R&D Partnerships and Innovation Performance: Can There Be too Much of a Good Thing?

R&D collaboration facilitates the pooling of complementary skills, learning from the partner as well as the sharing of risks and costs. Research therefore stresses the positive relationship between collaborative R&D and innovation performance. Fewer studies address the potential drawbacks of collaborative R&D. Collaborative R&D comes at the cost of coordination and monitoring, requires knowledge disclosure, and involves the risk of opportunistic behavior by the partners. Thus, while for lower collaboration intensities the net gains can be high, costs may start to outweigh benefits if firms perform a higher share of their innovation projects collaboratively. For a sample of 2735 firms located in Germany and active in a broad range of manufacturing and service sectors, this study finds that increasing the share of collaborative R&D projects in total R&D projects is associated with a higher probability of product innovation and with a higher market success of new products. While this confirms previous findings on the gains for innovation performance, the results also show that collaboration has decreasing and even negative returns on product innovation if its intensity increases above a certain threshold. Thus, the relationship between collaboration intensity and innovation follows an inverted‐U shape and, on average, costs start to outweigh benefits if a firm pursues more than about two‐thirds of its R&D projects in collaboration. This result is robust to conditioning market success to the introduction of new products and to accounting for the selection into collaborating. This threshold is, however, contingent on firm characteristics. Smaller and younger as well as resource‐constrained firms benefit from relatively higher collaboration intensities. For firms with higher collaboration complexities in terms of different partners and different stages of the R&D process at which collaboration takes place, returns start to decrease already at lower collaboration intensities.     

Creating shareholder value via collaborative innovation: the role of industry and resource alignment in knowledge exploration

Collaborative innovation provides firms with a privileged opportunity to perform exploration in an externally oriented mode. The central challenges in exploration via collaborative innovation lie in the selection of relevant partners and in gaining access to potentially valuable external knowledge that the focal firm lacks. This article focuses on two aspects of inter-organizational alignment that affect knowledge differences and may thus help explaining the shareholder value implications arising from collaborative innovation: industry and resource alignment. Relying on data covering 97 bilateral collaborative innovations (194 innovation partners) in R&D intensive high-technology industries, we used event study methodology and follow-up hierarchical regression analyses to test our conceptual framework. With regard to industry alignment, results suggest that investors value greater industry distance between collaborating partners, especially when the partner firm provides high-level R&D resources. Furthermore, the results show a positive effect of supplementary resource alignment (i.e., a focal firm's R&D resources are supplemented by a partner firm's R&D resources) and, notably, a negative effect of complementary resource alignment (i.e., a focal firm's R&D resources are complemented by a partner firm's marketing resources) on investors' valuation of the collaboration's expected future performance. They, thus, contribute to research on shareholder value implications of collaborative innovation. From a managerial perspective, the study provides a better understanding of partner selection and shows how managers should position a collaboration to signal the shareholder value-creating potential to investors.     

Assessing collaborative, pre-competitive R&D projects: the case of the UK LINK scheme

The paper addresses the evaluation of outcomes of collaborative, pre-competitive R&D projects. It draws on some empirical analysis carried out on data and information gathered under the UK 'LINK' scheme, a programme supporting R&D collaborative projects and assessing collaboration outcomes. A new indicator of performance, based on the outputs of LINK projects, has been constructed. It provides a relative and quite consistent measure of performance for making comparisons among different LINK projects. However it does not correlate with the more subjective grade applied by LINK's own management. For further improving evaluating mechanisms, more attention should be paid to the benefits that universities and companies as well as governments are drawing from R&D collaborations.     

Clustering and the R&D management of high-technology small firms: in theory and practice

Much of the policy assistance for high-technology small firms (HTSFs) over recent years has been directed at encouraging their research and development (R&D) collaboration through local networking and technology transfer. Following a consideration of why HTSFs are formed, and how they perform R&D in order to cope with the competitive environment, this paper explores the value of external collaborative R&D to internal R&D management, inside geographically concentrated incubators, science parks or clusters. It is concluded that, although R&D collaboration with external partners occurs in limited instances, much HTSF R&D is highly confidential, competitive and wholly internalised. This tendency, as far as it relates to R&D management, is significant in that it minimises the likelihood that local management collaboration between co-located firms will improve the performance of R&D projects.     

Collaboration in R&D with universities and research centres: an empirical study of Spanish firms

Innovation is sometimes the result of collaboration between different agents with complementary resources. When companies make formal agreements to collaborate in R&D they do so with different types of organizations, such as their competitors, suppliers, and customers, or universities and research centres. This paper focuses on attempting to understand the reasons that lead companies to cooperate with universities and research centres and the characteristics of the relationship that this involves. The empirical study is based on a sample of 747 Spanish firms that took part in some type of collaborative R&D project between 1994 and 1996. Results indicate that cooperation with centres is a nation–wide phenomenon involving basic research, conducted under the sponsorship of different research support schemes promoted by central and regional administrations.     

Types of R&D Collaborations and Process Innovation: The Benefit of Collaborating Upstream in the Knowledge Chain

This paper explains how research and development (R&D) collaborations impact process innovation; given the differences in innovation mechanisms, prior insights from studies of product innovation do not necessarily apply to process innovation. Extending the knowledge‐based view of the firm, this paper classifies four types of R&D collaborations—with universities, suppliers, competitors, and customers—in terms of two knowledge dimensions: position in the knowledge chain and contextual knowledge distance. Position in the knowledge chain is the position of the R&D collaboration partner in the knowledge chain of the industry—the input–output sequence of activities that result in the transformation of raw materials into products that are used by end customers. Based on this knowledge chain, this paper considers universities and suppliers as upstream R&D collaborators, and competitors and customers as downstream R&D collaborators. Contextual knowledge distance is the difference in industry‐related contexts of operation of the R&D collaboration partners and the firm. Based on this, this paper views R&D collaborators that are suppliers and competitors as having low contextual knowledge distance to the firm, and R&D collaborators that are customers and universities as having high contextual knowledge distance to the firm. Using this classification, this paper proposes a ranking of R&D collaborations in terms of their impact on process innovation: R&D collaborations with suppliers have the highest impact, followed by R&D collaborations with universities, then R&D collaborations with competitors, and finally R&D collaborations with customers. These arguments are tested on a four‐year panel of 781 manufacturing firms. The results of the analyses indicate that R&D collaborations with suppliers and universities appear to have a positive impact on process innovation, R&D collaborations with customers appear to have no impact, and R&D collaborations with competitors appear to have a negative impact. As a consequence, the main driver of the impact of R&D collaborations on process innovation appears to be position in the knowledge chain rather than contextual knowledge distance. These novel ideas and findings contribute to the literature on process innovation. Even though process innovation tends to be internal and tacit to the firm, it can still benefit from external R&D collaborations; this paper is the first to analyze this relationship and provide a theoretical framework for understanding why this would be the case. This study also has important managerial implications. It suggests that managers need to be careful in choosing the partners for their firms' R&D collaborations. Engaging in R&D collaborations with universities and suppliers appears to be helpful for process innovation, whereas conducting R&D collaborations with competitors may potentially harm process innovation.     

Towards networked R&D management: the R&D approach of Sonera Corporation as an example

In this paper the authors delineate the challenges of a dynamic environment to R&D management. The authors build on most recent ideas, such as the dynamic capability view of the firm, as strategic foundation for modern R&D management. Collaboration is emphasized as a meta-capability for innovation. These ideas are merged into a 'Networked R&D Management' approach that emphasizes internal and external collaboration networks as critical for companies operating in a dynamic business environment. The approach is illustrated with ICT industry as an example. The implementation of Networked R&D Management is reflected in the illustrative case discussion of R&D management of Sonera Corporation.     

R&D Collaborations and Product Innovation*

This paper studies the relative impact on product innovation of research and development (R&D) collaborations with universities, suppliers, customers, and competitors. It argues that each type of R&D collaboration differs in terms of the breadth of new knowledge provided to the firm and in the ease of access of this new knowledge, resulting in a different impact on product innovation. As a result, it proposes that R&D collaborations with universities are likely to have the highest impact on product innovation, followed by R&D collaborations with suppliers, customers, and, finally, competitors. These arguments are tested on the R&D collaborations undertaken by a sample of 781 manufacturing firms during 1998–2002. The tests find that R&D collaborations with suppliers have the highest positive impact on product innovation, followed by collaborations with universities. Surprisingly, R&D collaborations with customers do not appear to affect product innovation, and collaborations with competitors appear to harm it. Moreover, the positive influence of R&D collaborations with universities and suppliers is sustained over the long‐term, but the negative influence of R&D collaborations with competitors is, fortunately, short‐lived. These findings indicate that ease of knowledge access, rather than breadth of knowledge, appears to drive the success of R&D collaborations for product innovation. R&D collaborations with suppliers or universities, which are characterized by relatively easy knowledge access, have a positive influence on product innovation, whereas R&D collaborations with customers or competitors, which are characterized by reduced ease in knowledge access, are not related or are even negatively related to product innovation. Moreover, to achieve product innovation with the help of R&D collaborations, it appears that the collaboration must first have mechanisms in place to facilitate the transfer of knowledge; once these are in place, it is better if the partner has a relatively narrow knowledge base. Thus, while R&D collaborations with both suppliers and universities are positively related to product innovation, the narrow knowledge base provided by collaborations with suppliers appears to have a larger positive impact on product innovation than the wider knowledge base provided by collaborations with universities. These arguments and findings are important and novel. The paper is one of the first to theoretically explain and empirically show that various types of collaborations have a differential influence on product innovation. It goes beyond previous literature by providing a theoretical logic for ranking the likely impact of types of collaborations on product innovation. The study also suggests to managers to carefully select the partners for their firms' R&D collaborations. Collaborations with suppliers appear to be the most promising for product innovation, followed by collaborations with universities, whereas collaborations with competitors may be detrimental to product innovation.     

Joint learning in R&D collaborations and the facilitating relational practices

The present study considers joint learning as a relational dynamic capability and examines the role of relational practices as enablers of joint learning in R&D collaboration between suppliers and their customers. The study applies a qualitative comparative case method to analyze seven dyadic cases, selected based on a quantitative dataset and cluster analysis. Our results indicate that in dyadic relationships, firms would benefit from developing practices related to relational investments, relational structures, and relational capital that facilitate joint learning and yield collaborative advantages from R&D interactions. This paper contributes to the existing literature on joint learning in R&D collaborations by defining joint learning as a relational dynamic capability and by focusing on the practices that facilitate it in R&D collaboration.     

Social capital and innovation in R&D teams: the mediating roles of psychological safety and learning from mistakes

The relationship between social capital and R&D team innovation has received increasing attention in the literature. However, little is known about the mechanisms between the two. This study aims to narrow the gap by investigating the mediating roles of psychological safety and learning from mistakes between the three dimensions of social capital and innovation at team level. Our sample comprised 151 R&D teams with 585 members from nine Chinese high‐tech companies. The results showed that psychological safety and learning from mistakes (LFM) partially mediated the relationship between the structural and cognitive capital and innovation in R&D teams, and fully mediated the relationship between the relational capital and innovation in R&D teams. We further discussed subsequent managerial implications and future research directions.     

Joining Forces or Going It Alone? On the Interplay among External Collaboration Partner Types,Interfirm Governance Modes,and Internal R&D

This paper adds to the emerging literature stream advocating a contingency view on open innovation. Drawing on the relational view of the firm, this study sheds light on the complex interplay among collaboration partner types (market‐ and science‐focused innovation partners), governance modes (informal, self‐enforcing and formal, contractual collaboration governance), and internal research and development(R&D). More specifically, it is proposed that the use of governance modes tailored to both the characteristics of each innovation partner type and the specific innovation objectives pursued by the focal firm (incremental and radical new product development) can increase the payoff from innovation collaboration. Moreover, appropriate collaboration governance is expected to reduce the focal firm's vulnerability to possible negative side effects often assumed to be associated with the simultaneous pursuit of external collaboration and internal R&D, among which most notably the not‐invented‐here (NIH) syndrome. Cross‐industry evidence from 2502 German firms underlines the critical role of collaboration governance—a contingency factor that is at the heart of the relational view, yet has remained surprisingly absent from the open innovation debate so far.     

Non‐R&D innovation and firms’ new product performance: the joint moderating effect of R&D intensity and network embeddedness

Non‐R&D innovation increasingly plays a critical role in explaining firms’ new product performance. Yet, there has been little research on the consequences and contingent mechanisms of non‐R&D innovation for firms embedded in collaborative network environments. To address this research gap, we investigated a conceptual framework of non‐R&D innovation using data drawn from Chinese manufacturing firms. First, we found that non‐R&D innovation positively affects firms’ new product performance. Second, we discovered that high R&D intensity positively strengthens the impact of firms’ non‐R&D innovation on new product performance. Third, we provided critical analysis of the role of non‐R&D innovation in promoting new product performance, accomplished by enhancing R&D investment while simultaneously improving the degree of network embeddedness. Our findings extend both the non‐R&D innovation literature and open innovation literature while providing managers with several key recommendations.     

Why and How Combining Strong and Weak Ties within a Single Interorganizational R&D Collaboration Outperforms Other Collaboration Structures

The purpose of this paper is to demonstrate why and how an ambidextrous interorganizational R&D collaboration outperforms other collaboration structures in the creation of innovation. This research effort contributes to a growing stream of research in social network theory suggesting that the contradictory theories of the strength of weak ties and weak network structures on the one hand and the theory of strong ties and closed network structures on the other have a mutually reinforcing effect on innovation outcomes if combined rather than considered separately. An in‐depth exploratory single case study approach within an innovatively organized national R&D collaboration allowed giving further evidence for such a superior innovation performance and for this research to contribute to theory by demonstrating why and how such a combination may lead to higher innovation output and how this effect can be actively reinforced. It is suggested that the combination of strong and weak ties should occur at the individual rather than at the project or firm level. The authors distinguish between the additive effects of the respective innovation benefits of strong and weak ties, a positive interaction effect in the portfolio of dyadic ties of an individual and a second multilevel interaction effect of weak ties embedded in the ambidextrous network structure. Referring to previous empirical findings, intellectual property regulation and structural interdependency between network members showed a higher impact than trust with regard to leveraging weak ties and are important sources for achieving the multilevel interaction effect. Managerial implications of this research are that a large network will outperform several smaller, independent networks given that the right structure and processes are in place. Direct implications for the architecture of an ambidextrous R&D collaboration are discussed, and a framework for a new form of technology R&D collaboration called “semi‐open organization” is presented, which places itself between the extremes of traditional R&D in closed organizations and completely “open innovation” approaches.     

Patterns of international R&D cooperation for new product development: the Olivetti multimedia product

Abstract
The aim of the paper is to identify a number of different patterns of international R&D cooperation during the initial phases of the product development process. This is a case-study of new product development based on the work of the Olivetti Multimedia Laboratory in Pisa, how it set up its own pattern of multinational collaboration in the idea generation and pre-competitive phase; how, in turn, this collaboration led to new R&D collaboration agreements to satisfy specific problem-solving requirements connected with the confirmation of a dominant design, though limited to a certain extent by previous agreements between Olivetti and other firms; the role played by marketing in the choice of alternative solutions. Finally, in the product implementation phase, the emergence of a defined technological paradigm leads to a highly competitive environment, where R&D collaboration is increasingly directed towards multifunctional requirements (R&D, manufacturing, marketing) within a strategic network of alliances that involves large sized companies, start-up firms, industrial and university research units.     

Toward the development of benchmarking tools for R&D project management

This paper presents an audit model for the process of R&D project management that can be used to check the robustness and repeatability of processes and provide a template for internal and external benchmarking. The intention is to offer a 'fine-grained' model focusing rather closely on the R&D activities within the broader innovation process, thus complementing the more widely based innovation audit models that already exist.
Based on field-work in six business units in ICI and five companies from other industries, the paper sets out three major variants of the R&D project management process. These variants reflect the fact that R&D projects take place in different circumstances and have different objectives.     

University‐industry collaboration and front‐end success: the moderating effects of innovativeness and parallel cross‐firm collaboration

Collaboration with science‐based and/or market‐based partners is a promising means for firms’ R&D groups to leverage complementary expertise and resources to generate innovative results. However, R&D managers face the dilemma which partner type to choose in different innovative contexts and whether to focus on one partner type or to integrate both types in early stage R&D. Using survey data from 166 heads of R&D groups, this study investigates university–industry collaboration’s impact on front‐end success depending on the degree of innovativeness and the interaction with other industry partners. The results confirm an overall positive relationship between university–industry collaboration and front‐end success. However, innovativeness increases complexity in this relationship. Parallel collaboration with firms and universities can have a mixed impact on front‐end success depending on the degree of innovativeness. This simultaneous collaboration with firms and universities strengthens front‐end success for more radical innovations, while parallel collaboration activities for more incremental innovations do not necessarily strengthen front‐end success. These findings imply that both collaboration types should be used simultaneously in the front end of radical innovation and that firms could reduce complexity by focusing on either firms or universities as partners for incremental innovations.     

A model of value assessment in collaborative R&D programs

This study examines the tasks, processes, and frameworks central to performance assessment in collaborative research organizations. The domain of the study is the partnered learning approach to research and development (R&D) management. The empirical results highlight relationships between context (center scale) and performance (value perceived by industry sponsors) in such R&D collaborations. Insights from this research are broadly applicable to the maintenance of alliances among firms involved in collaborative R&D and are generalizable to that context. Data gathered from a national population of 58 National Science Foundation (NSF) sponsored centers over a 3-year period reveal significant evolutionary patterns in the development of collaborative relationships. Successful industry university consortia leverage four core process relationships: (1) the creation of research capacity yielding advances in process and product knowledge; (2) technology transfer behaviors within the participants' organizations; (3) participant satisfaction with the outcomes; and (4) the continuity of industry sponsor support, i.e., commitment to the collaboration.     

Innovation as response to emissions legislation: revisiting the automotive catalytic converter at Johnson Matthey

Can environmental legislation spur innovative response? This case describes the development of the automotive catalytic converter (ACC) at Johnson Matthey (JM), a precious metals company that entered the automotive industry as a component provider. The market was unfamiliar to JM and highly competitive, but in the 1970s the US Environmental Protection Agency (EPA) introduced standards for emissions control by automotive companies well ahead of current practice. JM responded to the prospect of market demand for a technology that could meet the regulations. The EPA policy of technology ‘forcing’ stimulated collaboration for innovation among companies from a variety of industries. Our case evidence shows that the key innovator, JM, achieved its breakthrough as a result of proactive R&D management by the product champion together with sustained corporate support at a high level and partnership strategies.     

Influences of cross-functional collaboration and knowledge creation on technology commercialization: Evidence from high-tech industries

Technology commercialization (TC) contributes to maintaining the competitive advantage of high-tech firms, but although researchers have established that product innovation and new product development are enhanced by cross-functional collaboration and organizational knowledge activities, this may not be the case for TC. Drawing on the knowledge-based view and the influence of cross-functional collaboration, the main goal of this study is to unravel the relationships among cross-functional collaboration, knowledge creation and TC performance in the high-tech industry context. Empirical findings from our survey of 203 marketing and R&D managers and employees in Taiwanese high-tech companies indicate that cross-function collaboration reveals fresh opportunities for creating knowledge and commercializing technologies. Our results also suggest that knowledge creation plays an important role in TC performance by partially mediating the relationship between cross-functional collaboration and TC performance. The contributions of this study provide new insights into industrial marketing literature by proposing a cross-functional collaboration-enabled TC model that takes into account the effect of knowledge creation.     

Interorganizational collaboration strategies and innovation abandonment: The more the merrier?

Investments in innovation activities involve uncertainty. Abandonments of innovative projects are frequent and can entail great losses. Interorganizational collaboration can help a firm to leverage and complement its own competencies and technologies, contrasting the factors that may cause the abandonment of innovation activities. This article shows that firms collaborating with a wider network of external partners to conduct their innovation activities are less likely to abandon them. The article also analyses how different categories of partners among customers & suppliers, competitors, consultants & private R&D institutions, universities & public R&D institutions are associated with the risk of innovation abandonment. Finally, the results show that international collaborations are more likely associated with innovation abandonment than domestic ones. Strategic and theoretical implications are drawn.