The focus of this study is to examine the factors that lead to growth in small firms in a Least Developed Country (LDC). The research is based on the manufacturing sector in Ghana. The main objectives of the research are to identify the key variables that lead to small firms' growth and to ascertain the critical barriers that impede growth. A research model which is developed out of an initial exploratory research and existing literature focuses on how the characteristics of the owner/manager, the characteristics of the firm and the business strategy variables interact to affect growth in employment. In addition factors that are perceived to have constrained the growth of the small firms during the study period are ascertained and discussed. To properly test the hypotheses developed a face to face interview survey involving 122 owner/managers of small manufacturing firms is conducted. This resulted in a range of variables that allowed for the construction of a comprehensive multivariate model of small firm growth. A resulting regression model provides about 68 percent of the explanation for the growth of the small firms sampled. It also indicates that the owner/manager characteristics variables offer the most powerful explanation to small firm growth. We find that the owner/manager's growth aspiration is the most influential factor in achieving growth. The other owner/manager characteristics variables that have positive influence on growth are level of education, prior industry experience and entrepreneurial family background. Owner/managers with local experience and/or with other business interests are less likely to achieve faster growth. Foreign owned/managed firms grow faster. Younger and smaller firms appear to grow faster. While firms with multiple ownerships tend to grow at a slower rate than firms owned and managed by one person. Business planning, marketing and export have positive and significant impacts on growth. Other business strategies such as innovations and staff training also have direct relationships with growth but not significant. Some of the main constraining factors to growth are cost of borrowing, lack of access to credit, high cost of inputs, lack of trust within the business community, high bureaucracy, late payments and lack of efficient support system. While the external environment plays important role in small firm growth and development, the behaviours, response and strategies pursued by individual owner/manager are significant factors that determine the rate at which a firm will grow.

The focus of this study is to examine the factors that lead to growth in small firms in a Least Developed Country (LDC). The research is based on the manufacturing sector in Ghana. The main objectives of the research are to identify the key variables that lead to small firms' growth and to ascertain the critical barriers that impede growth. A research model which is developed out of an initial exploratory research and existing literature focuses on how the characteristics of the owner/manager, the characteristics of the firm and the business strategy variables interact to affect growth in employment. In addition factors that are perceived to have constrained the growth of the small firms during the study period are ascertained and discussed. To properly test the hypotheses developed a face to face interview survey involving 122 owner/managers of small manufacturing firms is conducted. This resulted in a range of variables that allowed for the construction of a comprehensive multivariate model of small firm growth. A resulting regression model provides about 68 percent of the explanation for the growth of the small firms sampled. It also indicates that the owner/manager characteristics variables offer the most powerful explanation to small firm growth. We find that the owner/manager's growth aspiration is the most influential factor in achieving growth. The other owner/manager characteristics variables that have positive influence on growth are level of education, prior industry experience and entrepreneurial family background. Owner/managers with local experience and/or with other business interests are less likely to achieve faster growth. Foreign owned/managed firms grow faster. Younger and smaller firms appear to grow faster. While firms with multiple ownerships tend to grow at a slower rate than firms owned and managed by one person. Business planning, marketing and export have positive and significant impacts on growth. Other business strategies such as innovations and staff training also have direct relationships with growth but not significant. Some of the main constraining factors to growth are cost of borrowing, lack of access to credit, high cost of inputs, lack of trust within the business community, high bureaucracy, late payments and lack of efficient support system. While the external environment plays important role in small firm growth and development, the behaviours, response and strategies pursued by individual owner/manager are significant factors that determine the rate at which a firm will grow. / Ghana Leasing Company Limited.

Nesse trabalho foi abordada a situação em que observações de produtividade da cana-de-açúcar (TCH) foram tomadas na mesma unidade experimental em diferentes condições de avalições (anos). Foram avaliados os perfis médios de resposta de 48 genótipos de cana-de-açúcar em dois experimentos: Experimento 1 e Experimento 2, durante três e cinco anos respectivamente, ambos com o delineamento de blocos ao acaso. Esse tipo de planejamento produz uma forma de relação entre as observações tomadas na mesma unidade experimental, portanto requer outras suposições, além das usuais, para que análise seja correta e os testes produzam resultados válidos. Para que as inferências sobre as médias de produtividade sejam válidas e seguras é necessário que o modelo da matriz de covariância dos dados seja apropriado. Diante disso, foram avalidos três alterantivas de análise para dados longitudinais (medidas repetidas no tempo ), sendo utilizados portanto, o modelo univariado, conforme o planejamento do tipo \"split-plot on time\", que impõe forte restrição quanto a matriz de variâncias-covariâncias; o modelo multivariado, que utiliza uma matriz de variâncias-covariâncias não-estruturada e o modelo mistos, que possibilita a seleção de uma matriz que melhor representa os dados. Contudo, verificou-se que não houve diferença entre os resultados dos testes para as diferentes metodologias. Porém, é interessante a continuidade do estudo em relação ao modelo misto, pois devido a sua flexibilidade e precisão é possível obter estimativas mais seguras dos componentes de variância e predizer os valores genotípicos, que por fim poderá proporcionar a predição de produção de uma futura colheita para um determinado genótipo. / This work has been dealt with situation in which observations of productivity of sugar of cane (TCH) were taken in the same unit experimental in different condition of assessments (years). The response profiles average of 48 genotypes of sugar of cane were evaluated in two experiments: Experiment 1 and Experiment 2, for three and five years respectively, both with the randomized complete block design. This type of planning produces a form of relationship between the observations made in the same unit experimental therefore requires other assumptions, in addition to the usual, so that analysis is correct and the test results valid. To that inferences on the means of productivity are valid and safe it is necessary that the model of covariance matrix of the data is appropriate. Therefore, were evaluated three alternatives for analysis of longitudinal data (repeated measures over time), the univariate model as the planning of the split-plot on time which imposes strong restrictions on variances - covariances matrix, the multivariate model, which uses a non-structured variances - covariances matrix and mixed model, which they are enable the selection of a matrix that best represents the data. However, it was found that there was no difference between the results of tests for the different methodologies. But it is interesting the continuity of the study in relation to mixed model, because due to its flexibility and accuracy will be possible to obtain more reliable estimates of the variance components and predict the genotypic values, which ultimately could provide a prediction of production of a future harvest for a given genotype.

Nesse trabalho foi abordada a situação em que observações de produtividade da cana-de-açúcar (TCH) foram tomadas na mesma unidade experimental em diferentes condições de avalições (anos). Foram avaliados os perfis médios de resposta de 48 genótipos de cana-de-açúcar em dois experimentos: Experimento 1 e Experimento 2, durante três e cinco anos respectivamente, ambos com o delineamento de blocos ao acaso. Esse tipo de planejamento produz uma forma de relação entre as observações tomadas na mesma unidade experimental, portanto requer outras suposições, além das usuais, para que análise seja correta e os testes produzam resultados válidos. Para que as inferências sobre as médias de produtividade sejam válidas e seguras é necessário que o modelo da matriz de covariância dos dados seja apropriado. Diante disso, foram avalidos três alterantivas de análise para dados longitudinais (medidas repetidas no tempo ), sendo utilizados portanto, o modelo univariado, conforme o planejamento do tipo \"split-plot on time\", que impõe forte restrição quanto a matriz de variâncias-covariâncias; o modelo multivariado, que utiliza uma matriz de variâncias-covariâncias não-estruturada e o modelo mistos, que possibilita a seleção de uma matriz que melhor representa os dados. Contudo, verificou-se que não houve diferença entre os resultados dos testes para as diferentes metodologias. Porém, é interessante a continuidade do estudo em relação ao modelo misto, pois devido a sua flexibilidade e precisão é possível obter estimativas mais seguras dos componentes de variância e predizer os valores genotípicos, que por fim poderá proporcionar a predição de produção de uma futura colheita para um determinado genótipo. / This work has been dealt with situation in which observations of productivity of sugar of cane (TCH) were taken in the same unit experimental in different condition of assessments (years). The response profiles average of 48 genotypes of sugar of cane were evaluated in two experiments: Experiment 1 and Experiment 2, for three and five years respectively, both with the randomized complete block design. This type of planning produces a form of relationship between the observations made in the same unit experimental therefore requires other assumptions, in addition to the usual, so that analysis is correct and the test results valid. To that inferences on the means of productivity are valid and safe it is necessary that the model of covariance matrix of the data is appropriate. Therefore, were evaluated three alternatives for analysis of longitudinal data (repeated measures over time), the univariate model as the planning of the split-plot on time which imposes strong restrictions on variances - covariances matrix, the multivariate model, which uses a non-structured variances - covariances matrix and mixed model, which they are enable the selection of a matrix that best represents the data. However, it was found that there was no difference between the results of tests for the different methodologies. But it is interesting the continuity of the study in relation to mixed model, because due to its flexibility and accuracy will be possible to obtain more reliable estimates of the variance components and predict the genotypic values, which ultimately could provide a prediction of production of a future harvest for a given genotype.