Modeling and evaluating multi-stakeholder multi-objective decisions during public participation in major infrastructure and construction projects
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».