1There have traditionally been stark differences between Hungary’s regions, which on the one hand can be attributed to geographical factors and on the other to historical ones. The objective of this article is to examine whether or not regional differences can be perceived and if they can, in what way do information communication technologies (ICT) and their proliferation in the population (i.e. in the case that technologies that have played a significant role in reducing geographical factors). This issue also came under examination in regard to settlement size, not only to the regions. Data was utilised for the analysis from the World Internet Project, which spanned from 2002 to 2006. The World Internet Project (WIP) was initiated in 1999, by UCLA and the NTU School of Communications Studies in Singapore. WIP focuses on the social effects of the Internet, among Internet users as well as non-users.
2A prominent characteristic of Hungary is that its spatial layout shows very serious inequalities which have existed for a long time primarily because of historical and geographical reasons (fig.1). Various studies have found that these differences have not decreased since the political change of regime in 1989 and indeed they have become even starker. Budapest, the capital has consolidated its already dominant role, while less advanced regions (for example Northern Hungary) have fallen even further behind. The richer regions (for example Central Transdanubia) have started to develop and bridge the gap that separated them from the capital.
3There are significant differences between the capital and the countryside and also between the east and west of the country. Those parts of the country that are located closer to European centres found themselves in more favourable circumstances compared with the more remote areas. These differences are made starker by the deficiencies that could be perceived in the infrastructure of these regions. Due to the various factors, differences have evolved in the degree of economic development within the country and this is reflected in numerous indicators.
Fig. 1: The regions of Hungary
4Numerous articles have attempted to interpret these differences numerically but we have opted to use the work of Plummer and Vajsz (2005), which integrates 26 variables to show inequalities, to give a quick overview of the differences between regions (fig.2). Based on the value of the indicators the regions were ranked. The graph shows the averages and standard deviation for the ranked regions.
Fig. 2 : Regional differences in Hungary
The averages and standard deviation rangsorátlaga és szórása of indicators showing regional differences
Pummer and Vajsz, 2005
5As can clearly be seen in Figure 2, the three regions of Eastern Hungary significantly lag behind the rest of the country, while the central part of the country and Western Transdanubia are far more developed than the other regions. The explanation for Southern Transdanubia’s indicators being close to the average of the eastern part of the country can probably be attributed to its settlement structure being mostly comprised of tiny villages.
6According to the authors of the present article, the above ranking is further validated by seven indicators:
GDP per capita
difference resulting from domestic migration
the proportion of flats with a drainage system
the number of private cars per 1,000 inhabitants
the number of main telephone lines per 1,000 inhabitants
net income, HUF/per person
the rate of investment, HUF/per person
7The existing inequalities raise the question of whether these differences are also reflected in the use of information and communication technologies (ICT), which on the one hand can play an important part in bridging physical distances and on the other hand in enhance competitiveness. In addition to regional differences it is also interesting to look at what kind of differences can be found between settlements of varying sizes and how these differences have developed in recent years.
8The phenomenon and the development of the digital divide is one of the most investigated research topics on the field of new media and ICT research (Hargittai, 2002). According to the simplest definition the concept of digital divide describes the phenomenon that there is a difference between certain social groups in the likelihood of accessing and using the Internet. Theories usually make a distinction between different kinds of divides: the most general is to separate the so-called global digital divide and the social digital divide. While the first one refers to the differences between countries and greater geographic regions, the latter refers to inequalities between different social groups in a given social system (e.g.: in countries, smaller regions or groups) (Norris, 2001).
9Social digital divide research often focuses on the social demographic features along which these differences develop. According to the analyses, these determining factors are more or less the same in most countries, of course with different tones. These are usually income, education, age and gender, while in some cases geographic location and race are also important. (Bognár-Galácz, 2004)
10Rogers (2003) identified five factors having a central role in the diffusion of innovations: relative advantage, compatibility, complexity, trialability, observability. Considering the characteristics of broadband services, their relative advantage is rather significant, as they can offer a wide range of interactive services. Compatibility and complexity are a different matter, as one of the factors hindering development may be that many consumers find ICTs too complicated as the nature of the experience differs from traditional media and communications. That is why user-friendliness and simplicity are considered fundamental requirements in the interactive services market. Theoretically the ability to trial reduces the risk as consumers can gradually familiarise themselves with the new services without any significant negative consequence. Above a certain level of market penetration, observability of ICT may not be a problem, either (Rogers, 2003).
11The results of a multivariate analysis at a regional level in Germany do not support the hypothesis that a higher local proportion of people living in rural communities is accompanied by a lower county-wide Internet use rate (Schleife, 2008). Other regional characteristics, such as the proportion of foreigners, the proportion of highly qualified employees, and the regional rate of unemployment, turn out to be more important (Schleife, 2008). Thus, it is not rurality per se that explains differences in Internet use. The results rather indicate that it is the different composition of individual characteristics between rural and urban populations that accounts for the regional digital divide.
12At individual level, the estimation results show that the decision to become a new Internet user is strongly influenced by individual characteristics and in line with previous research results, individuals who are more highly educated, younger, and wealthier are more likely to access the Internet. (Schleife, 2008).
- 1 The sample was prepared by a multiple-stage, proportionally layered probabilistic sampling method. (...)
13According to recent findings of the World Internet Project1, computer- and Internet access at home have produced significant growth in the last five years. More than one third of Hungarian households have a computer, and slightly more than one fifth of households also have Internet access. This means that nowadays over 1.5 million households have a computer and nearly 800,000 are connected to the Internet from home in Hungary.
14As can be seen in the previous chapter, Hungary has been struggling with stark regional differences for many years. The declining industry and a restructured economy that resulted from the political change of regime have further increased these differences. However, can these differences also be found in the sphere of information technology?
15The authors primarily examined which areas demonstrated an outstanding achievement in the proliferation of the Internet and broadband during the last five years. In summary, it can be stated that the general differences found can also be identified in this respect too. However, regions with unfavourable circumstances are starting to make an effort to catch up with the central regions, which continue to occupy the leading positions. In 2002, the first year of the study, the proportion of households equipped with Internet access in Central Hungary was three to four times bigger than that which characterised the other regions; however, the majority of these have quickly begun the process of catching up.
16In the graph below (fig.3) shows the dynamic growth of households in disadvantaged regions such as?? in the interval of the four years studied. Although the majority of them were successful in reducing the differences compared to the leading regions, by 2006 the Northern Great Plains region was still lagging behind those regions that started off from a similar position in 2002.
Fig. 3: Internet access
Internet access in households according to regions
17In the spread of broadband connections (in which the situations of the respective regions have developed somewhat differently) some changes can be observed. The Northern Great Plains region stopped being among the innovator regions that were neck to neck in their ranking in 2002, and what is more, it became the region lagging behind the most (fig.4).
18The proportion of households with Internet access and the types of connection allow us to conclude that the citizens of the Northern Great Plains who regard it as important and/or can afford a quality Internet subscription – by which we mean broadband access – are keeping up with their peers in similar circumstances in other areas of the country who had already joined the information society in 2002-2004. Those that were not able to join are more difficult to involve in the process; in 2006 the Northern Great Plains regions lagged 20 percent behind the leading regions.
Fig. 4: Broadband
Broadband access in households according to regions
19The differences based on the size of settlement are also at least as interesting as the ones based on the differences between the capital and the rest of the country and the ones between the towns and villages (fig.5). When we look at settlement type the trend for regions to catch up is perceptible to a more noticeable degree, i.e. the capital’s leap forward was followed/is being followed with somewhat of a delay by the other settlements.
Fig. 5: Internet access
Internet access in households according to settlement type
20Every third household in the capital has an Internet subscription, while in other towns this proportion is 20%, and in villages it is 14%. The average for towns on the whole reflects the average for the country, while the capital significantly deviates from this average in an upward direction and the villages deviate in a markedly downward direction.
21If we examine the changes that have taken place over time, it becomes clear that while the rate of growth was the greatest in the capital between 2002 and 2004 the other towns and villages caught up between 2004 and 2006. To some extent this corresponds to what can be stated about the Hungarian population as a whole in regard to Internet use. The top third of society, i.e. the predominantly young, well-educated, skilled layer, are Internet users. This stratum of society started to use the Internet relatively quickly, after which the upswing lost momentum, thus allowing the other settlement types to reduce their disadvantage though there was a degree of delay due to distance however the same social stratum adapted to the technology.
22This same trend can be clearly observed in the number of those with broadband access (fig.6). Compared with previous years, three quarters of Hungarian households with an Internet connection have broadband, while the ratio of broadband access has increased the most in villages. Wherever it became physically possible to obtain a broadband connection those already using the Internet switched over to it; thus, the proportion of broadband use among all Internet users increased dramatically. Compared to its neighbouring countries Hungary has a high proportion of broadband access, while the penetration per capita is still low.
Fig. 6: Broadband
Broadband access in households according to settlement type
- 2 The generaly employed dimensions are as follows: age, sex, school qualifications, financial situati (...)
- 3 Computer and Internet access, as well as computer and Internet use generally and at home. For a det (...)
23In the following we examined how the digital divide, according to settlement type and region, changed in regard to access and use. We summarised2 the digital divide according to the type of region and settlement in an aggregated index, which is an aggregated index-number similar to the Digital Divide Index (DIDIX)3. Based on the DIDIX methodology we examined computer and Internet access in the home and computer and Internet use (anywhere). We adjusted the proportion of access and use of the group which was in a disadvantaged position in regard to access and use, i.e. inhabitants of small towns and villages in the case of settlement type and those living in unfavourable circumstances where we examined regional differences (this was mostly the Northern Great Plains region), to the proportions4 of access and use we discovered in the entire sample. We weighted the proportions we received, ascribing 0.3 to use and 0.2 to access and summarised them in each index5. We computed the annual aggregated index using the arithmetical average of the partial indices 6.
24The partial indices that we created and the aggregated INDEX equally contain the indicators relating to access and use of computers and the Internet. During the time interval studied the value of the aggregated INDEX rose from 68 points to 78, which can be regarded as a significant result. The conclusion that can be drawn from the graph below is that small settlements have been more successful in whittling down their disadvantage than the regions that were lagging behind. It is perceivable that regional differences have decreased more slowly, and while in 2002 the difference between the digital divide according to region and that according to settlement type was a mere three points, by 2004-2006 it had risen to six points (fig.7).
25All of this means that when everything is considered the digital divide according to settlement type has decreased; however, in the case of the regions the situation is changing more slowly, i.e. in Hungary the regional differences are more significant and change more slowly than the disadvantageous situation because of settlement type (settlement size).
Fig. 7 : Digital divide index
Changes in the digital divide according to settlement type and region
26Finally, after a study of the use and proliferation of ICTs it is also worth looking (using the WIP database from 2006) into why certain people refrain from using them, and whether regional characteristics can be found among these reasons. Based on the opinions of those who do not use the Internet they can be classified into two large groups: one of the groups is composed of those who do not use the Internet due to financial considerations, i.e. they cannot afford to do so because of the high costs. The other group is composed of those who do not use the Internet because of cognitive reasons, i.e. they do not need it, they are not interested in it, they cannot use it, etc.
27According to those questioned who do not use the Internet due to cognitive reasons, they refrain from use because they do not need it, they are not interested, they do not know how to use it, they are afraid of technology, they think it is not suitable for children, pornography is cited, they wish to protect their personal data, because of viruses, there are too many advertisements, or they do not have time for it. Among the financial reasons given of those questioned were: their computer was not good enough, they did not have a computer, technology is too expensive, access is too slow, or it is difficult to establish a connection.
28Among those who do not use the Internet the proportion of those who refrain for financial reasons has steadily been decreasing since the first WIP measurement in Hungary, i.e. since 2001, and along with this the proportion who refrain because of a lack of interest has been steadily rising (fig.8). This gives rise to the question as to whether the limit of the increase in use has been reached since further price decreases most probably cannot influence cognitive inhibition, thus allowing for a possible increase in the gap between users and non-users.
Fig. 8 : The barriers of Internet-usage
Reasons for refraining from use of the Internet
29Regional inequalities influence non-use of the Internet. The effect exerted by settlement type can be clearly seen on the graph (fig.9). It can be observed that more people cite cognitive reasons for non-use in the capital than in towns or in villages where the highest proportion (19%) cited purely financial reasons.
Fig. 9 : The barriers of Internet-usage
Reasons for refraining from Internet use according to settlement type
30Differences according to the regions can be observed in the 2006 data of the WIP (fig.10). It is no surprise that in the least developed Northern Great Plains region the largest proportion (25%) of non-users cite purely financial reasons. In the developed regions, i.e. Central Hungary and West Transdanubia, it was rather the case that purely cognitive factors dominated.
Fig. 10 : The barriers of Internet-usage
Reasons for refraining from Internet use according to regions
31The data reveals that the regional differences in the use and proliferation of ICT reflect the other kind of inequalities present. The central region (Central Hungary) of the country stands out from the others, while the east-west “contrast” is markedly present. The trend of increasing inequality according to decreasing settlement size presents a similar picture with the villages lagging behind the towns and even more significantly behind the capital. The results indicate that it is the different composition of individual characteristics between the rural and urban populations and between the populations of different regions that accounts for the regional digital divide (these are mainly based on income, education and age).
32At the same time it becomes clear from the timeline data that there has been some catching up in the last four years – while the Northern Great Plains, which underwent a serious nosedive, demonstrably lost its position during this time. The changes over time are similar according to settlement types although at times a more dynamic picture can be seen; the villages and towns equally produced a faster pace of growth in the last two years than the capital. It can also be observed from the data that the regional differences are perhaps more deeply rooted than the contrast between town and village.
33The most spectacular trend in closing the gap was in broadband use: where broadband connection became physically achievable Internet users switched over to it and because of this the proportion of broadband within the entire subscription to the Internet increased dramatically, especially in villages. In regard to this indicator it must nevertheless be noted that a high proportion of broadband within the entire Internet access even by European comparison is to no avail if the proportion of users in the population is very low. However, this group changed over to the latest technology as soon as it became possible.
34It is our view that this leap in growth consolidates the country’s achievements. Internet use predominantly spread in the top layer of the population, which likes to use it. When the possibility of access emerges this layer becomes users and adapts to the latest technology quickly. This takes place more quickly in the developed regions. After this takes place growth slows down and a catching-up period follows in the less developed regions (in which the greater proportion of those who refrain from use is occupied by those citing purely financial reasons) although it is probably the case that there too only a certain layer become users – or at least this can be inferred from the data up to 2006.