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Reconstruction of old buildings is often necessary after prolonged usage, but these projects encounter various complexities, leading to their failure. However, there is a lack of studies that focus on investigating the complexity of old building reconstruction initiatives. Thus, this study aims to examine the complexity of reconstruction projects for old buildings in Vietnamese urban areas.

Through a literature review and discussions with experienced practitioners, 12 significant complexity factors were identified. The study then utilized the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique to analyze the interrelationships among these complexity factors.

The findings revealed intricate interdependencies among the complexity factors, visualized in a complexity map. The map highlighted the critical complexities of site compensation, clearance and the long project duration. Furthermore, a causal diagram categorized the complexity factors into net-effect and net-cause groups.

By examining the relationships and interactions among these factors, the study emphasizes the interconnected nature of complex systems and the influence of one factor on others. Therefore, decision-makers and stakeholders involved in reconstructing old buildings are suggested to possess a comprehensive understanding of these interdependencies to ensure effective decision-making.

Demand forecasts are a key component of planning efforts and are crucial for managing core operations. This study aims to evaluate the use of several machine learning (ML) algorithms to forecast demand for residential construction in Jordan.

The identification and selection of variables and ML algorithms that are related to the demand for residential construction are indicated using a literature review. Feature selection was done by using a stepwise backward elimination. The developed algorithm’s accuracy has been demonstrated by comparing the ML predictions with real residual values and compared based on the coefficient of determination.

Nine economic indicators were selected to develop the demand models. Elastic-Net showed the highest accuracy of (0.838) versus artificial neural networkwith an accuracy of (0.727), followed by Eureqa with an accuracy of (0.715) and the Extra Trees with an accuracy of (0.703). According to the results of the best-performing model forecast, Jordan’s 2023 first-quarter demand for residential construction is anticipated to rise by 11.5% from the same quarter of the year 2022.

The results of this study extend to the existing body of knowledge through the identification of the most influential variables in the Jordanian residential construction industry. In addition, the models developed will enable users in the fields of construction engineering to make reliable demand forecasts while also assisting in effective financial decision-making.

Formulating strategic decisions poses a significant challenge for construction organizations, profoundly impacting their overarching strategic management. The success of an organization’s strategy relies on how information is managed and decisions are executed. However, the literature has a limited understanding of the connection between information quality and strategic decision-making, particularly in construction business performance. This study aims to bridge this gap by exploring how information quality mediates the relationship between strategic decision-making and the performance of construction businesses in New Zealand.

This quantitative study aims to fill this gap by assessing how information quality shapes strategic decision-making practices, impacting construction organizations’ performance. Analysing 102 viable responses through partial least squares structural equation modeling structural equation modelling offers partial support to the research framework.

The study used statistical analysis to gauge the impact of adopting strategic management practices on construction business performance, considering the mediation of the quality of information within New Zealand’s context. It affirmed a positive correlation between strategic decision-making management and construction business performance, underpinned by the mediation of quality of information.

This study underscores the critical role of information quality in evaluating strategic decisions for bolstering construction business performance. In essence, it affirms that enhancing the performance of construction organizations via strategic decision-making is intrinsically linked to the quality of information.

This study makes a noteworthy contribution by establishing connections between decision importance, process effectiveness, information quality, intuition in decision-making and model development, providing valuable insights to the field.

Holy cities in India are seeing tremendous gentrification. This study aims to investigate the effect of the changing lifestyle of people towards spirituality and the changing lifestyle's impact on consumer buying behavior on properties in Indian holy cities which has not been studied anecdotally.

The research is exploratory in nature. A questionnaire has been sent to collect primary data through SurveyMonkey. Simple random sampling was used to collect a sample of 450 respondents which was also verified using G* software. The data were analyzed using descriptive statistics and partial least square–structured equation modeling (PLS-SEM).

Findings obtained through the structural model using bootstrapping technique suggest that intrinsic and extrinsic factors are attracting tourists leading to an increase in the demand for real estate in holy cities.

The research findings may vary as per the cultural differences and belief in spirituality, which is subject to perceptual biases in different holy cities.

The traditional determinants of property buying behavior are considered inadequate to attract real estate investments. The inclusion of these behavioral aspects – intrinsic and extrinsic factors may improve the investment inflows in India.

Spirituality connects to the concept of behavioral real estate, where the decision to buy property is largely affected by the emotional attachment of people.

This research adds value to fill the gap by finding out the latent determinant – emotional reasons impacting transnational gentrification in India.

The construction industry in emerging economies have suffered from productivity issues related to poor resource management as a result of theft. Therefore, this study aims to carry out an exploratory factor analysis of the key causes of theft in the construction industry in Nigeria.

The methodology entailed a review of the literature which identified 58 causes of construction theft. The causes were operationalized through a Likert-scale questionnaire survey, which was revised in a pilot study with ten industry experts. The questionnaire was further distributed to experienced construction professionals in Nigeria. A total of 63 respondents participated in the study, and the results were analyzed through an exploratory factor analysis.

A Kruskal–Wallis test showed no difference in perception of the various group of respondents, while Cronbach alpha test indicated an acceptable level of internal consistency and reliability. The top causes from the literature review were determined through descriptive statistics. However, a Kaiser–Meyer–Olkin measurement resulted in the exclusion of ten causes, and exploratory factor analysis yielded twenty causes in six dominant factors that together account for 55.7% of the variance. The six dominant factors were general theft prevention measures, site security measures, site layout planning, management of materials and equipment, construction project management and policy and safety management.

The limited amount of research on construction site theft in emerging construction environments such as Nigeria contributes to poor construction productivity. This study advances our knowledge of construction site theft and is of significant value to construction stakeholders in effective material and resource management through theft mitigation measures.

Existing Neighborhood Sustainability Assessment (NSA) tools such as “Leadership for Energy and Environmental Design - Neighborhood Development” (LEED-ND) and “Building Research Establishment Environmental Assessment Method” (BREEAM Communities) are widely criticized for a lack of transparency in the selection of indicators and an unbalanced focus on specific sustainability dimensions.

This paper asks how the expectations and use values of the professionals and residents involved in developing, designing, managing and living in a sustainable neighborhood can shape sustainability indicators that affect progress towards project goals. Taking as its focus The Sustainable City (TSC), a neighborhood in Dubai, United Arab Emirates (UAE), the paper develops data from in-depth, go-along interviews with 46 different actors.

Findings indicate that when given the opportunity to express their opinion, many actors will prioritize metrics different than the metrics dictated to the by sustainability experts and international rating systems. The findings suggest that NSA tools should place greater emphasis on local factors, public engagement and operational concerns.

The paper provides a method that any community can replicate to better understand the different use values of local actors and establish its own NSA tool. This can help experts learn how design, management and operational decisions interact to impact different dimensions of performance.

This paper recognizes sustainable neighborhoods as spaces with multiple identities. Hence, the indicators used to evaluate these neighborhoods need to be based on the expectations and use values of different actors. This paper proposes using the priorities of different local actors to reshape how these neighborhoods are assessed.

This study aims to explore the level of adoption of Construction 4.0 (C4.0) technologies and of Lean Construction (LC) ambidexterity capability in China’s construction industry. By incorporating C4.0 and LC ambidexterity into a sociotechnical systems (STS) framework, this research provides practical insights for construction practitioners and companies seeking C4.0 and LC.

The study adopts the questionnaire survey method. Data was obtained from Chinese construction professionals working on projects using C4.0 technologies. The data were analysed using mean score ranking and three nonparametric techniques, including the Wilcoxon signed-rank test and the Spearman rank correlation.

According to the ranking analysis, building information modelling and offsite construction have the highest adoption level, while additive manufacturing and blockchain rank lowest. Digital technology is more widely used in China’s construction industry than in physical technology. Many C4.0 technologies are significantly correlated with LC ambidexterity. Based on the STS perspective, we propose a holistic approach that incorporates C4.0 technologies and LC ambidexterity.

Conceptually, the study incorporates C4.0 and LC ambidexterity into the STS framework. Empirically, this study fills the gap in the current literature by exploring the level of C4.0 technology adoption in the Chinese construction industry, as well as the level of LC ambidexterity capabilities. Construction companies can use this framework to make strategic decisions regarding investments in LC practices and the adoption of C4.0 technologies, such as investing in staff skill training and new technology deployment to adapt to the ever-changing environment.

This study aims to obtain governance strategies for managing the complexity of megaprojects by analyzing the impact of individual factors and their configurations using the fuzzy-set qualitative comparative analysis (fsQCA) method and to provide references for project managers.

With the continuous development of the economy, society and construction industry, the number and scale of megaprojects are increasing, and the complexity is becoming serious. Based on the relevant literature, the factors affecting the complexity of megaprojects are determined through case analysis, and the paths of factors affecting the complexity are constructed for megaprojects. Then, the fsQCA method is used to analyze the factors affecting the complexity of megaprojects through 245 valid questionnaires from project engineers in this study.

The results support the correlation between the complexity factors of megaprojects, with six histological paths leading to high complexity and seven histological paths leading to low complexity.

It breaks the limitations of the traditional project complexity field through a “configuration perspective” and concludes that megaproject complexity is a synergistic effect of multiple factors. The study is important for enriching the theory of megaproject complexity and providing complexity governance strategies for managers in megaproject decision-making.

The New Zealand (NZ) construction industry significantly impacts the country's economy and is one of the largest sectors in terms of total employment. However, a persistent and pressing need for improvement exists. Meeting the ongoing demand for housing and urban development requires enhancing residential construction productivity. The purpose of this paper is to determine what factors improve construction productivity in the NZ residential construction sector.

Data were obtained from construction industry bodies using a semi-structured online questionnaire survey. From 305 online questionnaires administered, 106 samples were completed by residential industry construction professionals across NZ. The data were analysed using descriptive and inferential statistics to establish the importance of empirical factors for improving construction productivity in the NZ residential construction sector.

The Garrett ranking technique revealed this study's top five factors for enhancing construction productivity: adequate design, communication, quality management (QM), supervision and organizational training. Other factors, such as unskilled workers, skilled workers, reworks and employee motivation, ranked less important.

While providing a valuable exploration of factors that can positively impact residential construction productivity in NZ, this study contains certain limitations. The study's focus on a specific geographic location and a small sample size (n = 106) may restrict the generalizability of its findings to other regions or countries. Furthermore, the reliance on self-reported data from industry professionals introduces the possibility of bias or inaccuracies in the results. In addition, this study did not investigate the potential influence of external factors, such as economic conditions or regulatory changes, on residential construction productivity. Despite these limitations, this study presents a foundation for future research on this topic. Future research could address these limitations by conducting multi-country studies and using objective productivity measures to provide a broader context. In addition, open-ended questions could be used to collect more detailed qualitative data, enhancing this study's dependability. This methodological constraint could have omitted important experiential nuances, which could be explored in future research to provide more comprehensive and rigorous findings.

Research studies indicate that several construction productivity factors have remained unchanged for over three decades (Arditi and Mochtar, 1996; Hasan et al., 2018). The implications of this study are significant for the residential sector in NZ. By identifying the key factors that can improve productivity in the sector, such as complete design and specifications, effective communication, quality management, adequate supervision, training, skilled labour and employee motivation, this study provides valuable insights for industry practitioners and policymakers. It expands the existing productivity literature around factors for improving NZ residential construction productivity. One important implication of this study is the link between QM and improved productivity, highlighting the significance of strategic organizational investments in QM and the added opportunity presented to policymakers concerning industry-wide improvements. Moreover, the findings suggest that investing in worker training is essential. Ensuring workers possess the necessary skills and knowledge to perform their tasks efficiently can enhance productivity and project outcomes. In conclusion, this study's findings emphasize the factors that can improve construction productivity in residential projects in NZ, ultimately leading to improved outcomes for all stakeholders.

This research offers a unique perspective on improving residential construction productivity in NZ by identifying and analysing specific factors that can enhance efficiency across the sector. It provides novel findings and valuable insight into possible organizational improvement strategies yet considered in the NZ residential sector.

The importance of lean and sustainability integration in sustainable construction (SC) has been extensively studied. However, a practical and thorough implementation methodology addressing the project life cycle phases is still inadequate. The present study has developed a novel phase-wise sustainable–lean implementation methodology for high-rise residential projects.

The current study has identified the 50 direct conceptual interactions between 11 lean principles and 11 sustainability criteria encompassing 44 different attributes covering 174 sustainability actions. A panel of nine experts validated these interactions, and 50 integration vectors were proposed addressing different phases of the project life cycle of high-rise residential buildings. The experts also analysed the identified integration vectors for their current and likely future implementation in high-rise residential projects.

The interactions between lean and sustainability principles led to the development of a phase-wise implementation methodology. The experts' survey responses on the current level of implementation revealed that 40, 32 and 28% of integration vectors were implemented rarely, sometimes, and frequently, respectively. For likely future implementation, 28 and 72% integration vectors were reported as very likely and extremely likely to implement, respectively. This survey response highlighted the usefulness of identified integration vectors for enhancing the sustainability of high-rise residential projects.

The proposed sustainable–lean implementation methodology acts as a comprehensive guideline for implementing a lean approach to achieve the objectives of SC in high-rise residential projects. This may facilitate the transition from conventional to sustainable building practices using a lean approach.