Harnessing Smart Technologies for Enhancing Organizational Sustainability and Green Growth: Managerial and Administrative Perspectives

A Special Issue of Administrative Sciences (ISSN 2076-3387) belonging to the section "Organizational Behavior".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 2576

Editors


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Guest Editor
1. Department of Management, Rockford College, Sydney, Australia
2. Department of Management, Windsor University, Washington, DC, USA
Interests: sustainability; emerging technologies; organizational behaviour; entrepreneurship
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Guest Editor
1. Salford Business School, University of Salford, Salford M5 4WT, UK
2. College of Interdisciplinary Studies, Zayed University, Abu Dhabi 144534, United Arab Emirates
Interests: e-commerce; digital business; digital innovation; artificial intelligence; metaverse; digital marketing; business analytics

Special Issue Information

Dear Colleagues,

The rapid advancement of smart technologies has opened new pathways for organizations to align growth strategies with sustainability goals, reshaping the way businesses operate in the era of green transformation. From managerial and administrative perspectives, the integration of technologies such as artificial intelligence, blockchain, the Internet of Things, and advanced analytics not only enhances operational efficiency but also promotes eco-friendly practices and responsible resource management. The goal of this Special Issue is to explore how smart technologies can be strategically leveraged from managerial and administrative perspectives to foster organizational sustainability and drive green growth. Emphasis is placed on examining innovative tools such as artificial intelligence, big data analytics, blockchain, IoT, and digital platforms that enable organizations to optimize resource utilization, reduce environmental impact, and build resilient business models. By focusing on leadership strategies, policy frameworks, and sustainable administrative practices, this Special Issue seeks to bridge the gap between technology adoption and sustainable management, offering actionable insights that support organizations in achieving long-term environmental, social, and economic objectives.

We request that, prior to submitting a manuscript, interested authors initially submit a proposed title and an abstract of 300–500 words summarizing their intended contribution. Please send it to the Guest Editors (rohit.bansal@rockford.edu.au) or to Administrative Sciences Editorial Office (admsci@mdpi.com). Abstracts will be reviewed by the Guest Editors for the purposes of ensuring proper fit within the scope of the Special Issue. Full manuscripts will undergo double-blind peer-review.

Dr. Rohit Bansal
Dr. Mostafa Mohamad
Guest Editors

Manuscript Submission Information

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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 double-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Administrative Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Publisher’s Notice

Following discussions between the Administrative Sciences editorial office and the Guest Editor, a new Guest Editor, Dr. Mostafa Mohamad, has been added to the Special Issue. This change has been approved by the journal Editorial Board, and the Special Issue website has been updated accordingly on 23 July 2026. The Special Issue will continue to be handled by the new Guest Editor team in accordance with MDPI’s Special Issue and editorial policies.

Keywords

  • smart technologies
  • green growth
  • sustainability
  • technological innovation
  • smart energy
  • renewable solutions
  • artificial intelligence
  • internet of things
  • big data analytics
  • blockchain technology
  • administrative science
  • environmental monitoring
  • industry 6.0
  • managerial perspective

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Published Papers (1 paper)

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25 pages, 576 KB  
Systematic Review
AI-Driven Demand Planning: A Systematic Review of Adoption, Barriers and Strategic Implications
by Anteo Korcari, Marina Saridi, Antonia Koumpoti and Foivos Anastasiadis
Adm. Sci. 2026, 16(6), 260; https://doi.org/10.3390/admsci16060260 - 29 May 2026
Viewed by 1531
Abstract
Agri-food organisations face a deepening governance challenge: managing demand un-certainty, supply chain volatility, and food waste under tight operational margins and in-creasing sustainability pressures. While artificial intelligence (AI) offers transformative potential for logistics and operations management, the organisational dimensions of its adoption, including [...] Read more.
Agri-food organisations face a deepening governance challenge: managing demand un-certainty, supply chain volatility, and food waste under tight operational margins and in-creasing sustainability pressures. While artificial intelligence (AI) offers transformative potential for logistics and operations management, the organisational dimensions of its adoption, including strategic alignment, human capital development, and change management, remain insufficiently synthesised in the literature. This study investigates AI-driven demand planning as a management and organisational innovation, presenting a systematic review of 37 peer-reviewed studies (2015–2025) following the PRISMA protocol. Thematic synthesis across four analytical pillars, such as forecasting model applications, inventory and waste management practices, strategic impacts and resilience, and methodological overviews, reveals that advanced AI tools can reduce the mean absolute percentage error (MAPE) by 20–40% over traditional statistical methods in empirical case studies, with direct consequences for logistics performance, food waste reduction, and inventory governance. Critically, the review identifies persistent organisational barriers, particularly for SMEs: data governance deficiencies, high costs of technology adoption, workforce skill gaps, and the need for structured change management to institutionalise AI-based planning systems. The findings demonstrate that AI integration in agri-food supply chains constitutes a fundamental organisational transformation, requiring aligned strategies in innovation management, human resource development, supply chain governance, and sustainable business development. This review contributes to the administrative and management sciences by providing a structured, evidence-based framework for managers, policymakers, and practitioners navigating the organisational transition towards AI-enabled agri-food operations. Full article
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