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The purpose of this paper is to identify the key facilitating factors for smart sustainable practices (SSP) and develop a project evaluation model (PEM) for SSP implementation in Nigeria and Hong Kong. SSP is coined from the integration of digital technologies such as Building Information Modelling (BIM) to facilitate sustainability practices.

The study employed a quantitative research design approach using empirical questionnaire surveys to solicit the opinions of 69 and 97 construction practitioners in Nigeria and Hong Kong. Purposive and snowball sampling techniques were used to identify the potential survey respondents. The fuzzy synthetic evaluation technique was used to develop the PEMs.

The findings revealed that adequate technical expertise of the SSP processes is critical in enhancing its implementation in Hong Kong and Nigeria; as well as the provision of training programs for specialists in smart and sustainable initiatives. Meanwhile, the study's findings advocated that for an SSP-enabled construction project, its project performance is mainly influenced by the client's satisfaction level and the early involvement of the project teams.

The study's results are limited to the Nigeria and Hong Kong construction industries.

Construction stakeholders such as the clients, developers, contractors can utilize the PEMs to determine and track SSP initiatives implementation in building projects in a reliable and practical way.

No tool has been developed for evaluating SSP initiatives at the project level in the construction industry. Using case studies of Hong Kong and Nigeria, PEM indices were developed to measure and track SSP implementation in construction projects.

Guaranteed maximum price (GMP) and target cost contracting (TCC) with a pain‐share/gain‐share arrangement have been adopted to integrate the construction delivery process and motivate service providers to seek continuous improvements in project outcomes. However, there is still a lack of research evidence to evaluate the levels of success and lessons learned from these innovative procurement strategies. Based on the analysis of a series of in‐depth interviews on the perceptions of various relevant experienced industrial practitioners, this paper aims to explore the key attributes of GMP/TCC including the underlying motives, perceived benefits, potential difficulties, critical success factors, key risk factors involved and optimal project conditions for adopting GMP/TCC. The research findings are useful in assisting key project stakeholders in minimising the detriments brought about by potential difficulties in and maximising the benefits derived from implementing GMP/TCC concepts. The study is also significant in contributing to new knowledge and practical information of GMP/TCC applications and implementation, in both a national and international context.

The purpose of this paper is to develop a fuzzy risk assessment model for construction projects procured with target cost contracts (TCC) and guaranteed maximum price (GMP) contracts using factor analysis (FA) and fuzzy synthetic evaluation method, based on an empirical questionnaire survey with relevant industrial practitioners in Hong Kong.

A total of 34 key risk factors (RFs) inherent with TCC/GMP contracts were identified through an extensive literature review and a series of structured interviews. A questionnaire survey was then launched to solicit the opinions of industrial practitioners on risk assessment of such RFs.

The most important 17 principal RFs after the calculation of normalised values were selected for undertaking FA. Five principal risk groups (PRGs) were then generated in descending order of importance as: design risks, pre‐contract risks, economic and financial risks, lack of experience in TCC/GMP procurement process and post‐contract risks. These survey findings also reveal that design risks may be the major hurdle to the success of TCC/GMP projects in Hong Kong.

An overall risk index (ORI) associated with TCC/GMP construction projects and the risk indices of individual PRGs can be generated from the model for reference. An objective and reliable assessment can be achieved. The model provides a solid platform to measure, evaluate and reduce the risk levels of TCC/GMP projects based on objective evidence instead of subjective judgments. The research methodology could be replicated in other countries or regions to produce similar models for international comparisons and the assessment of risk levels for different types of TCC/GMP projects worldwide.

The purpose of this study is to identify driving factors and a quantitative model for implementing public-private partnership (PPP) projects in Ethiopia as a case study in emerging economies.

A review of the literature and semi-structured interviews were carried out to identify driving factors affecting the implementation of PPP projects in the Ethiopian context. Data were collected through a questionnaire survey within three months, with 59 validated responses; mean score technique and factor analysis were conducted. The fuzzy synthetic evaluation (FSE) method was applied to develop a driving index (DI) for implementing infrastructure PPP projects. Finally, a comparative analysis of top-five drivers was conducted between four emerging economies.

Mean values show that all driving variables are important. Through factor analysis, 22 identified driving variables were grouped into six factors, namely, benefit for public and private sectors, attention of private sector, social development, cost reduction, management ability of public sector and ability of private sector. The FSE method constructs a DI and shows that benefit for public and private sectors is the most crucial factor for PPP implementation in the context of Ethiopia. Apart from this, most driving forces for adopting PPP projects in these countries related to financial problems.

This study is one of the first integrate driving factors for PPP implementation. The index provides the decision-makers with a comprehensive tool to assess the needs of PPP implementation.

The construction industry has been evolving in recent years through the adoption of smart tools such as building information modeling to reduce the complexity in the construction process and optimize the project's goals. This paper aims to identify and assess the key drivers for the implementation of smart sustainable practices in the construction industry.

Inferential and descriptive statistical techniques were employed in analyzing the data collected via an international empirical questionnaire survey deployed in soliciting the perceptions of 220 construction professionals across 21 countries. Factor analysis was used to categorize the identified key drivers into their underlying clusters for further discussion. Also, the data were analyzed based on the various groups and regions of the study's respondents.

The key drivers (KDs) are related to the technical competence of staff as well as knowledge and awareness level within the industry, issues related to organizational and project's strategy and policies, availability of financial resources and development of relevant standards and policies to aid its execution among others. A comparative analysis of the perceptions of the different respondents' groups was undertaken and discussed.

The analysis of the key drivers for the implementation of smart and sustainable practices in the construction industry is expected to aid the decision-making of the relevant stakeholders as well as serve as a consultation instrument for government agencies in their design of localized policies and guidelines to aid smart and sustainable urbanization. The findings revealed the gaps in the implementation of smart and sustainable practices in various climes and organization setups and provided useful and practical strategies for addressing the current hindrances during implementation.

The study has generated valuable insights into the significant drivers that can enhance the implementation of smart and sustainable practices across regions. It is evident that synergy among the relevant stakeholders in the built environment will help accelerate the implementation of smart sustainable practices in the construction industry. The study findings have provided profound contributions to theory and research as well as to industry practice.

This paper aims to develop a fuzzy risk assessment model for construction projects procured with target cost contracts and guaranteed maximum price contracts (TCC/GMP) using the fuzzy synthetic evaluation method, based on an empirical questionnaire survey with relevant industrial practitioners in South Australia.

A total of 34 major risk factors inherent with TCC/GMP contracts were identified through an extensive literature review and a series of structured interviews. A questionnaire survey was then launched to solicit the opinions of industrial practitioners on risk assessment of such risk factors.

The most important 14 key risk factors after the computation of normalised values were selected for undertaking fuzzy evaluation analysis. Five key risk groups (KRGs) were then generated in descending order of importance as: physical risks, lack of experience of contracting parties throughout TCC/GMP procurement process, design risks, contractual risks and delayed payment on contracts. These survey findings also revealed that physical risks may be the major hurdle to the success of TCC/GMP projects in South Australia.

Although the fuzzy risk assessment model was developed for those new-build construction projects procured by TCC/GMP contracts in this paper, the same research methodology may be applied to other contracts within the wide spectrum of facilities management or building maintenance services under the target cost-based model. Therefore, the contribution from this paper could be extended to the discipline of facilities management as well.

An overall risk index associated with TCC/GMP construction projects and the risk indices of individual KRGs can be generated from the model for reference. An objective and a holistic assessment can be achieved. The model has provided a solid platform to measure, evaluate and reduce the risk levels of TCC/GMP projects based on objective evidence instead of subjective judgements. The research methodology could be replicated in other countries or regions to produce similar models for international comparisons, and the assessment of risk levels for different types of TCC/GMP projects (including new-build or maintenance) worldwide.

The increasing urbanization of the built environment has bolstered the need to promote green Building Information Modeling (BIM) initiative in new construction projects and the rehabilitation of old premises. This study aims to explore and examine the key benefits of the implementation of BIM and sustainability practices in the built environment.

The study gathered the worldwide perceptions of 220 survey participants from 21 countries which were analyzed using descriptive and inferential analytical methods. The identified individual benefits of green BIM were further categorized into their underlying clusters using factor analysis.

The key benefits are related to enhancing project efficiency and productivity, ensuring real-time sustainable design and multi-design alternatives, facilitating the selection of sustainable materials and components, together with reducing material wastage and project’s environmental impact, among others. The study analyzed and compared the perceptions of the diverse groups of the respondents as well.

Effective blueprints and insightful recommendations for enhancing the various stakeholders’ capacities to implement green BIM in their construction projects were put forward to achieve the aim of sustainable smart urbanization.

The study identified salient benefits of the adoption of BIM and sustainability practices. The proper integration of these concepts and the execution of the recommended useful strategies by construction stakeholders, policymakers and local authorities will enable the built environment to reap the gains of its implementation.

Public–private partnerships (PPPs) are viewed as a reform tool for resolving inefficiency and absence of dynamism in water supply delivery in developing countries. However, the requirements for their successful implementation have received very little attention. This paper aims to describe a set of critical success factors (CSFs) that, when given special and continual attention, would ensure a successful project implementation and to provide a predictive tool to aid implementers to evaluate the likelihood of a successful PPP water supply project.

Fourteen perceived CSFs were initially derived from project cases and extant literature, and verified through a two-round Delphi survey. Factor analysis established five critical success factor groups (CSFGs) that were then used to develop a fuzzy synthetic evaluation tool for assessing the chance of a successful project.

The five key CSFGs are commitment of partners, strength of consortium, asset quality and social support, political environment, and national PPP unit. The model output showed that, overall, these factors have a “very high” positive impact on a successful implementation of a water supply project. Hence, there is an excellent correlation between achievement of the CSFGs and project success. Success indices of individual principal factors are also “very high”.

The study presents a tool to public clients and private audience, and it is hoped that the study will trigger policy development towards PPP practice in developing countries, because these findings have wider implications for legal and regulatory systems, public capacity, financing, public procurement and politics.

The workforce management model conceptualised for the effective management of the construction workforce was subjected to expert scrutiny to determine the suitability and applicability of the identified practices and their attributed variables to the construction industry. In achieving this, a Delphi approach was adopted using experts from construction organisations in South Africa. These experts comprised workforce management personnel and construction professionals in senior management positions. The data were analysed using appropriate statistical tools such as interquartile deviation, Kendell’s coefficient of concordance, and chi square to determine consensus among these experts. After a two-round Delphi, the seven constructs proposed in the conceptualised workforce management model were adjudged to be important and worthy of adoption by construction organisations seeking to improve workforce management in the current fourth industrial revolution era.