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Risks
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Risk Management in Shipping and Industry
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Risk Management in Shipping and Industry

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: 30 November 2024 | Viewed by 4669

Special Issue Editor

Prof. Dr. Eleftherios I. Thalassinos

E-Mail Website
Guest Editor
1. Faculty of Maritime and Industrial Studies, University of Piraeus, 185-33 Piraeus, Greece
2. Faculty of Economics, Management and Accountancy, University of Malta, 2080 Msida, Malta
Interests: sustainability; risk management; finance and financial institutions; business models
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

After the recent financial crisis, most transport activities have been highly evaluated with regard to their associated risks. In addition, financial services are covered by specialised products to protect the initial capital, the conditions of the agreement, exchange rates, premiums, and other related issues. For the industry, in addition to the financial crisis, the COVID-19 pandemic and the war in Ukraine have created a mix of uncertainties and irregularities in production, distribution and availability of final goods in markets, leading to additional coverage and higher insurance premiums depending on the level of risk associated with these activities.

For full protection, the shipping sector and the industry have organized risk units, using advanced quantitative and qualitative models and analysing business scenarios and financial conditions to overlap disturbances and unforeseen consequences during the times of disturbance ahead.

This Special Issue is designed to cover issues in the broad area of risks, uncertainties, irregularities and asymmetries in economics and finance, providing reliable solutions to the main problem of the best allocation of business resources in combination with the business benefit and consumers’ satisfaction.

We encourage authors to submit their manuscripts related, but not limited, to the following topics:

  • Optimum risk;
  • Business risk and benefits;
  • Maritime transport risk;
  • Commercial risk;
  • Risk in trading commodities;
  • Transfer risk;
  • Mathematical risk models;
  • Quantitative and qualitative applications related to risk;
  • Cost benefit analysis;
  • Project evaluation and approval;
  • Real estate risk models;
  • Financial risk.

Prof. Dr. Eleftherios I. Thalassinos
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Risks is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • maritime transport accidents
  • risk in trading commodities
  • mathematical risk models
  • financial risk
  • risk in transport payments
  • real estate risk models
  • optimum risk

Published Papers (2 papers)

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Research

31 pages, 8215 KiB  
Article
FMEA Model in Risk Analysis for the Implementation of AGV/AMR Robotic Technologies into the Internal Supply System of Enterprises
by Yuriy Bekishev, Zhanna Pisarenko and Vladislav Arkadiev
Risks 2023, 11(10), 172; https://doi.org/10.3390/risks11100172 - 30 Sep 2023
Cited by 1 | Viewed by 1927
Abstract
In the evolving economic landscape, Industry 4.0 emphasizes strategic planning and operational progress for large enterprises. This transformation relies on smart robotization technologies like AGVs (Automated Guided Vehicles) and AMRs (Autonomous Mobile Robots) for reducing transportation time, thereby reducing energy costs per unit [...] Read more.
In the evolving economic landscape, Industry 4.0 emphasizes strategic planning and operational progress for large enterprises. This transformation relies on smart robotization technologies like AGVs (Automated Guided Vehicles) and AMRs (Autonomous Mobile Robots) for reducing transportation time, thereby reducing energy costs per unit of production, increasing energy efficiency, as well as replacing combustible-fuel-powered tools with electric ones. A number of concerns arise with their introduction into the production cycle. This research aims to provide a methodical basis for averting substantial mistakes when executing projects centered around the incorporation of AGVs/AMRs into in-house logistics systems. The FMEA method and empirical analysis were employed to achieve a more accurate risk assessment. APIS and MS Excel softwares were chosen. We investigated the potential hazards related to the incorporation of mobile robotic solutions and identified both external and internal threats. To streamline and improve project efficiency, a risk management algorithm for high-tech projects is presented in the paper. Integrating FMEA into projects implementing robotic technologies can lead to significant enhancements in risk reduction, and therefore cost savings, efficiency, safety, and quality, while fostering a culture of collaboration and problem solving. The research contributes to the literature by introducing an AMR planning and control framework to guide managers in the decision-making process, thereby supporting them to achieve optimal performance. Finally, we propose an agenda for future research within the field of interest. Full article
(This article belongs to the Special Issue Risk Management in Shipping and Industry)
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19 pages, 2862 KiB  
Article
Optimal Structure of Real Estate Portfolio Using EVA: A Stochastic Markowitz Model Using Data from Greek Real Estate Market
by Theofanis Petropoulos, Konstantinos Liapis and Eleftherios Thalassinos
Risks 2023, 11(2), 43; https://doi.org/10.3390/risks11020043 - 12 Feb 2023
Cited by 2 | Viewed by 1824
Abstract
The purpose of this paper is to examine the issue of portfolio optimization. Optimization consists of minimizing the risk for a given rate of return or achieving a bigger return for a given level of risk. We use historical data from the Bank [...] Read more.
The purpose of this paper is to examine the issue of portfolio optimization. Optimization consists of minimizing the risk for a given rate of return or achieving a bigger return for a given level of risk. We use historical data from the Bank of Greece to calculate the net return and the standard deviation (std) for each type of property that is available. The objective is to maximize the economic value added (EVA) of a property’s assets portfolio under a specific rate of standard deviation, following the classic Markowitz model (M-V). The stochastic procedure entry in the model uses the Monte Carlo Simulation method with debt to equity (DTE) following PERT distribution for the portfolio’s invested budget, and the net return for the normal distribution with the mean of the expected return and std are taken from historical data, correspondingly. The returns verify that they follow the base assumption of normality through the Lilliefors test in the Greek real estate market. We observe the maximization of EVA and the expected return maximizing concurrently, but the minimizing risk of EVA is diversified with the minimization of portfolio risk. We observe that the max weight that a residential asset takes is 22.7% because a bigger percent reduces both mean and std. The study provides an explicit portfolio optimization procedure under uncertainty in the real estate market and enriches the academic debate about EVA and revenue. Full article
(This article belongs to the Special Issue Risk Management in Shipping and Industry)
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