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Measurement, Meaning and Consequences of .com Satisfaction

Qimei Chen

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Introduction

Fast growth of Internet usage Exponential increase of e-

commerce Lack of consensus definition of

online satisfaction Lack of standard, affordable and

accurate measure of online consumer satisfaction

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Research Questions

1. Is the two-factor .com Satisfaction|Dissatisfaction approach significantly better than the traditional one-factor approach?

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Research Questions

2. What are the major facets of .com Satisfaction and .com Dissatisfaction?

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Research Questions

3. Do .com Satisfaction|Dissatisfaction facets provide more information than the summated .com Satisfaction and .com Dissatisfaction scales?

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Research Questions

4. Is attitude toward the site a mediating variable between satisfaction and behavioral intentions?

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Research Questions

5. What variables moderate the relationship between attitude toward the site and behavioral intentions?

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Research Questions

6. Does the two-factor .com Satisfaction|Dissatisfaction approach perform significantly better than the traditional one-factor approach in the Expectancy-Disconfirmation with Performance model?

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Theoretical Background

Traditional Satisfaction Concept

Satisfaction

Dissatisfaction

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Theoretical Background

Herzberg’s Two-Factor Theory Motivators Satisfiers Hygienes Maintainers

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Two-factor .com Satisfaction|Dissatisfaction Concept .com

Satisfaction

.com Dissatisfaction

Lack of .com DissatisfactionLack of .com

Satisfaction

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Data Collection Processes

Literature Review Identify initial item pool based on

earlier literature

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Data Collection Processes

Depth Interviews (Web designers)

Supplement initial item pool; generate initial .com satisfaction|dissatisfaction model

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Data Collection Processes

Pilot Survey Purify the .com sastisfaction|

dissatisfaction instrument Cross-checking the final .com

satisfaction|dissatisfaction instrument (questionnaire) with Depth Interviews (Web users) Informal Survey of Industry Literature

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Data Collection Processes

Main Study Confirm the .com satisfaction|

dissatisfaction instrument; test competing models and test moderating effects of control variables

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Data Collection Processes Main Study—Respondents

Three sources Students enrolled in SJMC and IDSc Adults referred by student participants Respondents recruited via Service Quality

Institute Listserv mailing list 697 responses (33 were dropped)

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Data Collection Processes Main Study—Web Sites

Half of the respondents were directed to name an e-commerce site they had positive experience with

Half of the respondents were directed to name an e-commerce site they has negative experience with

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Findings (R1)1.Is the two-factor .com Satisfaction|

Dissatisfaction approach significantly better than the traditional one-factor approach? Tests of Semi-Independency Tests of Competing Models Relationships with Specific Behavioral

Intentions.

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Findings (R1)Tests of Semi-Independency

.com Satisfaction and .com Dissatisfaction are semi-independent

.com S/D is the overlapping part of .com Satisfaction and Dissatisfaction

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Findings (R1)

Tests of Competing Models

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Competing Model 1

Attitude Behavioral Intention

Traditional Satisfaction

.04

.21** .67**

Adjusted R2=.313 Adjusted R2=.118

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Competing Model 2

.44**

.42**

-.41**

.65**

-.26**

Behavioral Intention

Attitude

.com Dissatisfaction

.com Satisfaction

Adjusted R2=.477 Adjusted R2=.421 Adjusted R2=.313 Adjusted R2=.118

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Competing Model 3

.46**

.51**

-.36**

.50**

-.32**

Behavioral Intention

Attitude

.com Dissatisfaction

.com Satisfaction

.com Satisfaction

.19**

Adjusted R2=.479 Adjusted R2=.436

Adjusted R2=.313 Adjusted R2=.118 Adjusted R2=.477 Adjusted R2=.421

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Findings (R1)Relationships with Specific

Behavioral Intentions .com Satisfaction correlates most

significantly with specific positive behavioral intentions

.com Dissatisfaction correlates most significantly with specific negative behavioral intentions

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Therefore… The two-factor .com Satisfaction|

Dissatisfaction approach is significantly better than the traditional one-factor approach.

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Findings (R2)2.What are the major facets of .com Satisfaction

and .com Dissatisfaction? .com Satisfaction .com Dissatisfaction

Bipolars Organization Service Quality Simplicity Accuracy

Positive Unipolars AttractiveForgiving Sense of Community Flexible Personalizable Responsive Bricks parallel clicks Considerate

Negative Unipolars Difficult to use Cheap looking Deceptive Complicated Violates privacy Inconvenient Violates design norms

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Findings (R3)3.Do .com Satisfaction|Dissatisfaction facets

provide more information than the summated .com Satisfaction and .com Dissatisfaction scales? Regression analysis Bivariate correlation analysis

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Findings (R3)

Behavioral Intention

AttitudeAll Facets

Adjusted R2=.521 Adjusted R2=.446

Adjusted R2=.479 Adjusted R2=.436

Adjusted R2=.313 Adjusted R2=.118 Adjusted R2=.477 Adjusted R2=.421

Regression analysis facets account for more variance than summated scales in explaining attitudes and behavioral intentions

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Findings (R3)

Bivariate correlation analysis facets offer more informative and

meaningful associations with specific behavioral intentions

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Findings (R3)Snapshot of some findingsI would like to visit this Web site again in the

future Top Significant Correlations

Service Quality Simplicity

Accuracy AttractiveOrganizationBricks parallel Clicks

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Findings (R3)

Snapshot of some findingsI might send an email to express my

appreciation Top Significant Correlations

Sense of Community ResponsiveAttractiveService QualityPersonalizable

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Findings (R3)Snapshot of some findingsI might convince my friends not to use this

Web site Top Significant Correlations

Deceptive Violates Design NormsViolates PrivacyCheap LookingComplicatedDifficult to Use

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Therefore… .com Satisfaction|Dissatisfaction

facets do provide more information than the summated .com Satisfaction and .com Dissatisfaction scales.

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Findings (R4)4.Is attitude toward the site a mediating variable

between satisfaction and behavioral intentions? 3-step Least-squares multiple

regression analysis com Satisfaction and .com Dissatisfaction (partial

mediation) are more important predictors of behavioral intentions than Traditional Satisfaction (full mediation).

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Findings (R5)5.What variables moderate the relationship

between attitude toward the site and behavioral intentions? Moderated Multiple Regression Analyses

Brand Equity Monopoly Involvement Self-Efficacy

Internet Efficacy Online Shopping Efficacy

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Moderating Variable Test

Attitude

HighLow

Beh

avio

ral

Inte

ntio

n3.0

2.8

2.6

2.4

2.2

2.0

1.8

Monopoly

High

Low

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Moderating Variable Test

Attitude

HighLow

Beh

avio

ral

Inte

ntio

n 3.2

3.0

2.8

2.6

2.4

2.2

2.0

Involvement

Low

High

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Findings (R6)6. Does the two-factor .com Satisfaction|

Dissatisfaction approach perform significantly better than the traditional one-factor approach in the Expectancy-Disconfirmation with Performance model? Path Analyses

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.com Satisfaction

.com Dissatisfaction

Attitude Behavioral Intention

Behavior

.com S|DS Consequences of .com S|DS

Subjective Disconfirmation

Expectations

Antecedents of .com S|DS

Calculated Disconfirmation

Performance Outcomes

Findings (R6)

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Findings (R6) Expectancy Disconfirmation with

Performance Model holds true in the e-commerce domain

Treating .com Satisfaction and .com Dissatisfaction as partially independent constructs increases model fit

The two-factor .com Satisfaction|Dissatisfaction approach yields more meaningful associations with antecedent variables

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Theoretical Implications Produced an instrument that can be used in

future theoretically-oriented studies Proves that treating .com Satisfaction and .com

Dissatisfaction as partially independent concepts increases explanatory power

Shows that facet level analysis reveals important information

Indicates that Expectancy-Disconfirmation with Performance model works well in e-commerce domain

Enriches marketing theory by introducing insights from the MIS and job satisfaction arenas

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Managerial Implications The instrument

Reliable, comprehensive, affordable and easy-to-apply

Uses Cost-Benefit Analysis Competitive Analysis Longitudinal Analysis

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Managerial Implications Moderating Variables

Monopoly Involvement

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Suggestion for Future Studies Other kinds of Web Sites

.gov .edu

Other kinds of satisfaction in consumer research Brick-mortar settings (travel, banking)

Other domains of satisfaction Student satisfaction Patient satisfaction Communication Organization behavior