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African Journal of Business Management Vol. 6(2), pp. 573-577, 18 January, 2012
Available online at http://www.academicjournals.org/AJBM
DOI: 10.5897/AJBM11.1940
ISSN 1993-8233 ©2012 Academic Journals
Full Length Research Paper
Are mobile phones the 21st century addiction?
Richard Shambare*, Robert Rugimbana and Takesure Zhowa
Tshwane University of Technology, South Africa.
Accepted 16 September, 2011
The mobile or cell phone has become the 21
st
century icon. It is ubiquitous in the modern world, as an
on-the-go talking device, an internet portal, a social networking platform, a personal organizer, and
even a mobile bank. In the information age, it has become an important social accessory. Since it is
relatively easy to use, portable and affordable, its diffusion continues to surpass that of other ICTs.
Research increasingly suggests cell phone usage to be addictive, compulsive and habitual. Students
are among the heavy users of mobile technologies, and accordingly, a 33-item questionnaire measuring
addictive and habitual behaviour was administered to a sample of students. Results indicate that
indeed mobile phone usage is not only habit-forming, it is also addictive; possibly the biggest non-drug
addiction of the 21
st
century.
Key words: Addiction, dependency behaviour, cell phones, mobile phones, youths.
INTRODUCTION
As the popularity of ICT-driven communication increases,
mobile phone usage has been tipped into mainstream
culture. This is particularly true for young adults, who
increasingly consider mobile phones as part of their being
and identity (Hooper and Zhou, 2007; Madrid, 2003).
Past studies demonstrate that young adults and students
use cell phones for various purposes including Facebook,
and students spend at least three hours every day on
their Facebook accounts using mobile phones (Mvula
and Shambare, 2011).
Given the widespread adoption of mobile phones,
many researchers have posited that their use is addictive,
compulsive, dependent and habit-forming (Aoki and
Downes, 2003; Hooper and Zhou, 2007; Madrid, 2003).
Madrid (2003) particularly asserts that “mobile phone
usage is a compulsive and addictive disorder which looks
set to become one of the biggest non-drug addictions in
the 21
st
century”.
Despite this, very little research attention has focused
on this phenomenon, and even less has tested these
claims empirically. It is against this background that the
research reported on in this article investigated these
claims by testing whether mobile phone usage is indeed
addictive, compulsive and habitual. To achieve this, a
*Corresponding author. E-mail: shambarar@tut.ac.za.
mobile phone usage questionnaire developed by Hooper
and Zhou (2007) to measure addictive, compulsive and
habitual behaviour was tested on a sample of South
African students.
Since students usually take the lead in adopting
technological innovations, including mobile phone usage
(Rugimbana, 2007), a student population was considered
ideal.
Hooper and Zhou (2007) consider mobile phone usage
as having a mobile phone and using it to communicate by
means of calling or sending text messages commonly
known as SMSs.
For practical purposes, this definition was adopted for
the purposes of this research. Mobile phone usage is a
distinct consumer behaviour, the implications of which
are potentially valuable to a multiplicity of disciplines
including marketing and education.
For educators, understanding how and why students
use cell phones can provide them with knowledge not
only to facilitate learning, but to discover means of
embracing the technology in the classroom (Bicen and
Cavus, 2010; Carter et al., 2008; Mvula and Shambare,
2011). On the other hand, marketers may gain valuable
insight into using mobile phones as a medium for
advertising as well as marketing mobile phones.
Past research has identified numerous types of be-
haviour associated with mobile phone usage. Therefore,
this study concerned itself with the identification of these
574 Afr. J. Bus. Manage.
types of behaviour and the respective underlying moti-
vations for that behaviour. In other words, the objectives
of the research were to:
1. determine whether the types of behaviour, according to
Hooper and Zhou (2007), are identifiable in the context of
a developed nation such as South Africa
2. categorize mobile phone usage according to the
typologies identified in the latter study, based on the
underlying motivations
The remaining sections of the paper are structured as
follows: Firstly, the literature pertaining to mobile phone
usage is reviewed in the following section. Secondly, the
methodology employed to answer the research questions
is presented. Results are then discussed. Finally, the
paper concludes with implications of these findings, as
well as suggested topics for future research.
LITERATURE REVIEW
To appreciate mobile usage, the study considers a
multidisciplinary review of the literature. Following on
from Maslow’s motivation model, Hooper and Zhou
(2007) posit that human behaviour can be viewed as the
actual performance of behavioural intentions driven by
certain underlying motives. This view appears to be
consistent with adoption theories such as Ajzen’s theory
of planned behaviour (1991) and Davis’s technology
acceptance model (1989). Basically, these models
propose that product attributes (for example, relative
advantage, perceived ease of use, or perceived
usefulness) influence behavioural intention, which in turn
initiates behaviour (Taylor and Todd, 1995).
Motivation for mobile phone usage
Although mobile phones were initially used as
communication devices, today, they are a 21
st
century
icon that performs multiple roles (Garcia-Montes et al.,
2006). Mobile phones can represent a bank if used in
mobile banking (Jayamaha, 2008), a camera, personal
organizer, a calculator and a social networking device
(Bicen and Cavus, 2010). Aoki and Downes (2003)
further argue that a mobile phone is no longer a phone
linked to a space but rather a phone linked exclusively to
an individual (Boyd and Ellison, 2008; Mvula and
Shambare, 2011). Further, some of the more common
motivations for mobile phone usage are discussed.
Social interaction
Mobile phones are used for social interaction. Adopters
use them to stay in touch with friends and family (Aoki
and Downes, 2003). Improved mobile telephony and
technological advancement also guarantee mobile
subscribers the freedom to use the Internet, email, social
media such as Twitter and Facebook. Because of the
wide array of features, mobile phones are ideal social-
interaction tools.
Dependency
Following adoption, users become more comfortable
using cell phones. Rogers (1995) identifies this as
‘commitment’ to using an innovation. In other words, as
adopters begin using mobile phones regularly they
become part of the users’ lives to such an extent that the
users feel lost without them (Hooper and Zhou, 2007).
Image and identity
Mobile phones may also be considered as status
symbols. In particular, Shambare and Mvula (2011)
assert that South African students adopt mobile phones
to use on Facebook, simply because their friends use cell
phones for Facebook. Hence, Wilska’s findings (2003)
propose mobile phone usage as being addictive, trendy
and impulsive.
Behaviour associated with mobile phone usage
From these motives, the literature identifies six types of
behaviour associated with mobile phone usage. These
are habitual, addictive, mandatory, voluntary, dependent
and compulsive behaviour (Hanley and Wilhelm, 1992;
Hooper and Zhou, 2007; Madrid, 2003; O’Guinn and
Faber, 1989), and they are further discussed in detail.
Addictive behaviour
Hanley and Wilhelm (1992) define addictive behaviour as
any activity, substance, object, or behaviour that has
become the major focus of a person's life to the exclusion
of other activities, or that has begun to harm the
individual or others physically, mentally, or socially.
Addictive behaviours in general are a means of improving
feelings of low self-esteem and powerlessness (O’Guinn
and Faber, 1989). In the context, therefore, increased
attention, uncontrollable, and involuntary use of cell
phones by subscribers can be regarded as an addiction.
Compulsive behaviour
O’Guinn and Faber (1989) argue that compulsive
behaviour is behaviour that is repetitive that the
concerned individual usually experiences a strong urge to
continuously perform the behaviour. The behaviour is
Shambare et al. 575
Table 1. Demographic profile.
Demographic characteristics Percent
Gender Male 29
Female 71
Education level High school 42
University diploma/degree
26
Postgraduate 32
Mobile phones owned One 64
Two 28
Three or more 8
Mobile phone experience
< 1 year 7
1
–
3 years
15
3 – 5 years 10
5+ years 68
typically very difficult to stop and ultimately results in
harmful economic, psychological, or societal
consequences.
Dependent behaviour
Dependent behaviour is different from addiction in that it
is often motivated by the attached importance of a social
norm (Hooper and Zhou, 2007). In this context, it is not
addiction of mobile phone usage, but the attached
importance of communication.
Habitual behaviour
Many behaviours that people perform regularly can be
characterized as habits, since they are performed with
little mental awareness (Biel et al., 2005). These are
initiated by environmental cues in a given situation which
call for individuals to act. The cues send signals to an
established habit which corresponds to behaviour in a
given situation.
Voluntary behaviour
Unlike habitual and addictive behaviour, voluntary
behaviour is reasoned behaviour which is driven by
specific motivations.
Mandatory behaviour
Mandatory behaviour is defined as behaviour needing to
be done, followed, or complied with, usually because it is
officially required (Aoki and Downes, 2003), or parentally
mandated. In terms of motivation, mandatory behaviour is
usually driven or prompted by environmental
consequences (Aoki and Downes, 2003).
Research objectives
To achieve the research objectives, the following
research question was formulated:
RQ: What types of behaviour are associated with mobile
phone usage?
RESEARCH DESIGN
A survey method was used to collect data from students in Pretoria,
using non-probabilistic sampling methods (Kerlinger and Lee,
2000). Four undergraduate students, trained as research
assistants, administered the instrument to participants.
Sampling and sample size
The non-probabilistic sampling technique was utilized, and to
ensure a more representative sample consisting of students at all
study levels, both high school and university students were
surveyed (Calder et al., 1981). While these two groups may appear
to represent two separate populations, past studies (Livingstone,
2008) focusing on young consumers have tended to combine
consumers under 35 years old as one population group. The choice
for including the entire spectrum of students stems from the latter
views. Research assistants were positioned at strategic locations,
near schools and libraries, where they approached students to
participate in the study. The demographic characteristics of the
sample are illustrated in Table 1. A majority, some 71% of
respondents were female. By education level, 42% were high
school students, some 26% university students at undergraduate
576 Afr. J. Bus. Manage.
Table 2. Three-factor solution of mobile usage responses.
Variable Factor 1 (Dependent) Factor 2 (Habitual) Factor 3 (Addictive) Communalities
D5
0.840 0.721
M1
0.803 0.777
D1
0.783 0.687
D2
0.781 0.715
D3
0.765 0.712
D4 0.754 0.657
H3 0.828 0.727
H2
0.762 0.657
H1 0.722 0.584
H5 0.712 0.548
H4 0.695 0.629
A3 0.751 0.620
A2
0.737
0.629
C1 0.726 0.640
A1 0.633 0.454
A4 0.598 0.482
Eigenvalues
6.954 2.214 1.713 (Total)
Percentage of variance
26.065 18.209 16.181 60.455
Cronbach’s alpha (α)
0.915 0.832 0.788
level; the remaining 32% of participants were postgraduate
students. A significant proportion (64%) owned one cell phone and
about a quarter (28%) owned two cell phones. Some 8% indicated
they owned and used three or more cell phones. Cell phone
experience, as expected was very high, a vast majority of 68 per
cent indicated that they had been using cell phones for at least five
years.
Respondents’ ages ranged from 14 to 38 years, yielding a mean
age of age of 20.67 years with a standard deviation of 2.94 years.
The K-S normality test was not significant (D = 1.279, p = 0.076),
suggesting that the sample followed a normal distribution.
Data collection
In total, 180 self-completion questionnaires were distributed to
willing participants. Of these, 104 questionnaires were returned but
only 93 were usable, representing a response rate of about 52%.
The remaining 11 instruments had too many missing values to be
useful.
Questionnaire
To measure mobile phone usage patterns, Hooper and Zhou’s
mobile phone usage scale (MPUS) (2007) was adapted and used
to collect primary data. In keeping with the research objective of
establishing whether cell phone usage is indeed addictive (Aoki and
Downes, 2003; Madrid, 2003), the questionnaire used by Hooper
and Zhou was considered most appropriate, as the latter study also
considered a sample of students. A pilot test was conducted with 10
undergraduate students to ensure that the content of the
questionnaire would be comprehensible to the target respondents
(Dwivedi et al., 2006).
RESULTS
This research question and the research objectives
sought to identify the types of behaviour associated with
mobile phone usage. It was also important to determine
whether students exhibited one type of behaviour more
than another or perhaps a set of behaviour types more
than others. The MPUS was used to answer this
question. Factor analysis was performed on the MPUS.
According to Hooper and Zhou (2007), the MPUS
contains six behaviour typologies, each represented by
the six subscales: habitual, mandatory, dependent,
addictive, compulsive and voluntary. These items are
supposed to load independently in six factors or
behaviour typologies.
Tests to determine the suitability of factor analysis were
all satisfactory (KMO = 0.831; Bartlett’s test of sphericity
χ
2
= 845.195; df = 153; p < 0.000). Subsequently, factor
analysis, with a principal component analysis (PCA) as
an extraction method, was performed. As shown in Table
2, a three-factor solution explaining 60 per cent of
variance was extracted. Factors were extracted on the
basis of having eigen values greater than one.
Dependency behaviour items loaded in Factor 1, habitual
behaviour items loaded in Factor 2, and addictive
behaviour items loaded in Factor 3. Table 2 illustrates
that the three-factor solution accounts for at least 60% of
the variance. Tests for internal consistency of items in all
three factors yielded satisfactory results, as all factors
had Cronbach’s alphas in excess of the 0.7 cut-off (Field,
2009).
DISCUSSION
This research sought to establish the types of behaviour
identifiable in mobile phone usage. A secondary objective
was to assess how students in a resource-poor context
compare to those in a resource-rich country. The
researchers attempted to categorize mobile phone usage
according to the typologies commonly identified in the
literature. While earlier studies posit six typologies, this
study found support for only three: dependency, habitual
and addictive behaviour. These results suggest that
mobile phone usage is dependency-forming, habitual and
addictive. For instance, such dependent behaviour is
exemplified by the overwhelming response to statements
like: “I often feel upset to think that I might be missing
calls or messages.” The reliability of each of the factors,
namely dependency, habitual and addictive behaviour,
was 0.915, 0.832 and 0.788, respectively. These are
comparable to those found by Hooper and Zhou (2007),
which were 0.842, 0.793 and 0.880, respectively. The
high reliability loadings of these factors indicate that the
three different types of behaviour are in themselves
distinct constructs. Future research could consider
looking at these constructs utilizing a different sample of
mobile users.
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