Assistente AI
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00:28:760Rubina Canesi: I'll phone up.
00:58:900Rubina Canesi: Trust me.
01:00:920Rubina Canesi: Anyone else?
01:03:190Rubina Canesi: Yeah. Yeah.
01:11:70Rubina Canesi: And
01:22:700Rubina Canesi: what's different.
01:49:560Rubina Canesi: Yes, I had a request from a classmate of yours, Laura.
01:55:40Rubina Canesi: who is not a family so asked us to record the lessons.
04:23:500Rubina Canesi: Give back a little bit when start.
04:29:320Rubina Canesi: This is less for today, which is about a multi criteria decision, aiding method.
04:39:361Rubina Canesi: I've seen that you have already talked about this topic and see the application already.
04:45:510Rubina Canesi: Analytica hierarchy, also dhp, method.
04:50:710Rubina Canesi: And because we have just came back from the
04:54:560Rubina Canesi: the winter holidays. We try to make this lesson a little bit more interactive.
04:59:590Rubina Canesi: So I will start by introducing
05:02:960Rubina Canesi: a problem, a problem that you have already.
05:07:67Rubina Canesi: Briefly seen, because it is a famous example to to
05:13:120Rubina Canesi: to learn about the Ahp method and the HP software. And we will try to address this decision problem with another method.
05:23:130Rubina Canesi: and we will.
05:25:740Rubina Canesi: after the the application of this method that is called the deck of card game. This Dcm. Stands for the deck of card game.
05:36:200Rubina Canesi: We will see soon.
05:38:90Rubina Canesi: and after this game we will try to see in the Excel file that you have found uploaded in the, in the model, in the model page.
05:47:420Rubina Canesi: We will try to see how this method works, and which could be the benefit of using this method compared to the long list of method that you have seen that are possible to to be chosen to address a decision problem.
06:01:420Rubina Canesi: So before we get into the game, we
06:05:600Rubina Canesi: I just wanted to recall some concepts that are helpful for us, that multi-criterion decision aiding is an approach that is aimed to support
06:16:630Rubina Canesi: the decision making process by considering multiple perspectives. And it is aimed to help decision makers in reflecting and discussing and arguing about choices.
06:29:110Rubina Canesi: Okay, the microphone is working for the recording. So we are
06:32:400Rubina Canesi: sure that also the people who will see them. No. That's a good point.
06:42:710Rubina Canesi: Okay, maybe the entire desktop. Okay.
06:49:620Rubina Canesi: okay, so you can see the entire screen here.
06:56:20Rubina Canesi: And okay.
06:59:330Rubina Canesi: so this is a method that is aimed to support the decision makers in reflecting, discussing, arguing about the choices.
07:06:10Rubina Canesi: Who are the decision makers. It could be a lot of person, a lot of people. It could be you today. It could be one of your clients tomorrow. It could be someone could be a group. It could be a different kind of stakeholders, public, private citizens, local policymakers. There are a lot of stakeholders. A lot of people could have been could be, could have been involved in making a decision.
07:31:690Rubina Canesi: And this approach requires that the decision maker, it could be one or more. But the decision maker, express and share some preferences and some consideration and aspects about his decision process. And there is another actor which is the analyst
07:47:180Rubina Canesi: that, as I said before, today could be me tomorrow it could be you that are playing the role of an analyst. You will be asked to support someone to make a decision. And there could be different kind of problems and different kind of methods.
08:02:440Rubina Canesi: And in this decision process we have, we have been asked to assign some values to preference parameters based on the chosen method. What we're gonna see today is the
08:13:660Rubina Canesi: this
08:15:43Rubina Canesi: method, which is as many multi-criterion decision making methods are evolving during the time. So they were. They have been conceived
08:25:930Rubina Canesi: many decades ago to solve some problems. They've been implemented through the years. They found some difficulties in the application difficulties in the mathematical background of the method. There could be many ways in which a method is developed depending on the type of problems and the type of characteristics that we want to consider. These methods were conceived.
08:47:40Rubina Canesi: let's say, in the eighties by sessimos
08:51:760Rubina Canesi: to provide a method which is designed to support decision makers that don't have a big background on multi criteria decision aiding
09:01:820Rubina Canesi: processes, and it is meant to help to rank and prioritize the criteria. And we will see today not only the criteria in a, in a given context for a problem. So
09:13:680Rubina Canesi: one of the problems that some analysts ever faced in the past is that when they are talking to someone of their clients. They don't have a background in decision, aiding support. Maybe they don't have a background in mathematics or engineering, or maybe they don't have a full background on the problem that they want to solve. So it is not easy. The interaction between the analyst and the decision maker, the method that we
09:38:620Rubina Canesi: will try to see today is aim to try to reduce this gap and to find a way to make more, let's say, interactive and clear also for people without this kind of background. In supporting for a decision problem
09:52:240Rubina Canesi: through the Excel file, we will see that because the calculation is not immediate, so there is a structure of the model behind. But the interaction between the decision maker and the analyst
10:02:420Rubina Canesi: is, at least at least in the intention of the method has to be simplified. How this interaction could be simplified by the communication of preferences through the cards. So I've brought with me today some cards.
10:20:440Rubina Canesi: and after that I will show you how we're gonna play today. Unfortunately, not the traditional game cards, but we will try to to make it adapted for our purpose, and it is a supporters to provide and to assign the numerical weights to criteria. This word weights
10:38:990Rubina Canesi: could be said in different ways in different terms, depending on the problem, on the methodology, on the types sometimes call it weights, sometimes call it importance in Ahp could be the priorities. Okay, so there are a lot of methodology, a lot of words and terminology that could stay behind this word, let's use it for today. The weights of criteria.
11:01:750Rubina Canesi: and this method has been applied in several real life contexts, and it is at least in the perception of the decision makers involved in the past appreciated for this.
11:13:910Rubina Canesi: for this intuitivity.
11:17:00Rubina Canesi: This is not. We don't go into detail of this, but is just to provide you a list of the references of the development of of this met some
11:26:620Rubina Canesi: recent. There were some implementation of this method to make it more simple to address some aspects. So it is an evolving topic
11:35:940Rubina Canesi: that
11:38:650Rubina Canesi: and and this slide is meant just for you. If you want to deepen the topic, to have some references to guide you in the, in the history of this specific methods. All the methods you have seen, and you will see if we go in this subject have an historical development. So they were considered at the beginning and by the use of professionals and academics. Most of the times they've been implemented through the time.
12:05:330Rubina Canesi: So this method was used mostly at the beginning to elicit preference parameters in particular, to assess the criteria weights in the Electra methods, which is a family of type of methods in the outranking family. You have seen in the Mcda general part that there are a lot of type of methods depending on how they are
12:36:327Rubina Canesi: they conceived, and what is their purpose and their and and their aim? And here it is
12:44:320Rubina Canesi: this deck deck of card methods was meant at the beginning to rank the elements from the least to the most important.
12:51:600Rubina Canesi: to express the preference, trend through blank cards between the levels, and we will see later. What does it mean? And it is meant to define the ratio to compare this criteria from the most important to the least one.
13:08:89Rubina Canesi: So now we will start the game. And just to recall the role.
13:13:90Rubina Canesi: there will be some actor. I will be the analyst in this moment. Okay, you will be the decision maker. So you will be my client, for for today
13:22:930Rubina Canesi: there could be other stakeholders and
13:26:490Rubina Canesi: there is a set of actions and alternatives that in our problem will be the
13:35:40Rubina Canesi: the, the card, the choice of the card
13:38:740Rubina Canesi: you you were asked you. You asked me a problem about. You want to choose a car which is the best car you have to buy. So there is an alternative here. It is a short list of free alternatives, but there could be more. But for the sake of simplicity we will consider this free alternatives.
13:55:660Rubina Canesi: and there are some criteria which is the same of the Ahp example, which is the criteria of prestige, the criteria of price
14:03:940Rubina Canesi: of the miles per gallon. So the consumption and the comfort.
14:08:480Rubina Canesi: So now I will provide you some of the criteria to.
14:17:40Rubina Canesi: as you recall, we did the same experiment with the HP, right with the software. Do you recall that we did the same?
14:25:130Rubina Canesi: So the problem is the choice of which is the best car you have to buy. So the problem is the same. But we are using 2 different meters, 2 different approaches.
14:38:910Rubina Canesi: But we use the HP. And today we are going to use the backup cart.
14:55:800Rubina Canesi: one part with information for each criteria.
15:04:115Rubina Canesi: Yes, and
15:23:770Rubina Canesi: like an hour
15:44:625Rubina Canesi: missing one. Yeah, go ahead.
16:10:650Rubina Canesi: Welcome.
16:19:90Rubina Canesi: Okay.
16:31:820Rubina Canesi: some rest. Okay. So we have this problem.
16:36:710Rubina Canesi: which is the choice of the best car. And we added these 4 criteria
16:42:540Rubina Canesi: which in this case you have chosen. Okay, in reality you have not chosen. But for the sake of this problem you asked me that you want to evaluate your car
16:51:850Rubina Canesi: with this 4 criteria.
16:54:130Rubina Canesi: But how this criteria could be considered together I will try to help you in this decision
17:01:490Rubina Canesi: with giving you some cards.
17:03:900Rubina Canesi: but before that I will ask you to rank these 4 criteria that you have in front of you.
17:10:00Rubina Canesi: Well, which is the most important for you. I remember prestige of the car, the price of the car.
17:17:180Rubina Canesi: the Mpg.
17:19:630Rubina Canesi: The comfort.
17:20:900Rubina Canesi: And here there are some additional information of the
17:26:60Rubina Canesi: of the criteria. You can use all of them. In the meantime, let's say, equal, equally important.
17:35:770Rubina Canesi: Yeah, we can. Yeah, if you want, you can take it together.
17:41:700Rubina Canesi: No, I mean there are 4 of them. One. No, you have to. You have to. You have to rank from which is the best, which is the best, the most important, the most important for you, for me, for you.
17:59:840Rubina Canesi: and sorry, Master Gun, is the consumption. So how much how much you consume your fuel.
18:08:600Rubina Canesi: How? How much kilometers or miles? Okay, you consume for one gallon or one liter of your of your car?
18:17:650Rubina Canesi: Yeah. Sorry. The the bold one at the at the beginning is just to give you.
18:28:730Rubina Canesi: let's say it was have a was meant to separate the criteria. But it's just what is the maximum. Okay.
18:47:60Rubina Canesi: you. You have to think when you want to buy a car, which are the characteristics that you're looking for.
18:53:120Rubina Canesi: How much does it cost. How much does it consume? How much is
18:57:800Rubina Canesi: it's still really beautiful? Let's say how much is comfortable inside or to park to move, to guide, which criteria is the most important
19:07:600Rubina Canesi: for me. Like.
19:09:300Rubina Canesi: sorry, yeah. Okay. So you put it in a in a list. Okay, in an order. And I have put here another piece of information which is important.
19:22:190Rubina Canesi: that this was 2 for the most important 2 for the most important at the same level of importance. Okay, I will give you now additional information that I forgot to mention at the beginning, but which is the direction of each criteria.
19:36:570Rubina Canesi: because I I assume that for the price you want to pay less. Okay.
19:43:220Rubina Canesi: there could be some luxury goods that you want to pay more because it it's better. But this is not the case. These are common goods, let's say, and we are.
19:52:205Rubina Canesi: we have a direction which is the maxim, the maximization of sorry. The price which is the minimization we want to the lower the price the better.
20:01:980Rubina Canesi: There is a criteria which is a prestigious, so the more prestigious is the car, the better.
20:08:450Rubina Canesi: The miles per gallon is a minimization
20:13:990Rubina Canesi: sorry, a maximization. I want to drive more kilometers. There is a mistake here. Sorry we'll correct it.
20:21:640Rubina Canesi: This is maximization.
20:24:670Rubina Canesi: I want to
20:29:510Rubina Canesi: out how much miles you make for one gallon. So with one gallon I want to ride 20 kilometers.
20:38:780Rubina Canesi: The more kilometers I can ride. I can ride with my car
20:42:510Rubina Canesi: the length of the car. Okay.
20:45:620Rubina Canesi: it is Max in the excel is correct. We received it, but there is a also here, and
20:52:440Rubina Canesi: and information, and in the comfort part
20:56:390Rubina Canesi: I want to maximize, so more comfortable is my car.
21:02:250Rubina Canesi: So this will I. I gave it as an assumption when you thought about the price.
21:07:110Rubina Canesi: But giving you this additional information could maybe change some of the order that you make, if not great.
21:14:480Rubina Canesi: Let's say I give another piece of information which is the rating scale.
21:24:630Rubina Canesi: do we on how to measure and say our our criteria?
21:32:70Rubina Canesi: And we will be. Let's say
21:36:280Rubina Canesi: a car could have a prestige that it is excellent.
21:40:650Rubina Canesi: It could be above average, it could be average, it could be below average. It could be 4,
21:47:510Rubina Canesi: the price would be from 15 to €35,000.
21:54:470Rubina Canesi: Okay.
21:55:630Rubina Canesi: maybe there are some cars that cost more or less. But let's say that we are considering. Only car that stay inside
22:04:860Rubina Canesi: this budget of mine. Okay, less than 15. It's too late to
22:11:60Rubina Canesi: less for me. I don't want it more than 45 is in too much. I don't want to. I don't want to pay so much for a car.
22:18:350Rubina Canesi: The miles per gallon is from 20 to 40. Here is, let's say, kilometer miles per gallon. Okay?
22:28:520Rubina Canesi: And same for the comfort we have some.
22:34:120Rubina Canesi: let's say, opinions that could be an excellent level of comfort above evidence, level of comfort. And
22:42:890Rubina Canesi: let's say, average below average and poor level of call.
22:49:60Rubina Canesi: Now, I ask you if with this information is still the same for you, the order of criteria
22:55:960Rubina Canesi: that you're choosing. Or if you find that could be, the software could be changed.
23:04:950Rubina Canesi: See?
23:06:170Rubina Canesi: Okay.
23:07:500Rubina Canesi: okay. Now, I'll give you another piece, not a piece of information. But let's say a side explanation on how this method evolves in the past. For example.
23:18:340Rubina Canesi: that could be a problem.
23:20:400Rubina Canesi: If I consider the the criteria that let's say the the
23:28:920Rubina Canesi: A car that performed poor in prestige.
23:33:270Rubina Canesi: and we will assume that this is my order. Okay, from prestige to price to Mpg. To comfort
23:40:850Rubina Canesi: is is better. A car that perform poor in prestige.
23:45:670Rubina Canesi: Then a card that perform 35. Sorry yeah.
23:53:90Rubina Canesi: 15 in price.
24:01:170Rubina Canesi: It's usually an average monetizing. So
24:05:740Rubina Canesi: I think should be. Firstly, whatever whatever for the individual or project, or or construction side of company, and we will buy some car. I think the 1st 3 should be the budget.
24:24:700Rubina Canesi: the budget. If we want to buy a car almost. Of course, there are too much cars in the market. Yeah, let's say the price for you is the 1st is the 1st criteria we should. We should according to the budget, and to see the difference car. I think this is
24:42:610Rubina Canesi: but it depends on what I want, like if I want it from my private use, or if I want it for my company, so that I like transport the labor from inside to the company of the marketplace. It depends what I want. If you want my private, I would like look for the one at least.
24:59:800Rubina Canesi: if I want it for my joinable
25:02:210Rubina Canesi: public use of my like transporting the labor from the side to the company, so I would go for the poor one. No, no, I think, for the company use for public use should be.
25:13:370Rubina Canesi: So the percentage is very important. The price, yeah, okay, this kind of discussion is a representation of how different stakeholders would have different.
25:30:620Rubina Canesi: Let's say, evaluation compared to the, to the criteria.
25:35:390Rubina Canesi: What I wanted to show you is a different thing. But this is important to see how a problem
25:40:280Rubina Canesi: and how, how in the problem different stakeholders could have different rankings, different evaluations and perception.
25:47:610Rubina Canesi: But maybe the criteria in this way are easy to easy to rank it so for me it's clear that prestige is better than price. Price is better than Mpg. Mpg. Is better than comfort.
26:00:220Rubina Canesi: But there could be a situation where I'm not sure
26:04:320Rubina Canesi: to assess if the worst situation of prestige is better than the best situation of price, or if
26:13:400Rubina Canesi: comfort, which is the the more or less important criteria for me, perform excellent
26:18:290Rubina Canesi: is still worse than the prestige that perform poor.
26:23:570Rubina Canesi: Okay, so this is just a kind of problem that cause if the rank between the criteria is not easy to
26:30:410Rubina Canesi: to to assess. Okay, because inside one criteria that could be different aspects that I'm not sure how they affect my evaluation. So just in case you are in this situation, there is a way, and we will see to, let's say, isolate the criteria
26:48:310Rubina Canesi: to make to perform this ranking and the
26:52:510Rubina Canesi: I'll jump back and forth in the slides, because, I try to explain these concepts as long as they come out.
27:01:340Rubina Canesi: So there is this action that we could do.
27:05:600Rubina Canesi: Let's say, let's compare the criteria with the best performance
27:10:220Rubina Canesi: or or the the scenarios, the alternatives, the car with the best situation.
27:16:120Rubina Canesi: Let's say that there is a car that have the worst performance on all the aspects, but the best performance on of excellent.
27:22:300Rubina Canesi: and compare the A car that have the worst performance on all the aspects. But the best performance
27:29:20Rubina Canesi: in the price in this way with this
27:34:460Rubina Canesi: ideal car, let's say with this dummy car. So I create a fictional car. With this characteristics I can better assess
27:42:910Rubina Canesi: the isolate value of this criteria. So this could be.
27:47:160Rubina Canesi: let's say, a way to help you in the ranking. In the 1st activity
27:52:690Rubina Canesi: that you're asked for this problem.
27:56:150Rubina Canesi: Now, I will introduce the cards.
28:01:70Rubina Canesi: Yeah. Yeah. So for example, we were talking about prestige. Yeah. And
28:08:00Rubina Canesi: perhaps we know that maybe a Mercedes really good prestige. It's well known. And then there's this new new car on the market, this new brand, and because they're new they don't have a lot of prestige. But the price is low. Maybe the comfort is average, you know, and perhaps it has more miles per gallon compared to maybe the Mercedes isn't someone going to decide to
28:35:120Rubina Canesi: rank prestige heavily, because everyone knows the history that comes with the Mercedes. And you know, if you have to carry out maintenance, it's very easy to do. But this new branch, maybe it's hard to find parts, or despite it, ranking well, in other criteria.
28:50:960Rubina Canesi: Okay, I will try to answer to your question.
28:54:950Rubina Canesi: Let's say that this scale, this range is meant for a specific problem.
29:01:280Rubina Canesi: If there is a new alternative, a new car
29:05:180Rubina Canesi: that they want to consider, or a new aspect.
29:07:980Rubina Canesi: I will maybe ask to resize or re. Let's say, resize my problem.
29:14:370Rubina Canesi: Maybe Mercedes is a super excellent is a new level that I was not considering before.
29:20:950Rubina Canesi: Okay, I have to build my model again
29:25:280Rubina Canesi: in this case. So this is another part that is important in the decision making, let's say, the flexibility of a model.
29:33:420Rubina Canesi: Also in Ahp that you have seen
29:37:740Rubina Canesi: you. You work in a, you work in a software, but also you have
29:42:500Rubina Canesi: set the criteria, the goals, and the aspects. You compare each other.
29:47:950Rubina Canesi: But if you add another level, you have to make the comparison again.
29:52:250Rubina Canesi: Okay? So so if the Mercedes add something different, I could
29:59:530Rubina Canesi: resize my problem if the Mercedes became the new excellent and the other move to another another level. Okay.
30:07:780Rubina Canesi: maybe I would just reconsider my alternatives. Given this new value. But the model is not changing is the value of the car. Okay? So when such things happen, it'd be advisable to maybe add new criteria, maybe a new
30:22:30Rubina Canesi: well, it depends more complex. Could you add another criteria to make things clearer, or it depends.
30:36:440Rubina Canesi: Okay, it is a choice that you, as analysts, you have to make, of course, depending in the feasible of the problem, because each time I add one criteria, or I add one level to my problem, it become a little bit more complex. It could be the right answer to better get
30:52:430Rubina Canesi: the preferences from the the people, from from the decision makers.
30:56:700Rubina Canesi: because remember that the 1st thing I have is to support the decision maker. I am the owner. I don't want to sell you my model. I want to help you in deciding the best car. So if you say to me from 15 to 35 is not enough. I want to spend from 10 to 15,
31:15:70Rubina Canesi: maybe I will. We have to resize the problem.
31:18:940Rubina Canesi: Okay? So the there could be different. Good answers, and each answers have consequences. So if I start to consider 10 criteria.
31:28:410Rubina Canesi: the ranking, the the evaluation, the the time spent by the people to thought about it becomes heavier.
31:36:810Rubina Canesi: So of course, we want to consider multiple criteria because some problems, especially in real life, have multiple criteria. But the the more the problem and the more complicated the the structure, the the more complicated became the decision support process.
32:00:50Rubina Canesi: Then the rating scale. What about the rating scale. It's still excellent above average average. They. They are separate, they are independent.
32:10:530Rubina Canesi: this criteria. And so
32:13:320Rubina Canesi: and it is my choice to not my choice. Your choice, maybe to done by the standards because you pay the car on the euros or dollars. You don't pay it in apples. Okay? So the scale will be in euros, but we can decide it to measure it as a number or as a judgment.
32:31:190Rubina Canesi: So it is my choice to use this excellent above average and average for prestige. But, for example, that you could, you
32:41:120Rubina Canesi: would measure the price with the high, low, and medium.
32:47:190Rubina Canesi: Sorry I didn't focus on this aspect.
32:50:100Rubina Canesi: I. These criteria, are expressed in an ordinary way.
32:55:720Rubina Canesi: so there is an ordinal, an ordinal scale of judgment from poor to to excellent
33:04:100Rubina Canesi: or interval in continuous, because I could have
33:08:190Rubina Canesi: a value expressed in number from 15 to 35, and it could be 2223, 23, dot, 5. Okay. So
33:18:250Rubina Canesi: this is, let's say, a quantitative criteria. And the prestige is a qualitative criteria.
33:25:650Rubina Canesi: Okay, this example was made to see how different things works. But we have to put it together.
33:32:520Rubina Canesi: So the choice is that if I resize or try to change, something is like I am resizing or restructuring the model to support the problem.
33:43:500Rubina Canesi: So yeah, let's say, in the assumption there is that we have decided to address this criteria
33:49:120Rubina Canesi: by ordinal interval or ordinal scales.
33:53:940Rubina Canesi: It could be that there is a law that required you to evaluate your house performance from 8 to 12.
34:02:970Rubina Canesi: Okay, how's energy performance?
34:06:390Rubina Canesi: So that would be the scale you're using, for example.
34:11:460Rubina Canesi: But let's say, in this case, we are using this that are very common scale. That could be, let's say, more easily understood.
34:19:510Rubina Canesi: Okay. Now I will ask you to.
34:23:520Rubina Canesi: I will give you some cards
34:26:600Rubina Canesi: unless you give me back at the end of the lesson. But
34:30:630Rubina Canesi: let's say, for the sake of the example, let's use it.
34:37:670Rubina Canesi: Yeah, there is not an exact amount. If you need more crap, just ask me, okay.
35:00:990Rubina Canesi: with these cards.
35:02:500Rubina Canesi: I will ask you to make an evaluation between the criteria.
35:08:750Rubina Canesi: So let's say that if
35:12:650Rubina Canesi: there is between one criteria and the other, there is no that there is.
35:19:410Rubina Canesi: let's say, one unit of of distance. You place no cards.
35:24:130Rubina Canesi: let's say, for example, from comfort to Mpg, my worst criteria. And the second, the second worst. Okay, there is a distance.
35:34:780Rubina Canesi: I don't know how much there is a distance that is.
35:38:230Rubina Canesi: this is better than this, no cards in between.
35:42:570Rubina Canesi: But if, for example, from
35:46:70Rubina Canesi: Price and Mpg. I perceive that there is the double of this, let's say 0 unit, this unit of distance. I will place one card.
35:57:480Rubina Canesi: If it is 3 times I will place 2. If it is 4 time, I will place 4,
36:02:490Rubina Canesi: and maybe from prestige to price.
36:05:440Rubina Canesi: I understood that there is still one unit of distance. So 0 count.
36:11:590Rubina Canesi: So the mean of the 0 card doesn't mean that is equal.
36:15:400Rubina Canesi: 0 card means that there is one unit of this one unit. Okay, of the instance. And the one card means the double.
36:25:770Rubina Canesi: Can you please make an example? Yeah, yeah, I will try to. I will try to put it in the yeah with this.
36:39:510Rubina Canesi: Okay, if there are on the same level, you could put it in the same level. Okay.
36:44:750Rubina Canesi: I will make it visually like this.
36:47:690Rubina Canesi: For example, prestige price and Mpg. Are the same for me.
36:52:790Rubina Canesi: and then comfort is the worst.
36:54:710Rubina Canesi: Okay.
36:56:90Rubina Canesi: let's say that for the simplicity I have a clear orders, but there is the possibility that some criteria are equal.
37:04:510Rubina Canesi: but for me, from and from comfort. And Mpg. There is one kind of distance
37:10:940Rubina Canesi: from price and Mpg, there is a 0 card. There is only one unit of distance, they are not the same, but there is one unit, and between prestige and price there are 3 cards.
37:22:340Rubina Canesi: because for me, price the difference between price and all the other criteria is bigger 4 times 4 times.
37:33:450Rubina Canesi: This help us to collect another type of information. There is not a simple ranking for one second, 3rd floor
37:41:310Rubina Canesi: cool, but I started to visualize
37:47:330Rubina Canesi: the the length of distancing between the between the criteria.
37:51:410Rubina Canesi: Okay?
37:52:740Rubina Canesi: And even if I and I don't ask you which is.
37:56:980Rubina Canesi: let's say, the 0 value. It's just a proportion between the the criteria you are considering.
38:03:70Rubina Canesi: So maybe, he said at the beginning, for me, Price is the most important criteria. The others are very, very low.
38:12:230Rubina Canesi: 10 cars here, because I consider price
38:15:990Rubina Canesi: telecast. And yeah, from prestige and my tool, and from comfort and prestigious mind.
38:24:150Rubina Canesi: But there should be a like maximum and minimum for this, like 0 to 10 or 0 to 5.
38:33:400Rubina Canesi: So I will show you how the model works. The list is is correct
38:37:410Rubina Canesi: to to evaluate these things, we will need the maximum and a minimum.
38:41:501Rubina Canesi: So in the ahp you have a maximum and a minimum already set up. But in this case it's different.
38:48:530Rubina Canesi: Okay? But we see because we will require to set, which is the maximum and minimum. But in this case I'm just asking you to placing some cards.
38:56:700Rubina Canesi: and I'm not asking you why. Why and I'm not. I'm not asking you which is the level
39:03:820Rubina Canesi: of the 0 of the 0 card that I use. Okay.
39:08:10Rubina Canesi: you said to me it could be this length, or it could be. It could be that there is no distance.
39:14:460Rubina Canesi: It is a 0 1 1 each other from each level.
39:20:470Rubina Canesi: Linear. Okay.
39:28:210Rubina Canesi: I will place the cards here, so we will see later.
39:32:290Rubina Canesi: Are we forced
39:58:300Rubina Canesi: or in here there was the explanation. So
40:01:710Rubina Canesi: you rent cards from the least preferred to the most preferred, or
40:05:420Rubina Canesi: you evaluate the different preferences you place.
40:10:130Rubina Canesi: Yeah. Say, the white card is like this. The description?
40:15:430Rubina Canesi: No sorry. The white cars in our example, at least for the empty cars. Right?
40:20:30Rubina Canesi: No car, no 0 white cars is a minimal difference, a unit of alpha.
40:25:650Rubina Canesi: One card is a difference of the double double amount. So okay, is 3 times
40:38:290Rubina Canesi: sorry. 2 cards is free time. The alpha pick up before yeah, and so on.
40:50:100Rubina Canesi: So it's just the cards is, no, no. One is the double of the 0 cards level. Okay.
40:58:770Rubina Canesi: okay, have you thought about your preferences or the weights on your criteria?
41:05:10Rubina Canesi: So here, this is a visual explanation of let's say, the the example, where the one of the scientific papers that talk about this problem. So in this example, they have this 1, 2, 3, 4, 5 criteria.
41:22:560Rubina Canesi: and they place 2 cards, 1 0 3 cards with the same meaning.
41:31:370Rubina Canesi: And here you see 2 cards, because, for example, these 2 criteria are considered at the same level.
41:41:110Rubina Canesi: So this start to help us to provide some weight to how we evaluate the criteria.
41:52:570Rubina Canesi: This is the example I've shown you before. So if you have difficulties in ranking the criteria. That could be this
42:00:850Rubina Canesi: dummy use dummy scenarios that helps you to separate
42:07:620Rubina Canesi: the the relevance of the criteria. Okay.
42:16:730Rubina Canesi: okay, so I will move forward. I will replicate the exact example we are using here. Right?
42:26:10Rubina Canesi: So this is how we start to see how we will see in the Excel file. Okay.
42:32:490Rubina Canesi: that I've placed the 2 cards between prestige and price, one cards between miles per price and miles per gallon
42:41:30Rubina Canesi: and one card between corporate times.
42:43:740Rubina Canesi: Mpg, and cold front. Okay.
42:48:710Rubina Canesi: Now, the
42:50:660Rubina Canesi: another information I will ask you is to establish a relation between the 1st and the last criteria in the ranking.
43:00:620Rubina Canesi: Okay, here is another free choice. Let's say that we are using.
43:08:280Rubina Canesi: I took, for example, that for me, Prior, I'm sorry this
43:13:480Rubina Canesi: prestige is 10 times important than coffee, or
43:19:640Rubina Canesi: if I, if I perceive that I know this relations, I could use it.
43:24:660Rubina Canesi: Another way is to count the cards I have in the queue. It depends. Okay.
43:29:840Rubina Canesi: But if you, if you want to put it in a
43:34:380Rubina Canesi: if you perceive that the the the prestigious 10 times comfort.
43:41:800Rubina Canesi: We will use this information as the
43:45:563Rubina Canesi: ratio. The ratio in the Greek letter.
43:49:420Rubina Canesi: which is intended at the substitution rate between the criteria with the highest and the lowest rates.
43:58:190Rubina Canesi: So, for example, between my price and prestige.
44:01:890Rubina Canesi: I have like 5 cards, so should I say, for example, my price is
44:11:730Rubina Canesi: 5 times more important than prestige. You could say that. But what I wanted to underline is that you're not forced to
44:19:390Rubina Canesi: use the number of cards.
44:22:350Rubina Canesi: Okay, we are talking about 2 different things. So how much the best is, how many times the best is the lowest?
44:31:910Rubina Canesi: It's because I choose. That is 10,
44:41:70Rubina Canesi: because I am assessing. Well, you, as my client, is assessing that prestige is 10 times the the comfort.
44:50:140Rubina Canesi: So with this step, you want to assign to each card and await. Okay.
44:58:260Rubina Canesi: yeah. So it's used to do that. You are using this for assigning it. Yes, the time is, the time is, is I put it in the example. Yeah, yeah, exactly. Exactly. But you could tell me another language if you take notes on how you're placing the cards and how you're giving this ratio we will see in the excel your choice of the best card
45:25:920Rubina Canesi: yeah, you could use. You could also use one, let's say, but this will change the mathematics, but it's we adapted to. The value you give is the important is how you, which is the client, perceive the things because I'm trying to assist you in the decision. Okay.
45:45:810Rubina Canesi: by getting the real. Let's say the real, the more realistic weight you're take. You're considering for this kind of criteria.
46:04:710Rubina Canesi: No, no, no! This representation, or the the card I have played is what you say
46:17:300Rubina Canesi: you can choose. But what if I use 10? For?
46:20:480Rubina Canesi: I use the value? 10, because it is easier for the calculation. But
46:24:410Rubina Canesi: you could tell me that one criteria is 3 times the other.
46:28:500Rubina Canesi: because what I have done before is a ranking of the criteria.
46:32:450Rubina Canesi: and I'm with the cards I am trying to catch. How much is the distance between the levels. But I'm not saying that
46:41:70Rubina Canesi: this best, how much? How much is this distance inside? Okay.
46:47:500Rubina Canesi: so we are trying to capturing some values without giving an exact number right now, okay, so we're trying to. We're like walking around. And this, the decision we have to make to be in this model.
46:59:230Rubina Canesi: So to answer your question is.
47:01:630Rubina Canesi: these are the cards I have placed in between the levels.
47:05:280Rubina Canesi: And what I'm asking you is a a proportion. So a substitution rate from the best to the worst
47:12:770Rubina Canesi: and the
47:13:750Rubina Canesi: in this example I set the 10. But you can choose 5, 6, or a hundred times. Okay.
47:21:802Rubina Canesi: sorry. Yeah. So.
47:23:730Rubina Canesi: looking at the Ahp. The difference that Sati, you remember the scale of Sati gives you a readiness scale, and so you already know that one equal to equal importance. 2 were a little bit more importance. So in this case we don't have this. So we are weighting this. We are determined our scale.
47:43:550Rubina Canesi: So we are a step back.
47:45:980Rubina Canesi: So we are building that scale.
47:49:30Rubina Canesi: Okay, okay, so this zeta ratio, this substitution rate is one of the, let's say 2 important
48:00:630Rubina Canesi: aspects that we need them. Okay?
48:03:510Rubina Canesi: Because we are starting to getting the value of our criteria right? We have a proportion between them.
48:11:960Rubina Canesi: So this if you are, let's say, comfortable in saying that this 10 times
48:19:910Rubina Canesi: the the best criteria is 10 times the the lowest one
48:24:180Rubina Canesi: we can continue. But if you want another level, we could change it.
48:27:900Rubina Canesi: Let's say that there are
48:30:460Rubina Canesi: maybe, at the end of all the examples. I will tell you some other things, because this is one of the most critical
48:36:580Rubina Canesi: aspects. Because when I'm asking you this information I'm
48:41:120Rubina Canesi: requiring, I require some mental effort from you. Okay.
48:45:260Rubina Canesi: but this is one of the most difficult things in the decision making process.
48:49:490Rubina Canesi: Because if I ask you to calculate many values, it will require a lot of effort on different criteria, much more effort. So I'm trying to ask him some values without
49:02:90Rubina Canesi: requiring too much effort. Okay.
49:05:70Rubina Canesi: maybe I'm not succeeding. But maybe I will not be a good analyst in supporting decision making. But this is the aim of the
49:15:910Rubina Canesi: no.
49:20:180Rubina Canesi: What we are trying to calculate is another important information, which is the alpha value
49:28:660Rubina Canesi: which is that given our is that is that the ratio?
49:34:510Rubina Canesi: Is it that issue of them?
49:37:530Rubina Canesi: In my example, which is 10 over one.
49:44:10Rubina Canesi: you can use your 6 over 1, 9, over one a hundred over one.
49:49:990Rubina Canesi: It is possible for me to compute the alpha value, which is the famous 0 unit.
49:59:960Rubina Canesi: 0 card the value that I'm missing before, because I
50:09:970Rubina Canesi: consider the the value between the
50:14:90Rubina Canesi: the low, the highest, and the lowest, which is 10 minus one, divided by the number of cards.
50:22:960Rubina Canesi: plus one, because one was our alpha value that we were missing. Let's say our 0 card.
50:30:730Rubina Canesi: So each time we were placing some cards, we were considering the double of Alpha, the triple of Alpha.
50:37:680Rubina Canesi: Oh, in this way I will have 10 minus one, which is a 9. The distance between the highest and the lowest, and I will. I will divide it by the number of cards.
50:50:610Rubina Canesi: 2 plus 1, 1 plus 1 1 plus one, and I will get one dot 29. This is my alpha value in this model.
51:00:160Rubina Canesi: Of course it changes if I
51:02:720Rubina Canesi: place a different number of cards.
51:05:810Rubina Canesi: If I place free cards here, I will have to would free here. Okay?
51:14:700Rubina Canesi: Because my alpha value. So how much? How big is this unit of alpha I'm looking for depends on the number of cards. So if I place.
51:23:740Rubina Canesi: instead of 2 10 cards, I have more values inside my my scale, and I will.
51:33:560Rubina Canesi: and I will have a just, an over alpha, which is not a problem. It's just the unit. I will use it to assess my evaluation.
51:43:00Rubina Canesi: What I have done here is calculating the weight of the criteria given this set of value and given this alpha value.
51:52:430Rubina Canesi: so I have placed it.
51:54:490Rubina Canesi: The value of the highest criteria, which is 10, and I have
52:05:30Rubina Canesi: assess the weight of a sorry there is.
52:15:820Rubina Canesi: and we're sorry. We will see that in the excel. File the calculation of these weights. Okay, because there is a step. There is a step missing on how to calculate the value. But I will multiply the alpha
52:26:990Rubina Canesi: by the number of cards that are
52:29:720Rubina Canesi: necessary to reach that level. Okay, maybe I will have it not here.
52:49:500Rubina Canesi: Well, we can switch to this step, so it will become clear the the function
52:56:500Rubina Canesi: this procedure that we have done for for the criteria. Now I will ask you to do it also within the levels of each criterion.
53:06:370Rubina Canesi: What does it mean? This, that
53:11:310Rubina Canesi: I need to calculate the alpha value with the card game
53:15:420Rubina Canesi: within each of these? So I have to do the same procedure within the the prestige of
53:25:360Rubina Canesi: prize Npg. And comfort.
53:28:120Rubina Canesi: and I will ask you to. The the rank is already made, of course, because I am from the lowest of the highest value. But I will ask you to place some cards
53:37:930Rubina Canesi: between what I have to start to take the excel to see all the calculation. Okay?
53:48:910Rubina Canesi: Because here it is, let's say little bit easier, because, for example, from the
54:00:260Rubina Canesi: no, it's better to show you with excel. So we are not losing you in the calculation.
54:06:490Rubina Canesi: Yeah, yeah, yeah, yeah. Yeah.
54:12:920Rubina Canesi: Activate. You said that.
54:17:130Rubina Canesi: Now we show. Now, we show how it's calculated. Yeah, yeah, I've not explained it yet. So because
54:25:420Rubina Canesi: I say, from now on, I have to ask you to make this assessment.
54:31:500Rubina Canesi: This is what this was just the explanation of how the cards work. Okay, the. But now we have to complete the the model.
54:38:990Rubina Canesi: So how is this model built?
54:41:750Rubina Canesi: And say, this is what behind the what the client usually don't see. And this is what the analysts have to do.
54:49:800Rubina Canesi: I have my problem. I will zoom it so you can see it also from
54:58:530Rubina Canesi: the desk.
55:00:490Rubina Canesi: Do you? Do you see it? Okay? So the goal of my
55:04:460Rubina Canesi: problem is to choose the best car.
55:06:870Rubina Canesi: I have some alternatives that here are these 3 cards.
55:10:840Rubina Canesi: It couldn't be more. But we'll see you later.
55:13:270Rubina Canesi: I have my 4 criteria.
55:15:320Rubina Canesi: I have my rating scale within them.
55:20:730Rubina Canesi: I have the nature, let's say, the type of criteria, ordinary or internal.
55:25:230Rubina Canesi: What I have asked to you and explain to you now is the placement of cards. Okay.
55:32:230Rubina Canesi: between the criteria.
55:37:100Rubina Canesi: How do I calculate this?
55:44:410Rubina Canesi: Let's say that
55:46:220Rubina Canesi: the the value, time and the value one are easy, because it is the famous the famous value I've mentioned before. So 10 times the lowest, how do I calculate this
55:59:840Rubina Canesi: second level? So how the weight of Mpg.
56:03:990Rubina Canesi: If you see the formula, it is one last the number of cards
56:12:400Rubina Canesi: plus one. So it is our famous
56:16:130Rubina Canesi: 2 plus Alpha. Let's say No. 2 sorry, 2 plus one card, because we understood. Multiply by the alpha.
56:26:410Rubina Canesi: So one glass, 2 cards, alpha, the double of Alpha.
56:39:930Rubina Canesi: This. This were the 2 cards I have placed before between between prestige and price.
56:47:710Rubina Canesi: So now we are calculating the data of of Yes, let's say of here, you can see prestige, price Npg. And comfort.
56:58:625Rubina Canesi: Sorry because it is. Let's say, river.
57:04:830Rubina Canesi: it is revert in this. It'd be wonderful.
57:10:800Rubina Canesi: So where is the regular conference?
57:14:120Rubina Canesi: Where is it? Where do we cover from?
57:17:290Rubina Canesi: So comfort is here, and it is one the entity.
57:25:950Rubina Canesi: Yeah, so I am.
57:36:570Rubina Canesi: I have reversed the scale.
57:44:160Rubina Canesi: No, we don't qualify for.
58:03:440Rubina Canesi: Yeah, yeah, sorry it is. I have. I have to remake the
58:25:780Rubina Canesi: but what? Let's say that it is reverted to what it is here is sorry in this.
58:33:700Rubina Canesi: and show you here.
58:37:880Rubina Canesi: Sorry to follow our example. It is, it is inverted.
58:41:530Rubina Canesi: it is our lowest value, is the is the call for it right now. Our Mpg.
58:55:680Rubina Canesi: now it is sorry. Now it is, it is greater. Okay?
59:01:140Rubina Canesi: Because so this, this was how it was shown here.
59:05:110Rubina Canesi: I think the calculation
59:07:160Rubina Canesi: it is inverted. Of course you can build it in excel with the the different order. Okay, so it's just a way to show the calculation.
59:15:600Rubina Canesi: So what you were saying before. Sorry was that comfort was the lowest, and it is one.
59:20:830Rubina Canesi: An Mpg.
59:22:440Rubina Canesi: Is given by one plus number of cards plus one per the alpha value.
59:35:780Rubina Canesi: Yeah, yeah.
59:39:500Rubina Canesi: Our Z value is the ratio of
59:43:490Rubina Canesi: how important we think prestige is to conflict right? 10 to one a sorry good value.
59:53:350Rubina Canesi: Yeah. So the Z value is the 10, the 10 time I put before. Yes, so I thought that would mean prestige has a value of 10, and compact has a value of one.
00:03:490Rubina Canesi: So I think it was correct.
00:05:340Rubina Canesi: Yeah, I know we wasn't.
00:10:200Rubina Canesi: No now, like in in the slide in the slide which one
00:20:200Rubina Canesi: in the slide where we talked about the
00:23:160Rubina Canesi: the calculation of the Z value given the ratio. No, no, that very slight
00:28:680Rubina Canesi: this one. Okay, yes. Given the ratio, z ratio 10 equals 10.
00:34:405Rubina Canesi: I assume that the 10 was awarded to prestige, and one yes, yes.
00:45:110Rubina Canesi: so now it. It's it looks like it has been saved.
00:53:670Rubina Canesi: Why do you feel? Why, where do you feel it is split? I feel it is split there, because now I see the value of comfort is 10,
01:01:770Rubina Canesi: and that will be the strategic plan.
01:04:30Rubina Canesi: you know. Look at this prestigious standard.
01:07:650Rubina Canesi: Okay, yeah, no. That was the mistake that this this was reversed, but it was referred to. I put it in the right order here. So the calculation was right. It's just that this was, let's say, misleading, because it was the order of how you show from the best to the worst.
01:27:80Rubina Canesi: But it's not what was in the calculation. But let's say that the calculation was right. The structure we are following was
01:32:930Rubina Canesi: correct.
01:35:120Rubina Canesi: Sorry for the inconvenience, so I'll restart start again from comfort to Mpg.
01:41:610Rubina Canesi: We are considering the value one.
01:45:30Rubina Canesi: the number of cards plus one multiplied by the alpha value.
01:52:510Rubina Canesi: The price is
01:55:150Rubina Canesi: number of one plus the number of cards, plus one per alpha value, plus the number of cards
02:01:120Rubina Canesi: plus one per alpha value.
02:05:700Rubina Canesi: This one is not required is our 10. Okay.
02:09:330Rubina Canesi: But with this calculation, so number of cards plus one multiplied by the alpha value I have found. I now can calculate the value assigned to the other criteria in my ranking.
02:23:690Rubina Canesi: So this was the translating in numbers of the cards I have placed.
02:28:810Rubina Canesi: If in your example you put the 5 cards here, you see
02:40:740Rubina Canesi: the the values within this level he's changed.
02:45:840Rubina Canesi: If I put it, I can put as much card as I want. But just to show you. Okay. So now the distance from prestige, and price is
02:53:860Rubina Canesi: much bigger, because I put a hundred cards inside it.
02:58:480Rubina Canesi: Okay?
03:00:630Rubina Canesi: And if you said, for example, that it is 25, the proportion.
03:08:110Rubina Canesi: It changes our model, but is the same concept. It's just, it's just the measure I'm using
03:15:850Rubina Canesi: to consider the value.
03:17:730Rubina Canesi: Is it? Okay? This taboo? You want to see it again. It's a
03:24:170Rubina Canesi: okay, the waiting process. I will put again the value that we use in the example
03:32:50Rubina Canesi: just to make it simpler.
03:34:720Rubina Canesi: I sum this value, put it as a hundred percent and see what was the weight
03:42:250Rubina Canesi: in percentage of my of my criteria. Okay.
03:47:740Rubina Canesi: the sum is equal to 100. And this is the weight I'll just show you, be sure. So
03:57:630Rubina Canesi: 10 over the sum of the values I have found is 40%.
04:02:570Rubina Canesi: And so on.
04:05:120Rubina Canesi: Okay.
04:10:400Rubina Canesi: so this is what we have done with the criteria, with the criteria. And now for each criterion.
04:16:50Rubina Canesi: we would ask them to do the same thing.
04:24:780Rubina Canesi: So, for example, I have my criterion prestige.
04:33:710Rubina Canesi: I have my different levers.
04:39:270Rubina Canesi: Yes, from poor to excellent.
04:41:530Rubina Canesi: Okay.
04:45:350Rubina Canesi: I place the cards. So what I will ask you now is from poor below average, average above average and excellent.
04:54:200Rubina Canesi: How much card do you put
04:57:540Rubina Canesi: if you put any cards in your evaluation.
05:01:200Rubina Canesi: So let's say, for example, that in prestige
05:05:710Rubina Canesi: everything has the same. Let's say linear importance. So I put the 0 card, or an excellent card is a free time
05:14:570Rubina Canesi: better than above that the distance is 3 times than all the other levels. So I put this 2 cards to express this this level
05:25:280Rubina Canesi: and the same proceed with the same procedure. I calculated the alpha value.
05:31:250Rubina Canesi: which is the number of card place plus one for each time.
05:37:830Rubina Canesi: and I use the scale of that over 100. Okay, so my, my.
05:42:790Rubina Canesi: the way to express my scale was from 0 to 100 to make it simpler.
05:48:70Rubina Canesi: Thank you.
05:49:50Rubina Canesi: So we'll put everything now from 0 to 100, from the lowest and the highest value.
05:56:710Rubina Canesi: So here you see the formula, I show you how you calculate the alpha value in this problem? If I change the cards.
06:06:700Rubina Canesi: I will have to adopt the formula, because here, of course, it is fixed. Okay?
06:13:420Rubina Canesi: And it changes also the the alpha value. Now, it's not 11.
06:18:140Rubina Canesi: It's 1250. Okay, 12.
06:33:110Rubina Canesi: Are you following? It's okay.
06:35:130Rubina Canesi: Just yeah. Yeah.
06:37:490Rubina Canesi: Oh, 100 minus 0. Help me understand?
06:43:100Rubina Canesi: Yep.
06:44:330Rubina Canesi: is because I'm I'm not asking you. I'm not using anymore the proportion. And I have used before. But I'm using a standard from 0 to 100,
06:55:540Rubina Canesi: you could use it as a 1 0 to one or 0 to 10. I just use it as a 0 to 100, which is the maximum level
07:04:390Rubina Canesi: and 0 4.
07:07:10Rubina Canesi: The last previous case we use 10 to one. That's why it was 10 minus 100 0. So that's why it's 100 minus 0.
07:15:960Rubina Canesi: Yeah. But it's as I said before, it is a choice. Okay? So there is no right answer. You just have to be aware
07:24:650Rubina Canesi: the values you're missing, that you're measuring. Let's say, okay.
07:30:940Rubina Canesi: let's say that in this criterion, with the lowest performance I give 0 value.
07:37:300Rubina Canesi: This is the meaning of using this, of using this.
07:42:430Rubina Canesi: The calculation of the value of the judgment is given by the same.
07:52:890Rubina Canesi: So so as I don't know
07:55:880Rubina Canesi: so like when you were talking about earlier, when we were assigning the cards, and you said, no card means a value of one, a value of Alpha the value of Alpha. So when we were ranking like the most important one that we give 10.
08:10:900Rubina Canesi: Yes, does that mean, like our least important? Only one like one to 10? Or is it
08:16:430Rubina Canesi: like to calculate the yeah. Well, if I was giving you a substitution rate, so it was like 10 times this one.
08:25:120Rubina Canesi: which is one. Okay?
08:27:430Rubina Canesi: So in this example, the Z value is 1,200.
08:31:625Rubina Canesi: Yeah, no, it it. Yeah. Let's say that here is not the is not a substitution rate. It is.
08:39:790Rubina Canesi: let's say, the entire value we give to the prestige criterion.
08:44:359Rubina Canesi: Okay, okay, it's a total like level 1, 2, 3, 4, 5
08:51:620Rubina Canesi: it. It is a similar procedure. We are using the same calculate mathematical calculation. But to get another type of information, because the 1st one was, we are not asking how many times excellent is poor?
09:03:939Rubina Canesi: We are asking.
09:05:770Rubina Canesi: Given that prestige. Criterion has a value.
09:10:240Rubina Canesi: how much, how much value I give to, or below average above average and excellent.
09:18:700Rubina Canesi: Okay, yeah. And this according to level 1, 2, 3, 4, 5.
09:27:970Rubina Canesi: And I put it, of course, it is just the way I show you, but you could put it to the excellent above, the maximum above, and the, and of course adapt to the formula.
09:38:210Rubina Canesi: In this way it is the best is excellent. It is 100 and exactly exactly.
09:47:640Rubina Canesi: So. This is just to show you
09:50:29Rubina Canesi: a way to calculate it. Okay, so this. But
09:55:410Rubina Canesi: I will. I will have to ask you this information for each criterion and for the ordina for the ordina level. It's, let's say, an easy way
10:03:20Rubina Canesi: similar to the criteria. Okay, when it comes to the continues criteria, like the price
10:14:570Rubina Canesi: I have to show you how we, as an analyst, not you as a client. How we try to overcome this information.
10:22:280Rubina Canesi: how how we try to overcome this, let's say obstacle to our evaluation, because
10:28:530Rubina Canesi: I cannot ask you how much
10:31:460Rubina Canesi: one our scale is from 15 to €35,000.
10:37:750Rubina Canesi: How much is the 29
10:40:860Rubina Canesi: and dot 9? €9 is for you, it is very difficult calculation.
10:48:180Rubina Canesi: So we as an analyst, we create some range. Okay, some equal range of a file
11:02:640Rubina Canesi: of €5,000.
11:05:480Rubina Canesi: Okay?
11:06:350Rubina Canesi: And we ask you to put the cards between this this level of prices.
11:15:850Rubina Canesi: If I put a 0 card that doesn't mean that for me it has the same value. It means that it is a linear, let's say
11:27:660Rubina Canesi: the perceptual of the price. Okay.
11:31:970Rubina Canesi: so from a hundred to 0, from 15 to 35.
11:40:180Rubina Canesi: Now that I put the 0 card, it became, it became linear.
11:43:720Rubina Canesi: If I put again 1, 2, 1 0 card.
11:50:380Rubina Canesi: the graph evolvement. Now now I will show you which is the calculation behind this graph, which is very simple, but
11:56:460Rubina Canesi: the meaning is that
11:59:750Rubina Canesi: I gave us to the client the the client, to put some cards between the different levels. So from 15 to 20, compared to
12:08:770Rubina Canesi: from 20 to 25, how many, how many cards are?
12:17:540Rubina Canesi: And I have provided provided some values. Okay, I provided 1, 2, 1 0 cards.
12:24:220Rubina Canesi: Okay.
12:31:70Rubina Canesi: same. The maximum level is a hundred. If the card cost to 15,000, which is the best value.
12:38:50Rubina Canesi: the lowest price and the best value I can have 0 if it costs of 35.
12:48:500Rubina Canesi: Yeah, in this equation, what what means of p. 9.
12:56:750Rubina Canesi: So what means you have? P. 9.
13:00:170Rubina Canesi: In this question. Click this 100.
13:05:10Rubina Canesi: We oh, yes, in there. The YWP. 9.
13:09:900Rubina Canesi: Yeah, it is 0, it is 0.
13:14:470Rubina Canesi: Okay, this, as you asked before, we used one before. Now we use it. Let's say 0 to 10. Okay. But I didn't put it because it is a 0.
13:26:100Rubina Canesi: Okay? Because it is like, we are considering this 0 value you
13:32:840Rubina Canesi: between t, 9 through TT, 9,
13:36:130Rubina Canesi: yeah, exactly the TT, 10. Yeah, okay.
13:40:570Rubina Canesi: yeah, this I will. I will upload it again. Let's say the the excel with this correction. But the values are correct. Okay, it's it's just a formula that we're.
13:50:880Rubina Canesi: I said that they were working, but I removed some.
13:54:468Rubina Canesi: Let's say some values when they were 0 to not provided to to too much information that are not necessary.
14:03:20Rubina Canesi: But here, for example, with this placing cards between the level.
14:12:30Rubina Canesi: sorry between the level. I can calculate. If I put a 0 card, it is 25, okay.
14:21:700Rubina Canesi: 0 plus 1 0 plus 1 0 plus one a hundred 25.
14:27:490Rubina Canesi: So if you see the graphs perfectly, show you that it is 25, every level.
14:34:180Rubina Canesi: Okay, if I put some cards with this calculation, which is, by the way, sorry this 25 is.
14:48:400Rubina Canesi: Yeah is is, let's say it's just a simple placement of the number of cards in the graph. If I put again the the number.
14:58:110Rubina Canesi: the number of calls I have placed before you see how the it behave. Okay.
15:03:700Rubina Canesi: we have 85.7 62.25.
15:10:910Rubina Canesi: So with this interpolation between the level.
15:15:570Rubina Canesi: we will be able in the last steps to
15:19:550Rubina Canesi: give a value to the price of the car.
15:22:700Rubina Canesi: But this was a way to to
15:26:890Rubina Canesi: to consider the the continuous criteria. Of course it has some limitation, because
15:31:540Rubina Canesi: this range of 15 or 45 is a setting my problem if I use it from 5 to 80, I have to do it again, and I had also to
15:43:120Rubina Canesi: provide, let's say, equal equal in equal interval inside
15:50:390Rubina Canesi: to make to make this proportion, this interpolation working. Okay.
15:57:560Rubina Canesi: I will try to step forward. So we will, I say, reach the end of today, and maybe tomorrow we start again from
16:05:110Rubina Canesi: Just a recall of the Excel function and complete your assessment. But we do this card procedure for all the criteria.
16:14:370Rubina Canesi: So, for example, I will ask to do
16:18:170Rubina Canesi: for prestige between, above, between excellent above, average, average, below average and 4 replace a number of cards.
16:26:480Rubina Canesi: So the bold, the character is the maximum right? If you ask.
16:33:180Rubina Canesi: and after you have placed the cards you could complete, let's say the reconstructed model.
16:43:600Rubina Canesi: Going back to one of your initial questions. If I want to add an additional criteria, I have to
16:50:970Rubina Canesi: to build again the MoD to, let's say, adapt the model. Okay? Because I have to replace the cards.
16:57:320Rubina Canesi: I have to
16:58:550Rubina Canesi: calculate this in 5 levels in 4 levels or 6 levels, depending on how many, how many criteria you have to do, and the same is for
17:10:320Rubina Canesi: for the within each criterion. If I use the 9 scale of judgments of uhp, I have to resize, we can build it. But
17:19:390Rubina Canesi: it is another type of another amount of information. So
17:24:290Rubina Canesi: this is a limit of this kind of model.
17:28:170Rubina Canesi: So you have to adapt it to your choice. It could be reused if
17:33:140Rubina Canesi: other 1,000 students want to decide which car to buy with the this criteria. But if these models are very difficult to adapt sometimes. Okay.
17:48:900Rubina Canesi: So I have used the a placement of cards here. I have
17:53:860Rubina Canesi: assume the 0 here. If you see for criterion miles per gallon
18:00:370Rubina Canesi: is just, let's say reverse the if I
18:05:370Rubina Canesi: run the 20 kilometers per gallon is a 0 value. If I run 40 miles per gallon is a hundred.
18:12:80Rubina Canesi: If I place some cards between them, it changes.
18:23:360Rubina Canesi: Okay?
18:24:430Rubina Canesi: So you have a visual representation of your of- of the the.
18:32:200Rubina Canesi: the criteria, the criterion, and the placement of cards inside the criterion. Okay.
18:38:280Rubina Canesi: because I have given much value to this to this range, because if if it places there the consumption of gallon per
18:47:467Rubina Canesi: the the consumption of gallon per kilometers is, it's it's better for me. Okay.
18:53:440Rubina Canesi: I will evaluate it more and addition a marginal additional value.
19:00:380Rubina Canesi: Same for the last criterion comfort.
19:05:990Rubina Canesi: I put the wrong text because it is converted. Okay, excellent.
19:11:00Rubina Canesi: from poor. It's it's the reverse.
19:14:980Rubina Canesi: So I will change it and re-upload it.
19:25:410Rubina Canesi: Okay.
19:35:860Rubina Canesi: I will place some cards also here.
19:47:550Rubina Canesi: and just put in some cards to
19:50:120Rubina Canesi: provide an example. Hey? You can put your cars, for example.
19:57:180Rubina Canesi: So what we have now we have chosen our zeta ratio.
20:06:800Rubina Canesi: We have calculated our alpha value for the criterion.
20:10:980Rubina Canesi: We have the through, the cut placements assessed the weight of its criterion.
20:20:220Rubina Canesi: Within each criterion. I have placed the cards within the different levels.
20:29:630Rubina Canesi: It could be 0, or there could be differences, because I could express some preferences of I values
20:37:860Rubina Canesi: in one criterion, and now I can assess my
20:48:120Rubina Canesi: I can assess my car, and I have to translate these things in some values.
20:54:50Rubina Canesi: So, for example, this car, I don't know how they are in reality, but we assume that Akura Tl.
21:01:200Rubina Canesi: As an above average prestige, as a price of 33
21:08:240Rubina Canesi: as a miles per gallon, over 25
21:13:270Rubina Canesi: does 5, and it has an excellent comfort.
21:17:50Rubina Canesi: and so on, all the other, the other free alternatives.
21:24:40Rubina Canesi: One of the great advantage of this model is that us that you have us, that we have prepared the model. Now we are evaluating free cars, but if we are
21:33:800Rubina Canesi: adding another 100 cars within the same
21:37:600Rubina Canesi: within, with the same values, the model is already built. Okay.
21:45:870Rubina Canesi: now we we look at how much prestige
21:58:10Rubina Canesi: looks like in our scale value, built with the card placement.
22:06:320Rubina Canesi: So we can on a scale from 0 to 100
22:10:910Rubina Canesi: assign one numerical value to all the criteria I have done. Because.
22:16:350Rubina Canesi: okay, this was the last thing that was necessary to know that to calculate how much is.
22:25:170Rubina Canesi: how much is 33.
22:29:560Rubina Canesi: We use the the in.
22:41:120Rubina Canesi: Okay, how much is 33. We used the interpolation between 30 and 35.
22:49:450Rubina Canesi: Okay.
22:53:90Rubina Canesi: hey? This is a formula already built in excel. But in the slide there is also the calculation. We will complete the the with the slides.
23:02:300Rubina Canesi: These were the steps, of course, that we're missing is the how the model works. Okay? But with the interpolation, I know that 33
23:12:310Rubina Canesi: within 35 and 30 is almost here, which is a value from 0 and 25,
23:34:880Rubina Canesi: which is 10.
23:36:680Rubina Canesi: Okay, so you see that 33 is exactly 10 in the value if the car costs.
23:48:60Rubina Canesi: But before at 6.
23:56:960Rubina Canesi: Now the value became too.
24:00:350Rubina Canesi: Okay.
24:02:270Rubina Canesi: So along all this list, how how many detail. How many
24:07:60Rubina Canesi: regard, despite how many detail, is the price? Or we can have thousands of prices within this range and place it in our
24:16:600Rubina Canesi: 0 to 100 value for the price range.
24:23:320Rubina Canesi: So this 33 is converted in 10, this 25,
24:30:490Rubina Canesi: it's exactly 62.50.
24:34:620Rubina Canesi: If I change it to well, let's complete the 18.
24:39:890Rubina Canesi: Use it here, and it is a value.
24:48:250Rubina Canesi: It is a value just a little bit above 9, th 19,
24:54:780Rubina Canesi: so 87 point sorry it is.
24:58:540Rubina Canesi: it is not a little bit above it is 92,
25:02:740Rubina Canesi: and so on also for the mice per gallon. The same procedure
25:06:700Rubina Canesi: I have 25 dot. 5,
25:10:270Rubina Canesi: and through the interpolation I can calculate
25:14:410Rubina Canesi: the value of the 29 dot 29.
25:18:260Rubina Canesi: There is one step missing, then it is waiting these results, because now I have provided
25:26:820Rubina Canesi: a numerical value from 0 to a hundred
25:30:330Rubina Canesi: to each of the criterion, and each of the values of the cars within the Criterion.
25:38:760Rubina Canesi: We have already calculated the weights, and we just have to multiply
25:50:330Rubina Canesi: the prestige value for the weight of the criterion prestige.
25:57:610Rubina Canesi: See
26:02:320Rubina Canesi: same for price, save for Npg.
26:07:920Rubina Canesi: And for confidence.
26:09:770Rubina Canesi: This is the meaning of giving comfort the lowest level, which is, even if you're performing a hundred.
26:20:390Rubina Canesi: even if performing a hundred the value of the criterion.
26:25:70Rubina Canesi: It's very low.
26:28:320Rubina Canesi: In my evaluation. I will have
26:31:480Rubina Canesi: a ranking provided by the sum of this criterion.
26:40:40Rubina Canesi: So given this.
26:42:860Rubina Canesi: Given this criteria, given this card placement, I have built an entire model to support the decision. And now I can tell you that
26:52:170Rubina Canesi: Toyota, now an example is the best choice for you.
27:01:160Rubina Canesi: Is it convincing you?
27:03:460Rubina Canesi: The difference between 2 and 5 is very low. Yeah, okay, let me stay.
27:11:240Rubina Canesi: This. This is a good point.
27:14:350Rubina Canesi: Of course, the numbers say this. Okay. So in this case, Toyota is
27:21:810Rubina Canesi: the best with very few points.
27:24:930Rubina Canesi: What happens in this case here I mentioned a ranking problem. So we are just saying which is the best car.
27:34:740Rubina Canesi: and we are building a ranking.
27:37:990Rubina Canesi: There could be another possibility depending on the type of problem they want to do. It could be a classification, a sorting, a grouping problem. Okay?
27:47:10Rubina Canesi: So for example, if I say that I want to buy cars that reach only a point over 50,
27:56:390Rubina Canesi: or the 1st class cars are the one that reached the point over 70 and
28:07:30Rubina Canesi: the lowest over below, from 20 to 50 to 70, and the lowest from 20 to
28:14:470Rubina Canesi: 2 0. I I have a free classes, and I could insert the car in a class.
28:20:240Rubina Canesi: but depends on the problem you are facing here, even if the distance is very is very low, and
28:28:220Rubina Canesi: I suggest you to choose a Toyota.
28:31:60Rubina Canesi: But of course this, if you look at the characteristics of the car.
28:36:310Rubina Canesi: we are comparing a car that is is average, and
28:42:690Rubina Canesi: with a car that is below average. The consumption are
28:48:110Rubina Canesi: the so sorry. The the price is much higher for the Toyota, and but on the civic perform in the miles per gallon. Okay? So if we change the weight of the criteria.
29:03:780Rubina Canesi: our result will change. If I provide 6. Cardia
29:13:410Rubina Canesi: now on the civic is the better.
29:16:390Rubina Canesi: Why? Because comfort, for example, is the criteria that
29:28:250Rubina Canesi: give more weight.
29:31:600Rubina Canesi: Sorry the distance between sorry, the distance between
29:35:468Rubina Canesi: mile per gallons and comfort have more weight.
29:39:600Rubina Canesi: So, for example, the performance of my best gallon.
29:43:260Rubina Canesi: which is very high in the Honda.
29:46:780Rubina Canesi: is much better than the the below average performance of comfort, which now became very low.
29:54:920Rubina Canesi: If I do another things next one here and deeper evaluate.
30:06:470Rubina Canesi: Now Toyota cami begin again. The best Akura became the other.
30:12:980Rubina Canesi: but all them became below average. They're sorry, be below 50.
30:17:880Rubina Canesi: So it depends on the type of problem. So here I call it ranking. But
30:22:610Rubina Canesi: it could be a classification problem.
30:25:870Rubina Canesi: Okay? So
30:28:980Rubina Canesi: yeah, this is not a fixed law. Okay, it's not. It is a way to try to translate
30:36:740Rubina Canesi: evaluations. The expressions of preferences in criteria, within the criteria, etc. In numbers.
30:45:870Rubina Canesi: maybe the results is that I don't like to buy any of this car because it is so low performing that given this criteria is is not enough, but if I put the price here of 16
31:01:350Rubina Canesi: and the miles per gallon, 2 50.
31:06:500Rubina Canesi: Now to your account. No? Sorry. I made some mistakes.
31:10:120Rubina Canesi: Yeah, because it goes outside of the of the of the range.
31:23:870Rubina Canesi: See that
31:25:480Rubina Canesi: are changing the perform the the performances of that car changes. If I change, or if I had another car, that is super performing other aspects, it will get an higher, an higher evaluation.
31:39:470Rubina Canesi: Okay, so this is how the the model works.
31:46:220Rubina Canesi: I am showing you what it is behind this model. But if we stick to what I have asked you as a client. I have asked you to rank the criteria.
31:56:710Rubina Canesi: to express some preferences with the card between the criteria.
32:01:970Rubina Canesi: I to I asked you the ZZ. Ratio, to have the substitution rate.
32:08:420Rubina Canesi: and I have asked you to do the same within the criteria
32:12:980Rubina Canesi: by placing cards. I didn't ask you to know about anything
32:17:810Rubina Canesi: about the price of cars, the how much comfortable could be different cars. Maybe you're not an expert in these things, and maybe you're not an expert in evaluation models.
32:29:950Rubina Canesi: Every model has its pros and cons.
32:32:860Rubina Canesi: For example, HP. Is very commonly used, very well structured sometimes with software and all the things you have to express a value, a judgment with the
32:43:780Rubina Canesi: very good, very bad, between each level.
32:47:00Rubina Canesi: which sometimes it's easier sometimes could be a very mentally expensive process.
32:54:630Rubina Canesi: Okay, so this is just to give you an example of a similar problem required some adaptation, because
33:02:50Rubina Canesi: models work differently. Okay?
33:04:630Rubina Canesi: But by asking you to place in cards.
33:08:970Rubina Canesi: I can give you an answer that Toyota.
33:12:330Rubina Canesi: Toyota, Camry, is the one you you could. You should choose expressing this value.
33:19:970Rubina Canesi: And if we compare a list of a hundred cars, we could
33:26:130Rubina Canesi: just you within these values, we can make a ranking of a hundred cars without building another model.
33:34:240Rubina Canesi: Okay?
33:35:120Rubina Canesi: Of course, if you are asked to compare a free type of construction project as your colleague mentioned at the beginning, maybe price become the most important criteria, and if you are the one who is financing this construction project, you have this range. You are comparing the projects you
33:51:900Rubina Canesi: you have. You want to spend it much, much more. And
33:56:360Rubina Canesi: and then you give more cards to the credit and maybe give more cards to
34:01:500Rubina Canesi: the distance between that range of price to the other range of price.
34:06:570Rubina Canesi: because it's not the linear. Let's say the
34:09:920Rubina Canesi: from the low, the best to low to the worst criterion.
34:15:780Rubina Canesi: Okay, so this part behind is not so not so easy. But once you have understood how it works, I think it's it's much easier to see how you could reach this kind of value.
34:28:920Rubina Canesi: and of course you can adapt it to other kind of problems, and using the cards as a as a tool to overcome this information.
34:37:840Rubina Canesi: I will stop here today, maybe tomorrow we'll
34:42:40Rubina Canesi: yeah. We just record these concepts and complete this part.
34:47:920Rubina Canesi: Thank you.
34:49:720Rubina Canesi: Let's see, okay.