Input information complexity, perceived time pressure, and information processing in GSS-based work groups: An experimental investigation using a decision schema to alleviate information overload conditions
Collaboration technology enhances the ability of work groups to acquire and share large volumes of information within a short period. The processing of voluminous information is challenging and may lead to conditions of information overload. The issue of complexity of information processing in collaboration technology supported group work, and the mechanisms to overcome the information overload conditions have not received sufficient attention in the past. In this paper, we attempt to address this gap by building a theoretical model and validating it through a laboratory experiment. Based on prior research on information processing at individual level, we propose that information processing in groups that use group support systems (GSS) is shaped by input information complexity and time pressure. We examine information processing of GSS-supported groups to perform tasks involving cognitive conflict. We demonstrate that information processing has an inverted U-shaped relationship with input information complexity and a positive relationship with time pressure. The study also demonstrates that the inclusion of a decision schema that incorporates aggregate level information gleaned from the work of prior groups engaged in a similar decision situation alleviates the information overload, enabling groups to process larger and more complex information.
information complexity time pressure information processing information overload collaboration technology group support systems integrative complexity