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Which Resources Matter for What Impacts? Resource Mobilization and Impacts of Local

SMOs in Rural Lithuania, 2004-2006

Jurgita Abromaviciute

School of Sociology

University of Arizona

jurgitaa@email.arizona.edu

Ryan Seebruck

School of Sociology

University of Arizona

seebruck@email.arizona.edu

Bob Edwards

Department of Sociology

East Carolina University

edwardsr@ecu.edu

August 2016

Acknowledgements:

This research was partially supported by grants from The United States Department of State,

International Research Exchange (IREX), the East Carolina University, Russian Studies

Program, the Department of Sociology at East Carolina University, and the Department of

Sociology at Vilnius University.

The authors also wish to thank Arunas Juska, Arunas Poviliunas, and Richard Pozzuto for their

support of this project and insight and especially in the development of the initial survey in 2004.

We also thank Maria Dillard and Jesse Edwards for their assistance in administering the 2006

follow-up.

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Which Resources Matter for What Impacts? Resource Mobilization and Impacts of Local

SMOs in Rural Lithuania, 2004-2006

Abstract (215 words)

Do variations in mobilizing material, human and social resources affect the impacts of local,

social movement organizations that emerged in post-soviet Lithuania in the early 2000s?

Original, longitudinal data collected in 2004 and 2006, enables us to analyze three types of rural

advocacy organization impacts: issue awareness, local support, and media coverage. Based on

the premise that the importance of a given resource varies across impacts, we draw on Resource

Mobilization Theory and employ a series of ordinal logistic regression analyses to test a set of

hypotheses for each type of impact. In general resources do matter, yet different resource types

matter differently for the organizational impacts examined here.. In terms of human resources,

the ability to mobilize people supersedes the sheer number of members or a number of core

activists when predicting issue awareness. Similarly, for material resources, an organization’s

ability to maintain diversified funds is far more important than the reported size of the

annualized budget in predicting both issue awareness and local support. Social resources have no

effect on issue awareness, yet they negatively related to gaining local support and positively so

for gaining media coverage. This implies the need to differentiate between the unique

relationships of resource types and various impacts and also to make distinctions within specific

types of resources.

Key Words: social movements, resource mobilization, non-governmental organizations,

organizational impacts, advocacy organizations, rural issues, Lithuania

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Introduction

Resource Mobilization Theory (RMT) has long argued that access to resources is the key

predictor of social movement and social movement organization (SMO) capacity to act, impact

and success (McCarthy and Zald 2001; Edwards and McCarthy 2004). While the literature on

organizational survival and outcomes of SMOs is ample, there has been a dearth of systematic

studies testing this core assumption of RMT and little to no longitudinal research linking specific

types of resources to specific types of impacts, particularly for local SMOs (Edwards and Kane

2014). Our goal is to address these gaps by testing the impact of various types of mobilized

resources on local SMO success over time.

Our substantive focus is on widespread grass-root activism in rural areas that emerged in

Lithuania in the early 2000s. A typical rural community movement organization consists of five

to ten key activists who organize to solve social, cultural, and political problems affecting

theirvillage. Such groups engage in a range of activities, from developing handcraft circles for

elderly people, to computer and business training of the unemployed, to solving infrastructural

problems, and advocating for favorable public policy in the Capitol. Women led the majority of

groups which with few exceptions were run entirely with volunteer labor (Edwards, Dillard and

Juska 2009). In 2003, seven rural community organizations established the Union of Rural

Communities in Lithuania (LRCU), which, in 2016, represents over 880 organizations (ELARD

2016). As a member of The Committee of National Rural Development, Lithuanian Chamber of

Agriculture, the board of Lithuanian Chamber of Agriculture and other organizations, LRCU

intercedes for individual community organizations and government institutions. It also has

several programs designed to train community leaders. So while the Lithuanian rural community

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movement started as grass-roots activism, it is now represented by a broader umbrella

organization that trains local leaders in institutionalized programs.

Beyond our theoretical interests, this rural community movement is significant in several

ways. First, the emergence and development of civil society throughout rural Lithuania bodes

well for the long-term health of Lithuanian democracy and its ability to incorporate rural

villagers into democratic institutions. Second, the developing network of village-level and

regional organizations, along with national umbrella groups like the LRCU, increase the

representation of rural issues and concerns in national policy debates. Lastly, the efforts of rural

organizations’ activists should bring the rural issues to the attention of and elicit the support from

local people. The last point is the substantive focus of this study.

We combine our theoretical and substantive interests into the following research

questions. First, do social movement organizations with higher levels of various resources in

2004 report positive change in impacts—issue awareness, support, and media coverage—in

2006? Second, how does the importance of a given resource vary by the type of impact? Third,

are there any resources that are consistently important across various types of impacts?

We begin the analysis by situating our case in the political and socioeconomic context in

which this grass-roots social movement was born.

Background

The Case of Rural Community Movement in Lithuania

The emergence of the rural community movement in Lithuania has been largely

interpreted as a result of two intervening factors: on the one hand it was a response to the

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agricultural crisis that followed the aggressive neo-liberal economic reforms imposed after

independence; on the other hand, it has been seen as a response to favorable structural conditions

of changing rural policies and political opportunities associated to Lithuania’s accession to the

EU.1

The collapse of the Communist rule in 1991 and transition from a centrally planned to a

market economy led to a deep and protracted crisis in agriculture, which disproportionately

affected the rural population. During the Soviet period, Lithuanian agriculture was dominated by

a system of state-owned collective farms (kolkhoz). Throughout the early 1990s, the Lithuanian

government aggressively pursued neo-liberal reforms which included privatization of kolkhoz

land and property in rural areas. The majority of the rural population perceived those reforms as

illegitimate and arbitrary because they were carried out with little input from the dominant

majority of the agrarian population that did not want to abandon large scale production and

return to homesteads (Alanen 1999; Davis 1997). The chaos of privatization resulted in conflicts,

as neighbors and family members fought with one another over kolkhoz land and property (Juska

2007).

In addition to local tensions, most people who had previously worked in the kolkhoz

infrastructure lost their jobs. According to the data from 1997 to 2001, the official rates of

unemployment were as high as 17 to 21 percent in the most economically distressed rural areas

(Statistikos Departamentas 2002). However, because the official unemployment rate counted

1 For detailed analyses of both the origins of this community organizing movement and the conditions facilitating its

emergence and mobilization see Juska, Poviliunas, and Pozzuto 2005a; Juska et al. 2005b; and Edwards, Dillard,

and Juska 2009.

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subsistence farming as employment, the real rate of unemployment in rural areas was likely

twice as high as indicated by the figures.

As agriculture continued to decline through the 1990s, unemployment and poverty in

rural areas soared, resulting in the formation of a growing pauperized stratum mostly composed

of those displaced from agricultural employment. By the early 2000s, the rural population

represented only one-third of the nation’s population, yet more than 53 percent of all poor lived

in rural areas (Ratkeviciene 2004).

By the end of the decade, the Lithuanian government had abandoned its neo-liberal

reform agenda and had begun to institute protectionist policies (Frohberg and Hartman 2000). By

the early 2000s the national rural policy was expanded beyond agricultural support to emphasize

the overall rural development, including its sociocultural aspects.

Aside from national protectionist policies, there was a lot of support coming from the

European Union (EU). Several programs—SAPARD, PHARE, LEADER—were established to

ease the transition of the prospective members to the EU markets. For example, LEADER

funded various projects aimed to facilitate social and economic development of rural areas.

All these institutional changes stimulated rapid growth of rural community groups,

creating a political opportunity structure (Meyer 2004) ripe for local activism. Taking this

political opportunity as a constant, in what follows, we examine the effects of different types of

organizational resources on local impacts of these social movement organizations.

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Conceptualizing Impacts

Social movement scholars generally agree that SMO outcomes are understudied (Burstein

et al. 2002, Andrews 2001, Cress and Snow 2000, Burstein 1999, Giugni 1999, Giugni 1998,

Andrews 1997, Staggenborg 1995). This has been partially attributed to conceptual and

methodological problems that hinder systematic research of impacts (Amenta and Caren 2004,

Cress and Snow 2000, Burstein and Linton 2002, Giugni 1998).

Regarding social movement outcomes, the terms “impacts”, “success”, “outcomes”,

“consequences”, and “effects” are often used interchangeably, yet clarification is needed. Some

analysts (Amenta and Caren 2004, Giugni 1999, Amenta and Young 1999) note an important

distinction between the terms “impacts” and “success.” Even though both concepts refer to some

sort of consequences, the research questions they represent are different. The concept of success

is inextricably tied to the extent of achieving the set goals of a movement or an SMO. While we

acknowledge this distinction, in our study, we use the terms “impacts”, “effects”, and “success”

interchangeably, referring to an increase in a positive outcome over time.

Perhaps the most influential work in the area of social movement impacts remains

William Gamson’s The Strategy of Social Protest” (1990). Gamson approached the assessment

of success as a two-dimensional result which encompasses two types of outcomes: one has to do

with the fate of a challenging group itself whereas the other is concerned with the benefits won

by a group for its beneficiaries (Gamson 1990: 28-29). These outcomes are correspondingly

termed “acceptance” and “new advantages”. Acceptance is defined as a change from hostility or

indifference to a more positive view on behalf of antagonists. The four indicators and degrees of

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this more positive relationship include consultation, negotiations, formal recognition, and

inclusion (Gamson 1990).

In defining new advantages, Gamson (1990) holds that the starting point in assessing

achieved benefits is group’s goals and aspirations. The central question here is, “Did the

potential beneficiaries of the challenging group receive what the group sought for them?”

(Gamson 1990:34). Treating the two aspects of success as dichotomous variables, Gamson

distinguished four possible outcomes: full response, co-optation, preemption, and collapse

(Gamson 1990:28-29). Full response represents achievement of both (acceptance and new

advantages); co-optation means acceptance without new advantages; preemption stands for new

advantages without acceptance; and collapse represents failure to achieve them (1990:29).

Gamson’s conceptual scheme serves as a starting point for our analysis. One of the three

impact types—increased support from local people—can be loosely conceptualized as a local

new advantage; however, this term does not capture the other two types of outcomes we are

interested in. Moreover, the classical definition of Gamson’s impacts does not distinguish

between cultural and substantive gains. Cultural impacts involve changes in social norms and

behaviors, alterations in public understanding of an issue (Bernstein 2003), “collective

consciousness” which can affect future mobilization, and, consequently, the ability to influence

policy changes (Mueller 1987). As Mueller suggests (1987: 93), some movements (e.g.,

women’s movement), prior to seeking policy changes, need to challenge existing ideas and

cultural practices. Thus, she suggests distinguishing between cultural outcomes and substantive

benefits (new advantages). In our case, the increased awareness of rural issues and local media

coverage are cultural impacts that are likely to foster more substantive gains in the future.

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Predicting Impacts

A large portion of empirical research on the impacts of SMOs has been done within the

framework of Resource Mobilization Theory. The underlying assumption of this theoretical

tradition is that the access to and mobilization of resources is a key factor in making an impact.

The aim of this paper is to test the relevancy of some of the tenets of resource mobilization

theory to rural social movement organizations in Lithuania.

Current formulations of Resource Mobilization Theory differentiate five types of

resources: moral, cultural, social-organizational, human, and material resources (Edwards and

McCarthy 2004; Edwards and Kane 2014. Our data enable us to focus here on three types:

human, material, and social-organizational resources.

Human resources include labor, experience, skills, expertise, and leadership. Individuals

make their labor, experience, skills, and expertise usable through participation in SMOs activities

(Edwards and McCarthy 2004). Minkoff (1999) found that the number of individual members

increases survival prospects of SMOs focused on women’s or racial-ethnic issues. Similarly, in

the study of peace groups (Edwards and Marullo 1995), membership size and volunteer labor

were found to be positively related to the survival of SMOs. McCarthy and Wolfson (1996), in

their study of resource mobilization by local SMOs of the movement against drinking and

driving (MADD), assessed the role of activists’ efforts in mobilizing other kinds of resources.

They found that the amount of effort activists invest in collective action consistently predicts the

organization’s revenue.

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Material resources refer to financial and physical capital, such as budget, property, office

space, equipment, and supplies. Financial resources have an important role in determining the

capacity of SMOs (Zald and McCarthy 1987, Edwards and McCarthy 2004). Large budget

organizations can afford specialized committees that address membership, media coverage, and

organizational maintenance. It also can help to acquire moral resources, such as legitimacy and

support (Edwards and Kane 2014).

Three general forms of social resources include social networks and organizational

infrastructure. Social network ties are an important predictor of SMO’s survival. In their analysis

of small local peace movement organizations, Edwards and Marullo (1995) found that small,

local SMOs, like those studied here, are much more likely to persist over time when they have a

broad range of ties to other SMOs in their area. Similarly, in their analysis of the survival of local

chapters of Mothers against Drunk Driving (MADD), Edwards and McCarthy (2004) found that

groups with a greater stock of weak ties within the community were also more likely to survive.

These findings certainly do not imply that the organizations that had broad ties and therefore

survived, also achieved great impacts. However, it is plausible to hypothesize that social ties to

other similar organizations would also enhance the impact than an organization makes on its

community.

Regarding organizational structure, formalization has been frequently taken into account

in analyzing outcomes of SMOs, given that resource aggregation and management requires some

form of organization (McCarthy and Zald 1977). However, scholars have predominantly focused

on large, formal organizations (see McCarthy and Wolfson 1996). Thus little is known about the

effects of formalization in small local groups (Edwards 1994, Andrews and Edwards 2005).

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Formalization of an SMO refers to certain types of operating procedures. Specifically, it involves

procedures or structures that enable organizations to perform various tasks routinely and to

continue to function with changes in leadership (Staggenborg 1988). The concept of

formalization has been often used interchangeably with bureaucratization (Edwards 1994,

Staggenborg 1988, Gamson 1990). For example, Gamson (1990) considered an SMO to be

bureaucratic if it had procedural formality, record keeping, and complexity in role

differentiation. Staggenborg (1988), differentiating between formal and informal SMOs, set the

following criteria: bureaucratization of decision procedures, the degree of labor division for

various functions, presence of explicit criteria for membership, and presence of rules governing

sub-units. Informal organizations, as compared to formal ones, have few established procedures,

loose membership requirements, and minimal division of labor. The organizational structure is

frequently adjusted and assignments are developed to meet immediate needs. Also, informal

SMOs are dominated by volunteers and are vulnerable to leadership changes (Staggenborg 1988:

597).

Scholars have generally argued that formalization works in favor of SMOs (Minkoff

1999, Staggenborg 1988, Gamson 1990). Gamson (1990) found that bureaucratization is one of

the characteristics of “successful” groups. Staggenborg concluded in her research on pro-choice

movement organizations that formalized SMOs were better able to maintain themselves in two

ways: first, through paid staff that can be relied on in carrying out organizational tasks, and

second, through formalized structure which ensure continuity regardless of changing leaders or

environmental conditions (Staggenborg 1988). Minkoff (1999), in her study of survival of

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women’s and minority organizations, discovered that formalization is correlated with

organizational flexibility and survival.

So far we have discussed the role of various types of resources found in previous

research. In our study, we also control for other relevant factors, specifically tactics and

organizational age. Regarding tactical repertoire, the ongoing debate has centered on the

dimension of disruption vs. moderation. This debate has been framed as the question of whether

disruptive groups are more successful than the moderate ones. Piven and Cloward (1979, 1993)

are often cited as the primary proponents of the effectiveness of disruptive tactics (see Andrews

2001; Giugni 1998, 1999). According to them, disruption is a powerful resource that challengers

have at their disposal because they usually lack the institutional resources that are available to

other, dominant actors (Piven and Cloward 1993). Gamson (1975) also found that disruptive

tactics are associated with success. In a more recent study of local environmental groups

Andrews and Edwards (2005) showed that disruptive groups saw themselves as more successful

across various dimensions of impacts.

Others, however, argue that disruptive tactics are not that effective in achieving group

goals since they can alienate would-be allies and therefore hinder the movement’s goals

(Goodwin 2007). A greater effectiveness and persistence are achieved using more

institutionalized tactics, such as electoral politics, coalitions, lobbying, and litigation (Andrews

2001). For example, analyzing organizational mortality of peace movement organizations,

Edwards and Marullo (1995) found that SMOs that undertook an insider political action were

less likely to disband.

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Finally, we consider the age of an organization. Controlling for age is important because

structural inertia increases with organizational age (Hannan and Freeman 1989), meaning that

newer organizations, while at higher risk of death (Carroll 1983), are also more adaptive and able

to capitalize on new opportunities. This, in turn, could affect an SMO’s ability to see increases in

the impact areas of interest. On the other hand, increased organizational age has been argued to

increase levels of reliability among members, who have sunk costs after learning organization-

specific skills and therefore an incentive to keep the organization going, and older organizations

are more likely to have legitimacy among the public (Hannan and Freeman 1989), all of which

suggests older organizations should see higher levels of success.

Data and Methods

Our data come from an original, longitudinal survey of rural, non-governmental

organizations (NGOs) in Lithuania, administered by mail in the summer of 2004 with a follow-

up survey to responding organizations in the summer of 2006.

Sampling Frame

Enumerating the population of organizations from which to select a sample is a major

challenge in collecting the type of organizational data used here and the construction of sampling

frames for organizational populations can account for up to half of the costs of conducting such

research (Kalleberg et al. 1990). Thus, nearly all systematic research on social movement and

advocacy organizations has been based on widely available directories of non-profit groups

(Andrews et al. 2016). The sampling frame for the 2004 survey comes from an electronic

database compiled by the Lithuanian Non-Governmental Information and Support Center (2004).

At the time of the survey, it was the most comprehensive, nation-wide list of non-profit

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organizations operating in Lithuania. The criteria for constructing the sample included the

following: (1) rural location—all groups had to be located in rural areas away from major

metropolitan centers; (2) scope of operations— groups operating at the village-, municipal-, or

county-level were included; those with district-, national-, or international-level operations were

excluded. From these criteria, 527 organizations were identified and sampled in 2004.

Organizational Survey

Doing survey research on samples drawn from populations of organizations has become

common in the social sciences and in research on social movements (Edwards and Kane 2014).

Many researchers have successfully used surveys to collect data on a diverse range of advocacy

and movement organizations (Andrews et al 2016). The data collected here captures variations

in organizational structure, resource flows, leadership, decision-making processes, participation

in informal networks and coalitions, social change strategies, goals, and activities needed to

address important debates about movement organizations. The survey was similar in content and

format to prior research on social movement organizations and was translated into Lithuanian by

native speakers and pretested with community organization leaders (Edwards and Marullo 1995,

McCarthy and Wolfson 1996, Smith and Weist 2005, Andrews and Edwards 2005.) The survey

was administered by mail from Lithuania’s capital, Vilnius, in July and August of 2004.A total

of 527 questionnaires were sent to rural movement NGOs, of which 237 were completed and

returned for a preliminary response rate of 45 percent. Surveys were completed by organization

leaders knowledgeable about the group’s operations and activities. While using self-reported data

from representatives of the organizations may raise concerns about data validity and reliability,

McPherson and Rotolo (1995) found this method to be as reliable as other more labor-intensive

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strategies for collecting similar data on voluntary organizations. Though the exact status of the

non-responding groups remains undetermined, a response bias analysis was conducted to test for

significant differences between responding and non-responding groups using data from a source

independent from the survey that revealed no cause for concern (Smith 1997). The follow-up

survey in 2006 was sent to leaders of those organizations that responded in the 2004 survey

(N=237). A total of 171 groups completed and returned questionnaires in 2006, for a response

rate of 72.2 percent. Six of rural SMOs reported a scope of operation larger than county,

meaning that in the two-year span since the original survey was administered, they outgrew the

original population of interest and were therefore excluded from the analyses, resulting in a final

analytic sample of 165 social movement organizations. A subsequent response bias analysis used

2004 survey data to compare respondent and non-respondent organizations in 2006 and revealed

very few significant differences and none suggestive of theoretically relevant systematic bias

(Abromiviciute 2007).

Dependent Variables

Three measures of self-reported organizational impact are used in this analysis with no

independent validation from external sources. We focus on three types of perceived impact of

local social movement organizations: (1) success in increasing awareness of rural issues

(awareness); (2) success in gaining support from people in the village (support); and (3) the

volume of local media coverage (coverage). The questionnaire items that captured these impacts

were as follows: (1) “We have succeeded in increasing awareness of rural issues” (awareness),

(2) “Our group has been successful in gaining support in the village” (support), and (3) “During

the last year, about how much coverage has your group received from local newspapers?”

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(coverage). Each impact was gauged by asking organizational representatives to evaluate

statements using a 5-point Likert scale. For the first two types of impacts (awareness, support), 1

indicates “strong disagreement”; 2, “disagreement”; 3, “neutrality”; 4, “agreement”; and 5

signifies “strong agreement”. For the third impact (coverage), 1 represents “none”; 2, “a very

small amount”; 3, “a medium amount”; 4, “a fairly large amount”; and 5 indicates “a very large

amount”. While there may be concern about the inherent bias of self-reported measures of

perceived impact which are seldom used in studies of political organizations (Andrews and

Edwards 2005), research on work organizations frequently use similar methods to measure

organizational performance (i.e. Kalleberg and Moody 1994).

Because we are interested in organizational success over time, dependent variables based

on these impacts were created in three steps. First, to capture change over time, we subtracted the

2006 scores from the 2004 scores for the abovementioned Likert-scale responses. Second, in

order to standardize our comparisons, we calculated the Z-scores of these change variables.

Third, based on the distribution of the change variables’ Z-scores, for each of the impacts of

interest (awareness, support, coverage), we created our final dependent variables by coding

cases into three categories: (1) a decrease in success greater than one Z-score (i.e. negative

change); (2) a decrease or increase within one Z-score (i.e. no change); (3) an increase in success

greater than one Z-score (positive change). These three dependent variables capture change

between 2004 and 2006 in rural Lithuanian social movement organizations in the following

areas: (1) success in raising awareness of rural issues, (2) support from people in the village, and

(3) volume of local media coverage.

Independent Variables

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Drawing on resource mobilization theory, we examine how four types of resources

predict change in social movement organization success: human resources, material resources,

social resources, and organizational resources. Human resources include number of members

(“About how many members does your organization have now?”), number of active volunteers

(“About how many people contribute 5 or more volunteer hours a month to the organization”),

and action mobilization (“Our group has been successful in mobilizing people for activities”,

from 1 - “strongly disagree” to 5 - “strongly agree”). Total membership measures the overall

impact that having a large number of affiliated individuals has on SMO success. The number of

dedicated volunteers measures the importance of mobilizing volunteer labor on the perceived

success of an organization. Whereas the former measure can be seen as a quantity-over-quality

argument, the latter measure emphasizes quality over quantity. The final measure, mobilization,

gauges how active members are in pursuit of organizational goals.

Two measures capture organizations’ material resources: estimated revenue for the year

of 2004 (“Approximately, what is your group’s budget for the current year?”) and reported

success in maintaining diversified funding sources (“We succeeded in developing and

maintaining diversified funds”; 1 - “strongly disagree”, 5 - “strongly agree”). Whereas the former

measure indicates overall capital available, the latter measure ascertains whether an organization

has a broad array of support, which indicates that they are not overly dependent on any single

funding sources and also intimates that their organizational goals and tactics have mainstream

appeal.

Social resources are measured as a local SMOs’ affiliation with a broader organization

(“Is your group formally affiliated as a local chapter of a broader organization?”). Such alliances

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with broader organizations provide local chapters of SMOs with access to the larger resource

pools and a heightened ability to gain recognition and notoriety. For instance, Keck and Sikkink

(1998) note that less powerful groups often cannot resolve problems on their own and that links

to larger organizations or networks provide benefits such as information exchange, organization,

and a medium for organizations with a small voice that would otherwise be ignored.

Finally, organizational resources also have been shown to play an important role in social

movement success (Giugni 1998), with some arguing that movement success is unlikely to occur

without effective organization (Brill 1971). Gamson (1990) contended that successful SMOs

were more likely to be centrally organized. Staggenborg (1988) found that formalized SMOs are

more likely to survive when environmental factors hinder mobilization. Following that, we

include two structural variables: specialization (the organization has a specialized membership

recruitment committee) and formalization (the organization has an office).

Control Variables

In addition to resource variables, we control for organization’s age and tactics. Examining

tactics is important because tactics influence social movement success (Giugni 1998). We

examine two primary social movement strategies in our models: intentionally seeking media

coverage and abstaining from confrontational tactics. The former strategy is directly relevant to

the third model—media recognition—as it depicts a focused strategy in pursuit of that goal. The

effect of the latter strategy on movement success is less clear. Gamson (1990) argued that using

violent, disruptive tactics is positively associated with movement success. Although re-analyses

of his data corroborated this claim, a lot of extant research challenges these findings, revealing

that violent or disruptive tactics sometimes hinder movement success (Snyder and Kelly 1976;

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Taft and Ross 1969). Giugni (1998:379) suggests that this discrepancy is due to the context of

the movement: “Strategies that work in a given context may simply be ineffective in other

political settings and vice versa.” Specifically, many of the successful “unruly” groups in

Gamson’s analysis were labor groups who gained new advantages during a particularly

contentious period of American Labor history (Crist and Edwards 1989).

We also controlled for an SMO’s prior success by including the organization’s reported

impacts in 2004, for each impact measure. The premise of our decision is that it is much harder

to increase the impact from Time 1 to Time 2 if it is already reported as very high in Time 1.

We now turn to the ordered logistic regression results of changes in local issues

awareness, local support, and local media coverage of rural social movement organizations in

Lithuania from 2004 to 2006.

Models

Relying on Resource Mobilization Theory, we examine the role that various resources

have on perceived success for rural SMOs in Lithuania from 2004 to 2006. We test the effects of

the resources delineated above on SMOs’ success in the following areas: increased issue

awareness (Model 1), gaining support from local people (Model 2), and media coverage (Model

3).

The underlying premise of our study is that the importance of each resource is tied to the

type of the impact it predicts. For example, while the sheer number of members may be key to

visibility and hence increased awareness of rural issues, it may not have the same significance

for other types of impacts, such as local support. We also seek to examine whether some types of

resources are more universally instrumental than others. For instance, material resources are

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unique in that an organization can often transform them into other types of resources—human

capital, organizational assets, moral resources, etc. Therefore, we expect material resources,

especially the budget, to be significant predictors across all three types of impacts. But other

resources, such as having an office, may not matter to success in garnering media coverage.

While we advocate for a flexible rather than a “blanket” approach to examining the relationship

between various resources and organizational impacts, we articulate general hypotheses derived

from previous theory and research and use them as a heuristic tool to discover unique

associations between various types of resources and impacts they predict.

Hypotheses

Social movement scholars argue of the importance of human resources to movement

mobilization, impact and success (Edwards and Marullo 1995; Edwards and Kane 2014;

McCarthy and Wolfson 1996; Minkoff 1999. Accordingly, we expect human resources to be

positively associated with an SMO’s success on any of the three outcomes (awareness, support,

and media coverage). We state these expectations formally in the following hypotheses:

H1. The number of members will be positively associated with increased success,

however defined.

H2. The number of dedicated volunteers will be positively associated with increased

success, however defined.

H3. An organization’s ability to mobilize its members for action will predict increased

success, however defined.

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Similarly, in line with extant theory (Edwards and McCarthy 2004; McCarthy and Zald 1987),

we expect material resources to be positively associated with an SMO’s ability to raise

awareness:

H4. An organization’s total annual budget in 2004 will predict its increased success from

2004 to 2006, however defined.

As important as total material resources are to organizational success, research also

shows that having a diverse funding base is associated with organizational success, particularly

for nonprofit organizations (Crittenden 2000). Given the expected importance of both overall

material resources to social movement success, as well as a diverse source of those resources, we

propose the following hypothesis:

H5. An organization’s ability to maintain diversified funds in 2004 will predict its

increased success from 2004 to 2006, however defined.

Next, in line with scholars arguing of the importance of specialization and formalization

to social movement success (Gamson 1990; Minkoff 1999), we expect the following traits to be

associated with increased movement success:

H6. Organizations with a specialized recruitment committee will experience increased

success from 2004 to 2006, however defined.

H7. Organizations with an office will experience increased success from 2004 to 2006,

however defined.

As social network resources have also been argued to benefit SMOs (Edwards and

Marullo 1995; Keck and Sikkink 1998), we hypothesize that an SMO with external ties should

see increased success:

22

H8. Organizations affiliated with broader organizations will experience increased success

from 2004 to 2006, however defined.

Finally, given the positive association between organizational age and increased

likelihood of organizational survival (Hannan and Freeman 1989), we expect younger

organizations to have a more difficult time gaining success over time, compared to older

organizations:

H9. Older organizations will experience increased success from 2004 to 2006, however

defined.

Analyses

Using an original, longitudinal dataset to capture changes over a two-year period (2004-

2006), we examine the applicability of resource mobilization theory to social movement success

among local, rural SMOs in Lithuania, testing the aforementioned hypotheses. We employ

ordered logistic regression to analyze three types of movement success described above over

three models: community support of a SMO (Model 1), public awareness of a SMO’s goals

(Model 2), and media coverage of the SMO’s activities (Model 3). Each of those three outcomes

are based on whether movement success significantly decreased, stayed the same, or increased

over time: -1 indicates a decrease in movement success greater than one Z-score, 0 indicates no

change greater than one Z-score in either direction, and 1 indicates an increase in movement

success greater than one Z-score.

Because each outcome has a different definition of social movement success, we used

extant theory and goodness-of-fit tests to construct final models for each of the three impact

areas of interest. While we tested the effects of every resource for each type of impact, we

23

ultimately employed the models that simultaneously yielded the best goodness-of-fit tests results

while also enabling us to test some of the tenets of resource mobilization theory. We used

multiple imputation to fill in missing data, resulting in a final sample size of 165 organizations.

See Table 1 for summary statistics for each variable and model.

[Insert Table 1 about here].

Model 1: Predictors of Increased Issue Awareness

Table 2 lists the odds ratios for the success in raising awareness of rural issues from 2004

to 2006. We find support for four out of nine hypotheses: Hypotheses 2, 3, 5, and 7. Several

resources have a positive effect on increased issue awareness: the number of dedicated

volunteers providing at least five hours of labor per month to the organization, an organization’s

ability to mobilize people for activities, the ability to maintain diversified funds, and having an

office.

Net of various resource types, every additional dedicated volunteer increases an

organization’s odds of increasing awareness over time by 6 percent, corroborating Hypothesis 2.

Similarly, controlling for other resource types and organizational age, a one-unit increase in a

group’s ability to mobilize people for activities increases the odds of a group’s increased success

in raising issue awareness by 80 percent, relative to organizations that saw no change or a

negative change from 2004 to 2006. This finding supports Hypothesis 3.

Interestingly, the sheer number of members has no significant effect on the increase in

issue awareness, hence, failing to support Hypothesis 1 and suggesting that local SMOs are

better off spending resources on attracting dedicated volunteers rather than simply going after as

many recruits as possible. In terms of material resources, a larger annual budget has no

24

significant effect on raising issue awareness over time, failing to support Hypothesis 4. Ceteris

paribus, a one-unit increase in ability to maintain diversified funds (measured by a 5-point Likert

scale) multiplies a group’s odds of increasing awareness of rural issues by 1.19, which

undergirds Hypothesis 5. Further, organizations that report having an office benefit immensely

compared to those that do not have this type of organizational resource, as having an office

multiplies a group’s odds increasing issue awareness by a factor of thirteen. This finding bolsters

Hypothesis 7. Finally, affiliation with a broader organization has no significant effect on

predicting increased issue awareness, thereby failing to support Hypothesis 8.

In addition to these specific resources, organizations younger than two years of age are

twice as likely to report increased (rather than decreased or unchanged) success in raising

awareness, holding the other variables in the model constant, including an organization’s level of

success at Time 1. This is counter to Hypothesis 9, thereby contradicting extant literature, which

argues that older organizations are more likely to have public legitimacy (Hannan and Freeman

1989), which one would assume translates into see higher levels of increased success. This

finding challenges the “liability of newness” logic, suggesting that, for rural social movement

organizations, younger, more flexible organizations may be more effective in achieving their

goals than more established organizations (Hannan and Freeman 1989). Yet, this result is

consistent with research finding a “liability of adolescence” especially among smaller, less

formalized organizations (Aldrich and Auster 1986). Edwards and Marullo (1995) found that

local movement organizations between the ages of 3-8 years were 10 times more likely to

disband than newly founded or well-established groups. While our data do not allow a test of the

liability of adolescence, it is plausibly argued that small, newly founded groups reliant mainly on

25

volunteer labor enjoy benefits of enthusiasm for a new venture which helps them recruit

members and other resources. Though, once that initial enthusiasm fades, groups seem to

experience difficulty maintaining enthusiasm, quelling disillusionment, and maintaining an

ongoing level of support.

[Insert Table 2 about here]

Model 2: Predictors of Local Support

Table 3 reports the results of the predictors of increased local support over time. The

results support three of the nine hypotheses: Hypotheses 2, 5, and 7. As with Model 1, Model 2

results also reveal that the number of dedicated volunteers is a significant positive predictor of

organizations’ increased local support over time, corroborating Hypothesis 2. Each additional

volunteer who dedicates more than five hours of work per week to a local organization increases

its growth in local support over time by 9 percent. We find no support for other hypotheses

regarding human resources, as neither the total number of members nor the ability to mobilize

people for activities have significant effects on the increase in local support.

Consistent with our findings for the first type of impact, increased awareness, a group’s

ability to maintain a broad array of financial support and having an office are also both

statistically significant predictors of increased local support, which supports Hypotheses 5 and 7.

Net of other factors, a one-unit increment in an SMO’s reported ability to maintain diversified

funds yields a 26-percent rise in the odds of increased local support, compared to decreased

support or no change in support. All other things being equal, having an office multiplies an

organization’s odds of increased local support by a factor of thirteen. Finally, affiliation to a

broader organization also affects the change in local support of organizations over time but in the

26

opposite direction than predicted, failing to support Hypothesis 8: ceteris paribus, a group’s odds

of increased success decline by 34 percent if they are part of a broader organization. Further

research could examine this seemingly counterintuitive finding by investigating whether ties to

outside organizations by local SMOs delegitimizes them in the eyes of the public as no longer

being focused exclusively on local issues. Neither annual budget, nor specialized membership

recruitment committee yield any significant results, providing no support for Hypotheses 4 and

6.

In short, the resources that facilitate a local social movement organization’s ability to

increase local support over time consist of dedicated volunteers (H2), diversified funding (H5),

and a formal office (H7).

[Insert Table 3 about here].

Model 3: Predictors of Local Media Coverage

The final analysis examines change in the ability of small, volunteer led, organizations to

receive media coverage. Several findings stand out. First, no human, material, or organizational

resources bear statistical significance, failing to support all hypotheses except Hypothesis 8. Our

results are inconsistent with Andrews and Caren’s (2010) study of environmental organizations

in North Carolina which found that membership size and size of paid staff positively predicted

media coverage. Yet, our sample consists of volunteer run groups and is directly comparable to

the 42% of their sample with no paid staff and generally much smaller memberships that

garnered relatively little coverage.

27

The relevant factors, in this case, are network ties and tactics, as the following variables

are positively associated with an increase in self-reported local media coverage over time:

affiliation to a broader organization, employing non-confrontational tactics, and having an active

strategy of seeking media coverage. The latter of which we control for especially in this model

given the outcome variable of receiving media coverage and given that past research on social

movements have uncovered movement attempts to coopt the media as an intentional tactic

(Jenkins 1983). Controlling for other resources, groups that are affiliated with broader

organizations are four times more likely to experience increased (rather than decreased or no

change in) media coverage over time, compared to non-affiliated groups. This corroborates

Hypothesis 8.

Taking a non-confrontational stance yields a 68-percent increase in the odds of growth in

media coverage, all other things being equal. This result contradicts Gamson’s (1990) finding

that using unruly tactics is positively related to social movement success. Given the importance

of context to determining the efficacy of using disruptive tactics (Giugni 1998), we find that in

the context of rural, Lithuanian social movements seeking increased media coverage, disruptive

tactics are detrimental. This finding is more in line other studies that found violent or disruptive

tactics can hinder social movement success (Snyder and Kelly 1976; Taft and Ross 1969).

Finally, groups that intentionally pursue media coverage also have an advantage in

increasing media coverage, as compared to those that do not strategically seek it, holding

constant other factors, including the amount of media coverage an SMO received at Time 1.

However, while social movements have a long history of interacting with the media (Gamson

28

and Wolfsfeld 1993), it should be noted that not all media coverage is essentially beneficial to

the SMO (Smith et al 2001).

[Insert Table 4 about here].

Discussion

This research tests some tenets of Resource Mobilization Theory on an understudied

context: success over time by local social movement organizations in Lithuania. Using ordinal

logistic regression analyses on panel data from 165 social movement organizations, we tested

nine hypotheses based on Resource Mobilization Theory across three models, one for each type

of success: increased issue awareness, gaining support from local people, and receiving media

coverage. Overall, our results reveal the importance of context when applying resource

mobilization theory, as some resources mattered for some outcomes but not for others, and some

resources did not matter at all.

In line with basic tenets of Resource Mobilization Theory, we found that some resources

do matter. What consistently matters the most across the first two types of organizational

impacts—increasing issue awareness and gaining local support—is the number of dedicated

volunteers who are willing to devote their time and energy in achieving group’s goals, having a

diverse source of funding, and having a formal office. Simply having large numbers of members

was not enough: those members also needed to actively volunteer their labor for the SMO to

realize success. Similarly, for these two outcomes, simply having a larger annual budget did not

yield significant increase in impacts for the small organizations that we examined, suggesting

that having a cause that has a broader appeal is more likely to achieve success than simply

29

having a well-funded cause bankrolled largely by a few donors. Finally, having formal

organization in the form of an office also positively contributed to these two outcomes. Whether

this positive association with social movement success, however operationalized, is due to the

actual benefits of having an organized space to meet and strategize or rather to gains in perceived

organizational legitimacy in the public eye for simply having an office is unclear. But it is clear

that, for local social movement organizations in Lithuania, at least, having a formal office will

likely lead to an SMO’s increased success over time in increasing awareness and gaining local

support.

The results of the analysis for the third outcome—garnering media coverage—had unique

results. Unlike the other two outcomes, where social network ties were not significantly

associated with movement success over time, affiliation to a broader organization was positively

linked to increased media coverage for local Lithuanian SMOs. In contrast, human resources and

organizational resources, while significant predictors of success in increasing awareness and

support were not significantly related to increased success in receiving coverage by the press.

Instead, of these resources, movement strategies were more applicable to this outcome, with

those organizations eschewing confrontational tactics seeing increased success in obtaining

media coverage. Likewise, and not surprisingly, those SMOs that had a formally stated goal of

obtaining media coverage were also more likely to see an increase in media coverage over time,

reiterating the importance of strategizing—itself a form of organization—to social movement

success.

Overall our findings suggest that the importance of the resources is context dependent—

conditional on the size and scope of the social movement organizations. While the impacts of

30

large organizations with formalized structure may not be able to function without extensive

material and organizational resources, small informal organizations in a transitional society like

Lithuania, at least in their initial stages, are primarily dependent on the enthusiasm and

dedication of their members who are willing to put their time and effort bettering the quality of

community life. It is this reliance on zealous supporters and having broader appeal that primarily

lead to positive outcomes in this context.

However, our results should be considered a stimulus for further research rather than as a

definitive verdict on the role of resources to social movement organization success over time, as

there are some limitations of this study. Although the longitudinal nature of the data enables us

to measure SMO success over time, it is important to emphasize that the survey answers were

self-reported and not externally verified. Although the distribution of self-reported success offers

no indication of invalidity, finding ways to determine the impacts externally would further

increase the validity and reliability of the results. It would also be interesting to compare

objectively recorded achievements of groups and subjective evaluations of impacts made by

group representatives. Such results would be helpful in designing future research and

determining the degree to which subjectively reported impacts mirror the reality. We argue that

more systematic research is needed on small informal SMOs. It would be especially interesting

to see what happens as such organizations age, grow in size, and become more formalized.

31

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Table 1. Means, Standard Deviations, and Imputed Number of Missing Cases of Dependent and

Independent Variables, N = 165

Variable Mean SD Number of

Imputed Cases

Dependent variables

Awareness

Support

Coverage

Independent variables

Number of members

Action mobilization

Prop. affiliated to a broader org.

Annual budget (litas)

Number of dedicated volunteers

Prop. with a recruitment committee

Prop. with an office

Diversified funds

No confrontational tactics

Seeks media coverage

Prop. younger than 2 years

1.98

1.94

1.99

82.99

3.55

0.35

27,932.46

7.75

0.51

0.15

3.63

1.46

1.25

0.55

0.51

0.48

0.48

224.27

0.98

0.48

110,055.9

6.37

0.50

0.36

2.12

1.46

1.25

0.50

0

0

1

0

8

12

41

0

28

35

16

0

5

19

2

3

Table 2. Ordered Logistic Regression Results for Change in Awareness of Rural Issues from 2004

to 2006

Variables Odds Ratios 95% CI

Resources:

HR: Number of members

HR: Number of dedicated volunteers

HR: Action mobilization

SR: Affiliation to a broader organization

MR: Budget

MR: Diversified funds

OR: Membership recruitment committee

OR: Has an office

Controls:

Age (younger than 2 years)

High impacts in 2004

Threshold 1

Threshold 2

Model 𝜒2

Number of Observations

Pseudo R-squared

1.00

1.06†

1.80**

0.61

1.00

1.19†

1.39

13.37***

2.17†

0.13***

-5.84

0.16

84.57

165

0.36

0.999 – 1.002

0.995 – 1.127

1.137 – 2.839

0.255 – 1.482

0.999 – 1.000

0.980 – 1.435

0.608 – 3.169

3.925 – 45.209

0.932 – 5.075

0.072 – 0.235

-8.225 – -3.456

-1.830 – 2.141

Note: †p≤.10, * p≤.05, **p≤.01, *** p≤.001, two-tailed tests, N = 165

4

Table 3. Ordered Logistic Regression Results for Local Support from 2004 to 2006

Variables Odds Ratios 95% CI

Resources:

HR: Number of members

HR: Number of dedicated volunteers

SR: Affiliation to a broader organization

MR: Budget

MR: Diversified funds

OR: Membership recruitment committee

OR: Has an office

Controls:

Age (younger than 2 years)

High impacts in 2004

Threshold 1

Threshold 2

Model 𝜒2

Number of Observations

Pseudo R-squared

1.00

1.09*

0.34†

1.00

1.26*

2.00

13.21***

1.64

0.10***

-8.91

-0.48

101.09

165

0.44

0.999 – 1.003

1.007 – 1.190

0.119 – 0.999

0.999 – 1.000

1.011 – 1.576

0.776 – 5.171

3.091 – 56.490

0.633 – 4.253

0.046 – 0.197

-12.313 – -5.511

-2.814 – 1.854

Note: †p≤.10, * p≤.05, **p≤.01, *** p≤.001, two-tailed tests, N = 165

5

Table 4. Ordered Logistic Regression Results for Local Media Coverage from 2004 to 2006

Variables Odds Ratios 95% CI

Resources:

HR: Number of members

HR: Number of dedicated volunteers

SR: Affiliation to a broader organization

MR: Budget

MR: Diversified funds

OR: Membership recruitment committee

STR: Does not support confrontational

tactics

STR: Seeks media coverage

Controls:

Age (younger than 2 years)

High impacts in 2004

Threshold 1

Threshold 2

Model 𝜒2

Number of Observations

Pseudo R-squared

1.00

1.08

4.30*

1.00

1.08

1.92

1.68*

1.04†

0.52

0.01

-15.86

-4.35

150.68

165

0.65

0.996 – 1.004

0.970 – 1.207

0.117 – 16.532

0.999 – 1.000

0.813 – 1.440

0.299 – 12.357

1.047 – 2.700

0.622 – 1.729

0.152 – 1.814

0.002 – 0.061

-22.524 – -9.197

-8.942 – 0.239

Note: †p≤.10, * p≤.05, **p≤.01, *** p≤.00, two-tailed tests, N = 165

6

7

Table 5. Results’ Summary Table

Note: “+” means statistically significant positive effect; “-” means statistically significant negative effect

Resources

Impacts

Issue

Awareness

Local Support

Media Coverage

Human Resources

Number of members

Number of dedicated volunteers Positve Positve

Action mobilization

Positve

Social Resources

Affiliation to a broader organization

Negative Positve

Material Resources

Budget

Diversified funds Positve Positve

Organizational Resources

Membership recruitment committee

Office Positve Positve

Strategies

Does not support confrontational tactics Positve

Seeks media coverage Negative Negative Positve

Controls Age (younger than 2 years)

Positve

High impacts in 2004 Positve Positve Positve