Location Analytics in Systems Sciences Research and Education

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Now showing 1 - 8 of 8
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    Introduction to the Minitrack on Location Analytics in Systems Sciences Research and Education
    ( 2023-01-03) Sarkar, Avijit ; Diaz Lopez, Andres ; Satpathy, Asish ; Pick, James ; Erskine, Michael
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    Lost in the City? - A Scoping Review of 5G Enabled Location-Based Urban Scenarios
    ( 2023-01-03) Bäßmann, Felix ; Werth, Oliver ; Düffel, Torben J. ; Breitner, Michael H.
    5G mobile network technologies and scenarios with the associated innovations receive growing interest among academics and practitioners. Current literature on 5G technologies discusses several scenarios and specific chances and challenges. However, 5G literature is fragmented and not systematically reviewed. We conducted a scoping review on 5G applications in urban scenarios. We reviewed 1,394 papers and identified 20 studies about urban logistics and emergency indoor localization. Our review accumulates current academic knowledge on these scenarios and identifies six further research directions in four research fields. It reveals several further research opportunities, e.g., regarding trust and privacy concerns. We review and discuss 5G literature for academics and practitioners, contribute towards more tailored 5G research and reflect on cost- efficient 5G applications in urban scenarios.
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    Location-Based Service and Location-Contextualizing Service: Conceptualizing the Co-creation of Value with Location Information
    ( 2023-01-03) Zur Heiden, Philipp ; Priefer, Jennifer ; Beverungen, Daniel
    Location-Based Service (LBS) is an established concept and enables providers and customers to co-create value-in-use, building on location information on humans or mobile objects. LBS, however, is not the only way to co-create value by using location information, as LBS does not target immovable objects, such as infrastructure. Informed by a literature review, we set out to conceptualize Location-Contextualizing Service (LCS) as a class of service complementing LBS. LCS focuses on improving existing service, based on enabling users with static positions to contextualize and analyze data on immovable objects. We describe the conceptual properties of LCS vis- ́a-vis LBS and outline why we see Geographic Information System (GIS) as a crucial class of systems to enable LCS. We discuss why LCS highlights new aspects and shifts research priorities that constitute the LBS and GIS fields today.
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    Spatial and Socioeconomic Analysis of Purposeful Mobile Internet Use in US States
    ( 2023-01-03) Sarkar, Avijit ; Pick, James ; Bhat, Geeta
    The digital divide in the United States has received renewed attention during the COVID-19 pandemic. As achievement of digital equity remains a high priority, this study examines spatial patterns and socioeconomic determinants of the purposeful use of mobile internet for personal and business needs in US states. Agglomerations of mobile internet use are identified using K-means clustering and the extent of agglomeration is measured using spatial autocorrelation analysis. Regression analysis reveals that mobile internet use is associated with employment in management, business, science, and arts occupations, affordability, age structure, and the extent of freedom in US states. Spatial randomness of regression residuals shows the effectiveness of the conceptual model to account for spatial bias. Implications of these findings are discussed.
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    HUK-COBURG: The Implementation of an AI-Enabled Behavioural Insurance Business Model using Geo-Spatial Data
    ( 2023-01-03) Holland, Christopher ; John, Daniel
    Automotive insurance is undergoing digital transformation that exploits new forms of big data and Artificial Intelligence (AI) systems. Geo-spatial data from GPS and telematics systems enables innovative risk modelling to evaluate driver behaviour and leads to the creation of new insurance services and novel insurance business models. A research framework is proposed to analyse AI-enabled business models and applied to a detailed case analysis of behavioural insurance in HUK-COBURG. The results illustrate the application of geo-spatial data in an insurance context and demonstrate the utility of the research framework to analyse new AI-enabled business models. The analysis identifies important implementation issues and shows that the strategic logic, regulatory and ethical context are important elements of business models. The empirical analysis reveals the strategic properties and effects of the data flywheel concept, which has general applicability. The theory framework and empirical results have important implications for other markets and theoretical contexts.
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    Analyzing and Optimizing AED Placement Locations in Big Cites—A Geographical Information System Analysis
    ( 2023-01-03) Shi, Yuxuan ; Wang, Tianmei
    Out-of-Hospital Cardiac Arrest (OHCA) has been identified as a significant public health issue in China. Numerous studies have demonstrated that using automated external defibrillators (AEDs) can significantly improve the survival rate of OHCA patients, but their low utilization rate is partly due to the accessibility of AED deployment sites. This study collects the location information of AED devices in three representative cities in China: Beijing, Shanghai, and Shenzhen and then combines the kilometer population grid data (2021) with the AED geographic location data for visualization and data analysis through QGIS and Kepler.GL. Our model considers population distribution, subway, and road traffic factors and proposes a new method for AED index measurement. Through empirical analysis, we discovered that the existing AED distribution has an issue with unequal resource allocation. Thus, we have proposed specific suggestions on quantity and specific zones for AED deployment. Furthermore, this study proposes three specific suggestions for the problems currently in developing AEDs in China.
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    School Families: A New Formulation of School District Planning Problem
    ( 2023-01-03) Shimizu, Hitoshi ; Suwa, Hirohiko ; Iwata, Tomoharu ; Fujino, Akinori ; Sawada, Hiroshi ; Yasumoto, Keiichi
    This paper makes a plan to introduce school families. School families refer to a hierarchical system where the junior high school district encompasses the elementary school district. School families have the advantage of promoting efficient cooperation between elementary and junior high schools. Therefore, we formulated a new school district planning problem to introduce school families and created an optimal plan under changing population situations. Our formulation achieves school families by exploiting the continuity constraints of the school district. We also compare two different methods of reorganizing school districts in the simulation experiments: changing school districts by transferring current students in a given year (school-year method) and switching new students' schools over a multi-year period (birth-year method). We examined the cost and computation time of plans obtained with both methods and showed that the method combining the two provides the most significant cost savings.
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    MACH-T: A Behavior-based Mobile Node Trust Evaluation Algorithm
    ( 2023-01-03) Thurston, Karen ; Conte De Leon, Daniel
    Resiliency and availability in community and public service networks may be economically enhanced by building new ad hoc networks of private mobile devices and joining these to public service networks at specific trusted points. Resiliency in such ad hoc networks relies on the afforded increased availability but also on security which is in turn built on trust. In this article, we describe MACH-T, a novel behavior-based algorithm for mobile ad hoc network node trust building. MACH-T uses historical mobile node geographic location traces to incrementally calculate node trust values based on the concepts of node capability, commitment, and consistency. We describe experiments and results from evaluating MACH-T using real GPS traces from the Microsoft Research Geolife and University of Rome Tor Vergata Roma Taxi datasets. Our results show that MACH-T builds a reliable trust value and corresponding confidence value based on learned patterns of time spent in qualifying geographic locations.