(The) collective intelligence in e-commerce

Abstract

Online Consumer Review (OCR) is a real success story in e-Commerce as one of collective intelligence. Ever since online shopping malls began providing OCRs, buyers have been citing recommendations and references as their most important source of information about service providers and products. In other word, OCR is perceived as a typical form of electronic (eWOM). The majority of previous research on this topic has focused on motivations to create eWOM and the use of eWOM as revenue forecasting tool. However, the effect of OCRs could be different depending on the contents of OCRs and online context. The research objective is to find the effect of OCRs using various characteristics of contents such as message sidedness and the quality of OCRs and online context such as trust in website and location of OCRs. In addition, this research focuses on negative OCRs than positive OCRs because negative information is considered more useful or diagnostic in making decisions and is given greater weight than positive information. This research has three essays as negative OCRs increases with different characteristics of the context and the content. Essay 1 uses only positive OCRs, essay 2 uses a few negative OCRs, and essay 3 uses more negative OCRs. Essay 1 uses two characteristics of the context: site trust and the location of OCRs. Original OCRs are located independently from a product advertisement. However, marketers have used consumer endorsement for their advertisement. That is, they can quote OCRs as a part of advertisement. It is called as consumer endorsement which is one of typical advertisement strategies. In essay 1, we compare the effect of OCR and consumer reviews in advertisement (CRA) under two different site trust contexts (high/low site trust). Essay 2 uses the sidedness of OCRs with the attribute importance of a product and site trust. Two experiments are conducted in this essay. First experiment is conducted to compare one-sided OCR and two-sided OCR u...