Loyalty transfer from offline to online stores in the UK grocery industry
Loyalty transfer from offline to online stores in the UK grocery industry
复制标题
英国杂货行业的忠诚度从线下商店转移到线上商店
DOI:
10.1108/09590550510600861
复制
发表时间:
2005
影响因子:
4.4
通讯作者:
H. Fulford
中科院分区:
文献类型:
--
作者:
M. Rafiq;H. Fulford
– Aims to examine the effectiveness of UK supermarkets in transferring store loyalty to online loyalty., – An online survey of university staff is used to test both the brand equity proposition that loyal customers are more likely to adopt brand extensions, and the double jeopardy model's prediction that market leaders benefit disproportionately from loyalty transference., – The study provides support for the brand equity and double jeopardy propositions. Tesco's and Sainsbury's dominance of both the online and offline markets, coupled with their retention indices of 92 per cent (Tesco) and 76 per cent (Sainsbury's), support the brand equity view. Tesco also attracts a disproportionately higher percentage of its customers from competitors (67 per cent) compared with Sainsbury's (14 per cent), suggesting that it is benefiting from its market leadership position, as predicted by the double jeopardy model., – The relatively small size and restricted nature of the sample means that the exploratory findings now need to be investigated more rigorously. A larger sample would permit a more detailed exploration of the relationships between the different aspects of online loyalty., – The research suggests that smaller retail brands have two main options, namely growing the size of the brand or building a niche brand. For a market leader the challenge is to become a “super‐loyalty brand”. That is, to achieve levels of loyalty higher than predicted by the double jeopardy effect, either through segmentation or through better service provision than that of competitors., – This is the first study to examine transferability of store loyalty to online loyalty and demonstrate the usefulness of the brand equity and double jeopardy models for understanding and predicting loyalty transfer behaviour.