online shopping environmentsThe moderating role of consumer-generated information

The impact of product

information on preferences in

online shopping environments

The moderating role of consumer-generated information

Motivation to study

▪ Importance of online product information

▪ Increasing interest in literature for CGI

▪ Prior research focusses on main effects

▪ Gain a more complete image of the relationships

▪ Interesting for online retailers

▪ Adaptable display of product information

▪ Research question: “To what extent does consumer-generated information affect the relationship between firm-generated information and product preference?”

Main findings

▪ Importance of review valence

▪ CGI interacts with FGI

▪ Importance of price is moderated by number of reviews

▪ Review valence interacts with the number of reviews

▪ New information mode: diagnostic format

Theoretical

framework

Theoretical framework

▪ Introduction of diagnostic format

▪ Content diagnosticity: the extent to which a text contains alternative interpretations of a problem and possible solutions to it (Herr 1991)

▪ Content diagnosticity: helps to differentiate between the benefits and concerns about a certain product (Li et al. 2013) and help them in a decision-making task (Jiménez and Mendoza 2013)

▪ Interactions CGI

▪ Positive CGI  enhance perceived value

Research design

Attribute Attribute levels

Price € 419 € 499 € 579

Information presentation format Textual format Schematic format Diagnostic format

Third-party rating 1 out of 5 stars 3 out of 5 stars 5 out of 5 stars

Review valence 1 out of 5 stars 3 out of 5 stars 5 out of 5 stars

Number of reviews 2 review 21 reviews 118 reviews

Variance of the review Low-variance

Moderate-variance High-variance

▪ Choice-based conjoint analysis

Results

▪ Review variance not significant

▪ Interaction effects

Main effects

Support for hypotheses main effects

Relative importance Thirdpartyreviewrating Pricing Informationpresentationformat ReviewValence Numberofreviews

Hypotheses main effects Overall support

H1: The price of a product is negatively related to product preference. Supported

H2: The valence of a third-party rating is positively related to product

preference.

Supported

H3a: If product information is presented in a schematic format, the

preference for the product is larger than with a textual information presentation format.

Supported

H3b: If product information is presented in a schematic format, the

preference for the product is larger than with a (1) textual- and (2)

Interaction effects

Model LL Hit rate R²adj AIC Improved model fit?

Model without interactions -3711.15 66.59% 0.2967 7442.30 Model 2 (Price x valence) -3709.17 66.65% 0.2963 7446.34 No Model 3 (Price x #reviews) -3706.75 66.57% 0.2968 7441.51 Yes Model 4 (TRR x valence) -3709.05 66.34% 0.2963 7446.09 No Model 5 (TRR x #reviews) -3707.17 66.86% 0.2967 7442.34 No Model 6 (Format x valence) -3710.84 66.45% 0.2960 7449.68 No Model 7 (Format x #reviews) -3707.7 66.86% 0.2966 7443.40 No

H8: The price of a product has a weaker effect on product preference

when displayed with a high number of reviews compared to a low number of reviews.

Interaction effects

15,00% 17,50% 20,00% 22,50% 25,00%

Low #reviews Moderate #reviews

High #reviews

Relative importance pricing x number of reviews

Interaction effects

0,00% 5,00% 10,00% 15,00% 20,00% Negative valence Moderate valence Positive valence

1 star (TRR) 3 stars (TRR) 5 stars (TRR) 1 star -0,26 -0,01 0,28 3 stars -0,38 -0,03 0,41 5 stars -0,37 0,05 0,32 -0,70 -0,60 -0,50 -0,40 -0,30 -0,20 -0,10 0,00 0,10 0,20 0,30 0,40 0,50 0,60 A S T IT E L

Interaction effects

Low #reviews Moderate #reviews

High #reviews

Relative importance Review valence x #reviews

Multiple moderation

Model without interactions -3711.15 66.59% 0.2967 7442.30

Model 9 (Valence and #reviews x Price) -3689.92 67.07% 0.2977 7431.84 Yes Model 10 (Valence and #reviews x TRR) -3695.94 66.88% 0.2965 7443.87 No

Model 11 (Valence and #reviews x IPV) -3702.90 67.15% 0.2952 7457.81 No

Theoretical implications

▪ Review variance

▪ High importance

▪ Joint construct with number of reviews

▪ New information mode

▪ Interaction CGI with FGI

▪ Price with number of reviews (+ review valence)

▪ TRR with review valence

Managerial implications

▪ Importance of CGI

▪ Price interacts with CGI

▪ Conditional pricing strategies

▪ Expert rating as decision heuristic

▪ Use of diagnostic mode of information presentation

Thank you for your

attention!

Are there any questions?

References

▪ Herr, P.M. (1991), “Effect of word-of-mouth and product attribute information on

persuasion: An accessibility-diagnostic perspective,” The Journal of Consumer

Research, 17 (March), 452–62.

▪ Jiménez, Fernando R. R andNorma a. A Mendoza (2013), “Too popular to ignore:

The influence of online reviews on purchase intentions of search and experience products,” Journal of Interactive Marketing, 27 (3), 226–35.

▪ Li, M X, L Q Huang, C H Tan, and K KWei (2013), “Helpfulness of Online Product

Reviews as Seen by Consumers: Source andContent Features,” International