A Model of Household Online Buying

I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. ABSTRACT A Model of Household Online Buying The Internet has made profound changes in how people conduct their daily lives as well as how they buy goods and services. This study's objective is to shed light on the use and diffusion of online or electronic buying (e-buying). Canadian households have not adopted e-buying equally, as revealed by Statistics Canada's Household Internet Use Survey (HIUS) data of 1997 – 2003. We explore how e-buying varies across age groups, genders, education levels, income levels, and the nature of goods. We first develop a simple model for e-buying demand in the context of a utility-maximizing individual choosing between e-buying and conventional buying. We employ a parameter reflecting individual taste, so we can study the influence of individual-specific factors in e-buying adoption decisions. The taste parameter is distributed in a population in some unknown way, and we try different distributions in empirical tests. We use the literature in conjunction with the model to derive the model's implications in terms of variables available in the HIUS datasets. We employ Tobit and Poisson regression models for the empirical tests. The tests suggest that household e-buying is more when household income is more, when heads of households are more educated, and for homogeneous goods; but that household e-buying is less when heads of households are female. This understanding may help policy makers, businesses, and other interested parties find ways to promote Internet use and e-buying across all segments of society. iv ACKNOWLEDGEMENTS I express my heartfelt gratitude to my supervisor, Professor Brian Cozzarin, for his kindness, valuable advice, and encouragement throughout the course of this research. I also wish to express my sincere thanks to Professor Bonwoo Koo and Professor Scott A. Jeffrey, the readers of the thesis, for their valuable comments for the thesis. their timely help with the datasets of the Tri-University Data Resources (TDR). I sincerely acknowledge the help and support of my friends Vadivananthan Visuvalingam and Sachin Jayaswal throughout the research. I remain forever indebted to my parents Gandhimathi and S. M. Narayanan for instilling in me the value of education and endeavor. I thank my wife Seetha for her …