staff travel survey

How to run an employee travel survey

How do employees get to and from your workplace? Are people interested in walking, riding a bike or catching public transport more? Is your active transport effort making a difference?

An employee travel survey is a good way to answer these questions and others. Your Move offers an online survey tool to make it easy to run a survey with employees at your workplace. With the results you can make informed choices about what activities to run and assess the effect on employee travel.

Things to consider:

• Can all employees be sent a link to the survey and complete it online? Are there some employees who might need a printed version or other help to be included?
• What would encourage employees to take part? Having the right person promote the survey or offering an incentive (e.g. chance to win a shopping or café voucher) could boost participation. The more the better to help make the survey results representative of the workforce.
• When promoting the survey, what communications channels would work best? It might be an email to all employees at your site or an intranet article or posters in the kitchen or mention at team meetings.
• What do you want to find out? Check the questions included in the Your Move survey. Are there others you want to add? Remember not to make the survey too long or complex as this can discourage people.
• If you want to cover more than one site or compare results for different business units or roster patterns, you could have a separate survey for each site or include questions so you can segment responses.
• Run the survey in a typical work period and at a time of year when you could run it again in 12 months. Avoid school holidays and hot or wet weeks.

There may be other ways to seek input from staff or see how they are commuting, and using more than one method can provide better information for decisions or reporting your impact.

Check out the survey tool here . If you need help with the survey or other data gathering contact the Your Move team.

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Employee Travel Survey

As part of the ongoing monitoring and review programme, it is essential for an Employee Travel Survey to be undertaken every year to assess the progress of the Travel Plan.

This Sample Employee Travel Survey offers you a template for conducting your own survey.

The sample survey attached includes personal information questions (gender and age). These are not strictly necessary but can be a helpful check to make sure that responses are representative of the whole organisation. Having the personal information included can also help you to be more targeted with your marketing by identifying groups of employees who are showing interest in a particular measure.

It's worth making sure that you send any Employee Travel Survey out with a covering letter to set the context of the survey. It should be signed by a Senior Manager, have a contact name for any queries and also highlight any incentive that you are offering for completion of the survey. This Sample Covering Letter provides you with a template.

Depending on the size and geographic spread of your workforce, you might decide to run the survey online rather than paper based. If you decide to run an online survey, visit www.surveymonkey.com   where you can build your own online survey. They offer various packages, from a FREE standard questionnaire template, to a monthly fee package which allows you to design and brand your own questionnaire, including as many questions as you wish.

It's also worth noting that all surveys should be conducted in accordance with the Data Protection Act. The Act exists to prevent data collected from people being used for purposes other than that for which it was given. For example, guidance states that:

Personal data shall not be used or disclosed in any manner incompatible with the purpose for which it is collected.

If the respondent has given permission for data to be passed on in a form which allows for the respondent to be identified personally, the respondent must have first been told to whom the information will be supplied and the purposes for which it will be used.

If the data contains addresses it should also state who the results might be given to for various purposes.

For employees joining a car-sharing scheme, the information might be passed on to a company who will organise it.

Adaptable Travel Plan Template - Ready for you to download today!

Download this adaptable Travel Plan template and guidance notes and get started on your own Travel Plan. 

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Travelknowhow can also provide FREE access to marketing materials to assist you in promoting the benefits of sustainable travel to management and staff. For further details about the items available visit the   Communications Kit.

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Understand how your team currently commutes to work. Monitor and track the success of your behavioural change initiatives, and develop a clear understanding of your team’s commuting sentiment.

Get a clear picture of how your staff travel to understand commuter behaviours and design initiatives that will encourage positive behaviour change.

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Collect data on key commuter behaviours including modality, barriers to sustainable travel options, distance travelled, journey frequency and other key commuter attributes.

Use our built-in travel survey templates, or create your own custom surveys, to understand current employee travel habits. Capture your team’s sentiment towards commuting, as well as any changes they have made or plan to make to their journey.

Survey data is used to calculate your ACEL, allowing you to understand the full impact of your commuter emissions.

Travel surveys should be completed at least annually. By regularly repeating your survey you can measure the impact of behavioural change initiatives and examine seasonal variations in travel.

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5 steps to draft an outstanding travel survey, 14+ travel survey templates, 1. travel survey template in pdf, 2. national travel survey example, 3. household travel survey template, 4. national household travel survey, 5. travel survey report sample, 6. annual travel survey example in pdf, 7. family travel survey template, 8. sample travel survey template, 9. basic travel survey template, 10. basic travel survey example, 11. business travel survey template, 12. school travel survey example, 13. sample household travel survey, 14. transport survey template, 15. staff travel survey template, survey templates, 14+ travel survey templates in pdf | doc.

Traveling can provide people the experience to try different cultures and meet people from a variety of social classes and walks of life. If you are a travel service provider or a travel-related organization, try to use survey samples that can allow you to gather information about particular travel undertakings; projects; and experiences.

Step 1: Consider the Purpose and Objectives of Making the Travel Survey

Step 2: download printable templates of travel survey documents, step 3: draft the layout of a standard or basic travel survey, step 4: efficiently develop the header, body and footer of the travel survey, step 5: optimize your time and perfect the travel survey’s final draft.

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• v.2013; 2013

Measuring Workplace Travel Behaviour: Validity and Reliability of Survey Questions

Nicholas a. petrunoff.

1 Health Promotion Service, Sydney and South Western Sydney Local Health Districts, Level 9 North, King George V Building, Royal Prince Alfred Hospital, Missenden Road, Camperdown, NSW 2050, Australia

2 Prevention Research Collaboration, Sydney School of Public Health, Level 2, Medical Foundation Building, University of Sydney, Sydney, NSW 2006, Australia

Chris Rissel

Li ming wen, hidde p. van der ploeg.

3 Department of Public and Occupational Health, EMGO Institute for Health and Care Research, VU University Medical Centre, 1007 MB Amsterdam, The Netherlands

Background . The purpose of this study was to assess the (previously untested) reliability and validity of survey questions commonly used to assess travel mode and travel time. Methods. Sixty-five respondents from a staff survey of travel behaviour conducted in a south-western Sydney hospital agreed to complete a travel diary for a week, wear an accelerometer over the same period, and twice complete an online travel survey an average of 21 days apart. The agreement in travel modes between the self-reported online survey and travel diary was examined with the kappa statistic. Spearman's correlation coefficient was used to examine agreement of travel time from home to workplace measured between the self-reported online survey and four-day travel diary. Moderate-to-vigorous physical activity (MVPA) time of active and nonactive travellers was compared by t -test. Results . There was substantial agreement between travel modes ( K = 0.62, P < 0.0001) and a moderate correlation for travel time ( ρ = 0.75, P < 0.0001) reported in the travel diary and online survey. There was a high level of agreement for travel mode ( K = 0.82, P < 0.0001) and travel time ( ρ = 0.83, P < 0.0001) between the two travel surveys. Accelerometer data indicated that for active travellers, 16% of the journey-to-work time is MVPA, compared with 6% for car drivers. Active travellers were significantly more active across the whole workday. Conclusions . The survey question “How did you travel to work this week? If you used more than one transport mode specify the one you used for the longest (distance) portion of your journey” is reliable over 21 days and agrees well with a travel diary.

1. Background

Evidence suggests that reducing car use and increasing use of active travel (public transport, walking, and cycling) to travel to work have benefits for public health [ 1 – 5 ]. There is interest from both transport and public health practitioners in promoting active and sustainable travel. Workplace travel plans are a promising way of addressing this, although the evidence that they may improve employee health is equivocal [ 6 ].

Workplace travel plans are strategies for managing travel to, from, and during work. Most travel plans are implemented to alter the transport profile of an organisation. Government websites and reports provide guidance on developing workplace travel plans [ 7 ]. They outline a process for developing a travel plan which involves an assessment of the transport modes of employees of the organisation at baseline, which can be used to inform the development of the plan and measure the impacts of the plan over time. Since travel time to work is an important determinant of choice of transport mode, it is also measured.

Many travel plans implemented in various countries [ 6 , 8 , 9 ] have used similar questions to assess transport profiles. Whilst there are published studies assessing the validity and reliability of survey questions assessing travel mode to school [ 10 , 11 ], a literature search did not identify published studies assessing the validity and reliability of survey questions on travel mode and travel time to work. The purpose of this study was to examine the validity and reliability of a question to assess travel mode over the past week that is commonly used in surveys for developing workplace travel plans [ 12 ], as well as a question used to assess travel time.

The specific research questions of this study are the following.

• What is the level of agreement between online survey-reported travel mode and time compared with the self-report travel diary?
• How stable are the self-report survey questions on travel mode and travel time on average over a two-to four-week test-retest period?
• How physically active are people who have been classified as active or inactive commuters by the travel survey during their journey to work and over an entire day?

2.1. Study Design

This study was part of a workplace travel survey conducted whilst developing a travel plan for Liverpool Hospital in 2011. A subsample of respondents to the workplace survey of travel behaviour were invited to complete a travel diary for four working days, receiving SMS reminders to complete these each morning and evening. Throughout this period participants wore an accelerometer on their right hip, only taking it off during sleep and water-based activities. Participants then repeated the travel survey online when returning their diary and accelerometer one week later. Twenty participants were unable to recomplete the survey since the survey site was down at the time they returned.

Approval to conduct the research was provided by the Royal Prince Alfred Hospital Ethics committee, and site-specific assessment and governance approval was provided by Research Ethics and Governance at South Western Sydney Local Health District. All participating staff provided written consent following an explanation of the study.

2.2. Geographical Context and Travel Mode of Study Participants

Liverpool is a major centre in an outer metropolitan area of south-western Sydney, Australia. The Hospital is a principal referral teaching hospital. At the time of conducting the study, Liverpool Hospital was well serviced by trains, with two railway stations within ten-minute easy-walking distance. Hospital staff also had access to a bus network close to the main entrance of the Hospital and at a large bus interchange. The interchange at Liverpool train station serviced areas throughout south-western Sydney and beyond this area.

Although the off-road cycling network in the area did have off-road routes in all directions in a 10 km radius of the Hospital, apart from the route to the north along the railway, there were significant gaps in the cycling network in the immediate surrounds of the Hospital. Most of the surrounding area within a 10 km radius of the hospital is flat. There were 800 car spaces for 3700 FTE staff, and there was significant parking overspill in the surrounds. This overspill had the potential to create significant walking distances for some staff choosing to drive to the Hospital who did not have an on-site parking space.

The online all staff survey was conducted in late September of 2011, and the weather was fine on most days in both weeks the survey was conducted. The weather was typical of Spring in Sydney, being fine with moderate temperatures on most days throughout the study period. The survey found that 83% ( n = 605) of staff drove alone to work, whilst 11% ( n = 83) used public transport and 4 ( n = 28) used active transport modes (walking and cycling) to travel to work. The baseline survey results are described in detail elsewhere [ 13 ].

2.3. Study Participants

From 804 staff who had completed an online all-staff ( n = 3222) survey, 392 volunteered to participate in additional research and provided their contact details after reading an explanation of what the follow-up would involve and being offered an incentive of entering a prize draw. The list of 392 volunteers was printed in order of time and date of completing the survey. Volunteers were called in the order of this list until a total of 65 participants were recruited with an aim of achieving a sample size of at least 50 for this validation study. Since volunteers were called during work hours and a high proportion were clinical staff ( n = 109, 60%), many could not be contacted by telephone after reaching number 183 on the list. Of 74 staff who answered the telephone, 87% agreed to participate, and the sample was achieved after reaching volunteer 183 of the list of 392.

2.4. Measures

Participants completed the question: “How did you travel to work this week? (If you used more than one form of transport, show the method used for the longest (distance) part of the journey).” The 13 response options for each day of the week were walked, cycled, drove a car, car passenger, bus, ferry, train, taxi, truck, motorbike or scooter, worked at home, other, and I did not go to work. See http://www.activetravel.net.au/professionals/tools for survey. The survey also asked staff to indicate the time in minutes for the longest portion of their trip for each of these working days. Participants were also asked how long their daily trip to work was from their front door to their workplace. This was assessed by an online staff survey.

Public transport, walking, and cycling categories were considered “active travellers” since the public transport commute also included an approximate 10-minute walk to major bus and train interchanges in this location. Car categories were considered “nonactive travellers” since for the majority of car drivers their commute was likely to be inactive.

Participants were categorised as “active travellers” overall if they travelled using an active travel mode on half or more of the working days recorded in their travel diary.

Participants were instructed on how to complete a four-day travel diary which itemised each trip they made, what travel mode they used, and how long it took.

Participants were also asked to wear an accelerometer for the same four days they kept their travel diary. The Actigraph GT1M accelerometer (Actigraph, LLC, Fort Walton Beach, FL) is an objective measure of the physical activity and sedentary behaviour and was used as the criterion measure.

The Actigraph is a single axis accelerometer that records activity counts and steps taken, which were stored every 15 seconds. This enabled the accelerometers to capture short and intermittent bursts of activity, which may be expected during stop-start journeys to work by train, bus, walking, or bike.

Moderate-vigorous physical activity time was calculated using the accelerometer data. The travel diary was used to determine the start and finish of the journey to work for which the MVPA attributed to this trip could then be calculated.

After one week these participants returned their travel diary and accelerometer and redid the online survey before leaving.

2.5. Analysis

Data were analysed using SPSS V20.0 (Chicago, Illinois). Travel modes were categorised to car, walking/cycling and public transport. Car included travel mode categories of “I drove alone,” “I was a car passenger,” “truck,” “motorbike or scooter,” and “taxi”. Public transport included “bus,” “ferry,” and “train”. Response categories of “I worked at home,” “other,” and “I did not go to work” were excluded.

To assess the validity of the self-report online survey, the agreement in travel modes between self-reported survey and travel diary was examined with the Kappa statistic. Spearman's correlation coefficient was used to examine agreement of travel time from home to workplace measured between the self-reported online survey and four-day travel diary.

The test-retest reliability of the survey questions on travel mode and travel time between the two online surveys over the average 21-day period was assessed using the Kappa statistic. The test-retest reliability of travel time from home to workplace between two self-reported online surveys was determined with Spearman's correlation coefficient.

Statistical analysis of validity and reliability excluded weekends for individual days since there were small numbers of weekend workers. Data for weekend workers were included for the overall statistical analysis.

The comparison of the proportion of the time travelling to work that was spent in MVPA (from the accelerometer data) between active and nonactive travellers was assessed using a two-sample proportion test. The comparison of the mean MVPA time for the whole day between nonactive travellers and active travellers was assessed by t -test. Public transport users were grouped with walkers and cyclists as active travellers because the number of public transport users was very small. Moreover, this was also considered appropriate since in this geographical context the journey of public transport users included a substantial amount of walking from a rail or bus interchange to their workplace.

Data for all 65 participants was used to assess MVPA time. Data for 45 participants was used for the validity and reliability study since the survey site was down when some participants returned to redo the survey.

There was a high proportion (80%) of car users among study participants, and two-thirds of participants lived more than 10 km from their workplace. Table 1 shows the demographic and transport profiles of the 45 validation study survey recompleters and the 65 study participants whose data was used for assessments of MVPA time. The characteristics of the twenty missed participants were compared to other study participants, and there were no significant differences for any of the demographic variables presented in Table 1 .

Characteristics of participants in validity study and MVPA time assessment.

*Based on postcode of residence.

The validity and test-retest reliability of the self-reported travel survey are presented in Table 2 . Overall, there were a substantial agreement for travel mode between self-reported survey question and the travel diary ( K = 0.62, 95% CI 0.35–0.89) and moderate correlation between the survey and diary for travel time ( ρ = 0.75, P < 0.0001).

Spearman's and Kappa correlations for travel mode and travel time comparing online survey retest to travel diary and initial all-staff online survey.

When comparing the survey responses overall at two time points, travel mode from home to work had good reliability ( K = 0.82, 95% CI 0.57–1, P < 0.0001), as did travel time from home to work (Spearman's ρ = 0.83, P < 0.0001). When comparing travel mode day by day, most results for both validity and reliability study showed moderate-to-good agreement, with only one day each for validity and reliability reaching fair agreement.

The mean MVPA time assessed by the accelerometer during commute time (travel from home to work) for all active travellers was 6.1 minutes (SD 3.0), which is 16% of commute time, compared to 2.6 minutes (SD 2.1), which is 6% of commute time for nonactive travellers. This represented a difference of 4 minutes (95% CI 2.32–5.59). The mean MVPA time for the whole day for active travellers was 62.0 minutes (SD 8.7) versus 37.9 (SD 19.3) for inactive travellers, representing a difference of 24.1 minutes between the two means (95% CI 6.5–41.7). On separating public transport users from walked and cycled, this group travelled for the longest period to work and achieved 14% of their daily moderate-vigorous physical activity during their commute. Table 3 presents mean travel time from survey, travel diary, and MVPA time from accelerometer by three travel modes.

Mean survey, travel diary, and accelerometer outcomes by travel mode.

*% MVPA is the MVPA time for the journey to work from accelerometer data divided by the total time for the journey to work from travel diary.

**MVPA time in minutes for the journey to work calculated for all 65 participants.

4. Discussion

There were moderate-to-substantial correlations between the online survey questions and the travel diary travel mode and travel time measures. These are meaningful levels of agreement for these statistical tests [ 14 , 15 ].

The difference in the travel diary responses to travel mode across the week compared with the self-report response to the online survey retest may be explained by recall bias. Participants presented on a Thursday commenced their diary on the next working day and then recompleted the online survey the following Thursday. The survey question asks respondents to recall their travel modes for the past week. Therefore, for most participants Thursday and Friday were the furthest days to recall, and these days showed the weakest association with the travel diary response.

The discrepancy between travel mode in test and retest survey responses may also be explained by recall bias creating inconsistency in responses. Monday shows the weakest association, and in the test survey Monday would have been the farthest day to recall for most respondents since the survey was delivered on a Thursday. For the retest, Thursday or Friday would have been the furthest, and this may have created some inconsistencies that further exacerbated the poor association. In the test survey, this was done to maximise response rate since a significant proportion of staff did not attend work on Fridays. In the retest, participants were asked to fill in the travel diary for the next four working days, and on returning this diary they were asked to redo the survey and recall the week gone by.

Accelerometers are the “gold standard” objective measure for physical activity in population health research [ 16 ]. The accelerometer data used to calculate MVPA time showed that active travellers (defined as walkers, cyclists, and public transport commuters in this study) were significantly more active in their morning commute. This activity represented a significantly greater proportion of their total physical activity for the day, and they were more active overall. It is noteworthy that a high proportion of the participants defined as active travellers in this study were public transport users. These results are highly consistent with a recent review of the literature [ 1 ], and they do suggest that promoting use of public transport in medium and large workplaces may be an effective population health strategy for increasing physical activity levels.

Considering the small sample of walkers, cyclists, and public transport users in the study, we compared their results for MVPA time measure by accelerometers to the results for MVPA time for all staff that were measured using survey questions that have been validated previously [ 17 ]. For cyclists the average journey time to work in the survey sample was much shorter than MVPA time overall in the all-staff survey; therefore, these results are unlikely to be reflective of active commuting by bicycle generally and may have biased our results for research question 3 towards the null. However, for public transport users, the MVPA times of study participants were similar to those of all staff. This is logical since the major bus interchange and train stations are located at similar distances of about 10-minute easy-walking distance from the Hospital and most public transport users are likely to walk this distance. Further, many workplaces are located at walking distances from train or bus services that could make significant contributions to physical activity for health, and many have parking close to the door or lifts. Therefore, the comparison for MVPA time between public transport commuters and car drivers is likely to be generalisable to many workplaces.

The Hospital had large parking overspill at the time of the study, and there was potential for drivers to walk similar distances to public transport users from their parking spot to work. However, the average MVPA for drivers in the study was approximately two minutes; therefore, their journey did not include significant amounts of physical activity as they must have parked close to their workplace.

Accelerometers measure activity in the vertical plane; therefore, they can underestimate physical activity from cycling. Due to the small number of cyclists, it is unlikely to have changed the results relating to the difference in physical activity levels of active and nonactive commuters.

A limitation of the study was the small number of public transport commuters and participants who walked or cycled to work. In future research, the limited number of active commuters and public transport users could be overcome by oversampling these groups on recruitment into the study and recruiting more participants overall. However, the strength of the correlations in the tests of reliability and validity, and the simplicity of the questions on travel mode and travel time do provide confidence that the questions are stable and measure what they are trying to measure.

5. Conclusions

Whilst the evidence for organisational travel plans improving health is equivocal, they have been described as a promising intervention for increasing employee physical activity levels that are worthy of further research. Although guides exist for conducting workplace surveys for developing travel plans, to our knowledge, none of these questions had been assessed for validity or reliability at the time this study was published. The questions on travel mode and time tested in this study were found to be valid and reliable. Therefore, this study makes a significant contribution to the literature for a promising public health intervention. Whilst the sample size is small, the finding that public transport users accrued significant physical activity levels in their morning commute is consistent with a growing body of research on this topic and does indicate that promoting public transport use shows promise for increasing population physical activity levels [ 1 ].

Acknowledgments

This analysis is a component of a dissertation for a Doctor of Philosophy with the School of Public Health, University of Sydney. The authors acknowledge Health Promotion staff who contributed to the implementation of the validation study, including Jeni Bindon, Sufia Khan, Elissa Kiggins, Mandy Williams, and Rachel Wilkenfeld. They also acknowledge the Liverpool Hospital Sustainability Taskforce members for their support of the implementation of the all-staff survey and the Liverpool Hospital Executive for approving it. Funding for the research was provided by the South Western Sydney & Sydney Local Health Districts, Health Promotion Service.

How PAG’s employee travel surveys help the region’s planning efforts

It is easy to wrap one’s head around the meaning of travel reduction. Encouraging commuters to cut down on solo car trips to work, in turn, reduces vehicle emissions and improves our air quality. But perhaps it’s less obvious that Pima Association of Government’s Travel Reduction Program also helps with broader regional planning.

The program engages the region’s major employers to participate and administer an annual TRP employee survey. This survey provides a wide range of important regional transportation data.

It begs the question: who uses the data and what is it used for?

In the broadest sense, the anonymous TRP employee survey gathers valuable data that guides the region’s transportation planning efforts to reduce traffic congestion, energy consumption, the cost of transportation and air pollution. The program also is a cornerstone of workforce recruitment and retention, with the goal of improving job access, mobility options and quality of life for the region.

How employers use the data

The information provided by participants of the annual TRP employee survey generates a roadmap for a TRP employer’s HR department to analyze commuting patterns within their workforce and suggest commute options that are feasible for its employees.

The better the response rate, the more statistically significant the data is. Employers receive heat maps and other data at the end of the survey process which illustrates options for the employer worksite. This information allows a business’s HR team to evaluate if vanpooling, carpooling or transit are good choices for their workforce.

How the data helps the region

TRP data is the critical piece of the puzzle that plays a major role in PAG’s modeling work to support regional transportation planning efforts. The TRP survey data informs the model with employee mode choices, types of vehicles driven, miles traveled, and what industry and type of jobs are prevalent in the region.

PAG has begun to shift to a new activity-based model, and the TRP employee survey data is an essential calibration/validation input for the model. PAG can model travelers’ commute travel time/distance, work-from-home ratio, commute departure/arrival time, and many other travel behaviors more accurately by referencing numerous summary statistics estimated from the TRP employee survey data analysis. A large sample size and higher update frequency makes the TRP Employee Survey data more reliable to understand the behaviors affecting the regional traffic system.

The models are important for long-term transportation planning efforts. The more data and greater detail gives planners a better understanding of finer-resolution travel behavior that is more representative of travel in the region.

The model tells the story of how people move so that transportation plans can be developed to support growth and vitality in the region. In addition, the TRP is rooted in the Clean Air Act of 1970. Public health concerns are linked to air quality and planning efforts aimed to ensure planned growth addresses health, safety and quality of life.

Additional planning efforts focus on reducing congestion and designing the flow of travel. The model can forecast new mobility impacts and changing travel options and behaviors.

The state and others rely on the information, too

The TRP data collected from the annual employee survey is provided to the Arizona Department of Environmental Quality (ADEQ) monthly to track how many pounds of vehicle emissions are saved or offset. The monthly and annual numbers are submitted as part of the statewide effort to deploy transportation control measures to improve air quality and protect the community. Metrics are compared year over year to look for opportunities and identify trends in the commute arena. As communities navigate economic recovery after the pandemic, choices about how and where employees perform their work will be made. TRP data will be a guide revealing trends, operational pivots, and changes in how employees access and use mobility options in the region.

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Travel planning

What is a workplace travel plan, workplace travel plans are a way of encouraging efficient and environmentally friendly methods of travelling, for both commuting and work related journeys. they do this by promoting walking, cycling, lift sharing and public transport as an alternative to single occupancy car journeys. your travel plan may also include home working, flexible working and video conferencing as ways of minimising travel requirements., our free site audit, survey and travel planning service is the place to start if you want to dentify how to create a more positive travel environment at your workplace. it also allows you to establish the baseline data for monitoring and evaluating the results of your sustainable travel initiatives. email [email protected] to find out more., note: it is a requirement of your workplace travel grant application to have a travel plan in place as it identifies what changes are needed to reduce single car occupancy journeys within your organisation. .

Find out how to apply for a Workplace Travel Grant to help achieve the goals of your travel plan.   

This short video explains what a travel plan is for, what it can achieve for your organisation and how to ensure its success.

What should a Workplace Travel Plan contain?

An effective Travel Plan MUST include the following:

• Introduction
• Location, transport links and site audit
• Existing policies
• Staff travel survey and identified issues
• Travel measures to reduce ‘Single Occupancy Car use’
• Objectives and targets
• Action plan
• Monitoring strategy

Note: There are downloadable Word documents for each section at the bottom of this page.

What measures can be included in a travel plan?

A detailed overview of measures to consider for inclusion in your travel plan can be found in our Suggested Travel Plan Measures document which covers the following areas:

For additional background and guidance relating to each mode of tansport see our Travel Planning Toolkits .

What are the benefits of having a workplace travel plan?

Benefits for the employer include:

•  helps lower business costs, such as business travel or car park management costs
•  gets staff to be more active on the journey to work, increasing staff productivity and lowering sickness absence
•  helps recruit and keep staff by widening their travel choices
•  can help with parking problems by encouraging staff to travel by other means
•  makes a good contribution to your business' reputation and environmental policy

Benefits for employees include:

•  widens staff travel choices for the journey to work
•  can lessen individual travel costs
•  promotes health and fitness
•  can widen the job search areas of job seekers

Staff travel survey

Your staff travel survey provides the key data to inform your decisions regarding what travel measures to implement. You can choose the in-depth survey or a shorter version and y ou will receive a digital and paper copy of the results analysis. A downloadable sample of both versions of the FREE travel survey is available in the downloads section below.

Additional resource

Check out Ten Ways to Make Your Business Bike-Friendly , written in 2010 by Caitlin Dorsey. It is available below in the download section. 

Please note some of the content in this article has been adapted to reflect the UK cycle offering .

Downloads: 

Travel planning tool kits.

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2022 Boulder Valley Employee Survey Travel Findings Published 

Media Contacts: Aisha Ozaslan, Media Relations, 303-501-2318 Chris Hagelin, Principal Transportation Planner, 303-441-1832

Local transportation improves with growing gaps identified regionally

The City of Boulder has published findings from the latest Boulder Valley Employee Survey . Since the first survey in 1991, the statistically valid survey has tracked trends in employee travel behavior to help evaluate progress toward city goals. Key 2022 findings suggest that the city is back on track to meet its transportation goals locally, with continued challenges in regional transportation:

— The COVID-19 pandemic is still impacting travel behavior. Fewer employees use transit now than before COVID. Transit service level cuts related to COVID have not been restored to levels before the pandemic and employer participation in the RTD EcoPass program declined significantly during the pandemic.

— Work from home continues at high rates . 11% of reported commutes on the survey day were avoided due to teleworking. In total, 61% of respondents telework at least some of the time, a major increase since the last survey in 2017.

— More jobs in Boulder are held by non-resident employees than resident employees, and both groups continue to travel differently. Non-resident employees primarily use single-occupancy vehicles to get to their jobs in Boulder. However, resident employees have better access to multimodal options and take more multimodal trips to get to work. There is also a growing gap between the average commute distance for non-resident and resident employees, with non-resident employees currently commuting over 18 miles on average.

Survey results help inform policies, practices and planning toward city goals, which include lowering greenhouse gas emissions and increasing walking, biking and transit trips. 2022 findings support continued regional partnerships to restore transit service and improve multimodal options. The city also aims to continue focusing on improvements to Boulder’s Core Arterial Network (CAN) — a connected system of protected bicycle lanes, intersection enhancements, pedestrian facilities, and transit facility upgrades that will help reduce the potential for severe crashes and make travel more comfortable and convenient for all.

View the full survey report on the city’s website .

Keep Reading

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April 9, 2024

City and Partners Launch ‘Boulder Clean Commute’ Pilot Program to Encourage More Sustainable Transportation Options

April 1, 2024

City Begins Constructing 19th Street Improvements in North Boulder

March 20, 2024

What a Year in Transportation Looks Like in Boulder

February 13, 2024

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U.S. Macroeconomic News and Low-Frequency Changes in Small Open Economies’ Bond Yields

This paper investigates the importance of U.S. macroeconomic news in driving low-frequency fluctuations in the term structure of interest rates in Canada, Sweden and the United Kingdom. We follow two complementary approaches: First, we apply a regression-based framework that aggregates the impact of daily macroeconomic news on bond yields to a lower quarterly frequency. Next, we estimate a macro-finance affine term structure model linking the daily news to lower-frequency changes in bond yields and their expectations and term premia. Both approaches show that U.S. macroeconomic news is an important source of lower-frequency quarterly fluctuations in bond yields in these small open economies—even more important than the respective countries’ domestic macroeconomic news. Furthermore, the macro-finance model shows that U.S. macroeconomic news is particularly important to explain low-frequency changes in the expectation components of the nominal, real and break-even inflation rates.

DOI: https://doi.org/10.34989/swp-2024-12

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