Characteristics of Grey Analytic Models and Their Application Potential in Management Science Research

The chapter delves into the classification and properties of grey numbers in management science, distinguishing between discrete and continuous types, as well as finite and infinite ones. Details the formal designation of grey numbers within mathematical models, focussing on their boundaries and how they are influenced by their values within specific ranges. Various grey numbers are described, including continuous white numbers, discrete white numbers, finite grey numbers, and continuous infinite grey numbers, each with unique mathematical properties. The practical applications of grey numbers are emphasised, particularly their importance in interval grey numbers and the operational rules associated with them. Grey numbers are applied in management research through hybrid models that integrate grey numbers with other analytical models to address complexity and uncertainty in management systems. Grey incidence analysis (GIA) in management research is compared with statistical models, highlighting its utility in systems lacking comprehensive data. The research methodology using GIA is described, highlighting steps from conceptualisation to validation, focussing on the integration of qualitative and quantitative analyses. Grey forecasting models are explored as pivotal tools in predicting system behaviour based on limited data, detailing their operational steps, and emphasising the need for qualitative interpretation alongside quantitative analysis. Grey decision-making models are presented as essential tools in management, aimed at supporting complex decision-making processes through grey systems theory. In general, the chapter presents the grey systems theory as a robust framework for addressing uncertainties in management science, providing a comprehensive approach to modelling, analysing, and making decisions based on incomplete data.