This quick and handy guide will help you distinguish between the different variations of Primary and Secondary data that you may require for your dissertation. If you are unsure what type of data is best suited for your dissertation research, read on!
1. Primary Data
- This is the data collected from human participants through interviews or surveys.
- This is usually cross-sectional data (i.e. the data collected at one point of time from different respondents).
- Time-series are found very rarely or almost never in primary data.
1.1. Primary Quantitative Data
- This is the data that can be converted to numbers (e.g. Likert scale, yes/no questions converted to dummy variables, etc.)
- This data is usually collected through surveys using the method of structured questionnaires with closed-ended questions.
- Studies that use this type of data ask What questions (e.g. What are the determinants of customer loyalty? To what extent does marketing affect sales? etc.)
- Can be analysed with SPSS.
1.2. Primary Qualitative Data
- This is non-numerical primary data represented mostly by text or quotes from interviewees.
- This is best used in social studies including management and marketing when there are few respondents and if they are asked open-ended
- Studies that use this type of data usually ask Why and How questions (e.g. Why does social media marketing is more effective than traditional marketing? How do consumers make their purchase decisions?)
- Can be analysed with nVivo.
2. Secondary Data
- This is the data collected from databases or websites; it does not involve human participants.
- This can be both cross-sectional data (e.g. an indicator for different countries/companies at one point of time) and time-series (e.g. an indicator for one company/country for several years). A combination of cross-sectional data and time-series data is panel data.
- This data is more relevant for economic and financial research but it can also be found in management and marketing research.
- In management and marketing research, secondary data is usually employed in the context of the case study strategy.
- In the economic and financial research, secondary data is usually analysed with econometric and statistical methods.
2.1. Secondary Quantitative Data
- The most popular data in economics and finance
- Examples of secondary quantitative data are share prices; accounting information such as earnings, total asset, revenue, etc.; macroeconomic variables such as GDP, inflation, unemployment, interest rates, etc.; microeconomic variables such as market share, concentration ratio, etc.
- Examples of dissertation that will most likely use secondary quantitative data are FDI dissertations, Mergers and Acquisitions dissertations, Event Studies, Economic Growth dissertations, International Trade dissertations, Corporate Governance dissertations.
- Can be analysed with statistical software such as Eviews, Stata, R, Matlab, and SPSS.
2.2. Secondary Qualitative Data
- This is any textual or visual data (infographics) that have been gathered from reports, websites and other secondary sources that do not involve interactions between the research and human participants.
- Examples of the use of secondary qualitative data are SWOT analysis, PEST analysis, 4Ps analysis, Porter’s Five Forces analysis, most types of Strategic Analysis, etc.
- Often used in case studies.
- Cannot be analysed with statistical or econometric software such as Eviews, Stata, Matlab, SPSS.