Women's report of unwanted sexual attention during childhood

Unwanted Sexual Attention (UWSA) refers to unsolicited verbal comments, gestures, stares, and other non-physical attention toward another's sexuality and physical appearance. The present study describes the occurrence of childhood UWSA and explores its relation to child sexual abuse (CSA). Three hundred fifteen university women (mean age=19.5) completed the Exposure to Sexual Attention Scale, a 200-item inventory which assesses various forms of UWSA received prior to age 18. Findings suggested that non-contact UWSA is a pervasive experience across settings for girls, with 98.7% reporting UWSA during childhood. Those reported most often to perpetrate UWSA (e.g., other students, adult strangers, child strangers, and other children) were also most often reported as sexual abusers. Emotional reactions by women to both UWSA and CSA were predominantly negative. Although significantly greater levels of fear reactions were reported by the CSA group when compared to the UWSA group. No difference was found between the two groups on levels of anger reactions to UWSA and CSA. Overall findings suggest that UWSA is an almost universal experience for girls that causes significant anger and fear. Assessing UWSA will be important from a public health perspective in evaluating if such behaviors pose a risk factor for negative developmental outcomes for girls.     

Integrated scheduling and inventory management of an oil products distribution system

The oil supply chain is facing new challenges due to emerging issues such as new alternative energy sources, oil sources scarcity, and price variability with high impact on demand and production and profit margins reduction. Additionally, the existence of large, complex and world wide spread businesses implies a complex system to be managed where distribution can be seen as one of the key areas that needs to be efficiently and effectively managed. Different types of distribution modes characterize the oil supply chain where the pipeline mode is one of the most complex to operate when having multiproduct characteristics. This paper addresses the planning of a generic oil derivatives transportation system characterized by a multiproduct pipeline that connects a single refinery to a storage tank farm. Two alternative mixed integer linear programming models (MILP) that aim to attain a set of planning objectives such as fulfilling costumers’ demands (which is mandatory) while minimizing the medium flow rate are developed. Additionally, final inventory levels are avoided to be excessively low. A real world scenario of a Portuguese company is used to validate and compare the two alternative MILP models developed in this paper.     

Managing Production and Distribution for Supply Chains in the Processed Food Industry

We develop and evaluate a modeling approach for making periodic review production and distribution decisions for a supply chain in the processed food industry. The supply chain faces several factors, including multiple products, multiple warehouses, production constraints, high transportation costs, and limited storage at the production facility. This problem is motivated by the supply chain structure at Amy's Kitchen, one of the leading producers of natural and organic foods in the United States. We develop an enhanced myopic two‐stage approach for this problem. The first stage determines the production plan and uses a heuristic, and the second stage determines the warehouse allocation plan and uses a non‐linear optimization model. This two‐stage approach is repeated every period and incorporates look‐ahead features to improve its performance in future periods. We validate our model using actual data from one factory at Amy's Kitchen and compare the performance of our model to that of the actual operation. We find that our model significantly reduces both inventory levels and stockouts relative to those of the actual operation. In addition, we identify a lower bound on the total costs for all feasible solutions to the problem and measure the effectiveness of our model against this lower bound. We perform sensitivity analysis on some key parameters and assumptions of our modeling approach.     

HRD in 2020: a hop-on,hop-off city tour

This article reports on the outcome of a Future Search Conference in the UK to consider human resource development (HRD) in 2020 and beyond. We firstly consider themes from the past into the present. This includes the persistence of solutions in HRD that are systematic, predictable, how apprenticeships in the UK have had to accommodate government policies to ameliorate youth unemployment and the long-standing difficulty for HRD of failing to demonstrate a return on investment (ROI) on activities. We then present four scenarios based on key questions for the future relating to value of HRD and whether this will be a future for HRD. Reponses to the questions form scenario logics which we present against the theme of city tour. Each scenario is explained against the presented logic with positive, negative, ambiguous and uncertain implications for HRD. We suggest that each scenario carries a glimpse of what might be.     

LINGUISTIC DIVERSITY AND REDISTRIBUTION

This paper investigates the effect of linguistic diversity on redistribution in a broad cross‐section of countries. We use the notion of “linguistic distances” and show that the commonly used fractionalization index, which ignores linguistic distances, yields insignificant results. However, once distances between languages are accounted for, linguistic diversity has both a statistically and economically significant effect on redistribution. With an average level of redistribution of 9.5% of GDP in our data set, an increase byone standard deviation in the degree of diversity lowers redistribution by approximately one percentage point. We also demonstrate that other measures, such as polarization and peripheral heterogeneity, provide similar results when linguistic distances are incorporated. (JEL: D6, D74, H5, Z10)     

The Multiscale Importance of Road Segments in a Network Disruption Scenario: A Risk‐Based Approach

This article addresses the problem of the multiscale importance of road networks, with the aim of helping to establish a more resilient network in the event of a road disruption scenario. A new model for identifying the most important roads is described and applied on a local and regional scale. The work presented here represents a step forward, since it focuses on the interaction between identifying the most important roads in a network that connect people and health services, the specificity of the natural hazards that threaten the normal functioning of the network, and an assessment of the consequences of three real‐world interruptions from a multiscale perspective. The case studies concern three different past events: road interruptions due to a flood, a forest fire, and a mass movement. On the basis of the results obtained, it is possible to establish the roads for which risk management should be a priority. The multiscale perspective shows that in a road interruption the regional system may have the capacity to reorganize itself, although the interruption may have consequences for local dynamics. Coordination between local and regional scales is therefore important. The model proposed here allows for the scaling of emergency response facilities and human and physical resources. It represents an innovative approach to defining priorities, not only in the prevention phase but also in terms of the response to natural disasters, such as awareness of the consequences of road disruption for the rescue services sent out to local communities.     

Essence taxonomy of Brazilian family businesses and conceptual implications for governance strategy

Journal of Management and Governance - This study advances the discussion on the governance of family businesses in emerging markets by exploring a taxonomy based on the F-PEC model in order to...