Designing Business-To-Consumer (B2C) Interface Metaphors: An Empirical Investigation

Designing Business-To-Consumer (B2C) Interface Metaphors: An Empirical Investigation

Designing Business-To-Consumer (B2C) Interface Metaphors: An Empirical Investigation John D. Wells Washington State University William L. Fuerst University of Kansas The First Annual Workshop on HCI Research in MIS December 14th, 2002 Barcelona, Spain Overview What are metaphors? Using a war metaphor to explain the concept of an argument Interface metaphors Desktop metaphor Why is it worth studying?

Heterogeneity of interaction domains (i.e., eCommerce) Heterogeneity of users (i.e., customers) Supporting Literature Interface Metaphors Domain Familiarity Information Presentation Interface Metaphors "the essence of metaphor is understanding and experiencing one kind of thing in terms of another" (Lackoff and Johnson 1980, p. 5). Metaphors are human derived models that apply tangible, concrete, recognizable objects (i.e., source domain) to abstract concepts and/or processes (i.e., target domain) (Baecker, et al., 1995). The use of concrete objects creates an interface metaphor that contains a structure that is visually representative of the interaction domain that facilitates

a users understanding of the interface (Erickson 1990). Domain Familiarity Mental Models: Design Model, Users Model, and System Image (Norman 1990) Expert/Novice Perspective Experts can effectively interpret metaphors with either abstract OR concrete attributes (Gentner 1988) Novices rely on metaphors with concrete attributes to understand a target domain (Gillen et al. 1995) Information Presentation Consumer information processing and decisionmaking (Bettman, 1979) Cognitive Fit Theory suggests that there is a strong link between how information is represented in an interface and the effectiveness with which users interpret/use the information (Vessey, 1991)

Depending on the nature of the task, how spatial (i.e., graphical) and symbolic (i.e., textual) information are presented to the user is an important consideration (Vessey and Galletta 1991) Research Model Domain Familiarity Strong Familiarity H2 H3 b Weak Familiarity Symbolic Information Mode of Interface Concrete Interface Metaphor

Abstract Interface Metaphor Information Retention H3a Spatial Information H4a H4c , b H4 H1 Problem Domain Hypothetical Vacation Resort This problem domain was attractive because the possibility of subjects possessing specific domain

knowledge about the resort was eliminated. subjects could be polarized into two domain familiarity groups: strong and weak it was generalizable to other business domains (e.g., airlines, restaurant, etc.). Mode of Interface Context-Oriented (i.e., Concrete) Content-Oriented (i.e., Abstract) Domain Familiarity Instantiate using the concept of Mental Models Pre-test questionnaire administered to over 900 potential subjects Quantitative scores were used to created 3 groups: high, medium, low

The middle group was discarded to create 2 artificially dichotomous groups: Strong and Weak Information Retention (and Recall) A primitive, fundamental requirement for consumer information process (Johnson & Bettman, 1984) Relationship to information presentation and decision-making (Bettman, 1979) Used in IT-oriented information presentation studies (e.g., graphs vs. tables) (Umanath & Scamell, 1988) Effective operationalization 30 questions (15 symbolic, 15 spatial) Analysis of Results Overall Information Retention Averages Results Related to Research Hypotheses

Average Information Retention Scores Abstract Concrete Interface Metaphor Interface Metaphor Strong Domain Familiarity 17.09 (12.32) 14.09 (8.77) Weak Domain Familiarity 17.50 (11.41) 11.77 (5.95)

Note: (#.##) denotes 2-day retention scores ANOVA Results for Overall Information Retention Scores Source of Variation Sum of Squares DF Mean Square F-Ratio Prob. > F Domain Familiarity Mode of Interface DF*Interface 20.04545 418.91909 40.89906

1 1 1 19.10227 468.28409 40.89906 .2386 .0001 .0936 Error 1195.0000 84 14.226

C-Total 1674.8636 87 1.4091 29.4463 2.8756 ANOVA Results for Overall Information Retention Scores (2-Day Re-Test) Source of Variation Sum of Squares DF Mean Square F-Ratio Prob. > F

Domain Familiarity Mode of Interface DF*Interface 76.40909 445.5000 20.04545 1 1 1 76.40909 445.5000 20.04545 .0215 .0001 .2334

Error 1168.9091 84 13.916 C-Total 1710.8636 87 5.4909 32.0145 1.4405 Research Model

Domain Familiarity Strong Familiarity H2 (p=.0215) H3 b (p =.1 7 8) Weak Familiarity Symbolic Information Mode of Interface Concrete Interface Metaphor Information Retention

06) 5 . = (p 2) 6 0 H3a . (p= a 4 H ) Abstract Interface Metaphor H4b

p=.0 ( c 4 ), H 1 0 00 (p=. Note: Based on Re-Test results Spatial Information 02 H1 (p=.0001) Symbolic Information Retention

Information Retention 6 5 4 Strong Domain Familiarity 3 Weak Domain Familiarity 2 1 0 Concrete Interface Metaphor

Abstract Interface Metaphor Mode of Interface Note: Based on Re-Test results Spatial Information Retention Information Retention 8 7 6 Strong Domain Familiarity 5 4 Weak Domain

Familiarity 3 2 1 0 Concrete Interface Metaphor Abstract Interface Metaphor Mode of Interface Note: Based on Re-Test results Limitations Laboratory Setting Domain of Applicability Task Type

Need for Replication Contributions Theoretical Interface Metaphors (Methodological) Cognitive Fit and Mental Models Pragmatic Domain of Use Information Presentation Future Research Different Independent Variables Task Type Information Search, Purchase transactions Products vs. Services Intangibility Different Dependent Variables

Productivity, Accuracy, Satisfaction Replication in Different Problem Domain Q&A Detailed Summary of Hypothesis Testing Information Retention Research Hypothesis #1 An interface metaphor that is based on concrete business domain attributes will enable a user to retain significantly more information when compared to an interface metaphor that is based on abstract business domain attributes. Same Day 2-Day Lag

#2: A user who possesses strong familiarity of the business domain will retain significantly more information than a user who possesses weak familiarity of the business domain #3a: When using an interface metaphor based on abstract business domain attributes, the amount of symbolic information retained by SDFs will be significantly MORE than the amount of symbolic information retained by WDFs. #3b: The amount of symbolic information retained by WDFs when using an interface metaphor based on concrete business domain attributes will be significantly MORE than the amount of symbolic information retained by WDFs when using an interface metaphor based on abstract business domain attributes. #4a: When using an interface metaphor based on abstract business domain attributes, the amount of spatial information retained by SDFs will be significantly MORE than the amount of spatial information retained by WDFs. #4b: The amount of spatial information retained by WDFs when using an interface metaphor based on concrete business domain attributes will be significantly MORE than the amount of spatial information retained by WDFs when using an interface metaphor

based on abstract business domain attributes. #4c: The amount of spatial information retained by SDFs when using an interface metaphor based on concrete business domain attributes will be significantly MORE than the amount of spatial information retained by SDFs when using an interface metaphor based on abstract business domain attributes. - Significant at = .05 - p = .062

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