# Recall Bias of Environmental Campaigns

Michela Limardi

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# Recall Bias of Environmental Campaigns

Michela Limardi*

October 21, 2022

## Abstract

Environmental campaigns aim to increase the environmental awareness of individuals and induce a pro-environmental behavior. One of the criteria used to assess the effectiveness of a campaign is to ask people if they recall the campaign. However, a bias may exist in recalling campaigns according to the environmental behavior of individuals. The goal of this study is to measure this potential recall bias. We use an original survey conducted by a French Non-profit Organization in Paris region to assess the effectiveness of its drug recycle campaigns. We first conduct a probit analysis of the probability of an individual remembering the campaign and then we apply the difference-in-difference method. Our findings show that there is a systematic recall bias of the campaigns according to the environmental behavior of the respondent. This recall bias might be related to the type of message delivered. This finding implies that deeper reflection is needed in order to find the right message to successfully reach the target group of environmental campaigns, i.e. individuals with low environmental awareness.

Keywords: NGOs, Environmental Campaigns, Pro-environmental behavior

JEL: Q50, Q48

## 1 Introduction

Environmental campaigns aim to increase the environmental awareness of individuals and induce a pro-environmental behavior. Many resources are devoted to the organization of environmental

<footnote>*University of Lille (RIME) and University of Paris 1 (CES), email: michela.limardi@univ-paris1.fr</footnote>
campaigns, but still little is known about the actual effectiveness of those campaigns. One of the methods used to assess the effectiveness of environmental campaigns is to conduct a survey, after the end of the campaign, and ask if an individual remembers it. The higher the percentage of respondents remembering it, the more effective the campaign is considered to be. This method is normally used in the advertising literature on how to measure the success of campaigns. However, it is worth considering that recalling environmental campaigns might be related to some specific individual characteristics of the respondents.

The main idea of this article is that a bias may exist in recalling environmental campaigns according to the environmental behavior of individuals. This bias may affect ex-post evaluations of environmental campaigns. We want to measure this potential bias and investigate the main reasons behind that. We use an original survey conducted by a French non-profit organization, Cyclamed, in the Paris region to assess the effectiveness of its drug recycle campaigns. Cyclamed, which is responsible for drug disposal in France, regularly carries out environmental campaigns throughout the subway system in the Paris region. This is the region where drug recycling is the lowest in France. The aim of these campaigns is to increase the number of individuals recycling their unused or expired drugs. First, we conduct a Probit analysis of the probability of an individual remembering the campaign. Then we apply the difference-in-difference method, which allows us to estimate the difference between individuals who were exposed to the campaigns and those who were not, interacted with an individual dummy of the individual's recycling behaviour prior to the campaign.

Our findings show that there is a systematic recall bias of the campaigns according to the environmental behavior of an individual. Respondents who recycle drugs systematically remember the campaigns more than those who do not. They also appreciate the campaigns more than the non-recycling respondents and find them clearer and more convincing on the utility of recycling drugs for the environment. Interestingly, this effect does not depend on how often they were exposed to the subway campaign. This Recall bias of environmental campaigns might then reduce their potential impact by attracting the attention of people who are already interested in an environmentally-friendly behavior. This implies that deeper reflection is needed in order to find the right message to successfully reach the target group of environmental campaigns, i.e. individuals with low environmental awareness.
There is much literature on the role of environmental advertising in the private sector. The objective of many firms today is to provide a "green" image of their products to consumers. Studies show the effectiveness of this kind of green advertising according to different mechanisms (Minor & Morgan, 2011; Cabral, 2005; Kahn, 2007; Barrage et al., 2020). Several studies in the business literature consider recall as a measure of the effectiveness of advertising slogans (Molian, 1993; Dass et al., 2014; Kohli et al., 2013). Kohli et al. (2013) shows how the amount of media exposure have the biggest influence on slogan recall. However, few studies exist on the effectiveness of environmental campaigns conducted by the state or environmental non-profit organizations to raise environmental awareness. As far as we know, this is the first study that investigates the recall bias of an environmental campaign according to the environmental behavior of an individual, a factor that might reduce the potential impact of the campaign.

# 2 Empirical Analysis

## 2.1 Descriptive statistics

Cyclamed has conducted three campaigns in the subway system in the region of Paris: in February 2019, November 2019 and March 2020. Each campaign consisted in several posters placed in the subway and lasts one week.<fnref n="1" /> A survey is conducted after the end of each campaign to assess its effectiveness. We use data collected through these campaign evaluation surveys, which provides cross-sectional data and information of individual characteristics: income, job, home city, age, sex, the size of the household and if the individual is responsible of the drug recycling in the household. Our main variable of interest is the recycling behavior of the respondent before the campaign and whether or not they remembers the campaign. The variable *recycle* equals one if the respondent recycle drugs and zero otherwise; the variable *recall* equals one if the respondent remembers the campaign and zero otherwise. For each campaign, Table 1 shows the number of people surveyed (Column 1), the percentage of people recycling drugs (Column 2) and the percentage of people who remember the poster campaigns (Column 3). Almost 70 percent of the people surveyed recycle drugs and 36 percent of the sample remember the campaign.² In

<footnote n="1">¹The posters used in the three campaigns are included in the Appendix.
²This average 70 percent corresponds to the percentage of people declaring recycling drugs in the region of Paris in other surveys conducted by Cyclamed.</footnote>
the survey, the respondents were also asked to identify the organization (non-profit, profit or the State), that carried out the drug recycling campaign. Table 1 shows the percentage of people attributing the campaign to Cyclamed (Column 4), other NGOs (Column 5), the State (Column 6), pharmacies (Column 7) or Citeo (Column 8), a private organization that manages the disposal of other products. In the question concerning the organization that conducted the campaign, the response option of the State and Citeo was introduced in the survey of the last campaign, March 2020. On average, almost 40 percent of people attributes the campaigns to the right organization, Cyclamed.

## 2.2 Identification Strategy

In France, people can recycle unused or expired drugs by bringing them to any pharmacy.<fnref n="3" /> Cyclamed is a French Non-profit Organization that is in charge of the national system of drug disposal. It has been authorized by the State to manage the entire process.<fnref n="4" /> Therefore there is no other competitor in the drug disposal sector in France that could act as an external driver for the strategies of Cyclamed, such as the amount of resources to be devoted to environmental campaigns. Cyclamed's objective is to increase the number of people recycling drugs. The annual financial resources of Cyclamed are provided by pharmaceutical firms according to the "polluter pays" principle. Therefore, it does not even face the issue of providing certain outcomes to increase donations as other environmental Non-profit organizations do. Each year Cyclamed devotes almost 30 percent of its total annual budget to awareness-rising campaigns.

The Cyclamed campaigns are placed throughout the subway system in Paris region (Ile de France) for one week. After the end of the campaign a survey is conducted. More than the half of the individuals (60 percent) in the sample were surveyed the day after the end of the campaign while the other 40 percent were surveyed two days after. We exploit this time delay in the survey in order to estimate the recall bias. We use also the information on the recycling behavior of the individual, and the frequency of using the subway in the last week, to identify the impact of the participant's recycling behaviour on the recall bias of the campaign. We estimate the following

<footnote n="3">³In France it is mandatory under the law for pharmacies to accept unused or expired drugs and individuals are not paid for that.</footnote>

<footnote n="4">⁴The drug disposal process consists of collecting unused and expired drugs in the pharmacies and transporting them to recycling platforms. They are then incinerated in an environmentally-friendly process to release energy.</footnote>
model:

$$Pr(recall_{itd} = 1) = F(\alpha + \beta_1 recycle_i + \beta_2 exposure_i + \beta_3 X_i + \eta_t + \eta_d + \epsilon_{idt}) \quad (2.1)$$

where *recall* is a dummy variable that equals one if the individual *i* remembers the campaign and zero otherwise. Variable *exposure* can take values between 1 and 3 corresponding to the answers to the question on the number of trips taken on the subway in the previous week: *exposure* equals 3 if the answer is "every day", 2 if the answer is "yes, between 2 and 5 " and 1 if the answer is "yes, just one". We control for a set of respondents' characteristics: income, sex, age, job, household size. We put in all regressions campaign fixed effects $\eta_d$ and department fixed effects $\eta_d$. We cluster the standard error at department level. Finally, $\epsilon_{idt}$ is the error term.

Second, we exploit a set of questions in the survey to assess the attractiveness of the campaign. The interviewer shows the posters to the respondents and they have to assign a degree of attractiveness to each poster. We exploit these answers in order to identify a potential mechanism of the recall bias. We perform a difference in difference analysis. Our treatment are people potentially exposed to the subway campaign. The variable *Texposure* is a dummy variable that equals one if the respondent took the subway at least once during the Cyclamed campaign, and zero if he did not take the subway in the previous week. We run the following equation:

$$Y_{itd} = \alpha + \beta_1 norecycle_i + \beta_2 Texposure_i + \beta_3 norecycle_i * Texposure_i + \beta_4 X_i + \eta_t + \eta_d + \epsilon_{idt} \quad (2.2)$$

where *Y* is the level of attractiveness of a poster for an individual *i* that can take values between 1 and 10, where 1 means people completely disagree and 10 people completely agree to the following three sentences: "The message of the posters is clear" (Clear), "I like these posters" (Like), "These posters are convincing on the utility of recycling drugs for the environment" (Env). The variable *norecycle* equals 1 if the respondent did not recycle drugs prior to the campaign and zero otherwise. We interact the exposure dummy *Texposure* with the dummy of the individual's recycling behavior *norecycle*. We control as before for a set of respondents' characteristics:
income, sex, age, job, sizehousehold. We put in all regressions campaign fixed effects $\eta_d$ and
department fixed effects $\eta_{d'}$. We cluster the standard error at department level. Finally, $\epsilon_{idt}$ is the
error term.

## 2.3 Results

The results of our baseline estimation (2.1) are reported in Table 3. Columns (1) to (3) report the estimations of a specification that pools all respondents. The coefficient of our variable of interest *recycle* is positive and highly significant in all specifications. There is a systematic recall bias of the campaigns according to an individual’s environmental behavior. In Column (4) and (5) we split the sample in individuals surveyed the day after the end of the campaign (column 4) and individuals surveyed two days after the end of the campaign (column 5). It is interesting that for people interviewed two days after the end of the campaign, the magnitude of the variable *recycle* becomes even larger than the variable *exposure*. However, the recall bias can be different if the respondent knows Cyclamed even if he does not recycle drugs. Table 4 shows the results of the probit regression when we control for variables related to the attribution of the campaigns namely *cyclamed*, *NGO*, *State*, *pharmacies* and *citeo*. The attribution to the right organization, Cyclamed, positively affects the probability of recalling the campaign, however the variable *recycle* remains positive and highly significant. In contrast, a wrong attribution to another *NGO* (such as Green-peace, Unicef, WWf) or the State reduces the probability of recalling the campaign.<fnref n="5" />

This recall bias might be related to the type of message delivered. Table 2 presents the mean values of the variables *recall*, *exposure*, *Clear*, *Env* and *Like* for people recycling drugs and not recycling drugs. There is a statistically-significant difference in the average values of the two groups for the three variables concerning the assessment of the campaigns by the respondents. Importantly, there is no statistically significant difference in the average value of the variable *exposure*. The results of equation 2.2 are reported in Table 5. The results show that individuals who do not recycle drugs systematically appreciate the campaigns less and find the posters less clear and convincing on the utility of recycling drugs for the environment than individuals who do recycle drugs. Interestingly, this effect does not depend on the exposure to the subway campaign.

<footnote n="5">⁵This result supports our premise, where a bad attribution corresponds to less clear information.</footnote>
# 3 Conclusion

In this paper we have studied the potential recall bias of environmental campaigns, using data from original surveys conducted in the region of Paris after the end of drug disposal campaigns. First, we perform a Probit analysis, to estimate the probability of an individual remembering the campaign. Then we apply the difference-in-difference method, which allows us to estimate the difference between individuals who were exposed to the campaigns and those who were not, interacted with an individual dummy of the individual's recycling behaviour prior to the campaign.

Our findings show that there is a systematic recall bias of the campaigns according to the environmental behavior of an individual. Respondents who recycle drugs remember more the campaigns than respondents who do not. This recall bias might be related to the type of message delivered. We find that respondents recycling drugs appreciate the campaigns more and find them clearer and more convincing on the utility of recycling drugs for the environment than non-recycling individuals. Interestingly, this effect does not depend on the degree of exposure to the subway campaign. Recall bias of environmental campaigns may then reduce the potential impact of an environmental campaign by drawing the attention of people already concerned with an environmentally-friendly behavior. More research, like focus group analysis of advertising product campaigns, is needed to identify the most appropriate message of environmental campaigns to successfully capture the attention of the right target audience, i.e. non recycling individuals.
References

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Cabral, L. M. B. (2005). The economics of trust and reputation : A primer.

Dass, M., Kohli, C., Kumar, P., & Thomas, S. (2014). A study of the antecedents of slogan liking.
*Journal of Business Research*, 67(12), 2504–2511.

Kahn, M. (2007). Do greens drive hummers or hybrids? environmental ideology as a determinant of consumer choice. *Journal of Environmental Economics and Management, 54*, 129–145.

Kohli, C., Thomas, S., & Suri, R. (2013). Are you in good hands?: slogan recall: what really matters. *Journal of Advertising Research, 53*(1), 31–42.

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Molian, D. (1993). 'i am a doughnut': Lessons for the sloganeer. *European Business Journal*, 5(2), 40.
<table><caption>Table 1: **Recycle, Recall and Attribution of Cyclamed Campaigns: percentage of respondents**</caption><thead><tr><th>campaign</th><th>nb observations<br>(1)</th><th>recycle<br>(2)</th><th>recall<br>(3)</th><th>cyclamed<br>(4)</th><th>NGO<br>(5)</th><th>State<br>(6)</th><th>pharmacy<br>(8)</th><th>citeo<br>(9)</th></tr></thead><tbody><tr><td>February 2019</td><td>1044</td><td>0.66</td><td>0.28</td><td>0.47</td><td>0.29</td><td>n.a.</td><td>0.23</td><td>n.a.</td></tr><tr><td>November 2019</td><td>1039</td><td>0.72</td><td>0.38</td><td>0.40</td><td>0.40</td><td>n.a.</td><td>0.20</td><td>n.a.</td></tr><tr><td>March 2020</td><td>1045</td><td>0.73</td><td>0.40</td><td>0.36</td><td>0.16</td><td>0.30</td><td>0.14</td><td>0.03</td></tr><tr><td>Average</td><td>1042.67</td><td>0.71</td><td>0.36</td><td>0.41</td><td>0.28</td><td>0.10</td><td>0.19</td><td>0.01</td></tr></tbody></table>

*recycle* equals one if respondent recycles drugs and zero otherwise; *recall* equals 1 if respondent remembers the campaigns and zero otherwise; variables *Cyclamed*, *NGO*, *State*, *Pharmacy* and *Citeo* have values between 0 and 1, where 1 means people attribute the campaign respectively to each organization.
<table><caption>Table 2: Assessment of the advertising campaign. People recycling drugs compared to people not recycling drugs</caption><thead><tr><th>recycle</th><th>recall</th><th>exposure</th><th>Clear</th><th>Env</th><th>Like</th></tr></thead><tbody><tr><td>(1) Not recycle</td><td>.2721382<br>(.0146335)</td><td>1.641469<br>(.0409303)</td><td>6.844809<br>(.0756644)</td><td>6.403141<br>(.0985914)</td><td>6.291209<br>(.077121)</td></tr><tr><td>(2) recycle</td><td>.3914623<br>(.0104035)</td><td>1.634423<br>(.0261046)</td><td>7.756264<br>(.0430389)</td><td>7.625414<br>(.0518164)</td><td>7.378043<br>(.0444077)</td></tr><tr><td>(3) Difference</td><td>-.1193241<br>(.0186396)</td><td>.0070454<br>(.0482178)</td><td>-.9114555<br>(.0826433)</td><td>-1.222272<br>(.1037569)</td><td>-1.08683<br>(.0848744)</td></tr><tr><td>(4) t-test diff</td><td>-6.4017***</td><td>0.1461</td><td>-11.0288***</td><td>-11.7802***</td><td>-12.8052***</td></tr></tbody></table>

*recycle* equals one if respondent recycles drugs and zero otherwise; *recall* equals 1 if respondent remembers the campaigns and zero otherwise. *exposure* can take values between 1 and 3 corresponding to the answers to the questions on the number of trips taken on the subway in the previous week: equals 3 if the answer is "every day", 2 if the answer is "yes, between 2 and 5 " and 1 if the answer is "yes, just one". The variables *Clear*, *Like*, *Env* have values between 1 and 10, where 1 means people completely disagree and 10 people completely agree to the following three sentences: "The message of the posters is clear" (Clear), "I like these posters" (Like), "These posters are convincing on the utility of recycling drugs for the environment" (Env).
<table><caption>Table 3: Probit regression - pooled cross section. Recycle and The date of interview</caption><thead><tr><th></th><th colspan="5">Dependent variable: Recall</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th></tr><tr><th></th><th>Full sample<br>Coef./se</th><th>Full sample<br>Coef./se</th><th>Full sample<br>Coef./se</th><th>Day after<br>Coef./se</th><th>Two days after<br>Coef./se</th></tr></thead><tbody><tr><td>recycle</td><td>0.391***<br>(0.05)</td><td>0.432***<br>(0.05)</td><td>0.435***<br>(0.06)</td><td>0.426***<br>(0.08)</td><td>0.509***<br>(0.10)</td></tr><tr><td>exposure</td><td>0.491***<br>(0.03)</td><td>0.448***<br>(0.03)</td><td>0.437***<br>(0.03)</td><td>0.459***<br>(0.03)</td><td>0.414***<br>(0.04)</td></tr><tr><td>age</td><td></td><td>-0.007***<br>(0.00)</td><td>-0.009***<br>(0.00)</td><td>-0.012***<br>(0.00)</td><td>-0.002<br>(0.00)</td></tr><tr><td>N</td><td>3128</td><td>3112</td><td>3089</td><td>1891</td><td>1190</td></tr><tr><td>Campaign fixed effect</td><td>No</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Department fixed effect</td><td>No</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Control variables</td><td>No</td><td>No</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

The dependent variable *recall* equals 1 if respondent remembers the campaigns and zero otherwise; *recycle* equals one if respondent recycles drugs and zero otherwise; *exposure* can take values between 1 and 3 corresponding to the answers to the questions on the number of trips taken on the subway in the previous week: equals 3 if the answer is "every day", 2 if the answer is "yes, between 2 and 5" and 1 if the answer is "yes, just one". Sample in column (4) corresponds to individuals surveyed the day after the end of the campaigns, in column (5) individuals surveyed two days after the end of the campaigns. Control variables include: job, revenue, studies, sex. Standard error in parentheses, with * indicating significance at 0.10, ** indicating significance at 0.05 and *** indicating significance at 0.001. Cluster at department level.
<table><caption>Table 4: Probit - pooled cross section. Campaign attribution</caption><thead><tr><th colspan="6">Dependent variable: Recall</th></tr><tr><th></th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th></tr><tr><th></th><th>Coef./se</th><th>Coef./se</th><th>Coef./se</th><th>Coef./se</th><th>Coef./se</th></tr></thead><tbody><tr><td>recycle</td><td>0.401***<br>(0.07)</td><td>0.424***<br>(0.07)</td><td>0.418***<br>(0.07)</td><td>0.426***<br>(0.07)</td><td>0.427***<br>(0.07)</td></tr><tr><td>exposure</td><td>0.451***<br>(0.03)</td><td>0.448***<br>(0.03)</td><td>0.451***<br>(0.03)</td><td>0.450***<br>(0.03)</td><td>0.450***<br>(0.03)</td></tr><tr><td>cyclamed</td><td>0.300***<br>(0.06)</td><td></td><td></td><td></td><td></td></tr><tr><td>NGO</td><td></td><td>-0.202***<br>(0.03)</td><td></td><td></td><td></td></tr><tr><td>State</td><td></td><td></td><td>-0.337***<br>(0.10)</td><td></td><td></td></tr><tr><td>pharmacy</td><td></td><td></td><td></td><td>-0.038<br>(0.05)</td><td></td></tr><tr><td>citeo</td><td></td><td></td><td></td><td></td><td>0.032<br>(0.38)</td></tr><tr><td>N</td><td>3057</td><td>3057</td><td>3057</td><td>3057</td><td>3057</td></tr><tr><td>Campaign fixed effect</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Department fixed effect</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Control variables</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

The dependent variable *recall* equals 1 if respondent remembers the campaigns and zero otherwise; *recycle* equals one if respondent recycles drugs and zero otherwise; *exposure* can take values between 1 and 3 corresponding to the answers to the questions on the number of trips taken on the subway in the previous week: equals 3 if the answer is "every day", 2 if the answer is "yes, between 2 and 5" and 1 if the answer is "yes, just one". variables *cyclamed*, *NGO*, *State*, *pharmacy* and *citeo* have values between 0 and 1, where 1 means people attribute the campaign respectively to each organization. Control variables include: job, revenue, studies, sex. Standard error in parentheses, with * indicating significance at 0.10, ** indicating significance at 0.05 and *** indicating significance at 0.001. Cluster at department level.
<table><caption>Table 5: OLS regression - pooled cross section</caption><caption>Dependent variable: Clear (1), Like (2), Env (3)</caption><thead><tr><th></th><th>1<br>Coef./se</th><th>2<br>Coef./se</th><th>3<br>Coef./se</th></tr></thead><tbody><tr><td>Exposure*Norecycle</td><td>0.473<br>(0.31)</td><td>0.354<br>(0.33)</td><td>0.643<br>(0.41)</td></tr><tr><td>Exposure</td><td>0.163<br>(0.13)</td><td>0.304**<br>(0.11)</td><td>0.210<br>(0.18)</td></tr><tr><td>norecycle</td><td>-1.186***<br>(0.24)</td><td>-1.209***<br>(0.25)</td><td>-1.576***<br>(0.35)</td></tr><tr><td>r2</td><td>0.271</td><td>0.300</td><td>0.342</td></tr><tr><td>N</td><td>3054</td><td>3031</td><td>2045</td></tr><tr><td>Campaign fixed effect</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Department fixed effect</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Control variables</td><td>Yes</td><td>Yes</td><td>Yes</td></tr></tbody></table>

The dependent variables *Clear* (column 1), *Like* (column 2), *Env* (column 3), have values between 1 and 10, where 1 means people completely disagree and 10 people completely agree to the following three sentences: "The message of the posters is clear" (Clear), "I like these posters" (Like), "These posters are convincing on the utility of recycling drugs for the environment" (Env). *norecycle* equals one if respondent does not recycle drugs and zero otherwise. The variable *Exposure* is a dummy variable that equals one if the respondent took the subway at least once during the Cyclamed campaign, and zero if he did not take the subway in the previous week. Control variables include: job, revenue, studies, sex. Standard error in parentheses, with * indicating significance at 0.10, ** indicating significance at 0.05 and *** indicating significance at 0.001. Cluster at department level.