IDEAS home Printed from https://ideas.repec.org/a/wly/mgtdec/v43y2022i6p1773-1791.html

Quality control decision of government procurement of elderly care service based on multi‐index fusion of Pythagoras TOPSIS: Perspective of complex network

Author

Listed:
  • Zhengnan Lu
  • Yuting Zhang
  • Lan Xu

Abstract

In the face of quality problems in government procurement of elderly care services, mastering relationships between quality‐influencing factors and identifying key factors is beneficial for managers to make correct quality control decisions. From the complex networks' perspective, quality‐influencing factors of government purchasing elderly care services are obtained by case analysis, and the influencing factors' network topology is constructed. Importance indexes of nodes are determined with complex network theory, and multi‐indexes are fused by the Pythagoras TOPSIS to evaluate the importance of each factor. The results reveal key factors in the quality of government procurement of elderly care services.

Suggested Citation

  • Zhengnan Lu & Yuting Zhang & Lan Xu, 2022. "Quality control decision of government procurement of elderly care service based on multi‐index fusion of Pythagoras TOPSIS: Perspective of complex network," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 1773-1791, September.
    • Handle: RePEc:wly:mgtdec:v:43:y:2022:i:6:p:1773-1791
    DOI: 10.1002/mde.3488
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/mde.3488
    Download Restriction: no
    File URL: https://libkey.io/10.1002/mde.3488?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Olga Milliken & Rose Anne Devlin & Victoria Barham & William Hogg & Simone Dahrouge, 2011. "Comparative Efficiency Assessment of Primary Care Service Delivery Models Using Data Envelopment Analysis," Canadian Public Policy, University of Toronto Press, vol. 37(1), pages 85-109, March.
    2. Elaheh Nasiri & Asgarali Bouyer & Esmaeil Nourani, 2019. "A node representation learning approach for link prediction in social networks using game theory and K-core decomposition," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 92(10), pages 1-13, October.
    3. Bin Zhou & Sen Pei & Lev Muchnik & Xiangyi Meng & Xiaoke Xu & Alon Sela & Shlomo Havlin & H. Eugene Stanley, 2020. "Realistic modelling of information spread using peer-to-peer diffusion patterns," Nature Human Behaviour, Nature, vol. 4(11), pages 1198-1207, November.
    4. Andreas Koulouris & Ioannis Katerelos & Theodore Tsekeris, 2013. "Multi-Equilibria Regulation Agent-Based Model of Opinion Dynamics in Social Networks," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 11(1), pages 51-70.
    5. Anthony Chen & Chao Yang & Sirisak Kongsomsaksakul & Ming Lee, 2007. "Network-based Accessibility Measures for Vulnerability Analysis of Degradable Transportation Networks," Networks and Spatial Economics, Springer, vol. 7(3), pages 241-256, September.
    6. Knapp, Martin & Bauer, Annette & Perkins, Margaret & Snell, Tom, 2013. "Building community capital in social care: is there an economic case?," LSE Research Online Documents on Economics 46440, London School of Economics and Political Science, LSE Library.
    7. Shouzhen Zeng & Jianping Chen & Xingsen Li, 2016. "A Hybrid Method for Pythagorean Fuzzy Multiple-Criteria Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 403-422, 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. Yucesan, Melih & Kahraman, Gökhan, 2019. "Risk evaluation and prevention in hydropower plant operations: A model based on Pythagorean fuzzy AHP," Energy Policy, Elsevier, vol. 126(C), pages 343-351.
    2. Ermagun, Alireza & Tajik, Nazanin & Janatabadi, Fatemeh & Mahmassani, Hani, 2023. "Uncertainty in vulnerability of metro transit networks: A global perspective," Journal of Transport Geography, Elsevier, vol. 113(C).
    3. Tamsin Thomas & James Baker & Debbie Massey & Daniel D’Appio & Christina Aggar, 2020. "Stepped-Wedge Cluster Randomised Trial of Social Prescribing of Forest Therapy for Quality of Life and Biopsychosocial Wellbeing in Community-Living Australian Adults with Mental Illness: Protocol," IJERPH, MDPI, vol. 17(23), pages 1-14, December.
    4. Xu, Xiangdong & Qu, Kai & Chen, Anthony & Yang, Chao, 2021. "A new day-to-day dynamic network vulnerability analysis approach with Weibit-based route adjustment process," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    5. Zhichao Wang & Valentin Zelenyuk, 2021. "Performance Analysis of Hospitals in Australia and its Peers: A Systematic Review," CEPA Working Papers Series WP012021, School of Economics, University of Queensland, Australia.
    6. Amir Al Hamdi Redzuan & Rozana Zakaria & Aznah Nor Anuar & Eeydzah Aminudin & Norbazlan Mohd Yusof, 2022. "Road Network Vulnerability Based on Diversion Routes to Reconnect Disrupted Road Segments," Sustainability, MDPI, vol. 14(4), pages 1-22, February.
    7. Siva Srikukenthiran & Amer Shalaby, 2017. "Enabling large-scale transit microsimulation for disruption response support using the Nexus platform," Public Transport, Springer, vol. 9(1), pages 411-435, July.
    8. Aybike Ulusan & Ozlem Ergun, 2018. "Restoration of services in disrupted infrastructure systems: A network science approach," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-28, February.
    9. Hari Darshan Arora & Anjali Naithani, 2024. "Evaluating performance of novel similarity measures of Pythagorean fuzzy sets and their applications in pattern recognition and medical diagnosis," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(7), pages 3485-3494, July.
    10. Seungkyu Ryu & Anthony Chen & Xiangdong Xu & Keechoo Choi, 2014. "A Dual Approach for Solving the Combined Distribution and Assignment Problem with Link Capacity Constraints," Networks and Spatial Economics, Springer, vol. 14(2), pages 245-270, June.
    11. Johanna Guth & Sven Wursthorn & Andreas Ch. Braun & Sina Keller, 2019. "Development of a generic concept to analyze the accessibility of emergency facilities in critical road infrastructure for disaster scenarios: exemplary application for the 2017 wildfires in Chile and Portugal," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 97(3), pages 979-999, July.
    12. Ping Wang & Jie Wang & Guiwu Wei & Cun Wei, 2019. "Similarity Measures of q-Rung Orthopair Fuzzy Sets Based on Cosine Function and Their Applications," Mathematics, MDPI, vol. 7(4), pages 1-23, April.
    13. Erik Jenelius, 2010. "User inequity implications of road network vulnerability," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 2(3), pages 57-73.
    14. Zhichao Wang & Bao Hoang Nguyen & Valentin Zelenyuk, 2024. "Performance analysis of hospitals in Australia and its peers: a systematic and critical review," Journal of Productivity Analysis, Springer, vol. 62(2), pages 139-173, October.
    15. Sullivan, James L. & Novak, David C., 2024. "A method for evaluating accessibility in transportation problems considering social vulnerability," European Journal of Operational Research, Elsevier, vol. 317(3), pages 646-659.
    16. Mohamad Darayi & Kash Barker & Joost R. Santos, 2017. "Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network," Networks and Spatial Economics, Springer, vol. 17(4), pages 1111-1136, December.
    17. Khademi, Navid & Babaei, Mohsen & Schmöcker, Jan-Dirk & Fani, Amirhossein, 2018. "Analysis of incident costs in a vulnerable sparse rail network – Description and Iran case study," Research in Transportation Economics, Elsevier, vol. 70(C), pages 9-27.
    18. Jenelius, Erik & Mattsson, Lars-Göran, 2012. "Road network vulnerability analysis of area-covering disruptions: A grid-based approach with case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 746-760.
    19. Moshe Glickman & Tali Sharot, 2025. "How human–AI feedback loops alter human perceptual, emotional and social judgements," Nature Human Behaviour, Nature, vol. 9(2), pages 345-359, February.
    20. Almoghathawi, Yasser & Barker, Kash & Rocco, Claudio M. & Nicholson, Charles D., 2017. "A multi-criteria decision analysis approach for importance identification and ranking of network components," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 142-151.

    More about this item

    Statistics

    Access and download statistics

    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:wly:mgtdec:v:43:y:2022:i:6:p:1773-1791. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/7976 .

    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.