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In the original history of the socialist calculation debate (e.g., Bergson, 1948), Oscar Lange proved that bureaucrats can find the equivalent of equilibrium prices through trial and error. In the revised history of this debate (e.g., Caldwell, 1997; Lavoie, 1985), Lange proposed an erroneous solution to the calculation problem. Dynamic entrepreneurial rivalry moves prices toward equilibrium. Lange and other “Market Socialists” allies thought only in terms of a static competitive market equilibrium that excludes the role entrepreneurs play in adjusting prices.

Because that the crime in a wide way impacts the life of the people in the big metropolis, researchers have treated the question from several angles. The purpose of the paper, under the umbrella of operational research, is to develop a model of the ordering of police strategies, in the fight against crime in general, according to a certain criminal demand.

For the construction of the impact matrix of the strategies under the reduction of crime rates, considering a portfolio of crimes, a questionnaire applied to specialists was used. In a second moment, defined the criteria and strategies to be ordered, the multicriteria ELECTRE IV method was used, which with the help of the J-Electre software emulated the systematized data in the impact matrix and produced the final ordering of the most efficient strategies, in the fight against crime, in the perception of decision-makers.

As a result, the research revealed that policing strategies directed at solving specific crimes are the most effective in the perception of decision-makers after the emulation of data with the ELECTRE IV method.

As research implications, it can be inferred that the use of multicriteria methods in the modeling of problems in the area of public security can contribute to rationalization of the use of the means available in the fight against crime in large cities. The research showed that it is possible to use customized policing strategies to a certain reality.

The method presented in this research is directly related to the major strategies: problem-oriented policing and hot spot policing. This method allows public safety managers to consider the possibility of combining different law enforcement strategies in each context. In this sense, the use of the multiple-criteria decision analysis (MCDA) (ELECTRE IV) method allows the evaluation of a large set of alternatives according to a set of established criteria, speeding up the process and reducing subjectivity, allowing the manager to analyze several scenarios with greater clarity and impartiality and choosing an alternative that best solves the proposed problem. The expected result is the rationalization of the available means applied in the search for the reduction of crime rates.

The customization of policing strategies, according to criminal demands, implies the efficient way to reduce criminal charges. Reducing criminal rates enables the development of the local economy, tourism and the quality of life of people by exercising their freedom to the full.

The originality lies in filling a gap in the literature with the elaboration of the impact matrix of policing strategies in reducing criminal indices, and in their associated use in ordering strategies through a multicriteria method.

The purpose of this paper is to develop a methodology for knowledge discovery in emergency response service databases based on police occurrence reports, generating information to help law enforcement agencies plan actions to investigate and combat criminal activities.

The developed model employs a methodology for knowledge discovery involving text mining techniques and uses latent Dirichlet allocation (LDA) with collapsed Gibbs sampling to obtain topics related to crime.

The method used in this study enabled identification of the most common crimes that occurred in the period from 1 January to 31 December of 2016. An analysis of the identified topics reaffirmed that crimes do not occur in a linear manner in a given locality. In this study, 40 per cent of the crimes identified in integrated public safety area 5, or AISP 5 (the historic centre of the city of RJ), had no correlation with AISP 19 (Copacabana – RJ), and 33 per cent of the crimes in AISP 19 were not identified in AISP 5.

The collected data represent the social dynamics of neighbourhoods in the central and southern zones of the city of Rio de Janeiro during the specific period from January 2013 to December 2016. This limitation implies that the results cannot be generalised to areas with different characteristics.

The developed methodology contributes in a complementary manner to the identification of criminal practices and their characteristics based on police occurrence reports stored in emergency response databases. The generated knowledge enables law enforcement experts to assess, reformulate and construct differentiated strategies for combating crimes in a given locality.

The production of knowledge from the emergency service database contributes to the government integrating information with other databases, thus enabling the improvement of strategies to combat local crime. The proposed model contributes to research on big data, on the innovation aspect and on decision support, for it breaks with a paradigm of analysis of criminal information.

The originality of the study lies in the integration of text mining techniques and LDA to detect crimes in a given locality on the basis of the criminal occurrence reports stored in emergency response service databases.

The insecurity generated, today in various parts of the planet, by the various conflicts that arise in the violence in large cities, has motivated the academy to research the solutions and strategies adopted by local governments in the fight against crime. The volume of data generated by several universities over the past 50 years has increased exponentially. Consequently, researchers struggle to process essential data in today’s competitive world. The aim of this study is to explore and provide an overview of the studies carried out in the field of action to combat crime in different countries.

The Web of Science and Scopus databases were searched for publications from January 1945 to September 3, 2020 on the topic of policing strategies in titles, abstracts and keywords. References were analyzed using the R bibliometrix package, and abstracts were analyzed using latent Dirichlet allocation (LDA) with collapsed Gibbs sampling for topics related to policing and related subjects.

As a result of the research, this paper can assert that in the last 50 years, 3,361 authors have produced 2,085 documents on the theme of policing strategy and related subjects in 58 countries. Scientific production in this area grows at a rate of 5.10 per year. The USA is the leading country in publications with 42.58%, followed by the UK with 8.39% and Canada with 4.07%. As for journals, the highlight is Policing, Policing and Society and Police Quarterly, which account for more than 15.44% of all indexed literature. Regarding the authors, the highlight is Weisburd and Braga. As a result, the LDA grouped the latent words in the articles analyzed by themes studied and presented the list of articles by themes. The thematic map identifies the following themes as basic research subjects: community policing, problem-oriented policing, predictive policing, fear of crime and social control.

As the main implication between the combination of the bibliometric analysis method with the probabilistic topic modelling, is the emergence of a primordial step in the systematic literature review process, as this method allows to explore and group a large volume of data. Another practical implication that is intended is to provide the beginning researcher or any other reader with a panoramic view of the main authors who study the themes that impact police activity in any city in the world, which are the countries and reference centers of the study on the subject and, finally, the evolution of the main themes researched in the police area.

The value of these studies is summarized in the presentation of an overview on the theme in the last 50 years, offering the opportunity for other researchers to use this research as a starting point for other analyses.

The purpose of this paper is to develop a method for the discovery of knowledge in emergency response databases based on police incident reports, generating information that identifies local criminal demands that allow the selection of the appropriate policing strategies portfolio to solve the problem.

The developed model uses a methodology for the discovery of knowledge involving text mining techniques using Latent Dirichlet Allocation (LDA) integrated with the ELECTRE I multicriteria method.

The developed method allowed the identification of the most common criminal demands that occurred from January 1 to December 31, 2016, in the policing areas studied. One of the crimes does not occur homogeneously in a particular locality. In this study, it was initially observed that 40 per cent of the crimes identified in the Integrated Public Safety Area 5, or AISP-5, (historical city center of RJ) had no correlation with AISP-19 (Copacabana - RJ), and 33 per cent of crimes crimes in AISP-19 were not identified in AISP-5. This finding guided the second part of the method that sought to identify which portfolio of policing strategies would be most appropriate for the identified demands. In this sense, using the ELECTRE I method, eight different scenarios were constructed where it can be identified that for each specific criminal demand set there is a set of policing strategies to be applied.

The collected data represent the social dynamics of neighbourhoods in the central and southern zones of the city of Rio de Janeiro during the specific period from January 2013 to December 2016. This limitation implies that the results cannot be generalised to areas with different characteristics.

The developed methodology contributes in a complementary way to the identification of criminal practices and their characteristics based on reports of police occurrences stored in emergency response databases. The knowledge generated through the identification of criminal demands allows law enforcement decision makers to evaluate and choose among the available policing strategies, which best suit the reality they study, and produce the reduction of criminal indices.

It is possible to infer that by choosing appropriate strategies to combat local crime, the proposed model will increase the population’s sense of safety through an effective reduction in crime.

The originality of the study lies in the integration of text mining techniques, LDA and the ELECTRE I method for detecting crime in a given location based on crime reports stored in emergency response databases, enabling identification and choice, from customized policing strategies to particular criminal demands.

After decades of successful, if not always smooth, working relationships with regional library networks in the United States, Online Computer Library Center (OCLC), Inc., with approval of amended articles of incorporation in 2008, it implemented significant changes in how it would price its products and services and how it would govern itself. These changes proved to have profound impact on the networks, precipitating the merger of many and the dissolution of some. This chapter describes the results of many interviews with past and present leaders of OCLC and the regional networks, both existing and defunct, and other knowledgeable individuals. The contrasting opinions on how the changes came about and their consequences offer a perspective on the evolution and then decline of some of the powerful consortial relationships of the last four decades.

This paper aims to critically examine the applicability of disclosure‐based regulation in a pre‐emerging securities market.

The paper presents, by using archival data, an analysis of prerequisites for the usefulness of the disclosure philosophy making reference to some Asian securities markets with special reference to the contemporary experiences of the Bangladesh securities market.

The paper concludes that the disclosure philosophy itself is not a panacea, an effective disclosure regime requires a certain level of structural and infrastructural development of the market, and that a particular securities market should follow a paternalistic merit regulation until the attainment of that progress.

This paper contributes to the understanding of effectiveness of the disclosure philosophy for the regulation of securities markets from the perspective of investor protection.

The safety assessment of engineering structures under repeated variable dynamic loads such as seismic and wind loads can be considered as a dynamic shakedown problem. This paper aims to extend the stress compensation method (SCM) to perform lower bound dynamic shakedown analysis of engineering structures and a double-closed-loop iterative algorithm is proposed to solve the shakedown load.

The construction of the dynamic load vertexes is carried out to represent the loading domain of a structure under both dynamic and quasi-static load. The SCM is extended to perform lower bound dynamic shakedown analysis of engineering structures, which constructs the self-equilibrium stress field by a series of direct iteration computations. The self-equilibrium stress field is not only related to the amplitude of the repeated variable load but also related to its frequency. A novel double-closed-loop iterative algorithm is presented to calculate the dynamic shakedown load multiplier. The inner-loop iteration is to construct the self-equilibrated residual stress field based on the certain shakedown load multiplier. The outer-loop iteration is to update the dynamic shakedown load multiplier. With different combinations of dynamic load vertexes, a dynamic shakedown load domain could be obtained.

Three-dimensional examples are presented to verify the applicability and accuracy of the SCM in dynamic shakedown analysis. The example of cantilever beam under harmonic dynamic load with different frequency shows the validity of the dynamic load vertex construction method. The shakedown domain of the elbow structure varies with the frequency under the dynamic approach. When the frequency is around the resonance frequency of the structure, the area of shakedown domain would be significantly reduced.

In this study, the dynamical response of structure is treated as perfect elastoplastic. The current analysis does not account for effects such as large deformation, stochastic external load and nonlinear vibration conditions which will inevitably be encountered and affect the load capacity.

This study provides a direct method for the dynamical shakedown analysis of engineering structures under repeated variable dynamic load.