IDEAS home Printed from https://ideas.repec.org/a/spr/elcore/v18y2018i1d10.1007_s10660-017-9279-2.html
   My bibliography  Save this article

Product innovation based on online review data mining: a case study of Huawei phones

Author

Listed:
  • Hui Zhang

    (Hangzhou Dianzi University)

  • Huguang Rao

    (Hangzhou Dianzi University)

  • Junzheng Feng

    (Hangzhou Dianzi University)

Abstract

Online reviews contain a plethora of useful information that plays a vital role in consumer choices and provides a dominant reference for enterprises to adopt strategies for product development and improvement. The paper examines the www.zol.com.cn website as a source of information and Huawei Mate phones as a research target, processes the data of consumers’ online reviews on three types of Huawei Mate phones, discusses the correlations between online reviews and phone improvement, and proposes some suggestions for future product improvement. This empirical study shows that the correlation between the change in the degree of feature satisfaction and phone improvement is strong; the correlation between the change in the degree of feature satisfaction and product improvement is stronger than that between the change in the degree of feature attention and product improvement. Enterprises can determine the direction and contents of phone improvement based on information from reviews on its preceding phone model. This study can help enterprises master market requirements, understand consumers’ behaviour and improve the quality and efficiency of product innovation.

Suggested Citation

  • Hui Zhang & Huguang Rao & Junzheng Feng, 2018. "Product innovation based on online review data mining: a case study of Huawei phones," Electronic Commerce Research, Springer, vol. 18(1), pages 3-22, March.
    • Handle: RePEc:spr:elcore:v:18:y:2018:i:1:d:10.1007_s10660-017-9279-2
    DOI: 10.1007/s10660-017-9279-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10660-017-9279-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10660-017-9279-2?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. Yingtao Shen & Shenyu Li & Michelle DeMoss, 2012. "The Effect Of Quantitative Electronic Word Of Mouth On Consumer Perceived Product Quality," International Journal of Management and Marketing Research, The Institute for Business and Finance Research, vol. 5(2), pages 19-29.
    2. Ewa Genge, 2014. "A latent class analysis of the public attitude towards the euro adoption in Poland," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(4), pages 427-442, December.
    3. Schneider, Matthew J. & Gupta, Sachin, 2016. "Forecasting sales of new and existing products using consumer reviews: A random projections approach," International Journal of Forecasting, Elsevier, vol. 32(2), pages 243-256.
    4. Changli Zhang & Daniel Zeng & Jiexun Li & Fei‐Yue Wang & Wanli Zuo, 2009. "Sentiment analysis of Chinese documents: From sentence to document level," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(12), pages 2474-2487, December.
    5. Xu, Zhenning & Frankwick, Gary L. & Ramirez, Edward, 2016. "Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective," Journal of Business Research, Elsevier, vol. 69(5), pages 1562-1566.
    6. Chen, Yubo & Fay, Scott & Wang, Qi, 2011. "The Role of Marketing in Social Media: How Online Consumer Reviews Evolve," Journal of Interactive Marketing, Elsevier, vol. 25(2), pages 85-94.
    7. von Hippel, Eric, 1976. "The dominant role of users in the scientific instrument innovation process," Research Policy, Elsevier, vol. 5(3), pages 212-239, July.
    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. 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.
    10. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    11. Ulusoy, Gunduz, 2003. "An assessment of supply chain and innovation management practices in the manufacturing industries in Turkey," International Journal of Production Economics, Elsevier, vol. 86(3), pages 251-270, December.
    12. Haverila, Matti, 2011. "Mobile phone feature preferences, customer satisfaction and repurchase intent among male users," Australasian marketing journal, Elsevier, vol. 19(4), pages 238-246.
    13. Oded Netzer & Ronen Feldman & Jacob Goldenberg & Moshe Fresko, 2012. "Mine Your Own Business: Market-Structure Surveillance Through Text Mining," Marketing Science, INFORMS, vol. 31(3), pages 521-543, May.
    14. Thomas Lee, 2007. "Constraint-based Ontology Induction from Online Customer Reviews," Group Decision and Negotiation, Springer, vol. 16(3), pages 255-281, May.
    15. Garrett P. Sonnier & Leigh McAlister & Oliver J. Rutz, 2011. "A Dynamic Model of the Effect of Online Communications on Firm Sales," Marketing Science, INFORMS, vol. 30(4), pages 702-716, July.
    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. Yanlai Li & Zifan Shen & Cuiming Zhao & Kwai-Sang Chin & Xuwei Lang, 2024. "Understanding Customer Opinion Change on Fresh Food E-Commerce Products and Services—Comparative Analysis before and during COVID-19 Pandemic," Sustainability, MDPI, vol. 16(7), pages 1-22, March.
    2. Dan Ke & Heci Zhang & Ning Yu & Yanbin Tu, 2021. "Who will stay with the brand after posting non-5/5 rating of purchase? An empirical study of online consumer repurchase behavior," Information Systems and e-Business Management, Springer, vol. 19(2), pages 405-437, June.
    3. Yuanyuan Guo & Yanqing Wang & Chaoyou Wang, 2019. "Exploring the Salient Attributes of Short-Term Rental Experience: An Analysis of Online Reviews from Chinese Guests," Sustainability, MDPI, vol. 11(16), pages 1-19, August.
    4. Mustak, Mekhail & Salminen, Joni & Plé, Loïc & Wirtz, Jochen, 2021. "Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda," Journal of Business Research, Elsevier, vol. 124(C), pages 389-404.
    5. Shugang Li & Fang Liu & Yuqi Zhang & Boyi Zhu & He Zhu & Zhaoxu Yu, 2022. "Text Mining of User-Generated Content (UGC) for Business Applications in E-Commerce: A Systematic Review," Mathematics, MDPI, vol. 10(19), pages 1-26, September.
    6. Kyungbo Park & Jeonghwa Cha & Jongyi Hong, 2023. "Developing a Framework for Evaluating and Predicting Management Innovation in Public Research Institutions," Sustainability, MDPI, vol. 15(9), pages 1-18, April.
    7. Huang, Shupeng & Potter, Andrew & Eyers, Daniel & Li, Qinyun, 2021. "The influence of online review adoption on the profitability of capacitated supply chains," Omega, Elsevier, vol. 105(C).
    8. Jianping Li & Yinhong Yao & Yuanjie Xu & Jingyu Li & Lu Wei & Xiaoqian Zhu, 2019. "Consumer’s risk perception on the Belt and Road countries: evidence from the cross-border e-commerce," Electronic Commerce Research, Springer, vol. 19(4), pages 823-840, December.
    9. Cui, Xiling & Zhu, Zhongshan & Liu, Libo & Zhou, Qiang & Liu, Qiang, 2024. "Anomaly detection in consumer review analytics for idea generation in product innovation: Comparing machine learning and deep learning techniques," Technovation, Elsevier, vol. 134(C).
    10. Xiangfeng Luo & Yawen Yi, 2019. "Topic-Specific Emotion Mining Model for Online Comments," Future Internet, MDPI, vol. 11(3), pages 1-18, March.
    11. Xiaoguang Wang & Tao Lv & Lei Fan, 2022. "New Energy Vehicle Consumer Demand Mining Research Based on Fusion Topic Model: A Case in China," Sustainability, MDPI, vol. 14(6), pages 1-13, March.
    12. Satish Kumar & Weng Marc Lim & Nitesh Pandey & J. Christopher Westland, 2021. "20 years of Electronic Commerce Research," Electronic Commerce Research, Springer, vol. 21(1), pages 1-40, March.

    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. Peters, Kay & Chen, Yubo & Kaplan, Andreas M. & Ognibeni, Björn & Pauwels, Koen, 2013. "Social Media Metrics — A Framework and Guidelines for Managing Social Media," Journal of Interactive Marketing, Elsevier, vol. 27(4), pages 281-298.
    2. Kick, Markus, 2015. "Social Media Research: A Narrative Review," EconStor Preprints 182506, ZBW - Leibniz Information Centre for Economics.
    3. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
    4. 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.
    5. 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.
    6. 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.
    7. Kyungmin Park & Stephanie Lee & Shahryar Doosti & Yong Tan, 2023. "Provision of helpful review videos: Effects of video characteristics on perceived helpfulness," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2031-2048, July.
    8. Bitty Balducci & Detelina Marinova, 2018. "Unstructured data in marketing," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 557-590, July.
    9. Juan Feng & Xin Li & Xiaoquan (Michael) Zhang, 2019. "Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence," Information Systems Research, INFORMS, vol. 30(4), pages 1107-1123, December.
    10. 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.
    11. Xianghua Lu & Sulin Ba & Lihua Huang & Yue Feng, 2013. "Promotional Marketing or Word-of-Mouth? Evidence from Online Restaurant Reviews," Information Systems Research, INFORMS, vol. 24(3), pages 596-612, September.
    12. Gensler, Sonja & Völckner, Franziska & Liu-Thompkins, Yuping & Wiertz, Caroline, 2013. "Managing Brands in the Social Media Environment," Journal of Interactive Marketing, Elsevier, vol. 27(4), pages 242-256.
    13. Foster, Joshua, 2022. "How rating mechanisms shape user search, quality inference and engagement in online platforms: Experimental evidence," Journal of Business Research, Elsevier, vol. 142(C), pages 791-807.
    14. Xueming Luo & Jie Zhang & Wenjing Duan, 2013. "Social Media and Firm Equity Value," Information Systems Research, INFORMS, vol. 24(1), pages 146-163, March.
    15. Qingfeng Zeng & Qian Guo & Wei Zhuang & Yu Zhang & Weiguo Fan, 2023. "Do Real-Time Reviews Matter? Examining how Bullet Screen Influences Consumers’ Purchase Intention in Live Streaming Commerce," Information Systems Frontiers, Springer, vol. 25(5), pages 2051-2067, October.
    16. Tingting Nian & Yuheng Hu & Cheng Chen, 2021. "Examining the Impact of Television-Program-Induced Emotions on Online Word-of-Mouth Toward Television Advertising," Information Systems Research, INFORMS, vol. 32(2), pages 605-632, June.
    17. Schmidt, Christoph G. & Wuttke, David A. & Heese, H. Sebastian & Wagner, Stephan M., 2023. "Antecedents of public reactions to supply chain glitches," International Journal of Production Economics, Elsevier, vol. 259(C).
    18. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    19. Tingting Song & Jinghua Huang & Yong Tan & Yifan Yu, 2019. "Using User- and Marketer-Generated Content for Box Office Revenue Prediction: Differences Between Microblogging and Third-Party Platforms," Service Science, INFORMS, vol. 30(1), pages 191-203, March.
    20. Sungsik Park & Woochoel Shin & Jinhong Xie, 2021. "The Fateful First Consumer Review," Marketing Science, INFORMS, vol. 40(3), pages 481-507, May.

    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:spr:elcore:v:18:y:2018:i:1:d:10.1007_s10660-017-9279-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.