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Enterprise Risk Management Models

ISBN-13: 9783662680377 / Angielski / Twarda / 2023

David L. Olson;Desheng Wu
Enterprise Risk Management Models David L. Olson, Desheng Wu 9783662680377 Springer Berlin Heidelberg - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Enterprise Risk Management Models

ISBN-13: 9783662680377 / Angielski / Twarda / 2023

David L. Olson;Desheng Wu
cena 483,04
(netto: 460,04 VAT:  5%)

Najniższa cena z 30 dni: 424,07
Termin realizacji zamówienia:
ok. 22 dni roboczych.

Darmowa dostawa!

Enterprise risk management has always been important. However, the events of the 21st Century have made it even more critical. The top level of business management became suspect after scandals at ENRON, WorldCom, and other business entities. Financially, many firms experienced difficulties from bubbles. The problems of interacting cultures demonstrated risk from terrorism as well, with numerous terrorist attacks, to include 9/11 in the U.S. Risks can arise in many facets of business. Businesses in fact exist to cope with risk in their area of specialization. Financial risk management has focused on banking, accounting, and finance. We have discussed several aspects of risk, to include information systems, disaster management, and supply chain perspectives. The bulk of this book is devoted to presenting a number of operations research models that have been (or could be) applied to enterprise supply risk management, especially from the supply chain perspective.

Kategorie:
Nauka, Ekonomia i biznes
Kategorie BISAC:
Business & Economics > Insurance - Risk Assessment & Management
Business & Economics > Production & Operations Management
Computers > Computer Simulation
Wydawca:
Springer Berlin Heidelberg
Seria wydawnicza:
Springer Texts in Business and Economics
Język:
Angielski
ISBN-13:
9783662680377
Rok wydania:
2023
Waga:
0.56 kg
Wymiary:
23.5 x 15.5
Oprawa:
Twarda
Dodatkowe informacje:
Wydanie ilustrowane

David L. Olson is the James & H.K. Stuart Professor and Chancellor’s Professor at the University of Nebraska. With over 200 refereed journal articles, his research focuses on multiple objective decision-making, information technology, and supply chain risk management. Teaching in management information systems, management science, and operations management, he has authored over 40 books, including titles on decision aids, information systems project management, and supply chain management. He is a Fellow of the Decision Sciences Institute.

Desheng Wu is a Distinguished Professor at the University of Chinese Academy of Sciences and a Professor at Stockholm University. He has published over 150 papers in journals such as Production and Operations Management, Decision Sciences, and Risk Analysis. With research interests in mathematical modeling, game theory, and large-scale optimization, he is a member of prestigious academic institutions including Academia Europaea and the European Academy of Sciences and Arts. Prof. Wu has received several notable awards and serves as an editor for various journals, including Risk Analysis and IEEE Transactions on Systems, Man, and Cybernetics.

 

This textbook, now in its fourth edition, serves as a comprehensive guide to learning various aspects of risk, encompassing supply chain management, artificial intelligence, and sustainability. It demonstrates a wide range of operations research models that have been successfully applied to enterprise supply chain risk management. Each chapter of the book can function as a standalone module focusing on a specific topic, offering dedicated examples, definitions, and discussion notes.

The publication of this book comes at a crucial time when the world is facing increasing challenges from various forms of risk. Events such as Covid-19, the energy crisis, wars, and terrorism in the 21st century have all disrupted supply chains, thus highlighting the critical importance of enterprise risk management. Additional risks, such as financial and technological bubbles, along with concerns surrounding rampant artificial intelligence, contribute to a climate that demands enhanced risk management within organizations.







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