University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Consumer purchase intention of online mass customised female apparel : an explorative study of the influence of perceived risk and trust antecedents.

Kawala-Bulas, Sibilla (2016) Consumer purchase intention of online mass customised female apparel : an explorative study of the influence of perceived risk and trust antecedents. Doctoral thesis, University of Surrey.

Sibilla-kawala-thesis-final-30.06.pdf - Version of Record
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (3MB) | Preview


Several past studies have proven the market potential for mass customisation (MC) in various fashion sectors such as apparel, and revealed that ten to twenty percent of the market population claims to be interested in MC goods. Mass Customisation is a business strategy that embraces two opposing business practices, namely mass production and customisation. Several authors explain that although mass customisation might not turn into the dominant system, the numbers prove that these are promising market segments which are still not being served and are bigger than niche markets. But if there is a market for online customised fashion products, “why is mass customisation not there yet?” (Piller, 2004, p.314). Why are just a handful of MC companies operating in a mass market, while others are still testing this concept and operating in niche markets? To answer this question, the present study aims to explore the consumers’ side and to reveal what are the factors that prevent them from buying MC apparel online. For this purpose, the theory of perceived risk and trust has been applied. Further, price premium, the absence of a money-back guarantee, the co-design process (ability and time) and the longer delivery time were identified as important risk antecedents. Additionally, perceived reputation and perceived size were revealed as antecedents of perceived trust. Based on an exhaustive literature review, nine research hypotheses were developed. In order to answer them, LIMBERRY, an online shop for mass customised female apparel, was used as a real life case. An online survey was developed and, in order to test the survey, two pilot studies were conducted and amended in advance. Within 24 days, 236 completed and valid questionnaires were obtained from female LIMBERRY visitors. The data from the online survey was analysed and, in order to identify possible problematic items, the following four analyses were undertaken: (1) a reliability analysis for internal consistency, (2) an exploratory factor analysis, (3) the initial measurement model and (4) a confirmatory factor analysis. Next, a structural equation modelling was calculated without the identified problematic items. Since the model was misspecified, a modified model was developed using a step-wise procedure calculating modification indices. Further, three paths and three covariances were added to the model to enhance the fit statistics. Based on this modified model, the hypotheses were tested. Thus, five hypotheses found support, two could not be tested since the factors were excluded from analysis, one hypothesis was rejected and one possessed a zero effect. The results of this research suggest that perceived risk and trust are significant determinants of the online purchase intention of MC customers. Thus, marketing practitioners should apply activities to foster the customer’s trust and to reduce his risk perception.

Item Type: Thesis (Doctoral)
Subjects : mass customisation, e-commerce, consumer perspective, perceived risk, perceived trust, intention to purchase
Divisions : Theses
Authors :
Date : 31 August 2016
Funders : Kawala Handels GmbH
Contributors :
Depositing User : Sibilla Kawala-Bulas
Date Deposited : 06 Sep 2016 07:41
Last Modified : 31 Oct 2017 18:33

Actions (login required)

View Item View Item


Downloads per month over past year

Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800