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Employee Productivity statistical analysis

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See attached table and data chart:

A. What firm-specific and industry-specific factors might be used to explain differences among giant corporations in the amount of revenue per employee and profit per employee?

B. A multiple regression analysis based upon the data contained in the attached table reveals the following (t statistics in parentheses):

Profit/Emp=$17,267,679 + 0.052 Ind. Profit/Emp +
(1.26) (0.16)
0.083 Rev/Emp + 0.006 Ass./Emp.
(5.19) (3.86)

R squared = 98.0%, F Statistic = 417.12

Interpret these results. Is profit per employee more sensitive to industry-specific or firm specific factors for this sample of giant corporations?

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Firm-specific factors which can explain differences in employee productivity include:
Technology: do all the employee have access to state of the art equipment? Do they have to spend a lot of time trying to find things because of outmoded software?

Geographic location: different regions of the country are wealthier than others, and thus the firms in these areas are likely realize high profit margins
Company culture: Employees tend to look to their co-workers for clues about how to perform their duties. A company culture that motivates employees to work hard will likely have higher profits than one that doesn't.

Industry-specific factors include:
Type of work: Different industries have different profit margins. Companies that provide credit services, for example, will realize a high revenue per employee. Companies that use employees merely to help people locate things, like home improvement stores, will have lower revenue per employee figures.
Presence of unions: some industries have high rates of unionization among employees. This tends to increase wages and decrease profit per ...

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