IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i9p2717-d230774.html
   My bibliography  Save this article

A Data-Driven Approach to Development of a Taxonomy Framework for Triple Bottom Line Metrics

Author

Listed:
  • Fátima L. Vieira

    (Human Technology Group, Department of Electromechanical Engineering and Centre for Mechanical and Aerospace Science and Technology, Universidade da Beira Interior, 6201-001 Covilhã, Portugal)

  • Paulo A. Vieira

    (Department of Computer Science and Cloud Computing Competence Centre, Universidade da Beira Interior, 6201-001 Covilhã, Portugal)

  • Denis A. Coelho

    (Human Technology Group, Department of Electromechanical Engineering and Centre for Mechanical and Aerospace Science and Technology, Universidade da Beira Interior, 6201-001 Covilhã, Portugal
    Human Factors and Ergonomics Group, Department of Supply Chain and Operations Management, School of Engineering, Jönköping University, 55111 Jönköping, Sweden)

Abstract

This paper proposes a data-driven approach to develop a taxonomy in a data structure on list for triple bottom line (TBL) metrics. The approach is built from the authors reflection on the subject and review of the literature about TBL. The envisaged taxonomy framework grid to be developed through this approach will enable existing metrics to be classified, grouped, and standardized, as well as detect the need for further metrics development in uncovered domains and applications. The approach reported aims at developing a taxonomy structure that can be seen as a bi-dimensional table focusing on feature interrogations and characterizing answers, which will be the basis on which the taxonomy can then be developed. The interrogations column is designed as the stack of the TBL metrics features: What type of metric is it (qualitative, quantitative, or hybrid)? What is the level of complexity of the problems where it is used? What standards does it follow? How is the measurement made, and what are the techniques that it uses? In what kinds of problems, subjects, and domains is the metric used? How is the metric validated? What is the method used in its calculation? The column of characterizing answers results from a categorization of the range of types of answers to the feature interrogations. The approach reported in this paper is based on a screening tool that searches and analyzes information both within abstracts and full-text journal papers. The vision for this future taxonomy is that it will enable locating for any specific context, discern what TBL metrics are used in that context or similar contexts, or whether there is a lack of developed metrics. This meta knowledge will enable a conscious decision to be made between creating a new metric or using one of those that already exists. In this latter case, it would also make it possible to choose, among several metrics, the one that is most appropriate to the context at hand. In addition, this future framework will ease new future literature revisions, when these are viewed as updates of this envisaged taxonomy. This would allow creating a dynamic taxonomy for TBL metrics. This paper presents a computational approach to develop such taxonomy, and reports on the initial steps taken in that direction, by creating a taxonomy framework grid with a computational approach.

Suggested Citation

  • Fátima L. Vieira & Paulo A. Vieira & Denis A. Coelho, 2019. "A Data-Driven Approach to Development of a Taxonomy Framework for Triple Bottom Line Metrics," Sustainability, MDPI, vol. 11(9), pages 1-17, May.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:9:p:2717-:d:230774
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/9/2717/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/9/2717/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wagner Cezar Lucato & José Carlos da Silva Santos & Athos Paulo Tadeu Pacchini, 2017. "Measuring the Sustainability of a Manufacturing Process: A Conceptual Framework," Sustainability, MDPI, vol. 10(1), pages 1-12, December.
    2. Denis A. Coelho & Tiago E. P. Carrola & Ana F. Couvinhas, 2017. "Improvement of Certified Artisan Cheese Production through Systemic Analysis— Serra da Estrela PDO," Sustainability, MDPI, vol. 9(3), pages 1-18, March.
    3. Assâad El Akremi & Jean-Pascal Gond & Valérie Swaen & Kenneth de Roeck & Jacques Igalens, 2018. "How Do Employees Perceive Corporate Responsibility? Development and Validation of a Multidimensional Corporate Stakeholder Responsibility Scale," Post-Print halshs-01520959, HAL.
    4. Jessica Gurevitch & Julia Koricheva & Shinichi Nakagawa & Gavin Stewart, 2018. "Meta-analysis and the science of research synthesis," Nature, Nature, vol. 555(7695), pages 175-182, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Van Can Nguyen & Chi-Tai Wang & Ying-Jiun Hsieh, 2021. "Electrification of Highway Transportation with Solar and Wind Energy," Sustainability, MDPI, vol. 13(10), pages 1-28, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Oded Berger-Tal & Alison L Greggor & Biljana Macura & Carrie Ann Adams & Arden Blumenthal & Amos Bouskila & Ulrika Candolin & Carolina Doran & Esteban Fernández-Juricic & Kiyoko M Gotanda & Catherine , 2019. "Systematic reviews and maps as tools for applying behavioral ecology to management and policy," Behavioral Ecology, International Society for Behavioral Ecology, vol. 30(1), pages 1-8.
    2. Franck Brulhart & Sandrine Gherra & Bertrand V. Quelin, 2019. "Do Stakeholder Orientation and Environmental Proactivity Impact Firm Profitability?," Journal of Business Ethics, Springer, vol. 158(1), pages 25-46, August.
    3. Kim, Yeonshin & Hur, Won-Moo & Lee, Luri, 2023. "Understanding customer participation in CSR activities: The impact of perceptions of CSR, affective commitment, brand equity, and corporate reputation," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    4. Asif Khan & Chih-Cheng Chen & Kwanrat Suanpong & Athapol Ruangkanjanases & Santhaya Kittikowit & Shih-Chih Chen, 2021. "The Impact of CSR on Sustainable Innovation Ambidexterity: The Mediating Role of Sustainable Supply Chain Management and Second-Order Social Capital," Sustainability, MDPI, vol. 13(21), pages 1-25, November.
    5. Mario Morales-Parragué & Luis Araya-Castillo & Fidel Molina-Luque & Hugo Moraga-Flores, 2022. "Scientometric Analysis of Research on Corporate Social Responsibility," Sustainability, MDPI, vol. 14(4), pages 1-22, February.
    6. Castaldo, Sandro & Ciacci, Andrea & Penco, Lara, 2023. "Perceived corporate social responsibility and job satisfaction in grocery retail: A comparison between low- and high-productivity stores," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    7. Jelena Filipović, 2019. "Market-Oriented Sustainability of Sjenica Sheep Cheese," Sustainability, MDPI, vol. 11(3), pages 1-18, February.
    8. Phu Nguyen-Van & Anne Stenger & Tuyen Tiet, 2021. "Social incentive factors in interventions promoting sustainable behaviors: A meta-analysis," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-27, December.
    9. Yusheng Kong & Alex Antwi‐Adjei & Jonas Bawuah, 2020. "A systematic review of the business case for corporate social responsibility and firm performance," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(2), pages 444-454, March.
    10. David A. Jones & Alexander Newman & Ruodan Shao & Fang Lee Cooke, 2019. "Advances in Employee-Focused Micro-Level Research on Corporate Social Responsibility: Situating New Contributions Within the Current State of the Literature," Journal of Business Ethics, Springer, vol. 157(2), pages 293-302, June.
    11. Saskia Crucke & Marie Servaes & Tom Kluijtmans & Shana Mertens & Eveline Schollaert, 2022. "Linking environmentally‐specific transformational leadership and employees' green advocacy: The influence of leadership integrity," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 29(2), pages 406-420, March.
    12. Fasilat Aramide Sanusi & Satirenjit Kaur Johl, 2020. "A proposed framework for assessing the influence of internal corporate social responsibility belief on employee intention to job continuity," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(6), pages 2437-2449, November.
    13. Irsova, Zuzana & Doucouliagos, Hristos & Havranek, Tomas & Stanley, T. D., 2023. "Meta-Analysis of Social Science Research: A Practitioner’s Guide," EconStor Preprints 273719, ZBW - Leibniz Information Centre for Economics.
    14. Stephen J. Smulowitz & Didier Cossin & Hongze Lu, 2023. "Managerial Short-Termism and Corporate Social Performance: The Moderating Role of External Monitoring," Journal of Business Ethics, Springer, vol. 188(4), pages 759-778, December.
    15. Bilal Afsar & Waheed Ali Umrani, 2020. "Corporate social responsibility and pro‐environmental behavior at workplace: The role of moral reflectiveness, coworker advocacy, and environmental commitment," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(1), pages 109-125, January.
    16. Felipe Lillo-Viedma & Pedro Severino-González & Valentin Santander-Ramírez & Leidy Y. García & Nataly Guiñez-Cabrera & Nicolás Astorga-Bustos, 2022. "Corporate Social Responsibility and Social Network Analysis: Unionized Workers’ Perceptions," Sustainability, MDPI, vol. 14(7), pages 1-15, April.
    17. Andrea Stübner & Svenja Jarchow, 2023. "Family oblige: the link between CSR and succession intention in small and medium family firms," Journal of Business Economics, Springer, vol. 93(3), pages 389-431, April.
    18. Sebastien Knockaert & François Grima & Olivier Brunel, 2018. "Prestige, respect et responsabilité sociale : attributs symboliques comme facteur d'attractivité organisationnelle d'une association," Post-Print hal-02362420, HAL.
    19. Lukas Hafner & Maxime Pichon & Christophe Burucoa & Sophie H. A. Nusser & Alexandra Moura & Marc Garcia-Garcera & Marc Lecuit, 2021. "Listeria monocytogenes faecal carriage is common and depends on the gut microbiota," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    20. Changchun Zhu & Jianguo Du & Fakhar Shahzad & Muhammad Umair Wattoo, 2022. "Environment Sustainability Is a Corporate Social Responsibility: Measuring the Nexus between Sustainable Supply Chain Management, Big Data Analytics Capabilities, and Organizational Performance," Sustainability, MDPI, vol. 14(6), pages 1-20, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:9:p:2717-:d:230774. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.