Dear colleagues,
You are cordially invited to submit papers to the Location Intelligence track at The Hawaii International Conference on System Sciences (HICSS-56, Jan 3-6, 2023, Maui, Hawaii).
Location Analytics has emerged as an important area of analytics concepts, tools and techniques with increasingly critical applications in the private, public, and non-profit sectors. The entire geospatial industry has grown to be a worldwide market of $430 billion, fueled by advances in GIS and spatial technology and a growing demand by organizations for use of location analytics across a spectrum of industries. The goal of this invited track is to highlight the use and potential of location analytics across the domains of system sciences that are represented at HICSS.
At HICSS-56 (2023), the Location Intelligence track is expanding to 4 mini-tracks (MTs) –
[A] Geospatial Big Data Analytics,
[B] GIS, Industry 4.0, and Sustainability,
[C] Geospatial Analytics Education, Training, and Workforce Development, and
[D] Location Analytics for System Sciences Research.
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[A] Geospatial Big Data Analytics
This mini-track provides a forum for geospatial big data research using cutting-edge scientific approaches to provide spatial insights to complex problems and systems in business, government, and society. The goal of this mini track is to highlight the use and potential of Geospatial Big Data in a range of areas, including but not limited to:
(A1) Commercial Services,
(A2) Health Care,
(A3) Public Sector,
(A4) Geospatial Big Data and Personal Location Data,
(A5) Geospatial Big Data and Location Intelligence.
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[B] GIS, Industry 4.0, and Sustainability
This mini-track provides a research forum aiming to discuss the varied facets of Geographic Information Systems (GIS) for Industry 4.0 and sustainability. The fourth Industrial Revolution is characterized by emerging technologies, such as AI, IoT, blockchain, and the Cloud. Location data and spatial features embedded in such emerging technologies often facilitate and accelerate technological advancements in connected vehicles, connected homes, smart cities, and Industrial IoT, which can improve economic conditions and reduce negative societal impacts. Topic areas include but are not limited to:
(B1) GIS and Industry 4.0,
(B2) GIS and environmental sustainability,
(B3) GIS and smart cities,
(B4) GIS, government, and NGOs,
(B5) Societal Issues with big spatial data,
(B6) Spatial aspects of the sharing economy,
(B7) Mobile location-based applications,
(B8) Cloud-based or web-based GIS concepts and applications,
(B9) Spatial crowdsourcing
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[C] Geospatial Education, Training, and Workforce Development
This mini-track aims to explore the teaching, training, and workforce development of geospatial analytics topics (e.g., geospatial methods, geospatial tools, geo-visualization, artificial intelligence, big data, geo-medicine, public policies, cybersecurity, governance, and geospatial analyses/tools during a pandemic situation, among others). There is a need to develop sustainable and innovative approaches for education, training, competencies, workforce development, and curricular innovation in geospatial analytics. Scholars interested in sharing applied, conceptual, theoretical, technological, methodological, and empirical contributions employing various systems sciences methods (e.g., empirical research, teaching cases, curriculum innovation, design-oriented research, case studies, and action research) are invited to submit. Rigorous research papers from disciplines where geospatial data are central (e.g., data science, engineering, computer sciences, environmental sciences, medicine and health sciences, management, marketing, economics, real estate, and supply chain) are also welcome.
(C1) Geospatial analytics education in the system sciences
(C2) Geospatial analytics training in the system sciences
(C3) Curricular innovation with GIS and location analytics
(C4) Pedagogical approaches of location analytics infusion in various disciples
(C5) Geospatial competencies for system sciences
(C6) Geospatial workforce development
(C7) Case studies in geospatial analytics education in academia, industry, and government
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[D] Location Analytics for System Sciences Research:
This mini-track seeks scholarly research papers that apply a variety of theories and empirical techniques, quantitative, and qualitative, to understand how location, geography, and related data are increasingly important to incorporate into the system sciences. There is a need to develop new theories and modify existing ones for the systems sciences that incorporate spatial data, locational intelligence, and geographical concepts. Current concepts of data science, big data, trust, and privacy need attention in addressing locational intelligence research questions. Topic areas include but are not limited to:
(D1) Spatial Business
(D2) Spatial Health and Healthcare (including COVID-19)
(D3) Sustainability and Climate Change
(D4) Industry Clusters and Community Development
(D5) Emergency Management and Public Safety
(D6) Location Analytics for Spatial Big Data
(D7) Spatial Theory, Concepts and Methods
(D8) Locational Data Privacy and Security
(D9) Novel Theories and Applications of Geo-AI/ML in Business and Society
(D10) Novel Theories and Applications of Geo-Blockchain in Business and Society
(D11) Advances in Indoor Positioning Systems, Location Tracking, and Wayfinding
(D12) Geospatial Analytics and Digital Twins
Paper submission deadline is JUNE 15, 2021.
Please see the HICSS website (https://hicss.hawaii.edu/) for more information on the Location Intelligence track (https://hicss.hawaii.edu/tracks-55/location-intelligence/) and submission guidelines.
A list of papers published in the Location Intelligence track can be found in HICSS proceedings at https://scholarspace.manoa.hawaii.edu/handle/10125/72248 (HICSS-54, 2021) and https://scholarspace.manoa.hawaii.edu/handle/10125/79321 (HICSS-55, 2022).
Feel free to email abstracts (by May 1, 2022) to the co-chairs of the various Mini-Tracks to express interest or if you have any questions.
Sincerely,
Dr. Joe Aversa, Assistant Professor, Ted Rogers School of Management, Ryerson University (Chair of Geospatial Big Data Analytics MT) E-mail: javersa@ryerson.ca
Dr. Namchul Shin, Professor and Department Chairperson, Seidenberg School of CSIS, Pace University, and Dr. Dan Farkas, Professor, Seidenberg School of CSIS, Pace University (Co-Chairs of GIS, Industry 4.0, and Sustainability MT) E-mails: nshin@pace.edu & dfarkas@pace.edu
Dr. Michael A. Erskine, Assistant Professor, Jones College of Business, Middle Tennessee State University; Dr. Asish Satpathy, Lecturer, W. P. Carey School of Business, Arizona State University; and, Dr. Andres Díaz López, Clinical Assistant Professor, W. P. Carey School of Business, Arizona State University (Co-chairs of Geospatial Education, Training, and Workforce Development MT). E-mails: michael.erskine@mtsu.edu; asish.satpathy@asu.edu; adiazlop@asu.edu.
Dr. James Pick, Professor, School of Business, University of Redlands, and Dr. Avijit Sarkar, Professor, School of Business, University of Redlands (Co-Chairs of Location Analytics for System Sciences Research MT) E-mails: James_Pick@redlands.edu & Avijit_Sarkar@redlands.edu
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Avijit Sarkar
Professor
University of Redlands
Redlands CA
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