Real Construction Research Articles

LATENT DEFECTS: NAVIGATING THE DEFECTS LIABILITY PERIOD AND LEGAL ACTION DEADLINES FOR HOMEBUYERS IN MALAYSIA

This article provides a comprehensive understanding of latent defects in real property construction and a guide for homebuyers to navigate the defects liability period and legal action deadlines in Malaysia. Latent defects, hidden flaws that may emerge over time, pose significant risks to homebuyers. By uncovering the nature and implications of these defects, this article highlights the importance of recognising and addressing them within the defect liability period. It also explores the legal action deadlines set by the limitation legislation, emphasising the need to understand and adhere to these time limits for seeking remedies. This article serves as a valuable guide for homebuyers purchasing real properties from housing developers, ensuring they are equipped to identify and address latent defects, make effective use of the defect liability period, and initiate legal actions within the prescribed timelines.

Research on Personal Skills That Architects Should Focus on Improving in Professional Career Development

With the current downturn in the real estate and construction industries, the construction job market is saturated, and architects are facing an urgent employment crisis. Architectural education should understand the skill requirements of individuals in the labor market and make adjustments accordingly. This study examines the evaluation of and demand for skills from the perspective of employers. A research questionnaire was constructed based on the Kano theoretical model and distributed to 810 practitioners, and the results were analyzed. The results of the data analysis of demand attributes, importance, and group differences showed that the construction industry pays the most attention to strengthening professional soft abilities, while improving personal comprehensive abilities and maintaining professional hard abilities can support architects in maintaining strong competitiveness in the job market. Furthermore, different groups and regions have different needs for architectural skills. The cultivation of skills in colleges and universities must be targeted. This study provides an adjusted direction for architectural education and training and also provides guidance for architectural practitioners in improving their skills and expanding their career development with the trend of industry saturation.

Three‐dimensional characterization of particle morphology in natural gravel and blasted rock fragments using SfM‐MVS photogrammetry

AbstractThis study aims to develop a high‐precision and cost‐efficient method for the three‐dimensional reconstruction of large particles in natural gravel and blasted rock fragments, utilizing Structure from Motion (SfM) and Multi‐View Stereo (MVS) techniques. The proposed approach was applied to characterize the three‐dimensional morphology of rockfill dam materials at a real construction site. Particle shape was quantitatively analyzed using shape indices of sphericity, convexity, and angularity. The predominant morphology of natural gravel is characterized as slightly elongated and slightly flat, while rock fragments are slightly elongated and not flat. Probability density distributions of shape indices follow a skewed normal distribution: sphericity and convexity show leftward skewness, whereas angularity is right‐skewed. Skewness parameters of sphericity and angularity are consistent between natural gravel and blasted rock fragments, indicating comparable shape asymmetry. Convexity skewness is significantly higher in natural gravel compared to rock fragments, by approximately an order of magnitude. The relationship between size and particle shape shows that form ratios and associated shape descriptors change linearly with the logarithm of size; larger particles approach spherical or cubic forms. The innovative measurements contribute to the particle shape data set of rockfill dam materials, providing valuable insights into the three‐dimensional and statistical morphological characteristics of relatively large particles in natural gravel and blasted rock fragments. This approach enhances understanding of particle morphology's impact on the mechanical behavior of granular materials.

Determinants of Earnings Management: The Moderating Role of Firm Size

This study aims to provide empirical evidence on the impact of financial distress, financial ratios, and corporate governance on earnings management, using company size as a moderating variable. This study focuses on real estate, construction, and property companies listed on the Indonesia Stock Exchange (IDX) between 2020 and 2022, with a sample of 54 companies selected through purposive sampling. Data analysis was conducted using multiple linear regression to test the direct effect of independent variables on earnings management and interaction test to evaluate the moderating role of firm size. The research findings show that financial distress affects earnings management, which suggests that companies under financial stress are more likely to rely on earnings management to present favorable earnings performance. In contrast, financial ratios do not affect earnings management, which suggests that well-performing firms are less likely to engage in the practice. Good corporate governance, represented by the proportion of independent directors, audit committee and managerial ownership, also affects earnings management. In addition, firm size moderates the relationship between financial distress and earnings management, with larger firms showing a greater tendency towards earnings management when facing financial challenges. These results underscore the importance of considering financial conditions and firm size when monitoring earnings management, as larger firms may be more prone to earnings management practices under certain conditions.

Metal-organic frameworks encapsulating gold nanoclusters and carbon dots for ratiometric fluorescent detection of formaldehyde in real food samples, construction materials and indoor environments.

Anovel fluorescence sensing nanoplatform (CDs/AuNCs@ZIF-8) encapsulating carbon dots (CDs) and gold nanoclusters (AuNCs) within a zeolitic imidazolate framework-8 (ZIF-8) was developed for ratiometric detection of formaldehyde (FA) in the medium of hydroxylamine hydrochloride (NH2OH·HCl). The nanoplatform exhibited pink fluorescence due to the aggregation-induced emission (AIE) effect of AuNCs and the internal filtration effect (IFE) between AuNCs and CDs. Upon reaction between NH2OH·HCl and FA, a Schiff base formed via aldehyde-diamine condensation, releasing hydrochloric acid. The acid triggered the degradation of ZIF-8, releasing CDs and AuNCs, and thereby shifting the fluorescence to blue as the CDs disperse. The nanoplatform demonstrated high sensitivity (LOD of 0.26-2.19 μM), exceptional selectivity, and rapid response time (<1 min) toward FA. Additionally, test strips and hydrogel films integrated with smartphones were prepared for on-site and visual detection of FA. The portable and smartphone-assisted test strips effectively detected indoor FA gas, while wearable and intelligent hydrogel films provided reliable surface measurements of FA on fruits and vegetables. Real sample analyses achieved satisfactory FA recoveries (99.06-115.30%) with relative standard deviations (RSD) from 1.86% to 3.81%. The innovative sensing nanoplatform served as a promising approach for FA detection in food, construction materials, and indoor air quality, offering both analytical accuracy and convenient visualization.

A meta-analysis of ESG factors in the real estate investment trusts sector: exploring their impacts on REITs performance

PurposeThis study aims to analyse the inconsistencies found in previous research regarding the impact of environmental, social and governance (ESG) factors on real estate investment trusts’ (REITs) performance. By identifying the individual contributions of each ESG pillar, the research seeks to clarify ESG’s role in determining REIT outcomes.Design/methodology/approachThe study conducts a meta-analysis of 26 selected studies from a pool of over 300 academic papers that investigate the relationship between ESG factors and REIT performance. The meta-analysis aggregates regression findings from these studies, and logistic regression models are used to examine the distinct effects of each ESG factor on REIT performance.FindingsThe results indicate that the environmental and social pillars significantly influence the relationship between ESG and REITs performance. The social factor consistently shows a positive and significant effect, while the environmental factor is significant but with an unclear direction of influence. The governance factor does not show a significant impact, suggesting that under the current REITs regulatory framework, governance is less influential. The results address the distinct contribution of ESG factors in shaping REIT outcomes across different market contexts and time periods. Moreover, the positive impact of the social pillar aligns with Freeman’s (1984) social impact hypothesis, which suggests that business practices associated with stakeholders’ interests positively affect financial performance.Originality/valueThis study enhances the understanding of ESG factors’ impact on REITs by being the first to systematically analyse the underlying reasons for the varied outcomes in previous research. It is also the first attempt to employ meta-analysis in exploring the theoretical foundations of ESG effects within the real estate and construction sectors. The findings assist investors in making more informed decisions based on ESG components and offer guidance for policymakers in crafting regulations that better reflect the influence of ESG factors.

Investigating the Connection Between Income Inequality, Urbanization, and Real Estate Prices: A Comparative Analysis

This paper analyzes relationship of real estate, urbanization, road construction, and income disparity in the same system. It can theoretically solve problem of the excessive income disparity and slow urbanization. The author will utilize the literature research approach to clean up a lot of data in order to assess and summarize the three keywords in detail. This paper reviews and summarizes the literature at home and abroad from the perspective of three pairs of economic relations: (1) The impact of real estate price fluctuations on income disparity (2) the impact of urbanization on real estate prices (3) The impact of urbanization on income inequality. The relationship between the three are analyzed in the context of urbanization in the new era, From the literature research, it is concluded that the rise in real estate prices enlarges the gap of income inequality. (1) Real estate prices have an unsustainable impact on the urbanization path (2) The "negative effect" of the urbanization development model on the income gap will be greater than the "positive effect" Finally, according to the above analysis, it is concluded that urbanization can narrow the income gap between urban and rural areas through the medium of the real estate industry. Based on the research conclusions, the following suggestions are drawn: (1) Long-term development of urban planning: It is recommended to have more reasonable urban planning, avoid over-development of core cities, promote the development of small and medium-sized cities, and alleviate the upward pressure on real estate prices.

Optimizing Generalized Linear Models for Real Estate Investment Risk: A Hybrid Genetic Algorithm and IRLS Approach

Generalized Linear Models (GLMs) serve as a powerful extension of traditional linear regression, enhancing statistical analysis capabilities. This study employs a GLM to forecast the Return on Investment (ROI) within Nigeria’s real estate and construction sectors, utilizing a comprehensive dataset that includes data from the Nigerian Stock Exchange (NSE) and macroeconomic indicators from the National Bureau of Statistics (NBS) and the Central Bank of Nigeria (CBN), spanning 2017 to 2023. The model integrates critical macroeconomic indicators, including Gross Domestic Product (GDP) growth, the Consumer Price Index (CPI), Interest Rates (IR), and the Unemployment Rate (UR), while also considering interaction effects and non-linear terms to enhance predictive accuracy. Two methods were used to assess the GLM: Genetic Algorithms (GLM-GA) and Iteratively Reweighted Least Squares (GLM-IRLS), both of which revealed significant insights. Adjusted R2 values ranged from 0.68 to 0.73, with the highest in 2019 (0.73) and the lowest in 2021 (0.68). The Bayesian Information Criterion (BIC) exhibited variation, with values between 365.50 in 2019 and 386.30 in 2021, indicating differing model efficiency across years. Investment risk metrics, such as Value at Risk (VaR) and Conditional Value at Risk (CVaR), showed upward trends, with VaR increasing from 7.50 in 2017 to 9.20 in 2022, and CVaR rising from 7.00 to 8.70 in the same period, reflecting heightened risk exposure. The findings underscore the sensitivity of ROI predictions to macroeconomic conditions and highlight the challenges of forecasting amid economic volatility. This study emphasizes the substantial impact of macroeconomic factors on ROI and the necessity of considering these variables in investment risk assessments.

Analysis Of Differences in Financial Distress Levels Between the Property &amp; Real Estate Sub-Sector Industry and The Building Construction Sub-Sector Industry

This study investigates how the building construction industry in Indonesia Stock Exchange differs from the property and real estate industry in terms of financial bankruptcy rates. The population of this study is the property and real estate sub-sector and the building construction sub-sector in Indonesia Stock Exchange. The general objective of this study is to identify financial distress in the property &amp; real estate and building construction industries and the level of financial distress of the property &amp; real estate sub-sector and building construction sub-sector as a picture of the level of bankruptcy of the industrial group. While the specific objective is that companies can anticipate early and immediately make improvements in asset management and company financing. The results of this study can also be used as a reference for investors to restructure their investment portfolios with more accurate portfolio return estimation calculations. This study uses a purposive sampling method, with the consideration or criteria that the companies studied are companies that publish financial reports in 2022 and 2023 at least Q3. To measure the level of financial distress of the two industrial sub-sectors, the Springate (S-Score) analysis model is used with the Independent Sample T Test analysis technique. The results of this study indicate that there is no significant difference in financial distress in the property &amp; real estate and building construction industries that go public on the Indonesia Stock Exchange.

Improving predictions of the Estimate at Completion using the classic Earned Value input

The article investigates the author’s method of estimating the final cost of a construction investment. A list of proposed methods of calculating the value of the planned final cost of the EAC investment available in the world literature was used. The modification consisted in the first place in the verification and elimination of formulas that do not match the use in construction projects and the combination of formulas resulting in the same result. The study was aimed at enabling the right choice of the method of estimating the final cost of construction investments and determining the accuracy of this estimate. It should be emphasized that the analyzed investments were annexed many times during their implementation. On the basis of the obtained results of research carried out on real construction investments, it was found that 3 methods best predict the final cost of the investment. Finally, improvements were introduced, which were analyzed, the final effect of the article is a proposal of an original, universal formula, which in each of the analyzed construction investments, regardless of the trends, deviations from the cost at the time of the inspection, forecasts the most accurate result, consistent with reality. The conducted research gives the possibility of more effective financial management of a construction investment using the corrected EAC formula in EVM method.

Deep learning-based recognition of construction activities in real construction site environment

PurposeToday’s technological advancements have had a significant impact on the construction industry. Managing and controlling complex construction projects has been made significantly easier using technological tools. One such advancement is the automatic identification of workers’ activities. This study aims to classify construction worker activities by analyzing real-time motion data collected from sensors.Design/methodology/approachIn accordance with our specific goals, we utilized advanced deep-learning methodologies such as deep neural networks, convolutional neural network, long short-term memory and convolutional long short-term memory to analyze the data thoroughly. This involved experimenting with various window sizes and overlap ratios to determine the optimal combination that would result in the most accurate predictions.FindingsBased on the analysis results, the convolutional long short-term memory (ConvLSTM) deep learning model with a window size of 4.8 s and an overlap rate of 75% was found to be the most accurate prediction model. This model correctly predicted 98.64% of the basic construction worker activities in a real construction site environment.Originality/valuePrevious studies have mainly been conducted in laboratory environments and have focused on basic construction activities such as lifting, moving, sawing and hammering. However, this study collected data from real workers in a real construction site environment. Various deep learning models were employed to determine the most accurate one. Additionally, several options were tested to determine the optimal window size and overlap ratio during the data segmentation phase, aiming to select the most suitable ones for preparing the data for the model.

무한소수를 활용한 실수의 정의에 대한 소고

Lee(2014; 2015) claimed that, in the program of the pre-service school teacher training, real numbers should be defined using the infinite decimal expansion so as to resolve the double discontinuity problem between school and college mathematics. Li(2011) wrote a mathematical paper on the construction of the real numbers via the infinite decimal expansion and supported the argument. On the other hand, Park(2016) analyzed Li's paper and showed that this paper contains the error of circular logic using ‘limit to a real number’. This study shows that Park(2016) misunderstood the introduction of Li's paper and revealed that appropriate axiom must be assumed to avoid the error of circular logic in real number construction. Through this, we resolved the confusion in the studies of Lee(2014; 2015) and Park(2016) and discussed the implications for pre-service school teacher education proposed in each study could be compatible with each other.

CONTRIBUTIONS TO SUSTAINABILITY IN TECHNICAL EDUCATION: REUSE OF CONSTRUCTION WASTE AS A WAY TO REDUCE ENVIRONMENTAL IMPACT

This study investigates the impact of reusing solid waste generated during practical classes in the Technical Course in Civil Construction at CEFET-RJ. The main objective is to analyze how sustainable teaching practices can reduce the environmental impact of the construction sector, while simultaneously training students to face the global sustainability challenges in the sector. The research used quantitative and qualitative methods to evaluate the efficiency of reusing materials, such as 'argalama' mortar and PVC pipes, in two different laboratories: Masonry and Plumbing Installations. The results show that these practices, once obstacles are overcome, can reduce material costs and the consumption of natural resources, such as water and energy, without compromising the quality of teaching activities. The conclusions indicate that the integration of sustainable practices in technical education not only contributes to the training of professionals with greater environmental awareness, but also enables the development of solutions with this approach in real construction projects. The study highlights the relevance of technical education as an agent of transformation in the context of sustainability, in line with Sustainable Development Goals (SDGs) 4 and 12.

Automated daily report generation from construction videos using ChatGPT and computer vision

Automated daily report generation from construction videos using ChatGPT and computer vision

Assessing cyber risks in construction projects: A machine learning-centric approach

Assessing cyber risks in construction projects: A machine learning-centric approach

Xi'an Real Estate Financial Risk Early Warning System Construction

Xi'an Real Estate Financial Risk Early Warning System Construction

Study of the Structure and Properties of Concrete Modified with Nanofibrils and Nanospheres

The application of modifying nanoadditives in the technology of cement composites is currently a relevant and widely researched topic in global materials science. The purpose of this study was to investigate new nanoadditives—nanofibrils made from synthesized wollastonite (NF) and nanospheres from corundum (NS)—produced by LLC NPK Nanosystems (Rostov-on-Don, Russia) as a modifying additive. During the experimental investigations, the mechanical properties of cement pastes and concrete were examined. This included an analysis of the density, compressive and bending strength, as well as water absorption of concrete that had been modified with NF and NS additives. X-ray phase and microstructural analyses of concrete were performed. It was established that modification of cement composites with NF and NS additives had a beneficial effect on their properties, and the optimal amount for both types of additives was 0.3% by binder weight. The highest recorded enhancements in compressive and flexural strength of concrete with 0.3% NF were 7.22% and 7.04%, respectively, accompanied by a decrease in water absorption by 4.70%. When modifying concrete with 0.3% NS, the increases in compressive and flexural strength were 2.71% and 2.48%, and water absorption decreased by 1.96%. Modification of concrete with NF and NS additives did not have a significant effect on the change in concrete density, which was no more than 1%. Based on the results of phase analysis, it was established that concrete with NF and NS additives were characterized by the presence of five main phases: quartz, portlandite, calcite, larnite, and olivine-Ca. It was found that compositions with 0.3% NF and NS differed from the control composition by the presence of such a phase as olivine-Ca. Microstructural analysis confirmed the effectiveness of NF and NS additives. The microstructure of the modified concretes was distinguished by the extensive occurrence of clusters composed of calcium silicate hydrate zones. The conducted studies prove the possibility of using NF and NS as modifying nanoadditives in the technology of cement composites. The addition of nanofibrils from synthesized wollastonite is the most effective and promising and is recommended for use in real construction practice.

Technology “like a fork”. How PropTech shapes real estate innovation

PurposePropTech has shown important implications for real estate; however, it remains a poorly understood phenomenon in both academia and practice. This paper aims to advance the understanding of PropTech by disentangling what the real estate sector needs from technology and, in parallel, observing closely the activities of PropTech businesses in two different countries.Design/methodology/approachThe paper adopts a mixed-method approach relying on qualitative data collected through interviews with PropTech players and real estate operators, and quantitative data collected through multiple sources on the Finnish and Italian PropTech ecosystems. The analysis is exploratory and descriptive.FindingsThis study underscores the potential benefits that digital technologies, introduced by PropTech, can add to the real estate sector: data integration; decisions informed from data; balance of new and old approaches to problem-solving; change in vision; adaptability of technologies and business models; and new professional profiles. These benefits are obtained when technology enables innovation from cross-pollination of different sectors. This becomes evident through the analysis of NACE activities, which demonstrates that innovation not only depends on interactions between property and technology, but the phenomenon covers a much broader spectrum of activities and industries.Originality/valueOur exploratory analysis brings up new evidence that not only the real estate sector and property sector are affected by PropTech but the phenomenon covers a much broader spectrum of activities and industries. This paper contributes to the debate on technology innovations and value chain in the real estate and construction sector, while adding a cross-country perspective.

The Impact of Firm Size, Leverage, and Peer Effect on Cash Holding

This research aims to empirically test the influence of firm size, leverage, and peer effect on cash holding. The population of this research is 110 companies in property real estate and building construction sector that listed on the Indonesia Stock Exchange (BEI) in 2018-2022 period. The number of sample on this research is 61 which the criteria of sample is companies in property real estate and building construction sector that listed on the Indonesia Stock Exchange (BEI) in 2018-2022 period consecutively. Data testing uses SPSS25 software. The analysis technique used in this research is multiple linear regression. The results of this research indicate firm size influence cash holding. Meanwhile, leverage and peer effect have no effect on cash holding.

Local and global integrative retrofitting of reinforced concrete frames using in‐plane buckling steel braces

AbstractTwo large‐scale, single‐storey, single‐bay reinforced concrete (RC) moment frames, designed as per an outdated seismic code to represent a typical framing detail of a four‐storey building, have been tested under displacement‐controlled quasi‐static loading protocol as per ACI 374.1‐05. The RC frames include a plinth beam with brick infill underneath, a slab monolithically cast with the top beam and provision for applying axial load to the column to simulate real construction scenario. One of the frames has been tested as a bare frame, and the second one has been retrofitted with conventional steel braces designed to undergo in‐plane buckling. The size of the brace has been selected based on the result of a nonlinear time history analysis of representative low‐ to mid‐rise open‐ground storey RC buildings. Post‐installed chemical anchors have been utilized to connect the steel braces to the narrow RC frame members following the outcomes of an experimental investigation by the same authors. Local‐level retrofitting by steel jacketing using adhesives has been designed and utilized on columns and beams to achieve the desired seismic response. The seismic performance of the retrofitted frame has been compared with the bare frame in terms of strength, stiffness, ductility, energy dissipation and hysteretic damping. The tests provide insight into the role of the plinth beam, effect of RC slab on the strong‐column weak‐beam aspect and the achievement of the desirable hinge mechanism through a precise design and detailing of global and local level retrofitting technique.