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SOB_Qualitative_Guide_04_21_2021.pdf

Second Edition.Published by the Center for Teaching and Learning, Northcentral University, 2021

Contributors:Marie Bakari, Jennifer Biddle, Linda Bloomberg, John Frame, Namhee Kim, Sharon Kimmel, Jaime Klein, Paul Markham, Craig Martin, Stephanie Menefee, Eva Philpot, Wes Rangel, Randee Sanders, Abigail Scheg, Kimberly Scott, Patricia Steiner, Robert

Thompson, Marsha Tongel, Steven Ziemba

In addition to the collaborative process that engendered this guide, it was also informed by the qualitative methods course in the School of Business, BUS-7380 Qualitative

Business Research Design and Methodology.

For comments or suggestions for the next edition, please contact the School of Business: sb@ncu.edu

Foreword (P1)

Introduction (P2) Student-Chair Engagement (P2)

Qualitative Research Design (P3)

Research Questions (P3) Case Study (P5) Multiple Case Studies/Comparative Case Study (P6)

Participant Selection (P7)

Interviews (P7) Interviews: Minimum Number Recommended (P9) Focus Groups (P10) Observation (P11) Document Analysis (P12) Hermeneutics (P12) Phenomenological Design (P13) Constructive Research (P15)

Ethnography (P16) Grounded Theory (P18) Narrative Design (P19)

Delphi Method (P20) Mixed-Methods Research (P21) Online Questionnaires and Unsuitable Data Collection Practices (P21)

Interview Guides and Other Instruments (P22) Audio Recording and Transcribing Interviews (P24)

Sampling in Qualitative Research (P25) Data Saturation (P26) Triangulation (P27) Trustworthiness (P28) Member Checking (P30)

Coding and Thematic Analysis (P30)

Including Data in the Findings (Chapter 4) of the Dissertation (P32)

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Dear School of Business Community, Welcome to the Best Practice Guide for Qualitative Research Design and Methods in Dissertations! With well over 600 doctoral students in the School of Business working on their dis-sertation this year, this guide serves as an important resource in helping us shape and implement quality doctoral-level research. Its primary purpose is to offer direction on qualitative research in School of Business dissertations, serving students as they craft and implement their research plans, and serving faculty as they mentor students and evaluate research design and methods in dissertations. We encourage you to explore this guide. It is filled with details on important topics that will help ensure quality and consistency in qualitative research in the School of Business. Offering support for both faculty and students, this resource covers many topics, from those related to early stages of qualitative research design, to guidance on how to in-clude qualitative data in a dissertation.

Thank you to the faculty and staff of the School of Business and wider NCU community that worked to create this guide. It is a great contribution to our School, and each of these individuals played an important role in its development. We wish you the best on your dissertation journey!

SB Leadership Team

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IntroductionAs an accredited university, NCU aims to have ro-

bust expectations and standards for dissertations

produced by its students. This guide, developed

collaboratively by NCU School of Business (SB)

faculty in 2019, and updated in 2021, aims to

provide guidance on best practice in qualitative

research design and methods for SB dissertations.

While this guide can serve as a refresher to those

less familiar with qualitative methods, it will also

help ensure consistency in how faculty advise

students on qualitative methods. It is meant to help

ensure good practice vand rigor across commit-

tees and students.

To that end, this document is a guide to help

students when designing their research, as well as

faculty, when judging the merits of student disser-

tation prospectuses, proposals, and manuscripts.

Students should be familiar with the best practices

in this guide and apply them to their dissertation.

References and suggested reading:Yin, R.K. (2015). Qualitative research from start to finish. New York, NY: Guilford Publications.

Student-Chair EngagementClose engagement between students and facul-

ty is expected through the dissertation process.

Faculty should ensure that students are knowl-

edgeable about expectations, and students should

ensure they obtain necessary mentoring from their

Chair throughout the process. Key areas in the

dissertation sequence where closer than normal

engagement include:

• Developing chapter 1 and ensuring the re-

search questions align with the purpose statement,

problem statement, and methods.

• The IRB process.

• DIS-9902, which requires the completion of

several milestones (Chapters 2 and 3, and the

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Developing a qualitative design requires system-

atic planning and the ability to remain flexible.

According to Maxwell (2012: 215), “The activi-

ties of collecting and analyzing data, developing

and modifying theory, elaborating or refocusing

the research questions, and identifying and deal-

ing with validity threats are usually going on more

or less simultaneously, each influencing all of the

others.” In order to develop an effective design,

qualitative research procedures must be based on

the problem, purpose, and research questions.

Specifically, the research questions must reflect

the nature of the design. In addition, the purpose

must illustrate how the study is a logical, explicit

research response to the stated problem and the

research questions. Importantly, whereas in a

quantitative study, researchers measure or test

something, in a qualitative study one explores

and understands something. The language used

to describe this exploration should not include the

word ‘prove,’ but, rather, ‘explore’ (or another

similar word).

References and suggested reading:Maxwell, J.A. (2012). Qualitative research design: An interactive approach. Thousand Oaks, CA: Sage Publications.

Research QuestionsRigorous research questions help ensure a student

deeply probes and examines the issue under

investigation in the dissertation. Crafting rigorous

research questions takes time and great effort.

Typically, a student will want to have more than

one research question; but if having only one is

the best way to explore the topic, then the ques-

Dissertation Proposal). Progression data in the SB

indicates that students often need supplemental

courses (e.g. DIS-9902B) in order to complete

these milestones.

• Data collection: student and Chair should work

closely before and during data collection so that

the Chair is frequently apprised of the student’s

progress. Chairs should coach students to ensure

they are comfortable with data collection (e.g.

how to conduct interviews, with whom, and how

many).

• Writing up the findings. Chairs should ensure

students are knowledgeable about how to an-

alyze data and report their findings. See the

“Including Data in the Findings (Chapter 4) of

the Dissertation” section in this guide for further

information.

Qualitative Research DesignA research design is the ‘map’ that will guide the

study. Sufficient time and consideration should be

given to ensure that the design of a study is the

best ‘route’ for the student to take to complete the

dissertation journey. In other words, the research

design should clearly lead to answering the re-

search questions.

Regardless of the method or design that is uti-

lized, all research must be clear, concise, and

focused. Qualitative studies must demonstrate

validity within the context of the specific qualita-tive design (e.g., credibility, dependability, trans-ferability, trustworthiness). All research decisions should be justified with high-quality scholarly

sources.

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tion needs to be a rigorous question, ensuring the topic is explored in a wholistic way.

Research questions need to be narrow and focused, and related to the student’s degree program and specialization. They need to be connected to the problem statement in the disser-tation, rooted in the literature, and reflect re-search gaps. Having too many research questions is not wise, as the scope of the dissertation needs to be clear and focused. Research questions are not yes/no questions, because if the questions could be answered this easily, there would be no need to conduct a study. Furthermore, research questions should be more than ‘what’ questions (though a ‘what’ question can be asked). Em-phasis should be on examining the topic, not just reporting on the topic (a dissertation is not a list or answer to a ‘what’ question). Adding rigor to research questions can be done by including more complexity, such as by asking: ‘Why?,’ ‘How?,’ ‘In what ways?,’ ‘To what extent?,’ or ‘What difference does X make?,’ for example.

Research questions can be considered the heart of the dissertation–the engine that drives the thinking behind the dissertation. As a dissertation is a deep exploration and analysis of something, the research questions need to relate to the past

or present (not something that may occur in the future, as that cannot be examined presently). Thus, great care needs to be taken with questions that include the word ‘Can’ (as this likely might indicate that the questions relate to a future event that may not be adequately researchable in the present).

An example of an inadequate research question is:

This question is inadequate because it is a yes/no question, and it is too broad and not specific.

An example of a good research question is:

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This question is strong because it is focused,

clearly connected to a specific topic, and rigor-

ous.

Finally, research questions are different than the

interview questions asked of the participants in

a study. Whereas research questions drive the

entire study, interview questions are a means of

data collection, and are the specific questions

asked to get data to answer the research ques-

tions. There will thus be a clear link between

research questions and interview questions.

Case StudyA case study is a study that looks, for example, at

one issue in one or more businesses or organiza-

tions. It involves in-depth exploration, guided by

the dissertation research questions. As Bloomberg

(2018: 237) states, “Case study research is typ-

ically extensive; it draws on multiple methods of

data collection and involves multiple data sourc-

es. This method culminates in the production of

a detailed description of a setting and its partic-

ipants, accompanied by an analysis of the data

for themes, patterns, and issues.”

Case studies should create rich and complex

understanding of the topic under exploration.

Bloomberg (2018) states that a case study needs

to have clear boundaries (thus, students need to

be able to articulate what the case study does

and does not include). In addition, the student

needs to provide rationale for why a particular

case is being selected (Bloomberg, 2018).

Students need to collect data from more than one

source in order to ensure deep understanding of

the case. As further described in the Triangulation

section of this guide, having two or more data

sources is required in dissertations. For example,

a student could conduct interviews and analyze

documents from the organization(s) or busi-

ness(es) examined in the study.

Students may choose to design their case study

to include interviews, document analysis (e.g.

reports or specific content on relevant websites,

though this is not a literature review of peer-re-

viewed publications, etc.), direct observations,

participant observation, and/or analyzing physi-

cal artifacts (e.g. audiovisual materials). The goal

is to ensure thick narrative description, including

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context and important details that allow read-

ers to gain a deep understanding of the case

(Bloomberg, 2018). Importantly, the data collec-

tion methods should be closely aligned with the

research questions (Bloomberg, 2018). In other

words, data collected should directly result in

answering the dissertation research questions.

References and suggested reading:Yin, R.K. (2017). Case study research and applications: Design and methods. Thousand Oaks, CA: Sage Publications.

Bloomberg, L.D. (2018). Case study method. In B.B. Frey (Ed.), The Sage encyclopedia of educational research, measurement, and evaluation (pp. 237-239). Thousand Oaks, CA: Sage Publications.

Yin, R. K. (2012). Case study methods. In APA handbook of research methods in psychology, Vol 2: Research designs: Quantitative, qualitative, neuropsychological, and biological (pp. 141–155). Washington, DC: American Psychological Association.

Multiple Case Studies/Comparative Case StudyMultiple case studies (or a comparative case study) analyze similarities, differences, patterns, and themes across two or more cases (e.g. or-ganizations, companies). Yin (1993: 34) states, “The development of consistent findings, over multiple cases and even multiple studies, can then be considered a very robust finding.”

Goggin and Orth (2002: 49) state that cases in a comparative study are purposely selected “on the basis of similarity and comparability,” so that they “vary on the dimensions that are theoretically

relevant” (e.g. organisation type), and yet are “similar in as many other respects as possible.”

Comparative case studies should be carefully designed, with justification given as to why the research includes the cases planned for inclusion. There should also be care in how the study is described, as a study with multiple sites may be a multi-site (single) case study, rather than one that includes multiple case studies. Thus, a student

should consider if his or her design is actually a multiple case study or a multi-site (single) case study. This should be discussed in the dissertation. In any case, whether it is a multiple case study, or a multi-site (single) case study, a student needs to clearly articulate why the cases or sites were selected for inclusion in the study. In other words, the student should elaborate and defend what criteria were used to select them, and why that is important.

References and suggested reading:Goggin, Malcolm L., & Orth, D.A. (2002). How faith-based and secular organizations

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tackle housing for the homeless. Roundtable on Religion and Social Welfare Policy.

Yin, R.K. (1993). Applications of case study research. Newbury Park, CA: Sage Publications.

Yin, R. K. (2012). Case study methods. In APA handbook of research methods in psychology, Vol 2: Research designs: Quantitative, qualitative, neuropsychological, and biological (pp. 141–155). Washington, DC: American Psychological Association.

Yin, R.K. (2009). Case study research: Design and methods, 4th edition. Thousand Oaks, CA: Sage Publications.

Participant SelectionParticipants are people recruited to participate

in a study. Often, participants are those who are

interviewed. In selecting participants for a qual-

itative study, it is essential for a student to first

identify who will be included in the sample based

on the information that needs to be obtained to

answer the research questions. The student needs

to ensure that participants have experience or

knowledge about the topic being explored and

are the most appropriate choices to include in the

study. Also, students need to ensure that they will

be able to obtain access to the participants (e.g.

interviewing U.S Senators would not be a feasible

research design because it would be very unlikely

that a student could interview enough U.S. Sena-

tors to complete a dissertation). Importantly, once

participants are selected, students need to outline

how and why the participants were selected.

Interviews

Interviews are a method in which there is a con-

versation focused around interview questions or

topics that are discussed with the purpose of gath-

ering information to answer the research ques-

tions guiding the dissertation. Interviews allow the

researcher to get in-depth data from participants

in a one-to-one setting.

Structured interviews include pre-determined

open-ended questions that are asked in a prede-

termined order. For data analysis, the researcher

is able to compare and contrast the answers to

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the specific questions. In unstructured interviews,

the questions are not predetermined. Data anal-

ysis can be more challenging given variation in

the questions that were asked. Semi-structured

interviews contain the components of both struc-

tured and unstructured interviews. Interviewers

ask pre-determined questions to be answered by

all respondents but allow for clarification and

additional questions to be asked. Typically, stu-

dents will conduct structured, or semi-structured

interviews.

Interviews may be conducted in-person or through

an online medium, such as Skype, or by phone

(not email). With the participant’s permission,

interviews should be audio recorded (see “Audio

Recording and Transcribing Interviews” elsewhere

in this guide); if interviews are conducted by

phone, the student will need to consider how to

audio record the call. Students will also need to

consider—and discuss in their dissertation—the

limitations of conducting an interview virtually, or

on the phone (rather than in person), including

what ways communication and data may have

been hindered or limited because the interview

was not conducted in person.

According to Boyce & Neale (2006), conduct-

ing interviews should follow the same general

principles of the research plan: plan, develop

instruments, collect data, analyze data, and

disseminate findings. The plan identifies who will

be interviewed and what information will be ob-

tained. Developing the instruments will guide the

implementation of the interviews. When the data

is being collected, consent should be obtained

along with an explanation of the purpose of the

interview. To analyze the data, the researcher

will transcribe all data and review the findings.

The final step is to disseminate the findings to the

stakeholders and community.

References and suggested reading:Boyce, C., & Neale, P. (2006). Conducting in-depth interviews: A guide for designing and conducting in-depth interviews. Pathfinder International Tool Series.

Easwaramoorthy, M., & Zarinpoush, F. (2006). Interviewing for research: Tip sheet #6. Toronto: Canada Volunteerism Institute

Yin, R.K. (2015). Qualitative research from start to finish. New York, NY: Guilford Publications.

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Interviews: Minimum Number Recommended Several factors should be considered when de-termining the number of interviews a researcher should conduct in a qualitative study. Bryman (2012) recognizes the variety of recommenda-tions in the literature about the number of inter-views in qualitative studies, highlighting ranges from 20-30 and 60-150 interviews. A further

range was offered by Marshall, Cardon, Poddar, and Fontenot (2013: 20), who argued that, in research related to their own discipline (Informa-tion Systems), “Single case studies should gener-ally contain 15 to 30 interviews.” Furthermore, in a study of 179 doctoral theses from British and Irish universities that used the case study method, Mason (2010) found that the average number of interviews conducted was 36 (the mode was 40, and the median was 33).

While the target number of interviews for which a researcher should aim is usually not delineated in the literature, a minimum number of interviews is sometimes explicated. For example, the Archives of Sexual Behavior articulated policy for the minimum sample size for grounded theory studies published in their journal (Dworkin, 2012). They did this so that authors would have clarity on sample size expectations for a grounded theory design. Thus, it can be valuable for researchers—especially those rather new to the field—to have some guidance on what is expected in their discipline.

While constraints such as time and funds must be considered, Charmaz’s (2012: 22) advice should be given important consideration: “…learn what constitutes excellence rather than adequacy in your field—and beyond, if your project portends of having larger import—and conduct as many interviews as needed to achieve it.”

To ensure appropriate rigor and consistency with-in NCU SB dissertations, it is recommended that students conduct a minimum of 15-20 interviews. A maximum number is not stated. An accurate assessment of saturation should guide the number of interviews conducted (see “Data Saturation” in this guide).

The design of a qualitative study should be of an appropriate design and nature that allows for this recommended minimum number of interviews. This should be considered when designing the study, including the research questions and po-tential site(s) where the study will take place. In some research designs, such as phenomenolog-ical studies (see “Phenomenological Design” in this guide), students may wish to interview par-ticipants more than once (with different questions and at different times) in order to get thick and rich data. If this is part of the research design, a fewer number of participants may be selected, if appropriate (because they will be interviewed at least twice).

In all cases, saturation should be ensured (see “Data Saturation” in this guide), and the student

should provide a clear explanation and defense

of why saturation was believed to have been

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obtained. In addition, when possible, students are

encouraged to follow the best practice, stated by

Marshall, Cardon, Poddar, and Fontenot (2013),

of citing any previous studies that were conducted

with a similar design.

References and suggested reading:Bryman, A. (2012). Untitled contribution, in S.E. Baker, & R. Edwards, How many qualitative interviews is enough? Expert voices and early career reflections on sampling and cases in qualitative research (pp.18-20). National Centre for Research Methods Review Paper.

Charmaz, K. (2012). Untitled contribution, in S.E. Baker, & R. Edwards, How many qualitative interviews is enough? Expert voices and early career reflections on sampling and cases in qualitative research (pp. 21-22). National Centre for Research Methods Review Paper.

Dworkin, S.L. (2012). Sample size policy for qualitative studies using in-depth interviews. Archives of sexual behavior, 41(6), 1319-1320.

Marshall, B., Cardon, P., Poddar, A., & Fontenot, R. (2013). Does sample size matter in qualitative research?: A review of qualitative interviews in IS research. Journal of computer information systems, 54(1), 11-22.

Mason, M. (2010). Sample size and saturation in PhD studies using qualitative interviews. Forum qualitative Sozialforschung/Forum: Qualitative social research 11(3.8).

Focus GroupsA focus group, as described by Hair, Celsi, Ortin-

eau and Bush (2013), is a face-to-face experience

with a small group of individuals that are assem-

bled to have an interactive discussion concerning

a research topic of interest. In their dissertation,

students need to articulate why they have gath-

ered particular people into focus groups, justify-

ing the design and numbers of participants includ-

ed in their study. Students should keep in mind the

challenge entailed in attempting to gather busy

people together in the same room at the same

time. This is a challenge that needs to be consid-

ered carefully, as a student does not want to real-

ize when it is too late that gathering focus groups

is not feasible for his or her study (because partic-

ipants do not attend). Students should understand

that deciding to change the research methods

during the data collection period requires modifi-

cations to the IRB application, and IRB approval

needs to be sought again. This takes time away

from the time allotted to data collection.

Students need to justify why focus groups are the

best method for their data collection. Students

should keep in mind that multiple focus groups

will be needed in order to collect sufficient data.

Students should design their study so that the

amount of data they obtain is comparable to the

data that would be acquired in the section in this

guide discussing the minimum number of inter-

views in case study research (see the section on

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this topic in this guide). If a study includes focus

groups as one method used (for example, in addi-

tion to interviews), fewer number of focus groups

would be acceptable.

A focus group is comprised of three steps or

phases: planning the focus group study; imple-

menting the focus group; and evaluating, analyz-

ing and communicating the results. When plan-

ning a focus group, several important elements

need to be considered: Should the focus group be

conducted online (for example, in a group Skype

call) or in a face-to-face environment? How large

should the focus group be? Who should be con-

sidered to be part of the focus group, and why?

How should qualified participants be recruited?

Should incentives be used to improve the likeli-

hood of attracting committed participants? Where

should the focus groups be conducted?

Creswell (2013) noted that successful focus groups are interactive and, therefore, group dynamics play a significant role. Creswell (2013) also noted that effective focus groups are heavily dependent on the facilitator keeping the discus-sion focused on the primary objective of the re-search. A student thus needs practice and training in order to prepare for successfully conducting focus groups. Chairs need to ensure students are comfortable and prepared with conducting focus groups before they begin data collection.

References and suggested reading:Creswell, J.W. (2013). Qualitative inquiry & research design: Choosing among five approaches (3rd ed.). Thousand Oaks, CA: Sage Publications.

Hair, J.F., Celsi, M.W., Ortineau, D.J., & Bush,

R.P. (2013). Essentials of marketing research (3rd ed.). New York, NY: McGraw-Hill Irwin.

ObservationMarshall and Rossman (1989: 79) define obser-

vation as “the systematic description of events, be-

haviors, and artifacts in the social setting chosen

for study.” Observation enables one to describe a

situation using all of one’s senses, thus creating a

‘written photograph’ of the situation being studied

(Erlandson, Harris, Skipper, & Allen, 1993). Stu-

dents who use observation as a method need to

be cautious of the influence their presence might

bring.

It is imperative that observers take detailed and

accurate notes, to be coded and analyzed at

what could be a potentially much later date. The

notes taken will be the only record of what was

observed. So, without accurate and detailed

notes, the observation could be rendered useless.

As mentioned above, the observer should use all

five senses during the process. The environment

and setting is just as important as the situation

being observed. Finally, as is always the case,

research questions and the method to answer

the research questions must be closely linked.

If observation is a method used in a study, the

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student should clearly delineate in the dissertation

how and why observation is the best method to

answer the research questions.

References and suggested reading:Marshall, C., & Rossman, G.B. (1995). Designing qualitative research. Newbury Park, CA: Sage Publications.

Erlandson, D.A., Harris, E.L., Skipper, B.L., & Allen, S.D. (1993). Doing naturalistic inquiry: A guide to methods. Newbury Park, CA: Sage Publications.

Yin, R.K. (2015). Qualitative research from start to finish. New York, NY: Guilford Publications.

Document AnalysisOften used as a means of triangulation, document

analysis involves examining documents (which

can include those in print or online, including

websites) to extrapolate meaning, understanding,

and knowledge surrounding the topic or phenom-

enon in question. Importantly, document analysis

is not a literature review (which students complete

in Chapter 2 of the dissertation). Instead, docu-

ment analysis is a method to collect and analyze

data that will help to answer the research ques-

tions.

Because document analysis is typically used to

triangulate data, it is thus used in support of

other methods (e.g. in-depth interviews). So, for

example, if a student is doing a case study to

explore organizational decline, a student may

interview employees and also gather operational

documents to analyze. One thing to keep in mind

about this method is the ability (or inability) to ac-

cess documents. Students need to consider if they

will have permission from companies or organiza-

tions to review documents not publicly available

on the internet.

When embarking on document analysis, students

need to carefully consider, and articulate in their

dissertation, which documents (or types of doc-

uments) will be analyzed, and why. The process

for document analysis should be thought out well,

including how the documents chosen relate to the

research questions, the types of data expected

to be found within the documents, and how this

data collection method fits with the other form(s)

of data collection (e.g. interviews) planned for the

study. The process should be systematic and clear.

As Bowen (2009: 38) states, “the researcher

should make the process of analysis as rigorous

and as transparent as possible. Qualitative inqui-

ry demands no less.”

References and suggested reading:Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative research journal, 9(2), 27-40.

HermeneuticsHermeneutics refers to the interpretation of text.

Through a hermeneutical study, a researcher

interprets ‘sacred’ text in a manner that captures

the essence of the human experience. Since the

inception of hermeneutics, it has been used effec-

tively by more than one academic discipline to

interpret religious scriptures, laws, music, poetry,

and more. For a student interested in interpreting

text for deeper meaning, the references below

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are a valuable starting point. For the newcomer

to hermeneutics, Schmidt’s Understanding Herme-

neutics is the best place to begin. If hermeneutics

is a critical element of a dissertation, a student

should include a discussion of hermeneutics in the

dissertation, including how he/she will follow best

practices in the literature.

References and suggested reading:Davey, N. (2012). Unquiet understanding: Gadamer’s philosophical hermeneutics. Albany, NY: SUNY Press.

Schmidt, L.K. (2016). Understanding hermeneutics. Abingdon, UK: Routledge.

Thiselton, A.C. (2009). Hermeneutics: an introduction. Grand Rapids, MI: William B. Eerdmans Publishing Company.

Phenomenological DesignThe phenomenological research design (or phe-nomenological study) is focused on examining a phenomenon, or specific experience, and how it affects people, such as people who have been affected by an event. This phenomenon must have a business or administration-related context, de-pending on the student’s specialization.

Understanding the effect of an event (the phenomenon) requires the researcher to identify individuals who had a specific type of experience that was directly related to the event. If a student chooses a phenomenological design, the design should be clearly defended in the dissertation, with clear reason as to why the design was selected, and what phenomenon will

be explored.

All participants a student interviews must have

lived experiences related to the central phenom-

enon under study. Research questions guiding

a phenomenological design should allow for all

aspects of the experience under study to emerge

from the participants’ experience.

In a phenomenological study, a student is likely to

visit with participants individually (over multiple

interviews of at least one hour each). Students

should collect rich narrative and observational

data (i.e. field notes), and ensure immersion in

each participant’s world. The focus should be

on thorough description, and homing in on the

phenomenon under examination (Bevan, 2014).

Bevan (2014: 142-143) states that the focus of

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this design “is one of accurately describing and

thematizing experience in a systematic way. It

uses themes of contextualizing experience, appre-

hending the phenomenon, and clarification of the

phenomenon.”

At the end of each interview, it is recommended

that the student complete an entry in a research

journal, where reflections on the interview are

entered. In order for this to be done well, detailed

content and reflections should be added to the

journal (which can be a Microsoft Word file, etc.)

as soon as possible after each interview is complet-

ed. This journal will be especially beneficial when

developing themes for meanings behind the words

of the participants (when analyzing data). The

following research journal template can be used:

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In describing the interview process, Bevan (2014)

summarized another scholar’s approach (Seid-

man, 2006), which included interviewing the

same person 3 times. The first interview focused

on the interviewee’s life history, which provided

context. The second interview focused on recon-

structing the experience, including the relation-

ships and structures relating to the experience.

The final interview focused on how the interview-

ee reflected on the meaning of the experience.

A student should evaluate if phenomenology is the

correct method to be used for his or her disserta-

tion, and should clearly outline the projected inter-

views planned to explore the phenomenon under

examination. As stated earlier in this guide (see

“Interviews: Minimum Number Recommended”), it

is recommended that students conduct a minimum

number of 15-20 interviews in a qualitative study.

The reason is to ensure thick and rich data is col-

lected about the phenomenon explored. If inter-

viewing a fewer number of participants better fits

the research design (or this number is not practi-

cal because few participants have experienced

the phenomenon), then it is recommended that

students interview a minimum of 8-10 participants

twice (or, potentially, interview a fewer number of

participants 3 times each, if the phenomenon is

experienced by a very small number of people).

Students should ensure that the sample size and

number of interviews conducted is determined

from saturation (see “Data Saturation” in this

guide), continuing data collection until saturation

is reached. If multiple rounds of interviews are

planned, different questions should be asked

in each round. The interview questions should

be derived from the central research question(s)

about participants’ lived experiences relative to

the phenomenon under study.

This design should only be used for deeply ex-

ploring experiences and phenomena. It involves

a different approach than the typical act of sitting

down and talking with interviewees about a par-

ticular topic or issue.

Phenomenology is deeply rooted in a philosoph-

ical base, as well as being a research method-

ology. The intent of a phenomenological study is

to uncover, describe and interpret the essence of

experience and to provide greater insight and

understanding to the essence of the experience

under study.

Data analysis in a phenomenological study

should follow a thematic analysis process. This

process allows students to analyze the data via

coding (see “Coding and Thematic Analysis” in

this guide).

References and suggested reading:Bevan, M.T. (2014). A method of phenomenological interviewing. Qualitative health research, 24(1) 136–144.

Constructive ResearchConstructive research refers to research that has,

at its focus, a problem-solving mission. It is aimed

at producing solutions to both practical and theo-

retical problems (Oyegoke, 2011). As Oyegoke,

(2011: 576) states, “The identified research prob-

lems are used to propose research questions that

address the problem. The questions are solved by

16

developing or constructing a solution which will

be operationalised to determine its workability

and appropriateness.”

It is recommended that a constructive research dis-sertation be understood and designed as a case study (see “Case Study” in this guide). Guidance on case study, including triangulation, should thus be followed in constructive research. Oyegoke (2011) identifies six phases of a constructive research project: 1) problem identification; 2) in-depth understanding of the topic; 3) construc-tion of a solution; 4) justification of the construct; 5) highlighting both the theoretical and practical contributions; and 6) examining the scope of

applicability.

While those who may actually use the solution

constructed in a project are ideally involved in its

design, as well as the strategy for how it will be

applied (Oyegoke, 2011), given that a disserta-

tion is a single-person project, a student should

consider ways to feasibly include and integrate

input from these individuals throughout the study.

References and suggested reading:Oyegoke, A. (2011). The constructive research approach in project management research. International journal of managing projects in business, 4(4), 573-595.

EthnographyThe objective of the ethnographic researcher

is to gain an in-depth understanding about the

activities of a group under study and how their

activities are influenced by the culture within the

group. This is done by becoming immersed as a

participant in their daily activities. The researcher

must be immersed in the culture or the situation to

observe the culture in its natural environment. In

the field of business, this could be a business’s or

organization’s culture. The researcher seeks to

document the culture, practices and perspectives

of the group or community studied while partici-

pating within and observing the group or commu-

17

nity in its regular setting (Draper, 2015). Data col-

lection methods include unstructured observations

and informal inquiries while the researcher serves

as a participant. Data collection often includes

formal interviews, direct observations, document

reviews and focus groups when the researcher

acts as an outside observer (Draper, 2015). The

ethnographer normally will develop an extensive

set of field notes during the time serving as a

participant within the group, and as an observer

of the group setting.

Ethnography, as a qualitative research design,

has the intent to advance understanding about

how a group or community views the world in the

context of the beliefs, traditions and customs of

that group or community (Reeves, Kuper & Hodg-

es, 2008). Ethnography has its origins in an-

thropology and sociological research; however,

ethnography in 2019 involves a variety of con-

texts and settings, including healthcare, educa-

tion, businesses, and other organizations (Reeves,

Kuper & Hodges, 2008).

To facilitate the inductive analysis employed

in ethnography, the collected data often is fac-

tored into some combination of the following

8 dimensions: space, or physical layout, of the

setting; a description of the group or community

participants; the set of activities occurring in the

setting; tangible objects present; specific actions

of individuals present in the setting; time and/

or sequencing of actions; goals or objectives

people establish in the context of the setting; and

specific emotions expressed by participants while

in the setting (Reeves, Kuper & Hodges, 2008).

The researcher uses interpretive and descriptive,

systematic structures demonstrated as credible to

conduct the analyses of qualitative data (Patton,

2015). The objective of the analysis is to devel-

op interpretations of the meanings of activities

observed in the group or community setting in

the context of the beliefs, traditions and customs

established by the group or community. Explana-

tions about how or why participants within the set-

ting behave as they do contribute to a rich, com-

prehensive report (Humphreys & Watson, 2009).

Because the researcher often serves as a par-

ticipant, as well as an observer, ethnography

18

research has several additional challenges when

compared to other qualitative designs (Draper,

2015). To blend into the setting requires that the

researcher build rapport with other participants

within the group or community. The researcher

should consciously bracket out any prejudgments

or biases and seek to maintain an objective view-

point throughout the time of data gathering, so as

not to skew the interpretation of the data.

Ethnography studies enable the researcher to im-

merse oneself deeply within the group or commu-

nity to obtain an in-depth and rich understanding

about social interactions and behaviors observed.

As a participant, ethnographers might acquire

data hidden from public view which explains fur-

ther the behavior within the group or community

studied (Draper, 2015).

Importantly, because ethnography requires immer-

sion for a significant period of time, this research

design is likely not suitable for most NCU stu-

dents.

References and suggested reading:Draper, J. (2015). Ethnography: Principles, practice and potential. Nursing standard, 29(36), 219-225.

Humphreys, M., & Watson, T. (2009). Ethnographic practices: From ‘writing-up ethnographic research’ to ‘writing ethnography’. Organizational ethnography: Studying the complexities of everyday life, 40-55.

Patton, M.Q. (2015). Qualitative research & evaluation methods: Integrating theory and

practice (4th ed.). Thousand Oaks, CA: Sage Publications, Inc.

Reeves, S., Kuper, A., & Hodges, B.D. (2008). Qualitative research methodologies: Ethnography. British medical journal, 337(7668), 512-514.

Grounded TheoryGrounded theory (GT) is an inductive process

whereby analysis of collected data allows the

researcher to produce theory explaining the

phenomenon in question. In 1967, Glaser and

Strauss discovered this approach while research-

ing terminal illness. According to Charmaz and

Mitchell (2001), the process is characterized

by five general characteristics: (1) Simultaneous

data collection and analysis; (2) Searching for

emerging themes via early analysis; (3) Discov-

ering basic social processes within the data; (4)

Explaining those processes via inductive construc-

tion of abstract categories; and (5) Integrating all

of the above into a theoretical framework specify-

ing causes, conditions, and consequences of the

process(es).

There is a hidden challenge in grounded theory

research that makes this design less ideal for dis-

sertation-type research: to fully develop a theory,

the researcher must repeatedly test the emergent

theory to establish its true existence. Grounded

theory studies are time-consuming because repeat-

ed measures are required to confirm the existence

of the theory. It is a very rigorous method, but

once it is conducted well, it can contribute to the

foundations of theory building. Because of the

time it takes to conduct this type of study, it is not

19

recommended for an NCU dissertation.

For an in-depth review of GT, please refer to the

article listed below by O’Connor, Carpenter &

Coughlan (2018). In this article, the authors re-

view both the classic and constructivist viewpoint

surrounding GT, and the main tenets of properly

executing a GT study.

References and suggested reading:Charmaz, K., & Mitchell, R.G. (2001). Grounded theory in ethnography. In P. Atkinson, A. Coffey, S. Delamount, & J. Lofland (Eds.), Handbook of ethnography (pp. 160-174). London, UK: Sage Publications.

O’Connor, A., Carpenter, B., & Coughlan, B. (2018). An exploration of key issues in the debate between classic and constructivist grounded theory. Grounded theory review 7(1), 90-103.

Narrative DesignThe narrative design is used when the researcher

is trying to describe the lives of subjects or partic-

ipants, told by the subjects or participants them-

selves. The use of narrative design allows for the

emergence of voices that may otherwise not be

heard. It provides a means to understand and pres-

ent real-life experiences as told through the stories

of those who lived those experiences. The story-tell-

ing approach of narrative design allows for deep,

rich descriptions of experience and the meanings

of the experience to emerge and be shared. Exe-

cuting this type of research can be time-consuming

because of the number of hours that must be spent

with the participants to gather data.

This design uses stories told in the autobiograph-

ical words of the participant. The narrative

approach allows participants to share their ex-

periences and for the researcher to further exam-

ine multiple experiences in an effort to shape a

common true story through a collaborative effort

of participants and researcher. It focuses on the

participant creating a story based on the internal

processing of their own self-awareness, the deep

learning that resulted from reflection, and external

consequences as well as internal development as

a result of change (Connelly, & Clandinin, 1986;

Creswell, 2008; Mahler, 2008).

The researcher actively participates in the study

by interacting with the participants, thereby

becoming immersed in the study as they partic-

ipate in the telling of the stories of their partici-

pants. Semi-structured interviews are conducted

with each participant, transcribed, and coded to

capture significant insights into their behavior. A

descriptive vignette on each participant is devel-

oped from the coded transcriptions and review of

the audio recordings. Participants are invited to

reflect on their profile and provide any follow-up

comments.

20

In many ways, narrative design can appear sim-

ilar to phenomenological studies (See “Phenome-

nological Design” in this guide). In phenomenol-

ogy, the focus is on the essence of a particular

experience, while in narrative design the focus is

on a chain of experiences and the connection of

the events within the experiences.

If a student chooses a narrative design, the choice

should be clearly defended in the dissertation,

with clear reason as to why the design was select-

ed. Furthermore, the student will need to clearly

articulate a plan for how to gather rich data that

is comparable to the data that would be obtained

in a case study (see “Interviews: Minimum Num-

ber in a Case Study Design” in this guide). This

may be done by conducting multiple interviews

with the same person, for example.

References and suggested reading:Connelly, F.M., & Clandinin, D.J. (1986). On narrative method, personal philosophy, and narrative unities in the story of teaching. Journal of research in science teaching, 23(4), 293-310.

Creswell, J.W. (2008). Educational research: Planning, conducting and evaluating qualitative & quantitative research (4th Ed.). New Jersey, NJ: Pearson Education. Mahler, E.B. (2008). Defining career success in the 21st century: A narrative study of intentional work role transitions. ProQuest.

McAlpine, L. (2016). Why might you use narrative methodology? A story about narrative. Eesti Haridusteaduste Ajakiri. Estonian Journal of Education, 4(1), 32-57.

Delphi methodWhen students wish to employ a research method

that is untraditional for a qualitative study, they

need to ensure the data they collect will be rich

and rigorous; in addition, a similar level of work

as a more traditional qualitative study needs to be

involved.

For students wishing to do a Delphi Method study,

it is recommended that 15-20 panelists be inter-

viewed in a face-to-face meeting (or via zoom or

the telephone, etc.) in the first round, after which

another type of data collection method (after the

participants are interviewed) could gather addi-

tional data from these same participants.

21

While a Delphi study focuses on forecasting and

the unknowable future, a doctoral dissertation

focuses on a problem or issue—in the past or

present (examined empirically). Therefore, at least

one research question that aligns with a tradition-

al dissertation focus (related to empirical explora-

tion of something in the past or present) should be

included in the dissertation.

Using this approach, the Delphi Method can be

adapted to be a design appropriate for a qualita-

tive doctoral dissertation. Students should ensure

they conduct adequate research on the Delphi

Method before choosing this method.

Mixed-Methods ResearchMixed-methods research relates to a study that

involves both qualitative and quantitative data. It

uses the combination of qualitative and quantita-

tive methods to better understand the given re-

search problem (Creswell & Plano Clark, 2011).

Ivankova, Creswell & Stick (2006) advocated the

need for mixed-method research design in cases

where the research problem could not be ade-

quately addressed with either method in isolation.

Mixed-methods research is not a recommended

research method approach at Northcentral Uni-

versity. The use of this method bestows undue

complexity and time burden on the doctoral can-

didate. However, because of its rigor, it should be

understood for future reference.

References and suggested reading:Creswell, J.W., & Plano Clark, V.L. (2011). Designing and conducting mixed methods research (2nd ed.). Thousand Oaks, CA: Sage Publications.

Ivankova, N.V., Creswell, J.W., & Stick, S.L. (2006). Using mixed-methods sequential explanatory design: From theory to practice. Field methods, 18, 3-20.

Sale, J.E. M., Lohfeld, L.H., & Brazil, K. (2002). Revisiting the quantitative-qualitative debate: Implications for mixed-methods research. Quality and quantity, 36(1), 43-53.

Online Questionnaires and Unsuitable Data Collection PracticesQualitative research methods need to be rigorous

and in line with good practices of the wider aca-

demic community. One unsuitable data collection

practice for a dissertation with a qualitative re-

search design is sending out online questionnaires

to participants, including a questionnaire with

open-ended questions for participants to write or

type their answers, as these methods do not allow

for students to obtain thick and rich data (nor

nuances in responses) needed for doctoral-level

qualitative research. Instead of a questionnaire

for participants to write their answers, students

should develop an interview guide for use in in-

terviews or focus groups that are audio recorded

and transcribed (see “Interview Guides and Other

Instruments” in this guide).

Demographic questions, etc. can be asked during

an interview through a questionnaire (e.g. at the

beginning or the end of an interview), or before

an interview is scheduled (for example to help in

selecting interview participants), but a question-

naire should not replace an interview (because

22

this type of instrument does not result in gener-

ating thick and rich data, which is needed for

thorough inquiry in qualitative research, allowing

the student to acquire enough data to answer the

dissertation’s research questions).

Chairs and SMEs should guide students in select-

ing an appropriate qualitative data collection

method. Remember that the value of a qualitative

design includes the rich data obtained through

data collection. Therefore, methods, such as in-

depth interviews, should be used to obtain rich

qualitative data.

Another unsuitable practice for a doctoral dis-

sertation is designing the study to be a literature

review. The literature review should be one chap-

ter of the dissertation. The literature is not the data

in a dissertation. Thus, data that may be included

in a journal article is not an acceptable form of

data for a student’s dissertation. The literature is

an important part of the dissertation, as it informs

theory, and helps in the interpretation and anal-

ysis of the findings. But it is not the data itself.

It should not be confused with the data that is

collected or used in a dissertation. It is valuable

to note that the method of Document Analysis (see

“Document Analysis” in this guide) is different

than a literature review.

Interview Guides and Other InstrumentsInstruments created and used in qualitative re-

search are distinctly different from what are used

in quantitative studies. Qualitative instruments

include open-ended questions and must be struc-

tured so that the researcher is collecting deep

and broad data to fully understand the research

questions. In most cases, an instrument should be

designed to extract specific experiential informa-

tion from participants.

Data collection questions (the questions created

for the interview guide) are different than the

research questions in the dissertation. The pur-

pose of data collection questions is to provide

data to answer the research questions. Thus, there

is a clear link.

23

Data collected should be relevant and compre-

hensive enough to answer the research questions.

To gather enough data to answer the research

questions, the data collection questions need to

encourage respondents to provide accurate, in-

depth information.

It is a good idea to develop a crosswalk to show

the relationship between the research questions

and data collection questions. This could be in the

form of a table, or a figure, and should include

key concepts and terms.

A student should polish data collection questions

by ensuring they are open-ended and evoke flow-

ing information, carefully reviewing them to en-

sure they are not answerable with a ‘yes’ or ‘no’

response. Furthermore, questions should address

only one topic at a time. They should also not be

biased, or in any way influence the participant.

Questions should be conversational.

Interviews are social experiences. It is important

to establish and maintain a positive, respectful

social experience. A warm-up question should

be included. If the first question is easy to un-

derstand and answer, and non-threatening, then

the respondent will be encouraged to continue.

However, if the first question is too difficult, em-

barrassing, or threatening, then the respondent

will become distrustful and draw away from the

experience. Probing questions should also be

included as a means to solicit additional infor-

mation or to further explore an unclear response.

A probing question might be as simple as, “Can

you tell me more about that?” This is one reason

why online questionnaires are unsuitable for qual-

itative research (see “Unsuitable Data Collection

Practices” in this guide).

Students should ensure that the order of the

questions on the interview guide is logical. If a

break in topic is necessary, then a break for the

respondent could be introduced. Any reflective or

uncomfortable questions can be included about

two-thirds through the interview.

A student should consider asking four or more

persons to review data collection questions before

they are finalized and before interviews begin.

Three or more of these persons should represent

the target population, and one or more should

have experience in developing data collection

24

questions. These reviewers can be asked: Are the

questions clear? Is wording used in the questions

understandable to the target population? Does the

terminology have a shared meaning for the target

population? Are questions respectful of the target

population? Are questions free of bias and with-

out influence? Are there extraneous questions that

do not address the research topic and purpose?

Note: Persons acting as reviewers of the questions

should not be participants in the actual study.

A pilot study is a ‘test run’ or mock activity that

includes actual participant responses to the data

collection questions. Pilot studies require IRB ap-

proval before the study is performed. Pilot studies

are beneficial and might be considered to prac-

tice implementation, become comfortable with the

interview process, and to ensure the questions are

phrased well. The first three interviews may be

treated as a pilot study, adjusting the questions,

as necessary, after these first interviews.

Audio Recording and Transcribing InterviewsAudio recording interviews is an important part

of the interview process, and is expected. This

should be done with permission. Recording inter-

views can be done in several ways, such as with

a voice recorder app on a cell phone. Students

should ensure beforehand that the chosen record-

ing device or app is compatible with the chosen

transcription method.

The microphone should not be obstructed, and recording should be done in a quiet place, if pos

sible. Background noise can make transcribing

difficult, if not impossible, in some cases.

There are several methods available for transcrib-

ing interviews. The best way to better understand

the data is to transcribe it personally. There is

software available online that can replay an

interview at a slower speed, thus allowing it to be

typed more easily. If self-transcription is not possi-

ble, some companies offer transcription services

by a human, but these can be very costly. Alter-

natively, there are automated programs, mostly

web-based, promising anywhere from 90 – 95%

accuracy on transcript return. See below for links

to a few resources. (Note: the contributors of this

guide are in no way affiliated with any of the

below linked resources. Additionally, there are

more resources available than the ones listed

later in this section.) It is important to do a quality

check with transcripts to ensure they are accurate,

by carefully reviewing them while listening to the

audio again, and making corrections, before

beginning data analysis.

Something to think about when deciding how

audio files should be transcribed is the level of

confidentiality surrounding the interviews conduct-

ed for analysis, and this should be considered

when drafting the interview consent form.

25

Self-Transcription

Express Scribe: Transcription software for PC and Mac. There is a free version and a paid version of this software. As with most transcription soft-ware, all controls can be set via keyboard, but a foot pedal can also be used. https://www.nch.com.au/scribe

OTranscribe: Much like both of the above-men-tioned programs, OTranscribe is a simple tool for self-transcribing audio and video. Hosted on the web, this is a free service, and it enables one to upload a file to the website. https://otranscribe.com

Jotengine: A free website that allows the research-er to upload an audio file and transcribe the words. It is very simple and has easy shortcuts. For example, it allows one to go back 5 seconds or play the recording slowly. https://jotengine.com/diy

Transcription Services

Rev.com: This website allows one to upload audio files and receive a transcript in one day. The tran-script is done by a person, not speech recognition software. The current fee is $1.25 per minute. https://www.rev.com

Automated Transcription

NVivo: Now the coding software, NVivo, offers

researchers an automated transcription service

that works seamlessly with their software. The

cost structure is pay-as-you-go, and starts at 50

cents per minute. NVivo is now available to NCU

students through the Student Technology Resource

Center. You can access the software through the

University Services module in NCUOne. https://www.qsrinternational.com/nvivo/nvivo-prod-ucts/transcription

Trint: Audio and video files can be uploaded into

Trint for immediate transcription, through the use

of artificial intelligence. From there one can edit

and distribute the transcript. Additionally, with an

iPhone, one can download a recording app that

will send the audio files to Trint. Trint is a paid

service, costing approximately $15 for one hour

of audio. https://trint.com

Otter.ai: Files can be uploaded and are automat-

ically transcribed. A (limited) free option is avail-

able. https://otter.ai/

Sampling in Qualitative ResearchResearchers should recognize that each qual-

itative study is unique. Therefore, qualitative

researchers must investigate the totality of the

circumstances related to their problem, research

site, participants, legal implications, and ethics to

determine the best approach for recruitment, data

collection, and analysis. One sampling technique

does not fit all studies.

Sampling in Phenomenological Studies: consider-

ing the challenge of ensuring quality in qualitative

research, Tracy (2010) identified eight conven-

tional criteria for producing excellence. Four of

the criteria defined by Tracy related to the depth

of inquiry, specifically; the criteria are: rich rigor,

credibility, resonance, and significance of the

contribution. Meeting these criteria require a suf-

ficient number of participants so that the resulting

26

descriptions, discussions, and conclusions provide

rich, deep, and detailed information that is reli-

able and valid (Bernard, 2013).

Sampling in Case Studies: the sampling tech-

niques used in case studies vary and are de-

pendent on several considerations (Saunders &

Townsend, 2018). Irrespective of the technique

chosen, the researcher must justify (rationalize for

the reader) their use.

Furthermore, gaining access to a population or

subgroup for inclusion in a case study relates to

feasibility; will the researcher have physical or

virtual access to the participants?

Another consideration for case studies is the

issue of sample sufficiency. How and when does

the researcher know if the sample is enough?

Saturation is viewed as the gold standard to

determine when data are collected from enough

participants (see “Data Saturation” in this guide).

Triangulation of interview data with other identi-

fiable sources (i.e., government data, the body

of literature, reliable and related internet sources,

etc.) can lead to saturation (see “Triangulation” in

this guide). Member-checking (selective re-inter-

viewing of participants) or transcript review (each

participant reviews a transcript of their interview

to verify or correct the data) are supportive mea-

sures a researcher can use to develop a level of

thoroughness in the collection process.

References and suggested reading:Bernard, H.R. (2013). Social research methods: Qualitative and quantitative approaches. Thousand Oaks, CA: Sage.

Cassell, Catherine, Cunliffe, A.L. & Grandy, G. (2018). The Sage handbook of qualitative business and management research methods: History and traditions. Sage Publications, Ltd.

Saunders, M. & Townsend, K. (2018). Choosing participants. In The Sage handbook of qualitative business and management research methods (pp. 480-492). Sage Publications, Ltd., https://www-doi-org.proxy1.ncu.edu/10.4135/9781526430212 https://methods-sagepub-com.proxy1.ncu.edu/base/download/bookchapter/handbook-of-qualitative-business-management-research-methods-v1/i3035.xml

Tracy, S.J. (2010). Qualitative quality: Eight “big-tent” criteria for excellent qualitative research. Qualitative inquiry, 16, 837-851. Doi:10.1177/1077800410383121

Data SaturationData saturation is attained when there is sufficient

information to replicate the study, when the ability

to obtain additional new information has been

achieved, and when further coding is no longer

possible (Fusch and Ness, 2015). According to

Fusch and Ness, 2015: 1411), “There is a direct

link between data triangulation and data satura-

tion; the one (data triangulation) ensures the other

27

(data saturation).”

During data collection, students should consider

if and when they have reached saturation. Stu-

dents should aim for data saturation in their data

generation. Furthermore, they should state in their

dissertation how they know that they did, in fact,

reach saturation. It is not sufficient to simply claim

saturation was reached. Instead, students need to

articulate and defend how they reached it.

References and suggested reading:Fusch, P.I., & Ness, L.R. (2015). Are we there yet? Data saturation in qualitative research. The qualitative report 2015 20(9), 1408-1416. Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., Bartlam, B., … Jinks, C. (2017). Saturation in qualitative research: Exploring its conceptualization and operationalization. Quality and quantity, 52(4), 1893–1907.

Weller, S.C., Vickers, B., Bernard, H.R., Blackburn, A.M., Borgatti, S., Gravlee, C.C., & Johnson, J.C. (2018). Open-ended interview questions and saturation. Plos one, 13(6), 1-18.

Triangulation Triangulation refers to multiple approaches to

collecting data, with the goal of enhancing the

credibility – and ultimately the trustworthiness – of

a qualitative study. Triangulation leads to a more

comprehensive and rigorous understanding of the

phenomenon under study (Salkind, 2010), and is

a required part of case study research at NCU.

Furthermore, triangulation relates directly to data

saturation (see “Data Saturation” in this guide for

further discussion on this topic).

Dixon, Singleton, and Straits (2016: 329) state

that triangulation “refers to the use of two or more

dissimilar methods to address the same research

question,” where “the strengths of one method

offset the weaknesses of the other.”According

to Denzin (1978), there are four main types of triangulation: a) data source triangulation, b) method triangulation, c) theory triangulation, and d) investigator triangulation. The first two types are the most common in NCU doctoral research studies that employ a qualitative method. Theo-ry triangulation is used less frequently, whereas investigator triangulation is never used (because doctoral candidates must complete their own dissertation research, without the assistance of others). Data source triangulation means that the

28

student is collecting data from different categories

of people, documents, or sources. For example, a

student may interview both leaders and followers

in an organizational case study, in addition to

analyzing relevant company records about lead-

ership development programs. Method triangula-

tion involves “the use of multiple methods of data

collection about the same phenomenon” (Cope,

2014: 545) (See “Mixed-Methods Research” in

this guide). Theory triangulation means that the

student is analyzing and interpreting data from

the perspective of multiple theories. For example,

a student may explore a research question about

employee motivation by analyzing data from

interviews through the different lenses of Expec-

tancy Theory, Herzberg’s Two-Factor Theory, and

the Theory of Attribution.

It is possible for students to combine data source,

method and theory triangulation strategies. Stu-

dents should explain which types of triangulation

methods are used, justify the rationale, and ad-

dress the expected quality enhancements to the

overall credibility of study results.

References and suggested reading:Cope, D.G. (2013). The use of triangulation in qualitative research. Oncology nursing research, 41(5), 545-547.

Denzin, N.K. (1978). The research act: A theoretical introduction to sociological methods. New York, NY: Praeger.

Dixon, J.C., Singleton, Jr., R.A. & Straits, B.C. (2016) The process of social research. New York: Oxford University Press.

Salkind, N.J. (2010). Triangulation. In Encyclopedia of research design (pp. 1538-1540). Thousand Oaks, CA: Sage Publications, Ltd.

Vasileiou, K., Barnett, J., Thorpe, S., & Young, T. (2018). Characterising and justifying sample size sufficiency in interview-based studies: Systematic analysis of qualitative health research over a 15-year period. BMC medical research methodology, 18.

Yin, R. K. (2012). Case study methods. In APA handbook of research methods in psychology, Vol 2: Research designs: Quantitative, qualitative, neuropsychological, and biological (pp. 141–155). Washington, DC: American Psychological Association.

TrustworthinessThe focus of qualitative research is to develop rich

and complex explorations of phenomena based

on a relatively small number of participants, rath-

er than obtaining large, statistically representative

samples. This focus has led qualitative researchers

to substitute the traditional quantitative quality

measures of validity and reliability, in favor of

the trustworthiness quality criterion. Trustworthi-

ness, in a qualitative research study, indicates the

degree to which “the inquiry’s findings are worth

paying attention to” (Lincoln & Guba, 1985:

290).

In practical terms, this means students who use

a qualitative research method should describe

how they will address the following four aspects

29

of the trustworthiness quality criterion: credibility,

transferability, dependability, and confirmability.

Credibility of findings indicate the “confidence in

the truth of findings” (Cohen & Crabtree, 2006,

para 1). To enhance the credibility of findings, a

study may involve member checking, triangulating

collected data through use of various sources,

considering negative evidence, and integrat-

ing existing research into the analysis of study

findings to reach conclusions. Transferability of

findings indicates the degree to which findings

“have applicability in other contexts” (Cohen &

Crabtree, 2006, para 1). Dependability refers to

the degree to which research findings “are consis-

tent and could be repeated” (Cohen & Crabtree,

2006, para 1). Confirmability is a “degree of

neutrality, or the extent to which the findings of

a study are shaped by the respondents and not

researcher bias, motivation, or interest” (Cohen &

Crabtree, 2006, para 1).

Dependability and confirmability are often deter-

mined through a formal external research audit,

which may not be feasible or necessary for NCU

dissertation students. Instead, dependability can

be enhanced by consistent application of proper

qualitative data analysis techniques and through

the researcher’s awareness of personal bias.

Confirmability can be enhanced through careful

records management of all collected data; and by

maintaining a research journal to: a) document

coding rules and decisions made during data

collection and analysis; b) allow the researcher to

reflect on the research process and his or her role

during data collection and analysis; and c) articu-

late any observations and insights that may affect

the outcome of the study (Lamb, 2013).

References and suggested reading:Cohen, D., & Crabtree, B. (2006). Lincoln and Guba’s evaluative criteria. Robert Wood Johnson Foundation, ‘Qualitative Research Guidelines Project’. Retrieved from: http://www.qualres.org/HomeLinc-3684.html

Lamb, D. (2013). Research in the first person:

30

Reflection on the research experience using a research journal. Market & social research, 21(2), 32-29.

Lincoln, Y.S., & Guba, E.G. (1985). Naturalistic inquiry. Beverly Hills, CA: Sage Publications.

Member CheckingOne of the data validation techniques qualitative

researchers can use to help eliminate bias from

their data collection and analysis is “member

checking.” According to Creswell and Miller

(2000), member checking is the most crucial step

for ensuring credibility in a study, and consists of

taking data and interpretations back to partici-

pants. Member checking can take place in multi-

ple formats. Researchers can ask participants to

review an interview transcript to ensure that the

transcript includes what the participant said (Birt,

Scott, & Cavers, 2016). It could include the re-

searcher interpreting the responses received from

the participant and then allowing the participant

to review those interpretations to ensure that the

researcher interpreted the participant’s responses

correctly (Birt, Scott, & Cavers, 2016). In the case

of a focus group, it could mean interpreting and

synthesizing the responses of the collective group

and then asking the members of the group to re-

view those interpretations to ensure the researcher

interpreted the collective responses correctly (Birt,

Scott, & Cavers, 2016).

It is important to allow the respondents to have the ability to check researcher interpretations of their responses to ensure that the researcher has not interjected his or her own opinions, experiences, or biases into their responses in a way that will skew the results of the study. Validation of quali-tative research is extremely important, as it helps to eliminate a potential weakness of qualitative research. Students should build in time in their research plan to ensure member checking takes place.

References and suggested reading:Birt, L., Scott, S., & Cavers, D. (2016). Member checking: A tool to enhance trustworthiness or merely a nod to validation? Qualitative health research 26, 1802-1811.

Creswell, J.W., & Miller, D.L. (2000). Determining validity in qualitative inquiry. Theory into practice, 39(3), 124–130.

Coding and thematic analysisCoding is a critical part of analyzing qualitative data, including thematic analysis. Coding is not rocket science, but it seems to confound the qual-itative researcher. Coding data is the disassem-bling or deciphering step used to determine what the data means (Castleberry & Nolen, 2018).Saldaña explained coding as a “word or short phrase” that represents or captures the essence of a small section of narrative or visual data (Sal-daña, as cited in Rogers, 2018: 4).

There are two common starting points for gener-

31

ating codes for data analysis: starting with the

framework or beginning with the data itself. Con-

sider that every research problem is framed by a

theory or a set of concepts; this is an established

research norm. This theoretical or conceptual

framework can be the starting point for gener-

ating codes for data analysis (Gläser & Laudel,

2013). The researcher who deeply understands

the framework can develop a list, or nodal map,

of elements of the theory or concepts. The next

step would be to search the data for these ele-

ments to make annotations. Pierre and Jackson

(2014) used an earlier researcher’s terminology,

‘thinking in theory,’ to describe the results of cod-

ing. Applying codes based on the framework is

how the researcher disassembles the raw data.

Alternatively, the researcher can develop codes

from the data itself, and reverse engineer the data

into a logical interpretation of the phenomenon

under study. Essentially, the researcher uses a heu-

ristic approach to determine what the data means

(Rogers, 2018). Regardless of the approach cho-

sen by the researcher, the goal is to deconstruct

the data in preparation for the next phase of data

analysis.

Caulfield (2019) identifies coding as step #2

(after becoming familiar with the data) of the pro-

cess of thematic analysis. He states that coding

is creating short labels for parts of the text in the

data (e.g. interview transcripts) that describe what

it is about. All data is coded, adding new labels

(codes) during the process (Caulfield, 2019). Af-

ter coding is completed, the third step in the the-

matic analysis process is identifying patterns and

themes among the codes. The Caulfield (2019)

resource (see below) can be viewed for an exam-

ple of how to do this. Themes are then reviewed

and further analyzed, including identifying final

themes and what they mean (Caulfield, 2019).

Regardless of whether the process of coding

is aided by a software program (e.g. NVivo),

coding is done by the researcher (the software

does not do the coding). NVivo is now available

at no cost to NCU students through the Student

Technology Resource Center. You can access the

software through the University Services module

in NCUOne. One way of coding data, if done

in Microsoft Word, is to color code text, making

all text about the same code (or topic) the same

32

color. This text can then be later analyzed, using

further colors and codes, as necessary.

References and suggested reading:Castleberry, A., & Nolen, A. (2018). Thematic analysis of qualitative research data: Is it as easy as it sounds? Currents in pharmacy teaching and learning, 10, 807-815.

Caulfield,J. (2019). How to do thematic analysis. Available at: https://www.scribbr.com/methodology/thematic-analysis/.

Evers, J.C. (2016). Elaborating on thick analysis: About thoroughness and creativity in qualitative analysis. Forum: Qualitative social research, 17(1). Gläser, J., & Laudel, G. (2013). Life with and without coding: Two methods for early-stage data analysis in qualitative research aiming at causal explanations. Forum: Qualitative social research, 14(2).

Maguire, M., & Delahunt, B. (2017). Doing a thematic analysis: A Practical, step-by-step guide for learning and teaching scholars. All Ireland journal of higher education, 9(3). https://ojs.aishe.org/index.php/aishe-j/article/download/335/553

Rogers, R. (2018). Coding and writing analytic memos on qualitative data: A review of Johnny Saldaña’s the coding manual for qualitative researchers. Qualitative report, 23, 889-892.

St. Pierre, E.A., & Jackson, A.Y. (2014). Qualitative data analysis after coding. Qualitative inquiry, 20, 715-719.

Yin, R.K. (2015). Qualitative research from start to finish. New York, NY: Guilford Publications.

Including Data in the Findings (Chapter 4) of the DissertationIn order to substantiate the claims made in disser-

tations, it is important for students to include data

they have collected within their Findings chapter.

Verbatim quotes from interviews, or content from

documents analyzed, help to substantiate summa-

ries and general conclusions students make from

the data. Including data generously throughout

Chapter 4 of a dissertation helps students better

defend their claims and justify their arguments.

Including sufficient data within the dissertation is

also necessary to demonstrate that the data was

actually collected by the student, and that the stu-

dent is knowledgeable about how to adequately

integrate data into their writing. It also can make

reading a dissertation more enjoyable and en-

gaging, and helps ensure the reader that summa-

ries and the analysis of the data are congruent

with the actual data.

Quotes should not only be used to highlight

unusual or extreme issues (though these can be

included). Instead, they should be selected on the

basis of their appropriateness to the findings, and

33

how they represent major themes of the over-

all study. While specific numbers of how many

quotes to use are not provided here, Chapter 4

(and also, in some cases, Chapter 5) should be

rich with the inclusion of this data, providing evi-

dence for the claims made in the dissertation.

References and suggested reading:Corden, A., & Sainsbury, R. (2006). Using verbatim quotations in reporting qualitative social research: Researchers’ views. York, UK: University of York.

Yin, R.K. (2015). Qualitative research from start to finish. New York, NY: Guilford Publications.

www.ncu.edu

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