IDEAS home Printed from https://ideas.repec.org/a/spr/grdene/v32y2023i5d10.1007_s10726-023-09840-2.html
   My bibliography  Save this article

Robust and High-Accessibility Ranking Method for Crowdsourcing-Based Decision Making

Author

Listed:
  • Phan-Anh-Huy Nguyen

    (HCMC University of Technology and Education)

  • Ping-Yu Hsu

    (National Central University)

Abstract

With the advancement of online technologies in recent years, crowdsourcing data has been used for numerous applications in many fields. The preference sequences obtained through crowdsourcing are valuable resources for ranking. However, the aggregation of incomplete and inconsistent preferences is complicated. To address these challenges, this study proposed a novel method termed robust crowd ranking (RCR) based on a consistent fuzzy c-means approach to increase the robustness and accessibility of aggregated preference sequences obtained through crowdsourcing. To verify the robustness, accessibility, and accuracy of RCR, comprehensive experiments were conducted using synthetic and real data. The simulation results validated that the RCR outperforms Borda Count, Dodgson, IRV and Tideman methods.

Suggested Citation

  • Phan-Anh-Huy Nguyen & Ping-Yu Hsu, 2023. "Robust and High-Accessibility Ranking Method for Crowdsourcing-Based Decision Making," Group Decision and Negotiation, Springer, vol. 32(5), pages 1211-1236, October.
    • Handle: RePEc:spr:grdene:v:32:y:2023:i:5:d:10.1007_s10726-023-09840-2
    DOI: 10.1007/s10726-023-09840-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10726-023-09840-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10726-023-09840-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bart P. G. Van Parys & Peyman Mohajerin Esfahani & Daniel Kuhn, 2021. "From Data to Decisions: Distributionally Robust Optimization Is Optimal," Management Science, INFORMS, vol. 67(6), pages 3387-3402, June.
    2. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    3. Cook, Wade D., 2006. "Distance-based and ad hoc consensus models in ordinal preference ranking," European Journal of Operational Research, Elsevier, vol. 172(2), pages 369-385, July.
    4. Lipovetsky, Stan & Michael Conklin, W., 2002. "Robust estimation of priorities in the AHP," European Journal of Operational Research, Elsevier, vol. 137(1), pages 110-122, February.
    5. repec:reg:rpubli:460 is not listed on IDEAS
    6. Baback Vaziri & Shaunak Dabadghao & Yuehwern Yih & Thomas L. Morin & Mark Lehto, 2020. "Crowd-Ranking: a Markov-based method for ranking alternatives," Operational Research, Springer, vol. 20(1), pages 279-295, 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. Chun-xiang Guo & Ying Peng, 2015. "Lattice Order Group Decision Making with Interval Probability Based on Prospect Theory," Group Decision and Negotiation, Springer, vol. 24(5), pages 753-775, September.
    2. Flavio Martins & Maria Fatima Almeida & Rodrigo Calili & Agatha Oliveira, 2020. "Design Thinking Applied to Smart Home Projects: A User-Centric and Sustainable Perspective," Sustainability, MDPI, vol. 12(23), pages 1-27, December.
    3. Jochen Wulf, 2020. "Development of an AHP hierarchy for managing omnichannel capabilities: a design science research approach," Business Research, Springer;German Academic Association for Business Research, vol. 13(1), pages 39-68, April.
    4. Wu, Zhangsheng & Li, Yue & Wang, Rong & Xu, Xu & Ren, Dongyang & Huang, Quanzhong & Xiong, Yunwu & Huang, Guanhua, 2023. "Evaluation of irrigation water saving and salinity control practices of maize and sunflower in the upper Yellow River basin with an agro-hydrological model based method," Agricultural Water Management, Elsevier, vol. 278(C).
    5. D’Inverno, Giovanna & Carosi, Laura & Romano, Giulia & Guerrini, Andrea, 2018. "Water pollution in wastewater treatment plants: An efficiency analysis with undesirable output," European Journal of Operational Research, Elsevier, vol. 269(1), pages 24-34.
    6. Nermin Kişi, 2019. "A Strategic Approach to Sustainable Tourism Development Using the A’WOT Hybrid Method: A Case Study of Zonguldak, Turkey," Sustainability, MDPI, vol. 11(4), pages 1-19, February.
    7. Pathiraja, Erandathie & Griffith, Garry & Farquharson, Robert & Faggia, Rob, 2019. "The Cost of Climate Change to Agricultural Industries: Coconuts in Sri Lanka," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 10(05), December.
    8. Ayodele, T.R. & Ogunjuyigbe, A.S.O. & Odigie, O. & Munda, J.L., 2018. "A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria," Applied Energy, Elsevier, vol. 228(C), pages 1853-1869.
    9. V. Srinivasan & G. Shainesh & Anand K. Sharma, 2015. "An approach to prioritize customer-based, cost-effective service enhancements," The Service Industries Journal, Taylor & Francis Journals, vol. 35(14), pages 747-762, October.
    10. Patricija Bajec & Danijela Tuljak-Suban, 2019. "An Integrated Analytic Hierarchy Process—Slack Based Measure-Data Envelopment Analysis Model for Evaluating the Efficiency of Logistics Service Providers Considering Undesirable Performance Criteria," Sustainability, MDPI, vol. 11(8), pages 1-18, April.
    11. Abareshi, Maryam & Zaferanieh, Mehdi, 2019. "A bi-level capacitated P-median facility location problem with the most likely allocation solution," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 1-20.
    12. Franceschini, Fiorenzo & Maisano, Domenico, 2015. "Checking the consistency of the solution in ordinal semi-democratic decision-making problems," Omega, Elsevier, vol. 57(PB), pages 188-195.
    13. Datu Buyung Agusdinata & Wenjuan Liu & Sinta Sulistyo & Philippe LeBillon & Je'anne Wegner, 2023. "Evaluating sustainability impacts of critical mineral extractions: Integration of life cycle sustainability assessment and SDGs frameworks," Journal of Industrial Ecology, Yale University, vol. 27(3), pages 746-759, June.
    14. Xinxin Liu & Xiaosheng Wang & Haiying Guo & Xiaojie An, 2021. "Benefit Allocation in Shared Water-Saving Management Contract Projects Based on Modified Expected Shapley Value," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 39-62, January.
    15. Sushil, 2019. "Efficient interpretive ranking process incorporating implicit and transitive dominance relationships," Annals of Operations Research, Springer, vol. 283(1), pages 1489-1516, December.
    16. Kokaraki, Nikoleta & Hopfe, Christina J. & Robinson, Elaine & Nikolaidou, Elli, 2019. "Testing the reliability of deterministic multi-criteria decision-making methods using building performance simulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 991-1007.
    17. Hossein Yousefi & Saheb Ghanbari Motlagh & Mohammad Montazeri, 2022. "Multi-Criteria Decision-Making System for Wind Farm Site-Selection Using Geographic Information System (GIS): Case Study of Semnan Province, Iran," Sustainability, MDPI, vol. 14(13), pages 1-27, June.
    18. Moumita Palchaudhuri & Sujata Biswas, 2016. "Application of AHP with GIS in drought risk assessment for Puruliya district, India," 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. 84(3), pages 1905-1920, December.
    19. Kadir Kaan GÖNCÜ & Onur ÇETIN, 2022. "Evaluation Of Location Selection Criteria For Coordination Management Centers And Logistic Support Units In Disaster Areas With Ahp Method," Prizren Social Science Journal, SHIKS, vol. 6(2), pages 15-23, August.
    20. Tommaso Ortalli & Andrea Di Martino & Michela Longo & Dario Zaninelli, 2024. "Make-or-Buy Policy Decision in Maintenance Planning for Mobility: A Multi-Criteria Approach," Logistics, MDPI, vol. 8(2), pages 1-18, May.

    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:spr:grdene:v:32:y:2023:i:5:d:10.1007_s10726-023-09840-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.