Deductive and Inductive Research Methods - Essay Example

Research Methods and Strategies Both deductive and inductive research can yield valuable data about research questions and objectives. Each method has strengths and weaknesses which make them appropriate for use in certain situations. Both approaches may be used in different phases of the same study, depending on what is required. Deductive Research The deductive approach is considered to be a "top-down" approach in research. Deductive reasoning starts with a hypothesis of the topic of interest, which is then narrowed down to a more specific hypothesis. As the subject is further refined, the research begins to focus on a population in which one would reasonably expect to find the required evidence. The effect of this is that the focus of the research moves from theory to data. The deductive approach is also a descriptive approach in that it describes facts and illustrates theories. Deductive research is often applied to questionnaires and the collection of quantitative data which addresses the hypothesis. There are several advantages to deductive reasoning. It is a relatively simply research method to standardise, as it is a highly structured approach based on scientific principles. Furthermore the structured approach means that the researcher does not necessarily need to be highly knowledgeable about the research topic. Most managers are familiar with the deductive approach and therefore are much more likely to put faith in conclusions that are made using it. In addition it is a quick method of gaining data, as the time-consuming aspects of this type of research are mainly in the set-up and data collection phases. This also means that the amount of time needed to invest in the research can be scheduled and predicted relatively easily. All of these things make deductive research low risk in comparison to inductive research. There are also a number of concerns with this approach. Firstly it is important that causal relationships between all variables in the research are explained and defined. Selecting samples of sufficient size is a crucial factor in determining the success of this type of research. The sample must be large enough to generate accurate conclusions that are reliable in all applications of the data. A significant issue with deductive research is in clearly defining abstract concepts. Taking the example of employee morale, it must be defined in terms of level of satisfaction of employees, which is a personal concept and may mean different things to different people. Conducting this type of research means that concepts must be clearly defined to enable accurate responses from research subjects. Lastly, controls must be applied to ensure the validity of the data gained from the research. If the research was in defining levels of employee satisfaction in a particular department, reasons for high or low employee moral must be established. For example, the data taken from employees may indicate a relationship between workload and employee salary. This data can then be used to refine the hypothesis of a relationship between workload, employee salary, and morale, and then collect new data for analysis. This may include input from different departments, both to increase sample size and to note the effects of varying workloads or salaries in different departments. This ensures the accuracy of the hypothesis because it takes into account variation of these aspects in different departments. A larger sample size allows further refinement of the hypothesis - for example it may narrow down the hypothesis to focus on young employees, and allow the researcher to pinpoint different effects of low or high morale, such as absenteeism. In this way, an initial hypothesis focusing simply on employee morale can be progressively refined to pinpoint causal relationships that become evident as the focus of the research narrows. One of the main disadvantages of this type of research is that it relies on subjects to fill and return questionnaires, which may become more difficult to do as sample size increases. In addition, the methodology of such research tends to be too inflexible to permit analysis of alternative explanations - if the hypothesis is found to be false, then an entirely new hypothesis must be formed, and new research carried out. Inductive Research The inductive approach works in the opposite direction to deductive research, as it is considered a "bottom-up" approach in the way it is applied. The inductive approach usually requires the researcher to have a good understanding of the context of the research, and an understanding of the meaning humans may attach to events. Face-to-face interviews are essential to the research and gaining qualitative data is the primary focus. The inductive approach provides a number of advantages over deductive research. Inductive research tends to have a more flexible structure, and more easily allows changes in the focus of research. In addition, the researcher is part of the research process, which enables the process of gathering data to be more dynamic and interactive. Because the focus is on qualitative rather than quantitative data, there is less concern with the need to produce generalised conclusions, and the research has a wider focus which enables the researcher to see a bigger overall picture of causal relationships between variables. The main disadvantage of this type of research is that studies based on inductive research tend to be lengthier, as data collection and analysis is often carried out over an extended period. This means that the big picture often emerges only gradually. Because of this it can be some time into the study before any useful data patterns emerge. An inductive approach might involve entering several different departments, and interviewing employees and supervisors about their work experiences and attitudes. This would enable researchers to understand problems on the level of the individual. Their task then would be to analyse the data and formulate a theory based on it. This approach allows for the possibility that there may be less obvious influences on staff morale which may not be related to things like workload or salary. Research Strategies Research strategy is about developing an approach that can be used to answer a specific set of research questions. Valid reasons must be clearly demonstrated for the research strategy that is chosen, for the questions that are asked, and for the subjects that are chosen for study. A good research strategy may use more than one type of research method but care must be taken to ensure that strategies chosen are appropriate for the research questions and objectives that are involved. Surveys: these are usually associated with the deductive approach. Surveys are a popular and common strategy in business and management research, because they can be done independently, and they allow large amounts of data to be collected in a highly economical way. Survey data is normally obtained through use of a questionnaire. Data obtained in this way is standardised, and easy to compare and understand. The main limitations of surveys are that they can be time-consuming to organise and analyse, and addition that the number of questions must be limited to ensure that the goodwill of participants is not taken advantage of, hence limiting the scope of the survey. Ethnography: this is a time-consuming process which needs to be flexible and responsive to change, since the researcher is constantly developing new theories and patterns of thought about what they are observing. Ethnography is usually used by sociologists or anthropologists to study culture and society. Action Research: this focuses on first on gathering information and then on action and change within the organisation. As Coghlan and Brannick (2001) note: "the purpose of research and discourse is not just to describe, understand and explain the world but also to change it". The researcher is involved in application of the knowledge gained to implement change within the company. Employee involvement throughout the process is important, as they are more likely to apply changes they have helped to create. Once employees have identified a need for change and have widely shared this need it becomes difficult to ignore, and the pressure for change comes from within the organisation. Practitioner-Researcher: when the researcher also works within the company, they have a significant advantage in having knowledge of the organisation and being able to understand the complexity of how it functions as a unit. This in itself is also a disadvantage however as it can lead to assumptions and preconceptions when analysing data and forming theories. Care must also be taken to ensure that data-gathering is not inhibited when working with senior colleagues. Combining two different roles at work can also be very demanding not only in terms of time spent on the research. Case Studies: these are used to demonstrate how specific situations are identified and resolved, and the outcome of the resolution. Case studies organize information about a particular case, which can be analyzed by itself and through comparison with other cases. Grounded Theory: this involves collecting data by a variety of means, including interviews, observation, and conversation. Via constant comparison of the data, the key issues are noted and re-evaluated as more data is gathered, until a theory is formed. Structured Observation: is most frequently associated with organisation and methods research, and involves structured interviews. Cross-sectional and longitudinal studies: used to determine if conditions change over time within a given sample. Using Multiple Methods Various research methods can be used in conjunction with each other, and it is often beneficial to do for. Each type of method is particularly useful for carrying out different purposes within a larger study. For example, a general survey could be used to gather initial data, followed by interviews to narrow in on key issues that are raised by the survey results. The use of multiple methods also allows triangulation to take place, to ensure that the story the data is telling is an accurate one. Each method, tool or technique has its unique strengths and weakness (Smith 1975), and there is a relationship between the data collection method used and the results obtained. Since all different methods will have different effects, it makes sense to use different methods to cancel out the 'method effect'. This allows more accurate conclusions to be reached. Questionnaires "Questionnaire" is a general term which includes all data collection techniques in which subjects are asked to respond to the same set of question in a predetermined order. (deVaus, 2002) It includes structured interview and telephone questionnaires as well as written surveys. Questionnaires are useful certain standardised questions that can be interpreted confidently in the same way by all respondents. (Robson, 2002) Questionnaires can be classified into two categories: structured questionnaires that involves fixed questions with no variation and pre-coded response choices (such as online, postal, delivery and collection, telephone survey), and semi-questionnaires that are defined by a more flexible interaction with respondents (such as an interview schedule). Both types should always link back to research questions and objectives. Structured Questionnaires have an unambiguous approach which enables easy collection and analysis of quantitative data. This allows large numbers of respondents to be surveyed at once, making data collection economical and relatively simple. However, the pre-coded responses in structured questionnaires means that some respondents may be "forced" to choose inappropriate responses that do not entirely reflect their opinions. Structured questionnaires are intended to provide options for all respondents but this is not always possible, leading to errors in data collection. There is also scope for bias as respondents may sometimes desire to present a particular image in the answers they choose. Interviews allow for a better understanding of the context of the data and a more flexible interaction with subjects. More complicated and deeper questions can be asked, and more information and in-depth understanding can be obtained. In addition, inconsistencies and misinterpretations can be avoided, as clarification can be asked for by either party when it is required. Response rate is generally higher than with other questionnaire methods (such as postal or telephone). Open-ended questions can be used with well-trained interviewers during pilot studies to specifically target complex or unknown issues. Computer-assisted Questionnaires allow respondents to type in their answers on a computer screen. Inputting each answer prompts the display of the next question in the series. These can be very costly and time-consuming, and there is possible bias in conducting the data collection. A well-trained data analyst is essential to reduce potential bias. If both structured and semi-structured interviews are well-designed, highly accurate data can be obtained. Read More