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This book explores the dynamics of the interaction between the development of creative industries and urban land use. It is based on the case city of Nanjing, a metropolis representing the second tier of cities in China's urban system in the Yangtz River delta. This research adopts an interdisciplinary approach which integrates GIS, ABM, Questionnaire investigation and Interview.



Chapter 1. Introduction

The rising of creative industries in the 1990s marked the boom of a new component of the new economy. As it is believed that in a postindustrial society information rather than muscle power counts most, cities and regions around the world compete to promote new economy expecting to stand out in the new wave of global economic shift. Creative industries, due to its success in economic growth, close ties with culture and the prevalence of cultural consumption/symbolic economy, are even more zealously pursued. This book aims to answer questions arising from this global phenomenon in the planning realm: How will the flourishing of creative industries challenge urban land use? What are the implications for policy making? How can we handle the development of creative industries and urban land use in a dynamic and adaptive way?
Helin Liu, Elisabete A. Silva, Qian Wang

Chapter 2. The Development of Creative Industries and Urban Land Use: Revisit the Interactions from Complexity Perspective

It took more than 50 years for the concept of “creative industries” to evolve from “culture industry”, through “cultural industries” to “creative industries” (O’connor 2007). In contrast to this comparatively long conceptual evolution history, the time for creative industries to gain its global promotion is much shorter, only around 15 years since its coinage in the 1990s. The underlying policy rationale, as Foord (2008) concludes, is urban policy makers’ high expectation of urban growth and innovation. The wide cultivation of creative industries in urban development scheme, inevitably, presents urban government the issue of how to arrange land space to accommodate creative industries in an efficient and adaptive way. This question cannot be easily solved without a comprehensive and insightful understanding of creative industries and the dynamics of their interactions with urban land use. This chapter aims to revisit existent theoretical discussions on this aspect.
Helin Liu, Elisabete A. Silva, Qian Wang

Chapter 3. Application of Agent-Based Modelling to the Dynamics of Creative Industries’ Interactions with Urban Land Use: An Introduction

As has been proposed, the dynamics of creative industries’ interactions with urban land use is complex and can be examined by the approach of agent-based modelling. In agent-based modelling, one central issue is to clearly define the rules that the agents follow. However, the locational behaviours of the creative firms and the creative workers are not easy to describe as the factors are multidimensional. This chapter focuses on explaining how the concept of locational utility function is introduced to describe the locational behaviours of the firms and the workers and what the requisite data are for this purpose.
Helin Liu, Elisabete A. Silva, Qian Wang

Chapter 4. The Foundation for Agent-Based Modelling: Empirical Evidence of Creative Industries’ Interactions with Urban Land Use in Nanjing

The underlying idea of agent-based modelling is that many aggregate phenomena emerge from the complex interactions among individuals at a lower level in a system; the rules of these interactions are supposed to be simple which can be easily described and understood by mathematical or computational languages. So, the very foundation for agent-based modelling is to figure out these rules. By mining data collected in Nanjing, this chapter aims to provide empirical evidence for the generalisation of agent-based modelling-oriented interaction rules. First, the development of Nanjing is reviewed in historical perspective followed by an examination of the spatial distribution of the creative firms and the creative workers. Second, the locational factors that shape the firms’ office and the workers’ housing location preference are examined via data from questionnaires and checked against conclusions drawn from GIS analysis. Then, it proceeds to explore the citizens’ attitude/reaction towards creative industries’ booming and the corresponding supportive policies enforced by the government. Finally, by synthesising the conclusions drawn from the above analyses, the interactions among the four interest groups (the creative firms, the creative workers, the individual citizens and the urban government) are generalised into a dynamics framework which is the basis for modelling in the next chapter.
Helin Liu, Elisabete A. Silva, Qian Wang

Chapter 5. Simulating the Dynamics of Creative Industries’ Interactions with Urban Land Use by Agent-Based Modelling

The last chapter examined the locational behaviours of the creative firms and the creative workers and their interactions with the urban government and the citizens in Nanjing. This chapter continues with the aim to demonstrate how these empirical observations are parameterised and the dynamics simulated by agent-based modelling. It begins with a brief introduction to the model development platform NetLogo and its capability to simulate the dynamics. Then, it proceeds to model design, the first step of agent-based modelling which explains three issues: (1) How is the theoretical dynamics framework proposed in the last chapter further developed and simplified into an agent-based modelling framework? (2) How is the abstract urban space of Nanjing described in the model? (3) How are the condition-action rules of the three agent classes quantitatively defined? After this clarification, the chapter comes to its final section which focuses on the second step of modelling: model implementation. It details how the model design is translated into the supposed agent-based model in NetLogo.
Helin Liu, Elisabete A. Silva, Qian Wang

Chapter 6. Model Validation and Scenario Analysis

Now, we have already developed an agent-based model to simulate the dynamics of the interactions between the involved agents (the creative firms, the creative workers and the urban government) and urban land use. It is expected that, through scenario analysis by using this model, further insight into this dynamics can be generated. However, scenario analysis by using an agent-based model without validation of its correctness and reliability can very likely produce misleading conclusions. Regarding this, this chapter first concentrates on model validation. It then proceeds to scenario analysis, in searching for new features of the dynamics and further policy implications.
Helin Liu, Elisabete A. Silva, Qian Wang

Chapter 7. Examining the Dynamics by Incorporating GIS Data with the CID-USST Model

The spatial environment of the CID-USST model is a highly abstract and simplified version of Nanjing. One obvious limitation resulting from this manipulation is that policy implications cannot be easily projected to real urban location. In practice, however, policy makers are keen to know exactly where to invest so as to optimise plan efficiency constrained by limited budget. In addition, it is also crucial to customise policies and adjust land-use plan accordingly locally referring the dynamics of the creative industries in different sites. Regarding this, this chapter illustrates a further development of the agent-based model “CID-USST” by incorporating GIS data. The goal is to facilitate urban policy makers to decide where to develop offices for the creative firms and housing for the creative workers once a comprehensive land-use plan is formally approved and to customise supportive/guiding policies locally.
Helin Liu, Elisabete A. Silva, Qian Wang

Chapter 8. Conclusions and Further Development

This book aims to explore the dynamics of the interaction between the development of creative industries and urban spatial structure by agent-based modelling. Regarding the complexity of the interaction, it is proposed that this dynamics should be understood as a bottom-up and top-down process. In order to pave the foundation for agent-based modelling, a case study of Nanjing metropolis has been conducted. Through it, the locational behaviours of the firms and the workers, and the respective role of each involved interest group are clarified. By referring to these findings, an agent-based model named CID-USST is then developed and applied to scenario analysis with the aim to generate deeper insight into the dynamics. However, the spatial environment of this model is an abstract single-centred urban space, which limits its applicability to customising geographically coordinated policies at suburban-district level. Thus, the book continues with a further development of the model by incorporating the GIS data of Nanjing in the last chapter. In this concluding chapter, it will highlight the key findings and the possible topics for further development.
Helin Liu, Elisabete A. Silva, Qian Wang

Erratum to: Creative Industries and Urban Spatial Structure

Helin Liu, Elisabete A. Silva, Qian Wang


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