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The existence of the advertising delay effect and its impact on supply chain operations have been demonstrated in the current study. Therefore, this study develops a timely inventory control strategy for the fresh produce supply chain to address the advertising delay effect in the fresh produce supply chain.

This study proposes a game model based on the Nerlove-Arrow time delay differential equation and Pontryagin's maximum principle. Through comparative analyses of the optimal equilibrium strategies, the authors compare the optimal equilibrium strategies, product goodwill and optimal inventory trajectories for suppliers and retailers under secondary replenishment decisions and decentralized decisions.

The authors find that (1) Only when the sales cycle meets certain conditions can the overall profit of the supply chain under the secondary replenishment decision be greater than that under the decentralized decision. As the price markup coefficient increases, the total profit of the supply chain first increases and then decreases. (2) With the increase in the delay time, the replenishment quantity during the initial period gradually decreases. After the delay time elapses, the inventory depletion rate under secondary replenishment decisions is faster than that under decentralized decision-making. (3) Although there is a continuously increasing maximum value of product goodwill with the increase in delay time, it becomes difficult to achieve this value for longer delays.

The authors’ findings provide a theoretical basis for supply chain members of fresh agricultural products to select replenishment and inventory control strategies when adopting different levels of delay in advertising marketing.

Firstly, this paper explains the impact of advertising delay effect on fresh produce supply chain from a dynamic perspective, and secondly, it provides guidance on advertising formulation and inventory replenishment for fresh produce retailers under the influence of advertising delay effect.

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.

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.

This study develops and validates a theoretical model of real-time mobile connectivity, examining how employees' perceptions of their relationship with supervisors influence their emotional experiences. Through quasi-experiments, the authors investigate the behavioral patterns and emotional responses associated with real-time mobile connectivity in organizations, with a focus on messaging apps that indicate message read status. Specifically, they explore how supervisors' attentiveness or inattentiveness in mobile connectivity impacts emotional ambivalence (anxiety and pride) among subordinates. Additionally, they examine the downstream effects of this emotional ambivalence on employees' workplace thriving and job performance across various dimensions.

To address the paradox of real-time mobile connectivity, a quasi-experimental design involving 320 team members from 46 teams was implemented. Multi-level structural equation modeling was employed to analyze within-person variance and evaluate the proposed hypotheses.

The findings indicate that employees who do not receive timely indications from their supervisors are more likely to experience elevated levels of anxiety, while those who receive prompt indications experience a sense of pride. Moreover, the indirect effects of the real-time mobile connectivity paradox on employee performance, mediated by anxiety (negatively) and pride (positively), are fully explained through workplace thriving.

This study provides insights into the emotional ambivalence experienced in the workplace due to real-time mobile connectivity, highlighting its implications for organizational competitiveness. Integrating resource conservation theory and cognitive appraisal theory of emotion, the study explores the mediating role of workplace thriving and the impact on employee performance through pride and anxiety. Generalizability requires considering organizational settings and cultural contexts while acknowledging limitations such as a focus on messaging apps and specific samples. Future research should explore these dynamics in diverse contexts and identify additional factors influencing the relationship between real-time mobile connectivity and employee outcomes.

This study provides valuable insights for managers regarding the significance of message indications, as their attentiveness can elicit emotional reactions from employees that subsequently impact workplace thriving and job performance.

This study pioneers the exploration of the paradox of real-time mobile connectivity in the workplace, uncovering the discrete emotions experienced by employees. Furthermore, it elucidates the subsequent opposing effects on workplace thriving and job performance, contributing to the existing literature and knowledge in this area.

Construction projects commonly encounter complicated delay problems. Over the past few decades, numerous delay analysis methods (DAMs) have been developed. There is no consensus on whether existing DAMs effectively resolve delays, particularly in the case of complex concurrent delays. Thus, the primary objective of this study is to undertake a comprehensive and systematic literature review on concurrent delays, aiming to answer the following research question: Do existing delay analysis techniques deal with concurrent delays well?

This study conducts a comprehensive review of concurrent delays by both bibliometric and systematic analysis of research publications published between 1982 and 2022 in the Web of Science (WoS) and Scopus databases. For quantitative analysis, a bibliometric mapping tool, the VOSviewer, was employed to analyze 68 selected publications to explore the co-occurrence of keywords, co-authorship and direct citation. Additionally, we conducted a qualitative analysis to answer the targeted research question, identify academic knowledge gaps and explore potential research directions for solving the theoretical and practical problems of concurrent delays.

Concurrent delays are a critical aspect of delay claims. Despite DAMs developed by a limited number of research teams to tackle issues like concurrence, float consumption and the critical path in concurrent delay resolution, practitioners continue to face significant challenges. This study has successfully identified knowledge gaps in defining, identifying, analyzing and allocating liability for concurrent delays while offering promising directions for further research. These findings reveal the incompleteness of available DAMs for solving concurrent delays.

The outcomes of this study are highly beneficial for practitioners and researchers. For practitioners, the discussions on the resolution process of concurrent delays in terms of identification, analysis and apportionment enable them to proactively address concurrent delays and lay the groundwork for preventing and resolving such issues in their construction projects. For researchers, five research directions, including advanced DAMs capable of solving concurrent delays, are proposed for reference.

Existing research on DAMs lacks comprehensive coverage of concurrent delays. Through a scientometric review, it is evident that current DAMs do not deal with concurrent delays well. This review identifies critical knowledge gaps and offers insights into potential directions for future research.

Change orders are a typical occurrence in building projects. Change orders indirectly affect labor productivity, resulting in a significant delay in the completion of a building project. Change orders cause labor productivity losses that are difficult to describe, establish and account for contractors and subcontractors. This study aimed to look at the influence of change orders on labor productivity and develop methods to mitigate their adverse effects.

To assess the change orders' impact on productivity levels a system dynamic model was developed and devise ways were developed to counteract these negative impacts in this research. The impact of change orders on labor productivity and project time was then controlled using techniques established. Finally, a case study of KUET's hall extension was chosen, and the model and principles developed were implemented.

This study established that if the project delivery date is set and change orders are occurring often, labor productivity will be impacted. With adequate monitoring and supplemental management techniques, it can be reduced by prolonging the project.

The developed policies aid to mitigate the effect of change orders on labor productivity.

One of the insidious effects of government and business imposter scams is the potential erosion of trust among defrauded consumers. This study aims to assess the relationship between prior imposter scam victimization and present ability to discriminate between real and fake digital communications from government agencies and retail companies.

This paper tests whether a short, interactive training can help consumers correctly identify imposter scams without mistrusting legitimate communications. Participants were randomized into one of two control groups or to one of two training conditions: written tips on identifying digital imposter scams, or an interactive fraud detection training program. Participants were tested on their ability to correctly label emails, websites and letters as real or a scam.

This paper find that prior imposter scam victimization is not associated with greater mistrust. Compared to the control conditions, both written tips and interactive digital fraud detection training improved identification of real communications and scams; however, after a two- to three-week delay, the effect of training decreases for scam detection.

Results indicate that prior imposter scam victimization is not associated with mistrust, and that one-time fraud detection training improves consumers’ detection of imposter scams but has limited long-term effectiveness.

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.

Eco-innovation products, which means achieving more efficient and responsible use of resources and reducing the detrimental impact on the environment, can win a competitive advantage for the enterprises. But it is not easy to implement due to the high cost of eco-innovative technologies development, the uncertainty of market needs and return risk of investment. Many enterprises seek collaborations from their upstream suppliers to jointly carry out eco-innovation, such as Apple, IBM and Nike. A unique feature of collaboration is that efforts by one party enhance the marginal value of the other party's efforts. However, the collaboration will make the partner know the eco-innovation technology and prompt the partner to encroach the market to sell competitive products by herself. Motivated by this observation, this paper considers the optimal collaboration strategy on eco-innovation between upstream and downstream supply chain member and the optimal encroachment strategy of upstream supplier in a supply chain.

This paper models a supply chain wherein a supplier provides products or materials for her manufacturer and cooperates with her manufacturer in eco-innovation. Also, the supplier could encroach on the market to sell similar products by herself. Then this paper uses game theory and mathematical modeling to do relative analysis.

The analysis reveals several interesting insights. First, eco-innovation collaboration makes supplier encroachment no longer only rely on the encroachment cost. The delayed realized eco-innovation efficiency information also plays a vital role. Second, different from previous research, the authors find the manufacturer's preference for supplier encroachment depends on the uncertainty of eco-innovation efficiency and potential market demand. Third, both partial and full encroachment strategies of the supplier can effectively improve the eco-innovation level.

The paper is the first to take the interplay between collaboration and encroachment into account in a supply chain. The results caution enterprises and policymakers to take vertical collaboration and delayed realized information into account in the competitive supply chain before making any operational decisions. Furthermore, the authors propose that governmental intervention aimed at stimulating supplier encroachment in appropriate circumstances can contribute to the improved environmental performance of products.

The effects of the COVID-19 outbreak on the construction industry were formidable and far-reaching, as the construction sector is a major contributor to the gross domestic product (GDP), which balances various sectors of the global economy, and to infrastructure growth, which is a primary gauge of a nation’s advancement. The outbreak led to workforce disruptions, worker deficits, dwindling efficiency, elongated project durations, and scarce opportunities for training and mentorship, and despite endeavors to mitigate these challenges, construction timelines experienced significant interruptions. Various researchers have pinpointed contributing elements, but few have constructed a predictive model to gauge the degree of impact.

Therefore, this research intends to fill by introducing an ordinal logistic regression method to forecast the impacts of a pandemic or other similar type of crisis. To achieve this, an online survey was developed and distributed to collect the perceptions of the construction engineers and managers about the diverse contributors to the exceeding project timelines during the COVID-19 pandemic outbreak.

Findings from this study indicate that financial liquidity, modifications to original plans, delays in securing governmental clearances, and a shortage of competent labor have medium-to-high levels of impact on project schedules.

This study will furnish decision-makers with crucial knowledge that will give them the tools to refine their strategies and judiciously allocate resources to overcome the unique hurdles encountered by various construction segments and will enhance the industry's capability to respond more effectively to challenges inherent in this type of crisis.