Abstract Forensic schedule delay analysis plays a central role in construction dispute resolution, yet practitioners frequently rely on multiple institutional authorities that differ in scope, structure, and analytical emphasis. This paper examines how three widely cited authorities—the Society of Construction Law Delay and Disruption Protocol, second edition (SCL DDP2), AACE International Recommended Practice (RP) 29R-03, and ASCE 67-17—conceptualize and guide forensic schedule delay analysis. The study employs a comparative doctrinal and standards-based analysis. It reviews and synthesizes the treatment of delay methodologies, critical path identification, float ownership, concurrent delay, and evidentiary reliability across the three authorities, with emphasis on their implications for expert testimony and dispute resolution. The analysis demonstrates that the three authorities converge on foundational principles, including the dynamic nature of the critical path and the primacy of contemporaneous schedule records. At the same time, they diverge in institutional purpose and analytical emphasis: ASCE 67-17 functions primarily as a consensus-based professional standard, AACE RP 29R-03 provides a structured technical taxonomy of forensic delay methodologies, and the SCL protocol situates delay analysis within a contractual and entitlement framework.
Abstract Building information modeling (BIM) has transformed project delivery into a collaborative, data-dependent process, but construction law still tends to organize responsibility around discrete documents, bilateral duties, and physical defects. This article defines digital damage as a legally relevant impairment of the integrity, accessibility, reliability, authorship, evidentiary value, interoperability, or security of project information that causes or materially contributes to a recognized loss. Using doctrinal and structured comparative analysis of the United Kingdom, United States, and European Union, the article distinguishes nonactionable technical malfunction from contractual breach, evidentiary impairment, economic loss, intellectual property infringement, cybersecurity incident, and recoverable damage. It applies contractual liability, negligence, misrepresentation, causation, and risk allocation rules to corrupted models, inaccurate model reliance, interoperability degradation, access denial, and shared authorship. The case analysis shows that existing doctrine can protect access, reliance, performance expectations, and contractual risk allocation, but does not itself create a comprehensive BIM compensation regime. The article therefore proposes a differentiated matrix linking each digital incident to its legal characterization, responsible actor, evidence, recoverable loss, contractual provision, insurance response, and dispute mechanism. It concludes that effective compensation requires express model status and reliance clauses, binding information management duties, auditable digital records, proportionate cybersecurity obligations, and specialist dispute and insurance arrangements.
Abstract Price volatility in construction materials introduces uncertainty into highway project delivery, contributing to cost overruns, schedule delays, and contractual disputes. To help manage this risk, state DOTs incorporate price adjustment clauses (PACs) into eligible highway construction contracts. Although PACs are widely used, there is limited research examining their benefits, fairness, and implementation challenges under current market conditions. This study investigates stakeholder perceptions of PACs in terms of their advantages, fairness, and practical concerns within the context of US highway construction. Two national surveys were conducted in 2025: one distributed to 50 state DOTs, yielding responses from 40 agencies, and one distributed to highway contractors, yielding 140 responses from diverse firm sizes and regions. Categorical responses were summarized with frequency distributions, and multioption benefit items used weighted scores. Among state DOT respondents to the adoption item, 97% reported including at least one material PAC, and most contractors reported high interest in PAC inclusion. Across both stakeholder groups, volatility mitigation and facilitation of large or multiyear contracts received the highest benefit ratings, while influence on bidding participation and change-order frequency was lower. State DOT respondents indicated that contractors generally view PACs as fair, and 84% of contractor respondents rated PACs somewhat or very fair. More than 80% of state DOT respondents reported slight or no administrative burden. Implementation concerns centered on the regional applicability and timeliness of price indices, and 53% of state DOT respondents reported at least one prospective refinement, most often related to material coverage or threshold settings. Respondents perceived PACs as most useful for controlling exposure to material price volatility in multiyear work, and greater transparency in price index sourcing and adjustment procedures was associated with more favorable fairness perceptions, while administrative workload was generally described as low. This study provides insights that can assist state DOTs in refining PACs to maintain transparency, support fair risk allocation, and limit administrative complexity within current market conditions.
Abstract Alternative dispute resolution (ADR) mechanisms are considered to offer several advantages over litigation and arbitration, including greater flexibility, lower cost, and better preservation of cooperative relationships between disputing parties. However, they have not been widely adopted in China’s construction industry. This study aims to identify the barriers to the implementation of ADR mechanisms for dispute resolution in the Chinese construction industry. First, 15 barrier factors were identified through a literature review and expert interviews. Then, the integrated Decision Making Trial and Evaluation Laboratory-Interpretive Structural Modeling-Cross Impact Matrix Multiplication Applied to Classification (DEMATEL-ISM-MICMAC) approach was employed to analyze the interrelationships among these factors and to develop a multilevel hierarchical structural model of the barriers to implementing ADR mechanisms for dispute resolution in China’s construction industry, thereby identifying the most fundamental barriers. The results were further validated based on the driving power and dependence of the barrier factors. The findings indicate that the lack of supporting laws and regulations is the most fundamental barrier to the implementation of ADR mechanisms in China’s construction industry. The absence of explicit ADR provisions in contracts and the low willingness to use ADR mechanisms are identified as direct barriers. The results are of great significance for enriching the body of knowledge on ADR mechanisms and promoting their global development. They also provide useful references for the promotion of ADR mechanisms in China and in other countries and regions where ADR is still at an early stage of development.
Abstract Forecasting monetary outcomes in construction delay litigation remains difficult because cost awards are shaped by interacting factual, evidentiary, contractual, and forum-specific considerations rather than by incurred cost alone. This study develops interpretable machine learning models to estimate cost awards from published US construction delay decisions, with separate federal court and state court models to avoid pooling materially different adjudicative environments. The case database was assembled from Google Scholar case law searches using “delay” AND “critical path,” followed by eligibility screening, deduplication, and evidence-traceable coding. The coding framework was first piloted using 33 candidate factors and then reduced to 29 retained factors after excluding sparsely and inconsistently reported variables. Predictors were harmonized using controlled vocabularies, missing categorical information was coded as an explicit Not Specified category rather than imputed by mode, and monetary awards were modeled on a log-transformed scale. Extreme gradient boosting (XGBoost) was selected because it can model nonlinear interactions among heterogeneous categorical predictors while remaining interpretable through global feature importance diagnostics. Using an 80/20 train–test evaluation, the federal model achieved test R 2 of 0.837, root-mean-square error (RMSE) of USD 0.347 million, and mean absolute error (MAE) of USD 0.274 million, while the state model achieved test R 2 of 0.843, RMSE of USD 0.188 million, and MAE of USD 0.132 million. Percentage error metrics are also reported, although mean absolute percentage error (MAPE) and mean percentage error (MPE) are interpreted cautiously where actual awards approach zero. The findings support transparent, forum-specific benchmarking for early case assessment, subject to the limits of published US court decisions and the need for case-specific legal and forensic schedule judgment.
