Oil price dynamics and airline earnings predictability

This study examines the effect of oil price dynamics on quarterly earnings and their predictability with a sample of 30 airlines for 1994–2017. First, we document a significantly positive impact of demand-driven oil shocks on airline earnings, suggesting that the revenue effect from shifting air travel demands dominates the cost effect of aviation fuels. Regarding earnings predictability, we find evidence of deterioration in oil-volatile quarters as indicated by both the earnings variability based on common benchmarks and the quality of analyst forecasts issued early in the quarter. We further show that supply-driven oil shocks have a more detrimental impact on earning predictability than demand-driven oil shocks. Finally, we do not find supporting evidence for the possible moderating effect of hedging.     

A theory of supplier network-based innovation value

To understand how a supplier helps a buying company create value through innovations, studies have focused on a supplier's internal resources or its relationship with a buying company. Building upon this body of literature, we develop a theory of supplier network-based innovation value in this conceptual paper. This theory explains how a supplier's upstream and downstream value network can be a source of competitive advantage for a buying company. Specifically, it proposes that the levels and types of supplier innovation value is contingent on the configuration of a dual-ego value network, characterized by the locus and degree of buyer-supplier structural equivalence. This theory also explains how a supplier's ties with a buying firm's competitors can pose both opportunity and risk to buying company innovation. This theory contributes to the literature by showing when “seemingly undesirable” suppliers, due to a lack of technical capability or strong relationship with a buying company, might still be valuable to a buying company's innovation.     

Analyzing the impact of intermodal-related risk to the design and management of biofuel supply chain

This study presents a mathematical model that designs a reliable multi-modal transportation network for a biofuel supply chain system, where intermodal hubs are subject to site-dependent probabilistic disruptions. The disruption probabilities of intermodal hubs are estimated by using a probabilistic model which is developed using real world data. We developed an accelerated Benders decomposition algorithm to solve this challenging NP-hard problem. Numerical analysis show that the model selects to use intermodal hubs located in areas with low disruption probabilities. In case of a disaster, the reliable solution results in 6.21% savings over the minimum cost solution.     

Supply chain management executives in corporate upper echelons

Supply chain strategies and their implementation have been recognized as a source of competitive advantage. According to the principle “structure follows strategy”, we expect the number of firms having supply chain management (SCM) functions represented on their top management team (TMT) to have increased in the past years. However, little is known about the degree to which executives responsible for SCM functions (i.e., Chief Supply Chain Officers) are present or absent in TMTs and if their presence is related to firm performance. Therefore, we study the TMTs of large US corporations and show that SCM is present in upper echelons, either through executives whose responsibilities explicitly include SCM or indirectly by executives, especially CEOs, who had acquired SCM experience in their previous positions. However, firms׳ operating margins are lower when a Chief Supply Chain Officer is present in the TMT.     

Exploring impact factors of shippers’ risk prevention activities: A European survey in transportation

This paper reports results of a survey examining the impact factors for shippers to implement risk prevention activities. A regression analysis illustrates the relations between risk and quality related impact factors and the shippers’ ability to implement risk prevention activities. The study identifies the corporate risk culture and product vulnerability as main impact factors for the implementation of prevention activities in transportation. This paper will be beneficial for transportation managers considering the implementation of risk prevention activities in the transportation field, and will support further empirical research in the transportation management and supply chain risk management research area.     

Price promotion with reference price effects in supply chain

We consider the price promotion in a supply chain comprising one manufacturer and one retailer, who take into account the reference price effects of consumers. The problem is analyzed as a manufacturer-lead Stackelberg game. The results indicate that reference price effects could mitigate “double marginalization” effects, and improve the channel efficiency. We also show that the optimal price promotion benefits the manufacturer, retailer and consumers in consumer promotion model. Furthermore, we provide the conditions under which the retailer has an interest in offering price promotion to consumers. Finally, we employ numerical analysis to demonstrate more managerial insights.     

Effects of carbon emission reduction policies on transportation mode selections with stochastic demand

We are witnessing more frequent extreme weather events due to the global warming. There is an urgent need for governments, industries, general public, and academics to take coordinated actions in order to tackle the challenges imposed by the climate change. It is essential to incorporate the environmental objective in the transportation mode selection problem as transportation is a main contributor to carbon emissions. With this in mind, our paper studies the retailer’s ordering and transportation mode selection problem using stochastic customer demand and investigates the optimal ordering and transportation mode selection decisions under different carbon emission reduction policies. Our analytical results reveal that there are some important transportation mode shifting thresholds under different carbon emissions reduction policies. These findings do not only help firms to make optimal decisions under different carbon emission reduction policies but also support policy makers to develop effective policies on carbon emissions reduction.     

Delivery leadtime and channel structure decisions for make-to-order duopoly under different game scenarios

We develop game-theoretic models to explore the quoted delivery leadtime, price, and channel structure decisions for a make-to-order duopoly system under three game scenarios. Under the integrated-manufacturer first scenario, we find that (i) decentralization of the supply chain increases quoted leadtime; and (ii) both manufacturers may choose different channel structures under symmetric duopoly. By comparing with the symmetric scenario and the retailer first scenario, we find that a manufacturer facing a decentralized rival adopts decentralization when leadtime sensitivity, leadtime cost, and price elasticity are very small; the effect of decentralization on quoted leadtime largely depends on game scenario.     

A Generalized Nash Equilibrium network model for post-disaster humanitarian relief

We develop a Generalized Nash Equilibrium network model for post-disaster humanitarian relief by nongovernmental organizations (NGOs). NGOs derive utility from providing relief supplies to victims of the disaster at demand points in a supply chain context while competing with each other for financial funds provided by donations. The shared constraints consist of lower and upper bounds for demand for relief items at the demand points to reduce materiel convergence or congestion. This game theory problem is reformulated as an optimization problem and numerical examples and a theoretical case study on Hurricane Katrina given.     

A contingent plan for disaster response

Natural and man-made disasters imply a great deal of uncertainty in terms of potential damage, though it is certain that there would be a huge spike in the demand for relief supplies causing shortages and/or delays in providing aid. Ruptures in the infrastructure (roads, utility, and communication lines) cause additional delays due to repairs. Therefore, the relief providers need to work in collaboration with retailers, and infrastructure service providers for improving responsiveness. The relief providers (government and non government) rely on acquiring and delivering supplies in real time because such actions accompany little risk of resource underutilization, though the cost of real time acquisitions can be high. In contrast, a proactive response, while minimizing acquisition cost, can be very ineffective if demand surges are high. We study a hybrid of reactive and proactive approaches, where the reactive response is contingent upon the disaster intensity exceeding a certain threshold. We show how the threshold value may impact capacity acquisitions and prices and establish the optimality of contingent response. Further, we establish how an infrastructure contract may help reducing the social cost of disaster.