Tuesday, November 26, 2019
Carbohydrates in Society essays
Carbohydrates in Society essays Among the common fads and trends our society has seen in the past few years, a rather unlikely one would be that of carbohydrates. Carbohydrates provide our bodies with our basic source of energy to carry on day-to-day functions. Americans seem to be fascinated by the role that they play in our diets and the impact that they have on the body. What exactly is a carbohydrate? It is defined as 1. Any various compounds composed of carbon, hydrogen, and oxygen such as sugar and starch. All living organisms use carbohydrates as a fuel for energy. To obtain such, as humans we get our carbohydrates from eating foods such as breads, pastas, fruits and vegetables. Our bodies then digest the food and then convert it to glucose C6H12O6. In cellular respiration, cells take the energy that is stored in glucose molecules. The skeleton left behind is used for the synthesis of other molecules like amino acids and fatty acids. Carbohydrates are organized into three different groups, Monosaccharides, Disaccharides, and Polysaccharides. You might ask, What is the difference? Isnt a carbohydrate a carbohydrate? Each one is composed of glucose, but the amounts of glucose are completely different in each one. A Monosaccharide is made from a single glucose molecule. Disaccharides are formed from the linkage of two Monosaccharides. Finally, Polysaccharides are a product of a few hundred to a few thousand Monosaccharides linked together. Often, Polysaccharides are used for protecting a cell. Another common function for a Polysaccharide is that of storage. For storage, plants produce Starch, another form of a carbohydrate. Dr. Robert Atkinson famous for his book, Dr. Atkinsons New Diet Revolution, has sold millions of copies based on his world-renowned diet. He takes the ideas of low carbohydrates in place of low fats and calories, and incorporates high proteins and nutrients for a winning combination that has worked ...
Saturday, November 23, 2019
A Man is Not a Widow (Widow vs. Widower)
A Man is Not a Widow (Widow vs. Widower) A Man is Not a Widow (Widow vs. Widower) A Man is Not a Widow (Widow vs. Widower) By Maeve Maddox Last night, not for the first time, I heard someone refer to a man as a widow. Not only did I hear this usage, I saw it headlined across a Powerpoint slide at the presentation I was attending. In English a widow is a woman whose husband has died. A man whose wife has died is a widower. As widow is feminine in meaning, the regional expression widow woman is a tautology. That is, it says the same thing twice. Another tautology inscribed on a subsequent slide at this same meeting was the 100th Year Centennial. A centennial is the observance of a 100 year anniversary. Ex. The city council announced that the town would observe the centennial of its founding. TIP: As I urged in one of my very first articles for DWT, Let the Word Do the Work! Here are some examples of the redundant widow woman usage around the web: I am 28 year old man.I am attracted by a widow woman who is interested to talk with me deeply. What can I do? Quora.com I read in the paper that Jesse James held up a train and when he found out a widow woman who was on the train didnt have any money to give him Book In 2017 a movie titled The Widow Man was released, probably increasing the confusion on peoples minds. The careful writer will observe the distinction and avoid the redundancy when using widow and widower. Want to improve your English in five minutes a day? Get a subscription and start receiving our writing tips and exercises daily! Keep learning! Browse the Misused Words category, check our popular posts, or choose a related post below:15 Terms for Those Who Tell the Future55 Boxing Idioms5 Ways to Reduce Use of Prepositions
Thursday, November 21, 2019
Discussion Essay Example | Topics and Well Written Essays - 250 words - 45
Discussion - Essay Example Therefore, John is intelligent in Mathematics. It can be observed that the difference between the two reasoning can be defined by its falsifiability. Inductive reasoning permits the possibility that the conclusion of the proposed premises can be incorrect in that it is only a probability and could be disproved by solid evidence in the future. Deductive reasoning, in contrary, does not only rely on the soundness of the proposition but also in its validity. When a hypothesis is valid, it is impossible for it to have a false conclusion. It could lack soundness but it will retain its validity. That is why, Karl Popper’s strategy of disconfirmation is better in a sense that it considers hypothesis according to its falsifiability – a quality that every hypothesis is testable and that if something is wrong among and within its premise, it will manifest itself eventually. 2. The condition clearly involves conflict of interest as well as an ethical dilemma: there is a clear ambi valence on the part of Mary on whether to steal or not; to be altruistic or egoistic. One should remember that there is no justification for stealing. Stealing is morally wrong; nevertheless, to die because of starvation is likewise wrong. Hence, a conflict of interest arises. Mary has no choice to stay morally right at all; she is caught in the middle. Since to steal and to die of starvation are both wrong, one can choose to commit one wrong to prevent the other from becoming morally wrong. She should steal food so that his children don’t die of starvation. That way, there is only one wrong
Tuesday, November 19, 2019
T-Moblie Essay Example | Topics and Well Written Essays - 500 words
T-Moblie - Essay Example public, Austria, Hungary, Croatia, Montenegro, Macedonia, Poland, the Netherlands, United Kingdom and the Slovakia– including the US Virgin Islands, US, and the Puerto Rico. On the global level, the International subsidiaries of T-Mobile possess total subscribers which are roughly 150 million in number, which makes it the twelfth-largest service provider of mobile phone in the entire world in terms of subscribers. Besides this, T-Mobile bags the rank of the third-largest multinational and stand after Spains Telefà ³nica and UKs Vodafone. T-Mobile, in the year 2010, became the segment of the agreement of joint venture with the UK mobile-network provider of France Telecom, Orange UK. These companies combined and formed the largest mobile-network operator of UK and called itself Everything Everywhere. However, even after forming the joint venture, the Orange brands and T-Mobile go on to co-exist in the markets of United Kingdom. T-Mobile complies with all the laws which are applicable to the state and federal codes of laws and regulations. The management of the company does not indulge in any activity which violates the policies of the company such as non-retaliation, non-discriminatory and non-harassment policies. The unacceptable conduct in the company constitutes of violation of company laws and policies, removal of the property of company without permission, willful or neglectful damage or defacing of the company property, dishonesty, fraud, improper record keeping and all the related activities. Any criminal conviction amongst the employees results in their termination from the company. Besides this, all the secret trade laws and other legal information are kept confidential from others except the concerned parties. The company makes the decisions in the business by giving proper consideration to the social, ethical and legal regulations. The T-Mobile makes returns to the society through the afterschool community outreach program. The company makes efforts to
Sunday, November 17, 2019
Thinking About Rewards Essay Example for Free
Thinking About Rewards Essay From the article entitled Dump the Cash, Load On The Praise, why is salary alone not a motivator?            According to the article, while money has its merits and value, it is often not enough. Studies show that employees have always valued other things more than money. These other things include: verbal and non-verbal affirmations and praise of performance; the respect of colleagues and peers; feeling that one is making a contribution; having interesting work, and; getting involved in and being informed about whats happening within the company.            The article explains that recognition is vital in boosting an employees esteem, which would in turn improve his/her performance. Recognition makes the employee do something special because he/she knows that someone will notice and someone will care.            In contrast, relying on money alone will get the work done. But it is not necessary the employees best work. It was also found that in this situation, employees often do their least, and do not go above and beyond expectations.            In addition to money, the article suggests a compendium of motivators praise, recognition, promotion and growth opportunities, and challenging work. After reading Nelsons top ten ways to motivate todays employees list, identify five suggestions from that list that would be effective strategies to use to motivate you as an employee. Explain.            Be willing to take the time to meet with and listen to employeesas much as they need or want. This is most important to me at my current job, because above all, I need to learn about the job. Having regular discussions with my boss would not only help me in the learning process, it also gives me a chance to clarify some things, as well as, provide an indicator of my progress.            Provide specific feedback about performance of the person, the department and the organization. Basically, for reasons the same as above. Only this would also provide me with a glimpse of what values, attitudes and performance indicators are getting more weight. It also helps me learn more about the company, the people and the dynamics.            Strive to create a work environment that is open, trusting and fun. Encourage new ideas and initiative.  I like to work in an environment where I dont feel the need to conform to everyone elses expectations. And since I am new, I expect to contribute some systems that I have learned in the past. I want to be able to try out these systems without any fear of making mistakes, the same mistakes that we all can learn from. I would like to be able to express ideas and not be shot down without getting heard.            Involve employees in decisions, especially when those decisions affect them. I think its only fair to involve me in decisions about things that would affect me, both on a personal and professional level. That way, I can share my situation and opinions. It would also make me feel like my inputs are important, while giving me an opportunity to better understand the issue from the managements perspective.            Give people a chance to grow and learn new skills. Show them how you can help them meet their goals within the context of meeting the organizations goals. Create a partnership with each employee. Probably, the first thing that would make me leave is a sense of stagnation the feeling that I am no longer learning or the things Im doing is getting routine. From the Getting Happy with the Rewards King article, do you agree with Bob Nelson’s position that â€Å"while money is important to employees, thoughtful recognition motivates them to perform at higher levels?†Contrast Nelson’s perspective with that of Alfie Kohn in the For Best Results, Forget the Bonus article where he argues that rewards don’t work.             I agree with Nelson when he says that money is not everything, and that recognition motivates people to work at higher levels. I have seen this happen many times at work, with myself, or with my colleagues. Ive seen it happen in school.            It is also intuitive, and common sense. You cant get anything from beating a dead donkey. In the same manner that you cant get the best work out of a demoralized employee. Recognition builds the employees self-esteem, and shows him/her what is important in the organization. It helps him/her create positive relationships with colleagues and superiors.            Nelsons empirical ideas is backed by years of experience in human resources.            Kohn, on the other hand, drives home the point that the effect of rewards is, at most, temporary. Kohn argues that rewards are more like punishment. However, unlike Nelson, Kohns arguments are not rooted in research, or empirical observations. In fact, Kohns ideas run contrary to what Ive seen and learned thus far.            Sure, Kohn cites studies but fails to name them. I feel that the conclusions derived from these studies (if they do, in fact, exist) are either limited, or erroneous. Organizational behavior is a complex phenomenon that its difficult to weed out extraneous variables, even in most experimental settings. Kohn relates the findings found at an unnamed Midwestern company, where an incentive system was taken out. At first, Kohn says, the production went down as expected, but in the long term, production rose to a level at par or higher than before. Since the study was not actually named, we could only judge it from what Kohn wrote. Firstly, it seems simplistic that an experience or result at one company should apply to the general population. Secondly, Kohn failed to eliminate other causes, like the workers learning more about their processes or additional machinery acquired, and other things. For me, Kohns cited studies seem largely unscientific and and their applications are profoundly limited.            However, Kohn succeeds in explaining why recognition should work. Ironically, by comparing recognition and punishment, Kohn showed us that recognition as a catalyst for behavioral change has the same impact as punishment. We all report to work on time to avoid pay deduction, or a warning. We dont smoke in areas were not supposed to, because of the company policy, or the indignant stares we get. Like it or not, punishment works. By equating recognition with punishment, Kohn undermines his statement that recognition do not and will not work.            And since Kohn cites studies from social psychology, it would be interesting to know what Kohn thinks of conditioning theorists like Skinner who expoused the importance of positive reinforcement on behavior changes and learning.            In the end, all Kohn is arguing is the value of the reward involved, not the recognition system per se. For Kohn, a reward of higher value would make recognitions impact more felt. Intuit is cited as among the Fortunes Best Companies (#33 on the 2007 list, up from #78 in 2004) to work for because they have a corporate culture that is always focused on employee recognition. Go to the Intuit website and review their rewards program for employees http://web.intuit.com/about_intuit/careers/rewards/ . In light of our readings on rewards, what is your assessment of the Intuit rewards culture?             If I were to serve as a judge for Fortunes Best Companies to work for, Intuit would jump from #33 to at least the top 20. For one, Intuit has an enviable benefits package, including medical, vision and dental plans, a flexible spending account benefit, stock plans, assistance and referral programs.            While the Web site is largely silent on non-cash recognition, it can be inferred that the company cares for its employees. Its disability insurance that pays up to 70% of the employees basic salary promotes a sense of security for its labor force, in the event that something bad happens to them. The companys openness and assistance in their employees savings, as well as its assistance programs, also speaks about the companys concern. The company is also committed to help employees learn formally with a tuition assistance programs. Furthermore, the company even pays for their employees gym memberships and fitness classes.            More than that, the company says on its Web site that employees are recognized through cash and non-cash incentives.            Intuit is right up there on the list of best companies to work for because of all these. They are right on target and on track with recognizing their employees, making them a company to be emulated by others. How does your organization stack up with respect to creative and fun work environments with respect to reward systems?            I have just been recently hired as a contact representative by the Social Security Administration. Even though I am still in training, I find that my job is fulfilling based on what my colleagues tell me and what I see from them. First off, I have a supervisor who provides me regular feedback on my performance and how I am progressing, and even the things that I need to address or learn more. I work at an office that specifically values respect among its workers and to its callers. There is actually a written policy that says each employee must treat other employeesand customerswith respect, regardless of their race, gender, age, religion, etc. My colleagues are actually very friendly and helpful.            I also find that the very nature of my worktalking to a variety of people about their social security, their checks, and their benefitsis stimulating for me. There is always a new case with new circumstances every single day. I am grateful that my colleagues also find time to share their stories and their work. At various points of the day, we share tips on how to handle irate callers, or how to best process a complaint, or what to do in a particular instance.            Even if the SSA is a very structured organization, I find that we have leeways in handling calls. We actually can use our own methods in answering calls and getting the information to the callers. Its not that stiff. The quality of your work is based on how clearly youve communicated the information to the caller, and how you handled the caller.            Whats more, I work with people that puts a high value on camaraderie. Just yesterday, a colleague celebrated her birthday, and everybody chipped in to buy her a big chocolate cake, while our department boss gave her a bouquet of flowers.            I think Im going to like it there. In your experience, is employee recognition a scarce commodity in organizations? Why is that so?             No. I think I have been very lucky to be involved in organizations in the past that respected and valued diversity and initiative. In a way, I have been praised for my work. I have also been objectively reprimanded for lapses.            I am currently in an organization that strives to build relationships among its people. The same organization that is very clear with what it aims to achieve, and rewards the people who makes it happen.            Its not really just about commissions, or big fat incentives. Recognition comes in various forms. My personal criteria is that if it makes you feel warm all over, if it boosts your self-esteem, if it makes you want to repeat your behavior, then thats recognition. What is the most important lesson you took away from these readings and discussion?             My most important lesson is that while recognition has profound positive effects on the employeesand ultimately, the organizationit doesnt have to be expensive. Recognition could be as simple as a pat on the back, a good word, or singling out the employee/s who did good and thanking them. Recognition does not have to be elaborate, it just have to be apparent.
Thursday, November 14, 2019
Man Against God in Moby Dick Essay -- Moby Dick Essays
Man Against God in Moby Dick Thee Works Cited "God, God is against thee, old man; forbear! 'tis an ill voyage! ill begun; ill continued..." (418). Humanity has embarked on a journey. A journey of choice that will lead into the end days; one which will determine mankind's fate and weave the mat of life to completion. Humanity, like Captain Ahab, has chosen to follow the direction of his own desires rather than reason and faith. Refusing to hear the voice of reason, man has seared Starbuck-his conscience and morals-to "a lipless, unfeatured blank" (459). Following the desires of the flesh, he has thrown out the compass and declared himself "lord of the level loadstone" (425). And like Captain Ahab, humanity will suffer the consequences of "all his fatal pride" (425). Every person who lives believes he posses the power, the free will, to weave his mat of life, to make the designs come out the way he wishes. Yet, when the time of decision comes, every one will let "the ball of free will [drop] from [his] hand" and follow Captain Ahab in pursuit of the heart's passion and the mind's fantasy. The pressure of Ahab's voice drives the crew to compliance, and only Starbuck dares to stand up to him. But even Starbuck's courage wavers and he is unable to hold his ground. Seared into white noise, his silent pleas for obedience are seldom heard over Ahab's commands. For "[s]uch was the thunder of [Ahab's] voice," that "the men sprang over the railing" and into the sea (187). Ahab realizes the power he has and declares it many times outright. Yet he does not respect the authority granted to him and abuses it by taking his ship and crew on a voyage of revenge and "foolish, impious ... ... of God. Mankind has chosen to ignore the orders of the ship owners and the warnings of the compass, and like Ahab, has declared himself "immortal on land and sea" (411); therefore, "[I]nspite of all that mortal man could do," there will be "[r]etribution, swift vengeance" (468). "Remember therefore from whence thou art fallen, and repent, and do the first works; or else I will come unto thee quickly, and will remove thy candlestick out of his place..." (381) Works Cited The Holy Bible. Concordance and end-of-verse references ed. by Russell L. Surls. The Authorized King James Version. Iowa, World Bible Publishers, 1986. Melville, Herman. Moby Dick: An Authoritative Text; Reviews and Letters by Melville; Analogues and Sources; Criticism. A Norton Critical Edition. Ed. Harrison Hyford and Hershal Parker. New York, W. W. Norton and Company, Inc. 1967. Man Against God in Moby Dick Essay -- Moby Dick Essays Man Against God in Moby Dick Thee Works Cited "God, God is against thee, old man; forbear! 'tis an ill voyage! ill begun; ill continued..." (418). Humanity has embarked on a journey. A journey of choice that will lead into the end days; one which will determine mankind's fate and weave the mat of life to completion. Humanity, like Captain Ahab, has chosen to follow the direction of his own desires rather than reason and faith. Refusing to hear the voice of reason, man has seared Starbuck-his conscience and morals-to "a lipless, unfeatured blank" (459). Following the desires of the flesh, he has thrown out the compass and declared himself "lord of the level loadstone" (425). And like Captain Ahab, humanity will suffer the consequences of "all his fatal pride" (425). Every person who lives believes he posses the power, the free will, to weave his mat of life, to make the designs come out the way he wishes. Yet, when the time of decision comes, every one will let "the ball of free will [drop] from [his] hand" and follow Captain Ahab in pursuit of the heart's passion and the mind's fantasy. The pressure of Ahab's voice drives the crew to compliance, and only Starbuck dares to stand up to him. But even Starbuck's courage wavers and he is unable to hold his ground. Seared into white noise, his silent pleas for obedience are seldom heard over Ahab's commands. For "[s]uch was the thunder of [Ahab's] voice," that "the men sprang over the railing" and into the sea (187). Ahab realizes the power he has and declares it many times outright. Yet he does not respect the authority granted to him and abuses it by taking his ship and crew on a voyage of revenge and "foolish, impious ... ... of God. Mankind has chosen to ignore the orders of the ship owners and the warnings of the compass, and like Ahab, has declared himself "immortal on land and sea" (411); therefore, "[I]nspite of all that mortal man could do," there will be "[r]etribution, swift vengeance" (468). "Remember therefore from whence thou art fallen, and repent, and do the first works; or else I will come unto thee quickly, and will remove thy candlestick out of his place..." (381) Works Cited The Holy Bible. Concordance and end-of-verse references ed. by Russell L. Surls. The Authorized King James Version. Iowa, World Bible Publishers, 1986. Melville, Herman. Moby Dick: An Authoritative Text; Reviews and Letters by Melville; Analogues and Sources; Criticism. A Norton Critical Edition. Ed. Harrison Hyford and Hershal Parker. New York, W. W. Norton and Company, Inc. 1967.
Tuesday, November 12, 2019
Decision Making Tools
P A R T I V QUANTITATIVE MODULES Quantitative Module Decision-Making Tools A Module OutlineTHE DECISION PROCESS IN OPERATIONS FUNDAMENTALS OF DECISION MAKING DECISION TABLES TYPES OF DECISION-MAKING ENVIRONMENTS Decision Making Under Uncertainty Decision Making Under Risk Decision Making Under Certainty Expected Value of Perfect Information (EVPI) DECISION TREES A More Complex Decision Tree Using Decision Trees in Ethical Decision Making SUMMARY KEY TERMS USING SOFTWARE FOR DECISION MODELS SOLVED PROBLEMS INTERNET AND STUDENT CD-ROM EXERCISES DISCUSSION QUESTIONS PROBLEMS INTERNET HOMEWORK PROBLEMS CASE STUDIES: TOM TUCKER’S LIVER TRANSPLANT; SKI RIGHT CORP. ADDITIONAL CASE STUDIES BIBLIOGRAPHY L EARNING O BJECTIVESWhen you complete this module you should be able to IDENTIFY OR DEFINE: Decision trees and decision tables Highest monetary value Expected value of perfect information Sequential decisions DESCRIBE OR EXPLAIN: Decision making under risk Decision making under uncerta inty Decision making under certainty 674 MODULE A D E C I S I O N -M A K I N G T O O L S The wildcatter’s decision was a tough one. Which of his new Kentucky lease areasâ€â€Blair East or Blair Westâ€â€should he drill for oil? A wrong decision in this type of wildcat oil drilling could mean the difference between success and bankruptcy for the company.Talk about decision making under uncertainty and pressure! But using a decision tree, Tomco Oil President Thomas E. Blair identified 74 different options, each with its own potential net profit. What had begun as an overwhelming number of geological, engineering, economic, and political factors now became much clearer. Says Blair, â€Å"Decision tree analysis provided us with a systematic way of planning these decisions and clearer insight into the numerous and varied financial outcomes that are possible. †1 â€Å"The business executive is by profession a decision maker. Uncertainty is his opponent. Overcoming it is his mission. †John McDonaldOperations managers are decision makers. To achieve the goals of their organizations, managers must understand how decisions are made and know which decision-making tools to use. To a great extent, the success or failure of both people and companies depends on the quality of their decisions. Bill Gates, who developed the DOS and Windows operating systems, became chairman of the most powerful software firm in the world (Microsoft) and a billionaire. In contrast, the Firestone manager who headed the team that designed the flawed tires that caused so many accidents with Ford Explorers in the late 1990s is not working there anymore.THE DECISION PROCESS IN OPERATIONS What makes the difference between a good decision and a bad decision? A â€Å"good†decisionâ€â€one that uses analytic decision makingâ€â€is based on logic and considers all available data and possible alternatives. It also follows these six steps: 1. 2. 3. 4. 5. 6. Clearly define the problem and the factors that influence it. Develop specific and measurable objectives. Develop a modelâ€â€that is, a relationship between objectives and variables (which are measurable quantities). Evaluate each alternative solution based on its merits and drawbacks.Select the best alternative. Implement the decision and set a timetable for completion. Throughout this book, we have introduced a broad range of mathematical models and tools to help operations managers make better decisions. Effective operations depend on careful decision making. Fortunately, there are a whole variety of analytic tools to help make these decisions. This modHosseini, â€Å"Decision Analysis and Its Application in the Choice between Two Wildcat Ventures,†Interfaces, Vol. 16, no. 2. Reprinted by permission, INFORMS, 901 Elkridge Landing Road, Suite 400, Linthicum, Maryland 21090 USA. J. D E C I S I O N TA B L E S â€Å"Management means, in the last analysis, the substitution of th ought for brawn and muscle, of knowledge for folklore and tradition, and of cooperation for force. †Peter Drucker 675 ule introduces two of themâ€â€decision tables and decision trees. They are used in a wide number of OM situations, ranging from new-product analysis (Chapter 5), to capacity planning (Supplement 7), to location planning (Chapter 8), to scheduling (Chapter 15), and to maintenance planning (Chapter 17). FUNDAMENTALS OF DECISION MAKINGRegardless of the complexity of a decision or the sophistication of the technique used to analyze it, all decision makers are faced with alternatives and â€Å"states of nature. †The following notation will be used in this module: 1. Terms: a. Alternativeâ€â€a course of action or strategy that may be chosen by a decision maker (for example, not carrying an umbrella tomorrow). b. State of natureâ€â€an occurrence or a situation over which the decision maker has little or no control (for example, tomorrow’s w eather). Symbols used in a decision tree: a. â€â€decision node from which one of several alternatives may be selected. b. â€â€a state-of-nature node out of which one state of nature will occur. 2. To present a manager’s decision alternatives, we can develop decision trees using the above symbols. When constructing a decision tree, we must be sure that all alternatives and states of nature are in their correct and logical places and that we include all possible alternatives and states of nature. Example A1 A simple decision tree Getz Products Company is investigating the possibility of producing and marketing backyard storage sheds.Undertaking this project would require the construction of either a large or a small manufacturing plant. The market for the product producedâ€â€storage shedsâ€â€could be either favorable or unfavorable. Getz, of course, has the option of not developing the new product line at all. A decision tree for this situation is presented in F igure A. 1. A decision node A state of nature node Favorable market 1 Unfavorable market Favorable market 2 Unfavorable market no thi ng uct t str on plan C e g lar Construct small plant Do FIGURE A. 1 I Getz Products Decision Tree DECISION TABLES Decision tableA tabular means of analyzing decision alternatives and states of nature. We may also develop a decision or payoff table to help Getz Products define its alternatives. For any alternative and a particular state of nature, there is a consequence or outcome, which is usually expressed as a monetary value. This is called a conditional value. Note that all of the alternatives in Example A2 are listed down the left side of the table, that states of nature (outcomes) are listed across the top, and that conditional values (payoffs) are in the body of the decision table. 676 MODULE A D E C I S I O N -M A K I N G T O O L SWe construct a decision table for Getz Products (Table A. 1), including conditional values based on the following i nformation. With a favorable market, a large facility will give Getz Products a net profit of $200,000. If the market is unfavorable, a $180,000 net loss will occur. A small plant will result in a net profit of $100,000 in a favorable market, but a net loss of $20,000 will be encountered if the market is unfavorable. Example A2 A decision table TABLE A. 1 I Decision Table with Conditional Values for Getz Products ALTERNATIVES The toughest part of decision tables is getting the data to analyze.Construct large plant Construct small plant Do nothing STATES OF NATURE FAVORABLE MARKET UNFAVORABLE MARKET $200,000 $100,000 $ 0 $180,000 $ 20,000 $ 0 In Examples A3 and A4, we see how to use decision tables. TYPES OF DECISION-MAKING ENVIRONMENTS The types of decisions people make depend on how much knowledge or information they have about the situation. There are three decision-making environments: †¢ †¢ †¢ Decision making under uncertainty Decision making under risk Decision m aking under certainty Decision Making Under UncertaintyWhen there is complete uncertainty as to which state of nature in a decision environment may occur (that is, when we cannot even assess probabilities for each possible outcome), we rely on three decision methods: Maximax A criterion that finds an alternative that maximizes the maximum outcome. Maximin A criterion that finds an alternative that maximizes the minimum outcome. Equally likely A criterion that assigns equal probability to each state of nature. Maximaxâ€â€this method finds an alternative that maximizes the maximum outcome for every alternative.First, we find the maximum outcome within every alternative, and then we pick the alternative with the maximum number. Because this decision criterion locates the alternative with the highest possible gain, it has been called an â€Å"optimistic†decision criterion. 2. Maximinâ€â€this method finds the alternative that maximizes the minimum outcome for every altern ative. First, we find the minimum outcome within every alternative, and then we pick the alternative with the maximum number. Because this decision criterion locates the alternative that has the least possible loss, it has been called a â€Å"pessimistic†decision criterion. . Equally likelyâ€â€this method finds the alternative with the highest average outcome. First, we calculate the average outcome for every alternative, which is the sum of all outcomes divided by the number of outcomes. We then pick the alternative with the maximum number. The equally likely approach assumes that each state of nature is equally likely to occur. Example A3 applies each of these approaches to the Getz Products Company. 1. Example A3 A decision table analysis under uncertainty Given Getz’s decision table of Example A2, determine the maximax, maximin, nd equally likely decision criteria (see Table A. 2). TABLE A. 2 I Decision Table for Decision Making under Uncertainty STATES OF NAT URE FAVORABLE UNFAVORABLE MARKET MARKET $200,000 $100,000 $ 0 $180,000 $20,000 $ 0 MAXIMUM IN ROW $200,000 $100,000 $ 0 Maximax MINIMUM IN ROW $180,000 $20,000 $ 0 Maximin ROW AVERAGE $10,000 $40,000 $ 0 Equally likely ALTERNATIVES There are optimistic decision makers (â€Å"maximax†) and pessimistic ones (â€Å"maximin†). Maximax and maximin present best case–worst case planning scenarios. Construct large plant Construct small plant Do nothingTYPES 1. 2. 3. OF D E C I S I O N -M A K I N G E N V I RO N M E N T S 677 The maximax choice is to construct a large plant. This is the maximum of the maximum number within each row, or alternative. The maximin choice is to do nothing. This is the maximum of the minimum number within each row, or alternative. The equally likely choice is to construct a small plant. This is the maximum of the average outcome of each alternative. This approach assumes that all outcomes for any alternative are equally likely. Decision Making Under Risk Expected monetary value (EMV)The expected payout or value of a variable that has different possible states of nature, each with an associated probability. Decision making under risk, a more common occurrence, relies on probabilities. Several possible states of nature may occur, each with an assumed probability. The states of nature must be mutually exclusive and collectively exhaustive and their probabilities must sum to 1. 2 Given a decision table with conditional values and probability assessments for all states of nature, we can determine the expected monetary value (EMV) for each alternative.This figure represents the expected value or mean return for each alternative if we could repeat the decision a large number of times. The EMV for an alternative is the sum of all possible payoffs from the alternative, each weighted by the probability of that payoff occurring. EMV (Alternative i ) = ( Payoff of 1st state of nature) ? (Probability of 1st state of nature) + (Payoff of 2nd state of nature) ? (Probability of 2nd state of nature) + L + (Payoff of last state of nature) ? (Probability of last state of nature) Example A4 illustrates how to compute the maximum EMV. Example A4Expected monetary value Excel OM Data File ModAEx4. xla Getz Products operations manager believes that the probability of a favorable market is exactly the same as that of an unfavorable market; that is, each state of nature has a . 50 chance of occurring. We can now determine the EMV for each alternative (see Table A. 3): 1. 2. 3. EMV(A1) = (. 5)($200,000) + (. 5)( $180,000) = $10,000 EMV(A2) = (. 5)($100,000) + (. 5)( $20,000) = $40,000 EMV(A3) = (. 5)($0) + (. 5)($0) = $0 The maximum EMV is seen in alternative A2. Thus, according to the EMV decision criterion, Getz would build the small facility. TABLE A. I Decision Table for Getz Products ALTERNATIVES Construct large plant (A1) Construct small plant (A2) Do nothing (A3) Probabilities STATES OF NATURE FAVORABLE MARKET UNFAVORA BLE MARKET $200,000 $100,000 $ 0 . 50 $180,000 $ 20,000 $ 0 . 50 Decision Making Under Certainty Now suppose that the Getz operations manager has been approached by a marketing research firm that proposes to help him make the decision about whether to build the plant to produce storage sheds. The marketing researchers claim that their technical analysis will tell Getz with certainty whether the market is favorable for the proposed product.In other words, it will change Getz’s environment from one of decision making under risk to one of decision making under certainty. This information could prevent Getz from making a very expensive mistake. The marketing research firm would charge Getz $65,000 for the information. What would you recommend? Should the operations manager hire the firm to make the study? Even if the information from the study is perfectly accurate, is it worth $65,000? What might it be worth? Although some of these questions are difficult to answer, 2To EVPI pla ces an upper limit on what you should pay for information. eview these and other statistical terms, refer to the CD-ROM Tutorial 1, â€Å"Statistical Review for Managers. †678 MODULE A D E C I S I O N -M A K I N G T O O L S determining the value of such perfect information can be very useful. It places an upper bound on what you would be willing to spend on information, such as that being sold by a marketing consultant. This is the concept of the expected value of perfect information (EVPI), which we now introduce. Expected Value of Perfect Information (EVPI) Expected value of perfect information (EVPI) The difference between the payoff under certainty and the payoff under risk.If a manager were able to determine which state of nature would occur, then he or she would know which decision to make. Once a manager knows which decision to make, the payoff increases because the payoff is now a certainty, not a probability. Because the payoff will increase with knowledge of which state of nature will occur, this knowledge has value. Therefore, we now look at how to determine the value of this information. We call this difference between the payoff under certainty and the payoff under risk the expected value of perfect information (EVPI). EVPI = Expected value under certainty Maximum EMVExpected value under certainty The expected (average) return if perfect information is available. To find the EVPI, we must first compute the expected value under certainty, which is the expected (average) return if we have perfect information before a decision has to be made. To calculate this value, we choose the best alternative for each state of nature and multiply its payoff times the probability of occurrence of that state of nature. Expected value under certainty = (Best outcome or consequence for 1st state of nature) ? (Probability of 1st state of nature) + (Best outcome for 2nd state of nature) ? Probability of 2nd state of nature) + L + (Best outcome for last state o f nature) ? (Probability of last state of nature) In Example A5 we use the data and decision table from Example A4 to examine the expected value of perfect information. Example A5 Expected value of perfect information By referring back to Table A. 3, the Getz operations manager can calculate the maximum that he would pay for informationâ€â€that is, the expected value of perfect information, or EVPI. He follows a two-stage process. First, the expected value under certainty is computed. Then, using this information, EVPI is calculated.The procedure is outlined as follows: 1. The best outcome for the state of nature â€Å"favorable market†is â€Å"build a large facility†with a payoff of $200,000. The best outcome for the state of nature â€Å"unfavorable market†is â€Å"do nothing†with a payoff of $0. Expected value under certainty = ($200,000)(0. 50) + ($0)(0. 50) = $100,000. Thus, if we had perfect information, we would expect (on the average) $100 ,000 if the decision could be repeated many times. The maximum EMV is $40,000, which is the expected outcome without perfect information. Thus: EVPI = Expected value under certainty ? Maximum EMV = $100, 000 ? 40, 000 = $60, 000 In other words, the most Getz should be willing to pay for perfect information is $60,000. This conclusion, of course, is again based on the assumption that the probability of each state of nature is 0. 50. 2. DECISION TREES Decisions that lend themselves to display in a decision table also lend themselves to display in a decision tree. We will therefore analyze some decisions using decision trees. Although the use of a decision table is convenient in problems having one set of decisions and one set of states of nature, many problems include sequential decisions and states of nature.When there are two or more sequential decisions, and later decisions are based on the outcome of prior ones, the decision tree approach becomes appropriate. A decision tree is a graphic display of the decision process that indicates decision alternatives, states of nature and their respective probabilities, and payoffs for each combination of decision alternative and state of nature. Expected monetary value (EMV) is the most commonly used criterion for decision tree analysis. One of the first steps in such analysis is to graph the decision tree and to specify the monetary consequences of all outcomes for a particular problem.Decision tree A graphical means of analyzing decision alternatives and states of nature. DECISION TREES Decision tree software is a relatively new advance that permits users to solve decisionanalysis problems with flexibility, power, and ease. Programs such as DPL, Tree Plan, and Supertree allow decision problems to be analyzed with less effort and in greater depth than ever before. Full-color presentations of the options open to managers always have impact. In this photo, wildcat drilling options are explored with DPL, a product of Syn copation Software. 679 Analyzing problems with decision trees involves five steps: 1. 2. . 4. 5. Define the problem. Structure or draw the decision tree. Assign probabilities to the states of nature. Estimate payoffs for each possible combination of decision alternatives and states of nature. Solve the problem by computing expected monetary values (EMV) for each state-of-nature node. This is done by working backwardâ€â€that is, by starting at the right of the tree and working back to decision nodes on the left. Example A6 Solving a tree for EMV A completed and solved decision tree for Getz Products is presented in Figure A. 2. Note that the payoffs are placed at the right-hand side of each of the tree’s branches.The probabilities (first used by Getz in Example A4) are placed in parentheses next to each state of nature. The expected monetary values for each state-ofnature node are then calculated and placed by their respective nodes. The EMV of the first node is $10,000. T his represents the branch from the decision node to â€Å"construct a large plant. †The EMV for node 2, to â€Å"construct a small plant,†is $40,000. The option of â€Å"doing nothing†has, of course, a payoff of $0. The branch leaving the decision node leading to the state-of-nature node with the highest EMV will be chosen. In Getz’s case, a small plant should be built.EMV for node 1 = $10,000 = (. 5) ($200,000) + (. 5) (–$180,000) Payoffs Favorable market (. 5) $200,000 Co n ct stru e larg pla nt 1 Unfavorable market (. 5) Favorable market (. 5) 2 Unfavorable market (. 5) –$ 20,000 –$180,000 $100,000 Construct small plant Do no th in g EMV for node 2 = $40,000 = (. 5) ($100,000) + (. 5) (–$20,000) $0 FIGURE A. 2 I Completed and Solved Decision Tree for Getz Products 680 MODULE A D E C I S I O N -M A K I N G T O O L S A More Complex Decision Tree There is a widespread use of decision trees beyond OM. Managers often appreciat e a graphical display of a tough problem.When a sequence of decisions must be made, decision trees are much more powerful tools than are decision tables. Let’s say that Getz Products has two decisions to make, with the second decision dependent on the outcome of the first. Before deciding about building a new plant, Getz has the option of conducting its own marketing research survey, at a cost of $10,000. The information from this survey could help it decide whether to build a large plant, to build a small plant, or not to build at all. Getz recognizes that although such a survey will not provide it with perfect information, it may be extremely helpful.Getz’s new decision tree is represented in Figure A. 3 of Example A7. Take a careful look at this more complex tree. Note that all possible outcomes and alternatives are included in their logical sequence. This procedure is one of the strengths of using decision trees. The manager is forced to examine all possible outcom es, including unfavorable ones. He or she is also forced to make decisions in a logical, sequential manner. Examining the tree in Figure A. 3, we see that Getz’s first decision point is whether to conduct the $10,000 market survey.If it chooses not to do the study (the lower part of the tree), it can either build a large plant, a small plant, or no plant. This is Getz’s second decision point. If the decision is to build, the market will be either favorable (. 50 probability) or unfavorable (also . 50 probability). The payoffs for each of the possible consequences are listed along the right-hand side. As a matter of fact, this lower portion of Getz’s tree is identical to the simpler decision tree shown in Figure A. 2. Example A7 A decision tree with sequential decisions First Decision Point Second Decision Point $106,400 Favorable market (. 8) nt Payoffs $190,000 2 $49,200 1 Su re rve fav sult y (. 4 ora s 5) ble $106,400 la –$190,000 ep $63,600 Favorable market (. 78) arg L $ 90,000 Small 3 Unfavorable market(. 22) plant –$ 30,000 No pla nt –$ 10,000 Unfavorable market (. 22) vey –$87,400 Favorable market (. 27) pla nt $190,000 –$190,000 $ 90,000 –$ 30,000 –$ 10,000 y( rve Su ults e res ativ g ne t sur 4 Unfavorable market (. 73) (. 27) .55 arke $2,400 Con duct m L e arg $2,400 Favorable market 5 ) Small plant nt Unfavorable market (. 73) No pla $49,200 $40,000 FIGURE A. 3 I Getz Products Decision Tree with Probabilities and EMVs ShownThe short parallel lines mean â€Å"prune†that branch, as it is less favorable than another available option and may be dropped. Do t no co nd uc ts ur ve y $10,000 Favorable market pla nt (. 5) $200,000 –$180,000 $100,000 –$ 20,000 $0 6 Unfavorable market (. 5) (. 5) L e arg $40,000 Favorable market 7 Small plant nt Unfavorable market (. 5) No pla DECISION TREES You can reduce complexity by viewing and solving a number of smaller treesâ⠂¬â€ start at the end branches of a large one. Take one decision at a time. 681 The upper part of Figure A. 3 reflects the decision to conduct the market survey.State-of-nature node number 1 has 2 branches coming out of it. Let us say there is a 45% chance that the survey results will indicate a favorable market for the storage sheds. We also note that the probability is . 55 that the survey results will be negative. The rest of the probabilities shown in parentheses in Figure A. 3 are all conditional probabilities. For example, . 78 is the probability of a favorable market for the sheds given a favorable result from the market survey. Of course, you would expect to find a high probability of a favorable market given that the research indicated that the market was good.Don’t forget, though: There is a chance that Getz’s $10,000 market survey did not result in perfect or even reliable information. Any market research study is subject to error. In this case, there remai ns a 22% chance that the market for sheds will be unfavorable given positive survey results. Likewise, we note that there is a 27% chance that the market for sheds will be favorable given negative survey results. The probability is much higher, . 73, that the market will actually be unfavorable given a negative survey. Finally, when we look to the payoff column in Figure A. , we see that $10,000â€â€the cost of the marketing studyâ€â€has been subtracted from each of the top 10 tree branches. Thus, a large plant constructed in a favorable market would normally net a $200,000 profit. Yet because the market study was conducted, this figure is reduced by $10,000. In the unfavorable case, the loss of $180,000 would increase to $190,000. Similarly, conducting the survey and building no plant now results in a $10,000 payoff. With all probabilities and payoffs specified, we can start calculating the expected monetary value of each branch.We begin at the end or right-hand side of the decision tree and work back toward the origin. When we finish, the best decision will be known. 1. Given favorable survey results, EMV (node 2) = (. 78)($190, 000) + (. 22)( ? $190, 000) = $106, 400 EMV (node 3) = (. 78)($90, 000) + (. 22)( ? $30, 000) = $63,600 The EMV of no plant in this case is plant should be built. Given negative survey results, $10,000. Thus, if the survey results are favorable, a large 2. EMV (node 4) = (. 27)($190, 000) + (. 73)( ? $190, 000) = ? $87, 400 EMV (node 5) = (. 27)($90, 000) + (. 73)( ? $30, 000) = $2, 400 The EMV of no plant is again $10,000 for this branch.Thus, given a negative survey result, Getz should build a small plant with an expected value of $2,400. Continuing on the upper part of the tree and moving backward, we compute the expected value of conducting the market survey. EMV(node 1) = (. 45)($106,400) + (. 55)($2,400) = $49,200 4. If the market survey is not conducted. EMV (node 6) = (. 50)($200, 000) + (. 50)( ? $180, 000) = $10, 000 EMV (node 7) = (. 50)($100, 000) + (. 50)( ? $20, 000) = $40, 000 The EMV of no plant is $0. Thus, building a small plant is the best choice, given the marketing research is not performed.Because the expected monetary value of conducting the survey is $49,200â€â€versus an EMV of $40,000 for not conducting the studyâ€â€the best choice is to seek marketing information. If the survey results are favorable, Getz should build the large plant; if they are unfavorable, it should build the small plant. 3. 5. Using Decision Trees in Ethical Decision Making Decision trees can also be a useful tool to aid ethical corporate decision making. The decision tree illustrated in Example A8, developed by Harvard Professor Constance Bagley, provides guidance as to how managers can both maximize shareholder value and behave ethically.The tree can be applied to any action a company contemplates, whether it is expanding operations in a developing country or reducing a workforce at home. 682 MODUL E A D E C I S I O N -M A K I N G T O O L S Smithson Corp. is opening a plant in Malaysia, a country with much less stringent environmental laws than the U. S. , its home nation. Smithson can save $18 million in building the manufacturing facilityâ€â€and boost its profitsâ€â€if it does not install pollution-control equipment that is mandated in the U. S. but not in Malaysia.But Smithson also calculates that pollutants emitted from the plant, if unscrubbed, could damage the local fishing industry. This could cause a loss of millions of dollars in income as well as create health problems for local inhabitants. Example A8 Ethical decision making Action outcome Is it ethical? (Weigh the effect on employees, customers, suppliers, community versus shareholder benefit. ) Do it Ye s Ye No s Ye Is action legal? s Does action maximize company returns? Don't do it No No Is it ethical not to take action? (Weigh the harm to shareholders versus benefits to other stakeholders. Ye s Don't do it Do it, but notify appropriate parties Don't do it No FIGURE A. 4 I Smithson’s Decision Tree for Ethical Dilemma Source: Modified from Constance E. Bagley, â€Å"The Ethical Leader’s Decision Tree,†Harvard Business Review (January–February 2003): 18–19. Figure A. 4 outlines the choices management can consider. For example, if in management’s best judgment the harm to the Malaysian community by building the plant will be greater than the loss in company returns, the response to the question â€Å"Is it ethical? †will be no.Now, say Smithson proposes building a somewhat different plant, one with pollution controls, despite a negative impact on company returns. That decision takes us to the branch â€Å"Is it ethical not to take action? †If the answer (for whatever reason) is no, the decision tree suggests proceeding with the plant but notifying the Smithson Board, shareholders, and others about its impact. Ethical decisions can be quite complex: What happens, for example, if a company builds a polluting plant overseas, but this allows the company to sell a life-saving drug at a lower cost around the world?Does a decision tree deal with all possible ethical dilemmas? Noâ€â€but it does provide managers with a framework for examining those choices. SUMMARY This module examines two of the most widely used decision techniquesâ€â€decision tables and decision trees. These techniques are especially useful for making decisions under risk. Many decisions in research and development, plant and equipment, and even new buildings and structures can be analyzed with these decision models. Problems in inventory control, aggregate planning, maintenance, scheduling, and production control are just a few other decision table and decision tree applications.KEY TERMS Decision table (p. 675) Maximax (p. 676) Maximin (p. 676) Equally likely (p. 676) Expected monetary value (EMV) (p. 677) Expected value of perfect in formation (EVPI) (p. 678) Expected value under certainty (p. 678) Decision tree (p. 678) S O LV E D P RO B L E M S 683 USING SOFTWARE FOR DECISION MODELS Analyzing decision tables is straightforward with Excel, Excel OM, and POM for Windows. When decision trees are involved, commercial packages such as DPL, Tree Plan, and Supertree provide flexibility, power, and ease. POM for Windows will also analyze trees but does not have graphic capabilities.Using Excel OM Excel OM allows decision makers to evaluate decisions quickly and to perform sensitivity analysis on the results. Program A. 1 uses the Getz data to illustrate input, output, and selected formulas needed to compute the EMV and EVPI values. Compute the EMV for each alternative using = SUMPRODUCT(B$7:C$7, B8:C8). = MIN(B8:C8) = MAX(B8:C8) Find the best outcome for each measure using = MAX(G8:G10). To calculate the EVPI, find the best outcome for each scenario. = MAX(B8:B10) = SUMPRODUCT(B$7:C$7, B14:C14) = E14 – E11 PROG RAM A. I Using Excel OM to Compute EMV and Other Measures for Getz Using POM for Windows POM for Windows can be used to calculate all of the information described in the decision tables and decision trees in this module. For details on how to use this software, please refer to Appendix IV. SOLVED PROBLEMS Solved Problem A. 1 Stella Yan Hua is considering the possibility of opening a small dress shop on Fairbanks Avenue, a few blocks from the university. She has located a good mall that attracts students. Her options are to open a small shop, a medium-sized shop, or no shop at all.The market for a dress shop can be good, average, or bad. The probabilities for these three possibilities are . 2 for a good market, . 5 for an average market, and . 3 for a bad market. The net profit or loss for the medium-sized or small shops for the various market conditions are given in the following table. Building no shop at all yields no loss and no gain. What do you recommend? ALTERNATIVES Small sho p Medium-sized shop No shop Probabilities GOOD MARKET ($) 75,000 100,000 0 . 20 AVERAGE MARKET ($) 25,000 35,000 0 . 50 BAD MARKET ($) 40,000 60,000 0 . 30 684 MODULE A SolutionD E C I S I O N -M A K I N G T O O L S The problem can be solved by computing the expected monetary value (EMV) for each alternative. EMV (Small shop) = (. 2)($75,000) + (. 5)($25,000) + (. 3)( $40,000) = $15,500 EMV (Medium-sized shop) = (. 2)($100,000) + (. 5)($35,000) + (. 3)( $60,000) = $19,500 EMV (No shop) = (. 2)($0) + (. 5)($0) + (. 3)($0) = $0 As you can see, the best decision is to build the medium-sized shop. The EMV for this alternative is $19,500. Solved Problem A. 2 Daily demand for cases of Tidy Bowl cleaner at Ravinder Nath’s Supermarket has always been 5, 6, or 7 cases.Develop a decision tree that illustrates her decision alternatives as to whether to stock 5, 6, or 7 cases. Demand is 5 cases Demand is 6 cases Demand is 7 cases Solution The decision tree is shown in Figure A. 5. St oc k5 ca se s Demand is 5 cases Demand is 6 cases Demand is 7 cases oc k7 ca Stock 6 cases St se s Demand is 5 cases Demand is 6 cases Demand is 7 cases FIGURE A. 5 I Demand at Ravinder Nath’s Supermarket INTERNET AND STUDENT CD-ROM EXERCISES Visit our Companion Web site or use your student CD-ROM to help with this material in this module. On Our Companion Web site, www. prenhall. com/heizer Self-Study Quizzes †¢ Practice Problems †¢ Internet Homework Problems †¢ Internet Cases On Your Student CD-ROM †¢ PowerPoint Lecture †¢ Practice Problems †¢ Excel OM †¢ Excel OM Example Data File †¢ POM for Windows DISCUSSION QUESTIONS 1. Identify the six steps in the decision process. 2. Give an example of a good decision you made that resulted in a bad outcome. Also give an example of a bad decision you made that had a good outcome. Why was each decision good or bad? 3. What is the equally likely decision model? 4. Discuss the differences between dec ision making under certainty, under risk, and under uncertainty. . What is a decision tree? P RO B L E M S 6. Explain how decision trees might be used in several of the 10 OM decisions. 7. What is the expected value of perfect information? 8. What is the expected value under certainty? 9. Identify the five steps in analyzing a problem using a decision tree. 10. Why are the maximax and maximin strategies considered to be optimistic and pessimistic, respectively? 685 11. The expected value criterion is considered to be the rational criterion on which to base a decision. Is this true? Is it rational to consider risk? 12.When are decision trees most useful? PROBLEMS* P A. 1 a) b) c) Given the following conditional value table, determine the appropriate decision under uncertainty using: Maximax. Maximin. Equally likely. STATES OF NATURE ALTERNATIVES Build new plant Subcontract Overtime Do nothing VERY FAVORABLE MARKET $350,000 $180,000 $110,000 $ 0 AVERAGE MARKET $240,000 $ 90,000 $ 60,0 00 $ 0 UNFAVORABLE MARKET $300,000 $ 20,000 $ 10,000 $ 0 P A. 2 Even though independent gasoline stations have been having a difficult time, Susan Helms has been thinking about starting her own independent gasoline station.Susan’s problem is to decide how large her station should be. The annual returns will depend on both the size of her station and a number of marketing factors related to the oil industry and demand for gasoline. After a careful analysis, Susan developed the following table: SIZE OF FIRST STATION Small Medium Large Very large GOOD MARKET ($) 50,000 80,000 100,000 300,000 FAIR MARKET ($) 20,000 30,000 30,000 25,000 POOR MARKET ($) 10,000 20,000 40,000 160,000 a) b) c) d) e) For example, if Susan constructs a small station and the market is good, she will realize a profit of $50,000.Develop a decision table for this decision. What is the maximax decision? What is the maximin decision? What is the equally likely decision? Develop a decision tree. Assume each ou tcome is equally likely, then find the highest EMV. Clay Whybark, a soft-drink vendor at Hard Rock Cafe’s annual Rockfest, created a table of conditional values for the various alternatives (stocking decision) and states of nature (size of crowd): STATES OF NATURE (DEMAND) ALTERNATIVES Large stock Average stock Small stock BIG $22,000 $14,000 $ 9,000 AVERAGE $12,000 $10,000 $ 8,000 SMALL $2,000 $6,000 $4,000P A. 3 If the probabilities associated with the states of nature are 0. 3 for a big demand, 0. 5 for an average demand, and 0. 2 for a small demand, determine the alternative that provides Clay Whybark the greatest expected monetary value (EMV). P A. 4 For Problem A. 3, compute the expected value of perfect information (EVPI). *Note: OM; and means the problem may be solved with POM for Windows; means the problem may be solved with Excel P means the problem may be solved with POM for Windows and/or Excel OM. 686 MODULE A D E C I S I O N -M A K I N G T O O L S H. Weiss, Inc. is considering building a sensitive new airport scanning device. His managers believe that there is a probability of 0. 4 that the ATR Co. will come out with a competitive product. If Weiss adds an assembly line for the product and ATR Co. does not follow with a competitive product, Weiss’s expected profit is $40,000; if Weiss adds an assembly line and ATR follows suit, Weiss still expects $10,000 profit. If Weiss adds a new plant addition and ATR does not produce a competitive product, Weiss expects a profit of $600,000; if ATR does compete for this market, Weiss expects a loss of $100,000.Determine the EMV of each decision. For Problem A. 5, compute the expected value of perfect information. The following payoff table provides profits based on various possible decision alternatives and various levels of demand at Amber Gardner’s software firm: DEMAND LOW Alternative 1 Alternative 2 Alternative 3 $10,000 $ 5,000 $ 2,000 HIGH $30,000 $40,000 $50,000 P A. 5 P P A. 6 A. 7 a) b) c) The probability of low demand is 0. 4, whereas the probability of high demand is 0. 6. What is the highest possible expected monetary value? What is the expected value under certainty?Calculate the expected value of perfect information for this situation. Leah Johnson, director of Legal Services of Brookline, wants to increase capacity to provide free legal advice but must decide whether to do so by hiring another full-time lawyer or by using part-time lawyers. The table below shows the expected costs of the two options for three possible demand levels: STATES OF NATURE ALTERNATIVES Hire full-time Hire part-time Probabilities LOW DEMAND $300 $ 0 . 2 MEDIUM DEMAND $500 $350 . 5 HIGH DEMAND $ 700 $1,000 . 3 P A. 8 Using expected value, what should Ms.Johnson do? P A. 9 Chung Manufacturing is considering the introduction of a family of new products. Long-term demand for the product group is somewhat predictable, so the manufacturer must be concerned with the risk of choosin g a process that is inappropriate. Chen Chung is VP of operations. He can choose among batch manufacturing or custom manufacturing, or he can invest in group technology. Chen won’t be able to forecast demand accurately until after he makes the process choice. Demand will be classified into four compartments: poor, fair, good, and excellent.The table below indicates the payoffs (profits) associated with each process/demand combination, as well as the probabilities of each long-term demand level. POOR Probability Batch Custom Group technology a) b) . 1 $ 200,000 $ 100,000 $1,000,000 FAIR . 4 $1,000,000 $ 300,000 $ 500,000 GOOD . 3 $1,200,000 $ 700,000 $ 500,000 EXCELLENT . 2 $1,300,000 $ 800,000 $2,000,000 Based on expected value, what choice offers the greatest gain? What would Chen Chung be willing to pay for a forecast that would accurately determine the level of demand in the future?Julie Resler’s company is considering expansion of its current facility to meet incre asing demand. If demand is high in the future, a major expansion will result in an additional profit of $800,000, but if demand is low there will be a loss of $500,000. If demand is high, a minor expansion will result in an increase in profits of $200,000, but if demand is low, there will be a loss of $100,000. The company has the option of not expanding. If there is a 50% chance demand will be high, what should the company do to maximize long-run average profits? P A. 10 P RO B L E M S 87 P A. 11 The University of Dallas bookstore stocks textbooks in preparation for sales each semester. It normally relies on departmental forecasts and preregistration records to determine how many copies of a text are needed. Preregistration shows 90 operations management students enrolled, but bookstore manager Curtis Ketterman has second thoughts, based on his intuition and some historical evidence. Curtis believes that the distribution of sales may range from 70 to 90 units, according to the foll owing probability model: Demand Probability 70 . 15 75 . 30 80 . 30 85 . 0 90 . 05 a) b) This textbook costs the bookstore $82 and sells for $112. Any unsold copies can be returned to the publisher, less a restocking fee and shipping, for a net refund of $36. Construct the table of conditional profits. How many copies should the bookstore stock to achieve highest expected value? Palmer Cheese Company is a small manufacturer of several different cheese products. One product is a cheese spread sold to retail outlets. Susan Palmer must decide how many cases of cheese spread to manufacture each month. The probability that demand will be 6 cases is . , for 7 cases it is . 3, for 8 cases it is . 5, and for 9 cases it is . 1. The cost of every case is $45, and the price Susan gets for each case is $95. Unfortunately, any cases not sold by the end of the month are of no value as a result of spoilage. How many cases should Susan manufacture each month? Ronald Lau, chief engineer at South Dak ota Electronics, has to decide whether to build a new state-of-the-art processing facility. If the new facility works, the company could realize a profit of $200,000. If it fails, South Dakota Electronics could lose $180,000.At this time, Lau estimates a 60% chance that the new process will fail. The other option is to build a pilot plant and then decide whether to build a complete facility. The pilot plant would cost $10,000 to build. Lau estimates a 50-50 chance that the pilot plant will work. If the pilot plant works, there is a 90% probability that the complete plant, if it is built, will also work. If the pilot plant does not work, there is only a 20% chance that the complete project (if it is constructed) will work. Lau faces a dilemma. Should he build the plant? Should he build the pilot project and then make a decision?Help Lau by analyzing this problem. Karen Villagomez, president of Wright Industries, is considering whether to build a manufacturing plant in the Ozarks. Her decision is summarized in the following table: ALTERNATIVES Build large plant Build small plant Don’t build Market probabilities FAVORABLE MARKET $400,000 $ 80,000 $ 0 0. 4 UNFAVORABLE MARKET $300,000 $ 10,000 $ 0 0. 6 P A. 12 A. 13 P A. 14 a) b) c) A. 15 Construct a decision tree. Determine the best strategy using expected monetary value (EMV). What is the expected value of perfect information (EVPI)?Deborah Kellogg buys Breathalyzer test sets for the Denver Police Department. The quality of the test sets from her two suppliers is indicated in the following table: PERCENT DEFECTIVE 1 3 5 PROBABILITY LOOMBA TECHNOLOGY . 70 . 20 . 10 PROBABILITY STEWART-DOUGLAS ENTERPRISES . 30 . 30 . 40 FOR FOR a) b) For example, the probability of getting a batch of tests that are 1% defective from Loomba Technology is . 70. Because Kellogg orders 10,000 tests per order, this would mean that there is a . 7 probability of getting 100 defective tests out of the 10,000 tests if Loomba Technolo gy is used to fill the order.A defective Breathalyzer test set can be repaired for $0. 50. Although the quality of the test sets of the second supplier, Stewart-Douglas Enterprises, is lower, it will sell an order of 10,000 test sets for $37 less than Loomba. Develop a decision tree. Which supplier should Kellogg use? 688 MODULE A D E C I S I O N -M A K I N G T O O L S Deborah Hollwager, a concessionaire for the Des Moines ballpark, has developed a table of conditional values for the various alternatives (stocking decision) and states of nature (size of crowd).STATES OF NATURE (SIZE OF CROWD) ALTERNATIVES Large inventory Average inventory Small inventory LARGE $20,000 $15,000 $ 9,000 AVERAGE $10,000 $12,000 $ 6,000 SMALL $2,000 $6,000 $5,000 P A. 16 a) b) If the probabilities associated with the states of nature are 0. 3 for a large crowd, 0. 5 for an average crowd, and 0. 2 for a small crowd, determine: The alternative that provides the greatest expected monetary value (EMV). The e xpected value of perfect information (EVPI). Joseph Biggs owns his own sno-cone business and lives 30 miles from a California beach resort. The sale of sno-cones is highly dependent on his location and on the weather.At the resort, his profit will be $120 per day in fair weather, $10 per day in bad weather. At home, his profit will be $70 in fair weather and $55 in bad weather. Assume that on any particular day, the weather service suggests a 40% chance of foul weather. Construct Joseph’s decision tree. What decision is recommended by the expected value criterion? Kenneth Boyer is considering opening a bicycle shop in North Chicago. Boyer enjoys biking, but this is to be a business endeavor from which he expects to make a living. He can open a small shop, a large shop, or no shop at all.Because there will be a 5-year lease on the building that Boyer is thinking about using, he wants to make sure he makes the correct decision. Boyer is also thinking about hiring his old market ing professor to conduct a marketing research study to see if there is a market for his services. The results of such a study could be either favorable or unfavorable. Develop a decision tree for Boyer. Kenneth Boyer (of Problem A. 18) has done some analysis of his bicycle shop decision. If he builds a large shop, he will earn $60,000 if the market is favorable; he will lose $40,000 if the market is unfavorable.A small shop will return a $30,000 profit with a favorable market and a $10,000 loss if the market is unfavorable. At the present time, he believes that there is a 50-50 chance of a favorable market. His former marketing professor, Y. L. Yang, will charge him $5,000 for the market research. He has estimated that there is a . 6 probability that the market survey will be favorable. Furthermore, there is a . 9 probability that the market will be favorable given a favorable outcome of the study. However, Yang has warned Boyer that there is a probability of only . 12 of a favorabl e market if the marketing research results are not favorable.Expand the decision tree of Problem A. 18 to help Boyer decide what to do. Dick Holliday is not sure what he should do. He can build either a large video rental section or a small one in his drugstore. He can also gather additional information or simply do nothing. If he gathers additional information, the results could suggest either a favorable or an unfavorable market, but it would cost him $3,000 to gather the information. Holliday believes that there is a 50-50 chance that the information will be favorable. If the rental market is favorable, Holliday will earn $15,000 with a large section or $5,000 with a small.With an unfavorable video-rental market, however, Holliday could lose $20,000 with a large section or $10,000 with a small section. Without gathering additional information, Holliday estimates that the probability of a favorable rental market is . 7. A favorable report from the study would increase the probabil ity of a favorable rental market to . 9. Furthermore, an unfavorable report from the additional information would decrease the probability of a favorable rental market to . 4. Of course, Holliday could ignore these numbers and do nothing. What is your advice to Holliday? P A. 17 a) b) A. 18 A. 19 A. 20 A. 21 a) b) A. 22 Problem A. dealt with a decision facing Legal Services of Brookline. Using the data in that problem, provide: The appropriate decision tree showing payoffs and probabilities. The best alternative using expected monetary value (EMV). The city of Segovia is contemplating building a second airport to relieve congestion at the main airport and is considering two potential sites, X and Y. Hard Rock Hotels would like to purchase land to build a hotel at the new airport. The value of land has been rising in anticipation and is expected to skyrocket once the city decides between sites X and Y. Consequently, Hard Rock would like to purchase land now.Hard Rock will sell the la nd if the city chooses not to locate the airport nearby. Hard Rock has four choices: (1) buy land at X, (2) buy land at Y, (3) buy land at both X and Y, or (4) do nothing. Hard Rock has collected the following data (which are in millions of euros): SITE X Current purchase price Profits if airport and hotel built at this site Sales price if airport not built at this site 27 45 9 SITE Y 15 30 6 a) b) Hard Rock determines there is a 45% chance the airport will be built at X (hence, a 55% chance it will be built at Y). Set up the decision table. What should Hard Rock decide to do to maximize total net profit?C A S E S T U DY A. 23 689 Louisiana is busy designing new lottery â€Å"scratch-off†games. In the latest game, Bayou Boondoggle, the player is instructed to scratch off one spot: A, B, or C. A can reveal â€Å"Loser, †â€Å"Win $1,†or â€Å"Win $50. †B can reveal â€Å"Loser†or â€Å"Take a Second Chance. †C can reveal â€Å"Loserâ⠂¬ or â€Å"Win $500. †On the second chance, the player is instructed to scratch off D or E. D can reveal â€Å"Loser†or â€Å"Win $1. †E can reveal â€Å"Loser†or â€Å"Win $10. †The probabilities at A are . 9, . 09, and . 01. The probabilities at B are . 8 and . 2. The probabilities at C are . 999 and . 001. The probabilities at D are . 5 and . 5.Finally, the probabilities at E are . 95 and . 05. Draw the decision tree that represents this scenario. Use proper symbols and label all branches clearly. Calculate the expected value of this game. INTERNET HOMEWORK PROBLEMS See our Companion Web site at www. prenhall. com/heizer for these additional homework problems: A. 24 through A. 31. CASE STUDY Tom Tucker’s Liver Transplant Tom Tucker, a robust 50-year-old executive living in the northern suburbs of St. Paul, has been diagnosed by a University of Minnesota internist as having a decaying liver. Although he is otherwise healthy, Tucker ’s liver problem could prove fatal if left untreated.Firm research data are not yet available to predict the likelihood of survival for a man of Tucker’s age and condition without surgery. However, based on her own experience and recent medical journal articles, the internist tells him that if he elects to avoid surgical treatment of the liver problem, chances of survival will be approximately as follows: only a 60% chance of living 1 year, a 20% chance of surviving for 2 years, a 10% chance for 5 years, and a 10% chance of living to age 58. She places his probability of survival beyond age 58 without a liver transplant to be extremely low.The transplant operation, however, is a serious surgical procedure. Five percent of patients die during the operation or its recovery stage, with an additional 45% dying during the first year. Twenty percent survive for 5 years, 13% survive for 10 years, and 8%, 5%, and 4% survive, respectively, for 15, 20, and 25 years. Discussion Q uestions 1. Do you think that Tucker should select the transplant operation? 2. What other factors might be considered? CASE STUDY Ski Right Corp. After retiring as a physician, Bob Guthrie became an avid downhill skier on the steep slopes of the Utah Rocky Mountains.As an amateur inventor, Bob was always looking for something new. With the recent deaths of several celebrity skiers, Bob knew he could use his creative mind to make skiing safer and his bank account larger. He knew that many deaths on the slopes were caused by head injuries. Although ski helmets have been on the market for some time, most skiers consider them boring and basically ugly. As a physician, Bob knew that some type of new ski helmet was the answer. Bob’s biggest challenge was to invent a helmet that was attractive, safe, and fun to wear.Multiple colors and using the latest fashion designs would be musts. After years of skiing, Bob knew that many skiers believe that how you look on the slopes is more im portant than how you ski. His helmets would have to look good and fit in with current fashion trends. But attractive helmets were not enough. Bob had to make the helmets fun and useful. The name of the new ski helmet, Ski Right, was sure to be a winner. If Bob could come up with a good idea, he believed that there was a 20% chance that the market for the Ski Right helmet would be excellent. The chance of a good market should be 40%.Bob also knew that the market for his helmet could be only average (30% chance) or even poor (10% chance). The idea of how to make ski helmets fun and useful came to Bob on a gondola ride to the top of a mountain. A busy executive on the gondola ride was on his cell phone trying to complete a complicated merger. When the executive got off the gondola, he dropped the phone and it was crushed by the gondola mechanism. Bob decided that his new ski helmet would have a built-in cell phone and an AM/FM stereo radio. All the electronics could be operated by a co ntrol pad worn on a skier’s arm or leg.Bob decided to try a small pilot project for Ski Right. He enjoyed being retired and didn’t want a failure to cause him to go back to work. After some research, Bob found Progressive Products (PP). The company was willing to be a partner in developing the Ski Right and sharing any profits. If the market was excellent, Bob would net $5,000 per month. With a good market, Bob would net $2,000. An average market would result in a loss of $2,000, and a poor market would mean Bob would be out $5,000 per month. Another option for Bob was to have Leadville Barts (LB) make the helmet.The company had extensive experience in making bicycle helmets. Progressive would then take the helmets made by Leadville Barts and do the rest. Bob had a greater risk. He estimated that he could lose $10,000 per month in a poor market or $4,000 in an average market. A good market for Ski Right would result in $6,000 profit for Bob, and an excellent market wou ld mean a $12,000 profit per month. (continued) 690 MODULE A D E C I S I O N -M A K I N G T O O L S Cellular to make the phones, and TalRad to make the AM/FM stereo radios. Bob could then hire some friends to assemble everything and market the finishedSki Right helmets. With this final alternative, Bob could realize a net profit of $55,000 a month in an excellent market. Even if the market was just good, Bob would net $20,000. An average market, however, would mean a loss of $35,000. If the market was poor Bob would lose $60,000 per month. A third option for Bob was to use TalRad (TR), a radio company in Tallahassee, Florida. TalRad had extensive experience in making military radios. Leadville Barts could make the helmets, and Progressive Products could do the rest of production and distribution. Again, Bob would be taking on greater risk.A poor market would mean a $15,000 loss per month, and an average market would mean a $10,000 loss. A good market would result in a net profit of $7,000 for Bob. An excellent market would return $13,000 per month. Bob could also have Celestial Cellular (CC) develop the cell phones. Thus, another option was to have Celestial make the phones and have Progressive do the rest of the production and distribution. Because the cell phone was the most expensive component of the helmet, Bob could lose $30,000 per month in a poor market. He could lose $20,000 in an average market.If the market was good or excellent, Bob would see a net profit of $10,000 or $30,000 per month, respectively. Bob’s final option was to forget about Progressive Products entirely. He could use Leadville Barts to make the helmets, Celestial Discussion Questions 1. What do you recommend? 2. Compute the expected value of perfect information. 3. Was Bob completely logical in how he approached this decision problem? Source: B. Render, R. M. Stair, and M. Hanna, Quantitative Analysis for Management, 9th ed. Upper Saddle River, N. J. : Prentice Hall (2006). Re printed by permission of Prentice Hall, Inc.ADDITIONAL CASE STUDIES See our Companion Web site at www. prenhall. com/heizer for these additional free case studies: †¢ Arctic, Inc. : A refrigeration company has several major options with regard to capacity and expansion. †¢ Toledo Leather Company: This firm is trying to select new equipment based on potential costs. BIBLIOGRAPHY Brown, R. V. â€Å"The State of the Art of Decision Analysis. †Interfaces 22, 6 (November–December 1992): 5–14. Collin, Ian. â€Å"Scale Management and Risk Assessment for Deepwater Developments. †World Oil 224, no. 5 (May 2003): 62. Hammond, J. S. , R.L. Kenney, and H. Raiffa. â€Å"The Hidden Traps in Decision Making. †76, no. 5 Harvard Business Review (September–October 1998): 47–60. Jbuedj, C. â€Å"Decision Making under Conditions of Uncertainty. †Journal of Financial Planning (October 1997): 84. Keefer, Donald L. â€Å"Balancing Drug Safety and Efficacy for a Go/NoGo Decision. †Interfaces 34, no. 2 (March–April 2004): 113–116. Kirkwood, C. W. â€Å"An Overview of Methods for Applied Decision Analysis. †Interfaces 22, 6 (November–December 1992): 28–39. Perdue, Robert K. , William J. McAllister, Peter V. King, and Bruce G. Berkey. Valuation of R and D Projects Using Options Pricing and Decision Analysis Models. †Interfaces 29, 6 (November 1999): 57–74. Raiffa, H. Decision Analysis: Introductory Lectures on Choices Under Certainty. Reading, MA: Addison-Wesley (1968). Render, B. , R. M. Stair, Jr. , and R. Balakrishnan. Managerial Decision Modeling with Spreadsheets. 2nd ed. Upper Saddle River, NJ: Prentice Hall (2006). Render, B. , R. M. Stair Jr. , and M. Hanna. Quantitative Analysis for Management, 9th ed. Upper Saddle River, NJ: Prentice Hall (2006). Schlaifer, R. Analysis of Decisions Under Certainty. New York: McGraw-Hill (1969).
Saturday, November 9, 2019
If I Die in a Combat Zone
The novels If I Die in a Combat Zone and The Things They Carried were both written by Tim O’Brien. Tim O’Brien is a Vietnam War veteran and all of the novels he wrote are about his times in the war. He includes the same characters in the stories, but changed their names and descriptions. I do not believe that O’Brien wrote the books for any political reason. Both of the novels have very much in common including the style that it is written, and the stories that are told. There are also differences including the order of the stories, and the endings.These similarities and differences are important for the novels because it shows the diversity that different soldiers go through in times of war. The style that O’Brien writes in both novels is first person narrative. O’Brien tells the story in his point of view, and tells different stories. In If I Die in a Combat Zone the stories he tells his whole time in Vietnam. He starts with how he got drafted int o the war and his training. He considered leaving the country to go live in Europe. At the last minute he almost left, but then decided to stay and go to Vietnam.He continues the story in chronological order of the times and significant events that had happened throughout his duty. In The Things They Carried, O’Brien told significant stories that were told out of chronological order. The stories told in The Things They Carried were also less biographical and focused more on the men in his platoon. He also jumps back and forth between the war and post war, where he talked to the surviving men from his platoon. He tells the stories of the war, and the stories that the men told him. This is one of the differences between the two books.The ways the stories are told are different. Even though both books are told in the perspective of O’Brien, when he is telling the stories in The Things They Carried, we are more sympathetic to the other characters because it mostly focuses on them. In both of the stories, O’Brien also uses the same terminology in the books. He uses what I describe as â€Å"war†terminology. He uses words and acronyms. For example he said that they were looking for Charlie. I’m not very educated on the Vietnam War so I looked up who Charlie was. Then I realized that Charlie is the Vietnamese army.There were other terms including the different guns and different mine types. Thankfully, O’Brien explained those terms. O’Brien is consistent with his terms and it makes it easier to read one book after reading the other because of this consistency. The endings of If I Die in a Combat Zone and The Things They Carried are different. In If I Die in a Combat Zone, the end is O’Brien going home from Vietnam. He says that there is no joy in leaving Vietnam. He says that he thought of the friends he gained and the friends he lost. He reminisced what he learned, and realized that he did not learn a lot.The e nding of The Things They Carried is one last story that focused on O’Brien. It was the first time that he had seen a dead body in Vietnam. It then flashes back to his past where his girlfriend had died because of a brain tumor. That was the first time he had seen a dead body. The soldiers say that to keep a person alive is to always tell memories. But O’Brien didn’t do that, he just imagined that his girlfriend was still alive and waiting for him. Although collectively I did not like either of Tim O’Brien’s books, but I can say that they are well written.The reason I did not like the books was because of the graphics that were described. I understand that learning about the Vietnam War is important, and the horrific aspects are important to learn also, but I do not agree with describing in detail about bodies being blown to pieces. Both books have their similarities in being that they are about the Vietnam War, the style of the book, and the storie s and their content. Although the differences were big, including the order of the stories, and the perspective of the stories, the books are close in content. I believe that these books can be read simultaneously with each other.
Thursday, November 7, 2019
octavius essays
octavius essays Gaius Octavius, the great-nephew of Julius Caesar, was born in Rome on the 23rd of September, 63 BC (Southern 1). After Julius Caesars death on the Ides of March in 44 BC, a struggle for power in Rome ensued, even though 18 year old Octavian was the heir. Marc Antony, a good friend of Julius Caesar, disposed of the conspirators that murdered Caesar (Miller, ed. 153). In 43 BC, Octavian made an agreement with a major general, Marcus Lepidus, and Mark Antony. The agreement said that each man would be a dictator and they would rule together for a term of five years and avenge Caesar. One of the bloodiest acts in Roman history then occurred. A list was produced, and any man whose name was on it was sentenced to death and all his property was confiscated (Augustus). An exact copy of the war between Caesar and Pompey then took place. Marcus Brutus abandoned Greece and went to Asia due to the fact that there was a greater force of troops there. Cassius and Brutus faced Antony at Philippi. The first battle resulted in Brutus defeating Octavian and Antony defeating Cassius, and each man captured the others camp. Cassius, fearing his comrade Brutus was dead, committed suicide. This shocking event took away the best commander they had. Brutus, lacking in strategic sense, lost and also took his own life (Mommsen 69-70). After this battle, they all returned to Italy and Mark Antony took command of eastern Rome. Octavian faced many difficult battles including one led by the brother of Antony and one against Sextus Pompey. Mark Antony and Octavians friendship began to diminish (Augustus). Antony formed a friendship with Cleopatra while Octavian began to gather power in Italy. Lepidus was forced to give up politics by Octavian. Octavian became the dominant figure in western Rome after his victory over Sextus and the resignation of Lepidus from their triumvirate (Augustus). Cleopatra, queen of Egypt, and Antony married in 3...
Tuesday, November 5, 2019
Plus-sized women face shocking discrimination from hiring managers
Plus-sized women face shocking discrimination from hiring managers Have you ever left a job interview feeling like the interviewer was more focused on your appearance than your responses? Chances are you have - and new research shows that if you’re a woman, that gut feeling is quite rational. A new study from my company, Fairygodboss, asked 500 hiring professionals to look at images of 15 professional women of varied ages and races who had different hairstyles, body shapes, and attire. Respondents chose three adjectives (out of 11) to describe each woman and selected the women they’d be most likely to hire.The responses revealed that appearance does play a significant role in how hiring professionals perceive women.The dataIn our survey, we first asked hiring managers to pick the top qualities they look for when assessing job candidates. The most frequently selected qualities were professionalism (chosen by 68.28 percent of respondents), reliability (chosen by 60.69 percent), and leadership material (chosen by 46.21 percent).The top h iring choice was a young, Caucasian brunette. She was described as professional, confident, and friendly. While only one of these qualities overlaps with the three top-rated qualities among respondents, she was still the most likely to be hired.If a candidate’s appearance varied from this woman, she was less likely to be hired, regardless of whether or not she had the qualities hiring managers were looking for.Hiring managers were particularly harsh when judging the heaviest candidate. She was more likely than any other woman to be described as lazy (20 percent of respondents matched her with this adjective). Even though 44.8 percent said she was professional and 32.8 percent said she was reliable, just 15.2 percent said they would hire her over the other candidates. This placed her 14th of 15 for hireability.When shown an image of an older candidate, respondents ranked her sixth (out of 15) for professionalism, third for leadership ability, and first for reliability - yet j ust 29.2 percent said they would hire her over other candidates.Women of color also seemed to be facing a strong bias. Respondents rated most of the women of color as more reliable and having more leadership ability than the Caucasian woman, but remarkably enough, they were all less likely to be hired.This is how the data breaks down:The Caucasian brunette was rated:Professional – 75.4 percent of respondentsReliable – 19.6 percent of respondentsLeadership material – 27.8 percent of respondentsWould be hired – 60.0 percent of respondentsThe African-American woman was rated:Professional – 64.8 percent of respondentsReliable – 29.8 percent of respondentsLeadership material – 29.2 percent of respondentsWould be hired – 45.6 percent of respondentsThe Asian woman was rated:Professional – 57.6 percent of respondentsReliable – 37.0 percent of respondentsLeadership material – 27.6 percent of respondentsWould be hire d – 31.4 percent of respondentsThe Hispanic woman was rated:Professional – 42.2 percent of respondentsReliable – 19.6 percent of respondentsLeadership material – 33.2 percent of respondentsWould be hired – 26.6 percent of respondentsWhat this means for womenIt’s an unfortunate reality that you are still largely judged by how you look and dress. Hiring managers might perceive that you possess all of the qualities they’re looking for, but depending on your appearance, you still may not get the job. Since your age and race - and to some extent your weight - are out of your control, what can you do?In some situations, even the best interview responses might not overcome these biases. It is worth mentioning, however, that not all people share the same prejudices.Our data suggests that some hiring managers are less biased than others. For example, younger hiring professionals (between 25 and 34 years old) were more likely to hire the olde r candidate. Thirty percent said they’d consider the older woman, while just 15.4 percent of respondents over age 54 would. This means that older job seekers shouldn’t be afraid to apply for positions at up-and-coming companies that are largely led by young employees.Our research also shows that most women of color are more likely to be hired if their interviewer is of the same race. Both African-American and Asian respondents said they would hire the candidate of the same race.While you cannot choose the age or race of your interviewer, you can do research on companies to determine whether they prioritize diversity. Before interviewing, check review sites to see what current and former employees have to say about the organization in terms of inclusion.In the end, women are going to face unique and unfair obstacles during the job search. Hiring managers will look at them and make assumptions about who they are based on their appearance. But that doesn’t mean the re’s nothing you can do to prove you’re worth hiring.About the authorGeorgene Huang is obsessed with improving the workplace for women. She’s the CEO and Co-founder of Fairygodboss, a marketplace where professional women looking for jobs, career advice and the inside scoop on companies meet employers who believe in gender equality. Previously she ran the enterprise business at Dow Jones and was a Managing Director at Bloomberg Ventures. She is a graduate of Cornell and Stanford Universities.
Sunday, November 3, 2019
103 marketing plan Term Paper Example | Topics and Well Written Essays - 3000 words
103 marketing plan - Term Paper Example After the change of its name from Apple Computer Incorporated to Apple Inc., the most fascinating phone model; iPhone was introduced in the market. The future indicates how the efforts expressed through globalization flexibility make sense. The iPhone 5C has been aligned in relation to market demand and customer buying behavior. While it is a good idea for Apple Inc. to use the vertical marketing control, it is important that opens up its software and hardware for easy access to the outside market. Failure to do so gives applications like Android and Windows a chance to enjoy a huge market share. For the last five years, Apple Inc. constantly increased its revenue from 84.02 million to 101.25 million. The profits recorded a steady growth from 62.94 million to 68.45 million with the profit margin growing from 58.35% in 2009 to a almost constant rate of 65% in 2012 and 2013. However, the growth rate was highest in 2011 with 30.23% after recording the lowest growth rate in 2010 with a -0.90%. Thereafter, the growth rate recorded a sharp decrease in 2012, double the previous year to 15.54% and further dropped in 2013 to 0.82%. There has been a steady rise in the company’s stock price since the iPhone’s launch in 2009. It kicked off at $20.18 and increased at an increasing rate to $24.90 in 2010. The same was evident until it hit the high knot in 2013 with a $30.26 growth. From the above understanding about market segments and how to position its brand, the company summarized the iPhone’s marketing capability as flexible and convenient even for professional use because of its value added features. This makes everything easy because Apple Inc. is already an established brand since it always produces the most effective and technologically advanced gadgets (Robert Mohns). As an added advantage, the company has little time focusing on its brand and thus gets enough time to drill the iPhone in the
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