The performance of governments in the delivery of services to the pub-lic—which constitutes the customers who are the tax payers, is affected and influenced by a multitude of factors, some controllable and others outside the control of governments. In addition, each of the diverse factors impacts uniquely on performance while others may have only tangential influence. According to Hansen (1989), there are two streams of research regarding the determinants of firm performance. One is based on the economic tradition and emphasizes external market factors that are largely outside the control of firm management, while the other builds on the behavioral and sociological paradigms focusing on organizational factors as they fit into the environment; the latter therefore focuses on factors internal to the firm. A combination of various factors working together however, has the potential to generate a blend of influences, which is a significant departure from the impact of any factor tak en on its own. The ensuing study is set out to establish the joint effect of performance measurement, political stability and global competitiveness—critical internal and external factors that affect or influence the performance of governments—on public service delivery and its customer satisfaction derivative in Kenya. The study was based on the results of measurement and evaluation of the performance of 470 public agencies that operated on performance contracts between 2004 and 2011. Using regression analysis, it was found initially that each of the three factors had a uniquely significant effect on the relationship between public service delivery and customer satisfaction, with performance measurement showing a strong positive relationship (R = 0.858) with customer satisfaction. Performance measurement explained 73.6 percent (R2 = 0.736) of customer satisfaction levels with the remaining 26.4 percent accounted for by other factors. Global competitiveness on the other hand, had a weak positive relationship with customer satisfaction. The results showed that global competitiveness explained 0.7 percent (ΔR2 = 0.007) on the direct effect of performance measurement on customer satisfaction and had an average mean of 3.698 on a scale of 1 (very low) and 5 (very competitive). It turned out that there was no significant moderating effect of global competitiveness on the relationship between performance contracting, measurement and public service delivery in Kenya. The performance measurement variable had a t-value of 5.789 and was statistically significant while the effect of global competitiveness was positive although not statistically significant. Preliminary findings established initially that on its own, political stability had no significant relationship with or influence on customer satisfaction. It however had an effect on the relationship between performance contracting, measurement and public service delivery, where a unit change in political stability contributed negatively to customer satisfaction by a factor of 0.235, though not statistically significant. Correlation analysis established further that social chaos and turmoil, which result in political instability, negatively influenced the attractiveness of a country in the global arena. Overall, the results showed that performance measurement, political stability and global competitiveness were positively related to customer satisfaction. The joint effect of the three independent variables explained 78.5 percent (R2 = 0.785) of customer satisfaction levels with the remaining 21.5 percent accounted for by other factors implemented in the public sector.
There has been general consensus among practitioners of government performance management, academicians and bureaucrats that excellence in public service delivery is impelled by improvement in organizational performance. One cannot for example, expect excellence in transport services if the transport infrastructure, roads and rail are not well developed, organized and maintained, just as much as health services cannot approach excellence if drugs procurement and administration, personnel recruitment and medical task assignment are not done right. Neither can security services be excellent if the security forces are not well trained and disciplined, all of which fall into the realm of operational efficiency. This logic resonates with the essence of this study, that excellence in service delivery is predicated on and influenced by improvement in operational performance, while the latter is predicated on measurement as a prerequisite, as observed above. Performance measurement is a central mechanism in both assessment and evaluation, which provides the required data for identifying the most appropriate interventions to measurably improve performance (Guerra-López, 2008 [
The study revolved around the key construct of performance contracting and its flagship tool of performance measurement as veritable implements in the management, improvement and measurement of performance and the consequent derivative of excellence in public service delivery. This is essentially a system that has been described as ideally grounded in theory, supported by research, and that is able to communicate complex relationships, while maintaining simplicity; and should be sensitive to transactional relationships across performance levels (that is, individual, group, organizational and external impact).
Moreover, these postulates are solidly grounded on key performance management theories, among them the following:
1) Systems theory which addresses with systemic disconnects that affect performance adversely such as failure to clearly specify expected outcomes of an organization, and not having a clearly defined performance improvement system.
2) Theory of organizational performance management (OPM) which relates to a set of techniques used to measure success in meeting goals in a business context and is used to evaluate specific processes and systems, the performance of departments or the performance of individual employees.
3) Resource-Based Theory of Competitive Advantage which addresses the assessment of the potential of the resources for value generation and ends up by defining a strategy that will allow the capturing of maximum of value in a sustainable way and provides a basis for assessing whether or not program results are being achieved. As such they answer three questions: What is the program trying to achieve? How is the program progressing? Have desired results been achieved?
4) Results-Based Accountability Systems calls for institutions to take responsibility for initiating some action and the results of that action. It requires that organizations articulate how public monies will be spent on services and products that have an impact on people’s lives, monitor how effectively and efficiently these programs work, and take action to improve program results.
5) Total Quality Management aims to solve problems based on external customer satisfaction. TQM defines quality in terms of customer satisfaction and proceeds to analyze processes and work roles in an organization to seek ways to improve quality. TQM is a strategic management approach that aims to improve business as a whole and add value to customers.
6) Management by objectives (MBO) an operations strategy and modern performance appraisal method where the employee and the supervisor come together to identify common goals, chart down specific objectives and fix targets for the attainment of such goals within the specified period. MBO objectives usually relate to corporate goals and vision and the scope of the targets designed to meet such objectives remain confined to day-to-day applications. Management by Objectives seeks to solve problems based on internal goals and targets.
Performance measurement is a central mechanism in both assessment and evaluation, which provides the required data for identifying the most appropriate interventions to measurably improve performance (Guerra-López, 2008 [
According to Hansen, (1989), as referred in above references, there are two streams of research regarding the determinants of firm performance. One is based on the economic tradition and emphasizes external market factors, while the other builds on the behavioral and sociological paradigms focusing on organizational factors as they fit into the environment; the latter therefore focuses on factors internal to the firm. Organizational researchers have developed a wide variety of performance models and suggested that managers can influence organizational performance by influencing the behavior of employees. This entails taking consideration of multiple factors, among them the formal and informal structures, planning, reward, control and information systems, their skills and personalities and relating these to the environment.
One research stream that has managed to capture these multidimensional aspects is that of organizational climate. The latter encompasses the perceived properties and characteristics found in the work environment that result from actions taken consciously or unconsciously by an organization and which affect behavior. It refers to a broad class of organizational and perceptual variables that reflect individual organizational interactions which affect the behavior of the individual and provides the conceptual link between analysis at the organizational level and at the employee level. This means that changes in organizational structures, systems and practices can alter climate measures and hence individual performance. Other studies have suggested that organizational climate was directly linked to performance and that there are strong linkages between managerial practices and dimensions of organizational climate and firm performance. These studies brought out three key classes of factors that influence performance. These are the following: Organizational factors―structure, systems, size, history; Environmental factors―political, sociological, economic, and technological; and People factors―skills, personalities, age.
The study selected key constructs from each of the three categories. That is; organizational factors―performance contracting and measurement system, environmental factors―political stability and global competitiveness and people factors―effective and efficient public service. As discussed later in this study the issue of political stability is critical to the performance of the public service and the country at large.
Alesina et al. (1992: 2) [
The report contends however, that in Asia in particular, the so-called tiger economies either have political stability that is not as democratic as the ideal is, or, they are plagued by political instability leading to much volatility in the development of their country. FIDH, (2008 [
In Kenya, following positive political reforms subsequent to the post-election skirmishes of 2007/08, the country has attained a stable political equilibrium that has seen growth in real GDP rise from the measly 1.7% in 2008 to the 5.6 predicted for 2016!
Data on global competitiveness is compiled by the World Economic Forum (WEF) of the World Bank. The World Economic Forum in its Global Competitiveness Report, defines competitiveness in the context of a grouping of factors that drive productivity and competitiveness. These include institutions, infrastructure, the macro economy, health and primary education, higher education and training, market efficiency, technological readiness, business sophistication and innovation. The level of productivity, in turn, sets the level of prosperity that can be reached by an economy.
The productivity level also determines the rates of return obtained by investments in an economy, which in turn are the fundamental drivers of its growth rates. In other words, a more competitive economy is one that is likely to grow faster over time. The concept of competitiveness thus involves static and dynamic components. Although the productivity of a country determines its ability to sustain a high level of income, it is also one of the central determinants of its return on investment, which is one of the key factors explaining an economy’s growth potential. The index organizes the pillars into three sub-indexes: efficiency enhancers, innovation and sophistication factors and is based on a 1 - 5 scale (the higher the average score, the higher the degree of competitiveness).
The Global Competitiveness Indices for Kenya for the years 2006/07, 2007/08, 2008/09, 2009/10 and 2010/11 were, respectively, 3.57, 3.61, 3.84, 3.67 and 3.65.
The orientation of the study was positivistic and employed a cross-sectional design entailing identification of the research problem, review of previous and synthesizing of published literature, and specifying of hypotheses relating to the research questions. The study sought to explore the Joint Effect of Performance Measurement, Political Stability and Global Competitiveness on Customer Satisfaction in the delivery of public services in Kenya. The hypothesis that formed the basis of the study was that there is no significant joint effect of political stability and global competitiveness on the relationship between performance contracting and measurement and public service delivery in Kenya.
The study relied on secondary data drawn from the results of measurement and evaluation of the performance of public agencies on performance contract for the period 2007 to 2011, which was readily available. In 2010/11, which was the terminal year for data collection and analysis, the number of public agencies on performance contract was 470, made up of 46 ministries and accounting departments, 178 state corporations, 175 local authorities and 71 tertiary institutions. The focus of the study was the entire population of 470 public agencies. Further, the various categories of public agencies had, by 2010/11, been on performance contract for differing periods; these are 6 years for both ministries and state corporations, 5 years for local authorities and 4 years for tertiary institutions.
The study focused on the five years of 2006/07, 2007/08, 2008/09, 2009/10 and 2010/11, during which period customer satisfaction in the majority of the categories of public agencies was measured. The distribution of the various categories of institutions is shown in
The performance measurement and evaluation methodology in Kenya graded excellence on a composite-scoring scale ranging from 1 to 5 with 1 denoting
Category of MDA | No. | Percent |
---|---|---|
Ministries and Accounting Departments | 46 | 9.79 |
State Corporations | 178 | 37.87 |
Local Authorities | 175 | 37.23 |
Tertiary Institutions | 71 | 15.11 |
Total | 470 | 100.00 |
Source: Organization of government; office of the president (2006-2011).
the upper limit of “excellent” achievement and 5 representing the lowest limit of ‘poor’ achievement. The composite scores were inverted, in order to give a rising visual effect to positive achievement and a declining visual effect to poor achievement. Further, the composite scores in each of the four categories of public agencies were averaged for each year to contain the data within manageable parameters.
The data from the agencies was organized, summarized and collated in a manner that linked with the research question and subsequently analyzed using both descriptive statistics and inferential statistics. The analysis was carried out using the Statistical Package for Social Sciences (SPSS), version 21. Descriptive statistical analysis was carried out to summarize the data and to bring out variability, using the mean, the standard deviation and then computing the coefficient of variation (CV). Correlation coefficients were computed to establish the relationship between the study variables. The extent to which the dependent variable could be predicted from the independent variable, is seen by deriving the regression equation. Coefficient of determination was computed to reflect the goodness of fit of the model. Linear regression analysis was further used to examine the model’s overall and individual statistical significance by using F-value and t-value, respectively. A model equation was derived for the hypothesis using variables that were significant.
As indicated in the table, the public sector in Kenya had an average customer satisfaction index of 0.27779, implying that nearly 73 percent of customers were dissatisfied with the public sector service delivery. The value of CV 44.52%, also reflects that there was very high variability in the customers responses. Among other variables pitted against customer satisfaction, political stability was found to be the weakest with a mean of −1.31533 on a scale of −2.5 (very weak) and 2.5 (very strong) and had the lowest variability (CV = −8.13%) across the public sector made up of ministries, state corporations, local authorities and tertiary institutions. The coefficient of variation was computed to show the variability in the data of the study parameters. Customer satisfaction shows the greatest variability, followed by performance measurement. The global competitiveness shows the least variability, reflecting almost unanimous responses and there has been
Variable | T-value | Sig. (2-tailed) | Mean | Std. Deviation | CV% |
---|---|---|---|---|---|
Customer Satisfaction | 8.699 | 0.000 | 0.27779 | 0.12368 | 44.52 |
Performance Measurement | 37.720 | 0.000 | 2.65439 | 0.27255 | 10.27 |
Global Competitiveness | 157.181 | 0.000 | 3.69800 | 0.09112 | 2.46 |
Political Stability | −47.656 | 0.000 | −1.31533 | 0.10690 | −8.13 |
fairly unanimous response that lack of political stability would adversely affect customers satisfaction.
Further, a correlation analysis of the study variables (
The regression analysis further provided an estimate equation to predict the magnitude of the dependent variable (customer satisfaction) and give values for the predictor variables.
In addition, t-test and p-values were used to determine individual significance of the results of the analysis. Assessment of the overall robustness and significance of the regression models was done using the F-test and p-values. Pearson correlation coefficient, R2, beta coefficients, and p values were computed.
The results of the analysis carried out to establish the joint effect of performance measurement, political stability and global competitiveness on customer satisfaction are shown in
A model equation of the joint effect relationship is described in Equation (4.4)
CustomerSatisfaction = − 1.01 + 0.401 PerformanceImprovement − 0.271 PoliticalStability − 0.036 GlobalCompetitiveness (4.4)
Performance Measurement | Customer Satisfaction | Global Competitiveness | Political Stability | ||
---|---|---|---|---|---|
Performance Measurement | Pearson Correlation | 1 | |||
Sig. (2-tailed) | |||||
Customer Satisfaction | Pearson Correlation | 0.858** | 1 | ||
Sig. (2-tailed) | 0.000 | ||||
Global Competitiveness | Pearson Correlation | 0.086 | 0.159 | 1 | |
Sig. (2-tailed) | 0.760 | 0.571 | |||
Political Stability | Pearson Correlation | 0.099 | −0.134 | −0.468 | 1 |
Sig. (2-tailed) | 0.724 | 0.633 | 0.079 |
**Correlation is significant at the 0.01 level (2-tailed).
Model Summary | ||||
---|---|---|---|---|
Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
1 | 0.886a | 0.785 | 0.726 | 0.06471 |
ANOVAa | ||||||
---|---|---|---|---|---|---|
Model | Sum of Squares | Df | Mean Square | F | Sig. | |
1 | Regression | 0.168 | 3 | 0.056 | 13.380 | 0.001b |
Residual | 0.046 | 11 | 0.004 | |||
Total | 0.214 | 14 |
Coefficientsa | ||||||
---|---|---|---|---|---|---|
Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
B | Std. Error | Beta | ||||
1 | (Constant) | −1.010 | 0.720 | −1.404 | 0.188 | |
Performance Measurement | 0.401 | 0.065 | 0.883 | 6.213 | 0.000 | |
Political Stability | −0.271 | 0.185 | −0.235 | −1.464 | 0.171 | |
Global Competitiveness | −0.036 | 0.217 | −0.026 | −0.165 | 0.872 |
a. Predictors: (Constant), global competitiveness, performance measurement, political stability
a. Dependent variable: Customer satisfaction; b. Predictors: (Constant), global competitiveness, performance measurement, political stability.
a. Dependent variable: Customer satisfaction.
The equation demonstrates that a unit change in performance improvement, intervened and mediated respectively by political stability and global competitiveness, will result in customer satisfaction changing by a factor of 0.401. In the absence of performance measurement, political stability and global competitiveness customer, satisfaction will change by negative 1.01. In the study of the joint effect of political stability and global competitiveness on the relationship between performance contracting and measurement and public service delivery, it was found that for a unit percentage change in political stability, there would be a 0.271% decrease in customer satisfaction, while a unit percentage change in global competitiveness would result in a decrease of 0.036% in customer satisfaction, although both were individually not statistically significant.
The study brought out interesting inferences on the joint effect of performance contracting and measurement, political stability and global competitiveness on public service delivery in Kenya. The finding that measurement was highly correlated with both improvement in performance and customer satisfaction did not come as a huge surprise and vindicates both the observation by Osborne et al. (1992 [
The effects of political stability have been documented in both Kenya and the Kingdom of Lesotho. The fortunes of Kenya, as evidenced by growth in real GDP plummeted steeply following the 2007-2008 post-election skirmishes, which fomented widespread political instability, pitting communities against each other. Business activity in Lesotho was severely albeit gradually affected by political instability resulting from polarization in a loose coalition government Manchafalo, 2014 [
The most curious findings were that outside the relationship between performance contracting and measurement and public service delivery, political stability and global competitiveness on their own, did not have significant effect on customer satisfaction. That even within the relationship, only political stability had a significant relationship. This is somewhat surprising, considering the impact political instability had on economic growth and performance in Kenya in 2008, and considering further as observed earlier in the study, that improvement in organizational performance informs improvement in service delivery. It would be expected too, that improvement in global competitiveness would moderate the performance of an economy. This was not the case as brought out in the study.
Overall, the outcomes of the study should be of practical interest to governments desirous to improve public sector performance, practitioners in the field of performance contracting and measurement and public service delivery, academicians and the public as beneficiaries of public services.
The preliminary findings pointed out that customer satisfaction, performance measurement; political stability and global competitiveness are related but not perfectly. Based on the research findings, it can be concluded that performance measurement has a significant effect on customer satisfaction. Secondly, it can be concluded that political stability has an intervening effect on the relationship between performance measurement and customer satisfaction. Further, global competitiveness has a moderating effect on the relationship between performance measurement and customer satisfaction, although on their own, political stability and global competitiveness have no significant effect on customer satisfaction.
The authors declare no conflicts of interest regarding the publication of this paper.
Ndubai, R.E., Mbeche, I.M. and Pokhariyal, G.P. (2018) A Study of the Joint Effect of Performance Measurement, Political Stability and Global Competitiveness on Customer Satisfaction. Open Access Library Journal, 5: e4917. https://doi.org/10.4236/oalib.1104917