5 resultados para Key performance indicators

em Duke University


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The dissertation consists of three chapters related to the low-price guarantee marketing strategy and energy efficiency analysis. The low-price guarantee is a marketing strategy in which firms promise to charge consumers the lowest price among their competitors. Chapter 1 addresses the research question "Does a Low-Price Guarantee Induce Lower Prices'' by looking into the retail gasoline industry in Quebec where there was a major branded firm which started a low-price guarantee back in 1996. Chapter 2 does a consumer welfare analysis of low-price guarantees to drive police indications and offers a new explanation of the firms' incentives to adopt a low-price guarantee. Chapter 3 develops the energy performance indicators (EPIs) to measure energy efficiency of the manufacturing plants in pulp, paper and paperboard industry.

Chapter 1 revisits the traditional view that a low-price guarantee results in higher prices by facilitating collusion. Using accurate market definitions and station-level data from the retail gasoline industry in Quebec, I conducted a descriptive analysis based on stations and price zones to compare the price and sales movement before and after the guarantee was adopted. I find that, contrary to the traditional view, the stores that offered the guarantee significantly decreased their prices and increased their sales. I also build a difference-in-difference model to quantify the decrease in posted price of the stores that offered the guarantee to be 0.7 cents per liter. While this change is significant, I do not find the response in comeptitors' prices to be significant. The sales of the stores that offered the guarantee increased significantly while the competitors' sales decreased significantly. However, the significance vanishes if I use the station clustered standard errors. Comparing my observations and the predictions of different theories of modeling low-price guarantees, I conclude the empirical evidence here supports that the low-price guarantee is a simple commitment device and induces lower prices.

Chapter 2 conducts a consumer welfare analysis of low-price guarantees to address the antitrust concerns and potential regulations from the government; explains the firms' potential incentives to adopt a low-price guarantee. Using station-level data from the retail gasoline industry in Quebec, I estimated consumers' demand of gasoline by a structural model with spatial competition incorporating the low-price guarantee as a commitment device, which allows firms to pre-commit to charge the lowest price among their competitors. The counterfactual analysis under the Bertrand competition setting shows that the stores that offered the guarantee attracted a lot more consumers and decreased their posted price by 0.6 cents per liter. Although the matching stores suffered a decrease in profits from gasoline sales, they are incentivized to adopt the low-price guarantee to attract more consumers to visit the store likely increasing profits at attached convenience stores. Firms have strong incentives to adopt a low-price guarantee on the product that their consumers are most price-sensitive about, while earning a profit from the products that are not covered in the guarantee. I estimate that consumers earn about 0.3% more surplus when the low-price guarantee is in place, which suggests that the authorities should not be concerned and regulate low-price guarantees. In Appendix B, I also propose an empirical model to look into how low-price guarantees would change consumer search behavior and whether consumer search plays an important role in estimating consumer surplus accurately.

Chapter 3, joint with Gale Boyd, describes work with the pulp, paper, and paperboard (PP&PB) industry to provide a plant-level indicator of energy efficiency for facilities that produce various types of paper products in the United States. Organizations that implement strategic energy management programs undertake a set of activities that, if carried out properly, have the potential to deliver sustained energy savings. Energy performance benchmarking is a key activity of strategic energy management and one way to enable companies to set energy efficiency targets for manufacturing facilities. The opportunity to assess plant energy performance through a comparison with similar plants in its industry is a highly desirable and strategic method of benchmarking for industrial energy managers. However, access to energy performance data for conducting industry benchmarking is usually unavailable to most industrial energy managers. The U.S. Environmental Protection Agency (EPA), through its ENERGY STAR program, seeks to overcome this barrier through the development of manufacturing sector-based plant energy performance indicators (EPIs) that encourage U.S. industries to use energy more efficiently. In the development of the energy performance indicator tools, consideration is given to the role that performance-based indicators play in motivating change; the steps necessary for indicator development, from interacting with an industry in securing adequate data for the indicator; and actual application and use of an indicator when complete. How indicators are employed in EPA’s efforts to encourage industries to voluntarily improve their use of energy is discussed as well. The chapter describes the data and statistical methods used to construct the EPI for plants within selected segments of the pulp, paper, and paperboard industry: specifically pulp mills and integrated paper & paperboard mills. The individual equations are presented, as are the instructions for using those equations as implemented in an associated Microsoft Excel-based spreadsheet tool.

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This paper analyzes a class of common-component allocation rules, termed no-holdback (NHB) rules, in continuous-review assemble-to-order (ATO) systems with positive lead times. The inventory of each component is replenished following an independent base-stock policy. In contrast to the usually assumed first-come-first-served (FCFS) component allocation rule in the literature, an NHB rule allocates a component to a product demand only if it will yield immediate fulfillment of that demand. We identify metrics as well as cost and product structures under which NHB rules outperform all other component allocation rules. For systems with certain product structures, we obtain key performance expressions and compare them to those under FCFS. For general product structures, we present performance bounds and approximations. Finally, we discuss the applicability of these results to more general ATO systems. © 2010 INFORMS.

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In some supply chains, materials are ordered periodically according to local information. This paper investigates how to improve the performance of such a supply chain. Specifically, we consider a serial inventory system in which each stage implements a local reorder interval policy; i.e., each stage orders up to a local basestock level according to a fixed-interval schedule. A fixed cost is incurred for placing an order. Two improvement strategies are considered: (1) expanding the information flow by acquiring real-time demand information and (2) accelerating the material flow via flexible deliveries. The first strategy leads to a reorder interval policy with full information; the second strategy leads to a reorder point policy with local information. Both policies have been studied in the literature. Thus, to assess the benefit of these strategies, we analyze the local reorder interval policy. We develop a bottom-up recursion to evaluate the system cost and provide a method to obtain the optimal policy. A numerical study shows the following: Increasing the flexibility of deliveries lowers costs more than does expanding information flow; the fixed order costs and the system lead times are key drivers that determine the effectiveness of these improvement strategies. In addition, we find that using optimal batch sizes in the reorder point policy and demand rate to infer reorder intervals may lead to significant cost inefficiency. © 2010 INFORMS.

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The efficiency of shock wave lithotripsy (SWL), a noninvasive first-line therapy for millions of nephrolithiasis patients, has not improved substantially in the past two decades, especially in regard to stone clearance. Here, we report a new acoustic lens design for a contemporary electromagnetic (EM) shock wave lithotripter, based on recently acquired knowledge of the key lithotripter field characteristics that correlate with efficient and safe SWL. The new lens design addresses concomitantly three fundamental drawbacks in EM lithotripters, namely, narrow focal width, nonidealized pulse profile, and significant misalignment in acoustic focus and cavitation activities with the target stone at high output settings. Key design features and performance of the new lens were evaluated using model calculations and experimental measurements against the original lens under comparable acoustic pulse energy (E+) of 40 mJ. The -6-dB focal width of the new lens was enhanced from 7.4 to 11 mm at this energy level, and peak pressure (41 MPa) and maximum cavitation activity were both realigned to be within 5 mm of the lithotripter focus. Stone comminution produced by the new lens was either statistically improved or similar to that of the original lens under various in vitro test conditions and was significantly improved in vivo in a swine model (89% vs. 54%, P = 0.01), and tissue injury was minimal using a clinical treatment protocol. The general principle and associated techniques described in this work can be applied to design improvement of all EM lithotripters.

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Inflammation and the formation of an avascular fibrous capsule have been identified as the key factors controlling the wound healing associated failure of implantable glucose sensors. Our aim is to guide advantageous tissue remodeling around implanted sensor leads by the temporal release of dexamethasone (Dex), a potent anti-inflammatory agent, in combination with the presentation of a stable textured surface.

First, Dex-releasing polyurethane porous coatings of controlled pore size and thickness were fabricated using salt-leaching/gas-foaming technique. Porosity, pore size, thickness, drug release kinetics, drug loading amount, and drug bioactivity were evaluated. In vitro sensor functionality test were performed to determine if Dex-releasing porous coatings interfered with sensor performance (increased signal attenuation and/or response times) compared to bare sensors. Drug release from coatings monitored over two weeks presented an initial fast release followed by a slower release. Total release from coatings was highly dependent on initial drug loading amount. Functional in vitro testing of glucose sensors deployed with porous coatings against glucose standards demonstrated that highly porous coatings minimally affected signal strength and response rate. Bioactivity of the released drug was determined by monitoring Dex-mediated, dose-dependent apoptosis of human peripheral blood derived monocytes in culture.

The tissue modifying effects of Dex-releasing porous coatings were accessed by fully implanting Tygon® tubing in the subcutaneous space of healthy and diabetic rats. Based on encouraging results from these studies, we deployed Dex-releasing porous coatings from the tips of functional sensors in both diabetic and healthy rats. We evaluated if the tissue modifying effects translated into accurate, maintainable and reliable sensor signals in the long-term. Sensor functionality was accessed by continuously monitoring glucose levels and performing acute glucose challenges at specified time points.

Sensors treated with porous Dex-releasing coatings showed diminished inflammation and enhanced vascularization of the tissue surrounding the implants in healthy rats. Functional sensors with Dex-releasing porous coatings showed enhanced sensor sensitivity over a 21-day period when compared to controls. Enhanced sensor sensitivity was accompanied with an increase in sensor signal lag and MARD score. These results indicated that Dex-loaded porous coatings were able to elicit a favorable tissue response, and that such tissue microenvironment could be conducive towards extending the performance window of glucose sensors in vivo.

The diabetic pilot animal study showed differences in wound healing patters between healthy and diabetic subjects. Diabetic rats showed lower levels of inflammation and vascularization of the tissue surrounding implants when compared to their healthy counterparts. Also, functional sensors treated with Dex-releasing porous coatings did not show enhanced sensor sensitivity over a 21-day period. Moreover, increased in sensor signal lag and MARD scores were present in porous coated sensors regardless of Dex-loading when compared to bare implants. These results suggest that the altered wound healing patterns presented in diabetic tissues may lead to premature sensor failure when compared to sensors implanted in healthy rats.