Consumers' channel preferences: An integrated model
With the growing popularity of the internet as a channel of distribution many researchers are trying to determine factors that influence and hinder consumers' acceptance of this channel. Unfortunately, the explosion of articles studying internet patronage involve the same limitation as previous shopping motivation research. Namely, the internet is just one of many channels from which consumers' can choose to purchase products. Current articles on internet patronage, as well as the previous work on other channels, have failed to account for this fact. These studies examine patronage motives one channel at a time, while neglecting to account for how consumers choose between channels. As such, the main goal of this study was to develop an integrative consumer channel preference model which would allow for a comparison across channels to determine which factors are the most influential for each channel.
Participants for this study consisted of individuals 16 and older who had access to the internet. This sample was chosen to ensure that consumers have some type of access to the internet, which is essential for any on-line purchases. Two-thousand consumers were mailed a 6-page survey asking for their participation. Eight-hundred and one consumers returned the completed questionnaire (40% response rate), with 754 included in subsequent analyses due to a pre-qualification question.
The results showed that product class knowledge, familiarity/prior use with a purchasing channel, and immediate possession motives were the only predictors that influenced consumers' preferences for all three channels included in this study (i.e., bricks-and-mortar, catalogs, and internet). Other factors influencing channel preferences included risk aversion, merchandise uniqueness motives, loyalty to local merchants, catalog recreation motives, and the respondent's age. Despite the large number of constructs investigated in the current study only seven were consistently significant predictors of consumers' bricks-and-mortar preferences. Six consistently predicted catalog preferences, and only three predicted internet preferences. Additionally, these variables accounted for a small portion of the variance explained in consumers' channel preferences (ranging from 11% to 39%), with catalog models explaining the least variance. These results suggest that there are many other factors and motives that influence consumers' channel preferences than were captured in the current study.