Influence of model management systems on decision making: empirical evidence and implications
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In¯uence of model management systems on decision making: empirical evidence and implications QB Chung1*, TR Willemain2 and RM O'Keefe3 1
Villanova University, USA, 2Rensselaer Polytechnic Institute, USA; 3Brunel University, UK
Model management (MM) regards decision models as an important organisational resource deserving prudent management. Despite the remarkable volume of model management literature compiled over the past twenty-odd years, very little is known about how decision makers actually bene®t from employing model management systems (MMS). In this paper, we report ®ndings from an experiment designed to verify the idea that the adequacy of modeling support provided by a MMS in¯uences the decision maker's problem solving performance and behaviour. We show that the decision makers who receive adequate modelling support from MMS outperform those without such support. Also, we provide empirical evidence that the MMS help turn the decision makers' perception of problem solving from a number crunching task into development of solution strategies, consequently changing their decision making behaviour. Keywords: model management systems; decision support systems; problem complexity; solution strategy; qualitative analysis; decision making behaviour
Introduction Since the conception of operations research (OR) during World War II to solve demanding military problems, and through its subsequent civilian sector application known as management science (MS), problem solving research efforts have resulted in a rich compilation of analytical tools, often referred to as OR=MS models. Applications of the OR=MS techniques to real world problems have become documented facts, and the ef®cacy of the decision models has been proven in monetary terms.1 Models, paraphrasing Kac, are like caricatures, and like good caricatures, good models portray some of the features of the realityÐthough distorted.2 An important role played by models is to give structure to experience.3 Recently, in the domain of managerial formulation and model building, various non-traditional OR=MS approaches have been proposed and implemented, such as cognitive mapping4 and in¯uence diagramming,5 recognising the soft side of OR.6 In most cases of developing OR=MS models, however, it is essential to provide a mathematical structure to the problem at hand by expressing it in mathematical terms.7,8 Since the managers who play the role of decision makers tend to lack the mathematical skills with which to develop such decision models, it is believed that model building is done best by experienced modelers such as `operations researchers' or `management scientists'.9,10 Therefore, the decision makers, or the clients for whom *Correspondence: Dr QB Chung, Villanova University, 800 Lancaster Avenue, Villanova PA 19085, USA. E-mail: [email protected]
the models are developed, usually do not have a complete understanding of the given methods, and the m
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