Sustainability in returns

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DEGREE PROJECT ENVIRONMENTAL ENGINEERING, SECOND CYCLE, 30 CREDITS

,

STOCKHOLM SWEDEN 2020

Sustainability in returns

Analysis into the e-commerce market and

proposal of a framework to improve

environmental performance

LUCAS VELDKAMP

KTH ROYAL INSTITUTE OF TECHNOLOGY

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Abstract

The e-commerce sector has seen exponential growth in the recent years, and will continue this trend in the years to come. Not only has the overall volume of sales (in SEK) increased, certain sectors have seen an increase in the return rates1. This combi-nation leads to a significant increase in both the environmental and financial impact of these returns, as they have become a substantial part of day to day operations for these businesses.

The industry in the Nordics has been analyzed in order to set up a framework that can tackle the environmental impact of the returns in the e-commerce sector. The analysis has been based on semi-structured interviews with selected merchants in the industry, and the data of the interviews has been supplemented with quantitative data from a survey.

The analysis has led to certain common pain points in the industry. These form the backbone of the framework, which will be thoroughly discussed and analyzed in the discussion. Important points of the framework, and therefor the discussion, are related to general consumer behavior. This has lead to a discussion which entails the general aspect of consumer behavior, rather than a discussion purely limited to the returning aspect.

After the discussion it has been concluded that there is most definitely place for improvement and that the framework can assist in this aspect, albeit in a limited manner. It can also be said that purely looking at reducing the environmental impact of returns has limitations, and that a more useful approach would be to investigate both the sector and the consumer behavior as a whole. It is necessary to reduce the environmental impact of the sector, and as the majority of impacts in the sector come from production or waste management, the real changes should occur there, and not necessarily in the returning phase. Finally, the role of Klarna is raised and how the company is in an influential position to address the issues in the sector.

1_{The volume (in SEK) of items being returned to the merchant as percentage of the overall volume}

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Sammanfattning

E-handeln har under de senaste åren växt exponentiellt och trenden förväntas bara fortsätta. Säljvolymerna har inte bara ökat utan man ser även en ökning av antalet returer.2_{. Dessa faktorer bidrar till ökad påverkan på både miljön och ekonomin,}

eftersom de har blivit en del av den dagliga verksamheten för företagen.

För att hantera problemet med ökad miljöpåverkan, till följd av expansionen av returer, har ett ramverk skapats baserat på en analys av industrin i Norden. Analy-sen har baserats på semistrukturerade intervjuer med utvalda försäljare inom bran-schen, kompletterat med kvantitativ data från en enkätundersökning.

Analysen har identifierat gemensamma nyckelfrågor inom branschen som utgör ryggraden i ramverket och har analyserats vidare i diskussionen. Viktiga frågor i ramverket och således diskussionen kan relateras till konsumentbeteende, vilket har lett till en fördjupning i diskussionen kring detta, istället för att enbart fokusera på returer.

Sammanfattningsvis kan det sägas att det finns möjlighet för förbättring och att ramverket kan bidra till detta, om så i begränsad utsträckning. Genom att enbart undersöka hur man kan minska påverkan på miljö till följd av ökade returer är ett begränsat tillvägagångssätt. En annan infallsvinkel, där både branschens och kon-sumenternas beteende analyseras, skulle vara lämpligare. Det är viktigt att minska branschens miljöpåverkan, men eftersom den största påverkan kommer från pro-duktionen eller hantering av avfall, så bör de största förändringarna ske där och inte nödvändigtvis i returfasen. Slutligen beskrivs Klarnas inflytande i frågan och hur de som företag kan ta ställning till, samt ifrågasätta problematiken inom branschen.

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Acknowledgment

I could not have imagined a better ending to my academic career as the one I have had here at Klarna. Even though the last few weeks have been a bit of a roller coaster3_{, writing my thesis here has been a great experience and I am amazed by}

how the time flew by. I have had amazing support from everyone here at Klarna, and I am very grateful for the help I have received. I could not have imagined that binge-watching CNBC business videos4_{would have been the inspiration for my}

the-sis work, but I am glad I sacrificed that one rainy Sunday afternoon.

First and foremost, I’d like to thank Jack for his support, time and patience dur-ing the last few months. I have asked many questions, and I could always get an answer or some of his time when it was necessary. Without his ideas and feedback the thesis would have looked significantly different (read worse) than it is right now. Secondly, I would like to thank Larsgöran. From day one he has been supportive, and has helped me steering into the right direction and the two of them have been a good supervising duo during the last 20 weeks. I’m happy to have worked in the re-turns modeling team with Naomi. Even though we did not directly work together, it was great to have her there during the weekly and sometimes even daily stand ups. Also for the questions she has asked me during my time at Klarna, including the most important one, albeit slightly paraphrased: "What are you actually trying to do?"

I would not have been able to interview this number of merchants if it wasn’t for the commercial team at Klarna, who have been crucial in connecting me to specific merchants. Special gratitude goes to Sofia and Josefin, who helped me getting in touch with more than half of the merchants, and took the time to be present during the interviews. Furthermore, I would like to thank Paulina who has been crucial in the creation of the survey. Without her the survey would not have been possible, and I would have had missed out on a large quantity of data.

Although the last months have been hard work, I am also grateful for the people who have had a role in getting my mind of the work. I’d like to thank every one who has supported me in the recent weeks, but unfortunately I have limited space on this one piece of paper, so I cannot mention you all by name. I have had a great time at the office during the lunches and fika’s with Cecilia, Filip, Josefin & Paul and it would be great if we could continue that in the future.

Elif and Valentina have been a great support during the weekends and evenings. Working from home and living with the two of you in this time has been a great experience, and I am happy to have shared this exciting but weird time with you.

And last, but not least, I’d like to thank Sara. The evening walk and talks have been a great support. Furthermore, as my first and best Swedish friend, I’m grateful that she’s helped my out on several occasions with translations to Swedish.

Lucas Veldkamp Stockholm, May 2020

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2.4.2 Data limitations . . . 7 2.5 Exclusions . . . 8 3 Methodology 9 3.1 Data . . . 9 3.2 Selection criteria . . . 9 3.2.1 Merchant size . . . 10 3.2.2 Merchant category . . . 10 3.2.3 Merchant location . . . 11 3.3 Final selection . . . 12 3.4 Interviews . . . 13 3.5 Survey . . . 14 3.6 Analysis . . . 15

3.6.1 Life Cycle Analysis . . . 15

3.6.2 Multi criteria Analysis . . . 16

3.7 Framework. . . 17 3.7.1 Perspective . . . 17 3.7.2 Breakdown . . . 18 3.7.3 Comparative assessment. . . 19 4 Results 23 4.1 Interviews . . . 23 4.1.1 Painpoints . . . 23

Large increase in returns during sales period . . . 23

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Returns due to wrong sizing . . . 24

Abuse of return policy . . . 24

High revenue, high return rate customers . . . 25

Environmental impact related to shipping . . . 25

Expensive return shipping from other countries . . . 25

Unaccepted returns. . . 25

Return processing between consumer and merchants . . . 25

4.2 Survey . . . 25 4.2.1 Respondents. . . 26 4.2.2 Singular results . . . 26 4.2.3 Cross results. . . 26 4.3 Summary . . . 31 5 Framework 33 5.1 Structure . . . 33 5.2 Formulation of options . . . 34 5.3 Segmentation . . . 34 5.4 Pre-purchase . . . 34

5.4.1 Large increase during sales period . . . 35

Take preliminary actions against suspicious orders . . . 35

Reduce advertising for items high a high return risk . . . 36

5.4.2 Consumer behavior in fast fashion . . . 36

Educate consumers . . . 36

Shift towards a longer life cycle . . . 37

Creation of an environmental standard . . . 37

Life cycle ownership . . . 38

Discounts on shipping if items are recycled . . . 38

Increase the life time usage . . . 39

5.5 Purchase . . . 39

5.5.1 Returns due to wrong sizing . . . 39

Improve sizing information . . . 40

Remind customers of sizing recommendations . . . 40

Use 3rd party solutions . . . 41

5.5.2 Abuse of return policy . . . 41

Blocking abusing customers . . . 41

Reaching out to abusing customers. . . 41

5.5.3 High revenue, high return rate customers . . . 41

5.6 Shipping . . . 41

5.6.1 Environmental impact due to shipping . . . 42

Carbon compensated shipping . . . 43

Local waste management . . . 43

Shipping collaboration . . . 43

Decrease direct shipping options . . . 44

Recycling of packaging . . . 44

5.7 Returning . . . 44

5.7.1 Expensive return shipping. . . 45

5.7.2 Unaccepted returns. . . 45

5.8 Pre-purchase assessment . . . 46

5.9 Purchase assessment . . . 47

5.10 Shipping assessment . . . 48

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ix 6 Discussion 51 6.1 Priorities . . . 51 6.2 (Fast) Fashion . . . 52 6.2.1 Recent changes . . . 52 6.2.2 Impact of fashion . . . 52 6.2.3 Future projections . . . 53 6.3 Klarna . . . 53 6.3.1 Consumer education . . . 54 6.3.2 Environmental standard . . . 54

6.3.3 Life cycle ownership . . . 54

6.4 Interviews . . . 55 6.5 Survey . . . 55 6.5.1 Sample group . . . 55 6.5.2 Questions . . . 56 6.5.3 Languages . . . 56 6.6 Analysis . . . 56 6.6.1 Geographical scope. . . 56 6.6.2 Analysis perspective . . . 57 6.7 Framework. . . 57 6.8 Subjectivity. . . 57 7 Conclusion 59 7.1 General . . . 59 7.2 Actions . . . 59 7.3 Merchant groups . . . 60

7.4 Potential for Klarna . . . 60

7.5 Future Research . . . 60

Bibliography 61

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List of Figures

1.1 Growth of worldwide e-commerce in the recent years . . . 2

1.2 Gradual increase in return rates over the years . . . 3

2.1 The Nordic countries . . . 6

2.2 Flowchart of the problem space . . . 7

2.3 Population Density in Europe . . . 8

3.1 Percentage of returns per category . . . 12

3.2 Return rate per category . . . 13

3.3 Basic flowchart . . . 16

3.4 Example of a planning and implementation process . . . 18

3.5 Example of the comparative assessment . . . 20

4.1 Sales vs Returns of M3 over time . . . 24

4.2 Survey result, question 1 . . . 26

4.5 Survey result. . . 28 4.6 Survey result. . . 28 4.7 Survey result. . . 29 4.8 Survey result. . . 29 4.9 Survey result. . . 30 4.10 Survey result. . . 30 4.11 Survey result. . . 31 4.12 Survey result. . . 31

5.1 Phase 1 of the framework . . . 35

5.2 Municipal solid waste . . . 39

5.5 European Waste Generation . . . 44

5.7 Comparative assessment of phase 1 of the framework . . . 47

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List of Tables

2.1 Population density and rank of the Nordic countries. . . 7

3.1 Merchant size based on revenue through Klarna . . . 10

3.2 Volume and percentage of returns . . . 11

3.3 Merchants and other companies interviewed . . . 14

3.4 Cross-tabulation for the language preference and the merchant category 15 3.5 Scoring used in the multi criteria assessment . . . 19

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Acronyms

GHG Greenhouse gas emissions. 39

LCA Life cycle analysis. 15

MCA Multicriteria analysis. 16

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Glossary

COVID-19 The global pandemic as a result of the novel corona virus. 1

Framework A basic structure underlying a system. 5

Kyoto protocol UN treaty on a commitment to reduce greenhouse gases. 2

Nordics Geoghrapical area of Norway, Finland, Sweden and Denmark. 5

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Chapter 1

Introduction

Amazon.

What did you think of? The rain-forest?1Or a certain internet giant?2. And why did you think that?

1.1 Growth of e-commerce

E-commerce has been growing in the double digits year over year since the change of the millennium (Figure 1.1; Bogue,2016). Not only has e-commerce seen an impres-sive growth so far, it appears to keep on growing, even though the world around it is falling into a deep depression as a consequence of the COVID-19 outbreak (McK-insey & Company,2020). Growing as much even that companies such as Amazon have hired more than 75000 customers to keep up with that demand when there are record levels of workers on unemployment benefits (Palmer,2020). The massive growth has led to not only the richest man on earth, it also leads into an incredible impact on the society and the environment (Forbes,2020; Morgan,2019). There are countless ways one could measure or express the growth in this market section, but all of them say the same: The growth has been enormous, and there is more to come. With this in mind, it is good to investigate what the effects of this growth have been. There are numerous perspectives one could look at, varying from socioeconomic, where one cold look at the growing inequality as a consequence from this growth3, to the environmental aspect, which will be further investigated and is the main area of interest in this thesis.

1.2 Introduction of returns

One of the issues related to the aforementioned growth in sales, is not only the en-vironmental impact associated with it, there is also a growth in the Return rate (see

Figure 1.2). The return rate is the volume of goods that is returned to a merchant (in SEK in this research) divided by the volume of goods that is captured (in SEK in this research). This increase in return rate is caused by many factors, and the analysis of this increase can be a thesis of its own. Returns are associated with complex, cost in-effective reverse logistics which can cost merchants up to as 4 times as much as the original shipping (XiaoYan et al.,2012; Swisslog,2018). Because of these aspects, it is relevant and crucial from a business perspective to look into the return problem

1_{Amazon rainforest} 2_{The internet giant}

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2 Chapter 1. Introduction space. Another, and perhaps overlooked, perspective, is the environmental perspec-tive. The reverse logistics do not only lead to an increase in costs for the merchants, there is also an increase in environmental impact overall. Items and goods have to be shipped back to the fulfillment center, washed, repackaged, repaired, and each of these steps add on to the overall impact of a specific item. This aspect makes it worth to investigate the possibility of reducing the returns, or the environmental impact of the returns.

1.3 Environmental Awareness

Society has come a long way regarding the awareness of our environmental impact, and we have become a lot more aware of how we influence and interact with our surroundings (Vallero and Letcher, 2011). Some good examples can be found in e.g. the banning of unleaded fuel and the adoption of the Kyoto protocol(Stolark,

2016; UNFCCC,2005). Research even suggests that environmentally aware behav-ior of companies tends to get rewarded with a positive effect on the stock market, although this has effect has been decreasing overt time. This decrease has its ori-gins in the growing environmental awareness of stakeholders and consumers, who expect environmental awareness to be the standard rather than the exception. This trend has led to the opposite effect, where companies who are not as environmen-tally aware tend to experience a negative effect on the stock market (Flammer,2013). The question is how we can use this environmental awareness, and how we can ap-ply it to the high returns in e-commerce, and whether it is possible to reduce the environmental impact of these returns.

FIGURE1.1: Growth of worldwide e-commerce in the recent years There has been significant growth over the years in the worldwide e-commerce market (data fromstatista). The years 2020-2023 are

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1.4. Klarna 3

FIGURE1.2: Gradual increase in return rates over the years In the recent years there has been a gradual growth of not only the revenue of merchants, also the return rate. (Klarna AB,2020). Data is for the 10 biggest merchants using the Klarna platform, excluding Wish (see section2.5) (Figure made usingQliksense, which is experi-encing difficulties with the font-size. This should be fixed in the final

version)

1.4 Klarna

Klarnais a Swedish unicorn startup4_{which is operating in the financial technology}

space. Klarna is one of the companies that profits from the growth in e-commerce, and can even be seen as one of the drivers of this growth in e-commerce through their products aimed at both consumers and merchants intended to make the overall purchase process easier for both parties.

The thesis proposal was not proposed by Klarna, but there was the possibility to work together. Work was conducted at the Klarna headquarters in Stockholm in collaboration with the Merchant Shipping team which has greatly improved the outcome of the thesis. Even though work has been conducted in close collaboration with Klarna, it is an objective research into the e-commerce sector and the environ-mental impact related to the returns.

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Chapter 2

Aim and Objectives

The aim and objectives of this thesis are related to the environmental issues as a consequences to returns in e-commerce.

2.1 Aim

The aim of this thesis is to lay the foundations for a Framework for Klarna’s business customers in the Nordic countries1 to improve their return strategy from, but not limited to, an environmental perspective. It is expected that not only the merchants using the framework could use the platform to improve their environmental im-pact and their performance, it is also expected that the financial benefits are closely related to the environmental improvements of these companies (Cheremisinoff and Bendavid-Val,2001). Furthermore, as a large number of Klarna’s business customers consists of SME’s (small to medium enterprises), and as studies suggest this group is significantly challenged by environmental issues compared to larger enterprises (Brammer, Hoejmose, and Marchant,2011), the framework can help these SMEs with a small step in the right direction. As over 99% of business’ in the EU are SMEs, there is a huge potential for improvement (European Commission,2017).

2.2 Objectives

In order to achieve the aim of the thesis, it is important to fulfill the objectives, which means to:

• Identify possible partners in specific subgroups through analysis of return data and relevance to the research.

• Analyse return logistics and operations of business customers in Sweden through:

– Interviews conducted with selected companies, such as large merchants operating in the Nordics,or smaller merchants with interesting trends.

– Questionnaire results of merchants in the Nordics,

– Expert opinions on specific areas of interest

– Literature studies.

• Identify challenges and weaknesses, and define areas of improvement within these challenges and weaknesses.

1_{The official definition of the Nordics includes Greenland, Iceland, the Faroe Islands (and any other}

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6 Chapter 2. Aim and Objectives • Set-up the foundations for the framework

• Analyse the framework using various tools to determine the best alternative for specific categories and companies

• Communicate results through presentations, reports and final thesis.

FIGURE2.1: The Nordic countries

https://commons.wikimedia.org/wiki/File:Nordic_countries_ orthographic.svg

2.3 Perspective

The perspective of the research which is necessary to develop the framework is from an outside perspective and has an objective look and approach on the problem space of returns in e-commerce. The solution will not only be in the domain of the returns process, as there are multiple focus areas related to the prevention of online returns (e.g. through consumer manipulation). The perspective of the framework is from Klarna, and it is intended to provide merchants with knowledge on how to improve their environmental performance, and reduce their operating costs.

2.4 Limitations

There are certain limitations related to the research, which are a result of the scope of the thesis and the level of data collection through the interviews.

2.4.1 Scope related limitations

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2.4. Limitations 7

FIGURE2.2: Flowchart of the problem space

The flowchart offers a basic overview of the problem space and the research focus of this thesis. The pink line represents the cash flow of the consumer to the merchant. Note that the pink line is limited in the description (the merchant is paid straight away, and the risk lies at Klarna during the time the customer has to pay the invoice. When the consumer returns, the invoice is cancelled, en the money is

returned to Klarna by the merchant)

. The Blue line represents the product flow to the customer. The red line represent the return process. The red line is the focus point of this research, although the blue

and the pink line will be touched upon.

TABLE2.1: Population density and rank of the Nordic countries. The rank is based on the population density of other countries in

Eu-rope. Based on:Eurostat

Country Population Density (p/km2) Rank

Iceland 3.4 1

Norway 17.1 2

Finland 18.1 3

Sweden 24.7 4

Denmark 137.3 28

Not only is there a limitation in the geographical sense, the merchants themselves are limited as well. As merchants who use the services of Klarna are mostly used, there is a certain limitation in the sense of companies involved. If companies are in-terviewed who do not use the services of Klarna, it will not be possible to understand and analyse their operations with the data owned by Klarna. It is expected that the data will complement the qualitative research into their operations, and therefore it is desirable to work together with Klarna merchants.

Finally, fixing the entire problem of returns in e-commerce is not within the scope of this thesis. There are limitations in this part as well, as the thesis is foremost meant to be an introduction into the problem space. The framework is meant to guide certain merchants into the right direction, and will hopefully set more in motion, however, it is not intended as all inclusive solution.

2.4.2 Data limitations

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8 Chapter 2. Aim and Objectives

FIGURE2.3: Population density in Europe

NordregioNote the distinct difference in population density between the nordics and the rest of mainland Europe, and also the distinct

Urban areas in Sweden, Norway and Finland.

this, it has to be noted that the data that will be gathered through the interviews will definitely have limitations related to accuracy and integrity.

2.5 Exclusions

One of the biggest exclusions in this research is Wish. Wish is one of the biggest sellers on the Klarna platform in the Nordic countries, however, the platform is a very specific company2 in the market, and therefore it is excluded of the research. Also, findings related to the business and return operations of Wish are not expected to be usable or effective on the companies for which the final framework is aimed for.

2_{The company has a very low value per item, and ships an extremely large volume which results}

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Chapter 3

Methodology

The research will be focused on an analysis of the existing return policy and strategy of merchants operating in the Nordic region. Looking into the strategy and oper-ations of several types of merchants will give inside information in the Nordic e-commerce market. The merchants themselves can be categorized into different sales volumes and market segment, which will lead to a more in-depth analysis of the overall problem space. Not only will the analysis be more comprehensively through the usage of a large number of merchants from different categories and revenue size. It will also offer improved insights on the complexity of the issue which will allow the final framework to be more inclusive and at the same time be more suited for a wide variety of merchants. The data for this research will be provided through qualitative and quantitative interviews, in combination with existing literature data, on-going projects within Klarna or other companies. After the initial analysis of the interview data the information can be used to create a framework which can be used to look into the problem space of returns in e-commerce and suggest solution for merchants operating in the Nordic e-commerce. The research as a whole can be seen as a mixed method research, in which several techniques, methods, approaches and theories are all used and combined in one single study (e.g. quantitative and qualitative interviews, environmental analysis,multi-criteria analysis) (Johnson, On-wuegbuzie, and Turner,2007).

3.1 Data

There are various types of data used in this research, the two most important types of data are the qualitative data of the interviews, and the quantitative as provided by Klarna and the survey. The qualitative data is related to how the merchants per-ceive the problem space of returns in e-commerce, and how they operate within this problem space.

3.2 Selection criteria

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10 Chapter 3. Methodology

3.2.1 Merchant size

The merchant size is based on the volume of sales through the Klarna payment sys-tem in which Klarna can collect data on isys-tems sold. The data set used for the deter-mination of the merchant size and initial return rate stretches 3 years back (the data set spans 2017-01 : 2019-12), however, it has not a complete record for all the mer-chants during this time. There are various reasons for this, but the most common ones are that there is simply an incomplete data set because the merchants were not customers.

TABLE3.1: Merchant size based on revenue through Klarna.

Size Revenue

Large >100 Million SEK Medium 10-100 Million SEK Small <10 Million SEK

The revenue is based on the corresponding sales value in SEK. These sales have not always been conducted in Sweden, and correspond to sales to customers who have bought something through a Klarna service with a shipping address in the Nordic countries. Currencies have been conversed appropriately.

This data is used to generate an initial overview on the returns and sales of a com-pany, however, this is purely the returns and sales through the services of Klarna. This means that the numbers are not representative for the actual sales and returns figures for the companies or categories, as it could be that other volumes of sales and returns captured by a different payment method are not registered in the Klarna system. Furthermore, it depends on the specific product offered how much of the sales is captured through the product compared to other sales methods.

3.2.2 Merchant category

Within Klarna the merchants are categorized in 10 diferent merchant groups. These categories cover all of the merchants using their services, and these categories are the following:

• Electronics

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3.2. Selection criteria 11 • Other

One can imagine that each of the specific categories has its challenges, and it is important to differentiate between these categories. The differentiation is required, because each specific category varies in items, which in turn have various different characteristics. As these characteristics change, so does the problem space within each of these groups. Also, it is important to know the sales volume for each of these different categories, as it is important to know the volume of sales in the selection of the companies which will be included in the research. Figure 3.1clearly shows that the vast majority of the returns is made up by just two categories. These categories are Clothing & Shoes and Leisure, Sport & Hobby. The other two biggest categories are Home & Garden and Electronics. With the selection of these four categories 89.2% of the sales are covered, and a total of 41.23 BSEK (Table 3.2). (Klarna AB,

2020) The analysis of these four categories will therefore represent the vast majorities of sales within the merchants using the Klarna platform, and at the same time it also covers the categories with on average the highest return rates. Therefore it is justified to analyse these four categories, and to use this analysis for the creation of the framework, as this will be applicable to the vast majority of merchants.

TABLE3.2: Volume and percentage of returns

The revenue is based on the corresponding sales value in SEK. These sales have not always been conducted in Sweden, and correspond to sales to customers who have bought something through a Klarna service with a shipping address in the Nordic countries. Currencies

have been conversed appropriately. Category Returns (BSEK) % Clothing & Shoes XX XX Leisure, Sport & Hobby XX XX Home & Garden XX XX Electronics XX XX Total XX XX 3.2.3 Merchant location

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FIGURE3.1: Percentage of returns per category

The categories include the percentage of returns per category in the data of Klarna, this includes the data for smaller and medium mer-chants, and merchants outside the geographical area as specified by the study. (Figure made usingQliksense, which is experiencing

diffi-culties with the font-size.)

3.3 Final selection

The pre-selection of companies consisted of roughly 75 companies. As it is expected that not all companies will participate in the research project, the pre-selection is significantly larger than the final number of companies to be interviewed.

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3.4. Interviews 13

FIGURE3.2: Return rate per category

The categories include the percentage of return rate per category in the data of Klarna, this includes the data for smaller and mer-chants, and merchants outside the geographical area as specified by the study. The return rate is quantified as the quantity of captured volume (in SEK) and divided by the quantity of total returns (in SEK). This includes partial returns (a partial return is a return of which the whole order has not been returned, but a part has been e.g. 2 items on the order, but only 1 item has been returned). (Figure made using

Qliksense, which is experiencing difficulties with the font-size.)

3.4 Interviews

There are several different types of interviews, each leading to a certain outcome and type of data collection. For this research the interviews can be categorized as semi-structured and qualitative. Of course there is space for quantitative data as a result from the interviews, as quantitative data is needed in order to improve the findings, perspective and opinion compared to using purely qualitative data. (Ulmer and Wilson,2003) The goal of the research is not to define how much returns there are, or to quantify the problem. It is to identify and figure out why certain behavior and processes are occurring in the return processes in e-commerce, and to define a framework to combat this1. Qualitative interviews are used in this research, as they are used to obtain as much as possible information on reasoning and ideology behind the current returns process, rather than using the interviews to quantify the

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TABLE3.3: Merchants and other companies interviewed

Company Code Category Sales (MSEK) (2017-2020)

Return rate (2018-2020

Merchants

M1 Clothing & Shoes XX XX%

M2 Leisure, Sport & Hobby XX XX%

M5 Home & Garden XX XX%

M8 Jewellery XX XX%

M9 Electronics XX XX%

Logistics

L1 Logistical N/A N/A

L2 Logistical N/A N/A

Third party

logistics P1 Third party supplier N/A N/A

issue, because most useful for the aforementioned objective. (Sutton and Zubin,

2015)

The goal of the interviews is to obtain relevant information about the operations within the merchants, and to discover the common issues which are identified by the merchants themselves. Furthermore, there will be deviations in the questions between several companies, but in general they have been asked the same (type of) questions.

It is also important to gain insight on the day to day operations and their strate-gies2. Furthermore, there is space and a certain necessity to obtain data from the logistics companies related to the e-commerce, from companies such as Postnord,

Budbee, UPS andDHL and include opinions and information from their perspec-tive as they are significantly involved in the problem space of e-commerce returns.

The purpose of the interviews is not only to obtain more information about the problem space. The other aspect of the interviews is to discover what several e-commerce companies have done thus far to try and combat the problem space so far. What measures have certain companies taken, and what has been the effect of their actions so far. By making use of of this element of their knowledge, the framework itself can be improved with knowledge already obtained by certain companies.

3.5 Survey

Surveys are a very good way to collect large quantities of information (Nardi,2018). In order to complement the data from the interviews, a survey has been used. The survey has been send out to over 6000 companies in the Nordics (Table 3.4), with a response rate of 6.00%. Each survey has been sent to the preferred language by the merchant, in order to have the highest response rate possible. The results to the

2_{In this case one should think of the supply lines in the transport network, are there similar there}

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3.6. Analysis 15

TABLE 3.4: Cross-tabulation for the language preference and the

merchant category

Category/Language Swedish Norwegian Danish Finnish Total

Home & Garden 1035 334 43 122 1534

Electronics 270 80 10 44 404

Clothing & Shoes 578 214 36 104 932

Leisure, Sport & Hobby 672 345 31 212 1260

Unspecified 1297 423 90 235 2045

Total 3852 1396 210 717 6175

questions are presented in the results chapter (chapter 4). The questions asked in the survey, and the including logic steps3, are presented inAppendix A, inFigure A.1.

3.6 Analysis

The next step after the interviews is to start with the analysis of the interviews. The qualitative data has to be gathered and correlated (if possible) to the quantitative data. The data overall has to be analysed from several perspectives, but the clear focus of the analysis will be from an environmental perspective. The findings from the first analysis can than be used to lay the foundations for the framework.

During the discussion on the framework, the framework itself will be thoroughly analysed in order to determine the quality and validity. There are several analysis methods available, and all of these will be used to analyse and validate the frame-work.

3.6.1 Life Cycle Analysis

Life Cycle Analysis (LCA) is a tool which is used in order to asses potential envi-ronmental impacts and resource usage in a certain product life cycle or a certain product(ISO,2006a). The life cycle itself can be defined in various ways depending on the definition for the specific case, but an example of the life cycle could be the following steps (ISO,2006a):

1. Raw material acquisition 2. Production

3. Storage 4. Usage

5. Waste management.

An LCA has the potential to be a thesis on its own4 and therefore a full LCA is not within the scope of this thesis. However, the LCA can be used to assist in the analysis of the interviews and can be used to asses the final framework which will be created in the thesis. There are numerous types of LCA, and it all depends on the exact application which type suits the best. The aforementioned example is a clear example of a cradle-to-gate LCA, which includes all the steps of a product life cycle.

3_{Dynamic questions, the survey questions are dependent on previous answers}

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16 Chapter 3. Methodology As the scope of this research does not include an analysis of the whole life cycle of the product, but only the logistical processes in the return space, a cradle-to-gate analysis will not be used. For this research a comparative LCA will best suit the objectives. A comparative LCA can be used to differentiate between two or more different products or services, and items that are identical to each of the products being compared can be excluded from the analysis. In this case, as the products themselves share several life cycle stages, which means that the analysis itself can be focused on the logistical element in the return process. Most of the traditional LCA stages can actually be omitted from the research, as the comparison will be focused on the logistical aspect. LCA will not be conducted, the perspective from an LCA and certain aspects from LCA will be used however.

FIGURE3.3: Basic flowchart

The basic flowchart of the scope of the LCA. The 5 stages of the overall life cycle are represented, and the scope of the LCA for this thesis is represented by the pink dotted box. The red line represents the return flow which will be investigated, and the green line represents

a possible flow which would be present in a circular system.

3.6.2 Multi criteria Analysis

A Multicriteria analysis (MCA) will be used in the final analysis of the proposed framework. The goal of the analysis is to determine which options in the proposed framework will be the most suitable to implement, based on various assessment criteria. An MCA is a useful tool to analyze an the most suitable option from a selected group of options. MCA uses four different concepts in the analysis. These are: (gov.uk,2009; European-Commission,2018).

• Objectives

These indicate the direction, and these are in line with the objectives of the framework (chapter 5).

• Evaluation criterion

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3.7. Framework 17 • Goals

Where the objective can be seen as the direction of the framework, the goal is the target that in that specific direction. In this thesis this aspect is out of scope, as the focus point is to create the framework for the objective.

• Attributes

The attributes are the measures which can indicate weather the aforemen-tioned goals have or have not been met.

The MCA will consist of a performance matrix where 4 different evaluation criteria are assessed, based on 3 different scenarios (weights differ for each scenario, de-pending on which criteria are deemed most important).

The 4 different evaluation criteria are: • Cost

• Ease of implementation • Feasibility

• Effectiveness

The three different scenarios are a result of a combination of two of the four assessment criteria where specific weights have been increased. Each scenario is the expected consequence of the framework, regarding the 4 different evaluation criteria.

• Cost & Feasibility

This scenario focuses on two scenarios which are deemed an important combi-nation. The option whether an option is cost-effective and feasible. This is for a stakeholder which values the the monetary investment and if the solution is feasible.

• Ease of implementation& Effectiveness

This scenario is for stakeholders who value whether an option is easy to im-plement. Easy and feasible are two different evaluation criteria, as an option might be very easy to implement, but it is not very feasible (e.g. never use a sale in order to reduce the effect of impulsive buying).

• Cost & Effectiveness

The final scenario is the "cheap and effective" option, which offers stakeholders the best effect at the best price, but does not value whether the option is feasible or acceptable

3.7 Framework

3.7.1 Perspective

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18 Chapter 3. Methodology to combat this, as it intends to fix environmental issues in a broader range of com-panies operating in the Nordics rather than just trying to fix issues internally in the merchant, the logistical company or the payment provider. The framework tries to solve this problem of so called uncoordinated value chains through collaboration of multiple companies in distinct sectors, through for example looking from a product cycle perspective (Balkau and Sonnemann,2010; Leeuw,2006).

The goal of the framework is to work as and exhibit features of an environmental management system (EMS). An environmental management system is any kind or type of planning and implementation system that a company can use to manage the interactions of the company with the environment. (Cheremisinoff and Bendavid-Val,2001)

On a high level, an EMS has its focus on the general management system and not on the emissions, waste management as these are the focal point of environmental regulations. The framework is intended to work over a larger group of companies to overcome the aforementioned limitations. The most common used environmental management system is the ISO14001-2015 standard, however, this is meant for single companies and has an internal focus. The framework itself will not be able to fully match the scope of the ISO14001 standard, however, the goal is to try and align the framework as much as possible with the ISO standard.

3.7.2 Breakdown

The framework will cover various steps in a planning and implementation process (Figure 3.4; based on (Cheremisinoff and Bendavid-Val,2001; Bendavid-Val,1983)).

FIGURE3.4: Example of a planning and implementation process

The steps included in a planning and implementation process. The thesis will cover steps 1-4, whereas step 5-7 are more relevant for the actual implementation. As implementation is not part of the scope of

the thesis, this will not be covered.

1. Formulation of goals

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3.7. Framework 19 2. Formulation of objectives

The objectives will be based on the interviews with the companies. The pur-pose of the interviews is to gain insight into the e-commerce sector and to find specific pain points in the industry. These pain points will be used as the ob-jectives, as the objectives will be to reduce the impact of these pain points. 3. Identification of options

The options will be (minor) solutions to address specific objectives. Each op-tion will have an expected outcome, certain advantages and disadvantages. In the framework these will shortly be addressed, and a minor explanation regarding these items will be given.

4. Comparative assessment

Not all options will be equally feasible, nor will it be possible to implement them all equally efficient. Therefore, a comparative assessment is needed to determine which options are the best to implement. The comparative assess-ment will be done through the aforeassess-mentioned MCA.

The final three elements are out of scope for the thesis. 5. Implementation and planning

6. Implementation 7. Evaluation

3.7.3 Comparative assessment

Each of the options have certain advantages and disadvantages, and certain options will be more effective than others. The assessment of the framework will be done using an MCA (seesubsection 3.6.2). The framework will deliver numerous options, but that does not mean that each option will be equally viable for merchants or that the overall impact of the option will be beneficial for the merchants. The goal is therefore to analyze and discover which of the proposed options in the framework are the most relevant for specific types of merchants or stakeholders. This is done through scoring, weighting and the summation of these scores.

TABLE3.5: Scoring used in the multi criteria assessment Score Definition

1

It is expected that this option will not be favourable towards the assessment criterion when applied to the objective

3

It is expected that this option will be slightly favourable towards the assessment criterion when applied to the objective

5

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TABLE3.6: Weighting for the scenarios used in the evaluation Evaluation Criteria Cost Ease Feasible Effectiveness

Scenario 1 2x 1x 2x 1x

In the MCA, each of the assessment criteria will receive a score. The scoring is intended as a rough estimate, and it is a crude yet effective method to determine the most favorable options in the framework. The different scores are shown inTable 3.5. These scores are used to give an estimated expectation of the outcome of a certain option. Through discussion and comparison to literature, the estimated scores can be discussed and validated. If a score of 1 is applied, it is expected that the option will not be favorable in regards to the evaluation criteria. For the other definitions, seeTable 3.5. The individual scores are determined through expert consultation, brainstorming sessions and logical thinking and are subject to subjectivity by the researcher and co-workers.

The scoring and weighting is used to determine the final outcome of the option. The scoring depends on the option and the assessment criteria. The weighting de-pends on the scenario. There are three scenarios, each with a different stakeholder focus, and each scenario has different weights for the assessment criteria. As a result of this, the final score (the (weighted) average) will be different, depending on the scenario, and thus it can represent the best options for different types of stakehold-ers, who value certain evaluation criteria more than others. The weights per scenario for the different assessment criteria are are shown inTable 3.6.

FIGURE3.5: Example of the comparative assessment The comparative assessment as done in the thesis

Figure 3.5showcases the framework, and how the scores and weights are used to determine the overall outcome for each of the scenarios. An example:

1. The chosen option has an expected effect X on cost & ease of implementation, -X on feasible, and 3X on effectiveness

2. These effects result in a score of 3 on cost & ease of implementation, 1 on feasi-ble, and 5 on effectiveness

3. For scenario 1: •

Cost=weight∗score=2∗3=6 •

Easeo f implementation=weight∗score=1∗3=3 •

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3.7. Framework 21 •

E f f ectiveness=weight∗score=1∗3=6 •

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23

Chapter 4

Results

The results of this thesis will be characterized into two different elements. The first element is the result of the interviews and the survey. The second element is the cre-ation and analysis of the framework. The analysis of the interviews and the survey is necessary to gain the required insights into the problems of e-commerce regarding returns and their impact.

4.1 Interviews

The interviews led to a few common pain points as identified by the interviewees. Furthermore, the interviews led to some interesting points of discussion, which will be incorporated later on in the thesis. The pain points are varying in size, and im-pact, but all of them had an impact on the day to day operations of the interviewed merchants.

4.1.1 Painpoints

The pain points have been summarized below, with a short description about the pain point to further clarify the pain point.

Large increase in returns during sales period

Mentioned by Merchant 3,12-02-2020

This pain point is connected to an increase in the return rate during sales peri-ods. During sales periods the volume of sales goes up, which on its own is desirable ,however, the volume of returns increases as well, which leads to an increase in re-turn rate during the sales period (Klarna AB,2020). The reason for this additional increase, is that consumers are more susceptible to buy impulsively rather than to buy items which they actually need, or spend enough time thinking about. This effect can be seen in the sales figures of some of the merchants (Figure 4.1). The negatives associated with this are not only the increased return rate, it is also con-nected to the decreased availability of goods as more items are at customers and out of the warehouse, which means that the merchant can’t sell these goods and thus will remain with inventory.

Consumer behavior in fast fashion

Mentioned by Merchant 1, 14-02-2020; Merchant 3, 12-02-2020; Merchant 4, 25-03-2020; Merchant 6,27-03-2020

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24 Chapter 4. Results

FIGURE4.1: Sales vs Returns of M3 over time

Note that the return rate increases during the spring sale in June (Klarna AB,2020)

in fashion. The reason for this importance is not only because they are indirectly responsible for the impact, the consumers also have the possibility to exert influence on the fashion industry. (Barnes and Lea-Greenwood,2006)

Returns due to wrong sizing

One of the reasons why the return rates for e-commerce are higher than brick-and-mortar stores is because it is more difficult for customers to know if a product is right for them. Without physically seeing, feeling or wearing an item it is difficult to make good decision, which leads to higher return rates.

Abuse of return policy

Mentioned by Merchant 1, 14-02-2020; Merchant 4, 25-03-2020; Merchant 9, 17-04-2020

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4.2. Survey 25

High revenue, high return rate customers

Mentioned by Merchant 1, 14-02-2020; Merchant 3, 12-02-2020; Merchant 6, 27-03-2020

There are certain customers who do have high order values, yet, also high return rates. These are customers which still are profitable, but they have high operational costs, which means that it is important for merchants to be able to increase the mar-gins on these customers, by decreasing their costs.

Environmental impact related to shipping

Mentioned by Logistical Company 2,02-03-2020; Logistical Company 1,28-02-2020; 3PL,20-02-2020

Focus on the greenhouse gas (GHG) emissions related to shipping and the usage additional packaging material in the business to consumer (B2C) shipping industry.

Expensive return shipping from other countries

Return shipments by customers from abroad are expensive and inefficient, both for the brand as for the returning customer as international shipments are expensive per individual unit.

Unaccepted returns

Mentioned by Merchant 3,12-02-2020; Merchant 9,17-04-2020; 3PL,20-02-2020

Items being thrown out due to wear and damage, which happens due to poor care by the customer, or during shipping. Another element of this pain point is related to items being shipped using the wrong shipment label or packaging, which generates extra work for the merchants.

Return processing between consumer and merchants

Mentioned by Merchant 9,17-04-2020; Logistical Company 2,02-03-2020

There are several interfaces at which consumers interact with a merchant, and this is an important step in the return process as it is important for both the customer and merchant that this is an efficient process with as little friction as possible.

These pain points will be the core structure of the proposed framework, as nu-merous merchants mentioned these pain points.

4.2 Survey

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4.2.1 Respondents

Although the survey was anonymous, it is important to know the demographic of respondents and the general characteristics of the data set. Figure 4.2, Figure 4.3

andFigure 4.4visualize the general overview of the respondents. The figures show the distribution per country, per sales category and revenue respectively. From Fig-ure 4.2, Figure 4.3 and Figure 4.4 it is clear that the majority of the respondents is from Sweden, that the largest sales group is Clothing & Shoes and the smallest group is Electronics, and finally that the majority of the companies falls in the 1 to 10 million SEK annual revenue range. Sweden being the biggest respondent group is not surprising given the companies included in the survey (seeTable 3.4). What is surprising, is that most of the companies that responded identified themselves as Clothing & Shoes, whereas that was not the largest merchant category in the survey (Table 3.4).

FIGURE4.2: Survey result, question 1

The distribution of respondent is as expected, based on the original selection of merchants (Table 3.4)

4.2.2 Singular results

The first three questions on the survey were questions used to identify the respon-dents, whereas the other questions where the relevant questions to discover the at-titude of merchants regarding the returns in e-commerce. The most important in-sights from the single questions (without correlation to other questions) are shortly presented below.

4.2.3 Cross results

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4.2. Survey 27

The largest category in the respondents is the Clothing & Shoes cat-egory. This is surprising as this wasn’t the biggest category in the original selection (Table 3.4). The "other" group is significantly large, as there was a large number of merchants with an unknown category which results in a significant other group, and this can be attributed

to the data in the Klarna system

Most of the respondents are SMEs, with an average revenue between 1 MSEK and 10 MSEK

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(a) Combined survey results, Q1 & Q14

"In which country are you based?"×"Is reducing the return costs a priority for your organization?"

(b) Combined survey results, Q1 & Q15

"In which country are you based?"×"Is reducing the environmental impact of returns a priority for your organization?"

FIGURE4.5: Survey result

could show where certain collaborations between merchants could, or could not work.

Not all the merchants in the Nordics seem to be equally environmentally aware as can be seen in4.5(b). There is a clear distinction in between the several countries regarding the statement whether reducing the environmental impact of returns is a priority for their organization. Swedish merchants seem to be the most environmen-tally aware from the merchants in the Nordics.

"With which sales category do you identify your-self most with?"×"Have you tried to reduce the return rates in the last year?"

"With which sales category do you identify your-self most with?"×"Is reducing return costs a prior-ity for your organization?"

From4.6(a)it can be seen that merchants in the categories Electronics and Cloth-ing & Shoes have tried to reduce returns relatively the most. This makes sense, especially when looking at4.6(b), which shows that relatively seen the merchants in the category Clothing & Shoes and Electronics have the highest urge to reduce the cost of returns.

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4.2. Survey 29

"What is your yearly revenue?"×"Is reducing re-turn costs a priority for your organization?"

"Have you tried to reduce the return rates in the last year?"×"Is reducing costs a priority for your organization?"

(1MSEK-10 MSEK, and >10 MSEK) show a higher fraction that have reducing costs as a priority.

Merchant who have reducing costs as a priority seem to have actively taken ac-tion. A large group of merchants in this category that has reducing the cost as a priority, has actively taken action in order to try and reduce the return rate, as visi-ble in4.7(b)

"Is reducing return costs a priority for your organi-zation"×"Have you tried to reduce the return rates in the last year?"

"Is reducing return costs a priority for your organi-zation"×"Is reducing the environmental impact of returns a priority for your organization?"

4.8(a)presents the same data as4.7(b), but from a different perspective. It again shows how there is a correlation between the desire to reduce returns, and merchants actually reducing returns (in order to reduce costs)

4.8(b)shows that a large portion of merchants who

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"Is reducing the environmental impact of returns a priority for your organization?"×"Have you tried to reduce the return rates in the last year?"

"Is reducing return costs a priority for your organi-zation?"×"Do you believe your organization has the capability to improve the issue related to on-line?"

"Has it been successful?"×"What action did you take to reduce the return rate?"

(b) Survey result, Q11

"Have you tried to reduce the return rate in the last year?"

Actions taken by merchants and the effects of these actions are visualized in

4.10(a). It shows that blocking customers has been the least effective option, and the "other" class is the most effective. Unfortunately, this data has not been stored properly. A score of 50 means that there is no impact whatsoever, a score lower than 50 meant an increase in return rate, and a score higher than 50 means that there is a decrease in return rate. Not all merchants have taken actions however, as can be seen in4.10(b). The majority has not taken any actions to reduce the return rate.

4.11(a)and4.11(b)show once again the similarity in the results between ques-tion 14 and quesques-tion 15, which suggests that not all merchants have answered this question in the way the question was intended.

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4.3. Summary 31

(a) Survey result, Q14

"Is reducing return costs a priority for your organi-zation?"

(b) Survey result, Q15

"Is reducing the environmental impact or returns a priority for your organization?"

(a) Distribution of measures taken by merchants (b) Combined survey result, Q15 & Q17

"Is reducing the environmental impact or returns a priority for your organization?"×"Do you offer climate compensated shipping and returns?"

include product information on the product website. Other popular options are the adding or increasing of both shipping and return fees.

The final figure (4.12(b)) shows the contradiction between merchants who have reducing of the environmental impact as a priority and the ones who actually offer carbon compensated shipping as an option to their customers.

4.3 Summary

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33

Chapter 5

Framework

Using the information of the interviews and the surveys, the proposed framework can be conceptualized and developed.

5.1 Structure

The steps required in a planning and development are mentioned in section chap-ter 5. The framework requires the first four to be completed, these steps were:

1. Formulation of goals 2. Formulation of objectives 3. Identification of options 4. Comparative assessment

The objectives are the pain points as found by the interviews, and are the first step in the creation of the framework. Each of the pain points have an impact in a different element of the return problem space. The pain points from the interviews show that there are several areas1other than the physical returning process in which there are certain issues and causes which lead to returns, and these have to be in-cluded in the framework. Therefore,the proposed framework defines the problem space into four separate elements. Only the final element of the framework is di-rectly related to returns.

• Pre-purchase

Pre-purchase is the phase in which consumers are targeted, and where con-sumers actively look for items to purchase. This is a very large, and difficult to specify zone, as it contains many different interactions.

• Purchase

The purchase phase is the phase in which customers are in the process of buy-ing goods. In the framework this does not mean customers on the website of a merchant, but very specifically the act of consumers being in the on-line checkout and completing a purchase, and thus being converted. The last step in the so-called conversion funnel. The conversion funnel is the process which consumers go through from entering an online merchant to finalizing. (Fatta, Patton, and Viglia,2018)

1_{The obvious thought one might have when thinking of returns in e-commerce is thinking directly}

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34 Chapter 5. Framework • Shipping

Shipping describes the physical process of shipping the consumer goods from the merchant to the customer. The previous two phases are relatively abstract compared to the shipping phase.

• Returning

The last phase in the framework is the physical act of returning the items from the customer back to the merchant.

5.2 Formulation of options

After the assessment of the objectives (seesection 5.1), the actions had to be deter-mined. The actions and their have been determined through help of expert advice (both during the interviews and afterwards during brain-storm sessions), existing industry approaches and analytical thinking. The options will be analyzed compar-atively to determine the most suitable approaches and tested to existing literature.

5.3 Segmentation

During the interviews with merchants from various merchant categories it became clear that there was a division between the merchants (Merchant 1,14-02-2020; Mer-chant 3, 12-02-2020; Merchant 4, 25-03-2020; Merchant 5, 26-03-2020; Merchant 9,

17-04-2020). Based on this division, the decision was made to divide all the mer-chants into two specific segments rather than to keep them in their own respective merchant category to simplify the framework, as it would make more sense to have actions based on the defining issues, rather than the merchant category. The first segment is the segment for which returns pose the biggest issue (M1, M2, M3, M4 & M6). These merchants have high return rates, and their biggest issue is related to the quantity of returns. The second segment is the segment in which the returns are less of an issue (M5, M7, M8 & M9)2. Even though there is a loss in revenue, it is more acceptable in the overall sense to these companies and even poses a fun challenge from now and than. During the interviews with the merchants from segment 2 the pain points were practical of nature, e.g. the interaction with Klarna systems or the fact that a couch does not physically fit in a mailbox.

5.4 Pre-purchase

Two specific objectives have been identified for the first phase of the framework (Figure 5.1). In the pre-purchase phase the target is to influence customers before they reach the merchant website. The idea behind this is to prevent consumers from purchasing goods. Although this might sound counterproductive for any business, the goal of the framework is to reduce returns. By preventing the purchase of certain goods, the return of these goods is subsequently prevented as well. The idea behind this part of the framework is to prevent unnecessary items being bought.

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5.4. Pre-purchase 35

FIGURE5.1: Phase 1 of the framework

A summary of the pain points, actions and the effects of the actions of the first phase of the framework

5.4.1 Large increase during sales period

The first objective is to reduce unnecessary sales during a sales period. Two differ-ent options have been iddiffer-entified which could assist in achieving this objective. The options presented in the framework are:

Take preliminary actions against suspicious orders

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36 Chapter 5. Framework suspected to be returned3_{, after being placed on the merchant website, the merchant}

can reach out to confirm the order with a customer. The thought is that this added friction with the merchant, will reduce the overall conversion rate. (Fatta, Patton, and Viglia,2018). By reducing the number of customers that will be converted, the overall return rate would decrease, as the customers which are not converted would most likely have returned the item in the first place. The option itself is easy to implement, and is expected to lead to a decrease in the return rate, however, it will decrease the brand experience for these customers. This can on it’s own lead to an decreased brand perception. However, as this option is identified to work for smaller merchants, potential backlash is not as big as e.g. the backlash that happened when a certain merchant blocked customers on their website (Bielecka,2019).

Reduce advertising for items high a high return risk

Several merchants indicated an increase in the return rate during sales periods. This on its own is not surprising, as the decrease in price is a big factor in consumers who purchase goods. (Alvarez and Casielles,2005) However, as consumers buy goods as a result from a sale, consumers tend to return more items. A good example of this re-turn behavior can be seen during the annual Black Friday/Cyber Monday weekend. (Khusainova, 2018) However, it is possible that certain items tend to have higher return rate increase than average during sales periods. If merchants have insights on which specific items these are, it is possible for merchants to reduce the market-ing on these items, or increase the friction on the purchase process for these items in order to decrease the sales for these items. It is expected that the return rate on these specific items will decrease, however, it does not affect the overall increase in return rate, which is bound to happen during a sales period. In order to implement this, it is required for merchants to have this data availability. The feasibility heavily depends on the loss of revenue, compared to the decreased in return costs, but that will vary greatly merchant by merchant.

5.4.2 Consumer behavior in fast fashion

One reoccurring element in the interviews was the behavior of customers, and is therefore included in the framework. The objective in this part of the framework is to influence customers in general, and to discuss what possibilities there might be to influence the market which currently exists. The question whether this might be feasible is something which will be discussed in the discussion, however, chang-ing consumer behavior will definitely have an impact on the market and the way consumers return goods. The options in this category have been identified as:

Educate consumers

Not all consumers are aware of the impacts of their behavior (Merchant 1, 14-02-2020; Merchant 3, 12-02-2020; Merchant 4, 25-03-2020; Merchant 6,27-03-2020). By education of consumers it is thought that the impact of the consumer behavior on the industry will decrease. As not all consumers are aware of their return behavior, the industry has the potential to educate consumers on the impact of their behaviour. When done correctly, it is possible to positively influence consumers through in-centives and information (Stern,1999). Other examples of consumer education and

3_{An order by a certain customer, a certain quantity of items etc, merchants can decide their own}

Sustainability in returns

Sustainability in returns

Analysis into the e-commerce market and

proposal of a framework to improve

environmental performance

LUCAS VELDKAMP

Abstract

Sammanfattning

Acknowledgment

Contents

List of Figures

List of Tables

Acronyms

Glossary

Chapter 1

Introduction

1.1

Growth of e-commerce

1.2

Introduction of returns

1.3

Environmental Awareness

1.4

Klarna

Chapter 2

Aim and Objectives

2.1

Aim

2.2

Objectives

2.3

Perspective

2.4

Limitations

2.5

Exclusions

Chapter 3

Methodology

3.1

Data

3.2

Selection criteria

3.3

Final selection

3.4

Interviews

3.5

Survey

3.6

Analysis

3.7

Framework

Chapter 4

Results

4.1

Interviews

4.2

Survey

4.3

Summary

Chapter 5

Framework

5.1

Structure

5.2

Formulation of options

5.3

Segmentation

5.4

Pre-purchase