scholarly journals Full Information Product Pricing: An Information Strategy for Harnessing Consumer Choice to Create a More Sustainable World

2014 ◽  
Vol 34 ◽  
Author(s):  
Luis F. Luna-Reyes ◽  
Jing Zhang ◽  
Andrew Whitmore ◽  
Holly Jarman ◽  
Sergio Picazo-Vela ◽  
...  
Keyword(s):  
Consumer Choice ◽  
Full Information ◽  
Information Strategy ◽  
Information Product ◽  
Product Pricing

Information strategies to support full information product pricing: The role of trust

2013 ◽  
Vol 18 (1) ◽  
pp. 75-91 ◽  
Author(s):  
Luis F. Luna-Reyes ◽  
Jing Zhang ◽  
Réjean Roy ◽  
David F. Andersen ◽  
Andy Whitmore ◽  
...  
Keyword(s):  
Full Information ◽  
Information Product ◽  
Information Strategies ◽  
Product Pricing

Information service and information product pricing

1993 ◽  
Vol 45 (11/12) ◽  
pp. 297-305 ◽  
Author(s):  
Lynne J Brindley
Keyword(s):  
Information Service ◽  
Information Product ◽  
Product Pricing

Capturing Context-Sensitive Information Usage in Choice Models via Mixtures of Information Archetypes

2016 ◽  
Vol 53 (5) ◽  
pp. 646-664 ◽  
Author(s):  
Joffre Swait ◽  
Monica Popa ◽  
Luming Wang
Keyword(s):  
Consumer Choice ◽  
Task Complexity ◽  
Preference Heterogeneity ◽  
Testable Hypothesis ◽  
Sensitive Information ◽  
Full Information ◽  
Disciplinary Boundaries ◽  
Context Sensitive ◽  
Product Categories ◽  
Information Usage

The authors offer a new conceptualization and operational model of consumer choice that allows context-sensitive information usage and preference heterogeneity to be separately and simultaneously captured, thus transforming the axiom of full information use into a testable hypothesis. A key contribution of the proposed framework is the integration of two previously disjointed and often antagonistic research paradigms: (1) the economic rationality perspective, which assumes stable preferences and full information usage, and (2) the psychological bounded-rationality perspective, which allows context-sensitive preferences and information selectivity. The authors demonstrate that the two paradigms can and do coexist in the same decision-making space, even at the level of individual consumer choices. The proposed information archetype mixture model is tested in four studies that span different product categories and levels of task complexity. The findings have ramifications for choice modeling theory and implementation, beyond the disciplinary boundaries of marketing to applied economics and choice-focused social sciences.

Should Designers Worry About Market Systems?

2008 ◽  
Author(s):  
Ching-Shin Shiau ◽  
Jeremy J. Michalek
Keyword(s):  
Consumer Choice ◽  
Price Competition ◽  
Consumer Preferences ◽  
Distribution Channels ◽  
Channel Structure ◽  
Design Decisions ◽  
Market Structures ◽  
Product Pricing ◽  
Optimal Product Design ◽  
Design Case Study

Engineering approaches for optimizing designs within a market context generally take the perspective of a single producer, asking what design and price point will maximize producer profit predicted by consumer choice simulations. These approaches treat competitors and retailers as fixed or nonexistent, and they take business-oriented details, such as the structure of distribution channels, as separate issues that can be addressed post hoc by other disciplines. It is well established that the structure of market systems influences optimal product pricing. In this paper, we investigate whether two types of these structures also influence optimal product design decisions; specifically, 1) consumer heterogeneity and 2) distribution channels. We first model firms as players in a profit-seeking game that compete on product attributes and prices. We then model the interactions of manufacturers and retailers in Nash competition under alternative market structures and compare the equilibrium conditions for each case. We find that when consumers are modeled as homogeneous in their preferences, optimal design can be decoupled from the game, and design decisions can be made without regard to price, competition, or channel structure. However, when consumer preferences are heterogeneous, the behavior of competitors and retailers is key to determining which designs are profitable. We examine the extent of this effect in a vehicle design case study from the literature and find that the presence of heterogeneity leads different market structures to imply significantly different profit-maximizing designs.

OPTIMAL PORTFOLIO CONSTRUCTION UNDER PARTIAL INFORMATION FOR A BALANCED FUND

2007 ◽  
Vol 10 (06) ◽  
pp. 1015-1042
Author(s):  
SIMON KEEL ◽  
FLORIAN HERZOG ◽  
HANS P. GEERING ◽  
LORENZ M. SCHUMANN
Keyword(s):  
Risk Aversion ◽  
Asset Allocation ◽  
Partial Information ◽  
Absolute Risk ◽  
Closed Form Solution ◽  
Model Parameters ◽  
Full Information ◽  
Information Strategy ◽  
Information Approach ◽  
Drift Terms

The model parameters in optimal asset allocation problems are often assumed to be deterministic. This is not a realistic assumption since most parameters are not known exactly and therefore have to be estimated. We consider investment opportunities which are modeled as local geometric Brownian motions whose drift terms may be stochastic and not necessarily measurable. The drift terms of the risky assets are assumed to be affine functions of some arbitrary factors. These factors themselves may be stochastic processes. They are modeled to have a mean-reverting behavior. We consider two types of factors, namely observable and unobservable ones. The closed-form solution of the general problem is derived. The investor is assumed to have either constant relative risk aversion (CRRA) or constant absolute risk aversion (CARA). The optimal asset allocation under partial information is derived by transforming the problem into a full-information problem, where the solution is well known. The analytical result is empirically tested in a real-world application. In our case, we consider the optimal management of a balanced fund mandate. The unobservable risk factors are estimated with a Kalman filter. We compare the results of the partial-information strategy with the corresponding full-information strategy. We find that using a partial-information approach yields much better results in terms of Sharpe ratios than the full-information approach.

Computer-Controlled Hrem Alignment Using Automated Diffractogram Analysis

1990 ◽  
Vol 48 (1) ◽  
pp. 532-533
Author(s):  
G.Y. Fan ◽  
O.L. Krivanek
Keyword(s):  
Electron Microscope ◽  
High Resolution ◽  
The Other ◽  
Full Information ◽  
Resolution Electron ◽  
Skilled Operator ◽  
Automatic Alignment ◽  
High Resolution Electron Microscope ◽  
Computer Controlled ◽  
Recorded Image

Full alignment of a high resolution electron microscope (HREM) requires five parameters to be optimized: the illumination angle (beam tilt) x and y, defocus, and astigmatism magnitude and orientation. Because neither voltage nor current centering lead to the correct illumination angle, all the adjustments must be done on the basis of observing contrast changes in a recorded image. The full alignment can be carried out by a computer which is connected to a suitable image pick-up device and is able to control the microscope, sometimes with greater precision and speed than even a skilled operator can achieve. Two approaches to computer-controlled (automatic) alignment have been investigated. The first is based on measuring the dependence of the overall contrast in the image of a thin amorphous specimen on the relevant parameters, the other on measuring the image shift. Here we report on our progress in developing a new method, which makes use of the full information contained in a computed diffractogram.

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