6-12 Public Management

This response paper is over Chapters 6-12, of Research Methods in Public Administration and Public Management: an introduction, by Sandra Van Thiel (2014). The following is a comprehensive review of the chapters with added information. Dependent on the type of questions a researcher has and the strategy that will be used. The study can use many methods to gather the information that is needed to answer the questions the researcher has. One method is utilizing experiments as defined by Merriam Webster (2016) it is “a scientific test in which you perform a series of actions and carefully observe their effects in order to learn about something”. A researcher in emergency and disaster management (EM), could run many types of experiments to try to mitigate the results of a disaster. One type of experiment is the classic experiment, the classic experiment also referred to as a pure experiment, takes place in some type of controlled environment, where there would not be any influence from outside sources. Subjects of the experiment are usually divided into two groups one group would be considered the control group and the other the experimental group. An example of a pure experiment could be testing which way the public would be more receptive to learning EM and response information, in a video or by computer based training (CBT), both groups would have the exact same information and testing method. The researcher would run multiple test to quantify the information. Another type of experimental technique is simulations and gaming. This is similar to the pure experiment in many ways, except it usually does not have a control group and experimental group. One example of this method could be running a computer simulation on the effects of new type of barrier material used to reroute flood waters. Another example would be testing a new microorganism to clean up oil or other contaminants in a controlled environment. A field experiment is a different type of research method, these are “experiments that are conducted outside the laboratory or in the empirical world” (Thiel, 2014, p. 67). Therefore field experiments differ from the previous mentioned in one main aspect they do not take place in a controlled environment, such as a laboratory. An example of this method would be researching what are the effects to a shore line after a hurricane subsides. As stated “the main advantage of choosing the research strategy of the experiment is the high level of control that it offers over the research situation” (Thiel, 2014, p. 68), this is also a disadvantage, because it is not tested in a real world setting due to all the controls and limitations of a laboratory. A part of the experimental strategy is observation, the researcher can choose to be part of the experiment or detach themselves, a hidden observer thus there is no interaction with the participants of the experiment. A researcher could get more data by participating in the study, with that said, as a participant observer they need to ensure they don’t get to involved or drawn in to the study. If the researcher gets too involved they could lose objectivity and a role conflict may arise, thus possibly voiding the results of the experiment. Another strategy in research is conducting a survey, this is one of the most well-known forms of gathering information. A survey is a series of questions poised …show more content…
Two types of data analysis discussed in the chapters reviewed for this report where quantitative and qualitative data. As stated “quantitative data are always numerical in kind” (Thiel, 2014, p. 118). As an example a numerical value can be assigned to answers to questions during a survey these answers can then be sorted numerically to show the most popular answer. Qualitative data on the other hand are “non-numerical units of information” (Thiel, 2014, p. 138), these consists of data such as periodicals, photos or even interviews. Both quantitative and qualitative are similar in the fact they use the same basic structure of data collection, ordering and analysis. They differ in the sense that quantitative data can be easily arranged in a hierarchical structure, contrary to qualitative data that does not have an easily seen structure. Neither one of these types of data analysis is better than the other, it is the preference of the researcher and/or the type of study being