Indicator Problem in Measuring Social Capital: The Relationship between Human Capital Indicators and Social Capital
Ali Erbasi
Department of Management and Organization, Social Sciences Vocational School, Selcuk University, Konya, Turkey
Abstract—The purpose of the present study is examining the relationship between human capital indicators and social capital in reference to indicator problem in measuring social capital. For this purpose, the relationships between some human capital indicators and social capital index values in districts of Konya and Karaman provinces, which were defined as TR52 NUTS 2 Region according to Turkish Statistical Institute, Classification of Regional Units. Since all 31 districts of Konya, and 6 districts of Karaman were involved in the present study, no universe-sample distinctions were made. Data obtained from 37 districts were tested on SPSS 19.0 software package in accordance with the research hypotheses. Pearson Correlation Analysis was used to test the hypotheses. Research findings revealed that, there were statistically significant correlations between highly trained population rate, proportion of dropping out of school to total population, and literacy rate indicators and social capital. No statistically significant correlations were detected between the number of doctors per thousand and social capital. The findings obtained in the present research provide local administrators in the region and academicians studying in the field of intangible capital with important results.
Index Terms—social capital, human capital, indicator
Cite: Ali Erbasi, "Indicator Problem in Measuring Social Capital: the Relationship between Human Capital Indicators and Social Capital," Journal of Advanced Management Science, Vol. 4, No. 5, pp. 361-367, September 2016. doi: 10.12720/joams.4.5.361-367
Index Terms—social capital, human capital, indicator
Cite: Ali Erbasi, "Indicator Problem in Measuring Social Capital: the Relationship between Human Capital Indicators and Social Capital," Journal of Advanced Management Science, Vol. 4, No. 5, pp. 361-367, September 2016. doi: 10.12720/joams.4.5.361-367
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