เปรียบเทียบวิธี

	โมเดล Huff	แบบจำลองการแผ่รังสีของการเคลื่อนที่และการย้ายถิ่น	แบบจำลองอันตรกิริยาเชิงพื้นที่ (แบบจำลองแรงโน้มถ่วง)
สาขาวิชา	การวิเคราะห์เชิงพื้นที่	การวิเคราะห์เชิงพื้นที่	การวิเคราะห์เชิงพื้นที่
ตระกูล	Regression model	Regression model	Regression model
ปีกำเนิด	1964	2012	1971
ผู้ริเริ่ม	David Huff	Filippo Simini et al.	Alan Wilson (entropy-maximizing family)
ประเภท	Probabilistic spatial interaction model	Parameter-free spatial interaction model	Model of flows between spatial origins and destinations
แหล่งต้นตำรับ	Huff, D. L. (1964). Defining and estimating a trading area. Journal of Marketing, 28(3), 34–38.	Simini, F., González, M. C., Maritan, A., & Barabási, A.-L. (2012). A universal model for mobility and migration patterns. Nature, 484, 96–100.	Wilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32.
ชื่อเรียกอื่น	Huff Gravity Model, Probabilistic Retail Gravity Model, Huff Trade Area Model, Huff Çekim Modeli	Radiation Law of Human Mobility, Parameter-free Mobility Model, Simini Radiation Model, Radyasyon Modeli	gravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
ที่เกี่ยวข้อง	3	3	4
สรุป	Proposed by David Huff in 1964, the Huff Model is a probabilistic spatial interaction model that estimates the likelihood that consumers located in a given geographic zone will choose to shop at a particular retail outlet. It extends deterministic gravity models by assigning each consumer zone a probability of patronage across all competing stores, weighting store attractiveness (typically measured by floor area) against the friction of travel time or distance. The model is widely used in retail site selection, trade area delineation, and market share forecasting.	The Radiation Model, introduced by Simini et al. in 2012, is a parameter-free model for predicting human mobility and migration flows between geographic locations. Drawing an analogy from radiation physics, it predicts trip volumes based solely on population sizes at origin and destination, and the intervening population within the circle connecting them. It has been widely applied to commuting flows, migration, and epidemic spreading.	Spatial interaction models predict the volume of flows — migrants, commuters, shoppers, trade, trips — between origins and destinations as a function of the size of each place and the distance or cost separating them. By analogy to Newton's gravity, interaction rises with the 'mass' of origin and destination and falls with separation, and Wilson's 1971 entropy-maximizing family put these models on a rigorous footing for transport, migration, and retail analysis.