Search results

Request for information (RFI) documents play a pivotal role in seeking clarifications in construction projects. However, perceived as inevitable “non-value adding” tasks, they harbour risks like schedule delays and increased project costs, underlining the importance of strategic RFI management in construction projects. Despite this, a lack of literature dissecting RFI processes impedes a full understanding of their intricacies and impacts. This study aims to bridge the gap through a comprehensive literature review, delving into RFI intricacies and implications, while emphasising the necessity for strategic RFI management to prevent project risks.

This research study systematically reviews RFI-related papers published between 2000 and 2023. Accordingly, the review discusses key themes related to RFI management, yielding best practices for industry stakeholders and highlighting research directions and gaps in the body of knowledge.

Present RFI management platforms exhibit deficiencies and lack analytics essential for streamlined RFI processing. Complications arise in building information modelling (BIM)-enabled projects due to software disparities and interoperability hurdles. The existing body of knowledge heavily relies on manual content analysis, an impractical approach for the construction industry. The proposed research direction involves automated comprehension of unstructured RFI content using advanced text mining and natural language processing techniques, with the potential to greatly elevate the efficiency of RFI processing.

The study extends the RFI literature by providing novel insights into the problemetisation with the RFI process, offering a holistic understanding and best practices to minimise adverse effects. Additionally, the paper synthesises RFI processes in traditional and BIM-enabled project settings, maps a causal-loop diagram to identify associated issues and summarises approaches for extracting knowledge from the unstructured content of RFIs. The outcomes of this review stand to offer invaluable insights to both industry practitioners and researchers, enabling and promoting the refinement of RFI processes within the construction domain.

The main purpose of this study is to reveal the degree of association between lean, building information modeling (BIM) and construction project success. The study further intends to provide strategies for high and low associations of the factors.

Lean construction and BIM are two important applications that have recently gained popularity in terms of enhancing project success. Considering this impact, this study investigates the synergy between lean construction and BIM and determines to what extent these two contribute to the success of the projects. As a first step, lean, BIM and project success were examined based on an in-depth literature review. In the second stage, a structural equation model (SEM) was established to reflect the relationship among these three through hypotheses. Then, a questionnaire was designed and administered to the construction professionals experienced in both lean and BIM implementation. The SEM was tested using Analysis of Moment Structures (AMOS), an SPSS tool.

The results indicated that lean implementation has a significant and positive impact on BIM implementation and project success. On the other hand, BIM implementation had a lower significant impact on project success than lean implementation construct.

The results of this study can be used by both policymakers and industry practitioners in terms of developing strategies for effectively using both lean and BIM. The researchers can further develop other implementation models to investigate whether these concepts are more effective in increasing project success when used integratively.

This study considers both the impact of lean and BIM on project success through input from construction practitioners working on large projects. This way, the study fosters the use of lean, BIM or lean–BIM together in construction projects to enhance project success.

Construction waste reduction (CWR) plays a vital role in achieving sustainability in construction. A good CWR practice can result in optimizing material usage, conserving natural resources, limiting environmental pollution, protecting the environment and enhancing human health. In this regard, the purpose of the current study is to identify the most relevant organizational policies that aid in waste reduction and concurrently explores the congruent measures to be adopted during the construction process in the Indian high-rise building sector.

The research findings were obtained through a mixed- method approach. Content analysis was used to identify waste reduction measures (variables) targeting on the two domains of construction – “waste-efficient execution” and “waste – mitigating organizational policies.” Furthermore, the authors explored and documented the key measures from the identified waste reduction measures using the constraint value of the relative importance index. As the next step, the study listed the theoretical hypothesis based on expert interviews and tested the theory through confirmatory factor analysis.

The results revealed that “waste sensitive construction techniques and strategies” as the most significant category under the domain “Execution” with a path coefficient of 0.85. Concurrently, the study has also determined that “control procedures for budget, quality and resources” as the most effective organizational approach in reducing construction waste in the Indian building industry, with a path coefficient of 0.83.

The current research is context-sensitive to the Indian construction sector. It presents the stakeholder’s perspective on construction waste reduction and the relevant measures to be implemented to reduce construction waste in high-rise building projects in India. It can also act as a concordance for decision-makers to further focus on CWR management and aid in formulating policies suitable for the Indian context.

Building defects are becoming recurrent phenomena in most high-rise buildings. However, little research exists on the analysis of defects in high-rise buildings based on data from real-life projects. This study aims to develop dashboards and models for revealing the most common locations of defects, understanding associations among defects and predicting the rectification periods.

In total, 15,484 defect reports comprising qualitative and quantitative data were obtained from a company that provides consulting services for the construction industry in Victoria, Australia. Data mining methods were applied using a wide range of Python libraries including NumPy, Pandas, Natural Language Toolkit, SpaCy and Regular Expression, alongside association rule mining (ARM) and simulations.

Findings reveal that defects in multi-storey buildings often occur on lower levels, rather than on higher levels. Joinery defects were found to be the most recurrent problem on ground floors. The ARM outcomes show that the occurrence of one type of defect can be taken as an indication for the existence of other types of defects. For instance, in laundry, the chance of occurrence of plumbing and joinery defects, where paint defects are observed, is 88%. The stochastic model built for door defects showed that there is a 60% chance that defects on doors can be rectified within 60 days.

The dashboards provide original insight and novel ideas regarding the frequency of defects in various positions in multi-storey buildings. The stochastic models can provide a reliable point of reference for property managers, occupants and sub-contractors for taking measures to avoid reoccurring defects; so too, findings provide estimations of possible rectification periods for various types of defects.

In an era marked by artificial intelligence (AI), virtual reality (VR) and augmented reality (AR), this study presents a research paradigm centered on nurturing fundamental skills crucial for effective digital leadership in a paradoxical age where leaders are ambitious as well as skeptical for the adoption of such technologies. This study offers a strategic framework to seamlessly integrate diverse technologies into leadership development; the objective is to bridge the divide between theoretical understanding and practical implementation, especially through the lens of paradox theory.

This conceptual study delineates essential attributes that digital leaders must cultivate, drawing insights from the corpus of literature encompassing leadership, technology and organizational advancement. Synthesizing theoretical perspectives, the study proposes a comprehensive research framework that provides a systematic approach to harnessing the potential of AI, VR and AR to enhance leadership competencies. This conceptual study significantly contributes to paradox theory through method of “theory adaptation” as elaborated in the literature.

The study unveils a spectrum of foundational proficiencies, including technological acumen, adaptability, strategic acumen, effective communication, collaborative aptitude and ethical acumen, among others. These competencies underscore the multifaceted skill set required of digital leaders. To adeptly traverse the intricate digital terrain, foster innovation and align technological advancements with organizational objectives, these proficiencies are imperative for digital leaders to possess.

The distinctiveness of this study lies in its all-encompassing approach to digital leadership development by offering a paradoxical perspective and hence making a contribution to the body of knowledge for paradox theory. By amalgamating AI, VR and AR into a cohesive framework, the study enhances the comprehension of how these technologies collaboratively nurture leaders capable of cultivating organizational triumph in the digital age. This proposed paradigm serves as a bridge between cutting-edge digital technology usage and leadership proficiency paradox, furnishing pragmatic insights to benefit both academic researchers and industry practitioners.