Many Links = Internet?
The Role of Social Capital on the Diffusion of Information Technology Based on Surveys and Participant Observation
Keywords: social network, social capital, diffusion, information technology, computer-possession and professional knowledge, participant observation, Kaposvar-area.
THE SITE OF THE FIELD WORK
II. THE ROLE OF SOCIAL CAPITAL IN ADOPTING INFORMATION TECHNOLOGY
The Extension of Ego-Network and Computer Possession
Whom Do You Need To Get On Well With?
FIRST SUMMARY: WHAT KIND OF SOCIAL CAPITAL HELP IT ACCESS?
III. IS THE SPREAD OF COMPUTERS DIFFUSIONAL OR NOT?
The First Computer in the Village
Since When Have the Inhabitants of Kaposvar Area Had PCs?
Who/What Was the Effect for PC Purchase?
Motivations of Computer Purchase
Computer Technical Advisory Network at Cserenfa
SECOND SUMMARY: HOW DO COMPUTERS SPREAD?
Accomplished within the framework NKFP research “Information technology and
Local Society” at the Sociology Department of Budapest University of Economics
in March 2003. We thank the research’s supervisor, Dr. Gyorgy Lengyel, for his
support. We also thank our colleagues, Peter Futo, Agnes Hesz, Laszlo Lorincz
and Viktoria Siklos for their help in the field work and data-analysis. We are
grateful to Mrs. Zsuzsi Varga, Margit Feher, the Cseh, Papp and Biro families,
our hosts and interviewees for their kind support.
In our research we approach computer literacy and computer possession from two sides.
The first keyquestion of our research is: in what way does social capital influence the access of information technology. This question is closely connected to the plenary of the Hungarian Sociological Assosiation conference, in particular to Gyorgy Csepeli’s lecture, who, as a sociologist and specialist in the field, has made attempts to provide an answer to the question: what kind of factors shape the information society. Based on empirical research he presented on what kind of roles income and education play in someone becoming a computer user. The points of view he analyzed in Lazarsfieldian terms were all analytical explanatory factors. In contrast with the above, we do research on the basis of relational criteria and we lay stress on the fact that besides material and spiritual resources computer knowledge depends on relationships and social capital. During our research we tried to operationalize and put this observation into figures, which in some way seems to be commonplace. We set certain hypotheses, like how many friends and acquintances in particular work fields one needs to have to become a computer user. Our causal explanations were tested in a sample territory. We think that if our propositions were to be revised on a larger scale, efficient political information would result. Our view is that personal advice may serve as a major means in building an information society.
Nowadays, in relation to information technology, many sociologists take for granted that the spread of computers is a diffusional process, expressed by a certain diffusional S-graph. We question this fact as well, so our second keyquestion is the following: is the spreadof information technology a diffusional process? If so, can it be predicted by a diffusional chart in Hungary?
To provide answers to our questions we carried out empirical research in the Kaposvar-area. We applied sociological and cultural-antropological data-collection techniques. Further, we present the bibliography concerning the topic, then our hypotheses, results and, finally, the synopsis.
The Information Technology and Local Society research began in 2001 at the Department of Sociology and Social-Politics at Budapest University of Economics. The research focused on the diffusion of information technology and the digital gap. Our research team joined the research in the summer of 2002 during a fieldwork.
In 2002-2003 we applied two data-collection techniques.
Firstly, our questions referring to the social capital and diffusion of information technologies were introduced to a survey which was questioned on a representative sample in the Kaposvar area.
Secondly, in a smaller sample area, at Cserénfa, through participant observation we mapped out the ways and modes of computer and computer literacy diffusion. During our fieldwork at Cserénfa we kept a field work diary and made video recordings which we utilized to make an educational film. The aim of the field work was to clarify the results by revealing individual motivation besides quantitative methods.
During the analyses we utilize the results of both data-collection and participant observation technique. We also adopted relational- and dynamic analysing methods. To describe and illustrate in graphs the social network we used UCINET and Net Draw programs.
To complete the survey data-collection at Kaposvar we did field work at Cserénfa.
Situated 12 kms from Kaposvar, among the hills of Zselic, Cserénfa has 264 inhabitants. Taking into consideration that Cserénfa is a samll village, the inhabitants work at kaposvar or neighbouring villages, and children go to primary school at a neighboroughing village, Szentbalazs.
A major development made in the past few years at Cserénfa is the establishment of the telehouse in 2002. The telehouse works as a computer consultant providing the possibility of working on computer and internet. The telehouse also provides access to communication devices like fax-machine, copy-machine, CD writer, means to acquire basic information on the ways of computer-usage within the framework of certain specialized courses.
It is possible that the village’s dynamical developement and the social network structure influenced many families at Cserenfa to possess more PCs than in the neighbouring villages.
We approach the first topic of our research – the reason people buy PCs and the acquisition of expertise – from a relational point of view. We examine that computer technology innovations in which way are affected by the ego’s social capital composition.
The term “social capital” is central in our research, however, contemporary scientific literature and its branches refer to it distinctly. It is essential we should present the improvement of several theories regarding assets, while we designate the relevancy of our term usage.
According to classical economic approach, capital is one of the production factors, signifying the investment in trade and production. The term “capital” is meant in the sense of a part of the added value that results as difference between the consumer value of goods (on the consumer market) and its value (on the trade market). At this stage the analysis is structural, focusing on classes and not on individuals. One of the main differences between the levels of society is the possession of capital.
The multilateral expansion of the term “capital” began in 50s and 60s in the field of economics. The analysis of the conception of human capital is connected to Theodore Schultz (1961) and Gary Becker (1964). They regard human capital as a kind of human resource besides physical capital (machines, tools, etc.). Advantage gained by their application exceeds the investment beyond the expectations of the investor, thus producing economic growth. According to human resource theories people invest in further education because they will earn more on the labour market (higher salary) than the total of time and money spent on education. So, the individual stands in focus at this point of the theory.
The term „human capital” was further developed by James Coleman (1988). According to Coleman human capital results from further education, and as the individuals acquire new skills and knowledge the horizon of their activities expands. Coleman reflects on social capital as the result of changes in human relations in a way that they generate activities. In other words, he identifies social capital with some characteristics of social structure that can be used to serve the needs of the agents. One of the most important factors of its realization is trust, so, according to Coleman, social capital depends on the trustworthiness of the social surroundings, the extent of liabilities, information highways and efficiency of the relevant norms and sanctions.
In the 70s and 80s capital logic was expanded to social and cultural resources, too. Coleman’s integration concept is overrun by Mark Granovetter’s „embedded” concept (1973), which became a focal term in social network analysis. Regarding social relationships, he differentiates between “strong” and “weak ties”. Weakly embedded individuals in society (having weak ties) are most likely to mediate between social levels, or, if you like, using Granovetter’s term they are bridges in society and they play an important role concerning information expansion. Weak ties help the individual’s social advancement, expertise, in contrast with strong ties, which result through family, relative and friend relations.
Besides the examination of social capital, anthropological and sociological research deal with the concept of “cultural capital” as well, connected to the name of Pierre Bourdieu (1983). He strived to systematize the types of capital and provide a guideline for sociological tendencies. He thinks there are three types of capital: cultural, social and economic. The “largeness” of the individual’s social capital depends on the extension of his relationships and the “largeness” of the capital of persons in relation with him. Bourdieu proves that social capital has a multiple effect on other types of capital. If two persons possess cultural and social capital in the same value, they may reach different results depending how they can mobilize the resources in their relations (clubs, elite school friends, relatives). Bourdieu also introduced the concept of “capital conversion” which means that one can convert its economic capital to the other two types of capital.
From the 90s on Robert Putnam became one of the key figures in professional debates concerning the concept of social capital and its measure. Putnam (2000) adopting Bourdieu’s views, thinks that the criterion of social capital is reciprocation, mobilized by altruism on short term, and self-interest on long term. The “profit” may be promising on short term, but sometimes delayed and probable. According to Putnam social capital refers to the system of relations between individuals, trust, cooperation and reciprocation standing in its centre.
Adapted from Putnam, Barry Wellman and his co-authors (2001) make up social capital from the following: network capital (certain friend, neighbour, family interactions, which give spiritual and physical support), participation capital (it contains the ability and intention of voluntary participation, as in political and charity organisations), communal duty (the social capital means far more than interpersonal action, because it also contains the motivation of belonging somewhere).
In regard to this point of view, we may suggest that the network component of the social capital dominates in our research, because we focus on its ways of influencing the individual’s acquisition and application of computer literacy depending on the extension and content of his relations.
In our study we apply the ego-net approach of social capital. According to the social network point of view, the two factors of connections are set aside: dots (agents, actors) and edges (relations between factors, actors) (after Szántó and Tóth 1993, and Wasserman and Faust 1994). The points and edges define a certain connection which further constitutes a graph. Its characteristics can be analyzed by the concept of graph theory. The ego-net or ego-network is a primary network for an actor which shows all the connections of a specific actor (Szántó and Tóth 1993).
1. chart: “The part in the whole.” The social network and the ego network.
The central question of our study is in what ways do the structure of relations of indidividuals influence innovations, like computer technology and the acquisition of expertise. In contrast with the analytical approach mentioned in scientific literature, we deal with relational data. Accordingly, we analyze the extension of ego-network, that is the relations between the members of the community. Ego-network differs from social network in the sense that the former maps the individual’s relations and the latter the relations of the social group. Our study concerning social capital poses nine hypothese on the basis of nine causal relations.
1. Our first hypothesis states that a larger ego network makes it easier to get a PC and to acquire PC- and Internet-specific expertise. Taking into consideration that children rely on their parents’ relations, our first hypothesis claims that personal relation network is influenced by the number of adults in a family. According to our assumption, if there are more adults, then it is easier to acquire computer literacy.
2. We found it important to examine how many close adult relatives an interviewee had. Granovetter emphasises that extended acquintance relations (weak ties) are in favour of, whereas strong ties (relatives and friends) are unfavourable in personal career. In terms of our hypothesis the scale of close relative relations influences the probability of PC possession and PC literacy, however, we suppose this relationship is not always positive.
3. In terms of our third hypothesis the number of close friends influences the acquisition of a PC and PC-specific knowledge.
4. According to our fourth hypothesis the more acquintances one has, it is more probable that they possess a PC. So, the fact that people keep in touch with a number of persons, influences the obtaining of a PC. In the process of the survey we tried to shed light on the problem whether those possessing a PC name more such persons, than those without a PC.
5. The composition of ego-network may also influence the acquisition of a PC and knowledge related to it. We coined a hypothesis that the teachers participating in one’s ego-network influence the purchase of a PC and the development of PC- specific information.
6. A private enterprise demands innovative attitude on a large scale, because nowadays a computer is a basic existential instrument to many. In terms of our hypothesis the businessman acquintance increases the possibility of the purchase of a PC.
7. In our seventh hypothesis we pose that the leader of a company in the ego-net has a positive influence on the obtaining of a PC and PC-specific knowledge.
8. The position of an “official” is a particular, contemporary term, observed at Cserenfa as well. The “official” term covers the collective name of employees in an administrative position in a state institution. According to our eighth hypothesis the “officials” of the ego- network also influence positively the likelihood of a PC purchase.
9. Besides the above cases PC purchase is also influenced by computer technician acquintances.
During the survey analysis a certain column of questions refers to the extension and compostion of ego-network, as the explaining variant. We chose three questions from the questionnaire as the depending variant regarding PC possession and usage. The questions reffering to the PC possession and usage were not introduced by us.
1.table. Explanatory and dependent variables
EXTENSION OF EGO-NET
1. How many adult are in the household?
2. How many adult relatives do you have?
3. How many close friend do you have?
4. With how many people do you maintan relations?
1. Do you know to use a PC at least at a basic level?
2. Do you have a PC at home?
3. Do you use internet or e-mail?
COMPOSITION OF EGO-NET
5. How many of these are teachers?
6. How many of these are businessmen?
7. How many of these are company leaders?
8. How many of these are „officials”?
9. How many of these are informaticians?
The results concerning to the social capital influence on PC possession and usage were based both on the survey analysis and on participant obesrvation.
Regarding to the survey analysis the computer possession and its usage show that in 2003 in the Kaposvar-area 40,7% of the interviewees can handle a computer, 32,3% possess a PC and 15,8% use the Internet. During field work our discussions revealed that at Cserenfa many families cannot purchase a computer due to financial problems, but at the workplace or in the telehouse they use it and can deal with it properly. It might apear peculiar to see the small number of Internet users, but one needs to take into consideration that in some villages of the area the phone line makes it impossible to connect to the Internet.
2. chart: The frequency of PCs at home int he Kaposvár area
3.chart: The frequency of PC users int he Kaposvár area
4. chart: The frequency of interen users int he Kaposvár area
Based on 2003 survey data collection int he Kaposvár area, by Buapest University of Economics
During our research we dealt with the issues of possessing a computer and acquiring computer and Internet literacy. The analysis of these three factors could be realized only by surveys. In contrast with this, at our field work at Cserenfa the fact of possessing a computer or not was our starting point.
Based on the claster analysis of the answers regarding the extension of ego-network we found out that the majority (regardless of one small number cluster) can be put into three groups:
1. “Traditional village social network”: this is the group which has a strong social network with many friends and relatives. The average number of relations is 43. 21 of it are relative relations and 12 of it are friend relations. 4,8% of the interviewees had such ego-network.
2. “Average networks”: in this group people have an average number of relations. This is the group with at least 9 relatives, a few friends and fewer acquintances, altogether 26,6% of the interviewees .
3. “Marginals”: in the most common cases the individual lives in a family with two adults, an average number of 5 close relatives, 3 close friends and 8 acquintances. Most of the people belong to this cluster. (Our results show that the interviewees name a round number of friends and acquintances: 5, 10, 15 and 20 – this is to be noted later on. Most of them name 4 close relatives, 5 close friends and they keep in touch with 10.)
During the analysis process we utilized the results of the cluster analysis, correlation calculation and regression-analysis. In the case of regression-analysis we built in all the variants regarding the content and quantity of the relation-network. As a consequence, we could draw conclusions to their significance.
1. According to our first assumption, if there are more adults in a family, then it is easier to acquire computer literacy.
The interviews taken during the summer of 2002 showed that the purchase of a computer was an important decision due to fiancial problems or lack of appropriate scientific knowledge. The adults in the family get to know certain pieces of information regarding the purchase of a computer through their personal contacts. Serious financial decisions are made by adults, so, in our case, their social capital is crucial.
In the Kaposvár area 2 adult families are the most common (80% majority), followed by multigenerational families (with 3 or more adults) and 1 adult households.
Our quantitative analyses show that a significant relation exists between the number of adults in a household and computer – and Internet - specific literacy. The rise of the number of adults by units results in the 8% rise of the possibility of computer possession, 4% rise of computer literacy and 3% rise of Internet and e-mail usage in the household. One can also notice that in the case of the possession of a PC the most significant factor is the number of adults in the household.
The explanation of the causal relation may be due to social networks as well, in the sense that the adults discuss their experiences, so normal households possess more information than deficient ones. There may as well be some other kind of latent reason, like households with 2-3 working adults are better situated financially to buy a computer. We cannot reveal these latent reasons, but we can state that the rise of the number of adults in a family has a positive influence on the purchase of a computer and computer literacy.
Based on our personal experience we may claim that a PC is a sort of property and its acquisition leads to serious material and other kind of decisions. Further, based on the quantitative analyses we may state that there is a close connection between the possession of a computer and computer- and Internet-specific knowledge. Therefor, if an individual possesses either of these factors, it is highly probable that he will soon have the rest. During our field work at Cserenfa we also found out that the purchase of a computer isa very serious investment. In most of the households they wanted to help the expansion of the children’s computer-specific knowledge. Some opined that the scientific knowledge acquired at school can be widened at home with practice on the computer. Taking into consideration the financial situation, the families either bought a second-hand or a new computer, but most of them dealt with the idea that if once they invest in it, they should choose modern technology. In this case they asked for the help of an expert in this field. It is a general phenomenon during the field work that though children prompted the purchase of a PC, adults bought it with the assistance of acquintances. Along with our presuppositions it was proved that the parents used their personal relations to buy and install a PC. We also noticed that if a member of the household grew proficient in handling a PC, the rest supported its acquisition. Naturally, not every family had the appropriate financal frame to buy a PC, though a few who could deal with it planned to buy one in the near future.
2. According to our second assumption the number of close relative relations influences the acquisition of a PC and computer literacy.
The analyses lead to the conclusion that in the Kaposvar-area the number of close relatives does not explain the purchase of a computer and the acquisition of PC specific knowledge. In other words the relatives do not have an important role in the diffusion of PCs and relative skills.
During our field work we found out that computer- and computer related information spread in an diffusion-of-innovation manner. In case we can really speak about of a diffusional process, then its participants are not the “strong ties”, but the actors of “weak ties”, or other formal characters such as media or educational institutions. This fact was verified by the results of the field work. We noticed that those families who have outward social capital are more innovative. So, we can draw the conclusion that at Cserenfa the outward social network explains the people’s innovative tendencies and not the extension of relatives. During our discussions with the inhabitants of Cserenfa it was made clear that many gave their old computers as a present to their relatives, but they did not use them. The villagers also revealed that a small number of PC-owners bought PCs under the influence of relatives. Both cases show that at Cserenfa the diffusion of computers is not due to the relatives.
3. According to our third hypothesis the number of close friends also influences the purchase of a computer and the acquisition of specific knowledge. As Granovetter mentioned, it is weak ties and not strong ties that favour the adoption of innovation.
In this case our results can be interpreted in two ways: either there are overlaps between groups of relatives and friends or a third factor influences both groups. In the first case we may state that the circle of friends and relatives sometimes overlap: many good friends become relatives (brother-in law or godfather) and close friends may become close relatives. In the second case we may claim that a traditional village social network exists based on extended strong relations (friends and relatives). Whichever interpretation we may adopt, it is true that strong relations (friendship and relatives) are similar to each other. This is verified during the regression-analysis.
Based on our experiences at Cserenfa we have to emphasize another factor: localism. It created a strong connection between people, besides friends and relatives. Our first impression was that the inhabitants of Cserenfa lacked a strong local identity, but during the field work we grew to know that they were very much attached to the village. They did not allow an investor to create a fish pond to attract tourists, believing that “Cserenfa should be owned by its people”. The preservation of identity and its transmission is supported by authorities, millenium feasts, village memorial days and even the telehouse seems to serve this aim. The telehouse at Cserenfa was opened in August 2002 and we experienced that local children betwen the ages of 8-16 regarded it as a “modern playground”: they live the experiences of computer games brought from outside of the village here.
To put it simply, we may state that those inhabitants who have extended outward relations are likely to possess a PC. The majority of the villagers is attached to Kaposvar, situated 12 kms from Cserenfa, in different respects, among these the acceptance of a computer is mainly due to workplace, educational institutions and personal relations.
4. According to our fourth hypothesis an extended ego-network influences the acquisition of a computer and specific knowledge. To our surprise, the data showed that the extension of ego-network does not have a significant influence in the access of a computer and the acquisition of computer specific knowledge. An explanation to this phenomenon may be that an extended circle of acquintances is not only a characteristic of actors in the Kaposvar-area, but also of non- intellectuals mobile in their own social group.
We presented above that the local society – from the respect of ego-networks may be put into three groups: traditional village social network, average networks and the most common marginal networks. We found out that inhabitants who belong to the second group are more likely to have access to a computer and acquire specific knowledge. Extended traditional relations hinder the adoption of innovation, as marginalized situations and few relations do.
The surprising result draw our attention to structural equivalence, that is the analysis of relational patterns similar to each other.
The next illustration - created during the field work - shows who influenced who in the village to buy computers. Our question was: “Who usually helps you…?”. The participants are shown with dots, the relations with lines. The direction of lines shows the direction of consultation. We illustrate the participants outside the territory with black dots and the inhabitants of Cserenfa with red dots.
5. chart: Structural equivalence groups at Cserénfa 2003
With the help of whom did you bought the PC?
Who usually helps you in problems related to your PC?
On the basis of participant observation at Cserénfa.
The figure shows four structurally equivalent groups.
1. The isolated. A part of the inhabitants of Cserenfa are isolated (they do not help other villagers and do not reveal who they turn to for advice). They are shown in the top left corner. Supposedly their relation – network is far more extended, but does not originate in Cserenfa, so we could not reveal it with our methodology: participant observation.
2. Net advice seekers. From among the rest of the participants 7 are advise seekers. They can be seen on the right side of the illustration similarly to the isolated ones.
3. Net counselors. The figure on the left shows those to whom many turn for advice, but they themselves never get or seek advice. It is surprising that many ideas, suggestions and computer technical support reaches the village from the outside. The net counsellors are all from outside the village, most of them are institutions.
4. Mediators or brokers. Much information regarding computers originates from workplaces, acquintances and educational institutions. This knowledge reaches the village indirectly or directly through personal connections. We can see 7 such mediators in the centre of the illustration. The leader of the telehouse has a major role. His knowledge results from his previous workplace where she “experimented” with computers. 3 youngsters also have an outstanding role – “businessman”, “secondary school boy”, “college student” - who transmit their knowledge to a small number of group. No wonder these participants have the highest characteristic of in-between-mediation among the ego-networks. The participants of institutions in transmission of knowledge and those participants outside the village suggest that the puchase of a computer and the acquisition of computertechnical knowledge cannot be regarded as a diffusional process, since the transmission of innovation does not happen between participants, but only between certain participants of institutions and the actors.
We expected the confirmation of the results of our field work from UCINET CONCOR analysis, but this algorhythm provided us with sketchy results in our models, that is the four groups can be intepreted similarly, but there are no overlaps. We think that CONCOR algorhythm is insensitive to the direction of relations. In our interpretation the direction of consultation is important. Further, we would like to adopt a new structural algorhythm, which helps us to group the direction of relations.
6. chart: Structural equivalemt groups in CONCOR
Based on the field work and the questionnaire survey we found out that the adoption of innovation nowadays is not defined by the extension of ego-networks, but by indirect, personal relation to certain participants in an institution. In regard to this, it is of utmost importance to consider the following question: what kind of relations do we need to have to be easily integrated into informational society?
Further on we overview some such relations.
5. The educational society had the first possibility to acquire computer technology specific knowledge, since most of the schools today have computers and access to Internet due to state motivation and some special training in schools. According to our fifth hypothesis teacher acquintances in the ego-network have a positive influence on the purchase of a computer and the acquisition of computer-specific knowledge. Our research results show that there is a strong correlation between the teacher acquaintance and the possession of a PC and the knowledge to deal with it. A teacher in one’s ego-network increases the possibility of PC purchase and the acquisition of PC specific information by 3%. It is interesting to acknowledge that the teacher acquintance has a positive influence on the acquisition of Internet information, since in the area the phone line does not make it possible to connect to the Internet. We drew the conclusion that the acquisition of computer specific information is not connected to a place or location (somebody using the net at Kaposvar and teaching at Szilvasszentmarton.)
During our field work at Cserenfa computer proprietors did not mention that they acquired certain information from teacher acquintances or the idea of getting a computer originated from them, as there was no school in the village. Instead of those facts, many mentioned the role of schools. To our expectations we found out that school children directed the idea of a computer towards their parents, but during parental sessions at schools the parents themselves were faced with the idea coming from other parents or the teacher.
6. In our sixth hypothesis we analyzed the fact whether a businessman acquintance has an influence on the purchase of a computer.
Distinct statistics show contradicting results. It is possible that the businessmen, despite the fact that they are innovative due to their activities, have little time to pass on their expertise to friends. So if businessmen have certain possibilities, they still lack enough time to achieve results in the circle of their acquintances.
At Cserenfa most business households had a computer. In some cases, it was used by the children of the proprietor of the business. The businessmen at Cserenfa know about the Internet and its use, mainly from the telehouse. The direct effect of their innovative attitude cannot be measured by their followers or imitators but by their own behavior: some businessmen use the internet and e-mail at the Telehouse.
7. In our seventh hypothesis we conceptualized that the leader of a company in an ego-network influences the possession of a PC and specific knowledge.
Our analysis shows that a managing director acquintance increases the possibility of PC possession by 9,5 % , increases PC specific knowledge by 6,6% and Internet knowledge by 4,8%. This can be explained by the fact that supervisors hold it natural to have a PC and acquire scientific knowledge. Supposedly, one who has a supervisor acquintance – few such people in the model - are familiar with computer handling.
The interviewees at Cserenfa did not know managing directors.
8. According to our eighth hypothesis the „official” participant of ego-network has a positive influence on the purchase of a computer.
Based on our research results the relation is strongest between „official” acquintances and Internet specific knowledge. However, there is a close connection between computer possession and knowledge as well. A „official” acquintance raises the possibility of computer possession by 1%, computer knowledge by 3% and Internet usage by 3%.
The explanation is that in recent years computers have been introduced into offices in a larger number, which also motivated the acquisition of computer specific knowledge.
Our field work at Cserenfa supported our research: officials have a major role in the transmission of scientific knowledge. In the village we talked to one official, a civil servant and the leader of the telehouse with whom we also „logged on the net” (graph.nr.4) All of them acquired the ways of handling a computer at their workplace. The civil servant and the official got a computer (that is not personal computer, but the computer of his workplace) for domestic use due to an application and the office provides Internet access to them. The “official” passes on his knowledge to a student, the civil servant to none – this will probably change as they come to possess certain information. One of them is responsible for his acquintances’ duties: of his own will he types in official letters and prints them out. The leader of the Telehouse has a major role in transmitting information. 4 persons think he is an important source of help, 2 suggest the Telehouse as a source of consultation. This number would be higher if we conducted participant observation not only in the circle of computer owners.
9. Our ninth hypothesis states that computer possession is influenced by acquintances expert in computer technology.
Our research confirmed this realistic assumption only partially.
On the one hand, it turned out during statistics analyses that there was a close significant relation between computer literate acquintances and computer possession. In the regressive model with multiple variants these acquintances have an important role.
On the other hand, during our field work some signs pointed to the conclusion that computer literate persons do not always have computer specific cultural capital transmissive role.
During our field work at Cserenfa we found that computer literate people do not always transmit their knowledge. Such persons are undersocialized and have only a few relations. Among 22 computer owners we found 8 such persons in contrast to 7 who passed on their knowledge. This is also supported by the fact that the inhabitants of Cserenfa could not tell precisely who owned a computer and were misinformed on the first person who had a computer in the village or to what extent they could handle it.
To the question who had the first computer in the village, two-street Cserenfa provided two different answers: a college student and a businessman who obtained their PCs in 1996. They were not the first ones, there was one intellectual working at Kaposvár who had his PC earlier in 1992 but others also had one previously. The difference is that the knowledge did not reach the villagers from the early PC proprietors – so they did not sense the existence of a PC in the village - whereas the persons above consulted 2-3 other villagers, so the latter were at least aware of the former.
The result of participant observation provides the explanation that computer owner acquintance does not always pass on his knowledge, one cannot really turn to him for assistance.
The first key question of our study was in what ways social capital influences computer possession and specific knowledge.
Based on our research results we may propose that the extension of one’s ego-network does not always influence computer and scientific knowledge acquisition. Some ego-network characteristics (like too extended networks with strong relations, or marginalized situations) do not favour the adoption of innovation. The size of the household suggests a positive effect (the more adults there are in a family, it is more likely that they have a computer and can deal with it). But in this situation the effect mechanism is not clear: is this so, because more employees provide a better financial situation or because together they have a more extended social capital.
The composition of ego-network (who you need to get on well with) can be more easily analyzed with the collected data. Mainly teachers, officials, directors and computer literate people influence the individual’s computer possession and his knowledge positively. In contrast, businessmen acquintances’ positive influence was not found during the analyses.
We can draw the conclusions that the “quality” of relations influences the adoption of innovations, more likely than the “quantity”. This means that it is not important how many acquintances one has, but his circle of acquintances should be heterogeneous (according to Letenyei 1999), it should contain teachers, supervisors and officials, persons who do not belong to the individual’s social group.
Our results show that no significant connection can be seen between the extension of social network, computer possession and computer literacy. This is to support the fact that we are not talking of a diffusional process (Letenyei 2000, 2002 ), since the transmission of innovation is due to relations outside the village or between certain institutions and not to personal relations in the territory. As a consequence, it is indispensable to deal with the question of the diffusion of innovations in the next part of our study.
During our certain field works we experienced that the number of computer owners or computer literate people grows. The penetration of computers and the extension of their use increases year by year. This improvement in scientific literature is identified with the increasing section of the diffusion of innovations. In this way, according to Bornschier (2001) the expansion of Internet possession is part of a larger phenomenon, along with the diffusion of PCs, phone lines and Internet-client computers.
It was made clear at the analysis of social capital that the adoption of innovation is not defined by the dimension of ego-network extension, but by the existence or non-existence of indirect personal relations to participants of institutions. We had the possibility to conduct an analysis where we could observe on a small model the characteristics of computer diffusional process and computer specific knowledge expansion, which can be confirmed by the survey based on the small-area representative model. However, it is necessary for us to present the theoretical framework of diffusional innovations to support our research question.
Information technologies and Internet spread called forth a new paradigm (Volken 2002). In a small area computer technology and Internet serve as an innovation. Information technology expansion in our study is regarded as a kind of innovation-diffusion. For the purpose of the current research we referred to any computer and Internet related knowledge as “innovation”. “Innovation diffusion” is a type of process when computer related scientific knowledge is transmitted from one person to the other.
The concept of technical and economic innovation in economic scientific literature became popular as the keyword of the study “The Theory of Economic Development” (Schumpeter 1930). He differentiated between 5 types of innovation: new product, new process of production, source of acquisition or the establishment of a new organisation. The concept of innovation is treated similarly by authors since then.
The innovative processes and their effects on economic growth as well as the pattern of the process stands in the centre of economic interest. It seems Karshenas and Stoneman rightly state that the technological diffusion researches were not so popular in the scientific literature as research and development were (Karshenas and Stoneman 1995:291; cf. Dosi 2000, Conlisk 1989).
In contrast to economic approaches, economical-antropology and sociological studies put the diffusion of innovations in the focus of their attention. They referred to the diffusion of innovations as a process when the innovations became well-knonwn in a social group (Beal and Bohen 1955, in Rogers 1983:5). Authors regard the diffusion of innovation as a sociological phenomenon, because it could be analysed in referring to a social group. They use to say that the connections between people will determine the speed of the spread of innovations (Valente 1995).
The first diffusion analyses came from the field of economical-sociology. The first synopsis of diffusion research history was compiled in 1963 (Katz, Levine and Hamilton 1963, Rogers 1983). Maybe one of the most popular diffusion research nowadays was conducted in the field of public health, analyzing a new medicine, the tetracycline’s diffusion in the society of doctors (Coleman, Katz and Menzel 1966). In the 80s a lot of summaries appeared on the topic of diffusion (Granovetter 1983, Brown 1981, Mahajan és Peterson 1985, Fliegel 1993).
In the 1990-s a series of network-oriented articles were published on the theme of diffusion of innovation. The network researches are partly interested in modeling the diffusion of innovation. An excellent review of the recent models is presented by Valente (1995, 2003). Thanks to the methodological development the new methods and models have been introduced in different areas and fields: diffusion of information, diffusion of political opinions and/or organizational forms, or regional planning. The major part of these studies is focused on the estimation of the diffusion processes: “how information diffusion times and centrality measures depend on a series of network measures, such as degrees, bridges, etc?“ (Buskens and Yamaguchi 1999: 282, Chattoe 1998, Abrahamson and Rosenkopf 1997, Steyer and Zimmermann 1998). “How distances and relations between actors are likely to influence the growth and spread of social movements?“ (Hedström, Sandell and Stern 2001:146, Hedström 1994). “How can policy-makers stimulate innovation?“ (Christopoulos 2001:2).
The question of the social effects is also an important field of research. Castlefranci (2001) approached the problem as a socio-cognitive dispute. Strang and Macy (2001) studied the adaptive emulation in the case of success stories. Steyer and Zimmermann (1996) examined the mutual effects of the diffusion and social networks on each other. Frank, Topper and Zhao (2000) focused on the diffusions among members of organizations. “Members have common goals and identify with the collective of the organization. Thus they are more likely to support one another and more likely to exert social pressure on one another to adopt an innovation. While these processes have been noted, they have not been characterized under a general theoretical framework.” (Frank, Topper and Zhao 2000:2)
The problem of innovation-diffusion is also dealt with separately by the methodological books regarding to social network analysis(for example Knoke-Kuklinski 1982, Wasserman-Faust 1994, Valente 2003).
We overview the models of innovation expansion based on Valente (1995). He discusses them in four groups: structural diffusional network, relational diffusional network, thresholds models and critical mass models. The common factor of all models is the empirical S-shape graph which shows the spread of innovation and describes the expansion of innovation in a society: slow initial increase, sudden boost, then slowness again and lastly completeness.
5. chart: The empirical curve of diffusion of innovations
Based on Valente (1995) and Letenyei (2000)
Valente cites Granovetter in regard to the starting point of structural diffusion networks. Granovetter thinks that persons having expanded weak ties - people weakly embedded in society - are competent enough to mediate between groups within the society. In this way they transmit innovations.
The proposition of relational diffusion network models is that the speed of the spread of innovation is influenced by the personal relations of the members of society. Four subgroups can be mentioned: the opinion leader model (even public information reaches first people forming opinions, then is a second step the rest of the members of society), the model of group-participation (within certain groups some pieces of information spread fastly), the model based on the density of personal social network (it appraises the expansion of innovation based on the dimensions of ego-network) and finally the model of personal involvement (focuses on the question whether the ego-network contains points where innovation has already been used).
Valente’s idea is that thresholds and critical mass models belong to different schools but have a common root. In the sense of thresholds-models the individual’s threshold of the adoption of innovation equals the proportion of innovation users by which the individual tends to adopt innovation (Granovetter 1978). The model of critical mass has a similar approach: it analyzes how many members open to innovation a network needs in order not to break the process of innovation (Valente 1995).
Our research regarding the diffusion of computers abounds in keywords like innovation and diffusion. We may use the term “innovation” in connection with the possession of a computer and the acquisition of specific knowledge to the extent that besides containing innovative factors, it is appropriate in Schumpeter’s interpretation as well, that is it can introduce new technologies or make it possible to introduce previous technologies to the new market.
The concept of “diffusion” is much more precise: diffusion in scientific literature refers to the phenomenon when participants using innovation pass it on to participants yet unaware of innovation. In our present case – regarding the fact of PCs in certain households and the expansion of specific knowledge - we may refer to diffusion when the need for computers and appropriate knowledge is passed on by already competent users and PC owners to the rest. An alternative of diffusion is vertical, formal transmission of innovation based on a hierarchy.
In our study we cite Letenyei (2002) and use the difference between the terms “innovator” and “imitator”. An innovator is a person who introduces a new technology, he uses it for the first time in an area. An imitator is a person related to innovators, who uses the same computer to acquire specific knmowledge. An innovator serves as a gate: innovation reaches the area through him.
To answer the second keyquestion of our research we strive to achieve a practical result: we attempt to appraise the speed of the expansion of computers and computer related knowledge. In order to achieve our proposition we suppose that the expansion of the computer and related knowledge may be modelled with the diffusion of innovation.
The basis of our assumption within the framework of the field work we interpret the terms “innovation” and “diffusion” as presented in the theoretical part of the study. Both interpretations need empirical confirmation. Our first interpretation refers to diffusion:
1. Is the computer and computer related knowledge an innovation in the area of Kaposvar?
To answer the question we have to reveal the motivations of computer purchase and the acquisition of computer related knowledge. If the motivation is truly innovative, then we might suggest that computer purchase and the learning process may indeed be regarded as innovation. Contrary to this case(if computer games are the first priority for example) then the computer may not be regarded as innovation.
Our second interpretation refers to diffusion:
2. Can the S-graph of the spread of computers be empirically confirmed ? If yes, is this really the result of diffusion ? In other words: Did participants already familiar with innovation pass it on to the rest?
In case the answer to both of our questions is yes, that is the spread of computers and computer related knowledge may be regarded as innovation diffusion, then the process may be modelled and further appraised by one of the diffusion models.
Based on the interpretations we conceptualized two hypotheses.
1. The expansion of computers folow the S-graph explained by a diffusion process.
2. The expansion of computers and the acquisition of scientific knowledge originates from weak relations (“bridges”) outside the territory. Innovation reaches the area through knowledge.
During the analysis of the spread of computers we used the answers for two questions: in the first one we asked since when the household possessed a computer and in the second one we asked when the first computer reached the area.Using the representativness of the sample we could draw conclusions referring to Kapisvár area concerning the spread of computers.
During the process of survey in the area a column of questions tried to reveal the interviewees ego-network. We tried to put this complex question into operation through one point of view: the composition of related persons.
To map the motivations of transmission-adoption we proposed two questions. The first one analyzes the effect of personal relations, the second one researches user motivation, that is the purpose of purchase: what was the exact reason the respective household made the decision to buy a computer.
Further, we would like to present the results of the survey and those of participant observation. We follow the order of questions during the interpretation of the survey. Lastly, we present the mutual supportive network at Cserenfa based on participant observation.
During diffusion research it is crucial to know the date of the first innovation and the person of the innovator.
During our survey 77% of the interviewees could not provide an answer as regards the first computer in the area. When interpreting the 139 answers, we found it more appropriate to search for the reasons of the “I don’t know” answers. The results show that the majority of the inabitatants have no idea when the first computer arrived in the village and who the first owner was. In larger villages it is acceptable that the news of innovation spreads rather slowly. However, it is surprising that in a village with a couple of hundred inhabitants information does not spread in a way we expected. We tried to find reasons for it during participant observation.
At Cserenfa the inhabitants could not tell us precisely who had a computer then and they were misinformed about the first person who had a computer in the village and the persons who were computer literate. To the question: “What do you think how many families have a computer?”(we think 22 households) the answers extended between 2 and 14 families. Somebody named a person who actually did not have a computer.
The reason of the high rate of “I don’t know” answers and the reason of the misinformation could be the fact that the inhabitants of Cserenfa living in two streets do not really keep in touch. We suppose the geographical location of an area is important even in a small community. Our analyses showed that in the two streets the interviewees had different persons on mind as first computer owners: in one street they named a college student and in the other a businessman, both obtained their PCs in 1996. In reality an intellectual of Cserenfa working at Kaposvar already had his PC in 1992. The answer is provided by the computer consultant network of the village: while the intellectuals are situated on the periphery (they do not provide and do not get computer scientific knowledge to the villagers), the named persons have offered consultation to a few people, so the villagers were aware of them. Another inquiry technical reason is mistrust. One of our interviewees, who has owned a PC for a week said that besides his two neighbours who advised him in computer usage, nobody else knew about his PC, which was o.k.. He would not prefer others to come over and use the PC. And he was also careful as someone’s PC (who lived in the edge of the village) had already been stolen.
205 of all the households interviewed in the Kaposvar-area ( 32,4% of all the interviewees) had PCs and 197 answered to the question since when they have had a computer. The first computer was obtained in 1985, but most bought computers in 1998 (30 persons) and in 2002 (29 persons). Further, almost half of the inhabitants (46%) bought computers before 1999, and 54% after 1999 along the upcoming years.
2. table: Since When Have the Inhabitants of Kaposvár Area Had PCs?
By analyzing the chart we may see that the frequency and the cumulate graph corresponds to the generally accepted S-graph in innovation diffusion theories.
6. chart. The Spread of PCs in the Kaposvár Area.
By 800 representative sample in Kaposvár area
Taking into consideration the frequeny graph, we may predict that computer diffusion is still in the initial exponentially increasing stage. In the next few years a faster increase and then a slower one may be expected.
Within the frame of participant observation we collected data on households having a computer , so in this way we got to know when the first computer was bought.
7. chart. Spread of PCs at Cserénfa
Based on participant obeservation, 2003
The spread of computers at Cserenfa – similar to the data of Kaposvar area – reminds us of the initial data of the diffusional S-graph. In this stage the expansion of diffusion shows exponential increase, the number of new computer owners increases year by year. Taking a look at the graph we may draw the conclusion that a classical diffusional process exists in the village. The general opinion prevails that the village still stands in the preliminary stage.
As more and more households possess PCs, more people can transmit specific knowledge, so the number of PCs nuyers will eventually rise. This tendency – after the close of the increase period - will slow down in the future, and innovation will be accepted.
During the questionnaire of surveys 343 persons, more than half of the interviewees, who do not have a PC and do not plan to have one, we were not asked the above question. The several valid answers are shown in the graph (with the omission of the “I don’t know” category). Unfortunately, the rigid questionnaire did not allow other type of answers, so we do not know what the most important variant shows. Most (38,3%) replied that they decided to buy a PC influenced by the school. The interviewees valued the effect of the school higher than the effect of personal, relative, acquintance and other type of relations.
8. chart. Who/What Was the Effect for PC Purchase in the Kaposvár Area
Based on surveys in Kaposvár area, 2003
From a different point of view we may group the answers in two. The first contains alternatives characteristic to personal relations (close friend, computer literate acquintance), the second contains the possibilities of relating to an institution (TV, media, school, workplace, colleagues, telehouse, specific programs). Aggregating the two, we arrive to the following results (we left out other type of answers, as we cannot interpret them from this point of view):
3. table.The personal versus the institutional effect in the Kaposvár area
Personal or relational effect
Based on surveys in Kaposvár area, 2003
The content of the chart from the point of view of our research is very important: it contradicts the theory that the spread of computers is a diffusional process. A common feature of diffusional processes is that participants open to innovation are willing to pass it on to the rest. In this case we deal with a different situation: some institutions, like school, and to a certain extent the workplace pass on the need for computer technique and the acquisition of proper knowledge, realizing a kind of one-way communication.
The question may arise that the institution as itself or its participants are in effect. If a member of a family buys a PC to the effect of his colleagues or if the child suggests its purchase to the family influenced by his peers or teachers, then we may speak of motivation based on personal relations. The analysis of this question will not be dealt with in this study. However, we think that the effect of the institution still remains the same if the individual gets in touch with it through relatives, friends, colleagues, peers.
The major role of the school supports our idea that the motivation of investment is mainly due to chidren and their interests. We could not analyze the fact whether the child really needs a computer to make progress at school or - because there is computer technical education at every primary school- he gets to know computer games and motivates his parents to buy one. It is not questionable that in any case, it is only advantageous for the student to put in practice at home all the theory taught at school. He can have access to it any time and he develops his knowledge even while playing.
The category of “close friend, acquintance, relative” got to the third place. This supports our result that the use of a computer expands to a lesser extent due to strong relations.
The result shows that TV and media have a lesser influence on the expansion of information technology.
It seems institutions have the role to form opinions.
During the participant observation at Cserenfa we tried to find out why people bought PCs and who they were influenced by.12 of 22 PC owners said they needed one for their work, so their workplace motivated them for the purchase. Besides labourers among them, we may find brokers, businessmen and econimists as well. The rest of the households did not say any information or they simply marked the school as a motivational factor. They did not mark personal relations (my relatives had one, the idea came from him) – which would have contradicted our previous assumptions.
The Telehouse has a particular role in developing the need for PC purchase. Youngsters often come together to play there. From this circle only a few bought PCs so they did not appear in our model.
The inhabitants revealed some interesting information regarding PC purchase. It was not likely - as we expected - that a second-hand PC got to the household, they all bought it in shops. Before that they inquired about it, often seeking advice from acquintances.They were people outside Cserenfa: colleagues at Kaposvar, relatives from Pecs, friends at Szentbalazs. Information regarding PC usage (winchester, monitor) do not spread wihin the network, they rather reach the village from the outer world in different ways to every household. We can state that the computer did not reach Cserenfa through an innovator, so we cannot speak of imitators within the local network. The experiences of participant observation stand in line with the data of surveys: despite the fact that computer usage expands in the area in the shape of diffusional S-graph, we cannot speak of a diffusional process as the participants are not influenced by each other, since institutions motivate them for the purchase. The role of personal relations is also diminutive in the obtainment of the PCs, but the PC buyers rely on personal relations to acquire specific knowledge.
The last question tried to reveal the motivations for computer purchase. The question was posed to those who have basic motivation. Most replies outlined the children’s unequal opportunities and studying as first and second motivation. We find another proof that parents think it is important to buy a computer so that their children keep up with computer technical development.
During our field work at Cserenfa most parents said – from among the group who use their computers at their workplace – the computer will not change their lives, only their children’s lives. The purchase of a computer can be seen as an investment. First as computer game players then as serious computer users, the chidren will join the company of users all over the world. 2 ten-year old boys and a mother thought that a computer was necessary for studies, 6 children marked games as a motivational factor. This does not mean that in other households they disregard playing on the computer. On the contrary, they mostly play on the computer. It is natural that in a new device we find it interesting to play on it. The question remains whether the current players soon experience its other ways of usage. In the circle of youngsters, girls use Microsoft Word to type in letters of invitations and other small things. Supposedly they would need this program later on in their studies as well.
During our survey we tried to answer the question from where the users acquire specific knowledge. We would expect that in a village according to innovation diffusion theories, knowledge spreads from house to house as in a local community. The field work at cserenfa contradicted the expectations of the diffusion theory. Within the local community we may speak of diffusion when children exchange gameprograms and musicfiles. The knowledge to more serious programs comes from outside: acquintainces from Kaposvar, relatives, colleagues or people met at some places of entertainment.
With regard to geographical distances, an advantage of the community is that it is local. It would not be costly to go over to the neighbour for some information, than to travel to Kaposvar or call Szentbalazs. Still, this last attitude is most common. Theoretically, the explanation for this is that the villagers do no trust each other’s knowledge, that is why they turn outside. Our experiences do not support this theory.There are some computer literate inhabitants and almost each family mentioned someone whose knowledge they could rely on so we cannot speak of distrust. We think some longtme relations characterize the community: they ask guidance from those people whom they turned to for the first time, even if this is not an effective solution from a rationalistic point of view.
The chart above shows who turns for consultation to whom. The interviewees are anonymous, only their occupation is mentioned. The chart does not show the relations outside the village. The arrow on the chart shows open asymetrical relation: it directs from the consultant to the advised, based on the latter’s designation.
10. chart. Informatical consultation’s social network at Cserénfa
8 persons, one third of PC owners are isolated, that is they do not have consultants in the village, which is quite surprising in a community of 270 inhabitants among 22 PC owners. Most computer related knowledge reached the community from different workplaces and educational institutions.
On the basis of the results we may state that at Cserenfa the social network do not have a strong centralization figure. We need to refer to Thomas Valente once again, namely that diffusion may be observed among the members of society. We think that the spread of computers in the community cannot be viewed as a diffusional process, because the need for computers does not come from and is not passed on from user to user, rather it originates from institutional participants.
The second question of our study was whether the spread of computers can be seen as a diffusional process of innovation. In other words: can computer purchase or the acquisition of specific knowledge be explained by relational data.
Our research results show that computer purchase and knowledge related to it is not influenced by relations between people. Certain institutions have a far more important role in it (workplace, school, telehouse).
In our study we also concentrated on the transmission of innovation and the motivations lying behind its adoption. This question was answered by participant observation. It is characteristic of innovations that - because they bring economic growth - with its transmission one’s own profit becomes less: the more people live with opportunities gained from innovation, the more share the profit. This makes the diffusion of innovation slow down a bit. This does not refer to computers: the profit of the innovation transmitter does not become less if the neighbour also buys a computer According to current countryside practice a computer does not serve as a working tool, rather for fun, for children and the next generation. The computer can also be viewed as a modern toy, which later turns to a device serving more serious aims. Cserenfa did not receive computers from one particular innovator, nor did the adoption of previous technologies either. In this sense, since there was nobody to turn to, we cannot speak of imitators within the local network. Most households gained information from elsewhere.
The results of active participation overlap with the results of quantitative reasearch done in the area: the purchase of a computer and knowledge related to it is not generated by personal relations, rather by institutions, like the Szentbalazs Primary School and certain workplaces. The graph showing the spread of computers can be seen as corresponding to the S-graph occurring in certain theories as a starting point. Based on this we can claim that computer spread is in the initial, exponentially growing stage, which later will turn into a slowly increasing process. We argue whether we can speak of diffusion as the relation between participants do not play an important role, rather participants of institutions serve for this purpose.
To answer our research questions:
1. The spread of computers can be seen as innovation, its purchase is an investment in the future to make sure the generations’ equal opportunities.
2. The spread of computers cannot be viewed as a diffusional process (the participants do not transmit specific knowledge and the need for a computer).
It is not a diffusional process, so in this sense it is undesirable to predict the next stages of the process with diffusional models.
Our study focused on two main research questions:
1. How many and what kind of acquintances does an individual need to have to possess a computer and knowledge related to it?
2. Can the S- graph suggesting innovation diffusion be applied in the case of the spread of computers? Can the spread of computers be regarded as a diffusional process of innovation? If yes, can it be predicted by a diffusional model?
Our research questions were examined in a sample area with two methods: a sociological survey and anthropological participant observation.
Examining our first question we found out that the number or in other words the “quantity” of an individual’s social relations has a diminutive influence on computer purchase and the acquisition of related knowledge. The “quality” of the relations is far more important from the point of view of IT usage: a teacher, a businessman or an official may have a major influence in increasing the individual’s need for a computer and the acquisition of scientific knowledge. It is interesting to notice that acquintances connected in some way to an institution have an effect on IT usage from the individual’s point of view.
Our research shows that the build-up of information society depends on materials, spirituals and good relations as well. We believe that an important means to shape information society is relational consultation.
This observation leads us to the second question of our study: what kind of role do social relations play in the diffusion of innovation?
According to Valente (1995) we refer to a diffusional process when during an expansion innovation is passed on from users to adopters. The spread of innovation can be predicted by several models, their common trait being the S-graph. The cumulated graph showing the spread of computers is the same as the S shape of the exponentially increasing phase of diffusion. After meticulous analysis, we need to state that there is no diffusional process in this case because innovation is not transmitted by participants open to it on to new adopters. Knowledge is passed on through certain institutions (schools, workplaces). Institutions have a key role in the diffusional process and the shape of exponential increase - however, we do not know the effects of the mechanism yet.
Western scientific literature has more empirical examples to the function of diffusional S-graph in other cities. We find two possible answers for the distinction:
1. It may be probable, that the diffusional graph may function in the case when people do not transmit knowledge, firstly, it is passed on by institutions. We may think that IT does not necessarily need a critical crowd to adopt the innovation and make sure its expansion.
2. It may be so that in Hungary the built up of information society has a separate route than abroad. In Western societeies we may speak of a real diffusional process, in Hungary one is faced with a more centralized process in which the state - and to a lesser extent the significant participants of economy - has a focal role through educational institutions and local government.
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