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Scientific paper - Original scientific paper
Using location-based Social Networks for optimal placement of tourist facilities: Zagreb case study
In: Međunarodni znanstveni simpozij Gospodarstvo istočne Hrvatske – jučer, danas, sutra. Osijek: Ekonomski fakultet Sveučilišta Josipa Jurja Strossmayera u Osijeku, 2020. pp. 167-181. urn:nbn:hr:112:263371
Đokić, Kristian; Štavlić, Katarina; Potnik Galić, Katarina

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Đokić, K., Štavlić, K. & Potnik Galić, K. (2020). Using location-based Social Networks for optimal placement of tourist facilities: Zagreb case study. Međunarodni znanstveni simpozij Gospodarstvo istočne Hrvatske – jučer, danas, sutra (pp. 167-181). Osijek: Ekonomski fakultet Sveučilišta Josipa Jurja Strossmayera u Osijeku. Retrieved from https://urn.nsk.hr/urn:nbn:hr:112:263371

Đokić, Kristian, et al. "Using location-based Social Networks for optimal placement of tourist facilities: Zagreb case study." Međunarodni znanstveni simpozij Gospodarstvo istočne Hrvatske – jučer, danas, sutra, Ekonomski fakultet Sveučilišta Josipa Jurja Strossmayera u Osijeku, 2020, pp. 167-181. https://urn.nsk.hr/urn:nbn:hr:112:263371

Đokić, Kristian, Katarina Štavlić and Katarina Potnik Galić. "Using location-based Social Networks for optimal placement of tourist facilities: Zagreb case study." In Međunarodni znanstveni simpozij Gospodarstvo istočne Hrvatske – jučer, danas, sutra, 167-181. Osijek: Ekonomski fakultet Sveučilišta Josipa Jurja Strossmayera u Osijeku, 2020. Accessed 2024 September 01. https://urn.nsk.hr/urn:nbn:hr:112:263371

Đokić, K., Štavlić, K. and Potnik Galić, K. (2020) 'Using location-based Social Networks for optimal placement of tourist facilities: Zagreb case study', Međunarodni znanstveni simpozij Gospodarstvo istočne Hrvatske – jučer, danas, sutra, Ekonomski fakultet Sveučilišta Josipa Jurja Strossmayera u Osijeku, Osijek, pp. 167-181. Available at: https://urn.nsk.hr/urn:nbn:hr:112:263371 (Accessed 01 September 2024)

Đokić K, Štavlić K, Potnik Galić K. Using location-based Social Networks for optimal placement of tourist facilities: Zagreb case study. Međunarodni znanstveni simpozij Gospodarstvo istočne Hrvatske – jučer, danas, sutra. Osijek: Ekonomski fakultet Sveučilišta Josipa Jurja Strossmayera u Osijeku; 2020. Pp. 167-181. [cited 2024 September 01] Available at: https://urn.nsk.hr/urn:nbn:hr:112:263371

K. Đokić, K. Štavlić and K. Potnik Galić, "Using location-based Social Networks for optimal placement of tourist facilities: Zagreb case study", Međunarodni znanstveni simpozij Gospodarstvo istočne Hrvatske – jučer, danas, sutra Osijek: Ekonomski fakultet Sveučilišta Josipa Jurja Strossmayera u Osijeku, 2020. [Online] Available at: https://urn.nsk.hr/urn:nbn:hr:112:263371 [Accessed: 01 September 2024]

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Metadata
Title (english)Using location-based Social Networks for optimal placement of tourist facilities: Zagreb case study
AuthorKristian Đokić
AuthorKatarina Štavlić
AuthorKatarina Potnik Galić
Author's institutionPolytehnic in Pozega
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Economics
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Information and Communication Sciences
Abstract (english)
In the last decade, the advance of services and social networks that can store location coordinates and ratings by visitors has had a significant impact on how potential visitors choose their visit destination. The destination can be a landmark, a city, a restaurant, a hotel, etc., and people visiting the destination can be tourists or locals. Also, the data from these services can be used to analyse the location before potential investment in the tourist facility by an investor. Clustering unsupervised machine learning algorithms can be used for that analysis, combining individual municipalities of a city into clusters that have similar properties, making potential investors informed about municipality's properties. In this paper, the main goal is to propose an optimal placement model based on the available information. A prerequisite for this is the analysis of location-based service that can be used to make decisions about the location of a restaurant or bar, and the amount of information available at these service for the city of Zagreb. The proposed model is based on a k-means algorithm that belongs to unsupervised machine learning algorithms. The result of the analysis is the list of municipalities in the city of Zagreb divided into clusters with similar properties. The municipalities are divided into six clusters and that division brings objective knowledge to the potential investor. These results can be used as a basis for decision- making or as a test of expert recommendation. The proposed model can be used for other purposes, depending on the area of interest and the amount of data available on the service.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Publication titleMeđunarodni znanstveni simpozij Gospodarstvo istočne Hrvatske – jučer, danas, sutra
Numberingpp. 167-181
ISBN978-953-253-164-0
p-ISSN1848-9559
URN:NBNurn:nbn:hr:112:263371
Publication2020
ConferenceTitle: 9th International Scientific Symposium Region, Entrepreneurship, Development (RED 2020)
Location: Osijek, Croatia
Start date: 2020-06-04
End date: 2020-06-05
Assembly type: Lecture
Type of resourceText
PublisherEkonomski fakultet Sveučilišta Josipa Jurja Strossmayera u Osijeku
Publishing placeOsijek
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-05-06 10:28:21