Post-9/11 Veterans in Business Dissertation

Background

At present, the contribution of post-9/11 military veterans to organizational culture in the civilian workforce is under-researched; therefore, the current study focuses on the post-9/11 veterans in Yorktown Systems Group and examines what competitive business advantages might be achievable via intentional hiring strategies. The objective of the study is to explore how the adoption of a military mindset might influence the company culture and identify the competitive advantages of the post-9/11 veterans in the business setting.

The research questions are the following:

1. Can the adoption of a military mindset of post-9/11 era veterans impact the company culture?
2. What are common competitive advantages that businesses achieve through the hiring of post-9/11 era veterans?
3. Is the intentional hiring of post-9/11 veterans an effective practice from a human resource perspective?

Ultimately, the third chapter ‘Methodology’ introduces the proposed research methods and designs and summarizes the primary steps of qualitative research: the overview of population, sampling, data collection, data processing, and data analysis. Lastly, assumptions, limitations, delimitations, and ethical assurances of the methodology are thoroughly discussed.

Research Method and Design

The current sub-chapter provides insights into the research methods and designs implemented in the doctoral study project. Therefore, the primary objective of the chapter is to present an overview of the actualized research method, the advantages over other prominent research methods, and to justify the selection of the current research designs. Each of the aforementioned objectives is thoroughly described and substantiated to support the methodology for the DSP.

Research Method Overview

The proposed DSP utilizes the qualitative research method and focuses on interviews, questionnaires, and surveys as primary data collection techniques. In general, qualitative research refers to the research method that significantly emphasizes non-numerical data and frequently reveals phenomena that quantitative methods fail to uncover (Bansal, Smith & Vaara, 2018). Therefore, this type of methodology is utilized to conduct in-depth research and understand real-world problems by exploiting the narrative techniques of data collection (Moser & Korstjens, 2017). Qualitative research has received substantial attention from both the academic community and business organizations in recent years (Cassel, Cunliffe & Grandy, 2018). Qualitative methods are particularly efficient to identify the opinions, attitudes, behaviors, objectives, and other types of personal information of the selected target population (Cassel et al., 2018). As a result, the proposed methodology is suited to understand the perspectives of the employees of Yorktown Systems Group according to the stated research questions.

Unlike quantitative research, qualitative methods generally utilize smaller samples with no concern for numerical representation. As a result, qualitative research is subjective and is frequently implemented in exploratory studies with the objective to examine individual perspectives on the topic. Evidently, there are certain advantages and disadvantages associated with both methods, such as researcher bias of qualitative designs or the general superficiality of the quantitative research. However, qualitative research is generally considered to be appropriate for exploratory studies in the business setting due to the vast emphasis on the in-depth understanding of the analyzed phenomena (Basias & Pollalis, 2018). Therefore, the chosen research method for the current DSP is qualitative research, and the justification for the selection is thoroughly described in the consequent sub-chapters.

Research Design Overview

Consequently, it is essential to elaborate on the particular research designs implemented in the DSP. Qualitative research is a complex notion that includes a large variety of techniques, data collection methods, designs, analytical frameworks, etc. For instance, while there is certain disagreement concerning terminology in the academic community, most experts agree that qualitative designs include ethnography, phenomenology, grounded theory, case studies, critical social theory, etc. (Korstjens & Moser, 2017). At the same time, narrative techniques, such as interviews, questionnaires, and surveys, are transparently separated from the research designs and generally referred to as data collection methods. Furthermore, the definitions of qualitative designs are frequently interconnected, providing additional obstacles to choosing the most appropriate framework (Korstjens & Moser, 2017). A brief description of the most prominent qualitative research designs is presented below.

The five potential research designs that could be implemented in the current DSP are ethnography, phenomenology, content analysis, grounded theory, and case study. All of the aforementioned strategies are relevant research designs with certain advantages, disadvantages, and specific scope of the study. Ethnography emphasizes the cultural aspect of human relationships and attempts to understand the behavior of individuals within a group or an organization (Korstjens & Moser, 2017). While this objective transparently corresponds to the first research question ‘Can the adoption of a military mindset of post-9/11 era veterans impact the company culture?’, ethnography does not meet the requirements of the purpose statement. Thus, ethnography is not the appropriate research design for the current project.

Phenomenology is the most extensive research design concerning the psychology of the participants and explaining the certain phenomena behind their behavior. Similar to ethnography, phenomenology directly corresponds to one of the research questions and might transparently demonstrate the peculiarities of the military mindset of the post-9/11 veterans in the business setting (Jamali, 2018). However, this strategy does not reveal the potential competitive advantages of the veterans in the organizational culture. Thus, phenomenology cannot be considered an appropriate research design due to a more extensive scope of the study. Content analysis is another prominent strategy that attempts to retrieve necessary information from the narrative data obtained from the participants via interviews and questionnaires (Korstjens & Moser, 2017). However, the primary objective of this design is to establish a conceptual framework based on certain key themes mentioned by the informants and consequent analysis (Korstjens & Moser, 2017). Ultimately, while this strategy is efficient in regard to the immediate data analysis, the content analysis fails to grasp the whole scope of the current study.

The two remaining qualitative research designs that might be appropriate for the DSP are grounded theory and case study. Both strategies are frequently utilized in social and business settings to reveal the real-world connections between individuals and organizations (Jamali, 2018). Consequently, the foundation for the two designs is the in-depth research of a certain phenomenon in the natural context (Alam, 2020). In the current DSP, the phenomenon is the military mindset of the post-9/11 veterans, and the social context involves the business setting and organizational culture. From these considerations, both designs might be applicable to answer the research questions and meet the criteria of the purpose statement. Furthermore, grounded theory and case study reflect the exploratory nature of the current DSP and are particularly efficient to address complex social processes (Alam, 2020). Therefore, the primary subject of the research design selection is the choice between the grounded theory and case studies.

As mentioned prior, both designs share a large number of similarities, and many experts use the two terminologies interchangeably (Porter, 2019). However, for the sake of the current work, it is necessary to establish a singular research design. It is generally assumed that grounded theory is a fundamental methodology approach that might be utilized in various settings and multiple scenarios (Johansson, 2019). Even though the proposed research questions are generalized, the empirical part of the DSP focuses on the post-9/11 veterans in the Yorktown Systems Group. The emphasis on the sole entity is one of the typical features of qualitative case studies and allows for in-depth research of certain phenomena in the social context (Alam, 2020). As a result, the selected research design for the current project is acknowledged as a case study.

Research Design Summary

Similar to most qualitative research designs, case studies are generally associated with five primary steps: sampling, data collection, data processing, data analysis, and interpretation of the findings. These procedures allow for the most reliable results; however, each of the aforementioned steps should be completed according to the case study design to ensure the validity of the research. While the thorough description of sampling, data collection, data analysis, and interpretation will be presented in the following chapters, the current sub-chapter displays a brief overview of the mentioned procedures and provides support for the application of the chosen design.

According to qualitative case studies, the appropriate sampling size should consist of fifteen to twenty participants to establish a deep connection between the researcher and the informants (Alam, 2020). Furthermore, narrowing the sample would allow for in-depth conversations that produce more meaningful results. From these considerations, the proposed sampling size involves twenty participants, namely, fifteen post-9/11 veterans (currently employed at Yorktown Systems Group), two HR managers, and three senior executives. The selected format of sampling size meets the aforementioned criteria and is appropriate for a qualitative case study.

Similar to most qualitative designs, a case study utilizes interviews, questionnaires, and surveys as primary data collection techniques. All of these methods are exclusive to qualitative research and are highly subjective; therefore, they require an extensive level of expertise from the researcher (Alam, 2020). For instance, it is essential to minimize the researcher and interviewer bias to ensure the validity of the results. For this purpose, the expert should explicitly present the necessary information and guidelines to the informants, and maintain a healthy and relaxed atmosphere to retrieve honest answers (as opposed to socially expected responses). Furthermore, it is the responsibility of the researcher to maintain an unbiased stance on the subject and be transparent in regard to data collection procedures. Lastly, the questions in interviews should be presented in a neutral manner to minimize the response bias from the participants. The details of data collection techniques, such as the type of interviews, triangulation, and bias elimination, are thoroughly discussed in the respective sub-chapter. Ultimately, the current doctoral study project follows the aforementioned procedures concerning data collection methods; therefore, the qualitative case study is an appropriate research design for the paper.

After gathering the data, it is essential to process and analyze the information. The collected audio recordings are transcribed into written text by utilizing the web application Dedoose. This software significantly facilitates the qualitative research process by assisting the expert in transcribing, coding, and analyzing the data (Dedoose, n.d.). Consequently, the chosen data processing strategy is deductive coding. In general, this method refers to the processing of the data based on a set of pre-determined theories or key concepts (Azungah, 2018). In the current project, the points of interest include the qualities of the military mindset, such as leadership, discipline, resilience, and teamwork, and how these concepts are applied in the organizational culture. Based on these key points, the collected data is rationalized and designated to specific categories.

Lastly, after processing the information, the data is examined according to the content analysis method. Content analysis is one of the standard strategies used to rationalize transcribed interview texts in qualitative research and offers a large variety of advantages (Erlingsson & Brysiewicz, 2017). It provides a comprehensive analysis of the themes, categories, meaning units, and identifies explicit and implicit data (Erlingsson & Brysiewicz, 2017). Furthermore, it is possible to utilize the techniques of content analysis, such as affect extraction and proximity analysis, to rationalize questionnaires and surveys (Crosley, 2021). These strategies are particularly effective to establish the attitudes of the participants toward certain concepts and identify the rationale behind the behavioral patterns of the informants (Crosley, 2021). Ultimately, the brief overview of the procedures transparently indicates that the qualitative case study design is appropriate for the current doctoral study project.

Research Design Justification

As mentioned prior, qualitative research is associated with distinguished advantages and limitations, as opposed to quantitative methods. The primary differences include the non-numeric nature, the focus on the context, dimensions, inclusivity of the researcher, scope of the study, the structure of the research hypotheses, and type of the analysis (Queirós, Faria & Almeida, 2017). The current sub-chapter justifies the proposed research method and transparently explains why qualitative research is the optimal choice for the current doctoral study project.

The primary difference between qualitative and quantitative methods is their relation to the nature of research. Quantitative designs are associated with concrete numbers, quantified data, established hypotheses, and automated data analysis methods (Queirós et al., 2017). Furthermore, quantitative research is generally acknowledged to provide a shallow understanding of the subject due to large samples and the lack of the researcher’s direct participation (Queirós et al., 2017). Therefore, this method is not generally applied to exploratory studies concerning relevant social problems that require the direct involvement of the researcher, thus, quantitative design is not appropriate for the current DSP.

On the other hand, qualitative research is frequently utilized in exploratory studies in new research areas (Basias & Pollalis, 2018). The method is characterized by the in-depth analysis of the examined phenomenon, the proximity of the researcher to the target group, the flexibility of the approach, and the longer range of scope of the study in time (Queirós et al., 2017). Ultimately, due to the exploratory nature of the DSP purpose and research questions, the qualitative research designs might provide more insights into the topic and are explicitly justified.

Population

The population of the study is generally classified into two separate categories: general population and target population. The former refers to any potential stakeholders that might benefit from the current research, which includes the target population, the academic community, the researcher, and others. The target population is a narrower group that refers solely to the participants of the study. A more thorough description of the two populations is provided in the following sub-chapters.

General Population

The general population of the research refers to the major stakeholders of the study. In this DSP, the general population includes the post-9/11 veterans, business organizations (HR specialists and executives, in particular), government, the academic community, and the researcher. Currently there are more than three million post-9/11 veterans in the civilian workforce, and this number is projected to reach four million by 2026 (Aronson et al., 2019). Evidently, all the groups of the general population profit from the current study. Post-9/11 veterans and business organizations benefit from the empirical evidence explored in the DSP, which might include the competitive advantages of military veterans in business settings. The analysis of such initiatives might stimulate the interest of contemporary organizations in hiring post-9/11 veterans, which provides mutual interest for both parties.

Furthermore, the academic community and the researcher benefit due to the advancement of the subject and contribution to the scientific field of social sciences. While the current doctoral study project is self-sustaining and provides relevant information, it might also pave the way for future research, thus, contributing to the academic community. Lastly, the DSP might benefit the government and stimulate new initiatives and programs to support the employment services of post-9/11 veterans. In theory, such action reduces the percentage of unemployment in the country and significantly advances the national economy.

Target Population

The target population of the research refers to the participants of the study. As mentioned before, the three primary qualitative data collection methods implemented in the DSP are interviews, questionnaires, and observation. All informants of the study are employees of Yorktown Systems Group, namely, post-9/11 veterans of various occupations (business analysts, instructors, IT experts), HR specialists/managers, and executives. Each group is represented by a certain number of informants, and the overall sample does not exceed twenty participants.

All the groups of the target population will be asked to participate in interviews and to fill in the questionnaires. The active participation of the three target groups is necessary to establish reliable results and answer the research questions. The inclusionary trait for the employees of the Yorktown Systems Group is the participation in military activities after the 11th of September 2001. The inclusionary trait for HR specialists and executives is the work experience in Yorktown Systems Group. As a result, people with less than one year of service period are excluded from the target population. Ultimately, the described approach to the target population guarantees the coverage of both the military mindset in the business setting and organizational aspects.

Sample

Sampling is one of the most significant procedures in qualitative research to ensure the reliability and validity of the results. As mentioned prior, the optimal sampling size for qualitative research is fifteen to twenty participants (Alam, 2020). This range allows to establish a deep connection between the researcher and the informants to guarantee transparent findings. As a result, twenty employees of Yorktown Systems Group partake in the current DSP: fifteen post-9/11 veterans of various occupations (business analysts, instructors, IT experts), two HR specialists, and three executives of the organization. The number might deviate slightly due to the workload of the participants; however, the ultimate sampling size varies from fifteen to twenty-five informants and is appropriate to qualitative research. It is essential to provide a flexible schedule of interview sessions to the participants to minimize the fluctuations of the sampling size.

Furthermore, there is a large variety of sampling strategies, including purposive, criterion, theoretical, convenience, snowball, maximum variation, extreme case, typical case, and confirming and disconfirming sampling types (Moser & Korstjens, 2018). The current project utilizes criterion sampling, which implies the selection of participants with certain pre-determined qualities (Moser & Korstjens, 2018). For the largest part of the sampling size, only post-9/11 veterans are selected. Thus, the primary criterion for this group is the military experience after September 11, 2001. The decisive condition for HR specialists is the work experience period of more than one year. This criterion ensures that the interviewed managers have a complete understanding of the organizational culture in Yorktown Systems Group and the impact of the military veterans on business. Ultimately, the current DSP utilizes the criterion sampling strategy with fifteen to twenty-five participants.

Data Collection Instruments

The current sub-chapter displays the chosen data collection methods and justifies the selection. The data collection instruments are interviews, questionnaires, and surveys. The initial step to data collection is the overview of the secondary archived data and literature review of prior research concerning the subject. The implemented data collection methods, such as interviews and questionnaires, are widely used in social and business settings due to high emphasis on the research phenomenon and in-depth research (Basias & Pollalis, 2018). Due to the efficiency of these approaches, qualitative and mixed methods have become the flagman of social studies and are appropriate to answer the research questions of the current doctoral study project.

Overview of the Data Collection Methods

The qualitative data collection procedures implemented in the current doctoral study are interviews, questionnaires, and surveys. These techniques are the most commonly utilized methods to gather personal information, such as perspectives, attitudes, and behaviors of the participants, in qualitative research (Aspers & Corte, 2019). Interviews are one-on-one conversations with the objective to examine the perspectives and attitudes of the participants concerning certain phenomenon (Moser & Korstjens, 2018). They are typically administered in a face-to-face offline manner; however, in the realities of the coronavirus pandemic, the interviews will be executed via web-based applications, such as Skype or Zoom. While this is not the ideal case for reliable data collection, it is a necessary step to guarantee the safety of the informants and the researcher.

The two other instruments of data collection are questionnaires and surveys. The former refers to a set of questions presented to the informant in either an online or offline manner (Surveymonkey, n.d.). The survey is a broader concept that covers the questionnaire and the consequent analysis of the provided answers (Surveymonkey, n.d.). The two data collection methods are frequently confused and used interchangeably due to the similarities of the procedures (Surveymonkey, n.d.). In the scope of the current project, questionnaires represent a set of open-ended questions presented to the participants in an online manner via web-based applications after the interviews. Some of the most prominent websites to conduct questionnaires are SurveyMonkey and GoogleForms, which differ slightly in capabilities, interface, and pricing. Consequently, the surveys represent the analysis of the provided answers based on certain coding schemes. In the current DSP, the data processing is completed via deductive coding with a set of pre-determined key concepts. Ultimately, the surveys are considered to be a distinguished data collection method in the scope of the project.

Lastly, in the case of unforeseen circumstances, a focus group is acknowledged as a contingency data collection method. The contingency might occur due to the lack of gathered data from the established methods, the inability or reluctance of certain participants to engage in interviews or questionnaires, and other emergencies. In general, focus groups refer to collective discussions concerning a certain phenomenon under the supervision of a moderator (Sim & Waterfield, 2019). Similar to the interviews, this method is typically performed in the offline setting to ensure the direct interaction between the participants and the researcher. Nevertheless, at present, it is essential to conduct the focus groups in an online manner via web-based applications due to the pandemic restrictions. In the current DSP, focus groups are not considered as the primary data collection source primarily due to the significance of the direct interaction between the informants and the expert. Thus, focus groups might not be the effective method of data collection in the realities of COVID-19 restrictions. However, even though a focus group is a secondary data collection method in the scope of the current work, it is essential to establish the baseline of the approach and apprehend the understanding of its primary principles in case other data collection instruments do not suffice.

The implementation of interviews, questionnaires, surveys, and, potentially, focus groups at the same time ensures the reliability and validity of the research. The simultaneous application of three or more methods is called triangulation and is one of the most commonly used strategies in qualitative research (Alam, 2020). Such an arrangement allows recompensing the disadvantages of certain data collection methods by utilizing the advantages of others (Alam, 2020). Furthermore, the participants will fill in the questionnaires after engaging in the interviews, and the time between the two procedures allows the informants the re-evaluate the information concerning the subject. Therefore, the availability of several data collection methods guarantees more accurate findings.

Development of the Materials

Materials for the data collection instruments are developed according to the purpose statement, research questions, and the standards of qualitative research. Similar to the population and sampling criteria, the selected data collection methods reflect the primary objective of the project – to explore the military mindset of post-9/11 veterans in the business setting. For this purpose, semi-structured interviews, questionnaires, and surveys are chosen as the most optimal data collection methods.

For each of the methods, the standard variables of qualitative research, such as age, gender, ethnic heritage, and education level, are determined. Furthermore, each participant of the primary target group provides personal information concerning the military experience, work experience in Yorktown Systems Group, and preliminary training, according to the ethical assurances and restrictions. Consequently, the questions for each of the target groups (military veteran employees, HR specialists, and executives) differ, depending on their field of expertise. The post-9/11 veterans are inquired concerning their experience in the organization, transition to the civilian workforce, business operations, relationships with colleagues, and customer satisfaction. HR specialists are asked about employee satisfaction and expectations, skills development, and general ideas regarding the military mindset in business settings. Lastly, executives are inquired concerning the vision and mission of the company, organizational and culture changes, and operation functions. The semi-structured interviews and questionnaires are developed based on the aforementioned variables.

Interview and Survey Protocols

In the current project, the interviews with participants are semi-structured and allow the researcher to change questions during the procedure. Semi-structured interviews are the most commonly used type of interview in social sciences (Alam, 2020). They allow the researcher to establish a deep connection with the participants, thus, stimulating transparent answers and opinions (Alam, 2020). In semi-structured interviews, the expert prepares a set of pre-determined questions to ascertain the course of the dialogue and establish the baseline for the conversation (Alam, 2020). However, the researcher is also allowed to elaborate on certain topics and ask additional questions if they deem so. Therefore, unlike the survey, the questions do not necessarily reflect the specific phenomena but rather set the tone of the conversation (Alam, 2020).

Justification of the Data Collection Methods

The primary data collection methods of the current project are commonly utilized in qualitative studies, and various experts have had immense success by implementing interviews and questionnaires in their research. However, it is essential to conduct a pilot study of at least two members of the target group to ensure the efficiency of the selected data collection methods and their implementations. The pilot study comprises all of the aforementioned elements of qualitative research, such as method, design, data collection protocols, and will be conducted after IRB approval concerning ethical assurances. The pilot study will also determine whether the interview and questionnaire protocols are appropriate for the current project; thus, the protocols might change slightly after the empirical part of the pilot study.

Data Collection Procedures

The data collection procedures are categorized into three sequential steps: semi-structured interviews – questionnaires – surveys. As mentioned prior, the contingency data collection method is a focus group; however, it is not part of the primary research and will only be implemented in case of unforeseen emergencies. Concerning the ethical assurances, each participant is asked to complete the consent form, which allows the researcher and the academic advisor to examine and analyze the informants’ personal information and provided data, before engaging in the interviews.

Interviews

Semi-structured interviews are the most commonly used data collection instruments in qualitative research. However, they require a considerable level of expertise from the specialist to ensure the validity and reliability of the findings. For instance, the researcher must choose the questions carefully to minimize the interviewer and response biases. Since the interview is semi-structured, the tone of the conversation might change significantly, depending on the researcher and their understanding of the subject (McGrath, Palmgren & Liljedahl, 2019). As a result, the collected data is based both on the opinion of the participant and the expertise of the researcher (McGrath et al., 2019).

The interview protocols differ slightly depending on the target population group. All the guidelines for semi-structured interviews were designed according to the purpose statement and research questions. All of the interviews will be conducted via web-based applications, such as Skype or Zoom, depending on the availability of the software for the participants. The interviews will be recorded in audio files according to the consent agreement from the participants. Lastly, the respondents will be selected in a voluntary manner to ensure a mutual understanding of the objectives and transparent answers. Ultimately, the described procedure grasps the primary principles of conducting a semi-structured interview and is detailed enough for other researchers to replicate the process.

Questionnaires

Questionnaires are utilized both in quantitative research (close-ended questions) and qualitative research (open-ended questions). Evidently, only open-ended questions are used in the current project to ensure an in-depth understanding of the analyzed phenomena and adhere to the principles of qualitative research. Either SurveyMonkey or GoogleForms will be utilized for the distribution of the questionnaires among the participants. Similar to the interviews, questionnaires differ slightly depending on the target population group. All questionnaires comprise a set of ten questions, which is the optimal number to ensure in-depth answers from the respondents (SurveyMonkey, n.d.). Similar to the interviews, the given description is sufficient for other researchers to replicate the study.

Surveys

In the scope of the current work, surveys refer to the consequent analysis of the retrieved data from questionnaires according to the pre-determined coding schemes. Therefore, the survey is both the data collection and data processing method. This approach includes the questionnaire, the retrieval of information, and analysis of the responses (SurveyMonkey, n.d.). Therefore, the survey is a data collection method due to the transformation of raw data input into organized information, thus, creating a new data set, and a data processing method due to the consequent decoding. The data processing and analysis are described in detail in the followings chapters.

Data Processing

The data processing and consequent analysis are performed via both manual examination and via the assistance of digital applications. The audio recordings from interviews are transcribed via Dedoose – a web-based software application for qualitative and mixed methods research (Dedoose, n.d.). The program allows converting unorganized qualitative data, such as texts, audio recordings, images, and videos, into analyzable information by utilizing excerpting and coding strategies (Dedoose, n.d.). Dedoose allows to create specific codes and adjust their structure and weight to meet the requirements of the study. This is particularly efficient for the deductive coding strategy, which is selected as the primary instrument of data processing for the current project.

Deductive coding refers to the method of structuring data based on pre-determined key concepts (Linneberg & Korsgaard, 2019). This approach is opposed to inductive coding – a method that develops codes from the collected data (Linneberg & Korsgaard, 2019). Deductive coding is the preferred method of qualitative processing to narrow down the scope of the project and emphasize a certain phenomenon (Linneberg & Korsgaard, 2019). In the current work, the focus is the military mindset of post-9/11 veterans in business settings; therefore, it is possible to develop a set of pre-determined codes for the data processing. The codes include the key concepts, such as the military mindset, post-9/11 veterans, organizational culture, transmission to the civilian workforce, and individual qualities, such as leadership, discipline, resilience, adaptability, and teamwork. In general, the number of codes should not exceed ten concepts to maintain the proposed scope of the project (Linneberg & Korsgaard, 2019). Nevertheless, deductive coding is not an exclusive approach; therefore, if new themes and concepts emerge during the data collection process, it is possible to add new coding schemes into the data processing.

Lastly, it is essential to protect the collected data on both the physical and online mediums to ensure the confidentiality of the participants. From these considerations, the following measures are implemented: all online data is transferred to physical mediums (external hard drives or USB flash drives) each time after collecting, processing, or analyzing the data; no retrieved data is distributed to third parties, as specified in the consent agreement signed by both the researcher and the participants; efficient online data security means, such as firewalls, backup data, and OS updates, are implemented.

Data Analysis Procedures

Content analysis is the primary approach of data analysis in the current project. However, data processing and data analysis are interrelated processes, therefore, the initial steps of analysis are simultaneous to coding procedures (Linneberg & Korsgaard, 2019). Ultimately, some experts consider data coding a part of content analysis due to the vast importance of comprehensive transcription (Erlingsson & Brysiewicz, 2017). Furthermore, qualitative data analysis, as opposed to quantitative research, is not a linear process but rather a combination of coding schemes, categories, manual and software analysis (Erlingsson & Brysiewicz, 2017). As a result, content analysis requires a considerable level of expertise, proficiency, and creativity from the researcher.

Therefore, the necessary step of content analysis is deductive coding of the data retrieved from all the data collection methods to ensure the triangulation effect. For this purpose, the software Dedoose is used, which allows assigning weight and tags to all the pre-determined codes and, thus, categorize the information (Dedoose, n.d.). Evidently, the data from interviews, questionnaires, surveys, and, potentially, focus groups differ slightly; however, all the information is connected by the pre-determined key concepts and theories.

Consequently, all the excerpted texts with relevant codes are re-read again by the researcher, and the most appropriate paragraphs are categorized into themes, categories, and meaning units to further narrow down the scope of analysis (Erlingsson & Brysiewicz, 2017). By utilizing this approach, it is possible to categorize the data based on the abstraction level, where ‘theme’ (e.g. organizational culture) is the most abstract concept, and the ‘meaning unit’ (e.g. verbatim response of the participant) is the least abstract concept (Erlingsson & Brysiewicz, 2017). It is essential to keep track of all the categories to ensure a thorough analysis of the phenomenon.

Lastly, it is crucial to remember that the researcher is the most significant constituent of content analysis. Qualitative data interpretation is a reflective process, therefore, all data is analyzed via the prism of the researcher’s understanding of the subject (Erlingsson & Brysiewicz, 2017). Furthermore, the codes, categories, and themes are formulated by the researcher; thus, they need to be carefully selected to adhere to the purpose statement and research questions. Unlike quantitative data, there are always various approaches to interpret qualitative data, and different researchers might get drastically distinguished results from content analysis (Erlingsson & Brysiewicz, 2017). From these considerations, all the unique variables of qualitative analysis, such as researcher bias, intuition, pre-understanding of the subject, and even enthusiasm and determination, should be taken into account during the analysis of qualitative data.

Assumptions (300)

Assumptions of qualitative study refer to the pre-determined beliefs in regard to conducting the research. In the current DSP, the proposed assumptions concern the target population and responses of the participants. The first assumption implies that the post-9/11 military veterans, which are currently employees of the Yorktown Systems Group, reflect the corresponding part of the general population. In other words, the project assumes that the target population is subject to the research problem and purpose statement. To support this presupposition, a criterion sampling strategy is utilized, and the background of the participants is established. Nevertheless, the current hypothesis is impossible to prove completely, thus, it is subject to the assumption category.

The second assumption of the project concerns the transparency of the responses. In a qualitative study, it is complicated to ensure the complete honesty of the informants; however, it is possible to support the assumption. For this purpose, the project does not reveal any confidential information, that is pre-determined before the data collection, of the participants. Furthermore, the identities of the informants are concealed according to ethical assurances, if they require so. Such an approach promotes transparent answers and supports the described assumption. Ultimately, the two aforementioned statements are the major assumptions of the current methodology.

Limitations

Qualitative research is associated with several limitations, primarily concerning the reliability and validity of the collected data, the prevalence of socially expected answers, confidentiality, and the necessary concealment of information. Some of these risks occur regardless of the researcher’s participation; for instance, confidential information cannot be revealed for academic purposes. Furthermore, qualitative research is generally complex to replicate, thus, providing additional difficulties to determine the validity of the paper (Theofanidis & Fountouki, 2018). Nevertheless, it is possible to mitigate some of the limitations by utilizing effective research practices and ethical guidelines. It is the researcher’s responsibility to ensure the confidentiality of the participants and collected data, minimize the researcher and response biases, and provide conditions conducive to transparent conversations. The influence of the expert is the crucial aspect of conducting interviews in qualitative research. It affects the interviewer and response biases, transparency of the answers, provided by the participants, and the overall success of the project.

One more limitation of the current study concerns the obstacles posed by the coronavirus pandemic. At present, the restrictions caused by COVID-19 eliminate the possibility of direct interaction between the researcher and the informants; thus, the data collection methods will be implemented via accessible online software, such as Skype or Zoom. Furthermore, observation and focus groups have been denied as the data collection methods due to the uncertainty of the COVID-19 environment. As a result, the limitations caused by the coronavirus pandemic restrict the data collection strategies to interviews, questionnaires, and surveys via online software applications. While this is not the optimal choice for qualitative studies, this is a necessary measure to ensure the safety of both the participants and the expert. If the situation concerning the pandemic restrictions changes, it is possible to implement a more direct method of data collection and organize face-to-face interviews and focus groups.

Lastly, the chosen qualitative research design – a case study – is associated with certain limitations. The current project addresses the purpose statement and research questions based on Yorktown Systems Group. A case study of one organization does not necessarily reflect the characteristics that might represent the behavior of similar entities. Evidently, the case study design provides a large number of benefits, such as in-depth research, the proximity of the researcher to participants, and the natural context of the analyzed phenomenon; nevertheless, the findings of the project should not be generalized to the general population without precautions. As a result, additional research is frequently necessary to validate the findings of the qualitative study.

Delimitations (300)

Delimitations are the pre-determined conditions that narrow down the scope of the study and ensure the reliability of the results. In the current project, primary delimitations include the sampling type and size (criterion sampling of fifteen to twenty-five participants), setting (Yorktown Systems Group), and research method and designs (qualitative case study). The sampling size is selected according to the basic principles of qualitative studies to ensure the in-depth research and proximity of the experts to the participants. Based on the literature review, the optimal sample for qualitative case studies is equal to fifteen to twenty-five participants (Alam, 2020). The setting of the current project covers the Yorktown Systems Group, which is the only subject to the chosen qualitative design. A case study of a single entity, as opposed to multiple contexts, is an efficient method of in-depth research of a certain phenomenon (Alam, 2020). As a result, the delimitation concerning research design was pre-determined to adhere to the purpose statement and research questions.

Ethical Assurances

Due to the intimate nature of the qualitative designs and personal interactions with the participants, it is essential to adhere to ethical principles during the research. They include consent, disclosure, risk of harm, and confidentiality (Sim & Waterfield, 2019). The practical strategies that ensure all of the aforementioned assurances include briefing and debriefing, consent process, and conduct of the interview (Sim & Waterfield, 2019). Briefing and debriefing refer to the discussion with the participants concerning ethical assurances immediately prior to and after the interviews (Sim & Waterfield, 2019). These steps are necessary for qualitative research to ensure that the participants clearly understand the procedure and potential ethical risks. The mentioned approaches are used both in semi-structured interviews and focus groups.

The consent process is the most significant procedure concerning ethical assurances. In general, this term refers to the mutual agreement between the researcher and the informants in regard to confidentiality. In the current project, only the researcher and the academic advisor have access to the personal information of the participants, including age, gender, ethnic heritage, and their statements concerning the subject. The purpose of the current project is purely academic; therefore, none of the retrieved data will be revealed to the executives of Yorktown Systems Group. Confidentiality is necessary to ensure transparent answers and honest opinions from the employees of the organization. Furthermore, all the collected data will be protected during and after the study by utilizing the offline means of data storage and backup preservations. Lastly, all of the ethical principles are taken into consideration during the research, and IRB approval will be sought prior to data collection procedures.

Summary

The methodology is the necessary section in every project of the doctoral level and provides comprehensive guidelines for the empirical part of the research. Namely, it designates the type of the research method, design, sampling type, population, data collection, and data analysis instruments. Furthermore, methodology ensures the reliability, validity, and ethical assurances of the research by addressing the assumptions, limitations, and delimitations of the study. The key points of the proposed methodology are provided below.

Based on the research problem, purpose statement, and research questions, the chosen method of the project is qualitative. The selected qualitative design for the current project is the case study, and the primary means of data collection include interviews, questionnaires, and surveys. The general population of the research includes post-9/11 military veterans, business organizations, government, the academic community, and the researcher. The target population includes the employees of Yorktown Systems Group. Fifteen to twenty-five informants are chosen according to criterion sampling – a strategy based on the pre-determined conditions of the target population. As a result, approximately fifteen post-9/11 military veterans, two HR specialists, and three executives are inquired to participate in interviews and, potentially, focus groups.

The selected data collection instruments for the current project are semi-structured interviews, questionnaires, and surveys. The audio recordings from interviews are transcribed via Dedoose – a web-based software for qualitative analysis. The primary data processing method is deductive coding, which is based on a set of pre-determined codes, explained in the respective chapter. Consequently, the data is interpreted via content analysis. Lastly, the assumptions, limitations, delimitations, and ethical assurances are described in detail. After proposing the methodology for the project, the next step of the research is data collection and analysis, which are presented in the following chapter.

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