Research design

A research design refers to the approach used in order to collect and analyse data about a specific research topic. It includes an outline of the researcher‟s methods, from defining research questions/hypotheses through to the outcome of the study, and the criteria used for evaluating the conducted investigation. Therefore, the research design provides a framework for “the generation of evidence that is suited both to a certain set of criteria and to the research question in which the investigator is interested” (Bryman, 2008, p. 30).

For the purpose of collecting and analysing data about the qualities and success factors of commercial logistics companies and humanitarian aid agencies, a cross-sectional research design with secondary analysis of existing data and case studies was chosen.

A cross-sectional design, also called „survey design‟ refers to “the collection of data on more than one case (...) and at a single point in time in order to collect a body of quantitative or quantifiable data in connection with two or more variables (...), which are then examined to detect patterns of association

(Bryman, 2008, p. 44).

This approach involves investigation into the variation of results with regard to different cases. Hence, the researcher was able to explore variations between organisations, i.e. various commercial logistics companies and humanitarian aid organisations; and people, i.e. different job positions, age, etc. of logistics

employees and humanitarian aid workers. This design requires the collection of primary data on the variables of interest at a single point in time (Graziano & Raulin, 2010).

A questionnaire, which was completed by a determined sample population, served as the principle method for the gathering of primary information. However, this entailed that the data deployed in the study would come from a single data collection phase, since respondents were not post-tested in a later survey: although a comparison of data gathered on population characteristics to results collected at a subsequent date was not possible within this study, subgroups were sampled as defined by age (e.g. 30 to less than 40 years) in order to achieve a sufficient mode of comparison.

The choice of the research design was also based on the timescale and resources available and in particular on the feasibility of the research with some account of hidden or unknown problems that may have prevented it from being completed on time.

Overall, the research method provided a well-founded overview of the current views about cross-sector collaborations.

3.2.1 Deductive versus inductive research approach

In general, research can either be explanatory or descriptive and its findings either deductive or inductive. According to Saunders, Lewis, and Thornhill (2007), there are two ways of designing a research approach. First is the deductive approach, where the researcher creates a hypothesis and chooses a research strategy in order to examine the hypothesis. Hence, the research process is based on a previous logical line of reasoning in order to collect data towards confirming or negating the theory. Secondly is an inductive approach, that essentially works in the opposite way: the researcher collects and analyses data given and designs a theory resulting from information analysis (Saunders Lewis & Thornhill, 2007; Veal, 2005).

This study was based on inductive reasoning since the research process began with the gathering of primary and secondary data which was then analysed with final conclusions drawn from the information thus made available. The decision to follow an inductive approach was based on the fact that cross- sector collaborations in the area of humanitarian aid and disaster relief represent a relatively new phenomenon that has not yet been researched in depth: in

particular with regard to the qualities that commercial logistics providers and humanitarian aid agencies require for the establishment of successful partnerships.

However, a sufficient amount of articles based on corporate-humanitarian partnerships were available so that a relatively broad comprehension of the topic could be achieved. Additionally, primary data which was collected through a survey, provided specific information on the investigated topic and this allowed the researcher to develop a theory that displays the analysed results. Finally, it can be argued that an inductive approach left a margin for change in the research emphasis. This was especially helpful at the beginning of the research process since subsections of the topic could be adapted according to the availability of information.

3.2.2 Quantitative and qualitative methods

In terms of methodology, two distinctive approaches for conducting research can be distinguished. First, the quantitative strategy focuses on the quantification of data in the collection and analysis process. Numerical data is collected in order to test hypotheses/theories or draw conclusions (Bryman, 2008). It is often necessary to collect data from a relatively large sample size in order to ensure reliability of results (Veal, 2005). Quantitative methods, such as questionnaires, observation, and information from secondary sources aim at generalising findings of a representative sample studied to a wider population (Veal, 2005).

Qualitative research in contrast, is focused on the collection and analysis of words rather than statistical data (Veal, 2005; Bryman, 2008). Usually, a great amount of information about a smaller number of topics is gathered for the purpose of generating new theories. Qualitative data, however, might not be as representative as quantitative information because of the small sample size, often comprising only a few individuals or organisations, that is necessitated by the higher volume of information to be gathered from each source. Therefore, this approach places its emphasis on a deep understanding of the behaviour and experience of a small sample.

This thesis focuses on the analysis of quantitative information about corporate-humanitarian collaborations. The aim, as far as possible, was to generalise results derived from data collected from a broad sample, which can be

regarded as representative of a wider population. Adapting a quantitative approach enabled the researcher to provide a broad overview of the current trends in this area, which allows subsequent studies to focus on only a few points that might be of high importance to the subject. The principle method for collecting primary data was a questionnaire which mainly resulted in statistical information.