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The purpose of this study is modelling of a problem of policing strategy order using a multicriteria method.

For the construction of the impact matrix 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 PROMETHEE II method was used, which with the help of the Visual PROMETHEE software, emulated the systematised 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, this research revealed that radio patrol, when used in a non-randomised manner, is the most effective policing strategy in reducing the 18 criminal demands studied in the perception of decision makers after data emulation with the PROMETHEE II method.

As research implications, it can be inferred that the use of multicriteria methods in the modelling of problems in public security area can contribute to the rationalisation of use of the available means in the fight against crime in large cities. This research showed that it is possible to use customised policing strategies to absolute reality.

The practical impact of this research lies in optimising the resources available to law enforcement agencies in the fight against crime in general.

It can be inferred that by choosing appropriate strategies to combat local crime, there is a direct implication in optimising the resources that the government makes available to police agencies. This optimisation allows pressure reduction under the public budget for more features. The model for choosing more effective strategies contributes to local crimes decrease, increasing the sense of the population security.

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. This study contributed to applied police intelligence.

The authors aimed to identify the opinions of young adult consumers regarding food processing companies’ (FPCs) credibility in terms of food safety (FS).

The authors surveyed Generation Z (GenZ) consumers. The authors assessed the reliability of the research questionnaire using Cronbach’s alpha statistics. The authors used descriptive statistics and one-way ANOVA analysis of variance in the data analysis to determine intergroup variability. The authors performed statistical analyses using IBM SPSS Statistics. 27.

The most valued determinants for consumers were competence and skills, and the most valued family members’ opinions on FS, followed by experts’ opinions. FS concerns are more associated with FPCs than with farmers. The ethics of conduct and moral responsibility play an important role in assessing the FPCs’ credibility.

The questionnaire did not focus on specific food industries, such as fruit and vegetables, fish, meat, dairy, etc. In the future, a similar survey on producers’ credibility should consider the issue of FS risks associated with the specifics of a particular industry.

The authors proposed a set of factors that may determine young adult consumers’ perception of the FPCs’ credibility, which they may use for research within other consumer groups.

This paper aims to provide empirical evidence for using the prospect theory (PT) basic assumptions in the Argentine context. Mainly, this study analysed the financial decision-making process in students of the economic-administrative academic area of two universities, one public and one private, in Córdoba.

The analysis methodology included (1) the descriptive statistical analysis to identify the presence of the certainty, reflection and isolation effects; (2) the construction of a set of indicators on the application of the PT; (3) the chi-squared independence test, to determine if the decisions made are independent of the degree course taken; (4) the non-parametric Kruskal–Wallis test, to determine if the decisions made by individuals vary according to the semesters taken or students' levels of progress; and (5) the non-parametric Mann–Whitney test, to determine if there are differences between the decisions made by men and women.

The empirical results provided evidence on the effects of certainty, reflection and isolation in both universities, concluding that the study participants make financial decisions in situations of uncertainty based more on PT than on expected utility theory.

This study contributes to the empirical evidence in a different Latin-American context, confirming that individuals make financial decisions based on the PT independently of their degree course, semester, level of advance, gender or the kind of university where they belong (public or private).

This paper examines the role of institution in the combating crime in India. This study also assesses institutions for controlling property crime in India in the post-reform era.

Crime and socio-economic data are taken from National Crime Record Bureau and the Reserve Bank of India, respectively. Twenty major Indian states are selected for the study purpose for the period of 1994–2019. Fixed effect panel data technique is used for analysis purpose.

Property crime rate declines with economic growth, while it increases with financial development. Findings of fiscal policy instruments are different. Own tax is positively associated with property crime in India, while non-tax fiscal instruments such as fine, penalty, and so on, are inversely related to it. Property crime rate is inversely related to institutional factors like charge sheet and conviction rate.

Further research is needed for other crimes in India. State-level data are used here for analysis purpose; however, spatial or cluster analysis techniques might provide more insights for combating crimes in India.

This study suggests that economic growth and fiscal instrument along with institutional development are essential to control property crime in India.

Government should take steps to improve the law-and-order system to control property crime across states.

Impact of non-tax fiscal instrument reduces property crime while that of own tax is increases it in India. These findings are unique and added certain insight in the study. Institutional roles are captured its performances like charge sheet and convict rate, which are significantly reduce property crime in Indian states. Least square dummy variable model is applied to capture individual state effects.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0063

This paper describes the principles behind some of the search method possibilities for online chemical databases. In a subsequent paper, the actual methods available will be described.

The finance literature extensively documents the abnormal positive returns of unseasoned initial public offerings (IPOs) in the early trading. Neuberger and LaChapelle (1983), McDonald and Fisher (1972), Neuberger and Hammond (1974), Reilly (1977), Logue (1973), Ibbotson (1975), Ibbotson and Jaffe (1975), Ritter (1984), Miller and Reilly (1987), and Ibbotson, Sindelar and Ritter (1988) are but a few studies providing convincing evidence of initial price volatility in IPOs which, after some period of time, tends to level off. Some IPO studies, particularly Neuberger and LaChapelle (1983), Logue (1973), and Friend (1967), intentionally ignore institutional IPOs. Logue (1973) states that banking issues create a downward pricing bias because the market has already accurately priced the assets of financial institutions. Alli, Yau and Yung (1994) provided evidence that banking IPOs enjoyed significantly less positive abnormal returns in the early trading than a control sample of industrial firms. This study examines the early stock price movements of the 32 non‐US banking equities issued on the New York Stock Exchange (NYSE) from January 1986 through May 2001 and finds that virtually no underpricing exists in the early trading for those issues – a vast deviation from the results of most IPO and ADR event studies, but a strong indication that banking IPOs do create a downward pricing bias when considered in IPO studies with securities from different industries. All new foreign equity issues in this study are traded as American Depository Receipts (ADRs) except the Canadian stocks.

This study aims to investigate the relationship between financial inclusion and the business cycle.

Regression methodology is used to analyze the association between financial inclusion and the business cycle.

Using regression estimation, the findings reveal that the level of savings and the number of active formal account ownership are pro-cyclical with fluctuations in the business cycle. Also, savings by adults particularly for women and poor people declines during recessionary periods while the number of active formal account ownership declines for the adult population especially for women during recessionary periods. The findings also reveal that not all indicators of financial inclusion are pro-cyclical with fluctuating business cycles.

The implication of this observed pro-cyclical effect is that individuals and households will exit the formal financial sector during a recession, as banks become unwilling to lend money to individuals and households during bad times and this will lead to financial exclusion and vice versa. Policymakers seeking to increase the level of financial inclusion in their countries should focus on the timing of financial inclusion policies along the business cycle as the findings suggest that it might be more difficult to achieve financial inclusion objectives during recessions or periods of economic downturns.

The current debate on financial inclusion pays little attention to whether financial inclusion is pro-cyclical with the fluctuating business cycle. This study explores the association between financial inclusion and the business cycle.

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.