A Computational Model of Coordination for the Design of Organizational Decision Support Systems

Gary V. Howorka, Lorien A. Anderson, K. Michael Goul and Michael Hine

Intelligent Systems in Accounting, Finance and Management, 1995, vol. 4, issue 1, 43-70

Abstract: The Information Technology (IT) for realizing Organizational Decision Support Systems (ODSS) is in a nascent stage of development. This is particularly true in the area of coordination, which is a critical element of ODSS, and which distinguishes ODSS research from earlier research in Group DSS and individually oriented DSS. As a first step in ODSS coordination research, alternative representation schemes need to be examined in terms of both their match with the prevailing needs of organizations and of existing IT approaches that can be brought to bear. Matching ODSS needs with coordination representation requirements is examined by using several supporting reference disciplines including foundational DSS and recent ODSS research frameworks/architectures. Existing IT approaches are adapted from the reference disciplines of Active DSS, Distributed Artificial Intelligence (DAI), and Mathematical/Computational Organization Theory (MCOT) to operationalize a computational model of coordination that: (1) embodies the philosophies of Active DSS—including the idea that automated intelligent agents can play a significant role in supporting decision makers by independently carrying out rudimentary tasks to support the various phases of a decision making process; (2) adapts DAI and IT approaches to reflect practical human organizational realities including what we refer to as the ‘Open‐Ended Knowledge World‘, and the evolutionary nature of organizations—whereby ODSS coordination representations will be subjected to almost constant revision due to both external environment disruptions and internal events that require adjustments to a preliminary plan; and (3) reflects the fact that organizational goals are often vague, which implies that a coordination representation should be sufficiently robust to reflect ad hoc analysis accommodating of strategy changes.

Date: 1995
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