In this study, an optimal maintenance policy is developed for a k-out-of-n: G system subject to two types of maintenance services, preventive maintenance and corrective maintenance. We investigate the optimal replacement age when a component failure is not detected immediately until a k-out-of-n: G system fails. The optimal maintenance policy is determined to minimize the expected total system cost when a generalized block replacement model is developed using downtime period. It is assumed that component failures are not monitored until a system failure, thus, a k-out-of-n: G system failure occurs. The downtime period of each failed component using order statistics for life time and age distributions for a k-out-of-n: G system is investigated. Numerical examples are discussed in order to demonstrate the applicability of the methodology derived from this paper.

In a demand driven market, optimal allocation of capacity to the demand has been one of the major issues. In this paper, we consider a single global freight firm allocating its capacity to its own regional sales offices. The firm sells cargo space based on two types of contracts: long-term and spot sales. Regional sales offices utilize their effort to generate more demand in their designated region. In other words, it is assumed that the demand is dependent on their efforts. First, we find a closed-form solution for the optimal level of the efforts of a single sales office in a specific region. Then, we study the case when the firm allocates its limited total capacity to two sales offices. We investigate different methods of capacity allocation: decentralization, centralization, and mixed, by conducting numerical studies. Different from the traditional finding, we suggest that the decentralization method is not always dominated by the centralization method.

This study employs a novel perspective to assess corporate social responsibility (CSR) as a way of advertising by focusing on the biohealth industry. The biohealth industry is emerging as an important contributor to society, as its business operations directly affect people’s lives. The industry is based on intensive research and development (R&D). Based on CSR’s positive role in building brand equity, we examine whether the effect of CSR performance is positively associated with firm valuation and the effects of R&D. Further, we assess the interplay between CSR performance and R&D in the biohealth industry. The study also examines the moderating role of CSR performance on the interacting effect of traditional advertising and R&D on firm valuation. This highlights the relationship between R&D as strategic investment, strategic employment of CSR as advertising, and traditional advertising.

The office environment has changed rapidly due to the recent COVID-19 outbreak. Companies consider various types of remote work environments to contain the spread of the virus. Among them, a satellite office is a type of remote work environment where a number of employees are allocated to their nearest office. The benefits from satellite offices are twofold: The significant reduction of travel distance also reduces the amount of carbon emission and fuel consumption. In addition, dividing employees into smaller groups significantly reduces the potential risks of infection in the office. This paper addresses a satellite office allocation problem that considers social and environmental sustainability and infection control at work. In order to evaluate the effect of different satellite office allocation, quantitative measures are developed for the following three criteria: carbon emission, fuel consumption, and the probability of infection occurrence at work. Simulation experiments are conducted to investigate different scenarios of regional infection rate and modes of transportation. The results show that adopting satellite offices not only reduces carbon emission and fuel consumption, but also mitigates business disruption in the pandemic.

To optimize the firm’s profit during a finite planning horizon, a dynamic programming model is used to make joint pricing and inventory replenishment decision assuming that customers are loss averse and the firm is risk averse. We model the loss averse customer’s demand using the multinomial choice model. In this choice model, we consider the acquisition and transition utilities widely used by a mental accounting theory which also incorporate the reference price and actual price. Then, we show that there is an optimal inventory policy which is base‐stock policy depending on the accumulated wealth in each period.