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Digital dark matter and the economic contribution of Apache

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  • Greenstein, Shane
  • Nagle, Frank

Abstract

Researchers have long hypothesized that research outputs from government, university, and private company R&D contribute to economic growth, but these contributions may be difficult to measure when they take a non-pecuniary form. The growth of networking devices and the Internet in the 1990s and 2000s magnified these challenges, as illustrated by the deployment of the descendent of the NCSA HTTPd server, otherwise known as Apache. This study asks whether this experience could produce measurement issues in standard productivity analysis, specifically, omission and attribution issues, and, if so, whether the magnitude is large enough to matter. The study develops and analyzes a novel data set consisting of a 1% sample of all outward-facing web servers used in the United States. We find that use of Apache potentially accounts for a mismeasurement of somewhere between $2 billion and $12 billion, which equates to between 1.3% and 8.7% of the stock of prepackaged software in private fixed investment in the United States and a very high rate of return to the original federal investment in the Internet. We argue that these findings point to a large potential undercounting of the rate of return from IT spillovers from the invention of the Internet. The findings also suggest a large potential undercounting of “digital dark matter” in general.

Suggested Citation

  • Greenstein, Shane & Nagle, Frank, 2014. "Digital dark matter and the economic contribution of Apache," Research Policy, Elsevier, vol. 43(4), pages 623-631.
  • Handle: RePEc:eee:respol:v:43:y:2014:i:4:p:623-631
    DOI: 10.1016/j.respol.2014.01.003
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    Cited by:

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    3. Diane Coyle, 2017. "Do-it-yourself digital: the production boundary and the productivity puzzle," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2017-01, Economic Statistics Centre of Excellence (ESCoE).
    4. Schrape, Jan-Felix, 2017. "Open source projects as incubators of innovation: From niche phenomenon to integral part of the software industry," Research Contributions to Organizational Sociology and Innovation Studies, SOI Discussion Papers 2017-03, University of Stuttgart, Institute for Social Sciences, Department of Organizational Sociology and Innovation Studies.
    5. Daniel Sichel & Eric von Hippel, 2019. "Household Innovation, R&D, and New Measures of Intangible Capital," NBER Working Papers 25599, National Bureau of Economic Research, Inc.
    6. Frank Nagle, 2019. "Open Source Software and Firm Productivity," Management Science, INFORMS, vol. 65(3), pages 1191-1215, March.
    7. Prasanna Tambe, 2014. "Big Data Investment, Skills, and Firm Value," Management Science, INFORMS, vol. 60(6), pages 1452-1469, June.
    8. Heikkinen, I.T.S. & Savin, H. & Partanen, J. & Seppälä, J. & Pearce, J.M., 2020. "Towards national policy for open source hardware research: The case of Finland," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    9. Miric, Milan & Jeppesen, Lars Bo, 2023. "How does competition influence innovative effort within a platform-based ecosystem? Contrasting paid and unpaid contributors," Research Policy, Elsevier, vol. 52(7).
    10. Petraite, Monika & Mubarak, Muhammad Faraz & Rimantas, Rauleckas & von Zedtwitz, Max, 2022. "The role of international networks in upgrading national innovation systems," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    11. Frank Nagle, 2018. "Learning by Contributing: Gaining Competitive Advantage Through Contribution to Crowdsourced Public Goods," Organization Science, INFORMS, vol. 29(4), pages 569-587, August.
    12. Shaikh, Maha & Levina, Natalia, 2019. "Selecting an open innovation community as an alliance partner: Looking for healthy communities and ecosystems," Research Policy, Elsevier, vol. 48(8), pages 1-1.
    13. Wachs, Johannes & Nitecki, Mariusz & Schueller, William & Polleres, Axel, 2022. "The Geography of Open Source Software: Evidence from GitHub," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    14. J Bayoán Santiago Calderón & Carol Robbins & Ledia Guci & Gizem Korkmaz & Brandon L. Kramer, 2022. "Measuring the Cost of Open Source Software Innovation on GitHub," BEA Working Papers 0200, Bureau of Economic Analysis.
    15. Peng Huang & Marco Ceccagnoli & Chris Forman & D.J. Wu, 2022. "IT Knowledge Spillovers, Absorptive Capacity, and Productivity: Evidence from Enterprise Software," Information Systems Research, INFORMS, vol. 33(3), pages 908-934, September.
    16. Christian Peukert & Margaritha Windisch, 2023. "The Economics of Copyright in the Digital Age," CESifo Working Paper Series 10687, CESifo.
    17. Abhishek Nagaraj, 2021. "Information Seeding and Knowledge Production in Online Communities: Evidence from OpenStreetMap," Management Science, INFORMS, vol. 67(8), pages 4908-4934, August.
    18. Wen Wen & Marco Ceccagnoli & Chris Forman, 2016. "Opening Up Intellectual Property Strategy: Implications for Open Source Software Entry by Start-up Firms," Management Science, INFORMS, vol. 62(9), pages 2668-2691, September.
    19. Shane Greenstein, 2020. "Digital Infrastructure," NBER Chapters, in: Economic Analysis and Infrastructure Investment, pages 409-447, National Bureau of Economic Research, Inc.
    20. Korkmaz, Gizem & Santiago Calderón, J. Bayoán & Kramer, Brandon L. & Guci, Ledia & Robbins, Carol A., 2024. "From GitHub to GDP: A framework for measuring open source software innovation," Research Policy, Elsevier, vol. 53(3).
    21. Erdem Dogukan Yilmaz & Ivana Naumovska & Milan Miric, 2023. "Does imitation increase or decrease demand for an original product? Understanding the opposing effects of discovery and substitution," Strategic Management Journal, Wiley Blackwell, vol. 44(3), pages 639-671, March.

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    More about this item

    Keywords

    Open source; Apache; Economic measurement; Digital economics;
    All these keywords.

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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