A comparative empirical study of Analytic Hierarchy Process and Conjoint analysis: Literature review
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paper_title: An Introduction to Management Science: Quantitative Approaches to Decision Making

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Gain a sound conceptual understanding of the role that management science plays in the decision-making process with the latest edition of the book that has defined today's management science course: Anderson/Sweeney/Williams/Camm/Martin's AN INTRODUCTION TO MANAGEMENT SCIENCE: QUANTITATIVE APPROACHES TO DECISION MAKING, REVISED 13th Edition. The trusted market leader for more than two decades, the new edition now prepares readers for success with the latest developments in Microsoft Office Excel 2010, including data sets, applications and screen visuals throughout that reflect Excel 2010. Readers learn from the book's proven applications-oriented approach, powerful examples, and problem-scenario approach that introduces each quantitative technique within an applications setting. Readers can get a copy of LINGO software and Excel add-ins with the book's online content. A copy of the popular Microsoft Project Professional 2010 accompanies the book on CD.
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paper_title: Multiattribute Methods as a Means for Solving Ecological Problems in Water Resources—Lake Pollution

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Water as a natural resource refers to the groundwater and surface water (lakes, rivers, etc.) in the environment. Lake resources are considered to be a renewable resource of the freshwater which is essential for life of humans, animals, and plants. The pollution of lake resources, caused not only by humans, restricts its function in the ecosystem, including use for human need. Human negative influence and lack of protection measures for lake resources as freshwater reservoirs can be overcome and solved using multiattribute methods. As pollution problems are very complex due to the many environment variables and many solution alternatives, researchers use more than one method as a support to undertake scientific sustained decisions which are based on economic, ecological, social, technological,… goals in order to obtain the best solutions. Short literature review presented in this paper points out two most commonly used methods for this type of problems—Promethee II and AHP method. Promethee II is used for comparing the alternatives pair-wise for each criterion, finding the strength of preferring one over the other and the main objective of using AHP is to identify the preferred alternative and also determine a ranking of the alternative when all the decision criteria are considered simultaneously. Methodological framework proposed in this paper is designed in order to rank alternatives for each criterion by combining these two methods. Qualitative character of the AHP is exceeded using Promethee II in the first stage of the analysis by cutting off the alternatives with negative net outranking flow. The benefit is direct consistency increase of the AHP. Numerical example for the lake Vrutci, the most important freshwater supplier for the Užice area in western Serbia, is given in the paper. Long-term impact of human factors caused eutrophication of the lake Vrutci and led to the exclusion of the lake from the water supply system. The solution for pollution reduction of the lake Vrutci is obtained by implementing the methodological framework and combined application of the two methods and the results are discussed.
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paper_title: Strategic Decision Making: Applying the Analytic Hierarchy Process

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Strategic Decision Makingprovides an effective, formal methodology that provides help with decision making problems, especially strategic ones with high stakes involving human perceptions and judgements. Focusing on applying the AHP to decision-making problems, Strategic Decision Making covers problems in the realms of business, defence and governance. Using case studies drawn from years of experience, the book discusses decision making for real life problems and includes many worked examples and solutions to problems throughout. The reader will gain comprehensive exposure to the extent of assistance that a formal methodology, such as AHP, can provide to the decision maker in evolving decisions in complex and varied domains.
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paper_title: The Analytic Hierarchy Process

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This chapter provides an overview of Analytic Hierarchy Process (AHP), which is a systematic procedure for representing the elements of any problem hierarchically. It organizes the basic rationality by breaking down a problem into its smaller constituent parts and then guides decision makers through a series of pair-wise comparison judgments to express the relative strength or intensity of impact of the elements in the hierarchy. These judgments are then translated to numbers. The AHP includes procedures and principles used to synthesize the many judgments to derive priorities among criteria and subsequently for alternative solutions. It is useful to note that the numbers thus obtained are ratio scale estimates and correspond to so-called hard numbers. Problem solving is a process of setting priorities in steps. One step decides on the most important elements of a problem, another on how best to repair, replace, test, and evaluate the elements, and another on how to implement the solution and measure performance.
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paper_title: Measuring customer preferences in new product development: comparing compositional and decompositional methods

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Preference measurement is important in the early stages of new product development. Conjoint analysis (CA) and analytic hierarchy process (AHP) are common methods for measuring preferences with CA dominating marketing research and practice. These methods mainly differ with respect to their basic conception: AHP is a compositional method whereas CA is designed in a decompositional manner. This study aims at comparing the methods as instruments of preference measurement. The results show a high degree of predictive and convergent validity of both methods. However, inspecting the results in detail reveals considerable differences, which indicate that AHP performs slightly better.
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paper_title: A stated preference analysis comparing the Analytical Hierarchy Process versus Choice Experiments

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Abstract Our paper compares individual preferences for attributes and levels of an agro-food product using two different methodologies. A key question is whether different results are obtained when asking consumers what they “prefer” versus what they would “buy”. Within this context, we compare empirical results obtained from Choice Experiments (CE) versus the Analytical Hierarchy Process (AHP) due to their capacity to simulate the “purchasing” and “theoretical” stated preferences, respectively. We utilize a survey of restaurateurs’ stated preferences to include rabbit meat in their menus in Catalonia (Spain) in this exploratory study. Results demonstrate similarities and differences in the stated preferences for attributes and attribute levels with a 55.6% coincidence in their ranking between methods. Utility variation between levels in both approaches follows a similar shape for two of the three analyzed attributes.
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paper_title: An empirical comparison of three variants of the AHP and two variants of conjoint analysis

paper_content:

This paper provides an empirical comparison of two methods of attribute valuation: the analytic hierarchy process (AHP) and conjoint analysis. Variants within each approach are also examined. The results of two empirical studies indicate that the methods differ in their predictive and convergent validity. Within the AHP methods no significant difference in predictive validity was found. Within the conjoint methods, the ranking method significantly outperformed the rating method. The difference in predictive validity between the AHP and conjoint methods was significant in the second study but not in the first study, suggesting superior performance of the AHP over conjoint analysis in complex problems. Copyright© 1998 John Wiley & Sons, Ltd.
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paper_title: Solving multiattribute design problems with analytic hierarchy process and conjoint analysis: An empirical comparison

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Abstract We consider the multiattribute design problem (MADP) which contains a considerable number of alternatives, resulting from the combination of a limited number of discrete levels of several quantitative and/or qualitative attributes. In order to solve such problems, the preferences of individual decision makers have to be measured. Though a considerable number of methods is available from different research areas, only a subset is applicable to MADP. In this paper, we report on an empirical study which considered the problem of designing a university and involved more than 300 respondents. Because of this large-scale design, we performed a paper-and-pencil investigation and selected methods which could concisely be applied in such a setting: the analytic hierarchy process (AHP) and the conjoint analysis (CA). The results show that both methods give useful models of the respondents' preferences. However, inspecting the utility functions determined in detail reveals considerable discrepancies between them. Most of the measures used for comparison indicate AHP to be the better choice for the special decision situation considered. In order to get a more general recommendation, we categorize different types of MADP and discuss the applicability of AHP and CA.
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paper_title: Wie robust sind Methoden zur Präferenzmessung

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There is empirical evidence that self-explicated preference measurement methods are surprisingly robust in comparison to conjoint analysis. However, there has been no broad comparison of self-explicated methods with Choice-Based Conjoint analysis. The latter method gains more and more importance in marketing research practice. This empirical study shows that choice-based conjoint analysis leads to decisively better predictive validity than self-explicated measurement. Furthermore, its predictive validity is better than that of a new non-compensatory preference measurement method called RSS and the widespread Adaptive Conjoint Analysis (ACA).
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paper_title: Measuring customer preferences in new product development: comparing compositional and decompositional methods

paper_content:

Preference measurement is important in the early stages of new product development. Conjoint analysis (CA) and analytic hierarchy process (AHP) are common methods for measuring preferences with CA dominating marketing research and practice. These methods mainly differ with respect to their basic conception: AHP is a compositional method whereas CA is designed in a decompositional manner. This study aims at comparing the methods as instruments of preference measurement. The results show a high degree of predictive and convergent validity of both methods. However, inspecting the results in detail reveals considerable differences, which indicate that AHP performs slightly better.
---
paper_title: A stated preference analysis comparing the Analytical Hierarchy Process versus Choice Experiments

paper_content:

Abstract Our paper compares individual preferences for attributes and levels of an agro-food product using two different methodologies. A key question is whether different results are obtained when asking consumers what they “prefer” versus what they would “buy”. Within this context, we compare empirical results obtained from Choice Experiments (CE) versus the Analytical Hierarchy Process (AHP) due to their capacity to simulate the “purchasing” and “theoretical” stated preferences, respectively. We utilize a survey of restaurateurs’ stated preferences to include rabbit meat in their menus in Catalonia (Spain) in this exploratory study. Results demonstrate similarities and differences in the stated preferences for attributes and attribute levels with a 55.6% coincidence in their ranking between methods. Utility variation between levels in both approaches follows a similar shape for two of the three analyzed attributes.
---
paper_title: An empirical comparison of three variants of the AHP and two variants of conjoint analysis

paper_content:

This paper provides an empirical comparison of two methods of attribute valuation: the analytic hierarchy process (AHP) and conjoint analysis. Variants within each approach are also examined. The results of two empirical studies indicate that the methods differ in their predictive and convergent validity. Within the AHP methods no significant difference in predictive validity was found. Within the conjoint methods, the ranking method significantly outperformed the rating method. The difference in predictive validity between the AHP and conjoint methods was significant in the second study but not in the first study, suggesting superior performance of the AHP over conjoint analysis in complex problems. Copyright© 1998 John Wiley & Sons, Ltd.
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paper_title: A Comparative Empirical Study on Common Methods for Measuring Preferences

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Literature and practice reveal that most marketing related questionnaires measuring consumer preferences rely on some kind of conjoint analysis. Recent studies show the analytic hierarchy process to be suitable for this task, too. This paper gives a comparison of the approaches and the results of former studies. Because we found considerable differences in those results, an additional study has been performed being designed such that it has potential for explaining these differences. As we found respective explanations, we finally derive general guidelines on the selection of conjoint analysis and analytic hierarchy process depending on the complexity of the problem situation and the previous knowledge respondents have in preference measurement.
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Title: A Comparative Empirical Study of Analytic Hierarchy Process and Conjoint Analysis: Literature Review

Section 1: Introduction
Description 1: Provide an overview of the decision-making process, criteria involved, and the importance of making quality decisions in business settings.

Section 2: Conjoint Analysis
Description 2: Describe the Conjoint analysis method, including its phases, how it evaluates preferences, and its application in market simulations.

Section 3: The Analytic Hierarchy Process (AHP)
Description 3: Explain the AHP method, including its hierarchical structure, process for collecting data through pairwise comparisons, and calculation of consistency ratios.

Section 4: Conceptual Comparison of AHP and Conjoint Analysis
Description 4: Compare the theoretical and practical differences between AHP and Conjoint analysis, including their evaluation steps, scales, and cognitive requirements.

Section 5: Overview of Research Projects Based on the Comparison of the AHP Method and the Conjoint Analysis
Description 5: Present comparative findings from various studies that have used both methods, focusing on the conditions of application, complexity, and respondents' familiarity with the methods.

Section 6: Conclusions
Description 6: Summarize the theoretical and applied significance of the findings, providing guidance on choosing the appropriate method based on specific research conditions and desired outcomes.