perceived risk vs. intention to adopt e-commerce - a pilot study of potential moderators

perceived risk vs. intention to adopt e-commerce - a pilot study of potential moderators

;Patricea Elena Bertea;Adriana Zait
applied thermal engineering 2013 Vol. 25 pp. 213-229
171
bertea2013triteperceived

Abstract

E-commerce continues to develop as an important channel for consumer purchases. This explains the growing interest in determining the most important variables which affect online consumer behavior, especially perceived risk as a well-known behavioral deterrent. Previous studies have proved a negative influence of perceived risk on the intention to adopt e-commerce. However, depending on the type of product and the population investigated, results were often contradictory and this relationship was found to be stronger, weaker or even inconclusive. This led us to conclude that, besides direct influence factors, there could be moderating effects for the analyzed relationship. Moderators are qualitative or quantitative variables which modify a relationship, and affect the direction and/or strength of that relationship between an independent and a dependant variable. The purpose of our research was to investigate potential moderator variables which could change the relationship between perceived risk and the intention to buy online. We used three observable variables – gender, experience in using the Internet and experience with online shopping – and three latent, psychological variables – fear of uncertainty, trust in e-commerce and materialism. The research consisted of a survey conducted on a sample of 481 business students, followed by a Structural Equation Modeling approach. Although no moderation effect was proved, partly due to the homogeneity of the investigated pilot population, fear of uncertainty and trust in e-commerce were found to be antecedents of perceived risk in e-commerce, making perceived risk a mediator between these two variables and the intention to buy online.

Citation

ID: 198449
Ref Key: bertea2013triteperceived
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
198449
Unique Identifier:
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet