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Information Processing for Quality Assurance in Reverse Logistics Supply Chains: An Organizational Information Processing Theory Perspective

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  • Madduma Kaluge Chamitha Sanjani Wijewickrama

    (UniSA STEM—Sustainable Infrastructure and Resource Management, University of South Australia, Adelaide, SA 5000, Australia)

  • Nicholas Chileshe

    (UniSA STEM—Sustainable Infrastructure and Resource Management, University of South Australia, Adelaide, SA 5000, Australia
    Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2094, South Africa)

  • Raufdeen Rameezdeen

    (UniSA STEM—Sustainable Infrastructure and Resource Management, University of South Australia, Adelaide, SA 5000, Australia)

  • Jose Jorge Ochoa

    (Australian Research Centre for Interactive and Virtual Environments, University of South Australia, Adelaide, SA 5000, Australia)

Abstract

Every year, the construction industry produces a large volume of demolition waste (DW) recovered through reverse logistics supply chains (RLSCs). Information-centric QA plays an important role in the RLSC, providing an excellent solution for inferior-quality reprocessed products. However, information deficiency creates epistemic uncertainties that lead to information-processing needs (IPNs) for QA, for which the internal stakeholders in the RLSC should respond by undertaking appropriate information-processing mechanisms (IPMs). Given this, the current study aims to explore how internal stakeholders process information for QA in RLSC of DW through the organizational information processing theory (OIPT) perspective. The study follows a qualitative approach encompassing 30 semi-structured interviews with internal and external stakeholders in the RLSC of DW. The study found eight uncertainties that stem from the internal organizational environment and two uncertainties caused by the interactions with stakeholders in the supply chain. In addition, 15 IPMs were identified, which the demolishers and waste processors could undertake in response to the epistemic uncertainties. The study developed an information-processing management framework that would serve practitioners and academics to understand how effectively process, people, policy and technology elements contribute to responding to the epistemic uncertainties for successful QA in RLSC of DW.

Suggested Citation

  • Madduma Kaluge Chamitha Sanjani Wijewickrama & Nicholas Chileshe & Raufdeen Rameezdeen & Jose Jorge Ochoa, 2022. "Information Processing for Quality Assurance in Reverse Logistics Supply Chains: An Organizational Information Processing Theory Perspective," Sustainability, MDPI, vol. 14(9), pages 1-31, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5493-:d:807916
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    References listed on IDEAS

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