Field experiments offer significant strengths when compared to lab experiments. It offers a natural setting rather than an artificial lab setting. On the other hand, it is more difficult to control variables and, therefore, replicate the same conditions is very challenging. Additionally, and because it is difficult to control the environment, unanticipated actions can appear, which can adversely affect subjects and participants.
Therefore, it represents the behavior of real systems through the exercise of models. Simulation can be used to describe the behavior of the system, construct theories and hypotheses considering the observations made, or use the model to predict future behavior.
Simulation is an appropriate method to analyze complex and large practical problem, when it is not possible to model it previously using a mathematical model. Additionally, it can be used to compress a time frame, which is suitable to investigate quickly the effects of a change in a real life situation. However, the simulation also presents disadvantages, such as model building requires deep knowledge of the field and it can be time consuming and expensive.
It is one of the most used quantitative techniques, since it allows obtaining information about a given phenomenon, through the formulation of questions that reflect the opinions, perceptions and behaviors of a group of individuals.
Surveys offer several benefits. Two of those most important benefits include the high representativeness of the entire population and the low cost of the method when compared to other alternatives. On the other side, the reliability of survey data is very dependent on the survey structure and the accuracy of answers provided by the respondents. There is no manipulation of variables, but only an investigation of the extent to which the variables are related.
The strength and direction of the relationship are two characteristics highlighted by a correlational study. At the same, we can collect a wide range of information from many domains at one time and it is possible to study the interrelations among those variables.
However, correlation doesn't indicate causation, because the association between two variables could potentially be explained by a third variable.
The methods typically applied are included in the large group of descriptive statistics and inferential statistics. These techniques can be applied in a wide range of situations, such as market research, process optimization and quality control. Multivariate techniques allow researchers to explore relationships between variables using the most appropriate methods for each situation.
The statistical process to be adopted should be adjusted to suit the characteristics of the environment under analysis. However, these techniques are generally complex and require the use of specialized statistical software, which is generally expensive. Conclusion Scientific studies are fundamental to increase the horizons of theories and explain the phenomena of society.
Research methods are used for the development of scientific studies, which allow specific analysis according to the methodology employed by the researcher. The researcher is responsible to choose the research methodology that best suits the situation under analysis. Two methodologies of qualitative and quantitative nature stand out for their usefulness and wide acceptance in the scientific community.
Case studies, field research and focus group are the most adopted methods within the qualitative methodology. On the other hand, surveys and correlational studies are the most common methods to perform a quantitative research. The choice of method to be adopted should take into account the advantages and disadvantages of each method, and also the questions, specificities and the nature of the research study.
As future work, we intend to explore the potentialities and limitations of mixed methods research. The idea is to analyze the most promising qualitative and quantitative methods that could be used together to explore the strengths and mitigate the weaknesses of both quantitative and qualitative research. References 1. Acocella, I. The focus group in social research: advantages and disadvantages. Almeida, F. Approaches and principles for UX web experiences.
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Borrego, M. Quantitative, qualitative, and mixed research methods in engineering education. Journal of Engineering Education, 98 1 , Castellan, C. Quantitative and qualitative research: a view for clarity. International Journal of Education, 2 2 , Charmaz, K. Constructing grounded theory: a practical guide through qualitative analysis. London, United Kingdom: Sage. Choy, L. The strengths and weaknesses of research methodology: comparison and complimentary between qualitative and quantitative approaches.
Coughlan, M. Step-by-step guide to critiquing research. Part 1: quantitative research. British Journal of Nursing, 16 11 , Crescentini, A. Qualitative research articles: guidelines, suggestions and needs. Journal of Workplace Learning, 21 5 , Creswell, J.
Research design: qualitative, quantitative, and mixed methods approaches. Qualitative inquiry and research design: choosing among five approaches. Davies, M. Concept mapping, mind mapping and argument mapping: what are the differences and do they matter? Higher Education, 62 3 , Etikan, I. Comparison convenience sampling and purposive sampling.
American Journal of Theoretical and Applied Statistics, 5 1 , Flanagan, T. The scientific method and why it matters.
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Entries Per Page:. Methods Map Research Methods. Explore the Methods Map. Related Content. Back to Top. Why not five? Why not south and then east? He also had This easy-to-read book describes how Data General s engmeenng team some mistaken criteria for recognizing the Indies when he actuallyencoun- invented and developed the new computer.
The book begins with the initial tered them. In short, his exploration began with some rationale and direction conceptualization of the computer and ends when the engineering team relin- even if his initial assumptions might later have been proved wrong Wilford: quishes control of the machine to Data General's marketing staff. However, the book also exploratory case study. Is the case study about the minicomputer, or. Without such propositions, an investigator might he tempted to dynamics topiC.
Because the book is not an acadenuc study. For example, the proposi- to, nor does it. The more a study contains specific propoSItions, the more it will stay within feasible limits.
Case studies have been done about decisions, research design and data collection strategy. Beware of these types over another, your questions are probably either too vague or too numerous-- of topIcs-none IS easIly defined in tenns of the heginning or end points of and you may have trouble conducting your case study. Any case study of such a program would therefore have case studies of small groups for another example, confusIDg an IDnovauon to confront these conditions in delineating the unit of analysis.
OIY Smgapore,Is 10 fact a case study of Singapore's critical li' th The fourth and fifth components have been the least well developed in case make the cO,? Linking data to propositions can be done any number of ways, but none These two cases show how the definition of the main and embedded.
The main unit of analysis is likely at the level being addressed by the main study questions. One promising approach for case studies is the idea of "pattern-matching" described by Donald Campbell , whereby several pieces of information from the same case may be related to some theoretical proposition. To reduce the confusion, one good practice is to discuss the state law limiting the speed to 55 miles per hour.
If the two potential patterns are outsIde It the context for the case study Similarly I'fth. All of these types of questions need to be This article also illustrates the problems in dealing with the fifth compo- nent, the criteriafor interpreting a study'sfindings.
Campbell's data matched I 1 "-. This role of theory deVelopment, prior to the conduct of any actual obse Uons, data collection, is one point of difference between case studies and related Campbell, As a result, students - II "- IJ.
Figure 2. An Example of Pattern-Matching Theory development. Using a case study on the implementation of a new management information system MIS as an example Markus, , the one pattern much better than they matched the other. But how close does a simplest ingredient of a theory is a statement such as the following: match have.
Note that Campbell did not do any statistical test to make the comparison. Nor would a statistical test The case study will show why implemeniation only succeeded when the organi- have been possible, because each data point in the pattern was a single zation was able to re-structure itself, and not just overlay the new MIS on the number-the number of fatalities for that year-for which one could not old organizational structure.
Currently, there IS no precise way of setting the criteria for interpreting these types of findings,. The statement presents the nutshell of a theory of MIS implementation- One hopes that the different patterns are sufficiently contrasting that as in that is, that organizational restructuring is needed to make MIS implementa- Campbell's case the findings can be interpreted in terms of comparing at tion work.
Using the same case, an additional ingredient might be the following statement: Summary. A research design should include five components. Although the current state of the art does not provide detailed guidance on the last The case study will also show why the simple replacement of key persons was two, the complete research design should not only indicate what data are not sufficient for successful implementation.
Using a Metaphor to You can see that, as these two initial ingredients are elaborated, the stated Develop Deseriptive Theory ideas will increasingly cover the questions, propositions, units of analysis, logic connecting data to propositions, and criteria for interpreting the find- Whether four countries-the American colonies, Russia, England, and ings-that is, the five components of the needed research design.
In this sense, France-all underwent similar courses of events during their major political the complete research design embodies a "theory" of what is being studied. Tracing and analyzing these events IS don. The author If you are interested in international followed by a false tranquility, to describe the ebb and flow of events m the economic development, for instance, Peter Drucker's ''The Changed World four revolutions.
Economy" is an exceptional source of theories and hypotheses. Drucker claims that the world economy has changed significantly from the past. Nevertheless, as noted earher financial markets and the real economy of goods and services. Each different study would likely call for a successful. Drucker's theoretical framework would provide gUidance for designing these studies and even for collecting relevant data.
Illustrative types of theories. In general, to overcome the barriers to the- In other situations, the appropriate theory may be a descriptive theory see ory development, you should try tu prepare for your case study by? Ideas WIth col- realistic range of topics that might be considered a "complete" description of leagues or teachers; and asking yourself challengmg quesl10ns about what what is to be studied, and c the likely topic s that will be the essence of the you are studying, why you are proposing to do the study, and what you hope description.
Good answers to these questions, including the rationales under- to learn as a result of the study. For instance, n? Other types of theories for you to consider note. Such a knowledge base does not lend itself to the development of good include the foIlowing:! I behavIOr.
As another example, a common topic of Figure 2. In this situation, the development of a theory of how a program is supposed to work is essential to the design of the evaluation but has been commonly underemphasized in the past Bickman, According is commonly recognized because research investigators have ready access to to Bickrnan, analysts have frequently confused the theory of the program formulas for determining the confidence with which generalizations can be e.
Wberepolicymak- universe and sample. Moreover, this is the most common way of generalizmg ers want to know the desired substantive steps e. This mismatch can be avoided by giving closer A fatal flaw in doing case studies is to conceive of statistical generalization attention to the substantive theory. This is because cases are not "sampling units" and should not be chosen for this reason.
Generalizing from case study to theory. Theory development does not individual case srudies are to be selected as a laboratory investigator selects the topic of a new experiment.
Multiple cases, in this sense, should be only facilitate the data collection phase of the ensuing case study. The ap- considered like multiple experiments or multiple surveys. Under these propriately developed theory also is the level at which the generalization of circumstances, the method of generalization is "analytic generalization," in the case study results will occur.
This role of theory has been characterized which a previously developed theory is used as a template with which to throughout this book as "analytic generalization" and has been contrasted compare the empirical results of the case study. Iftwo or more cas,:". The empmcal results tion. In statistical generalization, an inference is made about a population Analytic generalization can be used whether your case study involves one or universe on the basis of empirical data collected about a sample.
This is or several cases, which shall be later referenced as single-case or multiple-case shown as a Level One ['lference in Figure 2. The main point at this juncture is that you should try to aim toward analytic generalization in doing case studies, and you should avoid thinking in such confusing terms as "the sample of cases" or the "small sample size of cases," as if a single case study were like a single In other words, draft caM Because of the imPOrtance of this distinction between the two ways of generalizing, you will find repeated examples and discussion throughout the Rather than resisting such a requirement, a good case study investigator should make the effort to develop this theoretical framework, no matter rellabUflJr The use of theory, in doing case studies, not only is an immense aid in defining the Figure 2.
Concepts that have been offered for these tests include trust- worthiness, Credibility, conf1flDability, and data dependability U. For case studies, an Important revelallon. IS that the several tactics to be used in dealing with these tests should be applIed throughout the i. In this is to have the draft case study report reviewed by key informants a procedure sense, "design work" actually continues beyond the initial design plans.
Construct Validity Internal Validity This fIrst test is especially problematic in case study research. Me an example such bell, Numerous "threats" to validity have been identifIed, maInly as studying "neighborhood change"-a common case stody topic. However, because so many textbooks already Over the years, concerns have arisen over how certain urban neighborhoods cover this topic, only two points need to be made here. However, without any prior speci- studies, in which an investigator is trying to determine whether event x led fIcation ofthe slgmfIcant, operational events that constitute "change," areader to event y.
If the investigator incorrectly concludes that there IS a causal cannot tell whether the rec. Note that this logic is inapplicable to descriptive or Neighborhood change can indeed cover a wide variety of phenomena: exploratory studies whether the studies are case studies, surveys, or experi- racial turnover, housing deterioration and abandonment, changes in the pat- ments , which are not concerned with making causal statements.
Basically, a case study borhoods. To meet the test of construct validity, an investigator must be sure involves an inference every time an event cannot be directly observed. Thus to cover two steps: an investigator will "infer" that a particular event resulted from some earlier occurrence, based on interview and documentary evidence collected as part I.
Select the specific types of changes that are to be studied in relation to the of the case study. Is the inference correct?
Have all the rival explanations and original objectives of the study and possibilities been considered? D,:,"s it appear to 2. Demonstrate that the selected measures of these changes do indeed reflect the be airtight? A research design that has anticipated these questions has begun specific types of change that have been selected. The second step now demands that you I tify. This is especially true in doing case studies.
As one set of suggestions, also justify why you might be using police-reported crime which happens Figure 2. Perhaps this is not a valid measure, given that large validity.
As Figure 2. The fIrst is the use of multiple sources ofevidence, In a manner encouraging convergent lines of inquiry, and this tactic is relevant External Validity during data collection see Chapter 4. A second tactic is to establish a chain of evidence, also relevant during data collection Chapter 4. The third tactic The third test deals with the problem of knowing whether a study's findings are generalizable beyond the immediate case study.
The external validity problem BOX 7 has been amajor barrier in doing Case studies. Critics typically state that single How Case Studies cases offer a poor basis for generalizing.
However, such critics are implicitly Can Be Generalized to Theory contrasting the situation to survey research, in which a "sample" if selected correctly readily generalizes to a larger universe. Thus analysts fall into the trap of try10g to select a survey research relies on statistical generalization, whereas Case studies as "representative" case or set of cases. In analytical generaliza-. If a study had focused on "gentrifica- tion" see Auger, , the procedure for selecting a neighborhood for study De!
In principle, theories about changes in all of these. A theory must be tested b "Jdi of a theory of urban planrung. Once such Partial result, new empm. This replication logic is the Same that underlies the use of experiments and allows scientists to generalize from one experiment to another and, as shown in Figure 2. Note that the emphasis is on doing the same case over again, not on "replicating" the results of one case by doing another Case study.
In accoun ng as If someoneone and bookkeeping. In thIS r ability check and must be able to One prerequisite for allOWing this other investigator to repeat an earlier Case study is the need to document the procedures follOwed in the earlier Case.
Four tests may be considered relevant in judging the quality of a research design. In designing and doing case studies, various tactics are designs designs available to deal with these tests, though not all of the tactics occur at the formal stage of designing a case study. Some of the tactics occur during the data collection, data analysis, or compositional phases of the research and are therefore described in greater detail in subsequent chapters of this book.
Four types of designs will be discussed, based on a 2 x 2 matrix see Figure 2. The matrix assumes that single- and multiple-case studies reflect different design situations and that, within these two types, there also can be a unitary or multiple units of embedded analysis.
Thus, for the case study strategy, the four types of designs are a TYPE 2 TYPE 4 multiple units single-case holistic designs, b single-case embedded designs, c multi- ple-case holistic designs, and d multiple-case embedded designs. The of analysis rationale for these four types of designs is as follows. This means the need for a decision, prior to any data collection, on whether a single-case study or multiple cases are going to be used to address the research questions. Such a study can even help to refocus future investigations The single-case study is an appropriate design under several circumstances.
See BOX 8 for another example, in the field of organiza- First, recall that a single-case study is analogous to a single experiment, and tional innovation. One rationale for a single case is when it represents the extreme or unique case. The theory has specified a clear set of propositions single case is worth doculI enting and analyzIng. To confirm, challenge, or extend the theory, there may exist a single case, meeting all of the conditions for testing the theory.
The single case can ones, friends, pictures of famous people, or in some cases. This syndrome appears to be due to some phYSIcal Injury to the whether some alternative set of explanations might be more relevant.
In this brain. In such CIrcumstances, the functioning and the Cuban missile crisis described in Chapter I, BOX 2 , single-case study is an appropriate research design whenever a new person the single case can represent a significant contribution to knowledge and with this syndrome-known as prnsopagnosia--is encountered.
Neal Another rationale for selecting a single--case rather than a multiple--case Gross et al. The case study is therefore worth conducting because The school was selected because it had a prior history of innovation and the descriptive information alone will be revelatory. The book is about a single group of black men, living in a poor, innovations failed. Gross et al. Implementation about their lifestyles, their coping behavior, and 10 particular therr sensItivIty processes, rather than barriers, appeared to account for the outcomes.
The book provides! Prior to the study, analysts had focused on the been only obscurely understood. The single case showed how mvestigations identification of barriers; since the study, the literature has been much more of such topics could be done, stimulating much further research and eventually dominated by studies of the implementation process. A third rationale for a single case study is the revelatory case. A outset. Liebow had the opportunity to meet the ,I mize the access needed to collect the case study evidence.
His observations of and insights into the problems ofunemployment I covered. Holistic versus embedded case studies. The same case study may involve were common across the country as distinguished from the rare or unique I more than one unit of analysis.
This occurs when, within a single. When other investigators have similar types of opportunities and can tention also is given to a subunit or subunits see BO. These three rationales serve as the major reasons for conducting a single-!
However the units are selected, the resuI'nng d ' eslgn i. The case study is about the inside politics of the International'! Ii would be called an embedded case study design see Figure 2. E 0 j:Q Another typical problem with the holistic design is that the entire case study may be conducted at an abstract level, lacking any clear i. Although some people have claimed J;. A major one occurs Multiple- versus single-case designs. In some fields, multiple-case studies when the case study focuses only on the subunit level and fails to return to have been considered a different "methodology" than single-case studies.
A program evaluation that includes project char- For example, both anthropology and political science have developed one acteristics as a subunit of analysis, for instance, becomes a project study if set of rationales for doing single-case studies and a second set for doing no investigating is done at the larger unit-that is, the "program. From the perspective of this book, however, subunit of study. However, if the data focus only on individual employees, the choice between single- and multiple-case designs remains within the the study will in fact become an employment and not an organizational study.
The choice is considered one of research design, with both being in- cluded under the case study strategy. Single cases are a common design for doing case studies, and Multiple-case designs have distinct advantages and disadvantages in com- two types have been described: those using holistic designs and those using parison with single-case designs.
The evidence from multiple cases is often embedded units of analysis. At the same time, the ration- of existing theory, where the case is a rare or unique event, or where the ale for single-case designs usually cannot be satisfied by multiple cases. The case serves a revelatory purpose. Moreover, the conduct of a multi- of analysis or the case itself. An operational definition is needed and some ple-case study can require extensive resources and time beyond the means of precaution must be taken--before a total commitment to the whole case study a single student or independent research investigator.
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