IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v12y2022i2p21582440221094600.html
   My bibliography  Save this article

Recognition and Evaluation of Data as Intangible Assets

Author

Listed:
  • Feng Xiong
  • Maoyue Xie
  • Lingjuan Zhao
  • Cheng Li
  • Xuan Fan

Abstract

Internet-based companies such as Amazon, Facebook, and Tencent hold an enormous amount of consumer data that are utilized to create business value via big data analytics. Although some companies use big data to provide professional services, such as targeted advertising and product recommendations, according to the current CAS, IFRS, and U.S. GAAP accounting standards, these assets are not recognized as assets since they are generated internally. This paper starts with a discussion of how Amazon, Facebook, Tencent, and Walmart use big data to create value for their businesses and then argues why it makes sense to recognize big data as intangible assets. Possible methods of data asset evaluation and their implications for business managers are also explored.

Suggested Citation

  • Feng Xiong & Maoyue Xie & Lingjuan Zhao & Cheng Li & Xuan Fan, 2022. "Recognition and Evaluation of Data as Intangible Assets," SAGE Open, , vol. 12(2), pages 21582440221, April.
    • Handle: RePEc:sae:sagope:v:12:y:2022:i:2:p:21582440221094600
    DOI: 10.1177/21582440221094600
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440221094600
    Download Restriction: no
    File URL: https://libkey.io/10.1177/21582440221094600?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
    ---><---

    References listed on IDEAS

    as
    1. Mariani, Marcello M. & Fosso Wamba, Samuel, 2020. "Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies," Journal of Business Research, Elsevier, vol. 121(C), pages 338-352.
    2. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    3. Tatiana Garanina & Henri Hussinki & Johannes Dumay, 2021. "Accounting for intangibles and intellectual capital: a literature review from 2000 to 2020," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(4), pages 5111-5140, December.
    4. Janssen, Marijn & van der Voort, Haiko & Wahyudi, Agung, 2017. "Factors influencing big data decision-making quality," Journal of Business Research, Elsevier, vol. 70(C), pages 338-345.
    5. Lev, Baruch & Sougiannis, Theodore, 1996. "The capitalization, amortization, and value-relevance of R&D," Journal of Accounting and Economics, Elsevier, vol. 21(1), pages 107-138, February.
    6. Wamba, Samuel Fosso & Gunasekaran, Angappa & Akter, Shahriar & Ren, Steven Ji-fan & Dubey, Rameshwar & Childe, Stephen J., 2017. "Big data analytics and firm performance: Effects of dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 356-365.
    7. Anne Wyatt, 2008. "What financial and non‐financial information on intangibles is value‐relevant? A review of the evidence," Accounting and Business Research, Taylor & Francis Journals, vol. 38(3), pages 217-256.
    8. 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.
    9. Côrte-Real, Nadine & Oliveira, Tiago & Ruivo, Pedro, 2017. "Assessing business value of Big Data Analytics in European firms," Journal of Business Research, Elsevier, vol. 70(C), pages 379-390.
    10. Barth, ME & Clinch, G, 1998. "Revalued financial, tangible, and intangible assets: Associations with share prices and non-market-based value estimates," Journal of Accounting Research, Wiley Blackwell, vol. 36, pages 199-233.
    11. Elisabeth Dedman & Sulaiman Mouselli & Yun Shen & Andrew W. Stark, 2009. "Accounting, Intangible Assets, Stock Market Activity, and Measurement and Disclosure Policy—Views From the U.K," Abacus, Accounting Foundation, University of Sydney, vol. 45(3), pages 312-341, September.
    12. Sophie Cockcroft & Mark Russell, 2018. "Big Data Opportunities for Accounting and Finance Practice and Research," Australian Accounting Review, CPA Australia, vol. 28(3), pages 323-333, September.
    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. Paniti Netinant & Nattapat Saengsuwan & Meennapa Rukhiran & Sorapak Pukdesree, 2023. "Enhancing Data Management Strategies with a Hybrid Layering Framework in Assessing Data Validation and High Availability Sustainability," Sustainability, MDPI, vol. 15(20), pages 1-28, October.

    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. Nguyen Anh Khoa Dam & Thang Le Dinh & William Menvielle, 2019. "A systematic literature review of big data adoption in internationalization," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 182-195, September.
    2. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    3. Ghasemaghaei, Maryam & Calic, Goran, 2019. "Does big data enhance firm innovation competency? The mediating role of data-driven insights," Journal of Business Research, Elsevier, vol. 104(C), pages 69-84.
    4. 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.
    5. Ashrafi, Amir & Zare Ravasan, Ahad & Trkman, Peter & Afshari, Samira, 2019. "The role of business analytics capabilities in bolstering firms’ agility and performance," International Journal of Information Management, Elsevier, vol. 47(C), pages 1-15.
    6. Wilkin, Carla & Ferreira, Aldónio & Rotaru, Kristian & Gaerlan, Luigi Red, 2020. "Big data prioritization in SCM decision-making: Its role and performance implications," International Journal of Accounting Information Systems, Elsevier, vol. 38(C).
    7. Dinh, Tami & Schultze, Wolfgang, 2022. "Accounting for R&D on the income statement? Evidence on non-discretionary vs. discretionary R&D capitalization under IFRS in Germany," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 46(C).
    8. Shamim, Saqib & Zeng, Jing & Khan, Zaheer & Zia, Najam Ul, 2020. "Big data analytics capability and decision making performance in emerging market firms: The role of contractual and relational governance mechanisms," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    9. Osama Musa Ali Al-Darras & Cem Tanova, 2022. "From Big Data Analytics to Organizational Agility: What Is the Mechanism?," SAGE Open, , vol. 12(2), pages 21582440221, June.
    10. Claudio Vitari & Elisabetta Raguseo, 2019. "Big data analytics business value and firm performance: Linking with environmental context," Post-Print hal-02293765, HAL.
    11. Morimura, Fumikazu & Sakagawa, Yuji, 2023. "The intermediating role of big data analytics capability between responsive and proactive market orientations and firm performance in the retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    12. Brinch, Morten & Gunasekaran, Angappa & Fosso Wamba, Samuel, 2021. "Firm-level capabilities towards big data value creation," Journal of Business Research, Elsevier, vol. 131(C), pages 539-548.
    13. Elisabetta Raguseo & Claudio Vitari, 2017. "Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects," Grenoble Ecole de Management (Post-Print) halshs-01923259, HAL.
    14. Liedong, Tahiru Azaaviele & Rajwani, Tazeeb & Lawton, Thomas C., 2020. "Information and nonmarket strategy: Conceptualizing the interrelationship between big data and corporate political activity," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    15. Dawn Iacobucci & Maria Petrescu & Anjala Krishen & Michael Bendixen, 2019. "The state of marketing analytics in research and practice," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 152-181, September.
    16. Sebastiano Cupertino & Gianluca Vitale & Angelo Riccaboni, 2018. "L?impatto dei Big Data sulle attivit? di pianificazione & controllo aziendali: In caso di studio di una PMI agricola Italiana," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2018(3), pages 59-86.
    17. Côrte-Real, Nadine & Ruivo, Pedro & Oliveira, Tiago & Popovič, Aleš, 2019. "Unlocking the drivers of big data analytics value in firms," Journal of Business Research, Elsevier, vol. 97(C), pages 160-173.
    18. Ashrafi, Amir & Zareravasan, Ahad, 2022. "An ambidextrous approach on the business analytics-competitive advantage relationship: Exploring the moderating role of business analytics strategy," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    19. Alberto Bertello & Alberto Ferraris & Stefano Bresciani & Paola Bernardi, 2021. "Big data analytics (BDA) and degree of internationalization: the interplay between governance of BDA infrastructure and BDA capabilities," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 25(4), pages 1035-1055, December.
    20. Oliveira, Lídia & Rodrigues, Lúcia Lima & Craig, Russell, 2010. "Intangible assets and value relevance: Evidence from the Portuguese stock exchange," The British Accounting Review, Elsevier, vol. 42(4), pages 241-252.

    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:sae:sagope:v:12:y:2022:i:2:p:21582440221094600. 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: SAGE Publications (email available below). General contact details of provider: .

    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.