GOST: an active modeling system for costing and planning NASA space programs

Castillo, David G.; Dolk, Daniel R.; Kridel, Donald J.

doi:10.1109/hicss.1991.184168

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…The process is illustrated with an application to the Mars Explorer Program. Castillo et al (1992) discussed GOST, a modeling system for cost estimation and mission planning. Berente and Youngjin (2010) discussed various issues associated with the implementation in 2004 of NASA's Full Cost, an activity-based accounting program.…”

Section: Applications Involving Organizational Design Project/programentioning

confidence: 99%

S-model

2013

Encyclopedia of Operations Research and Management Science

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Section: Applications Involving Organizational Design Project/programentioning

confidence: 99%

S-model

2013

Encyclopedia of Operations Research and Management Science

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“…Keen (1987) addressed the need for new decision support technologies to become more active in their support of decision-making processes. This new type of focus contributed to the development of ADSS, which takes the inclusion of intelligent agents in DSS one step further and advocates the development and implementation of DSS which encompass a set of tools that actively participate in various phases of the decision-making process (Manheim et al, 1991;Castillo et al, 1991;Raghavan, 1991;Papazoglou et al, 1990;Raghavan, 1990;Mili and Rada, 1990;Manheim et al, 1990;Manheim, 1989;Mastaglio, 1990;Mili, 1989;Raghavan and Chand, 1989;Mili, 1988;Raghavan, 1984). The use of technology as an active partner in the decision-making process is based on the following key premises:…”

Section: Active Decision Support Systemsmentioning

confidence: 99%

“…055 are being used to assist management in solving a variety of semistructured problems including scheduling, stock trading, strategic planning, etc. In addition to classical individual user 055, other types of decision support systems have been implemented including executive information systems (EIS), group decision support systems (GDSS) (Chen and Liou, 1991;Howorka et al, 1991;Goul et al, 1990;Eck et al, 1989;Richards, 1989;]arvenpaa et al, 1988;Crowston and Malone, 1988;DeSanctis and Gallupe, 1987;Dennis et al, 1988;Malone et al, 1987;Huber, 1984), active/symbiotic decision support systems (ADSS) (Dalal and Kasper, 1991;Manheim et al, 1991;Castillo et al, 1991;Raghavan, 1991;Papazoglou et al, 1991;Raghavan, 1990;Mili and Rada, 1990;Manheim et al, 1990;Mastaglio, 1990;Manheim, 1989;Mili, 1989;Raghavan and Chand, 1989;Mili, 1988;Raghavan, 1984), and knowledge-based systems (KBS) (Goul et al, 1992). Anyone or all of these types of systems are present in today's organizations.…”

Section: Introductionmentioning

confidence: 99%

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

Howorka

Anderson

Goul

et al. 1995

Intelligent Systems in Accounting, Finance and Management

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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 MathematicaVComputational Organization Theory (MCOT) to operationalize a computational model of coordination that: (1) embodies the philosophies of Active DS~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.

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