Structured Preference Representation and Multiattribute Auctions

Handling preferences over multiple objectives (or attributes) poses serious challenges to the development of automated solutions to complex decision problems. The number of decision outcomes grows exponentially with the number of attributes, and that makes elicitation, maintenance, and reasoning with preferences particularly complex. This problem can potentially be alleviated by using a factored representation of preferences based on independencies among the attributes. This work has two main components. The first component focuses on development of graphical models for multiattribute preferences and utility functions. Graphical models take advantage of factored utility, and yield a compact representation for preferences. Specifically, I introduce CUI networks, a compact graphical representation of utility functions over multiple attributes. CUI networks model multiattribute utility functions using the well studied utility independence concept. I show how conditional utility independence leads to an effective functional decomposition that can be exhibited graphically, and how local conditional utility functions, depending on each node and its parents, can be used to calculate joint utility. The second main component deals with the integration of preference structures and graphical models in trading mechanisms, and in particular in multiattribute auctions. I first develop multiattribute auctions that accommodate generalized additive independent (GAI) preferences. Previous multiattribute mechanisms generally either remain agnostic about traders’ preference structures, or presume highly restrictive forms, such as full additivity. I present an approximately efficient iterative auction mechanism that maintains prices on potentially overlapping GAI clusters of attributes, thus decreasing elicitation and computation burden while allowing for expressive preference representation. Further, I apply preference structures and preference-based constraints to simplify the particularly complex, but practically useful domain of multi-unit multiattribute auctions and exchanges. I generalize the iterative multiattribute mechanism to a subset of this domain, and investigate the problem of finding an optimal set of trades in multiattribute call markets, given restrictions on preference expression. Finally, I apply preference structures to simplify the modeling of user utility in sponsored-search auctions, in order to facilitate ranking mechanisms that account for the user experience from advertisements. I provide short-term and long-term simulations showing the effect on search-engine revenues.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/61670/1/yagil_1.pd

Auctions, Bidding and Exchange Design

The different auction types are outlined using a classification framework along six dimensions. The economic properties that are desired in the design of auction mechanisms and the complexities that arise in their implementation are discussed. Some of the most interesting designs from the literature are analyzed in detail to establish known results and to identify the emerging research directions.Engineering and Applied Science

Utility Independence of Multiattribute Utility Theory is Equivalent to Standard Sequence Invariance of Conjoint Measurement

Utility independence is a central condition in multiattribute utility theory, where attributes of outcomes are aggregated in the context of risk. The aggregation of attributes in the absence of risk is studied in conjoint measurement. In conjoint measurement, standard sequences have been widely used to empirically measure and test utility functions, and to theoretically analyze them. This paper shows that utility independence and standard sequences are closely related: utility independence is equivalent to a standard sequence invariance condition when applied to risk. This simple relation between two widely used conditions in adjacent fields of research is surprising and useful. It facilitates the testing of utility independence because standard sequences are flexible and can avoid cancelation biases that affect direct tests of utility independence. Extensions of our results to nonexpected utility models can now be provided easily. We discuss applications to the measurement of quality-adjusted life-years (QALY) in the health domain

Risk, ambiguity, and the separation of utility and beliefs.

We introduce a general model of static choice under uncertainty, arguably the weakest model achieving a separation of cardinal utility and a unique representation of beliefs. Most of the non-expected utility models existing in the literature are special cases of it. Such separation is motivated by the view that tastes are constant, whereas beliefs change with new information. The model has a simple and natural axiomatization. Elsewhere (forthcoming) we show that it can be very helpful in the characterization of a notion of ambiguity aversion, as separating utility and beliefs allows to identify and remove aspects of risk attitude from the decision maker’s behavior. Here we show that the model allows to generalize several results on the characterization of risk aversion in betting behavior. These generalizations are of independent interest, as they show that some traditional results for subjective expected utility preferences can be formulated only in terms of binary acts.

Momentous Choices: Testing nonstandard decision models in health and housing markets

__Abstract__ During more than half a century, several strands of research contributed to the development of decision theory. The standard normative model for choice under uncertainty – expected utility – was given a foundation by von Neumann and Morgenstern (1944) and Savage (1954). It advised – and expected – reasonable actors t

Procurement Auctions and Negotiations: An Empirical Comparison

This is an Accepted Manuscript of an article published by Taylor & Francis Group in Journal of Organizational Computing and Electronic Commerce on Aug. 2, 2017, available online: http://www.tandfonline.com/10.1080/10919392.2017.1363576.Real world procurement transactions often involve multiple attributes and multiple vendors. Successful procurement involves vendor selection through appropriate market mechanisms. The advancement of information technologies has enabled different mechanisms to be applied to similar procurement situations. Advantages and disadvantages of using such mechanisms remain unclear. The presented research compares two types of mechanisms: multi-attribute reverse auctions and multi-attribute multi-bilateral negotiations in e-procurement. Both laboratory and online experiments were carried out to examine their effects on the process, outcomes and suppliers’ assessment. The results show that in procurement, reverse auctions were more efficient than negotiations in terms of the process. Auctions also led to greater gains for the buyers than negotiations but the suppliers’ profit was lower in auctions. The buyer and the winning supplier jointly reached more efficient and balanced contracts in negotiations than in auctions. The results also show that the suppliers’ assessment was affected by their outcomes: the winning suppliers had a more positive assessment towards the process, outcomes and the system. The findings are consistent in both the laboratory and online settings. The implications of this study for practitioners and researchers are discussed

Improving Data Quality, Model Functionalities and Optimizing User Interfaces in Decision Support Systems

This dissertation contributes to the research on three core elements of decision support systems for managers and consumers: data management, model management and user interface. With respect to data management this dissertation proposes an approach for reducing unobserved product heterogeneity in online transaction data sets. The example of an online auction data set is used to investigate the approach’s ability to improve data quality. In the area of model management this dissertation contributes an approach to elicit consumer product preferences for exponential (beside linear) utility functions aiming at predicting consumers’ utilities and willingness-to-pay for individual products. The question which utility function (linear or exponential) is better suited for predicting product utilities and the willingness to pay is evaluated using a laboratory experiment. Further, in the area of user interfaces this dissertation deals with information visualization. Focusing on coordinate systems, a laboratory experiment is used to investigate which visualization format (two or three dimensional) is better suited for supporting simple vs. complex decision making scenarios and which criteria matter when choosing a visualization format for a particular level of decision making complexity