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The cognition map of financial ratios of shipping companies using DEMATEL and MMDE

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  • Paul Tae-Woo Lee
  • Cheng-Wei Lin

Abstract

This paper finds the inter-relationship of financial ratios to be identified by managers of shipping companies and financial experts and compares their cognition map of the financial ratios by country and by financial expert group, using both decision-making technique laboratory and maximum mean de-entropy algorithm with the questionnaires collected from major shipping companies in Taiwan and Korea. The empirical analysis of the cognition maps reveals that there are big differences between the two countries and among the four respondent groups and that the shipping managers are more concerned with a wider range of financial ratios when dealing with the financial problems; in contrast, the financial ratios focused by certificated public accounts (CPAs) are in relatively narrower range than the shipping managers. Both the shipping managers and the CPAs are little concerned with the groups of activity efficiency and cash flow out of the total six groups. The contribution of cognition map in this study enables stakeholders of the shipping companies to predict management behaviour of shipping managers. The cognition map also contributes to predicting business and financial strategies of the shipping companies, based on the cognition of financial ratios of their shipping managers, subject to global economic booming or slowdown conditions.

Suggested Citation

  • Paul Tae-Woo Lee & Cheng-Wei Lin, 2013. "The cognition map of financial ratios of shipping companies using DEMATEL and MMDE," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(2), pages 133-145, March.
    • Handle: RePEc:taf:marpmg:v:40:y:2013:i:2:p:133-145
    DOI: 10.1080/03088839.2012.757374
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    Citations

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    Cited by:

    1. Arthur J. Lin & Hai-Yen Chang & Brian Hung, 2022. "Identifying Key Financial, Environmental, Social, Governance (ESG), Bond, and COVID-19 Factors Affecting Global Shipping Companies—A Hybrid Multiple-Criteria Decision-Making Method," Sustainability, MDPI, vol. 14(9), pages 1-29, April.
    2. Ha, Min-Ho & Yang, Zaili, 2017. "Comparative analysis of port performance indicators: Independency and interdependency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 264-278.
    3. Dong-Shang Chang & Wei-De Wu, 2021. "Impact of the COVID-19 Pandemic on the Tourism Industry: Applying TRIZ and DEMATEL to Construct a Decision-Making Model," Sustainability, MDPI, vol. 13(14), pages 1-28, July.
    4. Paul Tae-Woo Lee & Cheng-Wei Lin & Yi-Shih Chung, 2014. "Comparison analysis for subjective and objective weights of financial positions of container shipping companies," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(3), pages 241-250, May.
    5. Tien-Chun Ho & Hsuan-Shih Lee, 2023. "An Analysis of the Technology, Service Quality, and Relevance for CSBC Corporation: Taiwan’s Installation of Scrubber Systems," Sustainability, MDPI, vol. 15(7), pages 1-20, March.
    6. Xinping Wang & Cheng Zhang & Jun Deng & Chang Su & Zhenzhe Gao, 2022. "Analysis of Factors Influencing Miners’ Unsafe Behaviors in Intelligent Mines using a Novel Hybrid MCDM Model," IJERPH, MDPI, vol. 19(12), pages 1-30, June.
    7. Vafadarnikjoo, Amin & Tavana, Madjid & Chalvatzis, Konstantinos & Botelho, Tiago, 2022. "A socio-economic and environmental vulnerability assessment model with causal relationships in electric power supply chains," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).

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