Observation, as the name implies, is a way of collecting data through observing. This data collection method is classified as a participatory study, because the researcher has to immerse herself in the setting where her respondents are, while taking notes and/or recording. Observation data collection method may involve watching, listening, reading, touching, and recording behavior and characteristics of phenomena. Observation as a data collection method can be structured or unstructured. In structured or systematic observation, data collection is conducted using specific variables and according to a pre-defined schedule. Unstructured observation, on the other hand, is conducted in an open and free manner in a sense that there would be no pre-determined variables or objectives. Moreover, this data collection method can be divided into overt or covert categories. In overt observation research subjects are aware that they are being observed. In covert observation, on the other hand, the observer is concealed and sample group members are not aware that they are being observed. Covert observation is considered to be more effective because in this case sample group members are likely to behave naturally with positive implications on the authenticity of research findings. Advantages of observation data collection method include direct access to research phenomena, high levels of flexibility in terms of application and generating a permanent record of phenomena to be referred to later. At the same time, this method is disadvantaged with longer time requirements, high levels of observer bias, and impact of observer on primary data, in a way that presence of observer may influence the behaviour of sample group elements. It is important to note that observation data collection method may be associated with certain ethical issues. As it is discussed further below in greater details, fully informed consent of research participant(s) is one of the basic ethical…

Qualitative data collection methods are exploratory in nature and are mainly concerned with gaining insights and understanding on underlying reasons and motivations. Qualitative data is a linguistic or visual material. Qualitative data collection methods emerged after it became evident that traditional quantitative data collection methods were unable to express human feelings and emotions. Monette et al (2010)[1] credit qualitative methods with the acknowledgement of abstraction and generalisation. Polonsky and Waller (2011)[2] categorize vision, images, forms and structures in various media, as well as, spoken and printed word and recorded sound into qualitative data collection methods. Qualitative data collection methods are used in order to examine the following phenomenon: Human feelings and experiences Meanings and relationships Social norms and cultural practices. It is noted that “qualitative methods are often regarded as providing rich data about real life people and situations and being more able to make sense of behaviour and to understand behaviour within its wider context. However, qualitative research is often criticised for lacking generalizability, being too reliant on the subjective interpretations by researchers and being incapable of replication by other researchers.”[3] Popular qualitative data collection methods used in business studies include interviews, focus groups, observation and action research. Moreover, grounded theory and document analysis can be also used as data collection method in qualitative studies.  The main sources and procedures associated with the most popular qualitative methods are presented on Table 1 below as proposed by Yamagata-Lynch (2010)[4]: Methodology Sources Procedure Document analysis Reports, newsletters, publications Read all materials and documented and descriptive statistics related to the research issue Interviews Primary participants Secondary participants Tape recorded semi-structured interviews, then transcribed the interviews for the participants to review Observations Observed participants’ interactions Took notes and videotaped the observations Exit interviews    Primary participants Secondary participants Presented findings to participants during…

Futures research can be defined as a systematic study of possible future events and circumstances. As a field of study, futures evolved in 1950s. Futures research is different from forecasting in a way that the former has a forward orientation and looks ahead, rather that backwards, and is not as mathematical as forecasting. It can be argued that highly dynamic nature of the contemporary global marketplace is making is difficult to conduct quality futures studies. For example, it is now evident that COVID-19 global pandemic has compromised findings of many futures studies. This is because no researcher could foresee the occurrence of extent of implications of pandemic on global business and economics. Disadvantages of futures research are straightforward – no event or situation can be forecasted in an accurate and complete manner. Nevertheless, futures studies may offer a substantial advantage. Specifically, although futures studies are not able to produce totally accurate and complete information about the future, some researched information about the future is better than no information at all when engaging in decision making for long-term perspective. There is wide range of techniques available that can be used to conduct futures studies. The following table illustrates types and techniques of the most popular futures techniques. Method Quantitative Qualitative Normative Exploratory Agent  Modeling ü        ü    Complexity based models ü        ü    Cross Impact Analysis ü        ü    Decision Models ü        ü    Delphi   ü    ü    ü    Econometrics ü        ü    Environmental Scanning   ü      ü    Futures Wheel   ü    ü    ü    Genius Forecasting   ü    ü    ü    Morphological Analysis   ü    ü      Participatory Methods   ü    ü      Regression ü        ü    Relevance Trees   ü    ü      Scenarios ü    ü    ü    ü    Science Road Maps   ü      ü   …

Quantitative research methods describe and measure the level of occurrences on the basis of numbers and calculations. Moreover, the questions of “how many?” and “how often?” are often asked in quantitative studies. Accordingly, quantitative data collection methods are based on numbers and mathematical calculations. Quantitative research can be described as ‘entailing the collection of numerical data and exhibiting the view of relationship between theory and research as deductive, a predilection for natural science approach, and as having an objectivist conception of social reality’[1]. In other words, quantitative studies mainly examine relationships between numerically measured variables with the application of statistical techniques. Quantitative data collection methods are based on random sampling and structured data collection instruments. Findings of quantitative studies are usually easy to present, summarize, compare and generalize. Qualitative studies, on the contrary, are usually based on non-random sampling methods and use non-quantifiable data such as words, feelings, emotions ect. Table below illustrates the main differences between qualitative and quantitative data collection and research methods:   Quantitative Qualitative Requirement Question Hypothesis Interest Method Control and randomization Curiosity and reflexivity Data collection Response Vewpoint Outcome Dependent variable Accounts Ideal Data Numerical Textual Sample size Large (power) Small (saturation) Context Eliminated Highlighted Analysis Rejection on null Synthesis Main differences between quantitative and qualitative methods   The most popular quantitative data collection methods include the following: Interviews. Only highly structured interviews with closed-ended questions can be used for quantitative data collection. Interviews can be conducted in one of the following formats: Face-to-face interviews; Telephone interviews; Computer-Assisted Personal Interviewing (CAPI). Questionnaires (surveys). Again, questionnaires only with closed-ended questions can be used as quantitative data collection method. The following are popular formats for questionnaires: Internet-based questionnaire; Mail questionnaire; Face-to-face survey. Observations. The type of observation that can be used to collect quantitative data is systematic,…

Data collection is a process of collecting information from all the relevant sources to find answers to the research problem, test the hypothesis (if you are following deductive approach) and evaluate the outcomes. Data collection methods can be divided into two categories: secondary methods of data collection and primary methods of data collection.   Secondary Data Collection Methods Secondary data is a type of data that has already been published in books, newspapers, magazines, journals, online portals etc.  There is an abundance of data available in these sources about your research area in business studies, almost regardless of the nature of the research area. Therefore, application of appropriate set of criteria to select secondary data to be used in the study plays an important role in terms of increasing the levels of research validity and reliability. These criteria include, but not limited to date of publication, credential of the author, reliability of the source, quality of discussions, depth of analyses, the extent of contribution of the text to the development of the research area etc. Secondary data collection is discussed in greater depth in Literature Review chapter. Secondary data collection methods offer a range of advantages such as saving time, effort and expenses. However they have a major disadvantage. Specifically, secondary research does not make contribution to the expansion of the literature by producing fresh (new) data.   Primary Data Collection Methods Primary data is the type of data that has not been around before. Primary data is unique findings of your research. Primary data collection and analysis typically requires more time and effort to conduct compared to the secondary data research. Primary data collection methods can be divided into two groups: quantitative and qualitative. Quantitative data collection methods are based on mathematical calculations in various formats. Methods of quantitative…

Descriptive research can be explained as a statement of affairs as they are at present with the researcher having no control over variable. Moreover, “descriptive studies may be characterised as simply the attempt to determine, describe or identify what is, while analytical research attempts to establish why it is that way or how it came to be”[1]. Three main purposes of descriptive studies can be explained as describing, explaining and validating research findings. This type of research is popular with non-quantified topic. Descriptive research is “aimed at casting light on current issues or problems through a process of data collection that enables them to describe the situation more completely than was possible without employing this method.”[2] To put it simply, descriptive studies are used to describe various aspects of the phenomenon. In its popular format, descriptive research is used to describe characteristics and/or behaviour of sample population. It is an effective method to get information that can be used to develop hypotheses and propose associations. Importantly, these types of studies do not focus on reasons for the occurrence of the phenomenon. In other words, descriptive research focuses on the question “What?”, but it is not concerned with the question “Why?” Descriptive studies have the following characteristics: 1. While descriptive research can employ a number of variables, only one variable is required to conduct a descriptive study. 2. Descriptive studies are closely associated with observational studies, but they are not limited with observation data collection method. Case studies and surveys can also be specified as popular data collection methods used with descriptive studies. 3. Findings of descriptive researches create a scope for further research. When a descriptive study answers to the question “What?”, a further research can be conducted to find an answer to “Why?” question.   Examples of Descriptive Research Research…

Exploratory research, as the name implies, intends merely to explore the research questions and does not intend to offer final and conclusive solutions to existing problems. This type of research is usually conducted to study a problem that has not been clearly defined yet. Conducted in order to determine the nature of the problem, exploratory research is not intended to provide conclusive evidence, but helps us to have a better understanding of the problem. When conducting exploratory research, the researcher ought to be willing to change his/her direction as a result of revelation of new data and new insights.[1] Accordingly, exploratory studies are often conducted using interpretive research methods and they answer to questions such as what, why and how. Exploratory research design does not aim to provide the final and conclusive answers to the research questions, but merely explores the research topic with varying levels of depth. It has been noted that “exploratory research is the initial research, which forms the basis of more conclusive research. It can even help in determining the research design, sampling methodology and data collection method”[2]. Exploratory research “tends to tackle new problems on which little or no previous research has been done”[3]. Unstructured interviews are the most popular primary data collection method with exploratory studies. Additionally, surveys, focus groups and observation methods can be used to collect primary data for this type of studies.   Examples of Exploratory Research Design The following are some examples for studies with exploratory research design in business studies: A study into the role of social networking sites as an effective marketing communication channel An investigation into the ways of improvement of quality of customer services within hospitality sector in London An assessment of the role of corporate social responsibility on consumer behaviour in pharmaceutical industry in the…

Applied research “aims at finding a solution for an immediate problem facing a society, or an industrial/business organisation, whereas fundamental research is mainly concerned with generalisations and with the formulation of a theory”[1]. Applied research is considered to be non-systematic inquiry and it is usually launched by a company, agency or an individual in order to address a specific problem.[2]    Applied research can be divided into the following three categories: 1. Evaluation research. This type of research focuses on analysing existing information about the phenomenon in order to generate objective research outcomes. A study into the ways of reducing supply-chain costs can be mentioned as an example for an evaluation research. 2. Research and Development. It is a type of applied research that focuses on the development of new products and services to satisfy needs and wants of target customer segment. This type of applied research is the least relevant to a business dissertation. 3. Action research. This type of study aims to tackle specific business problems. For example, a research into the ways of restoring Starbucks brand image in UK after the tax scandal can be classified as an action research.   Differences between Applied Research and Fundamental (Basic) Research The difference between applied and fundamental or basic research is straightforward – findings of applied research can be applied to resolve problems, whereas fundamental studies are used simply to explore certain issues and elements. Applied research can be a follow-up to the findings of a fundamental research. Moreover, differences between applied and basic research can be summarized into three points: 1. Differences in purpose. Purpose of applied studies is closely associated with the solution of specific problems, while the purpose of fundamental studies relate to creation of new knowledge or expansion of the current knowledge without any concerns to applicability.…

Same as research approach, different textbooks place different meanings on research design. Some authors consider research design as the choice between qualitative and quantitative research methods. Others argue that research design refers to the choice of specific methods of data collection and analysis. Research design is also placed as a master plan for conducting a research project and this appears to be the most authentic explanation of the term.  In your dissertation you can define research design as a general plan about what you will do to answer the research question.[1] It is a framework for choosing specific methods of data collection and data analysis. Research design can be divided into two groups: exploratory and conclusive. Exploratory research, according to its name merely aims to explore specific aspects of the research area. Exploratory research does not aim to provide final and conclusive answers to research questions. The researcher may even change the direction of the study to a certain extent, however not fundamentally, according to new evidences gained during the research process. Conclusive research, on the contrary, generate findings that can be practically useful for decision-making. The following Table 1 illustrates the main differences between exploratory and conclusive research in relation to important components of a dissertation. Research project components Exploratory research Conclusive research Research purpose General: to generate insights about a situation Specific: to verify insights and aid in selecting a course of action Data needs Vague Clear Data sources Ill defined Well defined Data collection form Open-ended, rough Usually structured Sample Relatively small; subjectively selected to maximize generalization of insights Relatively large; objectively selected to permit generalization of findings Data collection Flexible; no set procedure Rigid; well-laid-out procedure Data analysis Informal; typically non-quantitative Formal; typically quantitative Inferences/ Recommendations More tentative than final More final than tentative Table 1 Major differences between…

“Constructivism is the recognition that reality is a product of human intelligence interacting with experience in the real world. As soon as you include human mental activity in the process of knowing reality, you have accepted constructivism” Davis Elkind Constructivism accepts reality as a construct of human mind, therefore reality is perceived to be subjective. Moreover, this philosophical approach is closely associated with pragmatism and relativism. In simple terms, according to constructivism, all knowledge is constructed from human experience. This viewpoint is based on inseparability between knowledge and knower. Constructivism philosophy is based on cognitive psychology and its background relates to Socratic method, ancient Greece. Nevertheless, popularity of constructivism as a perspective in epistemology increased in recent years. The main distinction between constructivism philosophy and positivism relates to the fact that while positivism argues that knowledge is generated in a scientific method, constructivism maintains that knowledge is constructed by scientists and it opposes the idea that there is a single methodology to generate knowledge. There are various types of constructivism such as phenomenological constructivism, biological constructivism, cognitive constructivism and radical constructivism. However, in business dissertations you are not expected to discuss each of these types in great lengths.  The Table 1 below illustrates the major differences between constructivism, positivism and pragmatism philosophies: Philosophy Constructivism Positivism Pragmatism Type of research Qualitative Quantitative Mixed Methods Open-ended questions, emerging approaches, text and/or image data Closed-ended questions, pre-determined approaches, numeric data Both, open and closed-ended questions, both, emerging and predetermined approaches, and both, qualitative and quantitative data analysis Research practices Positions researcher within the context Collects participant-generate meanings Focuses on a single concept or phenomenon Brings personal values into the study Studies the context or setting of participants Validates the accuracy of findings Interprets the data Creates an agenda for change or reform Involves researcher in collaborating…