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A Model of Household Online BuyingNarayanan, Meyyappan January 2006 (has links)
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.
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A Model of Household Online BuyingNarayanan, Meyyappan January 2006 (has links)
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.
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A Model of Household Online BuyingNarayanan, Meyyappan January 2006 (has links)
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.
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A Model of Household Online BuyingNarayanan, Meyyappan January 2006 (has links)
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.
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