MAKERERE UNIVERSITY

ANALYSIS OF CUSTOMER SATISFACTION WITH SERVICES PROVIDED BY UMEME LIMITED SINCE INCEPTION.

A case study of Ntinda-Kampala (Mutoola Zone-Bukoto II Parish)

BY

KIYINGI VICTOR, BSc. QE(Mak)

16/U/6232/EVE

A DISSERTATION SUBMITTED TO THE

COLLEGE OF BUSINESS AND MANAGEMENT SCIENCES

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR

THE DEGREE OF BACHELOR OF SCIENCE IN QUANTITATIVE ECONOMICS OF MAKERERE UNIVERSITY.

AUGUST, 2019.

ACKNOWLEDGEMENT The path of every journey is what matters the most rather than the end. I would therefore declare with at most confidence that the journey to accomplish this research project has been a beneficial one. I would surely like to take note of all those that have walked this lovely journey with me.

Firstly, I would like to thank the Almighty God for availing me with the knowledge, wisdom and strength to thrive consistently throughout this active time to get all the activities for the project on track and accomplished

I sincerely thank my close classmates; Andrew Lutalo and Abel for their unconditional assistance offered to me. Their hospitality and eagerness to teach me new things that made the entire period a rewarding one. Their counsel whenever need arose cannot be underestimated.

Very special thanks go to Mr. Serunjoji Ambrose my supervisor who opened up to me, mentored me, assigned me and guided me in the work related aspects as well as a few life aspects. I can assert strongly that I followed his advice.

Special mention goes out to the LC1 chairman of Mutoola zone- Ntinda who guided me and offered assistance where necessary.

Finally, I would like to express my sincerest and deepest gratitude to my dear family for supporting me financially, mentally and socially and for all the love expressed throughout my academic path. Without you, I would not have made it through easily.

My experience was a great one, that I learnt a lot from. With my experiences, I hope to navigate the future better both in life and my work related aspects.

May the Almighty Lord bless you abundantly.

Table of Contents DECLARATION ...... Error! Bookmark not defined.

APPROVAL ...... Error! Bookmark not defined.

ACKNOWLEDGEMENT ...... 4

LIST OF TABLES ...... 9

ABSTRACT ...... 11

CHAPTER ONE: INTRODUCTION ...... 12

1.1. Background of the study ...... 12

1.2. Problem statement ...... 14

1.3. Research objectives ...... 15

1.3.1 Main Objective ...... 15

1.3.2 Specific objectives ...... 15

1.4 Hypothesis: ...... 15

1.5 SIGNIFICANCE OF STUDY ...... 16

1.6 SCOPE OF STUDY ...... 16

CHAPTER TWO: LITERATURE REVIEW ...... 17

2.0 Introduction ...... 17

2.1 Customer Satisfaction ...... 17

2.2 Customer satisfaction in the energy sector ...... 17

2.3 Service quality and customer satisfaction ...... 18

2.4 Price and customer satisfaction ...... 18

2.5 Customer care service and customer satisfaction ...... 19

2.6 Communication and customer satisfaction ...... 19

2.7 Education and customer satisfaction ...... 19

CHAPTER THREE: METHODOLOGY ...... 21

3.0. Introduction ...... 21

3.1. Research design ...... 21

3.2. Data collection methods ...... 21

3.2. DATA PROCESSING AND ANALYSIS ...... 22

3.2.1 Univariate data analysis ...... 22

3.2.2 Bivariate analysis ...... 22

3.2.3 Multivariate analysis...... 23

CHAPTER FOUR: PRESENTATION AND DATA ANALYSIS ...... 25

4.0 Introduction ...... 25

4.1 Response rate...... 25

4.2 Summary statistics...... 25

4.2.1 Sample demographics ...... 25

4.2.2 Summary statistics on other variables...... 26

4.3 Relationship between the dependent and independent variables ...... 27

4.3.1 Satisfaction and education ...... 27

4.3.2 Satisfaction and Quality ...... 28

4.3.3 Price and satisfaction ...... 29

4.3.4 Communication and satisfaction ...... 30

4.3.5 Friendliness of staff and satisfaction ...... 30

4.4 Effect of the independent variables on the dependent variable...... 31

4.4.1 Effect of communication ...... 32

4.4.2 Effect of price ...... 32

CHAPTER FIVE: SUMMARY OF FINDINGS, RECOMMENDATIONS AND CONCLUSIONS...... 33

5.0 Introduction ...... 33

5.1 Summary of Findings ...... 33

5.1.1. Price ...... 33

5.1.2 Communication ...... 33

5.2 Conclusions ...... 34

5.3. Recommendations ...... 35

REFERENCES ...... 36

APPENDICES ...... 40

Appendix 1: Questionnaire to analyse customer satisfaction with services provided by UMEME ...... 40

LIST OF ACRONYMS CS Customer Satisfaction SSP School of Statistics and Planning MUK Makerere University

LIST OF TABLES

Table 1 shows Management departments of UMEME...... 13 Table 2: shows the age distribution, gender of respondents together with their education level...... 25 Table 3: presented summary statistics on the variables of communication, quality, price and friendliness of staff...... 26

Table 4: Shows the relationship between education and customer satisfaction level...... 27

Table 5: Shows the relationship between Quality and customer satisfaction...... 28

Table 6: Shows the relationship between price and satisfaction ...... 29

Table 7: Shows the relationship between communication and customer satisfaction...... 30

Table 8: Shows the relationship between friendliness of staff and customer satisfaction. .. 30 Table 9: Shows the relationship between the significant independent variables with customer satisfaction which is a dependent variable...... 31

LIST OF FIGURES

Figure 1: A bar chart of Satisfaction and Quality ...... 28

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ABSTRACT This study purposely intends to assess the effects of UMEME’s services on the customer satisfaction.

To further explain this the study provides an analysis on the different services the company provides right away from the distribution of electricity and its quality, repairing broken poles, prices charged and also response to customer complaints among others and how they affect customer satisfaction either positively or negatively. Further it digs deeper to find out how issues like load shedding influence the level of satisfaction among customers.

The researcher will obtain data directly using simple random sampling from the target population using questionnaires. Secondary data will also be used to add onto the primary data source. The researcher uses cross sectional data to assess the effects of the services UMEME gives to its customers. Use of Cochran’s formula (1963) for an infinite population to determine sample size.

The findings in this research indicate that there is increased demand for electricity mainly due to the rampant population growth and rural electrification. However, majority of UMEME customers are dissatisfied with the company’s services and if provided an opportunity for another service provider aside from UMEME as a monopoly firm, they would shift with no second thoughts.

UMEME as a sole distributor of electricity in Uganda should try and meet the expectations of customers with the major concern among customers being the high charges per unit with the introduction of Yakka metres and listening to their grievances.

CHAPTER ONE: INTRODUCTION This section covers the background of the study, statement of the problem, purpose of the study, objectives of the study, research questions and scope of the study and its significance.

This study sought to analyse customer satisfaction in relation to the services UMEME offers. For example, if customers are not contented with the services, how does this affect their loyalty.

1.1.Background of the study It is hard to believe that 12 years back access to electricity was a taboo as it was only availed to the selected urban dwellers. Under Uganda Electricity Board power outages were a norm rather than an exception. The National Power Company was making so many losses until UMEME came into action to replace Uganda Electricity Distribution Company on 1st March, 2005. It was awarded a 20- year concession and has so far used up 13 years. It was introduced as a sole distributor of electricity in Uganda. At the beginning of the concession, only 80% billings were being collected. Uganda’s electricity system was not financially viable due to distribution inefficiency, characterised by high energy losses and uncollected bills. In the first year of the concession $6m was invested which has grown up to $565m by the end of December 2017. This investment has been put to great use as the company’s revenues and profits have continued to grow. However, there’s still a lot to do throughout the sector, bringing more power online and expanding the transmission and distribution grid. When UMEME, a private company came in, so many people in Uganda thought it was going to solve their complaints with the former company. however, the performance of UMEME Limited shows a successful run in its first decade in operation in Uganda. The company has incurred so many expenses in investments in the distribution network and so charge high tariffs to end users. The electricity Regulatory Authority wants UMEME to cut losses, expand the network and improve customer care. The impact of losses is minimal yet many complaints of poor service delivery, billing and delayed connection still remain (New Vision, 2004). According to (Wikipedia) UMEME Limited is the largest energy distributor in Uganda, distributing 97 percent of all electricity used in the country. The shares of the stock company are listed on the Uganda Securities Exchange and cross listed on the Nairobi Stock Exchange (NSE). UMEME made its first trade at NSE, electronic share transfer went live (David, Mugwe, 2013).

In October 2012, UMEME became a listed company on the Uganda Securities Exchange. A total of 622,378,000 shares, representing approximately 38 percent of its issued share capital at the time, became listed on the Ugandan bourse in an initial public offering (Ilungole ,Stephen, 2012)

UMEME is structured into 12 management departments, each headed by a senior manager. The senior managers form the Executive Committee; whose members were the following as of 1 June 2018 (UMEME , 2018).

Table 1 shows Management departments of UMEME Department Name of Manager Title of Officer Office of the Managing Selestino Babungi Managing Director Director Operations Management Florence Nsubuga Chief Operations Officer Technical Office Simbiso Chimbina Chief Technical Officer Corporate Development Blessing Nshaho Chief Corporate and Regulatory Officer General Manager Almero Grey Acting General Manager Capital and Contracts Division Finance Marie Nassiwa Martin Chief Financial Officer Information Systems Roger Bentley Chief Information Officer Internal Audit Ruth Doreen Head of Internal Audit Communications Sandor Lyle Head of Communication and Marketing Customer Service Agnes Nalwanga Head of Customer Service Supply chain Patrice Namisano Head of supply Chain

According to (Kotler Armstrong, 1999) customer satisfaction is defined as the extent to which products perceived performance matches customer’s expectation. Customer satisfaction can be measured using a quantitative survey. A customer that is satisfied is bound to make repeated purchases to express loyalty and in most cases inform others about their good experience with the product.

In December 2010, UMEME announced plans to invest US $32million during 2011 in new substations, improvements in grid connectivity and the introduction of pre- payment systems (Ojambo Fred, 2010). In March 2016, UMEME signed a contract with Uganda Electricity Transmission Company Limited to distribute the power generated from the Isimba Hydroelectric Power Station and the Karuma Hydroelectric Power Station (Muhumuza Mark Keith, 2016).

In June 2019 it was announced that UMEME planned to borrow US$70 million from the International France Corporation to add to the US$ 255 million raised internally in order to invest in network upgrades and expansion while reducing network losses along with increased collection targets during the 2019-2024 time frame (Christine Kasemiire, 2019).

From the (Global Energy Architectural Report , 2017) which ranks 127 countries basing on their abilities to provide sustainable energy , Uganda doesn’t appear yet its neighbours Kenya which is 83rd and Tanzania the 119th make it among the top countries. This shows Uganda’s performance is very poor due to lack of diversity in sources of production of power which leads to huge energy losses. With UMEME’s slow response to emergencies, customers are often faced with lengthy periods of power black outs. Customer satisfaction has therefore not been achieved by the company and therefore it was necessary to carry out this research.

Lastly, I selected this area of residence due to the rampant power cuts and complaints of UMEME taking long to respond. So I intended to establish a customer focused approach to measure satisfaction among different residents basing on the services the company provides.

1.2.Problem statement Poor service delivery by any firm or company has adverse effects on the level of satisfaction of their customers. First of all, despite the presence of UMEME in Uganda, not every individual has access to electricity. Studies show that only 20% Ugandans have access to power. There are high tariffs charged by the distribution company to its customers since it is the sole distributor in Uganda which has contributed greatly to electricity theft a s a way of cutting costs.

80 percent of companies say they deliver superior customer services, however only 8 percent of customers agree with this assessment.

The environment under which UMEME is operating is rapidly changing and its customer base has rapidly grown which forces the company to react and implement latest techniques in communication, reliability, cost and innovation like the new metre boxes.

The Company’s poor service delivery in terms of load shedding, estimation of bills, transformer breakdowns with low response, low voltage in some areas, low power supply due to unstable and broken electric poles, some of which rot has brought rampant complaints from consumers and low satisfaction. Amidst all this UMEME has been slow to respond to these complaints hence customers resort to other options like solar energy, thermal energy in addition to power theft which has caused dissatisfaction among them. In rural areas people have resorted to solar because it is cheaper compared to hydro power since there are no monthly charges. Therefore, this study intends to establish how this unstable and inconsistent service delivery by UMEME has affected the satisfaction of majority customers.

1.3. Research objectives 1.3.1 Main Objective The main aim of the study was to analyse customer satisfaction on service provision by UMEME.

1.3.2 Specific objectives a) To establish the effect of service quality on customer satisfaction. b) To investigate the effect of price on customer satisfaction. c) To investigate the effect of communication on customer satisfaction. d) To determine the effect of education level on customer satisfaction. e) To establish the effect of customer care services on customer satisfaction.

1.4 Hypothesis: a) Service quality has no significant effect on customer satisfaction. b) Price has no significant effect on customer satisfaction. c) Communication has no significant effect on customer satisfaction. d) Education level has no significant effect on customer satisfaction. e) Customer care services have no significant effect on customer satisfaction.

1.5 SIGNIFICANCE OF STUDY The findings of the study will be beneficial in the following ways.

I. The management of UMEME Ltd will be able to use the information to know the complaints customers bring up and what is expected of them so that they can capture ways to generate more revenue. II. To encourage customer satisfaction in utility management for example business focused enterprises to direct their efforts to customer satisfaction. III. Customers will be able to know other sources of energy that they can use apart from hydroelectricity like solar energy and thermal energy. IV. The management of UMEME Limited will be able to identify loopholes in their service quality so that they can work on them and improve electricity distribution countrywide.

1.6 SCOPE OF STUDY The study focused on the services provided by UMEME Limited and customer satisfaction generally providing an analysis between the two variables and how one affects the other. The services here involved include the cost of electricity, the response rate of UMEME staff to pole or transformer breakdown, the communication techniques or channels, the products introduced by the company. The study aimed at choosing customers. A sample was obtained after enumerating the total number of customers in a selected area of Ntinda (Mutoola Zone- Bukoto II Parish). Why I chose Ntinda is because it is my area of residence and it has been affected by various power cuts (load shedding), low power supply and low voltage on some occasions. It is also a busy and fast growing town which consumes a lot of power. The study therefore constituted approximately 80 respondents in total.

CHAPTER TWO: LITERATURE REVIEW 2.0 Introduction This chapter covered the literature on the study variables identified in chapter one. The concept of customer satisfaction is discussed in depth and literature illuminating the effect of the independent variables on the dependent variable is also presented.

2.1 Customer Satisfaction Various researchers have defined Customer Satisfaction (CS) in various ways. Some are inconsistent with one another while other definitions have some overlapping components but still partially inconsistent. Thus, there is lack of consensus on the definition of satisfaction as a concept. Oliver (1997) defined CS as the customer’s fulfillment response. It is a judgement that a product or service feature, provided (or is providing) a pleasurable level of consumption- related fulfillment, including levels of under-or over-fulfillment. Ostrom & Iacobucci (1995) defined customer satisfaction as a way to evaluate the gap between the expectations of the customer from a particular product or service and what the customer receives after use of the said product. Churchill & Surprenant (1982) stated that satsifaction is a result of purchase and use of a product or service, which derives from the customer’s comparison between the renumeration and the cost of purchase, taking into consideration the expected result. Also, Kotler (1991) approached the issue of CS from a marketing point of view and explained it as feelings of pleasure or discontent, which can be derived from the comparison between performance or result of the product or a service, and the expectations the person developed before paying it. In addition, Fornell (2008) noted that Customer Satisfaction is a key performance indicator of the activity of a firm or a corporation. Thus, CS is a scale for measuring how well a comapany’s product or service meets or exceeds the customer’s expectations. The theory of Customer Satsifaction has thus been presented in the international literature as a relaible tool for evaluation of a company,s results. It is also the leading indicator of customer retention and loyalty (Ling & Huat, 2016).

2.2 Customer satisfaction in the energy sector Throughout the years several studies have been carried out concerning customer satisfaction with energy providers. Satisfaction in the energy sector covers the quality of a number of services from provision of a new connection, payment, to handling of customer requests and complaints. Medjoudj, Aissani, & Haim (2013) stated the main objective of ana energy organisation is to acquire quality products and services that satsify it’s customers with measurable improvements yo mission capability and operational support in at a fair and

reasonable price. Mutua, Ngui, & Osiolo (2012) conducted a study about customer satisfaction in Kenya using the European Consumer Satisfction Index (ECSI). They found out that the electricity sector has the least satsified customers. (Luiz, Zhang, & Zhou (2007) developed an evaluation index system of electric power customers’satisfaction based on the service blueprint theory. The service blueprint model was divided into 4 parts, which are customer behaviour, front office staff behaviour, back office staff behaviour, and the support process. Also, Ibanez, Hartmann, & Calvo ( 2006) proposed a framework where retail customer satisfaction with energy providers is correlated with the dimensions of technical quality of the core services, technical quality of the peripheral services and service process quality. The study confirmed direct impact of the examined dimensions on customer satisfcattion.

2.3 Service quality and customer satisfaction Under the view of perceived quality, CS may be seen as the difference between the actual and the expected quality of a product or a service. Chalikias & Drosos (2016) suggested that industrial customer satisfaction is a much more complex concept which was closely connected with the quality of the provided products and services provided to customers. Walsh & Dinnie (2006) noted that customers who are satsified with the service quality they receive tend to trust their energy provider and thus have the potential to become loyal customers and attract new customers to the energy provider. Chodzaza & Gombachika (2013) examined functional quality offered by a public electricity provider to it’s industrial customers within the southern region of Malawi. Results from the study showed that service quality is poor, irrespective of the demographic characteristics of the industrial customers. Thus, customers were dissatsified with the availabilty of power and customer care services. Hartmann & Ibanez (2007) propounded a conceptual framework for the impact of customer satsifaction and switching costs on customer loyalty in energy market. Their results showed that inorder to increase customer satsifaction with energy providers and thus, indirectly customer loyalty, service quality should be increased.

2.4 Price and customer satisfaction Garcia-Acebron & Vazquez-Caseillas (2010) suggested that price is important for customers of energy providers. However, their study showed that industrial customers’satsifaction has an important effect on price tolerance even when switching barriers exist. In 2019, Drosos & Skordoulis stated that customers attached an 18.10% level of importance on the pricing. In parrallel with this, Smith, Nayak, Karig (2014) noted that overall satisfaction is highly correlated with price. Demtsura (2017) while examining constomer stasifaction of quality and

prices of services in the education sector found that prices for education services were key indicators of customer satsifaction. He suggested for constant monitoring of clients’ satsifaction to adjust pricing so as to attract new customers.

2.5 Customer care service and customer satisfaction According to a study by Helpscout (2016), 80% of comapanies claim the deliver ‘superior’ customer customer service. However, only 8% of customers agree with this assessment. The study aslo established that when customers are not satisified with customer service, 13% of them wull tell an additional 15 or more people that they are unhappy. Conversely, if they are happy, 72% of them will share their positive experience with 6 or more people. Drosos & Skordoulis (2019) conducted a study about natural gas in Greece and found out that customer care services had the second highest level of importance with a record of 85.31%. Rekettye & Tersztyanszky (2008) while assessing CS in Hungarian electricity distribution companies emphasized improvement in customer care services since it was one of the key indicators of satisfaction.

2.6 Communication and customer satisfaction A study conducted by Drosos & Skordoulis (2019) revealed that communication had the highest level of importance to customers with a record of 86.64%. Smith, Nayak, & Karig, (2014) stated that customers claim to appreciate information and initiatives that help them understand and reduce their energy usage. Their study revealed that effective communication with related with higher customer ratings on energy efficiency programmes. In line with this, Hassan & Yusuf (2015) while using the American Customer Satsifaction Index (ACSI) ranked communication as the 4th highest service dimension clients were more satsified with. Rekettye & Tersztyanszky (2008) also aggigated for improvement in communication as a way of improving customer satsifaction.

2.7 Education and customer satisfaction Aoudni & Rebai (2014) argued that customers who have an access to an education level that allows them to judge any product or service they pay for are more satsified than their counterparts. Consquently, a company that meets or even exceeds the customer’s expectations has a significant competitive advantage. This was further retrierated by Mirzagoli & Memarian (2015) who ranked eduaction as the 5th socio demographic facor to have the greatest impact on customer satsifaction. However, Haijan (1986) while studying patient satsifaction with health care services in Yahyanejad and Beheshti hospital in Babol found a significant inverse

relationship between education and satsifaction. This was further collaborated by (Amerian, Ebrahim, & Nia, 1988; Amin & Poor, 1992 ) who noted there was no significant relationship between the two variables.

CHAPTER THREE: METHODOLOGY 3.0. Introduction This chapter describes the methods that the researcher used to carry out the study, these include research design, data collection methods, data processing and analysis.

3.1.Research design The researcher used cross sectional data analysis to establish the extent to which customer satisfaction is affected by the services provided by UMEME Ltd. A descriptive cross sectional research design was employed to systematically provide information about the various services UMEME provides that are affecting customer satisfaction. The research design will make use of the survey method to collect data from respondents.

3.2.Data collection methods The researcher obtained data directly using simple random sampling from the target population using questionnaires and open discussions with personnel. Secondary data was also used to add onto the primary data source. Data from magazines, company supplements and brochures as well as external sources like the internet. Out of the 80 respondents, 70 were able to respond and the rest didn’t hence the response rate was 87%. I used Cochran’s formula (1963) for an infinite population to determine sample size. It considered the level of confidence interval measure (Z) where my critical value of z is 1.96 for 95% confidence interval. (P) is the degree of variability and (e) is the margin of error which will be 0.01. let those that had electricity access be 40% which is the value of p. The formula is given as;

푛 = 푧2푝(1 − 푝) 푒2 the sample size was obtained using this formula, hence;

n= (1.962) ∗ (0.4 ∗ 0.6) ≈ 80 respondents 0.012

3.2.DATA PROCESSING AND ANALYSIS On collection of data, this study used raw data which involved checking, coding, classifying, sorting, filling, updating data, making comparisons among others. The researcher established various analytical tools to analyse the data. Some of these were Stata package, MS Excel.

The researcher applied univariate analysis where frequency and percentage tables, graphs, descriptive statistics such as mean were used. He also carried out bivariate analysis to establish the empirical relationship between two variables e.g. chi-square test. Multi variate analysis where he employed logistic regression tool to determine significant factors affecting customer satisfaction.

3.2.1 Univariate data analysis Upon retrieval of the questionnaires, the different variables were subjected to univariate analysis. This was carried out by use of frequency tables, graphs, descriptive statistics such as mean, mode, skewness, range, standard deviation among others. For example; for categorical variables such as age, gender, price, quality, among others; frequency tables and graphs were provided to describe the structure of the respondents and their different composition.

3.2.2 Bivariate analysis Bivariate analysis sought to determine the empirical relationship between two variables. Specifically, the chi-square statistic test of independence, a non-parametric analytical tool was used to examine if the categorical variables under examination are related or not. The bivariate tool was adopted to test all the research hypotheses by comparing the different categorical variables with the dependent variable of consumer satisfaction. The test was conducted at a 0.05 level of significance with the aid of STATA software package 14.2.

If the p-value of the statistic obtained was less than 0.05, the null hypothesis was rejected. This implied that there is a significant relationship between the two categorical variables.

2 2 푟 푐 (표푖푗−퐸푖푗) 휒 = ∑푖=1 ∑푗=1 퐸푖푗

Where; -

휒2- Chi-square test

표푖푗 - Observed frequency

퐸푖푗- Expected frequency r - number of rows c - number of columns

3.2.3 Multivariate analysis The study employed the logistic regression tool to determine the significant factors of service provision that affect customer satisfaction. The choice for this tool stemmed from a fact that dependent variable was binary that is, a customer could either say yes or no. The dependent variable was regressed against independent variables that have significant association or effect as obtained from the bivariate analysis. The variables with their respective codes are represented below;

Variables Code

Dependent variable Yi = 1= Yes

Customer satisfaction 0= No Independent variables Communication X1 Price X2 Quality X3 Customer care X4 Education X5

Model Generation

푝푖 log ( ) = 훽0 + 훽1푋1 + 훽2푋2 + 훽3푋3 + 훽4푋4 + 훽5푋5 1−푝푖

Where; -

푝푖 log ( ) is the log-odds 1−푝푖

푝푖 is the probability that Yi =1

훽0 is a constant

훽푖 is the coefficient of 푋i with i = {1,2,3,4,5}.

The analysis for the regression model was conducted at 0.05 level of significance with the aid of STATA software package 14.2. From the analysis, the following were reported; -

i. The probability of the Likelihood Ratio (LR) chi-square statistic. If the probability value was less than 0.05, it would imply the model is a good fit. ii. The p-value for the statistic of each variable were also reported and the variable was rendered significant if its p-value was less than 0.05. iii. The odds ratios for each variable were reported and interpreted. iv. Also, the 95% confidence interval was reported to show the range in which the true value of the odds ratio was found. If the confidence interval contained a one, then the variable was not a significant predictor.

CHAPTER FOUR: PRESENTATION AND DATA ANALYSIS

4.0 Introduction This chapter presented the results originating from the analysis of the data collected. The data was subjected to univariate and then bivariate analysis and later, multivariate analysis was used to determine the effects of the independent variables on the dependent variables. The response rate was also discussed in this chapter.

4.1 Response rate Out of the 80 questionnaires distributed, 70 were retrieved and used in this study. This pointed to an 87% response rate. The high response rate was achieved due to the effort of the researcher who followed up on the respondents.

4.2 Summary statistics This section articulated the sample demographics and descriptive statistics of the variables related to this study using tables and figures.

4.2.1 Sample demographics Table 2: shows the age distribution, gender of respondents together with their education level. Variable Frequency Percentage (%) Age 18 to 24 38 54.29 25 to 34 11 15.71 35 to 44 11 15.71 45 and above 10 14.29 Total 70 100.00 Gender Female 38 54.29 Male 32 45.71 Total 70 100.00 Education Primary 1 1.43 Secondary 11 15.71 Tertiary 58 82.86 Total 70 100.00

Majority of the respondents (54.29%) were aged between 18 to 24 years, while 15.71% were aged between 25 to 34 years. A similar percentage was recorded for respondents aged between 35 to 44 years. Lastly, 14.29% of the respondents were aged from 45 years and above. In respect to the gender variable, majority of the respondents were females with a record of 54.29% with the rest being males. Using the education level of the respondents, majority (82.86%) had attained tertiary education followed by those who had attained education up to the secondary level with a record of 15.71%.

4.2.2 Summary statistics on other variables. Table 3: presented summary statistics on the variables of communication, quality, price and friendliness of staff.

Variable Frequency Percentage(%) Communication No 31 44.29 Yes 39 55.71 Total 70 100.00

Friendliness of staff No 14 24.14 Yes 44 75.86 Total 58 100.00 Quality of service Very Poor 3 4.29 Poor 27 38.57 Good 32 45.71 Very good 8 11.43 Total 70 100.00 Price 30,000 but less than 60,000 24 34.29 60,000 but less than 90,000 11 15.71 90,000 and above 4 5.71 Less than 30,000 31 44.29 Total 70 100.00

Majority of the respondents (55.71%) claimed that UMEME effectively communicates with them in case of power outages or other emergencies while the rest pointed to inefficiency in communication by the company. 75.86% of the respondents who had ever interacted with the company’s staff noted that they were friendly while the rest claimed UMEME staff were not friendly. In respect to the quality of services provided by the company, 45.71% described the quality of services as good, followed by those who described it as poor with a record of 38.57%. 11.43% and 4.29% of the respondents described the quality of services as very good and very poor respectively.

4.3 Relationship between the dependent and independent variables This section presented the results originating from the bivariate analysis on the dependent variable and each of the dependent variable using the chi-square statistic test of independence.

4.3.1 Satisfaction and education Table 4: Shows the relationship between education and customer satisfaction level. Crosstab of education with satisfaction χ2= 0.8579, p= 0.651 Satisfaction No Yes Total Education Primary Row % 0.00 100.00 100.00 Secondary Row % 45.45 54.55 100.00 Tertiary Row % 37.93 62.07 100.00

From the table above, none of the respondents who attained education up to the primary level were dissatisfied with services provided by UMEME. Majority of the respondents (54.55%) who had attained education up to the secondary level were satisfied with services provided by the company and similarly, majority of those who had attained tertiary education were satisfied with the services of the company with a record of 62.07%.

A chi square value of 0.8579 with a p value of 0.651 which is greater than 0.05 was obtained. This implied that there is not enough statistical evidence to show that the two variables are related.

4.3.2 Satisfaction and Quality

Bar Chart 26

25

20 18

15

Frequency 9 10 8 6

5 3

0 No Yes Very Poor Poor Good Very good

Figure 1: A bar chart of Satisfaction and Quality

Table 5: Shows the relationship between Quality and customer satisfaction. Crosstab Quality with Satisfaction χ2= 24.1021, p= 0.000 Satisfaction No Yes Total Satisfaction Very poor Row % 100.00 0.00 100.00 Poor Row % 66.67 33.33 100.00 Good Row % 18.75 81.25 100.00 Very good Row % 0.00 100.00 100.00

From figure 1 and table 3 above, all the respondents who described the quality of UMEME services as very poor were dissatisfied with the company’s services. Similarly, majority of the respondents (66.67%) who described the quality of the company’s services as poor were dissatisfied with the company’s services, while 81.2% of the respondents whole described the

quality of the UMEME services as good were satisfied with the company’s services. Also, all the respondents who described the company’s services as very good were satisfied with the company’s services.

A chi square value of 24.1021 with a p value of 0.000 which is less than 0.05 was obtained. This implied that the two variables are significantly related.

4.3.3 Price and satisfaction

Table 6: Shows the relationship between price and satisfaction Crosstab of price with Satisfaction χ2= 9.3460, p= 0.0250 Satisfaction No Yes Total Price Less than 30,000 51.61 48.39 100.00 Row % 30,000 but less than 60,000 Row % 29.17 70.83 100.00 60,000 but less than 90,000 Row % 18.18 81.82 100.00 90,000 and above Row % 50.00 50.00 100.00

51.61% of the respondents who pay less than 30,000 Uganda shillings were dissatisfied with services provided by UMEME while majority of the respondents (70.83%) who pay 30,000 but less than 60,000 Uganda shillings were satisfied with services provided the company. Similarly, 81.82 who those who pay 60,000 but less than 90,000 Uganda shillings were satisfied with the company’s services. Also, 50.00 of those who pay 90,000 Uganda shillings and above were dissatisfied with UMEME service provision.

A chi square value of 9.3460 with a p value of 0.0250 which is less than 0.05 was obtained. This implied that the two variables are significantly related.

4.3.4 Communication and satisfaction

Table 7: Shows the relationship between communication and customer satisfaction. Crosstab of communication and satisfaction χ2= 6.2626 , p= 0.0437 Satisfaction No Yes Total Communication Yes Row % 55.56 44.44 100.00 No Row % 37.21 62.79 100.00

Majority of the respondents (55.56%) who described UMEME’s communication as effective were not satisfied with the services provided by the company while 62.79% of those who described the company’s communication as effective were satisfied with the company’s service provision.

A chi square value of 6.2626 with a p value of 0.0437 which is less than 0.05 was obtained. This implied that the two variables are significantly related.

4.3.5 Friendliness of staff and satisfaction Table 8: Shows the relationship between friendliness of staff and customer satisfaction. Crosstab of friendliness of staff and satisfaction χ2= 0.0124 , p= 0.911 Satisfaction No Yes Total Friendliness of No staff Row % 25.00 75.00 100.00 Yes Row % 23.68 76.32 100.00

Majority of the respondents (76.32%) who had ever interacted with UMEME staff and claimed they were friendly were satisfied with service provision of the company while 75% of those who described UMEME staff as unfriendly were generally dissatisfied with the service provision of the company.

A chi square value of 0.0124 with a p value of 0.911 which is greater than 0.05 was obtained. This implied that there is not enough statistical evidence to show that the two variables are related.

4.4 Effect of the independent variables on the dependent variable. This section articulated the effects of the independent variables on the dependent variable using the logistic regression analysis.

Table 9: Shows the relationship between the significant independent variables with customer satisfaction which is a dependent variable. Logistic Regression. N=51, LR chi2(9) = 31.35, Prob > chi2 = 0.0003, Pseudo R2= 0.4589 Satisfaction Odds ratio Std. Error Z p>|z| [95%Conf.Interval]

_ICommunica_2 1.738568 1.161 2.03 0.042 1.4694753 6.438291 315 _IPrice_2 3.604082 2.786968 -2.22 0.026 1.4596209 28.26114 _IPrice_3 1.178654 1.691318 4.14 0.000 1.0707863 19.62563 _IPrice_4 1.6617653 .4889588 -2.14 0.032 1.1555165 2.815994 _IQuality_2 2.278683 3.026713 0.62 0.535 .1686769 30.78308 _IQuality_3 .5559403 1.142203 -0.29 0.775 .0099129 31.17868 _IQuality_4 .2355541 .2509167 -1.36 0.175 .0291994 1.900233 _cons 4.326605 24955.61 -0.01 0.996 .4596209 28.26114

A Likelihood Ratio chi square value of 31.35 was obtained with a p value of 0.0003 which is less than 0.05. This shows that the model is a good fit.

4.4.1 Effect of communication The odds of being satisfied with UMEME service provision by a customer who describes the company’s communication as effective were 1.738568 times that of a customer who describes the company’s communication as ineffective. This implied that customers who describe the company’s communication as effective are more likely to be satisfied than their counterparts.

A p value of 0.042 which is less than 0.05 was obtained and this implied that the variable is statistically significant. Also, the true value of the odds ratio was found to between 1.4694753 and 6.438291.

4.4.2 Effect of price The odds of being satisfied with UMEME service provision by a customer who pays less than 30,000 Uganda shillings were 3.604082 times that of a customer who pays 90,000 and above. This implied that customers who pay less than 30,000 Uganda shillings were more likely to be satisfied than those who pay 90,000 and above. A p value of 0.026 which is less than 0.05 was obtained and this implied that the variable is statistically significant. Also, the true value of the odds ratio was found to between 1.4596209 and 28.26114.

Also, the odds of being satisfied with UMEME service provision by a customer who pays 30,000 but less than 60,000 Uganda shillings were 1.178654 times that of a customer who pays 90,000 and above. This showed that customers who pay 30,000 but less than 60,000 Uganda shillings were more likely to be satisfied than those who pay 90,000 and above. A p value of 0.000 which is less than 0.05 was obtained and this further implied that the variable is statistically significant. Also, the true value of the odds ratio was found to between 1.0707863 and 19.62563.

In addition, the odds of being satisfied with UMEME service provision by a customer who pays 60,000 but less than 90,000 Uganda shillings were 1.6617653 times that of a customer who pays 90,000 and above. This showed that customers who pay 60,000 but less than 90,000 Uganda shillings were more likely to be satisfied than those who pay 90,000 and above. A p value of 0.032 which is less than 0.05 was obtained and this also implied that the variable is statistically significant. Also, the true value of the odds ratio was found to between 1.1555165 and 2.815994.

CHAPTER FIVE: SUMMARY OF FINDINGS, RECOMMENDATIONS AND CONCLUSIONS.

5.0 Introduction This chapter provides a review of the findings, recommendations and conclusions for the assessment.

5.1 Summary of Findings The purpose of this descriptive cross sectional study was to investigate the effect of various factors that affect service provision on the satisfaction of customers. This part of the chapter presented a discussion on the major findings as related to the literature reviewed on the variables related to service provision that affect customer satisfaction.

Two factors emerged out as the significant predictors of customer satisfaction and these were; the price UMEME charges onto its customers and lastly the communication channels it offers.

5.1.1. Price Price was considered a very important aspect in energy consumption of individuals on a weekly basis. The findings indicate that customers were more satisfied with low prices charged by UMEME. With low prices consumers are able to benefit from the services offered without it causing a significant impact on other household expenses. These results show that the price of a service or product increase the customer value in that they are able to tolerate price changes due to existing barriers within the energy sector. Customers are also more convinced when the increasing price is competing with quality.

There is a similarity in the research of Garcia-Acebron & Vazquez-Caseillas (2010) which suggested that price is important for customers of energy providers and his study showed that industrial customers’satsifaction has an important effect on price tolerance even when switching barriers exist.

5.1.2 Communication A dissatisfied customer can be quick to shoot arrows via social media and online reviews which are as a result of poor communications because a times it may be warranted or not. Such events occur because customer’s expectations were not met. When a customer does not

fully understand a company’s process, methods and idiosyncrasies it can lead to conflicts. This lack of communication can lead to poor reviews.

This is in line with the findings of Smith, Nayak, & Karig, (2014) who stated that customers claim to appreciate information and initiatives that help them understand and reduce their energy usage. Their study revealed that effective communication related with higher customer ratings on energy efficiency programmes.

5.2 Conclusions The main variables that affect revenues in UMEME limited are customer advocacy and customer satisfaction where as the main factors that affect satisfaction from the services provided by UMEME are price, quality and communication. UMEME limited is the sole distributor of electricity in Uganda and therefore shifting to another service provider is difficult as the other options available are more expensive as compared to UMEME so customers end up settling for it. This has encouraged high tariffs being charged per unit of electricity since there are no competitors to provide better services than UMEME. Price plays a major role in the consumption of energy by individuals whereby if the prices are high people are forced to use energy sparingly.

Due to the increase in tariffs there were customer grievances and in most cases they had resorted to stealing electricity as a way of reducing on the units being used. UMEME earlier introduced tamper proof meter boxes in households, this in return has led to dissatisfaction of customers because they think it is a way of cheating and overcharging them for the company to attain abnormal profits.

Customers are not contented with UMEME due to the various loopholes in the company such as load shedding especially in the rainy season, high tariffs, poor response to technical issues like pole breakdowns and the poor communication by the company. This has biased the customer relationship with the company. However, in comparison with the former company Uganda Electricity Distribution Company Limited, there has been great improvement in electricity distribution.

However, there is still some work to be done to match up the customer expectations. Some domestic customers are also not in agreement with the box meters and so decided to remain with the commercial system where they have to pay bills at the end of a certain period say

monthly. This is because they do not want to experience power shortages at a time when they need constant power supply.

The relationship between customer satisfaction and service provision is a positive one. When customers are contented with UMEME they are loyal and therefore use the electricity for longer periods of time and recommend others to use it. This has a great impact on the revenue obtained by the company. But if customers aren’t contented, they will be reluctant to continue with the services of the company and in most cases are looking for better alternatives in terms of costs. So for the company to monitor their customers and gauge the amount of electricity consumed in terms of units, tamper proof meters were introduced in majority of households. They are able to keep their customers loyal because they pay according to their potential to consume in a given period of time using these meters.

5.3. Recommendations For the company to ensure customer satisfaction, it should cooperate with its customers as a way of reducing theft of electricity in order to improve on its revenues.

UMEME should improve on their e-services in order to respond effectively towards customer complaints and field breakdowns. They should also notify their customers in time on future improvements that require load shedding and any other inconveniences. This strengthens customer relations with the company.

The company should reduce on the tariffs per unit of electricity that is levied onto consumers indirectly. With the introduction of tamper proof meters, consumers are able to monitor their daily consumption of energy but still the charge per unit stands out as it fluctuates occasionally.

UMEME should stabilise electricity notifying the various companies that work hand in hand with it say, Uganda Electricity Generation Company so that they can build more power dams in the country. This will increase the electricity supplied and reduce on breakdowns due to power shortage.

UMEME should remove the weak old electricity wires and connect households onto the new ones which have stable supply of electricity. The old wires are prone to electricity shocks and poor distribution throughout different regions.

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APPENDICES Appendix 1: Questionnaire to analyse customer satisfaction with services provided by UMEME

Good day! My name is Kiyingi Victor, a student pursing a Bachelors Degree of Science in Quantitative Economics at Makerere University. Through this brief survey, your responses will be helpful in analysing customer satisfaction with services provided by UMEME. This evaluation does take place anonymously and all the information collected from this survey will be strictly confidential. The information will specifically be used only for the purpose of my dissertation. It will take you approximately ten (10) minutes to complete this questionnaire and participation is completely voluntary. If you wish to receive further information about the study, please do not hesitate to contact me on +256786416629.

*Required

Section A: Demographic factors

These questions are for classification purposes only.

1. What is your age in years? *

18 to 24 c 25 to 34 35 to 44 45 and above

2. Please specify your gender *

Female Male

3. What is your highest educational level attained? *

Primary Secondary Tertiary(undergraduate/masters/doctorate ) Prefer not to say

4. Are you a permanent resident here? That is, is it where you live most of the time- or not?

Yes No

5. Do u have electricity in your home? * Yes No

6. If yes, what type of electricity is it? * Hydro Electric Power Solar Other:

7. How long have u been receiving electricity? * Under 6 months 6 months but less than a year A year but less than 3 years 3 years and above

Section B: Ratings and Services provided by UMEME

8. Have u ever experienced power outages? That is, temporary suspension of electricity supply due to broken transformers or poles or malfunctions in the system * No Yes b) If yes, what was the duration of the recent power outage experienced. That is, how long did the outage last? *

Under an hour An hour but less than 3 hours 3 hours but less than 6 hours 6 hours and more

9. Have u ever contacted UMEME in case of any power outage? * Yes

No

10. Estimate the restoration time. That is, how long did it take for UMEME to resolve the issue? * Under an hour c An hour but less than 3 hours c 3 hours but less than 6 hours c 6 hours and more c

11. Does UMEME effectively communicate to you incase it is experiencing malfunctions in its system or about power outbreaks so as to maintain and repair transformers or fallen poles?

Yes c No c

12. Have you ever interacted with any UMEME staff member? *

Yes c No c b) If yes, were they friendly?

c Yes No c

c 13. How much do you pay for your electricity on a weekly basis? *

Less than 30,000 c 30,000 but less than 60,000 c 60,000 but less than 90,000 c c 90,000 and above c

c 14. On a scale of 1 to 4, rate the quality of services provided by UMEME * c

Very poor

1 c 2 c 3 c c c c 4 c Verycc good c c cc

cc c

Section C: Satisfaction with UMEME

15. What is your overall satisfaction with UMEME? *

Very dissatisfied

1 c 2 c 3 c 4 c

c Very satisfied c

c 16. If someone you know was considering changing their current energy plan, would u c recommend UMEME? * c

Strongly recommend in favour c

c Recommend in favour c

c Recommend against cc

cc Strongly recommend against cc

cc Don't know c

c SUBMIT c

c Page 1 of 1 c c