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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.

This study aims to identify the characteristics of the maritime shipping network in Northeast Asia as well as compare the level of port connectivity among these container ports in the region. In addition, this study analyses the change in role and position of 20 ports in the region by clustering these ports based on connectivity index and container throughput and route index.

This study employs Social Network Analysis (SNA) to delineate the international connectivity of major container ports in Northeast Asia. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to identify each port's connectivity index and container throughput index, and the resulting indexes are employed as the basis to cluster 20 major ports by fuzzy C-mean (FCM).

The results revealed that Northeast Asia is a highly connected maritime shipping network with the domination of Shanghai, Shenzhen, Hong Kong and Busan. Furthermore, both container throughput and connectivity in almost all container ports in the region have decreased significantly due to the coronavirus disease 2019 (COVID-19) pandemic. The rapid growth of Shenzhen and Ningbo has allowed them to join Cluster 1 with Shanghai while maintaining high connectivity, yet decreasing container throughput has pushed Busan down to Cluster 2.

The originality of this study is to combine indexes of SNA into connectivity index reflecting characteristics of the maritime shipping network in Northeast Asia and categorize 20 major ports by FCM.

This research provides some evidence by the vine copula approach, suggesting the significant and symmetric causal relation between subsections of Baltic Exchange and hence concluding that investing in different indexes, which is currently a risk diversification system, is not a correct risk reduction strategy.

The daily observations of Baltic Capesize Index (BCI), Baltic Handysize Index (BHSI), Baltic Dirty Tanker Index (BDTI) and Baltic LNG Tanker Index (BLNG) over an eight-year period have been used. After collecting data, calculating the return and estimating the marginal distribution of return rates for each of the indexes applying asymmetric power generalized autoregressive conditional heteroskedasticity and autoregressive moving average (APGARCH-ARMA), and with the assumption of skew student's t-distribution, the dependence of Baltic indexes was modeled based on Vine-R structures.

A positive and symmetrical correlation was observed between the study groups. High and low tail dependence is observed between all four indexes. In other words, the sector business groups associated with each of these indexes react similarly to the extreme events of other groups. The BHSI has a pivotal role in examining the dependency structure of Baltic Exchange indexes. That is, in addition to the direct dependence of Baltic groups, the dependence of each group on the BHSI can transmit accidents and shocks to other groups.

Since the Baltic Exchange indexes are tradable, these findings have implications for portfolio design and hedging strategies for investors in shipping markets.

Vine copula structures proves the causal relationship between different Baltic Exchange indexes, which are derived from different types of markets.

The role of clusters in the development and growth of local and national economies has been extensively studied and discussed in global literature. Different methodologies are used for analysing the impact these have in national and regional economies, such as the input–output (IO) and gravity models. This paper aims to detail the methodologies present in the literature and propose a new robust theoretical framework, which facilitates the evaluation and comparison among maritime clusters in terms of attractiveness assisting stakeholders to devise strategies, which will attract companies.

An index is created composed of five key categories, namely, infrastructure, financing, governance, manpower and institution/legislation. For the analysis of the index, multi-attribute utility theory (MAUT) is used as a tool to evaluate the importance and performance of the different attributes using both quantitative and qualitative criteria. The methodology has been tested via the use the Piraeus maritime cluster.

The framework has been tested on its robustness and friendliness to the user providing useful insights to the stakeholders. Among the results has been the importance of the finance, manpower and infrastructure attributes, which appear to promote the cluster’s attractiveness. In addition, legislation and institutional partnerships, along with Government support, need to take place improve the performance of the cluster.

A key limitation is the fact that the methodology has been tested in a single case. Applying the methodological framework in a wider sample of clusters will significantly improve the present work.

The proposed model takes further existing research in the field via adopting the philosophy of the World Bank’s Logistics Performance Index. Among the benefits of the proposed index is that it offers the flexibility and robustness to compare among different maritime clusters globally and can be readily used as a benchmarking policy tool at national, regional and global levels at any given point in time and attribute dimension.

The purpose of this study is to construct a robust index and subindices to measure the quality of corporate governance for 266 firms listed in South Africa from 2004 to 2021.

Public information on the compliance of King Code of Good Corporate Governance is used to construct a main index predicated on provisions relating to board characteristics, accounting and auditing and risk management. These categories are transformed into three subindices. All constructs are scored with binary coding and equally weighted.

Cronbach’s alpha test reveals that the index and subindices are highly reliable measures of corporate governance. The principal component analysis supports the construct validity of all measures.

The index is limited to only three corporate governance subcategories and only focuses on South Africa.

These corporate governance indices provide governing authorities, policymakers, investors and other market participants direct information on the quality of corporate governance in South African firms.

As South Africa lacks a formal corporate governance indicator, the development of an appropriate corporate governance index and subindices contributes towards understanding the quality of corporate governance in South African firms. To the best of the authors’ knowledge, this is the first paper to conduct robustness tests on corporate governance indices designed for South African companies.

Internet search is a $120bn business that answers lists of search terms or keywords with relevant links to Internet webpages. Only a few companies have sufficient scale to compete and thus economics of the process are paramount. This study aims to develop a detailed industry-specific modeling of the economics of internet search.

The current research develops a stochastic model of the process of Internet indexing, search and retrieval in order to predict expected costs and revenues of particular configurations and usages.

The models define behavior and economics of parameters that are not directly observable, where it is difficult to empirically determine the distributions and economics.

The model may be used to guide the economics of large search engine operations, including the advertising platforms that depend on them and largely fund them.

Passive investing has established itself as the dominant force in the world of professionally managed assets, surpassing the concept of index funds. Its meteoric rise is fueled by investors’ preference for its dual benefits of strong diversification and low cost. A comprehensive study of the economic model, addressed areas and market structure has not yet been conducted, despite the existence of numerous studies on more specific topics. To address this gap, this paper examines 943 articles on passive investing published between 1998 and 2022 in SCOPUS and Web of Science.

The study utilizes the most pertinent tools for conducting a systematic review by the PRISMA framework. This article is the result of SLR and extensive bibliometric analysis. Contextualized systematic literature review is used to screen and select bibliographic data, which is then subjected to a variety of bibliometric analyses. The study provides a bibliometric overview of works on passive investment research that are indexed in Scopus and Web of Science. Bibliometrix, VoS Viewer and Cite Space are the tools used to conduct content and network analysis, to ascertain the present state of research, as well as its focus and direction.

Our exhaustive analysis yields important findings. One, the previous decade has witnessed a substantial increase in the number of publications and citations; in particular, the inter-disciplinary and international scope of related research has expanded; Second, the top three clusters on “active versus passive funds,” “price discovery and market structures” and “exchange-traded funds (ETFs) as an alternative” account for more than fifty percent of the domain’s knowledge; Third, “Leveraged ETFs (LETFs)” and “environmental, social and governance (ESG)” are the two emerging themes in the passive investing research. Fourth, despite its many benefits, passive investing is not suitable for everyone. To get the most out of what passive investing has to offer, investors, intermediaries and regulators must all exercise sufficient caution. Our study makes a substantial contribution to the field by conducting a comprehensive bibliometric analysis of the existing literature, highlighting key findings and implications, as well as future research directions.

While the study contributes significantly to the field of knowledge, it has several limitations that must be considered when interpreting its findings and implications. With our emphasis on academic journals, the study analyzed only peer-reviewed journal articles, excluding conference papers, reports and technical articles. While we are confident that our approach resulted in a comprehensive and representative database, our reliance on Elsevier Scopus and Web of Science may have resulted in us overlooking relevant work accessible only through other databases. Additionally, specific bibliometric properties may not be time-stable, and certain common distribution patterns of the passive investing literature may still be developing.

With this study, it has been possible to observe and chart the high growth trajectory of passive investing research globally, especially post-US subprime crisis. Despite the widespread adoption of passive investing as an investment strategy, it is not a one-size-fits-all proposition. Market conditions change constantly, and it frequently requires an informed eye to determine when and how much to shift away from active investments and toward passive ones. Currency ETFs enable investors to implement a carry trade strategy in their portfolios; however, as a word of caution, currency stability and liquidity can play a significant role in international ETFs. Similarly, LETFs may be better suited for dynamic strategies and offer less value to a long-term investor. Lastly, the importance of investor education cannot be underestimated in the name of the highly diversified portfolio when using passive alternatives, for which necessary efforts are required by regulators and investors alike.

The inexorable trend to passive investing creates numerous issues for fund management, including fee and revenue pressure, which forces traditional managers to seek new revenue streams, such as illiquid and private assets, which also implies increased portfolio risk. Additionally, the increased transparency and efficiency associated with the ETF market indicates that managers must rethink the entire value chain, beginning with technology and the way investments interact. Passive investments have triggered changes in market structure that are still not fully understood or factored in. Active management and a range of valuation opinions on whether a price is “too low” or “too high” provide much-needed depth to a market as it attempts to strike a delicate balance between demand and supply forces, ensuring liquidity at all price points.

I hereby certify that I am the sole author of this paper and that no part of this manuscript has been published or submitted for publication.

The purpose of this study is to investigate the impact of COVID-19 on some fiscal and monetary indicators in the Kingdom of Saudi Arabia.

The research relied on data, studies and reports issued by the International Monetary Fund, Arab Monetary Fund, Saudi Central Bank, Investing Website and the World in Data Website.

Many sectors have been affected by the COVID-19 pandemic, which outbreak has been associated with a high cost, in addition to increased inflation and prices, a result that was confirmed by the increase in consumer price indices for different sectors. The general consumer price index for the second period rose above that of the first period, while an upward shift occurred in the curve depicting the Saudi Riyal exchange rate against the United States (US) dollar during the second period above that of the first period, only in slope, due to outbreak of the pandemic. Impact of the number of daily new cases infected with COVID-19 was the highest on the opening and closing price indices of the food retail sector, the pharmaceutical sector and the transportation sector; while impact of the number of daily deaths by COVID-19 was the highest on the opening and closing price indices of the banking sector, the general index and the investment and finance sector. In addition, impact of the daily reproduction rate of COVID-19 was the highest on the opening price indices of the energy sector, the food production sector and the transportation sector.

The research aims to demonstrate measures taken by the Kingdom of Saudi Arabia through fiscal and monetary policies.

The COVID-19 pandemic is still an ongoing global pandemic. The virus was first identified in Wuhan City in China at the beginning of December 2019. At the end of January 2020, the World Health Organization (WHO) declared that the outbreak of the virus represented a public health emergency, and later, on March 11, 2020, WHO declared the situation had transformed into a pandemic. Until January 17, 2022, the pandemic had caused more than 328 million cases and 545 million deaths, while 188 million of the cases had recovered. It is worth mentioning that the pandemic caused several social and economic disruptions, including a global economic recession; shortages in goods, supplies and equipment due to consumers' panic and thus tendency to buy; besides causing other disruptions like the negative impacts on health, as well as political, cultural, religious and sport events that influenced economic policies, including both the fiscal and monetary policies of world countries (Wikipedia, 2022).

Social implications steps that taken to reduce the impacts of the COVID-19 pandemic, in addition to measuring the impacts of the COVID-19 pandemic (as the main event next to which other events fade up) on some of the fiscal and monetary indicators for the Kingdom of Saudi Arabia.

The research aims to demonstrate measures taken by the Kingdom of Saudi Arabia through fiscal and monetary policies to mitigate the impacts of the COVID-19 pandemic, in addition to measuring the impacts of the COVID-19 pandemic (as the main event next to which other events fade up) on some of the fiscal and monetary indicators for the Kingdom of Saudi Arabia.

In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

The purpose of this paper is to examine performance change in the Irish state-owned port sector over the 2000-2016 period using a case study approach.

For analysis, qualitative sources are used to construct an explanatory account for the quantitative measures of productivity, profitability and traffic shift-share change across the major ports within the system.

The results show that overall change in performance largely follows that of the macro-economic performance of the region, characterised by pre-recession growth, decline during the recession and post-recession recovery. Across the ports, however, there was a notable divergence in performance post-recession. Identified factors affecting performance change across the period include demand-side structural change, labour rationalisation and degree of private sector participation.

This study addresses a gap in the formal evaluation of port performance in Ireland. The study further demonstrates the potential of in-depth case study analysis for uncovering insights into the drivers of performance across a number of dimensions, thus allowing for the contextualisation of results. The study of a small number of cases enables the use of rich qualitative sources to create strong narratives, which combined with quantitative measures of performance, can lead to new insights.