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Title: Online retail : service quality derivation, market segmentation and organisational analysis
Author: Piercy, Niall C.
ISNI:       0000 0004 2748 4543
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2006
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Hie recent rise of the internet as a commercial trading channel has left retail marketers facing several challenges. As in any marketplace, customer intelligence is the lifeblood of organisational success online, yet no thoroughly tested and validated model exists to reliably capture customer service requirements. Traditional service quality models are an insufficient and inflexible means to capture the unique nature of the internet medium while those emergent models of online behaviour developed thus far have typically been of limited scope, sample size, sample breadth and not validated in continued practice. Beyond the problem of identifying customer demands, there remains a problem of how to group together customers for segmentation purposes. In the contemporary marketplace as a whole there is growing fragmentation and individuality with demographics no longer precise enough to be useful beyond describing broad definitions of product class users. E-businesses also face a pressing challenge in addressing customer alignment in the Value creating* marketing and operations departments. There is a need to move beyond the limiting scope of only corisklering marketing in relation to customer focus and to incorporate a wider consideration of organisational focus with true measures of customer requirements. Within this thesis each of these issues is addressed. With the support and collaboration of four internet companies, one of the largest surveys of online customers undertaken to date has been completed (n-3403). This has allowed for the construction of a new model of online customer service demands, validated with confirmatory factor analysis, generating a nine factor solution that comprehensively describes customers service demands. Secondly, a wide range of situational factors have been analysed for their suitability as a means of segmenting the marketplace. Structural equation modelling has provided a strong finding that finreripral measures account for far greater variance in customer demands than demographics, confirming the limited usefulness of demographics online and providing a superior replacement. An analysis of marketing and operations personnel in the four supporting companies also provided evidence that marketers were better at understanding customer requirements than their operations colleagues and that in all companies a generally good understanding of customers had resulted in high levels of customer satisfaction. Overall, this body of work stands apart in terms of holism of analysis (customer service quality, segmentation and organisational understanding), depth of analysis (extensive literature review and generation}, depth of research (sample size of n-3403) and rigour of analysis (iterative statistical process) making contributions to the academic body of knowledge and nature of managerial practice in the areas of online retail customer service, market segmentation and organisational analysis.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available