Social enterprises are gaining great importance, since they can efficiently solve social problems and help reduce unemployment. Thus, it is important to discover how social entrepreneurial intention (SEI) can be enhanced. In this paper, a model of the impact of entrepreneurial education (EE) on SEI is formulated by relying on the human capital theory. It is hypothesized that EE acts on SEI directly as well as indirectly by increasing the perceived importance of social entrepreneurship (PISE). The model was evaluated on a sample of 400 students from the Republic of Serbia, and Bosnia and Herzegovina. The analysis was conducted using partial least squares structural equation modelling (PLS-SEM). In addition, a multigroup analysis was conducted in order to establish differences in the proposed relationship between countries. The obtained results indicate a positive impact of EE on SEI and a positive impact of PISE on SEI in both observed countries. The influence of EE on PISE, as well as the indirect effect of EE on SEI through PISE, was confirmed in Serbia, but not in Bosnia and Herzegovina. The results of this paper justify further government investment in the development of educational programs. This paper also gives recommendations to universities, educators, and researchers.

The authors discuss why the current conceptual base of project management research and practice continues to attract criticism since it does not adequately address the complexity that leads to software-project failure. To do so, the study explores systems thinking and artificial neural networks to shed light on complexity in software-project behavior using nonlinear functional relationships between critical success factors and project success to utilize their connectedness as an approach in order to create project-outcome prediction models. The artificial neural networks were used to create two project-outcome prediction models: one for a binary classification task to discriminate failed from successful projects using a multi-input-single-output configuration and one for a multi-task binary classification to discriminate success from failure in multiple project-success dimensions using a multi-input multi-output configuration. The results yielded high-performance values for a binary classification task, performed to predict overall project success, and slightly lower performance values for the multi-task binary classification, which was also performed to predict success in project-success dimensions. It was found that the nonlinear behavior of critical success factors may be used to create prediction models, by embedding equifinality and connectedness constructs that prove to be useful to understand projects as complex, multi-loop, and nonlinear systems. Further research is needed to investigate the causality between critical success factors in order to explore the possible propagation of critical success factors within a project system network and its implications on project success.

This paper explores how entrepreneurial education and entrepreneurial environment affect entrepreneurial readiness (ER) of students from Science, Technology, Engineering, Mathematics (STEM), and business, i.e., economics and management (E&M) studies. Moreover, it examines how the combination of the aforementioned factors affect the difference in ER between STEM and E&M students. The evaluation is performed on the sample of 595 university students. The results show that two sources of entrepreneurial learning, entrepreneurial experience in the family environment and entrepreneurial education at university, combined with the field of studies represent significant factors that predetermine students’ ER. To be able to reach the highest level of ER, the combination of having entrepreneurial environment and entrepreneurial education is crucial for both E&M and STEM students. However, since E&M students show higher level of ER, the paper emphasises the importance of fostering systemic entrepreneurial education among STEM students.

Research Question: This paper explores the potential for technology entrepreneurship development at the country level through the creation of a new composite index. Motivation: Motivation for this paper arises from the fact there is a lack of the composite indices used exclusively for technology management as identified by Jovanovic et al. (2017). Technology indices are mostly used as important components of other composite indices used for tracking a country performance from the perspective of other global phenomena (e.g. competitiveness and innovativeness). The novelty of this paper reflects in the proposed Technology Entrepreneurship Development Potential (TED-pot) index which has multiple significances. It could serve as a help for policy makers in creating national policies; other companies and countries looking for the adequate environment to invest in technology entrepreneurship projects; academics who benefit from a new country-level view on technology entrepreneurship, especially ICT entrepreneurship. Idea: The idea of the paper was to create the TED-pot index to enable the cross-countries comparisons and examine whether the potential of Serbia lies in its entrepreneurial ICT sector. Data: Four indicators included in the created index are measured by the World Bank. The index is applied on six ex-Yugoslav countries and the EU for the period 2009-2014. All the data is collected from the World Bank database. Tools: The final index value is obtained by using the simple weighted function with equal weights. The overall TED-pot has been built upon the equal weighting of the two created pillars: ICT potential (ICT-pot) and Entrepreneurial potential (E-pot). The values for each pillar are calculated by the same procedure, through the simple mean of certain indicators. Findings: According to the calculated TED-pot values, Serbia stands out as a country with the greatest potential for technology entrepreneurship development in the region. Analysing individual pillars, ICT-pot indicates Serbia has very strong ICT sector, far ahead of other countries in the region, while the E-pot values show there is a space for administration to ease and speed up the process of starting new businesses in Serbia. This is a pilot research and the first presentation of the created index, which calls for further investigation. Contribution: This paper expands exiting research related to the country-level measurement in the field of technology management and entrepreneurship, especially focusing on ICT entrepreneurship development.

This chapter focuses on composite indices used in Technology Management (TM). It provides a critical comparative analysis of 5 indices, summarizes their structure, weighting process and emphasizes technology related components of indices as well as their advantages and disadvantages. The second part of the chapter examines the ranks of OECD and BRICS countries for Global Competitiveness Index (GCI), Global Innovativeness Index (GII) and Global Entrepreneurship Index (GEI), and further, we analyzed the correlations of GCI and GII pillars and clusters with the final ranks of countries. The research proved the presence and the importance of TM in the construction of the selected indices, but also identified that there is a lack of composite indicators used exclusively for TM performance which are measured globally by official institutions.