Aggarwal - PhD scholar, Department of Operational Research, University of Delhi, Delhi, India.
Tandon - Assistant Professor, Department of Management Studies, Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India.
Jindal - Professor, Department of Computer Science, Keshav Mahavidyalaya, University of Delhi, Delhi, India.
Aggarwal - Professor, Department of Operational Research, University of Delhi, Delhi, India.

Electronic word of mouth (eWOM) has been gaining popularity pertaining to its numerous benefits and ability to be applied in various fields. It helps consumers in making informed decisions and aids service providers in delivering an enhanced service or product. Despite all these benefits, dealing with the huge amounts of eWOM is a consistent problem. eWOM helpfulness comes handy in order to address this issue. In this study, we utilize ۱۶۶۹۹ hotels related eWOM written by ۱۰۹۹ reviewers which are collected from TripAdvisor.com. Our main objective is to analyze which factors impact eWOM helpfulness and how. For this purpose, eight unique variables belonging to three different categories are selected (eWOM length, eWOM subjectivity, eWOM polarity, eWOM readability, eWOM recency, hotel rating, reviewer badge and reviewer helpfulness) and are analyzed using econometric modelling. Our findings show that hotel rating as well as reviewer badge and helpfulness enjoy a positive significant relationship with eWOM helpfulness. It also suggests that eWOM length, readability and subjectivity positively influences eWOM helpfulness though eWOM polarity and recency are found to have an inverse relationship with the helpfulness of eWOM. Thus, our study reports that review, hotel and reviewer characteristics impact eWOM helpfulness in different ways. This study is summarized with the discussion of theoretical and practical implications.

eWOM helpfulness, review parameters, reviewer parameters, hotel parameters, econometric modelling