Information Systems Frontiers

, Volume 21, Issue 2, pp 441–452 | Cite as

Enhancing mobile data services performance via online reviews

  • Hua (Jonathan) YeEmail author
  • Cecil Eng Huang Chua
  • Jun Sun


The prevalence of portable computational devices like smartphones and tablets has increased the popularity and importance of mobile data services (MDS). However, the flood of new MDS in the market has caused hyper-competition among MDS providers and only a few of them profit. Past studies suggest that online reviews can help MDS providers gain market attention and provide information for improving MDS applications. As a result, MDS providers can leverage reviews to innovate and profit. However, little research has empirically investigated the influences of online reviews on MDS innovation and profitability. This paper studies MDS profitability (popularity) from two angles. We posit that one strategic advantage of certain MDS providers is their ability to rapidly innovate and that innovation inspiration can be derived from reviews ubiquitous in MDS download sites. Our results show that online reviews positively impact MDS popularity directly and indirectly via increasing MDS innovation.


Mobile data service innovation Online reviews Mobile data service popularity Awareness effect Persuasive effect 


  1. Andreassen, T. W., & Streukens, S. (2009). Service innovation and electronic word-of mouth: Is it worth listening to? Managing Service Quality, 19(3), 249–265.CrossRefGoogle Scholar
  2. Aral, S., Dellarocas, C., & Godes, D. (2013). Social media and business transformation: A framework for research. Information Systems Research, 24(1), 3–13.CrossRefGoogle Scholar
  3. Baron, R. M., & Kenny, D. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.CrossRefGoogle Scholar
  4. Berge, J. (2012). Bad reviews can boost sales. Here’s why. Harvard Business Review, 90(1), 28.Google Scholar
  5. Berry, L., Shankar, V., Parish, J. T., Cadwallader, S., & Dotzel, T. (2006). Creating new markets through service innovation. Sloan Management Review, 47(2), 56–63.Google Scholar
  6. Bland, M. (2000). An introduction to medical statistics, (3rd edition ed.) Oxford medical publications.Google Scholar
  7. Boudreau, K. J. (2012). Let a thousand flowers bloom? An early look at large numbers of software app developers and patterns of innovation. Organization Science, 23(5), 1409–1427.CrossRefGoogle Scholar
  8. Boudreau, K., & Lakhani, K. R. (2009). How to manage outside innovation. Sloan Management Review, 50(4), 69–76.Google Scholar
  9. Burrows, P. 2010. Apple vs. Google: How the battle between Silicon Valley's superstars will shape the future of mobile computing, BusinessWeek).Google Scholar
  10. Cadwallader, S., Jarvis C. B., Bitner, M. J., & Ostrom A. L. (2010). Frontline employee motivation to participate in service innovation implementation. Journal of the Academy Marketing Science, 38, 219–239.Google Scholar
  11. Carbonell, P., Rodriguez-Escudero, A. I., & Pujari, D. (2009). Customer involvement in new service development: An examination of antecedents and outcomes. Journal of Product Innovation Management, 26(5), 536–550.CrossRefGoogle Scholar
  12. Chang, W., & Taylor, S. A. (2016). The effectiveness of customer participation in new product development: A meta-analysis. Journal of Marketing, 80(1), 47–64.CrossRefGoogle Scholar
  13. Chen, N., Lin, J., Hoi, S., Xiao, X., & Zhang, B. (2014). AR-miner: Mining informative reviews for developers from mobile app marketplace, Proceedings of 36 th International Conference on Software Engineering. India: Hyderabad.Google Scholar
  14. Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 43(3), 345–354.CrossRefGoogle Scholar
  15. Clemons, K. E., Gao, G., & Hitt, L. M. (2006). When online reviews meet hyperdifferentiation: A study of the craft beer industry. Journal of Management Information Systems, 23(2), 149–171.CrossRefGoogle Scholar
  16. Das, S. R., & Joshi, M. P. (2012). Process innovativeness and firm performance in technology service firms: The effects of external and internal contingencies. IEEE Transactions on Engineering Management, 59(3), 401–414.CrossRefGoogle Scholar
  17. De Vaus, D. (2002). Analyzing social science data: Fifty key problems in data analysis. London: Sage.Google Scholar
  18. Di Gangi, P. M., & Wasko, M. (2009). Steal my idea! Organizational adoption of user innovations from a user innovation community: A case study of Dell ideastorm. Decision Support Systems, 48(1), 303–312.CrossRefGoogle Scholar
  19. Duan, W., Gu, B., & Whinston, A. B. (2008). Do online reviews matter? An empirical investigation of panel data. Decision Support Systems, 45(4), 1007–1016.CrossRefGoogle Scholar
  20. Eloranta, T. (2016). Online review site data on service innovation. International Journal of E-Services and Mobile Applications, 8(4), 20–34.CrossRefGoogle Scholar
  21. Eng, C. (2016). iSIM: An integrated design method for commercializing service innovation. Information Systems Frontiers, 18(3), 457–478.CrossRefGoogle Scholar
  22. Fang, E. (2008). Customer participation and the trade-off between new product innovativeness and speed to market. Journal of Marketing, 72(4), 90–104.CrossRefGoogle Scholar
  23. Ferreira, G. (2013). Gearbox recall in China expected to cost Volkswagen over $600 million, in 4WheelsNews,
  24. Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7, 117–140.CrossRefGoogle Scholar
  25. Gartner (2010). Market insight: Ten consumer mobile applications to watch in 2012,"
  26. Godes, D., & Mayzlin, D. (2004). Using online conversations to study word of mouth communication. Marketing Science, 23(4), 545–560.CrossRefGoogle Scholar
  27. Greene, W. H. (2003). Econometric analysis. Upper Saddle River: Prentice-Hall.Google Scholar
  28. Gupta, S. (2013). For mobile devices, think apps, not ads. Harvard Business Review, 91(2), 71–75.Google Scholar
  29. Haluk, D., & James, S. (2016). Emerging service orientations and transformations (SOT). Information Systems Frontiers, 18(3), 407–411.CrossRefGoogle Scholar
  30. Hong, S., & Tam, K. Y. (2006). Understanding the adoption of multipurpose information appliances: The case of mobile data services. Information Systems Research, 17(2), 162–179.CrossRefGoogle Scholar
  31. Hong, S., Tam, K. Y., & Kim, J. (2006). Mobile data service fuels the desire for uniqueness. Communications of the ACM, 49(9), 89–94.CrossRefGoogle Scholar
  32. Hong, S.-J., Thong, J. Y. L., Moon, J. Y., & Tam, K. Y. (2008). Understanding the behavior of mobile data services consumers. Information Systems Frontiers, 10(4), 431–445.CrossRefGoogle Scholar
  33. Hughes, J. (2011). iPhone & iPad apps marketing. Indianapolis, Indiana: QUE Publishing.Google Scholar
  34. IDC (2013). Android and iOS combine for 91.1% of the worldwide smartphone OS market in 4Q12 and 87.6% for the year, according to IDC ,
  35. Kankanhalli, A., Ye, H., & Teo, H. H. (2015). Comparing potential and actual innovators: An empirical study of mobile data services innovation. MIS Quarterly, 39(3), 667–682.CrossRefGoogle Scholar
  36. Kim, S. (2009). The integrative framework of technology use: An extension and test. MIS Quarterly, 33(3), 513–537.CrossRefGoogle Scholar
  37. Kim, B. (2010). An empirical investigation of mobile data service continuance: Incorporating the theory of planned behavior into the expectation-confirmation model. Expert Systems with Applications, 37(10), 7033–7039.CrossRefGoogle Scholar
  38. Kim, B., Choi, M., & Han, I. (2009). User behaviors toward mobile data services: The role of perceived fee and prior experience. Expert Systems with Applications, 36(4), 8528–8536.CrossRefGoogle Scholar
  39. Kim, M., Song, J., & Triche, J. (2015). Toward an integrated framework for innovation in service: A resource-based view and dynamic capabilities approach. Information Systems Frontiers, 17(3), 533–546.CrossRefGoogle Scholar
  40. Lau, A. (2011). Supplier and customer involvement on new product performance: Contextual factors and an empirical test from manufacturer perspective. Industrial Management & Data Systems, 111(6), 910–942.CrossRefGoogle Scholar
  41. Lee, S., Shin, B., & Lee, H. G. (2009). Understanding post-adoption usage of mobile data services: The role of supplier-side variables. Journal of the Association for Information Systems, 10(12), 860–888.CrossRefGoogle Scholar
  42. Li, X., & Hitt., L. M. (2008). Self-selection and information role of online product reviews. Information Systems Research, 19(4), 456–474.CrossRefGoogle Scholar
  43. Li, X., & Hitt, L. M. (2010). Price effects in online product reviews: An analytical model and empirical analysis. MIS Quaterly, 34(4), 809-831Google Scholar
  44. Lu, J., Liu, C., Yu, C. S., & Wang, K. (2008). Determinants of accepting wireless mobile data services in China. Information Management, 45(1), 52–64.CrossRefGoogle Scholar
  45. Magnusson, P. R., Matthing, J., & Kristensson, P. (2003). Managing user involvement in service innovation. Journal of Service Research, 6(2), 111–124.CrossRefGoogle Scholar
  46. Maltz, J. (2013). Choose your mobile business model wisely. The Wall Street Journal. Retrieval from
  47. Mazmanian, M., Orlikowski, W. J., & Yates, J. Y. (2006). Ubiquitous email: Individual experiences and organizational consequences of BlackBerry use, best paper proceedings of Academy of. Altanta: Management.Google Scholar
  48. Menor, L. J., & Roth, A. V. (2007). New service development competence in retail banking: Construct development and measurement validation. Journal of Operations Management, 25(4), 825–846.CrossRefGoogle Scholar
  49. Mudambi, S. M., & Schuff, D. (2010). What makes helpful online review? A study of customer reviews on MIS Quarterly, 34(1), 185–200.CrossRefGoogle Scholar
  50. Ordanini, A., & Parasuraman, A. (2011). Service innovation viewed through a service dominant logic lens: A conceptual framework and empirical analysis. Journal of Service Research, 14(1), 3–23.CrossRefGoogle Scholar
  51. Piezunka, H., & Dahlander, L. (2015). Distant search, narrow attention: How crowding alters organizations' filtering of suggestions in crowdsourcing. Academy of Management Journal, 58(3), 856–880.CrossRefGoogle Scholar
  52. Riasanow, T., Ye, H., & Goswami, S. (2015). Generating trust in online consumer reviews through signaling: An experimental study. Hawaii International Conference on System Sciences, 48, 3307–3316.Google Scholar
  53. Rowan, D., and Cheshire, T. (2009). The app explosion, in Wired,
  54. Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290–312.CrossRefGoogle Scholar
  55. Spence, M. (2002). Signaling in retrospect and the informational structure of markets. American Economic Review, 92, 434–459.CrossRefGoogle Scholar
  56. Statista, (2016). Worldwide mobile app revenues 2015–2020,
  57. Viswanathan, P. (2013). 2013 mobile devices readers’ choice awards winners,
  58. Yang, X., Wang, J., & Chau, M. (2015). Customer revisit intention to restaurants: Evidence from online reviews. Information Systems Frontiers, 17(3), 645–657.CrossRefGoogle Scholar
  59. Ye, H., & Kankanhalli, A. (2015). Investigating the antecedents of organizational task crowdsourcing. Information Management, 52(1), 98–110.CrossRefGoogle Scholar
  60. Ye, H., & Kankanhalli, A. (2017). User service innovation on mobile phone platforms: Investigating impacts of lead userness, toolkit support, and design autonomy, MIS Quarterly, forthcoming.Google Scholar
  61. Ye, H., Kankanhalli, A., Goh, K. Y., & Sun, J. (2011). Investigating value co-creation in innovation of it-enabled services: An empirical study of mobile data services, International Conference on Information Systems. Shanghai, China: AIS.Google Scholar
  62. Ye, H., Blohm, I., Bretschneider, U., Goswami, S., Leimeister, J., & Krcmar, H. (2016). Promoting the quality of user generated ideas in online innovation communities: A knowledge collaboration perspective, International Conference on Information Systems. Ireland: Dublin.Google Scholar
  63. Zhu, F., & Zhang, X. (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of Marketing, 74(2), 133–148.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Hua (Jonathan) Ye
    • 1
    Email author
  • Cecil Eng Huang Chua
    • 1
  • Jun Sun
    • 2
  1. 1.Department of Information Systems and Operations ManagementThe University of AucklandAucklandNew Zealand
  2. 2.Facebook Inc.Menlo ParkUSA

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