Keywords

1 Introduction

It is generally considered that the transport system needs the support and engagement of the public in its development and implementation. A social model approach to developing roads policy looks beyond the transport sector, beyond governments and beyond the road community to build wider acceptance of transport solutions. Here we describe at an approach for gaining insight into how the community views policies related to the performance of the road transport system: the “social license to operate the road system” (SLORS). In exploring the concept of the SLORS, we show how it can assist in the implementation of road policy and network considerations. We initially examined the (SLO) approach and how it adds to our understanding of the introduction of new products. The policy issues were then categorized into 5 zones: User Advocacy Zone, Support Zone, Equilibrium Zone, Tolerance Zone and Opposition Zone. Interpretation of the SLORS in a policy sense is outlined graphically.

2 Research into the Public’s Acceptance of Road Transport Systems

At its base, road infrastructure operations require a coordinated, efficient and well-informed planning process, triple bottom line assessment and strategic asset management system. Because it is generally thought that an acceptable road system must meet the needs of the community, their view of the transport policy is an important input into these processes and, in particular, their implementation. Community consultation and people’s behaviour are the main methods of collecting this information. As transport systems become more complex and invasive the general community expresses more concern about its impacts, and many transport projects and government decisions are questioned. In some cases transport projects have been stopped, delayed or not started. Public acceptance has been suggested as an important factor for the successful realization of transport plans, projects and policies, and a number of approaches have been used to quantify the performance and customer satisfaction with transport infrastructure [1]. In particular, BITRE looked at “…how customer preference might be better incorporated to improve the long term efficiency and operation of Australia’s infrastructure asset” [1]. A key component of communication with the community in the roads area is transparency and a need to quantify their views. We add to the above approaches by exploring the quantification of SLORS. In particular, how can SLORS be used to assist in the implementation and operation of particular policies and the introduction of new products.

3 Consideration of SLORS

We examined how to include the public in the development of road policy decisions as part of the planning and policy development processes. The views of the community about the future of roads comprise an essential input into each of the planning processes because they are the system’s end-users. This process can be assisted by the quantification of a SLORS. At the policy development level there could be varying levels of acceptance of particular issues by the community.

The survey methodology and data used in this study were collected from a series of cross-sectional questionnaires and focused group open-ended surveys over a period of 3 years. Industry and respondents were asked about the major issues and these were developed into a series of formal questionnaires. The questionnaire sample was collected using social media and a panel. The policy issues were developed over a 3-year period and changed as new issues were raised and old issues refined. Respondents were asked what “should” take place and what they think “will” take place. The “will” and “should” questions formed the basis of the quantified views using a 5-point semantic scales. Here, we only look at the stage 3 data.

There were 18 policy issues considered in stage 3 (Fig. 1) and these formed the basis for the exploration of the SLORS. Figure 2 presents the SLORS framework for consideration of these issues in a policy sense. The SLORS can be measured in terms of how the public perceives the acceptability or not of particular transport policies. That is, whether a policy issue will and should take place in road operation. The “will” provide an indication of what the respondent thinks the particular issue will be like in 30 years; “should” indicates what they think should occur. These 2 perceptions form a grid showing the implications of the SLORS: what should happen is the vertical axis and what will happen is the horizontal axis. The SLORS measure is the difference between the “should” and “will” ratings. Other relationships between the “should” and “will” ratings, such as ratios, logarithms etc. are shown by the graph, and will be explored further in the future. The vertical distance between the “should” rating and the line of equality (≈45° line) between the “will” and “should” ratings pictorially represents the SLORS, which is the discrepancy between what the respondent thinks should take place and what will take place. This discrepancy, depending on its positive and negative value, will indicate the level of support, tolerance and opposition to the particular issue. More specifically, the line of equality (Should–Will) is the level of acceptance the community thinks these issues will take place and that they should take place at the same level at a particular point in time. Above the line of equality is where the community thinks that these policy issues should take place and that they will take place at a lower level, which is a level of advocacy and support for these issues. Below the line of equality is opposition to particular issues. These measures of the issues can be subdivided into 5 zones (Fig. 2): User Advocacy Zone, Support Zone, Equilibrium Zone, Tolerance Zone and Opposition Zone.

Fig. 1
A scatter plot of should happen happen mean-stage 3, versus will happen Mean-stage 3 indicates 1 to 18, user advocacy zone, support zone, tolerance zone, equilibrium- mix of tolerance and support, and opposite zone. The summarized descriptions of policy issues in each zone are given below.

Issues presented in a SLORS framework

Fig. 2
A graph of should happen mean versus will happen mean indicates highly desirable and highly unlikely, social license surplus and deficiency zones, neither likely nor desirable, less desirable and less likely, lower desirability but highly likely, and highly undesirable and highly likely.

Some implications of the relativity of average “should” and “will” ratings in a SLORS framework

4 The Data

The data we used was a subset of data collected for a broad study of the future of roads. Stage 3 data includes only data where all “should” and “will” ratings were given, and were collected between 24/2/20 and 24/4/20. The 18 policy issues (Fig. 1) were included in the questionnaire. The respondents were asked to answer how likely they thought that each statement described WILL occur (Fig. 1) and to what extent they agreed that what the statement described SHOULD occur (Fig. 1). These ratings formed the base for the SLORS (Fig. 1) and are discussed below.

5 Quantification of the SLORS

5.1 Respondents’ View of What SHOULD Happen to Roads

The measure of the community’s support for particular policies comes in many parts. One is what they think should happen and was measured using a 5-point Likert scale: Strongly Agree (5), Agree (4), Neutral (3), Disagree (2) and Strongly Disagree (1). Figure 1 presents the mean for “should” rating for each policy issue. The quantitative results of the data showed that most things were changes that people thought “should” happen, as measured by a mean equal to and above an average score of 3.00. The average rating ranged from a high of 4.22 (separation of bicyclists and pedestrians from cars and trucks) to a low of 2.34 (paying tolls and road charge)s. Overall, the “should” ratings and the percentage of people disagreeing with the issue provided a good indication of the community support for particular policy issues. This is one measure of how the community views the road system and should be taken into account when considering particular policies.

5.2 Respondents’ View of What WILL Happen to Roads

A complementary measure to what “should” happen is the community’s view of what “will” happen and was also measured on a 5-point Likert scale: Very Likely (5), Likely (4), Neutral (3), Unlikely (2) and Very Unlikely (1). The ranking of average ratings for the “will” scores indicated the preferred products. The quantitative results of the data showed that most things are changes that people think will happen. The average “will” ratings ranged from a high of 4.26 (increasing traffic) to a low of 2.37 (improving driver behaviour). The respondents’ indication of what will happen is not an indication of the SLORS but taken together with the support levels for the policy issues provides a strong indication of the difference between what people want to happen and what they think will happen. This will be considered in the next section.

5.3 The SLORS

The “should” ratings provide one measure of the community’s view of road transport policy, but do not, however, provide an indication of the community’s dissatisfaction with the policies, because they understand some things will happen. The difference between the “should” and “will” ratings provides a measure of the level of discrepancy or dissatisfaction that people have with the transport policy. More specifically, the “will” ratings (Fig. 1) indicate what the respondents think the road system will be like in the future. The combination of this measure with the “should” rating (Fig. 1) gives the magnitude of dissatisfaction with what should and will take place in 30 years; that is, the SLORS. As shown in Fig. 1, the “should” minus the “will” difference for each respondent is averaged over the entire population. A positive ranking indicates that the desirability of a measure exceeds the likelihood of it happening, which is the support region in the SLORS diagram (Fig. 1). A negative indicates things that will happen but should not: The opposed region.

The SLORS diagram (Fig. 1) shows the mean “should” and “will” ratings for the data set plotted against one another, with the 45° line of equality between “should” and “will”. Because the SLORS is estimated by subtracting “will” from “should”, attributes with a positive rating are above the line and show where perceived desirability exceeded perceived likelihood of eventuating. For instance, it shows that although the respondents think that driver behaviour should improve (1.44), roads should be safer (1.15), and the physical quality of the roads should improve (0.99). These are unlikely to happen despite net support. Those attributes with a negative rating are below the line of equality and show where the perceived likelihood of happening exceeds perceived desirability. Increased congestion (−1.50), increased traffic (−1.34), road charges (−1.18) and the role of private companies in planning (−0.86) fall into this category and have less support. They are likely to happen but people think they should not happen. Increased action would need to be put in place to achieve these goals.

5.4 Interpreting the SLORS

There are two major differences in this application of SLO from previous social license to operate applications in roads.

  1. 1.

    Road users have views on a wide range of policy issues from planning through to constructed infrastructure and even the behavior of users. It does not look only at 1 project as do other applications of SLO.

  2. 2.

    Other than in project-specific studies, users are seldom asked for their views on what they think should happen and at the same time what they think will really happen on roads. Generally, studies look at only what should happen, which is only half of the picture.

These contributions by users are potential keys to solving a number of implementation agency issues before they occur. Strategic initiatives and policy changes may meet significant stakeholder opposition, effectively preventing implementation of something that makes engineering and/or economic sense. An example is road-pricing and the concept that users should pay for the network capacity they use, and, critically, only the network capacity that they use. The net result is that custodians of the road network often face a choice—do nothing or risk a public backlash. The net result is long lead-in times for projects and changes, giving rise to perceptions that change is slow. Thus, an important part of change is the marketing of the changes to stakeholders, including road users.

The methodology described here may allow an agency that is considering a basket of policy options or initiatives to gain some insight as to the phasing strategy. They can begin with options with a high SLORS to start getting some benefits of change, while change requiring a significant shift in attitudes can be shepherded over longer periods to win road users over, or gain their license to bring about the envisaged change.

Thus, points below the equality line in Fig. 2 represent issues where “will” is greater than “should”; that is, factors where support is less than the perceived inevitability or where social license is deficient. Points above the equality line represent issues where the social license is positive; road users want the change more than they perceive it to be likely to eventuate. Points on the line represent issues where support and perceived eventuation are in balance.

This gives some idea of what the ‘quick wins’ might be and where significant effort may need to be put into winning the support of road users. This approach can be incorporated into the SLORS framework (Fig. 3). The idea of road users taking on an advocacy role (User Advocacy Zone) against hold outs for changes the agency wants to make would have strong appeal to the agency. It avoids the agency being accused of forcing their change through and reduces the expenditure of resources that the agency needs to effect the change. To take advantage of this, it is necessary to know at what point support tips into advocacy on the road network.

Fig. 3
A scatter plot of should happen happen mean-stage 3 versus will happen mean-stage 3 indicates 1 to 18, high desirable and less likely, high desirable and highly likely, less desirable and less likely, less desirable and highly likely, and not desirable and not likely. The summarized descriptions are given below.

Alternate zone definitions for the SLORS framework

Similarly, it would be helpful to know—for those factors in the social license deficiency zone (Opposition Zone)—which are the issues where it is possible to change road user perceptions and gain social license in a reasonable amount of time, and which are candidates for really long-term efforts, or for which a rethink may be needed.

To illustrate how a finer gradation of support/opposition is introduced, 2 lines have been added to the SLORS framework in Fig. 3 to represent these tipping points: 120% (Support Zone) and 80% Opposition Zone) of the line of equality value (Equilibrium Zone = mix of tolerance and support).

By adopting such an approach to assessing social license, an agency would then have the following strategies available:

  1. 1.

    Supply users with materials and publicity for items in the Advocacy Zone

  2. 2.

    Embark on minor ‘marketing’ of items in the Support Zone to reduce resistance

  3. 3.

    Focus efforts on items in the Tolerance and Equilibrium zones in order to gain some degree of social license for them

  4. 4.

    Rethink the desirability of items in the Opposition Zone, form coalitions with others trying to achieve the same measures or make plans for a long process of persuasion.

Figure 3 shows the 18 policy issues identified in their SLORS zones, for the tipping points described above. Two of the Opposition Zone factors are in fact outcomes—increased traffic and congestion. Therefore, if an agency hoped to do nothing to reduce traffic or congestion that “do nothing” approach would be resisted. Conversely though, any actions taken to ameliorate outcomes in the Opposition Zone can be assumed to have the “Support”, or enjoy the “Advocacy”, of road users.

Put another way, the “should”, “will” and SLORS ratings provide guidance on the acceptance or not of particular policy issues by the community. These need to be put into an overall policy context. Figure 4 shows the full SLORS framework and the ratings for the 18 policy issues, illustrating the policy tipping points. Issues can be divided into zones: Advocacy support (Alignment between desirability and likelihood); Issues where people show some Tolerance; and Issues where there is Opposition.

Fig. 4
A scatter plot of should happen happen mean-stage 3 versus will happen mean-stage 3 indicates 1 to 18, user advocacy zone, support zone, tolerance zone, equilibrium- mix of tolerance and support, and opposite zone.

A comprehensive SLORS framework

Advocacy support can be found in the areas of improvement: driver behaviour (1.44), road safety improvements for all road users (1.15), improvements in the quality of the road surface (0.99) and road transport being environmentally sustainable (0.83). Support is likely for policies related to: physical separation of active transport from cars and trucks (0.61), use of technology to improve level of service (0.49) and public transport being a more common mode choice (0.47). A mix of tolerance and support may be obtained for: priority given to: more tunnels for road and rail (0.12), active travel in local and shopping roads (0.05), more smart infrastructure (0.05) and increased number and capacity of roads (0.03). For these factors, the views of desirability and likelihood are similar in magnitude. The factors where the respondents may show some tolerance are: banning parking on major roads (−0.14), roads and their use will stay the same (−0.33), and automation of the road transport network (−0.47). Those factors where there is likely to be opposition are private sector being involved in planning (−0.86), paying for the use of the network (−1.18), increased traffic in the future (−1.34), and increased congestion (−1.50).

Under the SLOR zones posited, Australian road agencies can rely on user advocacy for actions and strategies to:

  1. 1.

    Improve driver behavior, make roads safer, better physical quality and make use of roads more environmentally sustainable.

  2. 2.

    Reduce traffic and congestion, by virtue of “increased traffic” and “increased congestion” being in the “opposition” zone as posited.

  3. 3.

    Support strategies to improve the attractiveness of public transport as a choice, increase deployment of technology (ITS/VMS) to improve levels of service on roads and to physically separate motorized traffic from cyclists and pedestrians.

  4. 4.

    Work on public acceptance of an all-autonomous motorized vehicle fleets, a ban on parking along major roads and any plans to allow road usage to stay the same.

  5. 5.

    Reconsider pricing as a strategy, or significantly change how it may be applied, or simply educate the road users on an intelligent reframing of what “pay per use” means.

6 Conclusions

We explored an approach to gaining insight into how the community views the performance of the road system: the concept of a SLORS and shows how it can assist in the implementation of policy and network considerations. The measurement of the SLORS was described and 18 policy issues were rated for whether they “should” and “will” be implemented. The SLORS is the difference between the “should” and “will” ratings. The policy issues were categorized into 5 zones: User Advocacy Zone, Support Zone, Equilibrium Zone, Tolerance Zone and Opposition Zone. The Zone into which an issue falls provides information to policy makers on the public’s view of the policy. For instance: in the Advocacy Zone issues such as driver behaviour should improve, Roads must be safe for all users, the Physical quality of the road and their surface should improve, and Road travel should be more environmentally sustainable in the future are in the user Advocacy Zone. In the Opposition Zone People paying a toll or road charge, Private companies having a large role in planning and management, Increased congestion and Increased traffic on roads in the future receive less support. This information may assist in pointing policy makers in the best direction to gain community support.