e-wallet - designed for usabilitykth.diva-portal.org/smash/get/diva2:1322382/fulltext01.pdf ·...
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IN DEGREE PROJECT TECHNOLOGY,FIRST CYCLE, 15 CREDITS
, STOCKHOLM SWEDEN 2019
E-wallet - designed for usability
BERCIS ARSLAN
BLENDA FRÖJDH
KTH ROYAL INSTITUTE OF TECHNOLOGYSCHOOL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE
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E-wallet - designed for usability
Bercis Arslan and Blenda Fröjdh
2019-06-07
Bachelor’s Thesis
Examiner
Gerald Q. Maguire Jr.
Academic adviser
Anders Västberg
KTH Royal Institute of Technology
School of Electrical Engineering and Computer Science (EECS)
Department of Communications
SE-100 44 Stockholm, Sweden
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Abstract
As the use ofmobile payment applications (apps) and electronicwallets (e-wallets)
increases, so does the demand for a improved user experience when interacting
with these apps. The field of Human-Computer interaction (HCI) focuses on
the design, evaluation, and implementation of interactive computing systems for
human use. One aspect of HCI is usability, i.e., the quality of the interactions with
a product or system.
This thesis investigates how an e-wallet can be designed to provide a high level of
usability by conforming to best HCI practices and by formative evaluation using a
set of usability evaluation methods.
The research process consisted of an initial literature study and development
of a prototype, which was evaluated iteratively through Thinking-aloud-protocol
(TAP) and a combination of performance measurements and questionnaire by a
chosen test group.
By each iteration, the results of the performance measurements, as well as the
verbal data improved. The most complex or difficult task, for the test subjects
to perform, was, according to the results, Pay via manual input. All goals were
achieved for all tasks except for the performance goal of a percentage of errors
below 5%.
To conclude, it was clear that the test subjects had more trouble understanding
the concept of the e-wallet rather than navigating and completing tasks. The
difficulties lay in understanding how currencies were stored and how transactions
happened. When developing this e-wallet we noticed that the most important
issuewas tomake new functions and concepts familiar to the user through relating
it to recognizable ideas.
Keywords
Usability, usability testing, e-wallet, mobile payments, Think-aloud protocol,
performance measurements
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Abstract
I ochmed att användning av mobila betalningslösningar (appar) och elektroniska
plånböcker (e-plånböcker) ökar, ökar även efterfrågan på en förbättrad
användarupplevelse vid interaktion med dessa appar. Området människa-
datorinteraktion (MDI) fokuserar på design, utvärdering och implementering
av interaktiva datorsystem för mänsklig användning. En aspekt av MDI är
användbarhet, dvs kvaliteten på interaktionerna med en produkt eller ett system.
Detta kandidatexamensarbete undersöker hur en e-plånbok kan utformas för
att ge en hög användbarhet genom att anpassas till MDI praxis och formativ
utvärdering av designen med hjälp av en uppsättning utvärderingsmetoder för
användbarhet.
Forskningsprocessen bestod av en litteraturstudie och utveckling av en prototoyp,
som utvärderades iterativt genom Thinking-aloud Protocol (TAP) samt en
kombination av prestationsmätningar och frågeformulär av en vald testgrupp.
Efter varje iteration förbättrades resultaten av prestationsmätningarna, såväl
som för den verbala datan. Den mest komplexa eller svåra uppgiften,
för testpersonerna att utföra, var, enligt resultaten, Betalning via manuel
inmatning. Alla mål uppnåddes för alla uppgifter förutom prestationsmålet för
en procentandel av fel under 5 %.
Avslutningsvis var det tydligt att testpersonerna fann det svårare att förstå
konceptet av e-plånboken än att navigera och slutföra uppgifterna. Svårigheterna
låg i att förstå hur valutor lagrades och hur transaktioner gick till. När vi
utvecklade den här e-plånbokenmärkte vi att den viktigaste uppgiften var att göra
nya funktioner och koncept förståerliga för användaren genom att koppla dem till
igenkännliga idéer.
Nyckelord
Användarbarhet, användarbarhetstestning, e-plånbok, mobilbetalningar, tänk-
högt protokoll, prestationsmätningar
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Acknowledgements
We would like to thank our examiner Gerald Q. Maguire Jr. at KTH Royal
Institute of Technology, for his support and much needed guidance during our
project. For his detailed and useful feedback, given whenever needed.
Secondly we would like to thank Henrik Gradin at Centiglobe for giving us the
opportunity to do this project.
Stockholm, June 2019
Blenda Fröjdh and Bercis Arslan
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Authors
Bercis Arslan, [email protected] and Blenda Fröjdh, [email protected] Royal Institute of Technology
Place for Project
CentiglobeStockholm, Sweden
Examiner
Gerald Q. Maguire Jr.KTH Royal Institute of Technology
Supervisor
Anders VästbergKTH Royal Institute of Technology
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Contents
1 Introduction 11.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.4 Goal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.5 Benefits, Ethics, and Sustainability . . . . . . . . . . . . . . . . . . . 3
1.6 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.7 Stakeholders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.8 Requirements from Centiglobe . . . . . . . . . . . . . . . . . . . . . 7
1.9 Delimitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.10 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2 Background 92.1 Human computer interaction . . . . . . . . . . . . . . . . . . . . . . 9
2.1.1 Usability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.2 Usability evaluation . . . . . . . . . . . . . . . . . . . . . . . 10
2.1.3 Analytical modeling . . . . . . . . . . . . . . . . . . . . . . . 11
2.1.4 Inspection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1.5 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.6 Inquiry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.7 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.8 Measurement of usability . . . . . . . . . . . . . . . . . . . . 13
2.1.9 Prototypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.1.10 Design principles, guidelines, and theories . . . . . . . . . . 14
2.1.11 Task flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.2 E-wallet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2.1 E-wallets on the market . . . . . . . . . . . . . . . . . . . . . 18
2.2.2 Transaction and payment methods . . . . . . . . . . . . . . . 18
2.2.3 Task flow of existing E-wallets . . . . . . . . . . . . . . . . . 19
2.3 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3.1 User experience of Bitcoin wallets of usability and security . 20
2.3.2 Designing mobile wallets . . . . . . . . . . . . . . . . . . . . 21
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2.3.3 User experience of a mobile app . . . . . . . . . . . . . . . . 21
2.3.4 Acceptance of mobile wallets in Oman . . . . . . . . . . . . . 21
2.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3 Method 253.1 Research process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.2 Research paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.3 Data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.3.1 Test group . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.3.2 Consent form . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.3.3 Sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.3.4 Sample size . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.3.5 Target population . . . . . . . . . . . . . . . . . . . . . . . . 30
3.4 Experimental design/planned measurements . . . . . . . . . . . . . 31
3.4.1 Performance measurement . . . . . . . . . . . . . . . . . . . 31
3.4.2 Thinking-aloud protocol . . . . . . . . . . . . . . . . . . . . . 33
3.4.3 Test environment . . . . . . . . . . . . . . . . . . . . . . . . 33
3.4.4 Software and Hardware to be used . . . . . . . . . . . . . . . 33
3.5 Assessing reliability and validity of the method and data collected . 34
3.5.1 Reliability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.5.2 Validity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.6 Planned Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.7 Evaluation framework . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.7.1 Collection of data . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.7.2 Evaluation of data . . . . . . . . . . . . . . . . . . . . . . . . 37
4 The Work 414.1 Tasks to be analyzed . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.2 Test group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.3 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.4 Data collection and analysis . . . . . . . . . . . . . . . . . . . . . . . 43
4.5 The prototype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
5 Result and Analysis 45
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5.1 Results iteration 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
5.1.1 Changes after iteration 1 . . . . . . . . . . . . . . . . . . . . . 46
5.2 Results iteration 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
5.2.1 Changes after iteration 2 . . . . . . . . . . . . . . . . . . . . 48
5.3 Results iteration 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.3.1 Changes after iterations 3 . . . . . . . . . . . . . . . . . . . . 50
5.4 Results iteration 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.5 Reliability Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
5.6 Validity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
5.7 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
6 Conclusions and Future work 576.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
6.2 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
6.3 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
6.4 Reflection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
References 62
A First Appendix 69
B Second Appendix 71
C Third Appendix 72
D Fourth Appendix 78
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List of figures
2.1 Example of the task flow of buying milk . . . . . . . . . . . . . . . . 17
2.2 Task flow of Paypal . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.1 SEQ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.1 Example of changes made to the prototype between iteration 1 and
iteration 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
5.2 Example of changesmade on the prototype between iteration 2 and
iteration 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.3 Example of changesmade on the prototype between iteration 3 and
iteration 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
A.1 Task flow of Swish . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
A.2 Task flow of Paypal . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
C.1 Task instructions for iteration 1 . . . . . . . . . . . . . . . . . . . . . 72
C.2 Task instructions for iteration 2 . . . . . . . . . . . . . . . . . . . . 74
C.3 Task instructions for iteration 3 4 . . . . . . . . . . . . . . . . . . . 76
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List of tables
3.1 The performance measurements. . . . . . . . . . . . . . . . . . . . . 31
3.2 The performance goals. . . . . . . . . . . . . . . . . . . . . . . . . . 39
4.1 The test subjects and their perceived experience using mobile
payment apps and experience of software development. . . . . . . . 42
5.1 Median value of performance measurements iteration 1 . . . . . . . 46
5.2 Median value of performance measurements iteration 2 . . . . . . . 48
5.3 Median value of performance measurements iteration 3 . . . . . . . 50
5.4 Median value of performance measurements iteration 4 . . . . . . . 52
D.1 Exerpt of concept coded verbal data . . . . . . . . . . . . . . . . . . 78
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List of acronyms and abbreviations
App Application
E-wallet Electronic Wallet
HCI Human-Computer Interaction
High-fi High Fidelity
ICF Informed consent form
ICT Information and Communication Technology
Low-fi Low fidelity
Nav Navigation
NFC Near Field Communication
QR Quick Response
RPA Referring Phrase analysis
SDGs Sustainable Development Goals
SEQ Single Ease Question
TAP Think-aloud protocol
UE Usability evaluation
UEM Usability evaluation method
UI User interaction
UN United Nations
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1 Introduction
The demand for improved user experience when interacting with computers has
grown and developed into an important multidisciplinary field named Human-
Computer Interaction (HCI). This field consists of material from computer
science, psychology, ergonomics, and many more subject areas [6]. Today
electronic payment systems deployed on electronic wallets (e-wallets) are
becoming more common [46]. In this thesis, we investigate how an e-wallet can
be designed to ensure that the user’s experience will be as pleasing as possible and
will do so by applying HCI best practices and evaluation methods.
1.1 Background
The shift from analogue technology to digital technology, better known as ”The
Digital Revolution” has had an impact on our lives and enabled new possibilities
in different activities of society. One of these activities is electronic purchasing and
the digitization of money 1. This digitization introduces the need for e-wallets as
the next step in the digital revolution, as part of the transformation fromaphysical
wallet or plastic card payments to an all-electronic payment system [43].
An e-wallet is defined as a digital system that enables a user to perform electronic
transactions, including but not limited to, purchasing from (for example a store),
transferring money, receiving money, etc. Not only can monetary value be stored
but there is also the possibility to store ID documents, driver licences, and other
information that would normally be stored as cards in a wallet [26].
There are two important components of an e-wallet: the software and the
information. The information is stored in a database containing names, credit
cards, and payment methods. The software component handles the personal
information of the user and provides security through encryption of data.
Furthermore, it is possible to transfermoney via several techniques, such asQuick
Response (QR codes), Near Field Communication (NFC), Bluetooth, etc [39] [14].
1Throughout this thesis we will use the term money in its broadest sense, i.e., as a record thathas some value that can be used in an exchange
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At the time of writing this thesis, there are some existing e-wallets in the market,
each of which are used (some more frequently than others). This raises the
importance of examining how users use these applications (apps) and whether
these apps are designed in a way that makes it easy for people to interact with
them or not. This is where the field of HCI comes into play.
One aspect of HCI is the usability of a system. Usability refers to the ease of
access or ease of use of a product, and it is the features and context of the use
that determine an app’s level of usability [62].
Centiglobe is a trading company [9] that wants to develop a mobile payment app
(specifically an e-wallet), which enables payment with cryptocurrency as well as
international payments and has tasked us with researching how amobile payment
app can be designed that conforms to HCI practices, specifically usability.
1.2 Problem
As e-wallets are a fairly new invention, there is a lot of research still needed on
the usability (user experience) of these apps. This thesis will investigate how
an e-wallet can be designed to provide a high level of usability by conforming
to best HCI practices (from a usability perspective) as well as try to answer user
experience questions that can occur when designing new and innovative apps that
use unconventional technology. The question we want to answer is:
• How should a mobile payment app be designed in order to improve its
usability, with regards to a set of pre-defined usability criteria?
1.3 Purpose
The purpose of this bachelor’s thesis project is to improve the usability of e-wallets
and ultimately contribute to an improved and optimized user experience when
usingE-wallets. The overall aimof this thesis is to present and discuss the findings
from user testing of a series of prototypes of a mobile payment app.
The aimof the project is to create a prototype of amobile payment app and through
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iterative user testing, improve the prototype from a usability standpoint. The
resulting prototype will be the basis for a finished mobile payment app, to be
developed by Centiglobe.
1.4 Goal
The end goal of the project is to produce a prototype of a mobile payment app
with a design based on HCI principles. This prototype will be evaluated through
usability evaluation. This goal has been divided into the following six sub-goals:
• Gather information about previous usability research related to mobile
payment apps, existingmobile apps, and usability evaluation practices. This
will be done by conducting a literature study.
• Choose an evaluation method for user testing.
• Define measures through which to evaluate the usability of the design.
• Create a series of prototypes of a mobile payment app.
• Conduct iterative user-based usability testing on these prototypes.
• Iteratively improve the prototypes based on the evaluation of the previous
prototypes.
1.5 Benefits, Ethics, and Sustainability
Sustainable development implies the development that meets the needs of the
present without compromising the ability of future generations to meet their
own needs [8]. Three aspects are included: ecological, economic, and social
sustainability. There are a number of Sustainable Development Goals (SDGs),
defined by the United Nations (UN), aiming to increase sustainable development,
globally [38].
The result of this thesis might contribute to the design of mobile payment apps,
from a usability perspective. Hopefully, this improved design will increase the
use of such apps. An increased use of mobile payment apps, has some advantages
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froman ecological standpoint, as its increased usemay lessen the need for physical
cards and wallets (the production of which has an impact on the environment).
The use of mobile payment apps may instead increase the use of electricity,
smartphones, etc. The benefit of this thesis from an ecological standpoint is
dependant on whether or not the reduced use of cards (and paper) make up for
the increased use of electricity and the manufacturing of the e-wallet.
Should the result of this thesis contribute to the increased use of mobile payment
apps, companies developing apps in general, but more specifically companies
developing mobile payment apps could benefit economically. As they could
improve the usability of their product, based on the results of this thesis. An
improvement in the app’s usability could lead to greater customer satisfaction and
result in a larger customer base. This, in turn, can lead to a higher rate of return
and more loyal customers. Providing economic sustainability to the companies.
E-wallets may contribute to both social sustainability and economic sustainability
for society. Because of the high mobile penetration, especially in rural and poorer
areas, a large number of people have the possibility to gain access to mobile
financial services [24, pp. 12-14]which theymaynot have had access to previously,
because of geographical location. Access to financial services contributes to the
reduction of vulnerability to economic, social, and environmental shocks [51].
Thus increasing the resilience of the poor and contributing to the SDG number
1, ”No Poverty”.
Furthermore, increased access to financial services, through mobile payments,
contribute to the development of new business. Targeting SDGs number
eight, ”Decent work and Economic growth”, nine ”Industry, Innovation and
Infrastructure”, and ten ”Reduce inequality within and among countries” [51].
However, there exist some possible downsides with mobile payment. Firstly,
many of themobile apps available rely on an internet connection to function. Only
some types of transactions can be made without an internet connection. Limiting
the use of these apps to people with funds for and access to internet connection
or mobile data. The need for internet also disables the use of these apps during
internet blackouts. However, some developing and existing mobile apps are not
reliant on internet connectivity, as they offer an offline-mode; for example, by
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using tokens that can be used offline, but downloaded online [47, 57]. There
are also a number of security risk with e-wallets. Since phones are vulnerable to
malware and hacking, there exists a risk of sensitive financial information ending
up in the wrong hands, when using mobile payment apps [60].
1.6 Methodology
When conducting a degree project, the choice and use of methods and
methodologies are important. Methods and methodologies are tools through
which to assure the quality of the research. They also help guide the work and
help ensure proper and well founded results. There are a variety of methods and
methodologies from which to choose. The choice of methods and methodology
must match the research actually conducted in order to have any effect on the
work [23]. There are two categories of methods: quantitative and qualitative. A
quantitativemethod aims to prove a phenomenon by objectivemeasurements and
the statistical, mathematical, or numerical analysis of large sets of data [33]. In
contrast, a qualitative method is concerned with gathering non-numerical data
while studying a phenomenon or artefact in order to create theories or products
by examining the environment [23].
Within these categories, there are different research methods from which to
choose. These methods determine how the research process is conducted. A
few examples of methods are empirical research methods and analytical research
methods. Using an analytical research method, pre-planned hypotheses are
tested based on existing knowledge and findings. Using an empirical research
method hypothesis are instead tested based upon experiments, observations, and
experiences [23].
The method used in this degree project will be both quantitative and qualitative.
Some of the data will be quantitative, 5 seconds to do a given task, 4 errors when
doing the task, 3 negative comments etc. Additionally, some of the data will be
qualitative, content of comments from the user. However, as the test group is
small data is not expected to have statistical significance. To test the usability and
gather knowledge regarding the design, tests will be conducted. Since it is through
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testing and observations that data will be gathered, the research method used is
an empirical research method.
To ensure sufficient background knowledge in the area, a literature study will
be conducted. The literature study will explore existing usability research about
mobile payment apps, the design of current mobile payment apps, and HCI
practices. Based on this literature study and grounded theory in usability we will
choose an evaluation method and a set of usability measurements. A prototype of
the app’s design will be created. The design will be evaluated through iterative
testing where tests subjects will comment on the usability of the design and
performance measurements will be measured.
1.7 Stakeholders
The stakeholders for this degree project are first and foremost Centiglobe (the
company that will market, sell, and profit from the end result, a potential design
of an e-wallet mobile app). They will be directly affected by this thesis since the
design of the app candirectly or indirectly potentially affect their profits and future
development.
Furthermore, the finished app could be sold to other companies as a white label
app. Enabling these other companies to adopt the app and adapt it to realize
their own product. The finished app is intended to be used together with other
existing products and companies, such as other mobile payment apps and banks.
These potential customers will be indirectly affected by the design of the app and
therefore the outcome of this project.
Further stakeholders also include potential users of the app. The app’s design is
directly affected by the outcome of this thesis project. The target users for the app
are expected to have all sorts of different backgrounds, ages, and nationalities.
However, the early adopters will most likely be younger, technically skilled
persons.
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1.8 Requirements from Centiglobe
The requirements on the app from Centiglobe is that it has to be suited for
international use, have the ability to perform transactions to other users, (not
limited to users of the same app) and it should support several currencies
(cryptocurrencies as well).
1.9 Delimitations
We will only use a small test group as we do not have access to a large number of
people. Therefore, our results are not statistically reliable and do not necessarily
apply to our demographic of target users outside that of our test group. The
test group used is not an accurate representation of the target users of the final
product. Our results will only be applicable for the test group used. Furthermore,
due to limited resources, the same test group will be used for all iterations.
Because of time constraints we will only test some specific functions and not
present a fully developed app. This means that a high-fidelity (high-fi) prototype
will not be presented. We will only draw conclusions regarding the tested
prototypes.
The usability of the prototypes will only be tested based on a set of pre-defined
measurements hence there could be some aspects of usability that we could not
take into consideration since we had limitations in time and other resources.
Furthermore, the focus of the usability testing is discoveringmajor problems with
the design of the prototype. Therefore, no major effort will be put into finding
minor usability problems with the design.
A widely discussed topic in conjunction with e-wallets is the security level
of the apps. Studies show that users’ experience a lack of privacy and
confidentiality in transaction information and are therefore reluctant to perform
online transactions [54]. However, this is something that will not be discussed
further in our thesis since it is outside of our scope. On the other hand, if the
design or functionality of an e-wallet app can affect the user’s sense of security
this will be highly relevant to discuss.
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1.10 Outline
The following chapter in this thesis contains an in-depth theoretical background
to explain what HCI is and what methods can be used when evaluating apps.
Different e-wallets on the market and what technology and task flows exist will
also be presented. The method and methodology used in our study are presented
in Chapter 3. This chapter covers how the research process and data collection
was performed. The validity and reliability of the method are also discussed. This
is followed by a description of the implementation and results in Chapters 4 and 5
(respectively). Finally, a discussion of our work will be given and conclusions will
be presented in Chapter 6.
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2 Background
In this chapter, we present a detailed description of the background areas relevant
to answering our thesis questions involving HCI theories and practices as well as
describe how e-wallets work and inspect some of the apps currently on themarket.
2.1 Human computer interaction
HCI is the interdisciplinary study of interactions between humans, that is users,
and information technology design [58]. HCI is about designing interfaces in a
human-centredway, taking account of humanabilities andpreferences. It ensures
that systems are accessible, usable, and acceptable [6]. It encompasses several
areas of research, such as computer science, cognitive science, and human factors
engineering [58].
2.1.1 Usability
There are several ways to test if a design is ”good”, from an HCI standpoint. One
such way is testing the usability of the system design. There is not a set definition
of usability. However, the formal definition of usability from the ISO 9241-11
standards is ”The extent to which a product can be used by specified users to
achieve specified goalswith efficiency, effectiveness, and satisfaction in a specified
context of use” [28, p. 6]. A shorter definition is that usability is the quality of
the interactions with a product or system [6, p. 77]. As the definition of usability
can differ so can the parameters that define the usability. Some models include
parameters such as how safe the system is to operate in the context it will be used
[6, p. 81]. Others define the parameters as accessibility, clarity, learnability, and
feedback [12]. In the ISO model, however, the parameters are those ones stated
in the definition of usability, i.e., efficiency, effectiveness, and satisfaction.
In keeping with the definitions of the three parameters as given by ISO 9241-11
[28, pp. 9-12], efficiency is the resources used in relation to the results achieved,
effectiveness is the accuracy and completeness with which users achieve specified
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goals, and satisfaction is the extent to which the user’s physical, cognitive, and
emotional responses that result from the use of a system, product, or service meet
the user’s needs and expectations.
2.1.2 Usability evaluation
When evaluating the usability of a system different usability evaluations methods
(UEM) are used. These can be divided into different categories. Ivory and Herst
(2001) propose the following five classes and definitions [29]:
Analytical modelling
an evaluator employs user and interface models to generate usability
predictions.
Inspection
an evaluator uses a set of criteria of heuristics to identify potential usability
problems in an interface.
Inquiry
users provide feedback on an interface via interviews, surveys, and the like.
Simulation
an evaluator employs user and interface models to mimic a user interacting
with an interface and reports the results of this interaction.
Testing
an evaluator observes users interacting with an interface to determine
usability problems
Depending onwhether user participation is required or whether expert evaluators
are employed, a UEM is either user-based or expert-based. Expert-based UEMs
all include the involvement of an expert in the field of usability or the design of
interactive systems. In contrast, user-based UEMs instead employ a group of
people, preferably representative of the target users, to evaluate usability [34,
p. 256]. UEMs from the analytical, inspection, and simulation class can all be
expert-based. However, testing and inquiryUEMs are dependant on users and are
therefore user-basedmethods [29]. Furthermore, aUEMcanbe either summative
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or formative in nature. Each of these two types of testing is more appropriate
for different stages in a product’s development and purpose of evaluation [34,
p. 260]. Formative evaluation is best suited for the early stages of development.
In this case, testing is a part of the iterative design process, to explore designs that
are or are not usable. Formative testing is exploratory in nature and the focus
is on qualitative feedback and moderator observation. In contrast, summative
evaluation involves measuring the usability of a specific design choice. The focus
is onmetrics and quantitativemeasurements [48]. In short formative testing is for
discoveringwhat needs to be improved, while summative testing exploreswhether
the improvementswere successful. For example, according toMelodyY. Ivory and
Marti A. Hearst are UEMs in the testing, inspection and inquiry are best used for
evaluations that are formative in nature, while analytical and simulation methods
are summative [29].
2.1.3 Analytical modeling
Based on some representation or model of the UI and/or the user, analytical
modelling methods enable an evaluator to predict the usability of the UI, i.e., the
user’s performance when interacting with the UI [30].
One method, classified as analytical modelling, is GOMS analysis. This method
developed by David Kieras is based upon evaluating Goals, Operators, Methods,
and Selection rules [32]. AGOMSmodel specifies a set ofmethods that are used to
accomplish specific goals. Themethods are composed of operators. Operators are
steps that a user performs. Steps that are assigned an execution time. If several
methods can be used to achieve a goal, then selection rules are used to decide on
the correct method. Based on this model predictions of how users will use the
modelled system can be made.
2.1.4 Inspection
Inspection includes evaluation methods where experts examine the usability of
an interface based on a set of guidelines that range from very detailed to broad
descriptions of the guidelines [30]. However, studies show that the inspection
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methods are not always useful due to the fact that designers can be biased
towards aesthetically pleasing interfaces instead ofmeasuring the efficiency of the
design [52]. Examples of inspectionmethods are cognitive walkthrough, heuristic
evaluation, and guideline review.
2.1.5 Simulation
With simulation, it is possible to mimic a user interacting with an interface
with the help of computer programs. The simulations are done in a controlled
environment where the values of parameters can be chosen for each simulation.
This provides the designer with quantitative data which can be easy to interpret.
2.1.6 Inquiry
Methods that are categorized as inquiries include field observations, user
feedback, interviews, and questionnaires. When conducting evaluations using
these methods, the goal is not to test performance but rather collect data on
opinions. These methods are especially relevant in early stages of product
development but also after a product has been released in order to collect feedback
as can be done when conducting for example field observations [30].
2.1.7 Testing
Testing methods are the fundamental way of knowing how humans are going
to interact with a certain interface since participants are those who will test the
product. The participants will use a prototype or a system where the goal is for
them to complete a task given by the tester who will record the results and act on
them.
Testing methods include a think-aloud protocol (TAP) where the participant talks
during testing, performancemeasurement where the tester records the usage data
during the test, and coaching where the participant can ask the tester questions
about the interface.
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When using TAP, for usability evaluation, the comments can be audiotaped and
then transcribed. The transcription can be analyzed in multiple different ways.
One way is analyzing through three progressive steps: referring phrase analysis
(RPA), assertional analysis, and script analysis. In RPA each phrase is coded,
with names of concepts, based on the category of words contained in the phrase.
Concepts are categories based on the meaning of a word. For example, one
concept can be ”value” and refers to all words that are a rating or scaling of
usefulness, importance, or worth [21].
2.1.8 Measurement of usability
When measuring usability through usability evaluation, both performance and
subjective measures can be used. Performance measures are quantitative
measures that are observed. Such measurements can be the time it takes for a
user to learn how to perform a specific function, the rate of errors that occur
during use, the speed of task performance, or the number of observations of
frustration. Subjective measures are instead based on the subjective opinions of
the test subjects. They can be both qualitative and quantitative. This data can
be collected in the form of user comments or a user’s rating on a scale. The data
can be gathered a number of different ways. Some examples are surveys or a test
moderator observing the test subject as the subject performs certain tasks [17,
pp. 184-188].
When evaluating the three parameters for usability, as defined by ISO 9241-
11:2018 [28], some metrics of effectiveness are percentage of goals achieved,
functions learned, and number of errors. Some metrics for efficiency are the time
to complete a task, learning time, and time spent correcting errors. Lastly, some
metrics for the measurement of satisfaction include ratings for satisfaction, ease
of learning, and error handling [30, p. 7].
Measuring satisfaction using the rating of satisfaction can be done through
different types of questionnaires. These questionnaires can be distributed at
the end of a test, measuring the satisfaction of the entire system or they can be
distributed at the end of each task, measuring the satisfaction of that specific task.
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One such post-task questionnaire is Single Ease Question (SEQ). It consists of one
single question that refers to how easy or difficult participants think a task is to
perform. The respondent can rate the difficulty on a scale ranging from one to
seven. Where one is ”Very difficult” and seven corresponds to ”Very easy” [50].
The time it takes before a user gets frustrated is about 1 minute to perform one
task. If a system requires more than one minute to perform a task, it is likely that
the site will be abandoned [44].
According toMeasuringU [35], the average result when testing the difficulty of a
task is between 4.8-5.1 on a 7 level Likert scale.
2.1.9 Prototypes
A prototype of a product is an early sample or model of a product. Prototypes
are created to test a concept or a process [7]. When designing and evaluating
interactive products, prototyping is heavily relied on. Producing a prototype, of a
future product, provides the opportunity to experiment with alternative designs,
fix any problems that might occur, and provide a conceptual idea of the product
that can be used during testing. Since a prototype is relatively easy to change the
design can quickly be adjusted according to the results of testing. Depending on
the level of detail, a prototype has different degrees of fidelity in relation to the
final product [16]. Ranging from a low fidelity (low-fi) prototypes to high fidelity
(high-fi) prototypes.
2.1.10 Design principles, guidelines, and theories
There are several different guidelines andprinciples for the development of “good”
interactive products from a human interaction design standpoint. Some of these
principles are given in Ben Shneiderman’s eight golden rules of interface design.
If a design aligns with these principles, then these are the strengths, while those
that violate it will be the weaknesses. These rules [17] are:
• Strive for consistency,
• Enable frequent users to use shortcuts,
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• Offer informative feedback,
• Design dialogues to yield closure,
• Offer simple error handling,
• Permit easy reversal of actions,
• Support internal locus of control, and
• Reduce short term memory load.
Additionally, there exist several other well known rules of thumb, such as Don
Norman’s six design principles and JakobNielsen’s 10 usability heuristics for user
interface design. For example, Nielsen’s 10 heuristics are defined as [40]:
• Visibility of system status
Give the user appropriate feedback, in reasonable time.
• Match between system and the real world
Use language that user understands instead of system-oriented terms.
• User control and freedom
Support undo and redo, a user should not have to go through several steps
when a mistake has occurred.
• Consistency and standards
Follow conventions, thus do not use ”bye” and ”exit” interchangeably, rather
stick to one of them.
• Error prevention
Try not to put the user in situations prone to error. Present users with a
confirmation option before committing an action.
• Recognition rather than recall
Minimize users’memory load. Make actions visible so the user does not have
to remember them.
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• Flexibility and efficiency of use
Customize the interface for both the novice and the experienced user, for
example with shortcuts or actions that speed up the interaction for expert
users.
• Aesthetic and minimalist design
Do not present irrelevant information since it competes with relevant
information.
• Help user recognize, diagnose, and recover from errors
Use error messages that are easy to understand, and suggests solutions to
the problem.
• Help and documentation
The system should preferably be manageable without documentation but if
this documentation exists, it should be easy to find, be concrete, and not too
large.
Guidelines similar to the ones named above can in broad terms be summarized
as striving for consistency, give the user control, and be aware of a user’s limited
memory.
One way to conform to the principles stated above is to create local rules for each
design. As there exists a lot of guidelines which sometimes can be contradictory
it is very important to specify these rules beforehand.
An example of a local rule would be that all ”back” buttons in an interface have to
be red and with a width of at least 5 percent of the window width.
2.1.11 Task flow
Before developing an app it is important to have a clear mind map of where each
button press, swipe, etc. will take you to ensure that each interaction serves
an important purpose for the user. This can be done by creating task flows. A
task flow is the sequences of steps required to perform a certain task. It is often
represented by a flow chart showing the relations between each step [5]. See the
example in Figure 2.1.
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Figure 2.1: Example of the task flow of buying milk
2.2 E-wallet
E-wallets are a fairly new invention that in recent years have become increasingly
popular as we enter the digitization era, where a transition from physical money
and payments to electronic money and cryptocurrencies is currently taking place.
The markets for these electronic payment methods has a promising future, but
their successes are uncertain due to potential new technological inventions [15].
An e-wallet or digital wallet transforms the way people purchase and pay for
things, by changing the means of payment to be done via apps on mobile phones
[26]. All information that is stored in a wallet is encrypted through the use of
public and private key-pairs to ensure that payments and other data are handled
securely.
There are wallets for conventional currencies as well as for cryptocurrencies (such
as) Bitcoin, which require the same functionality, i.e., the ability to perform
transactions, check balance, etc. As there exist various e-wallets and the goal of
this thesis is to investigate how one can be designed from a usability standpoint,
it is desirable to present and compare e-wallets currently on the market. This
comparison is done in the following subsections.
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2.2.1 E-wallets on the market
It is important to be aware of existing apps, what functions are present, and to
understand their design when developing an e-wallet yourself. The agreements
between the e-wallet app and banks or other involved entities can limit the
user group for the app. Some e-wallets are location specific and cannot be
used overseas due to transactions only being enabled with country specific
requirements and some are only available to users who are customers of a defined
set of banks. Nonetheless, a desire for global use is not unusual.
Some examples of e-wallets are: the Swedishmobile app Swish [55],multinational
Apple Pay [4], EcoCash app for the Zimbabwean market [36], and the Chinese
apps WeChat Pay [61] and Alipay [2].
2.2.2 Transaction and payment methods
There are a few communication styles to choose fromwhen developing an e-wallet
app. The selected communication style refers to the technical functionality that
is chosen when a user of an e-wallet wants to transfer money to another account.
Different wallets have adopted different technical functionality and some of these
will be presented in this subsection.
Swish is a smartphone app consisting of minimal functions that enable receiving
and transferring money through a phone number connected to the bank. Both
users have to have their phone numbers known to Swish through their bank,
then subsequently the bank performs a real-time money transfer between the
associated accounts of these users [56]. When the party sending money has
confirmed the transaction, the money has been transferred. The user also needs
to have an electronic identification app that is only available to Swedish citizens.
Swish was developed for companies. It has the possibility to provide payment
information through aQR code [55] (a two-dimensional black andwhite code that
can be read by machines). A camera app can be used to decode and evaluate the
information encoded in the QR-code as cleartext [45].
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Apple Pay is a bit different from Swish because its main feature is electronic
purchases using any of the Apple products, but it does not supportmoney transfer.
It is currently only possible to transfermoney in the USA through a feature named
Apple Pay Cash. Apple Pay is using wireless payment via NFC.
NFC is an umbrella term for techniques using wireless data transfer for distances
shorter than 10 cm. Smartphones can through peer-to-peer communication
communicate with anything that has an NFC interface, thus they can receive
information from the payment terminal and this information enables purchases.
With the EcoCash app, a user can transfer money, or make deposits and
withdrawals of money [1]. The wallet links a user’s bank account and phone
number. To transfermoney the user needs the receiver’s phone number. EcoCash
is in partnership with Cassava Remit, which together enables money transfers
from the UK to Zimbabwe.
WeChat Pay is a Chinese messaging and social media app with the added
functionality of payment services. The app supports multiple payment methods
including QR code scanning for purchasing and smoother transactions. In-app
payments are also available [37]. In-app payments are payments made from
within the app. With in-app payments, the user can choose the payment method
directly inside the app instead of being redirected to another application or web
page.
Alipay is another popular e-wallet app that serves the Chinese market where
transactions can be made internationally by Chinese customers. Similar to
WeChat Pay, this app supports QR code scanning for local in-store payments [11]
and other services such as bank account management and peer-to-peer transfer
(money transfer without the need of a bank, i.e. money transfer directly between
two users).
2.2.3 Task flow of existing E-wallets
Many of the E-wallets in the market have similar functions. However, the task
flow within these apps differ. A functional requirement for the app to be designed
is, amongst other things, to facilitate international transactions as well as the
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exchange of currency. For this project, the most relevant mobile payment apps to
consider are therefore apps actively used in different countries, apps that facilitate
international payments, and apps that facilitate payment with cryptocurrency.
Appswith different communicationmethods, for example, NFC, QR code, are also
relevant. As noted earlier, the task flow of an app can be presented in the form of
a flow chart. The apps, whose task flow and/or overall design is considered in
this report, are Swish, Paypal, Alipay, WeChat, and Cassava Remit. The flowchart
for Swish and Paypal are presented in Appendix A. The flowchart for Paypal is
also presented in Figure 2.2. These five apps represent a small percentage of
the mobile payment apps available, namely less than 2 percent. At least 100 e-
wallet existed 2016 according to the list made by [59], and [19] listed the 70 best
cryptocurrency wallets of 2019 together being at least 200 e-wallets. However,
there is a possibility that even more exists. In Figure 2.2 is the task flow of Paypal
shown.
2.3 Related Work
This section present previous research done on the subject of e-wallets designed
for usability.
2.3.1 User experience of Bitcoin wallets of usability and security
In Abdulla Alshamisi and Peter Andras paper ”User perception of Bitcoin
usability and security across novice users” [3], they examine how digital
payment systems with cryptocurrencies (such as Bitcoin) influence new users in
comparison to credit card payments. They used surveys to collect data about
users’ perception and concluded that the users responded more positively to
conventional credit card payments which influenced their negative perception of
e-wallet security. Ultimately they say that a deeper understanding and education
about digital payment systems is needed together with improved user-centred
designs in order to elevate each user’s experience and thus increase acceptance.
Alshamisi and Andras tested and compared the usability of payment systems with
cryptocurrencies and credit card payment using subjective measures. Their test
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subjects completed a survey, responding to statements regarding usability. The
respondents could grade what level they agreed with each statement, through a
Likert scale.
2.3.2 Designing mobile wallets
Mia Olsen, Jonas Hedman, and Ravi Vatrapu have in their paper ”Designing
digital payment artefacts” [42] describe their scientific inquiry of a mobile wallet.
Four different user groups were identified, and then they developed and evaluated
mobile wallets from the perspective of its design. They presented sketches
and low-fi prototypes to user groups who were interviewed in order to collect
data. They concluded that there are two types of properties that are relevant
when designing a mobile wallet: (1) the functional properties and (2) the design
properties and that evaluation criteria needed to be expanded in order to take
everyday life contexts into consideration.
2.3.3 User experience of a mobile app
Fanny Chan and Sofia Johansson have in their bachelor’s thesis ”Evaluation
of user experience on a mobile application” [10] investigated if there could be
any design improvements in Shownight’s mobile app in order to increase the
quality of the user’s experience. The evaluation method they used consisted of a
combination of interviewswith the user group andmaking performancemeasures
in order to collect data. They were able to suggest improvements in the design but
left it as future work to redesign the app.
2.3.4 Acceptance of mobile wallets in Oman
Sujeet Kumar Sharma, Sachin Kumar Mangla, Sunil Luthra, and Zahran Al-Salti
in their article ”Mobile wallet inhibitors: Developing a comprehensive theory
using an integrated model” [53] reflect on what is hindering the acceptance
of mobile wallets in Oman as mobile wallets are increasingly accepted in both
developing countries and developed ones. They developed a hierarchical model
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and concluded from it that anxiety and lack of understanding of new technology
are some of the key reasons why the promotion of the use of mobile wallets in
Oman is difficult.
2.4 Summary
This chapter has presented several HCI practices, guidelines, and models.
Usability is one of theHCI practices that ismost significant in our thesis. The three
parameters defining usability and different types of usability testing methods
(user-based, expert-based, and automated testing) were introduced. An overview
of various e-wallet apps on themarket and their task flow and transactionmethods
were also presented.
Today it is common to investigate how usability and security of the mobile wallets
affect the acceptance of apps and how amobile wallet can be designed tomaximize
its acceptance by users. The next chapter will present details of the method used
in this thesis.
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Figure 2.2: Task flow of Paypal
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3 Method
The purpose of this chapter is to provide an overview of the researchmethod used
in this thesis. Section 3.1 describes the research process. Section 3.2 details the
research paradigm. Section 3.3 focuses on the data collection techniques used
for this research. Section 3.4 describes the experimental design. Section 3.5
explains the techniques used to evaluate the reliability and validity of the data
collected. Section 3.6 describes themethod used for data analysis. Finally, Section
3.7 describes the evaluation framework used.
3.1 Research process
This subsection lists the steps conducted in order to carry out this research.
1. Literature study
At first, a literature study was made in order to gather information about
HCI practices, usability, evaluation methods and to get an overview of the
functionality of e-wallets. This was done in order to accurately determine
suitable evaluation metrics and methods. The choice of sources were
mainly books on the subject as well as relevant papers in databases such as
ScienceDirect and Scopus. The search words among others were: mobile
wallets + usability, e-wallets + usability, HCI + mobile wallets, HCI +
mobile payment. A lot of information was also found on the internet where
HCI communities and interaction design foundations share their knowledge
and experiences. The credibility of these sources was checked through a
comparison of other material and inspected to see if there were any biased
or outdated information on the sites. The primary results of the literature
study are presented in Chapter 2.
2. Determine functionality
Secondly, a decision on the required functionality of the appwasmade. A list
of functions was produced together with Centiglobe. These functions were
the foundation of the prototype.
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3. Select usability evaluation parameters
In order to evaluate the usability of these functions, evaluation parameters
were selected. The selected parameters were the ISO 9241-11:2018 standard
parameters for usability: Efficiency, Effectiveness, and Satisfaction.
4. Create a prototype
A prototype had to be created based on Schneiderman’s eight golden rules
[17], Nielsen’s 10 heuristics [40], and from the app comparisons in the
literature study. The prototypes are presented in Appendix E.
5. Define a test group
Thereafter, a test group was constructed. The test group needed to be as
diverse as possible. The selection of this group is described in Section 3.3.1.
6. Choose evaluation methods
After the test group was constructed, the usability of the prototype was
evaluated through user-based evaluation. The UEMs that were used are
classified as a testing and inquiry UEMs (according to the classification by
Ivory and Hearst [30]). The methods we chose were TAP (testing method)
and a combination of performance measurement (testing method) and
questionnaire (inquiry). The questionnaire was used to collect performance
data regarding user satisfaction. We observed the test subjects performing
each task, having them comment during testing and measured a set of
measurements. For example, the time to perform a task. At the end
of each test, the subjects rated their satisfaction of the interaction with
the prototype. The test subjects were provided with a question regarding
the ease of performing the task and rated the ease of performance (on a
7 level Likert scale). Therefore, we gathered both subjective (TAP and
questionnaire) and objective (performance measurement) data. Since the
purpose of the usability evaluation was to develop a design of a mobile
payment app, the evaluation method was formative.
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7. Design experiments
Based on the methods and test groups chosen we designed the experiments.
These experiments were conducted four times during individual meetings
with the test subjects in a quiet setting. Details of the experiment are given
in Section 3.4.
8. Capture data
To capture data, participants expressions and comments were audiotaped
with mobile phones as well as noted on paper. Performance data such
as time was timed and noted on paper. The user interactions with the
prototype as well as errors made were recorded using screen recording. The
questionnaire was filled out online by the participant using Google forms.
9. Analyze and interpret data
The data from testing were both quantitative and qualitative. Qualitative
data (such as the content of comments and expressions from the TAP and
the types of errorsmade) weremore difficult to analyse than the quantitative
data. The data from the TAP was analyzed through a simplified version of
RPA. The number of negative, neutral, and positive commentswere counted.
The median value of the performance measurements was calculated. The
quantitative data was only used to measure the level of usability of the task
while the qualitative data was used to find areas of improvement.
10. Critique UI to suggest improvements
After the data was analyzed, suggested improvements were based on the
qualitative data as well as the quantitative data.
11. Iterate process
The process of designing and evaluating the prototype was iterated in order
to improve its usability. For each iteration, data was captured, analyzed
and new suggested improvements were decided and implemented in the
prototype. This iterative process made it possible to find new faults with
the design and remove them.
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3.2 Research paradigm
We are collecting data to describe the experience of using the prototype for a
certain number of people. We are also basing our conclusion on observing what
is happening in the world. We are therefore assuming that there exists some
experience that can be observed or tested empirically. Hence we are taking a
positive stance towards this phenomenon. The research paradigm that this work
adheres to is subsequently positivism.
3.3 Data collection
Data was collected during tests by several different means. The TAP data, i.e.
the verbal data, was collected through audiotape that was later transcribed.
Performance measurements data was collected using a stopwatch on a mobile
phone, to time the activity, and notes on paper. Performance data was also
recorded by screen recording. The responses to the SEQ were collected online
using Google forms.
No personal information was recorded or collected during the tests. The only
information that can be regarded as sensitive, that was collected, were the
comments expressed during the TAP. However, these cannot be tied to any one
person, since no names were recorded and therefore can’t be linked to them. The
testing process presented no risks to the participants.
3.3.1 Test group
The test group used during the user-based usability evaluation was limited to
7 people. This number of people was considered adequate since the research
performedwasmainly qualitative, to provide insight into the design, togetherwith
the fact that most usability problems can be discovered with a test group of five
people [41]. Furthermore, because of limitations in resources, the same test group
was used for all iterations. Since the target users are not limited to any specific
group it was important to construct a diverse group. However, we had limited
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resources when choosing test subjects. Because of this, the difference in the test
subjects’ characteristics was limited to:
• Experience using mobile payment apps.
• Experience of software development.
We chose ”experience using mobile payment apps” as one characteristic because
it could affect how the user interacts and experience the prototype. A user with
experience using mobile payment apps is used to performing similar actions that
were performed during testing. This could affect the speed of performance as
well as the number of errors they make. Furthermore, can they be more critical
as they can compare the prototype to other mobile payment apps. A user’s
experience of software development can possibly also affect how they experience
and interact with the prototype. A software developer may view the prototype
from a different perspective and be more technically skilled. The test subjects
rated their experience usingmobile payment apps and their experience of software
development on a 5 level Likert scale, respectively. Level 1 being ”no experience”
and level 5 being ”extensive experience”.
The language that was used for the instructions and the ICF for the participants
were in English, but any verbal interaction was done in Swedish. The language
used in the app prototype is in English.
3.3.2 Consent form
The ICF was designed by us, but it was partly based on a sample ICF provided
by the World Health Organisation [63]. Our goal was to obtain informed consent
from our test subjects. Therefore we designed a comprehensive consent form,
providing the test subjects with information about what the tests entailed. As
advised by Joseph S. Dumas and Janice C. Redish [17], in our ICF we explained
the procedure that we would follow, the purpose of the test, any risks to the
participants, the opportunity to ask questions, and the opportunity to withdraw
at any time. Furthermore, we made sure that the participants comprehended the
information by using clear language. The test subjects were not offered anything
in exchange for participating. All test subjects had reached the age of majority,
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i.e., 18 years old, in Sweden and were clear of mind.
The ICF is presented in Appendix B.
3.3.3 Sampling
As the test group was limited in size, all data collected from the TAP testing as
well as data from the performance measurements was needed when iterating and
improving the prototype. Therefore, no sampling was done.
3.3.4 Sample size
The size of the test group, responses during TAP, responses to the questionnaire
and the performance measurements taken determined the sample size. The
number of performance measurements and responses to the questionnaire were
static in size. However, as we used TAP as one testing method, the total sample
size varied with each iteration of testing and for each participant. Because the
number of comments and thoughts expressed varied for each iteration and for
each participant.
3.3.5 Target population
Since themain functionality of the app is the transaction ofmoney, a functionality
not limited to any specific group, and the app is intended for international use,
the target population was not limited. However, to what extent the app will be
adopted is expected to vary across groups. For example, early adopters will most
likely be younger, tech-savvy users. Furthermore, the app is limited to owners of
smartphones. The app will also require access to a bank account of some sort,
this will affect the minimum age of the users, as many banks have a minimum age
limit. There is no age limit to owning cryptocurrency. However, there is often an
age limit of 18 when selling and buying on trade sites [13].
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3.4 Experimental design/planned measurements
The subjects were scheduled for individual meetings in a quiet setting. To
facilitate using TAP. The sessions were audiotaped and then transcribed. After
subjects signed an informed consent form (ICF), described in Section 3.3.2, they
were randomly given an instruction and scenario card (with limited instruction
regarding what task to perform and the goal to achieve). Furthermore, the test
subjects were informed that performance measurements were to be performed
and that they were encouraged to constantly talk and think aloud as they
performed the task. If the test subjects were quiet for more than a few seconds
we gently reminded them to ”keep thinking out loud”. The test subjects then tried
to perform the specific task on the interactive prototype that was displayed on a
smartphone. At the end of each task, each test subject answered the questionnaire
concerning the specific task. During the test, performance measurements were
also measured and notes were taken. The interactions between us, as observers,
were limited during the performance of tasks. Only if a reminder, to keep thinking
aloud, was needed did we intervene.
We evaluated the usability of the prototype according to the ISO 9241-11:2018
definition of usability. Each parameter (efficiency, effectiveness, and satisfaction)
was evaluated using both TAP and performance measurements in combination
with the SEQ.
3.4.1 Performance measurement
The performance measurements we chose for each parameter can be found in
Table 3.1.
Table 3.1: The performance measurements.
Performance measurements
Efficiency Effectiveness Satisfaction
Time to complete a task Percentage of errors Questionnaire
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The efficiency was measured through the time to complete a task which is defined
as:
Tasktime = Endtime− Starttime (1)
The time was measured with a stopwatch on a mobile phone. When we asked
the participant to start, the stopwatch was started, and when the participant was
finished with the task and stopped interacting with the prototype the watch was
stopped.
The percentage of errors the participant makes when performing a task is the
chosen effectivenessmeasure. Errors are defined as slips, mistakes or unintended
actions. The screen and the user’s interaction, during the interaction with the
prototype, was recorded. Based on this recording the number of errors and
the total amount of interaction the user had with the prototype were noted.
Interaction is in this case defined as any interaction with the touch screen such as
press, swipe, etc. To calculate the percentage of interactions that were mistakes,
for each task, the following formula was used:
Number of errors
Total number of interactions(2)
The satisfaction of each task was measured through an SEQ. After each task, the
subjects were given the questionnaire. In the questionnaire, the test subjects rated
how difficult a task was to perform on a 7 level Likert scale. The single question
questionnaire, the SEQ, is presented in Figure 3.1 below.
Figure 3.1: SEQ
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3.4.2 Thinking-aloud protocol
The comments made during the usability evaluation were, as stated above,
audiotaped and then transcribed. Then sections of the transcript that were
identified as not reflecting verbal thoughts, such as when subjects were given or
reading task instructions, and filler words, such as ”um”, ”ah” etc, were eliminated
from the transcript. The transcript was then analyzed using a simpler version
of RPA. A set of concepts (categories of ideas) were defined based on the verbal
data. The phrases were concept coded based on the category of the idea a phrase
expressed. The concept codedphraseswere then categorized into these categories:
negative, positive, and neutral, based on whether the phrase expressed a positive,
negative, or neutral idea.
3.4.3 Test environment
Each participant decided the place to conduct the testing, meaning that the testing
environment was not the same for each participant. The only demand on our side
was that the environment had to be quiet so it would be easier to focus and not
being disturbed by otherswhen doing the testing. We chose a group roomat either
the Royal Institute of Technology in Kista or Campus if a participant wanted us to
decide where the testing should take place.
The rooms had to have at least one chair for the participant and a table where a
laptop for the questionnaire was placed along with the prototype. The prototype
was developed with the software ”Figma” displayed on a Huawei P20 (further
explained in Section 3.4.4). Other materials that were needed were pens, a
notebook, a laptop for taking notes and a mobile phone with a voice recorder and
a stopwatch. To record the screen during testing software available on theHuawei
P20 was used.
3.4.4 Software and Hardware to be used
The software used for prototyping was ”Figma”. Figma is a freemium, browser-
based interface design application. Among other things, a feature of Figma is
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making designs interactive. Meaning that the design can mimic the functions of
a real application and respond to the user’s interactions. For example, pushing a
button, in the design, can prompt a new view to appear or one can scroll on a page.
In presentation mode, only the interface is shown.
Furthermore, will the Figma mirror app be used to present the app on the phone.
With presentation mode the prototype can be viewed on a smartphone taking up
the whole screen of the phone, mimicking a real application [20].
The smartphonemodel used to display the prototype wasHuawei P20. The phone
had a screen size of 5,8 inches (measured diagonally) [27]. Making it a good
representation of the average smartphone. Themost popular smartphone’s screen
size varying between 4,7 to 6,5 inches [31].
The software used for recording the screen and users interaction was a built-
in screen recorder found on the Huawei P20. The software used for the
questionnaire was Google forms. The software used to calculate the median value
of the performance measurements was excel.
3.5 Assessing reliability and validity of the method and datacollected
The reliability (Section 3.5.1) and validity (Section 3.5.2) of our results will be
discussed down below as well as the reliability of the chosen method.
3.5.1 Reliability
In order to get reliable data from the TAP, we chose to audiotape the conversation
tominimize the disturbance to be able to transcribe when the testing was finished,
which otherwise can affect the results.
Furthermore, to get reliable results it is important that the analysis of the
transcription is done consistently. Same expressions should have the same value
for each participant and iteration. When analyzing the transcription it is necessary
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to be unbiased and that we do not draw conclusions in order to accept a certain
hypothesis [22].
The methods we have chosen, such as for example the TAP, are well known
and scientifically used in the field of HCI and in usability testing. According to
Hertzum and Jacobsen [25] some UEM’s as TAP can suffer from ”The Evaluator
Effect” which means that novice and expert evaluators that evaluate the same
system with the same marked problems come up with different issues with the
design. They concluded in their report that it is not recommended to use only one
evaluator as a reliable conclusion cannot be made due to this effect. As we used
several test subjects or evaluators of our prototype we say that it is reliable.
3.5.2 Validity
In order to get valid results from the TAP, it is important to not disturb or affect the
participants when talking and to not behave in a way that makes them say things
that they do not agree with. The only time the observer should intervene is when
the participants stay quiet and that is through saying ”keep talking” which does
not disrupt their thought process. Disrupting the thought process is something
that affects the validity of the results [18, 22].
Furthermore, the only opinions and expressions we can record are the ones
the participant verbally expressed through the TAP. Meaning that all views and
opinions of the participant that have not been shared will be unknown to us.
The sample size (number of participants) can affect the validity of the results. We
chose 7 which is argued for in Section 3.3.1 to why it is enough in our case.
3.6 Planned Data Analysis
As mentioned earlier we chose to analyze the data received from the TAP through
a simplified version of RPA.
The verbal data collected during TAPwas foremost used to find usability problems
and areas of improvement of the design for each task. Furthermore, the number
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of negative, neutral and positive comments was used to evaluate the prototype’s
usability.
Based on the screen recording the number of errors during the interaction could
be calculated and described. Furthermore, could the total number of interactions
be calculated. The percentage of errors could then be derived from the number of
errors and the total number of interactions. Themedianwas used to get an average
value for each performance measurement (time for performing a task, percentage
of errors, and rating of satisfaction) for each task. We chose the median value,
because of the small size of the test group. The arithmetic mean tends to be less
accurate for small sample sizes because of a few outliers and the geometric mean
cannot handle negative or zero values. [49].
The mean values of the performance measurements were used to check if an
improvement, of the usability, had beenmade between each iteration and if the set
performance goal had been reached. More specifically if the design had improved
in regards to and fulfilled the set performance goals for efficiency, effectiveness
and satisfaction of the interaction with the prototype.
3.7 Evaluation framework
The following subsections describe how we chose to collect and evaluate the data
from our testing.
3.7.1 Collection of data
As presented in Section 3.4, during the tests, we timed how long it took for each
participant to perform each task as well as record the screen to later count the
number of errors a user made and the total number of interactions for each
task. The percentage of interactions that were errors was then calculated. The
participants also rated their satisfaction of the interaction with the prototype. We
then calculated themedian value of themeasurements for each task. When timing
the user performing a task, the start timewas considered themoment the user was
told, by us, to start. The phone, on which the prototype was presented, was lying
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screen down on a surface in front of the user. When the user was told to start
performing the task, the user could pick up the phone and start performing the
task. The time it took the user to read the task instruction cards was not included,
only the time the user interacted with the prototype was included. The user was
instructed, beforehand, to put the phone down on the surface in front of them
when they considered that they had finished the task. The moment the user put
down the phone on the surface was regarded as endtime.
The errors a usermade during the performance of a taskwas counted. The number
of interactions the user performed on the device was also counted in order to
calculate the percentage of errors the user did. Interaction is defined as any press
or swipe on the touch screen. Some examples of what was considered errors were:
• Clicking on a wrong button
• Performing a wrong action
• Clicking on something that isn’t clickable
• Typing in a value in the wrong field
The verbal data collected during TAP was analysed using RPA, as stated above.
The number of negative, neutral, and positive comments expressed for each task
was counted.
3.7.2 Evaluation of data
The mean values of the performance measurements were compared to the values
from the previous iteration. Had the values improved, it was assumed that the
respective usability parameter had improved for the specific task. A decrease
in the percentage of errors, time to complete a task and an increase in rating
of satisfaction is considered an improvement of the efficiency, effectiveness, and
satisfaction of the prototype respectively.
If the mean value for every performance measurement (time to perform a task,
number of errors, and rating of satisfaction) had reached the set performance
goals the task was considered to have a satisfactory level of usability in regards
to performance measurements. If the number of positive comments, in the
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verbal data, was above the defined goal limit the task was considered to have
a satisfactory level of usability based on user’s comments. If the level of
usability of the task was considered satisfactory based on both the performance
measurements and the verbal data the overall level of usability was considered
satisfactory and testing on that specific task was considered finished. We chose
this definition of done since there exists, in principle, no limit to how good the
usability of a design can become and since we were limited in time, we chose that
the testing of that task was then to be considered complete.
The qualitative data (the content of the comments and description of errors)
was used to find areas of improvement and was used during the design of the
next iteration of the prototype. The qualitative data was therefore not used to
evaluate the level of usability of the task. Only the quantitative data (performance
measurements and the number of comments) was used as a basis for the level of
usability of the task.
The set performance goals are seen in Table 3.2:
The set goals for comments for each usability parameter was that the number of
positive comments was above 50%. Meaning that the number of comments that
were categorised as positive for each category of usability parameter was to be
either half or more of the number of total comments in regards to that usability
parameter.
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Table3.2:
Theperform
ance
goals.
Usability
parameter
Measurement
Goalmetric
Unit
Motivation
Efficiency
Tim
eto
complete
atask
1min
time
Userwillgetfrustratedafterthis
time
Effectiveness
Numberoferrors
5%
percentage
Userwillgetfrustratedby
alarge
amou
ntof
errors.Errorsaddon
theperform
ance
time.
Satisfaction
User’sratingof
ease
ofuse
5Likertscaleof1-7
Aratinghigher
than
5isarating
aboveaverage.
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4 The Work
This chapter presents the work process of creating, developing and improving the
prototype for each test iteration.
4.1 Tasks to be analyzed
The tasks chosen for testing were the following:
Pay via QR
Transfer money through the input of payment information via QR.
Pay via manual input
Transfer money through manual input of payment information.
Charge
Increase the balance of existing currencies in the wallet.
Exchange
Exchange currency.
These tasks were chosen because they test the most vital functions of the app.
These tasks were also the most complicated and had the greatest potential for
improvement.
To describe to the user what task should be performed and what goal they tried to
achieve instruction and scenario cards were created and presented to the users on
paper. The instruction and scenario cards presented to the users for each task
are presented in Appendix C. The task was, as stated previously, given to test
subjects in random order. This to prevent that the learning effects of performing
one task would influence the result of the remaining tasks. As the design of the
prototype changed, the task instructions were slightly modified to conform to the
new design.
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4.2 Test group
The test group and their characteristics are compiled in Table 4.1 shown down
below. Each test subject was given a number to represent them as seen in the
first column of Table 4.1. The second column shows their perceived experience of
mobile payment apps, and the third column shows their perceived experience of
software development based on a rating from a five-level Likert scale.
With regards to experience, the Likert scale ranges from 1: Strongly disagree, 2:
Disagree, 3: Neither agree or disagree, 4: Agree and 5: Strongly agree, on the level
of agreement of the two statements (1) You have experience with using mobile
payment applications and (2) You have experience in software development.
The Likert scale ranges from 1: No experience, 2: Little experience, 3: Some
experience, 4: A lot of experience and 5: Extensive experience.
Table 4.1: The test subjects and their perceived experience using mobile paymentapps and experience of software development.
Test subject Mobile payment apps Software development
1 4 5
2 2 4
3 4 3
4 3 4
5 3 4
6 5 1
7 2 5
Furthermore, three of the test subjects used smartphones with an Android
operating system and the other four test subjects used smartphones with an IOS
operating system.
4.3 Testing
The prototype was based on the given requirements from Centiglobe. All
prototypes are presented in Appendix E. Before the test subjects started
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interacting with the prototype and after they had read the task instructions they
were asked if they needed any clarification. It was noted that the concept of the
app was quite difficult to understand for the test subjects based on only the task
instructions.
4.4 Data collection and analysis
As stated previously the concepts used for the RPA was defined after the
transcription of the verbal data collected from iteration 1. The concepts used for
concept coding the verbal data, gathered from the TAP were the following:
Instruction
Repeating of instructions given, e.g ”I am to input text”
Error
Expression of an error made, e.g ”This was wrong”
Interpretation
Interpretation of view, e.g ”If I click on the red button I will navigate to view
B”
Value
Expression of a value, e.g ”fast”, ”slow”, ”smooth”, ”effective”, ”strange” etc.
Misinterpretation
Expression ofmisinterpretation, e.g ”The red button did not navigate to view
B”
Ambiguousness
Expression of ambiguousness or uncertainty, e.g ”I think this is correct”, ”I
am not sure this is right” etc.
Observation
Expression of observation of screen, e.g ”A number popped up on the screen”
Question
Gathering of information or expression of lack of understanding, e.g ”Huh?”
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Success
Expression of successful or correct interaction, e.g ”Yes, that was right”
Exploration
Expression of exploring, e.g ”I will try to push button A”
Action
Expression of performing an action, e.g ”I am pressing button A”
Furthermore, the comments were categorised into neutral, positive, and negative.
Phrases coded as questions, ambiguousness, errors, and misinterpretation were
categorised as negative since they expressed fault with the design. Phrases coded
as values could be categories as either negative or positive based on whether the
phrase expressed a positive or negative value. For example, a phrase containing
the value ”too fast” or ”bad” was considered negative, while a phrase containing
the value ”great” was considered a positive one. Phrases coded with success
were categorised as positive. Every phrase coded with solely instruction, action,
interpretation, exploration, and observation were categorised as neutral. Phrases
that could be categorised as both negative and positive were categorised as such.
During testing iteration 1, we discovered that the test subjects often wanted to
give further opinions about what could be improved after the testing of a task was
finished. We found that this was a very effective way of getting more information
about why certain errors weremade and what a good improvement would be. The
post-test comments were not used as a result of testing, but we did consider them
when improving the prototype. During the rest of our testing, we started asking
the test subjects if they had any post-test comments they wanted to share with us.
4.5 The prototype
The prototypes were developed in consultation with the product owner. Design
choices made during the development of all prototypes were based on personal
experience and opinions as well as HCI best practices such as Schneiderman’s
eight golden rules and Nielsen’s 10 heuristics.
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5 Result and Analysis
In this chapter, the results of the usability evaluation are presented and discussed.
In Sections 5.1 - 5.3 the results are presented. In Section 5.5 a reliability analysis
is performed. A validity analysis is performed in Section 5.6. Lastly, in Section 5.7
the results are discussed.
5.1 Results iteration 1
7 participants participated in iteration 1. Themajor problems thatwere discovered
based on the data collected during iteration 1, were:
Icons
The meaning of the icons was unclear for some test subjects. They were
tightly placed which made it more difficult to distinguish them.
Titles
Some views were missing explanatory titles which lead to uncertainty
amongst users.
Task instructions
As the idea of the app was very difficult to grasp, the task instructions were
not detailed enough. Task instructions can be found in Appendix C.
Action order
In some tasks, the form filling had to be executed in an order which made
users confused.
Navigation
The test subjects had difficulty to find and use the navigation bar.
End of task
The test subjects were not sure if and when they had finished a task. There
was no feedback.
All of these above have to be changed before proceeding with Iteration 2.
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The median values of the performance data gathered during iteration 1 of testing
were the following:
As shown in Table 5.1, only two performance goals were met for only one task.
The median value of the rating of satisfaction for the task exchangewas above the
set performance goal of 5. The median value of task time for the task exchange
was below the set maximum of 60 seconds. The task Pay via manual input stood
out as the task with the worst results with regards to performance measurements.
The largest problem test subjects had with performing the task was navigating to
the correct view. However, the percentage of negative comments for all tasks met
the goal of being below 50%.
Table 5.1: Median value of performance measurements iteration 1
Task Time Error Satisfaction Negative comments
Pay via QR 109,70s 72% 4 31%
Pay via manual input 167,54s 55% 2 30%
Charge 84,79s 50% 4 17%
Exchange 55,79s 54% 5 32%
An excerpt of the concept coded verbal data is presented in Appendix D.
5.1.1 Changes after iteration 1
Icons were changed, based on post-test comments from the test subjects. For
example, was the icon for Charge changed from an inbox icon to a plus icon,
this change can be seen in Figure 5.1. Titles were added to all views. The task
instructions were changed to give test users a better understanding of the function
of the app. Instead of having a bottom navigation (nav) bar we changed the
prototype to have a top nav bar containing a hamburger menu, QR icon, and back
button. In the menu, all alternatives were described with names instead of icons,
see Figure 5.1. Lastly, we added a confirmation message that popped up when
users were finished with a task.
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(a) Iteration 1 (b) Iteration 2 (c) Iteration 2 Menu
Figure 5.1: Example of changes made to the prototype between iteration 1 anditeration 2
5.2 Results iteration 2
7 participants participated in iteration 2. The major problems that were
discovered based on the data collected during iteration 2, were:
Cluttered views
Some views were very cluttered, containing a lot of text and information.
Input fields were ambiguous
Test subjects found it difficult to discern titles and descriptions from input
fields. Particularly pointing out underlined titles as confusing.
QR icon
Test subjects had problems finding the icon for scanning a QR code.
Pay icon
The meaning of the manual pay icon was unclear for some test subjects.
Understated titles
Many test subjects did not read the title of the view, i.e ”Charge”, ”Exchange”,
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etc.
Wording
Some wording was confusing and unclear for test subjects
Menu button
Many test subjects ignored or did not see the menu button.
All of these above have to be changed before proceeding with Iteration 3.
As seen in Table 5.2 all tasks had a median satisfaction rating above the set goal
of 5. Furthermore was the median value of task time for tasks exchange and
charge below the maximum of 60 seconds. Pay via manual input and Pay via
QR code had the worst results, with regards to all performance measurements
and the verbal data. This result is not surprising as these functions are the most
complex. However, all results were improved.
Table 5.2: Median value of performance measurements iteration 2
Task Time Error Satisfaction Negative comments
Pay via QR 81,29s 44% 5 14%
Pay via manual input 84,6s 38% 6 0%
Charge 37,05s 25% 6 8%
Exchange 54,9s 27% 6 0%
5.2.1 Changes after iteration 2
When developing prototype 3, i.e., the prototype used for testing iteration 3, the
product owner wanted major changes to the functions of the app. Meaning that
some functions were altered. The major changes that were made were that an
additional option of payout method was added to the pay view and an additional
option of transfer method was added to the charge view. Furthermore, some
wording was adjusted. Because of the changes made to the prototype the task
instructions given to the test subjects had to be altered.
Based on the results of iteration 2 the QR icon was made bigger and was put in
the centre of the top nav bar for better visibility. We also added a coloured box for
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encapsulation around the input fields in order to make the user understand what
input fields that were grouped together. This change is found in Figure 5.2.
The product owner wanted to merge some functions to a single view which was
done per request.
(a) Iteration 2 (b) Iteration 3
Figure 5.2: Example of changes made on the prototype between iteration 2 anditeration 3
5.3 Results iteration 3
7 participants participated in iteration 3. The major problems that were
discovered based on the data collected during iteration 3, were:
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Menu button
Test subjects still ignored or did not see the menu button.
Overload of information/ cluttered view
Test subjects found some views to be cluttered and that there was a lot of
information displayed.
All of these above have to be changed, if possible, before proceeding with Iteration
3.
As seen in Table 5.3 the results for task Charge worsened. Some results for
the task Pay via manual input also worsened. This is most likely due to the
functional changes implemented on the request of the product owner. These
changes made the functions more complex. The results for the tasks that were
not changed, Exchange and Pay via QR, improved, however. Task Pay via QR
met all performance goals.
Table 5.3: Median value of performance measurements iteration 3
Task Time Error Satisfaction Negative comments
Pay via QR 27,72s 0% 7 0%
Pay via manual input 77,13s 29% 6 10%
Charge 47,62s 40% 5 15%
Exchange 38,62s 27% 7 0%
5.3.1 Changes after iterations 3
We decided to change the visibility of the menu button since it was obvious from
the testing that some had trouble noticing the button. To make it more visible
contrasting colours were added instead of having a black and white icon and
background. This change can be seen in Figure 5.3.
Furthermore, tomake it easier for the eye to read information andmake the design
more minimalist we decided to change the input fields from having a bubble form
to an underlined text instead. This change can be seen in Figure 5.3. Furthermore,
was the design of the menu changed.
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(a) Iteration 3 (b) Iteration 4
Figure 5.3: Example of changes made on the prototype between iteration 3 anditeration 4
5.4 Results iteration 4
7 participants participated in iteration 4. The major problems that were
discovered based on the data collected during iteration 3, were:
Wording
Some test subjects found Transfer to be a better name for the function Pay
via manual input instead of Pay
As seen in Table 5.4 the performance goals regarding time, negative comments
and ratings of satisfaction were all met. However, no task reached a percentage
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of error below 5%. Based on the results, the most complex tasks for this iteration
are Pay via manual input and Exchange. There is a noticeable improvement of
the percentage of errors for the task Charge which dropped from 40% to 9% in
comparison with iteration 3, however, it is still not fulfilling the performance goal.
Table 5.4: Median value of performance measurements iteration 4
Task Time Error Satisfaction Negative comments
Pay via QR 21,90s 17% 7 0%
Pay via manual input 49,80s 33% 6 8%
Charge 48,42s 9% 7 0%
Exchange 30,32s 33% 7 7%
After the last iteration, for all tasks, all goals were met bar one. The results for all
tasks met the goals of task time, rating of satisfaction and percentage of negative
comments. However, no task had a result of a percentage of errors below the goal
of 5%. Furthermore, was the result of task time for all task quite a lot below the
goal of 60 seconds.
5.5 Reliability Analysis
Since we used the same test subjects for each iteration of testing the test subjects
became familiar with the prototype. This can affect the results since task time and
percentage of errors is expected to decrease as the test subjects are familiarised
with the design. However, the prototypes were majorly altered between each
iteration, lessening the learning effects.
After the first round of testing, we realised that the questionnaire used for
measuring satisfaction wasmisinterpreted by the test subjects. Some interpreting
the rating of 7 meaning that the prototype was difficult to use, while it was, in fact,
the other way around. After realising this, we instead asked the test subjects about
their rating, and ourselves wrote in the rating into the questionnaire.
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5.6 Validity Analysis
Since we interpreted the data from the TAP, there is a possibility that the users’
phrases and expressions are incorrectly categorized. For example, a positive
comment could be interpreted as negative. As we do not have a large sample size
this could negatively affect the validity of the results.
5.7 Discussion
As expected, the prototypes that were developed did not fully imitate the
interaction with the actual app. This was in keeping with our expectations as a
full emulation of the prototype was not the intention or goal. For example, the
emulation did not allow text input or full interactivity. This meant that all buttons
could not be pressed, and so on. The response time of the prototype varied, with
some actions having quite a long response time in comparison to others. This
presented a problem during testing since it increased the task time, resulting in
the task time results being affected. However, the biggest problem was that the
test subjects interpreted the long response time as an incorrect push and then
proceeded to push again or push somewhere else. Furthermore, the prototype
did not allow to input information in just any order. This was because we did not
have time to design the prototype to function for all possible outcomes/cases. The
result was that the test subject performed an interaction that generated an error in
the prototype, but that would have been correct in the final application. Therefore
our results are not fully equivalent to how a userwould navigate through the actual
app rather than our prototype. A consequence of this was that the percentage of
errors when interacting with the prototype are higher than they would be in the
final product which can be seen from the results of testing. Because of this source
of error, testing was concluded when all other performance goals were met.
The results were also affected by the fact that test subjects thought out loud while
performing the task, and that the task they were supposed to do was given to them
rather than known to them. It can be assumed that test subjects would perform
tasks slightly fast, would they not be required to think out loud during the process.
Furthermore, would test subjects probably have performed tasks faster, would
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they themselves have been inspired to do the tasks. During testing all information
theywere supposed to put in and choose, was given to themmeaning that they had
to refer back to the instructions at some points. For some test subjects, this added
quite a lot to the time it took to perform a task.
It was quite difficult to concept code the verbal data. Very often the test subjects
did not speak in full sentences and it was difficult to discern what they were
referring to at all times. When analysing the verbal data the data was divided into
phrases, and then each phrase was concept coded. However, since the test subject
did not speak in full sentences it was difficult to divide the data into phrases.
Because the percentage of negative comments were simply counted, the result
can be heavily influenced by how many phrases the verbal data was split into.
Although the design of the prototype was not strictly evaluated by the percentage
of negative comments, but also included the performance measurements - this
should compensate for some faults in the analysis of the verbal data. Furthermore,
some comments referred to the software used to realize the prototype, rather than
the design of the app. For example, some commented on the slow responsiveness
of the prototype.
It is worth to consider that the first prototype was designed with a bottom nav
bar, something more commonly used in Apple IOS apps. However, the second
and third prototype was designed with a hamburger menu, more commonly
used in Android apps, but also used in a number of IOS apps. Depending on
what operating system the test subjects were used to, this could influence how
recognisable the navigation design was and how quickly they could adapt to it. In
fact, about half of the test subjects were used to the IOS operating system and half
were used to the Android operating system.
It is important to note that we chose to change the task instructions to correspond
to the changes we made in the prototype. The altered instructions are presented
in Appendix C. Furthermore, it was understood that the instructions were not
detailed enough for the test subjects to fully understand what the goal of their
task was and the concept of the app. Not having a clear understanding of the
task and the concept of the app resulted in several errors that could have been
avoided otherwise. An onboarding process or beginners guide should probably
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be implemented in the final product to ensure that the concept of the app and
the different functions available are fully understood by users. In our opinion,
a ”good” design of the app is insufficient to convey how the app works and its
concept.
The results of iteration 1 showed that almost all performance measurements
were below the set goals. However, all the median values of the percentage
of negative comments were below the goal of a maximum of 50%. The results
for the percentage of negative comments were inconsistent with the results of
the performance measurements. From this, we can conclude that the goal
we set for the percentage of negative comments, was too generous. However,
as stated previously the design of the prototype was not evaluated only based
on the percentage of negative comments, but also considered the performance
measurements. This should compensate for small faults in the analysis of the
verbal data.
As the functions of the app were changed between iterations 2 and 3 the testing
results were affected. Not only was the design changed, but also the task flow.
This affected the result in that the results worsened, for some tasks, in between
iterations 2 and 3. The changes made task Charge more complex, and therefore
the usability of it declined. Since the product owner was consulted during the
design of a newprototype the product owner alsomade an evaluation of the design
of the prototype.
As the language used, both in the instructions and the prototype, was not the
native language of the test subjects this could have contributed to some problems
users had interacting with the prototype.
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6 Conclusions and Future work
The following subsections will discuss the positive effects and drawbacks of the
work as well as an evaluation of the results. Section 6.2 will discuss the limitations
of the results and Section 6.3 suggests future work and summarizes what is left
undone.
6.1 Conclusion
As discussed in Chapter 1, there is yet research to be done in the usability of e-
wallets and mobile payment apps. Since mobile payment apps usually feature
more complicated functions than the average smartphone app, but also because
of the nature of the functions. As the functions concern money, the demand for
usability and a ”good” design that instils a sense of security is higher. The concept
of this particular e-wallet and its functions was shown to be confusing to a lot of
users we tested it with. Particularly users had difficulty understanding how the
currencies were stored and how the transactions happened. What was important
to do and also the biggest challenge was to introduce new concepts, terminology,
and functions in a way that the users were familiar with and to relate them to
recognizable ideas. This involved displaying a large amount of information in
a clear and minimalist way. This was the most important issue that we had to
deal with in order for the app to work in an environment with people who have
no earlier experience of e-wallets. When testing we noticed that our experience
and the product owner’s technical experience and knowledge of the app made
us blind to some major issues. Some people had more difficulty grasping the
idea and purpose of the app as opposed to having difficulties with navigating
and completing the tasks. This showed when participants had trouble finishing
some tasks in the first iteration, but later on, were able to finish the same tasks
without any issues - despite the fact that they could still not grasp the meaning
of some information. To work around this issue, creating an onboarding process
for new users of the app was suggested to the product owner, but no testing of
this performed. The onboarding process does not necessarily have to include
information about for example the location of buttons, but rather could consist
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of animations or pictures combined with text to describe the bigger picture and
general idea of the app and its purpose. We believe that such a process would
increase understanding, especially for new users.
Our results showed that usability testing resulted in a huge improvement in
the design of the app. Even at the second iteration, huge improvements were
made as discussed in Chapter 5. It was clear that without any testing and
feedback from real users, more time and effort would have to been required
to redesigning a ”finished” app. In the worst case, the app would not have
performedwell with users, without improvements in its design. Reflecting on how
users experience apps in early stages broadens the perspective of developers and
motivates developers to come up with smart ideas to solve problems early on.
We met our set performance goals regarding time, meaning all tasks were
performed under 1 minute. We also met our goal of a satisfaction rate 5 or higher
on a Liker scale of 1 to 7. The goals for verbal data, a percentage of negative
comments under 50 % were also met. However, as for the percentage of errors,
we could not reach the goal of a maximum of 5%. The reason for this depended on
several factors such as: what is considered as an error in the prototype versus in
the final app, as well as the maximum number of interactions to complete a task
being a small number. Even though a tester only performed one error during the
whole task, we would never, even in that case, reach our goal. The only time we
would be able to reach such a goal would be if the user performed zero errors when
performing a task.
The drawbacks that affected the results and our efforts weremainly the limitations
in possibilities and flexibility of ”Figma” prototyping. The problem we had was
that it was too time-consuming tomake the whole prototype interactive so we had
to prioritize the most important functions and only make those tasks available
for the tester. There was no quick way to make the whole prototype interactive
and at the same time be easy to change after the feedback was received from the
testing. Because ”Figma” did not support text input we were not able to test the
design featuring a keyboard. Furthermore, could the prototype not enable the use
of an actual QR scanner or a camera. Instead, a QR code was simply displayed
on the view to mimic this feature. We noticed that other software for prototyping
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were all similar to ”Figma” so it would not help if we switched to another. There
existed no ”perfect” software for creating prototypes for usability testing that was
free of charge and also supported mirroring on the phone which we prioritized as
a feature. The learning effects of using the same test group for each iteration also
affected the results. The results were affected by the fact that people thought out
loud, but foremost by the fact that the task they were supposed to do were given
to them rather than known to them.
Would we have done the project again we would have not used the TAP. Instead,
we would have collected verbal data and comments about the prototype through
post-test interviews. We realised that post-test interviews would have been the
preferredmethodwhen test subjects offered spontaneous comments, after testing,
that were very useful for altering the prototype. Furthermore, did the verbal data
collected through TAP not offer much information and was time-consuming to
analyse.
6.2 Limitations
During this project, we limited ourselves to focusing on finding themajor usability
problems with the design of the prototype. Therefore a small, ad hoc test group
was sufficient. To discover minor usability problems a larger test group would
need to be used with new test subjects at each iteration. The fidelity of the
prototypes developed was the same throughout testing. Initially testing on a
low-fi prototype and later testing on a high-fi prototype would have made the
testing more time efficient since less time would have been spent developing the
prototypes while there were still major changes to bemade. As the app is intended
for use internationally and by all kinds of users, we should have selected a more
diverse test groupwith regards to nationality, technical experience, and disability.
Such a broader test group would have more accurately represented the target
users.
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6.3 Future Work
There is a lot that is left to be done in the future. The work that we did is only
the initial design and testing of a prototype which later on must be developed
into a real application for the company. Before releasing such an app it would
be appropriate to do further testing to address the limitations introduced by the
”Figma” prototyping when these would not occur in an actual app. This testing
should be done to find detailed usability problems that are too small to find when
testing on prototypes. Furthermore, a fully functional app would enable testing
with full interactivity and better response time. It would also enable testing
features like QR scanner and text input. If better software for prototyping for
usability testing is found, then further testing could be made to compare with our
results.
6.4 Reflection
Performing usability testing on an app design early and continuously during
production can save a large amount of time, effort, and money. This has a direct
effect on the economic costs of the company and potentially reduce the time to
market for the final product - thus enabling the company to begin to generate
revenue earlier and also provide a larger group of users who can generate feedback
to further improve the design. Discovering major problems early in the design
process can vastly reduce the amount of redesign of the app. Furthermore, it can
possibly ensure a better design of the final product. The app will also be designed
by keeping the users inmind. This should result in the appperformingbetterwhen
used by actual users. Having an easy to use e-wallet could have a major impact,
especially in a society thatwants to shift to electronic payments rather than the use
of coins and paper currency. The shift to electronic payments is expected to have
environmental benefits by reducing the needs to the currency and its replacement
due to wear and reducing the need for armoured cars to transport the currency.
Additionally, this transition is expected to reduce the costs and risks associated
with dealing with currency.
As mobile payment is in its infancy, the privacy and security requirements are
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still quite unclear. Therefore there are some privacy concerns with regards to e-
wallets. Furthermore, it is also unclear if e-wallets will be designed to track all
of the transfers in an auditable way or if they will hide these transactions from
access by other parties. There is also an ethical problem concerning whether the
interface and device ensure that only a legitimate user canmake use of the e-wallet
and that such a user is not under duress.
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[62] What is Usability? The Interaction Design Foundation. URL: https : / /
www.interaction- design.org/literature/topics/usability (visited
on 03/20/2019).
[63] WHO. WHO | Informed Consent Form Templates. 2019. URL: https://
www.who.int/rpc/research_ethics/informed_consent/en/ (visited on
04/01/2019).
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A First Appendix
Figure A.1: Task flow of Swish
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Figure A.2: Task flow of Paypal
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Informed Consent Form (ICF) Background We are two students Bercis Arslan [email protected] and Blenda Fröjdh [email protected] doing research as part of a 1st cycle degree project at KTH, together with Centiglobe. We are doing research on usability on the design of a mobile payment application. We want to investigate how an e-wallet can be designed to ensure that users’ experience is as pleasing as possible. Type of research This research will involve you being given a task to perform on a prototype of a mobile payment application, talking out loud as you perform it, and us observing you. You will also be asked to fill out a questionnaire regarding your experience using the prototype. This will take place in a quiet setting and will take about 30-60 minutes. Voluntary participation Your participation in this research is entirely voluntary. It is your choice whether to participate or not. You can change your mind at any time and immediately stop participating. Procedures You will be asked to perform a certain task and presented with a card containing information about the task. You can continue to refer to the instructions on the card as you go through the test. As you perform the task you will be asked to think aloud as you perform it, expressing whatever comes to your mind regarding the prototype and your experience using it. Furthermore, the meeting will be audiotaped. The audiotape will be transcribed and presented in our report but the audiotapes are confidential and no one else except us, Blenda Fröjdh and Bercis Arslan, will have access to the tapes. The tapes will be destroyed after 20 weeks. At the end of the meeting, you will be asked to fill out a survey using Google forms. The questions included in the survey will be limited to your experience using the prototype. This consent form will be retained by us for three years and will be destroyed after that time has passed. Confidentiality The information that we collect from this research will be presented in our report. Our report will be published and available in full-text in DiVA which is a database open to anyone. Any information about you in the report will have a number on it instead of your name. Certificate of consent I have read the foregoing information and I consent voluntarily to be a participant in this study Signature of participants _____________________ Date ___________________________
Signature of Researcher_______________Signature of Researcher_______________ Date ___________________________
1
B Second Appendix
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Pay via QR
Task Scan a QR code and choose the payment method Swish.
Scenario You are using an e-wallet application to transfer money and store different currencies. You now want to transfer money. To input the payment information you want to scan a QR code. Then you want to choose the payment method Swish.
Instructions ● Speak your thoughts or whatever you do as much as possible when using the prototype ● Don’t ask any questions related to the use of the prototype when performing the task.
Pay via manual input
Task Transfer 100 CRW to Nisse via SEK.NORDEA.VOLVO using the payment method Swish.
Scenario You are using an e-wallet application to transfer money and store different currencies. You now want to transfer money. You want to input the payment information manually (). You want to transfer 100 CRW to Nisse via SEK.NORDEA.VOLVO. You don’t want to input a message. You want to use the payment method Swish.
Instructions ● Speak your thoughts or whatever you do as much as possible when using the prototype ● Don’t ask any questions related to the use of the prototype when performing the task
C Third Appendix
Figure C.1: Task instructions for iteration 1
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Charge your account
Task Increase the balance of CRW with 100 CRW using the payment method Swish.
Scenario You are using an e-wallet application to transfer money and store different currencies. Currently, you have 1234.95 CRWs stored in your app. You now want to increase the amount of CRW stored in the wallet with a 100 CRW. The payment method you want to use to increase the balance is Swish. CRW is a type of currency.
Instructions ● Speak your thoughts or whatever you do as much as possible when using the prototype ● Don’t ask any questions related to the use of the prototype when performing the task.
Exchange
Task Exchange from one currency to another
Scenario You are using an e-wallet application to transfer money and store different currencies. You want to exchange an amount of money in the currency SEK.Nordea.Nordea to the currency CRW. The amount you want to change is 100 SEK.Nordea.Nordea.
Instructions ● Speak your thoughts or whatever you do as much as possible when using the prototype ● Don’t ask any questions related to the use of the prototype when performing the task.
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Charge
Task Increase the balance of CRW through charging 100 SEK from your Swish account.
Scenario You are using an e-wallet application to transfer money and store different currencies. Currently, you have 100 CRW stored in your wallet. You now want to increase the amount of CRW stored in the wallet with 100 SEK (100 SEK is 50 CRW). You want to charge through your Swish account. In the end you have added 50 CRW to your wallet. Instructions
● Speak your thoughts or whatever you do as much as possible when using the prototype
● Don’t ask any questions related to the use of the prototype when performing the task.
Exchange
Task Exchange from one currency to another
Scenario You are using an e-wallet application to transfer money and store different currencies. You want to exchange 100 SEK to the currency CRW. You want to exchange from your Nordea account to your Centiglobe account. Start by putting in the amount and currency you want to sell, then the currency you want to buy.
Instructions ● Speak your thoughts or whatever you do as much as possible when using the
prototype ● Don’t ask any questions related to the use of the prototype when performing the task.
Figure C.2: Task instructions for iteration 2
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Pay via QR
Task Scan a QR code and send 150 SEK to ICA Bank from your Nordea account.
Scenario You are using an e-wallet application to transfer money and store different currencies. You are at the ICA store and now want to buy something for 150 SEK. To input the payment information you want to scan a QR code. The currency you want to pay with is SEK. The account you want to send from is Nordea. You don’t want to add a message. The transfer method is Swish.
Instructions ● Speak your thoughts or whatever you do as much as possible when using the
prototype ● Don’t ask any questions related to the use of the prototype when performing the task.
Pay
Task Transfer 100 SEK from your Swish account to 150 KRC to John’s Mpesa account.
Scenario You are using an e-wallet application to transfer money and store different currencies. You now want to transfer money. You want to send money to John. You want to send 100 SEK from your Swish account. You want John to receive the money as 150 KRC to his Mpesa account. You don’t want to input a message. The transfer method is Swish.
Instructions ● Speak your thoughts or whatever you do as much as possible when using the
prototype ● Don’t ask any questions related to the use of the prototype when performing the task.
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Charge
Task Increase the balance of CRW through charging 100 SEK from your Swish account.
Scenario You are using an e-wallet application to transfer money and store different currencies. Currently, you have 100 CRW stored in your wallet. You now want to increase the amount of CRW stored in the wallet with 100 SEK (100 SEK is 50 CRW). You want to charge through your Swish account. In the end you have added 50 CRW to your wallet. The transfer method is also Swish. The CRW account is Centiglobe. Instructions
● Speak your thoughts or whatever you do as much as possible when using the prototype
● Don’t ask any questions related to the use of the prototype when performing the task.
Exchange
Task Exchange from one currency to another
Scenario You are using an e-wallet application to transfer money and store different currencies. You want to exchange 100 SEK to the currency CRW (100 SEK is 50 CRW). You want to exchange from your Nordea account to your Centiglobe account. Start by putting in the amount and currency you want to sell, then the currency you want to buy.
Instructions ● Speak your thoughts or whatever you do as much as possible when using the
prototype ● Don’t ask any questions related to the use of the prototype when performing the task.
Pay via QR
Task Scan a QR code and send 150 SEK to ICA Bank via provider Nordea.
Figure C.3: Task instructions for iteration 3 4
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Scenario You are using an e-wallet application to transfer money and store different currencies. You are at the ICA store and now want to buy something for 150 SEK. To input the payment information you want to scan a QR code. The currency you want to pay with is SEK. The provider you want to send money via is Nordea. You don’t want to add a message. The transfer method is Swish.
Instructions ● Speak your thoughts or whatever you do as much as possible when using the
prototype ● Don’t ask any questions related to the use of the prototype when performing the task.
Pay
Task Transfer 100 SEK via provider Swish to 150 KRC to John via provider Mpesa.
Scenario You are using an e-wallet application to transfer money and store different currencies. You now want to transfer money. You want to send money to John. You want to send 100 SEK using the provider Swish. You want John to receive the money as 150 KRC via provider Mpesa. You don’t want to input a message. The transfer method is Swish.
Instructions ● Speak your thoughts or whatever you do as much as possible when using the
prototype ● Don’t ask any questions related to the use of the prototype when performing the task.
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D Fourth Appendix
Table D.1: Exerpt of concept coded verbal data
Phrase Coding Category
okej, scanna in qr kod är väl där. Interpretation Neutral
Den gjorde det automatiskt Observation Neutral
Jag antar att det ska vara någon kamera Interpretation Neutral
Från sek. Action Neutral
Aa den är automatisk, nice. Observation, Value Positive
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TRITA TRITA-EECS-EX-2019:176
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