Search results

Despite the growing construction subject of Design for Safety (DfS) in Malaysia, little effort has been made to understand the construction organisational DfS capability in a dynamic environment. This study aims to propose a framework for dynamic DfS capabilities for construction organisations in Malaysia.

A quantitative research methodology was used for this study. Data were gathered from three hundred and six (306) practitioners from diverse construction organisations, including government agencies, consultants, contractors and developers in Malaysia, using an online questionnaire survey during four online DfS webinars. Descriptive and inferential analysis, as well as content analysis techniques, were used to analyse the collected data.

Analysis of the survey data showed that all six key DfS organisational capability elements identified in the literature, which the respondents were required to assess, have a strong influence on determining the DfS capabilities of construction organisations. The elements ranked as most influential include DfS knowledge of the designer; DfS experience of the designer; Top management’s commitment to DfS; Design risk management; and Project review. Based on these findings, a framework for dynamic DfS organisational capabilities is proposed. This framework incorporates four essential capabilities – sensing, learning, integrating and coordinating – and is anchored by the aforementioned six key elements as foundational to deriving value from DfS practices.

The proposed DfS organisational capabilities framework will facilitate construction organisations’ focus on the dynamic environment while striving for successful DfS practice in construction projects.

This study extends the DfS literature in the construction context by providing deeper insights into the conceptualisation of dynamic DfS organisational capabilities where DfS regulatory framework is still evolving. This study also highlights organisations’ importance in perceiving and prioritising their abilities to sense changes, learn and internalise new competencies, integrate resources and coordinate activities, reflecting their unique strategic focuses and operational needs toward DfS practice.

This article aims to explore valuable insights into the construction progress monitoring (CPM) research domain, which include main research topics, knowledge gaps and future research themes. For a long time, CPM has been significantly researched with increasing enthusiasm. Although a few review studies have been carried out, there is non-existence of a quantitative review study that can deliver a holistic picture of CPM.

The science mapping-based scientometric analysis was systematically processed with 1,835 CPM-related journal articles retrieved from Scopus. The co-authorship analysis and direct citation analysis were carried out to identify the most influential researchers, countries and publishers of the knowledge domain. The co-occurrence analysis of keyword was assessed to reveal the most dominating research topics and research trend with the visual representation of the considered research domain.

This study reveals seven clusters of main research topics from the keyword co-occurrence analysis. The evolution of research confirms that CPM-related research studies were mainly focused on fundamental and traditional CPM research topics before 2007. The period between 2007 and 2020 has seen a shift of research efforts towards digitalization and automation. The result suggests Building Information Modelling (BIM) as the most common, growing and influential research topic in the CPM research domain. It has been used in combination with different data acquisition technologies (e.g. photogrammetry, videogrammetry, laser scanning, Internet of Things (IoT) sensors) and data analytics approaches (e.g. machine learning and computer vision).

This study provides the horizon of potential research in the research domain of CPM to researchers, policymakers and practitioners by availing of main research themes, current knowledge gaps and future research directions.

This paper represents the first scientometric study depicting the state-of-the-art of the research by assessing the current knowledge domain of CPM.

Current solutions for monitoring the progress of pavement construction (such as collecting, processing and analysing data) are inefficient, labour-intensive, time-consuming, tedious and error-prone. In this study, an automated solution proposes sensors prototype mounted unmanned ground vehicle (UGV) for data collection, an LSTM classifier for road layer detection, the integrated algorithm for as-built progress calculation and web-based as-built reporting.

The crux of the proposed solution, the road layer detection model, is proposed to develop from the layer change detection model and rule-based reasoning. In the beginning, data were gathered using a UGV with a laser ToF (time-of-flight) distance sensor, accelerometer, gyroscope and GPS sensor in a controlled environment. The long short-term memory (LSTM) algorithm was utilised on acquired data to develop a classifier model for layer change detection, such as layer not changed, layer up and layer down.

In controlled environment experiments, the classification of road layer changes achieved 94.35% test accuracy with 14.05% loss. Subsequently, the proposed approach, including the layer detection model, as-built measurement algorithm and reporting, was successfully implemented with a real case study to test the robustness of the model and measure the as-built progress.

The implementation of the proposed framework can allow continuous, real-time monitoring of road construction projects, eliminating the need for manual, time-consuming methods. This study will potentially help the construction industry in the real time decision-making process of construction progress monitoring and controlling action.

This first novel approach marks the first utilization of sensors mounted UGV for monitoring road construction progress, filling a crucial research gap in incremental and segment-wise construction monitoring and offering a solution that addresses challenges faced by Unmanned Aerial Vehicles (UAVs) and 3D reconstruction. Utilizing UGVs offers advantages like cost-effectiveness, safety and operational flexibility in no-fly zones.

It is a well-accepted note that to enhance safety performance in a project by preventing hazards, recognizing the safety leading indicators is of paramount importance.

In this research, the relationship between safety leading indicators is determined, and their impacts on the project are assessed and visualized throughout the time of the project in a proactive manner. Construction and safety experts are first interviewed to determine the most important safety leading indicators of the construction industry, and then the relationships that may exist between them are identified. Furthermore, a system dynamics model is generated using the interviews and integrated with an add-on developed on the building information modeling (BIM) platform. Finally, the impacts of the safety leading indicators on the project are calculated based on their time of occurrence, impact time and effective radius.

The add-on generates a heat-map that visualizes the impacts of the safety leading indicators on the project through time. Moreover, to assess the effectiveness of the developed tool, a case study is conducted on a station located on a water transfer line. In order to validate the results of the tool, a survey is also conducted from the project's staff and experts in the field. Previous studies have so far focused on active safety leading indicators that may result in a particular hazard, and the importance of the effects that safety leading indicators have on another is not considered. This study considers their effects on each other in a real-time manner.

Using this tool project's stakeholders and staff can identify the hazards proactively; hence, they can make the required decisions in advance to reduce the impact of associated events. Moreover, two other potentially contributions of the presented work can be enumerated as: firstly, the findings provide a knowledge framework of active safety leading indicators and their interactions for construction safety researchers who can go on to further study safety management. Secondly, the proposed framework contributes to encouragement of time-based location-based preventive strategies on construction sites.

This study aimed to identify driving factors of safety attitudinal ambivalence (AA) and explore their influence. Construction workers' intention to act safely can be instable under conflicting information from safety management, co-workers and habitual unsafe behaviour. Existing research explained the mechanism of unsafe behaviours as individual decisions but failed to include AA, as the co-existence of both positive and negative attitude.

This study applied system dynamics to explore factors of construction workers' AA and simulate the process of mitigating the ambivalence for less safety behaviour. Specifically, the group model building approach with eight experts was used to map the causal loop diagram and field questionnaire of 209 construction workers were used to collect empirical data for initiating parameters.

The group model building identified five direct factors of AA, namely the organisational safety support, important others' safety attitude, emotional arousal, safety production experience and work pressure, with seven feedback paths. The questionnaire survey obtained the initial values of the factors in the SD model, with the average ambivalence at 0.389. The ambivalence between cognitive and affective safety attitude was the highest. Model simulation results indicated that safety experience and work pressure had the most significant effects, and safety experience and positive attitude of co-workers could compensate the pressure from tight schedule and budget.

This study provided a new perspective of the dynamic safety attitude under the co-existence of positive and negative attitude, identified its driving factors and their influencing paths. The group model building approach and field questionnaire surveys were used to provide convincible suggestions for empirical safety management with least and most effective approaches and possible interventions to prevent unsafe behaviour with tight schedule and budget.

This research aims to use meta-analytical structural equation modeling to look into how hospitality employees use technology at work. It further investigates if the relationship between the constructs of the technology acceptance model (TAM) is moderated by job level (supervisory versus non-supervisory) and different cultures (eastern versus western).

In total, 140 relationships from 30 empirical studies (N = 6,728) were used in this study’s data analysis in accordance with the preferred reporting items for systematic reviews and meta-analysis.

The findings demonstrated that perceived usefulness had a greater influence on “user attitudes” and “acceptance intention” than perceived ease of use. This study also identified that the effect sizes of relationships among TAM constructs appeared to be greater for supervisory employees or in eastern cultures than for those in non-supervisory roles or western cultures.

The findings provide valuable information for practitioners to increase the adoption of employee technology. Practitioners need to focus on the identification of hospitality employee attitudes, social norms and perceived ease of use. Moreover, hospitality practitioners should be cautious when promoting the adoption of new technologies to employees, as those at different levels may respond differently.

This is the very first empirical investigation to meta-analyze the predictive power of the TAM in the context of hospitality staff technology adoption at the workplace. The findings also demonstrated differences in the predictive power of TAM constructs according to job level and cultural differences.

This paper reviews academic literature related to the consequences that outside directors and boards may face in the wake of earnings restatements and suggests directions for future research. We examine loss of board seats; recruitment of new directors; proxy recommendations and shareholder support; pre-emptive director departures; director wealth effects; director reputation, litigation, and sanction risks; international evidence; and legal proposals for reform. The overall picture that emerges from the literature is that directors’ primary risk in the wake of earnings restatements is loss of board seats, in part through adverse proxy advisor recommendations and reduced shareholder support. Directors typically face little risk of legal liability or SEC sanctions, and some directors pre-emptively leave a problem company’s board and reduce their loss of interlocked board seats. Some legal scholars have called for director liability to be increased so as to promote more vigilant board oversight. Companies often focus on increasing the independence of the board in the wake of a restatement in an effort to repair organizational reputation. While researchers have revealed a host of important findings to date, much more can be learned about the effects of restatements on outside directors and boards.

This paper aims to initiate a new, formal theory of sociocultural physics.

Its intended scope is limited to predicting either long‐term, large‐scale or short‐term, small‐scale sociocultural events. The theory that the authors develop, called sociohistory, links three independent but relatable approaches: part of Sorokin's epistemological theory of sociocultural dynamics, Frieden's epistemological theory of extreme physical information (EPI), and Yolles's social viable systems (SVS) theory.

Although not all of Sorokin's ideas are universally accepted, a subset of them is found to be extremely useful for describing the conceptual context of complex systems. This includes how sociocultural processes link closely into political processes.

The theory that develops helps explain how opposing, cultural enantiomers or yin‐yang forces (represented, for instance, by the polar mindsets represented in Islamic fundamentalism and global enterprise) can result in violent conflict, or in either viable or non‐viable social communities. The informations I and J of EPI theory are regarded, respectively, as sensate and ideational enantiomers.

While the resulting sociocultural physics is in its infancy, an illustrative application to the developmental dynamics of post‐colonial Iran demonstrates its potential utility.

This paper aims to examine four key management processes, namely, communication, coordination, decision-making and knowledge-sharing, to determine how these impact on transportation infrastructure project success. The context for this study is the construction of a major highway in the United Arab Emirates.

Multiple sources of data are used in this case study that include the following: examination of various documents relating to the project in question; interviews with ten key stakeholders involved with the construction of the project; observations made during the site visit and interviews conducted with four site engineers; a focus group conducted with six key stakeholders involved in the project; and finally interviews conducted with the Minister of Public Works and the Director-General of the Ministry of Public Works. Analysis was conducted using NVivo.

Identification and involvement of key stakeholders, particularly in the early phases of a construction project, is found to be highly critical. Managers must develop detailed understanding of stakeholders’ influence in terms of their legitimacy, power and urgency in achieving effectiveness of the management processes.

The study highlights how different stakeholders influence communication, coordination, decision-making and knowledge-sharing at different stages of the construction project. Hence, understanding stakeholder’s level of legitimacy, power and urgency across the different stages of a project is highly critical.