Università Roma Tre

In today's digital age, information has become a vital resource for both managerial and personal success. The rapid pace of technological advancements has integrated information technology and communication technology, forming the ever-expanding ICT industry. Concurrently, socio-economic shifts have underscored the value of information access, making it an indispensable asset in the modern economy.

This course delves into the contemporary issues of managing corporate knowledge, particularly in information-intensive sectors, within the knowledge-based view of the firm. As knowledge quickly becomes outdated, firms must continually evolve their knowledge management strategies and practices to stay competitive. Recent trends such as big data analytics, artificial intelligence (AI), and machine learning have dramatically transformed the landscape of knowledge management. These technologies provide innovative tools and methodologies for capturing, analyzing, and leveraging information, thereby enhancing organizational effectiveness and enabling the creation of new business models.

The course aims to equip students with a deep understanding of data-driven knowledge within the contemporary economy. Students will learn to analyze the production, distribution, and consumption of information-based goods and develop strategies for effective knowledge management. Emphasis will be placed on integrating recent advancements in AI into these strategies. AI-backed knowledge management practices, such as automated data processing, predictive analytics, and intelligent information retrieval, will be explored to demonstrate how they can revolutionize decision-making processes, improve knowledge dissemination, and support innovation within organizations.

Furthermore, the course will explore how effective knowledge management informs the development of new business models and drives business model innovation. By harnessing data and insights, organizations can create more agile, responsive, and customer-centric business models. Students will examine case studies of companies that have successfully leveraged knowledge management to innovate their business models, adapt to market changes, and achieve competitive advantages.

Learning Outcomes:
- Understand the significance of data-driven knowledge in the contemporary economy.
- Analyze the production, distribution, and consumption of information-based goods.
- Develop strategies for effective knowledge management in organizations, incorporating recent trends like big data and AI.
- Evaluate organizational conditions and technologies that enable knowledge management.
- Assess the impact of emerging technologies on knowledge management practices.
- Explore AI-backed knowledge management practices, including automated data processing, predictive analytics, and intelligent information retrieval.
- Understand the ethical considerations and challenges associated with AI in knowledge management.
- Analyze how knowledge management informs the development of new business models and drives business model innovation.

Syllabus
This course explores the critical aspects of managing corporate knowledge in the digital age, focusing on information-intensive sectors and the integration of AI technologies. It covers the development of effective knowledge management strategies, the role of AI in knowledge processes, and how these elements drive business model innovation.

Week 1: Introduction to Digital Age and Knowledge Management
• Understanding Knowledge Management (KM) in the frame of the Industrial Revolutions
• The evolution of KM: From traditional methods to digital approaches
• The knowledge-based view of the firm

Week 2: Knowledge Management Frameworks and Models
• Key KM frameworks and models
• Knowledge creation, storage, transfer, and application
• Case studies on successful KM implementations
• Digital Transformation

Week 3: Knowledge Management Strategies and Digital Transformation
• Developing and implementing KM strategies
• Measuring KM effectiveness
• Continuous improvement in KM practices and DT

Week 4: Enabling Technologies for KM
• Collaboration tools and platforms
• Content management systems (CMS) and knowledge management systems (KMS)
• Organizational culture, leadership, and change management in KM
• Data-driven decision-making processes

Week 5: Organizational Conditions for DT
• Organizational culture and DT
• Leadership and DT
• Change management and DT

Week 6: The Role of (ICT) and Big Data in KM
• ICT and its impact on KM practices
• Integration of IT, communication technologies, and Big Data analytics in KM
• ICT trends in knowledge-intensive sectors
• Tools and technologies for managing Big Data

Week 7: Artificial Intelligence in Knowledge Management
• Introduction to AI and machine learning
• AI applications in KM: Automated data processing, predictive analytics, intelligent information retrieval
• Ethical considerations and challenges of AI in KM

Week 8: Business Model Innovation through KM
• Understanding business model innovation
• The role of KM in creating new business models
• Case studies on business model innovation driven by KM

Week 9: AI and Business Model Innovation
• AI-driven insights for business innovation
• Transforming business models with AI and KM
• Future trends in AI and business model innovation

Week 10: Capstone Project and Presentations
• Development of a KM strategy for a chosen organization
• Integration of AI tools in the KM strategy
• Presentation and peer review of capstone projects

Textbook
We will be using the following textbooks:
Marchegiani, L. (2021). Digital Transformation and Knowledge Management. Routledge.

Newell S., Robertson M., Scarbrough H., Swan J. (2009) Managing Knowledge Work and Innovation. Palgrave.

Additional material will be posted in this workspace or in the shared dropbox folder.