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Many investors have less interest in tendering for public-private partnership (PPP) construction projects as a result of the uncertain risks associated with the project delivery. Moreover, PPP project stakeholders have inadequate information about the probable impacts of time-based delay imposed on PPP projects under the PPP arrangement. This study aims to identify and categorize construction stakeholders’ perceptions of the impact of time-based delays on PPP construction projects.

A purposive sampling technique was adopted where questionnaires were used as the primary instrument for gathering data from PPP experts. Cronbach’s alpha coefficient and Kendall’s concordance were used to measure the reliability of the scale and the respondent’s level of agreement, respectively. One sample t-test, mean score ranking and principal component analysis were used to analyse the identified time-based delay impacts.

The study revealed seven significant impacts of time-based delay on PPP construction project delivery as: “project schedule overrun”, “idling of project resources”, “project cost overrun”, “poor quality of completed works”, “delayed realization of project benefits”, “frequent arbitration/litigation in PPP projects” and “total abandonment of PPP projects”. The study further identified the top five significant impacts of time-based delay on PPP project stakeholders as: “reduction in motivation to attract investment”, “high interest on finance (loans)”, “contractor in financial crisis”, “loss of public confidence in government” and “reduction in parties’ reputation”.

The identified significant impacts of time-based delays will increase stakeholders’ awareness of the repercussions and effects that time-based delays may impose on PPP construction projects if not appropriately managed throughout the project implementation. This awareness will further guide stakeholders to implement targeted risk management strategies to minimize the negative consequences of delays on PPP project performance.

As a pioneering study that provides a better understanding of the impacts of time-based delays on PPP construction projects, this study enhances knowledge of PPP construction project implementation.

The purpose of this study is to investigate how the price delay of cryptocurrencies to market news affects the herding behavior of investors, particularly during turbulent events such as the COVID-19 period.

The paper investigates the presence of herding behavior by using Cross-Sectional Absolute Deviation (CSAD) measures. We also investigate the herding activity in the crypto traders’ behavior during up and down-market movements periods and under investor extreme sentiment conditions. The speed of cryptocurrencies’ price response to the information embedded in the market is assessed based on the price delay measure proposed by Hou and Moskowitz (2005).

Our findings suggest that cryptocurrencies characterized by high price delays exhibit more herding among investors, thereby highlighting higher degrees of market inefficiencies. This is also apparent during periods of extreme investor sentiment. We also document an asymmetric herding behavior across cryptocurrencies that present different levels of price speed adjustments to market news during bullish and bearish market conditions. Our results are consistent and robust across different sub-periods, various market return estimations and different price delay frequencies.

The study provides crucial guidelines for investors’ asset allocation and risk management strategies. This study is also valuable to regulators and policymakers, particularly in light of the increasing importance of financial reforms aimed at mitigating market distortions and enhancing the resilience of the cryptocurrency market. More specifically, regulations that improve the market’s information efficiency should be prioritized to speed up the response time of cryptocurrency prices to market information, which can help reduce the investors' herding behavior.

This paper makes a novel contribution to the academic literature by investigating the unexplored relationship between cryptocurrency price delays and the presence of herding behavior among investors, especially in times of uncertainty such as the COVID-19 pandemic.

This study aims to determine and investigate the main causes of construction project delays. Construction projects are more intricate and associated with significant levels of risk owing to cost overruns. These overruns frequently lead to delays, incomplete work or other related challenges. Building delays are a prevalent problem in the building sector of developing nations. These delays prolong the duration of projects and result in increased costs and conflicts among stakeholders. A conceptual model consisting of the factors causing the delays in heating, ventilation and air conditioning (HVAC) projects was developed and tested in this study.

A comprehensive data collection process was undertaken. A meticulously designed survey was distributed to a diverse cohort of 294 participants, including contractors and sub-contractors from Chennai, Tamil Nadu. The data was collected using stratified sampling, ensuring a representative sample. The data was then analysed using ordinary least squares multiple regression.

The findings of this study have significant implications for the construction industry. They indicate that factors related to sales, clients, design, procurement, finance and labour all contribute to delays in HVAC projects. Understanding these factors can help stakeholders in the industry to better manage and mitigate project delays.

This study is unique because it is a perceptual study of stakeholders. It provides valuable information for analysing and assessing project performance by identifying the primary causes of HVAC project delays. To the best of the authors’ knowledge, the study conducted on HVAC projects is the first of its kind and hence makes a pivotal contribution to the literature on construction projects. Additionally, the study will assist policymakers and consultants in taking necessary steps to minimize delays.

To optimize train operations, dispatchers currently rely on experience for quick adjustments when delays occur. However, delay predictions often involve imprecise shifts based on known delay times. Real-time and accurate train delay predictions, facilitated by data-driven neural network models, can significantly reduce dispatcher stress and improve adjustment plans. Leveraging current train operation data, these models enable swift and precise predictions, addressing challenges posed by train delays in high-speed rail networks during unforeseen events.

This paper proposes CBLA-net, a neural network architecture for predicting late arrival times. It combines CNN, Bi-LSTM, and attention mechanisms to extract features, handle time series data, and enhance information utilization. Trained on operational data from the Beijing-Tianjin line, it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.

This study evaluates our model's predictive performance using two data approaches: one considering full data and another focusing only on late arrivals. Results show precise and rapid predictions. Training with full data achieves a MAE of approximately 0.54 minutes and a RMSE of 0.65 minutes, surpassing the model trained solely on delay data (MAE: is about 1.02 min, RMSE: is about 1.52 min). Despite superior overall performance with full data, the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals. For enhanced adaptability to real-world train operations, training with full data is recommended.

This paper introduces a novel neural network model, CBLA-net, for predicting train delay times. It innovatively compares and analyzes the model's performance using both full data and delay data formats. Additionally, the evaluation of the network's predictive capabilities considers different scenarios, providing a comprehensive demonstration of the model's predictive performance.

This review paper aims to highlight the causes of delays (COD) and their interactions in construction projects, potentially aiding in timely completion and waste reduction through early anticipation.

Forty-seven global literature were examined in detail to identify CODS and its interactions using the systematic literature review (SLR) method that utilised the PRISMA guidelines to ensure the studies reviewed were adequate to safeguard the robustness and comprehensiveness. Three-way analysis, such as Pareto, degree of centrality and loops, was undertaken to identify the critical Level 1,2 and 3 CODS that affect the Construction projects.

The research findings demonstrate that 65 CODs in eight categories affect construction projects. The CODs act in coherence rather than silos; the CLD displays complex interconnections of 44 factors obtained through the pairwise comparison of the 47 identified literature of the SLR. Through its systematic analysis of interaction loops, this research identified Ten level 1 critical CODs, two second-level critical CODs and 4 Third-level critical CODs. “Contractors' excessive workload/beyond potential/inadequate experience” emerged as the top COD that affects scheduling and project delay.

The study limitations include using only English articles and a restricted number of databases. However, the chosen databases were reputable and underwent thorough peer review processes. This study may have limitations due to the SLR, which means that factors affecting COD and interactions may vary by country, and future research is suggested for validation.

This study identified interactions of construction delays that potentially support scheduling risk management during the early stage of the project and reduce waste to improve sustainability. The theoretical implications of SLR-based research include helping develop a framework that would potentially have all COD in the current scenario and aid future academic and industrial research factor-wise and country-wise in aiding sustainability. This will support and provide construction professionals and academia with knowledge of the COD related to factors and their interactions to be considered in the early assessment and management of future projects and improve sustainability.

Most literature studies the factors or causes of construction delays that affect construction projects. The CODs primarily do not operate in silos but combine with other causes to enhance their influence on delays. Hence, it is of utmost importance to study the interactions of COD to enhance the knowledge in the construction field that would aid in schedule repair and, in turn, on-time project delivery. The study is the first related to COD and their interactions in construction projects in the digital era.

This study explores how auditors' emotions, specifically negative moods triggered by flight delays, impact auditing quality.

Utilizing flight delays during audit assignments as a mood indicator, weather conditions at departure airports serve as an instrumental variable to provide a robustness check between flight delays and audit outcomes, employing a two-stage least squares model.

The findings suggest that such negative moods improve auditing effort and quality, as evidenced by reduced future accounting restatements and increased audit fees. The positive effect of flight delays on auditing quality is consistent across different tests and measures.

This study highlights the significance of auditors' emotional states on their professional performance, indicating a unique angle on auditing quality research by focusing on the emotional well-being of auditors as influenced by external factors such as flight delays.

Clause 8 is about time; the time period for the performance of the Works (the beginning and the end), management of the Programme, the Contractor’s right to Extension of Time and the Employer’s right to suspend progress of the Works. Once the Works have been completed, Clause 9 [Tests on Completion] deals with the testing at completion and Clause 10 [Employer’s Taking Over] deals with the mechanics for the Employer’s Taking Over of the Works. Clause 11 [Defects after Taking Over] deals with defects after the Employer’s Taking Over. See also Figure 8.

The phenomenon of delayed payment to contractors, particularly in the construction industry, is a vital one and has implications for the health of economies of both developing and developed countries. However, the knowledge of this phenomenon seems patchy and scattered. This paper aims to provide a comprehensive overview of the knowledge on the subject matter with directions for future research.

A systematic literature review coupled with a scientometric analysis was used to identify the main strands of delayed payment to contractor research as a basis for qualitative analysis and directions for future investigations.

Current trends of delayed payment to contractor research are categorised into five broad themes, namely: causes, effects, mitigation measures, ethical and law and regulatory issues. On the basis of these themes, directions for future research are proffered.

To the best of the authors knowledge, this is the first attempt at providing a comprehensive and an integrated knowledge on delayed payment to contractor research with pointers for further investigation and policy directions.

Construction delay always causes massive damage to the advancing construction industries, which is no different in the case of Bangladeshi construction industries. This paper aims to investigate the major delay factors causing construction delays in public-funded, mixed and private-funded construction projects of Bangladesh. Also, it offers preventive suggestions from expert stakeholders to reduce the recurrence of delays.

At first, an extensive literature review was conducted to identify the thirty-seven major delay factors categorized under seven groups. A questionnaire was then developed for survey at ongoing construction projects at a different division of Bangladesh. Next, data from 110 respondents were collected, and the delay factors were ranked based on the Relative Importance Index (RII); lastly, probable solutions were suggested for top-ranked delay factors based on opinions from expert stakeholders in the construction sector of Bangladesh.

The overall RII ranking of the 37 delay factors showed “Construction mistakes and defective work,” “Contract modifications by the client” and “Adverse weather condition” as the top three factors causing the delay. For public-funded projects, “Construction mistakes and defective work” and “Slow decision making by a consultant” are the top delay factors. For mixed projects, “Slow decision making of the client” and “Construction mistakes and defective work ranked top, and for private-funded projects, “Financial problems and payment delay of the client” and “Adverse weather condition” ranked top. These nuances of ranking in individual project types ascertain that the causes of delay vary in terms of project features.

The outcome of this project will help identify the significant delay factors based on their severity of effectiveness associated with public-funded, mixed and private-funded projects in Bangladesh. The suggestions regarding preventing these delay factors obtained through the opinions of expert stakeholders can help reduce the effect of these delays in the context of Bangladesh and in countries where the similarity in construction environment prevails.

Previously, studies on construction delays in Bangladesh focused mainly on identifying the delays using qualitative analysis techniques. This study is based on a unique methodology of integrating quantitative research on delay factor identification and qualitative research on preventive measures following the opinions gathered from expert stakeholders in the construction sector.

Opportunistic and delayed maintenances are increasingly becoming important strategies for sustainable maintenance practices since they increase the lifetime of complex systems like aircrafts and heavy equipment. The objective of the current study is to quantify the optimal time window for adopting these strategies.

The current study considers the trade-offs between different costs involved in the opportunistic and delayed maintenances (of equipment) like the fixed cost of scheduled maintenances, the opportunistic rewards that may be earned and the cost of premature parts replacement. The probability of the opportunistic maintenance has been quantified under two different scenarios – Mission Reliability and Renewal Process. In the case of delayed maintenance, the cost of the delayed maintenance is also considered. The study uses optimization techniques to find the optimal maintenance time windows and also derive useful insights.

Apart from finding the optimal time window for the maintenance activities the study also shows that opportunistic maintenance is beneficial provided the opportunistic reward is significantly large; the cost of conducting scheduled maintenance in the pre-determined slot is significantly large. Similarly, the opportunistic maintenance may not be beneficial if the pre-mature equipment parts replacement cost is significantly high. The optimal opportunistic maintenance time is increasing function of Weibull failure rate parameter “beta” and decreasing function of Weibull failure rate parameter “theta.” In the case of optimal delayed maintenance time, these relationships reverse.

To the best of our knowledge, very few studies exist that have used mission reliability to study opportunistic maintenance or considered the different cost trade-offs comprehensively.