Proposal: Accounting Standard for Environmental Damage Costs

If I were contracted by the Accounting Standards Board, I would propose developing an accounting standard for environmental damage costs for the following reasons:

(i) Why develop the accounting standard?
The standard is appropriate because environmental damage can create significant financial obligations for companies, such as costs for pollution cleanup, rehabilitation, restoration, and legal penalties. A specific standard would improve consistency, transparency, and comparability in how companies recognize and report these costs.

(ii) One key issue to be covered
The key issue would be when environmental damage costs should be recognized as a liability. For example, a company may need to recognize a provision when it has caused environmental damage and has a present obligation to undertake restoration or pay related costs, even if the actual payment will occur several years later.

(iii) How the Conceptual Framework can help
The Conceptual Framework can help determine whether an environmental obligation meets the definition of a liability and whether the related information is relevant and faithfully represented. It provides principles for deciding recognition, measurement, and disclosure, helping ensure that environmental costs are reflected appropriately in financial statements.

Summary

• (i) Why develop the standard?

  • Environmental damage can create significant costs and financial obligations.

  • A standard would improve consistency, transparency, and comparability.

• (ii) Key issue to cover:

  • Determine when environmental damage costs should be recognized as a liability.

  • This may include cleanup, restoration, and rehabilitation costs.

• (iii) Role of the Conceptual Framework:

  • Helps determine whether an environmental obligation meets the definition of a liability.

  • Guides recognition, measurement, and disclosure of environmental costs.

Simple Summary

Requirement	Answer
(i) Why develop the standard?	To improve consistency and transparency in reporting environmental damage costs.
(ii) Key issue	When should environmental damage costs be recognized as a liability?
(iii) Conceptual Framework	Helps determine whether an obligation qualifies as a liability and how it should be recognized, measured, and disclosed.

Current Ratio and Company Liquidity

If I were the CEO of a company, I would use the current ratio to assess whether the company has enough short-term assets to meet its short-term financial obligations.

The formula is:

Current Ratio = Current Assets ÷ Current Liabilities

For example, if my company has:

• Current Assets = RM10 million

• Current Liabilities = RM5 million

Then:

Current Ratio = RM10 million ÷ RM5 million = 2.0

This means the company has RM2 of current assets for every RM1 of current liabilities.

How I would interpret it as CEO

A higher current ratio generally indicates stronger short-term liquidity because the company has more current assets available to pay its debts. However, an excessively high ratio may also indicate that assets such as cash or inventory are not being used efficiently.

A lower current ratio indicates greater liquidity pressure. If the ratio falls below 1.0, current liabilities are greater than current assets, which may make it more difficult for the company to meet its short-term obligations.

As CEO, I would therefore not look at the current ratio alone. I would also examine cash flow, inventory turnover, accounts receivable collection, and industry benchmarks to understand the company's actual liquidity position.

In summary: The current ratio helps me determine whether my company has sufficient short-term resources to meet its short-term obligations and provides an early warning of potential liquidity problems.

EVALUATION OF THE POTENTIAL OF LOW ALTITUDE ECONOMY IN THE PALM OIL INDUSTRY

1.0 Introduction

The palm oil industry is a geographically extensive and operationally complex industry involving plantation management, harvesting, transportation, milling, processing and supply-chain activities. In many producing regions, plantations and mills are located across large areas, including remote and difficult-to-access locations. Consequently, companies face operational challenges related to field inspection, crop monitoring, transportation, infrastructure inspection, worker safety and environmental management.

The emergence of the Low Altitude Economy (LAE) provides an opportunity to address some of these challenges through the use of drones, Unmanned Aerial Vehicles (UAVs), artificial intelligence (AI), advanced sensors and digital platforms.

For the palm oil industry, LAE should not be viewed only as a method of transporting goods by drone. Its greater potential lies in combining aerial mobility, remote sensing, automation and data analytics to improve operational decision-making.

The potential relationship can be expressed as:

UAVs + Sensors + AI + Digital Platforms → Better Information → Faster Decisions → Higher Productivity and Safety

2.0 Current Operational Challenges in the Palm Oil Industry

The palm oil industry has several operational characteristics that make it suitable for LAE applications.

2.1 Large geographical areas

Oil palm plantations can cover thousands of hectares. Traditionally, field inspections require workers and management personnel to travel physically through plantation roads.

This creates several challenges:

• significant travelling time;

• fuel consumption;

• vehicle maintenance;

• difficult access during wet weather;

• delays in identifying field problems; and

• significant manpower requirements.

Aerial monitoring can provide a different approach by allowing large areas to be surveyed relatively quickly.

2.2 Crop monitoring

Conventional crop monitoring depends heavily on field workers and periodic inspections.

Important information includes:

• planting density;

• palm health;

• nutrient deficiency;

• pest attacks;

• disease;

• water stress;

• drainage conditions; and

• harvesting readiness.

The limitation of conventional inspection is that observations may be sample-based rather than comprehensive.

UAVs equipped with cameras and multispectral or thermal sensors can potentially collect information across much larger areas.

2.3 Harvesting and crop estimation

Fresh Fruit Bunches (FFB) are the main economic output of an oil palm plantation.

Management needs reliable information regarding:

• crop maturity;

• expected production;

• harvesting intervals;

• field productivity; and

• crop forecasting.

LAE technologies can support aerial imaging and AI-based analysis to improve crop estimation.

This can contribute to better coordination between:

Plantation → Harvesting → Collection → Transport → Palm Oil Mill

3.0 Operational Challenges that LAE Can Solve

3.1 Plantation inspection

One of the clearest applications of LAE is aerial plantation inspection.

Traditional approach

Field worker → Plantation road → Physical inspection → Report → Management decision

LAE approach

UAV → Aerial image → AI/data analysis → Digital report → Management decision

The LAE approach can reduce the time required to obtain information about large plantation areas.

Instead of relying entirely on physical inspection, management can use aerial information to identify areas requiring further investigation.

3.2 Early identification of pest and disease problems

Pest and disease detection is important because delayed intervention can result in production losses.

UAVs equipped with appropriate sensors can potentially identify abnormal vegetation patterns.

For example:

Sensor → Image → AI analysis → Abnormal area detected → Ground verification → Treatment

This creates a targeted intervention model.

Instead of treating an entire plantation uniformly, management can potentially focus resources on identified problem areas.

This supports the concept of precision agriculture.

3.3 Fertiliser optimisation

Fertiliser represents a significant operating cost in plantation management.

Aerial data can potentially identify differences in vegetation condition across plantation blocks.

The information can then support:

• targeted fertiliser application;

• identification of nutrient-deficient areas;

• monitoring of fertiliser effectiveness; and

• reduction of unnecessary application.

This creates an opportunity to move from:

Uniform application

towards:

Data-driven application.

The economic benefit would potentially come from improved input efficiency rather than simply reducing the quantity of fertiliser used.

3.4 Drainage and water management

Water management is particularly important in oil palm plantations.

Excessive water can cause:

• waterlogging;

• poor root conditions;

• reduced accessibility;

• soil deterioration; and

• harvesting difficulties.

UAVs can provide aerial information about:

• drainage networks;

• standing water;

• erosion;

• blocked drains; and

• changes in plantation conditions.

This allows maintenance teams to prioritise areas requiring intervention.

3.5 Plantation road inspection

Plantation roads are essential because they connect harvesting areas to collection points and mills.

Poor road conditions can affect:

• harvesting operations;

• FFB evacuation;

• vehicle productivity;

• fuel consumption; and

• delivery time.

UAVs can potentially identify:

• damaged roads;

• erosion;

• flooded sections;

• bridge problems; and

• inaccessible areas.

This can support predictive and prioritised road maintenance.

4.0 LAE Applications in Palm Oil Milling

LAE is not limited to plantations. It can also support palm oil mill operations.

4.1 Mill infrastructure inspection

UAVs can potentially inspect difficult-to-access infrastructure such as:

• mill roofs;

• chimneys;

• stacks;

• storage tanks;

• pipelines;

• transmission lines;

• cooling systems; and

• other elevated structures.

This can reduce the need for workers to physically access certain hazardous locations.

The potential safety improvement is particularly important in an industrial environment where working at height may involve significant risk.

4.2 Thermal inspection

Thermal cameras mounted on UAVs can potentially identify abnormal heat patterns.

Applications may include:

• electrical equipment;

• motors;

• transformers;

• boilers;

• steam systems;

• bearings; and

• other industrial equipment.

The principle is:

Thermal image → Abnormal temperature → Further inspection → Corrective maintenance

This supports condition-based and predictive maintenance.

4.3 Stockpile and inventory measurement

UAVs can potentially be used to estimate the volume of:

• biomass;

• empty fruit bunches;

• fibre;

• shell;

• compost;

• palm kernel;

• other materials.

Three-dimensional aerial mapping can provide estimates of stockpile volume without requiring workers to physically measure the entire pile.

This can improve:

• inventory management;

• production planning;

• material utilisation; and

• financial reporting.

5.0 LAE for Worker Safety

Worker safety represents another important area where LAE can create value.

Palm oil operations can involve:

• working at height;

• remote field locations;

• heavy equipment;

• confined areas;

• difficult terrain;

• electrical infrastructure; and

• industrial machinery.

UAVs can perform certain inspection activities before workers enter an area.

For example:

UAV inspection → Identify hazard → Risk assessment → Controlled human intervention

This follows an important safety principle:

Use technology to reduce unnecessary human exposure to hazardous environments.

Therefore, the economic value of LAE is not limited to productivity. It can also arise through risk reduction and improved occupational safety.

6.0 LAE for Environmental Management

Environmental management is increasingly important in the palm oil industry.

UAVs can support monitoring of:

• rivers;

• drainage systems;

• plantation boundaries;

• erosion;

• water bodies;

• conservation areas;

• illegal land clearing; and

• environmental incidents.

For example, aerial monitoring can provide evidence of changes in drainage or river conditions.

This can support faster investigation and corrective action.

The combination of:

UAV + GPS + imagery + GIS + AI

can create a digital environmental monitoring system.

7.0 New Business Opportunities Created by LAE

The greatest long-term potential of LAE is not only solving existing problems but also creating new business opportunities.

7.1 Drone-as-a-Service

Palm oil companies do not necessarily need to own large fleets of UAVs.

Specialised companies could provide:

Drone-as-a-Service (DaaS)

The plantation company pays for services such as:

• aerial mapping;

• crop monitoring;

• inspection;

• thermal imaging;

• surveying; and

• data analysis.

This changes the business model from asset ownership to service utilisation.

7.2 Precision Agriculture Services

Specialised LAE companies could provide integrated services:

UAV → Data → AI → Crop Diagnosis → Recommendation

This could become a new agricultural technology service industry.

The company would not simply sell drones. It would sell agricultural intelligence.

7.3 Predictive Maintenance Services

UAV companies could provide industrial inspection services to palm oil mills.

For example:

Drone inspection → Image analysis → Defect identification → Maintenance recommendation

This creates a new market for predictive maintenance and industrial analytics.

7.4 FFB Transportation Opportunities

In the longer term, UAVs or other low-altitude autonomous vehicles could potentially support transportation of selected materials.

However, the economic feasibility depends on:

• payload;

• distance;

• battery capacity;

• operating cost;

• terrain;

• regulations; and

• comparison with conventional trucks.

Therefore, drone-based FFB transportation should currently be considered a potential niche application rather than a direct replacement for conventional FFB transport.

8.0 Integration with Artificial Intelligence

The most significant opportunity may arise when LAE is combined with AI.

A UAV by itself provides limited economic value.

The greater value comes from:

UAV → Data → AI → Information → Decision → Action

For example:

1. UAV collects images of a plantation.

2. AI identifies abnormal palm conditions.

3. GIS identifies the exact location.

4. Management receives an automated report.

5. Field workers verify the problem.

6. Targeted intervention is performed.

7. Results are monitored using subsequent UAV flights.

This creates a closed-loop digital agriculture system.

9.0 Economic Impact on the Palm Oil Industry

The potential economic effects can be grouped into five areas.

Area	Potential LAE Contribution
Productivity	Faster monitoring and better resource allocation
Cost	Reduced inspection time and potentially lower operating costs
Safety	Reduced human exposure to hazardous locations
Sustainability	More targeted use of fertiliser, chemicals and resources
Decision-making	Faster and more accurate operational information

The impact should therefore be evaluated using measurable Key Performance Indicators (KPIs), such as:

• inspection time per hectare;

• cost per hectare;

• labour hours;

• fuel consumption;

• fertiliser utilisation;

• crop-loss percentage;

• road maintenance response time;

• equipment downtime;

• safety exposure hours; and

• maintenance cost.

This provides a stronger basis for a business case than simply stating that drones are technologically advanced.

10.0 Challenges to LAE Adoption in the Palm Oil Industry

Despite its potential, several challenges need to be addressed.

10.1 Initial investment

Investment may be required for:

• UAVs;

• sensors;

• software;

• AI platforms;

• communication systems;

• trained personnel; and

• maintenance.

10.2 Regulatory requirements

Drone operations are subject to aviation regulations, particularly for more complex or Beyond Visual Line of Sight (BVLOS) operations.

Companies therefore need appropriate approvals, operating procedures and trained personnel.

10.3 Data management

Large plantations can generate enormous quantities of aerial imagery.

Companies need systems for:

• data storage;

• processing;

• cybersecurity;

• GIS integration;

• AI analysis; and

• data governance.

10.4 Weather

Tropical weather can affect UAV operations.

Heavy:

• rain;

• wind;

• thunderstorms; and

• poor visibility

can reduce operational reliability.

10.5 Skills

Successful implementation requires employees who understand both:

Palm oil operations + digital technology.

The future plantation workforce may therefore require greater knowledge of:

• GIS;

• UAV operations;

• AI;

• data analytics; and

• digital agriculture.

11.0 Strategic Evaluation

The potential of LAE in the palm oil industry can be evaluated using three levels.

Level 1 – Immediate opportunity

Applications that are already relatively practical include:

• plantation mapping;

• crop monitoring;

• infrastructure inspection;

• road inspection;

• environmental monitoring;

• stockpile measurement.

Level 2 – Emerging opportunity

More advanced applications include:

• AI-based disease detection;

• precision agriculture;

• predictive maintenance;

• autonomous inspection;

• integrated plantation digital twins.

Level 3 – Long-term opportunity

Potential future applications include:

• autonomous cargo transportation;

• advanced eVTOL logistics;

• autonomous plantation operations;

• aerial passenger mobility;

• highly automated agricultural ecosystems.

The timing of these applications will depend on technological maturity, economics, regulation and operational reliability.

12.0 Proposed LAE Framework for the Palm Oil Industry

A suitable conceptual framework for the industry is:

LOW-ALTITUDE TECHNOLOGIES

Drones + UAVs + Sensors + AI + eVTOL

↓

DATA GENERATION

Aerial Images + Thermal Data + GIS + 3D Mapping

↓

DATA ANALYTICS

AI + Machine Learning + Predictive Analytics

↓

OPERATIONAL APPLICATIONS

Crop Monitoring + Infrastructure Inspection + Environmental Monitoring + Maintenance + Logistics

↓

BUSINESS OUTCOMES

Productivity + Cost Efficiency + Safety + Sustainability + Faster Decision-Making

↓

ECONOMIC TRANSFORMATION

Smart and Data-Driven Palm Oil Industry

13.0 Conclusion

The Low Altitude Economy has significant potential to transform the palm oil industry because of the industry's extensive geographical coverage, dependence on field inspection, transportation requirements and need for effective environmental and safety management.

The most immediate value of LAE is likely to come from data collection, monitoring and inspection rather than replacing conventional transportation. UAVs can provide rapid aerial information about plantations, roads, drainage systems, infrastructure and environmental conditions. When combined with AI, this information can support precision agriculture, predictive maintenance and faster operational decision-making.

LAE can also create new business opportunities through Drone-as-a-Service, precision agriculture services, industrial inspection, predictive maintenance and data analytics. In the longer term, autonomous cargo and eVTOL applications may create additional possibilities, although their commercial viability will depend on technology, regulation and operating economics.

Therefore, the potential of LAE in the palm oil industry can be summarised as:

LAE can transform the palm oil industry from a predominantly labour-intensive and ground-based operating model toward a more data-driven, automated and digitally integrated industry.

The most important economic opportunity is not simply “using drones”, but using low-altitude technologies to convert aerial data into better operational decisions, improved productivity, safer work practices and new business models.

LOW ALTITUDE ECONOMY (LAE): ECONOMIC TRANSFORMATION AND ENABLING TECHNOLOGIES

1.0 Introduction

The rapid development of digitalisation, artificial intelligence (AI), autonomous systems, advanced batteries and unmanned aircraft has created new opportunities for economic activities in low-altitude airspace. One emerging concept associated with this development is the Low Altitude Economy (LAE). LAE refers broadly to an economic ecosystem in which low-altitude airspace is utilised for commercial, industrial and public-service activities through technologies such as drones, Unmanned Aerial Vehicles (UAVs) and electric Vertical Take-Off and Landing (eVTOL) aircraft.

Although the exact altitude boundary differs between jurisdictions and applications, the concept generally concerns aviation activities conducted relatively close to the Earth's surface. The IEEE describes LAE in the context of economic activities and services conducted below approximately 1,000 metres above ground level, while some national frameworks use a broader altitude range. Therefore, LAE should be understood primarily as an emerging economic ecosystem rather than as an aviation sector defined by one universally accepted altitude limit.

The importance of LAE extends beyond the use of drones. It represents a potential transformation of transportation, logistics, agriculture, infrastructure management, emergency services and urban mobility. By integrating aviation technologies with artificial intelligence, telecommunications, digital platforms and energy systems, LAE can create new business models and industrial value chains.

This report defines the Low Altitude Economy, examines its relevance to economic transformation, compares LAE with traditional aviation and logistics, and discusses the major technologies driving its development.

2.0 Definition of Low Altitude Economy

The Low Altitude Economy can be defined as:

An emerging economic ecosystem in which low-altitude airspace is utilised by manned and unmanned aerial systems, supported by digital infrastructure, aviation services, energy systems, data technologies and regulatory frameworks to deliver transportation, logistics and other commercial and public services.

The definition contains several important elements.

2.1 Low-altitude airspace

The first element is the utilisation of low-altitude airspace as an economic resource. Historically, economic activities have been concentrated primarily on land and maritime environments, while aviation has mainly been associated with higher-altitude passenger and cargo transportation.

LAE introduces a new economic dimension by allowing low-altitude airspace to become an operational environment for:

• drone delivery;

• agricultural activities;

• infrastructure inspection;

• aerial surveying;

• emergency response;

• passenger mobility;

• tourism; and

• other specialised services.

Therefore, LAE can be viewed as the development of a three-dimensional economic space.

2.2 Aircraft and aerial platforms

LAE involves a range of aerial technologies, including:

• drones;

• UAVs;

• remotely piloted aircraft systems;

• autonomous aerial vehicles;

• cargo drones;

• agricultural drones; and

• eVTOL aircraft.

These technologies differ in size, payload, range, level of autonomy and intended application.

2.3 Digital and physical infrastructure

The development of LAE requires more than aircraft. It also requires supporting infrastructure such as:

• vertiports;

• drone landing and take-off stations;

• charging facilities;

• communication networks;

• navigation systems;

• unmanned traffic-management systems;

• maintenance facilities; and

• digital platforms.

Consequently, LAE should be considered an ecosystem rather than simply an aircraft industry.

3.0 Relevance of LAE to Economic Transformation

LAE is relevant to economic transformation because it introduces a new transportation and service layer into the economy. Traditional economic activities have generally relied on roads, railways, ports and conventional airports. LAE adds low-altitude airspace as another means of moving people, goods, information and services.

3.1 From two-dimensional to three-dimensional economic activity

Traditional transportation largely operates across geographical surfaces. For example, goods may move from a factory to a warehouse and subsequently to a customer through roads.

A drone-based system can potentially establish a more direct connection:

Distribution Centre → UAV → Customer

The ability to operate above physical transportation networks can reduce dependence on roads for selected applications.

However, LAE should not necessarily be viewed as a replacement for traditional transportation. Instead, it can complement existing transportation systems by providing an additional layer for specific applications.

3.2 Improvement in transportation efficiency

One potential economic benefit of LAE is reduced transportation time.

Ground transportation is affected by:

• traffic congestion;

• road conditions;

• geographical obstacles;

• road-network capacity; and

• driver availability.

Aerial transportation can potentially provide more direct routes between locations. This is particularly valuable for time-sensitive products and services such as:

• medical supplies;

• emergency equipment;

• spare parts;

• high-value goods;

• food delivery; and

• urgent documents.

Therefore, LAE may improve supply-chain responsiveness and reduce delivery latency.

3.3 Increased productivity

LAE can contribute to productivity by automating repetitive and labour-intensive activities.

For example, conventional agricultural inspection may require workers to physically inspect large areas. A UAV can cover the same area using aerial imaging and sensors.

The process can become:

UAV → Data Collection → AI Analysis → Problem Identification → Management Decision

This transforms the role of the aircraft from merely a transportation device into a mobile data-collection and decision-support platform.

3.4 Development of new industries

LAE can stimulate several supporting industries.

The emerging value chain may include:

Battery Manufacturing → Sensors → UAV Manufacturing → Software → AI → Communication Networks → Airspace Management → Charging Infrastructure → Operations → Data Analytics

Therefore, the economic impact of LAE extends beyond aircraft manufacturers.

It can create demand for:

• aerospace engineers;

• software developers;

• AI specialists;

• drone operators;

• maintenance technicians;

• battery engineers;

• data analysts;

• airspace-management professionals; and

• infrastructure developers.

4.0 Differences Between LAE and Traditional Aviation

Traditional aviation is primarily associated with the transportation of passengers and cargo using conventional aircraft between established airports.

LAE has a substantially broader operating model.

Dimension	Traditional Aviation	Low Altitude Economy
Main aircraft	Commercial aircraft and helicopters	Drones, UAVs and eVTOLs
Main activities	Passenger and cargo transportation	Logistics, inspection, agriculture, mobility, emergency services and other applications
Infrastructure	Airports, runways and terminals	Vertiports, drone stations and charging infrastructure
Operation	Predominantly human-piloted	Increasingly automated or autonomous
Network	Airport-to-airport	Potentially point-to-point and distributed
Technology	Conventional aviation systems	AI, sensors, autonomous systems and digital platforms
Business model	Airlines and airport services	Aviation, technology and service-platform ecosystems
Operating environment	Established aviation routes and airports	Low-altitude airspace and distributed operational locations

The key distinction is that LAE is not simply small-scale aviation. It represents the convergence of aviation with robotics, AI, telecommunications, logistics, energy and digital services.

5.0 Differences Between LAE and Traditional Logistics

Traditional logistics relies heavily on road, rail, maritime and conventional air transportation.

A typical logistics chain may be represented as:

Supplier → Truck → Warehouse → Distribution Centre → Truck → Customer

LAE introduces an additional transportation model:

Distribution Centre → Drone → Customer

Traditional logistics is primarily constrained by:

• road capacity;

• congestion;

• distance;

• fuel;

• driver availability; and

• physical infrastructure.

LAE introduces different constraints, including:

• battery capacity;

• payload;

• weather conditions;

• communication reliability;

• airspace availability;

• navigation;

• cybersecurity; and

• aviation regulations.

Therefore, LAE does not eliminate transportation constraints. Instead, it changes the nature of those constraints.

6.0 Key Technologies Driving LAE Growth

Several technologies are responsible for the development of the Low Altitude Economy.

6.1 Drones

Drones are currently among the most widely recognised technologies associated with LAE.

They can be used for:

• parcel delivery;

• food delivery;

• agricultural spraying;

• aerial photography;

• surveying;

• mapping;

• environmental monitoring;

• infrastructure inspection; and

• emergency response.

Their economic value is particularly significant when they can perform tasks faster, more safely or more efficiently than conventional methods.

6.2 Unmanned Aerial Vehicles (UAVs)

UAVs are aircraft that can operate without a human pilot physically located inside the aircraft.

Modern UAVs can incorporate:

• cameras;

• LiDAR;

• radar;

• GPS/GNSS;

• thermal sensors;

• AI-based image recognition; and

• autonomous navigation.

For example, UAVs can inspect power lines, pipelines, bridges and industrial facilities without requiring workers to physically access potentially hazardous locations.

The economic value therefore comes from both physical flight capability and data generation.

6.3 Electric Vertical Take-Off and Landing (eVTOL)

eVTOL aircraft represent another important technology in LAE.

An eVTOL aircraft uses electric propulsion and can take off and land vertically. This provides an operational advantage in locations where conventional runways are unavailable or impractical.

Potential applications include:

• urban air taxis;

• regional transportation;

• medical transportation;

• cargo transportation;

• emergency services; and

• tourism.

eVTOL technology is particularly relevant to the development of Advanced Air Mobility (AAM).

6.4 Artificial Intelligence

AI is an important enabling technology because future LAE operations are expected to become increasingly automated.

AI can support:

• autonomous navigation;

• obstacle detection;

• route optimisation;

• image analysis;

• predictive maintenance;

• traffic management;

• demand forecasting; and

• agricultural monitoring.

For example:

Drone + Camera + AI

can transform thousands of aerial images into information about crop health, infrastructure defects or environmental conditions.

Consequently, the economic value of LAE increasingly comes from the combination of:

Aircraft + Data + Artificial Intelligence

6.5 Communication Networks

Reliable communication is essential for large-scale UAV operations.

Aircraft may need to communicate with:

• ground-control stations;

• other aircraft;

• airspace-management systems;

• satellites;

• customers; and

• digital platforms.

Technologies such as 5G, 5G-Advanced and future 6G networks may support high-density aerial operations through low-latency communication and high-speed data transmission.

6.6 Unmanned Traffic Management

As the number of UAVs increases, managing aircraft within low-altitude airspace becomes increasingly important.

Unmanned Traffic Management (UTM) systems can support:

• flight planning;

• aircraft identification;

• route management;

• geofencing;

• conflict detection;

• airspace coordination; and

• communication between operators and aviation authorities.

UTM therefore provides an important foundation for the safe scaling of LAE.

6.7 Battery and Energy Technology

Battery technology is a major factor affecting electric UAV and eVTOL performance.

Important areas include:

• battery energy density;

• battery-management systems;

• charging speed;

• battery life;

• thermal management; and

• charging infrastructure.

Improved energy technology can increase:

• flight range;

• payload capacity;

• operational efficiency; and

• aircraft utilisation.

Therefore, LAE is also connected to the wider energy transition and electrification of transportation.

6.8 Sensors and Navigation Systems

Advanced sensors enable UAVs to operate safely and collect high-quality information.

These include:

• GPS/GNSS;

• cameras;

• LiDAR;

• radar;

• inertial measurement units;

• ultrasonic sensors; and

• thermal imaging systems.

The combination of sensors, AI and UAVs can produce accurate three-dimensional maps and support applications such as construction, mining, agriculture and infrastructure management.

7.0 Major Applications of LAE

7.1 Logistics and Delivery

Potential applications include:

• parcel delivery;

• food delivery;

• medical supplies;

• emergency equipment; and

• industrial spare parts.

7.2 Agriculture

UAVs can support:

• crop monitoring;

• fertiliser application;

• pesticide spraying;

• plantation mapping;

• pest detection; and

• crop-health analysis.

7.3 Infrastructure Inspection

UAVs can inspect:

• bridges;

• power transmission lines;

• pipelines;

• telecommunications towers;

• buildings; and

• industrial facilities.

This can reduce the need for workers to enter difficult or hazardous environments.

7.4 Emergency and Disaster Management

LAE technologies can support:

• search and rescue;

• disaster assessment;

• emergency supply delivery;

• firefighting support; and

• communication restoration.

7.5 Urban Mobility

eVTOL aircraft could potentially provide short-distance passenger transportation between:

• airports;

• business districts;

• urban centres; and

• regional destinations.

8.0 LAE as an Emerging Economic Ecosystem

A major characteristic of LAE is its cross-sector nature.

The ecosystem can be represented as follows:

Technology Providers

↓

UAV/eVTOL Manufacturers

↓

Digital and AI Platforms

↓

Communication Infrastructure

↓

Airspace Management

↓

Vertiports and Charging Infrastructure

↓

Operators

↓

Logistics and Mobility Services

↓

Consumers and Businesses

This demonstrates that LAE is not an isolated aviation industry. It integrates multiple sectors into one economic ecosystem.

9.0 Economic Benefits of LAE

The potential economic benefits include:

9.1 Lower transportation time

Direct aerial routes can reduce travel time for selected applications.

9.2 Improved productivity

Automation can reduce time spent on repetitive inspections and monitoring.

9.3 New business opportunities

Companies can develop new services such as:

• Drone-as-a-Service;

• Inspection-as-a-Service;

• Agriculture-as-a-Service;

• Delivery-as-a-Service; and

• Mobility-as-a-Service.

9.4 Regional connectivity

LAE may improve connectivity for remote communities where conventional infrastructure is expensive or difficult to develop.

9.5 New employment opportunities

New occupations may emerge in:

• UAV operations;

• software engineering;

• AI;

• maintenance;

• battery technology;

• airspace management; and

• data analytics.

10.0 Challenges and Limitations

Despite its potential, LAE faces several challenges.

10.1 Safety

Large-scale autonomous aircraft operations require robust safety systems to prevent:

• collisions;

• system failures;

• loss of communication;

• navigation errors; and

• uncontrolled aircraft.

The challenge becomes more complex when thousands of aircraft operate simultaneously.

10.2 Regulation

Governments must establish rules covering:

• aircraft certification;

• operator licensing;

• autonomous operations;

• Beyond Visual Line of Sight (BVLOS) operations;

• airspace management;

• insurance;

• liability;

• cybersecurity; and

• privacy.

10.3 Infrastructure

Large-scale LAE requires investment in:

• vertiports;

• charging stations;

• communication networks;

• UTM systems;

• maintenance facilities; and

• digital infrastructure.

10.4 Public Acceptance

Public concerns may include:

• noise;

• privacy;

• safety;

• visual impact;

• surveillance; and

• cybersecurity.

Therefore, technological feasibility alone is insufficient. Successful LAE development also requires social acceptance and appropriate governance.

11.0 Conceptual Framework

The relationship between technology and economic transformation can be summarised as follows:

Enabling Technologies

Drones + UAVs + eVTOL + AI + 5G/6G + Sensors + Batteries

↓

Supporting Infrastructure

Vertiports + Charging Systems + Digital Networks + UTM

↓

Economic Applications

Logistics + Agriculture + Inspection + Emergency Services + Tourism + Urban Mobility

↓

Economic Outcomes

Higher Productivity + Faster Transportation + New Services + New Markets + Employment + Regional Connectivity

↓

Economic Transformation

Integration of Aviation, Digital Technology, Logistics, Energy and Services into a Three-Dimensional Economic Ecosystem

This framework demonstrates that technology is the enabler, while economic transformation represents the broader outcome.

12.0 Discussion

The development of LAE demonstrates how technological innovation can create new economic spaces and business models. Traditional aviation has historically focused on transporting passengers and cargo between airports, while traditional logistics has concentrated on moving goods through established transportation networks.

LAE introduces a different paradigm by integrating low-altitude airspace into everyday economic activities.

Its significance is therefore not limited to the drone industry. Instead, LAE represents the convergence of:

Aviation + Robotics + Artificial Intelligence + Telecommunications + Logistics + Energy + Data

This convergence can generate new sources of productivity and economic value.

However, the economic transformation associated with LAE should not be viewed as automatic. The benefits depend on technological maturity, infrastructure investment, regulatory development, public acceptance, safety management and the development of viable business models.

Consequently, the future development of LAE will require cooperation among governments, aviation authorities, technology companies, logistics providers, infrastructure developers, researchers and consumers.

13.0 Conclusion

The Low Altitude Economy is an emerging economic ecosystem that uses low-altitude airspace for transportation, logistics, agriculture, infrastructure management, emergency response, tourism and other commercial and public services.

Unlike traditional aviation, LAE relies increasingly on smaller, automated and digitally connected aircraft operating in distributed environments. Unlike conventional logistics, it can utilise three-dimensional airspace to provide direct transportation routes and services.

The major technologies driving LAE include drones, UAVs, eVTOL aircraft, artificial intelligence, advanced communication networks, unmanned traffic management, batteries and advanced sensors.

The economic significance of LAE is therefore broader than the development of new aircraft. It has the potential to create new industries, business models, employment opportunities and infrastructure while improving transportation efficiency and regional connectivity.

Ultimately, LAE can be understood as a transition towards a three-dimensional digital economy, where low-altitude airspace becomes another productive economic layer alongside land, sea and conventional aviation.

The central relationship can therefore be expressed as:

Low-Altitude Airspace + Advanced Technology + Digital Infrastructure + New Business Models = Low Altitude Economy and Economic Transformation

References

Federal Aviation Administration (FAA). (2025). Advanced Air Mobility. U.S. Department of Transportation.

International Civil Aviation Organization (ICAO). (2025). Unmanned Aviation. ICAO.

IEEE Standards Association. (2025). IEEE 3776: Standard for Low-Altitude Economy Terminology. IEEE.

[Academic literature on Low Altitude Economy and eVTOL development should be added according to the citation style required by the university, such as APA 7th edition.]

AN INSIGHT FROM ASSOC. PROF. DR. IDA YASIN LOW ALTITUDE ECONOMY (LAE)

Malaysia’s LAE Framework

Malaysia is expected to unveil its blueprint for the Low-Altitude Economy (LAE) by the end of the year, providing a clear framework to regulate and support the emerging sector. The Civil Aviation Authority of Malaysia (CAAM) is drawing up the blueprint, and the Malaysian government hopes to launch it later this year.

It will provide a clear roadmap for the LAE and marks the beginning of a national agenda to explore opportunities in low-altitude aviation technologies, including unmanned aircraft systems (UAS), advanced air mobility (AAM), and air logistics.

What is the Low-Altitude Economy?

The LAE typically refers to economic activities that use low-level airspace, typically below 1,000 metres, which is much lower than the altitude at which commercial aircraft operate, at around 9,000 to 13,000 metres.

So instead of cars, trucks, and motorcycles moving goods on the ground, the LAE imagines part of that movement taking place through the air.

This includes:

• Delivery drones

• Drones used for agriculture

• Security and infrastructure inspection

• Mapping and surveying

• Emergency and medical services

• Piloted aircraft known as Electric Vertical Take-Off and Landing (eVTOL) aircraft, or “flying taxis”

Thus, the LAE is expected to improve productivity, strengthen service delivery, open up new economic opportunities, and benefit the people.

“This new layer of economic activity sits above roads and buildings but below conventional commercial airplane routes.”

Why Malaysia is Well Positioned for LAE

Several factors make Malaysia well-positioned to embrace the LAE.

First, its strategic location at the heart of ASEAN means Malaysia can serve as a testing ground and distribution hub for drone-based logistics across Southeast Asia.

Second, with the rollout of 5G nationwide, Malaysia's strong digital infrastructure enables drones to operate with real-time connectivity, supporting safe navigation and efficient data transfer.

Third, a growing technology ecosystem means universities, startups, and multinational firms in Malaysia are increasingly investing in robotics, AI, and aerospace technologies.

Global Development and Workforce Requirements

Globally, countries like China and South Korea have already invested heavily in LAE ecosystems.

Malaysia's entry into this space signals its ambition to become a regional hub for drone innovation and aerial logistics.

The LAE will generate demand for:

• Drone pilots

• AI engineers

• Aerospace technicians

• Regulatory experts

Therefore, universities play a critical role in training the next generation of talent.

Profile: Assoc. Prof. Dr. Ida Md Yasin

Assoc. Prof. Dr. Ida Md Yasin

• PhD: UKM

• Master of Economics: UKM

• Bachelor of Economics: IIUM

Assoc. Professor Dr. Ida is a Senior Lecturer at Putra Business School and currently serves as the Manager of Society Engagement, Alumni, and Endowment.

She also holds the roles of:

• Programme Coordinator for International Business

• Advisor to the Putra Student and Alumni Association (PSAA)

Main Message of the Article

The article essentially highlights three interconnected developments:

1. LAE as a new economic layer
Economic activity is increasingly moving from roads and conventional aviation into low-altitude airspace.

2. Malaysia's opportunity
Malaysia's ASEAN location, nationwide 5G infrastructure, universities, technology companies, and growing investment in AI, robotics and aerospace create conditions for developing an LAE ecosystem.

3. The urgent need for workforce upskilling
The emergence of LAE will create new occupations and skills requirements, particularly in AI, drones, aerospace, digital connectivity and regulation. Universities and educational institutions therefore have an important role in preparing the workforce.

Business Economics by N. Gregory Mankiw and Mark P. Taylor

The book applies basic economic theory to real business decisions. It is especially useful for understanding how managers make decisions about prices, production, costs, markets, investment, competition, and government policy.

Below is a detailed but practical explanation, with examples related to your facilities/palm-oil processing environment.

1. The central idea of business economics

At its heart, economics asks:

How do people and organisations make choices when resources are limited?

For a business, resources are always limited:

• Money / CAPEX

• Labour

• Machinery capacity

• Energy

• Raw materials

• Land

• Time

• Management attention

Therefore, every decision has an opportunity cost.

Example: Palm-oil processing plant

Suppose you have RM10 million available for CAPEX.

You could use it for:

1. Boiler efficiency improvement

2. New production equipment

3. Wastewater treatment

4. Solar PV

5. Maintenance backlog

If you choose the boiler project, the opportunity cost is the benefit you could have obtained from the best alternative project.

This is one of the most important ideas in economics:

The real cost of something is what you give up to get it.

2. The Ten Principles of Economics

Mankiw is particularly well known for organising economics around 10 principles.

They can be divided into three groups.

A. How people make decisions

Principle 1 — People face trade-offs

You cannot have unlimited resources.

For example:

Higher production may require:

• more overtime

• more electricity

• more steam

• more maintenance

• more labour

So increasing production has benefits but also costs.

Principle 2 — The cost of something is what you give up to get it

This is opportunity cost.

Suppose a factory can use a machine for either:

• Product A → RM500,000 contribution

• Product B → RM350,000 contribution

If you choose Product B, the opportunity cost is the contribution from Product A that you sacrificed.

Principle 3 — Rational people think at the margin

This is extremely important for managers.

Instead of asking:

"Should we operate the machine?"

Ask:

"Should we operate the machine for one additional hour?"

This is marginal analysis.

For example:

Additional production:

+100 tonnes

Additional revenue:

RM80,000

Additional cost:

RM55,000

Therefore:

Marginal benefit = RM80,000

Marginal cost = RM55,000

Since:

MB > MC

the additional production is economically attractive, assuming no other constraints.

The basic decision rule is:

Do something when marginal benefit exceeds marginal cost.

Principle 4 — People respond to incentives

People change behaviour when costs and benefits change.

For example:

If an organisation introduces an energy-saving incentive:

Department achieving 10% electricity reduction receives recognition/bonus.

Managers and operators have an incentive to:

• reduce unnecessary running hours

• eliminate leaks

• optimise motors

• reduce idle equipment

• improve steam efficiency

This is why economics is closely connected with management.

3. How people interact

Principle 5 — Trade can make everyone better off

Businesses specialise because they cannot efficiently produce everything themselves.

For example:

Your plant may specialise in:

• palm-oil processing

• refining

• extraction

while other companies specialise in:

• engineering

• instrumentation

• electrical services

• chemicals

• spare parts

• automation

Trade allows each party to focus on what it does relatively well.

Principle 6 — Markets are usually a good way to organise economic activity

Markets coordinate millions of decisions through:

• prices

• demand

• supply

• competition

For example, if palm oil prices rise, producers have stronger incentives to increase production where feasible.

If electricity prices rise, businesses have stronger incentives to improve energy efficiency.

Principle 7 — Governments can sometimes improve market outcomes

Markets do not always produce desirable outcomes.

Examples include:

• pollution

• monopoly power

• unsafe working conditions

• information asymmetry

Government therefore establishes:

• environmental regulations

• safety regulations

• competition laws

• taxation

• standards

For an industrial organisation, this is particularly important because compliance itself has economic consequences.

4. How the economy works

Principle 8 — The standard of living depends on productivity

This is perhaps one of the most important principles for industry.

Productivity = output produced per unit of input.

For example:

A mill produces:

300,000 tonnes FFB/year

using:

• 100 workers

• 10,000 MWh electricity

• certain steam consumption

• certain maintenance cost

If technology allows the same output using less:

• labour

• electricity

• steam

• downtime

productivity increases.

Therefore:

Higher productivity → lower unit cost → greater competitiveness.

This is why engineering improvement is also an economic activity.

Principle 9 — Prices rise when too much money is created

This relates to inflation.

Inflation affects businesses through:

• wages

• spare parts

• chemicals

• construction

• equipment

• transportation

• maintenance contracts

Suppose a boiler spare part costs:

RM100,000 today.

If inflation increases the price by 5%:

RM100,000 × 1.05 = RM105,000

For large CAPEX projects, inflation can significantly affect project economics.

Principle 10 — Society faces a short-run trade-off between inflation and unemployment

This is mainly a macroeconomic concept.

When governments stimulate economic activity, employment may increase, but excessive demand can contribute to inflation.

For managers, macroeconomic conditions affect:

• interest rates

• exchange rates

• commodity prices

• investment decisions

• labour costs

• financing costs

5. Supply and Demand

This is probably the most important business economics concept.

Demand

Demand describes how much consumers are willing and able to buy at different prices.

Generally:

Price ↑ → Quantity demanded ↓

and:

Price ↓ → Quantity demanded ↑

This is the law of demand.

Example

If refined palm oil becomes more expensive, buyers may:

• reduce purchases

• switch suppliers

• substitute another vegetable oil

• delay purchases

6. Supply

Supply describes how much producers are willing and able to sell.

Generally:

Price ↑ → Quantity supplied ↑

because higher prices can make production more profitable.

7. Market equilibrium

The market reaches equilibrium where:

Quantity demanded = Quantity supplied

This produces:

• equilibrium price

• equilibrium quantity

For a commodity such as palm oil, prices are influenced by many factors:

• global supply

• global demand

• competing oils

• weather

• inventories

• biodiesel demand

• exchange rates

• geopolitical conditions

Therefore, a manager cannot look only at internal production costs.

8. Shifts in demand

Demand can change even when price does not initially change.

Factors include:

• income

• population

• consumer preferences

• prices of substitutes

• prices of complementary goods

• expectations

Example

If demand for sustainable products increases, demand for certified sustainable palm oil may increase.

This potentially affects:

• selling price

• market access

• certification investment

• production strategy

9. Elasticity

This is extremely important for business decision-making.

Elasticity measures how strongly one variable responds to another.

Price elasticity of demand

Formula:

Price Elasticity of Demand

= % change in quantity demanded
÷ % change in price

Example

Price increases by 10%.

Quantity demanded decreases by 20%.

Elasticity:

20% ÷ 10% = 2

Demand is therefore relatively elastic.

This means customers are highly responsive to price.

10. Why elasticity matters to managers

Imagine two products.

Product A

Price increases 10%.

Sales fall only 2%.

Demand is relatively inelastic.

Product B

Price increases 10%.

Sales fall 30%.

Demand is relatively elastic.

A manager must therefore consider elasticity before increasing prices.

This leads to an important relationship:

Revenue = Price × Quantity Sold

A higher price does not automatically mean higher revenue.

11. Income elasticity

Income elasticity measures how demand changes when consumer income changes.

For example:

If consumer income increases 10% and demand for a product increases 20%:

Income elasticity = 2.

This helps businesses understand how their products behave during:

• economic expansion

• recession

• income growth

12. Cross-price elasticity

This examines the relationship between two products.

For example:

Palm oil and soybean oil can be substitutes in some applications.

If soybean oil becomes significantly more expensive, demand for palm oil may increase, depending on the market and application.

This is why managers need to understand competitor products, not just their own product.

13. Production economics

Businesses transform inputs into outputs.

For example:

Inputs

FFB + labour + electricity + steam + water + chemicals + machinery

↓

Production process

↓

Outputs

CPO + PK + kernel + biomass + other products/by-products

Economics asks:

How can we produce the desired output using resources efficiently?

14. Fixed cost and variable cost

This is essential for managerial decisions.

Fixed costs

Costs that do not change significantly with short-run production.

Examples:

• building

• depreciation

• certain salaries

• insurance

Variable costs

Costs that change with production.

Examples:

• electricity

• fuel

• chemicals

• packaging

• production-related labour

15. Total, average and marginal cost

Total Cost

TC = Fixed Cost + Variable Cost

Average Cost

AC = Total Cost ÷ Quantity

Marginal Cost

MC = Change in Total Cost ÷ Change in Quantity

Marginal cost is particularly important for production decisions.

16. Economies of scale

A large plant may have lower average cost because fixed costs are spread over more production.

For example:

Plant A:

100,000 tonnes/year

Fixed cost = RM10 million

Fixed cost per tonne:

RM100/t

Plant B:

200,000 tonnes/year

Fixed cost = RM10 million

Fixed cost per tonne:

RM50/t

The larger production volume reduces fixed cost per unit.

This is an example of economies of scale.

17. Diseconomies of scale

Being bigger does not always mean being more efficient.

A very large organisation can suffer from:

• bureaucracy

• communication problems

• management complexity

• slower decisions

• maintenance complexity

• coordination problems

Therefore:

There is often an economically efficient scale of operation.

18. Four major market structures

Mankiw/Taylor economics also helps us understand different competitive environments.

1. Perfect competition

Many sellers and buyers.

Products are relatively homogeneous.

Individual firms have little control over market price.

2. Monopoly

One dominant supplier.

The firm has significant market power.

It can influence price, subject to demand and regulation.

3. Monopolistic competition

Many firms compete but products are differentiated.

Examples could include:

• branded food products

• restaurants

• consumer products

Competition occurs through:

• price

• quality

• branding

• service

4. Oligopoly

A small number of major firms dominate the market.

Each firm's decision affects the others.

Therefore companies must consider competitors' reactions.

This introduces strategic decision-making.

19. Externalities

An externality occurs when an economic activity affects a third party.

Negative externality

Pollution is the classic example.

A factory may produce a product profitably while imposing environmental costs on society.

For example:

Production → wastewater → environmental damage

The market price may not initially include the full social cost.

Government may therefore introduce:

• environmental standards

• treatment requirements

• taxes

• penalties

20. Public goods

Some goods are difficult for private markets to provide efficiently.

Examples include certain:

• public infrastructure

• national defence

• public information

Governments may therefore provide or regulate them.

21. Information economics

Business decisions often involve imperfect information.

For example, when buying a used industrial pump, the buyer may not know:

• remaining life

• vibration history

• maintenance quality

• hidden defects

This creates information asymmetry.

Good engineering practices reduce this problem through:

• inspection

• testing

• certification

• condition monitoring

• documentation

• warranties

22. Macroeconomics for managers

The book also connects business decisions to the wider economy.

Managers should monitor:

GDP

Measures overall economic activity.

Inflation

Measures general price increases.

Unemployment

Indicates labour-market conditions.

Interest rates

Affect borrowing and investment.

Exchange rates

Very important for companies involved in international trade.

23. Exchange rates and your industry

Suppose:

USD/MYR changes from:

USD1 = RM4.50

to:

USD1 = RM4.80

If your company imports equipment costing:

USD1 million

At RM4.50:

RM4.50 million

At RM4.80:

RM4.80 million

Difference:

RM300,000

Therefore exchange-rate movements can significantly affect CAPEX.

24. Cost-benefit analysis

This is one of the most useful applications of economics to engineering management.

Suppose an energy project costs:

CAPEX = RM1 million

Annual savings:

RM300,000/year

Simple payback:

RM1,000,000 ÷ RM300,000 = 3.33 years

But economics goes further than simple payback.

You should consider:

• time value of money

• inflation

• maintenance

• equipment life

• residual value

• risk

• opportunity cost

• financing cost

This leads to:

NPV — Net Present Value

IRR — Internal Rate of Return

ROI — Return on Investment

These are important tools for investment decisions.

25. The most important concept: marginal thinking

If you remember only one concept from Mankiw's economics, I would suggest:

Think at the margin.

Don't ask:

"Is this project expensive?"

Ask:

"What additional benefit will I receive from the additional cost?"

For example:

A motor replacement costs RM200,000.

Expected annual electricity saving:

RM80,000.

Additional maintenance saving:

RM20,000.

Total annual benefit:

RM100,000.

Then:

Marginal benefit = RM100,000/year

Compare this with:

Marginal cost = RM200,000 CAPEX

Then evaluate the project over its useful life using NPV/IRR rather than looking only at the RM200,000 price tag.

26. Applying Mankiw/Taylor to your organisation

For your facilities and energy-management responsibilities, I would translate the book into this practical framework:

Economics concept	Management application
Scarcity	Limited CAPEX, manpower and equipment
Opportunity cost	Choosing one project over another
Marginal analysis	Whether an additional improvement is worthwhile
Demand	Customer/market requirements
Supply	Raw material and equipment availability
Elasticity	Customer response to price changes
Fixed cost	Buildings, depreciation, certain salaries
Variable cost	Energy, chemicals, production inputs
Marginal cost	Cost of additional production
Economies of scale	Larger production lowering unit cost
Productivity	Output per worker/energy/machine
Externality	Pollution and environmental impacts
Market structure	Competitive environment
Inflation	Increasing operating/CAPEX costs
Interest rate	Cost of financing
Exchange rate	Imported equipment and spare parts
NPV	Long-term investment decisions
Risk	Uncertainty in project returns

---

27. A simple management model

You can turn the entire subject into six questions:

1. What is the objective?

For example:

Increase production while reducing unit cost.

2. What are the constraints?

• CAPEX

• manpower

• equipment

• energy

• regulations

• time

3. What are the alternatives?

For example:

A. Repair existing equipment
B. Upgrade equipment
C. Replace equipment
D. Outsource

4. What is the opportunity cost?

What benefit do we sacrifice by selecting one option?

5. What are the marginal benefits and marginal costs?

Does the additional benefit justify the additional cost?

6. What happens under different scenarios?

Consider:

• best case

• expected case

• worst case

This is essentially economic decision-making for managers.

28. One example using an industrial project

Imagine your plant is considering an energy-efficiency project.

CAPEX: RM1.5 million

Expected annual electricity saving:

RM400,000

Additional maintenance saving:

RM50,000

Additional production benefit:

RM100,000

Total annual economic benefit:

RM550,000

Simple payback:

RM1.5 million ÷ RM550,000 ≈ 2.73 years

But the proper economic question is not simply:

"Payback below 3 years?"

It is:

"Does the present value of the future benefits exceed the present value of the investment and associated risks?"

That is where economics + engineering + finance come together.

29. The big picture of the book

You can think of Mankiw/Taylor's Business Economics as a journey:

Scarcity

↓

Choice

↓

Opportunity Cost

↓

Marginal Analysis

↓

Demand & Supply

↓

Price & Market

↓

Production & Cost

↓

Competition

↓

Government & Market Failure

↓

Macroeconomics

↓

Business Decision-Making

The ultimate purpose is not merely to learn economic theories.

It is to learn how to make better decisions when resources are limited and the future is uncertain.

For you as an engineering/facilities manager

The strongest connection is:

Engineering tells you what can be done.
Economics tells you whether it is worth doing.
Finance tells you how to fund it.
Management decides how to implement it.

That combination is particularly powerful for CAPEX justification, energy management, maintenance strategy, production optimisation and asset-life-cycle decisions.

Demand, Supply and Market Equilibrium in the Digital Economy

1. Introduction

The traditional economic model explains market behaviour through three fundamental concepts: demand, supply, and market equilibrium. Demand represents the quantity of goods or services consumers are willing and able to purchase at different prices, while supply represents the quantity producers are willing and able to offer. The interaction between demand and supply determines the equilibrium price and quantity.

However, the emergence of the digital economy has significantly changed how these mechanisms operate.

Digital transformation has introduced:

• e-commerce platforms;

• digital payment systems;

• artificial intelligence (AI);

• big-data analytics;

• cloud computing;

• mobile commerce;

• digital advertising;

• online marketplaces;

• platform-based businesses;

• social commerce;

• automated supply chains; and

• algorithmic pricing.

Consequently, the traditional demand-and-supply model remains relevant, but the determinants, speed, transparency and flexibility of demand and supply have changed substantially.

A useful way to conceptualise the transformation is:

Digital transformation reduces information and transaction costs, expands market access, increases the speed of market adjustment, and enables firms to respond more rapidly to changes in consumer demand.

At the same time, digital markets can create new economic problems, including network effects, market concentration, information asymmetry, algorithmic pricing, privacy concerns and platform power.

---

2. Traditional Demand and Supply Framework

In a conventional market, demand can be represented as:

$$Q_d = f(P, Y, P_s, T, E, N)$$

where:

• $Q_d$ = quantity demanded

• $P$ = price

• $Y$ = consumer income

• $P_s$ = prices of substitute and complementary goods

• $T$ = consumer preferences/tastes

• $E$ = expectations

• $N$ = number of consumers

The basic law of demand states that, ceteris paribus, an increase in price normally reduces quantity demanded.

Supply can similarly be represented as:

$$Q_s = f(P, C, Technology, E, N_f)$$

where:

• $Q_s$ = quantity supplied

• $P$ = price

• $C$ = production costs

• Technology = production technology

• $E$ = producer expectations

• $N_f$ = number of firms

The law of supply states that, other things being equal, a higher market price provides an incentive for producers to supply more.

Market equilibrium occurs when:

$$Q_d = Q_s$$

At this point:

• quantity demanded = quantity supplied;

• there is no persistent shortage;

• there is no persistent surplus;

• the equilibrium price is established.

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The digital economy does not eliminate this fundamental relationship. Instead, it changes the forces that shift the demand and supply curves and the speed with which markets move toward a new equilibrium.

3. What Is the Digital Economy?

The digital economy refers to economic activities that are increasingly enabled by digital technologies, digital infrastructure, data and online networks.

Examples include:

• Amazon-style e-commerce;

• online banking;

• digital streaming;

• ride-hailing;

• online education;

• food-delivery platforms;

• digital financial services;

• online advertising;

• software-as-a-service;

• cloud computing;

• digital marketplaces.

The key difference from traditional markets is that information itself becomes a major economic resource.

In a traditional market, a consumer may need to visit several shops to compare prices.

In an online market, the consumer may compare:

• price;

• quality;

• customer reviews;

• delivery time;

• seller reputation;

• product specifications;

• competing products

within seconds.

This fundamentally affects demand elasticity, competition and market equilibrium.

4. How Digital Transformation Changes Demand

4.1 Greater Consumer Information

One of the most important effects of digital transformation is the reduction in information costs.

Previously, consumers had limited information about:

• competing prices;

• product quality;

• alternative sellers;

• customer experiences.

E-commerce provides substantially more information.

For example, a consumer purchasing a smartphone can compare dozens of sellers simultaneously.

This can make consumers more price-sensitive.

If consumers can easily find an alternative seller, a small increase in price may cause them to switch.

Therefore:

$$\text{Lower search cost} \rightarrow \text{greater consumer responsiveness}$$

This may increase the price elasticity of demand in some digital markets.

5. E-Commerce and the Expansion of Market Demand

Traditional physical markets are constrained by geography.

A small retailer may serve consumers within a 10–20 km radius.

E-commerce removes much of this geographical constraint.

A seller in Malaysia, Indonesia, China or the United States can potentially sell to consumers in many countries.

Thus:

$$\text{Digital access} \rightarrow \text{larger potential market}$$

This can shift market demand outward.

For example, consider a small producer of Malaysian handicrafts.

Traditional market

Potential customers:

Local consumers + tourists

Digital market

Potential customers:

Local consumers + national consumers + international consumers

Therefore, digital transformation can significantly increase the market size available to producers.

6. Personalisation and Demand

Another important development is data-driven personalisation.

Digital companies collect and analyse information about consumer behaviour, including:

• previous purchases;

• browsing history;

• search behaviour;

• location;

• product preferences;

• shopping frequency.

AI algorithms can then recommend products.

For example:

Consumer searches for running shoes → platform recommends running shoes → consumer becomes more aware of available products → probability of purchase increases.

This can effectively stimulate demand.

Therefore:

$$Data + AI + Personalisation \rightarrow \text{greater product visibility} \rightarrow \text{potential increase in demand}$$

This represents an important difference from the traditional demand model because consumer preferences are increasingly influenced by algorithmic recommendations.

7. Social Media and Demand

Social media has created another mechanism for shifting demand.

Consumers are exposed to:

• influencers;

• reviews;

• viral content;

• online communities;

• user-generated content;

• targeted advertising.

A product can become popular extremely quickly.

For example:

A product becomes viral on TikTok → millions of consumers see it → consumer preferences change → demand increases sharply.

Consequently, digital markets can experience very rapid demand shocks.

Traditional markets might take weeks or months to experience a change in consumer preferences.

Digital markets can experience the same change within hours or days.

8. Online Reviews and Demand

Online reviews also affect consumer demand.

A consumer may evaluate a product based on:

• average rating;

• number of reviews;

• customer comments;

• photographs;

• seller reputation.

This reduces uncertainty.

In economic terms, reviews can reduce information asymmetry between buyers and sellers.

However, this mechanism can fail when:

• reviews are fake;

• ratings are manipulated;

• sellers purchase positive reviews;

• negative reviews are suppressed.

Therefore, digitalisation can both reduce and create information problems.

9. Dynamic Pricing and Demand

Digital markets also enable firms to adjust prices rapidly.

Traditional retailers may change prices:

weekly or monthly.

Digital firms can potentially change prices:

hourly or even continuously.

Prices can respond to:

• demand;

• inventory;

• competitor prices;

• consumer behaviour;

• time of day;

• location;

• seasonal conditions.

This is known as dynamic or algorithmic pricing.

For example:

During high demand:

$$P \uparrow$$

During low demand:

$$P \downarrow$$

The objective is to bring demand and supply closer together while increasing revenue.

10. How Digital Transformation Changes Supply

Digital transformation does not only affect consumers. It fundamentally changes the supply side of the economy.

One major effect is increased production efficiency.

Digital technologies allow firms to use:

• automation;

• robotics;

• AI;

• predictive maintenance;

• cloud computing;

• digital inventory systems;

• real-time logistics tracking.

These technologies can reduce production costs.

If production costs decrease:

$$MC \downarrow$$

where $MC$ represents marginal cost.

This can shift the supply curve outward.

In simplified terms:

$$Technologyimprovement\to Lowerproductioncost\to Greatersupply$$

11. Digital Supply Chains

Traditional supply chains often depend on periodic information.

For example:

Manufacturer → Distributor → Wholesaler → Retailer → Consumer

Information moves relatively slowly.

Digital supply chains allow:

Consumer → Platform → Warehouse → Supplier → Manufacturer

Information can flow almost instantaneously.

A company can observe:

• current sales;

• inventory;

• orders;

• delivery status;

• consumer demand.

This improves inventory management.

12. Just-in-Time and Demand Forecasting

AI and big-data analytics can improve demand forecasting.

Suppose a retailer historically sells:

1,000 units per month.

But digital analytics identifies that demand will increase to:

1,500 units next month.

The company can increase its inventory before demand occurs.

Therefore:

$$\text{Better forecasting} \rightarrow \text{better production planning} \rightarrow \text{lower inventory risk}$$

This can make supply more responsive to demand.

13. Lower Transaction Costs

One of the most important economic effects of digitalisation is the reduction in transaction costs.

Transaction costs include:

• searching for suppliers;

• negotiating;

• payment processing;

• communication;

• contract management;

• logistics coordination.

Digital platforms reduce many of these costs.

For example:

A traditional procurement process may require:

1. identifying suppliers;

2. contacting suppliers;

3. requesting quotations;

4. comparing prices;

5. negotiating;

6. issuing purchase orders.

A digital procurement platform can automate much of this process.

Thus:

$$TransactionCost\downarrow \to MarketParticipation\uparrow$$

14. E-Commerce and the Supply Curve

E-commerce allows firms to reach customers without maintaining extensive physical retail infrastructure.

A traditional retailer may require:

• physical shop;

• sales staff;

• warehouse;

• electricity;

• geographic location.

An online seller may operate with substantially lower physical retail costs.

This can reduce average costs for some businesses.

Consequently:

$$AC \downarrow \rightarrow \text{greater ability to supply}$$

However, e-commerce does not eliminate all costs.

Instead, costs may shift toward:

• warehousing;

• fulfilment;

• packaging;

• delivery;

• platform commissions;

• digital advertising;

• cybersecurity;

• returns management.

Therefore, digitalisation often changes the structure of costs rather than simply eliminating costs.

15. The Role of Digital Platforms

Digital platforms represent one of the most important developments in the modern economy.

Examples include:

• online marketplaces;

• ride-hailing platforms;

• food-delivery platforms;

• app stores;

• social media platforms.

Platforms generally connect two or more groups.

For example:

$$Buyers \leftrightarrow Platform \leftrightarrow Sellers$$

This creates a multi-sided market.

16. Network Effects

A major characteristic of digital platforms is the network effect.

The value of a platform can increase as more users join.

For example:

More buyers → platform becomes more attractive to sellers.

More sellers → platform becomes more attractive to buyers.

This creates:

$$Users \uparrow \rightarrow Platform\ Value \uparrow \rightarrow More\ Users$$

This feedback loop can produce very large digital platforms.

Network effects therefore influence both demand and supply.

17. Market Equilibrium in Digital Markets

Traditional equilibrium assumes that buyers and sellers interact primarily through price.

Digital markets are more complicated.

Market equilibrium may depend on:

• price;

• platform fees;

• delivery costs;

• waiting time;

• product variety;

• reviews;

• search rankings;

• network size;

• algorithmic recommendations.

Therefore, the relevant concept becomes something closer to multi-dimensional market equilibrium.

For example, consumers may choose a platform not simply because it offers the lowest price.

They may choose it because:

price + convenience + trust + reviews + delivery speed + product variety

provide the highest perceived value.

18. Digital Markets Can Reach Equilibrium Faster

Traditional markets may require considerable time to respond to changes in demand.

Digital markets can adjust much more quickly.

Suppose demand increases suddenly.

Traditional response:

Demand ↑ → production adjustment → distribution adjustment → retail adjustment → price adjustment

Digital response:

Demand ↑ → algorithm detects change → price/inventory/order adjustment → suppliers notified

Therefore:

$$\text{Information speed} \uparrow \rightarrow \text{Market adjustment speed} \uparrow$$

This is one of the most significant effects of digitalisation on market equilibrium.

19. But Digital Markets Can Also Become Highly Volatile

Faster adjustment does not necessarily mean greater stability.

Digital markets can experience rapid fluctuations.

For example:

viral social-media trend → demand surge → inventory shortage → price increase → new suppliers enter → demand falls → excess inventory.

Therefore, digitalisation can produce faster but potentially more volatile equilibrium adjustments.

This is particularly important for products influenced by:

• fashion;

• social media;

• cryptocurrency;

• technology trends;

• online communities.

20. Price Elasticity in the Digital Economy

Price elasticity measures how responsive quantity demanded is to changes in price.

$$E_d = \frac{\%\Delta Q_d}{\%\Delta P}$$

Digital markets can increase elasticity because consumers can compare prices quickly.

For example:

If Seller A charges RM100 and Seller B charges RM85, consumers can immediately identify the difference.

The cost of switching is low.

Therefore:

Greater price transparency + lower search cost → potentially greater price sensitivity.

However, this is not universal.

Strong brand loyalty, switching costs, subscriptions and network effects can make demand less price-sensitive.

21. Zero-Price Digital Products

One unusual feature of the digital economy is that many products have a monetary price of zero.

Examples include:

• search engines;

• social media;

• email services;

• messaging applications.

Does this mean demand is infinite?

No.

The economic exchange may occur through another mechanism.

Consumers may pay through:

• attention;

• personal data;

• advertising exposure;

• behavioural information.

Therefore, digital markets challenge the traditional assumption that price is always the primary allocation mechanism.

22. Data as an Economic Resource

Data has become an important production factor.

Traditional production factors include:

• land;

• labour;

• capital;

• entrepreneurship.

In the digital economy, data can be viewed as a strategically important intangible asset.

Data allows firms to:

• forecast demand;

• personalise products;

• optimise prices;

• improve logistics;

• identify customer segments;

• detect fraud.

Therefore:

$$Data\to BetterInformation\to BetterDecisions\to PotentiallyGreaterEfficiency$$

23. Economies of Scale in Digital Markets

Digital products often have very low marginal costs.

For example, producing the first copy of software can be expensive.

But producing another digital copy may cost almost nothing.

Therefore:

$$MC \approx 0$$

for some digital products.

This creates significant economies of scale.

A digital firm can potentially serve millions of additional customers without proportionally increasing production costs.

This can lead to highly concentrated markets.

24. Market Concentration and Competition

Digital economies can therefore produce a paradox.

Digitalisation can:

lower barriers to entry and allow small firms to reach global consumers.

But it can also:

create economies of scale and network effects that favour very large firms.

Consequently, digital markets may simultaneously encourage:

greater market access

and

greater market concentration.

This is an important issue for PhD-level analysis.

25. Algorithmic Competition

Competition increasingly occurs through algorithms.

Algorithms can automatically monitor:

• competitors' prices;

• inventory;

• demand;

• customer behaviour.

Firms can then adjust prices automatically.

This may increase competitive efficiency.

However, it also creates potential concerns about:

• tacit coordination;

• discriminatory pricing;

• excessive price changes;

• lack of transparency.

Thus, algorithmic pricing creates new questions for competition economics.

26. Consumer Surplus in the Digital Economy

Consumer surplus represents the difference between:

what a consumer is willing to pay

and

what the consumer actually pays.

Digitalisation can increase consumer surplus through:

• lower prices;

• greater product variety;

• faster delivery;

• better information;

• greater convenience.

For example, a consumer who is willing to pay RM150 for a product but purchases it for RM100 obtains:

$$Consumer\ Surplus = RM50$$

Digital platforms may increase this surplus through greater competition and lower search costs.

27. Producer Surplus

Producer surplus is the difference between:

the price received

and

the minimum price at which the producer is willing to supply.

Digitalisation can increase producer surplus by:

• expanding market access;

• reducing transaction costs;

• increasing productivity;

• improving demand forecasting.

However, platform commissions and intense price competition can reduce producer margins.

Therefore, the effect is not automatically positive for every producer.

28. A Key PhD-Level Issue: Disintermediation vs Reintermediation

Digital transformation was initially expected to eliminate intermediaries.

This is called disintermediation.

For example:

Manufacturer → Consumer

instead of:

Manufacturer → Wholesaler → Retailer → Consumer.

However, digital platforms have created a new type of intermediary.

This can be described as reintermediation.

The structure becomes:

Manufacturer → Digital Platform → Consumer.

Platforms therefore replace some traditional intermediaries while creating new ones.

This is a major structural transformation of markets.

29. Digital Divide and Market Demand

Digital transformation does not affect all consumers equally.

Some consumers have:

• smartphones;

• broadband;

• digital payment access;

• digital literacy.

Others may not.

Therefore, digitalisation can create a digital divide.

If certain consumers cannot participate effectively in e-commerce, their effective market demand remains constrained.

Thus:

$$Digital\ Access \rightarrow Market\ Participation$$

This has implications for:

• income inequality;

• rural communities;

• elderly consumers;

• developing economies;

• small businesses.

30. Cybersecurity and Consumer Trust

Digital markets depend heavily on trust.

Consumers must believe that:

• payments are secure;

• personal information is protected;

• products will arrive;

• sellers are legitimate.

Cybersecurity failures can therefore reduce demand.

For example:

$$Cybersecurity\ Risk \uparrow \rightarrow Consumer\ Trust \downarrow \rightarrow Demand \downarrow$$

Thus, trust becomes an important non-price determinant of demand in digital markets.

31. Summary Comparison

Dimension	Traditional Economy	Digital Economy
Market access	Mainly geographical	Potentially global
Price information	Limited	Highly transparent
Search cost	Relatively high	Low
Transaction speed	Slower	Very fast
Consumer information	Limited	Extensive
Pricing	Relatively static	Often dynamic
Supply response	Slower	More responsive
Inventory management	Forecast-based	Real-time/data-driven
Distribution	Physical	Physical + digital
Market intermediaries	Wholesalers/retailers	Digital platforms
Competition	Mainly price/product	Price + algorithms + network effects
Consumer influence	Relatively limited	Reviews/social media/data
Marginal cost	Usually positive	Can approach zero for digital goods
Market boundaries	Often local/national	Potentially global
Information asymmetry	Significant	Can decrease but may create new forms
Market adjustment	Relatively slow	Potentially very rapid

---

32. Integrated Economic Model

A useful framework for your PhD assignment is:

Digital transformation

↓

Lower search and transaction costs

↓

Greater information availability

↓

Changes in consumer behaviour

↓

Changes in demand elasticity and market size

↓

Digital technologies improve productivity

↓

Lower production/distribution costs

↓

Greater supply responsiveness

↓

Faster adjustment of prices and quantities

↓

New market equilibrium

However, this process is influenced by:

network effects + platform power + data ownership + algorithms + digital divide + regulation.

33. Conceptual Framework for Your PhD Assignment

You could develop the following conceptual framework:

Independent Variable:

Digital Transformation

Measured through:

• e-commerce adoption;

• AI adoption;

• digital payment;

• big-data utilisation;

• automation;

• digital platforms.

↓

Demand-side mechanisms

• lower search costs;

• greater information;

• personalisation;

• greater product variety;

• convenience;

• changing consumer preferences.

↓

Supply-side mechanisms

• lower transaction costs;

• automation;

• improved forecasting;

• inventory optimisation;

• logistics efficiency;

• economies of scale.

↓

Market mechanisms

• price elasticity;

• competition;

• dynamic pricing;

• network effects;

• market concentration.

↓

Outcome

Market Equilibrium

Measured through:

• equilibrium price;

• equilibrium quantity;

• market efficiency;

• consumer surplus;

• producer surplus;

• speed of market adjustment.

34. Important Critical Discussion

For a PhD assignment, it is important not merely to argue that digital transformation improves markets.

A stronger academic argument is:

Digital transformation changes the mechanism through which demand and supply interact.

This is more sophisticated than saying:

“E-commerce increases demand and technology increases supply.”

The digital economy changes the information architecture of the market.

In traditional economics:

$$Price \rightarrow Information \rightarrow Decision$$

In digital markets, the relationship increasingly becomes:

$$Data \rightarrow Algorithm \rightarrow Recommendation/Price \rightarrow Consumer Decision$$

Therefore, data and algorithms increasingly participate in the market-allocation process.

This raises an important theoretical question:

Is the traditional price mechanism sufficient to explain market equilibrium in digital markets?

The answer is that the traditional model remains foundational, but it needs to be supplemented by theories of platform economics, network effects, information economics, behavioural economics, transaction-cost economics and industrial organisation.

35. Conclusion

The relationship between demand, supply and market equilibrium remains fundamental in the digital economy. However, digital transformation and e-commerce have significantly altered the mechanisms through which these forces operate.

On the demand side, digitalisation reduces search costs, increases price transparency, expands consumer choice, enables personalisation and allows social-media-driven changes in consumer preferences.

On the supply side, digital technologies reduce transaction costs, improve productivity, strengthen demand forecasting, optimise inventory and logistics, and allow firms to respond more rapidly to market changes.

As a result, digital markets can experience faster market adjustment, wider market participation and potentially greater efficiency. Nevertheless, digitalisation also introduces new economic challenges, particularly network effects, platform concentration, algorithmic pricing, data asymmetry, privacy concerns, cybersecurity risks and the digital divide.

Therefore, the central argument 

The digital economy does not replace the conventional forces of demand and supply; rather, it transforms the speed, information structure, cost structure and institutional mechanisms through which demand and supply interact to determine market equilibrium.

This provides a strong theoretical foundation for analysing e-commerce as a transformation of the conventional market mechanism rather than simply a new distribution channel.