Impact of specific investments, governance mechanisms and behaviors on the performance of cooperative innovation projects

Wu, Ai Hua; Wang, Zhuo; Chen, Sandy

doi:10.1016/j.ijproman.2016.12.005

Cited by 95 publications

(68 citation statements)

References 94 publications

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“…This result is similar to 669 pertinent studies in other fields. For example, Wu et al (2017b) demonstrated that trust is more 670 important than contracts for the performance of cooperative innovation projects in high-tech 671 enterprises. Trust grants information sharing to access the valuable knowledge of project 672 participants, and facilitates the acquisition of novel ideas and insights that lay the groundwork 673 for problem-solving.…”

Section: The Effect Of Governance Mechanisms On Relational Behavior 666mentioning

confidence: 99%

Governing Behavioral Relationships in Megaprojects: Examining Effect of Three Governance Mechanisms under Project Uncertainties

Zheng

Chang

2019

J. Manage. Eng.

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The relational behavior of project participants is crucial to the success of a 4 megaproject. Although project governance has been widely studied with the aim of improving 5 participants' relational behavior, limited research examines the distinct effectiveness of various 6 governance mechanisms on influencing relational behavior, especially in megaprojects. 7Through examining three varieties of governance mechanisms, including contract, trust and 8 institutional support, a hierarchical moderated regression analysis has been used to explore the 9 impact of each of the governance mechanisms in facilitating the relational behavior of 10 megaproject participants and further team performance. The analysis is based on data collected 11 from 202 contractors and consultants working at megaprojects in China. Results unveiled that 12 both contractual term specificity and its interaction with trust can facilitate relational behavior. 13 Project uncertainty moderates the relationship between governance mechanisms and relational 14 behavior in affecting project team performance. The findings offer both theoretical and 15 managerial implications for megaproject participants to cultivate beneficial relational behavior 16 so as to improve team performance in megaprojects. 17

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Section: The Effect Of Governance Mechanisms On Relational Behavior 666mentioning

confidence: 99%

Governing Behavioral Relationships in Megaprojects: Examining Effect of Three Governance Mechanisms under Project Uncertainties

Zheng

Chang

2019

J. Manage. Eng.

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“…In terms of e-commerce, An et al analyzed the return policy in an e-commerce environment based on system dynamics [31], and Fang et al used system dynamics to study the relationship between e-commerce investment and firm performance [32]. Wu et al used system dynamics to simulate the recommendation of personalized information by analyzing the relationships between personal intention, community influence, user preference, resource complexity, and label selection algorithm in a label-based recommendation system [33]. The process reveals the mechanism and system characteristics of information recommendation and provides research ideas on the dynamic evolution process of personalized information recommendation.…”

Section: System Dynamicsmentioning

confidence: 99%

“…The innovation performance of an enterprise has a positive impact on its organizational and technical mechanisms by influencing financial resources [58]. Through the commercial transformation of open innovation performance, enterprises will introduce new services or new products to the market, which not only satisfy the requirements of users and enhance the reputation of the enterprise, but also bring about an increase in revenue [33]. Part of the revenue will be invested in R&D and management, thus increasing the total R&D investment and management expense.…”

Section: Causal Relationship Of Governance Mechanism Subsystemmentioning

confidence: 99%

Impact of Open Innovation Communities on Enterprise Innovation Performance: A System Dynamics Perspective

Gong

2019

Sustainability

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Open innovation communities (OICs) can help enterprises make full use of external knowledge resources from users, but problems such as low user participation and low conversion rate of creative ideas impact the efficiency of OICs. Most studies on this topic employ qualitative or empirical methods from a static perspective, but ignore the effect of interaction between enterprises and users as well as the cumulative effect of time. A discussion on the dynamic evolution process of open innovation is lacking. Based on a review of the literature on OICs, innovation performance, and system dynamics, this study proposes a conceptual model of innovation performance impact, which comprises the knowledge management, governance mechanism, and user behavior subsystems. Xiaomi’s OIC in China was selected as the research object, and relevant data were collected through a web spider. According to the system dynamics modeling method, a causal relationship analysis was carried out on the three aforementioned interrelated subsystems. Then, a stock flow chart with 32 variables was constructed to determine the initial values and calculation equations for each variable. Finally, the model was constructed and verified using Vensim PLE software. The simulation results were as follows. (1) The number of product releases in the Xiaomi OIC was positively correlated with the number of posts, comments, and views. Compared with user interaction behavior (i.e., commenting and viewing), the impact of user innovation behavior (i.e., posting) on enterprise innovation performance (i.e., number of patents) is clearer. Specifically, regarding interaction behavior, the impact of the users’ commenting behavior on innovation performance (i.e., number of product releases) was relatively clearer than that of their viewing behavior. (2) Governance mechanism (i.e., R&D investment and management expense), which comprises technical and organizational mechanisms, positively affected the innovation performance of enterprises. Compared with the organizational mechanism (i.e., management expense), the impact of the technical mechanism (i.e., R&D investment) on the innovation performance was clearer. (3) Governance mechanism helped to increase the number of users in the OIC, and, in turn, affected the user innovation and interaction behavior. (4) The technical mechanism positively affected knowledge application capability, which, in turn, had a positive impact on the innovation performance of enterprises. Based on these findings, management strategies are proposed for the establishment and development of OICs.

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“…Prior relationship length (PRL) between the partners is likely to influence the degree of contractual details [42], and it was characterized by the duration of the prior relationship between the partners [13]. Asset specificity (AS) has a strong explanation power about the contractual governance [9,43], and it was also introduced as a control variable. AS includes the following: the extent to which the resources are wasted after the termination of cooperation [44,45]; the extent to which the adjustments have been made during the operation [45,46]; and the time and capital required to train and evaluate collaborative partners [44,47].…”

Section: Control Variablesmentioning

confidence: 99%

“…Some researchers argued that proper modes of contract management can be used to balance the benefits of participants, maximize the chance of success for project, and improve the performance of project [7][8][9]. In general, project alliances are divided into equity alliances and nonequity alliances [10,11].…”

Section: Introductionmentioning

confidence: 99%

Effect of Organizational Cultural Differences and Mutual Trust on Contract Management of Nonequity Construction Project Alliances

Zhao

Feng

Li³

2018

Advances in Civil Engineering

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is study aims to examine the impact of organizational cultural difference and mutual trust on the contract management of nonequity project alliances in the construction industry. A questionnaire survey was conducted to collect the quantitative data for this study. e relationships between the variables were analyzed using hierarchical regression analysis. It was found that the contractual complexity of nonequity project alliances was impacted by the differences in management style, differences in organizational responsiveness, mutual goodwill trust, and mutual competence trust. It was also found that the relationship between differences in organizational responsiveness and contractual complexity was moderated by mutual goodwill trust. e research may provide theoretical basis for the management when making decisions on the selection of project alliance partners and contracts. e findings imply that when the firms seek to form project alliances, they need to recognize the level of organizational cultural differences and then determine the proper contractual complexity of the project alliance. In addition, the establishment of mutual goodwill trust between alliance partners will not only reduce the costs of making contracts but also the costs of implementing the contracts.

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Impact of specific investments, governance mechanisms and behaviors on the performance of cooperative innovation projects

Cited by 95 publications

References 94 publications

Governing Behavioral Relationships in Megaprojects: Examining Effect of Three Governance Mechanisms under Project Uncertainties

Governing Behavioral Relationships in Megaprojects: Examining Effect of Three Governance Mechanisms under Project Uncertainties

Impact of Open Innovation Communities on Enterprise Innovation Performance: A System Dynamics Perspective

Effect of Organizational Cultural Differences and Mutual Trust on Contract Management of Nonequity Construction Project Alliances

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