3.0 Research methodology
3.1 Research philosophy
A research philosophy is a framework that guides how research should be conducted based on ideas about reality and the nature of knowledge (Collis and Hussey, 2014, p.43). The two main research philosophies are positivism and interpretivism. These philosophies represent two fundamentally different ways that we as humans make sense of the world around us: in positivism, reality is independent of us and researchers can therefore observe reality objectively. In interpretivism, reality is seen as highly subjective because it is shaped by our perceptions (Collis and Hussey, 2014, p.45).
Positivism originated in the natural sciences and focuses on scientific testing of hypothesis and finding logical or mathematical proof that derives from statistical analysis (Collis and Hussey, 2014, p.44). Positivists therefore tend to use large sample sizes and to produce precise, objective and quantitative data (Collis and Hussey, 2014, p.50).
This research study is underpinned by the interpretivist research philosophy. Interpretivism emerged as a result of the perceived inadequacy of positivism to meet the needs of social scientists (Collis and Hussey, 2014, p.44). It is concerned with exploring the complexities of social phenomena through achieving an empathic understanding of how the research subjects view the world (Bryman and Bell, 2011, p.16; Saunders et al., 2012, p.137), based on findings from a relatively small sample size (Collis and Hussey, 2014, p.50).
It is worth noting that the philosophy of interpretive research aligns with the way designers conduct research to gain insights about the context of the problem, learn and understand behaviour and analyse culture to achieve empathy for the users (see “Explore and empathise” under section 2.1 in Chapter 2). Design research too aims to interpret findings in order to generate theories about the nature of the problem and possible solutions.
3.2 Research approach
In line with the interpretive research philosophy, the research approach adopted for this study is qualitative and inductive. This means that the research is exploratory and aims to achieve depth rather than breadth, based on rich and subjective findings (Blaxter et al., 2010, pp.65–66; Collis and Hussey, 2014, pp.44–50). An inductively-based analytical approach allows for meanings to emerge from the data as it is being collected in order to identify patterns and relationships. The result of such an analysis is the formulation of a theory (Saunders et al., 2012, p.146).
The aim of this study is to explore the social phenomenon of design-driven strategy in organisations in order to provide a general theory about good practice for successful design adaptation in businesses. Thus, interpretivism and the inherent approaches of qualitative research and inductive analysis methods make the most appropriate approach for achieving the objectives of the research.
Unlike quantitative research, which is the common approach within the positivist research philosophy, qualitative research allows for a flexible data collection process. For example, data can be collected in several stages rather than once and the researcher can adapt the process mid-way if necessary. The researcher may decide to add or leave out certain questions on the basis of learnings that happen during the process. Moreover, qualitative research lets the researcher continue the collection and analysis of data until the researcher finds that no new issues are emerging (Denscombe, 2014, p.277). In qualitative research, data consists of words or visual images collected on the basis of observation and interaction with participants (Denscombe, 2014, p.308).
3.3 Research design
Interpretivist research allows for a deliberate selection of research participants (Collis and Hussey, 2014, p.131). Hence, the researcher mainly used purposive sampling to find and select research participants with lived professional experience of using design as a strategic tool in business (Blaxter et al., 2010, p.170; Collis and Hussey, 2014, p.132).
Snowball sampling was used in a few cases where potential research participants claimed not to personally have the relevant experience and therefore referred the researcher to other, more eligible potential research participants within their company. Apart from this minor challenge, the researcher faced no difficulties during the sampling as everyone contacted was willing to participate in the research.
In total, ten interviews took place. The sample size was not pre-determined. Rather, the researcher aimed to reach data saturation — the point when adding more participants to the study does not result in additional information (Guest et al., 2006). Each interview lasted approximately 60 minutes and was conducted face-to-face, either in person or on Skype. In order for the researcher to pay full attention in the conversations with the participants, the researcher did not take notes during the interviews. Instead, the interviews were recorded with the consent of the participants and later transcribed by the researcher.
The following ten industry professionals participated in this study:
- Lean Innovation Coach, DNB.
- Head of Applications, Altibox AS.
- Design Manager, Laerdal.
- Software Engineer, Storebrand.
- Founder and CEO, Think Outside.
- Strategic Designer, Telenor.
- Co-founder and CEO, Fiken.
- Group Leader of Digital Design and UX, NRK.
- Service Designer at a public Norwegian health organisation.
- Innovation Catalyst, Telia.
A detailed overview of research participants and interviews is available upon request.
The ten research participants can be divided into three groups:
- Key individuals within Nordic organisations who are making efforts to introduce their organisations to design.
- Key individuals within Nordic organisations, in which design is increasingly being used as a strategic tool.
- Key individuals within Nordic, design-driven startup companies.
According to Denscombe (2014, p.215), interviewing is the most appropriate research method for exploring complex and subtle phenomena like opinions, feelings and experiences, complex issues that call for a detailed understanding of how things work or privileged information based on someone’s experience or position. This is exactly what is required for this study to meet the research objectives. For this reason, semi-structured interviews were chosen as the most appropriate research method for this study (Denscombe, 2014, p.215; Easterby-Smith et al., 2012, p.132).
Semi-structured interviews are flexible and conversation-like; some questions are prepared in advance to ensure that the conversation addresses the main topics of interest (Collis and Hussey, 2014, p.133), but the researcher can choose to discard some of the pre-prepared questions in favour of letting the interviewee elaborate on interesting topics that may come up during the interview (Collis and Hussey, 2014, p.134). For this study, the researcher prepared four interview questions:
- How is your organisation using design as a strategic tool today?
- How does your current way of working differ from how it used to be before your organisation was introduced to design?
- What has been easy and what has been difficult in the process of becoming a design-driven organisation?
- How does your current way of working differ from what you consider to be the ideal way of using design strategically?
The researcher used the above questions to guide the conversations with the research participants, but took advantage of the flexibility of semi-structured interviews when other relevant topics were brought up by the participants.
There are some pitfalls of using interviews as a research method, particularly as interviewing is a time-consuming activity. After selecting relevant participants, they must be contacted in order to schedule the interviews. Then, the interviews are conducted, followed by very time-consuming tasks like transcribing and analysing the collected data (Denscombe, 2014, p.232). However, for this study, the researcher considered the collection of rich and elaborate data to be worthy of the time and effort required by this research method.
The purpose of the interviews was to gain deep insights into the industry professionals’ lived experiences with the implementation and use of design at a strategic level in their organisations. Through detailed accounts and reflections about their successes, failures and challenges in becoming more design driven, the researcher was able to gather insights into real-world issues, the varying perspectives on design and the many possible preconditions for success.
The final recommendations delivered in this study reflect industry realities. They are based on the contribution of industry experts and data drawn from real and lived experiences. For this reason, the recommendations were not tested as part of the research.
3.4 Data analysis methods
The qualitative data collected from the interviews was analysed using inductive thematic analysis. As an inductive analysis method, thematic analysis is about generating themes on the basis of the raw data (Boyatzis, 1998, p.4), which supports the research objective of developing a theory on the basis of the research findings. Just like the researcher favours the flexibility of a qualitative research methodology and the flexibility of conducting semi-structured interviews, thematic analysis offers flexibility in the data analysis process as it permits researchers to tailor it to match their own requirements (Boyatzis, 1998, p.4).
Thematic analysis is well suited for capturing the complexities of meaning within a data set (Guest et al., 2012, p.11). The researcher used thematic analysis to compare the perspectives, descriptions and reflections of the research participants, and identified themes within the data. A theme can be a pattern of explicit ideas and observations found in the data or interpretations of implicit aspects of the phenomenon being studied (Boyatzis, 1998, p.4; Guest et al., 2012, p.10). The themes serve as a basis for the researcher’s analysis and interpretation of the data. In this study, the data analysis included a comparison of theme frequencies, examination of the relationship between themes and identification of theme co-occurence (Guest et al., 2012, p.10). In this process, some themes were removed, some were merged with other themes under a new top-level theme and a few completely new themes were added. This phase was then followed by the writing up of findings, theme by theme grouped into categories, and the development of a framework providing the key factors and best practices for successful design adaptation in business. The entire research process for this study is illustrated in figure 8.
3.5 Ethics
The planned research was approved by the Teesside University Research Ethics Committee before the researcher contacted or involved any potential participants. Moreover, some guiding principles were established when designing this research on the basis of the principles for the ethical conduct of research as agreed by the Teesside University Research Ethics Committee (Teesside University, 2017):
- The research should be designed and undertaken to the highest standards of quality, integrity, ethical propriety and legal compliance.
- Research participants will be informed as fully and clearly as possible about the purposes, methods and intended use of the research, about what their participation entails and what risks and benefits are involved.
- Research participants must voluntarily consent to participate.
- The confidentiality of information supplied by research participants, as well as their anonymity, must be respected. All data obtained from and about research participants will be collected, processed, stored and disposed of in accordance with the UK 1998 Data Protection Act.
To adhere to the guiding principles for good research ethics, the researcher took a number of steps and precautions before, during and after the interviews. Before their participation in the interviews, each participant was given a Participant Information Sheet (available upon request) clearly stating the background and purpose of the research, what it means to participate in the study and the associated risks and benefits. Before their participation, informed and voluntary consent was obtained from all the research participants to include their contributions in this study (available upon request). The participants were given the option to withdraw from the study within ten days from the time of their interview without a need to give reason. The researcher considered the implications of identifying the research participants in this study and therefore contacted each of them individually to obtain consent to have their name, role and organisation identified (available upon request). All of them consented to have their name and role identified. One research participant requested to be described as a representative of their industry rather than an identified organisation. Finally, as the participants were largely asked about the workings of their organisations, their participation was approved by a senior person in each organisation unless the participant him/herself had a senior role (available upon request).
The researcher was aware of the importance of considering how the collected information is stored and took the necessary steps to ensure that only the researcher could access the raw data and personal information collected from the research (Denscombe, 2014, p.358). Interview notes, recordings (obtained with consent from each interviewee at the beginning of the interviews) and transcripts of the recorded interviews were kept secure and strictly confidential. All the raw data was destroyed upon publication of the study.
The potential bias from the researcher and measures taken for limiting researcher bias is addressed in section 3.6.
3.6 Credibility
Reliability
The concept of reliability refers to “the accuracy and precision of the measurement and absence of differences in the results if the research was repeated” (Collis and Hussey, 2014, p.52). Producing findings with high reliability can be a challenge in interpretivist research because of the subjectivity that comes with the high degree of researcher involvement in qualitative research methods (Collis and Hussey, 2014, p.46–47). In practice, this means that different researchers may collect different data and come to different findings at the end because the researcher’s background, identity, values and interests can influence the collection and analysis of the data (Denscombe, 2014, p.276).
To counteract a potential negative impact on the reliability of the results, the researcher remained conscious of her own role in the research so that potential bias in the findings could be eliminated or, at least, minimised. The researcher was also aware of the innate human tendency to validate one’s own beliefs, known as confirmation bias (Hallihan and Shu, 2013): researchers may unconsciously emphasise those perspectives that fuel their pre-existing views, while disregarding options that do not support these personal assumptions. In this study, the researcher tried to avoid confirmation bias and produce reliable results by consciously treating all data equally, being honest in the analysis of the collected data and avoiding any temptation to manipulate the data (Denscombe, 2014, p.358). Moreover, discussions and consultation with the research supervisor further contributed to avoiding researcher bias.
Validity
Like reliability, validity is a way of assessing the quality of the chosen research design and methods. If the research findings truly measure the phenomenon they claim to measure, the findings can be judged valid (Collis and Hussey, 2014, p.53).
On the basis of the appropriateness of the chosen methods of data collection and analysis, the data collected for the purpose of this study is highly likely to be accurate and appropriate (Denscombe, 2014, p.331). The validity of this study is further underpinned by the level of attention paid to ethical issues in the research design and the researcher’s conscious attempts to eliminate researcher bias throughout the entire research process.
Generalisability
As this research study is underpinned by the interpretivist research philosophy and the data is not statistically analysed, generalisation is not the aim of the study (Collis and Hussey, 2014, p.151). However, the findings are nonetheless likely to be generalisable to other settings similar to those that have been studied.
The researcher has attempted to capture the characteristics and complexities of adopting design as a strategic tool in organisations and has gained a comprehensive and deep understanding of this phenomenon. Thus, the richness of the collected data has enabled the generation of patterns, concepts and theories that ought to be true and applicable in other organisations that set out to become design driven (Denscombe, 2014, p.54).
References
Blaxter, L., Hughes, C. and Tight, M. (2010). How to research. 4th ed. Maidenhead: Open University Press.
Boyatzis, R. (1998). Transforming Qualitative Information: Thematic Analysis and Code Development. Thousand Oaks, CA: Sage Publications.
Bryman, A. and Bell, E. (2011). Business research methods. 3rd ed. Oxford: Oxford University Press.
Collis, J. and Hussey, R. (2014). Business research. 4th ed. Basingstoke: Palgrave Macmillan.
Denscombe, M. (2014). The Good Research Guide. 5th ed. Maidenhead, England: McGraw-Hill/Open University Press.
Easterby-Smith, M., Thorpe, R. and Jackson, P. (2012). Management research. 4th ed. London: Sage.
Guest, G., Bunce, A. and Johnson, L. (2006). How Many Interviews Are Enough? Field Methods, 18(1), pp.59–82.
Guest, G., MacQueen, K. and Namey, E. (2012). Applied Thematic Analysis. Los Angeles: Sage Publications.
Hallihan, G. and Shu, L. (2013). Considering Confirmation Bias in Design and Design Research. Journal of Integrated Design and Process Science, 17(4), pp.19–35.
Saunders, M., Lewis, P. and Thornhill, A. (2012). Research methods for business students. 6th ed. Harlow: Pearson Education Limited.
Teesside University (2017). Teesside University — Research — Research Governance. [online] Tees.ac.uk. Available at: https://www.tees.ac.uk/sections/research/ethics.cfm (Accessed: 26 Dec 2017).
© Nadine Ramsberg, 2018
Hyper Island — MA Digital Management
Industry Research Project