
Green Engineering for Optimizing Firm Performance
Description
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Explores topics such as green engineering, AI/ML applications, green finance, green HRM, and green innovation, showing their collective impact on business performance
Presents real-world case studies and empirical findings to demonstrate how organizations across different industries have successfully implemented sustainable technologies
Examines regional variations in green management practices, offering insights into the impact of economic, regulatory, and cultural contexts on sustainability initiatives
Critically analyzes contemporary challenges with practical strategies for addressing issues effectively
Recommends actionable policy and future research directions for sustainable business practices, providing a roadmap for advancing green management
This reference book is for academicians, scholars, and practitioners who are interested in emerging technologies that are reshaping firm performance and impacting sustainability.
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Persons
Dr. Balamurugan Balusamy is currently working as an Associate Dean Student in Shiv Nadar University, Delhi-NCR. Prior to this assignment he was Professor, School of Computing Sciences & Engineering and Director International Relations at Galgotias University, Greater Noida, India. His contributions focus on Engineering Education, Block chain and Data Sciences. His Academic degrees and twelve years of experience working as a faculty in a global University like VIT University, Vellore has made him more receptive and prominent in his domain. He does have 200 plus high impact factor papers in Springer, Elsevier and IEEE. He has done more than 80 Edited and authored books and collaborated with eminent professors across the world from top QS ranked university. Prof. Balamurugan Balusamy has served up to the position of Associate Professor in his stint of 12 years of experience with VIT University, Vellore. He has published 80+ books on various technologies and visited 15 plus countries for his technical course. He has several conferences in his resume and has published over 200 of quality journal, conference and book chapters combined. He serves in the advisory committee for several start-ups and forums and does consultancy work for industry on Industrial IOT. He has given over 195 talks in various events and symposiums.
Dr. Liza Macasukit Gernal is a distinguished academic with over two decades of experience in the field, having contributed her expertise in various countries such as the Philippines, Oman, and the United Arab Emirates. Dr. Gernal holds a Ph.D. in Management from the prestigious University of Liverpool in the United Kingdom, as well as a Doctor in Management from Liceo de Cagayan University in the Philippines. To further her academic journey, she is a candidate for her AQ Bridge to Business program at the University of Toledo in Ohio, USA.Dr. Gernal is renowned for her groundbreaking research, which delves into the profound impact of human activities on ecosystems.
She has also served as a dedicated mentor and supervisor to MBA and DBA students from Universidad de Catholica in Spain, nurturing the next generation of business leaders. Dr. Gernal's diverse research interests encompass environmental sustainability, human resource management, educational sustainability, AI in business, and various other business and technology-related fields.
Mahmoud Ahmad Al-Khasawneh holds a B.Sc. degree in Computer Science from Yarmouk University, Jordan, conferred in 2003. He obtained both his M.Sc. and Ph.D. degrees in Computer Science from Universiti Teknologi Malaysia (UTM), Johor, Malaysia, in 2013 and 2018, respectively. Currently, he serves as a faculty memeber in the School of ComputingSkyline University College, Sharjah UAE. Dr. Al-Khasawneh's scholarly pursuits span a diverse array of fields within computer science. He has authored numerous papers in esteemed, peer-reviewed journals across leading publishers. His research interests encompass Security, Image Encryption, Wireless Networks, Blockchain, Internet of Things, and Big Data.
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