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Consumer Adoption (consumer + adoption)
Selected AbstractsA Two-Step Estimation of Consumer Adoption of Technology-Based Service InnovationsJOURNAL OF CONSUMER AFFAIRS, Issue 2 2003EUN-JU LEE Firms initially offer new technology-based services to a limited number of customers to reduce risks and maximize their returns on the investments in the new technology. Consequently, consumers' adoption of new technology-based services is restricted by the limited access provided by the businesses. A model of consumer adoption was developed and estimated via a two-step procedure. A significant sample selection bias was found with regard to access when estimating consumer adoption of a relatively new innovation, computer banking, but no such bias was found for a mature innovation, ATMs. [source] Effects of superstitious beliefs on consumer novelty seeking and independent judgment making: Evidence from ChinaJOURNAL OF CONSUMER BEHAVIOUR, Issue 6 2008Monica D. Hernandez Cultural content has been examined in consumer adoption of new products, whereas the relationship between enduring cultural beliefs and adoption remains unexplored. In this study, proactive superstitious behaviors (e.g., carrying a lucky charm) and passive superstitious beliefs (e.g., belief in fate) were empirically tested as antecedents of consumer novelty seeking (CNS) and consumer independent judgment making (CIJM). The results suggest that proactive superstitious beliefs positively influence CNS, whereas passive beliefs negatively influence CNS. Only passive superstitious beliefs positively influence CIJM. Results also suggest that previous superstition scales are incomplete and fail to reflect contemporary thinking about superstitious beliefs. Copyright © 2008 John Wiley & Sons, Ltd. [source] Integrating technology readiness into technology acceptance: The TRAM modelPSYCHOLOGY & MARKETING, Issue 7 2007Chien-Hsin Lin Based on previous theoretical streams, the present study integrates technology readiness (TR) into the technology acceptance model (TAM) in the context of consumer adoption of e-service systems, and theorizes that the impact of TR on use intention is completely mediated by both perceptions of usefulness and ease of use. TAM was originally developed to predict people's technology-adopting behavior at work environments, but this research stemmed from a questioning of its applicability in marketing (i.e., non-work) settings. The differences between the two settings are exhibited by consumers' self-determining selection behavior and their high involvement in the e-service creation and delivery process. This paper first reviews the TAM and the construct of technology readiness, and then proposes and empirically tests an integrated Technology Readiness and Acceptance Model (TRAM) to augment TAM by taking technology readiness construct into the realm of consumers' adoption of innovations. The results indicate that TRAM substantially broadens the applicability and the explanatory power of either of the prior models and may be a better way to gauge technology adoption in situations where adoption is not mandated by organizational objectives. Further, theoretical and practical implications and future research directions are discussed. © 2007 Wiley Periodicals, Inc. [source] A longitudinal look at rural consumer adoption of online shoppingPSYCHOLOGY & MARKETING, Issue 4 2007Sharron J. Lennon Innovation diffusion theory guided research on the process of online apparel shopping adoption (i.e., changes in online shopping adoption) among rural consumers. Rural consumers in 11 states completed surveys in 2000 ( n = 2,198) and in 2003 (n = 879). Variables measured in 2000 were used to predict online apparel purchasing in 2003; structural equation modeling was used for data analysis and yielded satisfactory fit. Results revealed strong support for innovation diffusion theory: Previous practice and characteristics of the decision-making unit ( education, income, innovativeness) affected belief structures. Although beliefs about online shopping measured in 2000 did not affect online apparel shopping adoption in 2000, they did affect online apparel shopping adoption in 2003, demonstrating the dynamic nature of innovation diffusion. Characteristics of the decision-making unit (education, income) indirectly affected online apparel shopping via their influence on previous practice, which was the strongest predictor of online apparel purchasing in 2000 and 2003. General beliefs about the Internet and beliefs about the compatibility of online shopping with respondents' lifestyles predicted online apparel shopping in 2003, whereas beliefs about the benefits and advantages of online shopping did not. © 2007 Wiley Periodicals, Inc. [source] The effect of knowledge types on consumer-perceived risk and adoption of genetically modified foodsPSYCHOLOGY & MARKETING, Issue 2 2007Deon Klerck Scientists have asserted that genetically modified (GM) food offers financial, environmental, health, and quality benefits to society, but the realization of such benefits depends on consumer acceptance of this new technology. Consumer concerns about GM food raise questions about what consumers know about GM food and to what extent this knowledge translates into their evaluations of GM products. The present research empirically examines the effect of both objective and subjective knowledge on perceived risk and, in turn, key consumer behaviors associated with GM food. The results reveal that objective knowledge about GM food significantly reduces performance and psychological risks, whereas subjective knowledge influences only physical risk, and the valence of that impact depends on the level of the consumer's objective knowledge. Furthermore, different risk types enhance consumers' information search and reduce their propensity to buy GM food. The overall findings thus suggest the need for cooperation among government, scientific institutions, and the food industry to foster effective communication strategies that increase consumers' objective knowledge, reduce their risk perceptions, and encourage consumer adoptions of GM technology. © 2007 Wiley Periodicals, Inc. [source] A Two-Step Estimation of Consumer Adoption of Technology-Based Service InnovationsJOURNAL OF CONSUMER AFFAIRS, Issue 2 2003EUN-JU LEE Firms initially offer new technology-based services to a limited number of customers to reduce risks and maximize their returns on the investments in the new technology. Consequently, consumers' adoption of new technology-based services is restricted by the limited access provided by the businesses. A model of consumer adoption was developed and estimated via a two-step procedure. A significant sample selection bias was found with regard to access when estimating consumer adoption of a relatively new innovation, computer banking, but no such bias was found for a mature innovation, ATMs. [source] Integrating technology readiness into technology acceptance: The TRAM modelPSYCHOLOGY & MARKETING, Issue 7 2007Chien-Hsin Lin Based on previous theoretical streams, the present study integrates technology readiness (TR) into the technology acceptance model (TAM) in the context of consumer adoption of e-service systems, and theorizes that the impact of TR on use intention is completely mediated by both perceptions of usefulness and ease of use. TAM was originally developed to predict people's technology-adopting behavior at work environments, but this research stemmed from a questioning of its applicability in marketing (i.e., non-work) settings. The differences between the two settings are exhibited by consumers' self-determining selection behavior and their high involvement in the e-service creation and delivery process. This paper first reviews the TAM and the construct of technology readiness, and then proposes and empirically tests an integrated Technology Readiness and Acceptance Model (TRAM) to augment TAM by taking technology readiness construct into the realm of consumers' adoption of innovations. The results indicate that TRAM substantially broadens the applicability and the explanatory power of either of the prior models and may be a better way to gauge technology adoption in situations where adoption is not mandated by organizational objectives. Further, theoretical and practical implications and future research directions are discussed. © 2007 Wiley Periodicals, Inc. [source] | ||||||||||