BY YEAR |  BY AUTHOR |  BY TITLE |  BY COLLEGE/FACULTY/DEPARTMENT
Dr. Kate O. Litondo Publications | ||||
1 | 2016 | INFORMATION COMMUNICATION TECHNOLOGIES AND MARKETING DECISIONS AMONG SMALL SCALE FARMERS IN KENYA: REVIEW OF EVIDENCE Click to View Abstract
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2 | 2016 | Women Micro And Small Enterprises As A Platform For Human Development In Kenya: A Case Of Kisumu City Click to View Abstract
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3 | 2016 | A Theoretical Review Of Mobile Commerce Success Determinants Click to View Abstract
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4 | 2015 | Women Micro And Small Enterprises As A Platform For Human Development In Kenya: A Case Of Kisumu City Click to View Abstract Micro and Small Enterprises (MSEs) are contributing a lot to the Kenyan national | ||
5 | 2015 | Pro-Poor Mobile Financial Services Click to View Abstract
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6 | 2014 | Indicators Of Value Added Agri-Businesses On Small Farms In Kenya: An Empirical Study Of Kiambu And Murang’a Counties Click to View Abstract Kenya is ranked among the top ten largest economies in Africa and bearing the tag | ||
7 | 2013 | Mobile Phones And E-commerce Among Micro And Small Enterprises In The Informal Sector: An Empirical Investigation Of Entrepreneurship In Nairobi Click to View Abstract Lack of employment has pushed many people into self employment in the informal sector in Nairobi and Kenya at large. Micro and small enterprises (MSEs) are recognized by the government for their contribution to the GDP. Information and Communication Technologies (ICTs) are assisting the operators of MSEs in this sector to become more entrepreneurial. The ICT that is widely used in the sector is the mobile phone. Studies done on the usage of ICTs among MSEs have mostly concentrated on the roles of computers and internet usage, and given contradicting results on the benefits of using these technologies in e-commerce. Evidence on the role of mobile phones among MSEs in Kenya is lacking, especially, the evidence on factors facilitating and preventing their adoption, and the effects of the adoption on the performance of an MSE. This thesis analyzed the determinants of mobile phone possession, the extent of its usage in e-commerce, and the impact of mobile phone usage on the performance of an MSE. The hypotheses that were tested and strongly rejected were: a) e-readiness factors that is, characteristics of the owner, the attributes of the firm and the environment under which the firm operates, have no effect on the adoption of mobile phones and their usage in e-commerce; and b) the adoption of mobile phones and their use to transact business has no effect on the performance of an MSE. Data for the study was collected from the 8 divisions of Nairobi Province. Three models were estimated using these data, namely, the logit model, the probit model and the LPM (linear probability model). The main findings of the thesis are as follows: a) the majority of MSEs in Nairobi’s informal sector are poor although a few of them had sales running into millions of Kenya shillings; b) the sector is dominated by literate people, the majority of whom were male operators; c) many of the operators had mobile phones, and they used them for business transactions; d) each MSE paid a daily fee of 20 Kenya shillings to the City Council officers; e) the key readiness factor influencing the possession of the phone is electricity; f) education has a strong influence on the usage of the phone for e-commerce; and g) mobile phone possession and usage for e-commerce are highly associated with sales turnover and with employment creation within the informal sector. It is recommended that MSEs be categorized by the value of items sold and not the number of employees. A clear distinction should be made between MSEs in the informal sector and those in the formal sector. Further, a conducive, operating environment which accommodates electricity needs to be provided. Computer training and innovations associated with the usage of mobile phones should be encouraged and facilitated among MSEs to enhance their performance. Research on business start-ups and innovations due to mobile phone usage should be carried out. Finally, research on specific transactions of mobile phone usage in e-commerce needs to be conducted. | ||
8 | 2013 | An Investigation Into The Entrepreneurial Behaviours And Human Capital Formation Among Small-scale Farmers In Kenya Click to View Abstract Kenya is an agrarian economy and most people derive their livelihoods from smallholder agriculture but there is no consensus among policy makers and scholars on the viability of small scale farming in the country. There is a tendency for small farmers to ebeen made to identify entrepreneurial activities that result into human capital formation. This study addresses this problem by identifying the entrepreneurial | ||
9 | 2013 | Determinants Of Commercial Mixed Farming On Small Farms In Kenya Click to View Abstract Agriculture is a topic of concern for rural development programs in Kenya because of the high poverty incidents among farmers. Fundamentally, smallholder agriculture contributes substantially to total agricultural production and total employment. Despite the fact that Kenyan farmers largely practice mixed farming, some are unable to act commercially and consequently, unable to improve their livelihoods. This paper therefore aims at establishing the entrepreneurial indicators of farming activities that lead to improved rural livelihoods. Cross-sectional survey of 388 small farms in Thika was carried out to investigate the determinants of commercial mixed farming. Linear probability model, logit and probit models were used to estimate the determinants of commercial mixed farming. The results show that the size of the farm, gender of the farmer, availability of electricity supply and running water on the farm are the main determinants of mixed farming. This study suggests that policies be put in place to discourage partitioning of farm land into uneconomical sizes. It also recommend that rural electrification and training programs on best farming practices be intensified in the rural areas to enable farmers to act commercially. | ||
10 | 2013 | Determinants Of Mobile Phone Usage For E-Commerce Among Micro And Small Enterprises In The Informal Sector Of Kenya Click to View Abstract Studies done on the usage of Information and Commutation Technologies (ICTs) for e-commerce in the informal sector have mostly concentrated on the roles of computers and internet usage, and give contradicting results on the determinants and benefits of using these technologies. Evidence on factors leading to the mobile phones usage for business among Micro and Small Enterprises (MSEs) in Kenya is lacking. This paper investigates determinants of mobile phone usage among informal MSEs in Kenya. Primary data was collected from a survey of 384 MSEs in Nairobi County. Linear probability model, logit and probit models were used to estimate the determinants of mobile phone usage in e-commerce. The results of the study show that education level is the prime determinant of mobile phone usage for e-commerce. Number of employees and gender of MSEs also have a significant effect on the mobile phone usage for e-commerce. The study recommends the training of MSEs in the mobile phones applications for business and the government should create an enabling environment for MSEs to use mobile phone for e-commerce. | ||
11 | 2013 | Mobile Phones And Employment Among Informal And Small Enterprises In Nairobi Click to View Abstract
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12 | 2010 | Mobile Phones And E-commerce Among Micro And Small Enterprises In The Informal Sector: Click to View Abstract n/a | ||
13 | 2010 | Mobile Phones And Employment, Click to View Abstract n/a | ||
14 | 2010 | E-commerce: A Review Of Indicators And Theories Click to View Abstract n/a | ||
15 | 2008 | Data Warehousing And Business Intelligence Click to View Abstract Computers were first developed to process business transactions; the trend has been to have computers also support management in decision making. This led to the evolution of Management Information Systems (MIS). The concept of MIS can be traced from four major areas, namely, managerial accounting, management science or operations research, management theory and computer science. MIS is supported by a comprehensive set of data for business operations referred to as a database. There are several databases in any given organization. Organizations have realized that valuable information is hidden in separate databases which might sometimes contain overlapping and contradictory information, and are coming up with data warehouses. A data warehouse provides a platform for advanced, complex and efficient data analysis using On-Line Analytical Processing (OLAP) for data mining or Knowledge Data Discovery (KDD) to extract previously unknown strategic business information or business intelligence (BI). There are a lot of similarities between data warehousing and operations research (OR), they both require analytical processing to support executive decision making, yet OR, MIS and IT exist as separate communities, right from the education level to the organizations. There are many challenges facing data warehousing, with organizations viewing it as a purely IT project. The objective of the paper was to establish how some of the challenges of data warehousing could be addressed so as to reduce the failure rate of BI projects. It was concluded that data warehousing would be more successful if its development was a joint effort of both the OR & MIS community and the IT community. It is recommended that OR and MIS be taught as one discipline whose graduates will work very closely with IT specialists. | ||
16 | 2003 | Edited The Report On The Proceedings Of The Workshop On"Faculty Of Commerce" University Of Nairobi Click to View Abstract Computers were first developed to process business transactions; the trend has been to have computers also support management in decision making. This led to the evolution of Management Information Systems (MIS). The concept of MIS can be traced from four major areas, namely, managerial accounting, management science or operations research, management theory and computer science. MIS is supported by a comprehensive set of data for business operations referred to as a database. There are several databases in any given organization. Organizations have realized that valuable information is hidden in separate databases which might sometimes contain overlapping and contradictory information, and are coming up with data warehouses. A data warehouse provides a platform for advanced, complex and efficient data analysis using On-Line Analytical Processing (OLAP) for data mining or Knowledge Data Discovery (KDD) to extract previously unknown strategic business information or business intelligence (BI). There are a lot of similarities between data warehousing and operations research (OR), they both require analytical processing to support executive decision making, yet OR, MIS and IT exist as separate communities, right from the education level to the organizations. There are many challenges facing data warehousing, with organizations viewing it as a purely IT project. The objective of the paper was to establish how some of the challenges of data warehousing could be addressed so as to reduce the failure rate of BI projects. It was concluded that data warehousing would be more successful if its development was a joint effort of both the OR & MIS community and the IT community. It is recommended that OR and MIS be taught as one discipline whose graduates will work very closely with IT specialists. | ||
17 | 2000 | Computerization Of SACCOS For The Ministry Of Co-operatives Click to View Abstract Computers were first developed to process business transactions; the trend has been to have computers also support management in decision making. This led to the evolution of Management Information Systems (MIS). The concept of MIS can be traced from four major areas, namely, managerial accounting, management science or operations research, management theory and computer science. MIS is supported by a comprehensive set of data for business operations referred to as a database. There are several databases in any given organization. Organizations have realized that valuable information is hidden in separate databases which might sometimes contain overlapping and contradictory information, and are coming up with data warehouses. A data warehouse provides a platform for advanced, complex and efficient data analysis using On-Line Analytical Processing (OLAP) for data mining or Knowledge Data Discovery (KDD) to extract previously unknown strategic business information or business intelligence (BI). There are a lot of similarities between data warehousing and operations research (OR), they both require analytical processing to support executive decision making, yet OR, MIS and IT exist as separate communities, right from the education level to the organizations. There are many challenges facing data warehousing, with organizations viewing it as a purely IT project. The objective of the paper was to establish how some of the challenges of data warehousing could be addressed so as to reduce the failure rate of BI projects. It was concluded that data warehousing would be more successful if its development was a joint effort of both the OR & MIS community and the IT community. It is recommended that OR and MIS be taught as one discipline whose graduates will work very closely with IT specialists. | ||
18 | 1998 | Integrated Management Information Systems, Project Planning, Management And Evaluation For Intergovernmental Informatics Program For Kenya Click to View Abstract Computers were first developed to process business transactions; the trend has been to have computers also support management in decision making. This led to the evolution of Management Information Systems (MIS). The concept of MIS can be traced from four major areas, namely, managerial accounting, management science or operations research, management theory and computer science. MIS is supported by a comprehensive set of data for business operations referred to as a database. There are several databases in any given organization. Organizations have realized that valuable information is hidden in separate databases which might sometimes contain overlapping and contradictory information, and are coming up with data warehouses. A data warehouse provides a platform for advanced, complex and efficient data analysis using On-Line Analytical Processing (OLAP) for data mining or Knowledge Data Discovery (KDD) to extract previously unknown strategic business information or business intelligence (BI). There are a lot of similarities between data warehousing and operations research (OR), they both require analytical processing to support executive decision making, yet OR, MIS and IT exist as separate communities, right from the education level to the organizations. There are many challenges facing data warehousing, with organizations viewing it as a purely IT project. The objective of the paper was to establish how some of the challenges of data warehousing could be addressed so as to reduce the failure rate of BI projects. It was concluded that data warehousing would be more successful if its development was a joint effort of both the OR & MIS community and the IT community. It is recommended that OR and MIS be taught as one discipline whose graduates will work very closely with IT specialists. | ||
19 | 1996 | "Data Processing And Computers - Introduction To Business: A Kenyan Perspective" Edited By Prof. F.N. Kibera. Click to View Abstract Computers were first developed to process business transactions; the trend has been to have computers also support management in decision making. This led to the evolution of Management Information Systems (MIS). The concept of MIS can be traced from four major areas, namely, managerial accounting, management science or operations research, management theory and computer science. MIS is supported by a comprehensive set of data for business operations referred to as a database. There are several databases in any given organization. Organizations have realized that valuable information is hidden in separate databases which might sometimes contain overlapping and contradictory information, and are coming up with data warehouses. A data warehouse provides a platform for advanced, complex and efficient data analysis using On-Line Analytical Processing (OLAP) for data mining or Knowledge Data Discovery (KDD) to extract previously unknown strategic business information or business intelligence (BI). There are a lot of similarities between data warehousing and operations research (OR), they both require analytical processing to support executive decision making, yet OR, MIS and IT exist as separate communities, right from the education level to the organizations. There are many challenges facing data warehousing, with organizations viewing it as a purely IT project. The objective of the paper was to establish how some of the challenges of data warehousing could be addressed so as to reduce the failure rate of BI projects. It was concluded that data warehousing would be more successful if its development was a joint effort of both the OR & MIS community and the IT community. It is recommended that OR and MIS be taught as one discipline whose graduates will work very closely with IT specialists. | ||
20 | 1990 | Computer Vendors And Users Expectations As A Contributing Towards Curriculum Development For Training Managers And Supervisors In Kenya. This Was An Initiative Of The Kenya Government Click to View Abstract Computers were first developed to process business transactions; the trend has been to have computers also support management in decision making. This led to the evolution of Management Information Systems (MIS). The concept of MIS can be traced from four major areas, namely, managerial accounting, management science or operations research, management theory and computer science. MIS is supported by a comprehensive set of data for business operations referred to as a database. There are several databases in any given organization. Organizations have realized that valuable information is hidden in separate databases which might sometimes contain overlapping and contradictory information, and are coming up with data warehouses. A data warehouse provides a platform for advanced, complex and efficient data analysis using On-Line Analytical Processing (OLAP) for data mining or Knowledge Data Discovery (KDD) to extract previously unknown strategic business information or business intelligence (BI). There are a lot of similarities between data warehousing and operations research (OR), they both require analytical processing to support executive decision making, yet OR, MIS and IT exist as separate communities, right from the education level to the organizations. There are many challenges facing data warehousing, with organizations viewing it as a purely IT project. The objective of the paper was to establish how some of the challenges of data warehousing could be addressed so as to reduce the failure rate of BI projects. It was concluded that data warehousing would be more successful if its development was a joint effort of both the OR & MIS community and the IT community. It is recommended that OR and MIS be taught as one discipline whose graduates will work very closely with IT specialists. | ||
21 | 1988 | "Recurrent Cost Of Public Investment And Rationalisation In Kenya", Click to View Abstract Computers were first developed to process business transactions; the trend has been to have computers also support management in decision making. This led to the evolution of Management Information Systems (MIS). The concept of MIS can be traced from four major areas, namely, managerial accounting, management science or operations research, management theory and computer science. MIS is supported by a comprehensive set of data for business operations referred to as a database. There are several databases in any given organization. Organizations have realized that valuable information is hidden in separate databases which might sometimes contain overlapping and contradictory information, and are coming up with data warehouses. A data warehouse provides a platform for advanced, complex and efficient data analysis using On-Line Analytical Processing (OLAP) for data mining or Knowledge Data Discovery (KDD) to extract previously unknown strategic business information or business intelligence (BI). There are a lot of similarities between data warehousing and operations research (OR), they both require analytical processing to support executive decision making, yet OR, MIS and IT exist as separate communities, right from the education level to the organizations. There are many challenges facing data warehousing, with organizations viewing it as a purely IT project. The objective of the paper was to establish how some of the challenges of data warehousing could be addressed so as to reduce the failure rate of BI projects. It was concluded that data warehousing would be more successful if its development was a joint effort of both the OR & MIS community and the IT community. It is recommended that OR and MIS be taught as one discipline whose graduates will work very closely with IT specialists. | ||
22 | 1988 | Strategies For Improving Performance Of The Co-operative Movement In Kenya: Report Of Proceedings Of A Follow-up Workshop On The The Role Of Co- Click to View Abstract
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23 | 1986 | Edited The Report On The Proceedings Of A Follow-up Workshop On The"Role Of Co-operatives In Development Of Kenyan Economy", Click to View Abstract Computers were first developed to process business transactions; the trend has been to have computers also support management in decision making. This led to the evolution of Management Information Systems (MIS). The concept of MIS can be traced from four major areas, namely, managerial accounting, management science or operations research, management theory and computer science. MIS is supported by a comprehensive set of data for business operations referred to as a database. There are several databases in any given organization. Organizations have realized that valuable information is hidden in separate databases which might sometimes contain overlapping and contradictory information, and are coming up with data warehouses. A data warehouse provides a platform for advanced, complex and efficient data analysis using On-Line Analytical Processing (OLAP) for data mining or Knowledge Data Discovery (KDD) to extract previously unknown strategic business information or business intelligence (BI). There are a lot of similarities between data warehousing and operations research (OR), they both require analytical processing to support executive decision making, yet OR, MIS and IT exist as separate communities, right from the education level to the organizations. There are many challenges facing data warehousing, with organizations viewing it as a purely IT project. The objective of the paper was to establish how some of the challenges of data warehousing could be addressed so as to reduce the failure rate of BI projects. It was concluded that data warehousing would be more successful if its development was a joint effort of both the OR & MIS community and the IT community. It is recommended that OR and MIS be taught as one discipline whose graduates will work very closely with IT specialists. |