A growth predictive system for Chinese SMEs

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Abstract

In China, research into SME growth has become more important and has drawn considerable attention from both government and scholars. However, there is no universally accepted way to define and measure an SME's growth prospects, and traditional approaches have been criticized for encouraging short-termism, being backward-looking and inward-looking. Therefore, based on a comprehensive and systematic literature review on different aspects of SME growth, and the consensus achieved through using the Delphi technique among eleven experts including policy-makers, scholars and entrepreneurs, the growth predictive system was built in this paper using a holistic approach which incorporates multiple measures (financial and non-financial, backward looking and forward looking, external and internal elements) to allow users to gain a better understanding of Chinese SMEs' growth potential.

To validate the growth predictive system, the researcher collected data from 148 Chinese SMEs randomly selected, and did three tests for addressing three different questions: Whether the selected growth indicators can appropriately interpret each of the growth capabilities? Whether the calculated growth index (2012) of 148 Chinese SMEs has a positive correlation with the three years' actual profit growth rate (2012-2014)? Whether the growth rankings of local SMEs (Shenzhen) calculated by the predictive system has a good fit with the growth rankings provided by the local government? The answers to all these questions were "yes", so the growth predictive system developed in this paper has been validated.

By using the growth predictive system, the government could become more effective in their policy-making oriented towards SMEs; investors and financiers could make decisions logically rather than emotionally; and SMEs could more easily formulate business strategies in today's dynamic environment to give themselves sustainable competitive advantages over their counterparts.

Item Type: Thesis [via Doctoral College] (PhD)
Subjects: H Social Sciences > HF Commerce
Library of Congress Subject Headings (LCSH): Small business -- China, Small business -- Growth
Official Date: July 2015
Dates:
Date
Event
July 2015
Submitted
Institution: University of Warwick
Theses Department: Warwick Manufacturing Group
Thesis Type: PhD
Publication Status: Unpublished
Supervisor(s)/Advisor: Banerji, Suijit
Extent: 187 leaves : illustrations
Language: eng
URI: https://wrap.warwick.ac.uk/78809/

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