Dynamic Perspectives on Managerial Decision Making

A central question in drug policy is how control efforts should be divided among enforcement, treatment, and prevention. Of particular interest is how the mix should vary dynamically over the course of an epidemic. Recent work considered how various pairs of these interventions interact. This paper considers all three simultaneously in a dynamic optimal control framework, yielding some surprising results. Depending on epidemic parameters, one of three situations pertains. It may be optimal to eradicate the epidemic, to “accommodate” it by letting it grow, or to eradicate if control begins before drug use passes a DNSS threshold but accommodate if control begins later. Relatively modest changes in parameters such as the perceived social cost per unit of drug use can push the model from one regime to another, perhaps explaining why opinions concerning proper policy diverge so sharply. If eradication is pursued, then treatment and enforcement should be funded very aggressively to reduce use as quickly as possible. If accommodation is pursued then spending on all three controls should increase roughly linearly but less than proportionally with the size of the epidemic. With the current parameterization, optimal spending on prevention varies the least among the three types of control interventions.

The economics of art and science differs from other branches by the small role of material inputs and the large role of given talent and access to markets. E.g., an African violinist lacks the audience ( = market) to appreciate her talent unless it is so large that it transgresses regional constraints; conversely, a European violinist of equal talent may be happy to end up as a member of one of the regional orchestras. This paper draws attention to this second aspect and models dynamic interactions between investments into two stocks, productive capital and access (or bargaining power). It is shown that there exists multiple equilibria. The separation between pursuing an artistic career or quitting depends on both idiosyncracies, individual talent and individual market access (including or depending on market size), which explains the large international variation in the number of people choosing a career in arts as market access is affected by geographic, linguistic, and aesthetic dimensions.

This paper examines the existence of Markov-Perfect-Equilibria that give rise to coexisting locally stable steady states in asymmetric differential games. The strategic interactions between an incumbent in a market and a potential competitor, which tries to enter the market through product innovation, are considered. Whereas the potential entrant invests in the build-up of a knowledge stock, which is essential for product innovation, the incumbent tries to reduce this stock through interference activities. It is shown that in the presence of upper bounds on investment activities of both firms a Markov-Perfect-Equilibrium exists under which, depending on the initial conditions, the knowledge stock converges either to a positive steady state, thereby inducing an entry probability of one, or to a steady state with zero knowledge of the potential entrant. In the later case the entry probability is close to zero. It is shown that this Markov-Perfect-Equilibrium is characterized by a discontinuous value function for the incumbent and it is discussed that this feature is closely related to the existence of upper bounds on the investments of the players. Removing these constraints in general jeopardizes the existence of a Markov-Perfect-Equilibrium with multiple locally stable steady states.

The paper considers a market in which two firms compete on advertising over time. Each firm can use three types of advertising: offensive advertising which attempts to attract customers from the rival firm, defensive advertising which aims at protecting a firm’s customer base from the rival’s attacks, and generic advertising to make industry sales grow. We address questions like: How should a strategy for the simultaneous use of the three types of advertising be designed? How would the resulting time paths of sales look like? The paper studies a differential game played over an infinite time horizon and provides closed-form expressions for equilibrium advertising strategies and sales rate trajectories.

I propose a differential oligopoly game of resource extraction under linear and nonlinear feedback strategies, where firms are managerial and delegation contract are based on output levels. The model shows that delegation expands the set of stable nonlinear feedback equilibria as well as the residual steady state resource stock. Additionally, the separation between ownership and control mitigates the voracity effect associated with high values of the reproduction rate of the resource.

We study an optimal AK-like model of capital accumulation and growth in the presence of a negative environmental externality in the tradition of Stokey (Int Econ Rev 39(1):1–31, 1998). Both production and consumption activities generate polluting waste. The economy exerts a recycling effort to reduce the stock of waste. Recycling also generates income, which is fully devoted to capital accumulation. The whole problem amounts to choosing the optimal control paths for consumption and recycling to maximize a social welfare function that notably includes the waste stock and disutility from the recycling effort. We provide a mathematical analysis of both the asymptotic behavior of the optimal trajectories and the shape of transition dynamics. Numerical exercises are performed to illustrate the analysis and to highlight some of the economic implications of the model. The results suggest that when recycling acts as an income generator, (1) a contraction of both the consumption and capital stock is observed in the long run after an expansion phase; (2) whether polluting waste is predominantly due to production or consumption, greater consumption and lower capital stock are obtained in the long run compared with the situation when recycling does not create additional income; (3) greater recycling effort and lower stock of waste are resulted in the long run.

In this paper we deal with complex systems and how to handle them. We focus on a well-known class of dynamical systems, namely predator-prey models, firstly by applying this type of model to urban economic development and secondly by testing models in an experimental setting in order to ascertain how successful human decision makers are in managing such a system. Regarding urban economic development, we illustrate that residential density and air pollution can be understood in terms of a predator-prey model and show how pollution control affects the level of the long-run equilibrium and the transition path towards it. We do this to support the understanding of how urban economic development works today and how it can be managed by decision makers via different interventions to improve the quality of living in urban areas. Regarding the task of handling predator-prey systems, we analyse the results of an experimental study in which participants take the role of a decision maker who seeks to maximise revenues from simultaneously harvesting a prey and a predator species while avoiding their overexploitation. We find that participants fall significantly shorter of the optimal strategy when the price assigned to the predator species is very high, compared to the price assigned to the prey species, in contrast to the case where the price difference is smaller. We offer several explanations for this observation that shed light on the human capability to handle predator-prey systems in general.

The problem of optimal harvesting (in a fish population as a benchmark) is stated within a model that takes into account the age-structure of the population. In contrast to models disregarding the age structure, it is shown that in case of selective harvesting mode (where only fish of certain sizes are harvested) the optimal harvesting effort may be periodic. It is also proved that the periodicity is caused by the selectivity of the harvesting. Mathematically, the model comprises an optimal control problem on infinite horizon for a McKendrick-type PDE with endogenous and non-local dynamics and boundary conditions.

As many European countries have to cope with a shrinking and aging labor force, one important goal of redistributing work is to increase female labor force participation. In some countries, however, this increase could come at the cost of a reduced fertility rate as childcare facilities might be rare or institutional settings and social support are not sufficiently family friendly. In this paper we investigate how and especially at which ages female labor force participation could be increased in a country such as Austria, with an apparently strong negative correlation between childbearing and labor force participation, without reducing fertility even further. Our results indicate that an increase in female labor force participation is indeed possible if the participation rate remains low in the most fertile ages. It turns out, however, that the optimal labor force participation for females strongly depends on the initial fertility pattern of the female population.

We consider the neoclassical one-sector growth model in continuous time with elastic labor supply and a learning-by-doing externality. It is shown that this model can have a continuum of balanced growth paths. Some of these balanced growth paths can be locally unique (determinate) whereas others can be indeterminate.

In this paper we present an application of the dynamic tracking games framework to a monetary union. We use a small stylized nonlinear two-country macroeconomic model (MUMOD1) of a monetary union to analyse the interactions between fiscal (governments) and monetary (common central bank) policy makers, assuming different objective functions of these decision makers. Using the OPTGAME algorithm we calculate solutions for two game strategies: a cooperative solution (Pareto optimal) and a non-cooperative equilibrium solution (the Nash game for the feedback information pattern). We show how the policy makers react to demand shocks under non-cooperation and cooperation scenarios. The cooperative solution dominates the non-cooperative solution in all scenarios, which may be interpreted as an argument for coordinating fiscal and monetary policies in a monetary union in a situation of high public debt such as in the recent sovereign debt crisis in Europe.

Combat between governmental forces and insurgents is modelled in an asymmetric Lanchester-type setting. Since the authorities often have little and unreliable information about the insurgents, ‘shots in the dark’ have undesirable side-effects, and the governmental forces have to identify the location and the strength of the insurgents. In a simplified version in which the effort to gather intelligence is the only control variable and its interaction with the insurgents based on information is modelled in a non-linear way, it can be shown that persistent oscillations (stable limit cycles) may be an optimal solution. We also present a more general model in which, additionally, the recruitment of governmental troops as well as the attrition rate of the insurgents caused by the regime’s forces, i.e. the ‘fist’, are considered as control variables.

Recent discussions about the definition of economic growth in terms of welfare beyond GDP suggest that it is of urgent need to develop new approaches for measuring the economic performance of firms and national economies. For this purpose the DEA methodology is used by simultaneously taking into account economic as well as social and environmental indicators. SBM DEA models with restricted weights are used in order to analyse the impact of different strategies and goals of economic policy for measuring of social welfare. Using Malmquist productivity index the drivers of social welfare change over the period of 2003–2012 for 25 European countries are identified. This approach allows us to decompose the overall change to change in economic, environmental and social component. It can be shown that the main driver of the increasing social welfare in Europe was the environment-saving change of technology.

The speed with which an organization takes action against unplanned failure and scrapping of its capital equipment is used as a measure of organizational nimbleness. Operational decisions at the plant level are studied in terms of the optimal control model of Kamien and Schwarz for maintenance policy. In this context it is shown how the form of optimal policies at the lower operational levels change, as the degree of nimbleness in decision making at higher echelons of the organization is increased.

Safety stock planning that focuses on risk protection to cope with demand uncertainties is a very well researched topic in the field of supply chain management, in central as well as in local decision making systems. In contrast, there is only few knowledge about safety stock management in situations where supply risks have to be covered that are caused by uncertainties with respect to production yields. In this study, a two-stage manufacturer-retailer supply chain is considered in a single-period context that allows for an analytical study of the impact of yield randomness on safety stock determination. In order to concentrate the analysis on the effects of yield uncertainty demand will be assumed to be deterministic.

We consider three basic types of yield randomness which represent different reasons for yield losses in production processes each, namely the stochastically proportional, binomial, and interrupted geometric yield type. It will be shown that these different yield risk specifications can bring about completely different properties concerning how safety stocks react on various input parameters in supply chain planning.

This holds especially for the impact of the demand size and for the influence of the level of product profitability in a supply chain. In an analytical model-based investigation it is demonstrated that the safety stock properties not only differ between the respective yield types, but also between systems of central and decentralized supply chain decision making. Thus, this study presents general insights into the importance of a correct yield type specification for an effective safety stock management and explains resulting differences in the stock distribution across supply chain stages in both centralized and decentralized settings.

Dynamic pricing is an instrument to achieve operational efficiency in inventory management. We consider an economic ordering context with strategic customers who forward-buy or postpone their purchases in anticipation of price changes. By charging a lower price when inventories are high, significant profit improvements can be achieved. The paper analyzes a simple EOQ-type model with a single price change within each inventory cycle. Numerical examples illustrate its impact on profits, order cycle duration and optimal price discounts. In particular for slow moving and low margin products, improvements in retail-type environments are substantial.

In this paper we study a joint manufacturing–remanufacturing problem of a manufacturer under demand uncertainty. Supply of remanufacturable units is constrained by the availability of used and returned cores, which depends on previous supply of new units. Potential cost savings due to remanufacturing in later periods may induce the manufacturer to reduce its short-term profits by artificially increasing its supply in earlier periods. For dealing with this trade-off we formulate an intertemporal optimization problem in a classical two-period newsvendor setting. Exploiting first period information when taking second period supply decisions we provide analytical insights into the optimal strategy and compare this optimal strategy with a previously proposed heuristic, where both first and second period decisions are committed to prior to period 1. Through a comprehensive numerical study we evaluate the associated profit implications.

Determining lot sizes is an essential step during the material requirements planning phase influencing total production cost and total throughput time of a production system. It is well-known that lot-sizing and scheduling decisions are intertwined. Neglecting this relation, as it is done in the classical hierarchical planning approach, leads to inefficient and sometimes infeasible plans. In this work we compare different approaches for integrating the lot-sizing and the scheduling decisions in multi-stage systems. We show their abilities and limitations in describing relevant aspects of a production environment. By applying the models to benchmark instances we analyze their computational behavior. The structural and numerical comparisons show that there are considerable differences between the approaches although all models aim to describe the same planning problem. The results provide a guideline for selecting the right modeling approach for different planning situations.

This article extends a recently developed model for project scheduling and staffing by addressing two practically important features, namely the possibility of interruptions between the execution periods of a project on the one hand, and decisions between different types of labor contracts on the other hand. A hybrid metaheuristic employs a decomposition of the problem into a project scheduling problem and a personnel planning problem. For the scheduling decision, a guided variable neighborhood descent search is applied, whereas for the personnel planning decision, a greedy staffing heuristic is used to obtain initial solutions. In a post-processing phase, information about the best greedily evaluated schedule triggers a re-evaluation of the staffing decision by means of an exact solver. To test the approach, we compare the outcome of the developed hybrid metaheuristic with the results obtained by applying only the exact solver to the considered optimization problem. The numerical tests show that the metaheuristic performs well for small to medium-sized test instances and offers good solutions for larger instances where the exact solver fails to return a feasible solution.

Decision makers are often not able to provide precise preference information, which is required to solve a multicriteria decision problem. Thus, many methods of decision making under incomplete information have been developed to ease the cognitive burden on decision makers in providing preference information. One popular class of such methods, exemplified by the SMAA family of methods, uses a volume-based approach in parameter space and generates probabilistic statements about relations between alternatives. In the present paper, we study methods to transform this probabilistic information into a strict preference relation among alternatives, as such strict preferences are needed to actually make a decision. We compare these methods in a computational study, which indicates a trade-off between accuracy and robustness.

Messages using fear appeals often appear in social marketing, to promote causes such as smoking cessation, healthcare and driving accident prevention. Fear appeals can enhance the effectiveness of such communications, but they also may have unintended side effects. This study investigates the effect of fear-inducing public service announcements on evaluations of subsequent commercials in a commercial break. In two laboratory experiments, the authors measured participants’ evaluations of advertisements using a program analyzer. In line with affective priming theory, the results showed that fear-inducing public service announcements can negatively affect evaluations of subsequent commercials.

For successful emergency management (EM) it is crucial that all stakeholders, especially health care emergency responders, use the same terminology. Throughout the emergency management lifecycle it is necessary for individual agencies to work together, sharing information and resources. Emergency management is already a complex process, but a multi-agency response comes with added difficulties. Each agency has its own organisational cultures, structures, and technologies in place, managed by internal processes and systems. To address some of the challenges associated with a multi-agency response (e.g., lack of coordination, information, and interoperability), standardisation is promoted. By ensuring the use of shared terms, operational inefficiencies and delays can be reduced and a shared vocabulary can be promoted across multiple agencies. For this reason, the S-HELP Strategic Disaster Management wiki has been developed by University of Vienna, Austria (UNIVIE). The wiki provides main glossary terms, definitions, and standards to improve decision making. It is implemented as a part of the FP7-EU S-HELP (Securing Health.Emergency.Learning.Planning) project, which develops a Decision Support (DS) tool for EM and is coordinated by University College Cork (UCC), Ireland.

Car-sharing systems are increasingly employing environmentally-friendly electric vehicles. The design and management of Ecar-sharing systems poses several additional challenges with respect to those based on traditional combustion vehicles, mainly related with the limited autonomy allowed by current battery technology. We review the main optimization problems arising in Ecar-sharing systems at strategic, tactical and operational levels, and discuss the existing approaches often developed for similar problems, for example in car-sharing systems with traditional vehicles. We also outline open problems and fruitful research directions.

Tourism and travel with the purpose to do sports is gaining in popularity and the golf tourism market is considered to be one of the largest. Motivated by this phenomenon we model and solve the golf tourist problem which generalizes the orienteering problem with time windows. It aims at providing decision support for the traveling golfer by concurrently optimizing two objective functions: travel cost on the one hand and attractiveness of the generated travel plans on the other hand. Travel costs consist of flight cost, hotel cost, car rental cost, green fees as well as petrol cost for traveling between the selected golf courses. Attractiveness is measured by the total par scores of the visited golf courses. We assume that the traveling golfer provides a selection of regions in Europe that he or she is equally inclined to visit on his or her next trip. A feasible travel plan selects one region, contains only golf courses of this region and starts and ends at the respective airport. We solve the golf tourist problem to optimality by means of a recent bi-objective branch-and-bound algorithm and by means of the ε-constraint method. Furthermore, we devise a decomposition approach that solves each regional problem separately and then combines the obtained Pareto sets. The proposed methods are applied to several real world instances with up to nine regions and between 57 and 227 golf courses per region. Our results show that the decomposition approach is significantly more efficient than the holistic approach. They also show that the bi-objective branch-and-bound algorithm performs better than the ε-constraint scheme.

The vehicle routing problem was formulated more than 50 years ago and has attracted great attention since then, not least due to its high practical relevance and its computational complexity. Throughout the years, various generalizations and solution techniques were proposed. The purpose of this survey is to describe the developments in this particular field. Starting with a basic model, several generalizations to the classical vehicle routing problem are explained by gradually extending the initial model. A special focus lies on the contributions to this field of study by Richard F. Hartl and his colleagues at the University of Vienna, particularly with regard to developed solution methods.

This small note offers a “tongue-in-cheek” route to some game theoretical facets of Greek mythology. By using an apocryphal bilingual poem as well as mathematical arguments, we finally explain how Ulysses succeeded in detecting Achilles among the daughters of Lykomedes.