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Title: Networking and technological learning in small and medium scale manufacturing enterprises in Zimbabwe
Author: Chipika, Stephen
ISNI:       0000 0001 3544 9818
Awarding Body: Open University
Current Institution: Open University
Date of Award: 2004
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The overall aim of this thesis is to understand the relationship between technological learning and networking for small and medium enterprises (SMEs) engaged in manufacturing in Zimbabwe. This understanding is vital in order to facilitate a more purposeful mainstreaming of manufacturing SMEs into the national economy. The implications of the relationship between technological learning and networking are noted in the analyses, conclusions drawn and recommendations made for the strengthening of the development of manufacturing SMEs in the country. A combination of quantitative and qualitative methods are used to analyse largely primary data collected principally but not exclusively from Harare. The quantitative data are analysed by applying progressive statistical analysis which involves the use of scatterplot, linear correlation coefficient, Chi-square test and regression analysis. Case study analysis which focuses on four firms with varying characteristics is used to develop an in-depth understanding of the association between technological learning and networking. The research findings generally lend support to the hypothesis that 'small and medium scale light engineering firms that are strongly networked have a greater level of technological leaming than poorly networked firms'. However, there are also qualifiers to this broad hypothesis, of which two are paramount. Firstly, in order to learn from networks a firm must know how to learn. Secondly, while customer networks are consistently of high significance to firms, the same cannot be said of networks involving enterprise support organisations (ESOs). These qualifiers have important policy implications for the type of support that is offered to SMEs in Zimbabwe.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral