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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2004.07.053 Byline: Abba M. Krieger (a), Paul E. Green (b) Keywords: Marketing; Decision analysis; Expert systems Abstract: Models for optimal product positioning have received considerable attention by marketing researchers and marketing scientists over the past decade. Typically, optimizing models take the viewpoint that the manager wishes to find a specific vector of product attribute levels that, in the face of competitors' product profiles, maximizes the firm's market share (or, perhaps, return) over some designated planning horizon. This class of models emphasizes long run strategic modeling. In contrast, the authors introduce a tactical, short-term model, called SALIENCE, whose purpose is to allocate sales efforts in such a way as to increase the relative importance of attributes for which the sponsoring firm's current product has a (possibly temporary) differential advantage. In this case emphasis is on short-run, tactical decision making. We describe the SALIENCE model, both informally and mathematically. The model is applied, illustratively, to a real (disguised) study of overnight air shipment delivery. Author Affiliation: (a) The Wharton School of the University of Pennsylvania, Suite 400, John Huntsman Hall, Philadelphia, PA 19104, USA (b) The Wharton School of the University of Pennsylvania, Suite 700, John Huntsman Hall, Philadelphia, PA 19104, USA Article History: Received 22 October 2003; Accepted 13 July 2004

We present an optimized rerandomization design procedure for a non-sequential treatment-control experiment. Randomized experiments are the gold standard for finding causal effects in nature. But sometimes random assignments result in unequal partitions of the treatment and control group visibly seen as imbalance in observed covariates. There can additionally be imbalance on unobserved covariates. Imbalance in either observed or unobserved covariates increases treatment effect estimator error inflating the width of confidence regions and reducing experimental power. "Rerandomization" is a strategy that omits poor imbalance assignments by limiting imbalance in the observed covariates to a prespecified threshold. However, limiting this threshold too much can increase the risk of contracting error from unobserved covariates. We introduce a criterion that combines observed imbalance while factoring in the risk of inadvertently imbalancing unobserved covariates. We then use this criterion to locate the optimal rerandomization threshold based on the practitioner's level of desired insurance against high estimator error. We demonstrate the gains of our designs in simulation and in a dataset from a large randomized experiment in education. We provide an open source R package available on CRAN named OptimalRerandExpDesigns which generates designs according to our algorithm. • The rerandomization experimental design threshold can be optimized. • Our optimization considers both the effects of observed and unobserved covariates. • Our optimization improves upon linear regression for general response models. • We provide a CRAN package that implements three optimization procedures. [ABSTRACT FROM AUTHOR]

Development of a model for a decision support system, to help firms achieve successful product/service benefit positionings, and meet consumers' expectations is discussed.

An algorithm for selecting a subset from a large number of alternatives is presented. The criterion for selecting the subset is based on the assumption that at least one alternative will be chosen and implemented once the uncertainties are resolved. Intuitively, the subset may contain alternatives with high expectation and minimal uncertainty as well as alternatives with low expectation and high uncertainty. These subset selection techniques can be applied in such areas as foreign direct investment and new product development.

Even with today's high emphasis on management decision support systems, relatively little has been published on the motivations, tribulations, and post mortems that generally accompany the development of such systems. This paper reports (in a mixture of narrative style and more formal mod exposition) how a computerized decision support system for optimal price determination was developed implemented, and finally applied to a broad range of industry problems. Keywords: Pricing; demand analysis; conjoint analysis; multiattribute preference, The development, implementation and application of the PRIce-DEMand model (PRIDEM),a computerized decision support system for optimal price determination, is detailed. PRIDEM's concrete advantages over other product pricing models are featured. Use of the model is implemented on either a mainframe of a personal computer. Its limitations are also delineated.

Glutaraldehyde cross-linked heterograft tissues, bovine pericardium (BP) or porcine aortic valves, are the leaflet materials in bioprosthetic heart valves (BHV) used in cardiac surgery for heart valve disease. BHV fail due to structural valve degeneration (SVD), often with calcification. Advanced glycation end products (AGE) are post-translational, non-enzymatic reaction products from sugars reducing proteins. AGE are present in SVD-BHV clinical explants and are not detectable in un-implanted BHV. Prior studies modeled BP-AGE formation in vitro with glyoxal, a glucose breakdown product, and serum albumin. However, glucose is the most abundant AGE precursor. Thus, the present studies investigated the hypothesis that BHV susceptibility to glucose related AGE, together with serum proteins, results in deterioration of collagen structure and mechanical properties. In vitro experiments studied AGE formation in BP and porcine collagen sponges (CS) comparing 14C-glucose and 14C-glyoxal with and without bovine serum albumin (BSA). Glucose incorporation occurred at a significantly lower level than glyoxal (p <0.02). BSA co-incubations demonstrated reduced glyoxal and glucose uptake by both BP and CS. BSA incubation caused a significant increase in BP mass, enhanced by glyoxal co-incubation. Two-photon microscopy of BP showed BSA induced disruption of collagen structure that was more severe with glucose or glyoxal co-incubation. Uniaxial testing of CS demonstrated that glucose or glyoxal together with BSA compared to controls, caused accelerated deterioration of viscoelastic relaxation, and increased stiffness over a 28-day time course. In conclusion, glucose, glyoxal and BSA uniquely contribute to AGE-mediated disruption of heterograft collagen structure and deterioration of mechanical properties. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Bioprosthetic heart valves (BHV) fabricated from heterograft tissue, such as glutaraldehyde pretreated bovine pericardium (BP), are the most frequently used heart valve replacements. BHV durability is limited by structural valve degeneration (SVD), mechanistically associated with calcification, advanced glycation end products (AGE), and serum protein infiltration. We investigated the hypothesis that anti-AGE agents, Aminoguanidine, Pyridoxamine [PYR], and N-Acetylcysteine could mitigate AGE-serum protein SVD mechanisms in vitro and in vivo, and that these agents could mitigate calcification or demonstrate anti-calcification interactions with BP pretreatment with ethanol. In vitro, each of these agents significantly inhibited AGE-serum protein infiltration in BP. However, in 28-day rat subdermal BP implants only orally administered PYR demonstrated significant inhibition of AGE and serum protein uptake. Furthermore, BP PYR preincubation of BP mitigated AGE-serum protein SVD mechanisms in vitro, and demonstrated mitigation of both AGE-serum protein uptake and reduced calcification in vivo in 28-day rat subdermal BP explants. Inhibition of BP calcification as well as inhibition of AGE-serum protein infiltration was observed in 28-day rat subdermal BP explants pretreated with ethanol followed by PYR preincubation. In conclusion, AGE-serum protein and calcification SVD pathophysiology are significantly mitigated by both PYR oral therapy and PYR and ethanol pretreatment of BP. [ABSTRACT FROM AUTHOR]

Verbal fluency is commonly used to evaluate cognitive dysfunction in a variety of neuropsychiatric diseases, yet the neurobiology underlying performance of this task is incompletely understood. Electrocorticography (ECoG) provides a unique opportunity to investigate temporal activation patterns during cognitive tasks with high spatial and temporal precision. We used ECoG to study high gamma activity (HGA) patterns in patients undergoing presurgical evaluation for intractable epilepsy as they completed an overt, free-recall verbal fluency task. We examined regions demonstrating changes in HGA during specific timeframes relative to speech onset. Early pre-speech high gamma activity was present in left frontal regions during letter fluency and in bifrontal regions during category fluency. During timeframes typically associated with word planning, a distributed network was engaged including left inferior frontal, orbitofrontal and posterior temporal regions. Peri-Rolandic activation was observed during speech onset, and there was post-speech activation in the bilateral posterior superior temporal regions. Based on these observations in the context of prior studies, we propose a model of neocortical activity patterns underlying verbal fluency. • We recorded electrocorticography during overt responses in a verbal fluency task. • Left frontal regions activate during letter-motivated search. • Bifrontal regions activate during category-motivated search. • A distributed network over the left hemisphere activates during word planning. • Peri-Rolandic and posterior temporal regions activate with and after articulation. [ABSTRACT FROM AUTHOR]