The Fukushima Daiichi disaster and the future implications for Research Paper

The Fukushima Daiichi disaster and the future implications for building new nuclear power plants in the United States - Research Paper Example The calamity was observed to have taken place in the eastern coast, Tohoku in Japan. The severe tremors of the quake were experienced at Fukushima as well (American Nuclear Society, 2012). The above mentioned catastrophe was later found to have significantly affected the ‘nuclear power station’ or rather the nuclear plant that is situated at Fukushima Daiichi in Japan. This disaster was believed to have triggered the most far-reaching ejection of radioactivity in contrast to the Chernobyl mishap that took place in 1986. This particular radioactivity release was considered to be even shoddier than the case or disaster of Three Mile Island that took place in 1979 in the United States. However, the occurrence of Fukushima Daiichi was considered to differ from the stated incidents of Chernobyl and Three Mile Island as the devastation that occurred at Fukushima was learnt to be triggered owing to natural tragedies which was a massive earthquake chased by tsunami. The discharg e of the radioactive gases was regarded as a consequence of the natural disaster rather than any malfunction with regard to the equipments and even ruled out any chances of human faults. The tsunami was measured to have ruptured the systems that helped in providing backup power and which were required for the reason of cooling down the reactors that were present in the definite plant. The breakdowns of the backup systems as a result made a large number of those reactors go through hydrogen explosions, fuel melting and ultimately radioactive releases (Holt, Campbell, & Nikitin, 2012). The paper will intend to focus on the present situation of the mishap that occurred at Fukushima Daiichi along with providing an insight into the various policies or stands taken by the US after this incident. The Accident at Fukushima Daiichi in Japan The earthquake that took place in March, 2011 in the eastern coast of the island Honshu in Japan resulted in initiating a mechanical shutdown of around e leven nuclear plants out of fifty five. Majority of the shutdowns were found to have carried on without any kind of further events. However, the Fukushima and the Onagwa nuclear plants were found to be the ones that were closely located towards the epicenter owing to which severe damages were suffered by those plants. The plant at Fukushima Daiichi, as a result of the earthquake, accompanied with the tsunami experienced hydrogen outbursts and grave damages in relation to nuclear fuel which triggered the discharge of a noteworthy quantity of radioactive elements in the surrounding environment (Holt, Campbell, & Nikitin, 2012). The contamination of the surrounding environment, with the radioactive elements that originated from the plants, compelled the moving out of communities from the adjacent or the neighboring areas till 25 miles. The forceful move out of the communities resulted in disturbing the regular life of around 100,000 residents, majority of whom were believed to remain b anned from accessing their respective homes for an indefinite period. The evacuation activities made in this context are considered to have checked the degree of radiation exposure with regard to the concerned population from surpassing the Japanese authoritarian boundaries in majority of the incidences. However, the consequences of the exposure to the radioactive gases with regard to the residents were measured not to be quite grave. Future deaths as well as

Aviva Case study Essay Example | Topics and Well Written Essays - 2500 words

Aviva Case study - Essay Example t model proposed by Kurt Lewin can be considered as an important change management model that can help an organisation to address problems and challenges in its decision to adopting and implementing change in business operation process. This three phase change management model consists of three stages, such as unfreeze, movement and refreeze (Neelin, 2010, p.91). These three steps have been discussed with respect to the case study of Aviva. The management of Aviva should try to adopt and implement this change management process before implementation of the newly developed strategy of job cutting across its global business operation. Unfreeze is the first and more important stage of this change management model. It is clear from the news that the management of Aviva has decided to job-cutting across globe in order to reduce the overall business operation cost. This sudden decision and implementation of this decision can affect the business process of the organization as it can demoralise several effective employees to perform effectively. Most importantly, it can create fear among each and every employee that he or she may be axed. Therefore, Unfreezing can be considered as an important stage as in this stage the managers or leaders of the organization as it is their responsibility to inform the sub-ordinates and followers within an organisation to be ready for change. Therefore, it is important for the leaders to notif y the employees of the Aviva about newly decided change process way before implementation of this strategy (Liu, 2011, p.89). Aviva is one of the leading organisations around the globe. Therefore, it is highly important to attract the attention of the global employees regarding this decided change management process so that the management of the organisation can avoid the issues, such as workplace conflicts and inadequate business output (Marcus, 2010, p.12). Movement can be considered as another important step of this model. In this step the

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In one way or another [1], mobile phones have changed everyone’s life. We can say that nowadays more than half of the population has a mobile phone or at least has used a mobile phone. Mobile communication networks made it possible to be connected and reachable even in the most remote places. One might question whether this is good or bad. The truth is mobile phones can nowadays save lives but it can also endanger life if not kept below the allowed limits. Since predictions show that in future most of the communication will be in the mobile domain (maybe even the internet), it makes sense to optimize mobile networks for the most efficient utilization of the frequency spectrum and for minimizing smog. Both the telecommunication network providers and the users can only gain in efficiency and usability if we theoreticians provide them with the most efficient algorithmic solutions to all interesting problems raised by these networks. While there exist a number of results on several aspects of telecommunication network planning and management, very little is known about models that use a ...

History of Cheese Essay

In developing a search strategy the most important thing is to decide on the keywords that sum up the information one wants. In my research paper I am researching on the history of cheese. The keywords in my topic are history and cheese. The synonyms of cheese include cheese flower, high mallow, malva sylvestris and tall mallow. History synonyms include account, chronicle and story. Cheese production and consumption has proliferated all over the world since its discovery years ago. This is due to its availability in the stores all over the world. The process of making is also easy and the ingredients that are used in its production are easily presented. The main ingredient is milk. Production of cheese has been converted from small scale production to large scale production as years since its discovery progress (Martin 12). Cheese refers to a group of milk-based foods which come in different flavors, forms and textures. It comprises of proteins and fat that is gotten from milk. The milk is produced by cows, goats, sheep or buffaloes (Harbutt 8). Cheese is produced by curdling of milk protein. The mild is acidified and an enzyme called rennet is added to cause the curdling. The solid and liquid are separated and modeled into different forms and shapes. There are a variety of cheese that includes cheddar, camembert, stilton and parmesan. The history of cheese according to a study done at the University of Georgia was discovered by an accident. An Arabian merchant was carrying milk in a pouch. The pouch made from a sheep’s skin contained rennin. Due to the scorching heat from the sun, the enzyme rennin was activated causing the milk to turn into solid curds. Though the exact time of the discovery of cheese is unknown, cheese appeared 3500BC. It was widely used in Asia and then migrated to Europe. Cheese was mentioned in Homer’s epic, The Odyssey. In the scene the Cyclops is making cheese and placing in wicker (University of Georgia 1). In the early days of cheese production, milk from different sources was mixed, and a variety of seasonings added to produce abundant flavors. Cheese was introduced in America after Mayflower landed and became a staple component in many American households. The first cheese factory was established in 1851 in Oneida County, New York. The Jesse Williams factory eliminated the production of cheese individually or by local farms. This flourished the production of cheese (Sokol 2). Writers like Richard claims that cheese was first forum in the Middle East. It was in form of sour milk which came into being after it was discovered that domesticated animals could be milked. It was observed that milk left in a container turned into a solid especially in hot temperatures. The curds and whey that were gotten from milk were discovered to be edible. The history of cheese is also mentioned in the old testament of the bible. David was fed with cheese of kine when he escaped across the river Jordan. David was also asked to bring with him ten cheeses to his commander of his brothers as they were participating in the battle against the philistines (Sokol 2). The ingredient of cheese is mostly milk. All kinds of milk like reindeer, caribou, yak, and llama have been used to produce cheese. In the process of cheese production, Sokol in his book, â€Å"And That’s How You Make Cheese† claims that protein in the milk is curdled and separated from water. The curdles are cut, cooked, drained and pressed to drain out more water. This leads to the production of a solid cheese that can be sliced. Archeologists that were excavating lake dwellings on the shores of Lake Neuchatel found potsherds that had pierced with holes. The findings dated back to six hundred years before Christ. The vessels had been used as drainers that were used to separate curds from whey (Toussaint-Samat 103). This made them conclude that the production of cheese which was mainly from sheep and goats milk had been done on their land earlier. Cheese contains high concentration of essential nutrients. Some of these nutrients include quality proteins and calcium that help in the development of the body. The invention of cheese grew tremendously due to the many benefits that are accrued from it. Cheese contains high concentration of calcium that helps in cavity prevention in the teeth. It helps in the development of strong teeth because it has low concentration of lactose. The consumption of cheese after a meal such as cheddar, Swiss, Brie and Monterey helps in the prevention of tooth decay. Cheese has also been proven to prevent cancer due to its high concentration of conjugated Linoleic acid and Sphingolipids (Roberts, Petrini and Hooper 350). The cheese business has thrived in the world greatly due to the large profits accrued from the industry. Cheese production and consumption has increased all over the world. Companies have cropped up and ventured in the industry thus creating a viable business enterprise. Some of the companies like the Arena Cheese factory, Aria Foods, Inc and Andrew & Everett are some of the companies that have ventured in the cheese industry. They have enabled many households to enjoy wide variety of cheese after their meals. Cheese like the Provolone and Ricotta are used as appetizers, salads. They are first refrigerated and wrapped in order to retain freshness. Other types of cheese like the Parmesan and Roman are grated on soups, bread and spaghettis. Camembert cheese is used o crackers or with fruit that help in appetizers and desserts. It is first refrigerated during storage and preserved in a temperature controlled room. The United States is the largest producer of cheese in the world. This has been facilitated by the large supply of milk in the US. The United States has dedicated large amount of funds and time on investment and research work. The availability of large farms involved in milk production has also contributed to the production of cheese in the US. There are more than four hundred and fifty plants in the United States dealing in cheese production. The companies operate on a strict sanitary and quality standards set up to control the cheese industry. This has helped the United States to position itself as the premium cheese supplier (Pastorino, Hansen and McMahon 67). One of the most popular types of cheese is Roquefort. This cheese falls in the family of blue veined cheese because throughout the cheese, there are thin blue lines amidst the cream colored cheese. Originally produced in Southern France, it has moved across the world as a favorite of so many. For this cheese, one can choose between goat, sheep, and cow milk. The sheep the French use to make their cheese are fed grass in which there is a high level of limestone or calcium carbonate. Cheese-France 1) If the milk has too much or too little acid in it, a different cheese may be formed or the milk can spoil at a faster rate and therefore making an unappetizing block of cheese. The limestone helps balance the pH level and acts as a buffer. At time the cheese maker adds rennet, to start the curdling process, and then must wait at least two hours to allow the rennet to form. People can’t eat Roquefort cheese because of an allergy to penicillin. As one article states, â€Å"The traditional way of getting penicillium is to place loaves of bread in a dark, damp space, and letting them mold. After ten weeks the bread crust is pealed back to reveal the inside of the bread, which is nothing more than a fine green powder, the powder is called penicillium†. After combining the bacterium with the curd, the cheese begins to take shape but, the cheese needs to monitored because many other byproducts must be removed throughout the curdling process. Once the salt has settled, the cheese maker must put holes into the cheese to allow the carbon dioxide to release into the air. The cheese maker will receive his final product about six months later, as the bacterium is hard at for that long. Encyclop? dia Britannica 1) Cheese since its discovery has evolved in a great way. The production of cheese used to be in small scales during the early years. Today it is produced commercially by large companies. The use of cheese has also changed from the time when it was used as food. Cheese is currently used in prevention of teeth cavities, salad and preservatives. This shows that since cheese was invented tremendous changes have been experienced thus leading to its development to what it is in the present world (Sokol 29).

The Underground Railroad And The Civil War - 1709 Words

The Underground Railroad was a passage to freedom for the slaves which made the slave-owners exasperate. The slaves had to risk their lives while travelling to the northern states but it was worth it as the result of such hard work was freedom. The underground railroad, a secret network running from the Deep South through the free states and to the Canadian border that helped slaves escape from the slave-holding states before the Civil War, allowed abolitionists and their allies to help runaway slaves, made conductors like Harriet Tubman famous, and reached its height after the passage of the 1850 Fugitive Slave Act. Underground Railroad was a labyrinth of secret routes and havens inaugurated by both black and white abolitionists,†¦show more content†¦The fugitive slaves had to go through a long a perilous journey to reach their freedom while traveling along the Underground Railroad. In a very short time, the fugitive slaves had to travel great distances usually on foot, boats or trains were used very infrequently. They had to put their life on a stake while escaping as they had no or very diminutive amount of food and no protection from the slave catchers chasing them. The fugitive slaves were pursued by the slave owners as well as other men. The slave owners used to publish reward posters offering payment for the capture of their property to entice others to assist in the capture of their slaves. The fugitives would get severely punished if they were apprehended. Their punishment for running away was to be branded, flogged, jailed, killed and even sold back into slavery. The Undergroun d Railroad was successful because the slave owners had no clue about the routes and even no one from the system knew the entire routes. Each conductor was responsible for leading the slaves from one station to the following and then the next conductor would lead them to the next station. This would continue until the whole route was traversed. The integrity of the routes as well as the fugitive slavesShow MoreRelatedThe Underground Railroad And Its Influence On The Civil War1545 Words   |  7 PagesThe Underground Railroad was neither underground nor a railroad. A revolutionary event taking place during the civil war, it was an informal network of sympathetic whites in violation of the Fugitive Slave Act passed in 1850 to help enslaved African s escape secretly in order to gain freedom in Northern States or Canada. This research paper will examine the movement of the Underground Railroad by reviewing primary and secondary sources available to successfully describe several sentim ents regardingRead MoreThe Underground Railroad And The American Civil War1203 Words   |  5 Pagesthe American Civil War (1861 – 1865). On January 1, 1863, four million slaves were freed when President Abraham Lincoln signed the Emancipation Proclamation. However, the road to freedom for many slaves was long and brutal. Countless African American slaves were tortured and terrorized and many lost their lives. In the early 1800s, a secret network of routes and safe houses was established to help fugitive slaves reach freedom. This system became known as the Underground Railroad and spannedRead MoreThe Underground Railroad s Working Against Slavery During The Civil War2260 Words   |  10 Pagesinvestigate the Underground Railroad’s work to resist against slavery during the Civil War. The author will collaborate on the dealings of people who were leaders of the Underground Railroad, U.S. political stance on slavery, and the actions that were carried out for the cause of freedom. The authors main focus of the paper will be centered on operations of the Underground Railroad, members involved, struggles they went through to free enslaved people. The writer will go into detail of the Underground RailroadRead MoreUnderground Railroad Essay Outline1333 Words   |  6 PagesTHE UNDERGROUND RAILROAD 1 The Underground Railroad Raymond Allen Setlock West Catholic High School THE UNDERGROUND RAILROAD 2 Our country’s history had its good times and also its bad times. One of our bad times in our country’s history was the time when the United States allowed slavery toRead MoreTaking A Stand Against Slavery1228 Words   |  5 Pagesdeterminations. The Underground Railroad had its earliest beginnings with runaway slaves fleeing from the the Southern United States into Canada. By confronting human bondage without direct demands or violence, The Underground Railroad played a definite role in the destruction of slavery. The Underground Railroad was a great way to escape the hardships of their living conditions. It gave them hope, inspiration, and strength. It was also a major impact on the CIvil War. The Underground Railroad consisted ofRead MoreUnderground Railroad And West Virginia1318 Words   |  6 PagesUnderground Railroad in Delaware, Maryland, and West Virginia For this critical review, I chose Underground Railroad in Delaware, Maryland, and West Virginia by William J. Switala. The purpose of this book was to explain exactly what the underground railroad was, how the slaves communicated with safe places, how it operated, and a few stories of how some of the slaves escaped away to the underground railroad and freedom. He also gives insight to what happened if the slaves were caught trying toRead MoreHarriet Tubman And The Underground Railroad1097 Words   |  5 Pagesnurse, and a caregiver. However her greatest achievement was working in the Underground Railroad. One of the many achievements of Harriet Tubman is her work as a spy during the Civil War. â€Å"There she headed up a team of eight black spies to operate behind the lines and provide intelligence for a Union raid of free slaves...I kept on singing until we brought all aboard. We got 800 people that day, and we tore up the railroad and fired the bridge†¦Ã¢â‚¬  (Doc. C) Harriet Tubman went over enemy line to helpRead MoreThe Civil War : Opposing Slavery1139 Words   |  5 PagesBefore the Civil War: Opposing Slavery â€Å"By 1860, the South contained more slaves than all the other slave societies in the New World combined’ (Roark, 331). Slavery was the backbone of the American Southern states’ economy, a highly controversial topic, and eventually the cause of the American Civil war. Even before the Civil War, there were many American groups who opposed slavery. In the early 19th century there were several forces that opposed slavery, both in the North and the South, they usedRead MoreEssay about The Underground Railroad1092 Words   |  5 Pageseverything changed. Slavery became more and more prominent and by the time of the Civil War, it was estimated that over 4 million slaves were working in the South. Slaves were treated worse than the dogs of their owners. They were given little to eat and tiny shacks to live in. If they disobeyed, they were beaten. For these reasons, many slaves decided to risk their lives and run away in search of freedom. The Underground Railroad was formed in 1810 and more than 100,000 slaves escaped between 1810 andRead MoreEssay about An Inside Look at the American Civil War999 Words   |  4 PagesA civil war is a war between citizens of the same country. From 1861 to 1865, America was fighting its own civil war. The American Civil War began when several Southern slave states declared their secession. When they seceded, they formed the Confederate States of America which was also known as the confederacy. The states remaining were known as the Union. Before the Civil War, slaves were treated unfairly, like property, rather than people. One court case that proves this is the 1857 court case

Univariate ratio analysis development - Free Essay Example

Sample details Pages: 11 Words: 3261 Downloads: 10 Date added: 2017/06/26 Category Finance Essay Type Analytical essay Did you like this example? Prior to Poors publishing of assets, liabilities, and earnings information in the American Railroad Journals of 1849, credit-worthiness was assessed using qualitative data. Poors publications were the first instances of quantitative data being used to assess the risk of commercial lending. This continued until the early 1930s when the first academic studies were carried out to assess the quantitative differences in financial ratios between well performing and failing businesses (Altman 1968). Univariate Ratio analysis development Between 1930 and 1968, financial ratios were analysed using univariate methodology to establish differences between failing and non-failing companies. This methodology analysed many ratios but individually. However the model could not find relationships between multiple ratios. An example of this was The Bureau of Business Researchs study (1930). It used 24 ratios to analyse 29 failing manufacturing companies. The results were compared to look for similar financial ratio characteristics in the sample. This showed that failing firms had common financial ratio characteristics which meant that it was possible to see potential failure of a firm before bankruptcy occurred. The research found that decline in the following ratios suggested potential future bankruptcy. Working Capital to Total Assets Surplus and Reserves to Total Assets Net Worth to Fixed Assets Fixed Assets to Total Assets Current Ratio Net Worth to Total Assets Sales to Total Assets Cash to Tot al Assets (BBR, 1930) The key weakness of the BBR model was that only failing companies had been compared. There was now a need to compare companies that had failed against companies that were trading successfully in order to see a true difference in ratio performance. Fitzpatrick chose 13 ratios to compare 19 failed and 19 successful companies in order to established a benchmark for average performance. Subjects whose ratios were better than average were deemed successful and those that were below average were deemed unsuccessful. This gave more meaningful results than the BBR study as it made a comparison between failed and non-failed companies rather than comparing failing companies only. Fitzpatrick suggested the most significant ratios were Net Worth to Debt and Net Worth to Net Profits. (Fitzpatrick, 1932) In 1935 BBRs study was repeated using a larger sample. 183 bankrupt companies from numerous industries were sampled. This increased the models generalisability. The re search suggested that the Working Capital to Total Assets ratio was most significant when predicting bankruptcy and the key trend was that the Current Assets to Total Assets ratio fell when companies were failing. (Smith and Wanakor, 1935) These studies were useful for differentiating between bankrupt and non-bankrupt firms and suggested common financial trends of a failing businesses; but they could not predict how soon bankruptcy was likely to occur. However Merwin suggested that trends of reducing Net-Working Capital to Total Assets, Current ratio, and Net Worth to Total Debt could predict company weakness up to five years before bankruptcy (Merwin,1942). The majority of bankruptcy prediction research up to 1946 suggested that the Working Capital to Total Assets ratio and the Current ratios were the most significant indicators of financial distress (Bellovary et al, 2007). However Chudson suggested that bankruptcy prediction models developed for multiple industry types gave greater generalisability but were less accurate than an industry specific model when predicting the bankruptcy timeframe (Chudson, 1945). Don’t waste time! Our writers will create an original "Univariate ratio analysis development" essay for you Create order Multiple Discriminant Analysis Model Development By 1968 the financial academics decided that univariate analysis models were not as accurate at predicting bankruptcy as required and considered the use of statistical evidence of past company performance would be a viable replacement. While academics agreed liquidity, solvency, and profitability were effective, they could not agree on their order of significance. The main issue was that a company could have low profitability but have good liquidity. In this instance a univariate model might give an ambiguous result. (Altman 1968) To address these issues Altman developed a model that established the most significant ratios and gave a weighting to each one so that they could be multiplied together. This created one formula that categorized companies into bankrupt and non-bankrupt entities. The model linked five different ratios into one formula that classified its sample into two groupings according to their characteristics. This technique is known multiple discriminant analysis or MDA. Altman called it the Z-Score model (Altman 1968). Altmans Z-Score Development Methodology 33 bankrupt companies and 33 non-bankrupt companies were chosen from the U.S.A. manufacturing industry. The bankrupt companies had all filed under chapter 10 of the National Bankruptcy Act between 1946 and 1965. To ensure reliability, validity, and generalisability the non-bankrupt companies were chosen using paired sampling and stratified random techniques. They were stratified by asset size and industry. To ensure comparability between samples, non-bankrupt companies were chosen that had continuous trading results for the same time period as the bankrupts (Altman 1968). Altman classified the 22 most common ratios used to indicate financial stress into five categories. They were liquidity, leverage, solvency, profitability, and activity. Out of the 22 ratios, five were chosen for their statistical significance in each category. Computer analysis was then used to establish the most accurate weighting for each ratio (Altman 1968). Ratio Weighting Working Capital to Total Assets (X1) 0.012 Retained Earnings to Total Assets (X2) 0.014 Earnings before interest and tax to Total Assets (X3) 0.033 Market Value of Equity to Book value of total debt (X4) 0.006 Sales to total Assets (X5) 0.999 Z score function formula = 0.012(X1) + 0.014(X2) + 0.033(X3) + 0.006(X4) +0.999(X5) The following financial ratios were selected to create the Z-Score formula: The Significance of the five selected ratios X1, working capital / total assets ratio measures liquidity. The working capital is calculated by taking away the current liabilities from the current assets. If a company continually makes an operating loss, its current assets will be depleting in relation to its total assets, thus reducing liquidity. This was in agreement of Merwin, 1942 who suggested this was the strongest indicator of potential bankruptcy. (Altman 1968) X2, Retained Earnings / Total Assets This measures the companys accumulated profitability. By definition new companies will have less retained earnings than older companies; therefore they are more at risk of failure. Statistics have shown that younger companies are more likely to fail than older companies in real world situations, hence the significance of the ratio. (Altman 1968) X3, Earnings before Interest and Taxes / Total Assets. This ratio measures the companys asset productivity. It eliminates all tax and leverage so that the true earning potential of the companys assets can be measured. Assets are valued by their earning power, and since bankruptcy is defined as when total liabilities are in excess of valued assets, this ratio is of great importance. (Altman 1968) X4, Market value of Equity / Book value of total debt. This is in essence a debt to equity ratio, though it includes the current market value of all the companys shares inclusive of regular and preference shares. The debt part of the ratio includes both long term and current liabilities. This ratio is used to measure how much asset value can be depleted before the company becomes insolvent. Altman has added the market value element to the ratio where previous studies have not. He suggests that this is more effective at predicting bankruptcy than the univariate analysis of net worth to total debt ratio which had been the most commonly used prior to his study. (Altman 1968) X5, Sales / Total Assets This is the capital turnover ratio which measures the companys ability to generate sales from its assets. Individually it is of least significance; however its discriminate ability contribution is ranked second out of the five ratios used so is of great importance to the formula. (Altman 1968) Z-score Meanings After much research and modelling, Altman concluded that if a companys Z-score was above 2.99 it could be classed as definitively non-bankrupt. However if its Z-score was below1.81then it could be classed as definitively bankrupt. However if its Z-score fell between these two figures then it could not be definitively classed as being in either category. This was known as the grey area or zone of ignorance. Altman found that companies who scored within this grey area were open to mis-classification. He suggested that it was difficult to predict bankruptcy in a company whos Z-score fell within the grey area, particularly those that had recently started trading. To address this he developed guidelines for the classification of companies that Z-scored within this area. Eliminating the grey area Altman selected all the companies from his first sample that had fallen into the grey area and classified them by six Z-score ranges between 1.81 and 2.99. The results showed that as the Z-score increased from 1.8, the number of companies whos Z-score falls in each sub range decreases to two companies at 2.67 2.68 and then increases again as it reaches 2.99. Altman suggested that this shows the mid range of the grey area to be 2.67 2.68. Therefore 2.675 is the optimum Z-score value that discriminates between Bankrupt and Non-bankrupt companies. (Altman, 1968) The Z-Scores Accuracy at Predicting Bankruptcy Altman tested his Z-score model accuracy to five years too. The results showed the following: Year Prior to Bankruptcy Accuracy (%) 1 95% 2 72% 3 48% 4 29% 5 36% Altman suggested that on the basis of these results, his Z-score model was accurate at predicting bankruptcy up to two years before the company was bankrupt. However after the second year Altman suggests that the model is unreliable. The reason being that in year three there is less than a 50/50 chance of accurate prediction. Altmans Conclusions Altman concluded that as the companies came closer to bankruptcy, the ratios X1 to X5 showed increasing deterioration. Moreover there was massive deterioration during years three and two before eventual bankruptcy. Hence the Z-score also deteriorates as the company gets closer to bankruptcy. As all samples were from the manufacturing sector the model is most accurate when predicting bankruptcy in companies from this sector. Strengths and weaknesses of the Z-score model Before the Z-score model was developed, bankruptcy prediction models were univariate and not industry specific. Altman revolutionised bankruptcy prediction modelling and from 1968 MDA became the industry standard methodology. Altmans Z-score model has proven to be reliable and valid. He also developed other variations on the Z-Score model including one for non PLC manufacturing companies. On this basis the model is very versatile for predicting bankruptcy in numerous applications. However when developing the private company Z-Score model, Altman used unadjusted financial data the sample was small giving rise to reliability issues. Another possible problem is that the Z-score, was developed using American company data, so there may be generalisability issues when Z-scoring non U.S. companies. https://epublications.marquette.edu/cgi/viewcontent.cgi?article=1025context=account_fac https://www.exceluser.com/tools/zscore.htm However Mandru et al suggest that Z-score models are not suitable in modern credit risk analysis. They suggest that it does not consider the economic and business cycle impact and should consider qualitative variables as well as market trends, market share, and the quality of the companys products and management. Ultimately these variables are reflected in the companies share prices; hence why modern commercial credit risk analysts such as Moodys use this data within their computer modelling systems. https://www.wseas.us/e-library/conferences/2010/Cambridge/AIKED/AIKED-12.pdf Bankruptcy Prediction Model development after Altman Logit Probit Models Bankruptcy prediction modellers continued to use MDA through to the late 1980s. As MDA was being phased out, Logit and Probit analysis models were becoming more popular. They are both regression type analyses that use both univariate and multivariate techniques. The Logit analysis model estimates the probability of an event occurring. It uses a set of independant variables i.e. the financial ratios, and predicts an outcome in the form of a 1 (bankrupt positive) or a 0 (non-bankrupt). Probit analysis models produce a threshold level where if the companys score exceeds it, it is classed as bankrupt. https://www.iasri.res.in/ebook/EBADAT/6-Other%20Useful%20Techniques/5-Logit%20and%20Probit%20Analysis%20Lecture.pdf Neural Network Analysis The Neural network analysis for bankruptcy prediction has been developed since the late 1980s. It is an advanced version of the Logit and Probit regression analyses. Using computer simulation, the model acts like a human brain, creating neural pathways to remember previous events of bankruptcy. The programme then processes the companys data and compares it to the previous bankruptcy events. The result is a statistical probability of the company failing. Thus a quantitative credit risk value can be applied. An example of this type of analysis is a Back-Propagation neural network which can recognise patterns of business behaviour. The downside is that it requires an immense amount of data to be entered in order to train the system to successfully establish the ratio weightings. It also has seven parameters which makes it a complex task to ascertain the correct model structure to gain a meaningful outcome (Shin et al, 2005). https://www.iasri.res.in/ebook/EBADAT/6-Other%20Useful %20Techniques/5-Logit%20and%20Probit%20Analysis%20Lecture.pdf Support Vector Machines Support Vector Machines are another form of artificial intelligent bankruptcy prediction computer programme. They are closely related to the back-propagation neural network but can be used in a more generalised setting. Shin et al suggest they are better than the back-propagation neural networks because they only need two parameters and a much smaller data set to train the system to generate accurate predictions. Hence the SVM is more accurate and gives better generalisability than the BPN. (Shin et al, 2005) Mertons Expected Default Frequency Model However in 1974 Merton developed a new way of calculating credit risk. The emphasis here is placed on predicting when the borrower is likely to default on a repayment loan as opposed to the likelihood of bankruptcy. Though bankruptcy prediction is of utmost importance when calculating credit risk, a company is more likely to default on a loan before ultimate bankruptcy. So in the case of the lender, the risk of default could be construed as more important than the companys risk of bankruptcy; hence the development of the EDF model otherwise known as the Expected Default Frequency. EDF measures three values: The companys current market value (calculated by the market value of total assets) The level of liability in the company (risk to default before further lending) The current market value and its vulnerability to large changes form the external environment. (How volatile are the companys assets?) This was the first time that qualitative and quantitative data had been used to assess credit risk in one model. An improvement over Altmans Z-score and other previous models that used quantitative data only. In 1990 Kealhofer et al, co-founders of KMV the credit ratings agency bought the rights to use this model and called it the KMV-EDF model. Moodys analytics bought KMV in 2002 and the EDF model became the most widely accepted credit default model used today. It is now known as the Moodys KMV RISKCALC with updated versions being developed continuously. (Dwyer et al, 2004) Summing up A key issue with bankruptcy prediction models is the difficulty in comparing models. Karels and Prakesh, 1987 suggest that some studies define financial failure as an inability to pay financial obligations, whereas others define financial failure as filing for official bankruptcy. If this hasnt been defined properly throughout the research topic it is difficult to tell which model it is best to use in which circumstances. Accuracy is essential when predicting bankruptcy. If a company heading for bankruptcy is declared to be healthy there are many implications for the ratings agency such as lawsuits and loss of future clients. In terms of accuracy ratings the neural networks developed 100% accuracy at their peak of development and MDA models did not improve much further than Altman in 1968 at 95%. Although neural networks are 100% accurate, complex computer programmes are needed to run such prediction models. The reason Altmans Z-score model is still so popular is that an acco untant can reliably predict bankruptcy to the same degree of accuracy using only an excel spreadsheet. There is a general consensus throughout the literature that a model that can accurately predict bankruptcy at the earliest stage is the most valuable. There is a trend of models becoming less accurate as they predict further into the future. There is also a theme throughout the literature regarding the limitations of bankruptcy prediction models. The industry sector and time frame of the test subjects must be the same as the samples used to develop the model. If this rule is not kept to, the reliability of the model reduces. (Grice and Dugan, 2001) There have been over 150 bankruptcy prediction models developed with optimal accuracy. It has been suggested that new uses for existing models should be found and that new research should use existing models to be tested on real life situations, such as studying individual industries. https://epublications.marquette.edu/cgi/viewcon tent.cgi?article=1025context=account_fac The gap in the research The literature suggests that prior to Moodys RiskCalc 3.1; MDA and neural network analysis have proven to be the most accurate ways to predict the risk of credit default. However, due to the limitations of this studys scope and relevant resources; the use of Riskcalc 3.1 and neural network analysis is inappropriate. Therefore MDA will be used to analyse the risk of bankruptcy in the automotive industry, ranking firms in order of risk. As Altman revolutionized bankruptcy prediction by becoming the first developer to use MDA methodology, and that the accuracy of this model type did not improve greatly after this time, the Z-score model is most appropriate to analyse the risk of bankruptcy in my chosen industry. Another reason to use Altmans Z-score model is that Moodys riskcalc 3.1 expected default frequency value is derived from the companys share price and most recent financial statements. By using Altman 1968 we can eliminate the influence of the stock market and compare the re al financial performance within the automotive industry and rank them according to risk of bankruptcy on the basis of their published financial accounts only. The advantage of Altmans Z-score models is that accountants can use them to advise potential investors which companies within an individual industry are safest to invest in. Moreover they can accurately predict in ranked order how soon each company will become bankrupt. This information is most valuable in times of recession and global financial instability. With the current economic uncertainty and global financial market crisis, this information will prove invaluable to creditors and investors. Automotive Industry relevance During the recent global economic downturn, with exception to the banking industry, the largest global industry affected was the automotive industry. Hardest hit was General Motors which was nationalised by the United States federal government after chapter 11 bankruptcy. In 2010 this industry produced in excess of 60 million vehicles. Parts manufacturers situated in almost every country worldwide rely heavily on this industry for their livelihood. Many support industries are also reliant on the global automotive industry too. KPMGs 2010 global automotive industry study suggests that the industry is running at almost 40% over capacity and little is being done to address the problem. Worst affected is North America followed by Western Europe and Japan. The problem is being made worse by existing manufacturers moving into the emerging markets in Brazil, Russia, India, and China. It is predicted that these markets will become overcapacities within 5 years, with China becoming 20% o ver built by 2015. The current industry over capacity is unsustainable. The potential financial and human cost if car manufacturers started defaulting on liability repayments could be as catastrophic as the recent banking crisis. Bankruptcy risk assessment in this industry is extremely important to the lives of people worldwide. If we can rank this industry by Altmans Z-score we take away the influence of share trading, thus showing each companys true quantitative financial position and risk of bankruptcy with a high degree of accuracy and will be able to rank each manufacturer accordingly. (KPMG, 2011) Word Count 2953

Diversity And Public Administration By Harvey L. White And...

In the book entitled, Diversity and Public Administration by Harvey L. White and Mitchell F. Rice , White and Rice (2010) stated challenges will form from changes in demographics which are affecting the demands of delivery and visions of products and services. Since 2000, minority population has increased dramatically. In result of minority population increasing, public organizations have a more diverse work environment. In the workplace, diversity can be a benefit. According to the article entitled , â€Å"Advantages and Disadvantages of Diversity in the Workplace† by David Ingram, Ingram(2015) stated that by have a diverse workplace allows the company to utilize their employees’ cultural difference to strengthen the organizations’ productivity. Another advantage of diverse workplace is that it increase employee’s personal growth. By employees being expose to cultural difference and new ideas, this allows employees to have global perspective on how to conduct business (Ingram,2015). Diversity can also have disadvantages in the workforce. One of the disadvantages is the ability of employees to respect each other cultural differences. Diverse workplace has to endure several challenges and issues. One of the challenges of organizations having diverse working environment is gerontology. Managers concerns with workers being older is that they do not have ability to learn and adjust to new policies and methods. In the public organizations, age is a challenge becauseShow MoreRelatedStephen P. Robbins Timothy A. Judge (2011) Organizational Behaviour 15th Edition New Jersey: Prentice Hall393164 Words   |  1573 PagesTitle. 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