Managing knowledge sharing in distributed innovation from the perspective of developers: empirical study of open source software projects in China

Chen, Xiaohong; Zhou, Yuan; Probert, David; Su, Jun

doi:10.1080/09537325.2016.1194387

Cited by 39 publications

(34 citation statements)

References 59 publications

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“…Through a design process knowledge can be shared by and with all involved stakeholders, including designers and users of design. Multiple means can be used for sharing knowledge including sharing through participation in activities, sharing through organisational communication channels, and sharing through social networks which in some cases can be the most powerful tool for knowledge sharing (Chen, Zhou, Probert, & Su, 2017). Sharing knowledge and information acquisition is not only a result of a design activity, but also could be a vital attribute of the activity itself.…”

Section: Knowledge Sharingmentioning

confidence: 99%

Strategies for Empowering Collective Design

2019

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Collective activities such as crowdfunding, competitions, jams and hackathons are gaining more attention in innovation management. However, within the design domain such activities are often considered as a way for mass generation of ideas, rather than processes for developing proper design solutions. Information acquisition, gaining sufficient knowledge and generating feasible ideas are among the main challenges of collective design. In this study we applied three strategies of rapid design, informed participation, and knowledge sharing to overcome these challenges. During a one-week design hackathon, we conducted a collective design project in which three teams of participants conducted autoethnography research, shared their findings by an idea crowdsourcing platform, and tested their 3D printed prototypes with potential users. Although the tests showed efficiency of rapid design and informed participation strategy, we did not find knowledge sharing effective, mainly due to the absence of collaboration among teams.

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Section: Knowledge Sharingmentioning

confidence: 99%

Strategies for Empowering Collective Design

2019

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“…Heraud [6], consider that knowledge management is to improve the efficiency of knowledge innovation and application and make the knowledge level of supply chain members to achieve coordination and optimization. Chen et al [7] believe that enterprises share and utilize the knowledge of upstream and downstream enterprises through knowledge-based supply chain cooperation, which makes the knowledge of each member enterprise in the supply chain continuously improve its value in the movement, so as to enhance the core competencies of the entire supply chain. Zhao et al [8] think that the knowledge management problem in supply chain is very important for im-proving the core competitiveness of supply chain enterprises and the overall performance of supply chain.…”

Section: Related Workmentioning

confidence: 99%

Research on knowledge innovation of supply chain enterprises from the perspective of the thermodynamic entropy theory

2019

THERM SCI

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The theory of thermodynamic entropy is applied for reference to solve the basic problems of supply chain management science and knowledge innovation of supply chain enterprises. As for entropy, only thermodynamic entropy, statistical physical entropy and information entropy have been recognized, so management entropy is defined as the generalization of entropy. According to the similarity between state change of management system and that of the thermodynamics system, the revelation of the microscopic mechanism of entropy essence by statistical physical entropy, and the foundation that information entropy is regarded as the generalization of entropy by scholars, it is concluded that management entropy exists and has the same properties as thermodynamic entropy. For instance, it becomes a measure of the degree of chaos and disorder of a system and the time vector of the management system. A knowledge innovation sharing model of supply chain enterprises is constructed based on the thermodynamic entropy theory, the process of knowledge sharing in supply chain is analyzed, and the possibility of knowledge sharing among supply chain enterprises from the point of view of game theory is discussed. The principal-agent theory is used to analyze the incentive strategy to promote knowledge sharing in supply chain, and the model of knowledge sharing in supply chain is established.

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“…Although previous research has given attention to knowledge sharing concerning software engineering activities [22], [23], [24], [25], however, knowledge sharing in the context of MCR has not got much attention from the researchers [8], [9], [11], [20], [21]. No, systematize investigations are available concerning the knowledge sharing aspect in MCR that can help in minimizing waiting waste.…”

Section: Introductionmentioning

confidence: 99%

“…Though preceding studies [22], [23], [24], [25] focused on knowledge sharing in software engineering activities, however, slight indication is available in MCR [8], [9], [11], [20], [21], resulting in absence of knowledge sharing guidelines in MCR. Therefore, the study aims to identify factors influencing knowledge sharing in MCR to minimize waiting waste.…”

Section: Introductionmentioning

confidence: 99%

Knowledge Sharing Factors for Modern Code Review to Minimize Software Engineering Waste

Fatima¹,

Nazir²,

Chuprat³

2020

IJACSA

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Software engineering activities, for instance, Modern Code Review (MCR) produce quality software by identifying the defects from the code. It involves social coding and provides ample opportunities to share knowledge among MCR team members. However, the MCR team is confronted with the issue of waiting waste due to poor knowledge sharing among MCR team members. As a result, it delays the project delays and increases mental distress. To minimize the waiting waste, this study aims to identify knowledge sharing factors that impact knowledge sharing in MCR. The methodology employed for this study is a systematic literature review to identify knowledge sharing factors, data coding with continual comparison and memoing techniques of grounded theory to produce a unique and categorized list of factors influencing knowledge sharing. The identified factors were then assessed through expert panel for its naming, expressions, and categorization. The study finding reported 22 factors grouped into 5 broad categories i.e. Individual, Team, Social, Facility conditions, and Artifact. The study is useful for researchers to extend the research and for the MCR team to consider these factors to enhance knowledge sharing and to minimize waiting waste.

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Managing knowledge sharing in distributed innovation from the perspective of developers: empirical study of open source software projects in China

Cited by 39 publications

References 59 publications

Strategies for Empowering Collective Design

Strategies for Empowering Collective Design

Research on knowledge innovation of supply chain enterprises from the perspective of the thermodynamic entropy theory

Knowledge Sharing Factors for Modern Code Review to Minimize Software Engineering Waste

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