The resource based view of firms suggests that they should invest into intangible assets such as absorptive capacity, R&D, networks, human capital and internationalisation. In particular, SMEs require more investment in knowledge based assets (e.g., R&D, networks) for higher labour productivity growth. The aim of this study is to identify and analyse the drivers of firm growth and their impact on firm labour productivity growth. Previous studies were limited in scope in terms of analysis (i.e., at firm level) of the software industry. For data collection, owner-managers of software firms were face-to-face interviewed using a structured questionnaire. The data were collected from two regions of Pakistan, Islamabad and Rawalpindi. Information was gathered on variables such as firm size, age, firm innovation activities, business and management factors, exporting, inward/outward FDI and so forth. Prior estimation factor analysis is used to extract core information from Likert scale variables. Lastly, stepwise multiple regression analysis is used to examine the relationship between drivers of firm growth and labour productivity growth. The regression analysis examined firm size, access to finance, internationalisation (exporting and outward FDI), business improvement methods and knowledge management have a positive impact on firm labour productivity growth. In comparison, R&D, absorptive capacity, shortage of skills generally have negative relationship to firm labour productivity growth. In summary, empirical findings emphasise the importance of knowledge based assets for higher firm labour productivity growth as a low level of R&D, lack of access to finance, poor absorptive capacity, high sunk costs (non recoverable) and skills shortage reduced the labour productivity growth of software firms.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:560053 |
| Date | January 2012 |
| Creators | Rehman, Naqeeb Ur |
| Publisher | University of Glasgow |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://theses.gla.ac.uk/3697/ |
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