Building Information Modelling (BIM) is transforming the construction industry by improving project efficiency, accuracy, and teamwork. However, failure to determine accurately soft costs during BIM-based construction projects can lead to financial uncertainty and management issues, making it difficult to assess the return on investment (ROI) of BIM. Identifying the factors that influence BIM-related soft costs is crucial for determining the ROI of BIM. To address this issue, this study aimed to investigate the factors affecting soft costs in BIM-based construction projects, using Malaysia as a case study. Data collection involved conducting semi-structured interviews with BIM professionals, followed by thematic analysis to analyse the collected data. The findings revealed that the factors influencing soft costs can be categorised into two main themes: organisational factors and project factors. Within the former, the subthemes included development charges, certification fees, commissioning fees, and ongoing maintenance costs. Meanwhile, project factors encompassed contingency fees, levy fees, and documentation fees. Understanding these factors is crucial for determining the ROI of BIM, which can drive more widespread BIM implementation in developing countries. The study reveals that accurately identifying the factors influencing soft costs in BIM-based construction projects is essential for effective cost management. As a result, the findings emphasise that these factors must be addressed in order to improve financial planning and project execution in the construction industry. The originality of this study lies in its focus on soft costs within BIM-based construction projects, an underexplored area of the existing literature. This nuanced understanding will help organisations and policymakers to manage costs more effectively, contributing to more efficient construction practices and supporting the UN Sustainable Development Goals 9: Industry, Innovation, and Infrastructure and 11: Sustainable Cities and Communities by promoting sustainable building practices and resilient infrastructure development.

Purpose
This study aims to establish relationships between organizational attributes and strategies for developing accurate digital twins (DTs) of constructed facilities. To achieve this aim, the study objectives are: (1) identify the key organizational attributes and strategies, (2) develop underlying constructs among the organizational attributes and strategies, and (3) model the relationships between the underlying constructs of organizational attributes and strategies.

Design/methodology/approach
A systematic literature review and semi-structured interviews with architecture, engineering, construction, and operation (AECO) industry professionals identified twenty-one organizational attributes and thirty organizational strategies. Through a survey, 129 AECO industry professionals evaluated the criticality of the organizational attributes and strategies. The collected data were analyzed using normalized mean analysis, exploratory factor analysis, and partial least-squares structural equation modeling.

Findings
The analyses identified eleven and twenty key organizational attributes and strategies. Furthermore, the organizational attributes and strategies can be categorized into two (organizational DT capabilities and technological capabilities requirements) and three (organizational competitiveness and investments, organizational workforce management and training, and organizational management capabilities) underlying constructs. Finally, organizational DT capabilities significantly impact the need for all three underlying constructs of organizational strategies, whereas technological capabilities requirements do not. These findings indicate that strategic initiatives should be driven by organizational and human-centric attributes, including leadership, strategic planning, and talent development, rather than on technological readiness alone, challenging assumptions that technological readiness is the catalyst for strategy deployment in DT development.

Originality/value
This is the first study that models the relationships between organizational attributes and strategies for developing accurate DTs of constructed facilities.

Purpose
Building information modeling (BIM) offers numerous benefits for construction projects, but its implementation can include additional non-physical costs, commonly referred to as soft costs, distinct from traditional construction projects. Hence, understanding the soft cost elements (SCEs) is critical for accurate cost estimation in BIM-based construction projects. This study aims to identify the critical SCEs in BIM-based construction projects.

Design/methodology/approach
This study conducted a multi-stage approach, starting with an SLR to compile an initial list of SCEs, which was refined through a pilot test with BIM experts. A Delphi survey conducted with 16 experts evaluated the SCEs for two rounds. Data analysis included mean values and percentage of agreement analyses to identify the critical SCEs. Finally, a thematic analysis was conducted to categorize the critical SCEs.

Findings
This study identified eight critical SCEs in BIM-based construction projects, categorized into two categories: technology and human resources. Technology-related costs include BIM software, hardware, updates and BIM-specific planning/designing. Human resource-related costs encompass BIM consultant, modeler, coordinator and manager remuneration.

Originality/value
This is the first study to determine the critical SCEs in BIM-based construction projects. Understanding the critical SCEs provides stakeholders with actionable insights for developing strategies to improve the cost management of SCEs in BIM-based construction projects.

Purpose: Digital twin (DT) and building information modeling (BIM) are interconnected in some ways. However, there has been some misconception about how DT differs from BIM. As a result, industry professionals reject DT even in BIM-based construction projects due to reluctance to innovate. Furthermore, researchers have repeatedly developed tools and techniques with the same goals using DT and BIM to assist practitioners in construction projects. Therefore, this study aims to assist industry professionals and researchers in understanding the relationship between DT and BIM and synthesize existing works on DT and BIM. Design/methodology/approach: A systematic review was conducted on published articles related to DT and BIM. A total record of 54 journal articles were identified and analyzed. Findings: The analysis of the selected journal articles revealed four types of relationships between DT and BIM: BIM is a subset of DT, DT is a subset of BIM, BIM is DT, and no relationship between BIM and DT. The existing research on DT and BIM in construction projects targets improvements in five areas: planning, design, construction, operations and maintenance, and decommissioning. In addition, several areas have emerged, such as developing geo-referencing approaches for infrastructure projects, applying the proposed methodology to other construction geometries and creating 3D visualization using color schemes. Originality/value: This study contributed to the existing body of knowledge by overviewing existing research related to DT and BIM in construction projects. Also, it reveals research gaps in the body of knowledge to point out directions for future research.