Location Intelligence Research in System Sciences

Permanent URI for this collectionhttps://hdl.handle.net/10125/107544

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Now showing 1 - 8 of 8

Optimal Partition of the Compulsory Education Period
(2024-01-03) Shimizu, Hitoshi; Nakamura, Tsubasa; Suwa, Hirohiko
In the United States, the K-12 school system is implemented in compulsory education, but the educational system varies from country to country and from era to era. In this paper, we propose a mathematical model for optimally partitioning the education period based on the facility location problem. In simulation experiments using a dataset from Nara City, the ancient capital of Japan, we show that a parameter set that increases the school commuting cost for younger students can successfully explain the current number of schools. Then, we show that under that parameter set, changing the school-age partition has the potential to reduce the total commuting cost and operation cost. We also find the property that when the commuting costs are uniform, the optimal solution is to integrate all education periods into a single school.
Empirical Assessment of the IEDS Framework to Design a Geospatial Information Exchange (IE) Platform Utilizing the GIS Technology
(2024-01-03) Bazarah, Ali Mohammed; Li, Yan
This study provides an empirical assessment of the Information Exchange Decision Support (IEDS) framework (Bazarah & Li, 2022) that guides the design of an Information Exchange (IE) system for multiple stakeholders to improve decision-making. The framework depicts how to design an IE platform for multiple stakeholders to improve their decision quality. A geospatial IE platform called SES-IE instantiates the IEDS framework to exchange information among multiple stakeholders in a real-world case scenario. The SES-IE platform was evaluated using a quantitative method approach to measure the usability, usefulness, and user satisfaction of the system. The results show that the IEDS framework is useful for identifying stakeholders, specifying information to be exchanged, and maintaining motivation factors necessary for IE. The successful instantiation of the IE platform shows that the IEDS framework is useful for building an effective IE platform in a multiple-stakeholder environment. In addition to offering prescriptive knowledge for building an effective IE, the study exemplifies the practicality of the IEDS framework in guiding the designers and developers of IE platforms.
Wireless Signal Prediction using Deep Learning Models for WiFi Positioning and Security Concerns
(2024-01-03) Konak, Abdullah; Delattre, Simon; Bartolacci, Michael
Confining wireless signals (WiFi) in specific areas of indoor spaces is an efficient way to protect these networks against unwanted access. Unfortunately, these same WiFi signals can be utilized to track the location of mobile handsets. There is an apparent tradeoff between securing the range of such signals and their use for indoor geolocation purposes. The modeling of wireless signal coverage for both security and geolocation purposes in areas where measurements are difficult to record can be a daunting task. We utilized a deep autoregressive model and a convolutional neural network model trained on a synthetic floor plan dataset to accurately extrapolate signal coverage across such spaces without using specific information about antennae placements or floor plan designs. Computational experiments showed that these data-driven approaches were able to fill the gaps in signal coverage maps accurately.
Location Analytics to Support Wildfire Response Prepositioning
(2024-01-03) Baik, Jiwon; Murray, Alan
This study addresses wildfire resource prepositioning in a region. Location analytics is utilized for prepositioning decision-making, relying on bi-objective spatial optimization to identify a strategic location for monitoring and response that considers two objectives: optimizing the visibility of potential ignition sites and optimizing response access. The study broadens the conventional definition of coverage by incorporating visibility from the preposition. Despite the inherent complexity of the problem, the proposed solution approach guarantees the identification of the complete set of Pareto optimal solutions in an efficient manner, supporting real-time decision-making. This research contributes significantly to spatial decision-making by integrating viewshed analysis into location analytics. Additionally, the approach has broad applications in various domains, including facility location planning, wireless network design, environmental monitoring, and urban planning. To facilitate decision-making, an interactive web application (www.wri-ucsb.com:8000) is developed, allowing the selection of specific regions of interest and model parameter refinement.
Leveraging Location Intelligence for Enhanced Damage Insurance Underwriting in the Context of Climate Change
(2024-01-03) Chamberland-Tremblay, Daniel; Caron, Claude; Morin, Jean-François
This study presents the contribution of location intelligence to property damage risk evaluation in the insurance industry through a decision support system prototype. We followed a standard design science research methodology for the design and development of the prototype and its evaluation by 11 industry experts. The results indicate that underwriters, the intended primary users of the prototype, had a positive perception of the prototype, while actuaries and managers expressed concerns about data and process integration to existing practices. Overall, the prototype highlights the potential of geospatial data, emphasizes the need for standardized risk evaluation processes for underwriters, and underscores the competitive advantage gained through access to quality data. These findings contribute to the understanding of how location intelligence can enhance risk assessment in the insurance industry.
Host Participation in Short-term Rental Markets: Geospatial and Socioeconomic Analysis of Airbnb in San Francisco
(2024-01-03) Sarkar, Avijit; Pick, James; Jabeen, Shaista
This paper examines spatial patterns and socioeconomic influences on host participation in San Francisco’s short-term home rental markets. Spatial distributions of Airbnb property densities are mapped in a Geographic Information System and clusters and outliers are identified. Unlike major Airbnb markets, Airbnb hotspots in San Francisco are not located in the city’s core but are predominant in northeastern neighborhoods of the city located close to points of interest (POIs) frequented by visitors, have high proportions of hotel and lodging employment, and lower median household incomes. Regression results reveal that the dominant determinants of Airbnb property density are professional, scientific, and technical services, and hotel/lodging employment, Asian population, and POIs within located within 20 minutes of walking time from the centroid of the city’s census tracts. Implications of these findings are discussed to understand supply-side motivations of Airbnb hosts for participating in the shared accommodation economy.
Revitalizing Graduate Business Curriculum with Location Analytics Incorporating DEI & ESG
(2024-01-03) Rivera, Julio; Satpathy, Asish; Wellman, Elizabeth; Burgos , Miriam
This article explores the revitalization of the graduate business curriculum by incorporating location analytics. Despite the benefits of integrating location analytics in business education, its adoption in business schools is currently limited. By embracing spatial thinking, business schools can better prepare students for informed decision-making in critical areas such as diversity, equity, and inclusion (DEI); environmental, social, and governance (ESG); consumer marketing insights; and supply chain issues, to name a few. The article highlights the importance of effective course design, clear objectives, a learner-centric pedagogical framework, and robust assessment strategies. Additionally, it emphasizes the need for faculty development and collaboration, discusses challenges and future directions, and concludes with a call to action for business schools to prioritize the integration of location analytics, DEI, and ESG in their curricula.
Introduction to the Minitrack on Location Intelligence Research in System Sciences
(2024-01-03) Pick, James; Sarkar, Avijit

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