Replication Materials for "Revisiting Online Review Helpfulness: A Conceptual Replication of Mudambi and Schuff (2010)

This record contains the replication materials for the manuscript titled “Revisiting Online Review Helpfulness: A Conceptual Replication of Mudambi and Schuff (2010).” The study conceptually replicates the online review helpfulness framework of Mudambi and Schuff (2010) using the Amazon Reviews’23 dataset. The analysis focuses on six Amazon product categories classified as search and experience goods and covers the 2019–2022 period.

The materials include R scripts for file checking, pilot data preparation, model estimation, balanced sample construction, figure generation, and supplementary table production. The final empirical design uses a category-year balanced review-level sample and estimates PPML, negative binomial, and logit models to examine the relationships between review depth, rating extremity, product type, verified purchase status, and review helpfulness.

The original Amazon Reviews’23 source files are not included in this record because they are publicly available from the original data provider and are large in size. The scripts document how the analysis files and reported results can be reproduced from the source data. Output files, model summaries, coefficient tables, and figure files are included where applicable.