Strategic System Assurance and Business Analytics -

Strategic System Assurance and Business Analytics (eBook)

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2020 | 1st ed. 2020
XIX, 602 Seiten
Springer Singapore (Verlag)
978-981-15-3647-2 (ISBN)
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This book systematically examines and quantifies industrial problems by assessing the complexity and safety of large systems. It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues. Through contributions from researchers working in the area of performance, management, and business analytics, it explores the development of new methods and approaches to improve business by gaining knowledge from bulk data. With system performance analytics, companies are now able to drive performance and provide actionable insights for each level and for every role using key indicators, generate mobile-enabled scorecards, time series-based analysis using charts, and dashboards.


In the current dynamic environment, a viable tool known as multi-criteria decision analysis (MCDA) is increasingly being adopted to deal with complex business decisions. MCDA is an important decision support tool for analyzing goals and providing optimal solutions and alternatives. It comprises several distinct techniques, which are implemented by specialized decision-making packages. This book addresses a number of important MCDA methods, such as DEMATEL, TOPSIS, AHP, MAUT, and Intuitionistic Fuzzy MCDM, which make it possible to derive maximum utility in the area of analytics. As such, it is a valuable resource for researchers and academicians, as well as practitioners and business experts.



P.K. Kapur is Director of Amity Centre for Interdisciplinary Research, Amity University, Noida, and former Dean of the Faculty of Mathematical Sciences, University of Delhi, India. He has been the President of the SREQOM (Regd.) since 2000 and is former President of ORSI. He is the Editor-in-Chief of the International Journal of System Assurance Engineering and Management, Springer (India). He has published over 350 papers in respected international journals and proceedings and has co-authored two books on software reliability with OR applications.

Ompal Singh is an Associate Professor at the Department of Operational Research, University of Delhi, India. He obtained his Ph.D. in Software Reliability from the University of Delhi in 2004, and has more than 15 years of experience in teaching, research, and consultation in the area of data handling, data analysis, and modeling in the various fields of operational research. He has published more than 100 research papers in respected international journals and proceedings.

Sunil Kumar Khatri is Director, Amity University, Tashkent Campus, Tashkent, Uzbekistan and is a Fellow of Institution of Electronics and Telecommunication Engineers (IETE). He has edited seven books and seven special issues of international journals, as well as more than 100 papers in respected international and national journals and proceedings. He holds various patents, and has been involved in a number of international training projects to his credit. He is an Editor of International Journal of Systems Assurance Engineering and Management, Springer, and is on the editorial boards of several journals in the USA, Egypt, Hong Kong, Singapore and India.

Ajit K. Verma is a Professor (Technical Safety) of Engineering, Western Norway University of Applied Sciences, Haugesund, Norway. He was previously a Senior Professor at the Department of Electrical Engineering at IIT Bombay, India. He has published over 250 papers in various journals and conferences. He is a senior member of the IEEE and a life Fellow of the IETE and Editor-in-Chief of IJSAEM and the Journal of Life Cycle Reliability and Safety Engineering.


This book systematically examines and quantifies industrial problems by assessing the complexity and safety of large systems. It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues. Through contributions from researchers working in the area of performance, management, and business analytics, it explores the development of new methods and approaches to improve business by gaining knowledge from bulk data. With system performance analytics, companies are now able to drive performance and provide actionable insights for each level and for every role using key indicators, generate mobile-enabled scorecards, time series-based analysis using charts, and dashboards.In the current dynamic environment, a viable tool known as multi-criteria decision analysis (MCDA) is increasingly being adopted to deal with complex business decisions. MCDA is an important decision support tool for analyzing goals and providing optimal solutions and alternatives. It comprises several distinct techniques, which are implemented by specialized decision-making packages. This book addresses a number of important MCDA methods, such as DEMATEL, TOPSIS, AHP, MAUT, and Intuitionistic Fuzzy MCDM, which make it possible to derive maximum utility in the area of analytics. As such, it is a valuable resource for researchers and academicians, as well as practitioners and business experts.
Erscheint lt. Verlag 19.6.2020
Reihe/Serie Asset Analytics
Asset Analytics
Zusatzinfo XIX, 602 p. 235 illus., 189 illus. in color.
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Datenbanken
Mathematik / Informatik Informatik Theorie / Studium
Mathematik / Informatik Mathematik Finanz- / Wirtschaftsmathematik
Technik Maschinenbau
Wirtschaft Betriebswirtschaft / Management Logistik / Produktion
Wirtschaft Betriebswirtschaft / Management Planung / Organisation
Wirtschaft Betriebswirtschaft / Management Unternehmensführung / Management
Schlagworte Big Data Analytics • Management Analytics • Performance analytics • Quality Control, Reliability, Safety and Risk • Quality management • Reliability
ISBN-10 981-15-3647-3 / 9811536473
ISBN-13 978-981-15-3647-2 / 9789811536472
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