Abstract

Since its introduction, geographic information science has witnessed a tremendous growth and can build on enormous achievements (e.g. Cheng et al. 2012). Current geographic information systems and the decision support systems and models that have been accompanying these systems have a strong ‘geography’ identity, typical of the era in which geographic information system were introduced. Systems are mostly based on spatial entities (mostly grids or polygons). To the extent that commercial and open source geographic information systems have been enriched with models, a similar strong geographic flavor can be discerned. Most models of spatial choice behavior are related to the aggregate spatial interaction models, models of land use change are often based on cellular automata. The question then becomes whether dominant spatial decision support systems, fundamentally based on aggregate spatial interaction, cellular automata and similar models, are suitable for adequately predicting consumer response. We content that in light of the increasing complexity of the decision making process and increasing personalization of decisions and lifestyles, these systems and their underlying models have increasingly become inadequate and obsolete. The field should shift to the development of more integral microscopic models of choice behavior, allowing more integral policy performance assessments. Moreover, mobile computing should allow and stimulate the development of real-time information and decision support systems that support the management of urban functions and include persuasive computing. Uncertainty analysis should play an integral role in these developments.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call