Relevant bibliographies by topics / Utility theory Econometric models

Academic literature on the topic 'Utility theory Econometric models'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Utility theory Econometric models"

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Lewbel, Arthur. "Demand Systems With and Without Errors." American Economic Review 91, no. 3 (June 1, 2001): 611–18. http://dx.doi.org/10.1257/aer.91.3.611.

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Revealed preference theory assumes that each consumer has demands that are rational, meaning that they arise from the maximization of his or her own utility function. In contrast, econometric or statistical demand models assume that each consumer's demands equal a rational systematic component derived from a common utility function, plus an individual-specific, additive error term. This paper reconciles these differences, by providing necessary and sufficient conditions for rationality of statistical demand models given individual consumer rationality. (JEL D11, D12, C30, C43)
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Zenina, Nadezda, and Arkady Borisov. "Transportation Mode Choice Analysis Based on Classification Methods." Scientific Journal of Riga Technical University. Computer Sciences 45, no. 1 (January 1, 2011): 49–53. http://dx.doi.org/10.2478/v10143-011-0041-2.

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Transportation Mode Choice Analysis Based on Classification MethodsMode choice analysis has received the most attention among discrete choice problems in travel behavior literature. Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. This paper investigates performance of mode choice analysis with classification methods - decision trees, discriminant analysis and multinomial logit. Experimental results have demonstrated satisfactory quality of classification.
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Basmann, Robert L. "A Theory of Serial Correlation of Stochastic Taste Changers in Direct Utility Functions." Econometric Theory 1, no. 2 (August 1985): 192–210. http://dx.doi.org/10.1017/s0266466600011130.

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Methods of maximum-likelihood search (eg., Hildreth-Lu) for single equations models with autocorrelated disturbances are not easily extended to the multi-equation systems encountered in econometric studies of consumer demand. The obstacle is the large dimension of the space of independent serial correlation coefficients to be partitioned and searched. This paper treats stochastic disturbance vectors in demand/expenditure systems as functions of random disturbances in consumer utility functions. It specifies marginal utilities to be products of a systematic function and a nonnegative random disturbance. Under this specification, three hypotheses that readily come to mind in the context of consumer theory drastically reduce the number of independent elements of serial covariance matrices. This in turn makes practicable the extension of maximum-likelihood search methods in the estimation of parameters of large demand systems.
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Bhatta, Bharat P. "Theoretical, methodological and practical issues of choice models." International Journal of Entrepreneurship and Economic Issues 1, no. 1 (February 26, 2018): 21–37. http://dx.doi.org/10.32674/ijeei.v1i0.4.

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This paper analyzes and synthesizes the fundamentals of discrete choice models. This paper alsodiscusses the basic concept and theory underlying the econometrics of discrete choice, specific choicemodels, estimation method, model building and tests, and applications of discrete choice models. Thiswork highlights the relationship between economic theory and discrete choice models: how economictheory contributes to choice modeling and vice versa. Keywords: Discrete choice models; Random utility maximization; Decision makers; Utility function;Model formulation
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Juhl, Sebastian. "Measurement Uncertainty in Spatial Models: A Bayesian Dynamic Measurement Model." Political Analysis 27, no. 3 (November 9, 2018): 302–19. http://dx.doi.org/10.1017/pan.2018.35.

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According to spatial models of political competition, parties strategically adjust their ideological positions to movements made by rival parties. Spatial econometric techniques have been proposed to empirically model such interdependencies and to closely convert theoretical expectations into statistical models. Yet, these models often ignore that the parties’ ideological positions are latent variables and, as such, accompanied by a quantifiable amount of uncertainty. As a result, the implausible assumption of perfectly measured covariates impedes a proper evaluation of theoretical propositions. In order to bridge this gap between theory and empirics, the present work combines a spatial econometric model and a Bayesian dynamic item response model. The proposed model accurately accounts for measurement uncertainty and simultaneously estimates the parties’ ideological positions and their spatial interdependencies. To verify the model’s utility, I apply it to recorded votes from the sixteen German state legislatures in the period from 1988 to 2016. While exhibiting a notable degree of ideological mobility, the results indicate only moderate spatial dependencies among parties of the same party family. More importantly, the analysis illustrates how measurement uncertainty can lead to substantively different results which stresses the importance of appropriately incorporating theoretical expectations into statistical models.
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Hill, Brian. "A Non‐Bayesian Theory of State‐Dependent Utility." Econometrica 87, no. 4 (2019): 1341–66. http://dx.doi.org/10.3982/ecta15916.

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Many decision situations involve two or more of the following divergences from subjective expected utility: imprecision of beliefs (or ambiguity), imprecision of tastes (or multi‐utility), and state dependence of utility. This paper proposes and characterizes a model of uncertainty averse preferences that can simultaneously incorporate all three phenomena. The representation supports a principled separation of (imprecise) beliefs and (potentially state‐dependent, imprecise) tastes. Moreover, the representation permits comparative statics separating the roles of beliefs and tastes, and is modular: it easily delivers special cases involving various combinations of the phenomena, as well as state‐dependent multi‐utility generalizations covering popular ambiguity models.
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Chade, Hector, Jan Eeckhout, and Lones Smith. "Sorting through Search and Matching Models in Economics." Journal of Economic Literature 55, no. 2 (June 1, 2017): 493–544. http://dx.doi.org/10.1257/jel.20150777.

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Toward understanding assortative matching, this is a self-contained introduction to research on search and matching. We first explore the nontransferable and perfectly transferable utility matching paradigms, and then a unifying imperfectly transferable utility matching model. Motivated by some unrealistic predictions of frictionless matching, we flesh out the foundational economics of search theory. We then revisit the original matching paradigms with search frictions. We finally allow informational frictions that often arise, such as in college-student sorting. (JEL C78, D82, D83, I23, J12)
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Assaf, Matheus, and Pedro Garcia Duarte. "Utility Matters." History of Political Economy 52, no. 5 (October 1, 2020): 863–94. http://dx.doi.org/10.1215/00182702-8671855.

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The present-day standard textbook narrative on the history of growth theory usually takes Robert Solow’s 1956 contribution as a key starting point, which was extended by David Cass and Tjalling Koopmans in 1965 by introducing an intertemporal maximization problem that defines the saving ratio in the economy. However, the road connecting Solow to the Ramsey-Cass-Koopmans model is not so straightforward. We argue that in order to understand Koopmans’s contribution, we have to go to the activity analysis literature that started before Solow 1956 and never had him as a central reference. We stress the role played by Edmond Malinvaud, with whom Koopmans interacted closely, and take his travel from the French milieu of mathematical economics to the Cowles Commission in 1950-51 and back to France as a guiding line. The rise of turnpike theory in the end of the 1950s generated a debate on the choice criteria of growth programs, opposing the productive efficiency typical of these models to the utilitarian approach supported by Malinvaud and Koopmans. The Vatican Conference of 1963, where Koopmans presented a first version of his 1965 model, was embedded in this debate. We argue that Malinvaud’s (and Koopmans’s) contributions were crucial to steer the activity analysis literature toward a utilitarian analysis of growth paths.
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Starmer, Chris. "Developments in Non-Expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk." Journal of Economic Literature 38, no. 2 (June 1, 2000): 332–82. http://dx.doi.org/10.1257/jel.38.2.332.

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This article reviews recent developments in the economic theory of individual decision making under risk. Since the 1950s it has been known that individual choices violate the standard model of expected utility in predictable ways. Considerable research effort has now been devoted to the project of developing a superior descriptive model. Following an overview of non-expected utility theories which distinguishes between “conventional” and “non-conventional” approaches, the paper seeks to assess these alternative models in terms of empirical success (using laboratory and field data) and theoretical usefulness. The closing sections reflect on some new directions emerging in this literature.
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Chung, Hui-Kuan, Paul Glimcher, and Agnieszka Tymula. "An Experimental Comparison of Risky and Riskless Choice—Limitations of Prospect Theory and Expected Utility Theory." American Economic Journal: Microeconomics 11, no. 3 (August 1, 2019): 34–67. http://dx.doi.org/10.1257/mic.20170112.

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Prospect theory, used descriptively for decisions under both risk and certainty, presumes concave utility over gains and convex utility over losses; a pattern widely seen in lottery tasks. Although such discontinuous gain-loss reference-dependence is also used to model riskless choices, only limited empirical evidence supports this use. In incentive-compatible experiments, we find that gain-loss reflection effects are not observed under riskless choice as predicted by prospect theory, even while in the same subjects gain-loss reflection effects are observed under risk. Our empirical results challenge the application of choice models across both risky and riskless domains. (JEL C91, D12, D81)
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Dissertations / Theses on the topic "Utility theory Econometric models"

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Paraskevopoulos, Ioannis. "Econometric models applied to production theory." Thesis, Queen Mary, University of London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.392498.

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Adusumilli, Karun. "Essays on inference in econometric models." Thesis, London School of Economics and Political Science (University of London), 2018. http://etheses.lse.ac.uk/3760/.

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This thesis contains three essays on inference in econometric models. Chapter 1 considers the question of bootstrap inference for Propensity Score Matching. Propensity Score Matching, where the propensity scores are estimated in a first step, is widely used for estimating treatment effects. In this context, the naive bootstrap is invalid (Abadie and Imbens, 2008). This chapter proposes a novel bootstrap procedure for this context, and demonstrates its consistency. Simulations and real data examples demonstrate the superior performance of the proposed method relative to using the asymptotic distribution for inference, especially when the degree of overlap in propensity scores is poor. General versions of the procedure can also be applied to other causal effect estimators such as inverse probability weighting and propensity score subclassification, potentially leading to higher order refinements for inference in such contexts. Chapter 2 tackles the question of inference in incomplete econometric models. In many economic and statistical applications, the observed data take the form of sets rather than points. Examples include bracket data in survey analysis, tumor growth and rock grain images in morphology analysis, and noisy measurements on the support function of a convex set in medical imaging and robotic vision. Additionally, nonparametric bounds on treatment effects under imperfect compliance can be expressed by means of random sets. This chapter develops a concept of nonparametric likelihood for random sets and its mean, known as the Aumann expectation, and proposes general inference methods by adapting the theory of empirical likelihood. Chapter 3 considers inference on the cumulative distribution function (CDF) in the classical measurement error model. It proposes both asymptotic and bootstrap based uniform confidence bands for the estimator of the CDF under measurement error. The proposed techniques can also be used to obtain confidence bands for quantiles, and perform various CDF-based tests such as goodness-offit tests for parametric models of densities, two sample homogeneity tests, and tests for stochastic dominance; all for the first time under measurement error.
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McGarry, Joanne S. "Seasonality in continuous time econometric models." Thesis, University of Essex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313064.

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Forchini, Giovanni. "Exact distribution theory for some econometric problems." Thesis, University of Southampton, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242631.

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Kapetanios, George. "Essays on the econometric analysis of threshold models." Thesis, University of Cambridge, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286704.

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Hall, Stephen George Frederick. "Solving and evaluating large non-linear econometric models." Thesis, Queen Mary, University of London, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.261290.

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Lu, Maozu. "The encompassing principle and evaluation of econometric models." Thesis, University of Southampton, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.316084.

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Sherrell, Neill. "The estimation and specification of spatial econometric models." Thesis, University of Bristol, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.281861.

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Chambers, Marcus James. "Durability and consumers' demand : Gaussian estimation and some continuous time models." Thesis, University of Essex, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238563.

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McCrorie, James Roderick. "Some topics in the estimation of continuous time econometric models." Thesis, University of Essex, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388615.

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Books on the topic "Utility theory Econometric models"

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Harris, Chris. Utility and welfare optimization: Theory and practice in electricity. New York, NY: Palgrave Macmillan, 2015.

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Daboni, Luciano. Luciano Daboni: Scritti scelti. Trieste: Dipartimento di matematica applicata "Bruno de Finetti", 2001.

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1952-, Tanguiane Andranick S., and Gruber Josef 1935-, eds. Constructing and applying objective functions: Proceedings of the Fourth International Conference on Econometric Decision Models, Constructing and Applying Objective Functions, University of Hagen, held in Haus Nordhelle, August 28-31, 2000. Berlin: Springer, 2002.

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Giovannini, Alberto. Time-series tests of a non-expected-utility model of asset pricing. Cambridge, MA: National Bureau of Economic Research, 1989.

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Casella, Alessandra. Participation in a currency union. Cambridge, MA: National Bureau of Economic Research, 1990.

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Morton, Fiona Scott. Love or money?: The effects of owner motivation in the California wine industry. Cambridge, MA: National Bureau of Economic Research, 1998.

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Chaloupka, Frank J. Men, women, and addiction: The case of cigarette smoking. Cambridge, MA: National Bureau of Economic Research, 1990.

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Mocan, H. Naci. A dynamic model of differential human capital and criminal activity. Cambridge, MA: National Bureau of Economic Research, 2000.

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Goldberger, Arthur S. Econometric theory. Ann Arbor, MI: UMI Books on Demand, 1998.

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Nielsen, Lars Tyge. The utility of infinite menus. Fontainbleau: INSEAD, 1990.

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Book chapters on the topic "Utility theory Econometric models"

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De Siano, Rita, Valerio Leone Sciabolazza, and Alessandro Sapio. "Spatial Econometric Models: Theory." In Regional Resilience to Climate and Environmental Shocks, 31–43. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54588-8_3.

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Holden, K., D. A. Peel, and J. L. Thompson. "Expectations in Econometric Models." In Expectations: Theory and Evidence, 143–62. London: Macmillan Education UK, 1985. http://dx.doi.org/10.1007/978-1-349-17862-9_6.

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Italianer, Alexander. "Econometric Specification." In Theory and Practice of International Trade Linkage Models, 217–39. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4472-5_6.

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Bous, Géraldine, and Marc Pirlot. "Learning Multicriteria Utility Functions with Random Utility Models." In Algorithmic Decision Theory, 101–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41575-3_8.

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Dutta, Jayasri. "On Resampling Inference in Econometric Models." In Contributions to Econometric Theory and Application, 293–320. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4613-9016-9_10.

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Aleskerov, Fuad, and Bernard Monjardet. "Preference, Utility, and Choice: Classic Models." In Studies in Economic Theory, 15–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04992-1_2.

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Lengwiler, Yvan. "The Origins of Expected Utility Theory." In Vinzenz Bronzin’s Option Pricing Models, 535–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-85711-2_26.

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Mariel, Petr, David Hoyos, Jürgen Meyerhoff, Mikolaj Czajkowski, Thijs Dekker, Klaus Glenk, Jette Bredahl Jacobsen, et al. "Econometric Modelling: Basics." In Environmental Valuation with Discrete Choice Experiments, 61–81. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62669-3_5.

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AbstractThis chapter addresses basic topics related to choice data analysis. It starts by describing the coding of attribute levels and choosing the functional form of the attributes in the utility function. Next, it focuses on econometric models with special attention devoted to the random parameter mixed logit model. In this context, the chapter compares different coefficient distributions to be used, addresses specifics of the cost attribute coefficient and it pays attention to potential correlations between random coefficients. Finally, topics related to the estimation procedure such as assuring its convergence or random draws are discussed.
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Calzolari, Giorgio, and Lorenzo Panattoni. "Gradient Methods in Fiml Estimation of Econometric Models." In Developments of Control Theory for Economic Analysis, 143–53. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3495-5_10.

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Ronning, Gerd. "Potentials and Limitations of Econometric Forecast and Simulation Models." In Econometrics in Theory and Practice, 77–85. Heidelberg: Physica-Verlag HD, 1998. http://dx.doi.org/10.1007/978-3-642-47027-1_8.

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Conference papers on the topic "Utility theory Econometric models"

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Baruah, Gaurav, and Jimmy Lin. "The Pareto Frontier of Utility Models as a Framework for Evaluating Push Notification Systems." In ICTIR '17: ACM SIGIR International Conference on the Theory of Information Retrieval. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3121050.3121089.

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Van Bossuyt, Douglas, Chris Hoyle, Irem Y. Tumer, Andy Dong, Toni Doolen, and Richard Malak. "Toward Considering Risk Attitudes in Engineering Organizations Using Utility Theory." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70399.

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Design projects within large engineering organizations involve numerous uncertainties that can lead to unacceptably high levels of risk. Practicing designers recognize the existence of risk and commonly are aware of events that raise risk levels. However, a disconnect exists between past project performance and current project execution that limits decision-making. This disconnect is primarily due to a lack of quantitative models that can be used for rational decision-making. Methods and tools used to make decisions in risk-informed design generally use an expected value approach. Research in the psychology domain has shown that decision-makers and stakeholders have domain-specific risk attitudes that often have variations between individuals and between companies. Risk methods used in engineering such as Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), and others are often ill-equipped to help stakeholders make decisions based upon risk-tolerant or risk-averse decision-making conditions. This paper focuses on the specific issue of helping stakeholders make decisions under risk-tolerant or risk-averse decision-making conditions and presents a novel method of translating engineering risk data from the domain of expected value into a domain corrected for risk attitude. This is done by using risk utility functions derived from the Engineering-Domain-Specific Risk-Taking (E-DOSPERT) test. This method allows decisions to be made based upon data that is risk attitude corrected. Further, the method uses an aspirational measure of risk attitude as opposed to existing lottery methods of generating utility functions that are based upon past performance. An illustrative test case using a simplified space mission designed in a collaborative design center environment is included. The method is shown to change risk-informed decisions in certain situations where a risk-tolerant or risk-averse decision-maker would likely choose differently than the dictates of the expected value approach.
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Longpre, Luc, Scott Ferson, and W. Troy Tucker. "How to measure a degree of mismatch between probability models, p-boxes, etc.: A decision-theory-motivated utility-based approach." In NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society. IEEE, 2008. http://dx.doi.org/10.1109/nafips.2008.4531299.

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Lee, Benjamin D., Stephanie C. Thompson, and Christiaan J. J. Paredis. "A Review of Methods for Design Under Uncertainty From the Perspective of Utility Theory." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28721.

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In this paper, we present a review of methods for design under uncertainty. Specifically, we examine Reliability-Based Design, Robust Design, and Risk-Informed Design from the perspective of utility theory. Although these methods account for uncertainty, they differ from utility theory in that they limit the types of preferences that can be expressed. Limitations on the types of preferences that can be expressed can be valuable to designers because they reduce the effort required to elicit preference. However, the value of these methods for a particular design scenario depends greatly on the appropriateness of the preference model they implicitly impose. As such, they should be used with caution; they should not be applied when the associated preference models are not reasonable approximations of the designer’s true preferences. To help designers decide when the methods are appropriate, we identify the preference models by formulating the methods in a common framework of utility theory. The methods are then critically examined and compared based on their costs and the value they add to the design process.
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Chen, Xi, Ali E. Abbas, and Dusˇan M. Stipanovic´. "A Multiattribute Utility Approach to Target Assignment." In ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2594.

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This paper introduces the multiattribute utility theory to the control Lyapunov function design framework. As an illustration we focus on the problem of multi-target assignment. With this formulation, we use a global multiattribute utility function as a multivariate objective function that should be minimized for the agents to achieve their objectives. The objectives represent deviations of each agent from specified targets. We provide closed form feedback control laws, based on the multiattribute utility function, for general nonlinear multi-agent system models affine in control. Finally, we present simulation results and conduct sensitivity analysis for two different models that are affine in control; basic kinematic model and nonlinear nonholonomic unicycle model.
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Leonelli, M., and J. Q. Smith. "Using graphical models and multi-attribute utility theory for probabilistic uncertainty handling in large systems, with application to the nuclear emergency management." In 2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW 2013). IEEE, 2013. http://dx.doi.org/10.1109/icdew.2013.6547448.

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Kim, Tae-Hyun, Gu¨l E. Okudan, and Ming-Chuan Chiu. "Product Family Design Through Customer Perceived Utility." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-29112.

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Even though functional characteristics and various forms can be measured directly and objectively, many designers and engineers still fail to clearly evaluate product criteria due to consumers’ subjective inputs, which change over time. To appropriately evaluate product criteria, an effective design decision making analysis is required. In this study, we propose a methodology to assure this harmony using a mobile phone product family design scenario. Customer perceived utility of design features are first gathered using a questionnaire (with more than 500 responses), and then modeled using multi-attribute utility theory (MAUT) to allow for clustering based on consumer demographics (e.g., race, gender, and age). Based on the clustering, several mobile phone models are tested for their fitness. The goal of the methodology is to determine the appropriate product family size in order to satisfy customer needs as well as reduce supply chain complexity.
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Hargreaves, Eduardo Martins, and Daniel Sadoc Menasché. "Filters for Social Media Timelines: Models, Biases, Fairness and Implications." In XXXVIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/sbrc_estendido.2020.12414.

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Social media have a significant impact, on the lifestyle, behaviour and opinion of billions of users. To handle the flow of information between its members, social media developed personalization algorithms that filter the contents that flow into users' timelines. Despite the far-reach of social media filters, such algorithms lack transparency, motivating research to understand and improve its properties. In this thesis, bridging queuing theory, caching models and network utility maximization, we propose a reproducible methodology encompassing measurements, analytical models and a utility-based method to design timelines filters. Using Facebook as a case study, our empirical results indicate that a significant bias exists and it is stronger at the topmost position of News Feed motivating the proposal of a novel and transparent fairness-based timeline design which can be controlled by users. Among the implications, we indicate the accuracy of our model to make counterfactual analysis, the capability of auditing social media and its versatility in designing multiple filters accounting for users preferences in an open and transparent way.
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Wassenaar, Henk Jan, Wei Chen, Jie Cheng, and Agus Sudjianto. "Enhancing Discrete Choice Demand Modeling for Decision-Based Design." In ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/detc2003/dtm-48683.

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Our research is motivated by the need for developing a rigorous Decision-Based Design framework and the need for developing an approach to demand modeling that is critical for assessing the profit a product can bring. Even though demand modeling techniques exist in market research, little work exists on product demand modeling that addresses the specific needs of engineering design in particular that facilitates engineering decision-making. Building upon our earlier work on using the discrete choice analysis approach to demand modeling, in this work, we provide detailed guidelines for implementing the discrete choice demand modeling approach in product design. The modeling of a hierarchy of product attributes is introduced to cascade customer desires to specific key customer attributes that can be represented using engineering language. To improve the predictive capability of demand models, we propose to use the Kano method for providing the econometric justification when selecting the shape of the customer utility function. A real (passenger) vehicle engine case study, developed in collaboration with the market research firm J.D. Power & Associates and Ford Motor Company, demonstrates the proposed approaches. The example focuses on demand analysis and does not reach beyond the key customer attribute level. The obtained demand model is shown to be satisfactory through cross validation.
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Zhou, Feng, and Jianxin (Roger) Jiao. "Quantification of Customer Perception on Airplane Cabin Lighting Design Based on Cumulative Prospect Theory." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-13624.

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This paper aims to develop quantitative models of customer perception on products and/or services. Prevailing methods often deal with this issue using utility theory, which uses normative models to make rational decisions without considering affective factors. This paper takes another perspective using cumulative prospect theory through how human users’ subjective experience impacts their choice behavior under uncertainty. Toward this end, quantitative measure of customer perception based on cumulative prospect theory and affective influence in terms of parameter shaping based on hierarchical Bayesian model with Markov chain Monte Carlo is proposed. A case study of airplane cabin lighting design is presented to show the potential and feasibility of the proposed method.
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