What is qualitative research?

Qualitative research is defined as a market research method that focuses on obtaining data through open-ended and conversational communication.

This method is not only about “what” people think but also “why” they think so. For example, consider a convenience store looking to improve its patronage. A systematic observation concludes that the number of men visiting this store are more. One good method to determine why women were not visiting the store is to conduct an in-depth interview of potential customers in the category.

For example, on successfully interviewing female customers, visiting the nearby stores and malls, and selecting them through random sampling, it was known that the store doesn’t have enough items for women and so there were fewer women visiting the store, which was understood only by personally interacting with them and understanding why they didn’t visit the store, because there were more male products than female ones.

Qualitative research is based on the disciplines of social sciences like psychology, sociology, and anthropology. Therefore, the qualitative research methods allow for in-depth and further probing and questioning of respondents based on their responses, where the interviewer/researcher also tries to understand their motivation and feelings. Understanding how your audience takes decisions can help derive conclusions in market research.

Types of qualitative research methods with examples

Qualitative research methods are designed in a manner that help reveal the behavior and perception of a target audience with reference to a particular topic. There are different types of qualitative research methods like an in-depth interview, focus groups, ethnographic research, content analysis, case study research that are usually used.

Interviews: Types and Methods in Management Research

Observation Methods – Definition, Types, Examples, Advantages

Case Study Methodology in Management Research

Overview of Action Research Methodology

Content Analysis Method and Examples

How phenomenology can help us learn from the experiences of others

The results of qualitative methods are more descriptive and the inferences can be drawn quite easily from the data that is obtained.

Qualitative research methods originated in the social and behavioral sciences. Today our world is more complicated and it is difficult to understand what people think and perceive. Online qualitative research methods make it easier to understand that as it is more communicative and descriptive.

The following are the qualitative research methods that are frequently used. Also, read about qualitative research examples:

1. One-on-one interview:

Conducting in-depth interviews is one of the most common qualitative research methods. It is a personal interview that is carried out with one respondent at a time. This is purely a conversational method and invites opportunities to get details in depth from the respondent.

One of the advantages of this method provides a great opportunity to gather precise data about what people believe and what their motivations are. If the researcher is well experienced asking the right questions can help him/her collect meaningful data. If they should need more information the researchers should ask such follow up questions that will help them collect more information.

These interviews can be performed face-to-face or on phone and usually can last between half an hour to two hours or even more. When the in-depth interview is conducted face to face it gives a better opportunity to read the body language of the respondents and match the responses.

2. Focus groups: A focus group is also one of the commonly used qualitative research methods, used in data collection. A focus group usually includes a limited number of respondents (6-10) from within your target market.

The main aim of the focus group is to find answers to the “why” “what” and “how” questions. One advantage of focus groups is, you don’t necessarily need to interact with the group in person. Nowadays focus groups can be sent an online survey on various devices and responses can be collected at the click of a button.

Focus groups are an expensive method as compared to the other online qualitative research methods. Typically they are used to explain complex processes. This method is very useful when it comes to market research on new products and testing new concepts.

3. Ethnographic research: Ethnographic research is the most in-depth observational method that studies people in their naturally occurring environment.

This method requires the researchers to adapt to the target audiences’ environments which could be anywhere from an organization to a city or any remote location. Here geographical constraints can be an issue while collecting data.

This research design aims to understand the cultures, challenges, motivations, and settings that occur. Instead of relying on interviews and discussions, you experience the natural settings first hand.

This type of research method can last from a few days to a few years, as it involves in-depth observation and collecting data on those grounds. It’s a challenging and a time-consuming method and solely depends on the expertise of the researcher to be able to analyze, observe and infer the data.

4. Case study research: The case study method has evolved over the past few years and developed into a valuable qual research method. As the name suggests it is used for explaining an organization or an entity.

This type of research method is used within a number of areas like education, social sciences and similar. This method may look difficult to operate, however, it is one of the simplest ways of conducting research as it involves a deep dive and thorough understanding of the data collection methods and inferring the data.

5. Record keeping: 

This method makes use of the already existing reliable documents and similar sources of information as the data source. This data can be used in new research. This is similar to going to a library. There one can go over books and other reference material to collect relevant data that can likely be used in the research.

6. Process of observation:

Qualitative Observation is a process of research that uses subjective methodologies to gather systematic information or data. Since, the focus on qualitative observation is the research process of using subjective methodologies to gather information or data. Qualitative observation is primarily used to equate quality differences.

Qualitative observation deals with the 5 major sensory organs and their functioning – sight, smell, touch, taste, and hearing. This doesn’t involve measurements or numbers but instead characteristics.

Qualitative research: data collection and analysis

A. Qualitative data collection

Qualitative data collection allows collecting data that is non-numeric and helps us to explore how decisions are made and provide us with detailed insight. For reaching such conclusions the data that is collected should be holistic, rich, and nuanced and findings to emerge through careful analysis.

1. Whatever method a researcher chooses for collecting qualitative data, one aspect is very clear the process will generate a large amount of data. In addition to the variety of methods available, there are also different methods of collecting and recording the data.

For example, if the qualitative data is collected through a focus group or one-to-one discussion, there will be handwritten notes or video recorded tapes. If there are recording they should be transcribed and before the process of data analysis can begin.

2. As a rough guide, it can take a seasoned researcher 8-10 hours to transcribe the recordings of an interview, which can generate roughly 20-30 pages of dialogues. Many researchers also like to maintain separate folders to maintain the recording collected from the different focus group. This helps them compartmentalize the data collected.
3. In case there are running notes taken, which are also known as field notes, they are helpful in maintaining comments, environmental contexts, nonverbal cues etc. These filed notes are helpful and can be compared while transcribing audio recorded data. Such notes are usually informal but should be secured in a similar manner as the video recordings or the audio tapes.

B. Qualitative data analysis

Qualitative data analysis such as notes, videos, audio recordings images, and text documents. One of the most used methods for qualitative data analysis is text analysis.

Text analysis is a  data analysis method that is distinctly different from all other qualitative research methods, where researchers analyze the social life of the participants in the research study and decode the words, actions, etc.

There are images also that are used in this research study and the researchers analyze the context in which the images are used and draw inferences from them. In the last decade, text analysis through what is shared on social media platforms has gained supreme popularity.

Characteristics of qualitative research methods

1. Qualitative research methods usually collect data at the sight, where the participants are experiencing issues or problems. These are real-time data and rarely bring the participants out of the geographic locations to collect information.
2. Qualitative researchers typically gather multiple forms of data, such as interviews, observations, and documents, rather than rely on a single data source.
3. This type of research method works towards solving complex issues by breaking down into meaningful inferences, that is easily readable and understood by all.
4. Since it’s a more communicative method, people can build their trust on the researcher and the information thus obtained is raw and unadulterated.

When to use qualitative research

Researchers make use of qualitative research techniques when they need to capture accurate, in-depth insights. It is very useful to capture “factual data”. Here are some examples of when to use qualitative research.

• Developing a new product or generating an idea.
• Studying your product/brand or service to strengthen your marketing strategy.
• To understand your strengths and weaknesses.
• Understanding purchase behavior.
• To study the reactions of your audience to marketing campaigns and other communications.
• Exploring market demographics, segments, and customer groups.
• Gathering perception data of a brand, company, or product.

Qualitative research methods vs quantitative research methods

The basic differences between qualitative research methods and quantitative research methods are simple and straightforward. They differ in:

• Their analytical objectives
• Types of questions asked
• Types of data collection instruments
• Forms of data they produce
• Degree of flexibility

The post Qualitative Research: Definition, Types, Methods and Examples appeared first on HKT Consultant.

One qualitative method that goes back a long way is the case study.  When physicians like Sigmund Freud became interested in psychological problems, they continued their tradition of writing and publishing descriptions of their most interesting patients, the treatments they attempted to use, and the progress of the disorder.  Much of the content of abnormal psychology, for example, is built upon these case studies.

Another example is the méthode clinique or clinical method.  This method was particularly well used by Jean Piaget and his followers.  The basic idea is to present a person (in Piaget’s case, usually a young child) with a situation or problem for them to deal with.  The researcher observes how they handle the situation and asks them questions to try to understand the thought processes they are using.  Another version of the méthode clinique is called experimental phenomenology.  One study, for example, asked chess masters and novices to think out loud while playing chess, and analyzed the differences in approach.  One more example is the method of introspection used by Wilhelm Wundt — often considered the founder of scientific psychology — and his students.  Researchers paid careful attention to their own perceptions of simple events like colors, and noted changes in their perceptions following changes in the events.

Probably the oldest qualitative method is naturalistic observation.  This has been used by biologists who study animals in the wild (ethologists) for centuries, and by sociologists studying people’s behavior for nearly as long.  The idea of naturalistic observation is to step back from the situation and make every effort not to interfere.  A biologist studying birds, for example, may construct a blind — a small hut covered with natural materials — so as not to disturb the birds.  Child psychologists often observe children in a similar way.  In experimental schools, the children are often so used to being observed that the researchers don’t even have to hide!  Recently, video and audio technology has allowed us to do the same with people.  Unfortunately, the ethics of spying on people is very questionable!

A variation on naturalistic observation used by some sociologists and psychologists is called participant observation.  A sociologist who is interested in studying the lifestyles of people in some subculture (say a motorcycle gang) may actually join the subculture and interact with the people.  Many anthropologists use this technique as well.  In most cases, it is clear to all that the researcher is not really a part of the group, but sometimes the researcher hides his identity as a researcher.

One of the most useful qualitative techniques is interviewing.  It is often a part of all of the preceding methods.  Contrary to what many people believe, interviewing is not easy.  In fact, it is a rare person who is truly skillful at interviewing.  You have to be very careful not to listen to the person you interview through any prejudiced ideas you might have.  You have to make sure you are not leading the person in the direction you would like them to go.  You have to make sure you don’t misinterpret what they say.  In other words, you need to be very aware of your own biases!

Many researchers using qualitative methods adhere to a school of thought called phenomenology, and refer to their methods as phenomenological methods.  Phenomenology is the study of the contents of consciousness — phenomena — and phenomenological methods are ways of describing and analyzing these contents.  Originally, the methods focussed on describing one’s own thought, feelings, and perceptions.  For example, researchers would investigate their own experiences of an emotion such as anger, or cognitive processes like making a decision.  As you can imagine, the problem of biases are even more difficult to handle in these kind of studies.  Many people, if asked about their experiences of anger, might say something like “I could feel the adrenaline flowing through my veins!”  Unfortunately, that is a prejudicial statement based on people’s common knowledge about the presence of adrenaline.  In fact, nobody actually feels adrenaline in their veins!  We may feel muscle tension, or the hair raising in our necks, or a change in our hearing — but not adrenaline in our  veins.

As time went on, other ways of investigating phenomena were added.  For example, the researcher might ask other people to write what are called protocols — naïve descriptions of their experiences — and use them for analysis.  This is done, for example, when the researcher wants to investigate something he or she doesn’t have personal experience with, such as a schizophrenics verbal hallucinations.

There are arguments for and against the use of qualitative methods.  The most common criticisms of qualitative methods revolve around the problem of bias mentioned above:  It is much easier for biases to creep into qualitative studies than into quantitative ones.  The great advantage of measurement is that, once we have agreed upon what constitutes a measure (say, a meter stick), everyone can use it and be fairly confident that what they measure is what anyone else would measure.  If, on the other hand, we say “this looks like navy blue to me,” someone else might say “no, I think it’s purple,” and another person “no, it’s clearly royal blue!”

The arguments for qualitative methods revolve around realism.  Measures do not encompass the whole of an event.  You can ask people to rate their anxiety, but how much will that tell you about what they are actually feeling?  How do you measure something like love or hate?  Or think about the anthropologist looking at a culture:  Does counting the number of artifacts or timing rituals tell you much about their meaning to the people involved?  Or consider a person’s personality:  Do scores on personality tests tell you much about a person’s life or experiences?  Qualitative researchers would say not much!

Although quantitative methods are still preferred in psychology, more and more people are acknowledging that qualitative methods also have an important place.  Not everything about human beings can be understood by measurement, or in laboratories, or by using rats and pigeons.

Numerous specific research methods/instruments are used when conducting qualitative research.

Interviews: Types and Methods in Management Research

Case Study Methodology in Management Research

Observation Methods – Definition, Types, Examples, Advantages

Overview of Action Research Methodology

Content Analysis Method and Examples

How phenomenology can help us learn from the experiences of others

• Case Studies
• Conversation Analysis
• Field Studies
• Focus Groups
• Interviews
• Naturalistic Observation
• Participant Observation
• Ethnography
• Phenomenology
• Autoethnography- This bibliography is compiled from a section of Heather Forest’s ILA on Autoethnography & Storytelling. It includes citations for several peer review journal articles that describe recent autoethnographic studies.
• Grounded Theory Methods Folder- This bibliography contains references historical and recent books on grounded theory methodology and symbolic interactionalism.
• Critical Discourse Analysis- Books, chapters, journal articles, whole journals, & dissertations.

The post Qualitative methods: what and why use them? appeared first on HKT Consultant.

The post Difference Between Qualitative and Quantitative Research appeared first on HKT Consultant.

Respect the Structure of In-depth Interviews

We have found it important to adhere to the three-interview struc­ture. Each interview serves a purpose both by itself and within the series. Sometimes, in

The Three-Interview Series

Perhaps most distinguishing of all its features, this model of in­depth, phenomenological interviewing involves conducting a series of three separate interviews with each participant. People’s

Introduction to Interviewing as qualitative methods

Interview because I am interested in other people’s stories. Most sim­ply put, stories are a way of knowing. The root of the word story is

Alternatives to the Structure and Process of In-depth, Phenomenological Interviews

Researchers will have reasons for exploring alternatives to the structure and procedures described above. As long as a structure is maintained that allows participants to

Spacing of In-depth Interviews

The three-interview structure works best, in my experience, when the researcher can space each interview from 3 days to a week apart. This allows time

Length of In-depth Interviews

To accomplish the purpose of each of the three interviews, Dolbeare and Schuman (Schuman, 1982) used a 90-minute format. People learning this method for the

Questions to Structure the Interview Research Proposal

1. What? Proposal writers need to ask themselves some simple questions. These can be divided into several groups. First is a group of questions I

What Is to Be Done in Interview Research Method?

Peter Elbow (1981) offers an approach to writing that I think can be useful in such cases. He suggests that trying both to create with

From Thought to Language

Many students have trouble writing proposals because they are plagued by a sense of audience. The process seems dominated by doc­toral committees and Institutional Review

Commitment in Interview Research Method

When a candidate’s doctoral program is working well, a research topic arises out of work that has gone before. Course work, fieldwork, practica, clinical work,

Research Proposals as Rites of Passage in Interview Research Method

In some respects becoming an academic is like joining a club. As in most other somewhat-exclusive clubs, there are those who are in and those

Whose Meaning Is It? Validity and Reliability for In-depth, Phenomenological Interviewing

Whose meaning is it that an interview brings forth and that a re­searcher reports in a presentation, article, or book? That is not a simple

Informal Gatekeepers for Interview Research

Sometimes although there is no formal gatekeeper, there is an in­formal one (Richardson et al., 1965). Most faculties, for example, usu­ally include a few members

Access Through Formal Gatekeepers in Interview Research

When interviewers try to contact potential participants whom they do not know, they often face gatekeepers who control access to those people. Gatekeepers can range

The Perils of Easy Access for Interview Research

Beginning interviewers tend to look for the easiest path to their po­tential participants. They often want to select people with whom they al­ready have a

Piloting Your Interview Research

The best advice I ever received as a researcher was to do a pilot of my proposed study. The dictionary (Gove, 1971) definition of the

Working with the Interview Material

Research proposals should describe how researchers intend to work with and analyze the material they gather. Describing this process ahead of time is especially difficult

Rationale of Interview Research

Although the paradigms that underlie research methods in the social sciences seem to be changing rapidly (Kvale, 1996; Lincoln & Guba, 1985), the extent to

The Belmont Report

Faced with the fact that the disregard for human welfare in research occurred not just abroad but also at home, various departments of the U.S.

Selecting Participants for Interview Research

1. SELECTING PARTICIPANTS Either during the contact process or shortly thereafter the researcher takes the crucial step of selecting the people he or she will

Some Logistical Considerations in Interview Research

The experience of scheduling a contact visit often reflects what trying to schedule the actual interview with the participant will be like. If one is

Building the Participant Pool in Interview Research

Another primary purpose of the contact visit is to assess the appro­priateness of a participant for the study. The major criterion for appro­priateness is whether

Making Contact in Interview Research

1. MAKING CONTACT Do it yourself. Try not to rely on third parties to make contact with your potential participants. No matter how expedient it

Access and Hierarchy of Interview Research

One of the differences between research and evaluation or policy studies is that the latter are often sponsored by an agency close to the people

Interviewing as an “I-Thou” Relationship

In a section of his book that is elegant even in translation, Schutz (1967) explains that one person’s intersubjective understanding of another depends upon creating

Interview Techniques Isn’t Everything, But It Is a Lot

1. LISTEN MORE, TALK LESS Listening is the most important skill in interviewing. The hardest work for many interviewers is to keep quiet and to

The Complexities of Affirming the IRB Review Process and Informed Consent

When guidelines for seeking informed consent were first issued by federal agencies in the 1960s and 1970s, some researchers felt that the costs of the

Eight Major Parts of Informed Consent

A consent form adapted to in-depth interviewing should cover eight major parts: An invitation to participate in what, to what end, how, how long, and

The Informed Consent Form

While there may be some variance in what a local IRB will ask re­searchers to submit for review, the issue of an informed consent form

The Establishment of Local Institutional Review Boards

With the Belmont Report providing guidance, the federal government began the process of harmonizing the regulations that had been issued by various agencies into what

Equity in Interview Research

Interviewers and participants are never equal. We can strive to reduce hierarchical arrangements, but usually the participant and the interviewer want and get different things

Reciprocity in Interview Research :

The issue of reciprocity in the interviewing relationship can be trou­bling. The more the interviewing relationship is charged with issues of race, ethnicity, class, and

Avoid a Therapeutic Relationship

At the same time, interviewers must avoid changing the interview­ing relationship into a therapeutic one. Many see a similarity between the type of open-ended, relatively

Distinguish Among Private, Personal, and Public Experiences

Interviewing relationships are also shaped by what the interviewer and participant deem are appropriate subjects to explore in the interview. In considering what is appropriate,

Social Group Identities and the Interviewing Relationship

Issues of equity in an interviewing relationship are affected by the social identities that participants and interviewers bring to the interview. Our social identities are

Interview Rapport

That balancing act is central to developing an appropriate rapport with the participant. I have never been completely comfortable with the common assumption that the

Interview Note

The number of themes that emerge into prominence in an interview study has implications for the organization of a dissertation. While the format of a

Interpreting the Interview Material

Interpreting is not a process researchers do only near the end of the project. Even as interviewers question their participants, tentative inter­pretations may begin to

Making and Analyzing Thematic Connections

A more conventional way of presenting and analyzing interview data than crafting profiles is to organize excerpts from the transcripts into cat­egories. The researcher then

Sharing Interview Data: Profiles and Themes

One goal of the researcher in marking what is of interest in the inter­view transcripts is to reduce and then shape the material into a

Studying, Reducing, and Analyzing the Interview Text

As one can see, in-depth interviewing generates an enormous amount of text. The vast array of words, sentences, paragraphs, and pages have to be reduced

Transcribing Interview Tapes

Transcribing interview tapes is time-consuming and potentially costly work. It can be facilitated by using a transcribing machine that has a foot pedal and earphones.

Tape-Recording Interviews

I have no doubt that in-depth interviews should be tape-recorded; however, the literature reflects varying opinions on this point (Bogdan & Taylor, 1975; Briggs, 1986;

Keeping Interviewing and Analysis Separate: What to Do Between Interviews

It is difficult to separate the processes of gathering and analyzing data. Even before the actual interviews begin, the researcher may an­ticipate results on the

Managing the Interview Data

To work with the material that interviewing generates, the researcher first has to make it accessible by organizing it. Keeping track of partici­pants through the

Fundamental Types of Interviews in Research

A researcher has to conduct interviews with a group of participants at a juncture in the research where information can only be obtained by meeting and personally connecting with a section of their target audience. Interviews offer the researchers with a platform to prompt their participants and obtain inputs in the desired detail. There are three fundamental types of interviews in research:

• Structured Interviews:

Structured interviews are defined as research tools that are extremely rigid in their operations are allows very little or no scope of prompting the participants to obtain and analyze results. It is thus also known as a standardized interview and is significantly quantitative in its approach. Questions in this interview are pre-decided according to the required detail of information.

Structured interviews are excessively used in survey research with the intention of maintaining uniformity throughout all the interview sessions.

They can be closed-ended as well as open-ended – according to the type of target population. Closed-ended questions can be included to understand user preferences from a collection of answer options whereas open-ended can be included to gain details about a particular section in the interview.

Advantages of structured interviews:

• Structured interviews focus on the accuracy of different responses due to which extremely organized data can be collected. Different respondents have different type of answers to the same structure of questions – answers obtained can be collectively analyzed.
• They can be used to get in touch with a large sample of the target population.
• The interview procedure is made easy due to the standardization offered by structured interviews.
• Replication across multiple samples becomes easy due to the same structure of interview.
• As the scope of detail is already considered while designing the interview, better information can be obtained and the researcher can analyze the research problem in a comprehensive manner by asking accurate research questions.
• Since the structure of the interview is fixed, it often generates reliable results and is quick to execute.
• The relationship between the researcher and the respondent is not formal due to which the researcher can clearly understand the margin of error in case the respondent either degrees to be a part of the survey or is just not interested in providing the right information.

Disadvantages of structured interviews:

• Limited scope of assessment of obtained results.
• The accuracy of information overpowers the detail of information.
• Respondents are forced to select from the provided answer options.
• The researcher is expected to always adhere to the list of decided questions irrespective of how interesting the conversation is turning out to be with the participants.
• A significant amount of time is required for a structured interview.

Learn more: Market Research

• Semi-Structured Interviews:

Semi-structured interviews offer a considerable amount of leeway to the researcher to probe the respondents along with maintaining basic interview structure. Even if it is a guided conversation between researchers and interviewees – an appreciable flexibility is offered to the researchers. A researcher can be assured that multiple interview rounds will not be required in the presence of structure in this type of research interview.

Keeping the structure in mind, the researcher can follow any idea or take creative advantage of the entire interview. Additional respondent probing is always necessary to garner information for a research study. The best application of semi-structured interview is when the researcher doesn’t have time to conduct research and requires detailed information about the topic.

Advantages of semi-structured interviews:

• Questions of semi-structured interviews are prepared before the scheduled interview which provides the researcher with time to prepare and analyze the questions.
• It is flexible to an extent while maintaining the research guidelines.
• Researchers can express the interview questions in the format they prefer, unlike the structured interview.
• Reliable qualitative data can be collected via these interviews.
• Flexible structure of the interview.

Learn more: Quantitative Data

Disadvantages of semi-structured interviews:

• • Participants may question the reliability factor of these interviews due to the flexibility offered.
  • Comparing two different answers becomes difficult as the guideline for conducting interviews is not entirely followed. No two questions will have the exact same structure and the result will be an inability to compare are infer results.

• Unstructured Interviews:

Also called as in-depth interviews, unstructured interviews are usually described as conversations held with a purpose in mind – to gather data about the research study. These interviews have the least number of questions as they lean more towards a normal conversation but with an underlying subject.

The main objective of most researchers using unstructured interviews is to build a bond with the respondents due to which there are high chances that the respondents will be 100% truthful with their answers. There are no guidelines for the researchers to follow and so, they can approach the participants in any ethical manner to gain as much information as they possibly can for their research topic.

Since there are no guidelines for these interviews, a researcher is expected to keep their approach in check so that the respondents do not sway away from the main research motive. For a researcher to obtain the desired outcome, he/she must keep the following factors in mind:

• Intent of the interview.
• The interview should primarily take into consideration the participant’s interest and skills.
• All the conversations should be conducted within permissible limits of research and the researcher should try and stick by these limits.
• The skills and knowledge of the researcher should match the purpose of the interview.
• Researchers should understand the do’s and don’ts of unstructured interviews.

Advantages of Unstructured Interviews:

• Due to the informal nature of unstructured interviews – it becomes extremely easy for researchers to try and develop a friendly rapport with the participants. This leads to gaining insights in extreme detail without much conscious effort.
• The participants can clarify all their doubts about the questions and the researcher can take each opportunity to explain his/her intention for better answers.
• There are no questions which the researcher has to abide by and this usually increases the flexibility of the entire research process.

Disadvantages of Unstructured Interviews:

• As there is no structure to the interview process, researchers take time to execute these interviews.
• The absence of a standardized set of questions and guidelines indicates that the reliability of unstructured interviews is questionable.
• In many cases, the ethics involved in these interviews are considered borderline upsetting.

Learn more: Qualitative Market Research

Methods of Research Interviews:

There are three methods to conduct research interviews, each of which is peculiar in its application and can be used according to the research study requirement.

Personal Interviews:

Personal interviews are one of the most used types of interviews, where the questions are asked personally directly to the respondent. For this, a researcher can have a guide online surveys to take note of the answers. A researcher can design his/her survey in such a way that they take notes of the comments or points of view that stands out from the interviewee.

Advantage:

• Higher response rate.
• When the interviewees and respondents are face-to-face, there is a way to adapt the questions if this is not understood.
• More complete answers can be obtained if there is doubt on both sides or a particular information is detected that is remarkable.
• The researcher has an opportunity to detect and analyze the interviewee’s body language at the time of asking the questions and taking notes about it.

Disadvantages:

• They are time-consuming and extremely expensive.
• They can generate distrust on the part of the interviewee, since they may be self-conscious and not answer truthfully.
• Contacting the interviewees can be a real headache, either scheduling an appointment in workplaces or going from house to house and not finding anyone.
• Therefore, many interviews are conducted in public places, such as shopping centers or parks. There are even consumer studies that take advantage of these sites to conduct interviews or surveys and give incentives, gifts, coupons, in short; There are great opportunities for online research in shopping centers.
• Among the advantages of conducting these types of interviews is that the respondents will have more fresh information if the interview is conducted in the context and with the appropriate stimuli, so that researchers can have data from their experience at the scene of the events, immediately and first hand. The interviewer can use an online survey through a mobile device that will undoubtedly facilitate the entire process.

Telephonic Interviews:

Telephonic interviews are widely used and easy to combine with online surveys to carry out research effectively.

Advantages:

• To find the interviewees it is enough to have their telephone numbers on hand.
• They are usually lower cost.
• The information is collected quickly.
• Having a personal contact can also clarify doubts, or give more details of the questions.

Disadvantages:

• Many times researchers observe that people do not answer phone calls because it is an unknown number for the respondent, or simply already changed their place of residence and they cannot locate it, which causes a bias in the interview.
• Researchers also face that they simply do not want to answer and resort to pretexts such as they are busy to answer, they are sick, they do not have the authority to answer the questions asked, they have no interest in answering or they are afraid of putting their security at risk.
• One of the aspects that should be taken care of in these types of interviews is the kindness with which the interviewers address the respondents, in order to get them to cooperate more easily with their answers. Good communication is vital for the generation of better answers.

Email or Web Page Interviews:

Online research is growing more and more because consumers are migrating to a more virtual world and it is best for each researcher to adapt to this change.

The increase in people with Internet access has made it popular that interviews via email or web page stand out among the types of interviews most used today. For this nothing better than an online survey.

More and more consumers are turning to online shopping, which is why they are a great niche to be able to carry out an interview that will generate information for the correct decision making.

Advantages of email surveys:

• Speed in obtaining data
• The respondents respond according to their time, at the time they want and in the place they decide.
• Online surveys can be mixed with other research methods or using some of the previous interview models. They are tools that can perfectly complement and pay for the project.
• A researcher can use a variety of questions, logics, create graphs and reports immediately.

Undoubtedly, the objective of the research will set the pattern of what types of interviews are best for data collection. Based on the research design, a research can plan and test the questions, for instance, if the questions are the correct and if the survey flows in the best way.

In addition there are other types of research that can be used under specific circumstances, for example in the case of no connection or adverse situations to carry out surveyors, in these types of occasions it is necessary to conduct a field research, which can not be considered an interview if not rather a completely different methodology.

To summarize the discussion, an effective interview will be one that provides researchers with the necessary data to know the object of study and that this information is applicable to the decisions researchers make.

The post Interviews: Types and Methods in Management Research appeared first on HKT Consultant.

The observation method is described as a method to observe and describe the behavior of a subject. As the name suggests, it is a way of collecting relevant information and data by observing. It is also referred to as a participatory study because the researcher has to establish a link with the respondent and for this has to immerse himself in the same setting as theirs. Only then can he use the observation method to record and take notes.

Meaning and examples

Observation method is used in cases where you want to avoid an error that can be a result of bias during evaluation and interpretation processes. It is a way to obtain objective data by watching a participant and recording it for analysis at a later stage.

A researcher can use the observation method in a Montessori school and record the behavior of the children at a young age. Are the children comfortable sharing their tiffin at such an early age will make a good study for the researcher? In this example, the researcher can observe and record the details objectively. Observation data collection method is associated with a few ethical issues as it needs the full consent of a research participant.

Main contentsSee more from basic to advanced

The uses of observation as research method

The most general use of observation in research is exploratory, as it is in real life. When we take up a new job, enter university,

Observation and self-report: similarities and Differences

Both self-report (as in questionnaires and interviews) and observation techniques can differ in their degree of struc­ture. The first of these may involve short, prescriptive

Introduction to observation

Observation has one overpowering claim to validity: it deals not with what people say they do but what they actually do – to the extent

Event sampling in Structured observation

1. Event sampling Event sampling is used when the behaviour of interest is discontinuous and low frequency, where you would miss the events if you

Structured observation in practice

For the moment the terms structured, detached and non­participant are used almost interchangeably: that is not quite correct (see page 19) but sufficiently so to

Observation in multi-method research

In the same way that surveys can give the bigger picture within which more in-depth interviews are nested, so can observation provide a wider descriptive

Unstructured Observation: The Rise of Ethnography Method

Observation can vary in its degree of structure – how far the researchers’ approach is pre-formed, in the sense of know­ing what they want to

Observation as an Experimental Method

We commonly talk of ‘experimenting’ with things – whether it is a new multi-function mobile phone or an elaborate recipe culled from a magazine –

Semi-structured Observation in training, teaching and learning

1. Observation in training In a sense we are all ‘disabled’ when it comes to operating an unfamiliar and relatively complicated piece of equipment: the

Semi-structured Observation Method

If observation is a primary technique of real-world social research one can be forgiven for thinking that structured observation, with its ‘count’ emphasis and fragmented

Validating observation sampling

In survey research a sample of the population (however defined) is taken because it is much more economical to do so. A ‘valid’ – i.e.

Time sampling in Structured Observation

This is also known as interval sampling because you observe for a specified duration at specified intervals – like taking a succession of snapshots, an

Ethnographic collaboration with members of the ‘culture’ being studied

Human research, even of the culturally sensitive variety, can be seen as something done to people, the passive recipients of the researcher’s attention. But perhaps

The use of video

Video might seem to get round the issue of the process of selection which is self-evident in still photographs. Certainly continuous filming of a sequence

Photographic sequences as a structured narrative

Chapter 2 described how I first observed and recorded interaction between members of the public and Ian in Glasgow’s Argyle Street. As I did so

Text and images in Visual Ethnography

1. Text and images This discursive introduction in what is intended to be a practical book is because of the need to draw back from

Visual Ethnography Method

It seems obvious: if you want to describe a culture, making your account vivid and ‘real’, what more direct method could there be than the

Process of observation methodology

This chapter is written ‘as it happened’ so that much of it has an episodic quality. The chronological form of presentation also demonstrates the nature

The Limitations of Observation Method

In Chapter 8 we considered the role of self-observation as a research method in its own right, particularly direct access to ‘internal’ events, though these

Ethical Dilemmas of Observation Method

How would you feel about being observed systematically, whether for research or any other purpose? There is an intuitive, hard-to-define sense of unease in that

Self-Observation: What use is such an account to anyone else?

We are (most of us) very interested in ourselves and routi­nely engage in self-scrutiny at one level or another. But we do not usually seek

Reviewing the raw material from self-observation

A self-observation research procedure generates a lot of material. Its collection needs to be organized from the start, and progressively edited down. A good habit

Self-Observation: Observing how we work

The physical, habitual and social context of how we work or research is part of the picture. We don’t just exist in terms of what

Self-Observation method

Self-observation is best known as a way of enhancing per­formance, via video recording, widely used in interview training. Actors whose performances are filmed have long

Ethnographic methods: specific research problems

1. Ethnographic research is used to define a research problem Certain well-established research topics attract the researcher because of their extensive bodies of associated literature,

Ethnographic methods

1. Ethnographic methods: a general statement of utility As noted in the previous chapter, ethnographic methods have been adopted by scholars from many academic disciplines

Participant observation as style and context

It is certainly possible to use data collection techniques that are typical of ethno­graphic research (see Chapter 4) in ways that do not involve participant

Introduction to ethnography: basic principles, definition and nature

Despite this diversity of positions from which ethnographers may derive, we may still highlight a few important features that link the many and varied approaches:

Sociocultural theory and ethnographic research

As the ethnographic method has spread across disciplines, it has become associ­ated with a wide variety of theoretical orientations: structure-functionalism symbolic interactionism feminism Marxism ethnomethodology

A brief history of ethnographic research

Ethnography literally means a description of a people. It is important to under­stand that ethnography deals with people in the collective sense, not with indi­viduals.

A definition of observation

We have seen that ethnographic research is a judicious mix of observation, inter­viewing, and archival study. Since other volumes in this series will treat the

Data collection in the field for a ethnographic research

1. ‘Facts’ and ‘reality’ Trained biologists looking at cells under a microscope can come up with accu­rate descriptions of the components of those cells. If

Rapport on field site of ethnographic research

It goes without saying that all readers of this book are wonderful, generous, out­going, lovable people who would be welcome in communities around the world.

Selecting a field site for a ethnographic research

Having subjected yourself to a thorough personal review, you can now apply more objective criteria in deciding where you want to do your research. Some

Begin the ethnographic research with a personal inventory

It is often said that the one piece of equipment that an ethnographic researcher ultimately relies on is him or herself. It is all very

Ethnographic methods: research settings

Ethnographic research can be done wherever people interact in ‘natural’ group settings. Bringing people together for a specific purpose in controlled laboratory settings is a

Ethnography for the twenty-first century

1. The changing research context: technology Participant observation once implied a lone researcher working in a self- contained community, armed only with a notebook and

Ethical considerations in a ethnographic research

1. Levels of ethical considerations relevant for research There are three levels on which ethical considerations bear on the conduct of research: The official, published

Strategies for representing ethnographic data

1. Representing ethnographic data in traditional scholarly form Scientific writing of whatever length typically includes several key elements usually set out in a conventional order.

Analyzing ethnographic data

1. Patterns How do you recognize a pattern? Basically speaking, a true pattern is one that is shared by members of the group (their actual

Ethics and observational research

General questions of research ethics as they apply to ethnography are treated in a later chapter, but a few special points need to be dealt

Observations in public spaces

One of the most characteristic applications of observational research is that which is carried out in public spaces. Indeed, given the nature of this setting,

Observer bias

Ethnographers in general, and observation-based researchers in particular, are frequently criticized for the subjectivity that informs their work. Even the most apparently unobtrusive observation can

The question of validity in observational research

Quantitative researchers can demonstrate both the validity and the reliability of their data through statistical means. ‘Reliability’ is a measure of the degree to which

The process of observational research

‘Observation’ rarely involves a single act. Rather, it is a series of steps that builds toward the regularity and precision inherent in our working definition.

The task of observational research

Observational techniques are suitable for research dealing with specific settings (e.g. a shopping mall, a church, a school); events, which are defined as sequences of

Types of observational research

Although in its earliest manifestations as a research tool observation was sup­posed to be ‘non-reactive’, in fact observation presupposes some sort of contact with the

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See basic to advanced

Observation method in data collection can be

• Structured observation method – This is a systematic observation method where data is collected as per a pre-defined schedule. The specific variable is used in this method for data collection.
• Unstructured observation method – The unstructured observation method is conducted in a free and open manner without using any pre-determined objectives, schedules or variables.

Sampling methods for Observational Data

The researcher has a vital role to play as he will have to collect, record and classify the data appropriately. The primary sampling methods are

• Event sampling – In the event sampling observation method the researcher decides beforehand what events or behavior he will record and which ones he is going to ignore
• Time sampling – In the time sampling observation method, the researcher chooses the time when he will observe. He makes a record of the occurrence only in the specified and pre-determined period
• Target-time or instantaneous sampling –  In the target-time or instantaneous sampling observation method, the researcher decides beforehand the moments when the observation will happen and will be recorded at that moment. Everything that happens before or after that moment is of no consequence hence is typically ignored

Types of observation method

The different types of observation method are as follows:

1) Controlled observations

The controlled observation is carried out in a closed space. It is the researcher who has the authority to decide the place and the time where and when the observation will take place. He also decides who the participants will be and in what circumstances will he use the standardized process.

The participants are chosen for a variable group randomly. The researcher observes and records a detailed and descriptive data of behavior and divides it into a distinct category. Sometimes the researcher codes the action as per an agreed scale by using a behavior schedule. The coding can include letters or numbers or a range to measure behavior intensity and describe its characteristics.

The collected data is often turned into statistics. In a controlled observation method, the participants are informed by the researcher about the aim of the research. This makes them aware of being observed. The researcher avoids direct contact during the observation method and generally uses a two-way mirror to observe and record details.

Advantages of controlled observation method

1. The data and information received from a controlled observation method are structured and analytical. It is thus easy to analyze it quickly and is considered less time-consuming than the other observation methods
2. Other researchers can easily replicate the report that has been created through the controlled observation method. They use a similar observation schedule, and this makes it easy to test for reliability.
3. As the controlled observation method is several quick observations can be conducted within a short time frame. Thus the researcher can collect large samples which makes it easier for him to generalize a large population

Limitations of controlled observation method 

1. The controlled observation method lacks validity because when the participants are aware of being observed their behavior will automatically change

2) Naturalistic observations

Social scientists and psychologists generally use the naturalistic observation method. The process involves observing and studying the spontaneous behavior of the participants in open or natural surroundings. The role of the researcher is to find and record whatever he can see and observe in natural habitat.

Advantages of naturalistic observation method 

1. When a participant is in a natural habitat, his flow of behavior is natural and not forced.
2. The studies have gained better ecological validity than the controlled observation method
3. The naturalistic observation method is used by the researchers to create new ideas. The researcher has the chance to observe the total situation and can find avenues that other people have not thought about

Limitations of naturalistic observation methods

1. The naturalistic observation method facilitates observations on a micro-scale. It often lacks a representative sample and thus cannot help the researcher in making a generalization that relates to a broader society
2. In this type of observation method, the researcher needs proper training to recognize aspects that are significant and worth attention.
3. The observations through naturalistic observation method are not as reliable as the researcher wants them to be because it is not possible to control some variables. This is why other researchers cannot similarly repeat the study or research.
4. Establishing the cause and effect relationship is not possible because the researcher cannot manipulate the variables

3) Participant observations

The participant observation method is often considered a variant of the naturalistic observation method because it has some similarities with it. The point of difference is that the researcher is not a distant observer anymore because he has joined the participants and become a part of their group. He does this to get a more in-depth and greater insight into their lives.

The researcher interacts with other members of the group freely, participates in their activities, studies their behavior and acquires a different way of life. Participant observation can be overt or covert.

1. Overt –When the researcher asks permission from a group to mingle the observation method is known as overt. He does so by revealing his true purpose and real identity to the group with whom he wants to mingle
2. Covert– When the researcher does not show either his true identity or real meaning to the group he wants to join then the observation is known as covert. He keeps both concealed and takes on a false role and identity to enter and mingle in the group. He generally acts as if he is a genuine member of that group

Advantages of Participant Observation methods

1. It is easy to study and observe the natural behavior of the participants in the group by becoming a part of that group. The respondents generally do not know that they are being observed and behavior recorded, so they are not restrained or constrained in their activities and behavior
2. The researcher becomes understanding by following the events of the respondents from such a close angle.
3. During the participant observation method, the researcher develops a good and healthy relationship with the respondents. This rapport helps him to participate in all the activities and make observations with a detached mind
4. The participant observation method helps the research to observe the actual behavior of the respondents and create an inclusive and intensive case study of that group
5. Actual participation in the activities provides the researcher with an opportunity to converse freely with other members about various events, their meaning and their importance to them. He gains an in-depth knowledge which would not have been possible only by observation.

Limitations of Participant Observation methods

1. It is challenging to work undercover. For example, the researcher will have only to observe and not record in front of others because he will not want to blow his cover. He relies heavily on his memory which can be faulty at times
2. Sometimes the researcher becomes too involved in the intricacies of that group. There is a higher chance of losing his objectivity because his reporting will be selective and dependent on his memory
3. The emotional participation of the researcher can result in bias interpretation. He will be influenced to some degree and a time might come when he would start supporting them unconditionally because their views and behavior will ultimately become his. This will result in a personal viewpoint of the scenario and not an objective or scientific report
4. In the participant observation method, the researcher’s experience becomes intense because of his proximity to the group members but the range becomes limited
5. The researcher misses many vital points because of his familiarity
6. Proximity with the group will involve him in group factionalism, and he will have to take sides. He then loses his objectivity as an impartial observer with whom everyone is ready to cooperate.

Advantages of Observation Method

• Provides direct access to research phenomena
• By observing firsthand, the researcher can collect, check and record accurate data
• Greater flexibility in terms of application
• Generate a permanent record of phenomena and the researcher or others can refer with it later
• The organization method is one of the simplest methods of data collection. It does not require too much technical knowledge
• The observation method is one of the best ways to formulate a hypothesis. The researcher can observe and come to know about the activities, perceptions, likes and dislikes to form a theory on his subject
• Observation method is one of the most common methods used in all sciences and is very easy to follow and accept
• In some instances observation is the only available tool to collect essential data and information
• The observation method does not require the willingness of the participant to record. The researcher can observe from a distance and record his findings

Disadvantages of Observation Method

• Faces a severe disadvantage because it takes a longer time frame compared to other data collection methods
• There is a chance of higher observer bias in the observation method
• Several personal behaviors are not open for observation and this proves a limitation in case of observation method
• There is a higher chance of the observer influencing the behavior of a sample group elements
• Uncertainties of the event cannot determine the actual time when the event will take place, and this is why every occurrence that is open to observation cannot be observed
• Many of the incidents are abstract like love, affection and the researcher can’t gain an exact and correct account of those
• The social phenomena generalization made by observation are not considered reliable as it cannot be used for lab experiments
• In some cases, it is seen that two persons observing the same phenomena come at different results and this can lead to faulty perceptions
• Observation method is considered an expensive affair as it requires hard effort, plenty of time and high cost

The post Observation Methods – Definition, Types, Examples, Advantages appeared first on HKT Consultant.

A case study involves an up-close, in-depth, and detailed examination of a particular case or cases, within a real-world context. For example, case studies in medicine may focus on an individual patient or ailment; case studies in business might cover a particular firm’s strategy or a broader market; similarly, case studies in politics can range from a narrow happening over time (e.g., a specific political campaign) to an enormous undertaking (e.g., a World War).

Generally, a case study can highlight nearly any individual, group, organization, event, belief system, or action. A case study does not necessarily have to be one observation (N=1), but may include many observations (one or multiple individuals and entities across multiple time periods, all within the same case study).

Case study research has been extensively practiced in both the social and natural sciences.

Different Kinds of Case Studies, but a Common Definition

Our discussion has progressed without a formal definition of case studies. Moreover, commonly asked questions about case studies still have been unan­swered. For example, is

Comparing Case Studies with Other Research Methods in the Social Sciences

When and why would you want to do case studies on some topic? Should you consider doing an experiment instead? A survey? A history? An

The Case Study as a Research Method

Using case studies for research purposes remains one of the most challenging of all social science endeavors. The purpose of this book is to help

Case Study Designs

These general characteristics of research designs serve as a background for considering the specific designs for case studies. Four types of designs will be discussed,

Criteria for Judging the Quality of Research Designs

Because a research design is supposed to represent a logical set of statements, you also can judge the quality of any given design according to

General Approach to Designing Case Studies

In identifying the method for your research project, Chapter 1 has shown when you might choose to use the case study method, as opposed to

Preparation and Training for a Specific Case Study

1. Human Subjects Protection Some time between the completion of your design and the start of your data collection, you will need to show how

The Case Study Investigator: Desired Skills

Too many people are drawn to the case study strategy because they believe it is “easy.” Many social scientists—especially budding ones—think the case study strategy

Modest Advice in Selecting Case Study Designs

Now that you know how to define case study designs and are prepared to carry out design work, three pieces of advice may be offered.

The Pilot Case Study

Pilot cases may be conducted for several reasons unrelated to the criteria for selecting the final cases in the case study design. For example, the

Screening the Candidate “Cases” for Your Case Study

Another preparatory step is the final selection of the case(s) to be part of your case study. Sometimes, the selection is straightforward because you have

The Case Study Protocol

A case study protocol has only one thing in common with a survey question­naire: Both are directed at a single data point—either a single case

An Analytic Strategy in Case Study Research: More Than Familiarity with Analytic Tools

1. Need for an Analytic Strategy Introduction. The analysis of case study evidence is one of the least developed and most difficult aspects of doing

Three Principles of Data Collection in Case Study Method

The benefits from these six sources of evidence can be maximized if you fol­low three principles. These principles are relevant to all six sources and,

Six Sources of Case Study Evidence

The sources of evidence discussed here are the ones most commonly used in doing case studies: documentation, archival records, interviews, direct obser­vations, participant-observation, and physical

Targeting Case Study Reports

Giving some initial thought to your likely or preferred audience and reporting formats serves as a good starting point for composing your case study. It

Pressing for a High-Quality Analysis in Case Study Research

No matter what specific analytic strategy or techniques have been chosen, you must do everything to make sure that your analysis is of the highest

Five Analytic Techniques in Case Study Research

None of the analytic techniques should be considered easy to use, and all will need much practice to be used powerfully. Your objective should be

What Makes an Exemplary Case Study?

In all of case study research, one of the most challenging tasks is to define an exemplary case study. Although no direct evidence is available,

Procedures in Doing a Case Study Report

Every investigator should have a well-developed set of procedures for analyz­ing social science data and for composing an empirical report. Numerous texts offer good advice

Illustrative Structures for Case Study Compositions

The chapters, sections, subtopics, and other components of a report must be organized in some way, and this constitutes your case study report’s composi­tional structure.

Case Study Reports as Part of Larger, Mixed Methods Studies

Your completed case study may include data from other methods (e.g., surveys or quantitative analysis of archival data such as health status indicators). In particular,

Case Study Research Designs

As with other social science methods, no single research design dominates case study research. Case studies can use at least four types of designs. First, there may be a “no theory first” type of case study design, which is closely connected to Kathleen M. Eisenhardt’s methodological work. A second type of research design highlights the distinction between single- and multiple-case studies, following Robert K. Yin’s guidelines and extensive examples. A third design deals with a “social construction of reality”, represented by the work of Robert E. Stake. Finally, the design rationale for a case study may be to identify “anomalies”. A representative scholar of this design is Michael Burawoy. Each of these four designs may lead to different applications, and understanding their sometimes unique ontological and epistemological assumptions becomes important. However, although the designs can have substantial methodological differences, the designs also can be used in explicitly acknowledged combinations with each other.

While case studies can be intended to provide bounded explanations of single cases or phenomena, they are often intended to theoretical insights about the features of a broader population.

Case Selection and Structure

Case selection in case study research is generally intended to both find cases that are a representative sample and which have variations on the dimensions of theoretical interest. Using that is solely representative, such as an average or typical case is often not the richest in information. In clarifying lines of history and causation it is more useful to select subjects that offer an interesting, unusual or particularly revealing set of circumstances. A case selection that is based on representativeness will seldom be able to produce these kinds of insights.

While random selection of cases is a valid case selection strategy in large-N research, there is a consensus among scholars that it risks generating serious biases in small-N research. Cases should generally be chosen that have a high expected information gain. For example, outlier cases (those which are extreme, deviant or atypical) can reveal more information than the potentially representative case. A case may also be chosen because of the inherent interest of the case or the circumstances surrounding it. Alternatively it may be chosen because of researchers’ in-depth local knowledge; where researchers have this local knowledge they are in a position to “soak and poke” as Richard Fenno put it, and thereby to offer reasoned lines of explanation based on this rich knowledge of setting and circumstances.

Beyond decisions about case selection and the subject and object of the study, decisions need to be made about purpose, approach and process in the case study. Gary Thomas thus proposes a typology for the case study wherein purposes are first identified (evaluative or exploratory), then approaches are delineated (theory-testing, theory-building or illustrative), then processes are decided upon, with a principal choice being between whether the study is to be single or multiple, and choices also about whether the study is to be retrospective, snapshot or diachronic, and whether it is nested, parallel or sequential.

John Gerring and Jason Seawright list seven case selection strategies:

Typical cases are cases that exemplify a stable cross-case relationship. These cases are representative of the larger population of cases, and the purpose of the study is to look within the case rather than compare it with other cases.

1. Diverse cases are cases that have variation on the relevant X and Y variables. Due to the range of variation on the relevant variables, these cases are representative of the full population of cases.
2. Extreme cases are cases that have an extreme value on the X or Y variable relative to other cases.
3. Deviant cases are cases that defy existing theories and common sense. They not only have extreme values on X or Y (like extreme cases), but defy existing knowledge about causal relations.
4. Influential cases are cases that are central to a model or theory (for example, Nazi Germany in theories of fascism and the far-right).
5. Most similar cases are cases that are similar on all the independent variables, except the one of interest to the researcher.
6. Most different cases are cases that are different on all the independent variables, except the one of interest to the researcher.

For theoretical discovery, Jason Seawright recommends using deviant cases or extreme cases that have an extreme value on the X variable.

Arend Lijphart, and Harry Eckstein identified five types of case study research designs (depending on the research objectives), Alexander George and Andrew Bennett added a sixth category:

1. In atheoretical (or configurative idiographic) case studies the goal is to describe a case very well, but not to contribute to a theory.
2. In interpretative (or disciplined configurative) case studies the goal is to use established theories to explain a specific case.
3. In hypothesis-generating (or heuristic) case studies the goal is to inductively identify new variables, hypotheses, causal mechanisms and causal paths.
4. In theory testing case studies the goal is to assess the validity and scope conditions of existing theories.
5. In plausibility probes the goal is to assess the plausibility of new hypotheses and theories.
6. In building block studies of types or subtypes the goal is to identify common patterns across cases.

In terms of case selection, Gary King, Robert Keohane, and Sidney Verba warn against “selecting on the dependent variable”. They argue for example that researchers cannot make valid causal inferences about war outbreak by only looking at instances where war did happen (the researcher should also look at cases where war did not happen). Scholars of qualitative methods have disputed this claim, however. They argue that selecting on the dependent variable can be useful depending on the purposes of the research.

King, Keohane and Verba argue that there is no methodological problem in selecting on the explanatory variable, however. They do warn about multicollinearity (choosing two or more explanatory variables that perfectly correlate with each other).

Uses and Limits

Uses

Case studies have commonly been seen as a fruitful way to come up hypotheses and generate theories. Case studies are also useful for formulating concepts, which are an important aspect of theory construction. The concepts used in qualitative research will tend to have higher conceptual validity than concepts used in quantitative research (due to conceptual stretching: the unintentional comparison of dissimilar cases). Case studies add descriptive richness. Case studies are suited to explain outcomes in individual cases, which is something that quantitative methods are less equipped to do. Through fine-gained knowledge and description, case studies can fully specify the causal mechanisms in a way that may be harder in a large-N study. In terms of identifying “causal mechanisms”, some scholars distinguish between “weak” and “strong chains”. Strong chains actively connect elements of the causal chain to produce an outcome whereas weak chains are just intervening variables.

Case studies of cases that defy existing theoretical expectations may contribute knowledge by delineating why the cases violate theoretical predictions and specifying the scope conditions of the theory Case studies are useful in situations of causal complexity where there is equifinality, complex interaction effects and path dependency Case studies can identify necessary and insufficient conditions, as well as complex combinations of necessary and sufficient conditions. They argue that case studies may also be useful in identifying the scope conditions of a theory: whether variables are sufficient or necessary to bring about an outcome.

Limitations

Designing Social Inquiry, an influential 1994 book written by Gary King, Robert Keohane, and Sidney Verba, primarily applies lessons from regression-oriented analysis to qualitative research, arguing that the same logics of causal inference can be used in both types of research. The authors’ recommendation is to increase the number of observations (a recommendation that Barbara Geddes also makes in Paradigms and Sand Castles), because few observations make it harder to estimate multiple causal effects, as well as increase the risk that there is measurement error, and that an event in a single case was caused by random error or unobservable factors. KKV sees process-tracing and qualitative research as being “unable to yield strong causal inference” due to the fact that qualitative scholars would struggle with determining which of many intervening variables truly links the independent variable with a dependent variable. The primary problem is that qualitative research lacks a sufficient number of observations to properly estimate the effects of an independent variable. They write that the number of observations could be increased through various means, but that would simultaneously lead to another problem: that the number of variables would increase and thus reduce degrees of freedom.

The purported “degrees of freedom” problem that KKV identify is widely considered flawed; while quantitative scholars try to aggregate variables to reduce the number of variables and thus increase the degrees of freedom, qualitative scholars intentionally want their variables to have many different attributes and complexity. For example, James Mahoney writes, “the Bayesian nature of process tracing explains why it is inappropriate to view qualitative research as suffering from a small-N problem and certain standard causal identification problems.” By using Bayesian probability, it may be possible to makes strong causal inferences from a small sliver of data.

A commonly described limit of case studies is that they do not lend themselves to generalizability. Some scholars, such as Bent Flyvbjerg, have pushed back on that notion.

As small-N research should not rely on random sampling, scholars must be careful in avoiding selection bias when picking suitable cases. A common criticism of qualitative scholarship is that cases are chosen because they are consistent with the scholar’s preconceived notions, resulting in biased research.

Alexander George and Andrew Bennett note that a common problem in case study research is that of reconciling conflicting interpretations of the same data.

The post Case Study Methodology in Management Research appeared first on HKT Consultant.

Definition

Action research is known by many other names, including participatory research, collaborative inquiry, emancipatory research, action learning, and contextual action research, but all are variations on a theme. Put simply, action research is “learning by doing” – a group of people identify a problem, do something to resolve it, see how successful their efforts were, and if not satisfied, try again.  While this is the essence of the approach, there are other key attributes of action research that differentiate it from common problem-solving activities that we all engage in every day.  A more succinct definition is,

“Action research…aims to contribute both to the practical concerns of people in an immediate problematic situation and to further the goals of social science simultaneously.  Thus, there is a dual commitment in action research to study a system and concurrently to collaborate with members of the system in changing it in what is together regarded as a desirable direction.  Accomplishing this twin goal requires the active collaboration of researcher and client, and thus it stresses the importance of co-learning as a primary aspect of the research process.”

What separates this type of research from general professional practices, consulting, or daily problem-solving is the emphasis on scientific study, which is to say the researcher studies the problem systematically and ensures the intervention is informed by theoretical considerations.  Much of the researcher’s time is spent on refining the methodological tools to suit the exigencies of the situation, and on collecting, analyzing, and presenting data on an ongoing, cyclical basis.

Several attributes separate action research from other types of research.  Primary is its focus on turning the people involved into researchers, too – people learn best, and more willingly apply what they have learned, when they do it themselves.  It also has a social dimension – the research takes place in real-world situations, and aims to solve real problems.  Finally, the initiating researcher, unlike in other disciplines, makes no attempt to remain objective, but openly acknowledges their bias to the other participants.

The Action Research Process

Stephen Kemmis has developed a simple model of the cyclical nature of the typical action research process (Figure 1).  Each cycle has four steps: plan, act, observe, reflect.

Figure 1 Simple Action Research Model

(from MacIsaac, 1995)

Gerald Susman (1983) gives a somewhat more elaborate listing.  He distinguishes five phases to be conducted within each research cycle (Figure 2).  Initially, a problem is identified and data is collected for a more detailed diagnosis.  This is followed by a collective postulation of several possible solutions, from which a single plan of action emerges and is implemented.  Data on the results of the intervention are collected and analyzed, and the findings are interpreted in light of how successful the action has been.  At this point, the problem is re-assessed and the process begins another cycle.  This process continues until the problem is resolved.

Figure 2 Detailed Action Research Model

(adapted from Susman 1983)

Principles of Action Research

What gives action research its unique flavour is the set of principles that guide the research.  Winter (1989) provides a comprehensive overview of six key principles.

1) Reflexive critique

An account of a situation, such as notes, transcripts or official documents, will make implicit claims to be authoritative, i.e., it implies that it is factual and true.  Truth in a social setting, however, is relative to the teller.  The principle of reflective critique ensures people reflect on issues and processes and make explicit the interpretations, biases, assumptions and concerns upon which judgments are made.  In this way, practical accounts can give rise to theoretical considerations.

2) Dialectical critique

Reality, particularly social reality, is consensually validated, which is to say it is shared through language.  Phenomena are conceptualized in dialogue, therefore a dialectical critique is required to understand the set of relationships both between the phenomenon and its context, and between the elements constituting the phenomenon.  The key elements to focus attention on are those constituent elements that are unstable, or in opposition to one another.  These are the ones that are most likely to create changes.

3) Collaborative Resource

Participants in an action research project are co-researchers.  The principle of collaborative resource presupposes that each person’s ideas are equally significant as potential resources for creating interpretive categories of analysis, negotiated among the participants.  It strives to avoid the skewing of credibility stemming from the prior status of an idea-holder.  It especially makes possible the insights gleaned from noting the contradictions both between many viewpoints and within a single viewpoint

4) Risk

The change process potentially threatens all previously established ways of doing things, thus creating psychic fears among the practitioners.  One of the more prominent fears comes from the risk to ego stemming from open discussion of one’s interpretations, ideas, and judgments.  Initiators of action research will use this principle to allay others’ fears and invite participation by pointing out that they, too, will be subject to the same process, and that whatever the outcome, learning will take place.

5) Plural Structure

The nature of the research embodies a multiplicity of views, commentaries and critiques, leading to multiple possible actions and interpretations.  This plural structure of inquiry requires a plural text for reporting.  This means that there will be many accounts made explicit, with commentaries on their contradictions, and a range of options for action presented.  A report, therefore, acts as a support for ongoing discussion among collaborators, rather than a final conclusion of fact.

6) Theory, Practice, Transformation

For action researchers, theory informs practice, practice refines theory, in a continuous transformation.  In any setting, people’s actions are based on implicitly held assumptions, theories and hypotheses, and with every observed result, theoretical knowledge is enhanced.  The two are intertwined aspects of a single change process.  It is up to the researchers to make explicit the theoretical justifications for the actions, and to question the bases of those justifications.  The ensuing practical applications that follow are subjected to further analysis, in a transformative cycle that continuously alternates emphasis between theory and practice.

When is Action Research used?

Action research is used in real situations, rather than in contrived, experimental studies, since its primary focus is on solving real problems.  It can, however, be used by social scientists for preliminary or pilot research, especially when the situation is too ambiguous to frame a precise research question.  Mostly, though, in accordance with its principles, it is chosen when circumstances require flexibility, the involvement of the people in the research, or change must take place quickly or holistically.

It is often the case that those who apply this approach are practitioners who wish to improve understanding of their practice, social change activists trying to mount an action campaign, or, more likely, academics who have been invited into an organization (or other domain) by decision-makers aware of a problem requiring action research, but lacking the requisite methodological knowledge to deal with it.

Situating Action Research in a Research Paradigm

Positivist Paradigm

The main research paradigm for the past several centuries has been that of Logical Positivism.  This paradigm is based on a number of principles, including: a belief in an objective reality, knowledge of which is only gained from sense data that can be directly experienced and verified between independent observers.  Phenomena are subject to natural laws that humans discover in a logical manner through empirical testing, using inductive and deductive hypotheses derived from a body of scientific theory. Its methods rely heavily on quantitative measures, with relationships among variables commonly shown by mathematical means.  Positivism, used in scientific and applied research, has been considered by many to be the antithesis of the principles of action research (Susman and Evered 1978, Winter 1989).

Interpretive Paradigm

Over the last half century, a new research paradigm has emerged in the social sciences to break out of the constraints imposed by positivism.  With its emphasis on the relationship between socially-engendered concept formation and language, it can be referred to as the Interpretive paradigm.  Containing such qualitative methodological approaches as phenomenology, ethnography, and hermeneutics, it is characterized by a belief in a socially constructed, subjectively-based reality, one that is influenced by culture and history.  Nonetheless it still retains the ideals of researcher objectivity, and researcher as passive collector and expert interpreter of data.

Paradigm of Praxis

Though sharing a number of perspectives with the interpretive paradigm, and making considerable use of its related qualitative methodologies, there are some researchers who feel that neither it nor the positivist paradigms are sufficient epistemological structures under which to place action research (Lather 1986, Morley 1991).  Rather, a paradigm of Praxis is seen as where the main affinities lie.  Praxis, a term used by Aristotle, is the art of acting upon the conditions one faces in order to change them.  It deals with the disciplines and activities predominant in the ethical and political lives of people. Aristotle contrasted this with Theoria – those sciences and activities that are concerned with knowing for its own sake.  Both are equally needed he thought.  That knowledge is derived from practice, and practice informed by knowledge, in an ongoing process, is a cornerstone of action research.  Action researchers also reject the notion of researcher neutrality, understanding that the most active researcher is often one who has most at stake in resolving a problematic situation.

Evolution of Action Research

Origins in late 1940s

Kurt Lewin is generally considered the ‘father’ of action research.  A German social and experimental psychologist, and one of the founders of the Gestalt school, he was concerned with social problems, and focused on participative group processes for addressing conflict, crises, and change, generally within organizations.  Initially, he was associated with the Center for Group Dynamics at MIT in Boston, but soon went on to establish his own National Training Laboratories.

Lewin first coined the term ‘action research’ in his 1946 paper “Action Research and Minority Problems”,[v] characterizing Action Research as “a comparative research on the conditions and effects of various forms of social action and research leading to social action”, using a process of  “a spiral of steps, each of which is composed of a circle of planning, action, and fact-finding about the result of the action”.

Eric Trist, another major contributor to the field from that immediate post-war era, was a social psychiatrist whose group at the Tavistock Institute of Human Relations in London engaged in applied social research, initially for the civil repatriation of German prisoners of war. He and his colleagues tended to focus more on large-scale, multi-organizational problems.

Both Lewin and Trist applied their research to systemic change in and between organizations.  They emphasized direct professional – client collaboration and affirmed the role of group relations as basis for problem-solving.  Both were avid proponents of the principle that decisions are best implemented by those who help make them.

Current Types of Action Research

By the mid-1970s, the field had evolved, revealing 4 main ‘streams’ that had emerged: traditional, contextural (action learning), radical, and educational action research.

Traditional Action Research

Traditional Action Research stemmed from Lewin’s work within organizations and encompasses the concepts and practices of Field Theory, Group Dynamics, T-Groups, and the Clinical Model.  The growing importance of labour-management relations led to the application of action research in the areas of Organization Development, Quality of Working Life (QWL), Socio-technical systems (e.g., Information Systems), and Organizational Democracy.  This traditional approach tends toward the conservative, generally maintaining the status quo with regards to organizational power structures.

Contextural Action Research (Action Learning)

Contextural Action Research, also sometimes referred to as Action Learning, is an approach derived from Trist’s work on relations between organizations.  It is contextural, insofar as it entails reconstituting the structural relations among actors in a social environment; domain-based, in that it tries to involve all affected parties and stakeholders; holographic, as each participant understands the working of the whole; and it stresses that participants act as project designers and co-researchers.  The concept of organizational ecology, and the use of search conferences come out of contextural action research, which is more of a liberal philosophy, with social transformation occurring by consensus and normative incrementalism.

Radical Action Research

The Radical stream, which has its roots in Marxian ‘dialectical materialism’ and the praxis orientations of Antonio Gramsci, has a strong focus on emancipation and the overcoming of power imbalances.  Participatory Action Research, often found in liberationist movements and international development circles, and Feminist Action Research both strive for social transformation via an advocacy process to strengthen peripheral groups in society.

Educational Action Research

A fourth stream, that of Educational Action Research, has its foundations in the writings of John Dewey, the great American educational philosopher of the 1920s and 30s, who believed that professional educators should become involved in community problem-solving.  Its practitioners, not surprisingly, operate mainly out of educational institutions, and focus on development of curriculum, professional development, and applying learning in a social context.  It is often the case that university-based action researchers work with primary and secondary school teachers and students on community projects.

Action Research, Applied Research, and Qualitative Versus Quantitative Research

Action research refers to the conjunction of three elements: action, research, and participation. Unless all three elements are present, the process may be useful but

General Overviews of Action Research Are Hard to Find

We decided to write a general overview of AR because of our experience with university students and practitioners encountering the subject for the first time.

Action Research Defined

Action research is social research carried out by a team that encompasses a professional action researcher and the members of an organization, commu- nity, or

Our Take on AR: Pragmatic Action Research

Our experience is predominantly, though not exclusively, in industrial, com­munity, and higher education settings in Europe and the United States. Davydd Greenwood is an anthropologist

Action Research, the Disciplines, and Coverage

As noted earlier, AR is not a discipline. It involves practitioners from anthro­pology, development studies, education, engineering, gender studies, human services, psychology, human services, social

Action, Research, and Participation

Despite the significant differences among AR practitioners and their life situa­tions, we believe that several important commitments link most of us. AR is composed of

General Systems Theory

One stream of scientific ideas and concepts relevant to AR comes from a loosely integrated field that is known as “general systems theory” (GST), a

Defining Scientific Research

To anchor our discussion, we define scientific research as investigative activity capable of discovering that the world is or is not organized as our preconceptions

Action Research Cases of Cornell University’s School of Industrial and Labor Relations: Research and Extension

During one period in its history, Programs for Employment and Workplace Systems (PEWS) in the Extension Division of the School of Industrial and Labor Relations

Action Research Cases of Mondragon: Organizational Problems in Industrial Cooperatives

The Mondrag6n Cooperatives in Spain are one of the most successful examples of industrial democracy anywhere and are the subject of worldwide attention and debate.

Action Research Cases of Stongfjorden: Village Development in Western Norway

Sailing south along the Norwegian coast and passing the westernmost reach of the mainland, one sees a narrow, short fjord reaching 3 miles inland. Stongfjorden

A History of Action Research

History can be written in many ways, and no one ever writes the history. Our intention in this chapter is to present a genealogy of

Political Economy and the Social Structure of Science

Underlying what we have said is a set of ideas about power relationships in our society. AR is about the transformation of power relationships in

Readdressing the Action Research Processes

We argued that relevant actions to solve the problem at hand are the first out­come of an AR process. We also argued that the meaning

Credibility and Validity in Action Research Inquiry

Credibility and validity in conventional social science research function as the researchers’ amulet. In a world of confusing information, these practitioners seem to find comfort

The Action Research Inquiry Process Is Thus Inevitably Linked to Action

Knowledge emerges and is evaluated through acting or as a consequence of actions. The discovery process is not purely mental, receding into the intellec­tual sphere

Epistemological Foundations of Action Research

The presentations of GST and pragmatism connect directly to AR. AR aims to solve pertinent problems in a given context through a democratic inquiry where

Pragmatic Philosophy and Action Research

That a stereotypical view of science prevails among nonscientists does not mean that the world is or has been unaware of the perspectives we articulate

Action Research Is Not Merely “Qualitative Research”

We asserted at the outset that it is wrong to think of AR as “qualitative” research, yet a great many conventional researchers and far too

The Cogenerative Model

AR can be thought of as a process consisting of at least two analytically distinct phases. The first involves the clarification of an initial research

Conventional Social Research and Action Research

To organize this discussion, we begin by paralleling our treatment of conven­tional social science with our presentation of AR. We say much less about conventional

Science Is Humans in Action

There is much to learn from this story, but we want to stress the social and cul­tural dimensions of scientific activity that are revealed by

Physical and Biological Science as Iterative Cycles of Thought and Action

The episode that we recount here happened to Greenwood 25 years ago. He has retold the story often enough that, in the way of narratives,

Can Action Research Produce Scientifically Meaningful Results of Action Research?

We begin with a review of the standard criticism that AR is unscientific. Some of our AR colleagues address this issue by accepting the idea

Action Researcher: Creating Possibilities Rather Than Reinforcing Limits

The dominant imagery in conventional social research comes, for very good historical and political economic reasons, from the language of bureaucratic organizations. These organizations constantly

Action Researcher: Not Trying to Overcome an Unruly World

As we defined it earlier, action research is a cogenerative process through which professional researchers and interested members of a local organization, com­munity, or a

Writing Up Action Research

A secondary effect of applying the concept of a dialectic as a way of conceptu­alizing knowledge generation in AR is that it introduces the dynamics

The Knowledge Generation Process of Action Research

We argue that AR, in addition to generating valid knowledge and effective social action, embodies democratic ideals in its core practices. This democratization is involved

Local Knowledge and Professional Social Science Research Knowledge of Action Research

In AR, professional social researchers and insider community, organization, or network members are cosubjects and coresearchers in the research process. Both contribute many kinds ofknowledge

Workability and Explanation of Action Research

While many of the techniques used in AR and some of the operations that take place in AR projects are familiar to experienced social researchers,

Searching for Pragmatic Action Research

Although we argue strongly for pragmatic, multi-method techniques and work forms, and we have employed many different kinds of techniques and work forms in our

Constructing Arenas for Dialogue in Pragmatic Action Research

For us, the core element in pragmatic AR is the creation of arenas where discussion and collaborative research facilitate cogenerative learning. The encounter between local

Becoming an Action Researcher

In Part 4 of this book, we take up the education of action researchers in detail. Here, we briefly rehearse some of our central contentions.

The Friendly Outsider

In addition to the general orientation to skills we have articulated, we wish to point briefly to certain specific skills that AR practitioners must master

Practices and Skills of the Action Researcher

Up till now we have portrayed the situation of the professional action researchers in fairly abstract terms. From here forward, we become more concrete. 1.

Linking Theory and Local Understanding: Being Scientific, Counterintuitive, and Technically Competent

In conventional social research, expert knowledge is the basis of the high sta­tus of the researcher and his or her ability to impose controls and

Frameworks of Educational Action Research

Though not all AR-relevant educational work deals with adult education, one of the peculiarities of this field is that it seems that the major intellectual

Feminist Analyses of Inequality and Development in Pragmatic Action Research

In our teaching experience over the past decade, after we have laid out the basic perspectives of AR, students ask about the relationship between feminism

Educational Strategies in Pragmatic Action Research

One of the most important and frequent paths leading people into the practice of action research (AR) has been through the field of education5 in

Participatory Research and Southern Pragmatic Action Research

We begin with an analysis of participatory research (PR) and participatory action research (PAR), a set of approaches that came into existence as a critique

Planning and Executing a Pragmatic Action Search

1. COMMISSIONING THE SEARCH CONFERENCE The first step in searching is working with the local actors who want to commission a search. This discussion is

Preparing for the Pragmatic Action Search

Many roads lead to a search conference. In some cases, the local actors are familiar with search conferences and accordingly know what they are looking

Source: O’Brien, R. (2001). Um exame da abordagem metodológica da pesquisa ação [An Overview of the Methodological Approach of Action Research]. In  Roberto Richardson (Ed.), Teoria e Prática da Pesquisa Ação [Theory and Practice of Action Research]. João Pessoa, Brazil: Universidade Federal da Paraíba. (English version) Available: http://www.web.ca/~robrien/papers/arfinal.html (Accessed 20/1/2002)

The post Overview of Action Research Methodology appeared first on HKT Consultant.

Sources of data could be from interviews, open-ended questions, field research notes, conversations, or literally any occurrence of communicative language (such as books, essays, discussions, newspaper headlines, speeches, media, historical documents). A single study may analyze various forms of text in its analysis. To analyze the text using content analysis, the text must be coded, or broken down, into manageable code categories for analysis (i.e. “codes”). Once the text is coded into code categories, the codes can then be further categorized into “code categories” to summarize data even further.

Computerized Content Analysis

The increasing availability of written information on computer files, and the increasing number of computer programs to analyze text files, makes content analysis easier to

The Uses of Content Analysis

Here are several ways in which GAO evaluators have successfully used content analysis techniques. In Stars and Stripes: Inherent Conflicts Lead to Allegations of Military

A Definition of Content Analysis

In content analysis, evaluators classify the key ideas in a written communication, such as a report, article, or film. Evaluators can do content analysis of

How to Apply Content Analysis

GAO evaluators can use content analysis to articulate a program’s objectives, describe its activities, and determine its results. 1. Program Objectives Many evaluations characterize a

Some Disadvantages of Content Analysis

Because content analysis is systematic, sufficient human resources must be committed to it and rigorously applied to it. This may mean, for some evaluation applications,

Some Advantages of Content Analysis

1. It Can Be Unobtrusive One problem with surveys and some experimental methods is that evaluators and their informants can interact during data collection in

Defining the Variables in Content Analysis

The assignment’s evaluation questions lead directly to the relevant variables. In the Stars and Stripes example, we asked “To what extent does the content of

Resources Needed in Content Analysis

In content analysis, evaluators must consider three principal types of resources: an analyst with the technical knowledge and experience to plan and direct the content

Kinds of Analysis Required in Content Analysis

Considering data requirements goes hand in hand with analysis requirements. In many evaluations, the most important, or only, form of analysis may be a simple

Kinds of Data Required for Content Analysis

In the early stages of an assignment, evaluators choose variables of interest. For the descriptive Stars and Stripes assignment, for example, important variables included the

Data Available or to Be Collected for Content Analysis

Whether or not content analysis is appropriate depends on the nature of the information to be evaluated. The information can be anything written: an original

Assignment Objectives of Content Analysis

GAO often expresses an assignment’s objectives in the form of three broad categories of evaluation question: descriptive, normative, or impact questions. (GAO, 1991c) In theory,

Coder Selection and Training in Content Analysis

Coding is generally quicker and more accurate and credible the more expertise coders have in the subject of the material being analyzed. For example, in

Coding Options in Content Analysis

Textual material can be coded directly on the computer or it can be coded manually and transferred clerically to electronic media. With the latter option,

Creating Codes in Content Analysis

Codes are simply abbreviations, or tags, for segments of text. Before evaluators can code a document, they must first create a code for each variable’s

Developing an Analysis Plan in Content Analysis

Developing a plan for an analysis is the final planning step. It finks the data back to the evaluation question. Traditionally, most content analyses have

Defining the Recording Unit for Content Analysis

Once evaluators have defined the variables and selected the textual material, their next major task is to define the recording units. A recording unit is

Selecting Material for Analysis in Content Analysis

To select textual material to include in the content analysis, evaluators may find it easiest to think first about a population of documents. For some

Estimating Reliability of Content Analysis

When several coders code the documents, then- consistency is important. If the coders differ substantially, then the results of the content analysis become questionable. Chapter

Preparing for Data Analysis in Content Analysis

The basic analytic task in content analysis is to count the occurrence of codes, whether all occurrences of a given category (for example, all occurrences

Using a Computer to Code in Content Analysis

This section assumes that the documents to be coded are available in a word processing format such as WordPerfect and that coding proceeds with the

Applying Codes in Content Analysis

In manual coding on hard-copy documents, the coder simply marks the boundaries of the recording unit and writes the code in the margin of the

Selecting and Managing Documents in Content Analysis

1. Using All the Documents Even though the population of documents may seem conceptually clear, assembling them for coding generally has three problems: missing documents,

The Potential for Coding Error in Content Analysis

The four interrelated potential sources of coding inaccuracy in most applications of content analysis are (1) deficiencies in the documents, (2) ambiguity in the judgment

Analyzing and Reporting the Data in Content Analysis

1. Cross-Check Preliminary Results Things are not always what they seem. Try to verify findings by using related variables or slightly different analysis methods. This

Coding in Content Analysis

1. Produce a Coding Manual A good coding manual is indispensable. AvoSrf the temptation to save time by not producing one or by producing only

Planning the Content Analysis

1. Be Clear About the Questions The evaluation questions drive the study. If they are Questions ambiguous or not suited to the users’ needs, even a

Reporting the Methodology and Results of Content Analysis

The methodology and results of a content analysis should be reported the way they are for other evaluations. The methodology should be described in sufficient

Finding Associations in Content Analysis

Beyond simply counting, evaluators might look for an association between two or more variables. In the Stars and Stripes assignment, the frequency of news articles

Counting a Code’s Frequency in Content Analysis

Drawing inferences from the frequency of codes is the simplest and often the most useful form of data analysis. Drawing conclusions in the Stars and

Intercoder Reliability in Content Analysis

An important measure forjudging the quality of a content analysis is the extent to which the results can be reproduced. Known as intercoder reliability, this

Software for Content Analysis

This appendix describes computer software that may be useful to content analysis. The list of programs here is by no means complete, and it is

Analysis of Qualitative Data in Content Analysis

Content analysis applies to textual information in the form of words. An analyst can classify text into categories as described in chapter 1. The categories

Quantitative content analysis highlights frequency counts and objective analysis of these coded frequencies. Additionally, quantitative content analysis begins with a framed hypothesis with coding decided on before the analysis begins. These coding categories are strictly relevant to the researcher’s hypothesis. Quantitative analysis also takes a deductive approach.

Siegfried Kracauer provides a critique of quantitative analysis, asserting that it oversimplifies complex communications in order to be more reliable. On the other hand, qualitative analysis deals with the intricacies of latent interpretations, whereas quantitative has a focus on manifest meanings. He also acknowledges an “overlap” of qualitative and quantitative content analysis. Patterns are looked at more closely in qualitative analysis, and based on the latent meanings that the researcher may find, the course of the research could be changed. It is inductive and begins with open research questions, as opposed to a hypothesis.

Three different definition of content analysis are provided below.

• Definition 1: “Any technique for making inferences by systematically and objectively identifying special characteristics of messages.” (from Holsti, 1968)
• Definition 2: “An interpretive and naturalistic approach. It is both observational and narrative in nature and relies less on the experimental elements normally associated with scientific research (reliability, validity and generalizability) (from Ethnography, Observational Research, and Narrative Inquiry, 1994-2012).
• Definition 3: “A research technique for the objective, systematic and quantitative description of the manifest content of communication.” (from Berelson, 1952)

Uses of Content Analysis

• Identify the intentions, focus or communication trends of an individual, group or institution
• Describe attitudinal and behavioral responses to communications
• Determine psychological or emotional state of persons or groups
• Reveal international differences in communication content
• Reveal patterns in communication content
• Pre-test and improve an intervention or survey prior to launch
• Analyze focus group interviews and open-ended questions to complement quantitative data

Types of Content Analysis

There are two general types of content analysis: conceptual analysis and relational analysis. Conceptual analysis determines the existence and frequency of concepts in a text. Relational analysis develops the conceptual analysis further by examining the relationships among concepts in a text. Each type of analysis may lead to different results, conclusions, interpretations and meanings.

Conceptual Analysis

Typically people think of conceptual analysis when they think of content analysis. In conceptual analysis, a concept is chosen for examination and the analysis involves quantifying and counting its presence. The main goal is to examine the occurrence of selected terms in the data. Terms may be explicit or implicit. Explicit terms are easy to identify. Coding of implicit terms is more complicated: you need to decide the level of implication and base judgments on subjectivity (issue for reliability and validity). Therefore, coding of implicit terms involves using a dictionary or contextual translation rules or both.

To begin a conceptual content analysis, first identify the research question and choose a sample or samples for analysis. Next, the text must be coded into manageable content categories. This is basically a process of selective reduction. By reducing the text to categories, the researcher can focus on and code for specific words or patterns that inform the research question.

General steps for conducting a conceptual content analysis:

1. Decide the level of analysis: word, word sense, phrase, sentence, themes

2. Decide how many concepts to code for: develop pre-defined or interactive set of categories or concepts. Decide either: A. to allow flexibility to add categories through the coding process, or B. to stick with the pre-defined set of categories.

• Option A allows for the introduction and analysis of new and important material that could have significant implications to one’s research question.
• Option B allows the researcher to stay focused and examine the data for specific concepts.

3. Decide whether to code for existence or frequency of a concept. The decision changes the coding process.

• When coding for the existence of a concept, the researcher would count a concept only once if it appeared at least once in the data and no matter how many times it appeared.
• When coding for the frequency of a concept, the researcher would count the number of times a concept appears in a text.

4. Decide on how you will distinguish among concepts:

• Should text be coded exactly as they appear or coded as the same when they appear in different forms? For example, “dangerous” vs. “dangerousness”. The point here is to create coding rules so that these word segments are transparently categorized in a logical fashion. The rules could make all of these word segments fall into the same category, or perhaps the rules can be formulated so that the researcher can distinguish these word segments into separate codes.
• What level of implication is to be allowed? Words that imply the concept or words that explicitly state the concept? For example, “dangerous” vs. “the person is scary” vs. “that person could cause harm to me”. These word segments may not merit separate categories, due the implicit meaning of “dangerous”.

5. Develop rules for coding your texts. After decisions of steps 1-4 are complete, a researcher can begin developing rules for translation of text into codes. This will keep the coding process organized and consistent. The researcher can code for exactly what he/she wants to code. Validity of the coding process is ensured when the researcher is consistent and coherent in their codes, meaning that they follow their translation rules. In content analysis, obeying by the translation rules is equivalent to validity.

6. Decide what to do with irrelevant information: should this be ignored (e.g. common English words like “the” and “and”), or used to reexamine the coding scheme in the case that it would add to the outcome of coding?

7. Code the text: This can be done by hand or by using software. By using software, researchers can input categories and have coding done automatically, quickly and efficiently, by the software program. When coding is done by hand, a researcher can recognize error far more easily (e.g. typos, misspelling). If using computer coding, text could be cleaned of errors to include all available data. This decision of hand vs. computer coding is most relevant for implicit information where category preparation is essential for accurate coding.

8. Analyze your results: Draw conclusions and generalizations where possible. Determine what to do with irrelevant, unwanted or unused text: reexamine, ignore, or reassess the coding scheme. Interpret results carefully as conceptual content analysis can only quantify the information. Typically, general trends and patterns can be identified.

Relational Analysis

Relational analysis begins like conceptual analysis, where a concept is chosen for examination. However, the analysis involves exploring the relationships between concepts. Individual concepts are viewed as having no inherent meaning and rather the meaning is a product of the relationships among concepts.

To begin a relational content analysis, first identify a research question and choose a sample or samples for analysis. The research question must be focused so the concept types are not open to interpretation and can be summarized. Next, select text for analysis. Select text for analysis carefully by balancing having enough information for a thorough analysis so results are not limited with having information that is too extensive so that the coding process becomes too arduous and heavy to supply meaningful and worthwhile results.

There are three subcategories of relational analysis to choose from prior to going on to the general steps.

1. Affect extraction: an emotional evaluation of concepts explicit in a text. A challenge to this method is that emotions can vary across time, populations, and space. However, it could be effective at capturing the emotional and psychological state of the speaker or writer of the text.
2. Proximity analysis: an evaluation of the co-occurrence of explicit concepts in the text. Text is defined as a string of words called a “window” that is scanned for the co-occurrence of concepts. The result is the creation of a “concept matrix”, or a group of interrelated co-occurring concepts that would suggest an overall meaning.
3. Cognitive mapping: a visualization technique for either affect extraction or proximity analysis. Cognitive mapping attempts to create a model of the overall meaning of the text such as a graphic map that represents the relationships between concepts.

General steps for conducting a relational content analysis:

1. Determine the type of analysis: Once the sample has been selected, the researcher needs to determine what types of relationships to examine and the level of analysis: word, word sense, phrase, sentence, themes.
2. Reduce the text to categories and code for words or patterns. A researcher can code for existence of meanings or words.
3. Explore the relationship between concepts: once the words are coded, the text can be analyzed for the following:

• Strength of relationship: degree to which two or more concepts are related.
• Sign of relationship: are concepts positively or negatively related to each other?
• Direction of relationship: the types of relationship that categories exhibit. For example, “X implies Y” or “X occurs before Y” or “if X then Y” or if X is the primary motivator of Y.

4. Code the relationships: a difference between conceptual and relational analysis is that the statements or relationships between concepts are coded.
5. Perform statistical analyses: explore differences or look for relationships among the identified variables during coding.
6. Map out representations: such as decision mapping and mental models.

Reliability and Validity

Reliability: Because of the human nature of researchers, coding errors can never be eliminated but only minimized. Generally, 80% is an acceptable margin for reliability. Three criteria comprise the reliability of a content analysis:

1. Stability: the tendency for coders to consistently re-code the same data in the same way over a period of time.
2. Reproducibility: tendency for a group of coders to classify categories membership in the same way.
3. Accuracy: extent to which the classification of text corresponds to a standard or norm statistically.

Validity: Three criteria comprise the validity of a content analysis:

1. Closeness of categories: this can be achieved by utilizing multiple classifiers to arrive at an agreed upon definition of each specific category. Using multiple classifiers, a concept category that may be an explicit variable can be broadened to include synonyms or implicit variables.
2. Conclusions: What level of implication is allowable? Do conclusions correctly follow the data? Are results explainable by other phenomena? This becomes especially problematic when using computer software for analysis and distinguishing between synonyms. For example, the word “mine,” variously denotes a personal pronoun, an explosive device, and a deep hole in the ground from which ore is extracted. Software can obtain an accurate count of that word’s occurrence and frequency, but not be able to produce an accurate accounting of the meaning inherent in each particular usage. This problem could throw off one’s results and make any conclusion invalid.
3. Generalizability of the results to a theory: dependent on the clear definitions of concept categories, how they are determined and how reliable they are at measuring the idea one is seeking to measure. Generalizability parallels reliability as much of it depends on the three criteria for reliability.

Advantages of Content Analysis

• Directly examines communication using text
• Allows for both qualitative and quantitative analysis
• Provides valuable historical and cultural insights over time
• Allows a closeness to data
• Coded form of the text can be statistically analyzed
• Unobtrusive means of analyzing interactions
• Provides insight into complex models of human thought and language use
• When done well, is considered a relatively “exact” research method
• Content analysis is a readily-understood and an inexpensive research method
• A more powerful tool when combined with other research methods such as interviews, observation, and use of archival records. It is very useful for analyzing historical material, especially for documenting trends over time.

Disadvantages of Content Analysis

• Can be extremely time consuming
• Is subject to increased error, particularly when relational analysis is used to attain a higher level of interpretation
• Is often devoid of theoretical base, or attempts too liberally to draw meaningful inferences about the relationships and impacts implied in a study
• Is inherently reductive, particularly when dealing with complex texts
• Tends too often to simply consist of word counts
• Often disregards the context that produced the text, as well as the state of things after the text is produced

• Can be difficult to automate or computerize

The post Content Analysis Method and Examples appeared first on HKT Consultant.

Hermeneutic phenomenology

Hermeneutic phenomenology, also known as interpretive phenomenology, originates from the work of Martin Heidegger. Heidegger began his career in theology, but then moved into academia as a student of philosophy. While Heidegger’s philosophical inquiry began in alignment with Husserl’s work, he later challenged several key aspects of Husserl’s transcendental phenomenology. A foundational break from his predecessor was the focus of phenomenological inquiry. While Husserl was interested in the nature of knowledge (i. e., an epistemological focus), Heidegger was interested in the nature of being and temporality (i. e., an ontological focus) [21]. With this focus on human experience and how it is lived, hermeneutic phenomenology moves away from Husserl’s focus on ‘acts of attending, perceiving, recalling and thinking about the world [13]’ and on human beings as knowers of phenomenon. In contrast, Heidegger is interested in human beings as actors in the world and so focuses on the relationship between an individual and his/her lifeworld. Heidegger’s term lifeworld referred to the idea that ‘individuals’ realities are invariably influenced by the world in which they live [22].’ Given this orientation, individuals are understood as always already having an understanding of themselves within the world, even if they are not constantly, explicitly and/or consciously aware of that understanding [17]. For Heidegger, an individual’s conscious experience of a phenomenon is not separate from the world, nor from the individual’s personal history. Consciousness is, instead, a formation of historically lived experiences including a person’s individual history and the culture in which he/she was raised [22]. An individual cannot step out of his/her lifeworld. Humans cannot experience a phenomenon without referring back to his/her background understandings. Hermeneutic phenomenology, then, seeks ‘to understand the deeper layers of human experience that lay obscured beneath surface awareness and how the individual’s lifeworld, or the world as he or she pre-reflectively experiences it, influences this experience [35].’ Hermeneutic phenomenology studies individuals’ narratives to understand what those individuals experience in their daily lives, in their lifeworlds.

But the hermeneutic tradition pushes beyond a descriptive understanding. Hermeneutic phenomenology is rooted in interpretation—interpreting experiences and phenomena via the individual’s lifeworld. Here, Heidegger’s background in theology can be seen as influencing his approach to phenomenology. Hermeneutics refers to the interpretation of texts, to theories developed from the need to translate literature from different languages and where access to the original text (e. g., the Bible) was problematic [36]. If all human experience is informed by the individual’s lifeworld, and if all experiences must be interpreted through that background, hermeneutic phenomenology must go beyond description of the phenomenon, to the interpretation of the phenomenon. The researcher must be aware of the influence of the individual’s background and account for the influences they exert on the individual’s experience of being.

This is not to say that the individual’s subjective experience—which is inextricably linked with social, cultural, and political contexts—is pre-determined. Heidegger argued that individuals have situated freedom. Situated freedom is a concept that asserts that ‘individuals are free to make choices, but their freedom is not absolute; it is circumscribed by the specific conditions of their daily lives [22].’ Hermeneutic phenomenology studies the meanings of an individual’s being in the world, as their experience is interpreted through his/her lifeworld, and how these meanings and interpretations influence the choices that the individual makes [13]. This focus requires the hermeneutic phenomenologist to interpret the narratives provided by research participants in relation to their individual contexts in order to illuminate the fundamental structures of participants’ understanding of being and how that shaped the decisions made by the individual [37].

Another key aspect that distinguishes hermeneutic phenomenology is the role of the researcher in the inquiry. Instead of bracketing off the researcher’s subjective perspective, hermeneutic phenomenology recognizes that the researcher, like the research subject, cannot be rid of his/her lifeworld. Instead, the researcher’s past experiences and knowledge are valuable guides to the inquiry. It is the researcher’s education and knowledge base that lead him/her to consider a phenomenon or experience worthy of investigation. To ask the research to take an unbiased approach to the data is inconsistent with hermeneutic phenomenology’s philosophical roots. Instead, researchers working from this tradition should openly acknowledge their preconceptions, and reflect on how their subjectivity is part of the analysis process [16].

The interpretive work of hermeneutic phenomenology is not bound to a single set of rule-bound analytical techniques; instead, it is an interpretive process involving the interplay of multiple analysis activities [35]. In general, this process:

Starts with identifying an interesting phenomenon that directs our attention towards lived experience. Members of the research team then investigate experience as it is lived, rather than as it is conceptualized, and reflect on the essential [phenomenological] themes that characterize the participant’s experience with the phenomenon, simultaneously reflecting on their own experiences. Researchers capture their reflections in writing and then reflect and write again, creating continuous, iterative cycles to develop increasingly robust and nuanced analyses. Throughout the analysis, researchers must maintain a strong orientation to the phenomenon under study (i. e., avoid distractions) and attend to the interactions between the parts and the whole. This last step, also described as the hermeneutic circle, emphasizes the practice of deliberately considering how the data (the parts) contribute to the evolving understanding of the phenomena (the whole) and how each enhances the meaning of the other [35].

In the hermeneutic approach to phenomenology, theories can help to focus inquiry, to make decisions about research participants, and the way research questions can be addressed [22]. Theories can also be used to help understand the findings of the study. One scholar whose engagement with hermeneutic phenomenology is widely respected is Max van Manen [38]. Van Manen acknowledges that hermeneutic phenomenology ‘does not let itself be deceptively reduced to a methodical schema or an interpretative set of procedures [39].’ Instead, this kind of phenomenology requires the researcher to read deeply into the philosophies of this tradition to grasp the project of hermeneutic phenomenological thinking, reading, and writing.

A recent study published by Bynum et al. illustrates how hermeneutic phenomenology may be employed in HPE [2]. In this paper, Bynum et al. explored the phenomenon of shame as an emotion experienced by medical residents and offer insights into the effects of shame experiences on learners. As a means in scholarly inquiry, this study demonstrates how hermeneutic phenomenology can provide insight into complex phenomena that are inextricably entwined in HPE.

Main contentsSee more from basic to advanced

Normal Conditions and Experimental Observation

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Perceptual Properties: Sensory Effects and the Representational Structure of Perception

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Observing Phenomena “from the Outside”: Series and Order of Appearances

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Phenomenal Reality and Psychology of Perception in Metzger

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Husserl and the Form of the Theories of Perception

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The Empirical Grammar of Perception in Brentano

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Katz: The Phenomenological Method and Color and Touch Modes of Appearances

Katz recognized the importance of Husserl’s philosophical phenomenology and the application of its method to his research (Spiegelberg, 1972: 43). It is true that he

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In his work on the figure-ground structure, Rubin (1921) addresses similar questions to Brentano’s theory of boundaries and qualitative continua. Ru­bin was acquainted with the

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Experience, Science and Philosophy in Kohler

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Phenomenal Structures and Comparative Judgements in Phenomenology

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Bozzi: The Epistemological Foundation of Experimental Phenomenology

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Kanizsa: The Independence of Perception and the Autonomy of Vision Science

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Goldmeier: The Phenomenal Content of Similarity and the Structure of Visual Objects

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Forms of Visual Space in Phenomenology

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The Self as Spatial Part in Phenomenology: Meaning and Relations in Space

Kohler (1938) argues that physical and phenomenal space must be distin­guished from the epistemological standpoint without being committed either to ontological dualism, which admits physical

The Phenomenal Space Continuum

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Phenomenological Commitments

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Absolute Properties of Appearances

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Perceiving the Difference and the Phenomenal Basis of Judgments

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Meta-theory and Empirical Science

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Temporal Displacement and the Nature of Temporal Intervals

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The Intrinsic Geometry of Phenomena

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1. Qualitative and Quantitative Approaches

It is conventional in research to make a distinction between the qualitative and the quantitative. However this distinction is both equivocal and ambiguous.¹ The distinction is equivocal as it is based on a multiplicity of criteria. In con­sulting works on research methodology we find, in sections discussing the dis­tinction between qualitative and quantitative, references to ‘qualitative or quantitative data’ (Downey and Ireland, 1979; Glaser and Strauss, 1967; Miles, 1979; Miles and Huberman, 1984b; Silverman, 1993); to quantitative and quali­tative variables (Evrard et al., 1993; Lambin, 1990), and to ‘qualitative methods’ (Jick, 1979; Silverman, 1993; Van Maanen, 1979). The distinction between quali­tative and quantitative is, moreover, ambiguous because none of these criteria allow for an absolute distinction between the qualitative and the quantitative approach. We will turn now to a critical examination of the various criteria involved: the nature of the data, the orientation of the research, the objective or subjective character of the results obtained and the flexibility of the research.

As data collection methods, which are among the distinguishing characteris­tics of both qualitative and quantitative approaches, are discussed at length in another chapter in this book (Chapter 9), we will restrict our discussion here to other distinguishing characteristics.

1.1. The qualitative/quantitative distinction and the nature of our data

Does the distinction between qualitative and quantitative go back to the very nature of a researcher’s data?

Many authors distinguish between qualitative and quantitative data. For Miles and Huberman (1984b), qualitative data corresponds to words rather than figures. Similarly, Yin (1989: 88) explains that ‘numerical data’ provides quantitative information, while ‘non-numerical data’ furnishes information that is clearly of a qualitative nature. All the same, the nature of the data does not necessarily impose an identical method of processing it. The researcher can very well carry out, for example, a statistical and consequently quantitative analysis of nominal variables.

According to Evrard et al. (1993: 35), qualitative data corresponds to vari­ables measured on nominal and ordinal (non-metric) scales, while quantitative data is collected using interval scales and proportion scales. These scales can be arranged hierarchically according to the quality of their mathematical pro­perties. As shown in Figure 4.3, this hierarchy goes from a nominal scale, the weakest one from a mathematical point of view, to the proportional scale, the best of the measurement scales.

As Figure 4.3 shows, measuring variables on nominal scales allows us to establish relationships of identification or of belonging of a class. The fact that these classes may be identified by numbers (a department number, for example, or an arbitrarily chosen number) does not in any way change their properties. The one statistical calculation permitted is that of frequency.

Often a classification can be obtained using variables measured on ordinal scales, but the origin of the scale remains arbitrary. If the intervals between categories are unequal, statistical calculations are limited to measures of position (median, quartiles, deciles …). Arithmetical calculations cannot be performed with this data. Once the intervals between categories become equal, however, we can speak of interval scales. More statistical calculations can be carried out on variables measured on this type of scale, as here we move into data said to be ‘quantitative’, or to ‘metric’ scales, for which we can compare intervals and determine ratios of differences or distances. Means and standard deviations can be calculated, however, zero is defined arbitrarily.

The best-known example of an interval scale is that used to measure tem­perature. We know that 0 degrees on the Celsius scale, the freezing point of water, corresponds to 32 degrees on the Fahrenheit scale. We can convert a data item from one scale to another by a positive linear transformation (y = ax + b, where a > 0). However, if there is no natural zero, relationships cannot be estab­lished between absolute quantities. For example, it is misleading to say that ‘yesterday was half as hot as today’, when we mean that ‘the temperature was 50 per cent less in degrees Fahrenheit than today’. If the two temperatures are converted into Celsius, it will be seen that ‘half as hot’ is not correct. The arbi­trary choice of zero on the measuring scale has an effect on the relationship between the two measurements.

Where a natural zero exists, we come to proportional scales. Common examples include measurements of money, length or weight. This kind of data is therefore the richest in terms of the possible statistical calculations that can be operated on it, since the researcher will be able to analyze relationships in terms of absolute values of variables such as wage levels or company seniority.

The different aspects of qualitative and quantitative data that we have con­sidered in this chapter clearly show that the nature of the collected data does not dictate the employment of a qualitative or a quantitative research approach. To choose between a qualitative or a quantitative approach we have to evaluate other criteria.

1.2. The qualitative/quantitative distinction in relation to the orientation of the research: to construct or to test

Research in management is characterized by two main preoccupations: con­structing and testing theoretical objects. When researchers direct their work towards verification, they have a clear and definite idea of what they are look­ing for. On the other hand, if they are carrying out explorative research, typi­fied by theoretical construction, researchers are often far less sure of what they may find (see Chapter 3).

It is conventional to correlate investigation with a qualitative approach and verification with a quantitative. Silverman, for example, distinguishes between two ‘schools’ in the social sciences, one oriented towards the quantitative testing of theories, and the other directed at qualitatively developing theories (1993: 21). Once again, however, we find that this association is a received idea – researchers can equally well adopt a quantitative or a qualitative approach whether they are constructing or testing (see Chapter 3). ‘There is no fundamental clash between the purposes and capacities of qualitative and quantitative methods or data … Each form of data is useful for both verification and generation of theory’ (Glaser and Strauss, 1967: 17-18).

We should point out here, though, that researchers rarely choose a qualitative approach with the sole intention of testing a theory. This choice is generally accompanied by a fairly definite orientation towards construction. This tendency can be explained by the cost, particularly in time, of using a qualitative approach just to test a theory. If the test turns out to be positive, the researcher will have no choice but to test it again – by conducting another data collection and analysis process. The qualitative approach in effect locks the researcher into a process of falsification, as the only aim can be to refute the theory and not to validate it in any way.

The qualitative approach is not designed to evaluate to what extent one can generalize from an existing theory. In his discussion of the case study, which he positions within the qualitative method, Stake argues that ‘by counter-example, the case study invites a modification of the generalization’ (1995: 8). This modi­fication involves a construction. The limitation of qualitative approaches lies in the fact that such studies are necessarily carried out within a fairly delimited context. Although a researcher can increase the external validity of a qualitative study by including several contexts in the analysis, in accordance with a repli­cation logic (see Chapter 10), the limitations of the qualitative approach in terms of generalization lead us to attribute more external validity to quantitative approaches. Conversely, the qualitative approach gives a greater guarantee of the internal validity of results. Rival explanations of the phenomenon being studied are often far easier to evaluate than they are when a quantitative approach is taken, as researchers are in a better position to cross-check their data. The quali­tative approach also increases the researcher’s ability to describe a complex social system (Marshall and Rossman, 1989).

The choice between a qualitative and a quantitative approach therefore seems to be dictated primarily in terms of each approach’s effectiveness in relation to the orientation of the research; that is, whether one is constructing or testing.

Guarantees of internal and external validity should be considered in parallel, whatever type of research is being carried out. But in order to choose between a qualitative and a quantitative approach, researchers have to decide on the priority they will give to the quality of causal links between variables, or to the generalization of their results. Of course, it would be ideal to assure the greatest validity in results by employing both of these approaches together.

1.3. Qualitative/quantitative research for objective/ subjective results

It is generally acknowledged that quantitative approaches offer a greater assu­rance of objectivity than do qualitative approaches. The necessary strictness and precision of statistical techniques argue for this view. It is, then, not surprising that the quantitative approach is grounded in the positivist paradigm (Silverman, 1993).

While the objective or subjective nature of research results is often seen as forming a divisive line between qualitative and quantitative approaches, there are in fact several areas of possible subjectivity in management research, depending on the particular type of qualitative approach taken. A number of proponents of the qualitative approach have also discussed ways of reducing the subjectivity historically attributed to this research tradition.

According to Erickson (1986), the most distinctive feature of qualitative inves­tigation is its emphasis on interpretation – not simply that of the researcher but, more importantly, that of the individuals who are studied. This emphasis is com­parable to that of ethnographic research, which seeks ‘to reconstruct the cate­gories used by subjects to conceptualize their own experience and world view’ (Goetz and LeCompte, 1981: 54). Other writers, however, emphasize the subjec­tivity of the researcher more than that of the subjects. According to Stake (1995), researchers must position themselves as interpreters of the field they are study­ing, even if their own interpretation may be more labored than that of the research subjects. In fact, the qualitative approach allows for both the subjectivity of the researcher and that of the subjects at the same time. It offers an opportu­nity to confront multiple realities, for it ‘exposes more directly the nature of the transaction between investigator and respondent (or object) and hence makes easier an assessment of the extent to which the phenomenon is described in terms of (is biased by) the investigator’s own posture’ (Lincoln and Guba, 1985: 40).

However, the qualitative approach does not rule out an epistemological pos­ture of objectivity of the research with regard to the world that it is studying. This criterion of objectivity can be seen as an ‘intersubjective agreement’. ‘If multiple observers can agree on a phenomenon, their collective judgment can be said to be objective’ (Lincoln and Guba, 1985: 292). Some proponents of the qualitative approach, notably Glaser and Strauss (1967), have developed a posi­tivist conception of it. For Miles and Huberman (1984b) while the source of social phenomena may be in the minds of the subjects, these phenomena also exist in the real world. These authors argue for an amended positivism, advo­cating the construction of a logical chain of evidence and proof to increase the objectivity of results.

To sum up, data collection and analysis must remain consistent with an explicit epistemological position on the part of the researcher. Although the quali­tative approach allows the researcher to introduce a subjectivity that is incom­patible with the quantitative approach, it should not, however, be limited to a constructivist epistemology.

1.4. The qualitative/quantitative distinction in relation to the flexibility of the study

The question of the flexibility available to the researcher in conducting his or her research project is another crucial factor to consider in choosing whether to use a qualitative or a quantitative approach.

When a qualitative approach is used, the research question can be changed midway, so that the results are truly drawn from the field (Stake, 1995). It is obviously difficult to modify the research question during the more rigid process that is required by the quantitative approach, taking into account the cost that such a modification would entail. With the qualitative approach, too, the researcher usually has the advantage of greater flexibility in collecting data, whereas the quantitative approach usually involves a stricter schedule. Another problem is that once a questionnaire has been administered to a large sample of a population, it can be difficult to assess new rival explanations without taking the research program back to the draft stage.

2. Combined Approaches: Using Sequential Processes and Triangulation Strategies

One way researchers can exploit the complementary nature of qualitative and quantitative approaches is by using a sequential process:

Findings from exploratory qualitative studies may … provide a starting point for further quantitative or qualitative work. In multi-method projects, group discussions and in-depth interviews are frequently used in piloting to clarify concepts and to devise and calibrate instrumentation for inclusion in structured questionnaires.

(Walker, 1985: 20)

The qualitative approach can in this way constitute a necessary and remu­nerative stage in an essentially quantitative study. Given the considerable degree of irreversibility inherent to the quantitative approach, the success of such a research project very much depends on the researcher taking necessary precautions along the way.

Another practical way researchers can combine qualitative and quantitative approaches is by means of a triangulation. This involves using the two appro­aches simultaneously to take advantage of their respective qualities. ‘The achieve­ments of useful hypothetically realistic constructs in a science requires multiple methods focused on the diagnosis of the same construct from independent points of observation through a kind of triangulation’ (Campbell and Fiske, 1959: 81). The idea is to consider a formalized problem by formalizing along two complementary axes. The differential effect can then provide invaluable information for the researcher. Triangulation strategies aim to improve the pre­cision of both measurement and description.

Triangulation allows the research design to be put to the test, by ensuring that findings are not just a reflection of the methodology used (Bouchard, 1976). This does not simply mean commingling the two types of data and methods. Using complementary data does not of itself constitute a triangulation, but a natural action used in the majority of research projects (Downey and Ireland, 1979). It is a mistake to think that the ‘qualitative’ researcher does not make use of quantitative data, or that he or she is somehow opposed to measurement (Miles, 1979). The fact that a researcher uses a symbolic numerical system or a symbolic verbal system to translate an observed reality does not necessarily define the type of approach they are using. In their manual on qualitative analysis, for example, Miles and Huberman (1984b) suggest counting data items to highlight recurrence, for the reason that figures are more economical and easier to manipulate than are words, as well as having greater visibility in terms of trends.

The combination of qualitative and quantitative approaches, that is, their complementary and dialectical use, enables researchers to institute a dialogue distinguishing between what is observed (the subject of the research) and the two ways of symbolizing it:

Qualitative methods represent a mixture of the rational, serendipitous, and intuitive in which the personal experiences of the organizational researcher are often key events to be understood and analyzed as data. Qualitative investigators tend also to describe the unfolding of social processes rather than the social structures that are often the focus of quantitative researchers.

(Van Maanen, 1979: 520)

Triangulation allows the researcher to benefit from the advantages of the two approaches, counterbalancing the defects of one approach with the qualities of the other (Jick, 1979).

Source: Thietart Raymond-Alain et al. (2001), Doing Management Research: A Comprehensive Guide, SAGE Publications Ltd; 1 edition.

The post Choosing a Research Approach: Qualitative or Quantitative? appeared first on HKT Consultant.