is chosen to address the research questions.
3.3 Methods
3.3.1 Definitions and types of data
According to Bryman and Bell (2011), a research method is simply a technique for gathering data. The process of data gathering comprises the decisions on what to measure and how to measure it, i.e. how data are gathered (Field, 2013). In other words, data gathering refers to the methods used to gather information and the identification of variables to be measured (Easterby-Smith et al., 2012).
In contrast to qualitative data, quantitative data refers to the gathering of numerical data. Objective measurements and the statistical, mathematical, or numerical analysis of data gathered through questionnaires, and surveys, or by manipulating statistical data using computational techniques are employed (Bryman & Bell, 2011). Quantitative data are usually associated with positivism (Davies & Hughes, 2014). The underlying assumption of positivist methods is that the job of the researcher is either to start with a hypothesis of the nature of the world, and then seek data to confirm or reject it, or pose several hypotheses and seek data to select the correct one (Easterby-Smith et al., 2012). A hypothesis is an informed speculation about the possible relationship between two or more variables. A variable is an attribute on which cases vary (Bryman & Bell, 2011). To test hypotheses, variables have to be measured (Easterby-Smith et al., 2012). There are a lot of different forms and levels of variables. In general, variables can be categorical or continuous. Furthermore, they can have different levels of measurement (Field, 2013). An interval variable is defined as “data measured on a scale along the whole of which intervals are equal” (Field, 2013, p. 877). A ratio variable is “an interval variable with the additional property that ratios are meaningful” (Field, 2013, p. 882).
Most hypotheses can be expressed in terms of two variables, namely a proposed cause and a proposed outcome. One main goal of research is to determine the relationship or association between an independent variable and another variable
within a population. A variable that is a cause is known as an independent or
predictor variable, because its value does not depend on any other variables.
A variable that represents an effect is called a dependent or outcome variable, because its value depends on the cause (independent variable) (Field, 2013).
Given the research questions and the chosen research paradigm, gathering data through surveys or using secondary data sources are the principle methods of obtaining data that are available to the researcher. Both of them look for patterns and causal relations. For this research, interval or ratio variables are appropriate.
These are variables where the distances between the categories are identical across the range of categories (Bryman & Bell, 2011).
In general, survey research denotes a cross-sectional design in relation to which data are gathered by self-completion questionnaires or by structured interviews on more than one case and at a single point in time. Quantitative data in connection with two or more variables are gathered in order to examine patterns in the relationship (Bryman & Bell, 2011).
First, survey data of grid owner companies can be gathered either through self-completion questionnaires where respondents record their own answers, or administered by interviewers face-to-face or over the telephone (Easterby-Smith et al., 2012). On the one hand, postal questionnaire surveys are cheaper than any other method that requires face-to-face contact with individuals. On the other hand, response rates can be very low, because there is no personal contact with the respondents. Web-based surveys, located on a website, can be customised for individual respondents more easily than postal surveys (Easterby-Smith et al., 2012). Where postal addresses or other contact details are not available, structured interview surveys may be the most effective way to gather survey data.
A structured interview is defined as “a research interview in which all respondents are asked exactly the same questions in the same order with the aid of a formal interview schedule” (Bryman & Bell, 2011, p. 719). But they are more expensive than self-completion questionnaires as an interviewer has to be present. Finally, telephone interview surveys are cheaper than postal surveys and they also facilitate interactivity (Easterby-Smith et al., 2012).
Second, to address the research questions, it could be useful to undertake some secondary analysis of data (Davies & Hughes, 2014). In general, secondary data are research information or data that already exist in the form of publications or other electronic media and that were gathered by other people (Easterby-Smith et al., 2012). Archival sources of secondary data, such as financial or statistical data, could be used to gather data on legal forms, ownership structure, firm size and firm performance of grid owner companies in Germany. Typical archival sources are annual financial statements including balance sheets or profit and loss accounts, particularly from the Federal Gazette in Germany or other databases, e.g. Bloomberg, Thomson Reuters, etc. Furthermore, statistical data provided by the Statistical Offices of the German States in cooperation with the Federal Statistical Office are a frequently used archival source.
According to Easterby-Smith et al. (2012), the most important factor affecting the quality of what can be done with secondary data is the design of the database.
Davies and Hughes (2014) point out that the advantage of these databases can be seen in their size, because they include a large volume of cases. Economics and finance usually rely more on secondary data such as public or corporate financial data and statistics, because quantitative methods can be fast and economical (Easterby-Smith et al., 2012). Moreover, geographical variations or change over time could be analysed by combining datasets (Davies & Hughes, 2014). In Germany, almost every company is forced to disclose its financial data in the German Federal Gazette and in the German register of companies, depending on its size. The German Federal Gazette provides annual and quarterly income statements, balance sheets and supplementary data items for German companies (Bundesanzeiger, 2019). Thus, it is possible to compare absolute or relative figures from the annual financial statements. Furthermore, information about the legal form or the ownership structure of grid owner companies can be taken from the German register of companies. Being aware of the fact that balance sheets and profit and loss accounts are influenced by earnings management and do not always show the “real picture of the world”, it is important to appreciate qualitative data in the annual reports. For example, the notes and the management reports have to be analysed with regard to the use of accounting discretion. Furthermore, the background of grid owner companies and the reasons of municipalities and
energy companies for founding grid owner companies have to be considered while analysing financial data.