B2811 - Managerial Decision Making

Learning outcomes

This course aims to provide students with an understanding of management based on how people make decisions. Students will gain a basic understanding of how people make decisions and the decision-making processes that result in the behaviors of firms. By the end of the course, the student will develop a critical understanding of the role that management plays in fostering the achievement of organizational goals. At the end of this course, students should be able to: 1. Acquire knowledge of key principles of management and be able to apply this knowledge to the practice critically 2. Understand and apply a selected management topic to a real organizational setting 3. Understand how customers and their characteristics may affect the design of products and brand-related strategies 4. Understand how to guide consumers’ decision-making processes

Course contents

Module 1:

This module provides an overview of managerial decision making in the digital economy, with a focus on digital technologies that are shaping the digital transformation of organizations. It first illustrates the features and limitations of human rationality as well as decision-making processes in organizations. Later it shifts the attention to the context of the digital economy and deepens the theme of decision-making in a digital world as well as managerial and entrepreneurial decision making in the digital economy and in the 4^th industrial revolution (Industry 4.0).

You will be able to:

• Illustrate the features and limitations of human rationality;
• Characterize decision-making processes in organizations;
• Illustrate the characteristics of the digital economy;
• Identify and describe digital technologies underpinning the Industry 4.0 and digital transformation;
• Describe how managers, entrepreneurs and firms deploy digital technologies to support their decision making in the digital age

 

Module 2:

Cognitivism, habit, reinforcement; decision processes, heuristics and decision biases.

Readings/Bibliography

Module 1: 

Readings (available online on Virtuale, except for the books highlighted in bold)

• Blank, S. (2013). Why the lean start-up changes everything. Harvard Business Review, 91(5), 63-72.
• George, G., Osinga, E.C., Lavie, D., Scott, B.A. (2016). Big data and data science methods for management research, Academy of Management Journal, 59 (5), 1493–1507.
• Gurbaxani, V. and Dunkle, D. (2019). Gearing Up For Successful Digital Transformation, MIS Quarterly Executive: 18(3), Article 6.
• Mack, E.A., Marie-Pierre, L., Redican, K.(2017) “Entrepreneurs' use of internet and social media applications”, Telecommunications Policy, 41: 120–139.
• Mariani, M., & Dwivedi, Y. K. (2024). Generative artificial intelligence in innovation management: A preview of future research developments. Journal of Business Research, 175, 114542.
• Mariani, M. M., & Wamba, S. F. (2020). Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies. Journal of Business Research, 121, 338-352.
• Mariani, M. M., Borghi, M., & Okumus, F. (2020). Unravelling the effects of cultural differences in the online appraisal of hospitality and tourism services. International Journal of Hospitality Management, 90, 102606.
• Mariani, M., & Borghi, M. (2019). Industry 4.0: A bibliometric review of its managerial intellectual structure and potential evolution in the service industries. Technological Forecasting and Social Change, 149, 119752.
• Mariani, M., Di Fatta, G., & Di Felice, M. (2018). Understanding customer satisfaction with services by leveraging big data: the role of services attributes and consumers’ cultural background. IEEE Access, 7, 8195-8208.
• Nambisan, S. (2017) “Digital entrepreneurship: Toward a Digital Technology perspective of Entrepreneurship”, Entrepreneurship Theory and Practice, 41(6): 1029-1055.
• Osterwalder A and Pigneur, Y. (2010) Business Model Generation. Wiley. ISBN: 13: 978-0-470-87641-1.
• Power, B. (2014). How GE applies lean startup practices. Harvard Business Review. Available at https:// hbr.org/2014/04/how-ge-applies-lean-startup-practices, accessed 7 March 2017.
• Shane, S. & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), pp. 217-226.
• Skilton, M. (2015) Building the Digital Enterprise, Palgrave Macmillan. ISBN: 13: 978-1-137-47770-5.
• Simon, H.A. (1997) Administrative Behavior (4th Edition). The Free Press (1997) ISBN: 978-0684835822

Module 2:

-

Teaching methods

Frontal teaching.

Assessment methods

Module 1: Assessment based on: Written Exam in the lab (mandatory).

Module 2: Written exam. 

 

For each and both modules, no AI tools are allowed during the exam. The exam is based on the program of the academic year during which it takes place, regardless of the year one attended classes.

 

 

 

Evaluation:

18-23: sufficient preparation and analytical skills but related to a limited number of topics covered in the course.
24-26: technically adequate preparation but with some limits with respect to the topics covered, good analytical skills, even if not particularly articulated, expressed in correct language;
27-29: excellent knowledge of a large number of topics covered in the course, good analytical and critical skills, mastery of specific terminology;
30-30L: excellent and exhaustive knowledge of the topics addressed in the course, ability of critical analysis and connection, mastery of specific terminology.

Teaching tools

Slides

Office hours

See the website of Daniele Scarpi de Claricini

See the website of Marcello M. Mariani