Youngjin Yoo

This course is available on the CEMS Exchange, Global MSc in Management, Global MSc in Management (CEMS MIM), Global MSc in Management (MBA Exchange), MBA Exchange, MSc in Management (1 Year Programme), MSc in Management (1 Year Programme) (Work Placement Pathway), MSc in Management of Information Systems and Digital Innovation and MSc in Media and Communications (Data and Society). This course is available with permission as an outside option to students on other programmes where regulations permit. This course uses controlled access as part of the course selection process. For information on controlled access courses, including eligibility, application processes, deadlines, and departmental contact details, please refer to the Controlled Access Courses webpage.

How to apply:

Places on oversubscribed courses will be allocated via a random ballot process with priority given to students with the course in their Programme Regulations, followed by other Department of Management students, then students from elsewhere in the school. Providing you apply before the Department deadline of 10am on Monday 28 September 2026, the time you applied will not be taken into account. Please be aware that places on high demand courses cannot be guaranteed. By submitting an application, students are confirming that they meet any pre-requisites specified. Providing an additional written statement will not aid a student’s chances of being accepted onto a course, and statements are not read.

For further information and updates on course availability during Week 1, please see the Department of Management Electives Moodle page.

Deadline for application:

Please apply by 10am on Monday 28 September 2026 with your first course choices. No allocations are made before this date and time.

For queries contact:

Please view the Department of Management Electives page for contact emails.

Priority will be given to students on the MSc in Management of Information Systems and Digital Innovation programme.

Every socio-technical theory of technology innovation rests on a theory of value, the firm and technology. Because different machines impose different constraints on what can be produced and how it can be exchanged, each technological era generates its own logic of value creation and its own organizational form. The physical machines of the industrial era produced goods under scarcity: marginal costs were positive, marginal utility was diminishing, and firms existed to economise on transaction costs. The smart machines of the internet era connected users under network effects: platforms emerged to internalise the value spillovers that individual firms could not capture alone. The generative machines of the present era — large language models, foundation models, agentic systems — do something neither predecessor could do: they constitute value at runtime through semantic recombination of distributed resources. This course examines what changes when machines can do that. 

Generative machines can constitute value at runtime because three properties of digital technology have simultaneously inverted. The course calls these the Digital Inversion (from scarcity to ubiquity), the Organic Inversion (from deterministic to indeterministic architecture), and the Semantic Inversion (from syntactic to semantic computation). Each is necessary. None is sufficient. Their interaction produces what the course calls generative externality — systematic surplus value from unanticipated recombination at runtime — and this concept anchors the second half of the course. 

The first four weeks establish the theoretical foundations: industrial logic and its limits, the three inversions, and the technical substrate of generative machines. The middle weeks develop the consequences for value creation and organizational form: the digital value loop, endogenous utility, generative externality as a new theory of the firm alongside transaction cost and network externality theories, and the unbundling of organizations through API architectures. The final weeks confront what can go wrong — narcissistic reflection, mimetic escalation, winner-takes-all concentration — and what design demands in response: regulation, architecture, and mechanism design, and ultimately, the practical wisdom required to design systems whose runtime behaviour the designer cannot fully anticipate. 

20 hours of lectures and 10 hours of seminars in the Winter Term.

This course has a reading week in Week 6 of Winter Term.

In its Ethics Code, LSE upholds a commitment to intellectual freedom. This means we will protect the freedom of expression of our students and staff and the right to engage in healthy debate in the classroom.

Classes are based around reading and discussing select journal articles and case studies. Formative feedback is provided on class participation. In addition, formative assessments on individual research essay include:

• An initial proposal for the research paper (500 words).

• Acemoglu, D. (2024). "The Simple Macroeconomics of AI," NBER Working Paper 32487. 
• Acemoglu, D., and Lensman, T. (2024). "Regulating Transformative Technologies," American Economic Review: Insights (6:3), pp. 359–376. 
• Chatterji, A., Cunningham, T., Deming, D. J., Hitzig, Z., Ong, C., Shan, C. Y., and Wadman, K. (2025). "How People Use ChatGPT," NBER Working Paper No. 34255. 
• Coase, R. H. (1937). "The Nature of the Firm," Economica (4:16), pp. 386–405. 
• Goldfarb, A., and Tucker, C. (2019). "Digital Economics," Journal of Economic Literature (57:1), pp. 3–43. 
• Handa, K., et al. (2025). "Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations," Anthropic. 
• Katz, M. L., and Shapiro, C. (1985). "Network Externalities, Competition, and Compatibility," American Economic Review (75:3), pp. 424–440. 
• Parker, G., Van Alstyne, M., and Jiang, X. (2017). "Platform Ecosystems," MIS Quarterly (41:1), pp. 255–266. 
• Turing, A. M. (1950). "Computing Machinery and Intelligence," Mind (59:236), pp. 433–460. 
• Vaswani, A., et al. (2017). "Attention Is All You Need," arXiv. 
• Baldwin, C. Y. (2024). Design Rules, Volume 2: How Technology Shapes Organizations. MIT Press. 
• Fishman, S., and McLarty, M. 2024. Unbundling the Enterprise: APIs, Optionality, and the Science of Happy Accidents, IT Revolution. 
• Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform Revolution. WW Norton & Company. 
• Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). “Research Commentary—The New Organizing Logic of Digital Innovation: An Agenda for Information Systems Research,” Information Systems Research, 21(4), 724–735. 
• Baskerville, R. L., Myers, M. D., and Yoo, Y. 2020. “Digital First: The Ontological Reversal and New Challenges for Information Systems Research,” MIS Quarterly (44:2), pp. 509–523. (https://doi.org/10.25300/MISQ/2020/14418). 
• Um, S., Zhang, B., Wattal, S., and Yoo, Y. 2023. “Software Components and Product Variety in a Platform Ecosystem: A Dynamic Network Analysis of WordPress,” Information Systems Research (34:4), pp. 1339–1374. (https://doi.org/10/gsdqwh). 
• Yoo. 2010. “Computing in Everyday Life: A Call for Research on Experiential Computing,” MIS Quarterly (34:2), p. 213. (https://doi.org/10.2307/20721425). 
• Yoo, Y., and Euchner, J. 2020. “Digital First Thinking for Industrial Companies: An Interview with Youngjin Yoo,” Research-Technology Management (63:3), pp. 12–18. (https://doi.org/10/gtgd3w). 
• Yoo, Y., Henfridsson, O., Kallinikos, J., Gregory, R., Burtch, G., Chatterjee, S., and Sarker, S. 2024. “The Next Frontiers of Digital Innovation Research,” Information Systems Research, v35.n4. (https://doi.org/10.1287/isre.2024.editorial.v35.n4). 
• Zhang, Z., Yoo, Y., Lyytinen, K., and Lindberg, A. 2021. “The Unknowability of Autonomous Tools and the Liminal Experience of Their Use,” Information Systems Research. (https://doi.org/10.1287/isre.2021.1022). 
• Faulkner, P., & Runde, J. (2019). “Theorizing the Digital Object,” MIS Quarterly, 43(4), 1279–1302. 

Course participation (10%).

Research paper (40%).

Project (50%).

This component of assessment includes an element of group work.

Group Project (50%): Students will collaborate in groups to analyse a contemporary generative platform or technology, evaluating its organizational impacts, economic implications, and ethical considerations. The final presentation and report will be delivered in the last week of the course.

Class participation (10%): Students are expected to have read the material thoroughly to participate in class discussions.

Individual Research Paper (40%): A 3,000-word research paper due at the end of the term that explores a self-chosen topic related to digital-first strategies, the platform economy, or generative technologies. Students will submit a proposal in week 4 and an outline by week 7, receiving formative feedback to guide their research and writing process.

For detailed assessment information, including all deadlines and timings, please see the relevant course Moodle page. Assessment timings will be available at the start of each term.