Understanding customers' loyalty intentions towards online shopping: an integration of technology acceptance model and fairness theory

2009 ◽  
Vol 28 (4) ◽  
pp. 347-360 ◽  
Author(s):  
Chao-Min Chiu ◽  
Hua-Yang Lin ◽  
Szu-Yuan Sun ◽  
Meng-Hsiang Hsu
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Online Shopping ◽  
Integration Of Technology ◽  
Fairness Theory ◽  
Loyalty Intentions ◽  
Acceptance Model

Understanding Vietnamese Consumer Intention to Use Online Retailer Websites

2020 ◽  
Vol 12 (2) ◽  
pp. 1-15
Author(s):  
A. F. M. Jalal Ahamed ◽  
Yam Limbu ◽  
Long Pham ◽  
Ha Van Nguyen
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Perceived Risk ◽  
Structural Equation ◽  
Online Shopping ◽  
Equation Model ◽  
Ease Of Use ◽  
Intention To Use ◽  
Perceived Ease Of Use ◽  
Acceptance Model

This study examines the applicability of an extended technology acceptance model (TAM) that incorporates trust, perceived risk, and self-enhancement as antecedents to the TAM constructs. Data collected from 299 Vietnamese online consumers, through a self-administered survey, were entered into a structural equation model using AMOS 23 to establish causality. The results partially confirm the applicability of TAM to the online shopping intentions of Vietnamese consumer, though contrary to expectations, perceived ease of use does not predict behavioral intentions. Trust and self-enchantment fit well with the TAM; the inclusion of perceived risk as an antecedent is questionable. The findings offer new opportunities for explaining TAM theory in light of Schwartz's value dimensions. This article thus concludes with a discussion of the research contributions and implications.

The Factors Driving Continuance Online Shopping in Saudi Arabia

2010 ◽  
Vol 1 (2) ◽  
pp. 11-34 ◽  
Author(s):  
Talal Al-Maghrabi ◽  
Charles Dennis
Keyword(s):  
Saudi Arabia ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Regional Differences ◽  
Online Shopping ◽  
Perceived Usefulness ◽  
Factors Affecting ◽  
Central Regions ◽  
Acceptance Model ◽  
Intention To Continue

This study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure regional differences with regard to continuance online shopping intentions in Saudi Arabia. Perceived usefulness, enjoyment, and subjective norms are determinants of online shopping continuance in Saudi Arabia. Women in the eastern, western, and central region groups are equivalent. The structural weights are also largely equivalent, but the regression path from perceived usefulness to enjoyment is not invariant between female shoppers in the eastern and western regions or in the eastern and central regions. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The research model explains 60% of the intention to continue shopping online. Furthermore, this research suggests that online strategies cannot ignore the influence of either direct or indirect regional differences on continuance intentions; the model can be generalized across Saudi Arabia.

Recommendations to Buy in Online Retailing and Their Acceptance

2011 ◽  
pp. 237-252 ◽  
Author(s):  
Daniel Baier ◽  
Eva Stüber
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Online Shopping ◽  
External Factors ◽  
Specific Recommendation ◽  
Online Retailing ◽  
Shopping Experience ◽  
Acceptance Model ◽  
Online Shops ◽  
Adequate Design

Personal welcomings, individual assistance, as well as recommendations to inform and buy are becoming an integral part in online retailing. These new so-called personalization elements are assumed to increase the retailer’s share of wallet and the customer’s satisfaction. However, up to now only little is known about which external factors influence the customer’s acceptance of such personalization elements. This chapter discusses the forms of recommendations to buy and how their acceptance can be measured using the well-known Technology Acceptance Model (TAM) approach. An experiment is used, where volunteers are offered an online shopping experience with individually generated recommendations to buy. The experiment shows how high the acceptance of the generated recommendations is and how close this acceptance is connected to the quality and shopping relevance of the recommendations. Even though the results are limited to the specific recommendation types used, they give important implications for an adequate design of modern online shops.

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