Introduction of a game design in e-banking - Inter

Introduction of a game design in e-banking – thinking of business while
playing in a virtual environment
Luís Rodrigues, Abílio Oliveira and Carlos Costa
Abstract
The rapid proliferation of multiple software with features of video games gave way
to a trend called “Gamification”. This new paradigm lists the existing concepts to
study the interaction between man and machine, and introduces key elements such
as persuasion and an eye-catching design. However, there is no concise
explanation that allows the connection of the elements of game applications with
non-game features, especially in traditional and highly regulated sectors, such as
the financial sector. The aim of our study is to investigate the client perceptions
using a serious e-banking business application with games features. Therefore, we
developed mutual funds software gamified with the design and characteristics of a
football game. In this study it was analysed the behavior of more than 800 clients
who used the software, before they could respond to an online questionnaire. Our
findings show that the perceived ease-of-use has a strong influence on their
intentions to use and on the perceived usefulness. Socialness has influence on all
other studied variables, but the enjoyment and utility has no influence in the
intention to use the game. It was further investigated the respective impact on the
business of mutual funds from the use of the game in the electronic channel of the
bank. Our results show that the software gamified had a positive impact, proving
that the web design and the relationship between the financial product and the
football game had a good acceptance by the participants/clients, as demonstrated in
their intention to use it, and in the high average values in the response to
recommendation to friends. The use of computer games in a virtual environment,
configuring a concrete situation, has influence on the way users consider that
situation.
Key Words: Virtual environments, gamification, e-banking, computer games,
business software, creativity, information systems.
*****
1. Introduction
The technological evolution in the development of computer applications and
the increase of internet users has taken in recent years to the development of ebanking, fundamentally transforming the traditional mode how banks conduct their
business, as well as the shape and the process as clients perform their banking
activities.1 This constant attempt to be close to what clients like, aims to increase
the use of e-banking and loyalty, in this sense the banks seek to develop and/or
change their computer applications in order to include features appreciated by
users of online gaming.2 Even with the increased use of e-banking services in
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Introduction of a game design in e-banking
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recent years, banks face a dilemma, while the e-banking has benefits of
convenience and economy, the ease-of-use of e-banking services allow greater
client change to other banks, and therefore it reduces the long-term clients’
commitment and loyalty.3
The use of games as a factor in reducing barriers to the access of the internet,
such as the difficulty of human relationship with the computer and the internet,
usability, the lack of security and ease of use were developed in computer
applications.4 The high cost of attracting new clients to the e-banking and the
relative difficulty in keeping their loyalty, creates an opportunity in developing
applications with features of games, an essential resource for the banks, since the
games have a good acceptance of the users in general.
2. Main Objectives
The present study aims to investigate the impact of e-banking applications with
features of games in electronic business. It was developed new software with
games characteristics, and tested a theoretical model (with twelve hypotheses) in
order to determine the variables that could influence the user behavior in using and
purchasing products with the new application. Studying games and e-banking we
may be able to answer the central question: to what extent the e-banking may
benefit from the use of game design?
3. Research Model and Hypotheses
3.1. Business Application Gamified
The business application under study is called "Futebank". It is a digital
animation implemented on a banking website, based on the management of a
portfolio of mutual funds, on an animated model of a football league. The game
established the main relationship between a football team with a portfolio
investment fund and the positions of the players on the field with the risk rating
assigned to a specific mutual fund. The application was only available for clients
with mutual funds in their portfolio with the main objective of transforming a
complicated process of choosing, selecting and purchasing mutual funds, in a nice,
simple, funny and attractive process (cf. Figure 1).
Before gamified
After gamified
Luís Rodrigues, Abílio Oliveira and Carlos Costa
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Figure 1 - Transformation from a traditional business financial application to
gamification
3.2. Conceptual Model
In this empirical research, we analyse the ability of TAM5, to predict and
explain the acceptance or rejection of new computer applications with game
features. The proposed research model, relations and moderator variables applied
to this study are the following (cf. Figure 2).
Figure 2 - Conceptual model, adapted from Wakefield et al., (2011)
First test: Model with 10 hypotheses
Second test: Changed model, H5 and H7 replaced by H11 and H12
To determine the clients’ behavior and use intention of the new application, two
tests was performed with ten hypotheses (H1 to H10), but where H11 and H12
replace H5 and H7 in one of the tests. The observed variables have been grouped
by five latent variables not observed used in the proposed research, as well as
twenty-five endogenous variables observed, and which were used in the
measurement of the model (cf. Table 1).
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Table 1 - Construct variables and items
Construct Variable
Acronym
Items
6
Perceived Socialness
PSOC
5
Perceived Ease of Use7
PEOU
4
Perceived enjoyment8
PENJ
5
Perceived Usefulness9
PUSE
4
Perceived Intention to Use10
PINT
5
4. Research Methodology
In the context of the game available on the website in a bank, it was analysed
the participants/clients' reactions with the use of the financial application gamified
through their responses to an online questionnaire. All endogenous variables and
latent variables included in this study are measured by Likert scales. 11 The SEM
(Structural Equation Model) approach was adopted to analyse the data, since it
allows the confirmation and the exploration of the theoretical model.
4.1. Questionnaire, Sample and Profiling
The questionnaire was previously tested by a small sample of users who have
had prior access to the game, to evaluate the reliability of the survey, and that
procedure gave us the opportunity to modify in advance the questions that created
some type of confusion. The sample of this study consists of 183 users from a
universe of 862 clients that used the game, of which 427 had more than 6 mutual
funds/players in their investment portfolio and, thus, were eligible to participate
fully in the football league game. The data and the characteristics of the clients
included in this study are summarized in Table 2.
Table 2 - Demographic characteristics of the participants
Gender
Age (years)
Education degree
Sample Male Female < 25 25 to 40 >40 High school Bachelor’s Graduate
or less
183 88% 12% 3%
35% 62%
24%
62%
14%
4.2. Results
Analysing the answers (cf. Table 3) with mean higher than 4, showed that
clients have considered the game interactive (QSOC5, mean = 4.13), and revealed
a strong intention to talk to friends (QINT3, mean = 4.05), "Word-of-Mouth". With
a lower mean we found that the users did not feel a significantly spirit of adventure
while navigating on this website (QPENJ2, mean = 3.46) or enthusiasm (QENJ3,
mean = 3.51) nether time consuming to purchase (QPEOU3, mean = 3.53). These
Luís Rodrigues, Abílio Oliveira and Carlos Costa
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less positive feelings might be correlated with the fact that the game was only
available for existing clients, with a real portfolio of mutual funds.
Table 3 - Descriptive Statistic (SPSS v20) (*Indicates dropped item to increase
construct reliability analysis)
Mean
Mean
Std.Deviation Variance
Measurements items
Variable
Std.
Statistic
Statistic Statistic
Error
Friendly
QSOC1*
3.82
0.08
1.19
1.42
Helpful
QSOC2
3.61
0.07
1.06
1.14
Informative
QSOC3
3.68
0.07
1.02
1.05
Intelligent
QSOC4
3,86
0.07
1.02
1.05
Interactive
QSOC5*
4.13
0.07
1.02
1.04
I can quickly find the
information I need on this
QPEOU1
3.78
0.07
0.98
0.97
game
It is easy to select the
QPEOU2*
3.70
0.07
0.95
0.90
players/Mutual Funds
It would not be time
consuming to purchase a QPEOU3
3.53
0.06
0.90
0.82
mutual fund
My interaction with this
game
is
clear
and QPEOU4
3.81
0.06
0.88
0.78
understandable
During
the
navigation
process, I felt excitement QPENJ1
3.82
0.07
1.03
1.07
with the game animation
While navigating on this
website, I felt a sense of QPENJ2*
3.46
0.08
1.13
1.28
adventure
The enthusiasm of this
website is catching; it picks QPENJ3*
3.51
0.08
1.15
1.33
me up
This website it entertains me
with
the
soccer QPENJ4
3.73
0.06
0.92
0.84
championship analogy
I enjoyed being immersed in
exciting connection with the
QPENJ5
4.02
0.06
0.81
0.66
serious application and the
game
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Introduction of a game design in e-banking
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This website provides good
quality information to
manager my players / funds
and may team / portfolio
This website is useful for
selecting the best players /
mutual funds
Follows my mutual funds
from this website would fit
my interests
Information sharing is
useful
I would be willing to use this
website
I intend to use this game in
the future
I’m likely to recommend this
website to my friends
Awards
increases
my
involvement in the game
Social network connection
increases my participation
QPUSE1
3.66
0.07
1.00
1.00
QPUSE2
3,63
0.07
0.95
0.90
QPUSE3*
3.91
0.07
1.01
1.03
QPUSE4*
3.63
0.07
1.03
1.07
QPINT1*
3,51
0.11
1.48
2.21
QPINT2
3.63
0.07
1.06
1.13
QPINT3
4.05
0.08
1.16
1.34
QPINT4*
4.05
0.06
0.85
0.72
QPINT5*
3.87
0.08
1.08
1.16
To assess the validation of the constructs and the reliability of variables, the
Cronbach's Alpha for each latent variable and the underlying measurement items
was calculated. The results of all the coefficients of reliability are above the
recommended minimum of 0.70 Cronbach's Alpha 12, demonstrating that the results
of the constructs and the underlying elements (variables) are highly consistent.
With AMOS it was calculated the direct effect of the Futebank model and the
results obtained was: X² = 220, (P = 0.000), DF = 220, RMR = 0.1161, CFI =
0.660, IFI = 0.663. According to the measures of good fit model recommendations
(cf. Table 4), these results are indicating of poor model fit to the data, and imply
that the relationships in the data are not well described by the direct - effect model.
Table 4 - Measures of good fit model
Measures
Value
13
CFI-Comparative Fit Index
Greater than 0.9
NFI-Normed Fit Index14
Greater than 0.9
GFI-Goodness of fit statistic15
Greater than 0.9
IFI- Incremental fit index16
Greater than 0.9
17
CMIN/DF
Between 1 and 5
Luís Rodrigues, Abílio Oliveira and Carlos Costa
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RMR-Root Mean Square Residual18 Less or equal than 0.05
An individual validation of the dimensions CFA (Confirmatory Factor Analysis)
was performed.19 As the model did not provide satisfactory values for our level of
reliability20, we removed those variables to submit standardized lower coefficients,
or with a high Kurtosis value (high probability of extreme values) or R2 values with
very high error levels, correlation values (values of Phi too high) or Lambda
values.
After CFA has been performed, the hypothesis tests were conducted again and
the result of the model fit was: X² = 180.2, (P = 0.000), DF = 55, RMR = 0.507,
GFI = 0.873, CFI = 0.913, IFI = 0.914. The fit statistics are now indicative of a
good model fit the data, although GFI is below the recommended minimum of 0.9
in practice, GFI values above 0.8 are considered to indicate a good fit.21 The
standardized path coefficients with absolute values less than 0.10 may indicate a
small effect, values around 0.30 a medium effect and with absolute values greater
than 0.50 a large effect.22
The results of the first test (with the hypothesis H1 to H10) indicate that not all
standardized coefficients for all hypothesized paths in structural model are
significant (P<0.05). PENJ have no positive influence on PINT (H6, ß =0.036),
PUSE have no positive influence on PINT (H9, ß = -0.192) and PUSE have no
positive influence on PENJ (H10, ß = -0.298). All the others hypothesized paths
are significant, PSOC have a medium positive influence on PINT (H1, ß = 0.491)
and PEOU (H2, ß = 0.392) and PUSE (H3, ß = 0.426) and PENJ (H4, ß = 0.438).
Finally PEOU have a large positive influence on PENJ (H7, ß = 0.687), on PUSE
(H5, ß = 0.785) and on PINT (H8, ß = 0.857).
To test the influence of PUSE and PENJ in PEOU (strongest variable with
influence in PINT), a second test was performed where it was replaced the H5 with
H11 and H7 with H12 were conducted and results indicate that PUSE have positive
large influence on PEOU (H11, ß =0. 517). However, lower than the reserve (H5, ß
= 0.785) and PENJ have a positive medium influence on PEOU (H12, ß =0. 474)
but again lower than the reverse (H7, ß = 0.687).
The structural model test results are summarized in Table 5.
Hypothesis
H1
H2
H3
H4
H5
H6
Table 5 - Model test regression weights
Dependent Independent Regression
p Test result (positive
Variable
Variable
Weights (ß)
influence?)
PSOC
PINT
0.491
0.006
Medium
PSOC
PEOU
0.392
***
Medium
PSOC
PUSE
0.426
***
Medium
PSOC
PENJ
0.438
***
Medium
PEOU
PUSE
0.785
***
Large
PENJ
PINT
0.036
0.892
Rejected
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H7
PEOU
PENJ
H8
PEOU
PINT
H9
PUSE
PINT
H10
PUSE
PENJ
H11
PUSE
PEOU
H12
PENJ
PEOU
***absolute value is less than 0.001
0.687
0.856
-0.192
-0.298
0.517
0.474
0.001
0.037
0.459
0.065
***
***
Large
Large
Rejected
Rejected
Large
Medium
The results of multivariate tests of the structural model are provided in Figure
3, which outlines the regression coefficients for each factor.
Figure 3 - Structural model results
5. Conclusions
Results show that participants/clients that use the application gamified
perceived that the PEOU has a large positive influence on the intention to use the
application and highlights the importance that the PEOU as on PUSE. The
perceived ease-of-use has a positive influence on the perception of enjoyment,
showing that the easier is the use the more the application is enjoyable, which is
according to the study of Ramayah and Iggnatius23 that also concluded the PEOU
of technology induces positively the intention of use online shopping. Klomsiri
proposed a modification in TAM to measure the internet technology use for ebanking adoption where PUSE could influence PEOU, however he did not make
the tests that we have done in this study.24 The modified TAM with two new
hypotheses H11 and H12 (replacing H5 and H7) implies that PUSE have positive
large influence on PEOU (H11, ß =0.517) but lower than the reserve (H5, ß =
0.785) and PENJ have a positive medium influence on PEOU (H12, ß =0.474) but
Luís Rodrigues, Abílio Oliveira and Carlos Costa
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also lower than the reverse (H7, ß = 0.687). Our findings can contribute with
important information about the role of social usefulness, enjoyment and
perception of ease-of-use on the intention to use gamification in e-banking, as
demonstrated in the results of the theoretical model in which PEOU turn has a
large positive influence on PINT, and PUSE has no positive influence on PINT.
In response to the question “to what extent is the e-banking may benefit from
the use of game design?” the results of the hypotheses tests showed that, the game
had a positive impact on clients, thus increasing the future intention to use this type
of applications gamified in e-banking. The study of the business influence through
this new application with game design show a positive impact on the business in
terms of clients participation and on the business values (cf. Table 6).
Table 6 - Business results
Business measures
Clients access to the website
Visitors access to the website
Total clients that used the gamified software
Total clients with more than 6 mutual funds
Mutual funds purchased through the game
Total amount on the mutual fund portfolio´s
Value
+ 16%
+ 37%
862
232
+ 11%
+ 15%
The relationship between the mutual funds and the soccer players as resulted in
a good acceptance, as proved in the intention of use, and the recommendation to
friends (Word of Mouth) that is an important factor for business along with loyalty
and clients’ satisfaction.25
Overall the new application gamified, rests on innovation, differentiation of
selling products from other e-banking websites, more business with a complex
financial product. The clients' perception results in a less effort to use the new
software application, perception of usefulness and enjoyments when they have
used the new mutual fund application. In this sense, banks should be encouraged to
develop business applications with game features on their websites, not only to
increase the loyalty of the clients, but also to engage the clients to buy products in
a different and simple way, since games are easy to use and pleasing.
Notes
1
Kent Eriksson, Katri Kerem, and Daniel Nilsson, ´The adoption of commercial
innovations in the former Central and Eastern European markets: The case of
10
Introduction of a game design in e-banking
________________________________________________________________
2
3
4
5
6
7
8
9
Internet banking in Estonia.´ International Journal of bank Marketing 26, no. 3
(2008):154–169.
Ceren Sayar and Simon Wolfe, ´Internet banking market performance: Turkey
versus the UK.´ International Journal of bank Marketing 25, no. 3 (2007):12241.
Dan Sarel and Howard Mamorstein, ´Marketing Online banking services: The
voice of the customer.´ Journal of Financial Services Marketing 8, no. 2
(2003):106.
Cheolho Yoon, ´The effects of national culture values on consumer acceptance of
e-Commerce: online shoppers in China.´ Information Management 46, no. 5
(2009):294–301.
Fred D. Davis, ´Perceived usefulness, perceived ease of use, and user acceptance
of information technology.´ MIS Quarterly 13, no. 3 (1989):319–340.
Byron Reeves and Clifford Nass, The media equation: How people treat
computers, television, and new media like real people and places. CSLI
Publications, Stanford, CA, 1996; Clifford Nass and Jonathan Steuer. ´Voices,
Boxes, and Sources of Messages Computers and Social Actors.´ Human
Communication Research 19, no. 4 (1993):504–527; Robin L. Wakefield, Kirk
L. Wakefield, Julie Baker, and Liz C. Wang, How Website socialness leads to
Website use.´ European Journal of Information Systems 20, no. 1 (2011):118–
132.
Fred D. Davis, Richard P. Bagozzi, and Paul R. Warshaw, User acceptance of
computer technology: a comparison of two theoretical models. Management
Science 35, no. 8 (1989):982–1003; Hans Van der Heijden, ´User Acceptance of
Hedonic Information Systems.´ MIS Quarterly 28, no. 4 (2004):695-704; Robin
L. Wakefield, Kirk L. Wakefield, Julie Baker and Liz C. Wang, How Website
socialness leads to Website use.
Fred D. Davis, Richard P. Bagozzi, and Paul R. Warshaw, ´Extrinsic and intrinsic
motivation to use computers in the workplace.´ Journal of Applied Social
Psychology 22, no. 14 (1992):1111-1132; Hans Van der Heijden, ´User
Acceptance of Hedonic Information Systems.´ MIS Quarterly 28, no. 4
(2004):695-704; Robin L. Wakefield, Kirk L. Wakefield, Julie Baker and Liz C.
Wang, How Website socialness leads to Website use..
Leda Chen, Mark L. Gillenson, and Daniel L. Sherrell, ´Enticing online
consumers: an extended technology acceptance Perspective.´ Information and
Management 39, (2002):705-719; Fred D. Davis, Richard P. Bagozzi, and Paul
R. Warshaw, User acceptance of computer technology: a comparison of two
theoretical models.; Ji-Won Moon and Young-Gul, Kim, ´Extending the TAM
for a World Wide Web context.´ Information & Management 38, no. 4
(2001):217–230.
Luís Rodrigues, Abílio Oliveira and Carlos Costa
11
________________________________________________________________
10
Fred D. Davis, Richard P. Bagozzi and Paul R. Warshaw, User acceptance of
computer technology: a comparison of two theoretical models. Agarwal Ritu and
Elena Karahanna, ´Time Flies When You’re Having Fun: Cognitive Absorption
and Beliefs about Information Technology Usage.´ MIS Quarterly 24, no. 4
(2000):665-694; Ling-Land Tang and Hanh Nguyen, ´Common causes of trust,
satisfaction and TAM in online shopping: An integrated Model.´ Graduate
School of Management. Yuan Ze University, Taiwan, ROC (CSQ), 2011.
11
From 1-strongly disagree to 5-strongly agree.
12
Joeph F. Hair, William C. Black, Barry J. Babin, and Rolph E. Anderson,
Multivariate Data Analysis (7th ed.). Upper Saddle River, Pearson Education Inc,
NJ, 2006.
13
Joeph F. Hair, William C. Black, Barry J. Babin, and Rolph E. Anderson,
Multivariate Data Analysis.
14
Joeph F. Hair, William C. Black, Barry J. Babin, and Rolph E. Anderson,
Multivariate Data Analysis.
15
Joeph F. Hair, William C. Black, Barry J. Babin, and Rolph E. Anderson,
Multivariate Data Analysis.
16
Ken A. Bollen, Structural equations with latent variables. New York: Wiley,
1989.
17
Miguel A. Mateo Garcia, and Juan Fernandez Sanchez, Análisis confirmatorio de
la estrutura dimensional de un cuestionario para la evaluación de la calidad de
la enseñanza. Investigaciones Psicológicas, no. 11 (1992):73-82.
18
Barbara M. Byrne, Structural Equation Modelling with LISREL, PRELIS and
SIMPLIS: Basic Concepts, Applications and Programming. Mahwah, New
Jersey: Lawrence Erlbaum Associates, 1998.
19
The relationships between the variables were again estimated using the method
of maximum likelihood.
20
The adjustment indices were below the recommended.
21
Afzaal Seyal, Moha Rahman and Mahbubu Rahim, Determinants of academic
use of the Internet: a structural equation model. Behaviour and Information
Technology, no. 21(1) (2002):71-86.
22
Jacob Cohen, Statistical Power Analysis for the Behavioural Sciences 2nd ed.
Lawrence Erlbaum Associates, 1988.
23
T. Ramayah and Joshua Ignatius, Impact of Perceived Usefulness, Perceived
Ease of Use and Perceived Enjoyment on Intention to Shop online. ICFAI
Journal of Systems Management (IJSM), no. 3(1) (2005):36-51
24
Papaporn Klomsiri, Technology Acceptance of IT Innovative Services: Adoption
of E-banking by Customers. Naval Education Department, Royal Thai Navy.
Time,
February,
15,
2013,
from
Bangkok
University:
12
Introduction of a game design in e-banking
________________________________________________________________
http://www.bu.ac.th/knowledgecenter/executive_journal/july_sep_11/pdf/aw7.pd
f, 2010.
25
Shu-Hsien Liao, Yu-Chun Chung, Y.R. Hung and Retno Widowati, ´The
impacts of brand trust, customer satisfaction, and brand loyalty on word-ofmouth.´ Industrial Engineering and Engineering Management (IEEM),
(2010):1319-1323.
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Lawrence Erlbaum Associates, 1998.
Chen, Leda, Mark L. Gillenson, and Daniel L. Sherrell. ´Enticing online
consumers: an extended technology acceptance Perspective.´ Information and
Management 39, (2002):705-719.
Cohen, Jacob. Statistical Power Analysis for the Behavioural Sciences 2nd ed.
Lawrence Erlbaum Associates, 1988.
Davis, Fred D. ´Perceived usefulness, perceived ease of use, and user acceptance
of information technology.´ MIS Quarterly 13, no. 3 (1989):319–340.
Davis, Fred D., Richard P. Bagozzi, and Paul R. Warshaw. User acceptance of
computer technology: a comparison of two theoretical models. Management
Science 35, no. 8 (1989):982–1003.
Davis, Fred D., Richard P. Bagozzi, and Paul R. Warshaw. ´Extrinsic and intrinsic
motivation to use computers in the workplace.´ Journal of Applied Social
Psychology 22, no. 14 (1992):1111-1132.
Eriksson, Kent, Katri Kerem, and Daniel Nilsson. ´The adoption of commercial
innovations in the former Central and Eastern European markets: The case of
Internet banking in Estonia.´ International Journal of bank Marketing 26, no. 3
(2008):154–169.
Garcia, Miguel A. Mateo, and Juan Fernandez Sanchez. Análisis confirmatorio de
la estrutura dimensional de un cuestionario para la evaluación de la calidad de la
enseñanza. Investigaciones Psicológicas, no. 11 (1992):73-82.
Luís Rodrigues, Abílio Oliveira and Carlos Costa
13
________________________________________________________________
Hair, Joeph F., William C. Black, Barry J. Babin, and Rolph E. Anderson.
Multivariate Data Analysis (7th ed.). Upper Saddle River, Pearson Education Inc,
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of E-banking by Customers. Naval Education Department, Royal Thai Navy.
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Liao, Shu-Hsien, Yu-Chun Chung, Y.R. Hung, and Retno Widowati. ´The
impacts of brand trust, customer satisfaction, and brand loyalty on word-of-mouth.´
Industrial Engineering and Engineering Management (IEEM), (2010):1319-1323.
Moon, Ji-Won, and Young-Gul Kim. ´Extending the TAM for a World Wide Web
context.´ Information & Management 38, no. 4 (2001):217–230.
Nass, Clifford, and Jonathan Steuer. ´Voices, Boxes, and Sources of Messages
Computers and Social Actors.´ Human Communication Research 19, no. 4
(1993):504–527.
Ramayah, T., and Joshua Ignatius. Impact of Perceived Usefulness, Perceived Ease
of Use and Perceived Enjoyment on Intention to Shop online. ICFAI Journal of
Systems Management (IJSM), no. 3(1) (2005):36-51.
Reeves, Byron and Clifford Nass. The media equation: How people treat
computers, television, and new media like real people and places. CSLI
Publications, Stanford, CA, 1996.
Ritu, Agarwal, and Elena Karahanna. ´Time Flies When You’re Having Fun:
Cognitive Absorption and Beliefs about Information Technology Usage.´ MIS
Quarterly 24, no. 4 (2000):665-694.
Sarel, Dan and Howard Mamorstein. ´Marketing Online banking services: The
voice of the customer.´ Journal of Financial Services Marketing 8, no. 2
(2003):106.
Sayar, Ceren, and Simon Wolfe. ´Internet banking market performance: Turkey
versus the UK.´ International Journal of bank Marketing 25, no. 3 (2007):122-41.
Seyal, Afzaal, Mohd Rahman, and Mahbubu. Determinants of academic use of the
Internet: a structural equation model. Behaviour and Information Technology, no.
21(1) (2002):71-86.
14
Introduction of a game design in e-banking
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Luis Filipe Rodrigues is a PhD student at ISCTE-IUL, Lisbon, Portugal. While
works as CIO in a bank his research and writing about gamification in e-banking
and the web design characteristics.
[email protected]
Abílio Oliveira is an Assistant Professor, at Instituto Universitário de Lisboa
(ISCTE-IUL), Lisboa, Portugal, and a Researcher, at Centro de Investigação em
Sistemas e Tecnologias de Informação Avançados (ADETTI-IUL), Lisboa,
Portugal. He is the author of several books, namely, 'O Desafio da Vida' (The
Challenge of Life). http://abiliooliveira.weebly.com/
[email protected]
Carlos J. Costa is an Assistant Professor, at Instituto Universitário de Lisboa
(ISCTE-IUL), Lisboa, Portugal, and a Director and Researcher, at ADETTI-IUL.
Invited professor in MSc Programs from Portuguese Open University. Previously
worked as invited professor in IPAM. As develop research projects with many
publications related to Collaborative Systems, Electronic Brainstorming, Open
Source and e-voting.
[email protected]