General Cost Structure Research Articles

Truthful multi-unit double auction with transaction costs and sellers’ changing marginal costs

It is well-known that lots of sellers offer discounts for large orders because of decreasing marginal costs and large productive capacities. Then some procurement platforms provide ways for small buyers to cooperate with their procurements and get discounts from these sellers. Moreover, these transactions will incur pair-related transaction costs. Generally, buyers values and sellers’ costs are private information. Then a critical problem faced by the platforms is to induce the buyers (sellers) to reveal their values (costs) truthfully and to match the supplies and demands efficiently. To solve this problem, we design a multi-unit double auction mechanism based on the padding method where the buyers bid their values and the sellers submit their marginal costs of different quantities, and the platform selects the winners, allocates the transactions, and sets the transaction prices for both sides. We show that the mechanism is budget-balanced, individually rational, incentive-compatible, and asymptotically efficient. For the special case with zero transaction costs, we further simplify the mechanism and get some new findings. We further conduct numerical studies to compare our mechanism with four commonly used mechanisms to demonstrate its advantages and examine the impacts of some parameters on the performance of our mechanism. Finally, we consider the cases with general marginal cost structure as well as private quantity information, respectively.

Phase Transitions in Bandits with Switching Constraints

We consider the classic stochastic multiarmed bandit problem with a constraint that limits the total cost incurred by switching between actions to be no larger than a given switching budget. For this problem, we prove matching upper and lower bounds on the optimal (i.e., minimax) regret and provide efficient rate-optimal algorithms. Surprisingly, the optimal regret of this problem exhibits a nonconventional growth rate in terms of the time horizon and the number of arms. Consequently, we discover surprising “phase transitions” regarding how the optimal regret rate changes with respect to the switching budget: when the number of arms is fixed, there are equal-length phases, in which the optimal regret rate remains (almost) the same within each phase and exhibits abrupt changes between phases; when the number of arms grows with the time horizon, such abrupt changes become subtler and may disappear, but a generalized notion of phase transitions involving certain new measurements still exists. The results enable us to fully characterize the trade-off between the regret rate and the incurred switching cost in the stochastic multiarmed bandit problem, contributing new insights to this fundamental problem. Under the general switching cost structure, the results reveal interesting connections between bandit problems and graph traversal problems, such as the shortest Hamiltonian path problem. This paper was accepted by J. George Shanthikumar, data science. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4755 .

Shipment Consolidation with Multiple Shipping Methods Under Nonlinear Cost Structures

We study a shipment consolidation problem commonly faced by companies that outsource logistics operations and operate in a commit-to-delivery mode. It involves delivering a given set of orders to their destinations by their committed due times using multiple shipping methods at the minimum total shipping and inventory cost. The shipping cost is generally nonlinear in shipping quantity and can be represented by a subadditive piecewise linear function. We investigate two shipping scenarios, one involving long-haul shipping only and the other involving joint long-haul and short-haul shipping. We develop analytical results and solution algorithms for the shipment consolidation problem under each shipping scenario. The problem under the first shipping scenario is shown to be strongly [Formula: see text]-hard. We find that a simple policy, called the First-Due-First-Delivered (FDFD) policy, which assigns orders with earlier delivery due times to shipping methods with earlier destination arrival times, is very effective. This policy enables us to develop a polynomial time algorithm, which not only solves the problem under the concave shipping cost structure optimally but also achieves a performance guarantee of 2 for the problem under the general subadditive shipping cost structure. For the problem under the second shipping scenario, we extend the FDFD policy for long-haul shipping and derive another policy, called the No-Wait policy, for short-haul shipping. We use these policies to develop a polynomial time algorithm and analyze its performance guarantee. Our computational experiments show that the algorithm significantly outperforms a commercial optimization solver, and its performance is robust across different parameter settings that reflect various practical situations. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The data and e-companion are available at https://doi.org/10.1287/mnsc.2023.4835 .

Hospital multi-dimensional quality competition with medical malpractice

In this paper, we study the effect of competition on the plural dimensions of hospital quality in a market with regulated prices. Our results are obtained with the standard model of hospital competition where a distinction can now be made between two different dimensions of quality while using fair general demand and cost structure. In our setting, hospitals can choose to invest either in the quality of health care services which reduces exposition to the risk of medical error, or in another dimension of quality which is independent to the risk of medical malpractice (appropriateness, patient-centeredness, amenities, etc.). We derive the conditions under which an intensified competition can not only raise or decrease hospital quality, but can also lead to a substitution between the two dimensions of quality. We also investigate how hospital competition and tort law may interact to help improve quality of care by deterring negligent behaviors of providers of care. Lastly, we use a model of strategic pretrial negotiation under asymmetric information to examine the effect of hospital competition on the resolution of medical disputes through its effect on quality.

The impact of e-marketplace on the B2b relationships

PurposeConsidering the growing momentum of online marketplaces worldwide, the purpose of this paper is to develop a model to identify the main activities impacted by the implementation of an e-marketplace in the business-to-business relationship and assess the savings on costs for the main actors involved (i.e. manufacturer, distributor and retailer).Design/methodology/approachThe methodology used in the study is a quantitative one. The analytical model used to evaluate B2b e-marketplace's impacts followed three main steps: (1) model settings and general assumptions, (2) cost structure and (3) model simulation.FindingsThe findings reveal that beyond stock-out costs and inventory levels also other operating costs (i.e. transportation, penalty and administrative costs) play a significant role in determining overall impacts of B2b e-marketplace, and as such should be considered by managers in their process of e-marketplace evaluation, selection and performance optimisation. The model shows that compared with the offline scenario the B2b e-marketplace is expected to bring value to the overall supply chain, which tends to increase as the share of e-sales penetration is increased, ranging from a cost reduction of 0.1% (€ 229.2k) in the base-case of 10% e-sales adoption, up to 0.9% (€ −2.2 M) in case of full e-marketplace adoption.Originality/valueThis study aims to shed light and foster the adoption of B2b e-marketplace by providing some practical tools to support (1) research in future studies, filling the existing gaps on the topic, and (2) managers in the process of adoption and execution of e-sales through online marketplaces.

Understanding and Analysing Resource Utilization, Costing Strategies and Pricing Models in Cloud Computing

This paper is primarily focused on understanding the basics of cloud computing economics – specific pricing models and general cost structure and compares between basic cost structures. It also examines 15 pricing models dependent on various bases and attempts to consolidate the different pricing methods used to guarantee maximum profitability to both the service provider and consumer. To avail the services of cloud computing from the cloud service provider, the organization has to incur individual costs. There are three types of costs: fixed, variable, and semi-variable costs. Each type is computed and analyzed. There are more than 30 pricing models though the pay-as-you-go model, subscription model, and pay-for-resources models are in demand. To consider and discuss the basics of cloud computing, emphasizing its economics and pricing models considering various aspects and costing components, using and estimating plans from various cloud Registering suppliers. The paper also considers identifying gaps, if any, present in the current pricing models that are highly preferred with other pricing models that are designed but not implemented due to practical conditions and fear of higher percentage of risk and error and to compare the basic prices provided by the cloud service providers.

Quality competition between national and store brands

The private label literature assumes that store brands (SBs) are of lower quality than competing national brands (NBs). To contest this notion, this paper examines the quality competition between a NB manufacturer and a SB retailer. The NB manufacturer sells its products through the retailer, and hence the manufacturer and the retailer are in competition. Once both parties decide the right quality level of their respective products, the retailer decides the retail prices for both brands. Using a general quality-dependent cost structure, we explicitly characterise both the price- and quality-level equilibriums under various channel power structures. We find that the SB might have a higher quality level than the NB even with no cost disparity, but will have a lower retail price than the NB, whether its quality is superior or not. Further, price and quality competitions have opposite implications for equilibrium solutions as well as profitability levels. Interestingly, the manufacturer may benefit from a more costly production or quality investment scenario, although both the retailer and the supply chain may suffer from it. The paper highlights the importance of accountability for quality decisions in the study of private label products.

Effective Algorithms for the Economic Lot-Sizing Problem with Bounded Inventory and Linear Fixed-Charge Cost Structure

Efficient algorithms for the economic lot-sizing problem with storage capacity are proposed. On the one hand, for the cost structure consisting of general linear holding and ordering costs and fixed setup costs, an OT2 dynamic programming algorithm is introduced, where T is the number of time periods. The new approach induces an accurate partition of the planning horizon, discarding most of the infeasible solutions. Moreover, although there are several algorithms based on dynamic programming in the literature also running in quadratic time, even considering more general cost structures and assumptions, the new solution uses a geometric technique to speed up the algorithm for a class of subproblems generated by dynamic programming, which can now be solved in linearithmic time. To be precise, the computational results show that the average occurrence percentage of this class of subproblems ranges between 13% and 45%, depending on both the total number of periods and the percentage of storage capacity availability. Furthermore, this percentage significantly increases from 13% to 35% as the capacity availability decreases. This reveals that the usage of the geometric technique is predominant under restrictive storage capacities. Specifically, when the percentage of capacity availability is below 50%, the average running times are on average 100 times faster than those when this percentage is above 50%. On the other hand, an OT on-line array searching method in Monge arrays can be used when the costs are non-speculative costs.

ОСОБЛИВОСТІ ІНВЕСТУВАННЯ ЦЕНТРІВ РОЗВИТКУ

The early years of a children’s life are very important for his or her health and development. Healthy development means that children of all abilities are able to grow up where their social, emotional and educational needs are met. The role of education is a key factor for an individual’s development. The role of education is a key factor for an individual’s development. After the 1980s the findings of educational research has shown that preschool age is a very important period in one’s development. Preschool education is becoming important in the new millennium because a child’s personality, emotions, cognitive and social abilities develop during the first five years. The article examines the expedience and effectiveness of opening a child development center. The preconditions for the creation of development centers have been studied. The number of functioning preschool institutions in the period from 2011 to 2019 and the number of children born in Ukraine for the corresponding period are analyzed. There is a negative trend towards a decrease in the number of children's educational institutions. Based on these studies, it was concluded that the network of schools does not meet the needs of the population of Ukraine. The calculation of financial indicators of the development center, calculation of break-even point and indicators of project efficiency were made. It is shown what income the center can have from the first year of activity. The dynamics of revenue for three years was also shown. The costs of opening the center are calculated and the dynamics of costs for three years is shown. The cost structure is also analyzed, that is the percentage of fixed and variable in the general cost structure of the enterprise is shown. How many highly qualified staff are needed to ensure the operation of the center, as well as the level of competitive wages were considered. Thus, based on the results of the study, it can be concluded that the opening of a child development center is not only a profitable business but also helps to solve the problems of parents with a lack of places in kindergartens and provide quality services for child development. The study is based on the latest statistics.

Joint production and pricing inventory system under stochastic reference price effect

We investigate a manufacturer’s joint dynamic production and pricing problem under stochastic reference price effect over an infinite horizon in a continuous-time framework. The demand for products, which depends on their price and a memory-based reference price, is uncertain and characterized by a stochastic process. The reference price effect varies across consumers and subjects to some randomness characterized by a stochastic process. A joint dynamic production and pricing problem to maximize the total expected profit is modeled as a stochastic optimal control problem. We give the sufficient conditions of the existence of the optimal solutions and characterize the solutions for the general convex cost structure. In addition, we show that the strategies in a linear feedback form of the state variables (i.e., inventory and reference price) are optimal for a strictly convex cost structure, and provide sufficient conditions of stability and monotone convergence properties for the expected steady-state inventory and reference price. Numerical examples and sensitivity analysis are performed to provide several important managerial insights. We find that the optimal production rate and sales price are each negatively related to the inventory stock while positively to the reference price level. In expected steady-state, demand uncertainty has no influence on optimal strategies while a higher reference price uncertainty would result in a lower production rate as well as shortage level but a higher (reference) price. Moreover, the manufacturer is worse off when demand uncertainty is increased, whereas he can generate more profit by taking advantage of the randomness of the reference price. Finally, we show that the expected steady-state production rate decreases, but price increases as the reference effect factor or customers’ memory parameter increases.

Economic impact of heart failure with preserved ejection fraction: insights from the ALDO-DHF trial.

AimsAlthough heart failure (HF) with preserved ejection fraction (HFpEF) is a leading cause for hospitalization, its overall costs remain unclear.Therefore, we assessed the health care‐related costs of ambulatory HFpEF patients and the effect of spironolactone.Methods and resultsThe aldosterone receptor blockade in diastolic HF trial is a multicentre, prospective, randomized, double‐blind, placebo‐controlled trial conducted between March 2007 and April 2011 at 10 sites in Germany and Austria that included 422 ambulatory patients [mean age: 67 years (standard deviation: 8); 52% women]. All subjects suffered from chronic New York Heart Association (NYHA) class II or III HF and preserved left ventricular ejection fraction of 50% or greater. They also showed evidence of diastolic dysfunction.Patients were randomly assigned to receive 25 mg of spironolactone once daily (n = 213) or matching placebo (n = 209) with 12 months of follow‐up. We used a single‐patient approach to explore the resulting general cost structure and included medication, number of general practitioner and cardiologist visits, and hospitalization in both acute and rehabilitative care facilities.The average annual costs per patient in this cohort came up to €1, 118 (±2,475), and the median costs were €332. We confirmed that the main cost factor was hospitalization and spironolactone did not affect the overall costs. We identified higher HF functional class (NYHA), male patients with low haemoglobin level, with high oxygen uptake (VO2max) and coronary artery disease, hyperlipidaemia, and atrial fibrillation as independent predictors for higher costs.ConclusionsIn this relatively young, oligosymptomatic, and with regard to the protocol without major comorbidities patient cohort, the overall costs are lower than expected compared with the HFrEF population. Further investigation is needed to investigate the impact of, for example, comorbidities and their effect over a longer period of time. Simultaneously, this analysis suggests that prevention of comorbidities are necessary to reduce costs in the health care system.

On value functions for FCFS queues with batch arrivals and general cost structures

We develop a unified framework for analyzing and optimizing costs for systems of FCFS queues with batch arrivals, setup delays and a general nonlinear cost structure that includes costs associated with energy used, setup times and Quality of Service (QoS) measures. We focus on the MX/G/1 and GeoX/G/1 queues with i.i.d. service times, but our results hold also for arbitrary i.i.d. batch structures where service times within a batch may depend on the batch size and have different, possibly dependent, distributions. We use the notion of value functions from the theory of Markov decision processes (MDPs), along with exponential cost functions, to develop the notion of, and simple expressions for, value generating functions. These can be used to find efficient energy control and job dispatching policies.

A perturbation-based approach for continuous network design problem with link capacity expansion

This paper formulates a continuous network design problem (CNDP) as a nonlinear mathematical program with complementarity constraints (NLMPCC) and then a perturbation-based approach is proposed to overcome the NLMPCC problem and the lack of constraint qualifications. This formulation permits a more general route cost structure and every stationary point of it corresponds to a global optimal solution of the perturbed problem. The contribution of this paper from the mathematical perspective is that, instead of using the conventional nonlinear programming methodology, variational analysis is taken as a tool to analyse the convergence of the perturbation-based method. From the practical point of view, a convergent algorithm is proposed for the CNDP and employs the sequential quadratic program (SQP) solver to obtain the solution of the perturbed problem. Numerical experiments are carried out in both 16 and 76-link road networks to illustrate the capability of the perturbation-based approach to the CNDP with elastic demand. Results showed that the proposed model will solve a wider class of transportation equilibrium problems than the existing ones.

A perturbation-based approach for continuous network design problem with link capacity expansion

This paper formulates a continuous network design problem (CNDP) as a nonlinear mathematical program with complementarity constraints (NLMPCC) and then a perturbation-based approach is proposed to overcome the NLMPCC problem and the lack of constraint qualifications. This formulation permits a more general route cost structure and every stationary point of it corresponds to a global optimal solution of the perturbed problem. The contribution of this paper from the mathematical perspective is that, instead of using the conventional nonlinear programming methodology, variational analysis is taken as a tool to analyse the convergence of the perturbation-based method. From the practical point of view, a convergent algorithm is proposed for the CNDP and employs the sequential quadratic program (SQP) solver to obtain the solution of the perturbed problem. Numerical experiments are carried out in both 16 and 76-link road networks to illustrate the capability of the perturbation-based approach to the CNDP with elastic demand. Results showed that the proposed model will solve a wider class of transportation equilibrium problems than the existing ones.

An optimal stopping approach for the end-of-life inventory problem

We consider the end-of-life inventory problem for the supplier of a product in its final phase of the service life cycle. This phase starts when the production of the items stops and continues until the warranty of the last sold item expires. At the beginning of this phase the supplier places a final order for spare parts to serve customers coming with defective items. At any time during the final phase the supplier may also decide to switch to an alternative and more cost effective service policy. This alternative policy may be in the form of replacing defective items with substitutable products or offering discounts/rebates on the new generation ones. In this setup, the objective is to find a final order quantity and a time to switch to an alternative policy which will minimize the total expected discounted costs of the supplier. The switching time is a stopping time and is based on the realization of the arrival process of defective items. In this paper, we study this problem under a general cost structure in a continuous-time framework where the arrival of customers is given by a non-homogeneous Poisson process. We show in detail how to compute the value function, and illustrate our approach on numerical examples.

Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints

We consider the classical stochastic multi-armed bandit problem with a constraint that limits the total cost incurred by switching between actions to be no larger than a given switching budget. For this problem, we prove matching upper and lower bounds on the optimal (i.e., minimax) regret, and provide efficient rate-optimal algorithms. Surprisingly, the optimal regret of this problem exhibits a non-conventional growth rate in terms of the time horizon and the number of arms. Consequently, we discover surprising regarding how the optimal regret rate changes with respect to the switching budget: when the number of arms is fixed, there are equal-length phases, where the optimal regret rate remains (almost) the same within each phase and exhibits abrupt changes between phases; when the number of arms grows with the time horizon, such abrupt changes become subtler and may disappear, but a generalized notion of phase transitions involving certain new measurements still exists. The results enable us to fully characterize the trade-off between the regret rate and the incurred switching cost in the stochastic multi-armed bandit problem, contributing new insights to this fundamental problem. Under the general switching cost structure, the results reveal interesting connections between bandit problems and graph traversal problems, such as the shortest Hamiltonian path problem.

Distribution-Free Inventory Risk Pooling in a Multilocation Newsvendor

We study a multilocation newsvendor network when the only information available on the joint distribution of demands are the values of its mean vector and covariance matrix. We adopt a distributionally robust model to find inventory levels that minimize the worst-case expected cost among the distributions consistent with this information. This problem is NP-hard. We find a closed-form tight bound on the expected cost when there are only two locations. This bound is tight under a family of joint demand distributions with six support points. For the general case, we develop a computationally tractable upper bound on the worst-case expected cost if the costs of fulfilling demands have a nested structure. This upper bound is the optimal value of a semidefinite program whose dimensions are polynomial in the number of locations. We propose an algorithm that can approximate general fulfillment cost structures by nested structures, yielding a computationally tractable heuristic for distributionally robust inventory optimization on general newsvendor networks. We conduct experiments on networks resembling U.S. e-commerce distribution networks to show the value of a distributionally robust approach over a stochastic approach that assumes an incorrect demand distribution. This paper was accepted by Chung Piaw Teo, optimization.

Distribution-free Inventory Risk Pooling in a Multi-location Newsvendor

We study a multi-location newsvendor network when the only information available on the joint distribution of demands are the values of its mean vector and covariance matrix. We adopt a distributionally robust model to find inventory levels that minimize the worst-case expected cost among the distributions consistent with this information. This problem is NP-hard. We find a closed-form tight bound on the expected cost when there are only two locations. This bound is tight under a family of joint demand distributions with six support points. This result extends the well-known Scarf (1958) bound for a single location. For the general case, we develop a computationally tractable upper bound on the worst-case expected cost if the costs of fulfilling demands have a nested structure. This upper bound is the optimal value of a semidefinite program whose dimensions are polynomial in the number of locations. We propose an algorithm that can approximate general fulfillment cost structures by nested structures, yielding a computationally tractable heuristic for distributionally robust inventory optimization on general newsvendor networks. We conduct experiments on networks resembling U.S. e-commerce distribution networks to show the value of a distributionally robust approach over a stochastic approach that assumes an incorrect demand distribution.

The importance of non-monetary cost in start-up and annual cacao (Theobroma cacao L) production activities in Santander, Colombia

Based on a double-phase methodology (grouping by cluster method and costing) the costs of three activities of cacao establishment and annual management in San Vicente de Chucuri and El Carmen de Chucuri (Santander, Colombia) were structured. The grouping phase identified two productive typologies, one with low technification level and another with a medium level; moreover, technification levels were corroborated through cost structuring, in which, for all the activities, the medium technification typology generated higher average values than the low one. General cost structures showed that the most important item is labor, followed by inputs and plant material. The disaggregation of costs into monetary and non-monetary (implicit cost) showed that producers with low technification and low frequency of input use present 35% of non-monetary costs per tree, while producers with some level of crop management and relatively high execution of activities have a slightly higher non-monetary cost, 45% of the average total cost per tree. Within non-monetary costs, the labor (mainly family labor) contributed, on average, to 34% of the total cost structures, which constitutes a risk management factor when defining the financial equilibrium point of the cacao production activity.

Comparative Analysis of Additive Manufacturing over Conventional Manufacturing

Over several years additive manufacturing has grown and displaced traditional methods. Present market was occupied by 3D printers in rapid prototyping field. Numerous examples are indicated where additive manufacturing has entered new markets and picked up larger part advertise. In this task we investigate the use of additive manufacturing over customary assembling and the possibility of the disturbance of conventional techniques like injection molding. The possibility is dictated by a similar examination of the cost to influence parts according to bunch premise. We at that point decided the make back the initial investment point and the relationship to the general cost structure.