What is the Ordinal Priority Approach?
DOI:
https://doi.org/10.52812/msbd.72Keywords:
Evaluation research, multiple criteria decision analysis, ordinal priority approach, LINGO, software, Business decision makingAbstract
Humans, in their most important role as decision-makers, make choices every day. Simple choices don't even require a calculator, but more complicated ones require some calculation. Complicated choices, such as the ones where one has to choose one (or multiple) alternatives from a list of alternatives, whereas each alternative may be better than the other on different conflicting attributes, are not easy to make. Such problems are usually referred to as multiple attribute decision-making (MADM), and one of the easiest and most effective ways to solve such problems is the Ordinal Priority Approach (OPA). In this article, readers will learn: (1) what is the OPA (and some discussion on its background), (2) what distinguishes it from other MADM methods, (3) its scale, and (4) how to apply it. Readers, including those with the most elementary knowledge of mathematics and operations research, would find this article particularly useful as every effort has been made to make content easy to comprehend.
References
Agresti, A. (2010). Analysis of Ordinal Categorical Data (2nd Ed.). New Jersey: John Wiley & Sons.
Ala, A., Mahmoudi, A., Mirjalili, S., Simic, V., & Pamucar, D. (2023). Evaluating the Performance of various Algorithms for Wind Energy Optimization: A Hybrid Decision-Making model. Expert Systems with Applications, 221, 119731. https://doi.org/10.1016/j.eswa.2023.119731
Asgharpour, M. J. (2003). Group Decision Making and Game Theory in Operation Research. Tehran University Press.
Ataei, Y., Mahmoudi, A., Feylizadeh, M. R., & Li, D. F. (2020). Ordinal priority approach (OPA) in multiple attribute decision-making. Applied Soft Computing, 86, 105893. https://doi.org/10.1016/j.asoc.2019.105893
Bafahm, A., & Sun, M. (2019). Some conflicting results in the analytic hierarchy process. International Journal of Information Technology & Decision Making, 18(02), 465-486. https://doi.org/10.1142/S0219622018500517
Bah, M. K., & Tulkinov, S. (2022). Evaluation of Automotive Parts Suppliers through Ordinal Priority Approach and TOPSIS. Management Science and Business Decisions, 2(1), 5-17. https://doi.org/10.52812/msbd.37
Barron, F. H., & Barrett, B. E. (1996). Decision quality using ranked attribute weights. Management Science, 42(11), 1515-1523. http://dx.doi.org/10.1287/mnsc.42.11.1515
Barzilai, J. (2001, January). Notes on the analytic hierarchy process. In Proceedings of the NSF design and manufacturing research conference (pp. 1-6).
Borgatta, E. F., & Bohrnstedt, G. W. (1980). Level of measurement: Once over again. Sociological Methods & Research, 9(2), 147-160. https://doi.org/10.1177/004912418000900202
Brunt, M. W., Kreiberg, H., & von Keyserlingk, M. A. (2022). Invertebrate research without ethical or regulatory oversight reduces public confidence and trust. Humanities and Social Sciences Communications, 9(1), 1-9. https://doi.org/10.1057/s41599-022-01272-8
Candra, C. S. (2022). Evaluation of Barriers to Electric Vehicle Adoption in Indonesia through Grey Ordinal Priority Approach. International Journal of Grey Systems, 2(1), 38-56. https://doi.org/10.52812/ijgs.46
Chakraborty, S., Raut, R. D., Rofin, T. M., & Chakraborty, S. (2023). Optimization of drilling processes of aluminium metal matrix composites using the robust ordinal priority approach. Decision Analytics Journal, 7, 100258. https://doi.org/10.1016/j.dajour.2023.100258
Contreras, I. (2010). A distance-based consensus model with flexible choice of rank-position weights. Group Decision and Negotiation, 19(5), 441-456. https:// doi.org/10.1007/s10726-008-9127-9
Danielson M, & Ekenberg, L. (2017). A robustness study of state-of-the-art surrogate weights for MCDM. Group Decision and Negotiation, 26(4), 677-691. https:// doi.org/ 10.1007/s10726-016-9494-6
DCLG. (2009). Multi-criteria analysis: a manual. London: Department for Communities and Local Government.
Du, J, Liu, S., Javed, S.A., Goh, M., & Chen, Z. (2023). Enhancing Quality Function Deployment through the Integration of Rough Set and Ordinal Priority Approach: A Case Study in Electric Vehicle Manufacturing. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2023.3282228
Farkas, A. (2007). The analysis of the principal eigenvector of pairwise comparison matrices. Acta Polytechnica Hungarica, 4(2), 99-115.
Herzberger, H. G. (1973). Ordinal preference and rational choice. Econometrica: Journal of the Econometric Society, 187-237.
Hwang, C.-L., & Yoon, K. (1981). Multiple Attribute Decision Making Methods and Applications: A State-of-the-Art Survey. New York: Springer.
Javed, S. A., Mahmoudi, A., & Liu, S. (2020). Grey Absolute Decision Analysis (GADA) method for Multiple Criteria Group Decision Making under Uncertainty. International Journal of Fuzzy Systems, 22(4), 1073-1090. https://doi.org/10.1007/s40815-020-00827-8
Kmietowicz, Z. W., & Pearman, A. D. (1981). Decision theory and incomplete knowledge. England: Gower Publishing Co. Ltd.
Köksalan, M., Wallenius, J., & Zionts, S. (2016). An Early History of Multiple Criteria Decision Making. In: Greco, S., Ehrgott, M., Figueira, J. (eds) Multiple Criteria Decision Analysis. International Series in Operations Research & Management Science, vol 233. Springer, New York, NY. https:// doi. org/ 10. 1007/ 978-1- 4939- 3094-4_1
Mahmoudi, A., & Javed, S. A. (2022). Probabilistic Approach to Multi‑Stage Supplier Evaluation: Confidence Level Measurement in Ordinal Priority Approach. Group Decision and Negotiation, 31, 1051-1096. https://doi.org/10.1007/s10726-022-09790-1
Mahmoudi, A., & Javed, S. A. (2023). Uncertainty Analysis in Group Decisions through Interval Ordinal Priority Approach. Group Decision and Negotiation, 32, 807–833. https://doi.org/10.1007/s10726-023-09825-1
Mahmoudi, A., Deng, X., Javed, S. A., & Zhang, N. (2021). Sustainable Supplier Selection in Megaprojects through Grey Ordinal Priority Approach. Business Strategy and The Environment, 30, 318-339. https://doi.org/10.1002/bse.2623
Mahmoudi, A., Javed, S.A., & Mardani, A. (2022). Gresilient Supplier Selection through Fuzzy Ordinal Priority Approach: Decision-making in Post-COVID era. Operations Management Research, 15, 208–232 https://doi.org/10.1007/s12063-021-00178-z
Miller, G.A. (1956). The Magical Number Seven Plus or Minus Two: Some Limits on Our Capacity for Processing Information. Psychological Review, 63, 81-97.
Munier, N., & Hontoria, E. (2021). Uses and Limitations of the AHP Method: A Non-Mathematical and Rational Analysis. Switzerland: Springer
Nemoto, T., & Beglar, D. (2014). Developing Likert-scale questionnaires. In N. Sonda & A. Krause (Eds.), JALT2013 Conference Proceedings. Tokyo: JALT
Pearman, A. (2016). Fifty shades of Partial Information.... The Journal of Grey System, 28(1).
Pitka, P., Kovačević, T., Simeunović, M., Simeunović, M., & Jović, A. (2023, March). Estimation of transport service quality using an ordinal priority model. In: Proceedings of the Institution of Civil Engineers-Transport (pp. 1-10). Thomas Telford Ltd.
Popović, M., Andrić Gušavac, B., Marinković, S., & Pamučar, D. (2023). Selecting location of IT business units using unique DEA-MACBETH-OPA framework. Soft Computing. https://doi.org/10.1007/s00500-023-08451-y
Quartey-Papafio, T. K., Shajedul, I., & Dehaghani, A. R. (2021). Evaluating Suppliers for Healthcare Centre using Ordinal Priority Approach. Management Science and Business Decisions, 1(1), 5-11. https://doi.org/10.52812/msbd.12
Saaty, T.L., & Vargas, L.G. (2007). Dispersion of group judgments. Mathematical and Computer Modelling, 46, 918–925. https://doi.org/10.1016/j.mcm.2007.03.004
Sahashi, Y., Endo, H., Sugimoto, T., Nabeta, T., Nishizaki, K., Kikuchi, A., ... & Matsue, Y. (2021). Worries and concerns among healthcare workers during the coronavirus 2019 pandemic: A web-based cross-sectional survey. Humanities and Social Sciences Communications, 8(1), 41. https://doi.org/10.1057/s41599-021-00716-x
Shajedul, I. (2021). Evaluation of Low-Carbon Sustainable Technologies in Agriculture Sector through Grey Ordinal Priority Approach. International Journal of Grey Systems, 1(1), 5-26. https://doi.org/10.52812/ijgs.3
Stillwell, W. G., Seaver, D. A., & Edwards, W. (1981). A comparison of weight approximation techniques in multiattribute utility decision making. Organizational Behavior and Human Performance, 28(1), 62–77. https://doi.org/10.1016/0030-5073(81)90015-5
Su, C., Ma, X., Lv, J., Tu, T., & Li, H. (2022). A multilayer affective computing model with evolutionary strategies reflecting decision-makers' preferences in process control. ISA Transactions, 128, 565-578. https://doi.org/10.1016/j.isatra.2021.11.038
Triantaphyllou, E., & Mann, S. H. (1995). Using the analytic hierarchy process for decision making in engineering applications: some challenges. International Journal of Industrial Engineering: Applications and Practice, 2(1), 35-44.
Wiese, H. (2021). Advanced Microeconomics. Germany: Springer Gabler.
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Natural Science Research of Jiangsu Higher Education Institutions of China
Grant numbers 21KJB480011