goals (Tsai 2000). This dissertation defines network learning as the willingness to build strong relationships with parties in the broader environment outside of the firm, such as suppliers, distributors, consultants, universities, and government agencies. Strategic network learning provides a firm with access to a diversity of knowledge (Cohen and Levinthal 1990) that may stimulate the creation of new knowledge within the firm and foster innovation (Tsai 2001). An NPD team is more likely to formulate creative decisions if it has speedy access to timely information; diverse ideas; and critical instrumental, political, and emotional resources from the firm’s

external connections with diverse groups (Ancona and Caldwell 1992; Milliken and Martins 1996). Furthermore, network learning may also reduce innovation uncertainty through communication and information sharing (Kraatz 1998), which may further reduce the occurrence of competency traps.

The direct link between network learning and vision trap. In a direct way, network learning may increase firms’ broad external learning. According to Slater and Narver (1995), the development of long-term, stable relationships (e.g., Glazer 1991; Miles and Snow 1992; Mohr and Spekman 1994; Ruekert, Walker, and Roering 1985) with “learning partners” can lead to information sharing that benefits both partners. Networks of interfirm relationships may provide channels for sharing valuable information, experience, knowledge, connections, and resources (Luo 2003). In this situation, diverse information from outside the firm and its immediate environment may reduce the possibility that firms are overconfident in their existing NPD processes. Rather, firms with strong network learning systems in place will have a strong orientation to the broader environment that keeps them updated with novel ideas and new perspectives in the NPD process.

In addition, broad network learning may empower the firm with a broader NPD vision, because the firm’s conception of what is normal, legitimate, and superior extends beyond its own industry. The diverse sources of information, knowledge, and experience from network partners outside of the firm’s own industry may give firms an opportunity to view more dissimilar alternatives and to be aware of very novel fresh perspectives (Yli- Renko, Autio, and Sapienza 2001), which should provide firms with a less constrained vision. Successful examples of dissimilar NPD activities in other industries provide a strong

motivation to move away from current conventional NPD processes and to experiment different new NPD process.

Thus, I propose the following:

H10a: A firm’s network learning is negatively associated with the level of vision

traps in its NPD processes.

The direct link between network learning and technology trap. There are two main reasons to expect that network learning reduces the occurrence of technology traps. First, when firms experience uncertainty about the likelihood of technical success and its associated costs, they may expand their networks in order to learn about new practices and technologies (Powell, Koput, and Smith-Doerr 1996). Because such network partners may have different

operational resources (e.g., production facilities, technologies, and distribution channels) network learning increases a firm’s ability to discover and access different new technologies (Luo 2003). Second, network learning helps firms to see different new technologies as

legitimate and therefore acceptable to incorporate in NPD efforts. Through diversity in firms’ networks, technical uncertainty is more likely to be controllable (Beckman, Haunschild, and Phillips 2004). Diverse networks with others (e.g., organizations in other industries,

universities, technology labs, outside consultants, suppliers) can help firms maintain or regain legitimacy. These types of network relationships can signal to external constituents that technical uncertainty is being recognized and dealt with, which may reduce the propensity to select familiar and mature technologies in order to alleviate legitimacy concerns of customers and investors in technology-trapped firms.

For these reasons, I expect the following:

H10b: A firm’s network learning is negatively associated with the level of

technology traps in its NPD processes.

The direct link between network learning and routinization trap. There are two main reasons to expect that network learning may also reduce the occurrence of routinization traps. First, the broad external search involved in network learning is more likely to motivate firms to keep their NPD procedures updated and flexible over time. Broad network relationships provide firms with opportunities to share valuable information, experience, knowledge, resources, technology, and operation practices (Luo 2003). Through such network learning, firms may see very different NPD routines that may exist in other industries. This knowledge may motivate firms to experiment with new routines in their NPD process and discourage the kind of formalization that emerges from process inertia in NPD.

Second, the successful examples of different NPD routines that may be available from a broad network of learning partners may increase managers’ willingness to go against industry norms and discount legitimacy threats in their NPD process management. Network learning extends firms’ perceptions of what is normal and legitimate beyond its own industry (Beckman, Haunschild, and Phillips 2004). Network learning provides firms with unusual opportunities to see what others are doing with different NPD processes. When firms want to borrow the most successful NPD routines from their partners in other industries or markets, strong relationships may help firms be more successful in their process technology transfer efforts (Camp 1995). In this situation, managers may have the confidence to go against current industry norms and to experiment with novel NPD routines that competitors may not consider legitimate.

Thus, I expect the following:

H10c: A firm’s network learning is negatively associated with the level of

routinization trap in its NPD processes.

Creating superior customer value is the key objective of MO (Slater and Narver 1995). From this perspective, firms’ ideas concerning how to create superior values are based on knowledge derived from customer and competitor analyses. However, a market-oriented firm should not underestimate the potential contributions of other learning sources, such as suppliers, businesses in different industries, consultants, universities, government agencies, and others that possess knowledge valuable to creating superior customer value (Dickson 1992; Slater and Narver 1995). For example, Vorhies and Morgan (2005) argue that market- oriented firms learning from outside their own industry are less prone to blind spots. Their results show that firms are better off benchmarking marketing capabilities across all firms rather than just focusing on peer firms in their own industries.

As previously argued, because of MO’s focus on the proximate environment of customers and competitors, and internal orientation on interfunctional coordination, MO may not encourage broad external search and can therefore lead to competency traps. In the following section, I propose that network learning plays a moderating role in the link between MO and competency traps. In this moderating role, I suggest that external learning from the wider environment is a complement to MO that provides a broader external

orientation (Slater and Narver 1995). By providing broad external search and diverse external knowledge, network learning may weaken the tendency of market-oriented firms to have a

narrow focus on existing customers, competitors, and cross-functional relationships that facilitate the development of competency traps in the NPD process.

The moderating role of network learning in the link between market orientation and vision trap. In a moderating role, network learning is a valuable complementary asset to MO (Slater and Narver 1995). As argued in previous hypotheses, MO may lead to vision traps because it focuses on what existing customers want and what existing competitors are doing. According to H3a, customer orientation may limit firms’ vision because of existing customers’

preference inertia, the utility of customer opinions as a source of new product ideas, and the stability of existing customer populations. However, network learning may broaden the scope of customer orientation by opening firms to a new and fresh worldview from external

learning partners, such as distributors, suppliers, alliance partners, universities, and others. Broad external search introduces very dissimilar NPD knowledge and different customer populations from external network partners (Powell, Koput, and Smith-Doerr 1996; Yli- Renko, Autio, and Sapienza 2001). This may enable firms to avoid the limiting visions available solely from a customer orientation and motivate firms to seek fresh ideas from outside their proximate market environment (Li and Rowley 2002; Nerkar and Roberts 2004). Therefore, when a firm has a high level of network learning, novel and diverse knowledge from network partners is likely to weaken the relationship between MO and vision traps.

Similarly, as argued in H4a, a competitor orientation may limit firms’ NPD vision by

promoting imitative learning from competitors. However, network learning emphasizes a focus beyond competitors in the industry, thereby broadening external learning and widening

the conception of sources of legitimacy to those outside a firm’s own industry. This external orientation may effectively reduce competitor-oriented firms’ imitative learning behavior (Vorhies and Morgan 2005) and encourage them to experiment with new NPD approaches from outside the industry. Thus, network learning may weaken the relationship between competitor orientation and vision traps.

According to H5a, interfunctional coordination may limit firms’ vision by fostering

conformity, groupthink, and narrow internal orientation. However, network learning brings an external orientation beyond interdepartmental coordination and promotes broad external search in organizational learning. Furthermore, exemplars in other industries of how to smooth interdepartmental communication in challenging projects may also help firms with a focus on interfunctional coordination overcome the problems of conformity and groupthink. Therefore, network learning may weaken the link between interfunctional coordination and vision traps.

Thus, I argue:

H11a: A firm’s network learning weakens the positive relationship between its

MO and vision traps in its NPD processes.

The moderating role of network learning in the link between market orientation and

technology trap. In high network-learning firms, MO is less likely to create technology traps. According to H3b, a customer orientation may lead to technology traps because of customers’

limited technology knowledge and preferences for existing technologies (Adner 2002; Im and Workman 2004). Customer-oriented firms tend to make technology-selection decisions on the basis of existing customers’ feedback (e.g., Christensen, Suarez, and Utterback 1998).

However, network learning may supplement customer feedback and thus broaden the firms’ NPD vision by providing relevant information regarding technologies used and advocated by external learning partners and the preferences of their partners’ customers in other industries (Vorhies and Morgan 2005). This information and knowledge from network learning may reduce customer-oriented firms’ uncertainty regarding whether its customers would accept a new technology and provide insights regarding how customers may best be educated about a different new technology if it is adopted. In this situation, a customer-oriented firm is less likely to stick with technologies just because they are familiar and more certain for existing customers.

Similarly, as argued in H4b, a competitor orientation may also lead to technology traps

because it encourages the imitation of competitors’ technologies (Lukas and Ferrell 2000; Zahra, Nash, and Bickford 1995). However, network learning may weaken this link by broadening the firm’s knowledge of available and emerging technologies and enabling the firm to see these “in action” outside of the proximate industry environment. Network

learning may also enable competitor-oriented firms to see different new technologies in other industries as legitimate, enabling them to control the uncertainty associated with new and emerging technologies (Beckman, Haunschild, and Phillips 2004). Therefore, network learning may weaken the relationship between competitor orientation and technology traps.

According to H5b, a focus on interfunctional coordination may also lead to technology

traps, because the pressures to avoid sources of conflict encourages the use of familiar technologies in NPD (Argyris 1982; Carmel 1995; Crawford 1992; Lukas and Ferrell 2000). However, network learning may provide opportunities for firms to discover very different new NPD routines that can be successfully implemented by cross-functional teams in other

industries. Such successful examples from broad external search may decrease managers’ fear of legitimacy threats and increase managers’ confidence to go against industry norms in NPD.

For these reasons I expect the following:

H11b: A firm’s network learning weakens the positive relationship between its

MO and technology traps in its NPD processes.

The moderating role of network learning in the link between market orientation and routinization trap. In firms with strong learning networks, MO is also less likely to create routinization traps. As argued in H3c, customer orientation may lead to routinization traps

because of customers’ preference stability, trade-offs between cost and innovation, and relatively stable customer populations. However, network learning may weaken or break this link. Network learning introduces a broader external search and an orientation beyond the narrow focus of existing customers (Slater and Narver 1995). Broad network relationships may provide firms with opportunities to see different new NPD routines in other industries, how these are accepted by their partners’ customers, and whether novel NPD routines produce benefits above and beyond their costs for their network partners. Successful

examples may increase firms’ confidence to abandon industry norms and to experiment with new routines in their NPD process (Camp 1995).

According to H4c, a competitor orientation may also lead to routinization traps

because of its strong cost and efficiency focus, tendency toward imitative learning from competitors, and prioritization of threats to legitimacy. However, network learning may reduce or even sever this link. Network learning may broaden competitor-oriented firms’

narrow competitor focus and supplement it with a broader external orientation (Slater and Narver 1995). Network partners’ experiences with different new NPD routines may help the firm reduce any uncertainty toward the potential cost and benefit of experimentation in NPD efforts (Luo 2003). Successful examples of different new NPD routines in other industries may discourage the competitor-mimetic learning tendency in competitor-oriented firms. Furthermore, a wider conception of legitimacy and industry norms may motivate firms to follow the steps of partners outside the proximate industry environment and enable a firm to introduce radical new NPD routines to the industry.

According to H5c, a strong focus on interfunctional coordination may also lead to

routinization traps because of its internal orientation and pressures to avoid sources of conflict that encourage the use of familiar NPD routines. However, network learning

supplements the internal orientation of a focus on interfunctional coordination with a broader external orientation (Yli-Renko, Autio, and Sapienza 2001). Network partners may provide good examples of how cross-functional teams can be effectively coordinated in firms using different NPD processes. This kind of partnership help firms codify the coordination process of how cross-functional teams in successful learning partners in other industries reduce groupthink and enhance communication in challenging new NPD projects. In this situation, firms with a strong focus on interfunctional coordination are more likely to keep their NPD procedures updated and flexible over time.

For these reasons, I argue:

H11c: A firm’s network learning weakens the positive relationship between MO

and routinization traps in its NPD processes.