A comparative empirical study of Analytic Hierarchy Process and Conjoint analysis: Literature review
Keywords:
Analytic Hierarchy Process, Conjoint analysis, multi-criteria decision making (MCDM) methods, literature review
Abstract
This paper is based on the main difference between conceptual and theoretical frameworks as well as literature review of comparative studies of two multi-criteria decision making methods: Analytic Hierarchy Process (AHP) and Conjoint analysis. The AHP method represents a formal framework for solving complex multiatributive decision making problems, as well as a systemic procedure for ranking multiple alternatives and/or for selecting the best from a set of available ones. Conjoint analysis is an experimental approach used for measuring individual’s preferences regarding the attributes of a product or a service. It is based on a simple premise that individuals evaluate alternatives, with these alternatives being composed of a combination of attributes whose part-worth utilities are estimated by researchers. Bearing in mind the quality of desired results, it must be dependent on the problems and aspects of research: knowledge of the methods, complexity (number of attributes and their levels), order effects, level of consistency, chooses the appropriate method.
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References
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IJzerman, M. J., van Til, J. A., & Snoek, G. J. (2008). Comparison of two multi-criteria decision techniques for eliciting treatment preferences in people with neurological disorders. The Patient: Patient-Centered Outcomes Research, 1(4), 265-272.
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Saaty. T. L. (1980), The Analytic Hierarchy Process, McGraw-Hill, New York.
Scholl, A., Manthey, L., Helm, R., & Steiner, M. (2005). Solving multiattribute design problems with analytic hierarchy process and conjoint analysis: An empirical comparison. European Journal of Operational Research, 164(3), 760-777.
Şener, Ş., Şener, E., Nas, B., & Karagüzel, R. (2010). Combining AHP with GIS for landfill site selection: a case study in the Lake Beyşehir catchment area (Konya, Turkey). Waste management, 30(11), 2037-2046.
Tscheulin, D. K. (1991). Ein empirischer Vergleich der Eignung von Conjoint-Analyse und Analytic Hierarchy Process (AHP) zur Neuproduktplanung. Zeitschrift für Betriebswirtschaft, 61(11), 1267-1280.
Anderson, D.R., Sweeney, D.J., Williams, T.A., Camm, J.D., & Martin, K., (2012). An Introduction to Management Science: Quantitative Approaches to Decision Making, South-Western Cengage Learning.
Bhushan, N., & Rai, K. (2007). Strategic decision making: applying the analytic hierarchy process. Springer Science & Business Media.
Danner, M., Vennedey, V., Hiligsmann, M., Fauser, S., Gross, C., & Stock, S., (2017). Comparing Analytic Hierarchy Process and Discrete-Choice Experiment to Elicit Patient Preferences for Treatment Characteristics in Age-Related Macular Degeneration. Value in Health, 20(8), 1166-1173.
Figueira, J., Greco, S., Ehrgott, M. (2005). Multycriteria Decision Analysis: State of the Art Surveys, Springer Science + Business Media, Inc., Boston. ISBN: 0¬ 387¬23067¬X.
Gustafsson, A., Ekdahl, F., & Bergman, B. (1999) Conjoint analysis: a useful tool in the design process. Total Quality Management, 10(3), 327-343.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C., (1995). Conjoint Analysis, in: Multivariate Data Analysis, Prentice Hall, Englewood Cliffs NJ, 556-599.
Hartmann, A., & Sattler, H. (2004). Wie robust sind Methoden zur Präferenzmessung?. in: Zeitschrift für betriebswirtschaftliche Forschung (zfbf), 56 (2), 3-22.
Helm, R., Scholl, A., Manthey, L. & Steiner, M. (2004). Measuring customer preferences in new product development: comparing compositional and decompositional methods, International Journal of Product Development, 1(1), 12–29.
Helm, R., Steiner, M., Scholl, A. & Manthey, L. (2008). A Comparative Empirical Study on common Methods for Measuring Preferences, International Journal of Management and Decision Making, 9(3), 242-265.
Ijzerman, M. J., Van Til, J. A., & Bridges, J. F. (2012). A comparison of analytic hierarchy process and conjoint analysis methods in assessing treatment alternatives for stroke rehabilitation. The Patient-Patient-Centered Outcomes Research, 5(1), 45-56.
IJzerman, M. J., van Til, J. A., & Snoek, G. J. (2008). Comparison of two multi-criteria decision techniques for eliciting treatment preferences in people with neurological disorders. The Patient: Patient-Centered Outcomes Research, 1(4), 265-272.
Kallas, Z., Lambarraa, F., & Gil, J. M., (2011). A stated preference analysis comparing the analytical hierarchy process versus choice experiments. Food quality and preference, 22(2), 181-192.
Kuzmanović, M., Savić, G., Andrić-Gušavac, B., Makajić-Nikolić, D. & Panić B. (2013a). A Conjoint-based approach to student evaluations of teaching performance. Expert Systems With Applications, 40(10), 4083-4089.
Kuzmanović, M., Savić, G., Popović, M., & Martić, M. (2013). A new approach to evaluation of university teaching considering heterogeneity of students’ preferences. Higher Education, 66(2), 153-171.
Mulye, R. (1998). An empirical comparison of three variants of the AHP and two variants of conjoint analysis, Journal of Behavioral Decision Making, 11, 263-280.
Popovic, M., Andrić Gušavac, B., & Katic, A. (2018). Multiattribute Methods as a Means for Solving Ecological Problems in Water Resources - Lake Pollution, XIII Balkan Conference on Operational Research - BALCOR 2018, Belgrade, 25-28 May, 2018, University of Belgrade, Faculty of Organizational Sciences, Serbia.
Saaty. T. L. (1980), The Analytic Hierarchy Process, McGraw-Hill, New York.
Scholl, A., Manthey, L., Helm, R., & Steiner, M. (2005). Solving multiattribute design problems with analytic hierarchy process and conjoint analysis: An empirical comparison. European Journal of Operational Research, 164(3), 760-777.
Şener, Ş., Şener, E., Nas, B., & Karagüzel, R. (2010). Combining AHP with GIS for landfill site selection: a case study in the Lake Beyşehir catchment area (Konya, Turkey). Waste management, 30(11), 2037-2046.
Tscheulin, D. K. (1991). Ein empirischer Vergleich der Eignung von Conjoint-Analyse und Analytic Hierarchy Process (AHP) zur Neuproduktplanung. Zeitschrift für Betriebswirtschaft, 61(11), 1267-1280.
Published
2018-10-15
How to Cite
Popovic, M., Kuzmanović, M., & Savić, G. (2018). A comparative empirical study of Analytic Hierarchy Process and Conjoint analysis: Literature review. Decision Making: Applications in Management and Engineering, 1(2), 153-163. https://doi.org/10.31181/dmame1802160p
Section
Regular articles
