Abstract
Social marketing is all about creating, communicating, and delivering value to selected target markets; this value benefits society via the solution of major issues such as public health, safety, the environment, etc. Sadly, it seems that political mismanagement has created long-lasting or permanent ecological damage, a major public issue. Ecological environment issues impact future generations and humankind’s quality of life. This study aims to answer a crucial question: What do the political players due to help solve this problem? According to The CIS Model1, a government, a political party, or a politician not only need to create a political product (idea/proposal) but also needs to inform people about the product and support it. Given that The CIS Model is new, no studies were found to examine how a government can use The CIS Model as a strategy to advance Global Warming solutions for the benefit of the young generation (Generation Z). A sample of 205 adults aged 18–25 (Generation Z) from the USA, Europe, Asia, and Africa participated in the current study. According to the results of this study, the more a government uses The CIS Strategy to package global warming products, the higher Generation Z’s satisfaction (SFC), and the higher Generation Z’s loyalty to the government (LYT). The current study provides managerial implications and directions for future research.
Acknowledgments
The researcher would like to take this opportunity to acknowledge the time and effort devoted by the Editor-in-Chief and the reviewers of the Review of Marketing Science Journal. Their insightful comments enhanced the value of this paper. The researcher would also like to acknowledge the time and effort devoted by Dr. Valerio Mancini (Rome Business School, Italy) and Dr. Constantinos Constantinou (the Cyprus Institute of Marketing) to the collection of data.
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Research funding: This research did not receive any grant from any funding agency in the public, commercial, or not-for-profit sectors. The author warrants that the article is an original work. The author also confirms that everyone involved in the data collection has approved in writing their agreement to use this data for any individual research purpose.
Appendix A: Conceptualization of Constructs
| Variables | Constructs | Adapted from |
|---|---|---|
| The CIS strategy (C) | Create | Antoniades (2021a); Antoniades and Mohr (2019b) |
| My government creates political products (i.e. ideas, proposals) that can help fight climate change (CIS–C) | ||
| The CIS strategy (I) | Inform | Antoniades (2021a); Antoniades and Mohr (2019b) |
| My government provides detailed information on political products (i.e. ideas, proposals) that can help fight climate change (CIS–I) | ||
| The CIS strategy (S) | Support | Antoniades (2021a), Antoniades and Mohr (2019b) |
| My government supports political products (i.e. ideas, proposals) that can help fight climate change (CIS–S) | ||
| Generation Z satisfaction (SFC) | I am satisfied with my country’s government performance to deal with climate change (SFC) | Adapted from Antoniades and Haan (2018, 2019 |
| Generation Z loyalty (LYT) | Because of my country’s government actions on climate change, I am loyal to my country’s government (LYT) | Adapted from Antoniades and Haan (2018, 2019 |
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Note: This study used a structured approach with closed statements (as above) based on a 7-point Likert rating scale (1932) ranging from 1 (Strongly Disagree) to 7 (Strongly Agree).
Appendix B: Each Element of the CIS Model (Create, Inform, Support) with Satisfaction
| Summary output | ||||||||
|---|---|---|---|---|---|---|---|---|
| Regression statistics | ||||||||
| Multiple R | 0.68185 | |||||||
| R Square | 0.464919 | |||||||
| Adjusted R square | 0.456933 | |||||||
| Standard error | 1.329571 | |||||||
| Observations | 205 | |||||||
| ANOVA | |||||
|---|---|---|---|---|---|
| df | SS | MS | F | Significance F | |
| Regression | 3 | 308.7291 | 102.9097 | 58.21477161 | 3.96E-27 |
| Residual | 201 | 355.3196 | 1.767759 | ||
| Total | 204 | 664.0488 | |||
| Coefficients | Standard error | t Stat | p-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
|---|---|---|---|---|---|---|---|---|
| Intercept | 0.531925 | 0.219531 | 2.423005 | 0.01627882 | 0.099046 | 0.964805 | 0.099046 | 0.964805 |
| CIS–C | −0.08183 | 0.104297 | −0.7846 | 0.433613113 | −0.28749 | 0.123826 | −0.28749 | 0.123826 |
| CIS–I | 0.533667 | 0.123459 | 4.322631 | 2.42446E-05 | 0.290226 | 0.777107 | 0.290226 | 0.777107 |
| CIS–S | 0.299809 | 0.092959 | 3.22517 | 0.001469537 | 0.116509 | 0.48311 | 0.116509 | 0.48311 |
Appendix C: Each Element of the CIS Model (Create, Inform, Support) with Loyalty
| Summary output | ||||||||
|---|---|---|---|---|---|---|---|---|
| Regression statistics | ||||||||
| Multiple R | 0.571172 | |||||||
| R Square | 0.326237 | |||||||
| Adjusted R square | 0.316181 | |||||||
| Standard error | 1.62829 | |||||||
| Observations | 205 | |||||||
| ANOVA | |||||
|---|---|---|---|---|---|
| df | SS | MS | F | Significance F | |
| Regression | 3 | 258.0393 | 86.01312 | 32.44153325 | 3.81E-17 |
| Residual | 201 | 532.9167 | 2.651327 | ||
| Total | 204 | 790.9561 | |||
| Coefficients | Standard error | t Stat | p-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
|---|---|---|---|---|---|---|---|---|
| Intercept | 1.747267 | 0.268854 | 6.498945 | 6.24709E-10 | 1.217131 | 2.277403 | 1.217131 | 2.277403 |
| CIS–C | −0.08645 | 0.12773 | −0.67684 | 0.499283009 | −0.33832 | 0.165409 | −0.33832 | 0.165409 |
| CIS–I | 0.659978 | 0.151197 | 4.36503 | 2.03225E-05 | 0.361843 | 0.958113 | 0.361843 | 0.958113 |
| CIS–S | 0.098131 | 0.113845 | 0.861975 | 0.38972872 | −0.12635 | 0.322614 | −0.12635 | 0.322614 |
Appendix D: The CIS (whole) Model & Satisfaction
| Summary output | ||||||||
|---|---|---|---|---|---|---|---|---|
| Regression statistics | ||||||||
| Multiple R | 0.661834188 | |||||||
| R Square | 0.438024492 | |||||||
| Adjusted R square | 0.43525614 | |||||||
| Standard error | 1.355846945 | |||||||
| Observations | 205 | |||||||
| ANOVA | |||||
|---|---|---|---|---|---|
| df | SS | MS | F | Significance F | |
| Regression | 1 | 290.8696 | 290.8696 | 158.2257 | 3.31547E-27 |
| Residual | 203 | 373.1792 | 1.838321 | ||
| Total | 204 | 664.0488 | |||
| Coefficients | Standard error | t Stat | p-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
|---|---|---|---|---|---|---|---|---|
| Intercept | 0.560200879 | 0.222839 | 2.513923 | 0.012716 | 0.120824358 | 0.999577401 | 0.120824 | 0.999577 |
| CIS | 0.730731191 | 0.058092 | 12.57878 | 3.32E-27 | 0.616189363 | 0.84527302 | 0.616189 | 0.845273 |
Appendix E: The CIS (whole) Model & Loyalty
| Summary output | ||||||||
|---|---|---|---|---|---|---|---|---|
| Regression statistics | ||||||||
| Multiple R | 0.544256984 | |||||||
| R Square | 0.296215664 | |||||||
| Adjusted R square | 0.292748746 | |||||||
| Standard error | 1.655952856 | |||||||
| Observations | 205 | |||||||
| ANOVA | |||||
|---|---|---|---|---|---|
| df | SS | MS | F | Significance F | |
| Regression | 1 | 234.2936 | 234.2936 | 85.44063 | 3.32717E-17 |
| Residual | 203 | 556.6625 | 2.74218 | ||
| Total | 204 | 790.9561 | |||
| Coefficients | Standard error | t Stat | p-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
|---|---|---|---|---|---|---|---|---|
| Intercept | 1.737371534 | 0.272163 | 6.383569 | 1.15E-09 | 1.200742523 | 2.274000545 | 1.200743 | 2.274001 |
| CIS | 0.655826039 | 0.070951 | 9.24341 | 3.33E-17 | 0.51593129 | 0.795720788 | 0.515931 | 0.795721 |
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