| Title | Is sustainable aligning with smartness in transport domain?-marketing perspective of smart city rankings |
|---|---|
| ID_Doc | 36238 |
| Authors | Bruska, A; Boichuk, N |
| Title | Is sustainable aligning with smartness in transport domain?-marketing perspective of smart city rankings |
| Year | 2022 |
| Published | Scientific Journals Of The Maritime University Of Szczecin-Zeszyty Naukowe Akademii Morskiej W Szczecinie, 72, 144 |
| Abstract | Rising awareness of sustainable development challenges, along with the quest for optimization of the everyday functioning of the city, motivate many urban authorities to search for promising concepts and solutions. One of these is the smart city concept, which has gained governors of cities' attention for little more than ten years. An object of research and development, it is still a distinctive feature for the cities that adopt this concept. City marketers use such distinction towards a large palette of beneficiaries of the city. At the same time, it deploys some traits suggesting synergies between the implementation of smart city solutions and sustainable develop-ment goals.The main objective of our work was to verify if the relationship between these aspects (smartness and sustain -ability of a transportation) in smart city rankings exists and, if that is true, what impact it has on marketing com-munication of the city comprised in such rankings. To fulfill this goal, we answered such research questions as: what place sustainability criteria in smart city rankings have occurred, how is the transport represented in these criteria, what use graded cities make of their presence in such competition, and which perspective dominates (if any) in daily marketing communication activities of the city.To provide such an analysis, we considered the criteria used to rank the cities to find the places that accorded to sustainable ones. We examined the marketing use of the results of such rankings, referring to the official web -sites and social media of selected cities (random selection from the total population of 174 cities comprised). The sources used to provide the data in natural language, and their analysis proceeded with methods and tools used in NLP (natural language processing), which are accessible through CLARIN.EU infrastructure. The results determine that cities can be classed into different groups, accordingly to their sustainability/smartness pending, and ability to use accorded ranks in marketing context. |
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