The impact of Corporate Social Responsibility on corporate financial performance: an empirical study on shipping

ABSTRACT

Corporate social responsibility (CSR) attracts steaming attention in global maritime business, stimulated by critical priorities, such as the IMO 2020 regulations for environmental compliance and initiatives including the Poseidon Principles and ESG practices. The CSR implications for shipping corporate performance and value creation deserve updated empirical investigation. Based on international standards and ISO 26000 regulations, the paper proposes and sets up an innovative Corporate Social Responsibility (CSR) Index. This challenging metric tool is incorporated on a sample of 50 listed shipping companies in NYSE, NASDAQ, and Oslo markets, covering broadly all major shipping business sectors (bulks, tankers, containers, LNGs, cruises), over 2010–2019. The proposed CSR Index integrates 17 CSR components based on the ISO 26000 standard, as an alternative empirical index of the CSR impact on shipping company financial performance and value. The empirical results support the hypothesis of a significant positive correlation between CSR and shipping corporate performance and value and underline the preference of investors for shipping companies with established good CSR practices.

KEYWORDS:

• Corporate Social Responsibility
• CSR index
• ISO 26000
• shipping corporate performance and value creation

Acknowledgments

This article is a revised and expanded version of a paper entitled “The Impact of Corporate Social Responsibility on Corporate Financial Performance: An Empirical Study on Shipping” presented at IAME 2020 Conference, Hong Kong, 10-13 June 2020.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Each CSR pillar incorporated is extensively described in the ISO 26000 document (www.iso.org).

2. The respective shipping company share value on 31.12.2019 is used to calculate market capitalization weights.

Additional information

Funding

This work has been partially supported by the project Offspring, under the open call of ZDMP project, funded by the European Commission under Grant Agreement number 825631 through the Horizon 2020 Program.