This study evaluates the impact of personalization of review summaries on consumer's buying decision and cognitive efforts. Following a quasi-experimental procedure we tested two hypotheses pertaining to online buyers' decision process. Our results show that personalized review summary significantly reduces the information processing effort and information requirements of those who received personalized review summaries as compared to those who did not. This study thus contributes to e-commerce literature on online buyer behavior and recommender systems strategy. © 2016 IEEE.

Saji K Mathew

Department of Management Studies

data mining

electronic commerce

Engineering research

Sales

COGNITIVE PROCESSING

CONSUMER REVIEWS

EXPERIMENTAL PROCEDURE

INFORMATION REQUIREMENT

ONLINE WORD OF MOUTHS

Personalizations

Text Mining

WEB PERSONALIZATION

Online systems

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Impact of web personalization of online word of mouth on buyers' decision process: An experimental study

2016 IEEE International Conference on Management of Innovation and Technology, ICMIT 2016

E-Commerce firms have adopted Web Personalization techniques extensively in the form of recommender systems for influencing user behavior for customer retention. Although there are numerous studies in this area, academic research addressing the role of Web Personalization in user acceptance of technology is very scant. Further, owing to the potential of recommender systems to attract and retain customers, most studies in web personalization have been done in E-Commerce setting. In this research, the ‘Consumer Acceptance and Use of Information Technology’ theory proposed in previous research has been extended to include web personalization as a moderator and has been tested in an E-Government context. Data collection involved conducting a laboratory experiment with the treatment group receiving personalized web forms for requesting an E-Government service. Our analyses show that personalizing the Web by self-reference and content relevance has a significant moderator role in influencing the relationship between determinants of intention to use and behavioral intention in certain cases. © 2015, Springer Science+Business Media New York.

Information Systems Frontiers

Web personalization for user acceptance of technology: An empirical investigation of E-government services

Proceedings of the Sixteenth ACM Conference on Economics and Computation - EC '15

Bias and Reciprocity in Online Reviews

Journal of Product & Brand Management

Impact of online consumer reviews on sales and price strategies: a review and directions for future research

IEEE Transactions on Knowledge and Data Engineering

Estimating the Helpfulness and Economic Impact of Product Reviews: Mining Text and Reviewer Characteristics

Management Science

Deriving the Pricing Power of Product Features by Mining Consumer Reviews

Journal	Data powered by Typeset2016 IEEE International Conference on Management of Innovation and Technology, ICMIT 2016
Publisher	Data powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
Open Access	No