Automation, Research Technology, and Researchers’ Trajectories: Evidence from Computer Science and Electrical Engineering

Published Online:https://doi.org/10.1287/orsc.2019.1308

References

  • Acemoglu D (2002) Directed technical change. Rev. Econom. Stud. 69(4):781–809.CrossrefGoogle Scholar
  • Acemoglu D (2012) Diversity and technological progress. Stern S, Lerner J, eds. The Rate and Direction of Inventive Activity Revisited (University of Chicago Press, Chicago), 319–356.CrossrefGoogle Scholar
  • Acemoglu D, Autor D (2011) Skills, tasks and technologies: implications for employment and earnings. Card D, Ashenfelter O, eds. Handbook of Labor Economics, vol. 4, (Elsevier, Amsterdam, Netherlands), 1043–1171.Google Scholar
  • Acemoglu D, Restrepo P (2018) Modeling automation. Amer. Econom. Rev. 108:48–53.Google Scholar
  • Aghion P, Dewatripont M, Stein CJ (2008) Academic freedom, private-sector focus, and the process of innovation. RAND J. Econom. 39(3):617–635.CrossrefGoogle Scholar
  • Agrawal A, Goldfarb A, Teodoridis F (2016) Understanding the changing structure of scientific inquiry. Amer. Econom. J. Appl. Econom. 8(1):100–128.CrossrefGoogle Scholar
  • Agrawal A, Gans J, Goldfarb A, eds. (2018) The Economics of Artificial Intelligence: An Agenda (University of Chicago Press, Chicago).Google Scholar
  • Argyres NS (1999) The impact of information technology on coordination: evidence from the B-2 ‘stealth’ bomber. Organ. Sci. 10(2):162–180.LinkGoogle Scholar
  • Athey S, Imbens G (2015) Lectures on Machine Learning (National Bureau of Economic Research, Cambridge, MA).Google Scholar
  • Autor DH, Katz LF, Krueger AB (1998) Computing inequality: have computers changed the labor market? Quart. J. Econom. 113(4):1169–1213.CrossrefGoogle Scholar
  • Azoulay P, Furman JL, Krieger JL, Murray F (2015) Retractions. Rev. Econom. Stat. 97(5):1118–1136.CrossrefGoogle Scholar
  • Bessen J (2015) How computer automation affects occupations: technology, jobs, and skills. Working paper, Boston University, Boston.Google Scholar
  • Bilton N (2011) Microsoft sells 10 million Kinects, breaking record. New York Times Blogs (March 9), https://bits.blogs. nytimes.com/2011/03/09/microsoft-sells-10-million-kinects-breaking-record.Google Scholar
  • Borjas G, Doran K (2012) The collapse of the Soviet Union and the productivity of American mathematicians. Quart. J. Econom. 127(3):1143–1203.CrossrefGoogle Scholar
  • Borjas G, Doran K (2015) Cognitive mobility: native responses to supply shocks in the space of ideas. J. Labor Econom. 33(S1):S109–S145.CrossrefGoogle Scholar
  • Boudreau KJ, Guinan EC, Lakhani KR, Riedl C (2017) Looking across and looking beyond the knowledge frontier: intellectual distance, novelty, and resource allocation in science. Management Sci. 62(10):2765–2783.LinkGoogle Scholar
  • Bloom N, Sadun R, Van Reenen J (2012) Americans do IT better: US multinationals and the productivity miracle. Amer. Econom. Rev. 102(1):167–201.CrossrefGoogle Scholar
  • Bresnahan TF, Brynjolfsson E, Hitt LM (2002) Information technology, workplace organization, and the demand for skilled labor: firm-level evidence. Quart. J. Econom. 117(1):339–376.CrossrefGoogle Scholar
  • Bryan K, Lemus J (2017) The direction of innovation. J. Econom. Theory 172:247–272.Google Scholar
  • Brynjolfsson E, Hitt L (2003) Computing productivity: firm-level evidence. Rev. Econom. Stat. 85(4):793–808.CrossrefGoogle Scholar
  • Brynjolfsson E, Mitchell T, Rock D (2018) Why can machines learn and what does it mean for occupations and the economy. Amer. Econom. Rev. 108:43–47.Google Scholar
  • Buntine W, Jakulin A (2004) Applying discrete PCA in data analysis. Chickering M, Halpern J, eds. Proc. 20th Conf. Uncertainty Artificial Intelligence (AUAI Press, Arlington, VA), 59–66.Google Scholar
  • Carmody T (2010a) Adafruit offers $1000 bounty for open-source Kinect drivers. Wired Magazine (November 4), https://www.wired.com/2010/11/adafruit-offers-1000-bounty-for-open-source-kinect-drivers/.Google Scholar
  • Carmody T (2010b) How Microsoft learned to stop worrying and love Open Kinect. Wired Magazine (November 22), https://www.wired.com/2010/11/open-kinect/.Google Scholar
  • Choudhury P, Starr E, Agarwal R (2018) Machine learning and human capital: experimental evidence on productivity complementarities. Working paper, Harvard Business School, Boston.Google Scholar
  • Cockburn I, Henderson R, Stern S (2017) The impact of artificial intelligence on innovation: an exploratory analysis. Agrawal A, Gans J, Goldfarb A, eds. The Economics of Artificial Intelligence: An Agenda (University of Chicago Press, Chicago).Google Scholar
  • Cohen WM, Klepper S (1992) The tradeoff between firm size and diversity in the pursuit of technological progress. Small Bus. Econom. 4(1):1–14.Google Scholar
  • Cohen WM, Klepper S (1996) A reprise of size and R&D. Econom. J. 106(437):925–951.Google Scholar
  • Cohen WM, Sauermann H, Stephan PE (2018) Academics’ motives, opportunity costs, and commercial activities across fields. Working paper, Duke University, Durham, NC.Google Scholar
  • Deming DJ (2017) The growing importance of social skills in the labor market. Quart. J. Econom. 132(4):1593–1640.CrossrefGoogle Scholar
  • Dean, JW, Yoon SJ, Susman GI (1992) Advanced manufacturing technology and organization structure: empowerment or subordination? Organ. Sci. 3(2):203–229.LinkGoogle Scholar
  • Ding WW, Levin SG, Stephan PE, Winkler AE (2010) The impact of information technology on scientists’ productivity, quality and collaboration patterns. Management Sci. 56(9):1439–1461.LinkGoogle Scholar
  • Dos Santos B, Peffers K (1995) Rewards to investors in innovative information technology applications: first movers and early followers in ATMs. Organ. Sci. 6(3):241–259.LinkGoogle Scholar
  • Felten E, Raj M, Seamans R (2018) A method to link advances in artificial intelligence to occupational abilities. AEA Papers & Proc. 108:54–57.CrossrefGoogle Scholar
  • Forman C, McElheran K (2012) Information technology and the boundary of the firm: evidence from plant-level data. Working paper, Harvard Business School, Boston.Google Scholar
  • Furman JL, Stern S (2011) Climbing atop the shoulders of giants: the impact of institutions on cumulative knowledge production. Amer. Econom. Rev. 101(5):1933–1963.CrossrefGoogle Scholar
  • Furman JL, Murray F, Stern S (2012) Growing stem cells: the impact of federal funding policy on the U.S. scientific frontier. J. Policy Anal. Management 31(3):661–705.CrossrefGoogle Scholar
  • Giles J (2010) Inside the race to hack Microsoft’s Kinect. New Sci. 208(2789):22–23.CrossrefGoogle Scholar
  • Griliches Z (1990) Patent statistics as economic indicators: a survey. J. Econom. Lit. 28(4):1661–1707.Google Scholar
  • Grupp H (1990) The concept of entropy in scientometrics and innovation research. Scientometrics 18(3–4):219–239.CrossrefGoogle Scholar
  • Han J, Shao L, Xu D, Shotton J (2013) Enhanced computer vision with Microsoft Kinect sensor: a review. IEEE Trans. Cybern. 43(5):1318–1334.CrossrefGoogle Scholar
  • Hofmann T (1999) Probabilistic latent semantic analysis. Atkinson K, ed. Proc. 15th Conf. Uncertainty Artificial Intelligence (AUAI Press, Arlington, VA), 289–296.Google Scholar
  • Iacus SM, Porro K (2011) Multivariate matching methods that are monotonic imbalance bounding. J. Amer. Statist. Assoc. 106(493):345–361.CrossrefGoogle Scholar
  • Iacus SM, Porro K (2012) Causal inference without balance checking: Coarsened exact matching. Political Anal. 20(1):1–24.CrossrefGoogle Scholar
  • Jin W, McElheran K (2018) Economies before scale: survival and performance of young plants in the age of cloud computing. Working paper, Rotman School of Management, University of Toronto, Toronto.Google Scholar
  • Jones B (2009) The burden of knowledge and the death of the renaissance man: is innovation getting harder? Rev. Econom. Stud. 76(1):253–281.CrossrefGoogle Scholar
  • Jones B (2010) As science evolves, how can science policy? Lerner J, Stern S, eds. NBER Innovation Policy and the Economy (National Bureau of Economic Research, Cambridge, MA), 103–131.Google Scholar
  • Kaplan S, Vakili K (2015) The double-edged sword of recombination in breakthrough innovation. Strategic Management J. 36(10):1435–1457.CrossrefGoogle Scholar
  • Karabarbounis L, Neiman B (2014) The global decline of the labor share. Quart. J. Econom. 129(1):61–103.CrossrefGoogle Scholar
  • Krieger J, Li D, Papanikolou D (2018) Developing novel drugs. Working paper, Harvard Business School, Boston.Google Scholar
  • Merton RK (1938) Science and the social order. Philos. Sci. 5(3):321–337.CrossrefGoogle Scholar
  • Mokyr J (2002) The Gifts of Athena: Historical Origins of the Knowledge Economy. (Princeton University Press, Princeton, NJ).Google Scholar
  • Mokyr J, Vickers C, Ziebarth NL (2015) The history of technological anxiety and the future of economic growth: is this time different? J. Econom. Perspect. 29(3):31–50.CrossrefGoogle Scholar
  • Murray F, Aghion P, Dewatripont M, Kolev J, Stern S (2016) Of mice and academics: examining the effect of openness on innovation. Amer. Econom. J. Econom. Policy 8(1):212–252.CrossrefGoogle Scholar
  • Murray F, O’Mahony S (2007) Exploring the foundations of cumulative innovation: implications for organization science. Organ. Sci. 6(18):1006–1021.LinkGoogle Scholar
  • Myers K (2018) The elasticity of science. Working paper, Harvard University, Boston.Google Scholar
  • Nelson AJ (2016) How to share ‘a really good secret’: managing sharing/secrecy tensions around scientific knowledge disclosure. Organ. Sci. 27(2):265–285.LinkGoogle Scholar
  • Nordhaus WD (2007) Two centuries of productivity growth in computing. J. Econom. Hist. 67(1):128–159.CrossrefGoogle Scholar
  • Pinsonneault A, Kraemer KL (2002) Exploring the role of information technology in organizational downsizing: a tale of two American cities. Organ. Sci. 13(2):191–208.LinkGoogle Scholar
  • Rafibakhsh N, Gong J, Siddiqui MK, Gordon C, Felix Lee H (2012) Analysis of Xbox Kinect sensor data for use on construction sites: depth accuracy and sensor interference assessment. Cai H, Kandil A, Hastak M, Dunston P, eds. Construction Research Congress 2012: Construction Challenges in a Flat World (ASCE Publishing, Reston, VA), 848–857.CrossrefGoogle Scholar
  • Rafols I, Meyer M (2010) Diversity and network coherence as indicators of interdisciplinarity: Case studies in bionanoscience. Scientometrics 82(2):263–287.CrossrefGoogle Scholar
  • Richards-Rissetto H, Remondino F, Agugiaro G, von Schwerin J, Robertsson J, Girardi G (2012) Kinect and 3D GIS in archaeology. Guidi G, Addison AC, eds. 18th International Conf. Virtual Systems and Multimedia, (IEEE, Piscataway, NJ), 331–337.CrossrefGoogle Scholar
  • Smith A (1776) An Inquiry into the Nature and Causes of the Wealth of Nations (W. Strahan and T. Cadell, London).CrossrefGoogle Scholar
  • Teodoridis F (2018) Understanding team knowledge production: the interrelated roles of technology and expertise. Management Sci. 64(8):3625–3648.LinkGoogle Scholar
  • Teh YW, Jordan MI, Beal MJ, Blei DM (2006) Hierarchical Dirichlet processes. J. Amer. Statist. Assoc. 101(476):1566–1581.CrossrefGoogle Scholar
  • Terdiman D (2010) Bounty offered for open-source Kinect Driver. CNET News (November 4), https://www.cnet.com/news/bounty-offered-for-open-source-kinect-driver/.Google Scholar
  • Thompson N, Zyontz S (2017) Who tries (and who succeeds) in staying at the forefront of science: evidence from the DNA-editing technology CRISPR. Working paper, MIT Sloan School of Management, Cambridge, MA.Google Scholar
  • Uzzi B, Mukherjee S, Stringer M, Jones B (2013) Atypical combinations and scientific impact. Science 342(6157):468–472.CrossrefGoogle Scholar
  • Volkoff O, Strong D, Elmes M (2007) Technological embeddedness and organizational change. Organ. Sci. 18(5):832–848.LinkGoogle Scholar
  • Wortham J (2010) Off the shelf and into the garage. New York Times (November 22).Google Scholar
  • Zhang Z (2012) Microsoft Kinect sensor and its effect. IEEE Multimed. 19(2):4–10.CrossrefGoogle Scholar
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