Does Location Matter?
A Comparative Study on Mobile Phone Use Among Young People in Finland

Sakari Taipale (bio)
 Dept. of Social Sciences and Philosophy
University of Jyväskylä



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. Introduction

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., 2003).


This article 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.

1.2 Research questions

Three research 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:


Q1:      What are the main patterns of mobile phone usage among our respondents?

Q2:      Do the patterns of mobile phone use differ between the urban and the non-urban locations?

Q3.      What 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, 2004).


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). 


Nevertheless, earlier 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 mobile services.


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.

2.2 Determinants of mobile phone usage

Earlier studies 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).

3. Methodology

3.1 Data

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, 2002).


The questionnaires 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).


Table 1 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 non-urban.


3.2 Statistical methods

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 study, a 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 mutually exclusive.


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.


3.3 Locations


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. (, 2005). The cities and towns were selected into the survey to represent geographical and economical diversity of Finnish municipalities.

4. Analysis

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 everyday’.


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 relationships’.


In the 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.


The 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.




For further 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, SD=1.02, Range=1.00-5.00).

4.2 Differences 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.


4.3 Explaining 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 overcome.


Table 4 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).




The regression 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.


Regarding personal 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.


The last 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 variable.

5. Discussion and Conclusions

This article 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.


Coogan, 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 University Press.


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, 64-80.  


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.


Miyata, 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 MIT Press.


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.


Nurmela, 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.


Nurmela, J., Sirkiä, T., & Muttilainen, V. (2007). Suomalaiset tietoyhteiskunnassa 2006. (Finnish people in the information society 2006) Tiede, teknologia ja yhteiskunta. Katsauksia 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: maantieteen ja 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.


Oksman, 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 Press.


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 University Press.


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. 235-253.


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.


Urry, J. (2007). Mobilities. Cambridge, Polity.


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. (2005). Population and Area, Statistics by municipalities. Retrieved September 1, 2006 from;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.

Author's Note

This study was sponsored by the HPY Research Foundation, Helsinki, Finland.  


[i] Whereas in Factor Analysis factors are thought to cause variables, in PCA variables are taught to cause components (Jolliffe, 2002, pp. 150-151; Tabachnick & Fidell, 2007, pp. 611-612). Both aim to reduce the dimensionality of a data set, and are used to identify new meaningful underlying variables (cf. Widaman, 1993; Jolliffe, 2002).

[ii] If variance between these two groups is greater than variance within the groups, ANOVA signifies that there might be some difference between the urban and non-urban ways of using the mobile phone (Tabachnick & Fidell, 2007, pp. 195-199).

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