Sunday, 27 September 2026

A note on ABC allocation drivers

A note on ABC allocation drivers

Activity-based costing (ABC) allocation drivers are specific units of work or events—known as cost drivers—used to trace and assign overhead costs to products, services, or customers based on actual resource consumption.

Unlike traditional volume-based methods (like direct labor or machine hours), ABC uses multiple activity levels and detailed drivers for precise cost allocation.

Types of Allocation Drivers

·        Transaction Drivers: Count how many times an activity occurs (e.g., number of purchase orders, machine setups, or customer calls).

·        Duration Drivers: Measure the amount of time needed to complete an activity (e.g., hours spent on quality inspection or machine maintenance time).

·        Intensity/Effort Drivers: Reflect the direct consumption level or complexity of a unique task (e.g., design complexity or exact amount of materials used).

·        Levels of Activity Drivers

·        Unit-level: Performed each time a unit is produced (e.g., consumed power or machine hours).

·        Batch-level: Incurred regardless of units in a batch (e.g., machine setups or purchase orders).

·        Product-level: Relate to specific products regardless of batches or units (e.g., product design changes).

·        Customer-level: Relate to specific customers (e.g., specialized customer support or catalog distributions).

·        Organization-sustaining: Baseline facility costs that cannot be easily assigned to specific products.

 

Regarding the topic of activity based costing, provide 3 examples of the allocation drivers on the following activities:

1.    R&D

2.    Customer service

3.    Product delivery

4.    Packaging

5.    Product warranty

6.    Product assembly

 

Here are three practical allocation (cost) drivers commonly used in activity-based costing (ABC) for each of the activities you listed:

1. R&D

  • Number of new product development projects supported by the R&D team.
  • Engineering/design hours spent per product or product line.
  • Number of design changes/engineering change orders (ECOs) per product.

These drivers reflect how different products or product families consume R&D resources (time, staff, prototyping, testing).

2. Customer service

  • Number of customer contacts/cases (calls, emails, chats) per product or customer segment.
  • Average handling time (AHT) or total service hours spent on issues related to each product.
  • Number of warranty/service claims filed per product.

These capture the intensity and volume of service effort attributable to different products or customers.

3. Product delivery

  • Number of deliveries/shipments made for each product or customer.
  • Distance or freight tonne-kilometres (weight × distance) per product line.
  • Number of delivery stops/routes required for each product’s orders.

These drivers link delivery costs (fuel, driver time, vehicle use) to how much each product “uses” the delivery activity.

4. Packaging

  • Number of units packaged per product.
  • Number of packaging setups/changeovers (e.g., different box sizes, labels) per product.
  • Packaging material weight or volume used per product type.

These reflect both the variable packaging effort (per unit) and batch-related costs (setups, changeovers).

5. Product warranty

  • Number of warranty claims per product model.
  • Warranty repair/replacement hours (labour time) per product.
  • Number of units under warranty (or warranty exposure = units sold × warranty period).

These drivers allocate warranty costs according to actual claim experience and the scale of warranty exposure by product.

6. Product assembly

  • Direct labour hours spent assembling each product.
  • Machine hours used in assembly operations per product.
  • Number of assembly operations/stations (or number of components assembled) per product.

These drivers capture how much assembly capacity (labour, machines, complexity) each product consumes.


Use one calculation example on product assembly and another example on product warranty to illustrate the topic.

Below are two worked ABC examples—one for product assembly and one for product warranty—showing how to move from cost pool → driver rate → overhead assigned to products.


Example 1: Product assembly (ABC calculation)

Step 1: Define the activity and cost pool

  • Activity: Product assembly
  • Total assembly overhead cost pool for the period: $500,000

Step 2: Choose a cost driver and measure total driver volume

  • Cost driver: Assembly labour hours
  • Total assembly labour hours for all products in the period: 25,000 hours

Step 3: Calculate the activity (driver) rate

Assembly rate per hour = Total assembly overhead/ Total assembly hours

=500,000 / 25,000

=$20 per assembly hour

Step 4: Apply the rate to each product

Assume two products:

  • Product A
    • Units produced: 10,000
    • Assembly hours per unit: 0.5 hour
    • Total assembly hours for A: 10,000×0.5=5,000
    • Assembly overhead assigned to A: 5,000×20=$100,000 Assembly overhead per unit of A: 100,000 / 10,000​=$10 per unit
  • Product B
    • Units produced: 5,000
    • Assembly hours per unit: 2 hours
    • Total assembly hours for B: 5,000×2=10,000 hours
    • Assembly overhead assigned to B: 10,000×20=$200,000 Assembly overhead per unit of B: 200,000/ 5,000=$40per unit

This shows how a more assembly‑intensive product (B) attracts much higher assembly overhead per unit under ABC than a simpler product (A).


Example 2: Product warranty (ABC calculation)

Step 1: Define the activity and cost pool

  • Activity: Product warranty service
  • Total warranty cost pool for the period (repairs, parts, admin): $300,000

Step 2: Choose a cost driver and measure total driver volume

  • Cost driver: Number of warranty claims
  • Total warranty claims for all products in the period: 6,000 claims

Step 3: Calculate the activity (driver) rate

Warranty rate per claim = Total warranty overhead / Total warranty claims

=300,000/ 6,000 = $50 per claim

Step 4: Apply the rate to each product

Assume two products:

  • Product X
    • Units sold: 20,000
    • Warranty claims for X: 2,000 claims
    • Warranty overhead assigned to X: 2,000×50=$100,000 Warranty overhead per unit of X: 100,000/ 20,000
    • = $5 per unit
  • Product Y
    • Units sold: 10,000
    • Warranty claims for Y: 4,000 claims
    • Warranty overhead assigned to Y: 4,000×50=$200,000   Warranty overhead per unit of Y: 200,000 / 10,000=$20 per unit

Even though Y has fewer units sold, its higher claim rate means it absorbs much more warranty cost per unit—exactly the kind of insight ABC is designed to reveal.


Saturday, 26 September 2026

A review of the article on “Green sustainability balanced scorecard—Evidence from the Taiwan liquefied natural gas industry”

A review of the article on “Green sustainability balanced scorecard—Evidence from the Taiwan liquefied natural gas industry”

 

 

How to present this article in Harvard reference format?

You can cite this article in Harvard referencing style as follows:

Wang, J.-S., Liu, C.-H. & Chen, Y.-T., 2022. Green sustainability balanced scorecard—Evidence from the Taiwan liquefied natural gas industry. Environmental Technology & Innovation, 28, p.102862. Available at: https://doi.org/10.1016/j.eti.2022.102862 [Accessed date].

Remember to replace "[Accessed date]" with the date you accessed the online version of the article.

 

What are the key research issues the article wants to address?

The key research issues addressed by the article are:

1.    The sustainable development of the liquefied natural gas (LNG) industry in Taiwan is at an early stage, and companies in this sector lack relevant knowledge and skills to effectively manage and measure their sustainability performance.

2.    There is a need to develop an assessment framework tailored to the LNG industry that incorporates economic, environmental, social, and green operational perspectives to guide sustainable strategy creation and performance evaluation.

3.    The conventional Sustainability Balanced Scorecard (SBSC) lacks a specific focus on green operations; thus, the study aims to extend the SBSC by adding a green operational perspective to develop a Green Sustainability Balanced Scorecard (GSBSC) for theory development.

4.    Identifying and prioritizing key sustainability indicators and constructs specific to the Taiwanese LNG industry, including operational risk and cost management, customer satisfaction, product management and recycling mechanisms, and greenhouse gas emissions.

5.    Addressing how companies in the Taiwanese LNG industry implement green and environmentally friendly operations to ensure green sustainability.

In summary, the research focuses on developing an integrated and industry-specific sustainability performance measurement tool (the GSBSC) to help the LNG sector in Taiwan improve green practices and sustainability management.

 

Describe two main theories employed in this article.

The two main theories employed in this article are:

1.    Sustainability Balanced Scorecard (SBSC): The SBSC theory extends the traditional Balanced Scorecard (BSC) by incorporating sustainability aspects into corporate performance measurement. Unlike the conventional BSC, which primarily focuses on financial and strategic metrics such as profit and customer perspectives, the SBSC integrates environmental and social responsibility perspectives alongside economic goals. This framework helps companies connect strategy and execution with sustainability targets covering the economy, environment, and society, thus supporting long-term sustainable performance. The article builds upon SBSC by adopting its multi-dimensional approach for evaluating sustainability performance and decision-making support in the corporate context.

2.    Green Operation Theory: Green operation pertains to business processes and activities designed to minimize environmental impact, comply with green regulations, and foster sustainable development through internal operational improvements. This includes adopting green manufacturing standards, green innovation, purchasing green materials, green information systems, product management and recycling mechanisms, and green supply chain management. Green operation theory emphasizes embedding "green" criteria and restraints within organizational processes to enhance ecological sustainability and corporate social responsibility. In this article, green operation theory underpins the addition of a "green operational object" to the SBSC, deepening its relevance and effectiveness in promoting sustainable business practices specific to the LNG industry.

Together, these theories provide a comprehensive framework—the Green Sustainability Balanced Scorecard (GSBSC)—that combines strategic performance measurement with practical environmental operational management to advance sustainability in the Taiwanese LNG industry.

 

Highlight 2 main primary findings reported in this article.

Two main primary findings reported in this article are:

1.    Importance of Green Operational and Environmental Objects: The study found that within the Green Sustainability Balanced Scorecard (GSBSC) framework for the Taiwanese LNG industry, the green operational and environmental objects are relatively more important constructs compared to others. Experts emphasized these two objects as critical for achieving sustainable development in the LNG sector, indicating that companies should prioritize green operations and environmental management to foster sustainability.

2.    Key Indicators Within Objects: The fuzzy Delphi expert questionnaire identified specific indicators that are particularly important within their respective objects. For example, within the economic object, 'operating risk and cost management' was highlighted; within the societal object, 'customer satisfaction' stood out; and in the green operational and environmental objects, 'product management and recycling mechanism' and 'greenhouse gas (GHG) emissions' were noted as significant indicators. These findings suggest that these indicators should be focal points in formulation and evaluation of sustainability strategies in the LNG industry.

 

Describe 3 main claims of the article in terms of Toulmin's model of argument.

Using Toulmin's model of argument (which includes Claim, Grounds/Evidence, and Warrant), three main claims from the article can be described as follows:

1.    Claim 1: The green operational and environmental objects are the most critical components for measuring sustainability performance in Taiwan’s LNG industry.

  • Grounds/Evidence: Fuzzy Delphi technique expert evaluations showed these objects received the highest importance scores (8.25), indicating industry consensus on their significance.
  • Warrant: Because sustainable development increasingly depends on minimizing environmental impact and ensuring green operations, these areas must be prioritized for effective sustainability assessment.

2.    Claim 2: Specific indicators such as ‘operating risk and cost management’, ‘customer satisfaction’, ‘product management and recycling mechanism’, and ‘GHG emissions’ are key drivers of sustainable performance in the LNG industry.

  • Grounds/Evidence: Experts gave these indicators relatively high influence scores in the fuzzy Delphi analysis (around 8.0 or higher), highlighting their importance within their respective objects.
  • Warrant: These indicators reflect core economic, social, operational, and environmental processes that directly affect company sustainability and long-term success.

3.    Claim 3: Extending the conventional Sustainability Balanced Scorecard (SBSC) by adding a ‘green operational’ object (forming the GSBSC) provides a more comprehensive framework for evaluating and guiding sustainability strategies in the LNG industry.

  • Grounds/Evidence: The study developed the GSBSC framework by literature review and expert input, showing its applicability and relevance to the LNG sector in Taiwan.
  • Warrant: Incorporating green operational elements explicitly addresses internal business processes related to environmental performance, filling a gap in conventional SBSC and better aligning performance measurement with sustainability goals.

These claims collectively support the article’s argument for developing and applying a green sustainability balanced scorecard tailored to the LNG industry to improve sustainability management and performance.

 

Describe 2 main research limitations of the study.

Two main research limitations of the study are:

1.    Scope of Industry and Expert Participation: The study focuses only on the Taiwanese LNG industry and relies on expert opinions primarily from this sector, including government agencies, corporations, and academic institutes. This limits the generalizability of the Green Sustainability Balanced Scorecard (GSBSC) indicators to other industries or geographic regions. The authors suggest that future studies should interview experts from other industries to validate whether the constructed GSBSC indicators apply more broadly.

2.    Research Methods and Depth: Due to time and resource constraints, the study employed literature review, expert questionnaires, and the fuzzy Delphi technique but did not use additional analytical methods. The authors recommend that future research use other methodologies such as importance-performance analysis or fuzzy analytic hierarchy process to explore the indicators from different perspectives and to enhance the robustness and completeness of the findings.

These limitations highlight the need for broader empirical testing and methodological diversity to strengthen the GSBSC framework's application and validation.