The Similarities Between Volunteer Behavior and Consumer Behavior: A Study of Volunteer Retention

Introduction

By investigating volunteer satisfaction and motivation, nonprofit organizations can increase retention of volunteers. There have been numerous articles related to the recruitment of new volunteers (Culp III, 2009; Culp, Aldenerfer, Allen, Fannin-Holliday, Ford, & Goodwin 2006; Lobley, 2008). However, in order to meet youth development needs, Extension must not only recruit, but also retain its volunteers (Vettern, Hall, & Schmidt 2009). Annual volunteer retention rates for nonprofit organizations nationwide hover around 64% (Corporation for National and Community Service, 2011). Further studies have shown that the investment in a volunteer by an organization can be as much as $13,000 (Eisner, Grimm, Maynard, & Washburn, 2009). These two examples should raise increasing concern for those responsible for administering volunteer programs.

Theoretical Framework

The study reported here considered the ways in which volunteer behavior is analogous to consumer behavior. Specifically, the decision to volunteer has similar motivations to the consumer decision to purchase. Understanding individual elements of these two behaviors, specifically loyalty and satisfaction, can potentially increase volunteer retention.

Volunteers serve as invaluable helpers to many organizations, including 4-H. Conversely, the volunteer experience results in multiple perceived benefits to the volunteers themselves. Several studies have proven that satisfaction with volunteerism leads to significant long-term benefits related to personal well-being, such as lower stress levels, increase in self-esteem, and reduced risk of disease (Wilson & Musick, 1999; Thoits & Hewitt, 2001). While volunteers may not be aware of these inherent benefits during their time of service, many do seek the personal rewards that accompany service to others. Additionally, volunteer perceptions of their experiences, based on the organizational climate, can either create satisfaction or dissatisfaction. Volunteers who are satisfied are likely to become loyal helpers, while dissatisfied volunteers leave the organization in hopes of finding a more fulfilling volunteer opportunity (Clary & Snyder, 1999).

In many ways, consumer behavior seems to mirror this volunteer behavior. The study of consumer behavior attempts to anticipate the reasons consumers choose to buy or not buy products or services. Consumer loyalty, like volunteer loyalty, is dependent upon perceived service quality. This concept, customer satisfaction, is an important antecedent to customer loyalty (Lewis & Soureli, 2006). Service quality is one dimension of satisfaction and may be considered as the accumulated experience of a customer's purchase and consumption experiences (Terry & Israel, 2004). The links between the two concepts of consumer loyalty and volunteer retention is described in this article.

Purpose and Research Questions

The purpose of the research was to determine whether or not volunteer behavior was similar to consumer behavior theory related to loyalty. The following hypotheses were tested in the study:

1. Supportive leadership climate (LC) and volunteer benefits (B) relate positively with volunteer satisfaction (VS).
2. Supportive leadership climate (LC) and volunteer benefits (B) relate positively with volunteer retention (R).
3. Volunteer satisfaction (VS) relates positively with volunteer retention (R).
4. Volunteer satisfaction (VS) mediates the relationship between supportive leadership climate (LC) and benefits from volunteering (B) and volunteer intention to remain (R).

Methods

Participants and Data Collection

Participants included currently registered volunteers in county Extension programs in Florida. A 50% response rate was assumed from a systematic random sampling of 1,200 volunteers selected for the study. A total of 732 volunteers (N=732) took part in the study. The study was approved by the IRB of the academic institution. Using Dillman's survey techniques as a guide, data was collected using both online and mail methods for delivery over an 8-week period. No statistical difference was established between methods of survey delivery.

Measures and Data Analysis

The survey instrument used for the study was based upon the work of McLennan, Birch, Cowlishaw, and Hayes (2009), which explored adding value to volunteer retention. The instrument for the study was adapted by modifying items that were relevant to this specific organization. Participants were asked about their volunteer experiences in the county 4-H program.

Four variables measuring elements of volunteerism comprised the survey's 23 total items, with a scale of 1-5 for responses, clustered into: (1) Leadership Climate; (2) Benefits of Volunteerism; (3) Satisfaction with Volunteering; and (4) Intention to Remain a Volunteer. The variable Leadership Climate consisted of seven scale items (Table 1). Coefficient alpha for the scale was .88, indicating a high degree of internal consistency among measurement items. This provides evidence that the items measure an underlying construct. Benefits from volunteering consisted of seven scale items (Table 2). Coefficient alpha for the scale was .87, indicating a high degree of internal consistency among measurement items. Satisfaction with being a volunteer was measured using six scale items (Table 3). Coefficient alpha for the scale was .85, indicating a high degree of internal consistency among measurement items. Intention to remain a volunteer was measured using three scale items asking volunteers the likelihood they would remain a volunteer in 12 months and 36 months and if they moved to another state. Coefficient alpha for the scale was .86, indicating a high degree of internal consistency among measurement items (Table 4).

A mediator model was used to test the conceptual framework of the study. Simply stated, a mediator is an influence that accounts for the relationship between two variables, a predictor and outcome (Baron & Kenny, 1986). Mediators are considered to be part of the process of "causality" in which a predictor variable influences a mediator and the mediator, in turn, influences the outcome variable. Mediators, similar to third variables, help provide explanation as to how an independent and dependent variable relate. For example, a strong negative relation between a child living in poverty and her school performance can be better explained by the degree to which the child's parents are involved in her schooling. When the mediator, "parents' involvement in schooling," is introduced into the equation and accounted for, the influence of poverty on school performance is reduced to a nonsignificant level. Additionally, a structural equation model (SEM) was used to confirm the strength of the mediator model. All data was analyzed using SPSS version 15.0 and AMOS. AMOS is a type software that allows researchers to assess the relationships among proposed variables, forming a structural equation model based on the results.

Table 1.
Measured Variable: Leadership Climate

Measure	N	Mean	SD
My county keeps me informed about what is going on.	729	4.08	0.99
The county 4-H agent is always fair-minded	732	4.32	1.01
4-H is a safe environment	732	4.64	0.64
I always feel safe when working with other volunteers	732	4.65	0.70
I'm given responsibilities appropriate to my level of skill & experience	732	4.57	0.78
I have opportunities to meet other county 4-H volunteers	723	4.60	0.64
I have never experienced harassment or discrimination in 4-H	720	4.35	1.02
Overall		4.23	0.69

Table 2.
Measured Variable: Benefits to Volunteering

Measure	N	Mean	SD
Volunteering allows me to help others and not dwell on my concerns	729	3.60	1.11
My friends place a high value on 4-H volunteering	732	3.10	1.05
Being a volunteer helps meet my sense of obligation	732	3.62	0.98
I feel I am a valued member of my community	729	3.99	0.83
Being a volunteer adds to my career options	729	3.38	1.21
I feel my social life is more enjoyable since joining 4-H	729	3.44	0.98
Being a 4-H volunteer broadens my network in the community	726	3.57	1.03
Overall		3.57	0.71

Table 3.
Measured Variable: Volunteer Satisfaction

Measure	N	Mean	SD
I would recommend 4-H to other people I know	732	4.65	0.66
I feel that I have been fully accepted into the county 4-H program	732	4.25	0.89
I feel as though I have a significant role to play in 4-H	732	4.24	0.78
4-H continually offers new experiences	732	4.12	0.82
I have an opportunity to learn new things and apply new skills	729	3.83	1.03
Overall		4.39	0.57

Table 4.
Measured Variable: Intention to Remain a Volunteer

Measure	N	Mean	SD
It is likely that I will be a volunteer in 12 months	728	4.38	0.93
It is likely that I will be a volunteer in 3 years	725	4.03	1.03
If I move to another state, I will become a volunteer	720	3.79	0.99
Overall	720	4.07	0.86

Findings

Research Question One

Respondents were asked their perceptions of: (1) the benefits (B) that they received from their volunteer experience; (2) the leadership climate (LC) within the county program; and their satisfaction (VS) with their volunteer experience. Regression results showed that both benefits (β =0.33, ρ <0.001) and leadership climate (β = 0.48, ρ <.001) are positively related and predict volunteer satisfaction. The variables explain 53% of the variance in volunteer satisfaction (Table 5). These findings support hypothesis one of the study.

Research Question Two

Respondents were asked their perceptions of: (1) the benefits (B) that they received from their volunteer experience; (2) the leadership climate (LC) within the county program; and their intention to remain a volunteer (R). Regression results showed that both benefits (β =0.15, ρ <0.001) and leadership climate (β = 0.22, ρ <.001) are positively related and predict volunteer intention to remain. The variables explain 9% of the variance in volunteer satisfaction (Table 5). These findings support hypothesis two of the study.

Research Question Three

Respondents were asked their perceptions of their satisfaction (VS) with their volunteer experience and their intention to remain (R) a volunteer in the program. Regression results showed that volunteer satisfaction (β = 1.07, ρ <0.001) is positively related and predicts volunteer intention to remain. The variable explains 49% of the variance in volunteer intention to remain (Table 5). These findings support hypothesis three of the study.

Research Question Four

Regression results showed that volunteer satisfaction (β=0.40, p <0.001) mediates the relationship between benefits of volunteering (β=0.01, p=0.73) and leadership climate (β=0.04, p=0.36) and volunteer intention to remain. The findings support hypothesis four.

Table 5.
Regression Mediator Model for Volunteer Intention to Remain

Measurement		β	p
Step 1. Mediator Volunteer Satisfaction on Predictors (Leadership Climate & Benefits)	Benefits	0.33	0.00
	Leadership Climate	0.48	0.00
Adjusted R2                               0.53
Step 2. Dependent Variable Intention to Remain, on Predictors (Leadership Climate & Benefits)	Benefits	0.15	0.00
	Leadership Climate	0.22	0.00
Adjusted R2                                0 .09
Step 3. Dependent Variable Intention to Remain, on Predictor Volunteer Satisfaction	Volunteer Satisfaction	0.43	0.00
Adjusted R2                              0.49
Step 4. Dependent Variable Intention to Remain, on Predictors (Volunteer Satisfaction, Leadership Climate & Benefits)	Volunteer Satisfaction	0.40	0.00
	Leadership Climate	0.04	0.36
	Benefits	0.01	0.73
Adjusted R2                              0.61

To confirm this mediator model with a more rigorous statistical procedure, a structural equation model (SEM) utilizing AMOS was developed to evaluate the strength of direct relationships between the leadership climate (LC), benefits from volunteering (B), and volunteer satisfaction (VS). Additionally, SEM was used to test the indirect relationship that is mediated by volunteer satisfaction (Figure 1). The independence model was readily rejected (χ2 = 3567.72 p<0.00). The mediation model provided a good fit for the data (χ2 = 98.02 p<0.00, RMSEA =0.05, Pc=0.41). These findings further support hypothesis four of the study, indicating that the variable of volunteer satisfaction mediates the relationships between leadership climate and volunteer benefits with volunteer retention (Figure 1).

Figure 1.
Structural Equation Model

Conclusions

The research confirms that volunteer intention to remain and consumer behavior related to loyalty are very similar. Specifically, the findings showed that volunteer satisfaction fully mediates the relationship between volunteer retention and the leadership climate within the county program and the benefits that volunteers receive from their volunteer involvement. This is established by the fact that the variables of leadership climate, as well as volunteer benefits, are not statistically significant when the volunteer satisfaction variable is introduced into the model.

These findings are consistent with both common sense observations and implications of much of the literature on volunteerism: being a member of a well-led, inclusive, and harmonious organization is associated strongly with higher levels of both satisfaction and reported intention to remain a volunteer. In fact, 61% of volunteer intention is driven by volunteer satisfaction. Thirty-two percent of volunteer satisfaction is driven by the perceived benefits accrued from volunteering, and 53% of volunteer satisfaction is the result of the leadership and climate created by the Extension agent.

Implications & Recommendations

Recognizing that volunteers are consumers of volunteer opportunities, Extension professionals must shift their focus to increasing volunteer satisfaction. This can be best accomplished by providing more benefits, such as using recognition strategies to showcase the value of the volunteer. Satisfaction can also be ensured by involving loyal volunteers in the recruitment process. Additionally, refocusing commitment to volunteer screening and background verifications will result in a higher level of safety and satisfaction within the Extension organization. Extension personnel can monitor volunteer satisfaction in order to sculpt managerial decisions on the organization's behalf. These initiatives will result in increased volunteer satisfaction and, consequently, higher volunteer retention rates.

Based upon the findings of the study reported here, Extension agents working with volunteers need to focus on volunteer practices that increase volunteer satisfaction by:

• Clearly and continuously communicating to volunteers the significant role they play in a young person's life.
• Providing new and challenging experiences and opportunities for existing volunteers.
• Ensuring that new and existing volunteers feel accepted by all members of the Extension office.

Findings from the study can serve as encouragement for Extension professionals to actively pursue initiatives that refocus energies upon the creation of volunteer-friendly environments, enhancement of leadership skills, and the expansion of volunteer benefits.

References

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