Integrating Routine, Variety Seeking and Compensatory Choice in a Utility Maximizing Framework

Given the large number of choices that consumers make each day it seems likely that they will generally adopt decision strategies that minimize cognitive effort, particularly with low price products such as most items found in a supermarket. One such strategy may be to simply choose what has been chosen in the past, i.e. to fall into a pattern of routine choices or decisions. In contrast, there may be preferences for variety in markets for low price, highly differentiated goods. We develop a conceptual and empirical model of routine choice, and the factors that result in transitions to two strategies other than routine selection, to wit, utility maximizing choice among available alternatives and a variety seeking strategy. The empirical approach we employ provides a mechanism for the examination of panel data that avoids the state dependence issues present in most applications to these types of data. We apply this framework to the choice of two food products that illustrate the heterogeneity across types of products in decision strategies and routine choice patterns.Choice modeling, routine behavior, variety‐seeking, panel data, Consumer/Household Economics, Demand and Price Analysis, Institutional and Behavioral Economics, D12, D03, C25,

Seasonality Effects on Consumers Preferences Over Quality Attributes of Different Beef Products

Using discrete choice modelling, the study investigates 946 American consumers willingness-to-pay and preferences for diverse beef products. A novel experiment was used to elicit the number of beef products that each consumer would purchase. The range of products explored in this study included ground, diced, roast, and six cuts of steaks (sirloin, tenderloin, flank, flap, New York and cowboy or rib-eye). The outcome of the study suggests that US consumers vary in their preferences for beef products by season. The presence of a USDA certification logo is by far the most important factor affecting consumers willingness to pay for all beef cuts, which is also heavily dependent on season. In relation to packaging, US consumers have mixed preference for different beef products by season. The results from a scaled adjusted ordered logit model showed that after price, safety-related attributes such as certification logos, types of packaging, and antibiotic free and organic products are a stronger influence on American consumers choice. Furthermore, US consumers on average purchase diced and roast products more often in winter slow cooking season, than in summer, whereas New York strip and flank steak are more popular in the summer grilling season. This study provides valuable insights for businesses as well as policymakers to make inform decisions while considering how consumers relatively value among different labelling and product attributes by season and better address any ethical, safety and aesthetic concerns that consumers might have

Travel mode substitution in Sao Paulo : estimates and implications for air pollution control

How would travel demand in Sao Paulo respond to demand management instruments? Could higher gasoline prices or lower metro fares (or changes in travel time) help reduce congestion or pollution? The authors use cross-sectional variation from an urban travel survey to study the substitutability in demand between travel modes. The method assumes that the set of trips is given (that is, origin-destination pairs do not change). Choice of mode was found to be quite insensitive to changes; all elasticities were lower than 0.5 in absolute value, and most were close to zero. While the sensitivity of mode choice to relative travel times (that is, speeds) was somewhat greater than that to costs, the general finding is that mode choice is quite inflexible. So, subsidies to less polluting (less congesting) travel modes would not help much in attracting travelers from more polluting (more congesting) modes. (The same holds for subsidized means of making them run faster.) But there are important limitations in the scope of the study. First, the study does not discuss optimal pricing. It merely examines the likely sign and magnitude of the links between pollution and policy parameters such as prices and travel speeds. Second, aggregate demand by mode could also depend on the city's shape and its travel intensity (the number, direction, and length of trips). For example, if a"city"stretches along a constructed metro line, the study would not capture such a phenomenon, since sensitive trip generation is excluded. These issues are not examined in the study.Roads&Highways,Consumption,Economic Theory&Research,Environmental Economics&Policies,Transport Economics Policy&Planning,Roads&Highways,Economic Theory&Research,Urban Transport,Environmental Economics&Policies,Transport and Environment

Preserve or retreat? Willingness-to-pay for Coastline Protection in New South Wales

Coastal erosion is a global and pervasive phenomenon that predicates a need for a strategic approach to the future management of coastal values and assets (both built and natural), should we invest in protective structures like seawalls that aim to preserve specific coastal features, or allow natural coastline retreat to preserve sandy beaches and other coastal ecosystems. Determining the most suitable management approach in a specific context requires a better understanding of the full suite of economic values the populations holds for coastal assets, including non-market values. In this study, we characterise New South Wales residents willingness to pay to maintain sandy beaches (width and length). We use an innovative application of a Latent Class Binary Logit model to deal with Yea-sayers and Nay-sayers, as well as revealing the latent heterogeneity among sample members. We find that 65% of the population would be willing to pay some amount of levy, dependent on the policy setting. In most cases, there is no effect of degree of beach deterioration characterised as loss of width and length of sandy beaches of between 5% and 100% on respondents willingness to pay for a management levy. This suggests that respondents who agreed to pay a management levy were motivated to preserve sandy beaches in their current state irrespective of the severity of sand loss likely to occur as a result of coastal erosion. Willingness to pay also varies according to beach type (amongst Iconic, Main, Bay and Surf beaches) a finding that can assist with spatial prioritisation of coastal management. Not recognizing the presence of nay-sayers in the data or recognizing them but eliminating them from the estimation will result in biased WTP results and, consequently, biased policy propositions by coastal managers.Comment: arXiv admin note: substantial text overlap with arXiv:1902.0241

CHOICE AND TEMPORAL WELFARE IMPACTS: DYNAMIC GEV DISCRETE CHOICE MODELS

Welfare economics is often employed to measure the impact of economic policies or externalities. When demand is characterized by discrete choices, static models of consumer demand are employed for this type of analysis because of the difficulty in estimating dynamic discrete choice models. In this paper we provide a tractable approach to estimating dynamic discrete choice models of the Generalized Extreme Value (GEV) family that addresses many of the problems identified in the literature and provides a rich set of parameters describing dynamic choice. We apply this model to the case of recreational fishing site choice, comparing dynamic to static versions. In natural resource damage assessment cases, static discrete choice models of recreational site choice are often employed to calculate welfare measures, which will be biased if the underlying preferences are actually dynamic in nature. In our empirical case study we find that the dynamic model provides a richer behavioral model of site choice, and reflects the actual choices very well. We also find significant differences between static and dynamic welfare measures. However, we find that the dynamic model raises several concerns about the specification of the policy impact and the subsequent welfare measurement that are not raised in static cases.Demand and Price Analysis,

Citizen Participation in Patient Prioritization Policy Decisions: An Empirical and Experimental Study on Patients' Characteristics

Health systems worldwide are grappling with the need to control costs to maintain system viability. With the combination of worsening economic conditions, an aging population and reductions in tax revenues, the pressures to make structural changes are expected to continue growing. Common cost control mechanisms, e.g. curtailment of patient access and treatment prioritization, are likely to be adversely viewed by citizens. It seems therefore wise to include them in the decision making processes that lead up to policy changes. In the context of a multilevel iterative mixed-method design a quantitative survey representative of the German population (N = 2031) was conducted to probe the acceptance of priority setting in medicine and to explore the practicability of direct public involvement. Here we focus on preferences for patients' characteristics (medical aspects, lifestyle and socio-economic status) as possible criteria for prioritizing medical services. A questionnaire with closed response options was fielded to gain insight into attitudes toward broad prioritization criteria of patient groups. Furthermore, a discrete choice experiment was used as a rigorous approach to investigate citizens' preferences toward specific criteria level in context of other criteria. Both the questionnaire and the discrete choice experiment were performed with the same sample. The citizens' own health and social situation are included as explanatory variables. Data were evaluated using corresponding analysis, contingency analysis, logistic regression and a multinomial exploded logit model. The results show that some medical criteria are highly accepted for prioritizing patients whereas socio-economic criteria are rejected

Modelling online job search and choices of dentists in the Australian job market:Staged sequential DCEs and FIML econometric methods

Workforce participation decisions involve multiple stages: search, screening and offer evaluation. Standard econometric practice focusses on these stages in isolation. We conceptualize the focal behaviours as separate sequential decision stages, and provide a stated preference measurement framework for online job search and choice with a behaviourally consistent modelling approach. We demonstrate this approach in an empirical application of 275 dentists who completed an online survey including two Discrete Choice Experiments: the first mimicked an online job search site in which dentists decided which jobs they would apply to and the second presented dentists with a job offer which they accepted or rejected. Modelling these tasks requires a two-stage econometric model that incorporates the likelihood of application (first stage) into the job offer choice (second stage). The model detects differences in preferences (hence behaviours) across stages, facilitating the differentiation of policy aimed at search and job choice behaviours. Job screening occurs during search and the marginal propensity to apply for a job-type differs from the offer stage. We suggest that the approach presented provides a valuable way to investigate how dentists particularly, and perhaps the health workforce more generally, respond at different stages of workforce participation decisions and discuss practical implications

Jeopardizing brand profitability by misattributing process heterogeneity to preference heterogeneity

Brands develop strategies based on forecasts that allow for individual differences, usually attributed empirically to heterogeneity in consumers' preferences. Behavioral theories propose choice process heterogeneity as the conditioning stage for choice outcomes, and suggest that not accounting for it causes biases in parameters and policy measures. We conduct a Monte Carlo simulation to study how underlying choice process heterogeneity generates substantively significant biases in different market contexts if analysts (erroneously) channel heterogeneity solely into tastes. We extend the literature by using a game theoretical analysis, driven by the results from the demand simulation, to explore demand mis-specification effects on brands' profitability and market equilibrium. Through mixed strategies we examine necessary conditions for market equilibrium when managers have access to different demand representations but are uncertain about which is true. We demonstrate that biases generated by representing consumer response heterogeneity solely through preference heterogeneity are enough to significantly jeopardize brands' profits due to misalignment of firms' products and resources with demand. Our work forcefully demonstrates to both marketers and econometricians/data scientists the necessity of modeling choice process heterogeneity given its impacts on brands’ performance.</p

Combining Sources of Preference Data: The Case of the Lurking l‘s

This paper brings together several research streams and concepts that have been evolving in random utility choice theory: first, it reviews the literature on stated preference (SP) elicitation methods and introduces the concept of testing data generation process invariance across SP and revealed preference (RP) choice data sources; second, it proposes a general data generation process an useful framework for viewing this data combination process; third, it describes the evolution of discrete choice models within the random utility family, where progressively more behavioural realism is being achieved by relaxing strong assumptions on the role of the variance structure (specifically heteroscedasticity) of the unobserved effects. This latter topic is central to the issue of combining multiple data sources. Particular choice model formulations incorporating heteroscedastic effects are presented, discussed and applied to data. The rich insights possible from modeling heteroscedasticity in choice processes is illustrated in each of the empirical applications, which examine its relevance to issues of data combination and taste heterogeneity

Separating generalizable from source-specific preference heterogeneity in the fusion of revealed and stated preferences

Preference heterogeneity is one of the central behavioral concepts in applied econometrics. Its centrality is particularly evident in the choice modeling literature, notably in its widespread application to environmental and health economics, marketing, and transport. Despite conceptual and empirical advances in modeling preference heterogeneity, the generalizability of preference heterogeneity to different decision contexts and different data generation processes remains an open question. The basic premise of this paper is that latent sources of preference heterogeneity can be decomposed into components general to decision contexts and others specific to them. We study the structure of preference heterogeneity in different data generation processes with the goal of reliably identifying common (presumably generalizable) and specific (presumably not generalizable) sources of preference heterogeneity. The contribution of the paper is both conceptual and methodological, leading to the testing of five rival model specifications which together elucidate the heterogeneity structure present in two preference data sources of the same choice behavior. In the empirical application, we find that the multitrait-multimethod model of preference heterogeneity has the best fit and most sensible interpretations, indicating that while each data source contributes uniquely to certain heterogeneity components, both data sources contribute also to common (generalizable) preference heterogeneity. Recognition of the separability of the common versus source-specific preference heterogeneity will lead to more reliable and accurate demand model forecasts and assessments of welfare impacts