| Literature DB >> 35720807 |
Karolin Schmidt1, Theresa Sieverding1, Hannah Wallis1, Ellen Matthies1.
Abstract
The mobility sector was one of the sectors most affected by COVID-19 and its political restrictions, with, inter alia a huge drop in mobility behavior due to travel bans, lockdowns, and a reduced need to be mobile. The present study examined the potential of COVID-19 restrictions aiming at containing the spread of the virus to be a window of opportunity for the transition toward sustainable mobility by breaking up strongly habitualized daily and travel mobility behaviors through changes of behavioral contexts. We conducted an online survey in a sample representative for the German population (N = 3092) to study the consequences of the COVID-19 restrictions on Germans' daily and travel mode choices and on their wishes for future mobility. Furthermore, we examined the moderating effects of Germans' personal norms to protect the climate on changes in their mobility behavior toward sustainable mobility, both within and beyond the corona pandemic. In line with previous research, the present study shows an overall reduction of mobility across almost all modes of transport for daily and travel mobility during time periods of COVID-19 restrictions compared to pre-COVID-19-times, with different transport modes being affected differently. Our findings additionally point out the relevance of personal norms to protect the climate for the transition toward sustainable mobility behavior. Altogether, the present study provides first empirical evidence for the corona pandemic to represent a window of opportunity for the transition toward sustainable mobility. Furthermore, the study also points out relevant directions for further research.Entities:
Keywords: COVID-19; Climate protection; Habits; Mobility behavior; Personal norms; Sustainability
Year: 2021 PMID: 35720807 PMCID: PMC9188437 DOI: 10.1016/j.trip.2021.100374
Source DB: PubMed Journal: Transp Res Interdiscip Perspect ISSN: 2590-1982
Sociodemographic features of the final sample (N = 3092), compared to the German population (Kunst, 2020; Statistisches Bundesamt, 2020a, Bundesamt, 2020b, Bundesamt, 2020c, Bundesamt, 2021).
| Sample | German population | ||
|---|---|---|---|
| Age | |||
| Gender | Female | 50.5% | 50.6% |
| Male | 49.2% | 49.4% | |
| Highest education level | School was not finished | 0.4% | 4.0% |
| School was finished | 31.5% | 29.6% | |
| Secondary education | 30.8% | 23.3% | |
| Higher education entrance qualification | 37.2% | 32.5% | |
| Income | < €900 | 7.2% | |
| €900 - €1300 | 8.0% | ||
| €1301 - €1500 | 5.4% | ||
| €1501 - €2000 | 9.4% | ||
| €2001 - €2600 | 14.4% | ||
| €2601 - €4000 | 27.7% | ||
| > €4000 | 28% | ||
| Number of inhabitants per place of residence | < 5000 | 17.5% | – |
| 5000–15000 | 16.1 | – | |
| 15000–50000 | 21.2 | – | |
| 50000–100000 | 10.9% | – | |
| 100,000 and more | 34.3 | – | |
| Car availability | – | 81%* |
Items assessing frequencies of use of different modes of transport for daily and travel mobility during several time periods.
| Daily mobility | 8 | Please think about the last three months [the last 12 months]. Please state how frequently you used following means of transport:Please think about the next 12 months. State how frequently you will use the following means of transport. | a bike a car a carsharing vehicle a bus, tram, or train in your region ways exclusively by foot the train for single distances above 100 km the bus for single distances above 100 km | Daily use / nearly daily use; 1–3 days per week; 1–3 days per month; less then monthly; never/ nearly never |
| Travel mobility | Please think about the last three months [the last 12 months]. Please state how frequently you used a plane | At least once a month; at least once every 2–6 month; at least every 6–12 month; less often; never | ||
| Please think about the next 12 months. State how often you intend to take a plane. | At least once a month; at least once every 2–6 month; at least every 6–12 month; less often; never | |||
Items assessing participants’ wishes for future mobility based on the survey conducted by Acatech (2019).
| Variable | Number of items | Items | Answer options |
|---|---|---|---|
| Wishes for future mobility | 11 | What would you like to change about your mobility? | I would like to spend less money on my mobility. |
Items used to examine the effects of external factors possibly related to political COVID-19 restrictions on higher frequencies of bike use during times of COVID-19 restrictions (i.e., April – June 2020) compared to the same time period in 2019.
| Higher frequencies of bike use during times of COVID-19 restrictions (i.e., April – June 2020) compared to the same time period in 2019 | 1 | To what extend do you agree with the following statements? During the last three months I have ridden the bike more than in the same period last year. | Do not agree at all (1) to completely agree (7), I dońt know |
| Possible reasons for higher frequencies of bike use | 8 | Here you find a list of possible reasons that could play a potential role to use the bike more often. Please state how the following reasons are relevant for you. I felt safer on the streets. There were fewer cars on the road. Others used the bike more often as well. I could use more bike paths. The air quality was better. I would like to be on the move more environmentally friendly. I had more time at hand. I drove more often to destinations in closer proximity. | Do not agree at all (1) to completely agree (7), I dońt know |
| Perceived ease-of-bike use | 3 | It is easy for me to us the bike instead of the car. I made good experiences by taking the bike instead of the car. I am confident that I can get many things done by using the bike instead of the car. | Do not agree at all (1) to completely agree (7), I dońt know |
Items used to examine the effects of external factors possibly related to political COVID-19 restrictions on decreased intentions to fly in 2020 compared to 2019.
| Decreased intentions to fly in 2020 compared to 2019 | 1 | To what extend do you agree with the following statements? In comparison to 2019 I intend to fly less this year. | Do not agree at all (1) to completely agree (7), I dońt know |
| Potential reasons for a decreased intention to fly | 9 | Here you find a list of reasons that could play a potential role for flying less. Please state how the following reasons are relevant for you. There are attractive travel destinations nearby / in Germany as well. Long-distance travels seem financially too risky. I would like to travel more environmentally friendly. I want to support the German tourism sector. Long-term planning of trips seems difficult to me. I am afraid of being stranded in a foreign country with no guarantee to get back to Germany. The prices for long-distance travel are too high. Ím not sure whether I can take out a travel insurance / my travel health insurance would cover expenses abroad. | Do not agree at all (1) to completely agree (7), I dońt know |
| Perceived ease-of-flight avoidance | 3 | I can definitely imagine to avoid flying. I am certain that I can travel without flying. It is easy for me to give up flying. | Do not agree at all (1) to completely agree (7), I dońt know |
Items used to assess participants’ personal norms to protect the climate.
| Personal norms to protect the climate | 3 | To which extend do you agree with the following statements? Based on my personal values, I feel obligated to engage politically for the climate protection On the basis of my personal values, I feel obligated to contribute to the protection of the climate through my daily behavior. No matter what others expect from me, I feel obligated to contribute to climate protection by changing my lifestyle. | Do not agree at all (1) to completely agree (7), I dońt know |
Comparisons of frequency of use of different transport modes for daily and travel mobility during periods of COVID-19 restrictions (April – June 2020) and pre-COVID-19-times.
| Mode of Transport | Difference between the frequency of use during the past 12 months and the frequency of use during periods of political COVID-19 restrictions (April – June 2020) | |||
|---|---|---|---|---|
| Amount of positive differences | Amount of negative differences | |||
| Bike | 349 | 250 | 3.791 | <0.001*** |
| Car | 364 | 136 | 9.401 | <0.001*** |
| Public transportation | 611 | 297 | 11.082 | <0.001*** |
| By foot | 275 | 366 | −4.819 | <0.001*** |
| Long-distance train | 376 | 189 | 7.940 | <0.001*** |
| Remote bus | 166 | 61 | 6.981 | <0.001*** |
| Carsharing | 95 | 50 | 4.018 | <0.001*** |
| Plane | 119 | 0 | 9.637 | <0.001*** |
Fig. 1Wishes for future mobility in 2019 and in 2020 by comparison.
Results of multiple regression analyses of the external factors (independent variables) on higher frequencies of use of bikes during periods of COVID-19 restrictions (April – June 2020) compared to the same period in 2019 (dependent variable) – depending on personal norms to protect the climate.
| Personal norms to protect the climate | Explained variance | Independent variables | ß | ||
|---|---|---|---|---|---|
| Low | 1090 | 29.8% | Age | -0.06 | <0.03* |
| Gender | 0.04 | n.s. | |||
| Education | 0.06 | <0.03* | |||
| Perceived ease-of-bike use | 0.22 | <0.001*** | |||
| Perceived safety in traffic | -0.05 | n.s. | |||
| Fewer cars | -0.03 | n.s. | |||
| Perception of others riding the bike | 0.11 | <0.01** | |||
| More bike paths available | -0.01 | n.s. | |||
| More time | 0.07 | <0.05* | |||
| Destinations in close proximity | 0.33 | <0.001*** | |||
| High | 1317 | 33.0% | Age | -0.03 | n.s. |
| Gender | 0.02 | n.s. | |||
| Education | 0.05 | n.s. | |||
| Perceived ease-of-bike use | 0.18 | <0.001*** | |||
| Perceived safety in traffic | 0.07 | <0.02* | |||
| Fewer cars | -0.04 | n.s. | |||
| Perception of others riding the bike | 0.04 | n.s. | |||
| More bike paths available | 0.06 | n.s. | |||
| More time | 0.14 | <0.001*** | |||
| Destinations in close proximity | 0.28 | <0.001*** |
Results of multiple regression analyses of the external factors (independent variables) on participants’ decreased intention to fly in 2020 compared to 2019 (dependent variable) – depending on personal norms to protect the climate.
| Personal norms to protect the climate | Explained variance | Independent variables | ß | ||
|---|---|---|---|---|---|
| Low | 1030 | 15.8% | Age | 0.04 | n.s. |
| Gender | -0.02 | n.s. | |||
| Education | 0.05 | n.s. | |||
| Perceived ease-of-flight avoidance | 0.22 | <0.001*** | |||
| Attractive travel destinations nearby / in Germany | 0.01 | n.s. | |||
| Perceived safety in Germany | 0.06 | <0.05* | |||
| Financial risks of travelling far | 0.07 | n.s. | |||
| Supporting the German tourism sector | 0.03 | n.s. | |||
| Difficulties to plan trips long-term | 0.04 | n.s. | |||
| Fear of not getting home from a foreign country | 0.19 | <0.001*** | |||
| Costs to travel far are too high | -0.10 | <0.01** | |||
| Travel insurance and health insurance abroad | 0.08 | <0.02* | |||
| High | 1236 | 12.6% | Age | 0.07 | <0.03* |
| Gender | -0.01 | n.s. | |||
| Education | 0.04 | n.s. | |||
| Perceived ease-of-flight avoidance | 0.21 | <0.001*** | |||
| Attractive travel destinations nearby / in Germany | - 0.07 | <0.04* | |||
| Perceived safety in Germany | 0.03 | n.s. | |||
| Financial risks of travelling far | 0.10 | <0.01** | |||
| Supporting the German tourism sector | 0.11 | <0.01** | |||
| Difficulties to plan trips long-term | 0.11 | <0.01** | |||
| Fear of not getting home from a foreign country | 0.07 | n.s. | |||
| Costs to travel far are too high | -0.02 | n.s. | |||
| Travel insurance and health insurance abroad | -0.01 | n.s. |
Comparisons of frequencies of use of transport modes for daily and travel mobility between the past 12 months and the intended frequencies of use in the next 12 months – depending on personal norms to protect the climate.
| Personal norms to protect the climate | Type of Transport | Difference between intended frequencies of use for the next 12 months – frequencies of use during the past 12 months | ||||
|---|---|---|---|---|---|---|
| Amount of positive differences | Amount of negative differences | |||||
| Low | 1437 | Bike | 431 | 44 | 16.91 | <0.001*** |
| Car | 91 | 210 | −5.534 | <0.001*** | ||
| Public transport | 167 | 209 | −2.728 | <0.01** | ||
| Plane | 289 | 169 | 4.536 | <0.001*** | ||
| High | 1593 | Bike | 516 | 45 | 18.185 | <0.001*** |
| Car | 79 | 340 | −11.604 | <0.001*** | ||
| Public transport | 280 | 241 | 1.375 | <0.17 | ||
| Plane | 312 | 259 | 1.403 | <0.16 | ||