Cooperative Innovation Performance Research Articles

The relationship between the interactive behavior of industry-university-research subjects and the cooperative innovation performance: The mediating role of knowledge absorptive capacity.

Industry-university-research cooperation innovation, which is often characterized by resource complementarity and the sharing technology, has become one of the most preferred innovation cooperation methods for enterprises. However, various problems still occur in the process of industry-university-research cooperations, such as poor innovation performance and difficulty in sustaining cooperation. Existing studies mostly focus on the macroscopic perspectives of geographic location, cooperation scale, concentration, and diversification of industry-university-research cooperation subjects, and fail to explore the microscopic behavioral mechanisms. Therefore, this paper establishes the interactive behavior of industry-university-research subjects and defines its concepts and dimensions in an attempt to provide a mechanism for improving the cooperative innovation performance of industry-university-research from the micro-behavioral perspective. On the basis of theoretical analysis, this paper develops a model of the relationship between cooperative trust, cooperative communication, and cooperative innovation performance for interactive behavior, while exploring the mediating role of knowledge absorptive capacity. The model was validated by stepwise regression using data from 325 questionnaires. The paper found that cooperative trust and cooperative communication in the cooperative interactive behavior of industry-university-research positively contribute to the improvement of cooperative innovation performance. Knowledge absorptive capacity plays a partially mediating role between the interactive behaviors and cooperative innovation performance. More specifically, knowledge absorptive capacity partially mediates cooperative communication in cooperative innovation performance and completely mediates cooperative trust in cooperative innovation performance. The results are largely consistent with the results of the heterogeneity analysis of the sample. This paper not only explains why the cooperative innovation performance of industry-university-research is poor from the perspective of interactive behavior, but also enriches the research perspective of industry-university-research and provides theoretical support for enterprises to optimize the relationship between industry, university, and research institutes.

The Impact of Megaproject Stakeholders’ Psychological Ownership on Cooperative Innovation Performance: Territorial Behavior and Social Loafing as Mediator

Megaprojects encounter numerous innovation challenges as well as cross-organization cooperation demands. The paper aims to clarify the relationship between stakeholders’ psychological ownership and cooperative innovation performance. It proposes modelling the behaviors’ mediator process and how and why the megaproject stakeholders’ psychological ownership impacts their cooperative innovation performance. The research aims to expand the domain of psychological ownership by temporary cross-organization aspects and reveal behavioral influence mediation mechanism. This paper opted for an empirical study adapting the SEM approach. Tools such as pre-survey and documentary analysis are applied to design the questionnaire scale. This paper acquired 237 valid questionnaires from seven megaprojects to validate the impact of stakeholders’ psychological ownership on cooperative innovation performance. This paper finds that the following: (1) the psychological ownership of megaproject stakeholders has a negative impact on cooperative innovation performance, which is realized through the dual mediators of territorial behavior and social loafing; (2) psychological ownership has a positive effect on both territorial behavior and social loafing, while territorial behavior and social loafing have a negative effect on cooperative innovation performance. This paper reveals that psychological ownership’s negative influence mechanism on cooperative innovation performance, in temporary cross-organization, further provides support for improving cooperative innovation performance.

Empirical Research on Cooperative Innovation Performance of Agricultural Scientific Research Team and Effect Factors

Empirical Research on Cooperative Innovation Performance of Agricultural Scientific Research Team and Effect Factors

How cooperative innovation could be more effective in China: a relationship perspective

PurposeConsidering strategic information sharing (SIS), this paper aims to develop a better understanding of how relation-specific investments (RSIs) influence cooperative innovation performance (CIP) in downstream channel relationships. Also examined was the moderating effect of relational trust in that the indigenous practice ofguanxiis especially critical in China.Design/methodology/approachData were collected through a questionnaire in Chinese high-tech industries, with a valid response from 310 companies. A hierarchical regression analysis was used to test the conceptual model and hypotheses, combining mediation and moderation analysis.FindingsResults show that the influences of specific investments vary according to the specificity dimensions examined. Specifically, human RSI influences CIP and SIS most significantly, and the impact of procedural RSI is, relatively, the weakest. Relational trust’s moderating role is confirmed, and SIS plays a partially mediating role in enhancing vertical cooperative innovation.Practical implicationsManagers should know clearly different roles of RSIs in inter-firm cooperative innovation and prioritize human RSI and brand RSI when investing into channels. More importantly, the findings reveal that strategy-level information sharing should be valued more. It is also recommended that relational ties are vital, especially in Chinese business context.Originality/valueTo the best of the authors’ knowledge, this paper is among the first few to investigate how the effects of disaggregated RSIs in inter-firm cooperative innovation vary and the importance of SIS in vertical relationships. The results provide insightful guidance for researchers and managers in how to better manage RSIs to improve CIP.

Research on the Relationship between Structural Hole Location, Knowledge Management and Cooperative Innovation Performance in Artificial Intelligence

ABSTRACT This paper builds a conceptual model of the relationship between structural hole location, knowledge management, and collaborative innovation performance in the artificial intelligence environment. A questionnaire survey was conducted on 267 companies, and sample data were analysed using SEM statistics. In the artificial intelligence environment, under the influence of the embedded relationship of the collaborative innovation network structure, the influence of network structure hole position on the performance of collaborative innovation is discussed. The research results show that the location of network structure holes has a direct impact on the performance of collaborative innovation; At the same time, the location of network structure holes has a significant positive impact on knowledge management, and knowledge management plays a part of the mediating role in the process of network structure hole locations affecting collaborative innovation performance.

Impacts of knowledge spillovers and cartelization on cooperative innovation decisions with uncertain technology efficiency

Cooperative innovation is a popular way for firms to pursue technological innovation and profits. Two important aspects, knowledge spillovers and cartelization, have a considerable impact on firms’ cooperative innovation performance. This paper studies cooperative innovation decisions in a two-level supply chain including an upstream firm and a downstream firm with knowledge spillovers (natural or perfect) and uncertain technology efficiency. To investigate the effects of knowledge spillovers and cartelization, four innovation modes, namely, non-cooperative innovation, innovation cartel, research joint venture and research joint venture cartel, are examined. We obtain several findings: (i) enhancing either firm’s knowledge spillover benefits both firms and the whole supply chain, and the profits of the firms and the chain reach the maximum when the two firms perfectly share their knowledge; (ii) cartelization can help upstream and downstream firms achieve a win–win scenario in a Pareto zone, but the supply chain always benefits; and (iii) both knowledge spillovers and cartelization are beneficial for the supply chain when the demand elasticity is not too small, specifically, with the research joint venture cartel mode being the best and the non-cooperation mode being the worst. Moreover, we extend the model to involve a general probability distribution of stochastic technology efficiency and find that high uncertainty in technology efficiency leads to lower profit for the downstream firm; we also relax a general cost function of technological innovation and discuss the robustness of the theoretical results.

Network Structure and Innovation Performance in University-Enterprise Cooperation

Under the background of University-Enterprise Cooperation innovation (UEC), this paper explores the relationship between the network structure of UEC and its cooperative innovation performance. In the negative binomial model, the explained variable is the number of UEC patent applications, and explanatory variables are clustering coefficient, structural holes and centralities. The result shows that eigenvector centrality has an inverted U-shaped relationship with UEC performance especially.

Network Position, Technological Distance and Firm’s Cooperation Innovation

This paper studied the joint effects of network position and technological distance on firm’s cooperation innovation based on the data of firm’s patent cooperation from 2003-2013 in the electronic information, electric power and equipment manufacturing industry. Results show that both network centrality and structure holes have a significant positive impact on the firm’s cooperation innovation output; technological distance and cooperative innovation performance have an inverted u-shaped relationship; the interaction of network centrality and technological distance negatively regulates the cooperative innovation performance; the interaction of technological distance and structure holes can promote cooperative innovation performance.

The mediating roles of governance mechanisms and knowledge transfer on the relationship between specific investments and cooperative innovation performance

ABSTRACTThis study seeks to understand the influence of specific investments (SIs) to cooperative innovation performance (CIP) by examining the mediating roles of knowledge transfer (KT) and governance mechanisms (GMs), including formal contracts (FCs) and relational trust (RT). A sample of 238 projects is used to test the proposed model through structural equation modelling. The results show SIs act indirectly through RT to influence CIP. KT plays a mediating role between the two GMs and CIP. Moreover, the results suggest that the mediating effect of KT between FCs and performance is full; however its effect between RT and performance is only partial, and the mediating effect of RT between SIs and performance is also partial.

Innovation ecosystem: impact of interactive patterns, member location and member heterogeneity on cooperative innovation performance

The cooperative innovation performance of an innovation ecosystem depends on the interactive activities among members of the ecosystem. This study investigates the ways in which the evolution of an innovation ecosystem, member locations, heterogeneity and the pattern of interaction among members affect cooperative innovation performance. We build an interaction model and conduct a simulation experiment and empirical research on China’s railway transportation equipment industry. On the basis of a qualitative and quantitative investigation, we find that the interactive strength of focal firms and their upstream partners is more beneficial to cooperative innovation performance than the interactive strength of focal firms and their downstream partners. These findings also suggest that the exit of members of an innovation ecosystem decreases cooperative innovation performance; however, the effect of the exit of upstream component partners is more significant. We conclude that both the focal and the upstream component firms have positive influential power toward the cooperative innovation performance. In addition, this study suggests that asymmetric relationships between the focal firm and upstream and downstream partners tend to have more significant impact on their cooperative innovation performance, in which a centralized interactive pattern of the ecosystem members generated higher cooperative innovation performance than the dispersed pattern.