Data-Driven Business Innovation and Entrepreneurship

6 EC

Semester 2, period 4

5294DDBI6Y

Owner Master Information Studies
Coordinator dr. Angelo Tomaselli
Part of Master Artificial Intelligence, Master Information Studies, track Data Science, year 1Master Information Studies, track Information Systems, year 1

Course manual 2019/2020

Course content

Entrepreneurship is fundamental to generate value from innovation and it is an increasingly important subject for students and professionals, also in the context of data science. The growing complexity of the data science sector and its accelerating dynamics urge professionals to think and act in an entrepreneurial way. Due to the informatization of society, data about nearly everything emerge every day. By using data, searching for inferences and patterns, may entrepreneurs help to better support their new ventures.

This course is especially useful for ambitious students who want to demonstrate their ability to analyze data in order to pursue a career as an entrepreneur or who want to work at an entrepreneurial firm. During the last hundred years, entrepreneurial innovation is the main generator of jobs and welfare in Modern Society, the “true source” of national competitive advantage. Many Universities, Research Institutes and Research Departments of large Enterprises have adopted policies to stimulate the relationship between entrepreneurship and innovation, in the hope of facilitating economic growth.

During the course, students will learn basic knowledge about how to successfully launch a new venture and its underlying business idea. Working in teams, students will be requested to collect and analyze data in order to identify and validate an innovative and scalable business idea - representing a starting point for a potential start-up - to present in a “business pitch” and a “short final report” at the end of the course. Students must support their proposal with data analysis.

The course is based on three main pillars:  1) lectures; 2) tutorials; 3) coaching.

  • Lectures: aimed to transfer academic knowledge in the field of innovation and entrepreneurship; based on a recommended book, selected academic papers and speeches of industry experts in different entrepreneurial fields.
  • Tutorials: aimed to the development of personal entrepreneurial soft skills, which may contribute to entrepreneurial success. Tutorials are based on interactive lessons, discussion of selected empirical cases and execution of specific assignments representing the steps that entrepreneurs follow in order to create a new business idea.
  • Coaching (after teams’ presentations in tutorials): it is the time in which students have the opportunity to discuss their business idea with the instructors. During the coaching students will receive advice and instructions regarding the development of their business idea, their presentation and preparation of the final report (for example, how to identify a “minimum viable product”, implement a strategic analysis of industry competitors, writing a solid business plan).

Study materials

Literature

  • 1) The recommended book: "Entrepreneurship successfully launching new ventures - global edition - 6th edition” (R. Barringer and R.D. Ireland, 2019).

    https://www.pearson.com.au/9781292255330

     

    2) Academic papers and empirical cases will be uploaded on UVA Canvas and indicated in the following section “Lectures schedule and assignments for each tutorial”.

     

Syllabus

  • INSTRUCTORS

    • Lectures and tutorials: Angelo Tomaselli, Frank Slisser.
    • Special guest speakers will be invited.

    Please notice that:

    • The course will start with the lecture on 4th February 2020 (Tuesday).
    • After the first lecture, instructors will share students in two tutorial groups and will ask the students to form teams according to their preferences (when possible). Teams are formed by a maximum of 3 students.
    • Further instructions and study material will be given during the course.

    LECTURES SCHEDULE AND ASSIGNMENTS FOR EACH TUTORIAL

     

    1st Lecture: Introduction Course (Frank Slisser) – 4th February

    Topics:

    • The impact of the Entrepreneurial Innovation Revolution.
    • Recognizing opportunities and generating ideas.
    • The technique entrepreneurs use to generate ideas.
    • Closed, open and disruptive innovation
    • New product development and the (revised) stage-gate model
    • Customer development
    • Lean start-up and the concept of “minimum viable product”.

    Literature (mandatory):

    Literature (optional):

    1st Tutorial: Teams present their initial ideas (combined tutorial with all students in one class) - 10th February

     Each Team needs to present their initial idea in a PowerPoint presentation, convincing that it can become a “new business opportunity”.

    Every Total time: Each team has 8 minutes (including questions).

     

    2nd Lecture: Conducting a feasibility analysis (Frank Slisser) – 11th February

     Topics: 

    • Explaining the definition and importance of a feasibility/industry analysis.
    • Discussing critical issues in conducting a feasibility/industry analysis.
    • Describing a feasibility analysis template.

    Literature (mandatory): 

    • Chapter 3 of the book: “Feasibility analysis”.
    • Chapter 5 of the book: “Industry and competitor analysis”.
    • Porter, Michael E., Heppelman, J.E., How Smart, Connected Products Are Transforming Competition, Harvard Business Review, November 2014.

    Literature (optional):

    • Harari, G. M., Lane, N. D., Wang, R., Crosier, B. S., Campbell, A. T., & Gosling, S. D. (2016). Using smartphones to collect behavioral data in psychological science: opportunities, practical considerations, and challenges. Perspectives on Psychological Science, 11(6), 838-854.
    • Guest speaker to be confirmed.

    2nd Tutorial: Feasibility analysis presentation (tutorial shared in two classes) – 17th February

     Each team has to present in a PowerPoint presentation a feasibility analysis with the following key elements (see Chapter 3, Appendix 3.1 and 3.2 of the book):

    1) Strength of the business idea;

    2) Industry-related issues;

    3) Target market;

    4) Founders related issues;

    5) Financial issues;

    6) Overall potential;

    7) A list of the internet resources/data they believe useful to develop their business idea.

    Important: the assessment (score) of the first six elements must be supported by interviews that a team needs to realize with a small sample (20-30 persons) that represents their potential target market or potential investors.

     

    3rd Lecture: Designing an effective business model (Angelo Tomaselli) – 18th February.

     Topics: 

    • Describing a business model and its importance.
    • Distinguishing different types of business models.
    • Explaining the components of a business model.
    • Comparing the Barringer-Ireland template and the Canvas template.

    Literature (mandatory): 

    • Chapter 4 of the book: “Developing an effective business model”.
    • Hartmann, P. M., Zaki, M., Feldmann, N., & Neely, A. (2016). Capturing value from big data–a taxonomy of data-driven business models used by start-up firms. International Journal of Operations & Production Management, 36(10), 1382-1406.
    • Sorescu, A. (2017). Data‐driven business model innovation. Journal of Product Innovation Management, 34(5), 691-696.

    Literature (optional):

    • Massa, L., Tucci, C. L., & Afuah, A. (2017). A critical assessment of business model research. Academy of Management Annals, 11(1), 73-104.

    3rd Tutorial: Business Model workshop (tutorial shared in two classes) – 24th February

     Teams need to present in a PowerPoint presentation a “Canvas business model template” with respect to the final idea they aim to develop. The team needs to present each element of the business model.

    Goal per team: 20 minutes per team (including time for questions).

     

    4th Lecture: Value creation with data (Frank Slisser) – 25th February

    Topics:

    • Value creation with (big)data and analytics.
    • The value of data and metrics.
    • Data and the value chain.
    • Smart products.

    Literature (mandatory):

    Literature (optional):

    • van der Sloot, 'Big Data', Elementaire deeltjes, Amsterdam University Press, Amsterdam 2018.
    • Spijker, Arent van ‘t, “The New Oil: Using Innovative Business Models to Turn Data Into Profit”, Technics Publications, 2014
    • Persaud, Ajax and Sandra Schillo, Big Data Analytics: Accelerating Innovation and Value Creation, October 2017. 

    4th Tutorial:  Value creation workshop (combined tutorial in one class) – 2nd March

     

    Teams need to present a PowerPoint presentation showing how their data can create (additional) value according to their business model. They also need to present:

    • A value-to-customer metrics.
    • A value-to-firm metrics.

    Goal: 8 minutes per team (including questions)

     

    5th Lecture: The main sources of financing (Angelo Tomaselli) – 3rd March

    Topics: 

    • The main sources of financing that are available to entrepreneurs.
    • Debt and equity and financing.
    • The phenomenon of bootstrapping
    • Focus on crowdfunding (which data influence investment decisions).

    Literature (mandatory): 

    • Chapter 10 from the book - “Getting Financing or Funding”. 
    • Bi, S., Liu, Z., & Usman, K. (2017). The influence of online information on investing decisions of reward-based crowdfunding. Journal of Business Research, 71, 10-18.

    Literature (optional):

    • Mollick, E. "The dynamics of crowdfunding: An exploratory study." Journal of Business Venturing, 29, no. 1 (2014): 1-16. 

    5th Tutorial: “Crowdfunding workshop” (tutorial shared in two classes) – 9th March

    Teams need to present a “crowdfunding campaign” for the new company they intend to develop, using “Kickstarter” https://www.kickstarter.com/ or another platform.

    In their campaign teams needs to present basic elements: a short video or a website mockup, the funding goal, the duration of the campaign, the rewards structure.

    Goal: 20 minutes per team (including questions).

     

    6th Lecture: The business plan and the new venture’s financial strength (Angelo Tomaselli) – 10th March

    Topics: 

    • Explain the purpose of a business plan.
    • Explain how to effectively present a business plan and basic financial indicators (ratio analysis and forecasts).

    Literature (mandatory): 

    • Chapter 6 from the book - “Writing a Business Plan”.
    • Chapter 8 from the book - “Assessing a new venture financial strength and viability”.

     

    6th Tutorial: Final coaching (tutorial shared in two classes) – 16th March

    Teams have the opportunity to have a final meeting (for final advice) with their instructor. 10 minutes per team (the meeting time and order will be arranged with the instructor).

     

    Final business idea presentation (combined session in one class) : 20th March:

    The teams will present their business ideas during a pitch presentation using PowerPoint. Industry and faculty experts will be invited.

     

    Final Exam: 24th March

    There will be a final exam focusing on lectures' topics. Further instructions will be given during the course.

Practical training material

Other

  • Students will work in team (the list of student teams can be founded on Canvas/Datanose) and will receive a grade (from 0 to 10), which is a weighted average of:

    • The “individual” final exam (on lectures' topics). It represents the 60% of the final total grade.
    • The “team” participation and the accomplishment of assignments during the tutorial lessons. It represents the 20% of the final total grade. Only one tutorial class can be missed. Active participation during class is very important, strongly encouraged and will positively affect your grade. A scarce participation will negatively affect your grade.
    • The “team” final pitch presentation of their business idea and the evaluation of a final report presenting the idea. It represents the 20% of the final total grade.

Objectives

  • Identify and delineate the fundamental steps in the creation of a new venture, from the idea generation to its financing.
  • Better master and use the academic literature on entrepreneurship. In particular, critically making use of theoretical foundations for practice-based ideas.
  •  Acquire the ability to search for and recognize an innovative business idea (i.e., think ‘out of the box’).
  •  Use data analysis in order to translate a business idea into a set of criteria for a “minimum viable product”.
  •  Develop the ability to cooperate and constructively communicate a new business idea by the creation of a business pitch presentation and the writing of a business plan.
  •   Approach with confidence the entrepreneurial challenges in the creation of a new venture.

Teaching methods

  • Lecture
  • Seminar
  • Presentation/symposium
  • Self-study
  • Supervision/feedback meeting

Learning activities

Activity

Number of hours

Hoorcollege

14

Presentatie

4

Project

28

Tentamen

2

Werkcollege

14

Zelfstudie

106

Attendance

In TER part B of this programme no requirements regarding attendance are mentioned.

Additional requirements for this course:

Attendance in lectures and Tutorials is manadtory

Assessment

Item and weight Details

Final grade

1 (100%)

Tentamen

Multiple Choice Exam of 40 Questions; cut-off score 22

Literature: Book and Articles discussed in the tutorials

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Weeknummer Onderwerpen Studiestof
6 

Entrepreneurial

Innovation Revolution

 Ch1+2
7 Feasibility Analysis Ch 3
8 Ecosystems Lit
9 Business Model Ch 4
10 Financing Ch 10
11 New Ventures Ch 6
12    
13    

Timetable

The schedule for this course is published on DataNose.

Contact information

Coordinator

  • dr. Angelo Tomaselli

Staff

  • dr. Angelo Tomaselli