[AISWorld] Call for Papers - Decision Support Systems Special Issue on "Location Analytics and Decision Support"

[Pick, James]

Call for Papers: Decision Support Systems Special Issue on "Location Analytics and Decision Support"

(URL http://www.journals.elsevier.com/decision-support-systems/call-for-papers/call-for-papers-location-analytics-and-decision-support)


Guest Editors:

James B. Pick, University of Redlands, james_pick at redlands.edu
Avijit Sarkar, University of Redlands, avijit_sarkar at redlands.edu
Ozgur Turetken, Ryerson University, turetken at ryerson.ca
Amit Deokar, University of Massachusetts Lowell, amit_deokar at uml.edu


The uses of geographic information systems (GIS), location analytics, and spatial decision support along with related spatial technologies such as global positioning systems (GPS) and radio frequency identification (RFID) are growing rapidly worldwide across all organizations as well as in mass consumption markets. According to industry estimates (MarketsandMarkets, 2015), the global market for location based services and real-time location systems is expected to grow from USD 11.36 billion in 2015 to USD 54.95 billion by 2020, at a compound annual growth rate (CAGR) of 37.1%.
Prior studies of spatial decision support have leveraged spatial analytical capabilities of a GIS to solve problems in routing optimization, location-based marketing, patient monitoring, and infrastructure planning and development in industries such as transportation (Keenan, 1998; Hess et al., 2004; Ray, 2007), healthcare (Belien et al., 2013; Sneha and Varshney, 2013), and telecommunications (Scheibe et al., 2006; Grubesic, 2014). However emerging spatial topics such as utilization of spatial big data, georeferenced social media, and volunteered geographic information (VGI) for location analytics, use of web-GIS and mobile apps for decision support, management modeling based on the internet of things (IoT), geo-design for decision support and analytics, space-time methods for decision-making in real-time, GIS-based decision applications based on unmanned vehicles and light detection and ranging (LIDAR) have received little attention in recent IS literature. This gap provides underlying justification for the proposed special issue.


From the standpoint of theoretical development, prior studies in IS literature (Dennis and Carte, 1998; Walsham and Sahay, 1999; Mennecke et al., 2000; Jarupathirun and Zahedi, 2007) have employed and extended theories such as the actor-network theory and cognitive fit theory to explain management and cognitive aspects of GIS and map-based representations. However theories that explain and contextualize spatial analytical capabilities of a GIS or location based services within the broader scope of analytics – specifically location analytics – are largely absent or are yet to be fully developed. Such theories may be useful not just in the private sector considering development and adoption of location analytics technology for decision-support but also for deployment for location based services in response to humanitarian crises resulting from large-scale disasters. Empirical studies have been conducted to spatially analyze data sets with a location component for strategy and planning (Kisilevich et al., 2015; Grubsesic, 2010; Pick, Sarkar, and Johnson, 2015) and some design science studies have appeared (Zhu and Chen, 2005; Ray, 2007), but the potential in these areas is far from being realized.


The emerging use of GIS in business, nonprofits, and government needs to be further investigated.  These include: environmental analysis and decision making, pollution mitigation, geo-design of smart cities, customer analytics, market analysis and decision-making, geo-demographic analysis, asset management, and RFID-driven logistics and supply chain management.  Location is becoming pervasive with the advent of cloud-based web services, mobile devices, big data, and social media. Location analytics methods can be combined with well-known decision-making and analytics concepts and principles including those from decision support systems, strategic IS, databases, data mining, networks, web development, and mobile design. Statistical methods commonly used in management research can be enhanced by including location analytics and sophisticated geostatistical techniques.


The goal of this special issue is to explore and gain knowledge of contemporary GIS for decision-making and analytics emphasizing the emerging areas of mobile devices, analytics, big data, and social media applied to spatial decisions, as well as novel decision-making models, systems, and applications that demonstrate today’s more pervasive, complex, and sophisticated locational analytics tools and technologies.  Manuscripts that emphasize the following areas from theoretical, empirical, and design science approaches, using a variety of methodologies are welcome.


Topics of Interest:

·       Spatial decision support systems
·       Spatial analytics for decision making
·       Spatial Big Data and decision-making
·       Design science and GIS
·       Geo-design for decision-making
·       Internet of things (IoT) and spatial decision support
·       Location analytics
·       Geography of social media and volunteered geographic information
​                   (VGI) for decision support.
·       Space-time analytics for real-time decision-making
·       Mobile-based spatial decision making and applications
·       Novel location analytics and decision support system  applications in industry
·       Quality measures and evaluation of location analytics
·       Spatial data mining and knowledge discovery
·       Value-added determination  of GIS and spatial decision support


These and other related methodological, theoretical, and empirical contributions are all welcome.


References:

Belien, J., De Boeck, L., Colpaert, J., Devesse, S., and Van den Bossche, F. 2013. Optimizing the facility location design of organ transplant centers. Decision Support Systems 54(4):1568-1579.
Dennis, A.R. and Carte, T.A. 1998. Using geographical information systems for decision making: extending cognitive fit theory to map-based presentations. Information Systems Research 9(2):194-203.
Grubesic, T. 2010. Efficiency in broadband service provider provision: a spatial analysis. Telecommunications Policy 34(3):117-131.
Grubesic, T. 2014. Essential air service in the United States: exploring strategies to enhance spatial and operational efficiencies. International Regional Science Review. Published online May 12, 2014, doi: 10.1177/101269214532653.
Jarupathirun, S. and Zahedi, F. 2007.Exploring the influence of perceptual factors in the success of web-based spatial applications. Decision Support Systems 43(3):933-951.
Hess, R.L., Rubin, R.S., and West Jr., L.A. 2004. Geographic information systems as a marketing information system technology. Decision Support Systems 38(2):197-212.
Keenan, P. 1998. Spatial Decision Support Systems for Vehicle Routing. Decision Support Systems 22(1):65-71.
Kisilevich, S., Keim, D., and Rokach, L. 2013. A GIS-based decision support system for hotel room estimation and temporal price prediction: the hotel brokers’ context. 2013. Decision Support Systems 54(2):1119-1133.
MarketsandMarkets 2015. Location Based Services (LBS) and Real-Time Location Systems (RTLS) Market by Location (Indoor & Outdoor), Technology, Software, Hardware, Services, and Application Areas - Global Forecast to 2020. Retrieved from http://www.researchandmarkets.com/reports/3493628/location-based-services-lbs-and-real-time, on December 1, 2015.
Mennecke, B.E., Crossland, M., and Killingsworth, B. 2000. Is a map more than a picture? The role of SDSS technology, subject characteristics, and problem complexity on map reading and problem solving. MIS Quarterly 24(4):601-629.
Pick, J.B., Sarkar, A., and Johnson, J. 2015. United States digital divide: state level analysis of spatial clustering and multivariate determinants of ICT utilization. Socio-Economic Planning Sciences 49:16-32.
Ray, J.J. 2007.  A web-based spatial decision support system optimizes routes for oversize/overweight vehicles in Delaware. Decision Support Systems 43(4):1171-1185.
Scheibe, K.P., Carstensen Jr., L.W., Rakes, T.R., and Rees, L.P. 2006.  Going the last mile: a spatial decision support system for wireless broadband communications. Decision Support Systems 42(2):557-570.
Sneha, W., and Varshney, U. 2013. A framework for enabling patient monitoring via mobile ad hoc network. Decision Support Systems 55(1):218-234.
Walsham, G. and Sahay, S. 1999. GIS for district-level administration in India: problems and opportunities. MIS Quarterly 23(1):39-66.
Zhu, B. and Chen, H. 2005. Using 3D interfaces to facilitate the spatial knowledge retrieval: a geo-referenced knowledge repository system. Decision Support Systems 40(2):167-182.


Submission Requirements:

Presentation requirements: All submissions must be of high English standard. Papers containing significant number of grammatical and wording problems will be rejected without review.  As such, authors who are not well versed in English should seek help from professional English editors before submitting their manuscripts to avoid rejection due to language and presentation deficiencies.
Submitted papers should not be more than 34 pages, double spaced and use 11 point font size
including abstract, text, figures/tables and references (no extra online supplements). The journal is not interested in publishing any previously published material. The extensions of prior published papers in conference proceedings will not be considered for review if material from the conference proceeding is included.  All papers submitted will go through the initial screening processes.  For details of journal policies, manuscript preparation, and format requirements, please consult the Guide for Authors at the journal’s website (http://www.journals.elsevier.com/decision-support-systems).

Research requirements: A research paper should focus on discovery and resolution of one or more research issues/problems. A project report that does not address important research issues is not a research paper. A research paper must also have a strong evaluation component that is supported by evaluation techniques including statistical analysis, surveys, interviews, experiments, simulation, design science, theoretical proofs,
data mining, and other methodological approaches.

Papers (MS Word or PDF files) should be submitted electronically to DSS indicating that the submission is for this specific special issue. Any questions or inquiries should be addressed to the guest editors.   Please submit two copies of the manuscript: one with author information and affiliation and the other without any author information for review purpose.

Review Policy:

Given that the research in the area of GIS is progressing rapidly, the special issue must also be reviewed in an expedited manner in order to maintain relevancy. As such, papers submitted to this special issue and passing the first review will be given an opportunity for one and only one major revision followed by a possible minor revision.

Important Dates:

Full Paper Submission due date: September 20, 2016
Review Decision: December 5, 2016
Revision Due: January 16, 2017
Final Decision: February 15, 2017
Final Version Due: March 1, 2017
Final Publication Deadline: April 1, 2017.
Special Issue Published: Summer, 2017.


Special Issue Editorial Board:

Tony Grubesic, Arizona State University
Ashish Gupta, University of Tennessee, Chattanooga
Babita Gupta, California State University, Monterey Bay
Brian Hilton, Claremont Graduate University
Lakshmi Iyer, University of North Carolina, Greensboro
Nenad Jukic, Loyola University, Chicago
Peter Keenan, University College Dublin
Mehrdad Koohikamali, University of Redlands
Gene Moo Lee, University of Texas, Arlington
Jun Liu, Dakota State University
Mike McElroy, Claremont Graduate University and Esri Inc.
Asil Oztekin, University of Massachusetts, Lowell
Uzma Raja, University of Alabama
Rohit Rampal, SUNY Plattsburgh
Murray Rice, University of North Texas
Martin Swobodzinski, Portland State University