Operationalization: Making concepts measurable

In order to test our hypotheses through our quasi-experiment, we had to devise ways to measure the concepts in these hypotheses in real-life. The first step was to identify the dimensions that would best represent the system and supplier characteristics, recycling behaviour and performance in the given empirical setting.

We started by identifying what to measure, meaning the dependent variables:

Recycling behaviour and performance. We did not use cost or service as an indicator of performance, because recycling rate is the performance indicator consistent with the circular economy perspective. In Chapter 2, the recycling behaviour of the end-consumer-turned-supplier was also defined as the recycling rate of the individual, which means that recycling rate may measure both individual and system performance. The independent variables were chosen based on the empirical setting and theoretical findings, and are: Housing, activation of social norms, change in fractions from bring to kerbside scheme, and access to equipment. The rest of the supplier and system dimensions remained fixed in this experiment. This is illustrated in Figure 5-2.

Figure 5-2: The conceptual framework (Figure 3-1) showing independent and dependent variables, along with fixed dimensions of supplier and system characteristics.

The experimental group interventions had to affect the independent variables, thus affecting the recycling behaviour and recycling rate. Previously, we found that nudging appears to be an efficient way of achieving this. In combination, this lead to the following operationalization, which is summarized in Table 5-3.

Variable Characteristic Dimension and sub-dimensions Indicator/measurement as a percentage of weight of

total waste. Measured as

Lag in fill-rate of glass and metal container due to change in consumer logistics

strategy

Convenience Indirectly affected by access to equipment

See section 5.5.2 for details

Housing Type, size, number of

residents in each household

characteristic Pick-up frequency Number of pick-ups per week per fraction Table 5-3: Operationalization indicators and measurements for the chosen independent, dependent and fixed dimensions of supplier and system characteristics in the conceptual framework (Figure 5-3).

Some dimensions have several sub-dimensions, such as motivation (activation of social norms, monetary incentives).

The interventions that the experimental group was subjected to were the following:

1. Informational letter containing a nudge to activate social norms that target food waste recycling behaviour

2. System nudge through reduced distance to glass and metal collection point 3. System nudge through access to free waste bags for food, plastic and

residual waste, and reusable glass and metal bag

The purpose of the first intervention was to test H1. As outlined in the theoretical background, an informational nudge appears to be one way to affect motivation through the activation of social norms. Food waste was chosen as the fraction to target because it was an area with room for improvement, according to prior waste analyses (Mepex Consult AS 2015). Additionally, as food waste already belonged to the kerbside scheme, it was not possible to further optimize the system design by reducing the distance in this case. We combined a descriptive and injunctive norms (Cialdini 2003) into the following statement:

Did you know that 8 out of 10 of your neighbours separate their food waste into green bags? (Descriptive norm) Food waste is an important resource that is used to produce biogas and bio fertilizer. Even if you only have a small amount of food waste, it is important to use a green bag.

(Injunctive norm)

The second and third nudge was designed to test H2. The second intervention involved moving glass and metal from the bring scheme to the kerbside scheme.

This fraction was also chosen on the basis of prior analyses, and also because glass and metal in the residual waste could destroy the waste bags—thus making the recycling effort of other end-consumer-turned-suppliers pointless. Prior to the intervention, both groups used a glass and metal collection point that was next to the car park. The intervention involved placing a new glass and metal collection point near the experimental group’s existing kerbside collection point. The distance between the groups’ respective kerbside collection points and the glass and metal container is listed in Table 5-4.

Pre-test distance Post-test distance Change

Experimental group 230 m 6 m −224 m

Control group 120 m 120 m No change

Table 5-4: Distance to glass and metal collection point(s) before and after the intervention.

The third intervention was a consequence of the first two. As lack of equipment was identified in the literature as a potential barrier to action we had to ensure all participants in the experimental group had access to equipment needed to recycle food waste and glass and metal. We therefore wanted to distribute green bags and reusable bags for glass and metal. Prior analyses also revealed a certain degree of residual waste contamination in the blue and green bags (Mepex Consult AS 2015), and we therefore distributed both blue and green bags, as well as new red bags for residual waste. The purpose was to reduce contamination through improving access to bags, and thus improving perceived convenience among the end-consumer-turned-suppliers. This was also the purpose of distributing the reusable glass and metal bags. Together, the second and third interventions may count as system nudges (Stoknes 2015) that will increase the convenience for the consumers (see e.g. Perrin and Barton 2001, Miafodzyeva and Brandt 2013).

Through doorstepping, we distributed the intervention as a bundle to the end-consumer-turned-suppliers in the experimental group. An informational letter stated the purpose of the study, and also briefly explained the three interventions (Appendix A). The letter also contained the food waste nudge. It was distributed along with the waste bags and a standard sorting guide. All households in Oslo should already know of this sorting guide. Figure 5-3 illustrates this.

Figure 5-3: Material that was distributed to the experimental group during the intervention. Reusable glass and metal bag (left), and informational letter, sorting guide, and waste bags, (right).

In sum, this thesis used a quasi-experimental design with an experimental and control group chosen from the same housing cooperative. We have described how the sample was selected, as well as how the empirical setting and theoretical findings affected the operationalization of the conceptual framework. We also described the interventions that were designed to test the two hypotheses we derived to test our research question. The quasi-experimental design used a pre-test and post-pre-test waste analysis to investigate actual recycling behaviour through the use of recycling rates, and additional data regarding intention and demographics was gathered using a second post-test questionnaire. The waste analysis was conducted through the use of a pick-analysis, which will be described in more detail—as a pick analysis is also a method for data collection.