IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i1p883-d1024173.html
   My bibliography  Save this article

Modeling and Complex Characteristics of Urban Subway Co-Opetition Network: A Case Study of Wuhan

Author

Listed:
  • Yilei Pan

    (School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China)

  • Mengying Chang

    (School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China)

  • Shumin Feng

    (School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China)

  • Dongsheng Hao

    (School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China)

Abstract

In this study, to explore the co-opetition (competition–cooperation) relationship between urban subway lines, we constructed three directed weighted subway models of a competition network, cooperation network, and co-opetition network based on the Space R model of a complex network. Taking Wuhan, China, as the research area, we established a Wuhan subway co-opetition network and analyzed the network’s complex characteristics. Through the analysis, we found that the competition network, cooperation network, and co-opetition network are all scale-free networks that present the characteristics of a high-clustering and short-distance small-world network. The co-opetition relationship between subway lines was mostly of a conventional type (55.56%) and unrelated type (41.67%), with only cooperative-dominant types found among the conventional types. The co-opetition effect between lines in the long-term network increased from 7.616 to 15.17, and the relationship strength of the competition and cooperation between lines increased significantly. The competition effect deflection angle of all subway lines in the network was found to be smaller than the cooperation effect declination angle. Additionally, all lines had a significant role in cooperation within the network, and cooperation played a dominant role in the co-opetition relationship.

Suggested Citation

  • Yilei Pan & Mengying Chang & Shumin Feng & Dongsheng Hao, 2023. "Modeling and Complex Characteristics of Urban Subway Co-Opetition Network: A Case Study of Wuhan," Sustainability, MDPI, vol. 15(1), pages 1-17, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:1:p:883-:d:1024173
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/1/883/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/1/883/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Inoue, Hiroyasu & Souma, Wataru & Tamada, Schumpeter, 2007. "Spatial characteristics of joint application networks in Japanese patents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 152-157.
    2. Hu, Baoyu & Feng, Shumin & Nie, Cen, 2017. "Bus transport network of Shenyang considering competitive and cooperative relationship," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 259-268.
    3. Werner Hoffmann & Dovev Lavie & Jeffrey J. Reuer & Andrew Shipilov, 2018. "The interplay of competition and cooperation," Strategic Management Journal, Wiley Blackwell, vol. 39(12), pages 3033-3052, December.
    4. Fangru Wang & Catherine L. Ross, 2019. "New potential for multimodal connection: exploring the relationship between taxi and transit in New York City (NYC)," Transportation, Springer, vol. 46(3), pages 1051-1072, June.
    5. von Ferber, C. & Holovatch, T. & Holovatch, Yu. & Palchykov, V., 2007. "Network harness: Metropolis public transport," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 585-591.
    6. Haitao Jin & Fengjun Jin & Jiao’e Wang & Wei Sun & Libo Dong, 2019. "Competition and Cooperation between Shared Bicycles and Public Transit: A Case Study of Beijing," Sustainability, MDPI, vol. 11(5), pages 1-13, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hu, Baoyu & Feng, Shumin & Li, Jinyang & Zhao, Hu, 2018. "Statistical analysis of passenger-crowding in bus transport network of Harbin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 426-438.
    2. Marcelo Royo-Vela & Jonathan Cuevas Lizama, 2022. "Creating Shared Value: Exploration in an Entrepreneurial Ecosystem," Sustainability, MDPI, vol. 14(14), pages 1-23, July.
    3. Cicchini, Tomás & Caridi, Inés & Ermann, Leonardo, 2024. "Robustness of the public transport network against attacks on its routes," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    4. Rui Yao & Kenan Zhang, 2023. "How would mobility-as-a-service (MaaS) platform survive as an intermediary? From the viewpoint of stability in many-to-many matching," Papers 2310.08285, arXiv.org.
    5. Xueguo Xu & Chen Xu & Wenxin Zhang, 2022. "Research on the Destruction Resistance of Giant Urban Rail Transit Network from the Perspective of Vulnerability," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    6. Hu, Baoyu & Feng, Shumin & Nie, Cen, 2017. "Bus transport network of Shenyang considering competitive and cooperative relationship," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 259-268.
    7. Shimei Jiang & Yimei Hu & Ziyuan Wang, 2019. "Core Firm Based View on the Mechanism of Constructing an Enterprise Innovation Ecosystem: A Case Study of Haier Group," Sustainability, MDPI, vol. 11(11), pages 1-26, June.
    8. Steffen Runge & Christian Schwens & Matthias Schulz, 2022. "The invention performance implications of coopetition: How technological, geographical, and product market overlaps shape learning and competitive tension in R&D alliances," Strategic Management Journal, Wiley Blackwell, vol. 43(2), pages 266-294, February.
    9. Kirtonia, Sajeeb & Sun, Yanshuo, 2022. "Evaluating rail transit's comparative advantages in travel cost and time over taxi with open data in two U.S. cities," Transport Policy, Elsevier, vol. 115(C), pages 75-87.
    10. Frédéric Le Roy & Sea Matilda Bez & Johanna Gast, 2021. "Unpacking the management of Oligo-coopetition strategies in the absence of a moderating third party," Post-Print hal-03349671, HAL.
    11. Yuewei Wang & Cong Lu & Hang Chen & Yuyan Zhao, 2022. "Evaluation and Spatial Characteristics of Cooperation among Tourist Attractions Based on a Geographic Information System: A Case Study of The Yangtze River Delta Region, China," Sustainability, MDPI, vol. 14(20), pages 1-19, October.
    12. So Yoon Yoon & Su Jung Jee & So Young Sohn, 2021. "Mapping and identifying technological coopetition: a multi-level approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5797-5817, July.
    13. Anindya Ghosh & Thomas Klueter, 2022. "The Role of Frictions due to Top Management in Alliance Termination Decisions: Insights from Established Bio‐Pharmaceutical Firms," Journal of Management Studies, Wiley Blackwell, vol. 59(5), pages 1315-1353, July.
    14. Xiaotian Yang, 2022. "Coopetition for innovation in R&D consortia: Moderating roles of size disparity and formal interaction," Asia Pacific Journal of Management, Springer, vol. 39(1), pages 79-102, March.
    15. Raoul Rothfeld & Mengying Fu & Miloš Balać & Constantinos Antoniou, 2021. "Potential Urban Air Mobility Travel Time Savings: An Exploratory Analysis of Munich, Paris, and San Francisco," Sustainability, MDPI, vol. 13(4), pages 1-20, February.
    16. Crick, James M. & Crick, Dave, 2021. "The dark-side of coopetition: Influences on the paradoxical forces of cooperativeness and competitiveness across product-market strategies," Journal of Business Research, Elsevier, vol. 122(C), pages 226-240.
    17. Lambros Mitropoulos & Annie Kortsari & Emy Apostolopoulou & Georgia Ayfantopoulou & Alexandros Deloukas, 2023. "Multimodal Traveling with Rail and Ride-Sharing: Lessons Learned during Planning and Demonstrating a Pilot Study," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    18. Weiwei Liu & Yuan Tao & Zhile Yang & Kexin Bi, 2019. "Exploring and Visualizing the Patent Collaboration Network: A Case Study of Smart Grid Field in China," Sustainability, MDPI, vol. 11(2), pages 1-18, January.
    19. Jarryd Daymond & Eric Knight & Maria Rumyantseva & Steven Maguire, 2023. "Managing ecosystem emergence and evolution: Strategies for ecosystem architects," Strategic Management Journal, Wiley Blackwell, vol. 44(4), pages 1-27, April.
    20. Xin Geng & Harish Krishnan & Milind G. Sohoni, 2022. "Operational collaboration between rivals: The impact of cost reduction," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1856-1871, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:1:p:883-:d:1024173. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.