Katumba Charles Wasswa

THE ROLE OF E-PAYMENT IN REVENUE COLLECTION IN UGANDA; A Case of Umeme, Nakulabye Branch. BY MAY, 2020 TABLE OF CONTENTS TABLE OF CONTENTS ........................................................................................................... ii LIST OF TABLES .................................................................................................................... vi LIST OF ACRONYMS ........................................................................................................... vii ABSTRACT............................................................................................................................ viii CHAPTER ONE: INTRODUCTION ........................................................................................ 1 1.0 Introduction ...................................................................................................................... 1 1.1 Background to the Study .................................................................................................. 1 1.1.1 Historical background................................................................................................ 1 1.1.2 Theoretical background ............................................................................................. 1 1.1.3 Conceptual background ............................................................................................. 2 1.1.4 Contextual background .............................................................................................. 3 1.2 Statement of the Problem ................................................................................................. 3 1.3 Purpose of the study ......................................................................................................... 4 1.4 Objectives of the study..................................................................................................... 4 1.5 Research questions ........................................................................................................... 4 1.6 Hypothesis........................................................................................................................ 4 1.7 Scope of the study ............................................................................................................ 4 1.7.1 Geographical scope.................................................................................................... 4 1.7.2 Subject scope ............................................................................................................. 4 1.7.3 Time scope ................................................................................................................. 5 1.8 Significance of the study .................................................................................................. 5 1.9 Operational definition of key terms ................................................................................. 5 1.10 Conceptual Framework .................................................................................................. 7 CHAPTER TWO: LITERATURE REVIEW ............................................................................ 8 2.0 Introduction ...................................................................................................................... 8 2.1 E-payment in Uganda ...................................................................................................... 8 2.1.1 Mobile Money ........................................................................................................... 9 2.1.2 PayWay ...................................................................................................................... 9 2.1.4 E-funds transfer ....................................................................................................... 10 2.2 Revenue collection ......................................................................................................... 11 ii 2.2.1 Prepaid fees (Yaka) ................................................................................................. 12 2.2.2 Postpaid bills............................................................................................................ 13 2.2.3 Connection/Reconnection fees ................................................................................ 14 2.3 E-payment charges ......................................................................................................... 15 2.4 E-payment and revenue collection ................................................................................. 15 2.4.1 The effect of Mobile Money on revenue collection ................................................ 16 2.4.2 The effect of PayWay on revenue collection........................................................... 18 2.4.3 The effect of E-Funds Transfer on revenue collection ............................................ 19 2.5 Summary of literature review ........................................................................................ 21 CHAPTER THREE: METHODOLOGY ................................................................................ 22 3.0 Introduction .................................................................................................................... 22 3.1 Research design ............................................................................................................. 22 3.2 Study Population ............................................................................................................ 22 3.3 Sample size, design and procedure ................................................................................ 22 3.3.1 Sample size .............................................................................................................. 22 3.3.2 Sampling procedure ................................................................................................. 23 3.3.3 Sampling design ...................................................................................................... 23 3.4 Data sources ................................................................................................................... 23 3.5 Data collection methods and Instruments ...................................................................... 23 3.5.1 Questionnaire ........................................................................................................... 23 3.5.2 Documentary review................................................................................................ 23 3.6 Data collection instruments............................................................................................ 24 3.6.1 Questionnaires ......................................................................................................... 24 3.7 Data quality control........................................................................................................ 24 3.7.1 Validity .................................................................................................................... 24 3.7.2 Reliability ................................................................................................................ 24 3.8 Data processing and analysis ......................................................................................... 24 3.8.1 Data processing........................................................................................................ 24 3.8.2 Data analysis ............................................................................................................ 24 3.9 Measurement of variables .............................................................................................. 25 iii 3.10 Research Procedure ...................................................................................................... 25 3.11 Ethical consideration .................................................................................................... 25 3.12 Limitations and solutions ............................................................................................. 25 CHAPTER FOUR: PRESENTATION OF FINDINGS, ANALYSIS AND INTERPRETATION................................................................................................................ 26 4.0 Introduction .................................................................................................................... 26 4.1 General information about the respondents ................................................................... 26 4.1.1 Gender of respondents ............................................................................................. 26 4.1.2 Age of the respondents ............................................................................................ 27 4.1.3 Level of education of the respondents ..................................................................... 27 4.1.4 Departments of work of the respondents ................................................................. 28 4.1.5 Tenure of service in the organization ...................................................................... 28 4.2 Electronic Payment (Independent Variable) .................................................................. 29 4.2.1 The influence of Mobile Money on revenue collection .......................................... 29 4.3.2 Regression test........................................................................................................ 34 The beta value of 0.386 reveals that mobile money explained 38.6% of the variance in the dependent variable (revenue collection of Umeme), the remaining 61.4% is explained by other strategies. The regression coefficient r =.007 was significant implying that if Umeme wants to improve its revenue collection, then, it can manipulate mobile money as a strategy to realize its objective. ...................................................................................................... 35 4.2.2 The effect of PayWay on revenue collection........................................................... 35 4.3.2 Regression test........................................................................................................ 39 4.2.3 The effect of Electronic Funds Transfer on revenue collection .............................. 41 4.3.2 Regression test ......................................................................................................... 46 The beta value of 0.786 reveals that Electronic Funds Transfer explained 78.6% of the variance in the dependent variable (revenue collection at Umeme Nakulabye branch), the remaining 39.4% is explained by other strategies. The regression coefficient r =.000 was significant implying that if Umeme wants to improve its revenue collection, then, it can manipulate Electronic Funds Transfer as a strategy to realize its objective. ....................... 47 4.3 Revenue collection (Dependent Variable) ..................................................................... 47 4.3.1 Prepaid fees ..................................................................................................................... 47 iv 4.3.2 Postpaid bills............................................................................................................ 50 4.3.3 Connection/Reconnection fees ................................................................................ 52 CHAPTER FIVE: SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS ............ 54 5.0 Introduction .................................................................................................................... 54 5.1 Summary of the study findings ...................................................................................... 54 5.1.1 The effect of Mobile Money on revenue collection ................................................ 54 Standardized Coefficients Beta is equal to 0.386 (table 11) implying that mobile money explained 38.6% of the variance in revenue collection at Umeme. The remaining 61.4% is explained by other strategies. The regression coefficient r =.007 was significant implying that Umeme can manipulate mobile money as a strategy to improve its revenue collection. .......................................................................................................................................... 55 5.1.2 The effect of PayWay on revenue collection........................................................... 55 5.1.3 The effect of Electronic Funds Transfer on revenue collection .............................. 56 5.2 Conclusions .................................................................................................................... 56 5.2.1 The effect of Mobile Money on revenue collection ................................................ 56 5.2.2 The effect of PayWay on revenue collection........................................................... 57 5.2.3 The effect of Electronic Funds Transfer on revenue collection .............................. 57 5.3 Recommendations .............................................................................................................. 57 The study makes the following recommendations: ................................................................. 57 5.4 Areas for further research .................................................................................................. 58 REFERENCES ........................................................................................................................ 59 QUESTIONNAIRE ................................................................................................................. 63 v LIST OF TABLES Table 1: Distribution of Sample Size ....................................................................................... 22 Table 2: Findings on the gender of the respondents ................................................................ 26 Table 3: Findings on the age of the respondents...................................................................... 27 Table 4: Findings on the level of education of the respondents .............................................. 27 Table 5: Findings on the departments of work ........................................................................ 28 Table 6: Findings on the tenure of service of the respondents in the organization ................. 29 Table 7: Descriptive Statistics for the effect of Mobile Money on revenue collection ........... 30 Table 8: Showing Pearson correlation between Mobile Money and revenue collection ......... 33 Table 9: Showing model summary for Mobile Money and revenue collection ...................... 34 Table 10: Showing ANOVA values for Mobile Money and revenue collection ..................... 34 Table 11: Regression coefficients for Mobile Money and revenue collection ........................ 35 Table 12: Descriptive Statistics for the effect of PayWay on revenue collection .................. 36 Table 13: Showing Pearson correlation between PayWay and revenue collection ................ 39 Table 14: Showing model summary for PayWay and revenue collection .............................. 40 Table 15: Showing ANOVA values for PayWay and revenue collection ............................... 40 Table 16: Regression coefficients for PayWay and revenue collection ................................. 40 Table 17: Descriptive Statistics for the effect of E-Funds Transfer and revenue collection ... 42 Table 18: Showing Pearson correlation between E-Funds Transfer and revenue collection .. 45 Table 19: Showing model summary for E-Funds Transfer and revenue collection ................ 46 Table 20: Showing ANOVA values for E-Funds Transfer and revenue collection ................ 46 Table 21: Regression coefficients for E-Funds Transfer and revenue collection .................... 47 Table 22: Descriptive Statistics for prepaid fees ..................................................................... 48 Table 23: Descriptive Statistics for Postpaid bills ................................................................... 50 Table 24: Descriptive Statistics for connection/reconnection fees .......................................... 52 vi LIST OF ACRONYMS ACH Automated Clearing House ATMs Automated Teller Machines B2B Business to Business B2G Business to Governments BOU Bank of Uganda DSTV Dish Satellite Television EDI Electronic Data Interchange EFT Electronic Funds Transfer ERA Electricity Regulatory Authority G2B Governments to Business G2P Governments to Person ICT Information Communication Technology KCCA Kampala Capital City Authority COVID-19 Coronavirus Desease 2019 kWh Kilo Watt Hour MMI Mobile Money International MMSPs Mobile Money Service Providers MTN Mobile Telecommunication Network NGOs Non-Governmental Organizations NITA National Information Technology Authority NSDS National Service Delivery Survey P2B Person to Business P2G Person to Governments PoS Point of Sale SFI Supervised Financial Institution TAM Technology Acceptance Model TV Television UGX Uganda Shillings URA Uganda Revenue Authority vii ABSTRACT The main objective of the study was to determine the effect of electronic payment on revenue collection in Uganda, focusing on Umeme Nakulabye branch. The study specifically focused on; the effect of Mobile Money on revenue collection, the effect of PayWay on revenue collection, and the effect of Electronic Funds Transfer on revenue collection. The study employed a cross-sectional research design with a quantitative approach. Questionnaires were used to collect data from the target sample. The target sample was determined using the table which was developed by Krejcie & Morgan, (1970) for determining the sample of a given population. Both primary and secondary data sources were used in the study. Data was analysed using SPSS version 25 and presented in form of tables showing frequencies, percentages, means, standard deviations, correlations, and regressions. The study findings show that; Mobile Money alone contributes only 13.0% to revenue collection at Umeme -Nakulabye branch. The remaining 87.0% of revenue collection is influenced by other strategies, PayWay alone contributes only 26.8% to revenue collection at Umeme -Nakulabye branch. The remaining 73.2% of revenue collection is influenced by other strategies, Electronic Funds Transfer alone contributes 60.6% to revenue collection at Umeme -Nakulabye branch. The remaining 39.4% of revenue collection is influenced by other strategies. The study concludes that; the use of Mobile Money influences revenue collection by a magnitude of 38.6%, the use of PayWay influences revenue collection by 53.3%, and the use of Electronic Funds Transfer influences revenue collection by 78.4% at Umeme -Nakulabye branch. The study recommends that; the physical collection of money from customers by some officers from Umeme should be tightened to ensure that all departments adopt e-payments systems. There should be clear regulations and policies governing the adoption of e-payments systems. The organization should increase its public awareness campaigns to ensure that the consumers get the right information about e-payment revenue collection, It was very difficult to obtain study data due to the COVID-19 lockdown, the reluctance and uncooperativeness of the respondents, who felt that they were being disturbed and would even fail to explain some technical terms. It is suggested that, another study should be conducted on the same variables by another researcher to avoid the limitation of limited information. viii CHAPTER ONE: INTRODUCTION 1.0 Introduction This section presents the background to the study, problem statement, Purpose of the study, objectives, research questions, hypothesis, significance of the study, scope of the study, definition of key terms, and the conceptual framework. 1.1 Background to the Study 1.1.1 Historical background The electronification of payment services started in the 1980s and has reached a medium level of maturity in many African countries (Miva, 2011). The first stage of innovation, process innovation, changed the way interbank payments are processed but went almost unnoticed by the public. Further stages of innovation were more visible, since they affected the way that customers interacted with their banks. Most notable was the product innovation of electronic banking, e.g. ATMs, card payments, and remote banking facilities. The banking industry was the main driving force behind these developments, which were primarily aimed at cost-saving and gains in efficiency (Dave, 2011). Currently the electronification of payments is approaching another stage, which can be largely grouped around new business opportunities in electronic commerce that have arisen from the use of the internet. High-speed networks for fixed-line and wireless data transmission and communication allow new means of interaction between consumers and merchants (Baike, 2017). Many aspects of commerce have changed, including the availability of products and services and the way that customers search, order, and pay for them. Equally, they facilitate a larger variety of remote interactions with banks. This development can lead to greater efficiency and convenience, especially if purchasing, invoicing and payment solutions are interoperable or integrated in ways that allow straight-through processing of transaction data. Besides, the telecommunications industry and near-banks are now offering payment-related services (Yolo, 2015). 1.1.2 Theoretical background One of the theories to explain E-payment is the Technology Acceptance Model (TAM). User acceptance of new information technology has been extensively studied in the context of information systems management. The Technology Acceptance Model (TAM), introduced by Davis (1989), has gained much popularity for predicting information systems acceptance. 1 Technology Acceptance Model serves to explain and predict information technology acceptance and diagnose problems before users experience the technology. Following the Technology Acceptance Model, perceived usefulness and perceived ease of use are thought to be able to predict user behavior that leads to user acceptance of the technology. Perceived usefulness, defined by Davis, et al. (1989), is the user’s subjective opinion that using a system will increase the user’s job performance within an organizational context. Perceived ease of use refers to users’ expectations that software use will be free of effort. Perceived ease of use has a direct impact on perceived usefulness, but not vice versa. In their work on validating Technology Acceptance Model, Davis et al. (1989) have discovered stronger relationships between perceived usefulness and behavioral intentions to use, than between perceived ease of use and behavioral intentions. Technology Acceptance Model is a theoretic model based on extensive empirical evidence. In the work of Davis (1989) a validated scale for measuring user acceptance along the two model’s constructs was presented and substantiated with sufficient empirical evidence. 1.1.3 Conceptual background Revenue collection is very important for every business in the world as it enables the business to acquire assets which are not liable to debt and which the business uses to develop its economy (Ngotho & Kerongo, 2014). More importantly, high revenue collection performance is vital to promote efficiency in service delivery and economic development. However, studies and other journal publications have shown that most businesses face serious challenges in their revenue collection performance (Balunywa, 2014), where businesses are not able to collect sufficient funds to cover their budget expectations. For years, revenue collectors have not been channeling all the amount of money they collect to the business Treasury (Ngotho & Kerongo, 2014). For instance, Umeme’s revenue collection staff would collude with the revenue payers to avoid paying the prescribed charges and instead bribe the collector to shield against paying the correct amount to Umeme Uganda. The net effect was a bigger loss, which deterred Umeme’s economic development and improved service delivery (Namoit, 2012). To eliminate or significantly reduce corruption and achieve Umeme’s financial objective and simplify payments, Electronic Payment (E-payment) was introduced (Njanja, 2014). The world has 2 witnessed an upsurge of Electronic Payment systems meant to facilitate the elimination of losses of revenue through corruption and simplify payments (Abor, 2004). 1.1.4 Contextual background Revenue collection in the developing economies like Uganda has not always been as effective as it should be. They face various challenges in their revenue collection performance, where Parastatals are not able to collect sufficient funds to cover their budget expectations and thereby causing huge local revenue collection gaps (Onyango, 2013). E-payment was introduced by Umeme Uganda to increase revenue collection, reduce costs of bills payment, and improve bills payment compliance. The introduction of electronic bills payment systems was intended to reduce costs of handling, processing, and storing paperwork. However, bills payment compliance levels remain low and revenue collection is below the targets set by Umeme Uganda (UMEME Integrated Annual Report, 2016). The performance of revenue collection at Umeme Uganda is deteriorated by corrupt practices issues which result in tax evasion through corruption by corrupt revenue collection officers (Balunywa, 2014). Completely avoiding tax evasion would ensure total revenue collection performance (high revenue collection compliance). Elimination of corruption would ensure that the Parastatal collects all the projected revenue and thereby increasing the revenue collection performance. 1.2 Statement of the Problem Electronic payment also dubbed “TouchPay” was introduced by Umeme Uganda to increase revenue collection, administration, avail services to the electricity consumers all the time from anywhere. It also aimed at reducing the costs of bills payment and improve bills payment compliance. The introduction of electronic bills payment systems was intended to benefit both Umeme Uganda and electricity consumers. For Umeme Uganda, electronic payment lightens the workload and reduces operational costs –such as the costs of handling, processing, and storing paperwork. However, bills payment compliance levels remain low and revenue collection is below the targets set by Umeme (Umeme Integrated Report and Financial Statements, 2018). The Parastatal still registers power and financial losses resulting from illegal power connections despite the need to increase revenue collection and enforcement to provide better services. The researcher was therefore motivated by the above background to conduct a study on the role of electronic payment on revenue collection at Umeme Nakulabye branch. 3 1.3 Purpose of the study The main purpose of the study was to examine the role of E-payment in revenue collection in Uganda, taking Umeme, Nakulabye branch as the case study. 1.4 Objectives of the study The study was guided by the following objectives: i. To determine the effect of Mobile Money on revenue collection. ii. To examine the effect of PayWay on revenue collection. iii. To determine the effect of E-Funds Transfer on revenue collection. 1.5 Research questions The study sought to answer the following questions: i. What is the effect of Mobile Money on revenue collection? ii. What is the effect of PayWay on revenue collection? iii. What is the effect of E-Funds Transfer on revenue collection? 1.6 Hypothesis The study assumed that: H1: Mobile Money affects revenue collection. H0: Mobile Money does not affect revenue collection. H1: PayWay affects revenue collection. H0: PayWay does not affect revenue collection. H1: E-Funds Transfer affects revenue collection. H0: E-Funds Transfer does not affect revenue collection. 1.7 Scope of the study 1.7.1 Geographical scope The study was carried out at Umeme, Nakulabye branch, Plot 419 Kibuga, Mengo. This is because the researcher expected to get all the needed information from this branch, to fully complete the research. 1.7.2 Subject scope The study has two variables; the independent and dependent variables. The independent variable is E-payment and it involves; Mobile Money, PayWay, and E-Funds Transfer whereas 4 the dependent variable is the revenue collected by Umeme and it involves; Prepaid (Yaka) fees, postpaid bills, Connection/Reconnection fees and assessment fees. 1.7.3 Time scope The study covered three years, from- because it is the period when Umeme customers started extensive use of Electronic Payment. 1.8 Significance of the study The study may be significant to the different stakeholders in the following ways; Government: The study findings and recommendations may be beneficial to other government parastatals by providing information on how to ensure effective e-payment that would enrich the revenue collection process hence achieve the objectives of the parastatals and propel socioeconomic development through effective revenue collection. Umeme and Similar Organizations: The study may help Umeme Uganda and similar organizations to acquire information on how to ensure effective e-payment that may enrich the revenue collection system and enable them to achieve the set goals and objectives. Scholars: The findings from the study may contribute to the body of scholarly knowledge in e-payments as a tool for optimal revenue collection. The study is a window opener for more research in the area of effective e-payment systems that would enhance high revenue collection performance, making it useful to researchers. Public: The study may help the public to understand the benefits of using electronic payment in contrast to the traditional over the counter payment system. 1.9 Operational definition of key terms E-payment: An electronic payment (e-payment), is paying for goods or services on the internet. It includes all financial operations using electronic devices, such as computers, smartphones, or tablets. Mobile Money: This refers to the use of mobile phones to transfer funds between banks or accounts, deposit or withdraw funds, or pay bills. 5 E-Funds Transfer: Electronic Funds Transfer (EFT) is the electronic transfer of money from one bank account to another, either within a single financial institution or across multiple institutions, via computer-based systems, without the direct intervention of bank staff. Revenue: Revenue is the income that a business gets from its normal business activities, usually from the sale of goods and services to customers. 6 1.10 Conceptual Framework Independent Variable Dependent Variable Revenue Collection E-Payment Variable • Mobile Money • Prepaid fees (Yaka) • PayWay • Postpaid bills • E-Funds Transfer • Connection/Reconnection fees Intervening Variable • E-payment charges • Politics • ERA Policies Source: Dave Chaffey, (2011). E-business & E-commerce management-strategy, implementation, and Practice. From the figure above, e-payment (independent variable) which is done using services like; Mobile Money (Airtel Money, MTN Mobile Money, M-Pesa, Smart Pesa and Africell Money), PayWay, and E-Funds Transfer directly affects the revenue collected by Umeme (dependent variable) in form of Prepaid fees (Yaka), Post Paid bills, Connection/Reconnection fees and Assessment charges. The figure also shows that other factors (intervening variable) such as politics, e-payment charges, and Electricity Regulatory Authority (ERA) policies also intervene in this relationship. 7 CHAPTER TWO: LITERATURE REVIEW 2.0 Introduction This section covers e-payment, the different types of e-payment in Uganda, and their relationship with revenue collection as viewed by different scholars. 2.1 E-payment in Uganda Uganda’s leader for mobile and online payment processing is Direct Pay Online because it enables the businesses in Uganda to offer safe and secure credit card processing to local customers as well as tourists, who can pay online with credit cards, mobile money, or bank transfers in real-time. In Uganda, Direct Pay Online works with the following mobile providers; Airtel and MTN. Direct Pay Online is partnered with Equity Bank in Uganda. Like most East African nations, the government of Uganda has not imposed restrictions or regulations on online or mobile payments. Businesses that are ready to offer online payments must comply with the Payment Card Industry Data Security Standard and regulations of Visa, Mastercard, and other credit card companies, but have no further bureaucracy in the form of national restrictions or regulations (Bank of Uganda, 2017). To provide a variety of adequate payment instruments to the growing corporations and the corresponding increase in their transactions, Bank of Uganda in August 2003 implemented the Electronic Funds Transfer (EFT) for both credit transfers and direct debits. The EFT system provides fast, convenient, reliable, and secure domestic payment and collection of funds (Bank of Uganda, 2017). Credit Transfers are predominantly being used by government and corporate customers to transfer salary payments to the employees’/beneficiary’s account. Payment instructions using this channel have picked up both in volumes and values especially after capping cheques to UGX 20 million in July 2007, resulting in government stopping issuing cheques to its suppliers and employees in favor of EFTs (Bank of Uganda, 2017). Direct debits involve periodic financial instructions from a customer to his/her bank authorizing a utility provider or any organization to collect funds from their account to settle an obligation. Since January 2007, some schools have embraced EFTs for payment of fees/tuition. EFT sensitization and technical workshops have been held in Mbarara, Kigezi, Rwenzori, Mbale, and West Nile Regions (Bank of Uganda, 2017). 8 2.1.1 Mobile Money Mobile money services were first introduced in March 2009; currently there are seven mobile money schemes in Uganda. The main regulatory concern for the Bank of Uganda (BOU) has been to ensure the safety of customers’ electronic value which they purchase, with cash, from mobile money agents. The BOU has only approved mobile money operations when this is done in partnership with a Supervised Financial Institution (SFI). Mobile Money Service Providers (MMSP) are required to hold, in an escrow account in their partner SFI, the equivalent of all the mobile money that has been issued to their customers and agents. MMSPs, which are not regulated financial institutions cannot intermediate nor use the funds that have been mobilized through the sale of mobile money (Ssettimba, 2016). The ability to execute instantaneous person to Person transfers, compared to the alternatives of transporting money in person or using a bus driver increases one’s purchasing power, implying that they can consume immediately- this has a multiplier effect and positively impacts on output. A World Bank study finds a 1 percent increase in financial inclusion corresponds to a 0.51 percent increase in business creation, and a 15 percent inclusion increase leads to employment growth of 1 percent. Using mobile money instead of cash or cheque for makes it simple, easy and quick for a taxpayer to settle their obligations. Voluntary compliance is sometimes hindered by cost and difficulty of being compliant (Ssettimba, 2016). The adoption of mobile money services has decreased administrative costs for companies. Many firms, such as utility companies, spent significant time and money on the administration and processing of paper bills. Incorporating electronic receipts and reporting has reduced costs and improved speed and accuracy, reducing erroneous charges for arrears, for example. Besides, mobile money has increased transaction speeds and reduced outstanding credit times, minimizing how long it takes to collect and inquire after payments. The power company UMEME, reported a 99.1% revenue collection rate in 2014 compared to 94% in 2012, the increased revenue collection rate was partly attributable to an increase in mobile money payments (Ssettimba, 2016). 2.1.2 PayWay PayWay is an e-payment service provider in Uganda, a brand of African Vending Systems Ltd. It is a private company that emerged on the Ugandan instant payments market in 2009. It employs high-tech innovations to solve varying customer payment needs. Its main goal is to 9 develop and improve the capabilities of instant payment systems in Uganda and other African countries as a whole. As a conduit between the various service providers, dealers, and endusers, it seeks to create convenient and effective partnerships that are of mutual benefit for all (Mutua, 2017). PayWay develops solutions for various platforms and ensures the convenience of payment processes. It develops independent payment software for various platforms. As well as designing and developing payment apps and devices to offer easy-to-use tools for every-day payments including - public utilities and taxes, airtime top-ups, TV subscriptions, activations for Internet bundles, loan repayments, purchasing of tickets, among others (Mutua, 2017). The company’s mission is to provide the most affordable, secure, easy to use and convenient means dedicated to solving all payment-related needs and more and a vision to develop into the best and most preferred payment platform in the country, region, and Africa as a whole. The Managing Director appointed by the Board of Directors is responsible for the running of the company together with a team of Professional Staff. Current directors are George Matua and Alexander Ingmann. PayWay is regulated by the National Information Technology Authority - NITA and it’s a registered company under the laws governing the registration of businesses in the country (Mutua, 2017). The company also operates vending machines. Payway is a vending machine that can be found at supermarkets and are an ideal way of loading internet airtime for all carriers let alone paying for DSTV, Startimes, and GoTV. It saves a lot of time for airtime purchase bearing in mind that if you had to buy scratch cards, you would have to enter one by one depending on the plan you are on. The machine sends you an instant message on your phone to let you know that your transaction was successful on top of an instant receipt. There is a toll-free number just in case you are stuck (Mutua, 2017). 2.1.4 E-funds transfer Fund transfers or payments are broadly defined to include non-cash payments to third parties, cash withdrawals, and transfers from one account to another. Funds transfer is “a means of any transfer of funds either representing an order of payment or transfer of money, which is initiated by way of instruction, authorization or order to a financial institution to debit or credit an account maintained with that financial institution and includes point of purchase transfers, 10 ATM transactions, direct deposits or withdrawal of funds, transfer initiated by telephone, internet, card or other devices” (Humphrey et al., 2011) Money transfers are generally characterized by the type of entities involved and the direction of transfer. The most common types are from: (i) person to person (P2P), (ii) person to business (P2B), (iii) business to person (B2P), and (iv) business to business (B2B). Adding local and federal governments, transfers are also made from (v) person to governments (P2G), (vi) governments to person (G2P), (vii) business to governments (B2G), and (viii) governments to business (G2B). Leaving governments aside, P2P transfers hardly exist in the United States. P2B transfers are also rare except for salary direct deposits. P2P transfers are either cash-based or accomplished by writing personal paper checks (Knorr, 2008). Electronic funds transfers via online banking require payers to input the bank account and routing numbers of the person or business to whom they wish to send money and permit them to add remarks, such as an invoice number or other reason for the transfer, if needed. The recipient of a transfer, say, a family member, a friend, or a dentist, should be able to read the credited amount and the reason for the credit transfer on her (online or paper) account statement. In the case of a P2B transfer, the payee should be able to associate the transfer with a payment for a specific service, corresponding to a specific bill (Kuttner and McAndrews, 2012). 2.2 Revenue collection Electronic revenue collection tools are many and of a different kind as used by the organizations. Plouffe et al (2000) shows that in the late 1990s, newspaper and magazine headlines speak volumes about the lack of success of many smart card-based payment systems trials undertaken. In their research when smart cards were compared to other payment systems, the findings show that cash payment was favored by 80% (non- participating respondents) and by 50% (participating respondents) compared to other four options of payment namely credit cards, checks, debit or ATM cards, and the Exact card. However, many organizations are protecting their business using technology, the overall process of revenue collection must be coordinated. Duffy and Dale, (2008) argued that it is vital to ensure that all discounts, credits, payments, deliveries, and credit card clearance are monitored and ideally controlled by one financial system. 11 The goal of any tax authority is to establish a system of tax administration that allows for the collection of required taxes at minimum cost. A tax authority engages in many activities, such as processing returns and related information from taxpayers, entering tax return data into a database, matching returns against filing requirements, processing tax payments and matching them against assessments, and issuing assessments and refunds. One way to boost a tax authority’s efficiency is by expanding its use of information and communication technology. Such technology can facilitate a broad range of services, including registering taxpayers, filing returns, processing payments, issuing assessments, and checking against third-party information (Duffy and Dale, 2008). 2.2.1 Prepaid fees (Yaka) Prepaid (Yaka) service is very different from the standard electricity service used by most households. With standard service a customer receives a monthly bill to pay for the amount of electricity used over the previous month. A prepaid consumer receives no bill. Instead the customer pays in advance to open an account with Umeme. As the customer uses electricity, Umeme deducts what the customer owes from the account. The customer monitors and replenishes the account to make sure the money in the account does not run out as electricity is used (Biedrzycki, 2013). In making payments on the account, a prepaid customer has to follow the rules set by Umeme. These rules in comparison to standard rules can make it more difficult for a low-income customer to maintain a constant supply of electricity. Many prepaid electric customers have to pay online and they are charged a fee to pay online. Prepaid service is offered to customers who have advanced digital meters where disconnections and reconnections can be carried out electronically with little time-lapse. Umeme is not permitted to charge fees for the disconnection and reconnection of prepaid electric customers. However, this rule for utilities does not always apply (Biedrzycki, 2013). There is no limit to the number of times a consumer may have to pay for prepaid service for a month. There is no limit to the number of times a consumer can be disconnected for running out of funds in a month. Under many plans, fees for making payments, receiving statements of usage and payment, and reconnection fees can become a substantial portion of the customer’s cost for prepaid electric service. Prepaid service is risky. Prices can change frequently. Keeping a constant supply of electricity is a challenge. It can be complicated and confusing. It may even 12 be impossible to know how much electricity you can use for the amount of money you prepay into your account (Biedrzycki, 2013). Shopping for prepaid electricity is more complicated than shopping for postpaid electricity. The most basic element of choosing a plan, the price per kWh is seldom certain in a prepaid plan. The differences in prices and the fees profoundly affect the total cost of electricity to the consumer. Umeme needs to do more to ensure a competitive market where consumers can select electricity service that best meets their needs at the lowest available price (Biedrzycki, 2013). 2.2.2 Postpaid bills Postpaid form of electricity payment was the main form of electricity bill payment initially. Umeme later introduced the prepaid (Yaka) means of electricity bill payment by installing prepaid meters both in residential areas and commercial offices. The installation of the prepaid meters was cut short because it did not function in some of the areas where the installation was done. In Kampala, some residential and commercial areas still operate with the postpaid form of electricity bill payment because of the stopped prepaid meter installation while the areas that were fortunate enough to have been installed with fully functional prepaid meters still use the new prepaid form of electricity bill payment (Kamenju, 2016). Postpaid form of electricity bill payment is the form that uses an electricity meter which counts and accumulates the units that you have used by the end of the one month. Umeme subsequently sends the electricity bill to your post office address in good time for you to arrange for payments early enough and make the bill payment before the date stipulated in writing on the electricity bill. The bill also clearly states that failure to pay for the bill will result in the company disconnecting your power supply leading you to pay for a re-connection fee as a fine or in some instances it might lead to permanent disconnection which is a big loss (Kamenju, 2016). In many cases the installation of postpaid meters is usually already done by Umeme before the property is developed completely and this makes it convenient for you and ready for use when relocating to the developed house as a tenant or as a property buyer. The postpaid bill is sent to your post office address in good time before disconnection is carried out hence buying you enough time to arrange for payments. One does not need to worry himself regarding a reduction in the number of units while usage. This is because regardless of how many units you use they 13 will all accumulate and, in the end, and sum up on a bill that Umeme will send to you which is very convenient for your electricity usage. You can always check your electricity bill via your mobile phone. You can always pay your postpaid electricity bill via the mobile money transfer service (Kamenju, 2016). However, on the other side, it’s very easy for someone to tamper with your meter in your absence. Postpaid meters take much time to get repaired in case of damage. The risk of illegal electricity connection is very high because of the connection exposure of the postpaid meter (Kamenju, 2016). 2.2.3 Connection/Reconnection fees Sixty percent of Ugandans wishing to access electricity shied away because of high connection charges, according to the National Service Delivery Survey (NSDS) 2015 report. The report says 21 percent of the respondents wishing to have electricity but shied away, blamed poverty while 17 percent blamed it on high end-user charges. The report indicates that connection charges range between Shs 98,000 and Shs 2m (Wesonga, 2016). Where one decides to apply for electricity connection, an inspection fee of Shs41, 000 has to be paid first to the electricity distribution company. There are 10 distribution companies in Uganda although the two main ones by clientele size are Umeme Uganda and Ferdsult Engineering Services. During an interview with Ferdsult’s planning and finance director, Mr. Bonny Kizza, said that sparse population settlement patterns increase operational and consequently, connection costs (Wesonga, 2016). Asked about the company’s connection fees, Umeme’s media manager Stephen Ilungole said complaints of high charges are unjustified. “The average cost of an electricity pole is Shs 800,000. If we had not subsidized it, the complaint about connection fees being high would be justified,” he said (Wesonga, 2016). The Uganda Bureau of Statistics 2016 report indicated that presently, only 20 percent of Ugandans access electricity, and the government intends to increase this to 30 percent by 2020. In 2014, the government launched the output-based aid project through which it intended to connect at least 655, 000 rural households to electricity. Under the project, households that had been close to an electricity pole for at least 18 months but could not afford the assessment fees could be connected. In case the distribution utility, such as Umeme, or a concessionaire like 14 the Rural Electrification Agency was satisfied with the internal wiring of the household, it would then connect such a customer (Wesonga, 2016). Despite some efficiency gains many urban poor are still unable to access mains power supply particularly in areas of high population density. The cost of connection remains relatively high and illegal connections and tariffs based on meter bypasses, whilst not cheaper in terms of unit costs, are often more financially accessible to the poor as they offer a means for people to spread payments and pay for supply when they most need it. There is arguably limited interest in supplying poorer sections of the community by the provider due to perceptions of difficulty with revenue collection/willingness and ability to pay. Lack of access increases security risks at night and constrains small business activity/options. Revenue collection and payment systems have not significantly evolved and are still heavily reliant on a manual billing process which is often subject to lengthy delays and errors. While it is possible to now make payment within banks the sector has yet to develop options for making payment through other platforms and has been very slow to try out new innovative means of improving efficiency. For example, UMEME received a report in 2007 on prepaid metering but only began a pilot project to test feasibility in 2011 (ERA, 2011). 2.3 E-payment charges At the beginning of the 21st Century, many of us were suddenly pushed to explore digital modes of making payments even for the most basic of purchases like buying daily rations and paying simple bills like Electricity and TV. While a lot of us have moved to electronic payments, not many are aware of the costs attached to it. One of the examples of e-payment is Electronic funds transfer (EFT). One can access this service either by using Internet banking or by visiting the bank branch. (Not all bank branches are enabled with this service.) Once you initiate the transfer, the money reaches the beneficiary account within hours. There is no minimum or maximum amount, however, an individual bank may put restrictions on per transaction amount. This service does not come free of charge. The bank levies certain charges based on the amount being transferred (Kamenju, 2016). 2.4 E-payment and revenue collection Though the major aim of Revenue Collection for most government parastatals is to stimulate and guide the economic and social development of the country, there are several determinants for an effective realization of the exercise. As such government parastatals are successfully 15 implementing e-payment to overcome the challenges of the corruption earlier experienced and therefore enhance optimal revenue collection. According to Balunywa et al. (2014), the use of Information Communication Technology (ICT), such as e-payment, would considerably increase the revenue collection as it helps tracking noncompliant revenue payers. Thus, the implementation of e-payment is paramount in ensuring optimal revenue collection. Various ICT based revenue collection applications are available for use in the modern world today. These are simply referred to as Electronic Payment (E- payment) system (Ndunda, et. al., 2015), integrated into revenue collection. The e-payment system is accessible online through Point of Sale (PoS) terminal devices and physical agents (such as mobile phones, debit cards, agents, mobile money). The e-payment is intended to help the companies using it to eliminate or reduce and minimize corruption (some of the problems inherent in the settlement and payment process), by allowing customers to pay their bills without having to move to the firm premises. The customers have access to their account information and even transfer money to other accounts in the comfort of their homes (Wahab, 2012). 2.4.1 The effect of Mobile Money on revenue collection By definition, efficiency means achieving maximum productivity with minimum wasted effort or expense. In our case, mobile money has proved to be efficient by reducing delivery time and costs. Given the popularity of mobile money and that over 22 million customers in Uganda now have mobile money accounts, the government should continue promoting revenue collection through mobile money. Maybe then, the number of defaulters will be reduced (BOU, 2017). Mobile money may mean that we end up having so many small companies and individuals paying little sums as tax, which is better than our current situation where only a few companies and individuals are paying their taxes. The primary case for innovative finance is to increase revenue flows and aiding revenue collection. However, mobile money will also help reduce our financial exclusion statistic. Business may start encouraging the use of mobile money as they will need e-float to be able to remit (Muhumuza, 2016). Ugandans carry out Shs 22 billion transactions per day on mobile money. One of the findings is that mobile money can facilitate the effectiveness of monetary policy to the extent that it improves financial inclusion. Mobile money services were introduced in Uganda in March 2009. There are various mobile money schemes: MTN Mobile Money, Airtel Money, M-Sente, M-cash, and Africell Money. Power company Umeme, reported a 99.1 percent revenue 16 collection rate in 2014 compared to 94 percent in 2012. The increased revenue collection rate was partly attributable to an increase in mobile money payments (Muhumuza, 2016). Bank of Uganda only approved mobile money operations after the providers entered partnership with Supervised Financial Institutions. Mobile money service providers (MMSP) are required to hold money in an escrow account in Supervised Financial Institution (SFI). The money should be the equivalent of all the mobile money issued to their customers and agents. Ivan James Ssettimba, BOU's deputy director in charge of National Payment Systems says there is evidence that mobile money has increased transaction speeds and reduced outstanding credit times, minimizing how long it takes to collect and inquire after payments (BOU, 2017). After the first attempt with Warid Telecom failed, Uganda Revenue Authority (URA) tapped MTN Uganda to allow tax payments using mobile money services. The second attempt at using mobile money for tax payment allows taxpayers to use mobile money for clearance of taxes and other non-tax revenue like driving permits, passport fees, government tender fees and court fines, among others. Taxpayers have a transaction limit of Shs4 million. URA is transforming into a client-centric organization. Anyone that accepts payments to be made and doesn’t recognize mobile money payments is not client-centric, said Ms. Doris Akol, the Commissioner-General URA (Muhumuza, 2016). In 2012, URA signed a similar agreement with then Warid Telecom and Orient Bank but a year later the deal fell through when Airtel acquired Warid. The buyer did not continue with the payment system but still, they offered fewer options when it came to the types of taxes. MTN Uganda currently has about 10 million mobile money subscribers that URA tapped. The platform also facilitates payment of utility bills and pay-tv. According to Mr. Brian Gouldie, the chief executive officer of MTN Uganda, this has taken taxpayers off the queues in banking halls (Muhumuza, 2016). The invention of “Mobile Money Banking” has been adopted in urban governments in East Africa to promote efficient and unconventional (smart) revenue collection and payments as well as financial inclusion. In Uganda, local and urban authorities are steadily adopting smart local revenue collections and payment systems through Mobile Money to collect revenues from both dwellers and businesses in Kampala Capital City Authority (KCCA). The shift to unconventional revenue collection comes at the helm of growing outcry of corruption, bribery, 17 extra illegal extortion of revenues, and high costs of revenue mobilization in Kampala Capital City Authority (Matsiko, 2018). Therefore, the intentions were: promote convenient and cost-effective of revenue transactions, discourage direct interactions and negotiations between revenues authorities and payers. Here smart revenue collections were introduced. For instance, MTN and Airtel. Mobile Money services facilitate the transfer of payments initiated only through registered mobile phones. Similarly, “PayWay” is an integrated broad-based bill payment and money transfer system with a platform used to collect and facilitate the revenue collection from citizens. Besides, as the conventional banking systems are rigid and far from the reach of the citizens, the shift to unconventional revenue collection systems remains the only option to promote financial inclusion. The geographically hard to reach citizens can pay local revenues without extra costs: travel, time and bank costs (Matsiko, 2018). 2.4.2 The effect of PayWay on revenue collection Until a few years ago, payment systems throughout Uganda, including in urban areas were almost exclusively based on direct physical payment and revenue collection by representatives of the service provider with almost exclusively manual paper-based records of users kept. Payment either took place door to door or users were required to visit cash offices maintained by the service provider. This presented some problems to both service providers and service users, particularly to the urban poor. The introduction of PayWay partly solved these problems (Ndiwalana and Popov, 2008). In addition to the above, high costs and inefficiencies in revenue collection and payment systems would frequently result in people being more likely to resort to illegal connections or unofficial service provision for which they would often pay more per unit consumption (in the case of electricity and water) and which would result in a loss of revenue for the service providers. In some cases, issues related to the inability to provide services that were accessible to the poor and to collect sufficient revenue to maintain services has led to situations where essential services are simply unavailable to significant numbers of people (Okure, 2008). One supplier “Pay Way” who originated from Russia offers payment kiosks and mobile points of service agents or retailers (who use a handheld device) to collect payments and produce both printed receipts and payment confirmation by mobile phone. Payway works on three platforms; the self-service kiosk, the mobile Point of Sale, and the web interface. Currently it is possible 18 to pay for TV connections, mobile phone airtime and other services using this. Again, it is currently appealing to the high end of its potential consumer base but has the potential to provide a wider range of services that are of major interest to the people and in locations that are accessible to them (ERA, 2009). Achievements in the electricity sector suggest that it is possible to turn around a service/sector which is performing poorly and in which there is low public confidence and to improve service delivery, efficiency, and its public image. It also suggests that it is possible to do this whilst providing better services to the people and there is at least some evidence that if a service is perceived to be effective and more transparent that this increases people’s willingness to pay. Improved efficiency in terms of payment and revenue collection systems and the use of available new technologies like PayWay can be an important element of a change strategy within such services. However, the experience in the electricity sector also suggests that developments in payment and revenue collection have to be seen as components of an overall and integrated reform process if they are to realize their full potential (ERA, 2011). To tap into the informal sector and help taxpayers meet their obligations timely and conveniently, Uganda Revenue Authority launched URA services catalog, which offers information about all URA services and a service payment method known as PayWay in addition to the existing payment platforms such as MTN mobile payment, Mobile App and banks. URA is hopeful that PayWay will enable the reduction of turnaround time for the taxpayers and hence increase their efficiency and profitability (Matsiko, 2018). 2.4.3 The effect of E-Funds Transfer on revenue collection Electronic funds transfer is one of the oldest electronic payment systems. EFT is the groundwork of the cash-less and check-less culture where paper bills, checks, envelopes, stamps are eliminated. EFT is used for transferring money from one bank account directly to another without any paper money changing hands. The most popular application of EFT is that instead of getting a paycheck and putting it into a bank account, the money is deposited into an account electronically. EFT is considered to be a safe, reliable, and convenient way to conduct business. The advantages of EFT are; simplified accounting, improved efficiency, reduced administrative costs, and improved security (Sadler, 2017). Similar to regular cash, e-cash enables transactions between customers without the need for banks or other third parties. When used, e-cash is transferred directly and immediately to the 19 participating merchants and vending machines. Electronic cash is a secure and convenient alternative to bills and coins. This payment system complements credit, debit, and charge cards and adds additional convenience and control to everyday customer cash transactions. E-cash usually operates on a smart card, which includes an embedded microprocessor chip. The microprocessor chip stores cash value and the security features that make electronic transactions secure (Pariwat & Hataiseree 2004). You can still get your tax refund directly deposited into your account. Simply provide your banking information to URA at the time you are submitting your taxes. Direct deposit is the safest, easiest, and most convenient way to receive your tax refund, regardless of how you file your taxes. Electronic Funds Transfer (EFT) provides your office with the capability to: automate your payments, electronically update your account information, and streamline your cash flow. By using EFT, you eliminate the risks associated with lost, stolen, or misdirected checks. With EFT, you save yourself and your company valuable time. EFT eliminates excess paper and helps you automate the office (Gikandi and Bloor, 2010). The fund transfer process generally consists of a series of electronic messages sent between financial institutions directing each to make debit and credit accounting entries necessary to complete the transaction. The fund transfer can generally be described as a series of payment instruction messages, beginning with the originator’s (Sending customer’s) instructions, and including a series of further instructions between the participating institutions, to make payment to the beneficiary (Receiving customer’s). Once an amount is transferred, the bank cannot reverse a transaction. If you entered the target account number incorrectly, there is no way to reverse the transaction since the bank would process the transaction under the belief that the information you provided is accurate (Kaburia, 2014). One of the major disadvantages of EFT is the risk of Security issues. Electronic banking largest adversary is the hackers who try to steal the customer’s money and their information. When the account has been compromised, money can be stolen. Hackers can also use the information obtained to steal one’s identity. This could mean a lot of trouble for the customer that can take years to fix. One’s credit accounts are opened in his or her name it can be many years before the debts are taken care of and removed off of their credit report (Gikandi and Bloor, 2010). In the United States, EFTs are also sometimes referred to as ACH transactions. ACH stands for Automated Clearing House, which is the nationwide electronic payment network that 20 allows the actual clearing of electronic payments and payment-related information between financial institutions. Payment-related information can be sent along with ACH transactions, a process known as electronic data interchange, or EDI (Sadler, 2017). Companies that receive EFT payments from customers also enjoy cash-flow advantages because they are assured that payments will be made automatically on the date they’re due rather than having to wait for checks that may or may not be “in the mail.” Utility companies and health clubs were among the first businesses to begin using EFT on a large-scale basis, but smaller firms can enjoy the same cost savings and cash flow benefits (Abor, 2014). While many of these same benefits can be accrued by accepting credit cards as an automatic payment method, EFT debits and credits are usually less expensive because they incur a flat fee per transaction instead of a percentage of each transaction amount. The larger the transaction the more expensive accepting a credit card is. Also, bank accounts don’t have expiration dates like credit cards do; and people rarely switch banks, so there’s less risk of bounced EFT transactions (Sadler, 2017). Using the EFT is also a green alternative to mailing and processing hundreds or even thousands of checks. It reduces the resources used in the creation and transportation of paper checks, including fossil fuels, trees, and water, and limits the amount of greenhouse gasses released into the atmosphere. Finally, EFT transfers are safe and secure. Since the inception of the EFT nearly 40 years ago, there has not been a single reported instance of an EFT payment being lost (Sadler, 2017). 2.5 Summary of literature review From the various literature on the study, it is clear that electronic payments play a vital role in revenue collection. For example, as stated by Balunywa et al. (2014), the use of Information Communication Technology (ICT), such as e-payment, considerably increases the revenue collection as it helps to track noncompliant revenue payers. 21 CHAPTER THREE: METHODOLOGY 3.0 Introduction This presents the procedures that were used in collecting data for the research. It describes the research design that was used, the target population, sample size and sampling techniques, the data collection instruments, data collection procedure, validity, and reliability of the research instruments and methods that were used in analyzing data. 3.1 Research design The study adopted a cross-sectional research design. This technique collects data at a particular point in time. Data for this study were collected using a combination of both primary and secondary sources to obtain quantitative data. This was accomplished by the use of questionnaires and reviews of records or documents for numeric data. 3.2 Study Population The population of the study was the employees of Umeme Nakulabye branch. The branch has 55 permanent employees in the following departments; Finance, Human Resource Management, Administration and Management, and Operations Management. 3.3 Sample size, design and procedure The sample size, procedure and design were determined as follows; 3.3.1 Sample size A sample size of 48 respondents was selected from the total population using simple random sampling. This sample constituted employees of various departments at Umeme Nakulabye branch. It was determined using the table developed by Krejcie & Morgan (1970) for determining the sample size of a given population. Table 1: Distribution of Sample Size Category Population (N) Sample size (S) Staff at Finance Department 14 10 Staff at Human Resources Management 12 10 Staff at Administration and Management 10 10 Staff at Operational Management 19 18 Total 55 48 Source: Umeme Performance Report 2016, modified using Krejcie & Morgan (1970) 22 3.3.2 Sampling procedure In this study the sample was selected randomly. Simple random sampling was applied in selecting respondents from several departments at Umeme Nakulabye branch to provide equal chances of everyone being included in the study. 3.3.3 Sampling design The researcher used Probability (simple random) sampling technique. Simple random sampling is selecting samples from a larger population size, giving all individuals an equal chance of being included in the research. Respondents from the population were selected on probability and in no particular order. 3.4 Data sources Data was collected from both primary and secondary sources. Primary data was obtained from the field by the use of data collection instruments which were questionnaires. Secondary data was obtained from published and unpublished material, research reports, Newspapers, and the internet. 3.5 Data collection methods and Instruments 3.5.1 Questionnaire Questionnaires are data collection instruments through which subjects respond to questions or statements that generally require factual information. A questionnaire with close-ended questions was used in data collection. It enabled the researcher to get direct answers and hence less time-consuming in responding. The questionnaires were used because they enable the quick collection of data and the researcher does not need to be present when the questionnaires are being completed. 3.5.2 Documentary review This is a secondary data collection method. Secondary data refers to the data which has already been collected and analyzed by someone else. Kothari emphasizes the value of documents as they can provide more insight into the phenomenon being studied by cross-validating and augmenting evidence from other sources. Relevant information was extracted and reviewed from files, magazines, reports, and other records published and unpublished which contained vital information about the study theme. This method was useful because it supplemented the questionnaire methods of data collection. 23 3.6 Data collection instruments 3.6.1 Questionnaires A self-administered questionnaire comprising several questions was designed and distributed to the respondents to fill in the spaces meant for that purpose. The respondents had to answer the questions on their own; this enabled them to give their views freely without any interruption. 3.7 Data quality control 3.7.1 Validity Validity refers to the extent to which the concept one wishes to measure is being measured by a particular scale or index. It is the extent to which an account accurately represents the social phenomena to which it refers. The validity of the instruments was measured through seeking for views from experts at Ndejje University and Umeme Nakulabye branch who assisted on the relevance of the scales in the instruments using Content Validity Index (CVI). 3.7.2 Reliability Reliability refers to the consistency measure that produces the same results across time and observers. The reliability of the questionnaires was enhanced through pre-testing of pilot samples from the field which enabled the re-phrasing of some questions. Additionally, the reliability of the items was done with the application of the Cronbach Coefficient Alpha for the computations to check for the internal consistency of the items. 3.8 Data processing and analysis 3.8.1 Data processing Data given to the researcher was edited and coded to ensure the accuracy and consistency of the information collected. All the questionnaires from the respondents were checked for completeness to avoid errors and omissions then it was coded and tabulated. 3.8.2 Data analysis The analysis was done using Statistical Package for Social Sciences (SPSS) version 25 to generate descriptive statistics such as frequencies, percentages, means, and standard deviations. Descriptive statistics helped the researcher to describe the collected data while inferential statistics such as correlations and regressions helped the researcher to test statistical hypotheses. 24 3.9 Measurement of variables The study variables were measured using item scales developed by Likert Rensis, (1932) with modifications to fit the context of the study. A five-point Likert itemized scale was used to construct the items and assess the level of the variables. The questionnaire was designed such that 1 represents strongly disagree, 2-disagree, 3-uncertain, 4-agree and 5-strongly agree. 3.10 Research Procedure The researcher obtained an introductory letter from the Research Coordinator, Ndejje University which was presented to Umeme Nakulabye branch before starting the data collection process. Sensitization of the respondents for the study was sought to enable efficient and effective data collection. This enabled the researcher to carry out the study without fear and substantive information was obtained. 3.11 Ethical consideration This refers to the code of conduct while carrying out research. The researcher ensured that the identified information was not made available to anyone who was not directly involved in the research. The researcher provided an accurate account of the information. This accuracy required debriefing between the researcher and the participants in the quantitative research. 3.12 Limitations and solutions The unwillingness of the respondents to answer questions; however, the researcher was prepared to do anything possible like to reach and convince the respondents to provide the desired data. The cost of research in terms of finance, time, and other academic undertakings was too much. The researcher suspended all non-academic pursuits and obtain financial contributions from friends and well-wishers. Loss of questionnaires by some respondents which might lead to a standstill and delays in the research process. This will be solved by printing a lot of questionnaires to replace the lost ones. Research was conducted during the COVID-19 lockdown and it was difficult to move from one place to another or trace the employees of Umeme. The researcher designed an electronic questionnaire, asked for employees’ emails, and invited them to answer the questionnaire online. 25 CHAPTER FOUR: PRESENTATION OF FINDINGS, ANALYSIS AND INTERPRETATION 4.0 Introduction This chapter contains the presentation of the study findings, analysis, and interpretation. The study findings are presented in form of tables showing frequencies, percentages, mean scores and standard deviation. The chapter was organized basing on the study objectives which were; to determine the effect of Mobile Money on revenue collection, to examine the effect of PayWay on revenue collection, and to determine the effect of eFunds Transfer on revenue collection. 4.1 General information about the respondents This section presents the study findings on the respondents’ background information. This demographic information includes; gender, age, highest level of education, department of work, and tenure of service in the organization. The researcher collected this data because it influenced the extent to which the respondents were knowledgeable about the variables that were involved in the study and the extent to which the information that they provided can be generalized to similar organizations in Uganda. 4.1.1 Gender of respondents The researcher wanted to find out whether the gender of the respondents that participated in the study influences revenue collection at Umeme -Nakulabye branch. The results are presented in Table 2 below; Table 2: Findings on the gender of the respondents Frequency Valid Male 33 Female 15 Total 48 Source: Primary data -2020 Percent- Valid Percent- Cumulative Percent- From the study results, out of the 48 respondents that participated in the study, 33 (68.8%) were males, while 15 (31.3%) were females. This shows that the biggest percentage of employees working with Umeme -Nakulabye branch is male as compared to their female counterparts. It further implies that males were more interested in the study than females. 26 4.1.2 Age of the respondents The researcher was interested in finding out how the age of each of the respondent that participated in the study affects revenue collection at Umeme -Nakulabye branch. The results are presented in the table below; Table 3: Findings on the age of the respondents Valid 21-30 years 31-40 years Above 41 years Total Source: Primary data -2020 Frequency- Percent- Valid Percent- Cumulative Percent- When asked to indicate their age, majority of the respondents 25 (52.1%) were between the age of 31 and 40 years, 17 (35.4%) were between 21 and 30 years, 6 (12.5%) were above 41 years and none of the respondents was below 20 years. This indicates that Umeme -Nakulabye branch employs people of all working-age; the youths who are energetic to take on different tasks in the organization and the elderly with senior experience about all the operations. 4.1.3 Level of education of the respondents The researcher was interested in finding out whether education levels of the respondents that participated in the study affect revenue collection at Umeme -Nakulabye branch. The results are presented in the table below; Table 4: Findings on the level of education of the respondents Frequency Valid Diploma 5 Degree 32 Masters 9 PhD 2 Total 48 Source: Primary data -2020 Percent- Valid Percent- Cumulative Percent- From the study findings, the majority of respondents that participated in the study, 32 (66.7%) had Bachelors’ degrees, 5 (10.4%) were diploma holders, 9 (18.8%) had Master’s degrees and 27 2 (4.2%) had PhDs. This shows that the organization employs people of different education qualifications basing on their capability to handle the various tasks. However, those with Bachelor’s degrees constituted the majority. This is because degree holders go through Universities where they acquire knowledge on various operations which Umeme -Nakulabye branch requires. 4.1.4 Departments of work of the respondents The researcher was interested in finding out whether the departments of work of employees at Umeme -Nakulabye branch affect revenue collection. The results are presented in the table below; Table 5: Findings on the departments of work Valid Finance Department Human Resource Management Administration & Management Operational Management Others (Specify) Total Source: Primary data -2020 Frequency 6 7 Percent 12.5 14.6 Valid Percent 12.5 14.6 Cumulative Percent 12.5 27.1 6 12.5 12.5 39.6 24 5 48 - - - Asked about their departments of work in the organization, majority of respondents 24 (50.0%) stated that they were working under operations management, 6 (12.5%) were in Administration and Management, 7 (24.6%) were under Human Resource Management, 6 (12.5%) were in the finance department, and 5 (10.4%) were in other departments. This implies that people from different departments in the organization were interested in the study. This ensured the researcher of unbiased study results. The majority were from the operations management because it is the sector where all field technicians fall. 4.1.5 Tenure of service in the organization The researcher was interested in finding out whether the length of time the respondents had spent in the organization (Umeme -Nakulabye branch) affects revenue collection. The results are presented in the table below; 28 Table 6: Findings on the tenure of service of the respondents in the organization Valid Less than 1 year 1-5 years 6-10 years More than 10 years Total Source: Primary data -2020 Frequency- Percent- Valid Percent- Cumulative Percent- The study found out that majority of the employees 33 (68.8%) that participated in the study had worked with the organization for a period of 1 to 5 years, 2 (4.2%) had been in the organization for less than a year, 10 (20.8%) had been in the Bank for (6-10) years, and 3 (6.3%) had worked for more than 10 years. The majority of the respondents that participated in the research had spent 1 to 5 years in the organization because of the nature of the working conditions for example; good salaries, and good welfare. 4.2 Electronic Payment (Independent Variable) The findings presented below are views of respondents from Umeme -Nakulabye branch on electronic payment (Independent variable) and revenue collection (Dependent variable). Electronic payment includes; Mobile Money, PayWay, and E-Funds Transfer. The findings are presented as follows; 4.2.1 The influence of Mobile Money on revenue collection The aim was to determine the influence of Mobile Money on revenue collection. Respondents were given several statements and asked to indicate the extent they agreed with each of them. To achieve this, a 5-point itemized Likert scale was used. According to the scale, 1 point = strongly disagree; 2 points = disagree; 3 points = not sure; 4 points = agree; and 5 points = strongly agree. A standard deviation greater than 1 implies a significant variance meaning there was no consensus in the responses while a standard deviation less than 1 shows that there wasn’t much variance hence consensus in the responses. 29 Table 7: Descriptive Statistics for the effect of Mobile Money on revenue collection Statement Mobile money is efficient in reducing delivery time and transaction costs. Mobile money has helped in reducing financial exclusion. Mobile money facilitates the effectiveness of monetary policy to the extent that it improves financial inclusion. The increased revenue collection rate of Umeme is partly attributable to an increase in mobile money payments. Mobile money has increased transaction speeds and reduced outstanding credit times. People use mobile money for clearance of taxes and other non-tax revenues. Mobile Money platform facilitates payment of utility bills, school fees, medical bills, and pay-tv. Mobile Money Banking promotes efficient and unconventional revenue collection. In Uganda, authorities are steadily adopting Mobile Money to collect revenues from both dwellers and businesses Mobile Money promotes convenience, and encourages direct interactions and negotiations between revenues authorities and payers Overall Average Source: Primary data -2020 1 2 3 4 5 Mean S. Dev. 2 4.2% 7 14.6% 8 16.7% 28 58.3% 3 6.3% 3.48 .967 4 8.3% 2 4.2% 9 18.8% 18 37.5% 15 31.3% 3.79 1.184 5 10.4% 1 2.1% 7 14.6% 17 35.4% 18 37.5% 3.87 1.248 3 3.6% 5 10.4% 10 20.8% 19 39.6% 11 22.9% 3.63 1.142 3 6.3% 9 18.8% 9 18.8% 17 35.4% 10 20.8% 3.46 1.202 6 12.5% 4 8.3% 9 18.8% 12 25.0% 17 35.4% 3.63 1.378 6 12.5% 4 8.3% 14 29.2% 15 31.3% 9 18.8% 3.35 1.246 4 8.3% 3 6.3% 15 31.3% 18 37.5% 8 16.7% 3.48 1.111 3 6.3% 5 10.4% 16 33.3% 14 29.2% 10 20.8% 3.48 1.130 2 4.2% 5 10.4% 10 20.8% 17 35.4% 14 29.2% 3.75 1.120 3.59 1.173 30 From the study findings on the statement, “Mobile Money is efficient in reducing delivery time and transaction costs.”, 58.3% of the respondents agreed with the statement, 6.3% strongly agreed, 6.7% were not sure 14.6% disagreed and 4.2 strongly disagreed. A mean score of 3.48 implies that most of the respondents were not sure about the statement. This implies that respondents did not know whether transacting using Mobile Money reduces the transaction time and costs or not. This implies that employees at Umeme Nakulabye branch need to be sensitized about the benefits of Mobile Money. On the statement “Mobile Money has helped in reducing financial exclusion.”, 37.5% of the respondents agreed with the statement, 31.3% strongly agreed, 18.8% were not sure, 4.2% disagreed and 8.3% strongly disagreed. A mean score of 3.79 implies that most of the respondents agreed with the statement. Since the majority of respondents agreed with this statement, it means that Mobile Money has promoted financial inclusion by enabling people in remote areas to access financial services. On the statement “Mobile Money facilitates the effectiveness of monetary policy to the extent that it improves financial inclusion.”, majority of the respondents 37.5% strongly agreed with the statement, 35.4% agreed, 14.6% were not sure, 2.1% disagreed and 10.4% strongly disagreed. A mean score of 3.87 implies that most of the respondents agreed with the statement. Since 72.9% of the respondents in total supported this statement, it implies that Mobile Money has indeed promoted financial inclusion. As emphasized by Muhumuza (2016), Ugandans carry out Shs 22 billion transactions per day on mobile money. Power company Umeme, reported a 99.1 percent revenue collection rate in 2014 compared to 94 percent in 2012. On the statement “The increased revenue collection rate of Umeme is partly attributable to an increase in mobile money payments.”, 39.6% of the respondents agreed with the statement, 22.9% strongly agreed, 20.8% were not sure, 10.4% disagreed and 6.3% strongly disagreed. A mean score of 3.63 implies that most of the respondents agreed with the statement. This means that Mobile Money has a positive influence on Umeme -Nakulabye branch’s revenue collection. On the statement “Mobile Money has increased transaction speeds and reduced outstanding credit times.”, 35.4% of the respondents agreed, 20.8% strongly agreed, 18.8% were not sure, 18.8% disagreed and 6.3% strongly disagreed. A mean score of 4.46 implies that on average, 31 the respondents were not sure about the statement. This means that, Mobile Money has eased the payment of electricity bills thus minimizing the accumulation of credit. As stated by Ivan James Ssettimba, BOU's deputy director in charge of National Payment Systems (BOU, 2017), there is evidence that mobile money has increased transaction speeds and reduced outstanding credit times, minimizing how long it takes to collect and inquire after payments. On the statement “People use Mobile Money for clearance of taxes and other non-tax revenues.”, 25.0% of the respondents agreed with the statement, 35.4% strongly agreed, 18.8% were not sure, 8.3 disagreed and 12.5% strongly disagreed. A mean score of 3.63 implies that most of the respondents agreed with the statement. This means that Mobile Money reduced the burden of going to the banks to pay taxes. The long queues in the banks were preventing many people from paying taxes. As stated by Muhumuza (2016), taxpayers use mobile money for clearance of taxes and other non-tax revenue like driving permits, passport fees, government tender fees, and court fines, among others. On the statement “Mobile Money platform facilitates payment of utility bills, school fees, medical bills, and pay-TV.”, 31.3% of the respondents agreed with the statement, 18.8% strongly agreed, 29.2% were uncertain, 8.3% disagreed, and 12.5% strongly disagreed. A mean score of 3.35 implies that most of the respondents were not sure about the statement. This implies that respondents need to be sensitized about the different payments that can be done through the Mobile Money system. On the statement “Mobile Money Banking promotes efficient and unconventional revenue collection.”, 37.5% of the respondents agreed with the statement, 16.7% strongly agreed, 31.3% were not sure, 6.3% disagreed, and 8.3% strongly disagreed. A mean score of 3.48 implies that most of the respondents were not sure about the statement. This means that, Mobile Money facilitates easy payment of bills to utility companies Umeme inclusive. On the statement “In Uganda, authorities are steadily adopting Mobile Money to collect revenues from both dwellers and businesses”, 29.2% of the respondents agreed with the statement, 20.8% strongly agreed, 33.3% were not sure, 10.4% disagreed and 6.3% strongly disagreed on this statement. A mean score of 3.48 implies that most of the respondents were not sure about this statement. As emphasized by Matsiko (2018), the shift to unconventional revenue collection comes at the helm of growing outcry of corruption, bribery, extra illegal 32 extortion of revenues, and high costs of revenue mobilization in Kampala Capital City Authority. On the statement “Mobile Money promotes convenience, and encourages direct interactions and negotiations between revenues authorities and payers”, 35.4% of the respondents agreed on this statement, 29.2% strongly agreed, 20.8% were not sure, 10.4% disagreed, and 4.2% strongly disagreed. A mean score of 3.75 implies that most of the respondents agreed with the statement. With the majority agreeing, it means that mobile money is one of the ways authorities can use to reduce corruption, bribery, and extortion. Generally, respondents agreed to a moderate degree that Mobile Money affects revenue collection with an overall mean score of 3.59. An overall standard deviation of 1.173 indicates that, there was no consensus in the responses. This generally means that Mobile Money positively contributes to the revenue collection exercise at Umeme -Nakulabye branch. 4.2.1.1 Correlation between Mobile Money and revenue collection To measure the relationship between Mobile Money and revenue collection, the researcher carried out a correlation test. The results are presented in the table below; Table 8: Showing Pearson correlation between Mobile Money and revenue collection Mobile Money Mobile Money Revenue collection Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N 1 48 .386** .007 48 Revenue collection .386** - **. Correlation is significant at the 0.01 level (2-tailed). The table above shows the relationship between Mobile Money (independent variable) and revenue collection (dependent variable). It shows that, the correlation between Mobile Money and revenue collection is r = 0.386. This implies that there is a significant (0.007) positive relationship between Mobile Money and revenue collection. It also means that Mobile Money influences revenue collection at Umeme Nakulabye branch by a magnitude of 38.6%. The 33 remaining 61.4% is influenced by other strategies. The positive value of (r) means that an increased use of mobile money leads to a corresponding increase in revenue collection and vice versa. 4.3.2 Regression test To determine the effect of Mobile Money on revenue collection, the researcher carried out a linear regression test. The results are presented in the tables below; Table 9: Showing model summary for Mobile Money and revenue collection Model 1 R .386 a R Square .149 Adjusted R Square .130 Std. Error of the Estimate .461 a. Predictors: (Constant), Mobile Money Table 9 above shows R, R Square, and Adjusted RSquare values. R represents Pearson’s correlation coefficient which is 0.386, indicating a low degree of correlation. R Square is the coefficient of determination which shows the proportion of the variance in the dependent variable that is predictable from the independent variable. Adjusted R Square is the modified version of R-square that measures how much of the variation in revenue collection is explained by the variations in the use of mobile money. In this case, 13.0% (adjusted R square of 0.130) reveals that the sample reflected 13.0% of the phenomenon in the population, the remaining 87.0% of the phenomenon being contributed by other strategies. Table 10: Showing ANOVA values for Mobile Money and revenue collection Model Sum of Squares 1 Regression 1.705 Residual 9.760 Total 11.465 a. Dependent Variable: Revenue collection df Mean Square- .212 47 F 8.037 Sig. .007b b. Predictors: (Constant), Mobile Money The ANOVA table above is used to test the null hypothesis. The value of the calculated F is 8.037 for the variance generated by the regression. By comparing the values of F, it results that it is compulsory to accept the alternative hypothesis (Mobile Money affects revenue collection at Umeme -Nakulabye branch), meaning that not all regression coefficients are equal to zero. 34 This means that a significant influence of the regression model occurs over the dependent variable. Table 11: Regression coefficients for Mobile Money and revenue collection Model 1 (Constant) Mobile Money Unstandardized Coefficients B Std. Error 2.385 .541 .424 .149 Standardized Coefficients Beta .386 t- Sig. .000 .007 a. Dependent Variable: Revenue Collection The beta value of 0.386 reveals that mobile money explained 38.6% of the variance in the dependent variable (revenue collection of Umeme), the remaining 61.4% is explained by other strategies. The regression coefficient r =.007 was significant implying that if Umeme wants to improve its revenue collection, then, it can manipulate mobile money as a strategy to realize its objective. 4.2.2 The effect of PayWay on revenue collection The aim was to determine the effect of PayWay on revenue collection. Respondents were also given numerous statements and asked to indicate the extent they agreed with each of them using a scale: 1 point = strongly disagree; 2 points = disagree; 3 points = not sure; 4 points = agree, and 5 points = strongly agree. A standard deviation greater than 1 implies a significant variance meaning there was no consensus in the responses while a standard deviation less than 1 shows that there wasn’t much variance hence consensus in responses. 35 Table 12: Descriptive Statistics for the effect of PayWay on revenue collection Statement PayWay partly solved the problem of direct physical payment and revenue collection by service providers. PayWay solved the problem of high costs and inefficiencies in revenue collection and payment systems. PayWay helped to minimize illegal connections which resulted in loss of revenue. Pay Way offers payment kiosks and mobile point of sale services. Payway works on the selfservice kiosk, the mobile Point of Sale, and the web interface. It is possible to pay for TV, phone airtime using PayWay. PayWay improves the efficiency of payment and revenue collection systems. Umeme uses PayWay to help clients meet their obligations timely and conveniently. Umeme believes that PayWay enables the reduction of turnaround time for the payments hence increased efficiency and profitability. PayWay is a component of an integrated payment reform process. Overall Average Source: Primary data -2020 1 2 3 4 5 4 3 4 18 19 8.3% 6.3% 8.3% 37.5% 39.6% 2 11 8 15 12 4.2% 22.9% 16.7% 31.3% 25.0% 7 4 10 16 11 14.6% 8.3% 20.8% 33.3% 22.9% 5 2 4 25 12 10.4% 4.2% 8.3% 52.1% 25.0 % 0 6 9 12 21 0.0% 12.5% 18.8% 25.0% 43.8% 1 4 9 21 2.1% 2 8.3% 5 18.8% 7 4.2% 10.4% 3 Mean S. Dev. 3.94 1.227 3.50 1.220 3.42 1.334 3.77 1.189 4.00 1.072 13 3.85 0.989 43.8% 26 27.1% 8 3.69 1.014 14.6% 54.2% 16.7% 9 7 16 13 3.56 1.253 6.3% 18.8% 14.6% 33.3% 27.1% 2 2 5 17 22 4.15 1.052 4.2% 4.2% 10.4% 35.4% 45.8% 2 6 4 21 15 3.85 1.130 4.2% 12.5% 8.3% 43.8% 31.3% 3.77 1.148 36 From the study findings on the statement “PayWay partly solved the problem of direct physical payment and revenue collection by service providers.”, 37.5% of the respondents agreed with the statement, 39.6% strongly agreed, 8.3% were uncertain, 6.3% disagreed and 8.3% strongly disagreed. A mean score of 3.94 implies that most of the respondents agreed with the statement. Since the majority agreed, it means that PayWay somehow eliminated the direct collection of fees from customers by Umeme workers which was associated with bribery and extortion. On the statement “PayWay solved the problem of high costs and inefficiencies in revenue collection and payment systems.”, 31.3% of the respondents agreed with the statement, 25.0% strongly agreed, 16.7% were not sure 22.9% disagreed and 4.2% strongly disagreed with this statement. A mean score of 3.50 implies that most of the respondents agreed with the statement. This means PayWay as a bills payment platform is reliable and efficient. On the statement “PayWay helped to minimize illegal connections or unofficial service provision which resulted in loss of revenue.”, 33.3% of the respondents agreed with the statement, 22.9% strongly agreed, 20.8% were not sure 8.3% disagreed and 14.6% strongly disagreed on this statement. A mean score of 3.42 implies that most of the respondents were not sure about the statement. In the researcher’s view, some of the respondents were the beneficiaries of the illegal and unofficial electricity services provision commonly known as ‘Kamyufu’, so, it was hard for them to admit that PayWay helped to overcome this problem. On the statement “PayWay offers payment kiosks and mobile point of sale services.”, 52.1% of the respondents agreed, 25.0% strongly agreed, 8.3% were not sure, 4.2% disagreed, and 10.4% strongly disagreed. A mean score of 3.77 implies that most of the respondents agreed with the statement. As stated by ERA (2009), PayWay works on three platforms; the selfservice kiosk, the mobile Point of Sale, and the web interface. Currently it is possible to pay for TV connections, mobile phone airtime and other services using this. Again, it is currently appealing to the high end of its potential consumer base but has the potential to provide a wider range of services that are of major interest to the people and in locations that are accessible to them. On the statement “PayWay works on the self-service kiosk, the mobile Point of Sale, and the web interface.”, 25.0% of the respondents agreed, 43.8% strongly agreed, 18.8% were not sure 37 and 12.5% disagreed. A mean score of 4.00 implies that most of the respondents agreed with the statement. This confirms that PayWay works on the above mentioned three platforms which increases its accessibility and ease of paying bills. On the statement “It is possible to pay for TV, phone airtime using PayWay.”, 43.8% of the respondents agreed, 27.1% strongly agreed, 18.8% were not sure 8.3% disagreed, and 2.1 strongly disagreed. A mean score of 3.85 implies that most of the respondents agreed with the statement. This implies that PayWay offers numerous services in addition to paying utility bills. On the statement “PayWay improves the efficiency of payment and revenue collection systems.”, 54.2% of the respondents agreed, 16.7% strongly agreed, 14.6% were not sure, 10.4% disagreed, and 4.2% strongly disagreed. A mean score of 3.69 implies that most of the respondents agreed with the statement. As stated by ERA (2011), improved efficiency in terms of payment and revenue collection systems and the use of available new technologies like PayWay can be an important element of a change strategy within such services. However, developments in payment and revenue collection have to be seen as components of an overall integrated reform process if they are to realize their full potential. On the statement “Umeme uses PayWay to help clients meet their obligations timely and conveniently.”, 33.3% of the respondents agreed, 27.1% strongly agreed, 14.6% were not sure, 18.8% disagreed, and 6.3% strongly disagreed. A mean score of 3.56 implies that most of the respondents agreed with the statement. This means that people can pay their electricity bills from anywhere and at any time thereby minimizing the defaulting of payments. On the statement “Umeme believes that PayWay enables the reduction of turnaround time for the payments hence increased efficiency and profitability.”, 35.4% of the respondents agreed, 45.8% strongly agreed, 10.4% were not sure, 4.2% disagreed, and strongly disagreed respectively. A mean score of 4.15 implies that most of the respondents strongly agreed with the statement. This means that PayWay greatly reduces the time needed to make a transaction. On the statement “PayWay is a component of an integrated payment reform process”, 43.8% of the respondents agreed, 31.3% strongly agreed, 8.3% were not sure and 12.5% disagreed, and 4.2% strongly disagreed. A mean score of 3.85 implies that most of the respondents agreed 38 with the statement. This means that PayWay a new system and there is a need to sensitize the masses about it and its benefits. Respondents generally agreed to the statements concerning the effect of PayWay on revenue collection with an overall mean score of 3.77. An overall standard deviation of 1.148 indicates that, there was no consensus in the responses. This means that PayWay influences the tax collection at Umeme -Nakulabye branch. 4.2.2.1 Correlation between PayWay and revenue collection To measure the relationship between PayWay and revenue collection, the researcher carried out a correlation test. The results are presented in the table below; Table 13: Showing Pearson correlation between PayWay and revenue collection PayWay PayWay Revenue Collection Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N 1 48 .533** .000 48 Revenue Collection .533** - **. Correlation is significant at the 0.01 level (2-tailed). Table 13 above shows the relationship between PayWay (independent variable) and revenue collection (dependent variable). It shows that, the correlation between PayWay and revenue collection is r = 0.533. This implies that there is a significant (0.000) positive relationship between PayWay and revenue collection at Umeme. It also means that the PayWay influences revenue collection at Umeme -Nakulabye branch by a magnitude of 53.3%. The remaining 46.7% is influenced by other strategies. The positive value of (r) means that an increase in the use of PayWay leads to a corresponding increase in revenue collection and vice versa. 4.3.2 Regression test To determine the effect of PayWay on revenue collection, the researcher carried out a linear regression test. The results are presented in the tables below; 39 Table 14: Showing model summary for PayWay and revenue collection Model 1 R .533 a R Square .284 Adjusted R Square .268 Std. Error of the Estimate .423 a. Predictors: (Constant), PayWay Table 14 above shows R, R Square, and Adjusted R Square values. R represents Pearson’s correlation coefficient which is 0.533, indicating a moderate degree of correlation. R Square is the coefficient of determination which shows the proportion of the variance in the dependent variable that is predictable from the independent variable. Adjusted R Square is the modified version of R-square that measures how much of the variation in revenue collection is explained by the variations in the use of PayWay. In this case, the sample reflects 26.8% of the phenomenon in the population, the remaining 73.2% being accountable to other factors. Table 15: Showing ANOVA values for PayWay and revenue collection Model 1 Regression Residual Total Sum of Squares- df Mean Square- .179 47 F 18.223 Sig. .000b a. Dependent Variable: Revenue Collection b. Predictors: (Constant), PayWay The ANOVA table above is used to test the null hypothesis. The value of the calculated F is 18.223 for the variance generated by the regression. By comparing the values of F, it results that it is compulsory to reject the null hypothesis (PayWay doesn't affect revenue collection), meaning that not all regression coefficients are equal to zero. This means that a significant influence of the regression model occurs over the dependent variable. Table 16: Regression coefficients for PayWay and revenue collection Model 1 (Constant) PayWay Unstandardized Standardized Coefficients Coefficients B Std. Error Beta 1.868 .482 .541 .127 .533 a. Dependent Variable: Revenue collection 40 t- Sig. .000 .000 The beta value of 0.533 reveals that the use of PayWay explained 53.3% of the variance in the dependent variable (revenue collection at Umeme -Nakulabye branch), the remaining 46.7% is explained by other strategies. The regression coefficient r =.000 was significant implying that if Umeme -Nakulabye branch wants to improve its revenue collection, then, it can manipulate PayWay as a strategy to realize its objective. 4.2.3 The effect of Electronic Funds Transfer on revenue collection The aim was to determine the effect of Electronic Funds Transfer on revenue collection. Respondents were provided with several statements and asked to indicate to what extent they agreed with them, using the scale: 1 point = strongly disagree; 2 points = disagree; 3 points = not sure; 4 points = agree, and 5 points = strongly agree. A standard deviation greater than 1 implies a significant variance meaning there was no consensus in the responses while a standard deviation of less than 1 shows that there wasn’t significance variance hence consensus in responses. 41 Table 17: Descriptive Statistics for the effect of E-Funds Transfer and revenue collection Statement E-Funds transfer is used to transfer money directly from one bank account to another. In E-Funds Transfer, the money is deposited into an account electronically. E-Funds Transfer provides the capability to automate payments and streamline cash flow. E-Funds Transfer eliminates the risks associated with lost, misdirected checks. There is no way to reverse a transaction under the EFunds Transfer method. Hackers can try to steal customer’s money and information electronically. Companies that receive EFunds Transfer payments from customers enjoy cash-flow advantages. Utility companies are among the first businesses to begin using E-Funds Transfer on a large-scale basis E-Funds Transfer debits and credits are usually less expensive because of a flat fee per transaction. Using E-Funds Transfer is an alternative to mailing and processing multiple checks. Overall Average Source: Primary data -2020 1 2 2 0 3 5 4 22 5 19 4.2% 0% 10.4% 45.8% 39.6% 1 5 8 16 18 2.1% 10.4% 16.7% 33.3% 37.5% 1 5 7 19 16 2.1% 10.4% 14.6% 39.6% 33.3% 4 5 9 20 10 8.3% 10.4% 18.8% 41.7% 20.8% 4 12 9 9 14 8.3% 25.0% 18.8% 18.8% 29.2% 2 2 8 20 16 4.2% 4.2% 16.7% 41.7% 33.3% 11 5 3 16 13 22.9% 10.4% 6.3% 33.3% 27.1% 0 6 3 21 18 0% 12.5% 6.3% 43.8% 37.5% 2 3 6 25 12 4.2% 6.3% 12.5% 52.1% 25.0% 1 1 4 17 25 2.1% 2.1% 8.3% 35.4% 52.1% 42 Mean S. Dev- 3.94 1.080 3.92 1.048 3.56 1.183 3.35 1.360 3.96 1.031 3.31 1.546 4.06 0.976 3.88 1.003 4.33 0.883 3.85 1.104 From the study findings on the statement “Electronic funds transfer is used to transfer money directly from one bank account to another.”, 45.8% of the respondents agreed, 39.6% strongly agreed, 10.4% were not sure, and 4.2% strongly disagreed. A mean score of 4.17 implies that most of the respondents agreed with the statement. With the majority agreeing, it means that Electronic Funds Transfer concerns the transfer of money from one bank account to another or across various digital platforms such as mobile money. On the statement “In Electronic Funds Transfer, the money is deposited to an account electronically.”, 33.3% of the respondents agreed, 37.5% strongly agreed, 16.7% were not sure 10.4% disagreed and 2.1 strongly disagreed. A mean score of 3.94 implies that most of the respondents agreed with the statement. This means that with Electronic Funds Transfer, there is no handling of physical cash. All the transactions are made electronically using digital exchange. On the statement “Electronic Funds Transfer provides the capability to automate payments and streamline cash flow.”, 39.6% of the respondents agreed, 33.3% strongly agreed, 14.6% were not sure, 10.4% disagreed, and 8.3 strongly disagreed. A mean score of 3.92 implies that most of the respondents agreed with the statement. This means that, with Electronic Funds Transfer, a person can schedule payments in a particular interval that is to say, weekly or monthly which eases the payment of utility bills. On the statement “Electronic Funds Transfer eliminates the risks associated with lost, stolen, or misdirected checks.”, 41.7% of the respondents agreed, 20.8% strongly agreed, 18.8% were not sure, 10.4% disagreed, and 8.3 strongly disagreed. A mean score of 3.56 implies that most of the respondents agreed with the statement. Gikandi and Bloor (2010) emphasize that, with EFT, you save yourself and your company valuable time. EFT eliminates excess paper and helps you automate the office payments. On the statement “There is no way to reverse a transaction under the Electronic Funds Transfer method.”, 18.8% of the respondents agreed, 29.2% strongly agreed, 18.8% were not sure 25.0% disagreed and 8.3 strongly disagreed. A mean score of 3.35 implies that most of the respondents were not sure about the statement. Since the majority of the respondents were not sure about this statement. It means that the respondents were divided. Some were saying that the 43 transactions can be reversed in case of a mistake whereas others were saying that, the transactions cannot be revered. On the statement “Hackers can try to steal customer’s money and information electronically.”, 41.7% of the respondents agreed, 33.3% strongly agreed, 16.7% were not sure, 4.2% disagreed and strongly disagreed respectively. A mean score of 3.96 implies that most of the respondents agreed with the statement. As stated by Gikandi and Bloor (2010), hackers can use the information obtained from EFT platforms to steal one’s identity. This could mean a lot of trouble for the customer that can take years to fix. One’s credit accounts are opened in his or her name it can be many years before the debts are taken care of and removed off of their credit report. On the statement “Companies that receive Electronic Funds Transfer payments from customers enjoy cash-flow advantages.”, 33.3% of the respondents agreed, 27.1% strongly agreed, 6.3% were not sure, 10.4% disagreed, and 22.9% strongly disagreed. A mean score of 3.31 implies that most of the respondents were uncertain about the statement. Companies that use Electronic Funds Transfer payments enjoy cash flow advantages because the money is deposited directly to their bank accounts which eliminates theft that would arise when physical cash is involved. On the statement “Utility companies are among the first businesses to begin using Electronic Funds Transfer on a large-scale basis.”, 43.8% of the respondents agreed, 37.5% strongly agreed, 6.3% were not sure and 12.5% disagreed. A mean score of 4.06 implies that most of the respondents agreed with the statement. Since the majority agreed, it implies that utility companies such as Umeme were the first to adopt Electronic Funds Transfer to ease bill payment, reduce corruption, bribery, and extortion. On the statement “Electronic Funds Transfer debits and credits are usually less expensive because they incur a flat fee per transaction.”, 52.1% of the respondents agreed, 25.0% strongly agreed, 12.5% were not sure 6.3% disagreed and 4.2% strongly disagreed. A mean score of 3.88 implies that most of the respondents agreed with the statement. As stated by Sadler (2017), EFT debits and credits are usually less expensive because they incur a flat fee per transaction instead of a percentage of each transaction amount. Bank accounts don’t have expiration dates like credit cards do; and people rarely switch banks, so there’s less risk of bounced EFT transactions. 44 On the statement “Using Electronic Funds Transfer is an alternative to mailing and processing hundreds of checks.”, 35.4% of the respondents agreed, 52.1% strongly agreed, 8.3% were not sure, 2.1% disagreed and strongly disagreed respectively. A mean score of 4.33 implies that most of the respondents agreed with the statement. This implies that EFT helps to reducing paper checks and receipts as these are issued electronically. Respondents generally agreed to a moderate degree that Electronic Funds Transfer influences revenue collection with an overall mean score of 3.85. An overall standard deviation of 1.104 means that there was no consensus in the responses. This generally means that the use of Electronic Funds Transfer influences revenue collection at Umeme -Nakulabye branch. 4.2.3.1 Correlation between Electronic Funds Transfer and revenue collection To determine the relationship between E-Funds Transfer and revenue collection, the researcher carried out a correlation test. The results are presented in the table below; Table 18: Showing Pearson correlation between E-Funds Transfer and revenue collection Electronic Funds Transfer Revenue Collection Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Electronic Funds Transfer 1 48 .784** .000 48 Revenue Collection .784** - **. Correlation is significant at the 0.01 level (2-tailed). Table 18 above shows the relationship between Electronic Funds Transfer (independent variable) and revenue collection (dependent variable). It shows that, the correlation between Electronic Funds Transfer and revenue collection is r = 0.784. This implies that there is a significant (0.000) positive relationship between Electronic Funds Transfer and revenue collection at Umeme -Nakulabye branch. It also means that Electronic Funds Transfer influences revenue collection by a magnitude of 78.4%. The remaining 21.6% is influenced by other strategies. The positive value of (r) means that an increase in the use of Electronic Funds Transfer leads to a corresponding increase in revenue collection and vice versa. 45 4.3.2 Regression test To determine the effect of Electronic Funds Transfer on revenue collection, the researcher carried out a linear regression test. The results are presented in the tables below; Table 19: Showing model summary for E-Funds Transfer and revenue collection Model 1 R .784 a R Square .614 Adjusted R Square .606 Std. Error of the Estimate .310 a. Predictors: (Constant), E-Funds Transfer Table 19 above shows R, R Square, and Adjusted R Square values. R represents Pearson’s correlation coefficient which is 0.784, indicating a moderate degree of correlation. R Square is the coefficient of determination which shows the proportion of the variance in the dependent variable that is predictable from the independent variable. Adjusted R Square is the modified version of R-square that measures how much of the variation in revenue collection is explained by the variations in Electronic Funds Transfer. In this case, 60.6% (adjusted R square of 0.606) reveals that the sample reflected 60.6% of the phenomenon in the population, the remaining 39.4% of the phenomenon being contributed by other strategies. Table 20: Showing ANOVA values for E-Funds Transfer and revenue collection Model 1 Regression Residual Total Sum of Squares- df Mean Square- .096 47 F 73.302 Sig. .000b a. Dependent Variable: Revenue Collection b. Predictors: (Constant), E-Funds Transfer The ANOVA table above is used to test the null hypothesis. The value of the calculated F is 21.288 for the variance generated by the regression. By comparing the values of F, it results that it is compulsory to accept the alternative hypothesis (E-Funds Transfer has a significant effect on revenue collection at Umeme _Nakulabye branch), meaning that not all regression coefficients are equal to zero. This means that a significant influence of the regression model occurs over the dependent variable. 46 Table 21: Regression coefficients for E-Funds Transfer and revenue collection Model 1 (Constant) E-Funds Transfer Unstandardized Standardized Coefficients Coefficients B Std. Error Beta .776 .368 .814 .095 .784 t- Sig. .041 .000 a. Dependent Variable: Revenue Collection The beta value of 0.786 reveals that Electronic Funds Transfer explained 78.6% of the variance in the dependent variable (revenue collection at Umeme Nakulabye branch), the remaining 39.4% is explained by other strategies. The regression coefficient r =.000 was significant implying that if Umeme wants to improve its revenue collection, then, it can manipulate Electronic Funds Transfer as a strategy to realize its objective. 4.3 Revenue collection (Dependent Variable) The researcher wanted to find out the effect of electronic payment on revenue collection in the form of prepaid fees (Yaka), Postpaid bills, and Connection/reconnection fees. The results are presented as follows; 4.3.1 Prepaid fees The aim was to evaluate prepaid fees at Umeme -Nakulabye branch. Respondents were provided with several statements and asked to indicate to what extent they agreed with them using the scale: 1 point = strongly disagree; 2 points = disagree; 3 points = not sure; 4 points = agree, and 5 points = strongly agree. A standard deviation greater than 1 implies a significant variance meaning that there was no consensus in the responses while a standard deviation of less than 1 shows that there wasn’t significant variance hence consensus in the responses. 47 Table 22: Descriptive Statistics for prepaid fees Statement As a prepaid customer uses electricity, Umeme deducts what the customer owes from the account. The customer monitors and replenishes the account to make sure the money in the account does not run out as electricity is used. There is no limit to the number of times a consumer may have to pay for prepaid service for a month. Prepaid service is risky as prices can change frequently and keeping a constant supply of electricity is a challenge. Shopping for prepaid electricity is more complicated than shopping for postpaid electricity. The differences in prices and the fees profoundly affect the total cost of electricity to the consumer. Overall Average Source: Primary data -2020 1 0 2 2 3 2 4 19 5 25 0% 4.2% 4.2% 39.6% 52.1% 2 4 9 15 18 4.2% 8.3% 18.8% 31.1% 37.5% 1 3 9 21 14 2.1% 6.3% 18.8% 43.8% 29.2% 0 7 10 17 14 0% 14.6% 20.8% 35.4% 29.2% 2 2 10 15 19 4.2% 4.2% 20.8% 31.1% 39.6% 3 3 13 21 8 6.3% 6.3% 27.1% 43.8% 16.7% Mean S. Dev. 4.40 .765 3.90 1.134 3.92 .964 3.79 1.031 3.98 1.082 3.58 1.048 3.93 1.004 On the statement “As a prepaid customer uses electricity, Umeme deducts what the customer owes from the account.”, 39.6% of the respondents agreed, 52.1% strongly agreed, 4.2% were not sure disagreed respectively. A mean score of 4.40 implies that most of the respondents agreed with the statement. Since the majority agreed with this statement, it implies that Umeme charges for electricity depending on the manner it is being consumed by the client. The more the consumption, the higher the bill. 48 On the statement “The customer monitors and replenishes the account to make sure the money in the account does not run out as electricity is used.”, 31.3% of the respondents agreed, 37.5% strongly agreed, 18.8% were uncertain, 8.3% disagreed and 4.2% strongly disagreed. A mean score of 3.90 implies that most of the respondents agreed with the statement. This implies that if money runs out of the account, power is automatically disconnected. On the statement “There is no limit to the number of times a consumer may have to pay for prepaid service for a month.”, 43.8% of the respondents agreed, 29.2% strongly agreed, 18.8% were uncertain, 6.3% disagreed and 2.1% strongly disagreed. A mean score of 3.92 implies that most of the respondents agreed with the statement. This means that a customer can buy power as many times as he/she wishes. On the statement “Prepaid service is risky as prices can change frequently and keeping a constant supply of electricity is a challenge.”, 35.9% of the respondents agreed, 29.2% strongly agreed, 20.7% were uncertain and 14.6% disagreed. A mean score of 3.79 implies that most of the respondents agreed with the statement. This means that, customers need to always budget from electricity to avoid being disconnected from the service. On the statement “Shopping for prepaid electricity is more complicated than shopping for postpaid electricity.”, 31.3% of the respondents agreed, 39.6% strongly agreed, 20.8% were not sure, 4.2% disagreed and strongly disagreed respectively. A mean score of 3.98 implies that most of the respondents agreed with the statement. What makes it complicated is the automatic disconnection of power in case of failure to pay. This is because payment is affected before consumption. On the statement “The differences in prices and the fees profoundly affect the total cost of electricity to the consumer.”, 43.8% of the respondents agreed, 16.7% strongly agreed, 27.1% were not sure, and 6.3% disagreed and strongly disagreed respectively. A mean score of 3.58 implies that most of the respondents agreed with the statement. This means that prepaid electricity is more expensive as compared to postpaid because it involves more charges such as electronic transfer fees. 49 4.3.2 Postpaid bills The aim was to evaluate postpaid bills at Umeme -Nakulabye branch. Respondents were given statements and asked to indicate to what extent they agreed with them, using the scale: 1 point = strongly disagree; 2 points = disagree; 3 points = not sure; 4 points = agree, and 5 points = strongly agree. A standard deviation greater than 1 implies a significant variance meaning there was no consensus in the responses while a standard deviation of less than 1 shows that there wasn’t significant variance hence consensus in the responses. Table 23: Descriptive Statistics for Postpaid bills Statement Postpaid electricity payment was the main form of electricity bill payment initially. Postpaid electricity bill payment uses an electricity meter which counts and accumulates the units consumed by the end of the one month. A Postpaid bill is sent to the customer’s address in time before disconnection is carried out. With a Postpaid bill payment, one does not need to worry about a reduction in the number of units. You can always pay your postpaid electricity bill via the mobile money transfer service It's very easy for someone to tamper with the meter in your absence and Postpaid meters take much time to get repaired in case of damage. Overall Average Source: Primary data -2020 1 3 2 1 3 4 4 18 5 22 6.3% 2.1% 8.3% 37.5% 45.8% 2 1 12 18 15 4.2% 2.1% 25.0% 37.5% 31.3% 2 5 2 22 17 4.2% 10.4% 4.2% 45.8% 35.4% 3 6 6 20 13 6.3% 12.5% 12.5% 41.7% 27.1% 5 0 8 17 18 10.4% 0% 16.7% 35.4% 37.5% 2 3 8 20 15 4.2% 6.3% 16.7% 41.7% 31.3% 50 Mean S. Dev- 3.90 1.016 3.98 1.101 3.71 1.184 3.90 1.225 3.90 1.057 3.92 1.112 The study findings on the statement “Postpaid electricity payment was the main form of electricity bill payment initially.”, 37.5% of the respondents agreed, 45.8% strongly agreed, 8.3% were not sure, 2.1% disagreed and 6.3% strongly disagreed. A mean score of 4.15 implies that most of the respondents agreed with the statement. This implies that postpaid bill payment was the only bill payment platform before the invention of electronic payment. On the statement “Postpaid electricity bill payment uses an electricity meter which counts and accumulates the units consumed by the end of the one month.”, 37.5% of the respondents agreed, 31.3% strongly agreed, 25.0% were not sure, 2.1% disagreed, and 4.2 strongly disagreed. A mean score of 3.90 implies that most of the respondents agreed with the statement. On the statement “A Postpaid bill is sent to the customer’s address in time before disconnection is carried out.”, 45.8% of the respondents agreed, 35.4% strongly agreed, 4.2% were not sure, 10.4% disagreed, and 4.2% strongly agreed. A mean score of 3.98 implies that most of the respondents agreed with the statement. This means that with postpaid bill payment, a customer is given some time to clear the bill before disconnection is done unlike prepaid payment where the disconnection is automatically done. On the statement “With a Postpaid bill payment, one does not need to worry about a reduction in the number of units.”, 41.7% of the respondents agreed, 27.1% strongly agreed, 2.5% were not sure, 2.5% disagreed, and 6.3 strongly agreed. A mean score of 3.71 implies that most of the respondents agreed with the statement. A customer doesn’t need to worry about the number of units because he/she is given sufficient time to pay and the disconnection is not automatic. The disconnection is always done after presenting a disconnection order. On the statement “You can always pay your postpaid electricity bill via the mobile money transfer service”, 35.4% of the respondents agreed, 37.5% strongly agreed, 16.7% were not sure, and 10.4% strongly disagreed. A mean score of 3.90 implies that most of the respondents agreed with the statement. This means that Mobile Money is now the most convenient way of paying utility bills. On the statement “It's very easy for someone to tamper with the meter in your absence and Post-paid meters take much time to get repaired in case of damage.”, 41.7% of the respondents agreed, 31.3% strongly agreed, 16.7% were not sure, 6.3% disagreed and 4.2% strongly disagreed. Prepaid meters are always placed outside the building in the meter box which makes 51 it prone to tampering and damage unlike postpaid meters which are always placed on top of the electricity pole. 4.3.3 Connection/Reconnection fees The aim was to evaluate connection/reconnection fees at Umeme -Nakulabye branch. Respondents were also provided with several statements and asked to indicate the extent they agreed with each of them, using the scale: 1 point = strongly disagree; 2 points = disagree; 3 points = not sure; 4 points = agree, and 5 points = strongly agree. A standard deviation greater than 1 implies a significant variance meaning there was no consensus in the responses while a standard deviation of less than 1 shows that there wasn't significant variance hence consensus in responses. Table 24: Descriptive Statistics for connection/reconnection fees Statement Sixty percent of Ugandans wishing to access electricity shy away because of high connection charges. The average cost of an electricity pole is Shs800,000. Settlement patterns affect operational and connection costs. 30 percent of Ugandans access electricity. The cost of connection remains relatively high along with illegal connections and tariffs based on meter bypasses. Lack of access to electricity increases security risks at night and constrains small business activity/options. Overall Average Source: Primary data -2020 1 8 2 1 3 5 4 19 5 15 16.7% 2.1% 10.4% 39.6% 31.3% 0 3 5 20 20 0% 6.3% 10.4% 41.7% 41.7% 2 7 8 20 9 4.3% 14.6% 16.7% 41.7% 18.8% 2 2 6 20 1 4.3% 1 12.5% 7 2.1% 2.1% 3 6.3% 4.3% Mean S. Dev- 4.12 1.044 3.48 1.203 18 4.04 1.031 41.7% 20 37.5% 19 4.15 .899 14.6% 41.7% 39.6% 5 6 19 15 3.79 1.184 10.4% 12.5% 39.6% 31.3% 3.88 1125 52 On the statement “Sixty percent of Ugandans wishing to access electricity shy away because of high connection charges.”, 39.6% of the respondents agreed, 31.3% strongly agreed, 10.4% were not sure, and 16.7% disagreed. A mean score of 3.67 implies that most of the respondents agreed with the statement. This means that most Ugandans are not connected to electricity because of the high connection charges. This has been partly solved by the Rural Electrification Program of the government of Uganda. On the statement “The average cost of an electricity pole is Shs800,000.”, 41.7% of the respondents agreed, 41.7% strongly agreed, 10.4% were not sure, and 6.3% disagreed. A mean score of 4.12 implies that most of the respondents agreed with the statement. This means that the cost of an electric pole is too high thus, the government needs to provide free poles or reduce the amount to make it affordable to an ordinary Ugandan. On the statement “Settlement patterns affect operational and connection costs.”, 41.7% of the respondents agreed, 18.8% strongly agreed, 16.7% were not sure, 14.6% disagreed and 8.3% strongly disagreed. A mean score of 3.48 implies that most of the respondents agreed with the statement. On the statement “30 percent of Ugandans access electricity.”, 41.7% of the respondents agreed, 37.5% strongly agreed, 12.5% were not sure, 4.2% disagreed and strongly disagreed respectively. A mean score of 4.04 implies that most of the respondents agreed with the statement. This implies that, a small percentage of Ugandan use electricity which increases deforestation as people cut down trees to get fuel in the form of firewood and charcoal. On the statement “The cost of connection remains relatively high along with illegal connections and tariffs based on meter bypasses.”, 41.7% of the respondents agreed, 39.6% strongly agreed, 4.6% were not sure, 2.1% disagreed and strongly disagreed respectively. A mean score of 4.15 implies that most of the respondents agreed with the statement. This means Umeme makes a lot of losses because of illegal connections and meter bypasses. On the statement “Lack of access to electricity increases security risks at night and constrains small business activity/options.”, 39.6% of the respondents agreed, 31.3% strongly agreed, 2.5% were not sure, 10.4% disagreed and 6.3% strongly disagreed. A mean score of 3.79 implies that most of the respondents agreed with the statement. This means that electricity can be improved if authorities install street lights on all major roads in the country. 53 CHAPTER FIVE: SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS 5.0 Introduction This chapter presents the summary of major findings, conclusions, and recommendations about the study. The findings are discussed concerning the study objectives, case study, and reviewed literature. The summary gives an overview of the research from which conclusions and recommendations are drawn. 5.1 Summary of the study findings The summary is based on the study objectives which were; to determine the effect of Mobile Moneys on revenue collection at Umeme, to examine the effect of PayWay on revenue collection, and to determine the effect of Electronic Funds Transfer on revenue collection. 5.1.1 The effect of Mobile Money on revenue collection The study obtained an overall mean of 3.59 and a standard deviation of 1.173 (table 7). The overall mean of 3.59 implies that respondents agreed to a moderate degree that Mobile Money affects revenue collection. Whereas an overall standard deviation of 1.173 means that, there was no consensus in the responses. This means that the use of Mobile Money affects revenue collection at Umeme -Nakulabye branch. Pearson’s correlation between Mobile Money and revenue collection (table 8) shows that there is a weak positive relationship between the two variables with r = 0.386 and p = 0.007. This means that Mobile Money influences revenue collection at Umeme Nakulabye branch by a magnitude of 38.6%. The remaining 61.4% is influenced by other strategies. The positive value of (r) means that an increased use of mobile money leads to a corresponding increase in revenue collection and vice versa. Concerning the adjusted R square value (table 9), Mobile Money contributes only 13.0% to revenue collection at Umeme -Nakulabye branch. The remaining 87.0% of revenue collection is influenced by other strategies. Table 10 shows that the regression model predicts the dependent variable significantly well. There is a statistical significance of the regression model shown by F = 8.037 and P = 0.007. Therefore, H0 which was stated as, “Mobile Money doesn’t affect revenue collection at Umeme 54 -Nakulabye branch”, was rejected and H1 which was stated as, “Mobile Money has an effect on revenue collection at Umeme -Nakulabye branch”, was accepted. Standardized Coefficients Beta is equal to 0.386 (table 11) implying that mobile money explained 38.6% of the variance in revenue collection at Umeme. The remaining 61.4% is explained by other strategies. The regression coefficient r =.007 was significant implying that Umeme can manipulate mobile money as a strategy to improve its revenue collection. 5.1.2 The effect of PayWay on revenue collection The researcher obtained an overall mean of 3.77 and a standard deviation of 1.148 (table 12). The overall mean of 3.77 imply that respondents agreed that PayWay influence revenue collection. Whereas an overall standard deviation of 1.148 means that, there was no consensus in the responses. This means that PayWay influences the revenue collection at Umeme Nakulabye branch. Pearson’s correlation between PayWay and revenue collection (table 13) shows that there is a moderate positive relationship between the two variables with r = 0.533 and p = 0.000. This means that the use of PayWay influences revenue collection by 53.3% at Umeme -Nakulabye branch. Concerning the adjusted R square value (table 14), PayWay contributes only 26.8% to revenue collection at Umeme -Nakulabye branch. The remaining 73.2% of revenue collection is influenced by other strategies. Table 15 shows that the regression model predicts the dependent variable significantly well. There is a statistical significance of the regression model shown by F=18.223 and P=0.000. Therefore, H0 which was stated as, “PayWay doesn’t affect revenue collection at Umeme Nakulabye branch”, was rejected and H1 which was stated as “PayWay affects revenue collection at Umeme -Nakulabye branch”, was accepted. Standardized coefficients Beta is equal to 0.533 (table 16) implying that the use of PayWay explained 53.3% of the variance in revenue collection at Umeme -Nakulabye branch. The remaining 46.7% is explained by other strategies. The regression coefficient r =.000 was significant implying that Umeme -Nakulabye branch can manipulate PayWay as a strategy to improve its revenue collection. 55 5.1.3 The effect of Electronic Funds Transfer on revenue collection The researcher obtained an overall mean of 3.85 and a standard deviation of 1.104 (table 17). The overall mean of 3.85 implies that respondents agreed that Electronic Funds Transfer affects revenue collection. Whereas an overall standard deviation of 1.104 means that, there was no consensus in the responses. This means that the use of Electronic Funds Transfer affects revenue collection at Umeme -Nakulabye branch. Pearson’s correlation between Electronic Funds Transfer and revenue collection (table 18) shows that there is a strong positive relationship between the two variables with r = 0.784 and p = 0.000. This means that the use of Electronic Funds Transfer influences revenue collection at Umeme -Nakulabye branch by 78.4%. Concerning the adjusted R square value (table 19), Electronic Funds Transfer contributes 60.6% to revenue collection at Umeme -Nakulabye branch. The remaining 39.4% of revenue collection is influenced by other strategies. Table 20 shows that the regression model predicts the dependent variable significantly well. There is a statistical significance of the regression model indicated by F=73.302 and P=0.000. Therefore, H0 which was stated as, “Electronic Funds Transfer doesn’t affect revenue collection at Umeme -Nakulabye branch”, was rejected and H1 which was stated as, “Electronic Funds Transfer affects revenue collection at Umeme -Nakulabye branch”, was accepted. Standardized Coefficients Beta is equal to 0.784 (table 21) implying that Electronic Funds Transfer explained 78.6% of the variance revenue collection at Umeme Nakulabye branch. The remaining 39.4% is explained by other strategies. The regression coefficient r =.000 was significant implying that Umeme can manipulate Electronic Funds Transfer as a strategy to improve its revenue collection. 5.2 Conclusions Basing on the objectives of the study and the findings, the study makes the following conclusions: 5.2.1 The effect of Mobile Money on revenue collection The first research objective was stated as, “To determine the effect of Mobile Moneys on revenue collection” and the first research question was stated as, “What is the effect of Mobile 56 Money on revenue collection?” The study concludes that; Mobile Moneys affects revenue collection at Umeme -Nakulabye branch by 38.6%, basing on Pearson product-moment correlation coefficient of r = 0.386. The positive value of (r) means that, an increase in the use of Mobile Moneys increases revenue collection and vice-versa. Therefore, research objective one was achieved and research question one was answered. 5.2.2 The effect of PayWay on revenue collection The second research objective was stated as, “To examine the effect of PayWay on revenue collection.” and the second research question was stated as, “What is the effect of PayWay on revenue collection?” The study concludes that; PayWay affect revenue collection 53.3%, basing on Pearson product-moment correlation coefficient of r = 0.533. The positive value of (r) means that an increased use of PayWay increases revenue collection and vice-versa. Therefore, research objective two was achieved, and research question two was answered. 5.2.3 The effect of Electronic Funds Transfer on revenue collection The third research objective was stated as, “To determine the effect of Electronic Funds Transfer on revenue collection” and the third research question was stated as, “What is the effect of Electronic Funds Transfer on revenue collection?” The study concludes that; Electronic Funds Transfer affects revenue collection by a magnitude of 78.4% basing on Pearson product-moment correlation coefficient of r = 0.784. The positive value of (r) means that an increased use of Electronic Funds Transfer increases revenue collection and vice-versa. Therefore, research objective three was achieved, and research question three was answered. 5.3 Recommendations The study makes the following recommendations: The study recommends that, Umeme Uganda should review its revenue collection standards and audit policies to ensure that all its branches are compelled by regulations to adopt epayment and ensure proper management of the revenue. There should be structured e-payment adoption standards and structure in Umeme. The physical collection of money from customers by some officers from Umeme should be tightened to ensure that all departments adopt e-payments systems. There should be clear regulations and policies governing the adoption of e-payments systems. The organization 57 should increase its public awareness campaigns to ensure that the consumers get the right information about e-payment revenue collection. The study embarked on collecting data from employees at Umeme -Nakulabye branch. However, it isolated the specific basic revenue source, which limited the applicability of the results to Umeme only. So other studies should be done to assess the effects of e-payment to other organizations using it. It was very difficult to obtain some study data due to the COVID-19 lockdown, the reluctance and uncooperativeness of the respondents, who felt that they were being disturbed and would even fail to explain some technical terms. The study, therefore, recommends that another study should be conducted on the same variables by another researcher to avoid the limitation of limited information. Umeme uses developments for taxation purposes to avoid the creation of a separate and burdensome tax regime. However, modifying systems after they have been finalized is costly and should be avoided where possible. Umeme should co-operate with business initiatives to create protocols for trade that facilitate electronic offers, delivery, payment, documentation, and express views promptly to the bodies developing such protocols so that they can be developed, considering the views of URA. 5.4 Areas for further research The study specifically focused on the relationship between electronic payment and revenue collection. However, there are more areas for further research in this perspective such as; • Electronic payment systems and the performance of utility companies • Electronic payment systems and illegal electricity connections • Electronic payment and extortion of customers by utility company official 58 REFERENCES Abor, J. (2004). Technological Innovation and Banking in Ghana, An Evaluation of Customers' Perspective. American Academy of Financial Management, 1(3), 338-356. Baike, (2017). Third-Party online payment. 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QUESTIONNAIRE Dear Respondent, I am a student at Ndejje University, pursuing a Bachelor’s Degree in Procurement and Logistics Management. I am researching the topic “The role of e-payment in revenue collection in Uganda; A Case of Umeme, Nakulabye Branch”. You have been chosen to participate in this study and your opinions shall be strictly kept confidential and information provided will be used strictly for academic purposes. You are therefore kindly requested to provide the relevant information in good faith. SECTION A: Background Information (Tick the most appropriate) 1) Gender (a) Male (b) Female 2) Age (a) Below 20 years (b) 21-30 years (c) 31-40 years (d) Above 41 years 3) Highest level of education (a) Certificate (b) Diploma (d) Masters (e) PhD (c) Degree Others (Specify)……………………………………………………………………………… 4) Department of work (a) Finance Department (b) Human Resource Management (c) Administration & Management (d) Operational Management Others (Specify)………………………………………………………………………………... 5) Tenure of service in the organization (a) Less than 1 year (b) 1-4 years (c) 4-8 years (d) More than 8 years 63 SECTION B: E-PAYMENT (INDEPENDENT VARIABLE) Use the scale below to respond to the statements in the table (Tick a box of your choice) Scale; 1= Strongly Disagree, 2=Disagree, 3=Not sure, 4=Agree, 5= Strongly Agree SN Statement 1 2 3 4 5 Mobile Money 1 Mobile money is efficient in reducing delivery time and transaction costs. 2 Mobile money has helped in reducing financial exclusion. 3 Mobile money facilitates the effectiveness of monetary policy to the extent that it improves financial inclusion. 4 The increased revenue collection rate of Umeme is partly attributable to an increase in mobile money payments. 5 Mobile money has increased transaction speeds and reduced outstanding credit times. 6 People use mobile money for clearance of taxes and other non-tax revenues. 7 Mobile Money platform facilitates payment of utility bills, school fees, medical bills, and pay-tv. 8 Mobile Money Banking promotes efficient and unconventional revenue collection. 9 In Uganda, authorities are steadily adopting Mobile Money to collect revenues from both dwellers and businesses 10 Mobile Money promotes convenience, and encourages direct interactions and negotiations between revenues authorities and payers PayWay 1 PayWay partly solved the problem of direct physical payment and revenue collection by service providers. 2 PayWay solved the problem of high costs and inefficiencies in revenue collection and payment systems. 3 PayWay helped to minimize illegal connections or unofficial service provision which resulted in a loss of revenue. 4 Pay Way offers payment kiosks and mobile point of sale services. 5 Payway works on the self-service kiosk, the mobile Point of Sale, and the web interface. 6 It is possible to pay for TV, phone airtime using PayWay. 7 PayWay improves the efficiency of payment and revenue collection systems. 8 Umeme uses PayWay to help clients meet their obligations timely and conveniently. 64 - Umeme believes that PayWay enables the reduction of turnaround time for the payments hence increased efficiency and profitability. PayWay is a component of an integrated payment reform process. E-Funds transfer Electronic funds transfer is used to transfer money directly from one bank account to another. In electronic Funds Transfer, the money is deposited to an account electronically. Electronic Funds Transfer provides the capability to automate payments and streamline cash flow. Electronic Funds Transfer eliminates the risks associated with lost, stolen, or misdirected checks. There is no way to reverse a transaction under the Electronic Funds Transfer method. Hackers can try to steal customer’s money and information electronically. Companies that receive Electronic Funds Transfer payments from customers enjoy cash-flow advantages. Utility companies are among the first businesses to begin using Electronic Funds Transfer on a large-scale basis Electronic Funds Transfer debits and credits are usually less expensive because they incur a flat fee per transaction. Using Electronic Funds Transfer is an alternative to mailing and processing hundreds of checks. SECTION C: REVENUE COLLECTION (DEPENDENT VARIABLE) Use the scale below to respond to the statements in the table (Tick a box of your choice) Scale; 1= Strongly Disagree, 2=Disagree, 3=Not sure, 4=Agree, 5= Strongly Agree SN Statement 1 2 3 4 5 Prepaid fees (Yaka) 1 As a prepaid customer uses electricity, Umeme deducts what the customer owes from the account. 2 The customer monitors and replenishes the account to make sure the money in the account does not run out as electricity is used. 3 There is no limit to the number of times a consumer may have to pay for prepaid service for a month. 4 Prepaid service is risky as prices can change frequently and keeping a constant supply of electricity is a challenge. 5 Shopping for prepaid electricity is more complicated than shopping for postpaid electricity. 65 6 1 2 3 4 5 6 1 2 3 4 5 6 The differences in prices and the fees profoundly affect the total cost of electricity to the consumer. Postpaid bills Postpaid electricity payment was the main form of electricity bill payment initially. Postpaid electricity bill payment uses an electricity meter which counts and accumulates the units consumed by the end of the one month. A Postpaid bill is sent to the customer’s address in time before disconnection is carried out. With a Postpaid bill payment, one does not need to worry about a reduction in the number of units. You can always pay your postpaid electricity bill via the mobile money transfer service It's very easy for someone to tamper with the meter in your absence and Postpaid meters take much time to get repaired in case of damage. Connection/Reconnection fees Sixty percent of Ugandans wishing to access electricity shy away because of high connection charges. The average cost of an electricity pole is Shs800,000. Settlement patterns affect operational and connection costs. 30 percent of Ugandans access electricity. The cost of connection remains relatively high along with illegal connections and tariffs based on meter bypasses. Lack of access to electricity increases security risks at night and constrains small business activity/options. Thanks for your time 66