Modeling and evaluating multi-stakeholder multi-objective decisions during public participation in major infrastructure and construction projects
Bibliographic record
Abstract
With a desire to increase the chance of success of major infrastructure and construction (MIC) projects, it is increasingly common to invite the public participating in the planning and design processes. Public participation requires the involvement of individuals and groups who are positively or negatively affected by a proposed intervention (e.g. a project, a program, a plan, a policy). An effective public participation program can be beneficial to the parties involved (i.e. the decision makers and general public) in many ways. As a result, a number of participatory approaches have been developed by various sectors to drive the process of agenda-setting, decision-making, and policy-forming. Many research studies focusing on various aspects of participation in policy-making in general have been conducted, but few have looked into its application in the construction and infrastructure industry in particular. On the other hand, the decision making process of contemporary MIC projects is becoming ever more complicated especially with the increasing number of stakeholders involved and their growing tendency to defend their own interests. Failing to address and meet the concerns and expectations of stakeholders may result in project failures. To avoid this necessitates a systematic participatory approach to facilitate the decision making and evaluation. This research, therefore, aims to develop a multi-stakeholder multi-objective decision making and evaluation model to help resulting in consensus and increasing the satisfaction among various stakeholders (or stakeholder groups) in MIC projects. In this research, an extensive literature review was first carried out to examine the salient elements of public participation in MIC projects and to identify the barriers to effective public participation in project decision making in different countries (e.g. Australia, Canada, United Kingdom, United States, South Africa, etc.). China being a developing country was selected for in-depth case study analysis. Through a series of interviews, the underlying reasons for ineffective participatory practice in China were revealed. A questionnaire survey was then conducted to unveil those stakeholder concerns pertinent to MIC projects at the conceptual stages through the degree of consensus and/or conflict involved. Finally, a multi-stakeholder multi-objective decision model and a multi-factor hierarchical comprehensive evaluation model were developed. These two models were founded on the decision rule approach and the fuzzy techniques respectively. Another round of interview was conducted to investigate the (i) influence of different stakeholder groups in making decisions related to MIC projects during their conceptual stages; and (ii) relationship between the satisfaction of a single stakeholder group and that of the stakeholders overall. The application of the two models was demonstrated by two cases in Hong Kong and their validity was confirmed through validation interviews. The results indicated that the two models are objective, reliable and practical enough to cope with real world problems. The research findings are therefore valuable to the government and construction industry at large for successful implementation of public participation in MIC schemes locally and internationally in future, especially when the construction industry is becoming increasingly globalized and the trend of cultural integration between the East and West is ever growing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".