IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v307y2023i2p827-841.html
   My bibliography  Save this article

Multi-criteria mapping and prioritization of Arctic and North Atlantic maritime safety and security needs

Author

Listed:
  • Jones, Dylan
  • Labib, Ashraf
  • Willis, Kevin
  • Costello, Joseph T
  • Ouelhadj, Djamila
  • Ikonen, Emmi Susanna
  • Dominguez Cainzos, Mikel

Abstract

This paper details a methodology for the mapping and prioritization of needs for research and innovation across a multi-disciplinary topic area. The methodology is applied to needs arising from the field of Arctic maritime safety and security, in order to provide a roadmap for an ongoing multi-national European Union (EU) funded research project. A needs hierarchy containing topics, needs and sub-needs is first formed by utilization of multiple sources including facilitated stakeholder workshops, literature review and semi-structured questionnaires. A further round of stakeholder opinion is then sought in order to ascertain the importance and level of challenge involved in solving each identified sub-need. This information is utilized to form a PICK (Possible, Implement, Challenge, Keep Back) chart in order to visualize and categorize the sub-needs. A goal programming knapsack model is formulated to select a set of priority needs that satisfy goals relating to the maximization of overall importance, the balance between topics at the first level of the need hierarchy and the balance between more challenge (for longer term research) and implement (for shorter term implementation) needs. Sensitivity analysis is conducted around the number of chosen projects and the goal programming weights. Conclusions are hence drawn with respect to the methodology and the Arctic maritime safety and security field of application.

Suggested Citation

  • Jones, Dylan & Labib, Ashraf & Willis, Kevin & Costello, Joseph T & Ouelhadj, Djamila & Ikonen, Emmi Susanna & Dominguez Cainzos, Mikel, 2023. "Multi-criteria mapping and prioritization of Arctic and North Atlantic maritime safety and security needs," European Journal of Operational Research, Elsevier, vol. 307(2), pages 827-841.
  • Handle: RePEc:eee:ejores:v:307:y:2023:i:2:p:827-841
    DOI: 10.1016/j.ejor.2022.09.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221722006932
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2022.09.002?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. Parreiras, R.O. & Kokshenev, I. & Carvalho, M.O.M. & Willer, A.C.M. & Dellezzopolles, C.F. & Nacif, D.B. & Santana, J.A., 2019. "A flexible multicriteria decision-making methodology to support the strategic management of Science, Technology and Innovation research funding programs," European Journal of Operational Research, Elsevier, vol. 272(2), pages 725-739.
    2. Jones, Dylan, 2011. "A practical weight sensitivity algorithm for goal and multiple objective programming," European Journal of Operational Research, Elsevier, vol. 213(1), pages 238-245, August.
    3. Kiani Mavi, Reza & Kiani Mavi, Neda, 2021. "National eco-innovation analysis with big data: A common-weights model for dynamic DEA," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    4. Tommi Gustafsson & Ahti Salo & Ramakrishnan Ramanathan, 2003. "Multicriteria methods for technology foresight," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(2-3), pages 235-255.
    5. Babashahi, Saeideh & Hansen, Paul & Sullivan, Trudy, 2021. "Creating a priority list of non-communicable diseases to support health research funding decision-making," Health Policy, Elsevier, vol. 125(2), pages 221-228.
    6. Maria Iglesias-Mendoza & Akilu Yunusa-Kaltungo & Sara Hadleigh-Dunn & Ashraf Labib, 2021. "Learning How to Learn from Disasters through a Comparative Dichotomy Analysis: Grenfell Tower and Hurricane Katrina Case Studies," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    7. Mavrotas, George & Makryvelios, Evangelos, 2021. "Combining multiple criteria analysis, mathematical programming and Monte Carlo simulation to tackle uncertainty in Research and Development project portfolio selection: A case study from Greece," European Journal of Operational Research, Elsevier, vol. 291(2), pages 794-806.
    8. B B Bakirli & C Gencer & E K Aydoğan, 2014. "A combined approach for fuzzy multi-objective multiple knapsack problems for defence project selection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(7), pages 1001-1016, July.
    9. Hsing Hung Chen & He-Yau Kang & Amy H I Lee & Shountao Chen, 2015. "Strategies, decisions and operations for keeping exploitative and exploratory activities balanced," Knowledge Management Research & Practice, Taylor & Francis Journals, vol. 13(2), pages 198-213, May.
    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. Mitchell Caroline & Van Laar Darren & Strevens Caroline & Labib Ashraf, 2023. "No Harm in Learning – A Balanced High Reliability Organisation (HRO) Approach in Healthcare," Journal of Social and Economic Statistics, Sciendo, vol. 12(2), pages 1-19, December.

    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. Stojčić, Nebojša, 2021. "Social and private outcomes of green innovation incentives in European advancing economies," Technovation, Elsevier, vol. 104(C).
    2. Demirci, Mehmet & Bettinger, Pete, 2015. "Using mixed integer multi-objective goal programming for stand tending block designation: A case study from Turkey," Forest Policy and Economics, Elsevier, vol. 55(C), pages 28-36.
    3. Jones, Dylan & Jimenez, Mariano, 2013. "Incorporating additional meta-objectives into the extended lexicographic goal programming framework," European Journal of Operational Research, Elsevier, vol. 227(2), pages 343-349.
    4. Mila Bravo & Dylan Jones & David Pla-Santamaria & Francisco Salas-Molina, 2022. "Encompassing statistically unquantifiable randomness in goal programming: an application to portfolio selection," Operational Research, Springer, vol. 22(5), pages 5685-5706, November.
    5. Mila Bravo & Dylan Jones & David Pla-Santamaria & Graham Wall, 2018. "Robustness of weighted goal programming models: an analytical measure and its application to offshore wind-farm site selection in United Kingdom," Annals of Operations Research, Springer, vol. 267(1), pages 65-79, August.
    6. Jones, Dylan & Firouzy, Sina & Labib, Ashraf & Argyriou, Athanasios V., 2022. "Multiple criteria model for allocating new medical robotic devices to treatment centres," European Journal of Operational Research, Elsevier, vol. 297(2), pages 652-664.
    7. Carayannis, Elias G. & Grigoroudis, Evangelos & Wurth, Bernd, 2022. "OR for entrepreneurial ecosystems: A problem-oriented review and agenda," European Journal of Operational Research, Elsevier, vol. 300(3), pages 791-808.
    8. Bresciani, Stefano & Puertas, Rosa & Ferraris, Alberto & Santoro, Gabriele, 2021. "Innovation, environmental sustainability and economic development: DEA-Bootstrap and multilevel analysis to compare two regions," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    9. Ronyastra, I Made & Saw, Lip Huat & Low, Foon Siang, 2024. "Monte Carlo simulation-based financial risk identification for industrial estate as post-mining land usage in Indonesia," Resources Policy, Elsevier, vol. 89(C).
    10. Paola Cappanera & Filippo Visintin & Carlo Banditori, 2018. "Addressing conflicting stakeholders’ priorities in surgical scheduling by goal programming," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 252-271, June.
    11. Dylan F. Jones & Graham Wall, 2016. "An extended goal programming model for site selection in the offshore wind farm sector," Annals of Operations Research, Springer, vol. 245(1), pages 121-135, October.
    12. Chang, Ching-Ter, 2011. "Multi-choice goal programming with utility functions," European Journal of Operational Research, Elsevier, vol. 215(2), pages 439-445, December.
    13. Oliveira, Washington A. & Fiorotto, Diego J. & Song, Xiang & Jones, Dylan F., 2021. "An extended goal programming model for the multiobjective integrated lot-sizing and cutting stock problem," European Journal of Operational Research, Elsevier, vol. 295(3), pages 996-1007.
    14. George Mavrotas & Evangelos Makryvelios, 2023. "R&D project portfolio selection using the Iterative Trichotomic Approach in order to study how subjectivity of the weights is reflected in the selected projects of the final portfolio," Operational Research, Springer, vol. 23(3), pages 1-18, September.
    15. Khorramshahgol, Reza & Al-Husain, Raed, 2021. "A GP-AHP approach to Design Responsive Supply Chains for Pareto Customers," Operations Research Perspectives, Elsevier, vol. 8(C).
    16. Zhang, Xinwei & Yan, Yong & Wang, Lilin & Wang, Yang, 2024. "A ranking approach for robust portfolio decision analysis based on multilinear portfolio utility functions and incomplete preference information," Omega, Elsevier, vol. 122(C).
    17. Ibrahim, Awad Elsayed Awad & Elamer, Ahmed A. & Ezat, Amr Nazieh, 2021. "The convergence of big data and accounting: innovative research opportunities," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    18. Gasparini, Gaia & Brunelli, Matteo & Chiriac, Marius Dan, 2022. "Multi-period portfolio decision analysis: A case study in the infrastructure management sector," Operations Research Perspectives, Elsevier, vol. 9(C).
    19. Jan Ondrus & Tung Bui & Yves Pigneur, 2015. "A Foresight Support System Using MCDM Methods," Group Decision and Negotiation, Springer, vol. 24(2), pages 333-358, March.
    20. Franco, L. Alberto & Montibeller, Gilberto, 2010. "Facilitated modelling in operational research," European Journal of Operational Research, Elsevier, vol. 205(3), pages 489-500, September.

    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:ejores:v:307:y:2023:i:2:p:827-841. 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.elsevier.com/locate/eor .

    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.