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Optimal Robust Inventory Management with Volume Flexibility: Matching Capacity and Demand with the Lookahead Peak-Shaving Policy
No full textWe study inventory control with volume flexibility: A firm can replenish using period-dependent base capacity at regular sourcing costs and access additional supply at a premium. The optimal replenishment policy is characterized by two period-dependent base-stock levels but determining their values is not trivial, especially for non-stationary and correlated demand. We propose the Lookahead Peak-Shaving policy that anticipates or peak shaves orders from future peak-demand periods to the current period, thereby matching capacity and demand. Peak shaving anticipates future order peaks and partially shifts them forward. This contrasts with conventional smoothing, which recovers the inventory deficit resulting from demand peaks by increasing later orders. Our contribution is three-fold. Firstly, we use a novel iterative approach to prove the robust optimality of the Lookahead Peak-Shaving policy. Secondly, we provide explicit expressions of the period-dependent base-stock levels and analyze the amount of peak shaving. Finally, we demonstrate how our policy outperforms other heuristics in stochastic systems. Most cost savings occur when demand is non-stationary and negatively correlated, and base capacities fluctuate around the mean demand. Our insights apply to several practical settings, including production systems with overtime, sourcing from multiple capacitated suppliers, or transportation planning with a spot market. Applying our model to data from a manufacturer reduces inventory and sourcing costs by 6.7%, compared to the manufacturer's policy without peak shaving
Do you hear my accent? How nonnative English speakers experience conflictual conversations in the workplace
No full textPurpose The purpose of this paper is to investigate the experiences of nonnative speakers in conflictual situations with native speakers in the workplace. In three studies, the authors examine whether nonnative speakers experience stereotype threat in workplace conflict situations with native speakers, whether stereotype threat is associated with certain conflict managing behaviors (e.g. yielding and avoiding) and the relationship between stereotype threat, satisfaction with conflict outcomes and processes, and objective conflict outcomes. Design/methodology/approach Studies 1 and 2 use critical incident recall methodology to examine nonnative speakers’ conflict behaviors and satisfaction with conflict outcomes. In Study 3, data were collected from a face-to-face simulation with a random-assignment design. Findings Findings suggest that nonnative speakers indeed experience heightened stereotype threat when interacting with native speakers in conflict situations and the experience of stereotype threat leads to less satisfaction with conflict outcomes, perceptions of goal attainment, as well as worse objective conflict outcomes. Originality/value The current study is one of the first studies to document the effects of accent stereotype threat on conflict behaviors and outcomes. More broadly, it contributes to the conflict studies literature by offering new insight into the effects and implications of stereotype threat on workplace conflict behaviors and outcomes
Academy of Management Proceedings
No full textAligning CEO compensation with environmental sustainability is one of the primary channels through which firms which firms can improve their environmentally sustainability. In this study, we investigate the effect of board-level environmental expertise on the use of environmental criteria in CEO compensation. Using hand-collected data on environmental criteria from a European sample, we show that environmental expertise is positively associated with the use of environmental criteria. Moreover, we explore several mechanisms for the use of expertise, and find that in countries with lower environmental awareness, environmental expertise is more strongly associated with the likelihood of using environmental criteria
Deep reinforcement learning for inventory control: A roadmap
No full textDeep reinforcement learning (DRL) has shown great potential for sequential decision-making, including early developments in inventory control. Yet, the abundance of choices that come with designing a DRL algorithm, combined with the intense computational effort to tune and evaluate each choice, may hamper their application in practice. This paper describes the key design choices of DRL algorithms to facilitate their implementation in inventory control. We also shed light on possible future research avenues that may elevate the current state-of-the-art of DRL applications for inventory control and broaden their scope by leveraging and improving on the structural policy insights within inventory research. Our discussion and roadmap may also spur future research in other domains within operations management
New summary measures and datasets for the multi-project scheduling problem
No full textIn recent years, more researchers have devoted their attention to the resource-constrained multi-project scheduling problem, resulting in a growing body of knowledge on solution procedures. A key factor in the comparison of these procedures is the availability of benchmark datasets that cover a large part of the feature space. Otherwise, one risks that the conclusions from experiments on these sets do not hold when they are repeated on a different set. In this paper we propose new multi-project datasets that contain instances with a wide variety of characteristics. We first develop several new measures that describe three types of portfolio characteristics, two of the three types are not present in any of the existing datasets. Second, an algorithm is developed that can generate instances with the desired parameter values in a controlled manner. With this procedure, we create three datasets that each focus on one of the characteristics and a fourth dataset that contains all combinations. The computational results show (a) that these sets cover a significantly larger part of the feature space than existing benchmark libraries and (b) that they are more challenging for advanced algorithms.We acknowledge the support provided by the Special Research Fund [BOF grant no. DOC014-18 Van Eynde] and the National Bank of Belgium for providing the first author with a pre-doctoral fellowship. The computational resources (Stevin Supercomputer Infrastructure) and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by Ghent University, FWO and the Flemish Government department EWI
Lending when relationships are scarce: The role of information spread via bank networks
No full textWe investigate how information flows within bank networks facilitate syndicate formation and lending in the leveraged buyout (LBO) market, where relationships between banks and borrowers are scarce and borrower opacity is high. Using novel measures that characterize a bank's ability to source and disseminate information within its loan syndication network, we show that the extent of this capability influences which banks join the syndicate, the share the lead bank holds, and LBO borrowing terms. Banks' ability to source and disseminate network-based information is particularly useful when ties to prospective borrowers are lacking, with the information flows extending beyond knowledge on PE firms and LBO targets
Reconsidering the Notion of “Operating Model” in the context of Innovation and Transformation. A Systematic Literature Review
No full textThe notion of Operating Model (OM) is frequently used in the academic and practitioner-related literature, as well as in publications written by major consultancy firms. Despite its popularity, the concept is not unambiguously used, creating some issues in interpretation, and understanding. To fill this gap, we offer a Systematic Literature Review (SLR) to better capture the dynamic environment in which businesses take part. We have looked at the use of the concept in a context defined by innovation and transformation. Our goal was to investigate which decisions are made using the lens of OM. We have compared definitions, listed properties and boundaries of the notion of OM, as well as identified decision topics. We end this article by providing avenues for future research