相关论文: Validating Gravity-Based Market Share Models Using…

The Huff model has been widely used in location-based business analysis for delineating a trading area containing potential customers to a store. Calibrating the Huff model and its extensions requires empirical location visit data. Many…

Pervasiveness of tracking devices and enhanced availability of spatially located data has deepened interest in using them for various policy interventions, through computational data analysis tasks such as spatial hot spot detection. In…

Transaction data obtained by Personal Financial Management (PFM) services from financial institutes such as banks and credit card companies contain a description string from which the merchant, and an encoded store identifier may be parsed.…

The Gravity Model is the workhorse for empirical studies in International Economies for its empirical power and it is commonly used in explaining the trade flow between countries; it relies on a function that relates the trade with the…

The analysis and characterization of human mobility using population-level mobility models is important for numerous applications, ranging from the estimation of commuter flows in cities to modeling trade flows between countries. However,…

The necessity of data driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a Healthcare Provider Facility or a Hospital (from here on termed as Facility)…

Gravity is one of the most prominent models used across various social areas, including economics, demography, mobility, politics, and other systems where spatial interactions are relevant. The model represents a flexible approach that…

The problem of identifying the optimal location for a new retail store has been the focus of past research, especially in the field of land economy, due to its importance in the success of a business. Traditional approaches to the problem…

Accurate gravity field models are essential for safe proximity operations around small bodies. State-of-the-art techniques use spherical harmonics or high-fidelity polyhedron shape models. Unfortunately, these techniques can become…

Accurately modeling local surface properties of objects is crucial to many robotic applications, from grasping to material recognition. Surface properties like friction are however difficult to estimate, as visual observation of the object…

"Data" is becoming an indispensable production factor, just like land, infrastructure, labor or capital. As part of this, a myriad of applications in different sectors require huge amounts of information to feed models and algorithms…

What people buy is an important aspect or view of lifestyles. Studying people's shopping patterns in different urban regions can not only provide valuable information for various commercial opportunities, but also enable a better…

This study identifies the limitations and underlying characteristics of urban mobility networks that influence the performance of the gravity model. The gravity model is a widely-used approach for estimating and predicting population flows…

This paper continues to develop and explore the impact of multipurpose trips on retail location. We develop the model of locating multiple competing facilities of a chain where several competing facilities exist in the area. There may be…

Fairness in machine learning has attracted increasing attention in recent years. The fairness methods improving algorithmic fairness for in-distribution data may not perform well under distribution shifts. In this paper, we first…

The hospitality industry is one of the data-rich industries that receives huge Volumes of data streaming at high Velocity with considerably Variety, Veracity, and Variability. These properties make the data analysis in the hospitality…

Newly available data on the spatial distribution of retail activities in cities makes it possible to build models formalized at the level of the single retailer. Current models tackle consumer location choices at an aggregate level and the…

A geo-marketplace allows users to be paid for their location data. Users concerned about privacy may want to charge more for data that pinpoints their location accurately, but may charge less for data that is more vague. A buyer would…

Market share and quality, or customer satisfaction, go together. Yet inferring one from the other appears difficult. Indeed, such an inference would need detailed information about customer behavior, and might be clouded by modes of…

Machine learning models play a key role for service providers looking to gain market share in consumer markets. However, traditional learning approaches do not take into account the existence of additional providers, who compete with each…