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This article investigates subject-related research metrics from the most popular scientometrics platforms with the capability of citation count. Quantitative analyses have been carried out to determine the most- to the least-cited subject areas to indicate the most active and dynamic fields in research. Subject areas are classified based on statistical analyses and the number of citations received in the period of search. Numerous articles were analyzed from top-ranked journals in all research fields covered by SCImago journal classification. A comprehensive data set was generated in 27 research subject areas, including 313 subject categories and 81 high-ranked journals. Results showed that the highest number of citations were related to the sciences and science-related subject areas. The subject areas of computer science and mathematics had the lowest research metrics and the smallest number of highly cited publications. Web of Science performed better than Scopus for subject-related evaluations. Analysis of frequency data showed that Google Scholar cited fewer papers for low-cited publications than did Scopus or Web of Science. For highly cited publications, however, Google Scholar was found to have better performance. Web of Science showed the best consistency in citation coverage in most of the investigated subject areas. [ABSTRACT FROM AUTHOR]

In this paper we explore the hypothesis that constrained uses of imagination are crucial to economic modeling. We propose a theoretical framework to develop this thesis through a number of specific hypotheses that we test and refine through six new, representative case studies. Our ultimate goal is to develop a philosophical account that is practice oriented and informed by empirical evidence. To do this, we deploy an abductive reasoning strategy. We start from a robust set of hypotheses and leave space for the generation of further hypotheses and theoretical claims based on the qualitative analysis of new empirical data. [ABSTRACT FROM AUTHOR]

The paper highlights the importance and relevance of introducing economic studies to primary schools. The research aimed to investigate the appropriate age, environment, type, and composition of presentation for introducing combined economic knowledge. The 190 students participating in the research were students from three primary schools in Hungary from 10 classes. Given the fact that in the case of all of the significant results, a sufficient effect size could be measured, and furthermore, the relevant test value was very high, it is unambiguously proven that the size of the sample (n = 190) that was used for the examination was sufficient. The results suggest that teaching economic and financial knowledge through accounting and making lectures interactive using special tools of positive education is critical to stimulating children’s interest. Eighty percent of the students in the study liked the combined and interactive lecture. Another goal was to investigate whether those that liked the presentation would perform better on the related knowledge test, which proved to be the case. In the two target groups, students in grade 6 outperformed students in grade 3 on the test. An investigation of gender performance is also included in the research. Findings suggest that the respective education may appropriately be developed based on the close relationship between mathematics and accounting. The lectures can be adapted according to any national or international accounting standards (IFRS, etc.) and can be taught in an online classroom as well. The lectures aim to develop children’s independent problem-solving skills so they can adapt the information to their own lives and financial situations. The paper fills a gap in the research by describing a successful attempt to complex economic literacy.JEL Classification codeA29, M21, M41

The scale of tourism has continued to expand in recent years, and many associated activities cause damage to the natural environment. The tourism, economy and natural environment constitute a system: destruction of the natural environment reduces the value of tourism and a lack of tourism affects the development of the economy. To explore the relationship between the tourism, economy and natural environment, and to explore possibilities for sustainable development, this paper takes Hangzhou, a tourist city in China, as a research object. An analysis of time series data is carried out. First, the tourism, economy and natural environment subsystems are constructed by extracting time series data acquired between 2010 and 2020. Second, a tourism evaluation model with coupled economic and natural environment data is constructed and the coupling degree and coupling coordination level in Hangzhou are evaluated. Third, the time series of each subsystem and the coupling coordination level of the whole system are analyzed. Finally, an optimization strategy is proposed for the coupled coordinated development of the tourism, economy and natural environment in Hangzhou. A key result is that the tertiary industry represented by tourism has become the main source of local income. Hangzhou's tourism coupling coordination level has changed from slight disorder in 2010 to good in 2020. It is also found that the COVID-19 pandemic has become a major factor restricting the development of tourism. Before the outbreak of COVID-19, Hangzhou's tourism industry and economy were synchronized. After the outbreak of COVID-19, both the number of tourists and tourism revenue in Hangzhou fell by nearly 15%.

The importance of the opportunity to learn (OTL) for mathematics achievement has been extensively researched. However, there were still unanswered questions regarding OTL's measurement, analytical level, and relationship with motivational beliefs. To fill in the gaps, we aimed to (1) scrutinize the reliability and validity of OTL, (2) investigate the multilevel nature of OTL, and (3) explore the relationship among OTL, self-efficacy, and mathematics achievement. We used Programme for International Student Assessment (PISA) 2012 data provided by 470,745 15-year-old students from 63 economies. Psychometric analyses and doubly latent multilevel structural equating modeling were conducted. Results indicated that (1) OTL measured by familiarity with mathematical concepts displayed high reliability and validity, (2) student-reported OTL exhibited high reliability at the school-level, (3) OTL significantly predicted achievement both at student- and school-level, and (4) OTL mediated the relationship between self-efficacy and mathematics achievement at student-level. Theoretical and practical implications are discussed. [ABSTRACT FROM AUTHOR]

Why so few women graduate in Economics? We investigate the gender gap among Italian university graduates in Economics between 2010 and 2019. With women's probability of graduating in Economics being 27% lower than men's, the gap is larger than in Business and even STEM. The association between the gender gap and the mathematical content of high school curricula is especially strong in Economics. A triple difference analysis shows that a reform raising the mathematical content of traditionally low math curricula caused an increase in the gender gap, with women's probability of graduating in Economics decreasing by 12 percentage points. [ABSTRACT FROM AUTHOR]

In this paper, we introduce an approach to the management of infectious disease diffusion through the formulation of a controlled compartmental SVIR (susceptible–vaccinated–infected–recovered) model. We consider a cost functional encompassing three distinct yet interconnected dimensions: the social cost, the disease cost, and the vaccination cost. The proposed model addresses the pressing need for optimized strategies in disease containment, incorporating both social control measures and vaccination campaigns. Through the utilization of advanced control theory, we identify optimal control strategies that mitigate disease proliferation while considering the inherent trade-offs among social interventions and vaccination efforts. Finally, we present the results from a simulation-based study employing a numerical implementation of the optimally controlled system through the forward–backward sweep algorithm. The baseline model considered incorporates parameters representative of typical values observed during the recent pandemic outbreak.

The quality of products, maintenance activities, and transportation policies are primary concerns of managers in inventory and production planning problems. Environmental issues and regulations are growing increasingly and they have attracted much attention to achieve sustainable production. Previous authors have conducted a wide range of studies on these problems separately. Regarding the gap of an integrated framework, a sustainable economic production quantity model is formulated by considering preventive maintenance and multiple shipments policy where a portion of produced items is defective. Two particular cases are studied. In Case I, the production period's demand has been satisfied by the items produced in the previous cycle. In Case II, simultaneous production and consumption during the production period are considered and mathematically formulated. An analytical method is presented for solving the models, and a numerical example is discussed for both cases. The comparison of two cases proves that Case II is more beneficial and the overall cost of the inventory system is reduced. Sensitivity analysis of the models is performed, and some insights are derived by changing some of the parameters. [ABSTRACT FROM AUTHOR]

Modeling nonlinear data is a common practice in data science and Machine Learning (ML). It is aberrant for the outcome of a natural process to vary linearly with the values of input variable(s). A robust and easy methodology is needed for accurately and quickly fitting a sampled dataset with a set of covariates, assuming that the sampled data can be a complicated nonlinear function. A novel approach to the estimation of finite population parameter r, which is a linear combination of the population values, is considered in this article under superpopulation setting with known Basis Functions Regression (BFR) models. The problems of subsets selection with a single predictor using an automatic matrix approach and ill-conditioned regression models are discussed. Prediction error variance of the proposed estimator is estimated based on widely used feature selection criteria in ML. Finally, the Expected Squared Prediction Error (ESPE) of the proposed estimator and the expectation of estimated error variance under bootstrapping as well as simulation study with different regularizers are obtained to observe the long-run behavior of the proposed estimator. [ABSTRACT FROM AUTHOR]

AI in finance refers to the applications of AI techniques in financial businesses. This area has attracted attention for decades, with both classic and modern AI techniques applied to increasingly broader areas of finance, economy, and society. In contrast to reviews on discussing the problems, aspects, and opportunities of finance benefited from specific or some new-generation AI and data science (AIDS) techniques or the progress of applying specific techniques to resolving certain financial problems, this review offers a comprehensive and dense landscape of the overwhelming challenges, techniques, and opportunities of AIDS research in finance over the past decades. The challenges of financial businesses and data are first outlined, followed by a comprehensive categorization and a dense overview of the decades of AIDS research in finance. We then structure and illustrate the data-driven analytics and learning of financial businesses and data. A comparison, criticism, and discussion of classic versus modern AIDS techniques for finance follows. Finally, the open issues and opportunities to address future AIDS-empowered finance and finance-motivated AIDS research are discussed. [ABSTRACT FROM AUTHOR]

Our study commemorates this event by presenting a retrospective of the publications related to the use of mathematical tools for the analysis of economic, ecological, and environmental phenomena. We analyzed 1257 scientific publications using bibliometric techniques to examine the most productive and influential authors and their contributions in the economic, ecological, and environmental fields. Co-authorship among the top authors and countries, co-occurrence of the keywords, bibliographic coupling of the documents and authors, and author co-citation were analyzed by applying network analysis techniques using VOSviewer software, identifying the intellectual structure of the research and the collaborative networks in the fields. The results show that mathematics has grown impressively in terms of publication and citation. The contributions come from all over the world, but the majority are from the People's Republic of China and Spain. The results also show themes and trends in the economic, environmental, and ecological fields and a predominant use of mathematical tools in optimization processes in order to rigorously substantiate the decisions of investors and policymakers. Thus, our study offers support for any researcher to understand the current state of the art and develop a comprehensive understanding of journal publications. [ABSTRACT FROM AUTHOR]

The classic notion of a win–win situation has a key flaw in that it cannot always offer the parties equal amounts of winningsbecause each party believes they are winners. In reality, one party may win more than the other. This strategy is not limited to a single product or negotiation; it may be applied to a variety of situations in life. We present a novel way to measure the win–win situation in this paper. The proposed method employs fuzzy logic to create a mathematical model that aids negotiators in quantifying their winning percentages. The model is put to the test on real-life negotiation scenarios such as the Iraqi–Jordanian oil deal and iron ore negotiation (2005–2009), in addition to scenarios from the game of chess. The presented model has proven to be a useful tool in practice and can be easily generalized to be utilized in other domains as well.