RETRACTED: Innovation ability of industry-university-research cooperation and innovation considering split-combined quadratic big data dynamic model construction

Yan, Qing; Qi, Wang

doi:10.1177/0020720920929659

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…We extract from the "golden source" nonrelevant articles and papers which are not referred to the use of BD in the innovation process (these were mostly cases when BD had been used as a method for achieving the research purposes rather than involvement in the innovation process per se [42] or as a means for reaching BD innovation [43].…”

Section: Systematic Literature Review Design -Bd the Innovation Processmentioning

confidence: 99%

Big Data as a Stakeholder of the Firm’s Innovation Process

Yordanova

2023

TEM Journal

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Big data has already been used successfully by firms for innovation development and has been involved in many business processes to render them more efficient and productive. The innovation process is one of the most critical processes in firms related to all others at the firm level and beyond mostly due to its impact on a firm’s overall performance and potential. The innovation process is highly data-dependent, so it is exceedingly impacted by the development of emerging technologies and big data in particular. In this study, we are exploring how big data is affecting the firm’s innovation process and how it is incorporated into each of its process steps to facilitate its demands. To examine the overall picture of the multidisciplinary topic, we conduct both a bibliometric analysis and a systematic analysis of the scientific literature in order to define the scope of the current application of big data within the innovation process. Furthermore, we identify under-researched topics to indicate future research directions.

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Section: Systematic Literature Review Design -Bd the Innovation Processmentioning

confidence: 99%

Big Data as a Stakeholder of the Firm’s Innovation Process

Yordanova

2023

TEM Journal

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“…However, in the process of promoting industry–university–research cooperation, as a result of the information asymmetry of technology supply and demand, low trust in cooperative communication, and the concept of emphasizing results over process deviation, the practical problems of insufficient breadth, insufficient depth, and insufficient performance of industry–university–research cooperation exist. For many years, industry–university–research cooperation has been an important issue in the management of innovation academia ( Qing and Qi, 2020 ; Li et al, 2022 ), and how to effectively improve the cooperative innovation performance of industry–university–research is an urgent problem to be solved ( Cao et al, 2013 ; Yan et al, 2017 ; Liu et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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

Meng

et al. 2023

Front. Psychol.

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IntroductionIndustry–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.MethodsTherefore, 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.ResultsThe 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.DiscussionThis 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.

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Dynamic selection of cooperative partners of agricultural science and technology industry-university-research system based on field theory

Zhang,

Lu,

et al. 2025

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PurposeAgricultural science and technology (AST) often need the form of industry-university-research cooperation in successfully completing breakthrough agricultural technology innovations. Therefore, AST industry-university-research cooperation is not only the need of the AST development strategy in China but also the only way for the development of agricultural colleges and universities, agricultural scientific research institutions and agricultural enterprises. Among them, in the process of cooperative breakthrough agricultural technology innovation, the correct selection of partners is the basis for ensuring its effective operation.Design/methodology/approachAiming at the time-series characteristics and information ambiguity of decision information in the dynamic selection process of AST industry-university-research partners, this research introduces the dynamic intuitionistic fuzzy multi-criteria decision-making method of time degree and orthogonal projection. On this basis, field theory is used to construct the cooperative innovation capability field model of the partners, and the threshold for the partners to enter or exit the system is designed to dynamically select and eliminate the partners.FindingsResults show that this method fully considers the situation of cooperative innovation resources within the AST industry-university-research system and the resource complementarity of candidate partners.Originality/valueCombined with examples from agricultural scientific research institutions, the applicability and superiority of the model are verified.

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RETRACTED: Innovation ability of industry-university-research cooperation and innovation considering split-combined quadratic big data dynamic model construction

Cited by 5 publications

References 13 publications

Big Data as a Stakeholder of the Firm’s Innovation Process

Big Data as a Stakeholder of the Firm’s Innovation Process

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

Dynamic selection of cooperative partners of agricultural science and technology industry-university-research system based on field theory

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