Order Effects in Customer Satisfaction Modelling

This research examines the effects of question order on the output of a customer satisfaction model. Theory suggests that locating product attribute evaluations prior to overall evaluations of satisfaction and loyalty should increase the impact of performance drivers in the model, explain more variation in the overall evaluations, and make positive satisfaction and loyalty evaluations more extreme. Our results show that, although customers′ overall evaluations are more extreme and better explained when provided after attribute evaluations, the impact of satisfaction drivers is relatively unaffected. Consistent with expectations, question order does affect the explained variation in satisfaction and the levels of satisfaction and loyalty. Implications for satisfaction modelling are discussed

Choosing now or choosing later: The effects of time delay and preference uncertainty on *variety in repeated choice.

Consumers routinely purchase multiple items at once for future consumption, such as groceries and vacation packages. Interestingly, research has shown that people choosing multiple items from an assortment tend to choose a greater variety of items when all items are chosen simultaneously as a group, before consumption, versus when each item is chosen, then consumed, sequentially one at a time. This phenomenon is referred to as the diversification bias, implying that it results from perceptual biases or biased decision processes. We take an alternative approach and show that the stochastic nature of preferences can explain why and when we observe the diversification bias. Consumers choosing now for future consumption experience greater preference uncertainty than consumers choosing for immediate consumption, due to temporally inflated stochastic variation in anticipated utility. Even without anticipating any temporal shifts in the mean liking for alternatives, simultaneous decision makers will experience future preference uncertainty and choose greater variety than sequential decision makers---leading to the diversification bias. Using random utility theory, we demonstrate that increasing stochastic variation in utilities of available alternatives, while holding mean attractiveness of alternatives constant, will lead to the diversification bias. Using a heteroscedastic extreme value (HEV) choice modeling methodology that accounts for temporal differences in stochastic variation, we find strong empirical support that time delay between choice and consumption increases stochastic variation in consumers' anticipated future utility. Thus future preference uncertainty leads to the diversification bias. Using a series of controlled experiments, with snacks as stimuli, we show that increasing the number of available alternatives and the density of more-preferred alternatives can induce high preference uncertainty and eliminate the diversification bias. We also show that a choice set with a very low density of more-preferred alternatives can induce low preference uncertainty and eliminate the diversification bias. In addition, we find that risk attitude does not moderate the size of the diversification bias, as previous research suggests. Finally, we demonstrate that one would need impractically large sample sizes to observe statistically significant differences in choice with the traditional regression-based measures commonly used in consumer behavior research.Ph.D.MarketingSocial SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/125214/2/3186751.pd

Alleviating the Constant Stochastic Variance Assumption in Decision Research: Theory, Measurement, and Experimental Test

Analysts often rely on methods that presume constant stochastic variance, even though its degree can differ markedly across experimental and field settings. This reliance can lead to misestimation of effect sizes or unjustified theoretical or behavioral inferences. Classic utility-based discrete-choice theory makes sharp, testable predictions about how observed choice patterns should change when stochastic variance differs across items, brands, or conditions. We derive and examine the implications of assuming constant stochastic variance for choices made under different conditions or at different times, in particular, whether substantive effects can arise purely as artifacts. These implications are tested via an experiment designed to isolate the effects of stochastic variation in choice behavior. Results strongly suggest that the stochastic component should be carefully modeled to differ across both available brands and temporal conditions, and that its variance may be relatively greater for choices made for the future. The experimental design controls for several alternative mechanisms (e.g., flexibility seeking), and a series of related models suggest that several econometrically detectable explanations like correlated error, state dependence, and variety seeking add no explanatory power. A series of simulations argues for appropriate flexibility in discrete-choice specification when attempting to detect temporal stochastic inflation effects.brand choice, choice models, decisions under uncertainty, decision making over time, econometric models, lab experiments, measurement and inference, probability models, simulation, stochastic models

—Temporal Stochastic Inflation in Choice-Based Research

We examine the specification and interpretation of discrete-choice models used in behavioral theory testing, with a focus on separating “coefficient scale” from “error scale,” particularly over time. Numerous issues raised in the thoughtful commentaries of Louviere and Swait [Louviere, J., J. Swait. 2010. Discussion of “Alleviating the constant stochastic variance assumption in decision research: Theory, measurement, and experimental test.” (1) 18–22] and Hutchinson, Zauberman, and Meyer (HZM) [Hutchinson, J. W., G. Zauberman, R. Meyer. 2010. On the interpretation of temporal inflation parameters in stochastic models of judgment and choice. (1) 23–31] are addressed, specifically the roles of response scaling, preference covariates, actual versus hypothetical consumption, “immediacy,” and heterogeneity, as well as key differences between the experimental setup in Salisbury and Feinberg [Salisbury, L. C., F. M. Feinberg. 2010. Alleviating the constant stochastic variance assumption in decision research: Theory, measurement, and experimental test. (1) 1–17] and those typifying intertemporal choice and construal level theory. We strongly concur with most of the general conclusions put forth by the commentary authors, but we also emphasize a central point made in our research that may have been lost: that the temporal inflation effects observed in our empirical analysis could be attributed to stochastic effects, deterministic influences, or an amalgam; appropriate inferences depend on the nature of one's data and stimuli. We also report on further analyses of our data, as well as a meta-analysis of HZM's Table 1 that is consistent with our original findings. Implications for, and dimensions relevant to, future research on temporal stochastic inflation and its role in choice-based research are discussed.brand choice, choice models, construal level theory, decisions under uncertainty, decision making over time, econometric models, intertemporal choice, measurement and inference, probability models, stochastic models

Future Preference Uncertainty and Diversification: The Role of Temporal Stochastic Inflation

Consumers' choices tend to display greater variety when made for future versus immediate consumption. Previous accounts of such diversification differences suggested that they are driven primarily by (deterministic) shifts in underlying preference. Through a series of simulation studies, we propose and assess an alternative contributory mechanism: temporal stochastic inflation, the greater uncertainty typifying choices made for the future. We find effect sizes to be strongly influenced by relative brand attractiveness, brand attractiveness uncertainty, and degree of stochastic inflation, although not preference heterogeneity. Moreover, effect sizes are consistent with prior studies that attributed diversification differences to underlying preference shifts alone. (c) 2008 by JOURNAL OF CONSUMER RESEARCH, Inc..

Minimum required payment and supplemental information disclosure effects on consumer debt repayment decisions

Repayment decisions—how much of the loan to repay and when to make the payments—directly influence consumer debt levels. The authors examine how minimum required payment policy and loan information disclosed to consumers influence repayment decisions. They find that though presenting minimum required payment information has a negative impact on repayment decisions, increasing the minimum required level has a positive effect on repayment for most consumers. Experimental evidence from U.S. consumers shows that consumers’ propensity to pay the minimum required each month moderates these effects; U.K. credit card field data indicates that these effects are also moderated by borrowers’ credit limit and balance due. However, increasing the minimum level is unlikely to completely eliminate the negative effect of presenting minimum payment information. In addition, disclosing supplemental information, such as future interest cost and time needed to repay the loan, does not reduce the negative effects of including minimum payment information and has no substantial positive effect on repayments. This research offers new insights into the debt repayment process and has implications for consumers, lenders, and public policy

sj-pdf-1-jmx-10.1177_00222429221150910 - Supplemental material for Beyond Income: Dynamic Consumer Financial Vulnerability

Supplemental material, sj-pdf-1-jmx-10.1177_00222429221150910 for Beyond Income: Dynamic Consumer Financial Vulnerability by Linda Court Salisbury, Gergana Y. Nenkov, Simon J. Blanchard, Ronald Paul Hill, Alexander L. Brown and Kelly D. Martin in Journal of Marketing</p

Individuals' decisions in the presence of multiple goals

This paper develops new directions on how individuals’ use of multiple goals can be incorporated in econometric models of individual decision-making. We start by outlining key components of multiple, simultaneous goal pursuit and multi-stage choice. Since different goals are often only partially compatible, such a multiple goal-based approach implies balancing goals, leading to a deliberate goal-level choice strategy on the part of the decision-maker. Accordingly, we introduce a conceptual framework to classify different aspects of individuals’ decisions in the presence of multiple goals. Based on this framework, we propose a formalization of individual decision-making when pursuing multiple goals. We briefly review different previous streams on goal-based decision-making and how the proposed goal-driven conceptual framework relates to earlier research in discrete choice models. The framework is illustrated using examples from different domains, in particular marketing, environmental economics, transportation, and sociology. Finally, we discuss identification and modeling needs for goal-based choice strategies and opportunities for further research.Transport and Logistic