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Using Big Data for Sustainability in Supply Chain Management

Author

Listed:
  • Ricardo Chalmeta

    (Grupo de Integración y Re-Ingeniería de Sistemas (IRIS), Departamento de Lenguajes y Sistemas Informáticos, Universidad Jaume I, 12071 Castelló, Spain)

  • José-Eduardo Barqueros-Muñoz

    (Grupo de Integración y Re-Ingeniería de Sistemas (IRIS), Departamento de Lenguajes y Sistemas Informáticos, Universidad Jaume I, 12071 Castelló, Spain)

Abstract

In the literature, several frameworks have been proposed to help sustainability management in supply chains. Nevertheless, they present a number of shortcomings. With the aim of overcoming these shortcomings, this paper proposes a framework for sustainable supply chain management composed of six dimensions: methodology, organization, stakeholders, maturity model, human resources, and technology. The main innovations of the framework are that (1) it includes a methodology that acts as a guide to sustainability management and improvement in a holistic way by using a balanced scorecard for any type of supply chain and covering the whole project life cycle; (2) it combines quantitative and qualitative methods for sustainability assessment; (3) it describes the techniques and technology to be used in each task of the methodology; and (4) it identifies the past impact of SC sustainability, as well as predicting its future impact, using Big Data analytics. The practical utility, completeness, and level of detail of the framework were validated through questionnaires answered by both five academics and three professionals. In addition, the framework was applied to a case study to (1) validate its usefulness and (2) to improve it with the feedback obtained.

Suggested Citation

  • Ricardo Chalmeta & José-Eduardo Barqueros-Muñoz, 2021. "Using Big Data for Sustainability in Supply Chain Management," Sustainability, MDPI, vol. 13(13), pages 1-25, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:13:p:7004-:d:579556
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    References listed on IDEAS

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    Cited by:

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    3. Zuhal Cilingir Uk & Cigdem Basfirinci & Amit Mitra, 2022. "Weighted Interpretive Structural Modeling for Supply Chain Risk Management: An Application to Logistics Service Providers in Turkey," Logistics, MDPI, vol. 6(3), pages 1-22, August.
    4. Rosangela de Fátima Pereira Marquesone & Tereza Cristina Melo de Brito Carvalho, 2022. "Examining the Nexus between the Vs of Big Data and the Sustainable Challenges in the Textile Industry," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
    5. Anup Kumar & Santosh Kumar Shrivastav & Avinash K. Shrivastava & Rashmi Ranjan Panigrahi & Abbas Mardani & Fausto Cavallaro, 2023. "Sustainable Supply Chain Management, Performance Measurement, and Management: A Review," Sustainability, MDPI, vol. 15(6), pages 1-25, March.
    6. Pawlicka Kinga & Bal Monika, 2022. "Sustainable Supply Chain Finances implementation model and Artificial Intelligence for innovative omnichannel logistics," Management, Sciendo, vol. 26(1), pages 19-35, January.
    7. Maniyassouwe Amana & Pingfeng Liu & Mona Alariqi, 2022. "Value Creation and Capture with Big Data in Smart Phones Companies," Sustainability, MDPI, vol. 14(23), pages 1-22, November.
    8. Damianos P. Sakas & Nikolaos Th. Giannakopoulos, 2021. "Harvesting Crowdsourcing Platforms’ Traffic in Favour of Air Forwarders’ Brand Name and Sustainability," Sustainability, MDPI, vol. 13(15), pages 1-25, July.

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