Advances in computational capacity have enabled dynamic simulation modeling to become increasingly widespread in scientific research. As opposed to conceptual or physical models, simulation models enable numerical experimentation with alternative parametric assumptions for a given model design. Numerous design choices are made in model development that involve continuous or discrete representations of time and space. Simulation modeling approaches include system dynamics, discrete event simulation, agent-based modeling, and multi-method modeling. The model development process involves a shift from qualitative design to quantitative analysis upon implementation of a model in a computer program or software platform. Upon implementation, model analysis is performed through rigorous experimentation to test how model structure produces simulated patterns of behavior over time and space. Validation of a model through correspondence of simulated results with observed behavior facilitates its use as an analytical tool for evaluating strategies and policies that would alter system behavior.

Marketing is about communicating, delivering, and exchanging goods and services that are desired by customers, clients, and the public alike. They identify the groups the enterprise is striving to serve, developing offerings which match their needs, and establishing exchange relationships which satisfy those needs while accomplishing enterprise objectives of profit, service and/or social impact. Marketers use their planning processes to scan the relevant environment for opportunities, select target markets with unmet or insufficiently met needs, and design marketing mix strategies to serve them. In all of these activities, the qualitative and quantitative measures of location and geography are key.  Delivery of marketing mix strategies relies on tasks such as marketing research, market segmentation and customer profiling, all of which GIS supports.  In addition, specialized marketing functions and emerging technologies also benefit from location analytics resources. 

How effective is this fence at keeping people, objects, or sensitive information inside or outside? Location Privacy is concerned with the claim of individuals to determine when, how, and to what extent information about themselves and their location is communicated to others. Privacy implications for spatial data are growing in importance with growing awareness of the value of geo-information and the advent of the Internet of Things, Cloud-Based GIS, and Location Based Services.  

In the rapidly changing landscape of GIS and public domain spatial data, issues of location privacy are more important now than ever before. Technological trailblazing tends to precede legal safeguards. The development of GIS tools and the work of the GIS&T research and user community have typically occurred at a much faster rate than the establishment of legislative frameworks governing the use of spatial data, including privacy concerns. Yet even in a collaborative environment that characterizes the GIS&T community, and despite progress made, the issue of location privacy is a particularly thorny one, occurring as it does at the intersection of geotechnology and society.

Real Estate GIS concerns all dimensions of real estate that can be better understood or operationalized by knowing its geospatial context. Improving real estate decisions via GIS and related geospatial technologies is now expected by management of all industries, as well as home-renters and home-buyers in the residential market. Real Estate GIS Specialists are individuals who have applied knowledge and skills across the disciplines of business geography, the practice of real estate, and the application of geospatial technologies to support decision making in this realm. There is a good reason why the mantra of “location, location, location” is a long-standing tenet within the business of real estate.