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This paper presents an actor-based conceptualization of the increasing oscillatory pattern of prison overcrowding in Colombia. The research proposes a dynamic hypothesis that explains that unintended behavioural pattern as a result of delayed balance feedback loops shaped by decision-making processes of actors that intend to control crime. This system matches a well-known systemic archetype that explains those persistent oscillations. The paper also introduces a simulation model for testing that dynamic hypothesis and for delivering concrete courses of action. This work illustrates the relevance for policymakers to understand the dynamic complexity of social systems as the outcome of the agency of actors who take action to defend their own interests. Such actions ultimately form a complex web of interactions that drive the performance of such systems with unintended consequences. In particular, the construction of explicit models provides better chances of devising policies that consider the system-level implications of those interactions.

This work uses system dynamics modelling. First, the paper presents a conceptual model anchored in operational thinking, which refers to the identification of actors and decisions, and the manner in which those decisions ultimately build the respective social system in which the oscillatory pattern emerges. Second, it identifies key feedback structures that result from those chains of decisions. Finally, the paper introduces a simulation model for suggesting policy implications for decisionmakers.

The increasing oscillatory pattern that prison overcrowding in Colombia has displayed over the last 20 years is the outcome of a wide variety of laws that increase sanctions on criminal conducts, a phenomenon known as “legislative inflation”. Such reactions against crime are propelled and sustained by society and policymakers as the result of static and linear thinking that simply delivers “more punishment” of crime – harsher legislation and longer prison terms – which ultimately boosts long-term prison overcrowding and further cycles of crime control and overcrowding. Such actions create permanent negative feedback loops that involve various material and information delays, which – coupled with the reinforcing feedback loops – explain the previously mentioned behavioural pattern. Through a system dynamics simulation model, this paper tests and explains the proposed dynamic hypothesis and shows how policymakers can enhance and develop their dynamic understanding to explore and design effective policies intended to tackle prison overcrowding.

This paper presents a practical and concrete case that bridges the fields of criminal policy and prison management through systems thinking. It uses the case of prison overcrowding in Colombia to demonstrate the relevance of incorporating systemic thinking into the cognitive portfolio of policymakers if they aspire to improve complex systems.

Criminal policy and prison management are different fields that typically belong to different traditions (law and criminal psychology for the former, public administration for the latter). The work presented here bridges those perspectives under a single engineering and systemic perspective that answers questions in both fields and serves as a unifying framework for designing more coherent criminal policies that meet the practical requirements and restrictions that prison management implies.

The purpose of this paper is to analyze how sustainability was operationalized in the Spanish universities through plans and actions that contribute actively to the achievement of the sustainable development goals (SDGs).

A systematic search and content analysis served to examine information available on websites belonging to the 76 universities listed in the Conference of Rectors of the Spanish Universities (CRUE).

The participation of Spanish universities on initiatives focused on sustainability is very limited, highlighting the negligible role of private institutions in which topics like sustainability and the 2030 Agenda/SDGs were scarcely addressed.

The study outlines the actual extent of the inclusion of sustainability in particular co-curricular actions toward the SDGs in the CRUE. The findings enable to define a long-term sustainability road map for the Spanish university system.

This paper aims to investigate the political involvement of a corporate foundation (CF) though CSR under two perspectives: CF managers and the sponsor firm managers.

A single case with a Brazilian CF was conducted. Interviews with sponsor firms and foundations managers were combined with firms’ sustainability reports data and CF’s website information.

It was found that CF acts as an ambassador and can be a source of political legitimacy for their sponsor firm. They intermediate in governance challenges as the goals and working style of the CF, firms and municipalities can be sometimes antagonistic.

The authors could not reach the municipalities officials and their perception of the Public Management Program (PMP).

The PMP creates personal and organizational relationships with public officials, a resource that can be employed to impact the political strategies of the sponsor firm.

The authors also show how CF’s may help managers to deal with the typical Brazilian peculiarity of policy discontinuity in local governments.

This case study sheds light a new phenomenon: CF’s support on public management. It adds to the CSR and corporate political activities literature, the role of foundations as ambassadors of the relationship between the firm, government and society. They are not only filling gaps left by the State but are also dealing with local governments administrative deficiencies.

Curve fitting from unordered noisy point samples is needed for surface reconstruction in many applications. In the literature, several approaches have been proposed to solve this problem. However, previous works lack formal characterization of the curve fitting problem and assessment on the effect of several parameters (i.e. scalars that remain constant in the optimization problem), such as control points number (m), curve degree (b), knot vector composition (U), norm degree (k), and point sample size (r) on the optimized curve reconstruction measured by a penalty function (f). The paper aims to discuss these issues.

A numerical sensitivity analysis of the effect of m, b, k and r on f and a characterization of the fitting procedure from the mathematical viewpoint are performed. Also, the spectral (frequency) analysis of the derivative of the angle of the fitted curve with respect to u as a means to detect spurious curls and peaks is explored.

It is more effective to find optimum values for m than k or b in order to obtain good results because the topological faithfulness of the resulting curve strongly depends on m. Furthermore, when an exaggerate number of control points is used the resulting curve presents spurious curls and peaks. The authors were able to detect the presence of such spurious features with spectral analysis. Also, the authors found that the method for curve fitting is robust to significant decimation of the point sample.

The authors have addressed important voids of previous works in this field. The authors determined, among the curve fitting parameters m, b and k, which of them influenced the most the results and how. Also, the authors performed a characterization of the curve fitting problem from the optimization perspective. And finally, the authors devised a method to detect spurious features in the fitting curve.

This paper provides a methodology to select the important tuning parameters in a formal manner.

Up to the best of the knowledge, no previous work has been conducted in the formal mathematical evaluation of the sensitivity of the goodness of the curve fit with respect to different possible tuning parameters (curve degree, number of control points, norm degree, etc.).

The purpose of this paper is to analyse the role that different financial sources and financial specialization have on private research and development (R&D) activity in OECD countries.

The authors developed several panel regressions choosing as a final model a two-way random effects regression to understand which funding sources are related to the R&D expenditure, and how financial specialization has links to the private portion of R&D aggregated expenditure. The authors include data from the years 2000 to 2016 for OECD countries.

The results reinforce the critical role that stock markets have in enhancing private R&D and that bond markets have an inverse relationship with private R&D national expenditures. The authors do not find evidence of a link between bank sources and private R&D. Specialized financial systems (banking or market) support innovation in a better way than a mixed arrangement of those two systems.

The findings of this study have considerable policy implications. Policymakers need to be aware of these results, given that some variables related to financial markets, seems to boost the inputs for R&D. In the long term, this could be a signal that national and regional systems of innovation need a broad view of the factors hampering scientific activity, and also a signal that there are other ways to impact the results of the complex innovation activity through the development of stronger financial systems backing up national systems of innovation.

The authors found that the long discussion about the financial system that a country has to choose to enhance growth with R&D&I may have been misleading the public policy. The findings show that rather than a bank or a stock market financial system, economies looking to boost R&D&I, must specialize in one of the two systems, deepen these and generate the appropriate policies to promote science, technology and innovation using those financial markets.