Coordination Approaches to Foster Open Innovation R&D Projects Performance

https://doi.org/10.1016/j.jengtecman.2020.101603Get rights and content

Abstract

Open innovation R&D projects involve teams from different organizations, which may affect the team’s ability to communicate since people are from different locations and companies, which may have different priorities, procedures, goals, and expectations. To succeed in the project, the team needs coordination mechanisms that facilitate teamwork. However, in the open innovation R&D projects, the coordination approach that fosters project performance is not evident. Using structural equation modeling analysis (PLS-SEM) with a sample of 50 open innovation R&D projects, we assessed the relationship with the project performance of two coordination approaches (organic or mechanistic) focusing on the communication strategies used. We find evidence that both organic and mechanistic approaches are positively associated with performance, which means that each approach has its role in fostering the project's performance. Consequently, such projects benefit both from open, continuous, and informal communication flow and from a more formal procedure of sharing information through a clear definition of project objectives, evolution, and challenges. This research extends prior research on coordinating teamwork for an open innovation setting.

Introduction

Open innovation has been gaining attention as a way to face an increasing level of complexity in innovation projects (Stanko et al., 2017). Research in the field emphasizes the need to develop collaborative projects with external parties to access new and complementary knowledge distributed over different types of actors (Chesbrough, 2003), such as universities, suppliers, research institutes, and consumers. An open innovation project is a temporary organization where two or more partners, economic independently, share R&D activities (Hagedoorn, 2002). However, while potential benefits of open innovation are clear and demonstrated through a positive association with performance (Belderbos et al., 2004; Chen et al., 2016; Faems et al., 2005), literature also suggests that the effects of open innovation in performance are not always positive (Du et al., 2014a; Laursen and Salter, 2006), what encourages studies that help to identify improvement opportunities in such projects.

Literature suggests that the different findings in the relationship between open innovation and performance may be due to the fact that studies in open innovation are generally highly aggregated studies, which means that their focus is mainly at the firm level, what limits a more fine-grained understanding of project-level issues (Vanhaverbeke et al., 2014). Nevertheless, some managerial issues are being investigated at the project level. For instance, prior research showed that open innovation projects performance is influenced by how the projects are managed, such as the level of formality applied in the project management moderated by the type of partner (Du et al., 2014a) and the configuration of project management practices adopted (Barbosa et al., 2020). This discussion resonates with classical studies on organizing the company to innovate (Burns and Stalker, 1961). However, these studies also expand Burns and Stalker (1961) discussion, encompassing the complex setting of open innovation, which goes beyond organizing innovation within company boundaries. Open innovation R&D projects involve sharing knowledge and tasks with external partners demanding coordination mechanisms to foster team integration in inter-organizational settings.

Literature has focused on coordination mechanisms that most favors new product development team integration when team members from the same company are in several locations, not under the same roof. In this journal, Péréa and von Zedtwitz (2018) have set the basis for the discussion of team integration at distance. Nevertheless, literature has neglected a more complex type of integration, when team members are not only in different locations but also in different companies.

A coordination mechanism is “any administrative tool for achieving integration among different units” (Martinez and Jarillo, 1989, p. 490). It varies in a spectrum of more and less bureaucratic approaches (mechanistic and organic, respectively) (Chenhall, 2003). An organic coordination approach relies on less formal rules, open channels, free flow of communication, is more flexible and has informal controls. By contrast, mechanistic coordination relies on formal rules and standardized operation routines (Chenhall, 2003; Péréa and von Zedtwitz, 2018).

Classical literature on organizational theory suggests that the mechanistic approach is appropriate for stable environments, whereas organic is relevant for dealing with uncertainty settings (Burns and Stalker, 1961). However, in coordinating teams in R&D settings, new contingencies arise, such as team distribution (Gassmann and Zedtwitz Von, 2003; Péréa and von Zedtwitz, 2018). Literature suggests that in distributed teams knowledge sharing is constrained and processes are less efficient due to lower social interaction (Bierly et al., 2009), which challenge the organic coordination approach as team members are less likely to communicate spontaneously due to the limitations imposed by physical distance (Cummings et al., 2009; Espinosa et al., 2007). However, contrary to this view, more recent findings indicate that the more the team is distributed, the better it is integrated when the organic coordination approach is used (Péréa and von Zedtwitz, 2018), suggesting that an organic approach is more suitable for innovation projects, even in distributed teams. Moreover, the organic approach is associated with higher project performance in exploratory innovation (Ylinen and Gullkvist, 2014). Therefore, these recent studies show evidence that the organic coordination approach is suitable for a distributed team in innovation projects. However, the literature does not explore whether these findings can be extended to open innovation R&D projects since these projects share characteristics with these previous studies (distributed teams in the R&D settings), but they are also developed among different companies.

When developed with different companies, the dissimilarities between partners have been considered a contingency factor, which Du et al. (2014a) assessed through two types of partners (market-based and science-based partners) based on their orientation to scientific or market knowledge. With these dissimilarities, partners may focus on different aspects of the collaboration and may have different working methods, which may affect the success of the collaboration (Brocke and Lippe, 2015; Estrada et al., 2016), and thus, literature has been looking for enhancing its understanding on how to improve the success of open innovation projects with a dissimilar partner (Barbosa et al., 2020; Chen et al., 2016; Du et al., 2014a; Estrada et al., 2016).

Given this background, this study explores the relationship between coordination approaches and project performance in the context of an open innovation R&D project, involving teams of different companies. That is different locations and different companies. In this study, coordination approaches, whether mechanistic or organic, were described in terms of the communication strategies used, in which less bureaucratic communication is associated with the organic coordination, and more bureaucratic is associated with the mechanistic one.

The following research question guides the study: Which coordination approach enhances project performance of open innovation R&D projects?

Following classical literature that associates the organic coordination approach to uncertainty settings, there is an expectation that this approach might overcome the mechanistic one also for open innovation projects. This expectation is justified by the fact that organic coordination focus on mechanisms that can be beneficial to foster knowledge exchange, such as the open and continuous flow of communication, which is a core issue in the knowledge-intensive setting of open innovation projects, especially in R&D. In such projects, it can be complicated, if not impossible, to foresee and plan the project process (Loch et al., 2008). Moreover, a decision to engage in the complexity and risks of open innovation project relies, among other factors, on the opportunity of leveraging project output success by the access and recombination of knowledge from complementary resources (Kogut and Zander, 1992; Sammarra and Biggiero, 2008). However, recent research also posits that rules and procedures might not be as detrimental to innovation efforts as previously assumed (Calantone et al., 2010; Ylinen and Gullkvist, 2014). Consequently, we did not know the effect of these coordination mechanisms in the performance of open innovation projects, and so it proved to be a promising field to investigate.

This research's primary contribution is to provide an understanding of open innovation management at a more fine-grained level, which is the project-level. Usually, open innovation is accessed at the organizational level. Consequently, how to effectively manage the project remain less explored, especially in the R&D settings (Vanhaverbeke et al., 2014). This level is relevant in the sense that project-level coordination strategies have an essential role in providing the execution mechanisms of the collaboration as companies collaborate through projects. For that, coordination mechanisms are articulated to help the project achieve its purpose on a particular schedule, cost, and quality.

Moreover, we assess coordination approaches through the communication strategies adopted, as effective communication is one of the success factors of open innovation projects (Barnes et al., 2006, 2002; Dietrich et al., 2010). Communication is the vehicle through which team members share information that is critical to the successful implementation of the project (Pinto and Pinto, 1990). While communication within team members is an elementary success factor in innovative projects, it can be applied in project management in a more or less bureaucratic approach (Burns and Stalker, 1961; Péréa and von Zedtwitz, 2018). We discuss the communication strategies in the open innovation setting.

Section snippets

Communication throughout open innovation projects

Successful communication among team members is an elementary component to achieve project objectives (Griffin and Hauser, 1992), especially in the collaborative R&D context (Katz and Allen, 1982). It is through communication that knowledge is exchanged, information is shared, and tasks are coordinated. Accordingly, the lack of communication has been cited as one of the sources of coordination difficulties in innovative projects (Hoegl and Gemuenden, 2001; Péréa and von Zedtwitz, 2018).

Usually,

Method

In this study, we empirically examine the relationship of open innovation R&D project performance and coordination mechanisms, specifically the ones related to communication strategies. Moreover, we assess the moderating effect of the presence of science-based partners on the project's team (Fig. 1).

The latent variables in this model were measured with formative indicators, which are multidimensional entities. For the independent variables (latent constructs), the dimensions or indicators of

Sample Characteristics

R&D professionals from diverse industries answered the survey, most being from Pharmaceutical and Healthcare. Each professional was asked to answer about the last open innovation project that was developed with at least one external partner. From the 50 projects, 29 projects were developed with science-based partners. Most of the projects were developed by European multinationals in their headquarter or subsidiary. Most of the projects were applied research, but some of them involved more than

Discussion

This study aimed to contribute to a better understanding of communication strategies in coordinating open innovation R&D projects, including assessing the role of heterogeneous partners in moderating the relationship between coordination approaches and project performance.

Our results enable the discussion about the dichotomy between two coordination approaches in terms of which communication strategy use. More specifically, we found that both organic and mechanistic coordination approaches

Conclusion

This study indicates that both mechanistic and organic coordination approaches for communication strategies may have a positive relation to project performance in open innovation R&D projects. This result can be interpreted in some ways. First, since literature presents robust evidence relating to flexibility and organic structures, we could think of different types of open innovation R&D projects, some being quite predictable, more suitable for mechanistic approaches. Second, even very open,

References (59)

  • J.F. Hair et al.

    Assessing measurement model quality in PLS-SEM using confirmatory composite analysis

    J. Bus. Res.

    (2020)
  • F.Y.Y. Ling et al.

    Key project management practices affecting Singaporean firms’ project performance in China

    Int. J. Proj. Manag.

    (2009)
  • A. Neely et al.

    Performance measurement system design: should process based approaches be adopted?

    Int. J. Prod. Econ.

    (1996)
  • C. Péréa et al.

    Organic vs. Mechanistic coordination in distributed New Product Development (NPD) teams

    J. Eng. Technol. Manag.

    (2018)
  • M.B. Pinto et al.

    Project team communication and cross-functional cooperation in new program development

    J. Prod. Innov. Manag.

    (1990)
  • F. Todtling et al.

    Do different types of innovation rely on specific kinds of knowledge interactions?

    Technovation

    (2009)
  • M. Ylinen et al.

    The effects of organic and mechanistic control in exploratory and exploitative innovations

    Manag. Account. Res.

    (2014)
  • D. Archibugi

    Patenting as an indicator of technological innovation: a review

    Sci. Public Policy

    (1992)
  • B. Aschhoff et al.

    Empirical evidence on the success of R&D cooperation — happy together?

    Rev. Ind. Organ.

    (2008)
  • A.P.F.P.L. Barbosa et al.

    Configurations of project management practices to enhance the performance of open innovation R&D projects

    Int. J. Proj. Manag.

    (2020)
  • P.E. Bierly et al.

    The moderating effects of virtuality on the antecedents and outcome of NPD team trust

    J. Prod. Innov. Manag.

    (2009)
  • M.G. Brown et al.

    Measuring R&D productivity

    DeReMa

    (1988)
  • T. Burns et al.

    The Management of Innovation

    (1961)
  • R.J. Calantone et al.

    Inconclusive innovation ‘returns’: a meta-analysis of research on innovation in new product development

    J. Innov. Manag.

    (2010)
  • Y. Chen et al.

    The interaction between internal R&D and different types of external knowledge sourcing: an empirical study of Chinese innovative firms

    RD Manag.

    (2016)
  • H. Chesbrough

    Open Innovation: the New Imperative for Creating and Profiting From Technology

    (2003)
  • H. Chesbrough

    Engaging with startups to enhance corporate innovation

    Open Innovation Results

    (2019)
  • J.N. Cummings et al.

    Crossing Spatial and Temporal Boundaries in Globally Distributed Projects: A Relational Model of Coordination Delay

    Inf. Syst. Res.

    (2009)
  • P. Dasgupta et al.

    Toward a new economics of science

    Res. Policy

    (1994)
  • Cited by (13)

    View all citing articles on Scopus

    This work was supported by the FAPESP, Fundação de Amparo à Pesquisa do Estado de São Paulo [grant number: 2015/26662-5 and 2019/16948-0].

    View full text