Tuesday, January 28, 2020

The Perception Of Nepal By Tourists Tourism Essay

The Perception Of Nepal By Tourists Tourism Essay Bounded by the lofty heights of the Himalayas, Nepal is a country of eternal beauty and attraction. It is a land of interesting cultures, ancient history and indigenous people, picturesque scenery and some of the greatest walking on earth. It is universally known for the highest mountain peak of the world, Mount Everest that stands tall at 8848 meters. Nepal tourism notifies about places to visit in Nepal, Lumbini; famous for the birthplace of Gautam Buddha who laid the foundation of Buddhism in the country. Having rich traditions of art, historical sites, customs, culture and heritage, Kathmandu, the capital city of Nepal is a treasure house of ancient art and culture. Different article, Books, international publication and organization has mentioned that, Nepal is one of the most visited travel destination in South Asia. A report published by Lonely Planet names top ten destinations for 2010, Nepal is one the best destination including El Salvador, Germany, Greece, Malaysia, Morocco, New Zealand, Portugal, Suriname and USA  [1]  . Similarly, Magazine Current Issue December 2009/ January 2010 published by BBC, National Geography, had searched 200 top-rated travel destinations of the world and selected the best 25 destinations for 2010. Nepal is one of the best destinations out of 25  [2]  . Reactions of residents concerning tourism Figure 3 shows a matrix representing the attitudes and behaviour of local residents of the region to tourism. The matrix is based on the framework developed by Bjorklund and Philbrick (1972) and applied to tourism (tourist-host relationship) by Butler (1980)  [3]  . The two dimensions of analysis are the attitudes of local residents towards tourism (positive negative) and their behavioural responses (active passive). Attitudes and reactions of individuals change in time, according to the process of tourism development in an area. Host Attitudinal/Behavioural Responses to Tourist Activities in the Region (% of the Population) Active Passive Positive 57.7 17.4 Negative 4.5 13.6 In the Khumbu, Pokhara (including Annapurna), Chitwan and Lumbini regions, the majority of residents (57%) actively support and promote tourist activities and tourism development in the region (mainly by running their own tourist businesses, but also by other means, e.g. learning languages in order to be able to communicate with tourists, or trekking with tourist in trekking routes). Besides, only 5% of them oppose actively further tourism development in the region (mainly for environmental reasons). The remaining 6.8% of the population have neither positive nor negative attitude toward tourism development. 10.1.1. Tourists and Motivations A tourist is a person who travels for various activities form origin to destination with some period. The movement could be inside the country or outside. Similarly, the people who travel and stay in places outside their usual environment for not more than consecutive year for leisure, business and other purposes not related to the exercise of an activities remunerated from within the place visited  [4]  http://www.traveletour.com/. Why do tourists visit certain places? By overlooking in academic approach given by Dann (1981)  [5]  , listed seven elements: Travel is a response to what is lacking yet desired. Destination pull, in response to motivation push Motivation as fantasy- behavior not culturally sanctioned at home Motivation typologies: a) behavioural, such as sun worshipping or wanderlust and, b) typologies focusing on dimensions of the tourist role Motivation as classified purposes Motivation and tourist experiences-includes the authenticity debate Motivation as auto-definition and meaning Similarly, McIntosh et al., 1995, utilize four categories of motivations, physical, cultural, interpersonal and status and prestige motivators. In the case of Nepal, generally all international visitors are clubbed under the category of tourists. However, these visitors-cum-tourists visit the country for various purposes ranging from pilgrimage to purely official purposes. All of them spend money while they are in Nepal; they are contributing to this Himalayan economy. Therefore, such range of visitors might be put under the category of tourists. Nepal government has classified the categories of tourists according to activities, like pleasure, trekking, mountaineering, adventure and cultural activities, natural or eco-tourism activates business, education, health etc. (Agrawal, 2005, Tourism and economic development in Nepal). Nepal is best destination for pleasure trip and adventure activities as well as natural and cultural tourism. It is followed by trekking and mountaineering. The two together accounted for around 90 Per Cent of the total tourists arrival before the nineties. Since, 1990 the average share has been around 80 Per Cent of the total. It is clear from the above data the major purposes of tourists in Nepal are pleasure, trekking, mountaineering and adventure activities before 1990. After that, new types of tourists also found in Nepal like cultural tourists (Pilgrimages), study and research, meetings and seminar, and health, since 1991 have shown growth rate of these types of tourist 8.22 and 9.12 per Cent of respectively. By the year of 2007 and 2008, largest number of tourists 41.4% tourists were visited for adventure activities and average length of stay in the country was recorded 12 days.(Source; calculated from several issues of economic survey, Ministry of finance, HMG/N) On the basis on empirical data, the motivations of tourists were different according to the study areas. Tourists in the mountainous region like Khumbu and Annapurna are interested on adventure activities. Similarly, tourists in Lumbini, Janakpur and Kathmandu valley are interested on cultural pilgrimages. Again, tourists in Chitwan are interested on natural activities. However, majority of tourists agree on, adventure activities. Trekking is the gift of Nepal to the world in adventure tourism. To be one with nature, to regenerate ones own self-esteem, to rediscover oneself, to appreciate Nepals beauty, to interact with its hospitable and friendly people are some of the highlights of trekking in Nepal. Trekking is one long-term activity that draws repeat visitors to the country. Possessing eight of the ten highest mountains in the world, Nepal is hotspot destination for mountaineers, rock climbers and people seeking adventure. Therefore, Nepal is the ultimate destinations for the trekking enthusiast. So these are the characteristics of Nepalese tourism, to attract us again and again. A German couple, who has visited Nepal more than seven times in Khumbu region. Well, Nepal is excellent destination for natural tourism, having highest mountain, varieties of biodiversity, and unique geographic structures are the major attraction for us. A group of tourist from USA in Chitwan Nepal has many unique cities for tourists like Kathmandu and Pokhara. Kathmandu valley is one of the oldest city with full of religious and cultural heritages, city of living God and Goddess and capital city of Nepal with full range of historic and artistic achievement. Therefore, Kathmandu Valley is world famous. The seven touristic areas (listed in world heritages by UNESCO), the Durbar Squares of Hanuman Dhoka (Kathmandu), Patan and Bhaktapur, the Buddhist stupas of Swayambhu and Bauddhanath and the Hindu temples of Pashupatinath and Changu Narayan. The Kathmandu is an exotic and fascinating showcase of a very rich culture, art and tradition. Again I am very much interested to know the Hindu and Buddhist society and culture; therefore I travel to Nepal frequently. A tourist nearby Kathmandu Durbar Square When I was in school, I read a book; Nepal is only one Hindu kingdom in the world, only one Hindu kingdom (no more now) For me it was interesting because I know many Christian and Muslim countries but not only one Hindu kingdom, so I have desire to visit Nepal form school level, and finally I am here now. A French tourist in Pashupatinath, Kathmandu Nepal is holy land for us, because this is the land, where Lord Buddha was born. We are happy to visit Nepal, especially Lumbini (the birth place of God Buddha). Around 60 tourists (in-group) from Sri Lanka in Lumbini Nepal is best destination for us because, God Pashupatinath, many Hindus temples, religions and cultures are attraction for us so, once a year we visit Nepal. A large number of Indian tourists in Kathmandu, and Janakpur The Mountains, landscape, and silence natural heritages are the god gifted monuments of Nepal, I love it and thats why I am here. A German scientist in Chitwan Therefore, according to empirical data, Nepal is the best destination for adventure activities like mountaineering, trekking, natural heritages and many more. Similarly, having majority of Hindus people and its related culture, tradition, temple and more phenomenon, and being the birth of God Buddha, Nepal is significance destination for cultural tourism too. 10.1.2. Major touristic destinations in Nepal Roof of the world, home of the Gurkhas, land of legend and beauty: within its narrow confines, Nepal contains as amazing range of culture and physical environments offers the visitor and abundance of contrasts and the experiences. A unique landscape unequalled in beauty and variety, cultural diversity, aesthetically built monuments, rugged beauty and tranquility of snowcapped shimmering mountains, serenity and placidness of the lakes and valleys, an unmatched collection of flora, fauna and wild life, diverse races, ethnic groups, dialects and languages all combine to make Nepal a visitors dream come true. Formally, It is also known as the Himalayas kingdom, possessing 8 of 10 heights mountain of the world, unique combination of Buddhism and Hinduism and its phenomenon are always attraction for tourists. Some of the major tourist destinations in Nepal are mountain regions; include the beautiful cities of Kathmandu, Bhaktapur, Patan, Pokhara and other sites. The places in Nepal are known for their various historic sites and sightseeing. Tourists must visit the Royal Chitwan National Park, Nagarjuna Forest Reserve, Pashupatinath, Dakhshina Kali and many more. Ashok Vyas (2004) Nepal Darshan, indicated, the main touristic areas of Nepal are mountain regions, particular khumbu and Annapuran followed by, Pokhara, Lumbini, Kathmandu Valley, Chitwan and Janakpur. Again, small amount of tourist were interested to visit different parts of the Country. On the basis on empirical data, the researcher came to know that, tourists indicated different destinations according to their interest. Western tourists were interested to visit mountain regions but Asians were interested to visit cultural sites. In general, Majority (80 out of 100 respondents), were interested to visit mountain areas like Khumbu and Annapurna and they were involved in adventure activities like mountaineering, trekking and rock climbing etc. In addition, 61 out of 100 tourists were interested to visit religious and cultural heritages like Lumbini, Kathmandu Valley and Janakpur. Similarly, 48 out of 100 respondents were interested to visit natural heritages; Chitwan and the Mt. Everest. However, both of them were interested (88 out of 100) to visit lovely city Pokhara. Figure 5.12 Fig. 5.12, major touristic areas of Nepal visited by tourists Source: Field Study Mountain Area= Khumbu and Annapurna Region, Pokhara= Holiday, recreation and adventure Cultural Sites= Kathmandu valley+ Lumbini+ Janakpur Natural Heritages= Chitwan and the Mt. Everest With the help of above empirical data, the researcher agreed on Nepal has been a best destination for adventure tourists. Similarly, pilgrimage (Cultural phenomenon) has been introducing a new kind of tourism destination in Nepal. Lumbini, the birthplace of Buddha, could be an important destination for Buddhist people. Besides there is a famous shrine of Lord Pashupatinath at the Kathmandu and many other Hindus monuments all over the country could be the attraction point for huge Indians. 10.1.3. Nepal, an economical (cheaper) destination Nepal is the poorest and least developed countries in the world. More than 45 Per Cent of people are under the poverty line. Agriculture is the pillar of the economy, providing a livelihood for majority of the population and accounting for 38% of GDP. The unemployment rate of country is more than 45 Per Cent in the year of 2008. The per capita income of the county by the year 2008 was $473. Asian Development Bank, 2008. The current situation of foreign exchange rate against euro is more than 100 Rupees. Moscow, the capital city of Russia, is the most expensive city for travelers, followed by Tokyo, Japan. There is not any city or place from South Asians countries, which is expensive for tourist (Source; www.travelersdigest.com, 2009-7-20). Nepal could be one of the cheap destinations for tourists, Upadhyay, Rudra (2006). On my personal experiences, Nepal is cheaper destination, because now I am in Namche Bazaar, 3,440 m, local residents said that this is an expensive place for tourist. However, I do not feel so; I am paying $ 20 for a hotel per day, 5 to 20 Dollars for food, which is normal for me. If I were in Switzerland, I have to pay huge amount of money. Tourist in Namche Bazaar, Khumbu Region Within few moments, I will be in the sky by Paraglide, I paid around 100 euro. But, in Switzerland I have to pay five to seven times more for same thing. A German tourist, in Sharankot, Pokhara When I was applying visa for Bhutan, I proved that I can spend more than 200 US Dollars a day; this is rule of Bhutan government. But, look in Nepal no condition like this. Again; I am spending less than 50 Dollars a day, which is enough for me. A tourist in Pokhara Similarly, the researcher collected data from tourist on Nepal visit and tourists budget. Majority of respondents (54 Per Cent) were reported, Nepal is cheaper destination followed by, 30 Per Cent; middle and rest 16 Per Cent reported expensive. Figure 5.14; Figure 5.14, Nepal visit and tourists budget. Source: field study Therefore, on the basis on empirical data, the researcher found that, Nepal is the cheaper destination for tourists. During the field study, the researcher asked to the tourists, what amount of money are you planning to spend in Nepal. Majority of respondents ( 38 Per Cent) were reported up to 2000 US dollars, followed by 35 Per Cent; 2000 to 3000and rest 27 Per Cent more than 3000 US dollar, Table 5.13. Table 5.14, Amount of money tourist wants to spend in Nepal Source; Field study Average length of stay of tourist is if on higher side they will spend more money. Thus, more money brought by international tourist would be pumped in the local economy. The average length of stay by a tourist during 1975-90 had been 11.87 days that declined marginally to 11.23 days in the following period of 1991 -2000 and around 12 days in 2008 and 2009  [6]  . However, during the data collection the researcher found variety of data. Fig. 5.13, Average length of stay Source: Field study In average, tourists were interested to stay in Nepal around 20 days. Based on the answers given by local people and tourist, it was found that majority of respondents 84 % (210 out of 250) reported that average length of stay of tourist in tourist areas was 20 days (Fig. 5.13). XI CHAPTER SUMMARY OF FINDINGS AND RECOMMEDATION Title: Page No. Overall review of the research 214 Summary of the findings 215 Recommendations 218 11.1. Overall review of the research Chapter 6 provides an overall review of the research aim, objectives, research questions, issues, findings, conclusions and recommendations of this study. Chapter 6 begins by summarizing the background to the research, and the research purpose, methodology and findings. The researcher goes on to make explicit the contribution of this study to the discipline of Socio-cultural and economic impact of tourism in the process of globalization in Nepal. Suggestions are made for future research based on the theme of this study. The chapter concludes with key recommendations for Socio-cultural and economic impact of tourism in the process of globalization in Nepal The present researcher has attempted to fine out, Socio-cultural and economic impact of tourism in the process of globalization in Nepal. It is divided in five major topics with subareas. The first topic is introduction. This chapter has included the introduction, theoretical concerns, hypothesis, aims and objectives, statements (importance), research methodology, and data sources and data analysis model of present research. The key aspect of this chapter is research issues. This research has three major issues: change in socio-economic setup of Nepal due to globalization and tourism; cultural globalization due to inflict of tourism but also due to globalization in general, and perception of Nepal by tourists. Under the first issue: socio-economic inequality, impact of tourism on Nepalese economy, development and change in touristic areas were the major points for analysis. Similarly in second; impact of global tourism on food, drinks, clothing, languages, family structure and everyday life; tourism and socio-cultural change in Nepal; types of globalization and homogenization adapting by Nepalese by tourist or tourism were major points. The last or final issue of this research was; important and interesting fact of Nepalese tourism for tourist was main phenomenon. Research methodology is another important subarea of this research. The nature of this research is qualitative cum quantitative (mixed approach). The study areas of this research were major six touristic places of Nepal Mt. Everest National Park (Sagarmatha), Pokhara with Annapurna area, Lumbini (The birthplace of Lord Buddha), Chitwan National Park, Janakpur and Kathmandu Valley including Lalitpur and Bhaktapur. The total numbers of interlocutors of this research were 250 including local people (40 Per Cent), Tourist (40 Per Cent) and jobholder in tourism (20 Per Cent). Questionnaires, interviews, observation, case study and discussion were used for data collection on August to December 2008 and October 2009 to January 2010. The data analysis has been performed by using computer software like Excel, SPSS one way ANOVA and T-Test according to their necessity. Chapter Two is the collection of theoretical literature review. This chapter has explained the all-important terms and variables of this research. Similarly, chapter Three is the detail explanation of culture, people, land and society of country of the great Himalayas (Nepal). Chapter Four covers complete data analysis of this research. This covers general demographic (Age, Gender and Education) information of the respondents: tourism, globalization and its impact on Nepali economy, society and culture with different subareas and perception of Nepal by tourist. Similarly, Chapter 5 includes the summary of findings and suggestions and end part includes references. In conclusion, tourism is not a new phenomenon in Nepal. The county has welcomed tourists officially since 1953. Tourism has been a significant pillar in the countrys economy and the government using for socio-economic development of rural areas in Nepal. It was the aim of this study to address the important issues related to tourism and impacts in Nepal. The focal point, how residents evaluate the economic, social and cultural impacts of tourism on their community was examined. The final section dealt with the perception of Nepal by tourists. 11.2. Summary of the findings Tourism is an important process of socio-economic and cultural globalization. It has both positive and negative impacts on society, economy and culture of destination. The truth is that tourism has become one of the largest and most rapidly growing industries in the world by combining social and economic activities. The industry fosters development and affects the people and the place. Impacts of tourism could be positive or negative according to the degree of planning and the level of involvement of local residents in the development process. The outcome is dependent on the relationship between the local residents and the site. On the basis on data, it has both positive and negative impacts according to places regards to the impact of global tourism. The people are in Khumbu, Annapurana, Chitwan, Jankapur and Lumbini believe that tourism does not contradict religion or traditional customs; they are of the opinion that it has no influences on their daily life or their patterns of consumption. However, the people from Kathmandu and Pokhara Valley are strongly addressed there is huge impact of tourism and tourists activities on local culture, society, traditions, food, languages and everyday life. However, in general all respondents fell that it could influences in food, language, clothes and younger generations more. Finally, residents believe that tourism could be a solution for unemployment, poverty, income, and socio-cultural changes. It was found that tourism plays the important role in the Nepalese economy. Tourism has playing quantifiable and positive effects on the development of GDP of the country. It has been increasing the economy of the country in general and as a whole. The increase in the volume of tourist flow has direct as well as indirect impact on the development process of Nepal. Nevertheless, tourism was found to be more capital investor and employer in Nepal In general, tourism has both positive and negative impacts, but majority of residents have a positive attitude toward tourism and they believe that it can develop their communities, like main source of income, job, poverty alleviation, source of foreign reserves and revenue, and national and local business. People involved in this profession have found better life compare to others. They have better opportunity of employment, income, education, quality of life and many more. However, the largest economic impacts of tourism are experienced by the residents near the Khumbu, Annapurna, Pokhara, Lumbini, Chitwan, Janakpur and some part of Kathmandu Valley, while people living in remote areas and in off-site of tourist areas or routes could not reap the benefits of tourism as they have very limited things to offer. Thus, this is clear, tourism increasing socio-economic inequality among the Nepalese. A side effect of residents expecting profits is that locals evaluate tourists according to their expenditures, potentially leading to negative attitudes and conflicts between residents and tourists and between the various social groups living within the local community. In addition, while tourism has the potential to introduce economic benefits for the government and the people. Normally tourism still has little impact on local society and culture. Participants report that tourism has less contradicted religion and traditions, while some of them expressed the fear of potential impact on younger generations. Such sentiments were centered near Khumbu and Annapurna, where the impact on society and culture are more present than in the other sites. Among the negative impacts reported in study, areas are; the consumption of alcohol, the imitation of tourist behaviour and sexual relations with tourists, increasing foreign food, dress, drug, language, gambling and unwanted lifestyle change. The positive impacts of tourism were especially highlighted by those working in tourism. Some reported that tourism is single source of their economic life, while others claim to have learned positive skills from tourists that improve their interaction with family members and in society. Similarly, for the Government tourism is an important pillar of national economy and best way to reduce poverty in rural areas of Nepal. Finally, tourism is an important transmitter of globalization in Nepal. It seems a process of acculturation or westernization or Americanization and leads globalised homogenous society and culture. Majority of respondents agreed on tourism and globalization develops globalized homogeneous culture but the same time Nepalese cultures are reconstructed on local levels. Tourists were found highly satisfied with weather, natural scenery, wild animals, peoples behavior, hospitality, friendliness, helpfulness humbleness, honest, welcoming attitude of the people, sense of remoteness and authenticity, religious customs, fulfillment of scene of adventure, historical sites, culture, entertainment, language communication, agency services and guide services. However, they were found to be less satisfied with immigration, transportation, airlines services, lodging, sightseeing tour, shopping facilities, tourist information service, regular strike (Nepal banda), tax, and food and drinks in Nepal. Again, they had realized the potential for further tourism development in Nepal. Having top mountains of the World, colorful cultures, ancient history and people, picturesque scenery, birthplace of Gautam Buddha, rich traditions of art, culture and heritage and one of the best destination for adventure activities; the country of great Himalayas (Nepal) is one of the best destination for tourism. The perceptions of tourist are found positive. Out of different attraction phenomenon, adventure activities and places are the main attraction for tourists followed by religion and culture. Majority of tourist are agreed on Nepal is the cheapest destination. Recommendations There is no doubt tourism is a means of globalization and have impact on society, culture and economy of the country. Tourism is the main way of globalization in different phenomenon like economy, culture and society of Nepal. Nepalese society, culture and economy have been suffering from various impact of tourism. Basis on the empirical data, the researcher have found following suggestions on this research. Tourism is an important process of socio-economic and cultural globalization. It has both positive and negative impacts on society, economy and culture of destination. Therefore, it is recommended that Nepalese should be aware from such impact. Tourism is seen as the means of development in rural areas of Nepal. Therefore, government and local people should use tourism as the development tools for rural Nepal. It is found that tourism has both positive and negative impacts on society and culture according to places. Some tourist areas have less impact and some have more. Therefore, Nepalese and government should implement proper programme to reduce negative impacts. The impact of tourism on the social system and culture of locals are diversity according to tourist hubs. Participants from Kathmandu, Pokhara and Chitwan reported that tourism contradict religion, tradition, social norms, local culture, society, food, language, clothes and may more related to social and culture phenomenon, while others from rest tourist hubs reported tourism does not contradict religion and tradition. But, from both places people, express the fear of the greater impact on the younger generation. Therefore, to protect from such evidence, it is necessary to give proper education or information to the Nepalese and special education or information to the younger generation. Majority of respondents have positive attitude of tourism and believe that it can develop their communities. Tourism is pillar, employer, poverty eliminator, source of foreign currencies, revenue, local business and capital investor of Nepalese economy but government is not giving proper importance in it. It is recommended that government should give priority for tourism development. Regarding to the role of tourism in globalization of economy Nepal has been found that the direct impact of tourism on earning foreign exchange has been improving. However, if it is analyzed with respect to merchandize trade, overall foreign exchange earnings in the economy the role of tourism has been increasing. The ratio of foreign exchange earnings from tourism and GDP has been increasing very slowly. Nepalese and government of Nepal should think on it. The foreign participation in the tourism industry remains confined to mainly hotel, resorts and restaurants. Therefore, government and people should encourage foreign investors to invest in new areas of activities related to tourism in Nepal. The residents near the tourist hubs of Nepal experience the largest economic impacts of tourism, where a large number of residents have become dependent on tourism, while in the other sites tourism still has no significant economic meaning. Therefore, in this situation economic benefit of tourism should be managed to the equal manner It is found that people in tourism have better living standard because they have better income. Only few Nepalese are involved in tourism therefore they are getting better quality of life and education but majority of Nepalese are in off-site, which is socio-economic inequality due to tourism. To promote the living standard of those people, who are off-site, government and Nepalese should focus balanced tourism development project and distribute appropriate income of tourism. Regarding employment in tourism, it was also found that tourism is not yet considered a plausible and appropriate employment opportunity by local jobseekers. Among the reasons are lacks of education and training centers, low wages paid to employees in tourism service, lack of insurance and job security, to a certain degree, the traditional and social values of the communities. Concerning education and training, the study identified that the authorities do not consider tourism to be a helpful means in dealing with the issues of human resources. This reflects the low priority given to education and training in tourism as an independent field of study, even when there is a project with a scheduled budget for training. Therefore, it is necessary to create positive attitudes towards tourism related job for this educational institution should be established. Total foreign exchange earnings of Nepal have been growing after introduction of tourism. Foreign investment has been increasing in tourism because it will be potential sources of return for them. However, this analysis shows that foreign investors were keen to invest in hotels, resorts and restaurants. Other activities could not attract foreign investors. Here lies the need to promote other activities rela

Sunday, January 19, 2020

Ancient Kemet :: World History

Ancient Kemet Egypt was without question the first great civilization in Africa. Surrounded by the hostile desert, Egypt arose as a populous settlement as a "gift of the Nile River," which flooded surrounding plains and thus supported game and wild plants. Straddling the strategic land crossroads between Africa, Asia, and Europe, Egypt also became a point for interchange between the Mediterranean and Red seas and the Persian Gulf. Many developments affecting the rest of Africa took place in or near the Nile Valley, such as the cultivation of plants and the development of metal smelting. Thus, Egypt's major role in forming early African civilizations has been well established. In modern times, scholars often underestimated the contributions of ancient Egypt to European civilization. More than two millennia ago, when the Ptolemaic Greeks came to rule Egypt, they extensively adopted and interpreted Egyptian spiritual, material, political, aesthetic, and intellectual systems. Although later Greek authorities freely acknowledged their cultural debt to Egypt, during the nineteenth century many European writers, limited by their ethnocentrism and racism, decided that black Africa could have had nothing to do with Europe's rise to greatness. Some treated Egypt as Middle Eastern and divorced it from the rest of Africa, whereas others went further, asserting the preeminence of northern Aryan sources of Greek civilization to the virtual exclusion of Semitic, African, and Egyptian influences. Beginning in ancient times, Egypt was a genuine crossroads of peoples and cultures, and its peoples were multiethnic and multiracial, as depicted in dynastic drawings of their rulers. They came from as far way as Asia Minor and Nubia, in the upper Nile Valley. Ancient Kemet :: World History Ancient Kemet Egypt was without question the first great civilization in Africa. Surrounded by the hostile desert, Egypt arose as a populous settlement as a "gift of the Nile River," which flooded surrounding plains and thus supported game and wild plants. Straddling the strategic land crossroads between Africa, Asia, and Europe, Egypt also became a point for interchange between the Mediterranean and Red seas and the Persian Gulf. Many developments affecting the rest of Africa took place in or near the Nile Valley, such as the cultivation of plants and the development of metal smelting. Thus, Egypt's major role in forming early African civilizations has been well established. In modern times, scholars often underestimated the contributions of ancient Egypt to European civilization. More than two millennia ago, when the Ptolemaic Greeks came to rule Egypt, they extensively adopted and interpreted Egyptian spiritual, material, political, aesthetic, and intellectual systems. Although later Greek authorities freely acknowledged their cultural debt to Egypt, during the nineteenth century many European writers, limited by their ethnocentrism and racism, decided that black Africa could have had nothing to do with Europe's rise to greatness. Some treated Egypt as Middle Eastern and divorced it from the rest of Africa, whereas others went further, asserting the preeminence of northern Aryan sources of Greek civilization to the virtual exclusion of Semitic, African, and Egyptian influences. Beginning in ancient times, Egypt was a genuine crossroads of peoples and cultures, and its peoples were multiethnic and multiracial, as depicted in dynastic drawings of their rulers. They came from as far way as Asia Minor and Nubia, in the upper Nile Valley.

Saturday, January 11, 2020

Demand Forecasting and Production Planning

ScienceAsia 27 (2001) : 271-278 Demand Forecasting and Production Planning for Highly Seasonal Demand Situations: Case Study of a Pressure Container Factory Pisal Yenradeea,*, Anulark Pinnoib and Amnaj Charoenthavornyingb a Industrial Engineering Program, Sirindhorn International Institute of Technology, Thammasat University, Patumtani 12121, Thailand. b Industrial Systems Engineering Program, School of Advanced Technologies, Asian Institute of Technology, P. O. Box 4, Klong Luang, Patumtani 12120, Thailand. * Corresponding author, E-mail: [email  protected] tu. ac. th Received 24 May 2001 Accepted 27 Jul 2001 ABSTRACT This paper addresses demand forecasting and production planning for a pressure container factory in Thailand, where the demand patterns of individual product groups are highly seasonal. Three forecasting models, namely, Winter’s, decomposition, and Auto-Regressive Integrated Moving Average (ARIMA), are applied to forecast the product demands. The results are compared with those obtained by subjective and intuitive judgements (which is the current practice). It is found that the decomposition and ARIMA models provide lower forecast errors in all product groups. As a result, the safety stock calculated based on the errors of these two models is considerably less than that of the current practice. The forecasted demand and safety stock are subsequently used as inputs to determine the production plan that minimizes the total overtime and inventory holding costs based on a fixed workforce level and an available overtime. The production planning problem is formulated as a linear programming model whose decision variables include production quantities, inventory levels, and overtime requirements. The results reveal that the total costs could be reduced by 13. % when appropriate forecasting models are applied in place of the current practice. KEYWORDS: demand forecasting, highly seasonal demand, ARIMA method, production planning, linear programming, pressure container factory. INTRODUCTION Most manufacturing companies in developing countries determine product demand forecasts and production plans using subjective and intuitive judgments. This may be one factor that leads to production inefficiency. An accuracy of the demand forecast significantly affects safety stock and inventory levels, inventory holding costs, and customer service levels. When the demand is highly seasonal, it is unlikely that an accurate forecast can be obtained without the use of an appropriate forecasting model. The demand forecast is one among several critical inputs of a production planning process. When the forecast is inaccurate, the obtained production plan will be unreliable, and may result in over- or understock problems. To avoid them, a suitable amount of safety stock must be provided, which requires additional investment in inventory and results in an increased inventory holding costs. In order to solve the above-mentioned problems, systematic demand forecasting and production planning methods are proposed in this paper. A case study of a pressure container factory in Thailand is presented to demonstrate how the methods can be developed and implemented. This study illustrates that an improvement of demand forecasts and a reduction of total production costs can be achieved when the systematic demand forecasting and production planning methods are applied. The demand forecasting and production planning methods are proposed in the next section. The background of the case study, including, products, production process, and the forecasting and production planning procedures being used in the factory, are briefly described in Section 3. The detailed analyses of the forecasting methods and the production planning method are explained in Section 4 and Section 5, respectively. Finally, the discussion and conclusion are presented in Section 6. 272 ScienceAsia 27 (2001) P ROPOSED D EMAND F ORECASTING PRODUCTION PLANNING METHODS AND The proposed demand forecasting and production planning methods are depicted in a step-by-step fashion in Fig. . Most factories produce a variety of products that can be categorized into product groups or families. Individual products in the same product group generally have some common characteristics. For example, they may have the same demand pattern and a relatively stable product mix. As a result, it is possible to forecast the aggregate demand of the product group first, and then disaggregate it in to the demand of individual products. Since the forecast of the aggregate demand is more accurate than that of the individual demand1, it is initially determined in Step 1. Then the demands of individual products are determined in Step 2 by multiplying the aggregate demand with the corresponding product mix that is normally known and quite constant. Since the demand forecasts are always subject to forecast errors, safety stocks are provided to avoid stock-out problems. Based on the standard deviation of the forecast errors and the required service level, the safety stocks for individual products are determined in Step 3. Production planning decisions are so complicated and important that they should not be subjectively and intuitively made. Consequently, an appropriate production planning model should be formulated to determine the optimal decisions. With this model, its parameters, eg, demand forecasts, safety stocks, holding cost, overtime cost, machine capacity, inventory capacity, and available regular time and overtime, are entered or updated (Step 4). In step 5, the optimal decisions regarding the production quantities, inventory levels, and regular production time and overtime for each product in each production stage are obtained by solving the production planning model. Step 6 indicates that only the optimal production plan of the current month will be implemented. After one month has elapsed, the demand forecasts and the production plan will be revised (by repeating Steps 1 to 5) according to a rolling horizon concept. BACKGROUND OF THE CASE STUDY The pressure container factory manufactures 15 products, ranging from 1. 25 to 50 kg of the capacity of pressurized gas. The products are divided into eight product groups, namely, Group 1 to Group 8. The first six groups have only two components, â€Å"head† and â€Å"bottom†, while the last two groups have three components, â€Å"head†, â€Å"bottom†, and â€Å"body†. The production process can be divided into five stages as shown in Fig. 2. Stage 3 is only required to produce the products having three components (ie, those in Groups 7 and 8). Stage 4, the circumference welding, is found to be a bottleneck stage due to its long processing time. Presently monthly demand forecasts are subjectively determined by the Marketing Department based on past sales and expected future market conditions. No systematic method is used in forecasting. Using these forecasts and other constraints, such as availability of raw materials, equipment, and production capacity, the monthly production plan for a three-month period is intuitively determined without considering any cost factor. This results in inaccurate demand forecasts and, subsequently, an inefficient production plan. Stage 1 Blanking 1) Forecast the monthly demands of each product group throughout the planning horizon of 12 months 2) Determine the demand for each individual product 3) Determine the safety stock for each individual product Stage 2 Forming of bottom and head Stage 3 Forming of body 4) Update the parameters in the production planning model Stage 4 Circumference welding 5) Run the planning model to obtain the optimal planning dicisions ) Roll the plan by repeating Steps 1 to 5 after one month has elapsed Stage 5 Finishing Fig 1. Proposed forecasting and planning steps. Fig 2. The production process to manufacture a pressure container. ScienceAsia 27 (2001) 273 FORECASTING METHODS Steps 1, 2, and 3 of the proposed forecasting and planning process are discussed in detail in this section. Firstly, the aggregate demand forecasts of eight product groups throughout the planning horizon of 12 mont hs will be determined. Secondly, the demand forecasts of the product groups will be disaggregated into those of individual product. Thirdly, the safety stocks of individual product will be calculated based on the forecast error. Aggregate Demand Forecasts of Product Groups The typical demand pattern of each product group is seasonal. As an example, Fig. 3 shows the demand pattern of Product Group 3. Thus, three forecasting models that are suitable for making seasonal demand forecasts are considered. They are Winter’s, decomposition and Auto-Regressive Integrated Moving Average (ARIMA) models. 2-5 Because of their simplicity, the Winter’s and decomposition models are initially used to forecast the aggregate demand of each product group. If the Winter’s and decomposition models are inadequate (ie, the forecast errors are not random), the ARIMA model which is more complicated and perhaps more efficient will be applied. The Winter’s model has three smoothing parameters that significantly affect the accuracy of the forecasts. These parameters are varied at many levels using a computer program to determine a set of parameters that give the least forecast errors. There are two types of the decomposition model, namely, multiplicative and additive types. The former is selected since the demand pattern shows that the trend and seasonal components are dependent. The forecast errors of the Winter’s and decomposition models are presented in Table 1. Based on the calculated mean square error (MSE) and the mean absolute percentage error (MAPE), it is seen that the decomposition model has lower Original Series (x 1000) 16 forecast errors in all product groups than the Winter’s model. Thus, it is reasonable to conclude that the decomposition model provides better demand forecasts than the other. One way to check whether the forecasting model is adequate is to evaluate the randomness of the forecast errors. The auto-correlation coefficient functions (ACFs) of the errors from the decomposition model for several time lags at the significant level of 0. 05 of each product group are determined. The ACFs of Groups 1 and 3 are presented as examples in Fig. 4 and 5, respectively. The ACFs of Groups 4, 5, 6, 7, and 8 are similar to those of Group 1 in Table 1. Forecast errors of the Winter’s and decomposition models. MSE Products MAPE (%) Winter’s Decomposition Winter’s Decomposition 9,879,330 4,363,290 2,227,592 4,507,990 10,039,690 574,108 636,755 883,811 36. 14 48. 94 24. 25 30. 08 18. 80 53. 86 61. 99 46. 52 26. 97 31. 86 15. 97 23. 4 13. 14 34. 80 34. 45 28. 76 Group 1 16,855,149 Group 2 8,485,892 Group 3 5,433,666 Group 4 6,035,466 Group 5 23,030,657 Group 6 1,690,763 Group 7 2,034,917 Group 8 1,884,353 Estimated Autocorrelations 1 0. 5 coefficient 0 -0. 5 -1 0 4 8 lag 12 16 20 Fig 4. ACFs of the residuals from the decomposition model for Group 1. Estimated Autocorrel ations 1 0. 5 16 demand 3 coefficient 0 8 -0. 5 4 -1 0 0 10 20 30 time index 40 50 60 0 4 8 lag 12 16 20 Fig 3. Actual demand of Group 3. Fig 5. ACFs of the residuals from the decomposition model for Group 3. 274 ScienceAsia 27 (2001) Fig 4, while those of Groups 2 and 3 are similar. It can be seen from Fig. 4 that the ACFs of all lags are within the upper and lower limits, meaning that the errors are random. However, the ACF of lag 1 in Fig. 5 exceeds the upper limit. This indicates that auto-correlations do exist in the errors and that the errors are not random. From the ACFs, we can conclude that the decomposition model is adequate for forecasting the demands of Groups 1, 4, 5, 6, 7, and 8, but inadequate for forecasting those of Groups 2 and 3. Therefore, the ARIMA model is applied to Groups 2 and 3. From the original time series of the demand of Group 3 (in Fig. 3), and the ACFs of its original series (in Fig. ), it can be interpreted that the original series has a trend, and a high value of ACF of lag 12 indicates the existence of seasonality. 2 Hence, a non-seasonal first-difference to remove the trend and a seasonal first-difference to remove the strong seasonal spikes in the ACFs are tested. Fig. 7 shows the ACFs of the ARIMA (p,1,q)(P,1,Q) 12 model afte r applying the first difference. The nonseasonal plot indicates that there is an exponential decay and one significant ACF of lag 2. Thus, the AR(1) and MA(1) process denoted by ARIMA (1,1,1)(0,1,0)12 is identified. The ACFs of the residuals after applying this ARIMA model shown in Fig. reveals that there is a high value of ACF of lag 12. Therefore, the AR(1) and MA(1) process for the seasonal part or ARIMA (1,1,1)(1,1,1)12 can be identified. The ACFs of the residuals generated from this model are shown in Fig. 9. Since all ACFs are within the two significant limits, the ARIMA (1,1,1)(1,1,1)12 model is adequate. Using the Statgraphic program, the model coefficients can be determined. The demand forecast for Group 3 is presented in Eq. 1. Ft = 1. 197 X t ? 1 ? 0. 197 X t ? 2 + 0. 54408 X t ? 12 ? 0. 65126 X t ? 13 + 0. 10718 X t ? 14 + 0. 45592 X t ? 24 ? 0. 54574 X t ? 25 + 0. 08982 X t ? 26 ? 1. 6699et ? 1 ? 0. 7154et ? 12 + 0. 76332et ? 13 + 29. 34781 (1) where Ft is the demand fo recast for period t Xt is the actual demand for period t et is the forecast error for period t Similarly, the forecasting model for Group 2 is ARIMA (3,0,0)(3,0,0). 12 The demand forecast of Group 2 is presented in Eq. 2. Estimated Autocorrelations for Original Series 1 Estimated Residual ACF 1 0. 5 0. 5 coefficient coefficient 0 0 -0. 5 -0. 5 -1 0 5 10 lag 15 20 25 -1 0 5 10 lag 15 20 25 Fig 6. ACFs of the actual demand for Group 3. Fig 8. ACFs of the residuals of ARIMA (1,1,1)(0,1,0)12 model for Group 3. Estimated Residual ACF 1 Estimated Autocorrelations for 1 Nonseasonal Differences 1 Seasonal Differences 1 0. 5 0. 5 coefficient coefficient 0 0 -0. 5 -0. 5 -1 0 5 10 lag 15 20 25 -1 0 5 10 lag 15 20 25 Fig 7. ACFs after first differencing for Group 3. Fig 9. ACFs of the residuals of ARIMA (1,1,1)(1,1,1)12 model for Group 3. ScienceAsia 27 (2001) 275 Ft = 0. 36951X t? 1 + 0. 30695X t? 2 – 0. 18213X t? 3 + 0. 20132 X t? 12 ? 0. 07439 X t? 13 ? 0. 06180 X 14 + 0. 03667 X t? 15 ? 0. 03325X t? 24 + 0. 01228 X t? 25 + 0. 01021X t? 26 ? 0. 00606 X t? 27 + 0. 68660 X t? 36 ? 0. 25371X t? 37 ? 0. 21075X t? 38 + 0. 12505X t? 39 + 354. 4515 2) The forecast errors of the decomposition and ARIMA models for Groups 2 and 3 are presented in Table 2. It reveals that the ARIMA model has lower Table 2. Forecast errors of the decomposition and ARIMA models. MSE Products Group 2 Group 3 Decomposition ARIMA 4,363,290 2,227,592 3,112,974 1,235,788 MAPE (%) Decomposition ARIMA 31. 86 15. 97 29. 05 13. 18 MSE and MAPE than t he decomposition model. Therefore, the ARIMA model should be used to forecast the aggregate demands of Groups 2 and 3. For other product groups, however, the decomposition model should be used because it is more simple yet still adequate. The comparison of the demand forecast errors obtained from the forecasting models and those from the current practice of the marketing department (as presented in Table 3) indicates that the errors of the forecasting models are substantially lower than those of the current practice. Demand Forecasts of Individual Products The demand forecast of product i for period t, dit, is obtained by multiplying the aggregate demand forecast of the product group (obtained from the previous steps) by the corresponding product mix (as presented in Table 4). Table 3. Forecast errors of the current practice, decomposition, and ARIMA models. MSE Product Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Group 8 Current practice Decomposition 16,672,342 4,394,693 4,988,962 4,754,572 19,787,102 795,621 849,420 1,060,301 9,879,330 4,507,990 10,039,690 574,108 636,755 883,811 ARIMA 3,112,974 1,235,788 MAPE (%) Current practice Decomposition 30. 58 34. 68 23. 50 25. 73 17. 54 42. 70 38. 36 37. 93 26. 97 23. 24 13. 14 34. 80 34. 45 28. 76 ARIMA 29. 05 13. 18 – Table 4. Product mix. Product group Product 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1 0. 17 0. 20 0. 26 0. 23 0. 14 1. 0 0. 53 0. 47 0. 65 0. 35 1. 0 1. 0 1. 0. 3 0. 7 2 3 4 5 6 7 8 276 ScienceAsia 27 (2001) Calculation of Safety Stock The safety stocks of finished products must be provided to protect against stock-out problems due to inaccurate demand forecasts. Based on the forecast errors obtained from the demand forecasting models, the amount of the safety stock is calculated using the following formula. 12 SSit = sf * ? j * ? ij (3) PRODUCTION PLANNING METHO D The production planning model is developed by initially defining decision variables and parameters, and then mathematically formulating the production planning model. Step 4 of the method requires that the model parameters be estimated and entered into the model. The model is solved for the optimal solution (Step 5). Step 6 recommends that the model parameters are updated, and the model is solved again after one planning period has passed. The production planning problem of the factory under consideration belongs to the class of multistage, multi-item, capacitated production planning model. The models in this class have been discussed extensively in. 6-11 They differ in assumptions, objectives, constraints, and solution methods. Our production planning model is a modification of the multi-stage, multi-product model discussed in Johnson and Montgomery. 6 Its objective is to minimize the total overtime and inventory holding costs. Costs of laying off and rehiring are not considered because laying off and rehiring are not allowed according to the labor union regulation. Since the production cost is time-invariant and all demands must be satisfied, the regular time production cost is thus not included in the objective function. Relevant parameters and decision variables are defined as follows: Parameters : hik = Holding cost per unit of product i at stage k (baht/unit/period) co = Cost per man-hour of overtime labor (baht/man-hour) dit = Demand forecast of product i for period t (units) aik = Processing time for one unit of product i at stage k (hours/unit) (rm)kt = Total available regular time excluding preventive maintenance and festival days at stage k for period t (man-hours) (om)kt = Total available overtime excluding preventive maintenance and festival days at stage k for period t (man-hours) W = Warehouse capacity (units) SSit = Safety stock of product i for period t (units) Iik0 = Initial inventory of product i at stage k (units) N = Total number of products (15 products) T = Total number of periods in the planning horizon (12 periods) K = Total number of stages (5 stages) where SSit = Required safety stock level of product i for period t sf = Safety factor = 1. 64 for a required service level of 95 % of the standard normal distribution ? j = Standard deviation of forecast errors of Group j. ?ij = Product mix of Product i in Group j. Since the errors of the recommended demand forecasting models are lower than those of the current practice, it is clear that SSit based on the use of the models must be lower than that determined from the current practice (assuming that the service levels of both cases are the same). Table 5 presents the required safety stocks of the current practice and the recommended forecasting models at 95 % service level. Table 5. Required safety stock of current practice and of recommended forecasting models. Safety stock (units) Product 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Current practice 1,138 1,339 1,741 1,540 937 3,438 1,941 1,722 2,324 1,252 7,295 1,463 1,511 507 1,182 Recommended forecasting models 887 1,043 1,356 1,200 730 2,905 979 868 2,274 1,224 5,258 1,245 1,323 460 1,072 ScienceAsia 27 (2001) 277 Decision variables: Xikt = Quantity of product i to be produced at stage k in period t (units) Iikt = Inventory of product i at stage k at the end of period t (units) Rkt = Regular time used at stage k during period t (man-hours) Okt = Overtime used at stage k during period t (man-hours) LP model: Minimize Z = ? ? ? hik Iikt + ? ? co Okt , (4) i =1 k =1 t =1 k =1 t =1 N K T K T Eq. 7 represents the material balance constraint in Stage 3, which produces the body of threecomponent products, for Products 13, 14, and 15. Constraint (13) must be included since the finished products are very bulky and require significant warehouse space that is quite limited. Work-inprocess inventory does not require significant storage space because it can be stacked. The non-negativity constraint (16) ensures that shortages of work-inprocess inventory do not occur. Input Parameters The initial inventory of product i at stage k, Iik0, is collected from real data of work-in-process or finished good inventories on the factory floor at the beginning of the planning horizon. The inventory holding cost of product i at stage k, hik, is estimated by assuming that the annual inventory holding cost is 25% of the cost per unit of the product at the respective production stage. Since the cost per unit is constant over the planning horizon, the annual inventory holding cost is time-invariant. The factory has enough space in the warehouse to store not more than 40,000 units of finished products. The total available regular time, (rm)kt, is estimated based on the fact that the factory is normally operated 16 hours a day and six days a week, and the total available overtime, (om)kt, is calculated by assuming that the overtime could not be more than six hours a day. The overtime cost, co, is assumed to be constant throughout the planning horizon, and is estimated to be 60 Baht per man-hour. After all related parameters have been estimated and entered into the planning model, the optimal values of all decision variables are calculated using the LINGO software. The computation time takes less than one minute on a Pentium PC. Results of the Production Planning Models with Different Levels of Safety Stock In this section, two production planning models with different safety stock levels (as shown in Table 5) are solved to determine the total cost savings when the recommended forecasting models are applied in place of the current practice. The inventory holding, overtime, and total costs of both models are presented in Table 6. Based on the optimal total cost of the current practice (4,078,746 Baht per year) and the optimal total cost of the recommended forecasting models (3,541,772 Baht per year), the total cost saving is 536,974 Baht per year, or 13. 2 %. It can be also seen Subject to – Finished product requirement constraints I i 5,t? 1 + X i 5t ? I i 5t = dit – ? i, t ; k = 5, (5) Material balance between stages constraints ? i, t ; k = 4, (6) (7) ? i, t ; k = 2, (8) ? i, t ; k = 1, (9) I i 4 ,t? 1 + X i 4 t ? I i 4 t = X i 5t I i 3,t? 1 + X i 3t ? I i 3t = X i 4 t ?t ; i = 13, 14, 15; k = 3, I i 2,t? 1 + X i 2t ? I i 2t = X i 4 t I i1,t? 1 + X i1t ? I i1t = X i 2t Capacity constraints ? aik X ikt ? Rkt + Okt i= 1 N ?k , t , (10) – Available regular and overtime constraints. Rkt ? (rm) kt Okt ? ( om) kt ?k , t , ? k , t , (11) (12) – Inventory capacity of finished product constraints. ? I ikt ? W i= 1 N ?t ; k = 5, (13) – Safety stock of finished product constraints. I ikt ? SS it ?i, t ; k = 5, (14) – Non-negativity conditions X ikt ? 0 I ikt ? 0 ?i, k , t , ? i, t ; k = 1, 2, 3, 4 (15) (16) 278 ScienceAsia 27 (2001) Table 6. Comparison of the optimal costs of production planning models. Optimal costs (Baht/year) Model based on the current practice Inventory holding cost Overtime cost Total cost 2,117,051 1,961,695 4,078,746 Model based on recommended forecasting models 1,775,552 1,766,220 3,541,772 REFERENCES 1. Nahmias S (1993) Production and Operations Analysis, 2nd ed, Irwin, New York. 2. Vandaele W (1983) Applied Time Series and Box-Jenkins Models, Academic Press, New York. 3. Winters PR (1960) Forecasting Sales by Exponentially Weighted Moving Average. Management Science 6(4), 324-42. 4. Box GE and Jenkins GM (1970) Time Series Analysis, Forecasting, and Control, Holden-Day, San Francisco. 5. Makridakis S Wheelwright SC and McGee VE (1983) Forecasting Methods and Applications, 2nd ed, John Wiley & Sons, New York. 6. Johnson LA and Montgomery DC (1974) Operations Research in Production Planning, Scheduling, and Inventory Control, John Wiley & Sons, New York. 7. Bullington P McClain J and Thomas J (1983) Mathematical Programming Approaches to Capacity Constrained MRP Systems: Review, Formulation, and Problem Reduction. Management Science 29(10). 8. Gabbay H (1979) Multi-Stage Production Planning. Management Science 25(11), 1138-48. 9. Zahorik A Thomas J and Trigeiro W (1984) Network Programming Models for Production Scheduling in MultiStage, Multi-Item Capacitated Systems. Management Science 30(3), 308-25. 10. Lanzanuer V (1970) Production and Employment Scheduling in Multi-Stage Production Systems. Naval Research Logistics Quarterly 17(2), 193-8. 11. Schwarz LB (ed) (1981) Multi-level Production and Inventory Control Systems: Theory and Practice, North-Holland, New York. 12. Tersine RJ (1994) Principles of Inventory and Materials Management, 4th ed, Prentice Hall, New Jersey. that the optimal inventory holding cost and overtime cost in the production planning model based on the recommended forecasting models are almost equal which indicates that the model can efficiently achieve a tradeoff between both costs. Normally, the optimal decisions in the first planning period will be implemented. After the first period has passed, the new forecasts will be determined, and the model parameters will be updated. The updated model is solved again to determine the optimal decisions in the current period. This is called a rolling horizon concept. However, the details and results of this step are not shown in this paper. DISCUSSION AND CONCLUSION The ARIMA model provides more reliable demand forecasts but it is more complicated to apply than the decomposition model. Therefore the ARIMA model should be used only when the decomposition model is inadequate. When compared against those of the current practice of the company, the errors of our selected models are considerably lower. This situation can lead to substantial reductions in safety stocks. Consequently, the lower safety stocks result in decreased inventory holding and overtime costs. The results of the production planning model are of great value to the company since the model can determine the optimal overtime work, production quantities, and inventory levels that yield the optimal total overtime and holding costs. The production planning method is more suitable than the existing one that does not consider any cost factors. Moreover, it has been proven that an application of appropriate forecasting techniques can reduce total inventory holding and overtime costs significantly. In conclusion, this paper demonstrates that an improvement in demand forecasting and production planning can be achieved by replacing subjective and intuitive judgments by the systematic methods.

Friday, January 3, 2020

Taking a Look at the Asian American Fraternity - 1093 Words

Social Welfare The mid-19th century marked a horrid period in the American racism history. This period is often referred to with a lot of in-depth racial discrimination as well as oppression. Additionally, it is in these periods that terms such as ‘Yellow peril were coined (Greenberg, Edward Benjamin 66). The term was used by white nativist with reference by to Asians. On the contrary, it is often thought that if the perilous group of the foreigners were allowed to continue with their stay, there would have been a significant continuation of foreign cultures as well as unassailable traits. Additionally, there are various studies that have been out with regard to during the despicable period. Various races have been analyzed by a number of scholars, particularly their association with the white organizations. It is particularly noted that racism was associated with low positive impact on the victim race members. The various research results claimed that majorly the white society lead into increase in immoral behavior which stalled development issues. The black community was perceived to promote alcohol abuse, negative effects on education performance as well as depraved behavior. In contrast, Blacks organization existed on the horrific areas where racial discrimination was at its optimum. Mostly it could be found in institutional surrounding like university. However these organizations were for the good. They helped in peer counseling, development in leadership and mostShow MoreRelatedThe Blindside1532 Words   |  7 Pageschildren spend a lot of their free time watchi ng TV, and certain programs may affect their racial attitudes. The article Mass Media And Racism asserts, â€Å"Mass Media has played and will continue to play a crucial role in the way white Americans perceive African-Americans† (Mass Media and Racism). 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