IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v174y2022ics0040162521006995.html
   My bibliography  Save this article

Can customer sentiment impact firm value? An integrated text mining approach

Author

Listed:
  • Eachempati, Prajwal
  • Srivastava, Praveen Ranjan
  • Kumar, Ajay
  • Muñoz de Prat, Javier
  • Delen, Dursun

Abstract

Developing measures to capture customer sentiment and securing a positive customer experience is a strategic necessity to improve firm profitability and shareholder value. The paper considers the relationship between customer satisfaction, earnings, and firm value as these drives change in stock prices, customer, and investor sentiment. The present study investigates the impact of customer sentiment polarity on stock prices based on Indian automobile sector databased such as the Indian Nifty Auto SNE (Maruti Suzuki, Tata Motors, and Eicher). A top-down approach is adopted to construct a financial proxy-based sentiment index completed with sentiment extracted from automobile news and customer reviews. The paper uses a text mining approach to holistically measure customer sentiment's impact on investor sentiment and stock prices. The study was initially performed at the overall individual stock from the Nifty Auto NSE but focused on the top three passenger vehicle manufacturing companies i.e., Maruti Suzuki, Tata Motors, and Eicher. It was found that the sentiment index was augmented with news and customer reviews allows predicting more accurately NIFTY AUTO stock price movements. This implies that customer sentiment is a major driver of investor sentiment which in turn impacts the stock market and the firm value. Thus, the present study is an integrated approach to holistically measure customer sentiment's impact on investor sentiment and stock prices.

Suggested Citation

  • Eachempati, Prajwal & Srivastava, Praveen Ranjan & Kumar, Ajay & Muñoz de Prat, Javier & Delen, Dursun, 2022. "Can customer sentiment impact firm value? An integrated text mining approach," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
  • Handle: RePEc:eee:tefoso:v:174:y:2022:i:c:s0040162521006995
    DOI: 10.1016/j.techfore.2021.121265
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521006995
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2021.121265?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. Sengupta, Pooja & Biswas, Baidyanath & Kumar, Ajay & Shankar, Ravi & Gupta, Shivam, 2021. "Examining the predictors of successful Airbnb bookings with Hurdle models: Evidence from Europe, Australia, USA and Asia-Pacific cities," Journal of Business Research, Elsevier, vol. 137(C), pages 538-554.
    2. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    3. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    4. R Bird & R Gerlach & AD Hall, 2001. "The prediction of earnings movements using accounting data: An update and extension of Ou and Penman," Journal of Asset Management, Palgrave Macmillan, vol. 2(2), pages 180-195, September.
    5. Feng Gu & Weimin Wang, 2005. "Intangible Assets, Information Complexity, and Analysts' Earnings Forecasts," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 32(9-10), pages 1673-1702.
    6. Shivam Gupta & Théo Justy & Shampy Kamboj & Ajay Kumar & Eivind Kristoffersen, 2021. "Big data and firm marketing performance: Findings from knowledge-based view," Post-Print hal-03609916, HAL.
    7. Kothari, S. P., 2001. "Capital markets research in accounting," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 105-231, September.
    8. Ivanov, Vladimir & Joseph, Kissan & Wintoki, M. Babajide, 2013. "Disentangling the market value of customer satisfaction: Evidence from market reaction to the unanticipated component of ACSI announcements," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 168-178.
    9. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    10. Germann, Frank & Lilien, Gary L. & Rangaswamy, Arvind, 2013. "Performance implications of deploying marketing analytics," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 114-128.
    11. Robert Jacobson & Natalie Mizik, 2009. "—Customer Satisfaction-Based Mispricing: Issues and Misconceptions," Marketing Science, INFORMS, vol. 28(5), pages 836-845, 09-10.
    12. Daniel Huerta-Sanchez & Diego Escobari, 2018. "Changes in sentiment on REIT industry excess returns and volatility," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(3), pages 239-274, August.
    13. Ahir Gopaldas, 2014. "Marketplace Sentiments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 41(4), pages 995-1014.
    14. Yadong Luo & Rosalie L Tung, 2007. "International expansion of emerging market enterprises: A springboard perspective," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 38(4), pages 481-498, July.
    15. Zhen-Hua Yang & Jian-Guo Liu & Chang-Rui Yu & Jing-Ti Han, 2017. "Quantifying the effect of investors’ attention on stock market," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-16, May.
    16. Natalie Mizik & Robert Jacobson, 2007. "Myopic Marketing Management: Evidence of the Phenomenon and Its Long-Term Performance Consequences in the SEO Context," Marketing Science, INFORMS, vol. 26(3), pages 361-379, 05-06.
    17. Gupta, Shivam & Justy, Théo & Kamboj, Shampy & Kumar, Ajay & Kristoffersen, Eivind, 2021. "Big data and firm marketing performance: Findings from knowledge-based view," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    18. Bicha Karim, 2011. "Corporate name change and shareholder wealth effect: Empirical evidence in the French Stock Market," Journal of Asset Management, Palgrave Macmillan, vol. 12(3), pages 203-213, August.
    19. Seshadri Tirunillai & Gerard J. Tellis, 2012. "Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance," Marketing Science, INFORMS, vol. 31(2), pages 198-215, March.
    20. Patrick Jochem & Jonatan J. Gómez Vilchez & Axel Ensslen & Johannes Schäuble & Wolf Fichtner, 2018. "Methods for forecasting the market penetration of electric drivetrains in the passenger car market," Transport Reviews, Taylor & Francis Journals, vol. 38(3), pages 322-348, May.
    21. Keith Anderson & Chris Brooks, 2006. "Decomposing the price-earnings ratio," Journal of Asset Management, Palgrave Macmillan, vol. 6(6), pages 456-469, March.
    22. Mooweon Rhee & Pamela R. Haunschild, 2006. "The Liability of Good Reputation: A Study of Product Recalls in the U.S. Automobile Industry," Organization Science, INFORMS, vol. 17(1), pages 101-117, February.
    23. Schmalz, Ulrike & Ringbeck, Jürgen & Spinler, Stefan, 2021. "Door-to-door air travel: Exploring trends in corporate reports using text classification models," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    24. Verhoef, Peter C. & Lemon, Katherine N. & Parasuraman, A. & Roggeveen, Anne & Tsiros, Michael & Schlesinger, Leonard A., 2009. "Customer Experience Creation: Determinants, Dynamics and Management Strategies," Journal of Retailing, Elsevier, vol. 85(1), pages 31-41.
    25. Eachempati, Prajwal & Srivastava, Praveen Ranjan & Kumar, Ajay & Tan, Kim Hua & Gupta, Shivam, 2021. "Validating the impact of accounting disclosures on stock market: A deep neural network approach," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    26. Ahir Gopaldas, 2014. "Marketplace Sentiments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 41(4), pages 995-1014.
    27. Robert Merrin & Arvid Hoffmann & Joost Pennings, 2013. "Customer satisfaction as a buffer against sentimental stock-price corrections," Marketing Letters, Springer, vol. 24(1), pages 13-27, March.
    28. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 1-27, January.
    29. Trappey, Amy & Trappey, Charles V. & Hsieh, Alex, 2021. "An intelligent patent recommender adopting machine learning approach for natural language processing: A case study for smart machinery technology mining," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    30. Kumar, Ravi & Lamba, Kuldeep & Raman, Avinash, 2021. "Role of zero emission vehicles in sustainable transformation of the Indian automobile industry," Research in Transportation Economics, Elsevier, vol. 90(C).
    31. Feng Gu & Weimin Wang, 2005. "Intangible Assets, Information Complexity, and Analysts’ Earnings Forecasts," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 32(9‐10), pages 1673-1702, November.
    32. Chung, San-Lin & Hung, Chi-Hsiou & Yeh, Chung-Ying, 2012. "When does investor sentiment predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 217-240.
    33. Choi, Jaewoong & Oh, Seunghyun & Yoon, Janghyeok & Lee, Jae-Min & Coh, Byoung-Youl, 2020. "Identification of time-evolving product opportunities via social media mining," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    34. Li, Xin & Xie, Qianqian & Daim, Tugrul & Huang, Lucheng, 2019. "Forecasting technology trends using text mining of the gaps between science and technology: The case of perovskite solar cell technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 432-449.
    35. Christopher Ittner & David Larcker & Daniel Taylor, 2009. "—The Stock Market's Pricing of Customer Satisfaction," Marketing Science, INFORMS, vol. 28(5), pages 826-835, 09-10.
    36. Westbrook, Robert A & Oliver, Richard L, 1991. "The Dimensionality of Consumption Emotion Patterns and Consumer Satisfaction," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(1), pages 84-91, June.
    37. Ulrike Malmendier & Geoffrey Tate & Jon Yan, 2011. "Overconfidence and Early‐Life Experiences: The Effect of Managerial Traits on Corporate Financial Policies," Journal of Finance, American Finance Association, vol. 66(5), pages 1687-1733, October.
    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. Sook Fern Yeo & Cheng Ling Tan & Ajay Kumar & Kim Hua Tan & Jee Kit Wong, 2022. "Investigating the impact of AI-powered technologies on Instagrammers’ purchase decisions in digitalization era–A study of the fashion and apparel industry," Post-Print hal-03628402, HAL.
    2. Yeo, Sook Fern & Tan, Cheng Ling & Kumar, Ajay & Tan, Kim Hua & Wong, Jee Kit, 2022. "Investigating the impact of AI-powered technologies on Instagrammers’ purchase decisions in digitalization era–A study of the fashion and apparel industry," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    3. Chatterjee, Sheshadri & Chaudhuri, Ranjan & González, Vanessa Izquierdo & Kumar, Ajay & Singh, Sanjay Kumar, 2022. "Resource integration and dynamic capability of frontline employee during COVID-19 pandemic: From value creation and engineering management perspectives," Technological Forecasting and Social Change, Elsevier, vol. 176(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. Ron Bird & Daniel Choi & Danny Yeung, 2014. "Market uncertainty, market sentiment, and the post-earnings announcement drift," Review of Quantitative Finance and Accounting, Springer, vol. 43(1), pages 45-73, July.
    2. Lutz, Chandler, 2015. "The impact of conventional and unconventional monetary policy on investor sentiment," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 89-105.
    3. Fredström, Ashkan & Parida, Vinit & Wincent, Joakim & Sjödin, David & Oghazi, Pejvak, 2022. "What is the Market Value of Artificial Intelligence and Machine Learning? The Role of Innovativeness and Collaboration for Performance," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    4. Nawaf Almaskati & Ron Bird & Yue Lu & Danny Leung, 2019. "Corporate Governance, Information Uncertainty and Market Reaction to Information Signals," Working Papers in Economics 19/15, University of Waikato.
    5. Wang, Wenzhao & Duxbury, Darren, 2021. "Institutional investor sentiment and the mean-variance relationship: Global evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 415-441.
    6. John Garcia, 2021. "Analyst herding and firm-level investor sentiment," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(4), pages 461-494, December.
    7. Guo, Kun & Sun, Yi & Qian, Xin, 2017. "Can investor sentiment be used to predict the stock price? Dynamic analysis based on China stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 390-396.
    8. Tsung-Yu Hsieh & Huai-I Lee & Ying-Ru Tsai, 2018. "Idiosyncratic Risk, Stock Returns and Investor Sentiment," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 8(7), pages 914-924, July.
    9. Aissia, Dorsaf Ben, 2016. "Home and foreign investor sentiment and the stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 71-77.
    10. Ralph Yang-Cheng Lu & Hsiu-Chuan Lee & Peter Chiu, 2014. "Institutional Investor Sentiment and Market Returns: Evidence from the Taiwan Futures Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 140-167, December.
    11. Møller, Stig V. & Nørholm, Henrik & Rangvid, Jesper, 2014. "Consumer confidence or the business cycle: What matters more for European expected returns?," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 230-248.
    12. Yeo, Sook Fern & Tan, Cheng Ling & Kumar, Ajay & Tan, Kim Hua & Wong, Jee Kit, 2022. "Investigating the impact of AI-powered technologies on Instagrammers’ purchase decisions in digitalization era–A study of the fashion and apparel industry," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    13. Wu-Yueh Hu & Heng-Yu Chang, 2018. "Investor Sentiment, Corporate Transparency and Market Returns: Evidence from Taiwan Intraday Data," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 8(6), pages 1-4.
    14. Saade, Samer, 2015. "Investor sentiment and the underperformance of technology firms initial public offerings," Research in International Business and Finance, Elsevier, vol. 34(C), pages 205-232.
    15. N. S. Nanayakkara & P. D. Nimal & Y. K. Weerakoon, 2019. "Behavioural Asset Pricing: A Review," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 101-108.
    16. O'Sullivan, Don & Hutchinson, Mark C. & O'Connell, Vincent, 2009. "Empirical evidence of the stock market's (mis)pricing of customer satisfaction," International Journal of Research in Marketing, Elsevier, vol. 26(2), pages 154-161.
    17. Azilawati Banchit & Sazali Abidin & Sophyafadeth Lim & Fareiny Morni, 2020. "Investor Sentiment, Portfolio Returns, and Macroeconomic Variables," JRFM, MDPI, vol. 13(11), pages 1-14, October.
    18. Ahmed Salhin & Mo Sherif & Edward Jones, 2016. "Investor Sentiment and Sector Returns," CFI Discussion Papers 1602, Centre for Finance and Investment, Heriot Watt University.
    19. Mabel D Costa & Ahsan Habib, 2023. "Cost stickiness and firm value," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 34(2), pages 235-273, June.
    20. Yao, Can-Zhong & Li, Hong-Yu, 2020. "Time-varying lead–lag structure between investor sentiment and stock market," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).

    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:tefoso:v:174:y:2022:i:c:s0040162521006995. 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: http://www.sciencedirect.com/science/journal/00401625 .

    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.