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Predicting and Explaining Use Intention and Purchasing Intention in Online Group Shopping

Hongxiu Li, Yong Liu, Predicting and Explaining Use Intention and Purchasing Intention in Online Group Shopping. In: U. Lechner, D. Wigand, A Pucihar (Eds.), eDependability: Reliable and Trustworthy eStructure, eProdesses, eOperations and eServices for the Future, 355–364, AIS eL, 2012.

Abstract:

Online group shopping has emerged as a new e-commerce model and received attention in both academics and practice. Prior research focuses on investigating online group shopping mainly from the marketing discipline, and little research has tried to examine individual consumers’ acceptance of online group shopping from the technology acceptance perspectives. This paper aims at investigating the drivers determining individual consumers’ intention to use online group shopping as well as the relationships between the intention to use online group shopping and the intention to purchase via online group shopping websites. The research model was developed based on technology acceptance theories and extended to purchasing behaviour. The research model is empirically tested with data collected from 318 Chinese college students and analyzed using PLS. The results show that all the individuals’ intention to use online group shopping are motivated by relative advantages, perceived complexity and perceived enjoyment, and their use intention is significantly related to their purchasing intention via online group shopping websites. Finally, the limitations of the current research are discussed, and the directions for further research are suggested.

BibTeX entry:

@INPROCEEDINGS{inpLiLi12a,
  title = {Predicting and Explaining Use Intention and Purchasing Intention in Online Group Shopping},
  booktitle = {eDependability: Reliable and Trustworthy eStructure, eProdesses, eOperations and eServices for the Future},
  author = {Li, Hongxiu and Liu, Yong},
  editor = {Lechner, U. and Wigand, D. and Pucihar, A},
  publisher = {AIS eL},
  pages = {355–364},
  year = {2012},
}

Belongs to TUCS Research Unit(s): UTU Information Systems Science (ISS)

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