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Facilities management (FM) organizations are pivotal in enhancing the resilience of buildings against climate change impacts. While existing research delves into the adoption of digital technologies by FM organizations, there exists a gap regarding the specific utilization of artificial intelligence (AI) to address climate challenges. This study aims to investigate the drivers and barriers influencing the adoption and utilization of AI by South African FM organizations in mitigating climate change challenges.

This study focuses on South Africa, a developing nation grappling with climate change’s ramifications on its infrastructure. Through a combination of systematic literature review and an online questionnaire survey, data was collected from representatives of 85 professionally registered FM organizations in South Africa. Analysis methods employed include content analysis, Relative Importance Index (RII), and Total Interpretative Structural Modeling (TISM).

The findings reveal that regulatory compliance and a responsible supply chain serve as critical drivers for AI adoption among South African FM organizations. Conversely, policy constraints and South Africa’s energy crisis emerge as major barriers to AI adoption in combating climate change challenges within the FM sector.

This study contributes to existing knowledge by bridging the gap in understanding how AI technologies are utilized by FM organizations to address climate challenges, particularly in the context of a developing nation like South Africa. The research findings aim to inform policymakers on fostering a conducive environment for FM organizations to harness AI in fostering climate resilience in built assets.

This study aims to examine the concept of innovative technologies and identify their impacts on the environmental sustainability of commercial properties in South Africa. This slow adoption is attributed to South Africa’s energy building regulation, SANS 204, which does not promote energy-conscious commercial property development. Furthermore, it was observed that buildings waste significant amounts of energy as electrical appliances are left on when they are not in use, which can be prevented using innovative technologies.

The researchers attempted to evaluate the impact of innovative technologies through an overarching constructivist mixed-method paradigm. The research was conducted using a multi-case study approach on green buildings which had innovative technologies installed. The data collection took the form of online, semi-structured interviews, where thematic analysis was used to identify emergent themes from the qualitative data, and descriptive statistics was used to evaluate the quantitative data.

It was found that implementing innovative technologies to reduce the energy consumption of commercial buildings could achieve energy savings of up to 23%. Moreover, a commercial building’s carbon footprint can be reduced to 152CO2/m2 and further decreased to 142CO2/m2 through the adoption of a Photovoltaics plant. The study further found that innovative technologies improved employee productivity and promoted green learning and practices.

This research demonstrated the positive impact innovative technologies have on energy reduction and the sustainability of commercial properties. Hence, facility managers should engage innovative technologies when planning a commercial development or refurbishment.

The purpose of this study is to explore the increased uptake of Artificial Intelligence (AI) technology by Facility Management (FM) organizations for enhanced operational efficiency and competitive advantage. While AI adoption in FM has been widely reported, limited attempts have been made to assess its impact on the social well-being of FM employees. To contribute towards addressing this gap, this study established the essential employee social well-being factors mostly impacted by the adoption of AI in South African FM organizations.

A four-stage design comprising a comprehensive review of literature, expert interviews, questionnaire census and focus group discussion sessions was used to elicit data from a sample of participants drawn from 22 South African FM organizations. The data was analyzed using a combination of content analysis, relative importance index and interpretative structural modeling for various data sets toward achieving the study’s objectives.

Sixteen employee social well-being factors, classified under job satisfaction, social relationship and knowledge development categories, respectively, were identified as being impacted by AI adoption in FM organizations. Furthermore, it was established that job security, job autonomy and professional status, which belong to the job satisfaction social well-being factor category, were deemed by FM employees as being mostly impacted by AI adoption.

The enhanced understanding of the impact of AI adoption on FM employees’ social well-being factors will contribute to the development of a collaborative intelligence framework for managing AI adoption in FM organizations toward engendering optimal AI–FM employee relationships for improved productivity.

Besides being one of the foremost studies to investigate the impact of AI adoption on FM employees’ social well-being, this study introduces a hierarchical framework of understanding employee social well-being factors based on multi-stakeholder perspectives.

Safety and security (S&S) are critical concerns in South Africa, especially in Cape Town, one of the country’s most crime-ridden cities. The University of Cape Town (UCT), situated on a large, open campus, has experienced increased malefaction. Facilities management (FM) services at universities bear the primary responsibility for providing S&S to their communities. To comprehensively understand and address the community’s demands regarding S&S, the current study was conducted to investigate the challenges specific to open universities. This study aims to determine whether implementing community-based FM (CbFM) principles and using technological innovations could offer a more effective and sustainable solution.

The study adopted interpretivist overarching case study methodology, which is ontologically based. A mixed-method approach was used to incorporate the strengths and limitations of the weaknesses of both methods. The data collection took the form of an online survey of the university community and semi-structured interviews with university executive management to obtain data from the single case study of UCT. Descriptive statistics were used to analyze the quantitative data, and thematic analysis was used to identify emergent themes from the qualitative data.

The study presents an overall view of the provision of S&S at UCT, the unique challenges faced by management and the main S&S issues affecting the community. Moreover, the study reveals that UCT has implemented community participation processes in the past with limited success. This is because the strategies implemented constitute a narrow perspective of community participation. Therefore, a much smarter and more inclusive perspective using technological innovation is required for successful community participation to occur and to be successfully used in providing S&S toward achieving future-proofing facilities.

This research has demonstrated the influence of CbFM and innovative technologies on the S&S of the open campus. Hence, future-proof facilities can be achieved when FM actively engages university communities in managing campuses through technological innovation.

This study investigates the barriers and drivers of using green methods and technologies (GMTs) in supportive educational buildings (SEBs) in South Africa, and assesses their impact on the circular economy (CE) in achieving net-zero carbon goals. While there has been extensive literature on green building technologies, there is limited research on the barriers and drivers of using GMT in SEBs, as well as their impact on the circular economy (CE) in achieving net-zero carbon goals.

This study adopts an interpretivist approach with an ontological basis, using an overarching case study of a SEB at the University of Cape Town (UCT). Semistructured interviews were conducted with executive UCT management, and a field survey of a UCT supportive education building was performed.

At UCT, multiple GMTs have been installed across various buildings to enhance monitoring and management of water and energy consumption. Moreover, initiatives to positively influence student behavior, such as water and energy-saving campaigns around UCT premises, have been introduced. The findings further indicate that UCT has recently emphasized the implementation of GMTs, resulting in improved resource efficiency, CE practices and progress toward achieving net-zero carbon targets for supportive education buildings and the university as a whole.

This research highlights the positive impact of GMTs on a SEB’s CE and net-zero carbon operations. As a result, facility managers should consider incorporating GMTs when planning the development or refurbishment of SEBs.

This paper examines the use of intelligent technologies in buildings and whether the use of smart technologies impacts the circular economy performance of buildings in terms of energy and water consumption, their marginal cost and the management decision time and quality, for building management companies.

The study is initiated through the detailed build-up of the proposition that employs a systematic literature review and adopts the case study research design to make a cross-case analysis of the information extracted from data. The data are derived from the operating costs of two buildings in which most advanced smart technologies are used in Cape Town and interviews with their facility managers. These data provide two research case studies. The results of the investigation are then analysed and linked back to the literature.

The results of the research suggest that the implementation of smart technologies to create intelligent infrastructure is beneficial to the circular economy performance of buildings and the time taken for management decisions. The results of the study have proven that the impact of smart technologies on the circular economy performance of buildings is positive, as it lowers the cost of utilities and decreases the time required for management decisions.

The research reported in this paper is exploratory, and due to its limited sample size, its findings may not be statistically generalizable to the population of high-occupancy buildings in Cape Town, which incorporate smart infrastructure technologies within their building management systems (BMSs). Also, the empirical data collected were limited to the views and opinions of the interviewees, and the secondary data were obtained from the selected buildings.

The findings suggest that investment in smart technologies within buildings is of significant value and will improve the circular economy performance of buildings in terms of low energy and water use, and effective management decisions.

The results imply that there would be more effective maintenance decisions taken by facilities managers, which will enable the maintenance of equipment to be properly monitored, problems with the building services and equipment to be identified in good time and in improved well-being and user satisfaction.

The study provides evidence to support the concept that advanced smart technologies boost performance, the time required for management decisions and that they enable circularity in buildings. It supports the proposition that investment in the more advanced smart technologies in buildings has more positive rewards.

As a flood-prone region in Iran, Golestan province has encountered various disasters in its history. The last one occurred in March 2019, affected Aq-Qala County and caused irreparable physical, economic, social and environmental problems. The purpose of this study is to investigate the process of providing shelter in emergency, rehabilitation and reconstruction phases after the floods in the villages of Aq-Qala.

A research method is a hybrid approach. The collection of data involved a combination of qualitative and quantitative approaches in addition to reviewing the documented texts in resources to collect the required data using observations, field survey activities, questionnaires and in-depth interviews. From April 2019 to December 2019, nine separate visits have occurred to collect the needed information.

This paper shows dissatisfaction with providing shelter and attempts to identify the factors which caused the challenges. The findings revealed issues such as hygienic problems in collective camps, lack of thermal resistance in temporary accommodations and rising material prices. These findings lead to a contributive list of suggestions avoiding the recurrence of the harms in the future.

This study proposes solutions and approaches to improve the post-flood settlement process for possible floods in the future such as equipped camps, proper temporary housing, monitoring the reconstruction and the price of the materials. If these approaches are used by authorities and people in similar rural areas, the long-term effects of inadequate post-flood shelter can be reduced.