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This paper aims to investigate whether the establishment of commodity futures can effectively hedge systemic risk in the spot network, given the context of financialization in the commodity futures market.

Utilizing industry association data from the Chinese commodity market, the authors identify systemically important commodities based on their importance in the production process using multiple graph analysis methods. Then the authors analyze the effect of listing futures on the systemic risk in the spot market with the staggered difference-in-differences (DID) method.

The findings suggest that futures contracts help reduce systemic risks in the underlying spot network. Systemic risk for a commodity will decrease by approximately 5.7% with the introduction of each corresponding futures contract, since the hedging function of futures reduces the timing behavior of firms in the spot market. Establishing futures contracts for upstream commodities lowers systemic risks for downstream commodities. Energy commodities, such as crude oil and coal, have higher systemic importance, with the energy sector dominating systemic importance, while some chemical commodities also have considerable systemic importance. Meanwhile, the shortest transmission path for risk propagation is composed of the energy industry, chemical industry, agriculture/metal industry and final products.

The paper provides the following policy insights: (1) The role of futures contracts is still positive, and future contracts should be established upstream and at more systemically important nodes in the spot production chain. (2) More attention should be paid to the chemical industry chain, as some chemical commodities are systemically important but do not have corresponding futures contracts. (3) The risk source of the commodity spot market network is the energy industry, and therefore, energy-related commodities should continue to be closely monitored.

This paper provides a comprehensive review of the influential and intellectual aspects of the literature on the Gulf Cooperation Council (GCC) region's banking activities.

This study undertakes a bibliometric meta-analysis review of the GCC region banking literature, covering 199 articles published between 2004 and 2022, extracted from the Web of Science (WoS) database, followed by a content analysis of highly cited papers.

This paper identifies the influential aspects of the GCC region banking literature in terms of journals, articles, authors, universities and countries. The paper also identifies and discusses five major research clusters: (1) bank efficiency; (2) corporate governance (CG) and disclosure; (3) performance and risk-taking; (4) systemic risk, bank stability and risk spillovers and (5) intellectual capital (IC). Finally, it identifies gaps in the literature and highlights some important research issues that provide directions for future research.

This paper is limited to the articles indexed in the WoS database and written in English. Though the WoS database encompasses a wide range of multidisciplinary journals, there is a chance that some relevant articles are not included in the WoS database or written in another language.

This study provides regulators, practitioners and academics with valuable insight and an in-depth understanding of the banking system of the GCC region.

To the best of the authors' knowledge, this is the first review paper on GCC region banking literature. This study provides regulators, practitioners and academics with valuable insight and an in-depth understanding of the banking system of the GCC region.

This study aims to investigate the role of Islamic finance in supporting sustainable economic growth, innovation and digital transformation in the Gulf Cooperation Council (GCC) region. Amid global challenges like the Russia–Ukraine conflict and COVID-19, the focus extends beyond the GCC’s oil dependency to explore how Islamic finance can enable technological advancements and foster a digitally innovative economy. The research aims to reveal the potential of Islamic finance in driving economic diversification, technological progress and sustainable development in the GCC.

Using a content analysis approach, this study critically examines the economic repercussions of recent global crises, shedding light on how Islamic finance contributes to socio-economic justice and the provision of social goods in the GCC. The research synthesises findings from various secondary sources, including academic literature, reports and industry standards, to analyse Islamic finance’s role from an ethical and strategic perspective within the GCC’s evolving economic landscape.

The findings reveal Islamic finance’s potential to significantly contribute to the GCC’s economic diversification and resilience against global economic downturns. The study highlights how Islamic finance aligns with the sustainable development goals and its effectiveness in promoting ethical financial practices and socio-economic justice.

Future research should focus on global comparative studies to understand Islamic finance’s impact on sustainable development beyond the GCC. Longitudinal studies are also essential to assess the long-term effects of Islamic financial instruments on economic stability.

The research advocates for incorporating Islamic finance principles into the GCC’s economic strategies, emphasising its role in providing resilient and ethical financial alternatives conducive to sustainable development. It underscores the need for policy initiatives integrating Islamic finance to bolster socio-economic welfare and environmental sustainability.

Offering a novel perspective, this paper enriches the discourse on the contribution of Islamic finance to sustainable economic development. It presents critical insights into how Islamic finance can underpin long-term economic resilience and growth in the GCC. It provides valuable implications for academia and policymaking, particularly in emerging economies’ science and technology policy management.

Considering the frequency of extreme events, enhancing the global financial system's stability has become crucial. This study aims to investigate the contagion effects of extreme risk events in the international commodity market on China's financial industry. It highlights the significance of comprehending the origins, severity and potential impacts of extreme risks within China's financial market.

This study uses the tail-event driven network risk (TENET) model to construct a tail risk spillover network between China's financial market and the international commodity market. Combining with the characteristics of the network, this study employs an autoregressive distributed lag (ARDL) model to examine the factors influencing systemic risks in China's financial market and to explore the early identification of indicators for systemic risks in China's financial market.

The research reveals a strong tail risk contagion effect between China's financial market and the international commodity market, with a more pronounced impact from the latter to the former. Industrial raw materials, food, metals, oils, livestock and textiles notably influence China's currency market. The systemic risk in China's financial market is driven by systemic risks in the international commodity market and network centrality and can be accurately predicted with the ARDL-error correction model (ECM) model. Based on these, Chinese regulatory authorities can establish a monitoring and early warning mechanism to promptly identify contagion signs, issue timely warnings and adjust regulatory measures.

This study provides new insights into predicting systemic risk in China's financial market by revealing the tail risk spillover network structure between China's financial and international commodity markets.

The authors compare sentiment level with sentiment shock from different angles to determine which measure better captures the relationship between sentiment and stock returns.

This paper examines the relationship between investor sentiment and contemporaneous stock returns. It also proposes a model of systems science to explain the empirical findings.

The authors find that sentiment shock has a higher explanatory power on stock returns than sentiment itself, and sentiment shock beta exhibits a much higher statistical significance than sentiment beta. Compared with sentiment level, sentiment shock has a more robust linkage to the market factors and the sentiment shock is more responsive to stock returns.

This is the first study to compare sentiment level and sentiment shock. It concludes that sentiment shock is a better indicator of the relationship between investor sentiment and contemporary stock returns.

The purpose of this study is to increase awareness of current supply chain (SC) security-related issues by providing an extensive analysis of existing SC security solutions and their limitations. The security of SCs has received increasing attention from researchers, due to the emerging risks associated with their distributed nature. The increase in risk in SCs comes from threats that are inherently similar regardless of the type of SC, thus, requiring similar defence mechanisms. Being able to identify the types of threats will help developers to build effective defences.

In this work, we provide an analysis of the threats, possible attacks and traceability solutions for SCs, and highlight outstanding problems. Through a comprehensive literature review (2015–2021), we analysed various SC security solutions, focussing on tracking solutions. In particular, we focus on three types of SCs: digital, food and pharmaceutical that are considered prime targets for cyberattacks. We introduce a systematic categorization of threats and discuss emerging solutions for prevention and mitigation.

Our study shows that the current traceability solutions for SC systems do not offer a broadened security analysis and fail to provide extensive protection against cyberattacks. Furthermore, global SCs face common challenges, as there are still unresolved issues, especially those related to the increasing SC complexity and interconnectivity, where cyberattacks are spread across suppliers.

This is the first time that a systematic categorization of general threats for SC is made based on an existing threat model for hardware SC.

This study aims to evaluate the suspicious transaction reporting (STR) as a financial intelligence tool to identify the potential strengths and limitations of STR and to come up with the criteria, which will make this tool an effective one in early detection of terrorist financing activities.

Considering the research aim, this research uses the funnelling method for identifying effectiveness criteria. Funnelling is a method of literature review that helps find pertinent literature by refining the search through filtering the available research (Ridley, 2008). Using this method, the researcher first applied the criteria of actionable intelligence to filter the financial intelligence tools to select the most promising and important tool (suspicious transaction reporting) for early detection of terrorist financing activities. The funnelling method was also applied to derive the effectiveness criteria from the operational features, and corresponding limitations, of the suspicious transaction reporting system. The funnelling method was also used to identify those operational features and limitations of suspicious transaction reporting that have the most direct relevance to the early detection problem of suspicious transaction reporting.

There are some operational features of STR that give rise to certain limitations that undermine its effectiveness in terms of early detection of terrorist financing activities. The limitations of STR necessitate a search for criteria that will make STR effective in early detection of terrorist financing activities. Based on the operational features and their corresponding limitations, effectiveness criteria for STR have been derived in this study. It is shown how these effectiveness criteria can remove the limitations of STR.

The list of operational features and the corresponding limitations based on which the effectiveness criteria have been derived may not be exhaustive. There may have other operational features, and corresponding limitations that also make STR largely ineffective in the early detection of terrorist financing activities, and for which more effectiveness criteria should also be derived.

The limitations and the effectiveness criteria will pave the way for redesigning STR in such a way that will make it highly useful for detecting financing activities relating to imminent terrorist attacks.

The society will experience fewer terrorist attacks that will make the society peaceful, happy and vibrant.

In this study, the effectiveness criteria of STR for early detection of terrorist financing activities have been derived in an innovative way by deducing them from the operational features of STR and the corresponding limitations.