An Examination of Alternative Approaches to Risk Management and Insurance Research

ABSTRACT Much current risk management and insurance research follows a pattern prescribed by the science paradigm. This article discusses some well-recognized problems associated with the science paradigm, and then presents several alternatives that can supplement the science paradigm, thereby broadening and deepening the scope of risk management and insurance research and education. INTRODUCTION This article explores the current scope and direction of risk management and insurance (RMI) research. Its purposes are to examine the paradigm underlying much of this research, to cause researchers to assess their own beliefs about this important subject and to suggest some possible alternatives for expanding the nature and range of this work. Risk management and insurance research questions generally involve real-world issues, and research output could prove more useful to problem-solvers if multiple approaches were used. Moreover, many risk management problems involve "human nature," normative issues, and value judgments. Current concerns about funding social security, providing access to health care, and financing the terrorism loss exposure demonstrate that many areas of interest to RMI researchers have immediate and broad societal impact. Any contraction of the range of research issues addressed by the discipline caused, for example, by a need for historic data, or for any other reason, should be viewed as a cause for concern in that it reduces the range of questions that can be addressed. The general reliance on microeconomic analysis and on econometric techniques in research stems from a general reliance on the classical science paradigm. After establishing a basis for this assertion, the article identifies some distinct limitations affecting RMI research arising from this method. The article concludes with a discussion of some alternative approaches. THE CLASSICAL SCIENCE PARADIGM Definition By definition, the science paradigm, also known as the "scientific method," is a set of rules for explaining everything in the universe that can be measured and described. Generally, scientists approach this daunting task by formulating theories and then testing those theories through experiments and observations. Mathematics provides the lingua franca. Hawking suggests the scope of the classical or modern science paradigm as follows: "The eventual goal of science is to provide a single theory that describes the whole universe" (Hawking, 1988, 10). The Foundation of Business Research and Education The explanations for adoption of the science paradigm by the natural sciences rest on its logic, consistency, and the highly visible material progress in astronomy, chemistry, medicine, and other sciences during the past several centuries. The explanations for the adoption of this paradigm outside natural science, specifically by economics and other business disciplines, are more open to conjecture. Under some circumstances, the science paradigm may be the most appropriate model for understanding some economic issues and its use has led to a better understanding of some facets of economic life (Cummins, 1987). Undoubtedly, the adoption of the science model lends an aura of credibility and legitimacy to social sciences in general and American schools of business specifically. Bloom (1987,359,360), Sykes (1988,204,205), and Smith (1990,250,252) each charge that all the social sciences as well as some traditional liberal arts, including history, have adopted the science paradigm with dubious results for research and teaching, but with favorable impact on self-esteem. Much evidence exists of the pervasiveness of the science paradigm in modern business, and by extension RMI, research, and education. The general acceptance of the science paradigm by business disciplines is not even a point of contention (McCloskey, 1983, 484; Woo, 1986). Many commentators, including the authors, would assert that business research has moved forward from a model based mostly on description to the current model of hypothesis testing and theory building. …