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Toward a Sustainability Balanced Scorecard for Managing Corporate Social Responsibility: A Conceptual Model

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Advances and Applications in Computer Science, Electronics and Industrial Engineering

Abstract

The Sustainability Balanced Scorecard (SBSC) allows companies to track organizational operations and measure their impact on company objectives. To monitor the impact of Corporate Social Responsibility (CSR) activities and ensure its alignment with the company’s strategy, CSR elements need to be integrated into the organization’s dashboards. The main goals of this study are threefold: (1) identify the main CSR elements and the proposal of an analysis scheme for CSR’s strategies; (2) assess local and regional CSR implementations using the previously identified elements, and (3) incorporate the identified CSR metrics into a management dashboard based on the findings of the previous steps. Both a systematic literature review and in-depth analysis of case studies were used in this study. The results show that four elements: principles, dimensions, stakeholders, and means can be applied to analyze CSR strategies consistently. In addition, a structure for a management dashboard that incorporates subcategories and indicators for the assessment of sustainable CSR strategies aligned with the company goals is proposed.

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Acknowledgements

This research was carried out under the projects “Enhancing the Social Value of the Circular Economy in Latin-American” and “Incorporating Sustainability concepts to management models of textile Micro, Small and Medium Enterprises (SUMA)” funded by the Flemish Interuniversity Council (VLIR) and the Research Direction of the University of Cuenca (DIUC).

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Correspondence to Gabriela Sucozhañay .

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Sucozhañay, G., Cabrera, F., Sucozhañay, D., Guaman, R., Siguenza-Guzman, L., Vanegas, P. (2021). Toward a Sustainability Balanced Scorecard for Managing Corporate Social Responsibility: A Conceptual Model. In: García, M.V., Fernández-Peña, F., Gordón-Gallegos, C. (eds) Advances and Applications in Computer Science, Electronics and Industrial Engineering. Advances in Intelligent Systems and Computing, vol 1307. Springer, Singapore. https://doi.org/10.1007/978-981-33-4565-2_18

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