Multiple Criteria Decision Analysis

Overview

CONTENTS

1.0 Overview

1.1 Career Preparation

1.2 Technical Communication

1.3 Decision Making Challenges

1.4 Decision Analysis

1.5 Strategies for Success

2.0 Multiple Criteria Decision Analysis

2.1 MCDA Overview

2.2 MCDA Question Types

2.3 MCDA in Context

2.4 MCDA Process

2.5 MCDA Example

3.0 Course Design and Rationale

3.1 Product Versus Process Approach

3.2 Imitation Versus Expression Approach

4.0 Assignments

4.1 Overview

4.2 Prescribed Outline

5.0 Identifying a Topic

5.1 Research, Evidence, and Analysis

5.2 Trust the Process

5.3 Think About Optimization with Tradeoffs

5.4 Pursue Your Interests

5.5 Interview Friends and Family

5.6 Be Practical

6.0 Example Student Presentations

1.0 OVERVIEW

1.1 Career Preparation

This course is designed to help you advance your career. According to the National Association of Colleges and Employers, employers want students to have high grades as well as the following key attributes ranked from most to least desirable (Job Outlook, 2024):

• Problems-solving skills (#1)

In essence, this text asks you to be a consultant. Your work aims to help others clarify, understand, and make difficult decisions (i.e., solve problems). As you do that, you will encounter your own problems. You will struggle. Think about it. Your global commodity analysis will indicate to your readers the likely direction of change (i.e., increase or decrease) in the market price and quantity for your commodity over the next five to 15 year period. You will write and publish your findings a report of about 4,500 words and 10 minute video summary. What employers want to see is that you can solve problems and successfully deliver these kinds of project results without excuses.

• Ability to work in a team (#2)

Unless your instructor says otherwise, you will have to write your own paper and prepare your own presentation. However, that does not mean that you have to or should work alone. Employers want to see that you know how to interact with others to improve your work. That's the definition of teamwork. Who is in your network of colleagues and friends who you can call on for ideas, help, and/or feedback (i.e., "peer review")? Employers want to see that you are nurturing and building your own strong peer support and consultation network. How will you interact with your instructor? What efforts will you make to work with other students if your instructor gives you that option or expectation? Be aware that the default expectation to avoid plagiarism is that you clearly acknowledge others' work that you use. Having an individually strong work ethic--apart from the ability to work in a team--is also important (#6 ranking). 

• Communication skills (#3 and #6)

Employers want employees who they can rely on to publish content (e.g., emails, corporate memos, videos, speeches, etc.) that reflects positively on them. Employers want employees who can articulate complex ideas and suggestions succinctly in writing. Even if you are not a confident writer now, this text will guide you step-by-step how to write and publish a final product that will make you proud. Employers highly value both written (#3) and spoken (#6) communication skills. Employers say that there is a 45 percent difference--the largest of any skill area--between the "importance" of communication skills and new employees' "proficiency."  

• Strong work ethic (#4) and Initiative (#9)

This text includes a lot of detailed instructions. It's not possible to anticipate and answer every question that every student might have. Similarly, employers are not able to describe every expectation of you in your written job description or even in a verbal summary. Instead, employers want employees who are self-motivated, employees who demonstrate initiative, employees who see what needs to be done and do it without having to be asked. This is especially true when an employer assigns an employee a significant project to complete over a relatively long time period. Employers want employees who can document that they have initiative to get work done on time with minimum supervision.  

• Flexibility / Adaptability (#5)

Sometimes your initial plan won't work. you may on occasion underestimate the requirements for an assigned project. Be prepared for unexpected challenges, especially as deadlines approach. When you need others to be flexible, learn professional ways to ask. Ask ahead of time, if possible. When you ask for flexibility, propose a specific alternative to make it easy for others simply to reply, "Okay, I approve. What you have proposed will be the new expectations."

• Technical Skills (#7)

Employers value your ability to solve problems using hardware (e.g., video recording), software (e.g., spreadsheet), and internet search tools (e.g., to find public data). The assignments in this text require technical skills in these areas. Your success on these assignments can provide clear and strong evidence about the strength of your technical skills.   

• Analytical / quantitative skills (#8)

Human beings are miserly cognitive processors, meaning they generally resist analytical reflection and instead prefer the instantaneous satisfaction that comes from a relatively quick intuitive or "gut" response, even if such a quick response is more likely to make them worse off [1, 2]. The assignments in this text ask you to use an analytical approach--which is admittedly slower than most intuitive processes--to help inform or help someone make a difficult decision. Most employers want to hire college graduates with strong analytical skills because those employers know that, more often than not, the extra investment of time and energy in analytical thinking is worth it to them. Don't believe me? Consider this question: "A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost?" [3]. If you said, "Ten cents," congratulations! That's the answer that most people give who rely on their intuition, but unfortunately that's the wrong answer. Analytical reflection should lead you quickly to see that the correct answer is five cents. Score one for analytical thinking!

• Detailed-oriented (#10)

Most technical writing involves trying to persuade someone to do or think something based on a set of facts. No matter how brilliant your ideas might be, if you are not well-versed in the facts of the matter, you won't be persuasive. Details matter. This text provides clear instructions about how to use details--particularly in footnotes--to build your credibility as an analyst and thus make your recommendations more persuasive. 

The paper and presentation assignments described in this text are designed to help you not only strengthen these highly valued skills but also to demonstrate them in concrete ways that employers will easily recognize. Be sure to read the "Strategies for Success" section below for helpful advice about how to work effectively with a key member of your team--your instructor--to solve assignment-related problems and complete and publish your detailed analysis. 

1.2 Technical Communication

There are many different kinds of assignments that students could complete to learn and demonstrate the desirable career skills just mentioned. This text teaches these skills by guiding students how to complete two major technical communication assignments: a paper and presentation. 

Technical communication examples include resumes, cover letters, user manuals, textbooks, policy briefs, legal analyses, journal articles, and economic forecasts. Oral examples of technical communication include audio or video documentaries, commercials, public service announcements, news broadcasts, class lectures, and academic presentations. Even logos (e.g., the Nike swoosh) and brands (e.g., distinctive symbols burned into the skin of free-roaming cattle) qualify as technical communication. 

All of these examples involve someone (i.e., a technical writer or presenter) simplifying complex information and presenting it to people (e.g., employers, consumers, lawmakers, and investors) who need it to accomplish particular tasks or goals (e.g., hire a qualified employee, make a worthwhile purchase, approve a beneficial law, select an undervalued stock, or differentiate their cattle from others' cattle). Technical communication is sharing complex information in simplified ways to help their audiences accomplish particular tasks or goals.

But, technical communication is not usually a stand-alone skill. Prize-winning author and historian David McCullough once said, "Writing is thinking. To write well is to think clearly. That's why it's so hard" [4]. An economist might say that thinking and communication are produced jointly (i.e., they are complements in production). If you want to be an effective analyst, consultant, inventor, entrepreneur, or researcher, you'd better learn how to communicate your useful ideas clearly and vice versa. Technical communicators are thus typically skilled at organizing information to form logical analytical arguments. These organizing skills include knowing--or learning--how to define unclear terms and concepts, how to identify and justify simplifying assumptions, and how to estimate unknown values. It includes knowing how to identify and order a set of claims that, if true, logically lead to a specific conclusion. And, it includes knowing how to gather and arrange relevant factual details (i.e., evidence) to support those claims convincingly. 

1.3 Decision Making Challenges

In his book Thinking, Fast and Slow, Nobel Prize winning author Daniel Kahneman describes how "fast" (i.e., instinctive and emotional) thinking is different than "slow" (i.e., deliberative, logical, and analytical) thinking [5]. The "fast" system of thinking is quick, almost automatic, requires little energy or thought, but it is also error prone. The "slow" system of thinking takes more conscious effort, but it is also more reliable. Kahneman describes several experiments showing that people often reach different conclusions depending on which of these two systems of thinking they use. 

Some decisions, Kahneman suggests, are better suited to the "fast" system of thinking (e.g.,  day-to-day questions like what to eat for dinner) while other decisions (e.g., complex decisions like where should I live or what investments should I make) are better suited to the "slow" system of thinking. If you make a decision with the wrong kind of thinking, it can result in problems. If you use "slow" thinking to decide what to eat for dinner, you may waste valuable time and energy, not to mention you may cause a delay in your mealtime and get grumpy. If you use "slow" thinking to decide where to live, you might regret or underestimate the career, personal, or quality of life impacts. The analytical decision making processes described in this text clearly align with the "slow" type of thinking processes and, as such, are designed to help you avoid the impulsive responses that might seem initially correct but are more typically wrong or misguided.

1.4 Decision Analysis

There are nearly as many decision analysis approaches as there are decisions. This text describes decision making processes that are rational and evidence-based. While there are many different ways to analyze and make decisions, there are many common underlying skills [6]. These skills include thinking skills such as the ability to form arguments, define terms, identify assumptions, and estimate unknown values. These skills also include communication skills such as giving attribution correctly, using footnotes effectively, and formatting tables and figures properly. Details and guidance about about skills are found in the "Helpful Resources" section of this page. 

1.5 Strategies for Success

Students completing the assignments in this text should already have had some basic exposure to college-level writing (e.g., ENG 101). Some knowledge of the principles of microeconomics (e.g., ECO 201) or basic statistics (e.g., correlation) may also be useful or needed. 

Beyond these content prerequisites, students using this text should also agree to three other learning prerequisites. First, students should trust the author of this text and their instructor to guide them to a successful learning outcome (e.g., a particular desired grade in the course). Second, students should always pursue excellence which at minimum means doing one's best work. And third, students should expect positive results for their efforts.  

First, students must decide whether they are going to trust this text and their instructor to guide them to success. The alternative is instead to follow one's own ideas about how to do well. That is strongly discouraged. Trust is important in any course, but it is particularly important in a writing-intensive course. This is true for two related reasons. One, writing is hard work. Learning to write well is not a natural gift, and just about everyone who writes must work hard to become a better writer. Two, the harder something is, the more students face temptation to take short-cuts, to create for example writing products aided by cheating rather than by working hard and trusting the instructor's guidance. The Internet provides numerous links to unoriginal texts and to ghost writers who will write term papers for a fee. Make no mistake, copying someone else's work without clear attribution (i.e., plagiarism) is not the same as imitating a prescribed form with permission and filling that form with one's own content. The latter approach is adopted by this text with careful efforts to distinguish it from the former academically dishonest approach. 

Students have a decision to make. Students can either follow their own plan (cheat, plagiarize, or whatever), or they can follow the instructor's plan prescribed in this detailed text. This text is designed to guide students to success with their instructor's help. Students that do not trust the text or their instructor to do that and who think it is better to follow their own plan will most likely fail. Students that trust this text and their instructors may fail too, but this text is specifically designed to help students be successful, even students who struggle with analysis, writing, and presenting. 

Second, students must decide either to pursue excellence or not. It's that simple. Excellence basically means that students do their best and not merely convince themselves that something less than their best is the same thing as excellence. The two are different. To pursue excellence means that you avoid making excuses. It means that you accept that improved writing and communication is hard work that requires regular practice and attention. It means that you study (not just read) this text, prepare your assignments in advance, and review your work regularly. Making excuses and throwing something together at the last minute without studying the detailed instructions in this text should embarrass any student who thinks such an approach deserves any merit; it does not. Do your best and be proud of that. If you do your best, you certainly should be proud of the work you do and products you deliver.

Third, students should expect results. Students that trust their instructors and that really seek to understand their assignments should learn quickly. You should see obvious results. The results should excite you and make you excited to keep working hard. If you do not experience significant boosts to your confidence, you should check with your instructor immediately. Something is wrong. You should see exciting improvements in your writing every week that build your confidence and pride in your work. The lessons from this text should make your analysis, writing, and presentation skills better in ways that are obvious and clear to you.

In short, students who trust their instructors and pursue excellence should expect strong results.

2.0 MULTIPLE CRITERIA DECISION ANALYSIS

2.1 MCDA Overview

What do you do when you have to make a decision but no option or solution perfectly satisfies all of your preferences or your list of ideal criteria? 

Suppose for example that your friend ask you to advise him about a car to purchase. Suppose your friend wants a car that is very fuel efficient, very inexpensive,  very comfortable, and very powerful. It is not likely that any single car scores highest on all three of these criteria. A new 2021 Ford Mustang (sports car) may be very powerful (i.e., lots of horsepower) and very comfortable (i.e., lots of leg room), but it may also be relatively expensive (i.e., high list price) and not very fuel efficient (i.e., low miles per gallon). A clean low-mileage 1981 Toyota Corolla (rare four-cylinder collector sedan) may be very fuel efficient, but it may score low in terms of power and comfort, and because it is a classic antique it may be relatively expensive. A used high-mileage 2013 Chevrolet Sonic (economy car) may be very inexpensive and relatively fuel efficient, but it may also be uncomfortable and have low power.

What car do you recommend? How do you decide?

Or, suppose your friend is trying to decide among several different job offers or career prospects. Your friend wants a job that scores highly in terms of salary, promotion potential, work conditions, and location (i.e., sunny climate), but every available job seems to involve tradeoffs among these preferred characteristics. What do you advise your friend to do? How do you help her decide?

Multiple Criteria Decision Analysis (MCDA) is a decision process that is well-suited to answer questions like these where a decision maker faces multiple options (e.g., different cars or different job offers) that involve tradeoffs among competing performance criteria (e.g., fuel efficiency versus price or prestige versus location). MCDA is a logical, analytical process designed enable decision makers to identify objectively the best alternative or best solution to a specific decision task. MCDA is also sometimes called multiple attribute decision making.  

2.2 MCDA Questions Types

MCDA can be used to inform many different managerial decisions in most fields, including those dealing with financial, economic, environmental, tourism, risk, information, and other considerations [7]. MCDA is appropriate for common business management decisions such as which inputs to buy and use, which outputs to produce and sell, how to produce and market a good or service, and where to locate production or other business operations.

• What type of solution is best to implement?

• What type of employee is best to hire?

• What product or service is best to purchase or use?

• What product/service is best to produce/offer and sell?

• What production method is best to use?

• What distribution method is best to use?

• What policy is best to implement?

• What place is best to locate?

MCDA can be used to help decision makers at both for-profit businesses and at not-for-profit organizations. It can help inform social and business entrepreneurial decisions as well as personal decisions (e.g., where to study, retire, or travel). 

Notice that the list of MCDA questions above all imply some kind of optimization (i.e., identification of the "best" or optimal option).  Optimization (i.e., find the "best" option) is one key feature of MCDA analysis. The other key feature of MCDA analysis is the presence of multiple conflicting interests (i.e., there are two or more criteria or interests that force the decision maker to make tradeoffs).  Price or cost is typically one of the conflicting interests or evaluation criteria. For this reason (i.e., because economic considerations like price or cost are typical considerations in a MCDA analysis), MCDA is a useful analytical technique for students of agricultural economics to study.  The two key features of MCDA are:

• Multiple conflicting interests

• Optimization

If a decision maker only cares about one criteria (i.e., just find the lowest cost option), then analysis of that problem tends to be relatively intuitive. All we have to do is choose the option with the highest preference rating for the single criterion. However, when the decision maker has multiple preferences or evaluation criteria, the analysis is more complex. Problems such as preference weighting, preference dependence, and conflicts among criteria require more thoughtful analysis and consideration. In the most general sense, MCDA is designed to make decision making in these more complex situations more formal, objective, and transparent. 

The first assignment detailed in this text (i.e., the "Proposal") requires students to identify an emerging question like one of the ones just mentioned. For other examples, I encourage students to look at the publications mentioned in the footnotes 8 through 19. Don't worry if you don't understand the matrix algebra and mathematical notation in those articles. The math and notation is not critical to completing the assignments in this text. What is more important is that you understand the kinds of questions that can benefit from MCDA.     

2.3 MCDA in Context

Be aware that MCDA is just one kind of decision analysis method or subdiscipline within the general field of operations management. Within the subdiscipline of MCDA, there are many different approaches and techniques [20]. This text shows students how to conduct only a very basic kind of MCDA, namely the kind that uses a simple additive weighting (SAW) approach. Footnotes 8 through 19 are examples of analyses that use the SAW approach to MCDA. 

While it is a simple and probably the most popular MCDA approach, the SAW approach relies on some fairly constraining assumptions, namely preference independence [21]. The text examines this important assumption in more detail in the chapter on the "Criteria", but preference independence basically means that the value, importance, or priority that a decision maker places on any one criterion (e.g., car price) is not affected by the the level of any of the other criteria (e.g., comfort, fuel economy, or horsepower) [22].  

More advanced MCDA approaches utilize computer software and require relatively larger amounts of raw data. Linear programming is an MCDA optimization technique most appropriate when the analyst is able to identify reduce the decision maker's competing preferences into a set of mathematical equations. Again, this text describes the most basic approach. 

2.4 MCDA Process

As I define it, the MCDA process using the SAW approach has nine steps. I describe each of these steps very briefly here and in much more detail for each of the assignment descriptions. Here are the ten steps with the name of the assignment (underlined) that includes that step:

1. Proposal. Determine that MCDA is appropriate for a specific decision task. 

2. Objective. Define objectively and clearly the specific decision task, its importance, and the decision context.

3. Criteria. Identify, define, and justify objectively and clearly at least two evaluation criteria based on the decision maker's preferences.

4. Criteria. Identify, define, and justify objectively and clearly how you plan to measure or estimate the levels of each criterion. For each criterion, you need to define the unit of measurement (e.g., horsepower or miles per gallon), define reasonable minimum and maximum bounds for the measurement scale, and identify the source(s) of data and, if relevant, the estimation approach you will use to quantify its level. 

5. Criteria. Define and justify objectively and clearly the relatively importance of (i.e., weights for) all evaluation criteria based on the decision maker's preferences.

6. Options. Identify, describe, and justify objectively and clearly at least two creative and non-dominated solutions to the predefined decision task. A set of non-dominated solutions is a set that involves tradeoffs among the evaluation criteria.

7. Analysis. Measure how well the options score in terms of each evaluation criterion in a stepwise fashion using the predefined measurement plan. This will yield a table with the unweighted raw criteria sub-scores for each option.

8. Analysis. Normalize the unweighted raw criteria sub-scores for each option using a common scale (e.g., 0 to 10 where 10 is the best) and the predefined reasonable minimum and maximum bounds to get the unweighted normalized criteria sub-scores for option.

9. Analysis. Apply the predefined weights to the unweighted normalized criteria sub-scores to get the weighted normalized criteria sub-scores for each option.

10. Analysis. Finally, sum the weighted normalized criteria sub-scores for option to get the total weighted normalized score for each option and a ranking of the options.

2.5 MCDA Example

Click on the text below to watch a short video showing a basic example of how MCDA can be used to analyze complex questions objectively. The example below is very similar to kind of analytical approach that you will use for your analysis. The example video is borrowed and adapted (educational fair use) from the internet.

MULTIPLE CRITERIA DECISION ANALYSIS VIDEO (2:25)

In this video, you can track the ten steps of the MCDA process described in the previous section. Your work for this course will require you to identify a decision task that is suitable for MCDA, complete a MCDA analysis of that decision problem, and then write a paper and create a presentation that describe the process in detail. 

3.0 COURSE DESIGN AND RATIONALE

3.1 Product Versus Process Approach

The instructional approached used in this text emphasizes the quality of students' final products and not the creative process students use to create technical assignments. Since the mid-1990's, writing pedagogy in the US has emphasized the process of writing: brainstorming, outlines, drafts, peer-review, and revisions. The writing process is clearly important. No serious writer and certainly no serious technical writer prepares a single draft and then stops. And, the writing process is critical as a means to clear thinking and learning. This text does include process-oriented expectations and assignments. However, to meet the learning outcomes, students cannot merely or mechanically follow a particular writing process. Instead, this text and its prescribed argument and language emphasize final product quality as the greatest priority.  

One purported advantage of a process-oriented pedagogy is that, having learned how to write, students will appreciate and value writing more for its own sake. The expectation is that students who are rewarded early for mastery of the writing process will want to build on these initial successes and will want to write more and through additional practice over time eventually better.

The author of this text does not disagree with this approach. However, satisfaction and confidence in writing comes not only from understanding and even appreciating the value of the writing process. It also comes from creating high-quality final products. It is very rewarding to create a thoughtful, complete, technically accurate, well-reasoned, and highly-polished analysis. This text and its seven related assignments discuss the writing process mostly as a means to improving students' final products. The goal here is that students create high-quality final products that students find personally significant and worthwhile.  In the typical time allotted for a course like this, there simply is not enough time for every student to develop and propose a unique argumentative structure for analyzing a unique economic question. Instead, this text gives students a head-start by asking everyone to adapt the same flexible argumentative structure.  

We sometimes tell children that "it's not whether you win or lose, it's how you play the game." That is fine for children. And, it is true that winning is not everything, but in most professional situations winning is important. Strong technical communication is important. An illogical argument, an ill-defined term, or an unreasonable assumption in a technical proposal will result in less than zero credit; the author will lose credit, credibility, and maybe the job. Professionally, no one cares what process you use to create the final product (short of stealing; don't do that).  Instead, people care about the quality of the final product.

This text shows students what high-quality final products look like, how they sound, and how they are organized. This text is designed to show students how to create final products that they will be proud to keep and share with others, not because of what their work represents (i.e., a process followed) but because of what their work is (i.e., a high-quality product). 

PROCESS VERSUS PRODUCT APPROACH VIDEO (6:22)

3.2 Imitation Versus Expression Approach

When students are learning about the process of writing, teachers often encourage students to "free write" or "brainstorm" initially about what they want to write. The emphasis is on the individual student's ideas and especially the expression of those ideas. Again, individual expression is important and often very rewarding, but in the professional world we rarely have such latitude. Instead, we typically have much more specific communication assignments (e.g., write a resume, prepare a cover letter, conduct a market analysis, write a business plan, or present a new product proposal). And these tasks often have specific forms that we are expected to reproduce, more or less, through imitation. In other words, professional communication assignments tend to constrain open-ended personal expression and instead favor imitation of established forms.     

This author of this text believes that imitation of a given form is a useful way for students to understand what a high-quality final product looks and sounds like and, paradoxically, it also liberates students to think about to fill the given organizational structure creatively with compelling evidence. While free writing, journal keeping, conferencing, and other "process" techniques are helpful for what they do (i.e., help student discover what they want to say), these techniques do not especially help students write strong sentences, improve the organization of their arguments, or arrange their essays to appeal rhetorically to the demands of specific audiences or specific circumstances.

Imitation of a given form also forces students to be creative. An empty form begs students to fill it. Far from encouraging conformity, imitation helps student discover their own voices. Imitation and attention to form provide a discovery pathway that starts with students wrestling to understand the given organizational structure and then how to fill it. Freed from the logical demands of organizing an argument, students are able to focus on interpreting its structure and then filling the empty form with meaningful and appropriate content.

It is possible, however, to provide too explicit instructions. It is useful to give students an empty form and ask them to wrestle with how to fill it. It is not useful to give students a completed example and ask them merely or simply to copy it. An empty form creates anxiety for students because they desire to fill it. Most people want to avoid anxiety. But some discomfort of this sort is essential for learning to take place. When imitation involves mere replication there is no anxiety, discomfort, or learning. For this reason, the text does not provide--and students are strongly advised to avoid consulting--completed examples of the written assignments described in this text.

IMMITATION VERSUS EXPRESSION VIDEO (7:13)

You might wonder how a text can be highly prescriptive--including a prescribed outline and even prescribed language--without raising issues with plagiarism. Good question. The standard expectation is that any work (e.g., ideas, organization, wording, images, etc.) that authors do not clearly attribute to others is their own original work. Students using this text will clarify an alternate expectation, namely that you will make no effort to distinguish your work from the work in this text but that in all other instances the standard attribution expectations will apply. More details and a rationale are given in the Proposal assignment. 

4.0 Assignments

4.1 Overview

The multiple criteria decision analysis report includes a proposal assignment, only some of which should appear in the final written report, plus four more sections ("Objective", "Criteria", "Options", and "Analysis"). After submitting and typically receiving instructor feedback on these five assignments, students will adapt and improve them to create a final written report with between 5,000 and 7,000 words and a final presentation that is as close to 10 minutes as possible. 

4.2 Prescribed Outline

This text describes in very prescribed ways how students must complete the written report and video presentation. The text has separate chapters that describe each assignment and required section of the report. Here, I will just give a basic overview of each assignment and the prescribed outline for the report. The 10-minute presentation is a video summary of the report's analysis and findings. 

For the reasons given in the previous section ("Course Design and Rationale"), you must carefully study and exactly follow the detailed instructions in this textbook if you want to do well.   

After each prescribed item below, you will see in parentheses the typical number of paragraphs (P) needed (e.g., "1-2P" means "1 to 2 paragraphs are typically needed). The outline below also indicates when a figure (F) or table (T) is needed (e.g., "1F" and "1T" mean one figure and one table is needed, respectively). Details about how to create and format figures and tables is in the "Helpful Resources" section of this textbook.  

The Proposal assignment is the first assignment. The goal of this assignment is to make sure that multi-criteria decision analysis is likely to work well to analyze a topic that you choose. You must create at least one but you may create as many as three proposals for your instructor. Each proposal should be one page in length. Each one-page proposal must include the following:

1. Your name, email address, and phone number in the upper left-hand corner. 

2. The name and a description of the organization, if applicable. (1P or less)

3. The name and a description of a third-party (i.e., not you and not the instructor) decision maker or decision maker group. (1P or less)

4. A description of one specific future decision, why that decision is important, and when the decision is needed (1P or less).

5. A list and description of three or four measurable and potentially relevant criteria. (1P or less)

6. A list and description of three or four promising options to answer or solve the decision task. (1P or less) 

The Objective assignment is the second assignment. Before you begin the objective assignment, your instructor must approve the proposal. The goal of this assignment is to improve your descriptions of the decision maker (or decision maker group) and the organization, if applicable, and then to add the necessary context for the reader to understand the decision task and why it is an important decision. The Objective assignment must include:

1. An informative title and title page with one artistic visual aid, your name, email address, phone number, and date. (1F)

2. A purpose statement paragraph, appropriately adapted as prescribed, that includes prescribed footnote. (1P)

3. A methods statement paragraph, appropriately adapted as prescribed. (1P)

4. An expanded and improved description of the context for the decision task, including details about the organization and decision maker or decision making group. Typically include two figures, one highlighting the organization or other contextual detail and another highlighting the decision maker(s). If there is no organization, include alternate figure that highlights a relevant aspect of the context. (3-5P and 2F)

5. An improved description of the decision task, why the decision is important, and when the decision is needed. (1P)

The Criteria assignment is the third assignment.  The goal of this assignment is to identify an appropriate number (i.e., 3 to 5) evaluation criteria that are important to the decision maker(s). The number of criteria and number of options must add to eight with no less than three of each. The levels of at least three criteria must be objectively measurable (i.e., not subjectively assigned). The Criteria assignment must include:

1. An updated and improved version of the Objective assignment.

2. A transition paragraph that helps readers understand the next step of the analysis. (1P)

3. A description of the first criterion, including a short informative name (e.g., "Efficiency" or "Yield"), a rationale for why the decision maker or decision maker group values the criterion, a description of how the author will objectively measure the level of the criterion, and a reasonable minimum (i.e., worst) and maximum (i.e., best) potential level for the criterion. (1-2P and 1F showing example of high and low levels) 

4.  A description of the second criterion, including a short informative name (e.g., "Efficiency" or "Yield"), a rationale for why the decision maker or decision maker group values the criterion, a description of how the author will objectively measure the level of the criterion, and a reasonable minimum (i.e., worst) and maximum (i.e., best) potential level for the criterion. (1-2P and 1F showing example of high and low levels) 

5. A description of the third criterion, including a short informative name (e.g., "Efficiency" or "Yield"), a rationale for why the decision maker or decision maker group values the criterion, a description of how the author will objectively measure the level of the criterion, and a reasonable minimum (i.e., worst) and maximum (i.e., best) potential level for the criterion. (1-2P and 1F showing example of high and low levels) 

6. Optional: A description of a fourth criterion, including a short informative name (e.g., "Efficiency" or "Yield"), a rationale for why the decision maker or decision maker group values the criterion, a description of how the author will objectively measure or subjectively estimate the level of the criterion, and a reasonable minimum (i.e., worst) and maximum (i.e., best) potential level for the criterion. Subjectively estimated criteria must use a zero to ten scale where zero is least preferred and ten is most preferred. (1-2P and 1F showing example of high and low levels)

7. Optional: A description of a fifth criterion, including a short informative name (e.g., "Efficiency" or "Yield"), a rationale for why the decision maker or decision maker group values the criterion, a description of how the author will objectively measure or subjectively estimate the level of the criterion, and a reasonable minimum (i.e., worst) and maximum (i.e., best) potential level for the criterion. Subjectively estimated criteria must use a zero to ten scale where zero is least preferred and ten is most preferred. (1-2P and 1F showing example of high and low levels)

8. A description of the simple additive weighting (SAW) method of MCDA and a review of the preference independence of the selected criteria. (2P)  

9. A description and rationale for how the decision maker or decision making group weights the criteria. Include a table (i.e., Table 1) that shows vertically each criterion's short name and horizontally each criterion's weight, minimum (i.e., worst) value, maximum (i.e., best) value, measurement approach, and if applicable the unit for measuring the level of each. (1-2P and 1T) 

The Options assignment is the fourth assignment. The goal of this assignment is to identify and describe an appropriate number (i.e., 3 to 5) potentially useful options for how to answer or solve the decision task. NOTE: The number of criteria and number of options must add to eight with no less than three of each. The Options assignment must include:

1. An updated and improved version of the Criteria assignment.

2. A transition paragraph that helps readers understand the next step of the analysis. (1P)

3. A detailed description of the the first option, including a short informative name, an objective explanation of how the context or situation would likely change if this option were selected, and a hypothetical rating of the option with respect to each criterion ("Great", "Good", "Fair", "Poor", and "Bad"). Include a figure depicting the option. Include a table (i.e., Table 2) that shows vertically the criteria and horizontally each criterion's weight and its hypothesized rating for each option. (3-5P and 1F and 1T) 

4. A detailed description of the the second option, including a short informative name, an objective explanation of how the context or situation would likely change if this option were selected, and a hypothetical rating of the option with respect to each criterion ("Great", "Good", "Fair", "Poor", and "Bad"). Include a figure depicting the option. (3-5P and 1F)

5. A detailed description of the the third option, including a short informative name, an objective explanation of how the context or situation would likely change if this option were selected, and a hypothetical rating of the option with respect to each criterion ("Great", "Good", "Fair", "Poor", and "Bad"). Include a figure depicting the option.(3-5P and 1F) 

6. Optional. A detailed description of the the fourth option, including a short informative name, an objective explanation of how the context or situation would likely change if this option were selected, and a hypothetical rating of the option with respect to each criterion ("Great", "Good", "Fair", "Poor", and "Bad"). Include a figure depicting the option. (3-5P and 1F) 

7. Optional. A detailed description of the the fifth option, including a short informative name, an objective explanation of how the context or situation would likely change if this option were selected, and a hypothetical rating of the option with respect to each criterion ("Great", "Good", "Fair", "Poor", and "Bad"). Include a figure depicting the option. (3-5P and 1F) 

8. A description of the MCDA concept of non-dominated options and a cursory assessment to show that no option is dominated. (2P)

The Analysis assignment is the fifth assignment. The goal of this assignment is to measure or estimate each criterion's level for each of your options and then, through a process of normalization and weighting, identify which option is optimal. The Analysis assignment must include:

1. An updated and improved version of the Options assignment.

2. A transition paragraph that helps readers understand the next step of the analysis. (1P)

3. A comparison and discussion of how well the options score in terms of the first criterion, including a description of how you objectively measured or subjectively estimated the first criterion's level for each option. Discuss any measurement or estimation issues that arose and how you addressed those. Include a table (i.e., Table 3) that shows vertically the criteria and horizontally each criterion's weight, each criterion's worst and best possible values, and the unweighted measured level or estimated score for each option. This section will be relatively longer if you have more options versus criteria. (2-4P and 1T)

4. A comparison and discussion of how well the options score in terms of the second criterion, including a description of how you objectively measured or subjectively estimated the second criterion's level for each option. Discuss any measurement or estimation issues that arose and how you addressed those. This section will be relatively longer if you have more options versus criteria. (2-4P)

5. A comparison and discussion of how well the options score in terms of the third criterion, including a description of how you objectively measured or subjectively estimated the third criterion's level for each option. Discuss any measurement or estimation issues that arose and how you addressed those. This section will be relatively longer if you have more options versus criteria. (2-4P)

6. Optional. A comparison and discussion of how well the options score in terms of the fourth criterion, including a description of how you objectively measured or subjectively estimated the fourth criterion's level for each option. Discuss any measurement or estimation issues that arose and how you addressed those. This section will be relatively longer if you have more options versus criteria. (2-4P)

7. Optional. A comparison and discussion of how well the options score in terms of the fifth criterion, including a description of how you objectively measured or subjectively estimated the fifth criterion's level for each option. Discuss any measurement or estimation issues that arose and how you addressed those. This section will be relatively longer if you have more options versus criteria. (2-4P)

8. A description of how and why you need to normalize the values from the previous table (i.e., Table 3). Include a new table (i.e., Table 4) that shows those normalized values using a scale of zero (0) to ten (10) where a higher value are preferred. (1P and 1T)

9. A description of how and why you need to weight the normalized values from the previous table (i.e., Table 4). Include a new table (i.e., Table 5) that shows those weighted normalized values. (1P and 1T)

10.  A description of the results from the previous table (i.e., Table 5) that explains that each weighted normalized value reflects the relative ranking of each option on a scale of zero (0) to ten (10) where a higher value indicates a better option. Conclude your analysis by explaining that the option with the highest value is the best option. (2P) 

11. Identify and explain important caveats and limitations of the prescribed analysis. (1P)

The Paper assignment is the sixth assignment. The goal of this assignment is to improve the previous written work in all aspects, making it appealing and easy to read, including improvements to the paper's wording, layout, design, footnotes, citations, figures, and tables and elimination of spelling, grammar, and punctuation errors.  The Paper assignment must include:

1. An updated and improved version of the Analysis assignment. 

2. At least 5,000 words and not more than about 7,000 words. Notice that if you add up the minimum and maximum number of suggested paragraphs above you find that the range for the entire paper is between 42 and 66 paragraphs. These are the approximate minimum and maximum number of paragraphs required to compete the prescribed analysis persuasively. As further guidance, that equates to an average of 76 to 167 words per paragraph, excluding footnotes.

3. At least 16 but not more than 18 visual aids (i.e., figures and tables). There are ten figures (e.g., 1F) and five tables (e.g., 1T) that are prescribed in the outline plus a prescribed title page figure, making a total of 16 prescribed visual aids. Students may and should consider changes to the number of figures where doing so will improve the value of those visual aids, but in no case should students have fewer than one title page figure and ten other figures. All students should have exactly five tables (i.e., one table in the Criteria section, one table in the Options section, and three tables in the Analysis section). You may not have more than 18 visual aids total. 

The Presentation assignment is the seventh assignment. The goal of this assignment is to convey as clearly and completely as possible the process and conclusions of your MCDA analysis. The Presentation assignment must be: 

1. A  digital (i.e., recorded) video presentation with 16 to 18 visual aids,

2. As close to 10 minutes in length as possible, and

3. In a YouTube-ready (e.g., .MP4 or .MOV) file format.

Students should note that their individual instructor may amend some the assignment requirements and, if so, those expectations (e.g., expressed in the course syllabus) obviously take precedence over the expectation described in this text. 

5.0  IDENTIFYING A TOPIC

5.1 Research, Evidence, and Analysis

If your instructor invites you to choose a topic, situation, or problem to analyze, you might wonder what criteria you should use to identify the "best" topic?  One key is that you understand what the assignments in this textbook ask you to do.

Many student incorrectly think that "research" or writing a "research paper" means merely gathering and summarizing lots of statements and opinions from lots of experts in support and/or contradiction of a particular claim. That is not what this textbook asks you to do. Instead, the assignments in this textbook ask you to find and gather enough high-quality information that you can describe accurately a situation (e.g., a market) and then use your own analysis of that situation to make your own evidence-based claim. 

For the assignments in this textbook, it is critical that you see the important role you have as an analyst. There is not one "right" way to define a situation (e.g., a market) or problem. It is your responsibility as the analyst to gather information and define the situation or problem that makes the most sense to you given the analysis you are going to do. So, your readers (including your instructor) will see you as not having done your job as the analyst if you simply rely only on the thoughts, options, and ideas of others. Your conclusions your report in your paper and presentation assignments are expected to result from your analysis of a that situation you define. The strength of your conclusions will depend not on how many other so-called experts you line up who agree with you. No, it will depend instead on (1) how reasonably and thoughtfully you define the situation or problem, (2) how compelling the evidence is that you offer in support your individual claims, and (3) how logical your analysis is of those individual claims taken together, assuming each claim is true.     

Thus, I discourage you from choosing a topic just because you Google some key words and it looks like there is a lot of information and analysis that others have already done on the topic. That might (at best) give you some good background information, but it might (at worst) overwhelm you with such technical jargon and complications that you forget that the assignments are actually fairly simple ones that depend more on what you think rather than what others think.   

Plus, be aware that most analyses are actually conducted to satisfy a particular client and/or particular business need. In that context, analysts do not typically have choices about what situation or problem they must analyze. Most people reading this text, however, will be doing so as part of a course and thus will likely have some choice. Choose wisely. 

5.2 Trust the Process

Students should recall (and review, if needed) the three "strategies for success" presented above in Section 1.5.  The first of these suggested strategies is that students must trust their instructors and this text to guide them to success. Of course, success depends on students agreeing to the second suggestion, namely doing their best work and "pursuing excellence". The third suggestion is that students should expect results, again, provided they embrace the first two suggestion. 

This is important because students sometimes do not trust their instructors or their texts to lead them to success. Some students, for instance, trust themselves and their own plans for success. Some students try to achieve success in their own ways that don't align with the plan for success that their instructors have for them. Some students think that there must be short-cuts to learning that their instructors just don't want to share. That's not true. Your instructors want to make it as easy for you to learn as possible. Some students confuse the inherent hard work that is required to learn something new with poor teaching or poor assignment design; they blame their instructors, and trust is broken. Resist this kind of thinking. Trust that your instructor will help you be successful if you follow the instructor's plan. So, for example, do not choose your decision analysis problem based on, for example, easy access to a former students' work. The only work from past students that will help you be successful is already contained in this text. Do not make up your own plan for success. Do not plagiarize other students' work or cheat (e.g., by asking someone else to do your work).

I suggest that you actively avoid reviewing anything created by former students except what you find in this textbook. Work done by former students will distract you and, if you copy it, your work will not only be plagiarized; it will also be useless. Work done by others will have already been polished through that student's previous self and peer review efforts that included comments from that student's instructor. It is expected that you start with your own ideas and build on those with the trusted help of your instructor and this text. That is the path to success. That is the path to a useful analysis that will make you proud.

So, you have to decide that you are going to follow the guidance provided by this text and your instructor. For you to do your best, follow the path outlined in this text. That will be more likely than any other path to lead you to success (e.g., an A in the course). Other paths (e.g., plagiarism and cheating) will not lead to success. This is true even if you consider yourself a very poor writer. If you are a poor writer, that's okay. Trust this text. Trust your instructor. Study and follow the instructions carefully, step-by-step. Do your best. Ask your instructor questions when needed.

In short, do not look to anywhere else other than to yourself, your instructor, and this text for how to select a good decision problem to analyze. Do not try to adapt or modify any analysis from any former student or from the Internet.

5.3 Think About Optimization With Tradeoffs

Not all decisions are suitable for multiple criteria decision analysis. See Section 2.2 above ("MCDA Question Types"). The decisions problems that are suitable for MCDA are ones where you need to identify a "best" path forward and where it seems likely that the available options will all involve tradeoffs (e.g., to get a car with more power, you're going to have to have to trade off some efficiency). 

The idea of what is "best" reflects the aim to identify an option that is optimal in the sense that it is better than the other evaluated options. The idea of tradeoffs reflects the idea that no single option is able to score highest in terms of every criterion used to evaluate the options. No single car will have the highest power, be the most efficient, and also have the lowest cost. There are inherent tradeoffs. 

Here are some examples of topics that former students have examined that require optimization and where there are inherent tradeoffs among the options:

• What place is best to locate?

-- Which study abroad program is best for ___________?

-- Should a Kentucky-based couple retire fully now, negotiate a phased retirement, or keep working for three more years?

-- What U.S. city would be best for ___________ to live during retirement?  

• What product or service is best to purchase or use?

-- Which herbicide is best for a large row-crop farm in South Central Kentucky considering cost, yield, human health, and environmental safety?

• What product or service is best to produce and sell?

-- Which corn variety is best for a mid-sized Maryland farm considering yield, disease resistance, hardiness, and time to maturity?

• Which employee is best to hire?

-- How should a Kentucky-based apple orchard deal with labor challenges: improve technology or hire either more US or more H2A foreign workers?

• What policy is best to implement?

-- What combination of tailgating and fans in the stands is best for Marshall University's football program for the Fall 2020 given pandemic concerns?

• What distribution method is best to use?

-- Are online auctions, in-person auctions, or private on-farm treaties best for a small family livestock showing business in Mays Lick, Kentucky?

-- Which commercial van is best for a local delivery company in Lexington, Kentucky?

• What production method is best to use?

-- What manufacturer--local, international, or in-house--is best for a new, innovative skateboard product?  

• What solution is best to implement?

-- What post-graduate plans are best for ___________: get a job, travel, or do a master's degree in public administration?

-- Should a large automotive shop in Lexington, Kentucky remain closed, reopen partially, or reopen fully given prevailing Covid-19 concerns?

Keep in mind that this text requires that the number of evaluation criteria (e.g., power, efficiency, and price) and the number of options (e.g., three specific vehicles) must equal eight and that there must be no fewer than three criteria and three options.  

5.4 Pursue Your Interests

You will likely be more motivated and pleased with the final product of your analysis  if you choose a question that has personal meaning to you. Think about your past experiences (e.g., summer jobs). Your personal experiences can provide you with useful details for your analysis.

Also, think about your personal interests and about the contacts that you would like to create. For this assignment, you will have to conduct interviews with a decision maker. You might want to use this course as a reason to make a new professional contact with an industry participants or leader. Your work on your analysis can be a great excuse to develop valuable professional contacts. These people might be interested in your analysis (when it's finished) or having you work on a project of current concern.

Consider too the kinds of decision tasks that you think will be interesting to employers who you would like to work with in the future. If you are interested in working for an international agribusiness, you might choose a decision task that involves a location decision (e.g., expanding into a new international market) or that looks at a problem related to cross-cultural communications. Ideally, you should look for markets that meet all three of these personal criteria (Figure 1).

5.5 Interview Friends and Family

You can use MCDA to analyze complex decisions that you--as an individual-face. However, this text requires that you identify a decision maker who is not yourself and not the instructor. MCDA also requires that you gather information (e.g., about preferences) from this decision maker or it could a decision making group (e.g., a board of directors or two business partners). For these reasons, it is often helpful if you can identify a decision maker who will be willing to spend the time and effort necessary to supply you with the information you will need. 

Here are some examples of people and organizations that you might know personally--e.g., a friend, family member, or other acquaintance--who might have decision tasks appropriate for MCDA:

• Someone who owns or works for an existing small business

• An entrepreneur who wants to start a new business 

• Someone who attends or works for a church or other religious organization

• Someone who volunteers or works for a local non-profit organization

It is possible that some decision makers will sincerely welcome your interest to help them make good decisions and be willing to offer you extra time to ask questions and gather information. In any case, no matter how generous the decision maker might be, you should not expect that the decision maker to help you--as the analyst--to imagine options or articulate clearly for you a set of criteria. You should not, for example, simply ask the decision maker, "Please name four important evaluation criteria," or "Please tell me three options that you think might work." Instead, a good analyst adds value by asking general questions, listening to the responses, and then organizing the information (hopefully) in useful and accurate ways.  

5.6 Be Practical

MCDA is useful for analyzing complex decisions. However, this may be your first effort to apply this analytical approach to a real-world problem. The paper and presentation that you prepare for this project has to be completed in a single academic term usually, and you probably have other courses that you are taking at the same time. Some ambition is good, but don't be too ambitious. Rely on your instructor to help you identify a topic that is feasible and appropriate. The Proposal assignment invites you to share up to three proposals with your instructor. I encourage you to do this.

Consider decision tasks that involve tradeoffs among location attributes. Location decisions typically involve selecting an optimal place (e.g., a city, neighborhood, or specific address) where something (e.g., producing, selling, studying, living, vacationing, or hunting) will occur. Since there tends to be relatively a lot of freely available location-based data (see below), a decision among several location options should be fairly easy to evaluate and evaluation criteria should also be fairly easy to measure given the relatively abundance of location-based data.

Consider decision tasks that involve tradeoffs among physical attributes. Some decisions involve making choice about which physical things are best. Some examples include choosing the best type of manufactured product (e.g., choice of vehicle, law mower, or package labeling equipment) or choosing the best type of real estate options (e.g., choice of farm, primary residence, or investment property). Because these are physical things, it is fairly easy to look at them and measure their performance attributes in different ways that might be important to a decision maker. For example, there are lots of standard ways to describe and compare the performance of motor vehicles (e.g., miles per gallon, horsepower, coefficient of drag, and price). Similarly, real estate options can be easily compared in terms of acres of land, square footage of conditioned space, number of bathrooms or bedrooms, and the amount of road frontage. Decision tasks that involve tradeoffs among the physical attributes of an object--especially objects with freely available performance data--are relatively easy to analyze using MCDA.

Consider decision tasks that involve tradeoffs among commodity attributes. A commodity is a thing where individual units of output are fully or substantially substitutable, even if produced by different firms. For example, herbicides are physical products (and so may fall under the above category as well) that often have equivalent or nearly equivalent performance (e.g., in terms of toxicity, weed control, and cost) and are therefore fully or substantially substitutable. Investment options (e.g., bonds, stocks, and mutual funds, especially index funds) are not physical products, but they too often tend to have nearly equivalent and easily discoverable performance (e.g., in terms of historical risk, historical returns, liquidity, and cost), much like a physical commodity. Decisions that involve tradeoffs among intangible products like these that tend to be measured in standard ways with easily-to-find performance data tend to be good choices for a first-time MCDA.       

Avoid decisions that involve tradeoffs among intangible attributes. Some decisions involve comparing vague attributes of options. In general, for your first MCDA, you should avoid decision tasks that involve intangible attributes. For example, consider a decision maker how is trying to decide what profit-enhancing strategy or marketing strategy is best to pursue. Strategies are complex and abstract things that can be evaluated in terms of criteria such as "return on investment," "demand," "total revenue", and "total costs". These attributes are difficult to measure because they require specialize forecasting skills. For these reasons, I suggest that you avoid decision tasks that fall into this category for your first MDCA.    

5.7 Data for Measuring Criteria

When choosing a decision task to analyze, one important consideration is the availability of data to measure potentially relevant evaluation criteria. As noted above, data available for measuring potential evaluation criteria is probably high for decisions that involve tradeoffs among location, physical, and commodity attributes. By contract, data availability tends to be lower for decisions that involve tradeoffs among intangible attributes. Be aware that there is a whole chapter devoted to the Criteria assignment and how to measure criteria objectively. For now you only need to know that MCDA is easier and less costly to implement if you can get lots of information and data about the attributes of potential options. 

For example, decision tasks that seek to identify an option location are relatively easy because there is a lot of freely available information and data about lots of cities and other places. Whatever your decision maker or decision making group might care about a place (e.g., how sunny it is), there is likely freely available data measuring that aspect of many different places (e.g., the U.S. National Oceanic and Atmospheric Administration has data on the amount of sunshine for at least 174 U.S. cities) [26]. 

Here is a list of some location-based data.

• The United States Census Bureau has data (here and here) on state, county, and smaller areas (e.g., zip code) for many topics, including population, age, gender, race, housing, living arrangements, computer/internet use, education, transportation, business, and geography. 

• The World Health Organization (WHO) has global data by country and some sub-units related to many health and disease topics.

• The United States has a website called Data.gov that centralizes a lot (and eventually all) of the federal government's data . The site has a search bar on the website homepage. Some U.S. federal government data hasn't migrated there and may have its own special website (e.g., U.S. Health Data).

• Open source data on European countries is available at the European Union Open Data Portal. 

• The United States Bureau of Labor and Statistics contains place-based economic data on such topics as inflation, prices, employment, productivity, workplace injuries, and occupational requirements.

• The United States Central Intelligence Agency (CIA) has a website called "The World Factbook" that contains data about each country.

• The United Nations has a statistic division (here) that has mostly country-level data. This data covers topics related to poverty, education, health, development, and environment.

• The Organization for Economic Co-Operation and Development (OECD) is a multi-national quasi-governmental organization that compiles lots of mostly country-level data (here). The data covers topics including agriculture, education, economics, environment, finance, productivity, and transport. 

• The World Bank is a non-governmental organization that gathers lots of data primarily by country (here), including data on GDP, population, school enrollment, CO2 emissions, poverty levels, life expectancy, and much more. 

• City-Data.com is a website that compiles original data (e.g., from government and private sources). You should always find, review, and cite the original data since compilation sites like this one sometimes make errors. Keep in mind too that compilation sites like this rely on advertising for support, so be ready to see lots of distracting advertisements. Still, this site can help you identify sources of data (e.g., county- or city-level median household income, population, racial composition, housing starts, employment rates, industry composition, and climate data on temperature, humidity, sunshine, and snow fall). 

• StatsAmerica.org is a website with U.S. data related to economic development. Most data is available by state, county, and city. This website on its homepage also has some data generation tools. For example, the "Big Radius Tool" will create a radius from 25 to 500 miles and view information on people, industries, and workers in that circle).

• Google has an application called Dataset Search allows you to search all kinds of data using a familiar search tool. For instance, I entered the search term "Peace" and the application showed me the "Global Peace Index Report" (2020) from the Institute for Economics and Peace that scores each country in the world using their peace index. A related Google data product website is Google's Public Data site that has some interesting data visualization options mostly related to economic indicators. Google Trends is another data visualization application that might be useful.

• StatSilk is a private consultancy website that has a page (here) that lists sources of country, city, and regional data.  

6.0 Example Student Presentations

The links below point to presentations created by other students who followed the guidelines in this textbook. As similar as these presentations are to each other, that is how similar your presentation will likely be. However, while you are invited to use any of the work in this textbook without attribution [27], that invitation does not apply to the example student presentations referenced in this section of this textbook. These presentations are provided to you so that you can see good examples of how MCDA works. The visual aids in these student presentations are the same visual aids that appear in their papers. Taken together, a thoughtful set of visual aids becomes the scaffolding that ties together and supports the voiced over narrative that tells the story of each student's analysis.

In these example presentations, be sure to note the year when they were published. All of them were "current" analysis when they were published, meaning that they examined a future period of time. 

Also, note that this text is updated periodically, and as a result some analyses may differ in certain, sometimes significant, ways from the analysis that this text currently prescribes. The more recent examples will have the fewest differences.    

This student work is shared here with their permission.

• Taylor Carney.  Spring 2021.  "A Multi-Criteria Decision Analysis for Eddy Creek Marina: Storage Building Renovation." 

• Lucas Jacobs.  Spring 2021.  "Real Estate Appraisal: A Multi-Criteria Decision Analysis of Selecting the Optimum Company Vehicle."

• Jacob Patterson.  Spring 2021.  "A Multi-Criteria Decision Analysis of Dairy Cow Housing Options." 

• Abigail Calender.  Spring 2021.  "To Buy New or Used: How to Best Accomplish Harvest."

• Abbey Dickerson.  Spring 2021.  "Harvest Plan Recommendations: A Multi-Criteria Decision Analysis for Todd Dickerson."

• Jeffrey Stroesenreuther.  Spring 2021.  "Balancing Costs and Customer Expectations: Pricing Solutions for Gumbo Ya Ya."

• Kyla Kelley. Spring 2022. "A Multi-Criteria Decision Analysis of Green Coffee Sourcing Options."

----------------------

[1] Evans, J. 2008. "Dual-Processing Accounts of Reasoning, Judgment, and Social Cognition". Annual Review of Psychology. 59: 255–278.

[2] Pennycook, G., J. Fugelsang, and D. Koehler. 2015. "Everyday Consequences of Analytic Thinking." Current Directions in Psychological Science. 4(26): 425-432.

[3] Frederick, S. 2005. "Cognitive Reflection and Decision Making." The Journal of Economic Perspectives. 19: 25-42.

[4] David McCullough is an American author, historian, and recipient of the Presidential Medial of Freedom, two Pulitzer prizes, and two National Book awards.  This quote is from his interview with NEH chairman Bruce Cole (Humanities, 2002, 23).

[5] Kahneman, Daniel. 2011. Thinking, Fast and Slow. Macmillan.

[6]  Parsons, Jay. 2016. "Seven Characteristics of a Good Decision." Nebraska: University of Nebraska-Lincoln.

[7]  Mardani, A., A. Jusoh, K. Nor, Z. Khalifah, N. Zakwan, and A. Valipour. 2015. "Multiple Criteria Decision-Making Techniques and Their Applications: A Review of the Literature from 2000 to 2014." Economic Research-Ekonomska Istraživanja. 28: 516-571. 

[8]  This article looks for an optimal food choice based on an analysis of each food's differing nutrition characteristics. Adriyendi, M. 2015. "Multi-attribute Decision Making Using Simple Additive Weighting and Weighted Product in Food Choice." Information Engineering and Electronic Business. 6: 8-14.

[9] This article looks for an optimal investment portfolio of stocks and bonds based on each investment's risk and return characteristics. Melia, Y. 2016. "Multi-Attribute Decision Making Using Simple Additive Weighting and Weighted Product in Investment." International Academic Journal of Business Management. 3: 1-15.

[10]  This article looks for an optimal employee based on seven different employee characteristics (e.g., education and experience). Afshari, A., M. Mojahed, and R. M. Yusuff. 2010. "Simple Additive Weighting Approach to Personnel Selection Problem." International Journal of Innovation, Management and Technology. 1: 511.

[11]  This article looks for the best location for a deep-water port in northern Europe (Lithuania).  Bagočius, V., K. E. Zavadskas, and Z. Turskis. 2013. "Multi-Criteria Selection of a Deep-Water Port in Klaipeda." Procedia Engineering. 57: 144-148.

[12]  This article seeks to identify the best fish variety for fish farming in South Asia (Indonesia). Kurniawan, R., A. H. Kridalaksana, and M. L. Jundillah. 2019. "Decision Support Systems Selection of Soang Superior Brood Using Weighted Product (WP) and Simple Additive Weighting (SAW) Method." E3S Web of Conferences 125: 23004.

[13]  This article looks for the optimal way to determine employee salaries based on employee motivation and productivity. Setiawan, N., M. D. T. P. Nasution, Y. Rossanty, A. R. S. Tambunan, M. Girsang, R. T. A. Agus, and K. Nisa. 2018. "Simple Additive Weighting as Decision Support System for Determining Employees Salary." International Journal of Engineering Technology. 7: 309-313.

[14] This article examines how best to rank sports (soccer) teams for the purposes of competition bracketing. Gökgöz, F., and E. Yalçın. 2019. "An Integrated Approach to the World Cup Teams Using Entropy Based ARAS and SAW Methods." Conference on Literature, Languages, Humanities, and Social Sciences. Dec 5-6. Istanbul, Turkey.

[15] This article seeks to find the optimal way to identify top employees. Wijianto, V. M. A. 2018. "Comparison Methods of ELECTRE and Simple Additive Weighting (SAW) Methods in Determining the Best Employees of Reward Recipients." ICCSET Conference. October 25-26. Kudus, Indonesia.

[16] This article looks for the optimal input supplier based on product quality, delivery time, and service quality. George, J., P. Badoniya, an H. A. Naqvi. 2018. "Integration of Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for Supplier Selection." International Journal for Science and Advance Research in Technology. 4: 18-22.

[17] This article seeks to identify an optimal way to select outstanding employees based on sales volume, attendance, guest service, communication, and appearance. Jollyta, D., R. Yunarto, and J. Ridwan. 2018. “Comparison of Analytical Hierarchy Process and Simple Additive Weighting on the Selection of Outstanding Employees." American Journal of Engineering Research. 7: 36-45.

[18] This article seeks to identify the optimal location of a warehouse in disaster-prone Indonesia. Nawindah, N. 2017. "Simple Additive Weighting (SAW) Mathematics Methods for Warehouse Disaster Location Selection in Central Jakarta, Indonesia." International Journal of Pure and Applied Mathematics. 117: 795-803.

[19] This article looks to identify the optimal digital single lens reflex camera based on cost, resolution, ISO, and censor characteristics. Putri, T. P., and P.H.P. Rosa. 2016. "Decision Support System to Choose Digital Single Lens Camera with Simple Additive Weighting Method." Scientific Journal of Informatics. 3: 167-176.

[20] Tzeng, G. H., and J. J. Huang. 2011. Multiple Attribute Decision Making: Methods and Applications. CRC press.

[21] Keeney, R.L., and H. Raiffa. 1976. Decision with Multiple Objectives: Preferences and Value Tradeoffs. New York: John Wiley and Sons. 

[22] In the car example, this seems like a reasonable assumption. If all of the cars available to your friend were equally and very uncomfortable, would that affect how much you value or priority your friend places on the car's price, power, and fuel efficiency. Likely not, but maybe. What about the job preference example above? Suppose that the only jobs available for comparison all were in a very pleasant and sunny location. Would that fact affect how much emphasis or priority your friend places on the other criteria (i.e., salary, promotion potential, and work conditions)? Not likely, but maybe. Let's consider a clearer case where preferences are not independent. Suppose your friend just graduated from college and needs to find a job (rural land surveyor or city school teacher) and buy a vehicle (a SUV or a sedan). In this case, it is almost certain that your friend's preferred level of off-road vehicle capability (i.e., the vehicle choice) is depends on your friend's preferred job (i.e., a rural job or a city job). 

[23] Benen, Steve. 2013.  "Rand Paul to Be 'More Cautious' in Wake of Plagiarism Scandal." MSNBC November 1. Accessed: 1-27-2021 at  https://www.msnbc.com/rachel-maddow-show/paul-be-more-cautious-plagiarism-msna201426. 

[24] Zeleny, Jeff.  2008.  "Clinton Camp Says Obama Plagiarized in Speech."  The New York Times.  February 19.  Accessed: 1-27-2021 at http://www.nytimes.com/2008/02/19/us/politics/19campaign.html. 

[25]  Martin, Jonathan.  2014.  "Senator's Thesis Turns Out to Be Remix of Others' Works, Uncited."  The New York Times.  July 23.  Accessed: 1-27-2021 at http://www.nytimes.com/2014/07/24/us/politics/montana-senator-john-walsh-plagiarized-thesis.html?_r=0.  At this link, take a look at the "Interactive Graphic" that color-codes Senator Walsh's entire paper, showing what text was his own work and what text was stolen verbatim from others without clear attribution.

[26] NOAA has lots of data at  https://www.ncdc.noaa.gov/data-access and at https://www.ncdc.noaa.gov/climate-information. Here is an example of data from NOAA about sunniness: https://www1.ncdc.noaa.gov/pub/data/ccd-data/pctposrank.txt. 

[27] For details about how it is possible that you could use work (i.e., ideas, organization, and wording) from this textbook without attribution (i.e., without giving credit), see the Attribution, Citations, and Plagiarism section of the Resources chapter and also see the text of the footnote (#1) that you are required to put after the first sentence of your purpose statement paragraph and that is detailed in the Objective chapter.