Abstract—Research on open innovation has, in the main, focused on large, high technology firms and tended to adopt an organization-centric approach in examining external links. In contrast, this paper uses social network analysis and network centrality to explore open innovation among a cluster of 33 low technology SME manufacturers in Ireland. Adopting a mixed-methods approach this research looks beyond the immediate external links that SMEs form with external organizations and explores the wider network in which such firms are located, their position in these networks and the impact of such positioning on open innovation. This paper reports a generally positive relationship between networking activity and innovation performance. Within the context of the low technology cluster it is apparent that the positioning of a firm within the network may serve to enhance or impede its innovation activity in product development. Despite factors such as fears of appropriation limiting the degree of knowledge and resource exchange within the network, this evidence suggests that those firms occupying central network positions and thus connected to a greater number of other members of the cluster, typically demonstrate greater degrees of innovation activity. Finally, as a means of elucidating the factors that may influence a firm’s position the paper illustrates that firm size, absorptive capacity and managerial orientation serve as antecedents of network position.

Index Terms— Network Centrality, Open Innovation, Social Network Analysis, SME’s, Low Technology Sector

I. INTRODUCTION

HE current innovation landscape has changed with the innovation process becoming increasingly complex,

multi-directional and iterative, involving multiple actors [1], [2], [3], [4]. Researchers have increasingly highlighted the potential benefit of sourcing knowledge across the boundaries of the firm with sustained attention given to open innovation (OI) [5]. Indeed, the OI model has flourished and it represents a framework for understanding industrial innovation [6], [7], [8]. As defined by Chesbrough and Bogers [9] open innovation is, “a distributed innovation process that relies on purposively managed knowledge flows across organizational boundaries, using pecuniary and nonpecuniary mechanisms in line with the organization’s business model to guide and motivate knowledge sharing”. Within the OI framework knowledge flows can be inbound, outbound [7] or a coupled mode encompassing both inbound and outbound knowledge flows [11]. Piller and West [12] extended the coupled mode by uncovering a second, interactive coupled model of OI that entails the cooperative efforts of two organizations that co-

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develop new knowledge, products or processes outside the boundaries of each organization. This has widened the scope of OI research beyond the interaction between two firms to collaborations with other stakeholders and networks. While much of this OI research has emanated from explorations of bilateral collaborations [6], less attention has focused on the network structure as a whole [13].

As a result, West et al., [13] argues that more research is needed to develop the conception of coupled OI and to show how OI practices are similar (or different) in network settings. In particular, an examination of how OI is practiced by firms working within various network forms could benefit from advanced tools for network analysis that make it possible to show how social capital – at different level of analysis – can shape OI [13]. This was further reinforced by West and Bogers [7] who noted that beyond the computing and communications industries there is a dearth of OI research on specific network forms. Additionally, several scholars have agreed that OI research has primarily concentrated on large high-technology multinationals, largely ignoring open innovation practices within low technology small and medium-sized enterprises (SMEs) [1], [8], [10], [14]. Lee et al. [8] argue that OI exists in smaller organizations and that SMEs use non-internal sources of knowledge for innovation to a greater extent than large firms. OI practices such as external knowledge sourcing and cooperation may enhance and extend SME’s resources and technological competences [15]. Despite the potential benefits of cooperation, the evidence suggests that SMEs are less likely than larger firms to engage in inter-firm cooperation for innovation [16]. The reasons proposed for this include a greater inability to identify appropriate partners and a sub-optimal knowledge base with which to absorb external knowledge [17], [18].

While high technology industries are assumed by many as the main fora for learning and sources of economic growth [19] low technology industries continue to play important roles in world trade and employment, dominating the economies of highly developed as well as developing nations [20], [21]. Moreover, there are numerous examples of sectors and companies that have been successfully innovating low-tech products in high-tech countries of the European Union [22]. The character and activities of low-tech industries are profoundly changing as they become increasingly knowledge intensive [23]. While some low-tech firms increasingly move into technology intensive product categories [24], the majority of low-tech firms rely on a predominantly synthetic knowledge base that allows them to develop customer specific

Network Centrality and Open Innovation: A Social Network Analysis of an SME

Manufacturing ClusterJudith Woods, Brendan Galbraith, and Nola Hewitt-Dundas

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solutions and continuously improve products and production processes [23]. Thus, innovation processes and knowledge production in manufacturing are much more complex than suggested by the classic division into high, medium and low technology industries [23].

With low technology industries largely ignored by innovation policy and innovation research [21], [22], [25] and the current volume of work overly weighted towards the high technology sector, crucial aspects of innovation taking place in lower technology settings have been somewhat ignored [25], [23]. Consequently, the paucity of existing, internal innovation capability creates an imperative for an open and networked approach to help acquire and accumulate external knowledge, and thus counter this technology and innovation deficit.

This paper contributes to the aforementioned gaps by focusing on the interactive and networked, nature of OI within the context of a clustered, low technology manufacturing SMEs.

The main concern of this paper is to examine OI within the confines of a low-technology SME manufacturing cluster. More specifically, two key questions are addressed. Firstly, what factors may serve to influence the network position low-technology SMEs occupy with a network structure? Secondly, is there a relationship between the structural positioning of such low technology SMEs in a network and their innovation performance and does this matter within an OI context?

The remainder of this paper is structured as follows. Section 2 discusses OI, focusing on the importance of network structure for innovation and how the network position of a firm may be influenced by factors such as structural characteristics and absorptive capacity. In section 3 the methodology employed and the approach to data analysis is outlined. Section 4 presents and discusses the key findings, profiling the network positions of the individual SMEs, the factors contributing to their network position and finally the extent to which such position influences innovation performance. The paper is then concluded, highlighting implications as well as avenues for further research.

II. OUR ANALYTICAL FRAMING

The importance and benefits of networking in terms of improved innovation performance have been well documented [26], [27], [8]. Organizational scholars have shown how innovators rely on social relationships to tap into diverse networks and communities as a means of building on the ideas of others [28], [29]. The importance of a firm’s network position in providing opportunities for knowledge accumulation through brokerage and by knowledge exchange has been well documented [30]. There is synergy between networking and network positioning (i.e. access to external knowledge, new ideas etc.) and the open innovation process. The basic premise of open innovation is opening up the innovation process [31]. However, it has been found that internal R&D is a necessary complement to openness for outside ideas and it is unclear whether the outside ideas can be

a substitute for internal R&D [32]. Hence, absorptive capacity [33] – “the ability of innovating firms to assimilate and replicate new knowledge gained from external sources” – is often associated with OI. In order to benefit from external knowledge and engage in the knowledge acquisition process, firms first have to develop their absorptive capacity [33], [34]. The OI process relies on purposively managed knowledge flows across organizational boundaries, using pecuniary and nonpecuniary mechanisms in line with the organization’s business model to guide and motivate knowledge sharing [9].

With an acute awareness of the potential outcomes and benefits that firms experience as a result of OI and networking, much of this research has been based on explorations of bilateral collaborations. Consequently, the OI literature lacks insights into how the construct works within networks as a whole [7]. For example, how does the structure of a network and the relative positioning of member firms impact upon their capacity for open innovation and what factors serve to influence the positions that firms occupy within these network structures? If the OI literature is to be developed and our understanding of this concept improved (particularly the coupled mode) the importance of network structure within an OI context needs to be further investigated. Additionally, with prior work limited in scope and focusing on OI within specific settings [6,7], explorations of the model within different contexts such as SMEs and low rather than high technology firms will serve to further enhance our understanding and inform the paradigm overall.

According to the resource-based view (RBV) of the firm a firm’s innovation performance and ability to successfully compete and survive within its external environment will depend on its resources and capabilities [35], [36]. Whilst much of the research within the field of innovation has adopted a resource-based perspective one significant limitation of this approach is that the RBV focuses its attention on those resources and capabilities that are present within the firm [37], [38], [39]. Whilst internal resources and capabilities are important for innovation the external resources available to a firm are also important and merit consideration in the exploration of firm innovation [39], [37], [40]. Social Network Theory offers a framework that takes into account the external resources available to a firm via the network in which it exists. A central tenant of social network theory is the view that structural properties of a network influence the behavior of those present within the network [37], [39], [41], [42] with firm outcomes and future performance depending, in part, on its network position [42], [43].

With OI focusing on the importance of both internal and external sources of information, this research combines the RBV of the firm and social network theory. The integration of these theoretical perspectives provides a framework that considers the importance of internal resources as well as external relationships and the structure of these in relation to a firm’s innovation activity within a cluster of low-technology SMEs [39], [40].

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A. Determinants of Network Position

As previously stated, Social Network Theory espouses that firm outcomes and future performance depend, in part, on the network position it occupies. Thus, it could be inferred that if a firms’ innovation performance may be improved or hampered as a consequence of its position within a given network, knowledge of the factors that may influence such positioning is invaluable. While specific research considering network structure and position is scarce in the field of open innovation, a review of the literature relating to inter-firm networking more generally and studies in the field of social network theory offer some useful insights. Drawing from this body of work it is possible to address the paper’s first research question and develop a series of propositions in relation to the factors influencing the network position of an SME.

As expected, upon review of such literature it emerges that firm specific characteristics such as size and age are typically considered as variables that may serve to impact a firm’s network position [44], [45], [46]. Explored largely as a control variable in existing empirical research, findings suggest that larger firms tend to assume the most central network positions [45], [47]. For instance, Boschma and ter Wal [44] found evidence demonstrating a significant relationship between firm size and network position with larger firms being significantly more networked than their smaller counterparts. In terms of why this may be the case, Hanna and Walsh [48] propose that smaller firms may opt out of developing network relationships in favor of safe-guarding their limited stock of knowledge, skills, and expertise. In addition, smaller firms also demonstrate a greater inability to identify appropriate partners with whom beneficial relations may be established. Coupled with a sub-optimum knowledge base with which to absorb external knowledge smaller firms are therefore less likely to develop network relations and thus assume central network positions than their larger counterparts [17], [18].

Despite evidence suggesting a positive relationship consensus is yet to be established with studies failing to find any significant relationship between firm size and network centrality [49] or indeed an inverse relationship with smaller firms more likely to occupy more central positions than larger entities [50]. In explanation of the latter it is proposed that with a greater stock of resources and knowledge, larger firms may be less motivated to network than smaller firms who are driven to cooperate by the need to gain access to the assets they require [50].

Notwithstanding such inconsistencies in the empirical evidence the majority of the findings point to a positive relationship between firm size and network centrality thus leading to our first proposition:

Proposition 1: Larger SMEs will occupy a more central position within the cluster network.

As well as firm size, firm age or vintage is also argued to be of influence [51]. With age potentially affecting the experience of the SME as well as its awareness of the network and the opportunities for relationship development, some empirical evidence points to a positive relationship between firm age and network centrality [51], [52], [53], [55]. Furthermore, with older firms typically in possession of greater financial and human capital resources it is proposed that these firms are more inclined to collaborate and engage in the exchange of knowledge and information than their younger counterparts [53] thus resulting in their occupation of central network positions. Finally, with tenure, older firms may find it easier to establish more relationships and thus occupy a central network position as potential network partners are already aware of them and familiar with their activities [54], [55]. As Park and Luo [46] state “Young organisations are subject to the liability of newness...and links with key actors in the environment are irregular. It takes time for an organization to acquire institutional legitimacy among its members and to become valued in its own right”.

Once again, however, the evidence remains inconclusive with regard to the relationship between firm age and network centrality with suggestions that older firms might in fact be less likely to form inter-firm relationships [56]. Given the problems associated with youth or the “liability of newness” it may be the case that younger SMEs are motivated to adopt a “more proactive and aggressive” [46] approach to collaboration as a means of securing access to resources and knowledge required for the firms survival and growth. As a consequence of this more proactive and aggressive approach newer firms may therefore establish a greater number of external relationships and thus occupy a more central position within their network [46]. Taking the above into consideration and with the balance of evidence falling to a largely to a positive relationship between firm age and network centrality a similar relationship is proposed here:

Proposition 2: Older SMEs will occupy a more central position within the cluster network.

Defined as the firm’s ability “to recognize the value of new, external knowledge, assimilate it, and apply it to commercial ends” [33] absorptive capacity may also be regarded as an important variable in the exploration of the factors affecting network position [57], [58], [59], [55]. With absorptive capacity reflecting the human capital resources and in particular the stock of accumulated knowledge within the firm, it is likely that it will also influence a firm’s ability to recognise and respond to opportunities for linkage formation and thus impact the network position its occupies [33], [59] and [55]. More specifically, the greater a firm’s absorptive capacity, the better its ability to identify and develop a larger number of beneficial relations [57], [59] and consequently the more central its network position is likely to be. Conversely, for firms with particularly low levels of absorptive capacity their limited knowledge base may result in their occupation of

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more peripheral or isolated positions within a network. This may, on the one hand, be as a result of deficiencies in their capacity to identify, acquire and exploit the knowledge of other firms. Alternatively, with potentially little to offer network partners, low levels of absorptive capacity may render such firms less desirable and thus result in their occupation of more isolated network positions [59].

Despite scant empirical evidence delineating the impact of absorptive capacity on network position, Cantner and Joel [55], Weterings and Ponds [60] and Walker [58] find some evidence identifying a positive relationship. With research yet to fully explore and thus ascertain the influence of absorptive capacity on network position the current, albeit limited, evidence forms the basis of the following proposition:

Proposition 3: SMEs with greater absorptive capacity will occupy a more central position within the cluster network.

Finally, in addition to firm specific characteristics and absorptive capacity, the network strategy of the firm reflected in the manager’s orientation towards networking and collaboration has received some limited attention as a potential antecedent of network position. Empirical evidence reveals that owner-managers differ with regard to the importance placed on networking activities [61] with some regarding it as being of central importance to the firm and its success and others ascribing more importance to other features of the firms operation. This divergence is also perhaps more pronounced in respect to the importance of horizontal networking and the development of relationships with potential competitors [27]. It therefore stands to reason that the network position occupied by an SME is likely to be affected by the strategic importance the owner-manager places on networking and the development of network relationships [52]. As evidenced by Gilmore et al. [61] owner-managers that regard networking as strategically important for the firm develop a greater number of relations within a network and thus may be more likely to occupy central positions within the network structure [61], [52]. Similarly, Lee and Tsang [62] found that entrepreneurs who adopted a more independent and self-reliant approach i.e. that placed less strategic significance on external networking, were less likely to form network relationships and thus occupy a more peripheral network position.

As was the case with absorptive capacity the volume of empirical evidence in this area is scant and it is therefore difficult to categorically delineate the influence of managerial orientation on network centrality. That being said of the limited research that has taken it into consideration it is suggested that a positive relationship exists between the two [44], [61], leading to our fourth and final proposition of this section:

Proposition 4: SMEs with owner-managers that identify networking as strategically important will occupy a more central position within the cluster network.

B. Network Centrality and its Effect on Innovation

The importance and benefits of networking in terms of improved innovation performance have been well documented [26], [27], [8]. Despite focusing on the activities of the large enterprise the OI literature (alongside the innovation management and networking literature more generally) alludes to the benefit of networking and a more open approach to innovation for firms that are much smaller in size. The following section examines this literature and, seeking to address the second research question, formulates a proposition in relation to the association between the structural positioning of low technology SMEs in a network and their innovation performance within an OI context.

For SMEs in particular belonging to a network of other firms may generate externalities that help to overcome barriers to innovation. One of the most cited barriers to innovation is access to resources [35], [63]. In order to innovate firms require access to resources such as machinery and materials, as well as technological knowledge and information [64]. Inadequate resource access often inhibits firm innovation, especially within SME’s [35]. OI and Network theory suggests that firms can potentially improve their innovation performance by tapping into resources available outside of the firm through networking and inter-firm collaboration. Empirical research clearly indicates that many firms are often motivated to participate in networks as a means of overcoming this barrier and obtaining access to resources needed for innovation [26], [57], [1], [8]. Exploring the key motives for firms implementing OI practices, Van de Vrande et al. [1] state that “enterprises may engage in collaboration to acquire missing knowledge, complementary resources or finance, to spread risks, to enlarge its social networks, or to reduce costs”. Whilst OI practices can help firms overcome resource constraints, network theory informs us that a firm’s ability to access such external resources is highly contingent upon the position that they assume within the network [57], [65], an issue yet to be fully explored within the OI framework [26].

Network theory offers a range of mechanisms through which the network structure and relative positioning of a firm might be described [61], [67]. In relation to the latter one of the most commonly applied measures is that of network centrality, a construct that describes a firm’s position on the basis of how central / core or peripheral they appear to be in relation to the network as a whole. The underlining premise is that those firms occupying a central network position have better access to external resources and knowledge than firms in more peripheral positions [57], [68], [64]. In other words, firms with a high degree of network centrality are connected to a greater number of other firms, each possessing their own set of resources and capabilities that could be tapped into [57], [64]. Relating this to OI, firms which are more central within their networks possess greater access to external resources and knowledge that may be combined with internal resources to the benefit of firm innovation performance [4]. As a result, such centrally positioned firms are likely to demonstrate a

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higher level of innovation activity than firms assuming more peripheral network positions [42], [57]. For instance, Boschma and ter Wal [44] find, without exception, that firms in the center of a network structure excel in innovation as opposed to those more isolated firms. Similarly, Sheun and Peng [69] found evidence of a positive association between centrality and innovation with such firms benefitting from greater exposure and access to the range of knowledge that may be required for innovation.

As well as access to resources, the innovation efforts of SMEs may also be hampered as a consequence of the inability to recognize and respond to opportunities for innovation development [57]. With often limited internal knowledge bases the absorptive capacity of SMEs may be often be restricted, constraining their ability to monitor their external environment and recognize opportunities for innovation. OI practices such as external networking can assist SMEs in overcoming this barrier and enhance organizational learning [18]. As the firm interacts and exchanges knowledge with other firms in the network, the identification of innovation opportunities may become easier, with network relations helping the firm keep an eye on the market and responding accordingly [70]. Consequently, the more central the SME’s position in the network, the greater the number of other firms to whom the SME is connected thus placing it in a favorable position to recognize and respond to new market opportunities in the form of innovation activity.

Based on these arguments it is proposed that a central network position can enable the SME to overcome some of its barriers to innovation, offering access to much needed resources and exposing them to opportunities for development. With such barriers eased these firms are more likely to innovate and so it is proposed:

Proposition 5: Increased network centrality will be positively associated with increased innovation activity at the level of the SME.

III. METHODOLOGY

Seeking to move away from bilateral examinations of OI and a preponderance with the large high technology enterprise [6] this paper is centered on the network activities of SMEs within a low technology manufacturing cluster located in rural Ireland.

The cluster itself is located in the border region of Monaghan in the North-West of Ireland and, following OECD categorizations, would be regarded as a mature low technology cluster characterized by a low level of research and development expenses [71], [72]. In total there are approximately 33 furniture manufacturing SME’s currently operating within the cluster and providing direct employment to around 350 people. The activities of these firms can largely be disaggregated into hard furnishings such as bedroom and dining room furniture, soft furnishings such as upholstery, and fitted furniture such as kitchen and bar furniture [73], [74]. In

terms of performance, at its peak, after the two largest cities (Dublin and Cork) Monaghan’s wooden furniture industry accounted for the largest concentration of timber and wooden furniture firms throughout Ireland up until 2005 [74], [75] and [76]. Adopting a mixed methods approach, the paper sought to develop a comprehensive understanding of OI and the role of network structure and position within a cluster of low technology SMEs. The decision to adopt a mixed methodological approach was motivated by the fact that, by themselves, traditional qualitative and quantitative methods of research inadequately capture the degree of complexity associated with OI [77; 78 and 79]. Proponents of mixed method research argue that the adoption of such an approach allows for the creation of a more reliable set of findings, validating results by using different methods to generate the same conclusions (79; 80; 81 and 82). Embracing such benefits this research adopted a sequential explanatory strategy [82] combining quantitative and qualitative research methods to comprehensively address the research questions posed. More specifically a two staged approach was adopted involving an initial quantitative survey of cluster members followed by qualitative semi-structured interviews with selected SMEs and in-depth interviews with key informants (both operating within and in support of the cluster) [82]. The details of each of these stages of research will now briefly be outlined.

As a means of building a picture of the overall structure of the furniture cluster and acquiring details of the SMEs therein a 26-item survey was distributed to all 33 SMEs. The questions posed fell largely into 2 sections with the first seeking to gather information on demographics, market performance and innovation and the second section focusing on the relational aspects of the firm. Using a roster of all SMEs within the cluster, firms were asked to indicate their degree of formal and informal communication with each of the listed SMEs, thus generating a picture of the collaboration and interaction present in the cluster context. In research exploring horizontal relationships among potentially competing firms, formal networking is understood as the deliberate exchange of resources and business-related knowledge among firms for the purpose of firm development [83 and 84]. On the other hand, informal networking is more social in nature and may include personal exchange and interaction with the potential disclosure of very general information and ideas of minor importance [84].

Securing a response rate of 70% it was possible to ensure that the relational data and visualizations of the network structure appropriately reflected reality with such response rates identified as acceptable for the purposes of this investigation [85], [86], [87] and [88]. Non-response bias was also conducted through non-response testing. These tests found no significant relationship between respondents and non-respondents based on firm age; size; and innovation activity.

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The relational data was analyzed using the social network analysis software UCINET 6 [89]. The software package is designed for the analysis of network data through a variety of methods with measures of network centrality and network cohesion forming the focus of this research. Network centrality was calculated using the degree centrality network measure, a simple count of the total number of direct relations maintained by each of the SMEs within the network. Network cohesion was explored through the network density measure which focusses on the network as a whole and calculates the extent to which all possible relations are actually present within the network structure [66], [90]. The greater the network density the more connected and cohesive the network is overall. Integrated within the software is a graphical visualization tool called NetDraw which is used to create diagrams of networks using datasets imported from UCINET6. NetDraw was used in this investigation to graphically portray the formal and informal relations within the furniture cluster (Figure 1 and 2).

Having developed a picture of the overall network structure and the relative positioning of the SMEs therein, qualitative follow up interviews were used to explore the data in more detail and obtain in-depth insights into the research questions being considered [82]. During this second stage of the research a variety of categories were developed to classify and identify a purposive sample of firms for further investigation. The categories developed were as follows:

Firms occupying central / peripheral network positions and demonstrating high levels of innovation activity

Firms occupying central / peripheral networking positions and demonstrating low levels of innovation activity

In total 11 SMEs fell into one of the aforementioned categories. All 11 were approached for interview with 8 agreeing to participate. In each case the owner-manager was interviewed with discussions lasting between 60 and 80 minutes.

The semi-structured interviews facilitated further exploration of the quantitative data and provided rich and detailed information relating to OI and the role of network structure and position for firms operating within the furniture cluster [81]. Furthermore, unlike the surveys, the semi-structured interviews enabled the researcher to be more flexible and probe into issues that emerged as significant during the course of the interview [81].

Table 1 about here

IV. FINDINGS AND IMPLICATIONS

A. Network Structure of the SME Manufacturing Cluster

Figures 1 and 2 present an overview of the formal and informal network structures present within the furniture

cluster. It is apparent from these figures that most of the firms engage in some degree of formal and informal interaction within the network. The overall density of the formal network is 0.173, indicating that 17.3% of the possible direct network ties are effective. With a slightly lower density score of 0.152, 15.2% of the possible direct network ties that could be present within the informal network structure have been realized.

Comparing this to similar studies the density scores for the furniture cluster are relatively low, suggesting that both the formal and informal network structures are sparse with SMEs only loosely connected to one another [41], [91], and [39]. As well as network density, the centrality scores for each of the SMEs were calculated and are presented in Table 2. Upon review it is apparent that SME 129, 126, and 127 assume the three most central positions within the formal network. With no direct formal ties with any other firm, SME 115 and 119 assume the most peripheral positions. In the case of the informal network firm 120 and 129 occupy the most central positions followed by firm 111.

B. Determinants of Network Position

Firm Size

The objective of this paper was to develop the open innovation literature by exploring the importance of network structure and the relationship between network position and firm innovation among SME’s within a low technology cluster network. Considering the factors influencing the network position adopted by a firm the paper proposed that larger SMEs would assume the most central positions within the furniture cluster. Looking at the group as a whole statistical testing finds evidence of a weakly significant correlation between firm size and network centrality (Pearson correlation tests: r=0.302 [formal], p=.099 and r=0.309 [informal], p=.091). Exploring this in greater detail and focusing on those firms occupying the most central positions within the formal and informal networks, there is a degree of inconsistency in terms of the relationship between firm size and network centrality. For example, occupying one of the most central positions within the informal communication network SME 120 is relatively large in size with 15 members of staff. Similarly, within the formal network, SMEs 126 and 127 are central and employ 15 and 10 members of staff respectively. However, occupying the most central position within the formal and informal network, SME 129 would be regarded as relatively small with only 5 members of staff.

Whilst this appears to run counter to our expectations, documentary analysis and discussions with key informants indicate that SME 129 was once one of the largest furniture manufacturers within the region [74]. However, faced with increasing pressure from cheaper imports, economic decline, and the collapse of furniture retail sales in Ireland, SME 129 was forced to scale back in size, with more than 30 members of staff being made redundant. Once one of the largest furniture manufacturers in Monaghan, it is possible that the large number of network links possessed by SME 129 were

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developed at a time when it was much greater in size. As time has passed circumstances have forced SME 129 to downsize but the previously established network links remain potentially explaining the central network positions occupied by such a small firm.

Looking at the other end of the size spectrum the findings are more in line with our expectations with relatively smaller SMEs typically more isolated within each of the networks examined. In explanation, the data indicates that deficiencies in human and financial capital resources make it more difficult for these significantly smaller SMEs to engage in networking thus potentially explaining their occupation of more peripheral network positions. In this instance it is not possible to identify an unequivocal relationship between firm size and network centrality, but the data does suggest some positive association between the two.

Firm Age

Turning our attention to the second proposition it was suggested that, with tenure and the availability of more resources, older SMEs would occupy the most central network positions [52], [55]. Statistical testing found some evidence in support of this proposition, identifying a positive correlation between firm age and network centrality (Pearson correlation tests: r=0.397 [formal] and r=0.458 [informal], p<0.05). The average age of an SME within the furniture cluster was twenty-seven years and despite the observation of a generally positive relationship between age and centrality, closer examination of the data finds that this relationship is not unambiguous with some of the most central network positions also occupied by relatively younger firms. For example, having been in operation for 69 years SME 129 occupies one of the most central positions within the formal and informal networks. Similarly, firm 127 also maintains one of the most central positions within the formal network despite having been in operation for only 9 years. Upon review of the interview data it emerges that, as Park and Luo [46] suggests, firm 127 is motivated to adopt a more proactive and aggressive approach to networking as a means of overcoming the problems associated with youth. For example, by establishing an official Furniture Association, the owner-manager of firm 127 recalls how they were able to gain access to resources and information required for the firm’s development, assets they would not have been able to access in isolation.

Upon closer analysis of the informal network our expectations appear to be more aligned with the findings with older SMEs typically assuming those more central network positions. This is perhaps not surprising as it may stand to reason that the longer the SME has been established the more time it will have had to develop friendships and informal and ties with other members of the network. Such a suggestion is confirmed by SME 124 who, having been in operation for almost 50 years, describe how tenure has allowed to build up a plethora of informal and social relations with many SMEs within the furniture cluster:

“You build it over the years like, we all know each other. We would be chatting to all the other manufacturers quite a bit...It’s a friendship thing really” [SME no.124]

These findings imply that the activities associated with formal interactions differ from that of informal with the latter potentially more associated with social ties and influenced by longevity in the cluster. In contrast, formal ties appear to be less dependent on longevity in the cluster and, rather than ‘socially’ focused, are more ‘business’ focused or strategic in nature.

Absorptive Capacity

With absorptive capacity likely to influence a firm’s ability to recognise and respond to opportunities for linkage formation it was proposed that firms with greater absorptive capacity would occupy a more central network position [44], [59], [55]. Looking at the issue of absorptive capacity and measuring it in terms of the highest qualification held by staff, the quantitative data fails to support the proposition that absorptive capacity is positively related to network centrality. Conducting an independent samples t-test the results suggest that absorptive capacity does not have an effect on network centrality within either of the formal or informal networks examined. However, having adopted a mixed methods approach it was possible to delve deeper into this issue and explore the relationship via the qualitative accounts gathered from interviews with participating firms. Upon review of such data a more positive association was observed with evidence that many of the SMEs occupying central positions within both the formal and informal networks had knowledge bases that were particularly strong. Due to the nature of the work conducted, in-house and on-the-job training appears to be the preferred method of developing the skills and capabilities of the human capital employed within the SMEs in question. Taking this into consideration and assessing absorptive capacity in terms of workforce competence rather than formal training and education, a more positive relationship between absorptive capacity and network centrality is observed.

For instance, occupying a central position within the formal communication network, firm 126 provided an example of how the firms high levels of absorptive capacity helped develop beneficial relationships with other firms within the network. Using his skills and experience within the furniture industry, one employee recognised and responded to a commercial and networking opportunity. With an increasing amount of fabric going to waste and an awareness of other manufacturers operating within the Monaghan region, the employee approached the owner-manager and suggested the formation of a relationship with another competing upholsterer (firm 129) to reduce such wastage. As the owner-manager recalled:

“One lad came to me and said would you not think about working with [SME 129] and doing a simple fireside chair where we can use up that leftover fabric?... from this I then

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made contact with the owner of [firm 129] and it has resulted in a potential business opportunity” [SME no.126).

Focussing on the quantitative data, statistical analysis found no evidence of a relationship between absorptive capacity and network centrality in either of the networks examined. Whilst this may be the case, questions may be raised relating to the appropriateness of the metrics commonly used to measure absorptive capacity and their suitability in all settings. The evidence presented here suggests that, in some contexts, a high proportion of the training and education received by employees is on the job. As a result, measuring absorptive capacity in terms of educational attainment may fail to fully capture the degree of knowledge, skill and expertise present within a firm. With statistical testing finding no significant relationship between absorptive capacity (measured in terms of the highest qualification possessed by employees) and network centrality this may affirm the inappropriateness of traditional measures and the need to adopt a different approach within certain sectoral contexts.

Managerial Orientation

In terms of the factors that might explain the network position assumed by an SME, the last proposition was concerned with the orientation of the owner-manager. It was proposed that those SMEs with owner-managers that regard networking as strategically important are more likely to develop a greater number of relations within a network [92] and thus occupy a more central network position. An analysis of the qualitative data indicates that many of the owner-managers of firms located in the most central network positions regarded networking as being of strategic importance for the firm and its innovation performance. Perhaps, the most notable evidence comes from an interview with the owner-manager of SME 127. As mentioned earlier, as a relatively young firm, SME 127 adopts a very proactive approach to networking in order to overcome the problems associated with youth. Occupying one of the top four most central positions within the formal network, the owner-manager of SME 127 places great emphasis on networking externally and more specifically with other members of the furniture cluster. Appreciating the benefits that such networking can provide, the owner-manager created a formal association in Monaghan in an attempt to encourage interaction and collaboration among the furniture manufacturers within the region. In this instance it seems as though the strategic importance placed on networking by the owner-manager played a significant role in this firm’s occupation of a central network position. As the owner-manager stated:

“I started up the official Furniture Association and maybe for that reason I would be regarded highly. The Association was a very good thing for having chats with your fellow colleagues, sharing customer and supplier information” [SME no.127].

Further confirming the positive correlation between managerial orientation and network centrality, it is apparent that those SMEs occupying the more peripheral network

positions do not appear to place strategic importance on external networking, failing to recognise its importance for their firm. For example, as an isolate within the formal network structure and peripheral in the informal network, SME 115 demonstrates a clear reluctance to engage in inter-firm networking and when probed as to why this was the owner-manager stated:

“We would know them, some of them but we would see no reason or benefit to contact them... It’s something that never appealed to me, never felt that I would get any benefit from it.” [SME no.115]

Observing a positive correlation between managerial orientation towards networking and network centrality these results support those of Lee and Tsang [62] and Gilmore et al. [61].

C. Network Centrality and its Effect on Innovation

Analysis of the relational data indicates the presence of a positive relationship between network centrality and firm innovation with the more central actors showing higher levels of innovation activity. Figures 1 and 2 graphically demonstrate this positive association with many of the centrally positioned SMEs demonstrating high levels of innovation success. Despite being informative, analysis of the relational data via social network analysis techniques only provide an indication of a possible relationship between the network centrality and innovation. Turning to the more qualitative data a more in-depth exploration of this relationship is possible [81].

Access to resources and information

As previously outlined, enhanced access to resources and knowledge is often listed as a factor explaining the relationship between network centrality and innovation activity. Through the interviews it was possible to ascertain to what degree access to external resources and information may explain higher levels of innovation among central SMEs within the networks. Upon review, it is apparent that those SMEs assuming central positions within the formal and informal networks possess robust access to resources that exist externally, facilitating the combination of such resources with those already in their possession, much to the benefit of innovation performance. For instance, when questioned about resource sharing within the network, SME 124 and 127 both recounted how they would contact follow manufacturers within the network cluster should they need a particular resource such as fabrics or components required for specific product developments.

As SME 124 stated:

“Yeah we would often share resources and information. We would have often had guys down here who would have used our machines that did not have a machine of their own, to do a specific task and we would have said yeah no problem…Similarly if there was something that I needed to get of some

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of the other guys I would have no problem getting it” [SME no.124]

In terms of accessing information useful for the development of innovations, SME 127 stated that in the past they had acquired a great deal of information by utilizing their connections within the furniture cluster, facilitating the successful development of a range of product and process innovations. For example, in pursuit of enhancing their production processes, SME 127 recalled how they utilized their network connections and acquired vital information about ways in which their processes could be modified resulting in innovations such as the introduction of foil wrapping technology and CNC manufacturing:

“I would have had numerous conversations with others (in the network) and said such and so are very good machines and people would have went and bought machinery over that [and] vice versa. I have also bought because someone said that’s a good tool there, you should have one of them you know. [Same with] the foil wrap machine you would probably see a new product comes out...and its foil wrapped, and you say what kind of machine does that there. So, you make enquiries and you get all of this information from the network and then you go and buy one.” [SME no.127]

Similar benefits are outlined by SME 124 who stated:

“There is a guy up the road here who has a factory...and he would have helped me with a few things...He would show me ways he was doing things or he’d have invited me up to his factory and I’d have seen how he was producing his products so yeah certainly, I can and have learnt from what others like him were doing.” [SME no.124]

Market awareness and opportunity recognition

With a greater number of contacts within the cluster central SMEs also appear to be better able to monitor and gather information on the market, remaining abreast of changes and consequently better placed to identify opportunities for innovation. For instance, through interaction and collaboration with cluster partners, SME 127 recalled how they were able to identify, target and make contact with new customer groups and thus penetrate aspects of the market that had remained as yet untapped.

From of the qualitative, quantitative and relational data it is apparent that a significant and positive relationship exists between network centrality and innovation activity among this cluster of low technology SMEs. In explanation of this positive relationship it appears as though the assumption of a central network position assists SMEs in overcoming various barriers often impeding their capacity for innovation. With such barriers eased these central SMEs are in a better position to engage in innovation activities resulting in improved innovation performance as a result [57], [93], [94].

D. Network Cohesion

Although the interview data provides some evidence to suggest that being centrally located within the furniture networks is advantageous, the degree to which inter-firm interaction occurs is limited. This is evident from the low-density scores for both the formal and informal communication network structures. In addition, the interview data elaborates on this with almost all of the SMEs interviewed being reluctant to share certain information with other members of the network. For instance, many of those interviewed described a pattern of “paddling their own canoes” or “keeping their cards close to their chest” when asked about the nature of their interactions with other manufacturers in the region.

To provide more specific examples of this, when asked about such practices the owner-manager of SME 120 stated:

“No kitchen man in the same business as us would talk to each other ... nobody is networking.” … “If I network with 25 kitchen men and I am the only one out of the 25 that changes, well they will think why are we not changing as well then? So, you have already come up with the idea [and then they take it].” [SME no.120]

Explaining this further, the owner-manager went on to state:“Well the reason why they are saying that is, well why should I come up with a good idea and share it with another boy? It’s like anything, don’t get me wrong it’s like anything out there, it’s like the top end appliances, once they get something on the market which goes good, somebody else is knocking on the door looking for it. You know that yourself, they will design something similar.” [SME no.120]

In another instance the owner-manager of SME 129 stated:“We are all in competition at the end of the day, we really all are in competition with one another. And therefore, as much as you would like to help and assist you are not going to give everything away”. [SME no.129]

Similarly, the owner-manager of SME 124 indicated:

“I must say that I would have an open book, but at a certain point, we develop something that is working for us here, I will then close the door on it in that I won’t be telling anyone else about it. Because I realize I have done all this work and I have taken this to a certain stage I cannot afford to just tell everyone else about this. It would defy the whole point of getting it to where it is.” [SME no.124]

Finally, when asked about sharing information with furniture manufacturers involved in different, non-competing activities, SME 111 responded:

“Why disclose the information when it’s not going to give you any advantage, that’s the way it is.” [SME no.111]

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In this case it is apparent that although inter-firm networking does occur within the furniture networks, the extent to which it happens is limited. This confirms research results presented in other investigations in which the furniture firms within the Monaghan furniture sector are found to be largely independent and non-cooperatively minded [95]. This is likely to reflect the fiercely competitive environment in which they are operating and the inability to protect the intellectual property as embodied in product innovations. SMEs in this sector are overly dependent on the domestic (and typically local) market and constantly competing with each other for business. Further, intellectual property in this sector is difficult to protect, for example through patents, and therefore competitive advantage gained by a firm introducing a new or modified product, will be temporary until this is replicated by other firms. For this reason, many of the SMEs in this cluster are very protective of their intellectual property and the development of new products or processes. These findings support propositions made within the OI literature in which issues associated within the protection of intellectual property are identified as a significant barrier to OI among firms and SME’s in particular [96].

V. CONCLUSION

The results presented in this paper reveal some interesting findings that are of benefit to the OI literature. Concentrating on a cluster of low technology SME’s this paper explores the importance of network structure and the relationship between an SME’s network position and their innovation performance.

An assessment of the general level of networking and cooperation among the low technology SME’s reveals that while most of the firms network with one another to a degree, such interaction varies significantly between firms. Overall, the network cluster may be defined as loosely connected with many of the potential network ties remaining unrealized. Potentially motivated by vulnerability, fierce competition, and fears of appropriation this finding supports research which indicates that OI is limited in practice and among SMEs in particular.

Looking at the factors explaining the network positions occupied by SMEs the paper identifies the presence of a general, though not unequivocal, pattern of a positive relationship between firm size, firm age, absorptive capacity, managerial orientation and network centrality. In the case of

absorptive capacity the paper calls for further investigation with questions raised concerning the measurement of absorptive capacity within certain situations. The paper highlights that the orientation of the owner-manager also plays a vital role in the degree to which a firm engages in networking and thus occupies a central network position. SMEs wishing to occupy a central position and harness the benefits of horizontal relationships and the coupled model of OI should therefore be aware that the orientation of those in control of the firm will have an influence on the propensity of the SME to develop relationships with external network partners and thus facilitate the inbound and outbound flow of knowledge. The findings also illustrate how some variables such as firm size and firm age may in fact be intertwined in terms of their impact on network centrality. While firms may be subject to sudden changes in size their age and tenure can serve to preserve their relationships and consequently the network positions occupied. Finally, in identifying inconsistencies in the relationship between network position and the factors mentioned above, this research broadens existing understanding by exploring the conditions under which such anomalous relationships are observed thus offering a more comprehensive exploration of the complexity surrounding network position, structure and innovation performance.

In terms of the relationship between network centrality and innovation performance, the interview data provided some evidence indicating that network centrality provided SMEs with greater access to resources and information required for innovation. In addition, greater connectivity within the network placed the more central SMEs in a better position to identify market opportunities and innovate in response. However, the interview data also revealed that in general the degree to which information and resources are shared within the network is limited, with many of the SMEs preferring to innovate independently to perhaps avoid the perceived risks associated with competitor interaction. On the whole, this research has found partial evidence supporting the proposition that network centrality is positively associated with SME innovation within a low technology furniture network. However, it has also found that knowledge and resource exchange within the network is limited.

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This research contributes to existing knowledge in a variety of ways. Firstly, it provides an insight into a relatively neglected area of innovation research, namely open innovation among SME’s operating within a low-technology sector. Second, it contributes to an underdeveloped understanding of the structure of inter-firm networks, the factors that influence network position and how network position may help SMEs to innovate. Methodologically, the research also illustrates how Social Network Analysis can be applied to OI research, facilitating the examination of the relational profiles of inter-firm network structures. In terms of the implications for practice the paper highlights the importance of OI practices such as external networking and inter-firm cooperation for SMEs as a means of overcoming the barriers often impeding innovation within a low-technology sector. Despite many of the SMEs in this investigation demonstrating a reluctance to initiate and engage in inter-firm relationships, this research provides evidence of the benefits that firms can acquire by developing and maintaining relationships with other members of the cluster. For example, and, related to Piller and West’s [12] second interactive coupled model of OI, the findings demonstrated the co-development of new knowledge and products via the collaborative efforts of two organisations within the network cluster. The paper also indicates that certain factors within the firm’s control, such as absorptive capacity and managerial orientation, serve to influence network position. As a result, SMEs wishing to enhance their network relationships and occupy a more central network position should endeavor to improve their absorptive capacity. With higher levels of absorptive capacity the SME will be in a better position to identify and respond to opportunities for linkage formation. In addition, by developing their absorptive capacity they can ensure that they have something of value to offer potential network partners as well as develop the capacity to “acquire and exploit knowledge that others may have” [59 and 50].

Finally, at the policy level this research highlights the importance of policy support for open innovation as a means of improving SME innovation (within the low-tech sector especially). With the potential to provide SMEs with access to resources and information required for future development and

growth, it is important that policy makers foster such horizontal networking activities when trying to improve firm performance. As previously mentioned with absorptive capacity and managerial orientation found to be conducive to networking, policies aimed at improving inter-firm networking and facilitating the coupled model of OI should take factors such as these into account. Finally, this paper provides policy makers with an insight into the utility of social network analysis techniques, providing a potentially compelling method through which relational aspects of existing networks may be examined. With limitations on the funding and support that can be provided to encourage and facilitate networking and cooperation, the application of social network analysis techniques such as those employed in this paper could also prove beneficial at the initial stages of network formation, providing government agencies with an insight into the viability of the network and the level of interaction among participating organizations.

A limitation of this research was the small sample size among which the investigation was conducted. Although a larger sample size would have facilitated a greater exploration of the data through statistical analysis, the decision to select a network with a small population of SMEs was motivated by the high rate of response required when applying social network analysis [97], [98], [99]. With a larger sample size, the potential to obtain a response rate in excess of 70 per cent would have been more problematic. Furthermore, with a proportion of the sample not answering some of the survey questions it is necessary to acknowledge the limitation of such data and the degree to which it fully captures the innovation activity of those firms. Finally, given that this research was focused on the investigation of inter-firm relations, it was beyond the scope of this paper to explore the other relations maintained by firms within the cluster. In the future it might be of interest to examine in greater depth these other relationships and the benefits that each provide in terms of SME innovation performance. Furthermore, in response to a lack of comparative research in the field of open innovation and in order to enhance the validity of these findings, this research may be replicated in different industrial sectors and compared to the findings presented here.

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Judith Woods received the BSc (Hons) degree in Management and Ph.D. degree in Innovation from Queens University, Belfast, County Antrim, Northern Ireland UK. She is currently a lecturer in Organizational Behaviour at Ulster University. She has published in international journals including Entrepreneurship and Regional Development and is currently the Associate Editor of the Leadership and Organizational Development Journal.

Brendan Galbraith (M’16) received the BA (Hons) degree in Hospitality Management, M.S. degree in Business Studies and Ph.D. degree in Innovation and Entrepreneurship from the Ulster University, Newtownabbey, County Antrim, Northern Ireland, UK. He is currently an Associate Professor in Entrepreneurship at Zayed University in Abu Dhabi, UAE. He has published in a range of international journals including Entrepreneurship and Regional Development, Technovation, R&D Management, Technology Analysis and Strategic Management and International Journal of Production and Operations Management. He has co-authored and co-edited two books on Innovation Intermediaries and Social Innovation and is the Vice-President (TACs) and member of Board of Governors at the IEEE Technology Management Society.

Nola Hewitt-Dundas received the BSc (Hons) degree in Geography and Ph.D. in Economic Geography from Queens University, Belfast, County Antrim, Northern Ireland UK. She is currently a Professor of Innovation Management and Policy as well as Head of School at Queen’s University Management School. She has published widely in leading academic journals including Research Policy, Technovation, Small Business Economics, Scottish Journal of Political Economy, Regional Studies and the Journal of Technology Transfer. She has led and contributed to a wide range of public sector projects for national and international organisations and is currently an ESRC-Innovate UK Innovation Caucus Thought Leader.

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<<<Insert Table 2 and Figures 1 and 2 here>>>

Table 1: Population Characteristics of Participating SMEs

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Variable Name

Description Mean S.D.

Size Average number employed (full time equivalent employees)

11.4 13.2

Age Number of years since the SME was established

27.3 17.8

Absorptive Capacity

Percentage of employees with a degree or equivalent

2.7% 5.2

Innovation Success

Percentage of SME’s sales from new or improved products introduced in the previous 3 years

43.1% 35.6

Formal Degree Centrality

Number of others within the formal communication network that the SME has direct contact with.

31.6 20.2

Informal Degree Centrality

Number of others within the informal communication network that the SME has direct contact with.

27.3 18.6

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Table 2: Degree centrality scores for the formal and informal network

SME Number Formal Degree Centrality

Informal Degree Centrality

Innovation Success1

101 28.1 6.3 30.0102 43.8 37.5 0.0103 12.5 6.3 0.0104 12.5 12.5 0.0105 43.8 28.1 30.0106 28.1 18.8 N/A107 21.9 15.6 0.0108 43.8 28.1 N/A109 46.9 43.8 90.0111 56.3 56.3 30.0112 37.5 28.1 N/A113 56.3 43.8 35.0114 6.3 9.4 N/A115 0.0 3.1 25.0116 43.8 37.5 70.0117 9.4 9.4 0.0118 9.4 6.3 N/A119 0.0 3.1 N/A120 28.1 62.5 80.0121 9.4 6.3 30.0122 25.0 25.0 N/A123 40.6 31.3 N/A124 50.0 46.9 30.0126 62.5 18.8 100.0127 59.4 46.9 40.0128 43.8 37.5 100.0129 65.6 62.5 100.0130 6.3 21.9 91.0131 53.1 56.3 20.0132 3.1 .0 N/A133 15.6 18.8 N/A134 31.3 25.0 60.0135 50.0 46.9 30.0

Average 31.6 27.3 43.1%

1 Innovation Success is the proportion of all sales generated by new or improved products or services introduced within the previous three years (% sales intensity).

Denotes above average scores on the given variable.

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Figure 1: Graphical visualisation of the formal network among clustered SMEs

Innovation activity = % Sales Intensity

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Figure 2: Graphical visualisation of the informal network among clustered SMEs

Innovation activity = % Sales Intensity

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