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Patterns Of Mainly Tourism Sectors At Local Level By Employee'S Characteristics Using Gis Multivariate Clustering Analysis - Romania Case Study

Author

Listed:
  • Cristina LINCARU

    (Dr, FeRSA, Department of Labour Market, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0001-6596-1820)

  • Speranța PÎRCIOG

    (Dr, Scientific Director, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0003-0215-038X)

  • Draga ATANASIU

    (Senior Researcher, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0002-9695-8592)

  • Cristina STROE

    (Senior Researcher, Department of Social Policies, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0001-8384-6084)

  • Vasilica CIUCĂ

    (Dr, Dr, General Director, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania ORCID ID: 0000-0003-4687-6377)

  • Adriana GRIGORESCU

    (Dr., Department of Public Management, National University of Political Studies and Public Administration, Correspondent Member of Academy of Romanian Scientists, Bucharest, Romania ORCID ID: 0000-0003-4212-6974)

Abstract

The tourism sector, before the Corona Strikes, works as a inclusive development engine for many countries' economies and labour markets. In a global world, with increasing travel opportunities, tourism offers both labours intensive and knowledge-intensive activities, across many economic sectors. Tourism is a spatially dependent sector and also a tradable one. The Methodology for tourism statistics (Eurostat 2014), Tourism Satellite Accounts (TSA 2010) and The International Recommendations for Tourism Statistics 2008 (IRTS 2008) differentiate the "mainly tourism" industries at four digits. We identify the natural cluster by number and pattern, at 3189 local spatial units (NUTS 5) by eight attribute variable employees: gender (male, female), age (youth, adult and aged) and education detained level (low, medium and high). Sectors are detailed at two digits only (H51- Air transport, I55 - Hotels and other accommodation facilities and N79-Activities of tourist agencies and tour operators; other reservation services and tourist assistance). Romanian National Institute of Statistics provides 2011 Census data. We apply the Multivariate Clustering Analysis with K Means algorithm as a Spatial Statistical Tool in Arc Gis Pro 2.3, an unsupervised machine learning an Artificial Intelligence technique, appropriate for Big Data. Clusters resulted illustrates natural hidden patterns of local labour markets pooling in the sense of Urban& Jacobian economies, but also some insight regarding the Morettian externalities sources. These results are useful for Regions Smart Specialisation Strategies development of human resources & talents to increase innovation capabilities and inclusive job creation, but also for a prompt recovery post-Covid Pandemic.

Suggested Citation

  • Cristina LINCARU & Speranța PÎRCIOG & Draga ATANASIU & Cristina STROE & Vasilica CIUCĂ & Adriana GRIGORESCU, 2020. "Patterns Of Mainly Tourism Sectors At Local Level By Employee'S Characteristics Using Gis Multivariate Clustering Analysis - Romania Case Study," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 261-290, June.
    • Handle: RePEc:hrs:journl:v:xii:y:2020:i:1:p:261-290
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    Citations

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    Cited by:

    1. Cristina LINCARU & Speranța PÎRCIOG, 2022. "Mapping Clusters In Central And Eastern European Regions Based On Fdi, Remittances And Employment – A Spatial Statistics Grouping Analysis," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 67-104, June.
    2. Raisa M. IVANOVA & Olga V. SKROBOTOVA & Nadezhda K. MARTYNENKO & Olga S. TAMER & Anatoly V. KOZLOV, 2021. "Environmental Cooperation As A Way Of Developing Eco-Tourism In The Arctic Region," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 69-79, June.
    3. Filipos RUXHO & Christos Ap. LADIAS, 2022. "Increasing Funding For The Regional Industry Of Kosovo And The Impact On Economic Growth," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 117-126, June.
    4. Maria Palazzo & Iza Gigauri & Mirela Clementina Panait & Simona Andreea Apostu & Alfonso Siano, 2022. "Sustainable Tourism Issues in European Countries during the Global Pandemic Crisis," Sustainability, MDPI, vol. 14(7), pages 1-21, March.

    More about this item

    Keywords

    tourism; labour force characteristics; Multivariate Clustering Analysis; local labour markets; regional specialisation; education level; age and gender analysis;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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