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This study aims to explore the innovative governance structures enabled by blockchain-based decentralized autonomous organizations (DAOs) in the context of international business (IB). As nonhierarchical entities managed through collective voting and peer-to-peer interactions, DAOs challenge traditional assumptions of multinational corporation (MNC) governance.

The authors perform a literature review, which combines qualitative content analysis of both academic papers on DAO and whitepapers with quantitative analysis of bibliometrics using VosViewer.

The findings highlight DAOs’ ability to generate new research questions and offer a foundation for future studies on decentralized governance in IB. Through a bibliometric analysis of 73 papers from Web of Science and qualitative content analysis, the authors identify four primary research streams in the DAO literature. A deep dive into financial DAOs, or DeFi DAOs, reveals insights into their governance mechanisms and implications for the studies in the field of IB.

Research on DAOs is in its early stages, and the practice in IB is nascent. As the regulatory, economic and technological landscape for DAOs changes, more research will be needed on the governance mechanisms and their sustainability.

This paper advances the field by providing a multilevel analysis of DAOs’ potential impact on IB, considering macro (country), meso (MNC/DPE) and micro (multicultural team and individual) levels.

The chapter explored the critical components, challenges, and technological advancements in construction supply chain management (CSCM), focusing on stealth construction (STC). It delved into STC encompassing nature, highlighting its unique challenges in its supply chain management and the necessity for adaptive technologies. It further discussed the benefits of tailoring supply chain management specifically for STC, emphasising the importance of developing the building’s cross-section, managing visibility, controlling energy transmission, and implementing countermeasures. Practical applications of CSCM in STC are also examined. This chapter sheds light on the complexities of managing supply chains in STC contexts and offers insights into strategies and technologies to address these challenges effectively.

This study clarifies the history and significance of cryptocurrencies. It explores the underlying decentralisation and trustlessness concepts that set these digital assets apart from conventional fiat currencies. It clarifies how blockchain technology functions as the core component of decentralised money. The mechanics of mining, its function in creating and validating Bitcoin transactions, and the emergence of substitute consensus mechanisms to solve environmental issues are all covered in this study. An in-depth analysis of blockchain technology covers its advantages, such as immutability and transparency, as well as its architecture and consensus processes. This study continues with a focus on the future by examining the development of decentralised finance (DeFi) and showcasing numerous DeFi applications, including yield farming, lending protocols, and decentralised exchanges (DEXs). As a result of the development of cryptocurrencies and blockchain technology, DeFi has become possible, ushering in a new era of financial independence and inclusivity. This study emphasises the significance of striking a balance between innovation and suitable regulatory measures as the globe embraces this revolution in order to enable the proper integration of DeFi into the global financial environment. The revolutionary potential of DeFi, particularly in increasing financial inclusion and empowerment for marginalised groups globally, is one of the major themes discussed. To negotiate legal frameworks while maintaining DeFi's decentralised nature, this study looks at the regulatory problems that come with this potential.

As a crucial supply chain financing instrument, trade credit has become increasingly important for firms to enhance financial flows in supply chains. Yet, scant research has examined how firms’ green innovation affects the attainment of trade credit from their suppliers. To bridge this gap, this study aims to draw on signalling theory to investigate the impacts of incremental green innovation (IGI) and radical green innovation (RGI) on trade credit and the contingent roles of supplier concentration and industry dynamism.

Using a data set of 3,302 Chinese listed manufacturing companies from 2007 to 2021, our research adopts fixed-effect regression models to test the proposed hypotheses.

The authors find that both IGI and RGI exert a positive effect on trade credit. Interestingly, supplier concentration weakens the association between RGI and trade credit, whereas it does not significantly influence the association between IGI and trade credit. Moreover, industry dynamism attenuates the relationship between IGI and trade credit, whereas it does not significantly alter the relationship between RGI and trade credit.

The paper extends the supply chain finance literature by applying signalling theory to uncover the effects of IGI and RGI on trade credit and the distinct contingency roles of supplier concentration and industry dynamism. It also provides supply chain managers with important implications regarding how to tailor the strategies of implementing different types of green innovation to acquire more trade credit in different situations.

While the application of blockchain technology in the organic food supply chain has been increasingly recognized, the extant knowledge of how blockchain-driven traceability influences consumer perceptions and purchase intentions remains underexplored. Grounded in the stimulus-organism-response theory, this study aims to construct a moderated mediation model to examine blockchain-enabled traceability’s direct and indirect impacts on organic food purchase intention through perceived blockchain-related information transparency, considering the moderating role of blockchain-based trust.

A purposive sample of 5,326 Vietnamese consumers was surveyed using the PROCESS macro to test the proposed hypotheses.

The findings indicate that blockchain-enabled traceability significantly enhances perceived blockchain-related information transparency, which positively influences organic food purchase intention. Furthermore, blockchain-based trust was found to positively moderate both the direct effect of transparency on purchase intention and the indirect impact of traceability on purchase intention through transparency.

Practical and managerial insights for stakeholders in the organic food sector are also discussed.

These results contribute to the literature by extending the stimulus-organism-response model to the context of blockchain technology in supply chains and highlighting the critical role of trust in moderating the effectiveness of technological innovations.

Transporting hydrogen through natural gas pipelines in blended compositions has been proven to be a highly feasible solution in the short term. However, under hydrogen-rich environments, steel structures are prone to hydrogen-induced damage (HID). Additionally, uncertainties in various parameters can significantly impact the performance evaluation of hydrogen pipelines. Efficient reliability and sensitivity analyses of medium- to high-strength steel pipelines considering HID have become a challenge. Therefore, the primary aim of this study is to address this issue.

This study first establishes reliability analysis models for medium- to high-strength steels, represented by X65 and X80. In these models, the effect of HID is expressed by reduced stress, and its statistical parameters are calculated. Then, a highly efficient enhanced first order reliability method (FORM) is proposed for pipeline reliability analysis. This method overcomes the oscillation and convergence issues of traditional FORM when dealing with certain problems and can compute negative reliability indices. The proposed reliability analysis method is applied to solve the constructed reliability models. Finally, a reliability sensitivity analysis is conducted on the models to identify the key variables affecting the reliability of medium- to high-strength steel pipelines under HID.

First, two reliability analysis examples are used to validate the effectiveness of the proposed enhanced FORM. Then, using this method to solve the constructed reliability models for X65 and X80 steel pipelines under HID reveals that, for both types of steel, the reliability indices decrease significantly when considering HID compared to cases without HID. The decline is more pronounced for X80 steel than for X65 steel. As internal pressure increases, the reliability of both steels drops sharply, showing a concave parabolic trend. Moreover, the reliability sensitivity analysis shows that at a pressure of 10 MPa, for both X80 and X65, internal pressure, pipeline wall thickness and model error are the top three factors influencing reliability. As internal pressure increases, its influence becomes stronger, while the impact of other variables diminishes. Notably, for X80 steel, the presence of hydrogen amplifies the effect of internal pressure on pipeline reliability compared to when HID is not considered, but for X65, this trend is reversed.

Given the urgent need for safety evaluation studies on hydrogen transport through natural gas pipelines, this research provides new insights by constructing reliability models for X65 and X80 pipeline steels under HID and introducing an enhanced FORM method. The results of the reliability and sensitivity analyses of the models offer valuable insights and serve as a reference for engineering design.

This study examines the effect of non-audit fees (NAF) provisions on interest payments classification shifting. In addition, we investigate to what extent the NAF economic bonding and interest payments classification shifting is contingent on internal governance and firm financial well-being.

This study employed probit regression using a sample of UK non-financial firms indexed in FT UK (500) over the period from 2009 to 2017.

We find evidence that the economic bonding of NAF between external auditors and their clients is more likely to encourage managers in UK firms to manipulate operating cash flows through interest payment classification shifting. In addition, and interestingly, our results evince that classification-shifting may be the less costly and soft choice of managers in firms with strong governance and charging higher NAF. Furthermore, we show that financially distressed firms associated with their auditors in purchasing non-audit services are more prone to attempting to manipulate and engage in interest payments classification-shifting. Our result did not provide a significant effect of external auditor tenure on the interest payments classification shifting.

Our findings are subject to the following limitations: First, this study uses a composite index to measure the quality of internal corporate governance. It focuses only on the board of directors, but this index does not reflect other internal governance mechanisms. Second, this study is subject to limited study time due to the implementation of key IFRS standards (IFRS 9 Financial Instruments and IFRS 15 Revenue from Contract with Customers) from 2018–2019.

This study was motivated by the UK’s Financial Reporting Council regulators' pressure on the Big 4 audit firms to move more audit time into main auditing activities, reduce cross-selling to audit clients and separate their audit practices by 2024. Overall, we provide new evidence that directs a close spotlight on the threats of NAF that are potentially useful to regulators, shareholders and investors.

It is motivated by the UK’s Financial Reporting Council regulators' pressure on the Big 4 to move more audit firm time into main auditing activities, reduce cross-selling to audit clients and separate their audit practices by 2024. Overall, we provide new evidence that directs a close spotlight on the threats of NAS that are potentially useful to regulators, shareholders and investors.

This study aims to explore Augmented Language Models (ALMs) for synthetic data generation in services marketing and research. It evaluates ALMs' potential in mirroring human responses and behaviors in service scenarios through comparative analysis with five empirical studies.

The study uses ALM-based agents to conduct a comparative analysis, leveraging SurveyLM (Bickley et al., 2023) to generate synthetic responses to the scenario-based experiment in Söderlund and Oikarinen (2018) and four more recent studies from the Journal of Services Marketing. The main focus was to assess the alignment of ALM responses with original study manipulations and hypotheses.

Overall, our comparative analysis reveals both strengths and limitations of using synthetic agents to mimic human-based participants in services research. Specifically, the model struggled with scenarios requiring high levels of visual context, such as those involving images or physical settings, as in the Dootson et al. (2023) and Srivastava et al. (2022) studies. Conversely, studies like Tariq et al. (2023) showed better alignment, highlighting the model's effectiveness in more textually driven scenarios.

To the best of the authors’ knowledge, this research is among the first to systematically use ALMs in services marketing, providing new methods and insights for using synthetic data in service research. It underscores the challenges and potential of interpreting ALM versus human responses, marking a significant step in exploring AI capabilities in empirical research.

This study aims to explore the intention to quit and its associations among ambulance personnel and to compare the intention to quit and its associations between paramedic and non-paramedic staff.

A cross-sectional study was conducted on 492 Australian ambulance personnel. Participants were selected by stratified random sampling. Data were collected using phone interview-administered questionnaires. Descriptive analyses, bivariate associations and structural equation modelling were performed for data analysis.

The study found that 70% of ambulance personnel intended to quit their jobs. Intention to quit was similar between paramedics and non-paramedic staff. In both staff groups, supervisors' and colleagues' support was associated with mental health symptoms; job satisfaction was associated with the intention to quit. Supervisors' and colleagues' support was indirectly associated with the intention to quit via increasing job satisfaction and reducing the experience of mental health symptoms among paramedics only. Mental health symptoms were directly associated with the intention to quit and indirectly associated with the intention to quit via reducing job satisfaction among paramedics only.

The study findings provide evidence for resource allocation in human resource management. The findings suggest that interventions to increase job satisfaction may reduce the intention to quit for all ambulance personnel. Interventions to improve supervisors' and colleagues' support and to manage depression, anxiety and stress symptoms may help to reduce the intention to quit for paramedics only.

This is the first study to model and compare the direct and indirect associations of intention to quit between paramedics and non-paramedic staff in ambulance personnel.