United States

Department of

Agriculture

Rural

Development

Rural Business–

Cooperative

Service

RBS Research

Report 165

Member Participation in

Agricultural Cooperatives:

A Regression and Scale

Analysis
Abstract This research identifies characteristics that influence member participation in cooperatives. Participation measures include attendance at meetings, serving on committees,

serving as an elected officer, and recruiting other farmers to become members.

Nineteen characteristics were found statistically related to participation, and include

farm characteristics, member demographics, beliefs in cooperative principles, collective action, member influence, cooperative impartiality, and satisfaction with farming

and cooperative officers. 

Keywords: Cooperatives, dairy members, participation.

Member Participation in Agricultural Cooperatives: A Regression 

and Scale Analysis 

Thomas W. Gray, Ph.D.

Charles A. Kraenzle, Ph.D.

Rural Business-Cooperative Service

Research Report 165

December 1998

Price: Domestic $5.00; Foreign $6.00

Acknowledgments

The authors thank Faqir Bagi Singh of USDA’s Economic Research Service for his

technical assistance, and Carolyn Liebrand, RBS, for earlier work on data collection

and processing.
Preface Members may participate in cooperatives in a variety of ways. Some limit their participation to economic patronage while others attend meetings, serve on committees,

serve as elected officers, and/or recruit other members. If member participation is limited to economic patronage, a cooperative is little more than any other business.

Member participation in the governance aspects of the organization gives cooperatives

their distinctive character. Little research has been conducted in this area since the

early 1980s—although the research tradition extends back to the 1940s.

Several major social and economic changes have occurred since the earlier research

was conducted. Numbers of farms have declined continuously, while size in scale of

both farms and cooperatives has increased. An individualist ethic has increasingly

entrenched itself within our culture.

This report analyzes some of the more basic aspects of membership participation and

various characteristics associated with participation. The analysis uses complex techniques—regression analysis and Likert scale analysis. However, great care is taken to

explain these tools as the reader proceeds through the report. The authors use these

techniques to provide valid results that can be relied upon with degrees of statistical

confidence.

i
Contents Highlights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .iii

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

Analytical Approach—Likert Scales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2

Member Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2

Farm Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2

Member Demographics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

Cooperative Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Collective Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Identification With the Cooperative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

Satisfaction Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7

Member Influence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

Equity/Impartiality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

Participation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

Analytical Approach—Regression Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

Regression and Likert Scale Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

Attended Meetings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

Served on Committees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17

Elected to a Cooperative Office . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

Recruited Other Members . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24

Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .29

ii
Highlights This research identifies various characteristics of dairy-farmer members that influence

their participation in a cooperative. Participation measures included attending meetings, serving on committees, serving as an elected officer, and recruiting other farmers

to become members.

Member characteristics included beliefs concerning: cooperative principles, collective

action, individual member identities as associated with cooperative membership, life

satisfaction with farming, member satisfaction with the cooperative operations, and

representation, member influence on cooperative decision making, and equitable treatment among members. Demographic characteristics of members and measures of

farm size and farm type were included.

Regression analysis and Likert scale analysis were applied to 1,156 dairy farmer

respondents from North Central States. All were members of the same cooperative.

Analysis involved only dummy variables, limiting the total variation explained to very

small percentages. However, 19 characteristics were found statistically significant and

related to the four participation measures.

Eight characteristics were found positively related to attendance at meetings. The

greater the measured value of these characteristics, and the more intense the belief,

the more likely a member’s attendance at cooperative meetings. These characteristics

included: 1) Percent of gross farm sales from the sale of milk; 2) Gross farm sales; 3)

Size of milking herd; 4) “I feel I am part owner of the cooperative”; 5) “Ag co-ops

should practice one person, one vote”; 6) “Ag co-ops should support education for their

members and the public”; 7) Satisfaction with “farming as a way of life”; and 8)

Satisfaction with “my district director.”

Three characteristics were found negatively related to attendance at meetings. The

greater the measured value or frequency of these characteristics and/or the more

intense the belief, the less likely member’s attendance at cooperative meetings. These

characteristics included: 1) Spouse’s employment off-farm; 2) “Members have too

much say about how the cooperative is run”; 3) “The cooperative primarily benefits

small farms.”

Five characteristics were found positively related to serving on committees. The

greater the measured value or frequency of these characteristics and/or the more

intense the belief, the more likely a member’s service on committees. These characteristics included: 1) Gross farm sales; 2) More than half the farm labor is hired; 3) “Ag

co-ops should work with other ag co-ops”; 4) “Members receive benefits from doing

business the cooperative way”; and 5) Satisfaction with “my cooperative board of directors.”

Six characteristics were found positively related to service in an elected office. The

greater the measured value of these characteristics, and the more intense the belief,

the more likely a member’s service in an elected office. These characteristics included:

1) Gross farm sales; 2) Size of milking herd; 3) “Ag co-ops should practice one-person,

one-vote”; 4) “Ag co-ops should work with other ag co-ops”; 5) “I feel I am part owner

of the cooperative”; and 6) Satisfaction with “my board of directors.”

One characteristic was found negatively related to service in an elected office. The

more intensely members agreed that “an individual farmer can usually make better

iii
Highlights marketing decisions than a group of farmers or some agency,” the less likely those

members served as elected cooperative officers.

Two characteristics were positively related to recruitment of other farmers to the cooperative. The greater the measured value of these characteristics and the more intense

the belief, the more likely a member recruited others to join the cooperative. These

characteristics included:

1) Size of milking herd; and 2) “Belonging to the cooperative is an important part of my

identity as a farmer.”

One characteristic was found negatively related to recruitment of others. The more

intensely members agreed that “the cooperative primarily benefits large farms,” the

less likely they were to recruit others.

Two variables were significantly related to participation measures in a non-linear fashion—”the cooperative primarily benefits large farms” and “members have too little say

about how the co-op is run.”

A size bias was found in these analyses. Farmers from larger farm units were more

involved. Farmers from smaller units were less satisfied and had less time available to

participate. Also revealed was the importance that participation plays in validating or

developing farmer understanding and appreciation of cooperative organization.

Cooperatives may seek to improve the responsiveness of their organizations by being

sensitive to and making accommodations for greater involvement of farmers from

smaller units.

Given greater involvement, the cooperative and members may begin to identify ways of

improving the satisfaction of these farmers and strengthening the cooperative itself.

Study results suggest emphasizing cooperative principles, the benefits of cooperation,

and the importance of participation as a possible place to start.

The results also demonstrate the relevance and continuing importance of cooperative

principles, beliefs in collective action, and member identification with cooperative organization and action.

iv
Member Participation in Agricultural

Cooperatives: A Regression and Scale

Analysis

Thomas W. Gray, Ph.D. and Charles A. Kraenzle, Ph.D.

Rural Business-Cooperative Service (RBS)

Introduction

Members can participate in cooperatives in different ways. Some limit participation to economic

patronage while others may attend meetings, serve on

committees, serve as elected officers, and/or recruit

other members. There is no cooperative without member participation. If limited to economic patronage, a

cooperative is little more than any other business.

Member participation in governance gives cooperatives their distinctive character.

This report focuses on four levels of member

involvement in a cooperative—attending meetings,

serving on committees, serving as an elected officer,

and recruiting other farmers to become members. This

is the first study in the United States to examine cooperative participation since the early l980s (Lasley

l982)—although the research tradition extended back

to the l940s (Anderson and Sanderson l943). Several

major social and economic changes have occurred

since then. Farm numbers have declined continuously,

size in terms of both farms and cooperatives has

increased, and an individualist ethic has increasingly

entrenched itself within our culture (Hakelius l996;

Albrecht l993; Albrecht and Murdock l990; Ford l978;

Brown et al. l993; Lasley et al. l995, RBS l995, Mooney

l988).

This report analyzes some of the more basic

aspects of cooperative membership, i.e., attendance at

meetings, serving on committees, holding office, and

recruitment. The authors seek to understand what

characteristics of members are associated with these

forms of participation. Ultimately, the goal is to provide information that will encourage and increase

member participation in the cooperative.

The characteristics examined include member

beliefs concerning: 1) cooperative principles, 2) collective action, 3) individual member identities associated

with cooperative membership, 4) life satisfaction with

farming, 5) member satisfaction with the cooperative

operations and representation, 6) member influence on

cooperative decision making, and 7) equitable treatment among members.

Also considered were various demographic characteristics of members, as well as measures of farm

size and farm type. Relationships between most of

these variables and participation has been documented

in earlier work by Warner 1971, Rogers 1971,

Heffernan 1967, Torgerson 1972, Copp 1964, Morrison

1971, Havens 1968, and others.

This study 1) describes various characteristics of

members, including their participation behaviors, 2)

identifies member characteristics statistically related to

differences in observed participation behaviors, and 3)

draws implications from the results for cooperatives.

The study, examines the responses to a mail survey of more than 2,000 farmer-members of the same

Midwest dairy cooperative. A total of 1,156 usable

questionnaires were returned for a response rate of 53

percent. Responses came from farmers residing in four

North Central States.1,2

1

1 Extensive and detailed information on membership characteristics

and survey responses will be provided in this study. However, care

is taken not to identify geographic locality and size of the

membership to such a degree that confidentiality of the cooperative

organization is compromised.

2 The specific cooperative was identified in several survey questions.

For reporting purposes here, specific names have been replaced

with the words “my cooperative” or “the cooperative.”
Analytical Approach—Likert Scales

Several member characteristics were measured

using Likert scales—tools to determine degrees of

belief in specific thoughts, ideas, and/or attitudes

(Rubin and Babbie l995). The beliefs in cooperative

principles, collective action, equitable treatment

among members, cooperative identity, and satisfaction

with farming and with the cooperative were assessed.

Respondents were presented with a series of choices

ranging from “strongly disagree” or “very dissatisfied” to “strongly agree” or “very satisfied.” The percentage of members responding to each choice was calculated, determining the average intensity measure for

each effect and/or belief.

Member Characteristics

Farm Characteristics

The type of farm unit was assessed with several

different measures. Dairy predominance was measured by assessing the percent of gross farm sales

attributable to dairy. Farm size was measured by

assessing gross farm sales, total acres in operation, and

size of the milking herd. Tenure was measured by

assessing the percentage of acreage owned by the principal operator. Debt load was assessed by estimating

the net worth that would remain if all farm assets were

sold. Labor provision on the farm was measured by

assessing whether more than half of the farm labor

was hired.

Farm Type, Dairy: Most respondents were dairy

farmers (table 1). About 84 percent reported dairy sales

made up more than half of their gross farm sales.

Nearly 39 percent were from units where dairy sales

made up 75-89 percent of gross farm sales. Nearly 27

percent reported dairy sales in the 50-74 percent of

range. More than 18 percent had sales in the 90-100

percent range. Just l6.3 percent reported dairy sales

made up less than half of the gross farm sales.

Size, Acres: Only 2.2 percent had farms of greater

than 1,000 acres (table 2). Most (83.5 percent) were less

than 500 acres. About 60 percent were in the 180-499

acre category. Less than 2 percent had less than 50

acres.

Size of Milking Herd: About 92 percent had

milking herds of less than 100 cows (table 3). None had

herds of more than 500 cows. Less than 9 percent had

herds in the 100-499 range. About 44 percent milked

herds of less than 50 cows, with an additional 47.8 percent milking between 50 and 100 cows.

Size, Gross Farm Sales: Nearly 41 percent reported gross farm sales in the $100,000-$249,999 range

(table 4). An additional 26.9 percent were in the

$50,000-$99,999 range. These two categories accounted

for most respondents. Nearly 12 percent had gross

2

Table 1— Gross farm sales from dairy

Gross farm sales Farms

Percent Number

1 - 49 180

50 - 74 294

75 - 89 428

90 - 100 200 ———

Total 1,102

Percent 

1 - 49 16.3

50 - 74 26.7

75 - 89 38.8

90 - 100 18.1 ———

Total 2 100.0

1 Based on the number responding to each item.

2 Total may not add due to rounding.

Table 2— Acres in farming operation

Acres Farms

Number Number

Less than 50 21

50 - 179 250

180 - 499 665

500 - 999 160

1,000 and more 25 ———

Total 1,121

Number Percent 1

Less than 50 1.9

50 - 179 22.3

180 - 499 59.3

500 - 999 14.3

1,000 and more 2.2 ———

Total 100.0

1 Based on the number responding to each item.
farm sales of $250,000 or more. Less than 19 percent

reported gross farm sales in the $10,000-$50,000 range.

Only 2.1 percent had sales of less than $10,000.

Tenure, Ownership of Acreage: Table 5 presents

data on percentages of respondents reporting levels of

ownership of acreage in the farming operation. Nearly

45 percent indicated they owned 90-100 percent of the

acreage farmed. An additional 24 percent said they

owned 50-89 percent of the acreage. Nearly 12 percent

owned 1-49 percent. Nearly 20 percent owned none of

the land they farmed.

Labor Provision: More than 90 percent said that

less than half of the physical labor on the farm was

hired, meaning most of the labor came from the principal operators and their respective families (table 6).

Debt Load: Respondents were asked about the

value of their farm unit that would remain if all farm

3

Table 3— Size of milking herd

Milk cows Farms

Number

Less then 50 491

50 - 99 537

100 - 499 95

More than 500 - ———

Total 1,123

Percent1

Less then 50 43.7

50 - 99 47.8

100 - 499 8.5

More than 500 - ———

Total 100.0

1 Based on the number responding to each item.

Table 4— Size of farm by gross sales

Gross farm sales Farms

Dollars Number

Less than 10,000 23

10,000 - 29,999 90

30,000 - 49,999 111

50,000 - 99,999 291

100,000 - 249,999 440

250,000 or more 128 ———

Total 1,083

Dollars Percent1

Less than 10,000 2.1

10,000 - 29,999 8.3

30,000 - 49,999 10.2

50,000 - 99,999 26.9

100,000 - 249,999 40.6

250,000 or more 11.8 ———

Total 100.0

1 Based on the number responding to each item.

Table 5— Acreage owned by members 1

Acres Members

Percent Number

None 216

1 - 49 132

50 - 89 274

90 - 100 499 ———

Total 1,121

Percent Percent

None 19.3

1 - 49 11.8

50 - 89 24.4

90 - 100 44.5 ———

Total 100.0

1 Based on the number responding to each item.

Table 6— Farms where more than half of physical 

labor is hired

Response Farms

Number

No 1,011

Yes 111 ———

Total 1,122

Percent1

No 90.1

Yes 9.9 ———

Total 100.0

1 Based on the number responding to each item.
assets were sold and if all debts were paid (table 7).

More than 30 percent said they would have up to 50

percent of the value of the assets remaining. This was

the largest size category. An additional 26.4 percent

said they would have 50-74 percent of their assets.

Percentages become progressively smaller beyond

these two ranges. Slightly less than 18 percent would

be debt free. About 5 percent would have no assets.

Debts would exceed assets.

Summary: A profile of an average member in this

study i.e., one where more than half of the members

had similar characteristics, would be a farmer milking

less than 100 cows on a farm between 180 and 500

acres. Most of the acreage farmed would be owned.

This farmer would generate gross farm sales in the

$50,000-$250,000 range. Most within this range would

be in the $100,000-$250,000 range. Little hired labor

would be used. If all farm assets were sold, this member would have 50 percent or more of the value of total

assets remaining.

Member Demographics

Various measures were made of such member

demographics characteristics as age, educational

attainment, and off-farm employment (tables 8-11).

Age: The largest grouping of members fell in the

middle-aged category (table 8). Nearly 38 percent of

4

Table 7— Member’s net worth after sale of farm assets

Net worth Members

Percent Number

None, debts exceed assets 52

1 - 49 324

50 - 74 282

75 - 99 221

100 percent debt free 190 ———

Total 1,069

Percent1

None, debts exceed assets 4.9

1 - 49 30.3

50 - 74 26.4

75 - 99 20.7

100 percent debt free 17.8 ———

Total 100.0

1 Based on the number responding to each item.

Table 8— Age of members

Age Members

Number

Less than 35 years 251

35 - 50 426

51 - 65 329

More than 65 120 ———

Total 1,126

Percent 1

Less than 35 years 22.3

35 - 50 37.8

51 - 65 29.2

More than 65 10.7 ———

Total 100.0

1 Based on the number responding to each item.

Table 9— Education received by members

Education Members

Number

Did not complete high school 186

Completed high school 650

Some college 196

Received bachelor’s degree 70

Received master’s degree 5

Received doctorate 6 ———

Total 1,113

Percent 1

Did not complete high school 16.7

Completed high school 58.4

Some college 17.6

Received bachelor’s degree 6.3

Received master’s degree 0.4

Received doctorate 0.5 ———

Total 100.0

1 Based on the number responding to each item.
the respondents were aged 35-50, 30 percent 51-65,

nearly 11 percent older than 65, and 22 percent less

than 35 years of age.

Education: Table 9 indicates that 58 percent of

these farmer-members were high school graduates.

About 18 percent had some college education, 17 percent had not finished high school, and 7 percent were

college graduates.

Off-farm employment: The farm enterprise was

the primary source of employment for nearly 90 percent of the principal operators. Only 10 percent had

off-farm employment. Spouses of the principal operators were employed at higher rates. About one-third

had off-farm employment (table 10-11). About 58 percent reported spouses did not work off the farm.

Nearly 10 percent had no spouse.

Summary: Demographically, the average member

in this study had a high school diploma, was between

the ages of 35 and 65, and, within this age range, was

more likely to be 35-50. Neither the member, nor his or

her spouse, would likely hold an off-farm job.

Cooperative Principles

Member beliefs in cooperative principles were

assessed by using these statements: 1) “Ag co-ops

should accept any farmer who wants to join”; 2) “Ag

co-ops should practice one-person, one-vote”; 3)

“Members should receive patronage dividends in proportion to patronage”; 4) “Ag co-ops should support

education for members and the public”; 5) “Ag co-ops

should work with other ag co-ops.”

The beliefs listed in table 12 suggest that respondents strongly supported most cooperative principles.

With the exception of the “open membership” principle, at least 72 percent of the members agreed or

strongly agreed with each of the items. The “open

membership” principle was somewhat more contested.

About 40 percent of the members either agreed or

strongly agreed, or disagreed or strongly disagreed.

About 19 percent were unsure. With surpluses and

quality of milk issues ever present in dairy production,

these members may be quite ambivalent about accepting “any farmer” with milk to sell.

Summary: Average members in this study agreed

with most cooperative principles, although some

might express some ambivalence about “open membership.” 

Collective Action

Collective action refers to initiatives taken by an

identifiable group to realize their common interests.

Several items were used to assess member beliefs

about collective action (table 13): 1) “Farmers must

stick together in order to get things done even if they

have to give up some of their individual freedom”; 2)

“A basic cause of agricultural problems today is that

too many farmers want to go their separate and individual ways without regard for other farmers or some

agency”; 3) “An individual farmer can usually make

better marketing decisions than a group of farmers or

some agency”; 4) “Members receive benefits from

doing business the cooperative way”; 5) “It is only

through ag co-ops that farmers can assume an appro5

Table 10— Principal operator with occupation or

employment other than farming

Response Principal operator

Number

No 1,002

Yes 114 ———

Total 1,116

Percent 1

No 89.8

Yes 10.2 ———

Total 100.0

1 Based on the number responding to each item.

Table 11— Spouse has an occupation or employment

other than farming

Response Members

Number

No 647

Yes 361

No spouse 106 ———

Total 1,114

Percent 1

No 58.1

Yes 32.4

No spouse 9.5 ———

Total 100.0

1 Based on the number responding to each item.
priate role in the marketplace”; and 6) “Members of ag

co-ops have a competitive advantage in the marketplace.” 

In spite of research by Hakelius (1996) documenting the emergence of a predominant individualist orientation among farmers in Sweden, results in table 13

suggest many of the dairy farmers in this study favor

collective action. Nearly 60 percent preferred a collective or cooperative approach over an individualist one

for four of the six beliefs. Seventy-five percent agreed

or strongly agreed that the “members receive benefits

from doing business the cooperative way.” More than

64 percent agreed or strongly agreed that farmers must

stick together, even if it means giving up some individual freedoms. Nearly 63 percent rejected or disagreed

with the view that “An individual farmer can usually

make better marketing decisions than a group of farmers or some agency.” 

The most problematic item perhaps was also the

most extreme one: “It is only through ag co-ops that

farmers can assume an appropriate role in the marketplace.” Many independent-minded farmers may object

to the use of the word “only.” More than 31 percent

were unsure, although nearly 46 percent agreed or

strongly agreed with the statement.

Summary: Average members tended to agree

more with collective action beliefs than individualist

ones did. However, these members are not so collective-action minded as to see cooperatives as the sole

and exclusive choice for action.

Identification With the Cooperative

Identification refers to the degree of attachment a

member has toward the organization. Three different

measures were made: 1) “I feel I am part owner of the

cooperative”; 2) “Belonging to the cooperative is an

important part of my identity as a farmer”; and 3)

“The cooperative is my agent in the marketplace.”

About 60 percent agreed or strongly agreed with these

statements (table 14). Nearly 75 percent agreed or

strongly agreed that they felt like “part owners” of the

cooperative. Almost 85 percent agreed or strongly

agreed that they understood the cooperative was their

agent in the marketplace. More than half (51 percent)

strongly disagreed or disagreed that “the cooperative

is just another place to do business.”

6

Table 12— Members’ beliefs in cooperative principles

Strongly Strongly Weighted

Belief disagree Disagree Unsure Agree agree Total score

Number/Percent

Agricultural cooperatives should accept any

farmer who wants to join 60 395 205 387 59 1,106 2.99

5.4 35.7 18.5 35.0 5.3 100.0

Agricultural cooperatives should practice 

one-member, one-vote 9 48 158 711 185 1,111 3.91

0.8 4.3 14.2 64.0 16.7 100.0

Members should receive patronage dividends 

in proportion to patronage 5 25 148 741 191 1,110 3.98

0.5 2.3 13.3 66.8 17.2 100.0

Agricultural cooperatives should support 

education of members and the public 21 65 221 675 124 1,106 3.74

1.9 5.9 20.0 61.0 11.2 100.0

Agricultural cooperatives should work with 

other agricultural cooperatives 11 50 201 701 144 1,107 3.83

1.0 4.5 18.2 63.3 13.0 100.0

Every dairy farmer should have a choice of 

more than one place to sell their milk 3 29 123 732 222 1,109 4.03

0.3 2.6 11.1 66.0 20.0 100.0
Summary: Members on average identify with the

cooperative, take a personal interest in it, and don’t see

it as “just another business.” 

Satisfaction Levels

Three measures were used to assess farmer-members’ satisfaction with the social and economic context

within which they lived. Members were asked to specify to what degree they were satisfied or dissatisfied

with: 1) “dairy farming as a way of life”; 2) “dairy

farming as a way to make a living”; and 3) “the income

my family makes from dairy farming.”

Nearly 74 percent said they were satisfied or very

satisfied with dairy farming as a way of life. As statements narrowed, satisfaction levels declined. Fiftyseven percent were satisfied or very satisfied with

“dairy farming as a way to make a living.” However,

only 36 percent said they were satisfied or very satisfied with “the income their family makes from dairy

farming.” More than half were dissatisfied or very dissatisfied with the income from dairy farming, and 9.3

percent were very dissatisfied with the “income”

earned (table 15).

Members were also asked about their satisfaction

levels with member representatives, management, and

their cooperative overall (table 16). About 73 percent

were satisfied or very satisfied with their district and

board representatives and management. About 87 percent were satisfied or very satisfied with their cooperative overall.

About 19 percent of these members, however,

expressed some ambivalence with their district and

board representatives and cooperative management.

Summary: The average member was satisfied

with farming as a way of life and dairy farming as a

way to make a living, but dissatisfied with the income

made from dairy farming. In terms of transactions

with the cooperative, members were basically satisfied

7

Table 13— Members' beliefs in collective action

Strongly Strongly Weighted

Belief disagree Disagree Unsure Agree agree Total score

Number/Percent

Farmers must stick together in order to get 

things done even if they have to give up 

some of their individual freedom 34 148 214 580 137 1,113 3.57

3.1 13.3 19.2 52.1 12.3 100.0

A basic cause of agricultural problems today

is that too many farmers want to go their 

separate and individual ways 

without regard for other farmers 55 233 243 450 129 1,110 3.33

5.0 21.0 21.9 40.5 11.6 100.0

An individual farmer can usually make 

better marketing decisions than a group 

of farmers or some agency 125 572 273 118 22 1,110 2.41

11.3 51.5 24.6 10.6 2.0 100.0

Members receive benefits from doing 

business the cooperative way 10 38 229 747 86 1,110 3.78

0.9 3.4 20.6 67.3 7.7 100.0

It is only through agricultural cooperatives that 

farmers can assume an appropriate role in the 

marketplace 36 220 346 438 67 1,107 3.25

3.3 19.9 31.3 39.6 6.1 100.0

Members of agricultural cooperatives have a 

competitive advantage in the marketplace 22 92 333 588 72 1,107 3.54

2.0 8.3 30.1 53.1 6.5 100.0
8

Table 15— Member satisfaction levels with farming and their cooperative

Response

——————————————————————————————————

Item Very Very

dissatisfied Dissatisfied Unsure Satisfied satisfied Total

Number

Dairy farming as a way of life 17 139 140 669 155 1,120

Dairy farming as a way to make a living 57 216 208 537 102 1,120

The income my family makes from dairy farming 103 455 152 367 34 1,111

Percent 1

Dairy farming as a way of life 1.5 12.4 12.5 59.7 13.8 100.0

Dairy farming as a way to make a living 5.1 19.3 18.6 47.9 9.1 100.0

The income my family makes from dairy farming 9.3 41.0 13.7 33.0 3.1 100.0

1 Based on the number responding to each item.

Table 14— Members' identification with the cooperative

Response

——————————————————————————————————

Item Strongly Strongly

Disagree Disagree Unsure Agree Agree Total

Number

I feel I am part-owner of the cooperative 32 122 129 714 127 1,124

Belonging to the cooperative is an important part 

of my identity as a farmer 35 206 208 571 103 1,123

The cooperative is just another place to do business 52 518 116 401 31 1,118

The cooperative is my agent in the marketplace 13 39 120 820 127 1,119

Percent 1

I feel I am part-owner of the cooperative 2.8 10.9 11.5 63.5 11.3 100.0

Belonging to the cooperative is an important part 

of my identity as a farmer 3.1 18.3 18.5 50.8 9.2 100.0

The cooperative is just another place to do business 4.7 46.3 10.4 35.9 2.8 100.0

The cooperative is my agent in the marketplace 1.2 3.5 10.7 73.3 11.3 100.0

1 Based on the number responding to each item.
made from dairy farming. In terms of transactions

with the cooperative, members were basically satisfied

with district and board representatives and managers.

Member Influence

Cooperatives are organized around principles

which seek to provide member influence and control.

Member beliefs about their own influence, and members’ influence generally, were assessed with three

items: 1) “Cooperative members have a great amount

of influence on how the cooperative is run”; 2)

“Cooperative members have too much say about how

the cooperative is run”; and 3) “I am satisfied with the

amount of influence I have on how the cooperative is

run.” Fifty percent of the members agreed or strongly

agreed that cooperative members have a “great

amount of influence” on how the cooperative is run.

Nearly 80 percent disagreed or strongly disagreed that

members have too much say. When queried about

individual member influence, nearly 57 percent agreed

or strongly agreed that they were satisfied with the

amount of their influence on how the cooperative is

run (table 17).

Summary: A profile of the average member

would find a farmer who was satisfied with the

amount of influence he or she personally has on the

cooperative, who would believe that members in general have considerable influence on how the cooperative is run, and who would disagree that members

have too much say.

Equity/Impartiality

Fundamental to these organizations are concepts

of equity or understandings of the cooperative as

impartial in determining its use, function, and the benefits received. Three items were used in assessing

member beliefs about equity: 1) “The cooperative primarily benefits large farms”; 2) “The cooperative primarily benefits small farms”; and 3) “The cooperative

benefits Grade A producers more than Grade B producers.”

Results showed members were unsure about

these equity issues. Nearly 39 percent said they were

unsure whether the cooperative benefits Grade A more

than Grade B producers. Nearly 29 percent agreed or

strongly agreed that Grade A producers receive an

advantage, although about the same number disagreed

or strongly disagreed that one class of producer had an

advantage over the other (table 18).

In terms of possible advantages attributable to

size of farm, most respondents felt it was fairly clear.

Small farms were not the prime beneficiaries of the

9

Table 16— Member satisfaction with their cooperative

Response

——————————————————————————————————

Item Very Very

dissatisfied Dissatisfied Unsure Satisfied satisfied Total

Number

Satisfied with my cooperative over-all 15 43 83 781 201 1,123 

Satisfied with my district director 25 42 230 659 162 1,118 

Satisfied with the board of directors 16 40 239 685 141 1,121 

Satisfied with the cooperative's management 27 59 216 642 174 1,118 

Percent 1

Satisfied with my cooperative over-all 1.3 3.8 7.4 69.5 17.9 100.0

Satisfied with my district director 2.2 3.8 20.6 58.9 14.5 100.0

Satisfied with the board of directors 1.4 3.6 21.3 61.1 12.6 100.0

Satisfied with the cooperative's management 2.4 5.3 19.3 57.4 15.6 100.0

1 Based on the number responding to each item.
10

Table 18— Member beliefs on equity issues

Response

——————————————————————————————————

Belief Strongly Strongly

disagree Disagree Unsure Agree agree Total

Number

The cooperative primarily benefits large farms 61 401 350 216 76 1,104 

The cooperative primarily benefits small farms 129 552 379 39 9 1,108 

The cooperative benefits Grade A more than 

Grade B producers 45 311 434 263 58 1,111 

Percent 1

The cooperative primarily benefits large farms 5.5 36.3 31.7 19.6 6.9 100.0

The cooperative primarily benefits small farms 11.6 49.8 34.2 3.5 0.8 100.0

The cooperative benefits Grade A more than 

Grade B producers 4.1 28.0 39.1 23.7 5.2 100.0

1 Based on the number responding to each item.

Table 17— Member beliefs on the amount of influence on the cooperative 

Response

——————————————————————————————————

Item Strongly Strongly

disagree Disagree Unsure Agree agree Total

Number

Have a great amount of influence on how the 

cooperative is run 56 230 274 517 42 1,119

Have too much say about how the cooperative is run 151 741 201 16 9 1,118

Have too little say about how the cooperative is run 36 405 379 220 74 1,114

Satisfied with the amount of influence I have on how 

the cooperative is run 63 173 249 587 45 1,117

Percent 1

Have a great amount of influence on how the 

cooperative is run 5.0 20.6 24.5 46.2 3.8 100.0

Have too much to say about how the cooperative is run 13.5 66.3 18.0 1.4 0.8 100.0

Have too little say about how the cooperative is run 3.2 36.4 34.0 19.7 6.6 100.0

Satisfied with the amount of influence I have on how 

the cooperative is run 5.6 15.5 22.3 52.6 4.0 100.0

1 Based on the number responding to each item.
cooperative—only 4 percent agreed or strongly agreed

that they were. More than 61 percent did not believe

that small farms were the prime beneficiaries. The

remaining 34 percent were unsure.

When the question was asked in the reverse, 42

percent disagreed that large farms were the prime beneficiaries, 27 percent said they were, and 31 percent

were unsure.

Summary: The average responses for these equity questions were the most problematic of all the categories.

Participation

Four measures were made of member participation in the cooperative. Three were assessments of participation in member governance and one of loyalty

and commitment, i.e., recruitment of other members

(table 19).

More than 58 percent said they had attended

cooperative meetings in the past year—the most

involvement of the four measures. Nearly 18 percent

had served as an elected officer, another 11.8 percent

had served on a non-elective committee. Nearly 20

percent attempted to recruit other farmers as members,

though it needs noting that less than one-half of all

members responded to this question.

Summary: The average member attends meetings, but is much less likely to serve as an elected officer or on a committee, or to recruit other members.

Summary

The average member milked less than 100 cows,

farmed between 180 and 500 acres with less than 10

percent of it rented, produced gross farm sales ranging

from $50,000 to $250,000 and more likely in the

$100,000-$250,000 range, and hired little labor for the

operation. If all farm assets were sold on this farm, the

average member would be able to retain 50 percent or

more of the value of those assets.

Demographically, this member had a high school

diploma and was between the ages of 35 and 65, and

more likely was 35-50. On average, members or their

spouses did not hold off-farm jobs.

Most members believed in cooperative principles

although they were ambivalent about “open membership.” The average believed in collective action, but

not to the extent that they saw cooperatives as the sole

and exclusive choice for social action. In terms of identity, the average member felt attached to the cooperative and saw it as more than “just another business.” 

The average member was: satisfied with farming

as a way of life, dairy farming as a way to make a living, unhappy with the income it generated, basically

satisfied with district and board representatives and

managers, satisfied with the amount of influence he or

she personally had on the cooperative, believed that

members in general had considerable influence on

how the cooperative was run, and disagreed that

members have too much say. The average member—

with degrees of unsureness—did not see either large or

small farmers or Grade A or Grade B producers as

prime beneficiaries of the cooperative.

Concerning participation, this member attended

meetings, but was less likely to serve on committees,

serve in an elected office, or help recruit other members.

Analytical Approach—Regression 

Analysis

The major interest in this study is to understand

how characteristics of members are related to various

participation measures, i.e., attending meetings, serving on committees, serving as an elected officer, and

recruiting other members.

For example, how do members’ perceptions of

equity-fairness issues affect how they participate? Are

their feelings about cooperative principles related to

participation? Do members who believe in collective

11

Table 19— Member participation in the cooperative

Item No Yes Total

Number

Attended meetings 468 656 1,124

Served on committees 988 132 1,120

Elected to office 919 199 1,118

Recruited other farmers 

as members 348 82 430

Percent1

Attended meetings 41.6 58.4 100.0

Served on committees 88.2 11.8 100.0

Elected to office 82.2 17.8 100.0

Recruited other farmers as 

members 80.9 19.1 100.0

1 Based on the number responding to each item.
action participate more or less than those who do not?

Does the size of a member’s farm unit affect how he or

she participates? 

Regression Analysis: This is a powerful statistical method for sorting out influences among variables.

It allows the user to identify how several variables

simultaneously influence the value of another variable.

These influences can be assessed with statistically

computed degrees of confidence, i.e., whether the

results are due to some random occurrence or if the

observed influences occur in a systematic, non-random

fashion. Regression analysis as used here assesses how

various member characteristics influence the participation activities.

Regression Coefficients: One can understand

how variables are related to each other by examining

computed regression coefficients. These calculated

measures assess the strength and direction of association between variables. A positive coefficient between

two variables indicates they change congruently in the

same direction. A negative coefficient implies the

reverse—variables change in opposite directions, i.e.,

as one gets larger, its complement gets smaller.

The size of a regression coefficient indicates the

relative strength of a relationship between two variables. The absolute size of a standardized regression

coefficient always varies between 0.0 and 1.0. The larger the absolute size of the number, the stronger the

relationship.

Given the objectives of this report to understand

how member characteristics are related to participation, a value can be calculated, for example, on how a

member’s age, belief in principles and collective

action, and size of farm unit may all affect participation behaviors. This technique can measure the relationship between participation and the other variables,

with varying degrees of confidence, i.e., what we

observe happening between variables is due to some

systematic relationship and not just chance. 3

Likert Scales: Many member characteristics were

measured with these scales. There were five choices

along a range—from strongly disagree or very dissatisfied to strongly agree or very satisfied. These choices

are scored “1” (strongly disagree or very dissatisfied)

to “5” (strongly agree or very satisfied). The higher the

number, the stronger the agreement or level of satisfaction.

Scale scores are calculated for each belief item to

supplement interpretations and to cross-validate the

regression results. They are a check on the regression

results. When scale scores are incongruent with the

regression results, the regression coefficients likely

represent non-linear relationships with the participation measures. The variables may vary together, but in

a curvilinear fashion, sometimes increasing and/or

decreasing and then reversing themselves. The scale

scores identify these variables. Their interpretation is

more ambiguous and will not be interpreted here.

Regression Equations: These techniques are used

to show how various member characteristics are related to four measures of participation, i.e., attendance at

meetings, serving on committees, serving as an elected

officer, and recruiting other members. These objectives

can be specified in an equation format: participation is

understood as a function of, or associated with farm

type, farm tenure, labor provision, debt load, member

demographics, and beliefs about cooperative principles, collective action, equitable treatment, member

identity, member influence, and life and cooperative

satisfaction. Stated more formally in functional equation format: 

1 “Attending meetings” is a function of (demographics, farm type, tenure, labor, debt, cooperative principles, collective action, equity, member identity,

member influence, and life satisfaction.)

2 “Farmers serving on committees” is a function of

(demographics, farm type, tenure, labor, debt, cooperative principles, collective action, equity, member

identity, member influence, and life satisfaction.)

12

3 Readers uninitiated in regression analysis need only know a few

things to understand regression coefficients. Coefficients measure

relationships between things called variables. For example, the

daily temperature is a variable. The cloudiness of the sky is

variable. A standardized regression coefficient can only vary

between 0.0 and l.0. The larger the absolute size of the regression

coefficient, the stronger the relationship between the two

variables. If the coefficient between the amount of change in the

daily temperature, for example, and the amount of change in cloud

cover is [0.7], this suggests there is a fairly strong relationship

between changes in the daily temperature and the degree of clouds

in the sky.

Regression coefficients have a positive or negative sign.

Positive signs imply that when two variables change together, they

change in the same direction. Negative signs imply they vary or

change in opposite directions. For example, if the regression

coefficients between changes in the daily temperature and the

amount of cloud cover in the above example was found to be -0.8,

we would know that as larger proportions of the sky are overcast,

daily temperatures would be lower—i.e., more clouds, lower

temperatures.

A third variable might be the probability of rain. If a

regression coefficient +0.75 was found between cloud cover and

the probability of rain, this number suggests there is a strong

positive relationship between cloud cover and rain—i.e., the more

cloud cover, the greater the likelihood of rain.
3. “Farmers elected to office” is a function of (demographics, farm type, tenure, labor, debt, cooperative

principles, collective action, equity, member identity, member influence, and life satisfaction.)

4. “Farmers recruiting other farmers” is a function of

(demographics, farm type, tenure, labor, debt, cooperative principles, collective action, equity, member

identity, member influence, and life satisfaction.)

Regression and Likert Scale Analyses

The results of the four regression analyses are

shown in tables 20-23. Only statistically significant

variables are presented. These measures indicate

whether variables are related to each other by chance

or are systematic and non-random relationships.

Several variables were statistically related to four participation measures i.e., attending meetings, serving on

committees, serving on the board of directors, and

recruiting other members.

Regression analyses convey how variables

change and move together, either in the same or opposite direction. Regression coefficients summarize the

intensity and direction of these movements. Likert

scales measure the intensity of beliefs and attitudes.

They represent the average degree of belief members

hold collectively.

Attended Meetings

Thirteen variables were statistically related to

attending meetings and included the following characteristics and measures: farm type (percent gross farm

sales from the sale of milk); farm size (gross farm sales

and size of milking herd); demographics (does the

spouse hold an off-farm job); cooperative identification

(“I feel I am part owner of the cooperative”); cooperative principles (“Ag co-ops should practice one-person, one-vote” and “Ag co-ops should support education for members and the public”); two satisfaction

variables (“ with dairy farming as a way of life” and

“with the district director”); two comparative equity

variables (“the cooperative primarily benefits small

farms” and “the cooperative primarily benefits large

farms”); influence (“Members have too much say

about how the cooperative is run”), and collective

action (“Members receive benefits from doing business

the cooperative way”) (table 20).

Farm Type, Dairy: The farm type variable, “percent of gross farm sales from milk sales,” was found

statistically significant and positively related to attendance at meetings. Table 20 shows a regression coefficient of 0.06740 for this variable. The more farm sales

were composed of milk sales, the more likely members

were to attend meetings. Table 24 shows this tendency

is in part accounted for by the greater attendance of

members in the 75-89.9 percent sales category, and

their relatively smaller attendance in the 1-49 percent

sales category.

Farm Size: Two farm size variables, “size of milking herd” and “gross farm sales,” were found statistically significant and positively related to attendance at

meetings. Their regression coefficients were 0.11777 for

size of milking herd and 0.08423 for gross farm sales

(table 20). These positive regression coefficients indicate members with larger herds were more likely to

attend cooperative meetings than those with smaller

herds, as were members with smaller sales.

Table 24 shows these relationships in percentage

format. It compares attenders with non-attenders.

Fifty-eight percent who attend meetings came from

farms with gross sales volumes of $100,000 or more.

Only 6.3 percent came from farms with sales volumes

of less than $30,000. This size relationship is reflected

by the non-attenders as well. Compared with attenders, fewer non-attenders (44.8 percent) were from the

$100,000-plus units, while more (16.1) percent were

from the $30,000 and less units.

When examining herd sizes, a similar relationship is found (table 24). Nearly 64 percent of the members who attended meetings milked herds of more

than 50 cows. Only 36.3 percent of those who attended

had herds of less than 50 head. Compared with attenders, fewer non-attenders (46 percent) milked herds

larger than 50 cows and more non-attenders (54 percent) milked herds smaller than 50 head.

Demographic Variables: The variable, “Does

spouse hold an off-farm job?”, was found statistically

significant and negatively related to attendance at

meetings. The calculated regression coefficient was -

0.09009 (table 20). Members were more likely to attend

meetings if the spouse was not employed off the farm.

This relationship was supported by table 25 percentages. Nearly 63 percent of the attenders said their

spouses did not hold off-farm employment, compared

with 50+ percent of the non-attenders. More non-attenders than attenders had an employed spouse, (35 versus 30 percent).

Cooperative Principles: Two beliefs, “Ag co-ops

should practice one-person, one-vote” and “Ag co-ops

should support education for members and the public,” were found statistically significant and positively

related to meeting attendance. The calculated regression coefficients were 0.06072 for the one-person, one13
14

Table 20— Attendance at meetings and member characteristics: regression coefficients (n = 1,156)

Standardized

Member characteristics regression

coefficient (t-value)

Farm Type:

Percent of gross farm sales from milk 0.06740 *

(2.415)

Farm Size:

Gross farm sales 0.08423 *

(2.650)

Size of milking herd 0.11777 *

(3.796)

Demographic:

Spouse employed off the farm -0.09009 *

(3.319)

Cooperative Identification:

I feel I am part-owner of the cooperative. 0.14624 *

(4.236)

Cooperative principles:

Ag co-ops should practice one-person, one-vote. 0.06072 **

(1.757)

Ag co-ops should support education for members and the public. 0.06594 **

(1.890)

Satisfaction:

With dairy farming as a way of life. 0.10769 *

(3.669)

With my district director. 0.09049 *

(2.714)

Equity:

The cooperative primarily benefits small farms. -0.09451 *

(-3.256)

The cooperative primarily benefits large farms. 0.07424 *

(2.582)

Influence:

Co-op members have too much to say about how the co-op is run. -0.05030 *

(-2.084)

Collective Action:

Members receive benefits from doing business the cooperative way. 0.07271 *

(1.987)

—————————————————————————————————————————————————————————

Intercept 0.38529

R 2 0.22169

Adjusted R 2 0.21282

F 24.99946 *

* Variables significant at 0.05 probability level.

** Variables significant at 0.10 probability level.
vote principle, and 0.06594 for the education principle

(table 20). The greater the agreement with these principles, the more likely members were found to attend

meetings. The reverse was also true—less agreement

and less attendance.

The relationships between principles and attendance at meetings was supported by the Likert scale

analysis (table 26). The score for those attending meetings was 3.95, and 3.86 for non-attenders for the oneperson, one-vote principle. The scale scores for the

education principle was 3.80 for attenders and 3.66 for

non-attenders. Members who attended meetings subscribed to one-person, one-vote and the education

principles more strongly than non-attenders.

Collective Action: The item, “Members receive

benefits from doing business the cooperative way,”

was found statistically significant and positively related to attendance at meetings. The regression coefficient for this variable was .07271 (table 20). The

stronger they believed that “Members received benefits from doing business the cooperative way,” the

more likely they were to attend meetings.

The scale analysis supported this finding. The

score was 3.84 for attenders and 3.68 for non-attenders

(table 26). Members who attended meetings believed

in “the cooperative way” more strongly than nonattenders.

One identification variable, “I feel I am part

owner of my cooperative,” was found statistically significant. The regression revealed a coefficient of

0.14624 for this variable (table 20). The more strongly

members subscribed positively to this belief, the more

likely they were to attend cooperative meetings. When

scale scores between attenders and non-attenders were

compared, those attending scored higher (3.83) than

non-attenders (3.51) in their identification with the

cooperative.

15

Table 21— Service on committees and member characteristics: regression coefficients(n = 1,156)

Standardized

regression

Member characteristics coefficient

(t-value)

Farm Size:

Gross farm sales 0.13933 *

(4.842)

Percent of labor hired 0.09382 *

(3.318)

Cooperative principles:

Ag co-ops should work with other ag co-ops. 0.09014 *

(2.656)

Satisfaction:

With my board of directors. 0.19992 *

(6.372)

Influence:

Co-op members have too little to say about how the co-op is run. 0.07954 *

(2.916)

Collective Action:

Members receive benefits from doing business the cooperative way. 0.10466 *

(3.008)

—————————————————————————————————————————————————————————

Intercept 0.22919

R 2 0.19938

Adjusted R 2 0.19519

F 47.64737 *

* Variables significant at 0.05 probability level.
Member Satisfaction: Two satisfaction variables

were found positively related to meeting attendance,

“satisfaction with dairy farming as a way of life” and

“satisfaction with the district director.” The calculated

regression coefficients were 0.10769 (“farming as a way

of life,”) and 0.09049 (“district director”) (table 20).

Members who were more satisfied with “farming as a

way of life” and with the “district director” tended to

be attenders, while those less satisfied were less likely

to attend.

This relationship between these measures of satisfaction and attendance at meetings was supported by

the scale analysis. The score for attenders satisfied

with farming was 3.82, and 3.59 non-attenders. The

scale score for satisfaction with the district director

was 3.89 for attenders and 3.67 for non-attenders.

Members who attended meetings expressed more satisfaction with farming and with their district director

than non-attending members (table 26).

Member Influence: “Members have too much

say about how the cooperative is run” was found statistically significant and negatively related to attendance at meetings. Regression coefficient for this was -

0.05030 (table 20). Farmers who agreed that “Members

have too much say” were less likely to attend meetings.

The scale analysis supported this finding. The

score was 2.02 for attenders and 2.20 for non-attenders.

On average, both groups disagreed that members have

too much say. However, those who attended meetings

16

Table 22— Service in an election office and member characteristics: regression coefficients(n = 1,156)

Standardized

regression

Member characteristics coefficient

(t-value)

Farm Size:

Gross farm sales 0.08573 *

(2.672)

Size of milking herd 0.09121 *

(2.945)

Cooperative principles:

Ag co-ops should practice one-member, one-vote. 0.12766 *

(3.682)

Ag co-ops should work with other ag co-ops. 0.08031 *

(2.265)

Satisfaction:

With my board of directors. 0.15440 *

(4.357)

Cooperative Identification:

I feel I am part owner of the cooperative. 0.13140 *

(3.760)

Collective Action:

An individual farmer can usually make better marketing decisions -0.06393

than a group of farmers. (-2.320)

—————————————————————————————————————————————————————————

Intercept 0.23672

R 2 0.19955

Adjusted R 2 0.19466

F 40.84831*

* Variables significant at 0.05 probability level.
tended to disagree more strongly with the “too much

say” item while non-attenders were more likely to

believe that members have too much say (table 26).

Equity/Equality/Impartiality: The item, “The

cooperative primarily benefits small farms,” was

found negatively related to attendance at meetings.

The regression revealed a coefficient of -0.09451 (table

20). The more strongly members subscribed to this

belief, the less likely they were to attend cooperative

meetings. When scale scores between attenders and

non-attenders were compared, attenders scored lower

(2.23)—disagreed more intensely—than non-attenders

(2.44) (table 26).

A second equity variable, “The cooperative primarily benefits large farms,” was found positively

related to attendance. The calculated regression coefficient was 0.07424 (table 20). The more likely members

were to attend meetings, the more likely they were to

agree with the view that “The cooperative primarily

benefits large farms.”

The relationship between “equity “ and “attendance” was supported by the scale analysis. The score

was 2.80 for those attending and 2.94 for those not

attending. Both groups disagreed that “The cooperative primarily benefits large farms.” However members attending were less intense in their disagreement.

A score of 3.00 indicates ambivalence. Non-attenders

disagreed more intensely.

Served on Committees

Six variables were found related to serving on

non-elective committees—farm size (gross farm sales);

the percent labor hired; cooperative principle (“Ag coops should work with other ag co-ops”); collective

action (“Members receive benefits from doing business

the cooperative way”); satisfaction (“satisfaction with

the cooperative board of directors”); and influence

(“Members have too little say on how the cooperative

is run”).

Farm Size: The amount of gross farm sales was

found statistically significant and positively related to

members serving on a committee. The regression

revealed a coefficient of 0.13933 for this variable (table

21). Those from farms with greater gross sales were

more likely to serve than those with smaller gross farm

sales.

When comparing members who served on committees with those who did not, 78.3 percent who

served had gross sales volumes of $100,000 or more,

while just 48.7 percent who did not serve had similar

volumes (table 27). Only 1.6 percent of the committee

17

Table 23— Recruited other members and member characteristics: regression coefficients (n = 1,156)

Standardized

regression

Member characteristics coefficient

(t-value)

Farm Size:

Size of milking herd 0.08434 *

(2.877)

Cooperative Identification:

Being a co-op member is an important part of my identity as a farmer. 0.14294 *

(4.875)

Equity:

The cooperative primarily benefits large farms. -0.09535 *

(3.303)

—————————————————————————————————————————————————————————

Intercept -0.03080

R 2 0.04142

Adjusted R 2 0.03892

F 16.57946 *

* Variables significant at 0.05 probability level.
persons came from farms with sales volumes of less

than $30,000, while 11.8 percent of those not serving on

committees had such volumes.

Labor Provision: Hired labor was found statistically significant and positively related to member participation on a committee. The calculated regression

coefficient for this variable was 0.09382 (table 21).

Members serving on committees tended to be from

farms that hired more than half their labor needs.

Table 28 shows that while l7.4 percent of the members

serving on committees hired more than half of their

needed farm labor, just 8.8 percent of members not

serving on committees did so. While the percentage of

all respondents in the study hiring half of their labor

needs was small (less than 10 percent), those serving

on committees were more likely to hire labor than

those members not serving on committees.

Cooperative Principles: One belief concerning

cooperative principles, “Ag co-ops should work with

other ag co-ops,” was found statistically significant

and positively related to serving on committees. The

regression revealed a coefficient of 0.09014 for this

variable (table 21). The more members agreed, the

more likely they were found serving on committees

and conversely so (less likely, less service).

This relationship is supported by the scale analysis. The scale score for those serving was 4.07 and 3.8

for non-servers (table 29). Members serving on committees believed more intensely than those not serving

that “Ag co-ops should work with other ag co-ops.” 

Collective Action: This variable, “Members

receive benefits from doing business the cooperative

way,” was found statistically significant and positively

related to serving on committees. The calculated

regression coefficient was .10466. The more intensely

members believed that “Members received benefits

from doing business the cooperative way,” the more

likely they were to serve on committees. The scale

18

Table 24— Size of farm and member attendance at

meetings

Attended meetings

———————————————————

Size category No Yes

Cows Number Percent Number Percent

Number

Less than 50 250 54.0 236 36.3

50 - 179 183 39.5 349 53.7

180 - 499 30 6.5 65 10.0

500 - 999 - - - -

1,000 and more - - - - ——— ——— ——— ———

Total 463 100.0 650 100.0

Gross farm sales 

$1,000

Less than 10 14 3.2 9 1.4

10 - 29.9 57 12.9 31 4.9

30 - 49.9 53 12.0 56 8.9

50 - 99.9 120 27.1 169 26.7

100 - 249.9 153 34.6 285 45.1

250 and more 45 10.2 82 13.0 ——— ——— ——— ———

Total 442 100.0 632 100.0

Gross farm sales

from milk sales

Percent

1 - 49.9 89 19.7 88 13.7

50 - 74.9 124 27.5 168 26.2

75 - 89.9 155 34.4 271 42.2

90 - 100 83 18.4 115 17.9 ——— ——— ——— ———

Total 451 100.0 642 100.0

Table 25—Spouse with occupation or employment

other than farming and attendance at meetings

Attended meetings

——————————————

Spouse employed No Yes

Number

No 236 405

Yes 162 195

No spouse 62 44 —— ——

Total 460 644

Percent

No 51.30 62.89

Yes 35.22 30.28

No spouse 13.48 6.83 ——— ———

Total 100.00 100.00
19

Table 26—Member beliefs and attendance at meetings

Strongly Strongly Weighted

Belief disagree Disagree Unsure Agree agree Total score

Number

I feel I am part-owner of my cooperative

Did not attend meetings 18 66 67 288 26 465 3.51

Attended meetings 14 55 62 419 101 651 3.83

Agricultural cooperatives should practice onemember, one-vote

Did not attend meetings 2 20 84 284 66 456 3.86

Attended meetings 7 28 73 420 119 647 3.95

Agricultural cooperatives should support 

education of members and the public

Did not attend meetings 10 29 107 269 39 454 3.66

Attended meetings 11 35 114 400 85 645 3.80

The cooperative primarily benefits small farms

Did not attend meetings 40 204 190 18 5 457 2.44

Attended meetings 89 343 185 21 4 642 2.23

Members receive benefits from doing 

business the cooperative way

Did not attend meetings 5 16 123 289 24 457 3.68

Attended meetings 5 22 104 453 62 646 3.84

Members have too much to say about how the 

co-op is run

Did not attend meetings 54 276 123 9 2 464 2.20

Attended meetings 97 461 76 7 7 648 2.02

The cooperative primarily benefits large farms

Did not attend meetings 17 144 177 82 34 454 2.94

Attended meetings 44 255 170 131 42 642 2.80

Very Very Weighted

Dissatisfied Dissatisfied Unsure Satisfied Satisfied Total score

Satisfaction with my district director

Did not attend meetings 12 17 127 266 43 465 3.67

Attended meetings 13 25 102 387 119 646 3.89

Satisfaction with dairy farming as a way of life

Did not attend meetings 13 71 60 266 53 463 3.59

Attended meetings 3 66 79 398 101 647 3.82
likely they were to serve on committees. The scale

served on committees scored higher (3.98) than those

who didn’t participate (3.75).

Member Satisfaction: “Satisfaction with the

board of directors” was found positively related to

serving on committees. The calculated regression coefficient was 0.19992 (table 21). Those farmers more satisfied with their board of directors were more likely to

serve on committees. This relationship was borne out

by the Likert scale scores. Members who served on

committees scored higher (4.11) than those who did

not (3.76) (table 29).

Influence: “Members have too little say about

how the co-op is run” was found statistically significant and positively related to service on a non-elected

committee. However, this relationship is ambiguous

given the Likert scale analysis. The scale score was 2.69

for those who served on committees and 2.93 for those

who had not served. Overall, members disagree that

they have “too little say about how the co-op is run.”

However, members serving on committees disagreed

more intensely. This result is at variance to the regression analysis and reveals a non-linear relationship

between this item and service on a committee. 4

Elected to a Cooperative Office

Seven characteristics of members were found statistically related to members serving in an elected

office. They included the following variables and measures: farm size (gross farm sales and size of herd);

cooperative principles (“Ag co-ops should practice

one-member, one-vote” and “Ag co-ops should work

with other ag co-ops”); collective action (“An individual farmer can usually make better marketing decisions than a group of farmers or some agency”); identification (“I feel I am part owner of my cooperative”);

and satisfaction (“with the cooperative board of directors”) (table 22).

Farm Size: Two farm size variables, “gross farm

sales” and “size of milking herd,” were statistically

significant and positively related to serving in an elected office. The revealed regression coefficients were

0.08573 for gross farm sales, and 0.09121 for size of

milking herd (table 22). Members from farms with

larger gross farm sales were more likely to have served

as an officer than members with smaller sales numbers. Similarly, members with larger herds were more

likely to have served as an elected officer than members with smaller herds.

20

Table 27— Member served on a committee and 

size of farm

Served on a committee

————————————

Size category No Yes

Number of members

Gross farm sales

$1,000

Less than 10 23 -

10 - 29.9 88 2

30 - 49.9 104 5

50 - 99.9 268 21

100 - 249.9 361 74

250 and more 98 27 —— ——

Total 942 129

Percent

Less than 10 2.44 -

10 - 29.9 9.34 1.55

30 - 49.9 11.04 3.88

50 - 99.9 28.45 16.28

100 - 249.9 38.32 57.36

250 and more 10.40 20.93 ——— ———

Total 100.00 100.00

Table 28— Member served on a committee and hired

more than half of the physical labor performed on

the farm

Served on a committee

———————————

Hired over half

of the physical labor No Yes

Number

No 889 109

Yes 86 23 —— ——

Total 975 132

Percent

No 91.18 82.58

Yes 8.82 17.42 ——— ———

Total 100.00 100.00

4 Mathematically, regression coefficients are calculated from the

entire sample of members who answered the question, while in the

Likert scale computations, each score is calculated independent of

each other. The differences between the two methods may reveal a

skewness in the regression relationship of a curvilinear rather than

linear nature.
When comparing members who have served

with those who have not, table 30 indicates that 70.8

percent of the elected officers came from farms with

gross sales volumes of $100,000 or more. But the 47.8

percent of members who had not served as an officer

came from farms with similar volumes. Just 2.6 percent

of the officeholders came from farms with sales volumes of less than $30,000, while 12.3 percent of the

non-officeholders came from farms with such volumes.

Members with greater gross farm sales were more likely to serve in an elected capacity than members with

smaller gross farm sales.

Similarly, when examining herd sizes, more than

72 percent of the elected officers milked herds of more

than 50 cows, while only 52.5 percent of non-officeholders milked that many. Conversely with smaller

herds, 47.5 percent of non-officeholders milked herds

of less than 50 head, compared with just 27.6 percent

of the officeholders (table 30). Members with larger

milking herds were more likely to serve as an officer

than those with smaller herds.

Cooperative Principles: Two beliefs concerning

cooperative principles, “Ag co-ops should practice

one-person, one-vote” and “Ag co-ops should work

with other ag co-ops,” were found statistically significant and positively related to holding an elected office.

The coefficients revealed by the regression were

0.12766 for “one-person, one-vote” and 0.08031 for the

“Ag co-ops should work together” (table 22). The more

members accepted these two basic cooperative principles, the more likely they were to have held an elective

office.

The relationship between principles and holding

office was supported by the Likert scale analysis. The

average scale score for officeholders was 4.09 for the

one-person, one-vote principle and 3.88 for non-office

holders (table 31). Members who have held office tend

to subscribe to the one-person, one-vote principle

more strongly than non-officers.

The average scores for “Ag co-ops should work

with other ag co-ops” was 4.10 for officers and 3.77 for

nonofficers. Members who have held an elected office

believed more strongly that “Ag co-ops should work

with other ag co-ops” than members who did not

serve as an officer (table 31).

21

Table 29— Member beliefs and served on a committee

Belief Strongly Strongly Weighted

disagree Disagree Unsure Agree agree Total score

Number

Members have too little to say about 

how the cooperative is run

Did not serve on a committee 23 347 343 196 66 975 2.93

Served on a committee 12 55 32 23 8 130 2.69

Members receive benefits from doing 

business the cooperative way

Did not serve on a committee 9 36 211 648 66 970 3.75

Served on a committee 1 2 15 94 19 131 3.98

Agricultural co-ops should work with 

other agricultural co-ops

Did not serve on a committee 10 49 181 615 111 966 3.80

Served on a committee - 1 19 81 30 131 4.07

Very Very Weighted

Dissatisfied Dissatisfied Unsure Satisfied Satisfied Total score

Satisfied with my cooperative board of directors

Did not serve on committees 14 38 222 605 101 980 3.76

Did serve on committees 2 1 15 75 38 131 4.11
Collective Action: The view that “An individual

farmer can usually make better marketing decisions

than a group of farmers or some agency” was found

statistically significant and negatively related to holding an elected office. The regression revealed a coefficient of -0.06393. The more intensely members heed

this viewpoint, the less likely they were to have served

as an elected officer.

The scale analysis supported this finding. The

scale score was 2.13 for officeholders and 2.46 for nonofficeholders (table 31). Both measures are to the “disagreement” side of unsure. Neither group of members

agree that individuals can do better than a group, but

those who had held an office disagreed more so, and to

a statistically significant degree.

Identification: “I feel I am part owner of the

cooperative” was found statistically significant and

positively related to holding an elected office. The

revealed regression coefficient for this variable was

0.13140. The more intensely members believed they

were part owners of the cooperative, the more likely

they were to have served as an elected officer.

This relationship between “having been elected”

and “feeling like a part-owner” was supported by the

scale analysis. The average score was 4.11 for officeholders and 3.65 for non-officeholders. The average

member elected to an office felt more intensely about

their ownership of the cooperative than non-officers

(table 31.)

Member Satisfaction: The variable, “satisfaction

with the board of directors,” was positively related to

having served in an elected office. The calculated

regression coefficient was 0.15440 (table 22). Farmers

more satisfied with their board of directors were most

likely to have served as elected officers.

The scale analysis supported this finding. The

average score was 4.10 for officeholders and 3.73 for

non-officeholders (table 31.) Those who had held an

elected office were more satisfied with their board of

directors than those who had never been an officer.

Recruited Other Members

Three characteristics of members were found statistically related to differences in whether members

had recruited other members—”size of milking herd,”

“The cooperative primarily benefits large farms,” and

“Belonging to the cooperative is an important part of

my identity as a farmer.” 

Farm Size: “Size of milking herd” was statistically significant and positively related to recruiting other

members. The regression analysis revealed a coeffi22

Table 30— Member's size of farm and elected to office

Elected to office

———————————

Size category No Yes

Size of milking herd Number of members

Less than 50 431 55

50 - 99 407 122

100 - 499 70 22

500 and more - - ——— ———

Total 908 199

Percent

Less than 50 47.47 27.64

50 - 99 44.82 61.31

100 - 499 7.71 11.06

500 and more - - ——— ———

Total 100.00 100.00

Gross farm sales

$1,000 Number of members

Less than 10 23 -

10 - 29.9 85 5

30 - 49.9 102 8

50 - 99.9 246 44

100 - 249.9 319 113

250 and more 99 25 ——— ———

Total 874 195

Percent

Less than 10 2.63 -

10 - 29.9 9.73 2.56

30 - 49.9 11.67 4.10

50 - 99.9 28.15 22.56

100 - 249.9 36.50 57.95

250 and more 11.33 12.82 ——— ———

Total 100.00 100.00
cient of 0.08434 for this variable (table 23). Members

from farms with larger milking herds were more likely

to recruit others than members with smaller herd sizes.

Sixty-seven percent of the recruiters and 50.7 percent of the non-recruited milked herds of more than 50

cows. (table 32). Conversely, while nearly 49.3 percent

of non-recruiters milked herds of less than 50 head,

just 32.9 percent of the recruiters did so. Members with

larger milking herds were more likely to have recruited others than their fellow members with smaller herd

sizes.

Member Equity/Impartiality: “The cooperative

primarily benefits large farms” variable was statistically significant and negatively related to recruitment.

The regression analysis revealed a coefficient of -

0.09535 (table 23). The more strongly members agreed,

the less likely they were to have recruited others to

join the cooperative. Conversely, the less likely it was

that members agreed, the more likely it was that they

had recruited members.

The scale analysis supported these findings. The

average was 2.41 for recruiting members and 2.89 for

non-recruiters. Average scores for members indicate

that overall, members disagreed with the statement,

but those who had not recruited disagreed with

greater intensity (table 33).

Member Identification: “Being a co-op member

is an important part of my identity as a farmer” was

statistically significant and positively related to

recruitment. The regression coefficient for this variable

23

Table 31— Member's beliefs and elected to office

Strongly Strongly Weighted

Belief disagree Disagree Unsure Agree agree Total score

Number

I feel I am part-owner of my cooperative

Have not been elected 32 112 115 586 68 900 3.65

Have been elected - 10 14 118 56 198 4.11

Agricultural cooperatives should practice 

one-member, one-vote

Have not been elected 9 38 141 580 132 900 3.88

Have been elected - 9 15 123 51 198 4.09

An individual farmer can usually make better 

marketing decisions than a group of farmers or 

some agency

Have not been elected 95 441 237 108 19 900 2.46

Have been elected 30 124 33 7 3 197 2.13

Agricultural cooperatives should work 

with other cooperatives

Have not been elected 9 45 177 577 90 898 3.77

Have been elected 1 4 21 119 52 197 4.10

Very Very Weighted

Dissatisfied Dissatisfied Unsure Satisfied Satisfied Total score

Satisfied with my cooperative board of directors

Did not serve on committees 126 636 192 15 9 978 2.13

Did serve on committees 24 99 7 1 - 131 1.89

Satisfied with my cooperative board of directors

Had not been elected to office 16 33 215 563 84 911 3.73

Had been elected to office - 6 24 112 56 198 4.10
was 0.14294 (table 23). The more strongly members

believed this, the more likely they were to have

recruited other members.

The scale analysis supported this finding.

Recruiters had an average score of 4.00, while nonrecruiters scored 3.32. Members who sought to recruit

others identified more strongly with the cooperative as

an important part of their identity, than those who did

not recruit.

Summary

Nineteen variables were found statistically related to the various participation measures, i.e., attendance at meetings, service on a committee, service in

an elected office, and recruitment of other members.

Percent of gross farm sales from the sale of milk

was positively related to attendance at meetings. Gross

farm sales and size of milking herd variables were positively related to three participation measures. Gross

farm sales was related to attendance at meetings, service to committees, and service in an elected office.

Size of milking herd was related to attendance at meet24

Table 32— Member's size of milking herd and

recruitment of members

Recruited members

————————————

Size category No Yes

Number

Number of cows

Less than 50 168 27

50 - 99 149 40

100 - 499 24 15

More than 500 - - —— ——

Total 341 82

Percent

Less than 50 49.27 32.93

50 - 99 43.70 48.78

100 - 499 7.04 18.29

More than 500 - - ——— ———

Total 100.00 100.00

Table 33— Member's belief and recruitment of members

Strongly Strongly Weighted

Belief disagree Disagree Unsure Agree agree Total score

Number

The cooperative primarily benefits large farms

Recruited members 15 115 129 52 28 339 2.89

Did not recruit members 13 36 17 11 2 79 2.41

Belonging to the cooperative is an important 

part of my identity as a farmer

Recruited members 9 75 74 170 17 345 3.32

Did not recruit members - 7 9 43 23 82 4.00

Table 34— Member attended meetings and spouse

employed in an occupation other than farming

Attended meetings

——————————

Spouse employed No Yes

Number

No 236 405

Yes 162 195

No spouse 62 44 —— ——

Total 460 644

Percent

No 51.30 62.89

Yes 35.22 30.28

No spouse 13.48 6.83 ——— ———

Total 100.00 100.00
ings, service as an elected officer, and recruitment of

other members. Percent of labor hired was positively

related to service on committees. Spouse’s off-farm

employment was negatively related to attendance at

meetings. Attendance was greater when spouses were

not employed off the farm.

Three cooperative principles, “Ag co-ops should

use one-person, one-vote,” “Ag co-ops should support

education for the members and the public,” and “Ag

co-ops should work with other ag co-ops,” were positively related to three of the participation measures;

“One-person, one-vote” to attendance at meetings and

service as an elected officer; “Support education” to

attendance at meetings; and “Work with other ag coops” was related to service on committees and as an

elected officer.

Satisfaction measures were related to three of the

participation measures; “Satisfaction with dairy farming as a way of life” and “with district directors” to

attendance at meetings; and “Satisfaction with the

cooperative board of directors” to service on committees and as an officer.

Two equity/impartiality variables, “the cooperative primarily benefits small farms” and “the cooperative primarily benefits large farms,” were significantly

related to participation measures. “The cooperative

primarily benefits small farms” was negatively related

to attendance at meetings. “The cooperative primarily

benefits large farms” was positively related to attendance at meetings, although negatively related to

recruitment.

Two influence variables, “members have too little

say in the cooperative” and “members have too much

say in the cooperative,” were significantly related to

participation variables. “Too little say” was positively

related to service on a committee and “too much say”

was negatively related to “attendance at meetings.”

Two collective action variables were related to

three participation measures—attendance at meetings,

service to committees, and service as an elected officer.

“Members receive benefits from doing business the

25

Table 35— Member loyalty

Belief Strongly Strongly Weighted

disagree Disagree Unsure Agree agree Total score

Number

Agricultural cooperatives should work with 

other cooperatives

Did not attend meetings 9 45 177 577 90 898 3.77

Attended meetings 1 4 21 119 52 197 4.10

Lack of time prevents me from attending most 

cooperative functions and activities

Spouse was not employed off the farm 1 4 4 8 1 18 3.22

Spouse was employed off the farm 20 175 72 310 48 625 3.31

No spouse 11 85 45 181 33 355 3.39

Table 36— Member's education and served on a

committee

Served on committee

——————————

Education No Yes

Number

Not completed high school 170 14

Completed high school 570 71

Some college 165 30

Bachelor's degree 54 14

Master's degree 5 -

PHD degree 5 1 —— ——

Total 969 130

Percent

Not completed high school 17.54 10.77

Completed high school 58.82 54.62

Some college 17.03 23.08

Bachelor's degree 5.57 10.77

Master's degree 0.52 -

PHD degree 0.52 0.77 ——— ———

Total 100.00 100.00
cooperative way” was positively related to attendance

at meetings and service on a committee. “Individual

farmers can usually make better marketing decisions

than a group of farmers or some agency” was negatively related to service as an elected officer. All members, on average, disagreed with this item, although

officers disagreed more intensely than others.

Two identification variables were related to three

participation variables—attendance at meetings, service to committees, and recruitment of other members.

“I feel I am part owner of my cooperative” was positively related to attendance at meetings and service as

an officer. “Belonging to the cooperative is an important part of my identity as a farmer” was positively

related to recruitment of other members.

Two of these variables—”the cooperative primarily benefits large farms” and “members have too little

say in how the co-op is run”—proved ambiguous in

their respective relationships to attendance at meetings

and service on committees. The regression results and

the Likert scale analysis produced incongruent results

for these variables.

Implications

Attending Meetings: The most democratic aspect

of organized cooperation is the member meeting.

When members attend and articulate their needs, they

imprint the cooperative with their voices and improve

possibilities for shaping the cooperative in their joint

interests. While directors act in the collective interests

of all members, those who do not attend meetings

have little input into cooperative decision making,

including the selection of directors.

Differences were found between members who

did or did not attended meetings. Those who attended

were more satisfied with farming as a way of life, more

closely identified with the cooperative, and saw themselves as part-owners who believed in the benefits of

doing business the cooperative way. They believed

more strongly in the one-person, one-vote principle

and supported cooperative education for members and

the public. These members also had larger farm units,

larger gross sales volumes, and larger dairy herds.

Their spouses were less likely to work off the farm.

Members who did not attend meetings lacked a

strong appreciation of cooperatives and were less likely to identify themselves as part owners. They also had

a weaker appreciation for cooperative principles such

as one-member, one-vote, and education. They were

also less likely to identify with the view that

“Members benefit from doing business the cooperative

way.” These members also operated smaller farm

units, were less satisfied with farming as a way of life,

and were more likely to have a spouse working off the

farm.

A cooperative seeking to realize the fundamental

belief that the cooperative is for all members may want

to target members from smaller units. The equality

aspects of the organization should be emphasized with

these members—the one-member, one-vote principle

and the part-owner relationship.

Given that these members are more likely to have

a spouse working off the farm, some sensitivity should

be given to scheduling meetings at times convenient

for them. Table 34 indicates that such farmers felt that

“lack of time prevents me from attending cooperative

functions.”

Members who did not attend meetings were also

more likely to agree that “members have too much say

in how a cooperative is run.” Their view may be a

rationalization for their own lack of attendance or a

resentment of those who do. However, it again betrays

a misunderstanding of cooperatives.

Unfortunately, these farmers are the most

stressed and have the least contact with the cooperative. They don’t attend meetings to voice their needs

and do not learn about and can’t integrate the “cooperative” aspects of membership. Consequently, cooperative nor the member can learn from one another.

A member relations program that seeks to better

integrate more members from the smaller units could

help improve the cooperative’s response to all members, and help members from the smaller units better

realize “benefits from doing business the cooperative

way.”

Serving on a Committee: Some variables that

were statistically related to serving on committees

were similar to those related to attending meetings.

Farmers who served on committees tended to have

larger gross farm sales and hired more labor in their

operations. The hired labor measure not only indicates

the size of the operation, but may also be a measure of

available time. Farmers who hire labor are likely able

to slip away from farm chores more easily to attend

committee meetings than those who lack hired help.

These results also suggest that involvement

makes a difference. It is likely that the first-hand experience of serving on committees allows members to

understand “Ag co-ops should work with other ag coops” and that “Members receive benefits from doing

26
business the cooperative way.” These committee experiences may also account for greater member-satisfaction with the board of directors.

Committee members were also more likely to

agree that members have too little say in the cooperative. By their committee work, they may become aware

how much is done in the cooperative and how little

most members are involved.

All of the results for committee participation

imply that members gain considerably from their

involvement in the cooperative. They may learn that

“ag co-ops do need to work with other ag co-ops” and

that “members benefit from doing business the cooperative way.”

As with attendance at meetings, a member relations program could improve cooperative responsiveness for all members by targeting members from

smaller units. Study results suggest these members

have less time to serve and are less satisfied with their

board of directors. On-farm visits to members by directors could help mitigate some of their time disadvantages, improve participation in the organization, and

help familiarize them with cooperative operations.

Ideal scheduling would allow farmers from smaller

units greater participation on committees.

Elected to an Office: As with the other methods

of participation, size again is important in influencing

those who do or do not serve. Members who served as

an elected officer had larger milking herds and greater

farm sales volumes.

These members strongly believed in the “Onemember, one-vote” and “Ag co-ops should work with

other ag co-ops” principles. They also felt more strongly about their “part ownership” in the organization.

Farmers who had not served in an elected office

more intensely agreed that “an individual farmer can

usually make better marketing decisions than a group

of farmers or some agency.” Again, this suggests the

positive impacts of involvement. Members who serve

as elected officers deepen or develop these beliefs.

A member relations program should emphasize

these aspects of the organization to the general membership and involve members from the smaller farm

units.

Recruiting Other Members: Recruitment is perhaps the most intense form of participation in the

cooperative. Just 83 members recruited others. These

farmers identified themselves most closely with the

cooperative. Again, size of the farm unit was important. Although farmers who had the largest milking

herds often acted as recruiters, they disagreed most

intensely that “The cooperative primarily benefits

large farms.” Cooperatives might augment their member relations programs with these farmers, perhaps

helping them direct some of their efforts to farmers on

the smaller units.

These variables are important in improving participation in a cooperative by all members. They can

help the cooperative understand what beliefs and values are different for participators and non-participators. A member relations program then might highlight those beliefs. The organization may also seek to

better integrate those members from smaller farm

units who feel they are not benefiting from the organization.

Direct contact with these members, flexible meeting schedules, and direct recruitment of members to

meetings, committees, and offices could improve organizational responsiveness for all members. With

greater involvement, all members can articulate their

needs and the organization can better respond to them.

Of particular note is the continuing importance of

cooperative principles, the collective action variables,

and identification with the cooperative. Despite cultural trends emphasizing the individual, farmer members

continued to reflect an appreciation for cooperative

organization and collective action. This research

demonstrates clearly that these beliefs and the understanding of their value in action are best deepened by

participation in cooperative governance.

Limitations of Study: The analysis is most relevant for dairy farmers in the identified States and

within the response ranges summarized in the report.

As member characteristics vary out of these ranges—

for larger or smaller farms, other regions, different

average responses and scale scores on the belief

items—less reliance can be placed in the results.

These variables are statistically significant and

related to participation in the cooperative. Their identification can help cooperatives better tailor their member programs to encourage involvement at meetings,

service on committees or in an elective office, and in

recruiting other members.

However, this analysis measured member characteristics using dummy variables. The respondent

answers questions with very limited choices, e.g., yes,

no, or strongly disagree to strongly agree. This type of

analysis accounts for only a limited amount of the

variation in participation rates. Other influences, left

unidentified, more fully account for differences in participation. The variables identified here explain only

limited differences. However, they are statistically significant and can be used as a place to start.

27
Conclusions

This research identifies various characteristics of

dairy members that influence their participation in a

cooperative. Participation measures included attendance at meetings, serving on committees or as an

elected officer, and recruiting other farmers to become

members. Member characteristics included beliefs concerning: cooperative principles, collective action, individual member identities as associated with cooperative membership, life satisfaction with farming,

member satisfaction with the cooperative operations

and representation, member influence on cooperative

decision making, and equitable treatment among

members.

Demographic characteristics of members and

measures of farm size and farm type were included.

Regression analysis and Likert scale analysis were

applied to the 1,156 dairy farmer respondents from

Iowa, Illinois, Minnesota, and Wisconsin. All were

members of the same cooperative. Analysis involved

only dummy variables, limiting the total variation

explained to very small percentages. However, 19

characteristics were found statistically significant and

linearly related to the four participation measures.

Eight characteristics were positively related to

attendance at meetings. The greater their measured

value and/or the more intense the belief, the more

likely a member would attend cooperative meetings.

The characteristics are:

1. Percent of gross farm sales from the sale of milk.

2. Gross farm sales.

3. Size of milking herd.

4. “I feel I am part owner of the cooperative.”

5. “Ag co-ops should practice one person, one vote.”

6. “Ag co-ops should support education for their

members and the public.” 

7. Satisfaction with “farming as a way of life.”

8. Satisfaction with “my district director.”

Three characteristics were found negatively related to attendance at meetings. The greater the measured value or frequency of these characteristics and

more intense the belief, the less likely a member would

attend cooperative meetings. The characteristics are:

1. Spouse’s employment off-farm.

2. “Members have too much say about how the cooperative is run.”

3. “The cooperative primarily benefits small farms.”

Five characteristics were found positively related

to serving on committees. The greater their measured

value or frequency and more intense the belief, the

more likely a member would serve on committees. The

characteristics are:

1. Gross farm sales.

2. More than half of the farm labor is hired.

3. “Ag co-ops should work with other ag co-ops.”

4. “Members receive benefits from doing business the

cooperative way.”

5. Satisfaction with “my cooperative board of directors.”

Six characteristics were positively related to service in an elected office. The greater the measured

value and intensity of belief, the more likely a member

would serve in an elected office. The characteristics

are:

1. Gross farm sales.

2. Size of milking herd.

3. “Ag co-ops should practice one-person, one-vote.”

4. “Ag co-ops should work with other ag co-ops.”

5. “I feel I am part-owner of the cooperative.”

6. Satisfaction with “my board of directors.”

One characteristic was negatively related to service in an elected office. The more intensely members

agreed that “an individual farmer can usually make

better marketing decisions than a group of farmers or

some agency,” the less likely they were to serve as an

elected cooperative officer.

Two characteristics were positively related to

recruitment of other farmers to the cooperative. The

greater their measured value and more intense the

belief, the more likely members would recruit others to

join the cooperative. The characteristics are:

1. Size of milking herd.

2. “Belonging to the cooperative is an important part

of my identity as a farmer.”

One characteristic was negatively related to

recruiting others to join the cooperative. The more

intensely members agreed that “the cooperative primarily benefits large farms,” the less likely they were

to recruit others.

Two variables were significantly related to participation measures in non-linear fashion—”the cooperative primarily benefits large farms,” and “members

have too little say about how the co-op is run.”

A size bias was found in these analyses. Farmers

from larger farm units were more involved. Farmers

from smaller units were less satisfied and had less time

28
available to participate. Participation is important in

validating or developing farmer understanding and

appreciation of cooperative organization.

Cooperatives may seek to improve their responsiveness by being sensitive to and making accommodations for greater involvement of farmers from smaller units. With greater involvement, the cooperative

and members may identify ways of improving the satisfaction of these farmers and strengthening the cooperative. Study results suggest emphasizing cooperative

principles, the benefits of cooperation, and the importance of participation as a place to start.

Of particular importance, this research demonstrates the continued importance of “cooperative principles,” “beliefs in collective action,” and “personal

identification with the cooperative” as sets of belief

systems that continue to be relevant for members and

that are deepened with cooperative involvement.

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Ford, Thomas R. 1978 Rural U.S.A.: Persistence and

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Lasley, Paul F., Larry Leistritz, Linda M. Lobao, and

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Morrison, Denton and W. Keith Warner. l971.

“Correlates of Farmers’ Attitudes Toward Public

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30
U.S. Department of Agriculture

Rural Business–Cooperative Service

Stop 3250

Washington, D.C. 20250-3250

Rural Business–Cooperative Service (RBS) provides research,

management, and educational assistance to cooperatives to

strengthen the economic position of farmers and other rural

residents. It works directly with cooperative leaders and

Federal and State agencies to improve organization,

leadership, and operation of cooperatives and to give guidance

to further development.

The cooperative segment of RBS (1) helps farmers and other

rural residents develop cooperatives to obtain supplies and

services at lower cost and to get better prices for products they

sell; (2) advises rural residents on developing existing

resources through cooperative action to enhance rural living;

(3) helps cooperatives improve services and operating

efficiency; (4) informs members, directors, employees, and the

public on how cooperatives work and benefit their members

and their communities; and (5) encourages international

cooperative programs. RBS also publishes research and

educational materials and issues Rural Cooperatives magazine.

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discrimination in all its programs and activities on the basis of

race, color, national origin, gender, religion, age, disability,

political beliefs, sexual orientation, and marital or family

status. (Not all prohibited bases apply to all programs.)

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communication of program information (braille, large print,

audiotape, etc.) should contact USDA’s TARGET Center at

(202) 720-2600 (voice and TDD).

To file a complaint of discrimination, write USDA, Director,

Office of Civil Rights, Room 326-W, Whitten Building, 14th and

Independence Avenue, SW, Washington, D.C. 20250-9410 or

call (202) 720-5964 (voice or TDD). USDA is an equal

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