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To come up with a prudent decision on the installation of an appropriate green wall (GW) on buildings, this study presents a novel decision-making algorithm. The proposed algorithm considers the importance of barriers hampering GW adoption, as well as their relationships with regard to different types of GWs existing in a contextual setting.

The proposed methodological approach is based on the integration of qualitative and quantitative techniques by employing focus group discussion, fuzzy-based best-worst method and fuzzy TOPSIS.

Based on the experiences of qualified experts involved in related projects in Hong Kong, the following conclusions are drawn: (1) cost, installation and maintenance-related barriers are perceived to have the highest importance, (2) modular living wall system is the most suitable GW system for the context of Hong Kong and (3) existing barriers are found to have a pivotal role in the ranking of the most suitable GW systems.

The findings provide valuable insight not only for policymakers and stakeholders, but also for establishing a methodological approach that can assist decision-makers in identifying the most beneficial GW system rather than the most applicable one. This could have significant implications and introduce potential changes to the common way of practice within the industry and lay the foundation for wider adoption of GW.

While previous studies have investigated the sustainability-related issues of GW façade applications, the current body of knowledge is deprived of a comprehensive methodological approach for the selection of the most suitable GW systems.

Green walls (GWs), comprising living walls and green facades, have been touted as environmentally friendly products in architectural design. GWs can be viable in every aspect of sustainability; they provide residents of buildings with a wide range of economic, social and environmental benefits. Despite this, the adoption rate of GW is still in its infancy stage, and the existing literature concerning the hindrances inhibiting GW adoption is very limited. To address these gaps, the aim of this paper is to identify and prioritize the hindrances to GW adoption in Hong Kong.

After identifying 17 hindrances through an in-depth review of literature, the fuzzy Delphi method (FDM) is employed to refine the hindrances based on the local context with the help of 21 qualified experts in the field. Subsequently, Fuzzy Parsimonious Analytic Hierarchy Process (FPAHP) is exploited as a recently developed technique to prioritize the identified hindrances.

Results reveal that the most significant hindrances to the adoption of GW are maintenance cost, high installation cost, difficulties in maintenance, sophisticated implementation and inducement to fire. Findings call for scholars to address ways to improve GW installation practices and methods in order to eradicate the hindrances and provide lessons for policymakers, assisting them in facilitating the larger-scale adoption of GW.

Considering the dearth of studies on hindrances to the adoption of GWs, this paper provides a comprehensive outlook of the issue, providing knowledge that can be used as a building block for future scholars within the field. It also provides valuable insights for stakeholders within the construction industry about the hindrances to the adoption of GWs which could direct their efforts toward better implementation of it.

In the study, a five-dimensional-safety risk assessment model (5D-SRAM) is developed to improve the construction safety risk assessment approaches available in the literature. To that purpose, a hybrid multi-dimensional fuzzy-based model is proposed, which provides a comprehensive ranking system for the safety risks existing in a project by considering the contextualization of the construction-related activities resulting in an accident.

The developed 5D-SRAM is based on an amalgamation of different fuzzy-based techniques. Through the proposed fuzzy analytic hierarchy process (AHP) method, the importance weights of essential risk dimensions playing role in defining the magnitude of the construction-related risks are obtained, while a precise prioritized ranking system for the identified safety risks is acquired using the proposed fuzzy technique of order preference similarity to the ideal solution (FTOPSIS).

Through the application of the proposed 5D-SRAM to a real-life case study – which is the case of green building construction projects located in Hong Kong – contributions are realized as follows: (1) determination of a more complete range of risk dimensions, (2) calculation of importance weightings for each risk dimension and (3) obtainment of a precise and inclusive ranking system for safety risks. Additionally, the supremacy of the developed 5D-SRAM against the other safety assessment approaches that are commonly adopted in the construction industry is proved.

The developed 5D-SRAM provides the concerned safety decision-makers with not only all the crucial dimensions that play roles toward the magnitude of safety risks posing threats to the workers involved in construction activities, but also they are given hindsight regarding the importance weights of these dimensions. Additionally, the concerned parties are embellished with the final ranking of safety risks in a more comprehensive way than those of existing assessment methods, leading to sagacious adoption of future prudent strategies for dealing with such risks occurring on construction sites.

Numerous studies have documented the safety risks faced by construction workers including proposals for risk assessment models. However, the dimensions considered by such models are limited, generally constrained to risk event probability combined with risk impact severity. Overlooking other dimensions that are essential towards the calculation of safety risks' magnitude culminates in overshadowing the further adoption of fruitful mitigative actions. To overcome this shortcoming, this study proposes a novel 5D-SRAM.