AI Product Management Paper Support
Budget: $10 – $30 USD
I have a very rough first draft of an academic paper that explores how artificial intelligence is reshaping product management practices. Before I move further, I need a research-minded collaborator who can strengthen the backbone of the study through rigorous data work.
Here’s what I’m looking for:
• Literature review & background
– Locate, read, and summarise the most recent (last 5-7 years) peer-reviewed work on AI adoption, road-mapping, and decision-making in product management.
– Deliver an annotated bibliography and a well-structured review section formatted in APA.
• Data collection & surveys
– Design a brief online questionnaire for product managers (using Qualtrics or Google Forms).
– Source a relevant sample, administer the survey, and provide a clean, anonymised dataset (CSV/Excel).
• Statistical analysis & interpretation
– Run descriptive stats and appropriate inferential tests (t-test, ANOVA, or regression as warranted) in Python, R, or SPSS.
– Supply code/notebooks, output tables, and concise narrative explaining what the numbers mean for practitioners.
Acceptance criteria
1. At least 30 high-quality references integrated into the literature review.
2. Minimum 100 valid survey responses with demographic breakdown.
3. Reproducible analysis scripts plus a 1–2 page insight summary I can drop directly into the Results & Discussion sections.
If you have published in management or JPIM Research Forum journals, or regularly work with mixed-methods research on AI topics, I’d love to tap into that experience. Please outline your approach and share one relevant writing or analysis sample so I can gauge fit.
Here’s what I’m looking for:
• Literature review & background
– Locate, read, and summarise the most recent (last 5-7 years) peer-reviewed work on AI adoption, road-mapping, and decision-making in product management.
– Deliver an annotated bibliography and a well-structured review section formatted in APA.
• Data collection & surveys
– Design a brief online questionnaire for product managers (using Qualtrics or Google Forms).
– Source a relevant sample, administer the survey, and provide a clean, anonymised dataset (CSV/Excel).
• Statistical analysis & interpretation
– Run descriptive stats and appropriate inferential tests (t-test, ANOVA, or regression as warranted) in Python, R, or SPSS.
– Supply code/notebooks, output tables, and concise narrative explaining what the numbers mean for practitioners.
Acceptance criteria
1. At least 30 high-quality references integrated into the literature review.
2. Minimum 100 valid survey responses with demographic breakdown.
3. Reproducible analysis scripts plus a 1–2 page insight summary I can drop directly into the Results & Discussion sections.
If you have published in management or JPIM Research Forum journals, or regularly work with mixed-methods research on AI topics, I’d love to tap into that experience. Please outline your approach and share one relevant writing or analysis sample so I can gauge fit.