Digital transformation and corporate performance: evidence from China

References

• Acemoglu, D., D. Autor, D. Dorn, G. H. Hanson, and B. Price. 2014. “Return of the Solow Paradox? IT, Productivity, and Employment in US Manufacturing.” The American Economic Review 104 (5): 394–399. https://doi.org/10.1257/aer.104.5.394.
   Web of Science ®Google Scholar
• Acemoglu, D., and P. Restrepo. 2018. “The Race Between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment.” American Economic Review 108 (6): 1488–1542. https://doi.org/10.1257/aer.20160696.
   Web of Science ®Google Scholar
• Agrawal, A., J. S. Gans, and A. Goldfarb. 2019. “Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction.” Journal of Economic Perspectives 33 (2): 31–50. https://doi.org/10.1257/jep.33.2.31.
   Web of Science ®Google Scholar
• Baily, M. N. 1986. “What Has Happened to Productivity Growth?” Science 234 (4775): 443–451. https://doi.org/10.1126/science.234.4775.443.
   PubMed Web of Science ®Google Scholar
• Bajari, P., D. Nekipelov, S. P. Ryan, and M. Yang. 2015. “Machine Learning Methods for Demand Estimation.” American Economic Review 105 (5): 481–485. https://doi.org/10.1257/aer.p20151021.
   Web of Science ®Google Scholar
• Bakhshi, H., B. A. Bravo, and C. J. Mateos. 2014. “Inside the Datavores: Estimating the Effect of Data and Online Analytics on Firm Performance.” Nesta Working Paper, N° 14/05, August.
   Google Scholar
• Bakos, Y. 1998. “Economics and Technology: The Productivity Payoff of Computers.” Science 281 (5373): 52–52. https://doi.org/10.1126/science.281.5373.52.
   Google Scholar
• Bartel, A., C. Ichniowski, and K. Shaw. 2007. “How Does Information Technology Affect Productivity? Plant-Level Comparisons of Product Innovation, Process Improvement, and Worker Skills.” Quarterly Journal of Economics 122 (4): 1721–1758. https://doi.org/10.1162/qjec.2007.122.4.1721.
   Web of Science ®Google Scholar
• Barua, A., C. Kriebel, and T. Mukhopadhyay. 1995. “Information Technologies and Business Value: An Analytic and Empirical Investigation.” Information Systems Research 6 (1): 3–23. https://doi.org/10.1287/isre.6.1.3.
   Web of Science ®Google Scholar
• Basu, S., J. G. Fernald, N. Oulton, and S. Srinivasan. 2003. “The Case of the Missing Productivity Growth: Or, Does Information Technology Explain Why Productivity Accelerated in the United States but Not the United Kingdom?” NBER Working Paper N° 10010, October.
   Google Scholar
• Beccalli, E. 2007. “Does IT Investment Improve Bank Performance? Evidence from Europe.” Journal of Banking & Finance 31 (7): 2205–2230. https://doi.org/10.1016/j.jbankfin.2006.10.022.
   Web of Science ®Google Scholar
• Belleflamme, P. 2001. “Oligopolistic Competition, IT Use for Product Differentiation and the Productivity Paradox.” International Journal of Industrial Organization 19 (1–2): 227–248. https://doi.org/10.1016/S0167-7187(99)00017-X.
   Web of Science ®Google Scholar
• Bernstein, F., S. Modaresi, and D. Saure. 2019. “A Dynamic Clustering Approach to Data-Driven Assortment Personalization.” Management Science 65 (5): 2095–2115. https://doi.org/10.1287/mnsc.2018.3031.
   Web of Science ®Google Scholar
• Bharadwaj, A., O. El Sawy, P. Pavlou, and N. Venkatraman. 2013. “Digital Business Strategy: Toward a Next Generation of Insights.” MIS Quarterly 37 (2): 471–482. https://doi.org/10.25300/MISQ/2013/37:2.3.
   Web of Science ®Google Scholar
• Bharadwaj, A. S. 2000. “A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation.” MIS Quarterly 24 (1): 169–196. https://doi.org/10.2307/3250983.
   Web of Science ®Google Scholar
• Bloom, N., R. Sadun, and J. V. Reenen. 2012. “Americans Do IT Better: US Multinationals and the Productivity Miracle.” American Economic Review 102 (1): 167–201. https://doi.org/10.1257/aer.102.1.167.
   Web of Science ®Google Scholar
• Brynjolfsson, E., and L. M. Hitt. 2000. “Beyond Computation: Information Technology, Organizational Transformation and Business Performance.” Journal of Economic Perspectives 14 (4): 23–48. https://doi.org/10.1257/jep.14.4.23.
   Web of Science ®Google Scholar
• Brynjolfsson, E., L. M. Hitt, and H. H. Kim. 2011. “Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance?” SSRN Working Paper, N° 1819486, April.
   Google Scholar
• Brynjolfsson, E., X. Hui, and M. Liu. 2019. “Does Machine Translation Affect International Trade? Evidence from a Large Digital Platform.” Management Science 65 (12): 5449–5460. https://doi.org/10.1287/mnsc.2019.3388.
   Web of Science ®Google Scholar
• Brynjolfsson, E., and T. Mitchell. 2017. “What Can Machine Learning Do? Workforce Implications.” Science 358 (6370): 1530–1534. https://doi.org/10.1126/science.aap8062.
   PubMed Web of Science ®Google Scholar
• Brynjolfsson, E., T. Mitchell, and D. Rock. 2018. “What Can Machines Learn and What Does It Mean for Occupations and the Economy?” AEA Papers and Proceedings, edited by W. R. Johnson, and K. Markel, 43–47. Vol. 108.
   Google Scholar
• Brynjolfsson, E., D. Rock, and C. Syverson. 2017. “Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics.“ In NBER Chapters in The Economics of Artificial Intelligence: An Agendac, edited byA. Agrawal, J. Gans, and A. Goldfarb, 23–57. Chicago: University of Chicago Press.
   Google Scholar
• Carr, N. G. 2003. “IT Doesn’t Matter.” Harvard Business Review 81 (5): 41–49,128. https://doi.org/10.1109/EMR.2004.25006.
   PubMed Web of Science ®Google Scholar
• Chanias, S. 2017. “Mastering Digital Transformation: The Path of a Financial Services Provider Towards a Digital Transformation Strategy.” twenty-fifth European Conference on Information Systems, Guimarães, Portugal.
   Google Scholar
• Chen, M. A., Q. Wu, and B. Yang. 2019. “How Valuable is FinTech Innovation?” The Review of Financial Studies 32 (5): 2062–2106. https://doi.org/10.1093/rfs/hhy130.
   Web of Science ®Google Scholar
• Choi, C., and M. Hoon Yi. 2009. “The Effect of the Internet on Economic Growth: Evidence from Cross-Country Panel Data.” Economics Letters 105 (1): 39–41. https://doi.org/10.1016/j.econlet.2009.03.028.
   Web of Science ®Google Scholar
• Chu, L. Y., H. Nazerzadeh, and H. Zhang. 2020. “Position Ranking and Auctions for Online Marketplaces.” Management Science 66 (8): 3617–3634. https://doi.org/10.1287/mnsc.2019.3372.
   Web of Science ®Google Scholar
• Chun, H., and M. I. Nadiri. 2002. “Decomposing Productivity Growth in the US Computer Industry.” NBER Working Paper, N° 9267, October.
   Google Scholar
• Czernich, N., O. Falck, T. Kretschmer, and L. Woessmann. 2011. “Broadband Infrastructure and Economic Growth.” The Economic Journal 121 (552): 505–532. https://doi.org/10.1111/j.1468-0297.2011.02420.x.
   Web of Science ®Google Scholar
• Devaraj, S., and R. Kohli. 2003. “Performance Impacts of Information Technology: Is Actual Usage the Missing Link?” Management Science 49 (3): 273–289. https://doi.org/10.1287/mnsc.49.3.273.12736.
   Web of Science ®Google Scholar
• Dewan, S., and K. Kraemer. 2000. “Information Technology and Productivity: Evidence from Country-Level Data.” Management Science 46 (4): 548. https://doi.org/10.1287/mnsc.46.4.548.12057.
   Web of Science ®Google Scholar
• Dodgson, M. 1993. “Organizational Learning: A Review of Some Literatures.” Organization Studies 14 (3): 375–394. https://doi.org/10.1177/017084069301400303.
   Web of Science ®Google Scholar
• Du, W. Y., S. L. Pan, and J. S. Huang. 2016. “How a Latecomer Company Used IT to Redeploy Slack Resources.” MIS Quarterly 15 (3): 195–213.
   Web of Science ®Google Scholar
• Garicano, L. 2000. “Hierarchies and the Organization of Knowledge in Production.” Journal of Political Economy 108 (5): 874–904. https://doi.org/10.1086/317671.
   Web of Science ®Google Scholar
• Goldfarb, A., and C. Tucker. 2019. “Digital Economics.” Journal of Economic Literature 57 (1): 3–43. https://doi.org/10.1257/jel.20171452.
   Web of Science ®Google Scholar
• Gordon, R. J., and H. Sayed. 2018. “Transatlantic Technologies: The Role of ICT in the Evolution of US and European Productivity Growth.” NBER Working Paper, N° 27425, June.
   Google Scholar
• Haffke, I., B. Kalgovas, and A. Benlian. 2016. “The Role of the CIO and the CDO in an Organization’s Digital Transformation.” International Conference on Information Systems (ICIS 2016), Dublin, Ireland.
   Google Scholar
• Hsieh, C., and P. Klenow. 2009. “Misallocation and Manufacturing TFP in China and India.” Quarterly Journal of Economics 124 (4): 1403–1448. https://doi.org/10.1162/qjec.2009.124.4.1403.
   Web of Science ®Google Scholar
• Jorgenson, D. W., and K. J. Stiroh. 2000. “Raising the Speed Limit: US Economic Growth in the Information Age.” Brookings Papers on Economic Activity 1 (1): 125–211. https://doi.org/10.1353/eca.2000.0008.
   Google Scholar
• Kohli, R., and V. Grover. 2008. “Business Value of IT: An Essay on Expanding Research Directions to Keep Up with the Times.” Journal of the Association for Information Systems 9 (1): 23–39. https://doi.org/10.17705/1jais.00147.
   Web of Science ®Google Scholar
• Kusiak, A. 2017. “Smart Manufacturing Must Embrace Big Data.” Nature 544 (7648): 23–25. https://doi.org/10.1038/544023a.
   PubMed Web of Science ®Google Scholar
• Lane, P. J., J. E. Salk, and M. A. Lyles. 2001. “Absorptive Capacity, Learning, and Performance in International Joint Ventures.” Strategic Management Journal 22 (12): 1139–1161. https://doi.org/10.1002/smj.206.
   Web of Science ®Google Scholar
• Lee, S.-Y. T., R. Gholami, and T. Y. Tong. 2005. “Time Series Analysis in the Assessment of ICT Impact at the Aggregate Level–Lessons and Implications for the New Economy.” Information & Management 42 (7): 1009–1022. https://doi.org/10.1016/j.im.2004.11.005.
   Web of Science ®Google Scholar
• Levinsohn, J., and A. Petrin. 2003. “Estimating Production Functions Using Inputs to Control Unobservables.” Review of Economic Studies 70 (1): 317–342. https://doi.org/10.1111/1467-937x.00246.
   Google Scholar
• Li, F., R. Lundholm, and M. Minnis. 2013. “A Measure of Competition Based on 10-K Filings.” Journal of Accounting Research 51 (2): 399–436. https://doi.org/10.1111/j.1475-679X.2012.00472.x.
   Web of Science ®Google Scholar
• Li, K., F. Mai, R. Shen, X. Yan, I. Goldstein, and I. Goldstein. 2021. “Measuring Corporate Culture Using Machine Learning.” The Review of Financial Studies 34 (7): 3265–3315. https://doi.org/10.1093/rfs/hhaa079.
   Web of Science ®Google Scholar
• Loughran, T. I. M., and B. McDonald. 2016. “Textual Analysis in Accounting and Finance: A Survey.” Journal of Accounting Research 54 (4): 1187–1230. https://doi.org/10.1111/1475-679x.12123.
   Web of Science ®Google Scholar
• Luo, S., and N. J. Nagarajan. 2015. “Information Complementarities and Supply Chain Analysts.” The Accounting Review 90 (5): 1995–2029. https://doi.org/10.2308/accr-51011.
   Web of Science ®Google Scholar
• Mahmood, M. A., and G. J. Mann. 1993. “Measuring the Organizational Impact of Information Technology Investment: An Exploratory Study.” Journal of Management Information Systems 10 (1): 97–122. https://doi.org/10.1080/07421222.1993.11517992.
   Google Scholar
• Miklós-Thal, J., and C. Tucker. 2019. “Collusion by Algorithm: Does Better Demand Prediction Facilitate Coordination Between Sellers?” Management Science 65 (4): 1455–1947. https://doi.org/10.1287/mnsc.2019.3287.
   Web of Science ®Google Scholar
• Mikolov, T., K. Chen, G. Corrado, and J. Dean. 2013. “Efficient Estimation of Word Representations in Vector Space.” arXiv preprint.
   Google Scholar
• Morrison, C., and E. Berndt. 1991. “Assessing the Productivity of Information Technology Equipment in US Manufacturing Industries.” NBER Working Paper N° 3582, January.
   Google Scholar
• Nambisan, S., K. Lyytinen, A. Majchrzak, and M. Song. 2017. “Digital Innovation Management: Reinventing Innovation Management Research in a Digital World.” MIS Quarterly 41 (1): 223. https://doi.org/10.25300/MISQ/2017/41:1.03.
   Web of Science ®Google Scholar
• Nunn, N., and N. Qian. 2014. “US Food Aid and Civil Conflict.” American Economic Review 104 (6): 1630–1666. https://doi.org/10.1257/aer.104.6.1630.
   Web of Science ®Google Scholar
• Nwankpa, J. K., and Y. Roumani. 2016. “IT Capability and Digital Transformation: A Firm Performance Perspective.” Thirty-Seventh International Conference on Information Systems, Dublin, Irela.
   Google Scholar
• Olley, G. S., and A. Pakes. 1996. “The Dynamics of Productivity in the Telecommunications Equipment Industry.” Econometrica 64 (6): 1263–1297. https://doi.org/10.2307/2171831.
   Web of Science ®Google Scholar
• Rong, X. 2016. “Word2vec Parameter Learning Explained.” arXiv preprint arXiv:1411.2738.
   Google Scholar
• Seamans, R., and M. Raj. 2018. “AI, Labor, Productivity and the Need for Firm-Level Data.” NBER Working Paper N° 24239, January.
   Google Scholar
• Soh, C., and M. L. Markus. 1995. “How IT Creates Business Value: A Process Theory Synthesis.” Sixteenth International Conference on Information Systems, Netherlands.
   Google Scholar
• Song, Y., S. Shi, J. Li, and H. Zhang. 2018. “Directional Skip-Gram: Explicitly Distinguishing Left and Right Context for Word Embeddings.” Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 175–180. Vol. 2. New Orleans, Louisiana: Association for Computational Linguistics.
   Google Scholar
• Stiroh, K. J. 2002. “Information Technology and the US Productivity Revival: What Do the Industry Data Say?” American Economic Review 92 (5): 1559–1576. https://doi.org/10.1257/000282802762024638.
   Web of Science ®Google Scholar
• Syverson, C. 2017. “Challenges to Mismeasurement Explanations for the US Productivity Slowdown.” Journal of Economic Perspectives 31 (2): 165–186. https://doi.org/10.1257/jep.31.2.165.
   Web of Science ®Google Scholar
• Tam, K. Y. 1998. “The Impact of Information Technology Investments on Firm Performance and Evaluation: Evidence from Newly Industrialized Economies.” Information Systems Research 9 (1): 85–98. https://doi.org/10.1287/isre.9.1.85.
   Web of Science ®Google Scholar
• Tambe, P., and L. M. Hitt. 2012. “The Productivity of Information Technology Investments: New Evidence from IT Labor Data.” Information Systems Research 23 (3): 599. https://doi.org/10.1287/isre.1110.0398.
   Web of Science ®Google Scholar
• Timmer, M. P., and B. van Ark. 2005. “Does Information and Communication Technology Drive EU-US Productivity Growth Differentials?” Oxford Economic Papers 57 (4): 693–716. https://doi.org/10.1093/oep/gpi032.
   Web of Science ®Google Scholar
• Yoganarasimhan, H. 2020. “Search Personalization Using Machine Learning.” Management Science 66 (3): 1045–1070. https://doi.org/10.1287/mnsc.2018.3255.
   Web of Science ®Google Scholar
• Zhu, C. 2019. “Big Data as a Governance Mechanism.” The Review of Financial Studies 32 (5): 2021–2061. https://doi.org/10.1093/rfs/hhy081.
   Web of Science ®Google Scholar