Use this URL to cite or link to this record in EThOS:
Title: Exporting knitted apparel : a study of the determinants of exporting performance in the UK knitted apparel sector
Author: Murphy, Owen Patrick
ISNI:       0000 0004 2718 150X
Awarding Body: University of Bradford
Current Institution: University of Bradford
Date of Award: 2008
Availability of Full Text:
Access from EThOS:
Access from Institution:
As the globalisation process accelerates there is a growing need for individual countries to understand the bases for effective performance in international trade. Because it makes up such a large share of world trade, it is especially important to understand what determines effectiveness in exporting. Despite much empirical research, especially over recent decades, the state of knowledge on this topic remains fragmented, unclear and unsatisfactory. The motivation for the present study was therefore twofold: dissatisfaction with the present state of knowledge in this vital area and the importance to the UK economy of improving its export performance in a world of increasing competition. Its aim was to contribute to the resolution of both. In addition to finding what appeared to be quite serious methodological problems in a group of earlier studies, our review of the literature indicated that the best prospects for identifying the determinants of effective exporting were to be found, not at national or sectoral level but at that of the individual firm. Accordingly, an empirical survey research project was developed. To minimise unquantifiable inter-sectoral variability, it was focused on a single sector of industry. For a range of reasons, including the limited amount of information available about its current export activity and prospects, the UK knitted apparel industry was chosen. Special care having been taken to assemble the fullest possible sampling frame and to develop a suitable instrument (which included an export performance model), a mail survey in the form of a stratified random sample of exporting UK manufacturers of knitted apparel was carried through from late 2000. Persistent follow-up by mail and telephone generated a response rate of 70 per cent, comprising close to half of the sampling frame, that was representative of all company size bands, levels of exporting and products. The overall quality of the responses was good; tests of non-response did not find any indications of non-response bias. Data analysis, designed to test thoroughly our 10 export-determinants hypotheses, relied primarily on Pearsonian correlation at the bivariate level then sequentially on Multiple Regression Analysis, Canonical Correlation Analysis and Partial Least Squares. A perhaps slightly novel aspect of the research was that it was not solely cross-sectional in format; a longitudinal element was provided by drawing on the researcher's earlier surveys ; and a panel element by following-up, in 2007, the main 2000 field survey. Where possible, these data were drawn upon in the analysis and interpretation. There did not appear to be any conflict between the three multivariate techniques employed and indeed their findings were not dissimilar. The outcome of the data analysis was to uphold, to varying degrees, most of our hypotheses about the determinants of effective or successful exporting. Those that did not find support were three: firm size, product adaptation, and price determination method. Most strongly supported as determinants were promotional intensity, serving many markets and visits to trade fairs/exhibitions; others which were statistically significant, included management commitment, special staff skills and the use of Commission Agents. While the conclusions must remain a bit tentative they are encouraging.
Supervisor: Pickles, Tony. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Knitted apparel industry, UK ; United Kingdom ; Export performance model ; UK manufacturers ; Determinants of export ; Knitted garments exports ; Stratified random sample survey ; Data analysis