TMF2964 Software Economics – E3value Model Analysis

Pay & Go is a Malaysian technology company based in Sarawak that specializes in smart parking solutions and lifestyle convenience. Their platform is designed to replace traditional parking coupons with digital payments across various councils and shopping malls in Malaysia.

Core Services

• Smart Parking Management: Integrated with local councils (MBKS and DBKU) and major shopping malls in Kuching, allowing for seamless digital payment of parking fees.
• Auto Parking Collection (APC): Uses license plate recognition for automatic deduction from your Pay & Go wallet when entering and exiting participating car parks.
• Elderly Easy Payment (EEP): A dedicated service for seniors aged 60+ that automatically deducts parking charges from a registered wallet without requiring a smartphone at the time of parking.
• Lifestyle Convenience: Includes services such as EV charging, powerbank sharing, and digital ticketing for events.

Where to Use It

The service is widely available in Kuching at locations including:

• Shopping Malls: CityONE Megamall, The Spring, Vivacity Megamall, Plaza Merdeka, and Sarawak Plaza.
• Council Areas: Smart parking operations managed by MBKS and DBKU councils

In this project, you are required to adopt the e3value model to answer the following tasks,

• “Design an e3-value model for a Smart City Parking System(like Pay & Go). Show how the City Council, the App Developer, and the Citizen all benefit.”
• Provide the profitability analysis table and elaborate on it.
• To complete the e3-valueanalysis for a Smart City Parking System (like Pay & Go), students must test the “robustness” of the model.

Scenarios

Here are 5 scenarios you can provide to students. For each, they must explain how the diagram connections change and whether the Net Present Value (NPV) for each actor remains positive.

Scenario 1: The “Digital Divide” (Elderly Inclusion)

• The City Council mandates that the App Developer must support Elderly Easy Payment (EEP), where seniors park for free or at a 50% discount without using a smartphone.
• Who subsidizes the lost revenue—the App Developer (lower commission) or the City Council (lower collection)?

Scenario 2: The “Ghost Town” (Low Occupancy)

• A new mega-mall opens nearby with free parking, causing a 40% dropin on-street parking transactions in the Council zones.
• At what transaction volume does the App Developer’s NPV turn negative?

Scenario 3: The “Data Monetization” Pivot

• The App Developer decides to stop charging the City Council a commission. Instead, they sell Anonymized Traffic Data(Value Object) to local businesses for targeted advertising.
• Does this make the system more or less sustainable?

Scenario 4: The “Enforcement Failure” (Free-Riding)

• The LPR (License Plate Recognition) cameras have a 15% error ratedue to heavy rain or poor lighting, allowing many cars to park without the system triggering a payment.
• How does this “leak” affect the Reciprocitybetween the City Council and the App Developer? (i.e., will the Council continue the “License to Operate”?)

Scenario 5: The “Incentive” Strategy (Smart Refund)

• To reduce traffic congestion, the Council introduces a “Smart Refund”—if a Citizen leaves a parking spot 15 minutes early, they get a partial credit, and the spot is immediately flagged as “Available” in the app for the next user.
• Analyze the Value: Does having two people pay for the same spot in one hour increase the total net profit value of the network?

Submission

• E3value diagram
• Profitability analysis sheet
• Refined model and answers for the scenario
• Recorded presentation

Experts Answer on Above Questions on Software Economics

E2value model for a smart city parking system (Pay & Go)

Actors and value exchanges – the main actors or City Council(MBKS/DBKU), App developer (Pay & Go) and citizens. The City Council will provide parking space and operating licence and in return, it will get parking revenue and occupancy data. The app developer i.e. Pay & Go provides a mobile app, payment processing system and LPR technology, and in return it will get commission fees, and access to parking transaction data. The citizens would give a parking fee and their data and they will get convenient parking and cashless payment which will help in saving time.

Benefits to each actor

The City Council will benefit in terms of higher operational efficiency from reduced cost of printing parking coupons, better trophic management data and higher parking fee collection rates. The app developer would benefit in terms of earning commission on each transaction, and get access to valuable mobility data. The citizen could benefit in terms of a faster payment system, and lower overall risk of parking fines.

Profitability analysis

Scenario 1: Digital Divide (EEP)

As the City Council mandates the Elderly Easy Payment allowing seniors to park for free, it will benefit the senior citizen. The NPV impact will be a slight decline for City Council and increases significantly in respect to citizens.

Scenario 2: Ghost Town (40% Occupancy drop)

This will result in a decline in the number of parking transactions and it will ultimately cost the app developer in terms of lower commission revenue. The NPV impact will be negative on City Council, and the app developer NPV would turn negative below 50-60% normal transaction volume.

Scenario 3: Data Monetisation Pivot

It will result in a removal of commission flow and businesses would pay for anonymised traffic data. The impact on NPV will be positive for the City Council, and also for app developers if data demand is strong. For businesses also, the NPV will become positive through targeted marketing. This particular strategy is highly sustainable because the revenue is diversified, and it is not completely dependent on parking transactions only.

Scenario 4: Enforcement failure (15% LPR Error)

A 15% error rate would mean these vehicles would not make any payment and it will be considered as a revenue loss. The NPV impact on City Council is negative and the app developer would also face a reduced commission while some of the citizens would benefit unfairly. It will be important for the app developer to improve the camera accuracy in order to sustain the partnership.

Scenario 5 – The Incentive Strategy(Refund)

There would be partial refund available to the driver if they leave early, and this will make the parking spaces available to others on a frequent basis. This will increase the revenue even after giving partial refund because that will be more vehicles served during the same time period. The NPV impact will be positive for every actor, as City Council and app developers would get higher revenue from serving higher vehicles, whereas citizens would benefit in terms of getting incentives.

Refined model conclusion

The strongest business model would be the one that combines APC and LPR technology, EEP support funded by the City Council, smart refund incentives etc.

Want Detailed Answers with References?

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