Empirical Evidence for a Relationship between Business Growth and the Use of Structured Marketing Information Amongst Food and Drink SME's

Cacciolatti, L. and Fearne, A. (2011) Empirical Evidence for a Relationship between Business Growth and the Use of Structured Marketing Information Amongst Food and Drink SME's. Working paper. University of Kent, Canterbury, Canterbury (Full text available)

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Abstract

SMEs present peculiar characteristics that make their marketing distinctive from larger companies. We suggest the lack of resources in SMEs is a barrier to effective marketing and therefore to business growth. SMEs marketing decision-making is affected by whether the SME manages to acquire, analyse and utilise formalised marketing information. This paper analyses the relationship between business growth potential and the use of marketing information in food and drink SMES. The analysis was conducted using multivariate data analysis techniques, specifically PCA and binary logistic regression, on a sample of approximately 300 food and drink SMEs. The logistic regression was significant for both a model (R2=0.18) using the predictors direct effect on growth probability and a model (R2=0.30) using interaction terms. The hypothesised relationships on business growth probability and the use of information have been tested and significant effects have been identified on the interaction amongst the predictors of growth (23% of correlations were significant). Use of formalised marketing information was found to play an important role in generating SME growth in food and drink SMEs. However, SME characteristics played an important role in the way information was used and this affected business growth. Better use of information by SMEs focused their marketing activities. Therefore owner-mangers should be trained to make the best use out of formalised marketing information.

Item Type: Monograph (Working paper)
Additional information: Working Paper No. 243
Uncontrolled keywords: entrepreneurial marketing, food and drink SMEs, marketing information, logistic regression, multivariate data analysis
Subjects: H Social Sciences
H Social Sciences > H Social Sciences (General)
Divisions: Faculties > Social Sciences > Kent Business School
Faculties > Social Sciences > Kent Business School > Marketing
Depositing User: Cathy Norman
Date Deposited: 23 Apr 2012 14:50
Last Modified: 24 Apr 2012 09:19
Resource URI: http://kar.kent.ac.uk/id/eprint/29315 (The current URI for this page, for reference purposes)
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