External Auditors and their role in the Corporate Governance Framework

External Auditors and their role in the Corporate Governance Framework External Auditors check companys accounts and report to the company based on the accounts. Basically, the concern is how external auditors conduct these duties effectively. Legislations, such as The Companies Act 1965, have made great efforts to ensure external auditors conduct their duties and obligations effectively. The Code of Corporate Governance in 2001 and the amendment in 2007 have further enhanced the effectiveness of audit in the interests of stockholders and shareholders. In light of the recent scandals involving external auditors in the world, there is a growing concern for corporate governance globally as there is increased reliance by the stockholders and shareholders on external auditors. This study examines the role of external auditors in the corporate governance framework. The study then reviews the financial scandals involving auditors occurred in the world and investigate the role of external auditor in the collapse of the companies. Introduction Corporate governance is a central and dynamic aspect of business. It is very important for corporate success and social welfare. In the wake of Enron, HIH Insurance and other similar cases, countries around the world have reacted quickly by pre-examining similar events domestically. As a speedy response to these corporate failures, the USA issued the Sarbanes-Oxly Act in July 2002, and in UK, the Higgs Report and the Smith Report were published in January 2003 (Solomon, 2007). Nowadays corporate governance is a globally debated topic with many characteristics (Nobel, 1998). However, the concern is whether auditors play an important role in the framework of corporate governance. Corporate Governance Corporate governance is the relationship among various participants in determining the direction and performance of corporations. The main participants are the shareholders, the management and the board of directors. Corporate governance is the process whereby directors of a company are monitored and controlled. There are two areas considered to be fundamental to corporate governance, one is supervision and monitoring of management performance and the other is ensuring accountability of management to shareholders and other stakeholders (Marianne, 2009). Till now, probably the two most important basic elements of good corporate governance have been full disclosure and the presence of independent directors and auditors, who each has their own ways to confirm that the data provided by the corporation are true and fairly stated. The contents of full disclosure are listed out in regulatory demands and professional pronouncements, and companies are expected to fully comply. The independence of the outside director and external auditor means the directors and auditors will have to distance themselves considerably to assure shareholders that they have conducted their tasks (Bavly, 2004). Role of External Auditors in Corporate Governance External auditors play a key role in the corporate governance framework. They conduct one of the most important corporate governance checks that help to monitor managements activities. The audit of financial statement makes disclosures more reliable, thus increasing confidence in the companys transparency. The role of external auditors is to make sure that Board of Directors and the management are acting responsibly towards the shareholders investment interests. By keeping objectivity, the external auditors can add value to shareholders by ensuring that the companys internal controls are strong and effective. And by working with the audit committee and liaising with internal auditors, external auditors can help to facilitate a more effective oversight of the financial reporting process by the Board of Directors (Hassan, 2004). However, the audit expectations gap needs to be acknowledged, as the audit function can only do so much on the fraud. The external auditor can not be expected to find every fraud and error during an audit. In accordance with the Cadbury Report, it is important to know that the external auditors role is not to prepare the financial statements, nor to provide assurance that the data in the financial statements are correct, nor to guarantee that the company will continue as a going concern, but the external auditors have to state in the annual report that the financial statements show a true and fair view. The Cadbury Report highlighted that there was no doubt on whether there should be an audit but rather how the audit could be ensured to conduct effectively and objectively by the external auditors (Solomon, 2007). Auditor Independence External auditors are expected to be independent of the company and report on the company objectively. Actually, auditors can only play their role effectively if they are independent (Peel ODonnell, 1995). They have to conduct their tasks in the most independent and reliable manner to provide investing public with the level of assurance to make their decisions based on the financial statements. According to the Cadbury Report, auditor independence could be affected due to the close relationship between auditors and company managers and due to the auditors intention to develop a constructive relationship with their clients. There are a number of threats to auditor independence, one of which is to provide non-audit services since non-audit services are lucrative. Auditors can obtain the contracts for non-audit services only if they maintain a good relationship with the management. The Cadbury Report stressed that a balance is needed to be achieved in such way that external auditors will work with, not against, company management, but in doing so they need to serve shareholders. This is a difficult path. The easiest way to ensure this balance being attained is suggested to establish audit committees and develop effective accounting standards. The Cadbury Report recommended all companies to establish audit committees. Audit committees serve as representative of shareholder interests. They are not only responsible for monitoring financial reporting process to support good corporate governance, they are also considered to be able to ensure an appropriate relationship exists between the external auditor and the management whose financial statements are being audited (Hassan, 2004). The Smith Report issued in 2003 highlighted that the audit committee needs to be proactive and raise the concern with directors rather than brush them under the carpet. The Report also stressed that all members of audit committee should be independent non-executive directors. Companys annual reports should disclose detailed information on the role and responsibilities of their audit committee. Lessons from Financial Scandals 4.1 Collapse of Enron Enron, the energy trading company based on Texas is the first scandal shaking up the auditing profession. It has led to a crisis to the confidence on auditors and the reliability of financial reporting (Holm Laursen, 2007). The audit quality and the independence of external auditors were questioned. In this case, Enrons audit and accounting function were fraudulent. Arthur Andersen, the auditor of Enron, has been involved in Enrons fraudulent accounting and auditing. Failure of the audit function is one of the key factors contributing to the companys collapse. Enron created The Raptors, four special purpose entities (SPEs). SPEs are established in order that a company can form a joint venture with other interested parties to conduct a specific transaction. This transaction will not subject the other parties to the risks more generally associated with the companys operations. U.S Generally Accepted Accounting Principles (GAPP) allows companies to record the gains and losses of SPEs without reporting their assets and liabilities in certain instances. In this way, Enron avoided adding more than $1 billion debt to its balance sheet without consolidating certain SPEs (Jenkins, 2003). But the problems are, when the losses of these entities quickly rose into billions of dollars, these entities were brought into the core financial statements. It then became clear that Enron itself had great losses. The corporations stock price dropped sharply, and the company went into bankruptcy in December 2001 (Brown, 2005). Examples of Enrons devious accounting exist widely in the corporation. The company recorded profits, for example, from a joint venture with Blockbuster Video that was never materialized (The Economist, 7 February 2002). In 2002, Enron restated its accounts, which is actually a process that reduced reported profits by $600 million (The Economist, 6 December 2001). In fact, the process resulted in a cumulative profit decrease of $591 million and a rise in debt of $628 million for the financial statements from 1997 to 2000. The difference between the profit figures was mainly attributed to the earlier omission of three off-balance sheet entities. Such profit inflation enabled the company to raise its earnings per share (EPS). The company not only manipulated the accounting figures to inflate the earnings, but it also was found to remove substantial amounts of debt from its accounts by setting up a number of off-balance sheet entities. Such special purpose entities can be used to hide a companys liabilities from the balance sheet, in order to make the financial statements look much better than they really are (The Economist, 2 May 2002). It means substantial number of liabilities did not have to be disclosed on Enrons financial statements, because they were mainly attributed to another legal entity. All these issues raise the question, why did Enrons auditor allow this type of activity? This is because the conflicts of interest exist between the external auditor and the management. Conflicts of Interest Conflicts of interest are a frequent problem in the audit profession. Although independent appointment of external auditors by companys shareholders is regularly replaced by subjective appointment by the company management, the auditor is all too often appreciated to the companys senior management. Further, conflicts of interest arise from interactive functions of audit and consultancy. Arthur Andersen has been blamed to apply loose standards in their audits because of conflict of interest over the subatantial consulting fees collected from Enron. In 2000, Andersen collected $25 million for auditing Enrons books in addition to $27 million for consulting services. In 2001, Arthur Anderson earned US$55 million for provision of non-audit services (Brown, 2005). Although Arthur Andersen reported on the companys accounts, they did not report fraud to the shareholders. This is because the fraud was committed by the management. Kenneth Lay, the Chief Executive Officer (CEO) from Feb 1986 until Feb 2001, took home US$ 152 million although the company was facing a loss. If Andersen were to report, they probably will not be appointed in the following years or be engaged in non-audit services (Krishnan, L, 2009). Especially, close relationships are established over time between companies and their external auditors. It can again affect independent judgment and impact on the auditing function. In this case, there are regular exchanges of employees within Enron from Arthur Anderson. Such conflicts of interest affect the corporate governance function. Serious conflicts of interest have also arisen among members of Enrons internal audit committee, which causes the internal audit committee did not perform its functions of internal control and of checking the external auditing function. For example, Lord Wakeham, a member of the audit committee, was at the same time having a consulting contract with Enron (The Economist, 7February2002). This shows that people in responsible positions should have detected fraudulent activities if they were independent. Enrons board of directors was composed of a number of members who have been shown to be willing to conduct fraudulent activity. It is also because the non-executive directors were compromised by conflicts of interest. 4.2 Collapse of HIH Insurance In Australia, the collapse of HIH Insurance Ltd was observed as the beginning of the reflection into external auditors role. HIH is one of Australias biggest insurers, comprising several separate government-licensed insurance companies, including HIH Casualty General Insurance Ltd, FAI General Insurance Ltd, CIC Insurance Ltd and World Marine General Insurances Ltd. On 15 March 2001, HIH went into provisional liquidation with losses of A$ 800 million (Peursem, Zhou, Flood Buttimore, 2007). HIH is one of the largest corporate collapses in Australian history. Similar issues arise as in the Enron case. HIH is claimed to mislead investors by providing incorrect financial reports to the market and HIHs auditor, Arthur Andersen, may have played a part in its collapse. Andersen conducted the external audits for HIH from 1971 until its collapse in 2001. Their contribution to the failure of HIH is considered in the following sections: Audit Practices As part of audit process, auditors will conduct a risk assessment to determine the structure and plan of the audit. Andersen assessed the risk of HIH and deemed it a maximum risk client, however, the engagement team of Andersen had not prepared the risk management plan and therefore the senior management team at Anderson did not review and approve the plan (Peursem, Zhou, Flood Buttimore, 2007). At the end, the auditor simply drew the wrong conclusions. Andersen signed off HIHs annual report for the 30th June 2000 and stated that it was a going concern with net assets of $939 million. Nine months later, HIH collapsed with debts of $5.3 billion (Peursem, Zhou, Flood Buttimore, 2007). Andersen used HIH management reports and forecasts and did not obtain sufficient evidence to get the conclusions they did. The liquidator could not find the documentation on the reasons for considering HIH as a going concern. This implies that Anderson failed to produce sufficient working papers to prove that the audit actually is conducted. Auditor Independence Andersen had a close relationship with HIH. By the time of liquidation, three former Anderson partners who had conducted HIH financial audit work held positions on the HIH board of directors. This obvious lack of independence between the board of directors and the auditors indicated that the best interests of HIH may have not always be a priority. Andersons failure in producing adequate working papers or in obtaining adequate evidence to support their findings have serious concerns on the quality of the audit they did. A significant independence issue is also reflected in the form of Andersons payment to HIH Chairman, Geoffrey Cohen for consultancy fees. These fees totaled $190,887 in nine years and included the use of Andersons office and secretary. These fees were not disclosed to the remaining board members in the annual general meetings (Peursem, Zhou, Flood Buttimore, 2007). The close and complicated financial relationship between the auditors and HIH chairman raise further questions in this case. Finally, the threat to auditor independence is that Andersen provided both audit and non-audit services to HIH. It raises a question on how can an auditor provide an independent opinion on the financial statements when he may play a role in guiding the preparation of the statements? The Royal Commission in Australia, which investigates the collapse of HIH, has found that the largest corporate collapse in Australia was not due to fraud but the result of attempting to cover the cracks on the overpriced acquisition. Andersons role in it appeared to be substantial. Modern Approach to External Auditors Role in Corporate Governance External auditors now have to take a much stricter approach to their clients (Bourne, 1995). There is an increasing view to support that external auditors should take on a more proactive role (Baxt, 1970). The Companies Act has set the stipulation on appointment, eligibility, qualification, disqualification and removal of external auditors (Davies Prentice, 2003). The intention is to ensure that auditors are able to carry out audit in an impersonal, objective and professional way. It is also to ensure that auditors are independent of the company. The reason for such emphasis is to ensure the external auditors are not in a position of conflict of interests. When there is conflict of interest, disclosure must be made to shareholders and stakeholders. Alternatively, there should be prohibition to the provision of non-audit services to the company where they act as auditors. To ensure auditors are truly independent and not in a conflict of interest, auditors should be rotated every year. Thereafter there should be a gap of five years before the same auditors are appointed by the company. Conclusion External auditors have an essential role in corporate governance through their involvement and their examination of financial statements. The external auditors role in corporate governance is a fundamental complement to achieve the desired objective of corporate governance. Therefore, the duties and obligations of external auditors must be expanded for the rights and interests of shareholders and stakeholders. There must be a modern approach to the auditors role in the corporate governance framework.

Forecasting Essay

1. Tupperware only uses both qualitative and quantitative forecasting techniques, culminating in a final forecast that is the consensus of all participating managers. False (Global company profile: Tupperware Corporation, moderate) 2. The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of a product. True (What is forecasting? moderate) 3. Sales forecasts are an input to financial planning, while demand forecasts impact human resource decisions. True (Types of forecasts, moderate) 4. Forecasts of individual products tend to be more accurate than forecasts of product families. False (Seven steps in the forecasting system, moderate) 5. Most forecasting techniques assume that there is some underlying stability in the system. True (Seven steps in the forecasting system, moderate) 6. The sales force composite forecasting method relies on salespersons’ estimates of expected sales. True (Forecasting approaches, easy) 7. A time-series model uses a series of past data points to make the forecast. True (Forecasting approaches, moderate) 8. The quarterly â€Å"make meeting† of Lexus dealers is an example of a sales force composite forecast. True (Forecasting approaches, easy) 9. Cycles and random variations are both components of time series. True (Time-series forecasting, easy) 10. A naive forecast for September sales of a product would be equal to the sales in August. True (Time-series forecasting, easy) 11. One advantage of exponential smoothing is the limited amount of record keeping involved. True (Time-series forecasting, moderate) 12. The larger the number of periods in the simple moving average forecasting method, the greater the method’s responsiveness to changes in demand. False (Time-series forecasting, moderate) 13. Forecast including trend is an exponential smoothing technique that utilizes two smoothing constants: one for the average level of the forecast and one for its trend. True (Time-series forecasting, easy) 14. Mean Squared Error and Coefficient of Correlation are two measures of the overall error of a forecasting model. False (Time-series forecasting, easy) 15. In trend projection, the trend component is the slope of the regression equation. True (Time-series forecasting, easy) 16. In trend projection, a negative regression slope is mathematically impossible. False (Time-series forecasting, moderate) 17. Seasonal indexes adjust raw data for patterns that repeat at regular time intervals. True (Time-series forecasting, moderate) 18. If a quarterly seasonal index has been calculated at 1.55 for the October-December quarter, then raw data for that quarter must be multiplied by 1.55 so that the quarter can be fairly compared to other quarters. False (Time-series forecasting: Seasonal variation in data, moderate) 19. The best way to forecast a business cycle is by finding a leading variable. True (Time-series forecasting, moderate) 20. Linear-regression analysis is a straight-line mathematical model to describe the functional relationships between independent and dependent variables. True (Associative forecasting methods: Regression and correlation analysis, easy) 21. The larger the standard error of the estimate, the more accurate the forecasting model. False (Associative forecasting methods: Regression and correlation analysis, easy) 22. A trend projection equation with a slope of 0.78 means that there is a 0.78 unit rise in Y for every unit of time that passes. True (Time-series forecasting: Trend projections, moderate) 23. In a regression equation where Y is demand and X is advertising, a coefficient of determination (R2) of .70 means that 70% of the variance in advertising is explained by demand. False (Associative forecasting methods: Regression and correlation analysis, moderate) 24. Tracking limits should be within  ± 8 MADs for low-volume stock items. True (Monitoring and controlling forecasts, moderate) 25. If a forecast is consistently greater than (or less than) actual values, the forecast is said to be biased. True (Monitoring and controlling forecasts, moderate) 26. Focus forecasting tries a variety of computer models and selects the best one for a particular application. True (Monitoring and controlling forecasts, moderate) 27. Many service firms use point-of-sale computers to collect detailed records needed for accurate short-term forecasts. True (Forecasting in the service sector, moderate) MULTIPLE CHOICE 28. Tupperware’s use of forecasting a.involves only a few statistical tools b.concentrates on the low-level dealer, and is not aggregated at the company level c.relies on the fact that all of its products are in the maturity phase of the life cycle d.is a major source of its competitive edge over its rivals e.takes inputs from sales, marketing, and finance, but not from production d (Global company profile, moderate) 29. Which of the following statements regarding Tupperware’s forecasting is false? a.Tupperware’s fifty profit centers generate the basic set of projections. b.Tupperware uses at least three quantitative forecasting techniques. c.Tupperware uses only quantitative forecasting techniques. d.†Sales per active dealer† is one of three key forecasting variables (factors). e.†Jury of executive opinion† is the ultimate forecasting tool used at Tupperware. c (Global company profile, moderate) 30. Forecasts a.become more accurate with longer time horizons b.are rarely perfect c.are more accurate for individual items than for groups of items d.all of the above e.none of the above b (What is forecasting? moderate) 31. One use of short-range forecasts is to determine a.production planning b.inventory budgets c.research and development plans d.facility location e.job assignments e (What is forecasting? moderate) 32. Forecasts are usually classified by time horizon into three categories a.short-range, medium-range, and long-range b.finance/accounting, marketing, and operations c.strategic, tactical, and operational d.exponential smoothing, regression, and time series e.departmental, organizational, and industrial a (What is forecasting? easy) 33. A forecast with a time horizon of about 3 months to 3 years is typically called a a.long-range forecast b.medium-range forecast c.short-range forecast d.weather forecast e.strategic forecast b (What is forecasting? moderate) 34. Forecasts used for new product planning, capital expenditures, facility location or expansion, and R&D typically utilize a a.short-range time horizon b.medium-range time horizon c.long-range time horizon d.naive method, because there is no data history e.all of the above c (What is forecasting? moderate) 35. The three major types of forecasts used by business organizations are a.strategic, tactical, and operational b.economic, technological, and demand c.exponential smoothing, Delphi, and regression d.causal, time-series, and seasonal e.departmental, organizational, and territorial b (Types of forecasts, moderate) 36. Which of the following is not a step in the forecasting process? a.Determine the use of the forecast. b.Eliminate any assumptions. c.Determine the time horizon. d.Select forecasting model. e.Validate and implement the results. b (The strategic importance of forecasting, moderate) 37. The two general approaches to forecasting are a.qualitative and quantitative b.mathematical and statistical c.judgmental and qualitative d.historical and associative e.judgmental and associative a (Forecasting approaches, easy) 38. Which of the following uses three types of participants: decision makers, staff personnel, and respondents? a.executive opinions b.sales force composites c.the Delphi method d.consumer surveys e.time series analysis c (Forecasting approaches, moderate) 39. The forecasting model that pools the opinions of a group of experts or managers is known as the a.sales force composition model b.multiple regression c.jury of executive opinion model d.consumer market survey model e.management coefficients model c (Forecasting approaches, moderate) 40. Which of the following is not a type of qualitative forecasting? a.executive opinions b.sales force composites c.consumer surveys d.the Delphi method e.moving average e (Forecasting approaches, moderate) 41. Which of the following techniques uses variables such as price and promotional expenditures, which are related to product demand, to predict demand? a.associative models b.exponential smoothing c.weighted moving average d.simple moving average e.time series a (Forecasting approaches, moderate) 42. Which of the following statements about time series forecasting is true? a.It is based on the assumption that future demand will be the same as past demand. b.It makes extensive use of the data collected in the qualitative approach. c.The analysis of past demand helps predict future demand. d.Because it accounts for trends, cycles, and seasonal patterns, it is more powerful than causal forecasting. e.All of the above are true. c (Time-series forecasting, moderate) 43. Time series data may exhibit which of the following behaviors? a.trend b.random variations c.seasonality d.cycles e.They may exhibit all of the above. e (Time-series forecasting, moderate) 44. Gradual, long-term movement in time series data is called a.seasonal variation b.cycles c.trends d.exponential variation e.random variation c (Time-series forecasting, moderate) 45. Which of the following is not present in a time series? a.seasonality b.operational variations c.trend d.cycles e.random variations b (Time-series forecasting, moderate) 46. The fundamental difference between cycles and seasonality is the a.duration of the repeating patterns b.magnitude of the variation c.ability to attribute the pattern to a cause d.all of the above e.none of the above a (Time-series forecasting, moderate) 47. In time series, which of the following cannot be predicted? a.large increases in demand b.technological trends c.seasonal fluctuations d.random fluctuations e.large decreases in demand d (Time-series forecasting, moderate) 48. What is the approximate forecast for May using a four-month moving average? 49. Which time series model below assumes that demand in the next period will be equal to the most recent period’s demand? a.naive approach b.moving average approach c.weighted moving average approach d.exponential smoothing approach e.none of the above a (Time-series forecasting, easy) 50. Which of the following is not a characteristic of simple moving averages? a.It smoothes random variations in the data. b.It has minimal data storage requirements. c.It weights each historical value equally. d.It lags changes in the data. e.It smoothes real variations in the data. b (Time-series forecasting, moderate) 51. A six-month moving average forecast is better than a three-month moving average forecast if demand a.is rather stable b.has been changing due to recent promotional efforts c.follows a downward trend d.follows a seasonal pattern that repeats itself twice a year e.follows an upward trend a (Time-series forecasting, moderate) 52. Increasing the number of periods in a moving average will accomplish greater smoothing, but at the expense of a.manager understanding b.accuracy c.stability d.responsiveness to changes e.All of the above are diminished when the number of periods increases. d (Time-series forecasting, moderate) 53. Which of the following statements comparing the weighted moving average technique and exponential smoothing is true? a.Exponential smoothing is more easily used in combination with the Delphi method. b.More emphasis can be placed on recent values using the weighted moving average. c.Exponential smoothing is considerably more difficult to implement on a computer. d.Exponential smoothing typically requires less record keeping of past data. e.Exponential smoothing allows one to develop forecasts for multiple periods, whereas weighted moving averages does not. d (Time-series forecasting, moderate) 54. Which time series model uses past forecasts and past demand data to generate a new forecast? a.naive b.moving average c.weighted moving average d.exponential smoothing e.regression analysis d (Time-series forecasting, moderate) 55. Which is not a characteristic of exponential smoothing? a.smoothes random variations in the data b.easily altered weighting scheme c.weights each historical value equally d.has minimal data storage requirements e.none of the above; they are all characteristics of exponential smoothing c (Time-series forecasting, moderate) 56. Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast? a.0 b.1 divided by the number of periods c.0.5 d.1.0 e.cannot be determined d (Time-series forecasting, moderate) 57. Given an actual demand of 103, a previous forecast value of 99, and an alpha of .4, the exponential smoothing forecast for the next period would be a.94.6 b.97.4 c.100.6 d.101.6 e.103.0 c (Time-series forecasting, moderate) 58. A forecast based on the previous forecast plus a percentage of the forecast error is a(n) a.qualitative forecast b.naive forecast c.moving average forecast d.weighted moving average forecast e.exponentially smoothed forecast e (Time-series forecasting, moderate) 59. Given an actual demand of 61, a previous forecast of 58, and an of .3, what would the forecast for the next period be using simple exponential smoothing? a.45.5 b.57.1 c.58.9 d.61.0 e.65.5 c (Time-series forecasting, moderate) 60. Which of the following values of alpha would cause exponential smoothing to respond the most slowly to forecast errors? a.0.10 b.0.20 c.0.40 d.0.80 e.cannot be determined a (Time-series forecasting, moderate) 61. A forecasting method has produced the following over the past five months. What is the mean absolute deviation? 62. The primary purpose of the mean absolute deviation (MAD) in forecasting is to a.estimate the trend line b.eliminate forecast errors c.measure forecast accuracy d.seasonally adjust the forecast e.all of the above c (Time-series forecasting, moderate) 63. Given forecast errors of -1, 4, 8, and -3, what is the mean absolute deviation? a.2 b.3 c.4 d.8 e.16 c (Time-series forecasting, moderate) 64. The last four months of sales were 8, 10, 15, and 9 units. The last four forecasts were 5, 6, 11, and 12 units. The Mean Absolute Deviation (MAD) is a.2 b.-10 c.3.5 d.9 e.10.5 c (Time-series forecasting, moderate) 65. A time series trend equation is 25.3 + 2.1 X. What is your forecast for period 7? a.23.2 b.25.3 c.27.4 d.40.0 e.cannot be determined d (Time-series forecasting, moderate) 66. For a given product demand, the time series trend equation is 53 – 4 X. The negative sign on the slope of the equation a.is a mathematical impossibility b.is an indication that the forecast is biased, with forecast values lower than actual values c.is an indication that product demand is declining d.implies that the coefficient of determination will also be negative e.implies that the RSFE will be negative c (Time-series forecasting, moderate) 67. In trend-adjusted exponential smoothing, the forecast including trend (FIT) consists of a.an exponentially smoothed forecast and an estimated trend value b.an exponentially smoothed forecast and a smoothed trend factor c.the old forecast adjusted by a trend factor d.the old forecast and a smoothed trend factor e.a moving average and a trend factor b (Time-series forecasting, moderate) 68. Which of the following is true regarding the two smoothing constants of the Forecast Including Trend (FIT) model? a.One constant is positive, while the other is negative. b.They are called MAD and RSFE. c.Alpha is always smaller than beta. d.One constant smoothes the regression intercept, whereas the other smoothes the regression slope. e.Their values are determined independently. e (Time-series forecasting, moderate) 69. Demand for a certain product is forecast to be 800 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally-adjusted sales forecast for January? a.640 units b.798.75 units c.800 units d.1000 units e.cannot be calculated with the information given a (Time-series forecasting, moderate) 70. A seasonal index for a monthly series is about to be calculated on the basis of three years’ accumulation of data. The three previous July values were 110, 150, and 130. The average over all months is 190. The approximate seasonal index for July is a.0.487 b.0.684 c.1.462 d.2.053 e. cannot be calculated with the information given b (Time-series forecasting, moderate) 71. A fundamental distinction between trend projection and linear regression is that a.trend projection uses least squares while linear regression does not b.only linear regression can have a negative slope c.in trend projection the independent variable is time; in linear regression the independent variable need not be time, but can be any variable with explanatory power d.linear regression tends to work better on data that lack trends e.trend projection uses two smoothing constants, not just one c (Associative forecasting methods: Regression and correlation analysis, moderate) 72. The percent of variation in the dependent variable that is explained by the regression equation is measured by the a.mean absolute deviation b.slope c.coefficient of determination d.correlation coefficient e.intercept c (Associative forecasting methods: Regression and correlation analysis, moderate) 73. The degree or strength of a linear relationship is shown by the a.alpha b.mean c.mean absolute deviation d.correlation coefficient e.RSFE d (Associative forecasting methods: Regression and correlation analysis, moderate) 74. If two variables were perfectly correlated, the correlation coefficient r would equal a.0 b.less than 1 c.exactly 1 d.-1 or +1 e.greater than 1 d (Associative forecasting methods: Regression and correlation analysis, moderate) 75. The last four weekly values of sales were 80, 100, 105, and 90 units. The last four forecasts were 60, 80, 95, and 75 units. These forecasts illustrate a.qualitative methods b.adaptive smoothing c.slope d.bias e.trend projection d (Monitoring and controlling forecasts, easy) 76. The tracking signal is the a.standard error of the estimate b.running sum of forecast errors (RSFE) c.mean absolute deviation (MAD) d.ratio RSFE/MAD e.mean absolute percentage error (MAPE) d (Monitoring and controlling forecasts, moderate) 77. Computer monitoring of tracking signals and self-adjustment if a signal passes a preset limit is characteristic of a.exponential smoothing including trend b.adaptive smoothing c.trend projection d.focus forecasting e.multiple regression analysis b (Monitoring and controlling forecasts, moderate) 78. Many services maintain records of sales noting a.the day of the week b.unusual events c.weather d.holidays e.all of the above e (Forecasting in the service sector, moderate) 79. Taco Bell’s unique employee scheduling practices are partly the result of using a.point-of-sale computers to track food sales in 15 minute intervals b.focus forecasting c.a six-week moving average forecasting technique d.multiple regression e.a and c are both correct e (Forecasting in the service sector, moderate) 96. A skeptical manager asks what short-range forecasts can be used for. Give her three possible uses/purposes. Any three of: planning purchasing, job scheduling, work force levels, job assignments, production levels. (What is forecasting? moderate) 97. A skeptical manager asks what long-range forecasts can be used for. Give her three possible uses/purposes. Any three of: planning new products, capital expenditures, facility location or expansion, research and development. (What is forecasting? moderate) 98. Describe the three forecasting time horizons and their use. Forecasting time horizons are: short range—generally less than three months, used for purchasing, job scheduling, work force levels, production levels; medium range—usually from three months up to three years, used for sales planning, production planning and budgeting, cash budgeting, analyzing operating plans; long range—usually three years or more, used for new product development, capital expenditures, facility planning, and R&D. (What is forecasting? moderate) 99. List and briefly describe the three major types of forecasts. The three types are economic, technological, and demand; economic refers to macroeconomic, growth and financial variables; technological refers to forecasting amount of technological advance, or futurism; demand refers to  product demand. (Types of forecasts, moderate) 100. List the seven steps involved in forecasting. 1. Determine the use of the forecast. 2. Select the items that are to be forecast. 3. Determine the time horizon of the forecast. 4. Select the forecasting model(s). 5. Gather the data needed to make the forecast. 6. Make the forecast. 7. Validate the forecasting mode and implement the results. (Seven steps in the forecasting process, moderate) 101. What are the realities of forecasting that companies face? First, forecasts are seldom perfect. Second, most forecasting techniques assume that there is some underlying stability in the system. Finally, both product family and aggregated forecasts are more accurate than individual product forecasts. (Seven steps in the forecasting system, moderate) 102. What are the differences between quantitative and qualitative forecasting methods? Quantitative methods use mathematical models to analyze historical data. Qualitative methods incorporate such factors as the decision maker’s intuition, emotions, personal experiences, and value systems in determining the forecast. (Forecasting approaches, moderate) 103. List four quantitative forecasting methods. The list includes naive, moving averages, exponential smoothing, trend projection, and linear regression. (Forecasting approaches, moderate) 104. What is a time-series forecasting model? A time series forecasting model is any mathematical model that uses historical values of the quantity of interest to predict future values of that quantity. (Forecasting approaches, easy) 105. What is the difference between an associative model and a time-series model? A time series model uses only historical values of the quantity of interest to predict future values of that quantity. The associative model, on the other hand, attempts to identify underlying causes or factors that control the variation of the quantity of interest, predict future values of these factors, and use these predictions in a model to predict future values of the specific quantity of interest. (Forecasting approaches, moderate) 106. Name and discuss three qualitative forecasting methods. Qualitative forecasting methods include: jury of executive opinion, where high-level managers arrive at a group estimate of demand; sales force composite, where salespersons’ estimates are aggregated; Delphi method, where respondents provide inputs to a group of decision makers; the group of decision makers, often experts, then make the actual forecast; consumer market survey, where consumers are queried about their future purchase plans. (Forecasting approaches, moderate) 107. List the four components of a time series. Which one of these is rarely forecast? Why is this so? Trend, seasonality, cycles, and random variation. Since random variations follow no discernible pattern, they cannot be predicted, and thus are not forecast. (Time-series forecasting, moderate) 108. Compare seasonal effects and cyclical effects. A cycle is longer (typically several years) than a season (typically days, weeks, months, or quarters). A cycle has variable duration, while a season has fixed duration and regular repetition. (Time-series forecasting, moderate) 109. Distinguish between a moving average model and an exponential smoothing model. Exponential smoothing is a weighted moving average model wherein previous values are weighted in a specific manner–in particular, all previous values are weighted with a set of weights that decline exponentially. (Time-series forecasting, moderate) 110. Describe three popular measures of forecast accuracy. Measures of forecast accuracy include: (a) MAD (mean absolute deviation). This is a sum of the absolute values of individual errors divided by the  number of periods of data. (b) MSE (mean squared error). This is the average of the squared differences between the forecast and observed values. (c) MAPE (mean absolute percent error) is independent of the magnitude of the variable being forecast. (Forecasting approaches: Measuring forecast error, moderate) 111. Give an example—other than a restaurant or other food-service firm—of an organization that experiences an hourly seasonal pattern. (That is, each hour of the day has a pattern that tends to repeat day after day.) Explain. Answer will vary. However, two non-food examples would be banks and movie theaters. (Time-series forecasting, moderate) 112. Explain the role of regression models (time series and otherwise) in forecasting. That is, how is trend projection able to forecast? How is regression used for causal forecasting? For trend projection, the independent variable is time. The trend projection equation has a slope that is the change in demand per period. To forecast the demand for period t, perform the calculation a + bt. For causal forecasting, the independent variables are predictors of the forecast value or dependent variable. The slope of the regression equation is the change in the Y variable per unit change in the X variable. (Time-series forecasting, diff icult) 113. List three advantages of the moving average forecasting model. List three disadvantages of the moving average forecasting model. Two advantages of the model are that it uses simple calculations, it smoothes out sudden fluctuations, and it is easy for users to understand. The disadvantages are that the averages always stay within past ranges, that they require extensive record keeping of past data, and that they do not pick up on trends very well. (Time-series forecasting, moderate) 114. What does it mean to â€Å"decompose† a time series? To decompose a time series means to break past data down into components of trends, seasonality, cycles, and random blips, and to project them forward. (Time-series forecasting, easy) 115. Distinguish a dependent variable from an independent variable. The  independent variable causes some behavior in the dependent variable; the dependent variable shows the effect of changes in the independent variable. (Associative forecasting methods: Regression and correlation, moderate) 116. Explain, in your own words, the meaning of the coefficient of determination. The coefficient of determination measures the amount (percent) of total variation in the data that is explained by the model. (Associative forecasting methods: Regression and correlation, moderate) 117. What is a tracking signal? How is it calculated? Explain the connection between adaptive smoothing and tracking signals. A tracking signal is a measure of how well the forecast actually predicts. Its calculation is the ratio of RSFE to MAD. The larger the absolute tracking signal, the worse the forecast is performing. Adaptive smoothing sets limits to the tracking signal, and makes changes to its forecasting models when the tracking signal goes beyond those limits. (Monitoring and controlling forecasts, moderate) 118. What is focus forecasting? It is a forecasting method that tries a variety of computer models, and selects the one that is best for a particular application. (Monitoring and controlling forecasts, easy) 124. A management analyst is using exponential smoothing to predict merchandise returns at an upscale branch of a department store chain. Given an actual number of returns of 154 items in the most recent period completed, a forecast of 172 items for that period, and a smoothing constant of 0.3, what is the forecast for the next period? How would the forecast be changed if the smoothing constant were 0.6? Explain the difference in terms of alpha and responsiveness. 166.6; 161.2 The larger the smoothing constant in an exponentially smoothed forecast, the more responsive the forecast. (Time-series forecasting, easy) 126. The following trend projection is used to predict quarterly demand: Y = 250 – 2.5t, where t = 1 in the first quarter of 2004. Seasonal (quarterly) relatives are Quarter 1 = 1.5; Quarter 2 = 0.8; Quarter 3 = 1.1; and Quarter 4 = 0.6. What is the seasonally adjusted forecast for the four quarters of 2006? PeriodProjectionAdjusted 9 227.5341.25 10 225180.00 11222.5224.75 12220132.00 (Time-series forecasting, moderate) 127. Jim’s department at a local department store has tracked the sales of a product over the last ten weeks. Forecast demand using exponential smoothing with an alpha of 0.4, and an initial forecast of 28.0. Calculate MAD and the tracking signal. What do you recommend? 130. A small family-owned restaurant uses a seven-day moving average model to determine manpower requirements. These forecasts need to be seasonalized because each day of the week has its own demand pattern. The seasonal relatives for each day of the week are: Monday, 0.445; Tuesday, 0.791; Wednesday, 0.927; Thursday, 1.033; Friday, 1.422; Saturday, 1.478; and Sunday 0.903. Average daily demand based on the most recent moving average is 194 patrons. What is the seasonalized forecast for each day of next week? The average value multiplied by each day’s seasonal index. Monday: 194 x .445 = 86; Tuesday: 194 x .791 = 153; Wednesday: 194 x .927 = 180; Thursday: 194 x 1.033 = 200; Friday: 194 x 1.422 = 276; Saturday: 194 x 1.478 = 287; and Sunday: 194 x .903 = 175. (Associative forecasting methods: Regression and correlation, moderate) 131. A restaurant has tracked the number of meals served at lunch over the last four weeks. The data shows little in terms of trends, but does display substantial variation by day of the week. Use the following information to determine the seasonal (daily) index for this restaurant. 132. A firm has modeled its experience with industrial accidents and found that the number of accidents per year (Y) is related to the number of employees (X) by the regression equation Y = 3.3 + 0.049*X. R-Square is 0.68. The regression is based on 20 annual observations. The firm intends to employ 480 workers next year. How many accidents do you project? How much confidence do you have in that forecast? Y = 3.3 + 0.049 * 480 = 3.3 + 23.52 = 26.52 accidents. This is not a time series, so next year = year 21 is of no relevance. Confidence comes from the coefficient of determination; the model explains 68% of the variation in number of accidents, which seems respectable. (Associative forecasting methods: Regression and correlation, moderate) 133. Demand for a certain product is forecast to be 8,000 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally-adjusted sales forecast for January? 8,000 x 1.25 = 10,000 (Time-series forecasting, easy) 134. A seasonal index for a monthly series is about to be calculated on the basis of three years’ accumulation of data. The three previous July values were 110, 135, and 130. The average over all months is 160. The approximate seasonal index for July is  (110 + 135 + 130)/3 = 125; 125/160 = 0.781 (Time-series forecasting,  moderate) 135. Marie Bain is the production manager at a company that manufactures hot water heaters. Marie needs a demand forecast for the next few years to help decide whether to add new production capacity. The company’s sales history (in thousands of units) is shown in the table below. Use exponential smoothing with trend adjustment, to forecast demand for period 6. The initial forecast for period 1 was 11 units; the initial estimate of trend was 0. The smoothing constants are = .3 and  · = .3 136. The quarterly sales for specific educational software over the past three years are given in the following table. Compute the four seasonal factors. 137. An innovative restaurateur owns and operates a dozen â€Å"Ultimate Low-Carb† restaurants in northern Arkansas. His signature item is a cheese-encrusted beef medallion wrapped in lettuce. Sales (X, in millions of dollars) is related to Profits (Y, in hundreds of thousands of dollars) by the regression equation Y = 8.21 + 0.76 X. What is your forecast of profit for a store with sales of $40 million? $50 million? Students must recognize that sales is the independent variable and profits is dependent; the problem is not a time series. A store with $40 million in sales: 40 x 0.76 = 30.4; 30.4 + 8.21 = 38.61, or $3,861,000 in profit; $50 million in sales is estimated to profit 46.21 or $4,621,000. (Associative forecasting methods: Regression and correlation, moderate) 138. Arnold Tofu owns and operates a chain of 12 vegetable protein â€Å"hamburger† restaurants in northern Louisiana. Sales figures and profits for the stores are in the table below. Sales are given in millions of dollars; profits are in hundreds of thousands of dollars. Calculate a regression line for the data. What is your forecast of profit for a store with sales of $24 million? $30 million? Students must recognize that â€Å"sales† is the independent variable and profits is dependent. Store number is not a variable, and the problem is not a time series. The regression equation is Y = 5.936 + 1.421 X (Y = profit, X = sales). A store with $24 million in sales is estimated to profit 40.04 or $4,004,000; $30 million in sales should yield 48.566 or $4,856,600 in profit. (Associative forecasting methods: Regression and correlation, moderate) 139. The department manager using a combination of methods has forecast sales of toasters at a local department store. Calculate the MAD for the manager’s forecast. Compare the manager’s forecast against a naive forecast. Which is better?

Law and Hickey Judicial Body

Case 9-1 PERFROMING RIGHT SOCIETY, LIMITED v. HICKEY Judicial Body: Zambia, High Court at Lusaka, 1978, Judge Sakala Facts: Copyright infringement, Innocence of infringement; Injunction for damages Issue: Defendant played records of copyright music during a public performance. Defendant also performed the song without the permission of the copyright owner. This is an infringement and the song’s composer wants to be compensated for the use of his song. History: Defendant violated copyright laws by performing and playing records at his disco. Defendant did admit, but did not understand that he had violated any law. Plaintiff filed for an injunction of damages, and any profits earned during the time that his songs were performed and played. Decision: Zambia, High Court at Lusaka ruled that the defendant was not clear about the copyright laws and did not intentionally set out to violate the laws. The court ordered that defendant would be liable for any profits made the night of the disco. Relevancy: This case provides a reminder that any invasion of a right of property gives cause of action to the owner against the person responsible for the invasion, regardless it was intentional or not. If an infringement is admitted , but at the time of the infringement the defendant was not aware and had no reasonable grounds for suspecting copyright subsisted in the work , or other subject matter to which the action relates, plaintiff is not entitled to damages , but is entitled to an account of profits. The judge was very understanding; defendant claims that he was not aware of copyright infringement. I think one needs to consider moral rights, as a business owner, one knows that licenses are usually needed to run a restaurant , disco , and club. A license is needed for the business establishment, a license if needed to serve alcohol, I suppose it slipped his mind in regards to the music he chose to play and perform. Reference: International Business Law, Text, Cases, and Readings, August, Mayer, and Bixby, Fifth Edition

Lack Of Conflict Resolution Skills Essay - 924 Words

As stated by Balderrama-Durbin, Allen and Rhoades (2012) a communication breakdown and more accurately a lack of conflict resolution skills in a marriage or partnership is a top cause for a dissatisfied marriage than can potentially lead to infidelity. Couples that react in a negative way to conflict within a relationship are more likely to experience or engage in Gottman’s four horsemen of the apocalypse; criticism, defensiveness, contempt, and withdrawal (Balderrama-Durbin, Allen Rhoades 2012). This type of negativity and lack of positive communication can lead one or both members in a relationship down the road to infidelity. When the matter of cheating occurs it can take a larger toll on the partner not involved in the affair and can lead to depression and anxiety ( An extramarital affair is a betrayal of trust and can be likened to a trauma (Schadea Sandberg, 2012). An affair can cause turmoil within the marriage as well as cause the individuals to cast doubt upon thems elves. 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