When Zeros Count: Confounding in Preference Heterogeneity and Attribute Non-Attendance
(with Daniel Guhl and Friederike Paetz)
Identifying consumer heterogeneity is a central topic in marketing. While the main focus has been on developing models and estimation procedures that allow uncovering consumer heterogeneity in preferences, a new stream of literature has focused on models that account for consumers’ heterogeneous attribute information usage. These models acknowledge that consumers may ignore subsets of attributes when making decisions, also commonly termed “attribute nonattendance" (ANA). In this paper, we explore the performance of choice models that explicitly account for ANA across ten different applications, which vary in terms of the choice context, the associated financial risk, and the complexity of the purchase decision. We systematically compare five different models that either neglect ANA and preference heterogeneity, account only for one at a time, or account for both across these applications. First, we showcase that ANA occurs across all ten applications. It prevails even in simple settings and high-stakes decisions.
Work in Progress
Lottery Rewards in Incentive-aligned Choice-based Conjoint Studies
The use of incentive alignment mechanisms in choice-based conjoint (CBC) studies or discrete choice experiments has become state-of-the-art. Incentive alignment aims to reduce hypothetical bias, leading to higher external validity and more realistic WTP measures. Lottery rewards are often employed to mitigate high implementation costs, i.e., respondents’ choices are consequential at the realization probability. While in theory, any positive realization probability should induce truth-telling, recent studies find that higher ones lead to more attention to the choice-relevant information and better demand forecasting. This study investigates whether similar patterns hold when the realization probabilities are very low to begin with (e.g., 1% or lower) – a typical case for many studies (e.g., in the case of durable goods). The experimental results suggest that, indeed, the marginal increases in the realization probability matter and result in an improvement of external predictive validity. Furthermore, I investigate the role of ambiguity in the way the realization probabilities are communicated to the respondents – as an objective probability (e.g., 1:200 chances of winning), an interval (1:200 to 1:400 chances of winning), or as an ambiguous prospect (one lucky winner from the pool of participants). I find that respondents seem to penalize for ambiguity in communication, and even more so in the case of using an interval of chances of winning. I further investigate the role of risk and ambiguity preferences on the external predictive validity of incentive-aligned CBC.
The Effect of Information Transparency on Consumers' Data Disclosure Behavior: A Meta-Analysis
(with Maja Adena, Camila Back, Alaa Elgayar, Daniel Guhl, Daniel Klapper, Martin Spann, and Lucas Stich)
Information Processing Patterns during Choice. The Effect of Complexity and Product Category Involvement on Attribute Non-Attendance
(with Alaa Elgayar)
From a marketer’s standpoint, it is crucial to understand how potential customers process product information offered to them in a purchase scenario. When modeling choice behavior under standard random utility theory, we typically assume that decision-makers behave in a “rational” manner, i.e., exhibit stable preferences, process all available information, and apply compensatory decision rules. However, following the bounded rationality framework, the validity of these assumptions has been widely challenged. Experimental studies demonstrate that decision-makers may ignore some product attributes when making choices, commonly termed attribute non-attendance (ANA). Such behavior may be due to limited cognitive capacity and information overload or consumers may find some attributes not relevant. However, few studies have ventured into explicitly examining context- and person-related drivers of ANA as a decision heuristic. The contribution of our paper is two-fold. First, this paper investigates the joint effects of choice design complexity and product category involvement on ANA using three between-subject discrete choice experiments, where two aspects of complexity (number of attributes and alternatives) and product category involvement are experimentally manipulated. We hypothesize that an increase in complexity and decrease in involvement adversely affect attendance. Second, we explicitly test whether the proposed associations may vary according to the type of attribute information. Inspecting stated and inferred ANA, our results demonstrate complexity-induced ANA for one design dimension, a positive effect of involvement on attendance and the moderating effect of extrinsic attributes.