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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.

The purpose of this study is to examine the association between the combined roles of chief executive officer (CEO)-chairman titles (CEO duality) and investment efficiency, defined as a lower deviation from expected investment for targeted S-curve firms used to propel an innovation-driven economy. This study also aims to investigate the moderating effect of financial reporting quality on this association.

This paper focuses on the ten targeted S-curve industries – under the definition of the Thailand 4.0 model – listed on the Stock Exchange of Thailand (SET) from 2000 to 2019. Data related to CEO/chairman titles and investment supports were manually collected from the annual reports, the SET market analysis and reporting tool database and the company websites. Financial data used to estimate investment behaviors and discretionary accruals were extracted from 1999. The study analyzes unbalanced panel data using fixed-effects regressions. Additional tests embrace replacing the sample with nontargeted firms, partitioning into granted and nongranted firms, adding CEOs’ demographic moderators, using alternative variable measures and analyzing for lagged independent variables.

The main findings show that CEO duality reduces overinvestment but worsens underinvestment in targeted firms. Financial reporting quality (FRQ) appears to strengthen CEO duality in mitigating extreme spending but has no impact on the association between CEO duality and underinvestment. Additional results, for example, conclude that CEO duality has no association with both over- and underinvesting at nontargeted firms, but its effect becomes positively significant on overinvestment when financial reporting quality is high. The negative association between CEO duality and overinvestment is found only in government-granted and targeted firms. FRQ encourages CEO duality in lowering overinvestment among targeted firms without grants. CEOs’ female and serviced early years appear to elevate those main findings.

These findings assist innovative corporations in choosing a proper leadership structure to cope with investment inefficiency. The research gives the government and regulatory bodies an insight into the qualifications of the leadership structure and financial information that helps them put forward effective policies.

To the best of the author’s knowledge, this study is among the first to establish the association between CEO duality and investment efficiency for innovation-driven firms in a transforming economy. The study fills the gap in the literature on management, accounting and finance by unveiling the interplay between dual leadership and financial reporting in affecting the efficiency of investments.

The intelligent connected vehicle (ICV) is an important trend in automobile development, but little research has been conducted on the technological differences in the ICV industry across countries. In this regard, the authors select China, the United States (US) and the European Union (EU) as countries with developed ICV industries to reveal these differences based on the perspective of subdivision technology.

The authors use logistic regression to fit lifecycles at technology level and country level based on ICV-related patents from China, the US and the EU, then use the Revealed Technological Advantage (RTA) index, Fast-Growing Specialization Index (FGSI) and International Patent Classification (IPC) numbers to conduct comparison of national technology advantages, finally use the social network analysis to investigate the evolution of characteristics and intermediate nodes of each technology innovation network.

Technology lifecycles vary according to the subdivision technology and country. The global development of the ICV industry has reached the mature stage, and 2030 may be a watershed moment, ushering in a wave of new technology iterations. In various subdivision technologies, China and the US have more leading RTAs, and China and the EU have more leading FGSIs. Innovation networks in different countries expand with technology lifecycles, with that in China being the fastest. China's Universities, the US's enterprises and the EU's research institutes are active in cooperative innovation as intermediaries.

This is the first study to compare the development of the ICV industry in major countries from the perspective of subdivision technology and reveal characteristics of innovation networks in each.

A smart city integrates a comprehensive suite of technologies, which inherently require data to function effectively. It is designed with the intention of amassing all available data concerning machines, devices, infrastructure, individuals and their surroundings. This commentary addresses the evolution of smart cities over time, the increasing extent of data collection, the growing pressure on personal privacy and people's reactions to these trends. The article highlights the contradiction between the needs of the city and the desires of its inhabitants. It notes that people react differently to gradual versus abrupt changes in data-collecting technologies and services. It also suggests that more work needs to be done to prepare both smart cities and the human population for a sustainable, mutually beneficial future.

This commentary presents a viewpoint on the subject of data collection and privacy in smart cities, drawing on various sources to support its observations and conclusions.

The primary focus of this discussion is on the technological evolution of the cities. It emphasizes that, as cities get smarter, they offer more conveniences in exchange for various types of data, highlighting the likelihood that pressure on personal privacy will continue to escalate. This is due to the increasing pervasiveness of data-collecting technologies in every aspect of lives and urban environments. These environments are expected to become progressively smarter each year. Given this context, and to ensure a seamless transition to smart and sustainable cities, it is imperative that today's privacy discussions start to focus not only just on the existing but also on the future conditions and challenges that citizens are expected to encounter.

This commentary delves into the existing gaps in understanding the contradiction between the data-collection “needs” of smart cities, the direction in which the cities are evolving and people's awareness of how much data they will have to surrender in the future. It also highlights the risk of people gradually relinquishing nearly all their privacy, often without noticing, in exchange for the ever-increasing conveniences offered by smart cities.

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.

The purpose of this study is to improve communication success through barrier identification and analysis so that the identified barriers can help project teams establish effective information-exchange strategies.

The recent publications on construction communication about time management are reviewed. Then, the semi-structured interviews are performed with both questionnaires and audio recordings (n1 = 18). Next, the collected data are analyzed using both statistical measures on the questionnaire survey and qualitative coding analysis on the text transcripts from an audio recording. Particularly, the identified barriers are substantiated using a scientometrics approach based on the published articles (2011–2020, n2 = 52,915) for purposeful information-sharing solutions in construction time management. Furthermore, the intervention strategies from the top 10 most-cited articles are analyzed and validated by comparisons with the results from construction surveys and relevant studies.

Based on the discussed communication difficulties, five main barriers were identified during time-cost risk management: probability and statistical concepts, availability of data from external resources, details of team member experiences, graphics (and graphical presentation skills), and spatial and temporal (a.k.a. 4D) simulation skills. For the improvement of communication skills and presentation quality regarding probability and statistical concepts, project teams should emphasize context awareness, case studies and group discussions. Details of communication techniques can be adjusted based on the backgrounds, experiences and expectations of team members.

The dataset n1 has both size and duration limits because of the availability of the invited industry professionals. The dataset n2 considers the literature from 2011 to 2020. Any before-the-date and unpublished studies are not included in the study.

A thorough comprehension of communication barriers can help project teams develop speaking, writing and analytical thinking skills that will enable the teams to better deliver ideas, thoughts and meanings. Additionally, the established discussion on barrier-removal strategies may enhance time management effectiveness, reduce project delays, avoid confusion and misunderstanding and save rework costs.

This research calls for the awareness of communication barriers in construction project execution and team collaboration. The identified barriers and the established solutions enrich the approaches of construction companies to share information with communities and society.

This is the first identification model for communication barriers in the time management of the construction industry to the authors' knowledge. The influencing factors and the countermeasures of communication difficulties highlighted by the research were not examined systematically and holistically in previous studies. The findings provide a new approach to facilitate the development of powerful communication strategies and to improve project execution.

The purpose of this paper is to compile a comprehensive status report on pipes/piping networks across different industrial sectors, along with specifications of materials and sizes, and showcase welding avenues. It further extends to highlight the promising friction stir welding as a single solid-state pipe welding procedure. This paper will enable all piping, welding and friction stir welding stakeholders to identify scope for their engagement in a single window.

The paper is a review paper, and it is mainly structured around sections on materials, sizes and standards for pipes in different sectors and the current welding practice for joining pipe and pipe connections; on the process and principle of friction stir welding (FSW) for pipes; identification of main welding process parameters for the FSW of pipes; effects of process parameters; and a well-carved-out concluding summary.

A well-carved-out concluding summary of extracts from thoroughly studied research is presented in a structured way in which the avenues for the engagement of FSW are identified.

The implications of the research are far-reaching. The FSW is currently expanding very fast in the welding of flat surfaces and has evolved into a vast number of variants because of its advantages and versatility. The application of FSW is coming up late but catching up fast, and as a late starter, the outcomes of such a review paper may support stake holders to expand the application of this process from pipe welding to pipe manufacturing, cladding and other high-end applications. Because the process is inherently inclined towards automation, its throughput rate is high and it does not need any consumables, the ultimate benefit can be passed on to the industry in terms of financial gains.

To the best of the authors’ knowledge, this is the only review exclusively for the friction stir welding of pipes with a well-organized piping specification detailed about industrial sectors. The current pipe welding practice in each sector has been presented, and the avenues for engaging FSW have been highlighted. The FSW pipe process parameters are characteristically distinguished from the conventional FSW, and the effects of the process parameters have been presented. The summary is concise yet comprehensive and organized in a structured manner.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

In this paper, the authors aim to study the effect of hydrogen on the pitting corrosion behavior of Incoloy 825, a commonly used material for heat exchanger tubes in hydrogenated heat exchangers.

The pitting initiation and propagation behaviors were investigated by electrochemical and chemical immersion experiments and observed and analyzed by scanning electron microscope and energy dispersive spectrometer methods.

The results show that hydrogen significantly affects the electrochemical behavior of Incoloy 825; the self-corrosion potential decreased from −197 mV before hydrogen charging to −263 mV, −270 mV and −657 mV after hydrogen charging, and the corrosion current density increased from 0.049 µA/cm² before hydrogen charging to 2.490 µA/cm², 2.560 µA/cm² and 2.780 µA/cm² after hydrogen charging. The pitting susceptibility of the material increases.

Hydrogen is enriched on the precipitate, and the pitting corrosion also initiates at that location. The synergistic effect of hydrogen and precipitate destroys the passive film on the metal surface and promotes pitting initiation.

This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis.

The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making.

Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool.

To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.