Abstract

     Most sustainability assessment systems focus on comparing the sustainable progress across cities, and few concentrate on tracking the sustainability progress of cities over time with the consideration of the 17 United Nations Sustainable Development Goals. Tracking the sustainable progress of cities over time can help unveil the potential obstacles and challenges in city governance and provide references for city policy-makers. Hence, the present study built up a framework to evaluate sustainable development progress in Shenzhen from 2005 to 2019. Shenzhen is a young megacity with only 40 years of history, and it is one of the demonstration zones to represent sustainable development in China. Fifty indicators in the dimensions of innovation vitality, public service, and living environments are chosen to consider the focus of both UN SDGs goals and Shenzhen’s sustainable development plans. The potential bottlenecks for city development are identified, and effective policies implemented by Shenzhen policy-makers are highlighted. Results showed that the innovation vitality in Shenzhen had improved continuously since 2005, but public service and living environments both showed a falling trend after a peak in 2014 and 2016. The result revealed that as a megacity, Shenzhen should pay more attention to public service and living environments, especially in the construction of schools at all levels, salvation management centers, and green space, and improve air quality to meet the requirement of higher rank in sustainable urban development. It is suggested that cities build a solid system to monitor their progress towards achieving the 17 Sustainable Development Goals. The experience from Shenzhen can be adapted and implemented by other young megacities worldwide to accelerate their path towards sustainability.

Introduction

     The concept of sustainable development was first mentioned in the United Nations report named “Our Common Future” in 1987, which defined sustainable development as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” (Brundtland et al., 1987). Various economic development modes, strategies, and policies worldwide were then developed by considering economic, social, and environmental factors simultaneously, so-called in a sustainable way (Wu, 2013; Jepson, 2004; Moe et al., 2006; Strong, 2006). In 2015, the United Nations announced the report “Transforming our World: The 2030 Agenda for Sustainable Development” (The, 2030 Agenda), which put forward 17 global sustainable development goals (SDGs) by 2030, which lead the path towards sustainable development to the new page (UN, 2015b).

Conclusion

     The research focused on evaluating sustainable development progress in the megacity Shenzhen from 2005 to 2019 by constructing an index system covering three dimensions of innovation vitality, public service, and living environment with 15 s-level and 50 tertiary indicators. According to the assessment, overall sustainable development in Shenzhen was much better in recent years. The growth rate of sustainable development score was rapid before 2013 but slower afterward. In terms of the three dimensions of Shenzhen’s sustainable development, innovation vitality kept improving since 2005. Public service improved before 2014 but regressed after that. The living environment improved before 2016 but showed a falling trend afterward. The evaluation indicates that Shenzhen paid great attention to the construction of innovation vitality.

      In terms of future development, it is suggested that the local government build a more solid sustainable assessment system with indicators covering all 17 SDGs to monitor the progress to sustainability. Shenzhen could accelerate the construction of higher education institutions and research institutes by cooperating with top universities and financial and policy support for sustainable urban development. The burden of innovation investment may be relieved by training programs or networking organized by the government. The obstacle of public services is suggested to be taken seriously and could be reduced by urban renewal. The living environment is one of the strengths of sustainable development in Shenzhen and could be maintained by constructing a resource-saving society.

1- Introduction

2- Methods

3- Results

4- Discussion and conclusions

References

Abstract

The valuation of urban parks using hedonic pricing has been thoroughly documented in a number of studies set in many cities. Just as the value of existing parks can be estimated by investigating the relationship between housing prices and parks, the value of future parks can also be estimated using this approach. This study recognized that a series of planning processes and land use transitions to create urban parks not only influences the perceptions of real estate buyers but also the quality of the local environment. From the apartment sales data for the Busan metropolitan region of Korea, data on 11,498 sales of apartments within walking distance to planned parks (as well as existing parks) were collected. These data were applied in an analysis comprising three categories describing different planning contexts for the parks: “comprehensive plans,” “implementation plans,” and “completed parks.” A set of explanatory variables representing housing, park, and neighborhood characteristics was selected, with additional remarks regarding the planning specifications that might influence apartment buyers’ perceptions, such as the park type and the age of a plan, as defined in the official plans of the city. The results showed that smaller park types in residential settings were preferred throughout the processes of park planning, while all types were preferred once the processes were completed. The preference in park types is likely associated with the quality of the planning guidelines as well as the size of the project and the duration of planning.

Introduction

The urban park system is a crucial element of the urban fabric that enhances quality of life by promoting a healthy lifestyle, relaxation, and social engagement. Beyond the traditional value of a park space, urban park systems contribute to the larger urban objective of improving the quality of urban living. The broader view of the urban park system emphasizes the social benefits of reducing disorder and crime and strengthening ties among community members (Choi, 1999; Kuo, Sullivan, Coley, & Brunson, 1998; Kweon, Sullivan, & Wiley, 1998; Payne, Orsega-Smith, Godbey, & Roy, 1998; Sampson, Raudenbush, & Earls, 1997; Sturm & Cohen, 2014; Walker, 2004). Furthermore, vegetation, water bodies, and green spaces are valued components of the regional ecosystem and can also act as buffers against common urban nuisances, such as noise, air pollution, and congestion (Bayer, Keohane, & Timmins, 2009; Chiesura, 2004; Harnik & Welle, 2009; Kim, Park, & Kweon, 2007; Luttik, 2000). In the past few decades, a number of studies set in multiple cities have found that urban parks have a positive impact on real estate prices. These studies have used various empirical methodologies to determine the valuation of parks. Hedonic pricing allows us to capture the value of environmental amenities by estimating the marginal price included in the price of real estate. Assisted by the improved capability of dealing with spatial data and more sophisticated tools, the recent body of research has advanced the use of the hedonic price method, especially in an investigation into the proximity effect and a more detailed and diverse characterization of environmental amenities. An overview of the previous literature, with a focus on the proximity effect and the different characterizations of parks in urban settings, lays the groundwork for the valuation of urban parks in different planning contexts.

The ‘smart city’ is an oft-cited techno-urban imaginary that has been promoted by businesses and governments alike, locally and internationally. Smartening up our cities, so the rhetoric goes, promises to deliver ‘sustainable’, ‘efficient’, ‘secure’, ‘livable’, and ‘equitable’ outcomes. The smart city joins a long history of techno-urban imaginaries, including—from an architecture and design perspective—the modernist visions of Le Corbusier’s machine city and Archigram’s Plug-In City and Computor City, to the more recent and largely corporate and technically-driven visions of electronic, digital, cyber, virtual, wired, sentient, and ubiquitous cities. Yet, what sets the smart city apart from its predecessors, is the significance placed on data over infrastructure and the ways to collect it, collate it, and significantly, how to translate it into ‘useful’ information. In this way, the smart city is often seen as synonymous with the concept of so-called ‘big data’ that typically refers to massive-scale data sets that can only be processed and analysed through the use of computational tools, and that offer new ways to understand and manage city-scale operations. In addition to its common associations with big data, the smart city is also understood as the application of ‘intelligent’ digital technologies and computational processes to form smart systems that operate to improve ways of living in twenty-first century cities. Kitchin (2015) has summarised the smart city narrative as following two key paths including, the application of information communication technologies (ICTs) to stimulate economic development, and, the embedding of software-enabled technologies into the urban fabric to augment urban management (p.131). Similarly, Goodspeed (2015) argues that there are two key, yet diverging perspectives, including on the one hand the knowledge economy and urban development, and on the other governments’ use of technology. Above all, the smart city thinks big, and a key focus has been the implementation of large-scale ICT systems for data collection to enable real-time and predictive analytics. Given this, and not unsurprisingly, the bulk of smart city discourse is also focused at the big-picture scale; it is visionary, numbers focused, and gives emphasis to the ways big data can inform city-scale optimisation strategies, including infrastructure management such as road traffic, public transport, and waste services. Yet it is people’s use of digital devices and the network connectivity they enact that now figures centrally to the amassing of big data, and also increasingly, to the very delivery of smart city services. Despite this, what the smart city rhetoric typically overlooks are the human-scale implications of its proposed technological systems, that is, its users and the user-experience.