The global city

Globalization, economic change, urban formation and public governance during the twentieth century gave the impetus for the emergence of a special type of spatial expression at their intersection, which came to be known as the global city. The root of such a formation is more accurately conceptualized as ‘world city’, which was used in 1915 by Patrick Geddes to refer to those urban centres where a disproportionate amount of the world’s business was conducted (Doel and Hubbard 2002), but more properly conceptualized in the 1960s by the urban historian Sir Peter Hall, who conceptualized world cities primarily as concentrations of political and bureaucratic power surrounded by a range of professional associations, trade unions, headquarters of business concerns and cultural institutions (Newman and Thornley 2005: 20).

Around the early 1980s our understanding of globalization started to become more mature, including the re-conceptualization of world cities. This new insight is usually associated with John Friedmann (1986), who in turn relied on Wallerstein’s (1976) world systems theory but focused primarily on its implications for cities. This theorization became known as the ‘world city hypothesis’ which is based on the idea that economic globalization is articulated through urban nodal points, leading to the restructuring of these cities and the asymmetric relations with cities in terms of a global division of labour. Some of the cities became world cities – either primary or secondary world cities depending on their maturity and connections to the world economy – due to their role in global financial services, the availability of advanced business services, connections to major transportation hubs, the attraction of international institutions, the concentration of headquarters of multinational corporations and the size of population (Newman and Thornley 2005: 20).

This view started to feed the discussion about world cities and related global hierarchy, primarily seen as concentrations of international institutions, financial institutions and company headquarters. Such a conceptualization emphasizes economic power at the core of urban hierarchy formation. The seminal work that disseminated the view of the apex of global urban hierarchy, highlighting the role of New York, London and Tokyo as the major trans-territorial marketplaces and command-and-control centres of the global economy, was Saskia Sassen’s The Global City (2001 [1991]). Sassen was also one of those who started to point out the difference between ‘world city’ and ‘global city’, as not all world cities were global cities in the sense she understood them. (Newman and Thornley 2005: 20–1). Sassen explains her terminological choice as follows: “When I first chose to use global city, I did so knowingly – it was an attempt to name a difference: the specificity of the global as it gets structured in the contemporary period. I did not choose the obvious alternative, world city, because it had precisely the opposite attribute: it referred to a type of city which we have seen over the centuries in earlier periods in Asia and in European colonial centers. In this regard, it can be said that most of today’s major global cities are also world cities, but that there may well be some global cities today that are not world cities in the full, rich sense of that term.” (Sassen, 2005: 28)

What is essential in such a view is the focus on the function of cities in the global division of labour and in global networks rather than, say, their population size or political power. Thus there are many exceptionally large cities or megacities in different parts of the world, but only a few of them are genuine world cities and even fewer could be included among the highest ranking global cities. Beside command power and financial and business services, global cities essentially are defined by their connectivity, which has different layers, such as telecommunications, transportation and business networks (cf. Newman and Thornley 2005: 22–3). One aspect of such connectivity relates to the key topic of this book, the preconditions for a city’s ability to attract values from the global value flows.

It has been claimed that the concepts of world city and global city are atomistic – or at least ‘pointillist’ – as they are defined as bounded spatial entities with quantifiable attributes that are in their exclusive possession. The world city discourse started to change after Castells’ (1989) analysis of the informational city and Sassen’s analysis of the global city, as both of them in their own way shifted the root metaphor from hierarchy to network. A postmodern challenge to this view was articulated by Doel and Hubbard (2002) in an attempt to overcome the atomism implicit in the idea of functionally and spatially fixed positions of cities within a structured global network by focusing on how such relations are built, how flows drift in and out, how they contract and expand, how they fold and unfold space. At its extreme, in such a picture cities’ positions and intercity relations are in a perpetual state of becoming. Whether such a hyperbolic conception matches reality is another matter.

Even if cities such as New York and London are currently unchallenged as global cities, their ability to stay competitive cannot be taken for granted. Amirahmadi and Wah (2002) have pointed out how industry employment, occupational structure and educational attainment in New York City gives a glimpse of the daunting challenges ahead for economic restructuring. They state: “[t]he need to upgrade skill and educational levels and to grow quality jobs in the global city is of utmost importance to its economic restructuring. The question remains unanswered as to what types of industries would best suit the city’s population and would simultaneously maintain its global advantage … New York City will need to undertake the long and expensive process of generating highly educated residents if it is to retain and grow its global competitive advantage.” (Amirahmadi and Wah 2002: 101). In just the same way all global cities from London to Tokyo, San Francisco and Singapore face their own challenges which may threaten their long-term success.

Yet the global city is not a theoretical stance or paradigm that helps us to explain the realities of cities world-wide. As concluded by Newman and Thornley (2005: 268), grand theories of globalization and the world city or global city concept cannot account for the different experiences in cities throughout the developed world, from the USA to Europe and East Asia. What is needed is the analysis of the state and urban politics and governance. Local preconditions, histories and responses vary considerably, making it practically impossible to find a common pattern for the development of cities in the global context. This relates to the convergence hypothesis that cities, especially in the higher levels of global urban hierarchy, would become more similar owing to the pressure of global forces, the dominant model being business-led urban development or the neo-liberal city, epitomized by New York, Los Angeles or Toronto. In European cities, competitiveness policy is generally balanced by inclusion and a social agenda, as evidenced by Barcelona, Amsterdam, Stockholm and many other dynamic cities. The surge of Asian cities to the global top creates a new situation in the sense that they have traditionally been instances of the developmental state, which did not conform to the neo-liberal global city model. Seoul, just like Tokyo, is a developmental city that serves as a starting point for the Korean transnational corporations, not as a starting point for the global operations of footloose firms (Hill and Kim 2000). Even if the paradigmatic differences between Western neo-liberal global cities and Asian developmentalist global cities are definitively blurring, some traits of this dichotomy persist in representative top ranking cities in West and East.

The above is an excerpt from The Political Economy of City Branding by A.-V. Anttiroiko (Routledge, 2014, pp. 23-25).

References

Amirahmadi, Hooshang and Wah, Tatiana (2002) New York City: A Social Profile and Alternative Economic Futures. Journal of Urban Technology, 9(1), 85-107.

Castells, Manuel (1989) The Informational City. Information Technology, Economic Restructuring, and the Urban-Regional Process. Oxford: Blackwell.

Doel, M.A. and Hubbard, P.J. (2002) Taking World Cities Literally: Marketing the City in a Global Space of Flows. City, 6(3), 351-368.

Friedmann, John (1986) The World City Hypothesis. Development and Change, 17(1), 69-83.

Hill, Richard Child and Kim, June Woo (2000) Global Cities and Developmental States: New York, Tokyo and Seoul. Urban Studies, 37(12), 2167-2195.

Newman, Peter and Thornley, Andy (2005) Planning World Cities. Globalization and Urban Politics. Houndmills, UK: Palgrave Macmillan.

Sassen, Saskia (2001) The Global City: New York, London, Tokyo. First published 1991. Princeton, NJ: The Princeton University Press.

Sassen, Saskia (2005) The Global City: Introducing a Concept. The Brown Journal of World Affairs, XI(2), 27-43.

Wallerstein, Immanuel (1976) The modern world system. New York: Academic Press.

What’s the use of city rankings?

City rankings disclose strategic information about cities. Due to the nature of rankings, they inherently encourage people to take a relational and competitive view of cities, which contributes to the knowledge base of local economic policy. However, such a view is hampered by poor methodology and the generalist approach typical of many rankings. Especially when they use multiple criteria, this dramatically affects the overall scores and ranking order. In a similar way, finding ‘the best’ or ‘most attractive’ city in general terms may be relevant for high calibre global cities, but such a setting does not reveal much for assessing the role of more specialized middle-sized cities in the lower ranks. It is also difficult to determine how different aspects of ranking should be weighted. If Tokyo is a top city in global corporate headquarters, it may be on the problem side in terms of the cost of housing or living in general. If Helsinki is ranked innovative, it suffers from small scale, remoteness and a challenging climate. Mumbai may be one of the global leaders in attracting offshoring activities, but hygiene, health and infrastructure considerations put it definitively down in multi-criteria-based rankings. Combining a wide range of indicators tends to neutralize rankings, for global cities with multiple strengths will naturally stand out. The Economist Intelligence Unit’s (2012) benchmarking of global city competitiveness, PricewaterhouseCoopers’ Cities of Opportunity (PwC 2012) and MasterCard’s Worldwide Centers of Commerce Index (MasterCard Worldwide 2008) are good examples of such rankings. Their positive impact on local economic policy is, however, that they encourage policymakers and developers to look beyond narrow-minded economic indicators, implying that it is not only the number of headquarters, patents or skilled workers that count in global intercity competition and overall competitiveness, which is certainly true.

This creates an interesting methodological dilemma. ‘The World’s Best’ type of rankings become like a global city lottery, in which lower-rank global cities show up only randomly, depending on sampling and criteria. The problem becomes more obvious with the category of middle-sized cities, “which cannot compete in all fields of economic activity but have to focus on selected branches. This strategy of specialization is based on an accurate examination of existing economic, social and environmental potentials in order to find specific niches in which the city is able to establish some competitive advantage. For that reason, it does not really make sense to compare medium-sized cities generally and to evaluate their attractiveness in total.” (Giffinger et al. 2010: 303).

At the same time, rankings that are methodologically sophisticated enough have a strategic role to play as they are a powerful competitive instrument working on the basis of differences. This enables cities to find their position in the global urban hierarchy and economic division of labour, to sharpen their profiles and to initiate local learning processes (Giffinger et al. 2010: 310). In practice, such processes are largely affected by mediatized political economy, which leads to complex knowledge processes in which businesses, media, public managers, politicians and citizens interact. A simple expression of an impulse that ranking may give is the headline of a news item in Yahoo! Finance, India, published on the basis of a city ranking, ‘Mumbai among worst cities for intellectual capital and innovation: study’, or the one in Forbes in February 2013, ‘Detroit tops 2013 list of America’s most miserable cities’. Sometimes the results are used for promotional purposes too, as in the feature story in the investment portal of the City of Stockholm, entitled ‘Top ranking for Stockholm in prestigious report’, with a leader ‘The PWC ranking “Cities of Opportunity 2011” puts Stockholm at number four, together with New York, Toronto and San Francisco. It's the highest ranking city in Europe.’ Actually many large cities have started to publicize rankings in their economic development websites to substantiate the facts of their assets and performance, as in the website of the Economic Development Board of Singapore (https://www.edb.gov.sg/content/edb/en/why-singapore/about-singapore/facts-and-rankings/rankings.html). In such cases, rankings are powerful tools to convey a message of competitiveness, as the results are based on analyses and comparisons made by an independent party. Information on a city’s high position in different rankings gives an impression that the city really is a good place for business, belongs to the rank of global hubs, or is a member of a top league of creative cities or whatever is the message promoted by the city and supported by rankings. In addition, rankings serve many times as impulses for even leading cities to start the hard branding process, as was the case with Amsterdam in the first half of the 2000s (Gemeente Amsterdam 2004) or Sydney in the latter half of the 2000s (Parmenter 2011).

This discussion is an excerpt from The Political Economy of City Branding by A.-V. Anttiroiko (Routledge, 2014, pp. 137-139).

References

Economist Intelligence Unit (2012) Hot spots. Benchmarking global city competitiveness. A report from the Economist Intelligence Unit. The Economist.

Gemeente Amsterdam (2004) The Making of … the city marketing of Amsterdam. Het ontstaan van de city marketing van Amsterdam. I amsterdam. Amsterdam: Gemeente Amsterdam (City of Amsterdam).

Giffinger, Rudolf and Haindlmaier, Gudrun and Kramar, Hans (2010) The role of rankings in growing city competition. Urban Research and Practice, 3(3), 299-312.

MasterCard Worldwide (2008) Worldwide Centers of Commerce Index 2008. Insights. MasterCard Worldwide. Retrieved May 15, 2013, from http://www.mastercard.com/us/company/en/insights/pdfs/2008/MCWW_WCoC-Report_2008.pdf

Parmenter, Geoff (2011) The City Branding of Sydney. In: Keith Dinnie (Ed.) City Branding: Theory and Cases, pp. 199-205. Basingstoke: Palgrave Macmillan.

PwC (2012) Cities of Opportunity. PricewaterhouseCoopers. Partnership for New York City. Retrieved May 12, 2013, from http://www.pwc.com/us/en/cities-of-opportunity/assets/cities-opp-2012.pdf

 Amazon.com

Crowdsourcing 2.0 in Urban Planning

Crowdsourcing 2.0 refers to mass collaboration in which Web 2.0 technologies and services are utilized. In the context of urban panning, it includes such forms as wikipalnning, co-alerting, various forms of Web-assisted co-creation as well as participatory budgeting and crowdfunding. This mini-article clarifies the idea with a focus on wikiplanning, interactive websites, information platforms, participatory sensing, and co-creation. (Discussion is based on Anttiroiko, 2015).

Introduction

Web 2.0-based crowdsourcing platforms, applications, and services can be used to generate collective intelligence in urban planning (on crowdsourcing platforms and applications, see Doan et al., 2011). Crowdsourcing can smarten up various collective activities. Brabham (2013), for example, has proposed a problem-based typology of crowdsourcing approaches: (a) Knowledge discovery and management: mobilizing a crowd to find and assemble information, as in the case of creating collective resources; (b) Distributed human intelligence tasking: mobilizing a crowd to process or analyze information, such as large and diverse data sets not amenable to computer analysis; (c) Broadcast search or scientific problem solving: mobilizing a crowd to come up with a solution to a problem with an an objective, verifiable right answer; and (d) Peer-vetted creative production: mobilizing a crowd to come up with a solution to a problem with an answer that is subjective or dependent on public support - a category associated with design, esthetic, planning, and policy problems. In city planning the last aspect dominates, and a good example of this is wikiplanning.

From a more planning-oriented view we may consider the basic planning functions and assess the potential of Web 2.0-assisted crowdsourcing. Let us consider the following functions of a comprehensive planning process:

- Identifying issues: people may identify problems of the city, e.g. crowd ideation and involving citizens in problem identification.

- Stating goals: people expressing their ideas about the goals for city planning and the future of the city, e.g. wikiplanning.

- Collecting data: people can help in alert messaging, reporting, and collecting data, e.g. crowdsourced information platforms and mapping.

- Preparing the plan: people can contribute to the writing of the plan and designing solutions, e.g. wikiplanning, user-generated content creation, and mapping for the crowd.

- Evaluating alternatives: people can vote for or set priorities on alternatives or participate in scientific deliberative polling.

- Implementing the plan: people can assist in implementing a plan as co-creators and co-funders.

- Monitoring the plan: people may monitor and follow up the realization of the plan through crowdsourcing tools.

Such a range of Web 2.0 services and tools that can be applied to various planning functions illustrates the huge potential of crowdsourcing in urban planning. Next we elaborate this topic further. To structure the discussion let us rely on inductive categorization of the types of crowdsourcing derived from real-life cases in urban planning, which resemble the categories presented above. Discussion focuses on three forms of crowdsourcing 2.0: wikiplanning, informational crowdsourcing (co-alerting), and various forms of co-creation.

Wikiplanning and interactive websites

The first group of cases to be discussed is town planning exercises, which use content sharing and teamwork tools, such as wikis. A pioneering case of wikiplanning is Future Melbourne Wiki and Blog at http://www.futuremelbourne.com.au/wiki/view/FMPlan. The City of Melbourne, Australia, used wikis in 2008 to attract comments, to generate discussion, and to enable registered citizens to edit the content of the Future Melbourne draft plan. The City was possibly the first of its kind in the category of big cities to enter a new era of online community consultation focusing on large-scale city planning with the help of wikis.

Another pioneering case was the wikiplanning project of the City of San José, California, in conjunction with drafting the city’s general plan in 2009. It aimed at soliciting user input on the future of the city through a Web-based wiki. The core method for eliciting citizens’ views was a 19-question survey, which gathered citizen input in order to guide city officials making development decisions under the Envision San Jose 2040 plan. The survey was open to anyone at http://www.wikiplanning.org/. In addition to the survey, users were also able to post photos of elements from San Jose they liked or disliked. And if a user had seen something in another city that might be a good addition to San Jose, he or she could add photos of it or discuss it on a community message board. Citizens had also access to project data, background information, maps, PowerPoint presentations, and videos on city planning and sustainability. Besides utilizing collective intelligence through citizen participation and increasing the number of participants in the city planning process, wikiplanning was assumed to affect the composition of participants by attracting newcomers and especially younger citizens (Vander Veen, 2009; Bruensteiner, 2009).

Even if not literally wiki-based urban planning, there are hundreds of town planning cases where contributions from local inhabitants have been solicited. For example, the city of Bristol, Connecticut, set up a ‘Bristol Rising’ initiative with the idea of turning the city’s decaying downtown back into a thriving destination with a vibrant, walkable, contiguous experience. Residents were invited to upload their own ideas and join in discussions at the website so that developers could gauge exactly what the community wanted (See the site at http://www.bristolrising.com/). A similar project in New York starts with the question, “How can we make our city a better place to live?” Community members were invited to submit ideas at the ‘Change by Us NYC’ website (http://nyc.changeby.us/), where a network of city leaders read and considered each proposal. Successful projects operational in 2013 included a new community garden and greenhouse. Suggested improvements also included cleaning and repairing existing bike lanes, new pedestrian bridges, composting locations, and discounts on Citi Bike memberships for low-income residents. The third example worth special mention is My Ideal City (http://www.miciudadideal.com/en/), collaboration between several partners to redevelop the city of Bogota, Colombia, based on user input. The concept has certain peculiar features. First and foremost, the project organizes a half-year period of conversation through W Radio in Bogota and PSFK.com globally on trends around the future of the city, in Spanish and English respectively. Every week both parties discuss the same topic, on which audiences are asked to comment via Twitter or the project website. The responses are gathered and reviewed later by two experts working on a plan to redevelop a neighborhood in downtown Bogota (Fawkes, 2013; WebUrbanist, 2014).

Lastly, several planning-oriented crowdsourcing initiatives find their realization through commercially available citizen engagement platforms. A good example is Mindmixer, a platform that offers community leaders a chance to crowdsource ideas, pool assets and manage feedback (http://www.mindmixer.com/). Another case is Spigit software deployed by two US counties, Harford County, Maryland, and Maricopa County, Arizona, to gather ideas from citizens to make productivity gains and reduce costs. A similar community-based idea management system developed by Spigit was adopted by the City of Manor, Texas, in 2009. The project created an open innovation platform called Manor Labs as a common space for citizens to share their ideas on how to improve city operations (Vander Veen, 2010; Mergel, 2013; Mergel & Greeves, 2013).

Information platforms and participatory sensing

Crowdsourcing 2.0 has proved to be particularly useful in reporting problems. Such Web 2.0 applications and services can be used in the planning processes when identifying problem sites, disseminating information, learning from other cities, and generating development ideas. We could call these jointly informational or even ‘instant’ crowdsourcing. A paradigmatic case is New Urban Mechanics, an idea embraced by Tom Menino, Mayor of Boston to use technology for addressing the everyday problems of citizens. A showcase for their work is based on crowdsourcing via the use of smartphone-based applications available to citizens to alert officials about street-level problems in the city’s neighborhoods, such as complaints about potholes. In general, the phone + camera + GPS, all in one smart device, can make a revolution in such an instant crowdsourcing (Townsend, 2013, pp. 212-214; Goldsmith, 2010). It is close to the idea of participatory sensing, which empowers ordinary citizens to collect and share sensed data from their surrounding environments using their mobile phones (Kanhere, 2013).

Crowdsourced information platforms are changing the top-down nature of how news, opinions and complaints are gathered and disseminated by placing reporting tools in the hands of citizens. A case that takes us closer to the reality of urban planning is a project developed by the Beijing Transport Research Center and the World Bank aiming to find out to which areas transportation planners should be paying special attention. Anyone can submit a mini report on issues related to cycling and walking infrastructure through the website, smart phone applications, SMS, or social media. These user-generated reports are then mapped and visualized, and made available for public discussion (WebUrbanist, 2014).

Another somewhat similar snapshot is Place Pulse (http://pulse.media.mit.edu/), which aims to ascertain through user participation what makes a place feel safe, vibrant, active, unique, central, or family friendly. The site presents images side-by-side and asks users to rate them with questions like “Which place looks more beautiful?” The images are from cities around the world and provide researchers with data that can be used to study the association between urban perception and datasets like violent crime, creativity, and economic growth (WebUrbanist, 2014). To generalize, information platform-based crowdsourcing is a powerful tool for rating, comparing, and benchmarking the aspects of urban conditions, functionality, esthetics, and development.

Various forms of co-creation

Many Web 2.0 applications invite people to create their own drawings, videos or mockups to support a planning process. An illustrative prototype is Streetmix (http://streetmix.net/), an interactive street section builder that helps community members mockup the streets by modifying a street design template and presenting the results of their work as future plans for city planners (Miller, 2013). Another interesting pilot was Next Stop Design, a co-production website, which was part of a research project called “Crowdsourcing Public Participation in Transit Planning” active in 2009-2010. It was set up to find new ways of involving people as alternatives to traditional open meetings and workshops. This particular case had two rounds, of which the first was about letting citizens design bus shelters for the university campus in Salt Lake City and the second about dealing with the planning of an intersection in the Sugar House neighborhood of Salt Lake City. The project was a joint effort of the University of Utah and the Utah Transit Authority. (See Next Stop Design at http://www.nextstopdesign.com/).

To the category of co-creation-oriented crowdsourcing for the built environment we may also add CitiNiche from Australia, an online property development platform launched by a team of architecture, planning and digital technology professionals. The idea behind the project is to use crowdsourcing to develop proposals and attract potential owner-occupiers to residential properties, i.e., participants subscribe to “niches” matching their property preferences and enter further ideas for their ideal dwelling (see http://www.citiniche.com.au/). (Ward, 2013).

Betaville brings people together in the name of online gaming. This is an open-source multiplayer environment for real cities, in which ideas for new works of public art, architecture, urban design, and development can be shared, discussed, tweaked, and brought to maturity. It enables the public to visualize planned buildings that are to be built and also to collaborate or give feedback on urban planning (see http://betaville.net/). It started in New York City and has since expanded internationally (WebUrbanist, 2014). Another real-life planning game was known as Participatory Chinatown and launched in 2010. This was a 3-D immersive role-playing game designed to be part of the master planning process for Boston's Chinatown area (http://www.participatorychinatown.org/).

An important form of co-creative crowdsourcing utilizes geographical information and mapping. Hudson-Smith, Batty, Crooks and Milton (2009), for instance, have described how to harness the power of Web 2.0 technologies to create new approaches to collecting, mapping, and sharing geocoded data. There are applications like MapTube, GMapCreator, Image Cutter and PhotoOverlay Creator that let users make thematic maps, display images on the maps, and view, share, and mash maps online. An illustrative example is MapTube, which allows users to create new maps from scratch using a combination of crowdsourcing, crowdcasting, and broadcasting (http://www.maptube.org/). Another interesting case is the Ushahidi online mapping platform, which can be used for monitoring elections, pooling local resources, and mapping crisis information (see http://ushahidi.com/products/crowdmap/). Such tools contribute to our understanding of the opportunities provided by neogeography or ‘mapping for the masses’ (see Hudson-Smith, Crooks, Gibin, Milton & Batty, 2009; Haklay et al., 2008). In general, even if real-life cases of GeoWeb 2.0 in urban planning are still rare, combining crowdsourcing with geospatial intelligence has undeniable potential to smarten up urban planning practices. It is possible that a decisive impetus to the incorporation of such intelligence into planning comes through the increased use of tablets and smartphones (Leinbach et al., 2012; Allen et al., 2011).

Some relevant crowdsourcing applications and practices can be found in social or collaborative tagging (see Yi, 2012). In its paradigmatic form tagging allows users to add and change not only content (data), but content describing content (metadata). Users may tag basically any digital objects. In the libraries, for example, they may tag a library’s collections and thereby participate in the cataloguing process. Social bookmarking is another form of tagging, as in collecting Web site tips in Delicious or locating, organizing, and sharing one’s favorite online resources in PennTags at http://tags.library.upenn.edu/ (Maness, 2006; Lankes et al., 2007). Another form of social crowdsourcing based on tagging is the creation of folksonomies, i.e. classification systems created in a bottom-up fashion without central coordination. The result is a tag cloud that presents an aggregation of people’s usage or views rather than a systematic analysis of the structure of the given activity area (Lankes et al., 2007, p. 21; Anttiroiko & Savolainen, 2011; Casey & Sevastinuk 2006, 41). A special form of tagging worth mentioning is conversational tagging, which became popular through the use of hashtags (#) in Twitter. It does not create indexes for later retrieval but rather is motivated by attracting attention and making the message to appear in certain discourses or streams, as in the case of Twitter’s short-lived emergent topics known as micro-memes (Huang et al., 2010). Many of the projects around the world have substantiated the claim that people can significantly benefit the work of knowledge institutions and processes if organized in Web 2.0 style (Tay, 2009). The implications of such cases for urban planning are obvious. The experiences in commenting, rating, and tagging can serve communication, analysis, evaluation, and wrapping-up in the planning process.

Epilogue

There is a plethora of examples of how Web 2.0 tools can be applied to urban planning. However, experiences in Urban Planning 2.0 are so far thin and true breakthroughs and killer applications are still fairly few. Nevertheless, their potential to enhance various forms of social intelligence is undeniable. One of the areas that have clearly shown potential is the ability of Web 2.0 tools to support crowdsourcing, which is a primary method that generates collective intelligence. The cases discussed earlier in this chapter, most notably such as wikiplanning in Melbourne and Palo Alto, are indications of the potential to increase intelligence in urban planning via Web 2.0. Yet much remains to be learned about the preconditions for the realization of such potential. Besides, wikiplanning is only the tip of the iceberg of activities which have a potential for smartening up urban planning. The precondition for optimal enhancement of Web 2.0-assisted intelligence is the understanding of social and cultural dimension of the deployment of new ICTs. The other important element, which is critical to collective intelligence in particular, is the appreciation of diversity (Surowiecki, 2005). After learning from various facets of Web-enabled social intelligence in urban planning, the next step is to consider the need for their integration, which may pave the way for a new role of artificial intelligence and even technological singularity in urban planning, which may eventually profoundly change the way we plan and develop our cities.

References

Allen, M., Regenbrecht, H., & Abbott, M. (2011). Smart-phone augmented reality for public participation in urban planning. In: Proceedings of the 23rd Australian Computer-Human Interaction Conference (OzCHI'11), (pp. 11-20). New York: ACM. Retrieved May 20, 2014, from http://doi.acm.org/10.1145/2071536.2071538

Anttiroiko, Ari-Veikko (2015). Smart Planning: The Potential of Web 2.0 for Enhancing Collective Intelligence in Urban Planning. In: Carlos Nunes Silva (Ed.) Emerging Issues, Challenges, and Opportunities in Urban E-Planning. Hershey, PA: IGI Global, pp. 1-32.

Anttiroiko, A.-V. & Savolainen, R. (2011). Towards Library 2.0: The Adaption of Web 2.0 Technologies in Public Libraries. Libri, 61(2), 87-99.

Brabham, D.C. (2009). Crowdsourcing the Public Participation Process for Planning Projects. Planning Theory, 8(3), 242-262.

Brabham, D.C. (2013). Crowdsourcing. Cambridge, MA: The MIT Press.

Bruensteiner, M. (2009). San Jose experiment with "Wikiplanning". Metblogs, San Jose, August 11th, 2009. Retrieved November 2, 2009, from http://sanjose.metblogs.com/2009/08/11/san-jose-experiments-with-wikiplanning/

Casey, M.E. & Sevastinuk, L. C. (2006). Library 2.0 service for the next-generation library. Library Journal, 131(14), 40-42.

Doan, A., Franklin, M.J., Kossmann, D., & Kraska, T. (2011). Crowdsourcing Applications and Platforms: A Data Management Perspective. In: Proceedings of the VLDB Endowment, 4(12), 1508-1509. Retrieved May 20, 2014, from http://www.vldb.org/pvldb/vol4/p1508-doan-tutorial4.pdf

Fawkes, P. (2013). PSFK helps launch MyIdealCity, a crowdsourced plan to redesign a city in South America. PSFK.com, April 7, 2013. Retrieved May 27, 2014, from http://www.psfk.com/2013/04/my-ideal-city-crowdsourcing-project.html#!Q99IF

Goldsmith, S. (2010). Phone + GPS + Camera = Revolution. Governing, March 17, 2010. Retrieved May 22, 2014, from http://www.governing.com/blogs/bfc/Phone--GPS-.html

Haklay, M., Singleton, A., & Parker, C. (2008). Web Mapping 2.0: The Neogeography of the GeoWeb. Geography Compass, 2(6), 2011-2039.

Huang, J., Thornton, K.M., & Efthimiadis, E.N. (2010). Conversational tagging in twitter. In: Proceedings of the 21st ACM conference on Hypertext and hypermedia HT’10 (pp. 173-178). New York: ACM.

Hudson-Smith, A., Batty, M., Crooks, A., & Milton, R. (2009). Mapping for the Masses: Accessing Web 2.0 Through Crowdsourcing. Social Science Computer Review, 27(4) 524-553.

Hudson-Smith, A., Crooks, A., Gibin, M., Milton, R., & Batty, M. (2009). NeoGeography and Web 2.0: concepts, tools and applications. Journal of Location Based Services, 3(2), 118-145.

Kanhere, S.S. (2013). Participatory Sensing: Crowdsourcing Data from Mobile Smartphones in Urban Spaces. In: C. Hota & P.K. Srimani (Eds.), Distributed Computing and Internet Technology. Lecture Notes in Computer Science, Volume 7753 (pp. 19-26). Berlin and Heidelberg: Springer.

Lankes, R.D., Silverstein, J., & Nicholson, S. (2007). Participatory Networks: The Library as Conversation. Information Technology and Libraries, 26(4), 17-33.

Leinbach, J., Diaz-Uda, A., & Eggers, W.D. (2012). 'Where' Matters: Shaping Public Services for the Mobile Citizen. Governing, October 3, 2012. Retrieved May 22, 2014, from http://www.governing.com/columns/mgmt-insights/col-location-based-services-smartphones-government.html

Maness, J. M. (2006). Library 2.0 Theory. Web 2.0 and Its Implications for Libraries. Webology, 3(2). Retrieved March 4, 2010, from http://www.webology.ir/2006/v3n2/a25.html

Mergel, I. (2013). Social Media in the Public Sector. A Guide to Participation, Collaboration, and Transparency in the Networked World. San Francisco: Jossey-Bass.

Mergel, I. & Greeves, B. (2013). Social Media in the Public Sector Field Guide: Designing and Implementing Strategies and Policies. San Francisco: Jossey-Bass.

Surowiecki, J. (2005). The Wisdom of Crowds: Why the Many Are Smarter than the Few. London: Abacus.

Tay, A. (2009). Libraries and crowdsourcing – 6 examples. Retrieved March 4, 2010, from http://library20.ning.com/profiles/blogs/libraries-and-crowdsourcing-6

Townsend, A.M. (2013). Smart Cities. Big data, civic hackers, and the quest for a new utopia. New York: W.W. Norton & Company.

Vander Veen, C. (2009). San Jose, Calif.'s Wikiplanning Project on Course. Digital Communities, December 27, 2009. Retrieved May 20, 2014, from http://www.digitalcommunities.com/articles/San-Jose-Califs-Wikiplanning-Project-on.html

Vander Veen, C. (2010). Manor, Texas, Crowdsources Ideas for Running the Town. Digital communities, May 10, 2010. Retrieved May 22, 2014, from http://www.digitalcommunities.com/articles/102472519.html

Ward, M. (2013). Crowdsourcing the city. Architecture Australia, 102(5). Posted 2 Dec 2013. Retrieved May 20, 2014, from http://architectureau.com/articles/crowdsourcing-the-city-brickstarter-citiniche-and-digital-democracy/

WebUrbanist (2014). Crowdsourced City: 14 Citizen-Directed Urban Projects. Article by Steph. Retrieved May 26, 2014, from http://weburbanist.com/2014/03/05/crowdsourced-city-14-citizen-directed-urban-projects/

Yi, K. (2012). Harnessing collective intelligence in social tagging using Delicious. Journal of the American Society for Information Science and Technology, 63(12), 2488–2502.

* * *

This mini-article is a slightly modified excerpt from: Ari-Veikko Anttiroiko(2015) Smart Planning: The Potential of Web 2.0 for Enhancing CollectiveIntelligence in Urban Planning. In: Carlos Nunes Silva (Ed.) Emerging Issues,Challenges, and Opportunities in Urban E-Planning. Hershey, PA:IGI Global, pp. 1-32.

Typology of economic flows

One of the most challenging aspects of making sense of Flow Paradigm is to identify the relevant types of economic flows. To start with, it is worth stressing that the flows between hubs are difficult to identify and quantify (see e.g. Salisbury & Barnett, 1999, 35; Pain & Hall, 2008; Limtanakool et al., 2009). Some simple dichotomies have some relevance in this respect, such as frictionless vs. frictional flows. ‘Frictionless’ flows - what Castells (1996) has referred to as a whole as the 'space of flows' - that are generally transferable as electronic or digital flows are characteristically production factor flows (technology flows, capital flows, and information flows), whereas ‘frictional’ flows or physical flows are basically of three kinds: (i) freight and material flows; (ii) client flows, such as tourists, conference visitors and students; and (iii) productive actor flows, such as relocating firms, inflow of skilled and creative people and professionals as well as low-skilled immigrants (cf. Kostiainen, 1999). These flows make up two primary realms, both of which are expedited by technological development. Digitalisation changes symbolic, information, and monetary flows, whereas improvements in mobility and logistics do the same to material and client flows (see e.g. Williams & Balàz, 2009; see also Anttiroiko, 2014b).

To make sense of the field of flows, we may consider the fundamental economic roles of people in terms of consumption and production, the classic typology of markets (factor and product markets) and the city as an economic spatio-temporal locus that combines these elements through investment, production, distribution and consumption functions. Such a robust model of the main aspects of economic flow analysis is presented in Figure 1.

Figure 1. Illustration of city as the integrator of different types of flows. (Anttiroiko, 2015).

Some of the typologies of flows are based on contextual analysis, such as Appadurai’s (2003) five ‘flowscapes’ – people, technologies, finance, media and ideologies – as the landscape of late modernity. Yet, to achieve a scheme that is relevant for local economic development policy, such a typology should be accurate and provide a synthesised approach to flows. An example of the generic typology of flows that fulfils this criterion is proposed by Williams and Balàz (2009, 679-680). It is built on four major categories related to regional development: (1) trade, (2) labour migration, (3) capital and (4) knowledge. Similarly, in McKinsey Global Institute’s report on global flows the main flow categories analysed were goods, services, finance, people, and data (Manyika et al., 2014). In DHL Global Connectedness Index 2014 global connectedness of a country or macro-region was defined as their participation in international flows of trade, capital, information and people. These four pillars were further divided into following components (Ghemawat & Altman, 2014):

Trade

- Merchandise trade

- Services trade

Capital

- FDI stocks

- FDI flows

- Portfolio equity stocks

- Portfolio equity flows

Information

- International Internet bandwidth

- Telephone call minutes

- Trade in printed publications

People

- Migrants (foreign born population)

- Tourists (departures and arrivals)

- International students

To summarise, it seems that the four most frequently included categories of flow analysis are capital, trade, information and people.

These form a good starting point for identifying different flows that have a critical role in local economic development. Yet, they show also clearly the differences in the clarity and availability of relevant data. As a rule, any flow that can be expressed in units, such as money or number of items or people, are fairly easy to define, even if the availability of data may be occasionally a problem. Yet, categories like information or knowledge are obviously difficult to operationalise not to speak of the difficulty of obtaining relevant data. The problem in the latter case concerns both ambiguity and uncertainty (Daft & Lengel, 1986). This explains the use of surrogate data, which leads sometimes obvious methodological problems. To illustrate the complexity of this setting, let us combine various flows in a rudimentary model, presented in Figure 2.

Figure 2. Illustration of economic flow analysis. (Adopted from Anttiroiko, 2014a).

This kind of analysis helps to make sense of the nature of local economy in an increasingly 'fluid' economy. Increasing share of our wealth is created at the hubs of flows, which should be taken into account in local economic development policy. It urges us to learn more about how to attract flows from the space of frictionless and frictional flows, how to process such flows within a local 'dissipative structure' (i.e. open city), and how to create products and services that meet the demand in global markets.

References

Anttiroiko, A.-V. (2014a). International City Branding: Attraction Imperative, Specialization and New Urban Brand Analytics. Proceedings of the 17th Annual International Conference of ASBBS, pp. 12-25. Paris, June 20-22, 2014. San Diego, CA: American Society of Business and Behavioral Sciences.


Anttiroiko, A.-V. (2014b). The Political Economy of City Branding. London and New York: Routledge.


Anttiroiko, A.-V. (2015). New Urban Management: Attracting Value Flows to Branded Hubs. Basingstoke: Palgrave Macmillan.


Appadurai, A. (2003). Modernity at Large. Cultural Dimensions of Globalization. First published 1996. Sixth printing 2003. Minneapolis, MN: University of Minnesota Press.


Castells, M. (1996). The Rise of the Network Society. The Information Age. Economy, Society and Culture. Vol. I. Cambridge, MA and Oxford, UK: Blackwell.


Daft, R.L. & Lengel, R.H. (1986). Organisational Information Requirements, Media Richness and Structural Design. Management Science, 32, 554-571.


Ghemawat, P. & Altman, S.A. (2014). DHL Global Connectedness Index 2014. Analyzing global flows and their power to increase prosperity. DHL. Retrieved February 12, 2015, from http://www.dhl.com/content/dam/Campaigns/gci2014/downloads/dhl_gci_2014_study_low.pdf


Kostiainen, J. (1999). Competitiveness and Urban Economic Development Policy in Information Society. Futura, 18(3), 14-36.


Limtanakool, N. & Schwanen, T. & Dijst, M. (2009). Developments in the Dutch Urban System on the Basis of Flows. Regional Studies, 43(2), 179-196.


Manyika, J., Bughin, J., Lund, S., Nottebohm, O., Poulter, D., Jauch, S. & Ramaswamy, S. (2014). Global flows in a digital age: How trade, finance, people, and data connect the world economy. April 2014. McKinsey Global Institute. Retrieved February 20, 2015, from http://www.mckinsey.com/~/media/McKinsey/dotcom/Insights/Globalization/Global%20flows%20in%20a%20digital%20age/MGI_Global_flows_in_a_digial_age_Full_report.ashx


Pain, K. & Hall, P. (2008). Informational Quantity versus Informational Quality: The Perils of Navigating the Space of Flows. Regional Studies, 42(8), 1065-1077.


Salisbury, J.G.T. & Barnett, G.A. (1999). The World System of International Monetary Flows: A Network Analysis. The Information Society, 15, 31-49.

Williams, A.M. & Baláz, V. (2009). Low-Cost Carriers, Economies of Flows and Regional Externalities. Regional Studies, 43(5), 677-691.

City of Tampere, Finland