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This paper aims to develop a critical approach to the conceptualization of start-ups in emerging markets from a Kenyan perspective. This study used a theoretical route to conceptualize start-ups in emerging markets like Kenya. From the findings, it is important to note that the conceptualization of start-up is based on western concepts and might be flawed and poorly applicable to businesses in Kenya. Hence in the Kenyan context, a start-up should be viewed as an innovative business entity, which is scalable and has survived up to 3-5 years. To support the growth of the start-up ecosystem in Kenya, policymakers should promote start-ups through the formation of relevant legislation and provide incentives that stimulate their survival and growth. The study has brought out some interesting findings which can generate more debate. The study used an exploratory research design which is not conclusive in nature therefore future research should consider using a research design that is conclusive in nature and robust.

Worldwide, startup businesses are essential for any country's economic development. Despite the rapid growth of start-ups, their likelihood of success and viability remain low. This trend is more observed in developing countries due to the low uptake of business incubation services such as Kenya. The aim of the current study was to determine the effect of networking services, physical incubation, and management mentoring on the growth of start-ups in Kenya. The study was based on the social network theory, the theory of the firm, the stochastic theory and the trait theory of entrepreneurship. A cross-sectional research design was used. A sample size of 227 respondents was selected from a total population of 567 respondents using proportionate stratified and simple random sampling techniques. Primary data was collected using a structured questionnaire. The data was analyzed with multiple linear regression with the help of SPSS. The finding of the study indicated that there was a positive and significant effect between networking services, physical incubation infrastructure and management mentoring and growth of startups. The study suggests that startups should join associations like the Associations of Startups and SME Enablers of Kenya and the Association of Countrywide Innovation Hubs to access incubation infrastructure. This will allow access to investor networks, civil society programs, and government agencies, accelerating business growth. Additionally, business incubators can partner with universities for specialized research in areas like health, agriculture, and climate change through the triple helix model.

Non-Governmental Organizations (NGOs) play a critical role in addressing social ills like poverty, employment, and food insecurity; therefore, their growth prospects enhance their ability to address these social ills. Discovery of entrepreneurial opportunities amongst the agro-based NGOs has not got the desired attention, and it is the least researched area in social entrepreneurship. This study investigated the relationship between Entrepreneurial Opportunity Discovery Dimensions and Growth of Non-Governmental Organizations in Kenya. It employed correlation design and was anchored on the Kirznerian Entrepreneurship Theory. The target population was 135 agro-based NGOs in Kenya. A mixed-method approach was used, combined qualitative and quantitative techniques. Statistical Package for Social Sciences (SPSS) version 21 and Analysis of Moment Structures (AMOS graphic-25) aided in the analysis. Structural Equation Modeling (SEM) using AMOS and Simple linear regression analysis were the primary analysis techniques used to evaluate the relationship between entrepreneurial opportunity discovery dimensions and the growth of NGOs. The results indicated that alertness0.372, p=0.033)and prior knowledge (0.163, p=0.031) have a significant favorable influence on growth, while social networks 0.047, p=0.713) showed an insignificant effect on the growth of NGOs. Investing in acquiring alert individuals and helping them gain relevant knowledge in the 21sttechnologies and emerging issues can lead to increased NGO ability to continue serving the community effectively and be engines of development for the general good of Kenya.

The study sought to assess the importance of classifying incubators based on the programs offered for optimum performance. Client selection criteria were assessed through three constructs namely: models that fit program goals, uniqueness of ideas, and standard selection tool. A mixed cross-sectional and causal design was adopted and a census was carried out targeting all the 51 incubators. Primary data was collected with an incubator program as a grouping/ cluster variable yielding a multilevel data structure with incubator centres nested in programs. Linear mixed effect models were fitted using Stata to assess the study objective taking into account the fixed effects for the incubator centre level (level-1) and random effects for the program level (level-2). The uniqueness of ideas was found to have a significant fixed effect on performance at level one while at level two, the study found significant random intercepts of incubator centre performance across the programs. Models that match program goals and standard selection tools were also found to have significant random slopes as level two random covariates in the model. Based on the findings of significant random slopes, the study concluded that incubator classification is key for client selection criteria and enhances incubator performance.

Worldwide, startup businesses are essential for any country's economic development. Despite the rapid growth of start-ups, their likelihood of success and viability remain low. This trend is more observed in developing countries due to the low uptake of business incubation services such as Kenya. The aim of the current study was to determine the effect of networking services, physical incubation, and management mentoring on the growth of start-ups in Kenya. The study was based on the social network theory, the theory of the firm, the stochastic theory and the trait theory of entrepreneurship. A cross-sectional research design was used. A sample size of 227 respondents was selected from a total population of 567 respondents using proportionate stratified and simple random sampling techniques. Primary data was collected using a structured questionnaire. The data was analyzed with multiple linear regression with the help of SPSS. The finding of the study indicated that there was a positive and significant effect between networking services, physical incubation infrastructure and management mentoring and growth of startups. The study suggests that startups should join associations like the Associations of Startups and SME Enablers of Kenya and the Association of Countrywide Innovation Hubs to access incubation infrastructure. This will allow access to investor networks, civil society programs, and government agencies, accelerating business growth. Additionally, business incubators can partner with universities for specialized research in areas like health, agriculture, and climate change through the triple helix model.

This paper aims to develop a critical approach to the conceptualization of start-ups in emerging markets from a Kenyan perspective. This study used a theoretical route to conceptualize start-ups in emerging markets like Kenya. From the findings, it is important to note that the conceptualization of start-up is based on western concepts and might be flawed and poorly applicable to businesses in Kenya. Hence in the Kenyan context, a start-up should be viewed as an innovative business entity, which is scalable and has survived up to 3-5 years. To support the growth of the start-up ecosystem in Kenya, policymakers should promote start-ups through the formation of relevant legislation and provide incentives that stimulate their survival and growth. The study has brought out some interesting findings which can generate more debate. The study used an exploratory research design which is not conclusive in nature therefore future research should consider using a research design that is conclusive in nature and robust.

The study sought to assess the importance of classifying incubators based on the programs offered for optimum performance. Client selection criteria were assessed through three constructs namely: models that fit program goals, uniqueness of ideas, and standard selection tool. A mixed cross-sectional and causal design was adopted and a census was carried out targeting all the 51 incubators. Primary data was collected with an incubator program as a grouping/ cluster variable yielding a multilevel data structure with incubator centres nested in programs. Linear mixed effect models were fitted using Stata to assess the study objective taking into account the fixed effects for the incubator centre level (level-1) and random effects for the program level (level-2). The uniqueness of ideas was found to have a significant fixed effect on performance at level one while at level two, the study found significant random intercepts of incubator centre performance across the programs. Models that match program goals and standard selection tools were also found to have significant random slopes as level two random covariates in the model. Based on the findings of significant random slopes, the study concluded that incubator classification is key for client selection criteria and enhances incubator performance.

Non-Governmental Organizations (NGOs) play a critical role in addressing social ills like poverty, employment, and food insecurity; therefore, their growth prospects enhance their ability to address these social ills. Discovery of entrepreneurial opportunities amongst the agro-based NGOs has not got the desired attention, and it is the least researched area in social entrepreneurship. This study investigated the relationship between Entrepreneurial Opportunity Discovery Dimensions and Growth of Non-Governmental Organizations in Kenya. It employed correlation design and was anchored on the Kirznerian Entrepreneurship Theory. The target population was 135 agro-based NGOs in Kenya. A mixed-method approach was used, combined qualitative and quantitative techniques. Statistical Package for Social Sciences (SPSS) version 21 and Analysis of Moment Structures (AMOS graphic-25) aided in the analysis. Structural Equation Modeling (SEM) using AMOS and Simple linear regression analysis were the primary analysis techniques used to evaluate the relationship between entrepreneurial opportunity discovery dimensions and the growth of NGOs. The results indicated that alertness0.372, p=0.033)and prior knowledge (0.163, p=0.031) have a significant favorable influence on growth, while social networks 0.047, p=0.713) showed an insignificant effect on the growth of NGOs. Investing in acquiring alert individuals and helping them gain relevant knowledge in the 21sttechnologies and emerging issues can lead to increased NGO ability to continue serving the community effectively and be engines of development for the general good of Kenya.