R&D cooperation and innovation performance in emerging
economies: evidence from Nigeria
Frank Smilda*
MSc Business Administration: Small Business and Entrepreneurship University of Groningen: Faculty of Economics and Business
Abstract
While the relationship between R&D cooperation and innovation has been extensively explored within developed economies, similar studies have not been carried out in emerging economies. Regarding the different institutional environments in emerging economies, differences in this relationship might appear. The aim of this study is to get some preliminary insights in these differences. To do this, various hypotheses were drawn up and have been tested using multiple binary logistic regression analyses. The results of this study confirm a positive relationship between R&D cooperation and product and process innovation. For product innovation, a positive moderation effect of firm size was found, while for both product and process innovation no significant results were found for the moderation effect of the development of the cooperation partner’s economy. The results of this study provide important insights in the unexplored relationship between R&D cooperation and innovation in emerging economies. Keywords: product innovation, process innovation, R&D cooperation, cooperation partner, emerging economies.
Supervisor: Dr. M. Wyrwich, Co-assessor: S. Costa Date: 11-01-2020
Word count: 11.887
Introduction
In many industries, a firm’s ability to innovate is one of the fundamental instruments to survive (Schumpeter, 1942). Especially in times of technological turbulence, in which technological breakthroughs follow each other up quickly, firms that do not innovate have little chance to survive. Besides increasing chances of firm survival, innovativeness is also seen as one of the key capabilities for growth strategies, entering new markets, increasing the existing market share and to enhance the firm’s competitiveness (Gunday et al., 2011). From the perspective of emerging economies, innovation refers to products and processes which are new to firms in these economies, irrespective of whether the innovations already exist in developed economies (Mytelka, 2000). Research has proven that research and development
(R&D)
cooperation regarding product and process innovation can boost a firm’s innovation performance. Product innovation refers to both innovation of products and innovative services that are exploited, whereas process innovation refers to innovation aimed at improving internal processes within firms.When there is talk of R&Dcooperation, multiple types of potential cooperation partners could be involved. In the literature, suppliers, customers, competitors and institutional entities are the cooperation partners that are examined most often regarding innovation performance (Becker & Dietz, 2004; Weber & Heidenreich, 2017; De Marchi, 2012; Belderbos et al., 2004). However, these studies have so far only been conducted in developed economies (e.g. Germany, Spain and the Netherlands). This paper, in contrast, will focus on the relationship of R&D cooperation and innovation performance in emerging economies. Emerging economies have different institutional environments compared to developed economies, which might affect R&D cooperation within these economies. Studies regarding this matter have not been performed before and it will thus be interesting to examine the relationship between R&D cooperation and innovation within these different environmental conditions as well. The goal of this study is to create some preliminary insights in potential differences between the relationship of R&D cooperation and innovation in emerging economies compared to developed economies.
might be favorable for them to look for cooperation partners from developed economies or not. Based on this, the following research question has been formulated:
How does R&D cooperation relate to innovation performance in emerging economies and how do the development of the cooperation partner’s economy and the size of the firm
influence this relationship?
The rest of this paper is structured as follows. First, the literature review will briefly describe current research regarding R&D cooperation in emerging economies and will focus on social network theory and the institutional theory. Social network theory is about how organizations interact inside their networks and institutional theory dives deeper into different aspects of the relationships within these networks. Most arguments in this study are based on these two theories. After this, the theoretical framework will explain why the hypotheses are drawn up. This will be followed by a methodology section and the results of the performed tests. Hereafter, the results will be discussed and conclusions will be drawn. Finally, the implications of this study will be elaborated.
Literature review Social network theory
advanced alliance partners have a higher innovation rate than firms which lack these kind of alliance partners. Finally, Street & Cameron’s (2007) literature review, which covered more than 200 papers in the field of small business, confirms that small businesses’ external relationships have a positive influence on innovation. Building on these theories, this research will examine how the relationship between R&D cooperation and innovation applies within firms in emerging economies, in which differences appear within the institutional environment. Institutional theory
Institutional theory is a collection of ideas that together form a perspective of the mechanisms that support and restrict social behavior (Björck, 2004). Sociologists define trust as a characteristic of the institutional environment (McKnight et al. 2002). Regarding institutional theory and cooperation between firms, trust is an important aspect. In the literature, trust has been found to be one of the central means to achieve and sustain R&D cooperation. One of the most frequently mentioned positive effects of trust is improved cooperation among actors (Rus & Iglic, 2005). Moreover, multiple studies found that inter-firm trust enhances cooperation (Balliet & van Lange, 2013; McKnight, Cummings & Chervany, 1998; Zaheer et al., 1998).
Rus & Iglic (2005, p.381) found support for their argument that “the institutional theory of trust argues that different types of trust complement one another”. Institutional trust, which refers to general trust in the institutional environment in countries (Rus & Iglic, 2005), is, in general, lower in emerging economies compared to their developed counterparts. This means that other types of trust (e.g. interpersonal and inter-firm trust) are also expected to be relatively low. This general lack of trust implies that, within emerging economies, cooperation between domestic firms is expected to be less successful. On the other hand, international cooperation with firms from developed economies is expected to be more successful, since there is more trust in these institutional environments and hence, according to the argument of Rus & Iglic (2005), also trust in the alliance partner will increase.
alliances tends to be lower than in vertical alliances (Rindfleisch, 2000; Gulati, 1995), which might also increase chances of opportunistic behavior by horizontal alliance partners.
Innovation in emerging economies
In emerging economies, customer’s needs change faster than in developed economies (Chang & Taylor, 2016). The fast change in customer needs results in a relatively high demand for innovative products, which increases pressure for firms to innovate to satisfy the customer needs. Besides the fast-changing customer needs, the economic environment in emerging economies also differs from developed economies. “Emerging countries undergo rapid economic growth and dramatic change in market and technology development” (Chang & Taylor, 2016, p. 50). For this reason, there are relatively many young firms in emerging economies (Hitt et al., 2000). Young firms have relatively little established routines, which enables them to create new processes and structures to form specific capabilities (Rosenbusch et al., 2011). For this reason, it should be relatively easy for these firms to partially shift their focus to innovation of new products or implementing innovations in their internal processes. For these innovations, knowledge is needed (Thornhill, 2006). However, young firms often have relatively little knowledge resources, since knowledge resources develop over time (Mouritsen & Larsen, 2005). Hence, the incentive to cooperate with firms who do possess these resources can be higher in emerging economies (Egbetokun, 2012). Moreover, Medase & Abdul-Basit (2019) found that external sources of information are necessary to attain the desired level of innovativeness in emerging economies while Egbetokun & Siyanbola (2011) show proof that firms in emerging economies benefit from external cooperation partners.
Hence, the effect of R&D cooperation on innovation might be stronger for relatively small firms.
Theoretical framework
Innovation in this paper is approached in the same way as Tomlinson (2010) did in his study on cooperative ties and innovation. He made a distinction between two innovation variables: product innovation and process innovation. However, this research examines both manufacturing and service industries whereas Tomlinson (2010) included only firms from the manufacturing industry. Hence, product innovation in this study focusses on both the output of the production and service process: respectively, how innovative the products are that will be sold to the final customer, and how innovative the service is that the customer experiences. Process innovation, on the other hand, focusses on the production and service processes; methods to develop and manufacture products in manufacturing firms and, regarding service firms, process descriptions and working methods. In this study, four types of cooperation partners for R&D cooperation are included. The different types of cooperation will be discussed and their expected relationship with innovation will be explained.
Cooperation with suppliers
A well-known example in which knowledge sharing within the buyer-supplier relationship increases innovation performance is within the Japanese automobile industry, particularly at Toyota (Dyer & Nobeoka, 2000). Dyer and Nobeoka (2000) state that the source of many innovative ideas come from the network the firm has with its suppliers instead of within the individual firm. Their study focusses on the firm’s efficiency performance, which means that the firm’s innovation performance is mainly enhanced through process innovation. Moreover, Fritsch & Lukas (2001) found that cooperation with suppliers has a relatively low share in value added to turnover, which indicates a low influence on product/service innovations, while it does have a significant impact on internal R&D, indicating that the relationship does enhance process improvement. Finally, Belderbos et al. (2004) and Chung & Kim (2003) found subsequent results which showed that cooperation with suppliers is mostly focussed on efficiency performance instead of product or service innovation. Therefore, cooperation with suppliers is expected to mainly enhance process innovation.
Cooperation with competitors
However, recent research in developed economies has also shown that firms use coopetition for product innovation (Bouncken & Kraus, 2013; Luo, 2005; Gnyawali & Park, 2009; Ritala & Hurmelinna-Laukkanen, 2012). Coopetition is especially important for relatively small firms which compete in highly technological markets (Bouncken & Kraus, 2013). By using coopetition in these markets, small and medium-sized enterprises (SMEs) can bundle their resources and share their knowledge to enhance their product innovation ability. Since, within developed economies, the institutional environment is more developed, firms in these areas are willing to share more knowledge and resources with competitors since the risk of opportunistic behavior by the cooperation partner is relatively low according to institutional theory. However, regarding the institutional environment within emerging economies, firms are expected to be less eager to share knowledge with their competitors due to issues of trust. As a result, cooperation with competitors for product innovation, in which knowledge spillovers are relatively high, will be less attractive for firms in emerging economies. Hence, cooperation with competitors is expected to mainly improve process innovation, and not product innovation. Cooperation with customers
to have a positive relationship with new product innovativeness. Finally, von Hippel (2005) showed that cooperation with customers is relevant for product innovation. Therefore, cooperation with customers is expected to mainly enhance product innovation.
Cooperation with institutional entities
Institutional entities differ a lot from the cooperation partners discussed so far. In this study, institutional entities consist of universities, other high education institutes and public research institutes. The largest distinction arises within the main goals of institutional entities: they do not want to maximize their profit, but are interested in know-how and knowledge enhancement (Weber & Heidenreich, 2017). Moreover, Belderbos et al. (2004) found that in cooperation with institutional entities, knowledge spillovers are more than twice as large compared to cooperation with other cooperation partners. This is because institutional entities have a relatively low interest in protecting their knowledge and know-how regarding their unconcern for profit. Their high knowledge base and the willingness to share this knowledge makes institutional entities potential valuable cooperation partners, especially if the cooperation concerns (highly) technological innovations (Bozeman, 2000; Vuola & Hameri, 2006) or if the innovation has an explorative or disruptive character (Weber & Heidenreich, 2017). “R&D cooperation with universities is more likely to be chosen by R&D intensive firms in sectors that exhibit faster technological and product development” (Belderbos et al., 2004, p.2), since cooperation with institutional entities is mostly focussed on radical innovations through which new markets can be opened (Monjon & Waelbroeck, 2003; Tether, 2002). Finally, multiple studies showed that cooperation with institutional entities is the most successful form of cooperation regarding (radical) product innovation (Belderbos et al., 2004; Weber & Heidenreich, 2017; Faems et al., 2005). For these reasons, cooperation with institutional entities is expected to mainly enhance product innovation.
To summarize, cooperation with customers and institutional entities are expected to mainly enhance product innovation, whereas cooperation with suppliers and competitors are expected to mainly enhance process innovation. However, due to multicollinearity issues within the data, disentanglement between the different types of cooperation is not possible. Hence, one general cooperation variable is used in this study.
Firm size
In general, firm size is positively related to innovation, since larger firms have more resources to initiate new innovations (Zhu et al., 2006; Kumar & Saqib, 1996; Becker & Dietz, 2004). However, in this research firm size will be examined as a moderator between cooperation with external parties and innovation performance. Firm size, in this context, is expected to have a negative influence on this relationship. Since small firms have less knowledge resources they benefit more from R&D cooperation compared to relatively large firms. Small firm’s lack of resources has to be compensated and hence, they depend more on their cooperation partners for successful innovations. For cooperation with customers, this has been confirmed by Chang & Taylor (2016), who found that co-creation with customers is more effective for smaller firms than large firms. Furthermore, Bouncken & Kraus (2013) found that coopetition is especially important for relatively small firms which compete in highly technological markets, since they often will not be able to compete in these markets by themselves. Within low R&D intensity sectors, in which there are only limited opportunities to stand out from the competition, evidence has also been found that especially small firms increase their innovation performance from cooperation, since innovations in these sectors often include complex and risky technologies which small firms can’t develop by themselves (Becker & Dietz, 2004). Finally, “firms impeded by costs to innovate are more likely to cooperate with universities, attracted by the often government-subsidized cost sharing in public-private partnerships” (Veugelers & Cassiman, 2002, p.17). For these reasons, relatively small firms are expected to increase their innovation performance more through cooperation with external parties than relatively large firms.
H3a: Firm size negatively moderates the relationship between R&D cooperation and product innovation
H3b: Firm size negatively moderates the relationship between R&D cooperation and process innovation
International cooperation with firms in developed economies
innovation is costly, risky, and path-dependent, poor countries may have a rationale to rely on foreign technology acquisition for technological development” (Fu et al., 2011, p. 7). Moreover, Schmiele (2009) states that a lack of innovation-specific resources and services lowers the attractiveness of a domestic location to conduct innovation for firms in emerging economies. More specifically, lack of qualified personnel, potential cooperation partners, technological information, and high costs are mentioned as local obstacles. Regarding the relatively little knowledge resources firms in emerging economies often possess and the fact that these resources are often unavailable in their own country as well, it can be a good strategy to use the knowledge of firms which are located in more developed economies. Since firms in more developed economies are generally older and knowledge resources of firms increase over the years (Mouritsen & Larsen), firms in developed economies are expected to have more knowledge resources. Since cooperation partners from developed economies, besides knowledge resources, also possess more advanced technological resources, they can be the solution for the lack of resources in emerging economies. Using these resources for innovation, R&D cooperation can enhance the possibilities for innovation for firms in emerging economies, since they would not have access to these resources within their home country. Hence, R&D cooperation with firms from developed economies are expected to add more value to innovation performance than cooperation with domestic partners.
H4a: Development of the economy of the firm’s cooperation partner positively moderates the relationship between R&D cooperation and product innovation
Figure 1: Conceptual model
Methodology
Data
The current literature gap on R&D cooperation within emerging economies determines the research approach chosen in this study. Regarding the literature gap, a theory testing approach will be conducted. To test the proposed hypotheses, an existing dataset will be used. For this reason, data collection will not be necessary. The data that is used for this study has been collected by NEPAD (New Partnership for Africa’s Developent), the Federal Ministry of Science & Technology and National Centre for Technology Management. The dataset, with a total of 1359 observations and a response rate of 54%, consists of Nigerian manufacturing and service firms, which include both formal and informal firms. The data is cross-sectional pooled and collected in two waves in 2005-2007 and 2008-2010 to reduce common-method bias. Based on a list of the National Bureau of Statistics and the Nigerian Stock Exchange, the sample was randomly selected with only one criteria: the firm should consist of at least 10 employees. In total, 932 firms out of the sample of 1359 were involved in either product or process innovation. The observed firms are active in many different industries. To add some background information on the types of industries, the distinguished industries and the corresponding frequencies of the firms belonging to these industries have been added in table 2.
Cooperation, in this study, is based on whether firms have cooperated for innovation with either suppliers, customers, competitors or institutional entities. However, firms often cooperate with different cooperation partners simultaneously. To give an insight of which types of cooperation partners are involved in this study, the distribution of the different types of cooperation is shown in table 1.
Table 2: Overview of sample composition per industry
multicollinearity, a Pearson’s correlation test has been performed. The results of this test are shown in table 3. According to Hair et al. (2006), results of a correlation matrix can be interpreted as follows: very strong to perfect correlation (r = 0.81 to 1 or -0.81 to -1); strong correlation (r = 0.61 to 0.8 or r = 0.61 to 0.8); moderate correlation (r = 0.36 to 0.6 or r = -0.36 to -0.6); weak correlation (r = 0.21 to 0.35 or r = -0.21 to -0.35); no correlation (r = 0 to 0.2 or r = 0 to -0.2).
Table 3: Correlation matrix different types of cooperation
The correlation matrix shows that there is a very strong correlation between cooperation with suppliers and cooperation with customers. Also, strong correlations are shown between cooperation with competitors and cooperation with suppliers, cooperation with competitors and cooperation with customers, cooperation with institutional entities and cooperation with customers and finally, between cooperation with institutional entities and cooperation with competitors. These correlations reveal that multicollinearity issues can give problems if a binary logistic regression test is performed. For this reason, the different types of cooperation could not be tested separately, but were merged into a general cooperation variable, which only includes whether a firm has cooperated for innovation in any form, but does not distinguish between the different types of cooperation.
Measurements
commitment or satisfaction) are generally discouraged. For this study, single-item measures can be categorized as demographic-type information instead of psychological constructs, which mitigates the limitation that single-item measures might entail.
Cooperation for innovation. For the four different types of R&D cooperation (supplier, customer, competitor, or institutional entity), questions were answered whether the firm has cooperated for innovation and in which geographical area this cooperation partner operates. For each respondent, a dummy variable has been created. These dummy variables take “1” if the respondent has stated that it has cooperated for innovation with any of the cooperation partners. If there was no cooperation between the firm and a cooperation partner, the variable takes “0”.
Firm size. Firm size is hypothesized to have a moderating effect on innovation. However, the variable is also used in models where firm size itself is not the main variable. In these models, firm size acts as a control variable. Firm size will be measured based on the number of employees a firm has (Tomlinson, 2012). Only within the first wave of the respondents a distinction has been made between part time employees and full time employees, but in the second wave of data only the total number of employees has been measured (including both full time and part time employees). Hence, firm size is measured by the total numbers of employees in either 2007 (wave 1) or 2010 (wave 2). To smoothen the distribution of the variable, z-scores of the variable were computed and used instead of the number of employees itself. This avoids the risk that outliers will drive the model.
Firm size as moderating variable. To construct the moderating variable between cooperation for innovation and firm size, the cooperation variable (dummy variable) has been multiplied with the Z-scores of the variable firm size. First, the Z-scores of the variable firm size have been computed, and after this they were multiplied with the corresponding variable ‘cooperation for innovation’.
focusses on cooperation with domestic firms, takes “1” if a firm has at least 1 cooperation partner from Nigeria without having cooperation partners from developed economies simultaneously. Otherwise, it takes “0”.
Process innovation. In the database, three variables regarding process innovation are included. These variables focus on, respectively, (1) new or significantly improved production methods, (2) new or significantly improved logistics, delivery and distribution, and (3) new or significantly improved support activities. These questions have been answered with either “yes” or “no”. To measure the firm’s process innovation, a dummy variable has been constructed. The variable takes “1” if at least one of the questions regarding process innovation are answered with “yes”. If the answer to all three questions was “no” the variable takes “0”.
Product innovation. Product innovation in this study consists of innovation of both products and services. However, for better readability of the paper, it will be referred to as ‘product innovation’. For each firm, the question has been asked whether the firm produces new or significantly improved goods and whether the firm delivers new or significantly improved services. Both questions are answered with either “yes” or “no”. The same way as in process innovation, a dummy variable has been constructed. The variable takes “1” if at least one of the variables regarding product / service innovation has been answered with “yes” and takes “0” if both questions have been answered with “no”.
Control variables. To control for environmental differences, multiple control variables have been added to the models. First, the model is controlled for whether the firm is located in Nigeria’s capital Lagos or not, since the environment in the largest agglomeration of Nigeria is expected to influence the outcomes on the dependent variables. The variable takes “1” if the firm is located in Lagos, and “0” otherwise. Second, a control variable is added for whether the firm is a service or manufacturing firm. The variables takes “1” if the firm is a service firm and “0” if it is a manufacturing firm. Finally, a control variable focussed on the difference in time when the data was collected has been added, since the data collection occurred in two waves with three years in between. The variable takes “1” if the data was collected in 2011, and “0” if it was collected in 2008.
Logistic regression models
this study, the categorical outcome that is predicted, is whether firms have carried out product or process innovations. These variables are predicted by the categorical predictor whether the firm is cooperating for innovation or not. This statistical model is used to test hypotheses 1 and 2.
To test the moderating effect of firm size in the model (H3a/H3b), an interaction variable for cooperation and firm size has been constructed. According to Field (2014), creating an interaction variable between a binary and a continuous variable can be done by simply multiplying the two variables together. Furthermore, Field (2014) states that for the interaction term to be valid, the predictor and moderator must be included in the model as well. For this reason, both “Cooperation” and “Firm size”, together with the interaction variable between the two, have been added in the model to test the moderation effect of firm size.
Finally, to check for a moderating effect of the development of the cooperation partner’s economy (H4a/H4b), a distinction has been made between two types of cooperation: cooperation with only Nigerian firms and cooperation with firms from developed economies. Both variables act as categorical predictor in the regression model. To test the moderation effect of development of the cooperation partner’s economy, cooperation for innovation was extracted from the model and replaced by two cooperation variables which were split in cooperation with firms from developed economies and cooperation with firms from Nigeria. Potential differences between the outcomes of these variables are used to test H4a and H4b.
Results
from developed economies and firms from Nigeria. These two variables, together with the control variables, have been included in the models to test H4a and H4b.
Descriptive statistics and correlations Table 4: Descriptive statistics
The descriptive statistics (table 4) indicate that about 54% of the firms introduced product innovations, while 62% of the firms introduced process innovations. 18% of the firms stated that they cooperated with other organizations for innovation, while 11% of the firms cooperated only with Nigerian firms and 6% with firms from Europe or the USA. The mean number of employees, which is used to calculate firm size, is 186. Furthermore, 59% of the firms are located in Lagos. 46% of the data was collected in 2008, and 54% in 2011. Finally, 65% of the firms are grouped as manufacturing firms and 35% as service firms.
Table 5: Correlation matrix
Binary logistic regression analyses
Table 6: Main effect of cooperation on product and process innovation
Table 7: Moderation effect of firm size on product and process innovation
Table 6 shows that cooperation for innovation has a positive relationship with product innovation (β=1.626, p < .001). It also shows a positive relationship between cooperation for innovation and process innovation (β=2.459, p < .001). This does not change when variables for firm size are added to the model (table 7) or when cooperation for innovation is split up into cooperation with firms from developed economies and cooperation with firms from Nigeria (table 8). Hence, H1 and H2 are confirmed while the strongest effect is shown for H2. Furthermore, table 7 shows a weak interaction effect of firm size between cooperation and product innovation (β=1.731, p < .100). For this reason, the interaction effect of firm size on product innovation (H3a) will be further explored. Table 7 also shows that the interaction effect of firm size on process innovation is insignificant. Therefore, this interaction effect has not been further explored and H3b is rejected. To further explore the interaction effect of firm size between cooperation and product innovation (H3a), dummy variables for small, medium and large businesses have been constructed. Classification of these respective variables has been based on the definition of SMEs by the European Commission (2016), which classifies SMEs by number of employees. The European Commission classification for SMEs is as follows: small (and micro) firms have fewer than 50 employees, medium firms have a minimum of 50 and a maximum of 249 employees, large firms have 250 or more employees. Based on these classifications, three dummy variables were constructed of which two could be tested at the same time. The third variable acts as reference group. Tables 9-11 show the results for these tests.
Table 9: Moderation effect of small and medium businesses: large businesses as reference group
Table 10: Moderation effect of medium and large businesses: small businesses as reference group
Table 11: Moderation effect of small and large businesses: medium businesses as reference group
In table 9, in which large firms are used as a reference group, the variable ‘small businesses’ shows a negative moderation effect on cooperation for product innovation (β=-1.559, p < .05), while ‘small businesses’ shows a weaker, but also negative moderation effect on cooperation (β=-1.542, p < .10). This contrasts H3a, which states that relatively small firms should benefit more from cooperation than large firms. In table 10, in which small firms are the reference group, the moderation effect of large firms shows a positive effect for cooperation on product innovation (β=1.559, p < .05 ), while the interaction variable for medium firms in insignificant. In table 11, where medium firms are the reference group, ‘large businesses’ shows a weak positive moderation effect for cooperation on product innovation (β=1.542, p < .10 ), while the interaction variable of ‘small firms’ is insignificant. The results indicate that large firms have a positive moderation effect on cooperation for innovation in relation with product innovation. For small and medium firms, negative moderation effects have been observed. These results are interesting, since it actually indicates a positive moderation effect of firm size between cooperation for innovation and product innovation, opposing the expectations of h3a. Hence, h3a has been rejected.
Further exploration of the interaction effects of development of the cooperation partner’s economy has been done by performing a binary logistic regression analysis, as is done in table 8, but while splitting the data between manufacturing and service firms. Therefore, two new tables similar to table 8 emerge while one table only includes manufacturing firms and the other one only includes service firms. The results are shown in table 12 and 13.
Table 13: Development of cooperation partner’s economy on product and process innovation: service firms
Table 12, which includes only manufacturing firms, shows a positive relationship for both cooperation with firms from developed economies (β=2.153, p < .001) and cooperation with Nigerian firms (β=1.736, p < .001) for product innovation. For process innovation, it also shows a positive relationship for both cooperation with firms from developed economies (β=2.397, p < .001) and cooperation with Nigerian firms (β=3.503, p < .001).
Table 13, which includes only service firms, shows a positive relationship for both cooperation with firms from developed economies (β=1.024, p < .05) and cooperation with Nigerian firms (β=1.617, p < .001) for product innovation. For process innovation, service firms, again, show a positive relationship for both cooperation with firms from developed economies (β=2.716, p < .001) and cooperation with Nigerian firms (β=1.691, p < .001).
relationship with cooperation with Nigerian firms and when filtering for service firms, product innovation shows a stronger relationship for cooperation with Nigerian firms as well. Due to these mixed results, H4a and H4b have been rejected.
Discussion
R&D cooperation for innovation has a positive relationship with both product and process innovation. Throughout all statistical models, these results stay consistent and thus, H1 and H2 are supported. The positive effect of R&D cooperation on innovation has been found many times before in studies within developed economies. However, since only little research has been done in the field of emerging economies, these results are valuable in confirming the positive relationship between cooperation and innovation in these environments as well. Furthermore, H2 shows a stronger relationship than H1, which means that the relationship between cooperation for innovation and process innovation is found to be stronger than the relationship between cooperation for innovation and product innovation.
The institutional environment of emerging economies could be the underlying reason for this difference. Since there is a relatively low level of trust in emerging economies, firms might be less eager to cooperate and share knowledge regarding their products and services. Moreover, since rules and regulations regarding idea protection and copyright infringement are lagging in emerging economies, firms might be afraid that their ideas can be stolen by potential cooperation partners. However, cooperating to improve business processes (e.g. cutting costs by bulk purchasing together with competitors or improvements in logistics within the supply chain) often does not suffer from this lack of trust, since the incentive for opportunistic behavior of the other party is less present. Regarding the environmental differences in emerging economies, it would be interesting to further explore the differences in impact of R&D cooperation on product and process innovation compared to developed economies and examine why potential differences occur.
studies in developed economies, it is interesting to further explore the interaction effect of firm size between R&Dcooperation and innovation in emerging economies.
A reason for the opposite finding in this study could be that, on average, firms in emerging economies are younger than firms in developed economies. The study of Navaretti et al. (2014), which contains data on firm age for France, Italy and Spain has been used to compare firm age of developed economies with firm age from the database used for this study. One of the selection criteria for both databases was that firms should have at least ten employees. It turns out that especially the percentage of ‘very old firms’ (aged 21+) tends to be significantly smaller in Nigeria (32.6%) compared to developed economies (46.4%). Thus, the claim that small firms have a relatively small knowledge base compared to large firms might not apply for firms in emerging economies, since this knowledge base tends to grow when firms get older (Mouritsen & Larsen, 2005). Hence, also older firms in emerging economies, which are often relatively large, have a higher incentive to cooperate for innovation compared to large firms in developed economies.
Moreover, human capital is important, since it is positively related to innovation (Dakhli et al., 2004). The level of human capital in large firms in developed economies is often very high, since these firms attract the largest proportion of well-educated employees. For large firms in emerging economies this might be harder, since there are less well-educated people and a large proportion of them often decides to find their luck in western economies, leaving their home-country behind. This results in a high level of human capital for large firms in developed economies, while the level of human capital in large firms in emerging economies lags behind. Therefore, it is still hard for large firms in emerging economies to innovate by themselves regarding the relatively low level of human capital: a drawback which large firms in developed economies suffer less from.
with this issue. Hence, large firms might be better able to reap benefits from cooperation for product innovation.
Finally, in most emerging economies, there is no market for the most disruptive and newest innovations. Instead, firms in emerging markets depend more on copying innovations from western economies and, based on these, create frugal innovations. Frugal innovations are ‘good enough’, affordable products that meet the needs of resource constrained customers (Zeschky et al., 2011). Firms in emerging economies sometimes cooperate with firms from developed economies to ‘strip’ their products and sell them on the local market (van Beers et al., 2012). Firms from developed economies who want to cooperate with local firms in emerging economies, might be more interested in cooperating with relatively large firms, since they might have issues of trust to cooperate with small unknown firms from an emerging economy. For large firms it might be possible to mitigate issues of trust, since it might be easier to check their track record. Furthermore, large firms in emerging economies might have better communicative skills, which also makes them more attractive for cooperation. Therefore, a high proportion of frugal innovations in emerging economies could be a reason for the positive moderation effect of firm size for product innovation as well. Future research to frugal innovations could be very interesting. It should focus on the extent to which local firms in emerging economies cooperate with firms from developed economies by transforming their original innovations to frugal innovations and whether firms from developed economies prefer to cooperate with relatively large firms regarding this type of cooperation.
partner’s economy was only found for product innovation within manufacturer firms and for process innovation within service firms. A negative moderation effect of development of the cooperation partner’s economy was found for process innovation within manufacturer firms and for product innovation within services firms, meaning that in these industries, cooperation with Nigerian firms has a stronger positive relationship with innovation.
These mixed results indicate that cooperation for innovation with firms from developed economies might not always be as successful as expected. A reason for this could be that international alliances are often considered to be risky regarding high chances of opportunistic behavior or freeriding (Gulati, 1999). The fact that no distinction between the types of cooperation partners could be made (e.g. supplier or competitor), might also have something to do with the mixed results. Since for horizontal alliances, trust is more important than for vertical alliances, it could be that different results between the different types of alliance partners drive the insignificance of these results.
Moreover, the fact that no clear split could be made for firms that cooperate solely with firms from developed economies, could also be a reason for the mixed results, since most of the firms that cooperate with firms from developed economies, cooperate with firms from Nigeria as well. This has been one of the main limitations in this study. Since the data does not show how many cooperation partners a firm has from countries with different economic backgrounds, no hard conclusions can be drawn for H4a and H4b. Future research regarding the development of cooperation partner’s economy could be very interesting. However, to find clear results the data should decompose the number of cooperative agreements for different types of cooperation and type of economies. This way, the split between firms that have cooperative agreements with (mainly) firms from developed economies and firms from (other) emerging economies can be made more precise.
Conclusion
The first conclusion that can be drawn from this study is that, as found in studies in developed economies, R&D cooperation has a positive effect on both product and process innovation. However, the impact of R&D cooperation seems to be stronger for process innovation than product innovation. This result is probably caused by the different institutional environment of emerging economies, in which there are higher chances of opportunistic behavior and lower levels of trust between organizations. These challenging environmental conditions do more harm to product innovation than process innovation regarding R&D cooperation.
Moreover, the expected negative interaction effect of firm size on the relationship between R&D cooperation and innovation was not found. For product innovation, even a positive interaction effect of firm size was found, which is the opposite of the hypothesis. This effect might be explained due to the relatively low knowledge base of large firms in emerging economies, whereas this knowledge base is, on average, higher in developed economies since these firms are older. Moreover, the relatively low level of human capital in emerging economies could be a reason that large firms in emerging economies still need cooperation partners for product innovation. Furthermore, large firms might better cope with communication problems due to less advanced ICT-networks in emerging economies, since they have more resources. A final reason to explain this result is that firms from developed economies who want to cooperate with local firms in emerging economies to create and distribute frugal innovations of their products, might prefer cooperation with large local firms due to their track records and better communicative skills.
Finally, the moderation effect of the development of the cooperation partner’s economy showed mixed results for product and process innovation in the manufacturing and service sector. This could mean that success due to cooperation with firms from developed economies is not as obvious as expected, but differs per case. However, regarding the limited components in the data regarding this issue, no clear split could be made between cooperation with firms from mainly developed or emerging economies. Therefore, this moderation effect requires more research.
Limitations
and process innovation differently. Regarding the different expected outcomes for product and process innovation between different types of cooperation partners, it would be very interesting to examine the influence of different cooperation partners on innovation in emerging economies. The theoretical framework of this paper describes the expectations of different types of cooperation partners regarding product and process innovation. However, these expectations have, to a large extent, been based on the existing literature in this field, which has primarily focused on developed economies. It would be interesting to see what differences emerge if similar studies are performed in emerging economies as well, since this study has shown that different environmental conditions can result in different outcomes for these economies. If a study in which a distinction between types of cooperation partners would be performed in an emerging economy, this could help firms in these areas in choosing the right type of cooperation partner which fits with the purpose of their innovation outcome.
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