Background

Deciding is the process of choosing a course of action. It is a rational activity to diagnose a problem, generate alternative solutions, evaluate and choose solutions. In scientific management or industrial engineering, problem solving is applied systematically, using hard techniques such as operations research, decision theory, statistical analysis, decision models such as equilibrium point, preference matrix, decision trees, among others (^{Krajewski et al., 2013}). Rational decisions can be iterative, concurrent, or permanent (^{Acevedo & Linares, 2013}; ^{Acevedo, 2012}). They are also classified into programmed and non-programmed decisions, and individual and group decisions (^{Huber, 2012}). Other academic knowledge domains build their proposals with descriptive, prescriptive and normative models (^{Rodriguez & Pinto, 2018}), all of them focused on the rational logic of the choice of alternatives. Simon’s behavioral economics approach defines rational decisions, bounded rationality and intuitive (^{Estrada, 2011}). ^{Kahneman (2003}) differentiates intuition and reasoning of choice in contexts of uncertainty, risk aversion and frame effect in rational choice. Likewise, Kahneman and Sverky define heuristics and cognitive biases in the context of the expected utility model (^{Yáber, 2020}). The empiricist current includes the managerial criterion whereby decisions must be of quality, by a capable manager and with decisions that affect the entire organization, with multiple goals and group decision techniques (^{Witzel, 2013}).

The decisional process encompasses variables that go beyond the rationality of the scientific approach since human action, emotions, attitudes, and propensities entail different perceptions of the problems (^{Whetten & Cameron, 2016}). These variables add diversity to the definition of the decisional process and divergent solution proposals. Likewise, according to Simon, they may collide with a rationally optimal or satisfactory solution (^{Estrada, 2006}). Two major elements are considered to identify decisional importance: 1) the dimension of the scientific management (industrial engineer) paradigm, which includes the productivity of the system in operation and the change and improvement of the system in disequilibrium, and 2) the dimension of the decisional process, which includes the rational and systematic decision variables and the variables that extend beyond rationality. The proper selection and balancing of the decisional variables must lead to the correct, feasible and desirable choice for the organization and the people (^{Acevedo, 2011}). As roles of greater responsibility at managerial levels are assumed, the industrial engineer faces new scenarios with problems of increasing complexity that lead to the use of criteria such as emotions, beliefs, creativity, heuristics, empirical inquiry and mental experimentation, as well as the use of new tools, so that the ways of deciding have to be renewed, expanded and adapted to solve problems (^{Rocha & Silva, 2021}; ^{Badham, 2022}; ^{Savage et al., 2018}).

The approach of the present study refers to the fact that the professional development of the industrial engineer is constantly enriched over time, so that systematic techniques and structured rational decisions to solve problems are insufficient and ineffective to face an organizational reality of increasing complexity. Thus, when making decisions, the perspective of the context must be broadened, considering criteria that go beyond the initial rationality learned in the academy.

Objective and Research Problem

The approach of this study refers to the fact that the professional development of the industrial engineer is constantly enriched over time, so that systematic techniques and structured rational decisions to solve problems are insufficient and ineffective to face an organizational reality of increasing complexity. Thus, when making decisions, the perspective of the context must be broadened, considering criteria that go beyond the initial rationality learned in academia.

The research question of the study is: How does the problem setting or context where the problem is located influence the choice of rational or meta-rational decision criteria for the solution of the problem?

Investigation Hypothesis

The general hypothesis is: “The problem scenario influences the definition of decision criteria for solving management problems in complex organizations and human groups.”

Contribution and Impact

The direct contribution of the research is its contribution to the study of decision making in the Peruvian context, where there are no studies on profiles or decision theory that identify the forms and criteria of decision making in the different local environments. An additional contribution is the formulation of a conceptual model of decisions, which describes the rational and meta-rational elements to define a decision profile relative to the context and diverse scenarios where the industrial engineer performs in his decision-making or managerial role in complex organizations, human groups and other socio-technical business systems.

The indirect contribution is the identification of non-systematic elements that affect decision making and its effects.

The conceptual model of rational and meta-rational decisions

2. Structured Situation

To understand the common way of deciding for people, human groups and human organizations, which are not imbued with traditional academic and scientific knowledge, the complexity of the real world must be perceived and understood under a holistic weltanschauung (^{Heidegger, 2001}), called “systemic approach to problem scenarios” (^{Acevedo et al., 2017}). Within the continuum of scientific-narrative knowledge (^{Lyotard, 1991}), and depending of the level of problem complexity, the problem scenario is located which, conceptually, grants common systemic characteristics to the problems and allows the development of how to present the problem, which forms a framework that delimits the boundaries in which the problem is to be solved and the various tools, methods and techniques accepted to understand it.

Figure 1 shows the way in which the complexity of the problem is perceived and understood, and how the approach, analysis, alternatives and resolution action are described and determined.

Source: Prepared by the authors.

Figure 1 Continuum of narrative-scientific knowledge and the complexity of problems. 

4. Conceptual Model of Rational and Meta-Rational Decisions

Decisions can be rational or emotional, they are classified according to the following scheme:

Rational decision:

Rational per se (solving problems).

Post-rational (investigating problems), mainly embedded with the previous one.

Meta-rational decision: emotional, impulsive, paused and memetic (solving problems).

There are three types of decisions: rational, post-rational and meta-rational (Figure 2)

Source: Prepared by the authors.

Figure 2 Map of the conceptual model of decisions to investigate and solve problems in organizations and human groups. 

Rational Decisions. Decision refers to choosing a course of action or solving problems (^{Huber, 2012}). Rational decisions seek the best choice to meet a planned and defined criterion as a goal. Rational decisions to solve problems can be:

• Rational per se, when they are based on perfect or complete information where the analysis allows for optimal or maximizing choices.

• Bounded rationality, when information is partial and insufficient and appropriate choices can be approximate, satisfactory, or negotiated.

• Empirical intuitive, when the information is null or contradictory, so that the choice derives from a rationality not supported by proven or verifiable information. It is based on a posteriori judgments or experience in the field.

These decisions comprise tools from specialized domains such as industrial engineering (^{Heizer & Render, 2009}), operations research, decision theory, behavioral economics, organizational psychology, systems, and other empirical models (^{Hammond et al., 1999}).

Post-rational decisions. These overlap with rational decisions when faced with situations where knowledge is incomplete or insufficient. The decision contemplates inquiry through research and empirical experimentation. According to their purpose, decisions can be:

• Heuristic decisions, when empirical criteria are used to facilitate and accelerate the choice for resolution, action, or innovation. Heuristics are academic when they employ empirical rules such as analogy, managerial judgment, design thinking, strategic thinking, creative thinking, algorithms, and metaheuristics (^{Krogerus & Tschäppeler, 2017}; ^{Flogler & LeBlanc, 2009}; ^{Farson, 1997}) or pseudoscience. Heuristics is vulgar or popular when it employs timing, serendipity, procrastination, chindogu, fortune, luck, coin flipping, chance, improvisation, fortune telling, tarot, astrology, lying, cheating. It is confusing and mimics irrational decision criteria when it refers to chance, luck, astrology, pseudoscience, among others (^{Sterman, 2017}).

• Epistemological decisions, refers to the inquiry of new problems where theoretical or applied, laboratory or field, theoretical or experimental research hypotheses are raised. It considers various epistemological approaches, such as critical rationalism, positivism, phenomenology-hermeneutics, systems approach, dialectical materialism (^{Manrique & De Castro, 2019}), among other schools of scientific method. It includes the so-called “epistemological anarchism” before the profusion of the methodological proposals from authors.

• Decisions by a priori judgments, are based on pre-established principles and knowledge. They could be a) philosophical-religious, when they emphasize scholastic visions and criteria for choices that seek to govern human nature, the human condition or the supreme end; b) ideological-political, when they are based on dogmas that prioritize the interests of groups, whether political, economic, social or religious; c) domains of specialized knowledge, when they emphasize the methods, axioms and dogmas of specialized academic fields, without considering other options for reasoning (^{Hammond et al. 2002}, ¹⁹⁹⁹; ^{Bento et al., 2022}).

Meta-rational Decisions. The ideal rational decision paradigm considers reason free from emotion for the choice between options; on the contrary, the emotional intelligence paradigm contemplates the harmonization between mind and heart (^{Goleman, 2017}; ^{Raza-Ullah et al., 2022}), that is, integrating visible reason and invisible emotion in the decisions that influence groups and organizations. It is claimed that emotional or aesthetic aspects redefine the meaning of information (^{Saifer & Dacin, 2022}).

Decisions are meta-rational when they comprise a high portion of emotionality. There are three types: emotional impulse, controlled emotionality, tribal memetics.

• Decisions by emotional impulse or individual self. Decisions of the individual self-correspond to first impulse emotional decision making, where emotions drive action without prior reflection. Pure emotional decisions focus on speed and are directed directly to action. The emotional mind assimilates things as a whole by making intuitive judgments that may be true or false; it is faster than the rational mind. The emphasis on action provides a sense of strong certainty derived from the simple and simplified way of seeing things (^{Goleman, 2017}), where accuracy is sacrificed for speed. They can be due to pure emotion and the human element.

• Decisions by controlled emotions or emotional self. When a controlled emotional decision is taken, conceptual paradigms are applied and they add rationality to emotions, so that the choice takes into account the consequences or effects of the decision, in addition to the pragmatism or utilitarianism prevailing in organizations. Emotional decisions are impulse decisions; rational decisions are delayed reaction decisions. The scheme of emotions, with the human condition and its purpose is shown in Table 1.

• Memetic decisions of the tribe or social self. The choice of the individual self and the emotional self is always affected by the circumstance and its evolution, which involve the decision maker. Decisions are socially constructed from social information transmission units or memes (equivalent to genes) (^{Fomin, 2019}; ^{Espinosa, 2016}). They are the decisions of the tribe or social self (^{Goleman, 2006}), atavisms and beliefs that shape the historical space-time or influence of the tribe (direct group context, family, gang, neighborhood, sect, fraternity, profession, nation) to guide and reorient the choice. Decisions can be by cultural factor, by direct group factor, and by history-memetic factor. They involve the transmission of atavistic paradigms and cosmovisions such as animism, paganism, polytheism, witchcraft, ghosts, prophecies, mythology.

Table 1 Meta-Rational Decisions, Purpose, and Emotions. 

Dimensions of Human Nature (Hobbes)		Emotion Families (Goleman)		Human Condition (Hobbes)	Influence on Decisions in Organizations	Emotions in Decisions in Human Groups and Organizations.
		Basics	The Family
Of the natural condition of men: equality	DOMINION Desire for power	Shame	Humiliation Contrition	Desire for power Vanity	Pride Humility	Leading and managing: personal aptitude, self-control, motivation, empathy, social skills. Negotiation: position, role, appreciation, affiliation, autonomy. Emotional learning: by operant behavior. Group work: loyalty, trust. Values-based management: - - A posteriori values (perseverance, achievement, success, competitiveness). - A priori values (respect, charity, honesty, truthfulness, honesty).
		Surprise	Astonishment Bewilderment	Curiosity Wisdom	Doubt Science
	DISCORD Dissension	Fear	Concern Phobia	Distrust Antagonism	Envy Empathy
		Annoyance	Abhorrence Disdain	Competition Desire for glory	Ambition Colaboration
Of the supreme goal: happiness	WILL Voluntary actions	Anger	Animosity Violence	Will Prudence	Decision Dignity
		Sadness	Pessimism Depression	Experience Laziness	Demotivation Hope
	PREDISPOSITIONS Inclinaciones	Pleasure	Amusement Gratification	Appetite Aversion	Delight, irrational Flow-Happiness
		Love	Trust Devotion	Loyalty Sympathy Good, fair	Passion, whimsy Fraternity-Ethic

Source: Prepared by the authors, adapted and based on studies by ^{Goleman (2018}) and ^{Hobbes (2004}).

5° The meta-rational decision process. The meta-rational decision comprises three blocks: the first is directed to action; the second, oriented to emotions; and the third, to integration with the social side. This process has to be embedded with rationality for complex decisions (see Figure 3).

• Subprocess of pure emotional decision. It is the first reaction, without thinking, which is called first impulse. The first impulse is a direct and immediate emotional reaction, the decision is instantaneous and emphasizes action; it is useful in dangerous and unexpected situations. The emotional impulse leads to unreasoned actions that often collide with what is socially accepted, ethical or legal. This first impulse leads to the question “Why did I act this way?”, which has no answer. Control of one's own impulses must be maintained. In this process, education or knowledge suspends the action until verifying that it is moving towards a beneficial objective (it is useful, it serves, it works, it is profitable).

• Subprocess of controlled emotional decision. It is the slow emotional decision employing emotional intelligence, reaction control and high associative logic. Emotional intelligence is a social competence. This second impulse is a moderate emotional reaction where more complex emotions are applied, subsequent to the emotional impulse (or parallel if it is controlled) and prior to rational reflective thinking. It represents the emotionally reflective, thoughtful, slow, and prudent meta-rational decision, with systematic criteria to choose the feelings and emotions to be highlighted. It is characterized by its high associative logic and use of emotional intelligence. It precedes the rational decision and is related to it since it facilitates the achievement of our own purpose, fits with personal interests and predispositions, does not collide with paradigms and avoids the emergence of cognitive dissonance.

• Subprocess of the meta-rational choice. In this step, a rational decision integrated with emotionality is attempted. The sequence of the rational process is: 1) Perceiving the problematic situation, 2) Understanding and giving meaning to the problem, 3) Defining the intentions of decision-makers, 4) Prioritizing the elements of the problematic situation, 5) Proposing solutions in the field of action, 6) Applying solution techniques to the problematic situation, 7) Verifying expected results and emerging failures, 8) Evaluating compliance.

Source: Prepared by the authors.

Figure 3 Meta-rational decision process in problem solving and rational adjustment. 

Research Findings

About Null and Alternate Hypotheses:

Null hypothesis H₀: “Problem scenarios have no influence on the definition of decision criteria for solving management problems in complex organizations and human groups”.

Alternate hypothesis H₁: “Problem scenarios have influence on the definition of decision criteria for solving management problems in complex organizations and human groups”.

Hypothesis Testing

1º) Null hypothesis:

H₀: μ₁ = μ₂ = μ₃ = μ₄ = μ₅ = μ_i

All μ_i are equal; where i = 1, 2, ..k , k= 5

or: every mean of the preferences are equal

or: Alternate hypothesis:

H₁: Not all μ_i are equal

or: Ǝ i / μ_i ≠ μ

where:

μ_i = Mean of type of decision-maker j's decision in problem scenario i; where j = 1, 2, ..n, n=25

2º) Significance level and confidence level

Significance level α = 0.05

Confidence level 1 - α = 0.95

3º) F-test: Table 2 presents the decision descriptives according to the problem scenarios (academic in part a, complex narrative in part b). The table indicates the orientation towards rational decisions or meta-rational (emotional) decisions. Table 3 indicates the null hypothesis corroboration for part b, where the F-test is in the rejection region.

With high certainty (significance 0.00) the F test of hypothesis corroboration rejects the null hypothesis for both studies.

4º) Figure 4 shows the F-test for one-factor analysis of variance (ANOVA), which graphically shows the corroboration of hypotheses in both studies.

Source: Prepared by the authors.

Figure 4 Hypothesis testing - rational and meta-rational scenarios and decisions. 

Analysis of Results

For a significance level of 0.05, using the SPSS, the F is within the rejection region, with respect to the theoretical F (2.70 < 98.184). Therefore, it is not possible to accept the null hypothesis that states that, in complex problem scenarios, meta-rational elements do not influence problem-solving decisions.

Alternatively, the alternate hypothesis, which states that, in complex problem scenarios, meta-rational elements significantly influence problem-solving decisions, is corroborated.

- The null hypothesis is rejected at a significance level of 0.05.

- The alternate hypothesis is accepted at a significance level of 0.05.

Empirical contribution of the research

Individualized decisions are synthesized in the decision profile in Figure 6. When the scenario is perceived as stable and controlled, the problems are defined as structured with a rational response (academic problem); the appropriate method of analysis must be applied in the solution. When the scenario is complex, evolutionary, or global, decisions are meta-rational and with greater weight of emotions.

Source: Prepared by the authors.

Figure 6 Decision profile according to the problem scenario. 

Figure 7 shows that decision preference O₁ is equivalent to academia, where problems and solutions are defined and controlled (tamed problems), while O₂ is equivalent to the situation that presents problems in a natural state (wild problems), with the complexity of reality, where problems are presented in a chaotic and convoluted manner.

Source: Prepared by the author.

Figure 7 Pareto of decisions according to the problem scenario. 

In academic scenarios, rational decisions with systematic tools and techniques that lead to predictable and controlled results prevail. On the contrary, in narrative and global scenarios, decisions with emotional or other meta-rational criteria prevail. In the former, elements of rationality such as profitability, productivity, among others, constitute 66% of the elements of choice. On the other hand, in the second scenario, meta-rational elements, such as emotions and beliefs, prevail and constitute 71% of the choice elements (see Figure 8).

Figure 8 Composition of decisions in tamed problems and in wild problems. 

Theoretical contribution of the research

The theoretical contribution is found in the understanding that decisions, as well as problematic situations, form a puzzle with different parts that complement each other, where each domain of knowledge emphasizes a position, considering a rational-emotional axis and a unidisciplinary-transdisciplinary axis. It could be of use for future research in the field of management and decisions in human groups and organizations.

Social contribution of the research

The social contribution of the research lies in the integral perception of the decision-making puzzle, to which is added the relational logic of emotions and the tribal logic of the cultures of the various social groups in decision-making. The Peruvian environment, where there are marked differences between the modernity of the capital and the backwardness of the provinces, favors the study of greater depth to understand the modes of decision making in the various regions of the country.