QUANTITATIVE RESEARCH APPROACH

A quantitative approach is normally associated with a so-called deductive approach to testing theory (Greener, 2008). Often, numbers and facts (therefore, a positivist model and an objectivist view of the objects) are studied. The deductive approach begins with a look at theory, and produces hypotheses related to the focus of the research and used to test a theory. This approach will hereby be referred to as impersonal objective research to prove or disprove a hypothesis for the purposes of this research paper.

Daymon & Holloway (2011) associate quantitative methods with numbers and detachment and are, therefore, not well-suited to description. These methods point to research through testing, rather than that which emerges from meanings derived from participants. With reference to research in the field of public relations and marketing, quantitative research is considered to be grounded in positivism in order to explain

Evaluating thoughts

which examines questions about cause and effect. Contrastingly, the authors consider the quantitative approach to be less suited to investigating the complexity and transformability of contemporary communication relationships.

One important aspect considers how the research may be influenced due to significant consequences, such as evidence, which arises from the construction of the sampling design. A high response rate in a survey is important to make the sample representative (Easterby-Smith, Thorpe & Jackson, 2012).

If the sampling is wrong, accuracy in calculating the results is of no consequence because the results will not be generalised. If a summary measure does not alter significantly, it will be treated as robust. The greatest part of data analysis is seen in hypothesis testing, when it is appropriate to generalise beyond a specific sample. Sampling data has to be identified in order to draw conclusions from that pattern.

Analysis and testing of quantitative data from social sciences has to be of statistical significance. Variables as relations between the different answers must be identified. The collected data can then be put into a matrix or put directly into statistical package software, such as SPSS (Statistical Package for Social Sciences). Their statistical significance must be evaluated in order to test the hypotheses and to confirm or reject the theory.

Quantitative research, with regard to positivist research approaches, can be summarised as a view on causal explanations, focusing on describing and explaining behaviour, rather than describing meanings of social phenomena (Kura, 2012).

With respect to the research topic, the exploration of decision-making processes indicates a complex interaction of information, behaviours and feelings of end users. It also indicates the necessary interpretation of their feedback; in other words, what end users already know and how they form their interpretation of the topic. Answering and analysing a high volume of questionnaires to obtain reliable data for statistical analysis without personal interaction is supposed to lead to different conclusions. These deductions may be applied not only to the research participants, but also to the researcher.

As Greener (2008) argues, human behaviour is difficult to grasp and isolate, since it changes constantly and can offer different dimensions to different audiences. Greener says that it rarely makes sense to look only at numerically measured evidence when trying to understand what is going on in groups of people.

Against this background, following the standpoint of Easterby-Smith, Thorpe & Jackson (2012), it is contended that the validity of sufficient knowledge of the research participants during the data collection may cause incorrect sampling, but might be of no consequence to the outcome, based on a statistical analysis.

Some relevant comparison issues between quantitative and qualitative research are indicated in Table 3.

Aspects Quantitative approach Qualitative approach

Research path Rather deductive Rather inductive

Approach start Looking at theory and producing hypotheses

Generation of theory from data as description of participants’ experiences Data volume Large sample sizes to

model interaction effects

Small but comprehensive sample sizes, such as - in-depth interviews - observation

Base Explanation of already

known phenomena

Explanation of contemporary communication relationships

Critics Accuracy in calculation of

no consequence with wrong sampling

Examination of questions to cause and effects,

high subjectivity due to communication with

stakeholder research groups

Table 3: Comparison of quantitative and qualitative research approaches

Grounded research

3.3 QUALITATIVE RESEARCH APPROACH

Qualitative researchers seek to uncover the views and meanings of research participants in order to understand the world in their terms (Daymon & Holloway, 2011). One aspect that must be taken into account is the way in which their understanding changes when communicating as a member of a stakeholder group. However, some critics consider qualitative research too subjective.

Greener (2008) argues for qualitative approaches by claiming that behaviour is difficult to grasp as it changes. It rarely makes sense to look only at the numerical measured evidence of data. The focus will not only be on trying to estimate things about a population. The data shall be understood and related to theory or ideas.

Views and meanings are to be sought by the researcher (Daymon & Holloway, 2011). Qualitative research methods represent a powerful means of gaining an in-depth and holistic understanding of relationships.

There are various approaches that can be used in qualitative data collection (Easterby- Smith, Thorpe & Jackson, 2012): interviews are one way to use so-called language data. Another method is observations. In-depth interviews provide an opportunity to probe deeply and to enter into new dimensions and insights with the interviewee. The authors refer to constructivists and strong constructivist positions. In both cases, they assume that there may be different realities in their position, which require gathering views through different research methods. In the former case, they may be qualitative and quantitative. In the second case for strong positions, they may pay even more attention to the use of language and conversations as no pre-existing reality is assumed; thus, there is no absolute truth.

After collecting the data, framing the data indicates ways to make sense of qualitative data and to observe links between the data that can be developed (Easterby-Smith, Thorpe & Jackson, 2012).

The method of natural language analysis focuses on the detailed analysis of scripts, rather than other aspects such as physical or symbolic artefacts. Otherwise, incorrect interpretations could arise, since their interpretation requires the researcher to have more training for interviews. Two methods of natural language analysis are mentioned

First, content analysis approaches: the researcher considers the data for constructs and ideas that have been decided in advance. Content analysis indicates a deductive method.

Second, grounded analysis: the research data is linked in a more holistic way. Researchers let the data speak for itself and leave room for the use of more intuition in understanding the data.

The grounded theory approach represents the idea that research can be developed from the collected data (Daymon & Holloway, 2011). The inductive approach requires the researcher to begin without a hypothesis. However, it is worth developing a research question.

In their fundamental work, Glaser & Strauss (1967) consider grounded theory as a research approach, which derives from data, illustrated by characteristic data. They argue against deductive concepts which derive from certain relevant concepts and hypotheses. In contrast, a systematic discovery of the theory from the data is necessary to form theoretical concepts.

The grounded theory approach represents the idea that research can be developed in a more suitable way from the collected data (Daymon & Holloway, 2011). The starting point of research adopting a grounded theory approach lacks a hypothesis or theory; instead theory is developed throughout the course of the research both inductively and deductively.

Therefore, it is contended that this approach provides an exciting method for the creation of theoretical ideas, in a stepwise manner, by means of a processual approach. This approach also obtains reliable data in response to the criticism that it is too subjective. Glaser & Strauss (1967) argue that this approach should be embarked upon with an open mind and without pre-research assumptions. The goal is generating ideas by comparing where facts are similar or different to generate properties of categories in order to increase their generality.

Timonen et al. (2018) consider grounded theory study as explanations of a process or phenomenon to seek theories.

A sufficient number of users as interviewees have to be considered for a first sample. Compared to quantitative studies, the comprehensive single data collection process, which consists of in-depth interviews, can thus be limited. In-depth interviews will be a

way to evaluate meanings and interpretations (Easterby-Smith, Thorpe & Jackson, 2012). The number of interviewees will be reviewed as necessary with each interview by means of constant comparisons and increase of knowledge (Glaser & Strauss, 1967).

In-depth interviews can reflect on certain issues such as the technical background of the interviewees, which gives the researcher (interviewer) more comprehensive answers due to greater awareness of context. Some main issues are indicated in Table 4.

For the purposes of this research paper, the grounded research approach is considered as a worthwhile and exciting research approach. It will be constructed, grounded in the data, which develops with each single interview into a theoretical concept. This approach allows for more open research, where the structure of the data analysis derives from the data, rather than being imposed on the external data as with quantitative or more concrete positivist approaches (Easterby-Smith, Thorpe & Jackson, 2012). Whilst using provisional hypotheses, statements regarding the way in which the concepts are related may arise by a line-by-line analysis of the data (Strauss & Corbin, 1992).

Aspects Critics Advantages

Approach High subjectivity,

data interpretation requires training

Involving and communicating with research participants, communication is seen as formative process to create individual worldviews Hypotheses Too substantive, theory has

lower generality

No hypothesis allows guiding the conceptual framework by data and theoretical sampling

Generalisation Low and too weighty Quality of more importance than the sampling size, research ‘let the data speak’

Validity Grounded theory is

complex and shall not follow a simplified version, stages of categorisation or coding may be condensed

In-depth and holistic understanding of relationships in their context

Table 4: Pros and cons of grounded research as a qualitative research approach

Source: The Author, based on Easterby-Smith, Thorpe & Jackson (2012), Daymon & Holloway (2011),

Other Research Approaches

The nature of case study research is bounded in place and time (Daymon & Holloway, 2011). It requires intensive examinations often over a long period. Although, the findings will not be universal to all cases, some conclusions may resonate to apply findings to other situations. Case studies usually aim to capture features of contemporary events, so you can never have the final say. Case studies often require long examination periods.

The case study approach has a specific in-depth focus on a phenomenon (Daymon & Holloway, 2011), which this thesis relates to a very close consideration on the investigation already in the beginning of the research.

With respect to the research question, my research will focus on the exciting question: to what extent are end users prepared to adopt certain technologies, rather than examining the reasons why end users decide for or against the purchase of renewable heating technologies. Yin (2012) contextualises this closer consideration with boundaries of cases; for example, a boundary based on a behavioural condition or event. Daymon & Holloway (2011) even relate boundaries to place and time.

Action research is an action-based form of research where research participants reflect on an issue or problem (Daymon & Holloway, 2011). Commonly, action researchers are part of the organisation they study. One goal is to produce practical knowledge on the way in which people live their everyday lives. Herr & Andersen (2005) define action research as an inquiry, which is carried out by or with insiders of an organisation, but never to or on them. It is a spontaneous but also systematically undertaken process. Koshy (2005) argues for action research as a research methodology, developing the act of knowing through observation and questioning and, therefore, being involved in constructing one’s own knowledge – situation based.

Despite my constructivist viewpoint, work with action research as a methodological approach is something I consider possible. However, I prefer a stepwise approach, where analyses of the transcribed data prove more interesting. As with the pieces of a puzzle, my research paper aims to create a picture to reflect more strongly on the grounded research approach. Further, my thesis is not constructed as a member of the research member group. Instead, I will reflect on the interviewees’ information from a greater distance, on the basis of individual semi-structured interviews.

3.4 CRITICAL REFLECTION ON MY METHODOLOGICAL CONVICTION