Chapter 1 indians the settlements of america Essay Example for Free

Chapter 1 indians the settlements of america Essay 1. Jamestown was the first colony that gets found. It was there where the first permanent settlement occurs. Jamestown was a poor location for colonization. The men dug wells to obtain water, but the water they found could not drink because it was contaminated. In addition, the ground was wet and had too many mosquitos. The mosquitoes were carriers of diseases and made the settlers sick. After a year, about half of the settlers had died of disease and starvation. The Native American Indians kept the English alive providing them with food. The English were so busy trying to discover gold that they didnt bother trying to grow food. That was when Captain John Smith became leader of the Jamestown colony. He saved the colony by creating a rule, which maintained that anyone who did not work would have no right to eat. This made the colonist planted food, and they were forced to build shelters and fences to protect against any attack. These American Indians or â€Å"Amerinds†, showed them great diversity of character and attainments due to the differences in climate, soil, food, building material, and the activities necessary to preserve life. They taught the settlers how to plant and grow corn, beans, squash, etc. and also helped them to establish good relations with neighboring Indian tribes. On the other hand what the English settlers offered to Native Americans Indians was different. In exchange for food, they offered them weapons, horses, cattle, sheep, vegetables and fruits, hatchets, swords, metal pots, skillets and knives, which would give them the technological advantage over their enemies. They brought not only tools for the conquest of the wilderness, but also the forms of government, the religion, the books, and the languages of the Old World. But besides the different technologies and different lifestyles that they offered to them, the English brought with them different types of diseases, such as smallpox, which was lethal to Amerinds, this produced a lethal epidemic that affected a large portion of the tribe. American Indians had a very different culture from the English people. Despite some successful interaction, questions of ownership and control of land and trust between peoples, caused conflicts arise. Virginia suffers very frequent periods of drought and by that time the colonists did not understand that the natives were ill prepared to feed them during the hard times. In the years after 1612, settlers cleared the land to prepare it for export farms dedicated tobacco, its crucial crop for economic purposes. When the tobacco exhausted farmland, the settlers continuously had to clear more areas to replace them. This small wooded land was that the Indians could use to hunt and supplement their food crops. The more settlers arrived, the more demanding land. The spread of tobacco cultivation altered life for everyone, because its cultivation required abundant land. The tribes tried to fight the invasion of the settlers. The main conflicts occurred with the indigenous slaughter of 1622 and another in 1644, both under the command of the younger brother of the late Chief Powhatan, Chief Opechancanough. Recognizing the danger, the war leader launched coordinated attacks along the James River on March 22, 1622. By the end of the day 347 colonist lay dead, and only a timely warning from two Christian converts saved Jamestown itself from destruction. Europeans had a very mixed picture of the native Indians. On one hand, they believed that the Indians could be soft and generous and also attentive and willing to trade. At first it was a very positive image and the settlers had hoped that they would be welcomed with open arms and friendly hands. They wanted to believe their way to the Garden of Eden. 2. After reading the three sources that tell the story of the Indians and the Settlement of America, I found it more accurate the description number 3 A people and a Nation (2008) that gives us Mary Beth Norton, because I think is a very complete description about the events that occurred with the New World. She begins by describing how other civilizations of America were. She mentions how that residents, of what is now central Mexico began to cultivate food crops, especially corn, squash, beans, avocados, and peppers; while in the Andes Mountains of South America, people began to cultivate potatoes, and it was thanks to the improvement of these techniques of agriculture that could be spread this knowledge through America with the exception of those areas with harsher climates. Thanks to agriculture most of the Americans began to adopt a more sedentary life, without the need to spend so much time hunting and gathering. I believe that it is very appropriate that she mentions these details, since it is important to us as readers have an idea of how other civilizations in the Americas were, in this manner we can understand a little more about the civilization of the Native Americans Indians, because in some way they were very similar to each other. In the same way, in this source the author also makes mention of another significant civilization of America, the Aztecs; they were one of the most important and recognized civilizations of the American continent, they had a style a little different from other civilizations, they tended to be a little more wild, they use to forced their neighbors to pay tribute in textiles, gold, foodstuffs and even in human beings, who were sacrificed to the war god Huitzilopochtli. After the author made mention of these events, she continues her story mentioning the arrival of the English for the first time in 1607 to a region near to Chesapeake Bay called Tsenacomoco. It was a group of 104 men and boys, who established the palisaded settlement called Jamestown. This source tells us the beginning of a radical change to this Nation; the author mentions the number of people, the name of the region in which they arrived, and the date on which this happened; it seems to me that these data are necessary to know for any American person, I think it is important for all of us who live in this continent know this historical fact, and more specifically know what happened in this country. I am convinced that this source is more accurate, because it shows us these and more details, and is more precise describing how was the relationship between the colonists and the Native American Indians. It shows us what was the difference between these two different civilizations, and at the same time expresses us which were their similarities. Both groups held deep religious beliefs, subsisted primarily through agriculture, accepted social and political hierarchy, and observed well-defined gender roles. Despite the coexistence that came to have each other, both groups continued to have their own beliefs and thoughts, which for me in somehow led them to start a war, because the settlers wanted to impose their will on the Indians, and at the same time the Indians wanted to not let this happen, and also they were tired of being their food source and carriers of diseases that the settlers brought.

Sport specialization in children

Sport specialization in children Youth Sport Specialization Abstract Children should be encouraged to participate in a lot of different physical activities to develop a wide range of skills. Safety is an important factor of why sport specialization is such a big research topic. This paper will look at the research to determine at what age is the most beneficial for a youth athlete to specialize in one sport. The term â€Å"sport specialization† is defined as intense year round training in a single sport with the exclusion of other sports at a very young age. The myth of the only way to master a skill is 10,000 hours of practice will be looked at and what affects that might have on child as opposed to a more mature athlete. Keywords: Sport specialization, year-round training, burnout. Youth sport participation proves a rewarding experience for young athletes in which they can develop psychological, social, and physical benefits. It can also for some athletes serve as an opportunity to cultivate athletic talent similarly to school cultivating knowledge. The problem is that athletic talent development and the process how that occurs is misunderstood and it often results in unsuitable practices. Sport specialization is one way that young athletic talent can be abused. Sport specialization has been going on for years. With the new technology and advances in the medical field new research has been going on to determine what is the appropriate age group a person should start specializing in their specific sport to one day achieve a professional contract. â€Å"Sport scientists have reported that there are critical periods in the life of a young athlete in which the effects of training can be maximized† (Leite Sampaio, 2012). Over the last twenty years the practice of specializing in one sport on a year-round basis has increased. In a survey of 152 high schools athletic directors over 70 percent of them felt that sport specialization was on the rise (Hill Simons, 1989). Some of the important factors contributing the increase in sport specialization included: pressure from coaches, athlete’s want to participate in championships, an emphasis on specialization in the area the athlete lived, the high expectations of parents, and encouragem ent from college recruiters. The exact number of young athletes specializing today is not exactly known even though research shows that it is on the rise. Concerns over specialization include that athletic performance cannot be narrowed down to a specific age in childhood and correlate directly to performance at a later age. According to Weirsma, â€Å"98% of athletes who specialize will never reach the highest levels of the sport (2000). From the perspective of sociology early specialization can isolate the young athlete from friends and hinder normal identity development. Early specialization is also thought to be related to an increase in burnout or withdrawal from sport as a result of prolonged stress. One of the theories grabbed by pro specialization people is Ericsson’s 10,000 hours of deliberate practice (1996). The most important question is what age should young athletes specialize in a specific sport? Researchers and professionals are concerned that specialization is happening at too young of an age. Preliminary evidence shows that early specialization has little advantages, but it may also have negative psychological, social, and physical effects on young kids. The American Academy of Pediatrics (2000) ask for caution when it comes to early specialization. They also stress the importance of providing young athletes and coaches recommendations and knowledge to help them with avoiding the negative effects of early specialization. One of the key terms used in sport specialization is â€Å"year-round training†. This term is used for young athletes who are involved in A.A.U. or club sports that operate outside of a student’s school team sports. This is seen in basketball, volleyball, and soccer. Swimming and gymnastics are the outliers when it comes to sports. Gymnastics is proven that a child at a younger age is more flexible and can teach train their bodies to participate in the sport at high level at a young age. Most athletes who dedicate their young lives to gymnastics will stop when they hit puberty due to their body not being able to keep the flexibility they had when they were younger or they become burnout on the sport. Another key term used is â€Å"burnout†. Burnout occurs when the athlete either becomes bored with the sport or the outside stress put on the athlete by parents and coaches becomes too much for the athlete to handle and they drop out of the sport. For the future this topic of sport specialization will become evident with the students and athletes that I will be over as an athletic director. In high school I will see students either not wanting to participate in sports due to their previous experience in sports or I will have students with constant injuries due to their specialization in a specific sport. It is important to continually be looking at research so that I can hopefully educate my parents that I will be in contact with daily as well as the coaches that I will be conversing with directly. It is vital that my parents understand the potential issues and problems sport specialization can have on their son or daughter. It is also going to require discretion when I have these conversations with adults. There needs to be understand that the parents have sacrificed a lot of money, time, and miles so that their child can succeed in sports. Some parents may be open to hearing the research on the topic and others may be angry with even the suggestion that what they are choosing to do with their child is wrong. One idea is to post the research found on the school’s website along with other major issues seen in schools and sports across the United States. This will allow the parents the option to understand themselves what the research is saying about specific topics such as sport specialization and it can help them make decisions according to what they interpret from the research. It would be ideal to internship with a local middle school and high school athletic director to see what their day to day life is like during the school year and summer. This experience will help with the understanding of dealings with other schools, scheduling of games and referees, dealings with athletes, coaches, and parents directly, as well as what it takes to be in a highly touted position. It would also be interesting to ask questions of people in the athletic director position on tough decisions they have had to m ake and why they chose one decision over the other. I foresee the internship as a priceless experience that can answer a lot of questions as well as show the ins and outs of what it takes to be an athletic director in the area. In conclusion sport specialization is important for any athlete to become elite. As the research points out the hard part is pinpointing the age at which a child should specialize. The whole issue with specialization is raised because of safety. The most important goal of any coach, parent, or athletic director is safety. When the safety of the athlete is compromised it can be detrimental to the athletes psyche emotionally and physically. As long as the athlete’s safety is held in the highest regard then the job is done. Hopefully as more research comes to light on sport specialization parents, coaches, and athletic directors will use it to keep the athlete safe because life after sports is more important than the short term sporting career most athletes will have. References AAP Advises Against Early Sports Specialization. (2000).Physician Sportsmedicine,28(8), 15. Intensive Training and Sports Specialization in Young Athletes. (2000).Pediatrics,106(1), 154. Baker, J., Cobley, S., Fraser-Thomas, J. (2009). What do we know about early sport specialization? Not much!.High Ability Studies,20(1), 77-89. doi:10.1080/13598130902860507 Bodey, K. J., Judge, L. W., Hoover, J. V. (2013). Specialization in Youth Sport: What Coaches Should Tell Parents.Strategies (08924562),26(1), 3-7. Callender, S. S. (2010). The Early Specialization of Youth in Sports.Athletic Training Sports Health Care: The Journal For The Practicing Clinician,2(6), 255-257. Capranica, L., Millard-Stafford, M. L. (2011). Youth Sport Specialization: How to Manage Competition and Training?.International Journal Of Sports Physiology Performance,6(4), 572-579. Christianson, P., Deutsch, J. (2012). Making a Case for Early Sport Specialization in Youth Athletes.Journal Of Youth Sports,6(2), 3-6. Clarke, N. J., Harwood, C. G. (2014). Parenting experiences in elite youth football: A phenomenological study.Psychology Of Sport Exercise,15(5), 528-537. Gonà §alves, C. B., Rama, L. L., Figueiredo, A. B. (2012). Talent Identification and Specialization in Sport: An Overview of Some Unanswered Questions.International Journal Of Sports Physiology Performance,7(4), 390-393. Hill, G. M., Simons, J. (1989). A study of the sport specialization on high school athletics. Journal of Sport Social Issues, 13(1), 1-13. Leite, N. C., Sampaio, J. E. (2012). Long-Term Athletic Development Across Different Age Groups and Gender from Portuguese Basketball Players.International Journal Of Sports Science Coaching,7(2), 285-300. McLeod, T. V., Decoster, L. C., Loud, K. J., Micheli, L. J., Parker, J. T., Sandrey, M. A., White, C. (2011). National Athletic Trainers Association Position Statement: Prevention of Pediatric Overuse Injuries.Journal Of Athletic Training (National Athletic Trainers Association),46(2), 206-220. Mostafavifar, A. M., Best, T. M., Myer, G. D. (2013). Early sport specialisation, does it lead to long-term problems?.British Journal Of Sports Medicine,47(17), 1060-1061. NYLAND, J. (2014). Coming to Terms With Early Sports Specialization and Athletic Injuries.Journal Of Orthopaedic Sports Physical Therapy,44(6), 389-390. Russell, W. D. (2014). The Relationship between Youth Sport Specialization, Reasons for Participation, and Youth Sport Participation Motivations: A Retrospective Study.Journal Of Sport Behavior,37(3), 286-305. Wall, M., Cà ´t, J. (2007). Developmental activities that lead to dropout and investment in sport.Physical Education Sport Pedagogy,12(1), 77-87. doi:10.1080/17408980601060358 Wiersma, L.D., (2000). Risks and benefits of youth sport specialization: Perspectives and recommendations. Pediatric Exercise Science, 12, 13-22.

Poor Reproductive Fitness of Sperm in Aging Males

Poor Reproductive Fitness of Sperm in Aging Males Deterioration of germline DNA found to produce low quality offspring in aged male houbara bustards. A study in houbara bustards, an African bird species gives insight on what is happening with aging men. The scientists suggest that the decline in hatching success observed is caused by senescent decline of both male and female gametes. On the other hand, the development of chicks within the egg appear to be influenced solely by maternal aging which can be explained by reduction in older females’ abilities to provision their eggs. The researchers then monitored the artificial insemination of houbara bustards ranging in age from 1 to 23, recorded the egg hatching success as well as the growth of resulting chicks. Their results found that eggs produced from inseminating older females with ejaculate from older males have lower hatching success as compared to eggs of parents at peak age. The scientists suggest that the decrease in hatching success observed is caused by senescent decline of both male and female gametes. Of the eggs that did hatch, it was discovered that the mass of chicks at hatching were heaviest in chicks born to young mothers, suggesting that the development of chicks within the egg appear to be influenced solely by maternal aging. This can be explained by reduction in older females’ abilities to provision their eggs. Additionally, it was found that chicks born to young fathers had the best overall growth within the first month of life than those born to older fathers. The reason for this is that since males only contribute their DNA to offspring, the growth of the How Reproductively Fit is the Sperm of Older Males? A study in houbara bustards, an African bird species gives insight on the production of low quality offspring in aging men. Gametes are reproductive cells such as ovum or sperm, containing the genetic material required to form a new organism. This genetic material is essential in determining the quality of offspring produced. According to the paper by Brian Preston and his colleagues in Nature Communications, gametes from animals of advanced years undergo degradation by a process called senescence. Senescence is a gradual decline of function and can occur by two mechanisms. The first is the decline in the performance of their spermatogenic machinery such that the sperm has difficulty in carrying out its function. The second mechanism involves the build-up of genetic mutations within the germline of gametes, resulting in the degradation of the DNA carried within. These mechanisms lead to a reduction in both the viability and quality of offspring produced. To determine whether male aging has influence on reproductive fitness, Brian Preston and his colleagues examined 10 years’ worth of data regarding the post insemination success of male houbara bustards part of a captive breeding programme. To begin with, female bustards were inseminated with ejaculates collected from males. The male and female bustards involved in this study ranged from 1 to 23 years of age. Eggs produced were collected and the hatching success recorded. The researchers found that eggs produced from inseminating older females with ejaculate from older males have lower hatching success as compared to eggs of parents at peak age, suggesting that this is caused by senescent decline of both male and female gametes. Furthermore, of the eggs that did hatch, it was discovered that the mass of chicks at hatching were heavier in chicks born to young fathers compared to older fathers. Additionally, a measure of overall growth within the first month of life showed that chicks born to old fathers had the worst overall growth. The scientists reasoned that the cause for growth patterns observed in chicks born to old fathers confirms that the dominant mechanism of senescence in the bird species is mutation-based aging of germline DNA. This is because, since males only contribute their DNA to offspring, the growth of the chicks is inhibited. Eggs produced were collected for incubation and hatched chicks were hand-reared so as to avoid any confounding variables. The researchers monitored the artificial insemination of houbara bustards ranging from 1 to 23 years old, recorded the egg hatching success as well as the growth of resulting chicks. Their results found that eggs produced from inseminating older females with ejaculate from older males have lower hatching success as compared to eggs of parents at peak age, suggesting that this is caused by senescent decline of both male and female gametes. Of the eggs that did hatch, it was discovered that the mass of chicks at hatching were heaviest in chicks born to young fathers. Furthermore, it was found that chicks born to old fathers had the worst overall growth within the first month of life than those born to younger fathers. The scientists suggest that the development of chicks within the egg appears to be influenced solely by maternal aging. This can be explained by reduction in older females’ abilities to provide their eggs with nutrients. On the other hand, the researchers reasoned that the cause for growth patterns observed in chicks born to old fathers confirms that the dominant mechanism of senescence in the bird species is mutation-based aging of germline DNA. This is because, since males only contribute their DNA to offspring, the growth of the chicks is inhibited. According to a recent study by Brian Preston and his colleagues in Nature Communications, gametes (ovum or sperm) from animals of advanced years undergo degradation by a process called senescence. Senescence is a gradual decline of function and occurs by two mechanisms. The first involves the decline of the spermatogenic machinery performance while the second mechanism involves the build-up of genetic mutations within the germline DNA of gametes. To determine whether male aging has influence on reproductive fitness, the researchers examined 10 years’ worth of data on the post insemination success of male houbara bustards aged between 1 to 23 years that were part of a captive breeding programme. First, female bustards were inseminated with the male ejaculates collected so that gametes are the only influencing factor on offspring quality. The eggs produced from older parents were seen to have lower hatching success when compared to eggs of peak age parents. Of the eggs that did hatch, researchers observed that the lightest chicks at hatching were a result of maternal aging. Alternatively, a measure of overall growth within the first month after hatching revealed that chicks born to older fathers had the worst overall growth. In other words, as males age, their ability to produce offspring that are viable and of high quality diminishes. These findings lead scientists to conclude that the dominant mechanism of senescence in the bird species is mutation-based aging of germline DNA. Additionally, it seems that the decline in offspring development linked to paternal aging is similar in scale to that linked to maternal aging. Interestingly, when findings were compared with that of human studies similar patterns were observed, deepening concern for the recent trend of delayed parenthood in both sexes. In future, Brian Preston and his colleagues wish to be able to identify and quantify the reproductive cost associated with male aging in a long-lived species. In their most recent work, published in Nature Communications, they found that, not only did males appear less able to produce offspring successfully as they aged, they also appeared to produce offspring that were of intrinsically lower quality. Perhaps most surprisingly, these declines in offspring quality were of a similar size to those resulting from maternal aging. Patterns observed in humans are in line with the findings in houbara bustards and their interpretation, with paternal aging being linked to adverse reproductive outcomes, a number of genetic diseases, and some mental disorders. The evidence is beginning to accumulate that delaying parenthood until later life can potentially have negative consequences for the children of both older men and women. Read more at: http://phys.org/news/2015-02-male-birds-reproduction-life.html#jCp

Corporate Entrepreneurship Essay -- Entreprenuer

Corporate Entrepreneurship Corporate Entrepreneurship can be seen as the process whereby an individual or a group creates a new venture within an existing organization, revitalizes and renews an organization ,or innovates. Zahra’s(1986) definition of corporate entrepreneurship suggests a formal or informal activity aimed at creating new businesses in established firms through product and process innovations and market developments,whereas sathe(1985) defines corporate entrepreneurship as a process of organizational renewal. Corporate Entrepreneurship has emerged as a much needed ingredient contributing towards the growth of any organization under a changing business environment. Corporate entrepreneurship (CE) is widely considered as a vital means to stimulate and sustain the overall competitiveness of an organization. Both practitioners and researchers have recognized the challenges of pursuing entrepreneurship within a corporation. CE is the result of the joint activities of an organization’s members, activities that pursue strategic objectives and constitute strategic roles. Thus, to face the challenges that CE poses for both theory and practice we need to advance our understanding of the activities and strategic roles involved in the CE process and their implications for performance. While strategic roles have been extensively studied, most studies analyze the strategic role of top managers and ignore the contribution of middle managers. Moreover, while there is a growing body of empirical evidence of a positive relationship between CE initiatives and performance, little research emphasizes the contribution of middle managers’ strategic rol es to superior performance. Innovation and entrepreneurship are often regarded as ... ...ll as private sectors have gone international with new ventures outside the country. These companies are generating revenue, though modest compared to their overall sales revenue, by deputing their expert personnel outside. Strategic renewal is another desired outcome of corporate entrepreneurship. The new economic order and business environment has created a pace of change which requires businesses to adapt more frequently and rapidly than ever before. The changes could involve corporate structure, mergers and acquisitions, addressing new market opportunities, changing product portfolios, repositioning, adapting infrastructure, or adopting new technology. Managers in an organization must be able to take stock of its situation under changing market conditions and agree on a coherent new strategy that will meet the challenges of the present as well as of the future.

Psychological Analysis of Little Red Riding Hood Essay -- Little Red R

Psychological Analysis of Little Red Riding Hood In the story of Little Red Riding Hood, you hear about the grandmother, the granddaughter, and the wolf. But the reader does not hear much about the mother. In Olga Broumas' poem "Little Red Riding Hood", the reader can hear about the mother's impact on Little Red's life, or the lack of one. At the first glance, Little Red Riding Hood appears as a lament of a daughter who misses a dead mother or who is trying to explain to her mother about her lot in life. However, when viewed in the light of the Psychological approach, the reader is able to see the writer's life in full detail: her sexual orientation, her hate/fear of men, and her inability to have children. The "her" of course being the writer. The first part, we now deal with the sexuality of the narrator. In the poem, there was a verse that said this: I kept the hood secret, kept it sheathed more secret still. I opened it only at night, and with other women who might be walking the same road to their own grandma's house...their HOODS secure in the SAME PART(Stor...

APS essay

Culminating Activity, Identity and Behavior Profile In class and at home, you will have had a chance to study and evaluate different personality traits and theories of personality development. You will now Identify an aspect of your personality that you think Is Important In defining who you are as a person. You will then apply the previously studied traits and theories to yourself. As support for your analysis. You will use examples gathered from research on current events. Short Essay Topic:Based on the information you have learned about personality development, write a paragraph explaining how at least two theories helped shape your own personality. Refer to specific personality traits that you have and how they might have been formed by the elements of the various theories. Hints on Essay Structure: Follow the structure given on the Social Studies Essay Rubric and also include these additional points. In the Introductory paragraph, be sure to describe the behavior and personality trait you will analyze.You should also briefly introduce the theories that you will apply in your analysis. Your thesis statement should refer to the theories explain your behavior and personality trait. For the first Body paragraph, write about one theory and how it explains your behavior and personality trait. Be sure to fully explain how the theory applies to your trait, and then use an example from current news events to Illustrate your point. For the second body paragraph, write about another theory and the same trait. Make the same kind of explanation and analysis s you did In the first body paragraph.In the Concluding paragraph, end with a point about what your analysis of behavior and personality tells us about your Identity. Evaluation: Social Studies Essay Rubric. Please hand in rubric with paragraph. You may write in first person for this essay. Length: Approximately 2 pages, double-spaced Rubric for Identity and Behavior Profile Levels of Achievement Criteria Level 3 Le vel 1 Understanding (K) Understanding of terminology, facts and concepts related to topic Consistently monstrance a thorough understanding through correct application, definition and usage of facts, terms, etc.Demonstrates a considerable understanding, through correct application, definition and usage of facts, terms, etc. Demonstrates some understanding, through some correct application, definition and usage of facts, terms, etc. Demonstrates limited understanding, through incorrect or missing application, definition and usage of facts, terms, etc.

Traffic Movement in Lufthansa Airlines: a Supply Chain Perspective

Journal of Services Research Volume 10 Number 2 October 2010 – March 2011 FORECASTING THE PASSENGER TRAFFIC MOVEMENT IN LUFTHANSA AIRLINES: A SUPPLY CHAIN PERSPECTIVE Aniruddh Kr Singh Faculty of Management Studies University of Delhi, India. Debadyuti Das Associate Professor, Faculty of Management Studies University of Delhi, India. The Journal of IIMT FORECASTING THE PASSENGER TRAFFIC MOVEMENT IN LUFTHANSA AIRLINES: A SUPPLY CHAIN PERSPECTIVE Aniruddh Kr Singh Debadyuti DasThe present paper attempts to find out the forecasted passenger traffic movement of Lufthansa Airlines on quarterly basis at a global level by employing four forecasting methods namely moving average, exponential smoothing, Holt's model and Winter's model with the help of published data pertaining to passenger traffic movement of Lufthansa Airlines. The study has also found out the forecasting errors of all the four methods through Absolute error (AE), Mean squared error (MSE), Mean absolute deviation (MAD ) and Mean absolute percentage error (MAPE).The study also carried out the comparative analyses of the above forecasting methods in the light of the available data. The findings reveal that the forecasting errors are the least in case of Winter's model. Further the forecasted values suggested by Winter's model more closely resemble the observed data of passenger traffic movement of Lufthansa Airlines. This provides a valuable insight to the top management as regards formulation of suitable strategies for addressing the varying demand of passenger traffic movement.Few strategies in respect of both demand side and supply side options have been suggested with a view to improving the overall supply chain profit of Lufthansa Airlines. INTRODUCTION irlines industry across the globe is currently undergoing recession due to severe financial crisis faced by the major economies of the world. As per the estimates of International Air Transport Association (IATA), globally air travel has declin ed by 2. 9% and 1. 3% during September and October, 2008 respectively compared to the same months in the previous year.Segment-wise passenger traffic estimates provided by IATA further reveal that the Asia Pacific Carriers and North American Carriers registered a decline in passenger traffic flow by 6. 1% and 0. 9% respectively in October, 2008 compared to the same month in the previous year. African Carriers recorded the largest decline in traffic flow by 12. 9% in October, 2008 Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011)  ©2010 by Institute for International Management and Technology. All Rights Reserved. A 4 Forecasting the Passenger compared to the same month in the previous year. The remaining segments namely European, Latin American and Middle Eastern Airlines experienced a moderate growth in its traffic flow to the tune of 1. 8%, 4. 5% and 3. 5% respectively in October, 2008 (IATA International traffic statistics, 2008a, 2008b). Howe ver, the financial crisis sweeping across the globe does not appear to have much negative impact on Lufthansa Airlines in respect of its passenger traffic flow till September, 2008 as revealed from the data provided in table 2a.A cursory observation into the table 2 further demonstrates that the passenger traffic flow in Lufthansa Airlines has been following a very systematic pattern since October, 2006 to September, 2008. There has been hardly any departure from the pattern observed in passenger traffic movement during the above period. Despite difficult market conditions, Lufthansa passenger Airlines was able to achieve a sales growth of 4. 2% and 0. 7% in September and October, 2008 respectively.It registered an increase in its passenger traffic flow in three major markets namely America (North/South), Asia/ Pacific, and Middle East & Africa both during September and October, 2008. American segment recorded a growth rate of 6. 9% and 1% during September and October, 2008 respecti vely. Asia/Pacific region exhibited an increasing trend of 8. 8% and 6% while Middle East and African region recorded an increasing trend of 2. 5% and 11% during September and October, 2008 respectively. Only European market experienced a declining trend to the tune of 0. 4% and 3% during the above periods (Lufthansa Investor Info, page 1, 2008).The above phenomenon has motivated us to apply the most popular and well-established forecasting methods with a view to finding out the forecasted demand of passenger traffic movement of Lufthansa Airlines for future periods. The main objective of the paper is to find out the quarterly forecasted demand of passenger traffic flow in Lufthansa Airlines at a global level with the help of moving average (MA), exponential smoothing (ES), Holt’s model and Winter’s model by making use of published data pertaining to passenger traffic movement in Lufthansa Airlines.In addition, the paper has also attempted to find out the most suitable forecasting model for the above problem by comparing the forecasting errors of the above four forecasting models obtained through absolute error (AE), mean squared error (MSE), mean Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 65 Singh, Das absolute deviations (MAD) and mean absolute percentage error (MAPE). The following section provides a brief review of literature. Section 3 provides a brief overview of Lufthansa Airlines along with the recent data on passenger traffic movement.It contains a thorough analysis of forecasted passenger traffic movement by employing four forecasting methods and the comparative analysis of the same. Section 4 suggests few strategies for absorbing the varying nature of demand. The paper is concluded with a brief summary, potential contribution and limitations of the same. REVIEW OF LITERATURE Forecasting literature is replete with a number of studies ranging from simple time-series forecasting models to economet ric models as also the forecasting models employing artificial intelligence techniques etc.Researchers have employed the forecasting models with a view to finding out the forecasted demand of traffic for a particular period. However, the study findings reveal that there does not exist a single model which consistently outperforms other models in all situations. Quantitative forecasting methods can be categorized under three broad heads: (1) time-series modeling, (2) econometric models and (3) other quantitative models (Song and Li, 2008). Under time-series models, several techniques are available, e. g.Moving Average, Exponential Smoothing, Holt’s Model, Winter’s Model, ARIMA etc. (Makridakis et al, 2003). In time-series model, particular attention is paid to exploring the historic trends and patterns of the time-series involved and to predict the future of this series based on trends and patterns identified in the model. Since time-series models require only historica l observations of a variable, it is less costly in data collection and model estimation. However, these models cannot account for the changes in demand that might occur in different periods.The major advantages of econometric models over time-series models lie in their ability to analyze the causal relationships between the demand and its influencing factors (Song and Li, 2008; Makridakis et al, 2003). It is possible for econometric models to take into consideration several variables together, for example, air fare charged by an airline, competitive fare offered by other airlines, promotional campaign, perceived security threat, price and income elasticity of Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 6 Forecasting the Passenger demand etc. However, it is difficult and costly to collect data on each individual variable, incorporate the same into the model and explain its contribution towards the dependent variable. A number of new quantitati ve forecasting methods, predominantly Artificial Intelligence (AI) techniques, have emerged in forecasting literature. The main advantage of AI techniques is that it does not require any preliminary or additional information about data such as distribution and probability (Song and Li, 2008).Table 1 provides a brief overview of some related works pertaining to forecasting and traffic movement in airlines. Table 1: Brief Overview of Few Works Relating to Traffic Movement in Airlines Author Choo and Mokhtarian (2007) Contribution Developed a conceptual model in a comprehensive framework, considering causal relationships among travel, telecommunications, land use, economic activity and socio-demographics and explored the aggregate relationships between telecommunications and travel using structural equation modeling of national time-series data spanning 1950-2000 in the US.Proposed an artificial neural network (ANN) structure for seasonal time-series forecasting. Results found by the p roposed ANN model were compared with the traditional statistical models which reveal that the prediction error of the proposed model is lower than the traditional models. The proposed model is especially suitable when the seasonality in time-series is very strong. Developed a methodology for assessing the future route network and flight schedule at a medium-sized European airport.The existing origin and destination demand from the base airport across the world is considered. In addition, the growth rates by country or region is also taken into account. The future origin and destination demand in then converted into route traffic subject to a threshold for direct service. Where demand falls below this level, traffic is reallocated via various appropriate hubs. Applied Static-regression trend-fitting model for the purpose of forecasting future tourism demand in North Cyprus.Applied different types of time-series forecasting modeling with reference to China and compared the forecasting accuracy of the models. Applied different types of time-series forecasting modeling with reference to Australia for the purpose of forecasting business tourism and compared the forecasting accuracy of the models. Employed autoregressive distributed lag model (ADLM) for the purpose of forecasting tourism demand at Greece.Hamzacebi (2008) Dennis (2002) Bicak, Altinay and Jenkins (2005) Kulendran and Shan (2002) Kulendran and Witt (2003) Dritsakis and Athanasiadia (2000) THE CASE OF LUFTHANSA AIRLINES Deutsche Lufthansa (Lufthansa), the third largest airlines of Europe, is the world’s fifth largest airline in terms of overall passengers carried and operating services to 209 destinations in 81 countries. It has the 6th largest passenger airline fleet in the world.Lufthansa is headquartered in Cologne, Germany with its main base and primary traffic hub at Frankfurt International Airport in Frankfurt and a second hub at Munich International Airport. Lufthansa has built a premium b rand synonymous with quality, innovation, reliability, competence and safety despite operating in a tough market where cost cutting is commonplace. Lufthansa founded the world’s first multilateral airline grouping, ‘Star Alliance’ along with Air Canada, SAS, Thai Airways and United Airlines.At the same time, the airline invested in the most advanced passenger aircrafts and in 1999 it embarked on a vast IT programme that would transform the revenue and profit of its passenger Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 67 Singh, Das airline business (Lufthansa, Wikipedia, 2008). However, estimating the demand of passenger traffic for a particular period has always been the principal determinant in generating revenue for the airline. Table 2a shows the passenger traffic movement in Lufthansa (excluding the number in Swiss Airlines) Airlines for the period during October, 2006 to September, 2008.Table 2 (a): Monthly Traffic F low for the Last Two Years Traffic Year – Month Oct-06 Nov-06 Dec-06 Jan-07 Feb-07 Mar-07 Apr-07 May-07 Jun-07 Jul-07 Aug-07 Sep-07 Oct-07 Nov-07 Dec-07 Jan-08 Feb-08 Mar-08 Apr-08 May-08 Jun-08 Jul-08 Aug-08 Sep-08 Passenger traffic (in thousands) 4936 4327 3969 3851 3820 4668 4635 4991 5003 5241 5067 5193 5241 4604 4132 4141 4223 4625 5031 5152 5203 5171 4883 5164 2006 Q- 4 2007 Q- 1 2007 Q- 2 2007 Q- 3 2007 Q- 4 2008 Q- 1 2008 Q- 2 2008 Q- 3 13232000 12339000 14629000 15501000 13977000 12989000 15386000 15218000Table 2 (b): Quarterly Data of Passenger Quarters Passenger traffic Source of data: Key data, Lufthansa Investor Relations, 2008; Lufthansa Investor Info, page 2, 2008 The monthly passenger traffic shown in table 2 (a) has been utilized to calculate the quarterly data of passenger traffic for the last two years Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 68 Forecasting the Passenger (from Quarter 4, 2006 to Quarter 3, 2008) w hich has been shown in table 2 (b).With the help of these quarterly data of passenger traffic for the last two years, we have attempted to find out the forecasted values of passenger traffic movement by employing four forecasting methods namely 4-period Moving Average, Simple Exponential Smoothing, Holt’s Model and Winter’s Model. Table 3 presents the forecasted values through 4-quarter moving average while table 4 shows the forecasted data through simple exponential smoothing. Table 5 and 6 shows the forecasting through Holt’s model along with forecasting errors.Table 7 through 10 reveals, in detail, the forecasted demand of the passenger traffic flow by employing Winter’s Model. Table 10 also includes the forecasting errors. The exercise reveals that the forecasting errors are the lowest in case of Winter’s Model which are indicated by the values of AE, MSE, MAD and MAPE. Moreover, the quarterly forecasted values suggested by Winter’s Mode l closely follow historical pattern which is clearly depicted in figure 1. FORECASTING THROUGH 4-PERIOD MOVING AVERAGE (MA) Moving Average method is generally employed in a situation in which only level, i. e. eseasonalized demand is present and neither trend nor seasonality is observed. We took the average traffic flow of four quarters starting from the 4th quarter of 2006 and continued the exercise till the 3 rd quarter of 2008 for the purpose of finding out the forecasted passenger traffic movement in the immediate following quarter. Table 3 presents the forecasted values of passenger traffic movement through four-quarter MA method. In the same table, the values of forecasting errors measured in terms of AE, MSE, MAD and MAPE are also shown. Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 9 Singh, Das Table 3: Forecasting through 4-Period Moving Average & Forecasting Errors Period(t) 1 2 3 4 5 6 7 8 Quarters Traffic (D) Level (L) Forecast (F) Four Period Moving Average Method Absolute Error Mean Squared Error Error (E) (AE) (MSE) Mean Absolute Deviation (MAD) 2006 Q- 4 13232000 2007 Q- 1 12339000 2007 Q- 2 14629000 2007 Q- 3 15501000 13925250 2007 Q- 4 13977000 14111500 13925250 2008 Q- 1 12989000 14274000 14111500 2008 Q- 2 15386000 14463250 14274000 2008 Q- 3 15218000 14392500 14463250 -51750 1122500 -1112000 -754750 51750 1122500 1112000 754750 2678062500 6. 31342E+11 8. 3076E+11 7. 67219E+11 51750 587125 762083. 3333 760250 % Error MAPE Forecasted Traffic F9=F10=F11=F12=14392500 0. 37025113 0. 37025113 8. 64192779 4. 50608946 7. 22734954 5. 41317615 4. 95958733 5. 29977895 Formula used Systematic demand = Level Lt= (Dt + Dt-1+†¦.. Dt-n+1)/N Ft+1=Lt Ft+n=Lt (Chopra and Meindl, 2007) FORECASTING THROUGH EXPONENTIAL SMOOTHING (ES) Like moving average method, exponential smoothing is also used in a situation, in which only level is observed. However, ES attempts to smoothen the fluctuations observed in demand data o f different periods through smoothing constant (alpha).We first calculated the level of passenger traffic flow of the initial period by taking the average of actual traffic flow for the last eight quarters, which has been considered as the forecasted value of passenger traffic flow for quarter 1. Table 4 demonstrates the forecasted values through simple ES. The same table also contains the values of forecasting errors expressed in terms of AE, MSE, MAD and MAPE. Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 70 Forecasting the Passenger Table 4: Forecasting through Simple Exponential Smoothing & Forecasting Errors Period(t) 0 1 2 3 4 5 6 7 8 % Error 7. 0479897 13. 9977916 5. 02789835 9. 89599461 1. 02611209 8. 60018261 9. 04478131 7. 12621269 2006 Q- 4 2007 Q- 1 2007 Q- 2 2007 Q- 3 2007 Q- 4 2008 Q- 1 2008 Q- 2 2008 Q- 3 MAPE 7. 00479897 10. 5012953 8. 67682963 8. 98162087 7. 39051912 7. 5921297 7. 79965136 7. 71547153 Formula used Systematic de mand = Level Ft+1=Lt Ft+n=Lt Lt+1=alpha(Dt+1)+(1-alpha)Lt alpha=0. 1 Forecasted Traffic F9=F10=F11=F12=14241980 13232000 12339000 14629000 15501000 13977000 12989000 15386000 15218000 Quarters Traffic (D) Level (L) 14158875 14066187. 5 13893468. 75 13967021. 8 14120419. 69 14106077. 72 13994369. 95 14133532. 95 14241979. 66 14158875 14066187. 5 13893468. 75 13967021. 88 14120419. 69 14106077. 72 13994369. 95 14133532. 95 926875 1727187. 5 -735531. 25 -1533978. 1 143419. 688 1117077. 72 -1391630. 1 -1084467 926875 1727187. 5 735531. 25 1533978. 125 143419. 6875 1117077. 719 1391630. 053 1084467. 048 8. 59097E+11 1. 92114E+12 1. 46109E+12 1. 68409E+12 1. 35139E+12 1. 33413E+12 1. 42021E+12 1. 38969E+12 926875 1327031. 25 1129864. 583 1230892. 969 1013398. 313 1030678. 214 1082242. 762 1082520. 98 Forecast (F) Simple Exponential Smoothing Method Absolute Error Error (E) (AE) Mean Squared Error (MSE) Mean Average Deviation (MAD) (Chopra and Meindl, 2007) FORECASTING THROUGH HOLT'S MODEL We carried out a regression analysis wherein Time period was considered on X-axis and passenger traffic data was taken on Y-axis in order to find out the initial level and trend. Holt's model, also known as trend-corrected exponential smoothing, is applicable in a situation, in which level and trend are observed in the demand data. However, seasonality is not considered in Holt's model.We used the â€Å"Linest Function†of Microsoft Excel to calculate the values of L0 and T0, which is shown in table 5. Table 5: Regression to Find Initial Level and Trend for Holt's Model x (Period) 1 2 3 4 5 6 7 8 270154. 7619 T0 y (Traffic) 13232000 12339000 14629000 15501000 13977000 12989000 15386000 15218000 12943178. 57 L0 Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 71 Singh, Das Once the initial values of level of trend are found, the subsequent values of the level and trend of each period are iteratively calculated following Holt's model which is shown in table 6.This finally helps in finding out the forecasted values of passenger traffic movement as per Holt's model, which is shown in table 6. Table 6 also reveals the forecasting errors. Table 6: Forecasting through Holt's Model Period(t) 0 1 2 3 4 5 6 7 8 2006 Q- 4 2007 Q- 1 2007 Q- 2 2007 Q- 3 2007 Q- 4 2008 Q- 1 2008 Q- 2 2008 Q- 3 13232000 12339000 14629000 15501000 13977000 12989000 15386000 15218000 Quarters Traffic (D) Trend(T) 270528. 095 Level (L) 13215200 Forecast (F) 13213333. 33 13485728. 1 13618648. 82 13987484. 49 14436906. 91 14679788. 95 14765767 15095251. 1 Error (E) -18666. 67 1146728. 1 -1010351 -1513516 459906. 91 1690788. 9 -620233 -122748. 1 Absolute Error (AE) 18666. 66667 1146728. 095 1010351. 181 1513515. 506 459906. 9118 1690788. 949 620232. 9957 122748. 0864 T8=269916. 6 15377443 15647360 15917276 16187193 Formula used Systematic demand = Ft+1=Lt+T t alpha =0. 1 Beta = 0. 2 Lt+1 = alpha(D t+1)+(1-alpha)(Lt+T t) T t+1= beta(Lt+1-Lt)+(1-beta)Tt Lev el + Trend Ft+n =Lt+nT t Mean Squared Error (MSE) 348444444. 4 6. 57667E+11 7. 78714E+11 1. 15672E+12 9. 67677E+11 1. 28286E+12 1. 15455E+12 1. 01211E+12 270154. 762 12943178. 7 247593. 533 13371055. 29 267800. 557 13719683. 94 298070. 867 14138836. 04 288872. 729 14390916. 22 255056. 95 267461. 61 14510710. 05 14827790. 3 269916. 571 15107526. 72 Mean Average Deviation (MAD) 18666. 66667 582697. 381 725248. 6476 922315. 3622 829833. 6721 973326. 2183 922884. 3294 822867. 299 % Error 0. 141072148 9. 293525369 6. 906495187 9. 763986233 3. 290455117 13. 0170833 4. 031151668 0. 806598018 MAPE 0. 141072148 4. 717298758 5. 447030901 6. 526269734 5. 879106811 7. 068769558 6. 634824146 5. 90629588 L8=15107527 F9 F10 F11 F12 Forecasted Traffic Chopra and Meindl, 2007) FORECASTING THROUGH WINTER'S MODEL Winter’s model, also known as trend and seasonality-corrected ES, is generally employed in a situation in which all characteristic features of demand data, i. e. level (Lt), trend (Tt) and seasonality (St) are observed. The actual demand (Dt), being seasonal in nature, is transformed into deseasonalized demand (Ddt ). The deseasonalized demand data and corresponding time periods are employed to run regression analysis in order to calculate the initial level (L0) and trend (T0) which is shown in table 7.The values of L0 and T0 are then used to find out the estimated deseasonalized demand (Dt) of passenger traffic of different time periods. Seasonal factors for each period are calculated using the formula Dt /(Dt) as shown in table 8. Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 72 Forecasting the Passenger Table 7: Regression Analysis for Finding out the Deseasonalized Demand X (Period) 3 4 5 6 140439. 5 Y (Deseasonalized demand)(Ddt) 14018375 14192750 14368630 14427880 13619931 T0 L0 Table 8: Calculation of Seasonal Factors for Winter's ModelPeriod(t) 0 1 2 3 4 5 6 7 8 2006 Q- 4 2007 Q- 1 2007 Q- 2 2007 Q- 3 2007 Q- 4 2008 Q- 1 2008 Q- 2 2008 Q- 3 13232000 12339000 14629000 15501000 13977000 12989000 15386000 15218000 14018375 14192750 14368630 14427880 13760370. 5 13900810 14041249. 5 14181689 14322128. 5 14462568 14603007. 5 14743447 0. 961602015 0. 887646116 1. 041858846 1. 093029187 0. 97590243 0. 898111594 1. 053618578 1. 032187385 Quarters Actual demand (Dt ) Deseasonalized demand (Ddt) Dt =L+Tt Seasonal factors (Dt / D t) Subsequently seasonality (St) is recalculated for each period as per Winter's model which is shown in table 9.Level and trend of each period are also iteratively calculated following Winter's model which have been mentioned in detail in table 9. Finally table 10 demonstrates the forecasted data of passenger traffic flow along with forecasting errors. Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 73 Singh, Das Table 9: Determination of Level, Trend and Seasonal Factors (Winter's Model) Period(t) Quarters Actual Traffic (Dt) Deseasonalized demand (Ddt) Estimated deseasonalized demand (Dt) 13760370. 5 13900810 14018375 14192750 14368630 14427880 14041249. 5 14181689 14322128. 14462568 14603007. 5 14743447 Seasonality St Level(L) Trend(T) 0 1 2 3 4 5 6 7 8 9 10 11 12 2006 Q- 4 2007 Q- 1 2007 Q- 2 2007 Q- 3 2007 Q- 4 2008 Q- 1 2008 Q- 2 2008 Q- 3 13232000 12339000 14629000 15501000 13977000 12989000 15386000 15218000 0. 968752222 0. 892878855 1. 047738712 1. 062608286 0. 968072702 0. 892415518 1. 047252432 1. 065603208 0. 968770988 0. 892874843 1. 047722994 1. 062255808 13619931 13755292. 34 13891430. 02 14027555. 72 14187811. 57 14334567. 79 14480348. 88 14626058. 49 14744278 140439. 5 139931. 6844 139552. 284 139209. 6254 141314. 2474 141858. 4444 142250. 709 142596. 999 140158. 8902 Table 10: Forecasting through Winter's Model and the Forecasting Errors Forecast(F) 13330389. 5 12406751. 72 14700803. 33 15053722. 24 13871635. 54 12918987. 41 15313552. 98 15737526. 24 Error(E) 98389. 50148 67751. 71749 71803. 33314 -447 277. 7569 -105364. 4571 -70012. 58968 -72447. 01855 519526. 2416 Absolute Error(AE) 98389. 50148 67751. 71749 71803. 33314 447277. 7569 105364. 4571 70012. 58968 72447. 01855 519526. 2416 Mean Squared Error (MSE) 9680494002 7135394612 6475502625 54870974917 46117113697 39247888533 34390843099 63830427174 Mean Average Deviation (MAD) 98389. 0148 83070. 60949 79314. 85071 171305. 5772 158117. 3532 143433. 226 133292. 3392 181571. 577 % Error 0. 743572411 0. 549085967 0. 490828718 2. 885476788 0. 753841719 0. 539014471 0. 470863243 3. 413893032 MAPE 0. 743572411 0. 646329189 0. 594495699 1. 167240971 1. 084561121 0. 993636679 0. 91895476 1. 230822044 L8=14407445 T8=3284577 Formula used Systematic component of demand =(level+demand)*seasonal factor Ft+1 = (Lt+T t)St+1 Ft+i=(Lt+iTt)St+i L t+1 = alpha (Dt+1/St+1)+(1-alpha)(Lt+Tt) T t+1= Beta (Lt+1 – Lt) + (1- Beta)T t St+p+1= gamma (Dt+1/Lt+1) + (1-gamma)St+1 Alpha = 0. 5 beta=0. 1 gamma=0. 1 Forecasted traffic F9 F10 F11 F12 14419 610. 62 13415083. 6 15888462. 17 16257733. 32 (Chopra and Meindl, 2007) COMPARISON AMONG FOUR FORECASTING METHODS The following figure gives an interesting revelation regarding the behaviour of forecasted data by comparing the quarterly forecasted demand of passenger traffic obtained through all four methods. Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 74 Forecasting the Passenger Historical traffic Forecasted traffic Moving Average Simple exponential smoothing Holt’s Model Winter’s ModelFigure 1: Comparison among four forecasting methods The portion of the graph before the vertical line indicates historical data while the portion of the graph after the line is the forecasted data. The forecasted data of the model graph (Winter's Model) replicates the historical data. It indicates a positive trend as well as seasonality. FORMULATION OF SUITABLE STRATEGIES FOR ABSORBING VARYING DEMAND Keeping in view the overall objective of impr oving the supply chain profit, the management should explore all possible alternatives of both demand side as well as supply side options.It is observed that demand for passenger traffic movement is not uniform throughout the year. In order to level the demand, the management of the airlines can undertake the following well-established measures: †¢ †¢ Formulate suitable marketing strategies to create new demand in the lean period. During peak periods, when the demand will exceed capacity, the management needs to offer seats to the customers who will pay the highest fares. Of course, other customers need to be motivated and informed that they would probably be charged less fare, if they undertake their trip at some other period.Shift some proportion of demand from peak period to lean period by offering the customers a reasonable rate of discount in the lean period. Of course, the cost/benefit analysis of this exercise has to be thoroughly examined beforehand. †¢ Journa l of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 75 Singh, Das †¢ Considering the lean periods of the airline in different routes and destinations, the top management needs to explore new destinations which may appear to be very attractive from the perspective of the customers.Accordingly the management can withdraw some of the flights from the existing underloaded routes and ply the same in the new routes. Alternatively the management needs to examine the passenger traffic data of different routes on monthly/quarterly basis. If it is found that during the same period, some destinations experience very high demand while others have low demand, the management may withdraw some of the flights from underutilized routes and introduce the same in the heavily loaded routes. †¢In all cases, the detailed cost/benefit analysis of different alternatives is to be thoroughly examined. Then a particular course of a strategy or a combination of strategies m ay be adopted by the management. CONCLUSION The present study has attempted to find out the quarterly forecasted demand of passenger traffic flow of Lufthansa Airlines by employing the four forecasting methods, viz. moving average, simple exponential smoothing, Holt's model and Winter's model. The forecasted data suggested by Winter's model reflect the historical pattern in a better manner than three other forecasting methods.This gives a valuable insight to the managers regarding formulation of appropriate strategies in order to absorb varying nature of demand in different quarters. The same kind of study can be replicated in other airlines with suitable modifications. Of course, the present work have not taken into consideration important factors, for example, the prevailing slowdown in the global economy, perceived security threat in the wake of terrorist strikes at different parts of the globe etc.Moreover, the study has considered the total passenger traffic movement of Lufthan sa as a whole and has not paid attention to an individual market segment. This may not provide a clear picture to the management regarding increase or decrease in traffic flow in a particular segment. Future study should take care of this aspect. Journal of Services Research, Volume 10, Number 2 (October 2010 – March 2011) 76 Forecasting the Passenger The implications of varying demand on supply side need to be thoroughly examined and accordingly suitable strategies should be adopted for improving the profit across the whole supply chain.REFERENCES Bicak, H. A. , Altinay, M. & Jenkins, H. (2005) ‘Forecasting tourism demand of North Cyprus', Journal of Hospitality and Leisure Marketing, Vol. 12, pp. 87-99. Chopra, S and Meindl, P (2007) Supply Chain Management: Strategy, Planning & Operation, 3rd edition, Pearson Education, New Delhi. Choo S. and Mokhtarian, P. L. (2007) ‘Telecommunications and travel demand and supply: Aggregate structural equation models for the US', Transportation Research Part A, 41 pp. 4 -18. Dennis, N. P. S. 2002) ‘Long-term forecasts and flight schedule pattern for a medium-sized European airport', Journal of Air Transport Management, Vol. 8, pp. 313-324. Dritsakis, N. and Athanasiadis, S. (2000) ‘An econometric model of tourist demand: The case of Greece', Journal of Hospitality and Leisure Marketing, Vol. 7, pp. 39-49. Hamzacebi, C. (2008) ‘Improving artificial neural networks' performance in seasonal time series forecasting', Information Sciences, Vol. 178, pp. 4550-4559. IATA International traffic statistics, 2008a, Facts & Figures – 2008 Traffic Results, Montreal, Quebec, viewed 30 November,