Past price ‘memory’ in the housing market: testing the performance of different spatio-temporal specifications

Recent methodological developments provide a way to incorporate the temporal dimension when accounting for spatial effects in hedonic pricing. Weight matrices should decompose the spatial effects into two distinct components: bidirectional contemporaneous spatial connections; and unidirectional spatio-temporal effects from past transactions. Our iterative estimation approach explicitly analyses the role of time in price determination. The results show that both spatio-temporal components should be included in model specification; past transaction information stops contributing to price determination after eight months; and limited temporal friction is exhibited within this period. These findings highlight the decidedly non-linear temporal patterns of such information effects.     

Contextualized representations of brand extensions: Are feature lists or frames the basic components of consumer cognition?

According to the common view in consumer behavior, consumers represent brands and product categories mentally as lists of independent product features and engage in feature matching when they evaluate brand-product category compounds such as brand extensions. However, we demonstrate that brand extension concepts are subject to context effects and largely contextually organized — empirical evidence which suggests that they are represented by more flexible mental structures than independent feature lists. As an alternative, brand extensions (e.g., McDonald's Theme Park) may be viewed as conceptual combinations in which the original brand or company name (e.g., McDonald's) acts on the head concept of the extension category (e.g., theme parks) as a modifier. Moreover, we suggest that the contextual and relational structure of brand extensions may be explained more adequately by mental frames than feature list representations.     

Decision neuroscience and consumer decision making

This article proposes that neuroscience can shape future theory and models in consumer decision making and suggests ways that neuroscience methods can be used in decision-making research. The article argues that neuroscience facilitates better theory development and empirical testing by considering the physiological context and the role of constructs such as hunger, stress, and social influence on consumer choice and preferences. Neuroscience can also provide new explanations for different sources of heterogeneity within and across populations, suggest novel hypotheses with respect to choices and underlying mechanisms that accord with an understanding of biology, and allow for the use of neural data to make better predictions about consumer behavior. The article suggests that despite some challenges associated with incorporating neuroscience into research on consumer decision processes, the use of neuroscience paradigms will produce a deeper understanding of decision making that can lead to the development of more effective decision aids and interventions.     

Empirical Analysis of Indirect Network Effects in the Market for Personal Digital Assistants

We present a framework to measure empirically the size of indirect network effects in high-technology markets with competing incompatible technology standards. These indirect network effects arise due to inter-dependence in demand for hardware and compatible software. By modeling the joint determination of hardware sales and software availability in the market, we are able to describe the nature of demand inter-dependence and to measure the size of the indirect network effects. We apply the model to price and sales data from the industry for personal digital assistants (PDAs) along with the availability of software titles compatible with each PDA hardware standard. Our empirical results indicate significant indirect network effects. By July 2002, the network effect explains roughly 22% of the log-odds ratio of the sales of all Palm O/S compatible PDA-s to Microsoft O/S compatible PDA-s, where the remaining 78% reflects price and model features. We also use our model estimates to study the growth of the installed bases of Palm and Microsoft PDA hardware, with and without the availability of compatible third party software. We find that lack of third party software negatively impacts the evolution of the installed hardware bases of both formats. These results suggest PDA hardware firms would benefit from investing resources in increasing the provision of software for their products. We then compare the benefits of investments in software with investments in the quality of hardware technology. This exercise helps disentangle the potential for incremental hardware sales due to hardware quality improvement from that of positive feedback due to market software provision.     

The Joint identification of utility and discount functions from stated choice data: An application to durable goods adoption

We present a survey design that generalizes static conjoint experiments to elicit inter-temporal adoption decisions for durable goods. We show that consumers’ utility and discount functions in a dynamic discrete choice model are jointly identified using data generated by this specific design. In contrast, based on revealed preference data, the utility and discount functions are generally not jointly identified even if consumers’ expectations are known. The separation of current-period preferences from discounting is necessary to forecast the diffusion of a durable good under alternative marketing strategies. We illustrate the approach using two surveys eliciting Blu-ray player adoption decisions. Both model-free evidence and the estimates based on a dynamic discrete choice model indicate that consumers make forward-looking adoption decisions. In both surveys the average discount rate is 43 percent, corresponding to a substantially higher degree of impatience than the rate implied by aggregate asset returns. The estimates also reveal a large degree of heterogeneity in the discount rates across consumers, but only little evidence for hyperbolic discounting.     

A Spatiotemporal Solution for the Simultaneous Sale Price and Time‐on‐the‐Market Problem

There exists an important methodological challenge when dealing with sale price and time‐on‐the‐market variables because both variables are simultaneously determined and related to the motivation of the sellers and buyers. Exploiting the fact that transactions occur over space and time, we propose a two‐stage approach based on instrumental variables (IV) built from information collected from previous transactions. The unidirectional temporal property and the fact that other transactions are exogenous from the perspective of a single buyer or seller are exploited to evaluate the effect of the sale price on time‐on‐the‐market, and the effect of time‐on‐the‐market on the sale price. Based on 29,471 transactions occurring in the suburban neighborhood of Montréal (1992‐2000), the results suggest that, everything else being equal, houses staying longer on the market provide negative information to the market, which results in a lower final sale price, while the final sale price is negatively related to time‐on‐the‐market, indicating that houses of better quality (better amenities) stay less time on the market.     

Associations among Park Use,Age, Social Participation,and Neighborhood Age Composition in Montreal

Parks provide benefits for the physical, psychological, and social well-being of residents in neighborhood environments. Multilevel logistic regression was used to examine associations between neighborhood- and individual-level characteristics and the lack of park use in Montreal. Data on park use were collected from 787 adults residing in 299 different neighborhoods. Results found that older adults who lived in areas with a younger age composition were more likely not to use their nearby parks as compared to older adults living in areas with an older age composition. Forms of social participation were also important for the park use of older adults. Public policies should consider targeting aspects of the social environment to improve neighborhood park use.     

Towards a brain-to-society systems model of individual choice

Canonical models of rational choice fail to account for many forms of motivated adaptive behaviors, specifically in domains such as food selections. To describe behavior in such emotion- and reward-laden scenarios, researchers have proposed dual-process models that posit competition between a slower, analytic faculty and a fast, impulsive, emotional faculty. In this paper, we examine the assumptions and limitations of these approaches to modeling motivated choice. We argue that models of this form, though intuitively attractive, are biologically implausible. We describe an approach to motivated choice based on sequential sampling process models that can form a solid theoretical bridge between what is known about brain function and environmental influences upon choice. We further suggest that the complex and dynamic relationships between biology, behavior, and environment affecting choice at the individual level must inform aggregate models of consumer choice. Models using agent-based complex systems may further provide a principled way to relate individual and aggregate consumer choices to the aggregate choices made by businesses and social institutions. We coin the term “brain-to-society systems” choice model for this broad integrative approach.     

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Quantitative Marketing and Economics -