MAPPING CLUSTERS IN CENTRAL AND EASTERN EUROPEAN REGIONS BASED ON FDI, REMITTANCES AND EMPLOYMENT – A SPATIAL STATISTICS GROUPING ANALYSIS

Cristina LINCARU

Dr, FeRSA, Department of Labour Market, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania

cristina.lincaru@yahoo.de

ORCID ID: 0000-0001-6596-1820

Speranța PÎRCIOG

Dr Scientific Director, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania

pirciog@incsmps.ro

ORCID ID: 0000-0003-0215-038X

Abstract

Central and Eastern European (CEE) and Visegrad countries transform and develop in different spatial patterns in a global economy. Host labour markets benefit directly from Foreign Direct Investment (FDI) inward flows through jobs creation or increased productivity. On the other side, the labour force rises its geographical mobility and benefits from jobs in FDI’s source countries, sending personal remittances. Global integration marks that the “receipts of remittances have become an important and stable source of funds that exceeds FDI” (indexmundi.com). Are the CEE /Visegrad countries similar concerning their spatiotemporal pattern of FDI inflows? These countries are identical in their development model, described by the coordinates of FDI, remittances and Employment? We applied for 35 European countries from 2013-to 2019 the Similarity check –Grouping Analysis ARC GIS-tool from the Spatially Constrained Multivariate Clustering (Spatial Statistics) family. The FDI inflow as input proves to be more inertial, according to the categories set by EuroVoc. Simultaneously, the FDI inward as output (employment growth or labour productivity growth) differentiate CEE countries next to labour/ human capital mobility as personnel remittances in more heterogeneous categories.

In conclusion, for CEE countries, capital mobility and labour & human capital mobility create different development patterns globally. Therefore, it is not enough to build policies to attract capital (FDI) and attract high human capital.

Keywords: CEE, inward FDI rates, personal remittances receipt as GDP rate, employment rate, Similarity check –Grouping Analysis, spatial statistics

JEL classification: C23, F21, F22, F24, J21, J24, O52

 pp. 67-104

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EXPLORING THE COMPONENTS OF THE INTELLECTUAL CAPITAL IN TROSO WEAVING SMEs

Ngatindriatun

Departement of Management Science, Bina Nusantara University, Jakarta, Indonesia

ngatindriatun@yahoo.com

Didik Sofian Haryadi

STEKOM PAT, Semarang, Indonesia

didikshse@rocketmail.com

Abstract

This study aims to test and analyze the effects of intellectual capital to competitive advantage and company’s performance at Troso traditional weaving business. The variables in this research are human capital as exogenous variable and structural capital, customer capital, competitive advantage, and company performance as the endogenous ones. The subject of the study was 200 sample consisting 572 craftmen. This research applies structural equation modelling. The result of SEM analysis fulfills Goodness of Fit Index criteria, i.e. chi-square value = 432.543, significance probability = 0.000, RMSEA = 0.070, CMIN/DF = 1.966, TLI = 0.885, CFI = 0.900, GFI = 0.849 and AGFI = 0.810. Based on the research result, it can be concluded that human capital, structural capital, and customer capital influence on competitive advantage and company performance.

Keywords: Intellectual Capital, Competitive Advantage, Company Performance

JEL classification: A, M12, J24

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EXPLORING THE COMPONENTS OF THE INTELLECTUAL CAPITAL IN TROSO WEAVING SMEs

NGATINDRIATUN

Departement of Management Science, Bina Nusantara University, Jakarta, Indonesia

ngatindriatun@yahoo.com

Didik Sofian HARYADI

STEKOM PAT, Semarang, Indonesia

didikshse@rocketmail.com

Abstract

This study aims to test and analyze the effects of intellectual capital to competitive advantage and company’s performance at Troso traditional weaving business. The variables in this research are human capital as exogenous variable and structural capital, customer capital, competitive advantage, and company performance as the endogenous ones. The subject of the study was 200 sample consisting 572 craftmen. This research applies structural equation modelling. The result of SEM analysis fulfills Goodness of Fit Index criteria, i.e. chi-square value = 432.543, significance probability = 0.000, RMSEA = 0.070, CMIN/DF = 1.966, TLI = 0.885, CFI = 0.900, GFI = 0.849 and AGFI = 0.810. Based on the research result, it can be concluded that human capital, structural capital, and customer capital influence on competitive advantage and company performance.

Keywords: Intellectual Capital, Competitive Advantage, Company Performance

JEL classification: A, M12, J24
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