The effect of electronic word-of-mouth (eWOM) on mobile application downloads: an empirical investigation

In this study, we conduct empirical research to identify the effect of electronic word-of-mouth eWOM on the downloading of mobile applications. In addition, we examine how consumers' involvement affects the relationship between eWOM and mobile application downloads, comparing consumer behaviours for free and paid application downloads. For this analysis, we use actual data from T store, the largest mobile application store in Korea. We find that eWOM plays an important role in mobile application downloads. Furthermore, external eWOM, which is provided by third-party informediaries, plays an important role in paid application downloads because consumers are motivated to make an extensive search effort to get additional information. From a practical perspective, this study provides strategic directions on eWOM management to mobile application stakeholders.

[1]  J. Cacioppo,et al.  The Effects of Involvement on Responses to Argument Quantity and Quality: Central and Peripheral Routes to Persuasion , 1984 .

[2]  Andrew B. Whinston,et al.  Whose and what chatter matters? The effect of tweets on movie sales , 2013, Decis. Support Syst..

[3]  Bernardo A. Huberman,et al.  Predicting the Future with Social Media , 2010, Web Intelligence.

[4]  Li Qin,et al.  Word-of-Blog for Movies: A Predictor and an Outcome of Box Office Revenue? , 2011 .

[5]  Erin M. Steffes,et al.  Social ties and online word of mouth , 2009, Internet Res..

[6]  Panagiotis G. Ipeirotis,et al.  Estimating the Socio-Economic Impact of Product Reviews: Mining Text and Reviewer Characteristics , 2008 .

[7]  Wendy W. Moe,et al.  Measuring the Value of Social Dynamics in Online Product Ratings Forums , 2010 .

[8]  Russell S. Winer,et al.  A reference price model of brand choice for frequently purchased products. , 1986 .

[9]  J. Cacioppo,et al.  Central and Peripheral Routes to Advertising Effectiveness: The Moderating Role of Involvement , 1983 .

[10]  Yong Liu Word-of-Mouth for Movies: Its Dynamics and Impact on Box Office Revenue , 2006 .

[11]  Jiaqin Yang,et al.  Social reference group influence on mobile phone purchasing behaviour: a cross-nation comparative study , 2007, Int. J. Mob. Commun..

[12]  Richard L. Celsi,et al.  The Role of Involvement in Attention and Comprehension Processes , 1988 .

[13]  Ling Liu,et al.  Do online reviews affect product sales? The role of reviewer characteristics and temporal effects , 2008, Inf. Technol. Manag..

[14]  Jeffrey B. Schmidt,et al.  A proposed model of external consumer information search , 1996 .

[15]  J. Jacoby,et al.  The Components of Perceived Risk , 1972 .

[16]  Ioanna D. Constantiou,et al.  Exploring the influence of reference situations and reference pricing on mobile service user behaviour , 2006, Eur. J. Inf. Syst..

[17]  Bin Gu,et al.  Do online reviews matter? - An empirical investigation of panel data , 2008, Decis. Support Syst..

[18]  Ingoo Han,et al.  The Effect of On-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement , 2007, Int. J. Electron. Commer..

[19]  Hee-Woong Kim,et al.  An Exploratory Study on the Determinants of Mobile Application Purchase , 2011 .

[20]  George M. Giaglis,et al.  A roadmap for research in mobile business , 2005, Int. J. Mob. Commun..

[21]  Pirjo Laaksonen Consumer Involvement: Concepts and Research , 1994 .

[22]  U. Dholakia A motivational process model of product involvement and consumer risk perception , 2001 .

[23]  A. A. Mitchell,et al.  Involvement: a Potentially Important Mediator of Consumer Behavior , 1979 .

[24]  P. Resnick,et al.  The Market for Evaluations , 1999 .

[25]  Andrew Whinston,et al.  The Dynamics of Online Word-of-Mouth and Product Sales: An Empirical Investigation of the Movie Industry , 2008 .

[26]  R. Goldsmith,et al.  Measuring Motivations for Online Opinion Seeking , 2006 .

[27]  Michael D. Smith,et al.  All Reviews are Not Created Equal: The Disaggregate Impact of Reviews and Reviewers at Amazon.Com , 2008 .

[28]  R. Thaler Mental accounting matters , 1999 .

[29]  Chrysanthos Dellarocas,et al.  A Statistical Measure of a Population’s Propensity to Engage in Post-Purchase Online Word-of-Mouth , 2006 .

[30]  David Schuff,et al.  What Makes a Helpful Review? A Study of Customer Reviews on Amazon.com , 2010 .

[31]  Bin Gu,et al.  Research Note - The Impact of External Word-of-Mouth Sources on Retailer Sales of High-Involvement Products , 2012, Inf. Syst. Res..

[32]  David Godes,et al.  Using Online Conversations to Study Word-of-Mouth Communication , 2004 .

[33]  E. Clemons,et al.  When Online Reviews Meet Hyperdifferentiation: A Study of the Craft Beer Industry , 2006 .

[34]  S. Beatty,et al.  External Search Effort: An Investigation across Several Product Categories , 1987 .

[35]  Yubo Chen,et al.  Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix , 2004, Manag. Sci..

[36]  G. Laurent,et al.  Measuring Consumer Involvement Profiles , 1985 .

[37]  J. Zaichkowsky Measuring the Involvement Construct , 1985 .

[38]  R. Thaler Toward a positive theory of consumer choice , 1980 .

[39]  B. Gu,et al.  The impact of online user reviews on hotel room sales , 2009 .

[40]  J. Hausman Specification tests in econometrics , 1978 .

[41]  Peter H. Bloch,et al.  After the New Wears Off: The Temporal Context of Product Involvement , 1986 .

[42]  Chrysanthos Dellarocas,et al.  Exploring the value of online product reviews in forecasting sales: The case of motion pictures , 2007 .

[43]  Daniel L. Sherrell,et al.  Consumer Search: An Extended Framework , 1986 .

[44]  Andrew B. Whinston,et al.  Whose and What Chatter Matters? The Impact of Tweets on Movie Sales Framework , 2011 .

[45]  Anindya Ghose,et al.  Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets , 2008, Inf. Syst. Res..

[46]  Richard L. Divine The influence of price on the relationship between involvement and consideration set size , 1995 .

[47]  J. Hair Multivariate data analysis , 1972 .

[48]  Wei Chen,et al.  The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings , 2011, Comput. Hum. Behav..

[49]  Chrysanthos Dellarocas,et al.  The Digitization of Word-of-Mouth: Promise and Challenges of Online Feedback Mechanisms , 2003, Manag. Sci..