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This study aims to specify whether heterogeneous reference-point-based aspirations are related to the cooperation levels of R&D alliance portfolios in a positive or negative (or nonlinear) way, and to unveil how cooperative behaviors evolve in recurrent project cooperation.

This study establishes a network containing a cooperation subnetwork and a project subnetwork based on patent data in the “deep learning” field to investigate how cooperative behaviors evolve in R&D alliance portfolios. A model of evolutionary games on complex networks is constructed to gain insight into the dynamic evolution of DMs’ strategies.

First, the heterogeneous aspirations of DMs can improve the cooperation level in R&D alliance portfolios. Second, compared to prudent DMs, aggressive DMs are more likely to choose the cooperation strategy, implying that an appropriate aspiration level nurtures cooperative R&D endeavors with partners. Third, the effects of effort complementarity, knowledge reorganization capabilities and cooperation supervision on cooperation are contingent on the distribution of DMs’ aspiration types.

Policymakers should identify aspiration types of DMs when screening partners. They can encourage partners to focus more on historical payoffs and establish relatively higher aspiration levels to improve the cooperation level. Developing highly detailed contracts becomes crucial when cooperating with firms that possess extensive knowledge reorganization capabilities.

This work contributes a theoretical framework for investigating cooperation in R&D alliance portfolios through the lens of evolutionary games on complex networks, thus revealing the effects of heterogeneous reference-point-based aspirations of DMs on R&D cooperation.

The purpose of this paper is to analyse cooperation in R&D in the automobile industry in Spain. It first examines to what extent firms cooperate with external actors in the field of technological innovation, and if so, with what type of cooperation partner, paying special attention to the differentiation according to the size of the firms. Second, it aims to study how the firm’s size may affect not only the decision of cooperating but also with which type of partner.

The data in this study came from the surveys done in 2010 and 2013 by the Technological Innovation Panel (PITEC) for firms in the automotive industry. The paper estimates a bivariate probit model that takes into account the two types of cooperation mostly present in such an industry, vertical and institutional, explicitly considering the interdependencies that may arise in their simultaneous choice.

The empirical study confirms that small firms cooperate less frequently than big firms and that giving more importance to information publicly available and having public financial support from local and national governments are important determinants of collaboration agreements, mainly in the case of customers and suppliers.

This paper contributes to the understanding of the motivations of the automotive industry for engaging in R&D cooperation agreements. The authors study how the firm’s size may affect not only the decision of cooperating but also with which type of partner.

This study aims to explore the effect of digitalization on the promotion of enterprise R&D cooperation, and it analyzes the microimpact mechanism and boundary conditions of enterprise digitalization on enterprise R&D cooperation.

Based on survey data sourced from the World Bank Enterprise Surveys of the business environment of Chinese enterprises in 2012, this study applies multiple regression methods to test theoretical hypotheses.

Enterprise digitalization positively affects the breadth and intensity of enterprise R&D cooperation. Employees’ digital literacy plays an intermediary role between enterprise digitalization and enterprise R&D cooperation. The subordinate attributes of enterprises weaken the positive relationship between enterprise digitalization and the breadth and intensity of enterprise R&D cooperation. The shareholding of state-owned enterprises reinforces the positive relationship between digitalization and the intensity of enterprise R&D cooperation. However, such shareholding shows no significant regulatory effect on digitalization and the breadth of enterprise R&D cooperation.

Focusing on the digital transformation of the enterprise, this study discusses its impact mechanism on enterprise R&D cooperation, including the impact on the intensity and breadth of R&D cooperation. The study further examines the regulatory effect of organizational inertia on enterprise digital and R&D cooperation from two aspects: resource rigidity and routine rigidity. It emphasizes the significance of the digital literacy of employees in enterprise digitalization and discusses the micromechanism of enterprise digitalization and enterprise R&D cooperation.

The purpose of this paper is to explore how China’s manufacturers catch up with the forerunners through R&D cooperation by developing a new mode of latecomer–forerunner R&D cooperation, i.e. the periphery–core mode, which provides a viable way for China’s manufacturers to obtain forerunners’ core knowledge from their periphery knowledge via knowledge spillover and knowledge transfer.

The paper first reviews the literature on R&D cooperation process in the catching-up context and knowledge management in R&D cooperation. Then, three cases of R&D cooperation between China’s advanced technology manufacturers and their forerunners are introduced, with emphasis on interactivities in R&D cooperation and knowledge spillover. On the basis of the multi-case study, the periphery–core mode of R&D cooperation between latecomers and forerunners is conducted.

The paper finds that the latecomers can catch up with their forerunners by acquiring forerunners’ core technology used in periphery R&D activities. Through formal and informal interactions, the forerunners’ core technology can be extracted and transferred to latecomers, which the latecomers can then absorb and further develop. Thus, it can be concluded that the periphery–core mode of R&D cooperation is a viable way for the latecomers to get access to forerunners’ core technology.

The paper contributes to the literature on the catching-up theory by developing the periphery–core mode as a new mode for the latecomers to catch up with the forerunners. It expands the understanding of the latecomer–forerunner R&D cooperation by focusing on the way that China’s manufacturers as latecomers catch up with the forerunners by accessing the forerunners’ core knowledge from their R&D cooperation in periphery knowledge. The paper shows the mechanism of knowledge transfer and spillover in R&D cooperation. The role of communications, especially informal communication between cooperation partners, is emphasized in this process. This study also provides a new perspective for cooperation partner selection by arguing that latecomers can choose their cooperation partners according to the periphery and core knowledge they possess, other than the relationship between them. Besides, this paper emphasizes the mutual support between knowledge transfer, knowledge spillover and knowledge absorption, which is necessary for latecomers to achieve successful catching up in periphery–core R&D cooperation.

This paper analyzes the stability and the welfare properties of R&D cooperations in an oligopolistic market with n firms. It is shown that the sizes of stable coalitions vary significantly with the kind and the actual value of spillovers, the institutional arrangement of cooperation between the firms and the underlying stability concept. Moreover, the welfare maximizing coalition is rarely a stable equilibrium outcome, hence there is scope for political intervention. However, the informational requirements on part of the policy makers are high, and they are at risk to adopt inappropriate measures that are detrimental to social welfare.

Industry practice has shown that technology licensing has an important effect on the R&D cooperation between firms. Different licensing methods will significantly impact a supply chain member's cooperative and price R&D decisions. However, there is scant literature investigating the decision on technology licensing and its impact on a supply chain member's price and cooperative R&D decisions. To address this gap, the authors investigate the R&D cooperation and the technology licensing in a supply chain formed of an original equipment manufacturer (OEM), a contract manufacturer (CM), and a third-party manufacturer which will compete with the OEM when the technology licensing occurs.

The authors investigate two licensing patterns, royalty licensing, fixed fee licensing together with the no licensing, within the R&D cooperative supply chain by developing two three-stage and a two-stage Stackelberg models.

Compare to the no licensing strategy, technology licensing always benefits to the OEM and the society especially when the technology efficiency and the brand power of the third-party manufacturer are more significant; the royalty licensing benefits to the OEM more when the technology efficiency and the brand power of the third-party manufacturer are higher; the fixed fee licensing benefits to the OEM more when the technology efficiency and the brand power of the third-party manufacturer are lower.

The royalty licensing is more effective for mitigating price competition intensity and helping firms to maintain higher sales margins; the fixed fee licensing induces firms' lower sales margins but increases the firms' sales quantities; in most cases, the fixed fee licensing is optimal from the perspectives of consumer and society, however, the CM's investment intention to the R&D technology with the fixed fee licensing is lower.

So far, different licensing models under the R&D cooperation have not been investigated, and the authors propose two three-stage Stackelberg models with considering the competition caused by technology licensing under the R&D cooperation to deal with the cooperative R&D and technology licensing issues.

It is widely accepted that enterprises obtaining academic discoveries through R&D collaboration improve their innovation performance. However, it is not necessarily true in emerging economies, such as China and post-socialist countries in Europe. The purpose of this paper is to fill the gap by investigating how R&D collaboration between industry and academia (i.e. universities and research institutes) affects the industrial innovation performance; and whether and how intermediaries moderate their relationships.

This paper constructs the research model according to the knowledge production function, and the pooled ordinary least square regression is used to verify our hypotheses.

Evidence from a sample of Chinese industrial enterprises in thirty provinces spanning from 2009 to 2014 suggests that R&D collaboration with research institutes (CWR) is positively related to innovation output, while R&D collaboration with universities (CWU) exerts negative effect on innovation output measured by sales revenue of new product (NPSR). The significant moderating role of technology transfer institutions is confirmed in the negative relationship between CWU and NPSR.

This paper empirically examines the moderating role of intermediary organisations in academia–industry cooperation and industrial innovation, and has practical implications for the government to formulate policies to improve the quality and effectiveness of cooperation between academic and industrial sectors. These results vary in inland and coastal areas, which suggest the policy makers to formulate policies according to local conditions not only in China but also in other countries, like European countries.

This paper aims to investigate how the implementation of the inter-cooperation principle among Spanish machine-tool cooperatives helps them to coopete–collaborate with competitors, in their innovation and internationalization processes and achieve collaborative advantages.

The paper uses a multi-case approach based on interviews with 15 CEOs and research and development (R&D) managers, representing 14 Spanish machine tool firms and institutions. Eight of these organizations are worker-cooperatives.

Worker-cooperatives achieve advantages on innovation and internationalization via inter-cooperation (shared R&D units, joint sales offices, joint after-sale services, knowledge exchange and relocation of key R&D technicians and managers). Several mutual bonds and ties among cooperatives help to overcome the risk of opportunistic behaviour and knowledge leakage associated to coopetition. The obtained results give some clues explaining to what extent and under which conditions coopetitive strategies of cooperatives are transferable to other types of ownership arrangements across sectors.

Firms seeking cooperation with competitors in their R&D and internationalization processes can learn from the coopetitive arrangements analyzed in the paper.

Findings can be valuable for sectoral associations and public bodies trying to promote coopetition and alliances between competitors as a means to benefit from collaborative advantages.

Focussing on an “ideal type” of co-operation–cooperative organizations – and having access to primary sources, the paper shows to what extent (and how) strong coopetitive structures and processes foster innovation and internationalization.

The paper aims to examine the differences between manufacturing and service sector firms regarding the determining factors for the decision to cooperate with research institutions to perform R&D activities. The second key contribution provided is the identification of institutional cooperation profiles, based on the determining variables of institutional cooperation.

On the one hand, drawing on the Community Innovation Survey for Spain, a Logit Regression Model is used to study the determining factors for institutional cooperation decision. On the other hand, in order to identify institutional cooperation profiles a confirmatory analysis was carried out applying the cluster methodology.

The empirical study confirms that the differences are fundamentally related to transaction cost theory and resource‐based view with respect to the costs. Specifically, these theories' proposal dealing with the variable cost is not empirically confirmed for firms in the service sector.

The principal limitation of this paper derives from the data available, which made it impossible to extend the research to cover a longer time period and affected the manner in which some variables were constructed.

The main implication of the paper can be understood in terms of managerial implications due to the importance of the institutional cooperation on R&D as an innovation management decision. Along this line, the results of the study indicate the existence of various options associated with the active posture on institutional cooperation.

The contribution of the paper is the identification of institutional cooperation profiles, based on the determining variables of cooperation with institutions on R&D activities as well as the identification of the differences between manufacturers and services related to them.

This study aims to identify and accurately assess the risk factors of competitors’ cooperation in the NPD project.

New product development (NPD) is essential to the survival of companies and surpassing other competitors. A key prerequisite for the success of an NPD project is the timing of new product delivery to the market. The main challenge faced by many project managers is the delay in execution and completion phases due to the complex nature and uncertainty of these projects. Rival companies' cooperation reduces the time spent on an NPD project which is an excellent way to reduce the risk of losing the market, but it increases other risk factors.

Based on the results, the security and confidentiality of innovation, the competitors attracting human resources and the company’s brand credibility factors were ranked higher than other factors and should be predicted and managed before cooperating with competitors.

This paper proposed a new model to assess risk factors in cooperation with rival companies in NPD projects. This model takes into account new parameters, for example, negative and positive risks, negative and positive passable risks and risk-based multi-objective optimization by ratio analysis plus full multiplicative form methodology for the rival companies cooperation in NPD projects. To evaluate the efficiency of the proposed model, a real case of the R&D unit of Iran Khodro Company was studied.