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Online product review as an indicator of users’ degree of innovativeness and product adoption time: a longitudinal analysis of text reviews

  • Research Essay
  • Published:
European Journal of Information Systems

Abstract

Online reviews have become extremely valuable sources of information about products and their customers as electronic commerce continues to proliferate rapidly. Previous research has shown that reviews of a product change and evolve over its life. Identifying and understanding patterns of change in reviews and the forces that shape them is an underexplored topic with substantial potential for predicting and improving the market performance of products. In this study, we analyze review text of nearly 50 products over the course of their lives. Our longitudinal analysis of reviews reveals changes in certain personality-related characteristics of buyers in ways that are consistent with the predictions of product adoption and diffusion theories. The main findings and conclusions still hold when we replicate the same procedure on reviews of a different product category. Accordingly, based on online user-generated content in the form of online reviews, this research introduces a novel empirical method for identifying the product adoption and diffusion stage. Implications of the study for theory, methodology, and practice are discussed.

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References

  • Anderson C and Zeithaml C (1984) Stage of the product life cycle, business strategy, and business performance. Academy of Management Journal 27(1), 5–24.

    Article  Google Scholar 

  • Anderson M (2013) Local consumer review survey 2013. BrightLocal Blog. Retrieved from BrightLocal blog. http://searchengineland.com/2013-study-79-of-consumers-trust-online-reviews-as-much-as-personal-recommendations-164565.

  • Bates D, Maechler M, Bolker B, Walker S and Others (2013) lme4: linear mixed-effects models using Eigen and S4. R package version 1(4). http://keziamanlove.com/wp-content/uploads/2015/04/StatsInRTutorial.pdf.

  • Bates DM (2010) lme4: mixed-effects modeling with R. http://lme4.r-forge.r-project.org/book.

  • Bickart B and Schindler RM (2001) Internet forums as influential sources of consumer information. Journal of Interactive Marketing 15(3), 31–40.

    Article  Google Scholar 

  • Bordbar F (2010) Gender, identity, and language use: a case of Tehrani teenage bloggers’ virtual speech community. International Journal of Language Studies 4(2), 1–62.

    Google Scholar 

  • Bower JL and Christensen CM (1995) Disruptive technologies: catching the wave. Harvard Business Review Video Available at: http://immagic.com/eLibrary/ARCHIVES/GENERAL/JOURNALS/H950130C.pdf.

  • Breckler S, Olson J and Wiggins E (2006) Social psychology alive. Thomson Wadsworth, Belmont, CA.

  • Castaño R, Sujan M, Kacker M and Sujan H (2008) Managing consumer uncertainty in the adoption of new products: temporal distance and mental simulation. Journal of Marketing Research 45(3), 320–336.

    Article  Google Scholar 

  • Çelen B and Kariv S (2004) Distinguishing Informational Cascades from Herd Behavior in the Laboratory. American Economic Review 94(3), 484–498.

    Article  Google Scholar 

  • Çelen B and Kariv S (2005) An experimental test of observational learning under imperfect information. Economic Theory 26(3), 677–699.

    Article  Google Scholar 

  • Chevalier JA and Mayzlin D (2006) The effect of word of mouth on sales: online book reviews. Journal of Marketing Research (JMR) 43(3), 345–354.

    Article  Google Scholar 

  • Chintagunta PK, Gopinath S and Venkataraman S (2010) The effects of online user reviews on movie box office performance: accounting for sequential. Marketing Science 29(5), 944–957.

    Article  Google Scholar 

  • Clark RA and Goldsmith RE (2006) Interpersonal influence and consumer innovativeness. International Journal of Consumer Studies 30(1), 34–43.

    Article  Google Scholar 

  • Cleveland WS and Devlin SJ (1988) Locally weighted regression: an approach to regression analysis by local fitting. Journal of the American Statistical Association 83(403), 596–610.

    Article  Google Scholar 

  • Davis KM and Gardner WL (2012) Charisma under crisis revisited: presidential leadership, perceived leader effectiveness, and contextual influences. The Leadership Quarterly 23(5), 918–933.

    Article  Google Scholar 

  • Day GS (1981) The product life cycle: analysis and applications issues. Journal of Marketing 45(4), 60–67.

    Article  Google Scholar 

  • Dellarocas C, Gao G and Narayan R (2010) Are consumers more likely to contribute online reviews for hit or niche products? Journal of Management Information Systems 27(2), 127–158.

    Article  Google Scholar 

  • Dellarocas C, Xiaoquan Z and Awad NF (2007) Exploring the value of online product reviews in forecasting sales: the case of motion pictures. Journal of Interactive Marketing 21(4), 23–45.

    Article  Google Scholar 

  • Donnelly Jr JH and Ivancevich JM (1974) A methodology for identifying innovator characteristics of new brand purchasers. Journal of Marketing Research (JMR) 11(3), 331–334.

    Article  Google Scholar 

  • Doyle P (1976) The realities of the product life cycle. Quarterly Review of Marketing 1(4), 1–6.

    Google Scholar 

  • Duan W, Gu B and Whinston A (2009) Informational cascades and software adoption on the internet: an empirical investigation. MIS Quarterly 33(1), 23–48.

    Google Scholar 

  • Duan W, Gu B and Whinston AB (2008) Do online reviews matter? – an empirical investigation of panel data. Decision Support Systems 45(4), 1007–1016.

    Article  Google Scholar 

  • Easton H (1940) Word Frequency Dictionary. Dover, New York.

    Google Scholar 

  • Elias GS, Garfield RS, Gutschera KR (2012) Characteristics of Games. MIT Press, Cambridge, MA.

    Google Scholar 

  • Flesch RF (1951) How to Test Readability. Harper, New York.

    Google Scholar 

  • Fox HW and Rink DR (1977) Coordination of purchasing with sales trends. Journal of Purchasing and Materials Management 13(4), 10–18.

    Article  Google Scholar 

  • Gamon M, Aue A, Corston-oliver S and Ringger E (2005) Pulse: mining customer opinions from free text. In 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8–10, 2005, Proceedings, Vol. 3646, p. 121, Springer.

  • Gao GG, Greenwood BN, Agarwal R and Jeffrey S (2015) Vocal minority and silent majority: how do online ratings reflect population perceptions of quality? MIS Quarterly 39(3), 565–589.

    Google Scholar 

  • Godes D and Silva JC (2012) Sequential and temporal dynamics of online opinion. Marketing Science 31(3), 448–473.

    Article  Google Scholar 

  • Goes PB, Lin M and Au Yeung C (2014) ‘Popularity effect’ in user-generated content: evidence from online product reviews. Information Systems Research 25(2), 222–238.

    Article  Google Scholar 

  • Golder PN and Tellis GJ (2004) Growing, growing, gone: cascades, diffusion, and turning points in the product life cycle. Marketing Science 23(2), 207–218.

    Article  Google Scholar 

  • Goldsmith RE, Freiden JB and Eastman JK (1995) The generality/specificity issue in consumer innovativeness research. Technovation 15(10), 601–612.

    Article  Google Scholar 

  • Goldsmith RE and Hofacker CF (1991) Measuring consumer innovativeness. Journal of the Academy of Marketing Science 19(3), 209–221.

    Article  Google Scholar 

  • Goldsmith RE and Newell SJ (1997) Innovativeness and price sensitivity: managerial, theoretical and methodological issues. Journal of Product & Brand Management 6(3), 163–174.

    Article  Google Scholar 

  • Greene WH (2000) Econometric Analysis (4th ed). Prentice-Hall, Upper Saddle River, NJ.

    Google Scholar 

  • Hausman JA (1978) Specification tests in econometrics. Econometrica 46(6), 1251–1271.

    Article  Google Scholar 

  • Hennig‐Thurau T, Gwinner KP, Walsh G and Gremler DD (2004) Electronic word‐of‐mouth via consumer‐opinion platforms: What motivates consumers to articulate themselves on the Internet? Journal of Interactive Marketing 18(1), 38–52.

    Article  Google Scholar 

  • Hirschman EC (1980) Innovativeness, novelty seeking, and consumer creativity. Journal of Consumer Research 7(3), 283–295.

    Article  Google Scholar 

  • Hoeffler S (2003) Measuring preferences for really new products. Journal of Marketing Research 40(4), 406–420.

    Article  Google Scholar 

  • Hoffer CW (1975) Toward a contingency theory of business strategy. Academy of Management Journal 18(4), 784–810.

    Article  Google Scholar 

  • Holbert RL (2014) DICTION as a tool for studying the mass media. In Communication and Language Analysis in the Public Sphere, pp 462–476, IGI Global.

  • Holbrook MB (1993) Nostalgia and consumption preferences: some emerging patterns of consumer tastes. Journal of Consumer Research 245–256.

  • Holsti OR (1969) Content Analysis for the Social Sciences and Humanities. Addison-Wesle, Reading, MA.

    Google Scholar 

  • Jahng J, Jain H and Ramamurthy K (2002) Personality traits and effectiveness of presentation of product information in e-business systems. European Journal of Information Systems 11(3), 181–195.

    Article  Google Scholar 

  • Kabacoff R (2015) R in Action: Data Analysis and Graphics with R. Manning Publications Co., Shelter Island, NY.

    Google Scholar 

  • Karande K, Merchant A and Sivakumar K (2011) Erratum to: relationships among time orientation, consumer innovativeness, and innovative behavior: the moderating role of product characteristics. AMS Review 1(2), 99–116.

    Article  Google Scholar 

  • Khammash M and Griffiths GH (2011) ‘Arrivederci CIAO.com, Buongiorno Bing.com’-Electronic word-of-mouth (eWOM), antecedences and consequences. International Journal of Information Management 31(1), 82–87.

    Article  Google Scholar 

  • Koski H and Kretschmer T (2007) Innovation and dominant design in mobile telephony. Industry and Innovation 14(3), 305–324.

    Article  Google Scholar 

  • Kotler P and Armstrong G (2010) Principles of Marketing. Pearson Education.

  • Kozinets RV (2002) The field behind the screen: using netnography for marketing research in online communities. Journal of Marketing Research 39(1), 61–72.

    Article  Google Scholar 

  • Krippendorff K (2008) Testing the reliability of content analysis data: what is involved and why. In The Content Analysis Reader (Krippendorff K and Bock MA, Eds), pp 350–357, Sage, Thousand Oaks, CA.

    Google Scholar 

  • Levitt T (1981) Marketing intangible products and product intangibles. Cornell Hotel and Restaurant Administration Quarterly 22(2), 37–44.

    Article  Google Scholar 

  • Li X and Hitt LM (2008) Self-selection and information role of online product reviews. Information Systems Research 19(4), 456–474.

    Article  Google Scholar 

  • Martinez E, Polo Y and Carlos F (1998) The acceptance and diffusion of new consumer durables: differences between first and last adopters. Journal of Consumer Marketing 15(4), 319–342.

    Article  Google Scholar 

  • Midgley DF (1976) A simple mathematical theory of innovative behavior. Journal of Consumer Research 3(1), 31–41.

    Article  Google Scholar 

  • Midgley DF (1977) Innovation and New Product Marketing. Halsted Press, John Wiley & Sons, Inc, New York.

  • Midgley DF and Dowling GR (1978) Innovativeness: the concept and its measurement. Journal of Consumer Research 4(4), 229–242.

    Article  Google Scholar 

  • Midgley DF and Dowling GR (1993) A longitudinal study of product form innovation: the interaction between predispositions and social messages. Journal of Consumer Research 19(4), 611–625.

    Article  Google Scholar 

  • Miller GA (1995) Word Net: a lexical database for english. Communications of the ACM 38(11), 39–41.

    Article  Google Scholar 

  • Moe WW and Schweidel DA (2012) Online product opinions: incidence, evaluation, and evolution. Marketing Science 31(3), 372–386.

    Article  Google Scholar 

  • Moon S, Bergey PK and Iacobucci D (2010) Dynamic effects among movie ratings, movie revenues, and viewer satisfaction. Journal of Marketing 74(1), 108–121.

    Article  Google Scholar 

  • Moore GA (1991) Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Consumers. HarperBusiness, New York.

    Google Scholar 

  • Mudambi SM and Schuff D (2010) What makes a helpful review? A study of customer reviews on Amazon.com. MIS Quarterly 34(1), 185–200.

    Google Scholar 

  • Nan HU, Pavlou PA and Jie Z (2009) Overcoming the J-shaped distribution of product reviews. Communications of the ACM 52(10), 144–147.

    Article  Google Scholar 

  • Nelson P (1970) Information and consumer behavior. Journal of Political Economy 78(2), 311–329.

    Article  Google Scholar 

  • Nelson P (1974) Advertising as information. Journal of Political Economy 82(4), 729–754.

    Article  Google Scholar 

  • Ober S, Zhao JJ, Davis R and Alexander MW (1999) Telling it like it is: the use of certainty in public business discourse. Journal of Business Communication 36(3), 280–300.

    Article  Google Scholar 

  • Ogden CK (1968) Basic English: International Second Language. Harcourt, Brace & World, New York.

  • Ostlund LE (1974) Perceived innovation attributes as predictors of innovativeness. Journal of Consumer Research 1(2), 23–29.

    Article  Google Scholar 

  • Pan Y and Zhang JQ (2011) Born unequal: a study of the helpfulness of user-generated product reviews. Journal of Retailing 87(4), 598–612.

    Article  Google Scholar 

  • Parasuraman A and Colby CL (2001) Techno-Ready Marketing: How and Why Your Customers Adopt Technology. Free Press, New York.

  • Peres R, Muller E and Mahajan V (2010) Innovation diffusion and new product growth models: a critical review and research directions. International Journal of Research in Marketing 27(2), 91–106.

    Article  Google Scholar 

  • Ram S and Jung H (1994) Innovativeness in product usage: A comparison of early adopters and early majority. Psychology and Marketing 11(1), 57–67.

    Article  Google Scholar 

  • Rao AR and Ruekert RW (1994) Brand alliances as signals of product quality. Sloan Management Review 36(1), 87.

    Google Scholar 

  • Rogers EM (1963) What are innovators like? Theory Into Practice 2(5), 252–256.

    Article  Google Scholar 

  • Rogers EM (1976) New product adoption and diffusion. Journal of Consumer Research 2(4), 290–301.

    Article  Google Scholar 

  • Rogers EM (1983) Diffusion of Innovations. A Division of Macmillan Publishing Co., New York.

    Google Scholar 

  • Rogers EM and Kincaid DL (1981) Communication Networks: Toward a New Paradigm for Research. Free Press, New York.

  • Rogers EM (2003) Diffusion of Innovations. Free Press, New York, NY.

    Google Scholar 

  • Sebastiani F (2002) Machine learning in automated text categorization. ACM Computing Surveys (CSUR) 34(1), 1–47.

    Article  Google Scholar 

  • Steenkamp JEBM, Hofstede FT and Wedel M (1999) A cross-national investigation into the individual and national cultural antecedents of consumer innovativeness. The Journal of Marketing 63(2), 55–69.

    Article  Google Scholar 

  • Stöckl R, Kosyak A, Walter B and Hess T (2006) Success factors of communities for user driven content: the case of Ciao.com. In AMCIS 2006 Proceedings, 525.

  • Tornatzky LG and Klein KJ (1982) Innovation characteristics and innovation adoption-implementation: a meta-analysis of findings. IEEE Transactions on Engineering Management 1, 28–45.

    Article  Google Scholar 

  • Van Den Bulte C and Lilien GL (2001) Medical innovation revisited: social contagion versus marketing effort. American Journal of Sociology 106(5), 1409–1435.

    Article  Google Scholar 

  • Van Der Heijden H, Verhagen T and Creemers M (2003) Understanding online purchase intentions: contributions from technology and trust perspectives. European Journal of Information Systems 12(1), 41–48.

    Article  Google Scholar 

  • Vogt CA and Fesenmaier DR (1998) Expanding the functional information search model. Annals of Tourism Research 25(3), 551–578.

    Article  Google Scholar 

  • Wei R (2001) From luxury to utility: a longitudinal analysis of cell phone laggards. Journalism and Mass Communication Quarterly 78(4), 702–719.

    Article  Google Scholar 

  • Winter B (2013) Linear models and linear mixed effects models in R with linguistic applications. arXiv preprint arXiv:1308.5499.

  • Wood SL and Moreau CP (2006) From fear to loathing? How emotion influences the evaluation and early use of innovations. Journal of Marketing 70(3), 44–57.

    Article  Google Scholar 

  • Wu F and Huberman BA (2008) How public opinion forms. In Internet and Network Economics, pp 334–341, Springer. http://link.springer.com/10.1007%2F978-3-540-92185-1_39.

  • Xu YC, Zhang C, Xue L and Yeo LL (2008) Product adoption in online social network. In ICIS 2008 Proceedings, 200.

  • Yubo C and Jinhong X (2008) Online consumer review: word-of-mouth as a new element of marketing communication mix. Management Science 54(3), 477–491.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Management, Henry W. Bloch School of Management, University of Missouri-Kansas City, Kansas City, MO, 64110, USA

    Roozmehr Safi

  2. Department of MIS, Marketing and Digital Business, Saunders College of Business, Rochester Institute of Technology, Rochester, NY, 14623, USA

    Yang Yu

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  1. Roozmehr Safi
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  2. Yang Yu
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Correspondence to Yang Yu.

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Editor: Prof. Dov Te’eni.

Associate Editor: Dr. Michael J Gallivan.

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Safi, R., Yu, Y. Online product review as an indicator of users’ degree of innovativeness and product adoption time: a longitudinal analysis of text reviews. Eur J Inf Syst 26, 414–431 (2017). https://doi.org/10.1057/s41303-017-0045-2

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  • DOI: https://doi.org/10.1057/s41303-017-0045-2

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