Population growth and economic development

The paper deals with the relationship between the population growth and economic development in Yugoslavia and its republics, covering the period after the Second World War. Yugoslavia is a developing country with a specific demographic and economic structure which makes her unique in Europe. Its territory is comprised of both relatively developed regions where demographic transition is over, and underdeveloped regions with high natural increase of population where the demographic transition is only just beginning. Correlation and regression methods were used to quantify this relationship. The economic development and structural changes are discussed, relating to human factor. An adequate population policy through family planning is stressed as important in obtaining an increased return to scale with a more positive role of demographic factor.     

Reflective Photobooth – a way to visualise,and challenge perceptions and representations of distanced social groups

Taken-for-granted knowledge about people from other social groups is a key challenge for overcoming stereotypes. This article describes a novel arts-based research method to visualise participants’ frames of distanced social groups and aims to trigger reflections among them. The Reflective Photobooth invites participants to dress up as members of distanced social groups, stage a scene, produce pictures, answer prompting questions, and discuss their visualisations. We argue that the artistic re-enactment that underlies the visualisation process can attract diverse groups of participants to engage with research topics, create places for the articulation of critical statements against existing societal clichés and stereotypical media representations, and trigger reflections among participants about taken-for-granted knowledge. The method was tested within the Frame-a-Farmer project, in which the social distance between consumers and food producers in modern agrifood systems was addressed. Results indicate that despite the method bearing some risks and facing some challenges, three promising areas of future application could be identified: (i) raising awareness among large groups of people, (ii) collecting stories or topical vignettes, and (iii) deconstructing taken-for-granted knowledge and societal clichés.     

Two preprocessing algorithms for climate time series

We propose two preprocessing algorithms suitable for climate time series. The first algorithm detects outliers based on an autoregressive cost update mechanism. The second one is based on the wavelet transform, a method from pattern recognition. In order to benchmark the algorithms'' performance we compare them to existing methods based on a synthetic data set. Eventually, for exemplary purposes, the proposed methods are applied to a data set of high-frequent temperature measurements from Novi Sad, Serbia. The results show that both methods together form a powerful tool for signal preprocessing: In case of solitary outliers the autoregressive cost update mechanism prevails, whereas the wavelet-based mechanism is the method of choice in the presence of multiple consecutive outliers.     

On MLEs of the parameters of a modified Weibull distribution based on record values

The modified Weibull distribution can be used quite effectively to model complex data from mechanical engineering or survival analysis studies that posses a monotonic or a bathtub-shape hazard rate. In this paper, we study the MLEs of the parameters of a modified Weibull distribution model in the presence of upper kth record values. The existence and uniqueness of the MLEs are proven in this case. Real data analysis is performed for illustrative purposes.     

The relationship between reputation,employer branding and corporate social responsibility

Reputation management requires coordination between internal understanding and external expectations (Cornelissen, 2011). The focus of this study were external expectations of potential employees. The main goal of the study was to contribute to the understanding of corporate reputation and its connections with perceived corporate social responsibility and employer brands. All three concepts were investigated amongst 550 senior college business students. The units of analysis were top twenty national organizations, rated according to a syndicated study on employer attractiveness. The results show that students assign good reputation to those organizations that are perceived as socially responsible and with a good employer brand. Reputation, at least according to our results, seems to be the umbrella concept that encompasses both perceived corporate social responsibility and perceived employer brands. Organizations that develop different strategies, policies and practices with regards to socially responsible behavior and nurturing employer brands have higher levels of perceived reputation among students. Additionally, students' perceptions and position on the list of the most attractive employers is consistent.     

Welfare State and Social Enterprise in Transition: Evidence from Serbia

This paper analyses welfare regime changes in Serbia and their impact on social enterprise development in the last two decades. We cover the period of significant transition-related reforms within the welfare state, with important implications on the position of these enterprises. Using data gathered from the qualitative field research, our study shows that there are two broad groups of factors that are important for development of the new generation of social enterprises, those that emerged in the last decade with an idea to foster entrepreneurial spirit and expanded into new domains other than those providing assistance to the marginalized groups. First, their decision to enter the social economy sector still depends on the environment created by the state. Secondly, their sustainability is affected by the factors typically found in any other enterprise of comparable scale like business skills, capacity to form networks and partner with relevant stakeholders.     

Estimation of flood frequencies from data sets with outliers using mixed distribution functions

In this paper the estimation of high return period quantiles of the flood peak and volume in the Kolubara River basin are carried out. Estimation of flood frequencies is carried out on a data set containing high outliers which are identified by the Rosner’s test. Simultaneously, low outliers are determined by the multiple Grubbs–Beck. The next step involved the usage of the mixed distribution functions applied to a data set from three populations: floods with low outliers, normal floods and floods with high outliers. The contribution of the data set with low outliers is neglected, since it should underestimate the flood quantiles with large return periods. Consequently, the best fitted mixed distribution from the applied types (EV1, GEV, P3 and LP3) was determined by using the minimum standard error of fit.     

Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples

This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained.