ONLINE SHOPPING FREQUENCY - Adding e-Tailing Quality to the Mix

Rose Sebastianelli, Nabil Tamimi



A logistic regression model is developed to predict the frequency with which consumers make online purchases. Using survey responses from a national sample of U.S. online consumers, we categorize respondents as high and low frequency Internet shoppers. We include as predictor variables demographics (age, gender, education level and income), frequency of Internet browsing, product type (search versus experience), and seven empirically derived dimensions of e-tailing quality (reliability, accessibility, ordering services, convenience, product content, assurance and credibility).


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Paper Citation

in Harvard Style

Sebastianelli R. and Tamimi N. (2009). ONLINE SHOPPING FREQUENCY - Adding e-Tailing Quality to the Mix . In - ICE-B, (ICETE 2009) ISBN , pages 0-0

in Bibtex Style

author={Rose Sebastianelli and Nabil Tamimi},
title={ONLINE SHOPPING FREQUENCY - Adding e-Tailing Quality to the Mix},
booktitle={ - ICE-B, (ICETE 2009)},

in EndNote Style

JO - - ICE-B, (ICETE 2009)
TI - ONLINE SHOPPING FREQUENCY - Adding e-Tailing Quality to the Mix
SN -
AU - Sebastianelli R.
AU - Tamimi N.
PY - 2009
SP - 0
EP - 0
DO -