| This dissertation deals with the development of a decision support system (D.S.S.) for use in assisting a seller (e.g. a marketing manager) in his decision processes involving commonly-occurred, less structured and underspecified problems. As an antecedent to establishing a practicable framework to D.S.S., the dissertation examines in detail the buyers' multiattribute, multiagent decision processes employed in evaluating industrial product alternatives.;Industrial buyer decision processes are both multiattribute and multiagent in nature, i.e., a group of individuals interacting together to make a decision to select an alternative. Multiattribute, multiagent decision processes tend to become quite complex due to inherent heterogeneity of decision makers/influencers arising from group decision-making and a diversified group of end users with multiple evaluation criteria. Modeling a multiattribute, multiagent decision process, therefore, becomes a complicated phenomenon.;To model the multiattribute, multiagent decision processes, the dissertation first develops a comprehensive and eclectic conceptual framework which attempts to qualitatively represent the underlying structure of the alternative evaluation thought process. Next, it utilizes the market structure analysis approach to transform this framework into a set of managerially useful operational procedures, i.e., a procedural framework, by developing a number of interconnected behavioral models. Finally, this procedural framework is applied to a real world empirical study to validate the proposed framework and to gain insight into a very intricate industrial buyer decision process.;An assumption held by many scholars and adopted here is that, a decision maker (a single individual or a group of individuals) does not holistically evaluate each alternative (without taking into account its constituting attributes) as a single entity. Instead, he tends to apply an approach wherein he first examines the attribute levels possessed by each alternative on certain relevant criteria. Next, he forms an overall value or utility of each alternative by cognitively aggregating all attribute levels and, finally, makes a decision to select a specific alternative. This represents the ideal multiattribute decision process. |
