Data Analysis for Project Tutorial
Research Model Topic 2 Remanufactured Products Environmental Concern Attitude towards Recycling H2 (+) H1 (+) Subjective Norm Perceived Moral Obligation Convenience Perceived Behavioral Control Consequence Awareness H3 (+) H4 (+) H5 (+) H6 (+) H7 (+) Purchase Recycled/Remanufactured Products
Description of Variables Item code Variable name Source No. of Items ENV1 to ENV4 Environmental Concern Chen & Tung (2014) 4 ATT1 to ATT4 Attitude towards Recycling Wan et al. (2014) 4 SUB1 to SUB4 Subjective Norm Wan et al. (2014) 3 PBC1 to PBC4 Perceived Behavioral Control Wan et al. (2014) 4 MOR1 to MOR3 Perceived Moral Obligation Chen & Tung (2014) 3 CONV1 to CONV3 Convenience Lee et al. (2014) 3 FAC1 TO FAC2 Perceived Lack of Facilities Chen & Tung (2012) 2 AWR1 to AWR4 Consequences Awareness Wan et al. (2014) 4 HAB1 to HAB4 Habit Limayem et al. (2003) 4 INT1 to INT5 Intention to recycle Chen & Tung (2010) 5
Data Screening Check for data entry errors Can do sampling check Can do with frequencies and descriptives
Reliability of Measurement Scales
Reliability of Measurement Scales Variable N of Item Item Deleted Alpha Environmental Concern 4-0.844 Attitude towards Recycling 4-0.757 Subjective Norm 3-0.921 Perceived Behavioral Control 4-0.770 Perceived Moral Obligation 3-0.893 Convenience 3-0.942 Perceived Lack of Facilities 2-0.833 Intention to recycle 5-0.949
Table Presentation Variable N of Item Item Deleted Alpha Environmental Concern 4-0.844 Attitude towards Recycling 4-0.757 Subjective Norm 3-0.921 Perceived Behavioral Control 4-0.770 Perceived Moral Obligation 3-0.893 Convenience 3-0.942 Perceived Lack of Facilities 2-0.833 Intention to recycle 5-0.949
Data Entry Sheet
Computing Variables in your Model
After Computing 1 st Variables in your Model
COMPUTE You will need to compute the variables in your model In this example of Topic 2 there are 8 variables as such you have to compute 8 times.
After Computing All Variables in your Model
Running Frequencies Analysis
Running Descriptive Analysis
Results of the Analysis
Table Presentation Gender Male Female Ethnicity Malay Chinese Indian Others Frequency 51 99 43 91 15 1 Percentage 34.0 66.0 28.7 60.7 10.0 0.7
Results of the Analysis
Table Presentation Variable Mean Std. Deviation Skewness Kurtosis ENVIRONMENT 6.235 0.882-2.012 7.699 ATTITUDE 5.667 1.112-1.528 3.275 SN 4.648 1.526-0.834 0.154 PBC 4.942 1.225-0.750 0.776 MORAL 5.982 1.004-1.512 4.300 CONVENEINCE 4.813 1.626-1.145 0.795 LACK 5.377 1.357-0.939 1.275 INTENTION 4.451 1.624-0.640 0.033
Running Correlation Analysis
Results of the Analysis Correlations ENVIRONMENT ATTITUDE SN PBC MORAL CONVENEINCE LACK INTENTION ENVIRONMENT Pearson Correlation 1.431 **.054.209 *.620 **.065.260 **.070 Sig. (2-tailed).000.514.010.000.432.001.397 N 150 150 150 150 150 150 150 150 ATTITUDE Pearson Correlation.431 ** 1.544 **.372 **.413 **.556 **.035.477 ** Sig. (2-tailed).000.000.000.000.000.672.000 N 150 150 150 150 150 150 150 150 SN Pearson Correlation.054.544 ** 1.719 **.085.728 ** -.141.762 ** Sig. (2-tailed).514.000.000.299.000.086.000 N 150 150 150 150 150 150 150 150 PBC Pearson Correlation.209 *.372 **.719 ** 1.067.631 ** -.165 *.635 ** Sig. (2-tailed).010.000.000.413.000.044.000 N 150 150 150 150 150 150 150 150 MORAL Pearson Correlation.620 **.413 **.085.067 1.061.300 **.035 Sig. (2-tailed).000.000.299.413.455.000.667 N 150 150 150 150 150 150 150 150 CONVENEINCE Pearson Correlation.065.556 **.728 **.631 **.061 1 -.078.818 ** Sig. (2-tailed).432.000.000.000.455.340.000 N 150 150 150 150 150 150 150 150 LACK Pearson Correlation.260 **.035 -.141 -.165 *.300 ** -.078 1.073 Sig. (2-tailed).001.672.086.044.000.340.373 N 150 150 150 150 150 150 150 150 INTENTION Pearson Correlation.070.477 **.762 **.635 **.035.818 **.073 1 Sig. (2-tailed).397.000.000.000.667.000.373 N 150 150 150 150 150 150 150 150 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
Table Presentation 1 2 3 4 5 6 7 8 1. ENVIRONMENT 1 2. ATTITUDE.431** 1 3. SN 0.054.544** 1 4. PBC.209*.372**.719** 1 5. MORAL.620**.413** 0.085 0.067 1 6. CONVENEINCE 0.065.556**.728**.631** 0.061 1 7. LACK.260** 0.035-0.141 -.165*.300** -0.078 1 8. INTENTION 0.07.477**.762**.635** 0.035.818** 0.073 1
Running Regression Analysis
Regression Analysis - Assumptions
Regression Analysis - Assumptions
Results with Outliers Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 1.876 a.768.757.80099 1.711 a. Predictors: (Constant), LACK, ATTITUDE, PBC, MORAL, ENVIRONMENT, CONVENEINCE, SN b. Dependent Variable: INTENTION Coefficients a Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) -.832.551-1.508.134 ENVIRONMENT.021.108.011.195.845.477 2.094 ATTITUDE -.029.089 -.020 -.323.747.442 2.264 SN.381.078.358 4.896.000.306 3.273 PBC.113.086.085 1.312.192.384 2.602 MORAL -.153.088 -.094-1.735.085.552 1.812 CONVENEINCE.535.065.535 8.244.000.387 2.583 LACK.246.053.206 4.681.000.847 1.181 a. Dependent Variable: INTENTION
Results without Outliers Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 1.897 a.805.795.72175 1.711 a. Predictors: (Constant), LACK, ATTITUDE, PBC, MORAL, ENVIRONMENT, CONVENEINCE, SN b. Dependent Variable: INTENTION Coefficients a Unstandardized Coefficients Standardized Coefficients Collinearity Statistics Model B Std. Error Beta t Sig. Tolerance VIF 1 (Constant) -.844.497-1.699.092 ENVIRONMENT.051.098.028.526.600.475 2.104 ATTITUDE -.033.080 -.023 -.412.681.441 2.267 SN.308.071.293 4.317.000.302 3.316 PBC.106.078.081 1.353.178.384 2.606 MORAL -.181.079 -.114-2.273.025.551 1.813 CONVENEINCE.601.060.615 9.973.000.366 2.733 LACK.261.047.223 5.510.000.852 1.173 a. Dependent Variable: INTENTION
Table Presentation Hypothesis Variable B Std. Error Beta t-value p-value H1 ENVIRONMENT 0.051 0.098 0.028 0.526 0.600 H2 ATTITUDE -0.033 0.080-0.023-0.412 0.681 H3 SN 0.308 0.071 0.293 4.317 0.000 H4 MORAL -0.181 0.079-0.114-2.273 0.025 H5 CONVENEINCE 0.601 0.060 0.615 9.973 0.000 H6 PBC 0.106 0.078 0.081 1.353 0.178 H7 LACK 0.261 0.047 0.223 5.510 0.000
References References Chen, M.-F., & Tung, P.-J. (2014). Developing an extended Theory of Planned Behavior model to predict consumers intention to visit green hotels. International Journal of Hospitality Management, 36, 221-230. Chen, M-F., & Tung, P-J. (2010). The Moderating Effect of Perceived Lack of Facilities on Consumers Recycling Intentions. Environment and Behavior, 42(6), 824-844. Essoussi, L. H., & Linton, J. D. (2010). New or recycled products: how much are consumers willing to pay? Journal of Consumer Marketing, 27(5), 458-468. Kanchanapibul, M., Lacka, E., Wang, X., & Chan, H.K. (2014). An empirical investigation of green purchase behavior among the young generation. Journal of Cleaner Production, 66, 528-536. Leary, R.B., Vann, R.J., Mittelstaedt, J.D., Murphy, P.E., Sherry, J.F. Jr. (2014). Changing the marketplace one behavior at a time: perceived marketplace influence and sustainable consumption. Journal of Business Research, 67(9), 1953-1958. Lee, Y., Kim, S., Kim, M., & Choi, J. (2014). Antecedents and interrelationships of three types of pro-environmental behavior. Journal of Business Research, 67(10), 2097-2105. Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2003). Habit in the Context of IS Continuance: Theory Extension and Scale Development, in Proceedings of the 11th European Conference on Information Systems, C. U. Ciborra, R. Mercurio, M. de Marco, M. Martinez, and A. Carignani (Eds.), Naples, Italy, 19-21 June 2003. Wan, C., Cheung, R., & Shen, G. Q. (2012). Recycling attitude and behaviour in university campus: a case study in Hong Kong. Facilities, 30(13/14), 630-646. Wesley, S.C., Lee, M.-Y., & Kim, E.Y. (2012). The role of perceived consumer effectiveness and motivational attitude on socially responsible purchasing behavior in South Korea. Journal of Global Marketing, 25(1), 29-44.
Appendix Appendix 1 copy of Questionnaire Paper Cuttings Relevant Computer Outputs
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