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This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

This paper aims to explore the characteristics of lifting accidents and the significance of influencing factors and explain the causes from the perspective of human factors, thereby achieving a more accurate understanding of and prevention of lifting accidents.

A mixed simulation model for prefabricated component lifting is established by combining discrete event simulation (DES) with the system dynamics (SD) method. In addition, essential parameters and relationships within the system dynamics model are determined through survey questionnaires. Finally, the human factors analysis and classification system (HFACS) is used to analyze the cause of the accident.

The results show that workers falling from height and workers struck by objects are the most frequent types of lifting accidents. In 2072 experiments, these two types of accidents occurred three and five times, respectively. Besides, the links of “crane movement,” “component binding,” “component placement” and “component unhooking” are particularly prone to lifting accidents. In addition, the completeness of emergency plans, failure to observe the status of the tower crane and lack of safety education and training have emerged as primary influencing factors contributing to the occurrence of lifting accidents.

The findings of the study can serve as a reference basis for practitioners, enabling them to preemptively identify possible risk accidents and adopt corresponding measures to prevent them, ensuring the safety and property of practitioners. Additionally, targeted suggestions and innovative ideas are provided to enhance the safety guarantee of the lifting industry and promote its healthy and stable development through a more concrete theoretical foundation and practical guidance.

Humans now enjoy a better life because of Artificial Intelligence (AI). AI has a significant impact on the creation of smart cities. Modern applications based on big data, Internet of Things (IoT) systems, and deep learning require extensive use of complex computational solutions. Thus, the following problems arise: (1) what are smart cities? (2) what is AI? (3) How is AI used in smart cities? To respond to this problem, the following objective was set: to map how AI is used in smart cities. For this purpose, a qualitative methodology based on a narrative analysis of the literature was used. It is concluded that AI and smart cities are complementary technologies that can assist cities in tackling difficult issues including public safety, transportation, energy management, environmental monitoring, and predictive maintenance. This chapter’s findings, while broadly applicable, offer valuable insights into the Gulf region’s unique context, where rapid urbanization and technological adoption intersect with cultural and environmental considerations. The integration of AI in smart cities presents a promising avenue for the Gulf region to address its specific challenges and leverage its economic and infrastructural strengths, thereby contributing to the broader goals of innovation, development, prosperity, and well-being as envisioned in the region’s Vision 2040 initiatives.

This paper aims to model the impact of corporate social responsibility practices (CSRP) on job seekers’ organisational attractiveness (JSA) with particular reference to two Indian states, i.e. Andhra Pradesh (AP) and Odisha (OD). Further, the paper examines whether there are any significant variations in the perception of job seekers in these two states.

The sample for this exploratory research consisted of 943 business management students of AP and OD. The model was developed using the hierarchical component model method, and the associations were examined using partial least squares structural equation modeling (PLS-SEM). Furthermore, PLS-multi group analysis (PLS-MGA) was used to analyse the specific differences between two sample groups.

The study found that the CSR constructs, i.e. economical, legal, ethical and philanthropic, have a positive significant effect on CSRP for both groups of job seekers. The study also argued that the company selection by job seekers based on high or low CSR practices has no moderating effect on both sample groups for economical, legal, ethical and philanthropic dimensions. Further, the result revealed that the age and gender variables could not make any significant differences in the perceptions of job seekers.

The study provides research-based insights to relevant stakeholders (institutions, corporate, government and policymakers) that would be used in formulating strategies to strengthen the relationship between CSRP and JSA.

The study investigates CSR’s effect on organisational attractiveness from the theoretical lens of Carroll’s pyramid for two groups of job seekers. Limited studies have examined the complexity of this association with such a research context. The result guides educators, corporate, governments, practitioners and job seekers working on CSRP and JSA.

Following Howard Bowen's legacy for responsible business practices, together with the actual growing pressure of societal problems, such as climate change, social inequality, geopolitics instability, etc., business leaders all around the world are being asked, if not demanded, to show and act as action persons who effectively contribute to a better common value creation. This confluence of situations has led to many CEOs feeling pressured to take a stand in sociopolitical themes, many times outside their businesses' areas, which have become known as CEO activism.

This study aimed to explore if and how this international growing trend is manifesting in the Portuguese context, by exploring the perspective of Portuguese CEOs on the topic, the course of action that they are taking, and how they evaluate risks and opportunities.

For these purposes, we implemented a qualitative methodology based on interviews to 24 Portuguese CEOs and used thematic analysis to explore them. Our findings reveal that, although Portuguese CEOs are aware of this trend, they acknowledge both risks and opportunities, and their activism is still incipient. Plus, they strongly believe that CEO activism must be aligned with the values and mission of the organization they represent. Finally, Portuguese CEOs are convinced of activism being genuine, and therefore should be first implemented within the organization, which is where most of them focus their action. Our work provides an original mapping of the CEO activism landscape in Portugal and an insightful discussion of the CEO's perspective on this growing phenomenon.

This paper aims to understand the two-way interaction between corporate social responsibility (CSR) and the attractiveness of organization to job seekers (AOJS).

A system dynamics model is developed in the form of a causal loop diagram (CLD) that explains the CSR-AOJS interaction dynamically. To test the credibility of the developed model, the survey data are used to validate the causal relationships in the CLD.

This study found that developing an effective strategy or tool by capturing various essential CSR elements can attract potential job seekers.

The developed model is relevant to policymakers, decision-makers and managers when strategizing the CSR plan to attract potential job seekers.

The significance of event tourism in destination development underscores the importance of assessing the quality of events and their sustainability for competitiveness. This study investigates tourists’ perceptions of service quality and sustainability at the “Biggest São João in the World” event in 2023. Employing a quantitative approach, we conducted field research using questionnaires based on the Tourqual model, integrating sustainability indicators to address environmental impacts associated with such events. Data collection took place between June and July 2023, with a non-probabilistic convenience sample of 709 visitors. Descriptive statistics were applied to the 2022 survey data (397 respondents), on the 2023 data (709 respondents). Results reveal that the event’s diverse activities received the highest average rating at 4.03, while the use of sustainable transport during the event garnered the lowest rating at 1.93. This emphasizes the need for event organizers to implement continuous improvement plans, focusing particularly on areas with critical evaluations to enhance visitor satisfaction. This study’s originality and innovative approach contribute valuable insights for event managers and researchers and promote both local development and environmental awareness.

Despite several attempts to integrate building information modeling (BIM) with building circularity assessment (BCA), no systematic review has yet been carried out on this topic to the best knowledge of the authors. The objective of this review is to fill this gap by reviewing the current attempts, identifying the tools and exploring the state-of-the-art in BIM and BCA.

A systematic literature review (SLR) methodology was employed. A total of 30 documents published between 2015 and 2023 were selected and analyzed across the concept, methodology and value dimensions.

There has been an increase in the development of BIM-based BCA tools in recent years, with the Netherlands taking the lead. Most tools developed were based on the material circularity indicator (MCI) and by using Autodesk Revit as BIM software. Three integration approaches for BIM with BCA were identified: (1) using an external platform; (2) linking an external database to BIM and (3) within the BIM environment. The review has revealed that still there is no standard for BCA, and interoperability and lack of circularity databases are the major challenges.

Although the paper has made contributions, it is important to recognize certain limitations. One of these is the inability to explore all the tools in depth as some of them are not available or accessible. Another limitation is the relatively small number of studies that were reviewed, primarily because there is a lack of research in this area due to the BIM-based BCA is still in its infancy compared to the BIM-based LCA.

This study contributes to providing a comprehensive up-to-date overview of recent advancements in BIM–BCA integration, as well as a framework for understanding its concept, methodology and value dimensions. It also highlights significant areas where practitioners and researchers can identify knowledge gaps and future research directions.

The impact of dependence on self-care on people’s lives is very significant, with consequences for the person and their caregivers. The purpose of this study is to map the evidence on the factors that influence the empowerment of the person dependent on self-care on returning home.

Scoping review according to the criteria proposed by the Joanna Briggs Institute: population (people with a dependence on self-care), concept (factors that influence training) and context (return home after hospitalization in a medical-surgical context). The research was carried out from March 1 to April 30, 2022, in the databases CINAHL and MEDLINE (via EBSCO), Scielo, LILACS, Cuiden and MedicLatina; Gray literature searched RCAAP, DART-Europe and OpenGrey. Studies published in Portuguese, Spanish and English were included, with no time limit.

One hundred and eighty-one articles were obtained, which, after analysis according to the criteria, resulted in seven studies included for review, ranging from 2007 to 2021, with a level of evidence between 2. c and 4. a (according to Joanna Briggs Institute), and two thematic areas/four categories emerging.

The need for information and training, the relationship and proximity with the health-care team, the design of nursing care targeted at the person’s level of dependence, education, gender, type of surgical intervention and postoperative period, physical space and lack of privacy and audiovisual media.

The perception of these factors proves to be important in the person’s training process, with the nurse’s role being highlighted due to their emphasis on the transition home.