A hybrid multi-criteria decision-making approach for longitudinal data

Kalyana C. Chejarla () and Omkarprasad S. Vaidya ()
Additional contact information
Kalyana C. Chejarla: Institute of Management Technology Hyderabad
Omkarprasad S. Vaidya: Indian Institute of Management

OPSEARCH, 2024, vol. 61, issue 3, No 2, 1013-1060

Abstract: Abstract The purpose of this paper is to propose an approach to meet the need for a robust, longitudinal, and an objective multi-criteria decision-making method. This paper presents a hybrid approach that uses time-series data to produce multi-criteria decision-making (MCDM) based future rankings of alternatives. The suggested approach leverages the strengths of existing methods such as grey forecasting for small sample prediction, Criteria Importance Through Inter-criteria Correlation (CRITIC) for objective criteria weighting, Multiplicative, Multi-Objective Optimization on the basis of Ratio Analysis (MULTIMOORA) for robust aggregation, and a combination of rank integration methods. The proposed approach is illustrated using the case of the Logistics Performance Index dataset published by the World Bank for The Organisation for Economic Co-operation and Development (OECD) countries. Further, results are compared with the aggregate ranks published by the World bank (2010–2018), and the differences are discussed. Practitioners would find the suggested approach useful because of its predictive ability, versatility, objectivity, and robustness of results. Further, the suggested approach is a useful contribution to existing research in terms of providing a MCDM method to generate future ranks.

Keywords: Grey forecasting; Objective criteria weighting; Longitudinal MCDM; Hybrid MCDM; Logistics performance (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s12597-023-00736-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:opsear:v:61:y:2024:i:3:d:10.1007_s12597-023-00736-y

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/12597

DOI: 10.1007/s12597-023-00736-y

Access Statistics for this article

OPSEARCH is currently edited by Birendra Mandal

More articles in OPSEARCH from Springer, Operational Research Society of India
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().