Elements of Trust: The Cultural Dimension of Internet Diffusion Revisited1


Thomas Volken University of Zurich



For quite some time sociologists have been discussing information and communication technologies (ICT) as the heart and engine of societal change. But only recently have researchers begun to investigate the cultural preconditions of technological change. Trust as a cultural resource not only acts as a lubricant for transactions and fosters economic growth, which has been empirically demonstrated by recent research, but also facilitates more, and more innovative, actions. Bornschier in his seminal work on Internet diffusion in 34 developed countries finds strong empirical evidence that generalized trust is a necessary precondition for successful technological change. The context in which Bornschier (2001a) considered this question, however, as well as the conceptualization of trust, may have seriously affected his findings. Trust is a complex construct with multiple dimensions, and their relative effects on innovative actions may be highly dependent on their respective social context. The latter may be especially relevant in the highly fragile context of Eastern European transformation societies. This paper leads to the thesis that institutional properties (trust in systems) – rather than interpersonal generalized trust – substantially account for the differences in the diffusion of ICT not only between the transformation societies, but between developed societies as well. Using data of 47 countries from the World Values Survey and other sources, I can present strong empirical support for this thesis. Effects remain persistent even after controlling for material wealth, Internet access cost, early proliferation of tertiary education and density of scientists and engineers in research and development.

1 Introduction

Since the beginning of the 1990s the general concept of social capital and one of its specific forms, trust, has attracted substantial interest among the research community. In the field of economic sociology, generalized trust has been found in comparative studies to be a potent predictor of economic efficiency besides the conventional growth factors (Knack/Keefer 1997; Bornschier 2000; Leicht 2000; Whitely 2000; Zak/Knack 2001). Theoretically, it is argued that generalized trust functions as a cultural resource, which makes economic exchange and transactions more productive by allowing for more, and more encompassing, actions (networking), by reducing transaction costs and costly controls as well as by enhancing the flow of information.

However, trust is also important to innovation. Bornschier (2001a), in line with others (Humphrey/Schmitz 1998; Lorenz 1999; Moore 1999; Maskell 2000), argues that trust is likely to favor technological innovation and change. He empirically tested this claim by using trust as a predictor for cross-country differences in the diffusion of Internet hosts (1997 and 1999) and found statistically robust effects, which for his sample of rich countries were substantial. The context in which Bornschier (2001a) considered this question, however, as well as the conceptualization of trust, may have seriously affected his findings. Trust is a complex construct with multiple dimensions, and their relative effects on innovative actions may be highly dependent on their respective social context. The latter may be especially relevant in the highly fragile context of Eastern European transformation societies where trust in systems as compared to trust in generalized others may prove to be much more conductive to innovative actions. In this paper I shall explore these issues.

Section 2 outlines why trust must be considered important for innovative actions and addresses two conceptually different dimensions of trust and considers how different social contexts intersect with these dimensions. Section 3 presents the samples and data, section 4 presents the model as well as the method of analysis. Section 5 discusses the empirical findings and section 6 concludes with some remarks on further research.

2 Theory

Trust fulfills various and important societal functions. Most importantly for our concerns here, it facilitates innovative actions. However, this implicitly supposes that innovative actions are in need of the cultural resource of trust. Why is this? The argument here is inherently linked to the concept of a discontinuous technological change, as first formulated by Joseph Schumpeter (1912) and then further developed by other authors (Freeman, Clark, and Soete 1982; Perez 1983, 1985; Bornschier 1988, 1996, 1998, 2000; Freeman 1992). In short, the basic idea is that innovations2 are not a continuous but a discontinuous phenomenon over time. Falling profit rates enforce a re-allocation of capital and motivate entrepreneurs to search for new business opportunities. Once a radical innovation – that is, an innovation with the potential of a quantum leap in productivity, which transcends all spheres of society (Perez 1983, 1985) – emerges, there tends to be a clustering or swarming of further innovations, since entrepreneurs are attracted by the high profits involved with the new products. As a result, a new technological style or technological paradigm is born. This new technological style may act as the engine of a new Kondratiev upswing but, at the same time, it is the catalyst of what Schumpeter termed creative destruction. The commercialization of the Internet may well be regarded as a phase where such a new technological paradigm emerged. It is the high degree of market uncertainties and the absence of established “best practices” (Perez 1983) which make innovative action for entrepreneurs extremely risky. These risks, which have their origin in the very logic of the economic sphere (the socio-economic sub-system), are, moreover, reinforced by the lack of institutional arrangements. According to Perez (1983, 1985), this mismatch between the socio-economic and the socio-institutional sub-systems must be overcome and the two spheres synchronized in order to allow the new technological style to unfold its full potential.

Faced with this double risk, capital destruction due to market uncertainties and the lack of adequate institutional arrangements, entrepreneurs must have substantial trust in order to overcome these risks and innovate.

Finally it is clearly not sufficient that only the supply side develops the necessary amount of trust to innovate. The demand side has to trust as well in order to take up and use the innovation. This might be especially problematic in the purely digital arena of the Internet, as Brinkmann and Seifert (2001) have pointed out in their study of Internet auctioning at eBay.

Trust, one can summarize, is of fundamental importance for the diffusion of a new technological style in the knowledge society. Firstly, trust expands the scope of action and allows firms to enter into cooperative exchange under contingent conditions. More and new actions become possible because cooperative networks are effective and efficient channels for the flow of information and new ideas (Granovetter 1973). At the same time, trust substantially reduces transaction, control, monitoring and enforcement costs and therefore makes available more resources for productive use. Innovative networks with a high level of trust tend to reinforce not only the innovate capacity but also trust (Fecker 2001). Secondly, the critical phase of creative destruction imperatively demands trust in the self-transforming capacity of the socio-institutional sub-system. If agents believe that efficient and effective institutions are able to produce public goods, that is, infrastructure, rights, liabilities and regulations, which facilitate and secure the diffusion of the new technological style, they will be more prone to supply as well as demand the goods and services of the new technological era. Trust as a cultural resource raises the overall innovative capacity of a social system, since it allows economic and also political agents to take advantage of their extended potential for action. The matching process between the socio-economic and the socio-instititonal sub-systems may therefore be substantially accelerated, leading to a faster diffusion of the new technological style.

2.2 Towards a Heuristic Model of Trust

While the central problem of contemporary theories of trust is their rather static character, empirical research tends to underestimate the complexity of the concept. On the one hand, the dynamics of trust relations on various levels of society have so far attracted only marginal theoretical attention and the link between trust and time in particular has been substantially under-reflected. Of course, many scholars have pointed to historical processes of social change which resulted in a fundamental restructuring of trust relations (Simmel [1908] 1992b; Luhmann [1968] 1989; Giddens 1991). Alas, these authors, in concentrating on the object, fail to adequately address the subject of trust and the time-related character of their expectations. On the other hand, empirical studies tend to neglect the fact that trust may have different sources and these sources may substantially vary in their effects on innovative actions.

I therefore propose a simple heuristic model of trust which tries to capture two different sources of expectations – rationality and morality. They are the elements of trust; thus I shall speak of rational and moral trust whenever I focus on the trustor and his expectations.

Rational Trust

The basis of all forms of trust is experience. Trust needs a historical background and is impossible without empirical evidence (Simmel [1908] 1992b; Luhmann [1968] 1989). In the situation of rational trust, agents behave rationally insofar as they consciously take into account the expected costs and benefits when they decide whether to trust or not. Trust here may gradually evolve when agents repeatedly interact and get to know each other’s preferences better; very often this situation reflects the iterated prisoner’s dilemma game (Axelrod 1984). Since the production of trust through repeated interaction is very time consuming, rational trust based on interaction between individuals cannot easily generalize, and exchange relations under conditions of high risks tend to remain very limited (Kollock 1994; Yamagishi, Cook, and Watabe 1998) and may even resemble Granovetter’s (1973) strong ties. Therefore, to some degree, rational trust is always a situation of minimal trust (Humphrey/Schmitz 1998). However, introducing a powerful, external sanctioning apparatus which is able to modify agents’ motive structures can substantially expand the aggregate level of rational trust. On the one hand, sanctions change the costs perceived by the object of trust when he/she assesses the benefits resulting from breaking trust. And at the same time the general level of trustworthiness, as perceived by the subject of trust, is increased. Of course these mechanisms require that agents perceive the sanctioning apparatus itself as trustworthy. On the aggregated societal level, sanctions help the trustor to save time, since less time is required to gather information and accumulate experience through repeated interaction with potential exchange partners. This in turn substantially stimulates the expansion of exchange relations. In yet another sense, time is crucial. Since rational trust is based on experience which is mediated through the behavior of others, as well as rational cost-benefit calculations, it has two advantages. It may be monitored and influenced more easily by an external sanctioning instance; and it can be learned much faster, because no complex adaptation of intrinsic motives is needed. A trustworthy, effective and efficient sanctioning apparatus can for this very reason succeed in modifying the external costs-benefit structure of agents in a fairly small amount of time. Through the building and enforcement of rules that favor cooperative behavior and punish opportunistic behavior, trust can substantially be expanded. To be sure, rational trust, even in the presence of a powerful sanctioning apparatus, is still minimal trust, because agents in the absence of sanctions would very often have strong incentives to behave opportunistically.

Moral Trust

Values, norms and attitudes, as they are understood here, are patterns of shared orientations, which are culturally transmitted through processes of socialization and enculturation and remain relatively stable over time (Parsons [1939] 1994; Inglehart 1977, 1990; 1998; Inglehart/Baker 2000; Kunz 2000). Although those habitualized moral maps may influence the structure of motives and behavior, they cannot survive without periodic empirical support in the long run. This means that cultural patterns have to be reproduced through behavior. This is why a cooperative ethos in an environment of rampant opportunism is doomed to fail (Rothstein 2000) and other forms of moral maps develop, e.g. Banfield’s (1958) well-known amoral familialism, which optimizes the short-term utility of the core family, might evolve as the dominant ethos. Socialization, with regard to time, on the one hand points to a long period of cultural learning, which typically takes place in the formative years of childhood and youth. On the other hand, although the process of socialization must be understood as a life-long endeavor, moral maps stabilize and may not easily be changed. Common norms, values, and attitudes – in short, a generalized moral – help agents to recognize the goals and preferences of others; they structure expectations. However, a generalized moral need not necessarily result in the generalization of trust, since the expansion of trust is inherently dependent on a cooperative and inclusive ethos. The term moral trust, as it is used here, therefore refers to norms, values, and attitudes which enable and foster the generalization of cooperative actions. Once a cooperative moral diffuses in a society it develops its productive potential by acting as a substitute and catalyst of the norms, regulations and controls of the sanctioning apparatus. Agents will refrain from negatively-sanctioned opportunistic actions, even if their actions would not be detected. Since aspects of the common good are internalized, norm enforcement by the state is of subsidiary character, because agents feel that their common interests are adequately represented by the political and legal institutions.

The Aggregate Level of Trust in a Society

In harsh contrast to rational trust, moral maps cannot be authoritatively enforced, because this would threaten their intrinsic status. The elements of trust can only productively cumulate if they complement and are related to each other. A society will ideally reach a maximum level of trust if its socially sanctioned practices represent a common cooperative moral ethos and group solidarity is inclusive. In such societies, the sanctioning apparatus commands substantial reputation and legitimacy, and it works efficiently and effectively. The time horizon of agents is typically long term and agents’ motivations not only follow economic principles but moral and social ones as well (Korczynski 2000). Exchange relations in these contexts can be extended, even if in a particular relation an objective basis for trust is absent. The trustworthiness of agents is set as an apriori. This also permits the further production of collective goods, which add to the productive and adaptive capacity of the society as a whole and may strengthen the collective myth. However well coordinated and well developed the elements of trust in a given society are, their aggregated level of trust may be substantially lower than other societies’ or a historical period. The form, function, and power of a sanctioning apparatus as well as its legitimacy, efficiency, and effectiveness may change substantially and therefore influence the radius of rational trust in a society. The moral base of a society can shift over time and either motivate or hinder the extension of cooperative actions.

Since it has been rightfully argued by many authors (Seligman/Füzer 1994; Sztompka 1995, 1996; Misztal 1996) that the Eastern European transformation process is accompanied by widespread syndromes of anomie, such as low levels of shared cooperative orientations and attitudes, exploding rates of homicide and suicide, and increasing deaths from liver diseases, it may be argued that countries involved in this process of radical economic, political and social change face a situation, which may be characterized as a “start from scratch”. The specific problem which transformation countries face is the creation of two major institutions of modernity at the same time: markets and democracy. This, however, means that agents must learn to trust a completely new institutional framework as well as their fellow agents’ trust in it. This learning process takes time and advances step by step. When assuming a hypothetical “start from scratch” (approximately 1990) for all transformation countries, it then follows that those which were able to systematically promote rational trust will be better off in terms of cooperative and innovative capabilities. Because rational trust is grounded in agents’ experiences and does not need to be intrinsically motivated, it is safe to suggest that with regard to the object of trust, rational trust in modernity is fundamentally related to and secured by systems (Luhmann [1968] 1989; Giddens 1991).

Since we have no coherent data on how the trustors evaluate and perceive the new systemic properties, the object of trust – that is systems and their potential to extend trust – has to be taken as a proxy. As transformation countries put into practice effective and efficient democratic procedures and bureaucracies, follow the rule of law, fight corruption, welcome a free and independent press and promote economic freedom, they create a systemic environment which promotes rational trust (trustors’ perspective) and therefore strives for the realization of its own potential (trustees’ perspective). Rational trust and trust in systems are thus simply different aspects of the same coin. While trust in systems may be easily and relatively quickly promoted and learned by experience, trust in generalized others, as structured by moral expectations and feelings of identity and solidarity, is much more difficult to achieve. With regard to transformation societies, one can expect there to be trust in generalized others of subordinate importance, as compared to trust in systems, since the structure as well as the production of moral maps and solidarity is bound to processes of socialization and enculturation, which by definition consume time (Inglehart 1998; Inglehart/Baker 2000).

If notoriously social disorder and anomie plague a social context the best strategy might be to improve trust in systems, since, as stated earlier, it is far easier to learn, and can be produced fairly quickly, when sanctioning agents act efficiently and effectively (see also Knack/Keefer 1997; Humphrey/Schmitz 1998; Moore 1999). According to many scholars (Seligman/Füzer 1994; Sztompka 1995, 1996; Misztal 1996; Govier 1997), the situation of anomie – a result of the radical transformation process – is the prevailing scenario in transformation society.

One would therefore hypothesize that those countries which succeeded in building up trust in systems after the collapse of communist rule have more resources available for innovation. Accordingly, the effect of generalized trust in these transformation contexts should only be of minor importance as compared to trust in systems.

With regard to advanced countries, the influence structure and effects of trust are expected to change considerably. The importance of trust in systems as compared to generalized trust, it is suggested, should be substantially lower in advanced countries. More formally, one would expect the net effects of aggregated generalized trust G * and aggregated system trust S * in the context of transformation societies T and advanced democracies A to be3 :

Hypothesis I: (GT * ≠ 0) ∧ (ST * ≠ 0) ∧ (GA* ≠ 0) ∧ (SA * ≠ 0)

Both dimensions of trust will be significant across all country samples.

Hypothesis II: ST * >> GT * ((ST * : GT * ) > (SA * : GA * ))

Trust in systems will be more important in transformation societies as compared to advanced democracies.

3 Sample and Data4

In order to test the differential effects of trust in systems and generalized trust on innovative action, as measured by the diffusion of Internet hosts, four samples have been established. The first sample consists of twenty advanced democracies5 , the second sample is entirely reserved for the eighteen transformation countries6 , and the third sample is a pooled sample of the previous two (n=38). Finally, the fourth sample adds nine developing countries to the third sample, so that the maximum sample size of forty-seven countries is reached. Cross-sectional regression parameters have been estimated for all four samples in order to substantiate the claim that the effect of the different forms of trust might vary depending on the general conditions in the context.

As suggested, the commercialization of the Internet can well be regarded as the emergence of a new technological paradigm. The diffusion of Internet hosts, relative to a country’s population (Internet Software Consortium 2000), may therefore serve as a proxy of its innovative capacity. Although it is not entirely unproblematic to use the number of Internet hosts as a measurement for the diffusion of Internet technology as a whole, it still seems to be safe, because it has been demonstrated (Bornschier 2001a) that the diffusion of Internet hosts is part of a broader syndrome which goes together with a corresponding diffusion of personal computers, telephone mainlines and Internet client computers7 .

A principal component analysis (PCA) has been used to construct the two distinct dimensions of trust – the independent variables under study. As indicated by the PCA in table 1, two factors, which explain 75 percent of the variance, could be extracted. The item loading on both of the two factors clearly follows the theoretical distinction between trust in systems and trust in generalized others8 . The first dimension, which reflects trust in systems, shows a high correlation with those indicators, which point to a high degree of bureaucratic efficiency, the rule of law, absence of corruption, and the functioning of democratic procedures. A certain path dependence of these systemic properties is demonstrated by the high loading of autocracy and democracy between 1900 and 1945.

And this may substantiate the claim that trust in systems is to some degree historically transported (Putnam 1993; Rothstein 2000). The second dimension extracted by the principal component analysis can clearly be identified as trust in generalized others. Here items which mirror the parts of the moral map load high.

Table 1: Modern forms of trust: generalized trust and trust in systems


The living tolerance of liberal individualism substantially fosters trust in generalized others, while a culture of amoral egoism with its reckless opportunism reduces generalized trust, as indicated by the negative item loading9 . Moral determinism also has a substantial negative loading on the second component. Finally it shows that trust, as measured by the well-known question of the World Values Survey10 , seems to be more associated with values, attitudes, and moral orientations than with institutions. This certainly has to be kept in mind for further analysis.

4 The Model

The productive link between the innovative capacity of a society and its aggregate level of generalized trust and trust in systems has already been discussed. Yet, since countries may vary greatly in their resources, several control variables must be introduced. These are briefly discussed here.

Countries may vary in their asset of material resources, and therefore in their capacity to influence demand as well as the supply side factors of the diffusion process, the level of development or average wealth must be controlled for. Another factor, which may substantially affect the innovative capacity of a context, is the availability of human capital (Romer 1990; Stern, Porter, and Furman 2000; Fecker 2001). Not only are the roots of the early diffusion of Internet technologies tightly coupled with the academic community but, at the same time, the Internet favors those who are used to abstract symbol processing, as has been substantiated by various studies which examine the so called digital divide11 . The availability of human capital is therefore relevant in two ways. First of all, knowledge workers are a fundamental requirement for technological development. They provide the supplies that entrepreneurs can exploit. On the other hand, human capital is needed in order to productively use this new technology; in economic terms, it is also a demand-side factor. For these two important reasons, one would want to control for human resources, since it may be rightfully expected that the diffusion of Internet hosts is to some degree dependent on it. Finally, it can be argued that it is not just the average wealth in a context which considerably influences the diffusion of Internet technologies. Whether agents can afford the new technologies is essentially dependent on the relative costs of access. Where these costs are high in relation to average income, the diffusion of Internet hosts is expected to be hampered. Thus, it may not be the absence of adequate monetary resources alone which limit the possibility of financing important infrastructure projects (backbones, telephone mainlines etc.), and therefore hinder the exploitation of the new technological paradigm’s potential. It may as well simply be the extraordinarily high prices involved in the consumption of the new goods. Hence it seems reasonable that those relative Internet access costs are controlled for.

The model used to estimate the diffusion of Internet hosts follows a production function of the Cobb-Douglas type because it is supposed that various multiplier effects are present and predictors directly and indirectly influence each other. This is also true for the control variabels. For example, one may suppose that the different forms of trust directly affect the diffusion of Internet hosts through their potential to reduce all sorts of transaction costs, and indirectly have an effect on the diffusion by influencing the propensity to invest in human capital. In societies with low levels of trust, investments in human capital might prove to be inefficient and ineffective if ascriptive attributes, such as membership in an exclusive group, are used to allocate (management) jobs (Whiteley 2000). However interesting and fruitful these effects may be, they are beyond the theoretical scope of this paper.

The model used to estimate the diffusion of Internet hosts is as following:

Ii = b1Si b2 Gi b3 Wi b4 Ti b5 Bi b6 Vi b7 e ui

In order to specify a linear model, the estimation model is transformed as following:

log Ii = log b1 + b2 log Si + b3 log G + b4 log W + b5 log T + b6 log B + b7 log V + ui

The dependent variable I is the diffusion of Internet host per 10,000 inhabitants, S stands for trust in systems, G for generalized trust, W refers to the average wealth in the country, T reflects the technical competence and B the proliferation of tertiary education. Finally V is the relative Internet access costs and u i is the residual12 .

5 Results of the Parameter Estimation

Tables 2 and 3 show the results of the parameter estimates for each of the four samples. While Table 2 allows the detailed examination of the influence structure (all predictors are included here), Table 3 shows the results when only the significant predictors make part of the model (stepwise exclusion of predictors, which are statistically not insignificant). First of all, Table 2 shows that the influence structure of the variables nearly perfectly reflects the theoretical reasoning. And this is true for all models. The diffusion of Internet hosts increases together with increasing trust resources. Both, generalized trust and trust in systems display significant and positive effects across all samples. Thus hypothesis I gains substantial support.

Table 2: Diffusion of Internet hosts, January 2000 – Linear regression with inclusion of all variables


The control variables also display a coherent pattern. They are briefly discussed here in order to strengthen the plausibility of the model. The diffusion of Internet hosts increases with average wealth, and the proliferation of tertiary education, and it decreases with increasing access costs. However, the latter cannot be substantiated in the sample of the advanced democracies (see Sample 1). There the control variable points in precisely the opposite direction. However, this may be explained by the extraordinarily low relative access costs. In addition its influence is statistically not significant. Furthermore, one does not find the suggested effects of technical competence in the two pooled samples. This reflects the fact that, in these heterogeneous samples, the very high level of technical competence in Eastern European countries is accompanied by only moderate or low levels of Internet diffusion as compared to the advanced economies.

Table 3: Diffusion of Internet hosts, January 2000 – Linear regression with stepwise exclusion of variables


When looking at the models in Table 3, one can reveal, for the sample of advanced democracies, a substantial and significant effect of trust in systems (b=.61) and generalized trust (b=.57). The relative influence of the two discrete resources of trust is approximately the same, whereas the relative effect of education is of considerable minor importance and remains the only control variable, which reaches statistical significance.

In the sample of transformation societies one can find a substantial influence of trust in systems (b=.94), generalized trust (b=.52) and education as well. As compared to the advanced democracies, and in line with hypothesis II, the relative importance of the predictors has substantially changed in the context of post-communist countries. While in the sample of advanced democracies the relative effect of both resources of trust is approximately equal (b=.61 and b=.57), the relative effect of trust in systems (b=.94) is much more important in the social context of the transformation societies. In the highly fragile situation of these countries, the existence of trustworthy institutions is central. The more agents perceive the rational basis of trust as secured, the more they will innovate. The influence of trust in systems as well as generalized trust remains stable even when the two samples of the advanced democracies and transformation societies are joined (see Sample 3), or extended to include nine additional developing countries (Sample 4). In these very heterogeneous samples, the influence of the control variables — average wealth and Internet access costs — now prove to be important and significant. The higher the average wealth in a country and the lower the Internet access costs, the higher the rate of diffusion of Internet hosts.

This finding mirrors, on the one hand, the fact that relative Internet access costs in transformation societies are still extremely high. On the other hand, the limited financial resources of these countries circumscribe the capacity to provide the necessary infrastructure to boost the new technologies. Additionally, one can observe a decrease of the relative importance of the education effect in Sample 3. In the pooled sample, containing all observations, the effect disappears completely. This may be read as an indicator that here the digital divide is more a result of monetary restrictions than of human capital. Yet the cultural resources of trust both remain the most important factors which explain the diffusion of Internet hosts.

6 Conclusion

Since the beginning of the 1990s the concept of trust has attracted substantial interest among the research community. In the field of economic sociology, trust has been found in comparative studies to be a potent predictor of economic efficiency besides the conventional growth factors. But trust not only enhances the productivity of existing actions in an economy but also is likely to favor innovation and change. However, empirical research so far has not adequately addressed the complexity of the concept.

I argue that trust should be seen as plural expectation. Within my simple heuristic model of trust, I am constructing and linking two different sources of expectations – experience (rational trust) and moral (moral trust) – to the two specific objects of trust in modernity: trust in generalized others (generalized trust) and trust in systems. While on the personal level generalized trust facilitates weak ties and makes social interactions more inclusive, thus allowing long chains of action, systems permit agents to learn trust more easily because trust in systems is stabilized through experience. A trustworthy, effective and efficient sanctioning apparatus can for this very reason succeed in modifying the expectations of agents in a fairly small amount of time. Through the building and enforcement of rules that favor cooperative behavior and punish opportunistic behavior, trust can substantially be expanded. On the other hand, generalized trust inherently relies on a cooperative ethos and a collective moral map, which structure expectations and actions. Moral maps, however, are far more difficult to create since these patterns of shared orientations are culturally transmitted through processes of socialization and remain relatively stable over time.

To sum up, the more countries resemble each other in terms of their material resources, the less can the considerable and persistent differences in the rate of Internet diffusion be explained by these factors. While I find strong and significant positive effects of both dimensions of trust across all samples, the relative effects of trust in systems and generalized trust vary substantially. For societies in transition to a new social, political, and economic order, trust in systems is the most relevant resource promoting innovative actions, as measured by the diffusion of Internet hosts. However, generalized trust is still important in these countries. This suggests that it is not the absence of a cooperative moral ethos or the persistence of pre-modern forms of trust (Seligman/Füzer 1994) per se which accounts for low levels of innovation, but that the cooperative ethos needs to be backed by an adequate institutional framework which fosters such behavior. In the stable contexts of advanced democracies, trust in systems and generalized trust are of equal importance. Generalized trust, as a general expectation of an ethos of non-opportunistic behavior, may however be much more cost effective and become a substantial competitive advantage.

The findings presented here may deliver additional food for thought for economic sociology as well as economics, as they remind us that a one-sided view on trust may substantially distort results13 . It is neither rational expectations nor moral maps alone that structure agents’ expectations and foster trust. Both aspects have to be considered. This may prove to be particularly fruitful for growth and development research, since until now the cooperative ethos has attracted only little attention and researchers still use the highly debatable trust variable of the World Values Survey as an indicator.


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Appendix A

Table 4: Descriptive Statistics


Table 5: Correlations of the independent variables in all samples


Appendix B The construction of moral orientations — Liberal individualism and amoral egoism

Trust in the willingness of others to cooperate increases the more accepted and widespread norms of reciprocity are (Putnam 1993; Coleman [1990] 2000), the more tolerance governs social interactions (Leicht 2000; Bornschier 2000) and the more widespread individualistic normative orientations are (Durkheim [1893] 1996; Weber [1904] 1993; Simmel [1908] 1992b, Seligman 1998). These different normative patterns have been termed liberal individualism and amoral egoism (Bornschier/Volken 2002). The two dimensions are the results of a principal component analysis (see table 6). All variables are taken from the World Values Survey. Respondents are asked to judge on a scale from one (never justified) to ten (always justified) whether they considered a specific morally-debatable action as justifiable or not. The first factor (liberal individualism) reflects different attitudes with regard to one’s own body and privacy. Individuals with an affirmative attitude to those morally debatable actions demonstrate more tolerance and favor individual freedom and responsibility. Since they justify actions like abortion, suicide, and euthanasia, the individual gains primacy over society because the potential negative effects which these debatable actions may have on society are of minor concern.

Table 6: Dimensions of aggregated moral orientations and attitudes


At the same time, this primacy of the individual – his autonomy, his right of decision, privacy and intimacy – points to a broad belief and trust in the individual. The second factor (amoral egoism) consists of variables which can be interpreted as symptoms of an anti-civic moral (Halpern 2001; Bornschier/Volken 2002) or a free rider society. Individuals or societies which score high on this dimension are highly opportunistic in their moral orientations. For that reason – and in following Edward Banfield (1958) – this dimension has been termed amoral egoism, since agents are motivated to maximize their own short-term self-interest.

Social contexts that have cultivated amoral egoism excessively will – if one supposes an anthropological nature of the norm of reciprocity and the possibility of rationally inspecting the motive structure of generalized others – exhibit a substantially lower propensity for cooperation and innovation. Together, liberal individualism and amoral egoism are considered parts of agents’ expectations, which focus on the integrity and benevolence of generalized others. In Durkheimian terms one may say that these expectations are formed by the conscious collective.

Appendix C List of indicators for principal component analysis — Generalized trust and trust in systems

Absence of corruption: as an indicator for the absence of corruption, Transparency International’s Corruption Perception Index (CPI) 1999 is used. The index is based on subjective ratings of businessmen, investment analysts and the general public. At least three different, independent sources are combined in order to built the index per country. The index varies from 0 (highly corrupt) to 10 (no corruption).

Freedom of the press: The indicator is based on the respective index of Freedom House14 for the year 2000. It is a composit index, which covers several aspects of print and brodcast media, including laws restricting the publication of certain contents, political repression and control, economic influence on content and repressive actions like violence towards and murder of journalists. The index has been been transformed as following:

(100 – freedom of press index), thus 0 represents an unfree press, 100 a fully free press.

Political rights: The index is based on the Gastil, Freedomhouse Index for political rights for the year 2000. It has been transformed as following:

(7 – index of political rights), thus 0 means no political rights, 7 full political rights.

Civil rights: The indicator is based on the civil rights index of Freedomhouse for the year 2000.15 It has been transformed as following:

(7 – civil rights index), thus 0 stands for no civil rights, 7 means full civil rights.

Economic freedom: This indicator corresponds to the Index of Economic Freedom 1999, which is provided by the Heritage Foundation and is compiled form a series of 10 different factors including the rule of law, black market activity, regulatory restrictions for banking, red tape, beaurocratic efficiency, and regulations of the labor market.16 . The original index has been transformed as following:

(5 – index of economic freedom), 0 representing a low and 5 a high degree of economic freedom.

Autocracy (1900/1945): The indicator measures the average autocracy rule between 1900 and 1945. The autocracy index varies between 0 (low degree of autocracy) and 10 (high degree of autocracy) and stems from the Polity III Data of Keith Jaggers and Robert Gurr.17 .

Democracy (1900/1945): The indicator measures the average democracy during the period of 1900 to 1945. The index varies between 0 (low degree of democracy) to 10 (high degree of democracy) and comes form the Polity III data (Jaggers/Gurr).

Trust (World Values Survey): The indicator is constructed using the following question of the World Values Survey konstruiert18 : “Generally speaking, would you say that most people can be trusted, or that you can’t be too careful in dealing with people?” The percentage of individuals answering “Can be trusted” (without considering those answering “don’t know”) are aggregated for the year 1995 per country. Missing values for 1995 have been estimated based on the data of 1990 for the following countries: Rumania, Czech Republic, Slovak Repulic, Portugal, Ireland, Ireland, Italy, Netherlands, Canada, Australia, France, Denmark and Belgium.19

Moral determinism: This indicator is constructed using variable V178 of the World Values Survey. Individuals who agree with the statement “There are absolutely clear guidelines about what is good and evil. These always apply to everyone, whatever the circumstances.” are considered as morally determined. Moral determinism thus is the percentage of individuals per country who agree with the statement in question.

Liberal individualism: The values for this indicator result from a principal component analysis of individual moral orientations and attitudes in the period of 1981 to 1995 (see Table 6 above; also Bornschier/Volken 2002). The items used in the analysis include the variables V192 to V202 of the World Values Survey and are aggregated for each country under study.

Amoral egoismus: The values for this indicator result from a principal component analysis of individual moral orientations and attitudes in the period of 1981 to 1995 (see Table 6 above; also Bornschier/Volken 2002). The items used in the analysis include the variables V192 to V202 of the World Values Survey and are aggregated for each country under study.

Appendix D List of Indicators used in Linear Regression Models

Diffusion of Internet hosts: Data for the dependent variable – the number of Internet hosts per country20 – have been obtained from the Internet Software Consortium (http://www.isc.org). The following transformation has been applied:

log (Internet hosts per 10’000 inhabitants)

Trust in systems: Values for this indicator come from the first factor of the principal component analysis documented above (see appendix C and table 2). Trust in systems reflects a general syndrome of “objective” institutional factors, which are relevant to extend empirical trust. These are: freedom of the press, absence of corruption, political and civil right, rule of law, economic freedom and the historical experience of democracy and the absence of autocratic rule. Factor scores have been transformed as following:

log (10 + trust in systems)

Generalized trust:

Values for generalized trust come from the second factor of the principal component analysis documented above (see appendix C and table 2). Generalized trust refers to a general and average subjective perception of other’s ethos of cooperation, tolerance and freedom. The factor scores have been transformed as following:

log (10 + generalized trust)

Proliferation of tertiary education: Data for tertiary education comes from the 1999 Statistical Yearbook of the UNESCO. It is the percentage of 20-24 year old individuals who are enrolled in a tertiary educational institution in 1980. In following Bornschier (2001a) the early proliferation of tertiary education has been chosen purposely, since these people build a considerable demand potential during for the process of Internet diffusion. Data has been transformed as following:

log (proliferation of tertiary education)

Technical competence: Data come from the World Development Indicator 1999 and 2001 of the World Bank. The indicator reflects the average number of scientists and engineers in R&D per million inhabitants in the period between 1985-199521 . The data has been transformed as following:

log (technical competence)

Average Wealth: PPP per capita in US$, 1997. Data come from the World Development Indicators 1999 and 2001 of the World Bank. The data has been transformed as following:

log (Average Wealth)

Internet access costs: Monthly relative Internet access costs are measured by using the costs of a 20 hour local phone call22 and dividing it by the GNP per capita (ppp) per month (in US$). Data come from the World Development Indicators 1999 and 2000. The following transformation has been applied:

log (Internet access costs)


1. I would like to thank Volker Bornschier, Mark Herkenrath and the two anonymous reviewers for their helpful comments on this paper. My special thanks goes to Marianne Schindler who helped translating the paper into English. An earlier version of this paper has been presented at the World Congress of Sociology, Brisbane (Australia), July 2002, Research Committee 14, Session 4: Information and Knowledge Society.

2. While inventions fundamentally extend the stock of knowledge, innovations refer to the “doing of new things” (Schumpeter) in the sense that elements from the knowledge stock are (re-) combined by entrepreneurs and are introduced to markets. Sometimes even new markets are created. The concept of innovation therefore clearly aims at the productive exploitation of the “new thing”.

3. For example GT* is the level of aggregated generalized trust in the sample of transformation society.

4. Descriptive statistics can be found in Appendix A.

5. The advanced democracies are: Spain, Portugal, Italy, France, Ireland, United Kingdom, United States of America, Australia, Canada, Austria, Belgium, Switzerland, Denmark, Norway, Sweden, Finland, Germany, Netherlands, Japan and South Korea.

6. The transformation countries are: Bulgaria, Rumania, Lithuania, Latvia, Estonia, Czech Republic, Slovak Republic, Slovenia, Poland, Hungary, Ukraine, Georgia, Russia, Moldova, Croatia, Macedonia, Belarus and Azerbaijan.

7. That is, computers which only access Internet resources without providing services (this would typically be task of the Internet hosts (servers)).

8. All data has been aggregated to the national level.

9. A description of attitudes captured by liberal individualism and amoral egoism can be found in Appendix B.

10. “Generally speaking, would you say that most people can be trusted, or that you can’t be too careful in dealing with people?”

11. As an example the diagnosis of the NTIA (2000:15) may be used: “(…) our most recent data show that divides still exist between those with different levels of income and education (…)”

12. See appendix C for details of operationalization.

13. This is particularly problematic in the context of transformation societies since, as has been demonstrated here, a different weight is put on each of the trust resources in these countries. Thus, a failure to acknowledge a multi-dimensional concept of trust will lead researchers to conclude that trust is either absent in these fragile contexts or that the level of trust has no effect on the productive capacity (Haerpfer, Wallace, and Raiser 2001).

14. Freedom House (2000a): Censor Dot Gov. The Internet and Press Freedom 2000. http://www.freedomhouse.org.

15. dito

16. Johnson, Bryan T.; Holmes, Kim R.; Kirkpatrick, Melanie (1999): 1999 Index of Economic Freedom. Washington: The Heritage Foundation.

17. Jaggers, Keith; Gurr, Robert (1996): Polity III: Regime Type and Political Authority, 1800-1994. Michigan: Inter-university Consortium for Political and Social Research.

18. Variable V27 (wave 3).

19. The estimate uses the following formula: trust95 = -1.493 + 0.86 * trust90. The parameters for the estimates come form a regression, which has been performed on an extended sample of 71 countries. R2-adjusted is 0.842.

20. Because only a minority of Internet hosts in the United States is registered under the domain “us”, the number of hosts for the United States is estimated by adding the domains us, edu, com, org and net. This however will somewhat overestimate the diffusion.

21. Estimates have been made for the following four countries: Switzerland = average (Sweden, Norway, Netherlands); Latvia = average (Estonia, Lithuania); Columbia = average (Ecuador, Venezuela); Georgia = average (Armenia, Azerbaidjan).

22. Since data on real access costs is only available for a limited number of countries, it is assumed that individuals are using dial-up connections and use it 20 hours per month. This however does not take into consideration the costs charged by Internet Service Providers (ISP) or fixed connection costs charged by the telephone companies.

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