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Sustainable Management, Digital Technologies, and Data Analytics for Green Environmental Management

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Dear Colleagues,

Digital technologies (more specifically, artificial intelligence) have gained rapid traction for their use in multiple business applications. This Special Issue focuses on the utilization of digital technologies by businesses and management for the purpose of sustainability (environmental management, sustainability reporting, and business accountability, as well as social and environmental legal compliance and stakeholder expectations).

Digital technologies, including artificial intelligence, are of great interest to management as they can help alleviate sustainability problems (Bohnsack et al. 2022). Digital technologies are expected to address critical societal problems such as climate change and resource depletion (Bohnsack et al. 2022). Digital solutions such as AI, the Internet of Things (IoT), and big data analytics are expected to address sustainability problems in supply chains, promote resource and energy efficiency, and contribute to sustainability driven business innovations (Bohnsack et al. 2022). Other examples of the business applications of digital technologies include digital manufacturing, augmented reality, blockchains, and digital platforms (Schneider, 2019). Nevertheless, the application of digital technologies for sustainability management faces multiple challenges (Schneider, 2019). One challenge is the under-exploration of the potential uses of digital technologies for sustainability management (Wei et al. 2023). Other issues associated with the utilization of digital technologies include electronic waste, high energy consumption, carbon emissions, job insecurity, and data privacy issues (Raihan, 2024).

It is critical to address the opportunities and challenges associated with the utilization of digital technologies for sustainable management.

This Special Issue aims to cover multiple angles and applications (current and potential) of digital technologies for sustainable management. As such, this Special Issue fits in the scope of the journal, being the exploration of environmental and social sustainability and socio-economic approaches to sustainable development.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

Environmental impact management;
Climate risk management;
Carbon emission reduction;
Waste management;
Resource efficiency;
Supply chain sustainability issues (such as upstream and downstream Scope 3 emissions) management;
Social sustainable management.

References

Bohnsack, R., Bidmon, C.M. and Pinkse, J. eds., 2022. Sustainability in the digital age: Intended and unintended consequences of digital technologies for sustainable development (pp. 599-602). Hoboken, NJ, USA: Wiley.

Schneider, S., 2019. The impacts of digital technologies on innovating for sustainability. Innovation for Sustainability: Business Transformations Towards a Better World, pp.415-433.

Wei, C., Li, C.Z., Löschel, A., Managi, S. and Lundgren, T., 2023. Digital technology and energy sustainability: Recent advances, challenges, and opportunities. Resources, Conservation and Recycling, 190, p.106803.

Raihan, A., 2024. A review of the potential opportunities and challenges of the digital economy for sustainability. Innovation and Green Development, 3(4), p.100174.

I look forward to receiving your contributions.

Dr. Tehmina Khan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

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31 pages, 596 KB

Open AccessArticle

Conceptualization of Artificial Intelligence Use for GHG Scope 3 Emissions Measurement, Reporting, Monitoring, and Assurance: A Critical Systems Perspective

by Tehmina Khan and David Teh

Sustainability 2025, 17(22), 10153; https://doi.org/10.3390/su172210153 - 13 Nov 2025

Viewed by 1536

Abstract

This article provides a conceptual and exploratory examination of Scope 3 greenhouse gas (GHG) emissions, focusing on the complexities associated with their nature, measurement, reporting, and verification. It examines the emerging role of artificial intelligence (AI) in addressing these complexities, particularly considering the fragmented, opaque, and often inaccessible nature of Scope 3 data. The paper introduces Critical Systems Thinking (CST) as a foundational framework for considering the practicality of utilization of AI in this context. CST emphasizes three key principles: critical awareness of assumptions and contexts, emancipation through attention to power dynamics and continuous improvement, and methodological pluralism, to engage with complexity through diverse analytical approaches. Due to the complex nature of GHG emissions reporting and assurance, AI application for this purpose remains limited. While Scope 3 reporting has made progress in certain sectors and regions, overall maturity remains uneven—particularly in developing and emerging markets. Although AI applications in Scope 3 reporting are still at an early stage, they hold significant potential to enhance both reporting quality and assurance processes. A key factor that needs to be addressed in the future utilization of AI for Scope 3 emissions reporting and assurance is the integration of CST into the development and implementation of AI tools. This paper proposes such integration as a necessary step forward. At present, there are substantial gaps in Scope 3 emissions measurement and reporting due to the inherently highly complex, distributed, and fragmented nature of value chain emissions. This gap poses risks to data quality and consistency, which in turn can hinder the implementation of reporting legislation and informed decision making by management and stakeholders. Systemic fragmentation, power asymmetries in data access, and methodological inconsistencies present substantial challenges to traditional forms of validation. Rather than offering a predictive model or finalized solution, the paper aims to lay a conceptual foundation for future empirical research and highlights the importance of systems-based approaches in advancing the credibility and utility of Scope 3 GHG disclosures. This is a key limitation relating to this paper, as it mainly focuses on the CST framework and the potential incapacities of artificial intelligence in relation to the implementation of CST, rather than applications of CST, as they are limited at present. Full article

(This article belongs to the Special Issue Sustainable Management, Digital Technologies, and Data Analytics for Green Environmental Management)

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