228 research outputs found
Conceptual Framework for SDSS Development with an Application in the Retail Industry
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 andmethodologies 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
Geographic Information Systems: A Tutorial and Introduction
his tutorial provides a foundation in GIS including its basic structure, concepts, and spatial analysis. GIS is a new field in business schools and presents opportunities for research. It is derived from about a dozen disciplines, some unfamiliar to most IS researchers. Following an overview of vertical-sector uses of GIS, the paper introduces their costs and benefits. The links of GIS to related technologies such as GPS, wireless, location-based technologies, web services, and RFID are examined. Conceptual models and research methodologies are discussed, including Spatial Decision Support Systems (SDSS), and GIS in visualization, organizational studies, and end user computing. Suggestions for future research are presented
A Tutorial on Geographic Information Systems: A Ten-year Update
This tutorial provides a foundation on geographic information systems (GIS) as they relate to and are part of the IS body of knowledge. The tutorial serves as a ten-year update on an earlier CAIS tutorial (Pick, 2004). During the decade, GIS has expanded with wider and deeper range of applications in government and industry, widespread consumer use, and an emerging importance in business schools and for IS. In this paper, we provide background information on the key ideas and concepts of GIS, spatial analysis, and latest trends and on the status and opportunities for incorporating GIS, spatial analysis, and locational decision making into IS research and in teaching in business and IS curricula
Location-allocation models applied to urban public services. Spatial analysis of Primary Health Care Centers in the city of LujĂĄn, Argentina
The actual digital technologies and particularly the association between the Geographical Information Systems (GIS) and the assistance to the Spatial Decision Support System (BOSS) have generated important possibilities for the treatment of spatial information. As regards the use of location-allocation models, this presentation assesses the possibilities of using such models in the field of the geography of services. In this paper theoretical aspects of the analyzed problems are presented, as well as methodological standardized questions for their solution through the use of GIS+SDSS. An applied case study related to the spatial analysis of Primary Health Care Centers (PHCC) in the city of Lujan, Argentina is also presented.Fil: Buzai, Gustavo Daniel. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentina. Universidad Nacional de Lujan. Departamento de Ciencias Sociales; Argentin
Geographic Information Systems in Information Systems Research - Review and Research Prospects
Since historical times, cartographic maps have revealed spatial relations and enabled decisions and processes. Geographic Information Systems (GIS) allow for acquisition, management, analysis, and presentation of geospatial objects. With free geospatial data becoming available through open data policies and an increasing amount of digitally connected objects in the Internet of Things (IoT), GIS are becoming indispensable to Information Systems (IS) research. However, the consideration and relevance of GIS has only been investigated rarely. We examine, how and in which fields of application GIS have been studied in the IS literature and elicit the importance of GIS regarding their design and usage. A systematic literature review leads us to develop four research propositions. Our results indicate that GIS are still an undeservedly underrepresented discipline in IS and should be more theorized, put center-stage in design-oriented research, and considered for creating superior value co-creation in service systems
Intelligent spatial decision support systems
This thesis investigates the conceptual and methodological issues for the development of
Intelligent Spatial Decision Support Systems (ISDSS). These are spatial decision support
systems (SDSS) integrating intelligent systems techniques (Genetic Algorithms, Neural
Networks, Expert Systems, Fuzzy Logic and Nonlinear methods) with traditional modelling and
statistical methods for the analysis of spatial problems.
The principal aim of this work is to verify the feasibility of heterogeneous systems for
spatial decision support derived from a combination of traditional numerical techniques and
intelligent techniques in order to provide superior performance and functionality to that achieved
through the use of traditional methods alone.
This thesis is composed of four distinct sections: (i) a taxonomy covering the
employment of intelligent systems techniques in specific applications of geographical
information systems and SDSS; (ii) the development of a prototype ISDSS; (iii) application of
the prototype ISDSS to modelling the spatiotemporal dynamics of high technology industry in
the South-East of England; and (iv) the development of ISDSS architectures utilising
interapplication communication techniques.
Existing approaches for implementing modelling tools within SDSS and GIS generally
fall into one of two schemes - loose coupling or tight coupling - both of which involve a tradeoff
between generality and speed of data interchange. In addition, these schemes offer little use
of distributed processing resources.
A prototype ISDSS was developed in collaboration with KPMG Peat Marwick's High
Technology Practice as a general purpose spatiotemporal analysis tool with particular regard to
modelling high technology industry. The GeoAnalyser system furnishes the user with animation
and time plotting tools for observing spatiotemporal dynamics; such tools are typically not found
in existing SDSS or GIS. Furthermore, GeoAnalyser employs the client/server model of
distributed computing to link the front end client application with the back end modelling
component contained within the server application. GeoAnalyser demonstrates a hybrid approach
to spatial problem solving - the application utilises a nonlinear model for the temporal evolution
of spatial variables and a genetic algorithm for calibrating the model in order to establish a good
fit for the dataset under investigation.
Several novel architectures are proposed for ISDSS based on existing distributed systems
technologies. These architectures are assessed in terms of user interface, data and functional
integration. Implementation issues are also discussed.
The research contributions of this work are four-fold: (i) it lays the foundation for ISDSS
as a distinct type of system for spatial decision support by examining the user interface,
performance and methodological requirements of such systems; (ii) it explores a new approach
for linking modelling techniques and SDSS; (iii) it investigates the possibility of modelling high
technology industry; and (iv) it details novel architectures for ISDSS based on distributed
systems
Location intelligence: a decision support system for business site selection
As one of the leading âworld citiesâ, London is home to a highly internationalised workforce and is particularly reliant on foreign direct investment (FDI) for its continued economic success. In the face of increasing global competition and a very difficult economic climate, the capital must compete effectively to encourage and support such investors.
Given these pressures, the need for a coherent framework for data and methodologies to inform business location decisions is apparent. The research sets out to develop a decision support system to iteratively explore, compare and rank Londonâs business neighbourhoods. This is achieved through the development, integration and evaluation of spatial data and its manipulation to create an interactive framework to model business location decisions. The effectiveness of the resultant framework is subsequently assessed using a scenario based user evaluation.
In this thesis, a geo-business classification for London is created, drawing upon the methods and practices common to geospatial neighbourhood classifications used for profiling consumers. The geo-business classification method encapsulates relevant location variables using Principal Components Analysis into a set of composite area characteristics. Next, the research investigates the implementation of an appropriate Multi-Criteria Decision Making methodology, in this case Analytical Hierarchy Process (AHP) allowing the aggregation of the geo-business classification and decision makersâ preferences into discrete decision alternatives. Lastly, the results of the integration of both data and model through the development of, and evaluation of a web-based prototype are presented.
The development of this novel business location decision support framework enables not only improved location decision-making, but also the development of enhanced intelligence on the relative attractiveness of business neighbourhoods according to investor types
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