Investigating the effect of granularity on people's willingness
to support green policies.
University of Groningen Faculty of Economics and Business
MSc Marketing Management Master Thesis
Completion date: 13/1/2020
First supervisor: M. (Mehrad) Moeini Jazani Second supervisor: Prof. dr. B.M. (Bob) Fennis
Christos Zarmpalas S3404439 Soephuisstraatje 18-17
9712 BZ, Groningen, the Netherlands +30 6947572750
Abstract
This study examined the effect of time frame in people’s willingness to support “green” policies. Specifically, we assumed that when the time is communicated in more granular units it makes people more willing to support “green” policies. Building on the findings of the literature we conduct a 2x2 between subjects design, 2 (Duration: 27 vs 41 years) X 2 (Time frame: Days vs Year). We also wanted to examine whether the granularity increases people’s concern and make them enhance “green” policies, so the mediating effect of perceived concern was also tested. Additionally, this research also investigates if the skepticism and the political orientation of the participants moderate the effect. The results shown that the effect of granularity in
people’s willingness to support “green” policies was insignificant. Even though the time expressed in more granular units raises people’s concern about climate change and their tendency to support “green” policies, it does not mediate the effect since the initially the IV (granularity) does not predict the DV (policy support).The results also demonstrate that the effect of skepticism in people’s willingness to support “green” policies is significant in contrast to political orientation which does not moderate the effect.Finally, this paper tries to explain the results as well as the limitations of this study, in order to contribute more knowledge to the scientific community that researches the time frame in combination with policy support in the environmental domain.
Table of contents
Introduction--- 4 Theoretical Framework--- 6 Time Subjectivity---7 Time Frame---8 Policy Support---10 Hypotheses ---11 Conceptual model---16 Methodology---17 Manipulation of Granularity---17 Perceived Concern--- 18 Policy Support---19 Skepticism---19Demographics and Political Orientation--- 20
Attention Checks--- 20
Results---21
Attention Check--- 21
Manipulation Check---21
Potential Mediating Effect - Perceived Concern ---24
Potential Moderating Effect Of Skepticism---25
Potential Effect Of Political Orientation---27
Introduction
The American essayist, poet and philosopher Henry David Thoreau once stated: “What’s the use of a fine house if you haven’t got a tolerable planet to put it on.” This quote is an astute observation of the relationship between humans and nature in today's modern society that is defined by rapid changes, driven by luxurious idols and has been enslaved by its capitalistic thoughts. The greenhouse gas emissions have increased dramatically over the last few years and if people do not proceed in decisive efforts to solve the problem the critical consequences will be inevitable, since the global climate change constitutes one of the most enormous environmental threats that humans have ever faced (Hedberg T. 2018). Researchers have long debated the origins of those environmental problems.
According to some the dramatic rise of pollution and the ecological disaster are both an outcome of the general overpopulation problem that the earth faces the last decades. The expansion of the population in countries that present some of the greatest carbon and most serious ecological footprints is very harmful.(Abegão J. L. R. 2019). Driven from a more environmentalistic view, other researchers indicate that the vast industrial expansion is the route of the problem. However, both sides tend to agree that the lack of concern, that people seem to have while facing this major problem is the main issue, which for the hardliners indicates an absence of humility against nature.
the environment. Nonetheless, this passive behaviour may be due to the fact that people tend to not believe that the problem is real either because there is a lot of misinformation which
increases their skepticism or because they are not able to understand that the environmental disaster is so close as they might perceive time differently and that makes them conceive the risk as very distant. Another possible explanation for this indifference is the perception that climate change is a psychologically distant problem, since people tend to believe that it is most likely to affect people and places distant geographically and temporarily.(Leiserowitz, 2005; Rathzel and Uzzell, 2009).
This paper aims to examine how by using a time-framing mechanism, we can cause higher awareness on individuals about climate change and as a result make them endorse more environmentally friendly policies. Additionally, we will be investigating whether skepticism and political orientation can alter this effect.
In the following section, firstly we will be trying to explain how the aforementioned concepts are linked, in the theoretical background of the research. Moreover, there will be the methodology section, analyzing the proccessess we used, and the results of the experiment. In the last part of this paper, we will be discussing the results, laying out the limitations and making suggestions for future research.
Theoretical Background
One of the most important issues of the modern world and perhaps the most serious in terms of environmental danger, is the climate change. As mentioned previously, the opinions vary not only on what is the cause of the problem but also on how can humankind possibly find a solution. As many researchers have stated, the lack of concern that people tend to have in the presence of this threat constitutes a core element of this problem and a serious obstacle in finding a solution to the issue. Despite the fact that there will always be uncertainties with regards to climate modeling and in particular with regard to predicted impacts, the key policy debate is less about where we want to be in 40 years ' time and more about the means to achieve what appears to be an ever more optimistic collection of expectations.(Spence and Pidgeon, 2009).
In this study we examine how the manipulation of time could possibly have an effect on how people perceive risk and how different expressions of the same duration could raise their concern for climate change and eventually make them to support any “green” policies in order to solve or at least restrict the problem. We use two different durations 27 years and 41 years in order to be sure that a specific duration is not accountant for our results. Our temporal framing is time granularity and more specifically we expressed either on days and years respectively both of the durations.We conduct four hypotheses in order to find out if the time framing has any particular effect on people's intentions to support “green” policies and if granularity increases people’s concern about climate change.In order to be more assured about our results we include the level of skepticism and the political orientation of the participants as moderators because it is believed that they will affect people’s acceptance of “green” policies.
Time subjectivity
delayed outcomes for earlier (or shorter) delays and reverse their preferences as alternatives get closer towards the present. (Kim, B. K., & Zauberman, G. 2009).
It seems that it is difficult for people to understand time as an independent dimension and it is common to misjudge the specific duration of events, although much of the evidence
assessments. relates to retrospective assessments of duration rather than prospective
interpretation of time.(Zauberman, et.al.,2009). People’s subjective evaluation of duration do not reliably map objective time when forming intertemporal preferences. Consumers ' mapping of objective duration to subjective time is nonlinear and marked by inadequate sensitivity to shift in duration and by such a disparity between objective duration and subjective evaluation of
time.(Zauberman, et.al.,2009)
Time Frame
experiments show that customers view periods that end with losses as being shorter than comparable intervals that end with gains.(Bilgin, B., & LeBoeuf, R. A. 2010).
More particularly in this study the framing will focus on time. We will use time framing because it is assumed that if specific duration of time is expressed in different quantities it will affect people’s process procedure and eventually it will have a reckonable effect on their decision. However, it should be mentioned that similar time frame have been used before in other studies in different domains. (Zhang YC, Schwarz N 2013) in their study they frame the time in “30 days,” ”31 days,” or “1 month and in “1 year,”12 months," or "52 weeks and they find out that when the time was expressed in days rather than months or in months rather than years the same duration seemed closer.
Furthermore, in their recent study of (Lewis, N., & Oyserman, D. 2015) investigated how the manipulation of time can affect people’s decisions and make them feel that an event is less distant when the time is communicated in a more granular metric. They expressed the same duration of time in finer-grained units. Specifically, they communicated the years in months and the months in days in order to test if this manipulation could possibly have an effect on people's decisions about savings. The findings of this study suggest that the participants were indeed affected from granularity and their intention to start saving sooner was four times bigger when the time was expressed in days rather than in years.
Policy support
In this study we used the support of “green” policies as a dependent variable and we tried to find out if there are any effects in people’s decision processing when the time is framed as more granular. There are several studies that suggest that when people perceive the risk of climate change as more immediate tend to support “green” policies easily. People's perceptions of risk are critical elements of the policymakers’ socio-political agenda.(Leiserowitz AA 2005). Perceived risk factors and climate change conceptual models influence policy financing options. ”Green” policies like funding for research into sustainable technologies and planting trees are the most popular policies among others (Bostrom A et. al., 2012). Climate change is a very
H1: We assume that when the duration of time is communicated as more granular (Days vs Years) people’s intentions, to support “green” policies, will become stronger.
According to (Jérôme Euzenat, Angelo Montanari.2005) time granularity can be defined as the power of resolution of a statement's temporal qualification. Providing a formalism with the idea of time granularity enables time information to be modeled in relation to various grained temporal domains. This does not just mean you can use different units of time e.g., months and days, representing time quantities in a particular flat temporal model but requiring more complex semantic issues related to the problem of assigning proper meaning to the relation of statements with the various temporal domains of a layered temporal model and moving from one domain to a coarser / finer one. Such an ability to provide and connect temporal representations of the same reality at various "grain rates" is both an effective research trend and an important requirement for many applications (e.g. incorporation of structured requirements and communication of agents).
Monga, A., & Bagchi, R. (2011) in their study show that the numerosity which can be explained as the use of numbers as a basis for decisions, such as those concerning quantities and probabilities have an important role on how people perceive time when this time is grained in different units. Granularity influences quantity communication and its consequences for customer choice and decision-making (Zhang YC, Schwarz N 2013). More specifically,
grained (e.g., 104 weeks) rather than coarse (e.g., 2 years) units (Zhang YC, Schwarz N 2013). For example, when asked to estimate the earliest and latest likely finalization dates of a project, people will infer a smaller time window when the speaker will describe the intended completion date as "in 52 weeks" rather than as "in 1 year"(Zhang YC, Schwarz N 2013).Their confidence in the calculation is affected by the width of the interval that they believe the true value is stored (Zhang YC, Schwarz N 2013). The pragmatic assumptions of people from the granularity of quantitative statement influence their decisions. In particular, customers are more likely to believe that an organization or a product will fulfill its promises if the promise is transmitted in fine-grained rather than coarse units(Zhang YC, Schwarz N 2013). Additionally, the more fine grain expression provides higher accuracy, resulting in estimates of a lower probable deviation from the communicated value.(Zhang YC, Schwarz N 2013).
Recent research has shown that, when a present action is communicated with a
fine-grained time metric then individuals perceive this action as more immediate.(Lewis, N., & Oyserman, D. 2015) Specifically, considering the future in days makes people feel more connected with their present self in the future. Therefore, when the connection between the future and the present self is perceived as stronger, from the people, they feel that their present and their future self are more connected and agreeable.It is very interesting that the more congruent the present and future self feel, the less likely people are to dismiss future rewards in favor of existing ones.(Lewis, N., & Oyserman, D. 2015) . People answer with the suggestion that a future event communicated in terms of days will take place sooner than the same event even expressed in terms of years and will therefore require action sooner.(Lewis, N., &
to them in a matter of days and not those that can happen to them later, in months or years. (Lewis, N., & Oyserman, D. 2015)
H2: We assume that granularity can increase the perceived concern of the people and therefore it can increase policy support.
A lot of researchers, in order to make people perceive time differently and in many cases to raise their concern, have used different expressions of time to generate different attitudes. Furthermore, there are past studies in different domains which have undoubtedly showed that people perceived risk as more intense and solid when that risk is communicated in day-framing distance rather than in year-framing distance.Temporary framing effects imitate those of
temporal distance in such a way that people feel the risk presented in a day (as opposed to a year) to be more timely and concrete.Therefore, holding the time period objectively unchanged (i.e., the present), each day's temporal frame evokes a different psychological cycle from each year's. Everyday-framing makes risks seem more immediate, more direct and real than every
year-framing leading to increased expectations of self-risk.(Chandran, S. and Menon, G., 2004).Therefore we include perceived concern as a potential mediator.
H3: We assume that people with lower skepticism will have a higher support for “green” policies compared to people with higher skepticism who will be more influenced by the time framing effect.
We also include skepticism as a potential moderator since environmental skepticism doubts the importance and reality of environmental problems (Jacques, 2006). Skepticism is considering the status of honesty as a virtue and the fear that the resulting noble obligation would be too difficult to be morally requested.The examination of the role of an appeal for dignity in galvanizing the American public to have personal and political intervention in climate
change.(Hedberg T. 2018). Environmental skepticism is a significant threat to achieve
H4: We assume that people with liberal political orientation have a higher support for “ green” policies compared to people with more conservative political orientations who will be more influenced by the time framing effect.
Conceptual Model
Methodology
The purpose of this study is to provide evidence for our initial hypotheses, by showing that, when the time is communicated in more granular units it makes people more willing to support “green” policies. This study has a 2x2 between subjects design, 2(Duration: 27 vs 41 years) X 2 (Time frame: Days vs Year). We also assumed that granularity will increase people’s concern about climate change and make them enhance “green” policies.Therefore, perceived concern was a mediator. Additionally, the political orientation and the skepticism of the participants used as moderators since it is expected to affect people’s willingness to support “green” policies. Therefore, 358 American adults were recruited and had to answer a series of questions including demographics and attention checks.
Manipulation of granularity.
point of no return was communicated in different ways. In the first scenario the point of no return expressed in 9,855 days while in the second one it was expressed in 27 years, which is the same duration with the 9,855 days. Similarly in the third scenario the time was communicated as 14,965 days while in the fourth and last scenario the time was presented as 41 years, which again is the same duration with the 14,965 days. After those four differently expressed periods, the scenario stated that, according to many scientists, that are experts in the environment domain, the planet is in a very critical point and the scientific community warn that “we will reach a crucial threshold beyond which it will be impossible to recover the planet back to a normal state.”.The aim of that time frame was to find out if the more granular expression of time will increase the people’s concern about the threat of climate change and eventually make them support more intensively “ green” policies for the resolvement or the containment of that global issue. Moreover, the two different durations were used to generalize and in order to confirm that a specific duration has no impact on people's perception of risk and the element that affects their decisions is granularity.
After exposing the participants to the article, several questions have been asked to them. Further on the different measures that are used will be explained .All the measures are in the same order as they have been asked in the survey.
Perceived concern.
(2010) Hornsey et al 2015. Participants respond on a 7-point Likert scale (1 = Not at all agree, 7 = Very much agree). The scale that the perceived concern was measured consisted of statements such as, I feel the consequences of climate change are inevitable for future generations, I am concerned about the consequences of climate change etc.
Policy support.
At this phase, we used a measure to give us insights about the people’s willingness to support “green” policies. Policy support was measured on a 7-point Likert scale ( 1 = Strongly oppose, 7 = Strongly support ). The scale that measured policy support contained 14 items and was derived from (Schultz et al., 2018 JEP and Tobler et al., 2012). This scale included items like: Upgrade existing infrastructure to improve wind and flooding resilience in residential areas, Increase the cost of gasoline, heating oil, natural gas, electricity, and other energy sources which are based on fossil fuels etc.
Skepticism.
there is just more reporting of it in the media these days, There is too much conflicting evidence about climate change to know whether it is actually happening etc.
Demographic questions are also asked to the participants such as age, gender, number of members that live in the same household and the state that they live. The educational background also measured. Also there were questions about the ethnicity and employment status.
Additionally we asked the participants to define their political orientation. On a 7-point Likert scale ( 1 = Very conservative, 7 = Very liberal) we also measured the political preferences of the participants.
Attention checks
Results
Attention checkAs a first step in the analysis we checked whether the participants had a high level of understanding and attention while completing the survey, through five attention check questions. We came to the realization that 50 participants didn’t have satisfying answers, therefore they had to be excluded from the further analysis. Finally, 308 participants of the survey were included in the final analysis, since they matched the criteria.
Manipulation check
Overall, the comparison of mean values for the support of “green” policies showed no significant differences across the four message conditions (Myear-27=5.41, Myear-41=5.48, Mdays-27=5.23, Mdays-41=5.39).
(Figure 2)
Potential Mediating Effect - Perceived concern
In order to confirm a mediating variable and its significance in the model, we must show that while the mediator is caused by the initial time frame and is a cause of the policy support, the initial effect of time framing on policy support becomes weaker when the mediator is included in the model.
We performed a mediation analysis using Andrew Hayes process model 4. Time frame was the independent variable, perceived concern as a mediator and policy support as dependent variable
Results revealed that time frame is not a significant predictor of policy support (β = -0,1259, SE =,1130, t = -1,1141, p = 0,266 , 95% CI = [-.3482,.0964]). However it is a significant predictor of perceived concern (β = -0,4556, SE = ,1785 , t = -2,552, p = 0,0112
, 95% CI = [-.8069,-.1044]). The effect between the perceived Concern and the policy support in
Mediation requires that the effect among all three variables will be statistically significant. However the results show that this is not the case here because the initial effect of the independent variable on the dependent variable is not significant.
In this case, while the independent variable was not significant predictor for both the dependent and the mediator variables, it is not significant in the presence of the mediator variable.
Potential moderating effect of skepticism
It is assumed that the variable Skepticism moderates the effect between time frame and policy support. In order to test this hypothesis we performed a moderation analysis, using Andrew Hayes process model 1. Time frame served as the independent variable, skepticism as the moderator and policy support as the dependent variable. Results revealed that time frame does not have a significant effect on policy support (β = 0,3403, SE = 0,2145 , t = 1,5866, p = 0, 1136
, 95% CI = [-0,0818 ,.0 ,7624]). While skepticism has a significant effect on policy support (β = -0,4230, SE = 0,1371 , t =-3,0857, p = 0,0022 , 95% CI = [-0,6927 ,.-0,1532]). The interaction effect between time frame and skepticism on policy support is significant (β = -0,1799, SE = 0,0841 , t = -2,1398, p = 0,0332 , 95% CI = [-0,3453 ,.-0,0145]). Therefore the variable Skepticism moderates the effect between the time frame and the policy support.
(Figure 3) : Conditional effects of skepticism on policy support.
It seems people in high skepticism have lower policy support than people with lower skepticism. When the skepticism is high it seems that the time framed as years led to higher policy support than the time framed as days, in contrast to the low skepticism, in which framing does not create any significant difference in support for policy.
H3: Is partially supported since it is confirmed that time frame has a stronger effect for
Potential effect of political orientation (DegreeofLiberal)
(Figure 4) : Conditional effects of political orientation on policy support.
H4: Is rejected since people with more conservative political orientation are not more influenced by time framing effect liberal political orientation are.
Discussion
The objective of this study was to investigate how granularity can raise people's awareness about climate change and as a result make them endorse more environmentally friendly policies.The hypotheses were set as follows: H1: We assume that when the duration of time is communicated as more granular (Days vs Years) people’s intentions, to support “green” policies, will become stronger, H2: We assume that granularity can increase the perceived concern of the people and therefore it can increase policy support,, H3: We assumed that people with lower skepticism will have a higher support for “green” policies compared to people with higher skepticism who will be more influenced by the time framing effect.H4: We assume that people with liberal political orientation have a higher support for “ green” policies compared to people with more conservative political orientations who will be more influenced by the time framing effect.
of time as closer. Evidence on numerosity shows that variations are magnified by small units (vs. large), as a jump from 7 to 21 (vs. 1-3) tends to be greater. In the same study it was also
mentioned that a delay expressed in small units (7-21 days) appears larger than that expressed in large units (1-3 weeks) as a change from 7 to 21 appears larger than a change from 1 to 3
(Monga, A., & Bagchi, R. 2011).
Furthermore, people are focused on the number of units of scale used to describe a certain difference and disregard the type of unit that offers quantitative details. Pelham,et.al., (1994) argue in their study that the unit effect appears because people’s concentration is not on the type of units in which information is represented (numerosity effect) but on the number. Taking these studies under consideration we can’t exclude the possibility that people perceived the more granular expression of the same duration of time as bigger.
Other studies also support the previous statements, that people tend to believe that higher number of units signal higher possibilities. People mistakenly believe that cancer is more
dangerous because statistics show that it affects 1,286 of every 10,000 people compared to 24,14 deaths per 100 people.(Yamagishi 1997; see also Raghubir 2008). A 10 winning and 90
non-winning lottery is considered as more preferable from the people than one with 1 winning and 9 non-winning possibilities.(Kirkpatrick and Epstein 1992; Denes-Raj and Epstein 1994).
Additionally, it seems that granularity indeed has an effect on how people perceive concern and that increase people's tendency to support “green” policies. According to that it can be noted that the results for H2 are as they were predicted. Similarly, for H3 the results are as they were predicted since it seems that indeed people with lower skepticism have higher support for “green” policies. On the other hand, people with higher skepticism are more influenced from the time frame, however, that happens in a contradicting direction. When the skepticism is high and the time is framed in years higher policy support can be observed than when the time is framed in days.
Finally, and against all predictions the political orientation seem to be uncorrelated with the people’s willingness to support “green” policies.This result is contradicting many previously established research. The sample size and the fact that all the participants are currently from the United States of America are elements that can be considered as limitations. In future research a larger and more diverse sample, with participants from other countries, should be used.
Conclusion
and political orientation will also have an effect on people’s willingness to support “green” policies. Nonetheless, skepticism does affect people’s decisions about “green” policies but political orientation of the participants is irrelevant with their willingness to support them.
Future research
Future research could focus more on gross-grained expression of time in combination with policy support intentions of the public. Results indicate that people’s tendency to support “green” policies is not affected by granular communication of time. In addition to that, initial explorations have suggested that future time perception is indeed malleable. An example of that are time intervals seeming longer when described by amounts of time instead of by
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Descriptive Statistics
Dependent Variable: Policy Support (Average)
time_frame_cod
Duration Condition (13,
27, 41 Years) Mean Std. Deviation N
year 27 5,412698413 ,88647720 81 41 5,489795918 ,93316159 70 Total 5,448438978 ,906182804 151 day 27 5,237451737 1,11048250 74 41 5,398450947 1,02671632 83 Total 5,322565969 1,066613266 157 Total 27 5,32903225 1,000248338 155 41 5,440242764 ,982884461 153 Total 5,384276438 ,991610048 308
Tests of Between-Subjects Effects
Dependent Variable: Policy Support (Average)
Source
Type III Sum
of Squares df Mean Square F Sig.
a. R Squared = ,008 (Adjusted R Squared = -,002) Perceived concern Model : 4 Y : Policy Support X : time frame M : perceived Concern Sample Size: 308 VARIABLE: Perceive Model Summary R R-sq MSE F df1 df2 p ,1444 ,0208 2,4524 6,5158 1,0000 306,0000 ,0112 Model
coeff se t p LLCI ULCI constant 6,2531 ,2839 22,0276 ,0000 5,6945 6,8117 time frame -,4556 ,1785 -2,5526 ,0112 -,8069 -,1044 OUTCOME VARIABLE: Policy Support Model Summary R R-sq MSE F df1 df2 p ,7298 ,5326 ,4626 173,7549 2,0000 305,0000 ,0000 Model
Direct effect of X on Y
Effect se t p LLCI ULCI ,0842 ,0783 1,0749 ,2833 -,0700 ,2384 Indirect effect(s) of X on Y:
Effect BootSE BootLLCI BootULCI Perceive -,2101 ,0848 -,3846 -,0485
****************** TOTAL EFFECT MODEL ************** OUTCOME VARIABLE: Policy Support Model Summary R R-sq MSE F df1 df2 p ,0636 ,0040 ,9825 1,2412 1,0000 306,0000 ,2661 Model
coeff se t p LLCI ULCI constant 5,5743 ,1797 31,0235 ,0000 5,2207 5,9279 time_fra -,1259 ,1130 -1,1141 ,2661 -,3482 ,0964
******TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y *******
Total effect of X on Y
Effect se t p LLCI ULCI -,1259 ,1130 -1,1141 ,2661 -,3482 ,0964
Direct effect of X on Y
Effect se t p LLCI ULCI ,0842 ,0783 1,0749 ,2833 -,0700 ,2384
Indirect effect(s) of X on Y:
Effect BootSE BootLLCI BootULCI Perceive -, 2101 , 0841 -, 3771 -, 0463
Perceive -,2119 ,0826 -,3733 -,0473 Skepticism Model : 1 Y : PolicySupport X : time_frame W : Skepticism Sample Size: 308
OUTCOME VARIABLE: PolicySupport Model Summary
R R-sq MSE F df1 df2 p ,6984 ,4877 ,5087 96,4766 3,0000 304,0000 ,0000 Model
coeff se t p LLCI ULCI constant 6,5157 ,3465 18,8056 ,0000 5,8339 7,1975 time_fra ,3403 ,2145 1,5866 ,1136 -,0818 ,7624 Skepticim -,4230 ,1371 -3,0857 ,0022 -,6927 -,1532 Int_1 -,1799 ,0841 -2,1398 ,0332 -,3453 -,0145 Product terms key: Int_1 : time_fra x Skeptici
Test(s) of highest order unconditional interaction(s): R2-chng F df1 df2 p X*W ,0077 4,5786 1,0000 304,0000 ,0332 ---
Focal predict: time_fra (X) Mod var: Skeptici (W)
Policy Support Model : 1 Y : PolicySupport X : time_frame W : DegreeofLiberal Sample Size: 308
OUTCOME VARIABLE: PolicySupport Model Summary
R R-sq MSE F df1 df2 p ,4079 ,1664 ,8278 20,2292 3,0000 304,0000 ,0000 Model
coeff se t p LLCI ULCI constant 4,9926 ,5021 9,9437 ,0000 4,0046 5,9806 time_fra -,4516 ,3071 -1,4705 ,1425 -1,0558 ,1527 Degreeof ,1219 ,1049 1,1617 ,2463 -,0846 ,3284 Int_1 ,0781 ,0644 1,2138 ,2258 -,0485 ,2048 Product terms key: Int_1 : time_frame x DegreeofLiberal Test(s) of highest order unconditional interaction(s):
R2-chng F df1 df2 p X*W ,0040 1,4732 1,0000 304,0000 ,2258 ---
Focal predict: time_fra (X) Mod var: Degreeof (W)
Conditional effects of the focal predictor at values of the moderator(s): Degreeof Effect se t p LLCI ULCI
"OUR PLANET REACHES THE POINT OF NO RETURN IN
DAYS/YEARS", SCIENTISTS WARN
(Appendix 1) By Sam McGraw
Wednesday, December 18
Governments around the world must take "rapid, far-reaching and unprecedented changes in all aspects of the society" to prevent disastrous consequences of global warming, says a stark new report issued last month by the UN Intergovernmental Panel on Climate Change (IPCC ), the global scientific authority on climate change. The report, which came out in November, says the planet will reach the crucial threshold of 1.5 degrees Celsius (2.7 degrees Fahrenheit) above pre-industrial levels by as early as 9,855 days from now, precipitating the risk of extreme and frequent droughts, wildfires, floods, earthquakes, and severe food shortages for hundreds of millions of Americans and people around the world. With every degree of global warming, individuals’ health and wellbeing will be dramatically impacted by the realities and dangers of a warmer world.
“What makes this report particularly unique is that it provides concrete estimates of the so-called point of no return based on our current trajectory of emissions,” says Thomas Wirth, the IPCC spokesperson. According to the report, scientists forecast that in 9,855 days, we will reach a crucial threshold beyond which it will be impossible to recover the planet back to a normal state. In the US alone, the increased frequency and variety of natural disasters such as ultra-intense hurricanes Harvey, Florence, and Dorian as well as massive and extreme wildfires, floods and droughts across the country are pointed as harbingers of a warming globe and irreversible climate change threshold we are reaching in the next 9,855 days.
“It is possible to limit global warming to 1.5 degrees Celsius but doing so would require
(Appendix 2)
Perceived Concern Likert Scale
1) I feel climate change will affect my life and well-being soon. 2) I believe that climate change has to be tackled quickly.
3) I feel that the negative effects of climate change are of considerable urgency. 4) I feel climate change will affect the U.S soon.
5) I feel climate change will soon harm the environment in which my family and I live. 6) I feel the consequences of climate change are inevitable for future generations. 7) I am concerned about the consequences of climate change.
8) Climate change poses a serious threat to my health and well-being. 9) Climate change poses a serious threat to the natural environment. 10) Climate change poses a serious threat to the U.S.
11) The impact of climate change around the world is significant. 12) Climate change is an important issue.
(Appendix 3)
Skepticism Likert Scale
1) Claims that human activities are changing the climate are exaggerated. 2) Climate change is just a natural fluctuation in earth’s temperatures. 3) I don't believe climate change is a real problem.
4) I am uncertain whether climate change is really happening. 5) It is too early to say climate change is really a problem. 6) The evidence for climate change is unreliable.
7) There is too much conflicting evidence about climate change to know whether it is actually happening.
8) Climate change is too complex and uncertain for scientists to make useful forecasts. 9) Too much fuss is made about climate change.
10) Floods and heat-waves are not increasing, there is just more reporting of it in the media these days.
11) Many leading experts still question if human activity is contributing to climate change 12) The media is often too alarmist about climate change.
(Appendix 4)
Policy support Likert scale.
1) Provide government incentives for home modifications that improve energy efficiency. 2) Require automakers to increase the fuel efficiency of cars, trucks, and SUVs.
3) Require electric utility companies to increase their production from renewable energy sources.
4) Upgrade existing infrastructure to improve wind and flooding resilience in residential areas.
5) Regulate carbon dioxide as a pollutant.
6) Require businesses to invest in green roofs and other green infrastructures.
7) Increase the cost of gasoline, heating oil, natural gas, electricity, and other energy sources which are based on fossil fuels.
8) Improve infrastructure for public transportation (such as buses and subways). 9) Increase the cost of water heating & consumption for the average household. 10) Provide subsidies for research projects in the field of climate-friendly technology.
11) Improve early warning systems in cities to inform residents about the weather and natural hazard-related risks.
12) Require energy-efficient home designs.
13) Increase fares for public transportation (such as buses and subways) to offset energy costs.
