Digital Accounting Revolution and Misconception among Organizations and People
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Digital Accounting Revolution and Misconception among Organizations and People
Chapter 3: Research Methodology
There is a need to analyze the underlying trends in the professional accounting field. Primarily, this study seeks to establish how the accounting profession has been subjected to changes informed by factors such as technology. For instance, preliminary studies found that the accounting career had been exposed to a shift in practice. In a way, accountants no longer practiced their original tasks such as bookkeeping and preparation of statements of financial position. Instead, changes in the accounting sector informed by sustainable technological innovation have seen new advancements such as a shift in the traditional roles to more emerging roles such as consultancy and enabling companies to make informed decisions by providing expert opinions.
At the same time, the preliminary study findings presented in the literature review of this research established that the profession still encounters misconceptions. Whereas several individuals and organizations understand the nature and role of accounting in the decision-making process, there, for instance, exists a misconception among other segments on the same functions. This misunderstanding informed by the identified misconceptions impacts accounting positioning within the society, further impacting decision-making processes.
In lieu of the underlying background and identified needs, there is a need to analyze the accounting profession’s issues in-depth. Notably, an evaluation of the trends in professional duties and the overall understanding of the accounting profession. In the same breath, there is an imminent need to study the misconceptions surrounding the role of accounting for informed decision-making. For instance, establishing the highlighted concerns presents an opportunity for organizations, agencies, and related bodies to improve the gaps that give rise to the identified misconceptions.
The research objective is to evaluate the digital accounting revolution in a broader context. At the same time, the study is essential in promoting sustainable development and improvement that ensures that the accounting profession’s role remains solid and demonstrates efficiency in problem-solving when and as a need arises. This chapter presents the proposed approach to conducting the study. Notably, this seeks to evaluate the most appropriate data collection method in preparation for analysis. Thus, the nature of the data collection technique will be fundamental in enabling informed decision-making based on the study findings.
Subsequently, this chapter presents the proposed approach to data analysis. The nature of the data analysis approach is premised on the study objectives and research question. The other study objective given is the need to establish how digital accounting processes and dynamics impact financial automation processes and the underlying misconceptions. At the same time, the study must be objective to meet the identified needs and objectives for efficiency in recommendation and conclusions. Thus, the selected research methodology will play a massive role in strategic analysis, mainly the study’s scope, horizon, and population. Therefore, this research aims to achieve high-efficiency levels and provide a holistic approach to research methods applicable to the study.
Research Method and Design Appropriateness
Research Methods
This section presents three main research methods employed while designing the proposed approach to analysis and decision making. Quantitative research methods are concerned with numeric data and employ statistical tools to analyze the collected numerical data to conduct analysis that forms the decision-making base (Bloomfield and Fisher, 2019). On the other hand, the qualitative research method is concerned with the strategic collection, analysis, and evaluation using non-numeric data.
Subsequently, mixed methods involve using qualitative and quantitative research methods to conduct analysis and inform a basis for decision making. According to Wagner et al. (2019), the underlying research method is essential in cases where data exhibits numeric and non-numeric aspects. Thus, a qualitative approach to data analysis would be essential in analyzing the non-numeric elements of the identified data. In contrast, a quantitative research method would be essential for numeric data.
This research will employ a qualitative research design to conduct the analysis and inform the decision-making process in lieu of the underlying research methods. The choice of the research design is premised on several factors. First, the underlying topic seeks to examine the digital accounting trends and aspects over time (Teo et al., 2020). At the same time, the study is concerned with the underlying misconceptions about accounting as a practice. Thus, the nature of the research topic is more inclined to employ non-numeric data for informed decision-making processes. Hence, a qualitative research design would inform the study. Several advantages of the qualitative research method are highlighted in the following sections of this chapter.
Qualitative research has different advantages. The underlying research method is flexible from a holistic view. First, it enables the participants to express themselves as much as possible in the case of an interview. According to Bauer et al. (2021), qualitative data collected from the underlying participants enables the data collector to enjoy a flexible schedule by selecting aspects of the data collected that are essential in the decision-making process and leaving out aspects or components that are less important.
Also, qualitative research enables the data collector to gather or collect as much data from the underlying sample size. Thus, qualitative data would still gather much data in smaller sample sizes, thus promoting sustainable analysis and decision-making (Bauer et al., 2021). As such, it would enhance efficiency in the collection process and improve flexibility, meeting study objective needs.
Subsequently, qualitative research promotes high adaptability levels. Whereas this underlying feature is similar to flexibility, it is differentiated in part based on qualitative methods to uphold flexibility and enhance sustainable adjustments to ensure that the data meets the desired objectives and that the findings resonate with the underlying goals. In a broader context, this research established that adjustments in qualitative research do not necessarily impact the overall model. In essence, adaptability promotes improved time saving and decision making.
Research design
Qualitative and quantitative research are both important in informing the nature and choice of data analysis tools and approaches. In essence, wrong selection of a research design based on underlying data may lead to misrepresentation and inappropriate conclusions. Moreover, conducting an indepth analysis of selected data sources and proposed methodology is critical in ensuring that the research process is highly effective.
This study will employ a qualitative research design to conduct data analysis and establish findings for decision making processes. Qualitative research designs are sustainable in evaluating both numerical and non-numerical data, thus enhancing strategic analysis and diverse decision making. According to Levvitt et al (2021), qualitative research design is comprehensive, and goes beyond understanding the underlying data. Thus, it presents an opportunity to enhance comprehensiveness in data presentation.
Meanwhile, this study is tended to examine digital accounting revolution, and how the advent of accounting technology impacts performance among organizations; this study topic also, presents an opportunity to examine the inherent misconceptions among individuals and organizations. Additionally, the study presents a strategic opportunity to propose changes and frameworks that would improve the accounting profession, by drawing from real time occurrences and data collected from the participants. Based on the data’s nature, the research will adopt a qualitative research design, to achieve the SMART objectives, and enhance precision in recommendations.
In using qualitative research design to meet the study’s objectives, the research will employ primary sources to collect data. Essentially, the research will adopt interviews to collect data. Interviews present an opportunity for the study to gather data and information from the primary source, mitigating bias and data erosion that is informed by data transmission (Rahman, 2020). Thus, an interview approach to data collection will promote the SMART’s accuracy component to achieve the underlying study objectives.
Moreover, interviews enhance data diversity, thus, achieving comprehensiveness. Diverse data is essential in understanding how digital accounting revolution impacts accounting profession. By integrating interviews, the research presents an opportunity to evaluate accounting revolution and misconceptions, and how they are perceived from an individual and organizational perspective. Again, interviews promote precision, objectivity and data reliability thus, achieving efficient decision-making.
A case study may be defined as an in-depth approach to understanding an underlying societal issue, drawing from real-time events and happenings. According to Heale and Twycross (2018), case studies may be viewed as a multifaceted approach to evaluating an inherent issue in the society. This approach promotes a multi-dynamic approach to issue analysis. By developing different views to understanding real-time issues facing organizations and entities, case studies span efficient decision making processes because they mitigate bias and prejudice during the data collection and analysis process.
Similarly, data collection and sampling techniques are essential in achieving study objectives. This research will employ a purposive sampling criteria to achieve study efficiency and reliability. A purposive sampling ensures that the researcher filters participants based on the underlying criteria, to ensure that all the participants meet the required threshold. Additionally, the study will adopt a sample size of 8 participants, majorly, accounting professionals.
Also, the study’s scope is tended to focus on DC, Maryland and Virginia areas to ensure that the data is not only comprehensive but also, objective. The nature of data and sample size is critical in ensuring that the research objectives are met, and that the findings form a solid basis upon which future research processes are premised. In summary, the study will adopt a qualitative exploratory design, and collect data from primary sources using interviews. It will also, subject the data to analysis using a thematic analysis of the key misconception aspects.
Advantages of Case Studies[KO1]
This qualitative research methodology will adopt a case study to achieve study objectives and goals, because it promotes an indepth examination of the underlying issues, and presents a solid decision basis. Moreover, the nature of the case study adopted in this research is exploratory, because the research is tended to examine the misconceptions facing digital accounting processes, at an individual or organizational level. It moreover, focuses on how the advent of digital accounting revolution spans misconceptions in organizations, and how these concepts affect performance and organizational efficiency. These study findings are essential in providing a solid decision making basis, thus, improving the accounting profession.
Moreover, the nature of the adopted case study integrates a single case analysis opposed to the multiple case analysis. By integrating different study participants, the study is focused on digital accounting processes, and how the advent of accounting revolution spans misconceptions and people. Thus, a single case analysis will promote objectivity, by integrating an indepth examination of the misconceptions impacting organizational performance, as impacted by misconceptions facing accounting professionals and stakeholders.
Additionally, the study adopts a literary approach to present the case study analysis. It is essential to adopt existing literature in examining underlying concepts. By integrating underlying literature, the case study will not only add to the existing research, but will enhance diversity in research findings. Moreover, a literary case study enables the researcher to associate themselves with other academic works. Therefore, a literary case study will enhance objectivity, and strategic decision making processes by comparing existing literature to the case study findings.
Meanwhile, the research is tended to integrate a thematic analysis approach to enhance efficiency and objectivity; meeting the SMART objectives, thus, achieving the study’s objectives and goals. By integrating an exploratory case study approach, the study will focus on the underlying research themes, and keenly examine the underlying concepts, thus, forming a solid decision making basis. Therefore, a case study approach will not only promote sustainable decision making, but will enhance comprehensiveness in research findings, thus, improving existing accounting processes.
Primarily, case studies enhance objectivity the data collection processes. The researcher develops a checklist of objectives that must be filled to make the research successful. By employing a case study approach, the research aligns with the set objectives by looking for specific factors and concepts. For instance, the proposed study seeks to identify misconceptions surrounding digitalized accounting processes, and a case study would promote objectivity (Gibson, 2021). Thus, case studies promote informed decision-making that is born of objectivity.
Moreover, case studies are inexpensive and may be conducted remotely. While remote, case studies ensure that the research is extensive and highly effective by facilitating real-time interaction between the researcher and the target information or sample size. This approach ensures that efficient data is collected and effectively employed to make critical decisions.
Additionally, case studies enable the research to integrate information from multiple sources for effective decision making and concrete data findings. By integrating data from different sources, case studies do not only mitigate bias in the research process but also ensure that the information provided is highly diverse and extensive to meet the research needs. Thus, it facilitates efficiency during decision-making processes.
In summary, case studies promote objectivity, extensiveness and diversity in research. They achieve the mentioned aspects by integrating various data sources and components to ensure that the resultant data and conclusion is reliable. Whereas weaknesses related to case studies such as identifying bias may exist, case studies widely promote accuracy in decision making process.
Appropriateness of the Research Method and Design
To evaluate the appropriateness of the underlying research method and design, it is essential to evaluate the study objectives, research question, and relevant hypothesis. First, the study objective is tended to establish how digitalized accounts impact various organizations and people. Also, the study seeks to establish how digitalized accounting impacts various aspects of organizational performance and how individuals understand the various perspectives of accounting. The study will also evaluate digitalized accounting and how it relates to financial services and management as a critical aspect of decision-making processes in companies. Financial data conversion and management is also a critical aspect of companies’ decision-making processes. In summary, the study objective is tended on the environment surrounding digitalized accounting.
In lieu of the underlying statement of purpose and objectives, the study established that the proposed research design and method are most appropriate for decision making. First, primary data sources, mainly interviews, ensure that the information collected is comprehensive and meets the desired study outcomes. A close comparison of the underlying approach to data collection to the study objectives would ensure efficiency and accuracy in decision-making processes.
Subsequently, the selected research method and design are appropriate because they present an opportunity for the collected data to be adjusted to fit the study objectives. For instance, the study objectives would ensure that there is a strategic adjustment of the interview questions to meet the desired outcomes. Thus, the proposed approach to the research design and corresponding method appropriately meets the desired study objectives.
In summary, this study established that the selected research method, a qualitative approach, and the corresponding research design that comprises interviews and descriptive analysis meet the appropriate threshold for analysis and decision-making through the recommendations. Whereas the data collected may vary from one source to another, this study observes that the underlying design will enhance flexibility, thus enabling the findings to meet the desired outcomes. The two aspects, therefore, are appropriate and enhance sustainable analysis.
Research Questions and Hypothesis
A research question is the guiding aspect of an entity that enables the organization to meet its underlying objectives and ensure that the research plays a significant role in meeting sector improvement and development. In the underlying context, the main research question is “what is the impact of the digital accounting revolution and related misconceptions among organizations and people?” Thus, the underlying research question presents a need to evaluate digital accounting in a broader context to evaluate several concerns. First, the research is informed by changes in the accounting profession, such as digital and technological changes, career definitions, responsibilities, and shifts in underlying roles.
Secondly, the research presents another research question based on accountants’ experience and understanding of digitalized accounting systems. Primarily, the preliminary studies observe several misconceptions regarding the accounting profession. Moreover, shifts in digitalized accounting systems continue to enhance efficiency in the workplace, but at the same time, they are faced with misconceptions and misunderstandings. Thus, understanding the professional accountant’s experience is essential in informing the decision-making processes that would improve the underlying profession and promote a sustainable understanding of digitalized accounting systems and structures. The research question is essential in positively impacting accounting systems and processes.
Subsequently, the research questions present a need to understand the role of digitalized accounting tools on business performance and growth. Notably, this research question seeks to gather data on how digitalized accounting tools and systems impact performance and operations, including management and organizational structure and efficiency. The data collected based on this research would be essential in informing the source of underlying misconceptions on the topic under study.
According to Mosteanu et al. (2020) and Marushak (2021), accounting systems installation and integration processes are not only involving but also cost-intensive, thus, impacting overall business performance and sustainability. Therefore, this research question presents an opportunity for informed development that is premised on identifying the most feasible approach to integrating the said systems to realize business growth and development. Also, the study presented a need to evaluate how organizations and businesses may employ digitalized accounting tools and systems to realize improved business performance as enshrined in the research question. The data collected using the proposed qualitative tools will form a solid background for understanding the role of digitalized accounting systems and decision-making processes in improving overall organizational growth.
The research questions presented in the preliminary chapters also present a need to establish how historical accounting systems and processes compare with modern technologies. By drawing from this research question, the feedback collected from interviews will promote an understanding of the existing misconceptions about digitalized accounting processes and their impact on businesses. Based on the underlying background, the study would be fundamental in evaluating the accounting environment from a more holistic perspective geared towards identifying key trends and changes in digitalized accounting processes.
To also conduct a practical analysis of the role of digitalized accounting on organizational performance and trends, the study presents a research question that draws on the underlying systems and organizational performance. For instance, understanding how digitalized accounting systems impact data conversion and analysis would form a sustainable basis for decision-making and misconception evaluation. This understanding will also, inform practice in the underlying accounting field.
In summary, digitalized accounting systems and processes have continued to impact business performance and growth over time, resulting in changes in the overall understanding of the underlying career and its surrounding. Subsequently, these research questions form a solid base for intense study by collecting data that resonates with the established objectives, thus, positively impacting decision-making processes. Again, the questions will enhance continued objectivity through the research process.
Population and Sample
The population’s nature selected for analysis is critical in ensuring that the data collected meets the study needs. Moreover, it ensures that the research process is seamless and mitigated any underlying rigidities relating to systemic errors due to limited population. The extent to which the sample size is selected should be pegged upon the nature of the study, and what the researcher seeks to establish. While a larger sample size promotes benefits relating to diversity and extensive information, the underpinning principle must be objectivity (Park et al., 2020). Essentially, population and samples selected for research purposes must be authentic and customized to meet the underlying study needs.
This research will draw from 5 different organizations by employing a case study approach. The population and sample selection criteria for research is premised on accounting professionals, individuals and persons who are directly exposed to accounting processes in organizations. The sample size of 5 to be included in the case study will ensure that the research process is not only authentic but also diverse to ensure that the decision making process is flawless, and that the recommendations provided resonate with the current trends in the industry.
Additionally, the proposed sample size of 5 to be included in the case study is manageable and ensures extensive research process. By facilitating a greater attention to detail, the sample size will play a great role in meeting the authenticity and objectivity threshold inherent in research processes. In summary, the research will select 5 organizations and employ a case study approach to analysis to make informed recommendations.
Sample
A sample is a specific target the research employs out of the entire population to conduct effective study. Sample selection process varies based on the nature of the underlying research and scope. Studies that study a more defined area employ relatively smaller samples than studies that evaluate a more holistic or vast study field. Also, the underlying resources and timeframe allocated to conduct the research widely informs the sample size that the research selects (Majid, 2018). Essentially, the study’s nature and scope, resource availability, and timeframe concerns impact the sample size selected. However, there is a need to ensure that the sample size selected promotes study objectivity. While limited sample size may promote bias, extensive and overly large sample sizes may also impact the research process because of rigidities in data analysis.
By employing case studies as the proposed approach to conducting the research, a sample size of 5 will be employed. However, the selected sample size will not only be customized to promote efficiency but also to facilitate efficiency in the decision-making process. This sample size will integrate the proposed sample selection criteria to achieve objectivity and informed decision-making.
Informed Consent and Confidentiality
Data collection is a critical aspect in decision-making. However, there is a need to ensure that the sources from which data is collected are satisfied with the nature and manner in which the data is collected. According to Plutzer (2019), some of the critical aspects and concerns in the data collection process include consent, that is, the acknowledgment by the relevant source on how information and data will be used. Notably, the study observes that participants must exhibit understanding and awareness before collecting data and personal information.
On the other hand, confidentiality would imply the participant’s right over the information provided. For instance, they may be willing to share information with the researcher but unwilling to have their personal information such as name and identification aired as a source. Therefore, the researcher is limited to only using the collected data to make decisions and presentations, and not personal information.
This study will employ questionnaires, and will exclude any personal information. Essentially, it will only employ the data provided for decision making. Agai
Storage of Data
This research will employ electronic data storage methods to ensure that the information provided by the participants remains confidential and serves the intended purpose. Primarily, the interview process will involve an electronic approach to collecting data and storing the same information. Whereas the main threat impacting the proposed approach is cyber-attacks, there are more threats resulting from using a paper-related approach to collecting data, such as loss and access by unauthorized parties (Sloan et al., 2020). Thus, an electronic data and information storage approach will be the most appropriate data and information storage method.
Upon successfully achieving the research and study needs, the collected data will be destroyed to mitigate any inherent and unforeseen threats that may inconvenience the study and the participant. The approach will include deleting files from the computer to ensure that they are no longer accessible and resonate with the participant’s desires. At the same time, this report observes that any physical data collection tools and materials will also be destroyed. In summary, this research understands the need to ensure that participants’ information remains under control and assured of data security.
The underlying strategy is essential in promoting strategic decision-making. At the same time, it is essential to uphold ethical values and integrity. Some of the factors that would compromise the data collection process and participants’ trust include sharing personal or confidential data with third parties (Dyda et al., 2021). Thus, the research will endeavor to strictly utilize the information shared by the participant for the intended purposes only, and after successful usage, it will be subjected to destruction.
Instrumentation
Data collection processes are involving and require a more comprehensive approach to ensure that the information collected is efficient and that the involved procedure is accommodative. Thus, the choice of the instrument used to collect information must be adequate to promote sustainable decision-making and ensure that the instrumentation document aligns with the set research questions and objectives. Also, the choice will go a long way in determining the extent to which the study meets the underlying objectives.
This research will employ questionnaires to collect data from the selected participants and population. A semi-structured approach to data collection will be employed to collect the data under consideration. This instrumentation tool effectively ensures that the study meets the desired study objectives in several ways. First, it contains research questions and ensures a systemic approach to collecting the proposed information. Primarily, a series of underlying research questions will enable the researcher to ask more objective and meaningful questions to the participant and collect more comprehensive data for analysis.
Field Test
Field tests are an integral aspect in qualitative research processes. Essentially, they involve evaluating the selected model and design on a smaller sample size and tweaking it to meet the larger sample size needs. Field tests are essential in ensuring that the data collection methods are feasible and that any other relevant adjustments are made to ensure that the final model captures all study needs. According to Samek (2019), field test is qualitative research while pilot test is quantitative research. It is essential to conduct field tests before conducting the main study to ensure that the findings and results collected are as comprehensive and extensive as possible.
In conducting a field test, this research will meet its set objectives and establish a solid research basis upon which future research processes will be conducted. Field tests consider the proposed sample size for the main research, and employ a smaller sample size to experiment with the model’s goodness of fit and its ability to meet the research objectives. Importantly, this approach to conducting research does not only ensure that the objectives are well defined and adjusted accordingly, but also, ensures that the resultant model is comprehensive to manage costs and resources.
This study seeks to conduct a case study on a sample size of 5 that encompasses organizations and individuals. However, a field test will ensure that the case study’s objective are “SMART” that is, measurable, achievable, realistic and time-bound. The underlying research topic is critical because it directly affects the accounting sector, and relevant changes to accounting digitalization processes will be key in further improving the sector. Thus, ensuring that the final research findings are efficient to meet the set objectives is necessary.
The initial field test will integrate 1 to 2 samples. The study objectives and checklist will be administered and the results will be evaluated to measure the appropriateness of the underlying approach to meeting the objectives. Upon identifying key weaknesses and limitations in this initial model, the study will adjust the most and repeat the procedure to ensure that the final model is overly reliable.
Credibility and Transferability
Credibility is the extent to which data is accurate or true, hence, relied upon. On the other hand, transferability is the ability of the research findings to be replaced in a separate context, and enhance efficiency and high reliability (Sundler et al., 2019). Therefore, there is a need to ensure that the study findings are accurate and present a valid account.
First, this research will seek to achieve a high trustworthiness level. For instance, it will enhance objectivity in the data collection process by asking questions over and over to assert accuracy. At the same time, the study will seek to engage participants from their comfort level to ensure that the information provided is a true representation of their position, and that they are not providing answers to end the interview. This approach will ensure that the study objectives are met, and that the data collected from the underlying participants and sources are to be trusted, thus, credible.
On the other hand, data transferability is the ability to replace data or information in a different environment. It ensures that the model or information does not only apply to a particular case, environment, or scenario, but meets the threshold to be applied in different circumstances. To ensure that the data or information is transferable, the analysis will systematically review the findings by examining similar studies and corresponding findings. The analysis of both findings will be compared to establish similarities. A high similarity level or score in the findings will suggest that the data is transferable and, thus, valid. An internal test analysis will also be conducted by changing study parameters and variables to establish the corresponding effect on the findings.
However, the study seeks to meet the credibility and transferability thresholds by ensuring that it is as vast as possible, that is, it integrates different sources, professionals and careers. By achieving a diversification effect, the study may be subjected to continued analysis, and the findings be employed in decision-making processes. Diversification will ensure that the scope of the study is comprehensive and mitigates any inherent errors, while a relatively colossal sample size will ensure that the information is credible.
Data Collection
The data collection process is the most critical aspect in research because it deals with actual data, and examines how relevant the data being collected is to meeting the specified model needs. According to Zhou et al (2018), the data collection process must be objective to ensure that all key elements and research concerns are addressed, to ensure that the analysis and decision making phases are essential. Primarily, data collection ensures that research objectives are met.
However, data collection methods are also pertinent in achieving efficiency and sustainability in a research model. Several factors impact the choice of a data collection criteria. Interviews ensure that the researcher and participants have a direct engagement. According to Clark and Veale (2018), interviews enable the researcher to gather data from the direct source, thus, mitigating several other factors such as bias and systemic errors that are present in secondary sources.
Moreover, surveys enable the researcher to collect data by evaluating underlying sources and documents. Essentially, surveys enable the researcher to save time and resources by gathering data from secondary sources such as publications, articles and periodicals. While interviews enable the research to collect data from primary sources and subject it to further analysis, interviews are secondary sources, and contain already published information.
Additionally, questionnaires play a fundamental role in data collection processes, by ensuring that the data collected meets the set goals and objectives. Questionnaires have a set of questions pre-written, and which the researcher uses to collect the desired data (Newman et al., 2021). By administering questionnaires, the research ensures that the research process is highly objective and reliable by meeting the set goals and targets. It also ensures that further changes are initiated and implemented by evaluating underlying data collection processes, and identifying weaknesses that must be improved to realize efficiency in research processes. In summary, each of the underlying data collection technique or approach is efficient based on the underlying research’ nature. While some of the collection techniques may be employed in different research types, others are customized to serve more specific research types.
A review of the various data collection techniques established that the choice of a specific research is premised on its underlying features in relation to the proposed research model. Quantitative research techniques are more likely to employ more secondary sources to realize efficiency in the data collection process. In contrast, qualitative research designs mostly employ primary data collection strategies.
The proposed study is qualitative, and employs a case study to realize efficiency. While surveys and interviews are reliable data collection techniques, questionnaires are more reliable in the underlying cause. For instance, there is a need to identify the common misconceptions surrounding accounting practice and digitalized revolution. This data collection technique would not only promote efficiency in data analysis, but also, would enable the study to realize its set objectives by ensuring that all key concerns are accounted for and sufficiently addressed. Moreover, it ensures that the results can be compared to achieve efficiency, by identifying the most dominant misconception in the accounting profession, and the extent to which it impacts decision making processes. Thus, using a questionnaire will promote efficiency in decision making on digital accounting revolution, trends and advancements, and how these trends impact decision making processes in the wake of inherent misconceptions.
Nature of the Study
Qualitative and quantitative research approaches are the main methodologies employed in collecting data and making informed decisions upon conducting in-depth data analysis. However, the nature of the study is based on several underlying factors. For instance, the choice of the data collection method informs the study’s nature. Primary research collection sources in most cases would suggest that the study’s nature is widely qualitative. Conversely, secondary sources mostly suggest that the research is most likely quantitative (Carter et al., 2021). Thus, the choice of data collection technique and strategy informs the study’s nature.
Moreover, the approach employed to conduct data analysis greatly informs the study’s nature. Numerical datasets are subjected to mathematical models and tools that conduct several aspects such as regression, analysis of variance among other computations. In contrast, non-numeric data employs varying data analysis techniques that integrate ranking datasets and conducting a strategic analysis.
The underlying study seeks to evaluate the sector’s digitalized accounting processes and misconceptions. It also, will collect data from participants that encompass organizations and individuals. A majority of the data collected will be non-numeric, such as experiences and misconceptions on the selected topic. It implies that the choice of data analysis will be primarily qualitative to ensure that all non-numeric information provided is greatly accounted for. This study also utilizes primary sources to collect the desired information. Based on these key aspects, the study’s nature is therefore qualitative. While some of the data collected will numeric, it does not meet the threshold to constitute quantitative research techniques and designs.
Data Analysis
The most critical aspect of the research process is data collection and analysis. Primarily, the data analysis phase integrates evaluating data collected and applying relevant analytical methods to create meaning from the data collected. The analytical method employed to analyze data is primarily based on the nature of the selected data and its underlying attributes to the corresponding analytical tools and techniques. Primarily, the analytical method under review must meet the objective needs of the data collected and present an opportunity for strategic interpretation and decision-making processes that can be integrated into the short term and the long term.
This report seeks to employ a thematic analysis approach to evaluating the data collected in lieu of the underlying data structures and type. Primarily, the interviews are structured to resonate with the research questions and the corresponding objectives. Thus, the data collected ensures that it is comprehensive enough to cover the required content and provide a basis for strategic analysis and interpretation.
The study proposed to use themes that are borne of the research questions to promote a holistic approach to examining the identified data and making sustainable decisions. In particular, the central theme is tended to focus on the impact of digitalized accounting systems on organizations and individuals and how these people understand or interpret the said data. Above all, the study is geared towards establishing a more sustainable analysis that is both holistic and comprehensive. Therefore, the themes will incorporate the underlying research questions and study objectives. Applying a thematic analysis will imply that the data collected will be segmented or classified according to the identified themes.
However, the choice of the data analysis method is premised on several factors. First, a thematic approach to data analysis ensures that the analysis findings are coherent and comprehensive by ensuring that they cover the required content. This approach ensures that the study findings promote strategic decision making and form a basis for future advancements and improvement. Thus, a thematic approach is the most feasible qualitative analysis technique.
Subsequently, thematic analysis employs known structures, thus providing a basis for sustainable analysis and recommendation provision. Primarily, each identified theme is effectively analyzed and ranked in order of preference or according to which theme has the most significant impact on organizations. At the same time, it would make it easier to analyze and evaluate the identified misconceptions according to the information and data gathered from the participants. The decision-making process, recommendations for further improvement, and overall data efficiency will be sustainable.
Conclusion
This chapter sought to evaluate the underlying data nature and corresponding approach to collection, analysis, and interpretation. A review of the research topic established that it is qualitative, prompting a qualitative research method compared to quantitative techniques. Subsequently, the study established that a sampling technique would be most preferred in determining the nature and type of population subject to the study. Therefore, a purposive sampling technique was employed to conduct the analysis.
Moreover, the study will employ a case study to realize efficiency in data collection, analysis and decision making. Whereas each of the underlying data collection techniques is fundamental in the research process, questionnaires fit the proposed study. Meanwhile, the proposed sample size relevant for the study is 5, and would comprise organizations and individuals with different accounting backgrounds and experiences. By conducting successful study review, the research will present a solid basis for future decision making, policy implementation among other key processes.
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Would you rewrite three pages and combine/use the case study snapshot article?