Abstract
The analytic hierarchy process (AHP) and the analytic network process are important multiple criteria decision making methods for supporting complex, discrete strategic management decision problems. In order to exploit a broader information basis as well as to achieve a sufficient degree of objectivity strategic decision settings are mostly embedded into a multi-personal decision context to which different individuals with expert status contribute. Owing to the fact that there is a vast number of different methods and further internal possibilities (derivation of means) to aggregate the individual expert preferences to a group consensus, the first aim of this paper is to present a comprehensive literature review on various aggregation possibilities. The second aim is the conduction of a transparent comparative analysis of selected approaches and methods (geometric/arithmetic aggregation of individual judgments, geometric/arithmetic aggregation of individual priorities, geometric/arithmetic loss function approach and Group AHP model). Therefore, we use four different evaluation scenarios and point out under which assumptions which solution is suitable. Starting from these results, the aggregation techniques adequate to a specific decision context are provided.
Highlights
The trend towards more democratic organization structures, global networking and advanced technical possibilities often leads to strategic managerial decisions based on collective decision making and not on single decision makers
To show particular differences with regard to certain decision environments analytic hierarchy process (AHP)/analytic network process (ANP) group aggregation techniques were evaluated with respect to relevant criteria
While the procedure of Aggregation of individual judgments (AIJ) and the loss function approach to group aggregation (LFA) come to the conclusion that alternative A2 should be chosen, the procedure of Aggregation of individual priorities (AIP) and the Group AHP model recommend alternative A1
Summary
The trend towards more democratic organization structures, global networking and advanced technical possibilities often leads to strategic managerial decisions based on collective decision making and not on single decision makers. Organizations try to use the potential strengths of a collective decision making, assuming that a group of experts makes better or at least more objective decisions than individuals which underlie natural cognitive restrictions. Compared to single persons’ decision making, termed as individual decision making (IDM), groups are providing the advantages of a broader amount of information, much more experience and alternatives, a better diversification of the individuals’ cognitive restrictions, less evaluation mistakes, and an increased acceptance of the solution (Sims 2002; Kreitner and Cassidy 2011). The need for a systematic group decision support emerges
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