LC 00764

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Research questions

Deze onderzoeksvragen zijn van belang voor dit paper

• What is the role of the encounter for social innovation?

Method

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."