BSc Management (Innovation, Strategy and Entrepreneurship)

The course discusses a wide range of topics from recent economics literature on AI and the digital economy. These include the theory of network industries, multi-sided platforms, platform strategies, platform design, platform business models, big data analytics in online platform businesses, online pricing strategies, algorithmic pricing, online start-ups, AI technologies, generative AI, cognitive automation, big data analytics in platform businesses, AI start-ups, financial technology platforms, payment networks, blockchain and virtual currencies, firm digital transformation, strategic decisions for incumbent firms in adopting digital technologies, automation, and competition policies for the digital world.

Above all, the course will deeply delve into the very recent AI literature, particularly, generative AI to develop a rich conceptual framework for systematically understanding potential applications of AI in business and impact on the economy, labour market and the future of work. AI-driven businesses are thoroughly discussed.  

The course is an excellent fit for anyone considering starting a business or joining a start-up in the digital platform space, or those trying to decide which sector or business to focus on, as it draws on rich, recent economic and firm data to support empirically based analyses, enabling to gain a deep understanding of AI technologies.  

 

BMAN10001 is a Pre-Requisite for BMAN31952. Only available to students on: Mgt/Mgt Specialism; IMABS; IM and ITMB/ITMB Specialism.

This unit is core for ITMB students.

The unit aims to provide a solid understanding of foundational concepts, theories and technologies that are essential for understanding the digital economy. It offers a thorough review of platform strategies / competition and covers the emerging literature on corporate digital transformation: the process by which traditional firms adopt digital and AI technologies (including generative AI) to adapt to changes in the market.

The course also aims to demonstrate how emerging technologies such as AI, generative AI, machine learning algorithms, and Blockchain, joined with platform technologies, have begun to transform industries such as the financial sector, retail, advertising, healthcare, manufacturing, services, and transportation.

By examining a rich list of cases and data and using recent theories, the course aims to help students to form a systematic view of how digital technologies are likely to shape corporations and industries and change the nature of competition.

Finally, by examining numerous young online firms from different sectors, the course will seek to explain the process of start-up formation and show how to set up an online business.

The course combines recent economic theories with a rich selection of case materials to provide both an analytical and applied understanding of the digital economy / AI, supported by up-to-date data on each topic. 

•    Understand the logic of network industries, gain a solid understanding of the theory of multi-sided platform, AI (artificial intelligence) technologies and digital business,
•    Understand platform leadership strategies, platform competition, and algorithmic pricing,
•    Gain a solid knowledge of online / platform start-ups and their growth strategies, and learn how to establish and growth our online business
•    Understand platform design - various key components forming modern online platforms such as recommender and reputation systems as well as governance rules,
•    Form a sound understanding of the AI revolution, Blockchain and general-purpose technologies, and explore how these technologies are likely to transform businesses
•    Gain an understanding of how platform technologies, AI and cloud technologies have already begun to transform industries such as finance, providing a good understanding of Fintech start-ups
•    Understand challenges faced in digital transformation of industries and firms and relevant tactics and strategies - the process of corporate digital transformation,
•    Understand dominant internet business models and how to generate new online business models
•    Develop an ability to use Excel or R to analyse data in business decision making in firms.
•    Develop an ability to make sense of economic data / news in an intuitive manner to enhance decision making in the firm.
•    Design business strategies for growing and running digital marketplaces.
 

Methods of delivery: Lecture and practices (2 hour per week). The first hour of the lecture will cover theory and second hour will apply the theory to business cases and discuss emerging digital / AI start-ups.

Total study hours: 200 hours split between lectures, classes, self-study and preparation for classes, coursework and examinations.
 

Understand the logic of network industries, gain a solid understanding of the theory of multi-sided platform, AI (artificial intelligence) technologies and digital business.

Understand platform leadership strategies, platform competition, and algorithmic pricing.

Gain a solid knowledge of online / platform start-ups and their growth strategies, and learn how to establish and growth our online business

Understand platform design - various key components forming modern online platforms such as recommender and reputation systems as well as governance rules,

Understand emerging cognitive automation technologies, how they are transforming businesses, work, firms and the economy. 

Form a sound understanding of the AI revolution, Blockchain and general-purpose technologies, and explore how these technologies are likely to transform businesses.

Gain an understanding of how platform technologies, AI and cloud technologies have already begun to transform industries such as finance, providing a good understanding of Fintech start-ups.

Understand challenges faced in digital transformation of industries and firms and relevant tactics and strategies - the process of corporate digital transformation. 

Develop an ability to make sense of economic data / news in an intuitive manner to enhance decision making in the firm.

Design business strategies for growing and running digital marketplaces.

Understand dominant AI business models and how to generate new online business models 

Skills to develop prompts to use generative AI tools to assist with planning, problem solving and ideation.  

Skills to train machine learning algorithms

Skills to use Excel or R / Python to analyse data to support business decision making in firms. 

Formative: 12 short weekly mock randomised MCQ tests 

Mid-term online randomized multiple-choice test (15%)
End of term online randomized multiple-choice test (15%)
Final Individual Economic Project (70%)
 

•    Informal advice and discussion during a lecture, seminar, workshop or lab.
•    Responses to student emails and questions from a member of staff including feedback provided to a group via an online discussion forum.
•    Written and/or verbal comments on assessed or non-assessed coursework.
 

McAfee, A. and Brynjolfsson, E., 2017. Machine, platform, crowd: Harnessing our digital future. WW Norton & Company.

Agrawal, A., Gans, J. and Goldfarb, A., 2018. Prediction machines: the simple economics of artificial intelligence. Harvard Business Press.

The course comes with extensive self-sufficient teaching materials that cover advance topics not found in textbooks. The materials will mainly draw on research papers. In addition, the course will draw on:

Gawer, A. (Ed.). (2011). Platforms, markets and innovation. Edward Elgar Publishing

Peitz, M. and Waldfogel, J. eds., 2012. The Oxford handbook of the digital economy. Oxford University Press.
 

 

Additional notes
Programme Restrictions: BSc Management and Management (Specialisms), BSc International Management, BSc ITMB.

For Academic Year 2024/25

Updated: March 2024

Approved by: March UG Committee