Modelling framework of the Tandem Supply Chain Efficiency and Sustainable Financial Performance in the Automotive Industry
The research examines the causal relationship between supply chain efficiency and sustainable financial performance based on the evidence from the literature dealing with a transition from financial decision-making based on the financial outcome, including financial rationale in supply chain design,...
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Published in: | Zbornik radova Ekonomskog fakulteta u Rijeci Vol. 40; no. 1; pp. 201 - 224 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
30-06-2022
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Online Access: | Get full text |
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Summary: | The research examines the causal relationship between supply chain efficiency and sustainable financial performance based on the evidence from the literature dealing with a transition from financial decision-making based on the financial outcome, including financial rationale in supply chain design, operations, and management. The case study has included 100 companies selected from the automotive production sector over ten years, from 2010 to 2019. Methodologically, the study includes statistically fixed and random effects models, considering within the model parameters as dependent variables asset and efficiency-based ratios and as independent variables financial performance ratios related to returns on assets, equity, capital expenses, and sales. The selection of the fixed or random- effects model is accomplished by performing the Hausman test. The results of panel analysis indicate a causal relationship for the proposed models, highlighting the importance of efficiency ratios such as Fixed Assets Turnover Ratio, Total Assets Turnover Ratio, and Fixed Assets Turnover. From practitioners` perspective, the models` construction and the paper’s results gain insight into strategic supply chain areas that can be prioritised for increased efficiency and corporate competitiveness, promoting sustainable financial performance through asset structure, asset efficiency, and inventory management. |
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ISSN: | 1331-8004 1846-7520 |
DOI: | 10.18045/zbefri.2022.1.20 |