Spatial Demand Models in an Intrabrand Context

Black, William C.; Ostlund, Lyman E.; Westbrook, Robert A.

doi:10.1177/002224298504900310

Cited by 14 publications

(1 citation statement)

References 19 publications

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“…Our work is also related to the role of distance in store choice, a topic that has long been studied in marketing. Constrained by the availability of data, early work in this stream focused on the economic “transportation cost” between a consumer's residence and the store (Black, Ostlund, and Westbrook 1985; Hortman et al 1990). In a seminal article, Bell, Ho, and Tang (1998) uncover the heterogeneity in how customers in a given market area trade off basket size with the distance from nearby stores.…”

Section: Related Literaturementioning

confidence: 99%

Analyzing Purchase Decisions Using Dynamic Location Data

Shoshani¹,

Zubcsek²,

Reichman³

2023

Journal of Interactive Marketing

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Retailers’ efforts to monetize consumer location data remain dominated by inefficient protocols (e.g., geofencing) that customize marketing interactions based solely on app users’ current location. Although extant trajectory mining techniques can remedy these shortcomings, they require high-frequency location data, which poses severe risks to consumers’ privacy. The authors present a novel method to extract marketing value from low-granularity urban mobility data and demonstrate its use in analyzing gas station choice to value customers. The data, also used to infer gas station visits, contain 1.06 million location records on nearly 27,000 devices observed near selected retailers including gas stations during a six-month period in Staten Island, New York. The authors pool consumers’ mobility trajectories from several days to dynamically calculate the distance of stores from consumers’ anticipated trajectories. They then supplement the data with station-level daily fuel prices and estimate a conditional logit model to assess how consumers trade off gas prices versus store distance. In addition to a generally high station loyalty, the authors find that consumers strongly prefer not to deviate far from their common trajectories for fueling trips. Applying their methods in a predictive context, the authors infer the value of newly acquired customers to the studied gas stations to be between $3.00 and $7.59.

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Section: Related Literaturementioning

confidence: 99%

Analyzing Purchase Decisions Using Dynamic Location Data

Shoshani¹,

Zubcsek²,

Reichman³

2023

Journal of Interactive Marketing

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Consumer decision making: A model of the effects of involvement, source credibility, and location on the size of the price difference required to induce consumers to change suppliers

Gotlieb

Schlacter

Louis

1992

Psychology and Marketing

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A model is presented for analyzing the effects of involvement, source credibility, and location on consumers' reactions to price changes. The model is based on a schema proposed by Jacoby and Olson (1977) to explain consumers' reactions to price. Evidence is presented that strongly indicates that involvement, source credibility, and location importantly affect the size of the price change required to motivate consumers to switch suppliers.

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Extraction and monitoring approach of dynamic urban commercial area using check-in data from Weibo

Bai

Wang

et al. 2019

Sustainable Cities and Society

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Spatial Demand Models in an Intrabrand Context

Cited by 14 publications

References 19 publications

Analyzing Purchase Decisions Using Dynamic Location Data

Analyzing Purchase Decisions Using Dynamic Location Data

Consumer decision making: A model of the effects of involvement, source credibility, and location on the size of the price difference required to induce consumers to change suppliers

Extraction and monitoring approach of dynamic urban commercial area using check-in data from Weibo

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