This chapter provides an overview of the methodological approach and the research design selected for this study. In this context, the methodology proposed in the following points was considered the more appropriate to understand the reasons for knowledge management cloud solutions adoption by small companies. Moreover, the chapter presents motivations for the chosen methods and describes the processes of analysis and the applied research instruments in more detail.
In this section I present the general structure that I will follow in order to answer the research question and meet the study’s objective.
Approach – Inductive
This study follows an inductive reasoning approach, i.e. it does not try to test a theory or hypothesis (deductive reasoning) but instead it can be associated with theory building, where data is collected and theory is developed based on the results of the data analysis. This type of reasoning allows for a more close understanding of the research context (Saunders et. al., 2009).
Saunders et. al. (2009) further argues that when a subject is relatively new or there is little existing literature, it is proper to work inductively and reflect upon what theoretical constructs the data are suggesting.
Method – Qualitative
There are three research approaches that can be used to study a topic: quantitative, qualitative and mixed methods. Quantitative research is an approach applied for data that can be measured, used for testing objective theories by examining the relationship between and among variables. When using this type of approach, the researcher develops hypotheses and tests theories, being able to generalize and replicate the findings. In contrast, qualitative research is more concerned with data that cannot be measured and it is used for exploring and understanding a certain situation, where the researcher has to make interpretations of the meaning of the data. Mixed methods research involves gathering both quantitative and qualitative data, using distinct designs (Creswell, 2014).
In order to answer the research question “What are the main factors that influence the adoption of a KM cloud-based solution in small enterprises?” a qualitative research approach was chosen. The aim of this study is to identify the key drivers that might facilitate or inhibit the adoption of cloud computing for managing knowledge and understand what are the reasons behind adopting such solutions by small enterprises. The study will fill a gap in the theoretical field regarding the viability of implementing KM in the cloud in small enterprises, therefore there is a need for an in-depth understanding of the decision making process by enterprises. Based on Creswell (2014), qualitative research can be useful when a concept needs to be understood because there is little research about it.
Purpose – Exploratory
As explained by Saunders et. al. (2009), the purpose of a research study can be exploratory, descrip-tive or explanatory. Exploratory research is usually conducted to explore a topic, which is new or has not been clearly defined. Descriptive research is performed in order to describe situations and phe-nomena. It means that there is no need to clarify the problem because it has already been defined. An explanatory study is carried out in order to find and explain causal relationships between variables (Saunders et. al., 2009).
The purpose of this study is exploratory, as it tries to explore the adoption of cloud KM by identifying the key factors that influence the adoption process in small enterprises.
Strategy – Semi – structured interview
In regard to the qualitative research design of this study, Creswell (2014) presents four data collection methods; interviews, observations, documents and audio/visual materials. Interviews usually involve a face to face conversation with the participants. A qualitative observation happens when the researcher takes a passive role by only observing a phenomenon. Qualitative documents refer to collecting documents such as newspapers, meetings minutes, official reports, letters, e-mails etc. Gathering audio and visual materials involves data that may be gathered from photographs, videos, social media, art objects or any forms of visual and sound.
In this study the data collection method that will be used is the interview. The method was imposed by the nature of the research question and by the need to grasp the thoughts, perspectives and views of the interviewees regarding the reasons for choosing or not choosing a KM cloud-based solution for the enterprise.
Saunders et. al. (2009) distinguishes between (1) structured, (2) semi-structured and (3) unstructured interviews.
Structured interviews can be seen as interviewer administered questionnaires based on a predetermined and standardized set of questions where the researcher needs to ask the questions in the same order and adopt the same consistent behavior when interviewing each participant. In Semi-structured interviews the researcher has prepared a list of topics and questions that have to be covered but they might vary from interview to interview and some questions can be omitted or added judging by specific contexts. The unstructured interviews are more informal and are used to explore an areac in depth. There is no specific or predetermined set of questions and the interviewee is given the opportunity to talk freely about a certain topic area (Saunders et. al., 2009).
In this study, semi-structured interviews will be used as it can allow for a less formal interview by interacting with participants and asking the questions depending on the context and direction of the conversation.
Sampling – convenience
The sampling frame represents the list of all units in a population from which the sample will be selected. The sampling frame in this study can be defined as all small businesses from Romania.
Sampling represents the method of choosing participants that will be involved in a study. According to Saunders (2009) there are two types of sampling techniques: probabilistic and non-probabilistic. The probabilistic sampling technique gives the possibility to estimate statistically the characteristics of the population from the sample. The non-probabilistic sampling gives the possibility to generalize about a population but not on statistical grounds.
In order to choose the participants for this study, I used the non-probabilistic sampling technique, convenience sampling. This method involves selecting participants to the study depending on availability or accessibility. Convenience sampling was chosen because of the time constraints required to carry out the research and the accessibility of the chosen sample.
After having identified potential companies for the interviews (mainly by internet search, private recommendations and personal experiences), I contacted them by email, inviting them to participate in the interview and providing them with a short description of the thesis subject and purpose. A total number of four companies replied favorably and accepted to participate in the research. The four companies belong to manufacturing, advertising, consultancy, and IT sector. In consequence, four companies from four different sectors were chosen to represent small businesses in Romania.
Time horizons – Cross sectional
A topic can be studied at a particular point in time (cross-sectional) or it can be the representation of events over a given period in order to study change and development over time (longitudinal) (Saunders et. al., 2009).
This thesis will follow a cross-sectional time horizon by studying a particular phenomenon at a particular time. Cross-sectional studies are common for projects performed for academic courses, due to the time constraints involved (Saunders et. al., 2009).
Techniques – Data analysis
The data analysis in this qualitative study will consist of analyzing the text obtained from the interviews through conceptualization. The analysis of text consists in finding important themes, patterns and relations that will help reaching a conclusion and answer the research question. The answers from the interviews were summarized and structured in a logical sequence in order to ease the analytical process.
The analysis of prior research on similar topics provided a theoretical framework (TOE) that will be used as an orienting means to guide the interviews, but without trying to impose pre-existing expectations (Patton, 2002). Structuring the data collection in this way will also help to organize and direct the data analysis.
This method combines some elements of deductive approach as I developed a theoretical position followed by testing its applicability through subsequent data collection and analysis. Saunders et. al. (2009) argues that even though an inductive approach is incorporated in a research, starting the work from a theoretical perspective has its advantages. For example, it will link the research into an existing body of knowledge and help the researcher get started but also provide him/her with an initial analytical framework.
The representative sample was not limited to a specific industry, following the idea that every company must have in place some kind of knowledge management, being it formal or informal (see section 2.3.2), in order to operate in the current business environment. Succeeding this rationale, it was also not important if companies used cloud computing or not for managing knowledge, as it was presumed that both situations would give information on reasons.
I acknowledge that in companies pertaining to high knowledge intensive sectors, the management of knowledge is assumed to be more critical and requires an increased use of information technology (IT), but the purpose of this study was not to analyze the level of use of KM and cloud, but to explore reasons and perceptions of small companies. The only requirement for choosing the companies was the number of employees, which needed to be below 50.
1.4 Research question
1.5 Delimitations .
2 Theoretical background
2.1 Small enterprises
2.3 Knowledge management in small enterprises
2.4 Cloud computing in small enterprises
2.5 Knowledge management cloud based solutions
2.6 Defining adoption
2.7 Theoretical framework
3 Research methodology
3.1 Research structure
3.2 Industry selection
3.3 Data collection
4.2 Interview with company C1
4.3 Interview with company C2
4.4 Interview with company C3
4.5 Interview with company C4
6 Conclusion and discussion
6.1 Limitations and further research
List of references
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