Motivation factors for online buying: the price driver
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Price is often argued to be the determining factor for online (eBusiness) purchasing. The idea that buying online provides both asking and hidden cost savings is an assumption that has been promoted by IT advocates of the commercial opportunity. In this research Price (attribute) is to be investigated as a contributor to customer motivations for online purchasing. The investigation is to begin with a literature search for other factors that are claimed to influence online purchasing and studies others have published in the focus area. Previously research has been carried out by others to understand the changes brought by internet and ecommerce to our lives and business opportunities. It has been found that behavioural characteristics like shopping convenience, information seeking, immediate possession, social interaction, and variety affects the consumer behaviour towards shopping on the internet (Rohm, 2004). There are other factors such as privacy and security affecting consumer attitude towards shopping online (Shergill, 2005). In this research the factors identified from the literature are listed in priority order and the top two used to explain the relationship to price. This approach is taken to limit the cost (financial and time) of the survey and yet to still contribute valuable knowledge regarding price and other factors affecting online purchasing behaviour. The ability to collect price information and make comparisons between the different product and offerings from various providers is argued to be defining for competitive advantage in ecommerce (Jiang, 2002). The research is started by asserting an initial model that suggests price is a moderating factor for other factors when customers purchase online. This model is a “straw man” to be tested. The resource limitations of this short study are managed by selecting only two of the possible constructs affecting online buying motivations. The research is operationalised by submitting banks of potential questions to experts, a pilot study, and reliability testing and then surveying a stratified random sample of online purchasers. Structural equation modelling method is chosen for data analysis and the appropriate approach for confirming (or otherwise) a mediation role for price in online customer purchasing. A metric and a path model were constructed from the empirical data and compared with the initial model. It was found that Price was the dominant motivating factor for those in the sample for transacting online. The initial model was not the best fit for the empirical data and other relationships were explored. Best fit was found by removing the hypothesised relationship from trust to price and establishing the relationship between trust and security. The best fit model hence showed that Price and intention to buy was a very strong relationship.