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Copyright 1991 by the American Psychological iical Association, Inc. 0022-3514/91/S3.00

Journal of Personality and Social Psychology 1991, Vol. 61, No. 5. 734-742

Communication Network Influences on Information Diffusion and Persuasion Mieneke W H. Weenig and Cees J. H. Midden Department of Social and Organizational Psychology/Center for Energy and Environmental Research University of Leiden, Leiden, The Netherlands

Communication networks' influences on the information diffusion process and the effects of 2 virtually identical communication programs were studied. These programs were implemented in 2 Dutch neighborhoods with different levels of cohesion. It was expected that information diffusion would be related to the number of network ties, whereas program effects would be related to the strength of network ties. Data were collected from a representative sample of the target group by means of pre- and posttest surveys and 5 small process surveys. The data confirm the main hypothesis and also provide some support for the strength-of-weak-ties hypothesis (Granovetter, 1973). No significant interaction effects of neighborhood and network variables were found. The results provide some insight on how people restrain each other from adoption and how this is related to the strength and number of communication ties.

context plays an important role in attitude and behavior

Persuasive communication is predominantly studied as an isolated, one-way phenomenon between a receiver and a source

change, the assumptions underlying these programs have re-

who tries to influence the receiver's attitudes or behavior through some channel by means of a persuasive message. Most researchers have placed a strong accent on cognitive processes

ceived little research attention. As many community programs have been quite successful (e.g., Farquhar, 1978; Farquhar, Maccoby, & Solomon, 1984; Gaskell & Joerges, 1987; Keating, Love,

inside individuals (cf. Roberts & Maccoby, 1985). The social context in which persuasion attempts take place has received much less attention in research on persuasive communication. Evaluation studies of public communication campaigns are il-

Oliver, Peach, & Flynn, 1985; Nutbeam & Catford, 1987; Olsen & Cluett, 1982; Puska, Salonen, Tuomilehto, Nissinen, & Kottke, 1983), it is tempting to assume that this effectiveness stems, at least partly, from interpersonal communication pro-

lustrative in this respect. Most of these studies have focused almost exclusively on campaign outcomes of attitudes or of behaviors rather than on the process by which these outcomes

cesses. However, this assumption has never been tested. Researchers studying the diffusion of innovations, an area closely related to that of persuasive communication, have given more attention to the social context of persuasion and adoption

were obtained. Remarkably little is known about the manner in which these outcomes might have been affected by informal interpersonal communications among receivers. This is surprising considering that as early as the 1940s and 1950s, re-

decisions. In this research tradition, a spatial innovation diffusion pattern and an S-shaped adoption curve (e.g., Morrill, Gaile, & Thrall, 1988; Rogers, 1983) are often interpreted as

searchers had demonstrated that mass media directly influence a small part of their audience at best, but that face-to-face contacts with other people influence most people (e.g., Katz & La-

evidence of interpersonal influence on adoption decisions. Although this kind of research has yielded some interesting indications of social influence on adoption decisions (see, e.g., Coleman, Katz, & Menzel, 1957, for an early exemplary study in this

zarsfeld, 1955; Lazarsfeld, Berelson, & Gaudet 1948). How and by what channels this influence takes place has not been thor-

area, or Hurt, 1987, for an interesting recent reinterpretation of

oughly investigated. The lack of this kind of research is even

its results), it has provided little insight into how exactly this

more surprising in the light of the community-based communication program that was launched during the 1980s as a promising alternative to large-scale mass media campaigns. Although these programs are largely based on the notion that the social

influence takes place and how it is affected by existing communication networks. In addition, most diffusion of innovation research is heavily biased toward positive adoption decisions (cf. Rogers, 1983). We do not have any insight into whether and how people might deter each other from adoption. In the diffusion of innovations literature, there is a curious blind spot about

We thank Rene van der Vlist, Henk Wilke, and five anonymous reviewers for their helpful comments on this article. We also thank Leo van der Kamp and Ivo van der Lans for their methodological advice. Finally, we are indebted to Donald Warren for his contribution to this work. Correspondence concerning this article should be addressed to Mieneke W H. Weenig, Department of Social and Organizational Psychology/Center for Energy and Environmental Research, University of Leiden, P.O. Box 9555, 2300 RB Leiden, Leiden, The Netherlands.

negative advice and the nondiffusion of unsuccessful innovations. Finally, like research on persuasive communication, research on the diffusion of innovations has almost exclusively investigated the final stage of the innovation decision process, that is, positive adoption decisions. The preceding stages of the innovation diffusion process, such as awareness of the innovation and the subsequent seeking of extra information, have received little research attention. How these preceding stages are 734

COMMUNICATION NETWORK INFLUENCES

influenced by interpersonal communication and how this in turn affects adoption decisions have hitherto been virtually unexplored. In our research, we have tried to gain more insight into these processes. We present a study in which the influence of local communication networks on adoption decisions and the preceding process of information diffusion was investigated. For this purpose, a community-based communication program aimed at promoting the adoption of energy conservation measures' was implemented in two neighborhoods with different levels of cohesion. Before describing this study in more detail, we first take a closer look at the question, How do existing communication networks affect the information diffusion process and the outcomes of such a program? Information Diffusion and Influence in Communication Networks Basically, the effectiveness of a persuasive communication program aimed at promoting adoption decisions depends on the successful achievement of two successive processes: information diffusion and persuasion.2 During the stage of information diffusion, target individuals may become aware of the program and may pay attention to the information provided. If the program information does have the intended effect, attention is followed by a process of persuasion. During this stage, receivers decide on whether to agree or disagree with the message and whether to adopt the advocated measures. Awareness precedes attention, which in turn can be assumed to precede adoption decisions. One can hardly imagine people paying attention to program information without being aware of the program's existence. It is also unlikely that people first decide to adopt the advocated measures and afterwards pay attention to program information, although this sequence is not as unimaginable as the first one. Thus, the sequence awareness -* attention -> adoption decisions seems to be a logical one. In what way could interpersonal communication among community members affect these program stages? A target group can be regarded as an aggregation of individuals who may or may not be linked to each other by communication ties. Together, these ties form a communication network (e.g., Knoke & Kuklinski, 1982; Rogers & Kincaid, 1981). Communication ties may vary in strength, which has been denned as the "(probably linear) combination of the amount of time, the emotional intensity, the intimacy (mutual confiding), and the reciprocal services" (Granovetter, 1973, p. 1361). In other words, the strength of a tie refers to the quality of interaction between two individuals. For reasons we explain later in this article, we expected that the strength of ties would be primarily important during the stage of adoption decisions, whereas the number of ties would be important during the stage of information diffusion. The strength of ties might be important with respect to adoption decisions because, as a result of the amount of time invested and emotional involvement in strong ties, people will probably be motivated to comply with the opinions of strong ties rather than with those of weak ties. Various studies on group behavior have consistently shown that pressures toward uniformity in attitude and behavior are stronger in more cohesive groups (e.g., Back, 1951; Cartwright, 1968; Festinger, 1950,

735

1954; Festinger, Schachter, & Back, 1950), that is, groups in which people are strongly tied to one another. Second, strong ties, such as friends and kin, will usually be regarded as highly trustworthy sources of information and therefore have high potentials for persuasion. After all, the relation between source credibility and persuasion has been well documented (e.g., McGuire, 1985), especially under conditions of low elaboration likelihood (Petty & Cacioppo, 1984). This persuasive potential of strong ties will be even higher when these ties are also regarded as knowledgeable, which may for instance be the case when they have some experience of an innovation. We therefore expected that the extent to which community members influence each other in favor of or against program objectives will be related to the strength or quality of community ties. The number of existing ties within a communication network indicates the availability of routes for information diffusion and hence the probability that the information reaches a random network member; after all, the larger the number of ties in a network, the more alternative routes will be available for information diffusion. Thus, we expected that the speed and scope of information diffusion in a community will be related to the number of existing ties. Because they are referred to more frequently (by definition), strong ties offer more opportunities for information diffusion than weak ties do. However, strong ties tend to cluster into interlocking networks (see also Feld, 1981), which usually form subgroups (or cliques) in the larger communication network. In his seminal article, "The Strength of Weak Ties," Granovetter (1973) argued that communication ties between subgroups tend to be weak and that therefore weak ties may be even more useful to the purpose of information diffusion than strong ties because weak ties prevent information from remaining inside clique boundaries. Thus, new information from outside a clique, such as information about a program's existence, is likely to enter a subgroup by way of weak ties. In other words, weak ties may serve as information bridges between cliques of strong ties. Subsequent research has supported this notion (e.g., Friedkin, 1980; Weimann, 1983). Within a clique, however, strong ties appear to be more important for the flow of in-group information (Friedkin, 1982). On the basis of these notions, it might be expected that information diffusion will be related to the number of weak ties as well as to the number of strong ties. Direct ties with the source of information may be of special importance to the purpose of information diffusion because these are the most direct routes from the information source to a target individual. Several community communication programs have used local volunteers as an information source (e.g., Brummit, 1984; Farquhar et al, 1984; Maccoby & Solomon, 1981). Being personally involved in the program, these volunteers are likely to start communicating about the program in

' This means that the program was aimed to achieve a one-time change, that is, positive adoption decisions. Note that this aim differs somewhat from many other community programs, such as those dealing with health behavior, which usually attempt to achieve multiple action changes that may need to last a lifetime. 2 More differentiated stages have been suggested (see for instance McGuire, 1985). For reasons of simplification and clarity, however, we have used a subdivision in two broad stages.

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MIENEKE W H. WEENIG AND CEES I H. MIDDEN

their immediate social environment through their available communication ties. Thus, local volunteers may make other community members aware of the program's existence and its main objectives and also may stimulate them to pay attention to the information provided. Our main hypothesis was that information diffusion would be related to the number of ties, whereas the strength of ties would be decisive in influencing adoption decisions. More specifically, we hypothesized that the process of information diffusion (i.e., program awarenessand attention to information activities) would be positively related to a respondent's number of lies with community members, irrespective of their strength, as well as to the availability of a direct tie with the information source. Adoption decisions, on the other hand, were expected to be related to the strength of network ties rather than to their number. The direction of the expected relation between tie strength and adoption was expected to depend on the direction of interpersonal communications, that is, in favor of or against program objectives. Method Study Design Two virtually identical communication programs aimed at promoting the adoption of energy conservation measures were implemented in two Dutch neighborhoods. Neighborhood selection was based on an extensive pilot study in which the communication networks of eight Dutch working-class neighborhoods3 were investigated. For the purpose of this study, a neighborhood was operationally defined as a geographic area of at least 200 dwellings marked off by busy streets, railroads, or canals. The results of this pilot study are reported elsewhere (Weenig, Schmidt, & Midden, 1990). The neighborhoods selected for the study reported here were the most extreme on either side of the cohesion dimension that emerged from the pilot-study data as a combination of interaction quantity and quality. Neighborhood 1 was the cohesive neighborhood, with relatively high levels of communication quantity and quality. It consisted of approximately 400 nearly identical single-family dwellings, all belonging to a single housing association. Neighborhood 2 was the noncohesive neighborhood, with relatively low levelsof communication quantity and quality. Neighborhood 2 consisted of two 13-story apartment blocks of 188 apartments each in an isolated location on the edge of town. The reason for this selection of neighborhoods with opposite network characteristics was twofold. First, and most important, assessing network influences in neighborhoods with contrasting network characteristics would increase the generalization of the findings. Second, it would offer the opportunity to explore whether or how the expected relations might be affected by a community's level of cohesion. It was expected that the two neighborhoods would differ from each other with respect to the absolute amount of interpersonal communication, which should be highest in the cohesive neighborhood as a result of its higher communication quantity and quality. However, hypotheses concerning the relation of network variables with information diffusion and adoption were expected to be valid for both neighborhoods, regardless of their level of cohesion.

Communication Programs The first and most crucial step of both communication programs was the formation in each neighborhood of a project group consisting of representatives of the target group (i.e., the local residents) plus a representative of the housing association that owned the neighborhood

houses. Each project group was supported by local experts on technical and communication matters whenever necessary. The main task of the project group was to design an energy conservation plan for the neighborhood and to see to its promotion and implementation. To simplify this task, a program manual was developed that offered detailed guidelines for the preparation, organization, and implementation of program activities. The guidelines of the program left ample room for local adaptation. In Neighborhood 1, the project group consisted of representatives of the local residents, the housing association that owned most of the neighborhood houses, the local gas and electricity board, and several other local institutions. The energy conservation plan consisted of wall insulation" (Option 1) and double glazing* (Option 2). Both insulation measures were offered as separate options in exchange for a rent increase, which was lower than the calculated savings on the energy bill (i.e., both measures were bargains). Unfortunately, the expected savings were poorly communicated to the residents: Whereas the rent increase per month was clearly indicated on the form by which residents could give their consent to the installation o f the measures, residents had to make a complex calculation from a complicated table to get a notion of the estimatedsavings. Program activities included newsletters from the project group, an information meeting, a booklet from the housing association on energy conservation accompanied by a letter in which the insulation options were offered, and lessons on energy conservation at two local primary schools. In addition, the program was covered by the local media. In Neighborhood 2, the project group consisted of a representative from the housing association, who was elected as chairman, and 6 residents. The communication program included newsletters to the residents, an information meeting, a letter in which the options were formally presented, a demonstration house, and home visits to nonadopters by members of the project group. As in Neighborhood 1, the program was covered by the local media. Tenants were offered a standard offer (Option 1) that consisted of four conservation measures.6 In exchange for these measures, residents had to pay a rent increase that was about half of the calculated savings on the energy bill. Unlike in Neighborhood I , this payoff ratio was clearly communicated to the residents during the program. Residents could only sign up for the complete offer and not for any of its separate measures. Only in the case of adoption of the standard offer did residents have the extra option to sign up for double glazing (Option 2) in exchange for a rent increase that slightly exceeded the calculated savings on the energy bill.

Data Collection In each neighborhood, the number and quality of neighborhood ties were measured in a pretest that was administered in face-to-face interviews by trained interviewers to a randomsampleof residents. Communication quantity was measured by finding how many ties respondents

3 The choice of working-class neighborhoods was based on results from preliminary research that had revealed that these groups had hitherto been poorly reached by traditional (i.e., mass media) communication programs (Midden & Ritsema, 1984). 4 Wall insulation was the retrofit of polystyrene pearls in the cavity walls of the houses. 5 Double glazing was the retrofit of double pane windows in the living room, bedroom, or the kitchen. ' These four measures were (a) cavity wall insulation retrofitted to the side walls of the apartment blocks, (b) the retrofit of weatherstrips for each apartment, (c) energy meters to be installed in each apartment to enable individual registration of energy use, and (d) the installation of new boilers to the central heating system of each apartment block.

737

COMMUNICATION NETWORK INFLUENCES had with other residents by asking the question, "With how many people in this neighborhood do you speak regularly, by which I mean more than saying just 'hello' to each other?" Before this question, neighborhood boundaries were denned by the interviewer by naming all its perimeter streets. The quality of a respondent's neighborhood ties was measured by asking how many of the aforementioned neighborhood ties were kin and close friends. The quality of ties was also measured on a more aggregated level by asking respondents about their motivation to comply (Fishbein & Ajzen, 1975) with other residents by the question, "How important do you consider the opinions of (a) your direct neighbors and(b)other neighborhood residents?" with response categories ranging from not important (1) to very important (5). Finally, demographic characteristics such as age, educational background, and family income, as well as some ancillary variables not relevant to the study reported here, were measured in the pretest. Awareness of the program, attention to program activities, and adoption decisions were measured in a posttest. This test was administered by trained interviewers at the end of the program by means of face-to-face interviews with 125 respondents in Neighborhood 1 (73% of whom were pretest respondents) and with 121 respondents in Neighborhood 2 (62% of whom were pretest respondents). Program awareness was measured by asking whether respondents had heard of the program at all and then asking them to mention as many program activities as they could remember. Attention was measured by asking for each major program activity the extent to which the respondent had taken notice of the information provided (i.e., had read the written information and had attended the meetings). Respondents were also asked whether they had been acquainted with any member of the project group before the program (i.e, direct tie with information source). Adoption decisions were assessed by asking respondents what measures they had signed up for (discussed later in this article). Finally, respondents were asked whether they had received any positive or negative advice on the promoted insulation measures and from whom, with kinsmen, friends, project group members, and other community members as preceded response categories. Thus, we were able to make a distinction between strong tie advice (i.e., advice from friends and kinsmen) and weak tie advice (advice from project group members and other community members). To monitor the information diffusion process during the course of the program, a telephone survey was administered in each neighborhood immediately after every major information activity, with a total number of five in each neighborhood. By means of these process surveys, developments in the extent to which respondents were aware of program activities and paid attention to them were measured. This was done by means of the same questions used in the posttest described above. In addition, the extent to which residents discussed the program with other residents was measured by the question, "Did you discuss the. . .[program activity] with other residents? If yes, with whom?" The process surveys were administered to small samples of 40 residents who had not participated in the pretest. In each of these process surveys (except the first one), 50% were new respondents and the other 50% had participated in the immediately preceding process survey (i.e., a rotating sample). We used a rotating sample to avoid (panel) effects such as selective dropout from the sample, and artificially enhanced program awareness as a result of the repeated measurements.

Results Calculation of Network Variables Preliminary analysis of the data revealed that motivation to comply with direct neighbors and motivation to comply with other residents were highly correlated (r = .76, p < .001). Therefore, these two measures were combined into one indicator,

which was computed as the simple mean of the two measures. Respondents' number of strong ties in the neighborhood were computed by adding the number of kin to the number of close friends in the neighborhood. Their number of weak ties was computed by subtracting their number of strong ties from their total number of ties in the neighborhood. For each respondent, two advice scores were computed per option, resulting in a total of four advice scores per respondent: weak tie advice on Option 1 (wall insulation or the standard offer), strong tie advice on Option 1, weak tie advice on Option 2 (double glazing), and strong tie advice on Option 2. Respondents received a score of — 1 if they had received only negative advice on an option, 1 if they had received only positive advice, and 0 if they had received both positive and negative advice or no advice at all on an option.

Sample The means, standard deviations, and standard errors on the network variables for both neighborhoods are presented in Table 1. It was expected that the mean number of weak and strong ties and the mean score on motivation to comply would be higher in the cohesive neighborhood (Neighborhood 1) than in the noncohesive neighborhood (Neighborhood 2). This appeared to be the case (Table 1). Therefore, it can be concluded that the two neighborhoods differed on level of cohesion, as predicted. Table 1 also reveals marked differences between the neighborhoods on the direction of advice received on Option 1, which consisted of wall insulation in Neighborhood 1, and the standard offer in Neighborhood 2. In Neighborhood 1, the average advice was negative, whereas in Neighborhood 2, the average advice was positive. The difference is probably the reflection of a rumor that spread in Neighborhood 1 that cavity wall insulation would cause damp and moldy walls. In the noncohesive neighborhood, such a rumor did not occur, despite the fact that the circumstances were almost identical (i.e., local media coverage on negative experiences with cavity wall insulation, which was part of the standard offer). We return to this finding later. Program Awareness, Attention, and

Effects

For each respondent, an awareness score was computed by counting the number of program activities that the respondent was able to mention without the aid of the interviewer. Similarly, an attention score was computed by counting the number of program activities that the respondent had paid any notice to. The means, standard deviations, and standard errors on these measures and on adoption decisions are shown in Table 2. In Neighborhood 2, respondents were aware of more program activities than the respondents in Neighborhood 1 were. Attention to these activities was also higher in Neighborhood 2. Adoption figures on Option 1 differed strongly in the two neighborhoods: In Neighborhood 2, a large majority (68%) voted in favor of the standard offer, whereas in Neighborhood 1, a large majority (79%) decided against cavity wall insulation. In both neighborhoods, slightly more than half of the respondents made a positive adoption decision on double glazing (Option 2). In the next section, we explore to what extent awareness, atten-

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M1ENEKE W H. WEENIG AND CEES J. H. MIDDEN Table 1 Means, Standard Deviations, and Standard Errors of Communication Network Variables Neighborhood 1

Neighborhood 2

Variable

M

SD

SE

M

SD

SE

t

Number of weak ties' Number of strong ties' Motivation to comply* Weak tie advice on Option 1 b Strong tie advice on Option 1b Weak tie advice on Option 2 b Strong tie advice on Option 2 b

5.10 3.81 2.84 -0.22 -0.18 0.00 0.12

6.03 5.64 0.99 0.44 0.50 0.40 0.41

0.54 0.51 0.10 0.04 0.05 0.04 0.04

3.76 2.50 2.42 0.02 0.03 -0.05 0.06

5.85 3.75 1.19 0.34 0.20 0.31 0.30

0.55 0.34 0.12 0.03 0.02 0.03 0.03

1.74* 2.14» 2.62* -4.80* -4.28* 1.08 1.35

' One-tailed (test. " Two-tailed t test. * p < .05 after Hochberg's modified Bonferroni correction for experimentwise Type I error (Hochberg, 1988).

tion, and adoption decisions have been influenced by network variables.

The data in Table 3 indicate that the results generally support the main hypothesis. First, the two stages of information diffusion—awareness and attention—were both exclusively related

Network Influences

to network variables that reflect the availability of ties, whereas adoption decisions were related to variables that reflect the

The main hypothesis of our study was that the process of

strength of ties, albeit not exclusively. Availability of a direct tie

information diffusion would be related to the availability of network ties, whereas adoption decisions would be related to the strength of network ties. Translated at the operational level, this means that respondents' degree of awareness of and attention to program activities were expected to be positively related to the existence of direct ties with the community volunteers of

icant positive predictor of program awareness and of attention to program activities. Neither stage was found to be related to motivation to comply, which is also in agreement with expectations. Of the expected positive relations between awareness and number of both weak and strong ties, the relation to number of

the project group, as well as to their number of both weak and strong ties with other residents. Awareness and attention were both expected to be unrelated to motivation to comply. Adoption decisions, on the other hand, were expected to be positively related to advice received from strong ties and unrelated to advice from weak ties. In addition, adoption was expected to be related to motivation to comply, with the direction of this relation being contingent on the direction of the majority of exchanged advice in the neighborhood: positive in case of a majority of positive advices and negative in case of a majority of negative advices. Whether adoption decisions would be positively related to the existence of a direct tie with the project group was expected to be mediated by the actual performance of the community volunteers during the program. Hence, no hypotheses were formulated concerning this relationship. The hypotheses were tested by means of a series of multiple regression analyses, with network variables as predictors and

with the community volunteers of the project group was a signif-

weak ties was significant, but the relation to number of strong ties surprisingly was not. Adoption decisions on both options were positively related to advice received from strong ties and not to advice received from weak ties. This clearly and consistently supports our hypothesis. Motivation to comply with other residents seems to have had no influence on the adoption decisions. A stronger relation was expected as the majority of advice received on this option was positive. Therefore, this finding does not support the main hypothesis. Finally, adoption of Option 1 was found to be negatively related to the number of weak ties in the neighborhood, which was also not expected. Both findings are addressed in the Discussion section. In summary, it can be concluded that the findings of this study largely support our main hypothesis. The information diffusion process was related to the number of communication ties and unrelated to the quality of ties, whereas adoption deci-

with awareness, attention, and adoption decisions as respective criterion variables. The analyses were carried out on the pooled data of the two neighborhoods. To control for neighborhood differences on the criterion variables, a dummy variable neighborhood was added to the set of predictors. To enable the assessment of network influences on each criterion separately, the influence of the preceding stage was controlled for by entering the preceding criterion variable as an additional predictor. Thus, awareness served as an additional predictor of attention, and attention served as an additional predictor of adoption decisions. All predictors were entered simultaneously in the analyses. The results7 of the multiple regression analyses are summarized in Table 3.

7 Several diagnostics were performed on the multiple regression analyses. Examination of the standardized residual scatterplots revealed a random distribution of the residuals in all analyses. We checked for leverage points and used DFFIT (Belsley, Kuh, & Welsch, 1980) to test the combined effect on the fitted values of leverage and residuals. Following Belsley et al., a value o f 2p/N was used as the cutoff for leverage and a value of2V(p,W) was used as the cutoff for DFFIT. Only I leverage point was found with a DFFIT value that exceeded the limit in one analysis (analysis of attention). Because this case also had relatively high leverage values on the other three analyses, it was removed from all four analyses, resulting in an N of 245 for all reported multiple regression analyses. The issue of potential interaction effects of neighborhood and network variables is addressed in the next section.

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COMMUNICATION NETWORK INFLUENCES Table 2 Means, Standard Deviations, and Standard Errors of Awareness, Attention, and Program

Effects

Neighborhood 1 (« = 125)

Neighborhood 2 (« = 121)

Variable

M

SD

SE

M

SD

SE

Awareness Attention Adoption Option 1 (0 = no, 1 = yes) Adoption Option 2 (0 = no, 1 = yes)

2.43 1.90

1.31 1.11

0.12 0.10

3.08 2.26

1.75 1.05

0.16 0.10

-3.30* -2.62*

0.21

0.41

0.04

0.68

0.47

0.04

-8.39*

0.54

0.50

0.05

0.52

0.50

0.05

0.24

• Two-tailed f test. * p < .05 after Hochberg's modified Bonferroni correction for experimentwise Type I error (Hochberg, 1988).

sions were related to the quality of ties, albeit not exclusively. The finding that a direct tie with the project group predicts

strength, it is interesting to take a closer look at this relation-

awareness and attention, with the influence of awareness on attention controlled, indicates that the community volunteers played a crucial role in the information diffusion process in

ship. Table 5 presents an overview of advice received in both neighborhoods, split for positive-negative, tie strength, and conservation option. It can be concluded from Table 5 that in both neighborhoods, positive advice on adoption was mainly

their neighborhood: Apart from making residents aware of program activities, they also seem to have stimulated residents to pay attention to the information provided. However, the influ-

received from strong ties, whereas negative advice was obtained more frequently from weak ties. The only exception to this pattern was negative advice on cavity wall insulation in the cohe-

ence of a direct tie with the project group disappeared during the stage of adoption.

sive neighborhood, which was obtained as frequently from strong as from weak ties. Apparently, negative advice only required the availability of ties, whereas positive advice needed a certain degree of tie strength to be communicated. In the Discussion section we return to this finding.

Differences in Network Influence Between the Neighborhoods It was expected that the level of cohesion would affect the

Discussion

absolute quantity of interpersonal communication (with more communication in the cohesive neighborhood) but would not affect the relationships between predictors and criterion vari-

In general, the results support the main hypothesis: Information diffusion is related to the availability of communication

ables. In other words, no interaction effects of neighborhood and network variables were expected. To examine this, we en-

ties and unrelated to the strength of ties, whereas adoption decisions are related to the strength of ties.

tered the products of the scores on the network variables with the dummy variable neighborhood as a last step in each of the four analyses (c.f. Cohen & Cohen, 1983). None of the interaction terms had significant beta weights (at the 5% level).8 Therefore, it can be concluded that level of cohesion did not affect the

Somewhat unexpectedly, some support for the strength-ofweak-ties hypothesis was found, as program awareness appeared to be positively related to the number of weak ties but unrelated to the number of strong ties. It seems that even in small communities like the neighborhoods we investigated, new information that originates from outside the community

relations between predictors and criterion variables, just as predicted. Did level of cohesion affect the magnitude of program-induced interpersonal communication? It was expected that in the cohesive neighborhood, the program would induce more interpersonal communication than in the noncohesive neighborhood as a result of its higher number of strong and weak ties and its higher level of motivation to comply In general, this appeared to be the case, as is shown in Table 4. The program was consistently discussed by many more respondents in the cohesive neighborhood than in the noncohesive neighborhood. The only exception occurred after the information meeting, during which more interpersonal communication took place in the noncohesive neighborhood. However, this difference is not

(i.e., about the communication program) diffuses in a community through weak ties rather than through strong ties. This finding is consistent with Friedkin's observations (Friedkin, 1982). However, because we did not measure whether the weak ties spanned different subgroups, we do not know whether the strength of weak ties in diffusing information is due to their bridging capacity, as Granovetter (1973) hypothesized, or to their sheer number, as has been suggested by Friedkin (1982). The personal communication network of the community members of the project groups appears to be very important for the purpose of information diffusion. In both neighborhoods, the availability of a direct tie with the project group was an important predictor of awareness and attention to program ac-

significant. Therefore, it can be concluded that the results are ,

largely consistent with the expectations. Although we formulated no hypotheses concerning the relationship between the direction of advice received and tie

8 To save space, the results of these analyses are not presented in a table.

740

MIENEKE W H. WEENIG AND CEES J. H. MIDDEN

Table 3

Regression of Network Variables on Awareness, Attention, and Adoption (N = 245) Attention

Awareness

SE

Variable Neighborhood" Awareness Attention Number of weak ties Direct tie with information source Number of strong ties Motivation to comply Weak tie advice

-.20

.20 .28 .06 .01

Strong tie advice R2

-.21***

.19** .24***

-.04

.04

.15f 1.45

SD residual SD residual < 1 Outliers (SD revised > 3)

0.06

0.06 0.06 0.06 0.06

SE

r

0

SE

-.12 .25*'*

0.06 0.06

-.47

-.36*"

0.06

.34

.21 .10 .31 .07 .06

.05 .22*** .08 .07

0.06 0.06 0.06 0.06

-.18 -.04 -.03 -.01

.22*** -.12* -.10

0.06 0.06 0.06 0.06 0.05 0.06 0.06 0.42

-.16

1.47

.18t

.04

.22"

.06 .11

31

.21***

0.99

•33f

.98 73% 0

80% 0

Adoption Option 2

Adoption Option 1

r

.02 .21 -.10

.05 .03 .13 .02 .21

8

SE

.03

0.06

.26*** -.11 -.11 -.01

.12 -.06 7 3***

J3f .47 76% 0

.41 73% 0

0.07 0.06 0.07 0.06 0.06 0.06 0.06

0.47

iive =1. " Noncohesive = 0; cohesive = 1. b A spurious relation due to the combined effect of a lower mean predictor score in Neighborhood 1 and a higher mean score on the criteriion in Neighborhood 2, with a positive Pearson product-moment correlation between the two variables in both neighborhoods (+.12, m and .09, ns, respectively). This accounts for the relatively high beta weight of weak tie advice on the adoption of the second conservation option. Apart from this single relation, no indications of other spurious relations were found. None of the correlations of the pooled data sets exceeded the values of the separate data sets. Vs.05. **/>

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