Skip to main content
MyCourses MyCourses
  • Schools
    School of Arts, Design, and Architecture (ARTS) School of Business (BIZ) School of Chemical Engineering (CHEM) –sGuides for students (CHEM) – Instructions for report writing (CHEM) School of Electrical Engineering (ELEC) School of Engineering (ENG) School of Science (SCI) Language Centre Open University Library Aalto university pedagogical training program UNI (exams) Sandbox
  • CORONAVIRUS INFO
    Koronavirus - tietoa opiskelijalle Coronavirus - information for students Coronavirus - information för studerande Koronaviruksen vaikutus opiskeluun: kysymyksiä ja vastauksia Effects of the coronavirus on studies: questions and answers Coronaviruset och studierna: frågor och svar Corona help for teachers
  • Service Links
    MyCourses - Instructions for Teachers - Teacher book your online session with a specialist - Digital tools for teaching - Personal data protection instructions for teachers - Instructions for Students - Workspace for thesis supervision WebOodi Into portal for students Courses.aalto.fi Library Services - Resourcesguides - Imagoa / Open science and images IT Services Campus maps - Search spaces and see opening hours Restaurants in Otaniemi ASU Aalto Student Union Aalto Marketplace
  • ALLWELL?
    Study Skills Support for Studying Starting Point of Wellbeing About AllWell? study well-being questionnaire
  •   ‎(en)‎
      ‎(en)‎   ‎(fi)‎   ‎(sv)‎
  • Toggle Search menu
  • Hi guest! (Log in)

close

MNGT-E3001 - Researching Entrepreneurship and Innovation (Master's thesis seminar), 26.10.2020-04.12.2020

  1. Home
  2. Courses
  3. School of Business
  4. department of...
  5. mngt-e3001 - ...
  6. Sections
  7. topic 5 - qua...
Syllabus

Topic 5 - Quantitative Data

  • Topic 5 - Quantitative Data

    Topic 5 - Quantitative Data

    What if you want to find out whether entrepreneurs are different in Finland and in Germany, or inform the UK government on the sentiments of the export industry on their anticipations on the impact of Brexit. How would you go about it? Where would you start?

    Probably, you would first start asking questions on who or what it actually is that you want to learn about. In other words what is the population that your results should apply to.

    But how will you get information on this population? If you cannot include all of them, you must select. Should you do the sampling so that everyone has an equal chance, a probability, of getting selected, take those that are most conveniently reached, or snowball your way forward, i.e. ask the participants to suggest further participants? How many is enough? In quantitative research, sample sizes are larger than in qualitative research; this is because most quantitative studies seek to make generalisations to a wider population.  

    Let’s say you have a good sample of respondents that represent the population, how would you collect data on them? Should you rely on their subjective accounts, or find something more objective? You could either collect primary data yourself, or turn to the already existing secondary data, such as archives or databases. What would be benefits and drawbacks of surveys and questionnaires, or of doing field research? 

    Remember, in order to do statistical analysis, you will need the data in numerical form, so observations and interviews must be structured, coded and quantified. How can you measure the elusive concepts, such as attitudes, capabilities, orientations, and emotions – or the innovativeness of a firm, or the entrepreneurial culture of a country? In order to do statistical analysis, we must transform the concepts into measurable variables.

    How we measure and what kind of numbers we assign to these variables may also vary. Do we simply divide people, firms or other entities into categories? Or, is our measuring truly continuous, or is it discrete in a sense that only certain values are possible? The level of measurement will then also affect the way our data can be analysed. Different calculations can be done with binary variables (two groups) or nominal variables (more than two groups), ordinal variables (assigned order), interval variable (quantified differences) and ratio variables (percentages). As you might already realise, the level of measurement and the variables we receive also depends on the way we collect the data and the way we formulate questions. 

    Without even diving into the deep philosophical debates on whether there is a reality that we should discover and assign with true values (realism), or whether whatever we measure is what it then becomes central (nominalism), there are a number of issues to consider in regard to the quality of measurement. First of all, does the response in a questionnaire really tell about, for instance, ‘job satisfaction’? Is it a valid measure for that? And, what if we ask this again, would we get the same answer, or will the person tick a different box depending on the weather outside or due to her/his character – in other words, is the measure reliable? How could you test the reliability and validity of a selected measure?

    The saving grace is that research does not have to represent the reality to the full extent – it is actually meant to summarize and simplify it in such a way that we can make wise decisions, and accumulate knowledge. Thus, some measurement error always exists, and this is ok. However, the data is the bedrock of our research and no fancy analysis can correct the damage (or even carried out) if the data is flawed, and contains too much random noise or systematic bias. How could you avoid bias, and gain the best possible basis for further analysis?


    Readings

    Kuckertz, A. & Wagner, M. 2010. The influence of sustainability orientation on entrepreneurial intentions — Investigating the role of business experience. Journal of Business Venturing, 25(5), 524-539.


    Videos

     

    Population and Sample

       


    Sampling Methods

       



    Collecting Data

    1 - Objective and Subjective 

       


    2 - Primary and Secondary 

         


    3 - Observation, Survey, Experiment

       


    4 - Survey 

         


    Measurement and Scales

         


    Validity and Reliability 

        


       


    Summary of Quantitative Data Collection 

       




    Exercises

     

    Exercise 5.1 – Comprehend

    Take a look at two databases that are freely available and offer interesting data for entrepreneurship and innovation management researchers: Global Entrepreneurship Monitor (GEM) European Innovation Scoreboard (EIS).

    • https://www.gemconsortium.org/data
    • https://ec.europa.eu/growth/industry/innovation/facts-figures/scoreboards_en

    Give a brief (max 1 page) account on your impressions on one or both of the databases. What kind of data is available? How is the data collected? What do you find interesting in the database?

     

    If you are interested to learn more about databases, see for example: 

    Wennberg, K. 2005. Entrepreneurship research through databases: Measurement and design issues. New England Journal of Entrepreneurship, 8(2), 9-19.

    Available online: 

    https://www.emeraldinsight.com/doi/pdfplus/10.1108/NEJE-08-02-2005-B002

     

     

    Exercise 5.2 – Critique

    Read the Data, Measures and Limitations sections of the article by Kuckertz and Wagner (2010), and answer the questions on it: What kind of data does the study use? How well do the authors describe the process of data collection? Do they assess the validity and reliability of the data, and its potential limitations? Would you have ideas for improving the data (e.g. do you think they should have used different data, or collect more data)?

     


    Self-Assessment Checklist

     

    Please check. Did you gain an understanding of the following?

    • The meaning of population and sample
    • Some data collection methods used in quantitative research
    • Process of measuring and how to assess the quality of measurement

    If you can answer everything with a confident Yes!  then you have achieved the learning objective of this session.

     


    Previous section

    ◄QUANTITATIVE RESEARCH

    Next section

    Topic 6 - From Theory to Empirics►
    Skip Upcoming events
    Upcoming events
    Loading There are no upcoming events
    Go to calendar...
    • MNGT-E3001 - Researching Entrepreneurship and Innovation (Master's thesis seminar), 26.10.2020-04.12.2020
    • Sections
    • Introduction
    • Materials
    • Assignments
    • For Aalto users
    • Topic 1 - Usefulness of Theory in Research
    • Topic 2 - Research Paradigms in a Nutshell
    • QUALITATIVE RESEARCH
    • Topic 1 - Different Qualitative Research Approaches
    • Topic 2 - Observation and Note-taking
    • Topic 3 - Interviews as a Data Collection Method
    • Topic 4 - Qualitative Data Analysis
    • QUANTITATIVE RESEARCH
    • Topic 5 - Quantitative Data
    • Topic 6 - From Theory to Empirics
    • Topic 7 - Quantitative Analysis
    • Topic 8 - Interpreting and Publishing Research Findings
    • Home

    Aalto logo

    Tuki / Support
    • MyCourses help
    • mycourses(at)aalto.fi
    Palvelusta
    • MyCourses rekisteriseloste
    • Tietosuojailmoitus
    • Palvelukuvaus
    About service
    • MyCourses protection of privacy
    • Privacy notice
    • Service description
    Service
    • MyCourses registerbeskrivining
    • Dataskyddsmeddelande
    • Beskrivining av tjänsten
    
    Hi guest! (Log in)
    • Schools
      • School of Arts, Design, and Architecture (ARTS)
      • School of Business (BIZ)
      • School of Chemical Engineering (CHEM)
      • –sGuides for students (CHEM)
      • – Instructions for report writing (CHEM)
      • School of Electrical Engineering (ELEC)
      • School of Engineering (ENG)
      • School of Science (SCI)
      • Language Centre
      • Open University
      • Library
      • Aalto university pedagogical training program
      • UNI (exams)
      • Sandbox
    • CORONAVIRUS INFO
      • Koronavirus - tietoa opiskelijalle
      • Coronavirus - information for students
      • Coronavirus - information för studerande
      • Koronaviruksen vaikutus opiskeluun: kysymyksiä ja vastauksia
      • Effects of the coronavirus on studies: questions and answers
      • Coronaviruset och studierna: frågor och svar
      • Corona help for teachers
    • Service Links
      • MyCourses
      • - Instructions for Teachers
      • - Teacher book your online session with a specialist
      • - Digital tools for teaching
      • - Personal data protection instructions for teachers
      • - Instructions for Students
      • - Workspace for thesis supervision
      • WebOodi
      • Into portal for students
      • Courses.aalto.fi
      • Library Services
      • - Resourcesguides
      • - Imagoa / Open science and images
      • IT Services
      • Campus maps
      • - Search spaces and see opening hours
      • Restaurants in Otaniemi
      • ASU Aalto Student Union
      • Aalto Marketplace
    • ALLWELL?
      • Study Skills
      • Support for Studying
      • Starting Point of Wellbeing
      • About AllWell? study well-being questionnaire
    •   ‎(en)‎
      •   ‎(en)‎
      •   ‎(fi)‎
      •   ‎(sv)‎