4.1.2. Assumption

It was assumed that if the respondent reports no recycling behavior in his/her household, then the respondent do not recycle at home. However, some over-reporting of individual recycling behavior is possible where the respondent do not recycle but someone else in the household does. This possibility is captured in the responsibility item of the recycling behavior construct.

#### **5. Results and Discussion**

#### *5.1. Sample Profile (Demographic Composition)*

This study targeted a representative sample of households in the larger urban areas in South Africa. A total of 2004 households in 11 large urban areas, including all metropolitan municipalities, were interviewed. The demographic composition of the sample is provided in Appendix A, Table A1. Table 1 shows the descriptive statistics for each of the constructs (the latent variables), i.e., the means, as well as the values per percentiles. Tables 2–6 include descriptive statistics for each of the items per construct. The results from each construct are discussed in detail in the sections to follow, concluding with the TPB structural equation model (Tables 7–10).


**Table 1.** Descriptive statistics for the latent variables, mean scores, and percentiles (*n* = 2004).

> Where 1 = the lowest possible score, and 7 = highest possible score.

## *5.2. Recycling Behavior*

Of the total sample group (*n* = 2004), 540 of the respondents' households (26.9%) reported recycling behavior. The rest of the respondents (*n* = 1464; 73.1%) with a recycling behavior score of 1 (B = 1), reported no recycling activity in their households. The 26.9% recycling households includes those who, for example, reported very little recycling of one type of recyclable material only. Eighteen percent (18.5%) show very little recycling activity, which is indicated with a recycling score of 2–3. Only 3.3% of the respondents reported that their households often recycle about half or more of all their recyclables (recycling scores greater than 4). The low mean recycling behavior score (x-bar =1.44) confirms the low percentage of households in which recycling behavior is reported (Table 2).


**Table 2.** Descriptive statistics for the recycling behavior measurement and the separate items that make up the construct.

Where 1 represents no recycling activity and 7 represents the best possible mean value for recycling behavior. \* Qualitative measurement of recycling quantities (refer to Section 3.3.1).

The recycling behavior construct consists of three components: a "recycling frequency"-item; a "taking responsibility for recycling in the household"-item; and a "recycling quantity"-item (Table 2). Recycling quantity is measured by the average of the "quantities" reported to be recycled of each of five recyclables (paper, plastic, glass, metal, and compost) reported as being recycled. A comparison of the three main components that make up the recycling behavior construct shows that the average for recycling frequency (x-bar = 1.76) is higher than for taking responsibility (x-bar = 1.44) and for quantities recycled (x-bar = 1.35) (Table 2, main components). In addition, some respondents (3.4%) indicated that their households sometimes recycle, but failed to indicate recycling quantities of any recyclable materials. These 68 respondents form part of the 18.5% respondents that reported very little recycling activity. The data thus sugges<sup>t</sup> some over-reporting of recycling behavior which mainly originates from the frequency item. Being one of seven items in the behavior construct, the effect of the over-reporting of recycling frequency on recycling behavior is smaller than it would have been if recycling frequency was the only item measured for recycling behavior.

The overall higher self-reporting for recycling frequency compared to recycling quantities is most probably due to two reasons: firstly, it is easier to over-report recycling behavior on a "soft" frequency measurement than on actual physical quantities of items recycled; and secondly, the frequency question was asked first and thus before the reality check of the actual quantities. A possible third reason is that there is no correlation between recycling frequency and recycling quantities. However, the data show that the correlations are significant (*p* < 0.001) and of medium to high strength, depending on the recyclable material [68], i.e., correlation factors between recycling frequency and the "quantity" of paper, glass, metal, plastic, and compostables are 0.723, 0.648, 0.496, 0.671, and 0.467, respectively (Appendix A, Table A2). It is noteworthy that paper recycling is probably the most-established in South Africa, with the Ronnie bag collection system operating in many areas for more than 30 years.

Due to the random probability-sampling method the results for recycling behavior can be extrapolated to the South African population in the larger urban areas of the country. Given that the self-reported recycling behavior is expected to be higher than what it would be if measured [30,45], the reported results may reflect an optimistic view of the domestic recycling situation in South Africa. However, it should be noted that the purpose of the study was not to gather actual recycling-rate data. Although self-reported, the recycling behavior results provide valuable insight into recycling tendencies in South Africa at a given point in time—after the NEWWA came into effect but before wide implementaton of separation of waste.

The domestic recycling reality, as indicated by the results of this South African study, is that, at the time of the waste recycling survey (November 2010), the majority of South African households (73.1%) in large urban areas did not recycle. Only a small fraction of urban households (3.3%) recycled most of their household waste on a fairly frequent basis.

#### *5.3. Intention to Recycle*

The majority of respondents either expressed no intention to recycle or low levels of intention to recycle (x-bar = 3.76) (Table 3). The results sugges<sup>t</sup> that respondents are more likely to recycle if their recyclables are collected at curbside (x-bar = 4.21) than when they have to take recyclables to collection points (x-bar = 3.42). The likelihood that respondents will recycle also decrease the further the collection points are from their homes. The item that shows the lowest mean score (x-bar = 3.33) is the one implying travelling to a collection point the furthest away.


**Table 3.** Descriptive statistics for the intention of respondents to recycle.

Where 1 = the option very unlikely or not willing at all (no intention), and 7 = the option very likely or very willing (high level of intention).

It should be noted that the items are phrased to capture perceived distances, because a 2 km distance is just around the corner for someone who can drive there, but for someone who has to carry a bag of recyclables, it is a long distance. The role of the convenience factor in intention to recycle is emphasized by the difference in mean scores of two of the items, namely " ... if curbside collection for recyclables in area" (x-bar = 4.21) and "if to put recyclables out separately for curbside collection" (x-bar = 3.92). The latter, through the use of the word "separately", implies multiple sorting of recyclables, which is not so explicitly expressed in the first item. The results thus sugges<sup>t</sup> that people would be more willing to recycle should they be serviced with a 2-bag system which is collected at curbside, compared to multiseparation of recyclables.

The results sugges<sup>t</sup> that the intention to recycle is overruled by the practical reality of being able to recycle. The curbside collection item is the only item with a positive score (x-bar > 4.00) in the IR construct. The majority of respondents feel negative about taking their recyclables to drop-off points (x-bar < 4.00). The willingness to take recyclables to collection points decrease significantly the further the perceived distance to the collection point is. Since the majority of the respondents reported that the household does not have a motor vehicle in the household (Appendix A, Table A1), longer distances to recycling points are problematic for household recycling behavior.

#### *5.4. Attitude Towards Recycling*

With the mean score for attitude towards recycling (x-bar = 3.86) being less than the neutral point of 4.0 (Table 4), the majority of respondents has a negative attitude towards recycling. Only four respondents in total chose the "do not know"-option and only on a single item, which sugges<sup>t</sup> that the respondents do have an attitude and that this attitude leans towards the negative, rather than not having formed an attitude, yet. Due to the random sampling method the results can thus be extrapolated to sugges<sup>t</sup> the existence of an overall negative attitude towards recycling among South African city dwellers.



Where 1 implicates a most negative attitude towards recycling, and 7 implicates a most positive attitude towards recycling.

Within the attitude construct, the moral component as represented by the item "for your household to recycle is bad/good", shows the highest score (x-bar = 4.12) of all the attitude items. The "for your household to recycle is a hassle/easy" item shows the lowest mean score (x-bar = 3.48), and could be an indication of the influence of perceived convenience of recycling on householders' attitude towards recycling.

#### *5.5. Social Pressure to Recycle (Subjective Norm)*

The majority of respondents reported that they experience a lack of social pressure to recycle (x-bar = 3.37) (Table 5). The two items, "most of the people important to you want you to recycle" and "it is expected of you to recycle" show the lowest mean scores (x-bar = 2.96 and 3.27, respectively), and could indeed be a true reflection of the situation in South Africa, given the small percentage (3.3%) of respondents that reported that they engage in meaningful recycling (B > 4). Thus, extrapolated to the South African population, the individuals among family, friends, neighbors, and other significant people that would expect of others or exert pressure to recycle on others is part of a small group of South Africans. Nonrecyclers do not recycle and therefore would not be able to either be a recycling role-model or exert pressure to recycle in the manner that recyclers would be able to. In fact, someone who recycles would fall outside the norm of this-is-how-things-are-done-around-here, which suggests that the descriptive norm would not be pro-recycling. This is in line with the conclusion of Cialdini and coworkers [69] (p. 231) that an intervention which focuses on the descriptive social norm will only be successful in cases where the majority of people already conform to the desired behavior. If the majority do not recycle, the person who recycles would rather be considered and feel the odd one out. Minato (2012) also warns that the pressure through descriptive norms decline due to degrading social networks [70].

**Table 5.** Descriptive statistics for the subjective norm variable.


Where 1 implicates a most negative attitude towards recycling, and 7 implicates a most positive attitude towards recycling.

Another angle from which to interpret the results is that one would suspect that the respondents with high recycling behavior scores are represented by the high subjective norm scores, but with a correlation of 0.49 this only sugges<sup>t</sup> a relationship of medium strength (Appendix A, Table A3). A large percentage of those respondents from reportedly recycling households also do not experience any social pressure to recycle. Thus, it can be argued that the recyclers tap their motivation to recycle from a source independent of what others expect of them. It can be speculated that injunctive norms (moral values) could be a driver for recycling behavior, but because the questionnaire is weak on injunctive norm items, this possibility should be further researched.

#### *5.6. Perceived Control over the Act of Recycling*

The average (x-bar = 3.30) of the perceived behavioral control measurement is less than the neutral point (x-bar = 4.00). This result suggests that respondents do not feel that they have control over their ability to recycle (Table 6). All items making up this construct scored less than the neutral point. Albeit negative (x-bar < 4.00), the item "you know how to recycle" which represents a knowledge component, has the highest average (x-bar = 3.81) of all the perceived behavioral control items. The item "To recycle is difficult/easy" addressing the perceived difficulty to recycle and, also suggesting an underlying knowledge component, has the second highest score (x-bar = 3.59). The data thus suggests that, although the knowledge component of perceived behavioral control is not the main hurdle to overcome to change people's perceptions of their control over their ability to recycle, there is still a lack of sufficient knowledge among the majority of South Africans.

**Table 6.** Descriptive statistics for respondents' perceived behavioral control over recycling behavior.


Where 1 implicates a most negative attitude towards recycling, and 7 implicates a most positive attitude towards recycling.

The respondents perceived the opportunity to recycle ("The opportunities for you to recycle are none/plenty") less favorably (x-bar = 3.49) than the two knowledge items discussed above. But, the availability of recycling scheme items ("There are recycling schemes in your area" and "The necessary resources and facilities are available"; x-bar = 3.01 for both items) and the awareness of recycling scheme item fared the worst (x-bar = 2.94). Respondents thus feel that they do not have control over the act of recycling, especially in terms of where to recycle. Focused awareness-creation initiatives on the location of recycling drop-off infrastructure are thus needed.

#### *5.7. Testing the Theory of Planned Behavior Model*

The behavior, intention to recycle and attitude constructs show excellent reliability and internal consistency (Table 7). The reliability and internal consistency of the subjective norm and perceived behavioral control constructs are good. Thus, it was decided to keep all the items of all constructs.


**Table 7.** Reliability and internal consistency of the TPB constructs.

\* Where: α = Cronbach's alpha, λ6 = Guttman's lambda 6, β = Revelle's beta, ωh = McDonald's omega hierarchical, ω*lim* = McDonald's omega asymptotic, ω*t* = McDonald's omega total.

The results of the SEM analysis show a good fit of the survey data to the TPB theoretical model (Table 8).


**Table 8.** Goodness-of-fit statistics for the fitted SEM model.

The regression coefficients (βeta) are shown in Table 9. The proportion of variance explained for IR and B is shown in Table 10 and Figure 3.


**Table 9.** Parameter estimates for applying the TPB.

**Table 10.** Model R2-values.


The TPB explain 46.4% of the variance in intention to recycle and 26.4% of the variance in recycling behavior (B) (Figure 3).

Fitting the TPB model to the survey data shows that the subjective norm (SN) (*β* = 0.590) has greater influence than either attitude (A) (*β* = 0.275) or perceived behavioral control (*β* = 0.020) on intention to recycle. The relatively strong and significant relationship (*β* = 0.590; *p* < 0.0001) between subjective norm and intention to recycle supports H2. Overshadowed by the effect of subjective norm on intention to recycle, attitude results in having a smaller (*β* = 0.275), though significant (*p* < 0.0001), effect on intention to recycle (H1). Perceived behavioral control shows an insignificant effect on intention to recycle (*β* = −0.020; *p* = 0.54) and thus rejects H3. With R<sup>2</sup> = 0.464, the three variables attitude, subjective norm, and perceived behavioral control together account for 46.4% of the variance in intention to recycle. Both intention to recycle and perceived behavioral control influence recycling behavior, accounting for 26.4% of the variance in recycling behavior (R<sup>2</sup> = 0.264). Perceived behavioral control has a significant effect on recycling behavior (*β* = 0.276; *p* < 0.0001) (H5).

**Figure 3.** Path diagram of the TPB fitted to the unstandardized/raw latent variables.

The results from this study sugges<sup>t</sup> that perceived behavioral control carries more weight (H5) than intention to recycle (H4) in explaining recycling behavior. Typically, in studies where the behavior is likely to not only be affected by personal motivation, but also by other factors such as the availability of resources and access to services, perceived behavioral control appears to have a greater influence on intention [33]. This is in line with the argumen<sup>t</sup> that the effect of perceived behavioral control varies with the availability of curbside recycling schemes [36].

The small influence of attitude on intention to recycle (*β* = 0.275) is in line with findings of Martin et al. (2006) that a positive attitude towards recycling does not guarantee recycling behavior [72]. The attitude-behavior link proves to be strong where there is no "resources and cooperation" needed [40]. The relatively weak link between attitude and intention to recycle, which was found in this study, could thus be ascribed to ancillary variables and situational factors not accommodated or explained through the TPB. Although A is not the variable with the strongest/largest effect, attitude does contribute to the intention to recycle. Awareness-raising initiatives to improve people's attitudes towards recycling have a better chance for success should it include a moral component.

With the TPB explaining 26.4% of the variance in recycling behavior, the results from this study compares well with the Armitage and Conner meta-analysis of 185 behavioral studies dated pre-1998 [45]. The meta-analysis found that, on average, the TPB explained 27% of the variance in behavior and 39% of the variance in intention to act [45].

Armitage and Conner (2001) point out that, over the years, researchers measured the IR construct in different ways [45]. The IR construct is a measure of "how hard people are willing to try or how much effort they would exert to perform the behavior" [43] (p. 181). Distinguishing between intentions and self-predictions of behavior, it is argued that self-predictions (the likelihood to perform a behavior) provide a better prediction of behavior than intentions [45]. The inclusion of likelihood to recycle statements in the IR construct is a possible explanation for this study's higher explanation value of intention to recycle (46.4%) than Armitage and Conner's meta-analysis average of 39% [45].

Respondents show a higher probability that they intend to recycle than what their self-reported behavior suggests. In the behavioral sciences this is one of the challenges of predicting behavior [40]. There are several external factors that influence the path between intention and action even though the best intentions might exist. Examples may include a family crisis, or just forgetting to put out the recyclables, or a breakdown of a motor vehicle which makes it impossible to take recyclables to the drop-off center. The best intention might also be deliberately suppressed or ignored, for example due to unfavorable weather conditions on recycling day. Thus, from a personal point of view a person may be a recycler, but the actual recycling behavior may be absent.

Similar to what other studies showed [30,55,73], this study with 26.4% of the variance explained by the TPB, suggests that there are other variables than those proposed in the TPB that appears to have an effect on recycling behavior.

The importance of perceived behavioral control as the construct with the largest effect on recycling behavior in the TPB model, confirms that people should feel in control of their ability to recycle. One manner in which to promote a sense of control is through buy-in, e.g., through allowing communities to co-design their recycling services, because a waste scheme that is acceptable and functional in one area might not be suitable for another area [74]. Thus, through co-designing of recycling schemes, the necessary buy-in and awareness of the recycling facilities can be created. Co-designing also creates opportunity for established co-responsibility—a moral imperative (injunctive norm) which has the potential to be more successful at creating social pressure than descriptive norms in a society where recycling behavior is very low. Co-designing of a recycling scheme would also serve as a direct communication of the importance of the communities' participation in recycling and indicate that the municipality/recycling company takes recycling seriously (descriptive norm). Another advantage of co-designing of recycling schemes would be that potential leaders of the recycling initiative in communities would be identified. These leaders could assist with future recycling related communications and also through playing the part of much-needed role-models. In addition, recycling needs to be reinforced as a normative behavior through, e.g., well-targeted recycling advertisements, awareness creation, and the deliberate visibility of recycling bins.

#### **6. Conclusions and Recommendations**

The study shows that at a point in time, November 2010, before the NEMWA was widely implemented, about a quarter (26.9%) of South Africa's city dwellers engaged in some form of recycling which include their paper and packaging waste as well as compostable garden and/or food waste. Only 3.3% of the respondents reported that they recycle about half or more of their recyclables on a frequent basis. While the TPB remains a useful model for examining the variables that affects recycling behavior, the TPB explains 26.4% of the variance in recycling behavior and 46.4% of the variance in intention to recycle. Compared to intention to recycle, which has a far smaller effect on recycling behavior than expected, perceived behavioral control appears to be the most important variable to explain recycling behavior. This confirms that there are other variables than those proposed in the TPB that appears to play an important role in recycling behavior.

It is encouraging that respondents are positive about their intention to recycle should they have a curbside collection for their recyclables, especially given the very low self-reported recycling score and the negativity that is overwhelmingly present in all the variables. The results also sugges<sup>t</sup> that a less complicated and more convenient 2-bag waste collection system to accommodate the collection of recyclables at curbside has the greatest potential to be supported and thus encourage household recycling. The results strongly sugges<sup>t</sup> that awareness raising that has the greatest chance to influence recycling behavior positively, should contain a balanced mix of moral values (injunctive norms) and information about available recycling schemes. However, raising awareness would be meaningless without a positive contribution to householders' perceived behavioral control over their ability to recycle. One way to alleviate perceived behavioral control is through the provision of tailor-made recycling schemes to fit communities' particular needs. While co-designing of recycling schemes

would be beneficial for creating buy-in, such schemes should continue to operate as designed to ensure that the sense of having control over the act of recycling is obtained and maintained. For example, even the best designed recycling scheme will not show the envisaged results if such a scheme is failing or not well maintained.

The recommendation to policy-makers is to provide the most convenient and least complicated curbside collection for recyclables, such as a 2-bag collection system. However, it is important to acknowledge the need for diversity in designing recycling schemes, as well as the effect of continuity, reliability, and maintenance of recycling schemes on recycling behavior. Thus, the challenge for waste managemen<sup>t</sup> is the ability to create an enabling environment in South Africa that would not only encourage recycling behavior, but also ensure continuation of recycling behavior. In particular recycling of the materials currently recycled in the lowest quantities, i.e., garden and food waste, metals, and glass, would benefit from improved recycling facilities.

The implication of this research is that over time, as South Africans become more aware of recycling, and recycling behavior thus would have shifted from the current baseline for recycling, that the strategies to further improve recycling behavior needs to be adapted to the changed needs at the particular point in time. It should also be acknowledged that South Africa is a country with much diversity which complicates generalization. It can thus be dangerous to be prescriptive on the best ways for improving recycling behavior without considering specific areas, its unique characteristics due to its local set-up, and operating within its local constraints. Furthermore, some of the findings need clarification which confirms the need for further research.

**Funding:** This research was funded by the Council for Scientific and Industrial Research (CSIR).

**Acknowledgments:** Ipsos-Markinor was contracted to conduct the survey on behalf of the CSIR and included the set of questions in their biannual survey. The analysis of the data was partly outsourced to Mark Difford at the Nelson Mandela Metropolitan University. Suzan Oelofse assisted with pilot study logistics on the day of pilot data collection. Several colleagues in employment of the CSIR at the time, assisted with the initial literature review. Heidi van Deventer compiled the map (Figure 2) for this publication.

**Conflicts of Interest:** The author declares no conflict of interest.
