Grey Systems Theory as an Effective Method for Analyzing Scarce, Incomplete and Uncertain Data on the Example of a Survey of Public Perceptions of Safety in Urban Spaces

Abstract

Many processes and phenomena that occur in the natural and social environment have a complex character, and the interdependencies between social and economic phenomena are most often analyzed by identifying the relationships between multiple factors that shape urban space. Decisions concerning the visual attributes of cities are usually made by urban planners and civil officers, whereas social preferences are rarely considered in the planning process. The latest research indicates that urban planners should account for the needs and expectations of local residents who are the users of public spaces in cities. This paper discusses the results of selected research studies investigating the impact of geospatial attributes on perceptions of safety in urban areas. The theories that are used to improve safety in cities and selected methods for analyzing spatial data were presented. The analyzed attributes were selected by brainstorming, a heuristic technique for solving research problems. The selected attributes were ranked in a survey performed on an accidental (convenience) sample. In this study, Grey Relational Analysis (GRA), a type of Grey Systems Theory (GST) which supports the use of incomplete, uncertain and scarce data, was applied. The advantages of grey systems over statistical methods in analyses of spatial data were presented. Grey system analyses generate sequences of significant geospatial attributes and indicate which factors exert the greatest influence on the examined phenomenon. The results can be used to solve practical problems related to the shaping of space.

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