Sample Project Management Methodology
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CHAPTER 3: METHODOLOGY
A Comparison of The Management Approach To Complexity, Uncertainty And Dynamism In Cognitive Systems And Traditional Information Technology Development Projects
The methodology of the research contributes significantly towards the authenticity and accuracy of the data collection and evaluation. To carry out this research, the researcher has considered the aim and objectives of the research that has been formed in the introductory chapter of the research.
3.1 Research Philosophy
Research philosophy can be understood as a belief, according to which the data regarding research is collected. To understand the philosophy regarding research, one of the most important aspects of it is research epistemology which refers to what is known to be true (De Vaus, 2013).
The researcher uses several different research philosophies to collect the data. The most commonly used research philosophies are positivism and interpretivism. Positivism is a research philosophy that considers scientific reasoning and logic (Babbie, 2015). On the other hand, the interpretivism approach considers the qualitative aspect of the data (Walliman, 2015).
To carry out this research, the researcher has selected positivism philosophy and social constructionist philosophy. Positivism is used because it provides logical and scientific rationale regarding the participants’ responses regarding the complexity, uncertainty, and dynamism in the cognitive systems and traditional information technology development programs.
The social constructionist approach shows that knowledge is constructed as compared to creation. The qualitative responses are collected and evaluated based on this theory.
3.2 Research Approach
To test out the research hypothesis, the research approach is specified based on the research’s aim and objectives. There are two kinds of research approaches inductive approach and the deductive approach.
Inductive approach is where the research carries out the research based on an already developed theory or framework (Bryman, 2015). Deductive approach is based on the observations the results are deduced and the hypothesis is tested based on the obtained findings (Smith, 2015). Generally, qualitative researches use the former research approach while quantitative research uses the latter approach.
To carry out this research, the researcher has used an inductive research approach where the results and findings of the research will will be induced from the responses collected by the research participants regarding approaches of project management, AI, and sources of uncertainty in the AI projects.
3.3 Types of Investigation
There are different kinds of investigation methods that the researcher can use for data collection of the research. The three kinds of investigation are exploratory research, explanatory research, and descriptive research (Eriksson and Kovalainen, 2015).
Exploratory research is where the researcher explores a problem that has not previously been discussed by the past research or is not discussed intensely. Explanatory research is where the researcher tends to explain the research contents and the relationship among the research variables (Sekaran and Bougie, 2016).
Lastly, descriptive research is where the researcher tends to explain the components of the research descriptively. To carry out this research, the researcher has used explanatory research to analyze the suitability of traditional project management methods concerning AI projects, the impact of the complexity of AI projects on project management approach, and the uncertainty of AI compared to traditional IT projects.
3.4 Research Design
The three kinds of research design are qualitative research, quantitative research, and mixed research. As it is evident from each design’s name, qualitative research is the one for which the data is collected and evaluated based on the project’s content and quality (Creswell and Poth, 2017).
Quantitative research is the one for which the data is collected and analysed based on quantifiable figures and numeric values. Mixed research is the amalgamation of quantitative research and qualitative research.
For this research, the researcher has used mixed research design as described by Solomon. The mixed research has been used to collect quantitative information and qualitative information about comparing IT projects and AI projects. With mixed research design, the researcher has collected both quantitative and qualitative data to come up with authentic and accurate results.
3.5 Data Collection Method
To carry out any research the sources of data are of great importance hence a researcher carry out data collection method in accordance to the needs and requirements of the research (Best and Kahn, 2016).
Mainly there are two kinds of data collection methods: primary sources of data and secondary sources of data. Primary data is the one that is collected solely to research the specific needs and requirements of the research.
The primary data is in raw form. On the other hand, the secondary information is where the data is collected from the past sources. There are different sources with the help of which secondary data can be collected such as journal articles, books, and past researches.
To carry out this research, the researcher has used primary methods of data collection. The major reason for using primary data for this research is to focus on the research’s needs and requirements. Moreover, the researcher wanted to collect data directly from the participants to gain useful insights about the IT projects and complications, uncertainty, and dynamism of AI projects.
3.6 Research Instrument
Based on the data collection method, a research instrument is selected to collect data (Taylor, Bogdan, and DeVault, 2015). Like the data collection method, the research instrument is also selected based on its needs, requirements, and aim. Different kinds of instruments can be used for primary data collection: survey questionnaire, interview questionnaire, and focus group discussions.
On the other hand the major instruments from which secondary data can be collected are journal articles, research papers, newspaper articles, books, and case studies.To carry out this research, the research has used two instruments: survey questionnaire and interview questionnaire.
The major reason for selecting survey questionnaire as the research instrument is that it has allowed collecting large amount of data regarding comparison of IT projects and AI projects covering all the different aspects promptly.
On the other hand, interview questionnaire has also been used as a research instrument for this research because it has allowed the research to gain useful insights regarding the complexity, uncertainty, and dynamism of AI projects compared with IT projects comprehensively.
3.7 Sample Size
It refers to the number of participants who are directly involved in the data collection methods. The survey questionnaire responses have been obtained from 11 respondents while to carry out data collection via interview questionnaire 2 respondents were selected to carry out this research.
3.8 Sampling Technique
To select participants for research it is important to use a sampling method. The two major kinds of sampling methods are probability sampling and non-probability sampling (Silverman, 2016).
As the name suggests, probability sampling is where each individual in the population gets a fair chance to participate in the research. Non-probability sampling is where the researcher selected the participants based on specified criteria (Punch, 2013).
In probability sampling, there are four techniques: simple random sampling, cluster sampling, systemic sampling, and stratified sampling.
There are three major techniques of non-probability sampling: convenience sampling, quota sampling, and snowball sampling. To select participants for the survey questionnaire, the researcher has used convenience sampling as the sampling technique.
This means that the researcher has selected the participants based on convenience and ease. To collect data for the interview questionnaire, the researcher has selected the snowball sampling technique where the recruits were asked to suggest similar individuals to participate in the research.
3.9 Data Analysis technique
A researcher can use different techniques to analyze and evaluate the research’s collected data (McMillan and Schumacher, 2014). Data analysis techniques depend on the kind of data collected for the research and the needs and requirements of the research. In qualitative research, the data is analyzed with the help of different methods such as thematic analysis, content analysis, and discourse analysis.
In quantitative data, the techniques used for evaluation are mostly statistical and mathematical software. To analyze the results of the survey questionnaire, the researcher has used SPSS. Particularly, frequency analysis and one-way ANOVA is used to analyze the data. To analyse the qualitative data, the researcher has used thematic analysis to use different themes for the purpose analysis.
3.10 Research Limitations
While carrying out this research, certain limitations have impacted the results and findings of the research. The major limitation of this research is the sample size.
Firstly, 13 respondents were selected to collect their responses however 2 of the respondents did not fill the questionnaire. The researcher was only left with the responses of 11 respondents. The interview has also been collected from only two individuals. Overall, it can be said that with few respondents the results cannot be generalised. Other than this, the time and budget allotted for the research was limited which restricted the researcher to research on a large scale.
3.11 Ethical Considerations
While carrying out this research, the researcher has collected the data by following certain ethical considerations. The researcher ensured that the primary data was collected in accordance with the mutual consent of the participants. Moreover, the information obtained from the respondents was only used to carry out the research.
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Frequently Asked Questions
Cognitive systems refer to intelligent technologies that mimic human thought processes, using algorithms, data analysis, and machine learning. They enable machines to understand, learn, reason, and interact with humans, facilitating tasks such as problem-solving, decision-making, and natural language processing.