History matters: The impact of online customer reviews across product generations
We examine how online customer reviews for one generation of a product affect sales of another generation in the same product series. The main intriguing result is that previous generation valence has a positive impact on current generation sales; however, current generation valence has a negative i...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2022
|
| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/lkcsb_research/6863 https://ink.library.smu.edu.sg/context/lkcsb_research/article/7862/viewcontent/History_Matters__The_Impact_of_Online_Customer_Reviews_Across_Product_Generations.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Singapore Management University |
| Language: | English |
| Summary: | We examine how online customer reviews for one generation of a product affect sales of another generation in the same product series. The main intriguing result is that previous generation valence has a positive impact on current generation sales; however, current generation valence has a negative impact on previous generation sales. The positive impact of previous generation valence becomes even stronger (1) as the uncertainty (standard deviation) in reviews for the current generation increases and (2) when the current generation valence is high. In contrast, it becomes weaker (1) as the uncertainty in reviews for the previous generation increases and (2) when the current generation has been on the market for a longer period of time. Other results are discussed. Our data consist of intergenerational pairs of point-and-shoot cameras on the largest online seller of such devices, Amazon.com. We estimate the current and previous generation models jointly, allowing for errors to be clustered at the daily and product levels. In addition, we address endogeneity concerns over the online word of mouth measures by using instrumental variables. |
|---|