Start Date
14-12-2012 12:00 AM
Description
Researchers in many diverse areas have consistently found that we are unduly influenced by negative information. In electronic commerce, this negativity bias is evident in the effect of product reviews on consumer behavior in the information systems literature. While the negativity bias is well documented, there has been little systematic and empirical research on its underlying causes. Utilizing a novel data set collected from Apple’s App Store, we examine three probable causes of the negativity bias: that negative reviews are more specific, that they have higher surprise value, and that they increase our ability to avoid losses. The empirical analysis revealed that while all three mechanisms contribute to the negativity bias, the ‘surprise’ factor and the ability to avoid losses play a more prominent role when consumers process and integrate positive and negative review information. Our findings also carry important practical implications for review platforms and online companies.
Recommended Citation
Yin, Dezhi; Mitra, Sabyasachi; and Zhang, Han, "Mechanisms of Negativity Bias: An Empirical Exploration of App Reviews In Apple’s App Store" (2012). ICIS 2012 Proceedings. 5.
https://aisel.aisnet.org/icis2012/proceedings/HumanComputerInteractions/5
Mechanisms of Negativity Bias: An Empirical Exploration of App Reviews In Apple’s App Store
Researchers in many diverse areas have consistently found that we are unduly influenced by negative information. In electronic commerce, this negativity bias is evident in the effect of product reviews on consumer behavior in the information systems literature. While the negativity bias is well documented, there has been little systematic and empirical research on its underlying causes. Utilizing a novel data set collected from Apple’s App Store, we examine three probable causes of the negativity bias: that negative reviews are more specific, that they have higher surprise value, and that they increase our ability to avoid losses. The empirical analysis revealed that while all three mechanisms contribute to the negativity bias, the ‘surprise’ factor and the ability to avoid losses play a more prominent role when consumers process and integrate positive and negative review information. Our findings also carry important practical implications for review platforms and online companies.