Abstract
Spatial information is becoming crucial for strategic decision making, but accessing and understanding this information is not easy. Dedicated tools can support the decision process in many ways, such as visualization interfaces or data analyses. Numerous Decision Support System (DSS) development methodologies exist along with dedicated Spatial Decision Support System (SDSS). Unfortunately, for multiple reasons, these tools and methodologies are not easily adaptable for the development of another SDSS. This paper proposes a framework for the development of a flexible SDSS that is built on open source software, allowing for low cost implementation. To support the efficiency of our approach, the design of a specific SDSS that is currently in use will be presented. This SDSS was developed for a company that distributes products through various retail networks. The multiple capabilities of the resulting SDSS will be revealed through an explanation of the different development steps. The complete framework is applied to a real data set that will be detailed in a demonstration.
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Notes
Housing starts is an economic indicator that reflects the number of privately owned new houses on which construction has been started in a given period.
References
Adejuwon A, Mosavi A (2010) Domain driven data mining: application to business. Int J Comput Sci 7(4):41–44
Agrawal S, Gupta RD (2014) Development and comparison of open source based web GIS frameworks on WAMP and apache tomcat web servers. In: ISPRS -international archives of the photogrammetry, remote sensing and spatial information sciences XL-4, pp 1–5
Armstrong M, De S, Densham PJ, Lolonis P, Rushton G, Tewari V (1990) A knowledge-based approach for supporting locational decisionmaking. Environ Plan B Plan Design 17(3):341–364
Benoit D, Clarke GP (1997) Assessing GIS for retail location planning. J Retail Consum Serv 4(4):239–258
Bogorny V, Martins Engel P, Alvares LO (2005) A reuse-based spatial data preparation framework for data mining. In: Proceedings of the 17th international conference on software engineering and knowledge engineering (SEKE’2005), pp 649–652
Bootstrap. http://getbootstrap.com/. Accessed 13 July 2016
BoundlessGeo. http://boundlessgeo.com/. Accessed 13 July 2016
Bradlow ET, Gangwar M, Kopalle P, Voleti S (2017) The role of big data and predictive analytics in retailing. J Retail 93(1):79–95
Chart JS. http://www.chartjs.org/. Accessed 13 July 2016
Chen J, Maceachren AM, Guo D (2008) Supporting the process of exploring and interpreting space–time multivariate patterns: the visual inquiry toolkit. Cartogr Geogr Inf Sci 35(1):33–50
Cios K, Pedrycz W, Swiniarski R, Kurgan L (2007) The knowledge discovery process. In: Data mining: a knowledge discovery approach. Springer Science & Business Media, Berlin, pp 9–24
Cliquet G, Fady A, Basset G (2006) Management de la distribution, 2nd edn. Dunod, Paris
CMHC. https://www.cmhc-schl.gc.ca/. Accessed 13 July 2016
Crossland M, Wynne B, Perkins W (1995) Spatial decision support systems: an overview of technology and a test of efficacy. Decis Support Syst 14(3):219–235
Densham P (1991) Spatial decisions support systems. In: Longley P (ed) Geographical information systems: principles and applications. Wiley, Hoboken, pp 403–412
Dubelaar C, Bhargava M, Ferrarin D (2002) Measuring retail productivity: What really matters? J Bus Res 55(5):417–426
Erskine M, Gregg D, Karimi J, Scott J (2013) Business decision-making using geospatial data: a research framework and literature review. Axioms 3(1):10–30
Evans B, Sabel CE (2012) Open-source web-based geographical information system for health exposure assessment. Int J Health Geogr 11:1–11
Fayyad U, Piatetsky-Shapiro G, Smyth P (1996) From data mining to knowledge discovery in databases. AI Mag 17(3):37–54
Flowerdrew R (1991) Spatial data integration. Geogr Inf Syst 1:375–387
FORAC. http://www.forac.ulaval.ca/. Accessed 13 July 2016
GeoExplorer. http://suite.opengeo.org/opengeo-docs/geoexplorer/. Accessed 13 July 2016
GeoServer. http://geoserver.org/. Accessed 13 July 2016
Ghaemi P, Swift J, Sister C, Wilson JP, Wolch J (2009) Design and implementation of a web-based platform to support interactive environmental planning. Comput Environ Urban Syst 33(6):482–491
Golf-clubs. http://www.legolfquebecois.com/. Accessed 13 July 2016
Google. Google maps api. https://developers.google.com/maps/. Accessed 13 July 2016
Google. Google maps geocoding api. https://developers.google.com/maps/documentation/geocoding/start. Accessed 13 July 2016
Granell C, Díaz L, Gould M (2010) Service-oriented applications for environmental models: reusable geospatial services. Environ Model Softw 25(2):182–198
Hernandez T (2007) Enhancing retail location decision support: the development and application of geovisualization. J Retail Consum Serv 14(4):249–258
Hess R, Rubin R, West L (2004) Geographic information systems as a marketing information system technology. Decis Support Syst 38(2):197–212
Jin X (2011) A supply chain optimization DSS web-services-based for e-retail industry. In: 2011 IEEE power engineering and automation conference (PEAM). IEEE, Wuhan, pp 229–232
Jsoup. https://jsoup.org/. Accessed 13 July 2016
Keenan P (2004) Using a GIS as a DSS generator. ICFAI University Press, Hyderabad, pp 97–113
Keenan P (2006) Spatial decision support systems: a coming of age. Control Cybern 35:9–27
Khan M, Khan SS (2011) Data and information visualization methods, and interactive mechanisms: a survey. Int J Comput Appl 34:1–14
Knezic S, Mladineo N (2006) GIS-based dss for priority setting in humanitarian mine-action. Int J Geogr Inf Sci 20(5):565–588
Lloyd R (1997) Spatial cognition: geographic environments, vol 39. The GeoJournal library. Springer, Dordrecht
Loucks DP (1995) Developing and implementing decision support systems: a critique and a challenge. J Am Water Resour Assoc 31(4):571–582
MacEachren AM, Kraak M-J (2001) Research challenges in geovisualization. Cartogr Geogr Inf Sci 28(1):3–12
Maibec. http://www.maibec.com/. Accessed 13 July 2016
Mendes A, Themido I (2004) Multi-outlet retail site location assessment. Int Trans Oper Res 11(1):1–18
Mennis J, Guo D (2009) Spatial data mining and geographic knowledge discovery-an introduction. Comput Environ Urban Syst 33(6):403–408
Moreno-Sanchez R, Anderson G, Cruz J, Hayden M (2007) The potential for the use of open source software and open specifications in creating web-based cross-border health spatial information systems. Int J Geogr Inf Sci 21(10):1135–1163
OpenLayers. http://openlayers.org/. Accessed 13 July 2016
Otto B (2011) Data governance. Bus Inf Syst Eng 3(4):241–244
PgAdmin. http://www.pgadmin.org/. Accessed 13 July 2016
PostGIS. http://postgis.net/. Accessed 13 July 2016
PostgreSQL. https://www.postgresql.org/. Accessed 13 July 2016
QGIS. http://www.qgis.org/en/site/. Accessed 13 July 2016
R. http://www.r-project.org/. Accessed 13 July 2016
Reinartz W, Dellaert B, Krafft M, Kumar V, Varadarajan R (2011) Retailing innovations in a globalizing retail market environment. J Retail 87:S53–S66
Rey S (2009) Show me the code: spatial analysis and open source. J Geogr Syst 11(2):191–207
Rinner C, Keßler C, Andrulis S (2008) The use of web 2.0 concepts to support deliberation in spatial decision-making. Comput Environ Urban Syst 32(5):386–395
Roig-Tierno N, Baviera-Puig A, Buitrago-Vera J, Mas-Verdu F (2013) The retail site location decision process using gis and the analytical hierarchy process. Appl Geogr 40:191–198
Sikder IU (2009) Knowledge-based spatial decision support systems: an assessment of environmental adaptability of crops. Expert Syst Appl 36(3):5341–5347
Ski-resort. http://www.maneige.com/. Accessed 13 July 2016
Sprague RH (1980) A framework for the development of decision support systems. MIS Q 4(4):1–26
Statistics-Canada. https://www12.statcan.gc.ca/. Accessed 13 July 2016
Studio R. https://www.rstudio.com/. Accessed 24 October 2016
Sugumaran V (2007) Web-based spatial decision support systems (websdss): evolution, architecture, examples and challenges. Commun Assoc Inf Syst 19:844–875
Thompson A, Walker J (2005) Retail network planning: achieving competitive advantage through geographical analysis. J Target Meas Anal Mark 13(3):250–257
Tomcat. http://tomcat.apache.org/. Accessed 13 July 2016
Vatsavai RR, Shekhar S, Burk TE, Lime S (2006) Umn-mapserver: a high-performance, interoperable, and open source web mapping and geo-spatial analysis system. In: Raubal M, Miller HJ, Frank AU, Goodchild MF (eds) Geographic information science: 4th international conference, GIScience 2006, Munster, Germany, 20–23 Sept, vol 4197. Springer, Berlin, pp 400–417
Wanderer T, Herle S (2015) Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment. Environ Impact Assess Rev 52:2–8
Yeoman. http://yeoman.io/. Accessed 13 July 2016
Zhang C, Zhao T, Li W (2010) The framework of a geospatial semantic web-based spatial decision support system for digital earth. Int J Digit Earth 3(2):111–134
Zhu X, Healey R, Aspinall R (1998) A knowledge-based systems approach to design of spatial decision support systems for environmental management. Environ Manag 22(1):35–48
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Accepted after one revision by Prof. Dr. Kliewer.
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Daras, G., Agard, B. & Penz, B. Conceptual Framework for SDSS Development with an Application in the Retail Industry. Bus Inf Syst Eng 61, 357–373 (2019). https://doi.org/10.1007/s12599-018-0548-y
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DOI: https://doi.org/10.1007/s12599-018-0548-y