Modern Approaches to Risk Management and Their Use in Customs

In the article the analysis of experience and best practices of Europe and the world regarding the methods and tools of risk management in customs affairs. In accordance with the requirements of the Kyoto Convention the risk management is the main basic principle of modern customs control methods, which allows optimal use of resources of customs bodies, without reducing the effectiveness of customs controls, and exempt the majority of foreign trade operators from unnecessary bureaucratic control. Procedures based on risk management, concentrate customs control on areas, where there is the greatest risk, allowing the bulk of goods and individuals relatively free to pass the checkpoint at the customs border Special attention is paid to the principles and methods of risk management and their impact on the simplification of customs procedures through the use of risk-based thinking. The paper discusses the problems concerning the application and implementation of modern risk management techniques in customs procedures subject to the requirements of international standards ISO for the quality management system and risk management based on risk-based thinking

On the construction of stable project baseline schedules.

The vast majority of project scheduling efforts assume complete information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule will be executed. In reality, however, project activities are subject to considerable uncertainty, which generally leads to numerous schedule disruptions. It is of interest to develop pre-schedules that can absorb disruptions in activity durations without affecting the planning of other activities, such that co-ordination of resources and material procurement for each of the activities can be performed as smoothly as possible. The objective of this paper is to develop and evaluate various approaches for constructing a stable pre-schedule, which is unlikely to undergo major changes when it needs to be repaired as a reaction to minor activity duration disruptions.

Joint dimensioning of server and network infrastructure for resilient optical grids/clouds

We address the dimensioning of infrastructure, comprising both network and server resources, for large-scale decentralized distributed systems such as grids or clouds. We design the resulting grid/cloud to be resilient against network link or server failures. To this end, we exploit relocation: Under failure conditions, a grid job or cloud virtual machine may be served at an alternate destination (i.e., different from the one under failure-free conditions). We thus consider grid/cloud requests to have a known origin, but assume a degree of freedom as to where they end up being served, which is the case for grid applications of the bag-of-tasks (BoT) type or hosted virtual machines in the cloud case. We present a generic methodology based on integer linear programming (ILP) that: 1) chooses a given number of sites in a given network topology where to install server infrastructure; and 2) determines the amount of both network and server capacity to cater for both the failure-free scenario and failures of links or nodes. For the latter, we consider either failure-independent (FID) or failure-dependent (FD) recovery. Case studies on European-scale networks show that relocation allows considerable reduction of the total amount of network and server resources, especially in sparse topologies and for higher numbers of server sites. Adopting a failure-dependent backup routing strategy does lead to lower resource dimensions, but only when we adopt relocation (especially for a high number of server sites): Without exploiting relocation, potential savings of FD versus FID are not meaningful

Solution and quality robust project scheduling: a methodological framework.

The vast majority of the research efforts in project scheduling over the past several years has concentrated on the development of exact and suboptimal procedures for the generation of a baseline schedule assuming complete information and a deterministic environment. During execution, however, projects may be the subject of considerable uncertainty, which may lead to numerous schedule disruptions. Predictive-reactive scheduling refers to the process where a baseline schedule is developed prior to the start of the project and updated if necessary during project execution. It is the objective of this paper to review possible procedures for the generation of proactive (robust) schedules, which are as well as possible protected against schedule disruptions, and for the deployment of reactive scheduling procedures that may be used to revise or re-optimize the baseline schedule when unexpected events occur. We also offer a methodological framework that should allow project management to identify the proper scheduling methodology for different project scheduling environments. Finally, we survey the basics of Critical Chain scheduling and indicate in which environments it is useful.Framework; Information; Management; Processes; Project management; Project scheduling; Project scheduling under uncertainty; Stability; Robust scheduling; Quality; Scheduling; Stability; Uncertainty;

Project scheduling under undertainty – survey and research potentials.

The vast majority of the research efforts in project scheduling assume complete information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule will be executed. However, in the real world, project activities are subject to considerable uncertainty, that is gradually resolved during project execution. In this survey we review the fundamental approaches for scheduling under uncertainty: reactive scheduling, stochastic project scheduling, stochastic GERT network scheduling, fuzzy project scheduling, robust (proactive) scheduling and sensitivity analysis. We discuss the potentials of these approaches for scheduling projects under uncertainty.Management; Project management; Robustness; Scheduling; Stability;

Who Should Bear the Risk When Self-Driving Vehicles Crash?

The moral importance of liability to harm has so far been ignored in the lively debate about what self-driving vehicles should be programmed to do when an accident is inevitable. But liability matters a great deal to just distribution of risk of harm. While morality sometimes requires simply minimizing relevant harms, this is not so when one party is liable to harm in virtue of voluntarily engaging in activity that foreseeably creates a risky situation, while having reasonable alternatives. On plausible assumptions, merely choosing to use a self-driving vehicle typically gives rise to a degree of liability, so that such vehicles should be programmed to shift the risk from bystanders to users, other things being equal. Insofar vehicles cannot be programmed to take all the factors affecting liability into account, there is a pro tanto moral reason not to introduce them, or restrict their use

A Risk Management Model for Merger and Acquisitio

In this paper, a merger and acquisition risk management model is proposed for considering risk factors in the merger and acquisition activities. The proposed model aims to maximize the probability of success in merger and acquisition activities by managing and reducing the associated risks. The modeling of the proposed merger and acquisition risk management model is described and illustrated in this paper. The illustration result shows that the proposed model can help to screen the best target company with minimum associated risks in the merger and acquisition activity

Beyond the Win: Pathways for Policy Implementation

When it comes to policy, a lot of attention is given to "the win." Whether it is something new and big like the Affordable Care Act, a piece of legislation in a large federal omnibus bill, or inclusion of critical language in a state policy, seeing the fruits of advocacy efforts put into law makes advocates and champions feel that their hard work, often many years in the making, has paid off.However, in reality, "the win" is just the beginning -- a necessary first step in a much longer and equally as fraught process of policy implementation. Once a policy is created, there are numerous factors that shape and determine how that policy is implemented -- and ultimately, the impact it will have -- regardless of how well the policy is formulated. Some of these factors include rulemaking, funding, capacity of local implementing agencies, and fights to repeal or modify wins, among many others.And, just as in the case of "the win," advocacy plays an important role in shaping implementation whether in advocating across these factors or participating in ongoing monitoring over time. Interestingly, while the role of advocacy in agenda setting, policy formulation, and policy adoption has been widely explored in theory and practice, the role of advocacy in the policy implementation process has received less attention in the literature.To learn more about the role of advocacy at the policy implementation stage, ORS Impact spoke with organizations that engage in, or provide funding for, advocacy efforts at the state and/or federal level. We focused on the following questions:When had advocates played a positive role in policy implementation?When had implementation not gone as well as expected, and what did advocates take away from that?Our conversations yielded important learnings about the unique characteristics of, and range of approaches to, advocacy efforts during the implementation phase. The two following scenarios illustrate some of the different types and levels of advocacy intervention, as well as the results they produce, to demonstrate the ways advocacy can play out when shifting from policymaking to implementation