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Session Overview
Session
21-PM2-02: ST8.4 - Open Innovation in SMEs
Time:
Friday, 21/Jun/2019:
2:45pm - 4:15pm

Session Chair: Marie-Anne Le Dain, Grenoble INP Industrial Engineering and Management – G-SCOP Lab
Session Chair: Carène Tchuinou Tchouwo, Université Laval
Location: Amphi Sauvy

Session Abstract

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.


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Presentations

What do we know specifically about open innovation in SMEs? A descriptive review

Carène Tchuinou Tchouwo, Diane Poulin

Université Laval, Canada

Context

In recent years, Open Innovation (OI) has become a popular concept in the innovation literature. This concept works in two directions: on the one hand, a company opens itself up to knowledge from outside actors; on the other hand, it deliberately makes commercially useful internal knowledge available to the market.

Literature

Previous studies have focused on OI in large R&D-intensive enterprises where external technological knowledge is used to strengthen internal research (outside-in) and internal knowledge is outsourced to generate additional funds (Chesbrough, 2003). In these studies, OI takes various forms depending on the direction of knowledge flows (Chesbrough, 2006) and is primarily technology-driven.

More recently, researchers have been looking at OI in SMEs and have begun to explore its characteristics and determinants in that context (Van de Vrande et al., 2009). Indeed, some studies have shown possible advantages for SMEs, in particular an improved capability to cope with the limitations of being a small company and lacking resources and skills. However, other studies have shown possible disadvantages. SMEs are highly sensitive not only to the costs of OI but also to its risks, and such risks may hinder their development. Thus, SMEs are an interesting context for study of OI.

Literature Gap

Despite recent interest in OI within SMEs, research remains limited and studies are scattered or sometimes contradictory.As a result, there have lately been calls for further research and for a conceptual framework to consolidate and bring together all relevant OI studies on SMEs.This research is an answer to these calls.

Research Questions

We reviewed recent studies on OI in SMEs to explore its specific characteristics and determinants that enable SMEs to innovate openly. Our research questions were: What are the characteristics and the main determinants of OI in SMEs?How do these different elements relate to each other within an integrated conceptual framework?

Methodology

These questions led us to undertake a systematic review of the literature. We drew on the method of Tranfield et al. (2003) to develop a multi-stage approach: 1) formulate one or more explicit research questions, 2) establish inclusion and exclusion criteria, 3) search for relevant studies, 4) select studies according to the inclusion and exclusion criteria, 5) evaluate the selected studies, 6) summarize and bring together the results, and 7) interpret the results. Our research questions are listed above, and our selection criteria are outlined below.

Empirical Material

To be included in our literature review, the document must: 1) be a scientific paper published in a peer-reviewed journal; 2) have been published between January 2003 and December 2018; 3) be written in French or English; 4) focus on open innovation and, in particular, on the characteristics and / or determinants of open innovation; 5) provide a study of these elements in the context of SMEs; and 6) involve empirical work or be conceptual studies. We excluded dissertations, theses, books, editorials, book reviews, single case studies, and success stories.

The databases selected for the literature review were ProQuest ABI / Inform, EBSCO, and Web of Science. We searched each database both in French and in English, using the following pre-established algorithm: (“open innovation” OR “networked innovation” OR “distributed innovation” OR “collaborative innovation” OR “co-creation” OR “crowdsourcing” OR “openness” OR “inside-out” OR “outside-in” OR “inbound” OR “outbound” OR “coupled activities”) AND (“SME” OR “SMEs” OR “small and medium”). A total of 895 papers were identified from all four databases. After a triple sorting, 123 papers were kept.

Results

Based on papers we reviewed, we found that, SMEs have actively adopted inbound (or outside-in) practices, most frequently procurement of external knowledge (joint R&D, customer involvement). Technological tools are present and cited in most papers. Actors are internal (the manager or CEO and employees) or external (customers, consultants / intermediaries, research institutes, large companies, or start-ups).

We grouped OI determinants into five main categories: individual determinants (individual skills), organizational determinants (size, absorptive capacity, internal R&D department), value network determinants (trust, partner complementarity, proximity), industry-related determinants, and institutional determinants (government funding and other support programs). Among these categories, an SME is most affected by factors relating to its leaders and its dominant coalition, whose behaviors and individual characteristics determine its propensity to opt for OI or not. In addition, the elements of the context and particularly the existence of government support and funding can strongly incentivize adoption of more OI.

Finally, we argue that the four main elements under study (practices, tools, actors, and determinants) can be interlinked within a proposed integrative conceptual framework. When companies implement OI, they are motivated to choose a specific set of practices, tools, and actors by individual, organizational, network, or institutional factors.

Contribution to Scholarship

In academia, the research results will improve understanding of OI in SMEs and help identify its characteristics and determinants in that specific context. To our knowledge, no systematic review of the literature has brought these different elements together; we plan to fill this theoretical gap. In addition, our proposed conceptual framework will illustrate the complex relationships between OI characteristics and OI determinants. It will also provide a complete map and directions for future research, thus encouraging researchers to go further and test the generalizability of previous research results in different contexts.

Contribution to Practice

In practice, our findings will help SME managers and decision-makers make evidence-based recommendations on OI in their organization. Indeed, to the extent that they better understand why and how SMEs adopt OI, we may see more SME-oriented innovation strategies.

Fitness

Today, the benefits of opening up the innovation process are widely recognized and have been tested in different companies and contexts. This research will raise awareness of OI characteristics and determinants, thus encouraging and spurring SMEs in different industries to apply it and reap the benefits of improved performance.

Bibliography

- Brunswicker, S., & Van de Vrande, V. (2014). Exploring open innovation in small and medium-sized enterprises. New frontiers in open innovation, 1, 135-156.

- Brunswicker, S., & Vanhaverbeke, W. (2015). Open innovation in small and medium‐sized enterprises (SMEs): External knowledge sourcing strategies and internal organizational facilitators. Journal of Small Business Management, 53(4), 1241-1263.

- Chesbrough, HW. (2003). Open innovation: The new imperative for creating and profiting from technology. Boston, MA: Harvard Business Press.

- Chesbrough, H., Vanhaverbeke, W., & West, J. (Eds.). (2006). Open innovation: Researching a new paradigm. Oxford University Press on Demand.

- 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.

- Spithoven, A., Vanhaverbeke, W., & Roijakkers, N. (2013). Open innovation practices in SMEs and large enterprises. Small Business Economics, 41(3), 537-562.

- Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence‐informed management knowledge by means of systematic review. British journal of management, 14(3), 207-222.

- 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(6-7), 423-437.



Dancing with Wolves: How R&D Human Capital Can Benefit from Coopetition

Vesna Savic1, Carmen Cabello-Medina1, Shanthi Gopalakrishnan2, Haisu Zhang2, Melodi Guilbault2

1University Pablo de Olavide, Spain; 2New Jersey Institute of Technology

Context

This study examines the impact of competitor alliances on the development of internal R&D human capital, on a sample of biotech Spanish firms located in the five major biotechnology clusters, and US biotech firms located in the New Jersey Region.

Literature

Alliances with competitors, labeled as coopetition by Brandenburger and Nalebuff (1996).is increasingly discussed as an effective strategy for innovation (Bouncken, Fredrich, Ritala, & Kraus, 2018), given the opportunities for using joint market and technological knowledge provided by these types of agreements (Ritala & Hurmelinna-Laukkanen, 2009).

Coopetition is highly relevant for small and medium firms in knowledge intensive industries, who can share R&D costs and economies of scale, use synergistic effects by pooling resources, search for complementary resources and distribute risks, among other advantages (Bouncken & Kraus, 2013; Gnyawali & Park, 2009).

Literature on coopetition and innovation states that cooperation with competitors involves unique characteristics that are lacking in other types of alliances, and that these characteristics might produce different, either better or worse results for the concerned parties (Ritala & Hurmelinna-Laukkanen, 2009).

Literature Gap

Research has not shown conclusive findings about the effects of coopetition on performance, e.g. some studies demonstrate that coopetition facilitates the creation of new products while other studies show that cooperation with competitors is the least likely to produce highly novel innovations.

Research Questions

We propose two research questions:

1) How does coopetition influence human capital in biotech firms through the mediating role of alliance pro-activeness?

2) Are these relationships moderated by inter-organizational coordination capabilities and alliance satisfaction?

Methodology

Quantitative Analysis:

Confirmatory factor analysis (CFA) of all multi-item constructs.

For testing the hypotheses we used 3 models. The mediation effect was first tested in two separated models. With Model 3 we tested the moderating effects. Moreover, the bootstrapping analysis was performed to look for indirect effects.

Empirical Material

A survey technique was adopted in this study. In Spain the questionnaire was completed during the interview with the CEO or person responsible for R&D, while we designed an online questionnaire and collected data from biotechnology firms in the United States (US).

The survey was distributed to 285 Spanish firms located in five major biotechnology clusters: Andalusia, The Basque Country, Catalonia, Valencia, and Madrid. Ninety-three responses were returned, generating a response rate of 32.63%. In the US, the survey was sent to member firms of BioNJ (www.bionj.org), an organization of networking biotechnology firms in the state of New Jersey. Among 115 firms that received this survey, 30 firms responded, resulting in a response rate of 26.09%. We further removed 12 cases with substantial missing data. The remaining 111 cases were used for data analysis, resulting in a usable rate of 90.24% based on returned responses and 27.75% based on the entire sampling frame.

Results

Our results demonstrate that:

Alliances with competitors (coopetition) increase a firm’s internal R&D human capital and this relationship is mediated by the firm’s pro-activeness in the forming of R&D alliances. We found that competitor alliance is positively related to the firm’s pro-activeness in forming R&D alliances and pro-activeness in forming R&D alliance is positively related to the development of internal R&D human capital.

The study also supports our hipothesis that alliance satisfaction negatively moderates the relationship between coopetition and pro-activeness of R&D alliances.

We could not demonstrate that coordination positively moderate the relationship between coopetition and the firm’s pro-activeness in forming R&D alliances.

Contribution to Scholarship

Our study tries to add to the theory of alliances by further explaining how competitor alliances drive firm behavior in terms of further collaboration and the development of internal resources. Specifically, our main contributions are related to:

1) Studies concerned about the outcomes of coopetition have been mainly focused on its impact on innovation performance, although it is clear that other benefits may steam from coopetition. Our work tries to provide insights about different benefits of coopetition (Alliance proactiveness and R&D Human Capital) that can be itself particularly relevant.

2) Success of coopetition has proved to be contingent on a number of contextual factors. Nevertheless, more knowledge is needed about what circumstances make coopetition really advantageous. In our research, the role of alliance satisfaction and alliance coordination are examined as contextual factors that can determine the effectiveness of coopetition.

Contribution to Practice

From this study, managers of biotech companies can learn the benefits of alliances with competitors. Even if these alliances do not provide direct benefits regarding innovation performance, it is clear its impact on human capital of the firms, which represents a key resource of biotech companies.

For managers it is also useful to understand the role of some contextual factors that can make the alliances with competitors more effective.

Fitness

Open Innovation encompasses different practices and interactions with different types of organizations. Cooperation with competitors (coopetition) is a specific case of Open Innovation, particularly relevant in SMEs (they can share R&D costs, economies of scale, synergistic effects, complementary resources and risks, among other advantages)

Bibliography

Bouncken, R. B., Fredrich, V., Ritala, P., & Kraus, S. (2018). Coopetition in New Product Development Alliances: Advantages and Tensions for Incremental and Radical Innovation. British Journal of Management, 29(3), 391–410.

Bouncken, R. B., & Kraus, S. (2013). Innovation in knowledge-intensive industries: The double-edged sword of coopetition. Journal of Business Research, 66(10), 2060-2070.

Brandenburger, A. & Nalebuff, B. (1996). Co-opetition. Doubleday Publishing, New York.

Gnyawali, D. R., & Park, B. J. (2009). Co-opetition, and technological innovation in small and medium-sized enterprises: A multilevel conceptual model. Journal of Small Business Management, 47(3), 308–330.

Ritala, P., & Hurmelinna-Laukkanen, P. (2009). What’s in it for me? Creating and appropriating value in innovation-related coopetition. Technovation, 29, 819–828.



Effectiveness of Open Innovation: Evidence from an Information and Communications Engineering Company in Japan

Kumiko Miyazaki, Yoshitaka Nakamura

Tokyo Institute of Technology, Japan

Context

The importance of a paradigm shift from the closed to the open type innovation has been pointed out by Chesbrough.Up until the 1990s major Japanese companies adopted a closed innovation strategy but changes have been taking place since their capacity to innovate has reached a limit

Literature

Cheng, C.C.J., and Huizingh, E.K.R.E. (2014). When is open innovation beneficial? The role of strategic orientation, Journal of Product Innovation Management, 31(6), pp.1235-1253.

Chesbrough, H. (2003). Open innovation: The new imperative for creating and profiting from technology, Boston, Harvard Business School Press.

Laursen K and Salter,A(2006) Open for Innovation: The Role of Openness in explaining innovation performance among U.K.. manufacturing firms, Strategic Management Journal, 27, pp. 131-150

Osawa T and Miyazaki, K. (2006) An empirical analysis of the valley of death: Large-scale R&D project performance in a Japanese diversified company, Asian Journal of Technology Innovation, 14,2,pp93-116

Literature Gap

Recent work on open innovation has been based mainly on analyzing the effectiveness of open innovation in Western companies. It is also understood that obstacles exist towards value creation and structural trade off and negative effects on R&D performance have been suggested regarding Japanese firms. Such empirical study is missing.

Research Questions

How does the usage of open innovation affect the R&D outcome? How does the strategic orientation affect the usage of open innovation and R&D outcome? How does the external linkage orientation affect the usage of open innovation and R&D outcome? How do the findings vary among the different business units?

Methodology

We built a survey model by adapting the framework by Cheng and Huizingh and set up 4 hypotheses. Design, implementation and analysis of the questionnaire survey to verify the hypothesis were carried out.The questionnaire targeted 151 managers who belong to the business planning, marketing strategy and the business units. The model consists of activities of open innovation as independent variables, R&D outcome as dependent variables, strategic orientation and external collaboration orientation as moderating factors, the severity of market and technology change, and the competitive environment as a control variable.. In parallel, we conducted interviews with some project managers.

Empirical Material

In order to verify the hypothesis described above, we prepared a questionnaire according to the survey model and conducted quantitative analysis by questionnaire to managers of Company AT (151 people) from business planning, sales strategy, and R&D departments. We also conducted a case study of external collaborative R&D project for qualitative study. In addition, we conducted an interview with the project manager in Company AT who was involved in the collaborative R&D project with the university.We defined open innovation as to incorporate technology and knowledge from outside the company (including companies in the X group and research laboratories) into the company, to develop technologies and products in conjunction with their own technology and knowledge, to realize innovation (consider “request of R&D to other parties” as one form of open innovation).

Regarding the validity of the question items, the manager and three colleagues of the business planning division to which the author belongs reviewed them. 58 responses were obtained (out of 151).

Response is based on the Likert scale of 5 grades

Results

The findings show that regarding Hypothesis 1 "The usage of open innovation has a positive effect on the R&D outcome," the results of multiple regression analysis conducted show that among the R&D results, new product innovativeness, new product success and customer satisfaction were not supported and only the financial performance was supported. Among R&D outcomes, the interactive effects of strategic orientation on product innovativeness have a positive synergistic effect, but with regard to product success, customer satisfaction and financial performance, negative synergistic effect was observed. As for Hypothesis 3, "A strong linkage orientation with research institutes external to the corporate group has a positive effect on the usage of open innovation regarding R&D outcome", new product innovativeness, new product success, and customer satisfaction were not supported. However, when looking across divisions, there were differences in some of the results. It was confirmed that the company recognizes that open innovation is effective for R&D results in order to respond to new market trends and customer needs and to respond further to changes in market and technological environments. The case study revealed that open innovation will not emerge unless the market is ready even if innovative R&D outcome is obtained.

Contribution to Scholarship

This paper was able to clarify the characteristics of the effectiveness of open innovation in an actual company in the information and communication industry in Japan. For Hypotheses 1, "The usage of open innovation has a positive effect on the R&D outcome," the results show that of the effects of usage of open innovation on the R&D results, new product innovativeness, new product success and customer satisfaction were not supported, revealing a trend which is contrary to previous literature. In the result of Cheng & Huizingh (2014), open innovation activity and strategic trend, which includes entrepreneurial orientation, market orientation, and resource orientation, have a positive interaction effect on the all results of R&D. However, in this research, open innovation activity and strategic trend has a positive interaction effect only on the new product innovativeness of R&D result.

Contribution to Practice

The challenge related to open innovation for the company in the future is to search for technologies by cooperating partners outside the corporate group. A major issue is the utilization of open innovation towards "creating value." Regarding this issue, sufficient knowledge has not been accumulated in Company AT, which has been focusing on "manufacturing" so far as the major business, absorption of knowledge from the outside is absolutely necessary. In particular, as ICT, big data analysis technology progress, the enterprise needs new value creation under the new situation of dealing with economic and societal issues.

Fitness

This study presents the evidence of the effectiveness of open innovation on R&D outcome in a Japanese Information and Engineering Company using internal corporate data. It has been possible to carry out this research since one of the authors is a full time employee at this company.

Bibliography

Cabinet Office of Japan (2012). Trends of the World Economy 2012 I, Figure 2-3-22.

Cheng, C.C.J., and Huizingh, E.K.R.E. (2014). When is open innovation beneficial? The role of strategic orientation, Journal of Product Innovation Management, 31(6), pp.1235-1253.

Chesbrough, H. (2003). Open innovation: The new imperative for creating and profiting from technology, Boston, Harvard Business School Press.

Chiang, Y.H., and Hung, K.P. (2010). Exploring open search strategies and perceived innovation performance from the perspective of inter-organizational knowledge flows, R&D Management, 40 (3), pp.292-299.

Nobeoka, K. (2010). Disadvantages of Open Innovation: Problems in capturing value, The Journal of Science Policy and Research Management, 25(1), pp.68-77.



The Timing and Type of Alliance Partnerships in the New Product Development Process

Hadi Eslami1, Ashish Pujari2, Ruhai Wu2

1University of New Brunswick, Canada; 2McMaster University

Context

Small firms, operating in technologically-intensive sectors, are normally underfunded and lack required resources to conduct a full cycle of the new product development (NPD) on their own. Thus, they rely on open innovation strategy. However, it is critical for them to effectively manage their partnerships to reach their innovation objectives.

Literature

Previous research [5] indicates that firms are in a double bind between the increasing pressure to develop more innovative products and the escalating risks and costs associated with the NPD process. As a strategic remedy to this issue, R&D alliances with other organizations are vital for gaining access to share NPD costs and gain access to necessary knowledge and capabilities [4] for innovation. The importance of R&D alliances is even more important for survival and growth of high-technology (hi-tech) small firms [6] due to their lack of resources and experience in the effective selection of partners. However, in some circumstances, small firms may suffer from open innovation strategies due to transaction costs [2] involved in interorganizational relationships (e.g., product specificity and performance uncertainty). Therefore, despite the value-creation benefits of open innovation strategy for small firms [1], they may enter into collaborative R&D alliances with other organizations under unfavorable conditions [3].

Literature Gap

Innovation performance of open innovation (collaborative R&D alliances) has been mainly considered at the firm level of analysis. However, there is little research in the literature which focuses on the product innovativeness implications of R&D alliances hi-tech small firms form at different stages of the NPD process with different partners.

Research Questions

How can small firms use open innovation strategy to enhance the likelihood of their product innovativeness? More specifically, how the interaction of the alliance type and the alliance timing of R&D alliance formed during the NPD process to develop a new product affect the innovativeness of the new product?

Methodology

We integrate insights from both benefit and cost perspectives of alliances to develop and empirically test hypotheses regarding the effective management of alliance strategies to enhance the likelihood of product innovativeness. To this end, we introduce a new typology and demonstrate its application to product innovativeness. The typology categorizes alliance partnerships along two dimensions of partnership timing (the stage of the NPD process during which alliance is formed) and partnership type (role of alliance partner during the NPD process). We use this typology to determine the interaction effects of partnership timing and type on the probability of product innovativeness (radicalness).

Empirical Material

We chose Biopharmaceutical (biopharma) sector as our empirical setting, and our sample of small firms consists of dedicated biotechnology (biotech). Our unit of analysis is product (our outcome variable is innovativeness of ready-to-launch new products). We followed a multistage approach in collecting data from different data sources (Recombinant Capital; LexisNexis news items, Compustat financial data, and Food and Drug Administration (FDA) databases) to test theoretical hypotheses in the following systematic steps: 1) Create a list of 454 approved drugs from Food and Drug Administration (FDA); 2) Conduct keyword search on each drug in the FDA data source and collect related data (e.g. developer, radicalness, the technology used, disease indication, and approval date); 3) Search LexisNexis for news items published on the shortlisted drugs on related alliances at different stages of the drug development; and 4) Search Compustat database to collect focal firm-level variables of interests (e.g., SIC code, firm size, R&D expenditure). The final sample size was 230 drugs linked to 384 alliances developed by 85 biotech firms. We use a unique sample of 230 drugs developed by 85 relatively small biotechnology firms in collaborative alliances with 384 alliances in 1982-2016 to test the developed hypothesis in this thesis.

Results

Our main objective to check how the innovativeness of a new product is a function of its focal developer’s (biotech firms in this study) formation of R&D alliances during the NPD process. Our findings show that biotech firms’ alliances with universities during discovery and development of the NPD increases the likelihood of the innovativeness of the newly approved drug by FDA. However, such partnership during pre-launch stage will negatively affect the drug innovativeness. Moreover, biotech alliances with pharma firms will have negative effects during discovery and development stages of the NPD process and no effect during pre-launch stage. Lastly, biotech alliances with other biotech firms increases the likelihood of the drug innovativeness if such partnership is formed during the discovery stage. Such partnership will adversely affect the innovativeness of drugs if initiated during development and pre-launch stages. We have controlled for factors (other than alliances) which might affect the innovativeness of the drug upon FDA approval. We have controlled for the effects of R&D expenditure, therapeutic area, focal firm size, and prior alliance experience on the drug innovativeness.

Contribution to Scholarship

Alliance timing and type provide conditions under which the focal biotech firm can receive different benefits from entering into alliance partnerships. The proposed typology for alliance relationships in this study provides an opportunity to integrate insights from Transaction Cost Economics (TCE) with its cost-oriented view, and Resource-based view (RBV) of the firm and absorptive capacity with their benefit-oriented theoretical perspective. Prior studies with a focus on a cumulative view of alliances mainly used one or the other of these views. This study contributes to TCE theory by studying the dynamic conditions under which transaction costs vary. The idea is that transaction cost varies during the NPD process and between different partnership types. Similarly, this study extends the theoretical implications of RBV and absorptive capacity by providing empirical evidence that benefits obtained through alliances offer differential performance outcomes, conditional on both timing and type of alliance that the focal firm initiates.

Contribution to Practice

The need to access novel basic research and scientific knowledge and complementary resources of other firms, may cause some biotech firms to join alliances under unfavourable conditions, making these alliances prone to failure. Thus, small and underfunded firms sometimes overestimate the benefits and underestimate the risks of joining alliances. By applying the typology of alliance timing and type, small firms can better understand the risks and rewards of their strategic choices of alliances, as both the timing and type of alliances formed at different stages of the NPD process moderates the effects of alliances on innovativeness of its new product.

Fitness

In general, this research examines the effects of the R&D alliance timing and type on innovativeness of new products. In particular, a new product may be co-developed by multiple R&D alliances during the NPD process, proving immense implications for small high-tech firms to apply open innovation for their innovation management.

Bibliography

[1] Dyer, J. H., & Singh, H. (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23(4), 660-679.

[2] Heide, J. B. (1994). Interorganizational governance in marketing channels. The Journal of Marketing, 58(1), 71-85.

[3] Haeussler, C., Patzelt, H., & Zahra, S. A. (2012). Strategic alliances and product development in high technology new firms: The moderating effect of technological capabilities. Journal of Business Venturing, 27(2), 217-233.

[4] Rindfleisch, A., & Moorman, C. (2001). The acquisition and utilization of information in new product alliances: A strength-of-ties perspective. Journal of Marketing, 65(2), 1-18.

[5] Sivadas, E., & Dwyer, F. R. (2000). An examination of organizational factors influencing new product success in internal and alliance-based processes. Journal of Marketing, 64(1), 31-49.

[6] Yang, H., Zheng, Y., & Zhao, X. (2014). Exploration or exploitation? Small firms' alliance strategies with large firms. Strategic Management Journal, 35(1), 146-157.



 
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