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A new policy for joint optimization of age replacement and spare provisioning has been proposed by incorporating a continuous review (s, S) type inventory policy, where s is the reorder level and S is the maximum stock level. Gives cost formulations for a single operating unit situation and outlines simulation procedure to determine optimal values of the decision variables by minimizing total cost of replacement and inventory. Studies the behaviour of this policy for a large number of case problems and highlights the effects of different cost elements, item failure characteristics and lead time characteristics. Also determines, for all case problems, optimal (s, S) policies to support Barlow‐Proschan age policy. Simulation results clearly indicate that the jointly optimal policy is more cost‐effective than Barlow‐Proschan policy.

The purpose of this paper is to study the optimal contact policies for customers that belong to the mass affluent market.

The authors formulate a stochastic dynamic programming model to determine the optimal frequency of contacts in order to maximize the expected return of the company.

The authors show that personalized marketing strategies provide a competitive advantage to companies that contact their customers directly through, for example, phone calls or meetings. The authors show that a threshold policy is only optimal for customers with increasing sensitivity to contact. In all other cases, optimal policies might have a less intuitive structure. The authors also study the importance of the size of the customer database and determine the optimal maximum recency when maintenance costs are present.

Contact policies should be tailored for each company/industry individually, due to their sensitivity to customers’ purchasing behavior.

En este artículo se estudian políticas óptimas de contacto de clientes que pertenecen al segmento de mercado con alto poder adquisitivo.

Para ello formulamos un modelo de programación dinámica estocástica para determinar la frecuencia óptima de contactos durante un período de tiempo, de modo de maximizar el beneficio esperado de la empresa.

Los resultados muestran que una estrategia de marketing personalizada entrega una herramienta competitiva a aquellas empresas que contactan directamente a sus clientes, a través, por ejemplo, de llamadas telefónicas o reuniones periódicas. También se muestra que las políticas con un umbral a partir del cual es óptimo contactar a todos los clientes son óptimas solo en el caso de clientes con una creciente sensibilidad al contacto. En todos los otros casos, las políticas óptimas tienen una estructura menos intuitiva. Finalmente, se estudia el tamaño óptimo de la base de datos de clientes y hasta que antigüedad es recomendable mantenerlos en el sistema.

Las políticas de contacto a clientes deberían ser confeccionadas a la medida de las características individuales de la empresa, puesto que ellas son altamente sensibles al comportamiento de compra de los clientes.

The purpose of this paper is to explain how eventual pressures from national lobbies may lead governments to shift from an optimal into a non‐optimal innovation policy.

A theoretical model is developed in order to examine and explain the growth and welfare effects of optimal and non‐optimal innovation policies. The non‐optimal policy corresponds to a subsidy for national innovators that is equivalent to an optimal policy of incentives (tax cuts) to foreign investors. Since we are assessing what can nationals do with the support that could be oriented to foreign firms, we are measuring what the economy loses for not supporting foreign firms.

The authors find welfare loss when supporting national R&D instead of foreign R&D and conclude that the same support given to innovation can produce strikingly different outcomes depending on who receives the support.

The analysis allows the impact of the inefficiency caused by policies that are not sound, from a strictly economic point of view, to be measured.

The originality of the paper is related to the assessment of the implications and to the measurement of the effects of non‐optimal R&D policies.

The purpose of this paper is to characterize the optimal ordering and allocation policy for a store replenishment decision in the context of an omnichannel retailer in a franchise network. The authors further show that a myopic policy is optimal, which circumvents the curse of dimensionality for the multi-period inventory model and help store managers optimize their decisions about the amount of inventory to stock for both online and offline demands and the percentage of inventory to reserve for online orders.

This research is trigged by several managerial studies which suggest reserving a certain percentage of the in-store inventory for online orders as a good store inventory allocation practice for omnichannel retailers in a franchise network. The authors used an analytical model to develop this practice by clarifying how store managers can decide on the amount of inventory to replenish and the percentage to reserve for online orders.

This study develops a finite horizon, periodic review inventory model to identify an optimal and dynamic replenishment and allocation policy. The analysis uncovers the system’s fundamental structural property concavity. The research shows that, due to this property, the optimal replenishment policy is a base-stock policy. The latter is due to the base stock level being independent of the initial inventory at hand, and the optimal allocation level being non-decreasing on the base-stock level.

This study contributes to the literature on store inventory management for omnichannel retailers in a franchise network by investigating their optimal store inventory ordering and allocation policy. Nevertheless, the zero-lead time and zero-setup cost assumptions limit the findings.

Insights into an optimal store inventory policy may guide franchisee store managers to decide on the amount of inventory to replenish and the percentage to reserve for online orders.

The originality of this paper lies in its focus on in-store inventory management for omnichannel retailers in a franchise network. The findings are helpful for franchisor retailers to implement the omnichannel strategy at the level of in-store inventory management. Beyond using incentive systems, the franchisor should leverage legitimate powers by mentioning a relevant measure in their contracts with their franchisee to minimize their channel conflicts and ensure their customers have seamless shopping experiences.

From 2007, New Zealand firms must report the cost of granting employee stock options (ESOs). Market‐based option pricing models assume that option holders are unconstrained in their portfolio choices and thus are indifferent to the specific risk of any firm. By contrast, ESO holders are frequently required to hold portfolios that are over‐exposed to the firm that employs them and so adopt exercise policies that reflect their individual risk preferences. Applying the model of Ingersoll (2006) to hypothetical ESOs, we show that ESO cost can be extremely sensitive to employee characteristics of risk aversion and under‐diversification. This result casts doubt on the usefulness of any market‐based model for pricing ESOs, since such models, by definition, produce option values that are independent of employee characteristics. By limiting employee discretion over the choice of exercise date, vesting restrictions help reduce the magnitude of this problem.

Opportunistic maintenance (OM) policy is a prospective maintenance approach that instigates for a more effective and optimized system. The purpose of this paper is to provide the steps and methods used in model development processes for the application of the OM policy.

Dubbed as opportunistic principle toward optimal maintenance system (OPTOMS) for OM policy toward optimal maintenance system, the model is devised as a decision support system model and contains five phases. The motivation and focus of the model resolve around the need for a practical framework or model of maintenance policy for the application in an industry. In this paper, the OPTOMS model was verified and validated to ensure that the model is applicable in the industry and robust as a support system in decision making for the optimal maintenance system.

From the verification steps conducted in a case study company, it was found that the developed model incorporated simple but practical tools like check sheet, failure mode and effect analysis (FMEA), control chart that has been commonly used in the industry.

This paper provides the general explanations of the developed model and tools used for each phase in implementing OM to achieve an optimal maintenance system. Based on a case study conducted in a semiconductor company, the OPTOMS model can align and prepare the company in increasing machine reliability by reducing machine downtime.

The novelty of this paper is based on the in-depth discussion of all phases and steps in the model that emphasize on how the model will become practical theories in conducting an OM policy in a company. The proposed methods and tools for data collection and analysis are practical and commonly used in the industry. The framework is designed for practical application in the industry. The users would be from the Maintenance and Production Department.

The purpose of this paper is the simultaneous determination of optimal replacement threshold and inspection scheme for a system within condition-based maintenance (CBM) framework.

A proportional hazards model (PHM) is used for risk of failure and a Markovian process to model the system covariates. Total expected long-run cost (including replacement, inspection and downtime costs) is formulated in terms of replacement threshold and inspection scheme. Through an iterative procedure, for all different values of replacement thresholds, their associated optimal inspection scheme is determined using an effective search algorithm. By evaluating the corresponding costs, the optimal replacement threshold and its associated optimal inspection scheme are, then, identified.

The mathematical formulation, that takes into account all different costs, required for the simultaneous determination of optimal replacement threshold and optimal inspection scheme for an item subjected to CBM using PHM is provided. The proposed approach is compared against classical age policy and one state-of-the-art policy through a numerical example. The results show that the proposed approach outperforms other comparing policies.

In practical situations where CBM is implemented, inspections and downtime often incur cost. Under such circumstances, findings of this paper can be utilized for the determination of optimal replacement threshold and optimal inspection scheme so that the CBM cost is minimized.

In most of the reported researches, it is often assumed that inspections have no cost and/or that the time for replacements (either preventive or at failure) is negligible. In the contrary, in this paper the author takes all cost factors including inspection costs, replacement time(s) and their associated downtime costs into account in the simultaneous determination of optimal replacement threshold and optimal inspection scheme.

Order picking is one of the most costly logistics processes in warehouses. As a result, the optimization of order picking processes has received an increased attention in recent years. One potential source for improving order picking is the reduction of picker blocking. The purpose of this paper is to investigate picker blocking under different storage assignment and order picker-route combinations and evaluate its effects on the performance of manual order picking processes.

This study develops an agent-based simulation model (ABS) for order picking in a rectangular warehouse. By employing an ABS, we are able to study the behaviour of individual order pickers and their interactions with the environment.

The simulation model determines shortest mean throughput times when the same routing policy is assigned to all order pickers. In addition, it evaluates the efficiency of alternative routing policies–storage assignment combinations.

The paper implies that ABS is well-suited for further investigations in the field of picker blocking, for example, with respect to the individual behaviour of agents.

Based on the results of this paper, warehouse managers can choose an appropriate routing policy that best matches their storage assignment policy and the number of order pickers employed.

This paper is the first to comprehensively study the effects of different combinations of order picker routing and storage assignment policies on the occurrence of picker blocking.

This paper explores the effects of fiscal policy in an economy with reciprocity in labor relations and fair wages, consumption taxes and a common income tax rate in place.

To this end, a dynamic general-equilibrium model with government sector is calibrated to Bulgarian data (1999–2018). Two regimes are compared and contrasted – the exogenous (observed) vs optimal policy (Ramsey) case. The focus of the paper is on the relative importance of consumption vs income taxation, as well as on the provision of utility-enhancing public services. Bulgarian economy was chosen as a case study due to its major dependence on consumption taxation as a source of tax revenue.

(1) The optimal steady-state income tax rate is zero; (2) the benevolent Ramsey planner provides the optimal amount of the utility-enhancing public services, which are now three times lower; (3) the optimal steady-state consumption tax needed to finance the optimal level of government spending is 18:7%.

This is the first study on optimal fiscal policy with reciprocity in labor relations.