Think About Different Research Paradigms and Theme of Ontology and Epistemology Essay Example

when collecting data from the entire population is not feasible. This involves selecting sample sizes, using randomization techniques, and addressing biases. In this chapter, we explain and justify the preferred methods used in our research procedure compared to other available approaches.

In order to travel and conduct investigations effectively, it is crucial to comprehend the qualities of harmony and unbiased research (Flower, 2009, p. 1). Epistemic choice refers to the process of deciding which knowledge should be considered acceptable within a particular field (Bryman & Bell, 2007, p. 16).

Epistemology, the study of cognition and the limits of knowledge, is crucial for comparative examination (Eriksson and Kovalainen, 2008). It can be classified into three primary branches: positivism, interpretivism, and pragmatism.

Positivism: Positivism signifies the ultimate phase of scientific research in which a hypothesis is tested utilizing an established theory.

The concept of positivism is grounded in the notion that reliable knowledge stems from logic, practical experience, and affirmative evidence. Bryman and Bell (2007) assert that theory plays a key role in generating testable hypotheses to evaluate laws. Positivism is commonly linked to quantitative research methods, where scholars employ theories to collect data with the aim of confirming or refuting a hypothesis. According to Saunders et al. (2009), researchers who embrace positivism have the autonomy to choose their study topic, define research objectives, and select data collection methods.

114). It is believed that the rationalist research worker will utilize structured methodological analysis with the purpose of bring forthing replicability.


Interpretivism


Interpretivism is a stance reverse to positivism and is besides known as anti-positivism. Philosophers of societal scientific discipline believe that the capable affair of a research in a societal scientific

discipline that is undertaken upon some persons and personals or establishments are different from that of the natural scientific discipline (Bryman ; A ; Bell, 2007, p.

According to Saunders et al. (2009), interpretivism derives from two rational traditions: phenomenology and symbolic interactionism. Phenomenology encompasses the way we, as humans, comprehend the world. Symbolic interactionism, on the other hand, involves continuously interpreting the social world around us by analyzing the actions of others we interact with. This interpretation influences our own understanding and actions.

116). Realism: Realism is a subdivision of epistemology similar to positivism, affirming that reality exists independently of human perception. There are two main types of realism.

According to Bryman, Bell (2007), the two types of pragmatism are empirical pragmatism and critical pragmatism. In contrast, Saunders et al. (2009) refer to them as direct pragmatism and critical pragmatism. The main distinction between critical and direct pragmatism lies in the belief of critical pragmatism that our understanding evolves through two stages of development.

Firts there is an object and substance we see and see trough our senses and in 2nd stage procedure goes on after the senses receive the esthesiss. Whereas direct pragmatism claims first stage is adequate and what we see is what we get ( Saunders et al. , 2009, p. 117 ) . In epistemic consideration of our research we take the rationalist place.

The reason for our positive stance is based on our literature study, where we developed a hypothesis using prevailing theories. Through our empirical findings, we will test this hypothesis to determine its acceptance or rejection. Our analysis focuses on the usefulness of the Banks' internal rating model (CAMELS) in relation to external

recognition evaluation models like PACRA and Moody's. Another reason for choosing this stance is the use of secondary data, as positivism is commonly associated with quantitative research involving statistical tools and figures.

Ontology: This aspect of the research paradigm concerns the nature of social entities and human beings.

The question regarding whether societal entities can be considered objective entities with an external reality, or if they should be seen as societal constructs based on the perceptions and actions of societal actors, is raised (Bryman & Bell, 2007, p. 17). We previously discussed two aspects of ontology, referred to as objectivism and constructivism. In terms of ontology, our research thesis takes an objectivist stance.

To determine our thesis empirically, we will use statistical tools like fiscal ratios. The results from these ratios will be rated on a scale of 1 to 5 using the CAMELS evaluation model. We will then compare these results with the ratings from the PACRA evaluation agency for the same time period. This choice of methodology ensures that our research is unbiased.


Research Approach:


At this stage of research, one must decide whether to follow a deductive or inductive approach based on the chosen theory learned from literature.

The deductive attack involves developing a hypothesis based on a theory and creating a research plan to test and either accept or reject the hypothesis. On the other hand, the inductive attack involves gathering and analyzing information to develop a theory based on the resulting analysis (Saunders et al., 2009, p. 124).

Deductive attack: This attack involves the correlation between theory and research. Based on knowledge gained from theoretical contemplation about the research field, one forms a hypothesis that will be

observed in empirical analysis (Bryman & Bell, 2007, p. 14). According to Robson (2002, cited in Saunders et al., 2009, p.

The deductive research process consists of five steps. Firstly, a hypothesis is developed from a theory. Secondly, the hypothesis is expressed in operational terms. Thirdly, hypothesis testing is conducted. Fourthly, the specific result of the investigation is analyzed. Lastly, the theory is either verified or modified based on the findings. The collection of quantitative data is a crucial aspect of the deductive approach, although qualitative data may also be used. A highly structured methodology is implemented in the deductive approach to ensure reliability.

Generalization is an important feature of deductive attack (Saunders et al., 2009, p. 124-125). Inductive attack, on the other hand, involves developing theory based on research observations.

Inductive attack focuses on the actual events and uses a small sample, while deductive attack deals with a larger number. Qualitative data is typically used in inductive attack. The structure of research in inductive attack is more flexible and less generalized compared to the highly structured methodology and general features of deductive attack (Saunders et al., 2009, p. 126-127). In our research, we will use deductive attack instead of inductive attack.

The reason for choosing this attack is the correlation between the theory and hypothesis. Based on the literature studied and theoretical framework constructed, we have developed a hypothesis. Our research findings will determine whether the bank's internal rating models are of high quality compared to external evaluation agency models. Since the deductive approach is a highly structured methodology, our thesis will adhere to a predefined structure.

Research scheme:

According to Bryman and Bell (2007), "research scheme refers to

the general orientation of conducting business research."

The text discusses two distinct types of research: qualitative and quantitative research. These two approaches differ not only in the way they measure and quantify results but also in their epistemic and ontological foundations (Bryman & Bell, 2007, p. 28).


Quantitative research:


Quantitative research is primarily used in a deductive approach, with the goal of testing a hypothesis to prove a theory. In quantitative research, the analysis of results is mainly done using numbers and measurements.

Another characteristic of quantitative research is that the sample size is typically large. This type of research aims to minimize bias by utilizing statistical tools to analyze the results. Additionally, quantitative research is known for its generalizability and tends to have a more positive epistemic orientation.

According to Bryman and Bell (2007, p. 28), quantitative research in ontological orientation is objectivist in nature. They outline 11 steps in their book Business research methods: 1st Theory, 2nd Hypothesis, 3rd Research design, 4th Devise steps of constructs, 5th choice research site, 6th choice research capable / respondent, 7th administer research instruments / cod informations, 8th Process informations, 9th Analyze informations, 10th determination and decision and 11th is write up findings and decisions.

Qualitative research


Qualitative research differs from quantitative research in almost every aspect. It is primarily used in inductive research, focusing on the generation of theory based on observed research. Analysis of qualitative research is primarily based on words and statements, often in textual form. Qualitative research has a more interpretivist epistemic orientation.

Qualitative research, with its ontology and constructivist nature, employs a smaller sample size compared to quantitative research.

Skill in interpreting results is imperative for qualitative researchers. Unlike quantitative research, qualitative research has lower generalizability and replicability.

The text provides a differentiation chart comparing quantitative and qualitative research. The chart includes various research aspects, such as the scientific method, nature of the world, research aim, nature of observation, form of information, sample size, data analysis, consequences, and decision. It also explains that quantitative research is deductive and objectivist, while qualitative research is inductive and constructivist. Additionally, it states that quantitative research focuses on description, account, and anticipation, while qualitative research focuses on description, exploration, and finding. The chart concludes by mentioning that quantitative research uses statistical tools for data analysis and provides general findings, while qualitative research searches for forms, subjects, and holistic characteristics and provides particular findings through narrative study. The chart was created based on the study of various books and articles.

For our research thesis, we have opted to utilize a quantitative research approach instead of a qualitative one. This decision is driven by various factors, such as the necessity to present results in numerical and statistical formats. Our research is grounded in positivist epistemology and takes an objectivist stance in terms of ontology. These considerations further support our selection of quantitative research. The main focus of our study revolves around numbers and employing statistical tools for measurement and analysis.

We have chosen a deductive approach, typically associated with quantitative research methods, and we discussed its selection in a previous section. Considering our research question and objective, we have chosen this approach as it will be suitable and provide guidance throughout our research process.


Nature of Research


Researchers often describe, examine, and explain the relationship

between events or factors. The research can be descriptive, explanatory, exploratory, or predictive in nature. The nature of the research depends entirely on the research question.

In descriptive research, the research worker strives to identify or describe events. For example, in descriptive research, if the question is "What is the current or past state of events?" the research worker selects a representative sample of people. On the other hand, explanatory research is conducted by the researcher to explain events and find key reasons. Explanatory research is also known as interpretive research. For example, the researcher conducts explanatory research when asking "Why have these events happened in the manner they did?" or "What are the implications of these events occurring as they have?" (Rubin et al, 2010, 198). Exploratory research is a type of research where the researcher is unable to find any or very few previous studies on the research question.

Exploratory research surveys are conducted to search for ideas, patterns, or hypotheses instead of testing or confirming a theory. This type of research utilizes common techniques like observation, case studies, and previous studies. It incorporates both qualitative and quantitative data as it aims to gain initial knowledge and understanding of the subject area that will be further studied in later stages (Collis & Hussey, 2009, p.).

6) Predictive research takes explanatory research one step further. The purpose of the survey is to explain what is happening in specific circumstances. Predictive research focuses on anticipating the likelihood of an event occurring.

The aim of prognostic research is to generalize the probe by calculating some phenomena based on hypothesized, general relationships. Therefore, a solution provided by prognostic research in a

specific situation can be applied to other similar jobs, given that the solution is valid (Collis & Hussey, 2009, p. 6). Our research is explorative in nature as no previous research on the same topic was found. There are some articles and thesis that demonstrate the use of camels evaluation theoretical model on a specific or limited number of banks.

Our research focuses on examining the internal evaluation models of banks in relation to external recognition evaluation agencies. Surprisingly, there is no existing research in this specific area. Our study aims to contribute new insights and knowledge to the field of banking evaluation systems.

Research timeframe:

The timeframe of research is crucial for both researchers and readers. Researchers need to determine the type and quality of data necessary for their study and assess how easily it can be collected. Collecting data over a long period of time can be challenging and time-consuming.

According to Sunders et al. (2009, p. 155), the time frame of research, known as the time horizon, plays a crucial role in determining the credibility and quality of research observations. There are two types of time horizons identified: cross-sectional research and longitudinal research.

Longitudinal survey


A longitudinal survey involves observing the same sample of population over a longer period of time. It is a type of experimental research that does not use interventions, making it less likely to observe cause and effect relationships between variables. However, it allows researchers to observe changes and improvements over time (Lindborg & Ohlsson, 2009, p. 15).


Cross-sectional survey


A cross-sectional survey involves studying a

sample or population for a short period of time or on a single occasion. The researcher selects a sample from the population and collects data on the variables of interest, sometimes based on information obtained from other sources.

Descriptive and exploratory studies, like individual studies of a country's population at a specific time, are often cross-sectional. This type of survey is closely related to explanatory studies, where researchers conduct a survey on a national level to analyze a country's problem at a specific time. Based on this information, we can conclude that our research is a cross-sectional study. In our thesis, we will analyze the annual financial reports of 17 banks from Pakistan for the year ended on December 31, 2010. It would be beneficial to use reports from multiple years, however, it was challenging to collect published credit ratings for the same year as most banks do not retain records from previous evaluations.

As previously mentioned, cross-sectional surveys are mainly exploratory or descriptive in nature, and our research is also exploratory in nature.

Practical Methodology:



Choice of the research subject:

Both authors of the thesis are from Pakistan, where the banking industry is thriving despite the general economic turmoil. Our educational backgrounds also contribute to our interest in this field. One author holds a BBA (Hons) with a major in Finance, while the second author holds an MBA with a major in Finance. During our studies, we covered various courses related to banking and finance, which sparked our interest in this field. Now, as Master's students in Finance and considering our future professional careers in banking and finance, we have

chosen this research subject.

Our research focuses on the CAMELS evaluation theoretical model, which considers 6 important components of the banking industry. This will provide us with a better understanding and knowledge of the performance of the banking industry, particularly in Pakistan. Another reason for choosing this research topic is our personal curiosity about bank evaluations, especially in Pakistan.


Preconception:


Having preconceptions about the research topic is important as it develops the researcher's interest and involvement in the subject. Both authors of this thesis worked as interns in a conventional bank in Pakistan after completing their studies, gaining practical experience in banking.

In our practical experiences, we have observed that some factors addressed in evaluation models are very important for improving the performance of banks. These factors may not be all of the ones mentioned, but they are significant.

Position:


Perspective provides a viewpoint on the chosen field of study, considering various angles and aspects. This provides a range of options from which the most suitable one can be selected, while keeping your research question and purpose in mind. Our thesis focuses on the quality of CAMELS evaluation model results in relation to external evaluation agencies. However, we will also examine this model from the internal perspective of banks and their regulatory authorities. It is worth noting that our readers can also be external users, such as evaluation agencies, who will find this information useful.

Data Collection Method: For any type of research, survey information aggregation is an important aspect. Data is the source from where researchers can obtain relevant information to answer the research questions. To gather applicable

information, researchers use primary and secondary data as sources. Primary data is collected or perceived directly from the first-time experience.

Alternatively, we can assert that the information gathered for the initial video clip is specifically designed for this research project. The primary data sources include questionnaires, observations, social surveys, experiments, and interviews. However, secondary data, which is previously collected and published by someone else, is also utilized to address our issues, although the circumstances may differ from others. The sources from which we can gather secondary data encompass articles, books, journals, and web-based information (Ghauri & Gronhaug, 2005, p.).

Between 91 and 102, we developed a theoretical model for our survey using secondary sources. By thoroughly reviewing relevant literature, we gained comprehensive knowledge and understanding of our research questions. Based on this, further investigation should be conducted. Our research findings heavily rely on secondary information and are of a complex nature. However, our secondary data will aid us in achieving our objective. In our survey, the primary source we relied on was the Umea University electronic library, along with utilizing Google search, electronic books, and printed materials such as books.

Literature studied:

Accessing relevant and reliable literature is crucial for a researcher. It serves as a foundation for the researcher to develop the theoretical framework for their chosen field of study and research design (Brayman; A; Bell, 2007, p. 94). In the initial stages of our research, we examined articles pertaining to the financial crises caused by the collapse of prominent financial institutions at that time, as well as the banking industry in Pakistan. Subsequently, we gathered articles and books from university archives databases and conducted internet searches on

research methods. This was done to construct the methodology chapter of our thesis and provide guidance throughout our research.

Articles for this project were collected from various sources, including diaries of Banking and Finance, the diary of international banking ordinance, and the reappraisal of fiscal surveies accessed through university provided logins on its database. It can be challenging to find relevant articles among the many that appear relevant but are not actually. Additionally, we studied online books available on websites such as www.book.google.com. We also gathered materials like booklets and working documents about evaluation procedures and methods used by evaluation bureaus such as S's, PACRA, and regulatory authorities like Basel and SBoP. These materials enhance our understanding and capabilities in the field of evaluation systems.
Sampling: Sampling is the process of selecting a subset of a population to represent the whole population in research. This allows researchers to make statistical inferences and judgments about the entire population based on the selected sample. It is crucial for researchers to choose an appropriate sample from the population for making such inferences.

Research workers choose to use a sample for their research instead of studying the whole population due to cost and time constraints. According to Bryman & Bell, a sample is a smaller portion of the population that is selected for examination or research purposes. There are two main types of sampling approaches: probability and non-probability sampling (Bryman & Bell, 2007, p. 182). Probability sampling ensures that every unit in the population has an equal chance of being selected for the sample and has a selection probability greater than zero. This approach is the most appropriate as it eliminates biases

in sample selection and reduces sampling error.

Simple random sampling, systematic or interval random sampling, stratified sampling, and cluster sampling are different types of probability sampling (Brayman & Bell, 2007, p. 182). On the other hand, non-probability sampling is an approach where the chance of selecting elements is unknown or some elements of the population cannot be selected as a sample. Non-probability sampling includes referral (snowball) sampling, quota sampling, convenience sampling, homogeneous sampling, purposive sampling, and matched sampling. Referral sampling method is also referred to as snowball sampling. This type of sampling technique is used when it is difficult to find subjects or samples for research.

This type of research sample involves identifying initial topics and sources. By starting with these initial topics, we can continue to expand our research sample by identifying further topics, similar to a snowball effect (Swisher, 2010, p.1). Quota sampling is a method where the population is divided into subgroups based on certain criteria, and then a sample is selected from each group. Quota sampling can be further categorized into relative and non-relative quota sampling.

Relatively weighted age of the population is used to represent a sample of each bomber group in relative quota sampling. In non-relative quota, a minimum number of sample topics are set as a requirement, and their proportional representation in the population is not necessary. It is only important that the selected sample adequately represents a small group within the population. Heterogeneity sampling involves selecting a sample for research that represents all groups of ideas or variables in the population. In contrast, homogeneous sampling is used when studying specific factors or variables and their impact on the population's outcome.

Criteria sampling involves selecting a sample from the population based on specified and thoughtful criteria (Trochin & William, 2006).

Criteria established by researchers must be met by any topic representing the population in order to be included in the sample. Any topic that fails to meet the standards will not be included in the sample, which is meant to represent the population (Swisher, 2010, p.4).

To conduct our research, we have chosen a standards-based sampling method. Our research focuses on the CAMELS evaluation model and its applicability to the results of external credit rating agencies' published evaluations. Therefore, we need to analyze the annual financial reports of banks. The criteria for selecting banks to include in our sample is the availability of their audited annual financial reports for the year ending on December 31, 2010.

The population of banks in Pakistan is 38. Out of these 38 banks, 5 are Muslim commercial banks that operate according to Sharia standards, which differ significantly from the system of commercial banks. The relevance of the CAMELS evaluation model, designed for conventional banks, on Islamic banks is debated by some writers but contradicted by others. Therefore, we did not include Islamic banks in our sample for this specific reason. Additionally, there are 6 foreign banks operating in Pakistan as subsidiaries of multinational banks. These banks prepare their annual financial reports and submit them to their head offices, which are then included in their consolidated annual reports. Therefore, there were complications in collecting their annual reports and interpreting them.

We did not include these foreign banks in our thesis sample because they did not meet the predefined standards for providing their annual

audited financial reports. Additionally, we discovered that 10 banks had not published or announced their annual financial reports as of the current date. Therefore, these banks were also excluded from our sample. Consequently, our final sample consists of 17 commercial banks from Pakistan that have provided their audited annual financial reports.