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Recent Comments
Dear Editors,
I would like to submit the following chapter proposal for consideration in your edited volume From Linear to Circular Business Models — AI-Driven Sustainable Growth in Emerging Markets.
Proposed Chapter Title
From Enterprise AI to Circular Transitions: Examining the Role of Complementary Digital Technologies in Emerging Markets
Abstract
Background
Recent years have witnessed an influx in investments by companies to integrate AI to automate middle management layers and serve as a means of retrieval for larger repositories; however, suboptimal utilization practices and limited domain-specific understanding have resulted in lower-than-anticipated returns.
Research Context
Concurrently, the study utilizes secondary peer-reviewed sources to explore the possibility of synergistic deployment of AI and other modern technologies such as IoT, blockchain, and digital twins to help transition towards circular economies through resource optimization, predictive decision-making, and management.
Objectives
This chapter seeks to: (i) examine the relationship between AI, complementary digital technologies, and circular economy principles in the context of emerging economies; (ii) explore how AI and complementary technologies such as IoT, blockchain, and digital twins can support resource optimization and facilitate the transition from linear to circular economic models; (iii) identify the opportunities, challenges, and adoption patterns associated with the deployment of these technologies within ASEAN and BRICS economies; and (iv) provide a comparative perspective and propose pathways to guide future research and practical implementation in support of sustainable development goals and evolving market needs.
Research Gap
However, evidence regarding the successful impact of these architectures within ASEAN and BRICS economies remains limited.
Methodology
To address this gap, the scope of this study is not limited to the consolidation of evidence regarding how Industry 4.0 technologies are driving a paradigm shift towards a circular model, but also extends to a comparative case analysis to identify existing challenges and points of improvement in both theoretical and applied frameworks, proposing optimal pathways for the future and examining the impacts of emerging adoption patterns to enable this circular transition in line with SDGs and market needs.
Conclusions
Enterprise AI adaptation lacks the capabilities required for circular economy transitions. The study also observes that non-technical factors exert a greater influence on circular transition implementation; however, emerging economies may leapfrog traditional methods through the adoption of digitally enabled circular practices. The chapter is expected to highlight economies to accelerate circular transitions through digitally enabled practices and provide insights that may guide research and implementation line with sustainable development goals and needs.
Authors
Raghav Purohit
Email: 1ds24cb042@dsce.edu.in
Rudresh A S
Vibhav J Bharadwaj
Email: 1ds24cb058@dsce.edu.in
Dr. Archana Nandibewoor
Samriddh Pandey
Kind regards,
Raghav Purohit
Dear Editors,
I would like to provide an update regarding the authors' affiliations and designations for our submitted chapter proposal.
Raghav Purohit, Rudresh A S, Vibhav J Bharadwaj, and Samriddh Pandey are undergraduate students at Dayananda Sagar College of Engineering, Bengaluru, India. Dr. Archana Nandibewoor is the Head of the Department of Computer Science and Business Systems (CSBS) at Dayananda Sagar College of Engineering, Bengaluru, India.
Kindly consider these details for the final records associated with our submission.
Thank you for your time and consideration.
Kind regards,
Raghav Purohit
1ds24cb042@dsce.edu.in
Dear Editors,
I would like to submit the following chapter proposal for consideration in your edited volume From Linear to Circular Business Models — AI-Driven Sustainable Growth in Emerging Markets.
Proposed Chapter Title
From Enterprise AI to Circular Transitions: Examining the Role of Complementary Digital Technologies in Emerging Markets
Abstract
Background
Recent years have witnessed an influx in investments by companies to integrate AI to automate middle management layers and serve as a means of retrieval for larger repositories; however, suboptimal utilization practices and limited domain-specific understanding have resulted in lower-than-anticipated returns.
Research Context
Concurrently, the study utilizes secondary peer-reviewed sources to explore the possibility of synergistic deployment of AI and other modern technologies such as IoT, blockchain, and digital twins to help transition towards circular economies through resource optimization, predictive decision-making, and management.
Objectives
This chapter seeks to: (i) examine the relationship between AI, complementary digital technologies, and circular economy principles in the context of emerging economies; (ii) explore how AI and complementary technologies such as IoT, blockchain, and digital twins can support resource optimization and facilitate the transition from linear to circular economic models; (iii) identify the opportunities, challenges, and adoption patterns associated with the deployment of these technologies within ASEAN and BRICS economies; and (iv) provide a comparative perspective and propose pathways to guide future research and practical implementation in support of sustainable development goals and evolving market needs.
Research Gap
However, evidence regarding the successful impact of these architectures within ASEAN and BRICS economies remains limited.
Methodology
To address this gap, the scope of this study is not limited to the consolidation of evidence regarding how Industry 4.0 technologies are driving a paradigm shift towards a circular model, but also extends to a comparative case analysis to identify existing challenges and points of improvement in both theoretical and applied frameworks, proposing optimal pathways for the future and examining the impacts of emerging adoption patterns to enable this circular transition in line with SDGs and market needs.
Conclusions
Enterprise AI adaptation lacks the capabilities required for circular economy transitions. The study also observes that non-technical factors exert a greater influence on circular transition implementation; however, emerging economies may leapfrog traditional methods through the adoption of digitally enabled circular practices. The chapter is expected to highlight economies to accelerate circular transitions through digitally enabled practices and provide insights that may guide research and implementation line with sustainable development goals and needs.
Authors
Raghav Purohit
Email: 1ds24cb042@dsce.edu.in
Rudresh A S
Vibhav J Bharadwaj
Email: 1ds24cb058@dsce.edu.in
Dr. Archana Nandibewoor
Samriddh Pandey
Kind regards,
Raghav Purohit