Inferring Rationales from Choice: Identification for Rational Shortlist Methods

A wide variety of choice behavior inconsistent with preference maximization can be explained by Manzini and Mariotti's Rational Shortlist Methods. Choices are made by sequentially applying a pair of asymmetric binary relations (rationales) to eliminate inferior alternatives. Manzini and Mariotti's axiomatic treatment elegantly describes which behavior can be explained by this model. However, it leaves unanswered what can be inferred, from observed behavior, about the underlying rationales. Establishing this connection is fundamental not only for applied and empirical work but also for meaningful welfare analysis. Our results tightly characterize the surprisingly rich relationship between behavior and the underlying rationales. (JEL D11, D12, D83, M37)

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Dynamic Random Utility

Econometrica ◽

10.3982/ecta15456 ◽

2019 ◽

Vol 87 (6) ◽

pp. 1941-2002 ◽

Cited By ~ 2

Author(s):

Mira Frick ◽

Ryota Iijima ◽

Tomasz Strzalecki

Keyword(s):

Choice Behavior ◽

Empirical Work ◽

Parameter Estimates ◽

Random Utility ◽

Choice Data ◽

Stochastic Choice ◽

Axiomatic Analysis ◽

Special Cases ◽

Dynamic Stochastic ◽

Bayesian Rationality

We provide an axiomatic analysis of dynamic random utility, characterizing the stochastic choice behavior of agents who solve dynamic decision problems by maximizing some stochastic process ( U t ) of utilities. We show first that even when ( U t ) is arbitrary, dynamic random utility imposes new testable across‐period restrictions on behavior, over and above period‐by‐period analogs of the static random utility axioms. An important feature of dynamic random utility is that behavior may appear history‐dependent, because period‐ t choices reveal information about U t , which may be serially correlated; however, our key new axioms highlight that the model entails specific limits on the form of history dependence that can arise. Second, we show that imposing natural Bayesian rationality axioms restricts the form of randomness that ( U t ) can display. By contrast, a specification of utility shocks that is widely used in empirical work violates these restrictions, leading to behavior that may display a negative option value and can produce biased parameter estimates. Finally, dynamic stochastic choice data allow us to characterize important special cases of random utility—in particular, learning and taste persistence—that on static domains are indistinguishable from the general model.

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The Effect of Indivisibilities in Consumer Choice Theory

The American Economist ◽

10.1177/056943457001400205 ◽

1970 ◽

Vol 14 (2) ◽

pp. 47-56 ◽

Cited By ~ 1

Author(s):

Edward Gordon

Keyword(s):

Consumer Choice ◽

Fundamental Theorem ◽

Choice Behavior ◽

Choice Theory ◽

Budget Constraint ◽

Rational Behavior ◽

Strict Monotonicity ◽

Axiomatic Treatment ◽

Consumer Choice Behavior ◽

Weak Axiom

Consumer choice theory is normally based on the assumption that the domain of commodity mixes which can be chosen is continuously divisible (dense). The effects on consumer choice behavior recently attributed by Harwitz to indivisibilities are shown to be due to the removal of strong convexity and strict monotonicity from the expressed binary preference properties. A binary preference axiomatic treatment is presented which is applicable in the presence of indivisibilities. Tolerance to indivisibilities in the decision domain is accomplished with three binary preference axioms which are sufficient to assure the existence of a utility function. One axiom is added for the budget constraint and another to cover the expenditure minimization concept of rational behavior. With these five axioms, Samuelson's weak axiom and fundamental theorem of consumer behavior can be extended to be applicable with indivisibilities in the decision domain.

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Trust in Management Information Systems (MIS)

Zeitschrift für Arbeits- und Organisationspsychologie A&O ◽

10.1026/0932-4089/a000306 ◽

2020 ◽

Vol 64 (1) ◽

pp. 6-16 ◽

Cited By ~ 5

Author(s):

Sarah M. Meeßen ◽

Meinald T. Thielsch ◽

Guido Hertel

Keyword(s):

Information Systems ◽

Information Overload ◽

Management Information Systems ◽

Empirical Work ◽

Future Research ◽

Management Information ◽

Trust In Management ◽

Actual Use ◽

Trust In Technology ◽

The Internet Of Things

Abstract. Digitalization, enhanced storage capacities, and the Internet of Things increase the volume of data in modern organizations. To process and make use of these data and to avoid information overload, management information systems (MIS) are introduced that collect, process, and analyze relevant data. However, a precondition for the application of MIS is that users trust them. Extending accounts of trust in automation and trust in technology, we introduce a new model of trust in MIS that addresses the conceptual ambiguities of existing conceptualizations of trust and integrates initial empirical work in this field. In doing so, we differentiate between perceived trustworthiness of an MIS, experienced trust in an MIS, intentions to use an MIS, and actual use of an MIS. Moreover, we consider users’ perceived risks and contextual factors (e. g., autonomy at work) as moderators. The introduced model offers guidelines for future research and initial suggestions to foster trust-based MIS use.

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