The Evolutionary Dynamics of the Artificial Intelligence Ecosystem

References

• Adner R (2017) Ecosystem as structure: An actionable construct for strategy. J. Management Stud. 43(1):39–58.Google Scholar
• Adner R , Kapoor R (2010) Value creation in innovation ecosystems: How the structure of technological interdependence affects firm performance in new technology generations. Strategic Management J. 31(3):306–333.Crossref, Google Scholar
• Adner R , Puranam P , Zhu F (2019) What is different about digital strategy? From quantitative to qualitative change. Strategy Sci. 4(4):253–261.Link, Google Scholar
• Aghion P , Jones B , Jones C (2019a) Artificial intelligence and economic growth. Agrawal A , Gans J , Goldfarb A , eds. The Economics of Artificial Intelligence: An Agenda (University of Chicago Press, Chicago), 237–290.Google Scholar
• Aghion P , Bergeaud A , Boppart T , Klenow PJ , Li H (2019b) A theory of falling growth and rising rents. NBER Working Paper w26448. https://www.nber.org/system/files/working_papers/w26448/w26448.pdf.Google Scholar
• Agrawal A , Gans J , Goldfarb A (2019) The Economics of Artificial Intelligence: An Agenda (The University of Chicago Press, Chicago).Crossref, Google Scholar
• Alekseeva L , Azar J , Gine M , Samila S , Taska B (2019) The demand for AI skills in the labor market. Preprint, submitted October 25, DOI: https://dx.doi.org/10.2139/ssrn.3470610.Google Scholar
• Allen B , Gish R , Dreyer K (2019) The role of an artificial intelligence ecosystem in radiology. Ranschaert ER , Morozov S , Algra PR , eds. Artificial Intelligence in Medical Imaging (Springer, New York), 291–327.Crossref, Google Scholar
• Arenal A , Armuña C , Feijoo C , Ramos S , Xu Z , Moreno A (2020) Innovation ecosystems theory revisited: The case of artificial intelligence in China. Telecommunications Policy 44(6):101960.Crossref, Google Scholar
• Arora A , Belenzon S , Patacconi A (2018) The decline of science in corporate R&D. Strategic Management J. 39(1):3–32.Crossref, Google Scholar
• Autor D , Dorn D , Katz LF , Patterson C , Van Reenen J (2020) The fall of the labor share and the rise of superstar firms. Quart. J. Econom. 135(2):645–709.Crossref, Google Scholar
• Babina T , Fedyk A , He A , Hodson J (2020) Artificial intelligence, firm growth, and industry concentration. Preprint, submitted August 27, DOI: https://dx.doi.org/10.2139/ssrn.3651052.Google Scholar
• Baldwin C (2018) Bottlenecks, modules, and dynamic architectural capabilities. Teece DJ , Heaton S , eds. The Oxford Handbook of Dynamic Capabilities (Oxford University Press, Oxford, UK). https://www.oxfordhandbooks.com/view/10.1093/oxfordhb/9780199678914.001.0001/oxfordhb-9780199678914-e-011.Crossref, Google Scholar
• Baldwin C , Clark K (2000) Design Rules Volume 1: The Power of Modularity (MIT Press, Cambridge, MA).Crossref, Google Scholar
• Baldwin C , Woodard C (2009) The architecture of platforms: A unified view. Gawer A , eds. Platforms, Markets and Innovation (Edward Elgar Publishing, Cheltenham, UK), 19–44.Crossref, Google Scholar
• Barney J (1991) Firm resources and sustained competitive advantage. J. Management Stud. 17(1):99–120.Google Scholar
• Bloom N , Van Reenen J (2010) Why do management practices differ across firms and countries? J. Econom. Perspect. 24(1):203–224.Crossref, Google Scholar
• Boudreau K (2010) Open platform strategies and innovation: Granting access vs. devolving control. Management Sci. 56(10):1849–1872.Link, Google Scholar
• Breschi S , Orsenigo L , Malerba F (2000) Technological regimes and Schumpeterian patterns of innovation. Econom. J. (London) 110(463):388–410.Google Scholar
• Bresnahan T , Trajtenberg M (1995) General-purpose technologies “engines of growth”? J. Econometrics 65(1):83–108.Crossref, Google Scholar
• Brock J , von Wangenheim F (2019) Demystifying AI: What digital transformation leaders can teach you about realistic artificial intelligence. California Management Rev. 61(4):110–134.Crossref, Google Scholar
• Brin S , Page L (1998) The anatomy of a large-scale hypertextual web search engine. Comput. Networks ISDN Systems 30(1–7):107–117.Crossref, Google Scholar
• Brusoni S , Prencipe A , Pavitt K (2001) Knowledge specialization, organizational coupling, and the boundaries of the firm: Why do firms know more than they make? Admin. Sci. Quart. 46(4):597–621.Crossref, Google Scholar
• Brynjolfsson E , Hitt L (2000) Beyond computation: Information technology, organizational transformation and business performance. J. Econom. Perspect. 14(4):23–48.Crossref, Google Scholar
• Brynjolfsson E , Rock D , Syverson C (2019) Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics. Agrawal A , Gans J , Goldfarb A , eds. The Economics of Artificial Intelligence: An Agenda (University of Chicago Press, Chicago), 23–60.Crossref, Google Scholar
• Bughin J , Seong J , Manyika J , Chui M , Joshi R (2018) Notes from the AI Frontier: Modelling the Impact of AI on the World Economy (McKinsey Global Institute, McKinsey & Company).Google Scholar
• Burström T , Parida V , Lahti T , Wincent J (2021) AI-enabled business-model innovation and transformation in industrial ecosystems: A framework, model and outline for further research. J. Bus. Res. 127:85–95.Crossref, Google Scholar
• Candelon F , Reichert T , Duranton S , Charme di Carlo R , Stokol G (2020) Deploying AI to Maximize Revenue. Boston Consulting Group.Google Scholar
• Cefis E , Ciccarelli M (2005) Profit differentials and innovation. Econom. Innovation New Tech. 14(1–2):43–61.Crossref, Google Scholar
• Chan-Olmsted SM (2019) A review of artificial intelligence adoptions in the media industry. Internat. J. Media Management 21(3–4):193–215.Crossref, Google Scholar
• Clough DR , Wu A (2020) Artificial intelligence, data-driven learning, and the decentralized structure of platform ecosystems. Acad. Management Rev. DOI: https://doi.org/10.5465/amr.2020.0222.Crossref, Google Scholar
• Coase RH (1937) Some notes on monopoly price. Rev. Econom. Stud. 5(1):17–31.Crossref, Google Scholar
• Cockburn I , Henderson R , Stern S (2019) 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), 115–148.Crossref, Google Scholar
• Cohen W , Levinthal D (1990) Absorptive capacity: A new perspective on learning and innovation. Admin. Sci. Quart. 35(1):128–152.Crossref, Google Scholar
• Dhar P (2020) The carbon impact of artificial intelligence. Nature Machine Intelligence 2:423–425.Crossref, Google Scholar
• Dhinakaran A (2020) The AI ecosystem is a mess. Accessed February 11, 2021, https://towardsdatascience.com/the-ai-ecosystem-is-a-mess-c46bdfbf43e4.Google Scholar
• Economist (2017) Data are giving rise to a new economy. Accessed February 12, 2021, https://www.economist.com/briefing/2017/05/06/data-is-giving-rise-to-a-new-economy.Google Scholar
• Etchemendy J , Li F (2020) National research Cloud: Ensuring the continuation of American innovation. Accessed February 11, 2021, https://hai.stanford.edu/blog/national-research-cloud-ensuring-continuation-american-innovation.Google Scholar
• Ethiraj S (2007) Allocation of inventive effort in complex product systems. Strategic Management J. 28(6):563–584.Crossref, Google Scholar
• Etzkowitz H , Leydesdorff L (1995) The triple helix–university–industry–government relations: A laboratory for knowledge based economic development. EASST Rev. 14(1):14–19.Google Scholar
• Etzkowitz H, Leydesdorff L (2000) The dynamics of innovation: From National Systems and “Mode 2” to a Triple Helix of university-industry-government relations. Res. Policy 29(2):109–123.Google Scholar
• European Commission (2020) Artificial intelligence: A European approach to excellence and trust. White paper. https://ec.europa.eu/info/publications/white-paper-artificial-intelligence-european-approach-excellence-and-trust_en.Google Scholar
• Executive Office of the President (2019) Maintaining American leadership in artificial intelligence. Executive Order 1385. Federal Register 84(31):3967–3972. DOI: https://www.federalregister.gov/documents/2019/02/14/2019-02544/maintaining-american-leadership-in-artificial-intelligence.Google Scholar
• Freeman C (1995) The ‘National System of Innovation’ in historical perspective. Cambridge J. Econom. 19(1):5–24.Google Scholar
• Freeman C , Louçã F (2001) As Time Goes By: From the Industrial Revolutions to the Information Revolution (Oxford University Press, Oxford, UK).Google Scholar
• Furman J , Seamans R (2019) AI and the economy. Innovation Policy Econom. 19(1):161–191.Crossref, Google Scholar
• Furman JL , Teodoridis F (2020) Automation, research technology, and researchers’ trajectories: Evidence from computer science and electrical engineering. Organ. Sci. 31(2):330–354.Link, Google Scholar
• Garbuio M , Lin N (2019) Artificial intelligence as a growth engine for healthcare startups: Emerging business models. California Management Rev. 61(2):59–83.Crossref, Google Scholar
• Gawer A , Cusumano MA (2002) Platform Leadership: How Intel, Microsoft, and Cisco Drive Industry Innovation (Harvard Business School Press, Boston).Google Scholar
• Gawer A , Cusumano MA (2014) Industry platforms and ecosystem innovation. J. Production Innovation Management 31(3):417–433.Crossref, Google Scholar
• Gerbert P , Hecker M , Steinhäuser S , Ruwolt P (2017) Putting artificial intelligence to work. Accessed February 12, 2021, https://www.bcg.com/fr-fr/publications/2017/technology-digital-strategy-putting-artificial-intelligence-work.Google Scholar
• Goldfarb A , Taska B , Teodoridis F (2020) Artificial intelligence in healthcare? Evidence from online job postings. AEA Papers Proc. 110:400–404.Crossref, Google Scholar
• He X , Zhao K , Chu X (2020) AutoML: A survey of the state-of-the-art. Knowledge-Based Systems 212:106622.Crossref, Google Scholar
• Herr T (2020) Four myths about the cloud: The geopolitics of cloud computing. The Atlantic Council, Washington DC. https://www.atlanticcouncil.org/wp-content/uploads/2020/09/CLOUD-MYTHS-REPORT.pdf.Google Scholar
• Herweijer C , Combes B , Ramchandani P , Sidhu J (2018) Harnessing artificial intelligence for the Earth. PwC, World Economic Forum, Stanford Woods Institute for the Environment (World Economic Forum, Geneva).Google Scholar
• Hobday M (1998) Product complexity, innovation and industrial organisation. Res. Policy 26(6):689–710.Crossref, Google Scholar
• Hughes TP (1993) Networks of Power: Electrification in Western Society, 1880-1930 (Johns Hopkins University Press, Baltimore).Google Scholar
• Iansiti M , Lakhani KR (2020) Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World (Harvard Business School Press, Boston).Google Scholar
• Jacobides MG (2010) Strategy tools for a shifting landscape. Harvard Bus. Rev. 88(1):76–85.Google Scholar
• Jacobides MG , Lianos I (2021) Ecosystems and competition law in theory and practice. Preprint, submitted February 18, DOI: https://dx.doi.org/10.2139/ssrn.3772366.Google Scholar
• Jacobides MG , Tae CJ (2015) Kingpins, bottlenecks, and value dynamics along a sector. Organ. Sci. 26(3):889–907.Link, Google Scholar
• Jacobides MG , Winter SG (2005) The co-evolution of capabilities and transaction costs: Explaining the institutional structure of production. Strategic Management J. 26(5):395–413.Crossref, Google Scholar
• Jacobides MG , Winter SG (2012) Capabilities: Structure, agency, and evolution. Organ. Sci. 23(5):1365–1381.Link, Google Scholar
• Jacobides MG , Bruncko M , Langen R (2020) Regulating Big Tech in Europe: Why, so what, and how understanding their business models and ecosystems can make a difference. Evolution Ltd White Paper. Accessed July 8, 2021, https://www.evolutionltd.net/post/regulating-big-tech-in-europe.Google Scholar
• Jacobides MG , Brusoni S , Prencipe A (2009) Strategic dynamics in industry architectures and the challenges of knowledge integration. Eur. Management Rev. 6(4):209–216.Crossref, Google Scholar
• Jacobides MG , Cennamo C , Gawer A (2018) Toward a theory of business ecosystems. Strategic Management J. 39(8):2255–2276.Crossref, Google Scholar
• Jacobides MG , Knudsen T , Augier M (2006) Benefiting from innovation: Value creation, value appropriation and the role of industry architectures. Res. Policy 35(8):1200–1221.Crossref, Google Scholar
• Jacobides MG , MacDuffie JP , Tae CW (2016) Agency, structure, and OEM dominance: Change and stability in the automotive sector. Strategic Management J. 37(9):1942–1967.Crossref, Google Scholar
• Kaplan J , McCandlish S , Henighan T , Brown TB , Chess B , Child R , Gray S , Radford A , Wu J , Amodei D (2020) Scaling laws for neural language models. Preprint, submitted January 23, https://arxiv.org/abs/1401.0212.2001.08361.Google Scholar
• Kim N , Lee H , Kim W , Lee H , Suh JH (2015) Dynamic patterns of industry convergence: Evidence from a large amount of unstructured data. Res. Policy 44(9):1734–1748.Crossref, Google Scholar
• Kumar V , Rajan B , Venkatesan R , Lecinski J (2019) Understanding the role of artificial intelligence in personalized engagement marketing. California Management Rev. 61(4):135–155.Crossref, Google Scholar
• Lashkari D , Bauer A , Boussard J (2018) Information technology and returns to scale. Preprint, submitted May 17, https://dx.doi.org/10.2139/ssrn.3458604.Google Scholar
• Lee KF (2018) AI Superpowers: China, Silicon Valley, and The New World Order (Houghton Mifflin Harcourt, Boston).Google Scholar
• Lundvall BÅ (1992) National Systems of Innovation: Toward a Theory of Innovation and Interactive Learning (Anthem Press, New York).Google Scholar
• Lundvall BÅ (2007) National innovation systems—Analytical concept and development tool. Indust. Innovation 14(1):95–119.Crossref, Google Scholar
• Malerba F (2004) Sectoral systems of innovation: Basic concepts. Malerba F , ed. Sectoral Systems of Innovation Concepts, Issues and Analyses of Six Major Sectors in Europe (Cambridge University Press, Cambridge, UK), 9–41.Crossref, Google Scholar
• Malerba F , Orsenigo L (1999) Technological entry, exit and survival: An empirical analysis of patent data. Res. Policy 28(6):643–660.Crossref, Google Scholar
• Malerba F , Nelson R , Orsenigo L , Winter S (2016) Innovation and the Evolution of Industries: History-Friendly Models (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
• Marcus G (2018) Deep learning: A critical appraisal. Preprint, submitted January 2, https://arxiv.org/abs/1401.0212.1801.00631.Google Scholar
• Metcalfe J (1994) Evolutionary economics and technology policy. Econom. J. (London) 104(425):931–944.Google Scholar
• Mihet R , Philippon T (2019) The economics of big data and artificial intelligence. Choi JJ , Ozkan B , eds. Disruptive Innovation in Business and Finance in the Digital World (Emerald, Bingley, UK), 29–43.Crossref, Google Scholar
• Miller R , Laird R (2019) Reshaping the global IT landscape: The impact of hyperscale data centers. Accessed February 11, 2021, https://datacenterfrontier.com/reshaping-the-global-it-landscape-the-impact-of-hyperscale-data-centers/.Google Scholar
• Mou XM (2019) Artificial Intelligence: Investment Trends and Selected Industry Uses (International Finance Corporation).Google Scholar
• Nelson RR (1994) The co-evolution of technology, industrial structure, and supporting institutions. Indust. Corporate Change 3(1):47–63.Crossref, Google Scholar
• Nelson RR (2020) A perspective on the evolution of evolutionary economics. Indust. Corporate Change 29(5):1101–1118.Crossref, Google Scholar
• Nelson RR , Winter SG (1982) An Evolutionary Theory of Economic Change (Belknap Press, Cambridge, MA).Google Scholar
• Nuvolari A (2005) Open source software development: Some historical perspectives. First Monday 10(10):3.Google Scholar
• Parker GG , Van Alstyne MW , Choudary SP (2016) Platform Revolution: How Networked Markets Are Transforming the Economy and How to Make Them Work for You (WW Norton & Company, New York).Google Scholar
• Pisano GP , Teece DJ (2007) How to capture value from innovation: Shaping intellectual property and industry architecture. California Management Rev. 50(1):278–296.Crossref, Google Scholar
• Pratt GA (2015) Is a Cambrian explosion coming for robotics? J. Econom. Perspect. 29(3):51–60.Crossref, Google Scholar
• Ransbotham S , Khodabandeh S , Kiron D , Candelon F , Chu M , LaFountain B (2020) Expanding AI’s Impact with Organizational Learning (MIT Sloan Management Review and Boston Consulting Group).Google Scholar
• Rock D (2019) Engineering value: The returns to technological talent and investments in artificial intelligence. Preprint, submitted July 30, https://dx.doi.org/10.2139/ssrn.3427412.Google Scholar
• Rosenberg N (1982) Inside the Black Box: Technology and Economics (Cambridge University Press, Cambridge, UK).Google Scholar
• Saviotti PP (2005) Innovation systems and evolutionary theories. Edquist C , ed. Systems of Innovation: Technologies, Institutions, and Organizations (Pinter Publishers/Cassell Academic, London), 180–199.Google Scholar
• Schumpeter JA (1912) Theorie der wirtschaftlichen Entwicklung (Duncker & Humblot, Leipzig, Germany).Google Scholar
• Schumpeter JA (1942) Capitalism, Socialism, and Democracy (Harper and Brothers, New York).Google Scholar
• Sharir O , Peleg B , Shoham Y (2020) The cost of training NLP models: A concise overview. Preprint, submitted April 19, https://arxiv.org/abs/1401.0212.08900v1.Google Scholar
• Shrestha YR , Ben-Menahem SM , Von Krogh G (2019) Organizational decision-making structures in the age of artificial intelligence. California Management Rev. 61(4):66–83.Crossref, Google Scholar
• Simon HA (1970) The Sciences of the Artificial (MIT Press, Cambridge, MA).Google Scholar
• Simon JP (2019) Artificial intelligence: Scope, players, markets and geography. Digital Policy Regulation Governance 21(3):208–237.Crossref, Google Scholar
• Sosa LM (2013) Decoupling market incumbency from organizational prehistory: Locating the real sources of competitive advantage in R&D for radical innovation. Strategic Management J. 34(2):245–255.Crossref, Google Scholar
• Sudarshan PN , Abhishek V , Gupta G (2017) Artificial Intelligence: Why businesses need to pay attention to artificial intelligence? Deloitte Touche Tohmatsu India LLP, Member of Deloitte Touche Tohmatsu Limited.Google Scholar
• Tambe P , Hitt LM , Rock D , Brynjolfsson E (2019) IT, AI and the growth of intangible capital. Preprint, submitted August 6, DOI: https://dx.doi.org/10.2139/ssrn.3416289.Google Scholar
• Teece D , Pisano G , Schuen A (1997) Dynamic capabilities and strategic management. Strategic Management J. 18(7):509–533.Crossref, Google Scholar
• Varian HR (2019) Artificial intelligence, economics, and industrial organization. Agrawal A , Gans J , Goldfarb A , eds. The Economics of Artificial Intelligence (University of Chicago Press, Chicago), 399–422.Crossref, Google Scholar
• Winter SG (1995) Four Rs of profitability: Rents, resources, routines, and replication. Montgomery CA , ed. Resource-based and Evolutionary Theories of the Firm: Toward a Synthesis (Springer, Boston), 147–178.Crossref, Google Scholar
• Zigbee Alliance (2020) Amazon, Apple, Google, and the Zigbee alliance and its board Members FORM industry working group to develop a new, open standard for smart home device connectivity. Accessed February 11, 2021, https://zigbeealliance.org/news_and_articles/connectedhomeip/.Google Scholar
• Zuboff S (2015) Big other: Surveillance capitalism and the prospects of an information civilization. J. Inform. Tech. 30(1):75–89.Crossref, Google Scholar