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The purpose of this paper is to show the existence results for adapted solutions of infinite horizon doubly reflected backward stochastic differential equations with jumps. These results are applied to get the existence of an optimal impulse control strategy for an infinite horizon impulse control problem.

The main methods used to achieve the objectives of this paper are the properties of the Snell envelope which reduce the problem of impulse control to the existence of a pair of right continuous left limited processes. Some numerical results are provided to show the main results.

In this paper, the authors found the existence of a couple of processes via the notion of doubly reflected backward stochastic differential equation to prove the existence of an optimal strategy which maximizes the expected profit of a firm in an infinite horizon problem with jumps.

In this paper, the authors found new tools in stochastic analysis. They extend to the infinite horizon case the results of doubly reflected backward stochastic differential equations with jumps. Then the authors prove the existence of processes using Envelope Snell to find an optimal strategy of our control problem.

This study is motivated to provide a theoretically informed, data-driven assessment of the consequences associated with the participation of non-human bots in social accountability movements; specifically, the anti-inequality/anti-corporate #OccupyWallStreet conversation stream on Twitter.

A latent Dirichlet allocation (LDA) topic modeling approach as well as XGBoost machine learning algorithms are applied to a dataset of 9.2 million #OccupyWallStreet tweets in order to analyze not only how the speech patterns of bots differ from other participants but also how bot participation impacts the trajectory of the aggregate social accountability conversation stream. The authors consider two research questions: (1) do bots speak differently than non-bots and (2) does bot participation influence the conversation stream.

The results indicate that bots do speak differently than non-bots and that bots exert both weak form and strong form influence. Bots also steadily become more prevalent. At the same time, the results show that bots also learn from and adapt their speaking patterns to emphasize the topics that are important to non-bots and that non-bots continue to speak about their initial topics.

These findings help improve understanding of the consequences of bot participation within social media-based democratic dialogic processes. The analyses also raise important questions about the increasing importance of apparently nonhuman actors within different spheres of social life.

The current study is the first, to the authors’ knowledge, that uses a theoretically informed Big Data approach to simultaneously consider the micro details and aggregate consequences of bot participation within social media-based dialogic social accountability processes.

The retention and success of engineering undergraduates are increasing concern for higher-education institutions. The study of success determinants are initial steps in any remedial initiative targeted to enhance student success and prevent any immature withdrawals. This study provides a comprehensive approach toward the prediction of student academic performance through the lens of the knowledge, attitudes and behavioral skills (KAB) model. The purpose of this paper is to aim to improve the modeling accuracy of students’ performance by introducing two methodologies based on variable selection and dimensionality reduction.

The performance of the proposed methodologies was evaluated using a real data set of ten critical-to-success factors on both attitude and skill-related behaviors of 320 first-year students. The study used two models. In the first model, exploratory factor analysis is used. The second model uses regression model selection. Ridge regression is used as a second step in each model. The efficiency of each model is discussed in the Results section of this paper.

The two methods were powerful in providing small mean-squared errors and hence, in improving the prediction of student performance. The results show that the quality of both methods is sensitive to the size of the reduced model and to the magnitude of the penalization parameter.

First, the survey could have been conducted in two parts; students needed more time than expected to complete it. Second, if the study is to be carried out for second-year students, grades of general engineering courses can be included in the model for better estimation of students’ grade point averages. Third, the study only applies to first-year and second-year students because factors covered are those that are essential for students’ survival through the first few years of study.

The study proposes that vulnerable students could be identified as early as possible in the academic year. These students could be encouraged to engage more in their learning process. Carrying out such measurement at the beginning of the college year can provide professional and college administration with valuable insight on students perception of their own skills and attitudes toward engineering.

This study employs the KAB model as a comprehensive approach to the study of success predictors. The implementation of two new methodologies to improve the prediction accuracy of student success.

The article investigates whether and to what extent outsiderness is gendered in Western Europe, both in terms of its spread and degree. It thus explores which male and female post-Fordist social classes are more exposed to the risk of this phenomenon. It also scrutinizes whether such a gendered characterization has varied over time and across clusters of Western European countries.

Relying on a comparative analysis of the data provided by the European Social Survey (ESS) dataset and comparing two points in time – the early/mid-2000s and the late 2010s – the work provides both a dichotomous and continuous variable of outsiderness, which measure its spread and degree in the female and male workforces of a pooled set of growth models.

The empirical analysis shows that outsiderness is profoundly gendered in Western Europe and thus a feminized social phenomenon. However, the comparative investigation highlights that outsiderness has been genderized in diverse ways across the four growth models. Different patterns of gendered outsiderness can be identified.

The article provides a comparative and diachronic analysis of outsiderness from a gender lens, putting into a mutual dialogue different literature on labour market, and shows that outsiderness represents a key analytical dimension for assessing gender inequalities.

Exploring the influencing factors on urban rail transit (URT) ridership is vital for travel demand estimation and urban resources planning. Among various existing ridership modeling methods, direct demand model with ordinary least square (OLS) multiple regression as a representative has considerable advantages over the traditional four-step model. Nevertheless, OLS multiple regression neglects spatial instability and spatial heterogeneity from the magnitude of the coefficients across the urban area. This paper aims to focus on modeling and analyzing the factors influencing metro ridership at the station level.

This paper constructs two novel direct demand models based on geographically weighted regression (GWR) for modeling influencing factors on metro ridership from a local perspective. One is GWR with globally implemented LASSO for feature selection, and the other one is geographically weighted LASSO (GWL) model, which is GWR with locally implemented LASSO for feature selection.

The results of real-world case study of Shenzhen Metro show that the two local models presented perform better than the traditional global model (OLS) in terms of estimation error of ridership and goodness-of-fit. Additionally, the GWL model results in a better fit than GWR with global LASSO model, indicating that the locally implemented LASSO is more effective for the accurate estimation of Shenzhen metro ridership than global LASSO does. Moreover, the information provided by both two local models regarding the spatial varied elasticities demonstrates the strong spatial interpretability of models and potentials in transport planning.

The main contributions are threefold: the approach is based on spatial models considering spatial autocorrelation of variables, which outperform the traditional global regression model – OLS – in terms of model fitting and spatial explanatory power. GWR with global feature selection using LASSO and GWL is compared through a real-world case study on Shenzhen Metro, that is, the difference between global feature selection and local feature selection is discussed. Network structures as a type of factors are quantified with the measurements in the field of complex network.

This research enables the authors to highlight the importance of proper pricing for retailers. The purpose of this paper is to demonstrate the importance of demand-based pricing, providing empirical results that reveal the validity of this pricing philosophy in the sport retailing industry. In particular, this study has identified the limits of acceptable prices for the products studied, selected the most appropriate method for pricing products suffering from high competition and compared the impact produced on price perceptions according to different retail environments to be able to relate changes in the acceptable prices ranges according to the geographical location of each point of sale, differentiating between rural or urban environment and type of client.

The authors have carried out surveys of 350 customers in each of the three points of sale analysed. Therefore, there are a total of 1,050 interviewees, for the three products analysed. The direct method of acceptable prices setting is developed. In addition, ANOVA and t-test have been carried out to find differences between the three shops.

One main finding is that the acceptable price range is not unique. Each point of sale has one that is distinct because it depends on many factors: the competition, the economic capacity of the closest residents, the location of the point of sale or the ability to attract customers.

The foremost contribution of this paper is to demonstrate empirically how considering the local demand at setting prices would generate larger earnings, even for a small retail chain. The direct method of setting acceptable prices enables us to set the prices according to the demand. The best option is if these prices are above the costs. It can be noted that the prices should be set according to each shop, and a different price used in each point of sale to maximise profits and to adapt to what the typical customer of each shop is willing to pay, despite the products being the same and the points of sale belonging to the same retail chain.

Esta investigación nos permite resaltar la importancia de una fijación de precios adecuada para los minoristas. El objetivo principal de esta investigación es demostrar la importancia de la fijación de precios basada en la demanda, proporcionando resultados empíricos que revelan la validez de esta filosofía de fijación de precios en el sector minorista de productos deportivos. En particular, en este estudio se han identificado los intervalos de precios aceptables para los productos estudiados; se ha seleccionado el método más apropiado para la fijación de precios de productos que sufren alta competencia; y se ha comparado el impacto en las percepciones de precios según el entorno detallista y se han encontrado cambios en los intervalos aceptables de precios en función de la localización geográfica del punto de venta, diferenciando entre entorno rural y urbano, y el tipo de cliente.

Los autores han realizado encuestas a 350 clientes en cada uno de los 3 puntos de venta analizados. Por lo tanto, hay un total de 1050 entrevistados, para los 3 productos analizados. Se desarrolla el método directo de fijación de precios aceptables. Además, se han realizado pruebas ANOVAs y T para encontrar diferencias entre las 3 tiendas.

Un hallazgo principal es que el intervalo de precios aceptable no es único. Cada punto de venta tiene uno distinto porque depende de muchos factores: la competencia, la capacidad económica de los residentes más cercanos, la ubicación del punto de venta o la capacidad de atraer clientes.

La principal contribución de este artículo es demostrar empíricamente cómo considerar la demanda local al establecer precios generaría mayores ganancias, incluso para una pequeña cadena minorista. El método directo de establecer precios aceptables nos permite establecer los precios de acuerdo con la demanda. La mejor opción es si estos precios están por encima de los costos. Se puede observar que los precios deben establecerse de acuerdo con cada tienda, y se debe usar un precio diferente en cada punto de venta para maximizar los beneficios y adaptarse a lo que el cliente típico de cada tienda está dispuesto a pagar. A pesar de que los productos son los mismos y los puntos de venta pertenecientes a la misma cadena minorista.

This study conducts a comparative analysis of the impact of educational mismatch on Spanish wages. This paper aims to focus on the industrial, construction and service sectors at three levels of disaggregation: sector, occupation and gender.

The over-education, required education and under-education (ORU model), was applied to data from the 2018 Spanish Wages Structure Survey conducted by the Spanish National Statistics Institute.

The industrial sector is the one that best manages over-education by offering the highest returns to each year of over-education. It is also the sector that most values the education of women, particularly those in highly qualified positions.

This study compares the wage effects of educational mismatch in the service, industry and construction sectors. Previous literature has ignored the latter sectors in this field of study, but the results of the present study show that the industrial sectors significantly value and remunerates worker education. Therefore, it may be worthy to focus certain economic and social policies on this sector, to contribute to reducing gender wage gaps and gender employment discrimination in the economy.