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Generally, choosing research methods serves two goals: First to answer the research question and second to transform the information into knowledge, which is a long process. This process depends primarily on the conscious choice of appropriate methods. According to Rickenberg (2008) “methods serve as an infrastructure through which information is conveyed and knowledge is codified. […] In other words, they are the rules and routines with which practitioners develop common perspectives and build upon lessons learned by others” (p. 121). In this thesis, gathering, analyzing and interpreting the data occurs at multiple points and involves three sequential phases; accordingly different methods will be used for the specific purpose of each phase.

In the first phase, ANALYSIS, Vester’s Sensitivity Model will be used and key decisions will be taken.

Reasons will be given for selecting an intervention point and specifying critical conditions. The second phase, PROJECTION, will raise new research question: How might the environment look in which the problem at issue is embedded? This question will be approached via Schwartz’s scenario technique of exploring the desired future. These two phases will be followed by an experimental intervention applying different visual analysis and interpretation tools. This third phase, SYNTHESIS, will end with the development of a solution prototype in the form of a social business design model (see Research Design Picture).

4.4.5.1 Phase 1: ANALYSIS  Vester’s Sensitivity Model

Data has been collected from the following sources:

 Observation: conducting an observation and gathering field notes.

 Interviews: conducting a semi-structured, expert open-ended interview with interview notes (see initial interview questions, Appendix A).

 Documents: collecting and analyzing different Project Progress Reports (2004, 2005, 2006, 2007).

Vester’s Sensitivity Model, a computer software program, will be used for data analysis in this project, because of its ability to support the user in capturing the problem comprehensively ‒ i.e.

grasping reality as “a network of connections that transcend subject boundaries” (Vester 2007, p.

110) or, to put it another way, taking the complex nature of the problem into account instead of fragmenting it into separate components. Another useful quality is that by incorporating ‘soft’ data into the systemic model it can map reality while respecting human perceptions of it.

Moreover, applying the linguistic approach of fuzzy logic in a user-friendly way prevents one from getting lost in an endless number of mathematical processes while capturing the examined system (see Malik Management Zentrum St. Gallen, no date, p. 10). Vester (2007) further explains the benefits of applying fuzzy logic stating that

93 every stage of capturing and interpreting a system can be worked through with the same set of variables comprising 'hard' and 'soft' influence factors. Using appropriate table functions, even imprecise, purely qualitative effects can be described mathematically, with the result that the same variable can also be employed in the subsequent simulation. (p. 209)

This program has played an important role in quantifying the qualitative data: the qualitative data is converted to a numerical code to be analyzed and interpreted mathematically.

Preparing and processing the data used in the program will be explicitly presented in Chapter 6 (see Analysis) after explaining the background concepts of the software program in Chapter 5 (see Vester’s Sensitivity Model). But at this point, it is important to refer to the specific tool used in this program that will support the researcher to take decisions with respect to the dynamic character of the examined system. ‘Role allocation’ analysis, a two-dimensional diagram, is provided as an output that represents and distributes all the variables according to their character in the system (active/

reactive/ critical/ buffering). This tool will serve as a strategic indicator for determining intervention possibilities and critical conditions, in order to intervene in a sustainable way.

4.4.5.2 Phase 2: PROJECTION

 Schwartz scenario technique

After reasoning these choices, a sequential phase is required to explore the chosen variables. The second phase, PROJECTION, is related to the chosen variables and provides insights into the question as to the form of the environment in which the problem at issue is embedded.

In this regard, Schwartz scenario technique will be chosen for analyzing the data, after collecting new relevant data in the second phase from different sources: reports, surveys and scientific papers. This technique will be explained and presented in the form of a table in Chapter 5 (see Developing scenarios after Schwartz) while processing the data will be explained in Chapter 6 (see PROJECTION).

Scenario technique is generally a promising analysis method for exploring the future with respect to its uncertainty, and Peter Schwartz (1991) developed a step-by-step guideline specifically for scenarios that help people change their way of approaching reality and ‘re-perceiving’ rather than

‘predicting’ the future.

After applying this method of analysis, the data will be transformed into a ‘context scenario’ matrix where four scenario logics will be established. The core vision of each scenario will be described in an

“end-state” description that provides the answer to the proposed question in a narrative way.

Afterwards, a desirable scenario will be chosen and a strategic insight will be built upon this scenario, including goal, intention, and objective.

4.4.5.3 Phase 3: SYNTHESIS

 Visual analysis and interpretations

After collecting new data in the form of audiovisual materials, different visual analyzing tools will be used in this third phase such as: storyboard, system map, tables, user scenario, and model.

SYNTHESIS is the final phase planned in this thesis that aims at developing a sustainable strategy to

94 solve the proposed problem. Starting with collecting new data regarding the selected target groups, and presenting this data through a visual storyboard, enables target group to identify their wants and needs in a tangible way. Afterwards, collecting relevant information related to market forces will be presented and analyzed in a table in Chapter 5 (see Collecting relevant information on market forces). Then an interpretation of the problem will be presented in the form of a system map (see Designing the problem system-map). Finally transforming information into a business model will be explained and a user scenario and implementation strategy developed. Processing the data and results will be presented in detail in Chapter 5 (see Synthesis).

4.4.5.4 Validity, Reliability and Generalizability

Validity is kind of strategy adopted by researchers to check the quality of their collected data, their results and their interpretation (Creswell and Clark 2011, p. 210). There are two kinds of validity, internal and external.

 Internal validity: to validate the accuracy of the findings (validity) and to demonstrate the reliability of procedures (reliability)

 External validity: to discuss the role of generalization (generalizability) and apply results to new settings, people or samples.

Strategies of Internal and External Validity

Three techniques to ensure internal validity are utilized in this thesis:

 Triangulation technique (Creswell 2009, p. 191), a common technique discussed by many scholars, refers to collecting data from different sources to ensure the internal validity of the study. This technique has been adopted in this research by gathering data from multiple sources, such as conducting two-stage interviews and presenting them in a narrative that sheds light on the challenges and setbacks, as well as the opportunities for further intervention. Additional sources are derived from reviewing and analyzing many related project reports, observations, audio visual materials, photos, online local newspapers, video reports and published papers and human development reports.

 External auditor: After finishing the first two phases, ANALYSIS and PROJECTION have been scrutinized by an external auditor who is an expert in cybernetic thinking. I requested her feedback per mail, especially in processing the data through applying Vester’s Sensitivity Model, because she worked with Professor Vester on the development of interconnected thinking.

 Member checking (Creswell 2009, p. 191): After polishing the interviews and interweaving them in the form of different stories, the final output was taken back to one of the interviewees in order to get feedback.

External validity has been guaranteed in this thesis through adopting the provision of “rich, thick, detailed description” (Yin 2003, Creswell 2009, p. 190). Explaining every method in detail, providing detailed definitions of each variable, and documenting many data processing steps, both visualizes the experiences and enables them to be shared, should other researchers be interested in transferring them to another context.

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Conclusion

The list below summarizes the chosen terminology in a sequential way. The table provides a research design picture visualizing all the conceptual aspects in a single comprehensive framework.

Pragmatic worldview with transformative character -> ontological assumption (exploring and empowering) -> epistemological position (system thinking) ->

methodological approach (dynamic mixed methods design) -> strategy of inquiry (case study) -> methods (open-end interviews with experts, Vester’s Sensitivity Model, Schwartz scenarios, different visual analyzing and interpretation tools)

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