Influencing factors of and multiple paths to high performance in multidisciplinary scientific research cooperation in colleges in China: a fuzzy-set qualitative comparative analysis

被引:0
|
作者
Xue, Jing [1 ,2 ]
Liu, Xing [1 ,2 ]
Qin, Qun [1 ,2 ]
Huang, Weihong [2 ,3 ]
Feng, Song [4 ]
Guo, Hua [1 ,2 ]
机构
[1] Cent South Univ, Xiangya Hosp, Sci Res Div, 87 Xiangya Rd, Changsha 410008, Peoples R China
[2] Cent South Univ, Xiangya Hosp, Inst Hosp Management, 87 Xiangya Rd, Changsha 410008, Peoples R China
[3] Cent South Univ, Xiangya Hosp, Mobile Hlth Minist Educ, China Mobile Joint Lab, Changsha, Peoples R China
[4] Cent South Univ, Network Informat Ctr, Changsha, Peoples R China
基金
中国国家自然科学基金;
关键词
Multidisciplinary cooperation; cooperative performance; multiple paths; fuzzy-set qualitative comparative analysis (fsQCA);
D O I
10.21037/atm-22-2639
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: In the context of globalization of science and technology, multidisciplinary cooperation plays an important role in enhancing national scientific research strength. Many countries issue policies and reports to promote the implementation of interdisciplinary research. Colleges play a central role in knowledge generation and scientific inquiry and thus frequently contain a variety of scientific research organizations. With rapid advances in science, large-scale scientific research cooperation across disciplines and institutions is increasingly common. Many factors can affect the performance of research collaboration, and the implementation paths of some key factors remain unclear. In addition, no standardized collaboration system has been established in relevant research. Further studies on interdisciplinary scientific research cooperation will be particularly valuable for improving the efficiency of resource allocation and increasing the level of academic research. Here we explored the "joint effect" of various influencing factors on interdisciplinary collaborative research in colleges and the "interactions" among these factors. Methods: With stratified-cluster random sampling, 358 researchers from 181 research teams at 6 colleges across China were surveyed using a self-administered questionnaire. We used fuzzy-set qualitative comparative analysis (fsQCA) to analyze data to obtain more insight into the status quo of interdisciplinary cooperation among colleges. Results: The results showed that initiation and organization by an institution was a necessary condition for achieving high-performance scientific research collaboration. The performance incentive method of high-tech collaboration could be divided into four main paths: configuration organized by an institution; configuration organized by an institution, with high policy-based guarantees (PG); configuration organized by an institution, with high cooperation willingness (CW) and high cooperation ability (CA); and configuration organized by an institution, with high CW, abilities, and outputs. The drive mechanism of high performance in scientific cooperation could be divided into two types: organization-led and ability/willingness-driven. Conclusions: Only the integration of internal changes with the support of the external environment can ensure the stable development of multidisciplinary scientific research cooperation among colleges.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Influencing Factors and Multiple Paths of Entrepreneurship in High-Tech Enterprises: A Fuzzy-Set Qualitative Comparative Analysis of Configuration
    Zhang, Liyan
    Wang, Yuting
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2021, 2021
  • [2] A Fuzzy-Set Qualitative Comparative Analysis of Factors Influencing Servitization Transformation Performance in Chinese Manufacturing Enterprises
    Liao, Chengjun
    Xiang, Ziwei
    Li, Yuhua
    Li, Zhenyu
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2022, 2022
  • [3] A fuzzy-set qualitative comparative analysis of factors influencing successful shared service center implementation
    Plugge, Albert
    Nikou, Shahrokh
    Janssen, Marijn
    INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 2022, 122 (04) : 920 - 941
  • [4] Influencing factors and governance strategies of megaproject complexity based on fuzzy-set qualitative comparative analysis
    Wu, Quntao
    Bo, Qiushi
    Luo, Lan
    Yang, Chenxi
    Wang, Jianwang
    ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT, 2024, 31 (09) : 3533 - 3556
  • [5] Factors influencing proactiveness in supply chain risk identification: A fuzzy-set qualitative comparative analysis
    Ganesh, A. Deiva
    Kalpana, P.
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2023, 88
  • [6] Understanding the key factors and configurational paths of the open government data performance: Based on fuzzy-set qualitative comparative analysis
    Zhao, Yupan
    Fan, Bo
    GOVERNMENT INFORMATION QUARTERLY, 2021, 38 (03)
  • [7] Uncovering the paths to helpful reviews using fuzzy-set qualitative comparative analysis
    Ahmad S.N.
    Journal of Marketing Analytics, 2017, 5 (2) : 47 - 56
  • [8] Identifying the configurational paths to innovation in SMEs: A fuzzy-set qualitative comparative analysis
    Poorkavoos, Meysam
    Duan, Yanqing
    Edwards, John S.
    Ramanathan, Ramakrishnan
    JOURNAL OF BUSINESS RESEARCH, 2016, 69 (12) : 5843 - 5854
  • [9] What factors influence scientific concept learning? A study based on the fuzzy-set qualitative comparative analysis
    Ma, Jingjing
    Liu, Qingtang
    Yu, Shufan
    Liu, Jindian
    Li, Xiaojuan
    Wang, Chunhua
    BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY, 2025, 56 (01) : 250 - 275
  • [10] The paths of career aspiration for intern nursing students: A fuzzy-set qualitative comparative analysis
    Zhang, Yuye
    Li, Qiufang
    Wang, Xiaokai
    Zhang, Yan
    Li, Hongfeng
    Zhang, Ruixing
    NURSE EDUCATION IN PRACTICE, 2024, 81