Managerial Economics provides students with the opportunity to use economic theory to help make business decisions. The course will focus on how issues such as pricing, competition, incentives and biases impact how companies choose to allocate limited resources. Students will utilize economic theory to develop business strategies related to both external stakeholders (e.g., competitors, customers and suppliers) as well as internal operations, such as capital allocation.
Strategic Industry Analysis through Milestone Projects (Weeks 1–6)
Students complete a series of structured milestone assignments analyzing a public company through the lens of Porter’s Five Forces. These include:
Week 1: Company selection + risk classification
Week 2: Threat of substitutes (2-slide deck)
Week 4: Buyer and supplier power (4-slide deck)
Week 6: Threat of new entrants and industry rivalry (4-slide deck)
Weekly Case Studies Applying Economic Theory (Weeks 3, 5, and 7)
Students engage in three applied case studies, each tied to a central economic concept:
Week 3: Economies of Scope and Joint Production
Week 5: Product Differentiation and Competitive Advantage
Week 7: Strategic Positioning: Differentiation vs. Cost Leadership
Each case requires a written analysis (500–750 words) and peer feedback via structured discussion boards.
Peer Review and Collaborative Learning (Ongoing)
Throughout the course, students participate in small-group peer review discussions for each case and milestone. These collaborative activities reinforce critical thinking, applied economics, and industry-specific insight while helping students improve their own work before final submission.
Final Strategic Analysis Project (Week 8)
In the final week, students synthesize their work into a 6–10 slide strategic recommendation presentation, incorporating Five Forces analysis, cost structure insights, and competitive strategy. The project mirrors real-world executive briefings and includes optional narration or speaker notes.
Your grade in this course will be determined by the following criteria:
Assignment | Points |
---|---|
Academic Integrity Agreement | 1 |
Week 1 Discussion: Welcome and Introduction | 2 |
Week 1 Discussion: Course Project Launch – Company Selection | 2 |
Project Milestones (4 at 5 pts each) | 20 |
Quizzes (8 at 2 pts each) | 16 |
Peer Review Discussions (6 at 3 points each) | 18 |
Case Study Assignments (3 at 6 pts each) | 18 |
Week 8 Assignment: Final Strategic Analysis Project | 20 |
Week 8 Discussion: Final Reflection and Project Exchange | 3 |
Total | 100 |
Grade | Points Grade | Point Average (GPA) |
A | 94 – 100% | 4.00 |
A- | 90 – 93% | 3.75 |
B+ | 87 – 89% | 3.50 |
B | 84 – 86% | 3.00 |
B- | 80 – 83% | 2.75 |
C+ | 77 – 79% | 2.50 |
C | 74 – 76% | 2.00 |
C- | 70 – 73% | 1.75 |
D | 64 – 69% | 1.00 |
F | 00 – 63% | 0.00 |
Week 1: Wednesday – Sunday
Week 2: Monday – Sunday
Week 3: Monday – Sunday
Week 4: Monday – Sunday
Week 5: Monday – Sunday
Week 6: Monday – Sunday
Week 7: Monday – Sunday
Week 8: Monday – Friday
WEEK | TOPICS | ASSESSMENTS | DUE |
1 | Managerial Economics and Strategic Decision-Making |
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2 | Demand and Pricing |
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3 | Cost and Production |
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4 | Economics of Organization |
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5 | Market Equilibrium and the Perfect Competition Model |
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6 | Firm Competition and Market Structure |
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7 | Market Regulation |
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8 | Game Theory and Course Wrap-Up |
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A grade of 80% or higher is required to pass the course. A grade lower than 80% will result in you having to repeat the course. Obtaining two "Fs" in the program will result in dismissal from the program.
Generative AI (GenAI) applications (like ChatGPT) have proven to be powerful and effective tools, and students are encouraged to become familiar with and use them. However, as with any tool, students must use GenAI in ways that support their roles as learners and professionals. The use of AI in academic work falls under our academic integrity agreement, ensuring that all AI applications are used in alignment with our commitment to honest and responsible learning.
In situations in which AI tools are used as a resource, students must:
As GenAI continues to evolve, students should also stay abreast of best practices and changing risks and benefits.
Please note that individual courses or assignments may have specific guidelines regarding AI use — please refer to your faculty’s directions or assignment instructions for details.
The Student Orientation has a module "Artificial Intelligence Literacy for Students", please refer to this module for more information about navigating the use of AI.
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Make sure to cite your sources appropriately as well as use your own words in synthesizing information from published literature.
You can learn more about Turnitin in the guide on how to navigate your Similarity Report.
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Students taking online graduate courses through the College of Business will be administratively dropped for non-participation if a graded assignment/discussion post is not submitted before Sunday at 11:59 p.m. ET of the first week. Reinstatement is at the purview of the Dean’s Office.
The University of New England values academic integrity in all aspects of the educational experience. Academic dishonesty in any form undermines this standard and devalues the original contributions of others. It is the responsibility of all members of the University community to actively uphold the integrity of the academy; failure to act, for any reason, is not acceptable. For information about plagiarism and academic misconduct, please visit UNE Plagiarism Policies.
Academic dishonesty includes, but is not limited to the following: