A particularly difficult, but important, challenge in the design and development of contemporary information systems is dealing with complexity. Although complexity has been richly discussed from various perspectives in the literature, there is limited guidance on how to address complexity in information systems design. This research analyzes different approaches to handling complexity and finds that there exists a plurality of ways in which to address complexity that are dependent upon the given situation. This analysis results in the derivation of a framework for addressing complexity in information systems. The framework explicitly recognizes implications and limitations of decomposition, inner-outer environments, abstractions, and decentralization, and the role of Ontology. Application of the framework is intended to enable information researchers to identify and adapt applicable strategies for managing complexity in any domain.

The concept of commitment has recently been adopted by researchers to model cooperative organizational activities. By defining a commitment as an agreement by an agent to the requesting agent to carry out the requested action, a Commitment Reasoning Support System (CRSS) is proposed in an attempt to support the reasoning process in deciding whether or not to make a commitment. CRSS can be characterized as a specialized decision support system that emphasizes the accountability and the sentimental aspects of decision making. An empirical study was conducted on a CRSS prototype. The findings show that it is useful for commitment requests with high complexity and/or with important implications. The study also suggests possible conceptual insights of commitment reasoning for future research.

This paper suggests a new perspective for Decision Support Systems (DSS) that is guided by the dominant role of experience in decision making. This perspective is motivated by evidence from cognitive research supporting the view that organizational problem solvers rely to a large extent on episodic knowledge gained from similar problem solving experiences. In addition, research indicates that organizational workers tend to cooperate and seek others' experiences, especially as task domains become more complex and relevant knowledge becomes more sparse. To this end we propose a decision support architecture using a combined approach of Case-Based Reasoning and Analogical Reasoning, which utilizes previous decision making results to aid in current problem solving activities, and distributed case management, which facilitates the exchange of computer-mediated experiences among organizational workers. A prototype implementation that demonstrates the feasibility of this approach is also described.

Existing negotiation protocols used in Distributed Artificial Intelligence (DAI) systems rarely take into account the results from negotiation research. We propose a negotiation protocol, SANP (Speech-Act-based Negotiation Protocol), which is based on Ballmer and Brennenstuhl's speech act classification and on negotiation analysis literature. The protocol is implemented as a domain-independent system using Strudel, which is an electronic mail toolkit. A small study tested the potential use of the protocol. Although a number of limitations were found in the study, the protocol appears to have potential in domains without these limitations, and it can serve as a building block to design more general negotiation protocols.

An intelligent information system may be composed of hundreds or thousands of entities each of which may possess some part of the overall knowledge of an organization. In such an environment there is a need for these entities to communicate in order to share knowledge and to cooperate in accomplishing organizational activities. In this paper we propose an architecture for modelling intelligent information systems and discuss how this architecture supports the communication of knowledge in such information systems.

To improve the effectiveness of office workers in their decision making, office systems have been built to support (rather than replace) their judgment. However, these systems model office work in a centralized environment, and/or they can only support a single office worker. Office work that is divided into specialized domains handled by different office workers (where cooperation is needed in order to accomplish the work) is not supported. In this paper, we will present a model that supports office problem solving in a logically distributed environment. (In some systems, information is geographically distributed for performance purposes rather than for conceptual need. The term, logically , is therefore used to indicate the logical need of organizing information without having to worry about the physical location of the information.) In particular, cooperative tools that can be used to support office workers during the process of their problem solving is discussed.