| Since travel products are experience products that users cannot contact product itself before purchase,users tend to rely on others' online reviews to make purchase decisions.As a public good,online review suffers from lacking supply.This phenomenon encourgages firms to think how to improve user reviewing behavior.Firm reply is a communication channel between users and firms and can increase future user reviewing behavior.Several platforms have begun to adopt the function of firm reply.It not only allows firms to understand user opinions ande build communication with users timely,but also help firms cover as many users as possible.Thus,firm reply is used to alleviate the negative emtion of unsatisfied users and strengthen the positive emotion of satisfied users.This study focuses on the effect of some aspects of firm reply(reply number,reply content and reply performer situation)on user reviewing behavior and explores the underlying mechanism,providing valuable suggestions for online platforms and firms.This study explores three questions by adopting the method of econometrics and online experiment.The specific introduction of studies is shown as bellowed.First,this study investigates the effect of firm reply number on user engagement behavior.Based on the design that Qunar.com allows firms to adopt firm reply,this study builds empirical research model and uses mixed method(econometrics and online experiment method)to explore the direct effect of firm reply number and the moderating effect of the number of firms' high-quality user opinions on user reviewing effort in the future.Then this study explores the underlying mechinisms behind these effects,in other words,what user motivation drives user behavior in this situation.The results show that as users receive more firm replies in the past,their sense of reciprocity and reviewing effort toward future reviews increase.In addition,when the number of firm high-quality user opinions that users observed increases,the increased sense of reciprocity reduces,thus restricting user reviewing effort toward future reviews.The usage of mixed methods innovatively studies the influential factors of user motivation and behavior,promting the development of online review literature and motivation theory.The research provides practical suggestions for improving high-quality reviews for online tourism platforms.Second,this study explores the effect of firm reply content on user reviewing behavior.Similar to Qunar,Trip Advisor also allows firms to adopt reply function.Based on this design,this study buids empirical research model,utilizes text-mining method,and then employs econometrics to investigate the effect of the specific language in firm reply on user reviewing number.The results suggest that when firms include causal-related and certainty-related language in firm reply,user reviewing number in the future will reduce.The usage of uncertainty-related language in firm replies can alleviate the negative effect of causal-related language.In addition,the usage of positive emotional language can not only increase review number directly but can reduce the negative influence of causal-related language.This study has begun an innovative exploration toward firm reply contant and identified the key influence of different types of language on user reviewing behavior,thus providing theoretical foundation for future research on firm reply and user engagement behavior.The results also provide guidance for practical staff.Last,this study examines the influence of the level of firm reply performer on user reviewing behavior.Based on the presentation of reply performer positions on Trip Advisor,this study builds empirical research model and adopts text-mining analysis and econometrics analysis to explore the direct effect of the level of firm reply performer and the moderating effect of specific content in reply on user reviewing number in the future.The results show that as the levels of reply performers increase,the future review number will increase.When this kind of replies conduct content custermization,user reviewing number will further increase.However,when this kind of firm replies include substitute information on online reviews,the increase of future reviewing number will be restrained.By innovatively classifying job positions of firm reply performers to three levels and recognizing the effect of these levels on user reviewing behavior,this study establishes foundations for future firm reply research.The study also provides guidance for online firms who intend to apply firm reply. |
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