The spatial organisation of jobs in Sydney’s cognitive-cultural economy.

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The spatial organisation of jobs in

Sydney’s cognitive-cultural economy.

Chris Schmid

1060 1805 Thesis Research Report M.Sc. (Human Geography) Universiteit van Amsterdam

23 June 2014

Abstract:

This thesis investigates the spatial organisation of the cognitive-cultural economy by analysing industry and occupation employment patterns in the city of Sydney, Australia. It builds on two intersecting bodies of empirical study and theory; the cognitive-cultural economy, and the spatial organisation of employment in cities. Using 2011 fine-detail zonal industry and occupation employment data, a series of spatial analyses were undertaken to determine dispersion, centralisation and the characteristics of centres for various industrial and occupational groups within the cognitive-cultural economy. Findings suggested that the cognitive-cultural economy has highly variable spatial characteristics. Similar to other modern and globally-focused cities, Sydney’s CBD was both dominant and diverse. Furthermore, a range of secondary employment centres were identified, including tightly-clustered corridors near the city centre, and more decentralised sub-centres throughout the urban region. Findings from this study largely support literature that points to the significance of dense agglomeration economies that drive growth in modern cities. They also highlight the need for more detailed and differentiated study into different components of the cognitive-cultural economy.

Acknowledgements:

I would like to thank Prof. Dr. Robert Kloosterman and Dr. Barbara Heebels for their supervision, guidance and review throughout the research and drafting process. I would also like to thank Keenie Daly for her invaluable patience, support and proof-reading assistance. Cover image was created by the author from self-generated photography, cartography from this analysis and images of Sydney CBD and Surry Hills from Airbnb.com.

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LIST OF FIGURES

Figure 1 Investment in Knowledge-based capital vs investment in tangibles in USA 1971 to 2011. Source OECD, 2013, 24 ... 12 Figure 2 - Urban centres and localities functionally connected to Sydney ... 24 Figure 3- Number of jobs and proportion of Sydney’s employment within cognitive-cultural occupations and industries ... 39 Figure 4 - Share of jobs within cognitive-cultural industry and occupation groups in Sydney – 2011 ... 40 Figure 5 - Accumulative share of metropolitan cognitive-cultural jobs within TZ11 zones by employment density percentiles ... 43 Figure 6 - Average weighted distance of jobs from Sydney city centre, by occupation and industry group ... 45 Figure 7 - Proportion of jobs in Sydney cognitive-cultural economy within distance bands from city centre ... 46 Figure 8 - Share of employment within and outside centres by industry and occupation ... 47 Figure 9- Location of centres and their proportionate size for jobs in cognitive professionals occupations ... 51 Figure 10 - Location of centres and their proportionate size for jobs in managers and decision-makers occupations ... 51 Figure 11 - Location of centres and their proportionate size for jobs in cultural workers occupations ... 52 Figure 12 - Location of centres and their proportionate size for jobs in health, education and welfare professionals occupations ... 52 Figure 13 - Location of centres and their proportionate size for jobs in all cognitive-cultural occupations ... 53 Figure 14 - Location of centres and their proportionate size for jobs in advanced producer services industries ... 53 Figure 15 - Location of centres and their proportionate size for jobs in finance, insurance and real-estate industries ... 54 Figure 16 - Location of centres and their proportionate size for jobs in cultural production services industries. ... 54 Figure 17 - Location of centres and their proportionate size for jobs in health, education and public administration industries. ... 55 Figure 18 - Location of centres and their proportionate size for jobs in all cognitive-cultural industries .. 55 Figure 19 - A snapshot of the spatial organisation of Sydney’s cognitive-cultural economy ... 61

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LIST OF TABLES

Table 1 - Industrial and occupational attributes of jobs within the cognitive-cultural economy. ... 27

Table 2 - Industry group names, descriptions and examples. ... 29

Table 3 - Occupation group names, descriptions and examples. ... 30

Table 4 - Research operationalization including variables, measures and indicators for each hypothesis. 31 Table 5 - Absolute employment and employment density thresholds for centres. ... 36

Table 6 - Key for industry and occupation groups ... 38

Table 7 - Key metrics of cognitive-cultural employment dispersal in Sydney, by industry group – 2011 .. 41

Table 8 - Job-share characteristics of centres by occupation and industry group - 2011 ... 48

Table 9 - Relative size characteristics of centres by occupation and industry group - 2011 ... 49

Table 10 - Number of centres and location of centres by occupation and industry group - 2011 ... 50

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Introduction

This thesis investigates the spatial organisation of the cognitive-cultural economy by analysing industry and occupation employment patterns in the city of Sydney, Australia.

The cognitive-cultural economy is an increasingly important component of modern competitive economies (Scott, 2007). Formed of industries and occupations more traditionally associated with the knowledge economy, as well as those related to creative and cultural production, the cognitive-cultural-economy is firmly rooted within large, globally-connected metropolises that form the gateways to worldwide networks. In fact, the term cognitive-cultural economy is used by Scott (2007), Wyly (2013) and others to refer to the whole economy, as they argue that cognitive-cultural sectors are driving modern economies.

Work in the cognitive-cultural economy is heavily based around knowledge-based tasks laden in specialisation that depend heavily on the cognitive skills of workers. The completion of these tasks is aided by a rich and complex network of Information and Communications Technologies (ICT) infrastructure that enables rapid networking and somewhat eases certain requirements for the co-location of workers (Wainwright, 2010). Conversely, many aspects of work in the cognitive-cultural economy are dependent on the establishment of trust and the passing of tacit knowledge through dense and informal social networks. As such, proximity remains an important characteristic of work in the cognitive-cultural economy (Scott, 2010).

Contemporary empirical research has indicated that within many large cities throughout the world, the spatial distribution of employment is increasingly decentralizing from traditional central business districts. Much of this research also points to a rise in polycentric arrangements of sub-centres, some of which have particular employment specializations. Research that has specifically focussed on employment within the cognitive-cultural economy is however much less developed and has produced mixed findings regarding the spatial organisation of employment within cities. There has yet to be an explicit and comprehensive empirical analysis of the spatial patterns of the cognitive-cultural economy, considered according to both specific occupational and industrial groupings at the intra-metropolitan scale. This research aims to partially fill gaps in understanding the intra-metropolitan organisation of the cognitive-cultural economy. This will be achieved by:

(1) Comprehensively and explicitly studying the spatial organization of the cognitive-cultural economy at an intra-urban scale;

(2) Operationalising the cognitive-cultural economy based on occupational and industrial employment groups;

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(3) Further refining methodologies in determining spatial organization and polycentricity within urban regions;

(4) Completing this with recent (2011) fine-level geographic data that is able to accurately demonstrate the contemporary situation within a leading global city.

The proposed investigation will be conducted through a case study of Sydney, the most populous and economically prosperous city in Australia. Although it contains over 4.3 million residents and approximately 2 million jobs, Sydney is widely spread over an area of approximately 4,300 square kilometres and is characterised by continuous and sprawling low-density development. The general urban form of Sydney has been extensively studied and is the focus of large amounts of academic and policy study, particularly from urban and transport planners within government. This material identifies that Sydney contains concentrated areas of economic and cultural activity that have been defined as ‘centres’ within urban and transport planning policy (Freestone and Murphy, 1998; Pfister et al., 2000; Department of Planning and Infrastructure, 2013). Whilst these centres have been described according to their general economic and cultural characteristics, their importance has been considered in terms of all employment rather than employment within the cognitive-cultural economy. Studying the spatial characteristics of employment in the cognitive-cultural industries and occupations will provide insight into the largely unstudied and important component of economy.

Research Definition

The proposed research will attempt to answer the following question:

How are jobs within the cognitive-cultural economy spatially distributed throughout the Sydney region in terms of dispersion, centralisation and the formation of centres?

In order to sufficiently address this question, three hypotheses will be tested. These are that: (1) Jobs within the cognitive-cultural component of Sydney’s economy will be largely

concentrated within certain locations and centralized near the city centre.

(2) These cognitive-cultural jobs will be distributed primarily within a prime centre or CBD, with very high job-density and secondarily within series of sub-centres that are largely proximate to the main centre, suggesting that although employment in the cognitive-cultural economy in the region shows a degree of morphological polycentricity it is still largely monocentric.

(3) Jobs in cultural industries and occupations will be more concentrated, centralized and monocentric than those jobs in cognitive industries and occupations.

Thesis structure

This report is divided into four sequential chapters.

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cities and the findings of studies into the spatial organisation of employment in the cultural economy and knowledge-economy.

Chapter Two contains a detailed methodology section that will outline the operationalization of the research including a discussion of data, definitions, analysis techniques and approaches as well as discussion regarding the acknowledged limitations of the study.

Chapter Three details research findings. It will discuss the results of analyses and relate these to the findings of other studies into the spatial organisation of the cognitive-cultural economy. Finally, Chapter Four will summarise the findings and discussion, addressing the original research question and hypotheses. This section will also identify potential further avenues of research based on the findings of this study.

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Chapter 1: Literature Review

Chapter 1 contains a review of literature that forms the foundation of the empirical study into the spatial organisation of the cognitive-cultural economy in Sydney. The chapter is divided into four parts:

Section 1.1 discusses the various conceptions and definitions of the cognitive-cultural economy. Section 1.2 involves a description of the locational preferences and characteristics of employment in the cognitive-cultural economy.

Section 1.3 outlines different approaches and methods for describing the spatial organisation of employment within cities as well as key attributes of the cognitive-cultural economy that have been observed through empirical study.

Section 1.4 describes the key characteristics of Sydney, Australia which is the case study used for analysis in this thesis.

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1.1 Defining the cognitive-cultural economy

The practice of work has dramatically changed over the past decades as globalization processes and industrial specialization have resulted in widespread reductions in manual labour within the World’s more developed countries (Amin, 1994). The structure and competitiveness of economies in these countries has shifted from being based in the production of material goods to being fundamentally driven by the provision of knowledge-based services and innovation (Kloosterman, 2010; Muñiz & Garcia-López, 2010). Similarly, the rapid growth and integration of digital technologies into the everyday lives of individuals has opened new and quickly-expanding avenues of commerce (Wyly, 2013). Allen Scott has coined the term cognitive-cultural economy to describe modern economies where “labour processes have come to depend more and more on intellectual and affective human assets … and are increasingly less focused on bluntly routinized mental or manual forms of work.” (Scott, 2007: 1466).

The cognitive-cultural economy has similarities to other contemporary descriptions and interpretations of the economy such as the ‘knowledge-economy’ (Drucker, 2001; Miranda et al.; 2011; Hulten; 2013), ‘information economy’ (Sassen, 1994), ‘knowledge-based capital’ (OECD, 2013) and ‘post-Fordist’ economy (Amin, 1994). These descriptions are also largely structured around the increasingly intellectual characteristics of the types of work that drive wealth generation. For example, the Organisation for Economic Cooperation and Development (Miranda et al., 2011; OECD, 2013) uses terminology such as ‘knowledge economies’ and ‘knowledge-intensive capital’ to assess and characterise the economies of nation states based on labour force participation in industries based on knowledge and innovation. Specifically, these are industries that are involved in high-level producer and business, services, finance, banking, and high-technology manufacturing (Hulten, 2013). These industries have also been written about extensively in studies relating to ‘world city networks’; the connected set of globally-focussed cities that are theorised to be at the helm of the global economy. Within these studies the characteristics of knowledge-based industrial groupings such as advanced producer services (APS), and knowledge intensive business services (KIBS) are once again commonly used to measure the size and scope of connections between cities. The specific industries in these groups include banking and finance, international law, and accounting services (Taylor, 2000; Wall and Van der Knapp; 2011). These are argued to be those industries that have a major decision-making role regarding the direction of the global economy (Sassen, 1994). Similarly, Allen Scott (2010) posits that judgement, decision-making, social perceptiveness and the capacity for interactions with others are key skills that define the ‘modern’ workplace within the cognitive-cultural economy.

The key difference between the cognitive-cultural economy and these other descriptions of the economy inherently lies in the ‘cultural’ component of the economy. There is a long and complex debate regarding the specific definition of ‘culture’ and ‘creativity’ (see Power, 2002) lies beyond the scope of this study. It is noted however that the varied treatment of these concepts has led to a lack of methodological clarity in empirical research which in turn has led to ambiguities and mismatches when comparing studies on the cultural economy (Markusen et al., 2008; Kloosterman, 2010; Davis and Mills, 2012). For clarity in the framing of this research, the definition of Allen Scott is used. Scott argues that the cultural component of the economy derives its value from “non-utilitarian aesthetic and semiotic signals” (Scott, 2010, 116) and encompasses a range of pursuits closely tied to the notion of creativity. This is similar to the

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definitions of cultural and creativity from the widely-cited and somewhat divisive Richard Florida. Florida (2002) suggests that creativity is the sum of knowledge and information and that those occupations that involve creativity are indeed many of those in knowledge-based jobs.

Scott constrains the creative field of the city to those pursuits that are able to connect with a market, vis-à-vis their economic acceptability. Thus, the cultural component of the cognitive-cultural economy can be described as those industries or occupations that involve the embedding of cultural capital into aestheticized products (Scott, 2007). Examples include; production of specialised clothing, fine leather goods, books and magazines, perfumes and cosmetics, furniture, jewellery, film production, music recording, theatre, multimedia and tourist services as well as more contemporary industries such as creative web services, publishing and digital marketing (Scott and Ellis, 2000; Scott, 2011; Wyly, 2013).

Whilst some industries fit nicely within the definition of cognitive-cultural economy, they will likely employ at least some workers within occupations that fall outside the scope of this economy (for example the security or cleaning staff at a law firm) (Markusen et al, 2008). Conversely, some clearly cognitive-cultural occupations such as managers or artists will work within industries that fall typically outside the cognitive-cultural economy (for example, an advertising professional employed for a forestry company). These definitions and classifications have methodological implications when attempting to observe the spatial dimensions of the cognitive cultural economy, which will be discussed later.

ICT have deeply penetrated work within the cognitive-cultural economy (Scott, 2007; Kwan et al., 2007; Kloosterman, 2010). In addition to somewhat easing from the potential easing of co-some locational constraints in business, the use of ICT has contributed to the diversification of work in these industries and more unique and specialized outputs (Scott, 2007, 1467). The specialization of these outputs is ever-increasingly attached to the specific wants and needs of individual consumers. This is particularly the case for personally-tailored products sold to access, and for use within, the digital and online world. Here, where an increasing number of people are spending an increasing amount of their time, is the frontier of cognitive-cultural capitalism (Wyly, 2013).

1.1.1 The role of cognitive-cultural work in the overall economy

Regardless of these definitional matters it is clear that cognitive-cultural work is largely and increasingly responsible for the economic strength of many countries, particularly those within the developed world. It is largely attached to specific locations, including specialized districts within global cities that are used as platforms for connection to global markets (Lorenzen et al., 2008).

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Although the specific empirical metropolitan-level study of the cognitive-cultural component of the economy is a fairly new research area, descriptions of knowledge-intensive industry, knowledge-based capital and the growth of creative industries are able to indicate the relative strength of cognitive-cultural economy. The Organisation for Economic Co-operation and Development (OECD) notes that knowledge-based capital is “increasingly, the largest form of business investment and a key contributor to growth in advanced economies” (OECD, 2013: 22). For example, in the United States, investment in knowledge-based capital has more than doubled to now comprise over 16 per cent of gross domestic product (OECD 2013) (see Figure 1).

Figure 1 Investment in Knowledge-based capital vs investment in tangibles in USA 1971 to 2011. Source OECD, 2013, 24

Note: Estimates are for private industries excluding real estate, health and education. Source: OECD (2013: 24)

Alongside this, investment in tangible capital has decreased significantly over this period. Florida (2003) highlights the tenfold growth of creative bohemians in the USA from 1950 to 2000. Scott and Ellis (2000) suggest the creative economy accounts for up to 20 to 40 percent of the entire workforce in global ‘creative’ cities such as Los Angeles, Tokyo and London. Further, the OECD (2013) notes that product and services design; a field of work that is both knowledge-intensive as well as culturally derived, is an essential driver for innovation in advanced economies. Design forms a fundamental part of the development of consumer products (e.g. mobile phones, cars and furniture) and services (such as web-based commerce). Research in the United Kingdom has found that investment in design services has doubled between 1991 and 2011 and is at similar levels to investment into research and development (Goodridge et al., 2014).

1.2 Location characteristics of the cognitive-cultural

economy

1.2.1 Proximity, buzz and the importance of co-location

The cognitive-cultural economy is commonly characterised by concentration and clustering with firms co-locating and creating clear centres of employment (Shearmur and Coffey, 2002). Scott argues that when combined with the cognitive industries discussed above, “cognitive–

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cultural production and work in major cities thrive on the economies of agglomeration and specialization that can be reaped as globalization intensifies and markets expand” (Scott 2013, 386). The advantages of co-location and proximity have been demonstrated for a variety of craft-based and specialized manufacturing industries, where the sharing of highly specialized and generally non-codifiable knowledge occurs amongst pools of workers who work in close proximity (see for example Wolfe & Gertler, 2006 or Becattini and Ottati, 2006). This information sharing occurs through a mix of formally defined networks such as within the structures of businesses organisations and trade unions but also through informal networks, often based on social and cultural interactions. Storper and Venables (2004) classify these informal networks as ‘buzz’, which captures the sporadic, intense and constant nature of these interactions. For firms and employees, a specific investment in buzz does not necessarily occur beyond an investment into proximity and “information and communication is more or less automatically received by those who are located within the region and who participate in the cluster’s various social and economic spheres” (Bathelt et al, 2004, 38).

Many have argued that close proximity provides advantages to a range of industries where the information sharing, buzz, and tacit knowledge are important (Anas et al., 1998; Storper and Venables, 2004; Scott, 2011; Muñiz & Garcia-López, 2010). This includes many industries within the cognitive-cultural economy such as finance, biotechnology and media (Zeitlin, 2008).

1.2.2 Connecting to global markets

The advantages of proximity-derived ‘buzz’ are not limited to local environments however. Bathelt et al. (2004) argue that firms in knowledge-intensive industries form networks rooted in these localized environments, but also build ‘global pipelines’ to share and trade knowledge on a global scale. These pipelines are formal connections that involve a greater degree of trust and management than buzz and may be between firms that are largely separate. The cumulative effect of such pipelines creates a network of connections linking not only individual firms, but also different pools of localized buzz.

These connections have been observed to occur most intensely between leading global cities. Global City Network (GCN) literature provides some insight into the modern spatial organization of the knowledge-based economy at the global scale. These studies have identified that some cities have significantly higher concentrations of firms within industrial groupings of advanced producer services (APS) and knowledge-intensive business services (KIBS); which each form part of the overall cognitive-cultural economy (see Sassen, 1994; Taylor, 2000; Brown et al., 2010). Further, this work has demonstrated clear hierarchies between cities based on the connections between firms and their subsidiaries in these industries. Although the findings of these studies have varied, generally due a range of methodological approaches, a handful of urban regions are consistently identified as ‘global cities’. These cities have a large overlap with those noted by Scott (2000) and Lorenzen and Scott (2008) as ‘ideal type cities’ for cultural production and include locations such as New York, London, Tokyo, Paris, Hong Kong and Singapore. Kloosterman (2010) however argues that it is important not to oversimplify the classification of cities suggesting that that the variety of capitalism thesis can also be applied to observe multiple versions of the cognitive-cultural economy within different institutional contexts (2010, 134).

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Such institutional differences can occur not only at the national scale but also between different urban regions, through the application of land taxation (and concessions), municipal rates, urban land-use and transport policy. These institutions are able to influence the specific intra-metropolitan characteristics of the cognitive-cultural economy and potentially show a large degree of variation in the spatial distribution and intensity of cognitive-cultural production. The globally-focused GCN literature pays little attention to the cognitive-cultural economy within the city, which is the core focus of this research. Study in this area has uncovered evidence of specific patterns of employment concentration that have important implications not only for economic productivity, but also for the future planning for population growth, including the provision of housing, civic amenities and urban transportation networks. This is important not only for attracting ‘creative workers’ such as spruiked by Florida (2002), but also for meeting the needs of the vast ‘non-creative’ labour pool that supports these industries (Scott, 2007).

The effects of ICT on work location

The integration of technology in work environments has an effect on the spatial organization of the cognitive-cultural economy, particularly at more local scales. Advancements in telecommunications and ICT have in part reduced the requirements for spatial and temporal co-location of employees within cognitive industries, suggesting a possible future of telecommuting and employment land-use dispersion (Kwan et al. 2007). Castells (2000) considers the space of flows (from telecommunication) and the space of place (the physical world) as two potentially incompatible spatial logics. Similarly, Wainwright (2010) argues that technological ubiquity results in an increasing disconnection between people and their physical workspace. He posits that offices operating in a modern wireless world require greater synergy between software resources and human resources that are organized within a multi-faceted network known as the distributed workplace. Essentially, Wainwright and Castells both see a world where distance and proximity are increasingly less important to participation in work. Castells in particular sees a developing and potentially harmful incompatibility between physical and virtual spaces. The practice of telecommuting is one potential manifestation of the decoupling of people and their physical workspaces. This essentially involves people working from home or another location, and accessing the content and people they need to work with via telecommunications technologies including telephones, email and social media. The practice of telecommuting is expected to result in the decentralization of employment to some extent, as the actual practice of work is conducted at the homes of employees or at other varied locations. Findings by Felstead et al. (2003) and Shaz and Corpuz (2012) in the United Kingdom and Australia respectively suggest that this is occurring somewhat, particularly within certain professions such as technical writing. Nonetheless, findings also point to the limited nature of this workplace flexibility noting that for the vast majority of workers, a regular workplace remains a key trait of work and that telecommuting generally only occurs on occasion and in some cases actually supplements travel to regular office locations (Felstead et al., 2003). As a result of this, telecommuting does not so have a large impact on the built form or spatial organisation of employment locations.

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1.3 The spatial distribution of employment

1.3.1 Describing employment distribution

Empirical research has used a range of vernacular to describe the same or similar characteristics relating to the spatial distribution of employment, which leads to a degree of ambiguity and confusion when comparing studies. A notable example is the study of Giuliano et al. (2005) who attempt to describe the different characteristics of employment concentration and concentrations of employment with confusingly similar terminology. In order to provide clarity in this research, the wide range of terminology was assessed, drawing from the work of Anas et al. (1998), and is presented here as a specific and distinct set of terms for the description of the spatial distribution of employment.

The spatial distribution of employment, which is sometimes referred to as employment morphology (see Burger and Meijers, 2012; Vasanen, 2012), relates to both the location of jobs and intensity of these locational arrangements. Descriptions of the spatial distribution of employment can be classified broadly into two groups of characteristics:

 Regional characteristics – relating to overall employment distribution throughout a region, and;

 Centre characteristics – relating to the specific features of employment clusters or centres within a region.

These characteristics will now be explored in more detail.

Describing regional employment distribution

Regional employment distribution has been described according to concentration and dispersion (Shearmur and Alvergne, 2002; and Giuliano et al. 2007), as well as the distance it is located from the central city (Freestone and Murphy, 1998; Muniz and Garcia-Lopez (2010).

Regional descriptions of employment are able to provide overall metrics for employment and thus allow comparability between different urban regions. Their shortcoming is that they cannot provide information about specific locational characteristics. For example, regional descriptions can indicate how dispersed employment in a region is, but not which parts are concentrated. Regional employment is generally described according to two characteristics:

 Regional dispersion: variation of density of employment intensity throughout a region; and

 Regional centrality: proximity of employment to a central place within the urban region.

Describing centre characteristics

The spatial distribution of employment is also regularly described according to the characteristics of distinctly concentrated clusters of employment commonly referred to as ‘employment centres’. These descriptions form part of a growing body of literature, referred to

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Various definitions of polycentricity have been developed, with criteria differing in scope and stringency. Most simply, Parr (2004) defines polycentricity as the plurality of centres, without a more detailed metric upon which to assess ‘centre’. Kloosterman and Musterd (2001) argue that polycentricity refers to spatial clustering of a phenomenon. Although studies of polycentricity have been conducted extensively on an inter-urban scale, particularly through world cities literature, intra-urban studies are less prevalent. Intra-urban studies have attempted to define the degree of polycentricity within an urban region according to a range of criteria such as share of overall regional employment (Giuliano et al., 1991, 2007; Garcia-López and Muñiz, 2010; Burger and Meijers, 2012; Vasanen, 2012) Studies have also attempted to defined polycentricity according to the number of centres that exist in an area (Pfister et al. 2000), or according to the proximity of centres to the urban core (Freestone and Murphy, 1998). The wide variety of measurements and terminology used in these studies lead to criticisms of polycentricity literature for being conceptually fuzzy at times (Vasanen, 2012). This conceptual fuzziness is primarily due to the fact that polycentricity can be measured using any one of a number of possible dimensions rather than a mixture of all which would provide the appropriate level of complexity to the term. For example, Parolin (2005) concludes that he has ‘demonstrated the significance of centred employment and polycentric urban growth in Sydney’ but is not clear as to whether he considers polycentricity as simply the number of centres, the amount of employment in these centres, or a combination of both. Others, such as Burger and Meijers (2012) value certain dimensions of polycentricity more than others. This suggests that polycentricity should be considered according to an equal arrangement of centres rather than simply a multitude of centres.

In order to avoid ambiguity, this study will describe centres and ‘centricity’ according to three distinct dimensions that are evident throughout the empirical studies of employment centres:

 Number of centres: number of discrete centres in which employment is contained within a region

 Centre share: proportion of employment within centres compared to the urban region or proportion of employment within one centre compared to other centres.

 Centre centrality: proximity of centres to a central place within an urban region

These dimensions supplement the previously discussed regional employment distribution measures: dispersion and centrality and are together able to explain a great deal about the spatial organization of employment. Further discussion of the specifics in measuring the spatial organisation of employment can be found in section 2.2 of this thesis.

1.3.2 Spatial arrangements of employment in cities

Although every large urban region is somewhat different and unique, similar intra-urban employment formations have been classified using certain terminology that is based on the descriptions of regional employment and centre-based employment distribution discussed above. The following section will discuss these classifications, alongside theories that attempt to explain the reasons behind these formations.

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Monocentric urban regions

A monocentric or more simply a ‘one-centred’, urban region is dominated by a single centre of employment, most likely a central business district that contains all employment. Although they are more likely characteristics of traditional industrial metropolises (Pfister et al. 2000), there is no large urban region that is truly monocentric, as even small amounts of employment activity outside the urban core would constitute a degree of polycentricity. Nonetheless, a region can be considered monocentric if one centre is clearly dominant (see studies by Pfister et al. 2000; Parolin; 2005; Rodriguez-Gamez and Dallerba; 2012).

Polycentric urban regions, edge cities and techno poles

Polycentric urban regions, are those that have relative equality amongst centres (Green, 2007; Vasanen, 2012). Acknowledging the difficulties in conceptualising polycentricity, a range of studies have found that throughout large urban regions employment is decentralizing from traditional central business district locations and increasingly forming secondary districts. Cases in Barcelona (Muñiz & Garcia-López 2010, Garcia-López & Muñiz, 2010), Helsinki (Vasanen, 2012), Phoenix (Leslie, 2010) and Sydney (Freestone and Murphy, 1998; Pfister et al. 2000; and Parolin, 2005) all demonstrate the growth of sub-centres relative to CBDs.

The function of these sub-centres has also been explored and evidence suggests that different locales perform different roles in overall economic structure of an urban region. In Barcelona, Muñiz and Garcia-López (2010) found that employment centres outside the central business district had specific industrial characteristics. These characteristics aligned with previously theorized polycentric arrangements including ‘edge cities’ that form CBD-like functions within suburban settings (Lee, 2007) and ‘techno poles’ that have specialized functions in high-technology production and innovation (Muñiz and Garcia-López, 2010; 789). Reasons for such re-location vary from increased accessibility to employees (Abdel-Rahman and Fujita, 1993), reduced cost and the ability to use larger and more modern facilities (Harrington and Campbell, 1997). In essence, firms are able to reap many of the benefits of fine-level agglomeration economies whilst avoiding negative externalities found within city-centre locations (Lee, 2007: 481).

Dispersed regions and edgeless cities

A contrary view suggests that in some cases, particularly within expansive suburban settings, employment was found to have very limited concentration within centres, suggesting dispersed and haphazard development in large urban regions (Lang, 2003 in Lee, 2007; 482). The sprawling urban region of Greater Los Angeles is an example of such a setting (Gordon and Richardson, 1996). Although Giuliano et al. 2005 found that employment Los Angeles is somewhat concentrated , however the high levels of dispersion and low thresholds used to determine centres combined with a low share of regional employment contained within centres, indicates that the city shows very limited signs of employment concentration. Notably, amongst employment centres, the share of employment in non-CBD locations outweighed that in the Los Angeles CBD, supported by findings from Lee (2007). Lee found that employment dispersed outside of concentrated centres accounted for between 66 and 88 percent of all employment in New York, Boston, San Francisco, Los Angeles, Portland and Philadelphia in the year 2000, having increased in all cases from 1980. This points to increasingly dispersed employment patterns in the USA. Phelps (2010) argues that the dynamics of suburban economies are

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suburban locales is often clouded by the negative externalities created by urban sprawl and unhindered haphazard development.

The importance of scale

Scale is a crucial matter when interpreting the spatial organisation of employment and agglomeration economies within cities (Phelps, 2010). For the interpretation of centres it is particularly important to consider the effect of scale in terms of both aerial units of measurement and study area. Using very small areal units for analysis might fail to identify clusters appropriately whilst using areal units that are too large might overstate the importance of a particular region by aggregating employment that indeed has a separated form. As a result of this the distinction between an organized system of sub-centres and apparently unorganized urban sprawl depends very much on the spatial scale of observation (Anas et al. 1998).

1.3.3 Intra-urban spatial organisation of cognitive-cultural

employment

The spatial characteristics of the cognitive-cultural economy have had limited explicit study. Nonetheless, the individual components of this economy, namely the knowledge-economy and the cultural/creative economy have received more academic attention via a wide range of literature that has articulated the differences in spatial employment characteristics amongst different occupational and industrial groupings. The following section will discuss key findings related to spatial organisation of the cognitive-cultural economy.

The importance of the Central Business District

The importance of large metropolitan areas as gateways to global networks has been well-established through world city networks literature and is supported by findings in Canada and the USA (Shearmur and Doloreux, 2008). Scott (2007: 1469) notes that cognitive-cultural production is suited to such environments and are “typically concentrated in dense locational clusters”, despite reaching markets far beyond their location.

In particular, the CBD is the most important urban location for jobs in the cognitive-cultural economy. Scott (2013) goes as far to suggest that cognitive-cultural employment may be leading to a resurgence of formerly-declined central business districts: “the effects of this resurgence [of cities] are notably apparent in central business district areas where processes of aestheticized land use intensification are proceeding apace.” (Scott, 2013, 385). Scott’s view is arguably US-centric as elsewhere the CBD of many metropolises has retained its primacy. Indeed, some of the larger and older US cities have also maintained prime city centre employment locations (Lee, 2007).

Although the CBD has been found to be a dominant employment centre across many different industries, its importance as a district for high-order services has been particularly highlighted through empirical studies. In Barcelona, Muñiz and Garcia-López (2010) found that Finance, Insurance and Real Estate and Advanced Producer Services; both key industry sectors within the knowledge economy were the most centralized. Similarly, in Montreal, Shearmur and Coffey (2002) found that high order services were found to cluster almost exclusively within the CBD going as far to say that “there is no evidence of clusters of high-order services outside the CBD” (p122). Shearmur and Alvergne (2002) also found that the CBD of Paris was still a stronghold of

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employment within certain high order business service sectors; in particular finance and insurance agents. This study also highlighted how the distribution of employment in the cognitive-cultural economy was differentiated according to sub-sector, finding different industries of employment had different locational characteristics within the Paris region. Scott (2000) found similar differentiation within the creative economy of Paris, identifying a range of precincts and industrial districts, clustered in central city fringe.

The prominence of CBD and central-city locations for the cognitive-cultural economy supports theories of agglomeration that suggest such locations provide fertile ground for the growth of these industries through formal and informal information-sharing (Storper and Venables, 2004), a diverse and deep pool or shared service resources (ÓhUallacháin and Leslie, 2006), and access to the largest and most varied employee catchments (Clark, 2002). Further, the prestige of central business district locations and their close access to a large amount of entertainment and cultural facilities make them desirable locations for the ‘creative class’ who work in many cognitive-cultural jobs (Florida, 2002)

Increasing polycentricity

In some cases, employment in the cognitive-cultural economy has been forming within sub-centres outside the Central Business Districts of large cities. Allen Scott suggests that within the context of globally-focused cities, such decentralized locational traits allow firms to have “the best of both worlds’ by taking advantage of lower establishment costs outside core city-centre locations whilst also accessing dense relational networks and access to global markets (Scott, 2007: 1470). Empirical work by ÓhUallacháin and Leslie (2007) and Leslie (2010) supports this notion, and found that although the CBD of Phoenix, USA contained a large amount of employment in cognitive-based industries, a range of sub-centres had formed, and each had their own specialization in employment. For example, a sub-centre that contained high levels of education and government-based workers corresponded to a university district and several other sub-centres were found to contain large numbers of people working in Finance, Insurance and Real Estate, although with smaller firm sizes than city-centre locations. The findings of Muñiz and Garcia-López (2010) in Barcelona also indicate an increasing tendency for polycentric development within the knowledge economy. They uncovered several centres outside the Barcelona CBD, and also found that these centres had specialization in certain industries finding traditional ‘edge cities’ with large amounts of producer services. They also found technopoles specializing in high technology and advanced producer services jobs and high technology poles which had an exclusive specialisation in high-technology industry jobs within the greater Barcelona Metropolitan Region.

Cultural and creative clustering has been found to be extensively located near to CBD areas of large metropolises. In Stockholm, many cultural industries, in particular fine arts and media, were found to have high location quotients in the central city and city periphery regions, although some smaller regional agglomerations were found within certain industrial sub-sectors; such as broadcast media (Power, 2002). The specialised nature of these precincts is reflected in other competitive global cities such as a film and television hub around Hollywood in Los Angeles and a software and social media hub around Palo Alto, California (Scott, 2007: 1470).

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1.4 Case study: Sydney, Australia

1.4.1 Sydney: an overview

The proposed investigation will be conducted through a case study of Sydney, Australia. As the most populous and economically prosperous city in Australia; it is highly appropriate for this investigation. Even amongst OECD member states, Australia has one of the most service-driven economies (OECD 2013). Within Australia, Sydney employs both the highest relative and absolute number of people in financial and insurance services and also has tertiary education retention rates that are well above national averages (Major Cities Unit, 2013). With over 4.3 million inhabitants, Sydney is a large city in terms of population (Department of Planning and Infrastructure, 2013). It is also large in terms of physical space with a similar urban footprint to the Dutch Randstad1_{. Unlike the concentrated cities and towns of the Randstad, the population}

density of Sydney is however more distributed than the Randstad and generally characterised by continuous low-density development.

1.4.2 Development in Sydney

The metropolis of Sydney is relatively young, having developed from settlement in 1788. Since the beginning of the 20th_{century, and particularly since 1949, in an effort to manage post-war}

population growth, the city has been developed under the auspices of urban planning.

In contemporary Sydney, urban planning is administered at the state (sub-national) government and local government. Development on all urban land must occur in line with zoning provisions that dictate land use controls including activity/use restrictions, resident or worker density and building scale and bulk. The Department of Planning and Infrastructure is responsible for high-level planning policy and legislation as well as the approval of large-scale, high-cost or ‘state-significant’ development projects. Other government departments also provide advice to the Department of Planning and Infrastructure regarding matters such as transport, water and environmental impacts.

Specific development legislation, policy, assessment and approval is conducted at the local government level. There are 52 local government administrative areas within metropolitan Sydney. State and local government plays a limited role in the development of land they have been directly involved in promoting the redevelopment of key large sites throughout the metropolitan area.

1.4.3 The spatial organization of Sydney’s economy

Sydney’s spatial organisation has been studied within both academic and policy circles. This study has identified that Sydney contains concentrated areas of economic and cultural activity that have been defined as ‘centres’ within urban and transport planning and policy (Pfister et al., 2000; Department of Planning and Infrastructure, 2013). Within the Draft Metropolitan Strategy for Sydney (Department of Planning and Infrastructure, 2013), a series of job centres were defined according to a hierarchy largely according to economy size and strength but also

1_{The urbanised area of Sydney is 4,063km}2_{which is only slightly smaller than The Randstad, Netherlands}

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to some degree on their civic importance. Amongst employment centres very limited differentiation is communicated although centres are classified as either ‘strategic centres’ if they have a somewhat retail and service-dominated character or ‘specialised precincts’ if they relate to concentrations of health, education, transport and logistics or are in ‘business-park’ arrangements. The somewhat haphazard classification requirements for specialized precincts are further evident in that they “have an amount of employment that is of metropolitan significance, but other uses in the Precinct are not necessarily at a scale currently of metropolitan significance” (Department of Planning and Infrastructure, 2013: 106). What constitutes significance is unclear.

Academic studies into employment distribution in Sydney support the notion that employment in the city is somewhat concentrated in centres. Pfister et al. (2000) found that approximately 30 per cent of metropolitan jobs were in centres (with densities of greater than 25 employees per hectare) in 1996. Using a less stringent centre definition methodology Parolin (2005) found that over 50 per cent of metropolitan jobs were based in centres in 2001. Studies also note the dominance of the CBD compared to sub-centres, which according to Freestone and Murphy (1998) have over six times the employment of the largest sub-centre; Parramatta. From these results it is apparent that although there is a moderate degree of employment that is concentrated in centres, that this employment is largely based in the traditional central business district location. Further, between 50 and 70 per cent of Sydney’s employment lies outside dense centres – suggesting a largely dispersed employment profile similar to what Gordon and Richardson (1996) identified in Los Angeles (see Pfister et al. 2000). This paints a slightly ‘less-centred’ picture of Sydney compared the Draft Metropolitan Strategy for Sydney but is likely a due to differences in scale and stringency when defining urban centres.

Less is known regarding the spatial organisation of employment in cognitive-cultural occupations and industries. Freestone and Murphy (1998: 289) were able to provide limited insights into the characteristics of Sydney’s centres in 1996, describing an employment-dominant CBD, complemented by a vast typology of centres dispersed throughout urban Sydney including ‘techno burbs’; dominated by hi-tech industry estates and ‘office parks’ dominated by business services. More recently, the Bureau of Transport Statistics (2014) published high-level profiles of industry and occupational employment for the strategic centres defined in the Draft Metropolitan Strategy for Sydney (Department of Planning and Infrastructure, 2013). These profiles were able to describe the broad characteristics of these pre-defined centres however they were not of sufficient detail to determine the specific characteristics of dispersion, centrality and the different dimensions of centricity within the cognitive-cultural economy, nor understand the specific spatial attributes of different industry and occupation groups within the cognitive-cultural economy.

It is from here that this study departs the findings and theories of others to present an empirical analysis that determines the spatial characteristics of the cognitive-cultural economy in Sydney.

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Chapter 2: Methodology

Chapter 2 discusses the methodological approach that was undertaken for this research. It is divided into two sections:

Section 2.1 will explain and describe the choices leading to the use of study area, data, units of analysis and classification techniques used for empirical study of the cognitive-cultural economy in Sydney. This includes a discussion of limitations where appropriate.

Section 2.2 describes and justifies the analysis techniques used to determine the levels of dispersion, centrality and centricity within the cognitive-cultural economy in Sydney. It will also include a discussion of any challenges or limitations and how they were mitigated.

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2.1 Area of study, data and classifications

2.1.1 Study area definition

In order to analyse the detailed spatial distribution of employment in Sydney a study area was defined to be necessarily large so as to capture the full range of employment throughout the metropolis of Sydney but not too large as to include large areas of non-urban land that are redundant and risk skewing the results of analyses.

Unlike many European and some US cities that have a clear delineation between definitions of compact core city and more distributed metropolitan regions, Sydney’s urban density drops rapidly outside the dense CBD to an expansive low density, but continuous urban form that expands up to 60 kilometres from the city centre. Beyond this area, there are smaller settlements that contain people that regularly travel to the urbanised form of Sydney for work, recreation or shopping. The study area for this research was able to accurately capture only urbanised areas of the Sydney region whist using standardised geographical areas that allow this analysis to be compared to others with relative ease.

The Australian Bureau of Statistics (2012) provides spatial definitions the urban centre of Sydney and other urban centres/localities that are functionally connected to Sydney with the Australian Statistical Geography Standard (ASGS) (Australian Bureau of Statistics, 2012). Within this geographical standard, both the Greater Capital City Statistics Areas 2011 (Volume 1) and the Urban Centres and Localities 2011 (Volume 4) were used to define the study area geography for this research.

The Sydney Greater Capital City Statistical Area within the Greater Capital City Statistics Areas 2011 (Volume 1) was used as the broad bounding area for the study. Because this area included large swathes of non-urban land, particularly by way of national parkland and agricultural cropland those areas from the Urban Centres and Localities 2011 (Volume 4) that were within this area were selected to form the basis of the study area. These urban centres and localities are shown in Figure 2.

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Figure 2 - Urban centres and localities functionally connected to Sydney

Source: Australian Bureau of Statistics (2011).

2.1.2 Defining the cognitive-cultural economy

The cognitive-cultural component of the economy has been measured in a variety of ways including through the measurement of jobs and employment, investment and economic output and via measuring patent and intellectual property filings (OECD, 2013). Davis and Mills (2012:4) note the difficulties in operationalizing the cognitive-cultural economy but suggest that overall “the cognitive‐cultural economy is represented by certain industries or sectors that disproportionately rely on work tasks, functions, and occupations with high cognitive or cultural intensity”.

As outlined in the literature component of this paper, the cognitive-cultural economy can be split into both ‘cognitive’ or knowledge-based components and ‘cultural’ or creative components. A variety of phenomena have been used measure these existence of cognitive and cultural economy including the presence and size of firms (Leslie, 2010; ÓhUallacháin and

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Leslie, 2007), employment by industry (Muñiz and Garcia-López, 2010) and employment by occupation (Scott, 2000).

This study uses employment within cognitive-cultural occupations and cognitive-cultural industries as indicators for the presence of cognitive-cultural economy. This approach was chosen for the following reasons:

Firstly, studying both industries and occupations, allowed for a comparison between these two separate yet related definitions of the cognitive-cultural economy. Since data were available at the same scale, from the same data collection agency, detailed comparisons were possible. Secondly, large-scale, fine-level data were available to analyse the specific locational characteristics of industry and occupation employment in Sydney. Such detailed analysis would not have been possible with investment-based or output-based data. Notably, studies such as those by Wall and Van der Knapp (2011) have focused on an inter-metropolitan or international scale where such data are more commonly aggregated.

Thirdly, groupings of cognitive-cultural occupations and industries are constructed from standardised industrial and occupational classifications that are based on United Nations-defined standards, used in many jurisdictions worldwide. This provides maximum reliability of this study within other contexts.

2.1.3 Categorising employment data

Units of analysis

Data was analysed using the TravelZone 2011 areal unit (hereby TZ11) which is produced by the Bureau of Transport Statistics, New South Wales, Australia. TZ11 zones have been created primarily for the analysis for transportation data, but are able to be used to analyse a wide range of demographic data including occupation and industry-based employment data. Within the study area, there were 2,275 TZ11 zones covering a total area of approximate 270,000 hectares. Zones range in size, although not as much as if non-urban areas were included in the analysis. TZ11 sizes range from 0.5 hectares to almost 6,000 hectares however the vast majority of zones are have a land area of between 1 and 5 hectares.

A uniform grid of aggregated point data (such as used by Vasanen, 2012) is the ideal areal unit for this type of analysis. Given that such fine-level data is not produced for Sydney, the fine-level TZ11 are the most appropriate unit to analyse and describe detailed information about employment distribution with fairly limited modifiable areal unit problem effects.

Employment dataset

The research used data that describes the work characteristics of employed persons in relation to industry and occupation. The core data to be used is the ‘Journey to Work’ database derived from questions in the Census of the Australian Population 2011 (hereby JTW11) and was provided on request from the Bureau of Transport Statistics, New South Wales, Australia.

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 Data table 2: Destination TravelZone by 4-digit industry code2  Data table 3: Destination TravelZone by 4-digit occupation code3

As this data was collected as part of compulsory 5-yearly Census of the Australian population it is a highly representative sample of the work practices of the general populace4_{. This dataset}

contains the home (origin) location, work (destination) location, industry type and occupation type of usual work for all employed adults (16 and over). Although data was initially collected with exact address location of home and work, this is not available for privacy reasons. All data is aggregated and presented as TZ11 zones.

Categorising cognitive-cultural industries and occupations

At the 4-digit classification level the industry dataset contained 506 categories, and the occupation dataset 476 categories. In order to best determine which industries and occupations should form cognitive-cultural economy several criteria were created, based on core attributes of tasks involved in and output resulting from work in the cognitive-cultural economy. As noted in the review of literature for this study, there has been a degree of ambiguity and cloudiness in the definition of these attributes and tasks (Markusen et al., 2008). In defining the cognitive-cultural economy for this study, criteria were developed in order to transparently determine whether specific industries and occupations could be attributed to the cognitive-cultural economy.

Table 1 outlines these criteria as well as academic reference to support their application. The work of Allen Scott features prominently, due to the large amount of study and theory development he has produced regarding the cognitive-cultural economy. In other cases, the definition of the cognitive-cultural economy is considered as the combination of cultural and creative pursuits combined with knowledge-based pursuits, which are largely considered by different, yet related, bodies of literature.

An industry category was classified as part of the CC economy if it met at least two of the three criteria above or met the knowledge-based or cultural outputs criteria. Approximately one fifth (103 of 506) industry categories met these criteria. An occupation category was classified as part of the CC economy if it met any one of the three criteria. Approximately one third (164 of 476) occupation categories were classified as belonging to the cognitive-cultural economy.

2_{The 4-digit industrial code relates to the standardised and widely used definition of industries in the}

Australia and New Zealand Standard Industrial Classifications – 2006, (ANZSIC), Australian Bureau of Statistics, 2006.

3_{The 4-digit industrial code is derived from the standardised and widely used definition of industries in}

the Australia and New Zealand Standard Classification of Occupations- 2006 (ANZSCO)

4 Despite its compulsory nature, there is an acknowledged undercount within the Census data that varies depending on question due to incomplete or unfilled data. In 2011, approximately 14 per cent of respondents nationwide did not indicate a specific place of work.

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Table 1 - Industrial and occupational attributes of jobs within the cognitive-cultural economy.

Criteria Academic References

Ind

us

tr

ial

Production of new material

Industrial output is the creation of something new with the value added from labour rather than the

maintenance of existing material. This output need not be tangible.

Scott (2010:2) highlights the difficulty in ‘drawing a line’ between the production tangible and intangible goods within creative industry.

Knowledge-based or cultural outputs

The outputs of the industry are intrinsically based on knowledge or cultural-inputs

Pratt (1997:1960-61) Activities that are necessary for the social production of a cultural event or artefact.

Davis and Mills (2012: 4) “The cognitive‐cultural economy is represented by certain industries or sectors that disproportionately rely on work tasks, functions, and occupations with high cognitive or cultural intensity.”

Specialized output

The industrial output is highly specialized, often for specific purpose that may change from task-to-task.

Markusen (2008: 27) Cultural industries, then, are directly involved in the production of social meaning in the form of texts and symbols.

Power (2009:106) “production of goods and services whose value is primarily or largely determined by their aesthetic, semiotic, sensory, or experiential content” Cruz and Teixeria (2012: 9) “creative industries generate novelties protected by patents or intellectual rights” Scott (2007: 1466) “sectors that thrive on innovation, product diversity and the provision of personalized services.” Occupa tio n al Decision-making

Core or large part of role involves making decisions for which role is responsible

Scott (2007, 1468) “managerial and allied workers carry out the functions of administration, monitoring and control of the production system as a whole”

Creative

Role is predominantly based on the creativity of person

Garnham (1987) defines the cultural industries as the "social practices whose primary concern is to transmit meaning" (page 2). In Pratt (1997: 1956)

Scott (2007, 1468) “…workers with well-honed artistic and intellectual sensibilities make up an increasingly important part of the labour force.”

Specialised knowledge required

Highly specialized, requiring very specific knowledge and training

Florida (2003). A specialised knowledge requirement criteria will be met by those occupations that have a high cognitive component. Generally this has been applied according to requirement for higher education (university degree or similar).

The spatial organisation of jobs in Sydney’s cognitive-cultural economy.