A decision support methodology for strategic planning in maritime transportation

This paper presents a decision support methodology for strategic planning in tramp and industrial shipping. The proposed methodology combines simulation and optimization, where a Monte Carlo simulation framework is built around an optimization-based decision support system for short-term routing and scheduling. The simulation proceeds by considering a series of short-term routing and scheduling problems using a rolling horizon principle where information is revealed as time goes by. The approach is flexible in the sense that it can easily be configured to provide decision support for a wide range of strategic planning problems, such as fleet size and mix problems, analysis of long-term contracts and contract terms. The methodology is tested on a real case for a major Norwegian shipping company. The methodology provided valuable decision support on important strategic planning problems for the shipping company.     

Communicating risk to parents and those living in areas with a disaster history

This study explored how publics respond to risk communication in high probability but time-indeterminate natural disaster situations when parts of the area have been involved in a similar disaster before. An impending rockslide is expected to produce a tsunami in the fjord around Åknes in Norway. Waves may run up above sea level as high as 82 m or 269 ft. All residents (18 and older) of the four most threatened communities received a questionnaire to determine what they perceived to be useful risk information. Three hundred and eighty-two (43.6% of 875) responded. Results indicated that parents of children living within the tsunami risk zones perceived the risk information to be the most useful. Those who lived in communities that experienced a similar disaster in 1934 reported public meetings less useful than written or mediated information. Publics who lived in communities with such disaster history and those who were not parents posed special challenges in risk communication because they perceived information from the government agencies as lacking in usefulness. Therefore, committing the resources necessary to foster dialogues with a diversity of publics exposed to risk would be well served to fully understand the nature of risk communication responses, and to be able to save human lives.     

Vital tasks and roles of frontline workers facilitating job inclusion of vulnerable youth

Researchers and others are worried about the marginalization of vulnerable youth who drop out of school and work. Frontline workers are key support givers for vulnerable youth, but they have been described as professionals who lack a recognized body of knowledge they can rely on. This article investigates vital frontline roles and tasks related to job inclusion of vulnerable youth. Qualitative data are drawn from 16 Norwegian pilot projects aimed at developing social work approaches among vulnerable youth. The challenges and the support provided resemble those in other European countries. Cross-case analysis suggests four main support roles: (1) administration and securing of basic needs, (2) connection and relationship building, (3) job enabling, and (4) job customisation. Combining roles 1 and 2 with roles 3 or 4 seems to improve the outcomes, meaning that they improve the capabilities of vulnerable youth to find and master a job when that is something they have reason to value. Since this topic has been little explored for vulnerable youth, this article contributes to further developing job inclusion support for this target group in particular.     

Rotten Parents and Disciplined Children: A Politico‐Economic Theory of Public Expenditure and Debt

This paper proposes a dynamic politico‐economic theory of fiscal policy in a world comprising a set of small open economies, whose driving force is the intergenerational conflict over debt, taxes, and public goods. Subsequent generations of voters choose fiscal policy through repeated elections. The presence of young voters induces fiscal discipline, that is, low taxes and low debt accumulation. The paper characterizes the Markov‐perfect equilibrium of the voting game in each economy, as well as the stationary equilibrium debt distribution and interest rate of the world economy. The equilibrium can reproduce some salient features of fiscal policy in modern economies.     

THE POLITICAL COLOR OF FISCAL RESPONSIBILITY

We propose a dynamic general equilibrium model that yields testable implications about the fiscal policy run by governments of different political color. Successive generations of voters choose taxation, expenditure, and government debt through repeated elections. Voters are heterogeneous by age and by the intensity of their preferences for public good provision. The political equilibrium switches stochastically between left‐ (pro‐public goods) and right‐leaning (pro‐private consumption) governments. A shift to the left (right) is associated with a fall (increase) in government debt, an increase (fall) in taxation, and an increase (fall) in government expenditures. However, left‐leaning governments engage in more debt accumulation during recessions. These predictions are shown to be consistent with the time‐series evidence for the United States in the postwar period, and also with the evidence for a panel of OECD countries. (JEL: D72, E62, H41, H62, H63)     

Analyzing Designed Experiments with Multiple Responses

This paper is an overview of a unified framework for analyzing designed experiments with univariate or multivariate responses. Both categorical and continuous design variables are considered. To handle unbalanced data, we introduce the so-called Type II* sums of squares. This means that the results are independent of the scale chosen for continuous design variables. Furthermore, it does not matter whether two-level variables are coded as categorical or continuous. Overall testing of all responses is done by 50-50 MANOVA, which handles several highly correlated responses. Univariate p-values for each response are adjusted by using rotation testing. To illustrate multivariate effects, mean values and mean predictions are illustrated in a principal component score plot or directly as curves. For the unbalanced cases, we introduce a new variant of adjusted means, which are independent to the coding of two-level variables. The methodology is exemplified by case studies from cheese and fish pudding production.     

Blur-generated non-separable space–time models

Statistical space–time modelling has traditionally been concerned with separable covariance functions, meaning that the covariance function is a product of a purely temporal function and a purely spatial function. We draw attention to a physical dispersion model which could model phenomena such as the spread of an air pollutant. We show that this model has a non-separable covariance function. The model is well suited to a wide range of realistic problems which will be poorly fitted by separable models. The model operates successively in time: the spatial field at time t +1 is obtained by 'blurring' the field at time t and adding a spatial random field. The model is first introduced at discrete time steps, and the limit is taken as the length of the time steps goes to 0. This gives a consistent continuous model with parameters that are interpretable in continuous space and independent of sampling intervals. Under certain conditions the blurring must be a Gaussian smoothing kernel. We also show that the model is generated by a stochastic differential equation which has been studied by several researchers previously.     

The additive hazard estimator is consistent for continuous-time marginal structural models

Lifetime Data Analysis - Marginal structural models (MSMs) allow for causal analysis of longitudinal data. The standard MSM is based on discrete time models, but the continuous-time MSM is a...     

The newsvendor problem with advertising: an overview with extensions

The effect of advertising on sales has been the subject of recent studies as an important aspect in many demand-based problems. Herein, we deal with the newsvendor problem, due to its simple structure, as a suitable tool for illustrating how facets of marketing may affect decision-making concerning operational problems. In the setting presented, the newsvendor is faced with advertising-sensitive stochastic demand, where a demand-related random element comprises an advertising decision of the multiplicative or additive form. We assume that a suitable advertising strategy results in increased sales. Two advertising response functions are considered, these being concave downward and S-shaped. We review and extend the existing results relating to the newsvendor problem with marketing effects, which mostly pertain to the concave function. These are generalized by defining the S-shaped function, and some original insights into the effect of advertising are given. We establish that the optimal advertising expenditure for the multiplicative case is always less than or equal to the optimal amount in the equivalent deterministic model while it is always equal in the additive case. We finally illustrate the results that are obtained by providing numerical examples involving various advertising response functions, as well as management-related interpretations.