Assessment Type: Individual
Weighting: 50%
Learning Outcomes Assessed: ULO 1, 2, and 3
Word Limit: 3,000 words (Written Report)
Time Limit: 10 minutes (Video Presentation)
Due Date: 13 February 2026 (Friday) 11:59 pm (AEST)
All submissions must be submitted with a signed Ozford Institute of Higher Education Cover Sheet via Moodle. Late submissions will attract a penalty of 5% of the assessment weighting for each calendar day late unless the lecturer grants an extension.
Autonomous delivery robots are emerging as a solution for last-mile logistics, particularly in dense urban environments where labour shortages, high delivery costs, and growing e-commerce volumes are putting pressure on traditional courier models. These robots can transport parcels, groceries or prepared meals over short distances using pedestrian pathways, bike lanes or roadside infrastructure. Several firms overseas have piloted such services, but adoption in Australia remains limited.
An entrepreneur is considering launching a fleet of autonomous delivery robots in major Australian cities (e.g., Melbourne, Sydney, Brisbane). The venture is promising, but economic considerations, regulatory conditions and macroeconomic uncertainties must be evaluated before investment.
As a management consultant, you are required to analyse the business opportunity using both microeconomic and macroeconomic theory derived from the unit. Your report must demonstrate the ability to apply economic reasoning to real-world strategic decisions and business problems.
In particular, ensure you address the following areas using the relevant lecture content:
Identify key resource constraints (capital, robotics hardware, skilled labour, data infrastructure, charging stations). Evaluate the opportunity costs faced by the entrepreneur (e.g., capital investment in delivery robots vs human courier employment; focus on B2B vs B2C customers). Illustrate how a simple Production Possibility Frontier (PPF) represents trade-offs between different deployment strategies or output mixes.
Analyse expected demand for autonomous delivery services. Identify demand determinants such as urban density, consumer preferences, delivery time sensitivity, e-commerce activity and logistics outsourcing. Discuss the price elasticity of demand and the cross-price elasticity of demand for substitutes such as bicycle couriers, motorbike couriers, or human gig-workers. Evaluate supply-side constraints such as robotics suppliers, battery availability, pathway access and labour for maintenance.
Determine the market structure the business will operate in (likely oligopoly or monopolistic competition) and evaluate competitive behaviour. Discuss barriers to entry (capital intensity, technology, network effects), product differentiation (delivery time, reliability, pricing, app experience), and competitive strategy.
Analyse the cost structure, including fixed costs (robot purchase, charging infrastructure, software platforms) and variable costs (maintenance, electricity, replacement parts, data connectivity). Apply concepts such as marginal cost, average cost, diminishing returns, and economies of scale to evaluate output decisions and pricing strategies. Consider minimum efficient scale and break-even volume.
Evaluate how national macroeconomic trends may affect the venture, including:
Discuss how:
Analyse the impact of:
Analyse applicable micro policies such as:
Evaluate positive externalities (lower emissions, reduced congestion, improved delivery speed) and negative externalities (sidewalk congestion, job displacement, safety risks). Consider how policy may internalise externalities through taxes, subsidies, permits or zoning.
Summarise key findings and provide a judgement about the viability of the venture. Offer strategic recommendations to address microeconomic, macroeconomic, and policy risks.
Use Harvard referencing. Include credible data sources (ABS, OECD, industry reports, government documents, academic articles, news, etc.)
You must present the key findings of your report in a recorded video presentation.
Time limit: 8–10 minutes
Slides required: 5 - 10 (PowerPoint format)
Submission: PPTX + Video File (MP4 or similar)
Recommended structure:
| Criteria | High Distinction (80–100%) | Distinction (70–79%) | Credit (60–69%) | Pass (50–59%) | Fail (0–49%) | Marks |
|---|---|---|---|---|---|---|
| 1. Application of Microeconomic Theory (Scarcity, Opportunity Cost, PPF, Demand, Supply, Elasticity, Market Structure) | Demonstrates deep mastery of micro concepts; applies theory with excellent reasoning; integrates diagrams/models effectively; insights highly relevant to the case. | Strong application of concepts with clear reasoning; minor gaps in diagram integration; good contextual linkage. | Adequate application; mostly descriptive; limited analytical depth; some unclear linkage. | Basic understanding shown; mostly descriptive; weak linkage to case context. | Major gaps; incorrect or missing theory; irrelevant or absent analysis. | /12 |
| 2. Production Costs & Output Decisions (Cost curves, economies of scale, marginal analysis, pricing) | Sophisticated, realistic cost analysis; critically evaluates economies of scale, cost curves & pricing; strong optimisation reasoning. | Clear cost analysis; some evidence/data; good pricing & output discussion. | Adequate discussion; limited depth; minimal numerical/diagram use. | Limited descriptive discussion; little marginal analysis; weak data. | No meaningful cost analysis; misunderstandings evident. | /8 |
| 3. Macro & Policy Analysis (GDP, inflation, unemployment, cycle, monetary & fiscal, trade/FX) | Insightful evaluation using relevant current data; excellent integration of macro variables & policy impacts; strong analytical judgement. | Strong evaluation with relevant data; good understanding of macro & policy channels. | Adequate discussion; limited integration of data; mostly descriptive. | Basic awareness; minimal data; little policy analysis. | Inaccurate or absent macroeconomic discussion. | /8 |
| 4. Externalities & Micro Policy (Regulation, safety, emissions, market failure) | Thorough & critical evaluation; integrates examples; explains internalisation mechanisms (tax/subsidy/regulation); may include behavioural insights. | Good evaluation; relevant examples; sound policy discussion. | Adequate explanation; limited depth; minimal evidence. | Basic awareness; mostly descriptive. | Incorrect or absent analysis. | /5 |
| 5. Structure, Data & Communication (Academic format, clarity, data use, Harvard referencing) | Excellent structure; coherent argument; strong integration of data & diagrams; flawless Harvard referencing. | Clear structure; strong writing; some data; mostly accurate referencing. | Adequate structure; some data; inconsistent referencing. | Limited structure; minimal data; weak or incomplete referencing. | Poor structure; no data; referencing missing/incorrect. | /5 |
| 6. Visual Aids (Slides) | Clear, simple, consistent, wellformatted visuals; summarise key ideas effectively; error-free. | Mostly clear & consistent visuals; minor formatting issues. | Summarises some key points; readable but somewhat cluttered. | Do not summarise all key points; cluttered/hard to read. | Poor visuals or lacking basic content. | /3 |
| 7. Delivery (Presentation) | Excellent delivery; confident, engaging, well-paced; no reading; smooth transitions; within time. | Very good delivery; minor lapses; confident; within time. | Good delivery; some reading/pacing issues; acceptable timing. | Reasonable delivery; heavy reading; lack of confidence; timing slightly off. | Poor delivery; unclear; unprepared; severe timing issues. | /9 |
| TOTAL | /50 |
Note: This report is provided as a sample for reference purposes only. For further guidance, detailed solutions, or personalized assignment support, please contact us directly.
Rapid growth in e-commerce, rising urban congestion, and persistent labour shortages have intensified pressure on last-mile logistics in Australia. Autonomous delivery robots (ADRs) represent an emerging technological solution capable of reducing delivery costs, improving speed, and lowering emissions in dense urban areas. While ADR services have been piloted successfully in the United States, Europe, and parts of Asia, large-scale adoption in Australia remains limited due to regulatory uncertainty, high capital requirements, and macroeconomic volatility.
This report evaluates the economic viability of launching an autonomous delivery robot venture in major Australian cities using microeconomic and macroeconomic theory. By applying concepts such as scarcity, demand and elasticity, cost structures, market competition, business cycles, and public policy, the report assesses whether the venture represents a sound strategic investment.
The entrepreneur faces several binding resource constraints:
Scarcity forces trade-offs in deployment scale and service focus.
Key opportunity costs include:
Choosing ADRs implies foregoing flexibility and lower upfront costs associated with human couriers.
A simplified PPF can illustrate trade-offs between:
The concave shape of the PPF reflects increasing opportunity costs as more resources are shifted toward ADR deployment due to rising complexity, regulatory hurdles, and infrastructure needs.
Demand for autonomous delivery services depends on:
Demand is expected to be stronger for short-distance, high-frequency deliveries.
Demand is likely to be price elastic in early adoption stages due to:
As reliability improves and network coverage expands, demand may become more inelastic.
Substitutes include:
Cross-price elasticity is positive; an increase in human courier wages (due to minimum wage or fuel costs) increases demand for ADRs.
These constraints may restrict short-run supply, shifting the supply curve leftward.
The ADR market is best described as oligopolistic or monopolistic competition.
A differentiation strategy focused on reliability, safety, and sustainability is preferable to price competition, particularly during early adoption.
Fixed Costs
Variable Costs
This supports a high-volume, low-marginal-cost pricing model.
Profit maximisation occurs where MR = MC.
Initially, penetration pricing may be optimal to build demand and scale, followed by price stabilisation once minimum efficient scale is achieved.
Strong GDP growth increases discretionary spending and e-commerce demand. A slowdown reduces delivery volumes, particularly for non-essential goods.
Higher unemployment lowers courier wages, reducing the cost advantage of automation. Conversely, labour shortages strengthen the case for ADR adoption.
Inflation raises costs of imported batteries, sensors, and chips, increasing fixed costs and delaying break-even.
ADR services are moderately pro-cyclical, with demand falling during recessions but remaining resilient for essential goods delivery.
Higher interest rates:
Lower rates encourage automation investment.
Government support may include:
These policies can significantly improve project viability.
Recognition and implementation lags mean firms must anticipate policy changes rather than react after conditions shift.
Robots, batteries, and chips are largely imported, exposing the firm to:
AUD depreciation increases capital costs. Hedging strategies or supplier diversification can mitigate risk.
Tariffs, export controls, or geopolitical tensions (e.g., chip restrictions) may raise costs or delay deployment.
Regulation may restrict scale but also legitimise the industry.
Positive Externalities
Negative Externalities
Governments may internalise externalities via:
Autonomous delivery robots represent a promising but capital-intensive venture in Australia. Economic viability depends on achieving scale, navigating regulation, and managing macroeconomic uncertainty.
With prudent economic planning, ADRs can become a sustainable component of Australia’s urban logistics ecosystem.
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