Paper 1 - Aanpak
Social innovation is about people.
People come together. Interaction --> in-between --> the encounter
Interesting to look at social innovation from an social geography perspective and the concept of the encounter
Research questions
Deze onderzoeksvragen zijn van belang voor dit paper
- What is the role of the encounter for social innovation?
- Encounter as in-between to grapple with the quality of social innovation
Research does not pay enough attention to the process through which public professionals and citizens communicate (in-between) (p.21).
Despite the growing body of literature on public encounters, up to now, the encounter itself has not yet been adequately understood. Capturing this relational process of "knowing-in-interaction" can help to grapple with the quality of participatory democracy (p.22).
One particular outcomes of this thesis that would deserve more exploration is the concept of "process". The analysis demonstrated that participatory practise is best understood as process, or composition of processes, with distinct and "unowned" qualities. Communicative capacity was found to be an emergent property of these processes, in the sense that is resides in the "in-between", i.e. the interactions that local actors have with each ohter and the situation at hand. Accordingly, the thesis argues that capturing the processes through which public professionals and residents communicate is crucial to grappling the quality of participatory democracy. The concept of process has for long been the focal point of process philosophy (Rescher, 1996) and has recently entered debates in public administration and public policy (Cook & Wagenaar, 2011; Stout & Staton, 2011; Wagenaar & Cook, 2011). The application of the concept of process in both methodology and empirical analysis is still relatively young, and this thesis hopefully makes a contribution to developing it. Still, a central challenge for future research on participatory democracy, as well as policy making and politics more in general, remains the design and application of “methods that enable the analyst to register ... [the] give-and-take between the initial expectations and preconceptions of the individual subject and the way the world talks back to him” (Wagenaar, 2011, p. 62), together with a deeper understanding of the implications of process for social reality and our knowledge of it (p.247).
Reasoning
Participatory democracy
Structuring forces of social innovation - complex interplay of factors:
- complex webs of organisations
- rules and regulations
- finances and budget
- political power
- power inequalities
- antagonism
The quality of participatory democracy depends largely on the capacity of public professionals and citizens to recognise and break through dominant communicative patterns. (p.21)
How do people act upon them? (VWS)
Participatory democracy: The influence of non-elected individuals and organisations on public decision making and implementation is the norm for democracy, rather than a deviations from it (p.17).
The Netherlands: "Room to develop initiatives.... and take responsibility without interference of public professionals" (Ministerie van Binnenlandse Zaken, 2009, p.1 in Bartels, 2012, p.18).
Bartels (2010) argues the importance of communicative capacity for participatory practises in which (public) professionals and citizens navigate this complex interplay.
Making participatory democracy work on all levels proved to be really difficult (p. 18)
Communicative capacity is an end result rather than a starting point (p.19)
Social Innovation
Social innovation definitions are focussed on stressing the importance of meeting a social need and bring about social change (Cajaiba-Santana 2014).
Social innovation is mainly concerned with creating a positive impact on society and focusses on improving the quality of life of individuals and communities (OECD 2001; Moulaert 2009).
Westley et al. (2014) postulate social innovation is a complex set of processes and methodologies.
The definition of Baker and Mehmood (2015, p.321) suggests social innovation “can be understood as extraordinary measures taken by ordinary people and is closely tied to the notion of social capital.” In this vein, Benneworth and Cunha (2015, p.510) define social innovations as “bottom-up phenomena”
Scholars have recognised that enabling and strengthening collaboration, creating new social relationships and taking collective actions towards social challenges are increasingly becoming generally implied and sought for practises in social innovation (Murray et al. 2010; Grimm et al. 2013; Cajaiba-Santana 2014; Schweitzer et al. 2015). While the previous discussion indicates social innovation is a process which is goal-oriented and concerned with value creation for society at large, the process of incorporating for instance collective practises, bottom-up initiatives and cross sectional and interdisciplinary collaboration is an end in itself in social innovation. This is best captured by the definition of Grimm et al. (2013, p.450) stating
“social innovation is not purely target-oriented. The process – cooperation, coproduction, interaction, sharing of resources, etc. – of delivery is an important outcome of the innovation itself. In other words, social innovation is a means to an end and an end in itself. In stressing the significance of social processes, social innovation emphasizes the value of social capital for building sustainable and resilient societies that have the capacity to act in an environment of permanent change.”
Grimm et al. (2013, p.440) posit:
“There seems to be a general consensus that the social is neither a passive receiver of policy interventions or of global economic forces but, importantly, that social networks and processes themselves are important resources to anticipate change and to make societies more cohesive and resilient.”
Scholars perceive the strains on today’s society as the cause of the proliferation of research on social innovation (Cajaiba-Santana 2014; Phillips et al. 2015). From a general perspective global dilemmas, such as the economic crisis, climate change, energy and resource scarcity, and demographic imbalances, have been recognised as factors negatively affecting society (Moulaert 2009). A less utopian view identifies for instance social exclusion, cultural and environmental deterioration, congestion, accessibility and empowerment as topics of interest for social innovation (Caragliu et al. 2011; Malek and Costa 2015). Thus, the growing challenges in society as well as the need for transition towards sustainability are proliferating the focus on social innovation. Especially urban environments are increasingly experiencing such problems, which are decreasing the quality of life of citizens and tourists as well as limiting sustainable development (Sauer 2012; Dameri 2013).
"...presenting social innovation based on such instrumental view is a teleological mistake: the assumption that because we see a particular outcome to a process we conclude that the process must always have that specific result. This paper argues that this kind of instrumental definition leads to a too narrow view of social innovation. First, because an answer to a social problem is not necessarily a social innovation, even technical innovations might be aimed at solving social problems. Second, because it proposes a material dimension of social innovation (product), what is incoherent with the ontological immateriality of the phenomenon as highlighted by Neumeier [10]: ‘Social innovations are non-material: their material outcomes are solely a supplementary result and they focus not on needs but on asset building’ (p. 55). Hence, social innovations are manifested in changes of attitudes, behaviour, or perceptions, resulting in new social practices. Third, and this is a central aspect stressed in this article, social innovation is about social change and this should be the main characteristic to be put in evidence [10,18]. We are not only talking about changes in the way social agents act and interact with each other, but also changes in the social context in which these actions take place through the creation of new institutions and new social systems" (Cajaiba-Santana, 2014, p.44)
Quotes different studies
Bartels (2012)
The communicative capacity of public professionals and citizens is imperative to the quality of participatory democracy p.15
--> Communicative capacity - the ability the adjust communication to the situation at hand - is of importance to the quality of participatory democracy
--> Quality participatory democracy depends on the process of the communication between professionals and citizens
--> The communicative "in-between", i.e. interaction, encounter, I-Thou, is an ongoing, dynamic and relational process
The research reveals that participatory practise comes down to ongoing processes which draw the communication between public professionals and citizens into dominant patters and limit their ability to the needs of the situation at hand and solve public problems (p.21).
The encounter: That what happens in-between public professionals and citizens (between people) p.22
What public professionals and citizens are able to do and achieve is an emergent product of the relational, situated process through which they interact with each other (Campbell Rawlings & Catlaw, 2011; Stout & Staton, 2011) and the "push ad pull" of concrete situations at hand (Wagenaar & Cook, 2011; Cook & Wagenaar, 2012) p.22
The research concentrated on community participation - the institutions and practises through which residents and pubic professionals are involved in activities and decisions at the neighbourhood level - because policies are usually wide-ranging and ambitious while the actual possibilities for living up to these are heavily dependent on the local socio-political context and everyday practises (p.23)
Theology
About Karl Barth: "For Barth, it is non-human to strive to be on one’s own, apart from others. Experiencing oneself as an “I” in relation to the “thou” constitutes the very human condition. To be human in Barth’s vision, that is, to appropriate in whatever incomplete way the “true man,” is to be in relation with other humans. This insight provides Barth with the foundation for the specifically anthropological side of his theological anthropology. To say “I am human,” for Barth, is to say “I am-in-encounter.” Barth sets up what he calls “encounter” as the basic predicate of human existence. For Barth, encounter is the next conceptual step beyond maintaining that humans, simply by being humans, relate to one another; encounter is the way humans relate to one another as true humanity (Durheim, 2011, p.7-8)
Method
Bartles (2012) Practise illuminating theory (Hummel, 1998): open-ended exploration of a phenomenon in practise to enrich our theoretical understanding (p.23)
Text conference paper 2015 Smart Destination
"In order to explore the factors influencing the smartness of a Smart Tourism Destinations, this paper has been conceived with an exploratory research nature based on case studies. Case studies are here utilised to identify which factors contribute to the development of a Smart City and Smart Tourism Destination.
The case study methodology is often implemented when research is still in its early, formative stage (Benbasat, Goldstein, & Mead, 1987). The Smart City field of research is particularly multidisciplinary and even though scholars have focused on this topic, this field is still rather young. In addition, this area of research is typically characterised by the constant change in innovation and technology. Hence, the case study methodology enables to gain knowledge, and to explore how three established Smart Cities develop their smartness. This study conducts a multiple-case study research as it allows for cross-case analysis and a more general overview of the research results (Bonoma, 1985).
The case studies presented are based on secondary research of existing government, academic, and Internet sources (see table 1). For the analysis of these documents, this study conducts a content analysis for the separate case studies. A coding scheme is developed based on the analysis of secondary research on Smart Cities (Caragliu et al., 2011; Cocchia, 2014; European Parliament, 2014; Lombardi et al., 2012; Nam & Pardo, 2011). The collected data has been summarised for the individual documents and subsequently coded using the coding scheme. This is followed by cross-case examination and within-case examination along with literature review to develop coding clusters and to support external validity."
Article International Journal of Tourism Cities 2016
"Smart tourism is an emerging research topic and needs to be developed by exploring some of the forefront destinations. Therefore, given the exploratory nature of this paper and the contemporary character of the research topic, a case study approach was adopted (Yin, 2009). This approach has frequently been implemented in tourism (Beeton, 2005) when research is still in its early, formative stage (Benbasat et al., 1987). Smartness has only recently gained momentum in different disciplines and is still rather young (Albino et al., 2015; Carvalho, 2015; Meijer and Bolívar, 2015). Adopting the case study approach offers holistic insights regarding the core components of smartness, through the analysis of reports, studies, news articles and other text sensitive documentation. A comprehensive coverage of complementary material is required to explore all aspect of smartness.
Case selection
Smart cities initiated the notion of smart tourism destinations (Buhalis and Amaranggana, 2014). Cities have to deal with a large number of interconnected organisations and technologies to serve citizens and other stakeholders at a large scale. Hence, they are more mature in implementing smartness and thus provide the context for this research. Currently a variety of cities have developed smartness and innovation by developing comprehensive initiatives. To justify the selection of the cases, two international ranking schemes were used. First, the smart city classification by Cohen (2014b) was used to inform case selection since this classification syndicates a variety of global and regional rankings. This selection identified a list of the top ten smart cities. In order to narrow down these cases, the study on smart cities undertaken by the European Union (2014) was also taken into account. This particular study, “Mapping Smart Cities in the EU”, conducted an in-depth analysis of the cities within the EU28 with at least 100,000 residents. A selection of 240 cities was identified as “smart”. After a quantitative analysis of the characteristics and contributions of these cities, six top performing cities where identified, namely: Amsterdam, Barcelona, Copenhagen, Helsinki, Manchester and Vienna. Out of these six, Barcelona, Amsterdam and Helsinki were ranked as the three cities yielding the most innovative smart solutions in Europe and were selected as cases for this research.
Data collection
To collect information about the selected cases, three main databases/research strategies were used to search for relevant documents (i.e. Google, Google Scholar and EBSCO) following a five steps methodology (Denyer and Neely, 2004): key phrase identification; document identification; quality assessment; data extraction; and data analysis. Each step is described in more detail in the following sections.
Within the first step of this systematic process key phrases were identified for the document identification carried out in the second step. The key phrases identified were “Barcelona smart city case study”, “Barcelona smartness concept”, “Barcelona smart city analysis”, “Barcelona smart city strategy”, and “Barcelona smart city initiative”, respectively. The same key phrases were utilised for Amsterdam and Helsinki.
In the second step, the described key phrases were used to identify documents on the selected cases. The identification took place over a three-week period between 24 September and 15 October 2014. Google was used to query the key phrases and the documents presented on the first three result pages were chosen for further selection. Search results from Google, Google Scholar and the EBSCO database were also used to identify further academic sources. The document identification resulted in a wide data collection stemming from existing government reports, academic case studies, online news articles, and smart city project descriptions and presentations. Although the analysis of any case study cannot be fully exhaustive, the majority of the in-depth published documents on the cases researched were included in this study. The third step focused on the quality assessment of the selected documents. Three academic articles were included due to their peer-review assessment. The European Union report, used for the selection of the cases for this research, was the most comprehensive document identified, with an in-depth analysis of Barcelona, Amsterdam and Helsinki. In addition, four smart city projects were included as well as one presentation document, a presentation transcript and one online news article. Commercial documents or reports delivered by technology companies have been excluded to avoid bias. An overview of the various sources used for the empirical research of this study is depicted in Table II.
The fourth step of the data collection concentrated on the data extraction. An iterative thematic content analysis was carried out in which a bottom-up coding scheme was adopted. The identified codes were deduced from the analysed content (Yin, 2009). A three-level coding scheme was used (Bryman and Bell, 2011) and the three selected cases were separately coded. In the first level, a very basic coding was applied in which paragraphs were analysed for the research. Within this phase content describing, for example, the demographics of the cities was excluded from further analysis. The second level comprised a more in-depth approach in which codes such as “innovation”, “collaboration”, “work together” and “human skills” were used to characterise the units of text. After this level 58 codes were deduced from the content on Barcelona, 44 on Amsterdam and 52 on Helsinki.
Data extraction and data analysis were the two intertwined steps within the context of this research. Consequently, the data analysis initiated in the data extraction phase. The third level of coding took a more analytic approach. A cross-case examination (Yin, 2009) of the codes identified in the separate cases on the second level was conducted. Interconnections and differences were identified which provided more compelling and robust outcomes (Gillham, 2000) and consequently 28 codes have been deduced from the analysis. Further engagement with the content and codes identified four main themes, which have been selected as the core components of smartness. The results of this analysis are presented in the following section."