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The purpose of this study is to solve two unique but difficult partial differential equations: the foam drainage equation and the nonlinear time-fractional fisher’s equation. Through our methods, we aim to provide accurate solutions and gain a deeper understanding of the intricate behaviors exhibited by these systems.

In this study, we use a dual technique that combines the Aboodh residual power series method and the Aboodh transform iteration method, both of which are combined with the Caputo operator.

We develop exact and efficient solutions by merging these unique methodologies. Our results, presented through illustrative figures and data, demonstrate the efficacy and versatility of the Aboodh methods in tackling such complex mathematical models.

Owing to their fractional derivatives and nonlinear behavior, these equations are crucial in modeling complex processes and confront analytical complications in various scientific and engineering contexts.

Being an efficient mechanism for the value of money, public–private partnership (PPP) is one of the most prominent approaches for infrastructure construction. Hence, many controversies about the performance effectiveness of these delivery systems have been debated. This research aims to develop a novel performance management perspective by revealing the causal effect of key performance indicators (KPIs) on PPP infrastructures.

The literature review was used in this study to extract the PPPs KPIs. Experts’ judgment and interviews, as well as questionnaires, were designed to obtain data. Copula Bayesian network (CBN) has been selected to achieve the research purpose. CBN is one of the most potent tools in statistics for analyzing the causal relationship of different elements and considering their quantitive impact on each other. By utilizing this technique and using Python as one of the best programming languages, this research used machine learning methods, SHAP and XGBoost, to optimize the network.

The sensitivity analysis of the KPIs verified the causation importance in PPPs performance management. This study determined the causal structure of KPIs in PPP projects, assessed each indicator’s priority to performance, and found 7 of them as a critical cluster to optimize the network. These KPIs include innovation for financing, feasibility study, macro-environment impact, appropriate financing option, risk identification, allocation, sharing, and transfer, finance infrastructure, and compliance with the legal and regulatory framework.

Identifying the most scenic indicators helps the private sector to allocate the limited resources more rationally and concentrate on the most influential parts of the project. It also provides the KPIs’ critical cluster that should be controlled and monitored closely by PPP project managers. Additionally, the public sector can evaluate the performance of the private sector more accurately. Finally, this research provides a comprehensive causal insight into the PPPs’ performance management that can be used to develop management systems in future research.

For the first time, this research proposes a model to determine the causal structure of KPIs in PPPs and indicate the importance of this insight. The developed innovative model identifies the KPIs’ behavior and takes a non-linear approach based on CBN and machine learning methods while providing valuable information for construction and performance managers to allocate resources more efficiently.

The current estimation practice in construction projects greatly needs upgrading, as there has been no improvement in the cost overrun issue over the past 70 years. The purpose of this research was to develop a new multiple regression analysis (MRA)-based model to forecast the final cost of road projects at the pre-design stage using data from 43 projects in New Zealand (NZ).

The research used the case study of 43 completed road projects in NZ. Document analysis was conducted to collect data, and statistical tests were used for model development and analysis.

Eight models were developed, and all models achieved the required F statistics and met the regression assumptions. The models’ mean absolute percentage error (MAPE) was between 21.25% and 22.77%. The model with the lowest MAPE comprised the road length and width, number of bridges, pavement area, cut and fill area, preliminary cost and cost indices change.

The model is based on road projects in NZ. However, it was designed to be able to adapt to other contexts. The findings suggest that the model can be used to improve traditional conceptual estimating methods. Past project data is often stored by the project team but rarely used for analysing and forecasting purposes. This research emphasises that past data can be effectively used to predict the project cost at the pre-design stage with limited information.

No research was conducted to adopt cost modelling techniques into the conceptual estimation practice in the NZ construction industry.

The purpose of this paper is to investigate the mediating role of satisfaction (SAT) in relation to mobile banking service quality (MB-SQ) and continuance intention (CI) among Nepali mobile banking users.

The paper adopted a quantitative approach and cross-sectional survey research design. Data were collected with structured questionnaires from 326 mobile banking users. A partial least squares structural equation modeling (PLS-SEM) and artificial neuro network (ANN) approach were applied to examine hypotheses.

Results confirm a significant positive influence of MB-SQ on SAT and CI of mobile banking adoption. Moreover, MB-SQ partially mediates the relationship between SAT and CI of mobile banking adoption.

Based on the findings of this research, theoretically, this paper attempted to investigate the mediating role of MB-SQ in the CI of mobile banking, and managerially, mobile banking service providers could have insights on designing mobile banking service marketing strategy.

This paper is among the earliest studies to investigate the role of MB-SQ as a higher-order reflective-reflective construct on CI. Moreover, the endogeneity issue has been tested, and ANN has been applied to investigate the predictive relevance of SAT and MB-SQ on CI of mobile banking users. Furthermore, the authors have delved into the ongoing discourse surrounding Generation Y and Generation Z, exploring their implications on CI within the realm of mobile service quality. It provides a critical juncture for understanding continuance intention in the mobile service quality context.

The main goal of the article is to determine the mediating role of HRM outcomes in the relationships between staffing the organization and company performance results and to establish whether there are any identifiable regularity in this scope in the pre-pandemic and pandemic period in the HQs and foreign subsidiaries of MNCs.

The empirical research included 200 MNCs headquartered in Central Europe. To capture the actual relations between the variables under study the raw data in the variables were adjusted with the efficiency index (EI). The Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to verify the research hypotheses and assess the mediating effects.

The research findings show that, with the exception of the HQs in the pandemic period, when staffing had a negative effect on the company performance results in quality, in other cases it had a positive effect on results in HRM, finance, innovativeness and quality, both in the pre-pandemic and pandemic period, although this effect was not always statistically significant. Furthermore, the company's performance results in HRM mediate positively the relationships between staffing and the other three categories of company performance results, regardless of the organizational level (HQs' or subsidiaries') and time period under consideration. Additionally, during the pandemic, the company's performance results in HRM mediate the relationships between staffing and the other company's performance results stronger than in the pre-pandemic time.

In addition to confirming the results of some other studies, the article also provides new knowledge. It determines the mediating role of HRM outcomes in the relationship between staffing and company performance results in finance, innovativeness and quality. Moreover, it identifies certain regularities in the four studied contexts, which is a novelty in this type of research. It also uses an innovative approach to including employee KPIs as the efficiency index in analyzing the relationships between the variables under study.

The effectiveness of a message and its attributes have become important for digital media. This study aims to investigate how different elements of a website including both argument-oriented and emotional stimuli based on the elaboration likelihood model (ELM) can affect the issue involvement and change the attitude of the website visitors of a healthcare service provider.

The Ministry of Health and Education (MOHME) website was selected to explore how its content and design can persuade visitors. An online survey was conducted on 355 adults engaging in health protection behaviors during the COVID-19 pandemic.

Structural equation modeling (SEM) analysis showed that one design element, i.e. website navigation and one social cue, i.e. social connectedness, have positive impact on issue involvement, while social presence and website satisfaction have a negative effect on issue involvement because of the random fluctuation suppressor effect. In addition, prior knowledge significantly influenced the issue's involvement. Further, website satisfaction has impacted attitudes directly. There was no significant relationship between argument quality and issue involvement.

Previous works have studied health-related behaviors in offline contexts; however, the scholars have not focused on the individuals' persuasion using ELM regarding the healthcare services provided in online communities. The results of the current study have theoretical and practical implications for scholars, website designers and policymakers.

This paper aims to prevent gasket sealing failure in engineering, accurately predict gasket life, extend system life and improve sealing reliability. The accelerated life test method of flexible graphite composite–reinforced gaskets is established, the life distribution law of flexible graphite composite–reinforced gaskets is revealed, and the life prediction method of flexible graphite composite–reinforced gaskets with different allowable leakage rates is proposed, which can provide a reference for the life prediction of other types of gaskets.

In this study, flexible graphite composite–reinforced gaskets were tested for long-term high-temperature sealing performance on a multi-sample gasket accelerated life test rig. The data were also analyzed using the least squares method and the K-S hypothesis calibration method. A gasket time-dependent leakage model and an accelerated life model were also developed. Constant stress-accelerated life tests were conducted on flexible graphite composite–reinforced gaskets. On this basis, a gasket life prediction method at different allowable leakage rates was proposed.

The life distribution law of flexible graphite composite–reinforced gaskets is revealed. The results show that the life of the gasket obeys the Weibull distribution. The time-correlated leakage model and accelerated life model of the gasket were established. And the accelerated life test method of the flexible graphite composite–reinforced gasket was established. The life distribution parameters, accelerated life model parameters and life estimates of gaskets were obtained through tests. On this basis, a gasket life prediction method under different leakage rates was proposed, which can be used as a reference for other types of gaskets.

The research in this paper can better provide guidance for the use and replacement of gaskets in the project, which is also very meaningful for predicting the leakage condition of gaskets in the bolted flange connection system and taking corresponding control measures to reduce energy waste and pollution and ensure the safe operation of industrial equipment.

A multi-specimen gasket-accelerated life test device has been developed, and the design parameters of the device have reached the international advanced level. The life distribution law of the flexible graphite composite–reinforced gasket was revealed. The accelerated life test method for the flexible graphite composite–reinforced gasket was established. The life prediction method of the flexible graphite composite–reinforced gasket under different allowable leakage rates was proposed.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0254/

This study aims to empirically explore the influence of managerial ability on crash risk and the moderating effect of financial constraints on this interrelationship.

Using a sample of listed corporations in the Egyptian Stock Exchange during 2018–2021, the authors test the hypotheses by using the measures and methods well established in prior literature. The authors also conduct multiple robustness analyses to ensure the validity of the empirical results.

The findings suggest that managerial ability can effectively inhibit crash risk. In addition, the authors report that financial constraints significantly dampen this relationship. Thus, financial restrictions play a striking role in hampering the managerial ability to prevent stock crashes. Furthermore, the authors document that the moderating role of severe financing constraints is more prominent during the Covid-19 pandemic period.

The originality of this study stems from the following considerations. First, this study enriches relevant studies on crash risk by providing evidence from one of the emerging markets in the Middle East; thereby, contrasting with those in developed economies. Second, to the best of the authors’ knowledge, this is the first study investigating the moderating impact of financing constraints on the managerial ability and crash risk nexus. Therefore, this work adds value to the extant knowledge by scrutinizing this important issue and providing novel empirical evidence.

While COVID-19 mitigation measures (CMMs) aided in steady recovery during the pandemic, they also impeded movement across economies/borders, affecting quality assurance (QA) of Cross-border Construction Logistics and Supply Chain (Cb-CLSC). However, prior studies on the pandemic in the construction project industry have not revealed how CMMs have impacted QA. Thus, this study aims to evaluate the impact of the CMMs on the QA of Cb-CLSC.

This is achieved by adopting an embedded mixed-method approach involving a desk literature review and engaging 150 experts from different economies across the globe using expert surveys, and results verified via semi-structured expert interviews. Structural equation modelling-based multiple regression analysis (SEM-MRA) was integrated to examine the impact of the CMMs on the QA, along with descriptive and content analysis.

The study confirmed that CMMs have not only impacted the QA negatively but also influenced the positioning of the QA for the post-pandemic era and probably to survive the risks of future pandemics. Among all the identified CMMs, the top three critical measures include “lockdown (CMM2)”, “use of personal protective equipment, such as nose masks, disinfects, etc. (CMM5)”, and “electronic/virtual meetings (CMM7)”. However, CMM5 possesses the highest contributory power to form CMM in impacting the QA, and this can be regarded as largely positive by strengthening health and safety management systems. Its negative impact lies with the project cost increment and the inconveniences of using nose and face masks.

This study provides a better understanding to construction practitioners and policy makers on how the pandemic policies, i.e. CMMs, have impacted QA and can aid in formulating planning and operational decisions to adequately position the QA for the post-pandemic era and to endure the risks of future pandemics.

The study contributes to knowledge in that it provides a better understanding of how the pandemic policies, such as CMMs, have impacted QA and can aid in formulating planning and operational decisions to adequately position the QA for the post-pandemic era and to endure the risks of future pandemics. This area of study has been given limited attention among prior studies during the pandemic.

Through the “Going Digital Initiative,” the Ghanaian government has introduced policies that aim at improving the information and communication technology (ICT) infrastructure of the country. These ICT policies have benefited numerous sectors of the Ghanaian economy. In logistics management, ICT has impacted drone medical delivery in the healthcare and maritime sectors. However, the importance of ICT is not realized in the motorcycle goods transport (MGT) industry, regardless of its popularity and high economic dependency. Second, all research on motorcycles is focused on diverse social concerns, and no study has attempted to analyze ICT implementation for MGT operations. This is a significant gap in logistics management. Hence, the study aimed to investigate the impact of ICT on Ghana's MGT industry empirically.

The study adopts a two-phase data collection approach to collect the data. The authors use partial least square structural equation modeling to analyze the study's measurement and structural assessment model.

ICT positively impacts MGT and the drivers considered. The drivers positively influence MGT. The study further analyzes novel results on the relationships between the drivers and their mediating roles in enhancing MGT performance.

The study's originality is the extension of ICT adoption and usage in MGT. The lack of literature on the importance of ICT for MGT services makes this study the primary source of literature, and the relationships investigated are unique as the research area is unexplored.