The Crucible Essays (776 words) - The Crucible, Tituba, John Proctor

The Crucible The Crucible The trumped-up witch hysteria in Salem, Massachusetts, deteriorated the rational, and emotional stability of its citizens. This exploited the populations weakest qualities, and insecurities. The obvious breakdown in Salem's social order led to the tragedy which saw twenty innocent people hung on the accusation of witchcraft. Arthur Miller, author of The Crucible, used hysteria to introduce personality flaws in vulnerable characters. A rigid social system, fear, and confusion were evident conditions that became prevalent before and during the witchtrials. These conditions only contributed to the tragedy in Salem. The isolation of the Puritan society created a rigid social system that did not allow for any variation in lifestyle. The strict society that was employed at this time had a detrimental effect on the Proctor family. John Proctor, a hard working farmer who had a bad season the year before and struggling this year was occasionally absent at Sunday service. This was due to the fact he needed to tend to his crops. Also, Proctor did not agree with the appointment of Mr. Parris as the newest minister, and therefore did not have his last child baptized. With the latest craze of witchery and swirling accusations, John Proctor was easily indicted of being a messenger for the devil by the testimony of his disillusioned servant Mary Warren, who in the past committed perjury. The court who heard the testimony easily accepts it because she is a church going person, while John Proctor slightly deviates from the norm. This transfer of blame is also noticeable when the truth is first discovered about what the girls were doing in the woods. The girls were not blamed. The blame was put on Tituba, the "black" slave who was said to have "charmed" the girls. Abigail swears that "she [Tituba] made me do it".(pg.40) It is obvious that in the Puritan society that whatever did not conform to what the masses had decided as proper, then the deviated, but innocent, were to blame. This practice contributed to the tragedy in Salem. The fear of what was unknown created an uneasiness within Salem's population that added to Salem's social demise. The circumstances surrounding the witchtrials gave residents something to blame the supernatural on. The condemning of Tituba was mainly due to this. When Tituba took the girls into the woods, and they performed their ceremony, something the Puritans were not accustom to, she convicted of witchery. Along with Tituba, Martha Corey was indicted solely because she would not allow Giles to read them. Giles also stated that "I tried and tried and could not say my prayers. And then she close her book and walks out of the house, and suddenly--mark this--I could pray again!"(pg.38) This evidence of witchery is preposterous. The only thing that is true is that Giles was not allowed to read the books, and because he did not what the books contained, he feared them. This type of reaction throughout the community to the supernatural, and what was not known indicted many people, and contributed to the tragedy in Salem. The state of mass confusion in Salem created a society of individuals who were only concerned with what was good for them, so that they would not be the next one implicated in the witchery scandal. This situation is clearly evident after Hale becomes privy to the true story of what happened in the woods. Abigail abandons Tituba, and accuses her of "sending her spirit on me in church; she makes me laugh at prayer"(pg.41), and Abigail also says Tituba "comes to me every night to go and drink blood"[devil's blood](pg.41). Abigail reacts like this only to save her from being suspected of witchery. At the end of Scene One, many community members are accused of consorting with the devil. These names were given by all of the girls present that took part in the ritual in the woods, in an attempt to return to the graces of God and to be declared bewitched. This was a common reaction that many had when accused of witchery.It led to confrontations which pitted neighbor versus neighbor and husband versus wife. The delirium which created this situation aided in the misfortune proceedings in Salem. The evident destruction of Salem's social order was due to rigid stipulations on deviation, fear of the unknown, and mass confusion. These conditions left Salem susceptible to an apparent epidemic such as witchcraft. The susceptibility that Salem fell victim to, was the cause of a great tragedy which saw twenty townspeople hung at the hands of the state. The Crucible written by Arthur Miller is

Free Essays on Of Mice And Men Lennie Analysis

Lennie Small, from John Steinbacks Of Mice and Men, is the least dynamic character, but also the star of this short but impacting novel. John Steinbacks conception of this novel is centered on Lennie’s simplicity. Throughout the entire book, Lennie’s personality and life seem based on three things: soft things, devotion to his protector (George) and his dream of one day owning a farm. Within the novel, Lennie shows no significant changes, development, or growth; yet is a favorite character by most readers. To start with, Lennie is protected. Lennie is protected by Slim, but mostly by George. Slim keeps Lennie from getting fired when Curley got his hand â€Å"caught in a machine† (64). Lennie is also protected by George; as friends they stick together, â€Å"I got you. We got each other† (104) and as friends they contribute all they can. George protects Lennie from many things; but is most remembered for protecting Lennie from being killed painfully by Curley. Candy's regret that he didn't kill his dog himself, foreshadows George's decision to shoot Lennie before Curley gets to him first. Also, Lennie is devoted. Devoted to the rabbits, and devoted to George. The rabbits are an important part of the novel. The rabbits are Georges way of keeping Lennie from getting into any trouble. George often reminds Lennie that he â€Å"†¦aint gonna get in no trouble, because if you do, I wont let you tend the rabbits† (16). Lennie’s devotion to George is very strong; he does everything George tells him to do, simply because George is his friend. In Conclusion, Lennie is a dreamer. He someday dreams of having â€Å"†¦ a little house an’ a room to our self†¦We’d know what came of our planting†¦An it’d be our own, an’ nobody could can us† (58). The fact that two men during this time period with a dream like that that comes so close to coming true makes them so different from other men. Lennie shows enthusiasm for his dream, spr... Free Essays on Of Mice And Men Lennie Analysis Free Essays on Of Mice And Men Lennie Analysis Lennie Small, from John Steinbacks Of Mice and Men, is the least dynamic character, but also the star of this short but impacting novel. John Steinbacks conception of this novel is centered on Lennie’s simplicity. Throughout the entire book, Lennie’s personality and life seem based on three things: soft things, devotion to his protector (George) and his dream of one day owning a farm. Within the novel, Lennie shows no significant changes, development, or growth; yet is a favorite character by most readers. To start with, Lennie is protected. Lennie is protected by Slim, but mostly by George. Slim keeps Lennie from getting fired when Curley got his hand â€Å"caught in a machine† (64). Lennie is also protected by George; as friends they stick together, â€Å"I got you. We got each other† (104) and as friends they contribute all they can. George protects Lennie from many things; but is most remembered for protecting Lennie from being killed painfully by Curley. Candy's regret that he didn't kill his dog himself, foreshadows George's decision to shoot Lennie before Curley gets to him first. Also, Lennie is devoted. Devoted to the rabbits, and devoted to George. The rabbits are an important part of the novel. The rabbits are Georges way of keeping Lennie from getting into any trouble. George often reminds Lennie that he â€Å"†¦aint gonna get in no trouble, because if you do, I wont let you tend the rabbits† (16). Lennie’s devotion to George is very strong; he does everything George tells him to do, simply because George is his friend. In Conclusion, Lennie is a dreamer. He someday dreams of having â€Å"†¦ a little house an’ a room to our self†¦We’d know what came of our planting†¦An it’d be our own, an’ nobody could can us† (58). The fact that two men during this time period with a dream like that that comes so close to coming true makes them so different from other men. Lennie shows enthusiasm for his dream, spr...

Tear Gas - What to Do If You Are Exposed

Tear Gas - What to Do If You Are Exposed Tear gas (e.g., CS, CR, Mace, pepper spray) is used to control riots, disperse crowds, and subdue individuals. It is intended to cause pain, so exposure to it is not fun. However, the effects of the gas usually are temporary. You can expect relief from most of the symptoms within a couple of hours of exposure. This is a look at how to prepare for a potential encounter with tear gas, with tips on how to respond. Symptoms of Tear Gas Exposure stinging and burning of the eyes, nose, mouth, and skinexcessive tearingblurred visionrunny nosesalivation (drooling)exposed tissue may develop a rash and a chemical burncoughing and difficulty breathing, including a feeling of chokingdisorientation and confusion, which may lead to panicintense anger The disorientation and confusion may not be totally psychological. In some cases, the solvent used to prepare the tear gas may contribute to the reaction and may be more toxic than the lachrymatory agent. What to Do Tear gas usually is delivered in the form of a grenade, which is fitted onto the end of a gas gun and fired with a blank shotgun cartridge. Therefore, you may hear shots being fired when tear gas is used. Dont assume you are being shot at. Do not panic. Look up when you hear the shot and avoid being in the path of the grenade. Tear gas grenades often explode in the air, delivering a metal container which will spew gas. This container will be hot, so do not touch it. Do not pick up an unexploded tear gas canister, since it could explode and cause injury. The best defense against tear gas is a gas mask, but if you dont have a mask there are still steps you can take to minimize damage from tear gas. If you think you might encounter tear gas you can soak a bandana or paper towel in lemon juice or cider vinegar and store it in a plastic baggie. You can breathe through the acidified cloth for several minutes, which should give you sufficient time to get upwind or reach higher ground. Goggles are a great thing to have. You can use tight-fitting swim goggles if chemical safety goggles arent available. Dont wear contacts anywhere you might encounter tear gas. If you are wearing contact lenses, immediately remove them. Your contacts are a loss as is anything else you cant wash. You can wear your clothes again after you wash them  but wash them separately that first time. If you dont have goggles or any sort of mask, you can breathe the air inside your shirt, since there is less air circulation and therefore a lower concentration of the gas, but that is counterproductive once the fabric becomes saturated. First Aid First aid for eyes is to flush them with sterile saline or water until the stinging starts to abate. Exposed skin should be washed with soap and water. Breathing difficulties are treated by administering oxygen and in some cases using medication that are used to treat asthma. Medicated bandages can be used on burns.

Music Technology Coursework Example | Topics and Well Written Essays - 1000 words

Music Technology - Coursework Example +4dBu is generally found in professional level equipment such as public address systems. Finally, -85dBu indicates the level of noise floor (residual electronic noise) in the sound amplifying system. Noise floor is the measure of the lowest audible sound that can be amplified by the system. Collectively, the three levels are known as the operating line levels of an audio system (Glenn, 1998, p.731). A.2. What do the ranges of 24 dB, 89 dB and 109 dB indicate? Explain the function that each of these ranges has in an audio system? (9 marks) The range 24dB in the diagram indicates the headroom of the sound system (peak level- nominal level) = +28dBu-(+4dBu) =24dBu. According to Rossing (2002, p.168), the main function of this range is to describe the capacity of the sound amplifying system to handle loud sound peaks. For example, a sound system with a larger headroom range is often able to handle significantly louder sound peaks before the sound is distorted or broken. On the other hand , 89 dB range shown in the diagram indicates the S/N ratio (Signal to Noise ratio) of the sound amplifying system. Generally, S/N ratio refers to the difference between the nominal level of the sound system and the noise floor. When the S/N ratio is combined with the headroom, the result is known as the dynamic range assuming that there is no signal below the noise floor in the sound amplifying system (Borwick, 1980, p.45). ... gard, the dynamic range of the system function as the indicator of the difference between the electro-acoustic noise floor and the peak output level of the audio system. B. Why does the graphic refer to two different kinds of dB? Explain both types extensively using formulas for both types too. (15marks). The graphic diagram refers to the two types of dB namely the dB (SPL) and dBu scales. With regard to the dB (SPL), the primary variable measured is the sound pressure level in the audio system. This kind of dB is achieved by measuring the ratio amplified input signals using the logarithmic formula: 10  log  (P2/P1)  dB   Ã‚  where the log is assumed to base 10. (Rossing , Moore , Wheeler, 2002, p.87). The other type of dB used in the diagram is dBu which generally indicates the output of the sound amplifying system (amplitude ratios). dBu is the unit measure of the absolute value of the electrical potential of the system in volts (relative to the sound produced). The formula for this kind of dB is: 20 log10 (V/ V0) = 20 log10 (V/ 0.7746), where voltage is measured using root mean square (Glenn, 1998, p.851). ` C. About the values showed above, would you considered this to be a professional system or only a home-made-like system (e.g. cassette or vinyl) based)? Explain your choice. (5marks). According to the values given in the diagram, the system illustrated is most likely to be a professional system. For example, headroom of 24dB is capable of ensuring high fidelity sound that is only found in the professional sound amplification systems which are often comparatively more sophisticated than the normal homemade systems like those using vinyl and cassettes. Additionally, the large dynamic range indicated in the diagram is a likely suggestion that the system has a high

Writing an online news story about a speech in AP style Article

Writing an online news story about a speech in AP style - Article Example The realization however was not immediate. He did not even expect to learn it. He even had an unusual and different reason when he joined the military service. He signed up because college tuition was expensive and joining the military would help him get his degree. Wes Moore had no appetite for fighting or war even when he joined the military service. He just wanted to finish school through the help of military service. But when 9/11 came, it dramatically changed the role of military and that included Wes Moore’s role in the service. The 9/11 attack was about that unforgettable day in September 11, 2011 when terrorists simultaneously hijacked airplanes and slammed it to various structures the most famous of which was the World Trade Center that collapsed for the world to see (www.history.com, nd). From schooling in UK, he rejoined the Army and was sent overseas to fight as an officer. Wes Moore did not talk in details about his tour of duty as most servicemen would indicating that he had his share of the fight. Suffice to say that he could relate with the experience of a war to speak candidly about it and to also tell what many veterans are struggling. The speech was told in a manner that the listeners could relate. In the speech, Wes Moore bared the humanity of these struggles and the brotherhood forged in combat in the name of service without the heroic or stern military faà §ade. No adventurous combat stories were told but only the sacrifices made by the men and women in uniform in the name of service. And these experiences changed them with some still haunted by it. Thus, his apologies for what they have become (such as avoiding big crowds) that most of us would find odd solicited understanding and sympathy. And Wes Moore advocated that from the understanding and appreciation of these struggles should the words â€Å"thank you for your service† be contextualized and said for

Macbeth and R+J Essay Example for Free

Macbeth and R+J Essay Shakespeare communicates many moods in Macbeth and Romeo Juliet; the main moods are love, and hate fuelled betrayal, and in my work these are the themes I will analyse. In Romeo Juliet and Macbeth, vital characters have had to betray in order to achieve love, for example; In Romeo and Juliet; Juliet has to betray the authority of her father in order to fulfil her affection for Romeo. In terms of love this would mean that: The Storge (unconditional love, shared amongst family) that Juliet once felt for her father was met by misogyny (Hatred for Women) upon his realisation of Juliet’s Eros (love between two people) towards Romeo. Despite her subdued character, Juliet is adamant on not marrying Paris and betraying her family for Romeo. A quote to support this is; If all else fail, myself have power to die This signifies that Juliet would rather die than enter something that it not right. A quote from Juliet’s Father; â€Å"How now, how now, chop-logic! What is this? † – His use of repetition emphasises his fury in response to Juliet’s new found aggression in character, and his rhetorical question presents his dominance and highlights the hierarchy that was in place at the time to allocate superiority to male’s in a family, in this scene; the breakdown of Juliet’s Father and Mother’s relationship is most apparent. Furthermore this is a point where Juliet is most isolated from her family and becomes closer to Romeo. My alternate interpretation is that Juliet did not betray her family, but her family were betrayed by there own pride, Pride was the cataclysmic barrier between acceptance and condemnation. The most potent character development is Juliet’s, throughout the play she matures and becomes a lot more retaliant to authority and starts to become herself rather than obedient to thers, this process is strengthened because of the speed she has had to become responsible; due to the mandatory pressures she is expected to comply with and the swift 7 day time period in which the story is conveyed, this development in character gives her the willpower to betray her family; which also ultimately supports my point. The dramatic techniques used in Romeo and Juliet create a hastily strong impact due to the play being condensed into a week and an ambience of anxiety. In Macbeth there are several similarities that also support my point; Macbeth has to betray King Duncan despite his loyalty and Philia (The love of Friendship) has to betray him in order to acquire the Eros from the ever superior Lady Macbeth, this situation contradicts all convention as society was heavily patriarchal which suggests that women should be submissive to men; however in this occurrence Macbeth conforms with Lady Macbeths demands to murder King Duncan, this is the main contrast between Macbeth and Romeo Juliet. A quote that coincides with this is; â€Å"But screw your courage to the sticking-place, and well not fail† – Lady Macbeth challenges Macbeth to murder King Duncan, presenting her dominance and ambition over Macbeth. A quote from Macbeth after when placing the blame on the guards for King Duncan’s murder; Here lay Duncan, his silver skin laced with his golden blood†¦ the murderers, steeped in the colors of their trade – This illustrates the betrayal that Macbeth has committed, as his use of alliteration strengthens the deviation of this line and the fact that he is further betraying King Duncan post his death by laying the culpability on the guards; simultaneously justifying there execution. Additionally an alternative interpretation of betrayal is explained using this quote; â€Å"Who can be wise, amazed, temprate, and furious† – Macbeths use of antithesis (underlined) displays how he has slowly become contradictory since his brutal murder of King Duncan which I believe indicates he has betrayed his own nature. The main dramatic technique used in Macbeth is dramatic irony, dramatic irony is where something that is indicated at the start of the play will either become true or change at the end of the play or furthermore could mean the opposite of hat might happen. An example of this is that; â€Å"This castle hath a pleasant seat; the air nimbly and sweetly recommends itself unto our gentle senses. † – This is a significant use of dramatic irony, the description of the environment is pleasant; however unbeknown to King Duncan, this is where he will be murdered, and this also links in to betrayal. Moreover, at the start of the play, Macbeth describes Banquo to be a â€Å"Friend† however later in the play we know that Banquo becomes his enemy and has to be killed due to the fact he is a great threat to Macbeth’s throne; which is a further deception that Macbeth has carried out. Conclusively; I believe Shakespeare’s whole use of dramatic irony links in to betrayal directly, because the constant use of dramatic irony means that the plot keeps changing; effectively displaying that the plot betrays itself continually. This constantly conveys a mood of false anticipation and an eerie sense of the unknown. Reading more in depth into both plays, there are further comparisons; Such as the use of fate, when Romeo and Juliet fall in love we know that because of their backgrounds; it will lead to death, and similarly in Macbeth the witches tell a prophecy in which Macbeth becomes king and then dies both plays contain different forms of tragedy however both plays meet the same end. Evidence to support this in Romeo and Juliet is: â€Å"A pair of star-crossd lovers take their life† – Meaning that two different sided (Montague/Capulet) lovers take their life. And for Macbeth: â€Å"All hail, Macbeth, thou shalt be king hereafter! † – This is the prophecy of Macbeth becoming king and then dying. Furthermore, in Romeo ; Juliet and Macbeth, death is a necessary price to be paid for peace, for example, Romeo and Juliet have to die in order for the Capulet’s and Montague’s to live in tranquillity, to support this, a quote from the beginning soliloquy: â€Å"What here shall miss, our toil shall strive to mend† – This means that where we have failed before we will strive to succeed now, signifying that Romeo and Juliet’s death were essential to the ‘Fair Verona’ achieving peace, likewise in Macbeth, Lady Macbeth and Macbeth’s death was also fundamental to harmony being restored to the ingdom, an additional quote to support this is: â€Å"The usurpers cursed head: the time is free† – the quote is about Macbeth’s severed head, and diverts attention to the fact that with his death ‘the time is free’ which implies it is peaceful. However contrary there are many differences, for example the types of love/relationship between the two couples in each play; In Macbeth there relationship is very unstable and Lady Macbeth is very domineering over Macbeth; also there love for each other is not through passion; but through the lust for greed and power as Lady Macbeth is desperate for Macbeth to become king by killing King Duncan and betraying his loyalty to him: â€Å"And take my milk for gall, you murd’ring ministers† – This suggests she will do anything to become Queen and accentuates her ruthless nature; it also underlines the imbalanced relationship in which the position of superiority continuously changes dramatically. At the start Macbeth is a brave and noble hero and he is superior however as the play goes on and when Macbeth’s manhood is questioned by Lady Macbeth â€Å"are you not a man? † he then becomes submissive and is dictated by Lady Macbeth. In Romeo and Juliet

Raymond George Neher :: essays research papers fc

Because roads, streets, highways, boulevards, and freeways are an everyday part of our life, they understandably are part of our art. In the foreground or the background, they secure our art to reality, serve as symbols, or twist and turn in ways never dreamed by the imagination. Raymond Neher used roads and highways as his subject in many of his paintings. He began painting for his own benefit, because he â€Å"Enjoyed putting brush to canvas.† Raymond George Neher was born in Orange, New Jersey on September 14, 1943; he was the only child to Rudolph Neher and Evelyn Posadzki. Neher was awarded his Bachelor of Architecture form the Carnegie Mellon University and his Masters from the Columbia University. He began his career as an architect in New York City. In 1973 he transferred to San Francisco, California, where he worked on the Master Plan for a New Community in Ahwaz, Iran. He was well known and appreciated for his work in historical restorations and adaptive reuse. His projects included work on art and science museums, hotels and spas, hospital and medical school, as well as construction administration. As an artist his career spanned nearly 40 years. Neher worked mostly in acrylic paint on canvas. His works have been shown in exhibitions all across the United States of America and are in private collections throughout the United States, as well as Amsterdam, Rome and Santorini, Greece. Neher joined the Fort Mason Prin tmakers in the early 1980’s and created etchings and monoprints that often complemented his canvas work. Many of his subjects sprang from his travels around California’s Central Valley Interstate 5 highway. His roadscapes paintings he created were on photo quality. The images he creates, whether it is a highway, a bridge or a suburban street, are always free of pollution, road kill and litter. The paintings are full of colour which makes the painting a bit surreal, as if the image is just too good to be true. All his roadscapes are from the perspective a person in a vehicle on the road, making the viewer feel more engaged with the painting, as if they are actually there. The painting above is called Mount Hood Highway. Neher has used such contrasting colours to layer the painting. His use of straight lines and angles on the road, pine trees and the snow covered mountain in the background brake up the painting causing the painting to be easier to take in by the viewer.

Importance of Child Friendly Education Essay

All this does not mean that you turn your class into a place of dreary learning. First of all, the activities you would use with adults can work, but make them shorter. For example, a role play may have to last five minutes instead of 10. Also make sure activities are varied: an activity that involves moving about and noise needs to be followed by a quiet task that allows kids to â€Å"cool down†. Remember also that children will not do a task because it is good for their English. Tasks need an end result rather than being open-ended. Building in a quiz or competitive element can work or ask learners to produce work that is displayed on the wall. It’s a great feeling when the children are busy, but their enjoyment of a task might manifest itself in terms of noise. Develop signals to get attention. This can be a raised hand or switching off the lights. Whatever you do, don’t try to out-shout a class because they will always win. Where groups of children are getting really loud it may be time to change the groups around. Adults like praise, but children really love praise. Avoid over-praising individuals and try to compliment whole groups. Use affirmative commands like, â€Å"Please speak English† rather than negative reprimands like, â€Å"Stop speaking Spanish!† You’ll also avoid problems if you set out rules at the beginning of the course. If possible, involve the children in preparing and writing out the class rules – it is especially good practice with modal verbs. A child that then breaks these rules will see greater justice than if you make up your own rules on the spot. More importantly, you will be punishing the inappropriate behaviour, not the child.

Stability of Beta over Market Phases

International Research Journal of Finance and Economics ISSN 1450-2887 Issue 50 (2010)  © EuroJournals Publishing, Inc. 2010 http://www. eurojournals. com/finance. htm Stability of Beta over Market Phases: An Empirical Study on Indian Stock Market Koustubh Kanti Ray Assistant Professor, Financial Management at Indian Institute of Forest Management (IIFM), Bhopal, India. E-mail: [email  protected] ac. in Abstract The significant role played by beta in diverse aspects of financial decision making has forced people from small investors to investment bankers to rethink on beta in the era of globalization.In the present changing market condition, it is imperative to understand the stability of beta which augments an efficient investment decisions with additional information on beta. This study examined the stability of beta for India market for a ten year period from 1999 to 2009. The monthly return data of 30 selected stocks are considered for examining the stability of beta in diffe rent market phases. This stability of beta is tested using three econometric models i. e. using time as a variable, using dummy variables and the Chow test. The results obtained from the three models are mixed and inconclusive.However there are 9 stocks where all the three models reported similar signal of beta instability over the market phases. Keywords: Stability of Beta, Phase wise beta, Indian Market Beta, Dummy Variable, Chow Test 1. Introduction The Capital Asset Pricing Model (CAPM) developed by Sharpe (1964), Lintner (1965) and Mossin (1966) has been the dominating capital market equilibrium model since its initiation. It continues to be extensively used in practical portfolio management and in academic research. Its essential implication is that the contribution of an asset to the variance of the market portfolio – he asset’s systematic risk, or beta risk – is the proper measure of the asset’s risk and the only systematic determinant of the asse t’s return. Risk is the assessable uncertainty (Knight, 1921) in predicting the future events that are affected by external and internal factors. Sharpe (1963) had classified risks as systematic risk and unsystematic risk. The elements of systematic risk are external to the firm. The external factors are changes in economic environment, interest rate changes, inflation, etc. On the other hand, internal factors are the sources of unsystematic risk.Unsystematic risks are categorized as business risk or financial risk specific to the firm. The systematic risk related with the general market movement cannot be totally eradicated through diversification. The unsystematic risk, which is confine to a firm, can be eliminated or reduced to a considerable extent by choosing an appropriate portfolio of securities. Some of the sources of unsystematic risk are consumer preferences, worker strikes and management competitiveness. These factors are independent of the factors effecting stock market.Hence, systematic risk will influence all the securities in the market, whereas unsystematic risk is security specific. International Research Journal of Finance and Economics – Issue 50 (2010) 175 Theoretically defined, beta is the systematic relationship between the return on the portfolio and the return on the market (Rosenberg and Marathe, 1979). It refers to the slope in a linear relationship fitted to data on the rate of return on an investment and the rate of return of the market (or market index). Beta is a technique of telling how volatile a stock is compared with the rest of the market.When the return on the portfolio is more than the return on the market, beta is greater than one and those portfolios are referred to as aggressive portfolios. That means, in a booming market condition, aggressive portfolio will achieve much better than the market performance. While in a bearish market environment the fall of aggressive portfolios will also be much prominent. O n the other hand, when the return on portfolio is less than the market return, beta measure is less than one and those portfolios are treated as defensive.In case of defensive portfolios, when the market is rising, the performances associated with it will be less than the market portfolio. However, when the market moves down, the fall in the defensive portfolios would also be less than the market portfolio. In those situations where, the return of the portfolio accurately matches the return of the market, beta is equal to one that rarely happens in real life situations. Beta estimation is central to many financial decisions such as those relating to stock selection, capital budgeting, and performance evaluation. It is significant for both practitioners and academics.Practitioners use beta in financial decision making to estimate cost of capital. Beta is also a key variable in the academic research; for example it is used for testing asset pricing models and market efficiency. Given the importance of this variable a pertinent question for both practitioners and academics is how to obtain an efficient estimation. This study is aimed at testing the beta stability for India. Further the stability of beta is of great concern as it is a vital tool for almost all investment decisions and plays a significant role in the modern portfolio theory.The estimation of beta for individual securities using a simple market model has been widely evaluated as well as criticized in the finance literature. One important aspect of this simple market model is the assumption of symmetry that propounds the estimated beta is valid for all the market conditions. Many studies questioned this assumption and examined the relationship between beta and market return in different market conditions, but the results are mixed and inconclusive. In this paper, an attempt is made to investigate the stability of beta in the Indian stock market during the last 10 years i. . from August 1999 to August , 2009. With this objective, the paper is divided into five sections including the present section. Section 2 reviews the existing literature and discusses the findings of major empirical researches conducted in India and other countries. Section 3 describes the data sources and methodology. Section 4 outlines the results of tests for investigating the stability of beta and its findings. Section 5 is dedicated to summary, conclusion and scope for further research in the area. 2. Literature reviewSeveral studies are carried out to study the nature and the behavior of beta. Baesel (1974) studied the impact of the length of the estimation interval on beta stability. Using monthly data, betas were estimated using estimation intervals of one year, two years, four years, six years and nine years. He concluded that the stability of beta increases significantly as the length of the estimation interval increases. Levy (1971) and Levitz (1974) have shown that portfolio betas are very stable w hereas individual security betas are highly unstable.Likewise Blume (1971) used monthly prices data and successive seven-year periods and shown that the portfolio betas are very stable where as individual security betas are highly unstable in nature. He shows that, the stability of individual beta increases with increase in the time of estimation period. Similar results were also obtained by Altman et al (1974). In both the cases, initial and succeeding estimation periods are of the same length. Allen et al. (1994) have considered the subject of comparative stability of beta coefficients for individual securities and portfolios.The usual perception is that the portfolio betas are more stable than those for individual securities. They argue that if the portfolio betas are more stable than those for individual securities, the 176 International Research Journal of Finance and Economics – Issue 50 (2010) larger confidence can be placed in portfolio beta estimates over longer peri ods of time. But, their study concludes that larger confidence in portfolio betas is not justified. Alexander and Chervany (1980) show empirically that extreme betas are less stable compared to interior beta.They proved it by using mean absolute deviation as a measure of stability. According to them, best estimation interval is generally four to six years. They also showed that irrespective of the manner portfolios are formed, magnitudes of inter-temporal changes in beta decreases as the number of securities in the portfolios rise contradicting the work of Porter and Ezzell (1975). Chawla (2001) investigated the stability of beta using monthly data on returns for the period April 1996 to March 2000. The tability of beta was tested using two alternative econometric methods, including time variable in the regression and dummy variables for the slope coefficient. Both the methods reject the stability of beta in majority of cases. Many studies focused on the time varying beta using cond itional CAPM (Jagannathan and Wang (1996) Lewellen and Nagel (2003)). These studies concluded that the fluctuations and events that influence the market might change the leverage of the firm and the variance of the stock return which ultimately will change the beta.Haddad (2007) examine the degree of return volatility persistence and time-varying nature of systematic risk of two Egyptian stock portfolios. He used the Schwert and Sequin (1990) market model to study the relationship between market capitalization and time varying beta for a sample of investable Egyptian portfolios during the period January, 2001 to June, 2004. According to Haddad, the small stocks portfolio exhibits difference in volatility persistence and time variability. The study also suggests that the volatility persistence of each portfolio and its systematic risk are significantly positively related.Because of that, the systematic risks of different portfolios tend to move in a different direction during the per iods of increasing market volatility. The stability of beta is also examined with reference to security market conditions. For example, Fabozzi and Francis (1977) in their seminal paper considered the differential effect of bull and bear market conditions for 700 individual securities listed in NYSE. Using a Dual Beta Market Model (DBM), they established that estimated betas of most of the securities are stable in both the market conditions.They experienced it with three different set of bull and bear market definitions and concluded with the same results for all these definitions. Fama and French (1992, 1996), Jegadeesh (1992) and others revealed that betas are not statistically related to returns. McNulty et al (2002) highlight the problems with historical beta when computing the cost of capital, and suggest as an alternative- the forward-looking market-derived capital pricing model (MCPM), which uses option data to evaluate equity risk. In the similar line, French et al. (1983) m erge forward-looking volatility with istorical correlation to improve the measurement of betas. Siegel (1995) notes the improvement of a beta based on forward-looking option data, and proceeds to propose the creation of a new derivative, called an exchange option, which would allow for the calculation of what he refers to as â€Å"implicit† betas. Unfortunately the exchange options discussed by Siegel (1995) are not yet traded, and therefore his method cannot be applied in practice to compute forward-looking betas. A few studies are carried out to explore the reason for instability of beta.For example, Scott & Brown (1980) show that when returns of the market are subjected to measurement errors, the concurrent autocorrelated residuals and inter-temporal correlation between market returns and residual results in biased and unstable estimates of betas. This is so even when true values of betas are stable over time. They also derived an expression for the instability in the esti mated beta between two periods. Chen (1981) investigates the connection between variability of beta coefficient and portfolio residual risk. If beta coefficient changes over time, OLS method is not suitable to estimate portfolio residual risk.It will lead to inaccurate conclusion that larger portfolio residual risk is associated with higher variability in beta. A Bayesian approach is proposed to estimate the time varying beta so as to provide a precise estimate of portfolio residual risk. Bildersee and Roberts (1981) show that during the periods interest rates fluctuate, betas would fluctuate systematically. The change would be in tune with their value relative to the market and the pattern of changes in interest rate. International Research Journal of Finance and Economics – Issue 50 (2010) 177Few research studies are available in the Indian context to examine the factors influencing systematic risk. For example, Vipul (1999) examines the effect of company size, industry gro up and liquidity of the scrip on beta. He considered equity shares of 114 companies listed at Bombay Stock Exchange from July 1986 to June 1993 for his study. He found that size of the company affects the value of betas and the beta of medium sized companies is the lowest which increases with increase or decrease in the size of the company. The study also concluded that industry group and liquidity of the scrip do not affect beta.In another study, Gupta & Sehgal (1999) examine the relationship between systematic risk and accounting variables for the period April 1984 to March 1993. There is a confirmation of relationship in the expected direction between systematic risk and variables such as debt-equity ratio, current ratio and net sales. The association between systematic risk and variables like profitability, payout ratio, earning growth and earnings volatility measures is not in accordance with expected sign. The relationship was investigated using correlation analysis in the stu dy. 3. Data Type and Research MethodologyThe data related to the study is taken for 30 stocks from BSE-100 index. The top 30 stocks are chosen on the basis of their market capitalization in BSE-100 index. These 30 stocks are selected from BSE100 stocks in such a way that the continuous price data is available for the study period. The adjusted closing prices of these 30 stocks were collected for the last 10 years period i. e. from August 1999 to August 2009. The stock and market (BSE-100) data has been collected from prowess (CMIE) for the above period. BSE-100 index is a broad-based index and follows globally accepted free-float methodology.Scrip selection in the index is generally taken into account a balanced sectoral representation of the listed companies in the universe of Bombay Stock Exchange (BSE). As per the stock market guideline, the stocks inducted in the index are on the basis of their final ranking. Where the final rank is arrived at by assigning 75 percent weightage t o the rank on the basis of three-month average full market capitalization and 25 percent weightage to the liquidity rank based on three-month average daily turnover & three-month average impact cost.The average closing price for each month of 30 socks is computed for the period August 1999 to August 2009. Therefore we have 120 average monthly prices for each of the 30 stocks included in the research. The following method has been used to compute the monthly return on each of the stock. P i,t – P i,t-1 ri,t = –––––––––– P i, t-1 Where: P i,t = Average price of stock â€Å"i† in the month t Pi,t-1 = Average price of stock â€Å"i† in the month t-1 r i,t= Return of ith stock in the month t. The monthly market return is computed in the following way: Bt – Bt-1 mt = –––––––––– B t-1Where: Bt = BSE-100 Index at time period t Bt-1 = BSE-100 Index at time period t-1 mt = Market return at time period t. After the monthly stock and market returns are calculated as per the above formula, we identified the different market phases to compute beta separately. The market phases are identified, by creating a cumulative wealth index from the market returns. The cumulative wealth index data is presented in annexure-1. As per the cumulative wealth index, we identified five different market 178 International Research Journal of Finance and Economics – Issue 50 (2010) hases in BSE-100 index. We recognized that there are three bullish phases (Jan-1999 to Feb-2000, Oct-2001 to Dec-2007 and Dec-2008 to August 2009) and two bearish phases (Mar-2000 to Sept2001, Jan-2008 to Nov-2008). The summary of different market phases is depicted in Table -1& figure-1 below. Table-1: Different Market Phases Market Phases Phase I Phase II Phase III Phase IV Phase V Market Phase Timing Start End Jan-1999 Feb-2000 Mar-2000 Sep-2 001 Oct-2001 Dec-07 Jan-2008 Nov-08 Dec-2008 Aug-09 Market Type Bullish Bearish Bullish Bearish Bullish Figure-1: Different Market PhasesAfter these five market phases are identified, the beta value has been computed for each stock for each market phases following the below mentioned regression equation. ri,t = ? + ? mt + e (1) ri,t = Return on scrip i at time period t mt = Market rate of return at time period t e = Random error ? & = Parameters to be estimated The above regression equation is applied to calculate beta coefficient of each stocks for each market phases separately and taking the entire ten years period. As the objective of the paper is to test the stability of beta in different market phases, the hypothesis has been set accordingly.The null hypothesis (H0) being the beta is stable over the market phases, whereas the alternative hypothesis (H1) is that the beta values are not stable and varies according to phases in the market. The hypothesis has been tested with the help of three econometric models- using time as a variable, using dummy variables to measure the change of slope over the period and through Chow test. International Research Journal of Finance and Economics – Issue 50 (2010) 179 3. 1. Testing the Stability of Beta using time as a variableIn case of measuring stability of beta using time as a variable, in the above regression model (1) another variable i. e. † t mt† is used as a separate explanatory variable. Where the time variable t takes a value of t=1 for the first market phase, t=2 for the second market phase and so on for all other market phases identified. In this method the objective is to see whether the beta values are stable over time or not. After including the tmt variable, the above regression model (1) can be written as: ri,t = ? + ? 1mt + ? 2( t*mt) + e (2) The above regression equation can be re-framed as below: ri,t = ? + (? + ? 2*t )*mt + e (2) To test the stability of beta, we basically have to see whether the expression ? 2 is significant or not. If it is significant, we need to reject the null hypothesis and accept alternative hypothesis. It is implied that the sensitivity of stock return to market return i. e. (? 1 + ? 2*t)* mt changes with time, and hence, beta is not stable. If ? 2 is not significant, (? 1 + ? 2*t)* mt will get reduced to ? 1*mt , implying that ? 1, or the beta of stock, does not vary with time and is thus stable over time. The statistical significance of ? 2 is tested using the respective p-values. . 2. Testing the Stability of Beta using dummy variable In case of the second method of testing the beta stability, dummy variables are used in above mentioned regression equation (1) for the slope coefficients. As five market phases discovered, there are 4 dummy variables used in the new equation (Levine et al. 2006). The new regression equation is reframed as follows: ri,t = ? 0 + ? 1* mt + ? 2*D1* mt + ? 3*D2* mt + ? 4*D3* mt + ? 5*D4*mt + e (3) Where: D1 = 1 for phase 1 (Jan 1999 to Feb 2000) data = 0 otherwise. D2 = 1 for phase II (May 2000 to Sept 2001) data = 0 otherwise D3 1 for phase III (Oct 2001 to Dec 2007) data = 0 otherwise D4 = 1 for phase IV (Jan 2008 to Nov 2008) data = 0 otherwise = return on stock I in period t. r i,t mt = return on market in period t. e = error term and ? 0, ? 1, ? 2, ? 3, ? 4 & ? 5 = coefficients to be estimated. As there are 5 market phases, we use 4 dummy variables in the above equation (3). The use of 5 dummy variable would lead to a dummy variable trap. We treat the 5th phase viz. Dec-08 to Aug-09 as the base period. The significance of ? 2, ? 3, ? 4 and ? 5 will tell us whether the beta is stable over the time periods or not.For the beta to be truly stable over the entire period, all coefficients like, ? 2, ? 3, ? 4 and ? 5 should be statistically insignificant and where we need to accept the null hypothesis. The logic is that if ? 2, ? 3, ? 4 and ? 5 are insignificant, the equation reduces to the following, thus implying that beta is stable over time. ri,t = ? 0 + ? 1*mt + e (4) th 3. 3. Testing for Structural or Parameter Stability of Regression Model: The Chow Test In the third method, for structural or parameter stability of regression models, the Chow test has been conducted (Gujarati, 2004).When we use a regression model involving time series data, it may happen 180 International Research Journal of Finance and Economics – Issue 50 (2010) that there is a structural change in the relationship between the regress and the regressors. By structural change, we mean that the values of the parameters of the model do not remain the same through the entire time period. We divide our sample data into five time periods according to the different market phases identified earlier.We have six possible regressions for each stock (five regressions for each market phases and one for the whole ten year period). The regression equations are mentioned below. ri,t = ? 1 + ? 2 mt + ut (5) (6) r i, t = ? 1 + ? 2mt + ut Equation (5) is for each market phases and equation (6) is for the whole period. There are 128 observations (n=128) for the whole period and n1=14, n2=19, n3=75, n4=11 and n5=9 are the number of observations for phase-I to phase-V respectively. The u’s in the above regression equations represent the error terms.Regression (6) assumes that there is no difference over the five time periods and therefore estimates the relationship between stock prices and market for the entire time period consisting of 128 observations. In other words, this regression assumes that the intercept as well as the slope coefficient remains the same over the entire period; that is, there is no structural change. Now the possible differences, that is, structural changes, may be caused by differences in the intercept or the slope coefficient or both. This is examined with a formal test called Chow test (Chow, 1960). The mechanics of the Chow test are as follows: First the regression (6) is estimated, which is appropriate if there is no parameter instability, and obtained the restricted residual sum of squares (RSSR) with df = [(n1+n2+n3+n4+n5) ? k], where k is the number of parameters estimated, 2 in the present case. This is called restricted residual sum of squares because it is obtained by imposing the restrictions that the sub-period regressions are not different. Secondly estimated the phase wise other regression equations and obtain its residual sum of squares, RSS1 to RSS8 with degrees of freedom, df = (no of observations in each phase ? ). Since the five sets of samples are deemed independent, in the third step we can add RSS1 to RSS8 to obtain what may be called the unrestricted residual sum of squares (RSSUR) with df = [(n1+n2+n3+n4+n5)? 2k]. Now the idea behind the Chow test is that if in fact there is no structural change (i. e. , all phases regressions are essentially the same), then the RSSR and RSSUR should not be statistical ly different. Therefore in the fourth step the following ratio is formed to get the F-value. F = [(RSSR ? RSSUR)/k] / [(RSSUR)/ ((n1 + n2+n3+n4+n5) ? 2k)] ~ F [k, ((n1+n2+n3+n4+n5) ? 2k)] (7)We cannot reject the null hypothesis of parameter stability (i. e. , no structural change) if the computed F value is not statistically significant (F value does not exceed the critical F value obtained from the F table at the chosen level of significance or the p value). Contrarily, if the computed F value is statistically significant (F value exceeds the critical F value), we reject the null hypothesis of parameter stability and conclude that the phase wise regressions are different. 4. Test Results and Findings Initially the beta coefficient is calculated using the Ordinary Least Square (OLS) technique as defined in equation (1).The estimation was carried out by using monthly return data for the 5 market phases for each of the 30 stocks. To compare the phase wise beta estimation with the enti re 10 year period, the same estimation also carried out taking the whole 10 years for each stock separately. Stock wise beta values over 5 market phases and the entire period is reported in appendix-2. From annexure-2, it is revealed that there are 14 stocks beta value is greater than 1 in phase I. This figure (beta value greater than 1) has reduced to 6, 11, 12 and 10 for phase-2 to phase-5 respectively.It is also illustrated that, there are 8 stocks whose beta value is greater than 1 in respect to overall between Jan-99 to Aug-09 and highest being for Wipro of 1. 47. The stocks having beta value International Research Journal of Finance and Economics – Issue 50 (2010) 181 more than 1 are considered to be volatile securities. It is noticed that, as we increase the period of estimation to full ten years period, there are less number of stocks proved to be more volatile. Out of the total 30 stocks considered in the study, only one company i. e.L&T has beta more than 1 in all p hases including the overall period. But none of the company’s overall beta value is more than the phase wise betas. There are seven companies (RIL, NALCO, ITC, GAIL, Hindustan Lever, Hero Honda and Cipla) whose beta values are less than 1 all through the phases including overall period. These stocks are considered to be less volatile than the market. There are 3 companies (Cipla, ITC and Hindustan Lever) recent beta value (Dec 2008 to August 2009) is negative, where Cipla’s phase I beta value is also negative along with other two stocks like SAIL and NALCO.It is observed from annexure-2 that there are only two companies’ from the software sector (Infosys and Wipro) whose beta values are consistently declining over time. However there are 7 stocks viz. Cipla, Sunpharma, Wipro, Grasim, Hindustan Lever, Infosys and ITC whose beta values are showing a decreasing trend from phase 3 onwards, while Tata steel is the only stock whose beta values are showing an increasin g trend during the same period. It is observed from the annexure-2 that, on an overall basis 29 out of 30 stocks have their beta values statistically significant at 5% level.This number has varied from 8 to 30 over the various phases, indicating that the beta values of the stocks have fluctuated significantly. This implies that the volatility of the stocks depend on the market phases i. e. bearish or bullish. Thus the result rejects the null hypothesis that the beta is stable over various market phases. The null hypothesis is rejected in 29 out of 30 cases in case of overall period, while 30 out of 30 cases in respect to phase-3. Since the period of estimation of beta is more in case of overall period and in phase-3, the obtained results are similar in both the cases.But the remaining phase wise results do not follow any pattern. In respect of period of estimating the value of beat the results are comparable to the finding of Baesel (1974) and Altman et al (1974). It is mentioned ea rlier that to examine the stability of beta over different market phases, three separate models have been used in paper. The results obtained from these models are interpreted in the following paragraphs. The estimated results for regression model-2 that includes t*mt as a separate variable are depicted in annexure-3.It is observed that the value of R2, a measure of goodness of fit varies from 0. 11 to 0. 61. It is only in 5 out of 30 regression results, the value is greater than 0. 50. The coefficient of mt (? 1) is found to be highly statistically significant at 5% level in 19 out of 30 cases. It is in 11 regressions, the coefficient is statistically insignificant. As discussed earlier, the significance of the coefficient of variable t*mt implies the rejection of the null hypothesis of stable beta over time. It is observed that the coefficient (? ) is significant in 14 cases out of 30. The regression results indicate that in 50% cases the null hypothesis of stability of beta over the market phases is rejected. This means 50% stocks reported stability of beta over different phases. So model (2) cannot infer that beta is not stable over market phases. The estimated results for coefficients for regression model-3 that incorporates dummy variables are depicted in annexure-4. It is noticed from the results that the R2 value fluctuates from 0. 15 to 0. 62 and in case of 8 stocks this value is greater than 0. 0. It is mentioned earlier that the null hypothesis of stability of beta will be rejected if any of the coefficients (? 2, ? 3, ? 4 & ? 5) corresponding to D1*mt, D2*mt, D3*mt or D4*mt were found to be statistically significant. It is observed from the results presented in appendix-4, that there are 17 out of 30 stocks represented statistically significant at 5% level at least one of the coefficient. There are only 2 cases where 3 coefficients are significant and none of the stocks reported significant for all the 4 coefficients.Further in 6 cases where 2 out of 4 coefficients are reported significant, where as in 9 cases depicted significant only for one coefficient. The outcome of this model in brief can be stated that, in case of 17 stocks out of 30 stocks, the stability of beta hypothesis is rejected meaning, in rest 13 cases there is a stability of beta over the market phases. 182 International Research Journal of Finance and Economics – Issue 50 (2010) The estimated results of Chow test are depicted in annexure-5. The results show that, 12 out of 30 cases the F-value is statistically significant and rest 18 stocks are reported insignificant at 5% level.Based on the F- statistics and its corresponding p-values, the null hypothesis of beta stability over the market phases is rejected in 12 cases and accepted in 18 cases. The F-values are also supported by log likelihood ratio and it p-values, which also reported statistical significance in 12 cases. The outcome of Chow test confirms that the beta values are not stable or there is a structural change in 12 out of 30 stocks in different market phases. But the rest 18 stocks reported stability or no structural change in beta values over the market phases.From the above deliberations, it is observed that all the three models described above exhibit a mixed and inconclusive result. There are 14, 17 and 12 stocks are statistically significant as per model2, model-3 and model-7 respectively. This means as per model-2 the beta values of 14 stocks out of 30 stocks are instable over the period. But this number is 17 and 12 in case of model3 and 7 respectively. However, on the basis of results obtained from different models, it is not possible to conclude that the beta values of the stocks are stable or instable over the market phases.But if we closely glance at the results obtained from three models, it is very apparent that in case of 9 stocks where all the three models represented similar results and rejected the null hypothesis. These stocks include Sun pharmac eutical, Wipro, Tata motors, Tata Steel, Hindalco, Hindustan Unilever, HDFC, Infosys and Zee Entertainment. This indicates that beta values are not stable over the market phases in these 9 stocks. Similarly there are 6 stocks where two models recommended instability of beta and 4 stocks where only one model reported a change in beta values over the period.There are 11 cases where none of the models rejected the null hypothesis, which proved that the beta values are stable over the time in these stocks. 5. Conclusion The objective of the present study is to examine the stability of beta in different Indian market phases. For the purpose of the study monthly return data of 30 stocks for the period from 1999 to 2009 is considered. Considering the bullish and bearish condition in the Indian market, we divided the whole 10 years into 5 different market phases. Initially the beta has been estimated for different market phases and also taking the whole 10 years period.The results show that the beta values are not showing any particular pattern but in the overall phase almost all the stocks are statistically significant. Further the beta stability is examined using three different models. In the first method the beta coefficient is calculated considering the market phases as time variable. The results show that in 50% of cases the null hypothesis is rejected as the beta is stable over different market phases. In the similar line the results obtained in respect to model two states that in 17 out of 30 cases the null hypothesis is rejected.This confirms that in 17 cases the stability of beta is not there over the market phases but in rest 13 cases it stable over the market phases. In the third method of investigating beta stability, the Chow test has been conducted. The F-statistics under Chow test reveals that, beta is instable in 12 out of 30 stocks considered in the study in different market phases. We can thus finally conclude that the results obtained from differen t models are mixed and inconclusive in nature, where it is less ground to conclude that the beta values are stable or instable over the market phases.But there are 9 stocks which gives a strong indication that their beta values are not stable over the market phases. In these 9 cases, all the three models reported similar signal of beta instability over the market phases. The instability of beta has its implications in taking sound corporate financial decisions. Financial decisions should not be based on the overall beta of the company. Rather, the company’s periodical beta should be relied upon for taking certain managerial decisions.Considering the inconclusive results obtained from present study, it is suggested that the future research on beta in Indian market may be investigated from (a) industry wise stability of beta in different market phases (b) stability of beta from portfolio point of view (c) optimal time limit for stability of beta (d) forward looking beta and its stability (e) impact of market and company specific factors and stability of beta and (f) market efficiency study using phase wise beta under the event study methodology. 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Siegel, A. , (1995) â€Å"Measuring Systematic Risk Using Implicit Beta†, Management Science, 41, 124-128. Vipul (1999) â€Å"Systematic Risk: Do Size, Industry and Liquidity Matter? †, Prajanan, Vol. XXVII, No. 2, 1999. [26] [27] [28] [29] 30] [31] [32] [33] [34] 185 International Research Journal of Finance and Economics – Issue 50 (2010) Annexure-1: Month December 1998 January 1999 February 1999 March 1999 April 1999 May 1999 June 1999 July 1999 August 1999 September 1999 October 1999 November 1999 December 1999 January 2000 February 2000 March 2000 April 2000 May 2000 June 2000 July 2000 August 2000 September 2000 October 2000 November 2000 December 2000 January 2001 February 2001 March 2001 April 2001 May 2001 June 2001 July 2001 August 2001 September 2001 October 2001 November 2001 Dece mber 2001 January 2002 February 2002 March 2002 April 2002May 2002 June 2002 July 2002 August 2002 September 2002 October 2002 November 2002 December 2002 January 2003 February 2003 March 2003 April 2003 May 2003 June 2003 July 2003 August 2003 September 2003 October 2003 November 2003 December 2003 January 2004 February 2004 Identification of Market Phases Closing Price Return (R) 1+R Cumulative Wealth Index Market Phases 1359. 03 1461. 52 1506. 95 1651. 37 1449. 64 1714. 02 1790. 51 1988. 06 2192. 94 2213. 33 2071. 50 2253. 29 2624. 49 2875. 37 3293. 29 2902. 20 2396. 22 2156. 99 2397. 06 2153. 26 2306. 07 2075. 67 1916. 99 2061. 18 2032. 20 2209. 31 2139. 72 1691. 71 1682. 1 1763. 35 1630. 02 1564. 46 1534. 73 1312. 50 1389. 17 1557. 01 1557. 22 1592. 27 1707. 72 1716. 28 1671. 63 1596. 71 1650. 34 1506. 23 1580. 55 1473. 88 1458. 78 1594. 03 1664. 67 1600. 87 1628. 72 1500. 72 1470. 31 1641. 44 1819. 36 1893. 45 2229. 25 2314. 62 2485. 43 2594. 34 3074. 87 2946. 14 2923. 99 0. 0 8 0. 03 0. 10 -0. 12 0. 18 0. 04 0. 11 0. 10 0. 01 -0. 06 0. 09 0. 16 0. 10 0. 15 -0. 12 -0. 17 -0. 10 0. 11 -0. 10 0. 07 -0. 10 -0. 08 0. 08 -0. 01 0. 09 -0. 03 -0. 21 -0. 01 0. 05 -0. 08 -0. 04 -0. 02 -0. 14 0. 06 0. 12 0. 00 0. 02 0. 07 0. 01 -0. 03 -0. 04 0. 03 -0. 09 0. 05 -0. 07 -0. 01 0. 09 0. 04 -0. 04 0. 2 -0. 08 -0. 02 0. 12 0. 11 0. 04 0. 18 0. 04 0. 07 0. 04 0. 19 -0. 04 -0. 01 1. 08 1. 03 1. 10 0. 88 1. 18 1. 04 1. 11 1. 10 1. 01 0. 94 1. 09 1. 16 1. 10 1. 15 0. 88 0. 83 0. 90 1. 11 0. 90 1. 07 0. 90 0. 92 1. 08 0. 99 1. 09 0. 97 0. 79 0. 99 1. 05 0. 92 0. 96 0. 98 0. 86 1. 06 1. 12 1. 00 1. 02 1. 07 1. 01 0. 97 0. 96 1. 03 0. 91 1. 05 0. 93 0. 99 1. 09 1. 04 0. 96 1. 02 0. 92 0. 98 1. 12 1. 11 1. 04 1. 18 1. 04 1. 07 1. 04 1. 19 0. 96 0. 99 1. 08 1. 11 1. 22 1. 07 1. 26 1. 32 1. 46 1. 61 1. 63 1. 52 1. 66 1. 93 2. 12 2. 42 0. 88 0. 73 0. 65 0. 73 0. 65 0. 70 0. 63 0. 58 0. 63 0. 62 0. 67 0. 65 0. 51 0. 51 0. 54 0. 9 0. 48 0. 47 0. 40 1. 06 1. 19 1. 19 1. 21 1. 30 1. 31 1. 27 1. 22 1. 26 1. 15 1. 20 1. 12 1. 11 1. 21 1. 27 1. 22 1. 24 1. 14 1. 12 1. 25 1. 39 1. 44 1. 70 1. 76 1. 89 1. 98 2. 34 2. 24 2. 23 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 186 March 2004 April 2004 May 2004 June 2004 July 2004 August 2004 September 2004 October 2004 November 2004 December 2004 January 2005 February 2005 March 2005 April 2005 May 2005 June 2005 July 2005 August 2005 September 2005 October 2005 November 2005 ecember 2005 January 2006 February 2006 March 2006April 2006 May 2006 June 2006 July 2006 August 2006 September 2006 October 2006 November 2006 ecember 2006 January 2007 February 2007 March 2007 April 2007 May 2007 June 2007 July 2007 August 2007 September 2007 October 2007 November 2007 December 2007 January 2008 February 2008 March 2008 April 2008 May 2008 June 2008 July 2008 August 2008 September 2008 October 2008 November 2008 December 2008 January 2009 February 2009 Mar ch 2009 April 2009 May 2009 June 2009 July 2009 August 2009 International Research Journal of Finance and Economics – Issue 50 (2010) 2966. 31 3025. 14 2525. 35 2561. 16 2755. 22 2789. 07 2997. 97 027. 96 3339. 75 3580. 34 3521. 71 3611. 90 3481. 86 3313. 45 3601. 73 3800. 24 4072. 15 4184. 83 4566. 63 4159. 59 4649. 87 4953. 28 5224. 97 5422. 67 5904. 17 6251. 39 5385. 21 5382. 11 5422. 39 5933. 77 6328. 33 6603. 60 6931. 05 6982. 56 7145. 91 6527. 12 6587. 21 7032. 93 7468. 70 7605. 37 8004. 05 7857. 61 8967. 41 10391. 19 10384. 40 11154. 28 9440. 94 9404. 98 8232. 82 9199. 46 8683. 27 7029. 74 7488. 48 7621. 40 6691. 57 4953. 98 4600. 45 4988. 04 4790. 32 4516. 38 4942. 51 5803. 97 7620. 13 7571. 49 8176. 54 8225. 50 0. 01 0. 02 -0. 17 0. 01 0. 08 0. 01 0. 07 0. 01 0. 10 0. 07 -0. 02 0. 03 -0. 04 -0. 05 0. 9 0. 06 0. 07 0. 03 0. 09 -0. 09 0. 12 0. 07 0. 05 0. 04 0. 09 0. 06 -0. 14 0. 00 0. 01 0. 09 0. 07 0. 04 0. 05 0. 01 0. 02 -0. 09 0. 01 0. 07 0. 06 0. 02 0. 05 -0. 02 0 . 14 0. 16 0. 00 0. 07 -0. 15 0. 00 -0. 12 0. 12 -0. 06 -0. 19 0. 07 0. 02 -0. 12 -0. 26 -0. 07 0. 08 -0. 04 -0. 06 0. 09 0. 17 0. 31 -0. 01 0. 08 0. 01 1. 01 1. 02 0. 83 1. 01 1. 08 1. 01 1. 07 1. 01 1. 10 1. 07 0. 98 1. 03 0. 96 0. 95 1. 09 1. 06 1. 07 1. 03 1. 09 0. 91 1. 12 1. 07 1. 05 1. 04 1. 09 1. 06 0. 86 1. 00 1. 01 1. 09 1. 07 1. 04 1. 05 1. 01 1. 02 0. 91 1. 01 1. 07 1. 06 1. 02 1. 05 0. 98 1. 14 1. 16 1. 00 1. 07 0. 85 1. 00 0. 88 1. 12 . 94 0. 81 1. 07 1. 02 0. 88 0. 74 0. 93 1. 08 0. 96 0. 94 1. 09 1. 17 1. 31 0. 99 1. 08 1. 01 2. 26 2. 30 1. 92 1. 95 2. 10 2. 13 2. 28 2. 31 2. 54 2. 73 2. 68 2. 75 2. 65 2. 52 2. 74 2. 90 3. 10 3. 19 3. 48 3. 17 3. 54 3. 77 3. 98 4. 13 4. 50 4. 76 4. 10 4. 10 4. 13 4. 52 4. 82 5. 03 5. 28 5. 32 5. 44 4. 97 5. 02 5. 36 5. 69 5. 79 6. 10 5. 99 6. 83 7. 92 7. 91 8. 50 0. 85 0. 84 0. 74 0. 82 0. 78 0. 63 0. 67 0. 68 0. 60 0. 44 0. 41 1. 08 1. 04 0. 98 1. 07 1. 26 1. 66 1. 65 1. 78 1. 79 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5International Research Journal of Finance and Economics – Issue 50 (2010) Annexure-2: Beta values of individual securities over all the five phases Overall Phase I Phase II Phase III Phase IV ? p-val ? p-val ? p-val ? p-val ? p-val Bharat Heavy Electricals Ltd. 0. 86 0. 00* 0. 67 0. 21 1. 18 0. 00* 1. 10 0. 00* 0. 80 0. 02* Bharat Petroleum Corpn. Ltd. 0. 80 0. 00* 1. 02 0. 15 0. 66 0. 06 1. 13 0. 00* 1. 30 0. 06 Cipla Ltd. 0. 51 0. 00* -0. 04 0. 95 0. 75 0. 02* 0. 80 0. 00* 0. 51 0. 07 Sun Pharmaceutical Inds. Ltd. 0. 69 0. 00* 1. 13 0. 15 0. 80 0. 08 0. 57 0. 00* 0. 74 0. 00* Ranbaxy Laboratories Ltd. 0. 94 0. 00* 1. 19 0. 3 0. 63 0. 03* 0. 78 0. 00* 1. 07 0. 10 Wipro Ltd. 1. 47 0. 00* 2. 79 0. 02* 2. 63 0. 00* 0. 88 0. 00* 0. 87 0. 00* Reliance Infrastructure Ltd. 1. 24 0. 00* 1. 38 0. 02* 0. 26 0. 39 1. 20 0. 00* 1. 50 0. 00* Larsen & Toubro Ltd. 1. 30 0. 00* 1. 12 0. 08 1. 70 0. 00* 1. 21 0. 00 * 1. 07 0. 00* State Bank Of India 1. 01 0. 00* 1. 22 0. 08 0. 86 0. 00* 1. 03 0. 00* 1. 08 0. 01* Tata Motors Ltd. 1. 20 0. 00* 1. 07 0. 08 -0. 13 0. 65 1. 11 0. 00* 1. 20 0. 00* Oil & Natural Gas Corpn. Ltd. 0. 79 0. 00* 0. 43 0. 47 0. 59 0. 03* 1. 06 0. 00* 1. 03 0. 01* Steel Authority Of India Ltd. 1. 23 0. 00* -0. 31 0. 68 0. 99 0. 00* 1. 54 0. 0* 1. 12 0. 01* Tata Steel Ltd. 1. 22 0. 00* 0. 79 0. 17 0. 64 0. 05* 1. 25 0. 00* 1. 39 0. 00* Grasim Industries Ltd. 0. 94 0. 00* 1. 24 0. 13 0. 91 0. 01* 0. 95 0. 00* 0. 86 0. 00* H D F C Bank Ltd. 0. 79 0. 00* 1. 38 0. 03* 0. 36 0. 10 0. 68 0. 00* 0. 98 0. 00* Hero Honda Motors Ltd. 0. 47 0. 00* 0. 24 0. 64 0. 04 0. 85 0. 79 0. 00* 0. 93 0. 00* Hindalco Industries Ltd. 1. 00 0. 00* 0. 03 0. 95 0. 39 0. 06 1. 22 0. 00* 1. 44 0. 00* Hindustan Unilever Ltd. 0. 49 0. 00* 0. 78 0. 01* 0. 42 0. 06 0. 77 0. 00* 0. 67 0. 00* HDFC Ltd. 0. 74 0. 00* 0. 77 0. 01* 0. 50 0. 06 0. 85 0. 00* 1. 01 0. 00* Infosys Technologies Ltd. . 91 0. 00* 1. 33 0. 05* 1. 30 0. 00* 0. 73 0. 00* 0. 67 0. 06 G A I L (India) Ltd. 0. 49 0. 00* 0. 00 1. 00 0. 46 0. 11 0. 79 0. 00* 0. 34 0. 18 I C I C I Bank Ltd. 0. 84 0. 00* 1. 85 0. 05* 0. 06 0. 88 0. 50 0. 00* 0. 57 0. 14 I T C Ltd. 0. 37 0. 00* 0. 54 0. 13 0. 57 0. 01* 0. 42 0. 00* 0. 27 0. 24 National Aluminium Co. Ltd. 0. 49 0. 00* -0. 31 0. 75 0. 24 0. 37 0. 73 0. 00* 0. 21 0. 69 Indian Oil Corpn. Ltd. 0. 87 0. 10 0. 32 0. 56 0. 65 0. 00* 1. 24 0. 00* 0. 75 0. 01* Reliance Industries Ltd. 0. 51 0. 00* 0. 34 0. 47 0. 08 0. 81 0. 41 0. 00* 0. 74 0. 06 Sterlite Industries (India) Ltd. 1. 11 0. 00* 0. 99 0. 14 1. 3 0. 09 0. 87 0. 00* 0. 01 0. 96 Tata Communications Ltd. 0. 78 0. 00* 1. 10 0. 05* 1. 18 0. 00* 0. 87 0. 00* 0. 85 0. 09 Unitech Ltd. 0. 79 0. 00* 0. 47 0. 14 0. 48 0. 02* 0. 87 0. 00* 0. 21 0. 47 Zee Entertainment Ent. Ltd. 1. 00 0. 00* 1. 39 0. 08 0. 72 0. 07 0. 78 0. 00* 1. 13 0. 03* * indicates significance of coefficient at 5% level of significant Name of the Company Annexure-3: 187 Phase V ? p-val 0. 74 0. 00* 0. 48 0. 03* -0. 13 0. 65 0. 16 0. 55 1. 96 0. 01* 0. 78 0. 10 2. 46 0. 00* 1. 77 0. 00* 1. 55 0. 00* 1. 33 0. 02* 0. 94 0. 01* 1. 66 0. 00* 2. 07 0. 00* 0. 41 0. 29 0. 96 0. 00* 0. 29 0. 21 1. 63 0. 01* -0. 1 0. 68 0. 95 0. 00* 0. 07 0. 83 0. 38 0. 03* 1. 35 0. 02* -0. 01 0. 95 0. 50 0. 19 0. 98 0. 02* 0. 57 0. 10 0. 85 0. 03* 0. 43 0. 15 1. 27 0. 11 0. 74 0. 07 Estimates of regression equation using Time as a Variable Name of the Company Bharat Heavy Electricals Ltd. Bharat Petroleum Corpn. Ltd. Cipla Ltd. Sun Pharmaceutical Inds. Ltd. Ranbaxy Laboratories Ltd. Wipro Ltd. Reliance Infrastructure Ltd. Larsen & Toubro Ltd. State Bank Of India Tata Motors Ltd. Oil & Natural Gas Corpn. Ltd. Steel Authority Of India Ltd. Tata Steel Ltd. Grasim Industries Ltd. H D F C Bank Ltd. Hero Honda Motors Ltd. Hindalco Industries Ltd.Hindustan Unilever Ltd. HDFC Ltd. Constant 0. 02 0. 01 0. 02 0. 03 0. 01 0. 01 0. 01 0. 01 0. 01 0. 00 0. 01 0. 02 0. 01 0. 01 0. 0 2 0. 02 0. 00 0. 00 0. 02 mt (? 1) 0. 56 (0. 03) 0. 79 (0. 02) 0. 94 (0. 00) 1. 69 (0. 00) 0. 63 (0. 05) 3. 35 (0. 00) 0. 25 (0. 44) 1. 10 (0. 00) 0. 71 (0. 00) 0. 61 (0. 02) 0. 25 (0. 38) 0. 26 (0. 51) 0. 01 (0. 99) 0. 97 (0. 00) 0. 92 (0. 00) 0. 19 (0. 42) -0. 12 (0. 60) 0. 91 (0. 00) 0. 37 (0. 04) t*mt (? 2) 0. 10 (0. 22) 0. 00 (0. 96) -0. 14 (0. 10) -0. 33 (0. 00)* 0. 10 (0. 29) -0. 62 (0. 00)* 0. 33 (0. 00)* 0. 07 (0. 37) 0. 10 (0. 17) 0. 20 (0. 02)* 0. 18 (0. 03)* 0. 32 (0. 01)*

Ethics Associated with Global Business

Ethics Associated with Global Business Free Online Research Papers In the business world ethical dilemmas happen for a variety of reasons. One of the most common reasons is cultural differences in global settings (Gan, n.d.). Ethical dilemmas can arise in international business. Most companies have a main headquarters in the United States, but open manufacturing facilities in other foreign countries. An ethical dilemma arises when conditions that are considered normal in the foreign country conflicts with the standards that are set for the United States. The ethical dilemma becomes dangerous when a United States company lowers its standards due to the less stringent regulations in the foreign country. The Bhopal chemical plant disaster in India is an excellent example of a US company lowering standards. Union Carbide, taken over by Dow Chemical, allowed conditions to deteriorate at a plant that was located in Bhopal, India and as a result thousands have been affected and thousands have been killed (Gan, n.d.). A large scaled chemical disaster occurred in Bhopal, India in Dec 1984. Bhopal is the capital of the State of Madhya Pradesh. In the late 60s, one of the largest American industrial companies in the world named Union Carbide opened a chemical plant in the outskirts of Bhopal aimed at supplying pesticides to protect Indian agricultural production (Muller, n.d.). The outskirts of Bhopal were a densely populated shantytown that was estimated to house about 100,000 people. These people were actually living within a 1 km radius of the plant (Jackson, 1993). A carbamate insecticide involving methyl isocyanate (MIC), called Sevin was the main product in its production (Muller, n.d.). MIC shipped from the States was used in Sevin production initially, but the plant was constructed locally for manufacturing methyl isocyanate at Bhopal in the late 70s (Muller, n.d.). Methyl isocyanate is a colorless liquid with a low boiling point of 39 °C. When MIC comes into contact with water it causes an exothermic reaction resulting in the formation of carbon dioxide, methylamine gases and nitrogenous gases. The permissible exposure limit of MIC was documented as 0.02ppm averaged over an 8hr work shift. In the United States and in Europe storage tanks have smaller capacities, which should hold 17,500 L each for safety reasons. In two MIC holding tanks at Bhopal, the capacity was 57,120 L each, which was more than ten times the amount required for daily use (Mehta et al., 1990). This scenario is an example of poor safety management at the plant. The explosion at Union Carbide India pesticide plant released toxic gas in the form of methyl isocyanate (MIC) and its reaction products over the city. It was estimated that the death toll is believed to have been between 2500 and 5000 people, with up to 200,000 injured (Mehta et al., 1990). Evidence showed that an employee at the Bhopal plant had deliberately introduced water into a methyl isocyanate storage tank, with the result being the release of a cloud of poisonous gas (Jackson, 1993). 90,000 patients were seen in local hospitals and clinics within the first 24 hrs, and in total, about 200,000 people suffered acute effects of the MIC leak. After the accident, treatment was limited to symptom management, as it was still uncertain whether the effects observed were due to MIC, phosgene, HCN, or other MIC reaction products. The tragic consequences of Bhopal raise ethical issues. In poor countries, industrial risk is high, as evidenced by Bhopal industry is not always a good choice and it can kill. Pointed out by the World Health Organization â€Å"in most developing countries there are no effective legal or institutional structures to deal with pollution in the workplace or surrounding areas† (Garner, 1997). Companies that decide to open industrial operations in foreign countries must start taking responsibility for the company’s operations and actions. These companies should also ensure that safety regulations are met with regard for their workers and the area of operations. Union Carbide should have operated by the standards that the United States set even though the country did not have strict regulation as a result of their actions lawsuits were made against the company. Countless lives could have been saved if the right decision was made. To ensure that disasters do not continue to happen in foreign countries more attention needs to be placed on safety regulations in those foreign countries. The disaster at Bhopal raised concern about chemical plants being placed in heavily populated areas and how to ensure the safe operation and maintenance of industrial facilities. International business ethics is becoming very important in view of the globalization of business activity (Gan, n.d.). Companies all over the world has had to deal with the cost and consequences of unethical decisions and behavior that come from cultural differences. Even though there is no global consensus on what is morally and ethically right, people and companies should take the high road and make the best decision. 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A mom before the Prom Essay Example for Free

A mom before the Prom Essay ? Teen pregnancy has been gravelly increased in the last few years. Bad media influences (Many programs at TV programs or sexual content movies as well as other mediums) can be the factors that teen girls nowadays are getting a wrong advice that teen motherhood can a common way to live. Partners and friends’s bad influence is making them think that is right to have sex at a young age and will make them feel more popular. In that regards, this essay by Cristina page is restating the issue that more forms of bad media and wrong people’s influences are available today than ever before and consequently teens girls are much more exposed to a lot of information and these sometimes switch teen girl’s mind to do something wrong when they think is totally normal and it also has made teen girls to believe that having children at a young age might be beneficial because they think giving a child for adoption might improve their fortune giving them away for millions of dollars , so it can’t ruin her adolescence too but in reality it can really affect them. – Personally I can share the view of the author in this essay: Teen pregnancy is in reality one of the most difficult experiences a teen girl might ever face when that can interrupt her education or other plans such as getting a better career or maintain fathers with them, but most of the time it doesn’t work and that’s when the situation gets worse. Children usually grow without a father figure when their parents have them at a very young age or sometimes they don’t even live with both parents because they can’t take care of them or support them economically. So when this children start to live without a parental guide , they grow adopting a bad behavior and getting the wrong advices from other bad people and turned into criminals , stealers, or other people of bad reputation because they live in a poor ambient without having a parent who can guide and help them to raise their levels of education. – Most of the time, when teen moms decide to have a baby, teen girls don’t really take care of their babies when they are still formatting inside their body as old mothers and because of their immaturity, sometimes they don’t realize the huge damage they cause to their babies if they start smoking and drinking or working so hard because now they need to support themselves economically carrying heavy stuff when they have to rest the most during their pregnancy. Children are tending to born prematurely, with a disease, a mental retardation or even born death. – Usually we think that there’s not any difference of acquiring the same standards of education or a good life when a kid’s parents are so young and the other’s parent are more mature. The children of teen parents can suffer more of abuse at home and at school or disregard from their parents and grow more with farness or adopt a bad behavior, so that implies that they could not do so well at school, they could get lower grades and repeat their classes or drop out from High School without completing their education. This might increase the raise of poverty in families with young parents too and this leads society into decreasing its economy too. I really enjoyed reading this essay because it deals with a controversial issue and restates the causes of why teen pregnancy is becoming a worldwide problem, it must be thought in class so we can share our own viewpoints about it. 10-) – I encourage people to consider more this issue because if we want a better life for our A mom before the Prom. (2016, Apr 27).

W4As Premier Kayak Essay Example | Topics and Well Written Essays - 500 words

W4As Premier Kayak - Essay Example As such, the inefficiencies in previous booking and reservations system required designing a new model which would address the disclosed gaps. The model was noted to provide access to an accurate schedule of booked customers who already paid and the information is provided to crucial personnel at Premier Kayak to enable staff members, especially tour guides, to provide the needed service. The model thereby prevents overbooking and ensures accuracy in making reservations for scheduled tours only in defined number of kayaks at a particular available date and time. The key innovations that Premier Kayak’s reservation system which avoided making the reservation system a painful process to customers included defining the available slots for the kayaks in any particular day, time, and location to prevent overbooking. Likewise, only customers who confirmed reservations through payments made online would be confirmed for the kayak tours. In addition, these schedules have defined tour guides who could access the information and abide by the reservations made. As such, the reservation system, which is available and accessible to customers and employees, would avoid overbooking or the need for rescheduling. This prevented having to refund customers due to unavailable tour guides or lack of kayaks at preferred booking dates. The new method also prevented having to contend with irate customers or the need to make refunds. Overall, the system improved Premier Kayak’s image as a reliable and dependable organization in their field of endeavor. The evaluation method that is recommended to make certain that the innovations perform as expected is through customer feedback surveys (Foot, 2013). The survey would gather information pertinent to the customers’ satisfaction on services rendered by Premier Kayak. Likewise, the 360 degree assessment is another evaluation tool that solicits information from various