Quantitative Study Integrating the E-commerce Acceptance Model with Conversion Rate in the Education Market.
详细信息   
  • 作者:Wilson ; Frank C.
  • 学历:Ph.D.
  • 年:2014
  • 毕业院校:Northcentral University
  • Department:Business and Technology Management
  • ISBN:9781321057454
  • CBH:3629083
  • Country:USA
  • 语种:English
  • FileSize:3601843
  • Pages:129
文摘
The e-commerce acceptance model relates perceived ease of use,perceived usefulness,perceived risk,online trust,purchase intention,and purchase action. The specific problem was that the e-commerce acceptance model could not be directly applied to predict the performance of an e-commerce website. The purpose of this quantitative study was to extend the e-commerce acceptance model by creating an e-commerce website performance model that could be used to predict conversion rate. The quantitative study had a cross-sectional,correlational research design. The target population included consumers in the U.S. educational materials market that purchase educational materials online. Study participants visited one of eight assigned educational materials websites and subsequently responded to an online survey designed to measure the consumer's perceptions of the website as related to perceived ease of use,perceived usefulness,perceived risk,online trust,and purchase intention. Additionally,information related to past purchase behavior was collected. From the consumer responses,website perceived ease of use rating,website perceived usefulness rating,website perceived risk rating,website online trust rating,website purchase intention rating,and conversion rate for each evaluated website was determined. Multiple regression with backwards elimination was used to develop the e-commerce website performance model: conversion rate = -2.030 + 0.433 x (website online trust rating). This model was predictive with 74.7% of the variation in conversion rate being explained by the variation in website online trust rating. The constant term - 0.203 and the website online trust rating coefficient were statistically significant at the 0.01 level (p = 0.01 and p = 0.006,respectively). For the entire model,F = 17.758 and p < 0.01. This model may be used by vendors to predict e-commerce website conversion rates based on website online trust rating. Future research could refine the e-commerce website performance model and increase its external validity by increasing the demographic diversity of the sample to include more males and K - 12 teachers,by increasing the number and types of websites evaluated by consumers,and by using web analytics to determine conversion rate.

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