ghanaopendata/ghanaian-research-english huggingface dataset:
The practice of relationship marketing in the mobile phone industry for customer retention: a case study of Scancom

The priority of any business must be to win and keep customers. One of the tools of retaining customers is the practice of relationship marketing. In the past, marketers had focused on creating customers, selling what they produced, without maintaining their customers, forgetting that customer retention is the lifeblood of any business. Over the years, firms are working on effective strategies for retaining customers since it is now seen as cost effective to improve current customers rather than acquiring new customers. Generally, the study focused attention on identifying ways by which the mobile phone industry can attract, retain, enhance and develop a long term customer relationship for a profitable industry: determine how relationship marketing is practiced in Scancom, investigate customer perception of Scancom relationship marketing practices and recommend critical success factors for effective relationship marketing in Scancom for customer retention. One hundred (100) respondents were randomly selected which was guided by sampling procedure. The respondents were sampled across two regions of the country. Two different sets of questionnaires were administered. Sixty (60) questionnaires to the clients of Scancom, whilst the remaining forty (40) went to the staff of Scancom. The findings revealed that most of the staff rated improved customer services as the most critical success factor for Scancom relationship marketing, and most of the respondents who patronized their services rated their products as very expensive among others. It was recommended that in order to ensure that Scancom retains, enhance and develop a long term customer loyalty, there is the need to strategize an effective way of promoting and slashing down prices in order to win many new customers. It was also recommended that staff should be trained to be helpful, courteous and knowledgeable by offering good customer service as competitive weapon for customer retention.

Source: KNUST
The Practice of Relationship Marketing and Customer Retention in the Ghanaian Mobile Telecommunication Industry

A study on relationship marketing practice was undertaken to examine the practice of relationship marketing by Ghana Telecom (GT) Onetouch service. Data was collected from customers, Ghana Telecom staffs in Kumasi, and Ghana Telecom publications. The study revealed that most of the customers perceive quality relationship with the firm in areas such as pricing, call clarity, however in areas like wider coverage, brand awareness, and promotions have not been effective in establishing and nurturing quality relationship with customers. Recommendations have been made to Ghana Telecom (GT) Onetouch to improve its Current systems of operations to be able respond quickly to customers needs and complaints. There should be constant monitoring of customer relationship strategies And research to identify the tools that can be effective in establishing and retaining customers for long time in Ghana Telecom (GT) Onetouch of operations.

Source: KNUST
Practices of strategic human resource management on construction sites.

Construction projects are faced with many challenges day in day out in their line of operations. One of the challenges to be considered in this study is the practices of strategic human resources management on construction project sites. Since construction projects depends mostly on manpower in its activities as compared to other industries, its human resource management is very significant towards the success of every construction projects. This thesis is about the practices and management role of human resource on construction sites. The purpose of this study was to “establish the Strategic Human Resource Management practices that could increases labour performance on construction sites”. Though, earlier research studies show that different results could be obtained from different groups of previously working employees. This study then can be seen as an indication to a more detailed study to be carried by future researchers on the field of Strategic Human Resource Management (SHRM) as well as employee’s utilization on construction sites. The study established the Strategic Human Resource practices that increases labour performance on construction sites. After the analysis, the study identified existing human resource management practices embarked on construction site, which was Recruitment and Selection Practices. The study also examined challenges affecting the effectiveness of managing people on construction projects which was “Ensuring adequate training of personnel’s and the Male-Dominant Culture. The research revealed that the best strategic Human Resource Management practice to adopt is “Managing Employee Relations”. Descriptive analysis was used in the assessment of this study and used quantitative research approach in which the sample size and sampling technique for the study were presented based on a defined population of 78 respondents on the personnel of construction managers and quantity surveyors in the Kumasi Metropolis. The survey was intended to get their responses on what they feel, are the effective strategic measures that could contribute to the effective utilization of the human resources on construction sites through managements. In this light the research seeks to identify the utmost list of strategic human resource practices managing employee relations, communication of workers and information sharing, strong communication between supervisors and project managers, performance appraisal that provides feedback, team empowerment and creating a sense of job security.

Source: KNUST
Pre-feasibility studies of Hemang hydropower site

Ghana, though has a good number of small to medium hydro power potential sites, has still not exploited all of them. The focus of this thesis is a pre-feasibility study of the technical and financial viability of power generation from a medium hydropower potential site, the Hemang site, on the Pra River in the Western region of Ghana. This study is carried out using recent flow data (1980 -2011) from the gauge station on the Pra River. The results are compared with previous studies carried out on the Hemang site by ACRES International in 1985. The power capacity, yearly energy output, greenhouse gas reduction and financial feasibility of the potential hydro site are studied in this work. The study also covers a preliminary sizing of some mechanical components (water passages) including turbine, draft tubes and penstocks for the Hemang site. RETScreen® project analysis software package was used in both the technical and financial analysis of the project. The sizing of water passages, however, was done using codes written in MATLAB®. Technical analyses of the power output capacity and yearly energy output of three (3) hydro-turbine types (Kaplan, Propeller, and Francis) operable at the same given head and design flow and also the possible reduction in greenhouse gas (CO2) by the prospective project were performed. The highest power capacity and annual energy output of the site is determined to be 70.524 MW and 225,346 MWh respectively with a Kaplan type turbine. The power capacities and annual energy output results of the Hemang site using the recent flow data on the Pra River is seen to have reduced as compared to the values stated by the Acres International’s 1985 study with flow data from 1944-1984. The financial analysis (using RETScreen® cost and financial analysis modules) was carried out on a range of electricity export rate (US$ 50/MWh - US$ 150/MWh). With a project life of 40 years and an electricity export rate of US$ 64.90/MWh, the project’s net present value (positive) is found to be about 5 times the project’s initial cost, which indicates the project is financially viable to only an extent. At the same electricity export rates, the project has an equity payback time of 13.4 years and an after-tax internal rate of return of 13.7%. This value of IRR, however, makes the project financially uncompetitive with similar project elsewhere in Africa. A greenhouse gas (GHG) analysis on the project reveals that the project will annually cut GHG emission (CO2) by 109,739 tonnes.

Source: KNUST
Precipitable water comparisons over ghana using PPP techniques and reanalysis data

Atmospheric Water vapor is an important greenhouse gas and contributes greatly in maintaining the Earth’s energy balance. This critical meteorological parameter is not being sensed by any of the 22 synoptic weather stations in Ghana. This study presents a highly precise tool for water vapor sensing based on the concept Global Navigation Satellite Systems (GNSS) meteorology and tests the computed results against global reanalysis data. Conventional approaches used to sense the atmospheric water vapor or Precipitable Water (PW) such as radiosondes, hygrometers, microwave radiometers or sun photometers are expensive and have coverage and temporal limitations. Whereas GNSS meteorological concept offers an easier, inexpensive and all-weather technique to retrieve PW or Integrated Water Vapor (IWV) from zenith tropospheric delays (ZTD) over a reference station. This study employed precise point positioning (PPP) techniques to quantify the extend of delays on the signal due to the troposphere and stratosphere where atmospheric water vapor resides. Stringent processing criteria were set using an elevation cut-off of 5 degrees, precise orbital and clock products were used as well as nominal tropospheric corrections and mapping functions implemented. The delays which are originally slanted are mapped unto the zenith direction and integrated with surface meteorological parameters to retrieve PW or IWV. The gLAB software, Canadian Spatial Reference System (CSRS) and Automatic Precise Positioning Service (APPS) online PPP services were the approaches used to compute ZTD. PW values obtained were compared with Japanese Metro Agency Reanalysis (JRA), European Centre for Medium-Range Weather Forecasts Reanalysis (ERA-interim) and National Center for Environmental Prediction (NCEP) global reanalysis data. Correlation analysis were run on the logged station data using the three approaches and global reanalysis data. The obtained results show stronger correlation between the retrieved PW values and those provided by the ERA-interim. Finally, the study results indicate that with a more densified network of GNSS base stations the retrieved PW or IWV will greatly improve numerical weather predictions in Ghana.

Source: KNUST
Precipitation variability and trends in Ghana: An intercomparison of observational and reanalysis products

Inter-annual variability and trends of annual/seasonal precipitation totals in Ghana are analyzed considering different gridded observational (gauge- and/or satellitebased) and reanalysis products. A quality-controlled dataset formed by fourteen gauges from the Ghana Meteorological Agency (GMet) is used as reference for the period 1961–2010. Firstly, a good agreement is found between GMet and all the observational products in terms of variability, with better results for the gauge-based products— correlations in the range of 0.7–1.0 and nearly null biases—than for the satellite-gauge merged and satellite-derived products. In contrast, reanalyses exhibit a very poor performance, with correlations below 0.4 and large biases in most of the cases. Secondly, a Mann-Kendall trend analysis is carried out. In most cases, GMet data reveal the existence of predominant decreasing (increasing) trends for the first (second) half of the period of study, 1961–1985 (1986–2010). Again, observational products are shown to reproduce well the observed trends—with worst results for purely satellite-derived data—whereas reanalyses lead in general to unrealistic stronger than observed trends, with contradictory results (opposite signs for different reanalyses) in some cases. Similar inconsistencies are also found when analyzing trends of extreme precipitation indicators. Therefore, this study provides a warning concerning the use of reanalysis data as pseudo-observations in Ghana.

Source: KNUST
Precursors of the Arab spring: a study of in the country of men, autumn quail, memory in the flesh and the Earthquake

The ‘Arab Spring’ is a revolutionary wave of demonstrations and protests occurring in the Arab world (North Africa and the Middle East) that began on Saturday, 18 th December, 2010. The movement originated in Tunisia and quickly took hold in Egypt, Libya, Syria, Yemen, Bahrain, Saudi Arabia, Jordan, Algeria, Morocco, Mauritania, Oman, Kuwait, Lebanon and Iraq. To date, political rulers have been forced from power in Tunisia, Egypt, Libya and Yemen. This thesis discusses the causes of the ‘Arab Spring’ as we are currently witnessing it, and aims to draw a correlation between these causes and the preoccupation of selected works of some North African writers. The current causes of the ‘Arab Spring’ are not new. They have existed since time immemorial. What we are currently witnessing is only a culmination and outburst of pent up emotions; emotions which have been held back for decades by members of most Arab societies. The works of four North African writers have been discussed to show that these writers have, previously in their various works, discussed issues affecting the masses of most Arab societies which, if they were given the needed attention and consideration, would not have brought us to the current state of unrest within most North African and Middle Eastern countries. In other words, Hisham Matar in In the Country of Men, Naguib Mahfouz in Autumn Quail, Ahlam Mosteghanemi in Memory in the Flesh, and Tahir Wattar in The Earthquake, give insights into the dissatisfaction of Arab peoples at the treatment meted out to them by their various governments as well as the poor conditions of life they live under in their own countries while a few minority groups continue to enrich themselves at the expense of the majority population. The works under study discuss a number of issues that underpin the causes of the on-going ‘Arab Spring.’ Issues such as dictatorship or absolute monarchy, human rights violations, government corruption, economic decline, unemployment, extreme poverty, and a number of demographic factors, such as a large percentage of educated but dissatisfied youth within the population have been extensively discussed. Literature therefore has been put to mimetic use by the writers whose works are under study. These writers, through the use of literary and linguistic devices like symbolism, description, rhetorical questions, allegory and comparison, provide a vivid picture of what is going on in most Arab societies. In the end these literary works provide evidence of the rich corpus of Arabic literature which for decades has not been given due recognition like its counterparts in Europe and America.

Source: KNUST
Predator - prey model of security forces versus criminals in a contemporary Ghanaian Community

A Predator prey model is developed from the population dynamics of security forces versus criminals in a contemporary community. Using ve major crime data covering the period of 2000 to 2010 from Ghana Statistical Service, two models were developed and a local stability analysis of the model after determination of the equilibrium points was investigated. With some assumptions, the parameters of the model are estimated and the simulation of the model for various scenarios using MATLAB is done. These simulations give the typical almost sinusoidal trajectories for both the populations of the security forces and criminals. This appears to con rm that the propagation of security forces and criminals follows the predator - prey model. It also shows that the security forces and criminal activities keeps rising and falling with time. It was observed that, by analysing the same point in sequential phases and nding the time in between them the approximate periods of the phase plane cycle is found to be 12 months. The results obtained suggest that criminal activities persist if not the introduction of voluntary guards.

Source: KNUST
Predator-prey model of HIV propagation in a heterosexual community

The objective of this project is to apply the predator –prey model to come out with a model for the propagation of HIV, taking into consideration the population of newly infected males and newly infected females at a given time. This particular model is conjectured because it has been observed that there is an almost sinusoidal rising and falling of the time series trajectories of newly infected male and female cases of the Ghana data. With some few assumptions made the model is formulated and the analysis shows that it conforms to the predator – prey model. Even though parameters in respect of newly infected males and females were not directly available for the simulation, with some assumptions, the parameters of the model are estimated and the simulation of the model for various scenarios using MATLAB is done. These simulations give the typical almost sinusoidal trajectories for both the populations of the newly infected males and newly infected females. This appears to confirm that the propagation of HIV follows the predator – prey model. It also shows that the rate of infections of HIV keeps rising and falling with time. The curves also show that more females are infected at any given time than males. Some recommendations regarding the eradication of HIV or the curtailment of the spread of HIV are offered.

Source: KNUST
Predicting Bank Operational Efficiency Using Machine Learning Algorithm: Comparative Study of Decision Tree, Random Forest, and Neural Networks

%e financial crisis that hit Ghana from 2015 to 2018 has raised various issues with respect to the efficiency of banks and the safety of depositors’ in the banking industry. As part of measures to improve the banking sector and also restore customers’ confidence,efficiency and performance analysis in the banking industry has become a hot issue. %is is because stakeholders have to detect the underlying causes of inefficiencies within the banking industry. Nonparametric methods such as Data Envelopment Analysis (DEA) have been suggested in the literature as a good measure of banks’ efficiency and performance. Machine learning algorithms have also been viewed as a good tool to estimate various nonparametric and nonlinear problems. %is paper presents a combined DEA with three machine learning approaches in evaluating bank efficiency and performance using 444 Ghanaian bank branches, Decision Making Units (DMUs). %e results were compared with the corresponding efficiency ratings obtained from the DEA. Finally, the prediction accuracies of the three machine learning algorithm models were compared. %e results suggested that the decision tree (DT) and its C5.0 algorithm provided the best predictive model. It had 100% accuracy in predicting the 134 holdout sample dataset (30% banks) and a P value of 0.00. %e DT was followed closely by random forest algorithm with a predictive accuracy of 98.5% and a P value of 0.00 and finally the neural network (86.6% accuracy) with a P value 0.66. %e study concluded that banks in Ghana can use the result of this study to predict their respective efficiencies. All experiments were performed within a simulation environment and conducted in R studio using R codes.

Source: KNUST
Predicting bod levels of wastewater with neural network time series

The quality of treated wastewater has always been an important issue, but it becomes even more critical as human populations increase. An accurate well-timed measurement of quality variables is essential to the successful monitoring and controlling of wastewater treatment systems. Unfortunately, current ability to monitor and control effluent quality from a wastewater treatment process is primitive. Control is difficult because wastewater treatment consists of complex multivariate processes with nonlinear relationships and time varying dynamics. Because the measurements of these variables are difficult and often involve large time delays, there is a critical need for forecasting models that are effective in predicting wastewater effluent quality. In this paper, predictive models based on artificial neural networks are presented. Water quality measurements and process data from an urban wastewater treatment plant were used to develop models to predict biochemical oxygen demand (BOD). The results provide evidence that nonlinear neural network time series models achieve accurate forecast of wastewater effluent quality.

Source: KNUST
Predicting credit default in the microfinance industry (a case Study of first allied savings and loans limited)

The study examined the prediction of credit default in the microfinance industry in Ghana. Data for the study was collected from the credit data of First Allied Savings and Loans Limited from January 2014 to December 2014. Due to the predictive focus of the study, Logistic Regression analysis technique was adopted to analyze the relationship between the variables. The results show that sector of employment, interest rate, loan cycle and loan amount are the significant factors while Gender, loan term and age do not contribute significantly to predicting credit default. Among other things, the study recommends that the financial institution take measures to build the capacity of their clients’ simple book keeping and business ethics. This will help them separate business activities from domestic affairs and will put them in a better position to repay their loans. This is because the key factors affecting default is not economical but social factors. Finally, lending more to creditworthy male clients could improve the repayment performance of MFIs in Ghana. On the other hand, the micro finance institutions should find out why the repayment rate in females is poor and develop better structures to deal with it so that they can extend more credit to women which will be in line with the objectives of microfinance. In all, the current study contributes to the literature on predicting credit default in the microfinance industry of Ghana.

Source: KNUST
"Predicting Customer Churn in the Mobile Telecommunication Industry, a Case Study of MTN Ghana, Kumasi"

Customer churn has been of much concern for companies, very active in industries where lower switching cost exists. The Telecommunication Industry is among those industries which suffer from this phenomenon, producing an annual churn rate of 30%. The best way to handle this is to understand the behavior and trend of those who churn so as to be always ahead of them. MTN Ghana, Kumasi was used as a case study to develop a predictive model for the prepaid telephony segment. The objectives of this study were to find out the extent of customer churn in MTN Ghana, Kumasi, the causes and effects of customer churn and to develop a predictive model for churn in the telecommunication industry. Questionnaires were used to find the causes of churn from the customer‘s perspective. An already defined churn variable dataset of 3333 records was used for the Predictive Model with Data Mining Techniques. The monthly churn rate for the industry is 2.5%. Poor network quality, high call charges, poor customer service and promotions from competitors are the major causes of churn. Even with the low churn rate the effects on the telecommunication firms are serious; Churn affects Market share, frustrates effort to achieve projected revenue, dissatisfied customers dent the brand image, increases operational costs as it requires marketing intervention to win-back churners as well as potential churners. Developing the predictive model, the neural network was used to calculate the propensity for a customer in the dataset to churn while the decision tree describes the behavior of the churners. The propensity for a customer to churn is 1.03 times, customer service calls, day call and international calls were the major characteristics exhibited by the churners.

Source: KNUST