Assignment 5 – Path Model Assessment II using SPSS

In this assignment, you will be performing an analysis very similar to what was done in Assignment 4. The path model looks the same but has different variables. In this case, you will be asked to replicate the results from Meacham et al. (2013) related to the impact of information sharing (IS) and green information systems (GIS) on environmental performance (ENP). Note that I changed the acronym for environmental performance from EVP to ENP.

1. Read through the Meacham et al. (2013) article.
2. Answer the following questions related to the article:
   1. What is the purpose of the study?
   2. What are the results of the paper?
   3. How do the authors define IS, GIS, and ENP?
   4. List the three hypotheses illustrated in Figure 1. (Note that the hypotheses are numbered in a different order than in Assignment 4).
   5. Look at the results displayed in Figure 2. Are each of the three hypotheses supported?
   6. Does IS directly impact ENP? Explain.
   7. Does IS directly impact GIS? Explain.
   8. Does GIS directly impact ENP? Explain.
   9. Does IS indirectly impact ENP through GIS (ISGISENP)? Explain.
   10. Based on these results, do IS and GIS combine to improve ENP? Explain.
3. Access the "Assignment 5 IS_GIS_ENP.sav file.
4. Take a look at the figure 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 - ENP is the dependent variable; GIS and IS are the independent variables.
   2. Regression 2 – GIS is the dependent variable and IS is the independent variable.
5. Run Regression 1 by following this command sequence [analyze, regression, linear, move ENP to the dependent variable block and GIS and IS 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 and significance level for the GIS variable?
   3. What is the beta value and significance level for the IS variable?
6. Run Regression 2 by following this command sequence [analyze, regression, linear, move GIS to the dependent variable block and IS 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 and significance level for the IS variable?
7. Now, insert the R ² and beta values with significance notations (**, *, or ns ) into figure below.
8. Look at the betas for H2: and H3:. Calculate the indirect effect of IS on ENP through GIS 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 the figure (H4:).
   

   Path Analysis Results

   R ² =

   GIS

   
   

   H2: Beta =

   H3: Beta =

   
   

   R ² =

   
   

   IS

   ENP

   
   

   H1: Beta =

   
   

   H4: Indirect Effect (ISGISENP) =

9. Interpret the results in the figure.
   1. What percentage of the variation in GIS is explained by the variation IS?
   2. What percentage of the variation in ENP is explained by the variation in GIS and IS?
   3. Does IS directly impact GIS (H2:)? Include the beta and significance level to support your answer.
   4. Does GIS directly impact ENP (H3:)? Include the beta and significance level to support your answer.
   5. Does IS directly impact ENP (H1:)? Include the beta and significance level to support your answer.
   6. Does IS indirectly impact ENP through GIS (H4:)? Include the indirect effect and significance level to support your answer.
10. Finally, compare your answers to those in Figure 2 of the Meacham et al. (2013) article. While the numbers are slightly different (you used regression instead of PLS. This time, you are using the same data set as the one used in the article. Do your results generally match the results in the article?

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