Understanding how to change behavioural habits is playing a crucial role in mitigating greenhouse gas emissions. This holds true for private behaviour (e.g. using the bike instead of the car), as well as behaviour in the working environment. In the transportation sector, saving greenhouse gas emissions goes hand in hand with saving money: fuel consumption is the main variable cost component (~40 per cent). Additionally, the transportation sector is responsible for about 25-30 per cent of total greenhouse gas emissions in western industrialised countries. By increasing the driving performance and driving in an energy-efficient manner, an excellent driver can reduce fuel consumption by about 25 per cent. Therefore, understanding how we can improve the driving behaviour of professional drivers plays a key role in reducing greenhouse gas emissions from the transportation sector.
The concept of nudging individuals instead of using stick-and-carrot regulations became a highly debated topic. Nudging seeks to improve individuals’ behaviour, making them more effective or efficient without restricting the choice set. A typical type of nudge is to provide information to an individual without forcing them to consult it. Applying it to private energy consumption decisions, previous research has shown that providing information may help reduce energy consumption. However, whether nudges alone, without financial incentives, improve workplace performance is not sufficiently researched yet, even though nudges are a very inexpensive way to influence behaviour. Previous results are not clear-cut.
We ran a field experiment with 104 truck drivers of a German logistics company and randomly assigned half of them to a control or a treatment group, respectively. The treatment group could receive information about the fuel-efficiency of their driving style. In contrast, the control group could not monitor their driving. Both groups have been observed for seven months. Our research shows that informing truck drivers with the help of an app on their firm mobile phones about their driving performance can increase their fuel-efficient driving significantly. This informative, digital nudge may thus be an inexpensive tool to motivate employees to be energy efficient at work.
Our conclusion: informational nudges helped to improve fuel efficiency. Giving drivers the chance to inform themselves about their driving style improves their performance significantly. Additionally, we can show that the impact of this app is sustainable. The results provide evidence for the effectiveness of informational nudges. Giving a treatment group of drivers the chance to see via app an evaluation of their driving style and its underlying reasoning significantly improves their performance compared with their performance during a control phase and compared to a control group. This result remains if we control for other impact factors, like work experience and more.
Studying the underlying mechanism in more detail, we find evidence that (1) previous performance has a convex impact on performance during the treatment phase in the treatment group and that (2) an app that informs about performance and underlying reasons improves the performance of initially bad drivers more than those of initially good drivers. We assume the latter happens because initially good drivers have fewer possibilities to increase their performance. Informing initially bad drivers about their performance and its reasons offers the possibility for comparably large marginal increases in performance. Moreover, good drivers may have already been intrinsically motivated to drive well. Their motivation is not crowded out by nudging as their performance remains high. On the contrary, individuals who were not intrinsically motivated to drive well improved their performance after informational nudging. Thus, our results reveal that not all employees reacted equally to nudges, but nudges do not harm individuals’ performance and do help some individuals. Treated drivers saved on average 2.09 € per week in fuel costs compared to their control phase. Taking performance increase in the control group into account, we find a net impact of about 0.4€ saved per 100 km. The reduction in fuel consumption is linearly related to CO2 emissions. Throughout our field experiment, average CO2 emissions were significantly reduced from 837.54 g/km to 792.83 g/km.
- This blog post is based on the authors’ research presented in August 2019 at the annual congress of the European Economic Association in Manchester, England.
- The post gives the views of its author(s), not the position of LSE Business Review or the London School of Economics.
- Featured image by DEZALB, under a Pixabay licence
- When you comment, you’re agreeing to our Comment Policy
Kirsten Thommes is professor of organisational behaviour at the University of Paderborn. She holds a PhD from the Friedrich Schiller University Jena. Her research focuses on organisational behaviour and identity, human-machine-interaction, teamwork and time preferences.
Christin Hoffmann is a postdoctoral researcher at the Brandenburg University of Technology in Cottbus. She holds a PhD from the University of Bern. Her research focuses on behavioural environmental economics.