The Flow of Management Practices

Abstract

Which characteristics of NGOs are associated with the adoption of modern management practices and to what extent have those practices become standardized? Based on a national sample of 135 international and local NGOs operating in Cambodia, we address these questions by analyzing the dynamics of “monitoring and evaluation” (M&E), a term used to describe a broad range of activities that NGOs undertake to track, understand, and assess their work. We provide an overview of monitoring and evaluation in a developing country setting, investigate the factors associated with more extensive (or sophisticated) M&E using multivariate analysis, and look at how M&E practices vary between local and international NGOs. Findings demonstrate that professionalization, resource dependence, and social embeddedness all play important roles in explaining the activities of NGOs operating in Cambodia. The analysis also suggests that the flow of management practices in the NGO sector differs for local and international actors.

Keywords

nonprofit performance management professional NGO

The global field of nongovernmental organizations (NGOs) began expanding well before the beginning of the 20th century (Boli, 2006; Schofer & Longhofer, 2011). Not only has the number of NGOs providing services increased throughout the world, these organizations have penetrated into new domains of expertise (Drori, Meyer, & Hwang, 2006; Salamon & Anheier, 1996). NGOs are involved in traditional areas of program delivery such as education and hospital care, they contribute to relatively new industries like environmental protection and AIDS services, and they also engage in formal policy making and transnational social movement advocacy. The particularly rapid growth of NGOs since the end of the Second World War has led some to describe the phenomenon as a “global associational revolution,” dramatizing the role that many of these organizations play in building civil society and encouraging civic engagement (Anheier & Salamon, 2006; Brown, 2008; Salamon, Anheier, List, Toepler, & Sokolowski, 1999).

The increasing importance and visibility of NGOs has contributed to calls for greater accountability and transparency, with the sources of these demands reflecting the diversity and complexity of the field itself. In some instances NGOs have adopted metrics imposed by external agents, responding to requirements from governments, foundations, and other donors (DiMaggio & Powell, 1983; Pfeffer & Salancik, 1978). In other cases, NGOs have created their own standards for self-regulation, developing voluntary codes of ethics and establishing umbrella agencies for oversight (Gugerty, 2008; Sidel, 2011). Research in industrialized countries such as the United States indicates that the nonprofit sector has adapted by becoming rationalized and professionalized, meaning that organizations rely more on a credentialed, paid labor force and increasingly develop formal policies and reporting procedures (Abbott, 1988; Hwang & Powell, 2009).

These trends are well established, but questions remain about which characteristics of NGOs are associated with the adoption of modern management practices and the extent to which these practices have become commonplace in NGOs across a broad range of contextual settings. Empirical studies that test competing arguments about the adoption of management practices in NGOs are uncommon, especially in the poorest countries where concerns about local capacity are most pronounced (Barr & Fafchamps, 2006; Barr, Fafchamps, & Owens, 2005; Burger & Owens, 2010; Watkins, Swidler, & Hannan, 2012). We address this issue by analyzing monitoring and evaluation (M&E) in a national sample of 135 local and international NGOs operating in Cambodia. The diversity of the NGO sector in Cambodia, combined with the range of potential revenue sources available for programs and services, offers a useful context for analyzing M&E and the factors associated with the flow of management practices. Using data from in-person interviews with organizational leaders, we provide a detailed overview of the extent of M&E practices in a developing country setting based on a national sample. Then, using multivariate regression analysis we consider how professionalization, resource dependence, and social embeddedness are associated with M&E.

The Adoption of Management Practices: Monitoring and Evaluation

Monitoring and evaluation (M&E) refers to a broad range of activities used to assess organizational performance and meet the needs of diverse stakeholders (Ebrahim, 2003, 2005; Marshall, Hamilton, Marsh, McCaffrey, & Stecher, 2009). At the most basic level, monitoring comprises descriptive reporting, compliance, and the collection of data on expenditures and program costs (Carman, 2009; LeRoux & Wright, 2010). Management activities of this nature begin with the collection of information about operating costs and simple outputs (number of participants, planned vs. actual expenditures, etc.). Although this kind of information does not offer evidence of the quality of implementation, it can provide insight into how extensively an NGO tracks its programs. These activities are complemented by other practices like external audits that emphasize reporting and validation.

A second general area of monitoring and evaluation activity serves a formative purpose and can also be referred to as implementation evaluation. Formative evaluation relies heavily on feedback and participant opinion, with the NGO articulating a theory of action (or logic model) to understand the intermediate outcomes that are most directly affected by specific actions (Carman, 2010). This work can begin before the project formally begins, often in the form of an initial needs assessment based on both primary (expert opinions, feedback from partners and potential participants) and secondary (existing data, reports) sources. In this respect these activities are similar to client satisfaction surveys and the collection of simple efficiency measures, but they fall short of summative program evaluations.

The term summative highlights the end-of-project timing of program evaluation, and one reason for waiting to carry out this work is that program impacts may require some time to develop. Summative evaluation accordingly is synonymous with outcome measurement, or “an evaluative technique employed by organizations to measure the impact of programs on clients” (Barman & MacIndoe, 2012, p. 71). An emerging literature has focused specifically on outcome measurement in nonprofits, reflecting the growing relevance of the activity in the NGO sector (Alexander, Brudney, & Yang, 2010; Benjamin, 2008; Carman & Fredericks, 2010; MacIndoe & Barman, 2012).

The three types of M&E activity defined here (monitoring, formative evaluation, summative evaluation) present a spectrum of management tools, with monitoring capturing some of the more basic actions and outcome evaluations capturing more complex ones. However, it is not clear if these practices should be analyzed as discrete groups of activities, or if they can be merged together as a single phenomenon called “monitoring and evaluation” in nonprofit organizations. Previous research provides little guidance on this question since few studies have explored how different indicators of M&E are associated with one another (Carman, 2009; LeRoux & Wright, 2010). Moreover, the features of NGOs that help to explain the adoption of these practices remain unclear, the issue to which we now turn.

Explaining Variation in Monitoring and Evaluation Among NGOs

As noted above, research indicates that monitoring and evaluation is becoming more common in the NGO sector, but significant variation still characterizes the range of activities undertaken (Benjamin, 2008; Carman, 2009; LeRoux &, Wright, 2010). One straightforward approach for explaining the extent of monitoring and evaluation practices looks within an NGO to the professionalization of the leadership and staff. The growing professionalization of the NGO sector has received research attention, but the long-term consequences of change merit further analysis (Hwang & Powell, 2009; Karl, 1998; Korten, 1987; Roberts, Jones, & Frohling, 2005; Suárez 2011). From the perspective of sociological institutionalism, education and training expose individuals to a broad range of modern concepts and ideas, and professionalized NGOs might be likely to experiment with diverse monitoring and evaluation approaches (DiMaggio & Powell, 1983; Meyer & Rowan, 1977; Sahlin-Andersson & Engwall, 2002). NGOs with university-educated staff also may have a greater aptitude for monitoring and evaluation than nonprofits that rely less on formally trained employees, a straightforward human capital argument. In short, university education and other forms of training presumably expand the competence of leaders and staff for implementing sophisticated monitoring and evaluation programs, or at least acquaint them with popular practices that get discussed in academic settings.

Moving beyond “internal” organizational drivers for monitoring and evaluation, resource dependence theory has drawn attention to the influence of the wider resource environment on NGOs. Resource dependence theory claims that organizations seek to avoid uncertainty, yet efforts to balance competing environmental demands can reduce organizational autonomy and lead to unexpected trade-offs (Pfeffer & Salancik, 1978). In the context of international development, NGOs are playing a growing role in service delivery, due in part to donor concerns about providing foreign aid to corrupt, repressive, or weak governments (Brinkerhoff, 2002; Lewis, 2007). The intensifying interface between NGOs and different donors has potentially significant consequences for monitoring and evaluation activities. Recent research has documented the increasing demands placed on NGOs by government aid agencies, foundations, and international donors (Brinkerhoff, 2008; Smith & Gronbjerg, 2006). Institutional donors often want to assess how their resources are being utilized, and they have considerable leverage for obligating NGOs to document their practices and demonstrate precisely how they implement their programs. Since monitoring and evaluation offer a diversity of important tools for demonstrating accountability in the nonprofit sector, institutional donors could have a positive influence on the total range of M&E practices (Ebrahim, 2003, 2005a).

A third line of argument emphasizes social embeddedness. Rather than viewing M&E as resulting from professionalization or resource dependence, embeddedness emphasizes legitimacy and learning from interactions with peers (DiMaggio & Powell, 1983; Meyer & Rowan, 1977). For example, an NGO that participates in associations or “bridging organizations” might encounter other organizations that monitor and evaluate their own work, thereby increasing the chances that the NGO will emulate its peers and adopt similar practices (Brown, 1991). In effect, by looking beyond the boundaries of their organizations, NGOs can learn about a diversity of practices and broaden their commitment to M&E (Drori et al., 2006). Aligning with this perspective, prior research finds that countries with greater ties to international NGOs (INGOs) are more likely to enact governance reforms, human rights policies, and environmental protection laws, revealing that INGOs are prominent advocates for reform (Drori, Jang, & Meyer, 2006; Frank, Hironaka, & Schofer, 2000). In this work, INGOs are characterized as carriers of modern, rationalized practices, and as a result INGOs could be more active in implementing monitoring and evaluation within their own organizations.

The role played by INGOs in these dynamics is receiving more attention in the literature (Hulme & Edwards, 1997; Lewis, 2007). From an embeddedness perspective, INGOs are central to diffusing ideas about management practices, and they also “create credibility” for transnational civil society (Brown, 2008; Hammack & Heydemann, 2009). However, because international NGOs presumably differ from local NGOs with respect to their relationship to host governments and donors, they may not respond to pressures or to signals in the same ways. This line of reasoning suggests that research grouping local and international NGOs together potentially overlooks or masks important differences, a topic that has not received much scholarly attention.¹ While many studies recognize the growing importance of local NGOs for program implementation, the bulk of research on development NGOs either has emphasized international players or has not contrasted the management practices of international NGOs with those of their local counterparts (Boli, 2006; Brown & Moore, 2001; Edwards, 1999; Lewis & Wallace, 2000). Stated differently, research on NGOs frequently utilizes aggregated data or prioritizes case studies, meaning that there is not much comparative organization-level data (Barr et al., 2005; Fafchamps & Owens 2009). By considering INGOs and local NGOs separately yet within the same framework, comparative research can begin to specify differences in these two important groups.

In summary, the conceptual frame presented here suggests that professionalization, resource dependence, and social embeddedness will influence the total range of M&E activity in an NGO. Furthermore, because of differences in institutional context, we expect the flow of management practices to vary significantly between local and international NGOs. In the following section we describe the data and indicators we use to flesh out these general conceptual constructs as well as the country context and empirical methodology.

Country Context and Analytical Framework

Cambodia became a sovereign nation-state in 1953, and in 1975 a communist group led by Pol Pot took control of the country. The Khmer Rouge, as the insurgents were known, became infamous for genocide and agrarian policies that led to famine, and as many as 2 million people died during the reign of the group (Gottesman, 2004; Kiernan, 2002). In 1979 Vietnam invaded Cambodia to overthrow the Khmer Rouge, and the international community eventually intervened to restore stability. In 1991 the Paris Peace Accords were signed, and in 1993 the United Nations oversaw democratic elections in the country. NGOs have been pivotal in the development process since the Paris Peace Accords, with a Cambodian government analysis indicating that NGOs “provide or manage approximately 20% of all aid to Cambodia” (Royal Government of Cambodia [RGC], 2010, p. 14). The number of international NGOs exploded in the 1990s and continues to rise, reflecting similar trends in other countries (Chanboreth & Hach, 2008; Rasmussen, 2010; Salamon et al., 1999).

Our sampling framework was designed to provide a nationally representative sample of local and international NGOs (Cooperation Committee for Cambodia, 2009; Suárez & Marshall, 2012). We first defined an NGO population based on the 1,240 organizations that were listed on the Cambodian government’s Council for the Development of Cambodia (CDC) online database (www.cdc.khmer.biz). We then chose 230 organizations at random from this database, divided evenly between local and international NGOs. Of this original batch we confirmed that 16 had closed and another 34 had no current contact information. This left 180 organizations, from which we were then able to interview 135 organizations, or 75%. To address the issue of nonresponse (and closings) we adjusted the sample using survey weights obtained from a multivariate response function. This weight also was adjusted to correct for the original sampling imbalance between local and international NGOs.

The data collection process began with an initial proposal and survey instrument that was shared with a small group of Khmers (Cambodians) and foreign consultants who work in the NGO sector in Cambodia. Together with a local consulting firm we finalized the survey instrument, translated it into the Khmer language, and then piloted it in four NGOs in Phnom Penh. For the final data collection the interviews took place in NGO offices or, in a few cases, in local cafes. The interviewee was allowed to choose the language of the interview (English or Khmer). To help with the consistency in the interview across languages, a small group of interviewers (4) carried out approximately 15 interviews together at the beginning of the data collection period together with at least one of the two main researchers. The remaining interviews were completed between October 2010 and June 2011, and on average the interview took about 75 min to complete.

Table 1 summarizes all of the independent variables used in the analysis, divided into the various categories introduced in our conceptual discussion—professionalization, resource dependence, and social embeddedness. We expect professionalization to be positively associated with monitoring and evaluation, and our indicator is based on three measures that cover different aspects of professionalization within these organizations: leader education, staff education, and staff training. Based on our interviews, 81% of NGOs send staff members to professional training, 83% of NGO leaders have at least an undergraduate degree, and 57% of NGOs have a majority of staff with an undergraduate degree.² To create a single measure we incorporated factor analysis based on tetrachoric correlation coefficients (due to the dichotomous nature of the indicators), and the three variables load onto one factor with an Eigenvalue of 1.17.

Table 1.

Variable Definitions, Means, and Standard Deviations.

Variable	definition	sample average	SD
Dependent variable
Monitoring & evaluation	Factor based on nine indicators (see Table 2)	1.20	.37
Independent variables
Professionalization
Education and training	Factor based on three indicators of training and education	.74	.31
Resource dependence
INGO	1 = International NGO provides funding	.61	—
International	1 = IGO or foreign government provides funding	.39	—
Foundation	1 = Foundation provides funding	.22	—
Social embeddedness
Networks	Number of networks to which an NGO organization belongs	2.20	1.82
CCC certification	1 = Leader is aware of CCC Voluntary Certification process	.43	—
INGO	1 = NGO has an international home office	.37	—
Controls
Main field of work	Excluded category includes all other fields
Education	1 = Organization’s main area of work is Education-training	.21	—
Health	1 = Organization’s main area of work is health-water	.22	—
Religious	1 = Organization has a religious affiliation/mission	.14	—
NGO size (log)	NGO employed staff	2.92	1.15
NGO age (log)	NGO total years of operation in Cambodia	2.31	.64

Note. All averages based on weighted data. Professional is missing 7 cases, funding is missing 5, and sector categories are missing 1. Other variables have all 135 cases. Source: Author data.

Our second group of indicators addresses resource dependence, which argues that funding from institutional donors is more likely to be associated with monitoring and evaluation than other sources (such as donations or earned income). As Table 1 clarifies, 61% of NGOs in our sample receive funding from INGOs, 39% from international sources like governments and multilateral agencies, and 22% from foundations. Finally we include three variables for social embeddedness, all of which we expect to be positively associated with monitoring and evaluation. The first is an indicator of network participation, or the total number of NGO networks to which the NGO belongs (average is 2.2 networks). The second is an indicator for whether or not the NGO is familiar with the Cooperation Committee for Cambodia’s (CCC) Voluntary Certification process, which is a service provided by the largest Cambodian NGO network to improve capacity in the sector (Sidel, 2011); about 43% of the NGOs in our sample are aware of the program.³ The third is whether or not an organization is international (INGO), with 37% of the sample reporting a home base outside of Cambodia.

To test these various arguments and identify the most salient influences on monitoring and evaluation behaviors, we need to incorporate a number of general controls. This begins with two indicators for primary field of expertise, designed to capture potential variation related to program focus (health and education). We also include a religious/secular dichotomy since previous work indicates that religious organizations might be slower to adopt some managerial practices than secular organizations (Bromley, 2010). Age is an important control because some management practices could develop with time and experience. The average age in the sample is almost 13 years, with a standard deviation of nearly 10 years (the indicator is logged to reduce skewness). Finally, we include an indicator for NGO size based on the number of staff employed by the organization. The average staff size if 52, but the standard deviation is large (147.44) because of a number of very large NGOs in the sample. This indicator is also logged to reduce skewness.

Our formal data analysis begins with factor analysis using a wide-ranging set of M&E indicators (introduced below) to create our dependent variable. The factor analysis is a natural place to begin the empirical work because it allows us to address two related issues. First, we can assess the extent to which our conceptual framework (monitoring, formative evaluation, summative evaluation) is supported empirically in our national sample of NGOs operating in a poor, developing country context. We cannot rule out the possibility that these three areas are essentially facets of a single M&E phenomenon. Factor analysis is an appropriate technique for addressing this question since it tests for correlations among different variables to identify distinct latent “traits” or features. If most of our M&E indicators from the three areas are highly correlated with each other, it suggests that monitoring and evaluation is best understood in this context using a single general measure.

Factor analysis also provides an effective method for data reduction, which is especially useful for data analysis extensions like multivariate regression. We could create an index for M&E (i.e., using all indicators), both overall as well as for each of the three areas we introduced earlier. However, the factor analysis in effect tells us how relevant or necessary it is to have different categories. Furthermore, the standardized loadings that are generated by factor analysis provide a correlation-based solution for one of the trickier aspects of data reduction (or index creation), which is deciding how much importance or weight to give each variable in the configuration. Based on the factor analysis-generated dependent variable we then incorporate ordinary least squares (OLS) regression to model monitoring and evaluation as a function of variable vectors corresponding to professionalization, resource dependence, and social embeddedness. All statistical estimations, like the descriptive summaries used throughout this article, are based on weighted data.

Results

Table 2 provides an overview of the data we collected for the dependent variable on monitoring and evaluation. In the first three columns, we present the overall sample average for each facet of M&E as well as averages for NGO and INGO subsamples together with tests of significance for differences between them (see INGO column). As the table indicates, more than 90% of organizations in the sample report having an annual budget, and most update their budget on a quarterly basis. Moreover, about 60% of the sample reports having had an external financial audit. We also found that 37% of the organizations reported using a census or survey database, and many incorporated diverse needs assessment strategies.

Table 2.

Monitoring and Evaluation, Descriptive Overview and Factor Loadings.

Variable	Sample average	Subsamples		Factor loading
Variable	Sample average	Local	INGOs	Factor loading
External audit	.60	.54	.71*	.72
Prepares annual budget	.91	.87	.97**	.69
Regularly updates budget^a	4.05	3.92	4.28	.48
Data collection activities^b	.76	.76	.76	.55
Use secondary or census data	.37	.30	.49**	.59
Needs assessment strategies/methodology
Interviews, questionnaires	.52	.50	.53	.51
Needs assessment model	.15	.18	.08	.38
Evaluation strategies/methodology
Quantitative or change-oriented	.13	.04	.27***	.38
Evaluation model	.32	.24	.44**	.40
Eigenvalue	—			2.58
Variance explained	—			.69
N	—			132

Frequency scale: 1 = Never; 2 = Annually; 3 = Biannually; 4 = Quarterly; 5 = Monthly. ^bThe indicator is an average of eight general data collection activities like creating targets and baselines. Source: Author data.

Significant at p ≤ .10 level. **p ≤ .05 level. ***p ≤ .01.

We asked about program evaluation as well, finding that 13% employed formal data collection processes by using questionnaires, interview protocols, and impact indicators. Interestingly, a relatively large group of NGOs (32%) incorporated a formalized evaluation model, often outsourcing the work to external evaluators that come from a home office or are hired by the NGO. As expected, there are some differences between INGO and NGO averages in Table 1. International NGOs are more likely to enact the most “intensive” practices—they are more likely to use survey data, and they also are more likely to use quantitative approaches and formal evaluation models.

The last column of Table 2 summarizes the final loadings that resulted from our factor analysis. We included all of the variables in Table 2 in the analysis using polychoric correlation coefficients, and all of the indicators load onto one factor that we call monitoring and evaluation (M&E). The factor has an Eigenvalue of 2.58 and explains 69% of the variance. The result of one predominant factor is not entirely surprising since an organization’s commitment to M&E is likely to be associated with a broad range of activities, and different dimensions of M&E are not necessarily independent of each other. This result does not preclude analyzing different areas of M&E separately, of course, as in prior quantitative work that examines specific aspects of evaluation activity (Carman, 2009; Carman & Fredericks, 2010; LeRoux & Wright, 2010; MacIndoe & Barman, 2012; Thomson, 2010). For comparative purposes, we include separate multivariate analyses of the indicators associated with monitoring and with evaluation in Appendix Table A1.⁴

Table 3 summarizes the results from the multivariate analysis. Model 1 introduces our indicator for professionalization, along with the controls. Among the controls, organizational size, NGO age, and religious affiliation all produce statistically significant effects. Organizational size and age appear to be important proxies for capacity, and religious organizations clearly differ from their secular counterparts. Professionalization also is strongly associated with M&E, a result that accords with research on NGO rationalization and procurement of government funding (Hwang & Powell, 2009; Suárez, 2010). Moving to Model 2, resources from institutional donors also appear to have a strong influence on monitoring and evaluation in the NGO sector in Cambodia. International sources (governments and multilateral agencies) and INGOs contribute to explaining the amount of M&E in an NGO, suggesting that some funding sources may be more demanding than others (Thomson, 2010).

Table 3.

Summary of Predictors of NGO Monitoring and Evaluation.

	Full sample				Subsamples
	1	2	3	4	Local	INGO
Professionalization
Education and training	.34***	—	—	.21*	.18	.26
Resource dependence
INGO	—	.11*	—	.10*	.19**	.06
International	—	.19***	—	.10	.09	.17*
Foundation	—	.06	—	.06	−.01	.09
Social embeddedness
Networks	—	—	.05***	.05***	.03	.06***
CCC certification	—	—	.14**	.11*	.22**	−.04
INGO	—	—	.18**	.13*	—	—
Controls
Main area of work
Education	.01	.02	.01	.07	.03	.22**
Health	.06	.03	.06	.11	.02	.25**
Religious	−.29***	−.23***	−.30***	−.25***	−.31**	−.20**
Size	.10***	.09**	.08**	.04	.01	.08**
Age (log)	.16***	.13***	.08*	.13***	.16**	.13**
Constant	.32*	.52***	.59***	.31*	.35	.22
Sample size	121	121	121	121	67	54
Explained variance (R²)	.29	.31	.35	.43	.45	.51

Note. Dependent variable is the factor presented in Table 2. Source: Author data.

Significant at p ≤ .10 level. **p ≤ .05 level. ***p ≤ .01.

In Model 3, all three indicators for social embeddedness produce positive and statistically significant effects. The model explains 43% of the variance, more than either of the other models. The rather strong effects for networks strongly suggest that memberships provide access to training and capacity building, including monitoring and evaluation. Our survey confirms as much, with 67% of respondents stating that networks provide training and 74% saying that networks help to improve capacity. This result for networks is similar to other recent work on NGOs, and the model estimation also highlights a strong effect for NGOs that are aware of the Cooperation Committee for Cambodia’s (CCC) Voluntary Certification process (Fafchamps & Owens, 2009). Finally, conforming with some of the significant differences we found between international and local NGOs in Table 1, international NGOs engage in more monitoring and evaluation than their local equivalents even when controlling for elements such as age and size.

By testing the various conceptual frames simultaneously, the final full model helps to provide more conclusive evidence for the associations we found in looking at each one separately. Model 4 reveals that organizational size no longer constitutes a significant predictor of monitoring and evaluation, a perfectly reasonable result if our substantive independent variables capture aspects of capacity. The other two control variables that produced statistically significant results in the reduced-form regressions, age and religion, continue to help explain monitoring and evaluation. Moreover, indicators from all three conceptual frames continue to provide explanatory power. For example, professionalized NGOs are more likely to engage in monitoring and evaluation activities than NGOs that have staff and leadership with less education and training.

For the indicators of resource dependence, funding from international NGOs is associated with more M&E, suggesting that INGOs subcontract work to other organizations and then require more follow-up than other donors (Lewis, 2007). With respect to embeddedness, NGOs with direct and indirect ties to networks tend to be more involved in monitoring and evaluation. NGOs that engage the broader development community are more involved in M&E, either because they are learning in those interactions or because they already are involved in M&E and seek out like-minded NGOs. Finally, international NGOs also appear to monitor and evaluate their work more than local NGOs, conforming with research documenting their role in “carrying” management ideas (Boli, 2006; Drori et al., 2006; Frank et al., 2000).

To compare the predictors of engagement with M&E for INGOs to the predictors of engagement with M&E for NGOs, we also estimated separate models by NGO category (last two columns of Table 3). For local NGOs, involvement with M&E is associated primarily with funding from INGOs and awareness of the CCC Certification System. The results for the certification system suggest that local NGOs that are attuned to the self-regulation initiative conform by monitoring and evaluating their work. By contrast, the result for INGO funding indicates that international nonprofits may be particularly interested in holding local organizations accountable for subcontracted work. In addition, older NGOs are more likely to adopt multiple M&E tools, and religious organizations are less likely to do so.

For international NGOs, the predictors of M&E are quite informative. The results reveal that all of the controls help to explain the total amount of M&E. The sector controls did not produce any statistically significant effects until this final model, but among international NGOs, health organizations and education organizations monitor their work more than nonprofits in other fields. Also, larger INGOs score higher on the factor score than smaller organizations. As with local NGOs, religious organizations adopt fewer M&E tools and older NGOs adopt more. For the main substantive indicators, INGOs appear to be influenced mainly by international funders and network memberships. The effect for networks indicates that social learning is more powerful for international NGOs than awareness of local efforts for self-regulation, a reasonable finding given that international NGOs have multiple homes.

Discussion

Research on NGOs (or nonprofits) increasingly is exploring the influence of internal stakeholders and external forces on management practices (Guo & Acar, 2005; Hwang & Powell, 2009; MacIndoe & Barman, 2012; Thomson, 2010). These studies demonstrate that NGOs face a variety of institutional demands, demands that may be especially complex in international development contexts. Besides responding to host governments and other donors that are conventional in industrialized countries, development NGOs sometimes interface with multilateral agencies and multiple governments. Studies on the flow of management practices among development NGOs consequently help to build theory and contribute to a nuanced appreciation of organizational behavior. They also serve applied purposes that can impact practice in the field. For instance, self-regulation initiatives in the NGO sector have become more prevalent over the last decade, but how they influence local management practices remains unclear (Bies, 2010; Gugerty, 2008, 2010; Sidel, 2011). By comparing and contrasting the influence of diverse stakeholders, it is possible to gauge how innovations like self-regulation initiatives affect the work of NGOs.

Understanding what influences the adoption of management practices also can be useful for discerning the determinants of organizational effectiveness and for reforming development agency policies (Benjamin, 2008; Fowler, 1997; Lewis, 2007). NGOs are widely recognized for their role in advocacy and humanitarian aid, but research on management in international and “indigenous” NGOs is badly needed for improving collaborative development projects and for building local capacity (Brinkerhoff, 2002; Dichter, 1999; Edwards, 1999; Edwards, Hulme, & Wallace, 1999). Furthermore, NGOs are central players in the delivery of foreign aid, providing services funded by multilateral agencies and development arms of donor countries, yet the links between capacity, accountability, and performance require much more investigation (Edwards & Hulme, 1996; Hudock, 1999). If institutional donors require NGOs to reform their management policies primarily for accountability purposes, then NGOs may undertake those activities more for legitimacy than for any desire to inform practice (Ebrahim, 2003, 2005a; Lewis, 2007).

We contribute to this research agenda by exploring the characteristics of organizations that are associated with a wide-ranging indicator of monitoring and evaluation. Our results demonstrate that professionalization contributes to the adoption of management practices. Though this result aligns with other research on the professionalization of the nonprofit sector, it also raises a variety of questions about unintended consequences. While professional training and a reliance on university-credentialed staff do seem to orient organizations toward monitoring and evaluating their work, studies on social movement organizations find professionalization to be associated with less advocacy and a narrower, instrumental mission focus (Jenkins, 1998; Staggenborg, 1988). The implication is that professionalization may help to construct NGOs that engage in rigorous assessments of programmatic accomplishments while simultaneously reducing their involvement in direct social change activity, a topic that merits further investigation (Korten, 1987).

Our results also highlight the salience of INGOs in the flow of management practices. INGOs appear to influence the adoption of monitoring and evaluation in two distinct ways. First, after controlling for a variety of organizational characteristics, NGOs that receive funds from international NGOs utilize a greater variety of M&E tools. Drawing on the resource dependence literature, INGOs are likely to develop subcontracting relationships and pressure their partners to demonstrate accountability through the use of metrics for performance, lending credibility to the argument that INGOs sometimes impose “managerialism” as a form of capacity building (Lewis, 2007). Second, international NGOs tend to be more likely to embrace monitoring and evaluation than local organizations in their own programs, suggesting that their embeddedness in a global environment contributes to their role as models or “carriers” of modern reforms (Frank et al., 2000; Drori et al., 2006; Sahlin-Andersson & Engwall, 2002). Extending from these findings, an important next step is to develop a nuanced understanding of how INGOs promote organizational effectiveness and shape local nonprofit sectors.

Finally, our study reconfirms the role of intermediary organizations in the diffusion of management practices while also offering avenues for additional research (Brown & Kalegaonkar, 2002). Among local NGOs in Cambodia, we find that awareness of the voluntary certification system—rather than the number of network memberships—is associated with greater involvement in M&E. Among international NGOs, network memberships are associated with greater involvement in M&E but not the voluntary certification system. For local NGOs to be more attuned to a national self-regulation initiative than INGOs is reasonable, but why networks are so much more influential for INGOs is not clear. As Brown (1991, p. 807) argued in an important early study on networks, “Bridging organizations can play key roles in building local organizations, creating horizontal linkages, increasing grassroots influence on policy, and disseminating new visions and organizational innovations.” Since intermediary organizations play such key roles, developing a better understanding of local memberships in networks is a pressing issue.

In summary, new research on how management ideas flow through professionalization, through resource ties, and through networks could help to formulate strategies for targeting development interventions. One important step in that direction would be to add a longitudinal component to extant research on NGOs, continuing to address potential differences between local and international NGOs. A second step is to expand research on NGOs, particularly in developing countries (Barr et al., 2005; Barr & Fafchamps, 2006; Brass, 2012). Research of this nature also could clarify the applicability of our findings in other contexts. Cambodia provides an informative context for testing ideas about the flow of management practices, but the country has received a great deal of foreign aid and international attention. By increasing the diversity of national-level studies on development NGOs, research can continue building a scaffold to assess how global and local contexts interact to structure the flow of management practices.

Footnotes

Appendix

Table A1.

Summary of Predictors of NGO Monitoring and Evaluation, Based on Separate Factors.

Independent variables	Monitoring			Evaluation
Independent variables	Full	Local	INGO	Full	Local	INGO
Professionalization
Education and training	.33*	.31	.25	.21*	.18	.26
Resource dependence
INGO	.20***	.28**	.16**	.10*	.19**	.06
International	.03	−.03	.16*	.10	.09	.17*
Foundation	.08	.09	.03	.06	−.01	.09
Social embeddedness
Networks	.02	.02	.01	.05***	.03	.06***
CCC certification	.03	.06	−.04	.11*	.22*	−.04
INGO	.12	—	—	.13*	—	—
Controls
Sector
Education	−.03	−.05	.13	.07	.03	.22**
Health	.12	.10	.17	.11	.02	.25**
Religious	−.19	−.47*	−.05	−.25***	−.31**	−.20**
Size	.05	−.01	.15***	.04	.01	.08**
Age (log)	.08	.05	.14***	.13***	.16**	.13**
Constant	1.09***	1.31***	.75**	.31	.35	.22
Sample size	121	67	54	121	67	54
(R²)	.25	.27	.46	.43	.45	.51

Note. Dependent variables for monitoring and for evaluation are factors based on reduced forms of the main dependent variable presented in Table 1. See note 4 for more information. Source: Author data.

Significant at p ≤ .10 level. **p ≤ .05 level. ***p ≤ .01.

Acknowledgements

The authors would like to thank Emily Barman, Lehn Benjamin, Tricia Bromley, Nicole Esparza, Joe Galaskiewicz, Tom Hannan, John Meyer, Carl Milofsky, Steve Smith, and Nuno Da Silva Themudo for comments on prior drafts.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Jeffery H. Marshall, PhD, is a consultant who works in the areas of international education policy and research, program evaluation, and assessment. He provides technical and research support to education projects throughout Africa, Asia, and Latin America and formerly worked as an associate social scientist with the RAND Corporation.

David Suárez, PhD, is an associate professor at the Evans School of Public Affairs. His current work focuses on the relationship between managerialism and organizational outcomes and the consequences of professionalization for the nonprofit sector. He is particularly interested in collaboration, advocacy, and civic engagement.

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