Relevant bibliographies by topics / Preferences

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Preferences'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Preferences"

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Walden, Brian E., Rauna K. Surr, Mary T. Cord, Ken W. Grant, Van Summers, and Andrew B. Dittberner. "The Robustness of Hearing Aid Microphone Preferences in Everyday Listening Environments." Journal of the American Academy of Audiology 18, no. 05 (2007): 358–79. http://dx.doi.org/10.3766/jaaa.18.5.2.

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Automatic directionality algorithms currently implemented in hearing aids assume that hearing-impaired persons with similar hearing losses will prefer the same microphone processing mode in a specific everyday listening environment. The purpose of this study was to evaluate the robustness of microphone preferences in everyday listening. Two hearing-impaired persons made microphone preference judgments (omnidirectional preferred, directional preferred, no preference) in a variety of everyday listening situations. Simultaneously, these acoustic environments were recorded through the omnidirectio
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Sánchez-Cuenca, Ignacio. "A Preference for Selfish Preferences." Philosophy of the Social Sciences 38, no. 3 (2008): 361–78. http://dx.doi.org/10.1177/0048393108319470.

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Purcell, A. T., R. J. Lamb, E. Mainardi Peron, and S. Falchero. "Preference or preferences for landscape?" Journal of Environmental Psychology 14, no. 3 (1994): 195–209. http://dx.doi.org/10.1016/s0272-4944(94)80056-1.

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McLaughlin, John P. "Aesthetic preference and lateral preferences." Neuropsychologia 24, no. 4 (1986): 587–90. http://dx.doi.org/10.1016/0028-3932(86)90103-x.

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Kreitner, Roy. "Anti-preferences." Theoretical Inquiries in Law 22, no. 2 (2021): 299–328. http://dx.doi.org/10.1515/til-2021-0024.

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Abstract This Article offers a critical evaluation of preference satisfaction as a frame for normative thinking. It begins with an internal critique of the way preferences work in normative economics, distinguishing among three elements: welfare; preferences; and choices. For preference satisfaction to work well, it must be able to bridge two gaps, one between choice and preferences, and another between preferences and welfare. In contexts where both those gaps are bridged, preference satisfaction offers a workable normative framework; where at least one of those gaps is unbridgeable, the fram
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Fishburn, Peter C. "Ordered preference differences without ordered preferences." Synthese 67, no. 2 (1986): 361–68. http://dx.doi.org/10.1007/bf00540076.

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Warren, Caleb, A. Peter McGraw, and Leaf Van Boven. "Values and preferences: defining preference construction." Wiley Interdisciplinary Reviews: Cognitive Science 2, no. 2 (2010): 193–205. http://dx.doi.org/10.1002/wcs.98.

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Huang, Hui, Juan Zhang, Xuan Ren, and Xiang Zhou. "Greenness and Pricing Decisions of Cooperative Supply Chains Considering Altruistic Preferences." International Journal of Environmental Research and Public Health 16, no. 1 (2018): 51. http://dx.doi.org/10.3390/ijerph16010051.

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With the development of the economy and science technology, global resource shortages and environmental pressures have become the focus of attention. More and more consumers tend to buy non-polluting and environmentally friendly green products, and many manufacturers and retailers are beginning to produce or sell green products to enhance their competitive advantage in the market. Considering the green preference attributes of consumers, the altruistic preference is introduced into the supply chain, and we establish four models: two cooperative manufacturers and one retailer are completely sel
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Williams, Evan G. "Preferences’ Significance Does Not Depend on Their Content." Journal of Moral Philosophy 13, no. 2 (2016): 211–34. http://dx.doi.org/10.1163/17455243-4681064.

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Moral theories which include a preference-fulfillment aspect should not restrict their concern to some subset of people’s preferences such as “now-for-now” preferences. Instead, preferences with all contents—e.g. ones which are external, diachronic, or even modal—should be taken into account. I offer a conceptualization of preferences and preference fulfillment which allows us to understand odd species of preferences, and I give a series of examples showing what it would mean to fulfill such preferences and why we ought to do so.
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Griffey, Jack A. F., and Anthony C. Little. "Similarities in Human Visual and Declared Measures of Preference for Opposite-Sex Faces." Experimental Psychology 61, no. 4 (2014): 301–9. http://dx.doi.org/10.1027/1618-3169/a000248.

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Facial appearance in humans is associated with attraction and mate choice. Numerous studies have identified that adults display directional preferences for certain facial traits including symmetry, averageness, and sexually dimorphic traits. Typically, studies measuring human preference for these traits examine declared (e.g., choice or ratings of attractiveness) or visual preferences (e.g., looking time) of participants. However, the extent to which visual and declared preferences correspond remains relatively untested. In order to evaluate the relationship between these measures we examined
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Dissertations / Theses on the topic "Preferences"

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Vosper, Jane. "Using stated preference choice modelling to determine treatment preferences : investigating preferences for depression treatment." Thesis, University of Bristol, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.559707.

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Background & Aim The PhD aimed to quantify preferences for depression treatments using Discrete Choice Experiments (DCEs). A secondary aim was to investigate the relationship between demographic variables, psychological variables and preferences. Methods & Analysis Two DCEs were designed and administered, investigating preferences for treatment of depression by: (1) a drug and (2) a physical activity intervention. The DCE designs were informed by focus groups and qualitative interviews. A best-worst scaling DCE was used for both studies. The physical activity intervention DCE was included in t
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Zhao, Jinhua 1977. "Preference accommodating and preference shaping : incorporating traveler preferences into transportation planning." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/54221.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2009.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student submitted PDF version of thesis.<br>Includes bibliographical references (p. 212-220).<br>This dissertation examines the psychological factors that influence travel behavior such as people's personality traits, environmental attitudes, car pride and perceptions of convenience and comfort. Despite the recognition of the impor
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Rybáková, Nina. "Mezičasová volba osob romského etnika a většinové populace." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-75191.

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This thesis deals with the differences in time preferences, individual discount rates, among non-Romany (Czechs) and Romany ethnic group in the Czech Republic. Subjects of almost homogenous ethnic groups -- low income, low education, currently unemployed -- were subjected to experiments based on an in-depth questionnaire (Romany N = 35, N = 25 non-Romany). In addition to time preferences, their relationship with the socio-economic and demographic characteristics was inspected. The sub-tests showed a difference across ethnic groups in regard to the discounting models. Romany ethnic group is bet
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Clark, Michael D. "Eliciting preferences using discrete choice experiments in healthcare : willingness to pay, stakeholder preferences, and altruistic preferences." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/88792/.

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Chapter 1 of the thesis is divided into 5 sections. Section A begins by defining a Discrete Choice Experiment (DCE), and outlines the key stages involved in conducting a DCE. Sections B and C outline theories underpinning DCE analysis. Section B outlines the characteristics theory of demand, whilst section C, explains random utility theory (RUT), compensating variation (CV), marginal willingness to pay (MWTP), and willingness to pay (WTP) analysis. Section D of the thesis provides a review of the DCE literature. Section E outlines the research questions addressed in the thesis including calcul
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Harris, Alexander Nicholas Edward. "Preferences and cooperation." Thesis, University of Cambridge, 2019. https://www.repository.cam.ac.uk/handle/1810/287933.

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Chapter 1: Evolution of reciprocator preferences when agents can pay for information. A benchmark result in the evolutionary games literature is that a preference for reciprocity will evolve if preferences are observable (at zero cost), since reciprocators can cooperate with each other rather than with materialists, thereby achieving a fitness advantage. I investigate how a preference for reciprocity evolves if individuals can observe an opponent's preferences only by bearing a fitness cost. My main result applies when observing an opponent's type is cheap, but cooperating only gives a modest
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Serra, Jaime, Antónia Correia, and Paulo M. M. Rodrigues. "Yielding Tourists’ Preferences." Bachelor's thesis, Emerald Group Publishing Limited, 2015. http://hdl.handle.net/10174/16858.

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This chapter uses stated tourist preferences as a proxy of visitor yield measures, in order to analyse and understand the yield potential of different markets’ preferences. A literature review revealed that there is much progress to be made in terms of discussion, consensus and stability of methodology for the measurement of visitor yield. The aim of the visitor yield analysis, in the current chapter, is also to bring another dimension into yield analysis and discussion, contributing with a new form of measuring yield potential. Since the objective is to identify yield patterns based on touris
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Boxer, Christie Marie Fitzgerald. "Predicting Spouse Preferences." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/3266.

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I test canonical theories in the preference literature - evolutionary psychology, social role theory, and social exchange theory - using group mean comparisons to replicate basic sex differences in spouse preferences. I find that, consistent with past studies, males prefer attractiveness and females prefer resources in potential partners, and in general, we prefer partners who are similar, rather than different, to us. I also find that males who anticipate enacting the "traditional" male role of "provider" within their marriage tend to prefer spouses who would fulfill the caregiver role, compa
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Shay, Nathan Michael. "Investigating Real-Time Employer-Based Ridesharing Preferences Based on Stated Preference Survey Data." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1471587439.

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Skedgel, Chris D. "Estimating societal preferences for the allocation of healthcare resources using stated preference methods." Thesis, University of Sheffield, 2013. http://etheses.whiterose.ac.uk/6307/.

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Most governments in the world provide some publicly funded healthcare to their citizens, but given the scarcity of resources relative to potential demand, some form of rationing or priority setting is required, and some patients must be denied effective treatment. The thesis took the position that an explicit approach based on maximising the value that society derives from healthcare is the preferred way to address this rationing problem. Conventional health economic practice proposes that value should be equated with quality-adjusted life years (QALYs), leading to a policy of QALY maximisatio
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Freeman, Shannon. "Developing preferences for low-preference age-appropriate leisure activities in adults with developmental disabilities /." Available to subscribers only, 2005. http://proquest.umi.com/pqdweb?did=1079659771&sid=19&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Books on the topic "Preferences"

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Epstein, Larry G. Habits, interdependent preferences and time preference. Dept. of Economics and Institute for Policy Analysis, University of Toronto, 1991.

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Fehige, Christoph, and Ulla Wessels, eds. Preferences. DE GRUYTER, 1998. http://dx.doi.org/10.1515/9783110804294.

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Loewenstein, George. Preferences. Oxford University Press, 2002.

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Christoph, Fehige, and Wessels Ulla, eds. Preferences. Walter De Gruyter Inc, 1998.

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Duggan, Anthony. Voidable preferences. Faculty of Law, University of Toronto, 2006.

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Broome, John. Extended preferences. Bristol University, Department of Economics, 1992.

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Farmer, Roger E. A. R.I.N.C.E. preferences. University of Cambridge Department of Applied Economics, 1988.

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Yip, Ngai Ming. Tenure preferences. University of York, Centre for Housing Policy, 1993.

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(Firm), Richard Ellis, and Harris Research Centre, eds. Occupiers' preferences. Richard Ellis, 1994.

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Dean, Judith Myrle. Quantifying the value of U.S. tariff preferences for developing countries. World Bank, 2006.

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Book chapters on the topic "Preferences"

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Vind, Karl. "Preferences and preference functions." In Independence, Additivity, Uncertainty. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-24757-9_3.

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Marczak, Edward, and Greg Neagle. "Preference Manifests and “Raw” Preferences." In Enterprise Mac Managed Preferences. Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-2938-4_10.

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Seip, Knut Lehre, and Fred Wenstop. "Preferences." In A Primer on Environmental Decision-Making. Springer Netherlands, 2006. http://dx.doi.org/10.1007/978-1-4020-5067-1_7.

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Saha, Bibhas. "Preferences." In Advanced Microeconomics. Routledge, 2024. http://dx.doi.org/10.4324/9781003226994-2.

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von Wright, Georg Henrik. "Preferences." In The New Palgrave Dictionary of Economics. Palgrave Macmillan UK, 1987. http://dx.doi.org/10.1057/978-1-349-95121-5_1335-1.

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Jureta, Ivan. "Preferences." In The Design of Requirements Modelling Languages. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18821-8_14.

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Mochrie, Robert. "Preferences." In Intermediate Microeconomics. Macmillan Education UK, 2016. http://dx.doi.org/10.1007/978-1-137-09166-6_4.

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von Wright, Georg Henrik. "Preferences." In The New Palgrave Dictionary of Economics. Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_1335.

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von Wright, Georg Henrik. "Preferences." In Utility and Probability. Palgrave Macmillan UK, 1990. http://dx.doi.org/10.1007/978-1-349-20568-4_22.

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Steppan, Bernhard. "Preferences." In Eclipse Rich Clients und Plug-ins. Carl Hanser Verlag GmbH & Co. KG, 2015. http://dx.doi.org/10.3139/9783446433168.016.

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Conference papers on the topic "Preferences"

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Gould, Adam, Guilherme Paulino-Passos, Seema Dadhania, Matthew Williams, and Francesca Toni. "Preference-Based Abstract Argumentation for Case-Based Reasoning." In 21st International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/kr.2024/37.

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In the pursuit of enhancing the efficacy and flexibility of interpretable, data-driven classification models, this work introduces a novel incorporation of user-defined preferences with Abstract Argumentation and Case-Based Reasoning (CBR). Specifically, we introduce Preference-Based Abstract Argumentation for Case-Based Reasoning (which we call AA-CBR-P), allowing users to define multiple approaches to compare cases with an ordering that specifies their preference over these comparison approaches. We prove that the model inherently follows these preferences when making predictions and show th
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Karnan, Haresh, Elvin Yang, Garrett Warnell, Joydeep Biswas, and Peter Stone. "Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference-Aligned Path Planning." In 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2024. http://dx.doi.org/10.1109/icra57147.2024.10611475.

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Honda, Tomonori, and Erik K. Antonsson. "Preferences and Correlated Uncertainties in Engineering 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-48675.

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The Method of Imprecision (MOI) is a multi-objective design method that maximizes the overall degree of both design and performance preferences. Sets of design variables are iteratively selected, and the corresponding performances are approximately computed. The designer’s judgment (expressed as preferences) are combined (aggregated) with the customer’s preferences, to determine the overall preference for sets of points in the design space. In addition to degrees of preference for values of the design and performance variables, engineering design problems also typically include uncertainties c
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Cao, Dongxing, Karthik Ramani, Zhanjun Li, Victor Raskin, Ying Liu, and Zhanwei Li. "Developing Customer Preferences for Concept Generation by Using Engineering Ontologies." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28499.

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As customer preference is viewed as a reflection of desires for product features and even future product opportunities, it is crucial for the generation of design concepts. In this paper, a six-stage methodology is described for developing customer preference by using engineering ontology. The methodology mainly focuses upon understanding the product domain knowledge and preference concepts. A modeling process of the preference ontology for searching, indexing, and retrieving domain knowledge is described. The taxonomies of the customer preferences are elicited by classifying specific concepts
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Alfano, Gianvincenzo, Sergio Greco, Francesco Parisi, and Irina Trubitsyna. "Preferences and Constraints in Abstract Argumentation." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/345.

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In recent years there has been an increasing interest in extending Dung's framework to facilitate the knowledge representation and reasoning process. In this paper, we present an extension of Abstract Argumentation Framework (AF) that allows for the representation of preferences over arguments' truth values (3-valued preferences). For instance, we can express a preference stating that extensions where argument a is false (i.e. defeated) are preferred to extensions where argument b is false. Interestingly, such a framework generalizes the well-known Preference-based AF with no additional cost i
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Seimetz, Valentin, Rebecca Eifler, and Jörg Hoffmann. "Learning Temporal Plan Preferences from Examples: An Empirical Study." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/572.

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Temporal plan preferences are natural and important in a variety of applications. Yet users often find it difficult to formalize their preferences. Here we explore the possibility to learn preferences from example plans. Focusing on one preference at a time, the user is asked to annotate examples as good/bad. We leverage prior work on LTL formula learning to extract a preference from these examples. We conduct an empirical study of this approach in an oversubscription planning context, using hidden target formulas to emulate the user preferences. We explore four different methods for generatin
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MacDonald, Erin, Richard Gonzalez, and Panos Papalambros. "Preference Inconsistency in Multidisciplinary Design Decision Making." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35580.

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Research from behavioral psychology and experimental economics asserts that individuals construct preferences on a case-by-case basis when called to make a decision. A common, implicit assumption in engineering design is that user preferences exist a priori. Thus, preference elicitation methods used in design decision making can lead to preference inconsistencies across elicitation scenarios. This paper offers a framework for understanding preference inconsistencies, within and across individual users. We give examples of three components of this new framework: comparative, internal, and exter
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Xue, Wanqi, Bo An, Shuicheng Yan, and Zhongwen Xu. "Reinforcement Learning from Diverse Human Preferences." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/586.

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The complexity of designing reward functions has been a major obstacle to the wide application of deep reinforcement learning (RL) techniques. Describing an agent's desired behaviors and properties can be difficult, even for experts. A new paradigm called reinforcement learning from human preferences (or preference-based RL) has emerged as a promising solution, in which reward functions are learned from human preference labels among behavior trajectories. However, existing methods for preference-based RL are limited by the need for accurate oracle preference labels. This paper addresses this l
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Delic, Amra, Francesco Ricci, and Julia Neidhardt. "Preference Networks and Non-Linear Preferences in Group Recommendations." In WI '19: IEEE/WIC/ACM International Conference on Web Intelligence. ACM, 2019. http://dx.doi.org/10.1145/3350546.3352556.

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Li, Minyi, and Borhan Kazimipour. "An Efficient Algorithm To Compute Distance Between Lexicographic Preference Trees." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/262.

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Very often, we have to look into multiple agents' preferences, and compare or aggregate them. In this paper, we consider the well-known model, namely, lexicographic preference trees (LP-trees), for representing agents' preferences in combinatorial domains. We tackle the problem of calculating the dissimilarity/distance between agents' LP-trees. We propose an algorithm LpDis to compute the number of disagreed pairwise preferences between agents by traversing their LP-trees. The proposed algorithm is computationally efficient and allows agents to have different attribute importance structures an
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Reports on the topic "Preferences"

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Andreoni, James, and Charles Sprenger. Risk Preferences Are Not Time Preferences: Discounted Expected Utility with a Disproportionate Preference for Certainty. National Bureau of Economic Research, 2010. http://dx.doi.org/10.3386/w16348.

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Crawford, Ian, Richard Blundell, Abi Adams, and Martin Browning. Prices versus preferences: taste change and revealed preference. IFS, 2015. http://dx.doi.org/10.1920/wp.ifs.2015.1511.

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Mollerstrom, Johanna, Avner Strulov-Shlain, and Dmitry Taubinsky. Preferences for Giving Versus Preferences for Redistribution. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w29375.

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Afrouzi, Hassan, Alexander Dietrich, Kristian Myrseth, Romanos Priftis, and Raphael Schoenle. Inflation Preferences. National Bureau of Economic Research, 2024. http://dx.doi.org/10.3386/w32379.

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Cohen, Jonathan, Keith Marzilli Ericson, David Laibson, and John Myles White. Measuring Time Preferences. National Bureau of Economic Research, 2016. http://dx.doi.org/10.3386/w22455.

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Alesina, Alberto, and Paola Giuliano. Preferences for Redistribution. National Bureau of Economic Research, 2009. http://dx.doi.org/10.3386/w14825.

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Backus, David, Bryan Routledge, and Stanley Zin. Exotic Preferences for Macroeconomists. National Bureau of Economic Research, 2004. http://dx.doi.org/10.3386/w10597.

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Canavan, G. H. Sensitivity to attack preferences. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/501500.

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Jenter, Dirk, and Katharina Lewellen. CEO Preferences and Acquisitions. National Bureau of Economic Research, 2011. http://dx.doi.org/10.3386/w17663.

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Beshears, John, James Choi, David Laibson, and Brigitte Madrian. How are Preferences Revealed? National Bureau of Economic Research, 2008. http://dx.doi.org/10.3386/w13976.

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