Environmental Analysis Essay

Environmental Analysis
My firm is Expedia, and it operates in the travel industry. The company’s core site is a consolidator, but the company operates a range of complementary sites in the travel business. There are a few key macroeconomic variables that impact on the travel industry in general. The most important is the state of the economy (WTO, 2010), which we can take as a combination of GDP and the unemployment rate. These two variables are important because travel is largely a luxury item for consumers. During difficult times, consumers are more apt to save than spend on luxury items. As such, the savings rate is also a variable to which there is a correlation between travel industry demand. This demand will be reflected in firm revenues.
In addition, because firms like Expedia are in an environment characterized by rapidly changing technology, these companies must constantly invest in research and development in to ensure that their websites are up-to-date. This often requires debt financing, so the prevailing interest rates will be a factor in the company’s economic success. This paper will analyze these different sets of variables in to determine the degree of correlation between them.
The first set of variables is the rate of GDP growth and the rate of revenue growth at Expedia. All financial data on Expedia is sourced from MSN Moneycentral (2010). The GDP growth figures were derived from the BEA. Personal savings rate figures came from the St. Louis Fed. Unemployment figures come from the BLS, and the discount rate figures come from the Federal Reserve.
The first correlation is as follows:
This shows that there is only a moderate correlation between the firm’s revenue growth and the growth in the economy. The most important element of this correlation is in the year 2007, when the firm’s growth spiked despite a slowdown in GDP growth. However, after that point there is more of a correlation, as evidenced by the fact that as the GDP continued to fall, revenues at Expedia also fell.
The second correlation is as follows:
The expectation for this graph is an inverse relationship. During the early part of the graph, there is no such relationship, but it begins to emerge in the last couple of years when the unemployment rate goes up quickly and the rate of revenue growth at Expedia collapses. The lack of improvement in unemployment statistics in 2010 is not an encouraging sign for Expedia, which relies on Americans having the ability to afford vacations for its business.
The third correlation is as follows:
With this graph, the savings rate and revenue growth rate are expected to have an inverse relationship. This is the case for the most part. In particular, in the last two years of the study the savings rate increases while revenue growth experiences a rapid decrease. The shape of the graph is skewed somewhat by the large revenue growth in 2007, but the general trend that was predicted is evident. It is worth noting that in 2010 the savings rate has declined somewhat. This would be expected to signal a slight uptick in the company’s revenue growth rate, all other factors being equal.
The fourth correlation is as follows:
With this graph, it is expected that if the discount rate drops, R

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