A HYBRID APPROACH COMBINING CONJOINT ANALYSIS AND THE ANALYTIC HIERARCHY PROCESS FOR MULTICRITERIA GROUP DECISION-MAKING
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Published
Jun 13, 2025
Ruffin-Benoît M. Ngoie
Jean-Roger Bansimba
Falonne N. Mpolo Rama M. Bazangika Jean-Aimé B. Sakulu
Ruffin B. Mbaka Fabrice N. Bonkile
https://orcid.org/0000-0001-9348-9105
Jean-Roger Bansimba
Falonne N. Mpolo Rama M. Bazangika Jean-Aimé B. Sakulu
Ruffin B. Mbaka Fabrice N. Bonkile
Abstract
In this article, we introduce the Conjoint Analytic Hierarchy Process (CAHP), a novel multi-criteria aggregation function that hybridizes Conjoint Analysis (CA) and the Analytic Hierarchy Process (AHP). Most of the limitations of traditional multi-criteria methods are addressed by CAHP. The proposed approach has many practical implications in various sectors such as business, industry, healthcare, education, and more. The keystone of the method is to apply CA to obtain the weights of criteria before applying the usual AHP in the subsequent steps (level of alternatives). Prior to using the AHP, decision tables from decision-makers were transformed into a unique decision table using the arithmetic mean of alternatives’ performances on criteria. Appropriate formulas were then used to turn this aggregated decision table into pairwise comparison matrices, upon which the AHP was applied. We tested the CAHP in two real-world situations to demonstrate its reliability. The results show that the rankings obtained from CAHP are identical to those from other methods, such as TOPSIS, ELECTRE II, and PROMETHEE II. Future research should focus on developing user-friendly tools to facilitate CAHP application. Other perspectives would involve carefully classifying each criterion’s modalities to prevent inversions in respondent preferences during CA and assessing possible biases to manage unexpected preferences.
How to Cite
Ngoie, R.-B., Bansimba, J.-R., Mpolo, F., Bazangika, R., Sakulu, J.-A., Mbaka, R., & Bonkile, F. (2025). A HYBRID APPROACH COMBINING CONJOINT ANALYSIS AND THE ANALYTIC HIERARCHY PROCESS FOR MULTICRITERIA GROUP DECISION-MAKING. International Journal of the Analytic Hierarchy Process, 17(1). https://doi.org/10.13033/ijahp.v17i1.1308
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Keywords
AHP, Conjoint Analysis, Criteria Weighting, Group Decision-Making, Multicriteria Analysis, Pairwise Comparison
References
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Carricano, M., & Poujol, F. (2008). Analyse conjointe: Méthodes et applications. Paris: Dunod.
Chang, W.-Y., Taecharungroj, V., & Kapasuwan, S. (2022). Sustainable luxury consumers’ preferences and segments: Conjoint and cluster analyses. Sustainability, 14(15), 9551. https://doi.org/10.3390/su14159551
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Hong, B. X., Ichihashi, M., & Ngoc, N. T. B. (2024). Analysis of consumer preferences for green tea products: A randomized Conjoint Analysis in Thai Nguyen, Vietnam. Sustainability, 16(11), 4521. https://doi.org/10.3390/su16114521
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IBM Corp. (2015). IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM Corp.
Ieta, A., Silberberg, G., Kucerovsky, Z., & Greason, W. D. (2005). On scales and decision-making based on arithmetic mean. Quality & Quantity, 38(5), 559–575. https://doi.org/10.1007/s11135-005-2177-z
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Ishizaka, A., & Labib, A. (2011). Review of the main developments in the Analytic Hierarchy Process. Expert Systems with Applications, 38(11), 14336–14345. https://doi.org/10.1016/j.eswa.2011.04.143
Jahanshahloo, G. R., Lotfi, F. H., & Davoodi, A. R. (2009). Extension of TOPSIS for decision-making problems with interval data: Interval efficiency. Mathematical and Computer Modelling, 49(5-6), 1137–1142. https://doi.org/10.1016/j.mcm.2008.07.009
Keršulienė, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243–258. https://doi.org/10.3846/jbem.2010.12
Kuzmanovic, M., & Savic, G. (2020). Avoiding the privacy paradox using preference-based segmentation: A Conjoint Analysis approach. Electronics, 9(9), 1–21.
Liquet, J.C. (2001). Cas d’analyse conjointe. Paris, Editions TEC & DOC.
Longaray, A. A., Gomes, C. F. S., Elacoste, T., & Machado, C. M. D. S. (2019). Efficiency indicators to evaluate services in port services: A proposal using fuzzy-ahp approach. Pesquisa Operacional, 39(3), 437–456. https://doi.org/10.1590/0101-7438.2019.039.03.0437
Lou, X., & Xu, Y. (2024). Consumption of sustainable denim products: The contribution of blockchain certified eco-labels. Journal of Theoretical and Applied Electronic Commerce Research, 19, 396–411. https://doi.org/10.3390/jtaer19010021
Madzik, P., & Falt, L. (2022). State-of-the-art on analytic hierarchy process in the last 40 years: Literature review based on Latent Dirichlet Allocation topic modelling. PLOS ONE, 17(5), e0268777. https://doi.org/10.1371/journal.pone.0268777
Marcarelli, G., & Mancini, P. (2022). School and academic performance for ranking high schools: Some evidence from Italy. International Journal of the Analytic Hierarchy Process, 14(2), 2–3. https://doi.org/10.13033/ijahp.v14i2.948.
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