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Activity 9 Prepare applied research strategy and hypothesis Once you have chosen your research topic or subject, you will need to decide how you will approach the research process – by formulating a hypothesis or developing a research question. This can be determined by starting with the following questions. Is there a significant body of knowledge already available about your subject that allows you to make a prediction about the results of your study before you begin? If so, you will be using a hypothesis. Or is your research more exploratory and investigative in nature and will require that you collect data and analyze results before drawing any conclusions? If this describes your research topic, you will be developing a research question. Understanding this difference and choosing the correct approach will drive the rest of your research project. The following sections further describe research questions and hypotheses and provide examples of each19 . 19 Source: Center for Innovation in Research and Teaching, as at https://cirt.gcu.edu/research/developmentresources/research_ready/quantresearch/question_hypoth, as on 12th March, 2018. 152 | P a g e
Research Questions: Used to analyze and investigate a topic. It is written as a question and is inquisitive in nature. A properly written question will be clear and concise. It should contain the topic being studied (purpose), the variable(s), and the population. Three main types of questions: o Causal Questions – Compares two or more phenomena and determines if a relationship exists. Often called relationship research questions. Example: Does the amount of calcium in the diet of elementary school children effect the number of cavities they have per year? o Descriptive Questions – Seek to describe a phenomena and often study “how much”, “how often”, or “what is the change”. Example: How often do college-aged students use Twitter? o Comparative Questions – Aim to examine the difference between two or more groups in relation to one or more variables. The questions often begin with “What is the difference in...”. Example: What is the difference in caloric intake of high school girls and boys? The type of research question will influence the research design. Once data has been collected, it will be analyzed and conclusions can be made. Hypothesis: It is predictive in nature and typically used when significant knowledge already exists on the subject which allows the prediction to be made. Data is then collected, analyzed, and used to support or negate the hypothesis, arriving at a definite conclusion at the end of the research. It is always written as a statement and should be developed before any data is collected. A complete hypothesis should include: the variables, the population, and the predicted relationship between the variables. Commonly used in quantitative research, but not qualitative research which often seeks answers to open-ended questions. Examples: A company wellness program will decrease the number sick days claimed by employees. Consuming vitamin C supplements will reduce the incidence of the common cold in teenagers. Develop a Research Strategy20 With your topic narrowed down and focused and your research questions developed, you are ready to dive into the bulk of your research; first, create a research plan, and develop a research strategy. Your strategy should involve answering three questions to shape your research, creating a plan timetable, preliminary outline and research log. Research strategy question #1: What amount of research do you need? 20 Source: Write, as at http://www.write.com/writing-guides/research-writing/research-process/making-aresearch-plan-how-to-develop-a-research-strategy/, as on 12th March, 2018. 153 | P a g e
To answer this research strategy question, you must take the following into consideration: The required length of the research paper The number of sources required Most likely, there are a minimum number of sources you are required to use, but if not, you can determine that based off other particulars of the assignment. Research strategy question #2: What types of sources are appropriate for your topic? The types of sources are primarily determined by your instructor and the assignment itself, but if you are granted some leeway on topic and source selection, consider these types of sources: Primary Secondary Current Historical Scholarly Popular Research strategy question #3: What types of materials are you permitted or required to use? Your organisation may specifically require certain types of research materials or may restrict your use of others. Make sure you understand what is and is not permitted. Establish a timetable for your research plan Once you have asked the three research strategy questions, establish a timeline. The biggest consideration is the due date of your research paper. This sets the pace for how quickly you conduct research to continue working through the research writing process. Use these guidelines when creating a timeline: Allow adequate time to conduct thorough research Start as soon as possible to eliminate stress that is likely to build at the last minute Remember that researching well and finding the right sources of information takes time Create a preliminary outline Once you have established a timeline, create a preliminary outline. Think about and decide on the main points you intend to cover and which answer your research question(s). Take those points, and organize them in a loose order. Nothing is set in stone at this point. In fact, your preliminary outline is likely to change many times, but at the beginning it helps you keep your research structured and focused. 154 | P a g e
Keep a log of your research in a journal With a preliminary outline in hand, you are ready to start researching. As you do so, start and keep a research log. Any spiral notebook or journal-style notebook is suitable. Index cards or files on your computer work just as well, too. This step of structured research corresponds with your note-taking methods and strategies. However, in addition to the information you record while note-taking, you also want to keep a record of the following: Your ideas Relevant keywords Questions you develop as a result of further research Keywords that generated successful searches, including the search tool used As you work through sources of information, remember to evaluate sources as an ongoing process. If you follow the research plan you put in place, you are more likely to conduct thorough, structured research that only strengthens your research. It can quite difficult to isolate a testable hypothesis after all of the research and study. The best way is to adopt a three-step hypothesis; this will help you to narrow things down, and is the most foolproof guide to how to write a hypothesis. Step one is to think of a general hypothesis, including everything that you have observed and reviewed during the information gathering stage of any research design. This stage is often called developing the research problem. An Example of How to Write a Hypothesis A worker on a fish-farm notices that his trout seem to have more fish lice in the summer, when the water levels are low, and wants to find out why. His research leads him to believe that the amount of oxygen is the reason - fish that are oxygen stressed tend to be more susceptible to disease and parasites. He proposes a general hypothesis. “Water levels affect the amount of lice suffered by rainbow trout.” This is a good general hypothesis, but it gives no guide to how to design the research or experiment. The hypothesis must be refined to give a little direction. “Rainbow trout suffer more lice when water levels are low.” Now there is some directionality, but the hypothesis is not really testable, so 155 | P a g e
the final stage is to design an experiment around which research can be designed, i.e. a testable hypothesis. “Rainbow trout suffer more lice in low water conditions because there is less oxygen in the water.” This is a testable hypothesis - he has established variables, and by measuring the amount of oxygen in the water, eliminating other controlled variables, such as temperature, he can see if there is a correlation against the number of lice on the fish. This is an example of how a gradual focusing of research helps to define how to write a hypothesis. The Next Stage - What to Do with the Hypothesis Once you have your hypothesis, the next stage is to design the experiment, allowing a statistical analysis of data, and allowing you to test your hypothesis. The statistical analysis will allow you to reject either the null or the alternative hypothesis. If the alternative is rejected, then you need to go back and refine the initial hypothesis or design a completely new research program. Generate a Research Hypothesis After choosing a research question, the next step is to formulate a research hypothesis (plural: hypotheses). A research hypothesis is a tentative answer to the research question. That is, after reading previous research studies, researchers predict in advance what they think the outcome of a research study will be. This may seem silly at first-why try to answer the question beforehand? Why not simply conduct the study to learn the answer to the research question? Researchers form hypotheses "tentative answers for a research question" because the hypothesis will influence how the research study is conducted. As you'll see in later sections, there are many methods researchers use to answer research questions. Which method a researcher chooses will also depend on the hypothesis, i.e. the answer a researcher aims to find. Scientists use theories as they develop their research hypotheses. Therefore, in this section, we first address theories, and then focus on how to develop a hypothesis. What are theories? < Explanations for why people behave the way they do; coherent and logical frameworks that guide research 156 | P a g e
Theories are explanations about how nature works. Business researchers propose theories about the nature of how organizations and people function and reasons why people (and organizations) behave the way they do. In business research, the theories used are often derived from theories in other disciplines. For example, psychological theories, such as theory of planned behaviour, are often used to explain issues in organizational behaviour. Network theories, originally developed by sociologists, explain how the structure of relationships between different people affect their behaviour and have successfully applied to investigate which relationships companies form and maintain, and why they do so. Economic theories in industrial organization form the base for many considerations in strategic management, such as the framework of competitive advantage proposed by Porter. A good theory has to accomplish several things. First, a theory needs to define and describe the events or phenomena it seeks to explain, and predict when we can expect certain behaviours or events to occur. Finally, theories must explain the causes of events described in the theory. These predictions and explanations are tested in research studies. The process of developing and testing theories follows these steps: 1. Theorists develop their ideas by reviewing all the research evidence for a particular phenomenon or behaviour. 2. They attempt to organize this evidence into a coherent and logical framework that explains the phenomenon. 3. Using this theory, new ideas and hypotheses are developed to guide the next research projects in an area. 4. These new research studies help to refine the theory. 5. The end result is a greater understanding of human behaviour and mental processes. A hypothesis is an assumption or suggested explanation about how two or more variables are related. It is a crucial step in the scientific method and, therefore, a vital aspect of all scientific research. There are no definitive guidelines for the production of new hypotheses. The history of science is filled with stories of scientists claiming a flash of inspiration, or a hunch, which then motivated them to look for evidence to support or refute the idea21 . 21 Source: Lumen Learning, as at https://courses.lumenlearning.com/boundless-sociology/chapter/theresearch-process/, as on 12th March, 2018. 157 | P a g e
The Scientific Method is an Essential Tool in Research: This image lists the various stages of the scientific method. While there is no single way to develop a hypothesis, a useful hypothesis will use deductive reasoning to make predictions that can be experimentally assessed. If results contradict the predictions, then the hypothesis under examination is incorrect or incomplete and must be revised or abandoned. If results confirm the predictions, then the hypothesis might be correct but is still subject to further testing. Both quantitative and qualitative research involve formulating a hypothesis to address the research problem. A hypothesis will generally provide a causal explanation or propose some association between two variables. Variables are measurable phenomena whose values can change under different conditions. For example, if the hypothesis is a causal explanation, it will involve at least one dependent variable and one independent variable. In research, independent variables are the cause of the change. The dependent variable is the effect, or thing that is changed. In other words, the value of a dependent variable depends on the value of the independent variable. Of course, this assumes that there is an actual relationship between the two variables. If there is no relationship, then the value of the dependent variable does not depend on the value of the independent variable. What is a research hypothesis? < Simpler, more tentative explanation that can be tested 158 | P a g e
A research hypothesis is simpler and more tentative than a theory. That is, any particular hypothesis may represent only a small part of the theory. Several criteria determine whether a hypothesis is testable (i.e., can be investigated in a research study). First, the concepts addressed by the hypothesis must be clearly defined and measurable. Hypotheses cannot be tested if they are circular. A circular hypothesis occurs when an event itself becomes an explanation for the event. We can find circular hypotheses on many talk shows and in our everyday conversations. For example, to say "The company Biosyns files for many patents … because it is innovative" is circular. Because being innovative can be defined by the number of patents filed, this hypothesis doesn't explain anything. It offers no more than saying, "Biosyns is innovative because it is innovative." A good hypothesis avoids this type of circularity. Finally, research hypotheses must refer to concepts that can be studied scientifically. To say that a company’s aggressive strategies are caused by the devil isn't a testable hypothesis because this hypothesis refers to a concept (the devil) that isn't in the province of science. Science deals with what can be observed; this is the basis for empirical observation. How can I come up with a research hypothesis? < Read research studies, consider personal experiences, think of exceptions and inconsistencies There are many ways to generate a research hypothesis. After reading research studies related to your research question, you may consider whether your personal experiences match what is described by the theories and past research. You may also "brainstorm" to think of "exceptions to the rule." That is, a theory or past research may describe only specific situations; you may think of conditions in which the theory may not apply. As you continue to read research articles, you will find inconsistencies or disagreements among researchers. In all of these situations, you may think of explanations for the discrepancies among previous research articles, and why the theories and research may differ from your own experience. These explanations become fruitful research hypotheses. Our next step in the research process is to look at the theories that influenced the thinking of the role of social networks in the decision to start a business and the hypothesis they generated. Also, we will ask you to think of a hypothesis for this research. 159 | P a g e
Which theories guided the research. A central theoretical consideration comes from the well-known paper “Economic action, social structure and embeddedness” by Mark Granovetter published 1985 in the American Journal of Sociology. The main thought of the paper is that how people are related with others will influence their behaviour and that this idea also extends to business companies, i.e. the relationship companies have with each other will influence the decisions and choices made. It should be noted that this thought challenges the neo-classical economic assumption that economic actors are anonymous. Following this paper, other scholars have further investigated the phenomena of social embeddedness and networks. Most notably, James Coleman analysed the relationship between actions and relations and structures of actions in his book “Foundations of Social Theory” published in 1990, while Ronald Burt introduced ‘structural holes’ as a new concept in network research in his book “Structural Holes” published in 1992. We built our research on this stream. The work of Coleman and Burt suggests that dense networks as well as loose networks have beneficial effects. Departing from this, we theorize that one should look not only at the overall network structure or social embeddedness, but rather should start to look at the specific relationships and what characterizes them. Thus, we argue that a network is not sufficiently captured by its structure but also needs to account for characteristics of the individual relationships. What hypothesis did we test in our research project? In one of our studies we derived the following three grand hypotheses. • Potential business starters with personal networks characterized by (a) many ties (b) more diverse ties and (c) a large share of ties to other self-employed possess more relevant social capital and are therefore more likely to start a business. • Potential business starters with personal networks characterized by (a) a high network homogeneity (b) a high share of closed ties, and (c) a high share of old ties increase the quality of resources they can access and are therefore more likely to start a business. • The larger the proportion of weak ties that are also old or close, in a network, the higher the chances are to start a business. 160 | P a g e
What hypothesis would you develop? A first step in developing a hypothesis is to see how ideas match your experience. Ask yourself these questions: • Do you often use network contacts to get things done? • What can you ask from different people in your network? On what does it depend what you can ask for and whether they will provide it willingly? An important step in developing hypotheses is to know the findings from previous research. Generate a Research Hypothesis A central component of the research process is the hypothesis. Ask yourself these questions when you read or hear about research to evaluate the researcher's hypothesis: • Does the researcher present a theory about the phenomena that are investigated? • Does the theory define and describe events, predict when specific phenomena or events should occur, and explain the causes of events described in the theory? • Is a research hypothesis presented? • Is the hypothesis testable? That is, are the concepts clearly defined and measurable; does the hypothesis avoid circularity; does the hypothesis refer to concepts that are scientific? • Is the hypothesis very general or very specific? (Specific hypotheses provide better tests of theories.) 161 | P a g e
Activity 10 Provide 2 examples of a research hypothesis. 162 | P a g e
Activity 10 163 | P a g e
Activity 10 Strong hypotheses22: Give insight into the proposed research question; Are measurable and testable; Are developed directly from the experiences of the researcher; Should be concise, as a rule, no more than three hypotheses should be proposed for any given project; There should be a well-founded rationale for all proposed hypotheses. o Why did you make these predictions? o Why are they important? o Provide alternative possibilities for the hypotheses that could be tested. o Why did you choose the ones you did over others? You might find it helpful to consult a statistician once your research questions and corresponding hypotheses are finalized to discuss experimental design, data collection, and statistical analyses. Ultimately, the success and quality of research is a direct product of the amount of time and effort invested in the development of your research ideas. Thorough planning and design will help facilitate data acquisition and analysis and help alleviate research stress during the next phase of the research process. 22 Source: Armed with Science, as at http://science.dodlive.mil/2010/10/04/defining-the-beginningimportance-of-research-questions-hypotheses/, as on 12th March, 2018. 164 | P a g e
Research Process Hierarchy: Tips for Formulating a Research Question and Study Design (Image: U.S. Army Institute of Surgical Research) Business Research Key Considerations to Design Your Research Approach23 Good business research is about collecting the information you really need, when you need it, to answer important questions and make important business decisions. What is the key to doing good business research? To make the best use of your time, get the information you really need, and make the best business decision, consider the following key questions before doing your research: 1. Why am I doing this research? What important decision am I trying to make? Always have an important decision in mind when you are doing your research. You are too busy to waste time collecting information to help make a decision that is not vital to your business, or worse yet – collecting information with no purpose in mind. With a clear decision in mind, you will be able to keep your research focused. 2. When do I need to make my decision? Timing is everything in business. Having 60% of the questions answered in time to make your decision is better than having 100% of the answers after the deadline’s passed. But on the other hand, if your important decision really can wait, there’s no sense in rushing into things and acting on less information that 23 Source: management Help, as at https://managementhelp.org/businessresearch/planning.htm, as on 14th March, 2018. 165 | P a g e
you might have been able to get if you had taken your time. So you need to have a clear sense of when you need to make your important decision. 3. What questions do I really need to answer to make my decision? What information do I really need to answer my questions? This is where many people get lost in their research. What do you really need to know to be able to make your business decision? Do you need to know a little about a bunch of things, or a lot about a few things? What kind of information do you need? Numbers? Opinions? And how much is enough? (A good rule of thumb is, the more important the decision, the better the information you should collect.) How you answer these questions will have a big impact on where you are going to have to go to get your information, and how you are going to get it. 4. Where is the best place (and who are the best people) to get the information I really need? Overall, information sources can be broken down into two kinds: primary and secondary. Primary sources are those people and organizations in your marketplace, for example, your potential customers, suppliers, and competitors. Secondary sources are reports, articles, and statistics about the people in your marketplace. While there are exceptions, it is usually safe to start with your secondary sources, because the information’s usually readily available at low or no cost. Once you have gotten what you can from the secondary sources, ask yourself the question, “Do I really need more information to make my decision?” If you really do, turn your attention to your primary information sources to get the last vital pieces of information you need. But often you can get what you really need from secondary sources. The real challenge for you with secondary information sources is not having too little information. You will likely be faced with a large amount of information for any decision. The real challenge will be to selectively pick the best from what is available. And it is always a good idea to use at least two good sources of information for any decision, and to make sure that these different sources agree with each other. If you have done things right up to this point, selecting your sources – primary and secondary – should not be too hard. You will know what decision you are trying to make and when you need to make it, and you will know what information you really need to make that decision. And if you can explain this to the reference librarian at your local library, they will get you pointed in the right direction. It is worth noting that many people go “researching” way before they really know what they are researching – and they waste a lot of time in the process. 5. What options do I have to collect that information? 166 | P a g e
With secondary information sources, collection is straightforward. You go to the source (library, resource center or website) and ask for the information. With primary information sources, deciding upon the right method is a little more involved. When considering your options, always remember to keep your business decision, timing and the information you really need clearly in your mind. These will help you to make the best decision. 6. What resources do I have to collect that information? Who or what can help me? You are almost ready to go out and do your research. One final consideration is about the resources you have, or have access to. These resources can include: The time you are willing to commit Friends and family members who are willing and able to help you The money you are willing and able to spend Access to the internet, your trainer Other resource people in your community like the reference librarian at your local library 7. Given the time, options, and resources I have, what is the best way for me to get the information I need? Now it is time to make a decision about how you are going to do your research. This is not so much a separate step as it is something that will emerge as you go through the earlier steps. Still, it is good to stop and think it through one last time before you move forward. 8. What am I actually going to do and when? Okay – it is time to commit to a plan of action. Create a business research action plan to collect your thoughts. Frame a research strategy in consideration of available tools and resources Research Design A research design encompasses the methodology and procedure employed to conduct scientific research. Although procedures vary from one field of inquiry to another, identifiable features distinguish scientific inquiry from other methods of obtaining knowledge. In general, scientific researchers propose hypotheses as explanations of phenomena, and design research to test these hypotheses via predictions which can be derived from them. The design of a study defines the study type, research question and hypotheses, independent and dependent variables, and data collection methods. There are 167 | P a g e
many ways to classify research designs, but some examples include descriptive (case studies, surveys), correlational (observational study), semi-experimental (field experiment), experimental (with random assignment), review, and metaanalytic, among others. Another distinction can be made between quantitative methods and qualitative methods. Quantitative Methods Quantitative methods are generally useful when a researcher seeks to study large-scale patterns of behaviour, while qualitative methods are often more effective when dealing with interactions and relationships in detail. Quantitative methods of sociological research approach social phenomena from the perspective that they can be measured and quantified. For instance, socioeconomic status (often referred to by sociologists as SES) can be divided into different groups such as working-class, middle-class, and wealthy, and can be measured using any of a number of variables, such as income and educational attainment. Qualitative versus Quantitative Methods: These two researchers are debating the relative merits of using qualitative or quantitative methods to study social phenomena such as the learning processes of children. Qualitative Methods Qualitative methods are often used to develop a deeper understanding of a particular phenomenon. They also often deliberately give up on quantity, which is necessary for statistical analysis, in order to reach a greater depth in analysis of the phenomenon being studied. While quantitative methods involve experiments, surveys, secondary data analysis, and statistical analysis, qualitatively oriented sociologists tend to employ different methods of data collection and hypothesis testing, including participant observation, interviews, focus groups, content analysis, and historical comparison. Qualitative sociological research is often associated with an interpretive framework, which is more descriptive or narrative in its findings. In contrast to the scientific method, which follows the hypothesis-testing model in order to find generalizable results, the interpretive framework seeks to understand social worlds from the point of view of participants. Although sociologists often specialize in one approach, many sociologists use a complementary combination of design types and research methods in their research. Even in the same study a researcher may employ multiple methods. Defining research strategy in a research paper on business studies24 Sarantakos defined research method as “the theory of methods” (Sarantakos 2012; p. 465), or the way through which a researcher makes sense of the object 24 Source: Project Guru, as at https://www.projectguru.in/publications/research-strategy-business-studies/, as on 12th March, 2018. 168 | P a g e
of inquiry. Within research methodology, research strategy assumes as the “general plan of how the researcher will go about answering the research questions” (Saunders et al. 2009; p. 90). Research strategy is of seven types: 1. experiments, 2. surveys, 3. case studies, 4. ethnography, 5. grounded theory, 6. action research and 7. archival research. Research strategies based on inductive approach Action research is based on four themes wherein the first theme is to focus on purpose of research e.g. to study the implication of change within an organisation. Secondly, the role of researcher within the research study. Therefore, the researcher should involve in the change management process or is facing the implications of change within the case organisation. Thirdly, the process of diagnosing, planning and taking action is the central theme of this strategy. Final theme indicates that action research should have implications beyond the immediate research. Ethnography is rooted firmly in inductive approach. The purpose of this strategy is to describe and explain research subjects just the way it would provide a description or explanation to the subjects. This strategy is time consuming. Most of the studies in business perspectives avoid using this strategy. For example, one can apply ethnography to understand and interpret from the perspective of those involved in the process. Archival research is based on administrative records and documents as a source of data which can be both recent or historical. Data which is collected for different purposes is analysed to determine the implications of the same. For example, one can use the data of Olympic players of specific countries to study the pattern of medal over the years. Also one can draw comparisons on different parameters. Research strategies based on deductive approach Experiment was first applied to natural sciences with a purpose to study casual links. In other words to examine whether the change in independent variable induces change in dependent variable. The number of independent variables can be different. In a classic experiment, two or more groups are established with each group denoted as experimental group. For example, An experiment to evaluate customer satisfaction on a product based on the satisfaction level among different groups. This is possible by 169 | P a g e
subjecting the members of each group to try the product and define satisfaction on different parameters. Survey is associated with deductive approach. Most of the studies related to business and management adopt this strategy. Survey enables the researcher to collect huge amount of data from a sizeable target population. The data can be analysed using descriptive and inferential analysis tools. For example, level of employee satisfaction in an IT organisation is determined with a questionnaire. Research strategies based on mixed approach (deductive and inductive approach) Case study involves empirical investigation to study contemporary phenomenon using multiple sources of evidence (Robson, 2002). Case study is opposite to experimental strategy which is not bound to a context. It is most suitable when to gain in-depth insight of the research context. For example, one can adopt the case study strategy to study reasons which led to the fall of Nokia as a case example. Grounded theory is the best example to mixed approach where the emphasis is on theory building. This strategy is adopted to predict and explain a behaviour. In this strategy, the research initiates with the development of theoretical framework. New theories are developed on the basis of the theoretical framework. For example, one can study the impact of culture on eating behaviour in a particular city on the basis of theoretical underpinnings. This can be proven with respect to a specific case. Need for research strategy Research strategy enables the researcher to answer the research questions or the elementary questions which shapes the flow and structure of the study. Therefore, the necessity of deploring a research strategy is based on the aims and objectives of the study. As Saunders et al. (2009) has emphasised that the choice of research strategy is guided by research questions and objectives. Similarly the extent of existing knowledge, the availability of amount of time, as well as philosophical underpinnings are also important. For instance, to examine the degree of customer’s satisfaction from online shopping, then the strategy should be to employ survey or interview method. This method enables to record views of vast amount of customers (like 100 to 1000 or more respondents), engaged in online shopping. Similarly, by deploying interview method, one can personally collect varied and in-depth perspectives of e-customers and therefore analyze their degree of satisfaction acquired. 170 | P a g e
Selecting research strategy based on research approach Based on three different approaches of reasoning in a methodology, it is important to adopt a strategy. As mentioned above, some are applied to researches based on inductive strategy. Types of research strategy 171 | P a g e
Research methodology and different research approaches A research plan is crucial in understanding the aims and objectives of the study as it describes the proposed research’s principal elements: how and what will be researched. It is a broader term than research methods as it is broad and not specific (Punch and Punch, 2005). This consists of the following parts: Aim and objectives in clear and precise terms. Background of the study and its significance. Progress report. Preliminary studies. Research methodology. The research onion. (Source: Saunders, Philip and Thornhill, 2009) Research approaches Researches can be of any of the following approaches described as under: Qualitative study Qualitative study is also known as ethnographic research. It studies things in their natural settings, attempting to interpret them. It involves the studied use and collection of a variety of empirical materials- case study, personal experience, introspective, life story, interviews, observational history, interaction and visual texts (Denzin and Lincoln, 1994: 2). The major factors researchers keep in mind during this type of research are inductive reasoning, 172 | P a g e
development of hypotheses, attitudes, processes and beliefs of the people. However, the shortcomings of qualitative research are that it is broad, vague and inclusive (Merriam, 2009). Descriptive study Descriptive study, as the name suggests, describes the attitudes and behaviours observed during the investigation. This approaches in many ways converse of experimental research with respect to advantages and disadvantages. It takes place in a natural, real-life settings (Vander Steop and Johnson, 2008). The main aim of descriptive research is to discover new facts about a situation, people, activities or events, or the frequency with which certain events occur. Descriptive research can be conducted using a range of methods like surveys and correlation studies to explore the relationship between variables (Cormack, 2000, p. 213). Correlation study Correlation study is one where variables and parameters are related to one another and information is systematically integrated as theories begin to develop (Cohen et al, 2007; p. 16). The main interest in conducting a correlation study is to observe whether two or more variables covary and if so, to establish the directions, magnitudes and forms of the observed relationships (Border, 2006; p.99). In this type of research, there is no attempt to manipulate variables, but observe them as it is. Causal comparative study Casual comparative study typically involves comparing two groups on one dependent variable (Lodico et al, 2010). It is used to explore reasons behind existing differences between two or more groups. In this sense, it is quite similar to correlation research (Johnson, 2005). It serves as a bridge with descriptive and correlation designs on one end and the experimental designs yet to be considered on the other (Goodwin and Goodwin, 1995, p. 43). The investigation begins by noticing a difference within a set of people. Experimental study Experimental study is the easiest type of research. The research is distinguished by three main characteristics: calculation of an independent variable, the related variables are all held consistent and the calculation of independent variable is observed on the dependent variable. Review and evaluate a range of applied research methods, theories and data collection techniques 173 | P a g e
The research question, ethics, budget and time are all major considerations in any design. This is before looking at the statistics required, and studying the preferred methods for the individual scientific discipline25 . Every experimental design must make compromises and generalizations, so the researcher must try to minimize these, whilst remaining realistic. For ‘pure’ sciences, such as chemistry or astrophysics, experiments are quite easy to define and will, usually, be strictly quantitative. For biology, psychology and social sciences, there can be a huge variety of methods to choose from, and a researcher will have to justify their choice. Whilst slightly arbitrary, the best way to look at the various methods is in terms of ‘strength’. Experimental Research Methods The first method is the straightforward experiment, involving the standard practice of manipulating quantitative, independent variables to generate statistically analyzable data. Generally, the system of scientific measurements is interval or ratio based. When we talk about ‘scientific research methods’, this is what most people immediately think of, because it passes all of the definitions of ‘true science’. The researcher is accepting or refuting the null hypothesis. The results generated are analyzable and are used to test hypotheses, with statistics giving a clear and unambiguous picture. This research method is one of the most difficult, requiring rigorous design and a great deal of expense, especially for larger experiments. The other problem, where real life organisms are used, is that taking something out of its natural environment can seriously affect its behaviour. It is often argued that, in some fields of research, experimental research is ‘too’ accurate. It is also the biggest drain on time and resources, and is often impossible to perform for some fields, because of ethical considerations. The Tuskegee Syphilis Study was a prime example of experimental research that was fixated on results, and failed to take into account moral considerations. In other fields of study, which do not always have the luxury of definable and quantifiable variables - you need to use different research methods. These should attempt to fit all of the definitions of repeatability or falsifiability, although this is not always feasible. 25 Source: Explorable, as at https://explorable.com/different-research-methods, as on 13th March, 2018. 174 | P a g e
Opinion Based Research Methods Opinion based research methods generally involve designing an experiment and collecting quantitative data. For this type of research, the measurements are usually arbitrary, following the ordinal or interval type. Questionnaires are an effective way of quantifying data from a sample group, and testing emotions or preferences. This method is very cheap and easy, where budget is a problem, and gives an element of scale to opinion and emotion. These figures are arbitrary, but at least give a directional method of measuring intensity. Quantifying behaviour is another way of performing this research, with researchers often applying a ‘numerical scale’ to the type, or intensity, of behaviour. The Bandura Bobo Doll experiment and the Asch Experiment were examples of opinion based research. By definition, this experiment method must be used where emotions or behaviours are measured, as there is no other way of defining the variables. Whilst not as robust as experimental research, the methods can be replicated and the results falsified. Observational Research Methods Observational research is a group of different research methods where researchers try to observe a phenomenon without interfering too much. Observational research methods, such as the case study, are probably the furthest removed from the established scientific method. This type is looked down upon, by many scientists, as ‘quasi-experimental’ research, although this is usually an unfair criticism. Observational research tends to use nominal or ordinal scales of measurement. Observational research often has no clearly defined research problem, and questions may arise during the course of the study. For example, a researcher may notice unusual behavior and ask, ‘What is happening?’ or ‘Why?’ Observation is heavily used in social sciences, behavioural studies and anthropology, as a way of studying a group without affecting their behaviour. Whilst the experiment cannot be replicated or falsified, it still offers unique insights, and will advance human knowledge. Case studies are often used as a pre-cursor to more rigorous methods, and avoid the problem of the experiment environment affecting the behaviour of an organism. Observational research methods are useful when ethics are a problem. 175 | P a g e
In an ideal world, experimental research methods would be used for every type of research, fulfilling all of the requirements of falsifiability and generalization. However, ethics, time and budget are major factors, so any experimental design must make compromises. As long as a researcher recognizes and evaluates flaws in the design when choosing from different research methods, any of the scientific research methods are valid contributors to scientific knowledge. Identify differing research paradigms for business What is a paradigm? Try web-searching for the word “paradigm”. Is it only researchers and academics who use this term? Is it helpful – or could you find a better word which is less academic? Kuhn (1970) describes it as a cluster of beliefs, which guide researchers to decide what should be studied and how results should be interpreted. Saunders, Lewis and Thornhill cite research by Burrell and Morgan (1979 cited p112) which offers four paradigms for social sciences research, within which business research is just one type: Functionalist (problem-solving and rational approach to organizations) Interpretive (organizations only understood through perceptions of people about those organizations) Radical humanist (organizations are social arrangements and research is about changing them) Radical structuralist (organizations are a product of structural power relations, where conflict is inherent) These paradigms are held by the authors to be inconsistent with each other, in other words, if you hold one paradigm, you cannot also hold a different one. They therefore foster different research methods and focus on different areas for study. For example, a functionalist paradigm takes a classic survey approach to issues, which are thought to have objective reality. A climate survey of employees would be an example, made to assess something “real” how employees feel about working in an organization, and using a questionnaire with both quantitative and qualitative questions to gain descriptive responses about that “reality”. An interpretive paradigm uses a qualitative research method such as discourse analysis, unstructured interviews to investigate perceptions and constructions of reality by “actors” in organizations, i.e. employees, managers, shareholders etc. A radical humanist paradigm would suggest again a qualitative method but looks not necessarily at the perceptions of social actors in the organization but seeks to probe a deeper level of values and social definitions, which underpin the organization. A relevant method would be grounded theory, which looks for 176 | P a g e
theory through a structured method of investigation of what is said or written (inductive) and produces categories of idea, which can then be used to characterize, develop or change organizations. A radical structuralist paradigm may suggest a historical analysis of power in the organization, by developing case studies or seeking to symbolize transactions between actors in the organization, for example an analysis of employee relations over time. This is one attempt to pull together the ontological and epistemological debates about conducting social science research. It is the ontological and epistemological stance of the researcher which affect the methodology and specific methods they choose for their research. Does this make sense to you? We are talking about how you think about the world and the stuff you find in it; for example, whether you believe in objective truth, or whether you find all things subjective. What kind of status business organizations have, and the policies and plans and structures and cultures they develop. As researchers we have to develop a clear sense of how we understand the world so that we don’t make the mistake of thinking everyone else thinks about it the same way. We have to learn to be as objective as possible, to recognize when our assumptions and philosophies may cloud our thinking and try to dispel them for the purposes of research. Key differences between qualitative and quantitative research methods and how and why they may be mixed You can have integrated paradigms as just mentioned, but you can also have a mix of qualitatative data from a case study approach and the perspective of “grounded theory” (Glaser, B and Strauss, A 1967; Locke, K 2001; Strauss, A and Corbin, J 1998) and quantitative data from a subsequent survey. We will go into detail about grounded theory when we cover qualitative data analysis. For now, you should know that this approach is interpretive, as written and verbal data are collected and transcribed so that the texts can be fragmented into ideas, categories and themes by the researcher. So such a mix involves mixed methods as well as an integrated paradigm. Research approaches or strategies need to be seen as related but distinct from the actual methods used in research. Make sure you understand what methods are; for example: experiment, interview, survey, case study, action research, grounded theory, ethnography, archival research. This is by no means an exhaustive list of research methods, but it is a useful broad range to keep in mind at this stage. Why should a business researcher want to mix qualitative and quantitative research methods? 177 | P a g e
It is increasingly usual for business research to mix methods of data collection and analysis. This can be done by using different data collection methods which are all either quantitative or qualitative (e.g. web and paper survey, or interviews and focus groups) (a multi-method approach), or you can use both qualitative and quantitative data collection and analysis methods (e.g. survey and interview and action research) (a mixed method approach) . One of the reasons for this is “triangulation” where different methods of data collection and analysis will both enrich and confirm the picture you collect of a situation. Often survey results are used to map out a broad view of the research question, and to provide themes or areas for investigation in more depth through interview. Triangulation can also provide a check on findings from a particular method. It will also be important to decide whether research should take a point in time approach, i.e. look at a phenomenon (a new training course, induction process, technology, product launch) at a particular time from the perspectives of more than one person – this is cross-sectional research, or whether you have the opportunity to look at a phenomenon over a time period (for example tracking a new product from launch to maturity, looking at industry trends over time, or following cohorts of new employees through their employment over an extended period) – this is a longitudinal study. Most academic studies for qualifications tend to be cross-sectional as they are completed in a very limited time period. Longitudinal studies usually require external funding to protract the period of research. Activity 11 If you used a mixed method approach, what reasons would you give to justify this choice? 178 | P a g e
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Activity 11 Criteria of validity and reliability in the context of business research Reliability Another term for consistency or repeatability over time. Reliability is required of research studies. We must try to design research which is auditable i.e. 183 | P a g e
transparent and clear so that the reader can either undertake the same method themselves and produce the same results, or at least the method is clear enough to instill confidence in the reader that the results were not fudged in any way. (Triangulation will help here). Make sure you understand the concepts of participant error, participant bias, observer error and observer bias. Validity There are three main ways of characterizing validity in research studies. It is important that research methods have “face validity” and “construct validity” and “internal validity”. Face validity means effectively that the non-researcher or lay person can broadly see that this is a valid method of researching this question “on the face of it” it makes sense as a method. Face validity is important to encourage participation in surveys or interviews, as well as other experimental or research designs. We want to be able to answer the question “why do you want to know that?”. Construct validity is a more complex idea and means that the method must actually measure what you think it measures. There are, for example, statistical ways of checking surveys and questionnaires to check that the questions are really asking what you think (factor analysis and item response theory). Construct validity is particularly important in questionnaires which are not administered face to face by a researcher but sent by post, email on done online, as there is no chance then to discuss and clarify the meaning of a question. Sometimes results can be invalidated because respondents have misunderstood a question and answered in a way which was not intended. This is also referred to as “measurement” validity. We can illustrate this idea by the famous IQ test which was intended to measure intelligence (IQ stands for Intelligence Quotient) but includes items which bias towards particular ethnic groups and educational norms. Or we could ask the question, do examinations test knowledge? Is their measurement validity strong? Or do they actually test something else, for example examination technique? Internal validity relates to causality, i.e. does factor X cause factor Y to happen? It is sometimes easy to assume causality when in fact there is only association of two factors. For example, does strong motivation cause or lead to effective teamwork, or does effective teamwork lead to or cause strong motivation? In this case causality can work either way or may be quite independent concepts. We cannot assume causality either way. In business research it is easy to make assumptions about a factor (or “independent variable”) causing an effect (or “dependent variable). To test internal validity we have to ask the question, does the independent variable account completely for a change in a dependent variable, or are other factors affecting this outcome. Usually in business organizations, there are very few simple cause and effect relationships. Does a performance bonus make someone work harder? 184 | P a g e
Other kinds of validity which are sometimes talked about include: external validity (this is more often called generalisability, ie can we generalise the results of our study to other contexts or situations?) and ecological validity (this relates to whether the act of researching a situation itself has an effect on that situation; it may be that findings from a business research study are clear within the study, but when applied to a different “ecology” ie outside the research study in “real life”, they no longer apply). Your choice of research strategy or design A research design is a grand plan of approach to a research topic. It takes quite a lot of work and reading, as well as simply understanding your views as a researcher. For a start, there will be no one right way of conducting business research – this will depend on a number of factors such as research topic, audience for the research (you, your university tutor or your company for example), time and other resources available to you, and the kind of study which is considered appropriate for that topic. There will also be other practical considerations such as access to information and people. Suppose you wanted to investigate what shoppers thought about a particular marketing strategy associated with an organisation. Can you stand outside its shop and ask passers-by questions? From an academic perspective, it is never that simple. There are ethical issues (you would need permission from the retailer to stand outside accosting customers), practical issues (you may cause an obstruction or even a breach of the peace in a public place!), sampling issues (which ones do you talk to because you will have to make a choice), what language will you use for your questions (relevance to the interview subject, their ability to understand the questions), their motivation to respond (why should they? Do you offer an incentive? Will that affect results?) and how do you analyse the results (quantitative analysis of tick box answers? Textual analysis of their comments? Both? Record their body language as well?). And so on. Many of these questions are practical and detailed, but underpinning your approach there will be philosophical assumptions which you must make explicit. So, designing your research will be vital and choosing a strategy will mean you have considered your views on truth and knowledge, social entities, what business research can and cannot achieve and how all this will affect what you actually do to answer a research question. We have talked about the underpinning role of philosophy and research strategy, which then guides your choice of research method (e.g. survey, interview, grounded theory etc) and whether they should be mixed, i.e. both qualitative and quantitative. These questions need settling and justifying before you rush off to ask people questions. 185 | P a g e
Activity 12 Review the ideas of epistemology/ontology, research paradigms, validity and reliability, mixed and multi-methods and triangulation. How do all these relate to yourself as a researcher? 186 | P a g e
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Activity 12 Select appropriate methods to gather and analyse data Social scientists employ a range of methods in order to analyze a vast breadth of social phenomena. Many empirical forms of sociological research follow the scientific method. Scientific inquiry is generally intended to be as objective as possible in order to reduce the biased interpretations of results. Sampling and data collection are a key component of this process. It is important to determine the scope of a research project when developing the question. The choice of method often depends largely on what the researcher intends to investigate. For example, a researcher concerned with drawing a statistical generalization across an entire population may administer a survey questionnaire to a representative sample population. By contrast, a researcher who seeks full contextual understanding of the social actions of individuals may choose ethnographic participant observation or open-ended interviews. These two types of studies will yield different types of data. While quantitative research requires at least 30 subjects to be considered statistically significant, qualitative research generally takes a more in-depth approach to fewer subjects. 193 | P a g e
Collecting Data: Natural scientists collect data by measuring and recording a sample of the thing they’re studying, such as plants or soil. Similarly, sociologists must collect a sample of social information, often by surveying or interviewing a group of people. In both cases, it behoves the researcher to create a concrete list of goals for collecting data. For instance, a researcher might identify what characteristics should be represented in the subjects. Sampling can be used in both quantitative and qualitative research. In statistics and survey methodology, sampling is concerned with the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population. The stages of the sampling process are defining the population of interest, specifying the sampling frame, determining the sampling method and sample size, and sampling and data collecting. There are various types of samples. A probability sampling is one in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined. Nonprobability sampling is any sampling method where some elements of the population have no chance of selection or where the probability of selection can’t be accurately determined. Examples of types of samples include simple random samples, stratified samples, cluster samples, and convenience samples. Good data collection involves following the defined sampling process, keeping the data in time order, noting comments and other contextual events, and recording non-responses. Errors and biases can result in the data. Sampling errors and biases, such as selection bias and random sampling error, are induced 194 | P a g e
by the sample design. Non-sampling errors are other errors which can impact the results, caused by problems in data collection, processing, or sample design. How and why sampling relates to business research Problem 1: the world is large and full of people. To find out things about people we need to ask (research) them. We usually can’t ask all of them because the numbers make this impossible. So we ask some of them. We sample the population. Problem 2: we wanted to find out things about people, so we researched a sample of them. To what extent do our results relate to all people, and to what extent do they only relate to our sample? Problems 1 and 2 put sampling in a nutshell. Sampling is a practical way of studying people and their activities, thoughts, attitudes, abilities, relationships etc in relation to business. But because we are not asking everyone in the chosen “population” (which could be the members of a company, or all sales managers in the United States, or all applicants for a particular job – any group we define in relation to our research objective), then how can we have any certainty that our results can be representative of the whole population? The crunch is that we don’t want any old sample, we usually want a sample to be representative of a group (population). That would mean that our findings can be generalised to the whole group. To make this happen, we have to learn about a number of issues and technical words and phrases in sampling. In the next section there is a brief glossary based on Box 4.1 in Bryman and Bell (2003 p 93): A range of probability and non-probability sampling techniques The table below is a glossary of techniques and terms associated with sampling. 195 | P a g e
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Of all the sampling techniques included in the table, quota sampling and convenience sampling, to some extent snowball sampling, are the least “statistical” in nature. These techniques offer varying levels of generalisability but always less than a random sampling method. Think about these three techniques and decide how justified you think each is for conducting business research. Selecting appropriate techniques for different research studies When we are designing a research study, the most common question about sampling is – how large should the sample be? In the definitions of random sampling above, we have ignored this question so it is now time to tackle it. Unfortunately, there is no right answer to sample size. You cannot just apply a consistent proportion to the total sample frame. Instead the following issues need consideration: Absolute sample size: it is more important to look at the absolute size of a sample than its relative size in relation to the total population. Imagine 10% of a population as a possibly sensible sample. If the population total is 100,000, then your sample size is 10,000 – yes this would probably be a good sample size (but see the next problem on this list). However if we apply a 10% sample size to a population of 10, we have a sample of 1 unit or person. We can see that this unit or person could be quite unrepresentative of the total population by itself. So relative sample size is not important. Absolute size is. The bigger the sample size, the more the sample is likely to represent the population and the lower is likely to be the sampling error. (Referred to as the Law of Large Numbers). Statistics and the Central limit theorem: the larger the absolute size of a sample, the more closely its distribution will be to the “normal distribution” (What is this? If you have not done any work on statistics before, do some quick web-searching or look at the index of the textbook to find out). If you wish to conduct a statistical analysis on your data, the minimum size of sample for any one category of data should be 30, as this is most likely to offer a reasonable chance of normal distribution. If your sample frame is 30 or less, then it would be wise to include the whole frame, rather than sampling. 198 | P a g e
same as saying 95% certainty) is the maximum normally appropriate for rigorous research. If your population size was 50, you would have to include at least 44 of them to achieve a 95% certainty that the sample would represent charactistics of the population. A very high proportion of the population will be needed to achieve 99% certainty. There is a diminishing need for higher samples at the high population end of the table (the figures to achieve 95% certainty for a population of 1m are the same as for a population of 10m ). Time and cost: Bryman and Bell (2003 p101) suggest the law of diminishing returns kicks in at around a sample size of 1000 – i.e. that precision in the data increases up to a sample total of 1000, but then begins to decrease, making it less worthwhile to interview or survey more than 1000. Of course, the population you are researching may be way below 1000 in total, and it may in any case be very costly or timeconsuming to use a large sample size. Practical considerations are important in research studies. Just bear in mind that if you choose a sample size which is small in absolute terms, then you must justify this action and take into account the fall in generalisability and representativeness which may result. Non-response: this is described as normal in the glossary above. Inevitably your respondents are less likely to be as motivated as you, the researcher, about your research, so some – and sometimes a majority – will not respond, ie refuse to take part. On top of this, some of those who do respond may not produce “useable” data (e.g. you may find that a high proportion of questions in a survey are unanswered, or that some people or units in your sample frame have moved away, changed job, stopped functioning in the role you expected etc). All this is taken into consideration when a) choosing your sample size and b) calculating the actual response rate. Variation in the population: if the population you are studying is highly varied, then the sample size will need to be larger than if you are studying a population with less variation (eg people who have chosen to join a membership organisation). Assessing representativeness of samples and generalisability from samples Even if we use probability sampling techniques, we can only hope to produce generalisable outcomes in relation to the population we were sampling. So if all questionnaire respondents are chosen from one company or organisation, the best to hope for is that our results can be generalised to the whole workforce of that company or organisation. We cannot assume that these results will in fact describe other workforces, as very different conditions and variables may apply in other organisations. 199 | P a g e
In a similar way, we could conduct a large sample study by random sampling a country’s population based on official census statistics, and if the study was large and rigorous, we might propose conclusions, which apply to this country’s population (with a specified degree of confidence in the statistics). However, we cannot then apply these conclusions to other countries without further research, nor can we apply these conclusions over time to the same country, as major variables could have changed over time. Think back here to what we discussed earlier about epistemology – what we can really know. We find this kind of generalisation being made all the time in the media. For practical time and cost reasons, media production teams often take quota sampling research (or research done by more dubious methods) and suggest its applicability to everyone watching or listening to a programme. Look out for examples and try to find out what kind of sampling was applied to their research. Remember the ethics discussion about not causing “harm” – how does this relate to TV, radio or webcast research you come across? If you are worried about the representativeness of your sample, in some cases it may be possible to check this by using a test of statistical significant difference to compare the profile of characteristics in your sample with that of another data list eg a census or company database. Clearly if there is no statistically significant difference between your sample and the full population data list, you have added more authority to the representativeness of your sample. If you are using a non-probability sampling technique then even the flimsy size rules associated with probability sampling fall away. Your sample size for purposive or snowball sampling will really depend on your research questions and objectives. In qualitative research, the focus will not be on trying to estimate things about a population, but in trying to understand or relate the data to theory or ideas. How many people do you need to talk to, to understand their perception of something for example? It could be just one. Or it could be several or many. The question is here, what are you trying to find out and what sample size would give me confidence that my results had validity? We will go further into this when we discuss different qualitative methods, but often a good lead can be taken from research studies in peer-reviewed academic journals, where information has been given about sample size in relation to research question. Find one that is close to your area of study (which you would want to do anyway in your literature review) and check the sample size studied in this type of enquiry. 200 | P a g e