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An S-curve is an essential project-management tool. However, it is difficult to adjust S-curve to deal with a force majeure event. The present study develops four valuable adjustment approaches, designed to achieve a compromise between the views of the client and contractor. These can be used to control projects after a force majeure event.

The present study develops four adjustment approaches, which can be used to achieve a compromise between the views of the client and those of the contractor when controlling projects after a force majeure. To determine the S-curves during a force majeure event, two approaches can be selected: BCWS (budgeted cost of scheduled work)-base approach, or BCWP (budgeted cost of work performed)-base approach. To determine the rest of S-curves after a force majeure event, two approaches can be considered: maintaining the original curve of the remaining BCWS, or allocating the original curve of the remaining BCWS. Based on the validation of three empirical cases, drawn from a professional project-management website, this study confirms the feasibility of four proposed empirical approaches and a selection procedure for S-curve adjustment.

The S-curve-adjustment approaches presented here can be used to deal with cases that are ahead of, on and behind schedule. Using the proposed approaches and selection procedure, contractors can easily revise S-curves and control projects more effectively. To deal with a force majeure event, such as COVID-19, they are strongly advised to adopt the approaches labeled SA-A1 (to adjust the S-curve based on the extension ratio multiplied by the difference in progress during the force majeure) and SA-B1 (to maintain the original curve of the remaining BCWS) for the A/E and E/F curves, respectively.

The proposed approaches can be used in cases of continuous construction during force majeure events. If construction work is totally suspended during such an event, it will be necessary to fine-tune the proposed approaches.

Previous studies have used case-oriented or mathematical-simulation approaches to forecast S-curves. The present study proposes simple approaches that allow the client and contractor to adjust the S-curve easily after a force majeure event. These approaches can be used to adjust work and project-completion targets within an extended duration. Selecting the right S-curve adjustment approach can help to control the remainder of the project, reducing the possibility of delay claims.

This paper aims to propose an expatriate psychological adjustment model that postulates expatriate mental health as an antecedent to psychological adjustment. It presents novel predeparture and post-arrival international human resource management (IHRM) expatriate management mental health supportive interventions.

This paper critically reviews theoretical frameworks in the IHRM domain around expatriate psychological adjustments such as the U-Curve Adjustment Theory (Lysgaard, 1995), the Framework of International Adjustment (Black et al., 1991), the Dimensions of Expatriate Adjustment (Haslberger et al., 2013) and the Stress Outcome Model (Bader and Berg, 2014), in a quest to develop a new conceptual framework. This study presents a new conceptual framework along with propositions to take into consideration the relationship between mental health and expatriates' psychological adjustment.

The findings suggest that mental health is an antecedent paramount to psychological adjustment. The paper proposes mental health-supportive IHRM expatriate management interventions to address the potential failure of expatriates' psychological adjustment. The authors elaborate on the IHRM expatriate management policies and practices at the home and host country to ensure the mental health of company-assigned expatriates sent on international assignments.

The novel conceptual framework underpins mental health as the antecedent paramount to expatriate adjustment, taking into consid eration the elevated stress of situational events such as COVID-19, which had previously not received substantive formal consideration by research scholars in the IHRM domain. The conceptual framework encourages the inclusion of mental health as an antecedent in future research.

This paper aims to conduct an analysis of the influence of both the breadth and depth of outward foreign direct investment (OFDI) undertaken by Chinese high-tech listed companies during the period spanning 2010–2019. The data pertaining to these companies was used as a research sample to analyze the effects of OFDI on radical innovation performance.

Hierarchical regression analysis was used to test the proposed models, using survey data collected from 442 high-tech companies in China.

The findings of this study indicate a curvilinear (i.e. U-shaped) relationship between the breadth/depth of OFDI and radical innovation performance. Additional analysis reveals that OFDI plays a role in facilitating innovation breakthroughs by enhancing the internal dynamic capabilities of companies. Moreover, it is observed that a well-established institutional environment in the host country of investment can positively moderate the relationship between OFDI breadth/depth and radical innovation performance.

This study proffers a significant contribution to the understanding of the crucial role played by OFDI from emerging economy companies in enhancing radical innovation performance. Moreover, it offers theoretical guidance for multinational companies aiming to foster innovation breakthroughs.

Recent years have witnessed an unexpected and astonishing rise of AI-generated (AIGC), thanks to the rapid advancement of technology and the omnipresence of social media. AIGCs created to mislead are more commonly known as DeepFakes, which erode our trust in online information and have already caused real damage. Thus, countermeasures must be developed to limit the negative impacts of AIGC. This position paper aims to provide a conceptual analysis of the impact of DeepFakes considering the production cost and overview counter technologies to fight DeepFakes. We will also discuss future perspectives of AIGC and their counter technology.

We summarize recent developments in generative AI and AIGC, as well as technical developments to mitigate the harmful impacts of DeepFakes. We also provide an analysis of the cost-effect tradeoff of DeepFakes.

The mitigation of DeepFakes call for multi-disciplinary research across the traditional disciplinary boundaries.

Government and business sectors need to work together to provide sustainable solutions to the DeepFake problem.

The research and development in counter-technologies and other mitigation measures of DeepFakes are important components for the health of future information ecosystem and democracy.

Unlike existing reviews in this topic, our position paper focuses on the insights and perspective of this vexing sociotechnical problem of our time, providing a more global picture of the solutions landscape.

The Saudi 2030 Housing Program Vision aims to increase the population of Riyadh City, the capital of the Kingdom of Saudi Arabia, to between 15 and 20 million people. This paper aims to predict the demand for residential units in Riyadh City by 2030 in line with this vision.

This paper adopts a statistical modeling approach to estimate the residential demands for Riyadh City. Several population growth models, including the nonlinear quadratic polynomial spline regression model, the sigmoidal logistic power model and the exponential model, are tested and applied to Riyadh to estimate the expected population in 2030. The growth model closest to the Kingdom’s goal of reaching between 15 and 20 million people in 2030 is selected, and the paper predicts the required number of residential units for the population obtained from the selected model. Desktop database research is conducted to obtain the data required for the modeling and analytical stage.

The exponential model predicts a population of 16,476,470 in Riyadh City by 2030, and as a result, 2,636,235 household units are needed. This number of housing units required in Riyadh City exceeds the available residential units by almost 1,370,000, representing 108% of the available residential units in Riyadh in 2020.

This study provides valuable insights into the demand for residential units in Riyadh City by 2030 in line with the Saudi 2030 Housing Program Vision, filling the gap in prior research. The findings suggest that significant efforts are required to meet the housing demand in Riyadh City by 2030, and policymakers and stakeholders need to take appropriate measures to address this issue.

This paper aims to investigate the effect of chemical nickel plating and mechanical alloying on the mechanical and tribological properties of FeS/iron-based self-lubricating materials as well as the wear mechanism of the materials.

Surface modification of FeS powder was carried out by chemical nickel plating method and mechanical alloying of mixed powder by ball milling. The mechanical properties of the material were tested by tribological testing by M-200 ring block type friction and wear tester. Optical microscope was used to observe the surface morphology of the material and the transfer film on the surface of the mate parts, and scanning electron microscope and EDS were used to characterize the wear surface.

Mechanical alloying ball milling was carried out so that the lubricating particles in the matrix are uniformly dispersed; nickel-plated layer enhances the interfacial bonding of FeS and the matrix, and the combination of the two improves the mechanical properties of the material, and at the same time the friction side of the surface of the lubrication of FeS lubricant transfer film formed is denser and more intact, and the friction coefficient of friction side and the wear rate of the material have been greatly reduced.

This work aims to improve the mechanical and tribological properties of FeS/iron-based self-lubricating materials and to provide a reference for the preparation of materials with excellent overall properties.

The participation of females in economic activity remains a challenge, and received a lot of attention for a better labor policy discourse. The empirical research focused widely on the relationship between female labor force participation (FLFP) and economic development, called the feminization U-shape hypothesis. However, the linear/nonlinear relationship has been questioned due to empirical and methodological anomalies. Hence, this study aims to extend the previous work by reexamining this relationship in Pakistan.

The annual data from 1980 to 2021, the unit root tests augmented Dickey–Fuller and Phillips and Perron, the conventional autoregressive distributed lag bound test approach by including the quadratic-term of GDP per capita and the novel Sasabuchi–Lind–Mehlum (SLM) U test (2010) used for empirical estimation.

The findings revealed the prospects of a long-run nonlinear association between FLFP and economic development in Pakistan. However, an inverse U-shape exists between the female labor force participation rate (FLFPR) and GDP per capita, predicting that FLFP may decline in the future.

The traditional feminization U-shape hypothesis has little empirical support in the case of Pakistan. Therefore, the Government of Pakistan should enhance the enabling environment for females through the provision of better job opportunities, technical skills, on-the-job training and social security benefits during all phases of economic development.

The conventional approach of testing U-shape is insufficient. To the best of the authors’ knowledge, therefore, this study incorporated a wider data set in a time series that is less evident, an advanced methodology SLM U test (2010), to validate the feminization U-shape hypothesis in Pakistan for the first time.

This paper aims to design a hybrid model of knowledge-based performance management system (KBPMS) for facilitating Lean Six-Sigma (L6s) application to increase contractor productivity without compromising human safety in Indonesian upstream oil field operations that manage ageing and life extension (ALE) facilities.

The research design applies a pragmatic paradigm by employing action research strategy with qualitative-quantitative methodology involving 385 of 1,533 workers. The KBPMS-L6s conceptual framework is developed and enriched with the Analytical Hierarchy Process (AHP) to prioritize fit-for-purpose Key Performance Indicators. The application of L6s with Human Performance Modes analysis is used to provide a statistical baseline approach for pre-assessment of the contractor’s organizational capabilities. A comprehensive literature review is given for the main pillars of the contextual framework.

The KBPMS-L6s concept has given an improved hierarchy for strategic and operational levels to achieve a performance benchmark to manage ALE facilities in Indonesian upstream oil field operations. To increase quality management practices in managing ALE facilities, the L6s application requires an assessment of the organizational capability of contractors and an analysis of Human Performance Modes (HPM) to identify levels of construction workers’ productivity based on human competency and safety awareness that have never been done in this field.

The action research will only focus on the contractors’ productivity and safety performances that are managed by infrastructure maintenance programs for managing integrity of ALE facilities in Indonesian upstream of oil field operations. Future research could go toward validating this approach in other sectors.

This paper discusses the implications of developing the hybrid KBPMS- L6s enriched with AHP methodology and the application of HPM analysis to achieve a 14% reduction in inefficient working time, a 28% reduction in supervision costs, a 15% reduction in schedule completion delays, and a 78% reduction in safety incident rates of Total Recordable Incident Rate (TRIR), Days Away Restricted or Job Transfer (DART) and Motor Vehicle Crash (MVC), as evidence of achieving fit-for-purpose KPIs with safer, better, faster, and at lower costs.

This paper does not discuss social implications

This paper successfully demonstrates a novel use of Knowledge-Based system with the integration AHP and HPM analysis to develop a hybrid KBPMS-L6s concept that successfully increases contractor productivity without compromising human safety performance while implementing ALE facility infrastructure maintenance program in upstream oil field operations.

This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).

Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.

LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.

This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.

Lattice structures are widely used for achieving optimal topology in additive manufacturing. However, the use of different lattices in a single design can result in stress concentrations at the transition points. This study aims to investigate the influence of Bezier curves on mechanical properties during the transformation from one lattice structure to another. It specifically focuses on the transition from a hexagonal to diamond lattice, using Bezier curves of various orders.

The curves were designed by passing them through the same control points for different orders, such as third, fifth and seventh. The samples were sliced for 3D printing, and a tensile test was conducted. Young’s modulus and energy absorption abilities were measured to compare the mechanical properties of the models created with Bezier curves for the transformation between hexagonal and diamond models.

The analysis revealed a gradual change in mechanical properties from the hexagonal to the diamond lattice. Moreover, different orders of Bezier curves exhibited varying mechanical properties during the transformation between the two lattices. As the order of the Bezier curve increased, the mechanical properties smoothly changed from the hexagonal to diamond lattice. This prevented stress concentrations or mechanical behavior mismatch caused by sudden deformations at the transitions between the curves used in the design.

The study’s innovative use of Bezier curves of different orders to smoothly transformation between hexagonal and diamond lattices in additive manufacturing offers a practical solution to prevent stress concentrations and mechanical inconsistencies during such design transitions.