Exploring Future Pricing Strategies for Electric Heavy-Duty Road Freight Services
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Program
Management and economics of innovation (MPMEI), MSc
Data science and AI (MPDSC), MSc
Data science and AI (MPDSC), MSc
Publicerad
2023
Författare
Hegardt, Johan
Hedenblad, Leonard
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
The road freight industry is undergoing a transition with the increase in demand
for electric trucks and increased digitalisation. The pricing strategies in this industry are still underdeveloped and need reformation. This thesis project aims to: 1.
Investigate the implications of various pricing strategies for heavy-duty road freight
services in a digitalised, electric-only urban environment, and 2. Provide insights
into the development of effective pricing strategies that balance profitability and risk
while accounting for the challenges of a future environment with new technologies,
cost structures, electrification, and digitalisation.
A methodology that incorporates Multi-Objective Robust Optimisation (MORO)
and scenario analysis to identify robust pricing policy alternatives that can withstand
different stochastic realisations of both deep uncertainties and well-characterised
uncertainties was used. The methodology uses EMA (Exploratory Modeling and
Analysis) and EMA Workbench as computational modeling tools to analyse complex systems. The methodology section outlines the research design used to achieve
the research objectives. A conceptual XLRM model of the system, with relevant
pricing levers and uncertainties, was developed through a literature review and expert opinions from the case company that was collaborated with, which was then
translated into a computational model using EMA Workbench. Exploratory research using scenario analysis and feature scoring was conducted to assess risks and
benefits associated with each pricing strategy, and sensitivity analysis was used to
identify parameters with the greatest impact on outcomes of interest.
The results of the study show that the methodology incorporating MORO and scenario analysis can be used to explore pricing strategies in systems of deep uncertainty. 12 optimal pricing policies were suggested and sensitivity analysis was used to identify features with the greatest impact on outcomes of interest. The study
provides insights into potential risks and benefits associated with different pricing
strategies in a transportation system characterised by deep uncertainty.
The study concludes that there is no one-size-fits-all pricing policy, there are best
performing policies depending on a company’s goals and uncertainties. The 12
optimal pricing policies were divided between dynamic pricing policies, which are pricing each customer individually, flat per km pricing policies, which are setting
a fixed price per km for all customers, and flat per month pricing policies, which
are setting the same price for each customer. Two of the dynamic pricing policies were found as top-performers, while the only selected flat per month approach
seems to be suitable for maintaining predictability of profits and cash flows along
with maximising market share and capacity utilisation rate, rather than maximising
total profit. Computational models like the MORO approach can be used to explore pricing strategies in deep uncertainty, but decision makers should be cautious
of the assumptions and parameters of the model. Future research should explore
alternative methodologies and consider behavioral mechanisms in pricing strategies.
Overall, this report provides valuable insights into decision making on pricing strategies for heavy-duty electric road freight under deep uncertainty, i.e., in which sort
of scenarios different pricing strategies performs optimally and when certain pricing
strategies should be avoided.
Beskrivning
Ämne/nyckelord
Deep uncertainty, Exploratory Modeling and Analysis (EMA), Multi Objective Robust Optimisation (MORO), modeling, Python, value at risk, profit analysis, road freight services, electric transition