Effects of Community-Based Collaborative Group Characteristics on Social Capital

RESEARCH

Effects of Community-Based Collaborative Group Characteristicson Social Capital

Cheryl L. Wagner Æ Maria E. Fernandez-Gimenez

Received: 23 May 2007 / Accepted: 2 July 2009 / Published online: 18 August 2009

� Springer Science+Business Media, LLC 2009

Abstract Recent research suggests that community-

based collaboration may build social capital—defined as

trust, norms of reciprocity, and networks. Social capital

may improve a group’s ability to collaborate, manage risk,

innovate, and adapt to change. We used mail surveys of

group participants and key informant interviews to assess

whether the following collaborative group characteristics

affected social capital built within 10 collaborative groups

in northwest Colorado: perceived success, conflict,

activeness, stakeholder diversity, previous collaboration

experience, similar values and beliefs, group size, group

age, and initial social capital. Perceived success and initial

levels of social capital were the strongest predictors of

current levels of and changes in social capital over time.

Collaboration experience negatively influenced current

levels of trust. Our results suggest that collaborative groups

may need to consider the outcomes of collaborative inter-

actions in order to build social capital.

Keywords Collective action � Trust � Values �Norms of reciprocity � Natural resource agencies �Success � Conflict

Introduction

Social capital has been defined as trust, norms of reci-

procity, and networks among individuals that can be drawn

upon for individual or collective benefit (Coleman 1988;

Putnam 1993). Recent research has established that social

capital may be an outcome of collaborative processes, in

addition to being an important initial input (Carr and others

1998; Leach and Sabatier 2003; Pretty and Ward 2001;

Selin and others 2000; Sturtevant and Horton 2000;

Wagner and Fernandez-Gimenez 2008). This research has

also shown that collaborative groups vary in the degree to

which social capital increases or decreases over time. To

date, there has been little research to explain these differ-

ences and explore how collaborative group characteristics

affect social capital development. More specifically, group

characteristics, such as the perceived level of conflict and

success, group size, the amount of time participants spend

working together, stakeholder diversity, and initial social

capital, have yet to be investigated in light of their effect on

groups’ ability to build social capital. In this article, we

begin to address these questions by examining which

characteristics of community-based collaborative groups

are associated with high levels of social capital and

increases in social capital over time.

Social Capital in Community-Based Collaboration

We define community-based collaborative natural resource

management (CBCRM) as groups of diverse stakeholders

who convene voluntarily to work on natural resource pol-

icy, planning or management issues specific to a particular

location. In the context of CBCRM, social capital is an

asset that a group or stakeholder can use to obtain results

that they seek and accomplish goals that may otherwise be

unattainable (Putnam 1993). Social capital is important

because it can provide access to other forms of capital such

as financial capital (e.g. grants, funding) or human capital

(e.g. information, skills, scientific expertise), can facilitate

collaboration and therefore increase a group’s likelihood of

C. L. Wagner � M. E. Fernandez-Gimenez (&)

Department of Forest, Rangeland, and Watershed Stewardship,

Colorado State University, Fort Collins, CO 80523-1472, USA

e-mail: [email protected]

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Environmental Management (2009) 44:632–645

DOI 10.1007/s00267-009-9347-z

success (Leach and Sabatier 2003, 2005; Schuett and Selin

2002; Sobels and others 2001), and can increase a group’s

and community’s ability to innovate and adapt to change

(Adger 2003; Olsson and others 2004).

Based on social capital theory, group characteristics

likely affect whether and to what extent social capital is

developed (Putnam 1993). This is because group charac-

teristics influence the nature and quality of social interac-

tions within the group, which in turn affect the production

of major dimensions of social capital such as networks and

norms (Eastis 1998). For example, Burt (2001) notes, dif-

ferent types of interactions, such as between strongly

interconnected individuals or between disconnected indi-

viduals, may have disparate effects on social capital.

Similarly, Scholz and others (2008) and Berardo (2009)

found that networks in which participants interacted indi-

rectly with each other through key, centrally-positioned

individuals or organizations developed more trust and were

more effective at collaborating than smaller, denser net-

works in which participants interacted directly with each

other. Collaborative group characteristics that potentially

could affect social capital development include group

structure (e.g. the number and diversity of stakeholders or

participants; the balance of power or proportional repre-

sentation from different stakeholder groups; and the bal-

ance of participation of local, regional, and national

interests), whether the group is citizen- or agency-driven,

group process and developmental stage (e.g. facilitation,

group age, activeness of participants, previous experience

of participants, and the degree of conflict or controversy

within and around the group), group outcomes (e.g. per-

ceived success), the similarity of participant values and

beliefs, and the scope and scale of the group’s goals and

objectives.

Research Objective and Hypotheses

To address how group characteristics affect social capital,

our study examined the social capital of CBCRM organi-

zations at the group level. By group-level or organizational

social capital we mean the aggregate perceptions of indi-

vidual participants in each group, of relationships among

members of the group (Leana and van Buren 1999). We

refer to groups rather than organizations, because many of

the CBCRM groups we studied did not have formal orga-

nizational status.

The objective of this study was to examine whether

participant perceptions of group success, conflict, and

similar values and beliefs, activeness of participants,

stakeholder diversity, group size, group age, previous

collaboration experience, and initial social capital

affected the level and development of social capital in

community-based collaborative groups. Although this is

not an exhaustive list of potentially important variables,

existing research suggests that these characteristics are

likely some of the most important factors affecting social

capital development in community-based collaborative

groups (Agrawal 2002, Daniels and Walker 2001, Leach

and Pelkey 2001, Libecap 1995, O’Leary and Bingham

2003, Olson 1965). Below we briefly explain how we

expected each of these factors to influence social capital

development.

We hypothesized that participant perception of group

success would positively affect social capital development.

In order to reach and implement agreements, one dimen-

sion of success, group members must be committed to the

process and communicate openly (Leach and Pelkey 2001).

This commitment and open and clear communication leads

to repeated interactions over time and helps participants

find common ground—recognized prerequisites to building

social capital (Ostrom 1998). Past research has shown that

even small successes help keep participants engaged in the

collaborative process (Wondolleck and Yaffee 2000).

Further, success may promote social capital development

because it encourages new stakeholders to participate and

demonstrates that ‘‘stakeholders honor their commitments

and work competently’’ and they ‘‘negotiate in good faith

and are willing to compromise’’ (Leach and Sabatier 2005

p. 234). Because the definition of success in collaboration

is subject to debate (Conley and Moote 2003), we

emphasize that our focus is on participants’ perceptions of

success relative to their group’s purpose, its ability to find

common solutions to its problems, and the actions it has

taken to implement agreements or plans.

We expected participant perception of group conflict to

be negatively associated with high social capital and social

capital development because conflict, characterized by

distrust and fundamental behavior and value differences

among participants (O’Leary and Bingham 2003), is a

major barrier to working together, which is necessary for

social capital development (Ostrom 1997). Based on

O’Leary and Bingham (2003) and Daniels and Walker

(2001), we defined conflict as a situation in which collab-

orative group participants perceived incompatability of the

actions acceptable to different individuals or stakeholder

groups in their collaborative process, or where disputes

among participants (i.e. participant behavior) disrupted the

collaborative process.

We expected stakeholder diversity to be negatively

associated with high levels of social capital because it is

related to conflict. The more stakeholders are involved in a

process, the more viewpoints and values will be repre-

sented, leading to greater potential for value differences,

disagreement and conflict. If open communication, agree-

ment, and common viewpoints (or at least respect for

Environmental Management (2009) 44:632–645 633

123

others’ viewpoints) positively contribute to building social

capital among participants, then not communicating, dis-

agreeing over acceptable actions, and holding fundamen-

tally differing viewpoints and values will negatively affect

its development. In addition, much of the literature on

collective action emphasizes that groups whose members

have heterogeneous interests are less likely to successfully

solve collective action problems (Libecap 1995, Agrawal

2002). Conversely, common values and shared interests are

expected to reduce transaction costs in seeking solutions to

collective action problems (Agrawal 2002, Taylor and

Singleton 1993). For this reason we hypothesized that

similar values and beliefs would be positively associated

with social capital.

We also expected group size to be negatively associated

with social capital because increasing the number of par-

ticipants typically increases stakeholder diversity and

opportunities for conflict. Theories of collective action

have long suggested that larger groups face greater chal-

lenges in organizing and acting for collective benefits

(Olson 1965). However, it is important to note that in

theory, group size and stakeholder diversity may be posi-

tively associated with social capital. The larger a group and

the more diverse the stakeholders involved, the more

opportunity participants have to make connections, par-

ticularly with individuals that may have resources dissim-

ilar to their own. In a synthesis of literature on management

of common pool resources, Agrawal (2002) notes that

heterogeneous endowments may be a predictor of suc-

cessful collective action, though homogeneous identities

and interests are also important.

We hypothesized that participant activeness, in terms of

number of meetings and activities attended and length of

time involved in the group, would be positively associated

with social capital development, since social capital theory

suggests repeated interactions over time are necessary for

individuals to build trust and norms of reciprocity (Putnam

1993). We anticipated that group age would be positively

associated with social capital for the same reasons. The

more time the group has been active, the more opportunity

the group will have to develop strong norms and build

relationships with participants and partners such as agen-

cies. We hypothesized that previous collaboration experi-

ence would be positively associated with social capital for

similar reasons. Participants involved in other collabora-

tions might have existing relationships with the same

individuals or with other individuals that hold diverse

viewpoints, and would thus come to the table with a better

understanding of other stakeholders’ interests and con-

cerns. In addition, participants who have taken part in other

collaborative efforts may have learned how to collaborate

effectively (Daniels and Walker 2001) by listening to

other’s viewpoints and being honest, open, and forthright.

These collaboration skills presumably would help to build

trust and strengthen relationships in subsequent cooperative

efforts.

Site Description and Study Groups

This research focused on Moffat, Routt, and Jackson

counties in northwest Colorado. Historically, livestock

grazing was one of the dominant uses of public and private

lands in this area and ranchers were among the primary and

most influential public land users. Recently, however,

partially as result of rapid growth and development in this

region, conflict over access, use, and management of the

area’s resources is increasing. In particular, other users of

public lands, such as recreationists and oil and gas com-

panies, have increasingly demanded access to public lands

and expressed interest in their management. Consequently,

public land managers and communities are seeking ways to

resolve the conflict over access and management of these

public lands. The numerous community-based collabora-

tive groups in this area are largely a response to the

increased diversity of interests and conflict among resource

users.

In this study, we included 10 community-based collab-

orative groups based in northwest Colorado. These groups

range in size, mission, duration and frequency of interac-

tion and are described in Table 1. Our sample encompassed

a diversity of groups, some of which are typical of many

similar groups across the West, such as coordinated

resource management groups, other multistakeholder col-

laborations focusing on public lands, and wildlife working

groups focused on sensitive species. Several others were

focused on land conservation and agricultural preservation

on primarily private lands. Overall, our sample reflected

the diversity of collaborative groups in the region, and

mirrored the similar diversity found in many locations

across much of the USA.

Methods

Sampling Frame

This study employed a mixed-methods approach to gather

data about the level and change of social capital in

CBCRM groups in northwest Colorado. We compiled a list

of all active, idle, and disbanded collaborative groups

consisting of a diverse group of stakeholders focused on

natural resource management in Moffat, Routt, and Jack-

son Counties by contacting government agencies, cooper-

ative extension offices, and community organizations.

From the sampling frame of 24 collaborative groups 7

634 Environmental Management (2009) 44:632–645

123

groups were excluded due to lack of information. From the

remaining 17 groups we purposively chose groups that

were sufficiently large to compare (4 groups were

excluded because they had fewer than 10 participants),

were representative of collaborative groups in the study

area (2 groups excluded), and wanted to participate (1

group excluded). The remaining 10 groups were included

in the initial study and survey.

Table 1 Summary of characteristics of the 10 community-based collaborative groups included in the study

Group name Group mission/focus Years

active

Number & type of

participants

Meeting

frequency

Counties

involved

Northwest Colorado

Stewardship (NWCOS)

Improve public lands decision making by

promoting cooperation among diverse interests.

A primary focus is to contribute to the

development of the BLM Resource Management

Plan (RMP) for the Little Snake Resource Area in

NW Colorado

2003–

Present

112 (local residents,

agency staff,

statewide

organizations)

At least once a

month, often

more

Primarily

Moffat

Owl Mountain

Partnership (OMP)

Bring together agencies and private landowners to

address resource conflicts on public and private

lands. Issues the group has worked to address

include livestock grazing on public lands,

noxious weeds, and livestock/wildlife

interactions

1993–

Present

17 (local residents &

agency staff)

About once a

month

Jackson

Community Agriculture

Alliance (CAA)

Promote preservation of agricultural lands and

increase awareness of the Yampa Valley’s

agricultural heritage. The group has worked to

achieve this by bridging diverse sectors of the

community through various programs, events,

and courses

2000–

Present


organizations &

agencies)

Between once a

month and

quarterly

Routt

Emerald Mountain

Partnership (EMP)

Work toward preserving Emerald Mountain for

recreation, wildlife, and grazing. The group has

been working with the BLM to orchestrate a land

exchange in order to protect the mountain from

future development

1995–

Present


agency staff)

About once a

month

Routt

Columbian Sharp Tail

Grouse Working Group

(CSTG)

Developed a management plan for protecting Sharp

Tail Grouse in NW Colorado. The group

developed specific conservation actions that

incorporated the needs, values, and interests of

diverse stakeholders

2000–

2001


agencies and

NGOs)

Met at least once

a month

Moffat &

Routt

Axial Basin Coordinated

Resource Management

(AB-CRM)

Work to resolve resource use conflict between

agencies and landowners. The group developed a

management plan to resolve conflict regarding

availability of forage resources for wildlife and

livestock

1992–

Present


agencies)

Initially met once

a month, now

meet twice a

year

Moffat

Northwest Colorado Sage

Grouse Working Group

(SGWG)

Developed a management plan for protecting sage-

grouse in NW Colorado while meeting the needs

of the community and diverse stakeholders. The

group developed conservation actions that could

be taken to meet their goals

1996–

Present


agencies & NGOs)

About once a

month

Moffat &

Routt

Yampa River System

Legacy Project (YRLP)

Work to protect ecological health of the Yampa

River and adjacent agricultural lands, while

providing opportunities for recreation. The group

worked to purchase conservation easements and

to negotiate cooperative management agreements

1996–

Present


agencies & NGOs)

About once a

month

Moffat &

Routt

Sand Wash Coordinated

Resource Management

(SW-CRM)

Worked to manage natural resource and wildlife

conflicts between landowners, concerned

citizens, and local government agencies in the

Sand Wash Basin

1995–

2000


agencies)

About once a

month

Moffat

Bald Mountain Basin

Coordinated Resource

Management (BMB-

CRM)

Worked to find common ground and solutions to

resource conflicts among landowners, concerned

citizens, and resource agencies in the Bald

Mountain Basin

1993–

1998


agencies)

About once a

month

Moffat


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Survey Design and Implementation

In order to assess change in social capital over time the

survey was designed with 2 sets of identical questions. The

first section asked the respondent to answer the questions

thinking about the group as it was when he/she first joined

it. The second section asked the respondent to answer the

same set of questions, thinking about the group as it is

today, or when he/she last participated. With this design,

we were able to mimic a pre- and post-test design in cir-

cumstances in which a pre-test would otherwise be

impossible.

As with many surveys, recall bias may be a source of

error. In order to check the data for accuracy and consis-

tency, we conducted semi-structured interviews with 12

key informants based on their knowledge of or involve-

ment in one or more of the surveyed groups. In these

interviews we asked several open ended questions to elicit

respondents’ perceptions of changes in relationships among

group participants over time. In addition, in our survey we

asked respondents about 2 points in time, the beginning and

the end of their participation, which were likely the most

salient and therefore which respondents are most likely

able to recall (Eisenhower and others 2004). Survey

respondents included participants who joined late or left

early, and as well as those who joined early and were still

involved at the time of the survey.

We incorporated elements into the survey design in

order to ensure content validity of social capital as it is

conceptualized and operationalized in this study. We

thoroughly reviewed the existing literature on social capital

measures, concentrating on measures that have been eval-

uated for reliability and validity (Krishna and Shrader

1999; O’Brien and others 2004; Onyx and Bullen 2001;

Stone and Hughes 2002). Based on this literature review

we included three dimensions of social capital: trust, rules

and reciprocity, and communication quality and quantity.

As previously indicated, an important aspect of social

capital is social networks, but time and resource constraints

prevented a comprehensive network analysis. Instead we

used communication quality as a proxy for network quality

because social networks are ‘‘produced through commu-

nication’’ and in turn, ‘‘determine the communication of its

members’’ (Pace and Faules 1994).

For each of the three social capital dimensions we

selected and developed measures that were relevant to a

group-level measure of social capital. The majority of

items were based on a 7-point Likert-like scale in which

response values were: 1 = not at all, 4 = somewhat,

7 = to a great extent. This allowed us to determine the

extent to which respondents felt each statement described

the participants of the group. (For the specific items used

for each dimension, refer to the tables in the results

section). For each dimension of social capital, we created

an index, calculated as the mean score of the component

items for each social capital dimension. For total social

capital, the index was the mean of all social capital metrics.

We submitted the survey instrument for review by

scholars of social capital and community-based collabora-

tion. We also pilot tested the survey on 2 collaborative

groups outside of the study area (52 respondents), after

which we made revisions to improve the survey’s appli-

cability and clarity.

Additional survey sections asked respondents about their

perceptions of group success (3-item mean composite

index; 7-point Likert like scale: 1 = strongly disagree,

7 = strongly agree) (Table 2), conflict [3-item mean com-

posite index; 7-point Likert like scale: 1 = not at all (i.e. no

conflict), 7 = to a great extent (i.e. high conflict)]

(Table 2), participant activeness [3 items: number of years

an individual has participated with the group (fill in the

blank), number of meetings attended per year, number of

group activities (e.g. field trips) attended per year (6-point

Likert like scale; 1 = 0 times, 6 = more than once a

week)], similar values and beliefs (3-item mean composite

index; 7-point Likert like scale: 1 = strongly disagree,

7 = strongly agree) (Table 2), previous collaboration

experience [2 part question: (a) have you participated with

any other collaborative group before you began participat-

ing with the group? (yes/no), (b) if yes, how many?], and

stakeholder diversity (respondent checked the stakeholder

group they represented). Group stakeholder diversity was

measured by calculating a Brillouin’s diversity index for

each group, which considers both richness (i.e., the number

of different stakeholder groups involved) and evenness (i.e.,

the distribution of participants among the stakeholder cat-

egories). The formula for Brillouin’s Index is:

H ¼ ln N!�X

ln ni!ð Þ

N where, N is the total number of observations, and ni is

the number of observations in category i (Brillouin 1956).

We determined group age (length of years group has

been active) from group informants and records, and group

size (number of participants involved) by identifying par-

ticipants from the group mailing list, checking the accuracy

of the mailing list with group informants, and excluding

individuals that did not attend at least one group meeting.

Using Dillman’s tailored design method (Dillman 2000),

we sent questionnaires to all participants of the 10 study

groups, as identified from group mailing lists. Participants

involved with more than 1 group in our sample received

multiple surveys, 1 for each group in which they partici-

pated. In all we sent out a total of 422 surveys to 339

people. We revised the participant lists to exclude indi-

viduals who never attended a group meeting based on


123

respondents’ answers to the question of how many meet-

ings were attended. From the 10 groups included in the

analysis, we received 181 completed surveys for an overall

response rate of 53%. Individual group samples sizes for

the 10 groups ranged from 3–56 respondents and response

rates ranged from 27–77%.

We conducted a non-response bias analysis to deter-

mine whether non-respondents differed from respondents.

We used a stratified random sampling procedure to select

10% of the non-respondents from the 8 groups that had

response rates below 65%. We phone surveyed the non-

respondents and compared their responses to respondents

for 4 items. Differences between respondents and non-

respondents for all items were not statistically significant

(P [ 0.05) and had small to medium Cohen’s D effect

sizes (0.06 to 0.67). Thus we concluded our sample was

representative and we could generalize to the group

(Cohen 1988).

Interviews

In order to validate and enrich the survey data, we inter-

viewed 12 participants selected from the groups in our

study. We selected group participants who had compre-

hensive knowledge of a particular group or who were

actively involved in numerous groups. Interviews were

semi-structured and focused on the change in group par-

ticipants’ relationships over time. Interviews included 6

broad questions with several optional probing questions

and covered how and why the respondent became involved

in the group, the respondent’s perceptions of changes in

relationships among group participants over time, their

perceptions of changes in relationships between the group

and other community groups or agencies over time, their

views on what they had personally gained by participating,

and what kind of impact, if any, they perceived the group

had on the larger community.

Table 2 Scale assessment for initial and current ‘‘trust,’’ ‘‘rules and reciprocity,’’ ‘‘communication quality,’’ ‘‘values and beliefs,’’ ‘‘conflict,’’

and ‘‘success’’ items

Index Item Cronbach’s Alpha

Initial Current

Trust Were honest .94 .97

Could be trusted

Were true to their word

Rules and reciprocity Worked according to common ground rules .95 .95

Returned acts of good will

Were helpful

Were committed

Recognized group value

Showed concern for group welfare

Were willing to compromise

Shared resources

Shared information

Communication quality Were willing to listen .93 .94

Respected others’ viewpoints

Considered all input equally

Communicated openly

Total social capital All items included in Trust, Rules and Reciprocity and Communication Quality .98 .98

Values and beliefs Shared similar values .94 .96

Shared similar opinions

Shared similar goals

Conflict Stakeholder groups differ dramatically in what they think are acceptable actions .81

Individual stakeholders differ dramatically in what they think are acceptable actions

Disputes among stakeholders have disrupted the collaborative process

Success Group was successful in fulfilling its purpose .86

Group found common solutions to its problems

Group has taken actions to implement key agreements


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Data Analysis

Statistical Analysis

We examined the relationship between current levels and

change over time of group social capital dimensions and

the following group characteristics: success, conflict,

activeness, previous collaborative group experience,

stakeholder diversity, group size, group age, similar values

and beliefs, and initial levels of social capital. Due to the

small number of groups in our sample and the small

number of individuals and respondents in some groups, we

pooled all participants from all groups and analyzed them

together. To examine group characteristic variables that are

based on the perceptions or behaviors of individual

respondents within each group (success, conflict, collabo-

ration experience, similar values and beliefs, and measures

of activeness), we used the participants’ survey responses.

To evaluate the effects of group-level characteristics such

as diversity, group age and group size on individual-level

social capital, we calculated a single value for each group.

Statistical analyses were conducted using SPSS 17.0. For

all analyses, relationships were deemed statistically sig-

nificant at P \ .05.

Predicting Current Levels of Social Capital

Because some independent variables were measured or

calculated at the group level, with no within-group varia-

tion (diversity, group age, and group size), while others

were based on the perceptions or behaviors of individual

respondents (success, conflict, collaboration experience,

similar values and beliefs, and measures of activeness), we

conducted our analysis in two stages. First, we conducted a

multiple regression to examine the relationship between

group characteristics measured at the group level and

current social capital (n = 10 groups). We examined 4

models, 1 for each of the 3 dimensions of social capital,

and a fourth model in which a total social capital index (the

combined total of the 3 social capital dimensions) was the

dependent variable.

Second, we used the general linear model (GLM) pro-

cedure in SPSS to assess the relationship between the

remaining independent variables, measured at the individ-

ual level, and current social capital. In order to account for

potential correlations among responses from participants

within the same group, we treated group as a random

factor, and the remaining independent variables as covar-

iates. In these analyses, current social capital was the

dependent variable, and the independent variables were the

group participant’s perceptions of group success and con-

flict, his/her activeness in the group, previous experience

with collaborative groups, similar values and beliefs, and

initial social capital. Using this approach, we examined the

same 4 models described for stage one.

We also conducted a simple mediation analysis using a

macro written for SPSS (Preacher and Hays 2004) to

determine the degree to which the relationship between our

predictor (initial social capital) and criterion (current total

social capital index) was mediated by success. The macro

conducts a series of regression analyses and estimates the

total, direct, and indirect effects of the predictor variable on

the outcome variable through the proposed mediator vari-

able. It also calculates the Sobel test for significance of the

indirect effect, as well as an effect size measure (Fairchild

and others 2009). This analysis was conducted after our

initial results revealed that both success and initial social

capital were significantly related to all social capital

measures.

Predicting Change in Social Capital Over Time

We examined the relationship between the change in social

capital over time and the group characteristics using the

same two-stage approach described above. The difference

between initial and current levels of social capital was

calculated as the current social capital score minus the

initial social capital score, creating a variable that varied

from -7 to ?7, with ?7 representing the maximum

potential increase in social capital and -7 representing the

maximum potential decrease in social capital over time. As

with our analysis of current levels of social capital, we

conducted a mediation analysis to determine whether suc-

cess mediated the relationship between initial social capital

and change in social capital over time.

Interview Analysis

Following transcription of all recorded interviews, we

deductively coded (Coffey and Atkinson 1996) all inter-

views using NVivo, a qualitative software package

(NVIVO QSR revision 1.2, QSR International Pty, Vic-

toria Australia, 1999–2000). Deductive codes were based

on survey items and included group characteristics such

as success, conflict, activeness, and diversity, and

dimensions of social capital such as trust, reciprocity, and

networks. The coded data were analyzed by reading

through the codes looking for emergent sub-themes.

Specifically, we searched for sub-themes that would

provide explanation for our survey results, and further,

that would provide insight into why group characteristics

were associated with the development, or lack of devel-

opment, of social capital.


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Results

Predicting Current Levels of Social Capital

Success, initial social capital, and collaboration experience

significantly predicted current levels of social capital

(P \ .05) (Table 3). Success and initial social capital pre-

dicted all 3 dimensions of social capital. When we con-

ducted a mediation analysis, we found that the relationship

between initial social capital and current social capital was

partially mediated by success (Table 4), and this indirect

effect was significant. Using Fairchild and others’s effect

size measure, 45% of the variation in total current social

capital was accounted for by success. Success had a posi-

tive relationship with all social capital measures, which

suggests that as the participants’ perceptions of group

success increased, their level of social capital also

increased. Collaboration experience was negatively asso-

ciated with trust, indicating that participants with past

experience in many collaborative groups were less trusting

of other participants than participants with little previous

collaborative experience. None of the group characteristics

(diversity, age or size) was significantly associated with

any social capital measure (Table 5). Overall, initial levels

of social capital and perceived success were the variables

most significantly correlated with current levels of social

capital.

Predicting Change in Social Capital Over Time

Success and initial social capital were significant predictors

of an increase in social capital over time (p \ .05)

(Table 6). Our mediation analysis showed that the rela-

tionship between initial social capital and change in social

capital over time was weakly but significantly mediated by

success (Table 7). Fairchild’s approach indicated that 20%

of the variation in the change in social capital over time

was accounted for by success. As with current levels of

social capital, group diversity, age and size were not sig-

nificantly related to change over time in any social capital

measure (Table 8).

Discussion

This study explored the effect of community-based col-

laborative group characteristics on the current level, and

changes over time, in group social capital. We predicted

Table 3 Predicting the influence of success, conflict, activeness (mean number of years in the group, mean number of meetings attended, mean

number of activities attended), previous collaboration experience, similar values and beliefs, and initial social capital on current levels of social

capital using four models

Current level of social capital

Trust Rules and reciprocity Communication quality Total social capital

b SE t b SE t b SE t b SE t

Success .464 .072 6.461a .430 .068 6.307a .562 .072 7.810a .465 .063 7.341a

Conflict .038 .063 .596 -.046 .064 -.714 .049 .064 .762 .002 .058 .039

# of Years in group -.033 .029 -1.174 .004 .027 .138 -.017 .028 -.602 -.007 .025 -.265

# of Meetings attended .086 .088 .981 .011 .083 .136 .038 .086 .446 .030 .077 .398

# of Activities attended -.013 .088 -.152 .021 .082 .256 .077 .086 .900 .030 .076 .395

Collaboration experience -.067 .027 -2.465a -.026 .026 -.982 -.001 .027 -.039 -.025 .024 -1.027

Similar values and beliefs -.090 .071 -1.254 -.112 .073 -1.533 -.056 .077 -.728 -.106 .069 -1.538

Initial social capital .531 .074 7.160a .416 .099 4.216a .378 .085 4.450a .453 .091 4.992a

In all models, group is treated as a random factor and the remaining independent variables as covariates. N = 136 participants in 10 community-

based collaborative resource management groupsa Significant at P \ .05

Table 4 Mediation analysis to assess the role of perceived success as a potential mediator in the relationship between initial social capital and

current social capital

Coefficient SE t P-value

Effect of initial SC on current SC .7254 .0475 15.2651 .000

Effect of success on current SC .6756 .0696 9.7080 .000

Effect of success on current SC, controlling for initial SC .3452 .0494 6.9820 .000

Effect of initial SC on current SC, controlling for success .4922 .0530 9.2872 .000


123

that groups’ perceived success, conflict, activeness, stake-

holder diversity, previous collaboration experience, simi-

larity of values and beliefs, size, age, and initial social

capital would be associated with the level and development

of social capital within the study groups. We found that

perceived success and initial levels of social capital were

most strongly associated with the level and change over

time of group social capital. In addition, initial levels of

social capital partially explained perceptions of group

success. Collaboration experience was negatively associ-

ated with current levels of trust.

Generalizations from these findings to other collabora-

tive groups should be made cautiously. We included only

10 groups in our analysis, and these groups do not represent

a random sample of community-based collaborative

groups. Further, we surveyed only group participants, and

Table 5 Predicting the influence of stakeholder diversity, group size and group age on current levels of social capital using four multiple

regression models

Current level of social capital


.22a .09 .15 .13


Stakeholder diversity .295 .901 .625 .434 .987 .850 .381 1.005 .772 .398 .971 .795

Group size -1.092 .013 -1.880 -1.041 .014 -1.655 -.976 .015 -1.605 -1.041 .014 -1.691

Group age -.394 .082 -.976 -.259 .090 -.592 -.127 .092 -.300 -.251 .089 -.586

N = 10 community-based collaborative resource management groupsa Adjusted R2

Table 6 Predicting the influence of success, conflict, activeness (mean number of years in the group, mean number of meetings attended, mean

number of activities attended), previous collaboration experience, similar values and beliefs, and initial social capital on change in social capital

over time using four models

Change in social capital over time



Success .464 .072 6.461a .430 .068 6.307a .044 .648 .069a .465 .063 7.341a

Conflict .038 .063 .596 -.046 .064 -.714 .562 .072 7.810 .002 .058 .039

# of Years in group -.033 .029 -1.174 .004 .027 .138 .049 .064 .762 -.007 .025 -.265

# of Meetings attended .086 .088 .981 .011 .083 .136 -.017 .028 -.602 .030 .077 .398

# of Activities attended -.013 .088 -.152 .021 .082 .256 .038 .086 .446 .030 .076 .395

Collaboration experience -.067 .027 -2.465 -.026 .026 -.982 .077 .086 .900 -.025 .024 -1.027

Similar values and beliefs -.090 .071 -1.254 -.112 .073 -1.533 -.001 .027 -.039 -.106 .069 -1.538

Initial social capital -.469 .074 -6.332a -.584 .099 -5.918a -.056 .077 -.728a -.547 .091 -6.019a

In all models, group is treated as a random factor and the remaining independent variables as covariates. N = 136 participants in 10 community-

based collaborative resource management groupsa Significant at P \ .05

Table 7 Mediation analysis to assess role of perceived success as a potential mediator in the relationship between initial social capital and the

change in social capital over time

Coefficient SE t P-value

Effect of initial SC on change in SC -.2776 .0470 -5.9075 .0000

Effect of success on change in SC .6910 .0699 9.8849 .0000

Effect of success on change in SC, controlling for initial SC .3360 .0477 7.0457 .0000

Effect of initial SC on change in SC, controlling for success -.5097 .0525 -9.7152 .0000


123

did not include non-participants, which could lead to more

extreme views of group success and interpersonal trust

(Leach 2002). Nevertheless, these findings help refine

social capital theory as it relates to CBCRM specifically,

and offer practical implications for community-based col-

laborations. Specifically, our research suggests that the

outcomes of social interactions in CBCRM settings sig-

nificantly affect the extent to which social capital develops.

Success

This study shows that participants’ perceptions of group

success are significantly correlated with their perceptions

of group social capital. These findings are consistent with

the literature that suggests that small but consistent suc-

cesses keep people at the collaborative table (Wondolleck

and Yaffee 2000). Our findings indicate that collaborative

groups may develop different levels of social capital

depending on their perceived level of success. This is not to

say that unsuccessful groups do not build any social capital,

but rather that groups build the most social capital when

they are perceived as successful by participants. If a given

group does not make tangible progress towards goals, then

listening, communicating, and understanding other’s

viewpoints do not seem to be sufficient to build significant

social capital. Though theory suggests success will

encourage social capital development, results from at least

one recent study do not support this relationship. Leach and

Sabatier (2005) concluded that success (measured as

agreements reached and restoration projects implemented)

did not have a significant feedback effect on trust and

social capital. Our results generally contradict this finding,

and support the theory that success, as perceived by par-

ticipants, helps build social capital.

Interviews also supported the finding that perceived

success helps develop social capital. Interviewees com-

monly voiced the opinion that success is important for

building social capital. For example, past experiences of

finding common solutions or making agreements, can help

to build trust and expectations of reciprocity. As one par-

ticipant commented, ‘‘It is kind of having it in the back of

your mind, oh we have done this before and we will work it

out again.’’ Success in implementing an agreement may

also help to build trust. For example, one group coopera-

tively designed a research program to answer questions that

stemmed from two conflicting viewpoints on a contentious

wildlife and grazing issue. One participant commented, the

success of designing and implementing the research pro-

gram, ‘‘helped the trust immeasurably, to get past posi-

tioning to real data.’’ These examples confirm prior

research and experience. For instance, in the case studies

reviewed by Wondolleck and Yaffee (2000), successful

collaborations were ‘‘structured to provide participants

with an early tangible success: They started small, pro-

duced results, and went on to bigger issues and efforts. By

taking small steps, success was more likely’’ (p.187).

In turn, being unsuccessful may negatively affect social

capital. For example, a participant of a group commented,

‘‘I think that because the [group] has realized that

they have kind of come to the end of the rope and not

accomplished what they were thinking they were

going to accomplish, I think that has led to a little loss

of respect for the [agency].’’

Initial Social Capital and Previous Collaboration

Experience

Initial levels of social capital were associated with the

current level of social capital and with changes in social

capital over time. Initial social capital was positively

associated with current social capital and negatively asso-

ciated with changes in social capital over time. Initial

social capital may be beyond the immediate control of the

Table 8 Predicting the influence of stakeholder diversity, group size and group age on change in social capital over time using four multiple

regression models

Change in of social capital over time


-.42a -.13 .27 -.09


Stakeholder diversity .291 .603 .456 .572 .395 1.007 .789 .459 1.721 .613 .433 1.095

Group size -.326 .009 -.414 -.188 .006 -.269 -.203 .007 -.360 -.238 .006 -.345

Group age .001 .055 .002 .261 .036 .537 .397 .042 1.011 .259 .040 .542

N = 10 community-based collaborative resource management groupsa Adjusted R2


123

group. Beginning levels of social capital are difficult to

change because they are the initial conditions that the

group has to deal with from the start of the collaborative

process. Perhaps the only way to change the level of social

capital at the inception of a collaborative group would be to

take steps to develop social capital before the group’s work

actually begins.

If collaboration builds social capital, we would expect

individuals with more collaborative experience to express

higher levels of trust in other participants and other social

capital dimensions, than participants without previous

collaboration experience. We found that previous collab-

oration experience was an important predictor of current

levels of trust, though not in the direction we hypothesized.

In this study, previous collaboration experience was neg-

atively associated with trust, which suggests that individ-

uals with previous collaboration experience were less

trusting of other participants than those with little or no

previous collaboration experience. Theory suggests it takes

time to develop trust, and if the previous collaboration

experience was with the same participants (as was often the

case in our study groups), this experience may represent

additional opportunities for interaction, through which trust

could be built. Data from our interviews support this view,

and are at odds with our survey results. For example, one

participant who has worked with the same agency in two

consecutive groups commented,

‘‘I think that [the previous group] has helped because

now [in the current group] I have more appreciation

for what the agency has to try and do, and I have a

new respect for what they have to deal with.’’

Another participant commented,

‘‘I think without the training that occurred in those

[previous groups], this [group] would have not been

possible. Without a lot of the work that went into the

early years of the [previous groups], the hard work of

banging heads and trying to come up with some

agreements, I’m not sure this [group] would have

been possible or lasted as long as it has, if it wasn’t

for the history of those [previous groups].’’

Interviews also suggested that previous collaboration

experience with different participants could also affect

trust. When asked if their previous collaboration experi-

ence influenced their ability to work together in a current

group, one participant commented,

‘‘I think it helped because it is a learning process. I

think that the more you work at this, the better you

get at it, at trying to look at different points of view,

and trying to help come up with a solution….I think

over time, you get into groups and you can take ideas

that you’ve learned in other groups and apply it. You

become better at trying to come up with solutions.’’

Further research is needed to understand our findings

that show a negative relationship between previous col-

laboration experience and development of trust. Perhaps

individuals involved with numerous collaborative groups

become less trusting over time. Alternatively, these indi-

viduals may be less trusting to begin with, and choose to be

involved in numerous groups for fear of decisions being

made without their input. Our results somewhat support the

findings of Berardo (2009), who found that network density

was not necessarily the best predictor of trust, leading him

to question whether trust is an essential ingredient in

collaboration.

Stakeholder Diversity, Similarity of Values and Beliefs,

Number of Years in a Group, Group Size, Age, and

Activeness

Stakeholder diversity, similarity of values and beliefs,

years in the group, group size, age and activeness did not

predict current social capital or changes in social capital

over time in this study. One interview respondent explained

why stakeholder diversity may not matter:

‘‘I don’t think the diversity [of the stakeholders] has

much to do with it. Because as long as you have

[stakeholder group A] and [stakeholder group B] at

the table, that is where the conflict is coming from. I

don’t care if the [stakeholder group C] folks are there,

I don’t care if the [stakeholder group D] folks are

there, it doesn’t change the conflict dynamic between

[stakeholder group A and B] at all.’’

In this case, the level of social capital within the

group was clearly restricted by the presence of two

particular stakeholder groups, regardless of the total

number of stakeholder groups involved. Further research

is needed to examine the tradeoffs between group size,

stakeholder diversity, and the level and development of

social capital.

In our survey, participant activeness in terms of the

frequency, duration, and type of interaction among partic-

ipants was not significantly associated with the level of

social capital. However, some interview responses sug-

gested that frequency and duration of interaction can affect

social capital passively. For example, one participant

commented,

‘‘I think you develop a relationship whether you like

it or not. You start to understand how they think and

where they are coming from if you spend very much

time with them.’’


123

Is frequency or duration of participant interaction more

important for social capital development? One participant

seemed to think they were fairly equal and commented,

‘‘I’ve known [participant A] for a long time, but we

haven’t spent a lot of time together in meetings. And

then [participant B], I haven’t known for very long,

but we have spent a lot of time together in meet-

ings…I would put them actually pretty similar in

terms of my relationship with them. We have famil-

iarity, there is a certain level of trust, maybe not a

very high level of trust, but we can definitely con-

verse easily without too much tension…That’s

interesting, I don’t see a big difference between those

two relationships.’’

Further research could explore whether frequency of

interactions or duration of relationships provides greater or

more quality opportunities for social capital development.

Interviews also suggested that the type of interaction

may affect social capital development. Some participants

felt that activities such as field trips were beneficial for

social capital development. Field trips provided opportu-

nities for socialization outside of group meetings that

allowed participants to exchange information and explain

where they are coming from, and as one participant noted,

‘‘actually tie it to the ground.’’ Another participant

commented,

‘‘The [group] did go out on field trips together. I think

that was a tremendous help, to go out and look at sites

and look at the habitat. We actually went out on

several tours and actually looked at different areas

and I think that helped a lot.’’

However, other participants felt such activities did not

make a significant difference. One participant commented,

‘‘I think this group could meet outside for a year and

not get anywhere. I think it helps, but it is certainly

not the silver bullet, get outside and everything is

going to be better.’’

Conclusion

Research has suggested that social capital may facilitate

collaboration and in turn, collaboration may build social

capital. However, little research has sought to address the

question of why some CBCRM groups build constructive

and valuable connections while others are unable to build

trust and form new relationships. By examining group

characteristics, this study sought to uncover potential cat-

alysts and barriers to the development of productive and

meaningful connections among participants in CBCRM

groups.

This research suggests that the level and development of

social capital in a CBCRM group is associated with certain

group characteristics. We found that groups that are per-

ceived as successful, start off with social capital, and lack

previous collaboration experience are most likely to have

and develop high levels of trust, strong norms of reci-

procity, and quality network connections. Group size, age,

activeness, conflict, and similarity of values and beliefs

were not associated with social capital in our study. These

results suggest that the outcomes of interactions within

collaborative groups may be more important for develop-

ing social capital than the duration or frequency of inter-

actions, the diversity of participants, their associated values

and beliefs, group conflict, or the size of the group.

For CBCRM practitioners, our most important finding

may be the association between perceived success and

social capital. Is collaboration a worthwhile investment

because of the social relationships it may build, even when

agreements are not reached or are not implemented? Our

research suggests that it may not be. In this study, social

capital development depended largely on the perceived

success of the group. Groups that feel they are making

progress towards or attaining their goals develop more

social capital than groups that perceive themselves as

unsuccessful in achieving their objectives. These findings

imply that if collaborative groups want to build social

capital, they must achieve tangible outcomes, such as

reaching agreements and implementing actions on the

ground.

The relationship between collaboration and social cap-

ital is complex. While group characteristics such as par-

ticipants’ collaboration experience may contribute to low

levels of or declines in social capital, high levels of social

capital seem to require progress towards group goals. It is

generally accepted that social capital facilitates collabora-

tion, innovation, and adaptation. The question remains,

how much social capital is needed to achieve these

benefits?

Collaborative processes continue to be important for

managing natural resource conflicts. Building social capital

to facilitate these processes is crucial to their effectiveness,

and CBCRM practitioners need effective tools to develop

trust and norms of reciprocity and forge strong relation-

ships among group members. This study has provided

insight into some of the group characteristics associated

with social capital development. Continued research into

the complex relationship between collaboration and social

capital will help increase the efficacy of collaborative

processes as well as our understanding of their broader

benefits to society.


123

Acknowledgments This research was supported by the Colorado

Agricultural Experiment Station. We thank the collaborative group

members who responded to our survey and participated in interviews

as well as the two anonymous reviewers who provided extensive

comments on our initial manuscript. We also thank Drs.Tara Teel,

Jerry Vaske, and Jim Zumbrennen for their consultations on our

statistical analysis.

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Documents

Effects of Community-Based Collaborative Group Characteristics on Social Capital