No abstract

Quick response is a supply chain practice that can help improve operations by responding quickly to market changes. In particular, when retailers are perfectly rational and risk neutral, quick response is known to be a highly beneficial strategy to the retailers. However, in practice, retailers may possess different kinds of unstable risk preferences, which include risk‐averse and risk‐seeking attitudes. Thus, retailers may be stochastically risk sensitive. In this article, we consider all these factors simultaneously and explore how the retailer's stochastic risk preference affects the values of quick response to the supply chain and its members. Among various findings, we show that quick response is always beneficial to the supply chain when the retailer is stochastically risk sensitive. In most cases, we demonstrate that if the retailer is more risk averse (risk seeking) stochastically, the retailer is benefited more, whereas the manufacturer suffers a smaller profit loss (a bigger profit loss), under quick response. We prove that different commonly used supply chain contracts can achieve robust Pareto improvement in the supply chain. We also uncover that if the manufacturer ignores the retailer's stochastic risk preference, the achievability of Pareto improvement by contracts will be negatively affected.

Platform operations are very common in the sharing economy. Nowadays, retailers can sell the end‐of‐season product leftovers to platforms which offer product rental services to the market. Motivated by this observed industrial practice, we build stylized supply chain models to explore the platform supported supply chain operations. We uncover that the presence of the platform creates the “triple marginalization” problem in which supply chain coordination cannot be achieved even if the manufacturer is willing to supply at cost using the wholesale pricing contract. We show how the markdown sponsor (MS) contract can deal with the triple marginalization problem and achieve supply chain coordination. However, we illustrate that a moral hazard problem, in which the retailer has incentive to overclaim the amount of markdown sponsor, arises. We reveal that the moral hazard problem brings a loss to the manufacturer, an immoral gain for the retailer, and there is no impact on the platform and consumers. We analytically derive the impact of moral hazard (which means the loss to the manufacturer, and the gain for the retailer) and find that it relates to the markdown sponsor rate, as well as the degree of overclaiming. To overcome the moral hazard problem under MS contract, we propose measures such as the adoption of blockchain technology, and “discounted” markdown sponsor contract, to help. We also explore the implementations of other contracts to overcome the moral hazard, like virtual buyback with inventory reallocation contract, and wholesale pricing contract with side payments.

The classical newsvendor problem seeks to minimize the expected inventory cost or maximize the expected profit. But optimizing an expected value alone does not fully capture the stochastic nature of the newsvendor problem. Inspired by the higher‐moment analyses explored in finance literature, we conduct a mean‐variance‐skewness‐kurtosis (MVSK) analysis for the newsvendor problem. We first derive the analytical expressions for the profit’s mean, variance, skewness, and kurtosis in the standard newsvendor setting, and reveal their structural properties. We then establish various MVSK optimization problems and find the solution to each of them. We show that kurtosis aversion always induces the newsvendor to order less, while skewness seeking can induce the newsvendor to order either more or less depending on the specific structure of the profit’s skewness, which is affected by the symmetric and asymmetric properties of the demand distribution. Finally, based on the Pareto‐optimality concept, we address the challenge of supply chain coordination (SCC) in the presence of MVSK agents in two specific cases: (i) each agent maximizes its MVSK‐objective‐function and (ii) each agent maximizes its expected profit function, subject to given constraints on the profit’s variance, skewness, and kurtosis. In each case, we explore whether and how the supply chain can be coordinated. We find that considering the MVSK preferences of supply chain agents will affect the achievability of SCC and flexibility of the coordinating contract. We also uncover that if we assume an individual MVSK agent to be an MV one, the achievability of SCC by contracts will be very much negatively affected.