The Cognitive Enterprise Project

References & Bibliography

The works this is built upon.

The Foundational Series stands on a body of prior thought — 128 works across economics, organizational learning, decision theory, and the history of technology. Cited in Chicago style; works are referenced in the footnotes by author and short title after first appearance.

The Library
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A8

  • Agrawal, Ajay, Joshua Gans, and Avi Goldfarb. Prediction Machines: The Simple Economics of Artificial Intelligence. Boston: Harvard Business Review Press, 2018.
  • Agrawal, Ajay, Joshua Gans, and Avi Goldfarb. "Prediction, Judgment, and Complexity." NBER Working Paper 24243, 2018.
  • Akerlof, George A. "The Market for ‘Lemons’: Quality Uncertainty and the Market Mechanism." Quarterly Journal of Economics 84, no. 3 (1970): 488–500.
  • Argote, Linda. Organizational Learning: Creating, Retaining and Transferring Knowledge. 2nd ed. New York: Springer, 2013.
  • Argote, Linda, Sara L. Beckman, and Dennis Epple. "The Persistence and Transfer of Learning in Industrial Settings." Management Science 36, no. 2 (1990): 140–54.
  • Argote, Linda, and Dennis Epple. "Learning Curves in Manufacturing." Science 247, no. 4945 (1990): 920–24.
  • Argyris, Chris. "Double Loop Learning in Organizations." Harvard Business Review 55, no. 5 (1977): 115–25.
  • Argyris, Chris, and Donald A. Schön. Organizational Learning: A Theory of Action Perspective. Reading, MA: Addison-Wesley, 1978.

B10

  • Bainbridge, Lisanne. "Ironies of Automation." Automatica 19, no. 6 (1983): 775–79.
  • Barney, Jay. "Firm Resources and Sustained Competitive Advantage." Journal of Management 17, no. 1 (1991): 99–120.
  • Bell, Daniel. The Coming of Post-Industrial Society: A Venture in Social Forecasting. New York: Basic Books, 1973.
  • Beniger, James R. The Control Revolution: Technological and Economic Origins of the Information Society. Cambridge, MA: Harvard University Press, 1986.
  • Berners-Lee, Tim, James Hendler, and Ora Lassila. "The Semantic Web." Scientific American 284, no. 5 (2001): 34–43.
  • Bezos, Jeffrey P. "Letter to Shareholders." Amazon.com Annual Report, 1997 and 2015.
  • Blair, David C., and M. E. Maron. "An Evaluation of Retrieval Effectiveness for a Full-Text Document-Retrieval System." Communications of the ACM 28, no. 3 (1985): 289–99.
  • Brier, Glenn W. "Verification of Forecasts Expressed in Terms of Probability." Monthly Weather Review 78, no. 1 (1950): 1–3.
  • Bryar, Colin, and Bill Carr. Working Backwards: Insights, Stories, and Secrets from Inside Amazon. New York: St. Martin’s Press, 2021.
  • Brynjolfsson, Erik, Danielle Li, and Lindsey R. Raymond. "Generative AI at Work." Quarterly Journal of Economics 140, no. 2 (2025): 889–942.

C6

  • Carr, Nicholas G. "IT Doesn’t Matter." Harvard Business Review 81, no. 5 (2003): 41–49.
  • Castells, Manuel. The Rise of the Network Society. Oxford: Blackwell, 1996.
  • Chandler, Alfred D., Jr. The Visible Hand: The Managerial Revolution in American Business. Cambridge, MA: Belknap Press, 1977.
  • Christensen, Clayton M. The Innovator’s Dilemma. Boston: Harvard Business School Press, 1997.
  • Codd, E. F. "A Relational Model of Data for Large Shared Data Banks." Communications of the ACM 13, no. 6 (1970): 377–87.
  • Columbia Accident Investigation Board. Report. Vol. 1. Washington, DC: NASA and U.S. Government Printing Office, 2003.

D10

  • Dalio, Ray. Principles: Life and Work. New York: Simon & Schuster, 2017.
  • Darling, Marilyn, Charles Parry, and Joseph Moore. "Learning in the Thick of It." Harvard Business Review 83, no. 7 (2005): 84–92.
  • Davenport, Thomas H. "Putting the Enterprise into the Enterprise System." Harvard Business Review 76, no. 4 (1998): 121–31.
  • Davenport, Thomas H., and Laurence Prusak. Working Knowledge: How Organizations Manage What They Know. Boston: Harvard Business School Press, 1998.
  • Dehghani, Zhamak. Data Mesh: Delivering Data-Driven Value at Scale. Sebastopol, CA: O’Reilly, 2022.
  • Dell’Acqua, Fabrizio, et al. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper 24-013, 2023.
  • Dierickx, Ingemar, and Karel Cool. "Asset Stock Accumulation and Sustainability of Competitive Advantage." Management Science 35, no. 12 (1989): 1504–11.
  • Doshi-Velez, Finale, and Been Kim. "Towards a Rigorous Science of Interpretable Machine Learning." arXiv:1702.08608, 2017.
  • Drucker, Peter F. The Age of Discontinuity: Guidelines to Our Changing Society. New York: Harper & Row, 1969.
  • Drucker, Peter F. "Knowledge-Worker Productivity: The Biggest Challenge." California Management Review 41, no. 2 (1999): 79–94.

E3

  • Earl, Michael J., and Ian A. Scott. "What Is a Chief Knowledge Officer?" Sloan Management Review 40, no. 2 (1999): 29–38.
  • Einhorn, Hillel J., and Robin M. Hogarth. "Confidence in Judgment: Persistence of the Illusion of Validity." Psychological Review 85, no. 5 (1978): 395–416.
  • European Union. Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act). OJ L, 2024/1689, 12 July 2024.

F1

  • Freeman, Chris, and Francisco Louçã. As Time Goes By: From the Industrial Revolutions to the Information Revolution. Oxford: Oxford University Press, 2001.

G5

  • Garvin, David A. "Building a Learning Organization." Harvard Business Review 71, no. 4 (1993): 78–91.
  • Gebru, Timnit, et al. "Datasheets for Datasets." Communications of the ACM 64, no. 12 (2021): 86–92.
  • Gompers, Paul, Steven N. Kaplan, and Vladimir Mukharlyamov. "What Do Private Equity Firms Say They Do?" Journal of Financial Economics 121, no. 3 (2016): 449–76.
  • Gruber, Thomas R. "A Translation Approach to Portable Ontology Specifications." Knowledge Acquisition 5, no. 2 (1993): 199–220.
  • Guyatt, Gordon H., et al. "GRADE: An Emerging Consensus on Rating Quality of Evidence and Strength of Recommendations." BMJ 336 (2008): 924–26.

H4

  • Haspeslagh, Philippe C., and David B. Jemison. Managing Acquisitions: Creating Value through Corporate Renewal. New York: Free Press, 1991.
  • Hogan, Aidan, et al. "Knowledge Graphs." ACM Computing Surveys 54, no. 4 (2021): 1–37.
  • Hounshell, David A. From the American System to Mass Production, 1800–1932. Baltimore: Johns Hopkins University Press, 1984.
  • Hughes, Thomas P. American Genesis: A Century of Invention and Technological Enthusiasm, 1870–1970. New York: Viking, 1989.

I2

  • Inmon, W. H. Building the Data Warehouse. New York: Wiley, 1992.
  • International Organization for Standardization. ISO/IEC 42001:2023, Information Technology — Artificial Intelligence — Management System. Geneva: ISO, 2023.

J2

  • Ji, Ziwei, et al. "Survey of Hallucination in Natural Language Generation." ACM Computing Surveys 55, no. 12 (2023): 1–38.
  • Johnson, H. Thomas, and Robert S. Kaplan. Relevance Lost: The Rise and Fall of Management Accounting. Boston: Harvard Business School Press, 1987.

K2

  • Kahneman, Daniel, and Gary Klein. "Conditions for Intuitive Expertise: A Failure to Disagree." American Psychologist 64, no. 6 (2009): 515–26.
  • Kaplan, Robert S., and David P. Norton. "The Balanced Scorecard: Measures That Drive Performance." Harvard Business Review 70, no. 1 (1992): 71–79.

L6

  • Leonard, Dorothy, and Walter Swap. Deep Smarts: How to Cultivate and Transfer Enduring Business Wisdom. Boston: Harvard Business School Press, 2005.
  • Levinson, Marc. The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger. Princeton: Princeton University Press, 2006.
  • Levitt, Barbara, and James G. March. "Organizational Learning." Annual Review of Sociology 14 (1988): 319–40.
  • Lewis, Patrick, et al. "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks." Advances in Neural Information Processing Systems 33 (2020): 9459–74.
  • Lichtenstein, Sarah, Baruch Fischhoff, and Lawrence D. Phillips. "Calibration of Probabilities: The State of the Art to 1980." In Judgment under Uncertainty: Heuristics and Biases, edited by Daniel Kahneman, Paul Slovic, and Amos Tversky, 306–34. Cambridge: Cambridge University Press, 1982.
  • Liker, Jeffrey K. The Toyota Way. New York: McGraw-Hill, 2004.

M6

  • March, James G. "Exploration and Exploitation in Organizational Learning." Organization Science 2, no. 1 (1991): 71–87.
  • March, James G., and Herbert A. Simon. Organizations. New York: Wiley, 1958.
  • Markus, M. Lynne, and Cornelis Tanis. "The Enterprise System Experience: From Adoption to Success." In Framing the Domains of IT Management, edited by Robert W. Zmud, 173–207. Cincinnati: Pinnaflex, 2000.
  • Mazzucato, Mariana, and Rosie Collington. The Big Con: How the Consulting Industry Weakens Our Businesses, Infantilizes Our Governments and Warps Our Economies. London: Allen Lane, 2023.
  • Mitchell, Margaret, et al. "Model Cards for Model Reporting." In Proceedings of the Conference on Fairness, Accountability, and Transparency, 220–29. New York: ACM, 2019.
  • Moore, Geoffrey A. Crossing the Chasm. New York: HarperBusiness, 1991.

N8

  • National Institute of Standards and Technology. Artificial Intelligence Risk Management Framework (AI RMF 1.0). NIST AI 100-1. Gaithersburg, MD: NIST, January 2023.
  • National Institute of Standards and Technology. Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile. NIST AI 600-1. Gaithersburg, MD: NIST, July 2024.
  • Nelson, Richard R., and Sidney G. Winter. An Evolutionary Theory of Economic Change. Cambridge, MA: Belknap Press, 1982.
  • Nonaka, Ikujiro. "A Dynamic Theory of Organizational Knowledge Creation." Organization Science 5, no. 1 (1994): 14–37.
  • Nonaka, Ikujiro, and Hirotaka Takeuchi. The Knowledge-Creating Company. New York: Oxford University Press, 1995.
  • Noy, Natalya F., and Michel Klein. "Ontology Evolution: Not the Same as Schema Evolution." Knowledge and Information Systems 6, no. 4 (2004): 428–40.
  • Noy, Shakked, and Whitney Zhang. "Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence." Science 381, no. 6654 (2023): 187–92.
  • Nutt, Paul C. "Surprising but True: Half the Decisions in Organizations Fail." Academy of Management Executive 13, no. 4 (1999): 75–90.

O6

  • OECD. Government at a Glance 2025. Paris: OECD Publishing, 2025.
  • OECD. Recommendation of the Council on Artificial Intelligence. OECD/LEGAL/0449. Paris: OECD, 2019, amended 2024.
  • Ohno, Taiichi. Toyota Production System: Beyond Large-Scale Production. Cambridge, MA: Productivity Press, 1988.
  • O’Neil, Cathy. Weapons of Math Destruction. New York: Crown, 2016.
  • Open Group, The. TOGAF Standard. 10th ed. Reading, UK: The Open Group, 2022.
  • Orlikowski, Wanda J. "Learning from Notes: Organizational Issues in Groupware Implementation." In Proceedings of CSCW ’92, 362–69. New York: ACM, 1992.

P6

  • Parasuraman, Raja, and Victor Riley. "Humans and Automation: Use, Misuse, Disuse, Abuse." Human Factors 39, no. 2 (1997): 230–53.
  • Paulk, Mark C., et al. The Capability Maturity Model: Guidelines for Improving the Software Process. Reading, MA: Addison-Wesley, 1995.
  • Peng, Sida, et al. "The Impact of AI on Developer Productivity: Evidence from GitHub Copilot." arXiv:2302.06590, 2023.
  • Perez, Carlota. Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages. Cheltenham: Edward Elgar, 2002.
  • Pfeffer, Jeffrey, and Robert I. Sutton. Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management. Boston: Harvard Business School Press, 2006.
  • Polanyi, Michael. The Tacit Dimension. Garden City, NY: Doubleday, 1966.

R8

  • Ranft, Annette L., and Michael D. Lord. "Acquiring New Technologies and Capabilities: A Grounded Model of Acquisition Implementation." Organization Science 13, no. 4 (2002): 420–41.
  • Reich, Leonard S. The Making of American Industrial Research: Science and Business at GE and Bell, 1876–1926. Cambridge: Cambridge University Press, 1985.
  • Repenning, Nelson P., and John D. Sterman. "Nobody Ever Gets Credit for Fixing Problems That Never Happened: Creating and Sustaining Process Improvement." California Management Review 43, no. 4 (2001): 64–88.
  • Ridgway, V. F. "Dysfunctional Consequences of Performance Measurements." Administrative Science Quarterly 1, no. 2 (1956): 240–47.
  • Ross, Jeanne W., Peter Weill, and David C. Robertson. Enterprise Architecture as Strategy: Creating a Foundation for Business Execution. Boston: Harvard Business School Press, 2006.
  • Rousseau, Denise M. "Is There Such a Thing as ‘Evidence-Based Management’?" Academy of Management Review 31, no. 2 (2006): 256–69.
  • Rudin, Cynthia. "Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead." Nature Machine Intelligence 1 (2019): 206–15.
  • Rumelt, Richard P. Good Strategy / Bad Strategy: The Difference and Why It Matters. New York: Crown Business, 2011.

S15

  • Senge, Peter M. The Fifth Discipline: The Art and Practice of the Learning Organization. New York: Doubleday, 1990.
  • Shapiro, Carl, and Hal R. Varian. Information Rules: A Strategic Guide to the Network Economy. Boston: Harvard Business School Press, 1999.
  • Shewhart, Walter A. Economic Control of Quality of Manufactured Product. New York: Van Nostrand, 1931.
  • Shook, John. Managing to Learn: Using the A3 Management Process. Cambridge, MA: Lean Enterprise Institute, 2008.
  • Simon, Herbert A. Administrative Behavior. 4th ed. New York: Free Press, 1997. First published 1947.
  • Simon, Herbert A. "Designing Organizations for an Information-Rich World." In Computers, Communications, and the Public Interest, edited by Martin Greenberger, 37–72. Baltimore: Johns Hopkins University Press, 1971.
  • Smith, Barry. "Ontology." In Blackwell Guide to the Philosophy of Computing and Information, edited by Luciano Floridi, 155–66. Oxford: Blackwell, 2003.
  • Smith, Barry, et al. "The OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration." Nature Biotechnology 25, no. 11 (2007): 1251–55.
  • Sobek, Durward K., II, and Art Smalley. Understanding A3 Thinking. New York: Productivity Press, 2008.
  • Spear, Steven, and H. Kent Bowen. "Decoding the DNA of the Toyota Production System." Harvard Business Review 77, no. 5 (1999): 96–106.
  • Stanford Institute for Human-Centered Artificial Intelligence. The AI Index 2026 Annual Report. Stanford, CA: Stanford HAI, 2026.
  • Sterman, John D. "Misperceptions of Feedback in Dynamic Decision Making." Organizational Behavior and Human Decision Processes 43, no. 3 (1989): 301–35.
  • Stigler, George J. "The Economics of Information." Journal of Political Economy 69, no. 3 (1961): 213–25.
  • Sturgeon, Timothy J. "Modular Production Networks: A New American Model of Industrial Organization." Industrial and Corporate Change 11, no. 3 (2002): 451–96.
  • Szulanski, Gabriel. "Exploring Internal Stickiness: Impediments to the Transfer of Best Practice within the Firm." Strategic Management Journal 17, S2 (1996): 27–43.

T7

  • Taylor, Frederick Winslow. The Principles of Scientific Management. New York: Harper, 1911.
  • Teece, David J., Gary Pisano, and Amy Shuen. "Dynamic Capabilities and Strategic Management." Strategic Management Journal 18, no. 7 (1997): 509–33.
  • Tetlock, Philip E. Expert Political Judgment: How Good Is It? How Can We Know? Princeton: Princeton University Press, 2005.
  • Tetlock, Philip E., and Dan Gardner. Superforecasting: The Art and Science of Prediction. New York: Crown, 2015.
  • Toulmin, Stephen E. The Uses of Argument. Cambridge: Cambridge University Press, 1958.
  • Tufte, Edward R. The Cognitive Style of PowerPoint: Pitching Out Corrupts Within. 2nd ed. Cheshire, CT: Graphics Press, 2006.
  • Tversky, Amos, and Daniel Kahneman. "The Framing of Decisions and the Psychology of Choice." Science 211, no. 4481 (1981): 453–58.

U2

  • U.S. Census Bureau. "Firms in Production Sectors and Northern States Have Some of the Highest Shares of Older Workers." Business Dynamics Statistics of Human Capital. Washington, DC: U.S. Census Bureau, 2025.
  • U.S. Department of the Army. TC 25-20: A Leader’s Guide to After-Action Reviews. Washington, DC: Headquarters, Department of the Army, 1993. Superseded by U.S. Army Combined Arms Center, The Leader’s Guide to After-Action Reviews (AAR), Fort Leavenworth, KS, 2013.

V1

  • Vaughan, Diane. The Challenger Launch Decision: Risky Technology, Culture, and Deviance at NASA. Chicago: University of Chicago Press, 1996.

W9

  • Walsh, James P., and Gerardo Rivera Ungson. "Organizational Memory." Academy of Management Review 16, no. 1 (1991): 57–91.
  • Wenger, Etienne. Communities of Practice: Learning, Meaning, and Identity. Cambridge: Cambridge University Press, 1998.
  • Wernerfelt, Birger. "A Resource-Based View of the Firm." Strategic Management Journal 5, no. 2 (1984): 171–80.
  • Whittaker, Steve, and Candace Sidner. "Email Overload: Exploring Personal Information Management of Email." In Proceedings of CHI ’96, 276–83. New York: ACM, 1996.
  • Wilensky, Harold L. Organizational Intelligence: Knowledge and Policy in Government and Industry. New York: Basic Books, 1967.
  • Womack, James P., Daniel T. Jones, and Daniel Roos. The Machine That Changed the World. New York: Rawson Associates, 1990.
  • World Wide Web Consortium. OWL 2 Web Ontology Language Document Overview. 2nd ed. W3C Recommendation, 2012.
  • World Wide Web Consortium. PROV-DM: The PROV Data Model. W3C Recommendation, 30 April 2013.
  • World Wide Web Consortium. RDF 1.1 Concepts and Abstract Syntax. W3C Recommendation, 2014.

Z1

  • Zachman, John A. "A Framework for Information Systems Architecture." IBM Systems Journal 26, no. 3 (1987): 276–92.