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Judul Quantitative Risk Management in Agricultural Business / Edited by Hirbod Assa; Peng Liu; Simon Wang
Pengarang Assa, Hirbod
Liu, Peng
Wang, Simon
Penerbitan Cham, : Springer Nature, 2025
Deskripsi Fisik 332 p. :ill.
ISBN 9783031805738
Subjek RISK ASSESSMENT
Catatan This open access volume explores the cutting edge of quantitative methods in agricultural risk management and insurance. Composed of insightful articles authored by field experts, focusing on innovation, recent advancements, and the use of technology and data sciences, it bridges the gap between theory and practice through empirical studies, concrete examples and case analyses. Evolving challenges in risk management have called for the development of new, groundbreaking models. Beyond presenting the theoretical foundations of these models, this book discusses their real-world applications, providing tangible insights into how innovative modeling can elevate risk management strategies in the agricultural sector. The latest risk management tools incorporate novel concepts such as index insurance, price index risk management frameworks and risk pools. The practical implications of these approaches are investigated, and their impact on contemporary agricultural risk mitigation and insurance practices is examined.
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Lokasi Akses Online https://directory.doabooks.org/handle/20.500.12854/158415

 
No Barcode No. Panggil Akses Lokasi Ketersediaan
052826192 658.15 Qua Dapat dipinjam Perpustakaan Pusat - Online Resources
Ebook
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245 # # $a Quantitative Risk Management in Agricultural Business /$c Edited by Hirbod Assa; Peng Liu; Simon Wang
260 # # $a Cham, :$b Springer Nature,$c 2025
300 # # $a 332 p. : $b ill.
505 # # $a This open access volume explores the cutting edge of quantitative methods in agricultural risk management and insurance. Composed of insightful articles authored by field experts, focusing on innovation, recent advancements, and the use of technology and data sciences, it bridges the gap between theory and practice through empirical studies, concrete examples and case analyses. Evolving challenges in risk management have called for the development of new, groundbreaking models. Beyond presenting the theoretical foundations of these models, this book discusses their real-world applications, providing tangible insights into how innovative modeling can elevate risk management strategies in the agricultural sector. The latest risk management tools incorporate novel concepts such as index insurance, price index risk management frameworks and risk pools. The practical implications of these approaches are investigated, and their impact on contemporary agricultural risk mitigation and insurance practices is examined. Field experiences illustrate the implementation of these tools and their resulting outcomes. Modern data analysis techniques in agricultural risk and insurance include machine learning, spatial analysis, text analysis, and deep learning. In addition to scrutinizing these ideas, the authors introduce an economic perspective towards risk, highlighting areas that have developed thanks to technological progress. Examples illustrate how these combined methodologies contribute to informed decision-making in agriculture, and their potential benefits and challenges are considered. This carefully compiled volume will be a valuable reference for researchers, practitioners, and students intrigued by the dynamic intersection of agricultural risk management and insurance practices.
650 # # $a RISK ASSESSMENT
700 1 # $a Assa, Hirbod
700 1 # $a Liu, Peng
700 1 # $a Wang, Simon
856 # # $a https://directory.doabooks.org/handle/20.500.12854/158415
990 # # $a 052826192
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