Dynamic pricing models for used products in remanufacturing with lost-sales and uncertain quality

In this paper, we investigate the remanufacturing problem of pricing single-class used products (cores) in the face of random price-dependent returns and random demand. Specifically, we propose a dynamic pricing policy for the cores and then model the problem as a continuous-time Markov decision process. Our models are designed to address three objectives: finite horizon total cost minimization, infinite horizon discounted cost, and average cost minimization. Besides proving optimal policy uniqueness and establishing monotonicity results for the infinite horizon problem, we also characterize the structures of the optimal policies, which can greatly simplify the computational procedure. Finally, we use computational examples to assess the impacts of specific parameters on optimal price and reveal the benefits of a dynamic pricing policy. © 2013 Elsevier B.V. All rights reserved.

Developmental care for high-risk newborns:Emerging science, clinical application, and continuity from newborn intensive care unit to community

Neonatology has optimized medical outcomes for high-risk newborns yet neurodevelopmental outcomes continue to be a concern. Basic science, clinical research, and environmental design perspectives have shown the impact of the caregiving environment on the developing brain and the role of professional caregivers in providing supportive intervention to both infants and their families. This recognition has prompted a focus on early developmentally supportive care (DSC) for high-risk newborns both in the hospital and in community follow up. DSC has emerged as a recognized standard of care in most neonatal intensive care units. Still, many questions remain and much integrative research is needed.

Dynamic pricing for used products in remanufacturing with back orders(ABS 3* Journal, Accepted with Revision on 2nd December 2011).

In remanufacturing, the supply of used products and the demand for remanufactured products are usually mismatched because of the great uncertainties on both sides. In this paper, we propose a dynamic pricing policy to balance this uncertain supply and demand. Specifically, we study a remanufacturer’s problem of pricing a single class of cores with random price-dependent returns and random demand for the remanufactured products with backlogs. We model this pricing task as a continuous-time Markov decision process, which addresses both the finite and infinite horizon problems, and provide managerial insights by analyzing the structural properties of the optimal policy. We then use several computational examples to illustrate the impacts of particular system parameters on pricing policy.

Influence of unit operations on the levels of polyacetylenes in minimally processed carrots and parsnips: An industrial trial

Carrots and parsnips are often consumed as minimally processed ready-to-eat convenient foods and contain in minor quantities, bioactive aliphatic C17-polyacetylenes (falcarinol, falcarindiol, falcarindiol-3-acetate). Their retention during minimal processing in an industrial trial was evaluated. Carrot and parsnips were prepared in four different forms (disc cutting, baton cutting, cubing and shredding) and samples were taken in every point of their processing line. The unit operations were: peeling, cutting and washing with chlorinated water and also retention during 7 days storage was evaluated. The results showed that the initial unit operations (mainly peeling) influence the polyacetylene retention. This was attributed to the high polyacetylene content of their peels. In most cases, when washing was performed after cutting, less retention was observed possibly due to leakage during tissue damage occurred in the cutting step. The relatively high retention during storage indicates high plant matrix stability. Comparing the behaviour of polyacetylenes in the two vegetables during storage, the results showed that they were slightly more retained in parsnips than in carrots. Unit operations and especially abrasive peeling might need further optimisation to make them gentler and minimise bioactive losses.

Environmental pricing of externalities from different sources of electricity generation in Chile

The rapid increase in electricity demand in Chile means a choice must be made between major investments in renewable or non-renewable sources for additional production. Current projects to develop large dams for hydropower in Chilean Patagonia impose an environmental price by damaging the natural environment. On the other hand, the increased use of fossil fuels entails an environmental price in terms of air pollution and greenhouse gas emissions contributing to climate change. This paper studies the debate on future electricity supply in Chile by investigating the preferences of households for a variety of different sources of electricity generation such as fossil fuels, large hydropower in Chilean Patagonia and other renewable energy sources. Using Double Bounded Dichotomous Choice Contingent Valuation, a novel advanced disclosure method and internal consistency test are used to elicit the willingness to pay for less environmentally damaging sources. Policy results suggest a strong preference for renewable energy sources with higher environmental prices imposed by consumers on electricity generated from fossil fuels than from large dams in Chilean Patagonia. Policy results further suggest the possibility of introducing incentives for renewable energy developments that would be supported by consumers through green tariffs or environmental premiums. Methodological findings suggest that advanced disclosure learning overcomes the problem of internal inconsistency in SB-DB estimates.