The objective of the book as declared on its back cover: “The book offers guidance in identifying and applying accurate methods for designing a strategy as well as implementing these strategies in a real world.” The book’s seven chapters cover the process of decision making (under uncertainties), conceptual and empirical inconclusiveness, decision making using multiple criteria, the human decision-making process, the science of optimal decision making, improving employee emotional intelligence, slow and fast thinking for problems, and the influence of certainty and affectivity. Thus, the volume covers a wide portion of the decision-making landscape without being a comprehensive treasure. I am not convinced the volume meets its declared objective.

Each chapter is by the editor, Mohanty, and other coauthors. Chapters 1 through 6 provide a basic analysis of the literature available in the area of focus, while chapter 7 describes an experiment conducted by Mohanty et al. followed by an analysis of the results. The book should be quite handy to researchers with an interest in human decision making.

Chapter 1, “Decision Making Under Uncertainty and Problem Solving,” identifies three paths for dealing with uncertainty that are recognized in literature: (1) knowledge seeking (attempts to isolate new pieces of information and/or knowledge while ignoring uncompensated knowledge); (2) certainty maximization (seeks to minimize uncertainty through definitive models and ignoring the rest); and (3) probability theory (attempts to predict the consequences of uncertainty). The chapter also underlines how certain certainty assumptions may ignore uncertainties in the context definitions and assumptions made at deeper levels. It has more than 70 references.

Chapter 2, “Are Positive People More Flexible in Cognitive Processing? Addressing the Conceptual and Empirical Inconclusiveness,” deals with the flexibility in decision making and the attitudes of decision makers. It is a literature survey and has 34 references. The conclusion: decision makers with positive attitudes appear to be more flexible; they tend to recognize the global features of problems quicker.

Chapter 3, “A Review of Decision Making Using Multiple Criteria,” is a literature review with 36 references. It briefly discusses multiple objective decision making (MODM), multiple-criteria decision making (MCDM), the weighted sum model (WSM), the TOPSIS method, the analytic hierarchy process (AHP) method, the fuzzy AHP method , ELECTRE, PROMETHEE, and multiple attribute decision making (MADM). The authors show a preference for MADM due to its ability to handle conflicting criteria.

Chapter 4, with 90-plus references, is “Mid Brain Connective for Human Information Processing: A New Strategy for the Science of Optimal Decision Making.” It surveys literature widely, including Vedic Sanskrit literature, for the effects of spirituality on decision making. The authors assert: in the modern era, the society has focused on economies using logical, linear, and digital methods akin to computer systems while desiring outcomes to be human development, peace, and happiness. The desired outcomes can be achieved only by a decision process that takes care of “entities within,” such as emotions and spiritual wisdom, that is, by evolving mid-brain activities.

Chapter 5, “Need of Improving the Emotional Intelligence of Employees in an Organization for Better Outcome,” has ten references. The chapter lists elements that constitute emotional intelligence, such as self-awareness, authenticity, and emotional reasoning. It then highlights how control of employee emotions is required, which can be achieved through person-centric, open, and pleasant communications, and command structures and methods that uplift a person’s disposition. Improvements can be seen in the quality of field data, absolution, communication, and self-management. The authors suggest three steps for improved emotional intelligence: (1) perceive and name feelings, (2) seek criticism, and (3) improve understanding of writings that show other points of view.

Chapter 6, “Slow and Fast Thinking for Problem Solving Under Uncertainty,” has 11 references. It stipulates that “thinking” is the process of “finding all solution paths/alternatives” in the problem space; “slow thinking” attempts to “find features in details” in the problem space; and “fast thinking” is the attempt to “use known situation/solutions.” The authors state that the optimal problem solution can be obtained by combining fast and slow approaches and maybe jumping between them in an attempt to find a solution to the problem.

Chapter 7, “Decision Making in Positive and Negative Prospects: Influence of Certainty and Affectivity,” describes an experiment: Mohanty et al., at the Indian Institute of Technology Kharagpur (IIT Kharagpur), gave unannounced quizzes emulating positive and negative decision spaces. The chapter starts with a discussion of the experimental procedure set and statistical analysis methods, with an objective to verify:

(1) “Most individuals will prefer risk-aversion in positive prospects (certainty, isolation, and reflection effects) and risk seeking in negative prospects”;

(2) Certainty will increase with the amount of processing required with choices;

(3) “Higher positive affectivity will promote risk aversion and higher negative affectivity will promote risk seeking in decision making”; and

(4) “More negative (positive) affectivity and certainty in the choice will increase (decrease) more information processing to determine the choice.”

The obtained data is tabulated and analyzed, and the study is broadly inconclusive as results show that certainty and negativity affect half of the participants in half of the hypothetical situations.