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Lynn University Doctoral Dissertation Defense Hearing

Lynn University Doctoral Dissertation Defense Hearing. Service Quality, Customer Satisfaction, and Customer Loyalty in Consumer Electronics E-Tailers: A Structural Equation Modeling Approach. Kuang-Wen Wu (Kevin) January 25, 2006. AGENDA. Introduction to the Study

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Lynn University Doctoral Dissertation Defense Hearing

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  1. Lynn UniversityDoctoral Dissertation Defense Hearing Service Quality, Customer Satisfaction, and Customer Loyalty in Consumer Electronics E-Tailers: A Structural Equation Modeling Approach Kuang-Wen Wu (Kevin) January 25, 2006

  2. AGENDA • Introduction to the Study • Literature Review, Theoretical Framework, and Research Questions • Methodology • Results • Discussion • Questions and/or Comments

  3. INTRODUCTION

  4. Background to the Problem

  5. Background to the Problem (cont.)

  6. Purpose of the Study • To validate the dimensions of E-S-QUAL and E-RecS-QUAL for CE e-tailers • To validate the ACSI model • To link the construct of service recovery to the ACSI model

  7. Definition of Terms Types of Variables Manifest Variable 1 Manifest Variable 4 Exogenous Latent Variable Endogenous Latent Variable Manifest Variable 2 Manifest Variable 5 Manifest Variable 3 Manifest Variable 6

  8. Definition of Terms (cont.)

  9. Justification • Significance • No previous study focused on CE e-tailers • No previous study examined E-S-QUAL and E-RecS-QUAL in the CE field • The instruments are new, and in need of further psychometric evaluation • Researchability • All variables could be measured • Feasibility • Subjects were available • Concepts could be measured

  10. Delimitations • Only nine categories of CE products (by CEA) • Geographic setting – The continental U.S. • U.S.-based CE e-tailers • Participants • 18+ • Read and write English • Lived in the U.S. • Previous online purchase of CE

  11. LITERATURE REVIEW, THEORETICAL FRAMEWORK, AND RESEARCH QUESTIONS

  12. Literature Review • Customer Satisfaction • Antecedents of Customer Satisfaction • Customer Expectations • Performance • Equity • Consequences of Customer Satisfaction • Customer Loyalty • Customer Complaints • Service Quality • Electronic Service Quality • Service Recovery

  13. Literature Review (cont.) • ACSI Model (Fornell et al., 1996) Perceived Quality Customer Complaints ＋ － Overall Customer Satisfaction (ACSI) ＋ Perceived Value ＋ ＋ ＋ Customer Expectations Customer Loyalty ＋ ＋

  14. Theoretical Framework • Hypothesized Electronic Service Quality Model Efficiency Responsiveness H2a H1a Fulfillment Electronic Service Quality Electronic Recovery Service Quality H1b H2b Compensation System Availability H1c H2c Contact H1d Privacy

  15. Theoretical Framework (cont.) • Hypothesized Electronic Customer Satisfaction (e-CS) Model Electronic Recovery Service Quality Electronic Service Quality Customer Complaints H10 H9 H11 H3 Customer Satisfaction H7 Perceived Value H4 H6 H8 Customer Expectations Customer Loyalty H12 H5

  16. METHODOLOGY

  17. Research Design & Population • Research Design • Quantitative, non-experimental • Correlational • Online survey • Questionnaire: 70 questions in 11 sections • Target Population • All American online CE shoppers • Accessible Population • Online CE shoppers who could be reached by e-mail

  18. Sampling Plan • Quota and Snowball Sampling Plan • Non-probability sample • Quota sample: 320 • 50% male • 60% under 45 years old • 60% with some college or more • 55% with family income less than $75K • Sent invitation e-mails to the quota sample

  19. Instrumentation

  20. Instrumentation (cont.)

  21. Instrumentation (cont.) • A Sample Print Out of Online Survey

  22. Procedures Obtained permission to use scales Designed a Web site for online survey Received approval from IRB Sent invitation e-mails (Bcc feature) Participation is voluntary 8-10 minutes to complete Anonymous Did not track IP address Did not track personal identification information Collected data for two months

  23. Methods of Data Analysis • Descriptive Statistics • SPSS 11.5 • Confirmatory Factor Analysis • Structural Equation Modeling (SEM) • Measurement Model Assessment • Structural Model Assessment • Goodness-of-Fit Criteria • Absolute Fit Measures • Incremental Fit Measures • Parsimonious Fit Measures • AMOS 5.0

  24. Methods of Data Analysis (cont.) • Goodness-of-Fit Criteria • Absolute Fit Measures • To determine the degree to which the overall model fits the sample data • Incremental Fit Measures • To compare the proposed model to a baseline model • Parsimonious Fit Measures • To diagnose whether model fit has been achieved by over-fitting the data with too many coefficients

  25. Evaluation of Research Methods • Internal Validity • The instruments have evidence of good estimates of reliability and validity • Methods of data analysis strengthen internal validity • External Validity • Quota samples strengthen the external validity • Non-random samples may cause sampling bias • The results may be difficult to generalize to the target population • Generalizing will depend upon how closely the final data-producing sample matches the "quota".

  26. RESULTS

  27. Socio-Demographic Characteristics • Gender (N = 274)

  28. Socio-Demographic Characteristics (cont.) • Age (M = 35.23; SD = 10.9); (N = 268) • 26-35 (47%)

  29. Socio-Demographic Characteristics (cont.) • Marital Status (N = 276) • Married (52%)

  30. Socio-Demographic Characteristics (cont.) • Employment Status (N = 276) • Full-time (80%)

  31. Socio-Demographic Characteristics (cont.) • Hollingshead’s Occupation Scale (N = 274) • Business Managers (26.3%)

  32. Socio-Demographic Characteristics (cont.) • Hollingshead’s Education Scale (N = 276) • Professional/Graduate (40.6%)

  33. Socio-Demographic Characteristics (cont.) • Index of Social Position (N = 253) • Upper-Middle Class (50%)

  34. Socio-Demographic Characteristics (cont.) • Annual Household Income (N = 273) • $60K-$74,999 (19.4%)

  35. Socio-Demographic Characteristics (cont.) • Annual Personal Income (N = 272) • $30K-$44,999 (22.4%)

  36. Socio-Demographic Characteristics (cont.)

  37. Online Purchasing Characteristics • Purchasing Frequency (N = 273) • Less than once a month (72%)

  38. Online Purchasing Characteristics (cont.) • Last Purchase (N = 273) • Six months to one year ago (25.6%)

  39. Online Purchasing Characteristics (cont.) • Annual Spending (N = 272) • $101-$300 (26.5%)

  40. Online Purchasing Characteristics (cont.) • Negative Experiences (N = 276)

  41. Hypothesis 1 • 22 items  17 items Efficiency H1a Fulfillment Electronic Service Quality H1b System Availability H1c H1d Privacy

  42. Hypothesis 1 (cont.)

  43. Hypothesis 2 • 3 Dimensions  2 Dimensions Responsiveness H2a Electronic Recovery Service Quality Compensation H2b H2c Contact

  44. Hypothesis 2 (cont.) Responsiveness and Contact Electronic Recovery Service Quality Compensation

  45. Hypothesis 2 (cont.)

  46. Hypotheses 3 through 8 • e-SQ  CS (t = -2.19; p < .05) • CE  CS (t = .50; p > .05) Electronic Recovery Service Quality Electronic Service Quality Customer Complaints H10 H9 H11 H3 Customer Satisfaction H7 Perceived Value H4 H6 H8 Customer Expectations Customer Loyalty H12 H5

  47. Hypotheses 3 through 8 (cont.) • H3 and H5 were not supported. Electronic Service Quality － Customer Satisfaction ＋ Perceived Value ＋ ＋ ＋ Customer Expectations

  48. Hypothesis 9 • e-RecSQ  CS (t = 1; p > .05) • Not supported Electronic Recovery Service Quality Electronic Service Quality Customer Complaints H10 H9 H11 H3 Customer Satisfaction H7 Perceived Value H4 H6 H8 Customer Expectations Customer Loyalty H12 H5

  49. Hypothesis 10 • Supported Electronic Recovery Service Quality Electronic Service Quality Customer Complaints H10 t = 7.4; p < .01 H9 H11 H3 Customer Satisfaction H7 Perceived Value H4 H6 H8 Customer Expectations Customer Loyalty H12 H5

  50. Hypotheses 11 and 12 • Supported Electronic Recovery Service Quality Electronic Service Quality Customer Complaints H10 H9 H11 H3 Customer Satisfaction H7 Perceived Value H4 H6 H8 Customer Expectations Customer Loyalty H12 H5

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