UCL School of Management

Strategy & Entrepreneurship

This group’s faculty share an interest in understanding what makes firms successful and what leads to the formation of new businesses. Topics of interest include digitization, big data analytics, machine learning, information environment, platform ecosystems, new organizational forms, learning, innovation, competition, interorganizational relationships, corporate strategy, entrepreneurial strategy, entrepreneurship for development, and social innovation.

Our research methods are diverse and include regression analysis, field experiments, archival data analysis, surveys, ethnography, formal modeling, simulation, and network analysis. Despite this diversity, there is a common focus on how firms can grow and innovate.

Social Innovation: Climate Change & Human Rights

The focus of this research is on how organisations may facilitate social innovation and social change in 'adverse' institutional contexts.

Tracking M&As

Tracking M&As using machine learning generated counterfactuals

Alternative perspectives on reputation

How can we revisit our theories of organizational reputation to better reflect the current reputational landscape?

History, memory and identity

How do people in organizations relate to history and heritage? How do history and memory shape strategy and innovation?

Design, designers, innovation and change

How do designers think and how does their work contribute to strategic change and innovation?

Symbolic value creation

How does design contribute to infusing products with valuable meanings?

Organizational identity, culture and change

How do organizational identity and culture change? How do they affect organizational and strategic change? Can identity be managed at all?

Strategic Discipline in New Technology Ventures

How do new firms that lack pre-defined capabilities and market positions develop a strategy for commercializing technological breakthroughs?

Topology and evolution of networks

How to capture the topological characteristics of networks and their evolution.