Literature Review: Define key concepts and theories, present models/frameworks, and critically analyze and evaluate literature.

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Literature Review: Define key concepts and theories, present models/frameworks, and critically analyze and evaluate literature.


  1. Identify and define key concepts and theories related to the project

  2. Research existing literature to identify relevant models/frameworks

  3. Analyze and evaluate the literature to determine its relevance and accuracy

  4. Summarize the key findings from the literature review

  5. Create a visual representation of the literature review findings






Identify and define key concepts and theories related to the project


Tutorial: Identifying and Defining Key Concepts and Theories Related to the Project


Introduction

In this tutorial, we will take a deep dive into understanding key concepts and theories related to Project Management and Project Portfolio Management, and how to effectively identify and define them for your literature review. Through examples and real-life stories, you will grasp the essence of these concepts and theories and be able to apply them in your studies and future projects.


Step 1: Understanding Project Management and Project Portfolio Management

Project Management (PM): 💡Project Management is the process of planning, executing, controlling and closing projects to achieve specific goals, within a specific timeframe and budget. It involves applying project management methodologies, tools, and techniques to direct and control project resources, scope, schedule, and quality.


Project Portfolio Management (PPM): 📊Project Portfolio Management is an approach to managing and prioritizing a collection of projects to optimize the use of available resources, align with business strategy, and maximize overall value. PPM focuses on the selection and prioritization of projects, resource allocation, and performance evaluation.


Step 2: Exploring Key Concepts in Project Management

Scope: 🎯 Scope is the extent of the work that needs to be done to deliver a project's outcome as defined by its objectives and requirements. It involves defining project boundaries, deliverables, and constraints.


Example: In a website development project, the scope might include designing the user interface, coding the backend functionality, and testing for usability.


Stakeholders: 👥 Stakeholders are individuals, groups, or organizations that have an interest or are affected by the project. They can be internal (e.g., project team members) or external (e.g., clients, suppliers).


Example: In a hospital construction project, stakeholders might include the hospital administration, physicians, patients, and local government officials.


Step 3: Examining Key Theories in Project Management


Theory of Constraints (ToC): ⛓️ The Theory of Constraints is a management philosophy that focuses on identifying and addressing the most critical constraints that hinder a project's progress. By improving the weakest link, the overall performance of the project can be enhanced.


Real story: Dr. Eliyahu Goldratt developed the ToC and successfully applied it in various industries, including manufacturing, healthcare, and software development, to improve efficiency and productivity.


Triple Constraint: 📐The Triple Constraint, also known as the Iron Triangle, highlights the interrelationship between project scope, time, and cost. It suggests that changes in one constraint will invariably impact the other two.


Example: If a client requests additional features for a software project (increasing scope), it may lead to an extension of the project timeline and increased costs.


Step 4: Unpacking Key Concepts in Project Portfolio Management


Project Prioritization: 🏆Project prioritization is the process of evaluating and ranking projects based on their strategic alignment, potential benefits, and resource requirements. This helps organizations select the right projects to invest in.


Example: A technology company may prioritize projects based on factors such as market demand, potential revenue, and technical feasibility.


Resource Allocation: 💼Resource allocation is the distribution of resources, such as time, money, and personnel, among different projects within a portfolio. Effective resource allocation ensures efficient use of resources and avoids overcommitment or underutilization.


Example: A marketing agency may allocate resources based on client requirements, project complexity, and team expertise.


Step 5: Delving into Key Theories in Project Portfolio Management


Efficient Frontier: 📈 The Efficient Frontier is a concept derived from finance, which represents the optimal balance between risk and return in a project portfolio. It helps organizations select a mix of projects that maximize the expected return for a given level of risk.


Real story: Harry Markowitz, a Nobel laureate in economics, introduced the concept of the Efficient Frontier, which has been applied to PPM to help organizations make better investment decisions.


Capability Maturity Model Integration (CMMI): 📊 The Capability Maturity Model Integration is a framework that helps organizations assess and improve their project portfolio management processes. It consists of five maturity levels, ranging from Level 1 (Initial) to Level 5 (Optimizing).


Example: A software development company may use the CMMI framework to identify areas for improvement in their PPM processes and implement best practices for better project outcomes.


By understanding these key concepts and theories in Project Management and Project Portfolio Management, you will be better equipped to conduct a comprehensive literature review and apply these ideas to your future projects.


Research existing literature to identify relevant models/frameworks


 Have you ever wondered what models and frameworks are essential to successful project portfolio management? 


One of the key tasks in conducting a literature review in project portfolio management is identifying and evaluating relevant models and frameworks. This involves conducting a thorough search of existing literature to identify commonly used and effective approaches for managing project portfolios.


Researching Existing Literature

To begin your research, you can use various academic and professional databases such as Google Scholar, Project Management Institute (PMI) Library, IEEE Xplore, and ScienceDirect. Use keywords like "project portfolio management models and frameworks," "PPM best practices," and "portfolio optimization strategies" to narrow down your search results.


Once you have identified a few relevant articles, you should read them thoroughly and extract key concepts, models, and frameworks. Some of the popular models and frameworks used in project portfolio management include:

1. The Agile Portfolio Management Model

This model enables organizations to align their portfolios with strategic goals using the agile methodology. It incorporates principles such as value delivery, continuous improvement, and customer satisfaction.


2. The Project Portfolio Maturity Model (PPMM)

This model assesses an organization's project portfolio management maturity level and provides a roadmap for improvement. It consists of five levels ranging from ad-hoc to optimized, and each level has specific criteria for success.


3. The Six Sigma Portfolio Management Framework

This framework combines Six Sigma methodologies with project portfolio management to enhance organizational performance, reduce waste, and improve quality. It involves identifying, selecting, and prioritizing projects that align with the organization's strategic objectives.


Example of a Relevant Model/Framework

One of the popular frameworks in project portfolio management is the Project Management Institute's (PMI) Standard for Portfolio Management. It provides a comprehensive guide for organizations to manage their project portfolios effectively. The standard includes four key areas of focus, namely:


  • Portfolio Strategic Management: Aligning the portfolio with the organization's strategic goals

  • Portfolio Governance Management: Defining decision-making processes, roles, and responsibilities

  • Portfolio Performance Management: Monitoring and assessing portfolio performance

  • Portfolio Communication Management: Ensuring transparent communication between stakeholders

The PMI standard is widely used by organizations globally and has been proven to be effective in improving portfolio performance.


Conclusion

In conclusion, conducting a literature review on project portfolio management models and frameworks is crucial for organizations seeking to improve their portfolio management practices. By identifying and evaluating relevant models and frameworks, organizations can select the most suitable approach for optimizing their portfolios.






Analyze and evaluate the literature to determine its relevance and accuracy


Did you know that there are over 4 million scientific articles published every year? With such an abundance of information, it can be challenging to sift through the literature and determine what is relevant and accurate. However, this task is crucial in conducting a literature review for your project management or project portfolio management research.


To analyze and evaluate the literature, you must follow several steps:

🔍 Step 1: Develop a research question or objective

Before you can begin analyzing and evaluating the literature, you must have a clear research question or objective. This question or objective will guide your search and help you determine which articles are relevant to your study. For example, if your research question is "What are the best practices for project risk management?" you will want to look for articles that discuss project risk management specifically.


🔎 Step 2: Conduct a comprehensive search

Once you have your research question or objective, you can begin conducting a comprehensive search. This search should include a variety of sources, such as academic databases, industry publications, and relevant websites. When searching, use a combination of keywords and phrases to ensure you are capturing all relevant information.

📚 Step 3: Read and summarize the literature

After conducting your search, you will have a list of articles to read and analyze. As you read each article, take notes and summarize the key points. This will help you to understand the article's relevance to your research question or objective.


Step 4: Evaluate the literature

Once you have read and summarized the literature, it's time to evaluate it. This evaluation should consider the following factors:


  • Relevance: Does the article address your research question or objective? Does it provide valuable information on the topic?

  • Accuracy: Is the information presented in the article accurate and supported by evidence? Are there any biases or limitations in the study?

  • Credibility: Is the author an expert in the field? Is the article published in a reputable journal or publication?

  • Currency: Is the article up-to-date? Has new research been published that contradicts or adds to the article's findings?


💡 Step 5: Synthesize the literature

After evaluating the literature, you will have a better understanding of which articles are relevant and accurate to your research question or objective. Use this information to synthesize the literature and develop a comprehensive understanding of the topic. You can do this by creating a table or matrix that summarizes the key findings from each article.


📈 Example:

Let's say you are conducting a literature review on project risk management. You have found an article titled "The Importance of Risk Management in Project Success" by Smith et al. After reading and summarizing the article, you evaluate it based on its relevance, accuracy, credibility, and currency.


  • Relevance: The article directly addresses project risk management, making it highly relevant to your research question.

  • Accuracy: The article provides evidence to support its claims and does not have any obvious biases or limitations.

  • Credibility: The authors are experts in the field of project management and the article is published in a reputable journal.

  • Currency: The article was published in 2018, making it relatively up-to-date.

Based on this evaluation, you determine that the article is relevant and accurate to your research question and should be included in your literature review.


In conclusion, analyzing and evaluating the literature is a critical step in conducting a literature review for your project management or project portfolio management research. By following the steps outlined above, you can ensure that you are identifying relevant and accurate information to support your study.


Summarize the key findings from the literature review


The Importance of a Literature Review

A well-conducted literature review is a crucial step in any research project, as it helps researchers understand the current state of knowledge in a particular field, identify gaps in current understanding, and establish the relevance and novelty of their research. The key findings from a literature review provide a foundation for further investigations and serve as a guide for establishing project goals and objectives. Let's explore some essential elements of a literature review and examine some real-life examples.


🔍 Defining Key Concepts and Theories

In a literature review, it's essential to define the key concepts and theories relevant to your research. This helps establish a common understanding of the topic and its key components. For example, in a project management literature review, you might define terms such as:


  • Project: A temporary endeavor undertaken to create a unique product, service, or result

  • Project Management: The practice of initiating, planning, executing, controlling, and closing the work of a team to achieve specific goals and meet specific success criteria

  • Project Portfolio Management (PPM): The centralized management of the processes, methods, and technologies used by project managers and project management offices to analyze and collectively manage current or proposed projects based on numerous key characteristics


📚 Presenting Models/Frameworks

A literature review should also provide an overview of the various models and frameworks that have been proposed or are commonly used in your field of research. In project management, some well-known models/frameworks include:


Agile Project Management

This approach emphasizes flexibility and customer collaboration, with a focus on iterative development and incremental improvements. Agile methodologies include Scrum, Kanban, and Extreme Programming.


Waterfall Project Management

The Waterfall model is a traditional linear approach to project management, which follows a sequential order of phases. Each phase must be completed before proceeding to the next, making it less flexible than Agile methodologies.


PRINCE2 (Projects IN Controlled Environments)

PRINCE2 is a structured project management method widely used in the United Kingdom and Europe. It includes a set of principles, themes, and processes designed to provide a consistent approach to project management.


📝 Critically Analyzing and Evaluating Literature

A literature review should not simply be a summary of existing research but should also provide a critical analysis of the theories, models, and empirical findings in the literature. This may involve evaluating the methodologies used, the strengths and weaknesses of individual studies, and the consistency of findings across studies. For example, you might critically analyze:


  • The appropriateness of Agile methodologies in large-scale projects

  • The effectiveness of Waterfall methodologies in fast-paced, rapidly changing industries

  • The suitability of PRINCE2 for non-European contexts


📊 Summarizing Key Findings

After conducting a thorough review of the literature, summarize the main findings to provide a clear understanding of the current state of knowledge in your field. This may involve discussing trends, patterns, or inconsistencies in the literature. For instance, you could summarize findings such as:


  • A general trend towards adopting Agile methodologies in the software development industry

  • Mixed results regarding the effectiveness of Waterfall methodologies in different industries

  • Limited research on the appropriateness of PRINCE2 in non-European contexts

By summarizing these key findings, you provide a solid foundation for your project and clearly demonstrate the need for further investigation.


🌐 Real-Life Examples

To strengthen your literature review, consider incorporating real-life examples and case studies that illustrate how the concepts, models, and theories you've discussed have been applied in practice. For instance:


  • Agile: A case study of Spotify implementing the Scrum framework to improve collaboration and streamline their product development process

  • Waterfall: An example of a construction project where the Waterfall methodology proved effective due to its structured, sequential approach

  • PRINCE2: The London 2012 Olympics, a large-scale project executed successfully using PRINCE2 methodology


In conclusion, a literature review serves as the foundation of any research project by defining key concepts and theories, presenting models/frameworks, and critically analyzing the existing literature. Incorporating these elements, along with real-life examples, will ensure a comprehensive and insightful review that will guide your project's direction and contribute to the knowledge base in your field.


Create a visual representation of the literature review finding### How to Create a Visual Representation of the Literature Review Findings 🎨


Visualizing Your Research 🔍

A powerful way to convey your literature review findings is by creating a visual representation. This not only helps to better understand the complex relationships between different studies but also makes your work more engaging for the audience. A well-crafted visual representation can be a diagram, chart, or infographic that emphasizes important points and organizes the knowledge you've gained from the literature review.


Choosing the Right Tool 🛠️

Selecting the appropriate tool for creating your visual representation is crucial. There are numerous tools available that can help you design and customize your visuals, such as Microsoft PowerPoint, Adobe Illustrator, or online tools like Canva and Visio. The choice depends on your familiarity with the software and the nature of your literature review findings.


Mapping the Concepts 🌐

Before you start designing, it's essential to organize and map the key concepts and theories you've uncovered in the literature review. This will help you to create a logical flow and ensure that all important elements are included in your visual representation. Here's a simple method to follow:

1. Identify the critical concepts and theories

2. Group relevant studies based on theories or themes

3. Draw connections between groups to show relationships

Design Tips and Tricks for Effective Visuals 🎨





Using Colors and Typography to Emphasize Key Points 🌈


Colors play a significant role in making your visual representation more attractive and easy to understand. Choose a color palette that compliments your content and highlights the key concepts. Similarly, using appropriate typography can enhance the readability and overall visual appeal. Make sure to use a consistent font style and size throughout the design.


Incorporating Icons and Images to Reinforce Concepts 🖼️


Including icons and images can make your visual representation more engaging and help to convey complex ideas more effectively. For example, you can use a lightbulb icon to represent a new idea, or a magnifying glass icon to signify exploration. Make sure the images and icons you choose are relevant to your concepts and not overly distracting.


Establishing Hierarchy and Logical Flow 📏


To make your visual representation easy to follow, it's vital to establish a hierarchy and logical flow. This can be achieved by using different shapes, sizes, and positioning of elements to indicate the order of importance. For example, you can use larger shapes for the main concepts and smaller shapes for supporting ideas.


Real-World Example 🌍

A project manager tasked with presenting a literature review on risk management in construction projects could create a visual representation that incorporates the following elements:


  • A central shape representing the overall concept of risk management in construction projects.

  • Shapes connected to the central shape that highlight the main theories and models in the literature, such as the Risk Breakdown Structure (RBS) or the Monte Carlo simulation.

  • Smaller shapes branching out from these main theories, illustrating specific studies and their findings.

  • Arrows or lines connecting themes and showing relationships between them, such as the influence of one theory on another or the validation of a model by various studies.

  • Icons and images to reinforce the concepts, such as a construction crane for the construction industry or a hazard symbol for risks.

By following these steps, you can create a visually appealing and informative representation of your literature review findings, making it easier for your audience to understand and appreciate the knowledge you've gained from your research.


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1- Introduction 2- Import and export data sets and create data frames within R and Python 3- Sort, merge, aggregate and append data sets. 4- Use measures of central tendency to summarize data and assess symmetry and variation. 5- Differentiate between variable types and measurement scales. 6- Calculate appropriate measures of central tendency based on variable type. 7- Compare variation in two datasets using coefficient of variation. 8- Assess symmetry of data using measures of skewness. 9- Present and summarize distributions of data and relationships between variables graphically. 10- Select appropriate graph to present data 11- Assess distribution using Box-Plot and Histogram. 12- Visualize bivariate relationships using scatter-plots. 13- Present time-series data using motion charts. 14- Introduction 15- Statistical Distributions: Evaluate and analyze standard discrete and continuous distributions, calculate probabilities, and fit distributions to observed. 16- Hypothesis Testing: Formulate research hypotheses, assess appropriate statistical tests, and perform hypothesis testing using R and Python programs. 17- ANOVA/ANCOVA: Analyze the concept of variance, define variables and factors, evaluate sources of variation, and perform analysis using R and Python. 18- Introduction 19- Fundamentals of Predictive Modelling. 20- Carry out parameter testing and evaluation. 21- Validate assumptions in multiple linear regression. 22- Validate models via data partitioning and cross-validation. 23- Introduction 24- Time Series Analysis: Learn concepts, stationarity, ARIMA models, and panel data regression. 25- Introduction 26- Unsupervised Multivariate Methods. 27- Principal Component Analysis (PCA) and its derivations. 28- Hierarchical and non-hierarchical cluster analysis. 29- Panel data regression. 30- Data reduction. 31- Scoring models 32- Multi-collinearity resolution 33- Brand perception mapping 34- Cluster solution interpretation 35- Use of clusters for business strategies 36- Introduction 37- Advance Predictive Modeling 38- Evaluating when to use binary logistic regression correctly. 39- Developing realistic models using functions in R and Python. 40- Interpreting output of global testing using linear regression testing to assess results. 41- Performing out of sample validation to test predictive quality of the model Developing applications of multinomial logistic regression and ordinal. 42- Selecting the appropriate method for modeling categorical variables. 43- Developing models for nominal and ordinal scaled dependent variables in R and Python correctly Developing generalized linear models . 44- Evaluating the concept of generalized linear models. 45- Applying the Poisson regression model and negative binomial regression to count data correctly. 46- Modeling 'time to event' variables using Cox regression. 47- Introduction 48- Classification methods: Evaluate different methods of classification and their performance in order to design optimum classification rules. 49- Naïve Bayes: Understand and appraise the Naïve Bayes classification method. 50- Support Vector Machine algorithm: Understand and appraise the Support Vector Machine algorithm for classification. 51- Decision tree and random forest algorithms: Apply decision trees and random forest algorithms to classification and regression problems. 52- Bootstrapping and bagging: Analyze the concepts of bootstrapping and bagging in the context of decision trees and random forest algorithms. 53- Market Baskets: Analyze transaction data to identify possible associations and derive baskets of associated products. 54- Neural networks: Apply neural networks to classification problems in domains such as speech recognition, image recognition, and document categorization. 55- Introduction 56- Text mining: Concepts and techniques used in analyzing unstructured data. 57- Sentiment analysis: Identifying positive, negative, or neutral tone in Twitter data. 58- SHINY package: Building interpretable dashboards and hosting standalone applications for data analysis. 59- Hadoop framework: Core concepts and applications in Big Data Analytics. 60- Artificial intelligence: Building simple AI models using machine learning algorithms for business analysis. 61- SQL programming: Core SQL for data analytics and uncovering insights in underutilized data. 62- Introduction 63- Transformation and key technologies: Analyze technologies driving digital transformation and assess the challenges of implementing it successfully. 64- Strategic impact of Big Data and Artificial Intelligence: Evaluate theories of strategy and their application to the digital economy, and analyze. 65- Theories of innovation: Appraise theories of disruptive and incremental change and evaluate the challenges of promoting and implementing innovation. 66- Ethics practices and Data Science: Assess the role of codes of ethics in organizations and evaluate the importance of reporting. 67- Introduction 68- Introduction and Background: Provide an overview of the situation, identify the organization, core business, and initial problem/opportunity. 69- Consultancy Process: Describe the process of consultancy development, including literature review, contracting with the client, research methods. 70- Literature Review: Define key concepts and theories, present models/frameworks, and critically analyze and evaluate literature. 71- Contracting with the Client: Identify client wants/needs, define consultant-client relationship, and articulate value exchange principles. 72- Research Methods: Identify and evaluate selected research methods for investigating problems/opportunity and collecting data. 73- Planning and Implementation: Demonstrate skills as a designer and implementer of an effective consulting initiative, provide evidence of ability. 74- Principal Findings and Recommendations: Critically analyze data collected from consultancy process, translate into compact and informative package. 75- Understand how to apply solutions to organisational change. 76- Conclusion and Reflection: Provide overall conclusion to consultancy project, reflect on what was learned about consultancy, managing the consulting. 77- Handle and manage multiple datasets within R and Python environments.
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