Public administrations are organizations whose mission is to serve the interests of society by providing efficient and sustainable services. Much of the information received from public administrations uses social media due to their versatility and capacity to reach a large number of citizens. Among them, Twitter is the most widely used, especially to disseminate messages with a high social content. This type of messages falls within the discipline of social marketing. However, when public administrations use Twitter for social marketing communication, it is not known which factors are the most decisive to achieve the social objective for which they are issued. This article provides an answer to this question, using the Analytic Network Process Multicriteria method to determine which factors matter and how they are interrelated when issuing social marketing messages through Twitter. The result of this research reveals that from the 22 factors analyzed, the most influential from a social marketing point of view are the average age of population, the existence of a strategic communication plan, the number of tweets and the average number of tweets per day, the number of followers, retweets and mentions, as well as the efficiency of the account.

One of the most frequently used inventory policies is the order-point, order-up-to-level (s, S) system. In this system, the inventory is continuously reviewed and a replenishment request is placed whenever the inventory position drops to or below the order point, s. The variable replenishment order quantity and the variable replenishment cycle characterize the system by the use of complex mathematical computations. Different methodological approaches diminish the mathematical complexity by neglecting the undershoots, i.e., the quantity that the inventory position is below the order point when it is reached. In this paper, we conceptually and empirically analyse the bias that neglecting the undershoots introduces into the estimation of the fill rate. After that, we suggest a new methodology developed under a data-driven perspective that uses a state-dependent parameter algorithm to correct such a bias. As a result, we propose two new methods, one parametric and the other nonparametric, to enhance the fill rate estimate. Both methods, named analytics fill rate methods, remove the bias that neglecting the undershoots introduces and are used to illustrate the practical implications of this hypothesis on the performance and design of the (s, S) system. This research is developed in a lost sales context with simulated stochastic and i.i.d. discrete demands as well as actual sales data.

Purpose: One challenge in inventory control models is to know the stock available at the beginning of the cycle to satisfy future demands, i.e. to know the on-hand stock levels at order delivery. For inventory managers, this knowledge is necessary to both determine service levels and establish the control parameters of the inventory policy. However, the calculation of on-hand stock levels when unfilled demand is lost is mathematically complex since on-hand stock cannot be negative by definition. The purpose of this paper is to propose a new approach to estimate on-hand stock levels when the inventory is periodically reviewed and unfilled demand is lost, through the use of fuzzy techniques.Design/methodology/approach: This paper applies fuzzy set techniques for the calculation of the on-hand stock levels at order delivery in the lost sales context, based on the uncertainty that real demand introduces. To this end, we propose a new approach based on modeling the on-hand stock as an imprecise Markov chain using possibility functions, which reduces significantly the computational effort required to obtain the on-hand stock levels.Findings: To illustrate the performance of the proposed method, two experiments are carried out. The first experiment shows that the proposed fuzzy method correctly calculates on-hand stock levels with insignificant deviation with respect the exact vector. Additionally, the results illustrate that the fuzzy method simplifies the calculation and highly reduces the computational efforts. The second experiment shows the performance of the fuzzy method when it is used to estimate service levels by means of the fill rate. The results show that the proposed method accurately estimates the fill rate with average deviations lower than 0.00015.Practical implications: Knowing the on-hand stock vector is important for inventory managers to establish the control parameters of the system, i.e. to determine the minimum base stock level, S, that guarantees the achievement of a target service level. The difficulty of this estimation is that to obtain the on-hand stock vector in a lost sales context requires a huge computational effort and it is difficult to implement in companies’ information systems. However, the proposed fuzzy method leads to a very accurate calculation of the on-hand stock vector significantly reducing the computational costs, which makes this method easily implementable in practical environments.Originality/value: Fuzzy set techniques have been widely used in inventory models to introduce the uncertainty of demand, costs or shortage. However, to the best of our knowledge, this is the first paper which deals directly with fuzzy estimation of on-hand levels.

Actualmente las organizaciones públicas están potenciando el uso de las redes sociales como herramienta de comunicación de marketing social, con el fin de influir en el comportamiento de los individuos y lograr un bienestar social. Metodología: Se ha utilizado la técnica multicriterio AHP (Analytical Hierarchical Process) aplicada a cuatro perfiles de Twitter de fuerzas y cuerpos de seguridad de distintos ámbitos territoriales. De este modo, se ha representado el modelo como una jerarquía, se han identificado las variables explicativas del buen uso de las redes sociales como instrumento de comunicación y se han agrupado en clústeres de variables. Posteriormente, se han ponderado tanto las variables como los clústeres mediante el juicio de un experto en comunicación. Resultados: De los clústeres de variables explicativas utilizados para el estudio, “C3. Impacto de la cuenta” se ha revelado como el más importante para el experto. En cuanto a las dimensiones, la más relevante es “Número de seguidores”. Por otra parte, los resultados muestran la eficacia en la comunicación de las cuentas de Twitter de los diferentes cuerpos y fuerzas de seguridad analizados. Conclusiones: Este trabajo aporta información de gran utilidad práctica, pues se identifican cuáles son las variables fundamentales para conseguir un uso eficiente en las redes sociales y conseguir el objetivo propuesto de influir en los ciudadanos para lograr un bienestar conjunto. Por otra parte, se abren nuevas líneas de investigación que pueden complementar los resultados obtenidos.

El objetivo de este trabajo es presentar una metodología cuantitativa utilizada para la evaluación de la competencia transversal Trabajo en equipo y Liderazgo en la asignatura Gestión de Recursos Humanos de Grado en Gestión y Administración Pública de la Universitat Politècnica de València. Las profesoras han recogido datos de la evaluación por pares y de la autoevaluación de los estudiantes. Con esto, han realizado una evaluación cuantitativa a través de la aplicación de un coeficiente de adecuación que ha permitido comprobar qué estudiantes se han ajustado mejor al nivel requerido por las profesoras en los distintos ítems que componen la competencia transversal, tanto desde el punto de vista de los compañeros como de uno mismo. En adición, se ha comprobado en qué modo el trabajo en equipo ha reforzado el trabajo individual de cada estudiante. El método de evaluación presentado en este artículo es de uso universal, pues se puede adaptar a cualquier otra asignatura de cualquier otro curso, título, o nivel educativo, incluso no universitario. El conocimiento de los resultados permite orientar mejor el desempeño docente a los resultados de aprendizaje de los estudiantes mediante el trabajo en equipo.