Compare And Contrast Piaget And Vygotsky Education Essay

Compare And Contrast Piaget And Vygotsky Education Essay Research into the way a person learns can be explained by looking at the psychological perspective. Cognitive development is concern with the ways in which childrens thinking develops in stages of life to adulthood. One of the most well known researches that can be applied to today is Piaget. This can be compared and contrast to Vygotskys theory however it can contradict against behaviourlist psychologist who say childs knowledge is due to reinforcement or punishment. This essay will compare and contrast Piaget to Vygotsky and the application it has to education, with reference to strength and weaknesses. Piaget was a Swiss psychologist who provided a highly influential theory of cognitive development. Piaget was struck by the fact that younger children gave different answers than other children, not because they were less intelligent but because they were interpreting the questions differently. Piaget saw children as scientists, and the believed they should learn by themselves. Piaget believed that the childs knowledge of the world is organised into schemas, structured patterns of knowledge and action. From birth the child has action schemas, enabling the child to know the world through acting upon it. During the 2nd year, the child begins to think about actions, and mental schemas develop. At all times, the child is motivated to keep their schemas organised, to incorporate new experiences into existing schemas, and to develop new schemas. Piaget considers we are innately programmed to adapt to our environment. Piaget used the term adaptation, to refer to the way the child learns as a result to their encounters and interactions with their environment. Adaptation takes 2 possible forms, Assimilation; this is when the child learns something that readily slots into their existing schemas. Accommodation is when the child has to change their existing schemas in order to take in a new experience. A schema allows an individual to make sense of the world as scheme are experiences, memory and information. This shows that cognitive development in a child is the process of revising knowledge to fit the ideas into this world. Another important point in Piagets theory is the existence of a third functional invariant called equilibration to keep the whole system in balance. Any changes in any part of the system will cause imbalance or disequilibrium. Equilibration keeps assimilation and accommodation in balance. Piaget developed a model of self regulating interaction which showed a link between the natu re of the physical and social environment with the childs cognitive structure. Piagets view is that cognitive development happens in stages, and at each stage the child recognises the way they think. Piaget identified 4 stages of cognitive development. Stage 1 is the sensorimotor stage from birth to 2 years. This is when the child knows the world initially through sensation and action. Piaget studied the sensorimotor phase by observing his own children. There are 2 principle features of this stage. First, those children develop object permanence, the realisation that objects exist permanently even when the child cannot see them. Second, is action schemas, by which the child knows the world through sensation and action, are supplemented and superseded by mental representations. Piaget divided the sensorimotor phase into 6 sub-stages. However, not everyone agreed with Piagets claim about object permanence. Bower (1981) showed that if an object disappeared behind a screen and then the screen was lifted, babies as young as 5 months would show surprise if the object was not there. This suggests that they did except the object to be there. However, the issue is not so much at what age these changes occur, but that they could occur and Bowers evidence merely suggests that Piaget may have underestimated what infants could do. The pre-operational stage (2-7 years) is when the children understand the world through visual appearances and non-logical assumption. From the age of about 2 years, children have mental schemas and can symbolise objects and actions in the mind as representational thought. Thought can be expressed through fantasy, play, language and drawing. Piaget divided the pre-operational Piaget divided the pre-operational stage into 2 sub stages, the preconception stage- from 2-4 years and the intuitive stage- from 4-7 years. In the pre-conceptual phase, childrens grasp of concepts is vague. They may, for example, think that if a dog is small enough it becomes a cat. Egocentrism is perhaps the most serious limitation in pre-operational childrens thinking. Typically, preoperational children said that the scene would look just the same as from their own viewpoint The next stage is the concrete operational stage (7-11 years), the child develops a degree of logic and reason, but is limited to practical problems and specific examples. Children develop mental operations Egocentrism is left behind, children become decentred, and they master principles of classification and class inclusion, and eventually full conversation of volume, number and quality. Their understanding of the world is fact-based and practical rather than theoretical. The last stage is the formal operational stage (11 years), the child achieves mature thinking and is capable of abstract theorising and scientific reasoning therefore they are fully developed by the age of 15. Formal operational adolescents are scientific in their thinking, use abstract logical reasoning and theorising, make hypotheses and test them systematically, and deduce conclusions from premises. At this stage, language plays an important role in thinking, and this means that instruction can play a more direct role than in earlier stages. There are weaknesses to this theory. Piaget underestimated the age at which children could so things- this may be because he failed to distinguish between competence (what a child is capable of doing) and performance (how a child performs on a particular task). Piagets studies tested performance and then he assumed that a child who failed simply lacked underlying cognitive structures, that he believed were needed to succeed on that task. Piaget underplayed the role of language and social factors in cognitive development. In an earlier experiment she found that children who were non-conservers differed in terms of the language they used from children classed as conservers. Non-conservers mainly used absolute rather than comparative terms and single term for different dimensions such as small to mean short, thin, or few. These findings suggest that cognitive and linguistic development is tied together, but which comes first despite many shortcomings, the strengths of Piagets approach and theory should not be overlooked. Piaget produced the first comprehensive theory of childrens cognitive development. The theory has been more extensively developed than any other. It has changed our ideas about children and has had a general influence on educational practice. Like all good theories, it has also generated research. Vygotsky development is a social process which contributes to the cognitive development through social interaction. Vygotsky (1935- 1978) through social interactions with more experienced and knowledgeable member of society parent, teacherà ¢Ã¢â€š ¬Ã‚ ¦- children are able to acquire the knowledge and skills that culture deems to be important. Vygotsky believed that culture teach people how to think as well as what to think as he put a lot of emphasis on practical way of learn and remembering. He used the expression zone of proximal development (ZPD) to express the area between the level of performance a child can learn alone and of which the child can achieve with someone with knowledges help. Vygotsky believed that children cannot be accelerated beyond this zone. Therefore children learn little when left alone to struggle but neither do they learn when someone takes over their task. The term scaffolding can be used to express how a child learns according to Vygotsky. This can be d efined as support frame work for childrens learning. When the child becomes more capable and confident a gradual withdrawal of help with scaffolding is an important aspect. Roger (1990) argue children become better problem solver if they practise solving problems with their parent or more experience children. Vygotsky further believes that language is important; the use of speech influences their cognitive development. In early days, children talk to themselves when playing; this is referred as private speech. Berk (1994) demonstrate that private speech is important as it a child would use it more when doing a difficult task compare to a easier one. Piaget notice this as well and referred to this as egocentric speech, because of the inability at pre school level to think from another perspective, in comparison Vygotsky state children talk to themselves in power to help them with their level of behaviour, and how to reflect and organise their behaviour in certain situation. Like Piaget, Vygotsky believe children are active in their own learning, by exploring their environment which helped shape their own knowledge. Vygotsky theory can be applied to education as it is concern how a child is taught. Vygotsky emphasized that the most important force into a child development was the social environment unlike Piaget theory of development heavily focus on the evolutionary biology. Both psychologists took notice in children pretend playing and becoming roles of people in society. Vygotsky however noticed that pretend play places the children in a zone of proximal development in which the play in advance of their real capabilities as they take the role as doctors, parents, teachers, as pretend play is based on rules. This guide behaviour in these roles, indirect they learn norms of society and how people expect them to act.The main difference between both psychologist is the degree social and interpersonal interaction causes development. Piaget idea had a huge influence on British education. The Ploweden report was an prominent, influential and emphasised many of Piagetian principles such as development age, readiness and the developmental stages. This document was published in 1967 and principles it brought to education was that children should discover for themselves and being active learner. Teachers role if to ask question and provide material to provide the children in state of disequilbration that enable them to modify their schema. Piaget theory suggests child centre learning, as all children mature at different rates, this help create small group activity and different children learn in different way. Vygotskys theory has high implication for education; especially in the recent years as he stresses out the importance of social interaction with more experienced others as an essential, as education was a fundamental aspect of human development. Peer tutoring is a key concept as children learn little when on their own or from a teacher who so advance, but rather with children a year or two ahead of those being taught. This is seen to be scaffolding. The zone of proximal development helps as a guide to help children achieve according to their abilities. Finally as Piaget influences argues children should be active learner, Vygotsky believes children should learn through play, especially through role plays as children operate beyond their usual level of thinking. To conclude, both theories have an effect to education and different ways of learning to a certain extent, however they are both different in a significant way even though there are similarity such as a strong debate between nature and nurture. How this can be seen to an advantage as both theories put together help each other to explain cognitive education biological and environmental influences. As Vygotsky overemphasised the role of social factor, Piaget overestimated the difference between stages.

Prediction of Stock Market Indices

Prediction of Stock Market Indices-Using SAS Author—B. Siddhartha Reddy Abstract— The SAS © System has a powerful suite of tools for analyzing and forecasting data taken over a selected time period. The paper concentrates more on Stock Market (NSE-Nifty, India) & its prediction, by and large a risky venture. Knowledgeable investors base their predictions either on the basis of Fundamental Analysis, or Technical Analysis, or both. But most of the investors rely on the tips given by the experts for Stock Market Predictions.However there are many such models available such as Interrupted Time Series, Auto Regression (AR), Exponential Smoothening, Moving Average (MA), and Distributed Lags Analysis. The procedures FORECAST, ARIMA process will be illustrated. analysis, traditional time series analysis and machine learning methods. The analyzing and predicting of the indices is in one line-To reap returns while investing on the index derivatives, Index derivatives provide in vestors the exposure to price movements of entire indices through a single futures or options contract.Using index options, a very interesting kind of â€Å"portfolio insurance† can be obtained, whereby an investor gets paid only if the market index drops. If one does not want to bear index fluctuations in the coming weeks, then the index futures or index options can be used to reduce (or even eliminate) the consequent index exposure. This is far more convenient than distress selling of the underlying equity in the portfolio. Thus, such prediction of indices would help the investor to play safe in the dynamic volatile market arena. Analyzing What?Analyzing the indices as in NIFTY MIDCAP 50, one can determine various trends the market has seen on day-to-day basis-the process which includes determining the trends underneath the data series (at a stretch of 13 years from 19972010) brought down from various secondary sources. Moreover, these trends can be used to identify the pat terns in the series and thus laying the foundation for forecasting adopting a couple of iterative processes which will be explained in the following sections. Details of the data: Observations-3282, Type-Daily Tools used: SAS © and Eviews. II.DATA FEATURES AND EXAMPLE The first step in time series analysis, or any good statistical analysis for that matter, is to plot the data. However, unless the user knows what to look for in the plots this exercise is futile. Features of interest usually include: Trend – an overall long term upward or downward movement in the data. Do we handle this by differencing the data or fitting a low order polynomial in time? Seasonality – a component of the series repeats periodically, for example, retail sales have a tendency to be high around November and December and lower near the first of the year.Do we look at seasonal differences or put in seasonal â€Å"indicator variables†? Keywords— forecasting, prediction, stock mar ket prediction Time series analysis. I. INTRODUCTION Stock market is the market for securities where organized issuance and trading of Stocks takes place either through exchanges or over-the-counter in electronic or physical form. It plays an important role in channelizing capital from the investors to the business houses, which consequently leads to the availability of funds for business expansion.Determination of stock price considers that market is supreme and it discounts everything (economical, political and all related factors). It presumes that all the investors behave rationally and the value of the asset is estimated based on future expectations. Hence, with every new information, the future expectation of the market is liable to change and consequently the stock prices. As the new information is erratic in nature so it influences the price in a random way. The purpose of this trend analysis is to enable the organizations/individuals improve their knack of trading their ind ex options/futures in the available markets (NSE, BSE).The SAS technology helps the organization/individual to speed up the process of investing in this second’s market (changing over a period of seconds) and timely reducing the loss at all the levels in a trading process thus leveraging their portfolios. Why Analyze? Stock Market Investments are subjected to market risks and the returns are variable in nature because it is an uncertain existence. Hence Stock Market Prediction is not a guaranteed one. It is based on certain analyses linked to the Macro & Micro economic factors or variables such as demand & supply.There are certain other analyses available such as fundamental Siddhartha Reddy. B is with IBS Bangalore, Karnataka, INDIA. Ph: 91+9886768492,e-mail:Siddhartha. [email  protected] com Page | 1 Variability – is the variation additive or multiplicative (in which case we might want to analyze the logarithms of the data). Special events – was there a stri ke sometime during the period? Does the time period include the dotcom bubble and the recession in 2008? Is there an effect of the same or some other impingements?The features of the data determine which procedures are appropriate and identify those that are not appropriate. There are statistical checks available in the system for deciding, for example, the best approach for modeling the trend. As an example, Fig 1 shows the change in the Index values of NIFTY MIDCAP 50 in INDIA. While not exactly steady, we can see an overall increase/decrease in market with time. If we are thinking in terms of polynomials, it seems that at least a cubic polynomial might be needed to approximate the curvature in the historic data plot.The flexibility of high degree polynomials allows them to fit historic data well, but becomes a liability in forecasting in that such polynomials can, by their inherent flexibility, produce unreasonable increases or decreases as they are projected out into the future. Having checked with the seasonality and stationary test of the data, the logarithmic value of the data CLOSE (closing point of NIFTY) is taken and rechecked for the stationary test. If the data is a stationary, then the data is ready to model into a time series. The stationarity tests are done by using the Time Series Analysis in SAS, preferably The Fullers Test. Fig. Log Transformed Flows (Data Series: Obs – 3282 Type – Daily) The accuracy of the above forecast shown in fig 2 can be viewed in the fig 3 which shows the difference of the actual values and the predicted values of the market by considering the entire data of 13years at once and later on the same difference in case of the splitted graph. Fig 3 shows the statistics of differences in forecasting of the data: the graph (trend) with split and without split. Fig. 3 Differencing of Forecasted Data with Split & Without Split Thus, from Fig 3 it is evident that the data series has to be split as per the trends an d seasonality available.Having inspected the trends available in the above data series, it is found that there are various trends in the market index (closing) and had resulted in the 10 splits. The entire project has been verified while considering each and every split that shows some or the other trend and/or the impact of global impacts such as the Dotcom bubble and followed by the Recession in the year of 2008. The above impingements referring the dotcom bubble and recession are clearly observed globally and their impacts on the Indian Market are analyzed and assessed.It can be inferred that though Indian markets have shown a slight drift in its market during the above impacts, the overall effect of the recession on India is far negligible compared to the other developed countries (in reference to the BPO sector: India at its best) and we can say India along with other Pan-Asia countries have stood back from such wallops. III. RELATED WORK The Time Series Prediction analyzes his toric data and attempts to approximate future values of a time series as a linear combination of these historic data.In econometrics there are two basic types of time series forecasting: univariate (simple regression) and multivariate (multivariate regression). These types of regression models are the most common tools used in econometrics to predict time series. The way they are applied in practice is that firstly a set of factors that influence Fig. 2 Log Transformed Forecast Siddhartha Reddy. B is with IBS Bangalore, Karnataka, INDIA. Ph: 91+9886768492,e-mail:Siddhartha. [email  protected] com Page | 2 (or more specific is assumed that influence) the series under prediction is identified.These factors are the explanatory variables xi of the prediction model. Methodology: The methodology includes ? Collecting the Secondary data from the market sources such as National Stock Exchange (Nifty). ? Checking the seasonality in the data series (if any) and minimizing the same for an ac curate prediction. ? Claiming the data series to be precise – i. e. checking whether the data series obtained is stationary and raising the steps to make it a stationary series. Having checked with the stationarity, the data would be crisp and apparently ready to fetch a good forecast. Subjecting the resultant series into various models such as AR, MA etc. ? Forecasting the index and plotting the change in behavior of the market indices which is a real time analysis. This will help analysts/investors to make good and accurate investment decisions. Limitations: ? Access to the market’s real time data would be time variant and a slight change in the market may change the trend. ? Time series forecasting heavily depends upon the availability of the data. Long time series give the flexibility of verifying alternative models and choose the best. Exact modeling needs lots of experience and trend identification will be heavily depend upon this experience. ? Though the study g ives a trend analysis it might not work in a uniform way for all the investors, therefore the behavior of the investor also plays a vital role in the modeling. ? The resultant analysis may work only for a specific period and may always subject to change depend on other externalities which will impact the economy of the country. ? Limited time may or may not fetch good results in implementation of the analysis since share market cannot be cracked in the real time. Fig. Forecasting System The Model Building and The Forecasting Process IV. PERFORMANCE ANALYSIS The Performance analysis is been considered for the 10th split of the above data series since the entire paper concentrates on the Real-Time analysis of the NIFTY market, while comparing the predicted values with that of the Real-Time Index values and the same difference of Prediction is shown in the below Excel table. Fig 5 shows the graph (LCLOSE) for a time period of July 09 – Feb 10 and is not stationary. It can be det ermined by just viewing its trend and moreover the data is not moving in and out of the MEAN at equal intervals.However, the series clearly shows the trend with a non-stationary series. Such a trend does require a differencing while fitting into the model. Fig. 5 Log Transformed Close Values (LCLOSE) Siddhartha Reddy. B is with IBS Bangalore, Karnataka, INDIA. Ph: 91+9886768492,e-mail:Siddhartha. [email  protected] com Page | 3 The stationary series (ref fig 5) is best fitted into the AR Model (Auto Regressive Model) and is fitted for eight lags. Fig 5 shows AR (8, 1) since the parameter estimates show that: The probability is 0. 221 which says that the series (LCLOSE) is more significant at lag 8 and the coefficient of the standard error is almost zero (0. 0839) as obtained during the evaluation of the above model leading to the best fit than any other model. Fig 6 shows the statistics of fit of LCLOSE graph with RSquare as 0. 961 which says that the series is been fitted into th e model with the 96. 1% of confidence with the adjusted R-Square of 0. 958 (almost same) and with the mean absolute error being almost zero thus leading to the best fit. Fig. 6 Statistics of Fit Fig. 8 Predictions and Data OverlaidThe predictions of LCLOSE in fig 8 are listed for the next 6 days: 7. 8190 to 7. 8274 are the forecasted values of the NIFTY closing for the dates above 24th of Feb 2010 that is for the real time of the future. These values are checked with the real time closing values of the NIFTY MIDCAP 50 on the following days. Fig 9 shows the predicted values and real time values of the same. Fig. 9 Predicted Vs Real Time Values The reason for this best fit of almost 96. 1% is due to the upward trend with the elevation of the data series which could make the prediction more accurate as it is a stationary.Fig. 7 96. 1% Confidence Interval Forecast (LCLOSE) From fig 9 it is evident that the predicted value of the NIFTY MIDCAP 50 as 7. 8190 and can be arrived at 2487. 416 (anti-log of Predicted) which has just 4. 2167 points of difference with the real time i. e. 2483. 20 which is a secondary data downloaded from the NSE site. The real time values for the rest of the periods are written manually and the difference is checked accordingly. V. FINDINGS AND CONCLUSIONS ? The above forecasts of the time series models clearly show the behavior pattern of the market (NIFTY MIDCAP 50) in the near future.One may or may not find a difference in the values of predicted to that of the real time. Fig 7 is obtained on this day of 24th Mar 2010 (the updated data) and the values of the above forecasted graph are fed into the excel sheet to calculate the anti-log of the same in order to come up with the predicted values for the NIFTY closing. ? There is always a possibility of certain standard errors in case of the time series analysis which may be found due to the absence of the best fit models than which are fitted above. Siddhartha Reddy. B is with IBS Bangalore, Karnataka, INDIA.Ph: 91+9886768492,e-mail:Siddhartha. [email  protected] com Page | 4 ? Such and such above models namely AR do have some limitations which would result in an inaccurate prediction since these predicted values may sometimes have a huge difference with that of the real time values caused due to the external factors. These external factors can be: 1. 2. Policies implemented by the GOVERNMENT OF INDIA. Variation in the rates such as ? Interest Rates. ? Fluctuations of Indian Rupee with the impact of other currencies. ? Foreign Exchange Rates etc. Unforeseen issues such as : ?A sudden decline in the foreign markets. ? A variation in the chain of demand and supply. ? Sudden attack by the outlaws. 3. ACKNOWLEDGMENT I would like to take this opportunity to thank Prof. Prashobhan Palakkeel and Prof. Veena Bhat (faculties, IBS Bangalore) for their assistance in the concepts of Business Intelligence and statistical tools used in this research namely SAS 9. 1 & Eviews 6. 0; their ceaseless support has resulted in such a vulnerable & successful explore. This research paper would not been possible without the untiring support provided by my family and friends.The input and guidance provided by other faculties have been invaluable. I would like to extent my gratitude to all these people. REFERENCES [1] www. nse-india. com (NSE National Stock Exchange, India) as a secondary data source for Nifty daily. [2] http://www. statsoft. com/textbook/time-series-analysis/ [3] http:/webspace. qmul. ac. uk/dsgpollock/public_html/courses /tseries/1trends. pdf [4] www. nse-india. com/content/fo/fo_NIFTYMIDCAP50. htm [5] Brocklebank, J. C. and D. A. Dickey (2003) SAS for Forecasting Time Series, SAS Institute, Cary, N.C. [6] http://nseguide. com/press-releases/nse-index-weightsbased-on-nse-daily-bhav-copy/ [7] http://www. hkbu. edu. hk/~billhung/econ3600/application/a pp03/app03. html [8] http://webspace. qmul. ac. uk/dsgpollock/public_html/course s/tseries/8idntify. pdf [9] http://www. duke. edu/~rnau/411arim. htm â€Å"Model Selection is seldom Precise in Time Series modeling, because it’s An Art more Than a Science† Siddhartha Reddy. B is with IBS Bangalore, Karnataka, INDIA. Ph: 91+9886768492,e-mail:Siddhartha. [email  protected] com Page | 5

Damien Peter Parer

Damien Peter Parer (1 August 1912 – 17 September 1944) was an Australian war photographer. He became famous for his war photography of the Second World War, and was killed by Japanese machinegun fire at Peleliu, Palau. He married Elizabeth Marie Cotter on 23 March 1944, and his son, producer Damien Parer, was born posthumously. He was also the uncle of Australian politician Warwick Parer and film-maker David Parer. He was cinematographer for Australia's first Oscar winning film, Kokoda Front Line, an edition of the weekly newsreel, Cinesound Review which was produced by Ken Hall. Damien Parer was born at Malvern in Melbourne, the tenth child of Teresa and John Arthur Parer, a hotel manager on King Island, Tasmania. In 1923, he and his brother, Adrian, were sent as boarders to St Stanislaus' College in Bathurst and St. Kevin's College, Melbourne . He joined the school's camera club, and decided that he wanted to be a photographer, rather than a priest. However, finding a job as a photographer in depression-era Australia proved difficult, and so he resumed his education at St Kevin's in east Melbourne. While at this school he won a prize in a photographic competition run by the Melbourne newspaper, the Argus, and used the money to buy a Graflex camera used by professionals. Parer obtained an apprenticeship with Arthur Dickinson. He said later that he learnt most about photography from Dickinson and Max Dupain. He finished his apprenticeship in 1933 and, sometime later, obtained work with the director, Charles Chauvel, on the film Heritage, where he met and became friends with another up and coming filmmaker of the time, John Heyer. At the conclusion of that film, and with the help of Chauvel, he obtained work in Sydney, and so moved there in 1935. By World War II, Parer was experienced at photography and motion pictures, and was appointed as official movie photographer to the Australian Imperial Force (AIF). His first war footage was taken on HMAS Sydney after it had sunk the Italian cruiser Bartolomeo Colleoni. Soon after, he was aboard HMS Ladybird while it was bombarding the sea port of Bardia in Libya. His first experience at close quarters was during a troop advance at Derna. Parer filmed in Greece and in Syria, covering the action from aircraft, the deck of a ship and on the ground with the infantry. After Syria he travelled to Tobruk in August 1941 before covering the fighting in the Western desert. By mid-1942 Parer was in New Guinea ready to cover the fighting against the Japanese. During this phase of the war, he filmed some of his most famous sequences, some at Salamaua and, most notably, those used in Kokoda Front Line. This documentary won its producer, Ken G. Hall, an Academy Award for documentary film-making. Parer was killed by Japanese gunfire while filming a United States Marine advance in Peleliu on the island of Palau.

Comparison of B2B and B2C Companies - 1062 Words

Comparison of B2B and B2C Companies This report is a supply chain comparison between two companies in which one is a business-to-business (B2B) model company and the other is a business-to-consumers (B2C) model company. The comparison will be between the companies Wal-Mart and Grainger. Wal-Mart is a well-known conglomerate known around the world that is in the retail business that seeks to sell products to consumers at a significantly reduced discount compared to its rivals. Grainger sells supplies to different companies through the company s own website. First, let s start by distinguish between what a B2B company is and what a B2C company is. The definition of a business-to-business is when businesses sell products or services†¦show more content†¦Grainger supplies its business to a variety of businesses but sells primarily to industrial and commercial maintenance departments, contractors, and government customers. The company sells more 800,000 products so Grainger relies heavily on the use of more than 1,200 suppliers to fill this need. One interesting fact is that nearly 40% of their purchases are from random purchases from customers that rarely buy the same product more than once a year (Grainger 2006 Fact Book). So how does Grainger fulfill these needs and keep customers happy? Grainger operates in the United States by having 416 branches, 10 distribution centers, and its own website. What separates Grainger from competition is the fact that Grainger offers the best combination of product selection, local availab ility, and speed of delivery. In fact, 99 percent of customers receive their orders the very next day. Grainger recently launched a catalog in 2006 that contains more than 115,000 products. That is a staggering number of products available for customers and a lot of information for Grainger to be accountable for. 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Most B2B companies are committed to building a strongRead MoreSupply Chain Mgmt in B2B and B2C Environment1451 Words   |  6 PagesManagement in B2B and B2C Environments Supply chain management, whether in a traditional or E-commerce environment, involves distributing products, goods and services from point of manufacture to the delivery of the final product. Supply chain management, whether related to B2B or B2C retailers involves manufacturing, storage, distribution and delivery of products and services to consumers and other businesses. B2B supply chain management is slightly more complex than B2C transactions, as B2B wholesalersRead MoreDifference Between Business Marketing And Consumer Marketing1304 Words   |  6 PagesArmstrong, Adam, Denize Kotler (2011) defines marketing as a management process that is responsible to identify and satisfy customer need and wants. Business to business (B2B) and business to customer (B2C), are two key areas of marketing that is often used to distinguish organization in a particular market. Business marketing is defined as the process of purchase a good or a service from a supplier for consumptions, incorpo ration and reselling purposes (Hutt Speh 2011). Customer marketing canRead MoreBusiness Overview: Saxon Plumbing Services London Ltd1529 Words   |  7 Pagesbrothers – Peter and Harvey Blair. The company currently employs 40 staff, the majority of which are based at its Head Office in South London, UK. Last year (2011) the company generated a turnover in excess of  £5.0m and a gross profit of  £1.2m. Company Background SPSL specialises in commercial plumbing services for businesses located in South London. Clients include: small and medium sized retailers, manufacturers, distributors and insurance companies. The company has built a reputation for providing