21-PM1-02: ST8.4 - Open Innovation in SMEs
This track aims to examine current research on open innovation (OI) in small and medium-sized enterprises (SMEs). In fact, because OI has been mainly developed for large companies, its definition and its identifying characteristics do not always take into account the contexts and specific characteristics of SMEs (small and medium-sized enterprises). Indeed, SMEs find it challenging to engage in OI. They are sometimes hampered by their inherent limitations, such as scarcity of resources, weakly developed innovation processes, and unstructured internal capabilities. On the other hand, they are less bureaucratic, are more flexible in decision-making, take more risks, and often have specialized knowledge in a specific market. As a result, some SMEs manage to meet the challenges of OI while others do not.
We want to explore the specific characteristics of OI in SMEs (practices, tools, players, etc.) and to identify the determinants that enable SMEs to overcome its limitations and innovate openly. Although there is some recent research on OI within the SMEs, this field is still largely unexplored. Little is known about the characteristics and determinants of OI in such companies Thus, there have recently been new calls to clarify the concept in the context of SMEs, and this proposition will be a response to these calls.
Exploring SMEs’ open innovation practices diversity in different countries.
Open Innovation (OI) concept has been studying for a long time in large firms, neglecting SMEs (Kirschbaum, 2005; Ollila & Elmquist, 2011). Even if these entities were excluded from the mainstream discussion on OI, this model seems to be especially relevant for SMEs, but only if it is fully understand.
Several researchers have identified OI as a lever strategy to overcome the typical weaknesses of SMEs (Van de Vrande, De Jong, Vanhaverbeke, & De Rochemont, 2009; Verbano, Crema, & Venturini, 2015), such as resource constraints, lack of competences (Bougrain & Haudeville, 2002; Dahlander & Gann, 2010; Lee, Park, Yoon, & Park, 2010; Rahman & Ramos, 2010; Wynarczyk, Piperopoulos, & McAdam, 2013). Unlike large companies generally more rigid, SMEs’ flexibility and unbureaucratic nature make them particularly suited to implement OI practices, thus increasing the probability of adopting the approach effectively. (Dufour & Son, 2015; González-Benito, Muñoz-Gallego, & García-Zamora, 2016; Parida, Westerberg, & Frishammar, 2012).
Based on research work addressing OI practices, a list of eleven OI practices was obtained: open-source, user involvement, crowdsourcing, know-how acquisition, joint R&D, research consortium, in-sourcing, licensing-out, alliances, venture and spin-off.
Open innovation paradigm was initially based on large high-tech companies (Chesbrough, 2006). In recent years, research on OI in SMEs has quickly grown, and shows that OI do not have a universal character. Same models cannot be applied to both small and large entities (Stanisławski & Lisowska, 2015).
Our exploratory study shows that no OI practice is mostly adopted and this practices differ from one country to another. The addressed question is are there some socio-economic and scientific characteristics that influence open innovation practices adoption?
To determine how practices are correlated to some criteria of innovation country performance used to estimate the Global Innovation Index, we applied multiple linear regressions. First of all, we begin by identifying the more correlated criteria from those identified. Then we made a correlation test to eliminate three variables and keep the others. The obtained correlation matrix was also used to evaluate the dependency between innovation country performance variables and OI practices.
Previous studies focused on OI practices adopted by SMEs in Korea (Ahn et al., 2015), Germany (Van de Vrande et al., 2009), UK (Cosh & Zhang, 2011) and Italy (Bigliardi & Galati, 2016). These studies focus on seven practices (in-sourcing, joint R&D, M&A, user involvement, licensing-out, open-sourcing and know-how acquisition) frequently observed with positive effects (Mazzola, Bruccoleri, & Perrone, 2012).
As already mentioned, none of these seven open innovation practices is mainly adopted by these four countries. Also, the correlation matrix evinces :
• In-sourcing is influenced by none of this criteria.
• Joint R&D and know-how acquisition are influenced only by the number of patents
• Open-source is affected only by working population with higher education.
• M&A is not correlated to working population with higher education.
• User-involvement is independent of working population with higher education.
The multiple linear regression allows understanding how some country’s characteristics affect adoption Open Innovation practices adoption.
Contribution to Scholarship
By this study, we confirmed that OI is not a universal character. Its adoption seems to be affected by socio-economic and scientific characteristics of the environment in which the company operates. To fully understand the Open Innovation adoption, it is necessary to consider external characteristics
Contribution to Practice
Our results highlight the importance to consider external characteristics to understand fully the OI adoption. This study can help practionner to guide their strategic choices regarding the implementation of open innovation practices.
To have a better understanding of open innovation in SMEs, this study aims to analyse the open innovation practices adoption by SMEs by proposing an analytical analysis based on socio-economic and scientific characteristics.
Bougrain, F., & Haudeville, B. (2002). Innovation, collaboration and SMEs internal research capacities. Research Policy, 31(5), 735‑747.
Chesbrough, H. (2006). Open business models : How to Thrive in the New Innovation Landscape.
Dahlander, L., & Gann, D. (2010). How open is innovation? Research Policy, 39(6), 699‑709.
Dufour, J., & Son, P.-E. (2015). Open innovation in SMEs : towards formalization of openness. Journal of Innovation Management, 3(3), 90‑117.
González-Benito, Ó., Muñoz-Gallego, P., & García-Zamora, E. (2016). Role of collaboration in innovation success: differences for large and small businesses. Journal of Business Economics and Management, 17(4), 645‑662.
Kirschbaum, R. (2005). Open innovation in practice. Research Technology Management, 48(4), 24‑28.
Lee, S., Park, G., Yoon, B., & Park, J. (2010). Open innovation in SMEs-An intermediated network model. Research Policy, 39(2), 290‑300.
Ollila, S., & Elmquist, M. (2011). Managing open innovation: exploring challenges at the interfaces of an open innovation arena. Creativity and Innovation Management, 20(4), 273‑283.
Parida, V., Westerberg, M., & Frishammar, J. (2012). Inbound Open Innovation Activities in High-Tech SMEs: The Impact on Innovation Performance. Journal of Small Business Management, 50(2), 283‑309.
Rahman, H., & Ramos, I. (2010). Open Innovation in SMEs: From closed boundaries to networked paradigm. Informing Science and Information Technology, 7(4), 471‑487.
Stanisławski, R., & Lisowska, R. (2015). The Relations between Innovation Openness (Open Innovation) and the Innovation Potential of SMEs. Procedia Economics and Finance, 23(October 2014), 1521‑1526.
Van de Vrande, V., De Jong, J. P. J., Vanhaverbeke, W., & De Rochemont, M. (2009). Open innovation in SMEs: Trends, motives and management challenges. Technovation, 29(6‑7), 423‑437.
Verbano, C., Crema, M., & Venturini, K. (2015). The Identification and Characterization of Open Innovation Profiles in Italian Small and Medium-sized Enterprises. Journal of Small Business Management, 53(4), 1052‑1075.
Wynarczyk, P., Piperopoulos, P., & McAdam, M. (2013). Open innovation in small and medium-sized enterprises: An overview. International Small Business Journal, 31(3), 240‑255.
Open innovation practices flexibility in a Thai food manufacturing SME
1The Institute for Knowledge and Innovation, Bangkok University, Thailand; 2Institut Mines-Télécom Business School
During the past decades, Food and Beverage Industry (FBI) value chain's actors faced an increasingly competitive race to better meet customer demands, shortened product life cycles & time-to-market and still differentiate themselves from their competitors (Bellairs, 2010).
This growth in velocity and volatility is complexified by the difficulties to meet simultaneously various institutional requirements (Sarkar & Costa, 2008) e.g. growing attention is needed to meet the Thai Food Safety Regulation institution's demands.
Therefore, the driving forces of FBI SMEs’ innovation have evolved through the development of new internal and external innovation dynamics. SMEs implement new product development (NPD) processes and create and/or apply creative technological solutions. If these processes were first developed in proprietary logic, external technologies, skills, and knowledge are more and more leveraged using collective innovation strategies (Traitler et al., 2011; Saguy & Sirotinskaya, 2014; Bigliardi & Galati 2016; Vanhaverbeke, et al. 2018; Bigliardi, 2019). This innovation logics’ paradigm shift (Moore, 1993; Chesbrough, 2003) is of particular importance for SMEs which cannot control all the required resources to innovate and are therefore forced to partner with complementary organizations (Capitanio et al., 2010).
If OI logics in SMEs are now better illustrated (Vanhaverbeke, et al. 2018), OI practices implemented in FBI SMEs remain poorly understood. Height models of OI implementation have been proposed (Bigliardi & Galati, 2016) and, only one explores OI practices implemented by FBI SMEs (Bigliardi & Galati, 2013).
Is the theoretical food machinery framework model (Bigliardi & Galati, 2013) matching OI logics and practices observed empirically in a Thai FBI SME?
The food machinery framework model (Bigliardi & Galati, 2013) has been applied in a diachronic case study of one SME: Sahapan Century Co. Ltd. (SHC), a Thai food machinery company. OI practices, as defined by van de Vrande et al. (2009), are identified in a critical realist perspective among 76 NPD projects over a period of 5 years from 2012 to 2017. SHC is considered as the core actor in its network. Knowledge flows are analyzed by focusing on food recipes at the Lab-scale and Manufacturing-scale which are most of the time connected but can be achieved independently.
Non-structured interviews have been conducted with SHC executives and all the involved NPD partners. National Institutions, regulatory bodies e.g. Thai Food and Drug Administration, testing laboratories, distributors, wholesalers, retailers, and end consumers are considered as other suppliers.
To ensure 1) that the empirical data collected have been adequately analyzed and interpreted, and 2) that saturation has been reached, one series of interviews have been conducted every week over a period of 6 months. This process also allows to enrich progressively the data collected and to respect Pierce's ([1931-1935]) recursive loop refinement process and Bhaskar (2013) critical realist perspective.
OI logics are established using exchange flows. When OI is coupled, volumes of resources exchanged (recipe, tacit knowledge, explicit knowledge, technology, ingredients...) are considered to define the inbound or outbound dominance. OI practices associated with each NPD are qualified and classified using the typology of Van de Vrande et al. (2009) at the lab-scale and the manufacturing scale. When the observed practices didn’t match the typology, new categories have been created and characterized.
OI practices identified empirically reveal 14 different main categories: 7 in technology exploration and 7 categories in technology exploitation. Six additional OI practices have been added to van de Vrande’s et al. (2009) typology: 2 in technology exploration, 4 in technology exploitation.
Moreover, the food machinery framework model appears to be too generic to distinguish all the empirically observed combinations of OI practices. Therefore, 5 declinations of that model are proposed to better specify knowledge flows and their associated inter-organizational OI coupling mechanisms.
The case study reveals that the choice of OI practices depends on the type of partnerships and, the technological particularities of the recipe to develop.
Finally, the growing operational agility of the observed SME also demonstrated that his business model evolved from a food machinery company to an innomediary (Mele & Russo-Spena, 2015).
Contribution to Scholarship
The present case study aims at supporting OI logics and practices theorization and modeling in FBI SMEs. By entering the black box of operational routines recombination, this study helps 1) to characterize the generative mechanisms (and their associated triggering factors) involved in dynamic capabilities’ development (Teece et al., 1997) and 2) to understand how FBI organizations co-evolve their dynamic capabilities (Teece, 2017) to trigger the emergence of innovation ecosystems (Parisot et al., 2019).
Contribution to Practice
This empirical testing of 1) van de Vrande's et al. (2009) OI practices' typology and 2) the food machinery framework model (Bigliardi & Galati, 2013) contributes to a more fine-grained understanding of FBI SMEs coordination processes in their innovation ecosystems and, paves the way for further empirical characterization of yet unidentified OI generative mechanisms.
In FBI, innovation is increasingly led by ecosystems exploiting SME's creative ideas. To help organizations build or join these ecosystems, strategic management must move from description to prediction and, produce theoretical models able to support ecosystemic generative and activation mechanisms identification through empirical validation.
1-Bellairs, J., 2010. Open innovation gaining momentum in the food industry. Cereal foods world, Vol.55, n°1, p.4-6.
2-Bhaskar, R. (2013). A realist theory of science. Routledge.
3-Bigliardi, B. (2019). Open Innovation and Traditional Food. In Innovations in Traditional Foods (pp. 85-99). Woodhead Publishing.
4-Bigliardi, B., & Galati, F. (2013). Models of adoption of open innovation within the food industry. Trends in Food Science & Technology, Vol.30, n°1, p.16-26.
5-Bigliardi, B., & Galati, F. (2016). Open innovation and incorporation between academia and food industry. In Innovation Strategies in the Food Industry (pp. 19-39). Academic Press.
6-Capitanio, F., Coppola, A., Pascucci, S. (2010). Product and process innovation in the Italian food industry. Agribusiness, An International Journal, Vol.26, p.503–518.
7-Chesbrough, H. W. (2003). Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business Review Press.
8-Mele, C., & Russo-Spena, T. (2015). Innomediary agency and practices in shaping market innovation. Industrial Marketing Management, Vol.44, p.42-53.
9-Moore, J. F. (1993). Predators and prey: a new ecology of competition. Harvard business review, 71(3), 75-86.
10-Parisot, X., Isckia, T. and Vialle P. (2019). Entering the Black Box of Platform Orchestration: A metaphoric co-evolutionary framework for platform-based ecosystems. R&D management Conference, 17th-21st June 2019, Paris, France. Submitted.
11-Pierce, C.S., [1931-1935]. Collected Papers, Cambridge: Ed. Harvard University Press, Vol. 1-6.
12-Saguy, I. S., & Sirotinskaya, V. (2014). Challenges in exploiting open innovation's full potential in the food industry with a focus on small and medium enterprises (SMEs). Trends in Food Science & Technology, 38(2), 136-148.
13-Sarkar, S. & Costa, A.I. (2008). Dynamics of open innovation in the food industry. Trends in Food Science & Technology, Vol.19, n°11, p.574-580.
14-Teece, D. J. (2017). Dynamic capabilities and (digital) platform lifecycles. In Entrepreneurship, Innovation, and Platforms (pp. 211-225). Emerald Publishing Limited.
15-Teece, D.J., Pisano, G. & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic management journal, p.509-533.
Traitler, H., Watzke, H. J., & Saguy, I. S. (2011). Reinventing R&D in an open innovation ecosystem. Journal of food science, Vol.76, n°2, p.R62-R68.
16-Van de Vrande, V., De Jong, J. P., Vanhaverbeke, W., & De Rochemont, M. (2009). Open innovation in SMEs: Trends, motives and management challenges. Technovation, 29(6), 423-437.
17-Vanhaverbeke, W. et al. (Eds.). (2018). Researching Open Innovation in SMEs. World Scientific.
Servitization maturity - a novel contextual element of successful collaborative R&D innovation projects
University Cote d'Azur
This research is conducted within the specific context of French Pole SCS. These new industrial policies were implemented to settle clear objectives of reinforcement of specific geographic places within France via academic-industrial collaboration for technological purposes within collaborative innovation projects, and with the aim to impact market and society.
The boundaries between services and products are becoming blurred, where products are being assigned the characteristics of services through “servitization”, while services are taking on the characteristics of products via widespread use of mICT (Barret et al., 2008), where the concept of “a servitization solution” outlines the product/services complementarity and interchangeability (Araujo and Spring, 2006).
This raises a concern about the development and management of collaborative mICT servitization innovation projects, so that the four conditions enhancing innovation (Nahapiet and Ghoshal, 1998) become activated.
The successful outcomes and the management of collaborative innovation projects is approached essentially in terms of technology and from the perspective of structural antecedents of innovation (Uzzi, 1996; Anand and Khanna, 2000; Kale, et al., 2002; Hagedoorn, 1993; Ahuja, 2000; Stuart, 2000), while the activation of these mechanisms, becomes possible through a rotating leadership approach throughout the period of the project realisation (Davis and Eisenhardt, 2011).
The servitization literature raises key conditions related to the complexity and multidimensionality of the collaborative innovation processes within the servitization effort. However, it neither provides a clear understanding of how to perform these requirements, nor how they allow to activate the conditions suggested by Nahapiet and Ghoshal (1998).
“What makes some of the mICT collaborative servitization projects (mCIP's) successful in innovating mICT servitization solution?”
In other words, this research paper targets to show the variety of configurations of mCIP’s and explores the key elements responsible for successful realisation of mICT servitization within open innovation efforts.
Using a comparative multiple case study of 14 mCIP’s, firstly we described all projects in terms of their characteristics and results, and identified four different types within them.
Secondly, based on the abstractive process of open coding (Strauss&Corbin, 1998) adapted by Gioia et al. (2012) we identified key factors that explain the results of the projects in terms of servitization innovation for each type of mCIP’s.
Finally, we compared the results of analysis within each of types to improve our understanding of the role of the key factors of success.
We selected the most pertinent CIP’s of Pole SCS around mICT servitization. As a starting point, we collected extensive data about CIP’s originating within Pole SCS.
We were able to reunite the information about 419 CIP’s, referenced by Pole SCS over a seven-year time period of innovative activities. From this base we selected mCIP’s with formally declared objective of service development and with the availability of funds. Thus, we obtained 23 servitization mCIP’s from which 14 agreed to participate in our research.
In total, we conducted 43 interviews with the participants of these 14 projects. The interviews represent 46 hours and eight minutes of recordings; some 528 pages. The interviewing process was based on semi-structured interviews with open-ended questions searching for explanations of differences in results.
Our study provides empirical evidence that only a small number of projects resulted in servitization innovation. This emphasises the complexity of creating an innovative service in the mICT sector. Comparing and contrasting more and less well performing servitization projects suggests that higher performance, in terms of novel service development and positive impact on market and society requires more than top-down state policies for service development, or resources in terms of leadership and change management competencies. Rather, it also requires a real maturity of the idea of future services that should be a core of new industrial policies.
Contribution to Scholarship
First, the study enriches the current knowledge on contextual conditions regarding the role of antecedents of innovation (Uzzi, 1996; Anand and Khanna, 2000; Kale et al., 2002) by reaffirming their importance within open servitization innovation dynamics as only one of the critical elements of context. Indeed, all four types of servitization mCIP’s were launched with similar antecedents, but developed different collaborative efficiencies. The study introduces the concept “servitization maturity” as a novel key element of context.
Secondly, our study highlights that simultaneous innovation of technology and novel service development within servitization mCIP’s increases complexity and multidimensionality of service innovation processes. Actually, the idea of the service component of the servitization solution must be mature enough to allow a clear anticipation of value creation which reinforces the initial engagement and the collaboration efficiency of knowledge combination including service knowledge (Storey et al., 2016).
Contribution to Practice
From a practical prospective, the study shows that, in reaction to opportunities and requirements of local innovation policies, numerous projects might emerge with formally declared servitization objectives, and a real engagement in service development. However, such initiation of policies is not sufficient to generate value unless oriented towards servitization maturity. To be efficient, these policies should be focussed on the support of project actors in both accessing and developing specific market knowledge and competencies related to the development of service maturity as well as a shared servitization framework and a market-oriented engagement.
The focus of the R&D Management Conference 2019 on the challenges of open innovation and co-creation on the cross of research, industry and society are the key issues of this research, namely: open mICT and service innovation based on academic-industrial collaboration with aiming to impact both market and society.
Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: a longitudinal study. Administrative Science Quarterly, 45, pp.425–455.
Anand, B. N., and Khanna, T. (2000). Do firms learn to create value? The case of alliances. Strategic Management Journal, 21, pp. 295–315.
Araujo, L. and Spring, M. (2006). Services, products, and the institutional structure of pro- duction. Industrial Marketing Management, 35(7), 797–805.
Barret M., Dvidson E., Middleton C. and DeGross J.I. (2008) – Information technology in the service economy: challenges and possibilities for the 21st century. International Federation for Information Processing, Spindler Series. New York.
Davis, J. P. and Eisenhardt, K. M. (2011). Rotating leadership and collaborative innovation: Recombination processes in symbiotic relationships. Administrative Science Quarterly, 56(2), pp.159-201.
Gioia, D. A., Corley, K. G., Hamilton, A. L. (2012). Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology, Organizational Research Methods, published on line http://orm. sagepub.com, pp.1-17.
Hagedoorn, J., (2003). Sharing intellectual property rights - an exploratory study of joint patenting amongst companies, Industrial and Corporate Change, 12(5), pp. 1035- 1050
Kale, P., Dyer, J. H., Singh, H. (2002). Alliance capability, stock market response, and long-term alliance success: The role of the alliance function. Strategic Management Journal, 23, pp.747–767.
Nahapiet, J., and Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. The Academy of Management review 23(2), pp. 242-266.
Strauss, A. and Corbin, J. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory. Thousand Oaks, CA: Sage.
Stuart, T. E. (2000). Interorganizational alliances and the performance of firms: A study of growth and innovation rates in a high-technology industry. Strategic Management Journal, 21, pp. 791–811.
Uzzi, B. (1996). The sources and consequences of embeddedness for the economic perfor- mance of organizations: The network effect. American Sociological Review, 61, pp. 674–698.