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This paper aims to explore the past and future impacts of automation on family businesses, with a focus on the opportunities for human capital empowerment.

This paper draws upon a contemporary literature search to examine a range of scholarly and practitioner perspectives of the challenges and benefits of automation, exploring the evolvement towards hyperautomation and the empowerment of human capital in family businesses.

Automation, transforming to hyperautomation, general purpose artificial intelligence (AI) and beyond has the possibility of radically improving productivity. Fear of job obsolescence has been present since the birth of modern automation, and whilst some jobs are at risk of redundancy, a net gain towards higher-skilled labour is already evident. Family business leaders must be prepared to react appropriately to the accelerating war for talent by implementing a strategy for human capital empowerment.

This unique paper synthesises developments in automation and proposes a future perspective centred upon the empowerment of human capital in family businesses.

Accounting information is essentially multivariate and the relationships among variables may be difficult to establish. Differing multivariate information presentation methods may impact on the quality of the decisions made by users. Existing studies in this area have given scant attention to differences between individual users, despite earlier suggestions from the second author of this paper that both gender and personality might impact on information processing. This study focuses on the interaction of the decision maker (addressing issues of gender, personality, cognitive style and ability) with the data presentation method (including tables, graphical and pictorial methods) in the management decision making process. The paper reports on experiments conducted with respondents of varying degrees of accounting sophistication, using a failed/non‐failed decision environment. Results provide support for the use of graphical and pictorial methods as means of representing data for this decision task, while also identifying the influence of gender, spatial ability and tolerance of ambiguity. These findings have implications for the matching of information presentation with the characteristics of the decision maker in management decision making.

The purpose of this paper is to examine the education-job match of political science graduates from Slovenia, as well as from selected EU countries, in the context of other disciplines. In the frame of contested theoretical approaches, the implications of matching the knowledge that is acquired during education to the skills that are needed on the job are also examined.

Using the REFlex HEGESCO database, as well as other secondary data, the wider disciplinary and contextual environments are presented. Disciplinary and contextual mapping is followed by binary logistic regression of primary data collected from Slovene political science graduates. Based on the results, the authors determined the validity of certain theoretical premises of human capital, credentialist, and assignment approaches, specifically regarding education-job matching.

In terms of graduate education-job match, the results indicate that the relevance of the sector of employment relates to educational as well as skill match. The results also indicate that matched candidates utilize the skills acquired during the education process to a greater degree, which adds weight to the assignment theory's presumption. The effect of formal credentials is relevant, because graduates with Bologna degrees, despite having attended programs with virtually identical curricula at the same institution, are significantly less matched when compared to non-Bologna graduates. Accordingly, the effect of the change to the structure of the system of higher education (HE), which is amplified by the period effect of the economic crisis, implies a serious change to graduates’ opportunity structure.

The study should motivate a re-examination of the teleological purpose of the study by professional associations in the state. It should also motivate the adjustment of the study programs to the new conditions graduates face and strengthen the educator-employer relationship to make the latter cognizant about the study programs and the skills of graduates. In addition, the study should provide grounds for a critical discussion about the implications of governmental austerity measures on the public sector.

The paper provides new insights into the early careers of political scientists and social scientists at large. It also offers early evidence on the effect of the Bologna's HE reform and indications about the early career achievements in a crisis-struck post-communist country.

While the terms theatre and drama are often used synonymously, they are marked by distinct differences. Drama is concerned with the literature of the theatre, the written basis for theatrical presentations. Theatre refers to the art of presentation, and includes the creations of the playwright, the designer, the architect, and the actor.

A variety of phenomena such as world wide web, social or business networks, interactions are modelled by various kinds of networks (such as the scale free or preferential attachment networks). However, due to the model‐specific requirements one may want to rewire the network to optimize the communication among the various nodes while not overloading the number of channels (i.e. preserving the number of edges). The purpose of this paper is to present a formal framework for this problem and to examine a family of local search strategies to cope with it.

This is mostly theoretical work. The authors use rigorous mathematical framework to set‐up the model and then we prove some interesting theorems about it which pertain to various local search algorithms that work by rerouting the network.

This paper proves that in cases when every pair of nodes is sampled with non‐zero probability then the algorithm is ergodic in the sense that it samples every possible network on the specified set of nodes and having a specified number of edges with nonzero probability. Incidentally, the ergodicity result led to the construction of a class of algorithms for sampling graphs with a specified number of edges over a specified set of nodes uniformly at random and opened some other challenging and important questions for future considerations.

The measure‐theoretic framework presented in the current paper is original and rather general. It allows one to obtain new points of view on the problem.

The purpose of this paper is to provide a review of the issues related to cluster analysis, one of the most important and primitive activities of human beings, and of the advances made in recent years.

The paper investigates the clustering algorithms rooted in machine learning, computer science, statistics, and computational intelligence.

The paper reviews the basic issues of cluster analysis and discusses the recent advances of clustering algorithms in scalability, robustness, visualization, irregular cluster shape detection, and so on.

The paper presents a comprehensive and systematic survey of cluster analysis and emphasizes its recent efforts in order to meet the challenges caused by the glut of complicated data from a wide variety of communities.