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Article

In such a complex and well-researched domain as decision support systems (DSS), with a long history of authors making insightful contributions since the 1960’s, it is critical for researchers, especially those less experienced, to have a broad knowledge of the seminal work that has been carried out by prior generations of researchers. This can serve to avoid proposing research questions which have been considered many times before, without having consideration for the answers which have been put forward by previous scholars, thereby reinventing the wheel or “rediscovering” findings about the life of organizations that have been presented long before. The study of human and managerial decision-making is also characterized by considerable depth and seminal research going back to the beginning of the 20th century, across a variety of fields of research including psychology, social psychology, sociology or indeed operations research. Inasmuch as decision-making and decision support are inextricably linked, it is essential for researchers in DSS to be very familiar with both stream of research in their full diversity so they are able to understand both what activity is being supported and how to analyze requirements for developing decision support artefacts. In addition, whilst the area of decision support has sometimes been characterized by technology-based hype, it is critical to recognize that only a clear focus on the thinking and actions of managers can provide decisive directions for research on their decision support needs. In this article, we consider first the characteristics of human cognition, before concentrating on the decision-making needs of managers and the lessons that can be derived for the development of DSS.

Article

A geographic information system (GIS) is a system designed to capture, store, organize, and present spatial data, which is referenced to locations on the Earth. Locational information is of value for a wide range of human activities for decision-making relating to these activities. As spatial data is relatively complex, GIS represents a challenging computer application that has developed later than some other forms of computer systems. GIS uses spatial data for a region of the Earth; such regional data are of interest to a wide range of users whose activities take place in that region, and so many users in otherwise disconnected domains share spatial data. The availability and cost of spatial data are important drivers of GIS use, and the sourcing and integration of spatial data are continuing research concerns. GIS use now spans a wide range of disciplines, and the diversity created is one of the obstacles to a well-integrated research field. Location analysis is the use of GIS for general-purpose analysis to determine the preferred geographic placement of human activities. Location analytics uses spatial data and quantitative spatial models to support decision-making, including location analysis. The growth of location analytics reflects the increasing amounts of data now available owing to new data collection technologies such as drones and because of the massive amounts of data collected by the use of mobile devices like smartphones. Location analytics allow many valuable new services that play an important role in new developments such as smart cities. Location analytics techniques potentially allow the tracking of individuals, and this raises many ethical questions, however useful the service provided; therefore, issues related to privacy are of increasing concern to researchers.