Expert Decision Making in a Complex Engineering Environment: A Comparison of the Lens Model, Explanatory Coherence, and Matching Heuristics

This study investigated the complex decisions made by engineers when conducting contaminated-land risk assessments. Experienced assessors studied summaries of site reports, which were composed of different combinations of relevant cues, and decided on the risk level of each site. Models from three theories of decision making were compared. Applying judgment analysis to develop a lens model provided the best account of the data, lending support to social judgment theory. A model based on a fast-and-frugal heuristic, the matching heuristic, did not fit the data as well; nor did a coherence model based on the theory of explanatory coherence. Comparison with decisions generated with the use of industry guidance showed only a moderate fit, suggesting that the standard procedure does not accurately represent how highly proficient domain practitioners make assessments in this context. Qualitative analyses of comments made by participants suggested that they used a combined approach that applied key cues as predicted by social judgment theory, integrated into a meaningful, coherent account, as predicted by the theory of explanatory coherence. Overall, these findings suggest a novel process in which a range of information is combined to form a coherent explanation of the data but in which key cues are more influential than others

Expert Decision Making in a Complex Engineering Environment: A Comparison of the Lens Model, Explanatory Coherence, and Matching Heuristics

This study investigated the complex decisions made by engineers when conducting contaminated-land risk assessments. Experienced assessors studied summaries of site reports, which were composed of different combinations of relevant cues, and decided on the risk level of each site. Models from three theories of decision making were compared. Applying judgment analysis to develop a lens model provided the best account of the data, lending support to social judgment theory. A model based on a fast-and-frugal heuristic, the matching heuristic, did not fit the data as well; nor did a coherence model based on the theory of explanatory coherence. Comparison with decisions generated with the use of industry guidance showed only a moderate fit, suggesting that the standard procedure does not accurately represent how highly proficient domain practitioners make assessments in this context. Qualitative analyses of comments made by participants suggested that they used a combined approach that applied key cues as predicted by social judgment theory, integrated into a meaningful, coherent account, as predicted by the theory of explanatory coherence. Overall, these findings suggest a novel process in which a range of information is combined to form a coherent explanation of the data but in which key cues are more influential than others

Decision support methodology for complex contexts

Complex decision contexts involving multiple (and often competing) policy objectives are common in both strategic and operational decisions encountered in engineering projects or programmes. The need to consider multiple objectives and to address the concerns of diverse stakeholders raises particular difficulties in applying sustainable development principles to defining and choosing an optimum project, process, product, policy or solution. This paper derives some fundamental characteristics of appropriate support for sustainable development decisions. Using these characteristics, three methodologies, which have been proposed as support tools for making strategic decisions and assessing policy choices for their contributions towards sustainable development, are reviewed critically with reference to their theoretical basis and informed by case studies of engineering applications. Recommendations are made to support best practice and to develop more effective support for such decisions in future

The Governance of coal ash pollution in post-socialist times: power and expectations

The coal energy sector in Bosnia and Herzegovina (BiH) represents both a significant economic hope and a considerable environmental threat for the country. One of the major problems of the coal industry is the disposal of large amounts of coal combustion residues. RECOAL was an EU-supported project (2005-7) whose objective was to develop remediation solutions for coal ash disposal (CAD) sites in BiH. Most of RECOAL's environmental fieldwork was based around TEP in the municipality of Tuzla, one of the biggest thermo-electric power plants in the country. Qualitative research was carried out to understand the environmental governance structure of the area and inform and test the acceptance of different remediation solutions proposed by RECOAL. Interviews with institutional stakeholders showed a highly complex institutional structure, where government institutions and industry are involved in complicated negotiations about the distribution of the liabilities resulting from TEP's pollution. Interviews among local residents show that locally organised action could help steer the policy-making process towards more sustainable solutions

Contaminated land risk assessment: Variability in site assessment and decision making in the UK

Judgement forms an integral part of a risk-based approach to the assessment of land affected by contamination. Legislation and guidance suggest that the assessor should use a rational step-wise process to identify pollutant linkages in order to assess risk from land contamination. The present study aims to investigate the decision-making processes that are used by experienced contaminated land assessors. This study required 29 participants with a minimum of five years’ relevant experience to rate the level of risk from land contamination on 27 hypothetical housing development sites. Each site was designed with specific information (variables) used as indicators of the potential for unacceptable risk. Linear regression analysis was used to identify the significance of each of the variables in determining the level of risk assessed by participants. The first of the key findings was that considerable disagreement was observed between participants, and this was correlated to cases with contradictory information. This may have also been related to the participant’s perception of the available risk scale. The linear regression analysis showed that the most influential variables were chemical-test data and the presence of human-exposure pathways. These findings would suggest that experienced assessors focus on a few key aspects of the information available to assess risk from land contamination. However, analysis of the qualitative data collected in the study supported a more holistic decision-making process, in line with use of pollutant linkages described in guidance. The results suggest that when presented with limited data for development sites, assessors may rely on a few variables to rate the risk, but that a coherent picture of the interaction of all of the variables is required for a more confident assessment. The findings of the study presented here can be used to inform training and future guidance in this sector