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Performance drivers of shipping loans: an empirical investigation

Mitroussi, Kyriaki, Abouarghoub, Wessam, Haider, Jing, Pettit, Stephen John and Tigka, N. 2016. Performance drivers of shipping loans: an empirical investigation. International Journal of Production Economics 171 (3) , pp. 438-452. 10.1016/j.ijpe.2015.09.041

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Abstract

Credit risk is a major issue for lenders and borrowers, threatening the reliability of global logistics operations. Enhanced mechanisms of credit risk analysis are needed to safeguard banks and the flow of goods in supply chains. Little emphasis has been given to the contextual examination of such factors, either in terms of market conditions or the particular characteristics of different industries. This paper investigates the varying importance of a number of factors connected with the performance of corporate bank loans during times of financial turbulence in the shipping industry. Little extant literature exists on default risk drivers for loans made to shipping companies for new build vessels or second-hand ship purchases. A binary logit model is used to examine the criteria for assessing the security of shipping loans issued by banks. Thirty shipping loans made during the period 2005–2009 are examined. Results suggest that financial factors, non-financial factors, shipowners׳ experience, and employability and market risk indicators are the best criteria for evaluating the performance of shipping loans during turbulent market conditions and periods when financing options are restricted. The paper makes a specific contribution to the literature on risk management with regard to credit risk analysis by highlighting shipping specific factors and their importance for risk measurement. The results are of interest to banks seeking to accurately assess the credibility of shipping loans; shipowners, who can identify credit risk factors on which to focus; and supply chain participants where unfulfilled bank financing can cause disruptions to their logistics operations.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > HD Industries. Land use. Labor
Uncontrolled Keywords: Credit risk; Shipping loans; Performance drivers; Binary Logit Model
Publisher: Elsevier
ISSN: 0925-5273
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 29 September 2015
Last Modified: 27 Jun 2019 11:06
URI: http://orca-mwe.cf.ac.uk/id/eprint/83587

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