Neurofuzzy decision support system for efficient risk allocation in public-private partnership infrastructure projects

The performance of public-private partnership (PPP) infrastructure projects is largely contingent on whether the adopted risk allocation (RA) strategy is efficient. Theoretical frameworks drawing on the transaction cost economics and the resource-based view of organizational capability are able to explain the underlying mechanism but unable to accurately forecast efficient RA strategies. In this paper, a neurofuzzy decision support system (NFDSS) was developed to assist in the RA decision-making process in PPP projects. By combining fuzzy and neural network techniques, a synthesized fuzzy inference system was established and taken as the core component of the NFDSS. Evaluation results show that the NFDSS can forecast efficient RA strategies for PPP infrastructure projects at a highly accurate and effective level. A real PPP infrastructure project is used to demonstrate the NFDSS and its practical significance.

Decision support tool for production planning of a machining line

A decision support tool for production planning was developed to perform the difficult and time consuming task of allocating resources within the industrial partner's machining line, consisting of identical Computerized Numerically Controlled machines. The production-planning tool identified significant labour savings in a number of the industrial partner's production plans.

Child protection practitioners and decision-making tools : observations and reflections from the front line

Decision-making tools, particularly risk-assessment tools, have been implemented by governments around the world, perhaps most notably in the field of child protection, though little attention has been paid to how practitioners use them. This article presents the findings from ethnographic research that explored how child protection practitioners in the Department of Child Safety, Queensland, Australia, used four Structured Decision Making tools developed by the Children's Research Centre in Wisconsin in their daily practice in the intake and investigation stages of a case. The findings that the tools were not being used as intended by their designers and, in fact, tended to undermine the development of expertise by child protection workers has profound implications for the future development of technological approaches to child protection and, more broadly, human services practice.

Decision support in interest based negotiation support systems: the AssetDivider system

Negotiation Support Systems (NSS) model the process of negotiation from basic template support to more sophisticated decision making support. The authors attempt to develop systems capable of decision support by suggesting possible solutions for the given dispute. Current Negotiation Support Systems primarily rely upon mathematical optimisation techniques and often ignore heuristics and other methods derived from practice. This chapter discusses the technology of several negotiation support systems in family law developed in their laboratory based on data collected and methods derived from practise. The chapter explores similarities and differences between systems the authors have created and demonstrates their latest development, AssetDivider.

Managing negotiation knowledge with the goal of developing negotiation decision support systems

While Information Technology has been used to support negotiation there is little research in the domain of knowledge management in legal negotiation. In this paper we discuss the nature of negotiation knowledge and how such knowledge can be utilized to construct negotiation decision support systems. We conduct an in-depth examination of the notion of a BATNA (Best Alternative to a Negotiated Agreement) and given a useful BATNA, how we can use issue and preference elicitation and compensation and trade-off strategies to provide negotiation decision support. We conclude by indicating how current negotiation support systems can be extended to support Online Dispute Resolution and haw we can extend the Family_Winner system in light of the need to more adequately manage negotiation knowledge.

Trade-off manipulations in the development of negotiation decision support systems

Our model of negotiation for constructing Negotiation Decision Support Systems is based upon Principled Negotiation and uses trade-off manipulations in order to provide decision support. A resulting system, Family_Winner, was constructed using several information systems techniques. Trade-off Maps (a variant of Constraint Diagrams) are used to represent trade-off opportunities, while an empirically derived formula calculates the amount of compensation given to the ratings of issues remaining in dispute. The Issue Decomposition Hierarchy embedded in the system allows for the incorporation of sub-issues. Family_Winner was originally built for use in Australian Family Law. We believe our model can be extended for use in various other domains.

Family_Winner has been evaluated in the areas of industrial relations, international disputation and company disputes. Results from our evaluation suggest the system works satisfactorily in these domains. We conclude this paper by describing future projects that will develop and extend Family_Winner's functions and applicability.

Developing negotiation decision support systems that support mediators : a case study of the Family_Winner system

Negotiation Support Systems have traditionally modelled the process of negotiation. They often rely on mathematical optimisation techniques and ignore heuristics and other methods derived from practice. Our goal is to develop systems capable of decision support to help resolve a given dispute. A system we have constructed, Family_Winner, uses empirical evidence to dynamically modify initial preferences throughout the negotiation process. It sequentially allocates issues using trade-offs and compensation opportunities inherent in the dispute.

Virtual melawati : 3D GIS as a decision support tool for urban planning

Virtual Melawati is an environment for developing expertise in the application of 3D interactive visualization and GIS (Geographic Information System) to address problems of the built environment and to test the model as a decision support tool in the context of the local planning authorities in Malaysia. The visual approach enables the integration of highly complex spatial GIS information such as the evolution and transformation of the urban precinct as well as the impact of planned developments into the decision making process. The study will examine the techniques of data acquisition, data reconstruction from physical to digital, urban analysis and visualization in constructing an interactive 3D GIS model to support and assist the decision making process in urban design and planning. The outcomes of the study will deliver an experimental test bed for improving decision making processes in urban planning and design utilizing 3D modeling and GIS. The project will accelerate the uptake of digital and multimedia methods in local government, facilitate current planning and consultation processes between councils and stakeholders and improve the dissemination and management of spatial information about urban environments.

An Intelligent Human-Computer Interaction System for Decision Support

This paper proposes a novel architecture for
developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be
incorporated into a computerized system and, at the same time, to
preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking
process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first
employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed
approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.

Application of an Adaptive Neural Network to Medical Decision Support

Medical diagnostic and prognostic problems are prime examples of decision making in the face of uncertainty. In this paper, we investigate the applicability of the Fuzzy ARTMAP neural network as an intelligent decision support system in clinical medicine. In particular, Fuzzy ARTMAP is employed as a predictive model for prognosis of complications in patients admitted to the Coronary Care Units. A number of off-line and on-line experiments have been conducted with various network parameter settings, training methods, and learning rules. The results are compared with those from other systems including the logistic regression model. In addition, the outcomes of a set of on-line learning experiments revealed the potential of employing Fuzzy ARTMAP as an autono-mously learning system that is able to learn perpetually and, at the same time, to provide useful decision support.

Decision support and the effectiveness of web-based delivery and information tailoring for bowel cancer screening : an exploratory study

Background: Colorectal cancer (CRC) is the third most commonly diagnosed cancer in males and the second in females throughout the developed world. Population screening using fecal occult blood tests (FOBTs) facilitates early detection and greater chance of survival, but participation rates are low. We developed a Web-based decision tool to provide information tailored to an individual’s decision stage for CRC screening and attitude toward screening utilizing the Preventive Health Model (PHM) and Precaution Adoption Process Model (PAPM) as theoretical frameworks for screening behavior. We describe the practical steps employed in the tool’s design and the subsequent conduct of an exploratory study.
Objective: To design a decision tool for CRC screening and conduct an exploratory study among average-risk men and women to (1) test the impact of message type (tailored vs non-tailored) and message delivery modality (Web-based vs paper-based) on attitudes toward screening and screening uptake, and (2) investigate the acceptability of the decision tool and relevance of materials.
Methods: Participants (n = 100), recruited from a population sample of men and women aged 50-76 residing in urban Adelaide, Australia, were randomly assigned to a control group or one of 4 interventions: (1) Web-based and tailored information, (2) paper-based and tailored information, (3) Web-based and non-tailored (generic) information, or (4) paper-based and non-tailored information. Participation was augmented by snowball recruitment (n = 19). Questionnaires based on PHM variables were administered pre- and post-intervention. Participants were given the opportunity to request an FOBT. Following the intervention, participants discussed the acceptability of the tool.
Results: Full data were available for 87.4% (104/119) of participants. Post-intervention, perceived susceptibility scores for individuals receiving tailored information increased from mean 10.6 (SD 2.1) to mean 11.8 (SD 2.2). Scores on self-efficacy increased in the tailored group from mean 11.7 (SD 2.0) to mean 12.6 (SD 1.8). There were significant time x modality x message effects for social influence and salience and coherence, reflecting an increase in these scores for tailored Web-based participants only; social influence scores increased from mean 11.7 (SD 2.6) to mean 14.9 (SD 2.3), and salience and coherence scores increased from mean 16.0 (SD 2.2) to mean 17.7 (SD 2.1). There was no greater influence of modality or message type on movement toward a decision to screen or screening uptake, indicating that neither tailored messages nor a Web modality had superior effect. Overall, participants regarded tailored messages positively, but thought that the Web tool lacked “media richness.”
Conclusions: This exploratory study confirms that tailoring on PHM predictors of CRC screening has the potential to positively address attitudes toward screening. However, tailoring on these variables did not result in significantly increased screening uptake. Future research should consider other possible psychosocial influences. Mode of delivery did not affect outcomes, but as a delivery medium, the Web has economic and logistical advantages over paper.