The Longitudinal Effect of Digitally Administered Feedback on the Eco-Driving Behavior of Company Car Drivers

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

It is to study the eco-driving behavior by a longitudinal experiment, the data and process are also valuable for the similar researches, the results sound reasonable. However, this paper still has several problems to be published as follows,

1, The abstract is simple and not too clear in the description of contents and methods.

2, There is no clear conclusions not equaling to results.

3, Some photos are expected to display what is digital administered feedback system, software or device?

4, The eco-driving behaviors are better to be listed to help readers to understand this study well.

5, The title is not grammatical with two sentences.

6, There is no research framework to illustrate the logical arrangement clearly.

7, Table 1 can be transposed to let parameters on the head row. 

8, Author also needs to pay attention to other grammar, organization, and information expression issues by refering to other published papers.

Author Response

Thank you for taking the time to review our paper in-depth! In response to your comments, we attempted to embed the study better in existing (more recent) research on the topic. To illustrate, we added a new section in the new version of the manuscript text under the heading: 2. Embedding in recent literature on eco-driving. This section contains the following text:

 “In the global effort to combat climate change, the promotion of eco-driving emerges as a strategic avenue to reduce CO2 emissions. Fafoutellis, Mantouka, and Vlahogianni [14] offer a comprehensive overview, emphasizing eco-driving's multidimensional nature, encompassing driving behavior, route selection, and various choices influencing fuel consumption. This holistic perspective aligns with the broader sustainability goals of reducing the environmental footprint of individual vehicles. The critical analyses presented by Fafoutellis and colleagues [14] highlight the importance of a nuanced understanding of eco-driving practices, crucial for shaping policies that enhance both driver awareness and system performance in the pursuit of sustainable transportation. Collectively, these insights underscore eco-driving as a vital component of sustainable transportation, shedding light on diverse strategies and technological advancements that contribute to the broader agenda of reducing environmental impact. Within this landscape, the unique challenge posed by company car drivers (constituting a substantial market share), demands innovative solutions. Despite their significant impact on carbon emissions, company car drivers often lack financial incentives to adopt fuel-efficient and eco-friendly driving practices. The next section reviews literature examining the effectiveness of digitally administered feedback systems (in an eco-driving context), setting the stage for understanding the potential impact on eco-driving behavior.

Fafoutellis, Mantouka, and Vlahogianni [14] emphasize the importance of nuanced models for calculating fuel consumption and understanding the factors influencing them. Their work underscores the need for comprehensive insights into driving behaviors, laying a foundational understanding for evaluating the impact of digitally administered feedback systems on fuel efficiency. Coloma et al.'s [15] investigation into the environmental effects of eco-driving within courier delivery services sheds light on the challenges faced by professional drivers. Although the focus is on a different professional context, the study's findings suggest that time pressure and professional obligations may influence the effectiveness of eco-driving interventions. This prompts consideration of how such contextual challenges might impact the reception and efficacy of digitally administered feedback in professional driving settings. Günther, Kacperski, and Krems [16] delve into persuasive strategies for promoting eco-driving, specifically with battery electric vehicles (BEVs). While the study centers on BEV drivers, its findings on the impact of feedback, gamification, and financial rewards offer relevant insights for encouraging sustainable driving behaviors. The emphasis on real-world driving conditions aligns with the ecological validity sought in professional settings, mirroring the circumstances faced by company car drivers. Lin and Wang's [17] exploration of factors influencing drivers' intentions to practice eco-driving and their acceptance of eco-driving technology provides a theoretical framework. Integrating the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM), the study's insights guide the understanding of how digitally administered feedback may impact drivers' intentions and acceptance. This theoretical underpinning is instrumental in exploring the motivational factors shaping eco-driving behaviors. Alli-son and Stanton's [18], Sanguinetti et al. [19] and Picco et al. [20] emphasize feedback as a tool for reducing emissions from everyday driving behaviors. The focus on the maintenance of eco-driving behaviors provides a valuable perspective for evaluating the sustained impact of digitally administered feedback over time in professional driving settings.”

 

We also attempted to link the results more clearly with the conclusions (as suggested as a possible improvement point in the reviewer feedback received) by adding some paragraphs and extra text lines to the Discussion section. These relate our study and the key results to the questions that we raised in the introduction. One of these add-ons is depicted below:

 

“Informed by this context, this study addresses the often-overlooked group of company car drivers as a key target for promoting eco-driving practices. This group is crucial in the global effort to mitigate climate change. Employing a digital feedback and coaching system, we conducted a longitudinal field study with 327 participants. We monitored their driving behavior through a 'dongle' installed in company cars. Our results, analyzed using Structural Equation Modeling, reveal that the provision of digitally administered personal performance feedback significantly enhances eco-driving behavior both during and after the intervention, as indicated by increased eco-driving scores (see Results section). Surprisingly, the addition of social comparison elements to the feedback, such as comparisons with same car brand users, did not yield further improvements. The study makes a notable contribution to the eco-driving literature by shedding light on the effectiveness of personalized feedback for company car drivers, while also prompting a reflection on the unexpected ineffective-ness of social comparison information.”

 

In addition, we made adaptations considering other specific suggestions made. For example, we added some more depth/nuance to our abstract, and made a clear reference to “contents & methods used” in that abstract, as suggested. The latest version of our abstract is depicted below:

 

“In the global fight against climate change, stimulating eco-driving could contribute to the reduction of CO2 emissions. Company car drivers are a main target in this challenge as they represent a significant market share and are typically not motivated financially to drive more fuel efficiently (and thus more eco-friendly). As this target group has received little previous research attention, we examine whether digitally administered feedback & coaching systems can trigger such company car owners to drive eco-friendly. We do so by using respondents (employees of a financial services company (N = 327)) that voluntarily have a digital device (‘dongle’) installed in their company car, which monitors and records driving behavior-related variables.  In a longitudinal real-life field study, we communicate eco-driving recommendations (e.g., avoid harsh braking, accelerate gently, …) to the respondent drivers via a digital (computer) interface. Over a 21-week time frame (one block of seven weeks before the intervention, seven weeks of intervention, and seven weeks after the intervention), we test whether eco-driving recommendations in combination with personalized, graphical ‘eco-score index evolution’ feedback increase eco-driving behavior. We also experimentally evaluate the impact of adding social comparison elements to the feedback (e.g., providing feedback on a person’s eco-driving performance compared to that of same car brand users). Structural Equation Modeling (in MPlus 8.4) is used to analyze the data. Our results show that digitally administered personal performance feedback increases eco-driving behavior both during and after the feedback intervention. However, we do not observe increased effects when social comparison information is added to the feedback. As this latter element is surprising, we conclude with a reflection on possible explanations and suggest areas for future research. We contribute to the sustainable eco-driving literature by researching an under-studied group: company car drivers. More specifically, we contribute by demonstrating the effectiveness of digitally administered personal performance feedback on eco-driving for this group, and by observing and reflecting about the (in)effectiveness of feedback containing social comparison information.”

 

In response to another comment, we included a graphical depiction (as no actual photo materials are available) of the set-up that was used to communicate the eco-driving feedback. In this depiction we included the actual screen that the respondents saw during the experiment. In the manuscript the picture is accompanied by some clarification text lines to optimize the understanding of the study for the reader. Please find the graphical depiction in Figure 2 and the  accompanying text lines included below: 

“After a seven-week baseline measurement period, we experimentally assigned participants to a control condition (who only received tips and tricks on eco-driving; see Figure 1), an individual comparison feedback condition (who additionally received a weekly mail with their visually graphed eco-driving score over time), and three social comparison-oriented conditions who received a weekly mail with their visually graphed eco-driving score over time alongside a group-based average eco-driving score that served as a benchmark (see Figure 2 for an example).”

As a follow-up of another comment, we shortened the title (from 2 sentences to 1 sentence – as suggested). The title proposed in the latest version of our manuscript is “The longitudinal effect of digitally administered feedback on eco-driving behavior of company car drivers.”

We also transposed table 1 as suggested in the reviewer feedback (please refer to Table 1 in the revised manuscript).

Another feedback comment refers to listing the eco-driving behaviors. Apologies that it was unclear in the first version of our manuscript what the eco-driving behaviors are (or where to find these). The eco-driving behaviors are depicted in Figure 1 (i.e., Avoid idling; Avoid harsh braking, Accelerate quietly; Shift in a timely manner and drive in the highest gear possible; Avoid using your car for short trips; Drive with a constant and moderate speed; Anticipate traffic conditions and look as far ahead as possible (avoid unnecessary acceleration or braking); Shift between 2000-2500 revolutions/min; Decelerate smoothly by releasing the accelerator in time while leaving the car in gear (this is called ‘‘coasting”); If you are driving in traffic jam, leave as much space ahead of you as possible. This allows you to drive fluently; On flat, straight roads you can switch directly from first to third gear; accelerate quietly and avoid pushing the accelerator pedal more than halfway; Avoid maneuvers with a cold engine (park your car in the right direction…); When taking an exit, change lanes on time and adapt your speed).

In response to this comment, we made a more explicit reference to this section earlier on in the manuscript. See the introduction section, where we added the text bit “(see Figure 1 for an overview)”. Another reference to this figure is made in the Procedure section.

We are thankful for all the comments made. We believe that the suggestions helped us improve the quality of our manuscript.

Reviewer 2 Report

Comments and Suggestions for Authors

Dear authors

I am privileged to review your interesting research, which addresses how and whether digitally administered feedback systems can motivate company car owners to drive eco-friendly cars. This paper is of great value since it has done a longitudinal study with rigorous results. I would add some comments that hopefully help the authors improve their research. 

1- Abstract: I believe that the abstract is well-structured. Just one point I think is missing. I suggest you might add at the end how and where your research has added a new contribution. 

2- Introduction: I think it is too short. You need to substantiate your research problems. You have just explained the importance of your topic but, theoretically, it is not clear why we need this study and how it could add new knowledge to the past established literature. I think three paragraphs can be added here. One would be related to what we know from past research concerning the topic. The second relates to what we actually don't know. And the last one is how this research would add to the past body of research. 

3- Disclaimer: I'm a qual researcher, so I have not commented on your method and results sections. 

4- Discussion: I believe this part is also too short. You need to find the key aspects where your results would complete or contrast previous studies. Then, you need to clearly map out how theoretically this study has added to a new way of understanding your topic. 

 

 

Author Response

Thank you for the kind words that mention the appreciation of our work. In response to one comment made we added (in the abstract) what the contribution is of the research. The abstract was also extended considering comments of another reviewer. This is the latest version of the abstract:

“In the global fight against climate change, stimulating eco-driving could contribute to the reduction of CO2 emissions. Company car drivers are a main target in this challenge as they represent a significant market share and are typically not motivated financially to drive more fuel efficiently (and thus more eco-friendly). As this target group has received little previous research attention, we examine whether digitally administered feedback & coaching systems can trigger such company car owners to drive eco-friendly. We do so by using respondents (employees of a financial services company (N = 327)) that voluntarily have a digital device (‘dongle’) installed in their company car, which monitors and records driving behavior-related variables.  In a longitudinal real-life field study, we communicate eco-driving recommendations (e.g., avoid harsh braking, accelerate gently, …) to the respondent drivers via a digital (computer) interface. Over a 21-week time frame (one block of seven weeks before the intervention, seven weeks of intervention, and seven weeks after the intervention), we test whether eco-driving recommendations in combination with personalized, graphical ‘eco-score index evolution’ feedback increase eco-driving behavior. We also experimentally evaluate the impact of adding social comparison elements to the feedback (e.g., providing feedback on a person’s eco-driving performance compared to that of same car brand users). Structural Equation Modeling (in MPlus 8.4) is used to analyze the data. Our results show that digitally administered personal performance feedback increases eco-driving behavior both during and after the feedback intervention. However, we do not observe increased effects when social comparison information is added to the feedback. As this latter element is surprising, we conclude with a reflection on possible explanations and suggest areas for future research. We contribute to the sustainable eco-driving literature by researching an under-studied group: company car drivers. More specifically, we contribute by demonstrating the effectiveness of digitally administered personal performance feedback on eco-driving for this group, and by observing and reflecting about the (in)effectiveness of feedback containing social comparison information.” 

In response to another comment, we re-wrote (and lengthened) the introduction section. In the new version, we attempted to include the suggested 3-paragraph structure (including a more clear indication of the research gap that needs to be filled ,and explicitly mentioning how our research contributes to addressing that gap). This is the latest version of the Introduction:

“The urgency of finding strategies to protect the natural environment has become increasingly evident in the past decades [1-2]. A key environmental issue pertains to air pollution and its negative climate change effects. Air pollution is one of the greatest challenges for business and society [3] and has been identified as the single largest environmental health risk globally by the World Health Organization (WHO) [4]. Thus, it is not surprising that climate change as a result of human caused greenhouse gas emissions is high on the policy and research agenda [5-8]. In the global fight against air pollution and its negative climate change effects, the large-scale adoption of eco-driving can be a contributor. Prior literature has stressed that eco-driving can reduce fuel consumption by 10%, on average and over time, thereby reducing CO2 emissions from driving by an equivalent percentage [9]. Eco-driving is defined as the implementation of ecologically beneficial driving techniques like keeping the speed down; efficient gear shifting; anticipatory, calm, and steady driving; and efficient braking [10]. Apart from reducing air pollution and greenhouse gas emissions, eco-driving has other beneficial effects such as improving road safety and reducing fuel costs [9,11-12]. In the automotive market, company car drivers are an important target. They compose a significant part of the market in some geographical areas. For ex-ample, they account for 11% of all cars in the Netherlands, and more than double that in Belgium [13]. Importantly, as many company car drivers (vs private car drivers) can use fuel (payment) cards provided by their employer, they are not financially motivated to drive more fuel efficiently (and therefore eco-friendly).

More research is needed to better understand how societies can achieve large-scale adoption of eco-driving. This probably requires education efforts and social norm reinforcement [9]. Digitally administered driving feedback systems may be help-ful to contribute to this objective and speed up the process, but it remains unclear how feedback influences eco-driving in a setting where drivers have no financial stake in reducing their fuel consumption. It is also unknown to what extent adding social comparison elements may be helpful to obtain eco-driving-increasing effects. Whether, and if so, how feedback (provided by digitally administered systems) can trigger eco-driving in such a context is an understudied literature area. As to the ‘how’, assessing the extent to which specific social comparison elements (e.g., comparisons of eco-driving performance with that of same car brand users) is an area of research that can contribute to the existing literature. To address these knowledge gaps, this study focuses on company car drivers and examines the effect of digitally administered tips and feedback on eco-driving behavior (see Figure 1 for an overview). While doing so, we also test the effectiveness of different social comparison feedback set-ups (e.g., comparisons of eco-driving performance with that of same car brand users). We do this by using a pool of company car owners (whose fuel is paid for by the company) that take part in a real-life field study over the span of multiple weeks. With this approach we aim to contribute to the literature in at least two important ways. First, we evaluate the effectiveness of providing digitally administered feedback on real-life longitudinal eco-driving performance in a field study. Second, we compare the effectiveness of different socially comparative framings, thus also contributing to the literature that studies the influence of social comparison on pro-environmental behavior.”

Finally, we also re-wrote (and lengthened) the Discussion section as proposed. Specifically, we attempted to elaborate more on how the proposed study contributes to understanding the topic studied as suggested. This is the latest version of the Discussion:

“6.1 Main Observations

In the face of escalating environmental challenges (particularly the adverse effects of air pollution and climate change), the promotion of eco-driving has emerged as a strategic imperative for mitigating the impact of human-caused greenhouse gas emissions. This study, situated within the broader context of sustainable transportation, addresses a critical gap in the existing literature by focusing on company car drivers. Whereas some recent existing literature starts from the perspective of the type of vehicle (e.g., connected and automated vehicles [63] or Battery electric vehicles [64]), this study starts from the perspective of a specific group of drivers: company car users. This is a significant yet often overlooked segment of the automotive market. The literature review underscores the importance of eco-driving as a multifaceted approach, encompassing driving behaviors, route selection, and choices influencing fuel consumption. Previous research has demonstrated that eco-driving not only reduces air pollution and greenhouse gas emissions but also enhances road safety and reduces fuel costs. However, company car drivers, who play a pivotal role in carbon emissions, are less incentivized to adopt eco-friendly practices due to the availability of employer-provided fuel cards.

Informed by this context, this study addresses the often-overlooked group of company car drivers as a key target for promoting eco-driving practices. This group is crucial in the global effort to mitigate climate change. Employing a digital feedback and coaching system, we conducted a longitudinal field study with 327 participants. We monitored their driving behavior through a 'dongle' installed in company cars. Our results, analyzed using Structural Equation Modeling, reveal that the provision of digitally administered personal performance feedback significantly enhances eco-driving behavior both during and after the intervention, as indicated by increased eco-driving scores (see Results section). Surprisingly, the addition of social comparison elements to the feedback, such as comparisons with same car brand users, did not yield further improvements. The study makes a notable contribution to the eco-driving literature by shedding light on the effectiveness of personalized feedback for company car drivers, while also prompting a reflection on the unexpected ineffective-ness of social comparison information.

The main research goal was to investigate (1) whether personal comparison feedback could enhance drivers' eco-driving scores, and if so, (2) whether adding a social comparison element would further boost feedback effectiveness. After a seven-week baseline measurement period, we experimentally assigned participants to a control condition (who only received tips and tricks on eco-driving; see Figure 1), an individual comparison feedback condition (who additionally received a weekly mail with their visually graphed eco-driving score over time), and three social comparison-oriented conditions who received a weekly mail with their visually graphed eco-driving score over time alongside a group-based average eco-driving score that served as a benchmark (see Figure 2 for an example). As hypothesized (H1), the main results indicate that providing personal comparison feedback by email on a weekly basis has a positive impact on the aggregate eco-driving score observed in our study. An interesting add-on observation is that the increase in average eco-scores during the seven-week intervention period also persisted in a seven-week post-intervention period (compared to the seven-week baseline measurement period). Such an increase was not observed in the control condition and can therefore not be attributed to unintended external events or circumstances. Counter to expectations, adding a social comparison layer to the feedback does not result in a significant additional effect. This is a different result than hypothesized (H2 is not supported). Below we reflect on possible explanations for this unexpected observation. We also address related limitations and formulate areas for future research.

6.2 Reflections, limitations, applications and future research suggestions

The experimental set-up did not include gamification elements like leader boards. Previous research has demonstrated the impact of such elements [21,65-67]. In our study these elements were deliberately left out to have a clean manipulation. However, they may be more important than initially expected for triggering social comparison effects. Possibly the social comparison feedback format may have been insufficiently engaging to facilitate such a mechanism. This may be an element to consider in future research. Another reflection about the absence of a social comparison effect focuses on a possible mindset misfit. Intuitively, one might argue that a pro-social, environmentally beneficial mindset does not fit with a pro-self, social comparison-based competitive mindset. However, earlier research has suggested that pro-selves act more sustainably in a competitive setting, than in a non-competitive setting, whereas pro-socials act sustainably, independent of competition; as a result, the net effect of social comparison-based competition should still be positive [68]. Still, future research could explore whether a more inclusive type of social comparison framing shows better results. A final thought centers around who the other party is in a social comparison frame. We experimented with a “peers” set-up (i.e., those driving the same car brand, those driving a similar engine car). However, Merrikhpour and Donmez [69] demonstrated that comparing one’s behavior with a “close important other” can be very effective in steering eco-driving behavior. Close or important others are for example a person’s friends or family. Exploring in what way such a set-up could be translated to a digital interface context, and next testing it – could be a research avenue to further look into.

Despite these limitations, and in addition to the future research suggestions offered, we also want to stress some possible application domains of the research findings at hand. Specifically, we believe that there are hands-on learnings in the context of the development of feedback technologies for drivers that aim to encourage an eco-driving style. Specifically, we advance that developing digitally-administered feedback systems is valuable to motivate company car drivers (that have no financial incentive to drive in a more sustainable way) to adopt eco-driving.  Inspiration is also offered (indicating what might work and what not) regarding motivational programs for fleet managers of company vehicles. Although the use of social comparison mechanisms (e.g., how do you perform compared to the average brand x car driver in eco-driving? Or how do you score in terms of eco-driving compared to those that drive a technically similar car?) feel intuitively promising, our study does not demonstrate an increased effect on eco-driving behavior.  Finally, applications in the domain of environmental protection policy and ecological education can also be derived from our study. For example, including gamification elements (missing in our study) may be a truly valuable element to include in real-life executions. Another context factor (not tested in our study) is to have a frame where a comparison is made with ‘close important ones’.”

We are thankful for all the suggestions. We hope acting on these has improved the quality of our manuscript.

Reviewer 3 Report

Comments and Suggestions for Authors

The only thing I have to notice about this material, which is personally very interesting to me, is that the literature base is relatively outdated - I don't see that the calls from the last century are so important, that there are no newer and more relevant ones. Eco-friendly behavior is examined, which seems to me to be a hit now. Why isn't literature like that? Or maybe I'm wrong...

Author Response

Thank you for making the effort to review our manuscript. In response to your comments, we updated the literature referenced and added more recent references. These are the references that were added in the latest version of the manuscript (listed in alphabetical order):

 

 

• Allison, C. K., & Stanton, N. A. Eco-driving: The role of feedback in reducing emissions from everyday driving behaviors. Theoretical Issues in Ergonomics Science, 2019, 20(2), 85-104. DOI: 10.1080/1463922X.2017.1363519
• Chadaa, S.K., Görgesa, D., Ebertb, A., Teutschc, R. and Subramany, S. P. Evaluation of the Driving Performance and User Acceptance of a Predictive Eco-Driving Assistance System. Transportation Research Part C Emerging Technologies 2023, 153, 104193-104217. DOI:10.1016/j.trc.2023.104193
• Coloma, J. F., García, M., Fernández, G., & Monzón, A. Environmental effects of eco-driving on courier delivery. Sustainability 2021, 13(3), 1415-1436. DOI: 10.3390/su13031415
• Degirmenci, K, Breitner, M. H. Gamification and sensory stimuli in eco-driving research: A field experiment to reduce energy consumption in electric vehicles. Transportation Research Part F: Psychology and Behaviour 2023, 92, 266-282. DOI:10.1016/j.trf.2022.10.014
• Fafoutellis, P., Mantouka, E. G., & Vlahogianni, E. I. Eco-driving and its impacts on fuel efficiency: An overview of technologies and data-driven methods. Sustainability 2021, 13(1),226-242. DOI:10.3390/su13010226
• Günther, M., Kacperski, C., & Krems, J. F. Can electric vehicle drivers be persuaded to eco-drive? A field study of feedback, gamification, and financial rewards in Germany. Energy Research & Social Science 2020, 63(11), 101407-101415. DOI: 10.1016/j.erss.2019.101407
• Kramer, J., Riza, L., & Petzoldt, T. Carbon savings, fun, and money: The effectiveness of multiple motives for eco-driving and green charging with electric vehicles in Germany. Energy Research & Social Science, 2023, 99, 103054-103068. DOI: 10.1016/j.erss.2021.101054
• Li, J., Fotouhi, A., Liu, Y., Zhang, Y., & Chen, Z. Review on eco-driving control for connected and automated vehicles. Renewable and Sustainable Energy Reviews 2024, 189, 114025-114.061. DOI:10.1016/j.rser.2021.114025
• Lin, R., & Wang, P. Intention to perform eco-driving and acceptance of eco-driving system. Transportation Research Part A: Policy and Practice 2022, 166, 444-459. DOI: 10.1016/j.tra.2021.12.018
• Sanguinetti, A., Queen, E., Yee, C., & Akanesuvan, K. Average impact and important features of onboard eco-driving feedback: A meta-analysis. Transportation Research Part F: Traffic Psychology and Behaviour 2020, 70, 1-14. DOI: 10.1016/j.trf.2020.01.001
• Stephens, R. A review of gamified approaches to encouraging eco-driving. Frontiers in Psychology 2022, 13, 970851-970862. DOI:10.3389/fpsyg.2022.97085
• Picco, A., Stuiver, A., de Winter, J., de Waard, D. The use of monitoring and feedback devices in driving: An assessment of acceptability and its key determinants, Transportation Research Part F: Traffic Psychology and Behaviour 2023, 92, 1-14. DOI:10.1016/j.trf.2022.10.021

 

 

We also attempted to link the results more clearly with the conclusions (as suggested as a possible improvement point in the reviewer feedback received) by adding some paragraphs and extra text lines to the Discussion section. These relate our study and the key results to the questions that we raised in the introduction. One of these add-ons is depicted below:

 

“Informed by this context, this study addresses the often-overlooked group of company car drivers as a key target for promoting eco-driving practices. This group is crucial in the global effort to mitigate climate change. Employing a digital feedback and coaching system, we conducted a longitudinal field study with 327 participants. We monitored their driving behavior through a 'dongle' installed in company cars. Our results, analyzed using Structural Equation Modeling, reveal that the provision of digitally administered personal performance feedback significantly enhances eco-driving behavior both during and after the intervention, as indicated by increased eco-driving scores (see Results section). Surprisingly, the addition of social comparison elements to the feedback, such as comparisons with same car brand users, did not yield further improvements. The study makes a notable contribution to the eco-driving literature by shedding light on the effectiveness of personalized feedback for company car drivers, while also prompting a reflection on the unexpected ineffective-ness of social comparison information.”

 

We are thankful for all observations. We actively considered these to attempt to improve the quality of our manuscript.

Reviewer 4 Report

Comments and Suggestions for Authors

Dear Authors,

Thank you very much for the interesting article. I read it with great interest. Taking up a topic related to the fight against climate change is always worthy of recognition. Every attempt to identify a way to reduce CO2 emissions is extremely important for the modern world. Therefore, I rate the topic of the article highly and consider it important and original.

The methodology adopted by the authors constitutes a great scientific value of the article. Experiment as a research method provides reliable results and inspires further research. I appreciate the authors' effort in planning and implementing experimental research.

The research hypotheses put forward by the authors and the results enabling their confirmation/rejection are cognitively valuable. The authors skillfully refer to the obtained results.

The article is very useful. The results obtained by the authors have a wide range of applications (environmental protection policy, ecological education, feedback technologies for drivers about driving style, motivational programs for fleet managers of company vehicles and others). However, the authors did not indicate the directions of use of their research. In this aspect, it is necessary to complete the text.

The number of literature items seems to be a bit too small for the magazine's standards.

Best regards!

Author Response

Thank you for the kind words mentioned in your reviewer feedback. We are glad to learn that you appreciate our research. In response to your comments made, we added some sentences that indicate the directions of use of the research that were suggested in the revision notes (i.e., environmental protection policy, ecological education, feedback technologies for drivers about driving style, motivational programs for fleet managers of company vehicles). Specifically, we added the following was in the Discussion section:

 

“Despite these limitations, and in addition to the future research suggestions offered, we also want to stress some possible application domains of the research findings at hand. Specifically, we believe that there are hands-on learnings in the context of the development of feedback technologies for drivers that aim to encourage an eco-driving style. Specifically, we advance that developing digitally-administered feedback systems is valuable to motivate company car drivers (that have no financial incentive to drive in a more sustainable way) to adopt eco-driving. Inspiration is also offered (indicating what might work and what not) regarding motivational programs for fleet managers of company vehicles. Although the use of social comparison mechanisms (e.g., how do you perform compared to the average brand x car driver in eco-driving? Or how do you score in terms of eco-driving compared to those that drive a technically similar car?) feel intuitively promising, our study does not demonstrate an increased effect on eco-driving behavior.  Finally, applications in the domain of environmental protection policy and ecological education can also be derived from our study. For example, including gamification elements (missing in our study) may be a truly valuable element to include in real-life executions. Another context factor (not tested in our study) is to have a frame where a comparison is made with ‘close important ones’.”

 

We also increased the number of literature citations and the accompanying literature list. We specifically attempted to integrate some more recent, relevant literature references. These are the references that were added in the latest version of the manuscript (listed in alphabetical order):

• Allison, C. K., & Stanton, N. A. Eco-driving: The role of feedback in reducing emissions from everyday driving behaviors. Theoretical Issues in Ergonomics Science, 2019, 20(2), 85-104. DOI: 10.1080/1463922X.2017.1363519
• Chadaa, S.K., Görgesa, D., Ebertb, A., Teutschc, R. and Subramany, S. P. Evaluation of the Driving Performance and User Acceptance of a Predictive Eco-Driving Assistance System. Transportation Research Part C Emerging Technologies 2023, 153, 104193-104217. DOI:10.1016/j.trc.2023.104193
• Coloma, J. F., García, M., Fernández, G., & Monzón, A. Environmental effects of eco-driving on courier delivery. Sustainability 2021, 13(3), 1415-1436. DOI: 10.3390/su13031415
• Degirmenci, K, Breitner, M. H. Gamification and sensory stimuli in eco-driving research: A field experiment to reduce energy consumption in electric vehicles. Transportation Research Part F: Psychology and Behaviour 2023, 92, 266-282. DOI:10.1016/j.trf.2022.10.014
• Fafoutellis, P., Mantouka, E. G., & Vlahogianni, E. I. Eco-driving and its impacts on fuel efficiency: An overview of technologies and data-driven methods. Sustainability 2021, 13(1),226-242. DOI:10.3390/su13010226
• Günther, M., Kacperski, C., & Krems, J. F. Can electric vehicle drivers be persuaded to eco-drive? A field study of feedback, gamification, and financial rewards in Germany. Energy Research & Social Science 2020, 63(11), 101407-101415. DOI: 10.1016/j.erss.2019.101407
• Kramer, J., Riza, L., & Petzoldt, T. Carbon savings, fun, and money: The effectiveness of multiple motives for eco-driving and green charging with electric vehicles in Germany. Energy Research & Social Science, 2023, 99, 103054-103068. DOI: 10.1016/j.erss.2021.101054
• Li, J., Fotouhi, A., Liu, Y., Zhang, Y., & Chen, Z. Review on eco-driving control for connected and automated vehicles. Renewable and Sustainable Energy Reviews 2024, 189, 114025-114.061. DOI:10.1016/j.rser.2021.114025
• Lin, R., & Wang, P. Intention to perform eco-driving and acceptance of eco-driving system. Transportation Research Part A: Policy and Practice 2022, 166, 444-459. DOI: 10.1016/j.tra.2021.12.018
• Sanguinetti, A., Queen, E., Yee, C., & Akanesuvan, K. Average impact and important features of onboard eco-driving feedback: A meta-analysis. Transportation Research Part F: Traffic Psychology and Behaviour 2020, 70, 1-14. DOI: 10.1016/j.trf.2020.01.001
• Stephens, R. A review of gamified approaches to encouraging eco-driving. Frontiers in Psychology 2022, 13, 970851-970862. DOI:10.3389/fpsyg.2022.97085
• Picco, A., Stuiver, A., de Winter, J., de Waard, D. The use of monitoring and feedback devices in driving: An assessment of acceptability and its key determinants, Transportation Research Part F: Traffic Psychology and Behaviour 2023, 92, 1-14. DOI:10.1016/j.trf.2022.10.021

 

Thank you for making the effort to review our manuscript. We believe your comments and those of the other reviewers helped us to improve the quality of our manuscript.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Table A1 should be listed better with two parts or  horizontal arrangement.

Figure 3 should be more accurate in pdf format.

Reviewer 2 Report

Comments and Suggestions for Authors

Congratulation! Your paper has improved a lot and is ready to gets published.