IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2022i1p144-d1017471.html
   My bibliography  Save this article

Formulation of a Grey Sequence and an Optimization Solution to Present Multi-Layer Family Networks

Author

Listed:
  • Shahryar Sorooshian

    (Department of Business Administration, University of Gothenburg, 40530 Gothenburg, Sweden
    Department of Management, Apadana Institute of Higher Education, Shiraz 7187985443, Iran
    School of Prime Logistics, Saito University College, Petaling Jaya 46200, Malaysia)

Abstract

Despite the potential benefits of family relationships and family events, insufficient studies have been undertaken to address how to overcome their obstacles. So, the main objective of this paper is to present a systematic model for prioritizing family members in response to standing limitations on family relationships. For this, the chosen methodology is conceptual sequence modeling, and the proposed model is optimized to include family membership motives and demotivators. Moreover, multiple criteria for the membership nominations are included to respond to the dynamic scenarios and complexity of decision-making. The feasibility of the proposed model is proven in a numerical case. Thus, the contribution of the proposed model is predictable to be from event planning to relative relationship management.

Suggested Citation

  • Shahryar Sorooshian, 2022. "Formulation of a Grey Sequence and an Optimization Solution to Present Multi-Layer Family Networks," Mathematics, MDPI, vol. 11(1), pages 1-11, December.
    • Handle: RePEc:gam:jmathe:v:11:y:2022:i:1:p:144-:d:1017471
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/1/144/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/1/144/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Haddad, Malik & Sanders, David, 2018. "Selection of discrete multiple criteria decision making methods in the presence of risk and uncertainty," Operations Research Perspectives, Elsevier, vol. 5(C), pages 357-370.
    2. Sorooshian, Shahryar & Azizan, Noor Azlinna & Ale Ebrahim, Nader, 2022. "Weighted Aggregated Sum Product Assessment," MPRA Paper 114715, University Library of Munich, Germany, revised 31 Aug 2022.
    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. Haddad, M. & Sanders, D. & Tewkesbury, G., 2020. "Selecting a discrete multiple criteria decision making method for Boeing to rank four global market regions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 1-15.
    2. Magdalena Krysiak & Aldona Kluczek, 2021. "A Multifaceted Challenge to Enhance Multicriteria Decision Support for Energy Policy," Energies, MDPI, vol. 14(14), pages 1-20, July.
    3. Kuzyutin, Denis & Smirnova, Nadezhda & Gromova, Ekaterina, 2019. "Long-term implementation of the cooperative solution in a multistage multicriteria game," Operations Research Perspectives, Elsevier, vol. 6(C).
    4. Johanna Vásquez & Sergio Botero, 2020. "Hybrid Methodology to Improve Health Status Utility Values Derivation Using EQ-5D-5L and Advanced Multi-Criteria Techniques," IJERPH, MDPI, vol. 17(4), pages 1-18, February.
    5. Renan Favarão da Silva & Marjorie Maria Bellinello & Gilberto Francisco Martha de Souza & Sara Antomarioni & Maurizio Bevilacqua & Filippo Emanuele Ciarapica, 2021. "Deciding a Multicriteria Decision-Making (MCDM) Method to Prioritize Maintenance Work Orders of Hydroelectric Power Plants," Energies, MDPI, vol. 14(24), pages 1-22, December.
    6. Dayo-Olupona, Oluwatobi & Genc, Bekir & Onifade, Moshood, 2020. "Technology adoption in mining: A multi-criteria method to select emerging technology in surface mines," Resources Policy, Elsevier, vol. 69(C).
    7. Vaida Zemlickienė & Zenonas Turskis, 2022. "Performance Measurement in R&D Projects: Relevance of Indicators Based on US and German Experts," Sustainability, MDPI, vol. 14(18), pages 1-15, September.
    8. Vaida Zemlickienė & Zenonas Turskis, 2022. "Determination of Importance of Key Decision Points in the Technology Commercialization Process: Attitude of the US and German Experts," Sustainability, MDPI, vol. 14(23), pages 1-13, November.
    9. Tohidi, Amirhossein & Ghorbani, Mohammad & Karbasi, Ali-Reza & Asgharpourmasouleh, Ahmadreza & Hassani-Mahmooei, Behrooz, 2020. "Comparison of Fuzzy Multi-Criteria Decision-Making Methods to Rank Business Strategies and Marketing Resources," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 10(3), September.
    10. Arjomandi, Amin & Mortazavi, Seyed Abolghasem & Khalilian, Sadegh & Garizi, Arash Zare, 2021. "Optimal land-use allocation using MCDM and SWAT for the Hablehroud Watershed, Iran," Land Use Policy, Elsevier, vol. 100(C).
    11. Betul Yagmahan & Hilal Yılmaz, 2023. "An integrated ranking approach based on group multi-criteria decision making and sensitivity analysis to evaluate charging stations under sustainability," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(1), pages 96-121, January.
    12. Pasura Aungkulanon & Walailak Atthirawong & Pongchanun Luangpaiboon, 2023. "Fuzzy Analytical Hierarchy Process for Strategic Decision Making in Electric Vehicle Adoption," Sustainability, MDPI, vol. 15(8), pages 1-20, April.
    13. Majumdar, Abhijit & Tiwari, Manoj Kumar & Agarwal, Aastha & Prajapat, Kanika, 2021. "A new case of rank reversal in analytic hierarchy process due to aggregation of cost and benefit criteria," Operations Research Perspectives, Elsevier, vol. 8(C).
    14. Sorooshian, Shahryar & Tavana, Madjid & Ribeiro-Navarrete, Samuel, 2023. "From classical interpretive structural modeling to total interpretive structural modeling and beyond: A half-century of business research," Journal of Business Research, Elsevier, vol. 157(C).
    15. Omrani, Hashem & Valipour, Mahsa & Emrouznejad, Ali, 2021. "A novel best worst method robust data envelopment analysis: Incorporating decision makers’ preferences in an uncertain environment," Operations Research Perspectives, Elsevier, vol. 8(C).
    16. Thi Yen Pham & Gi-Tae Yeo, 2019. "Evaluation of Transshipment Container Terminals’ Service Quality in Vietnam: From the Shipping Companies’ Perspective," Sustainability, MDPI, vol. 11(5), pages 1-14, March.

    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:jmathe:v:11:y:2022:i:1:p:144-:d:1017471. 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.