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Female consumers' preferences for shopping via CD/ROM, television or catalogue versus in a specialty store were investigated. Videotaped shopping simulations were viewed by 191 subjects who selected preferred options within each of six forced‐choice pairs. Specialty store was most and television least preferred. Catalogue was most preferred among non‐store options. Fashion Opinion Leadership, Clothing Interest Inventory and Shopping Orientation measures, and demographic and open‐ended questions were used to profile and explore preference behaviour. Analysis with Chi‐Square Automatic Interaction Detector (CHAID) profiled five consumer segments. Subjects had positive and negative perceptions of each venue and believed that shopping through electronic media will be dominant non‐store options in the future.

The overall purpose of this research was to explore the potential for applying mass customization in the apparel manufacturing and retail sectors by investigating consumers’ interests in it as a concept. A series of seven focus groups were used to explore consumer preferences related to mass customization and to identify potential barriers to adoption of the concept. Potential scenarios illustrated with video were used to describe how mass customization might be implemented. A deductive approach to data reduction allowed researchers to distill and describe data according to predetermined categories and to identify additional categories that emerged in the analysis. Converging positive consumer comments moved researchers forward in understanding the concept while negative comments were viewed as barriers. The result was the construction of a consumer‐based model which provides an initial framework for researchers and the business community to use in exploring how the paradigm of mass customization could be applied as a business strategy in the apparel industry.

Agent‐based modelling is a bottom‐up approach to understanding systems which provides a powerful tool for analysing complex, non‐linear markets. The method involves creating artificial agents designed to mimic the attributes and behaviours of their real‐world counterparts. The system’s macro‐observable properties emerge as a consequence of these attributes and behaviours and the interactions between them. The simulation output may be potentially used for explanatory, exploratory and predictive purposes. The aim of this paper is to introduce the reader to some of the basic concepts and methods behind agent‐based modelling and to present some recent business applications of these tools, including work in the telecoms and media markets.