This paper analyses the Serbian socio-economic spatial differentiation via a purely quantitative approach. In Serbia, huge development disparities between north and south, urban and rural as well as central and peripheral areas are obvious. Getting to the bottom of these spatial differences is one of the fundamental scientific and planning challenges of the region. This question of unevenly distributed living conditions is examined on the basis of factor analyses of secondary statistical data of the Serbian municipalities. The intention thereby was to identify the distribution of regional or spatial inequality by correlating an amount of 25 reliable variables. Combining the spheres of population structure, economy, employment, infrastructure, pre-school education and medical care an overall Index of Socio-economic Pressure is proposed to detect patterns of regional development on the Serbian territory.
Supplier selection is an integral part of supply chain management (SCM). It plays a prominent role in the purchasing activity of manufacturing and trading companies. Evaluation of vendors and procurement planning requires simultaneous consideration of tangible and intangible decision factors, some of which may conflict. A large body of analytical and intuitive methods has been proposed to trade off conflicting aspects of realism and optimize the selection process. In the large companies the fields of decision makers’ (DMs) expertise are highly distributed and DMs’ authorities are unequal. On the other hand, the decision components and their interactions are very complex. These facts restrict the effectiveness of using the existing methods in practice. The authors present a multicriteria decision analysis (MCDA) method which facilitates making supplier selection decisions by the distributed groups of experts and improves quality of the order allocation decisions. A numerical example is presented and applicability of the proposed algorithm is demonstrated in the Raiffeisen Westfalen Mitte, eG in Germany.
To investigate the interrater reliability of stroboscopy evaluations assessed using Poburka's Stroboscopy Evaluation Rating Form (SERF).
Single-factor experiment with repeated measures on the same element.
Evaluations of nine experts pertaining to 68 stroboscopy recordings and 16 SERF variables were analyzed. For the 14 SERF variables possessing interval scale level, interrater reliability was investigated using the intraclass correlations for absolute agreement (ICC-a) and consistency (ICC-c). ICCs-c were computed for both original values and values standardized with respect to raters' means and standard deviations (ipsative values). For the two nominally scaled SERF variables, "vertical level" and "glottal closure" interrater reliability was investigated using kappa coefficients.
For evaluations of single raters, ICCs-a ranged from 0.32 to 0.71, ICCs-c for original values from 0.41 to 0.72, and ICCs-c for ipsative values from 0.43 to 0.72. For mean evaluations of two raters, the corresponding values were 0.48 to 0.83 for ICCs-a, 0.58 to 0.84 for ICCs-c for original values, and 0.60 to 0.84 for ICCs-c for ipsative values. The interval scale variables with the lowest interrater reliabilities were phase closure, phase symmetry, and regularity. The kappa coefficients for vertical level and glottal closure were 0.15 and 0.38, respectively.
The interrater reliabilities for vertical level, glottal closure, phase closure, phase symmetry, and regularity are so low that these variables should not be assessed via stroboscopy. For the remaining variables, adequate reliability can be obtained by aggregating evaluations from at least two raters.