The main principles of decision-making applied in business practice by advance analytics are summarized in this book . The book is the compilation of chapters written by authors who are experts in the topic covered. Main disciplines, such as management, engineering/technology, economic, etc., are considered as interface with decision-making, being complementary to others, e.g., administrative, finance, risk analysis, marketing, etc.
Decision-making could be defined as the choosing process from several options. It can be done by simple or advanced analytics, by exact or not procedures, by the opinion of any, etc. . The frequency at which the decision-making is done is also variable, from 1 to any. If the effect of decision is considered in a period, then decision-making is classified as operational (short period: daily, weekly, or monthly), strategic (long period: generally 1 year), and politic (very long period: usually more than 1 year).
Decision-making is gaining more importance because the new market scenario is being more competitive [3, 4, 5, 6]. This leads the researchers to focus on this topic, together with new technologies and advanced analytics, generating new software and tools based on the Internet of Things [7, 8].
Triantaphyllou analyzed the best decision-making method according to the best decision-making method .
The measurement of the efficiency for decision-making units was done via linear and nonlinear programming methods . The authors also took into account the economic and engineering relationship for decision-making.
Hwang and Masud  and White  showed a complete review of decision-making methods. New algorithms are appearing, for example, [12, 13, 14], where more robust and complex problems are being solved by employing artificial intelligence [15, 16, 17] and the most important ones are presented in this book.
The main theories are studied and presented in this book in different case studies. The main results are analyzed and discussed, suggesting new future works to continue working on that. Case studies are going from simple to complex cases, including big data, from static to dynamic problems, and also from offline to online cases, including the Internet of Things. Models, methods, and algorithms based on dynamic analysis, mathematical optimization, and computational techniques are designed and implemented to carry out the data analysis of decision-making, also considering the constraints.
The book has been written to be used by students and professionals of multiple disciplines, e.g., industrial organization, applied microeconomics, business administration, among others, and, of course, decision science applied to simple problems to complex and large problems and for different case studies. The book is also written for academics and researchers on different disciplines.
Marugan AP, Marquez FPG. Decision-Making Management: A Tutorial and Applications. Cambridge, MA: Academic Press; 2017
Marugán AP, Márquez FPG. Decision making approach for optimal business investments. In: Advanced Business Analytics. Berlin, Germany: Springer; 2015. pp. 1-20
Pliego Marugán A, García Márquez FP, Lev B. Optimal decision-making via binary decision diagrams for investments under a risky environment. International Journal of Production Research. 2017; 55:5271-5286
Hwang C-L, Masud ASM. Multiple Objective Decision Making—Methods and Applications: A State-of-the-Art Survey. Vol. 164. Berlin, Germany: Springer Science & Business Media; 2012
Pérez JMP, Asensio ES, Márquez FPG. Economic viability analytics for wind energy maintenance management. In: Advanced Business Analytics. Berlin, Germany: Springer; 2015. pp. 39-54
Márquez FPG, Lev B. Advanced Business Analytics. Berlin, Germany: Springer; 2015
Bose R. Advanced analytics: Opportunities and challenges. Industrial Management & Data Systems. 2009; 109:155-172
Barton D, Court D. Making advanced analytics work for you. Harvard Business Review. 2012; 90:78-83
Triantaphyllou E. Multi-criteria decision making methods. In: Multi-Criteria Decision Making Methods: A Comparative Study. Berlin, Germany: Springer; 2000. pp. 5-21
Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. European Journal of Operational Research. 1978; 2:429-444
White D. Multiple attribute decision making—A state-of-the-art survey. Journal of the Operational Research Society. 1982; 33:289-289
Marugán AP, Márquez FPG. Improving the Efficiency on Decision Making Process via BDD. In: Proceedings of the Ninth International Conference on Management Science and Engineering Management. 2015. pp. 1395-1405
Pliego Marugán A, García Márquez FP, Lorente J. Decision making process via binary decision diagram. International Journal of Management Science and Engineering Management. 2015; 10:3-8
Marugán AP, Márquez FPG, Lavirgen JL. Decision Making via Binary Decision Diagrams: A Real Case Study. In: Proceedings of the Eighth International Conference on Management Science and Engineering Management. Germany: Springer; 2014. pp. 215-222
Chen S-J, Hwang C-L. Fuzzy multiple attribute decision making methods. In: Fuzzy Multiple Attribute Decision Making. Berlin, Germany: Springer; 1992. pp. 289-486
Jiménez AA, Muñoz CQG, Marquez FPG, Zhang L. Artificial intelligence for concentrated solar plant maintenance management. In: Proceedings of the Tenth International Conference on Management Science and Engineering Management. Germany: Springer; 2017. pp. 125-134
Marquez FPG, Pliego A, Lorente J, Trapero JR. A new ranking method approach for decision making in maintenance management. In: Proceedings of the Seventh International Conference on Management Science and Engineering Management Lecture Notes in Electrical Engineering. Germany: Springer; 2013. pp. 27-38