Redox Potential: Monitoring and Role in Development of Aroma Compounds, Rheological Properties and Survival of Oxygen Sensitive Strains During the Manufacture of Fermented Dairy Products

International audienc

Sourcing Flexibility, Spot Trading, and Procurement Contract Structure

We analyze the structure and pricing of option contracts for an industrial good in the presence of spot trading. We combine the analysis of spot trading and buyers' disparate private valuations for different suppliers' products, and we jointly endogenize the determination of three major dimensions in contract design: (i) sales contracts versus options contracts, (ii) flat-price versus volume-dependent contracts, and (iii) volume discounts versus volume premia. We build a model in which a supplier of an industrial good transacts with a manufacturer who uses the supplier's product to produce an end good with an uncertain demand. We show that, consistent with industry observations, volume-dependent optimal sales contracts always demonstrate volume discounts (i.e., involve concave pricing). However, options are more complex agreements, and optimal option contracts can involve both volume discounts and volume premia. Three major contract structures commonly emerge in optimality. First, if the seller has a high discount rate relative to the buyer and the seller's production costs or the production capacity is low, the optimal contracts tend to be flat-price sales contracts. Second, when the seller has a relatively high discount rate compared to the buyer but production costs or production capacity are high, the optimal contracts are sales contracts with volume discounts. Third, if the buyer's discount rate is high relative to the seller's, then the optimal contracts tend to be volume-dependent options contracts and can involve both volume discounts and volume premia. However, when the seller's production capacity is sufficiently low, it is possible to observe flat-price option contracts. Furthermore, we provide links between production and spot market characteristics, contract design, and efficiency.National Science Foundation (U.S.) (contract CMMI-0758069)National Science Foundation (U.S.) (contract DMI-0245352

Integrating Long-Term and Short-Term Contracting in Beef Supply Chains

Published version made available with the permission of INFORMS</p

Coordination in closed-loop supply chain with price-dependent returns

This paper proposes two Closed-loop Supply Chain (CLSC) games in which a manufacturer sets some green activity programs efforts and a retailer sets the selling price. Both strategies influence the return rate, which is a state variable. The pricing strategy plays a key role in the identification of the best contract to achieve coordination as well as in achieving environmental objectives. The pricing strategy influences the return rate negatively, as consumers delay the return of their goods when the purchasing (and repurchasing) price is high. We then compare a wholesale price contract (WPC) and a revenue sharing contract (RSC) mechanism as both have interesting pricing policy implications. Our result shows that firms coordinate the CLSC through a (WPC) when the sharing parameter is too low while the negative effect of pricing on returns is too severe. In that case, the low sharing parameter deters the manufacturer to accept any sharing agreements. Further, firms coordinate the CLSC when the sharing parameter is medium independent of the negative impact of pricing on returns. When the sharing parameter is too high the retailer never opts for an RSC. We find that the magnitude of pricing effect on returns determines the contract to be adopted: For certain sharing parameter, firms prefer an RSC when the price effect on return is low and a WPC when this effect is high. In all other cases, firms do not have a consensus on the contract to be adopted and coordination is then not achieved

Evaluating SKI as a candidate gene for non-syndromic cleft lip with or without cleft palate

Non-syndromic cleft lip with or without cleft palate (NSCL/P) is one of the most common of all congenital malformations and has a multifactorial etiology. Findings in mice suggest that the v-ski sarcoma viral oncogene homolog (SKI) gene is a candidate gene for orofacial clefting. In humans, a significant association between rs2843159 within SKI and NSCL/P has been reported in patients from the Philippines and South America. In the South American patients, the association was driven by the subgroup of patients with non-syndromic cleft lip only (NSCLO). Here we investigated the association with rs2843159 in a Mayan Mesoamerican population (172 NSCL/P patients and 366 controls). In addition, we analyzed the phenotypic subgroups NSCLO and non-syndromic cleft of lip and palate (NSCLP). A trend towards association between rs2843159 and NSCL/P was observed in the Mayan cohort (P = 0.097), and we found a stronger association in the NSCLP subgroup (P = 0.072) despite a limited sample size. To investigate whether other common variants within the SKI gene contribute to NSCL/P susceptibility in European and Asian populations, we also analyzed genotypic data from two recent genome-wide association studies using set-based statistical approaches. These analyses detected a trend toward association in the European population. Our data provide limited support for the hypothesis that common SKI variants are susceptibility factors for NSCL/P

Multiple order-up-to policy for mitigating bullwhip effect in supply chain network

This paper proposes a multiple order-up-to policy based inventory replenishment scheme to mitigate the bullwhip effect in a multi-stage supply chain scenario, where various transportation modes are available between the supply chain (SC) participants. The proposed policy is similar to the fixed order-up-to policy approach where replenishment decision “how much to order” is made periodically on the basis of the predecided order-up-to inventory level. In the proposed policy, optimal multiple order-up-to levels are assigned to each SC participants, which provides decision making reference point for deciding the transportation related order quantity. Subsequently, a mathematical model is established to define optimal multiple order-up-to levels for each SC participants that aims to maximize overall profit from the SC network. In parallel, the model ensures the control over supply chain pipeline inventory, high satisfaction of customer demand and enables timely utilization of available transportation modes. Findings from the various numerical datasets including stochastic customer demand and lead times validate that—the proposed optimal multiple order-up-to policy based inventory replenishment scheme can be a viable alternative for mitigating the bullwhip effect and well-coordinated SC. Moreover, determining the multiple order-up-to levels is a NP hard combinatorial optimization problem. It is found that the implementation of new emerging optimization algorithm named bacterial foraging algorithm (BFA) has presented superior optimization performances. The robustness and applicability of the BFA algorithm are further validated statistically by employing the percentage heuristic gap and two-way ANOVA analysis