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Statistics skills are crucial for researchers in psychology, but research suggests that graduate training is insufficient to meet modern quantitative research demands. Consequently, researchers tend to seek training outside of their current or former graduate programme. However, little is known regarding the frequency of use and perceptions surrounding various supplementary statistical resources. This study aimed to investigate how psychology researchers acquire statistical training beyond their graduate programme, how necessary and useful they find various resources, and if there were differences based on student status. The final sample included 280 academic researchers in Canada or the United States. Participants engaged with statistical content more frequently than limited prior research suggests. We found that online resources and quantitative method articles were the most frequently used, statistical consultants had the highest perceived usefulness, and quantitative method articles had high perceived necessity. Student researchers, on average, rated most of the statistical resources as more necessary than researchers with a PhD, with notable differences for online resources and statistical consultants. Usefulness ratings and frequency of use, however, were fairly similar across the groups. Implications and recommendations for students, researchers, instructors and programme administrators are discussed. Data and study materials can be found at https://osf.io/673kj/. Les compétences en statistiques sont essentielles pour les chercheurs en psychologie, mais les recherches suggèrent que la formation universitaire n'est pas suffisante pour répondre aux exigences actuelles de la recherche quantitative. Par conséquent, les chercheurs ont tendance à rechercher une formation en dehors de leur programme universitaire actuel ou antérieur. Or, l'on sait peu de choses sur la fréquence d'utilisation et les perceptions des différentes ressources statistiques supplémentaires. Cette étude visait à examiner comment les chercheurs en psychologie acquièrent une formation en statistiques au-delà de leur programme universitaire, dans quelle mesure ils jugent les différentes ressources nécessaires et utiles, et s'il existe des différences en fonction du statut des étudiants. L'échantillon final comprenait 280 chercheurs universitaires au Canada ou aux États-Unis. Les participants ont utilisé des contenus statistiques plus fréquemment que ne le suggèrent les recherches antérieures limitées. Nous avons constaté que les ressources en ligne et les articles sur les méthodes quantitatives étaient les plus fréquemment utilisés, que les consultants en statistiques étaient perçus comme les plus utiles et que les articles sur les méthodes quantitatives étaient jugés très nécessaires. En moyenne, les étudiants chercheurs ont jugé la plupart des ressources statistiques plus nécessaires que les chercheurs titulaires d'un doctorat, avec des différences notables pour les ressources en ligne et les consultants en statistiques. Toutefois, les notes attribuées à l'utilité et la fréquence d'utilisation étaient assez similaires entre les groupes. Les implications et les recommandations pour les étudiants, les chercheurs, les enseignants et les administrateurs de programmes sont examinées. Les données et les documents d'étude sont disponibles à l'adresse suivante : https://osf.io/673kj/. Public Significance Statement This study found that researchers frequently use various statistics resources, contradicting limited research suggesting poor methodological engagement in psychology. Online resources and research articles were frequently used, while research articles and statistical consultants were considered the most useful statistical resources.

Very large nonlinear unconstrained binary optimization problems arise in a broad array of applications. Several exact or heuristic techniques have proved quite successful for solving many of these problems when the objective function is a quadratic polynomial. However, no similarly efficient methods are available for the higher degree case. Since high degree objectives are becoming increasingly important in certain application areas, such as computer vision, various techniques have been recently developed to reduce the general case to the quadratic one, at the cost of increasing the number of variables by introducing additional auxiliary variables. In this paper we initiate a systematic study of these quadratization approaches. We provide tight lower and upper bounds on the number of auxiliary variables needed in the worst-case for general objective functions, for bounded-degree functions, and for a restricted class of quadratizations. Our upper bounds are constructive, thus yielding new quadratization procedures. Finally, we completely characterize all “minimal” quadratizations of negative monomials.

Different solution methods are developed to solve an inventory routing problem for a perishable product with stochastic demands. The solution methods are empirically compared in terms of average profit, service level, and actual freshness. The benefits of explicitly considering demand uncertainty are quantified. The computational study highlights that in certain situations although a simple ordering policy can achieve very good performance, statistically and economically significant improvements are achieved when using more advanced solution methods. Managerial insights concerning the impact of shelf life and store capacity on profit are also obtained.

We introduce this volume of the Annals of Operations Research that collects updated versions of the invited surveys that appeared in the journal 4OR—A Quarterly Journal of Operations Research.

Parenting during the COVID-19 pandemic is highly challenging, with parents having to meet various demands simultaneously. An increase in adverse childhood experiences (ACEs) has been widely predicted, but empirical evidence is still scarce. This study aimed to (1) generate representative data on pandemic-related stress, parental stress, general stress, parental subjective and mental health, and the occurrence of ACEs; (2) identify risk factors for an increase in ACEs, and (3) provide qualitative data on parents' experiences. A representative survey was conducted in Germany in August 2020 with 1024 parents of underage children (Mage = 41.70, 50.9% female). More than 50% of parents reported being stressed by social distancing and the closure of schools and childcare facilities. Parental stress increased significantly during the pandemic (d = 0.21). Subgroups of parents also reported very high levels of depressive symptoms (12.3%) and anxiety (9.7%). Up to one-third of the sample reported ACEs in the child's lifetime. In this group, 29.1% reported an increase in children witnessing domestic violence during the pandemic, and 42.2% an increase verbal emotional abuse. These families were characterized by higher parental stress, job losses, and younger parent and child age. Positive aspects of the pandemic related primarily to personal or family life (e.g. slower pace of life, increase in family time). While some parents coped well, a particularly negative pattern was observed in a subgroup of families that experienced an increase in ACEs. Parental stress emerged as important target point for interventions addressing the negative sequelae of the pandemic.

A patrolling strategy that defines fare inspection frequencies on a proof-of-payment transportation system is operationally useful to the transit authority when there is a mechanism for its practical implementation. This study addresses the operational implementation of a fare inspection patrolling strategy under an in-station selective inspection policy using an unpredictable patrolling schedule, where the transit authority select a patrolling schedule each day with some probability. The challenge is to determine the set of patrolling schedules and their respective probabilities of being selected whose systematic day-to-day application matches the inspection frequencies that inhibit the action of opportunistic passengers in the medium term. A Stackelberg game approach is used to represent the hierarchical decision making process between the transit authority and opportunistic passengers. The heterogeneity of opportunistic passengers’ decisions to evade fare payment is taken into account. Numerical experiments show that a joint strategy-schedule approach provides good-quality unpredictable patrolling schedules with respect to the optimality gap for large-scale networks.

Distributors are faced with loading constraints in their route planning, e.g.,multi-dimensional packing constraints, unloading sequence constraints, stability constraints and axle weight limits. Ignoring these constraints impairs planning and induces last-minute changes resulting in additional costs. Developing vehicle routing models incorporating loading constraints is critical to more efficient route planning. The last couple of years has seen a huge increase of contributions to this field of research with almost 60 % of these being published after 2009. Our contribution is twofold. First, we overview the recent developments in the literature on all vehicle types in which loading constraints play a key role (trucks, airplanes, ships, and automated guided vehicles), using a state-of-the-art classification scheme to identify the loading constraints considered in each article. Second, we identify research gaps and opportunities for future research.

We investigate a novel database of 10,217 extreme operational losses from the Italian bank UniCredit. Our goal is to shed light on the dependence between the severity distribution of these losses and a set of macroeconomic, financial, and firm-specific factors. To do so, we use generalized Pareto regression techniques, where both the scale and shape parameters are assumed to be functions of these explanatory variables. We perform the selection of the relevant covariates with a state-of-the-art penalized-likelihood estimation procedure relying on L₁-penalty terms. A simulation study indicates that this approach efficiently selects covariates of interest and tackles spurious regression issues encountered when dealing with integrated time series. Lastly, we illustrate the impact of different economic scenarios on the requested capital for operational risk. Our results have important implications in terms of risk management and regulatory policy.

Urban parcel delivery is increasingly restricted by regulations limiting access to certain heavy or high emitting vehicles to reduce emissions and noise pollution in cities. Cargo bikes represent an alternative solution that enables deliveries with low environmental impact, but they may represent a higher economic cost and come with constraints like battery autonomy or small loading capacity. As a transport scheme relying on bikes for the last miles with fewer externalities, it is regarded as an environmentally friendly choice, and economic sustainability is assessed. This paper aims to present the environmental and economic aspects of different delivery means of transport in European urban areas. Life cycle assessment (LCA) methodology is selected to analyse the environmental impact of several vehicles, allowing us to quantify the emissions according to the loading factor. The electricity mix is an important parameter and makes the results vary according to the country studied. For the economic aspect, the cost price allows us to quantify the operational cost of each means of transport. A trade-off can thus be made between the two.

The main objective of this paper is to propose a tool for measuring the productivity and performance gaps across a set of Decision Making Units for monitoring their evolution and analyzing their components over time. To do this, we use the approach proposed by Aparicio and Santín (Eur J Oper Res 267(1):227–235, 2018) which is grounded on a base-group base-period productivity index and Data Envelopment Analysis. Additionally, we propose a new index for measuring the performance gap between two or more groups of production units and its decomposition in effectiveness gap and outcome possibility set gap. As an empirical illustration of the approach, we focus our attention on the educational sector. In particular, we analyze six Latin American countries over time. For this purpose, we rely on OECD–PISA data aggregated at school level. Over the period 2006–2018, performance and productivity followed very different paths in each country showing that the correlation between school performance and productivity is very low. Therefore, we suggest that the simultaneous analysis of performance and productivity gaps together with their evolution over time is a must in order to benchmark countries and monitor improvements and weaknesses in education systems.