Assignment 4 – Path Model Assessment using SPSS

In Assignments 1, 2, and 3, you read some of the current literature related to environmental sustainability. Most of you were able to answer the discussion questions but had some problems when it came to understanding the statistical results presented in the papers. It is time for you to begin using SPSS to analyze the datasets yourself. You will be using SPSS throughout the rest of the semester. In this assignment, I want you to replicate the results presented in the market orientation/GSCMP paper you read in Assignment 3 using SPSS. Follow my instructions carefully.

1. Go to the Content Section of Blackboard and read the note associated with the SPSS installer.
2. If you do not currently have access to SPSS on your personal computer, run the SPSS Installer that is located in the Content Section of Blackboard. If you have problems with the Installer, contact the SAU HelpDesk.
   1. The HelpDesk is only responsible for helping you load SPSS on your personal computer. The HelpDesk workers cannot help you with the steps required to complete your assignments.
   2. If for some reason, you are unable to get SPSS to run remotely from the SAU server, you will have to lease the software from www.studentdiscounts.com . In this case any version of the SPSS Grad Pack (Basic) will work.
3. Access the "Assignment 4 MO_GSCMP_EVP.sav file. Note that there are three columns of numbers – MO, GSCMP, and EVP.
4. Take a look at Figure 1 below. Note that you will need betas and R ² values to insert in the model. These values will be come from the regression results provided through SPSS. There are two regressions in the model:
   1. Regression 1 - EVP is the dependent variable; GSCMP and MO are the independent variables.
   2. Regression 2 – GSCMP is the dependent variable and MO is the independent variable.
5. Run Regression 1 by following this command sequence [analyze, regression, linear, move EVP to the dependent variable block and GSCMP and MO to the independent variable block, OK]. SPSS will output three tables. The first table is the Summary Table which contains the R ² value. The third table is the Coefficients Table which contains the betas and the Sig. values necessary to determine the significance levels of the betas. Answer these questions related to Regression 1:
   1. What is the R ² value?
   2. What is the beta value for the GSCMP variable?
   3. What is the Sig. value for the GSCMP variable?
   4. Based on the Sig. value for the GSCMP variable, how significant is the GSCMP beta?
   5. What is the beta value for the MO variable?
   6. Based on the Sig. value for the MO variable, how significant is the MO beta?
6. Run Regression 2 by following this command sequence [analyze, regression, linear, move GSCMP to the dependent variable block and MO to the independent variable block, OK]. Answer these questions related to Regression 2:
   1. What is the R ² value?
   2. What the beta value for the MO variable?
   3. What is the beta value for the MO variable?
   4. Based on the Sig. value for the MO variable, how significant is the MO beta?
7. Now, insert the R ² and beta values with significance notations (**, *, or ns ) into Figure 1 below.
8. Look at the betas for H1: and H2:. Calculate the indirect effect of MO on EVP through GSCMP by multiplying the two betas together. If the two betas are significant at the .01 level (**) the indirect effect is also significant at the .01 level. If one of the betas is significant at the .01 level and the other at the .05 level, the indirect effect is significant at the .05 (*) level. If one or both of the betas are non-significant, the indirect effect is also non-significant ( ns ). Insert the indirect effect with its associated significance level into Figure 1.
   

   R ² =

   
   

   GSCMP

   Figure 1 – Path Analysis Results

   
   

   H1: Beta =

   H2: Beta =

   
   

   R ² =

   
   

   H2: Beta =

   MO

   EVP

   
   

   H4: Indirect Effect (MOGSCMPEVP) =

9. Interpret the results in Figure 1. If you don’t remember how to interpret R ² values or how to determine the significance levels of beta values, look at the "R-square and significance levels in regression" document included with this assignment.
   1. What percentage of the variation in GSCMP is explained by the variation MO?
   2. What percentage of the variation in EVP is explained by the variation in GSCMP and MO?
   3. Does MO directly impact GSCMP (H1:)? Include the beta and significance level to support your answer.
   4. Does GSCMP directly impact EVP (H2:)? Include the beta and significance level to support your answer.
   5. Does MO directly impact EVP (H3:)?Include the beta and significance level to support your answer.
   6. Does MO indirectly impact EVP through GSCMP (H4:)? Include the indirect effect and significance level to support your answer.
10. Finally, compare your answers to those in Figure 2 of the Market Orientation/GSCMP article from Assignment 3. While the numbers are slightly different (you used regression instead of PLS and your sample is somewhat larger, are all of the hypotheses supported in Figure 1 above and Figure 2 in the article?

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