A Framework for Big Data Analytics on Service Quality Evaluation of Online Bookstore

With the advancement of Internet technology and the rise of e-commerce, Big Data Analytics can be applied to assess service quality for e-commerce industry achieving customer relationship improvement and reflecting the service quality of transaction. Online bookstore is a form of electronic commerce which allows consumers to directly buy books or services from a seller over the Internet using a web browser or a app program. Most researches are focus on expert opinion or few sample to measure the critical criteria. The goal of this study is to explore and demonstrate the utility of big data analytics by using it to study core online bookstore service quality variables that have been extensively studied in past decades. Text analysis method to extract a large number of consumer reviews from Amazon to deconstruct the bookstore customer experience and examine its relationship with satisfaction. This paper proposed a framework that integration of big data analytic and SERVQUAL model to measure the importance and relationship of service quality criteria. How to provide a level of service quality that satisfies consumers is an important issue for operators of online bookstores. Further research will apply Amazon data set to evaluate the criteria.