Innovation studies from an interactive perspective

Based on previous innovation studies, this section examines how innovation processes have been studied from an interactive perspective. This is structured from two perspectives: understanding the firm level of innovation and the connected cluster or regional level of innovation. Networks have been regarded as an effective and efficient form of organization, a form of new competition

with their lateral and horizontal inter-linkages (Dennis, 2000). Dennis (2000) identified five traits of networks. They were namely unity (shared experience), altruism (welfare for others), allegiance, trust (shared past situation), and parity. She pointed out that it was, however, more often the non-monetary aspect of the network that helped to create economies of scale that aided networks of small firms to have a long-term economic development goal.

The study of relationships between networks and innovation is a more recent research direction. Previous similar studies have examined vertical relationships between suppliers and customers and horizontal relationships with competitors providing the other spectrum of the phenomenon studied.

Networks in this instance are regarded as evolving and temporal as they are made up of relationships that are “continuously constructed and reconstructed during interaction” (Grabher, 1993). Hyvärinen (1990) suggested that the environment of an enterprise could be seen in two aspects: the direct environment (demand and supply markets, consumer attitudes, environmental pollution, and possible anti-business attitudes) and the general environment (national and international economy and political situation, education, technology, and population). Bjerke and Johansson (2015) pointed out that while networking activities may be conducted both within and outside the organization, this was also dependent on how the firm is connected to the innovation systems (Lundvall et al., 2002).

2.5.1.1 Cluster/regional innovation levels

Literature focusing on a specific area or cluster of innovation can be drawn from studies on systems of innovation (Bengt-Åke Lundvall, 1992, Edquist, 1997). According to Lundvall (1992), innovation systems may be defined as

“organizations and institutions involved in searching and exploring—such as R&D departments, technological institutes and universities.” Innovation systems are often discussed in terms of actors, networks, and institutions, with the role of actors related to production structures, knowledge infrastructures, and support structures (Nilsson and Moodysson, 2011). Here, the subclass of regional innovation systems or clusters is examined in the context of microenterprises to investigate the advantages of the local environment for the innovation activities of microenterprises. Regional innovation systems or regionally networked innovation systems are understood to be “firms and organizations...embedded in a specific region and characterized by localized, interactive learning” (Asheim and Coenen, 2005). These systems have a deliberate element of intervention from the government and may be

characterized by public-private collaborations (Asheim and Coenen, 2005, Asheim, 2007). These agglomeration advantages “are the advantages gained by business from being located in regional environments where there are many other businesses and/or a high population density” (Henning et al., 2010). An example of such an environment is in industrial districts that may be characterized by small firms specializing in niches along the product value chain (Henning et al., 2010). While the industrial district illustrates localization externalities in which it is characterized by concentrations of firms in a traditional industry, the other end of the spectrum points out other forms of externalities such as urbanization and Jacob’s externalities. These externalities highlight the accessibility of firms to different knowledge bases, services, and infrastructure due to the presence of different industries (Henning et al., 2010). A hybrid of these externalities can thus exist in a region where there are different actors in complementary industries.

An interesting concept comes from Mitra (2000) in the use of the term

“environment munificence,” which is claimed to “influence patterns of network change and plays an important role in the innovation process.

Munificence describes the ‘amount’ of resources available to an organization from the environment and indicates the capacity of the environment to support innovation.” Stressing the role of cooperation with other institutions for the main purpose of accessing various types of resources, such as with universities (Tether and Tajar, 2008, Perkmann and Walsh, 2007), collaboration on the regional level is often a way to gain access to resources without the need to invest in infrastructural changes, a condition that suits the resource-lacking small firm population. Håkansson and Waluszewski (2007) agreed with Penrose (1959) interpretation of the way a resource creates value for the firm: through combination with other resources, interaction with organizations, and relationships within and outside of the firm. The use of new knowledge is dependent on a firm’s ability to integrate with its existing knowledge. This means that actors need to be “willing to experiment with established combinations to find new possibilities for utilizing old and new resources. This implies that mobilizing others is crucial, not in terms of developing a certain strategy others can join but more in term of creating endurance in the combining endeavors” (Håkansson and Waluszewski (2007).

The food industry provides an interesting illustration of the amalgamation of this form of hybrid externalities. The food sector has been portrayed as a stagnant industry in the past but is increasingly being looked upon by researchers as a sector that has its own dynamism with changing relationships and practices (Beckeman and Skjöldebrand, 2007, Sarkar and Costa, 2008,

Muscio et al., 2010, Menrad, 2004, Machat et al., 2004, Lagnevik, 2008, Grunert et al., 1997, Earle, 1997, Batterink et al., 2010, Baregheh et al., 2012). A mature industry like the food sector has been characterized by low technology firms with little radical change (Galizzi and Venturini, 1996). An innovation that starts as a research result from a food technology academic can have ripple effects on other parts of the food system, such as the way the product is distributed or consumed (Earle, 1997). Earle (1997) suggested that there were three types of innovation in the food sector: a novelty, an improvement, or a fundamental change. These innovations may be incremental and characterized by low levels of R&D due to some type of imitation strategy, coupled with a deliberate flow of new food introductions in consideration of market adjustments (Grunert et al., 1997). Avermaete et al.

(2003) noted the importance of innovation for small food firms and pointed out that capital-intensive innovations were more likely to take place with small firms than with microenterprises. Innovation in the food sector can impact and involve more actors than one would normally expect of a sector with such little track record of innovation. The impact of innovation from one area to another in the food system needs to be taken into consideration when considering the innovation process in this sector. Grunert et al. (1997) suggested that introducing new products into the food sector was “an essential element of competition” and hence the understanding of this innovation process was critical. They observed that introducing new products to the food sector is often associated with technological change driven by R&D or market-oriented innovation, which is driven by a detection and understanding of potential customers. These types of innovation have often been explored by scholars of new product development (NPD) as they relate to coordinating development activities with a constant eye on market changes. Despite the recognition of technology-related innovations, the food sector is still considered as a low-tech industry due to the low R&D to sales ratio, as the technology used has typically originated from outside the industry (Grunert et al., 1997). While there are merits to the NPD approach to understanding the development during an innovation process, Costa and Jongen (2006) highlighted that it

“does not explicitly address the role of chain actors other than consumers” in the product innovation process, thereby lacking in addressing the interactive aspects.

Beckeman and Skjöldebrand (2007) examined a cluster of frozen food producers and supporting industries in Sweden that was seen as an initiative driven by some entrepreneurs who networked with the government to provide information along the frozen food supply chain. This supply chain consisted of

the food packaging, equipment, ingredients suppliers, and trade partners. In their case study, they noted a new supply chain around frozen food and a

“spontaneous cluster of food industries and supporting industries assembled in the south of Sweden, particularly around frozen food and with more or less strong links to the network” being formed. This network can be seen as one form of clustering, with agglomeration and industrial complexes forming two other forms of clustering (Gordon and McCann, 2000). Asheim and Coenen (2005) examined the Scandia functional food cluster in terms of understanding innovation from a learning economy approach that “was developed in a national context of small-sized industries relying on incremental, non R&D based product innovations.” The emphasis in their research was therefore placed on knowledge bases in the innovation process of firms and industries.

The study made a deliberate distinction between the concepts of learning economy clusters and regional innovation systems. In the specific context of the functional food cluster example in their research, the role of the university was pointed out to be a “seedbed for the original scientific ideas underpinning”

the establishments of functional food companies. An important knowledge base was a cross-faculty research center supported by the Swedish public agency Vinnova to promote regional innovation systems in which the roles of knowledge workers were highlighted. At that point of research, Asheim and Coenen (2005) noted that the rise of the functional food sector needed the endorsement of both consumers and the traditional food sector. This highlights the multipronged barriers surrounding innovating microenterprises in the food sector, including an alignment of support from regional actors to local (microenterprise) demand. Bjerke and Johansson (2015) suggested that when small firms gain access to a larger network, they have the opportunity to be innovative like their larger peers. Interaction related to innovation, especially outside of the region the small firm operates in, can be important in the innovation process of small firms.

2.5.1.2 Firm innovation level

According to Hoffman et al. (1998), while there are similarities in the innovation activities of SMEs and microenterprises, innovation activities conducted along formal channels are often undertaken by larger SMEs while informal ones by smaller SMEs. This preference of microenterprises for innovation activities at the firm level tend towards those that are less capital intensive (Avermaete et al., 2003). This can explain why networking, which is perceived to to add value through the exchange of experience and knowledge

between network actors, can be an attractive option which allows small firms to enter different and perhaps bigger markets than they would have ventured into on their own (Dennis, 2000). BarNir and Smith (2002) examined the social networks of small-firm executives to understand how these executives form inter-firm alliances. They observed some properties of the social network that may be of interest to the study of microenterprises innovating at the firm level.

For instance, the propensity for individuals to network to initiate social contacts can be used to access potential resources. While this is commonly associated with access to external resources, it also relates to the ability to mobilize and manage these resources. Small firms are also seen to have social networks that allow them to drew on the quality and strength of ties. A strong tie implies that efforts have been put into establishing and maintaining the relationship. The strength of ties can indicate the diversity and quality of information received; strong ties can be beneficial for the ready support that can be provided. Another property relates to the prestige of the network, which is associated with the status or positions of the actors that one socializes with.

These associated qualities can improve the “reputation of the network” and can also be seen as providing better resources and information. In addition to improving the reputation of the individual firm, the small firm can gain legitimacy due to its association with actors in the network known for their reputation in the innovation context.

These interactions of networks at the firm level were examined by Powell and Grodal (2005) in networks consisting of actors from research institutions, industry, and academic sectors. While Powell and Grodal (2005) found that there were limited studies on how networks between firms affected innovative performance, Håkansson and Olsen (2011) reviewed studies that took an

“anthropological research perspective” which viewed business practices as being interrelated and interdependent on external relations and that “innovations emerge through extended interactions.” What this implies is that the interaction is a way through which actors, activities and resources are combined and linked. Medlin (2006) pointed out that how actors perceived each other in the network had a bearing on their actions and related behavior for the development of the network. In such a network, there is need for the firm to have the ability to convert network interest (collective) to self-interest to enable better innovation outcomes.

Past studies have shown that small firms have access to different types of external ties to knowledge or networks through which they gain access to external knowledge bases (Rothwell, 1989, Beesley and Rothwell, 1987, Rothwell and Dodgson, 1991). These knowledge bases have helped to

strengthen the existing competencies of the firm and improve their competitive positions. The success of these microenterprises (small firms, start-ups, SMEs) have been attributed to traits such as “entrepreneurial style, emotional intelligence, innovation capability as well as social capital and networking activities” (Hoang and Antoncic, 2003). Having a heterogeneous group of actors in the network is a generally accepted advantage, because it offers diversity and breadth of access to a variety of resources and assets in addition to diverse knowledge bases. These networks can also make up a common knowledge base from the combination of firms from which resources are pooled, enabling the development of new ideas and skills. Håkansson and Olsen (2011), in relating the interdependence of network actors, pointed out that “historical innovations” which made their mark in terms of material and social relations in the network include the existence of “sufficient interactive capacities” to aid in the manifestation of economic phenomenon. In their words, innovations have “a large number of interfaces towards a variety of existing resources, activities and actors.” This setup is intensified when in the context of knowledge-intensive industries, but can also be observed in strategic alliances which have the in-house R&D and technology know-how to benefit from this locus of innovation.

Robertson and Smith (2008) defined distributed knowledge bases as “a set of knowledge/knowledge sources maintained across an economically and/or socially integrated set of agents and institutions.” The firms are considered key to coordinating the different types of knowledge originating from different sources and locations (geographical, intellectual or social). According to the Robertson and Smith (2008) literature review, knowledge distribution among formal distributed activities such as joint ventures, strategic alliances, and outsourcing is viewed as “uncertain and uneven.” This uncertainty can make it hard to trace relevant knowledge or may have “invisible” linkages. The management of knowledge bases in network interactions thus can be challenging not just due to the nature of knowledge itself. The sources of knowledge need to be traced, weighed in terms of importance, and mapped according to the circumstances in which they are utilized.

Innovation by microenterprises in low-tech sectors are often more practical and architectural in nature in that they recombine existing components to design and develop new products/processes. Small firms interacting in the network should not be confined to the start-up stage, according to Nieto and Santamaría (2010). The benefits to what microenterprises can gain through the actors in the network can range from tangible to intangible resources; the most crucial one is perhaps information and advice from expert actors in their

networks. These expert actors can be venture capitalists, professional services organizations like lawyers, or industry experts who have held management positions in their sector for ten to twenty years. They can provide advice for problem solving or direct the question to a suitable contact, and in certain cases, offer legitimacy to the enterprise. This may be due to the positive perception associated with the microenterprise when the expert actor or organization is recognized to have a committed relationship or stake in the microenterprise. These positive associations can have subsequent impacts on the resource requirements and exchanges of microenterprises with other actors in the network.

The studies on innovation based on the interactive approach can be described as a “virtuous cycle” (Powell and Grodal, 2005) between networks and innovation. Due to the linkages established to facilitate innovation, the innovative outputs attract further collaborations to be established. However, Cohen and Levinthal (1990) pointed out a vicious cycle that firms with low innovative aspirations have also suffered from. This observation compels further investigation into issues such as “the effects of the duration of linkages, experience with collaboration and the consequences of broken ties on rates of innovation” (Powell and Grodal, 2005), an area that this thesis hopes to contribute to. Powell and Grodal (2005) purported that “young and smaller firms may benefit more from collaborative relationships than do larger firms,”

but at the same time noted that “firms with a central location within networks generate more innovative output…both direct and indirect ties provide a positive contribution to innovation but the effect of indirect ties is moderated by the prevalence of direct ties.”

The liability of smallness implied that there are assumed resource constraints of microenterprises that prevent them from developing competencies in-house. This is subsequently linked to a “natural” quest for external resources or organizations to learn from and then to leverage their revamped internal competencies with cooperation with others to enable, for example, innovation to occur. However, microenterprises are credited with being nimble in decision-making due to their small size. Since the owners/managers/founders have to oversee most things associated with driving the innovation process, they have a good overview of what is happening and are able to make critical decisions quickly. In addition, due to their social interactions and networking, they are also the resource that ventures to the outside world to bring new inspiration to the firm. This places an even higher emphasis on a microenterprise’s ability to manage the complex process of coordination and communication as well as relations with external

organizations (Mitra, 2000). This ability may be to have a better awareness of the interaction level at which collaboration is managed as this can have implications for establishing the quality and expectations of the relationships (Blomqvist and Levy, 2006).

Bassayannis and Cronin (2009) suggested that interaction in networks can be viewed as “knowledge based resource interaction,” which can be understood as the “ways which organizations, through networking, mobilize their knowledge bases to innovate.” This type of interaction combines resources in an innovation network that are relevant to the innovation process. In the context of this research, finding organizational and technological complementariness in the innovation network is important for microenterprises (Bjerke and Johansson, 2015). Larson and Starr (1993) suggested in their network model that there were three stages of development with regards to network formation aimed at conducting activities to access economic and non-economic resources, which are required to start any business. Each stage shows a change in the content of the relationship; subsequent stages show evolvement through the addition of complexity and layers in terms of the nature of exchanges. The assembling of contacts that can help provide the resources to kick-start the venture defines the first stage. Essential relationships are harnessed through family and friends’ ties, and existing and new contacts. The second stage is when these relationships develop beyond their functional role to include a social dimension. Social dimensions of these relationships may not only be pursued for advancement of economic interest at this stage. The third stage depicts an increase in complexity among the relationships and an improvement in the quality of exchanges between actors. This can be illustrated, for example, with the establishment of routine interaction and commitment among the actors. Another way that these concepts of interaction in a network can be explored is outlined in the field of studies conducted by the IMP (Industrial Marketing and Purchasing) group of researchers.