arXiv subjects

Shawn Berry

Publications and source records attributed to Shawn Berry.

13 recordsLinked to original sources

arXiv2026

Housing Price Appreciation, Housing Affordability, and the Spatial Restructuring of Toronto Commuting

This study investigates the spatial relationships among housing-market appreciation, housing affordability, and automobile commuting to Toronto across 23 census metropolitan areas and municipalities in southern Ontario from 2016 to 2021. Utilizing Statistics Canada Census data, the analysis employed linear and quadratic ordinary least-squares regression, Global and Local Moran's I, and residual spatial diagnostics to assess geographic patterns in average dwelling values, owner shelter-cost burden, and lone-driver commuting. The study found that average dwelling values increased significantly throughout the region, maintaining a strong nonlinear relationship with distance from Toronto, which indicates a persistent metropolitan accessibility gradient. Commuter volumes also demonstrated pronounced nonlinear distance gradients; however, housing appreciation was not significantly correlated with percentage changes in commuting ($R^2$ = .045, p = .331), suggesting that the expansion of the housing market did not result in proportional growth in Toronto-bound automobile travel. The shelter-cost burden exhibited weaker distance relationships and greater residual spatial dependence, indicating localized affordability influences not fully explained by distance or dwelling values. Overall, the findings suggest an increasingly extensive regional housing market with spatially heterogeneous affordability and commuting outcomes, highlighting the importance of integrating housing, transportation, and regional planning.

econ.GN↗

arXiv2026

A Cost-and-Place-Utility Model of the Move-versus-Commute Decision

Deciding where to live involves a complex balance between commuting and moving, as households must weigh housing affordability, transportation expenses, access to workplaces, and social ties. Traditional urban economic theories focus on the balance between housing expenses and commuting costs, while modern studies also consider housing affordability, transportation access, and utility maximization. However, few studies have combined these elements into a clear mathematical model that can be used for both policy analysis and household decision-making. This paper introduces an algebraic model for deciding whether to commute or move, expanding on traditional residential location theories by including direct housing and commuting expenses, income-related affordability limits, indirect social and service access costs, and location-based utility within a single utility-maximization framework. The model uses the common 30% housing affordability rule as a constraint, acknowledging that residential choices are also shaped by social networks, access to institutions, neighborhood ties, and quality-of-life factors. The decision rule derived from the model integrates direct financial costs with weighted social benefits and indirect access costs to assess when moving offers more overall utility than staying put and commuting. Unlike complex discrete-choice, nested-logit, or agent-based models, this framework offers a mathematically clear, understandable, and flexible decision model that can easily be expanded to include more household characteristics, transportation options, or policy factors. The model advances urban economics, migration studies, and housing affordability research by providing a practical analytical tool for assessing residential mobility decisions within financial and behavioral limits.

econ.TH↗

arXiv2025

Antecedents of Consumer Regret Frequency: The Roles of Decision Agency, Status Signaling, and Online Shopping Preference

Consumer regret is a widespread post-purchase emotion that significantly impacts satisfaction, product returns, complaint behavior, and customer loyalty. Despite its prevalence, there is a limited understanding of why certain consumers experience regret more frequently as a chronic aspect of their engagement in the marketplace. This study explores the antecedents of consumer regret frequency by integrating decision agency, status signaling motivations, and online shopping preferences into a cohesive framework. By analyzing survey data (n=338), we assess whether consumers' perceived agency and decision-making orientation correlate with the frequency of regret, and whether tendencies towards status-related consumption and preferences for online shopping environments exacerbate regret through mechanisms such as increased social comparison, expanded choice sets, and continuous exposure to alternative offers. The findings reveal that regret frequency is significantly linked to individual differences in decision-related orientations and status signaling, with a preference for online shopping further contributing to regret-prone consumption behaviors. These results extend the scope of regret and cognitive dissonance research beyond isolated decision episodes by emphasizing regret frequency as a persistent consumer outcome. From a managerial standpoint, the findings suggest that retailers can alleviate regret-driven dissatisfaction by enhancing decision support, minimizing choice overload, and developing post-purchase reassurance strategies tailored to segments prone to regret..

econ.GN↗

arXiv2025

Traffic jams and driver behavior archetypes

Traffic congestion represents a complex urban phenomenon that has been the subject of extensive research employing various modeling techniques grounded in the principles of physics and molecular theory. Although factors such as road design, accidents, weather conditions, and construction activities contribute to traffic congestion, driver behavior and decision-making are primary determinants of traffic flow efficiency. This study introduces a driver behavior archetype model that quantifies the relationship between individual driver behavior and system-level traffic outcomes through game-theoretic modeling and simulation (N = 500,000) of a three-lane roadway. Mann-Whitney U tests revealed statistically significant differences across all utility measures (p < .001, d > 2.0). In homogeneous populations, responsible drivers achieved substantially higher expected utility (M = -0.090) than irresponsible drivers (M = -1.470). However, in mixed environments (50/50), irresponsible drivers paradoxically outperformed responsible drivers (M = 0.128 vs. M = -0.127), illustrating a social dilemma wherein defection exploits cooperation. Pairwise comparisons across the six driver archetypes indicated that all irresponsible types achieved equivalent utilities while consistently surpassing responsible drivers. Lane-specific analyses revealed differential capacity patterns, with lane 1 exhibiting a more pronounced cumulative utility decline. These findings offer a robust framework for traffic management interventions, congestion prediction, and policy design that aligns individual incentives with collective efficiency. Directions for future research were also proposed.

econ.TH↗

arXiv2025

An experiment in price perception error

The process of consumer decision-making is multidimensional, and price perception is a very important but still not well-understood dimension for both marketers and consumers. Although heuristics or mental shortcuts are seen as biased and can cause decision errors, consumers tend to use price knowledge heuristics for purchase decisions, sometimes relying on old information. This study examined the effects of individual attitudinal and demographic factors on the ability of 351 respondents to correctly guess the prices of 13 products and services using ANOVA and the development of a seven-factor price perception model using latent variable analysis. While most respondents preferred to either research prices first or compare prices to a similar product, they either systematically underestimated or overestimated the prices of the products. In the ANOVA, brand loyalty, importance of substitute products and knockoff products, how financially well-off the respondent household was growing up, product quality importance, haggling tendency, and level of income were statistically significant predictors of price perception error. Latent variable analysis revealed that demographics, decision making, and price sensitivity factors had the greatest influence on price perception error. Level of education and income, frequency of regret, coupon importance, and how respondents chose to save or spend money were significant latent variables.

econ.GN↗

arXiv2025

Trust of Strangers: a framework for analysis

Trust among people is essential to ensure collaboration, social network building, transactions, and the development and engagement of new audiences for brand promotion or social causes. In Berry (2024), the trust attitudes of respondents toward strangers on the street, other groups of people, and information sources were measured. This study evaluates the trust of strangers using a 5-factor structural equation model. The analysis yielded a robust model with four of five factors and all variables being statistically significant, with social trust and institutional trust yielding the greatest positive effect on trust of strangers on the street. While demographic characteristics had a small positive effect, the trust of friends and family had a mild negative effect on the trust of strangers on the street. Trust of information sources was not statistically significant and had a negligible positive effect on the trust of strangers. The results also indicate that almost 48% of respondents distrust strangers on the street, implying that trust is not automatically endowed. Directions for future research and implications for business and social causes are discussed.

econ.GN↗

arXiv2024

Positive and negative word of mouth in the United States

Word of mouth is a process by which consumers transmit positive or negative sentiment to other consumers about a business. While this process has long been recognized as a type of promotion for businesses, the value of word of mouth is questionable. This study will examine the various correlates of word of mouth to demographic variables, including the role of the trust of business owners. Education level, region of residence, and income level were found to be significant predictors of positive word of mouth. Although the results generally suggest that the majority of respondents do not engage in word of mouth, there are valuable insights to be learned.

econ.EM↗

arXiv2024

Distrust of social media influencers in America

The popularity of social media influencers (SMI) as a means for businesses and causes to engage with the public and develop followers is undeniable. However, the use of SMI have been scrutinized due to various scandals that reflect poorly on brands and firms. Consequently, the distrust of SMI can create the potential for damage to a brand if audiences are not receptive to communications and messaging. This study (n=351) shares insights and findings of the apparent distrust of SMI that were discovered during the data analysis phase of my dissertation (Berry, 2024a). The study examines levels of trust and distrust toward SMI in the United States according to various demographic characteristics of respondents, specifically, age, gender, income level, education level, and region of the United States. Chi square analysis of the variables and a predictive model of trust of SMI are presented. Finally, recommendations and suggestions for future research are discussed.

econ.GN↗

arXiv2024

Consumer lying in online reviews: recent evidence

The persistence of lying by some consumers in their online posts of experiences with businesses is problematic, and taints the global pool of information that is used for decision making by people that assume they are true accounts of experiences. This study is based on data from my dissertation about fake online Google reviews of restaurants (Berry, 2024), and leverages an instrument that quantifies the trust of people. The findings are based on a sample of n=351, and provide a general proxy for lying in online reviews, and sketch out the characteristics of a typical person that has the propensity to be untruthful. A predictive model of posting untrue online reviews is constructed. The findings have wider implications for the study and monitoring of deceptive behavior, including the propagation of misinformation, and a means of quantifying the potential for antisocial behavior as measured by the trust of people instrument in Berry (2024). Directions for future research and limitations are also discussed.

econ.GN↗

arXiv2024

Prediction of retail chain failure: examples of recent U.S. retail failures

Over the last several years, several well-established and prominent brick-and-mortar retail chains have ceased operations, raising concerns for something that some have referred to as a retail apocalypse. While the demise of brick-and-mortar is far from certain, scholars have attempted to model the likelihood that a retailer is about to fail using different approaches. This paper examines the failures of Bed Bath and Beyond, J.C. Penney, Rite Aid, and Sears Holdings in the United States between 2013 and 2022. A model of retail failure is presented that considers internal and external firm factors using both annual report and macroeconomic data. The findings suggest that certain revenue-based financial ratios and the annual average U.S. inflation rates are statistically significant predictors of failure. Furthermore, the failure model demonstrated that it can provide a nontrivial early warning signal at least the year before failure. The paper concludes with a discussion and directions for future research.

econ.GN↗

arXiv2024

Is the price right? Reconceptualizing price and income elasticity to anticipate price perception issues

Price perception by consumers represents a challenge to the ability of a business to correctly and profitably price and sell their products or services in a given market and any new target market. Complicating the perception of prices is the dynamics of price and income elasticity, both of which are key for estimating demand. This article proposes a novel and elegant identity that conceptualizes elasticity as a means of quantifying the potential for price perception problems in a market. Elasticity studies from 1990 to 2023 (n=30) were sampled to evaluate the relationship between price and income elasticity for various consumer commodities using the identity. The results suggest that, given known price and income elasticity values, a business can anticipate pricing perception problems in advance and address the potential for damaging distortion of their value proposition. Further, the business can use this insight to correctly choose a strategic pricing approach.

econ.GN↗

arXiv2024

Fake Google restaurant reviews and the implications for consumers and restaurants

The use of online reviews to aid with purchase decisions is popular among consumers as it is a simple heuristic tool based on the reported experiences of other consumers. However, not all online reviews are written by real consumers or reflect actual experiences, and present implications for consumers and businesses. This study examines the effects of fake online reviews written by artificial intelligence (AI) on consumer decision making. Respondents were surveyed about their attitudes and habits concerning online reviews using an online questionnaire (n=351), and participated in a restaurant choice experiment using varying proportions of fake and real reviews. While the findings confirm prior studies, new insights are gained about the confusion for consumers and consequences for businesses when reviews written by AI are believed rather than real reviews. The study presents a fake review detection model using logistic regression modeling to score and flag reviews as a solution.

econ.GN↗

arXiv2024

An income-based approach to modeling commuting distance in the Toronto area

The purpose of this article is to propose a novel model of the effects of changes in shelter and driving costs on car commuting distances in the overheated Toronto housing market from 2011 to 2016. The model borrows from theoretical concepts of microeconomics and urban geography to examine the Toronto housing market. Using 2011 and 2016 Census data for census metropolitan areas (CMAs) and census agglomerations (CAs) in Southern Ontario and computed driving costs, the model of car commuting distance is based on variables of allocation of monthly household income to monthly shelter costs and driving costs as a function of the car driving distance to Toronto. Using this model, we can predict the effect on car commuting distance due to changes in any of the variables. The model also offers an explanation for communities of Toronto car commuters beyond a driving radius that we might expect for daily commuting. The model confirms that increases in shelter costs in the Toronto housing market from 2011 to 2016 have forced the boundaries of feasible housing locations outward, and forced households to move farther away, thus increasing car commuting distance.

econ.GN↗