This article aims
to explore to what extent young people living in different kind of cities and
towns use the mobile phones similarly or not. The article relies on Georg
Simmel’s theory on urban everyday life and contemporary analyses on mobile
communication. According to them, the mobile phone is an urban phenomenon as it
responds best to the needs of hectic urban life. The article takes advantage of
quantitative survey data collected in 2005 (N=421). It consists of young people
aged 15 to 25 years living in urban and non-urban location in Finland. The
results show that the non-urban users are more active mobile ‘entertainers’ and
‘time-coordinators’ than those living in the urban environment. It is deducted
from the results that detected differences may stem from the lack of alternative
sources of amusement in the non-urban locations. On the other hand, longer
physical distances and a lack of public transportation may generate more need
for time-coordination in the non-urban areas.
1.1 Young people and mobile phones in Finnish society
The mobile phone
revolution has rapidly taken possession of Finnish society. In 2006, already
97% of all people owned a mobile phone in Finland (Nurmela,
Sirkiä, & Muttilainen,
2007, p. 40). Nevertheless, the extensive penetration of mobile handsets does
not yet indicate the total absence of disparities in the everyday use of mobile
phones. Even if the mobile phones have spread throughout society, the ways of
using mobile phones may create some differences, for instance, between regions
and generations. In Finland, there is evidence that young people,
the residents of metropolitan areas and other major cities stand out from the
rest regarding the use of new mobile services and the mobile internet (Nurmela & Ylitalo,
2003; Nurmela et al., 2004; Nurmela,
Sirkiä, & Muttilainen,
2007). The differences are not enormous, and it is also noticed that the
people of small municipalities are in some respects more active mobile phone
users than urban dwellers (Nurmela, J., Parjo, L., & Ylitalo, M.,
approaches this phenomenon from a within-country perspective. It explores to what
extent young people living in different kind of cities and towns use the mobile
phones similarly or not. In the study, the cities and towns are grouped into
two poles according to their level of urbanity. Firstly, the article aims to
find out what are the main patterns of mobile phone use among our respondents in
Finland. Secondly, the article aims to find out the extent of the resemblance
that the young people of urbanised cities and less-urbanised towns have with
each other as mobile phone users. Thirdly, the article tries to bring out the
factors predicting differences and similarities in mobile phone use between the
urban and the non-urban locations.
In terms of
sociological theory, the article is built on studies on urban ways of life and
those arguing for the urbanity of mobile phones as a sociological phenomenon
(e.g. Simmel, 1964; Kopomaa, 2000; Mäenpää, 2001;
Fortunati, 2002; Townsend, 2002; Okada, 2006). In these studies, urban space is
typically regarded as the most fertile location for experimental and versatile
mobile phone use. Being hectic, impulsive, and full of alternatives, urban
space may open up the possibility of more social situations and opportunities
for the inherent use of mobile communication technologies. In contrast to this,
the urban living environment contains several competing means and ways to spend
free time, have fun and socialize with other people.
From this starting
point, the study hypothesises that young people in urban cities employ mobile
phones to respond to the demands of a hectic and impulse-rich life. It is said that
the urban technology-mediated lifestyles are nomadic and require a lot of
temporal and spatial coordination (Kopomaa, 2000). Secondly, the article
hypothesises that the use of mobile phones for social and entertainment
purposes could be used more common in less-urbanised locations. In the less-urbanised
locations the mobile phones could be employed with the purpose of compensating for
the lack of physical proximity and alternative sources of entertainment. To
tackle these issues, the article takes advantage of quantitative survey data
collected in 2005 (N=421). The data consists of young people aged 15 to 25
years living in four cities and towns in Finland.
questions are set for the study. The questions are formulated to discover
similarities and differences in the use of mobile phones among young people,
and to explain possible variations between the urbanized and the non-urbanized
locations. The questions are as follows:
are the main patterns of mobile phone usage among our respondents?
the patterns of mobile phone use differ between the urban and the non-urban
factors explain the differences and similarities in the use of the mobile
phones between the two types of locations?
The first research
question is descriptive by nature and to some extent confirmatory. It addresses
the issue of whether the main patterns of mobile phone use are similar to those
found previously (O’Keefe and Sulanowski, 1995;
Fortunati & Maganelli, 1998). The second question
aims to discover potential differences between the two groups. In this case, the groups are formed by those young people residing in different
socio-cultural locations; some in rather urbanised and hectic cities and other
in less-urbanized small towns. The third research question is the most
challenging and explanatory. It tries to discover what are the determining
factors explaining differences and similarities in the patterns of mobile phone
usage between the two types of cities and towns.
2. Theoretical Background
2.1 Young people
and mobile phones in Finland
Despite the fact
that young experts and careerists were the first adopters of the technology in
most countries, young people have inspired sociologists as a subject of
research the most (Fortunati & Manganelli, 2002).
In this study, the term ‘young people’
is used to refer to 15 - 25 year-olds. Defining the term is essential, as
previous studies have pointed out that children, pre-teens, teenagers and
pre-adults use mobile phones quite differently. The ways of using the mobile
phone begin to diversify and become more complex during these particular years
and even at a younger age. Mobile use for entertainment, including all kinds of
off-line use, is challenged by more instrumental, affective and expressive uses
(Oksman & Rautianen,
2002; Castells et al., 2007). Until today, an array of studies about young
people of all ages has been carried out. Various aspects of texting culture,
relationships between parents and children, and security issues have been analysed
rather extensively, especially through qualitative methods. (e.g.
Kasesniemi & Rautiainen,
2002; Oksman & Rautiainen,
2002; Skog, 2002; Fortunati & Manganelli, 2002; Höflich & Rössler, 2002;
Green, 2002; Kasesniemi, 2003; Yoon, 2003; Ling,
In contrast, there
is a considerably smaller number of quantitative
approaches attempting to model the patterns of ICT use and identify their
antecedents (cf. Fortunati & Manganelli, 1998; Wilska, 2003; Miyaki, 2006).
Numeric accounts have mostly focused on ownerships rates, ‘early’ and ‘late
adopters’, mobile ‘haves’ and ‘have-nots’, the amount of mobile phone use, and the
relationship between mobile telephone and internet
use. (Leung & Wei, 1999; Rice & Katz, 2003; Davie,
Panting, & Charlton, 2004; Park, 2005). Much less is known about
differences in the patterns of mobile phone use, and whether they are related
to the socio-geographical locations of use (Fortunati, 2002; Campbell, 2007;
Castells, et al., 2007).
studies imply that young people use mobile telephones in the most varied manner
(Castells et al., 2007, 167). The results of Finnish studies also support this observation
(Kasesniemi & Rautiainen,
2002; Kasesniemi, 2003), although researchers have
also noted that a section of young people consider this type of social standing
to be a form of social burden, something hard to identify with (Coogan & Kangas, 2001). This
is to say that young people should not be considered to be a consistent mass of
ICT users, who are all in an equal position as mobile phone users. Those living
in the urban cities, particularly in metropolitan areas, are most likely to have
the greatest variety of mobile phone services ready at hand. For example, in
many countries, Finland included, urban dwellers have been the first to be
within the coverage area of the G3 mobile network that allows fast data
transmission, mobile internet, and a variety of new
To sum up, if we
only look at the mobile phone and service penetration rates it is not possible
to get the whole picture of equalities and inequalities in the use of the
mobile phones. The mobile phone ownership rates are showing high figures for
all age cohorts and for every part of the country (Nurmela
et al., 2007). In terms of ownership rates, only women aged 60-74 are slightly,
although not dramatically, lagging behind the rest of the population. At the turn
of the new millennium, it was noted that some Eastern and Northern provinces
register slightly lower increase rates in mobile phone ownership (Nurmela et al., 2000). In the absence of newer figures, it
can be still assumed that these provinces have since caught up.
2.2 The patterns
of usage and urban space
In which ways do
young people then use mobile telephones? What are the main patterns of usage according
to earlier literature? Fortunati and Manganelli (1998, pp. 141-149) have produced a three-part
classification, which typifies the use of information and communication
appliances, in a set of European countries. In their rather extensive survey
study three patterns of usage arose; facilitation of
social relationships, management of time, and entertainment. A few years earlier, O’Keefe & Sulanowski
(1995) were able to classify four patterns of phone use in their telephone survey targeted at three US
counties. The patterns identified by O’Keefe and Sulanowski
were similar to those of Fortunati and Manganelli.
They were used for sociability, time management, entertainment and acquisition.
From the perspective of sociological theory, there
is reason to believe that the different patterns of mobile phone usage respond
to the different needs of urban and non-urban life styles. For example, the use
of mobile phones for social relationship facilitation reminds us of
Georg Simmel’s (1962) analysis of urban sociability. Socialising with others is
a kind of necessity in everyday life as one tries to
prevent oneself from feeling the sense of alienation which is a result of the
increased individualization brought about by urban metropolitan life. At the
same time, the urban dweller must also be able to block out a part of the
overflowing sociability of the urban sphere of living, in order to maintain
some privacy. In other words, urban life is about sustaining an adequate level
of privacy amidst overwhelming sociability. Thus, the use of mobile phones for
social relation facilitation could be most beneficial for those who are lacking
social relations and the corporeal proximity of others. This is the case
particularly in non-urban, sparsely populated towns.
It is also argued that the urban sphere of life sets
new kind of requirements for temporal coordination. This is because various
everyday tasks (job, home, recreational activities etc.) are spatially and
temporally separated in urbanised societies. The
mobile phone is thus considered as a supplement and substitute to time as a
basis for coordination (Kopomaa, 2000; Townsend, 2002, p. 62; Ling, 2004, pp.
57-81). It combines several
previously separated coordination tools, such as a watch, alarm clock, calendar
and fixed phone. Richard Ling (2004, pp. 61-81) has applied the term ‘micro-coordination’
in this connection. The term is apt as
it describes the increased technological mediation in the arrangements of everyday life
by giving only a limited role to the mobile phone.
The mobile phone use for entertainment can also be linked
with the discourse of urbanity. The urban living-space
is full of stimuli. It contains several competing means and ways to spend free
time, have fun and socialize with other people (Simmel, 1964). It is not only
the mobile phone with a set of content services and mobile games, but also
restaurants, coffee shops, movie theatres, and amusement arcades that try to
persuade young people to have fun and spend time with their friends. The mobile
phone, as a means of entertainment, has to battle against these rivals everyday
in the urban space of living. Therefore, it may well be that the less urban mobile
users take more advantage of the mobile phone as the source of entertainment.
The mobile phone may be used to compensate for the relative lack of urban
entertainments, especially when it comes to the youngest users.
of mobile phone usage
have pointed out many determinants explaining variation in the ways of using
the mobile phones. Gender is perhaps the most studied aspect of mobile communication
in this respect. These studies indicate that the patterns of mobile phone use
differ to some extent between men and women. Women are more likely to use the mobile
telephone for facilitating social relationships whereas men are more
technology-oriented users (Ling, 2002; Castells et al., 2007, pp. 45-46). Among
the teenagers, boys seem to be more interested in the performance and
applications of the mobile phones whereas the girls are more curious about
design, colours and ring tones (Skog, 2002). There is also some empirical
evidence that women might use the mobile phones to a wider variety of purposes
than men (Puro, 2002).
Age seems to
modify the relationship between gender and mobile phones’ usage. In childhood,
differences between girls and boys in mobile phone usage are almost
non-existent (Kangas, 2002; Wilska,
2003). The younger users consider the mobile phone
more as a toy and a game-gadget. The instrumental or functional uses of the mobile
phone increase with age (Castells et al., 2007; Wilska
& Pedrozo, 2007). It is also noted that use for
temporal and spatial coordination increases with the age of young users.
For pre-adolescents, this kind of use is not as essential as it is for older
teenagers whose everyday schedules and social interactions are more complex
(Ling, 2004, p. 100). In addition to age and gender, earlier studies have found
out that the level of education predicts the use of ICTs as well. Education is one
of the most powerful predictors of digital divides within and between counties
(Räsänen, 2006; Wilska & Pedrozo, 2007).
The article is
based on quantitative survey data that was gathered through a postal survey in
March-April 2005. The target group consisted of 15-25 year-olds in four Finnish
cities and towns. The cities and towns were grouped into two pairs for the
purpose of analysis. Helsinki and Jyväskylä form the urban pole of the study
whereas Pori and Kuusamo are representatives of non-urban
locations. Although the division is in some respects rough, it is based on
several demographic and socio-cultural factors presented later. The questionnaire
was designed by combining some established question patterns from previous
survey studies with new components specifically framed for this survey. The
established question patterns were mainly adopted from studies carried out by
Statistic Finland (Tilastokeskus, 1999). Some
questions were also selected from the ‘Telecommunication and Society’ survey of
1996 (Fortunati and Manganelli, 1998; Fortunati,
were posted to 800 people, 200 from each city or town, in May 2005. Respondents
were selected through a random sampling that was carried out by the Population
Register Centre of Finland. The sampling was targeted at native Finnish
speakers only. Reminders were sent to the non-respondents a month later in
April 2005. The final response rate was 53 % (N=421).
illustrates the main characteristics of the data, and shows that the data
manifests the young age of the respondents in many ways. The respondent from
the urban and non-urban locations differ from each other mainly by the age and
the basic educational level of the respondents. As young people move to urban
cities to attain further education, it is apparent that the respondent of the
urban cities are also older and more educated. The data is slightly skewed by
gender as well. There are more men than women represented in the data set. In
other respects, the urban and non-urban users register rather similar figures.
More than 60 % of the respondents are pupils or students, more than 70 % are
residing with their parents and less than 20 % have their own children. However,
these structural differences are controlled when analysing the differences and
similarities in the patterns of mobile phone use between the urban and the
The study uses a range of statistical methods typical
to the social sciences. Regarding the first research question, the study
applies Principal Component Analysis (PCA) to reveal the factors - or more
precisely, principal components - typifying different patterns of mobile phone
use. PCA is extensively understood to be one type of factor analysis, even if these
two differ in terms of their conceptual foundations[i].
PCA like the common factor analysis, can be carried out with different rotation
models to find the most efficient way to group separate variables. In this
non-orthogonal rotation is used as it permits the inter-correlations of factors
(Tabachnick & Fidell,
2007, pp. 637-638). This is appropriate also in terms of theory as there is no
reason to believe that the different patterns of mobile phone usage would be
The study makes use
of the analysis of variance (ANOVA) when tackling the second research question.
One-way ANOVA is the simplest form of variance analysis as it includes only one
independent variable. In this study, all different patterns of mobile phone
usage, derived from PCA, are treated as independent variables one after
another. It is studied whether there is any difference between the urban and
non-urban users regarding the different patterns of mobile phone usage[ii].
As one-way ANOVA is only capable of pinpointing differences
between the groups, another method is needed to tackle the third research question which aims to discover the factors explaining
variation in usages between the urban and the non-urban users. Multiple Regression Analysis (MRA) allows us to control a
set of background variables and to find out which variables modify the relationship
between the patterns of mobile phone usage and the location of use. In MRA,
there is typically one dependent variable and its variation is explained with
two or more independent variables. In this study, the patterns of mobile phone
usage are used as dependent variables, and they are explained with the urbanity
of users and a set of other variables. MRA has also been successfully applied
in other mobile communication studied (e.g. Park, 2005; Miyata, et al., 2007).
MRA allows the controlling of background variables which
irons out many problems related to skewed data.
Helsinki and Jyväskylä
are regional growth poles and university cities. They form the urban pole of
the study. Helsinki is the only real metropolitan city of the country with some
560 000 inhabitants. Together with
the other cities of the metropolitan area, they cover a population of
approximately 1 million people. Helsinki is also the most densely populated
(3031 inhabitants/km2) city included in the study (deg. of urbanization
97 %). Jyväskylä is a notably smaller, medium-sized city of around 85 000
inhabitants. The population of Jyväskylä region rises to 150 000 when the
surrounding municipalities are included in the number. The urbanisation rate of
Jyväskylä (98.4 %) is even higher than in Helsinki but its population is not as
condensed (789 inhabitants/km2).
Pori and Kuusamo are representatives of non-urban locations as they share
some characteristics of de-industrialisation. Both are located quite far away
from the nearest growth poles. Although Pori’s household and income structure
is quite similar to Jyväskylä, it has suffered from more severe unemployment.
The possibilities for higher education are also much more limited in Pori than
in the two more urbanized cities. People also live more spaciously in Pori (151
inhabitants/km2). Kuusamo is clearly the
most non-urban location of the study and can be classified as a small-town by
its size, services, distances, culture and ways of life (Ojankoski,
1998). It is the least urbanized (61.6 %) and the most sparsely populated (31
inhabitants/km2) of the four research sites. (www.localfinland.fi,
2005). The cities and towns were selected into the survey to represent
geographical and economical diversity of Finnish municipalities.
4.1 Three patterns
of mobile phone usage
The first research
question aims to specify for what are the main patterns of mobile phone usage
among our respondents. The questionnaire included a multiple-choice pattern
that was planned to provide clarification about different ways of mobile phone
use. In this particular pattern, the respondents were asked to assess how often
they use the mobile phone in order to carry out twenty-two different kinds of
tasks (e.g. to keep in touch with your people; to ask and tell news; to gossip;
to play games; to take photos; to listen radio). The respondents were asked to
estimate each item according to the 5-point Likert-scale, where the choices varied from ‘never’ to ‘regularly
In general, a
Principal Component Analysis is used to summarise a large number of variables
into a few factors and to decrease the incoherence of the data set. First, all
twenty-two items of the multiple-choice pattern were added to PCA in order to
classify the different patterns of mobile phone usage. From the twenty-two
included items, altogether fourteen received remarkably high factor loadings
and communalities. Only these fourteen items were then included in the
subsequent analysis. In this second phase, principal component extraction with a
non-orthogonal promax-rotation produced the factors with
the greatest utility and interpretability. (Tabachnick & Fidell, 2007).
In this case, PCA produced three interpretable factors with eigenvalues greater
than 1.0. The factors and factor loadings are presented in Table 2. The factor loadings smaller than 0.575 were removed from the table
for the sake of clarity. The three factors explained approximately 53 %
of the total variance.
The first emerged
factor is termed ‘Sociability’. This factor received high loadings with
statements inquiring if the respondent uses the mobile phone in order to
contact friends and family members, tell news, delight others or inform others
of being late. Moreover a statement about the mobile use for arranging
appointments got a high loading with relation to this factor. Many of these
statements refer directly to mobile-mediated social relationships, while others
refer to arrangements contributing to sociability (e.g. informing others that
you are late). This factor explains approximately 32 % of the total variance.
The factor comes very close to what Fortunati and Manganelli (1998) call ‘the facilitation of social
second factor, statements asking about the use for gossiping, cheating, passing
time and playing games through the mobile phone got high loadings. This factor
is named ‘Entertainment’ as all the statements depict a kind of affective use,
instead of functional uses characterized by factors 1 and 3. According to previous
studies, this kind of use is most common to the youngest users (Kasesniemi & Rautiainen,
2002; Thulin & Vilhelmson, 2007). It is
also worth noticing that this factor may partially overlap with the first one. For
example, use for sociability may well include elements of entertainment and
passing time. Nevertheless, this factor alone explains slightly less than 12 %
of the total variance.
third factor, which is named use for ‘Time-coordination’, is perhaps the most
specified factor in content. It is loaded with statements inquiring about the
use of the mobile as an alarm clock and calendar, as well as to remind the user
himself with a note and alarm about important issues. Other statistical
accounts have also recognized this aspect of use as well (O’Keefe & Sulanowski,
1995; Fortunati and Manganelli,
1998), although it is most vividly discussed in qualitative studies as
part of the concept of micro-coordination. Ling’s (2004,
pp. 57-81) micro-coordination, however, is a much broader concept that refers
to spatial coordination of social activities too. This factor explains slightly
less than 10 % of the total variance within the factor model.
analysis, the three sum variables were composed based on the items loaded on
each factor. To maintain the original 1-5 scales and interpretability, mean
values were used as the basis for sum variables. To ensure the internal
consistency of the new variables, their reliabilities were first
tested by using Cronbach’s alpha. Cronbach's alpha is a statistical index that measures how well
a set of variables measure a single underlying
construct. Regarding ‘Sociability’, the alpha was .827
(Mean=3.93, Standard Dev.=.68 , Range=1.00-5.00). The ‘Entertainment’
sum variable reached an alpha value of .667 (M=2.00, SD=.75,
Range=1.00-5.00) and ‘Time-coordination’ got an alpha of .683 (M= 3.63,
and similarities in the patterns of mobile phone usage
The second research question of the study is to detect whether the discovered
three patterns of mobile phone usage differ between the urban and non-urban users. An initial comparison between the two
groups is implemented here through analysis of variance. Here one-way ANOVA measures
whether the variance between the urban and the non-urban users is greater than the
variance between them, when use for sociability, entertainment and time-coordination
are used as independent variables one after another. If the variance between
the groups is higher than that of within the groups, it implies that some other
variables might explain the differences.
The results of ANOVA are
presented in Table 3. The sig-value for F-test indicates whether the
differences are statistically significant. The table shows no statistically significant
difference between the urban and the non-urban users with regard to the use for
sociability. This is interesting as it could have been
expected that the non-urban users would compensate for the lack of physical
proximity of others with the heavy use of mobiles to foster social
relationships. However, the data does not support this idea. In contrast, young
people in the urban and the less-urban locations seem to utilize the mobile
phones rather equally. Previous
studies have implied that the mobile is not employed so much to maintain
distant relations or establish new ones as it is to keep in touch with close
friends and family members (e.g. Ling, 2004, pp. 111-112). The finding might
indicate that people living in urban and non-urban environments are alike also
in these respects.
On the other hand,
ANOVA alludes to the existence of some differences in the use for time-coordination
and entertainment. When analysing these differences more carefully at the level
of mean values, it appears that the respondents of non-urban locations register
higher levels of use for both entertainment and time-coordination. Regarding
the use for time-coordination, the urban users get a mean value 3.49 of and
non-urban 3.75 (range=1-5, F=6.776, sig.=.010).
Regarding the use for entertainment, the mean value for the urban residents is
1.82 and that of non-urbans 2.18 (range=1-5,
F=24.681, sig.=000). As the data is skewed in terms of age, and to a lesser
extent in terms of gender as well, a strong conclusion cannot yet be drawn from
these findings. However, the findings indicate that the users of less-urban
locations have fewer alternative sources of entertainment, and that this lack
may be compensated for by the use of mobile phones for entertainment. This is
explored in the next section.
differences and similarities in the patterns of usage
The third research
question of the study aims to find out what variables explain the differences
and similarities in the use of mobile phones between the urban and the
non-urban users. To explain similarities and differences reliably, a set of background variables have to be controlled. Multiple Regression Analysis (MRA) is an appropriate method for
this kind of research setting. As the gender and age of respondents can be controlled
in MRA, problems related to the skewed variables of the data sets can also be
illustrates three MRAs, one for each of the dependent
variables that are the three patterns of mobile phone use. The MRAs are carried out with an entered model meaning that all
independent variables are added to the analysis at once. In stepwise or
hierarchical models, on the contrary, independent variables are added one after
another either according to their explanatory capacity or thematical relevance.
The strength of the entered model here is that it makes possible comparisons
between the three parallel models as the order and
composition of independent variables remain the same.
The MRA models
presented in Table 4 consist of seven independent variables measuring the level
of urbanity (urban/non-urban location, urban recreations), personal characteristics
(gender, age and children) and respondents’ activity as mobile phone users
(e.g. how many mobile handsets one has owned (M=4.13, sd=2.73,
range=0-20) and how much the mobile costs per month (M=29.98, sd=21.59, range 0-170). The urban recreations variable was
constructed by combining four statements inquiring how frequently people use leisure
time for a set of purposes (e.g. going out to restaurants, pubs and bars;
spending time at cafes, and hanging out with friends). Cronbach’s
alpha for this sum variable was .651 (M= 2.79, SD=.63, Range=1.00-4.00).
Before the presentation of MRAs, it is worth
mentioning that the age of respondents is highly correlated with their level of
education, form of dwelling and current employment status. To avoid collinearity between the dependent variables, only age is
included in MRAs. Correlations between the main
variables are presented in Table 5 (Appendix).
analysis for the use for sociability confirms that this type of use is not related
to the urbanity of residents’ living environment. This may be related to the
fact that many connections with peoples do not require a physical propinquity
with others (Urry, 2007, p. 47; Ling, 2008). In the non-urban towns young
people may socialise and maintain their social relationships through the mobile
phone, even if others may be physically more distant. In the urban environment
physical contacts with others may be considerably more frequent and varied, but
this as such is not related to the more active mobile phone use for
sociability. Rather, the analysis shows that recreational activities typical to
city life predict the use for sociability considerably. The more people go out
to bars, restaurants and hang out with their friends, the more they use the
mobile phone to facilitate sociability. In other words, the use for sociality
is linked to active and outgoing life styles (e.g. Ling & Haddon, 2001; Madell & Muncer, 2005; Thulin & Vilhelmson, 2007),
which are not directly dependent on the urbanity of one’s living environment.
characteristics, in turn, the analysis shows that women are inclined to use the
mobile phone for sociability more than man. This result has emerged in other
studies as well (Ling, 2002; Castells et al., 2007, 45-46). Having children is
likely to increase this type of mobile phone use as well but the respondent’s
age is not related to the use for sociability. Regarding the respondent’s activity
as a mobile phone user, the analysis shows that there is a positive
interdependence between the costs of the mobile phone and use for sociability.
This model explains 30 % of the total variance of the sociability sum variable.
Regarding the use
for entertainment, the analysis confirms the preliminary findings of ANOVA,
which pointed out some differences between the urban and the non-urban users.
After controlling gender, age, children and the general activity of mobile
phone usage, the non-urban respondents use the mobile phone for entertainment
to a greater extent than those living in the urban environment. Simultaneously,
urban recreations are also predicting this kind of use rather powerfully. The
young age of the respondent - and to a rather limited extent the female gender
- also determine the mobile phone use for entertainment in this data set. It
may also be noticed that the general activity of mobile phone use is also
linked with the use for entertainment. The more frequently the respondent has changed
the handset, the more habitually he also uses the mobile phone to entertain
himself or others. It is almost self-evident that this kind of use is also
reflected in the higher average cost of mobile phone use. This regression model
is capable of ironing out 21 % of total variance of the dependent sum variable.
regression analysis attempts to model the mobile phone use for time
coordination. In addition this model confirms the initial findings brought out
by ANOVA and further specifies them. The non-urban users take more advantage of
mobile-mediated time-coordination practices than those living in the bigger
urban cities. Urban recreational activities are powerful predictors of this
type of mobile phone usage as well. This implies that the young people residing
in less-urban areas aspire to spend their free time rather similarly to urban
youth. Furthermore, the analysis points out that use for time-coordination is
common to all kinds of young people: gender, age and children do not explain the
use of the mobile for time-coordination. However, those who change their mobile
handsets often use the mobile telephone, according to this model, more
frequently for the temporal coordination of everyday life. The explanatory
capacity of this model is about 11 % of total variance of the dependent
5. Discussion and Conclusions
addressed the issue of mobile phone usage among young people in Finland.
Respondents living in urban and non-urban locations were compared. The analysis
was based on quantitative survey data and a set of statistical methods. In response
to the first research question, the study was able to identify three patterns
of mobile phone use, namely use for sociability, entertainment and time
coordination. It was also underlined that these data-based
categories are partly overlapping. For example, use for entertainment may
contain various elements of being social with the mobile phone.
To answer the
second research question, the study compared the urban and non-urban users in
relation to three patterns of usage. Statistical differences were found
regarding the use for entertainment and time-coordination but not unlike the
use for sociability. It appeared, as it was hypothesised, that the non-urban
users are more active mobile ‘entertainers’ than those living in the urban
environment, replete with alternative sources of amusement. Even more
interestingly, and contrary to what was hypothesised, the study pointed out
that the use for time-coordination activities is also more common among the
non-urban mobile users. In the non-urban locations, the need for temporal
coordination may arise, for instance, from longer physical distances and a lack
of public transportation that forces people to plan their schedules in advance.
However, more empirical evidence is still needed on this phenomenon.
The main outcomes
of the study are related to the third research question that aimed to explain
the existing similarities and differences. It was discovered that factors
predicting the various forms of mobile usage differ from one another. Gender,
for instance, predicted the use for sociability and entertainment. Girls were
more likely than boys to use mobiles for entertainment purposes, which may
partially stem from the composition of the sum variable, too. It included only
one question about playing games while others were more ‘social’ and ‘unisex’
by nature (e.g. gossiping, cheating). Age, in turn, was only related to the use
of mobile phones for entertainment, and having children to the use for
sociability. Thus, the study did not give support to the idea that the use for
coordination would become more typical as young persons grow older (Ling & Yttri, 2002; Ling, 2004, p. 100).
The study has
certain limitations which can be viewed as future
research items. The study focused only on four cities and towns in Finland. In
order to further elaborate the findings and generalise them to apply to the
whole population, a more representative survey data would be needed. It may
also be asked whether the identified spatial differences in the use of mobile
phones exist in other countries. Like in mobile communication studies in
general, there is a lack of comparative international studies on spatial
disparities in the use of mobile phones. It is mostly unknown, for instance,
whether there is any location-based differences in the use of mobile phones in
developing countries, and to what extent they are similar to those of developed
countries. Furthermore, it would be of great value to have more in-depth
qualitative information on spatial differences in mobile telecommunication
practices as well. For example, the meanings urban and the rural mobile phone
users attribute to the mobile phone, its mobility and
various patterns of mobile phone usage may vary considerably.
This study focused
solely on young mobile phone users. It should be taken into account that
the patterns of mobile phone behaviour and interests among young people differ
significantly from those of the rest of the population. This study showed that
variation within the group of 15-25 year-olds is also noticeable and
measurable. However, the study did not encompass other age groups or
socioeconomic factors, such as the level of education or the socio-economic
status of respondents, which may be associated with spatial differences in the
patterns of mobile phone behaviour. It is apparent that older and more educated
people may not utilize the mobile phones for entertainment purposes as eagerly
as the young users studied.
Despite these restrictions,
the study managed to demonstrate that the relationship between the mobile phone
and urbanity is a complex one. As the mobile phone does not presume the
physical proximity of others (Urry, 2007, p. 47; Ling, 2008), it can be used to
facilitate everyday life in multiple manners also in sparsely populated towns.
The spatial complexity of mobile communication should not be taken for granted
and it needs to be studied by empirical methods and from comparative
perspectives as well.
Campbell, S.W. (2007). A cross-cultural comparison of
perceptions and uses of mobile telephony. New Media
Society, 9, 343-363.
Castells, M., Fernándex-Ardèvol,
M., Qiu, J. L., & Sey,
A. (2007). Mobile communication and society. A global perspective. Cambridge, The MIT Press.
K., & Kangas, S. (2001). Nufix - nuoret ja kommuniaatio-akrobatia:
16-18 vuotiaiden kännykkä- ja internet-kulttuurit (Young people and communication acrobatics:
the mobile phone and internet cultures of 16- to 18-year-olds).
Elisa Research Center report
No. 158. Elisa Communications and Finish Youth Research Network, Helsinki.
Davie, R., Panting, C., & Charlton, T. (2004). Mobile phone
ownership and usage among pre-adolescents. Telematics and Informatics, 21, 359–373.
Fortunati, L. (2002).
Italia: Sterotypes, true and false. In J. Katz
& M. Aakhus (Eds.), Perpetual contact: mobile
communication, private talk, public performance (pp.
170-192). Cambridge, Cambridge University Press.
Fortunati, L., & Manganelli, A. M. (1998).
La comunicazione tecnologica:
comportamenti, opinioni ed emozioni degli
europei. In L. Fortunati (Ed.) Telecomunicando in Europa (pp.
125-194). Milano, Angeli.
Fortunati, L., & Manganelli, A. M. (2002).
Young people and the mobile phone. Revista de Estudios
de Juventud, 57, 59-78.
Green, N. (2002). Outwardly mobile: young
people and mobile technologies. In J. E. Katz (Ed.) Machines that become us:
the social context of personal communication technology (pp. 201-218). New Brunswick & London, Transaction Publishers.
Höflich J., & Rössler, P. (2002). More than JUST a telephone: the mobile
phone and use of the short message service (SMS) by German adolescents: Results
of a pilot study. Revista de Estudios de Juventud, 57, 79-99.
Jolliffe, I. T. (2002). Principal component analysis. New York, Springer-Verlag.
Kangas, S. (2002). “Mitä sinunlaisesi tyttö tekee tällaisessa paikassa?” Tytöt ja elektroniset
pelit (“What is a girl like you doing in a place like
this?” Girls and electronic games). In
E. Huhtamo & S.
Kangas (Eds.), Mariosofia. Elektronisten pelien
kulttuuri (pp. 131–152). Helsinki: Gaudeamus.
Kasesniemi, E-L. (2003). Mobile
messages: young people and a new communication culture. Tampere, Tampere
Kasesniemi, E-L., & Rautiainen, P. (2002). Mobile culture of
children and teenagers in Finland. In J. Katz & M. Aakhus (Eds.), Perpetual contact: mobile communication,
private talk, public performance (pp.170-192). Cambridge, Cambridge University Press.
Kopomaa, T. (2000). The city in your pocket: birth of the mobile
information society. Helsinki, Gaudeamus.
Leung, L. & Wei, R. (1999). Who are the mobile phone have-nots? Influences and consequences. New Media & Society, 2, 209-226
Ling, R (2008). New Tech, New Ties: How Mobile Communication Is Reshaping
Social Cohesion. Cambridge, The MIT Press.
Ling, R. & Haddon, L. (2001) Mobile telephony and
the coordination of mobility in everyday life. In J. E. Katz (Ed.) Machines
that become us: The social context of personal communication technology (pp. 245-66).
New Brunswick & London, Transaction Publishers.
Ling, R. (2002). Adolescent girls and young adult men: two sub-culture
of the mobile telephone. Revista de Estudies de Juventud, 52, 33-46.
Ling, R. (2004). The mobile connection: the cell phone’s impact on society.
San Francisco, Morgan Kaufman.
Ling, R., & Yttri, B. (2002) Hyber-coordination via mobile phones in Norway. In J. Katz
& M. Aakhus (Eds.), Perpetual contact: mobile
communication, private talk, public performance (pp.139-169).
Cambridge, Cambridge University Press.
Madell, D. & Muncer, S.
(2005) Are internet and mobile phone communication
complementary activities amongst young people: a study from a ‘rational actor’
perspective. Information, communication, and society, 8,
Mäenpää, P. (2001). Mobile communication as a way of urban life. In J. Gronow & A. Warde (Eds.), Ordinary
consumption (pp. 107-123). London, Routledge.
Miyaki, Y. (2006). Keitai use among Japanese
elementary and junior high school students. In M. Ito, D. Okabe, &
M. Matsuda (Eds.), Personal, portable, pedestrian. Mobile
phones in Japanese life (pp. 277-299). Cambridge, The MIT Press.
K., Boase, j., Wellman, B., & Ikeda, K. (2007).
The mobile-izing Japanese. Connection to the internet
by PC and webphone in Yamanashi. In M. Ito, D.
Okabe & M. Matsuda (Eds.), Personal, portable, pedestrian. Mobile phones in Japanese life (pp. 143-164). Cambridge: The
Nurmela, J., & Ylitalo, M. (2003). The evolution of the information
society: how information society skills and attitudes have changed in Finland
in 1996-2002. Reviews 2003/4. Helsinki, Statistic Finland.
Nurmela, J., Heinonen, R., Ollila, P., & Virtanen, V. (2000). Matkapuhelin
ja tietokone suomalaisen arjessa (Computers and mobile phones in the everyday
life of Finns). Helsinki, Tilastokeskus.
J., Melkas, T., Sirkiä, T.,
Ylitalo, M., & Mustonen,
L. (2004). Suomalaisten viestintävalmiudet 2000-luvun vuorovaikutusyhteiskunnassa (Communication skills among the
Finns in the communicative society of the 21st century). Reviews 2004/4.
Helsinki, Statistics Finland.
Nurmela, J., Parjo,
L., & Ylitalo, M. (2003). A great migration to
the information society: patterns of ICT diffusion in Finland in 1996-2002.
Reviews 2003/1. Helsinki, Statistics Finland.
J., Sirkiä, T., & Muttilainen,
V. (2007). Suomalaiset tietoyhteiskunnassa 2006. (Finnish
people in the information society 2006) Tiede, teknologia ja
2007/1. Tilastokeskus, Helsinki
O’Keefe, G. J., & Sulanowski, B. K.
(2002). More than just talk: Uses, gratifications, and the telephone. Journalism & Mass Communication Quarterly, 4, 922-933.
Ojankoski, T. (1998). Oikea pieni kaupunki:
asukkaiden näkökulma suomalaiseen pikkukaupunkiin (The
real small town: the Finnish small-towns from the point of view of geography
and small-town residents’). Turun yliopiston julkaisuja
C 142. Turku, University of Turku.
Okada, T. (2006) Youth culture and the shaping of
Japanese Mobile Media. In M. Ito, D. Okabe & M. Matsuda (Eds.), Personal,
portable, pedestrian. Mobile phones in Japanese life (pp.
41-60). Cambridge: The MIT Press.
V., & Rautianen, P. (2002). Perhaps it is a
body part: how the mobile phone became an organic part of the everyday lives of
the Finnish children and teenagers. In J. E. Katz (Ed.) Machines that become
us: The social context of personal communication technology (pp. 293-308). New Brunswick & London, Transaction Publishers.
Park, W. K. (2005) Mobile phone addiction. In R. Ling &
P. E. Pedersen (Eds.) Mobile communication. Re-negotiation of
the social sphere (pp. 253-272). London, Springer-Verlag.
Puro, J. (2002). Finland: a mobile culture. Perpetual
contact: mobile communication, private talk, public
performance (pp. 19-29). Cambridge, Cambridge University
Räsänen, P. (2006). Consumption disparities in information Society. Comparing
the traditional and digital divides in
Finland. International Journal of Sociology and Social
Policy, 1/2, 48–62.
Rice, R.E & Katz, J.E (2003) Comparing internet
and mobile phone usage: digital divides of usage adoption, and dropouts. Telecommunication policies 27, 597-623.
Simmel, G. (1964). The sociology of Georg Simmel. New York & London, The Free Press.
Skog, B. (2002). Mobiles and the Norwegian teen: identity, gender and
class. In J. Katz & M. Aakhus (Eds.), Perpetual
contact: mobile communication, private talk, public
performance (pp. 255-273). Cambridge, Cambridge
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Fifth
edition. Boston: Allyn & Bacon.
Thulin, Eva & Vilhelmson
Bertil (2007). Mobiles everywhere: Youth, the mobile
phone, and changes in everyday practice. Young, 15.
Tilastokeskus (1999). Tietoyhteiskuntatutkimuksen
laitelomake 1999 (The questionnaire of information society
research 1999). Helsinki, Tilastokeskus.
Townsend, A. (2002). Mobile Communication in the twenty-first century
city. In B. Brown, N. Green and R. Harper (Eds.) Wireless world: social and
interactional aspects of the mobile age (pp. 62-77). London, Springer-Verlag.
(2007). Mobilities. Cambridge,
Widaman, K. F. (1993). Common factor analysis versus principal
component analysis: Differential bias in representing model parameters. Multivariate Behavioral Research, 28, 263-311.
Wilska, T.-A. (2003). Mobile phone use as part of young
people’s consumption styles Journal of Consumer
Policy, 26, 441–463.
Wilska, T-A, & Pedrozo,
S. (2007). New technology and young people's consumer identities: A comparative
study between Finland and Brazil. Young 15; 343–368.
www.localfinlad.fi (2005). Population and Area, Statistics by municipalities. Retrieved
September 1, 2006 from http://www.kunnat.net/k_peruslistasivu.asp?path=1;161;279;280;43252;43270
Yoon, K. (2003). Retraditionalising the mobile.
Young people’s sociability and mobile phones use in Seoul, South Korea. European Journal Cultural Studies, 3, 327-343.
was sponsored by the HPY Research Foundation, Helsinki, Finland.