Influence of Usability on Customer Satisfaction: A Case
Study on Mobile Phone Services
Rodrigo de Oliveira
Telefonica Research
Mauro Cherubini
∗
Google
Nuria Oliver
Telefonica Research
ABSTRACT
Designing for better user experiences (e.g., interactions more
satisfying, enjoyable) is usually more difficult than aiming
for clearer usability goals (e.g., improve systems’ efficiency,
easy of use). In this paper, we present a conceptual model val-
idated with data from 603 mobile phone users that clarifies the
relationship between usability of basic mobile services and
the users’ satisfaction with them. Our findings indicate that
satisfaction is mostly influenced by how users perceive the us-
ability of these services, more specifically their efficiency. We
discuss the model and propose three implications that shall in-
crease satisfaction with basic mobile services: a few solutions
to minimize routine disruption, personality-based service per-
sonalization, and persuasive strategies to raise awareness of
one’s technology consumption saturation point.
Author Keywords
Big Five; mobile phone services; personality; structural
equation modeling; usability.
ACM Classification Keywords
H.1.2 Models and Principles: User/Machine Systems: Hu-
man Factors
INTRODUCTION
The Human-Computer Interaction community was once con-
cerned primarily with usability, but has since become more
interested in understanding, designing for and evaluating a
wider range of user experience aspects. According to Rogers
et al. [29], interactive systems should now be designed in
terms of their objectives classified in terms of usability and
user experience goals. Traditionally, usability goals are re-
lated to specific usability engineering criteria (e.g., systems
designed to be more efficient, effective, easy to use), whereas
user experience goals aim to explain the nature of the user ex-
perience (e.g., interactions more satisfying, enjoyable, engag-
ing) [29]. Although usability goals are nowadays better estab-
lished and integrated into Software Engineering, UX goals
are still considered somewhat fuzzy, being their connection
∗
Research conducted while working for Telefonica Research.
Copyright is held by the authors/owners.
with usability goals even less clear. In this paper we focus
on clarifying this connection in the context of mobile phone
services, particularly between two key usability goals (i.e. ef-
ficiency and ease of use) and an important UX goal: user
satisfaction. More specifically, we present findings of a con-
ceptual model validated with data from 603 customers of a
telecommunication operator that provides insights on the re-
lationship between perceived usability of basic mobile phone
services and their satisfaction with them. The model also cap-
tures the influence of other variables, such as the users’ per-
sonality profile and their usage of mobile services. In the
following sections we explain how the proposed model was
empirically validated and discuss how designers and software
engineers could leverage the model towards improving cus-
tomers’ satisfaction with basic mobile services.
CONCEPTUAL MODEL
The way people appropriate technology has been previously
studied. Several theoretical models have been introduced and
tested to explain user acceptance behavior, such as the The-
ory of Reasoned Action [15], the Theory of Planned Behavior
[2] and the Technology Acceptance Model [11]. While these
models have contributed a great deal to our understanding of
users’ preferences and acceptance behavior of technological
artifacts, they fall short in explaining the users’ experience
with technology.
User experience encompasses the experiential, affective, and
cognitive aspects of a person interacting with a product, sys-
tem or service
1
. Therefore it is not limited to the user’s in-
tention to use a certain technology. However, user experience
models do not typically capture the role of the user’s personal-
ity when interacting with a certain piece of technology. Ryck-
man [30] defined personality as a “dynamic and organized set
of characteristics possessed by a person that uniquely influ-
ences his or her cognitions, motivations, and behaviors in var-
ious situations”. Recent studies have demonstrated that per-
sonality influences directly how people experience the world
[28]. Hence, we believe that there is an opportunity to better
understand the user’s interaction with technology by taking
into account his/her personality profile.
Personality profiles are typically assessed by means of sur-
veys. Goldberg [17]’s Big Five model is one of today’s most
well-known, accessible—and of public domain—and empir-
ically validated personality assessment models. It structures
a personality profile into five factors (or traits): Extroversion,
1
Adapted from en.wikipedia.org/wiki/User_experience,
last retrieved September 2012.
Agreeableness, Conscientiousness, Emotional Stability, and
Intellect (also known as Openness). The five factor model
is not only well known in Personality Psychology, but also
extensively used by the HCI community [25, 14, 6].
Our proposed model aims at explaining the customer’s satis-
faction with basic mobile phone services by means of his/her:
(1) personality traits, (2) perceived usability of the services,
and (3) actual usage of these services. Figure 1 depicts the
model with references to prior work related to each of the
five hypothesized relationships among the different concepts.
Detailed explanations on relationships 4 and 5 from Figure 1
are out of the scope of this paper. Next we therefore concen-
trate on presenting prior art that sheds light on the first three
hypothesized relationships.
Personality
[Goldberg, 1992]
Personality
[Goldberg, 1992]
Behavior
Behavior
Perceived Usability
[Rogers et al., 2011]
Perceived Usability
[Rogers et al., 2011]
Customer Satisfaction
[Oliver, 1997]
Customer Satisfaction
[Oliver, 1997]
Davis, 1989
Frøkjær et al., 2000
Hornbæk & Law, 2007
Heo et al., 2009
Niklas & Strohmeier, 2011
Turel and Serenko, 2006
Sathish et al., 2011
Sawng et al., 2011
Ryckman 2004
Lee and Nass, 2003
Hendriks et al., 2006
Alsajjan, 2010
Ryckman 2004
Lee and Nass, 2003
Graziola et al., 2005
Devaraj et al., 2008
Antoniou & Lepouras, 2010
Paunonen & Ashton, 2001
Saati et al., 2005
Khan et al., 2008
Butt & Phillips, 2008
Arteaga et al., 2010
Oliveira et al., 2011
Zhou & Lu, 2011
3
1
2
4
5
Figure 1. Proposed conceptual model. References that address each
relationship are indicated onto the corresponding arrow or ellipse.
Relationship 1: Perceived Usability of mobile phone ser-
vices influences the customers’ satisfaction with them. Us-
ability goals (e.g., effectiveness, efficiency, learnability) have
been said to be positively correlated with how people evalu-
ate their user experience with technology (e.g., satisfying, en-
joyable) [29]. However, these correlations depend in a com-
plex way on the application domain, the user’s experience
and the context of use [16]. Additionally, effectiveness, ef-
ficiency and satisfaction should be considered to be different
goals [16, 22]. These recent findings motivate the study of
our hypothesis in the case of mobile services. In this regard,
Heo et al. [21] created a framework to evaluate the usability
of mobile services, and showed that there were correlations
between usability and user experience constructs, such as sat-
isfaction. Another support for this hypothesis comes from the
Technology Acceptance Model [11] that has been adapted to
the specific case of mobile services [27]. In both cases sig-
nificant correlations between usability goals and user satis-
faction were found. In this paper we investigate the impact
of perceived usability on customer satisfaction with mobile
phone services.
Relationship 2: Mobile phone usage influences customer
satisfaction with mobile phone services. The way cus-
tomers use mobile technology influences their experience of
the mobile services they use. Turel & Serenko [34] worked
on a model that incorporated self-reported behavioral ac-
counts of mobile service usage. They found that it was
possible to use these measures to benchmark service opera-
tors in terms of customer satisfaction and loyalty. Similarly,
Sawng et al. [33] worked on a model that included social ben-
efits, satisfaction and service risks and that could be used to
predict customer behavior when using mobile phone services.
In market research, behavioral patterns are typically used to
predict switching to a different operator (i.e., churn). For
instance, Sathish et al. [32] studied the factors that affected
churn decisions in India. They found that self-reported call
frequency was among the most important factors in determin-
ing whether customers were satisfied with their carriers. In
this paper, we investigate the impact that actual—as recorded
by the operator—mobile phone usage has on customer satis-
faction with mobile services.
Relationship 3: Personality influences the perception of
usability of mobile phone services. Many researchers have
worked on the relation between personality and the measures
that are usually taken into account to define the usability of
a system. Ease of use and usefulness were studied by De-
varaj et al. [13], who conducted a study with 180 new users
of a collaborative technology and found correlations between
the personality dimensions and the perceived usefulness and
ease of use. Other related measures of usability have been
studied for mobile services. Antoniou & Lepouras [5] worked
on an adaptive mobile museum guide and showed that per-
sonality traits are related to the acceptance of the adaptivity
dimensions of the service. A similar study was conducted by
Graziola et al. [19], who found a relation between person-
ality traits and the user’s preferences of interface modality.
Our work builds on these previous findings and investigates
whether and how they hold in the context of the proposed
model.
METHODOLOGY
According to Rogers et al. [29], usability testing has been in-
creasingly performed remotely, thus allowing services to be
evaluated with larger samples and improving ecological va-
lidity by keeping participants in their own environment. Fur-
thermore, Nielsen & Levy [26]’s work on the relationship be-
tween self-reported measures and objective measures of us-
ability have encouraged the community to also consider mea-
suring usability in a subjective manner. We therefore opted
for measuring both usability and user satisfaction using an
online survey approach. Participants were recruited via email
from an online panel with members living in Mexico and who
satisfied two filtering criteria: they all owned a Telefonica
2
pre-paid mobile phone number, and were using basic mo-
bile phone services for at least the past six months (i.e., calls,
SMS, MMS, and basic GPRS/3G related services). The on-
line survey had two main sections. The first section included
50 questions [1] to assess their personality traits according to
the Big Five model (i.e. extroversion, agreeableness, consci-
entiousness, emotional stability and intellect) [17], whereas
the second section collected the participants’ opinions about
the basic mobile phone services that they were using.
2
Telefonica S.A. is currently the 3rd largest telecommunication
company worldwide with over 300 Million customers (21 Million
in Mexico). See www.telefonica.com for further details.
Measures. Items were measured either subjectively or ob-
jectively. A total of seven constructs were created from sur-
vey items and hence subjectively measured: extroversion,
agreeableness, conscientiousness, emotional stability, intel-
lect, perceived usability, and satisfaction with mobile phone
services. Each of the five personality traits were captured by
10 survey items that were later grouped into personality facets
using Goldberg’s [18] classification (shown in Table 1). This
was performed by computing summated scales for each facet,
i.e., summating all positive survey items and reversed neg-
ative items related to the same facet. For instance, if one
participant gave the ratings 2, 8, and 7 to the survey items
q8r, q33, and q43 respectively (see Table 1), then the sum-
mated scale for his/her Orderliness personality facet would
be: (10 − 2) + 8 + 7 = 23. The remaining two subjec-
tively measured factors—customer satisfaction and perceived
usability—were assessed in relation to the mobile services
contracted by the participants (phone calls, messages, i.e.
SMS and MMS, Internet access and operator’s mobile Web
portal). Finally, mobile phone usage was the only factor com-
posed of items that were measured objectively: the total num-
ber of mobile phone calls made/received between January
and June 2010, the total duration of phone calls, and the to-
tal number of messages sent/received during the same period.
Table 1 summarizes data and constructs used in the study.
Participants. A total of 603 valid responses (male: 50.2%,
controlled for a balanced distribution) were obtained in the
final study. Participants’ age ranged between 18 and 35 years
old (¯x = 25.87, s = 5.25)—as per our invitation filtering
criteria—and they predominantly belonged to the middle so-
cioeconomic class. The majority reported using computers
(93.4%) and the Internet (92.4%) at least once a week. In
terms of mobile phone use, 81.6% reported using their mo-
bile phone everyday and 14.8% several times a week. Based
on their mobile phone call data, participants made or received
an average of 101 calls per month and sent or received an av-
erage of 171 messages per month.
Data analysis. The conceptual model depicted in Figure 2—
note that we expanded the personality variable from Figure
1 into the Big Five traits—was evaluated using Structural
Equation Modeling (SEM) [7]. We highlight at least three
reasons for using this approach: (1) SEM models relation-
ships between concepts given that its objective function max-
imizes the probability of predicting the covariance matrix in-
stead of predicting values of a certain variable; (2) SEM takes
measurement unreliability into account by modeling equa-
tion errors and non-measurable concepts—e.g., extroversion,
satisfaction—as latent variables, thus avoiding unrealistic as-
sumptions of error-free measurements; and (3) SEM allows
researchers to leverage previous knowledge given that it uses
confirmatory rather than exploratory factor analysis.
The conceptual model was evaluated using Maximum Like-
lihood (ML) estimation and the data was bootstrapped (1000
samples) to meet the estimation’s assumption of joint mul-
tivariate normality of observed variables [7]. The SEM esti-
mation process was split in two steps as recommended by An-
derson and Gerbing [4]. First we developed a measurement
model, i.e. relationships between each factor construct—
e.g. usability—and its corresponding items—e.g. efficiency
and easy of use. Then we estimated the structural paths—
e.g. between factors usability and satisfaction. The measure-
ment model was evaluated for uni-dimensionality, reliability,
convergent and discriminant validity. Finally, the hypothe-
sized structural paths between constructs were included in the
model for the final estimation.
RESULTS AND DISCUSSION
Figure 2 depicts the validated conceptual model with the most
relevant statistics. Fit measures like SRMR (.05), RMSEA
(.05), CFI (.94), and PRATIO (.80) reveal that our model has
a good fit according to widely accepted cutoff criteria [23,
7]. Next we discuss only those results related to the influence
of perceived usability on customer satisfaction, and how one
can leverage the findings of the model in order to propose new
design solutions for basic mobile phone services that encom-
passes both usability and UX goals.
F1. Extroversion
F1. Extroversion
F2. Agreeableness
F2. Agreeableness
F3. Conscientiousness
F3. Conscientiousness
F4. Emotional Stability
F4. Emotional Stability
F5. Intellect
F5. Intellect
F8. Mobile Phone Usage
F8. Mobile Phone Usage
.16 (.09)
.03 (.05)
.04 (.07)
-.03 (.06)
-.07 (.08)
F6. Perceived Usability
F6. Perceived Usability
.29 (.11)
.06 (.07)
.25 (.09)
-.01 (.08)
.01 (.10)
F7. Satisfaction
F7. Satisfaction
.47 (.07)
.04 (.10)
-.07 (.06)
.14 (.08)
.01 (.06)
-.19 (.07)
-.11 (.04)
R
2
=.25 (.05)
R
2
=.28 (.05)
R
2
=.03 (.02)
.82 (.04)
.61 (.04)
err
err
err
err
ease of useefficiency
R
2
=.38R
2
=.67
Figure 2. Validated conceptual model. Standardized loadings next to the
corresponding arrows with standard errors in parenthesis (bootstrap-
ping to 1000 samples). Significant paths (p < .05) indicated by solid
black arrows and non-significant paths indicated by grey dashed arrows.
Error variables and covariance paths omitted for clarity.
Perceived usability positively influences customer satis-
faction with mobile phone services. The validated concep-
tual model corroborated that the usability of mobile phone
services is positively correlated with the customers’ satisfac-
tion with these services (β
76
= .47; p = .002). The stan-
dardized direct effect of perceived usability on satisfaction
was .47, which means that when usability goes up by 1 stan-
dard deviation, satisfaction goes up by .47 standard devia-
tion, and hence has a very strong influence on it. In fact, this
is the strongest direct influence present in the model. With
Table 1. Construct factors and associated items captured subjectively by the survey and objectively by the mobile phone operator.
Construct Factor
Item code
Summated item
Item name
Survey
code
a
Item description in English / Item description in Spanish (used in the survey)
Removed from
the model
g
Extroversion
b
x1
Gregariousness
q1
q6r
q16r
q21
q31
q36r
q46r
Am the life of the party / Soy el alma de la fiesta
Don't talk a lot / No hablo mucho
Keep in the background / Prefiero mantenerme al margen
h
Start conversations / Comienzo las conversaciones
Talk to a lot of different people at parties / En las fiestas hablo con muchas personas diferentes
Don't like to draw attention to myself / No me gusta llamar la atención
Am quiet around strangers / Cuando estoy entre desconocidos me mantengo callado
x2
Poise
q11
Feel comfortable around people / Me siento cómodo con la gente
x3
Leadership
q26r
Have little to say / No tengo mucho que decir
x4
Provocativeness
q41
Don't mind being the center of attention / No me importa ser el centro de atención
Agreeableness
b
x5
Understanding
q2r
q17
q22r
Feel little concern for others / Me preocupo poco por los demás
Sympathize with others' feelings / Soy sensible hacia las emociones de otros
Am not interested in other people's problems / No me interesan los problemas de otras personas
x6
Warmth
q7
q32r
q37
q42
q47
Am interested in people / Me intereso por la gente
Am not really interested in others / En realidad no me intereso por los demás
Take time out for others / Dedico tiempo a los demás
Feel others’ emotions / Siento las emociones de los otros
Make people feel at ease / Hago sentir cómoda a la gente
x7
Pleasantness
q12r
Insult people / Ofendo a la gente
x8
Nurturance
q27
Have a soft heart / Tengo un corazón sensible
Conscientiousness
b
x9
Conscientiousness
q28r
Often forget to put things back in their proper place / A menudo olvido poner las cosas en su lugar
x10
Orderliness
q8r
q33
q43
Leave my belongings around / Dejo mis pertenencias en cualquier lado
Like order / Me gusta el orden
Follow a schedule / Hago un programa y lo sigo
x11
Organization
q13
Pay attention to details / Pongo atención en los detalles
x12
Efficiency
q23
q48
Get chores done right away / Realizo mis tareas inmediatamente
Am exacting in my work / Soy perfeccionista en mi trabajo
x13
Purposefulness
q3
q18r
q38r
Am always prepared / Siempre estoy preparado
Make a mess of things / Soy desordenado
Shirk my duties / Evado mis obligaciones
Emotional Stability
b
x14
Stability
q4r
q24r
q29r
q34r
Get stressed out easily / Me estreso con facilidad
Am easily disturbed / Me molesto fácilmente
Get upset easily / Me disgusto con facilidad
Change my mood a lot / Cambio mucho de humor
x15
Tranquility
q9
q39r
Am relaxed most of the time / Estoy relajado la mayor parte del tiempo
Have frequent mood swings / Tengo cambios frecuentes de estado de ánimo
x16
Happiness
q14r
q19
q49r
Worry about things / Me preocupo por todo
Seldom feel blue / Rara vez me siento triste
Often feel blue / Me siento triste frecuentemente
x17
Calmness
q44r
Get irritated easily / Me irrito fácilmente
Intellect
b
x18
Intellect
q5
q20r
q40
Have a rich vocabulary / Tengo un vocabulario amplio
Am not interested in abstract ideas / No me interesan las ideas abstractas
Use difficult words / Utilizo palabras difíciles
x19
Creativity
q10r
Have difficulty understanding abstract ideas / Me cuesta entender ideas abstractas
x20
Imagination
q15
Have a vivid imagination / Tengo mucha imaginación
x21
Ingenuity
q25
q30r
q50
Have excellent ideas / Tengo excelentes ideas
Do not have a good imagination / No tengo una buena imaginación
Am full of ideas / Estoy lleno de ideas
x22
Quickness
q35
Am quick to understand things / Soy rápido para entender las cosas
x23
Introspection
q45
Spend time reflecting on things / Dedico tiempo a reflexionar
Usability
c
x24
Ease of Use
q51
I find it easy to make mobile phone services do what I need /
Me resulta fácil conseguir que los servicios de telefonía celular hagan lo que necesito
x25
Efficiency
q52
Using mobile phone services saves my time /
Utilizar los servicios de telefonía celular me hace ahorrar tiempo
Satisfaction
x26
General Satisfaction
d
q53
What is your general satisfaction level with the mobile phone services that you are paying for?
¿Cuál es tu nivel de satisfacción general con los servicios de telefonía celular que estás pagando?
x27
Expectations Met
e
q54
How do you think the mobile phone services that you are paying for meet your expectations? /
¿Cómo consideras que los servicios de telefonía celular que estás pagando cumplen con tus expectativas?
x28
Ideal Mobile Services
f
q55
How close are the mobile phone services that you are paying for to your ideal mobile services?
¿Dónde consideras que se encuentran los servicios de telefonía celular que tienes contratados con
respecto a tu ideal de servicios de telefonía celular?
Mobile Phone Usage
X29
Calls
N/A
[not survey]: Number of mobile phone calls made/received between January and June 2010
x30
Duration of calls
N/A
[not survey]: Total duration of mobile phone calls made/received between January and June 2010
x31
Messages
N/A
[not survey]: Number of phone messages (SMS, MMS) sent/received between January and June 2010
a
Numbers in item code indicate the order of appearance in the survey while the letter “r” indicate the item is reversed.
b
Associated survey items measured in a 9-point scale ranging from 1: “almost never” and 9: “almost always” as suggested by Goldberg (1992).
c
Associated survey items measured in a 9-point scale ranging from 1: “strongly disagree” and 9: “strongly agree”.
d
Measured in a 9-point scale ranging from 1: “completely not satisfied” and 9: “completely satisfied”.
e
Measured in a 9-point scale ranging from 1: “don’t meet my expectations at all” and 9: “meet all of my expectations”.
f
Measured in a 9-point scale ranging from 1: “very far” and 9: “very close”.
g
Item-analysis suggested that personality facets measured by one survey item were violating unidimensionality of their corresponding factors and should therefore be removed. Furthermore,
convergent validity analysis and subjective inspection of questions pointed out that the extroversion factor should be improved by removing items q16r and q36r.
h
When reusing the Spanish translation, change this item for: “Intento no llamar la attención” as suggested by Cupani (2009).
respect to the key usability goals that defined customer sat-
isfaction, service efficiency came in first place (R
2
= .67),
followed by ease of use (R
2
= .38). The model changed
significantly when usability loadings for these variables were
constrained to be equal (χ
2
/df = 8.813, p = .003). These
results indicate that the efficiency of basic mobile phone ser-
vices might be the most important usability goal determining
user satisfaction—in the context considered herein.
Mobile phone usage influences customer satisfaction with
mobile phone services. According to our model, this influ-
ence is rather negative (β
78
= −.11; p = .005), meaning
that the more one uses basic mobile phone services, the less
satisfied s/he is with them. One possible explanation of this
finding is that technology consumption might have a satura-
tion point. Satisfaction could be maintained up to a point
where the given technology addresses people’s needs without
compromising their daily routines and personal values. If by
overusing mobile services one jeopardizes these routines and
values, then dissatisfaction might be a natural outcome due
to several reasons, e.g., realizing that too much time is being
wasted using them, creating anxiety to keep up with the flow
of messages and calls, etc. Note that the construct factor for
Mobile Phone Usage comprised more information about syn-
chronous disruptive activities like phone calls (R
2
= .94) and
their durations (R
2
= .83), than about sent/received asyn-
chronous text messages (R
2
= .45). Therefore, the mo-
bile phone usage patterns as captured by our model include
mostly activities that can break daily routines and hence be
more susceptible to the argument of technology consumption
saturation point. While previous work demonstrated the exis-
tence of a link between usage behavior and satisfaction with
mobile services [34, 33], our work goes one step further by
finding that these are negatively linked (and quantifying the
relationship), suggesting a possible explanation, and consid-
ering actual mobile phone usage as captured by the mobile
operator.
Personality influences the perception of usability of mo-
bile phone services. More specifically, extroversion (β
61
=
.29; p = .004) and conscientiousness (β
63
= .25; p = .006)
had significant effects on perceived usability of mobile phone
services. The interpretation of this finding is grounded on be-
havior theories associated to personality traits. If today’s mo-
bile phone services are useful to shorten distances between
people and allow them to efficiently interact more often, it
is expected that extroverts—who interact with peers more
frequently—will recognize such qualities and hence highly
evaluate these services’ usability. Likewise, if these services
indeed help people save time, one would expect that those
who care about efficiency when following daily schedules—
i.e., people with high scores on the conscientiousness trait—
would positively rate the services’ usability. We cannot di-
rectly compare our work with previous models because these
studies do not group usability goals into one single factor [33,
35]. However, our work offers synergic findings by revealing
that extroversion and conscientiousness have a significant ef-
fect on the usability construct (composed of efficiency and
ease of use).
Limitations of the Study
As described in the methodology section, the conceptual
model from Figure 2 was validated using data from 603 sub-
jects living in Mexico with an age range of 18-35 years old,
who had a pre-paid cellphone, and were using mobile services
for at least six months (calls, messages and basic GPRS/3G
related services). Our findings can therefore be safely gen-
eralized to this sample profile only (CL = 95%; margin of
error: ±4%). Note that pre-paid mobile phone services are
predominant in developing economies, but it is not in the de-
veloped world. Future work should verify whether the model
also holds for smartphone users with unlimited data plan.
FROM THEORY TO PRACTICE
The conceptual model validated in the previous section con-
tributes to our understanding of how software engineers
and HCI practitioners could improve customers’ satisfaction
based on more clear usability goals. For example, the per-
ceived usability of the basic mobile phone services used by
our participants was the most important factor when explain-
ing customer satisfaction. Moreover, the concept of usability
was mostly characterized by efficiency (R
2
= .67) rather than
ease of use (R
2
= .38), thus highlighting an important trend
for satisfaction. Note that saving people’s time is a recurrent
result from our research as mobile phone usage had a signif-
icant negative effect on satisfaction. Next, we propose three
design solutions:
First, project managers in charge of developing new mobile
communication services should focus their efforts on design-
ing more efficient solutions that minimize disruption of the
users’ routine. For instance we can think about leaving the
possibility to request statements of the monthly bill or per-
forming operations on the contract such as enabling (or dis-
abling) options of the call plan via SMS or email instead of
requesting the customers to go through call centers that too
often require an enormous effort from their side. In terms of
minimizing routine disruption, the user’s contextual informa-
tion could be leveraged in order to identify the most suitable
periods of the day for sending them notifications or contact-
ing them.
Second, personalized services could be created to help users
with low scores on the extroversion and conscientious-
ness traits better manage their time when overusing mobile
phones. For example, less organized people could overuse
mobile services during a certain time period without planning
much for the additional costs and end up with an unpleasant
surprise when receiving their monthly bill. Mobile services
with personality-based user models could help these “less or-
ganized” users by sending them periodic feedback on how
much they have spent with phone calls and text messages,
and how close they are to their preferred maximum expense.
Recent work by Cherubini et al. [9] has revealed that the
lack of personalization is actually one of the biggest barriers
for the adoption of today’s mobile phone contextual services.
Although related mostly to basic mobile phone services, our
findings are in agreement with these conclusions and further
identify new opportunities for personality-based personaliza-
tion. We expect their practical relevance to increase as tech-
niques for the automatic assessment of personality are more
accurate and pervasive [24, 12].
Finally, mobile services should identify and provide aware-
ness of the user’s saturation point when consuming mobile
phone services. Persuasive techniques (e.g., social support,
reminders, etc.) are relevant in this context towards prevent-
ing mental/physical stress and hence low satisfaction.
ACKNOWLEDGMENTS
Telefonica Research participates in the Torres Quevedo sub-
program (MICINN), cofinanced by the European Social
Fund, for researchers recruitment.
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