Rational Decision-Making Model

The rational decision-making model, pros and cons of the rational decision-making process, evaluation of my decision making.

The rational decision-making model provides a systematic approach to making decisions using logic and cognitive functions such as creativity and imagination (Morcol, 2006). The word “rational” means that the process applies logic and aims to get the most feasible solution to a problem. The method can be used by individuals and organizations to ensure that discipline and consistency are vital parts of their decision-making processes.

The rational decision-making model comprises several steps that follow each other in a coherent style. For instance, the first step involves the identification of a problem that needs to be addressed, while the last step involves the enumeration of actions that need to be taken in order to implement the decision made (Morcol, 2006). The process commences with the identification of a problem or an opportunity that needs to be addressed.

This is followed by information gathering regarding the issue. In the second step, it is imperative to identify the criteria for the process and the desired outcome in order to complete the remaining steps successfully. The third step involves the analysis of the situation using the information gathered. The fourth step involves the development of possible solutions, options, or alternatives (Ahlstrom & Bruton, 2009). This is a critical step and consumes a lot of time.

The fifth step involves the evaluation of these options and their effectiveness in satisfying the specific criteria chosen form the process. The strengths and weaknesses of each solution are considered against the background of the problem or opportunity being addressed.

Finally, the best option is chosen after conducting a thorough analysis of possible solutions and their future implications (Ahlstrom & Bruton, 2009). A comparison of solutions is conducted using several methods that include the decision grid, decision matrix, and the selection matrix. This method can be used to determine the most effective way of reducing employee turnover.

The rational decision-making process has several pros. First, it provides a structured approach that is easy to use (Morcol, 2006). Therefore, anybody can use it successfully to address any issue. Second, it ensures that a full range of factors is considered, thus reducing errors that lead to poor decisions. A thorough evaluation of information and other critical factors results in good decisions (Morcol, 2006).

Third, it creates discipline and ensures that logic reigns in finding solutions to various issues (Ahlstrom & Bruton, 2009). Fourth, it can be applied in both individual and group settings. The model has cons too. It functions under the assumption that a perfect solution to any problem exists. It seeks to find the best outcome or solution (Ahlstrom & Bruton, 2009). This search for perfection is a hindrance to speedy decision-making and could affect the effectiveness of the process by causing delays.

Moreover, the model presupposes that it is possible to consider all possible solutions and accurately determine their future implications (Ahlstrom & Bruton, 2009). However, the future is unpredictable, and this model could endorse solutions that fail to solve a specific problem effectively. The model requires an evaluation of a lot of information.

Therefore, it is time-consuming and tiresome. Finally, it is limited by the cognitive capabilities of the individuals involved in the process (Morcol, 2006). For instance, decisions are based on factors such as creativity and imagination.

After taking a quiz to evaluate my decision making, my total score was 56. The sub-scores were different in various areas of the process. The sub-scores were as follows: establishing a positive decision-making environment (11 out of 20), generating potential solutions (13 out of 15), evaluating alternatives (8 out of 15), deciding (9 out of 15), checking the decision (6 out of 10), and communicating an implementing (12 out of 15).

The score means that my decision-making process is satisfactory. I am knowledgeable with regard to the basics of decision making. However, I need to improve and become more practical by focusing on generating more solutions and assessing the risk associated with each alternative. There are several practical steps I can take to improve my decision making.

They include developing a habit of making decisions, learning different techniques of brainstorming and generating solutions, learning how to evaluate the risks, consequences, and feasibility of each solution, improving my creativity and imagination and developing ways of determining the rationale behind every decision made. I had low scores in certain parts of the decision-making process, namely evaluating alternatives, deciding, and checking the decision.

In order to improve my ability to evaluate alternatives, I need to gain more knowledge on how to evaluate the risk, consequences, and feasibility of a solution. This can be achieved by taking a short course on decision making. It is necessary to determine whether the solutions are pragmatic and feasible.

Before starting the decision-making process, I need to determine what the outcome is in order to improve the accuracy of the decision. This can be achieved by learning different ways of brainstorming and generating ideas. Finally, I need to learn how to check a decision to determine its effectiveness and validity. This can be accomplished by learning how to use different methods of comparing outcomes. Creativity and imagination can be improved by taking a creative writing course.

Ahlstrom, D., & Bruton, G. (2009). International Management: Strategy and Culture in  the Emerging World . New York, NY: Cengage Learning.

Morcol, G. (2006). Handbook of Decision Making . New York, NY: CRC Press.

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rational decision making essay

Rational Decision-Making Model: Meaning, Importance And Examples

What is the rational decision-making model? Rational decision-making is a method that organizations, businesses and individuals use to make the…

Rational Decision Making Model

What is the rational decision-making model? Rational decision-making is a method that organizations, businesses and individuals use to make the best decisions. Rational decision-making, one of many decision-making tools, helps users come up with the most suitable course of action. In this blog, we will look at the meaning of rational decision-making, the importance of rational decision-making and study some rational decision-making examples.

Rational decision-making is a process in which decision-makers go through a set of steps and processes and choose the best solution to a problem. These decisions are based on data analysis and logic, eliminating intuition and subjectivity.

Rational decision-making means that every variable factor, every piece of information about all the available options, has been taken into account. 

What Is The Rational Decision-Making Model Used For?

What is the rational decision-making process, non-rational decision making.

The most basic use of the rational decision-making model is to ensure a consistent method of making decisions. This could be used as a standardized decision-making tool across an organization or to ensure that all managers receive the same information to make decisions. The rational decision-making process can be used to maintain a structured, step-by-step approach for every decision.

What Is The Rational Decision-Making Process ?

How the rational decision-making model is implemented can be explained in seven steps:

(There is also an example to help you understand the importance of rational decision-making)

1. Understand and define the scope

Just stating that a problem exists isn’t enough. Solid, accurate data is required to understand and analyze the problem in depth. This lets you know how much attention it requires.

It’s vital to collect as much relevant and accurate data around the problem as possible.

Here’s a rational decision-making example:

Your social media posts aren’t translating to conversions. What could the problem be? Once the analytics reports come in, you realize there isn’t enough engagement. The issue isn’t that your posts are not reaching the right audience, it’s that they don’t engage them. This sets up the next step: figuring out why the problem exists. Why is user engagement low?

2. Research and get feedback

The next step in the rational decision-making process is to delve into the problem. Find out what is causing the problem and how it can be solved. You could start with a brainstorming session and find out what your team thinks.

Rational decision-making example continued:

The budget is good, there are enough views and likes on the posts. So, why is there a lack of engagement? Why aren’t users interacting with the post? Why aren’t they clicking on the CTA?

You might need new types of posts; perhaps the current posts aren’t trendy. Maybe the posts don’t evoke an emotional response from the audience. Or they don’t convey what the product can do for the audience.

Now that you know what the causes could be, you are a step closer. It’s time to collate the data.

The team comes together with their opinions and findings. After a few customer surveys, the major issues are identified as follows:

  • Potential consumers don’t know how the product will add value to their lives.
  • Potential customers don’t understand the posts’ objectives and aren’t clear on what the product is.

3. List your choices

There are bound to be a host of opinions and innumerable choices about how to address the issue. Consider all of them so that you don’t create more problems later.

This is where you start to use rational decision-making:

Now that the problem has been understood, it’s time to list your options.

You could create a post that showcases what the product does.

You could have an informative GIF that shows that product in action.

You could create additional whitepapers to showcase how the product adds value and thus is beneficial for the customer to buy.

The analytics show that traffic isn’t the issue, so you don’t have to focus on garnering more traffic. Your focus has to be on conversions.

Your color schemes and CTA could be a little more impactful.

Maybe video clips are the way to go?

4. Analyze your options carefully

Now that you have all the options in front of you, cross out the ones that don’t add value or don’t solve the problem. Understand how each of the potential solutions could turn out and what other effects they could have.

Point 6 is about having a back up plan. Once you’ve chosen the plan that is likely to serve you the best, choose the second best option as well. You could use that as your back up, in case things don’t go according to plan.

While it’s great to get a quick solution to a real problem, the solution should be permanent or at least solve the majority of the issue.

The example of the rational decision-making process continued:

This is where you set about deciding the benefits of each of your choices mentioned above.

A video clip post would mean additional costs.

Redesigning the graphics may lead to more views and interaction but dilute your following.

A whitepaper is a good idea, but it doesn’t help with conversions. It’s ideal for customers to click on the CTA.

While GIFs are very popular, the image you choose has to convey the right information and be impactful. You may need to rework the branding for this to work.

While it would be great to have a post that showcases how the product works, it can’t be overly technical.

5. Understand the results you want

This is where the importance of rational decision-making comes into play. Understand what you expect from the solutions. There has to be a clear outcome because of the decision that is made. Knowing what you expect from your actions is important. It’s always a good idea to test the solution to see if it resolves the problem entirely.

Rational decision-making model example continued:

The best course of action might be to assign different teams for the different potential solutions.

One team could create a GIF, while the other works on the video clip and another on the ‘how to use’ post.

Once the teams have all made rough drafts, a productive critiquing session could be conducted. The teams can then look at each others’ solutions and point out the merits and drawbacks of each.

This way a general consensus can be reached and the best option or options can be selected. It is also advisable to use predictive social media tools. There are algorithms and equations that could help predict the success of a post to some degree.

6. Have a backup plan

While this may not always be necessary and can be a little cost-intensive, it may be worthwhile to have a backup plan if the solution doesn’t give you the intended results. This means that you should either have another strategy in place, created using the rational decision-making model .

Even though your plan has been made after careful thought, there is a chance that it either does not go as per plan or that an external factor interferes and throws your plan into chaos.

Try to have a back-up plan to make sure that your business isn’t impacted.

Now that you’ve decided to go with a combination of a GIF and an information-based post, go ahead and begin drafting your white paper as well.

7. Implement

Once the team has done all the work and created the solution, implement it. Implementing this plan means that everyone has to be on board. This means that everyone should be informed and be willing to contribute in executing the plan. The plan won’t work if everyone isn’t working toward the same goal.

As logic and data have been used to reach the decision, it’s likely going to be the most effective one.

Non -Rational Decision-Making

Non-rational decision-making is quite simply the opposite of rational decision-making . Non-rational decision-making is generally used when there isn’t enough information available or when there isn’t enough time to carry out the research and analysis required to employ rational decision-making methods.

Non-rational decision-making can be used when the person or team making the decisions has experienced that issue before or their collective experience allows them to predict what the outcome of their decision would be.

To sum it up, rational decision making can be the difference between a high performance culture driven by results and an unorganized setting. If you would like to drive decisions that guarantee results, you have to employ strategies that kindle organizational objectives based on real data. Let’s sum up the steps explained in this post about the importance of rational decision-making.

  • Understand and define the scope
  • Research and get feedback
  • List your choices
  • Analyze your options carefully
  • Understand the results you want

Now that you have some idea of what the rational decision-making process is, you may be curious to find out how to make better decisions for your business. To understand more about the importance of rational decision-making , take a look at Harappa’s Making Decisions course. It delves deep into how the best decisions can be reached. The course is for you if you’re looking to get into business and learn how to use rational decision-making.

Explore Harappa Diaries to learn more about topics such as How To Define Problem , Steps involved in Ethical Decision Making , Importance Of Decision Making and How To Overcome Indecisiveness to classify problems and solve them efficiently.


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Rational Decision Making Essay

Type of paper: Essay

Topic: Management , Finance , Thinking , Training , Decision Making , London , Theater , Decision

Published: 11/22/2019


What is Rational Decision Making


Rational decision making is defined as a systematic approach to long term decision making. As the word rational suggests, the approach brings logic and order to decision making. Rational decision making involves six main steps to achieve the desired solution. The first step is identifying a problem or opportunity. This has to do with verifying, defining and detailing the exact problem. Everyone involved in the decision should share the same definition of the problem and only then will it be possible to propose alternative solutions. The second step in rational decision making is to identify the decision criteria that will provide critical direction when seeking solutions to the problem. After the problem has been defined, the decision maker needs to identify an objective assessment criterion that is appropriate as far as the problem is concerned. This involves identify the most relevant approach in making the decision by bringing the decision makers points of view to an agreement. The third step is to weigh the previously defined two criteria so as to give the correct priority in the decision. The person making the decisions rates the items listed in step 2 to identify those that need to be given the most attention. Fourthly, possible alternatives which can serve as a solution to the problem are developed. Possible approaches that can assist in dealing with the problem are then derived by the decision makers. At this stage the alternatives are only listed and are not appraised. Then, the alternatives are rated based on each criterion. Each step should undergo critical analysis and evaluation. The merits and demerits of each preference can only become apparent when viewed in relation to the ones that are used the previous steps. The last step is to compute the optimal decision by evaluating the chosen alternatives against those that are set and choosing the best. After doing this, those who are affected by the decisions should also commit themselves to implementing the decision. Despite the systematic approach of the rational decision making model, most managers do not follow this model. In most cases, the extent through which a manager will engage in rational decision making is determined by their competency levels, grasp of key information and level of emotional underpinning. Thus, poor decision making can lead to wastage of organizational resources. (Berret-Koehler, 2002). As managers, the truth is that we satisfy rather than maximize all of the time (Vecchio, 2006). Satisfying being the construction of simplified models that only extract the essential features from problems. The result of satisfying decisions; is that only fairly good enough solutions are found. In practice, the business environment today is fast paced and does not give room for rational decisions to be made. Rational decision making models are seen to be bureaucratic and time consuming. The other reason why the model is not relied upon is because most managers are not experts so their cognitive and imaginative skills are limited to their scope of knowledge of the subject area in which they are making decisions The biggest barrier that exists in any company when it comes to implementing decisions is underlying policies, some decisions, however good, might be against policy or generally accepted principles. In all commercial companies, every decision has to be assessed from a financial angle, how the decision will impact revenue, cash flow and capital expenditure. Mangers are reluctant to commit to decision that may adversely affect these financial variables.

It is arguably evident that a rational decision making model can help us the decision makers make better decisions since it provides the decision maker with a range of alternatives to choose from.


Butler R. (1991). Designing Organizations: A Decision Making Perspective. London: Routledge. Cooke S., Slack N. (1991), Making Management Decisions, Second edition. London: Prentice

Hall. Cyert R., March J. G. (1963), A Behavioral Theory of the Firm, Prentice Hall, New Jersey. Drucker P.F. (1985), The Practice of Management. London: Pan Books.


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Book cover

Bending the Law of Unintended Consequences pp 63–77 Cite as

Rational Decision-Making

  • Richard M. Adler 2  
  • First Online: 11 February 2020

674 Accesses

People employ both intuitive and deliberate thinking when making critical decisions. Chapter 4 described how our intuitions give rise to cognitive biases that impair critical decision-making and open the door to the Law of Unintended Consequences (LUC). Robert K. Merton also identified constraints on deliberate thinking as equally important contributors to LUC. This chapter examines Herbert Simon’s pivotal cognitive scientific research on these bounds on human rationality. Section 5.1 provides a brief sketch of Simon’s accomplishments. Section 5.2 introduces Simon’s concept of bounded rationality and contrasts it with Tversky and Kahneman’s research on cognitive biases. Sections 5.3 through 5.5 unpack the key elements of Simon’s research: his critique of rational choice theory, his cognitive model for deliberate (System 2) thinking, and his cognitive model of how people reason in order to make critical decisions. Section 5.6 recaps the significance of Simon’s research.

  • Herbert Simon
  • Bounded rationality
  • Satisficing
  • Rational actor theory
  • System 2 thinking

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Augier and March [ 1 ], Feigenbaum [ 5 ], and Simon [ 19 ].

Feigenbaum [ 5 ].

Simon and his co-workers developed the first symbolic programming language, the precursor to John McCarthy’s List Processing Language (LISP) that dominated AI for many decades. He used it to create a program that automatically derived theorems for set theory and number theory Simon [ 19 ].

An example cryptarithmetic puzzle is DONALD + GERALD = ROBERT, where the goal is to assign the numbers 0–9 to the letters uniquely, decrypting the code into a correct arithmetic addition problem.

Simon [ 20 ].

Simon cites Tversky and Kahneman’s work in numerous places, such as Simon [ 20 , 21 ].

Simon [ 21 ] viewed intuitions (and cognitive biases) as a mental model, which people inevitably fall back on as a lens for viewing, understanding, and navigating reality due to our cognitive limits in coping with the world. As Heuer [ 7 ] notes, these intuitions are “not always well adapted to the requirements of the real world.”

Their research methodologies differed as well as their agendas. and Kahneman used questionnaires that elicited judgments and choices. These tests were tailored to highlight and isolate where and how our System 1 intuitions fail, in the sense of deviating from what a rational actor would judge or decide. In contrast, Simon investigated what people do to get things right. In addition to watching and interviewing subjects as they performed tasks in the lab, Simon developed computer-based simulations of problem solving and decision-making to emulate human cognitive structures and processes. In doing so, he helped conceive many of the key ideas and tools that catalyzed AI.

Although Kahneman oriented his research towards understanding System 1, he readily acknowledged the second horn of Merton’s LUC dilemma: “System 2 is not a paragon of rationality. Its abilities are limited as is the knowledge to which it has access. We do not always think straight when we reason, and its errors are not always due to intrusive and incorrect intuitions. Often we make mistakes because we (our System 2) does not know any better.” Kahneman [ 10 ].

Simon [ 18 ], pp. xxviii–xxx.

Simon [ 18 ] offers another rationale for economists’ attachment to rational agent theory: its premises of utility maximization and perfect knowledge “freed economists from any dependence on psychology”. In contrast, bounded rationality entails a deep study of cognitive and behavioral psychology. Bookstaber [ 2 ] makes a similar point: “Modern neoclassical economics sweeps humanity off the stage. It prefers to use mathematical models of a representative agent with stable preferences…”.

Kahneman [ 10 ] writes: “…The definition of rationality as coherence is impossibly restrictive; it demands adherence to rules of logic that a finite mind is not able to implement…our research only showed that Humans are not well described by the rational-agent model.” Klein’s studies of first responders (1998), Simon’s studies of chess grandmasters (2011) and other cognitive experiments show that people generally consider only one or at most a few decision options. Finally, economists criticize the procedural feasibility of defining, much less computing a coherent and defensible metric for utility of outcomes that suitably reflects non-financial benefits of decision options. Levin and Milgrom [ 13 ] and Gollier [ 6 ].

Simon [ 18 ], p. 67. See also Simon [ 18 ], p. 81 and Augier and March [ 1 ], p. 398 for similar formulations.

For example, options to increase growth include: acquiring other companies; licensing products or technologies (from or to others); developing new products or new marketing and sales strategies; and combinations thereof.

Simon [ 21 ].

In fact, Simon’s argument holds even for decisions where our System 1 intuitions don’t distort our judgments or choices: whether or not our judgments are correct, we cannot identify optimal choices.

Simon’s argument is epistemological, grounded in the finite nature of human knowledge and analytical capacity, whereas Tversky and Kahneman’s depends on behavioral dispositions (System 1) that can sometimes be overridden. Bookstaber [ 2 ] offers a more recent critique of rational choice theory in line with Simon’s bounded rationality, focusing on arguments relating to complexity such as computational intractability, emergent behaviors, and history dependence (i.e., ergodicity).

Simon’s use of the term “adaptation” here refers to situation-specific adjustments rather than to generalized evolution in the Darwinian sense. In contrast, System 1 intuitions probably did develop through natural selection. Dennett [ 4 ] and Lo [ 14 ].

The executive control function is an active area of cognitive research. Newell and Bröder [ 16 ].

Sudoku is a popular logic puzzle that consists of a 9 × 9 grid of cells, divided into 3 × 3 blocks, with a few cells filled in with numbers from 0 to 9. The objective is to fill in all of the remaining cells, subject to the constraint that no number can occur more than once in any row, column or block. Sudoku are solved by applying deductive logic to fill in cell values. For example, if 8 values are already filled in a row, you can deduce the ninth value by elimination. Another useful pattern is to identify two cells in a row or column that can only assume the same two values, which allows you to eliminate those values as candidates for other empty cells in that row or column.

Simon’s architecture for AI systems employed heuristic rules called productions. Here is an example expert production rule for automatically diagnosing infectious blood diseases. (Italic terms are properties, underlined terms are symbolic values. The IF clauses represent tests, the THEN clause an action, namely a diagnostic conclusion Buchanan and Shortliffe [ 3 ]:

IF: (1) The identity of the organism is not known with certainty and (2) The stain of the organism is gramneg and (3) The morphology of the organism is ro d, and (4) The aerobicity of the organism is aerobic

THEN: There is strongly suggestive evidence ( .e8 ) that the class of the organism is enterobacteriaceae.

Each such individual “chunk” can be quite complex and informationally dense. For example, chess grandmasters employ “condensed” representations of positions chess boards, as a single (complex encoded) pattern. Mnemonic methods such as “memory palaces” also extend this limit. Miller [ 15 ].

We commonly use external resources to cope with large-scale problems or decisions as solutions are developed, refined, and shared (e.g., blueprints, schematics, word processing documents). These tools allow people to swap chunks of information into and out of short-term memory while preserving an overall context. They scale our capacity for attention and long-term recall somewhat (i.e., by degree, but not by kind).

Neuroscience suggests that our processing of sensory stimuli involves significant parallel processing. However, such “multitasking” seems confined to automatic System 1 functions related to perception. Simon [ 20 ], Hogarth [ 8 ].

See, for example, Simon [ 20 ], Hogarth [ 8 ], Kahneman[ 10 ], and Krippendorff [ 12 ].

Simon [ 18 ] writes: “Administrative theory must be concerned with the limits of rationality and the manner in which organizations affect those limits. Organizations manage complex tasks by leveraging their hierarchical structures to direct work by individuals.

Even when we are forced to make guesses, the key to a reliable process for making judgments is to estimate the level of uncertainty quantitatively, for example using confidence intervals. Hubbard [ 9 ].

Simon models this process using “productions”—conditional (“if-then”) rules that associate particular conditions and changes in states of the world with actions that will bring such changes about. Conditions can be either goal-driven (e.g., “I am trying to achieve X”) or data-driven (e.g., “Y is already done” or “I know that Y”).

These include variations across current and potential product and service lines, marketing and sales programs and channels, and relevant competitors in all of your markets. Not all of these options are equally plausible, but for Simon, this is a search problem, not one of formulating alternatives.

For critical decisions, a goal such as increasing annual growth by 5% decomposes into sub-goals. The actions required to achieve a strategic goal generally must be decomposed similarly into specific, often interdependent sub-actions. For example, expanding production capacity often resolves into an enormous number of subordinate decisions about plants, equipment, and vendors, involving tradeoffs of quality, speed, cost, financing, taxes, resources, plans, and schedules (Sterman [ 22 ]). The resulting hierarchies allow fine-grained projections of how sub-actions close gaps between the current state and goal, they also spawn fine-grained assumptions about contingencies that expand the space of possible action-outcome projections that needs to be searched.

Situational complexity would be even worse were it not for the temporal discounting aspect of bounded rationality: “…the events and prospective events that enter into our value systems are all dated, and the importance we attach to them generally drops off sharply with the passage of time. By applying a heavy discount factor to events, attenuating them with their remoteness in time and space, we reduce our problems of choice to a size commensurate with our limited computing capabilities.” Simon [ 20 ].

Simon [ 20 ] argues that natural and artificial systems that are adaptive and have robust feedback mechanisms. For example, we cannot predict blizzards with great precision, but we can recover from them in cities by having snowplows ready.

Simon [ 20 ]. See also Zsambok and Klein [ 23 ] and Klein [ 11 ] on naturalistic decision-making.

Simon [ 20 ], p. 30. Simon also asserts that aspirations are incommensurable: “There is no simple mechanism for comparison between dimensions. This means that a large gain along one dimension may be needed to compensate for a small loss along another – hence the system’s net satisfactions are history-dependent, and it is difficult for people to balance compensatory offsets.”

Lo [ 14 ] notes that economists criticized Simon’s concept of satisficing because it is not clear when to stop analyzing options on this model, whereas optimality is an unambiguous, mathematically precise notion. He offers a defense of Simon in terms of heuristic rules derived by trial and error.

First responders studied by Klein [ 11 ] apparently consider one or two options at most, a draconian type of satisficing. These decisions are often urgent and life-threatening, but not critical in our sense.

Even powerful AI systems such as IBM’s Big Blue chess program don’t search this enormous space exhaustively; instead, they “prune” their searches for their next best move by restricting how deep into the game they look and with move scoring and heuristics. Human grandmasters employ very different pattern-based heuristics to compensate for their limited speed and focus of attention.

Simon [ 20 ], p. 29.

This is not to assert that human cognition is identical with or reducible to Simon’s cognitive simulations and AI rule-based reasoning systems (i.e., similar to some neuroscientists’ reductionist claims that consciousness is nothing more than neurological events and processes). Rather, the fact that his models and intelligent systems perform in ways that compare qualitatively to human problem solvers and decision-makers warrants a claim that human cognition likely involves similar kinds of structures and processes.

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Making Rational Decisions

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The economist Keynes once posited that when the quantitative calculation of expected utility can hardly help us make a decision, it is our “animal spirits” – or emotional states – that kick in and urge us into action (Keynes, 1936). This surmise proved prescient. From unbridled optimism that fuels an economic bubble, to stubbornness that undermines policies meant to raise social welfare, many suboptimal decision patterns that repeat themselves throughout history can be attributed to people’s “irrational” sides getting the better of them (Akerlof et al., 2009).

How We Make Suboptimal Decisions

A rational economic agent acting in accordance with expected utility theory is expected to evaluate a set of perfect information using mathematical logic: He calculates the utility he could gain from each option. Then, he chooses the option that maximises his utility within his budget constraints. However, real-life decisions are not informed purely by such mathematical calculations, but also by heuristics, biases and misconceptions which make us imperfect decision-makers.

Heuristics are mental shortcuts that people use to save time and mental effort in decision-making. Using these heuristics sometimes leads to statistically systematic errors in one’s information processing, also known as cognitive biases. For example, people tend to form an impression based on only a few salient examples that come to mind. This leads to the availability bias, whereby a minority of salient information disproportionately influences one’s judgement on the probability of something happening (Thaler, 2009). Resultant distortions in people’s probability judgements can lead them to make suboptimal decisions. For example, influenced by the preceding bull run in Internet stocks and the palpable optimism of fellow investors, investors in the 1990s came to display “irrational exuberance” in their expectations (Greenspan, 1996) and grossly overvalued Internet stocks. Energy consumers, on the other hand, tend to overconsume energy when they are not provided salient information like their level of energy usage (Thaler, 2009). People make suboptimal decisions when they over- or under-estimate an action’s utility: In one instance, important but non-salient information, like energy usage, is ignored; In another instance, salient but unrepresentative information, like overoptimistic expectations, is used to form the big picture.

Other cognitive biases can similarly distort one’s ability to make rational decisions. People tend to feel losses (shown as the red arrow in Figure 1) about twice as hard as gains (shown as the blue arrow) for the same change in wealth from a reference point (Tversky et. al, 2000). This leads them to exhibit loss aversion bias.

rational decision making essay

Loss aversion bias has been used to explain the endowment effect, where people tend to value goods they own higher than an identical good they do not own (Thaler, 2015). This is because they likely overvalue their loss in utility should they give up what they own. Consequences can be serious: If policymakers exhibit sufficient loss aversion, they may overprotect loss-making sectors, or develop anti-trade biases (Tovar, 2009).

Besides cognitive biases, misconceptions can also influence suboptimal decision making. As shown in Figure 2 below, World Bank development staff were generally shown to have believed that the poor were more suspicious of vaccines that they actually were. If such biases form assumptions in models which are used to predict an audience’s vaccine receptivity, this could lead to suboptimal allocation of resources for health outreach initiatives.

rational decision making essay

Separately, public health beneficiaries in developing countries can also hold misconceptions that impede policymakers’ efforts. In a South Asian nation, 35-50% of poor, lesser-educated women wrongly perceived the appropriate treatment for diarrhoea to be a reduction of water intake (World Bank, 2015). In fact, rehydration of the body is essential to treat diarrhoea. This caused the beneficiaries to undervalue the utility of the Oral Rehydration Therapy (ORT) programme, and thus under-consume it. Committing to misconceptions that are prevalent in a certain society can cause people to make suboptimal judgements.

Hitherto, we have discussed how biases, heuristics and misconceptions affect both governor and governed, both buyer and seller. If these factors result in suboptimal decision making, one forgoes the opportunity to choose an alternative option that would have yielded greater utility in the long run – avoiding over-buying inflated stocks, saving energy, bettering trade policies or receiving healthcare treatment.

rational decision making essay

The prevalence of sub-optimal decision-making implies that the application of traditional economic theory is limited in the real world. General Laws like the Law of Supply and Demand logically optimise resource allocation, but only if one makes rational choices. Influenced by a multitude of biases and heuristics and egged on by the lightning-speed pace of information spread, people inevitably make irrational choices. In the past, news of the Titanic’s sinking took hours to reach news outlets. Today, online tweets and posts make information, both real and fake, available instantaneously. Traders across the globe may be triggered to make knee-jerk, heuristic-influenced trading decisions. This increases the chance that market prices may overshoot their true value.

The prevalence of sub-optimal decision-making also sparks a re-examination of the soundness of traditional economic theory. Strict mathematical logic forms the bedrock of traditional economic tools’ axioms of rationality. It enables human behaviour to be modelled, albeit over-simplified. Expected Utility Functions, for example, model choice under risk, but the choices they model must, among other criteria, be well-defined and transitive (meaning if one prefers A to B and B to C, one prefers A to C) (Starmer, 2000). However, modern-day experiments show people defy these axioms: their preferences reverse when choices are differently framed, (Lichtenstein et. al, 1971) and as low as 8% of consumers’ choices follow transitive logic (Guadalupe et. al, 2020).

Behavioural economics research seemingly undermines the elegance and universality of application that traditional economics ventured to provide. However, it also presents opportunities for markets and policymakers to incorporate realities and mitigate inefficiencies.

Mitigating Inefficiencies

Expectation management

Expectations significantly drive buying and selling in the capital markets, just like how expectations of future food supply, rather than utility, have been shown to influence feeding behaviour in the animal kingdom (McNamara et. al, 2014). In addition to monetary policies such as the tweaking of interest rates, central banks including the US Federal Reserve engage in expectation management to smoothen out market recalibrations, thus reducing market volatility. When the Fed deems market expectations to have overvalued or undervalued a good, they intervene by releasing public statements hinting at interest rate changes. This cost-effective method has successfully readjusted market prices closer to their true value in numerous occasions (El-Erian, 2016).

Bias-checking mechanisms

Instituting bias-checking mechanisms can help policymakers weed out biases in the policy process. For example, the World Bank considered institutionalising “Red Teaming”, whereby an outsider group challenges a policymaking team’s assumptions, forcing policymakers to defend their views and become less prone to fall back on their prior biases (World Bank, 2015). 68% of IT companies that implemented a “Red Teaming” approach to tests of their IT systems achieved more effective tests (Exabeam, 2019).

Behavioural Insights

Behavioural insights, as shown below, can be used to optimise monetary policies such as basic needs subsidies. By leveraging on the powerful emotional attraction that a free product elicits, as well as the social norm it conveys that everyone should be using it, subsidising a good to zero cost, instead of low cost, can more than proportionately incentivise the take-up rate of a merit good, as shown in Figure 4 below. The subsidy dollar is thus maximised.

rational decision making essay

Behavioural insights on cognitive biases, like the Framing Effect, can help decision makers optimise consumer behaviour towards savings policies. Participation rates in US defined contribution savings plan jumped from 65% under an opt-in approach to a more ideal 98% under an automatic enrolment approach (Madrian et. al, 2001). The automatic enrolment approach mitigated workers’ “irrational” inertia in signing up for plans, strategically framing consumer decisions for optimal socio-economic outcomes.

To apply behavioural economics’ insights, policy approach must shift from the process of pure traditional modelling and then applying models: case-specific empirical research must first be done to identify “irrational” quirks undergirding societal behaviour. Additionally, plans must likely be reviewed, with a rigorous feedback loop in place, to evolve with changing consumer behaviour. In Figure 4, multiple data points had to be collected before policymakers could identify a behavioural trend.

Our “animal spirits” may lead us astray from rational choice. Yet, once we recognise them and harness them positively, the very same “animal spirits” can lead our herd to greener pastures, collectively.

Akerlof, G. A., & Shiller, R. J. (2009). Animal spirits: How human psychology drives the economy, and why it matters for global capitalism. Princeton, NJ: Princeton University Press.

El-Erian, M. (2016, May 23). The Fed, the markets and expectation management. The Financial Times. Retrieved 2020, from https://www.ft.com/content/fb033693-82ed-30bd a4ee-0f5851025440

Exabeam. (2019, August 15). More than One-third of Security Professionals’ Defensive Blue Teams Fail to Catch Offensive Red Teams, According to Exabeam Study [Press release]. Retrieved from https://www.exabeam.com/pr/more-than-one-third-of-security professionals-defensive-blue-teams-fail-to-catch-offensive-red-teams-according-to exabeam-study/

Greenspan, A. (1996). Remarks by Chairman Alan Greenspan At the Annual Dinner and Francis Boyer Lecture of The American Enterprise Institute for Public Policy Research, Washington, D.C. [Transcript]. Retrieved from https://www.federalreserve.gov/boarddocs/speeches/1996/19961205.htm

Guadalupe-Lanas, J., Cruz-Cárdenas, J., Artola-Jarrín, V., & Palacio-Fierro, A. (2020). Empirical evidence for intransitivity in consumer preferences. Heliyon, 6(3). doi:10.1016/j.heliyon.2020.e03459

Keynes, John M. (1936). The General Theory of Employment, Interest and Money. London. Macmillan. pp. 161-162.

Lichtenstein, S., & Slovic, P. (1971). Reversals of preference between bids and choices in gambling decisions. Journal of Experimental Psychology, 89(1), 46-55. doi:10.1037/h0031207

Madrian, B. C., & Shea, D. F. (2001). The Power of Suggestion: Inertia in 401(k) Participation and Savings Behavior. The Quarterly Journal of Economics, 116(4), 1149-1225. doi:10.1162/003355301753265543

McNamara, J. M., Trimmer, P. C., & Houston, A. I. (2014). Natural selection can favour ‘irrational’ behaviour. Biology Letters, 10(1), 20130935. doi:10.1098/rsbl.2013.0935

Starmer, C. (2000). Developments in Non-Expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk. Journal of Economic Literature, 38(2), 332-382. doi:10.1257/jel.38.2.332

Thaler, R. H., & Sunstein, C. R. (2009). Nudge: Improving decisions about health, wealth, and happiness: Rev. and exp. ed. New York: Penguin. pp. 24-26, 196

Thaler, R. H. (2015). Misbehaving: The Making of Behavioral Economics. New York, NY: W. W. Norton & Company. pp. 12-19

Tovar, P. (2009). The effects of loss aversion on trade policy: Theory and evidence. Journal of International Economics, 78(1), 154-167. doi:10.1016/j.jinteco.2009.01.012

Tversky, A., & Kahneman, D. (2000). Advances in Prospect Theory: Cumulative Representation of Uncertainty. Choices, Values, and Frames, 44-66. doi:10.1017/cbo9780511803475.004

World Bank. (2015). World Development Report 2015: Mind, Society, and Behavior. Washington, DC: World Bank. doi: 10.1596/978-1-4648-0342-0.

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Decision Making Essay


Decision-making is undoubtedly a fundamental practice the management of corporations. It denotes the progression of choosing and executing options, which are in tandem with an aspiration. It also connotes a string of actions commencing with a broad objective, trickling down to generating, appraising, choosing and executing favourable options.

Decisions made in organizations may have in-depth upshots on the firm and its employees. Such judgements in organizations are distinctive in terms of the risks involved, reservations managers have on them, their importance and contribution to the attainment of the firm’s broader objectives.

Some are tricky and requires insight thought, and may include setting of new policies, reorienting firm’s purposes and objectives, and large-scale ventures with a potential to impact on the economy of the firm. On the other hand, routine decisions also form part of a firm (Martin & Fellenz 2010, p. 227).

Rational model is a conventional representation of making decisions, and it leans on realistic financial hypothesis where the concerned members think of what constitutes best way of arriving at a judgement. Managements regularly use this model to make fiscally sensible decisions, which are capable of contributing to organization’s financial growth.

The model helps delineate how managers should make decisions. In addition, it presents guidelines, which enable decision maker to reach a favourable panacea for organizational development. The mould also negates the decision makers from applying their personal interests while searching for favourable outcomes.

It is highly applicable on decisions characterised by assurances and possibilities since suitable information is accessible. Furthermore, the model exposes opportunities to computations. For instance, usage of Information Technology to automate programmed decisions such as airline companies apply it is seat bookings, flight routes, and services pricing.

It is worth noting that decision-making techniques relying on quantitative information benefit processed in computers enable the model to gain usage. The model; however, has assumptions including decision makers’ ability to fulfil goals already agreed on and setbacks critically prepared and definite.

The decision makers also aim to attain certainty and collect relevant data, options and prospective outcomes computed. Procedure for evaluating options is clear and those able to optimize fiscal returns chosen. Finally, it assumes that the decision maker is logical and can use judgment to choose options, which will optimize economic gains.

The model describes the six stages of decision making as identifying a dilemma or opportunity. Daft and Marcic note that organizations face problems when they underperform and opportunities when administrators realize potentials of improving performance past existing echelon. This becomes the initial step in decision-making and warrants company’s inner and external forces surveillance (Daft & Marcic 2010, p. 188).

The managers utilize internal fiscal reports to forecast on possible threats and openings. Information gathering is another crucial stage that follows. This normally guarantees the manager an opportunity to analyze the possible causes of problems identified. This is tenable when decision makers, through creativity, develop questions reading the problem and opportunity state (Griffin, & Moorhead 2010, p. 198)

. The third stage is to develop alternatives, which seeks to generate potential optional answers to react to the requirements of the condition and give feedback on the basic reasons. It is easy to discover realistic options within the firm’s regulations since the decision-making is based on certainties and threats.

The identified options are deemed to ease the disparities regarding current state of affairs against conditions considered necessary.

Selection of desired options becomes the fourth step, which seeks to select among the options, the most realistic alternative that can best respond to the firms broad objectives. It is imperative to assert that the best attainable option must be requiring minimal resources to attain the needed outcomes. Furthermore, decision maker selects an option with the lowest quantity of uncertainties and threats.

This would aid in avoiding errors in the process. The fifth step is implementing the selected option, which requires corporation from the organization’s stakeholders. The managers, administrators and other staff work together to implement the option.

The ultimate step is to evaluate and present feedback on the status of implementation. Decision makers collect data on the effectiveness of the option in responding to the objectives. This final step is important since decision-making is an uninterrupted cycle. Therefore, the provision of feedback forms the benchmark for future decision-making.

There are factors, which influence decision-making course thus leading to a deviation from the rational form discussed above. Individuality personality and values is one of the leading parameter that affects the process. Different attributes of people manipulate decision-making choices. It is normal to discover that various individuals become nervous, worried, and agitated while in the crucial stages of decision-making.

Such attributes normally leads to fallacious interpretation in the process. It is crucial to declare that being nervous compromises reasoning; therefore, a manager may fail to arrive at the best decision. The attitudinal traits also interfere with decision in an organization. Some managers have fixed thoughts concerning what happens at the organization.

They believe that specific employees or figures must be present whenever there is a crucial matter to make decision. This implies that they have preset minds that such individuals are the best decision makers. This normally prompts the organization to believe such people contribute, regardless of the impacts they present on the organization.

Various managers possess different personalities. Some possess elevated self-esteem, which is motivational in during decision-making. Managers with strong personalities normally dominate the discussion during the process. This may flaw the process since their juniors may fear to contribute. This offers fewer options on the best way of solving organizational problems. This is incoherent with the rational model.

Preconceived fears about the consequences of the decisions would have on the organization normally send chills in the managers, and other concerned parties. This refers to emotional attributes of an individual. Griffin and Moorhead outline that perceived impacts, as well as post resolution effects may impair decision-making.

Furthermore, cognitive ideals such as outright biases have an effect on decision-making (Griffin, & Moorhead 2010, p. 202). Values that an individual embrace also influence decision making, and many counter the rational model. It is factual that managers espouse divergent principles and would attempt to maintain them in every situation. People would always propose what they like regardless of what impact it has on others.

Group relationship is another important parameter that influences decision making to a greater deal. The success of making decisions in groups is subject to the extent of understanding among members forming the team. Martin and Fellenz, posit that the group must have the right intensity of diversity thus enabling them to iron their differences.

Group decision making is highly applicable in organizations where it intricate issues, which can only be managed by a team with varied knowledge backgrounds (Martin & Fellenz 2010, p. 284). Group polarization connotes the way people react to situations of decision-making. People normally arrive at decision-making meetings with different views; however, they tone down to borrow the ideas of their fellows.

Therefore, a group that comprises of people with deep understanding of the dynamics that exists normally makes rational decision. Nonetheless, some groups might not arrive at a decision easily owing to the divergent notions members possess. This may be due to the everlasting differences that exist amongst members.

The level and kind of relationship within a group normally dictates how people make decisions. Superior relationship may prompt others to seek support from their fellows; however, this may flaw the process thus leading to irrationality. Group decision-making in organizations enable extra people to sustain influential contributions during the process than they would achieve individually.

Another issue is group thinking, which happens a when a decision making team is greatly involved in a discussion and the motivation to evaluate options is cancel out by their unanimity. This fails to support the rational model of decision-making since it thwarts other possible options that are crucial in the process.

Rational model upholds that divergent group may arrive at better conclusion than a group that has similar interest. Therefore, a divergent group, where people have good relation, but varied interest, would offer beat avenue of exploring many options.

The peak management makes tactical decisions within the organization. Varied aspects of power and its availability in any firm, coupled with inter personality conditions give rise to the relationships (Venkatachalam & Sellappan 2011, p. 97). Managers can influence decision making as they comment on what qualifies for discussions.

Power relations contribute to decision making through the engagement of organization staff on involvement in undertaking activities. Managers merely comply with the already set standards while leading other people. Whenever this takes place, the managers hold discussions with the relevant people to make decisions collectively on work aimed at meeting company goals (Venkatachalam & Sellappan 2011, p. 97).

Power leads to conflict in the organization, which needs adequate deliberation to decide on the best move. Different echelons of power requires transmitting information from pinnacle to bottom, which may cause damaged communication due to structural circumstances of those involved. Decisions making is necessary to solve the predicaments resulting from such conflicts.

Furthermore, power denotes leadership, which requires excellent qualities including superior decision-making ability. Managers must be able to identify threats and solutions to problems when options, facts, and goals are unclear. Managers ought to encourage shared decision-making. This is a way of empowering subordinates to be able to take part in an advice-giving decision making processes.

Power ought to organize the team members involved in decisions making. However, managers sometimes misuse their powers while engaging employees on making decisions about certain issues.

Decision choice less is the situation of managers seeking the opinion of the junior employees on vital organizational development agendas. The employees provide their information, which the manager discards and cannot include as one of the options for improving conditions in the organization (Shapira 2002, p. 145)

Political behaviour refers to as actions displayed by people in organizations; moreover, it depicts the requirements in such organizations. Political issues among some decision makers are an important aspect of decision-making. The politics include how managers use power to influence decision-making or the behaviour of employees while agitating for better remunerations.

It concentrates on designing and utilizing power in firm to ensure people who lack power get it to organizational level. The impact of political behaviour on managers includes the possibility of drawing up new policies for an organization upon learning the prevailing political happenings (Robbins, Judge, Odendaal & Roodt 2009, p. 358).

The managers take advantage of political unrest in an organization to destroy critical documents, which might be relevant for decision-making. People view political behaviour as a way of democratic decision-making, communicating demands for performance.

However, political behaviour in firms also presents dark side including intentionally telling lies, and intimidation. Political behaviours within an organization may thus impair decision following the divides it creates. Every political move has adverse impact in the process thus thwarting the rational model.

In conclusion, decision-making refer to a progression of choosing and executing options that are consistent with one’s inspirations. Rational model has contributed immensely to the decision-making in various organizations since it tend to eliminate all external forces that may hinder the course.

It is notable that myriads of parameters may influence the process. Personage personality and values normally may affect decision within the organization. Some managers hold particular values that they may not sacrifice in the process of decision-making. Self-esteem and other emotional attributes also affect decision. Anger, aggression and being overjoyed may compromise reasoning since they interfere with the psychology.

Making decision under such pressures may hinder the process, but soberness may lead to appropriate decision-making. Group relationship is another parameter that hinders decision since it influences individual thinking. Power relationship in an organization influences decision, as employees view high cadre to dominate during the process. This would allow them to offer options and easily convince people to consider their ideas.

The politics within corporations normally hinders decision-making, as it may lead to intergroup formations with competing attitudes. Decision-making should thus occur in a rational setting, which allows for adequate and rational consideration of every option.

List of references

Daft, R. & Marcic, D. (2010) Understanding Management , 7 th Ed. Ohio, OH. Cengage Learning.

Griffin, R. & Moorhead, G. (2010) Organizational Behavior: Managing People and Organizations, 9 th Ed. Ohio OH. Cengage Learning.

Martin, J. & Fellenz, M. (2010) Organizational Behaviour & Management . Ohio, OH. Cengage Learning.

Robbins, P. Judge, T. Odendaal, A. & Roodt, G. (2009) Organizational Behaviour: Global and Southern African Perspectives , 2 nd Ed. Cape Town.Pearson South Africa.

Shapira, Z. (2002) Organizational Decision Making . New York, NY. Cambridge University Press.

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    Rational decision making has been defined as a more advanced type of decision-making model, laying emphasis on the characteristics of thorough research and logical evaluation, selecting among possible choices based on reason and facts. The basic idea of rational choice theory which is premised on the assumption that cumulative social behavior ...

  7. Rationality in Decision-Making

    Handel, further reinforces this assertion affirming that rational systems generally focus on instituting within consideration, choice behaviors and hence organizational decision making, which is the basis for economic linked to firms ( Handel 434). According to Handel (435), rational choice theorists often work on the presumption that personal ...

  8. Rational Decision Making

    Abstract. Rational decision making requires executing an appropriate decision-making process to select the best alternative. This can be challenging when information is uncertain or when time is limited. This article describes three important perspectives on decision making: (i) the problem-solving perspective, (ii) the decision-making process ...

  9. Rational Model of Decision Making

    The rational model of decision making, since its introduction, has been used to make calculated decisions from business firms and companies. It is through this pure rational, calculated-numerical, process that the companies tend to make business plans for their future (Taylor, 2006, p. 4). As a manager of a financial service offering company I ...

  10. Rational Decision Making Model

    The Rational Decision-Making Model. The Rational Decision-Making Model is a method of taking emotion out of making decisions and applying logical steps to work towards a solution. The model ...

  11. Essay On Rational Decision Making

    What is Rational Decision Making. Rational decision making is defined as a systematic approach to long term decision making. As the word rational suggests, the approach brings logic and order to decision making. Rational decision making involves six main steps to achieve the desired solution. The first step is identifying a problem or opportunity.

  12. Decision Making Models

    A case in point for this model is the six-step decision-making process, which involves following six steps before coming up a viable decision. The first step involves defining what the decision maker wants to achieve (Williams 2008: 182). This necessitates recognising the need for change or decision-making.

  13. Rational Decision-Making

    Models of man: social and rational - mathematical essays on rational human behavior in a social setting. New York: John Wiley and Sons. Google Scholar Sterman, John D. 1989. Misperceptions of feedback in dynamic decision-making. Organizational Behavior and Human Decision Processes. 43(3): 301-335. Google Scholar

  14. Making Rational Decisions

    Making Rational Decisions. Clarissa Wern Ting Wong is one of our 2020 winners for the HIEEC. The economist Keynes once posited that when the quantitative calculation of expected utility can hardly help us make a decision, it is our "animal spirits" - or emotional states - that kick in and urge us into action (Keynes, 1936). This surmise ...

  15. The Rational Decision Making Of People Philosophy Essay

    Classical decision theory was mostly developed within the first sixty years of the 20th century. This focuses on how humans can most easily attain their desires with regard to their beliefs. Decisions can occur under varying circumstances; certainty being one, with a completely assured end result.

  16. (PDF) Rational Model of Decision Making

    Definition. Being the opposite of intuitive decision making, rational model of decision making is a model. where individuals use facts and information, anal-. ysis, and a step-by-step procedure to ...

  17. The Power of Rational Decision Making Essay

    Essay on Decision Making. Decision making can be described as a process of making a decision or decisions, based on choices made amongst two or more competing course of actions. The 'Decision making' also requires making a define choice between two or more alternatives course of actions that are available. 3079 Words.

  18. Rational Decision Making Essay

    Rational Decision Making Essay. 1846 Words8 Pages. According to Trewatha & Newport (1982: 148), decision-making involves the selection of a course of action from among two or more possible alternatives in order to arrive at a solution for a given problem. Decision making arises when alternative solutions can solve a particular problem.

  19. Rational Decision Making

    Abstract. Rational decision making requires executing an appropriate decision-making process to select the best alternative. This can be challenging when information is uncertain or when time is limited. This article describes three important perspectives on decision making: (i) the problem-solving perspective, (ii) the decision-making process ...

  20. 1.2.1 Rational Decision Making

    In your examinations, the essay questions test your ability to think critically.The command words for these questions are evaluate, discuss, or examine.. One way in which you can demonstrate critical thinking is to challenge the underlying assumptions of economic theory. The idea of rational decision making is one such assumption.Do consumers act rationally when they make impulse purchases?

  21. Decision Making

    In conclusion, decision-making refer to a progression of choosing and executing options that are consistent with one's inspirations. Rational model has contributed immensely to the decision-making in various organizations since it tend to eliminate all external forces that may hinder the course.

  22. Rational Decision-Making Essay

    Rational Decision-Making Essay. Decision making is is the process of making choices by setting goals, gathering information, and assessing alternative occupations (umassd.edu 2016). The three types of decision making are impulsive, rational, and dependent decisions. Everybody has and will encounter situations that will require them to make one ...

  23. Non-Rational and Rational Decision Making in Organisations

    Rational decision making (RDM) is a systematic process that utilises reason and facts when making a choice. RDM focuses on using objective data and analysis over subjection and instinct as a tool when making a decision (Attribution-ShareAlike, 2019). Decision-making goals are calculated with a holistic approach with knowledge of alternatives ...