Efficiency of International Non-Governmental organisations (INGOs) and Local Non-Governmental organisations (LNGOs) in Mezam Division, Cameroon

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1. Introduction

Non-Governmental Organizations (NGOs) have become indispensable actors in global development by complementing government efforts in poverty reduction, humanitarian assistance, health care, education, environmental protection, and social justice. Their growing role has attracted substantial financial support from governments, multilateral agencies, philanthropic foundations, and private donors. As global development challenges continue to increase, stakeholders increasingly expect NGOs to utilize scarce resources efficiently while demonstrating accountability, transparency, and measurable development outcomes. However, despite remarkable achievements, concerns about operational inefficiency, duplication of activities, weak governance structures, poor financial management, and inadequate performance measurement continue to undermine the effectiveness of many NGOs worldwide. Consequently, improving organizational efficiency has become a major concern among policymakers, donors, beneficiaries, and researchers seeking sustainable development and value for money (Murtaza, 2012; Salamon & Sokolowski, 2016) [33, 40].

Across Africa, NGOs play a significant role in addressing socio-economic challenges arising from poverty, unemployment, health crises, food insecurity, humanitarian emergencies, and weak public service delivery. Nevertheless, many African NGOs struggle to transform donor resources into sustainable development outcomes because of limited managerial capacity, inadequate governance systems, dependence on external funding, weak accountability mechanisms, and insufficient monitoring and evaluation practices. These challenges reduce operational efficiency and often diminish public confidence in civil society organizations. Empirical evidence from African countries further indicates that strengthening governance, accountability, and internal control systems significantly improves NGO performance and resource utilization, highlighting efficiency as a prerequisite for sustainable development interventions (Edwards, 2014; World Bank, 2021) [18, 49]. In Cameroon, NGOs have increasingly become strategic partners in delivering humanitarian assistance, health services, education, environmental conservation, governance reforms, and community development, particularly in underserved and conflict-affected regions. Despite this contribution, many NGOs continue to experience inefficiencies characterized by weak internal governance, poor accountability, ineffective financial controls, donor dependency, project duplication, and inadequate coordination among civil society organizations. Studies conducted in Cameroon reveal that deficiencies in governance, transparency, and internal control systems adversely affect organizational efficiency and accountability, thereby limiting the ability of NGOs to achieve intended development outcomes and maintain stakeholder confidence (Abia et al., 2016; Ghasemi et al., 2022) [1, 21].

1.1. Statement of the Problem

Global non-profit operations rely heavily on internal control environments to ensure financial governance and operational efficiency (COSO, 2013; Berglund and Sterin, 2021) [13, 6]. The control environment sets the organizational tone by enforcing integrity, ethical values, and oversight structures (COSO, 2013) [13]. Globally, weaknesses in control environments lead to financial misstatements, misallocated aid, and diminished donor trust, which directly compromise non-governmental organization (NGO) efficiency (Petrovits, Shakespeare and Shih, 2011; Berglund and Sterin, 2021) [38, 6].

In Africa, where NGOs frequently bridge gaps in basic public service delivery, weak control environments exacerbate operational inefficiencies (Alio, 2021) [2]. Sub-Saharan NGOs often struggle with poor board oversight, inadequate segregation of duties, and high vulnerability to management override, preventing the optimal conversion of external funding into sustainable community outcomes (Boit, Chumba and Chepkorir, 2021; Oyedokun and Felejaye, 2022) [7, 37]. In Cameroon, these structural vulnerabilities are further heightened by complex socio-political conditions, such as humanitarian emergencies in conflict-affected zones (Ghasemi, Ngegah Marie and Rokni, 2022) [21]. Weak accountability, limited technical capacity, and poor governance mechanisms undermine internal controls, impairing aid delivery and resource efficiency across local and international NGOs (Ghasemi, Ngegah Marie and Rokni, 2022) [21]. Evaluating the control environment as a predictor of NGO efficiency is therefore critical to offering empirical insights for policy reforms and maximizing development impact globally and locally. This study therefore seeks to provide answers for the following questions. 1. How efficient are all NGO’s in Mezam division, Cameroon?

2. How efficient are INGO’s in Mezam division, Cameroon?

3. How efficient are LNGO’s in Mezam division, Cameroon?.

2. Literature Review

2.1.1. Efficiency

Efficiency is a core concept in economics, management, and public administration, referring to an organization's ability to maximize outputs from available inputs or minimize inputs while maintaining outputs. Its theoretical foundations were established by Koopmans (1951) [29], Debreu (1951) [15], and Farrell (1957) [20], who distinguished technical and allocative efficiency as components of overall economic efficiency. These concepts underpin modern frontier techniques such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) (Coelli et al., 2005) [12]. The development of DEA by Charnes et al. (1978) [11] and its extension by Banker et al. (1984) [4] enhanced efficiency measurement across sectors, including banking, healthcare, education, manufacturing, government, and nonprofit organizations. Contemporary literature recognizes technical, allocative, cost, scale, dynamic, environmental, and sustainable efficiency (Emrouznejad and Yang, 2018; Worthington, 2004) [19, 51]. Modern perspectives also integrate efficiency with effectiveness, accountability, governance, sustainability, stakeholder value, and social impact to provide a comprehensive assessment of organizational performance, particularly in NGOs and other mission-driven organizations as seen in how Ebrahim and Rangan (2014) demonstrate that NGO effectiveness and performance can better be measured using an input-output analysis that measure how efficient NGO’s are (Drucker, 1974; Ebrahim and Rangan, 2014) [16, 17].

2.1.2. International Non-Governmental Organisations

International Non-Governmental Organizations (INGOs) are independent, non-profit organizations that operate across national boundaries to address humanitarian, developmental, environmental, health, human rights, and social welfare challenges. They are established independently of government control, although they may collaborate with governments, international agencies, and local organizations in implementing development programs. According to the United Nations (1945) [43], NGOs are organizations that contribute to international cooperation and may be granted consultative status with international bodies such as the Economic and Social Council (ECOSOC). Lewis and Kanji (2009) [32] define INGOs as voluntary organizations that mobilize resources internationally to promote sustainable development, advocacy, and service delivery in multiple countries. Similarly, Vakil (1997) [46] describes INGOs as mission-driven organizations that pursue public benefit objectives through humanitarian assistance, capacity building, policy advocacy, and community development while remaining accountable to donors, beneficiaries, and other stakeholders.

2.1.3. Local Non-Governmental Organisations (LNGO). Local Non-Governmental Organizations (LNGOs) are non-profit, voluntary organizations established and managed within a specific country or community to address local social, economic, environmental, and humanitarian challenges. Unlike international NGOs, LNGOs primarily operate within national boundaries and possess a deeper understanding of local cultures, needs, and institutional contexts. They work closely with communities, government agencies, donors, and other stakeholders to deliver development programs, advocate for vulnerable groups, and promote sustainable livelihoods. According to Lewis and Kanji (2009) [32], local NGOs play a critical role in community participation, service delivery, and grassroots development by mobilizing local resources and fostering citizen engagement. Vakil (1997) [46] describes local NGOs as mission-driven organizations that pursue public benefit objectives through advocacy, capacity building, and community-based interventions while remaining accountable to beneficiaries and funding partners. Their proximity to local communities enhances responsiveness, ownership, and the sustainability of development initiatives (Brass et al.,2018) [8]. Presently all stakeholders’ partners have stated embracing the concept of localisation as an instrument to increasing efficiency and ensuring sustainability of LNGO’s especially in developing countries. Localisation refers to the process of shifting leadership, decision-making authority, resources, and responsibilities from international actors to local and national organizations in the planning and implementation of humanitarian and development interventions. It emphasizes empowering local institutions, communities, and civil society organizations to lead responses based on their contextual knowledge, capacities, and priorities. The concept gained global prominence through the Grand Bargain agreement of the 2016 World Humanitarian Summit (Grand Bargain, 2016) [22], which committed international donors and agencies to increase direct funding and support for local actors. According to the Inter-Agency Standing Committee (IASC, 2022) [24], localisation seeks to strengthen local ownership, sustainability, accountability, and resilience by ensuring that local organizations play a central role in humanitarian action. Similarly, Barbelet (2018) [5] argues that localisation enhances the effectiveness and long-term impact of development initiatives by building the capacity of local organizations and promoting equitable partnerships between international and local actors.

2.2. Theoretical Literature

Productive Efficiency Theory and Systems Resource Theory provide complementary explanations of NGO efficiency. Productive Efficiency Theory, developed by Farrell (1957) [20], posits that organizations are efficient when they maximize outputs from available inputs or minimize inputs while maintaining outputs. It distinguishes technical and allocative efficiency and underpins modern efficiency measurement techniques such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA). In NGOs, the theory explains how donor funds, staff, and other resources can be transformed into maximum development outcomes. Conversely, Systems Resource Theory, proposed by Yuchtman and Seashore (1967) [53], views organizations as open systems whose effectiveness depends on their ability to acquire, manage, and sustain critical external resources. For NGOs, efficiency depends not only on internal resource utilization but also on securing donor funding, partnerships, legitimacy, and stakeholder support. Together, these theories explain that NGO efficiency results from both optimal internal resource utilization and effective acquisition, protection, and management of external resources to achieve sustainable humanitarian and development objectives.

2.3. Empirical Literature

The reviewed studies consistently demonstrate that organizational efficiency in NGOs is best understood as the ability to transform limited resources into maximum social and developmental outcomes through effective resource utilization and performance measurement. Worthington (2004) [51] established that Data Envelopment Analysis (DEA) is a suitable approach for evaluating efficiency in nonprofit organizations because it accommodates multiple inputs and outputs beyond financial performance. Similarly, Kong (2010) [28] emphasized that DEA enables NGOs to benchmark their performance against best-performing organizations, identify inefficiencies, and improve accountability, resource management, and donor confidence. Verschuere and Suykens (2020) [47] further argued that systematic efficiency assessment strengthens transparency, strategic planning, and evidence-based decision-making by helping NGOs optimize the use of funding, personnel, and other resources. Emrouznejad and Yang (2018) [19] reinforced this view by showing that DEA effectively measures donor fund utilization, project implementation, and organizational productivity while promoting accountability and improved service delivery. Likewise, Sarrico and Dyson (2004) [42] demonstrated that DEA identifies efficiency frontiers that guide organizations in reducing resource waste and enhancing performance. Collectively, these studies explain that NGO efficiency extends beyond cost minimization to include accountability, optimal resource utilization, benchmarking, improved service delivery, and the achievement of sustainable social impact through informed managerial and policy decisions.

This study therefore seeks to measure and assess how efficiency of NGO’s differs across INGO’s and LNGO’s in Mezam Division, Northwest Region, and Cameroon. The study also proposes a scale that can be used to classified NGO’s according to their determine efficiency score so as to better prescribed appropriate policy recommendations for stake holders involve in the third sectors such as funders, government, UN and other international organisations, community leaders and researchers.

3. Reseasrch Methodology

3.1. Scope and area of Study

This study assesses the efficiency of NGOs across international non-governmental organisations and local non-governmental organisations in Mezam Division, Cameroon. Specifically, it looks at the individual decision-making units for each NGO and the overall decision-making units for all NGO’s, INGO’s and LNGO’s. The study focuses on the 468 NGOs officially registered in Mezam Division since 2012 records to 2025, including 56 international NGOs and 412 local NGOs. Using a sample of 226 respondents, comprising 34 international NGOs and 192 local NGOs, the study was conducted in 2026. It seeks to identify challenges face by NGO’s in Mezam and recommend appropriate policies that can improve NGO’s ability to efficienctly transform input into output and outcomes without waste of resources and practical recommendations for strengthening accountability, transparency, resource utilization, and long-term sustainability.

3.2.1. Research Design

A quantitative research survey is a systematic approach to data collection that involves gathering numerical information from a sample of respondents through structured instruments, such as questionnaires, with the purpose of measuring variables, examining relationships, and statistically testing research hypotheses. Our population which is associations and NGO’s in Mezam is made up of sub-types of different NGO’s which are Associations, NGOs and International Organisations. A literature review was conducted on both primary and secondary sources. This covered all the key concepts that were used in the study to provide the theoretical framework and background against which important tool of the study, the questionnaire was developed. The total population of our study is seen on the table below.

3.2.2. Sample Size

This study adopted the Yamane (1967) [52] formula for determining the sample size because the total population of registered non-governmental organizations (NGOs) was known and finite. Yamane’s formula provides a simplified statistical approach for calculating an appropriate sample size from a finite population while considering a predetermined level of precision. The formula is particularly applicable in survey-based studies where researchers seek to obtain a representative sample from a clearly defined population without requiring complex statistical computations (Yamane, 1967) [52]. Therefore, its application in this study was considered appropriate because the population of registered NGOs in the study area was identifiable, allowing the researcher to estimate a sample that would provide sufficient representation for examining the relationship between internal control systems and NGO efficiency. The Yamane (1967) [52] formula is expressed as:

Where: n = Required sample size N = Total population size e = Level of precision (sampling error), usually 0.05 for a 95% confidence level For this study, the required sample size 216 was calculated using the above formula based on the total number of NGOs 468 included in the sampling frame and a margin of error of 5%, which corresponds to a 95% confidence level and following the sampling frame, the data is distributed across local and national NGO’s as below.

Table 1: Determination of Sample Units for Each Stratum of Stratified Population Stratum / Item Total Population (N) Calculations Formula Sample Units (n) Local Organisations (LNGO) 412 (412 / 468) × 216 = 190.15 190 International Organisations (INGO) 56 (56 / 468) × 216 = 25.85 26 Total 468 190 + 26 = 216 216 Source: Kedze, 2026 From Table 1, The study sampled out a total of 216 NGO’s out of 468 of which 190 of the 216 are Local non-governmental organisations and 26 out of 216 are international non-governmental organisations out of the 412 and 56 LNGO and INGO existing in Mezam Division as of the time of the study as a minimum requirement as determine by Yamane Sampling formulae. However, our respondent replied more than the minimum required sample size determine by Yamane formulae thus, here reduces sampling error and improves the precision and stability of statistical estimates (Krejcie & Morgan, 1970) [31].

3.3. Variables on which Data will be collected

This objective has two categories of variables; inputs, and outputs variables as seen below;

3.3.1. Inputs Variables

Input variables in NGOs refer to the financial, human, material, and organizational resources used to implement programmes and achieve development objectives. In efficiency analysis, inputs are the resources consumed to generate outputs such as beneficiaries reached, projects completed, and services delivered (Farrell, 1957; Charnes et al., 1978) [20, 11]. The appropriate selection of input variables is essential for assessing organizational efficiency because they reflect an NGO's resource capacity and operational potential (Cooper et al., 2007) [14]. Key inputs include donor funding, policy documents, administrative costs, staff, and training programmes. Donor funding provides the financial resources needed for programme implementation and organizational sustainability (Organisation for Economic Co-operation and Development, 2021; Lewis and Kanji, 2009) [36, 32]. Policy documents strengthen governance, accountability, and internal controls (Committee of Sponsoring Organizations of the Treadway Commission, 2013; Bryson, 2018) [13, 9]. Administrative costs support organizational operations, while qualified staff provide the expertise required for effective service delivery (Drucker, 1974; Armstrong and Taylor, 2023) [16, 3]. Staff training further enhances knowledge, competence, and organizational capacity, making these inputs fundamental determinants of NGO efficiency and effectiveness (Noe, 2020) [35]. Our study uses 3 inputs which include donor funding, number of qualified staff employed and expenditure on communication and technological fascilities.

3.3.2. Output variables

In NGOs, output variables are the direct and measurable results achieved through the utilization of organizational inputs such as donor funding, staff, training, administrative resources, and institutional policies. Within Data Envelopment Analysis (DEA), outputs represent the goods, services, or outcomes generated by organizations and are essential for assessing efficiency and performance (Charnes et al., 1978; Cooper et al., 2007) [11, 14]. Key NGO output indicators include the number of beneficiaries reached, projects completed, social or youth groups engaged, timely service delivery, and client satisfaction. Beneficiaries reached reflect the scale and outreach of programme implementation, while completed projects demonstrate the organization's ability to convert resources into tangible development outcomes (Lewis and Kanji, 2009; Bryson, 2018) [32, 9]. Reaching social and youth groups indicates effective community engagement and empowerment (Chambers, 1997; UNDP, 2020) [10, 45]. Timely service delivery reflects operational responsiveness and efficient internal processes (Kaplan and Norton, 1996) [26], whereas client satisfaction measures the quality, relevance, and effectiveness of services provided, making these outputs essential indicators of NGO efficiency, accountability, and social impact (Kotler and Keller, 2016; Kettner et al., 2017) [30, 27]. Our study two uses two output number of beneficiaries reach and number of social or community groups supported.

Input variables in NGOs refer to the financial, human, material, and organizational resources used to implement programmes and achieve development objectives. In efficiency analysis, inputs are the resources consumed to generate outputs such as beneficiaries reached, projects completed, and services delivered (Farrell, 1957; Charnes et al., 1978) [20, 11]. The appropriate selection of input variables is essential for assessing organizational efficiency because they reflect an NGO's resource capacity and operational potential (Cooper et al., 2007) [14]. Key inputs include donor funding, policy documents, administrative costs, staff, and training programmes. Donor funding provides the financial resources needed for programme implementation and organizational sustainability (Organisation for Economic Co-operation and Development, 2021; Lewis and Kanji, 2009) [36, 32]. Policy documents strengthen governance, accountability, and internal controls (Committee of Sponsoring Organizations of the Treadway Commission, 2013; Bryson, 2018) [13, 9]. Administrative costs support organizational operations, while qualified staff provide the expertise required for effective service delivery (Drucker, 1974; Armstrong and Taylor, 2023) [16, 3]. Staff training further enhances knowledge, competence, and organizational capacity, making these inputs fundamental determinants of NGO efficiency and effectiveness (Noe, 2020) [35]. Our study uses 3 inputs which include donor funding, number of qualified staff employed and expenditure on communication and technological fascilities.

Table 2: Description of Study Variables, Symbols, and Data Collection Methods Variable Type & Description Symbol Measurement Level Data Collection Method Input Variables Average donor funding per year INPUT1 Ratio / Likert scale Questionnaire Number of qualified staff employed INPUT2 Ratio / Likert scale Questionnaire Average expenditure on communication and tech facilities INPUT3 Likert scale Questionnaire Output Variables Average number of beneficiaries reached per year OUTPUT1 Ratio / Likert scale Questionnaire Number of social or youth groups reached OUTPUT2 Ratio / Likert scale Questionnaire Source: Kedze, 2026.

3.4. Method of Data Analysis and Model Specification

The study adopts the CCR Data Envelopment Analysis (DEA) using model using excel solver because it is simple to apply with multiple inputs and outputs and effectively measures the overall technical efficiency of decision-making units (DMUs), which aligns with the objective of assessing the overall performance of NGOs in Mezam Division. Developed by Charnes, Cooper, and Rhodes (1978) [11] from Farrell’s (1957) [20] concept of technical efficiency, the CCR model assumes constant returns to scale, homogeneous operating conditions, and accurate measurement of inputs and outputs. A major advantage of the model is that it evaluates efficiency without requiring a predefined production function while identifying efficient organizations, benchmarking inefficient ones, and recommending input reductions and output improvements. Although the CCR model is sensitive to outliers, measurement errors, and its assumption of constant returns to scale may not always hold, it remains the foundation of DEA and is widely used to measure organizational efficiency. Consequently, it provides an appropriate and reliable framework for evaluating the overall technical efficiency of NGOs in Mezam Division (Charnes et al., 1978; Cooper et al., 2007; Emrouznejad and Yang, 2018) [11, 14, 19].

To state this CCR Model mathematically as a linear programming model, we assume that, there are n DMUs, each using m inputs to produce s outputs.

For a particular DMU₀ under evaluation:

Non-Negativity Constraint:

Ur, Vi > 0 Where: • θ0 = efficiency score of the DMU being evaluated • yrj = amount of output r produced by DMU j • xij = amount of input iii used by DMU j • ur = weight assigned to output r • vi = weight assigned to input i • n = number of DMUs • s = number of outputs • m = number of inputs

4. Presentation and Interpretation of Results

The results are presented and interpreted in three main categories of NGO’s which include; all NGO’s, international NGO’s (INGO), and Local NGO’s on which data was collected on using DEA CCRT input/output model by interpreting the efficiency score obtained calculated by using excel solver. The result obtained shows the following results and interpretation below. Our study has modified the interpretation scale use by other authors in interpreting DEA efficiency scores such as the scale proposed and used by Charnes et al. (1978) [11] who propose a two scale 1 for efficiency and less than 1 for inefficiency, while others such as Cooper et al. (2007) and Emrouznejad and Yang (2018) extended scale to Four level scale. This variety in scale has made it such that there’s no universally accepted scale as of now. Our study proposes a scale of 5 categories of efficiency classification that include: less than 0.5 for highly inefficient organisations, 0.5 – 0.74 for fairly inefficient organisations, 0.75 – 0.84 for moderate efficiency, 0.85 – 0.99 for highly efficient organisations and 1 for fully efficient organisations that serve like bench marks for other inefficient organisation as seen in the table below.

Table 3: Comparative Efficiency Scale for Classifying Efficiency Scores S/N Cooper et al. Scale (1978) Kedze Scale (2026) Scale Description Policy Prescription 1 1.00 1.00 Fully efficient Maintain current practices; act as a benchmark. Consider expanding geographic coverage or branch network. 2 0.00 0.85 – 0.99 Highly efficient Implement minor managerial and resource allocation adjustments to reach the efficiency frontier.

3 - 0.75 – 0.84 Moderately efficient Enhance operational and managerial efficiency; re-strategize resource attraction and deployment.

4 0.99 0.50 – 0.74 Fairly inefficient Review resource utilization and program implementation strategies to build donor confidence.

5 < 0.50 Highly inefficient Undertake structural reforms in resource management, program delivery, and strategic partnerships. Note. The Kedze Scale (2026) provides a disaggregated evaluation framework adapting Cooper et al. (1978). From table 3, we observe that this study main area of modification is bringing down the scale of fairly inefficiency to 0.5, because we believe some young NGO’ can be having a low inefficiency not because of poor managerial practices or low budget scale but because their period of operation do not warrant them to receive certain funding yet and as such they should be encourage to continue operating to attain greater levels and expand their scale and apply their managerial competence fully to achieve full efficiency and operate on their best efficiency frontier.

4.1. Presentation and Interpretation of Results for All

NGO’s in Mezam Division, Cameroon Our study collected data from 226 organisations where 34 are INGO and 192 are local NGO’s. The overall results from our findings using the Cooper scale shows that 17 organisations are fully efficient while 209 are inefficient. However, findings from the data where we applied our recommended efficiency score scale above reveal the following results as seen in the table below.

Table 4: Efficiency Classification and Policy Prescriptions for All NGOs in Mezam Division, Cameroon S/N Efficiency Scale Range Frequency (f) Percentage (%) Policy Prescription 1 1.00 17 7.5 Maintain current practices; act as a benchmark and expand operations. 2 0.85 – 0.99 3 1.3 Minor improvements in management style and resource allocation. 3 0.75 – 0.84 6 2.6 Improve operational efficiency by re-strategizing resource acquisition. 4 0.50 – 0.74 38 16.8 Review resource utilization and program implementation strategies. 5 < 0.50 162 71.2 Undertake substantial structural reforms in governance and program delivery. Table 4, based on our recommended DEA efficiency scale, all NGOs demonstrate varying levels of operational efficiency in converting available inputs into desired outputs. NGO 9 attained an efficiency score of 1.000, indicating that it is fully efficient and operates on the efficiency frontier. This means that the organisation utilizes its available resources optimally, producing the maximum possible outputs without wasting inputs, and therefore serves as a benchmark or role model for other NGOs. NGO 26 recorded an efficiency score of 0.8816, placing it in the highly efficient category (0.85–0.99). This suggests that the organization is performing very well and is close to the efficiency frontier but still has a small improvement potential of about 11.8% (1 – 0.8816 = 0.1184) to achieve full efficiency. NGO 10 achieved an efficiency score of 0.7633, classifying it as moderately efficient (0.75–0.84). This indicates that although the NGO utilizes its resources reasonably well, it could still improve efficiency by approximately 23.7% through better resource allocation, stronger management practices, and improved operational processes.

Also, NGO 12 obtained an efficiency score of 0.7167, placing it in the fairly inefficient category (0.50–0.74). This implies that the organization experiences noticeable inefficiencies in transforming inputs into outputs and would need to improve its efficiency by approximately 28.3% to reach the efficiency frontier. Finally, NGO 1 recorded an efficiency score of 0.188, classifying it as highly inefficient (less than 0.50). This very low score indicates severe inefficiency in resource utilization, meaning that the organization is producing only about 18.8% of the output that a fully efficient NGO could generate with similar resources. Consequently, NGO 1 would require substantial improvements in governance, internal control systems, budgeting, staff capacity, resource management, and operational processes to improve efficiency by approximately 81.2% and reach the efficiency frontier. Overall, these scores illustrate the wide disparity in efficiency among NGOs and highlight the importance of adopting best practices from fully efficient organizations to enhance operational performance.

Summary Results of Ngo’s Categories According to Recommended Efficiency Scale The table below shows the number of INGO’s, LNGO’s and total for all NGO’s that fall in the various categories on our recommended scale of classification of efficiency scores. Table 5: Cross-Tabulation of Efficiency Scores by Organization Type (INGOs vs. LNGOs) Organization Type Fully Efficient (1.00)

Highly Inefficient (< 0.50) Total NGOs INGOs 5 1 0 7 21 34 LNGOs 12 2 6 31 141 192 Total 17 3 6 38 162 226 Source: Kedze,2026. Table 5; shows how the efficiency scores frequency of the 226 NGOs was classified using our recommended DEA efficiency scale: Fully Efficient (1.00), Highly Efficient (0.85–0.99), Moderately Efficient (0.75–0.84), Fairly Inefficient (0.50–0.74), and Highly Inefficient (less than 0.50). The results show that only 17 NGOs (7.5%) were fully efficient, indicating that they operated on the efficiency frontier by optimally utilizing available resources to generate maximum outputs. Furthermore, 3 NGOs (1.3%) were classified as highly efficient, while 6 NGOs (2.7%) were moderately efficient; suggesting that these organizations performed relatively well but still had some scope for improving resource utilization. In contrast, 38 NGOs (16.8%) were fairly inefficient, and the overwhelming majority, 162 NGOs (71.7%), were highly inefficient. This implies that nearly three-quarters of the sampled NGOs operated far below the efficiency frontier, highlighting widespread inefficiencies in the use of organizational resources and the need to strengthen management practices, internal control systems, and operational processes.

With respect to International Non-Governmental Organizations (INGOs), the findings indicate that 5 out of 34 INGOs (14.7%) were fully efficient, while 1 INGO (2.9%) was highly efficient. None of the INGOs were classified as moderately efficient, whereas 7 INGOs (20.6%) were fairly inefficient and 21 INGOs (61.8%) were highly inefficient. Although the majority of INGOs remained inefficient, they recorded a higher proportion of fully efficient organizations than the overall sample and the LNGOs. This suggests that INGOs generally possess stronger institutional capacity, more stable funding, better governance structures, and more effective managerial practices, enabling some of them to achieve optimal efficiency despite the large proportion that still experiences operational inefficiencies. Among the 192 Local Non-Governmental Organizations (LNGOs), 12 organizations (6.3%) were fully efficient, 2 organizations (1.0%) were highly efficient, and 6 organizations (3.1%) were moderately efficient. In addition, 31 LNGOs (16.1%) were fairly inefficient, while 141 LNGOs (73.4%) were highly inefficient. Although LNGOs recorded a larger absolute number of fully efficient organizations than INGOs, their proportion of efficient organizations was considerably lower because they constituted the majority of the sample. The high percentage of highly inefficient LNGOs suggests that many local organizations face significant constraints, including limited financial resources, inadequate technical and managerial capacity, weak governance systems, and ineffective internal controls. These findings underscore the need for LNGOs to strengthen internal management systems, improve budget participation, build organizational capacity, and adopt better resource management practices to enhance operational efficiency and long-term sustainability.

4.2. Results and Interpretation for INGO in Mezam

Division, Cameroon Our study collected data from 34 INGO and our findings using the Cooper scale shows that 5 organisations are fully efficient while 29 are inefficient. However, findings from the data where we applied our recommended efficiency score scale above reveal the following results as seen in the table below.

Table 6: Frequency and Percentage Distribution of Efficiency Scores for INGOs S/N Kedze Scale (2026) Frequency (f) Percentage (%) Policy Prescription 1 1.00 5 14.71 Maintain current practices; serve as benchmark organizations and consider expansion.

2 0.85 – 0.99 1 2.94 Minor managerial improvements to operate on the efficiency frontier. 3 0.75 – 0.84 0 0.00 Improve operational and managerial strategies for resource utilization. 4 0.50 – 0.74 7 20.59 Review resource allocation and program implementation efficiency. 5 < 0.50 21 61.76 Undertake structural reforms in funding sourcing and organizational management.

From Table 6, The selected International Non-Governmental Organizations (INGOs) demonstrate different levels of operational efficiency in converting available inputs into desired outputs based on the DEA efficiency scale. INGO 50 achieved an efficiency score of 1.000, indicating that it is fully efficient and operates on the efficiency frontier. This means that the organization utilizes its financial, human, and material resources in the most optimal manner, producing the maximum attainable outputs without resource wastage. As such, it represents a best-practice organization and can serve as a benchmark for other INGOs seeking to improve their operational performance. INGO 89 recorded an efficiency score of 0.9846, placing it in the highly efficient category (0.85–0.99). This score indicates that the organization is utilizing approximately 98.5% of its resource potential efficiently and requires only about 1.5% improvement to attain full efficiency. Such a high score reflects effective management practices, sound governance structures, prudent financial management, and efficient utilization of organizational resources.

Also, INGO 13 obtained an efficiency score of 0.5122, classifying it as fairly inefficient (0.50–0.74). This suggests that the organization is producing only about 51.2% of the outputs that a fully efficient NGO could generate using similar resources, implying an efficiency gap of approximately 48.8%. To improve its performance, the organization should strengthen its internal control systems, enhance planning and budgeting processes, improve staff productivity, and optimize resource allocation. Finally, INGO 40 recorded an efficiency score of 0.3075, placing it in the highly inefficient category (less than 0.50). This indicates severe operational inefficiency, as the organization is generating only about 30.8% of its potential output with the resources available. Consequently, it would need to improve its efficiency by approximately 69.3% to reach the efficiency frontier. Achieving such improvement would require comprehensive organizational reforms, including strengthening governance and leadership, improving financial and project management, enhancing staff capacity, implementing effective internal controls, and adopting the best practices demonstrated by fully efficient INGOs such as INGO 50. Overall, these efficiency scores highlight substantial variation in the operational performance of INGOs and emphasize the importance of benchmarking against high-performing organizations to enhance efficiency and sustainability.

4.3. Results and Interpretation For LNGO in Mezam

Our study collected data from 192 LNGO and our findings using the Cooper scale shows that 12 LNGO’s organisations are fully efficient while 180 LNGO’S organisations are inefficient. However, findings from the data where we applied our recommended efficiency score scale above reveal the following results as seen in the table below.

Table 7: Frequency and Percentage Distribution of Efficiency Scores for LNGOs S/N Kedze Scale (2026) Frequency (f) Percentage (%) Policy Prescription 1 1.00 12 6.25 Maintain current practices; act as benchmarks and expand operations. 2 0.85 – 0.99 2 1.04 Minor managerial improvements to optimize resource allocation. 3 0.75 – 0.84 6 3.13 Improve operational and managerial efficiency to attract steady funding. 4 0.50 – 0.74 31 16.15 Review resource utilization strategies to build donor trust. 5 < 0.50 141 73.44 Substantial reforms required in resource management and program delivery. The selected Local Non-Governmental Organizations (LNGOs) exhibit varying levels of operational efficiency in transforming available inputs into desired outputs according to the recommended DEA efficiency scale. LNGO 20 achieved an efficiency score of 1.000, indicating that it is fully efficient and operates on the efficiency frontier. This means the organization makes optimal use of its financial, human, and material resources to generate the maximum possible outputs, thereby serving as a benchmark for other LNGOs. LNGO 52 recorded an efficiency score of 0.9377, placing it in the highly efficient category (0.85–0.99). This indicates that the organization is performing exceptionally well and is utilizing approximately 93.8% of its resource potential efficiently, with only about 6.2% improvement required to achieve full efficiency. LNGO 11 attained an efficiency score of 0.8054, classifying it as moderately efficient (0.75–0.84). This suggests that while the organization is utilizing its resources reasonably well, it still has an efficiency gap of approximately 19.5% and could improve its performance through better planning, stronger internal controls, enhanced budgeting practices, and more effective resource management.

Also, LNGO 17 obtained an efficiency score of 0.5075, placing it in the fairly inefficient category (0.50–0.74). This implies that the organization is producing only about 50.8% of the outputs that a fully efficient NGO could generate with similar resources and therefore requires an improvement of approximately 49.3% to reach the efficiency frontier. Such improvements could be achieved by reducing operational inefficiencies, strengthening governance structures, and improving managerial decision-making. Finally, LNGO 2 recorded an efficiency score of 0.2586, categorizing it as highly inefficient (less than 0.50). This indicates severe underutilization of available resources, as the organization is producing only about 25.9% of the potential outputs achievable with comparable inputs. Consequently, it requires an improvement of approximately 74.1% to attain full efficiency, which would likely necessitate substantial reforms in internal control systems, financial management, staff capacity, organizational leadership, and resource allocation. Overall, these results demonstrate considerable variation in efficiency among LNGOs and emphasize the need for less efficient organizations to adopt the best practices of fully efficient LNGOs in order to improve operational performance and long-term sustainability in Mezam Division, Cameroon.

5. Discussion of Results

The findings of this study revealed substantial variation in the efficiency of NGOs in Cameroon, with only 17 out of 226 NGOs (7.5%) operating on the efficiency frontier, while 162 NGOs (71.7%) were classified as highly inefficient. These findings are consistent with Worthington (2004) [51], who emphasized that Data Envelopment Analysis (DEA) is an appropriate tool for measuring the relative efficiency of nonprofit organizations using multiple inputs and outputs. Similarly, the results support Kong (2010) [28], who argued that DEA enables organizations to identify resource wastage and establish performance improvement targets without increasing available resources. The findings further agree with Sarrico and Dyson (2004) [42], who demonstrated that DEA identifies benchmark organizations capable of guiding weaker institutions towards improved performance.

Likewise, the study corroborates Emrouznejad and Yang (2018) [19] and Verschuere and Suykens (2020) [47], who highlighted DEA as a robust approach for measuring efficiency and enhancing accountability in nonprofit organizations.

The findings are broadly consistent with the study's a priori expectation that NGOs should utilize available resources efficiently to maximize outputs. However, the large proportion of highly inefficient NGOs indicates that many organizations are yet to achieve optimal resource utilization. This suggests that considerable opportunities exist for improving managerial practices, resource allocation, planning, and operational performance. The observed differences in efficiency further imply that NGOs vary considerably in their ability to convert scarce financial, human, and institutional resources into developmental outcomes. The findings also support the theoretical foundations underpinning the study. They are consistent with Productive Efficiency Theory (Farrell, 1957) [20], which posits that organizations achieve superior performance by maximizing outputs from available inputs while minimizing resource wastage. Similarly, the findings align with Systems Resource Theory (Yuchtman and Seashore, 1967) [53], which argues that organizational effectiveness depends on the ability to acquire, utilize, and sustain valuable resources from the external environment. The variation in efficiency observed among NGOs demonstrates that effective resource utilization remains central to organizational performance and sustainability. The findings have important policy implications for governments, donors, NGO regulatory agencies, and NGO managers. Policymakers should institutionalize routine efficiency assessments using DEA to monitor organizational performance and identify best-performing NGOs that can serve as benchmarks. Donors should complement financial assistance with technical support aimed at improving managerial capacity and resource utilization, while regulatory agencies should incorporate efficiency evaluation into NGO oversight frameworks. Furthermore, NGO managers should adopt best practices in planning, resource allocation, monitoring, and evidence-based decision-making to improve operational efficiency, enhance accountability, strengthen donor confidence, and ensure the long-term sustainability of NGO interventions.

Comparative Analytical Discussion of Efficiency of INGO and LNGO in Mezam, Division, Cameroon From the perspective of cosmopolitanism, humanitarianism, the Responsibility to Protect (R2P), and liberal internationalism, international organizations are better positioned to lead humanitarian interventions because humanitarian obligations transcend national boundaries. Cosmopolitanism maintains that all individuals belong to a global moral community, imposing a universal duty on international actors to protect human dignity regardless of nationality (Kant, 1795/2006; Pogge, 2008) [25, 39]. Similarly, humanitarianism emphasizes that assistance should be delivered impartially, independently, and solely according to need, principles that international organizations such as the United Nations, the International Committee of the Red Cross (ICRC), and international NGOs are often better equipped to uphold due to their financial resources, technical expertise, operational experience, and global coordination mechanisms (Weiss, 2016) [48].

Likewise, the Responsibility to Protect doctrine argues that when states are unable or unwilling to protect their populations from mass atrocities, the international community has a collective responsibility to intervene (United Nations, 2005) [44]. Liberal internationalism further reinforces this position by advocating collective action through international institutions to address humanitarian crises that exceed national capacities (Ikenberry, 2018) [23].

Conversely, the localisation agenda argues that local and national organizations should assume a leading role in humanitarian action because they possess contextual knowledge, community trust, cultural competence, and long-term presence that international actors often lack. The Grand Bargain of the 2016 World Humanitarian Summit recognized that humanitarian responses become more effective, accountable, and sustainable when leadership and resources are transferred to local actors. According to the Inter-Agency Standing Committee (IASC, 2022) [24], localisation strengthens local ownership, resilience, and accountability by placing affected communities at the centre of humanitarian decision-making. Similarly, Barbelet (2018) [5] contends that local organizations are better positioned to identify community priorities, respond rapidly, and sustain interventions after international agencies withdraw. Nevertheless, while localisation promotes sustainability and community empowerment, large-scale emergencies frequently require the financial capacity, technical expertise, and international coordination possessed by international organizations. Consequently, contemporary humanitarian practice increasingly advocates complementarity rather than competition, where international organizations provide strategic support and resources while local organizations lead implementation and community engagement.

6. Recommendations

To improve the efficiency of NGOs, organizations should institutionalize routine efficiency assessments using Data Envelopment Analysis (DEA) and other performance measurement tools to monitor resource utilization, identify operational weaknesses, and implement corrective actions. NGOs should also benchmark their operations against highly efficient organizations and adopt best practices in financial management, governance, and service delivery. Strategic resource allocation based on evidence-driven budgeting should be prioritized to ensure that financial, human, and material resources are directed toward programmes with the greatest developmental impact. Furthermore, governments, donors, and development partners should strengthen capacity-building initiatives by providing continuous training in project management, strategic planning, monitoring and evaluation, and financial management. Donors are encouraged to adopt performance-based funding mechanisms that reward efficient resource utilization, accountability, and measurable organizational outcomes.

Additionally, NGOs should establish robust monitoring and evaluation systems with clearly defined performance indicators to facilitate continuous performance assessment and informed decision-making. The Government of Cameroon should develop national efficiency benchmarking standards to promote sector-wide performance improvement and accountability. Greater collaboration and knowledge sharing among NGOs should be encouraged through networks and forums that facilitate the exchange of best practices and innovations. NGOs should also diversify funding sources through partnerships, community mobilization, and income-generating activities to enhance sustainability and reduce donor dependency. Finally, policymakers should strengthen regulatory frameworks that promote transparency, performance audits, and efficiency reporting, while adopting the proposed five-category efficiency classification scale—Fully Efficient, Highly Efficient, Moderately Efficient, Fairly Inefficient, and Highly Inefficient—to guide performance evaluation and policy interventions.

7. Conclusion

Improving NGO efficiency requires a sustained commitment to evidence-based management, continuous performance evaluation, and strategic resource optimization. The study demonstrates that systematic application of Data Envelopment Analysis (DEA) and related performance tools can significantly enhance transparency, accountability, and operational effectiveness across NGOs. By benchmarking against fully efficient organizations, NGOs can identify performance gaps and adopt best practices in governance, financial management, and service delivery. This approach ensures that limited resources are directed toward high-impact interventions, thereby maximizing developmental outcomes and strengthening donor confidence in the sector. Furthermore, the findings highlight the need for stronger institutional support, particularly through capacity building, regulatory reforms, and performance-based funding mechanisms. Governments, donors, and development partners must collaborate to institutionalize efficiency standards and promote a culture of continuous improvement. The adoption of a standardized efficiency classification system will further guide policy decisions and organizational reforms. Ultimately, enhancing NGO efficiency is essential for achieving sustainable development, improving service delivery, and ensuring long-term impact in communities.