Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior

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Applying the Technology AcceptanceModel and Flow
Theory to OnlineConsumer Behavior

• Koufaris, M. (2003). Applying the Technology
  Acceptance Model and Flow Theory to Online
  Consumer Behavior. Information Systems Research,
  13(2), 205-223. 

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Introduction

• B2C
• emotional and cognitive
• using different types of search mechanisms on the
  Web site

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Theoretical Framework andStudy Measures

• 1a. Shopping enjoyment is positively related to
  intention to return.
• 1b. Perceived control is positively related to
  intention to return.
• 1c. Concentration is positively related to
  intention to return.
• 
  flow

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• 2a. Perceived usefulness of the Web store is
  positively related to intention to return.
• 2b. Perceived ease of use of the Web store is
  positively related to intention to return.
  
• 
  TAM

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• 3a. Consumers with higher shopping enjoyment are
  more likely to make unplanned purchases.
• 3b. Consumers with higher perceived control are
  less likely to make unplanned purchases.
• 3c. Consumers with higher concentration are more
  likely to make unplanned purchases.
  flow

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• 4a. Product involvement is positively related to
  shopping enjoyment.
• 4b. Product involvement is positively related to
  concentration.
• 
  flow

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• 5a. Perceived skills are positively related to
  perceived control.
• 5b. Perceived skills are positively related to
  shopping enjoyment.
• 5c. Perceived skills are positively related to
  concentration.
  
• 
  flow

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• 6a. The use of value-added search mechanisms is
  positively related to perceived control.
• 6b. The use of value-added search mechanisms is
  positively related to shopping enjoyment.
• 6c. The use of value-added search mechanisms will
  be positively related to concentration.
  flow

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• 7a. The level of challenges of a Web store is
  positively related to perceived control.
• 7b. The level of challenges of a Web store is
  positively related to shopping enjoyment.
• 7c. The level of challenges of a Web store is
  positively related to concentration. flow

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Methods

• online questionnaire
• Booksamillion.com---for several reasons
• (1) The site is comprehensive and functional
• (2) unknown online bookseller that guaranteed
  us enough first-time customers for our sample.
• (3) unlike Amazon.com,primarily sells books.
  Coffee and magazines, the main focus of the store
  is books.

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Study Design

• Survey---difficult
• simulated actual customers by recruiting subjects
• unplanned purchases
• Simulated an initial purchase plan
• --10 gift certificate

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• The first part --unrelated to their particular
  visit, including how many intended to buy when
  they visited the online bookstore.
• created a binary variable
• value zero ---no unplanned purchases value
  one ---some unplanned purchases.

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Implementation

• Data--Dynamic Logic--online market research
• randomly selected--e-mailed
• 10 gift certificate
• --code and a button --new window opened
• 10 in cash (via check), and the chance to
• win 1,000 in cash.
• leaving only new customers.

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Sample and Descriptive Statistics

• ran for one week.
• The first part -- 300 subjects, and 280--second
  part
• There were 12 international respondents, mainly
  from Canada.
• 63 female, and about 50 of the subjects were 30
  to 50 years old. 77 of the subjects college
  education
• 48 income of over 50,000.

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• Almost half of the subjects reported having
  children under the age of 18,
• 68 reported spending over 15 hours per week
  online.
• Almost 50 of the subjects reported buying books
  online at least four times a year.
• rate loyalty --one to six, (over 45) reported
  low customer loyalty

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• (73.2) intended to buy no books or not know how
  many they would buy.
• 20--one book.
• almost half purchased at least one book, 10
  purchasing more than one.
• 32 unplanned purchase
• 24 bought one more book than planned

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• 6 bought two more
• Very few purchased crossselling items such as
  coffee (4 subjects) or magazines (17 subjects).
• (65) spent 20 minutes or less at
  Booksamillion.com,
• 33 would return to Booksamillion.com (giving six
  or seven on a seven-point scale).
• 14 would not return (giving one or two on the
  same scale).

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Results
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Discussion

• as a shopper and a computer user
• TAM research--more important predictor
• Enjoyreturn
• on unplanned purchasesno relationship
• value-added search mechanisms may influence the
  experience
• actual new customers

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• Many issues remain unresolved and many questions
  unanswered.
• Future research can use these metrics to explain
  how and why consumers think, act, and feel when
  shopping on the Web.

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