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In this paper, the authors aim to study the relationship between hydrogen embrittlement (HE) susceptibility and cathodic current density applied on the X70 steel girth welds.

The HE susceptibility of X70 steel girth welds were investigated through slow strain rate tensile test and observed and analyzed by optical microscope and scanning electron microscope methods.

The results show that HE susceptibility of X70 girth weld was basically unchanged with increasing of ion concentration while gradually increased and maintain at a specific value with the increase of cathodic current density. As for same ion content, a dense calcareous deposit layer generated on the sample surface in soil simulation solution with Ca2+ and Mg2+ resulted a decreased HE susceptibility while the porous calcareous deposit layer resulted a increased HE susceptibility.

A logistic regression model was established to describe the correlation between HE index and the cathodic current density.

The purpose of this study is to investigate the synergism of convection, current density distribution and additives by numerical simulation and electrochemical experiments for good throwing power (TP) of copper electro-deposition in printed circuit board (PCB) manufacture.

The flow field of THs and current density distribution on various AR of THs are calculated and analyzed. Meanwhile, corresponding simulation is used to study the performance of plating electrolytes on TP. Two electrochemical parameters, overpotential (η) and potential difference (△η), are chosen to evaluate the electrochemical properties of different plating solutions by galvanostatic measurement and potentiodynamic cathode polarization at different rotating speeds.

By combining both the results of simulation and practical plating, these two electrochemical properties of electrolytes exhibit significant impact to the system at varied conditions. Especially, the electrolyte with higher polarizing η and △η values lead to the elevated TP for AR of more than 2:1.

The harring cell model is built as a bridge between the theoretical and experimental study for control of uniformity of plating THs in PCB manufacturing. This dual-parameter evaluation is validated to be a promising decisive method to guide the THs plating with particular AR in industry.

This chapter explores the significance of blockchain technology in protecting data for intelligent applications across various industries. Blockchain is a distributed ledger that ensures the immutability and security of transactions. Given the increasing need for security measures in industries, understanding blockchain technology is crucial for preparing for its future applications.

This chapter aims to examine the use of blockchain technology across industries and presents a compilation of existing and upcoming blockchain technologies for intelligent applications. The methodology involves reviewing research to understand the security needs of different industries and providing an overview of methods used to enhance multi-institutional and multidisciplinary research in areas like the financial system, smart grid, and transportation system.

The findings highlight the benefits of blockchain networks in providing transparency, trust, and security for industries. The Responsible Sourcing Blockchain Network (RSBN) is an example that utilizes blockchain's decentralized ledger to track sustainable sourcing from mine to final product. This information can be shared with auditors, corporate governance organizations, and customers.

The practical implications of this chapter are significant, serving as a valuable resource for industries concerned with identity privacy, traceability, immutability, transparency, auditability, and security. Understanding and implementing blockchain technology can address the growing need for secure and intelligent applications, ensuring data protection and enhancing trust in various sectors.

This systematic review aims to identify the key determinants of knowledge transfer (KT) activities among researchers.

This study systematically reviewed KT literature in academic settings from 1995–2023. The authors searched Web of Science and Scopus using predefined keywords, following PRISMA guidelines for screening and eligibility assessment. From 158 selected articles, the authors extracted data and conducted a descriptive analysis to map KT activities’ evolution. A narrative synthesis approach categorized determinants of researchers’ KT activities.

The systematic review findings revealed a general conceptual framework that categorizes the identified determinants of KT into four categories. At the individual level, the factors are related to the sociodemographic characteristics of the researcher (e.g. gender, age, experience), their psychological aspects (e.g. attitude, intrinsic motivation, intention) and personal characteristics (e.g. self-efficacy, communication skills). At the research team level, leadership style and team dynamics. At the organizational level, the findings emphasize university characteristics (e.g. size, structure and ranking), KT culture installed and university resources. At the inter-organizational level, the key determinants were funding sources, network strength and trust.

The studies included in our database were different in terms of contexts, country of the study, the disciplines of KT and the types of KT activities examined. This variety restricts the direct comparison of research findings thus the generalizability of our conclusions. Future research should focus on specific contexts, disciplines, countries or types of KT activities to provide generalizable findings.

A better understanding of all the factors influencing KT among university researchers is essential for several reasons. First, it will enable the government to develop effective policies to promote KT ecosystems. Second, universities can create strategies, policies and programs to support researchers’ engagement in KT activities. Finally, researchers can be more strategic in their KT efforts.

This systematic review contributes to the literature by providing a comprehensive conceptual framework that identifies KT determinants at different levels and fills a gap in the existing literature that only addresses specific aspects of KT determinants. This framework can be a theoretical reference for future empirical studies. Furthermore, it practically provides recommendations for different actors including, government, universities and researchers.

China's experience of investing in Latin America in one of the main sectors included in the BRI architecture, railways, has faced significant challenges: only one of four Chinese potential railway projects in Latin America has materialised. The purpose of this paper is to explore these challenges and to provide an explanation focusing on the importance of the “domestic politics” factor.

The paper proposes a comparative study of four cases, developing a qualitative analysis based on an in-depth review of the literature and primary and secondary sources of information.

The findings suggest that domestic politics played a significant role in the outcomes of the Brazil–Peru Bi-Oceanic railway (changes in government), in Argentina's Belgrano Cargas modernisation project (multiple “domestic politics” factors, such as a presidential campaign), in Venezuela's failed Tinaco-Anaco high-speed train project (authoritarian turn/country's stability) and in Mexico's Querétaro-Ciudad de México high-speed train project (corruption and popular contestation). The paper suggests that one should not expect an easy or fast projection of the BRI in the region, at least in the short- and mid-term, because becoming familiar with the domestic politics of Latin American is a complex and gradual task.

The particular impact of the political risks related to domestic politics in the Chinese Foreign Direct Investment (FDI) in Latin America has not been extensively explored, especially in the railway sector. This paper intends to contribute to this literature gap by analysing four cases of Chinese investment in railways in Latin America, an area that has received little attention in the studies of the Chinese FDI in the region, and proposing an explanation of their outcomes focusing on the “domestic politics” factor.

This paper aims to evaluate non-financial reporting (NFR) frameworks insofar as risk reporting is concerned. This is facilitated through analysis of the adequacy of climate- and pandemic-related risk reporting in three industries that are both significantly impacted by the COVID-19 pandemic and are at risk from climate change. The pervasiveness of pandemic and climate-change risks have been highlighted in 2020, the hottest year on record and the year the COVID-19 pandemic struck. Stakeholders might reasonably expect reporting on these risks to have prepared them for the consequences.

The current debate on the “complexity” of sustainability and NFR frameworks/standards is critically analysed in light of the COVID-19 pandemic and calls to “build back better”. Context is provided through analysis of risk reporting by the ten largest airlines and the five largest companies in each of the hotel and cruise industries.

Risk reporting on two significant issues, pandemics and climate change, is woefully inadequate. While very little consideration has been given to pandemic risks, disclosures on climate-related risks focus predominantly on “risks” of increased regulation rather than physical risks, indicating a short-term focus. The disclosures are dispersed across different corporate reporting media and fail to appreciate the long-term consequences or offer solutions. Mindful that a conceptual framework for NFR must address this, the authors propose a new definition of materiality and recommend that sustainable development risks and opportunities be placed at the core of a future framework for connected/integrated reporting.

For sustainable development risks to be perceived as “real” by managers, further research is needed to determine the nature and extent of key sustainable development risks and the most effective mitigation strategies.

This paper highlights the importance of recognising the complexity of the issues facing organisations, society and the planet and addressing them by encouraging robust consideration of the interdependencies in evolving approaches to corporate reporting.

This study contributes to the current debate on the future of corporate reporting in light of two significant interconnected crises that threaten business and society – the pandemic and climate change. It provides evidence to support a long-term oriented and holistic approach to risk management and reporting.

Because of the high volatility with unstable data patterns in the real world, the ability of forecasting price indices is notoriously embarrassing and represents a major challenge with traditional time series mechanisms; especially, most of the traditional approaches are weak to forecast future predictions in the high volatile and unbalanced frameworks under the global and local financial depressions. The purpose of this paper is to propose a new statistical approach for portfolio selection and stock market forecasting to assist investors as well as stock brokers to predict the future behaviors.

This study mainly takes an attempt to understand the trends, behavioral patterns and predict the future estimations under the new proposed frame for the Colombo Stock Exchange (CSE), Sri Lanka. The methodology of this study is carried out under the two main phases. In the first phase, constructed a new portfolio mechanism based on k-means clustering. In the second stage, proposed a nonlinear forecasting methodology based on grey mechanism for forecasting stock market indices under the high-volatile fluctuations. The autoregressive integrated moving average (ARIMA) predictions are used as comparison mode.

Initially, the k-mean clustering was applied to pick out the profitable sectors running under the CSE and results indicated that BFI is more significant than other 20 sectors. Second, the MAE, MAPE and MAD model comparison results clearly suggested that, the newly proposed nonlinear grey Bernoulli model (NGBM) is more appropriate than traditional ARIMA methods to forecast stock price indices under the non-stationary market conditions.

Because of the flexible nonlinear modeling capability, proposed novel concepts are more suitable for applying in various areas in the field of financial, economic, military, geological and agricultural systems for pattern recognition, classification, time series forecasting, etc.

For the large sample of data forecasting under the normality assumptions, the traditional time series methodologies are more suitable than grey methodologies. However, the NGBM is better both in model building and ex post testing stagers under the s-distributed data patterns with limited data forecastings.

The purpose of this paper is to identify funders’ motivations for investing in crowdfunding. It applies trust theory to propose a research model including three subject measures – fundraiser-related, project-related and platform-related factors. Trust has been categorized into cognitive and affective dimensions to specifically analyze the influential factors.

Bootstrapping is employed to analyze data collected from respondents with investment experience on equity crowdfunding projects. Structural equation modeling techniques are adopted to examine the factors that influence trust between funders and crowdfunding as well as the outcomes of this trust.

The results indicate that calculus trust and relationship trust collectively or separately transmit the effect of some antecedents to investment intention. However, there is no evidence indicating the mediating effects of calculus trust and relationship trust on the relationship of structural assurance and value congruence to investment intention.

This paper provides insights for crowdfunding fundraisers on how to build a strong relationship with funders, and it also gives crowdfunding designers advice on how to improve and perfect the platform functions.

This study contributes to a better understanding of the driving forces of calculus and relationship trust and their influence on investment intention. It is also the first to address a funder’s trust using a theoretical model describing the investor intention in crowdfunding and thereby extending the knowledge base of trust theory.

The money raised for projects on crowdfunding platforms is determined not only by the merit of the projects themselves but also, to a large extent, by the design of the project introduction on the platforms. The purpose of this study is to identify the clear relationships between the financing result and the design factors to give preferable design suggestions to the fund initiators.

The data for this study were abstracted with Python from the Jingdong crowdfunding platform on a certain day. In all, 11 hypotheses are put forward in the study with the two main purposes of exploring the function of the quality signaling and level setting.

All design factors can impact the money raised for a project. However, the impact differs in certain situations. The level setting can significantly impact the amount of money raised. The quality of signals has a complex impact on the two dimensions.

Three major contributions are made by this paper. First, the level setting is explored after overcoming the difficulty of scrawling data. Second, the authors create the Success Index and Weighted Gap Index to measure the level of success from comprehensive dimensions and quantify the dispersion of the levels. Third, this study shows a comprehensive theoretical framework which can function as a reference for research in the future.

The purpose of this paper is to identify and develop a hierarchical model for the barriers affecting the growth of mobile commerce (M-commerce). Based on the model developed, the authors’ objective is to identify those variables that are of strategic nature and are the root cause of the issue.

Variables considered as barriers are identified, and utilizing the interpretive structural model approach, a relationship model is developed. Further, the impact matrix cross-reference multiplication applied to a classification approach is used to analyze the effect and dependence among these factors.

The research in the area of M-commerce in the Arab world and related to the strategic aspect is limited in the extant literature. The present study tries to fill this gap by investigating the variables that inhibit the growth of M-commerce in Qatar. The research shows that there exists a group of barriers having a high driving power and low dependence requiring maximum attention and of strategic importance, while another group consists of those variables that have high dependence and are the resultant actions.

There is a growing concern that although the numbers of mobile subscribers are increasing at a very fast pace in Qatar, actual M-commerce activities in the country remain low. The findings of this study can be used to understand the differences between the independent and dependent variables and their mutual relationships. The study would also help the policy makers to develop suitable strategies to facilitate growth of M-commerce in the country.

This research was the first attempt to investigate the relationships among the variables inhibiting the growth of M-commerce in a fast-growing economy in a Gulf Cooperation Council (GCC) region. Given that there is limited research on M-commerce in the GCC context, the study can be viewed as an investigation that provides a good understanding of the variables and their interrelationships affecting M-commerce proliferation.