• Understand the strategic role of technology in and for organisations, i.e., gain a deep understanding of how technology shapes the efficiency, effectiveness, and performance of organizations, industries and societies. • Engage critically with core concepts: explore and critically analyse theories while reflecting on their practical applications in diverse settings. • Develop problem-framing and problem-solving skills: cultivate the ability to critical assess and address complex and discontinuous challenges, considering factors such as culture, leadership, technology, AI, and environmental uncertainty.

By the end of the course, students will be able to: • Understand the strategic role of technology and innovation in shaping firms, industries and markets. • Distinguish among different sources, types and patterns of innovation. • Analyse how firms create, capture and protect value from technological change. • Explain why established firms often struggle with disruptive or architectural innovation. • Understand how organisations can be designed to support both exploitation and exploration. • Interpret innovation as an economic, organisational and social process rather than a purely technical event. • Assess how platforms, ecosystems and digital infrastructures reshape competition and collaboration. • Critically analyse the implications of artificial intelligence for technology management, work and organisation. • Develop problem-framing, analytical and communication skills through cases, class discussion and oral assessment.

Technology matters because it reshapes firms, markets, industries and society. Managing technology therefore requires the ability to understanding how technologies work, how technological change emerges, how it becomes economically and organisationally consequential, and how firms can mobilise knowledge, resources, routines and imagination to turn technological possibilities into innovation. The course introduces students to the strategic and organisational perspectives on technology and innovation. It examines sources and patterns of technological change; the economics of innovation; technology strategy; business model innovation; appropriability and complementary assets; market-innovation interfaces; disruption and incumbent response; organisational routines and ambidexterity; platforms and ecosystems; and the implications of artificial intelligence for work, organising and the management of technology.

Attending students: course materials (papers and cases) as reported in the syllabus. Non attending students: - course materials (papers and cases) as reported in the syllabus. - Melissa Schilling. Strategic Management of Technological Innovation (6th ed) New York: McGraw-Hill Publishers.

Course architecture and educational approach Course logic. This is a multi-voice course. The course is organised around three connected blocks: (1) technology as competitive strategy; (2) innovation as organisational capability; and (3) innovation as experimentation under uncertainty. The aim is to avoid a narrow understanding of technology management as the administration of technical assets. Technology is treated as a strategic, organisational, and epistemic phenomenon: it reshapes markets, requires new organisational capabilities, and demands disciplined forms of learning under uncertainty. Weekly rhythm. Each week includes two complementary sessions. The Analytical Framing session introduces the conceptual, theoretical and empirical foundations of the topic through research-based and interactive teaching. The Contextual Enquiry session places those ideas in motion through case discussion, live cases, guest speakers, simulations, AI-assisted exercises, and structured class debate. The aim is to move continuously between concepts and contexts, models and situations, analytical rigour and managerial judgement. Indeed, during the course the Contextual Enquiry session may precede the Analytical Framing one. Depending on the topic of the session, the course also contemplates Meet the Expert sessions, i.e., a 20’ discussion with an academics or a practitioner who has developed and refined relevant research or practical experience on a specific subject contemplated in the course syllabus. Students will work with academic papers, managerial cases, short videos, live cases and guest speakers. Particular attention will be paid to the capacity to frame problems before solving them: innovation fails because of poor execution as well as because organisations ask the wrong questions, listen to the wrong signals, or remain trapped in yesterday’s categories.

Assessment architecture The assessment design preserves the distinction between unaided judgement and AI-assisted work. Attending students – to qualify as an attending you are supposed to attend at least 70% of the sessions, as registered via the Luiss app at the beginning of each session; you are assessed through a variety of methods with the aim to evaluate your understanding (analytical and critical) of the key concepts of the course. The use of AI-based tools is encouraged and favoured to support your learning processes, with the understanding that this course enables you to develop and refine skills to govern such tools and therefore you will attend practice and exam sessions where AI is not allowed and practice and exam sessions where AI is allowed (see below). Component Weight Focus Participation and contribution 10% Engagement in plenary, group discussion, group presentations and class activities on technology management challenges: quality of the questions asked are key! Midterm written exercise 20% This is three-stage in-class written assignment focused on technology management challenge faced by an organisation. Students are required to frame and solve the challenge: first individually and then in a group. Please note these two are pen-&-paper assignments, no technology allowed – i.e., smartphones, smartwatches, tablets, laptops and the likes. The third stage allows students to use AI. Emphasis on conceptual clarity and problem framing. Final oral exam 70% Individual and group oral discussion integrating the three blocks of the course. Non-attending students: the final grade will be based on a final assessment composed of an oral exam (60%) as well as on a written exam (40%) on the extended version of the programme. Please note that non-attending students are required to fill in a form on the Luiss website.

Thesis assignment is based on a proposal elaborated and presented by the student. The proposal (max 1 pages) must include: abstract, the research question, a potential table of content, and main references. Students involved in internship may well develop a thesis proposal based on the internship project. Timing – the proposal should be emailed to the course leader at least 6 months before the planned graduation session.