How to Build Your Group Presentation Without Winging It
Your team has the Uber case. The question is about how information systems affect driver management and monitoring — and whether that is a net positive or negative for drivers. This is not a simple summary task. It is an IS analysis problem that requires frameworks, evidence from the case, and a defensible conclusion. This guide walks through how to do it right.
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This is not a case summary. Your team is not being asked to retell the Uber story to people who already read it. The rubric wants you to apply IS models and course concepts to a specific question about how information systems function as managerial tools — and then reach a conclusion about whether those tools help or hurt the workers they control. That is three distinct intellectual moves: identify the IS mechanisms, apply theory, take a position. Groups that only do the first one earn about half the marks.
The format is a PowerPoint deck of 6 to 10 slides with an embedded podcast recorded through PowerPoint’s Insert > Audio function. One team member posts it to the Canvas discussion board. The rubric grades you on background (1 point), analysis (4 points), conclusions (1 point), and organization (4 points). That weighting tells you something. Analysis and organization together are 8 of 10 points. A beautiful slide deck with weak analytical content still scores around a 5.
Your Assigned Question Is Not the Same as the Book’s Question 3
The book’s discussion question 3 asks about organizational culture. Your team’s assigned question — as written in the course instructions — asks specifically how Uber’s IS implementation affected driver management and monitoring, and whether those systems are beneficial or harmful to drivers. These are different analytical targets. Do not let the book’s question numbering confuse your team’s focus. Your slides need to answer the question as your course instructions phrase it, not as it appears in the textbook.
The assignment also says to use at least one external source — not from the textbook. That source needs to be cited in APA format. Company websites, industry publications, journal articles, and government sources all count. Wikipedia does not. You have one required external source and a case study packed with specific details. Use both. Groups that cite only the textbook and nothing else are leaving an easy point on the table.
One more thing worth saying upfront: the rubric explicitly grades teamwork under organization. A presentation where one person wrote all the slides and one person recorded all the audio does not demonstrate collaborative work. Distribute slide ownership and narration across team members. It will show in the final product, and graders can tell.
How to Read the Uber Case — What to Pull Out and What to Ignore
The case gives you a lot of detail. Not all of it is equally useful for your question. The background slide is worth 1 point, and the rubric says it should identify symptoms, critical factors, and the current state “as relevant to the particular question.” That phrase matters. You are not summarizing the whole case — just the parts that connect to driver management and monitoring through IS.
Read the case once for orientation. Then read it again with a highlighter mentality, asking: what specific IS mechanisms does Uber use to manage driver behavior? You will find about eight distinct ones buried in the text. Pull those out first. Everything else — the company founding story, the general ride-hail market context — is background noise for your purposes.
Eight IS Mechanisms the Case Explicitly Describes
These are direct from the case text. Each one is a specific information system feature being used to manage driver behavior. Your analysis needs to engage with at least three or four of them specifically.
Surge Pricing + Push Notifications
- Algorithmic fare increases during peak periods
- Real-time push: “Demand is high in your area”
- Soft coercion to work hours drivers would not otherwise choose
- Technically voluntary — drivers can still log off
Gamification + Progress Alerts
- Video game mechanics: badges, noncash rewards
- “You’re almost halfway there” progress notifications
- Income target alerts triggered when drivers try to log off
- Signing bonuses tied to initial ride-count milestones
Route Tracking + Acceptance Rate Surveillance
- GPS tracks every route taken vs. optimal route
- Minimum acceptance rate enforced by the system
- Minimum trip and availability thresholds for bonus eligibility
- Blind acceptance: drivers do not see destination or rate before accepting
Passenger Star Ratings as KPI
- 1–5 star system is primary performance metric
- No traditional human manager — ratings replace supervision
- Ratings can affect ride allocation
- Drivers report strong negative feelings about rating-based earnings
Pre-Loading Next Fare
- Next ride request sent before current ride ends
- Netflix binge-watching comparison made explicitly in case
- Reduces natural stopping points in driver’s shift
- Psychological mechanism: commitment and sunk cost
Suspension and Permanent Removal
- Drivers who cancel unprofitable fares risk deactivation
- No appeals process clearly defined in case
- Asymmetric power: Uber knows the algorithm, drivers do not
- Functions as a disciplinary mechanism without a human manager
That is your case evidence. Those six mechanism clusters are what you draw on when building both your background slide and your analysis section. The background slide should introduce three or four of the most critical ones — enough to establish context without becoming a summary of everything. Save the deeper analysis for the analysis slides where you apply IS theory to explain why these mechanisms work the way they do.
Identify the Real Problem, Not Just the Symptoms
The rubric says to “identify the real problem and not the symptoms of the problem.” In this case, the symptoms are things like high driver turnover (50% within the first year) and driver dissatisfaction with star ratings. The real problem underneath those symptoms is the structural information asymmetry built into the platform — Uber has complete data visibility over driver behavior while drivers have near-zero visibility into how the algorithm actually works. That asymmetry is what enables the control mechanisms. Name that in your background. It is more analytically precise than saying “Uber monitors its drivers.”
Breaking Down the Assigned Question — Two Parts, One Coherent Argument
The question has two halves and your presentation needs to answer both explicitly. Part one: how has Uber’s implementation of information systems affected the way drivers are managed and monitored? Part two: are those systems beneficial or harmful to drivers?
Part one is descriptive and analytical. You map the IS mechanisms to managerial functions — scheduling, monitoring, performance evaluation, discipline — and explain how each one operates through technology rather than through a human manager. This is where your IS framework goes. You are not just listing what the app does. You are explaining how it functions as a managerial control system, using theory to frame that explanation.
Part two is argumentative. You have to take a position. “It depends on the driver” is not a conclusion — it is a dodge. Pick a side. Either the systems are net beneficial to drivers, net harmful to drivers, or harmful in ways that outweigh the benefits. The case gives you enough evidence for any of those positions. What matters is that your conclusion is fully supported by the analysis you built in slides 3 through 6.
The drivers don’t know how the system that is directing them works.
— Managing & Using Information Systems, Uber case, 8th editionThat single sentence from the case is analytically significant. It is the clearest statement of information asymmetry in the entire text. If you want to argue that the systems are harmful to drivers, that sentence is your anchor. If you want to argue they are beneficial with significant caveats, you need to address that sentence head-on and explain why the lack of algorithmic transparency does not negate the benefits.
Which IS Models to Apply — and How to Apply Them Without Just Naming Them
The rubric says to “apply IS models, course content, and outside research.” Naming a framework in a slide header is not the same as applying it. Application means taking the framework’s logic and showing how the Uber case fits within it — specifically, using case details to illustrate the model’s concepts. Here are the frameworks that work best for this question.
Technology-Mediated Control (TMC)
TMC describes how organizations use digital systems to monitor, direct, and evaluate worker behavior in place of direct human supervision. Cram and Wiener (2020), cited in the case itself, define TMC as a form of control where the technology — not a manager — is the mechanism of organizational authority. In Uber’s system, the app is the supervisor. Apply this by mapping each Uber IS mechanism (surge pricing, deactivation threats, acceptance rate monitoring) to the TMC control types: behavior control, outcome control, and input control.
Algorithmic Management Theory
Möhlmann et al. (2021) in MIS Quarterly — also cited in the case — define algorithmic management as a system where algorithms both match workers to tasks and control their behavior. The matching function is where the platform creates value. The control function is where the managerial relationship lives. For your analysis, separate these two functions explicitly: the matching algorithm (connecting riders to drivers efficiently) has clear benefits; the control algorithm (blind fares, deactivation threats, psychological nudges) has documented harms. That distinction is analytically more precise than treating the platform as one undifferentiated system.
Information Asymmetry
Drawn from economics but widely used in IS. Information asymmetry exists when one party in a transaction has significantly more or better information than the other. In Uber’s platform, the company has complete behavioral data on every driver. Drivers have no visibility into the algorithm, the pricing logic, or why they were deactivated. This asymmetry is the structural basis for all of Uber’s control mechanisms. Apply it by showing how each IS feature — blind acceptance rates, opaque deactivation — depends on and reinforces the asymmetry. It also connects directly to the harm argument: asymmetry prevents informed consent.
You do not need all three frameworks in your slides. Two strong, well-applied frameworks are better than three frameworks named in passing. Pick the one that fits your team’s argument most cleanly and develop it fully across your analysis slides. The second framework can be a supporting lens rather than a primary one.
How to Apply a Framework on a Slide — Specifically
The Case Already Cites the Frameworks — Use That to Your Advantage
The case’s source list includes Möhlmann et al. (2021) in MIS Quarterly and Cram and Wiener (2020) in the Communications of the Association for Information Systems. These are peer-reviewed IS sources cited directly in your textbook case. You can engage with them by name — briefly explain the concept, then show how it maps to the case evidence. This demonstrates you can work with primary IS literature, not just restate the case narrative. Your external source requirement is separate from this — pick something the case does not already cite.
Building the Beneficial vs. Harmful Argument — Evidence on Both Sides, Then a Verdict
Your analysis slides need to present both sides before your conclusion slides pick one. This is not fence-sitting — it is analytical rigor. A presentation that only lists harms without acknowledging the real benefits a driver gets from the platform is as weak as one that only lists benefits while ignoring a 50% first-year turnover rate. Show you understand the complexity, then explain why one side outweighs the other.
Evidence for Beneficial — From the Case
- True scheduling flexibility: drivers can log on and off when they choose
- Surge pricing creates high-income windows drivers can plan around
- GPS route optimization reduces dead miles and improves earnings efficiency
- Automated ride matching eliminates the need for drivers to source their own customers
- Performance data (ratings, completion rates) gives drivers visible feedback metrics
- Signing bonuses and milestone incentives provide income supplements for new drivers
- Low barrier to entry — no office, no application process beyond driver approval
Evidence for Harmful — From the Case
- Blind acceptance policy: drivers accept fares without knowing destination or pay rate
- Canceling unprofitable fares risks deactivation — a permanent income loss
- Psychological manipulation: income target pop-ups, Netflix-style next-ride loading
- Drivers do not understand the algorithm directing their behavior
- Star ratings as sole KPI — a metric drivers cannot contest or appeal
- 50% turnover within first year signals the model does not retain drivers
- Uber’s own senior official admits underinvestment in driver experience
Now, which side wins? Look at the turnover number. A 50% first-year dropout rate is not a sign of a beneficial system. Workers who find something beneficial tend to stay. The psychological manipulation evidence — the Netflix-style ride loading, the income-target pop-ups timed to appear when drivers try to stop — is not a neutral feature. It is documented behavioral engineering designed to override driver decision-making. That does not sit alongside “flexible scheduling” as an equal benefit. It actively undermines the autonomy that flexible scheduling is supposed to provide.
A defensible conclusion: the systems are structurally harmful to drivers because the control mechanisms — information asymmetry, psychological nudges, deactivation threats — systematically override the autonomy benefits that nominally exist. The flexibility is real but conditional on compliance with algorithmic directives the driver cannot see, contest, or understand.
You Can Argue Beneficial — But You Need to Directly Counter the Turnover Data
If your team wants to argue the systems are net beneficial, you need to explain the 50% turnover rate without dismissing it. The best counter-argument: high turnover in gig work reflects low switching costs and market competition for driver time, not dissatisfaction with the platform specifically. Drivers may churn because Lyft launched a promotion, not because Uber’s app is harmful. That is a legitimate argument if you support it. But if you ignore the turnover number entirely, the argument is incomplete and a grader will notice the gap.
All Four Discussion Questions — How to Approach Each One
Your team is presenting on your assigned question, but the broader course discussion may require engagement with all four. Here is how to approach each one analytically, not just descriptively.
| Question | What It Is Really Asking | Key Analytical Move | Frameworks to Use |
|---|---|---|---|
| Q1: How effective is Uber’s “algorithmic boss” as a managerial control system? | Evaluate the algorithmic management system against the criteria of an effective managerial control system — does it actually achieve consistent driver behavior, and at what cost? | Separate short-term effectiveness (it does get drivers on the road during surge periods) from long-term effectiveness (50% turnover suggests the system burns through its workforce). A control system that achieves compliance but destroys retention is partially effective at best. | TMC (Cram & Wiener, 2020), managerial control typology from IS course content, organizational behavior theory on intrinsic vs. extrinsic motivation |
| Q2: What are the benefits and downsides to Uber of using algorithmic control? | This question is Uber’s perspective, not the driver’s. Analyze the platform economics — what does algorithmic control enable for the business that human management could not? | Benefits for Uber: scale (millions of contractors managed at near-zero marginal cost), real-time behavioral data, dynamic pricing that maximizes revenue. Downsides: reputational risk, regulatory exposure (misclassification lawsuits), and the driver shortage risk when turnover is high enough to affect service availability. | Platform economics, gig economy business models, IT as competitive advantage |
| Q3 (Team 5 — Your Question): How has IS affected driver management and monitoring? Beneficial or harmful? | Map the specific IS mechanisms to managerial functions, then evaluate net impact on drivers. Requires both descriptive analysis and a normative conclusion. | Use algorithmic management theory (Möhlmann et al., 2021) to separate matching from control. Show how the control mechanisms specifically undermine driver autonomy despite the scheduling flexibility that nominally exists. Build toward a conclusion that accounts for the turnover data. | Algorithmic management (Möhlmann et al., 2021), TMC, information asymmetry, surveillance theory |
| Q4: Is the Uber digital business model sustainable? | Evaluate the long-term viability of a model that depends on independent contractors managed by algorithm, in the context of regulatory pressure, driver churn, and market competition. | The model is under pressure from three directions simultaneously: labor regulators questioning contractor classification (California AB5 as precedent), market competition from Lyft and international platforms, and a driver supply problem created by high churn. Sustainability requires addressing driver retention, which the current algorithmic control model is not built to do. | Porter’s five forces adapted for platform businesses, gig economy regulatory risk, platform sustainability literature |
A Note on Q4 and Current Events
The textbook case was written in the 2021–2022 timeframe. Since then, Uber has faced additional regulatory and labor market pressures. If your course allows citing recent news sources (and the assignment says Wall Street Journal and Business Week are acceptable), you can reference current developments around driver pay minimums in cities like New York, or ongoing labor classification legal battles in multiple jurisdictions. That brings the analysis up to date and shows you can connect the textbook case to real-world developments — which is exactly what the rubric means by “outside research.”
Verified External Source: MIS Quarterly — Möhlmann et al. (2021)
The paper “Algorithmic Management of Work on Online Labor Platforms: When Matching Meets Control” by Möhlmann, Zalmanson, Henfridsson, and Gregory was published in MIS Quarterly, Vol. 45, No. 4 (2021). It is the most rigorously peer-reviewed IS source directly applicable to this case — and notably, it is already cited in the textbook case itself. The paper develops the theoretical distinction between matching and control in algorithmic management and analyzes how these dual functions create tension between platform efficiency and worker experience. It is accessible through most university library databases. APA citation: Möhlmann, M., Zalmanson, L., Henfridsson, O., & Gregory, R. W. (2021). Algorithmic management of work on online labor platforms: When matching meets control. MIS Quarterly, 45(4), 1999–2022.
Structuring the 6–10 Slide Deck — Section by Section
Six slides is tight. Ten slides is comfortable. Aim for eight. That gives you room to develop the analysis without padding. Here is how to allocate slides so the rubric criteria each get enough real estate.
| Slide(s) | Section | What Goes Here | Rubric Criterion |
|---|---|---|---|
| Slide 1 | Title + Team | Case name, question number and text, team number, course code, date. Keep it clean. No need for decorative elements that waste space. | Organization |
| Slide 2 | Background | Uber’s operational model (independent contractors, algorithmic platform), the specific IS mechanisms used to manage drivers, and the core problem: information asymmetry between platform and driver. Do not summarize the entire case. Only what is relevant to Q3. End with the real problem statement — not “drivers are monitored” but “the platform’s IS architecture gives Uber complete behavioral visibility while giving drivers none.” | Background (1 pt) |
| Slides 3–4 | Analysis Part 1 — How IS Affects Management | Apply your primary IS framework (algorithmic management or TMC) to map the specific mechanisms — surge pricing, blind acceptance, deactivation threats, gamification — to managerial functions. Show how each one substitutes for a human managerial action: scheduling → surge nudges; performance review → star ratings; discipline → deactivation. Cite the framework and at least one external source here. | Analysis (4 pts) |
| Slides 5–6 | Analysis Part 2 — Beneficial vs. Harmful Evaluation | Present the benefits case (flexibility, matching efficiency, income potential) and the harms case (blind fares, psychological manipulation, asymmetric information, 50% turnover). Use a visual comparison — two-column format or a simple pros/cons table. The analysis should clearly show which side of the evidence is stronger and why, setting up the conclusion. This is not just a list — explain the mechanisms behind each benefit and harm. | Analysis (4 pts) |
| Slide 7 | Implications and Tradeoffs | The rubric mentions “logically discuss options, implications and tradeoffs.” This slide acknowledges that Uber’s model creates real tradeoffs — platform efficiency versus driver welfare, scalability versus sustainable labor supply. If applicable, briefly note regulatory implications (labor classification pressure) and what the high turnover rate means for long-term platform viability. This slide shows you can think beyond the question to its consequences. | Analysis (4 pts) |
| Slide 8 | Conclusions + Recommendations | State your verdict on beneficial vs. harmful, supported by your analysis. Then add at least one practical recommendation for Uber — the rubric says “if applicable, flows smoothly into relevant and practical recommendations.” Good options: implement algorithmic transparency (show drivers their acceptance rate threshold before they face deactivation), restructure the deactivation policy so drivers can appeal, or redesign the blind acceptance system so rates are disclosed upfront. These come directly from the case’s identified harms. | Conclusions (1 pt) + Organization |
| Slide 9 | References | APA format. Textbook, the Möhlmann et al. MIS Quarterly paper (or your chosen external source), and any other sources cited in slides. Double-check that every in-slide citation has a reference list entry. Use a font small enough to fit on one slide — 10pt is acceptable for references. | Organization |
The Podcast: What It Needs to Do and How to Record It
The podcast is not a separate deliverable from the slides — it is embedded audio using PowerPoint’s Insert > Audio feature. Each team member should narrate the slides they own. Record in a quiet space. Laptop microphones are acceptable but test the audio quality before recording the final version. Background noise, echo in a large room, and audio that cuts in and out are all avoidable and all signal low effort.
The audio should add to the slides, not just read them aloud. If your slide says “Uber uses surge pricing to incentivize peak-hour availability,” the narration should explain why that matters — “this is not just a pricing feature; it functions as a scheduling tool that shifts driver behavior without Uber technically mandating when drivers work.” That is the kind of depth the rubric rewards in the analysis criterion.
Slide Design Principles for a Professional Management Presentation
The rubric says the presentation should be “well structured, professional and organized.” A few specifics that matter: use no more than five bullet points per slide (three is better), put your takeaway in the slide title rather than a generic label (“Star Ratings Replace Human Performance Reviews” beats “Performance Management”), and use a consistent color scheme and font across all slides. Charts or visuals on the beneficial vs. harmful slide make the comparison cleaner than a text list. Do not use videos from external sources — the rubric explicitly prohibits this.
Finding One Strong External Source — and Making It Count
The assignment requires at least one external source beyond the textbook. One source. That is a low bar, but it still needs to be a credible, APA-cited reference that strengthens your analysis. The easiest mistake is picking something generic — a news article that says “Uber controls drivers with an app” — when something more specific and authoritative is available.
For this case, the most analytically valuable external sources fall into two categories: peer-reviewed IS research and credible industry/news journalism. The rubric permits both. Here is where to look for each.
Best Database: MIS Quarterly, MISQ Executive, JAMIA
Search terms: “algorithmic management gig economy,” “platform labor control IS,” “ride-hailing driver monitoring.” The Möhlmann et al. (2021) paper is pre-cited in the case — use it or find something that cites it. Filter for 2018 onward. MIS Quarterly and the Journal of Management Information Systems are the top outlets for this topic area.
WSJ, New York Times, Harvard Business Review
The case itself cites the New York Times Scheiber (2017) article on Uber’s psychological tricks. The Wall Street Journal covers Uber’s ongoing labor disputes and regulatory battles. Harvard Business Review has published analysis of gig economy platform models. These are all explicitly permitted source types in your assignment instructions.
Pick the source that does the most analytical work for you. If your argument leans on information asymmetry and psychological manipulation, a peer-reviewed paper on platform labor control gives you the theoretical grounding. If your argument leans on real-world consequences — turnover, regulatory pressure, driver income instability — a well-sourced journalism piece from WSJ or HBR gives you current evidence. You can use one of each if your team wants to strengthen the presentation, since the rubric says “at least 1” external source, not “maximum 1.”
The Scheiber Article Is Citable — But With One Caveat
The New York Times article “How Uber Uses Psychological Tricks to Push Its Drivers’ Buttons” by Noam Scheiber (2017) is cited in your textbook case. It is technically a journalistic source, not a peer-reviewed one, but the rubric explicitly permits periodicals like the Wall Street Journal — and the NYT is in the same class. If you use it, cite it properly in APA: Scheiber, N. (2017, April 2). How Uber uses psychological tricks to push its drivers’ buttons. The New York Times. The caveat: it is from 2017, which is aging. Pair it with something more recent if you use it.
Mistakes That Cost Points — and What to Do Instead
| # | The Mistake | Why It Costs Points | The Fix |
|---|---|---|---|
| 1 | Answering a different question than the one assigned | The book’s question 3 is about organizational culture. Your team’s assigned question is about driver management and monitoring. If your slides answer the culture question instead of the management and monitoring question, you have missed the analytical target regardless of how well-designed the slides are. | Write the assigned question text on a sticky note. Before finalizing each slide, ask: does this slide directly address how IS affects driver management and monitoring? If not, revise or cut it. |
| 2 | Presenting a background that covers the entire case | The rubric says background should be relevant “to the particular question you are analyzing.” A background that walks through Uber’s founding, business model, global expansion, and revenue growth is covering the case, not the question. It wastes a slide and it signals the team did not read the rubric carefully. | Background slide should cover exactly three things: Uber’s IS platform as a managerial system, the specific mechanisms used to monitor and direct drivers, and the information asymmetry that structures the whole relationship. That is it. |
| 3 | No IS framework applied — just a list of app features | The rubric’s highest-value criterion (4 points) is analysis, and it specifically requires applying IS models and course content. A slide that lists “surge pricing, push notifications, star ratings” without connecting them to an IS framework has described the case rather than analyzed it. That is a background-level deliverable, not an analysis-level one. | Name one or two IS frameworks in your first analysis slide. Then spend the remaining analysis slides showing how the case evidence maps to those frameworks. Every case detail you mention should connect back to a framework concept. |
| 4 | Ending without a clear verdict on beneficial vs. harmful | The question explicitly asks you to state whether the systems are beneficial or harmful and explain your answer. A conclusion slide that says “there are benefits and harms on both sides” and stops there has not answered the question. It has summarized the analysis without concluding from it. | Your conclusion slide needs one clear declarative statement: either these systems are net harmful to drivers, net beneficial to drivers, or beneficial in the matching function but harmful in the control function. Then support it in two or three bullet points drawn directly from the analysis slides. |
| 5 | Missing or incorrectly formatted APA citations | Organization is worth 4 points and includes the professional quality of the presentation. Slides that cite sources as “(Uber, 2019)” or “from the textbook” rather than using proper APA in-text format signal carelessness. A missing reference slide means the external source requirement may not be verifiable. | Use APA in-text citations on slides where you reference a source: (Möhlmann et al., 2021). Include a references slide at the end with full APA entries. Run your reference entries against the Purdue OWL APA 7th edition guide before submitting. |
| 6 | Audio recorded by one person only | Organization includes teamwork. A podcast where only one voice appears from start to finish suggests unequal contribution. With 4 points on organization, an uneven team effort has real point consequences beyond just optics. | Assign slides to team members, and each member records narration for their assigned slides. Do a quick sound check before final recording. Consistent audio quality is as important as having multiple voices — if one member’s audio is significantly worse than others, re-record it. |
| 7 | Using an external video instead of the audio podcast | The assignment instructions are explicit: “Do not use videos from external sources in your presentation.” This prohibition is not ambiguous. A YouTube embed or linked external video is a direct violation of the assignment format requirement. | Use PowerPoint’s Insert > Audio feature. Record directly into the file or insert a pre-recorded .mp3 or .wav file. Test playback in the PowerPoint file before submitting to make sure the audio plays when the file is opened. |
Pre-Submission Checklist — Uber Group Case Presentation
- Assigned question (Q3 as written in course instructions) is stated on slide 1 and answered in conclusions
- Background slide covers only content relevant to driver management and monitoring — not the whole case
- At least one IS framework applied specifically to case evidence — not just named
- Both beneficial and harmful evidence presented from the case before a conclusion is reached
- Conclusion slide states a clear verdict on beneficial vs. harmful with supporting reasons
- At least one external source cited in APA format — not the textbook alone
- References slide at the end with full APA entries for all cited sources
- Audio podcast embedded via PowerPoint Insert > Audio — plays on file open
- Multiple team member voices in the podcast narration
- No external videos embedded or linked
- Slide count between 6 and 10
- Slides posted to Canvas discussion board by the end of Week 2 deadline
- PowerPoint file attached and podcast embedded or attached as instructed
FAQs — Uber Case Group Presentation
What the Best Group Presentations on This Case Do That Average Ones Do Not
The presentations that score highest treat the Uber case as a real IS analysis problem, not a story to retell. They name specific mechanisms — blind acceptance rates, deactivation thresholds, psychological push notifications — and explain exactly why those mechanisms constitute managerial control in IS terms. They apply a framework with precision. They show evidence for both beneficial and harmful effects before making a reasoned verdict. And they have a conclusion that actually concludes something.
The podcast narration in strong presentations adds analytical depth that the slides alone cannot carry. When a narrator explains why the Netflix-style next-ride loading is significant — it exploits commitment bias to extend driver shifts past the driver’s stated intention to stop — that is the kind of insight that earns marks in the analysis criterion. Reading slide text aloud is not the same thing.
The source requirement is one external citation. That is genuinely minimal. Use something that actually strengthens your argument — a peer-reviewed IS paper, a credible industry analysis, or well-sourced journalism. Cite it in APA on the slide where you use it and in full on the references slide.
If you need support building the slide structure, writing the analytical narration, identifying the right IS framework, or locating your external source, the team at Smart Academic Writing works on IS course assignments, group presentation analysis, and APA-formatted academic work. You can visit our academic writing service, our research paper service, or our PowerPoint presentation writing service. You can also read about how we handled a different kind of IS-adjacent analysis on our INFO 310 medication administration workflows guide to see how we approach complex case-based assignments.