IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v186y2023ipas0040162522006539.html
   My bibliography  Save this article

Selecting the most suitable blockchain platform: A case study on the healthcare industry using a novel rough MCDM framework

Author

Listed:
  • Erol, Ismail
  • Oztel, Ahmet
  • Searcy, Cory
  • Medeni, İ. Tolga

Abstract

Healthcare networks are sophisticated systems, which are commonly comprised of medical and drug suppliers, insurance companies, third-party logistics (3PL) providers, and regulators. Effective healthcare systems should be capable of sustainably delivering high quality and accessible patient care services using data shared through the best available technologies. However, healthcare data are generally hard to comprehend, use, and share since they are also inaccessible, non-standardized, and disseminated throughout the network. Blockchain may be employed to alleviate the impact of these challenges. However, only a few blockchain platforms (BP) have reached the stable design and established user base needed to give a healthcare organization (HO) confidence in their implementation. Each digital transformation project employing blockchain faces the challenge of picking a BP suitable to the requirements of a HO. While some research has been conducted to choose an appropriate BP, quantitative studies on specific industries, including healthcare, are currently insufficient. This investigation provides a case addressing the selection of the most feasible BP for a healthcare group. To this end, we propose a new multi-criteria decision-making (MCDM) framework that integrates the extent analysis-based rough Analytic Hierarchy Process (RAHP-E) and rough Compromise Programming (RCP). The findings of this study are validated through several analyses.

Suggested Citation

  • Erol, Ismail & Oztel, Ahmet & Searcy, Cory & Medeni, İ. Tolga, 2023. "Selecting the most suitable blockchain platform: A case study on the healthcare industry using a novel rough MCDM framework," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
  • Handle: RePEc:eee:tefoso:v:186:y:2023:i:pa:s0040162522006539
    DOI: 10.1016/j.techfore.2022.122132
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162522006539
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2022.122132?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. Yuanfeng Cai & Dan Zhu, 2016. "Fraud detections for online businesses: a perspective from blockchain technology," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 2(1), pages 1-10, December.
    2. Greco, Salvatore & Matarazzo, Benedetto & Slowinski, Roman, 2001. "Rough sets theory for multicriteria decision analysis," European Journal of Operational Research, Elsevier, vol. 129(1), pages 1-47, February.
    3. Chang, Yu-Chun & Lee, Wei-Hao & Wu, Chi-Hung, 2019. "Airline new route selection using compromise programming - The case of Taiwan-Europe," Journal of Air Transport Management, Elsevier, vol. 76(C), pages 10-20.
    4. Parviz Fattahi & Saeed Fayyaz, 2010. "A Compromise Programming Model to Integrated Urban Water Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(6), pages 1211-1227, April.
    5. Allouche, Mohamed Anis & Aouni, Belaïd & Martel, Jean-Marc & Loukil, Taïcir & Rebaï, Abdelwaheb, 2009. "Solving multi-criteria scheduling flow shop problem through compromise programming and satisfaction functions," European Journal of Operational Research, Elsevier, vol. 192(2), pages 460-467, January.
    6. Chang, Da-Yong, 1996. "Applications of the extent analysis method on fuzzy AHP," European Journal of Operational Research, Elsevier, vol. 95(3), pages 649-655, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sudhanshu Joshi & Manu Sharma & Banu Y. Ekren & Yigit Kazancoglu & Sunil Luthra & Mukesh Prasad, 2023. "Assessing Supply Chain Innovations for Building Resilient Food Supply Chains: An Emerging Economy Perspective," Sustainability, MDPI, vol. 15(6), pages 1-21, March.

    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. Choudhary, Devendra & Shankar, Ravi, 2012. "An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India," Energy, Elsevier, vol. 42(1), pages 510-521.
    2. Durbach, Ian N. & Stewart, Theodor J., 2012. "Modeling uncertainty in multi-criteria decision analysis," European Journal of Operational Research, Elsevier, vol. 223(1), pages 1-14.
    3. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    4. Benyou Jia & Slobodan P. Simonovic & Pingan Zhong & Zhongbo Yu, 2016. "A Multi-Objective Best Compromise Decision Model for Real-Time Flood Mitigation Operations of Multi-Reservoir System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3363-3387, August.
    5. Hu, Zhineng & Chen, Yazhen & Yao, Liming & Wei, Changting & Li, Chaozhi, 2016. "Optimal allocation of regional water resources: From a perspective of equity–efficiency tradeoff," Resources, Conservation & Recycling, Elsevier, vol. 109(C), pages 102-113.
    6. Pang, Jifang & Liang, Jiye, 2012. "Evaluation of the results of multi-attribute group decision-making with linguistic information," Omega, Elsevier, vol. 40(3), pages 294-301.
    7. M. J. Naderi & M. S. Pishvaee, 2017. "Robust bi-objective macroscopic municipal water supply network redesign and rehabilitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2689-2711, July.
    8. Eduardo Fernández & José Rui Figueira & Jorge Navarro, 2023. "A theoretical look at ordinal classification methods based on comparing actions with limiting boundaries between adjacent classes," Annals of Operations Research, Springer, vol. 325(2), pages 819-843, June.
    9. Doumpos, M. & Marinakis, Y. & Marinaki, M. & Zopounidis, C., 2009. "An evolutionary approach to construction of outranking models for multicriteria classification: The case of the ELECTRE TRI method," European Journal of Operational Research, Elsevier, vol. 199(2), pages 496-505, December.
    10. Juan Carlos Martín & Veronika Rudchenko & María-Victoria Sánchez-Rebull, 2020. "The Role of Nationality and Hotel Class on Guests’ Satisfaction. A Fuzzy-TOPSIS Approach Applied in Saint Petersburg," Administrative Sciences, MDPI, vol. 10(3), pages 1-24, September.
    11. Jelena Lukić & Mirjana Misita & Dragan D. Milanović & Ankica Borota-Tišma & Aleksandra Janković, 2022. "Determining the Risk Level in Client Analysis by Applying Fuzzy Logic in Insurance Sector," Mathematics, MDPI, vol. 10(18), pages 1-17, September.
    12. Sharma, Mahak & Antony, Rose & Sehrawat, Rajat & Cruz, Angel Contreras & Daim, Tugrul U., 2022. "Exploring post-adoption behaviors of e-service users: Evidence from the hospitality sector /online travel services," Technology in Society, Elsevier, vol. 68(C).
    13. Skorupski, Jacek & Uchroński, Piotr, 2017. "A fuzzy model for evaluating metal detection equipment at airport security screening checkpoints," International Journal of Critical Infrastructure Protection, Elsevier, vol. 16(C), pages 39-48.
    14. Bouyssou, Denis & Marchant, Thierry, 2007. "An axiomatic approach to noncompensatory sorting methods in MCDM, II: More than two categories," European Journal of Operational Research, Elsevier, vol. 178(1), pages 246-276, April.
    15. repec:dau:papers:123456789/4080 is not listed on IDEAS
    16. Becchio, Cristina & Bottero, Marta Carla & Corgnati, Stefano Paolo & Dell’Anna, Federico, 2018. "Decision making for sustainable urban energy planning: an integrated evaluation framework of alternative solutions for a NZED (Net Zero-Energy District) in Turin," Land Use Policy, Elsevier, vol. 78(C), pages 803-817.
    17. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea," Energies, MDPI, vol. 10(12), pages 1-22, December.
    18. Chia-Nan Wang & Ngoc-Ai-Thy Nguyen & Thanh-Tuan Dang & Chen-Ming Lu, 2021. "A Compromised Decision-Making Approach to Third-Party Logistics Selection in Sustainable Supply Chain Using Fuzzy AHP and Fuzzy VIKOR Methods," Mathematics, MDPI, vol. 9(8), pages 1-27, April.
    19. Fernandez, Eduardo & Navarro, Jorge & Bernal, Sergio, 2010. "Handling multicriteria preferences in cluster analysis," European Journal of Operational Research, Elsevier, vol. 202(3), pages 819-827, May.
    20. Pawel Lezanski & Maria Pilacinska, 2018. "The dominance-based rough set approach to cylindrical plunge grinding process diagnosis," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 989-1004, June.
    21. Tsoukias, Alexis, 2008. "From decision theory to decision aiding methodology," European Journal of Operational Research, Elsevier, vol. 187(1), pages 138-161, 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:eee:tefoso:v:186:y:2023:i:pa:s0040162522006539. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.