PLASTIC RECYCLING INITIATIVES IN SWITZERLAND...recycling potential from plastic waste. Enhanced...

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Identifying factors and their constellation that foster transition towards

separate collection of plastic waste in households through qualitative

comparative analysis

PLASTIC RECYCLING INITIATIVES

IN SWITZERLAND

Master’s Thesis by Elisabeth Güttinger

Supervisors:

Prof. Dr. Michael Stauffacher

Mert Duygan

Dr. Grégoire Meylan

Submitted 20th June 2017

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Table of contents

Acronyms ............................................................................................ 4

Acknowledgements ................................................................................. 5

Abstract .............................................................................................. 6

1. Introduction .................................................................................... 7

2. Methods ......................................................................................... 9

2.1 Introduction into QCA ................................................................... 9

2.2 Identification of plastic recycling initiatives ....................................... 11

2.3 Development of interview guide ..................................................... 11

2.4 Interviews with stakeholders .......................................................... 12

2.5 Selection of cases for QCA............................................................. 13

2.6 Definition of the outcome ............................................................. 15

2.6.1 Amount of collected plastic ..................................................... 16

2.6.2 Specific recycling rate per case ................................................. 16

2.6.3 Potential users ..................................................................... 17

2.6.4 Potential amount of plastic to collect ......................................... 18

2.6.5 Outcome calculation .............................................................. 22

2.6.6 Outcome calibration .............................................................. 24

2.7 Conditions ................................................................................ 25

2.7.1 Type of Collection ................................................................. 26

2.7.2 Costs for Consumers .............................................................. 26

2.7.3 Density of Collection Sites ....................................................... 27

2.7.4 History .............................................................................. 27

2.7.5 Communication .................................................................... 28

2.7.6 Supervised Collection ............................................................. 28

2.8 Conduct QCA............................................................................. 31

2.8.1 Sufficient conditions .............................................................. 31

2.8.2 Necessary conditions .............................................................. 35

2.9 Sensitivity analysis ...................................................................... 37

3. Results ......................................................................................... 39

3.1 Collection Rate .......................................................................... 39

3.1.1 Necessary Conditions ............................................................. 39

3.1.2 Sufficient Conditions .............................................................. 40

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3.2 Recycling Rate .......................................................................... 42

3.2.1 Necessary Conditions ............................................................. 42

3.2.2 Sufficient Conditions .............................................................. 43

3.3 Sensitivity analysis results ............................................................. 45

4. Discussion ..................................................................................... 47

4.1 Solution pathways for the outcomes ................................................. 47

4.2 Investigating the influence of the excluded conditions ........................... 48

4.3 The significance of mixed vs. selective collection ................................. 50

4.4 Limitations and recommendations for further research .......................... 51

5. Conclusions .................................................................................... 53

Bibliography ........................................................................................ 54

Appendix ............................................................................................ 57

Methods .......................................................................................... 57

Interview guide ............................................................................... 57

Calibration of outcome measures .......................................................... 59

Raw data and calibration of analysed conditions ........................................ 62

Results ............................................................................................ 68

QCA results .................................................................................... 68

Sensitivity analyses .......................................................................... 69

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Acronyms

EPS Expanded polystyrene

FOEN Swiss Federal Office of the Environment

MSW Municipal solid waste

MSWI Municipal solid waste incineration

PE Polyethylene

PET Polyethylene terephthalate

PE-HD High-density polyethylene

PE-LD Low-density polyethylene

PP Polypropylene

PS Polystyrene

PVC Polyvinyl chloride

QCA Qualitative comparative analysis

WEEE Waste of electrical and electronic equipment

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Acknowledgements

I would like to sincerely thank everybody who helped me in any way with my thesis.

First a big thanks to my supervisors Prof. Dr. Michael Stauffacher, Mert Duygan and

Dr. Grégoire Meylan for their support and time to discuss my work and pointing me in the

right direction, especially to Mert Duygan for the many meetings, valuable inputs, advice

and problem solving. A special thanks to Grégoire Meylan for the big help with the

preparation and conduct of the two interviews in French.

I would also like to thank my interview partners who took time during their busy work

hours to meet with me and answer my questions.

A heartfelt thanks to my boyfriend Marc who not only took the time to thoroughly review

my thesis but also supported me in any other possible way.

A special thanks to my fellow student Lea, it was very nice to have someone to talk to

about problems related to the qualitative comparative analysis.

Also, a big thanks to my brother Peter for helping me with my many computer related

problems.

Furthermore, I would like to thank my family for listening to my thoughts about the

diverse issues during my thesis.

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Abstract

In Switzerland, 5.5 million tons of municipal solid waste (MSW) is being generated every

year, whereof half is recycled, and half is incinerated. There is a considerable unused

recycling potential from plastic waste. Enhanced plastic recycling would result in

environmental benefits in form of saved energy and greenhouse gas emissions. Even

though plastic recycling is a new field in Switzerland, there are already a number of

operating plastic recycling initiatives.

This thesis analyses the factors and factor combinations leading to increased recycling in

the context of the existing plastic recycling initiatives in Switzerland. The thesis applies

the method the qualitative comparative analysis (QCA) for the analysis, which is suited

to analyse factor combinations for a moderate number of initiatives.

The six factors, type of collection, history, communication, costs for users, density of

collection sites and supervised collection are analysed regarding their influence on the

collection rate and recycling rate for each examined plastic recycling initiative.

The results from the analysis show that not only one combination of factors (pathway)

leads to the outcomes, but several different pathways. For the outcome high collection

rate, three pathways were detected and for the outcome high recycling rate four

different pathways. The pathways for a high recycling rate are composed of three to four

factors whereas the pathways for a high collection rate consist of only two to three

factors. This indicates that for a high recycling rate more factors must be fulfilled than

for a high collection rate.

Another key finding from the analysis is that to achieve a high recycling rate, supervised

collection is found to be an important factor. This means that it is recommended to

plastic recycling programs to supervise the collection of the plastic waste.

Also an important finding is, that plastic recycling programs with selective collection as

well as ones with mixed collection can achieve high recycling and collection rates.

However, the pathways with selective collection are shorter, indicating that for cases

with mixed collection, more conditions must be fulfilled.

It was also found, that the type of provider of a plastic recycling program does not have

an influence on the outcomes. Whether the provider is a municipality, a canton, a private

company or a retailer does not matter, all are able to achieve high recycling and

collection rates.

Besides these analysed factors, also other factors are important for a high collection and

recycling rate. Those factors include the costs for the consumers to use a plastic

recycling program, the expertise and competence of employees, preliminary studies and

the net costs of a program for the provider.

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1. Introduction

In Switzerland, 5.5 million tons of municipal solid waste (MSW) is being generated

every year. Half of the waste is recycled and half is incinerated. Whether generated

waste is incinerated or recycled depends foremost on the material. While there are

well-established separate collection programs for the recycling of PET, glass, paper,

bio-waste, waste of electrical & electronic equipment (WEEE) and aluminium other

materials, mostly plastic fraction, are hardly recycled (Steiger, 2014). The recycling

differences between the various waste fractions depicted in Figure 1 show unused

recycling potential, especially for plastics. Enhanced plastic recycling results in

environmental benefits in form of saved energy and greenhouse gas emissions

(Worrell & Reuter, 2014).

Figure 1: Comparison of the incinerated waste with the separate collected waste for recycling. Adapted from Steiger (2014)

The collection and recycling of plastic waste in Switzerland has become a prominent and

much discussed topic over the last few years. In the year 2010 the round table plastic

recycling was initiated to meet the demand for increased plastic recycling. Two studies

were commissioned by the round table regarding the current state of plastic recycling,

material flow analysis and determination of the potential (Schelker & Geisselhardt,

2011a) as well as the assessment of the ecological benefits, economic feasibility and

technical viability (Seyler, Sommerhalder, & Wolfensberger, 2013). Other studies

examine the best recovery options for plastic waste (Holinger & treeze, 2015), the future

of the separate collections of recyclable materials (Schelker & Geisselhardt, 2011b) or

the life cycle of different plastics (Kägi & Dinkel, 2015).

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However, none of the existing literature focuses on the drivers and barriers behind plastic

recycling in the context of the existing plastic recycling initiatives in Switzerland. Even

though plastic recycling is a new field in Switzerland, there are already a number of

operating plastic recycling initiatives. According to socio-technical transition theory,

such initiatives provide a protective niche for ideas and innovations to grow (Smith &

Raven, 2012). Studying the plastic recycling initiatives can yield insights for succeeding

plastic recycling projects.

Drivers and barriers behind general recycling participation have already been analysed

by various studies (Timlett & Williams, 2007; Tonglet, Phillips, & Read, 2003; McDonald

& Oates, 2003; Martin, Williams, & Clark, 2006) but not in the context of plastic recycling

in Switzerland. To the author’s knowledge no study investigated the interaction of

different factors leading to increased recycling. Often, not one factor alone, but a

combination of several factors leads to increased recycling.

Because of the explained reasons, the research focus of this thesis are the driving factors

and their interaction for increased recycling in plastic recycling initiatives in Switzerland.

The method chosen for the analysis is the qualitative comparative analysis (QCA), which

is suited to analyse factor combinations for a moderate number of initiatives. The

research question for the analysis reads as follows:

WHICH FACTORS OR FACTOR CONSTELLATIONS FOSTER TRANSITION FROM DISPOSING PLASTIC

WASTE IN THE GARBAGE TOWARDS A RECYCLING OF PLASTIC WASTE FROM SWISS HOUSEHOLDS?

The results of the thesis provide insights for policy makers and providers of plastic

recycling programs regarding the operation of such programs.

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2. Methods

The main method used in this thesis was QCA (qualitative comparative analysis). The

data necessary to conduct QCA was collected through literature review and interviews

with stakeholders from plastic recycling initiatives. This chapter gives first an

introduction into QCA, followed by a detailed description of all methodical steps used in

this thesis as shown in the following list:

• Identification of plastic recycling initiatives

• Development of interview guide

• Interviews with stakeholders

• Selection of cases for QCA

• Definition of the outcome

• Selection of conditions

• Calibration

• Conduct QCA

To assure the confidentiality of the information collected in the interviews and

questionnaires, the references to information is kept anonymous, the plastic recycling

initiatives are referred to as cases 1 – 20 for the analysis and some of the collected data

is only shown in the confidential annex.

2.1 Introduction into QCA

Qualitative comparative analysis is a set-theoretic method suited for analysing complex

causalities, in which an outcome (i.e. the dependent variable) may be explained by

different combinations of causal conditions (independent variables) (Ragin, 2008). QCA

is often applied in studies with a moderate number of cases of about 10 – 50. In that

sense, it constitutes a mid-way between standard statistical approaches and comparative

case studies. Nevertheless, QCA is also suitable for set relation studies with a high

number of cases (Schneider & Wagemann, 2012).

As QCA is grounded in set-theory, i.e. the examination of relations between sets is

essential. An example of a simple set relation is the subset, for instance, children are a

subset of humans. The set relation can also be expressed as supersets, e.g. living beings

are a superset of humans. These sets are represented in QCA through membership scores.

A 7-year old is a member of the set children and would thus get a membership score of

1 whereas a 50-year old, who is not a member of the set children, would get a

membership score of 0. Such dichotomous (binary) representation of the data in members

and non-members are called crisp sets. However, various types of real-world data are

not dichotomous, but continuous, for instant age. In QCA this can be represented by

fuzzy sets, which allow partial set memberships. For the set children, a 7-year old would

be a full member (membership score of 1), a 19-year old a partial member (membership

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score less than 1 and greater than 0) and a 50-year old a full non-member (membership

score of 0). (Schneider & Wagemann, 2012)

Assigning set membership scores is a crucial part of conducting a QCA. This

transformation of the raw data (e.g. age) to membership scores between 0 (full non-

membership) to 1 (full membership) is called calibration. The calibration is based on the

variation between the cases, i.e. their relative distribution of scores in the raw data to

each other (“high” vs. “low” scores). The assignment of membership scores should be

based on theoretical knowledge or case specific knowledge. (Ragin, 2017)

A central element of QCA is the analysis of set relations in terms of sufficiency and

necessity. A condition is sufficient, if whenever the condition is present, also the

outcome is present. There should not be a case where the condition is present but not

the outcome. This means that a sufficient condition is a subset of the outcome as is

depicted in the left Venn diagram in Figure 2. As an example, if the condition eating

chocolate is a sufficient condition for the outcome happiness, then every person eating

chocolate should be happy, and not one person eating chocolate should be sad. However,

happiness could also be achieved by another condition. (Schneider & Wagemann, 2012)

A condition is necessary, if whenever the outcome is present, also the condition is

present. The outcome cannot be achieved without the condition. There should not be a

case with the outcome present but not the condition. A necessary condition is a superset

of the outcome which is shown in the right Venn diagram in Figure 2. For the example of

happiness, good health could be a necessary condition. This would mean that a person

can only be happy if he is healthy, no unhealthy person should be happy. However, a

healthy person can also be unhappy. (Schneider & Wagemann, 2012)

Figure 2: Venn diagram for a sufficient condition (left) and necessary condition (right). Adapted from Schneider & Wagemann (2012)

Other important concepts regarding the causal complexity in the set-theoretic QCA are

equifinality and conjunctural causation. Equifinality refers to the scenario where

different, non-exclusive conditions explain the same outcome. Conjunctural causation

occurs whenever a single condition does not display the effect alone but in combination

with other conditions. Taking these concepts into consideration, QCA can handle

conditions that are neither necessary nor sufficient on their own, but which play a crucial

role in inducing the outcome in combination with other conditions. These concepts of

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equifinality and conjunctural causation are interlinked with the concepts of necessity

and sufficiency. The existence of a sufficient but not necessary condition implies that an

outcome can also be achieved through other conditions, which precisely characterises

equifinality. The existence of a necessary but not sufficient condition implies that the

condition must be combined with another condition, thereby displaying conjunctural

causation. (Schneider & Wagemann, 2012)

2.2 Identification of plastic recycling initiatives

The identification of plastic recycling initiatives encompassed a general internet-based

research, as well as knowledge transfer from related projects and experts. The first step

was a simple keyword search on the internet. The results from this search included

several websites of plastic recycling initiatives from private plastic recycling providers

and news articles about various initiatives. More news articles were found on the websites

of the private initiatives. Through these news articles, more plastic recycling initiatives

were identified, and if they led to more news articles, those were also checked until no

article mentioned any unidentified initiatives. However, this procedure did mostly cover

initiatives that already gained a certain amount of publicity. To also include less known

initiatives, the further internet searches were restricted to plastic recycling initiatives

in the bigger cities of each canton. Thereby, more initiatives could be identified; mostly

those initiated by municipalities which were not covered extensively by the media, yet.

Furthermore, the identified initiatives were compared to the ones analysed in the project

KuRVe which aims to provide a life-cycle analysis of the different plastic recycling

initiatives. Finally, two experts in the field of recycling were asked to complete the list

of initiatives according to their current state of knowledge. The identified initiatives are

listed in Table 1.

2.3 Development of interview guide

The interview guide was the main tool of data collection to conduct the QCA. The

interview questions were organized into ten categories:

- Design of the collection and recycling system

- Operation of the plastic recycling system

- Initiating reasons

- Design process

- Context analysis

- Historical background

- Competence

- Availability of outlet

- Communication

- Self-assessment

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The questions were prepared by a deductive approach, possible conditions were derived

from transition theory (Smith & Raven, 2012) and answers gathered through the

interviews. Besides responses to possible conditions, also data related to the outcome

was gathered through the interviews. The outcome and the data necessary for its

measurement is explained in more detail in chapter 2.6.

The interview guide also contained open questions to allow the interviewees to add any

additional information about their initiative, for instance about conditions they thought

had an influence on the outcome. This inductive approach was added to the interview

guide to get to know the cases better and learn from them, as familiarity with the cases

is an important aspect for a QCA (Wagemann & Schneider). The specific interview

questions can be found in the appendix. They were adapted slightly for each individual

interview.

2.4 Interviews with stakeholders

To get a comprehensive understanding of each initiative, interviews in person with

stakeholders from the identified initiatives were conducted. However, due to various

reasons, not all stakeholders were able to meet this objective. Three of them still agreed

to answer the interview questions in the form of a questionnaire. For this purpose, the

interview guide was slightly changed to serve as a questionnaire. Coop answered a few

questions.

Table 1 gives an overview of the identified initiative and the type of data collected per

case. The interviews were conducted mostly in February and March of 2017. A

transcription of each interview was done to serve as a data source for the QCA.

Table 1: Identified initiatives and type of data collected from the initiatives

Initiative Method of data collection

Kunststoffsammelsack von Innorecycling Interview

Supersack -

Kuh-Bag Interview

GAF Fricktal Questionnaire

Recycling-Sack Interview

Kunststoffsammelsack von Baldini -

Allschwil Interview

Spar Interview

AVAG Interview

Maag Recycling Interview

Coop 6 Questions

Hunzikerareal Interview

Aldi Questionnaire

Bern Interview

Canton Obwalden Interview

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Table 1: Continued

2.5 Selection of cases for QCA

The final set of cases was selected after all interviews were conducted. Based on the

information provided by the interviews, some of the identified initiatives had to be

excluded from the analysis, whereas others were split into two separate cases. Reasons

for exclusion were primarily related to insufficient data availability or quality.

Namely, the three cases that did not participate in the interviews were excluded due to

data availability. The cases Aldi and GAF Fricktal had to be excluded from the analysis

as they have not been running for a year, yet. Therefore, the available data about the

amount of plastic collected was not comparable to the other cases: i.e. projections for

the amount of plastic collected in a year were deemed unreliable. Finally, the case

Hunzikerareal had to be excluded as it only started its operations in Mai 2017.

The initiatives Bern, Fribourg and ZEBA were each separated into two cases as they

consisted of two distinctive phases: a mixed collection followed by a selective collection.

From the case Fribourg 2007, only the first year was used in the analysis because even

though they continued the separate collection, the collected plastic was incinerated in

the following years.

Table 2 provides an overview over the key characteristics of the different plastic

recycling initiatives. Allschwil is the only analysed initiative with a kerbside collection,

but also the excluded initiative in Fricktal is a kerbside collection

Initiative Method of data collection

Fribourg Interview

Migros Interview

ZEBA Zug Interview

Neuchâtel Interview

Haldimann Interview

Zürich Questionnaire

Canton Appenzell Innerrhoden Interview

Kunststoff-Recycling-Sack Nidwalden -

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Table 2: Characteristics of the different plastic recycling initiatives

Case Type of

collection

Mode of

collection

Starting

year

End

year Provider

Type of

provider

Migros selective bring system 2014 - Migros retailer

ZEBA 2006 - 2015 mixed bring system 2006 2015 ZEBA association

ZEBA 2016 selective bring system 2016 - ZEBA association

MAAG selective bring system ? - Maag Recycling AG private

Zürich selective bring system 2016 - Entsorgung & Recycling Zürich municipality

Recycling-Sack selective bring system 2015 - Müller Recycling AG & REDILO GmbH association

Spar selective bring system ? - Spar retailer

Allschwil mixed kerbside 2016 - Municipal administration municipality

Fribourg 2007 mixed bring system 2007 2013 Tiefbauamt Stadt Freiburg municipality

Fribourg 2014 selective bring system 2014 Tiefbauamt Stadt Freiburg municipality

Kuh-Bag mixed bring system 2015 - Verband KVA Thurgau & ZAB association

Canton Appenzell IR selective bring system 2013 - Amt für Umwelt canton

Coop selective bring system 2016 - Coop retailer

Neuchâtel mixed bring system 2012 2016 Service des Infrastructures de la Ville

de Neuchâtel municipality

Haldimann selective bring system 2013 - Haldimann AG private

AVAG selective bring system 2012 2014 AVAG association

Kunststoffsammelsack mixed bring system 2011 - InnoRecycling AG private

Bern 2005 - 2012 mixed bring system 2005 2012 Entsorgung & Recycling Stadt Bern municipality

Bern 2012 selective bring system 2012 - Entsorgung & Recycling Stadt Bern municipality

Canton Obwalden selective bring system 2007 2012 Entsorgungszweckverband Obwalden association

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2.6 Definition of the outcome

To assess the different plastic recycling initiatives, two common indicators for recycling

programs (Worrell & Reuter, 2014) were chosen as outcome measures for the QCA: the

collection rate and the recycling rate. The collection rate refers to the amount of waste

recovered from a waste stream, and the recycling rate refers to the amount of waste

available for recycling. For a better overview, Figure 3 depicts the waste flows of a

recycling system.

The collection rate is defined as the amount of waste recovered from a waste stream

through the separate collection (flow c) divided by the overall quantity of generated

waste in that waste stream (flow a). For this thesis, the recycling rate is defined as the

material of waste available for recycling (flow d) and the generated waste (flow a). This

means that the recycling rate used in this thesis depends, apart from the recovered

amount, strongly on impurities and lost material, but also on unrecyclable material (flow

I1). Such unrecyclable plastic is in some mixed cases intentionally collected, because the

different kinds of plastics are hard to differentiate therefore some cases decide to collect

all plastics to make the collection as easy as possible for the consumers.

Employing the ratio between the effectively recycled material (flow f) and the generated

waste (flow a) as recycling rate was not feasible as the measurement of that ration is out

of scope of this thesis. To calculate and measure the two outcomes, several variables

were required and are described in detail in this section. The measurements of the

variables, as well as the calculation of the collection and recycling rate, are depicted in

Table 5.

Figure 3: Waste flows of a simplified recycling system. Adapted from Haupt, Vadenbo & Hellweg (2016)

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2.6.1 Amount of collected plastic

Data about the amounts of plastic collected was either obtained through the interviews

or literature about the cases. For most of the cases, the data relates to 2016 which was

deemed to be the most appropriate year of reference as many cases have not been

running for very long, and the collected amount is still increasing. However, the amounts

of some cases relate to other years. For the case 12, the collected amount refers to the

year 2014, which was the last year the initiative was running. And in the case 8, only the

amount of plastic collected in the first year (2007) was used in the analysis, because in

the later years all collected plastic was incinerated.

For initiatives running over a duration of 5 years or more (e.g. case 6, 7, 10, 2, 18 and

19), it was assumed that the collected amounts reached stabilisation and that the use of

the average stabilised amount of plastic collected per year is more appropriate. The case

13 was special as it exhibited a decrease in the collected amount of plastic. Because it

was also running for over 5 years, the average collected amount was chosen. However,

data was only available beginning from the year 2012, not from the beginning of the

initiative in 2007. The collected amount per year also decreased for case 9, but because

it has not been running for 5 years and to remain consistent with the other cases, the

amount collected in 2016 was used as a reference.

In some cases, materials were excluded from the analysis. First, the case 18 initiative

does not collect all of the plastics with the intent of recycling, and thus the corresponding

amounts were excluded from the analysis. Those plastics include polystyrene (PS) and

polyvinyl chloride (PVC) which are used as substitute fuel in cement factories as they are

not suitable for recycling. Second, the obtained amounts for the cases 1, 2, 3, 16 and 12

included beverage cartons which were subtracted to obtain the sole amounts of collected

plastic.

As the comparison between cases with stabilised collection amounts and cases that have

only been running for a year is not perfectly consistent, a sensitivity analysis on the

collected amounts was performed.

The amount of plastic collected by each initiative is reported in the confidential annex.

2.6.2 Specific recycling rate per case

The recycling rates reported by each case are referred to as specific recycling rates in

this thesis. As depicted in Figure 3,they describe the ratio between the amount available

for recycling per case (flow d) and the amount of plastic collected separately per case

(flow c). The available data for the specific recycling rate per case differs. In some cases,

a detailed analysis of the recycling rate was available, whereas in other cases the

interviewees were only able to give a rough estimate. This was often the case for

municipalities, as they are only involved in the collection and not the recycling of the

material.

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Some interviewees could not give an estimate at all; for these cases, assumptions had to

be made. For the cases 9, 11, 15 and 16, the interviewees stated that the collected

material can be used directly as input for making re-granulate without a separate sorting

step. This means that all of the collected material is available for recycling,

conservatively, a specific recycling rate of 95% was assumed for these cases. For the

cases 5, 7 and 18 an estimation was based on a theoretical consideration: the specific

recycling rate depends on the amount of impurities, lost material and unrecyclable

materials in the collected material. Because the three cases in question all selectively

collect recyclable plastic, the specific recycling rate depends mostly on the impurities.

All three cases indicated a good collection quality, and therefore the specific recycling

rate was adapted from the other cases with selective collection and good collection

quality. The specific recycling rate was assumed to be equal to lowest recycling rate of

such a case.

A sensitivity analysis for the specific recycling rate was performed to inspect the effects

of the assumption on the recycling rate outcome.

The specific recycling rate for each initiative is presented in the confidential annex.

2.6.3 Potential users

To be able to compare the different initiatives of which some are available throughout

Switzerland and some only in one municipality, the amount of collected material was

compared to the number of potential users which was defined as all inhabitants in the

catchment area of a case. The population number should ideally refer to the year the

plastic was collected, which was for most cases, except the ones that are not running

anymore, the year 2016. However, the newest data available is for the year 2015, and

thus these numbers were used. For the cases running for five or more years, also the

latest population count was used as to enhanced the comparability with the other cases.

The slight variation of the population difference over the years does not affect the

outcome.

For the cases 4, 5, 7, 9, 10, 11, 14, and 15, the potential users were simply the

inhabitants of each municipality or canton respectively in the year 2015. For the cases 6

and 8 the population number refers to the inhabitants in the year 2011 and 2007

respectively and an additional 10% of that number as these collections were considerably

used by people living outside of the municipality. For case 12, the catchment area was

defined as all the municipalities in which a collection site was established with the

number of inhabitants from the year 2014. Also for case 13, the inhabitants of the

municipalities with a collection site were taken, but once again of the year 2015. For the

case 1 and 3, this was done similarly, by counting all inhabitants of the municipalities

with a selling point or collection point. For case 2, a cruder assumption had to be made,

as it is available in a large number of municipalities. The catchment area was defined as

the cantons Thurgau, Schaffhausen, Freiburg, Solothurn, Basel-Land, Aargau as well as

Bern and Zurich without the two capital cities. For case 17 and 20, the catchment area

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was defined as whole Switzerland. For case 19, again the inhabitants from municipalities

with a store were taken.

2.6.4 Potential amount of plastic to collect

Both outcome measures, the collection and the recycling rate, refer to the amount of

waste generated (flow a in Figure 3). However, this waste stream is not the same for all

cases, it refers only to the type of waste they collect separately. For cases only collecting

plastic bottles, the separately collected bottles are compared to the amount of waste

bottles generated. And for cases that collect mixed plastic, the separately collected

plastic is compared to the generated waste of mixed plastic. The generated waste flow

is the maximal amount of waste possible to collect per case. Therefore, it could also be

called the potential per case. The potential assumptions are based on the study by

Schelker & Geisselhardt (2011a) in which they evaluated the plastic flows within

Switzerland for the year 2010. They created a table with the consumption of plastic

fractions in households, which is depicted in Table 3. The used plastic in households is

divided into several fractions. The table shows a short description of plastics in each

fraction and most importantly, the amount of used plastic in each fraction. Also, the

main plastic per fraction is reported as well as the share of this main plastic per fraction.

Table 3: Potential plastic fractions in households (Schelker & Geisselhardt, 2011)

Fraction Description Main

plastic

Share of main

plastic small up

to 33%, medium

50%, big as of

66%

Usage

total

[t/a]

1 Foils

Food packaging like meat, cheese,

chips, pasta, frozen foods, also for

magazines, electronic equipment

etc.

PE-LD small 50'000

2 Shopping bags Shopping bags for clothes, foods;

pouches etc. PE-LD big 12'000

3 Hollow vessels

without bottles Bowls, cans, blister etc. PE medium 45'000

4 Cups Yoghurt, ice cream, coffee cups

etc. PS big 5'000

5 Beverage

bottles PET

Mineral water, soft drinks, juices

etc. PET big 55'000

6 Bottles milk

products Milk, cream, milk products etc. PE-HD big 5'000

7 Bottles diverse

Detergents und cosmetics,

cleaning, Food (without PET

beverage bottles) etc.

PE-HD medium 10'000

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Table 3: Continued

The potential per case was assessed by accumulating the usages per fraction from Table

4 from all fractions each case collects. For a case only collecting plastic bottles, only the

usage of two bottle fractions, bottles milk products and bottles divers, were

accumulated. For a case with mixed collection the usages of more fractions were

accumulated. Sometimes only a part of the usage of a fraction was included in the

potential if cases only collect parts of that fractions. The fraction beverage bottles PET

was excluded from all potential calculations, as PET beverage bottles are and always

should be collected through the separate collection for PET bottles. Also, the fraction

electrical and electronic equipment was excluded as it was assumed they end up in the

separate collection for electrical and electronic waste. The fraction vehicles was also

excluded as it was assumed discarded vehicles are not disposed of through the separate

plastic collections. Moreover, none of the examined cases specifically collect any of the

three above mentioned fractions. The potential calculations for each case are described

in more detail in the following sections. In Table 4 the calculated potentials for each

case are presented together with the fractions or part of the fraction from Table 3 that

were included in the potential calculation.

The two cases 1 and 2 both collect mixed plastics from packaging, therefore their

potential was assumed to be the sum of the fractions foils, shopping bags, hollow vessels,

cups, bottles milk products & diverse and miscellaneous. The thereby calculated

potential is 21.5 kg/a*inhabitant.

The cases 4 and 6 collect apart from mixed packaging plastics also other smaller mixed

plastic pieces. Bigger plastic pieces are not being collected as they do not fit in the bag

or through the deposit hole. Therefore, the fraction household goods was added to

Fraction Description Main

plastic

Share of main

plastic small up

to 33%, medium

50%, big as of

66%

Usage

total

[t/a]

8 Filling material

packaging

Filling material mainly for

Electrical and electronic

equipment

EPS big 3'000

9 Miscellaneous Packaging diverse, e.g. garbage

bags - - 45'000

10 Vehicles Interior, electrics, motor /

technic, insulation PP small 90'000

11 Furniture foams, garden furniture etc. ? small 40'000

12 Household

goods Kitchen utensils, tools etc. PP small 30'000

13

Electrical and

electronic

equipment

IT, entertainment electronics,

telephony, kitchen utensils etc. PP small 50'000

20

packaging fractions, increasing the potential to 25.25 kg/a*inhabitant. In comparison, in

the study about the waste composition in Switzerland in the year 2012 (Steiger, 2014)

the amount of plastic in the collected municipal solid waste was 26.7 kg/a*inhabitant.

The potential for the cases 10 and 8 was assumed to be even higher, as those cases also

collected bigger mixed plastic pieces like garden chairs. To account for these bigger

pieces a part of the fraction furniture was included. As very little about the composition

of the fraction furniture is known and it also included for instance foam which is not

collected, only a third of the fraction was used for the potential calculation. Thereby the

fraction is regarded, but not given too much weight because of the high uncertainty

about the composition of the fraction. The potential for the two cases was calculated as

26.90 kg/a*inhabitant. The potential for the case 14 was calculated similarly, only the

fraction filling materials packaging was added, as also Styrofoam was collected. Hence,

the calculated potential is 27.28 kg/a*inhabitant.

In the case 13, all kinds of hollow vessels were being collected. Therefore, the potential

was calculated as the sum of the fractions hollow vessels without bottle, cups, milk

bottles and bottles diverse, which is 8.13 kg/a*inhabitant.

The three cases 18, 16 and 9 all collect the same type of plastic, high-density

polyethylene (PE-HD), low-density polyethylene (PE-LD) and polypropylene (PP) pieces.

To assess their potential the information in regarding the main plastic per fraction and

its share (Table 3) was used. PE-HD, PE-LD and PP is the main plastic in the considered

fractions foils, bags, hollow vessel, milk bottles, bottles diverse and household goods.

Since only a part of these fractions are made up of PE-HD, PE-LD or PP, only these shares

were used for the potential calculation. The given information regarding the proportion

of the main plastic is given in three ranges, small from 0 – 33%, medium from 34 – 66%

and big from 67 – 100%. A proportion value per range had to be determined in order to

calculate the potential. One approach would be to take the mean values of each range,

hence 16.5%, 50% and 83.5%. However, this may lead to an underestimation of the small

shares and an overestimation of the big shares. Also, a proportion of the main plastic of

a fraction of only 16.5% does not seem very high. To attain a better balance, proportion

values of 25%, 50% and 75% respectively were chosen. From the available information, it

was not possible to account for PE-HD, PE-LD or PP when they are not the main fraction

as no data regarding their share is available. The finally calculated potential is 7.53

kg/a*inhabitant.

For the case 15, where bottles and PP-pieces are being collected, the potential is made

up of the fractions milk bottles and bottles diverse, as well as the share of PP in the

fraction household goods. The thereby calculated potential is 2.81 kg/a*inhabitant.

All of the cases 3, 5, 7, 12, 17 and 20 collect all kinds of plastic bottles, therefore their

potential was assumed to be the sum of the fractions milk bottles and bottles diverse

which is 1.88 kg/a*inhabitant.

With the collection from case 11 only PE-bottles are being collected. Similar to case 16,

9 and 18, the potential was assumed to be the usage of the fractions milk bottles and

21

bottles diverse times the respective proportion of PE in the fraction. This results in a

potential of 1.09 kg/a*inhabitant.

With the collection of case 19, only milk bottles are being collected, therefore its

potential is equivalent to the fraction milk bottles, which is 0.63 kg/a*inhabitant.

Table 4: Potential of collectable plastic waste per case

Initiative Collected material Included fractions potential

[t]

potential /

inhabitant

[kg/a*

inhabitant]

Case 1 Mixed packaging plastics 1, 2, 3, 4, 6, 7, 9 172'000 21.50

Case 2 Mixed packaging plastic 1, 2, 3, 4, 6, 7, 9 172'000 21.50

Case 3 Plastic bottles 6, 7 15'000 1.88

Case 4 Mixed plastics 1, 2, 3, 4, 6, 7, 9, 12 202'000 25.25


Case 6 Mixed plastics, no bigger

pieces 1, 2, 3, 4, 6, 7, 9, 12 202'000 25.25


Case 8 Mixed plastics including

bigger pieces

1, 2, 3, 4, 6, 7, 9,

11*0.33, 12 215'200 26.90

Case 9 PE-HD, PE-LD and PP-

pieces

1*0.25, 2*0.75,

3*0.5, 6*0.75, 7*0.5,

12*0.25

60'250 7.53

Case 10 Mixed plastic including

bigger pieces

1, 2, 3, 4, 6, 7, 9,

11*0.33, 12 215'200 26.90

Case 11 PE-bottles 6*0.75, 7*0.5 8'750 1.09


Case 13 Hollow plastic vessels 3, 4, 6, 7 65'000 8.13

Case 14

Mixed plastics including

bigger pieces and

Styrofoam

1, 2, 3, 4, 6, 7, 8, 9,

11*0.33, 12 218'200 27.28

Case 15 Plastic bottles, PP-pieces 6, 7, 0.25*12 22'500 2.81


pieces

1*0.25, 2*0.75,

3*0.5, 6*0.75, 7*0.5,

12*0.25

60'250 7.53

22

Table 4: Continued

Initiative collected material Included fractions potential

[t]

potential /

inhabitant

[kg/a*

inhabitant]



pieces

1*0.25, 2*0.75,

3*0.5, 6*0.75, 7*0.5,

12*0.25

60'250 7.53

Case 19 Plastic milk bottles 6 5'000 0.63


Table 4 provides an overview over the calculated potentials. The column collected

material gives a simplified summary of the kinds of plastics collected by each case. The

numbers in the column fractions refer to the fractions of household plastics in Table 3.

This column shows how each potential per case was calculated by adding up the usages,

or parts of usages, of the mentioned fractions. The potential per case is divided by all

inhabitants of Switzerland to enable the comparison between the different cases. In

accordance with Schelker & Geisselhardt (2011a) a population of 8’000’000 inhabitants

was chosen for the calculation of the potential amount of plastic waste to collect per

resident.

2.6.5 Outcome calculation

After the collection and calculation or estimation of all variables necessary for the two

outcome measures, they were calculated. Table 5 depicts the measures of all necessary

variables as well as the calculated recycling and collection rates. The two outcome

measures were calculated as described in Figure 3 in the following way:

𝐶𝑜𝑙𝑙𝑒𝑐𝑡𝑖𝑜𝑛 𝑅𝑎𝑡𝑒 = 𝑐𝑜𝑙𝑙𝑒𝑐𝑡𝑒𝑑 𝑎𝑚𝑜𝑢𝑛𝑡 [𝑘𝑔/𝑖𝑛ℎ𝑎𝑏𝑖𝑡𝑎𝑛𝑡]

𝑝𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙 [𝑘𝑔/𝑖𝑛ℎ𝑎𝑏𝑖𝑡𝑎𝑛𝑡]

𝑅𝑒𝑐𝑦𝑙𝑖𝑛𝑔 𝑅𝑎𝑡𝑒 = 𝑐𝑜𝑙𝑙𝑒𝑐𝑡𝑒𝑑 𝑝𝑙𝑎𝑠𝑡𝑖𝑐 [𝑘𝑔/𝑖𝑛ℎ𝑎𝑏𝑖𝑡𝑎𝑛𝑡] ∗ 𝑠𝑝𝑒𝑐. 𝑟𝑒𝑐𝑦𝑐𝑙𝑖𝑛𝑔 𝑟𝑎𝑡𝑒

𝑝𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙 [𝑘𝑔/𝑖𝑛ℎ𝑎𝑏𝑖𝑡𝑎𝑛𝑡]

The collection rate of the case 13 was calculated differently. As in this case more than

50% of the collected material was essentially waste and not the targeted plastic fraction,

the collected amount was reduced by 50% for the collection rate. Even though almost all

cases report a certain amount of foreign material, 50% is extraordinary high and would

have distorted the collection rate of case 13 making it not really comparable to the other

cases. For the recycling rate this was not necessary, as the proportion of foreign material

is already included in the specific recycling rate.

23

Table 5: Variables and the calculated collection rate & recycling rate

Initiative Inhabitants

Collected

amount per

inhabitant

[kg/inhabitant]

Amount available

for recycling per

inhabitant

[kg/inhabitant]

Potential per

inhabitant

[kg/inhabitant]

Recycling

rate [%]

Collection

rate [%]

Case 1 439'169 0.7 0.5 21.50 2.1 3.3

Case 2 3'813'448 0.4 0.2 21.50 1.0 1.7

Case 3 189'023 0.0 0.0 1.88 1.3 1.4

Case 4 20'464 5.4 3.5 25.25 14.1 21.3

Case 5 396'955 0.0 0.0 1.88 0.6 0.7

Case 6 138'249 2.2 0.8 25.25 3.0 8.6

Case 7 131'554 0.1 0.1 1.88 3.8 4.5

Case 8 37'220 2.7 1.3 26.90 4.9 9.9

Case 9 38'489 1.6 1.5 7.53 20.0 21.0

Case 10 28'603 12.2 4.9 26.90 18.2 45.5

Case 11 122'134 0.4 0.4 1.09 34.1 35.9

Case 12 117'116 0.3 0.3 1.88 14.7 17.3

Case 13 31'348 3.3 1.3 8.13 16.5 20.6

Case 14 33'712 8.2 2.4 27.28 9.0 29.9

Case 15 15'974 0.8 0.7 2.81 25.6 26.9

Case 16 6'638 1.8 1.7 7.53 22.2 23.4

Case 17 8'327'126 0.3 0.3 1.88 13.5 15.9

Case 18 108'268 1.4 1.2 7.53 15.6 18.4

Case 19 2'254'466 0.0 0.0 0.63 0.4 0.5

Case 20 8'327'126 0.2 0.2 1.88 8.7 10.2

24

2.6.6 Outcome calibration

To perform a QCA, membership scores for the two outcome measures had to be defined.

The degrees of membership range from 0 (full non-membership) to 1 (full membership),

whereas in between varying degrees of membership are possible, namely cases can be

more in (closer to 1) or more out (closer to 0). The calibration is based on the variation

between the cases, i.e. their relative distribution of scores on the outcome measures to

each other (“high” vs. “low” scores). The outcome measures were calibrated to

membership scores between 0 and 1 using the direct calibration method (Ragin, 2017).

By means of a logistic function, this method fits the raw data between three qualitative

anchors: the threshold for full membership (1), the cross-over point (0.5), and the

threshold for full non-membership (0). The starting point of any set calibration however,

is a clear specification of the target set.

For the calibration of the outcome high recycling rate, thresholds for full non-

membership of 1.5% and for full membership of 30% were selected. The cross-over point

was chosen where there is the maximum ambiguity to whether a case is more in or more

out of the target set (Ragin, 2017). This was done by locating a prominent gap in the

values of the raw data (Schneider & Wagemann, 2012) which is depicted in Figure

4. There are two gaps, one between case 8 (4.9%) and case 20 (8.7%) and another

between case 14 (9%) and case 17 (13.5%), of which the latter is the bigger gap.

Therefore, a cross-over point of 11% was selected. The detailed table with the

calculations for the direct calibration is presented in the appendix. The calibrated data

for the high recycling rate is presented in Table 6.

A sensitivity analysis to examine the influence of different thresholds, especially a

different cross-over between case 8 and case 20, was conducted.

Figure 4: Recycling rate of all cases

0

5

10

15

20

25

30

35

40

RECYCLIN

G R

ATE

CASES

25

The outcome high collection rate was calibrated in a similar way. The threshold of full

non-membership was set at 1.5% and the threshold for full membership at 40%. A gap

between the different collection rate values was used to establish the cross-over point.

Figure 5 depicts the collection rates of the examined initiatives and shows a

notable gap between case 20 (10.2%) and case 17 (15.9). The cross-over point was

therefore chosen at 13%.

Figure 5: Collection rate of all cases

2.7 Conditions

Based on the knowledge gained from the interviews, a pool of potential conditions was

created. In a subsequent selection process, relevant ones were identified and non-

relevant ones discarded. This selection was necessary because the number of conditions

should be kept moderate for a QCA as too many conditions lead to a high number of

possible combinations of conditions. This in in turn results in an increased number of

logical remainders (i.e. configurations for which no empirical case exists) and causes the

problem of limited diversity (Wagemann & Schneider).

The conditions discarded include oil price, social pressure from locals, extent of

preliminary studies, competence of the staff members and the net costs of a plastic

recycling program. For instance, no initiative stated that the oil price had an influence

on the initiation of their program, thus this potential condition was discarded.

Regarding social pressure from locals, it was hypothesised that it could lead to the

initiation of a plastic recycling program. Moreover, such a program could be used more

intensely if the locals themselves show interest in plastic recycling. However, only a few

initiatives established their programs because of social pressure from residents.

0

5

10

15

20

25

30

35

40

45

50

CO

LLECTIO

N R

ATE

CASES

26

Furthermore, the collected data did not allow for an accurate assessment of the

resident’s attitude towards plastic recycling.

The third excluded condition, preliminary studies, explains whether the context was

properly analysed, especially the technical viability and the economic feasibility, but

also the consumer needs. Even though the collected data suggests that a good context

analysis and according planning is essential, the collected data was not comparable

enough to use this condition in the QCA.

The potential condition about the expertise and competence of the staff members was

discarded because there was not enough variation between the initiatives. All value this

condition and carry out further training on a regular basis.

The last condition excluded is the net cost of a plastic recycling program and refers to

the program costs imposed on the providers themselves. It was hypothesised and stated

by the interviewees as being important, however the costs for the provider does not have

a direct influence on the collection or the recycling rate. Therefore, this condition could

not be used in the QCA. Though, it can explain why some initiatives were discontinued.

The final set of conditions as well as their calibration to membership scores between 1

and 0 are described in the following sections. The raw data is presented in the appendix.

Table 6 depicts the calibrated data of the selected conditions.

2.7.1 Type of Collection

The condition type of collection refers to the kind of material being collected by an

initiative. A collection can be mixed, i.e. all kinds of plastic fractions are being collected,

or selective, i.e. only one plastic fraction is collected, for instance only plastic bottles.

The types of fraction being collected by each case are shown in Table 4. The condition

selective collection was calibrated using a four-value fuzzy set: (fully in), 0.67 (more in

than out), 0.33 (more out than in) and 0 (fully out) (Ragin, 2008). For all cases with mixed

collection, no matter how extensive, the value 0 (full non-member) was assigned. To all

cases that selectively collect solely one plastic fraction, the value 1 (full member) was

assigned. The four cases 16, 18, 9 and 15, which all collect two or three different plastic

fractions separate, the value of 0.67 (more in than out) was assigned. Even though the

calibration was performed using a four-value scale, only three values were used, as the

value 0.33 is not assigned to any case. This happens, as no initiative is only more in than

out of mixed collection and not a full member.

2.7.2 Costs for Consumers

This condition captures whether the consumer must pay to use the separate plastic

collection or whether it is free of charge. For all initiatives, this was either 0 or 1, except

for case 18 where the collection of PE-HD and PE-LD is free but not the collection of PP-

pieces. The calibration of this condition was performed using a four-value fuzzy set with

27

1 as no costs and 0 as costs for consumers. case 18 is the only case with a value in-

between (0.67, more in than out). The cases with costs for consumers, i.e. the ones that

require to purchase a collection bag, are full non-members (0). All other cases offer their

collection free of charge for the consumers, hence they are full members (1).

2.7.3 Density of Collection Sites

To take the aspect of user convenience into account, the density of collection sites was

added. The number of collection sites was compared only to the settlement area in the

catchment area of a case, not to the whole area. The data necessary for the calculation

and calibration is presented in the appendix. For the case with the kerbside collection

in, a collection point per 100 inhabitants was assumed. The condition was calibrated

using the direct calibration method. The threshold for full membership was chosen at 1.5

collection sites per settlement area (km2) and for full non-membership at 0.1 collection

sites per settlement area. The cross-over point was determined graphically by comparing

the slopes of the curve in Figure 6, and set at 0.5 collection sites per settlement area.

Due to the above assumption, the number for this case is significantly larger than for the

other cases. Therefore, it is not depicted in the figure.

A sensitivity analysis was conducted to examine the influence of a different cross-over

point between case 19 and case 6.

Figure 6: Collection sites per settlement area

2.7.4 History

This condition was constructed by assessing whether an initiative is the first of its kind

in the area or if there has already been a predecessor. The expectation is, that initiatives

with a preceding initiative collect more plastic as the residents are already familiar with

the concept of plastic recycling. For most cases, this assessment was straight forward.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

DEN

SIT

Y O

F C

OLLECTIO

N S

ITES

CASES

28

The plastic bottle collection from case 17 was the first nationwide plastic collection,

thus it was defined as a new initiative, even though in some regions other initiatives had

started before case 17. The case 4 was defined to count as new initiative even though

the plastic bottle collection from case 17 was in the area before, because its mixed

collection is a novelty. The condition was calibrated into a crisp set with 0 for no

preceding initiative and 1 for preceding initiative in area before.

2.7.5 Communication

The condition communication to the consumers was constructed as only people who know

about a plastic collection program can use it. Therefore, the knowledge of people about

a collection is important. The idea behind the condition is to capture all information

flows to the residents about the plastic collection. This information should increase the

knowledge of the consumers about a plastic recycling program, and thus it could be used

more. The information can originate from the provider of a plastic collection program,

but also news articles about an initiative which were not initiated by the provider were

included. According to the field of marketing, two metrics are among others important

for the measurement of marketing performance, reach and frequency (Farris, Bendle,

Pfeifer, & Reibstein, 2010). Reach refers to the number of people who receive

information and frequency relates to the number of times an individual receives

information. An extensive measurement of the communication exceeded the scope of

this thesis, therefore a rough assessment based on the two metrics, reach and frequency,

was performed. In short, it was evaluated through which channels with which reach the

providers communicate with what frequency. Reach and frequency were only assessed

dichotomously, i.e. whether they were high (2) or low (2). To assess reach, each

information channel was attributed with either a high or low reach. Websites,

newsletters, events, flyers & notes or posters at the collection site were assigned a low

reach. Newspapers, radio, TV and waste disposal information (Abfallkalender) were

assigned a high reach. For each case, it was assessed for each used information channel,

whether the channel was used frequently or not. The resulting matrix is presented in the

appendix. To calculate the communication score for each case, the reach of each

information channel was multiplied by the frequency it was used and the resulting

products were summed up. The thereby calculated communication scores range from 1 –

12. The scores were calibrated to membership scores between 1 and 0 using the direct

calibration method. The threshold for full memberships was placed at 11 and the

threshold for full non-membership at 2. The cross-over point was placed in the medium

at 6.5. The calibration calculations are depicted in the appendix.

2.7.6 Supervised Collection

This condition originates in the interviews, as many interviewees stated that a supervised

collection is crucial for the collection quality of the plastic recycling program. The

condition supervised collection is only used for the analysis of the recycling rate not the

29

collection rate, as it does not have an influence on the amount of material collected,

but on the collection quality. The condition was evaluated using a four-point scale from

supervised, more supervised, more unsupervised and unsupervised. Programs with only

one collection site were categorized to supervised or unsupervised. For programs with

more than one collection site, it was determined whether more or less than half of the

collection sites were supervised and accordingly categorized. The kerbside collection was

defined as unsupervised because the content of collected bags is not being inspected.

For the three retailers case 17, 20 and 19 the collection was categorised as more

supervised because the material is being collected at the stores where a certain amount

of social control is present even if the collection itself is not supervised. The condition

was calibrated using a four-value fuzzy set directly transforming the four categories to

the values between 1 and 0 with supervised as 1, more supervised as 0.67, less supervised

as 0.33 and unsupervised as 0.

A sensitivity analysis for the categorization of the retailer’s collection as less supervised

is conducted.

30

Table 6: Calibrated data of outcomes and conditions

Case

High

Recycling

Rate

High

Collection

Rate

Selective

Collection

High

Density of

Collection

Sites

History

Intensive

Communica

tion

No Costs for

Consumers

Supervised

Collection

Case 1 0.06 0.07 0 0.20 1 0.73 0 0.33

Case 2 0.04 0.05 0 0.10 0 0.58 0 0.33

Case 3 0.04 0.05 1 0.20 1 0.27 0 0.33

Case 4 0.62 0.72 0 1.00 1 0.98 0 0

Case 5 0.04 0.04 1 0.03 1 0.09 1 1

Case 6 0.07 0.24 0 0.37 0 0.42 1 0

Case 7 0.09 0.10 1 0.04 1 0.73 1 1

Case 8 0.13 0.31 0 0.97 0 0.42 1 0.33

Case 9 0.81 0.71 0.67 0.08 1 0.98 1 1

Case 10 0.76 0.97 0 0.08 1 0.58 1 1

Case 11 0.97 0.93 1 0.58 1 0.58 1 1

Case 12 0.64 0.62 1 0.41 0 0.91 1 0.67

Case 13 0.70 0.70 0.67 0.45 0 0.58 1 0.33

Case 14 0.35 0.87 0 0.07 0 0.27 1 1

Case 15 0.91 0.82 0.67 0.06 0 0.27 1 1

Case 16 0.85 0.76 0.67 0.67 0 0.91 1 1

Case 17 0.60 0.58 1 0.09 0 0.91 1 0.67

Case 18 0.68 0.65 0.67 0.03 0 0.16 0.67 1

Case 19 0.03 0.04 1 0.22 1 0.02 1 0.67

Case 20 0.33 0.33 1 0.16 1 0.73 1 0.67

31

2.8 Conduct QCA

The QCA was conducted with the help of the program fsQCA. The program is suited to

analyse the interplay between causal complexity and necessity and sufficiency. To

analyse the complex causation, where an outcome can be achieved by different

combinations of causal conditions, the program constructs a truth table. A truth table

lists all logically possible combinations of causal conditions. The number of logically

possible combinations depends on the number of causal conditions, calculated with the

function 2k where k is the number of causal conditions. By means of the truth table,

connections between causal conditions and outcomes are analysed. The different

logically possible combinations can be analysed regarding their sufficiency (Ragin, 2008).

In this section, the analysis of sufficiency through truth tables as well as the analysis of

necessary conditions are described.

2.8.1 Sufficient conditions

To analyse sufficient conditions, two concepts are important, consistency and coverage.

As already mentioned, to analyse sufficiency a truth table with all logically possible

combinations of conditions is constructed. These logically possible combinations of

conditions are also called configurations, pathways or recipes. As the number of

configurations increases exponentially by the formula 2k (k is the number of conditions),

a truth table with 3 conditions would have 8 configurations or rows, one with 4 conditions

would have 16 configurations, one with 5 conditions already 32 configurations and one

with 10 conditions already 1’024 configurations. (Ragin, 2008)

The construction of the truth table is handled by the program fsQCA. For the input

conditions, it automatically constructs a truth table with all logically possible

combinations of conditions, the configurations. The program assigns each case to the

truth table row it belongs to. An example of a truth table with all configurations and the

assigned cases per configuration is depicted in Table 7. As can be observed in rows 12 -

16, not for all possible configuration an empirical case exists. Such rows are called logical

remainders. The higher the number of analysed conditions, the higher the number of

logical remainders as the number of possible configuration grows exponentially. This is

the reason the number of conditions analysed should be kept moderate. (Schneider &

Wagemann, 2012)

32

Table 7: Example of a truth table

Conditions Outcome

Row Selective

Collection

Density

of coll.

sites

History Communi-

cation

Collection

Rate Consistency Cases

1 1 0 1 0 0 0.276 3, 5, 19

2 1 0 0 1 1 0.883 12, 13, 17

3 1 0 1 1 0 0.556 7, 9, 20

4 0 0 0 0 0 0.75 6, 14

5 0 0 1 1 0 0.598 1, 10

6 1 0 0 0 1 0.990 15, 18

7 0 1 0 0 0 0.724 8

8 0 0 0 1 0 0.703 2

9 0 1 1 1 0 0.709 4

10 1 1 0 1 1 1 16

11 1 1 1 1 1 0.865 11

12 0 0 1 0 - -

13 0 1 1 0 - -

14 0 1 0 1 - -

15 1 1 0 0 - -

16 1 1 1 0 - -

For each row, it has to be assessed whether the row can be considered a sufficient

condition for the outcome and if so, the row is assigned an outcome value of 1. This

determination of sufficiency and outcome values is performed by hand, not by the

program. A problem for the analysis of sufficiency of a row pose contradictory rows, in

which cases that are members in a truth table row do not share the same membership in

the outcome. This means the same configuration leads to both the occurrence and non-

occurrence of the outcome. In Table 7 this occurs in rows 3,4 and 5, as the rows both

lead to the presence (cases in bold) and absence of the outcome. Therefore, based on

the empirical evidence, it is not straightforward to decide whether these rows are

sufficient for the outcome or not. (Schneider & Wagemann, 2012)

33

Figure 7: Venn diagram of a consistent (left) and inconsistent (right) sufficient condition.

Adapted from Schneider & Wagemann (2012)

One way of dealing with this is to analyse to which degree a row deviates from a perfect

subset relation. For instance, for a row where nine out of ten cases display the outcome,

90 percent of the evidence is in line with a subset relation. For a row where only 5 out

of 10 cases display the outcome, the subset relation is less perfect. This measure of

subset relations is called consistency. The Venn diagrams in Figure 7 depict different

degrees of consistency. The diagram on the left displays a perfect subset relation

between the condition X and the outcome Y, and therefore consistency. For the other

Venn diagram, the consistency is decreased as the subset relation is violated, meaning

that cases display the condition without also displaying the outcome which is not

consistent with the notion of sufficiency. The consistency of a condition can be

calculated by the following formula: (Schneider & Wagemann, 2012)

𝐶𝑜𝑛𝑠𝑖𝑠𝑡𝑒𝑛𝑐𝑦 =𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑎𝑠𝑒𝑠 𝑑𝑖𝑠𝑝𝑙𝑎𝑦𝑖𝑛𝑔 𝑏𝑜𝑡ℎ 𝑡ℎ𝑒 𝑐𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛 𝑎𝑛𝑑 𝑜𝑢𝑡𝑐𝑜𝑚𝑒

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑎𝑠𝑒𝑠 𝑑𝑖𝑠𝑝𝑙𝑎𝑦𝑖𝑛𝑔 𝑡ℎ𝑒 𝑐𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛

To help identifying truth table rows as sufficient conditions, fsQCA calculates the

consistency value for each configuration as portrayed in Table 7 in the column

consistency. Cases with low consistency values should be ruled out as they contradict the

subset relationship of sufficiency. Schneider & Wagemann (2012) recommend a

consistency threshold of 0.75. This means that only configurations with a consistency

value of 0.75 or higher are identified as sufficient configurations. Accordingly, the

outcome values of 1 and 0 are assigned to the rows by hand; 1 for consistency values of

0.75 or higher and 0 for lower consistency scores. However, the rows identified as

sufficient conditions have to be checked for true logical contradictions. These are cases

that display a condition but not the outcome. Row 4 with the case 6 displays a true logical

contradiction as case 6 displays the condition but not the outcome. Therefore, this row

is deemed as being not a sufficient condition, and therefore an outcome value of 0 is

assigned. (Schneider & Wagemann, 2012)

34

The program fsQCA simplifies the truth table to derive the solution. This process of logical

minimization does not alter the information contained in the truth table but generates

solution formulas with a lower degree of complexity. The result of the minimization are

one or more solution terms, which describe different pathways to achieve the outcome.

For the example, the minimization of the truth table leads to the solution terms

presented in Table 8. (Schneider & Wagemann, 2012)

Table 8: Example of a solution term

raw

coverage

unique

coverage

consistency cases covered

selective collection * ~history 0.404 0.225 0.825 12, 17, 13, 15, 16, 18

selective collection * high density

of collection sites * communication 0.279 0.100 0.947 4, 16

high density of collection sites *

~history * communication 0.324 0.145 0.849 16, 11

Solution coverage: 0.649

Solution consistency: 0.803

The outcome high collection rate can therefore be explained by three different

pathways. An important measure to interpret the pathways is coverage. Coverage

sufficiency refers to the proportion of the outcome covered (explained) by an outcome.

The Venn diagrams in Figure 8 depicts two degrees of coverage. Whereas in the first

diagram the condition X covers a big part of the outcome Y, therefore having a high

coverage value, the condition X in the second diagram only covers a small part of the

outcome Y, therefore its coverage value will be smaller. Coverage is calculated with the

following formula: (Schneider & Wagemann, 2012)

𝑐𝑜𝑣𝑒𝑟𝑎𝑔𝑒 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑎𝑠𝑒𝑠 𝑑𝑖𝑠𝑝𝑙𝑎𝑦𝑖𝑛𝑔 𝑡ℎ𝑒 𝑐𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛 𝑎𝑛𝑑 𝑡ℎ𝑒 𝑜𝑢𝑡𝑐𝑜𝑚𝑒

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑎𝑠𝑒𝑠 𝑑𝑖𝑠𝑝𝑙𝑎𝑦𝑖𝑛𝑔 𝑡ℎ𝑒 𝑜𝑢𝑡𝑐𝑜𝑚𝑒

Regarding the solution terms, the raw coverage refers to the proportion of the outcome

covered by a single configuration. The unique coverage indicates how much of the

outcome is uniquely covered by a single path. The solution coverage states how much of

the outcome is covered by the entire solution term. The solution consistency refers to

the degree the both solution terms are a subset of the outcome. (Schneider & Wagemann,

2012)

35

Figure 8: Venn diagram of different levels of coverage sufficiency. Adapted from Schneider & Wagemann (2012)

2.8.2 Necessary conditions

The analysis of necessary conditions can also be performed with the program fsQCA.

Necessity is assessed based on the measures of consistency and coverage, which the

program computes for the entered conditions.

A condition is necessary for the outcome if no case displays the outcome without the

condition. The consistency of a necessary condition is determined by the degree to which

a case’s membership values in the condition are equal or greater than their membership

in the outcome. In a visual representation of consistency on an XY plot (Figure 9) of the

condition and the outcome, the cases should fall on or below the diagonal for a

consistency value of 1. Cases that are located above the line are inconsistent. Amongst

those inconsistent cases are also true logical contradictory cases that do not display the

condition (membership < 0.5) but display the outcome (membership of > 0.5). In the

example, case 4 and case 13 are true logical contradictory cases while case 7 – 2015 is

slightly inconsistent. (Schneider & Wagemann, 2012)

36

Figure 9: XY plot, condition supervised collection, outcome high recycling rate

The program fsQCA computes the necessity consistency of each condition, to be more

specific, it computes the necessity consistency for the presence and/or absence of each

condition. Whether the necessity consistency should be computed for the presence of

absence of the condition or both, depends on whether it is expected that the presence

or absence, or both, of a condition should lead to the outcome. An example of an output

for an analysis of necessity through the program fsQCA is presented in Table 9. It is for

the researcher to decide which conditions should be considered as necessary conditions.

A consistency threshold of at least 0.9 is suggested (Schneider & Wagemann, 2012).

However, the assessment of necessity should not only rely on the consistency measures,

but the condition should also be checked for true logical contradiction as explained

above. In this example one could argue that a consistency level of the condition

supervised collection of 0.8784 is close enough to 0.9 to count it as a necessary condition,

however the presence of two true logical contradictory cases as shown in Figure 9 advises

against this. The condition no costs for consumers can be determined as a necessary

condition if it does not entail true logical contradictions. (Schneider & Wagemann, 2012)

Table 9: Analysis of necessity

Condition Consistency Coverage

High density of collection sites 0.4220 0.6437

Supervised collection 0.8784 0.5746

No costs for consumers 0.9117 0.5073

case 4

case 6

case 13

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Hig

h R

ecycling R

ate

Supervised Collection

37

The second measure to assess necessity is the notion of coverage. Necessity coverage

expresses how much smaller the outcome set is in relation to the condition set. The term

coverage is misleading, the issue at stake is that of relevance or trivialness. This notion

of relevance is depicted in the Venn diagrams in Figure 10. The set of the condition X in

the second Venn diagram is considerably larger than the outcome set Y and can therefore

be interpreted as a trivial necessary condition. For conditions that were deemed

necessary based on their consistency level, the coverage level helps to determine

whether a necessary condition is relevant or trivial. A high coverage value indicates

relevance, while smaller values indicate trivialness. The condition no costs for consumers

with a coverage value of 0.5073 would be interpreted as a trivial necessary condition.

Another indication of trivialness is the clustering of cases to the right axis on the XY plot.

(Schneider & Wagemann, 2012)

Figure 10: Venn diagram for a non-trivial (left) and trivial (right) necessary condition. Adapted from Schneider & Wagemann (2012)

2.9 Sensitivity analysis

Several sensitivity analyses were conducted to examine the effect of different

assumptions in the creation of the outcome measures and the conditions on the solution

of the QCA. Also, the effects of the choice of different thresholds in the calibration of

outcome measures and conditions are examined. The results of the different sensitivity

analyses are shortly described in the end of the chapter results.

The sensitivity of the calculated recycling rate to the amount of collected plastic was

evaluated. Therefore, the collected amount of plastic for the cases that have only been

running for only a year was increased by 25% to see whether this leads to a high recycling

rate for these cases. The cases in question are: cases 4, 5, 20 and 11.

To examine the effects of the taken assumptions for the specific recycling rate on the

calculated recycling rate, the specific recycling rate was changed by 25% for the cases

where assumptions had to be made. This affects the cases 5, 7 and 18.

38

The sensitivity of the results for the outcome recycling rate to a different cross-over

point of 7 between case 8 and case 20 was analysed.

Also, the effects of a different cross-over point for the condition density of collection

sites of 0.38 between case 19 and case 6 were analysed.

The sensitivity of the results for the outcome recycling rate to a different categorization

of the retailer’s collection as less supervised from the condition supervised collection is

evaluated.

39

3. Results

In this chapter, the results from the QCA for the two outcome measures and the

sensitivity analyses are presented. Firstly, the results from the necessity and sufficiency

analysis for the outcome collection rate are described, followed by the necessity and

sufficiency results for the recycling rate. Finally, the results of the different sensitivity

analyses are reported.

3.1 Collection Rate

For the outcome collection rate, five of the six presented conditions are expected to

have an influence on the collection rate and are therefore used to perform the QCA. The

test of necessity was conducted first and its results are presented first, followed by the

construction of the truth table and the analysis of sufficiency.

3.1.1 Necessary Conditions

Table 10 presents the computed consistency and coverage measures for the conditions.

For the conditions high density of collection sites, communication and no costs for

consumers their presence is expected to lead to the outcome. For the conditions

selective collection and history, both their presence and absence could lead to the

outcome, therefore they were tested for both. The “~” stands for the absence of a

condition.

Table 10: Analysis of necessity - outcome collection rate


Selective collection 0.629 0.530

~Selective collection 0.510 0.564


History 0.414 0.396

~History 0.586 0.560

Communication 0.736 0.633


Only the condition no costs for consumers has a consistency value of over 0.9 and could

therefore be interpreted as a necessary condition. However, its coverage value of 0.553

indicates trivialness. Figure 11 shows the XY plot for the condition and the outcome.

First, it can be observed that there is one true logical contradictory case. Second, the

cases cluster to the right which is besides the coverage value an indication for trivialness.

It was decided to not use this condition in the construction of the truth table due to its

suggested trivialness and the logical contradictory case.

40

Figure 11: XY plot of the outcome high collection rate and the condition no costs for consumers

No necessary condition is identified for the outcome collection rate. The condition

communication has the highest consistency value with 0.736.

3.1.2 Sufficient Conditions

For the construction of the truth table, the four conditions selective collection, density

of collection sites, history and communication are used. The condition no costs for

consumers was excluded as described above. The program fsQCA constructed the truth

table depicted in Table 11 with all logical combinations of conditions except the

remainders as well as the corresponding consistency values and cases. The cases that

display the outcome (i.e. have a membership of > 0.5 in the outcome set) are represented

in bold. A consistency threshold of 0.75 was applied to assign the outcome values of 1.

Furthermore, true logical contradictory cases, who display the condition but not the

outcome, were detected. One such a true logical contradiction is the case 6 in row 4.

Because of this, row 4 was determined to not be sufficient for the outcome and an

outcome value of 0 was assigned.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Hig

h C

ollecti

on R

ate

No costs for consumers

41

Table 11: Truth table for the outcome collection rate

Conditions Outcome

Row Selective

Collection

Density

of Coll.

sites

History Communi-

cation

Collection


1 1 0 1 0 0 0.276 3, 5, 19

2 1 0 0 1 1 0.883 12, 13, 17

3 1 0 1 1 0 0.556 7, 9, 20

4 0 0 0 0 0 0.75 6, 14

5 0 0 1 1 0 0.598 1, 10

6 1 0 0 0 1 0.990 15, 18

7 0 1 0 0 0 0.727 8

8 0 0 0 1 0 0.703 2

9 0 1 1 1 0 0.796 4

10 1 1 0 1 1 1 16

11 1 1 1 1 1 0.865 11

The minimization process leads to three different solution formulas depicted in Table 12.

The table shows for all three solution terms the raw coverage, unique coverage,

consistency as well as the cases they cover. Also shown are the overall solution coverage

of 0.649 and consistency of 0.803. The signs “*” stands for the operator “AND” and the

“~” stands for the absence of a condition. The first solution term selective collections *

~history can therefore be read as selective collection and new initiative.

Table 12: Solution terms for the outcome collection rate

raw

coverage

unique

coverage


selective collection * ~history 0.404 0.225 0.825 12, 17, 13, 15, 16, 18

selective collection * high density of

collection sites * communication 0.279 0.100 0.947 4, 16

high density of collection sites * ~history

* communication 0.324 0.145 0.849 16, 11



42

The second and third solution term only differ by one of three conditions and can

therefore be simplified and presented as shown below. The sign “+” stands for the

operator “OR”.

selective collection * new initiative

communication * high density of collection sites * (selective collection + new initiative)

3.2 Recycling Rate

For the outcome recycling rate, the condition supervised collection is added to the ones

already used for the outcome collection rate. First, the necessity test is conducted and

its results presented and second the truth table is constructed and the results from the

sufficiency are test presented.

3.2.1 Necessary Conditions

Same as for the outcome collection rate, the presence and absence of the two conditions

selective collection and history is tested. For the conditions high density of collection

sites, communication, no costs for consumers and new the supervised collection, only

the presence is analysed.

Table 13: Analysis of necessity - outcome recycling rate


Selective collection 0.698 0.537

~Selective collection 0.422 0.425


History 0.430 0.375

~History 0.570 0.497

Communication 0.778 0.610

Supervised collection 0.878 0.575


The condition no costs for consumers is again the only condition above the threshold of

0.9. However, the condition is excluded from the test of sufficiency for the same reasons

as for the outcome collection rate, an indicated trivialness and a true logical

contradictory case that can be observed in the XY plot in the appendix.

The condition supervised collection is with a consistency value of 0.912 very close to the

threshold of 0.9 and might therefore be interpreted as a necessary condition. The XY plot

43

depicted in Figure 12 however shows two true logical contradictory cases 4 and 13,

therefore interpreting supervised collection as a necessary condition does not seem

warranted.

Figure 12: XY plot for the outcome recycling rate and condition supervised collection

3.2.2 Sufficient Conditions

The truth table for the five conditions selective collection, high density of collection

sites, history, communication and supervised collection, constructed by the program

fsQCA is presented in Table 14.

None of the rows above the consistency threshold of 0.75 contain a true logical

contradictory case, therefore the assignment of the outcome values is straightforward.

There are six rows deemed sufficient for the outcome and hence assigned an outcome

value of 1. The minimization process yields the four solution terms presented in Table

15.

case 4

case 13

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Hig

h R

ecycling R

ate

Supervised Collection

44

Table 14: Truth table for the outcome recycling rate

Conditions Outcome

Row Selective

Collection

Density

of coll.

sites

History Communi-

cation

Supervised

collection

Collection


1 1 0 1 1 1 0 0.561 7, 9, 20

2 1 0 0 0 1 1 1 15, 18

3 1 0 1 0 1 0 0.315 5, 19

4 1 0 0 1 1 1 0.970 12, 17

5 0 0 0 0 0 0 0.346 6

6 0 1 0 0 0 0 0.421 8

7 1 0 1 0 0 0 0.268 3

8 0 0 0 1 0 0 0.346 2

9 1 0 0 1 0 1 1 13

10 0 1 0 1 0 0 0.541 4

11 0 0 1 1 0 0 0.090 1

12 0 0 0 0 1 0 0.691 14

13 1 1 0 1 1 1 1 16

14 0 0 1 1 1 1 0.782 10

15 1 1 1 1 1 1 0.856 11

45

Table 15: Solution terms for the outcome recycling rate

raw

coverage

unique

coverage


selective collection * ~history *

communication 0.335 0.029 0.834 12, 17, 16, 13


supervised collection 0.411 0.104 0.973 12, 15, 16, 17, 18

~selective collection * ~history *

communication * supervised collection 0.111 0.102 0.782 10


collection sites * communication *

supervised collection

0.291 0.1 0.941 16, 11



The overall solution coverage is 0.65 and the solution consistency 0.849. The first two

solution terms have the highest coverages; therefore, they cover more of the cases. This

can also be observed from the number of cases they cover. The solution terms can be

simplified and presented in the following way:

Selective collection * new initiative * (communication + supervised collection)

Mixed collection * new initiative * communication * supervised collection

Selective collection * high density of collection sites * communication * supervised collection

3.3 Sensitivity analysis results

This section shortly presents the results from the different sensitivity analyses. The

detailed results are presented in the appendix.

For the sensitivity test of the collected amount of plastic, the amount was increased by

25% for the initiatives that have only been running for a year. For the two cases 4 and

11, which already have a high recycling rate, the recycling rate is now even higher. For

the case 5 with a very low recycling rate, the increase in collected material is not enough

to cross the cross-over point. For the case 20 however, the increased amount leads the

recycling rate to meet the cross-over point. This means that the results are sensitive to

the amount of plastic case 20 collects. Another sensitivity analysis examines which

effects this would have on the results of the QCA.

The recycling rate is not sensitive to a 25% change in the specific recycling rates of the

cases 5, 7 and 18. The recycling rate of case 18 falls nearer to the cross-over point but

does not cross it.

46

The sensitivity analysis of the calibration of the outcome recycling rate to a different

cross-over point of 7 between case 8 and case 20 show, that one of the solution terms

changes, the others stay the same. The solution term selective collection, new initiative

and supervised collection changes to low density of collection sites, new initiative, few

communication and supervised collection. The results of the QCA are therefore not very

sensitive to the cross-over point chosen for the calibration of the recycling rate, however

they do change a little.

The sensitivity analysis of the effects of a different cross-over point on the condition

density of collection sites results in a change of two of the four solution terms. The

condition high density of collection sites is now featured in two and not only one solution

terms. This means the results are to some extend sensitive to the calibration of the

density of collections sites.

The solution terms for the recycling rate are not sensitive to a different categorization

of the retailer’s collection as less supervised. The four solution terms do not change at

all, only their coverage values vary a little.

47

4. Discussion

In this chapter, the results, as well as their relevance and consequences for the research

question, are interpreted and discussed. Also, possible conditions that were excluded are

discussed regarding their relevance for the operation of plastic recycling programs.

Finally, limitations of the study and recommendations for further research are portrayed.

4.1 Solution pathways for the outcomes

Several conditions and configurations were identified to answer the research question:

"Which factors and factor constellations foster transition from disposing plastic waste in

the garbage towards a recycling of plastic waste from Swiss households?" The most

important finding from the analysis is in line with the strength of a QCA, namely that

not only one configuration leads to the outcomes, but several different pathways. For

the outcome high collection rate, three pathways were detected and for the outcome

high recycling rate four different pathways.

The solution terms selective collection in combination with new initiative for the

outcome collection rate is surprising. Contrary to this result, the expectation was that

plastic recycling programs with a previous program would lead to higher collection rates

because the residents were already familiar with the concept of collecting plastic

separately from mixed household garbage. This finding should be treated with caution

and further investigated. One aspect to take into consideration is that plastic recycling

is a still a young field and therefore many initiatives were the first in their area. It might

be that the observed solution will fade in the future when plastic recycling becomes more

popular and nationwide available. Thus, it will be interesting to monitor whether the

pioneering plastic recycling programs still have higher collection rates and manage to

attract and keep consumers even in the presence of other plastic recycling programs.

The results show that a high collection rate can also be achieved through intensive

communication and a high density of collection sites in combination with either a

selective collection or being a new initiative. The two paths each cover two cases, with

the case 16 being explained by both, thus covering a total of three cases. The pathway

selective collection, high density of collection sites and intensive communication is in

line with the expectations. Then again, the pathway with new initiative instead of more

communication is surprising. Both, however, illustrate that intensive communication and

a high density of collection sites are vital for a high collection rate. Therefore, it is

important that residents are well informed to motivate them to use the collection. A

further implication is that they use collections more often if there is a collection point

at a convenient distance.

For the outcome recycling rate, the two configurations that cover the most cases are

selective collection and new initiative (with coverage values of 0.335 and 0.411

respectively), with either more communication or supervised collection. Except for the

surprisingly prominent part of the condition new initiative, the results are in line with

48

the expectations. The condition selective collection takes a considerable part in these

two configurations and also appears in another configuration that leads to a high

recycling rate. This implies that collecting a plastic fraction selectively tends to lead to

high recycling rates. However, as stated above a selective collection alone does not lead

to a high recycling rate, but only in combination with other conditions.

Achieving a high recycling rate is also possible with a mixed collection, as shown by the

solution term mixed collection, new initiative, communication and supervised

collection. Because this pathway covers only one case, it should be interpreted with care.

In comparison to the other shorter configurations it can be noticed that for cases with

mixed collections, more conditions must be fulfilled.

The configuration selective collection, high density of collection sites, communication

and supervised collection is in line with the expectation, however it only covers two

cases which limits its explanatory power.

The condition supervised collection appears in three of the four solution terms whereby

its frequent occurrence is implied by the high necessity consistency value of almost 0.9.

Its importance was also emphasised by several interviewees. This condition does not lead

to a high recycling rate by increasing the collected amount of plastic, but by improving

the collection quality. And, a good collection quality is invaluable for plastic recycling as

it tends to reduce the impurities, and hence leads to a higher specific recycling rate.

Comparing the pathways that result in a high collection rate to those that result in a high

recycling rate reveals that the configurations for a higher recycling rate tend to be

composed of more conditions. The three configurations for a high collection rate consist

of two to three conditions whereas the four configurations for a high recycling rate

consist of three to four conditions. This difference suggests that a high recycling rate

requires the fulfilment of more conditions. Given the definition of these two outcomes,

this finding seems reasonable. Namely, a high collection rate is achieved by increasing

the amount of waste recovered from the waste stream. In contrast, a high recycling rate

depends not only on the amount of recovered waste, but also on its suitability for

recycling. Determining for its suitability is that the amount of impurities and non-

recyclable material in the recovered waste is low. As stated above, the condition

supervised collection, which is analysed for the outcome recycling rate and not collection

rate, influences the impurities in the collected plastic. To sum up, the larger number of

conditions reflect the fact that increasing the recycling rate is more difficult than

increasing the collection rate.

4.2 Investigating the influence of the excluded conditions

Not only the examined conditions can have an influence on the collection and recycling

rate, but also the ones that had to be excluded from the analysis. The condition no costs

for consumers was identified as a potentially trivial necessary condition. This means that

this condition is essential to achieve a high collection and recycling rate. In fact, most

49

of the data support this finding, except for the case 4. Therefore, it can be assumed that

plastic recycling collections which do not impose costs on the consumers work well.

However, as the case 4 illustrates, it is also possible to attract consumers if the program

does impose costs. The case 4 collection is not only mixed, but also the only kerbside

collection analysed in this thesis, which might be a decisive factor to outweigh the costs

for the consumers. It will be informative to analyse the results from the mixed kerbside

collection in Fricktal to verify this assumption.

Except for case 18, only the cases with mixed collection in a bag impose costs on the

consumers. Thus, these costs might be the driving factor behind their low collection and

recycling rate. However, as their low collection and recycling rate mostly originate from

the comparison of their collected amount of to all inhabitants of their large catchment

areas, it seems more probable that these cases are still too unknown within their

catchment areas. Hence, one strategy to increase the collection and recycling rate of

the respective cases is to make their collection more known through increased

communication efforts.

Furthermore, many interviewees considered the expertise and competence of employees

to be of high importance for the operation of a plastic recycling program, particularly

regarding the various types of plastics. The different types, including PP, PE-HD, PP-LD

and others are difficult to distinguish for laypeople. Even though symbols are printed on

some plastic products, not all products and packaging bear them. Therefore, it is almost

impossible for consumers to dispose of them correctly. The employees, on the other

hand, are trained to identify the different plastic types and can assist the consumers

optimally.

Another condition that might have an influence on the collection and recycling rate is

conducting preliminary studies to analyse the context properly and design programs

according to the results of the preliminary analysis. Aspects to consider include the

technical viability, economic feasibility and consumer needs. The interviews suggested

that thoroughly analysing the technical viability is crucial to achieve a high recycling rate

by ensuring to collect primarily recyclable plastic. For mixed collections, such studies

should ensure that effective and economic sorting opportunities are available to deal

with the non-recyclable material. Furthermore, a proper analysis of the economic

feasibility was indicated to be important for a well-working plastic recycling program. A

thorough analysis of the economic possibilities helps to ensure that the resulting net costs

from a plastic recycling program are within a bearable range for the provider.

As already indicated, the net costs of a plastic recycling program for the provider are an

important aspect of a plastic recycling initiative. As the net costs of a program do not

have a direct influence on the collection or recycling rate, they were not included in the

QCA. They do however influence the operation of a plastic recycling program because

high uncovered costs likely lead to the termination of the program. Nonetheless, many

interviewees stated that the collection does not have to be fully cost covering; in fact,

few separate collections are, but the net costs need to be in a bearable range. Often,

the costs imposed by the plastic recycling program were compared to the baseline

50

alternative, the costs the incineration of the collected waste would have incurred and

deemed bearable if they are even to or lower than the incineration costs. An often-stated

factor leading to high costs is logistics. Because plastic is a very light material, transport

is costly. In most cases, the collected plastic is thus pressed prior to transport to the

remote sorting and recycling facilities. Logistics is particularly challenging if the plastic

recycling initiative cannot build on an already existing collection network but has to

establish new collections points. The financing for plastic collection differs from the

financing of the other recyclables collections in Switzerland as there is no corresponding

prepaid recycling fee. This means that the provider of the plastic recycling program has

to bear all costs. Or impose costs on the consumers as the cases with a bag to collect the

material in do.

4.3 The significance of mixed vs. selective collection

One of the most distinctive features of a plastic recycling program is whether its

collection is mixed or selective. The choice between these types of collection has several

consequences. For instance, selective collections tend to have higher recycling rates.

Only collecting recyclable plastic has the benefit that a big proportion of the collected

amount will be available for recycling; only impurities have to be sorted out. This entails

that, depending on the collection quality, less or no sorting at all is necessary to prepare

the material for recycling which in turn saves transport and sorting costs.

Another advantage of a selective collection is that the collected material is homogenous.

This is beneficial for the recycling because homogenous input material generally leads to

high-quality re-granulate. The quality of the re-granulate affects its possible

applications. Only high-quality secondary material can be recycled back into the same

product whereas lower quality secondary material can only be used to manufacture

different products (Haupt, Vadenbo, & Hellweg, 2016). Furthermore, secondary material

from mixed collection tends to be of lower quality than secondary material from selective

collection. However, a thorough assessment of the quality of the secondary material from

each initiative exceeded the scope of this thesis and was not done. Therefore, no exact

statement regarding the difference in quality of the re-granulate form selective and

mixed is possible.

A distinct advantage of mixed collection is that a significant amount of the overall waste

stream can be recovered and (at least a part of it) recycled. The amount of recovered

and recycled plastic waste from mixed collections is considerably larger than that of

selective collections. In conclusion, both mixed and selective collections have its

advantages and disadvantages, and it is the provider's responsibility to decide upon the

adequate type of collection. As already mentioned, the results from the QCA indicate

that it is easier to achieve a high collection or recycling rate with a selective collection

as more of the solution terms contained selective collection and only a few mixed

collection. However, a high collection and recycling rate is also possible with a mixed

collection.

51

In contrast to the other separate collections of recyclable materials in Switzerland like

PET, aluminium, glass or paper, the collection and recycling rate of plastic recycling

programs does not seem very high, with 46% being the highest collection rate and 35%

the highest recycling rate. It must be noted though that no examined plastic recycling

program is likely to yield a collection or recycling rate near 100% as they are in direct

competition to each other. Thus, the sums of all programs' collection and recycling rates

would be the adequate value for a more meaningful comparison. It has also to be

considered that plastic recycling on a nationwide scale has only been introduced by case

20 and case 17 which is another difference to the well-established collection networks

of other recyclable materials. Moreover, plastic recycling is a comparably young

endeavour that has not reached the familiarity of the other collection networks. Thus,

the adoption of plastic recycling behaviour could take some time for the consumers.

The presented results provide useful insights to plastic recycling providers regarding the

design of their plastic recycling programs. The different configurations that lead to a

high collection or recycling rate could be used as orientation to adapt plastic recycling

programs to the individual circumstances and requirements in an area.

4.4 Limitations and recommendations for further research

The thesis is limited in several aspects. For a better assessment of the collection and

recycling rate, several variables should be determined more thoroughly. The collected

amount of plastic used in this thesis is only limited comparable, due to the difference in

years the initiatives have been running. For a better evaluation, the cases should be

compared after the same amount of years after initiation of the plastic recycling

program.

Another limitation regarding the assessment of the collection and recycling rate is the

assumptions of the potential amount of plastic to collect per case. The assumptions are

based on data collected in the year 2010. Furthermore, the potential could only be

assessed based on rough waste amounts per plastic fraction. For an accurate assessment

of the collection and recycling rate, a detailed material flow analysis should be

conducted for each case. In addition to a more accurate assessment of the potential

amount of waste to collect, also a more detailed elicitation of the recycling rate would

be possible. It could be precisely assessed how much of the collected plastic is effectively

recycled into another product.

Regarding the conditions, especially the assessment of communication is limited. A

thorough enquiry of all information channels regarding their reach and the frequency of

provided information would be beneficial.

The condition high density of collection sites is only one possible measure of convenience

and does not capture the reason behind consumer’s behaviour. A survey among

inhabitants in the catchment areas of the different plastic recycling program would

provide insight into the consumer’s attitude towards recycling and drivers for their

52

recycling behaviour. Based on the survey, a better assessment of convenience could be

performed.

As the two outcomes collection and recycling rate did not allow for the inclusion of the

condition net cost of program for the provider, even though it was indicated to be

important for the operation of a plastic recycling program, a further study should take

this condition into account.

53

5. Conclusions

The aim of this thesis was to identify conditions and combinations of conditions that lead

to a transition towards an increased collection and recycling of plastic waste. The results

show that there is not only one way to achieve high collection and recycling rates, but

several different pathways. For the outcome high collection rate, three pathways were

detected and for the outcome high recycling rate four different pathways. The pathways

for a high recycling rate are composed of three to four factors whereas the pathways for

a high collection rate consist of only two to three factors. This indicates that for a high

recycling rate more factors must be met than for a high collection rate.

Another key finding from the analysis is that plastic recycling programs with selective

collection as well as ones with mixed collection can achieve high recycling and collection

rates. However, the pathways with selective collection are shorter, indicating that for

cases with mixed collection, more conditions must be fulfilled.

For the outcome high recycling rate, supervised collection is found to be an important

factor as it appears in most of the solution pathways. This means that for new plastic

recycling programs it is recommended to supervise the collection of the plastic.

The type of provider of a plastic recycling program does not have an influence on

achieving high collection and recycling rates. Whether the provider is a municipality, a

canton, a private company or a retailer does not matter, all are able to achieve high

recycling and collection rates.

Also, other conditions not included in the analysis are important for a high collection and

recycling rate. Those factors include the costs for the consumers to use a plastic

recycling program, the expertise and competence of employees, preliminary studies and

the net costs of a program for the provider.

54

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Source cover picture: iStock

57

Appendix

The appendix features additional data for an in-depth comprehension of the analysis.

The supplementary data is organised according to the chapters they refer to.

Methods

Interview guide

KONZEPT DER KUNSTSTOFFSAMMLUNG

Könnten Sie kurz den Recyclingprozess in den einzelnen Schritten, von der Sammlung in den Haushalten bis

zum effektiven Recycling respektive der thermischen Verwertung beschreiben?

Was waren die Gründe, dass Sie sich spezifisch für die Sammlung dieses Sammelguts entschieden haben?

Hat die Kunststoffsammlung bestimmte Zielsetzungen? Wenn ja, wie spezifisch sind diese Ziele?

BETRIEB DER KUNSTSTOFFSAMMLUNG

Wie viel Kunststoff wird durch die Kunststoffsammlung pro Monat gesammelt? Wie hoch ist das geschätzte

theoretische Sammlungspotential?

Haben Sie eine Schätzung über das «Einzugsgebiet» der Sammlung? Wie viele Leute nutzen die Sammlung

und wie viele könnten sie theoretisch nutzten?

Wie viel Prozent des gesammelten Kunststoffes wird recycelt? Wie genau wird dieses Recyclingpotential

berechnet? Wie hoch wäre das theoretische Recyclingpotential?

Wie gut ist die Qualität des gesammelten Kunststoffes? Änderte die Qualität im Laufe der Zeit?

Zu welchem Grad wurden gesetzte Ziele erfüllt?

Was sind Ihre Pläne für die Zukunft? Würden Sie (theoretisch) das Konzept der Kunststoffsammlung gerne an

einem anderen Ort aufgezogen sehen, von ihnen oder jemand anderem?

Wäre es möglich ein wenig über die Finanzierung der Kunststoffsammlung zu reden? Wenn ja, wie sehen die

Einnahmen respektive Ausgaben der einzelnen Prozessschritte aus? Resultiert im Ganzen ein Profit, Verlust

oder geht es gerade auf?

Was beobachten Sie/ haben Sie beobachtet bezüglich Konsumentenzufriedenheit und -adaption? Brauchte es

eine Weile, bis die Konsumenten von der Kunststoffsammlung so richtig gebraucht machten und haben Sie

das Gefühl, die Konsumenten sind zufrieden mit der Kunststoffsammlung?

INITIIERUNGSGRÜNDE

Könnten Sie mir erzählen, wie die Kunststoffsammlung initiiert wurde? Wer oder was gab den Anstoss?

Waren bestimmte Faktoren fördernd für die Lancierung? Zum Beispiel folgende:

- Sozialer Druck (z.B. von der lokalen Bevölkerung)

- Ein leidenschaftlicher Verfechter der den Prozess vorantrieb

- Makro-ökonomischer oder regulatorischer Druck

- Geschäftsmöglichkeiten

- Druck von einer Behörde (Gemeinde, Kanton, Bund)

- Wissenschaftliche Studie, Interne Begutachtung, Beratungsbericht

GESTALTUNG DER KUNSTSTOFFSAMMLUNG

Könnten Sie mir beschreiben, wer wie involviert war bei der Gestaltung der Kunststoffsammlung? Wie wurden

Entscheidungen getroffen und allfällige Konflikte gelöst?

58

War die Öffentlichkeit involviert?

Was waren die Gründe, dass Sie sich spezifisch für die Sammlung dieses Sammelguts entschieden haben?

Haben Sie irgendwelche Erfahrungen/Knowhow von anderen Plastikrecyclingprojekten in die Gestaltung der

Kunststoffsammlung miteinbezogen? Wenn ja, könnten Sie dies näher beschreiben?

GESCHICHTLICHER HINTERGRUND

Gab es ein Plastikrecyclingprojekt in der gleichen oder angrenzenden Region (Gemeinde/Kanton) innerhalb

von 3 – 5 Jahren vor Projektstart? Wenn ja, waren diese Projekte Erfolge oder Misserfolge?

Hat Ihre Organisation schon einmal an einem anderen Ort ein ähnliches Projekt lanciert?

KONTEXTANALYSE

Was waren die Vorbereitungen vor der Lancierung der Kunststoffsammlung? Wurde irgendeine Art von Analyse

betreffend technischer Machbarkeit, Wirtschaftlichkeit, Konsumentenbedürfnissen oder der gesetzlichen

Lage durchgeführt? Wenn ja, könnten Sie diese Analysen kurz beschreiben?

KOMPETENZ

Denken Sie das Knowhow /die Schulung Ihrer Mitarbeiter ist ein wichtiger Faktor für ihr Erfolg/Misserfolg?

Werden Ihre Mitarbeiter für Ihre Aufgaben speziell geschult?

Wie würden sie die Kunststoffsammlung bezüglich genügend und gut ausgebildeten Mitarbeitern einschätzen?

Wie würden Sie die Kompetenz Ihrer Partner einschätzen?

ABSATZMÖGLICHKEITEN

Was für eine Art Vertrag haben Sie mit Ihren wichtigsten Partnern?

Ist die Kapazität Ihrer wichtigen Partner genügend hoch?

Engagieren Sie oder Ihr Verarbeitungspartner sich in Forschung und Entwicklung?

Gibt es einen Markt für Plastikrecycling? Profitieren Sie von dieser Marktverfügbarkeit? Wenn nicht, wo sehen

sie die Möglichkeiten einen Markt für Plastikrecycling zu generieren?

Wie fest hängen Sie vom Marktpreis von Plastik oder Öl ab? Haben Sie gewisse Massnahmen getroffen um

dieses finanzielle Risiko zu vermindern?

KOMMUNIKATION

Wie häufig kommunizieren Sie mit Ihren Partnern? Haben Sie gewisse Konflikte mit Ihnen?

Mithilfe welcher Medien kommunizieren Sie mit der öffentlichen Bevölkerung? Wie häufig? Richten Sie sich

an ein bestimmtes Konsumentensegment?

Wie formulieren sie die Nachrichten an die öffentliche Bevölkerung?

ERFOLG, ERFOLGSFAKTOREN UND HINDERNISSE

Würden Sie sagen die Kunststoffsammlung ist ein Erfolg? Wenn ja, warum?

Wie würden Sie Erfolg in Bezug auf die Kunststoffsammlung definieren?

Was denken Sie waren Faktoren, die zu dem Erfolg/Misserfolg der Kunststoffsammlung beigetragen haben?

Was waren Hindernisse, wo standen Sie vor Herausforderungen? Wie reagierten Sie?

Was haben Sie seit der Lancierung der Kunststoffsammlung gelernt? Was war unerwartet, was würden Sie ein

nächstes Mal anders machen oder planen Sie zu ändern?

59

Calibration of outcome measures

Table 16: Direct calibration of the outcome collection rate

Case Scores Crossover Deviation from

Crossover Scalar Log odds

Set membership

scores

Case 1 3.3 13 -10 0.26 -2.5365 0.07

Case 2 1.7 13 -11 0.26 -2.9570 0.05

Case 3 1.4 13 -12 0.26 -3.0380 0.05

Case 4 21.3 13 8 0.11 0.9209 0.72

Case 5 0.7 13 -12 0.26 -3.2161 0.04

Case 6 8.6 13 -4 0.26 -1.1494 0.24

Case 7 4.5 13 -9 0.26 -2.2280 0.10

Case 8 9.9 13 -3 0.26 -0.8178 0.31

Case 9 21.0 13 8 0.11 0.8938 0.71

Case 10 45.5 13 32 0.11 3.6099 0.97

Case 11 35.9 13 23 0.11 2.5480 0.93

Case 12 17.3 13 4 0.11 0.4778 0.62

Case 13 20.6 13 8 0.11 0.8458 0.70

Case 14 29.9 13 17 0.11 1.8786 0.87

Case 15 26.9 13 14 0.11 1.5481 0.82

Case 16 23.4 13 10 0.11 1.1559 0.76

Case 17 15.9 13 3 0.11 0.3233 0.58

Case 18 18.4 13 5 0.11 0.5996 0.65

Case 19 0.5 13 -13 0.26 -3.2691 0.04

Case 20 10.2 13 -3 0.26 -0.7180 0.33

60

Table 17: Membership values for the calibration of the collection rate

full member-

ship

full non-

membership

Cross-over

point

value 40 1.5 13

scalars: 0.11 0.260869565

Table 18: membership values for the calibration of recycling rate

full member-

ship

full non-

membership

Cross-over

point

value 30 1.5 11

scalars: 0.16 0.315789474

61

Table 19: Direct calibration of the outcome recycling rate

Cases Scores Crossover Deviation from

Crossover Scalar Log odds Set membership scores

Case 1 2.1 11 -9 0.3158 -2.8011 0.06

Case 2 1.0 11 -10 0.3158 -3.1582 0.04

Case 3 1.3 11 -10 0.3158 -3.0631 0.04

Case 4 14.1 11 3 0.1579 0.4816 0.62

Case 5 0.6 11 -10 0.3158 -3.2934 0.04

Case 6 3.0 11 -8 0.3158 -2.5238 0.07

Case 7 3.8 11 -7 0.3158 -2.2767 0.09

Case 8 4.9 11 -6 0.3158 -1.9161 0.13

Case 9 20.0 11 9 0.1579 1.4197 0.81

Case 10 18.2 11 7 0.1579 1.1361 0.76

Case 11 34.1 11 23 0.1579 3.6530 0.97

Case 12 14.7 11 4 0.1579 0.5850 0.64

Case 13 16.5 11 5 0.1579 0.8668 0.70

Case 14 9.0 11 -2 0.3158 -0.6403 0.35

Case 15 25.6 11 15 0.1579 2.3031 0.91

Case 16 22.2 11 11 0.1579 1.7737 0.85

Case 17 13.5 11 3 0.1579 0.3984 0.60

Case 18 15.6 11 5 0.1579 0.7321 0.68

Case 19 0.4 11 -11 0.3158 -3.3406 0.03

Case 20 8.7 11 -2 0.3158 -0.7230 0.33

62

Raw data and calibration of analysed conditions

Table 20: Raw data of the two outcome measures and the analysed conditions

Case Recycling

rate

Collection

rate

selective

collection

high density

coll. sites history

cost for

consumers

supervised

collection

Case 1 2.1 3.3 mixed 0.32 yes yes more no

Case 2 1.0 1.7 mixed 0.20 no yes more no

Case 3 1.3 1.4 selective 0.32 yes yes more no

Case 4 14.1 21.3 mixed 53.47 no yes no

Case 5 0.6 0.7 selective 0.06 yes 0 yes

Case 6 3.0 8.6 mixed 0.43 no 0 no


Case 8 4.9 9.9 mixed 1.70 no 0 more no


Case 10 18.2 45.5 mixed 0.17 yes 0 yes


Case 12 14.7 17.3 selective 0.45 no 0 more yes

Case 13 16.5 20.6 selective 0.47 no 0 more no

Case 14 9.0 29.9 mixed 0.16 no 0 yes

Case 15 25.6 26.9 selective 0.12 no 0 yes

Case 16 22.2 23.4 selective 0.73 no 0 yes

Case 17 13.5 15.9 selective 0.19 no 0 more yes

Case 18 15.6 18.4 selective 0.04 no partly yes

Case 19 0.4 0.5 selective 0.33 yes 0 more yes

Case 20 8.7 10.2 selective 0.28 yes 0 more yes

Data sources for the conditions history, costs for consumers and supervised collection are the respective interviews/questionnaires

63

Table 21: Calculation density of collection sites

Case Settlement area

[km2]

Number of

collection points

Density coll.

Sites [points /

km2]

Case 1 166.2 53 0.3189

Case 2 1'230.8 250 0.2031

Case 3 79.0 25 0.3165

Case 4 3.8 - 53.4727

Case 5 54.4 3 0.0551

Case 6 23.3 10 0.4297

Case 7 23.3 2 0.0859

Case 8 5.9 10 1.7014

Case 9 5.9 1 0.1701

Case 10 5.8 1 0.1732

Case 11 19.9 12 0.6041

Case 12 39.8 18 0.4521

Case 13 14.8 7 0.4714

Case 14 6.4 1 0.1552

Case 15 8.1 1 0.1237

Case 16 2.7 2 0.7316

Case 17 3'096.8 600 0.1938

Case 18 22.9 1 0.0437

Case 19 557.3 186 0.3338

Case 20 3'096.8 860 0.2777

Data source of the settlement area: Regionalporträts 2016: Gemeinden - Kennzahlen; Bundesamt für Statistik; scource of the number of

collection points: interviews/ questionnaires

64

Table 22: Direct calibration of condition density of collection sites

Case Score Crossover

Deviation

from

Crossover

Scalar Log odds Set membership

scores

Case 1 0.32 0.5 -0.2 7.5 -1.3584 0.20

Case 2 0.20 0.5 -0.3 7.5 -2.2266 0.10

Case 3 0.32 0.5 -0.2 7.5 -1.3760 0.20

Case 4 53.47 0.5 53.0 3.00 158.9181 1.00

Case 5 0.06 0.5 -0.4 7.5 -3.3365 0.03

Case 6 0.43 0.5 -0.1 7.5 -0.5272 0.37

Case 7 0.09 0.5 -0.4 7.5 -3.1054 0.04

Case 8 1.70 0.5 1.2 3.00 3.6041 0.97

Case 9 0.17 0.5 -0.3 7.5 -2.4740 0.08

Case 10 0.17 0.5 -0.3 7.5 -2.4507 0.08

Case 11 0.60 0.5 0.1 3.00 0.3122 0.58

Case 12 0.45 0.5 0.0 7.5 -0.3589 0.41

Case 13 0.47 0.5 0.0 7.5 -0.2146 0.45

Case 14 0.16 0.5 -0.3 7.5 -2.5861 0.07

Case 15 0.12 0.5 -0.4 7.5 -2.8222 0.06

Case 16 0.73 0.5 0.2 3.00 0.6949 0.67

Case 17 0.19 0.5 -0.3 7.5 -2.2969 0.09

Case 18 0.04 0.5 -0.5 7.5 -3.4222 0.03

Case 19 0.33 0.5 -0.2 7.5 -1.2468 0.22

Case 20 0.28 0.5 -0.2 7.5 -1.6672 0.16

65

Table 23: Membership scores for the calibration of the condition density of collection sites

full member-

ship

full non-

membership

cross-over

point

value: 1.5 0.1 0.5

scalars: 3.00 7.5

Table 24: membership values for the calibration of the condition communication

full member-

ship

full non-

membership

cross-over

point

value: 11 2 6.5

scalars: 0.67 0.6667

66

Table 25: Measurement of communication

Abfallkalender Website

Flyer/

notes at

collectio

n site

Newsletter

s

local

newspapers newspapers

Radio,

TV,

social

media

special

event

Communicatio

n score

Reach of each channel

(1: low; 2: high)

2 1 1 1 2 2 2 1

Case 1

2

2

1

2 8

Case 2

2 1 2

1

7

Case 3

2 1 2

5

Case 4 1 1 1

2 1

2 12

Case 5 1 1

3

Case 6 1 1 1

1

6

Case 7 1 1 1

1 1

8

Case 8 1 1

1 1

6

Case 9 1 1 1

1 1 1 2 12

Case 10 1 1 1 1

1

7

Case 11 1 1 1 1

1

7

Case 12 1 1 1 2

1

2 10

Case 13 1 1 1

1

1 7

Case 14 1 1

1

5

Case 15 1 1

1

5

Case 16 1 1 1 2 1 1

10

Case 17

1 1

1 1 1 2 10

Case 18 1 1 1

4

Case 19

1

1

Case 20

1 1

2 1

8

67

Table 26: Direct calibration of the condition communication

Case Score Crossover Deviation from

Crossover Scalar Log odds

Set

membership

scores

Case 1 8.00 6.5 1.5 0.6667 1.0000 0.73

Case 2 7.00 6.5 0.5 0.6667 0.3333 0.58

Case 3 5.00 6.5 -1.5 0.6667 -1.0000 0.27

Case 4 12.00 6.5 5.5 0.6667 3.6667 0.98

Case 5 3.00 6.5 -3.5 0.6667 -2.3333 0.09

Case 6 6.00 6.5 -0.5 0.6667 -0.3333 0.42

Case 7 8.00 6.5 1.5 0.6667 1.0000 0.73

Case 8 6.00 6.5 -0.5 0.6667 -0.3333 0.42

Case 9 12.00 6.5 5.5 0.6667 3.6667 0.98

Case 10 7.00 6.5 0.5 0.6667 0.3333 0.58

Case 11 7.00 6.5 0.5 0.6667 0.3333 0.58

Case 12 10.00 6.5 3.5 0.6667 2.3333 0.91

Case 13 7.00 6.5 0.5 0.6667 0.3333 0.58

Case 14 5.00 6.5 -1.5 0.6667 -1.0000 0.27

Case 15 5.00 6.5 -1.5 0.6667 -1.0000 0.27

Case 16 10.00 6.5 3.5 0.6667 2.3333 0.91

Case 17 10.00 6.5 3.5 0.6667 2.3333 0.91

Case 18 4.00 6.5 -2.5 0.6667 -1.6667 0.16

Case 19 1.00 6.5 -5.5 0.6667 -3.6667 0.02

Case 20 8.00 6.5 1.5 0.6667 1.0000 0.73

68

Results

QCA results

Figure 13: XY plot for the condition no costs for users and the outcome high recycling rate

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Hig

h R

ecycling R

ate

No costs for consumers

69

Sensitivity analyses

Table 27: Results of the sensitivity analysis of the collected amount on the recycling rate

baseline sensitivity

Case recycling rate [%] recycling rate [%]

Case 1 2.1 2.1

Case 2 1.0 1.0

Case 3 1.3 1.3

Case 4 14.1 17.6

Case 5 0.6 0.7

Case 6 3.0 3.0

Case 7 3.8 3.8

Case 8 4.9 4.9

Case 9 20.0 20.0

Case 10 18.2 18.2

Case 11 34.1 42.7

Case 12 14.7 14.7

Case 13 16.5 16.5

Case 14 9.0 9.0

Case 15 25.6 25.6

Case 16 22.2 22.2

Case 17 13.5 13.5

Case 18 15.6 15.6

Case 19 0.4 0.4

Case 20 8.7 10.9

70

Table 28: Results of the sensitivity analysis of the specific recycling rate on the recycling rate

baseline sensitivity

Case recycling rate [%] recycling rate [%]

Case 1 2.1 2

Case 2 1.0 1

Case 3 1.3 1

Case 4 14.1 14

Case 5 0.6 0

Case 6 3.0 3

Case 7 3.8 3

Case 8 4.9 5

Case 9 20.0 20

Case 10 18.2 18

Case 11 34.1 34

Case 12 14.7 15

Case 13 16.5 16

Case 14 9.0 9

Case 15 25.6 26

Case 16 22.2 22

Case 17 13.5 14

Case 18 15.6 12

Case 19 0.4 0

Case 20 8.7 9

71

Table 29; Truth table for the sensitivity analysis of the recycling rate to a different cross-over points in its calibration

Selective

Collection

High

Density of

Coll. Sites

History Communication Supervised

Collection

High

Recycling

Rate

cases raw consist.

1 0 1 1 1 0 7, 9, 20 0.659

1 0 0 0 1 1 15, 18 1.000

1 0 1 0 1 0 5, 19 0.332

1 0 0 1 1 1 12, 17 1.000

0 0 0 0 0 0 6 0.368

0 1 0 0 0 0 8 0.521

1 0 1 0 0 0 3 0.268

0 0 0 1 0 0 2 0.368

1 0 0 1 0 1 13 1.000

0 1 0 1 0 0 4 0.645

0 0 1 1 0 0 1 0.104

0 0 0 0 1 1 14 0.788

1 1 0 1 1 1 16 1.000

0 0 1 1 1 1 10 0.790

1 1 1 1 1 1 11 0.856

72

Table 30: Truth table for the sensitivity analysis of the recycling rate to a different cross-over point for the calibration of the condition high density of collection sites

Selective

Collection

High Density

of Coll. Sites History Communication

Supervised

Collection

High

Recycling

Rate

cases raw consist.

1 0 1 1 1 0 7, 9, 20 0.550

0 1 0 0 0 0 6, 8 0.371

1 0 0 0 1 1 15, 18 1.000

1 0 1 0 1 0 5, 19 0.303

1 1 0 1 1 1 12, 16 1.000

1 0 1 0 0 0 3 0.270

0 0 0 1 0 0 2 0.346

0 1 0 1 0 0 4 0.522

1 1 0 1 0 1 13 1.000

0 0 1 1 0 0 1 0.091

0 0 0 0 1 0 14 0.691

1 0 0 1 1 1 17 0.968

0 0 1 1 1 1 10 0.782

1 1 1 1 1 1 11 0.822

73

Table 31: Truth table for the sensitivity analysis of the recycling rate to a categorization of the retailer’s supervision as less supervised

Selective

Collection

High Density of

Coll.S ites History Communication

Supervised

Collection

High Recycling

Rate cases raw consist.

1 0 1 0 0 0 3, 19 0.211

1 0 0 1 0 1 13, 17 0.955

1 0 0 0 1 1 15, 18 1.000

1 0 1 1 1 0 7, 9 0.636

0 0 0 0 0 0 6 0.346

0 1 0 0 0 0 8 0.421

0 0 0 1 0 0 2 0.346

0 1 0 1 0 0 4 0.541

0 0 1 1 0 0 1 0.090

1 0 1 1 0 0 20 0.406

0 0 0 0 1 0 14 0.691

1 0 1 0 1 0 5 0.357

1 0 0 1 1 1 12 1.000

1 1 0 1 1 1 16 1.000

0 0 1 1 1 1 10 0.782

1 1 1 1 1 1 11 0.856

74

Table 32: Solution terms for the sensitivity of the recycling rate to a different cross-over points in its calibration

raw

coverage

unique

coverage



communication 0.314 0.119 0.889 12, 17, 16, 13

~high density of collection sites *

~history * ~communication *


0.274 0.170 0.834 18, 14, 15

~selective collection * history *

communication * supervised

collection

0.099 0.091 0.79 10




0.256 0.088 0.941 16, 11



Table 33: Solution terms for the sensitivity of the recycling rate to a different cross-over point for the calibration of the condition high density of collection sites.

raw

coverage

unique

coverage



supervised collection 0.411 0.209 0.973 12, 15, 16, 17, 18


collection sites * ~history *

communication

0.228 0.026 1 16, 13, 12



collection

0.111 0.1 0.782 10




0.323 0.11 0.925 16, 11, 12



75

Table 34: Table 30: Solution terms for the sensitivity of the recycling rate to a categorization of the retailer’s supervision as less supervised.

raw

coverage

unique

coverage



communication 0.335 0.06 0.834 12, 17, 16, 13


supervised collection 0.38 0.104 0.991 12, 15, 16, 18



collection

0.111 0.102 0.782 10




0.291 0.1 0.941 16, 11



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