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The impact of early XBRL adoption on analysts’ forecast accuracy - empirical evidence from China

Abstract

Developing common standards, such as eXtensible Business Reporting Language (XBRL), to smoothen information sharing in the value chain is considered the leading issue for releasing the potential of e-business. Data standards such as XBRL play a critical role in an increasingly networked environment. Despite promises of XBRL to improve data accuracy, few empirical studies have tested the impact of early XBRL adoption on the quality of information. Theories explaining information technology (IT) productivity paradox indicate that value realization from IT innovations may experience time lag due to the need for technology refinement and diffusion. This study examines the impact of early adoption of XBRL on analysts’ forecast accuracy with empirical data of Chinese firms. The uncertainty related to the unproven technology, such as information errors, has decreased analysts’ forecast accuracy during the early adoption period among firms in an economy with little public information on listed firms. Our findings have practical implications that will facilitate the quality improvement of financial information in a networked business environment. Our findings highlight the importance of quality assurance and policy enforcement for value realization from XBRL adoption to regulators, filers, information consumers, the accounting profession and other stakeholders.

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References

  1. Acker, D., Horton, J., & Tonks, I. (2002). Accounting standards and biased earnings? The role of reported earnings in explaining apparent bias and over/underreaction in analysts’ earnings forecasts. Journal of Accounting and Economics, 36(1–3), 105–146.

    Google Scholar 

  2. Alford, A., & Berger, P. (1999). A simultaneous equations analysis of forecast accuracy, analyst following, and trading volume. Journal of Accounting, Auditing, and Finance, 14(3), 219–240.

    Google Scholar 

  3. Barniv, R. (2009). Does foreign investor demand for information affect forecast accuracy? Evidence from the Chinese stock markets. Journal of International Accounting, Auditing, and Taxation, 18, 101–118.

    Article  Google Scholar 

  4. Barron, O. E., Kile, C. O., & O’Keefe, T. B. (1999). MD&A quality as measured by the SEC and analysts’ earnings forecasts. Contemporary Accounting Research, 16(1), 75–109.

    Article  Google Scholar 

  5. Bonson, E., Cortijo, V., & Escobar, T. (2009). Towards, the global adoption of XBRL using international financial reporting standards. International Journal of Accounting Information Systems, 10, 46–60.

    Article  Google Scholar 

  6. Boritz, J. E., & No, W. G. (2009). Assurance on XBRL-related documents: the case of united technologies corporation. Journal of Information Systems, 23, 49–78.

    Article  Google Scholar 

  7. Bradshaw, M., Richardson, S., & Sloan, R. (2006). The relation between corporate financing activities, analysts’ forecasts and stock returns. Journal of Accounting and Economics, 42, 53–85.

    Article  Google Scholar 

  8. Brown, L. (1993). Earnings forecasting research: its implications for capital markets research. International Journal of Forecasting, 9(3), 295–320.

    Article  Google Scholar 

  9. Brown, L. D. (1997). Analysts forecasts errors: additional evidence. Financial Analysts Journal, 53, 81–88.

    Article  Google Scholar 

  10. Burgstahler, D. C., Hail, L., & Leuz, C. (2006). The importance of reporting incentives: earnings management in European private and public firms. The Accounting Review, 81(5), 983–1016.

    Google Scholar 

  11. Chang, C., & Jarvenpaa, S. (2005). Pace of information systems standards development and implementation: the case of XBRL. Electronic Markets, 15(4), 365–377.

    Article  Google Scholar 

  12. Chang, L. S., & Most, K. S. (1985). The perceived usefulness of financial statements for investors’ decisions. Gainesville: University Presses of Florida.

    Google Scholar 

  13. Chen, C. J., Chen, S. M., & Su, X. J. (2001). Is accounting information value-relevant in the emerging Chinese stock market? Journal of International Accounting, Auditing, and Taxation, 10(1), 1–22.

    Article  Google Scholar 

  14. Chen, S., Sun, Z., & Wang, Y. (2002). Evidence from China on whether a harmonized accounting standard harmonizes accounting practices. Accounting Horizons, 16(3), 183–197.

    Article  Google Scholar 

  15. Coen, A., Desfleurs, A., & L’Her, J. F. (2009). International evidence on the relative importance of the determinants of earnings forecast accuracy. Journal of Economics and Business, 61, 453–471.

    Article  Google Scholar 

  16. Debreceny, R. S., & Gray, G. L. (2001). The Production and use of semantically rich accounting reports on the Internet, XML and XBRL. International Journal of Accounting Information Systems, 2, 47–74.

    Article  Google Scholar 

  17. Debreceny, R. S., Gray, G. L., & Rahman, A. (2002). The determinants of internet financial reporting. Journal of Accounting and Public Policy, 21, 371–394.

    Article  Google Scholar 

  18. Debreceny, R. S., Farewell, S., Piechocki, M., Felden, C., & Graning, A. (2010). Does it add up? Early evidence on the data quality of XBRL filings to the SEC. Journal of Accounting and Public Policy, 29, 296–306.

    Article  Google Scholar 

  19. DeFond, M., & Hung, M. (2007). Investor protection and analysts’ cash flow forecast around the world. Review of Accounting Studies, 12, 377–419.

    Article  Google Scholar 

  20. Doolin, B., & Troshani, I. (2007). Organization adoption of XBRL. Electronic Markets, 17(3), 199–209.

    Article  Google Scholar 

  21. Folmer, E., Luttighuis, P. O., & van Hillegersberg, J. (2011). Do semantic standards lack quality? A survey among 34 semantic standards. Electronic Markets, 21, 99–111.

    Article  Google Scholar 

  22. Frankel, R., Kothari, S. P., & Weber, J. (2006). Determinants of the informativeness of analyst research. Journal of Accounting and Economics, 41, 29–54.

    Article  Google Scholar 

  23. Gu, Z., & Wu, J. S. (2003). Earnings skewness and analyst forecast bias. Journal of Accounting and Economics, 35(1), 5–29.

    Article  Google Scholar 

  24. Higgins, H. N. (1998). Analyst forecasting performance in seven countries. Financial Analysts Journal, 54(3), 58–62.

    Article  Google Scholar 

  25. Hitt, L., & Brynjolfsson, E. (1996). Productivity, business profitability, and consumer surplus: three different measures of information technological value. MIS Quarterly, 20(2), 121–142.

    Article  Google Scholar 

  26. Hope, O. K. (2003). Disclosure practices, enforcement of accounting standards, and analysts’ forecast accuracy: an international study. Journal of Accounting Research, 41(2), 235–272.

    Article  Google Scholar 

  27. Hope, O. K. (2004). Variations in the financial reporting environment and earnings forecasting. Journal of International Financial Management and Accounting, 15(1), 21–43.

    Article  Google Scholar 

  28. Hope, O. K., & Kang, T. (2005). The association between macroeconomic uncertainty and analysts’ forecast accuracy. Journal of International Accounting Research, 4(1), 23–38.

    Article  Google Scholar 

  29. Hunton, J. E., & McEwen, R. A. (1997). An assessment of the relation between analysts’ earnings forecast accuracy, motivational incentives and cognitive information search strategy. The Accounting Review, 72(4), 497–515.

    Google Scholar 

  30. Hwang, Y. (2005). Investigating enterprise systems adoption: uncertainty avoidance, intrinsic motivation, and the technology acceptance model. European Journal of Information Systems, 14, 150–161.

    Article  Google Scholar 

  31. Hwang, Y. (2009). The impact of uncertainty avoidance, social norms and innovativeness on trust and ease of use in electronic customer relationship management. Electronic Markets, 19, 89–98.

    Article  Google Scholar 

  32. Im, K. S., Dow, K. E., & Grover, V. A. (2001). A reexamination of IT investment and the market value of the firm—an event study methodology. Information Systems Research, 12(1), 103–117.

    Article  Google Scholar 

  33. Keeling, D., & Domingo, L. (2004). Debating XBRL. Accountancy Age, available at http://www.accountancyage.com/features/1139010 (accessed on 2 January 2005).

  34. Kernan, K. (2008). XBRL around the world. Journal of Accountancy, October 2008, Available from http://www.journalofaccountancy.com/Issues/2008/Oct/XBRLAroundTheWorld.htm on 4 January 2011.

  35. Kivijarvi, H., & Saarinen, T. (1995). Investment in information systems and the financial performance of the firm. Information & Management, 28(2), 143–163.

    Article  Google Scholar 

  36. Kross, W., Ro, B., & Schroeder, D. (1990). Earnings expectations: the analysts’ information advantage. The Accounting Review, 65, 461–476.

    Google Scholar 

  37. Lang, M. H., & Lundholm, R. J. (1996). Corporate disclosure policy and analyst behavior. The Accounting Review, 71(4), 467–492.

    Google Scholar 

  38. Leuz, C., Nanda, D., & Wysocki, P. D. (2003). Earnings management and investor protection: an international comparison. Journal of Financial Economics, 69, 505–527.

    Article  Google Scholar 

  39. Li, S. (2010). Does mandatory adoption of international financial reporting standards in The European Union reduce the cost of equity capital? The Accounting Review, 85(2), 607–636.

    Article  Google Scholar 

  40. Li, S., & Pinsker, R. (2005). Modeling RBRT adoption and its effects on cost of capital. International Journal of Accounting Information Systems, 6, 196–215.

    Article  Google Scholar 

  41. Liang, T. P., & Huang, J. S. (1998). an empirical study on consumer acceptance of products in electronic markets: a transaction cost model. Decision Support Systems, 24(1), 29–43.

    Article  Google Scholar 

  42. Liu, C. (2013). XBRL: a new global paradigm for business financial reporting. Journal of Global Information Management, (21)4.

  43. Liu, C., Sia, C. L., & Wei, K. K. (2008). Adopting organizational virtualization in B2B firms: an empirical study in Singapore. Information & Management, 45, 429–437.

    Article  Google Scholar 

  44. Liu, C., Wang, T.W., Yao, L.J. (2013). An empirical study of XBRL’s impact on analyst forecast behavior. Journal of Accounting and Public Policy, (in press).

  45. Locke, J., & Lowe, A. (2007). XBRL: an (open) source of enlightenment or disillusion? European Accounting Review, 16(3), 585–623.

    Article  Google Scholar 

  46. Loonam, M., & O’Loghlin, D. (2008). Exploring E-service quality: a study of Irish online banking. Marketing Intelligence & Planning, 26(7), 759–780.

    Article  Google Scholar 

  47. Luttman, S. M., & Silhan, P. A. (1995). Identifying factors consistently related to value line earnings preditability. The Financial Review, 30(3), 445–468.

    Article  Google Scholar 

  48. Marquardt, C. A., & Wiedman, C. I. (1998). Voluntary disclosure, information asymmetry, and insider selling through secondary equity offerings. Contemporary Accounting Research, 15(4), 505–537.

    Article  Google Scholar 

  49. Myers, R. (1990). Classical and modern regression with applications (2nd ed.). Boston: Duxbury.

    Google Scholar 

  50. O’Brien, P. (1988). Analysts’ forecasts as earnings expectations. Journal of Accounting and Economics, 10, 53–83.

    Article  Google Scholar 

  51. O’Brien, P. (1990). Forecast accuracy of individual analysts in nine industries. Journal of Accounting Research, 28(2), 286–304.

    Article  Google Scholar 

  52. O’Kelly, C. (2010). XBRL adoption update. Available on 4 January 2011 from http://www.slideshare.net/xbrlplanet/xbrl-world-wide-adoption-survey-april-2010.

  53. Otto, B., Lee, Y. W., & Caballero, I. (2011a). Information and data quality in networked business. Electronic Markets, 21, 79–81.

    Article  Google Scholar 

  54. Otto, B., Lee, Y. W., & Caballero, I. (2011b). Information and data quality in business networking: a key concept for enterprises in its early stages of development. Electronic Markets, 21, 83–97.

    Article  Google Scholar 

  55. Peek, E. (2005). The influence of accounting changes on financial analysts’ forecast accuracy and forecasting superiority: evidence from the Netherlands. European Accounting Review, 14(2), 261–295.

    Article  Google Scholar 

  56. Peng, J., & Chang, C. J. (2010). Applying XBRL in an accounting information system design using the REA approach: an instructional case. Accounting Perspectives, 9(1), 55–78.

    Article  Google Scholar 

  57. Peng, S., Tondkar, R. H., van der Laan Smith, J., & Harless, D. W. (2008). Does convergence of accounting standards lead to the convergence of accounting practices? A study from China. The International Journal of Accounting, 43, 448–468.

    Article  Google Scholar 

  58. Petersen, M. (2009). Estimating standard errors in finance panel data sets: comparing approaches. Review of Financial Studies, 22(1), 435–480.

    Article  Google Scholar 

  59. Premuroso, R. F., & Bhattacharya, S. (2008). Do early and voluntary filers of financial information in XBRL format signal superior corporate governance and operating performance? International Journal of Accounting Information Systems, 9, 1–20.

    Article  Google Scholar 

  60. Rai, A., Patnayakuni, R., & Patnayakuni, N. (1997). Technology investment and business performance. Communications of the ACM, 40(7), 89–97.

    Article  Google Scholar 

  61. Richardson, S., Teoh, S. H., & Wysocki, P. (2004). The walk-down to beatable analyst forecasts: the role of equity issuance and insider trading incentives. Contemporary Accounting Research, 21(4), 885–924.

    Article  Google Scholar 

  62. Rock, S., Sedo, S., & Willenborg, M. (2001). Analyst following and count-data econometrics. Journal of Accounting and Economics, 30, 351–373.

    Article  Google Scholar 

  63. Roulstone, D. (2003). Analyst following and market liquidity. Contemporary Accounting Research, 20, 552–578.

    Article  Google Scholar 

  64. Sircar, S., Turnbow, J. L., & Bordoloi, B. (2000). A framework for assessing the relationship between information technology investments and firm performance. Journal of Management Information Systems, 16(4), 69–97.

    Google Scholar 

  65. Sledgianowski, E., Fondeder, R., & Slavin, N. S. (2010). Implementing XBRL reporting. The CPA Journal, 80(8), 68–72.

    Google Scholar 

  66. Srivastava, R. P., & Kogan, A. (2010). Assurance on XBRL instance document: a conceptual framework of assertions. International Journal of Accounting Information Systems, 11, 261–273.

    Article  Google Scholar 

  67. Teo, H. H., Oh, L. B., Liu, C., & Wei, K. K. (2003). An empirical study of the effects of interactivity on web user attitude. International Journal of Human-Computer Studies, 58, 281–305.

    Article  Google Scholar 

  68. Vanstraelen, A., Zarzeski, M. T., & Robb, S. W. G. (2003). Corporate nonfinancial disclosure practices and financial analyst forecast ability across three European countries. Journal of International Financial Management and Accounting, 14(3), 249–278.

    Article  Google Scholar 

  69. Vergoossen, R. G. A. (1993). The use and perceived importance of annual reports by investment analysts in the Netherlands. European Accounting Review, 2(3), 219–244.

    Article  Google Scholar 

  70. Wigand, R. T., Markus, M. L., & Steinfield, C. W. (2005). Preface to the focus theme section: vertical industry information technology standards and standardization. Electronic Markets, 15(4), 285–288.

    Article  Google Scholar 

  71. Xiao, J. Z., Yang, H., & Chow, C. W. (2004). The determinants and characteristics of voluntary internet-based disclosures by listed Chinese companies. Journal of Accounting and Public Policy, 23, 191–225.

    Article  Google Scholar 

  72. Yao, L. J., Liu, C., & Chan, S. H. (2010). The influence of firm specific context on realizing information technology business value in manufacturing industry. International Journal of Accounting Information Systems, 11, 353–362.

    Article  Google Scholar 

  73. Yoon, H., Zo, H., & Ciganek, A. P. (2011). Does XBRL adoption reduce information asymmetry?’. Journal of Business Research, 64, 157–163.

    Article  Google Scholar 

  74. Yu, M. (2010). Analyst forecast properties, analyst following and governance disclosures: a global perspective. Journal of International Accounting, Auditing, and Taxation, 19, 1–15.

    Article  Google Scholar 

  75. Zhou, J. (2003). Getting nowhere: Private equity in P. R. China. Available: http://www.altassets.com/casefor/countries/2003/nz3219.php.

  76. Zhu, H., & Wu, H. (2011). Quality of data standards: framework and illustration using XBRL taxonomy and Instances. Electronic Markets, 21, 129–139.

    Article  Google Scholar 

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Acknowledgements

The authors are indebted to Dr. Xin Luo, anonymous reviewers and senior editors for their enlightening comments and helpful suggestions. The authors also thank the participants of the Annual Conference on Global Economy, Business and Finance 2012.

A dedication

The authors hope to dedicate this paper to Dr. Lee J. Yao who passed away on Nov. 14, 2012 due to complications from cancer.

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Correspondence to Chunhui Liu.

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Responsible Editor: Xin Luo

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Liu, C., Yao, L.J., Sia, C.L. et al. The impact of early XBRL adoption on analysts’ forecast accuracy - empirical evidence from China. Electron Markets 24, 47–55 (2014). https://doi.org/10.1007/s12525-013-0132-8

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Keywords

  • XBRL adoption
  • Innovation diffusion
  • e-Business IT business value
  • Online financial reporting

JEL classification

  • M150
  • M410
  • O330