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The importance of the satisfaction derived by participants has escalated in all manufacturing sectors. Due to increased opposition and dissatisfied participants, the importance of participant satisfaction is being stressed in construction as well, despite the fact that only a few studies have been conducted thus far. Many stakeholders are involved in construction projects, and their satisfaction may result in having a direct effect on the successful delivery of the project. Construction projects have to do with several stakeholders; also, their satisfaction could straightforwardly impact the presentation of resulting projects. It is difficult to express participant satisfaction solely in terms of numbers. Achievement of specific objectives (successes) that lead to compensation of specific project goal could be achieved all through the recurring value–goal procedures at the design and development phases, when construction professionals are involved in the project. It can be inferred that participant satisfaction is critical to preserving the project's consistency and degree of collaboration.

There has been a substantial growth in the construction industry in the last decades. However, as this sector grows, there is also a growth in its effects on the environment. Owing to this fact, professionals in the sector are promoting practice focusing on how these environmental impacts caused by construction activities can be reduced to the barest minimum during and after construction. This study focuses on the environmental performance of construction projects with the goal of mitigating the negative environmental impacts of building construction. In this chapter, the environmental performance characteristics, forms of pollution that cause these environmental difficulties and the relevance of sustainable construction were not overlooked.

Climate change has been identified as a pressing social, environmental and economical challenge that has been unequivocally linked to human activity through latest Intergovernmental Panel on Climate Change (IPCC) reports. It is here to stay with us for generations to come and is already causing severe tribulations across the world. As nations devise policies to mitigate to climate change to stay within the 1.5 degrees Celsius target and small island developing states (SIDS) like Mauritius and the developing world in general find means to adapt to its consequences, a core shortcoming highlighted is the lack of community engagement and grassroots action so that policies permeate to concrete action. Of prime importance for this to happen is raising awareness on the climate change phenomenon, which has so far been a topic deemed complex for the general public, hence creating systemic barriers for climate action. The use of artificial intelligence (AI) can play a significant role in designing such community outreach programmes based on outcomes reported in literature in the educational sector in support of Sustainable Development Goal (SDG) 4: Quality Education. There is growing interest for a green lifestyle in the world population, and this chapter shows how the home can be used as a basic building block for allowing each household to contribute to climate action, while offering an effective case study to raise awareness on climate change through practical examples and demonstration, in support for SDG 11: Sustainable Cities and Communities. Based on an energy-water-materials nexus, the circular home concept is a clear contribution to SDG 13: Climate Action, with huge potential to use AI techniques and underpinning technologies to implement and optimise the efficacy of the proposed measures.

The construction sector has significantly evolved in recent decades, in parallel with a huge increase in the amount of data generated and exchanged in any construction project. These data need to be managed in order to complete a successful project in terms of quality, cost and schedule in the the context of a safe project environment while appropriately organising many construction documents.

However, the origin of these data is very diverse, mainly due to the sector’s characteristics. Moreover, these data are affected by uncertainty, complexity and diversity due to the imprecise nature of the many factors involved in construction projects. As a result, construction project data are associated with large, irregular and scattered datasets.

The objective of this chapter is to introduce an approach based on a fuzzy multi-dimensional model and on line analytical processing (OLAP) operations in order to manage construction data and support the decision-making process based on previous experiences. On one hand, the proposal allows for the integration of data in a common repository which is accessible to users along the whole project’s life cycle. On the other hand, it allows for the establishment of more flexible structures for representing the data of the main tasks in the construction project management domain. The incorporation of this fuzzy framework allows for the management of imprecision in construction data and provides easy and intuitive access to users so that they can make more reliable decisions.

The attraction of public private partnerships (PPPs) for governments is that the on-ground fructification of infrastructure projects is far higher than the traditional implementation route through public sector or departmental undertakings. Besides, time overruns are also considerably reduced. However, empirical evidence does not clearly establish that PPPs are cost efficient. This coupled with the risk intensity has impacted the long run flow of private capital to infrastructure PPPs and it therefore calls for a more scientific approach to management of profitability related risks. Appropriate management control systems (MCS) could be the answer, provided they can favorably impact profitability. Aggregating data from road, ports, airports, urban infrastructure, railways and power PPP ventures implemented in India, this chapter attempts to study the relationship between MCS and returns to sponsors through regression analysis. The study concludes that multiple MCS have a significant relationship with sponsors’ profitability.