By
Egbunu, Theresa Ilayi
egbubutessy@gmail.com
And
Iluyomade Martins
Iluyomade.martins@gmail.com
Doctor of Strategic Management and Leadership
Development (DSMLD) Learn To Live Business School
ABSTRACT
The study investigated applying the Ability-Motivation-Opportunity (AMO) model to enhance employee performance in Nigerian Public Sector Entities (PSEs). The study was guided by three objectives: to examine the impact of training and development initiatives, financial and non-financial incentives, and a supportive work environment on employee performance. A quantitative methodology was used, with data collected through structured questionnaires administered to 133 employees within Nigerian PSEs. Descriptive and inferential statistics, including multiple regression analysis, were employed to assess relationships between AMO components and performance outcomes. The data was analysed using Jamovi Statistical Software (version 2.3.28). Findings showed a positive and significant influence of training, incentives, and supportive work environments on employee performance, validating the AMO model’s relevance in this context. Specifically, each component—ability through training, motivation via incentives, and opportunity through supportive environments—significantly contributes to performance enhancement. The study concluded that the AMO model provides a robust framework for understanding and improving employee performance in Nigerian PSEs. The study recommends targeted investments in training, strategic incentives, and the development of supportive work conditions to maximize employee productivity.
INTRODUCTION
1.1 Background of the Study
Employee performance is a critical determinant of organisational success and has been extensively studied across various contexts. Globally, employees’ performances are often viewed as a crucial success variable influenced by several factors, including learning and skills development, performance management, incentives and supportive work environments, job/work design, and career development opportunities (Tuffaha, 2020; Zhenjing et al., 2022). Recent studies demonstrate that effective learning and skills development programmes significantly enhance employees’ abilities (skills and knowledge), leading to improved job performance (Arulsamy et al., 2023). Similarly, financial and non-financial incentives have been shown to motivate employees to perform better (Manjenje & Muhanga, 2021). Additionally, a supportive work environment — characterised by job/work design, career development, autonomy, and a collaborative culture—provides the opportunities employees need to excel in their roles (Radu, 2023).
The Ability-Motivation-Opportunity (AMO) model, developed by Boxall and Purcell (2003), serves as a valuable framework for examining how these factors can be aligned to enhance employee performance. The model posits that performance (P) is a function of an individual’s ability (A), motivation (M), and opportunity (O) to perform, encapsulated in the equation P = f(A, M, O). This suggests that optimal performance occurs when these three components—ability, motivation, and opportunity—are effectively aligned (Boxall & Purcell, 2016; Bos-Nehles, et al., 2023). According to Armstrong and Brown (2019), an individual’s performance is influenced not only by their skills, knowledge, and aptitudes but also by their desire or obligation to perform and the support provided by the work environment.
Ability refers to the skills and competencies employees possess, which are crucial for job performance. Human resources management initiatives like robust recruitment and ongoing learning and development ensure employees have the necessary abilities (Armstrong and Brown 2019; Mohammad, Showkat & Imran, 2020; Supriya, et al., 2023). Effective talent management further aligns these abilities with organisational needs, ensuring a capable and adaptable workforce (Al Aina & Atan, 2020; Ngiu, et al., 2021). Motivation drives employees to apply their abilities effectively. Performance management systems, performance-based pay, and leadership development are key motivators (Gerhart & Fang, 2015; Armstrong and Brown (2019). Regular feedback and performance-based rewards (financial and non-financial) encourage higher performance, while leadership development fosters a culture that inspires employees to excel (Neves & Eisenberger, 2014; Mbukwana & Ayandibu, 2023). The opportunity involves the organisational environment that allows employees to utilise their abilities and motivation. Human resources management practices focusing on job design, work environments, and career management create opportunities for employees to perform optimally (Armstrong and Brown (2019). These initiatives provide the necessary support and growth paths, leading to enhanced job satisfaction and performance (Anwar, & Abdullah, 2021).
1.2 Statement of the Problem
Despite the global applicability of the AMO model, its relevance in the context of the Nigerian public sector is under-researched (Abboh, Majid & Fareed, 2019). PSEs in Nigeria are often marked by inefficiencies and poor performance. Notwithstanding efforts to reform and improve this sector, challenges such as inadequate training, low motivation, and unsupportive work environments persist. Training programmes often fail to meet employees’ actual needs, leading to a skills mismatch and a gap in their ability to perform their duties effectively (Omale et al., 2023). Economic instability and bureaucratic challenges undermine incentive schemes, resulting in low motivation. Additionally, many public sector organisations lack the necessary resources and conducive environments for optimal performance (Osawe, C.O. 2015; Abah & Nwokwu, 2016). These issues are particularly critical, given the sector’s role in delivering essential services and driving national growth.
Given these challenges, this study focuses on enhancing employee performance within the Nigerian public sector by applying the Ability-Motivation-Opportunity (AMO) model model. AMO model which links employee performance to their ability, motivation, and the opportunities provided by their work environment, offers a promising framework for addressing these challenges For example, previous applications of the model in different contexts have shown significant performance improvements when ability, motivation, and opportunity are adequately addressed (Kellner, Cafferkey, & Townsend, 2019; Bos-Nehles, et al., 2023). However, while the model has been successfully implemented in various other contexts to improve performance, its effectiveness in the Nigerian public sector, with its unique challenges, is not well-documented.
1.3 Purpose of the Study
The overarching purpose of this study is to explore how the Ability-Motivation-Opportunity (AMO) model can be leveraged to enhance employee performance in Nigerian PSEs.
1.4 Objectives
To achieve this aim, the study is guided by the following specific objectives:
- To analyse the impact of learning and skills development programmes (Ability) on employee performance in Nigerian PSEs.
- To investigate how financial and non-financial incentives (Motivation) influence employee performance in PSEs.
- To determine the impact of a supportive work environment (Opportunities) on employee performance in Nigerian PSEs.
1.5 Research Questions
1. How do learning and skills development initiatives impact the employees’ performance in Nigerian PSEs?
2. How do financial and non-financial incentives influence employee performance in Nigerian PSEs?
3. How does a supportive work environment impact employee performance in Nigerian PSEs?
1.6 Research Hypotheses
HO₂: There is no significant influence of financial and non-financial incentives (motivation) on the performances of employees in Nigerian PSEs.
HO₃: There is no significant impact of a supportive work environment (opportunities) on the performances of employees in Nigerian PSEs
METHODOLOGY
2.1 Research Design
The study employs a quantitative, correlational research design (Creswell, 2014; Apuke, 2017), to explore the relationship between the Ability-Motivation-Opportunity (AMO) model and employee performance. This design is appropriate as it enables the researcher to focus on measurable data, offering objective and generalizable results (Devi, et. al., 2023). A cross-sectional approach is used, which involves collecting data at a single point in time (Setia, 2016). This approach is practical because it provides a snapshot of how employees perceive AMO factors concerning performance, allowing for timely and broad generalisations (Bryman & Bell, 2015; Kellner, et al., 2019). A structured survey questionnaire was utilised to ensure systematic data collection, offering consistency across a large, diverse sample (Saunders et al., 2016).
2.2 Population / Sampling Technique
The study focuses on a population of 200 employees from public and private sector entities across diverse industries and organisational sizes in Nigeria. To ensure the sample accurately reflects the population’s diversity, a stratified random sampling technique is used. This method is appropriate because it divides the population into key subgroups (or strata) such as sector and job level and randomly selects participants from each stratum, ensuring each subgroup is represented (Saunders et al., 2019). Additionally, snowball sampling is employed to reach participants through referrals. This technique is particularly effective when some participants may be difficult to access directly, ensuring broader reach and inclusivity in the sample (Leighton et al., 2021). For questionnaire distribution, the sample size of 133 is determined using Yamane’s (1967) sample size determination technique.
2.3 Instrument(s)
This study utilises a structured questionnaire based on validated measures to ensure reliability and relevance. The questionnaire consists of three key sections aligned with the research objectives: Training and Development, Incentives and Rewards, and Supportive Work Environment. Additionally, Employee Performance is measured as the dependent variable.
For Training and Development Initiatives, the Learning and Development Scale (LDS) (Aguinis & Kraiger, 2009) was used to measure the impact of training initiatives on employee performance. Items assess the relevance, effectiveness, and application of training programs in the workplace.The Multidimensional Work Motivation Scale (MWMS) adapted from Gagné et al., (2015) was used to measure the influence of financial and non-financial rewards. To evaluate a supportive work environment, the Perceived Organizational Support (POS) Scale developed by Eisenberger et al. (1986) was used. It measures employees’ perceptions of organisational support and its influence on performance. Additionally, the Job Diagnostic Survey (JDS) by Hackman (1980) was employed to assess job design and its conduciveness to employee satisfaction and performance.Employee performance was measured using the Individual Work Performance Questionnaire (IWPQ) developed by Koopmans et al., 2014). This scale evaluates task performance, contextual performance, and counterproductive work behavior.
The questionnaire uses a Likert scale of 1-5 (strongly disagree to strongly agree) to measure participants’ responses (Chyung, et al., 2017), which is appropriate for quantifying perceptions, making it easier to analyse the data statistically (Tanujaya, et. al., 2023). This instrument is chosen for its ability to provide structured, consistent responses across a large sample, facilitating clear and measurable insights (Sullivan, 2013).
2.4 Method of Data Collection
The data is collected electronically using Google Forms, and distributed via email, Telegram, and WhatsApp platforms. This method is appropriate as it provides participants the flexibility to respond at their convenience, thereby increasing response rates (Vasantha & Harinarayana, (2016). Google Forms is particularly suitable for its cost-effectiveness, accessibility across devices, and real-time data collection capabilities, which enable convenient, easy, and quick data collection (Holtom et al., 2022). Moreover, the anonymity offered by Google Forms ensures participant confidentiality, promoting honest and accurate responses while adhering to ethical research standards (Kang & Hwang, 2023).
2.5 Method of Data Analysis
The collected data is analysed using both descriptive and inferential statistics. Descriptive statistics, such as mean, standard deviation, and frequency distribution, provide a summary of key trends within the data, which is essential for understanding the general characteristics of the sample (Creswell, 2014). Inferential statistics, specifically correlation and multivariate regression, are used to test relationships between AMO components and employee performance, making this method appropriate for establishing whether the independent variables (AMO factors) significantly influence the dependent variable (employee performance) (Ugwu et al., 2021). The analysis is conducted using Jamovi statistical software (Version 2.3.8), chosen for its user-friendly interface and robust analytical capabilities, ensuring precise and efficient data analysis (Dibekulu, 2020).
RESULTS
Responses from the 133 participants were labeled according to the variables of the study coded, and exported to Jamovi software. Reliability analysis, descriptive statistics, correlation, and multivariate regression analyses were conducted and the results of the study are presented in accordance with the research questions and hypotheses.
3.1 Reliability Results
The reliability analysis (see Appendix 1) shows strong internal consistency across all scales. The overall scale has a Cronbach’s α of 0.869, indicating good reliability. The Ability (ABT) scale has excellent reliability with a Cronbach’s α value of 0.910. The Motivation (MOT and Opportunity (OPT) scales show good reliability, with values of 0.884 and 0.879, respectively. The Employee Performance (EMP) scale also demonstrates good reliability, with Cronbach’s α of 0.843. Overall, all scales have Cronbach’s α values above 0.70, indicating they are reliable for further analysis (Taber, 2018).
3.2 Descriptive Statistics
The Descriptives statistics in Table 1 summarise the mean, median, standard deviation, variance, minimum, and maximum scores for the predictor variables – Ability (ABT), Motivation (MOT), and Opportunity (OPT) scales – and the Dependent variable – Employee Performance (EMP) scale.
| Table 1: Descriptives Statistics of the variables | |||||||||
| ABT | MOT | OPT | EMP | ||||||
| N | 133 | 133 | 133 | 133 | |||||
| Missing | 0 | 0 | 0 | 0 | |||||
| Mean | 4.02 | 4.66 | 3.95 | 4.04 | |||||
| Median | 4.00 | 4.80 | 4.00 | 4.00 | |||||
| Standard deviation | 0.688 | 0.859 | 0.673 | 0.563 | |||||
| Minimum | 1.00 | 1.20 | 1.60 | 2.00 | |||||
| Maximum | 5.00 | 5.00 | 5.00 | 5.00 | |||||
Source: Jamovi Output
The mean scores for the variables show that responses are generally high. MOT has the highest mean at 4.66, indicating that participants rated motivation quite positively, while ABT and EMP have similar mean values of 4.02 and 4.04, respectively. OPT has the lowest mean at 3.95, though it is still relatively close to the others.
In variability, MOT has the highest standard deviation (0.859), suggesting that responses for motivation varied more than for the other variables. EMP has the lowest standard deviation at 0.563, indicating more consistent responses for employee performance. The standard deviations for ABT and OPT are 0.688 and 0.673, respectively, reflecting moderate variability responses.
The maximum and minimum values indicate the highest and lowest scores for each variable. Minimum scores are 1.00 (ABT), 1.20 (MOT), 1.60 (OPT), and 2.00 (EMP), reflecting low ratings from some respondents. Maximum scores are 5.00 for ABT, OPT, EMP, and MOT, showing higher ratings. These values highlight the range of responses in the dataset.
Essentially, the descriptive statistics suggest that Ability (ABT), Motivation (MOT), and Opportunity (OPT) are positively perceived and likely to influence employee performance, as shown by high mean scores. The higher variability in MOT suggests motivation may require more focus for improving performance, while the low variability in EMP indicates consistent employee performance. Overall, the AMO factors are relevant and impactful in explaining employee performance outcomes.
3.3 Correlation Results
The correlation matrix in Table 2 reveals the relationships between the independent variables—Ability (ABT), Motivation (MOT), and Opportunity (OPT)—and the dependent variable, Employee Performance (EMP).
| Table 2: Correlation Matrix | |||||||||||
| ABT | MOT | OPT | EMP | ||||||||
| ABT | Pearson’s r | — | |||||||||
| p-value | — | ||||||||||
| MOT | Pearson’s r | 0.472 | — | ||||||||
| p-value | < .001 | — | |||||||||
| OPT | Pearson’s r | 0.480 | 0.781 | — | |||||||
| p-value | < .001 | < .001 | — | ||||||||
| EMP | Pearson’s r | 0.620 | 0.764 | 0.771 | — | ||||||
| p-value | < .001 | < .001 | < .001 | — | |||||||
Source: Jamovi Output
Ability (ABT) and Employee Performance (EMP): There is a moderate positive correlation (r = 0.620, p < 0.001) between ABT and EMP. This indicates that as employees’ abilities increase, their performance tends to improve as well.
Motivation (MOT) and Employee Performance (EMP): The correlation is strong (r = 0.764, p < 0.001), suggesting that higher motivation is significantly associated with better employee performance. This highlights the critical role that motivation plays in driving performance outcomes.
Opportunity (OPT) and Employee Performance (EMP): Similarly, there is a strong positive correlation (r = 0.771, p < 0.001) between OPT and EMP. This implies that when employees perceive greater opportunity within their organisation, their performance levels will likely rise.
3.4 Linear Regression Results
| Table 3: Model Fit Measures | |||||||||||||||
| Overall Model Test | |||||||||||||||
| Model | R | R² | Adjusted R² | F | df1 | df2 | p | ||||||||
| 1 | 0.849 | 0.721 | 0.714 | 111 | 3 | 129 | < .001 | ||||||||
Source: Jamovi Output
In Table 3, the correlation coefficient (R = 0.849) reflects a robust positive relationship between the independent variables and Employee Performance (EMP), suggesting that the model effectively captures significant variance in performance outcomes. The coefficient of determination (R² = 0.721) shows that approximately 72.1% of the variance in employee performance can be explained by the independent variables, indicating a good fit for the model. The adjusted R² value of 0.714 confirms that the model remains effective even after accounting for the number of predictors. Lastly, the F-statistic (111) and p-value (< 0.001) indicate statistical significance, suggesting that the independent variables collectively contribute to employee performance, leading to the rejection of the null hypothesis. Overall, these measures demonstrate that the model is well-suited for the data and effectively captures the relationships between the independent variables and employee performance.
| Table 4: Model Coefficients – Employee Performance | |||||||||
| Predictor | Estimate | SE | t | p | |||||
| Intercept | 0.849 | 0.1811 | 4.69 | < .001 | |||||
| ABT | 0.230 | 0.0441 | 5.22 | < .001 | |||||
| MOT | 0.226 | 0.0496 | 4.56 | < .001 | |||||
| OPT | 0.306 | 0.0636 | 4.82 | < .001 | |||||
Source: Jamovi Output
The model coefficients for Employee Performance (EMP) indicate the impact of each predictor variable – Ability (ABT), Motivation (MOT), and Opportunity (OPT)—on employee performance outcomes.
The coefficient of Ability (ABT) is 0.230, with a standard error of 0.0441. The t-value of 5.22 and p-value of less than 0.001 indicate a significant positive relationship between ABT and EMP. This means that higher ability is associated with improved employee performance.
Motivation (MOT) has a coefficient of 0.226, a standard error of 0.0496, a t-value of 4.56, and a p-value of less than 0.001. This also suggests a significant positive impact of motivation on employee performance.
Lastly, the coefficient for Opportunity (OPT) is 0.306, with a standard error of 0.0636, a t-value of 4.82, and a p-value of less than 0.001. This indicates that greater opportunities are strongly associated with enhanced employee performance.
Overall, all three predictors—ABT, MOT, and OPT—are statistically significant and positively contribute to employee performance.
3.5 Test of Hypotheses
To test the research hypotheses, each null hypothesis (H0) was evaluated against the corresponding statistical evidence derived from the model coefficients and associated p-values. Statistical significance of p < 0.05.
Since the coefficient for Ability (ABT) has a t-value of 5.22 with a p-value of < 0.001, there is a significant effect of training and development initiatives on employee performance. Therefore, the null hypothesis (H0₁) that “there is no significant effect of learning and skills development initiatives (ability) on performances of employees in Nigerian PSEs”is rejected.
The Motivation (MOT) coefficient shows a t-value of 4.56 with a p-value of < 0.001. This indicates a significant influence of financial and non-financial incentives and rewards on employee performance. Therefore, the null hypothesis (H0₂) which states that“there is no significant influence of financial and non-financial incentives (motivation) on the performances of employees in Nigerian PSEs” is rejected.
The Opportunity (OPT) coefficient has a t-value of 4.82 with a p-value of < 0.001. This demonstrates the significant effect of a supportive and conducive work environment on employee performance. Therefore, the null hypothesis (H0₃) that“there is no significant impact of the supportive work environment (opportunities) on performances of employees in Nigerian PSEs” is rejected.
3.6 Summary of Findings
The results revealed the following major findings:
- Training and development initiatives have a significant positive impact on employee performance, as evidenced by a t-value of 5.22 and a p-value of < 0.001.
- Financial and non-financial incentives and rewards significantly influence employee performance, with a t-value of 4.56 and a p-value of < 0.001.
- A supportive and conducive work environment has a significant effect on employee performance, as shown by a t-value of 4.82 and a p-value of < 0.001.
- Overall, each component of the AMO model (Ability, Motivation, and Opportunity) contributes positively and significantly to enhancing employee performance.
DISCUSSION
This study aimed to explore the effectiveness of the Ability-Motivation-Opportunity (AMO) model in enhancing employee performance within Nigerian Public Sector Entities (PSEs), focusing on the impact of training and development, incentives, and a supportive work environment. The findings align with and build on previous research, offering valuable insights into how these components influence performance.
The results reveal that training and development initiatives significantly improve employee performance, supporting previous research by Arulsamy et al. (2023) and Armstrong and Brown (2019), which emphasize that learning and skill development programmes enhance employees’ abilities. This increase in ability equips employees with the necessary competencies, as posited by Mohammad, Showkat, and Imran (2020) and Supriya et al. (2023), thereby fostering an adaptable and capable workforce.
The influence of financial and non-financial incentives on performance is also significant in this study, reinforcing findings from Manjenje and Muhanga (2021) and Gerhart and Fang (2015). These scholars demonstrate that incentives are powerful motivators that encourage employees to perform at higher levels. This aligns with the AMO model’s component of motivation, showing that rewards—both material and psychological—drive employees to apply their abilities effectively in the workplace.
Furthermore, the supportive work environment component was found to have a substantial effect on employee performance. In consonance with Radu (2023) and Zhenjing et al. (2022), this study shows that a conducive work environment characterised by autonomy, collaborative culture, and career development opportunities creates essential conditions for performance improvement. Armstrong and Brown (2019) and Anwar and Abdullah (2021) also highlight how job design and career management play critical roles in providing employees with the necessary opportunities to apply their abilities and motivation optimally. The present study thus confirms the central tenet of the AMO model, which posits that performance is maximised when employees are provided with the necessary skills (ability), motivation, and opportunity within a supportive environment.
In summary, the findings across all three objectives reinforce the AMO model, proposed by Boxall and Purcell (2003), which posits that performance is a function of an individual’s ability, motivation, and opportunity. This study supports that performance is maximised when all three components are aligned and adequately provided, consistent with global and local empirical evidence. This alignment implies that organisations seeking to optimise employee performance should consider an integrative approach that addresses each aspect of the AMO framework, ensuring employees are well-trained, motivated, and supported within their work environment.
4.4 Implications of the Study
The findings from this study hold significant implications for various stakeholders. Firstly, public sector managers can leverage insights on training, incentives, and supportive environments to structure more effective performance improvement strategies, addressing specific areas like skill gaps and motivational needs. Policymakers in Nigeria’s civil service and government agencies can use these findings to design and implement frameworks that align with the AMO model, ensuring resources are allocated to employee development and supportive work environments. Lastly, employees themselves stand to benefit, as improved training programs, incentives, and work conditions can lead to increased job satisfaction and productivity, ultimately enhancing service delivery in the public sector.
CONCLUSION AND RECOMMENDATIONS
5.1 Conclusion
This study concludes that applying the Ability-Motivation-Opportunity (AMO) model to Nigerian Public Sector Entities (PSEs) can significantly enhance employee performance by aligning training, incentives, and workplace support with practical needs.
5.2 Recommendations
- Nigerian PSEs should conduct regular needs assessments to tailor training programs that directly enhance employee skills relevant to job demands, to address the prevalent mismatch between training and workplace needs.
- Financial and non-financial incentive structures should be reinforced to counteract economic instability, ensuring that employees feel motivated and valued for their contributions.
- PSEs should invest in resources and facilities that create a conducive work environment, such as collaborative tools, adequate facilities, and clear support mechanisms that empower employees to perform effectively.
5.3 Contribution to Knowledge
This study contributes to knowledge by providing empirical evidence on the practical application of the AMO model in Nigeria’s public sector, where it has been underexplored. By identifying the impact of ability, motivation, and opportunity on performance, the research addresses gaps in understanding how these factors interact within Nigerian PSEs and highlights actionable steps for enhancing public sector productivity.
5.4 Suggestions for Further Studies
Future research could explore the sustained effects of specific AMO model components, such as customised training initiatives or incentive structures, on employee performance in Nigerian public sector organisations. Additionally, examining how cultural and economic factors influence the AMO model’s effectiveness across various regions or industries in Nigeria would provide a broader understanding of its applicability.