Transportation policymaking in Beijing and Shanghai: Contributors, obstacles, and process

Journal Pre-proofs Transportation Policymaking in Beijing and Shanghai: Contributors, Obstacles, and Process Jungwoo Chun, Joanna Moody, Jinhua Zhao PII: DOI: Reference:

S2213-624X(18)30300-6 https://doi.org/10.1016/j.cstp.2019.09.003 CSTP 387

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Case Studies on Transport Policy

Received Date: Revised Date: Accepted Date:

12 September 2018 7 July 2019 28 September 2019

Please cite this article as: J. Chun, J. Moody, J. Zhao, Transportation Policymaking in Beijing and Shanghai: Contributors, Obstacles, and Process, Case Studies on Transport Policy (2019), doi: https://doi.org/10.1016/j.cstp. 2019.09.003

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Transportation Policymaking in Beijing and Shanghai: Contributors, Obstacles, and Process

Jungwoo Chun Department of Urban Studies & Planning Massachusetts Institute of Technology 77 Massachusetts Avenue, Rm 9-569, Cambridge, MA 02139 Tel: 617-319-8324; Email: [email protected] Joanna Moody Interdepartmental Program in Transportation Massachusetts Institute of Technology 77 Massachusetts Avenue, Rm 1-151, Cambridge, MA 02139 Tel: 434-409-5679; Email: [email protected] Jinhua Zhao (corresponding author) Edward H. and Joyce Linde Associate Professor of City and Transportation Planning Department of Urban Studies & Planning Massachusetts Institute of Technology 77 Massachusetts Avenue, Rm 9-523, Cambridge, MA 02139 Tel: 617-324-7594; Email: [email protected] Word count (excluding references and abstract): 8,518 ACKNOWLEDMENTS The authors would like to thank all of the subjects of our interviews for their time and detailed commentary. We also acknowledge our colleagues in the MIT JTL Urban Mobility Lab who have contributed their critical commentary and support to this work, particularly Shenhao Wang and Xuenan Ni. This work was supported through the MIT Energy Initiative's Mobility of the Future study.

Transportation Policymaking in Beijing and Shanghai: Contributors, Obstacles, and Process ABSTRACT With continued motorization and urbanization in Chinese cities, there is a growing demand for innovative transportation policies at the city level to address the challenges of congestion, local air pollution, and greenhouse gas emissions. Using Beijing and Shanghai as case studies, this paper draws on 32 in-depth semi-structured interviews with municipal government officials, academics, and transportation professionals to explore the city-level transportation policymaking process in Chinese megacities. Across the two cities, we identify three common contributors – policy learning, data informatization, and public opinion—and four obstacles—public complaint, unilateral decision-making, inadequate coordination among relevant departments, and lack of

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adaptiveness in policy implementation practice—to adopting timely and appropriate transportation policies. We then introduce a processual model that connects the contributors and obstacles identified within the flow of transportation policy among key actors in city-level government. This process shows how transportation policymaking in Chinese megacities is often reactive to public outcry over a transportation problem. This problem is investigated by a technical government research center that reports to the municipal transport committee. This committee then assesses public opinion and submits a policy recommendation to city government leadership, who make the final policy decision. Based on both case studies, we discuss potential recommendations for how to better enable transportation policymaking at the city level in China through more formalized processes of policy experimentation and public participation. We conclude with a discussion of limitations and areas of future research.

Keywords: China municipal transportation policy; Beijing; Shanghai; policymaking process; public opinion

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1. INTRODUCTION Chinese cities have been subject to accelerated urbanization and motorization over the past two decades (Woetzel et al., 2009), leading to issues such as congestion, local air pollution, and energy shortages (Wang, 2010; Gakenheimer, 1999). Nationwide, the growth rate of privately owned vehicles approached 30 percent in 2010 and a third of the world’s 50 most congested cities were in China (Alam and Ahmed, 2013). According to the Ministry of Environmental Protection, only three cities in remote areas, among China's seventy-four major cities, met national standard for "fine air quality" in 2013 (Saikawa, 2014). To combat these issues arising from rapid urbanization and motorization, Chinese cities are adopting new urban transportation management strategies (Peng, 2005). While China is often seen as a top-down, command and control system with policymaking power vested in the national government, when it comes to transportation policy city governments enjoy significant policymaking autonomy and discretion when addressing challenges of traffic congestion and local air pollution. The Chinese national government sets a broad, national policy framework, but city governments formulate and implement new urban transportation policy based on local priorities (Wan, Wang, and Sperling, 2013; Liang, 2014; Yang, 2013; So and Kao, 2014). In response, governments of major Chinese cities are actively seeking ways to implement new policy reforms and adopt updated strategic plans. Given this level of local autonomy in transportation policymaking and trends of continued urbanization, it makes sense to focus on cities as cases of Chinese transportation policy decisions rather than the national government (Wan, Wang, and Sperling, 2013). However, within the transportation domain there is little scholarship around how policy decisions are made at the city level in China. Rather than look at the impact or effectiveness of transportation policies already adopted by Chinese cities, this study focuses on the internal process by which transportation policies are formulated, identifying key contributors and obstacles to effective and efficient policy formulation. This study uses qualitative analysis to characterize the transportation decision-making process in city governments in Beijing and Shanghai, China. Studying the internal operations of the Chinese government at any level and in most policy areas is typically a challenge for international researchers. Yet with in-depth interviews and iterative qualitative data analysis, this study identifies existing contributors and obstacles to transportation policy implementation and investigates the transportation policy decision-making process. In the transportation context, we corroborate and add to existing literature on city-level policymaking by identifying three key contributors in the transportation context—policy learning from other cities, emerging sources of data for transportation planning (or “transportation informatization”), and public opinion. We further identify four prominent obstacles to transportation policy decisions in Beijing and Shanghai—public complaint, unilateral decision-making structure, lack of cross-departmental communication and coordination, and lack of adaptiveness in policy implementation. We then illustrate how these factors connect to policy decision outcomes by mapping them to a processual model of how policy flows from one actor to another in the city governments in Beijing and Shanghai. In each section examining contributors, obstacles, and process, we connect our findings for the transportation domain and the Chinese context to relevant literature in city-level policymaking. We then discuss how transportation policymaking in Beijing and Shanghai may benefit from more formalized processes of public participation and policy experimentation. We conclude with acknowledgment of the limitations of this study and a case for further research into transportation decision-making at the city level in China.

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The findings in this paper can inform both the academic community and local governments in Beijing, Shanghai, and other Chinese megacities with similar municipal government structures. For academics, this work highlights the complexity of transportation policymaking in Chinese megacities and the need to conduct a study with a more nuanced understanding of the many actors and pressures influencing policy decisions. Government officials may take note of what contributors to policymaking might be fostered at the city level or how to remove obstacles to improve the efficiency and efficacy of transportation policy formulation. 1.1 Case Selection We conduct this study in two Chinese megacities: Beijing and Shanghai. These cities were chosen for both their similarities to one another and other Chinese megacities, their reputation as policy trendsetters, and the potential to leverage their unique differences for comparative analysis. Despite having the distinction of being provincial-level municipalities, Beijing and Shanghai are comparable in size, economic and socio-demographic characteristics to each other and many of China’s largest megacities. Furthermore, many of these cities share urbanization and motorization trends with our two case cities (Wang and Zhao, 2018) and thereore face similar challenges such as congestion and local air pollution that drive local transportation policy innovation. Among Chinese megacities, Beijing and Shanghai are seen as policy trendsetters. Both cities have recently demonstrated innovative policy implementation, being the first to experimenting with transportation policies including license plate lotteries and auctions aimed at restricting vehicle ownership (e.g., Chen & Zhao, 2013) as well as rolling restrictions on vehicle use (e.g., Gu, Deakin, & Long, 2017). In fact, Beijing and Shanghai are often considered the pacesetters or engines for economic and socio-political development in China overall (Li, 2007). Therefore, lessons learned from these two cities may transfer to other megacities facing similar urbanization and motorization challenges with similar municipal policymaking structures and processes. The selection of these two cities as case studies also provides a unique opportunity to identify differences between the two cities and any factors that drive these differences. For example, Beijing is known for a higher level of conservatism, while Shanghai possesses the image of a market-oriented, liberal city (Li, 2007). Beijing, as the nation’s capital, hosts the national government as well as the city government. While transportation policies and other developmental policies are primarily administered by the city government, due to geographic proximity to the national government, it may be fundamentally challenging to completely exclude the influence of the national government in transportation policy decision-making at the local level in Beijing. 2. METHODOLOGY 2.1 Semi-Structured Interviews The research was conducted using principles from grounded theory, a methodology designed to build theories from data about the social world such that “theories are ‘grounded’ in people’s everyday experiences” (Knigge and Cope, 2006). Research using this approach involves iterative stages of data collection, coding and analysis, critical reflection on emerging themes and concepts, and constant comparison of the insights that evolve (Knigge and Cope, 2006, Knox Hayes, 2016). Specifically, the study is conducted using an iterative process in which preliminary interview findings influence the analysis of subsequent phases, including: 1) preliminary analysis to identify

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key factors that seem to most dominantly influence final transportation policy decisions in the selected cities; 2) analysis and grounded visualization of qualitative data to link actors and decision-making processes; and 3) surveys of government officials' perception of factors that drive or inhibit transportation policy decisions by asking questions around specific transportation policy examples that they were directly involved in formulating (Knox Hayes, 2016). We conducted in-person semi-structured interviews with 32 individuals (see Table 1). Interviewees were selected using a snowball sampling method (Small, 2009) from governmental agencies, non-governmental organizations, and academia (see Table 1). Interviewees included city government officials who are both directly and indirectly participating at multiple stages of transportation policy decisions in the two cities. The government officials interviewed in both cities are members of technical research centers rather than those with decision-making authority at the top-levels of city government. The authors experienced significant difficulties finding government officials in Beijing who felt comfortable talking openly about the policy-making process within their city; therefore additional interviews were carried out among non-governmental professionals and academics using a modified version of the interview script (see Appendix B). These non-governmental interviewees have first-hand knowledge of the transportation policymaking process within their city’s government because the city government often invites them to participate in expert research meetings that advise on the validity and feasibility of certain transportation policy proposals. Subsequent analysis was conducted on the combined pool of interviews across both cities and all interviewee types. Table 1. Number and affiliation of interviewees by type for each city. Type Academia

Beijing (N=16) N Affiliation – Tsinghua University 10 – Beijing Jiaotong University

N 5

City government

2

– Transportation Committee – Transportation Development Research Center

10

Professionals

4

– World Bank – Energy Foundation

1

Shanghai (N=16) Affiliation – Tongji University – Shanghai Maritime University – Transportation and Port Research Center – Housing and Urban and Rural Construction Management Committee – Maritime Safety Administration – World Bank

Each interview lasted from 40 to 60 minutes and was conducted in Chinese. The first part of the interview featured a standard set of questions (see Appendix B). These interview questions focused on the participant’s experience of and actions within the transportation policy decision-making process in each city, personal involvement in certain exemplary policy cases, assessment of the current structure of transportation policymaking process, and observations of public engagement, and their discourses on transportation policy. The second part of the interview consisted of follow-up questions based on individual’s responses in the first part. 2.2 Data Analysis Interviews were transcribed, professionally translated, and uploaded to Atlas.ti software package to facilitate analysis. The interview transcripts were coded in three steps according to grounded

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theory (Corbin and Strauss, 2008). First, text segments from the interview transcripts were labeled in a process of “open coding” to identify, categorize, and describe decision-making procedure, actors, and relevant organizational structure, as well as factors contributing to or obstructing policy reforms. The initial coding process resulted in 81 open codes (see Table 2 in Appendix A for examples). Second, axial coding was used to relate open codes to one another and to identify associational relationships (Corbin and Strauss, 2008). This axial coding is done via a combination of inductive and deductive thinking aided by computer-generated information of how frequently one code appears with another among the interview transcrpts (see Table 3 in Appendix A for examples). For example, we generate a list of member codes that fall under “influential factors for the transportation policy-making process.” Grouping and ungrouping among these member codes and reading of the context in which they are mentioned in the interview text allow us to further identify positive and negative relationships such as “contributing to policy making process” or “inhibiting policy making process.” The axial codes were finally consolidated into analytical categories to inform models for each of the two objectives of the study: identification of underlying contributors and obstacles in policy decision-making and detailed description of the entire process of transportation policy formulation at the city level. The analysis looks for instances where specific policy successes or failures have explicit connections to certain contributing or oppositional factors, as well as the context specific conditions which can be associated to the policy decision outcomes. Finally, supplementary survey data is presented to further validate some of the findings derived from the qualitative data analysis. Through this iterative coding process, we identified key underlying factors that help determine the evolution of transportation policy decisions as well as when certain transportation policies become adopted while others do not. We were able to also illustrate and explain the detailed process leading to policy decisions, derived from in-depth, recursive discourse with the relevant participants directly involved in the process in the two cities. Finally we cross validate our major analytical categories with our process model, explaining how these contributors and obstacles may impact different steps in the policy formulation process. This validation was done qualitatively; interview data was used to confirm where in the processual model each of the contributors and obstacles appear most prominently. 2.3 Supplemental Questionnaire Survey Interviews were complemented with a structured questionnaire survey that was distributed to and returned by individuals via email. Survey questions were designed to explore some of the specific contributors and obstacles to transportation policy decisions identified from the interviews (see Appendix C). The survey was distributed to a snowball sample of 90 government officials who are involved in the transportation policymaking process in Beijing and Shanghai. We received 57 valid responses from Shanghai and only 2 from Beijing, again highlighting the unwillingness of Beijing government officials to share details of their city’s policymaking process. 3. CONTRIBUTORS AND OBSTACLES TO TRANSPORTATION POLICY DECISIONS Contributors to policy decision-making are ways in which policy decision can be facilitated by city governments. In our study, we explore to what extent contributors identified for city-level policy decisions in other domains apply to the context of transportation policy in Chinese megacities. Coding the interview data according to Section 2.2, we identify three prominent contributors to transportation policy decisions – policy learning from other cities, transportation informatization (emerging, real-time sources of data for transportation planning), and public opinion – and four

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prominent obstacles to transportation policy decisions – public complaint, unilateral decision-making structure, lack of cross-departmental communication and coordination, and lack of adaptiveness in policy implementation. Generated by the Atlas.ti software based on our qualitative coding of concepts and their relations, Figure 1 illustrates connections among the key contributors and obstacles to city-level transportation policy decisions in China identified in this study. Many of these factors build on existing discussions of contributors of city-level policymaking which are summarized below, but we evidence many for the first time in the transportation context in China. The following sections discuss each of these contributors and obstacles in turn, first providing a brief overview of relevant literature (where applicable) and then summarizing and discussing the interview results from this case study. Figure 1. Relations among key contributors and obstacles to transportation policymaking in Chinese megacities.

3.1 Contributors to Policy Decisions 3.1.1 Policy Learning from Other Cities The concept of policy learning from other cities or lesson drawing refers to the idea that cities learn from transportation policy implementation in other cities both domestic and foreign. Dolowitz and Marsh helped formalize the study of policy transfer (between or within nations) as a result of strategic decisions taken by actors inside and outside government (1996; 2000). While such a rational choice framework for policy transfer has been challenged (Peck, 2011), the framework of Dolowitz and Marsh continues to be used to analyze the role of voluntary policy transfer (lesson drawing or policy learning) in facilitating policy at the city (EU—Timms, 2011) and national (China—Zhang and Marsh, 2016) levels. In the field of transportation, evidence shows that policy transfer is largely attributed to city officials (Marsden and Stead, 2011). In general, city government officials tend to value specific policy experiences by other cities because these policy experiences are derived from real-world cases (Marsden and Stead, 2011; Marsden et al., 2011). Often these are compelling because they incorporate objective data and emphasize tangible (as opposed to theoretical) outcomes (Marsden et al., 2011). City officials have a strong tendency to rely on policy learning because it is based on a documented ‘implementation stories’ and not just subjective accounts (Marsden and Stead, 2011). The results of this study further validate this claim and show that policy learning contributes to transportation policy decisions in large cities in China.

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In our interviews, there is substantial evidence of learning between Chinese cities. For example, Shanghai government officials indicated that Shanghai’s policies on how to plan lanes and parking sites for bike sharing systems are informed by the ‘Guidelines on Regulating Bike Sharing’ issued by Chengdu and Shenzhen. Additionally, a policy that restricted the registration of small cars in Beijing through a lottery was studied in comparison to an auction policy in Shanghai. Government officials in the two cities were quite confident that Beijing and Shanghai will continue to be models for other cities in China when it comes to adopting new transportation policies. This corroborates previous literature that identifies Beijing and Shanghai as past and current trendsetters in innovative transportation policymaking in China (Li, 2007). A number of examples also demonstrate policy learning from foreign cities. Government officials in Beijing and Shanghai devote a tremendous amount of time and resources to studying other international cases and incorporate this data and analysis in their policy decisions: BJTRC (Beijing Transportation Development & Research Center) mostly focuses on collecting data and doing research… They research on the international cases, especially the successful cases, and then they collect data and make their own decision. And after that, they invite some experts from both universities and industries/companies to make suggestions to the existing report. Several government officials at the Shanghai Transportation and Port Development Research Center explained that they visit other foreign cities like London, New York, Tokyo, Paris, Seoul, and Singapore to research transportation policy success cases and evaluate their feasibility and applicability to Shanghai. Specific policy examples include, Tokyo’s subway, Seoul’s rapid bus system, and Singapore’s congestion charging. While the validity and relevance of policy learning in the field of transportation is accepted as everyday practice, such a contributor should not be over-emphasized as the sole underlying approach to policy decisions in the transportation sector. There is also a possibility that more than one underlying contributor may drive policy adoption; for example, policy learning may initially drive adoption of new public transportation infrastructure such as bus lanes (by doing research on success stories in other cities), and subsequently data driven simulations, scenario evaluations, and other traditional planning tools conducted by city-level research units may determine the feasibility or applicability of such policy, utilizing data as key evidence (Volkery and Ribeiro 2009; Anda, Erath, and Fourie, 2017). 3.1.2 Transportation Informatization Champions of evidence-based policy decisions claim that since data-driven policymaking relies on after-the-fact objective measurement, it is more likely to minimize policy failures. Thus, policy reform, they believe, ought to prioritize “evidentiary” decision-making based on timely, accurate, and appropriate information (Howlett, 2009; Head, 2016; Arinder, 2016). Notably, the “policy analytical capacity” to argue that public policy is significantly determined by the analytical capacity of the responsible government entities (Howlett, 2009). Mu, Mouter, and de Jong (2016) also underscore the importance of analytical information when making decisions on transportation policy options.

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In our study, some participants identified transportation informatization as being an additional contributor to policy decisions. This term, coined by government officials in this study, refers to the newly developed information technologies that provide more hands-on data, which can be utilized to formulate more accurately targeted transportation policies. Newly developed platforms that allow for additional collection of transportation data significantly help the policy decision-making process by generating more rigorous, data-driven research reports. These new information platforms include “customized station videos, mobile phone applications, and other computer software.” For example, government officials in Shanghai explained that transportation informatization has opened up access to real-time arrival information for buses at every station, increasing the convenience of the system for passengers. Higher public transportation ridership (and associated increase in public transportation revenues) can then be used as evidence in support of public transportation-related policies. Interview participants from both cities expressed confidence that such newly developing platforms of information will be critical in the facilitation of future transportation policy decisions. Transportation informatization may be a key catalyst towards more data-driven policymaking, commonly cited as a contributor to better policymaking (Howlett, 2009). While most interviewees looked on transportation informatization as a contributor to effective and efficient policymaking, to have such a positive impact resources must be dedicated to data collection and systems must be put in place to process the data and generate knowledge for practice. 3.1.3 Public Opinion In addition to policy learning and data-driven policymaking, bottom-up public participation has emerged as a potentially valuable contributor to urban policymaking, particularly when working with multisectoral problems such as transportation (Carpini et al., 2004). While public participation is seen as an established part of democratic government, it can contribute value even in top-down policymaking regimes. Increased public participation can help frame the policy problem in more accurate and viable ways than professionals and government officials acting alone (Fung, 2015). When decisions involve important ethical or material trade-offs, the general public may be best placed to adjudicate those trade-offs and provide information relevant to devising solutions and evaluating implementation (Fung, 2015). Finally, the general public can sometimes become directly engaged in solving public problems and thus contribute additional resources through coproduction (Fung, 2015). While transportation policymaking at the city level in China still lacks formalized processes of public participation, in this study public opinion was identified by government officials as a third contributor to transportation policy decisions in China’s largest cities. While public participation and coproduction of policy are well-developed topics in Western democracies, the general public is not directly involved in the policy formation process in China. While there may not be direct avenues of public participation, our interviews indicate that city government officials in charge of policy formation pay significant attention to public perception. Respondents in Shanghai in particular (less prominent in Beijing) suggest that the government actively collects reactions of the public by publicizing policy research reports online and reviewing public reactions before implementing a specific policy. For example, a draft policy report on ride-hailing was published on the internet to observe how the public reacted to that specific policy. Evidence also supported other means by which city governments in China constantly monitor public perception towards potential policy decisions, such as via telephone call centers and other social network platforms like Weibo. Through various media platforms, government officials, particularly in Shanghai,

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observe general public opinion and this knowledge contributes to transportation policy decisions. In this way, public opinion serves as a key contributor to effective and efficient policymaking by drawing attention to critical transportation issues in need of policy action; however, public complaint in opision to policies can also be seen as an obstacle to policy decisions (as discussed below). 3.2 Obstacles to Policy Decisions 3.2.1 Lack of Cross-Departmental Communication and Coordination Based on the coding process, four primary obstacles to and challenges for transportation policy decisions in the two cities emerged from the data. Transportation policies in Chinese cities are primarily the responsibility of a municipal Transportation Committee and its subsidiary organizations. However, many transportation policies touch on issues related to housing, urban development, and the environment, and therefore necessitate close correspondence across several bureaus or departments within the city government. Due to the inherent organizational setting and notion of competition that exists among these departments, lack of communication and coordination among key bureaus and department is one of the key obstacles to effective transportation policy implementation. For example, one of the government officials in Shanghai expressed difficulties in getting ideas developed into a policy decision when that policy decision involves other relevant departments: If I promote it up to my direct leader, it won’t be that difficult. But when it involves the peer department, or peer-crossed department, which sometimes indeed will happen, it will become difficult. Because once the peer department is involved, my leader needs to communicate with them, instead of me. In China, as for the coordination and communication including that of information and some other matters between government departments, the two departments involved need to coordinate at the city government level. Interviews also suggested that departments within the same city government are reluctant to share information, even when certain policy outcomes rely heavily on cross-departmental correspondence – such as transportation policies like bus rapid transit that are closely associated with the housing and construction department. In particular, the issue of competition arose between two departments after a change in organizational structure in 2014, when Shanghai Transportation Committee absorbed a portion of functions in transportation of the Shanghai Construction and Transportation Authorities. But since 2014, the Shanghai Housing and Urban and Rural Construction Management Committee is still not willing to give up some of its role in transportation due to unclear division of functionality. This identification of the lack of cross-departmental communication and coordination as a key obstacle in city-level policymaking in China is corroborated by other studies. With reference to the organizational structure in Wuhan, Spear (2006) explains that a main challenge is for key agencies to cooperate and to reconcile the “overlaps and gaps in responsibility.” Such intrinsic tensions further inhibit possibilities for closer correspondence, which may be critical in pushing certain transportation policy ideas into policy decisions. Huang (2003) also underscores the importance of data sharing among governmental agencies, pointing out that information sharing is an inherent cultural challenge. In China, open discussion and cross-departmental exchange in information is

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not widely practiced. As indicated in Figure 1, cultural value coupled with the established hierarchical decision-making structure is closely associated with the lack of active cross-departmental coordination. 3.2.2 Public Complaint Interview participants also identify public complaint as one of the key obstacles to transportation policy decisions. While the general notion of public opinion may facilitate a transportation policy decision, public complaint may inhibit immediate policy adoption. One prominent example is the potential implementation of congestion charging in both Beijing and Shanghai. Participants in Beijing, in particular, emphasized that congestion charging was seriously considered over the past five years after careful study of similar systems in London and Singapore. However, the policy was not adopted because the public was not favorable towards the idea of congestions charging. One official from Beijing’s said: [When it comes to] congestion charging, mainly the pushback comes from local residents. They make a big noise on the Internet, and they don't quite understand the logic behind the congestion charge [or charging]. It's not that straightforward. The people feel, “I have the right to drive around. Why do you charge me extra money for my existing rights?" It's part of the communication issue. Other participants in Beijing suggested that congestion charging policy may have failed to gain support because a large proportion of the city population resides in the inner city. In contrast to the case of public complaint stalling the implementation of congestion charging, the Beijing city government was quick to adopt “bus only lanes” since the public did not seem to express disagreement to such a policy initiative. Interviews in Shanghai also suggest that public complaint can be an obstacle in policy decision-making. In Shanghai, for any issues related to city construction and transportation, anyone can dial ‘12319’ and file a complaint. Thus, depending on the type of policy and city, public opinion can be both a contributor and a hurdle to immediate transportation policy decisions. 3.2.3 Unilateral Decision-making Another obstacle in implementing transportation policy is unilateral decision-making. Government officials in both cities commented on how one or two individuals in top leadership positions in the city government make final policy decisions, and that these decisions may not always reflect the details or recommendations of research reports. In both cities, government officials in research units under the city’s Transportation Committee (i.e. technical staff) expressed their lack of agency in the decision-making process. It is clear that in most cases, either the mayor of each city or the leader of each Transportation Committee makes the final decision on transportation related policy decisions. Our case study corroborates findings by Matsumoto (2007), who finds that mayors in Chinese cities have enormous discretion over transportation policy decisions and budget planning compared to mayors in other international cities. This unilateral decision-making evokes an important tradeoff between the efficiency of transportation policy implementation and the efficacy of transportation policy. While having centralized decision-making authority at the discretion of the mayor may expedite the adoption of certain transportation policies, such unilateral policy decisions may be the product of political

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expedience rather than objective, analytical data that suggests effectiveness in addressing actual needs. In extreme cases, such decisions may primarily be driven by an individual mayor’s desire to improve his/her performance record for career promotion (de Jong, 2013). Based on case studies in Dalian, Mu, Mouter, and de Jong (2016) claim that transportation policy decision-makers use analytical information in a symbolic way, as a “rational ritual.” They suggest that the policy research process and resulting analytical information in China is pursued to create the image of a logical process rather than to directly inform the policy decision-making process (Mu, Mouter, and de Jong, 2016). Therefore, analytical reports can be highly dependent on political guidance and Chinese city government leaders are capable of justifying their decisions by pulling in selective resources that purposefully support the viability of their decisions (Mu, Mouter, and de Jong, 2016). Under such circumstances, the analytical information is no longer neutral or transparent (Mu, Mouter, and de Jong, 2016) and despite logical, investigative frameworks political leaders make ultimate policy decisions unilaterally. 3.2.4 Lack of Adaptiveness Associated with the above concept is the fact that it takes a long time to implement transportation policies. In certain cases, initial policy recommendations made by research units may become outdated before policy is actually implemented. Many interview participants suggested that the current transportation policy decision process is inefficient because it lacks the capacity to adapt to ever-changing environments in local contexts. The following statement made by one of the government officials in Shanghai clearly demonstrates how the current transportation policymaking process does not quickly respond to prominent transportation-related problems in the city: I think the best choice is to make a policy that is needed to solve the existing problem and immediately implement the policy and achieve the desired result. In contrast, if we have researched all policies and established them only for back-up, after two or three years, the situation would have changed. Even if we have many back-up policies to use, as they don’t meet the development needs any longer, we have to remake the policy when we really need it. In such case, a lot of time, resources and manpower would be wasted. The process of transforming a policy in theory into practical implementation is not so smooth, and this is mainly due to a critical problem, that is, we haven’t done enough in achieving adaptive or dynamic effect. Likewise, interview participants from both cities cite a need to improve the current policy decision-making process to implement transportation policies in a more effective and efficient manner.

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3.3 Survey Results and Contributors to Transportation Policy Decisions In addition to the in-depth interviews, we conducted the questionnaire survey among government officials in Beijing and Shanghai. Given the lack of response from Beijing officials, we present here only the results for the N = 57 responses from Shanghai. In particular, here we look at responses to four Likert-format questions related to the two most important contributors according to groundedness theory: public opinion and policy learning (see Table 2 in Appendix A). Respondents were asked about their organization’s policy learning from both domestic and foreign cities as well as their levels of awareness of public opinion and media coverage: 1. ‘I am aware of the public perceptions of current transportation policies’ 2. ‘I am aware of the media coverage on current transportation policies’ 3. ‘I believe my organization/department/bureau studies best transportation policy cases in other cities in China’ 4. ‘I believe my organization/department/bureau studies best transportation policy cases in other cities in the world’ In addition, one Likert-format question related to the obstacle of unilateral decision-making. Respondents were asked about how they perceived their own agency in the policymaking process: 5. ‘I have some authority in making policy decisions’ For each question, respondents were asked to rank each statement from ‘strongly agree’ to ‘strongly disagree.’ Figure 2 provides the distribution of responses. Figure 2. Agreement with statements on policy learning from other cities and awareness of public opinion among Shanghai government officials (N=57).

An overwhelming majority of respondents agreed with all four statements related to the contributors of public opinion and policy learning. This corroboraties the findings from the qualitative interviews that officials pay attention to public opinion and the media and participate in policy learning from both domestic and foreign cities. In regards to awareness of public perception and media coverage of current transportation policies, the majority (60%) of Shanghai government officials partially to strongly agreed. An even greater proportion of officials expressed awareness of media coverage on transport policies. This reinforces the finding that public opinion is a contributor to mobility policy decisions in Chinese cities, but may suggest that it is not quite as common a practice for government officials as policy learning. In regards to policy learning, an

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overwhelming majority of Shanghai government officials agreed that their organization participates in both foreign and domestic policy learning. However, our survey might suggest that government officials in Shanghai look to international best-practice more than domestic experience when it comes to policy learning from other cities. When it comes to obstacles to effective and efficient policymaking in the transportation sector, some interviewees noted unilateral decision-making as a key factor. Our survey responses suggest that many government officials in Shanghai feel that they have at least some authority in making policy decisions. However, over one third of respondents (35.2%) were either neutral or disagreed, suggesting that a significant number of government officials feel they have little agency when it comes to effecting transportation policy. Therefore, our survey data helps reinforce our findings regarding the key contributors of public opinion and policy learning and alludes to obstacles related to unilateral decision-making and a lack of agency among government officials. The following section further elaborates on the transportation policymaking process and maps where these contributors and obstacles fit within the actors and steps of this policy decision-making. 4. PROCESSUAL MODEL OF TRANSPORTATION POLICY DECISIONS In addition to identifying key contributors and obstacles to transportation policy decisions in Chinese cities, coded interview data also clarify the process by which the city governments of Beijing and Shanghai arrive at transportation policy decisions. While there are studies that (i) introduce the institutional structure of key organizations involved in transportation related matters (Huang, 2003; Spear, 2006), (ii) describe the general process of how certain large scale transportation infrastructure projects are instigated (from conception, feasibility study, and approval to operation) (Mu, Mouter, and de Jong, 2016), and (iii) emphasize the role city governments can play in addressing the complex interplay of constantly changing physical characteristics such as demographics, housing developments, motorization and people’s travel demand (Shen, 2002), to the author’s knowledge there is not yet a study that explains the internal decision-making process of transportation policies at the city level in China. Extending beyond descriptions of organizational distribution and responsibility, this section offers a detailed process of city-level transportation policymaking, carefully compiled from the analyzed data. It also connects each of the contributors and obstacles identified in the previous section to the relevant actors and policy flows within this process. In brief, we find that transportation policies at the city level are responsive to transportation problems or strong demand from the general public. Once a problem is identified, the transportation committee in each city tasks their respective research centers to analyze the problem and possible policy responses and produce recommendations. These recommendations may translate into actual policy adoption at the city transportation committee level, or be submitted to the city government leadership for final decision. Figure 3 summarizes the overall process leading to transportation policy decisions in the two representative cities in China, including how certain contributors and obstacles identified in Section 3 connect to this process.

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4.1 Responding to a Transportation Problem and the Importance of Public Opinion Interviews suggest that in most, if not all transportation policy cases, policy decisions are initiated in response to prominent and prolonged transportation-related problems. In interviews, government officials and external experts all observed that only when problems like air pollution or severe congestion become serious enough did the city government begin the process to issue specific policies to remedy these problems. The following is a quote from a city government official from Shanghai. [The government] can't sense some problems, predict the underlying consequences and take some measures in advance but only begin to find solutions until the problems are very prominent and intense. While it may be natural that policies are inherently designed to address problems, interview data also indicate that such a purely responsive transportation policymaking process may prohibit proactive and predictive measures. Moreover, coded findings indicate that public complaints, identified as an obstacle to policy decisions in Section 3.1, may in some cases trigger city government to take concrete action by highlighting the transportation issues that need a policy response. For example, congestion has been a prolonged issue in both Beijing and Shanghai and the general public continues to complain to city government to take affirmative action to mitigate these problems. Pressure from the public led to government consideration of adopting congestion charging policy and other intermediate measures. Via specific action such as posting complaints online on social networks platforms, or filing complaints by phone, the general public plays a role in asking for concrete policy action from the city government. In parallel, So and Kao (2014) claim that despite the authoritarian regime in China, the public policymaking process is gradually shifting towards greater civic engagement, unconventional forms of political participation such as street protests, public participation, and internet discussions (So and Kao, 2014). In extreme cases, they point out that street protests have been particularly effective as a means for the public to get its message across, since Chinese local governments have been quite concerned about maintaining political stability (So and Kao, 2014). Our interviews seem to corroborate these findings, suggesting that, despite lacking a formal public participation process, Chinese cities account for both public opinion and public complaint when making transportation policy decisions. 4.2 Initial Response at the National and City Level When a certain transportation problem receives sufficient attention, both the Ministry of Transportation (national government) and the Transportation Committee in each city begin to take action. The national government sets general targets or goals, as exemplified by its 13th Five-Year Plan, which lays out general targets to address challenges including urbanization, transportation, and climate change (Koleski, 2017). However, the Ministry of Transportation does not usually dictate specific transportation policies for cities to meet these targets. Instead, the interview results indicate that once the Ministry of Transportation recognizes a nation-wide transportation-related problem, it issues an “instructive suggestion” to the 31 provinces, cities, or autonomous regions nationwide to come up with localized solutions that fit within the national agenda. The specific research, study, and adoption of transportation policies occur within each autonomous region as

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evidenced by the following statement made by a city government official in Shanghai: As for the specific transportation policies, they are now all decided by local departments or adjusted according to local conditions. We can understand it from the policy in Shanghai. Alternatively, in certain cases, a city government’s Transportation Committee may react to smaller, more localized transportation problems without a national-level directive. In either case, whether the initiation begins from the Ministry of Transportation (at the national-level) or the Transportation Committee (at the city level), the process then continues to the research centers under each city government. 4.3 City Research Centers Based on the particular transportation-related problem identified by the Transportation Committee, the respective research center – like the Shanghai Transportation and Port Development Research Center or the Beijing Transportation Development Research Center – in each city is assigned the policy task. The appropriate research center (by area of expertise) conducts internal surveys to test certain policy ideas. Government officials in the research centers in both cities indicated that they usually do not share the survey reports with the Transportation Committees or Ministry of Transportation. Then the research centers generate research reports that combine the internal survey results with other materials that are collected from existing research or from the experiences of other cities. This is where learning from other foreign and domestic cities, previously identified as a key contributor, is incorporated in the transportation policy decision. One important finding in this phase of the process is that, instead of blindly adopting best case practices from what other international cities have done, Chinese officials contextualize the lessons learned with their own analysis based on internal survey results. The notion of contextualization in policy transfer agrees with previous studies into the re-association of successful policy ideas into the new institutional environment and domestic context (de Jong, 2013). Once the research report is produced, the respective research centers host expert group meetings to analyze and discuss the research report on the feasibility of possible policy decisions. During this phase, experts like academics from local universities provide their own opinions and suggestions on the proposed research reports. Through revision and final review meetings internally, the revised research report is submitted back to the Transportation Committee. 4.4 Final Policy Decision The interviews indicate that the final transportation policy decisions are either made by the city government leadership – the mayor or the party secretary – or the Transportation Committee. While the former process depends largely on the mayor’s individual discretion, the latter involves additional steps to “absorb the opinion from [the] social public” by publicizing policy research documents. Then, depending on the public reaction, policy implementation decision may be announced or the Transportation Committee may withhold immediate implementation decision due to unfavorable local acceptance. This is the reason why the general public appears twice in the processual model in Figure 3: once as a contributor in the problem initiation phase and again as an obstacle during the consultation phase at the Transportation Committee level.

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The transportation policy decision-making process may vary by the type and scale of policies. For example, when it comes to specific, smaller scale policies – like providing free subway passes for the elderly in Shanghai – the implementation decision can be directly made by the Transportation Committee. However, larger scale policies like the introduction of a car license plate auction must be submitted to the city government leadership for review. It is this phase in the process where the obstacles such as unilateral decision-making and lack of adaptive policymaking become most prominent. Coded data indicate that when recommendations on larger scale policies are submitted to the city government, officials in leadership positions possess full discretion to make policy decisions regardless of the details of the technical reports. In other words, even though the researchers in the subsidiary bodies provide reports on data analysis and modeled results, when decisions move to higher levels of government their recommendations may not be implemented at all. Similarly, interviews suggest that since local conditions continually change over time, when policies are held for long periods some of the policy recommendations may become outdated and may require new research processes with a new set of policy research results. The processual model is not an exclusive or exhaustive summary of all transportation policymaking processes in all Chinese cities. However, the coded results reveal a very similar procedure for the two case cities on how transportation policy ideas are generated and how such ideas are re-shaped, altered, and substantiated by multiple actors and public opinion until finally implemented.

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1

2 3 4 5

Figure 3. Processual model for transportation policymaking at the city level in China.

Key: Input (from initial problem) Flow (within the Research Center)

Output (Transportation Committee) Output (City Gov’t Leadership)

Actor

Contributor

Obstacle

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4.5 Variations in Beijing and Shanghai As explained in Section 1.2, the cities of Beijing and Shanghai are similar across a number of attributes including population size, area of land development, degree of economic development, and diversity in transportation policy adoption. From interviews with government officials, professionals, and academics in both of these cities, we identified a common processual model for transportation policy decisions, incorporating key contributors and obstacles. However, there may be variation across departments and bureaus within each city (dependent on an individual leader’s style or the key functions of an organization). Other differences between the two cities appear to be steeped in underlying cultural differences. For example, our data collection experiences corroborate common wisdom that Shanghai has a more transparent policymaking process than Beijing, which tends to be more conservative and closed. Furthermore, multiple interviewees pointed out that Shanghai’s city government is generally more visionary than Beijing. The following is an exemplary remark by one of the government officials in Shanghai: I think Shanghai and Beijing are quite different. Beijing is like problem-driven. It is the congestion that people complain, and it's more like rescue-type of policy. It's not very visionary, not like Shanghai. And also, as compared to Shanghai and Shenzhen, which is more market-oriented economy, I think people are more open to innovations, like some of the bottom-up good exercise get absorbed in the policymaking process much easier than in Beijing. While in both cities the initial policy idea is driven by intensification of transportation-related problems, the interviews suggest that Beijing is more likely to be problem-driven than Shanghai. Shanghai is presented as more visionary in terms of policy formation. Participants in Shanghai suggested that those in top leadership positions with decision-making authority in their city were more optimistic towards policy innovation compared to those in Beijing. This variation provides some evidences towards a claim that while Beijing does possess many similar characteristics as Shanghai, it demonstrates a higher tendency towards more conservative, top-down policymaking processes. Distinctions between the cities such as these are important areas for future research, but not necessarily captured in our current processual model that is designed to be representative of the general process in both cities and other Chinese megacities like them. 5. DISCUSSION We acknowledge that using 32 interviews in two megacities can only offer a first impression of the current transportation policymaking process at the city level in China. However, we believe that the findings in this paper can inform both the academic community and the Chinese national and local governments. Future research can replicate, verify, and update the identification of contributors, obstacles, or the processual model introduced in this research, through application to other Chinese cases. Government officials may take note of what contributors to policymaking might be fostered at the city level or how to remove obstacles. For example, government officials may wish to support policy learning and transportation informatization at the research center level and to establish transparent communication channels between higher-level political decision-makers and research staff empowered with this comparative, case-study knowledge and new forms of information technology. These communication channels may help to reduce unilateral decision-making and encourage adaptiveness in the policymaking process. In addition,

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city-governments may endeavor to clarify roles over transportation functions and encourage data sharing among different departments for large-scale policy decisions that affect transportation, housing and development, construction, and other sectors. In addition to supporting existing contributors, government officials in Chinese cities may want to build on positive experiences of policy experimentation in other contexts as a way to build adaptiveness in their transportation decision-making. China has been lauded for its national policy process of decentralized experimentation, in which central policymakers encourage local officials to problem-solve and then model national policy formulation on successful local experience (Heilmann, 2008). At the city level, Mei and Liu (2014) demonstrate that urban housing policymakers in Chinese cities are conscious of the value of experimentation in policy design, initiating small-scale experiments on different policy options, then finally, making policy implementation decisions based on the outcomes of these experiments. While the idea of learning through purposeful policy experimentation and adaptiveness is well accepted, our interviews suggest that in transportation policymaking at the city level, bureaucratic realities and processes fall short. Therefore, this study suggests that Chinese cities may benefit from more formalized processes for policy experimentation in the transportation context. This study also suggests further research and attention is needed to address public participation in the policymaking process at the city level in China. In 2014, China’s national government issued the ‘National New-Type Urbanization Plan’ (2014-2020), which promoted goals of urban sustainability and drew attention to encouraging and supporting citizen participation in the process of new-type urbanization. Despite this national goal, literature suggests that the policymaking processes and cultural practices in China’s urban development are still imbued with a distinctive top-down mode of decision-making in which public participation is not well institutionalized in strategy development (Li and de Jong, 2017). A case study in Suzhou suggests that the extent of citizen participation differs between the decision-making and implementation phases, with local government taking a top-down approach to strategy development but involving citizens in its implementation (Li and de Jong, 2017). Other studies also suggest that government authorities still “regard public participation first and foremost as a means to increase the effectiveness of policy measures and officials leave no doubt that the promulgation of… goals and policies should remain an exclusively state affair” (Martens, 2006). Many see this involvement of the public during downstream implementation of policy rather than in policy formation is deeply rooted in traditional Chinese “principle of mass participation,” where the focus is on participating in the implementiation of government plicies, plans, or projects rather than the Western concept of participation that focuses on the development of the policies themselves (Li, Ng, and Skidmore, 2012). In view of this cultural difference, it is perhaps not a surprise to that public participation, in the Western sense, is limited in many policymaking domains in China. Our interviews provide a more in-depth and nuanced understanding of public involvement in city-level transportation policymaking from the government’s perspective. Our results suggest that public opinion plays an indirect role as a contributor to early project initiation by drawing government attention to key transportation issues, while public complaint acts as an obstacle to policy implementation. Therefore, although there may be no formalized public participation process during policy development, we found that technical government officials involved in strategy and policy development are aware of and responsive to public opinion expressed through call centers, government websites, in print and social media. However, by not involving

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constructive public contributions in early planning and the development of policy, public complaint – and other traditional forms of (ex-post) public involvement in “decide-announce-defend” style policymaking – proves an obstacle in legislative procedure (Enserink and Koppenjan, 2007). The role of the public remains ad-hoc and transportation policymaking at the city level in China may benefit from carefully structured, formalized processes of public participation that constructively capture public opinion, particularly during policy formation (between policy initiation and implementation). However, any such “democratization” of the policymaking process may need to take different forms than those commonly found in the West to speak to the different cultural and historical view on participation in political and social affairs held by Chinese citizens (Martens, 2006; Li, Ng, and Skidmore, 2012). 6. CONCLUSION AND FUTURE WORK Through iterative qualitative analysis of primary interviews of government officials, this research identifies key contributors and obstacles to transportation policy decisions in Beijing and Shanghai, China. For the first time in existing scholarship, we map the process of transportation policy decisions among different governmental actors in Beijing and Shanghai. The processual model for transportation policy decisions described in this paper is drawn from similarities among 32 interviews with government officials, academics, and transportation professionals in two Chinese megacities. Government officials and participants directly involved in the process of policy formulation in these cities, who strive to improve the current process to engender more effective transportation policies, ought to foster the contributors and remove the obstacles identified in this study. While the identification of contributors, obstacles, and the processual model did undergo an ad-hoc validation process of comparison to the interview transcripts and review by a few government officials and academic colleagues, it should continue to be validated and developed through discussion with practitioners in Beijing and Shanghai. Future work could consider the generalizability and applicability of our contributors, obstacles, and process to other Chinese cities and other international cities at different stages of city-level transportation policymaking. Other areas for future research include additional semantic and mixed methods analysis of the interview and survey data. This may help to identify a few successful and unsuccessful transportation policy initiatives that warrant a deep-dive investigation of draft policy documents and related research reports. Such an investigation could illustrate how our general presentation of contributors, obstacles, and transportation policymaking process play out in certain situations. In addition, this study adopts a grassroots approach, in which we ask policymakers, practitioners, and academics in our target cities to identify existing contributors and obstacles. Future work might also consider a high-level approach that reviews existing literature on effective and efficient policymaking and discusses how these general lessons might apply to the context of the transportation sector in China’s megacities. While future work remains to refine the processual model, validate its applicability to other cities in China, and illustrate its application to specific policies, the authors hope that this study will begin a broader discussion on the ways in which transportation policy is managed at the city rather than national-level in China and other countries. This discussion can be informed through

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APPENDIX A. ATLAS.TI INTERVIEW CODING Table 2. Examples of open codes sorted by groundedness Open Codes process of policy-making actors in the process structure public opinion [contributor] policy learning [contributor] foreign city example of horizontal learning post policy implementation evaluation problem-based policy-making public complaint [obstacle] example of policy unilateral decision-making structure [obstacle] differences between Beijing and Shanghai cross-bureau communication coordination [obstacle] congestion charging transport policy failure example reasons for policy failure foreign city learning lack of communication and coordination [obstacle]

Groundedness1 52 33 25 14 10 8 8 8 7 7 6 6 6 6 5 5 5 5

Note: The Atlas.ti software package calculates groundedness and density for each code, which shows how often the codes are used and how they relate to one another. Higher values of groudedness indicate more often used and connected codes.

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Table 3. Examples of axial (associational) coding Association or Category Influential factors for the transportation policy-making process

Shanghai transportation policy-making organizational structure

Members codes – adhoc complementary transportation policy planning – public opinion Policy learning: – domestic city example of horizontal learning – examples of foreign cities – foreign city example of horizontal learning – foreign city learning Reasons for policy failure (obstacles): – transport policy failure – transport policy failure example – cultural problem – issue of competition among departments and bureaus – lack of communication and coordination – reasons for lack of communication and coordination – no innovative policy-making – public complaint – unilateral decision-making structure Actors in the process: – academia – mayor's office – national level government – research center – Shanghai transportation commission – structural change in 2014 Steps in the process: – survey research – survey report – expert consultation meetings – research report – revision of research report – submit report to municipal government

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APPENDIX B. INTERVIEW QUESTIONNAIRE Version for Government Officials 1. In your opinion, what factors are important in making transportation policy decisions? 您认为什么是影响交通政策制定的重要因素？ 

What are some of your reasons for describing those factors? 您为什么选择描述这些因素？



Do you pay attention to the following for example: statistics on congestion and pollution levels, complaints from citizens, other international cities' experience etc.? 您（你们）是否注意到了以下因素：拥堵和污染程度的统计，市民的意见，世界其他城市 的经验等？

2. Can you give me an overview of the specific issues your department/bureau addresses or works on? 您能谈一下你们部门具体是做什么吗？ 3. Can you describe your role and your practice in your department/bureau? 您在部门里负责哪方面的工作？ 

Do you think that you are directly or indirectly involved in the policy-making process? 您直接参与还是间接参与政策制定的过程？



If so, how? 如果是，如何参与的？

4. I’d like to know more about how transportation policy is made. In particular, I’m interested in what causes policy changes in transportation. 我想知道交通政策是如何制定的。特别地，我希望了解什么引发了交通政策的变化。 

Can you give me an example of a recent policy shift that addressed transportation problems in your city? 请举一个例子关于最近的交通政策变动？



What is the overall process like? Does it involve initial research? 总体程序是怎样的？有初期研究吗？



How is the decision proposed? 这个决策是如何提出的？



I'd also like to hear more about the process leading to implementation. 这些政策是如何落实的？



Who makes the final decision? 谁做最终决定？

5. How would you evaluate the policy-making process that you described? What criteria do you use to evaluate the transportation policy you just described? 您如何评价您所描述的政策决策的过程？您用哪些标准来评估这个政策？ 

What do you think worked and did not work? 对于决策过程，哪些是成功的？哪些不成功？

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If it did not work, how would you improve the process? 如果有不成功的地方，您认为如何改善？

6. Can you give me some examples of successful policies? Also can you give some examples of failed policies? 您能给我一些成功政策的例子吗？以及失败政策的例子？ 

What is your reasoning behind your thoughts? 这些成功的政策，您为什么认为它是成功的？

Version for Non-Government Professionals 1. In your opinion, what factors are important in making transportation policy decisions? 2. May I ask your current position and your current work at your organization? 3. Can you talk about your experience with working related to [your city’s] transportation or mobility policy? Please provide any examples. 4. Can you describe your understanding on how [your city’s] municipal government’s mobility/transportation sector is structured - i.e. key departments or bureaus. Here it would be great if you could talk about municipal level transport policy structure, who are mainly involved, what are their main interests, etc. 

Perhaps because Beijing is also the capital city of the country, do you think Beijing municipal government has less say in local transportation policy decisions, (the national government being involved)?

5. Please share your knowledge on how process of mobility policy making in Beijing or any other city what is not often revealed in the books, for example, 

What is overall process like - example) Hierarchical?

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What is the practice at department level and individual level

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Involve study or internal research?

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Pay attention to data?

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Public opinion? Or other agencies?

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Borrow from other cities or foreign cities?

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What are the key factors in making policy decisions? Here, feel free to use specific policies as examples.

6. How would you evaluate this process? 

What will you propose or recommend the city government do differently if you had the opportunity?

7. Can you provide some insights on policies that you think worked well and failed? and why? 8. Decision making dynamics: 

How much leverage does each department have in making own decisions?

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Is decision-making more vertical (from national) or in some sense horizontal (from other cities)?

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Respective of external expert opinion?

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Who makes final decision?

9. How is the private sector (industry itself) involved in transportation/mobility policy making process? How much participation do they have?

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APPENDIX C. FOLLOW-UP SURVEY QUESTIONS 1. Which city do you work for? 您在哪个城市工作？ o o

Shanghai 上海 Beijing 北京

2. Do you periodically observe any transportation data in your city? 您经常关注您城市的交通数据吗？ o o

Yes 是 No 否

3. If answered yes, please indicate which data you regularly follow: ______________. 如果是，请说明什么数据是您经常关注的。 4. What do you consider the most serious problem in transportation in your city? 您觉得在您的城市最严重的交通问题是什么？ o o o o o o

Lack of public transportation 缺少公共交通 Congestion in traffic 交通拥堵 Lack of bicycle lanes and walkways 缺少自行车道和人行道 Pollution from automobiles 机动车污染 Insufficient parking spots 停车位不足 Other: _______. 其他

5. When dealing with congestion problems, which of the following variables do you think should be given greater attention? Rank the following five variables where: 1 = least important to 5 = most important. 当面对拥堵问题时，下面哪一个因素您认为需要额外注意？请为下列因素打分，1, 2, 3, 4, 5 （1=最不重要，5=最重要）     

Number of private vehicles owned (number of license plates) 私家车拥有量（牌照数量） Vehicle usage captured by ridership 机动车使用量 Population density 人口密度 Road density 道路密度 Public transport ridership 公共交通使用量

6. Do you believe that the number of private cars registered in your city reaching a certain threshold affects the formulation of policies to address congestion? 您认为在您的城市私家车数量达到一定数值会引起有关治堵的政策出台吗？  Yes 是的  Somewhat 一定程度上  No 不  Do not know 不知道  Not applicable 不成立 7. I’d also be interested in knowing your thoughts on public perceptions towards transportation issues:

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我想知道您对交通问题的一些想法 Neither Strongly Partially Partially Strongly Agree Agree Agree Agree Disagree Disagree Disagree nor 非常同 同意 部分同 部分不 不同意 非常不 Disagree 意 意 同意 同意 中立

I am aware of the public perceptions on current transportation policies. 我知道公众对现在交通政策的想法 I am aware of media coverage on transportation policies in my city. 我知道媒体对交通政策的报道范围 I find congestion to be most serious transportation issue. 我认为拥堵是最严重的交通问题 I believe my organization/department/ bureau studies best transportation policy cases in other cities in China. 我认为我的组织或机构学习研究了中 国其他城市最好的交通政策案例 I believe my organization/department/ bureau studies best transportation policy cases in other cities in the world. 我认为我的组织或机构学习研究了国 外其他城市最好的交通政策案例 I have some authority in making policy decisions. 我在制定政策上有一定权威

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8. To deal with transportation problems in your city, which of the following values do you most strongly uphold? Rank the following five values where: 1 = least important to 5 = most important. 在处理您城市的交通问题上，以下哪些价值您最看重？请为下列因素打分，1,2,3,4,5 （1=最不 重要，5=最重要）     

Protect the liberty and personal freedom 保障个人自由 Increase the efficiency of the existing transportation system 加强已有交通系统的效率 Expand accessibility and mobility to more people within the city/region 为更多乘客提供交通设施的可接近度，增加人群的能动性。 Cause less harm to the environment 减少环境危害 Ensure social and economic equity in the city 保障城市中社会平等和经济平等

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9. If your city decides to introduce additional policies this year, which of the following policies would you support? Please choose your top three options. 如果您的城市决定在今年制定新的政策，您将支持哪一项政策？请选择前三个您将支持的政策。            

Build additional roads 新建公路 Provide more parking spaces 新建停车空间 Limit private vehicle registration/ownership 控制私家车登记数量或保有量 Price the use of private automobiles in city center (i.e. congestion pricing, more expensive parking) 对城市中心的私家车收费 （比如拥堵费，较贵停车费） Physically limit passage of private automobiles in city center by closing off roads to traffic 限制私家车进入城中心 Subsidize clean energy vehicle ownership (i.e. tax cuts in hybrid or electric vehicles purchase) 补贴清洁新能源汽车（如对混合能源或耗电机动车减少税收） Expand public transportation service (bus/train) and/or provide new, sustainable forms of public transportation 扩大公共交通服务并/或提供新的可持续发展的公共交通模式 Prioritize public bus lane and/or bus rapid transit 公共交通线道优先或 BRT Increase government subsidy of public transportation fares (i.e. discount on transit) 提高政府对公共交通费用的补贴（如公共交通乘车费折扣） Expand bike lanes 扩展自行车道 Improve pedestrian facilities (i.e. sidewalks, street crossings, courtyards, etc.) 改善人行设施（如人行道，交叉口等） Other: ________. 其他

HIGHLIGHTS  Identifies policy learning, data informatization and public opinion as contributors  Identifies public complaint, unilateral and fragmented decision-making as obstacles  Suggests indirect public participation is both a contributor and obstacle  Proposes processual model for transportation policymaking in Chinese megacities  Discusses lack of adaptiveness and potential for city-level policy experimentation