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Part 1: Firm Performance In this spreadsheet, you will find data with a number of variables that are commonly studied in business strategy research. Working

Part 1: Firm Performance

In this spreadsheet, you will find data with a number of variables that are commonly studied in business strategy research. Working from column A across, each firm has an identifier code. Firm ownership is a dummy coded variable where 0 = publicly-traded and 1 = privately-held firm ownership. Firm performance is the companys self-assessment about the extent to which they meet/exceed performance expectations.

The remaining variables are factors that are predicted to influence performance. Customer orientation measures the extent to which a firm focuses on its customers and their needs, wants, and preferences. Long term orientation, benchmarking, and planning are variables that speak to the firms strategic planning capacity. Finally, risk taking is the firms capacity for risky strategic moves. Each variable is measured by managers reporting on a 1-7 Likert scale.

Firm ID

ownership (private = 1)

firm performance

customer orientation

long-term orientation

benchmarking

planning

risk taking

Risk taking squared

firm performance

1

1

4.33

5.50

6.20

5.00

1.00

5.00

25.00

4.33

2

0

4.00

6.25

4.80

1.83

4.17

5.80

33.64

4.00

3

0

4.67

6.25

2.00

5.50

5.33

4.80

23.04

4.67

4

0

4.00

4.25

3.80

1.67

5.00

6.00

36.00

4.00

5

1

4.67

6.25

5.60

4.50

4.50

5.20

27.04

4.67

6

1

5.67

5.25

4.20

5.00

2.17

3.00

9.00

5.67

7

0

2.67

3.00

5.40

5.33

5.50

4.60

21.16

2.67

8

0

2.67

5.75

3.00

4.33

4.67

6.80

46.24

2.67

9

1

5.00

6.25

5.00

3.33

3.83

4.80

23.04

5.00

10

1

6.00

6.25

5.80

3.83

4.33

2.80

7.84

6.00

11

1

5.00

6.00

3.80

4.00

3.00

3.60

12.96

5.00

12

0

5.00

6.25

5.00

4.67

3.83

4.20

17.64

5.00

13

1

5.33

5.50

5.40

2.67

4.00

3.20

10.24

5.33

14

0

5.00

4.75

5.20

6.67

6.00

1.60

2.56

5.00

15

0

4.67

6.50

6.80

4.67

5.50

4.00

16.00

4.67

6. Does multicolinearity appear to be a problem in this dataset? How do you know, and how would you proceed?

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