Strategic Human Resources Management in Nonprofit Organizations

Abstract

This study explores the prevalence of strategic human resources management (HRM) practices in nonprofit organizations as well as the organizational and contextual determinants. Based on survey data collected from 229 charitable nonprofit organizations, we find that organizations that are larger in size, technologically savvy, and dependent on the work of independent contractors all appear to be more likely to implement strategic HRM practices. Local affiliates of national organizations are more likely to implement strategic HRM practices. In addition, younger organizations, educational organizations, and organizations that do not have dedicated HR staff are also more likely to implement strategic HRM practices. Although dependence on volunteer labor has no significant effect on the outcome, further analysis indicates that volunteer-dependent organizations differ from others in several aspects of strategic HRM.

Keywords

strategic human resources management nonprofit organizations charitable organizations

The nonprofit sector in the United States continues to grow as we approach the end of the first decade of the twenty-first century. Constituting a significant part of the national economy, the sector today accounts for 5% of gross domestic product (GDP), 8% of wages and salaries, and 10% of employment (Wing, Pollak, Blackwood, & Lampkin, 2008). Nonprofit organizations rely on the dedicated work of their employees to achieve their social missions, and yet they often experience difficulties in recruiting and retaining top-quality workers (Ban, Drahnak-Faller, & Towers, 2003). Given the importance of the human resources (HR) functions to nonprofit organizations, the processes of attracting, selecting, and retaining staff require greater attention from practitioners and scholars (Watson & Abzug, 2004).

In recent years, leaders in the nonprofit sector are increasingly aware of the importance of nonprofit capacity building and organizational effectiveness (e.g., Kearns, 2004). Meanwhile, they have begun to realize that “doing good” is not good enough and that knowledge of best business practices may be helpful in improving organizational effectiveness (Cunningham, 1999). Within this context, there have been strong pressures on nonprofit managers to reevaluate their human resources management (HRM) approaches and to integrate HRM with the missions of their organizations in a strategic manner. Accordingly, growing scholarly attention has been paid to strategic HRM in nonprofit organizations (e.g., Akingbola, 2006; Kong & Thomson, 2006; Lynn, 2003; Pynes, 2004). Strategic HRM integrates HRM practices with the strategic purposes of the organization.

Notwithstanding the considerable promise of the concept for improving organizational performance, the nascent body of literature on strategic HRM in nonprofit organizations suffers from an important limitation: the lack of empirical data. Indeed, this limitation is part of a broader issue in the existing research on HRM in nonprofit organizations. Despite the publication of numerous prescriptive studies about recommended HRM practices, there is surprisingly scant empirical evidence describing how nonprofit organizations have used these practices and the factors that influence the adoption of these practices (Ridder & McCandless, 2010). The existing empirical studies focused on specific HRM practices such as executive compensation (e.g., Carroll, Hughes, & Luksetich, 2005; Gray & Benson, 2003) and recruitment and retention (e.g., Ban et al., 2003; Nickson, Warhurst, Durron, & Hurrell, 2008; Watson & Abzug, 2004).

This study attempts to address this limitation by exploring the prevalence of strategic HRM practices as well as their organizational and contextual determinants. Two research questions guide the development of this study: What current strategic HRM practices are used in nonprofit organizations? What organizational and contextual factors are associated with the prevalence of such practices? Based on survey data of 229 charitable organizations in Maricopa County, Arizona, we find that organizations that are larger in size, technologically savvy, and dependent on the work of independent contractors all appear to be more likely to implement strategic HRM practices. Local affiliates with national organizations are more likely to implement strategic HRM practices. In addition, younger organizations, educational organizations, and organizations that do not have dedicated HR staff are also more likely to implement strategic HRM practices. Although dependence on volunteer labor has no significant effect on the outcome, further analysis indicates that volunteer-dependent organizations differ from others in several important aspects of strategic HRM.

The rest of the article is organized as follows. We begin with a review of relevant literature that leads to our main hypotheses on factors affecting the adoption of strategic HRM practices by nonprofits. The third and fourth sections describe the methodology and present findings respectively. We conclude with a discussion about the implications and limitations of the study.

Literature Review

Traditionally treated as merely an administrative function, HRM is now recognized as a vital contributor to organizational success (Phillips, 1996). Highlighting the value of integrating HRM practices with the strategic objectives of the organization (Daley, Vasu, & Weinstein, 2002; Delery & Doty, 1996), strategic HRM focuses on “designing and implementing a set of internally consistent policies and practices that ensure a firm’s human capital contributes to the achievement of its business objectives” (Huselid, Jackson, & Schuler, 1997, p. 172). Delery and Doty (1996) identified seven core strategic HRM practices: internal career opportunity, formal training systems, appraisal measures, profit sharing, employment security, voice mechanisms, and job definition. Research shows that when organizations employ such practices, they are more able to achieve their goals and objectives (Daley et al., 2002). As part of the movement toward strategic HRM, there has also been a call for a systematic approach to attracting and retaining talented, committed employees (e.g., Berger & Berger, 2004; Buckingham & Vosburgh, 2001; Morton, 2004). Morton (2004), for example, presented a talent management strategy that covers eight categories of initiatives: recruitment, retention, professional development, leadership/high potential development, performance management, feedback/measurement, workforce planning, and culture.

In the context of public and nonprofit sectors, strategic HRM has also been increasingly regarded as essential to organizational performance (e.g., Condrey, 1998; Farazmand, 2004; Perry & Mesch, 1997). In the face of a constantly changing resource and institutional environment, the contributions of HRM functions and strategies to the mission and future direction of public and nonprofit organizations are too important to ignore: public and nonprofit organizations must think strategically, and HR departments must take a proactive role in guiding and supporting agency efforts to meet the changing demands of their environment (Lynn, 2003; Pynes, 2004).

However, evidence shows that HRM in the nonprofit sector might be different in many ways from its counterparts in the private and public sectors. Without a clear financial bottom line, nonprofit organizations rely on the mission to attract resources (including employees and volunteers) and guide decision making (Drucker, 1989). Mission statements are recognized as a strong management tool that can motivate employees and keep them focused on the organization’s purpose (Ban et al., 2002; Brown & Yoshioka, 2003; Kim & Lee, 2007). Within this context, financial incentives and controls become less effective, as many individuals in nonprofits regard money as a means to achieve larger purposes and not as an end in itself, either personally or organizationally (Mason, 1996). Nonprofit managers are therefore inclined to use strategies that draw on employees’ intrinsic motivations rather than on the extrinsic motivation of money (Brown & Yoshioka, 2003; Nickson et al., 2008). There is accumulating empirical evidence that nonprofit jobs provide more satisfaction and intrinsic rewards than those in business or government (e.g., Mirvis, 2006; Mirvis & Hackett, 1983).

In light of the unique nature of the nonprofit sector and the tremendous potential of strategic HRM to achieve mission and enhance performance, it is imperative that we empirically explore the prevalence of the adoption of strategic HRM practices in nonprofit organizations, as well as the organizational and contextual factors that influence it. Existing literature suggests that approaches to HRM are influenced by the context in which an organization operates and the strategy which it is pursuing (Tyson, 1997; Legge, 1995; Schuler & Jackson, 1987; Parry, Kelliher, Mills, & Tyson, 2005). Accordingly, we posit that strategic HRM practices are influenced by the following organizational and contextual factors.

Organizational Size

The effect of organizational size on HRM practices is well documented (e.g., Ng & Maki, 1993; Wagar, 1998). The pressures for larger organizations to invest more in HRM come from both resource and institutional dimensions. In terms of the resource environment, larger organizations are more likely to have the necessary resources and experience to make considerable investment in a more sophisticated system of HRM. Ban et al. (2003) found that limits imposed by funders constrained nonprofits from devoting resources to management functions including HR. Many smaller organizations reported that funders want their money to go to direct service activities rather than administrative staff. In terms of the institutional environment, institutional theory suggests that the size of an organization indicates its visibility and level of attention from institutional stakeholders (Goodstein, 1994). As an organization grows in size, it becomes more visible and is under growing pressure to gain legitimacy, and therefore needs to adopt more sophisticated and socially responsive HRM practices (Jackson & Schuler, 1995). Following these lines of reasoning, we expect that larger organizations will implement more extensive strategic HRM practices.

Hypothesis 1: Organizational size is positively associated with the extent to which an organization adopts strategic HRM practices.

Affiliation With an Umbrella Organization

A significant number of nonprofit organizations operating in the United States are affiliates of national nonprofits, organized as either branch offices or franchises (Oster, 1996). It is estimated that at least 20% of all nonprofit organizations belong to a national (or umbrella) association. Most of the local nonprofits are incorporated separately from the national organization (Hodgkinson, Weitzman, Noga, & Gorski, 1993; Young, 2001). Examples of such organizations include the United Way organizations, YMCAs, Boys and Girls Clubs, and Goodwill Industries, and so on.

Grossman and Rangan (2001) identified two important benefits or advantages of belonging to a national (or umbrella) association. First, national affiliation enhances an affiliate’s ability to attract volunteers and donors through a strong brand name, and facilitates the sharing of best practices and emerging trends. Second, national affiliation allows for the economies of scale by pooling resources to gain franchise-wide cost advantage in performing certain functions (e.g., accounting, marketing, and so on). Within the context of HRM, these benefits seem to suggest that the affiliation with a national organization may foster the diffusion of standardized HRM practices: it is probably more cost effective to implement standardized HRM practices throughout the franchise network as a larger number of entities undertaking the practices will reduce the average cost per employee (Whitfield, 2000).

Its benefits notwithstanding, this “cookie-cutter” or one-size-fits-all approach to HRM might reduce a local affiliate’s incentive to adopt strategic HRM practices. Ban and colleagues (2003) found that some organizations relied on umbrella organizations that manage HR and other business functions for small nonprofits. As one respondent in their study explained, “The umbrella organization is an incubator for nonprofits. For a fee, you can buy back-office services and piggyback off its nonprofit status. . . . The organization can focus on what it needs to do instead of all the other stuff” (Ban et al., 2003, p. 136). As such, belonging to an umbrella organization might result in the use of “cookie-cutter” HRM policies that are not responsive to the strategic needs of local affiliates.

Hypothesis 2: Affiliation with an umbrella organization is negatively associated with the extent to which an organization adopts strategic HRM practices.

Dependence on Government Funding

There appears to be two contrasting effects associated with government grants and contracts. On one hand, Akingbola (2004) found that the increased dependence on government funding affects recruitment and selection in that nonprofits are increasingly recruiting more of their staff on temporary contracts. Moreover, nonprofit agencies that are dependent on the government for most of their revenue are reluctant to be seen as “spending too low a proportion of resources on direct services and too high a proportion on administration, staff development and internal communications” (Cunningham, 1999, p. 22).

On the other hand, the recent trend of professionalization among those nonprofit organizations that receive government funding (Salamon, 1995) might lead to a more strategically proactive approach to managing HR. Government agencies often establish sophisticated regulatory and procedural requirements as well as rigorous program-evaluation systems for their contracts (Krashinsky, 1990; Siegel, 1999). To implement the contracts in compliance with these complex requirements, nonprofit contractors must rely on experienced employees who have more professional and technical skills (Frumkin & Kim, 2002; Pynes, 2004; Smith & Lipsky, 1993). Within this context, establishing a more sophisticated HRM approach such as strategic HRM in an organization might lead to successful funding applications and help maintain its relationship with funding agencies by showing that it can deliver the required quality of service (Cunningham, 1999).

In light of the two competing effects associated with government grants and contracts, we propose that reliance on government funding has influence on the use of strategic HRM practices, though the exact nature of the relationship between the two has yet to be determined.

Hypothesis 3: Dependence on government funding is associated with the extent to which an organization adopts strategic HRM practices.

Dependence on the Work of Independent Contractors

In the United States today, nearly one in three workers are in nonstandard jobs, including on-call work and day labor, temporary-help agency employment, independent contracting, other self-employment, and part-time work in conventional jobs (Kalleberg, Reskin, & Hudson, 2000, p. 256; Knoke & Yang, 2003). Independent contracting in particular has become an increasingly popular form of nonstandard employment in recent years (Connelly & Gallagher, 2006). As independent contractors are predominantly self-employed, they provide the organization with a means of obtaining specialized worker capabilities while retaining employment flexibility and controlling cost (Davis-Blake & Uzzi, 1993; Gallagher & Sverke, 2005).

The increased use of independent contractors has important implications for strategic HRM. Knoke and Yang (2003) discussed two alternative HRM strategies: a contingent workforce strategy of hiring both permanent and contingent employees, and an employability strategy of enhancing their employees’ human capital. Organizations adopting a contingent workforce strategy are usually reluctant to invest in improving their nonstandard employees’ job skills, as investments in improved human capital do not necessarily lead to enhanced productivity in the absence of a long-term employment relationship. By contrast, organizations following an employability strategy are more willing to upgrade the job skills of their employees, despite the absence of a long-term employment relationship.

Although it is difficult to determine the exact nature of the association between the use of independent contractors and the implementation of the above two HRM strategies due to the scarcity of empirical evidence, we argue that an organization that uses independent contracting will likely implement both strategies: the contingent workforce strategy in managing independent contractors, and the employability strategy in managing permanent employees. On one hand, independent contracting allows the organization to acquire specialized skills and knowledge (Gallagher, 2002). On the other hand, the use of independent contractors allows the organization to outsource its peripheral functions and focus strategically on investing in permanent employees who are instrumental to its core functions and competencies (Connelly & Gallagher, 2006). Taken together, this combined strategy not only provides the organization with greater staffing flexibility, but also enables the organization to free up valuable resource for improving the skills and commitment of permanent employees. It thus seems reasonable to expect that the use of independent contractors will have a positive effect on the prevalence of strategic HRM practices in an organization. Therefore, we propose the following:

Hypothesis 4: Dependence on the work of independent contractors is positively associated with the extent to which an organization adopts strategic HRM practices.

Use of Information Technology

Although often characterized as a “soft” or nontechnical profession, the HRM function has been on the forefront of integrating information technology in an organization (Lengnick-Hall & Moritz, 2003; Townsend & Bennett, 2003). There is accumulating evidence that information technology helps achieve strategic HRM by relieving HR professionals from the burden of administrative tasks to being a strategic partner to the organization (Bell, Lee, & Yeung, 2006; Gardner, Lepak, & Bartol, 2003; Haines & Lafleur, 2008). In public and nonprofit sectors, information technology is regarded by some as “the central intelligence of strategic human resource management,” providing “a strategic tool for collecting, processing, and managing strategic data and information” that facilitates organizational decision making for managing HR (Farazmand, 2004, p. 11). As such, information technology changes the way work is organized and managed, and therefore challenges public and nonprofit organizations to recruit and hire people with a new set of skills and orientations in response to these changes (Pynes, 2004).

More specifically, information technology offers an organization a number of advantages in recruiting job candidates, such as broader access to job candidates; improved ability to target specific audience; reduced cost of placing job announcements; faster speed; absence of middlemen; convenience; better quality of candidates; and less paperwork; among others (Kay, 2000; Singh & Finn, 2003). For job seekers, the organization’s technology adeptness increases its attractiveness (Dicke & Ott, 2003). Besides recruitment, information technology also enables nonprofit organizations to reward and motivate current employees by creating opportunities for continuous learning and career development. As Saidel and Cour (2003) point out, “While technology demands new skills, the introduction of updated technology also frequently creates new positions. From Web site administrators to help desk professionals, nonprofits may develop new jobs that current employees can fill” (p. 13). Thus, employees are able to move laterally into more challenging jobs and even develop a new career path.

All nonprofit organizations are not equally ready for the use of information technology. Extant research indicates that substantial variation exists across nonprofit organizations in the adoption of such information technology as computers and the Internet (e.g., Corder, 2001; Hanna, 1995). This variation might result from the lack of resources necessary for nonprofits to invest in information technology, the lack of organizational discretion in purchasing and choosing technology, among others (Corder, 2001). If, as its advocates suggest, information technology serves as a valuable facilitator for strategic HRM, then we should be able to observe that strategic HRM practices are more prevalent among those technologically savvy organizations.

Hypothesis 5: The use of information technology in an organization is positively associated with the extent to which it adopts strategic HRM practices.

Data and Method

This study is part of a larger research project designed to examine the compensation and HR practices in nonprofit charitable organizations. In June 2004, 1,119 nonprofit charitable organizations in Maricopa County, Arizona, were mailed a letter inviting them to participate in the study. The mailing list was derived from the National Center for Charitable Statistics (NCCS) core data file. The NCCS is a national repository of data on the nonprofit sector in the United States; its core data file is comprised of charitable organizations and contains information obtained from form 990, the annual financial disclosure to the IRS.

We limited the mailing list by applying the following study selection criteria: organizations had to be located within Maricopa County and had to have at least one paid employee. Hospitals, foundations, and institutions of higher education were eliminated from the study and from the mailing list, due to the differences in their compensation practices and the availability of other compensation information for these specific types of organizations. All other classifications of charitable organizations were included in the study. Organizations that met the selection criteria comprised the final mailing list of 1,119 organizations. Data were collected primarily through an online survey instrument. A letter addressed to the HR director was mailed to these organizations. The letter introduced the study and included a website address where the survey could be completed online. Instructions were also given for downloading or requesting a paper copy. A follow-up postcard was sent 2 weeks after the survey was mailed, reminding participants to fill out and return the survey. A total of 229 eligible organizations completed the survey (a 20.5% response rate).

As this fairly low response rate can often produce biased samples, we performed checks to find out whether our sample differs from the state and national data in potentially significant ways. Of the 229 participating organizations in the present sample, 79 (34%) were human service organizations, 32 were health organizations (14%), 25 were education and research organizations (11%), and 18 were arts organizations (8%), among others. By comparison, the NCCS core data file for 2004 reports the following breakdowns of registered public charities in Maricopa County: human service organizations, 28%; health organizations, 10%; education and research organizations, 15%; and arts organizations, 9%. According to an analysis of the national data during the same time period, the most common categories of reporting public charities are human services (35%); education and research (16%); health (15%); and arts, culture, and humanities (11%; see Weitzman & Jalandoni, 2002). Although the overall distribution pattern of the current sample appears to be consistent with those of the county and national data, it should be noted that education and research organizations are slightly underrepresented, whereas human service and health organizations are overrepresented, in the present sample. This difference might be partially due to the relatively small size of the sample, where the breakdowns of organizations might vary significantly with the addition (or reduction) of a few organizations in any particular category.¹

Strategic HRM Practices

Our variable of interest is the prevalence of strategic HRM practices. We constructed this variable as follows. First, we created a strategic HRM Index, which included a total of 13 practices derived from the existing literature (Berger & Berger, 2004; Morton, 2004; see Table 1 for a complete list of items). The respondents were asked to indicate the extent to which their organizations used these strategic HRM practices on a scale of 1 to 7; 1 being not used at all to 7 being used to a very high degree. Table 1 lists the strategic HRM practices and the mean scores for all the organizations included in our study.

Table 1.

Strategic Human Resources Management Practices in Nonprofit Organizations

Strategic human resources management practice	M ^a
Use the mission and values of the organization to attract employees	5.56
Encourage and allow flexibility in work schedule and working arrangements	5.7
Have internal communication practices that consistently reach all employees with valuable information	5.36
Use recruitment practices that might include recruiting college graduates and targeting experienced individuals	4.14
Engage in practices to retain employees such providing competitive wages and bonuses	4.60
Provide professional development opportunities for employees	4.78
Specifically target high quality employees for leadership development	4.67
Evaluate employees through multiple performance assessment strategies such as supervisor assessment, peer evaluations, and customer feedback	4.10
Link indicators of effective employee performance to organizational objectives	4.68
Provide opportunities for systematic employee feedback through surveys, exit interviews, etc.	4.06
Conduct planning related to workforce needs	4.60
Communicate and reinforce a widely recognized corporate culture	4.80
Practice workforce diversity initiatives	5.00

Seven-point scale with 1 being not at all to 7 being used to a very high degree.

As shown in Table 1, some of the strategic HRM practices were widely adopted by the responding organizations. These practices include “encourage and allow flexibility in work schedule and working arrangements” (5.7), “use the mission and values of the organization to attract employees” (5.56), and “have internal communication practices that consistently reach all employees with valuable information” (p. 5.36). By contrast, a few other practices were less widely adopted. These practices include “provide opportunities for systematic employee feedback through surveys, exit interviews, etc.” (4.06), “evaluate employees through multiple performance assessment strategies such as supervisor assessment, peer evaluations, and customer feedback” (4.10), and “use recruitment practices that might include recruiting college graduates and targeting experienced individuals” (4.14).²

Second, we conducted a principal component factor analysis to determine whether or not there was a large principal component in these items. The results revealed two factors, with eigenvalues of 5.39 and 2.75. To determine which factors are meaningful, we considered two criteria: the Kaiser test, which suggests only factors with an eigenvalue of 1.0 or greater are meaningful; and the Scree test, which uses a graphical method and keeps the factor up until the line becomes flat or flatter. According to the Kaiser test, both Factors 1 and 2 would be worth keeping. In contrast, the result of the Scree test clearly showed that only Factor 1 was worth keeping. For the purpose of our study, we decided to go with the Scree test and keep Factor 1 only. We then calculated the index score using Factor 1 and used the calculated index as the measure of our dependent variable.

Independent Variables

Organizational size

This variable is measured by the total number of full-time employees (35 or more hr per week) on the organizational payroll as of June 2004.³ The number of full-time employees in our sample ranges from as few as 1 and as many as 600. Because this variable is substantially nonnormal, logarithmic transformation is applied to this variable.

Dependence on government funding

This variable is measured by the percentage share of the average government grants and contracts in relation to average total revenues in the year prior to the survey.

Dependence on contractors

This variable is measured by the percentage of independent contractors on an organization’s payroll.

National affiliation

This variable indicates whether an organization is affiliated with a national organization. It is defined as a binary variable and takes on two values: 1, indicating that an organization was part of a larger (“parent”) organization; otherwise 0.

Use of information technology

This variable examines the extent to which an organization’s staff used information technology. The respondents were asked to indicate what percentage of your staff currently uses computers on a daily basis (from 0 to 100%), uses an email account provided by the organization (from 0 to 100%), and what percentage of computers have Internet connections (from 0 to 100%). The scores were then averaged to obtain a single measure for this variable.

Control Variables

Organizational age

This variable is measured by the difference between the year of 2004 and the year when a given nonprofit organization was founded. The youngest organization in our sample was 1-year-old, whereas the oldest organization was 112 years old. Logarithmic transformation is applied to this variable due to the substantially nonnormal nature of the variable.

Dependence on volunteer labor

This variable is measured by the percentage of total work in the organization that was done by volunteers.

Industry of operation

The nonprofit sector is diverse and ranges from small local community groups to large international organizations. Charitable organizations alone include the subsectors of arts and culture, education and research, health care, and social services, among others. Each subsector also has unique characteristics that drive HR tradition and practice (Watson & Abzug, 2004). More specifically, industry is controlled by coding respondents according to four broad industries.

Arts and culture, education and research, health services, and human services

Each industry is defined as a binary variable.

HR staff

This variable is measured by the total number of dedicated HR positions in a given organization. The descriptive statistics shows that the dominant majority of the responding organizations (79.9%) do not have dedicated HR staff. Among those organizations that have dedicated HR staff (20.1%), the number of HR staff ranges from 1 to 6.

Findings

Correlation Analysis

Table 2 provides the means and standard deviations of all variables and the correlation matrix.

Table 2.

Descriptive Statistics and Correlation Matrix

	Observations	M	SD	1	2	3	4	5	6	7	8	9	10	11	12	13
1. Strategic HRM Index	229	4.77	1.12	1.00
2. Org. age	229	27.4	23.8	0.03	1.00
3. Arts and culture	229	0.08	0.27	−0.11	0.02	1.00
4. Education and research	229	0.11	0.31	0.07	0.13	−0.10	1.00
5. Health services	229	0.14	0.35	0.08	−0.08	−0.12	−0.14*	1.00
6. Human services	229	0.34	0.48	0.01	0.12	−0.21*	−0.25*	−0.29*	1.00
7. Size of staff	229	40.98	82.14	0.26*	0.45*	−0.22*	0.06	0.10	0.17*	1.00
8. Govt. funding (%)	229	23.84	32.03	0.12	0.08	−0.08	−0.08	0.29*	0.02	0.35*	1.00
9. Contractors (%)	228	14.47	22.42	0.09	−0.15*	0.04	−0.09	0.03	−0.04	−0.29*	−0.03	1.00
10. National affiliation	229	0.27	0.45	0.15*	0.16*	−0.07	0.10	0.07	0.01	0.03	−0.07	0.03	1.00
11. Info. technology	229	84.34	22.48	0.10	−0.02	0.10	−0.06	−0.03	−0.07	−0.16*	0.05	0.14*	0.04	1.00
12. HR staff	229	0.29	0.72	0.05	0.26*	−0.05	0.05	0.24*	−0.04	0.57*	0.17*	−0.16*	−0.02	−0.08	1.00
13. Work done by volunteers (%)	229	20.57	25.45	−0.10	−0.12	0.03	−0.12	−0.11	−0.03	−0.37	−0.33*	0.04	0.11	0.02	−0.18*	1.00

Associations are significant at 5%.

A brief discussion of the relationship between independent variables is appropriate to ascertain how they might work together. There is a strong and positive correlation between staff size and number of dedicated HR staff (r = .57, p < .01) recognizing the obvious relationship between these variables. There is also a positive yet rather weak correlation (r = .35, p < .01) between percentage of government funding and organizational size, suggesting that larger organizations tend to rely on a larger percentage of their funding from the government. Similarly, there is a positive yet weak correlation (r = .29, p < .01) between percentage of government funding and health services organizations.

Multiple Regression Analysis

The dependent variable in this study—the prevalence of strategic HRM practices—is a continuous variable measured by a Strategic HRM Index. We employ the weighted least squares (WLS) regression model to analyze the data in the presence of heteroskedasticity.⁴ The results are presented in Table 3.

Table 3.

Factors Associated with the Prevalence of Strategic Human Resources Management Practices: WLS Regression Analysis

Independent variables	Coefficient	Beta
Size of staff	0.370** (0.051)	0.69
Percentage of government funding	−0.001 (0.002)	−0.02
Percentage of contractors	0.715** (0.230)	0.20
National affiliation	0.301** (0.104)	0.18
Information technology	0.007** (0.002)	0.18
Percentage of work done by volunteers	0.002 (0.002)	0.05
Organizational age (log)	−0.203** (0.061)	−0.23
Arts and culture	−0.056 (0.265)	−0.01
Education and research	0.401* (0.155)	0.19
Health services	0.016 (0.172)	0.01
Human services	−0.027 (0.133)	−0.02
HR staff	−0.260** (0.077)	−0.26
Constant	−1.084** (0.315)
Observations	228
R ²	0.278
Adjusted R²	0.238
F	6.90
p	0.000

Note: Robust standard errors in parentheses.

p < .1. **p < .05. ***p < .01.

Hypothesis 1 maintains that organizational size is positively associated with the use of strategic HRM practices. Consistent with our prediction, this variable has a positive and significant coefficient in the model, indicating that a larger organization (i.e., an organization with more full-time paid staff) tends to demonstrate a higher level of prevalence in the adoption of strategic HRM practices.

Hypothesis 2 predicts that an organization’s affiliation with an umbrella organization is negatively associated with the extent to which it adopts the strategic HRM practices. Contrary to our prediction, the variable national affiliation has a positive and highly significant coefficient in the model, suggesting that an organization that is affiliated with an umbrella organization tends to demonstrate a higher use of strategic HRM practices.

Hypothesis 3 examines the effect of dependence on government funding on the adoption of strategic HRM practices. It posits that an organization’s dependence on government funding is associated with the extent to which it adopts the strategic HRM practices. The variable dependence on government funding does not have a significant coefficient, thus providing no support to our prediction.

Hypothesis 4 examines the effect of independent contractors on the adoption of strategic HRM practices. It posits that an organization’s dependence on the work of independent contractors is positively associated with the extent to which it adopts the strategic HRM practices. Consistent with our prediction, the variable dependence on contractors has a positive and highly significant coefficient in the model, suggesting that the use of independent contractors is related to a higher level of prevalence in the adoption of strategic HRM practices.

Hypothesis 5 examines the effect of the use of information technology on the adoption of strategic HRM practices. Conforming to our prediction, the variable use of information technology has a positive and highly significant coefficient in the model, suggesting that the use of information technology in the organization is positively associated with the extent to which an organization adopts the strategic HRM practices.

Among the control variables, organizational age is found to be related to a lower use of strategic HRM practices. One of the industry dummies—education—has a significant coefficient in the model, suggesting that organizations operating in the education industry seem more likely to adopt strategic HRM practices. In addition, the number of dedicated HR staff is found to be negatively related to the adoption of strategic HRM practices.

Because the coefficients in the Beta column are all in the same standardized units, we can compare these coefficients to assess the relative impact of each of independent variables. For example, “size of staff” has the largest Beta coefficient, .69, and “HR staff” has the second largest Beta, .26 (in absolute value). Thus, a one standard deviation increase in size of staff leads to a 0.69 standard deviation increase in predicted Strategic HRM Index, with the other variables held constant. And, a one standard deviation increase in HR staff, in turn, leads to a 0.26 standard deviation decrease in predicted Strategic HRM Index with the other variables in the model held constant. Next, a one standard deviation increase in the organizational age, leads to a 0.23 standard deviation decrease in predicted Strategic HRM Index, whereas a one standard deviation increase in the percentage of independent contractors leads to a 0.20 standard deviation increase in predicted Strategic HRM Index.

Finally, we conduct Chow tests to check if the coefficient estimates in Table 3 are the same in different subgroups of the sample (defined by national affiliation, independent contracting, organizational size, and dependence on volunteer labor). Although dependence on volunteer labor—one of our control variables—has an insignificant coefficient in Table 3, our further analysis shows that volunteer-dependent organizations (i.e., organizations where more than 10% of work was done by volunteers) actually develop different patterns of strategic HRM practices than others.⁵ The regression results for the subgroups are presented in Table 4.

Table 4.

Effects Associated with the Prevalence of Strategic HRM Practices (Volunteer-Dependent Organizations vs. Others)

	Volunteer-dependent organizations (more than 10% of work done by volunteers)	Other organizations (10% or less of work done by volunteers)
Size of staff	0.508*** (0.097)	0.397*** (0.067)
Percentage of government funding	−0.010** (0.005)	0.001 (0.002)
Percentage of contractors	1.277*** (0.349)	0.452 (0.311)
National affiliation	0.146 (0.187)	0.315** (0.133)
Information technology	0.001 (0.004)	0.009*** (0.003)
Percentage of work done by volunteers	0.000 (0.003)	0.015 (0.019)
Organizational age (log)	−0.156 (0.118)	−0.257*** (0.076)
Arts and culture	0.194 (0.415)	−0.179 (0.337)
Education and research	0.598** (0.282)	0.287 (0.201)
Health services	0.379 (0.249)	−0.326 (0.245)
Human services	0.09 (0.178)	−0.123 (0.191)
HR staff	−0.837*** (0.183)	−0.157* (0.092)
Constant	−0.76 (0.504)	−1.190*** (0.434)
Observations	93	135
R ²	.373	.337

Note: Robust standard errors in parentheses.

p < .1. **p < .05. ***p < .01.

Based on the results, the percentage of contractors is positively and significantly associated with the prevalence of strategic HRM practices only in volunteer-dependent organizations. Similarly, dependence on government funding is negatively and significantly associated with the prevalence of strategic HRM practices only in volunteer-dependent organizations. On the other hand, however, national affiliation and use of information technology are significant only in organizations that are not volunteer dependent. Organizational size (size of staff) remains positive across both groups.

Discussion and Conclusions

This study contributes to the existing literature by providing rare empirical evidence on the prevalence of strategic HRM in nonprofit organizations and the organizational and contextual factors that are associated with such practices. Major findings from the study indicate that there exists substantial variation in the adoption of strategic HRM practices by nonprofit organizations. More specifically, organizations that are larger in size (i.e., have more full-time paid staff), technologically savvy, affiliated with national organization, and dependent on the work of independent contractors all appear to be more likely to implement strategic HRM practices. In addition, younger organizations, educational organizations, and organizations that do not have dedicated HR staff are also more likely to implement strategic HRM practices.

Some of the findings require further discussion. The finding that older organizations are less likely to adopt strategic HRM practices is consistent with the organizational ecology theory and research, which suggests that older organizations may be more inertial, thus making it more difficult to implement organizational change and innovation (e.g., Carroll & Teo, 1996; Hannan & Freeman, 1984). Interestingly, and perhaps counterintuitively, having dedicated HR staff is found to be negatively associated with the adoption of strategic HRM practices. This finding suggests that having dedicated HR staff does not facilitate adopting strategic HRM practices. A possible explanation is that, in organizations without dedicated HR staff, it is often the chief executive or a member of the top management team who is in charge of the HR function, which allows the organization to implement strategic changes to its HRM practices in a timely manner; by contrast, HR professionals in organizations with a more formalized HR department may not be strategic decision makers, but primarily engaged in administrative HR functions such as payroll processing and record keeping.

Our additional analysis indicates that volunteer-dependent organizations may develop different patterns of strategic HRM practices than other organizations. This finding corroborates with earlier observations that volunteers differ from the paid employees in many aspects such as job attitudes (Clary & Snyder, 1999; Liao-Troth, 2001; Pearce, 1983, 1993). Certain strategic HRM practices (e.g., monetary compensation and professional development) that are appropriate for paid employees might not be feasible for the management of volunteers. Moreover, volunteer dependence might moderate the effects of other context factors on strategic HRM. For example, national affiliation has no impact on the adoption of strategic HRM practice among volunteer-dependent organizations, though it serves as a valuable facilitator for strategic HRM among other organizations. One possible explanation is that, given their stronger ties with the community, volunteer-dependent organizations might have a stronger commitment to their community-based character (Guo, 2007) and therefore might be more hesitant to follow the recommendation of national umbrella associations to implement strategic HRM practices. Further investigation is needed to determine whether this is actually the case.

Several important lessons for nonprofit practitioners can be drawn from our findings. First, if an organization’s technology savvyness facilitates the transition of the HR function from routine administrative tasks to a value-adding strategic partner, then nonprofit leaders may consider introducing and expanding the use of information technology in their organizational practices before the adoption of strategic HRM practices. Second, the positive relationship between national affiliation and strategic HRM revealed in our study carries an encouraging message: rather than hindering the ability of local affiliates to adopt innovative HRM practices in response to their strategic needs, national affiliation might actually facilitate innovation diffusion while offering association-wide cost advantage. National umbrella associations therefore should be encouraged to realize more of their potential in this area. Third, our finding suggests that the use of independent contractors is associated with the adoption of strategic HRM practices in an organization, as it allows the organization to outsource its peripheral functions and focus on implementing strategic HRM practices in its core functions. Finally, the observation that having dedicated HR staff is negatively associated with the adoption of strategic HRM practices serves a reminder for nonprofit leaders: if they expect the HR function to contribute to organizational strategy and performance, then efforts should be made to include HR staff in the organizational decision-making process.

The limitations of the study suggest several avenues for future research. First, although our results suggest the association between various contextual factors and the prevalence of strategic HRM practices, the cross-sectional nature of the survey data precludes causal interpretations of these relationships. Future research should collect longitudinal data so as to examine lagged effects of organizational and contextual factors. Second, all the sampled organizations in our study operate in Maricopa County, Arizona, a typical urban, metropolitan setting; therefore we have to use caution when generalizing findings and applying them into organizations of different settings (e.g., a suburban or rural area). Third, the fact that our model produced only a small level of explained variance (24%) suggests the possibility that some important factors might have been omitted. For example, there is a great amount of discussion about how organizational culture influences performance in public organizations (e.g., Rainey, 2003). The effect of organizational culture on certain HR practices (e.g., employee retention) has also been well documented (e.g., Sheridan, 1992). Future research in this direction might offer additional insights on the relationship between organizational culture and the implementation of strategic HRM. Finally, due to the scope of the article and the limitation of our data, we have not examined the possible relationship between the adoption of strategic HRM practices and organizational performance. Prescriptive studies have suggested a positive relationship between strategic HRM and organizational performance, yet the empirical test is lacking, and it is unclear which mechanisms are involved in translating strategic HRM practices into increased organizational effectiveness. One challenge associated with this line of research, of course, is the lack of consensus on how to understand and measure nonprofit performance (Forbes, 1998; Herman & Renz, 1999). In view of this challenge, future research should consider empirically testing the link between strategic HRM practices and various objective (e.g., fiscal efficiency) and subjective measures (e.g., stakeholder perceptions; Herman & Renz, 1997) of organizational performance.

Footnotes

Acknowledgements

The authors would like to thank the editor and three anonymous reviewers of this journal for their excellent suggestions. They are also grateful to Stephanie La Loggia for her contribution to this project.

Earlier versions of this article were presented at the 2006 annual meeting of the Association for Research on Nonprofit Organizations and Voluntary Action in Chicago, Illinois, and the 2008 annual meeting of the Academy of Management in Anaheim, California.

The authors declared no potential conflicts of interests with respect to the authorship and/or publication of this article.

The authors received no financial support for the research and/or authorship of this article.

1.

To further validate our sample, we followed the work of Osterman (1994) and Shaw, Delery, Jenkins, Douglas, & Gupta (1998) and ran a logistic regression analysis to detect any differences between respondent and nonrespondent organizations. The dependent variable was dummy coded: 1 if a questionnaire had been completed and returned; 0 otherwise. The independent variables for this bias check included organizational revenue and four industry dummies. None of these variables was significant, suggesting that response bias should not have affected our statistical results.

2.

A potential methodological problem is that socially desirable responding might have exaggerated the extent to which strategic HRM practices were adopted. In light of the fact that the values for the strategic HRM variables are skewed slightly to the right, this possibility of social desirability bias cannot be ruled out. This said, it seems less likely to be a serious problem in an anonymous web survey like ours than in a telephone survey or face-to-face interviews, as previous research has demonstrated (e.g., de Leeuw, 2005, pp. 245-246).

3.

Two variables, namely size of staff and size of revenue, were originally created to measure organizational size. Given the fairly strong correlation between the two variables (r = .84, p < .01) and the fact that size of revenue has more missing observations, only size of staff is used as the proxy for organizational size in the article.

4.

Results of the Breusch–Pagan test show a chi-square value of 23.99 and a p-value of .000, indicating that the variances of observations are not homogenous. In such cases, WLS regression provides more efficient parameter estimates than ordinary least squares (OLS).

5.

In terms of the percentage of work done by volunteers, the median value in our data is 10%. The F-statistic for the Chow test is 2.02 with a p-value of .028, indicating significant differences between the two subgroups. We have also tried alternative measures of volunteer dependence based on “number of volunteers” and “percentage of volunteers.” Similarly, the Chow test results show significant differences between subgroups.

References

Akingbola

(2004). Staffing, retention and government funding: The Canadian Red Cross, Toronto region. Nonprofit Management and Leadership, 14, 453-467.

Akingbola

(2006). Strategy and HRM in nonprofit organizations: Evidence from Canada. International Journal of Human Resource Management, 14, 453-465.

Ban

Drahnak-Faller

Towers

(2003). Human resource challenges in human service and community development organizations: Recruitment and retention of professional staff. Review of Public Personnel Administration, 23, 133-153.

Bell

Lee

S. W.

Yeung

(2006). The impact of e-HR on professional competence in HRM: Implications for the development of HR professionals . Human Resource Management, 45, 295-308.

Berger

(Eds.). (2004). Talent management handbook. New York, NY: McGraw-Hill.

Brown

W.A.

Yoshioka

C.F.

(2003). Mission attachment and satisfaction as factors in employee retention. Nonprofit Management and Leadership, 14(1), 5-18.

Buckingham

Vosburgh

(2001). The 21st century human resources function: It’s the talent, stupid! Human Resource Planning, 24(4), 17-23.

Carroll

G.R.

Teo

A.C.

(1996). Creative self-destruction among organizations: An empirical study of technical innovation and organizational failure in the American automobile industry, 1885-1981. Industrial and Corporate Change, 5, 619-644.

Carroll

Hughes

Luksetich

(2005). Managers of nonprofit organizations are rewarded for performance. Nonprofit Management and Leadership, 16(1), 19-41.

10.

Clary

E. G.

Snyder

(1999). The motivations to volunteer: Theoretical and practical considerations. Current Directions in Psychological Science, 8, 156-159.

11.

Condrey

S. E.

(1998). Toward strategic human resource management. In Condrey

S. E.

(Ed.), Handbook of human resource management (pp. 676-680). San Francisco, CA: Jossey-Bass.

12.

Connelly

C. E.

Gallagher

D. G.

(2006). Independent and dependent contracting: Meaning and implications. Human Resource Management Review, 16, 95-106.

13.

Corder

(2001). Acquiring new technology: Comparing nonprofit and public sector agencies. Administration and Society, 33, 194-219.

14.

Cunningham

(1999). Human resource management in the voluntary sector: Challenges and opportunities. Public Money and Management, 19(2), 19-25.

15.

Daley

Vasu

M. L.

Weinstein

M. B.

(2002). Strategic human resource management: Perceptions among North Carolina County social service professionals. Public Personnel Management, 31, 359-375.

16.

Davis-Blake

Uzzi

(1993). Determinants of employment externalization: A Study of temporary and independent contractors. Administrative Science Quarterly, 38, 195-223.

17.

de Leeuw

E. D.

(2005). To mix or not to mix data collection modes in surveys. Journal of Official Statistics, 21, 233-255.

18.

Delery

J. E.

Doty

D. H.

(1996). Modes of theorizing in strategic human resource management: Tests of universalistic, contingency and configurational performance predictions. Academy of Management Journal, 39, 802-835.

19.

Dicke

L. A.

Ott

J. T.

(2003). Post-September 11 human resource management in nonprofit organizations. Review of Public Personnel Administration, 23(2), 97-113.

20.

Drucker

P. E.

(1989, July-August). What business can learn from nonprofits. Harvard Business Review, 88-93.

21.

Farazmand

(2004). Innovation in strategic human resource management: Building capacity in the age of globalization. Public Organization Review, 4, 3-24.

22.

Forbes

D.P.

(1998). Measuring the unmeasurable: Empirical studies of nonprofit organization effectiveness from 1977-1997. Nonprofit and Voluntary Sector Quarterly, 27, 183-202.

23.

Frumkin

Kim

M.T.

(2002). The effect of government funding on nonprofit administrative efficiency: An empirical test. Cambridge, MA: Ash Institute for Democratic Governance and Innovation. Retrieved from http://www.innovations.harvard.edu/cache/documents/26/2600.pdf

24.

Gallagher

D.G.

(2002). Contingent work contracts: Practice and theory. In Cooper

C. L.

Burke

R. J.

(Eds.), The new world of work: Challenges and opportunities (pp.115-136). Oxford, UK: Blackwell.

25.

Gallagher

D. G.

Sverke

(2005). Contingent employment contracts: Are existing employment theories still relevant? Economic and Industrial Democracy, 26, 181-203.

26.

Gardner

S. D.

Lepak

D. P.

Bartol

K. M.

(2003). Virtual HR: The impact of information technology on the human resource professional. Journal of Vocational Behavior, 63, 159-179.

27.

Goodstein

J. D.

(1994). Institutional pressures and strategic responsiveness: Employer involvement in work-family issues. Academy of Management Journal, 37, 350-382.

28.

Gray

S. R.

Benson

P. G.

(2003). Determinants of executive compensation in small business development centers. Nonprofit Management and Leadership, 13, 213-227.

29.

Grossman

Rangan

V. K.

(2001). Managing multisite nonprofits. Nonprofit Management and Leadership, 11, 321-337.

30.

Guo

(2007). When government becomes the principal philanthropist: The effect of public funding on patterns of nonprofit governance. Public Administration Review, 67, 456-471.

31.

Haines

V. Y.

Lafleur

(2008). Information technology usage and human resource roles and effectiveness. Human Resource Management, 47, 525-540.

32.

Hanna

(1995). Towards consensus in human services computer networking. Computers in Human Services, 12, 179-194.

33.

Hannan

M. T.

Freeman

(1984). Structural inertia and organizational change. American Sociological Review, 49, 149-164.

34.

Herman

R. D.

Renz

D. O.

(1997). Multiple constituencies and social construction of nonprofit organizational effectiveness. Nonprofit and Voluntary Sector Quarterly, 26, 185-206.

35.

Herman

R. D.

Renz

D. O.

(1999). Thesis on nonprofit organizational effectiveness. Nonprofit and Voluntary Sector Quarterly, 28, 107-125.

36.

Hodgkinson

V. A.

Weitzman

M. S.

Noga

S. M.

Gorski

H. A.

(1993). A portrait of the independent sector. Washington, DC: Independent Sector.

37.

Huselid

M. A.

Jackson

S. E.

Schuler

R. S.

(1997). Technical and strategic human resource management effectiveness as determinants of firm performance. Academy of Management Journal, 40, 171-188.

38.

Jackson

S. E.

Schuler

R. S.

(1995). Understanding human resource management in the context of organizations and their environments. Annual Review of Psychology, 46, 237-264.

39.

Kalleberg

A. L.

Reskin

B. F.

Hudson

(2000). Bad jobs in America: Standard and nonstandard employment relations and job quality in the United States. American Sociological Review, 65, 256-278.

40.

Kay

A.S.

(2000). Recruiters embrace the Internet. Information Week, 778, 72-80.

41.

Kearns

K. P.

(2004). Management-capacity building in the Pittsburgh region. Nonprofit Management and Leadership, 14, 437-452.

42.

Kim

S. E.

Lee

J. W.

(2007). Is mission attachment an effective management tool for employee retention? An empirical analysis of a nonprofit human services agency. Review of Public Personnel Administration, 27, 227-248.

43.

Knoke

Yang

(2003). Fattenin’ frogs for snakes? Company investments in job skills training. Research in the Sociology of Work, 12, 3-30.

44.

Kong

Thomson

S. B.

(2006). Intellectual capital and strategic human resource management in social service non-profit organisations in Australia. International Journal of Human Resources Development and Management, 6, 213-231.

45.

Krashinsky

(1990). Management implications of government funding of nonprofit organizations: Views from the United States and Canada. Nonprofit Management and Leadership, 1(1), 39-53.

46.

Legge

(1995). Human resource management: Rhetorics and realities. Basingtoke, UK: MacMillan Business.

47.

Lengnick-Hall

M. L.

Moritz

(2003). The impact of e-HR on the human resource management function. Journal of Labor Research, 24, 365-370.

48.

Liao-Troth

M. A.

(2001).Attitude differences between paid workers and volunteers. Nonprofit Management & Leadership, 11, 423-442.

49.

Lynn

D. B.

(2003). Symposium: Human resource management in nonprofit organizations. Review of Public Personnel Administration, 23(2), 91-96.

50.

Mason

D. E.

(1996). Leading and managing the expressive dimension: Harnessing the hidden power source of the nonprofit sector. San Francisco, CA: Jossey-Bass.

51.

Mirvis

P. H.

(2006). The quality of employment in the nonprofit sector: An update on employee attitudes in nonprofits versus business and government. Nonprofit Management and Leadership, 3(1), 23-41.

52.

Mirvis

P. H.

Hackett

(1983). Work and work force characteristics in the nonprofit sector. Monthly Labor Review, 106(4), 3-12.

53.

Morton

(2004). Integrated and integrative talent management: A strategic HR framework. New York, NY: Conference Board.

54.

Maki

(1993). Human resource management in the Canadian manufacturing sector. International Journal of Human Resource Management, 4, 897-916.

55.

Nickson

Warhurst

Durron

Hurrell

(2008). A job to believe in: Recruitment in the Scottish voluntary sector. Human Resource Management Journal, 18(1), 20-35.

56.

Oster

(1996). Nonprofit organizations and their local affiliates: A study in organizational forms. Journal of Economic Behavior and Organization, 30, 83-95.

57.

Osterman

(1994). How common is workplace transformation and who adopts it? Industrial and Labor Relations Review, 47, 173-188.

58.

Parry

Kelliher

Mills

Tyson

(2005). Comparing HRM in the voluntary and public sectors. Personnel Review, 34, 588-602.

59.

Pearce

J. L.

(1983). Job attitude and motivation differences between volunteers and employees from comparable organizations. Journal of Applied Psychology, 68, 646-652.

60.

Pearce

J. L.

(1993). Volunteers: The organizational behavior of unpaid workers. New York, NY: Routledge.

61.

Perry

J. L.

Mesch

D. J.

(1997). Strategic human resource management. In Ban

Riccucci

(Eds.), Public personnel management: Current concerns, future challenges (pp. 21-34). New York, NY: Longman.

62.

Phillips

J. J.

(1996). Accountability in human resource management. Huston, TX: Gulf.

63.

Pynes

J. E.

(2004). Human resources management for public and nonprofit organizations (2nd ed.). San Francisco, CA: Jossey-Bass.

64.

Rainey

H. G.

(2003). Understanding and managing public organizations (3rd ed.). San Francisco, CA: Jossey-Bass.

65.

Ridder

McCandless

(2010). Influences on the architecture of human resource management in nonprofit organizations: An analytical framework. Nonprofit and Voluntary Sector Quarterly, 39(1), 124-141.

66.

Saidel

J. R.

Cour

(2003). Information technology and the voluntary sector workplace. Nonprofit and Voluntary Sector Quarterly, 32(1), 5-24.

67.

Salamon

L. M.

(1995). Partners in public service: Government-nonprofit relations in the modern welfare state. Baltimore, MD: Johns Hopkins University Press.

68.

Schuler

R. S.

Jackson

S. E.

(1987). Linking competitive strategies with human resource management practices. Academy of Management Executive, 1, 207-219.

69.

Shaw

J. D.

Delery

J. E.

Jenkins

Douglas

Gupta

(1998). An organization-level analysis of voluntary and involuntary turnover. Academy of Management Journal, 41, 511-525.

70.

Sheridan

J. E.

(1992). Organizational culture and employee retention. Academy of Management Journal, 35, 1036-1056.

71.

Siegel

G. B.

(1999). Where are we on local government service contracting? Public Productivity and Management Review, 22, 365-388.

72.

Singh

Finn

(2003). The effects of information technology on recruitment. Journal of Labor Research, 24, 395-408.

73.

Smith

S. R.

Lipsky

(1993). Nonprofits for hire: The welfare state in the age of contracting. Cambridge, MA: Harvard University Press.

74.

Townsend

A. M.

Bennett

J. T.

(2003). Human resources and information technology. Journal of Labor Research, 24, 361-363.

75.

Tyson

(1997). Human resource strategy: A process for managing the contribution of HRM to organizational performance. International Journal of Human Resource Management, 8, 277-290.

76.

Wagar

T. H.

(1998). Determinants of human resource management practices in small firms: Some evidence from Atlantic Canada. Journal of Small Business Management, 36(2), 13-23.

77.

Watson

M. R.

Abzug

(2004). Finding the ones you want, keeping the ones you find: Recruitment and retention in nonprofit organizations. In Herman

R. D.

and Associates (Eds.), The Jossey-Bass handbook of nonprofit leadership and management (2nd ed.; pp. 623-659). San Francisco, CA: Jossey-Bass.

78.

Weitzman

M. S.

Jalandoni

N. T.

(Eds.). (2002). The new nonprofit almanac and desk reference. San Francisco, CA: Jossey-Bass.

79.

Whitfield

(2000). High-performance workplace: Training, and the distribution of skills. Industrial Relations, 39(1), 1-25.

80.

Wing

K. T.

Pollak

T. H.

Blackwood

Lampkin

L. M.

(2008). The nonprofit almanac 2008. Washington, DC: Urban Institute Press.

81.

Young

D. R.

(2001). Organizational identity and the structure of nonprofit umbrella associations. Nonprofit Management and Leadership, 11, 289-304.