Quartz 4

PhD Literature Review Raw

8 min read

PhD General Info Literature Review

Tools

Mendeley Google Collab https://colab.research.google.com/drive/1nFkKdW4HNnG9xeA8TUGgABhGcfRQu6mT#scrollTo=elolzk35QSqG Google Drive - Papers Vault - https://drive.google.com/drive/folders/11eCxOHNDZd-g5s4ONTem7losDdS2y_A6?hl=pt-br XJournay

Planning

It’s tough to narrow down a literature review without knowing the topic! To give you really helpful advice, I need some more information. Could you tell me:

  • What is the specific topic of your paper? The more focused, the better.
  • What is the main argument or thesis you are trying to make? Your literature review should only include studies that directly relate to this.
  • What are some of the key themes or areas you’ve covered in your current review? Maybe you’ve cast your net too wide.
  • What kind of feedback did your advisors give you? Did they suggest specific areas to cut or focus on?

Once I have this information, I can help you identify:

  • Irrelevant studies: These are studies that might be interesting, but don’t directly contribute to your argument.
  • Outdated studies: Are there newer studies that supersede older ones?
  • Overlapping studies: Do you have multiple studies saying essentially the same thing?
  • Tangential themes: Are there any themes that are interesting, but stray from your core argument?

I can also help you with:

  • Identifying key seminal works: These are the foundational studies in your field that you definitely need to include.
  • Finding more focused literature: I can help you search for studies that specifically address your narrowed-down topic.
  • Organizing your literature review: A clear and logical structure can help you stay focused and avoid unnecessary tangents.

I’m here to help you refine your literature review and make it a strong foundation for your paper. Just give me a bit more information to work with!

Here are my responses

  • What is the specific topic of your paper? The impact of AI in the product manager work.

  • What is the main argument or thesis you are trying to make? Considering a organization that is small, growing fast and thus not yet mature in some of the processes (Startup) and thus does not have a structured approach for product management (eg. well defined roles, one of the co-founders acting in great part as the product manager), but is looking for methodologies to solve some of their business challenges, and do believe increasing their maturity of software product management, what would the AI impact for this organization on the path of gaining maturity.

  • What are some of the key themes or areas you’ve covered in your current review? Maybe you’ve cast your net too wide.

  • What kind of feedback did your advisors give you? Did they suggest specific areas to cut or focus on?

Processo:

Anotar vários DOIs, dos que tem pelo menos 5 citações Montar uma análise critica em cima - para aumentar ou diminiur Subir no NotebookLM Fazer a pergunta chave? Fazer a pergunta se tem algo que se conflita?

When i find a result in the searches that is a book or a bibliographic, i send it to corresponding session.

Findings & Insights

productization agile Adjcent Topics

Inspirations

PotentialPaperInspiration

Log

Next

  • Continue with - Introducing “product management” in software development - gscholar -  15.200 resultados resultados
  • Lit Review Process
  • Confirmar que todas as pesquias que eu usei no meu mestrado estao aqui
  • productization?
  • Search terms in English to find research on introducing Software Product Management practices in an organization
  • Gorschek, T., Gomes, A., Pettersson, A., Torkar, R.: Introduction of a process maturity model for market-driven product management and requirements engineering. J. Softw. Evol. Process 24(1), 83–113 (2012) - As yet another model, the market-driven product management and requirements engineering model (MDREPM) enables software process improvement and process assurance in market-driven software engineering [13]. The model targets the unique challenges that product development organizations operating in market-driven environments are facing and can be seen as both a best-practice guide and a process assessment framework.
  • Missing → Study cases?
    1. Rautiainen, K., Lassenius, C., Sulonen, R.: 4CC: a framework for managing software product development. Eng. Manag. J. 14(2), 27–32 (2002) - Finally, the 4CC (Four Cycles of Control) framework combines business management and software product development, and takes both a long-term and short-term view to software product release management [30]. The framework involves the type, timing, and content of different product releases, and aims at providing a common understanding for how to organize software product development.
  • Ver O’Reilly

Ciclo → Pesquisa e Seleção Initialk no Database # X - NOITE Ciclo → Leitura e seleção final dos dos artigos selecionados do Database # X - MANHA

Outros frameworks de software product management, deveria estudá-los?

2025-01-28 Revanp Narrow

  • Pomos:
  • R2D2 Search

2025-01-25 From

  • Colab - Data from databases
  • First database oriented search in specific database (Springer)
  • Organized the deck-

2024-01-16 From XX to YY

  • Organized this document and canvas
  • Evolved the process (video review/helena paper)
  • Covered 3 searches
  • Testes NotebookLLM

R2D2 AI can help introduce

what are the most relevant research papers that talk about how AI can help introduce Software Product Management into a organization?

### **1. "AI AND PRODUCT MANAGEMENT: A THEORETICAL OVERVIEW FROM IDEA TO MARKET" (Ogundipe et al., 2024)**

[AI AND PRODUCT MANAGEMENT: A THEORETICAL OVERVIEW FROM IDEA TO MARKET | International Journal of Management & Entrepreneurship Research](https://www.fepbl.com/index.php/ijmer/article/view/965)

Local PDF: [965-Article Text-2441-1-10-20240326_annotated.pdf](https://drive.google.com/drive/search?q=965-Article%20Text-2441-1-10-20240326_annotated.pdf%20parent:11eCxOHNDZd-g5s4ONTem7losDdS2y_A6)

- **Relevance:** This paper provides a comprehensive overview of how AI can be integrated into various stages of the product lifecycle, from ideation to launch. This is crucial when introducing Product Management, as it demonstrates the value AI brings to the process.
- **Key takeaway:** AI can streamline processes, improve decision-making, and enhance product development, making a strong case for adopting a Product Management framework.

### **2. "Artificial Intelligence in Product Management" (Mahajan, 2024)**

- **Relevance:** This paper delves into the practical applications of AI in Product Management, including user research, product development, and product strategy.
- **Key takeaway:** By showcasing AI's ability to gather and analyze data, predict user needs, and personalize experiences, this paper highlights the benefits of a data-driven approach that Product Management facilitates.

Local PDF: [Artificial-Intelligence-in-Product-Management.pdf](https://drive.google.com/drive/search?q=Artificial-Intelligence-in-Product-Management.pdf%20parent:11eCxOHNDZd-g5s4ONTem7losDdS2y_A6)
### Artificial Intelligence, Scientific Discovery, and Product Innovation

**3. "Artificial Intelligence, Scientific Discovery, and Product Innovation" (MIT Doctoral Student)**

- **Relevance:** While focused on scientific discovery, this paper explores how AI tools can augment human creativity and decision-making in product development.
- **Key takeaway:** It provides insights into how AI can empower product teams to generate ideas, evaluate options, and make informed choices, which are essential aspects of effective Product Management.

Local PDF: [2412.17866v1.pdf](https://drive.google.com/drive/search?q=2412.17866v1.pdf%20parent:11eCxOHNDZd-g5s4ONTem7losDdS2y_A6)

[Aidan Toner-Rodgers](https://arxiv.org/search/econ?searchtype=author&query=Toner-Rodgers,+A)

This paper studies the impact of artificial intelligence on innovation, exploiting the randomized introduction of a new materials discovery technology to 1,018 scientists in the R&D lab of a large U.S. firm. AI-assisted researchers discover 44% more materials, resulting in a 39% increase in patent filings and a 17% rise in downstream product innovation. These compounds possess more novel chemical structures and lead to more radical inventions. However, the technology has strikingly disparate effects across the productivity distribution: while the bottom third of scientists see little benefit, the output of top researchers nearly doubles. Investigating the mechanisms behind these results, I show that AI automates 57% of “idea-generation” tasks, reallocating researchers to the new task of evaluating model-produced candidate materials. Top scientists leverage their domain knowledge to prioritize promising AI suggestions, while others waste significant resources testing false positives. Together, these findings demonstrate the potential of AI-augmented research and highlight the complementarity between algorithms and expertise in the innovative process. Survey evidence reveals that these gains come at a cost, however, as 82% of scientists report reduced satisfaction with their work due to decreased creativity and skill underutilization.

2412.17866v1.pdf

### **4. "AI Product Management 2 Years In" (Cagan, 2024)**

- **Relevance:** This article discusses the evolving role of product managers in the age of AI and how AI is reshaping product development practices.
- **Key takeaway:** It emphasizes the importance of integrating AI into product strategy and the need for product managers to adapt to AI-powered tools and workflows.

Local PDF: [AI Product Management 2 Years In.pdf](https://drive.google.com/drive/search?q=AI%20Product%20Management%202%20Years%20In.pdf%20parent:11eCxOHNDZd-g5s4ONTem7losDdS2y_A6)

**5. "Harnessing AI in Product Management To Build Better Products" (DigitalOcean)**

- **Relevance:** This article provides a practical guide to using AI in various Product Management tasks, such as project management, market research, and user feedback analysis.
- **Key takeaway:** It demonstrates how AI tools can automate tasks, improve efficiency, and enhance decision-making for product managers.

Local PDF: [Harnessing AI in Product Management To Build Better Products _ DigitalOcean.pdf](https://drive.google.com/drive/search?q=Harnessing%20AI%20in%20Product%20Management%20To%20Build%20Better%20Products%20_%20DigitalOcean.pdf%20parent:11eCxOHNDZd-g5s4ONTem7losDdS2y_A6)

**Why these papers are relevant:**

- **Demonstrate Value:** These papers collectively illustrate the value proposition of AI in product development, which is crucial for convincing organizations to invest in Product Management and AI-powered tools.
- **Provide Practical Guidance:** They offer practical insights and examples of how AI can be applied to various Product Management activities, making it easier for organizations to understand and implement these changes.
- **Highlight Evolving Roles:** They discuss the changing role of product managers in the context of AI, emphasizing the need for new skills and approaches to leverage AI effectively.

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