How Tolerable is Delay? Consumers' Evaluations of Internet Web Sites After Waiting

How consumers’ waiting times affect their retrospective evaluations of Internet Web Sites is investigated in four computer-based experiments. Results show that waiting can but does not always negatively affect evaluations of Web Sites. Results also show that the potential negative effects of waiting can be neutralized by managing waiting experiences effectively. A conceptual framework and formal random utility model is introduced.Marketing;consumer preference models;waiting experiences;Internet marketing

Complexity and accuracy in consumer choice : the double benefits of being the consistently better brand

This study investigates the impact of choice complexity on consumer utility and choice. The authors find that for choices with up to seven alternatives and seven attributes choice accuracy is affected by three context-based complexity effects but not by task-based complexity. The results suggest that brands that are able to create products that outperform competing products and that do so consistently across multiple attributes benefit from a double bonus. Not only is their product more attractive to consumers, but the accuracy with which consumers choose the product also increases, leading to a further increase in the brand's market shar

Optimal effort in consumer choice : theory and experimental analysis for binary choice

This paper develops a theoretical model of optimal effort in consumer choice. The model extends previous consumer choice models in that the consumer not only chooses a product, but also decides how much effort to apply to a given choice problem. The model yields a unique optimal level of effort, which depends on the consumer's cost of effort, the expected utility gain of a correct choice, and the complexity of the choice set. We show that the relationship between effort and cost of effort is negative, whereas the relationships between effort and product utility difference and choice task complexity are undetermined. To resolve this theoretical ambiguity and to explore our model empirically, we investigate the relationships between effort and cost of effort, product utility difference and choice task complexity using data from a conjoint choice study of two-alternative consumer restaurant choices. Response time is used as a proxy for effort and consumer involvement measures capture individual differences in (relative) cost of effort and perceived complexity. Effort is explained using the (estimated) utility difference between alternatives, the number of elementary information processes (EIP's) required to solve the choice problem optimally and respondent specific cost of effort and complexity perceptions. The predictions of the theoretical model are supported by our empirical findings. Response time increases with lower cost of effort and greater perceived complexity (i.e. higher involvement). We find that across the range of choice tasks in our survey, effort increases linearly with smaller product utility differences and greater choice task complexity

Combining and comparing consumers' stated preference ratings and choice responses

In this study we develop and test an econometric model for combining choice and preference ratings data collected from the same set of individuals. Choice data are modeled using a multinomial logit framework, while preference data are modeled using an ordered response equation. Individual heterogeneity is allowed for via random coefficients providing a link between the choice and ratings data. Parameters are estimated by Simulated Maximum Likelihood. An application of the model to consumer yoghurt choice in The Netherlands found that ratings based preference estimates differ significantly from choice based estimates, but the correlation between random coefficients driving the two is very stron

Insurers' profits in the third-party liability insurance

In this note we derive the expected total discounted profit of an insurer due to a single policy holder within a third-party liability insurance. We consider both a policy holder claiming optimally and non-optimally

iSAM2 : incremental smoothing and mapping using the Bayes tree

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Sage for personal use, not for redistribution. The definitive version was published in International Journal of Robotics Research 31 (2012): 216-235, doi:10.1177/0278364911430419.We present a novel data structure, the Bayes tree, that provides an algorithmic foundation enabling a better understanding of existing graphical model inference algorithms and their connection to sparse matrix factorization methods. Similar to a clique tree, a Bayes tree encodes a factored probability density, but unlike the clique tree it is directed and maps more naturally to the square root information matrix of the simultaneous localization and mapping (SLAM) problem. In this paper, we highlight three insights provided by our new data structure. First, the Bayes tree provides a better understanding of the matrix factorization in terms of probability densities. Second, we show how the fairly abstract updates to a matrix factorization translate to a simple editing of the Bayes tree and its conditional densities. Third, we apply the Bayes tree to obtain a completely novel algorithm for sparse nonlinear incremental optimization, named iSAM2, which achieves improvements in efficiency through incremental variable re-ordering and fluid relinearization, eliminating the need for periodic batch steps. We analyze various properties of iSAM2 in detail, and show on a range of real and simulated datasets that our algorithm compares favorably with other recent mapping algorithms in both quality and efficiency.M. Kaess, H. Johannsson and J. Leonard were partially supported by ONR grants N00014-06-1-0043 and N00014-10-1-0936. F. Dellaert and R. Roberts were partially supported by NSF, award number 0713162, “RI: Inference in Large-Scale Graphical Models”. V. Ila has been partially supported by the Spanish MICINN under the Programa Nacional de Movilidad de Recursos Humanos de Investigación

What Are the Ants Doing? Vision-Based Tracking and Reconstruction of Control Programs

©2005 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the 2005 IEEE International Conference on Robotics and Automation (ICRA), 18-22 April 2005, Barcelona, Spain.DOI: 10.1109/ROBOT.2005.1570762In this paper, we study the problem of going from a real-world, multi-agent system to the generation of control programs in an automatic fashion. In particular, a computer vision system is presented, capable of simultaneously tracking multiple agents, such as social insects. Moreover, the data obtained from this system is fed into a mode-reconstruction module that generates low-complexity control programs, i.e. strings of symbolic descriptions of control-interrupt pairs, consistent with the empirical data. The result is a mechanism for going from the real system to an executable implementation that can be used for controlling multiple mobile robots

Beyond nudges: Tools of a choice architecture

The way a choice is presented influences what a decision-maker chooses. This paper outlines the tools available to choice architects, that is anyone who present people with choices. We divide these tools into two categories: those used in structuring the choice task and those used in describing the choice options. Tools for structuring the choice task address the idea of what to present to decision-makers, and tools for describing the choice options address the idea of how to present it. We discuss implementation issues in using choice architecture tools, including individual differences and errors in evaluation of choice outcomes. Finally, this paper presents a few applications that illustrate the positive effect choice architecture can have on real- world decisions