All the articles included empirical material, but the size of the samples varied.
Article I is a small-N study, focusing on three case examples. Article III is a large-N statistical analysis performed using material from 377 cities, and Article IV is a medium-N document analysis with a sample of 12 C40 member cities. In Article II, the analysis is based on a relatively large-N (all the members of the CP network), but the results are interpreted by focusing on what they reveal about this single CBN case.
In Article I, I analysed the role of institutionalised networks in three case example cities: Helsinki, Madrid and Stockholm. All three participate in several formalised networks. Although all these cities are European capitals and have the shared context of the EU, they offer three different points of view on multilevel networking. Following the classification of Lamb et al. (2019), Madrid is a large city, Helsinki is a small one, and Stockholm falls in between.
None is among the most studied cases in this area (Lamb et al. 2019).
Stockholm was the first city to achieve the European Green Capital Award (European Commission 2010). It participates actively in several networks; for example, it has been the vice-chair of Eurocities and is one of the cities that
joined C40 the year the network was founded. Stockholm has been described as a model city for sustainability (European Commission 2010).
Although Helsinki and Madrid are also active in climate issues, their international reputation does not equal that of Stockholm. However, Madrid is a member of C40, among other networks, which at the time of the study had its European office situated in the city. Unlike the other two cases, Madrid does not have internal networks or CBNs. Helsinki has sought to join C40 but has not been selected. However, the city participates in other international networks and also has internal networks as well as CBNs.
To collect material to analyse how the city officials viewed formalised networking, I conducted semi-structured interviews (Magnusson & Marecek 2015). This information generated by these interviews was also used in Articles II and IV. Interviews lasted, on average, 54 minutes. The themes varied depending on the role the respondent played in climate mitigation (for details, see the supplement of Article I, Section 1A). Although my interest was to determine the benefits of networking, I started by posing the question concerning impacts so that the respondents had the possibility to decide if they wanted to talk about negative or positive impacts. I also asked about unexpected or surprising impacts. I interviewed all respondents face-to-face except one, whom I interviewed via Skype’s video call feature. Before the interview, I offered them information about the study and processing of data, informing them that the data would be anonymised but that I would publish direct quotes from it. I recorded, transcribed and anonymised all the interviews. I did not include all filler words and sounds in the transcriptions as they were not relevant for the analysis. I conducted and analysed the interviews in Finnish in Helsinki, Spanish in Madrid and English in Stockholm. Since the interviews were carried out in 2017, the experiences referred to had occurred before that year. The time covered depended on the respondents, since some had been working with urban climate governance for decades while others had familiarised themselves with the topic only recently.
In Article II, I focused on the CBN of Helsinki, the CP, as a case example of a CBN. My co-authors and I analysed the performance of the CP network and its members from two viewpoints: participation and self-reported climate action. To evaluate the participation, we used graph analysis and indicator analysis; to evaluate the self-reported climate action, only the indicators were used. For the graph analysis, we used the participation data of the events organised by CP from the beginning of the network in 2012 to 2018. The data were provided by the coordinator of the network, that is, the City of Helsinki, on condition that they would be anonymised. Hence, we divided the members of the CP into 15 fields. First, we divided the participants in the events based on their membership status into business members (BMs), other members (OMs) and non-members (NMs). Then, we created the following fields: city of Helsinki, other public services, NGOs and educational institutions. All these belong to the OM or NM membership class. Next, we divided the BMs and the remaining NMs into nine business fields (e.g. logistics, consultation and
energy; see Supplementary Table 1 of Article II for details) based on the information available on their web pages. We anonymised the data so that every participant was given an alias consisting of their membership class, a code describing their field and a number that individualised them within that field. We made sure that the fields were general enough for the purpose of anonymisation, always containing more than one company or organisation.
The CP network asks its members to report their climate actions on a yearly basis. This is a voluntary activity, but discussions with the CP coordinator indicate it was found to be an important way to participate in the network.
Reports also gave us the opportunity to analyse what the companies participating in the network plan to do and have done during their membership. We collected the reports from the webpage of the CP since they were publicly available. Until 2017, the network produced the reports, after which the members submitted their information directly to the webpage.
In Article III, we used the data collected by Araos and colleagues (2016) between January 2nd and March 29th 2014 and data about network memberships. The data comprise 997 adaptation initiatives in 402 urban areas with populations of more than one million people around the world. Following a method used by other studies that collected information about adaptation planning (Reckien et al. 2014, 2018, Lesnikowski et al. 2016), Araos and colleagues collected climate change documents through the Google search engine using ‘climate change’ and city names as search terms. Documents in the following languages were included: English, Spanish, French, Chinese, Arabic, Russian, German, Portuguese, Farsi, Korean, Japanese, Turkish and Indonesian (Araos et al. 2016). This kind of search method focuses the study on ‘highly intentional’ adaptation policies (Dupuis & Biesbroek 2013, p. 1480).
I added information to these data about whether the cities were members of C40, ICLEI and/or GCoM in 2019. For the members, I also marked the years in which the cities joined the networks, checking whether they were members before 2014, the year in which API data were collected (Araos et al. 2016). The membership data were provided by the networks in 2019, and I checked some details from the webpages of the cities. Due to missing data, I had to exclude some cities in this phase, which decreased the sample size to 377 cities.
For Article IV, I collected the climate change mitigation and adaptation plans from 12 C40 member cities, six located in the Global North and six in the Global South: Buenos Aires, the City of Melbourne, Copenhagen, Delhi, Ho Chi Minh City, Johannesburg, Lagos, London, Madrid, New York City (NYC), São Paulo and Vancouver. Here, I defined the Global North as Annex I countries and the Global South as Non-Annex I countries under the UNFCCC.
The cities were selected based on the availability of the strategies and to ensure there were cases from all six continents. To ensure that network membership had the potential to affect the plans, I only selected cities that had joined C40 before the strategies were published. Furthermore, I estimated that the cities mentioned often in the documents of C40 are probably more active in the network than those mentioned rarely. Therefore, I calculated the times
different cities were mentioned in two major reports by C40, ‘Climate Action in Megacities’ (CAM3, 2015) and ‘Unlocking Climate Action in Megacities’
(2016). I selected both frequently and rarely mentioned cities for the analysis.
I obtained some documents from the researchers Patrick Driscoll (Technical University of Denmark) and Martin Lehmann (Aalborg University) and collected the rest from the web pages of the cities in 2016. For a summary of the material used in the four articles, see Table 4.
Table 4. Materials used in the articles
Article Materials Timeframe in materials
Collected I Interviews with city
officials and other informants in Helsinki, Madrid and Stockholm
Before 2017 2017 by MH
II Event participation data
2011–2018 2019, received from the network coordinator Reports from the
network webpage
2012–2018 2019 by MH
III City-level climate adaptation
documents (for API)
2014 2014 by Araos
et al.
Membership data in C40, ICLEI and GCoM
From date of network foundation to 2019
2019 received from said networks, partly collected by MH
IV Climate change adaptation and mitigation plans from the city webpages;
documents produced by C40
Published 2009–
2015, set targets to different timescales, e.g., overall
mitigation goals for 2020, 2025 or 2030
2016 by MH, Patrick Driscoll and Martin Lehmann