Cost-benefit Function Research Articles

Offshore financial centres: the political economy of regulation

This paper claims that the regulation profile of the Offshore Financial Centres (OFCs) with respect to the international standards defined to prevent potentially harmful phenomena—such as aggressive taxation, financial instability, money laundering and terrorism finance—depends on their specific structural features. In the designing of the regulatory framework the OFCs policymakers define the optimal degree of compliance maximizing a political cost benefit function. A simple model shows that the policymaker convenience to establish an OFC jurisdiction can depend on peculiar country endowments, consistently with a path-dependency approach. The model is empirically tested using a 222 countries’ sample, using different classifications of OFCs. On the one hand we find that the probability to be an OFC is greater with higher political stability, lower crime level, lower voice in international organizations, and if the country is characterized by a Common Law juridical system. Furthermore a low resource endowment seems to have a slightly influence on the choices to be an OFC. On the other hand it seems not to be crucial to use English as official language, to be a former colony, and also the geographical position it is not fundamental. The results are used for an overall assessment of the adequacy of the international policy aimed to fill the regulation gap, raising doubts on the persistency of the name and shame approach.

Marketing Segmentation Through Machine Learning Models

Customer relationship management (CRM) aims to build relations with the most profitable clients by performing customer segmentation and designing appropriate marketing tools. In addition, customer profitability accounting (CPA) recommends evaluating the CRM program through the combination of partial measures in a global cost—benefit function. Several statistical techniques have been applied for market segmentations although the existence of large data sets reduces their effectiveness. As an alternative, decision trees are machine learning models that do not consider a priori hypotheses, achieve a high performance, and generate logical rules clearly understood by managers. In this article, a three-stage methodology is proposed that combines marketing feature selection, customer segmentation through univariate and oblique decision trees, and a new CPA function based on marketing, data warehousing, and opportunity costs linked to the analysis of different scenarios. This proposal is applied to a large insurance marketing data set for alternative cost and price conditions showing the superiority of univariate decision trees over statistical techniques.

A Multiphase Fuzzy Logic Approach to Strategic Planning of a Reverse Supply Chain Network

Strategic planning (also called designing) is a challenging aspect of a reverse supply chain network. To effectively satisfy drivers such as profitability, environmental regulations, and asset recovery, only the most economical used products must be reprocessed in only the recovery facilities that have the potential to efficiently reprocess them. Due to uncertainties in supply, quality, and reprocessing times of used products, the cost-benefit function in the literature that selects the most economical product to reprocess from a set of used products is not appropriate for direct adoption. Moreover, due to the same uncertainties, any traditional forward supply chain approach to identify potential manufacturing facilities cannot be employed to identify potential recovery facilities. This paper proposes a three-phase fuzzy logic approach, taking the above uncertainties into account, to design a reverse supply chain network. Application of the approach is detailed through an illustrative example in each phase.

Evaluating cost-effectiveness of conservation management actions in an agricultural landscape on a regional scale

Agricultural landscapes are the dominating landscape types in many parts of the world. Land-use intensification and spatial homogeneity are major threats to biodiversity in these landscapes. Thus cost-effective strategies for species conservation in large-scale agricultural landscapes are required. Spatial optimisation methods can be applied to identify the most effective allocation of a given budget for conservation. However, the optimisation of spatial land-use patterns in real landscapes on a large spatial scale is often limited by computational power. In this paper, we present a simplifying methodology for analysing cost-effectiveness of management actions on a regional scale. A spatially explicit optimisation approach is employed to identify optimum agricultural land-use patterns with respect to an ecological-economic goal function. Based on the optimisation results for small scale landscape samples we derive a target- and site-specific cost–benefit function that can be applied to predict ecological improvement as a function of costs and local conditions on a large spatial scale. Thus, it is possible to identify areas where management actions for ecological improvement are most efficient with respect to a certain conservation goal. The fitted function is validated independently. In a case study, we analyse cost-effectiveness of management actions to enhance habitat suitability for three different target species. The approach is flexible and could be applied to a variety of other landscape planning problems dealing with the effective allocation of management measures.

Offshore Financial Centres: Explaining the Regulation

This paper claims that the regulation profile of the Offshore Financial Centres (OFCs) respect to the international standards defined to prevent potentially harmful phenomena - such as aggressive taxation, financial instability, money laundering and terrorism finance - depends on their specific structural features. In the designing of the regulatory framework the OFCs policymakers define the optimal degree of compliance maximizing a political cost benefit function. A simple model shows that the policymaker convenience to establish an OFC jurisdiction can depend on peculiar country endowments, consistently with a path dependency approach. The model is empirically tested using a 222 countries' sample, using different classifications of OFCs. On the one hand we find that the probability to be an OFC is greater with higher political stability, lower crime level, lower voice in international organizations, and if the country is characterized by a Common Law juridical system. Furthermore a low resources endowment seems to have a slightly influence on the choices to be an OFC. On the other hand it seems not to be crucial to use English as official language, to be a former colony, and also the geographical position it is not fundamental. The results are used for an overall assessment of the adequacy of the international policy aimed to fill the regulation gap, raising doubts on the persistency of the name and shame approach.

Cost–benefit functions for the allocation of security sensors for air contaminants

In this paper, we study various functional forms of the cost–benefit function in a context of risk analysis and multi-objective decision-making for the allocation of hazard protection. An approach of benefit–cost analysis under uncertainty is used. The study identifies measures of hazard intensity and population exposure as well as additional parameters that influence assessments of benefits and costs. Parameter uncertainties are propagated by numerical interval analysis. Several tiers of the uncertainty of the benefit-to-cost ratio are generated to compare hazard intensity and population exposure in multi-objective tradeoff analysis. We develop an example application with the allocation of chemical, biological, and radiological air contaminant sensors throughout a region. The sensors provide local protection to non-identical sectors of the population that are exposed to non-identical intensities of the hazard. The results illuminate the significance of the cost–benefit function for the allocation of sensors. The paper has implications for anti-terrorism, disaster preparedness, transportation safety, and other areas of public safety.

Strategic planning of a reverse supply chain network

Strategic planning of a supply chain network is one of the most challenging elements of managing reverse logistics. To effectively satisfy drivers such as profitability, environmental regulations and asset recovery, only the most economical used-products must be re-processed in only the recovery facilities that have the potential to efficiently re-process them. Due to uncertainties in supply, quality and re-processing times of used-products, the cost–benefit function used in the literature to select the most economical product to re-process from a set of used-products, is not appropriate for direct adoption. Moreover, due to the same uncertainties, any traditional forward supply chain approach to identify potential manufacturing facilities cannot be employed to identify potential recovery facilities. This paper proposes a three-phase mathematical programming approach, taking the above uncertainties into account, for strategic planning of a reverse supply chain network. Application of the approach is detailed through illustrative examples.

Dynamic Portfolio Optimization with Expected Value-Variance Criteria

In the paper, a problem of dynamic optimal portfolio selection is considered. We examine an approach with two criteria: expected value and variance. The main difficulty is of that the variance criterion is not separable in time, even for the cost (benefit) function of Bolza type. Two methods of determining optimal control with expected value-variance criteria are tested: method based on the Lagrange function (finite time horizon) and method based on the linear programming (infinite time horizon). These methods were applied to a problem of investing in assets at the main market of the Warsaw stock-exchange.

Optimum Diet and Body Size in Backswimmers (Heteroptera: Notonectidae, Pleidae)

Relations between predator and prey sizes and profitability of the prey to the predator were analyzed for cost-benefit in the backswimmers Notonecta lunata Hungerford, N. undulata Say, N. irrorata Uhler, N. insulata Kirby (Notonectidae) and the pigmy backswimmer Neoplea striola (Fieber) (Pleidae). As costs of pursuing prey are often great (i.e., subjecting predator to predation), the probability of prey capture (p) was incorporated multiplicatively in a cost-benefit function. Attack distances of Notonecta spp. increased with prey size and decreased with predator size; attacks by Neoplea were the same length on all prey sizes. In both genera, handling time and the amount of a prey item eaten depended on both predator and prey size. Pursuit costs of time and energy appear too low to affect the profitability of prey. Generally, larger predators obtained less profit from prey. The profitability of prey appeared normally distributed with reference to prey size in N. lunata, N. undulata, and N. irrorata, but generally remained constant in N. insulata and Neoplea striola. Prey density did not affect the sizes in the diet of Neoplea but starvation increased the proportion of large prey eaten. This tendency poorly fits an hypothesis of diet optimization. Prey-sizes selected by Notonecta spp. reveal little or no diet optimization. Alternatives to diet optimization are examined.

Management of optimum water quality in a stream

An optimal waste discharge policy along a stream is investigated based on a program of minimizing the total cost benefit function on a regional basis. The system consists of a stream along which are located several inputs of waste and intakes of water. The cost benefit function comprises of the sum of the cost of waste treatment and the cost of water treatment minus the benefits derived from maintaining a certain water quality in the stream. The biochemical oxygen demand and the dissolved oxygen are considered to be the primary indicators of water quality. A steady state dispersion model is employed to predict the BOD and DO concentrations along the stream. In order to optimize the system or minimize the cost benefit function within certain constraints on water quality, a search scheme is proposed. The feasibility of obtaining a solution by a sequential minimization technique, employing a discrete search, is studied for cases with two and three decision variables. The analysis procedure can be used to examine existing water quality programs and to study the influence of alternate policies and constraints.

Theory of Feeding Strategies

Natural history is replete with observations on feeding, yet only recently have investigators begun to treat feeding as a device whose performance­ as measured in net energy yield/feeding time or some other units assumed commensurate with fitness-may be maximized by natural selection (44, 1 13, 135, 156, 181) . The primary task of a theory of feeding strategies is to specify for a given animal that complex of behavior and morphology best suited to gather food energy in a particular environment. The task is one, therefore, of optimization, and like all optimization problems, it may be tri­ sected: 1. Choosing a currency: What is to be maximized or minimized? 2. Choosing the appropriate cost-benefit functions: What is the mathematical form of the set of expressions with the currency as the dependent variable? 3. Solving for the optimum: What computational technique best finds ex­ trema of the cost-benefit function? In this review, most of the following section is devoted to possible answers to the first problem. Then four key aspects of feeding strategies will be considered: (a) the optimal diet, (b) the optimal foraging space, (c) the optimal foraging period, and (d) the optimal foraging-group size. For each, possible cost-benefit formulations will be discussed and compared, and predictions derived from these will be matched with data from the literature on feeding. Because the third problem is an aspect of applied mathematics, it will be mostly ignored. Throughout, emphasis will be placed on strategic aspects of feeding rather than on what Holling (75) has called tactics.

On the Nature of the Cost-Benefit Schedule

In this paper the nature of a set of coat-benefit studied alternatives is studied. An integrated set of submodels is assumed to provide the foundation for a cost-benefit schedule. The model is formulated as an efficiency problem using the technique of vector maximization. Efficient points are characterized by a set of decision rules. A local cost-benefit function is developed. Comparative statics (sensitivity analysis) results show that there exist efficiency substitution and benefit effects. These effects are the basis for rigorous definitions of efficiency substitutes and complements.