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In 2019, FIU-the Netherlands celebrated its 25th anniversary. This study takes the occasion to reflect on the role of the FIU in financial surveillance and to describe its core practices of collecting, analysing and disseminating financial intelligence.

Because FIU practices are often secret and its transaction data classified as state secrets, the FIU’s daily operational activities remain obscure. Drawing on interviews, public reports and an online training course, this study encircles secrecy and offers a fine-grained analysis of the FIU's core activities.

The article finds that the FIU plays a pivotal role in financial surveillance because it can operate at various intersections. An FIU operates at the intersection of finance and security, in between the public and private sector and at the national and international domain. This pivotal role makes the FIU indispensable in the surveillance of payment systems and spending behavior.

The article poses that the desirability and effectiveness of financial surveillance has to date not received sufficient consideration, while it affects (the privacy of) anyone with a bank account. The article asks: is it ethically justifiable that transaction information is declared suspect, investigated, and shared nationally and internationally, without the individual or entity concerned officially being notified and legally named a suspect?

This case-study is not only relevant for the study of finance/security, AML/CFT and financial surveillance, but also to policy makers and the broader public who merit an understanding of how their financial behaviour is being surveilled.

The review examines the existing literature on blockchain-based small and medium enterprise (SME) finance and highlights its trend, themes, opportunities and challenges. Based on these factors, the authors create a framework for the existing literature on blockchain-based SME financing and lay down future research paths.

The review follows a systematic approach. It includes 53 articles encompassing multiple dimensions of blockchain-based SME finance, including peer-to-peer lending platforms, supply chain finance (SCF), decentralized lending protocols and tokenization of assets. The review critically evaluates these approaches' theoretical underpinnings, empirical evidence and practical implementations.

The review demonstrates that blockchain-based SME finance holds significant promise in addressing the credit gap by leveraging blockchain technology's decentralized and transparent nature. Benefits identified include reduced information asymmetry, improved access to financing, enhanced credit assessment processes and increased financial inclusion. However, the literature acknowledges several challenges and limitations, such as regulatory uncertainties, scalability issues, operational complexities and potential security risks.

The article contributes to the growing knowledge of blockchain-based SME finance by synthesizing and evaluating the existing literature. It also provides a framework for the existing literature in the area and future research paths. The study offers insights for researchers, policymakers and practitioners seeking to understand the potential of blockchain technology in filling the SME credit gap and fostering economic development through improved access to finance for SMEs.

Many studies have analysed the impact of various variables on the ability of companies to raise capital. While most of these studies are sector-agnostic, literature on the effects of macroeconomic variables on sectors that established over the last 20 years like property technology and financial technology, is scarce. This study aims to identify macroeconomic factors that influence the ability of both sectors and is extended by real estate variables.

The impact of macroeconomic and real estate related factors is analysed using multiple linear regression and quantile regression. The sample covers 338 observations for PropTech and 595 for FinTech across 18 European countries and 5 deal types between 2000–2001 with each observation representing the capital invested per year for each deal type and country.

Besides confirming a significant impact of macroeconomic variables on the amount of capital invested, this study finds that additionally the real estate transaction volume positively impacts PropTech while the real estate yield-bond-gap negatively impacts FinTech.

For PropTech and FinTech companies and their investors it is critical to understand the dynamic with mac-ro variables and also the real estate industry. The direct connection identified in this paper is critical for a holistic understanding of the effects of measurable real estate variables on capital investments into both sectors.

The analysis fills the gap in the literature between variables affecting investment into firms and effects of the real estate industry on the investment activity into PropTech and FinTech.

The purpose of this study is to examine the South African banks’ customer due diligence (CDD) practices in the fintech era to mitigate money laundering (ML) risks and ensure financial stability. Financial technologies have brought substantial transformations to the financial services sector. However, such technologies have exposed the sector to emerging risks that threaten the integrity and stability of the financial system globally. Before any bank–customer relationship is established, proper customer background checks must be conducted. These background checks enable financial institutions to validate information provided and ensure customers are properly risk profiled. Failure to risk profile customers could result in financial institutions being used as conduits for ML. Undoubtedly, CDD procedures are pivotal to overall anti-money laundering efforts and curbing financing terrorism in a regulatory framework.

A qualitative research approach was adopted to address the research questions of the study. Given the confidentiality associated with the financial services sector, data triangulation was used in blending mainly secondary and primary data sources. Secondary data sources used in the study were published reports available in the public domain that were corroborated with subject matter experts’ interviews.

Based on the findings of this study, it is concluded that in South Africa, technological solutions have been incorporated into CDD functions, which is now risk-based (enhanced due diligence). Also, legally, South Africa has incorporated the biometrics, integration with Department of Home Affairs and Companies and Intellectual Property Commission databases, customer consent to third-party sources with the Financial Intelligence Centre Act and the Protection of Personal Information Act.

The shift towards digital banking in South Africa results in increased data and dynamic risk profiling. This study advocates a policy shift requiring a risk-based approach to mitigating emerging ML risks (in particular digital laundering), especially in the wake of South Africa’s recent greylisting by the Financial Action Task Force.

Digital supply chains require nascent technologies like blockchain and Internet of Things (IoT). There is a need to develop a roadmap for the implementation of these technologies, as they require a huge amount of resources and infrastructure. The purpose of this paper is to analyze the challenges of implementing blockchain-IoT integrated architecture in the green supply chain and develop strategies for the same.

After a thorough literature survey of Scopus-indexed journals and books, 37 barriers were identified, which were then brought down to 15 barriers after confirming with industry and academic experts using the Delphi method. Using the total interpretive structural modeling (TISM) method and cross-impact matrix multiplication applied to classification (MICMAC) analysis, the barriers were modeled, and finally, strategies were formulated using a concept map to handle the barriers in the blockchain-IoT integrated architecture for a green supply chain.

This paper presents the research on barriers that can be considered for incorporating blockchain and IoT in the green supply chain. It was found from the TISM model that environmental concerns are Level-1 barriers and need to be addressed by developing appropriate technology and allocating funds for the same. An integrated ecosystem with blockchain and IoT is developed.

The focus of this study was on the challenges of blockchain and IoT; hence, it is required to extend the research and find challenges for different industries and also analyze the criteria using other multi-criteria decision-making (MCDM) methods. Further research is required for the integration of blockchain-IoT with supply chain functions.

The transformation of a traditional supply chain into a green supply chain is possible with the integration of technologies. This research work and the strategies developed are useful to managers and practitioners working on technology implementation. Planning resources and addressing key barriers is possible with the concept maps and architecture developed.

Green supply chain management (SCM) is gaining importance in industry as well as the academic sector due to government Policies and norms worldwide for reducing emissions and encouraging environment-friendly production systems. Incorporating blockchain and IoT in a green supply chain will further digitize and increase transparency in supply chains.

We have done a categorization of all barriers based on the expert survey by academicians and industry experts from industries in India. The concept map helps in identifying possible solutions for the challenges and initiatives to be taken for the smooth integration of technologies in the green supply chain.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

The paper aims to identify and analyze passengers’ riding paths for providing better operational support for digital transformation in megacity metro systems.

The authors develop a method to leverage certain passengers’ deterministic riding paths to corroborate other passengers’ uncertain paths. Using Automatic Fare Collection data and train schedules, a witness model is built to recover the actual riding paths for passengers whose paths are unknown otherwise. The identification and analysis of passenger riding paths between three different types of origin–destination) pairs reveal the complexity of passenger path choice.

The results show that passenger path choice modeling is usually characterized by complexity, experience and partial blindness. Some passengers choose paths that are not optimal due to their experience and limited access to overall metro system information. These passengers could be the subject of improved path guidance in light of riding efficiency improved through digital transformation.

This research contributes to the improvement of metro management and operations by leveraging ongoing digital transformation in megacity metro systems. Based on the riding paths and trip chains of a large number of individual passengers identified by the proposed method, metro operation management could prevent risks in areas with concentrated passenger flow in advance, optimally adjust train schedules on a daily basis and deliver real-time riding guidance station by station, which would greatly improve megacity metro systems’ service safety, quality and operational efficacy over time.

This paper aims to provide an overview of the application of blockchain to agri-food supply chains, including key issues and trends. It examines the state of the art and conceptual structure of the field and proposes an agenda to guide future research.

This article performs a bibliometric analysis using VOSviewer software on a sample of 205 articles from the WoS database to identify research trend topics.

The number of publications in this area has increased since 2020, which shows a growing research interest. The research hotspots are related to the integration of blockchain technology in the agri-food supply chain for traceability, coordination between all actors involved, transparency of operations and improvement of food safety. Furthermore, this is linked to sustainability and the achievement of the sustainable development gtoals (SDGs), while addressing key challenges in the implementation of blockchain-based technologies in the agri-food supply chain.

The application of blockchain in the agri-food supply chain may consider four key aspects. Firstly, the implementation of blockchain can improve the traceability of food products. Secondly, this technology supports sustainability issues and could avoid disruptions in the agri-food supply chain. Third, blockchain improves food quality and safety control throughout the supply chain. Fourthly, the findings show that regulation is needed to improve trust between stakeholders.

The paper provides a comprehensive overview of the blockchain phenomenon in the agri-food supply chain by optimising the search criteria. Moreover, it serves to bridge to future research by identifying gaps in the field.

This research aims to examine the impact of RPTs and board of directors' characteristics on the market value of Indian listed banks. Further, this study evaluates the moderation effect of board composition on the association between RPTs banks’ market value.

The sample size consists of 38 banks listed on Bombay stock exchange. The current study is based on secondary data for ten years from 2010 to 2019. Generalized Method of Moment (GMM) was used for estimating the results.

Subsidiary transactions, board of directors' size, composition, diligence, promoters, remuneration and banks' size and leverage have a significant impact on the market value of Indian listed banks. Further, board of directors' composition positively moderates the association between RPTs and banks value measured by Tobin's. Furthermore, corporate governance characteristics have a significant impact on RPTs measured by total RPTs and all subsidiary transactions.

This research is limited only to listed banks whose data are available in the ProwessIQ database, which makes it difficult to generalize the findings on other unlisted banks. This research helps policymakers, investors and creditors to categorize RPTs into different groups to identify the harmful and beneficial once to the bank. The findings suggest that policymakers, investors and creditors should not consider all key personal transactions as harmful transactions; instead, the policymakers, investors and creditors should consider all subsidiary transactions as harmful in the absence of independent directors.

The present study contributes to the existing literature on RPTs by evaluating the interaction effect of board composition on the association between related party transactions and banks' value. Further, this research focuses on the financing industry; Indian banks, which has not been sufficiently researched in comparison to the non-financing industries.

The purpose of this study is to focus on structured data provision and asset information model maintenance and develop a data provenance model on a blockchain-based digital twin smart and sustainable built environment (DT) for predictive asset management (PAM) in building facilities.

Qualitative research data were collected through a comprehensive scoping review of secondary sources. Additionally, primary data were gathered through interviews with industry specialists. The analysis of the data served as the basis for developing blockchain-based DT data provenance models and scenarios. A case study involving a conference room in an office building in Stockholm was conducted to assess the proposed data provenance model. The implementation utilized the Remix Ethereum platform and Sepolia testnet.

Based on the analysis of results, a data provenance model on blockchain-based DT which ensures the reliability and trustworthiness of data used in PAM processes was developed. This was achieved by providing a transparent and immutable record of data origin, ownership and lineage.

The proposed model enables decentralized applications (DApps) to publish real-time data obtained from dynamic operations and maintenance processes, enhancing the reliability and effectiveness of data for PAM.

The research presents a data provenance model on a blockchain-based DT, specifically tailored to PAM in building facilities. The proposed model enhances decision-making processes related to PAM by ensuring data reliability and trustworthiness and providing valuable insights for specialists and stakeholders interested in the application of blockchain technology in asset management and data provenance.