Investigating the Evolution of Hotel Internet Adoption

Jamie Murphy, R. Schegg, D. Olaru
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引用次数: 52

Abstract

This article draws upon Diffusion of Innovations and Configurational theories to investigate how website features and email responses by 200 Swiss hotels reflect evolving Internet adoption. Complementary multivariate and artificial neural network (ANN) techniques support classifying the hotels into three clusters based on their website features. These clusters and the results of a structural equation model confirm that Internet adoption evolves from static to dynamic use, as organizations add website features and provide quality responses to customer emails. Practically, differences among these clusters suggest caution in adopting some website features. Academically, the study extends diffusion research and introduces metrics, particularly domain name age and quality email responses, for future research of organizational Internet adoption. Finally, the study illustrates how ANNs complement and help overcome limitations of multivariate techniques.
调查酒店互联网采用的演变
本文借鉴创新扩散理论和配置理论,调查了200家瑞士酒店的网站功能和电子邮件回复如何反映互联网采用的演变。互补的多元和人工神经网络(ANN)技术支持将酒店根据其网站特征分为三个集群。这些集群和结构方程模型的结果证实,随着组织增加网站功能和提供高质量的客户电子邮件响应,互联网的采用从静态发展到动态使用。实际上,这些集群之间的差异表明在采用某些网站功能时要谨慎。在学术上,该研究扩展了扩散研究,并为未来的组织互联网采用研究引入了指标,特别是域名年龄和电子邮件回复质量。最后,该研究说明了人工神经网络如何补充和帮助克服多元技术的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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