Experimental Interface Design, Procedure and Time

This research designs a hypothetical retailer’s website with two stimuli. The first stimulus was illustrated on 3D product visualisation sites that allowed participants to view the focal product, laptops, from different angles; they also can rotate the products and zoom in or out. The 3D stimulus is intended to help consumers to imagine the product in appropriate and relevant ways and thus enhance their virtual experiences (Li et al., 2001). The second stimulus was illustrated on static sites where participants could only see product images of laptops without being able to change or modify them. Choosing two stimuli in one retailer’s website came about to answer the research questions regarding the main influences of 3D product visualisations and 2D static pictures on consumers’ perceptions (i.e., hedonic and utilitarian values).

In designing interfaces for this thesis, the research makes sure to include almost all the types of product visualisation forms that a consumer may find in any electrical online retailer. Moreover, this study adds more features and cases to the ones that might be found in real sites. For example, none of the national sites that sell laptops (e.g., Sony and Dell) has a flash combining both 3D visualisation and information about laptops.

This study chooses the electrical industry to investigate the impact of 3D and 2D product visualisations on consumers’ virtual experience. Specifically, this study designs a fictitious website that sells one product, namely laptop computers. The choice of the laptop industry arises from the Image Marketing Retailer Group (IMRG, December, 2009) Capgemini e-Retail Sales Index, which shows that the number of U.K. online shoppers and online spending by U.K. consumers increase steadily. For example, in February 2008 online spending by U.K. consumers reached £4.2bn, which equates to £69 for every person in the U.K. and represents an increase of 46 per cent compared to February 2007. By December 2009 online spending has increased 11 per cent from 2008. Moreover, IMRG asserts that both electricals and clothing are the favourite purchases

108 among U.K. shoppers, with 38 per cent and 32 per cent share of revenues respectively. See Figure 5.2 for latest information.

http://www.silicon.com/retailandleisure/0,3800011842,39170154,00.htm

Figure 5.2 Year-on-year growth across UK online retail sectors

Source: Image credit, silicon.com. (2008/2009)

To eliminate individual differences, this thesis employed a within-subjects design for the first four stages. Each subject, therefore, represents his or her own control (Greene and d’Oliveira, 1999). This design increases the statistical power of the experiment, because it requires fewer subjects than for a between-subjects design. Moreover, it helps reduce error variance, which is associated with individual differences. Furthermore, this design helps reduce costs because it takes several observations from the same subject (Greenwald, 1976; Keppel and Wickens, 2004). However, Bordens and Abbott (2008) posit that carrying out an experimental design using a within-subjects design is not disadvantage free. The

109 authors emphasise carryover effects as one of the most vital disadvantage. To deal with the carryover problem, this research follows a counterbalance order strategy to make sure that all the sample candidates have surfed and used all stimuli (i.e. static pictures and 3D product visualisations) randomly. To do this, for example, 50% of the sample surfs the static pictures and then surfs 3D product visualisations. On the other hand, the remaining 50% surfs 3D product visualisations first and then surfs the static pictures in the designed websites.

As an aside, this thesis notes that most previous research in this field has been carried out using either a between-subjects design or a mixed design (e.g., Fiore and Jin, 2003; Fiore et al., 2005a; Kim et al, 2007; Li et al., 2002; Suh and Chang, 2006). As a result, the previous research has ended up with two separate samples in which some participants used 3D product visualisations and others used static pictures. Many authors, such as Grice (1966) and Bordens and Abbott (2008), assert the possibilities of having different functional relationships when using between-subjects designs. The authors posit that researcher’s ability to compare results when employing a within-subjects design is greater than when employing a between-subjects design.

The designed websites (in all the stages) were not previously known to the users, nor did users have any knowledge of the fictitious brands on the sites. Thus, this thesis eliminated any impact of previous experiences or attitudes (Fiore et al., 2005a). The designed sites offer a wide variety of laptops, similar to those that many college-aged women and men currently buy and use. Therefore, the created sites provide a suitable context for the present sample.

This thesis follows Zajonc’s (2001) recommendation regarding the time limit to a stimulus. Zajonc (2001) asserts that time exposure influences users’ end responses. Moreover, some authors (e.g., Fiore and Jin, 2003; Fiore et al., 2005a; Kim et al., 2007) have followed Zajonc’s (2001) study in determining the appropriate time exposure to an online stimulus (i.e., 3D) and they reported the importance of time exposure to any experiment that used 3D product visualisation. The current research follows the previous studies (e.g., Fiore and

110 Jim, 2003; Kim et al., 2007) in determining the limit exposure for each stimulus up to five minutes. After surfing, the stimuli subjects completed a questionnaire.

To test the hypotheses, this study designed five separate stages. In the first stage, this research tested H1 by asking participants questions about the authenticity and telepresence of the simulation of the laptops. The second stage tested the hypotheses (H2 and H3) and demonstrated the difference between the indirect experience (i.e., using 2D static pictures) and the virtual experience (3D product visualisations) in providing more information and fun to consumers. Stage three tested H4 and used a two-way repeated measures ANOVA to determine the effects of the progressive levels of the antecedents (control and animated colours) on 3D authenticity. The fourth stage tested H5 and used a two-way repeated measures ANOVA to determine the effects of the progressive levels of 3D authenticity consequences (hedonic and utilitarian value) on the dependent variable (i.e., behavioural intention). Finally, in the fifth stage, this research developed a conceptual framework, based on the online S-O-R framework, and tested the relationships in the proposed model using the high levels of 3D authenticity antecedents, consequences, and behavioural intention. The impact of control and animated colours on 3D authenticity; and the impact of 3D authenticity, hedonic and utilitarian values on behavioural intention were tested.

5.6.2 Stage 1: 3D Authenticity Vs 3D Telepresence