@inbook{supak_brothers_ghahramani_van berkel_2016, title={Geospatial Analytics for Park & Protected Land Visitor Reservation Data}, ISBN={9783319442624 9783319442631}, ISSN={2366-2611 2366-262X}, url={http://dx.doi.org/10.1007/978-3-319-44263-1_6}, DOI={10.1007/978-3-319-44263-1_6}, abstractNote={Reservation databases utilized by parks and protected lands (PPLs) are a source of empirical data that holds a wealth of spatiotemporal information about both destination usage (from the supply side) and visitor characteristics (the demand population). Unfortunately, PPL reservation databases are rarely explored with these goals in mind. Geovisualizations of reservation data can be used to identify longitudinal patterns, trends and relationships that can help PPL managers generate knowledge useful in decision support. To demonstrate the knowledge that can be gained through geospatial analytics of PPL reservation data, 12.5 million reservation records from the recreation.gov database between January 1, 2007 and December 30, 2015 are examined. The database includes 3272 distinct destinations that provided camping, permitting or ticketing on U.S. Federal PPLs. This chapter discusses both the value of, and the methodology for, inductively exploring spatiotemporal PPL reservation data through geovisualization. Efforts such as those described in this chapter can provide decision support to managers of Federal, State and County agencies tasked with tourism and resource management.}, booktitle={Analytics in Smart Tourism Design}, publisher={Springer International Publishing}, author={Supak, Stacy and Brothers, Gene and Ghahramani, Ladan and Van Berkel, Derek}, year={2016}, month={Oct}, pages={81–109} }
 @article{supak_brothers_bohnenstiehl_devine_2015, title={Geospatial analytics for federally managed tourism destinations and their demand markets}, volume={4}, ISSN={2212-571X}, url={http://dx.doi.org/10.1016/J.JDMM.2015.05.002}, DOI={10.1016/J.JDMM.2015.05.002}, abstractNote={Understanding geospatial demand for destinations can improve management decisions affecting destination planning, marketing, natural preservation, and resident as well as visitor experiences. Visualization and analysis of demand markets are significantly enhanced by the capabilities of Geographic Information System (GIS) technology and help to support management objectives. This study implements traditional desktop GIS as well as a free, web-delivered decision-support tool for tourism planning and marketing to assess ~7.5 million overnight accommodation reservations made for federal recreational facilities between 1999 and 2007. Visitor origin frequency and median travel distance for overnight accommodations are summarized by visitor zip code and by facility. National results indicate: (1) facilities in the west, the Great Lakes and the southern Appalachians regions draw overnight visitors from the greatest median distances; (2) residents in the Northeast have the lowest per-capita utilization; (3) residents within the south-central Midwest and central-west Southern States have the highest percapita utilization and tend strongly toward local overnight reservations. Three selected national park regions are used to illustrate destinations characterized by highly localized utilization (Hot Springs National Park, AR), both local and regional utilization (Yosemite National Park, CA) and regionally to nationally dispersed utilization with few local residents reserving overnight accommodations (Canyonlands National Park, UT). Market profiling derived from local, regional and national customer origin markets can help any tourism destination, including national parks and their gateway communities, make smarter management and marketing decisions.}, number={3}, journal={Journal of Destination Marketing & Management}, publisher={Elsevier BV}, author={Supak, Stacy and Brothers, Gene and Bohnenstiehl, DelWayne and Devine, Hugh}, year={2015}, month={Oct}, pages={173–186} }
 @article{supak_brothers_bohnenstiehl_2015, title={Geospatial analytics for federally managed tourism destinations and their demand markets}, volume={4}, number={3}, journal={Journal of Destination Marketing & Management}, author={Supak, S. and Brothers, G. and Bohnenstiehl, D.}, year={2015}, pages={173–176} }
 @article{buckley_singh_brothers_mcarthur_2015, title={What is wrong with the concept of carrying capacity?}, volume={70}, journal={Challenges in tourism research}, author={Buckley, R. and Singh, S. and Brothers, G. and McArthur, S.}, year={2015}, pages={267–308} }
 @article{supak_devine_brothers_rozier rich_shen_2014, title={An Open Source Web-Mapping System for Tourism Planning and Marketing}, volume={31}, ISSN={1054-8408 1540-7306}, url={http://dx.doi.org/10.1080/10548408.2014.890153}, DOI={10.1080/10548408.2014.890153}, abstractNote={ABSTRACT Core retail management functions include defining market areas and profiling customers. For tourism enterprises, market areas are geographically dispersed with many customers residing beyond the immediate area surrounding the attraction. Visualization and analysis of these distributed market areas are significantly enhanced by the capabilities of Geographic Information System (GIS) technology and help to support management objectives. Unfortunately, many businesses are unable to utilize GIS due to its complexity and expense. This study develops a decision support tool for tourism planning and marketing that is customized and easy to use, employs open source software to reduce expense, and allows for broad accessibility via web delivery. Users can easily visualize and examine the spatial distribution of their own United States (US) client origins and visitation patterns along with relevant tourism-specific and general demographic information. This functionality can be beneficial in developing or augmenting business plans or marketing strategies, and for informing tourism theory.}, number={7}, journal={Journal of Travel & Tourism Marketing}, publisher={Informa UK Limited}, author={Supak, Stacy Kathleen and Devine, Hugh Alexander and Brothers, Gene Leroy and Rozier Rich, Samantha and Shen, Wenbo}, year={2014}, month={Oct}, pages={835–853} }