Evaluating decision making performance in the GDSS environment using data envelopment analysis

Abstract

We provide a framework to evaluate decision making performance with Group Decision Support Systems (GDSSs) using an overall performance indicator. The indicator is constructed using Data Envelopment Analysis (DEA), which measures the economic efficiency of a decision-making process, or how efficiently a GDSS user converts decision resources into decision outcomes. To illustrate how our framework can be applied, we conduct an experiment that manipulates three contextual factors: communication mode, incentive structure, and group leadership. Within these contexts, we obtain an individual DEA decision efficiency score during the GDSS decision process, where participants are engaged in a mixed-motive task. We find that the communication mode, incentive structure, and interaction between the two significantly influence decision efficiency within this GDSS setting. However, the leadership structure does not have a significant impact on decision efficiency. The current study presents the first application of DEA in the area of GDSS. We illustrate how DEA is useful for evaluating GDSS-supported decision efficiency. The results suggest implications that guide the design of the next generation GDSS to support individuals within collaborative work groups involved in mixed-motive tasks.