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This paper aims to analyze the impact of sustainability measures taken during the design and construction phases, by examining two categories of sustainability: energy efficiency and reducing carbon emissions and material selection and waste management. These aspects are examined from the perspectives of long-term building performance and maintenance practices, as well as user/tenant satisfaction.

This study includes a literature review related to the two topics under consideration, followed by a comparative case study analysis of four projects to determine practical validity. All case studies in this paper used a semi-structured survey with various project stakeholders, which helped the authors identify measures taken as well as obstacles and challenges during the process.

According to the four case studies, adequate attention should be paid to the two areas of interest during a project’s design and construction phases. Including case studies from around the world (four case studies from three different countries) offers insights into effective sustainability practices in building design and construction, providing instances of successful implementation and emphasizing the obstacles and potential when incorporating sustainability into the design and construction phases.

The findings also show that design and construction participants and companies should reduce waste generation and carbon emissions. In addition, they should make decisions on material selection to enhance projects’ sustainability and to contribute to creating a habitable planet for the future.

The influence of the design and construction phases on long-term project sustainability is of major importance and concern to users, owners, designers, contractors and facility managers. This study illustrates the necessity of including sustainability measures in the design and construction phases, highlighting the importance of sustainability in building design and construction through effective implementation techniques and interdisciplinary teamwork to realize sustainable goals.

This paper is based on the personal connections of the four authors to Shivaji Park, the largest public space in Mumbai. Three of the authors are childhood friends and were once long-term residents of that area. The focus of this article is Shivaji Park, anecdotally the largest park in the island city of Mumbai, with its historical connotations and its ongoing role as a relational and cultural artefact in the lives of these authors. The ongoing member status of all four authors in connection with the public space is explored despite all of them now ceasing to be locals.

This article uses a qualitative approach utilising informal conversations between the four authors recorded on zoom as the research method. Supported by belonging and emotional reflexivity as conceptual frames, it investigates how the spatial context fosters a binding relationality, which is ongoing despite the now disparate locations of the authors.

Based on a critical analysis of the recorded conversations between the authors the findings highlight that belonging/unbelonging centres around emotionally tinged representations of place.

The core of this paper rests in the emotional connections between the authors based on their collective memories with a public space and its surrounding areas as a focus. The use of informal conversations is crucial in teasing out nuanced aspects of data collected based on human relationalities. The paper emphasises the repercussions of ongoing changes stemming from urban progress. They incur emotional and human costs through a “culling” of connections and belongings.

This chapter focuses on a case study of Kareem Exchange Company and its use of big data analysis to detect and prevent fraud and suspicious financial transactions. The chapter describes the various phases of the big data analysis cycle, including discovery, data preparation, model planning, model building, operationalization, and communicating results, and how the Kareem Exchange Company team implemented each phase. This chapter emphasizes the importance of identifying the business problem, understanding the resources and stakeholders involved, and developing an initial hypothesis to guide the analysis. The case study results demonstrate the potential of big data analysis to improve fraud detection capabilities in financial institutions, leading to informed decision making and action.