VECTOR21: Simulating Future Vehicle Market Share and CO2 Emissions

Why It Matters

Understanding the complex interplay of factors influencing vehicle adoption and environmental impact is crucial for strategic planning in the automotive sector. This model provides a framework for designers and engineers to explore the potential outcomes of design choices and policy interventions.

Key Finding

The study developed a simulation model that predicts how different vehicle types will be adopted in the market and their resulting CO2 emissions, by considering what influences buyers and manufacturers, including costs, policies, and learning over time.

Key Findings

• The VECTOR21 model can simulate the diffusion of vehicle technologies and fuels in the automotive market.
• Relevant Cost of Ownership is a key factor in customer purchasing decisions.
• Learning curves and variable margins influence production costs and selling prices.
• Policy instruments and raw material prices significantly impact market outcomes and emissions.

Research Evidence

Aim: To develop a scenario model for simulating future vehicle market shares and CO2 emissions based on various influencing factors.

Method: Computational modelling and simulation

Procedure: A computer model (VECTOR21) was developed to calculate scenarios for the future development of the automotive market. It considers market shares of different vehicle technologies and fuels, and associated CO2 emissions for passenger cars in Germany from 2009 to 2030. The model simulates customer decision-making in new vehicle purchases, reflecting the diffusion of technologies and fuels, based on 'Relevant Cost of Ownership'. It also incorporates learning curves and variable margins for producers' costs and prices, alongside the impact of tax instruments (e.g., CO2 fleet targets) and raw material prices.

Context: Automotive market analysis, environmental impact assessment

Design Principle

Anticipate market diffusion and environmental impact through scenario-based modelling.

How to Apply

Use simulation tools to test the market viability and environmental performance of design concepts under different future scenarios.

Limitations

The model's accuracy is dependent on the quality and completeness of the vehicle and technology database, and the assumptions made about future influencing factors.

Student Guide (IB Design Technology)

Simple Explanation: This study created a computer program to predict which types of cars people will buy in the future and how much CO2 they will produce, by looking at things like cost, new technology, and government rules.

Why This Matters: This research shows how complex systems can be modelled to predict future outcomes, which is useful for understanding how design choices impact markets and the environment.

Critical Thinking: How might the assumptions within a simulation model, such as those concerning 'Relevant Cost of Ownership' or 'learning curves', introduce bias into the predicted outcomes?

IA-Ready Paragraph: The development of scenario models, such as VECTOR21, demonstrates the utility of computational tools in predicting future market dynamics and environmental impacts. This approach, which simulates customer decision-making and considers factors like cost of ownership, technological diffusion, and regulatory influences, provides valuable insights for design strategy and product development.

Project Tips

• When designing a product, think about how it will be adopted by the market over time.
• Consider how external factors like cost, regulations, and new technologies might affect your design's success.

How to Use in IA

• Reference this study when discussing the importance of market simulation and forecasting for design projects.
• Use the concept of modelling customer decision-making to inform your own user research and product development strategy.

Examiner Tips

• Demonstrate an understanding of how models can be used to predict the impact of design decisions.
• Discuss the limitations of any predictive models used in your design project.

Independent Variable: ["Cost of ownership","Technological advancements","Government policies (e.g., CO2 targets)","Raw material prices"]

Dependent Variable: ["Market share of vehicle technologies/fuels","CO2 emissions"]

Controlled Variables: ["Time period (2009-2030)","Geographic market (Germany)","Vehicle type (passenger cars)"]

Strengths

• Comprehensive consideration of multiple influencing factors.
• Simulation of complex market diffusion processes.

Critical Questions

• To what extent can future consumer behaviour be accurately modelled?
• How sensitive are the model's predictions to changes in input parameters?

Extended Essay Application

• Develop a simulation model to predict the adoption rate of a new sustainable material in a specific product category.
• Investigate the impact of different pricing strategies on the market penetration of innovative technologies.

Source

Entwicklung eines Szenariomodells zur Simulation der zukünftigen Marktanteile und CO2-Emissionen von Kraftfahrzeugen (VECTOR21) · OPUS Publication Server of the University of Stuttgart (University of Stuttgart) · 2010 · 10.18419/opus-6760