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- An Award At The 8th International Communication Management Conference
 
  

 

  #  An award at the 8th International Communication Management Conference 



 Published on 14/02/2022   [  View profile on Facebook](https://www.facebook.com/sharer.php?u=https://neoma-bs.com/news/award-8th-international-communication-management-conference) [  View profile on X-twitter](https://twitter.com/intent/tweet?urlhttps://neoma-bs.com/news/award-8th-international-communication-management-conference) [  View profile on Linkedin](https://linkedin.com/shareArticle?url=https://neoma-bs.com/news/award-8th-international-communication-management-conference) [   View profile on Email](mailto:?subject=https://neoma-bs.com/news/award-8th-international-communication-management-conference) [   View profile on Copy](javascript:void(0);https://neoma-bs.com/news/award-8th-international-communication-management-conference)

 **Indranil Bose, professor at NEOMA, has been awarded for a conference paper at the International Communication Management Conference 2022 organised by MICA on “The Future of Business in a Digital Era: Data, Analytics and Narratives”.**

Prof. [Indranil Bose](https://neoma-bs.com/professors/bose-indranil) (NEOMA) and Ms. Madhuri Prabhala (doctoral student at IIM Calcutta) received a consolation prize of 700 euros for presentation of their paper titled **‘Influence of Search Trends and Review Sentiments on Automobile Sales**‘ at the [International Communication Management Conference organised by MICA](https://www.mica.ac.in/icmc/icmc-2022) on ‘The Future of Business in a Digital Era: Data, Analytics and Narratives’ held on January 5-7, 2022.

## Short summary

**Influence of Search Trends and Review Sentiments on Automobile Sales**

While diverse approaches have quantified the influence of online search and reviews on sales of products, limited studies have examined this relationship for high involvement products. This study adopts an unstructured predictive analytics approach to identify important review and online search features that can impact the sales of automobiles in the Indian market. The monthly sales and searches data as well as 95,000= online reviews on various brands and models of automobiles are analyzed for this purpose. The techniques of Random Forest and XGBoost are used to identify important features, which are then used in a multinomial logistic regression to classify the automobile sales into high, medium, and low categories. The study finds that the highest-selling category of automobiles is also the most searched. Secondly, it determines that negative sentiment of reviews is more important than positive sentiment in predicting sales. Furthermore, the highest prediction accuracy for sales of automobiles is observed when both sentiment and search related variables are included in the model. The findings of this research imply that firms should track online reviews along with online searches and undertake necessary promotions to counter the effect of prevalent negative sentiments to enhance sales of automobiles.



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