Maximum Likelihood Estimation of Central-City Food Trading Areas

Haines, George H.; Simon, Leonard S.; Alexis, Marcus

doi:10.1177/002224377200900206

Cited by 27 publications

(6 citation statements)

References 4 publications

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“…In a retail context, locations can be selected to maximize the market share taken from competitors and to minimize self-cannibalization. The model is a special case of the Luce choice model (Haines et al, 1972). A large number of extensions have been developed for the Huff gravity model, include those that incorporate store image (Stanley and Sewall, 1976), elasticities of demand (Griffith, 1982), and social media location data (Lovelace et al, 2016).…”

Section: Geographic and Spatial Visualizationmentioning

confidence: 99%

Marketing analytics: Methods, practice, implementation, and links to other fields

Ghose

2019

Expert Systems with Applications

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Marketing analytics is a diverse field, with both academic researchers and practitioners coming from a range of backgrounds including marketing, expert systems, statistics, and operations research. This paper provides an integrative review at the boundary of these areas. The aim is to give researchers in the intelligent and expert systems community the opportunity to gain a broad view of the marketing analytics area and provide a starting point for future interdisciplinary collaboration. The topics of visualization, segmentation, and class prediction are featured. Links between the disciplines are emphasized. For each of these topics, a historical overview is given, starting with initial work in the 1960s and carrying through to the present day. Recent innovations for modern, large, and complex "big data" sets are described. Practical implementation advice is given, along with a directory of open source R routines for implementing marketing analytics techniques.

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Section: Geographic and Spatial Visualizationmentioning

confidence: 99%

Marketing analytics: Methods, practice, implementation, and links to other fields

Ghose

2019

Expert Systems with Applications

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“…Research on spatial behavior based on gravity models has provided initial insights into this phenomenon by predicting a negative relationship between households' store patronage and distance to stores (Haines et al. 1972, Huff 1964).…”

Section: Theory Development and Hypothesesmentioning

confidence: 99%

“…In turn, this variation may influence households' share of shopping expenditures at WC stores in relation to their share of travel costs allocated to the stores to make those expenditures. Research on spatial behavior based on gravity models has provided initial insights into this phenomenon by predicting a negative relationship between households' store patronage and distance to stores (Haines et al 1972, Huff 1964.…”

Section: Theory Development and Hypothesesmentioning

confidence: 99%

Shopping Activity at Warehouse Club Stores and Its Competitive and Network Density Implications

Lim

Rabinovich

Park

et al. 2021

Production and Operations Management

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Warehouse club (WC) retailers have typically expanded to new markets using stand‐alone stores, rather than pursuing dense store networks as other (non‐WC) retailers have in the past. While this strategy generates operating efficiencies, it also imposes high travel costs on households to shop, which calls into question WC stores' resilience to spatial competition from stores operating other formats. We examine this phenomenon by using data on households' shopping activity across markets served by Costco Wholesale stores. Specifically, we evaluate these stores' resilience to spatial competition by estimating the share of households' expenditures relative to travel costs to shop at the stores and comparing this estimate with that for non‐WC stores. Controlling for households' travel costs across Costco and non‐WC stores, we find that households' share of expenditures at Costco stores exceeds the share at non‐WC stores by 61%. This suggests that Costco stores have an advantage over non‐WC stores when serving market areas with sparse store networks. Nevertheless, we also find that this advantage diminishes with the distance between Costco stores and households and that there is a finite distance beyond which this advantage disappears. We show that this distance (approximately 21 miles) is an important reference point for the evaluation of spatial competition between Costco stores and other stores and the examination of demand saturation at Costco stores.

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“…In this study, we focus on the Huff gravity model, which is widely used in retailing practice (Hernandez and Bennison, 2000) because of (1) its ease of use (Park et al, 2006;Lv et al, 2008;Ahn et al, 2009) and (2) the accuracy of its predictions (Drezner and Dressner, 2002), even though the two-variable specification is too parsimonious for policy purposes (Gautschi, 1981). Several empirical studies (Huff and Blue, 1966;Haines et al, 1972) support the usefulness of the Huff model in predicting the market share of shopping centres (Craig et al, 1984). In this model, the probability that customer i shops at location j depends upon two factors: the size of the store and the time it takes to travel to the store (Levy and Weitz, 2007).…”

Section: Previous Study and Proposed Modelmentioning

confidence: 99%

“…Travel time, or distance, is more important for convenience goods than shopping goods because consumers are less willing to travel a longer distance to buy a bottle of milk than a pair of new shoes. The calculation of λ has been discussed in previous studies (Huff and Blue, 1966;Haines et al, 1972). However, Japan and Korea have been using a fixed value of 2 for λ Table 2.…”

Section: Previous Study and Proposed Modelmentioning

confidence: 99%

Retail sales forecast analysis of general hospitals in Daejeon, Korea, using the Huff model

Youn¹

2012

Afr. J. Bus. Manage.

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This paper seeks to develop a sales estimation model to forecast the demand for general hospitals in small and medium-sized cities. We focus on deriving the parameter λ in the Huff model, which is used in sales forecasting. When opening new hospitals in cities, actual sales can be calculated on the basis of a demand forecast. Currently, many researchers in Korea use the Huff model to estimate the sales of retail stores, but we employ it to analyze the impact of such factors as hospital size and the proximity of hospitals to consumers. We look at in what ways and to what extent these factors affect the λ calculation. From past experiments, we know that the parameter varies according to city size. By making comparisons with existing studies on large cities, we verify that consumers in small and medium-sized cities are less sensitive to travel time. Meanwhile, we determine λ to be 0.1 in the case of such cities, implying that hospital size has a greater influence on consumers than travel time does. According to existing studies, this figure is 0.38 for small and medium-sized cities and more than 1 for large cities.

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Maximum Likelihood Estimation of Central-City Food Trading Areas

Cited by 27 publications

References 4 publications

Marketing analytics: Methods, practice, implementation, and links to other fields

Marketing analytics: Methods, practice, implementation, and links to other fields

Shopping Activity at Warehouse Club Stores and Its Competitive and Network Density Implications

Retail sales forecast analysis of general hospitals in Daejeon, Korea, using the Huff model

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