Mapping Conflicts in the Development of Smart Cities: the Experience of Using Q Methodology for Smart Gusu Project, China

The concept of smart cities is now firmly on the current urbanisation agenda around the world. Although such ideas are now widely accepted, the planning practice has experienced operational difficulties in supporting the development of smart cities in the real-life context. While great emphasis has been laid on the importance of collaboration in the development of smart cities, there has been little analysis on how to develop an empirical framework to evaluate different opinions and potential conflicts in smart cities. This paper aims to investigate the stakeholder’s perspective and attitude in the smart city development, and highlight lessons from their experience. For this purpose, the research uses Q methodology to measure attitudes and subjective opinions of smart city stakeholders. The research shows that stakeholders have expressed different priorities in the development of smart cities based on the particular standing point of the observed participants based on their work and social backgrounds. This subjective landscape on smart cities can be valuable to understand the existing debates in practice and implement projects more efficiently by mapping possible conflicts in advance

Rethinking the Strategic Dimensions of Smart Cities in China’s Industrial Park Developments: the Experience of Suzhou Industrial Park, Suzhou, China

Although smart cities have been widely recognised as a new tool to transform the industrial parks in China, planners have faced the complex challenge of how to translate the concept of smart cities into reality. While great emphasis has been put on the applicability of information and communication technologies (ICT) to smart city projects, there has been little analysis or evaluation in such planning process of smart cities. This is mainly because smart cities employ rather unclear definition and work scope. This research draws attention to the ‘strategic dimensions’ of smart cities in planning practice, which need to be considered in the transformation of industrial parks in China. The research uses a case study of smart city development in Suzhou Industrial Park (SIP), Suzhou, China, which is widely acknowledged as one of the successful industrial park developments in China. SIP is in transition, and accommodating manufacturing industries is no longer the primary function of SIP. The research found that it is necessary to redirect the smart city strategy of SIP by mirroring the needs of the workers and local residents in SIP. It requires a transformation of traditional compartmentalised planning practices and the engagement of a wider range of players including those who were not previously involved in traditional practice

Tourism identity in social media: The case of Suzhu, a Chinese historic city

In the context of tourism planning and promotion, there is wide acknowledgement that conceptualisations of tourism identity cannot be grounded merely in physical place, but should also encompass a wide range of factors including, for instance, cultural relations, tourist activities, and social networking. There are opportunities in late modern society for relating the identity of a city’s tourism with digitally-presented tourists’ perceptions and activities through social media studies. This research explores multiple research approaches to delineate the digital identity of Suzhou’s tourist destinations, as presented in online user-generated contents. It is hoped that this social media study can provide supplementary information for tourism bureaus and agencies to make informed judgements on effecting pertinent improvements to optimise existing tourism resources and create more enticing environments for tourists. The research follows a case study approach and conducts an empirical study on Suzhou, a Chinese historic city. The analysis of the results show that the social media study is potentially useful in identifying the key characteristics of particular tourist destinations from visitors’ perspectives that may also be helpful for the evaluation of tourists’ experiences

Sanity Simulations for Saliency Methods

Saliency methods are a popular class of feature attribution tools that aim to capture a model's predictive reasoning by identifying "important" pixels in an input image. However, the development and adoption of saliency methods are currently hindered by the lack of access to underlying model reasoning, which prevents accurate method evaluation. In this work, we design a synthetic evaluation framework, SMERF, that allows us to perform ground-truth-based evaluation of saliency methods while controlling the underlying complexity of model reasoning. Experimental evaluations via SMERF reveal significant limitations in existing saliency methods, especially given the relative simplicity of SMERF's synthetic evaluation tasks. Moreover, the SMERF benchmarking suite represents a useful tool in the development of new saliency methods to potentially overcome these limitations