Department of Management Science

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Micro and Small Enterprises (MSEs) are contributing a lot to the Kenyan national
development in general and human development in particular. However, it was observed
that many of the women MSEs in the informal sector of Kisumu city are performing
poorly. Nevertheless, limited use of strategic management practices has been cited as one
of the main causes of poor business performance. This study therefore investigated the
best strategic management practices of women MSEs and their effect on human
development. Best strategic management practices investigated were: closing time, locus
of planning, planning horizon, change in government regulations, and possession of a
business plan, stock, change in technology, creditors, sales, debtors, competitors, profits
and opening time. A cross sectional survey design was used and systematic random
sampling employed to collect data from the women MSEs in Kisumu city. Descriptive
statistics, correlation analysis and linear probability model were used to analyze the
collected data. The results revealed that most of the women in Kisumu city are literate
and have at least attained primary level of education. The study established that strategic
management practices of women MSEs have a significant effect on human development.
However, few women MSEs apply best strategic management practices. The study also
shows that the women who keep records of their business transactions and involve their
employees in their business planning process have high chances of improving their
livelihoods by buying land, building permanent houses, getting business premises, and
joining Savings and Credit Co-operative Societies (SACCOs). The study recommends
that the Kisumu County government, church leaders, civil society groups and NonGovernmental
Organizations should organize workshops and seminars to sensitize
women entrepreneurs on the best strategic management practices. Microfinance
institutions should be prevailed over to give loans at reasonable interest rates to
prospective women entrepreneurs.

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Kenya is ranked among the top ten largest economies in Africa and bearing the tag
of middle income. This tag should motivate the country to have food security but
this does not seem to be the case as many small farmers, who are the backbone of
the economy, are not adding value to their agricultural produce. Adding value is an
entrepreneurial process that creates wealth for both the farmers and the country.
This study investigated the factors that influence value addition on small farms in
Kenya. The study employed a cross-sectional survey design and a multi-stage
sampling technique where 15 locations from Kiambu and Murang’a counties were
identified. 388 farms were selected by line transect technique for this study.
Descriptive statistics was used to estimate the extent of value addition in agribusinesses
on small farms. Linear Probability Model (LPM), Logit, and Probit
models were used to estimate the determinants of value addition on the small farms.
The study reveals that kenya’s agrarian economy is suffering from limited value
addition as the statistics show that 6% of small farmers add value to their
agricultural produce. It was discovered that farm sizes are negatively correlated with
value addition. The distance to the market and accessibility to loan facilities were
found to be the major determinants of value addition in Kenya. The study
recommended that the government should create rural markets for the farmers and
facilitate financial institutions to lend money to small farmers at reasonable interest
rates. Small and Micro Enterprises should be encouraged to play an active role of
value addition in the agri-businesses of the Kenyan middle-income economy.

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.

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
behaviour that lead to human capital collected from a survey of a sample size of 388 small farmers, drawn from Thika region of Kenya. Quantitative description was used to measure the extent of entrepreneurial behaviour while logit model was used to e
entrepreneurial behaviour on the human capital formation. The results show that
the entrepreneurial behaviour of blending agricultural and non
businesses have a significant effect on the small farmers’ ability to pay med
bills. However, commercial mixed farming and value addition in agriculture were
found to be more of survival strategies as they do not result in human capital
formation. Furthermore, availability of business opportunities and favourable government policies, has a positive influence on the human capital formation. The research recommends the government to come up with policies that can create a favourable environment for farmers to establish non agricultural businesses.

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.
Key words: Commercial Mixed Farming, Farm Characteristics, Entrepreneurship, Logit and Probit models

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.
Key words: Mobile phone usage, e-commerce, informal sector, MSEs, and Education

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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.

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.

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.

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.

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.

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.

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.

No 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.