...Decision Analysis Model and Report JaKaiser Smith Southern New Hampshire University Date: 07/09/2015 Abstract In this report following resources have been utilized to establish a relationship between Retail Salesperson’s salaries and their intent to shoplift at their own workplace: * The Larceny theft data from Federal Bureau of Investigation’s official website for the years 2011, 2012 and 2013; * 25th and 26th Annual Retail Theft Surveys by Hayes International for the years 2011, 2012 and 2013; * National Conference of State Legislatures website for Labor and employment data for the years 2011, 2012 and 2013. ‘Shoplifting’ is undoubtedly a psychological issue for most of the people. Shoplifting for most individuals is rarely about greed or poverty. It’s about people struggling with their own personal conflicts and needs. There are approximately 27 million shoplifters (or 1 in 11 people) in the USA today. More than 10 million people have been caught shoplifting in the last five years. The pleasure produced from “getting away with it” yields a chemical reaction causing in what shoplifters describe as an incredible “rush” or “high” feeling. Many shoplifters have committed to the fact that this high is their “true reward,” rather than the stolen product itself. It is assumed in this project that all the shoplifting instances in different states of the USA have been performed by the front-end Retail Salesperson. This might not be 100% true as the members...
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...Presenter Notes for Power-point Decision Analysis Task 4A-E A. (Slide 1) Gloria Rodriguez, Shuzworld's retail development specialist, was looking at some possibilities of placing a Shuzworld store into a major target area and has three options to consider. The first option is to build a proposed stand-alone store, the second option is to open an Auburn Mall store, and the third option is to do nothing at the moment. (Slide 2) With the information given from Ms. Rodriguez, the stand-alone store could see profits for a favorable market of seven hundred thousand dollars; if the market was unfavorable the losses would be four hundred thousand dollars. The Auburn mall could see profits for a favorable market of three hundred thousand dollars, and if the market was unfavorable the losses would be fifty thousand dollars; this is having a probability of fifty-fifty for both choices of a favorable and unfavorable market. Of course, not doing anything or not opening a store, Shuzworld would not suffer any losses or make any profits. Shuzworld is considering market research and this can produce positive or negative impacts on the market or not purchase the research at all to have no effect. To purchase the market research it would come with a price of twenty thousand dollars with a sixty percent chance towards a favorable market and a chance of an unfavorable market of forty percent. Having a favorable market, if the survey is positive, can cause an incline to seventy percent...
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...Chapter 14 Decision Analysis Learning Objectives 1. Learn how to describe a problem situation in terms of decisions to be made, chance events and consequences. 2. Be able to analyze a simple decision analysis problem from both a payoff table and decision tree point of view. 3. Be able to develop a risk profile and interpret its meaning. 4. Be able to use sensitivity analysis to study how changes in problem inputs affect or alter the recommended decision. 5. Be able to determine the potential value of additional information. 6. Learn how new information and revised probability values can be used in the decision analysis approach to problem solving. 7. Understand what a decision strategy is. 8. Learn how to evaluate the contribution and efficiency of additional decision making information. 9. Be able to use a Bayesian approach to computing revised probabilities. 10. Know what is meant by utility. 11. Understand why utility could be preferred to monetary value in some situations. 12. Be able to use expected utility to select a decision alternative. 13. Be able to use TreePlan software for decision analysis problems. 14. Understand the following terms: |decision alternatives |decision strategy | |chance events |risk profile...
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...2-1 2.1 Decision Analysis: Expected Value of Perfect Information (EVPI) The Expected Value of Perfect Information (EVPI) will be explained with the following example: Example: “Flip the Coin Game” Richard has to decide whether to play a game of “flip the coin” with Karin. The game is as follows: If the coin ends up heads Karin pays Richard one dollar and if the coin ends up tails Richard pays Karin eighty cents. What is the most Richard should pay a clairvoyant (look up this word if you do not know its meaning) to tell him whether the coin will turn up heads or tails prior to the next toss? In the figure below we portrayed Richard’s initial decision problem (the endpoints are Richard’s payoffs in cents). Heads (.5) 10 Tails (.5) Do not play the game Figure 2.1. Decision Tree (without perfect information) It is not hard to calculate that without perfect information Richard should decide to play the game, assuming he is using EMV as his decision making criterion. The EMV for this decision is ten cents. Of course, if a clairvoyant would tell Richard the outcome of the next toss, Richard would play the game if told “heads”, but would not play the game if told “tails”. However, Richard has to pay the clairvoyant before the outcome will be disclosed. How much should Richard pay for this perfect information? IT IS IMPORTANT TO NOTE THAT THE CLAIRVOYANT CAN ONLY TELL WHAT THE OUTCOME OF THE NEXT TOSS WILL BE. HE IS NOT ABLE TO INFLUENCE THE TOSS. (Think about this before reading on...
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...MAT 540 Week 2: Decision Analysis |Slide # |Topic |Narration | |1 |Introduction |Welcome to Quantitative Methods. In this lesson, we will discuss the concept of decision | | | |analysis, a valuable technique for decision making process. | | | | | | | |Please go to next slide. | |2 |Objectives |When you complete this lesson, you will be able to: | | | |Analyze decision-making problems electronically. | | | | | | | |To meet this outcome we will cover the following supporting topics: | | | |Components of decision making; | | | |Decision making without probabilities; ...
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...Business Intelligence and Decision Making of Successful Women Entrepreneurs in Northern States of Malaysia Heng Man Chia, Tan Wen Pei, Lim Wang Ru and Yew Bee Jue (2012,UUM) ABSTRACT Women entrepreneurs increasingly become the important role and make a contribution to the economics of the country. The main purpose of this paper is to determine the effects of business intelligence and decision making to the successful women entrepreneurs. This research is mainly focused on the women entrepreneurs in the Northern States of Malaysia as there is no previous research are done in this study. Currently, the government had provided the incentives to support the women entrepreneurs in their business activities. There are plenty of women set up their business in the Northern States of Malaysia. The quantitative methodology used by the researchers in this study based on 95 women entrepreneurs, engaging in their business in the Northern States of Malaysia. The business they engaged mostly in the food industry. The findings of this research indicated that the business intelligence and decision making has not influenced the women entrepreneurs that lead them to success. There are other factors that lead to women entrepreneur success. They might depend on their intuition or advice from others. Most of them are running the micro enterprise. The women entrepreneurs concerned the significance of the education. A discussion on the demographic profile of women entrepreneurs is also provided...
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...|Decision-Making Analysis[1] | The Components of a Decision Problem 2 Decision Making under Uncertainty 3 Maximax Procedure 3 Maximin procedure 4 Equal Likelihood Procedure 5 Minimax Regret Procedure 5 Decision Making under Risk 6 Maximizing Expected Gain 6 Minimizing Expected Regret 7 The Expected Value of Perfect Information 8 Summary 17 Discussion Questions 18 Solved Problems 18 Problems 24 Key Terms 31 |The Components of a Decision Problem | The three basic components of a decision problem are the decision alternatives; the possible environments, conditions, or states of nature within which a decision is to be implemented; and the outcomes or payoffs that will result from each possible combination of alternatives and states of nature. The decision alternatives are those actions from among which the decision maker must choose. That is, they are the aspects of the decision situation over which the decision maker has direct control. The states of nature are those aspects of the decision situation over which the decision maker does not have direct control. They certainly include things over which there is no control, such as the weather, the general state of the economy, or actions taken by the national government. They may also include things which can be influenced to some extent but not completely. The market response to a new product (which is partly determined by...
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...Science, 10e (Taylor) Chapter 12 Decision Analysis 1) A state of nature is an actual event that may occur in the future. Answer: TRUE Diff: 1 Page Ref: 527 Main Heading: Components of Decision Making Key words: state of nature 2) A payoff table is a means of organizing a decision situation, including the payoffs from different decisions given the various states of nature. Answer: TRUE Diff: 1 Page Ref: 527 Main Heading: Components of Decision Making Key words: payoff table 3) The maximax criterion results in the maximum of the maximum payoffs. Answer: TRUE Diff: 2 Page Ref: 529 Main Heading: Decision Making without Probabilities Key words: maximax criterion 4) The maximin approach involves choosing the alternative with the highest payoff. Answer: FALSE Diff: 2 Page Ref: 530 Main Heading: Decision Making without Probabilities Key words: maximin criterion 5) Regret is the difference between the payoff from the best decision and all other decision payoffs. Answer: TRUE Diff: 2 Page Ref: 531 Main Heading: Decision Making without Probabilities Key words: minimax regret criterion 6) The minimax regret criterion minimizes the maximum regret. Answer: TRUE Diff: 2 Page Ref: 529 Main Heading: Decision Making without Probabilities Key words: minimax regret criterion 7) The minimax regret criterion maximizes the maximum regret. Answer: FALSE Diff: 2 Page Ref: 531 Main Heading: Decision Making without Probabilities Key words:...
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...Decision Analysis: Decision analysis is a set of quantitative decision making techniques for decision situations in which uncertainty exists. Now, uncertainty can be classified into two ways/ types: 1. Subjective Probability: Subjective probability is the degree of belief to occurrence of the event. 2. Objective Probability: Objective probability is the probability which can be derived either based on historical occurrences or based on experimentation. Alternatively can be derived from statistical formula. Consistency requirement: If the probability of an event A is 0.65, then the probability of event B must be 0.35. i.e. P(A) + P(B) = 1 Mathematically, if A, B Є E Then A, B [pic] E A [pic]B = φ P(A) + P(B) = 1, which is called Consistency requirements. # Elements of Decision Problems: A decision problem is usually viewed as having four common elements 1. The alternative course of action: The alternative course of action involves two or more options or alternative course of action. One and only one of these alternatives must be selected. 2. The states of nature: The state of nature are factors that affect the outcome of a decision but are beyond control of the decision maker, such as rain, inflation, political development etc. 3. Payoff table: A payoff table is the combination for each possible combination of alternative course of action and state of nature...
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...DECISION MODELS Decisions Making Under Uncertainty Decisions Making Under Risk 1. Max-Min Criteria (pessimist) 1. Expected Payoff (Average) - Best of the worst A. Multiply payoffs by probabilities and -Becomes (Min-Max) if loss table add up. (For each action separately) A. Find min (max) in each row B. Pick best action B. Pick the best of the Max (Min) 2. Expected Opportunity Loss A. Set up loss matrix -Subtract all numbers in each column Criteria Max-Max Criterion (Optimist) from the largest number in that column -Best of the best B. Find average opportunity loss Becomes (min-min) if loss table for each action. A. Find max (min) in each row - multiply the probability time loss and B. B. Pick the largest (smallest) add up. C. Pick smallest number (want to min loss) 3. Most Probable State of Nature 3. Weighted Average Criterion A. Determine the most probable state of nature - Coef. of Optimism = α (one with highest probability) - Optimistic=1, pessimistic=0 A. Calculate weighted value B. Pick the action with the highest expected α (best) + (1 - α) (worst) payoff. B. Pick best value C. Good criteria for a non-repetitive Decision 4. Minimizing Regret 5. Expected Value of Perfect Information - Savage opportunity...
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...HW3 – Due 02/14/2015,11:55PM on Moodle Please submit your answers in Moodle as one Word file, named HW3_FirstnameLastname.docx, that includes the complete solution to these problems, including your decision tree and final conclusions about the recommended decision. Please also post the corresponding Excel file that contains the decision trees to these problems, one per worksheet, clearly labeled with the problem number. TOTAL: 100 points 1. The NC Airport Authority is trying to solve a difficult problem with the over-crowded Raleigh-Durham airport. There are three options to consider: A. The airport could be totally redesigned and rebuilt at a cost of $8.2 million. The increased revenue from a new airport is in question. There is a 70% chance this would be $11 million, a 20% chance it would be $5 million, and a 10% chance it would be $1 million, depending on whether the airport is a success, moderate success, or a failure. B. The airport could be remodeled with a new runway for a cost of $4.7 million. The increased revenue would be $6 million (80% chance) or $3 million (20% chance). C. They could do nothing with the airport and suffer a loss of revenue of either $1 million (65% chance) or $4 million (35% chance). Construct a decision tree to help the Airport Authority to maximize the profit. (30 points) 2. Nagyteteny is a Hungarian soccer club. The management team is considering three options to improve the team’s performance, attract more spectators but mostly to make some...
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...Britanie Baker Decision Making Analysis Summary April 27, 2015 MGT/230 Ronald Sprague Decision Making Analysis Summary “The business executive is by profession a decision maker. Uncertainty is his opponent. Overcoming it is his mission” John McDonald. This statement is the best description for Anne Mulcahy. CEO of Xerox, Anne Mulcahy, is a very successful CEO who started her made her way up the corporate latter starting in sales. Anne Mulcahy was dedicated to the success of Xerox, and had to make difficult decisions in order to make the company see growth in profits again. In order to fulfill her vision of the success of Xerox she had to sell divisions, and lay off employees. All though these were tough decisions to make Anne had to do what was necessary to save Xerox from bankruptcy. Ms. Mulcahy cut a billion in cost in her first year as CEO. She also made the executive decision to put money into new technology as a way of reinventing Xerox. During week two Learning Team A had to answer questions based on this information. Learning Team A discussed how Xerox embraced characteristics of taking risk, and characteristics of managerial decisions. Throughout the discussion it was clear that most of the team members in Learning Team A agreed that Xerox embraced risk taking. The reason for this is that Xerox was on the verge of falling into bankruptcy. In order to save the company Anne Mulcahy had to cut, terminate positions, and sell divisions in order to...
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...Decision Making Analysis Shon Kele MGT/230 August 28 2015 Steve Brennan Decision Making Analysis In every organization there is a golden goose. There is a hidden talent that most times is over looked and the potential of that individual is never unleashed. But there are a few that gets past with the vision of someone seeing potential, passion, and pride. Anne M. Mulcahy, was just the person Xerox was looking for. Potential, Passion, and Pride From reviewing the video in this week’s lesson, Anne Mulcahy was a sister of a brother whom worked for Xerox and thought it would be a great opportunity for his sister to work there. She did just that, and like everyone else would have to start from the bottom. An English Major who started off in Sales has worked her way up the cooperate ladder and was definitely making a name for herself. She became the head of human resources where I believe is an amazing place to work. I mean what better way to learn about the company and the people behind the scenes. Soon afterwards she developed a desktop printer division. Lastly, the final stepping stone was a former CEO by the name Paul Allaire, saw great things in Anne Mulcahy and requested she be put into company president positon and a molding tool for a shot at CEO. Making a difference Paul Allaire, saw so much potential in Anne Mulcahy, he appointed her President of Xerox where she worked a few years and soon became CEO. While at CEO, she had a few situations...
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...Decision Making Analysis Discussion Summary MGT/230 09/07/2015 Decision Making Analysis Discussion When Ann Mulcahy became the CEO of Xerox she was born into an environment full of conflict and strife. Inheriting a disastrous mess and the company drowning in debt, she had to make bold, decisive decisions that took the company away from its’ entrenched way of doing things. Conflict was definitely one of the characteristics of management that Mulcahy dealt with when she became the acting CEO of Xerox. Mulcahy had been with the company for thirty years and had held various positions in human resources, sales, and was the creator and leader of a desk jet printer division. In the video it says that Mulcahy considered the people of Xerox to be her family. This fact must have taken a heavy toll when she needed to make decisions about cutting costs and restructuring the company. Within the first year of Mulcahy taking over she cut one billion in costs, and included in that one billion was the deskjet printer division that she herself created. Job elimination was certainly part of Mulcahy’s plan to reduce costs, the source material does not specify whether or not employees were repurposed to different divisions or if many were subject to straight layoffs or if it was a combination of the two. It was fortunate that Mulcahy had a wealth of knowledge of how different departments operated before she became CEO. Having a from the ground up background with the company undoubtedly gave...
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...Customer Interview Assignment – Magazine Purchase Decision-Making Process Demographics Gender | Male | Rough income level : upper middle | Age | 37 | for this study: low = less than $20K, lower middle = $20-50K, upper middle= $50-100K, high = $100K | Marital Status | Married | | Target Market Fit A magazine subscription that included online access to current and archived article | Low | A magazine subscription that included access to articles on a reading device (i.e. Kindle, iPad) | Low | One-off, on demand purchases of magazine issues on a reading device (i.e. Kindle, iPad) | Low | DMP Description: Customer Decision Making Process (DMP) is really a very complicated process. Different customer will show difference expression during the process. The objective of this survey is to find out how customers make decision when they want to purchase magazines. Based on my interview and the DMP mode, analysis of this customer is as below: Life part: The internal fact to impact on this customer’s choice is this customer loves to know every single thing about fashion. Apparently, he is not satisfied by only searching data through internet. He wants to hold real magazine on his hand to enjoy the knowing process about information. That is why he likes to buy several magazines each month. The fact, he knows his needs very well, gives meaning, purpose and relevance to what he do. The external fact on this part is this customer connects to fashion industry closely...
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