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A STUDY OF RETURN POLICY

LENIENCY IN ONLINE CLOTHING

RETAIL IN UK

IBRAHIM HAMDHAN MOHAMED

17150910

A Major Project Thesis

Submitted in Partial Fulfilment of the Requirements for the MSc

Management Programme

Birmingham City University

Faculty of Business, Law and Social Sciences

MSc Management and International Business

Module: Major Project BUS7048

Supervisor: Stephen Raybould

Submitted on 11th January 2019

Word count: 8,177

Abstract

Return policies come in different forms and can be differentiated between

lenient and non-lenient return policies. Consumers benefit from lenient return

policies as it decreases the consumer risk. From a retailer’s perspective, lenient

return policies are more likely to contribute to increase in sales, however, is an

expensive process as it results in the increase in returned items.

In order to understand return policy leniency in online clothing categories in UK,

it is essential to differentiate between lenient and non-lenient return policies,

and identify the main factors that contribute to leniency. A triangulation analysis

that includes prior academic journals, online clothing retailers, and data on

consumer satisfaction levels reveal that consumer protection laws in UK drive

return policy leniency in terms of scope, exchange, money and time. The

leniency requirements for online retailers are higher due to the consumers’

inability to conduct pre-purchase physical inspections on the product. As a

result, online clothing retailers vary return policy leniency based on the number

of return collection options offered to consumers, monetary restrictions

imposed on those return collection options, and by changing the time allowed

to return sale items.

The main factors that online clothing retailers should consider are increasing

time given to consumers to return items, imposing less monetary restrictions on

return collection options, and increasing the number of return collection options

offered which leads to an increase in effort leniency. Furthermore, the increase

in return collection options offsets the competitive edge that multi-channel

retailers have over purely online-based retailers. However online retailers must

increase the quality and convenience of the return collection options offered to

consumers. Finally, imposing minor monetary restrictions on alternative return

options in order to utilise in-store returns may benefit multi-channel retailers in

encouraging customers to use in-store returns which can lead to an increase in

efficiency in terms of re-selling returned items and may provide cross-selling

opportunities to returning customers. The findings provide an understanding of

leniency factors that online clothing retailers vary in the UK and how it impacts

consumer satisfaction.

Table of Contents

Page

1.0 Introduction -----------------------------------------------------------------------1 - 3

2.0 Literature Review --------------------------------------------------------------- 4 - 10

2.1 The purpose of return policies

2.2 The impact of return policy leniency on consumer behaviour

2.3 The impact of return policy leniency on retailers

2.4 Use of theoretical frameworks

2.5 Factors that contribute to leniency

2.6 Framework to measure return policy leniency

3.0 Methodology----------------------------------------------------------------------11 - 16

3.1 Research Philosophy and Methods

3.2 Use of Academic Journals

3.3 Analysis of Four Online Clothing Retailers

3.4 Leniency Dimensions

3.5 Measuring Leniency

3.6 Identifying Main Leniency Factors

3.7 Mintel Report

3.8 Tools Used for Analysis and Limitations

4.0 Results---------------------------------------------------------------------------- 17 - 21

4.1 Results of the Four Retailers’ Return Policies

4.2 Main Leniency Factors and Weightings

4.3 Ranking of Four Retailers

4.4 Comparison of Rankings Against Mintel Report

5.0 Discussion----------------------------------------------------------------------- 22 - 24

6.0 Conclusion----------------------------------------------------------------------- 25 - 27

7.0 Reflective Account------------------------------------------------------------- 28 - 30

8.0 References-----------------------------------------------------------------------31 - 35

9.0 Appendix--------------------------------------------------------------------------36 - 54

Page 1 of 54

1.0 Introduction

Returns policies are a post-customer service in retail (Chen and Chen, 2015).

The concept of allowing returns has been around since the late 1800’s when

Montgomery Ward first implemented the commitment of giving money back to

unsatisfied customers (Brennan, 1991). In the modern business setting, almost

every retailer offers some form of return provision to customers as a result of

consumer protection laws and competition between retailers. Research shows

that there is a trend towards more liberalised return policies especially in

industries such as fashion e-commerce (Hjort and Lantz, 2016). One of the

main factors for the use of return policies and its shift towards leniency is due

to the laws that require retailers to accept returns. Hence, returns policies can

vary considerably depending on the country and the governing legislative body

(Hjort and Lantz, 2016). In addition to legal/contractual obligations, as Yarrow

(2012) highlights return policies are used as a competitive strategy.

Retailers use returns policies as an instrument to lower consumer risk and

increase consumer demand (Janakiraman et al., 2015). Even though it may

increase consumer demand, research indicates that due to the high expenses

that retailers incur in the process of returned items, it may significantly reduce

profitability (Janakiraman et al., 2015). Furthermore, Gecker and Vigoroso

(2006) highlight the process of returning items as the most challenging aspect

of reverse logistics. From a consumer’s perspective, leniency in returns policy

is essential as it is one of the factors that influences the consumer’s decision to

purchase the product (Chen and Chen, 2015).

The importance of return policies is especially felt in online clothing retail, as

consumers have to sacrifice the benefit of physical inspection of the product

(BBC, 2018). Mostard and Teunter (2006) revealed that return rates for fashion

items could be as high as 75% of the demand. Mintel (2018) UK clothing retail

market report considers returns policy as one of the dimensions of measuring

satisfaction with retailer in their consumer survey. Furthermore, a survey

conducted by KPMG (2018) in UK shows that 31.4% of customers from both

genders who purchased fashion apparel online intended to return one or more

of the same item, and 62% of shoppers in general identify free returns as the

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most important factor when returning orders. Hence it shows the significance

of return policies in online clothing retail in the UK. This study aims to

understand the factors that contribute towards returns policy leniency and

provide a guideline on return policy best practices in the UK.

Previous academics have examined the different forms of returns policies in

order to identify the factors that contribute to leniency. Even though the existing

literature identify several leniency factors, those factors have not been tested

in any of the industry specific categories. Based on the findings of previous

research, this paper seeks to answer the following questions:

(1) What differentiates a lenient and non-lenient return policy?

(2) What are the major factors that contribute to return policy leniency?

(3) Which online clothing retailers in the UK offer the most lenient return

policies?

(4) Do the retailers with more lenient return policies increase customer

satisfaction?

This study identifies leniency factors from previous literature and test those

factors against the online clothing retail category in the UK. The objectives are

to understand what factors contribute towards a lenient returns policy, to

analyse returns policies of a sample of online clothing retailers in the UK based

on a framework adopted from prior academics, to compare and rank the

selected retailers’ returns policy based on their leniency, and to compare the

returns policy ratings result against customer satisfaction levels of those

retailers in the UK.

As the research focuses on the implications of returns policies from a consumer

perspective, the results presented in this paper can assist managers in

identifying different factors that are associated with returns policy leniency and

determine returns policies that suit best in the online retail clothing category.

Furthermore, as the study provides information on the returns policy

frameworks adopted in the UK by brands from multinational companies, it

provides a perspective of how return policies differ nationally based on

consumer protection laws and the state of the market.

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The paper is structured as follows: Section 2 contains the literature review,

which provides a broader analysis on how certain returns policy factors have

been determined, and how returns policies impact consumer behaviour and

demand. Section 3 describes the methodology that the study employs, followed

by the methods section which explains the type of research that was conducted

and the logic behind the chosen retailer sample used for analysis. Sections 4

and 5, presents the findings of the research, empirically validates and discusses

the results. The final section concludes the paper by answering the research

questions, and provides limitations and routes for future research.

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2.0 Literature review

2.1 The purpose of return policies

Chen and Chen (2015) refers to Yarrow (2012) who states that retailers use

return policies as one of their competitive marketing strategies. Contrary to a

product warranty which focuses on reducing the product quality uncertainty as

a form of guarantee that the product will be replaced or the money will be

refunded to the consumer, return policies allow consumers to return an item

even though the product fulfils its functions flawlessly, and instead offers a more

extensive protection against mismatches between consumer needs and

product benefits (d’Astous and Gue`vremont, 2008). In the UK, retailers are

required to have a returns policy under the consumer protection law

(Government of UK, 2018). However, the law provides the basic requirements

that retailers must meet in shaping their return policies. Based on this, some

retailers offer return policies that are more lenient than others.

2.2 The impact of lenient return policies on consumer behaviour

Wood (2001) states offering lenient return policies can be a way of minimising

risk that is passed on to the consumer during purchase. This is supported by

Peterson and Kumar (2010) who argue that when customers have knowledge

that they can return a product, it reduces customer’s perception of risk which

results in customer satisfaction. Pei et al. (2014) also show that a return policy

that offers more leniency has a positive influence on the consumer’s perceived

fairness of the return policy and purchase intention. However, Javadi et al.

(2012) report that among the factors they tested to analyse attitude towards

online shopping behaviour (product risk, convenience risk, financial risk, non-

delivery risk, and return policy and service and infrastructural variables), return

policy does not have a significant influence on attitude towards online shopping.

Overall, these studies indicate that although the impact may be minor, lenient

return policies minimise customer risk, hence results in customer satisfaction.

Furthermore, the importance of return policies depends on the stage of the e-

commerce market in context. In an underdeveloped e-commerce market,

consumers may value basic factors such as convenience risk, financial risk,

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and non-delivery risk as more important. However, in a developed market,

return policy leniency can be a more influential factor.

2.3 The impact return policy leniency on retailers

Even though consumers benefit from the increase in return policy leniency, the

volume of products returned by customers increase, which results in logistical

costs for retailers (Wood, 2001). As a result, retailers are faced with a trade-off

between adjusting their return policies to minimise product returns and avoiding

the loss of potential sales as a result of stricter return policy. Some retailers use

stricter return policies in order to reduce returns by increasing the cost of

returning items and/or by reducing the time given to the consumer to return a

product (Janakiraman and Ordóñez, 2012). Lantz and Hjort (2013) show in their

analysis that even though lenient return policies increase order frequency, due

to the high probability of returns it reduces the profitability of online retailers. In

contrast to these studies, Peterson and Kumar (2010) find that with a more

lenient return policy, number of returns inevitably increase, however the

increase in returns is offset by the increase in customer purchase and referral

behaviour which results in higher profits and a rapidly-growing customer base

for the retailer. Conversely Hjort and Lantz (2016) state that policies that allow

free returns do not benefit retailers in terms of profits in the long-term. Griffis et

al. (2012) propose that improving the operational returns management process

of an online retailer can significantly and positively influence consumers’

repurchase behaviour. Some of the research are done in the U.S whereas

others are done in Europe. Furthermore, the analysed retailer in various studies

differs in terms of retail category and format as for instance, some of the

research is focused on online retail while the others are focused on brick-and-

mortar stores. As a result, even though previous research determines that the

increase in return policy leniency increases consumer demand, it is

inconclusive whether this results in higher profits for the retailer in the long-

term.

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2.4 The use of theoretical frameworks in explaining the impacts of lenient return

policies on customers and retailers

Previous research has also used several theoretical frameworks to explain the

impact of return policies on consumers and retailers. Wood (2001) uses

signalling theory to explain that return policies act as positive quality signals by

the retailer. In addition, Janakiraman and Ordóñez (2012) uses the construal

level theory to explain that when individuals face lenient return policies, they

are likely to focus on the benefits of purchase rather than the costs of purchase.

Furthermore, previous literature that have used the endowment effect show that

return policies that allow longer deadlines to return increases perceived product

endowment more than shorter return deadlines which suggest that return policy

leniency would increase perceived product endowment (Janakiraman et al.,

2016; Janakiraman and Ordóñez, 2012; Wang 2009; Wood 2001). Therefore,

the theories used by previous academics indicate a positive relationship

between return policy leniency, the customer and retailer.

2.5 Proposed changes in return polcies

In order to improve retailers’ return policies, Janakiraman et al. (2016) state that

return policies should be differentiated based on product type or category rather

than having the same return policy for all items in the store. In addition, Lantz

and Hjort (2016) report that managers should avoid using blanket return policies

and instead customise the return policies based on customer segments. Bahn

and Boyd (2014) argue that return policies can be made restrictive and reduce

the consumer’s negative perception at the same time if the retailer can provide

sufficient information for the consumer to ensure more certainty in their

purchase. However, this research is limited to product assortments only and

does not provide evidence of its effectiveness on other product categories.

Overall these studies indicate that variations in returns policies are essential

based on product category, type and customer segments.

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2.6 Factors that contribute to leniency

The leniency of the return policy is recognised by the different terms and

conditions linked to the policy (Chen and Chen, 2015). Several authors have

done research on return policy leniency and its impact on consumer purchase.

However, there are differences in how leniency is measured in those studies.

Some experiments varied the amount of monetary refund such as the research

by Wood (2001) in which the results showed that with more monetary leniency

such as offering full cash refund on product returns increased the order

frequency. In another study, the scope of returnable products was varied to

differentiate a strict and lenient return policy which resulted in more purchases

(Peterson and Kumar, 2010). This indicates that both monetary and scope

leniency impacts customer purchase behaviour. Additional factors were also

explored in recent studies which included testing two factors together such as

the time allowed, and effort required to return products (Janakiraman and

Ordóñez, 2012). The research identified that the combination of less return

effort (customers not having to fill out return forms) and shorter deadlines lead

to higher return rates (Janakiraman and Ordóñez, 2012). As this study is

focused on identifying return leniency factors, it suggests that both time and the

level of effort required by the return policy influences leniency. Janakiraman

and Ordóñez (2012) referred to time as the deadline given to the consumer by

the retailer to return the product. Time can be extended further to include the

time taken by the retailer to process the return and refund or exchange the

product. Although it is logical to assume that quicker return processing times

can increase customer satisfaction, previous literature have not included this

aspect as a factor that contributes to return policy leniency (Janakiraman and

Ordóñez, 2012; Wood, 2001; Peterson and Kumar, 2010). However, effort may

not be limited to simply filling out a return form as De Leeuw et al (2016) refers

to Mukhopadhyay and Setaputra (2004) who highlight that customers who are

able to return online purchases to physical stores are more satisfied than

customers who are unable to do so. This is supported by Sen (2008) and Tarn

et al. (2003) who state that multi-channel retailers (retailers that operate both

physical and online stores) benefit by offering consumers the option to return

items to one of their physical stores. Hence a multi-channel clothing retailer that

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utilises both brick-and-mortar stores and its online store for returns can have

an advantage over retailers that operate only online in establishing return

policies as such retailers would be limited to third party collection drop off points

such as Hermes and DHL. An additional factor called ‘exchange’ was included

in previous research by Davis et al. (1998) and Heiman et al. (2001) to define

the mode of exchange as a return policy that allows a full cash refund or an

exchange of the product in which a full cash refund is considered the most

lenient form of exchange. This factor is supported by a recent study conducted

by Janakiraman et al. (2016) that considers exchange as either offering full-

cash refund, store credit or an exchange of the product.

2.7 Framework to measure return policy leniency

It is essential to have a framework that includes sufficient factors in order to

classify return policies as lenient or non-lenient. Previous researchers have

attempted to create a framework, such as Davis et al. (1998) who included five

factors which are the acceptance of exchanges or cash refunds by the store,

the requirement of having a receipt or not, the condition of having the original

packaging when returning, whether there are visible signs of use or not and the

time frame given to return products. Another framework created by Heiman et

al. (2001) included four factors which are, the time frame given to return,

whether the customer has to pay for the return cost fully, or partially, the

provision of monetary refund or product exchange by the retailer, and the

requirement of having the original packaging when returning. Janakiraman et

al. (2016) combines these factors to include five dimensions that determine a

return policy leniency which are, time leniency, monetary leniency, effort

leniency, scope leniency and exchange leniency. As this framework combines

previous literature’s factors, it is more comprehensive. Therefore, based on

these 5 dimensions, the research will question how return policy leniency can

be measured and compare return policies in clothing retailers in UK based on

their leniency. In addition, the scope of this research is on online clothing retail.

However, this does not exclude multi-channel retailers (Retailers that operate

physical stores and online stores). Furthermore, the research will test to see if

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the market share of the selected retailers for this study increase with the

increase in return policy leniency.

Therefore, the above literature helps to understand what a return policy is, and

what shapes a return policy. Based on various theories and empirical results, it

is evident that the increase in return policy leniency increases consumer

demand for the retailer. However, researchers’ opinions differ on whether the

increase in consumer demand results in an increase in profits for retailers. One

of the major limitations of prior research on this area is that each study was

focused on one or two return policy leniency factors in order to determine its

impact on consumer behaviour and retailer. Furthermore, the studies differ

based on analysed country, retail category and retail channel. However, the

above literature has provided a proper understanding of the factors that

contribute towards a lenient return policy. The leniency dimensions proposed

by Janakiraman et al. (2016) which was based on a meta-analytical review of

all previous literature relating to the subject takes into context the limitations of

previous literature and proposes a five-dimensional framework that can be

applied to any retail category or format in order to analyse the leniency of return

policies.

Based on the five-dimensional framework, this research will analyse return

policies of a group of online clothing retailers in the UK and compare and rank

them based on their leniency. Finally, the ranking of those return policies will

be compared to the customer satisfaction levels towards those retailers’ return

policies in order to determine whether the ranking of return policies based on

the dimensional framework accurately reflect on the customer satisfaction

levels. Previous researchers argue that multi-channel retailers (Retailer that

operate both brick-and-mortar stores and online stores) have an advantage

over retailers that operate solely online, as multi-channel retailers offer

consumers the option to return items to one of their brick-and-mortar stores (De

Leeuw et al., 2016; Sen, 2008; Tarn et al., 2003). Furthermore, Mukhopadhyay

and Setoputro (2004) state that consumers will be more satisfied when they are

offered the option to return online purchases to a physical store. Hence, while

assessing the online retailers in UK, this study will consider the advantage of

having a physical store as highlighted by previous academics. In summary, the

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objectives of this research are to understand the factors that contribute to return

policy leniency, rank the leniency factors in terms of influence, analyse and rank

return policies of a sample of online clothing retailers in UK based on a

dimensional framework, and compare the results of the policy rankings against

previous academics and market survey data.

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3.0 Methodology

The objectives of this study are to understand the factors that contribute to

return policy leniency, determine the main leniency factors, analyse and rank

return policies of a sample of online clothing retailers in UK based on a

dimensional framework, and compare the results of the policy rankings against

previous academics and market survey data. An exploratory research design is

used to understand the best practices in returns policies used in online clothing

retail in UK. The research will focus on answering the following research

questions:

(5) What differentiates a lenient and non-lenient return policy?

(6) What are the most important factors that contribute to return policy

leniency?

(7) Which online clothing retailers in the UK offer the most lenient return

policies?

(8) Do the retailers with more lenient return policies increase customer

satisfaction?

3.1 Research Philosophy and methods

A pragmatist philosophy was used in this research as the study is an

exploratory analysis from three different points of view which are, research

conducted on the subject by previous academics, research carried out in this

paper, and UK customer surveys and reports. This is under the belief that

multiple opinions provide a more comprehensive understanding of the subject

and can yield better results. Hence, an inductive approach was used for theory

development, which suited the framework of this research. Data collection

enabled to identify themes, patterns and create a framework for analysing data.

As a result, this paper consists mainly of quantitative methods.

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3.2 Use of Academic Journals

Multiple sources were used while collecting data such as journal articles to

identify and develop theories, and retailer websites to collect information on

their return policies. In addition, UK customer surveys and reports were taken

from Mintel (2018) to determine consumer satisfaction levels for the group of

retailers assessed in this research. In order to build a list of academic journals

related to the subject, online searches were conducted through the university’s

online library database and other electronic databases which include

EBSCOhost, ABI/INFORM Global and ABI Trade & Industry, Emerald, Google

Scholar and Science Direct. The references in the academic journals provided

access to additional journals and scholarly articles relevant to the subject.

Keyword searches such as “Return policies”, “Return policy leniency”, “Return

policies and consumer behaviour”, “Return policies in e-commerce”, “Return

policies on clothing retail” and “Customer behaviour in e-commerce” were used.

3.3 Analysis of four online clothing retailers

Four retailers that operate in the UK were selected to analyse their return

policies. These retailers are similar in type and are categorised as high street

fashion retailers. Furthermore, all four retailers operate online stores, and three

of the four retailers are multi-channel retailers (Retailers that operate online

stores as well as brick-and-mortar stores). The inclusion of ASOS, an

exclusively online-based retailer provided an opportunity to analyse the benefits

that multi-channel retailers have over exclusive online retailers as highlighted

by previous researchers (De Leeuw et al., 2016; Sen, 2008; Mukhopadhyay

and Setaputra, 2004; Tarn et al, 2003).

# Retailer Retail Format

1 H&M Multi-channel

2 NEXT Multi-channel

3 New Look Multi-channel

4 ASOS Online only

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As the law for online and distant selling in the UK requires retailers to disclose

the length of their contract, and the terms and conditions, online retailers

provide necessary details of their return policies on their official websites

(Government of UK, 2018). Hence, details of their return policies were

accessible online through specific links in their website that directed to their

return policies.

3.4 Leniency Dimensions

Based on previous literature, a dimensional framework was identified in order

to measure return policy leniency of the selected sample of online clothing

retailers in UK. The dimensions were deduced by Janakiraman et al., (2016)

referring to previous studies, which are:

1. Time Leniency: Policies that offer a longer time frame to return products

are considered more lenient.

2. Monetary Leniency: Policies that do not impose monetary restrictions on

the customer such as “Return shipping fee” are considered more lenient.

3. Effort Leniency: Policies that require less effort on the part of the

customer are considered more lenient.

4. Scope Leniency: Policies with a greater scope of returnable items are

considered more lenient.

5. Exchange Leniency: Policies that allow the option of a cash refund

instead of only product exchange or store credit are considered more

lenient.

In order to maintain a structure for the purpose of observing, comparing and

measuring the different return policies of the sample retailers, and to adjust the

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return policy requirements that suited to the UK, some of the above dimensions

were further defined as follows:

● Time Leniency includes: The time frame given by the retailer to return

items.

● Monetary Leniency includes: Return fees charged by the retailer.

● Effort Leniency includes: Whether the retailer provides a pre-printed

return label with the initial delivery of the item, and the number of return

options provided by the retailer.

● Scope Leniency includes: Whether the returnable items include sale

items or not.

● Exchange Leniency: Whether the retailer offers a full cash refund.

3.5 Measuring Leniency

The following method for measuring the leniency was adopted for the purpose

of measuring the sample retailers selected for this research only and may have

its own limitations. Furthermore, the leniency criterion given to each dimension

was determined after analysing the retailers’ returns policies and the law on

return policies in the UK. There is no maximum score achievable as the purpose

of the score is to determine leniency of each policy and to rank the policies. A

point-based system for each dimension was used to calculate the overall score

for each return policy as follows:

1. Time

• If the return window for both regular and sale items is the same, and is

equal to 28 days and above = 10 points

• If the return window for regular items is 28 days, and the return window

for sale items is <28 days = 5 points

2. Money

• If no return fees are charged for all available return options = 10 points.

• If there is/are return fees charged for some options = 5 points.

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3. Effort

• If retailer provides in-store return option = 2 points.

• Each return option of the retailer (except in-store return option) = 1 point.

• If the retailer provides a pre-printed shipping label = 2 points.

4. Scope

• If sale items are included = 10 points.

• If sale items are excluded = 5 points.

5. Exchange

• If exchange includes full-cash refund = 10 points

• If exchange includes a partial refund or product exchange = 5 points

3.6 Identifying main leniency factors

In addition to obtaining a dimensional framework, thirty academic journals were

used to determine the weight of each dimension, based on the number of

studies done on each one of them. This was carried out in Microsoft Excel,

where all the authors’ names, journal titles, published year and the analysed

dimensions were listed. The “COUNTIF” formula in Excel was used to

determine the number of academic journals that used the dimension for their

analyses. Excel’s “RANK.EQ” formula was used to compute the ranking of

those dimensions based on frequency of use. Finally, the weight of each

dimension was determined by dividing the number of studies done on each

dimension used over the sum of all the dimensions that were used in the thirty

academic journals.

3.7 Mintel Report

Mintel’s (2018) clothing retailing report which was released in October 2018

was used to compare the results of both this study and previous academics.

The Mintel survey report provided extensive information on the market

conditions, especially customer opinions and satisfaction levels. Furthermore,

as the report was country specific, it provided details of the retailers’ market

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share and satisfaction levels related to their UK operations. Although it provided

the satisfaction levels of customers towards the return policies of retailers

analysed in this research, it did not provide further analysis on those retailers

regarding their return policies. This was mainly due to the nature of the survey,

as it was a questionnaire conducted online (Mintel, 2018). The sample size was

1,855 internet users aged 16+ who purchased clothing for themselves in the

last 12 months.

3.8 Tools used for analysis and overall advantages and limitations of the

methods used

Microsoft Excel was used for the analyses and presentation of the result of this

research. The use of secondary sources has its positives and negatives like

any other research method. The positives include time efficiency, especially

due to the limited time that was available to work on the research (Saunders et

al., 2016). Furthermore, it provided comparative and contextual data which

corresponded to the aims and objectives of this research. However, the use of

secondary sources limited the amount of depth the information or data provided

with regards to the research questions, as those data were collected and used

for a different purpose. As this is a time and cost efficient study, triangulation of

sources helped to improve the accuracy, reliability and usefulness of the

results. In addition, the three sources provided the sufficient level of information

required for this research.

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4.0 Results

Table 1 presents the return policies of the four retailers that were examined in

this research based on the five dimensions by Janakiraman et al. (2016). The

return policies show that all four retailers allow a 28-day return window, which

is in line with the UK’s law on online and distance selling (Government of UK,

2018). However, some of the retailers such as NEXT and New Look restrict the

time allowed to return sale items to 14 days. Other leniencies which are

common across the four retailers include offering full-cash refunds under the

exchange dimension and including sale items in the scope of returnable items,

which is also mandatory under the online and distant selling laws of the UK

(Government of UK, 2018).

4.1 Results of the four retailers’ return policies

H&M

H&M offers free returns for its customers as well as free courier collection. In

terms of effort, H&M provides pre-printed return labels with the initial package

delivery. This would allow customers to return packages without going through

the step of downloading and printing the return labels when returning items.

Among the four return options, in-store returns are included as H&M is a multi-

channel retailer. One of the positive aspects of H&M’s return policy is that the

time allowed for returns between regular and sale items is indifferent.

NEXT allows 28 days to return regular priced items, however the time allowed

for sale items is reduced to 15 days. Even though free returns are allowed for

in-store returns, the retailer charges GBP 1 for the Hermes home collection and

parcel shop options. Pre-printed return labels are provided with the initial

delivery of items and offers 4 options to return them as H&M.

New Look

New Look offers 28 days to return regular priced items however sale items are

required to be returned in 14 days. In contrast to the rest of the retailers, New

Look does not provide courier collection and pre-printed return labels to their

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customers. However, the retailer provides 4 return options as H&M and NEXT,

which include, In-store returns, Collect+, Doddle and Post.

ASOS

In contrast to other retailers in the analysis, ASOS is the only retailer that is

exclusively online based. As H&M, ASOS allows 28 days for their customers to

return items including sale items and does not impose any monetary

restrictions. Furthermore, in terms of effort, ASOS provides its customers with

pre-printed return labels, and offers 7 return options which is much higher than

the others. The increase in return options could be due to the retailer’s inability

to offer in-store return option to customers.

Table 1 – Analysis of the four retailers’ return policies based on the five dimensions.

# Dimensions H&M NEXT New Look ASOS

1 Time

Time allowed for return

Within 28 days from the

day of the delivery

including sale items

Within 28 days for

regular items. 15

days for sale items

Within 28 days from the

day of the delivery. 14

days for sale items

Within 28 days from the day

of delivery

2 Monetary

Free returns? Yes Not for all return

options Yes Yes

Free Courier

collection? Yes

No. £1 pound is

charged for courier

home collection and

Hermes parcel shop

No courier collection

option provided Yes

3 Effort

A Provides printed return

labels? Yes Yes No Yes

B No. of Return options

provided

4 return options: In-store

return, Royal Mail,

Hermes Parcel Shop,

Hermes Courier

4 return options: In-

store return, Courier

collection (Hermes),

Hermes Parcel shop,

Post Office

4 return options: In-store

return, Collect +, Doddle,

By Post (Royal Mail)

7 return options: Collect+,

Doddle, Hermes Parcel

shop, Hermes courier

collection, InPost, toyou via

Asda store, Royal Mail

4 Scope

Are sale items

included? Yes Yes Yes Yes

5 Exchange

Offers full cash

refund? Yes Yes Yes Yes

(Source: H&M UK, 2018; NEXT, 2018; New Look, 2018; ASOS, 2018)

Page 19 of 54

4.2 Main leniency factors and weightings

Table 2 - Journal articles used to analyse the return policy dimensions most commonly used by authors.

Leniency Dimensions Examined

# Authors Time Money Effort Scope Exchange

1 Bernon and Cullen (2016) Y Y

2 Jeng (2017) Y Y Y Y

3 Hsieh (2012) Y Y Y

4 Oghazi et al. (2017) Y Y Y

5 Rao et al. (2017) Y

6 Ülkü and Gürler (2018) Y Y

7 Chen and Chen (2016) Y Y Y

8 Hjort and Lantz (2016) Y Y Y

9 De Leeuw et al. (2016) Y Y

10 Bahn and Boyd (2014) Y

11 Bonifield, Cole, and Schultz (2010) Y Y Y Y

12 Bower and Maxham (2012) Y

13 d'Astous and Guevremont (2008) Y Y

14 Derbaix (1983) Y

15 Griffis et al. (2012) Y

16 Huppertz (2007) Y Y

17 Janakiraman and Ordóñez (2012) Y Y

18 Javadi et al. (2012) Y Y Y Y Y

19 Kang and Johnson (2009) Y Y Y

20 Kim and Wansink (2012) Y Y Y Y Y

21 Lantz and Hjort (2013) Y

22 Maity and Arnold (2013) Y Y Y Y Y

23 Pei, Paswan, and Yan (2014) Y Y Y Y Y

24 Posselt, Gerstner, and Radic (2008) Y Y

25 Powers and Jack (2013) Y Y Y Y Y

26 Shao, Chang, and Zhang (2014) Y

27 Suwelack, Hogreve, and Hoyer (2011) Y Y Y

28 Van den Poel and Leunis (1999) Y

29 Wang (2009) Y Y

30 Wood (2001) Y Y Y Y Y

TOTAL 20 23 19 9 9 80

Page 20 of 54

Table 2 shows the analysis of 30 studies conducted on the five dimensions.

The results show that with 23 studies conducted, money was the most common

leniency factor analysed among academics followed by time and effort.

However, few studies have been carried out on scope and exchange factors.

The results reveal that the most common numbers of dimensions analysed by

the authors were one and two dimensions together. For instance, analysing

monetary leniency only (Bower and Maxham, 2012) or analysing monetary and

time leniency together (Wang, 2009).

Based on the above results, Table 3 shows the weightings for each dimension.

Monetary leniency holds the most weight as it is the most commonly analysed

factor among previous academics. As observed, time and effort hold nearly the

same weight as Time was analysed 20 times and effort was analysed 19 times.

From the thirty academics observed, only nine of those considered scope and

exchange, hence both dimensions weigh eleven percent

Table 3 – Weightings of five dimensions in percentage.

Weightings

Time 25%

Money 29%

Effort 24%

Scope 11%

Exchange 11%

100%

4.3 Ranking of four retailers

Table 4 presents the scores of the four retailers calculated based on the

framework explained in Section 3 of this paper. The weights measured in Table

3 were used in the calculation to determine leniency of the four retailers. The

retailers are listed based on their score which represents their leniency from

first being the most lenient to fourth being the least lenient. ASOS scored the

highest by a considerably higher margin than others and represents the most

lenient return policy from the four retailers. H&M came second with a score of

8.41 followed by New Look and NEXT, which scored the lowest among the four

retailers. The details of the calculations can be found on Appendix 1.

Page 21 of 54

Table 4 – Scores and Rankings of retailers.

# Retailer Score

1 ASOS 10.00

2 H&M 8.41

3 New Look 7.56

4 NEXT 6.60

4.4 Comparison of rankings against Mintel Report

Charts 1 and 2 presents the comparison between the leniency scores and

customer satisfaction levels of the four retailers’ return policies from Mintel’s

market report. Details of Mintel (2018) satisfaction levels of the four retailers

can be found in Appendix 2. The Mintel results reveal that the customer

satisfaction for ASOS is the highest with the overall satisfaction level at 83%,

followed by NEXT with 77% and New Look and H&M that have a satisfaction

level of 75%. Both H&M and New Look share a similar overall dissatisfaction

level of 6%.

Chart 1 & 2 – Comparison of Return Policy scores against Mintel’s return policy satisfaction levels.

Chart 1: Return policy scores from Table 4.

Chart 2: Return policy satisfaction levels – Mintel (2018)

0.00 5.00 10.00

New Look

H&M

ASOS

Return Policy Scores

70 75 80 85

New Look

H&M

ASOS

Return Policy Satisfaction Level - Total

Satisfied (Mintel, 2018)

Page 22 of 54

5.0 Discussion

5.1 The Law and the main factors that contribute to return policy leniency in UK

The analysis of this research on prior academic journals on return policies

reveal that monetary leniency is the most important factor in the overall return

policy leniency as 23 out of 30 academic journals have analysed this factor.

The results highlight that in return policies, time and effort leniency are the

second and third most important factors, respectively. The importance of time

and monetary leniency is noticeable in the UK, as the law requires online

retailers to provide a return time frame and refunds to consumers (Government

of UK, 2018). Even though the results reveal scope and exchange as least

important, the law requires online retailers to refund items returned by

consumers as a form of exchange, including sale items (Government of UK,

2018). Hence, return policy variations in online clothing retailers in UK primarily

occur in terms of number of return collection options offered by the retailer,

monetary restrictions imposed on return collection options, and time restrictions

to return sale items.

5.2 Increasing return collection options increases effort leniency

Consistent with findings from prior research by De Leeuw el al (2016), and

Mintel’s (2018) survey data on satisfaction levels of retailers’ return policies, the

results from this research reveal that an increase in return collection options by

the retailer increases the effort leniency which therefore increases the overall

leniency of the return policy. It is evident that effort leniency is a major

contributor to the overall return policy leniency in online clothing retail in UK, as

the results show that the online-based retailer ASOS offers the highest number

of return options and scores the highest on return policy leniency.

5.3 Multi-channel retailers hold no significant advantage over online-base

retailers on return policy leniency

In contrast to prior academics who state that multi-channel retailers (Retailers

that operate both physical and online stores) have an advantage on return

policy leniency over purely online-based (De Leeuw et al., 2016; Sen, 2008;

Mukhopadhyay and Setaputra, 2004; Tarn et al., 2003), the results of this

Page 23 of 54

research and Mintel (2018)’s survey data reveal that in terms of customer

satisfaction on return policies, multi-channel retailers do not hold a significant

advantage by having physical stores over solely online-based retailers. This is

evident in the return policy analysis of ASOS which only operates online and

scored the highest on overall return policy leniency in this research.

5.4 Home collection return option does not contribute to return policy leniency

One of the factors of effort leniency that this research considered was the home

collection return option that was offered by H&M, NEXT and ASOS. However,

Mintel (2018)’s survey data reveals that retailers that offer home collection do

not have a significant advantage on leniency over retailers that do not offer the

service. This is evident from the same satisfaction levels achieved by H&M and

New Look in which the latter does not offer home collection in their return

options.

5.5 Time restrictions on sale items does not have an impact on return policy

leniency

In contrast to prior research and this study’s findings, Mintel (2018)’s survey

data does not show a difference in satisfaction levels for retailers that offer more

time to return sale items over retailers that restrict the time window for sale

items. This is evident from the satisfaction level that NEXT and New Look

achieved in the Mintel (2018) survey. Unexpectedly, NEXT, which imposes time

restrictions on sale items, has a higher satisfaction level compared to H&M

which offers the same return window for both sale and non-sale items.

5.6 Monetary restrictions on some of the return collection options do not have

an impact on return policy leniency

In contrast to findings by Janakiraman et al. (2016) and Wood (2001), and the

results of this paper, Mintel (2018) data show that NEXT, which imposes

monetary restrictions on some of the return collection options except for in-store

returns, scored higher on return policy satisfaction than other retailers that offer

more monetary leniency such as H&M and New Look. This was unforeseen

especially due to the influence monetary leniency factors have on the overall

return policy leniency. However, this strategy could encourage consumers of

Page 24 of 54

NEXT to use their free in-store return option and as De Leeuw et al. (2016) and

Tarn et al. (2003) highlight, there is potential for cross-selling opportunities.

Furthermore, as evident in Mintel (2018), NEXT’s target market is consumers

aged 25 to 45 years old, which is more mature compared to other retailers, and

the Office for National Statistics (2018) reveals that this age group has a higher

disposable income.

Page 25 of 54

6.0 Conclusion

Based on the findings, the research reveals that the strict consumer protection

laws in the UK requires all types of retailers to offer return policies that mainly

addresses scope, exchange, monetary and time factors of return policies. The

regulations imposed on online retailers are more stringent under the distance

and online selling laws as consumers are unable to physically examine a

product before purchasing (Government of UK, 2018). As a result, in order to

compete, online clothing retailers vary the number of return collection options

offered to consumers, monetary restrictions on those return collection options,

and the time allowed to return sale items.

6.1 The approach, overall findings and answers to research questions

Overall, the findings of this study provided answers to return policy leniency in

an industry and country specific context. Focusing on a specific industry

allowed to test theoretical frameworks proposed by previous academics, and

add/modify elements to relate to online clothing retail. The use of triangulation

in this research enabled to increase the validity by analysing from multiple

perspectives. Furthermore, inconsistencies in findings provided an opportunity

to uncover deeper meaning and draw conclusions from them. Therefore,

regarding the research questions of this paper, this study was able to

understand lenient and non-lenient return policies and identify major factors that

contribute to return policy leniency in online clothing retail in the UK. However,

the results for the relation between return policy leniency and customer

satisfaction levels is ambiguous and requires further exploration. Nevertheless,

this research revealed new findings related to single and multi-channel retailers

and adds new knowledge to the existing literature. Furthermore, the findings

provide supporting and contrasting points relating to prior academic research

concerning return policy leniency and its impact on consumers and retailers.

6.2 Objectives of the research

In terms of the research objectives, this paper has:

1. Determined that monetary and effort leniency factors are the main

contributors to return policy leniency in UK.

Page 26 of 54

2. Analysed the return policies of four online clothing retailers in UK which

are H&M, NEXT, New Look and ASOS. The return policies were

analysed based on frameworks that were proposed by prior academics,

however, were modified to relate to the retail clothing category in UK.

3. Measured and ranked the return four return policies by following a

framework. The results showed that ASOS has the most lenient return

policy due to the difference in the number of return collection options

offered by the retailer compared to others.

4. Compared the rankings against Mintel (2018) market data on customer

satisfaction levels of the four retailers. Consistent to the paper’s analysis,

the comparison of results showed that ASOS scores the highest on

return policy satisfaction. In contrast to the paper’s analysis, Mintel

(2018) data revealed that minor monetary restrictions and time

restrictions on returning sale items does not have an impact on the

customer’s perceived return policy leniency.

6.3 Implications of the research

This study highlights the importance effort leniency in online clothing retail in

UK, as the findings suggest that when retailers increase the number of return

collection options, it increases the overall return policy leniency and customer

satisfaction. This is in line with findings by De Leeuw et al. (2016) who find that

offering multiple collection options to return items increases consumer

satisfaction. Furthermore, this study contradicts prior research that suggest that

multi-channel retailers that have physical stores have an advantage over purely

online-based retailers (De Leeuw et al., 2016; Sen, 2008; Mukhopadhyay and

Setaputra, 2004; Tarn et al., 2003), as results show that by increasing return

options, online-based retailers can offset the advantage multi-channel retailers

have in terms of consumer effort, provided that online-based retailers offer

quality and convenient collection services for returning items.

A final implication for retailers based on the findings is that return policies

should be designed with the consideration of the target market. The results

suggest for multi-channel retailers, minor monetary restrictions can be used to

maximise the utilisation of in-store returns. As stated by De Leeuw et al. (2016),

Page 27 of 54

this would enable multi-channel retailers to increase the efficiency of

gatekeeping of returned items which would result in decreasing the cost on

returned items and being able to place them on the shelf sooner to re-sell. The

ability to re-sell returned items soon is vital as the clothing category has a

shorter life cycle compared to most of the other categories.

6.4 Limitations and recommendations for future research

While the research makes practical and theoretical contributions to the subject

of return policies in the UK, some limitations need to be considered. First, as

this was a time-restricted research, data for the study was collected from

secondary sources thus are limited in depth as the data collected by the

sources was used for another purpose (Saunders et al., 2016). Including

primary data such as a questionnaire or a focus group in triangulation may

provide more clarity and accuracy in comparisons and validation. Second,

increasing the size of the sample retailers and/or using transaction data of the

retailers for the analysis may also increase accuracy of the results. Third, the

results are relevant only to the clothing category in the UK. As the research on

return policy leniency is an evolving field, especially due to the increase in

return rates and the losses that retailers accumulate, there is potential for new

studies on this topic to address issues focused from a retailer’s perspective

which may provide additional interesting insights into return policies. One of the

issues that future research could explore is analysing the reasons for returns in

online clothing retail, and understanding how technology can contribute to

lowering rate of returns in clothing such as returns related to size/fit issues.

Page 28 of 54

Reflective Account

My research project on “A study on return policy leniency in online clothing retail

in UK” began after reading a news article on return policies and its impact on

retailers’ profits. As I read further on the subject I became aware that the impact

of return policies was higher for online retailers, and the category of products

with the highest rate of returns are clothing. This elevated my interest on the

subject and lead to additional research on the topic. Hence I began to read

academic journals related to return policy leniency and its impact on the

consumer and retailer.

By the time I was assigned Steve Raybould as my supervisor, I had collected

few literature related to the topic however was unable to determine an

appropriate title and where to focus on regarding return policies. As the pathway

of my course required me to focus on an International context, with the

assistance of my supervisor, I was able to form a topic that was relevant to the

pathway. One of the challenges that I faced was determining the type of

research I would be conducting to obtain data. Finally, by discussing with my

supervisor Steve, I decided to undertake the second option of the research

project, which was the use of only secondary research mainly due to the

adequate secondary resources that were available for the research from the

university library’s online database.

Three main sources of data were used for the research, which were resources

from academic journals, my own analysis conducted on four online clothing

retailers in the U.K, and Mintel’s consumer opinion surveys on those retailers

that also provided satisfaction levels of consumers on the return policies. With

further discussions with my supervisor I decided to conduct a triangulation

research that compared the findings of the three sources of data and validated

certain theories from prior academics. Furthermore, it allowed me to explore

the return policy leniency factors in more depth and understand how they are

used in the online retail clothing category in U.K. The university’s access to

major databases such as Mintel helped me to a great extent, as I was able to

get access to data on consumer opinions and satisfaction levels on clothing

retailers specific to the U.K. The main sources that I used to collect academic

Page 29 of 54

journals were BCU online library catalogue, EBSCOhost, ABI/INFORM Global,

Emerald, Google Scholar and Science Direct.

As my research continued, I began to see how I could modify some of the

dimensions and theories proposed by previous academic researchers to make

the research more relevant to the online retail clothing category of U.K.

Modifying the leniency dimensions and what it meant was essential as they

were created to explain the leniency factors associated to return policies in a

more broad retail context. In addition, I learnt that the use of tables and

diagrams particularly in the methods and results section, aided in consolidating

large sets of data and helped to explain frameworks and theories used in the

study.

I believe that collecting the relevant sources of data early helped me complete

this research on time as I learnt how time consuming it is to access and analyse

relevant data. Furthermore, by being methodical and by following a time line, I

was able to complete and show drafts of each section to my supervisor for

feedback. As this was the first dissertation that I attempted, the support my

supervisor gave helped me immensely in completing this project. The

responsiveness and flexibility that he gave in providing suggestions, feedback

and scheduling meetings made the process convenient.

Overall, by undertaking this project, I have learnt to manage my time more

effectively, and the input that colleagues can contribute by showing sections of

my work to them. Furthermore, I have learnt the importance of critical analysis

in research, in order to draw meaningful conclusions. This project also showed

the importance of triangulation in research in order to compare, validate and

understand theories and issues. I have also learnt that when conducting

research projects, I may not be able to answer every research question that I

initially set out to answer, however I can explore alternative findings that can

make an important contribution to the overall research.

Moving on, some elements that I would like to change and explore when doing

future research would be using primary research in my paper. For instance,

questionnaires would have enabled me to collect data that would strictly be

relevant to the purposes of my research and would have provided more depth

Page 30 of 54

to the research if I had mixed qualitative and quantitative questions in a survey.

Moreover, the inclusion of primary data in a triangulation research would have

had the potential to increase the clarity of findings of the research. Finally, I

believe that I need to be more decisive in choosing a topic, scope and methods,

when working on a time efficient study such as this research.

Page 31 of 54

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https://www.ons.gov.uk/peoplepopulationandcommunity/personalandhous

eholdfinances/expenditure/bulletins/familyspendingintheuk/financialyearen

ding2017 [Accessed 20 December 2018].

Oghazi, P., Karlsson, S., Hellström, D., Hjort, K. (2018) Online purchase

return policy leniency and purchase decision: Mediating role of consumer

trust. Journal of Retailing and Consumer Services, 41, pp. 190-200.

Pei, Z., Paswan, A., Yan, R. (2014) E-tailer’s return policy, consumer’s

perception of return policy fairness and purchase intention. Journal of

Retailing and Consumer Services, 21, pp. 249-257.

Peterson, J.A., Kumar, V. (2010) Can Product Returns Make You Money?.

MIT Sloan Management Review, 51(3), pp. 84-89.

Posselt, T., Gerstner, E., Radic, D. (2008) Rating E-tailers’ Money-back

Guarantees. Journal of Service Research, 10(3), pp. 207-219.

http://academic.mintel.com/display/859493/

http://academic.mintel.com/display/590236/

https://help-uk.newlook.com/hc/en-gb/sections/360002145692-How-to-return

https://help.next.co.uk/Section.aspx?ItemId=10272

https://www.ons.gov.uk/peoplepopulationandcommunity/personalandhouseholdfinances/expenditure/bulletins/familyspendingintheuk/financialyearending2017

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Powers, T.L., Jack, E.P. (2013) The Influence of Cognitive Dissonance on

Retail Product Returns. Psychology & Marketing, 30(8), pp. 724-735.

Rao, S., Lee, K.B., Connelly, B., Iyengar, D. (2017) Return Time Leniency

in Online Retail: A Signaling Theory Perspective on Buying Outcomes.

Decision Sciences: A Journal of the Decision Sciences Institute, 49(2) 275-

305.

Reuters (2013) Online retailers go hi-tech to size up shoppers and cut

returns. Available at: https://www.reuters.com/article/net-us-retail-online-

returns/online-retailers-go-hi-tech-to-size-up-shoppers-and-cut-returns-

idUSBRE98Q0GS20130927 [Accessed 29 November 2018].

Saunders, M., Lewis, P., Thornhill, A. (2016) Research Methods for

Business Students. 7th edn. Harlow: Pearson Education Limited.

Sen, A. (2008) The US fashion industry: a supply chain review. International

Journal of Production Economics, 114(2), pp. 571-593.

Shao, B., Chang, L., Zhang, L. (2013) The Effect of Online Return Shipping

Insurance and Regulatory Focus on Consumer Behavior. 23rd International

Business Research Conference, 18-20 November. Melbourne: Marriott

Hotel.

Suwelack, T., Hogreve, J., Hoyer, W.D. (2011) Understanding Money-Back

Guarantees: Cognitive, Affective, and Behavioral Outcomes. Journal of

Retailing, 87(4), pp. 462-478.

Tarn, J.M., Razi, M.A., Wen, H.J., Perez, A.A. (2003) E-fulfilment: the

strategy and operational requirements. Logistics Information Management,

16(5), pp. 350-362.

Ülkü, M.A., Gürler, U. (2018) The impact of abusing return policies: A

newsvendor model with opportunistic consumers. International Journal of

Production Economics, 203, pp. 124-133.

Wang, X. (2009) Retail Return Policy, Endowment Effect, and Consumption

Propensity: An Experimental Study. The BE Journal of Economic Analysis

& Policy, 9(1).

Wood, S.L. (2001) Remote purchase environments: The influence of return

policy leniency on two-stage decision processes. Journal of Marketing

Research, 38(2), pp. 157-169.

Yan R. (2009) Product categories, returns policy and pricing strategy for e-

marketers. Journal of Product & Brand Management, 18(6), pp. 452-460.

https://www.reuters.com/article/net-us-retail-online-returns/online-retailers-go-hi-tech-to-size-up-shoppers-and-cut-returns-idUSBRE98Q0GS20130927

Page 36 of 54

Appendix

Appendix 1

Calculation of return policy leniency of four retailers.

H&M

Dimension Points Weight Score

Time The return window for sale items and regular items is the same and is 28 days and above 10 25% 2.500

Money All return options for customers are free 10 29% 2.875

Effort 3 Return options 3 24% 0.788

Provides pre-printed shipping label 2

In-store return option 2

Scope Sale items are included 10 11% 1.125

Exchange Offers full cash refund 10 11% 1.125

TOTAL 8.41

ASOS

Dimension Points Weight Score

Time The return window for sale items and regular items is the same and is 28 days and above 10 25% 2.500

Money All return options for customers are free 10 29% 2.875

Effort 8 Return options 3 24% 2.375

Provides pre-printed shipping label 2

In-store return option 0

Scope Sale items are included 10 11% 1.125

Exchange Offers full cash refund 10 11% 1.125

TOTAL 10.00

Page 37 of 54

New Look

Dimension Points Weight Score

Time

Return window for sale items and regular items are different and the average time is less than 28 days 5 25% 1.250

Money All return options for customers are free 10 29% 2.875

Effort 3 Return options 3 24% 1.188

Does not provide pre-printed shipping label 0

In-store return option 2

Scope Sale items are included 10 11% 1.125

Exchange Offers full cash refund 10 11% 1.125

TOTAL 7.56

Dimension Points Weight Score

Time

Return window for sale items and regular items are different and the average time is less than 28 days 5 25% 1.250

Money Charges for some return options 5 29% 1.438

Effort 3 Return options 3 24% 1.663

Provides pre-printed shipping label 2

In-store return option 2

Scope Sale items are included 10 11% 1.125

Exchange Offers full cash refund 10 11% 1.125

TOTAL 6.60

Page 38 of 54

Appendix 2

Return Policy Satisfaction Levels – Mintel (2018)

Returns policy Next New Look H&M ASOS

Total 445 421 460 177

Any satisfied 77% 75% 75% 83%

Very satisfied 25% 25% 25% 31%

Satisfied 52% 51% 50% 53%

Neither satisfied nor dissatisfied 15% 15% 15% 11%

Any dissatisfied 4% 6% 6% 3%

Dissatisfied 3% 5% 5% 2%

Very dissatisfied 1% 1% 1% 1%

Not applicable 4% 3% 4% 2%

(Source: Mintel, 2018)

Page 39 of 54

Appendix 3

Tutorial Record -1

BIRMINGHAM CITY BUSINESS SCHOOL

MSc Management: Individual Major Project – RECORD OF TUTORIAL

This form (apart from supervisor’s comments) should be completed by the student for each meeting.

A copy should be sent to the supervisor as an e-mail attachment within 3 days of the meeting.

Student name: Ibrahim Hamdhan Mohamed

Student ID number:

17150910

Supervisor name: Stephen Raybould

Date of Tutorial: Tuesday 9th October 2018

Comments on Progress since last meeting:

*First Meeting

Matters Discussed:

• Discussion on the scope of the research topic and an appropriate title

• Suggestions on where to find literature

• General discussion on research philosophies and methods that would be suitable

Action/Research to be undertaken before next meeting:

Find literature

Supervisor’s comments:

Date and Time of next meeting:

Tuesday 23rd October 2018

Page 40 of 54

Tutorial Record - 2

BIRMINGHAM CITY BUSINESS SCHOOL

MSc Management: Individual Major Project – RECORD OF TUTORIAL

This form (apart from supervisor’s comments) should be completed by the student for each meeting.

A copy should be sent to the supervisor as an e-mail attachment within 3 days of the meeting.

Student name: Ibrahim Hamdhan Mohamed

Student ID number:

17150910

Supervisor name: Stephen Raybould

Date of Tutorial: Tuesday 23rd October 2018

Comments on Progress since last meeting:

Collected sufficient literature to draft the research proposal

Matters Discussed:

• Discussion on the requirements of the proposal

• Primary and secondary research

• Finalised scope and title of the research (for proposal)

Action/Research to be undertaken before next meeting:

Complete proposal for submission

Supervisor’s comments:

Date and Time of next meeting:

Friday 9th November 2018

Page 41 of 54

Tutorial Record – 3

BIRMINGHAM CITY BUSINESS SCHOOL

MSc Management: Individual Major Project – RECORD OF TUTORIAL

This form (apart from supervisor’s comments) should be completed by the student for each meeting.

A copy should be sent to the supervisor as an e-mail attachment within 3 days of the meeting.

Student name: Ibrahim Hamdhan Mohamed

Student ID number:

17150910

Supervisor name: Stephen Raybould

Date of Tutorial: Friday 9th November 2018

Comments on Progress since last meeting:

Submission of Research Proposal

Matters Discussed:

• Feedback on proposal

Action/Research to be undertaken before next meeting:

Expand Literature review for final submission and continue work on subsequent sections of the

research

Supervisor’s comments:

Date and Time of next meeting:

Wednesday 27th November 2018

Page 42 of 54

Tutorial Record – 4

BIRMINGHAM CITY BUSINESS SCHOOL

MSc Management: Individual Major Project – RECORD OF TUTORIAL

This form (apart from supervisor’s comments) should be completed by the student for each meeting.

A copy should be sent to the supervisor as an e-mail attachment within 3 days of the meeting.

Student name: Ibrahim Hamdhan Mohamed

Student ID number:

17150910

Supervisor name: Stephen Raybould

Date of Tutorial: Wednesday 27th November 2018

Comments on Progress since last meeting:

Completed final draft of Introduction and Literature Review

Matters Discussed:

• Feedback on Literature review

• How to structure Methods/Methodology section

• Philosophy used in the research

Action/Research to be undertaken before next meeting:

Show a draft of Methods section by next meeting

Supervisor’s comments:

Date and Time of next meeting:

Monday 3rd December 2018

Page 43 of 54

Tutorial Record – 5

BIRMINGHAM CITY BUSINESS SCHOOL

MSc Management: Individual Major Project – RECORD OF TUTORIAL

This form (apart from supervisor’s comments) should be completed by the student for each meeting.

A copy should be sent to the supervisor as an e-mail attachment within 3 days of the meeting.

Student name: Ibrahim Hamdhan Mohamed

Student ID number:

17150910

Supervisor name: Stephen Raybould

Date of Tutorial: Monday 3rd December 2018

Comments on Progress since last meeting:

Draft of Methods section and analysis done for results

Matters Discussed:

• Finalised structure for methods and subsequent sections

• Benefits of conducting a triangulation research

• Feedback on the three sources used for triangulation

• Use of diagrams and tables in results section

Action/Research to be undertaken before next meeting:

E-mail a completed draft of Results

Supervisor’s comments:

Date and Time of next meeting:

Page 44 of 54

Appendix 4

Research Proposal

Course: Msc Management and International Business

Module: BUS7048 – Major Project

A comparative study of return policy leniency in

clothing retail in U.K

Word Count: 1,485

Submitted by: Ibrahim Hamdhan Mohamed (Student Number: 17150910)

Submitted to: Steve Raybould

Date of Submission: 26th October 2018

Page 45 of 54

A comparative study of return policy leniency in clothing retail in U.K

Background

The concept of allowing returns has been around since the late 1800’s when

Montgomery Ward first implemented the commitment of “Satisfaction

guaranteed or your money back” to its customers (Brennan, 1991). In the

modern business setting, almost every retailer offers some form of return

provision to customers as a result of consumer protection laws and competition

between retailers.

The importance of return policies are especially felt in online clothing retail, as

consumers have to sacrifice the benefit of physical inspection of the product. A

survey conducted by KPMG in U.K shows that 31.4% of customers from both

genders who purchased fashion apparel online intended to return one or more

of the same item, and 62% of shoppers in general identify free returns as the

most important factor when returning orders (KPMG, 2018). The purpose of this

research is to identify the factors that contribute towards a lenient return policy

in retail and compare the return policies of five clothing retailers in U.K.

Literature review

Retailers are required to have a returns policy under the consumer protection

law in the U.K (Government of U.K, 2018). However the law provides the basic

requirements that retailers must meet in shaping their return policies. Based on

this, some retailers offer return policies that can be considered more lenient

than others. Wood (2001) states offering lenient return policies can be a way of

minimising risk that is passed on to the consumer during purchase. This is

Page 46 of 54

supported by Peterson and Kumar (2010) who explain that when customers

have knowledge that they can return a product, it reduces customer’s

perception of risk in purchasing it. However offering lenient return policies is a

cost for retailers. As return policy leniency increases, the volume of products

returned by customers increase, resulting in logistical costs for retailers (Wood,

2001).

Maintaining a lenient return policy that allows customers to return almost any

product at any time will increase the customer’s future purchases hence

benefiting the retailer in the long-term (Peterson and Kumar 2010). However

Lantz and Hjort (2013) argue that even though a lenient return policy increases

order frequency, it reduces the average value of purchased items, and

increases the probability of return. Hence retailers are faced with a trade-off of

adjusting their return policies to minimise product returns or to avoid losing

potential sales as a result of stricter return policy.

Several authors have done research on return policy leniency and its impact on

consumer purchase. However there are differences in how leniency is

measured in those studies. Some experiments varied the amount of monetary

refund such as the research by Wood (2001) in which the results showed that

with more monetary leniency such as offering full cash refund on product

returns increased the order frequency. In another study, the scope of returnable

products were varied to differentiate a strict and lenient return policy which

resulted in more purchases (Peterson, Kumar, 2010). This indicates that both

monetary and scope leniency impacts customer purchase behaviour. Additional

factors were also explored in recent studies which included testing two factors

together such as the time allowed and effort required to return products

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(Janakiraman and Ordóñez, 2012). The research identified that the

combination of less return effort (customers not having to fill out return forms)

and shorter deadlines lead to higher return rates (Janakiraman and Ordóñez,

2012). As this study is focused on identifying return leniency factors, it suggests

that both time and the level of effort required by the return policy influences

leniency. Janakiraman and Ordóñez (2012) referred to time as the deadline

given to the consumer by the retailer to return the product. Time can be

extended further to include the time taken by the retailer to process the return

and refund or exchange the product. Although it is logical to assume that

quicker return processing times can increase customer satisfaction, previous

literature have not included this aspect as a factor that contributes to return

policy leniency (Janakiraman and Ordóñez, 2012; Wood, 2001; Peterson and

Kumar, 2010). However effort may not be limited to simply filling out a return

form as Leeuw et al (2015) refers to Mukhopadhyay and Setoputro (2004) who

highlight that customers who are able to return online purchases to physical

stores are more satisfied than customers who are unable to. This is supported

by Sen (2008) and Tarn et al. (2003) who state that multi-channel retailers

benefit by offering consumers the option to return items to one of their physical

stores. Hence a multi-channel clothing retailer that utilises both brick-and-

mortar stores and its online store for returns can have an advantage over

retailers that operate online only in establishing return policies as such retailers

would be limited to third party collection drop off points such as Hermes and

DHL. An additional factor called ‘exchange’ was included in previous research

by Davis et al. (1998) and Heiman et al. (2001) to define the mode of exchange

as a return policy that allows a full cash refund or an exchange of the product

Page 48 of 54

in which a full cash refund is considered the most lenient form of exchange.

This factor is supported by a recent study conducted by Janakiraman et al.

(2016) that considers exchange as either offering full-cash refund, store credit

or an exchange of the product.

It is essential to have a framework that includes sufficient factors in order to

classify return policies as lenient or non-lenient. Previous researchers have

attempted to create a framework such as Davis et al. (1998) who included five

factors which are the acceptance of exchanges or cash refunds by the store,

the requirement of having a receipt or not, the condition of having the original

packaging when returning, whether there are visible signs of use or not; and

the time frame given to return products. Another framework created by Heiman

et al. (2001) included four factors which are, the time frame given to return,

whether the customer has to pay for the return cost fully, or partially, the

provision of monetary refund or product exchange by the retailer, and the

requirement of having the original packaging when returning. Janakiraman et

al. (2016) combines these factors to include five dimensions that determine a

return policy leniency which are, time leniency, monetary leniency, effort

leniency, scope leniency and exchange leniency. As this framework combines

previous literature’s factors, it is more comprehensive. Therefore based on

these 5 dimensions, the research will question how return policy leniency can

be measured and compare return policies in clothing retailers in U.K based on

their leniency.

Page 49 of 54

Methodology

The overall approach of this research will be deductive by which an existing five

dimensional framework will be used to test and determine lenient return policies

among five multi-channel (Online and physical store) clothing retailers in the

U.K, which are H&M, NEXT, Mango, New Look, and Zara. Research will be

based on secondary sources such as online databases, journals, and from the

information available on retailers’ websites.

A comparative analysis will be done on the return policies of the five retailers

based on their leniency. The measurement of leniency will be done by following

the five dimension framework created in the research of Janakiraman et al.

(2016) which are:

1. Time leniency: Policies that provide a longer time frame to return

products are considered more lenient.

2. Monetary leniency: Policies that do not impose monetary restrictions

such as “return shipping fee” on the consumer such are considered more

lenient.

3. Effort leniency: Policies that require less effort (such as not requiring

original packaging, printing of shipping label, more courier options to

return, allowing online sales to be returned to store) on the part of the

customer are considered more lenient.

4. Scope leniency: Policies with a greater scope of returnable items (such

as including sale items) are considered more lenient.

5. Exchange leniency: Policies that allow cash refund instead of product

exchange or store credit are considered more lenient.

Page 50 of 54

Objectives

1. To understand what factors contribute towards a lenient return policy

2. To analyse return policies of clothing retailers based on a dimensional

framework

3. To compare and rank the selected retailers’ return policy leniency based

on the framework

Rationale

This research aims to measure, test and compare returns policy leniency on a

product category based on a framework. It will identify lenient return policies

that are used by clothing retailers in the U.K. One of the limitations of this

research is that it does not consider the cost of implementing lenient return

policies from a retailer’s perspective. Research done by Pei et al. (2014) show

that return policy leniency positively influences consumer’s perceived return

policy fairness, trust and purchase intention. This is supported by Oghazi et al.

(2017) that shows the same positive relationship between return policy leniency

and customer purchase intention. Hence this study can be a reference for

existing and future businesses to identify return policies that work best with

consumers in clothing retail.

Page 51 of 54

Work Plan

Week commencing 22/10 29/10 05/11 12/11 19/11 26/11 03/12 10/12 17/12 24/12 31/12 07/01

Number 05 06 07 08 09 10 11 12 13 14 15 16

Firm up topic

Prepare research proposal

Literature review (1st

draft)

Methodology (draft)

Design

research instrument

Methodology (final)

Collect data

Analyse data (draft)

Literature review (final)

Data analysis (final)

Discussion (draft)

Discussion (final)

Full dissertation

(draft)

Proofreading and final

preparation

Proposa l

deadline

Hand- in

deadli ne

11/01/1

End of supervision s deadline

Page 52 of 54

References (Research Proposal)

Brennan, S.E., Clark, H.H. (1991) Grounding in Communication. American

Psychological Association, pp. 127-149.

Davis., Scott., Hagerty, M., Gerstner, E. (1998) Return Policies and the

Optimal Level of “Hassle”. Journal of Economics and Business, 50(5), pp.

445-60.

GOV.UK (2018) Accepting returns and giving refunds: the law. Available at:

https://www.gov.uk/accepting-returns-and-giving-refunds [Accessed 24

October 2018].

Heiman., Amir., McWilliams B., Zilberman D. (2001) Demonstrations and

Money-Back Guarantees: Market Mechanisms to Reduce Uncertainty.

Journal of Business Research, 54(1), pp. 71-84.

Janakiraman, N., Ordóñez, L. (2012) Effect of effort and deadlines on

consumer product returns. Journal of Consumer Psychology, 22(2), pp.

260-271.

Janakiraman, N., Syrdal, H.A., Freling, R. (2016) The Effect of Return Policy

Leniency on Consumer Purchase and Return Decisions: A Meta-analytic

Review. Journal of Retailing, 92(2), pp. 226-235.

KPMG (2018) Annual Retail Survey, 2018. [pdf] U.K: KPMG. Available at:

https://assets.kpmg.com/content/dam/kpmg/uk/pdf/2018/01/kpmg-annual-

retail-survey-2018.pdf [Accessed 15 September 2018].

https://www.gov.uk/accepting-returns-and-giving-refunds

Page 53 of 54

Lantz, B., Hjort, K. (2013) Real e-customer behavioural responses to free

delivery and free returns. Electronic Commerce Research, 13(2), pp. 183-

98.

Leeuw, S.D., Minguela-Rata, B., Sabet, E., Boter, J., Sigurdardottir, R.

(2016) Trade-offs in managing commercial consumer returns for online

apparel retail. International Journal of Operations & Production

Management, 36(6), pp. 710-731.

Mukhopadhyay, S.K., Setoputro, R. (2004) Reverse Logistics in e-business:

optimal price and return policy. International Journal of Physical Distribution

& Logistics Management, 34(1), pp. 70-89.

Oghazi, P., Karlsson, S., Hellstrom, D., Hjort, K. (2018) Online purchase

return policy leniency and purchase decision: Mediating role of consumer

trust. Journal of Retailing and Consumer Services, 41, pp. 190-200.

Pei, Z., Paswan, A., Yan, R. (2014) E-tailer’s return policy, consumer’s

perception of return policy fairness and purchase intention. Journal of

Retailing and Consumer Services, 21, pp. 249-257.

Peterson, J.A., Kumar, V. (2010) Can Product Returns Make You Money?.

MIT Sloan Management Review, 51(3), pp. 84-9.

Sen, A. (2008) The US fashion industry: a supply chain review. International

Journal of Production Economics, 114(2), pp. 571-593.

Tarn, J.M., Razi, M.A., Wen, H.J., Perez, A.A. (2003) E-fulfilment: the

strategy and operational requirements. Logistics Information Management,

16(5), pp. 350-362.

Page 54 of 54

Wood, S.L. (2001) Remote purchase environments: The influence of return

policy leniency on two-stage decision processes. Journal of Marketing

Research, 38(2), pp. 157-169.

Zhang, J., Li, H., Yan, R., Johnston, C. (2017) Examining the signalling

effect of e-tailers’ return policies. J. Comput. Inf. Syst., 57(3), pp. 191-200.

Cover Page
Abstract
Table of Contents V1
Dissertation Compiled V2