IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v70y2023ics096969892200234x.html
   My bibliography  Save this article

Impact of seller- and buyer-created content on product sales in the electronic commerce platform: The role of informativeness, readability, multimedia richness, and extreme valence

Author

Listed:
  • Cai, Xiaowei
  • Cebollada, Javier
  • Cortiñas, Mónica

Abstract

Due to the development of e-commerce, customers are rapidly shifting from passive receivers of information to content contributors. Two types of content coexist on modern e-commerce platforms like Amazon.com, called seller-created and buyer-created content. Extant literature suggests a range of factors that influence product sales on e-commerce platforms, including informativeness, readability, multimedia richness, and extreme valence. However, interactions among the mentioned factors from both seller-created and buyer-created content remain to be empirically verified. This research embeds dual processing theory and dual coding theory as theoretical foundations in the conceptual framework, which determines the interrelationships among key drivers that affect product sales. To verify the hypotheses, we collected the data from Amazon (n = 5248) and estimated the empirical model using partial least squares structural equation modelling (PLS-SEM). Among the results, it is highlighted that review informativeness fully mediated the influence of product description informativeness on product sales. While readability, multimedia richness, and extreme valence from buyer-created content exert both direct and moderating effects, the only factor from seller-created content that significantly affects product sales is multimedia richness. These findings confirm that, with the presence of customer reviews on product pages, sellers are losing control over the relevant information on their brands and products on the e-commerce platform: factors from buyer-created content are more directly influencing product sales. Nevertheless, sellers can still influence product sales by enhancing their content's informativeness and media richness.

Suggested Citation

  • Cai, Xiaowei & Cebollada, Javier & Cortiñas, Mónica, 2023. "Impact of seller- and buyer-created content on product sales in the electronic commerce platform: The role of informativeness, readability, multimedia richness, and extreme valence," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
  • Handle: RePEc:eee:joreco:v:70:y:2023:i:c:s096969892200234x
    DOI: 10.1016/j.jretconser.2022.103141
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096969892200234X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jretconser.2022.103141?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kaushik, Kapil & Mishra, Rajhans & Rana, Nripendra P. & Dwivedi, Yogesh K., 2018. "Exploring reviews and review sequences on e-commerce platform: A study of helpful reviews on Amazon.in," Journal of Retailing and Consumer Services, Elsevier, vol. 45(C), pages 21-32.
    2. Judith Chevalier & Austan Goolsbee, 2003. "Measuring Prices and Price Competition Online: Amazon.com and BarnesandNoble.com," Quantitative Marketing and Economics (QME), Springer, vol. 1(2), pages 203-222, June.
    3. Dhar, Vasant & Chang, Elaine A., 2009. "Does Chatter Matter? The Impact of User-Generated Content on Music Sales," Journal of Interactive Marketing, Elsevier, vol. 23(4), pages 300-307.
    4. Zhenhui Jiang & Izak Benbasat, 2007. "Research Note---Investigating the Influence of the Functional Mechanisms of Online Product Presentations," Information Systems Research, INFORMS, vol. 18(4), pages 454-470, December.
    5. Fang, Bin & Ye, Qiang & Kucukusta, Deniz & Law, Rob, 2016. "Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics," Tourism Management, Elsevier, vol. 52(C), pages 498-506.
    6. Wang, Feng & Liu, Xuefeng & Fang, Eric (Er), 2015. "User Reviews Variance, Critic Reviews Variance, and Product Sales: An Exploration of Customer Breadth and Depth Effects," Journal of Retailing, Elsevier, vol. 91(3), pages 372-389.
    7. Folkes, Valerie S, 1988. "Recent Attribution Research in Consumer Behavior: A Review and New Directions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(4), pages 548-565, March.
    8. Jonah Berger & Alan T. Sorensen & Scott J. Rasmussen, 2010. "Positive Effects of Negative Publicity: When Negative Reviews Increase Sales," Marketing Science, INFORMS, vol. 29(5), pages 815-827, 09-10.
    9. Dixit, Saumya & Jyoti Badgaiyan, Anant & Khare, Arpita, 2019. "An integrated model for predicting consumer's intention to write online reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 46(C), pages 112-120.
    10. Liu, Zhiwei & Park, Sangwon, 2015. "What makes a useful online review? Implication for travel product websites," Tourism Management, Elsevier, vol. 47(C), pages 140-151.
    11. Biehal, Gabriel & Chakravarti, Dipankar, 1983. "Information Accessibility as a Moderator of Consumer Choice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 10(1), pages 1-14, June.
    12. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    13. Crowley, Ayn E & Hoyer, Wayne D, 1994. "An Integrative Framework for Understanding Two-Sided Persuasion," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(4), pages 561-574, March.
    14. Evanschitzky, Heiner & Armstrong, J. Scott, 2013. "Research with In-built replications: Comment and further suggestions for replication research," Journal of Business Research, Elsevier, vol. 66(9), pages 1406-1408.
    15. Hartmann, Jochen & Huppertz, Juliana & Schamp, Christina & Heitmann, Mark, 2019. "Comparing automated text classification methods," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 20-38.
    16. Floyd, Kristopher & Freling, Ryan & Alhoqail, Saad & Cho, Hyun Young & Freling, Traci, 2014. "How Online Product Reviews Affect Retail Sales: A Meta-analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 217-232.
    17. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    18. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "When are extreme ratings more helpful? Empirical evidence on the moderating effects of review characteristics and product type," Post-Print hal-03511272, HAL.
    19. Maity, Moutusy & Dass, Mayukh & Kumar, Piyush, 2018. "The impact of media richness on consumer information search and choice," Journal of Business Research, Elsevier, vol. 87(C), pages 36-45.
    20. Pan, Yue & Zhang, Jason Q., 2011. "Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews," Journal of Retailing, Elsevier, vol. 87(4), pages 598-612.
    21. Biehal, Gabriel & Chakravarti, Dipankar, 1982. "Information-Presentation Format and Learning Goals as Determinants of Consumers' Memory Retrieval and Choice Processes," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 8(4), pages 431-441, March.
    22. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "When are extreme ratings more helpful? Empirical evidence on the moderating effects of review characteristics and product type," Grenoble Ecole de Management (Post-Print) halshs-01923243, HAL.
    23. Eslami, Seyed Pouyan & Ghasemaghaei, Maryam, 2018. "Effects of online review positiveness and review score inconsistency on sales: A comparison by product involvement," Journal of Retailing and Consumer Services, Elsevier, vol. 45(C), pages 74-80.
    24. Barnes, Stuart J., 2020. "Information management research and practice in the post-COVID-19 world," International Journal of Information Management, Elsevier, vol. 55(C).
    25. Andrew E. Wilson & Michael D. Giebelhausen & Michael K. Brady, 2017. "Negative word of mouth can be a positive for consumers connected to the brand," Journal of the Academy of Marketing Science, Springer, vol. 45(4), pages 534-547, July.
    26. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2019. "What moderates the influence of extremely negative ratings? The role of review and reviewer characteristics," Post-Print hal-03511270, HAL.
    27. Easley, Richard W. & Madden, Charles S. & Dunn, Mark G., 2000. "Conducting Marketing Science: The Role of Replication in the Research Process," Journal of Business Research, Elsevier, vol. 48(1), pages 83-92, April.
    28. Iris Vessey & Dennis Galletta, 1991. "Cognitive Fit: An Empirical Study of Information Acquisition," Information Systems Research, INFORMS, vol. 2(1), pages 63-84, March.
    29. Book, Laura A. & Tanford, Sarah & Chang, Wen, 2018. "Customer reviews are not always informative: The impact of effortful versus heuristic processing," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 272-280.
    30. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "When are extreme ratings more helpful? Empirical evidence on the moderating effects of review characteristics and product type," Post-Print halshs-01923243, HAL.
    31. Kai H. Lim & Izak Benbasat & Lawrence M. Ward, 2000. "The Role of Multimedia in Changing First Impression Bias," Information Systems Research, INFORMS, vol. 11(2), pages 115-136, June.
    32. Kim, Junyong & Gupta, Pranjal, 2012. "Emotional expressions in online user reviews: How they influence consumers' product evaluations," Journal of Business Research, Elsevier, vol. 65(7), pages 985-992.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhao, Ying & Guan, Zhi-min & Zhang, Jun, 2023. "Return freight strategies and selling formats in e-commerce supply chain: The perspective of consumer fairness concerns and online shopping returns," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    2. C, Deep Prakash & Majumdar, Adrija, 2023. "Predicting sports fans’ engagement with culturally aligned social media content: A language expectancy perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    3. Reimer, Thomas, 2023. "Environmental factors to maximize social media engagement: A comprehensive framework," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Moradi, Masoud & Dass, Mayukh & Kumar, Piyush, 2023. "Differential effects of analytical versus emotional rhetorical style on review helpfulness," Journal of Business Research, Elsevier, vol. 154(C).
    2. Yani Wang & Jun Wang & Tang Yao, 2019. "What makes a helpful online review? A meta-analysis of review characteristics," Electronic Commerce Research, Springer, vol. 19(2), pages 257-284, June.
    3. Yi, Jisu & Oh, Yun Kyung, 2022. "The informational value of multi-attribute online consumer reviews: A text mining approach," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    4. Zheng, Lili, 2021. "The classification of online consumer reviews: A systematic literature review and integrative framework," Journal of Business Research, Elsevier, vol. 135(C), pages 226-251.
    5. Filieri, Raffaele & Lin, Zhibin & Pino, Giovanni & Alguezaui, Salma & Inversini, Alessandro, 2021. "The role of visual cues in eWOM on consumers’ behavioral intention and decisions," Journal of Business Research, Elsevier, vol. 135(C), pages 663-675.
    6. Yi Luo & Xiaowei Xu, 2019. "Predicting the Helpfulness of Online Restaurant Reviews Using Different Machine Learning Algorithms: A Case Study of Yelp," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    7. Colmekcioglu, Nazan & Marvi, Reza & Foroudi, Pantea & Okumus, Fevzi, 2022. "Generation, susceptibility, and response regarding negativity: An in-depth analysis on negative online reviews," Journal of Business Research, Elsevier, vol. 153(C), pages 235-250.
    8. Sangjae Lee & Kun Chang Lee & Joon Yeon Choeh, 2020. "Using Bayesian Network to Predict Online Review Helpfulness," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    9. Raoofpanah, Iman & Zamudio, César & Groening, Christopher, 2023. "Review reader segmentation based on the heterogeneous impacts of review and reviewer attributes on review helpfulness: A study involving ZIP code data," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    10. Yi Feng & Yunqiang Yin & Dujuan Wang & Lalitha Dhamotharan & Joshua Ignatius & Ajay Kumar, 2023. "Diabetic patient review helpfulness: unpacking online drug treatment reviews by text analytics and design science approach," Annals of Operations Research, Springer, vol. 328(1), pages 387-418, September.
    11. Jin Li & Yulan Zhang & Jianping Li & Jiangze Du, 2023. "The Role of Sentiment Tendency in Affecting Review Helpfulness for Durable Products: Nonlinearity and Complementarity," Information Systems Frontiers, Springer, vol. 25(4), pages 1459-1477, August.
    12. Ismagilova, Elvira & Dwivedi, Yogesh K. & Slade, Emma, 2020. "Perceived helpfulness of eWOM: Emotions, fairness and rationality," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
    13. Ravula, Prashanth & Bhatnagar, Amit & Gauri, Dinesh K, 2023. "Role of gender in the creation and persuasiveness of online reviews," Journal of Business Research, Elsevier, vol. 154(C).
    14. Kim, Taeyong & Hwang, Seungsoo & Kim, Minkyung, 2022. "Text analysis of online customer reviews for products in the FCB quadrants: Procedure, outcomes, and implications," Journal of Business Research, Elsevier, vol. 150(C), pages 676-689.
    15. Li, Yuanshuo & Zhang, Zili & Pedersen, Susanne & Liu, Xudong & Zhang, Ziqiong, 2023. "The influence of relative popularity on negative fake reviews: A case study on restaurant reviews," Journal of Business Research, Elsevier, vol. 162(C).
    16. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    17. Elvira Ismagilova & Emma L. Slade & Nripendra P. Rana & Yogesh K. Dwivedi, 2020. "The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis," Information Systems Frontiers, Springer, vol. 22(5), pages 1203-1226, October.
    18. Agnieszka Zablocki & Bodo Schlegelmilch & Michael J. Houston, 2019. "How valence, volume and variance of online reviews influence brand attitudes," AMS Review, Springer;Academy of Marketing Science, vol. 9(1), pages 61-77, June.
    19. Yanni Ping & Chelsey Hill & Yun Zhu & Jorge Fresneda, 2023. "Antecedents and consequences of the key opinion leader status: an econometric and machine learning approach," Electronic Commerce Research, Springer, vol. 23(3), pages 1459-1484, September.
    20. Chen, Jie & Teng, Lefa & Yu, Ying & Yu, Xueer, 2016. "The effect of online information sources on purchase intentions between consumers with high and low susceptibility to informational influence," Journal of Business Research, Elsevier, vol. 69(2), pages 467-475.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:joreco:v:70:y:2023:i:c:s096969892200234x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-retailing-and-consumer-services .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.