Finding Choice Alternatives in Memory: Probability Models of Brand Name Recall

1994 ◽  
Vol 31 (4) ◽  
pp. 441-461 ◽  
Author(s):  
J. Wesley Hutchinson ◽  
Kalyan Raman ◽  
Murali K. Mantrala
Keyword(s):  
Consumer Choice ◽  
Memory Search ◽  
Brand Names ◽  
Brand Name ◽  
Probability Models ◽  
Order Model ◽  
First Order ◽  
Recall Latency ◽  
Recall Data ◽  
Special Cases

Recalling brand names is an important aspect of consumer choice in many situations. The authors develop a general Markov model that relates probabilistic aspects of recall to consumer and marketing mix variables. Then they illustrate how parameters can be estimated from recall data for three special cases of the model: The first is a “baseline” version of the model that can be used to assess the extent to which categories of brands can be automatically included in or excluded from memory search; the second is a zero-order model that can be used to estimate the effects of brand variables and individual usage rates on recall latency; and the third is a first-order model that uses aggregate recall data to assess market structure. Finally, the authors demonstrate how the model can be used in numerical analyses to evaluate awareness-building strategies.

Composite Branding Alliances: An Investigation of Extension and Feedback Effects

1996 ◽  
Vol 33 (4) ◽  
pp. 453-466 ◽  
Author(s):  
C. Whan Park ◽  
Sung Youl Jun ◽  
Allan D. Shocker
Keyword(s):  
Consumer Choice ◽  
Brand Extension ◽  
New Product ◽  
Brand Names ◽  
Brand Name ◽  
Feedback Effects ◽  
Direct Extension ◽  
Attribute Levels ◽  
Preference Study

The authors report two studies investigating the effectiveness of a composite brand in a brand extension context. In composite brand extension, a combination of two existing brand names in different positions as header and modifier is used as the brand name for a new product (e.g., Slim-Fast chocolate cakemix by Godiva). The results of both studies reveal that by combining two brands with complementary attribute levels, a composite brand extension appears to have a better attribute profile than a direct extension of the header brand (Study 1) and has a better attribute profile when it consists of two complementary brands than when it consists of two highly favorable but not complementary brands (Study 2). The improved attribute profile seems to enhance a composite's effectiveness in influencing consumer choice and preference (Study 2). In addition, the positions of the constituent brand names in the composite brand name are found to be important in the formation of the composite's attribute profile and its feedback effects on the constituent brands. A composite brand extension has different attribute profiles and feedback effects, depending on the positions of the constituent brand names.

Data Dependent Systems Approach to Stochastic Tool Life and Reliability

1978 ◽  
Vol 100 (3) ◽  
pp. 318-322 ◽  
Author(s):  
S. M. Pandit
Keyword(s):  
Tool Life ◽  
Failure Time ◽  
Systems Approach ◽  
A Priori ◽  
Optimal Strategies ◽  
Shop Floor ◽  
Order Model ◽  
First Order ◽  
Special Cases ◽  
Tool Replacement

A Data Dependent Systems approach is outlined for obtaining tool life distribution and reliability models directly from shop floor and/or laboratory failure data. The approach does not require any a-priori knowledge of the distribution and can be used with a limited amount of data. Estimation of the first order model is illustrated by application to HSS tools in turning. The tool life signatures at three different speeds are exhibited in the form of plots of hazard rate, reliability and failure time probability density functions. Formulation of simple tool replacement strategies from these plots by the shop personnel is illustrated; the mathematical expressions given for these functions can be used to develop more elaborate optimal strategies in computerized adaptive control. It is shown that most of the commonly used tool life distributions are well approximated by special cases of the first order model and hence are included in the approach.

A first-order model of thermal lensing of laser propagation in the eye and implications for laser safety

2005 ◽  
Author(s):  
Robert J. Thomas ◽  
Rebecca L. Vincelette ◽  
Gavin D. Buffington ◽  
Amber D. Strunk ◽  
Michael A. Edwards ◽  
...  
Keyword(s):  
Thermal Lensing ◽  
Order Model ◽  
Laser Safety ◽  
First Order ◽  
Laser Propagation

EXPRESS: Is Nestlé a Lady? The Feminine Brand Name Advantage

2021 ◽  
pp. 002224292199306
Author(s):  
Ruth Pogacar ◽  
Justin Angle ◽  
Tina M. Lowrey ◽  
L. J. Shrum ◽  
Frank R. Kardes
Keyword(s):  
Boundary Conditions ◽  
Brand Names ◽  
Brand Name ◽  
Brand Performance ◽  
The Feminine ◽  
And Performance ◽  
Typical User

A brand name’s linguistic characteristics convey brand qualities independent of the name’s denotative meaning. For instance, name length, sounds, and stress can signal masculine or feminine associations. This research examines the effects of such gender associations on three important brand outcomes: attitudes, choice, and performance. Across six studies using both observational analyses of real brands and experimental manipulations of invented brands the authors show that linguistically feminine names increase perceived warmth, which improves brand outcomes. Feminine brand names enhance attitudes and choice share–both hypothetically and consequentially–and are associated with better brand performance. The authors establish boundary conditions, showing that the feminine brand name advantage is attenuated when the typical user is male and when products are utilitarian.

scholarly journals Extensions in graph normal form

2020 ◽  
Author(s):  
Michał Walicki
Keyword(s):  
Normal Form ◽  
Fixed Points ◽  
Propositional Logic ◽  
Order Logic ◽  
First Order Logic ◽  
First Order ◽  
Special Cases

Abstract Graph normal form, introduced earlier for propositional logic, is shown to be a normal form also for first-order logic. It allows to view syntax of theories as digraphs, while their semantics as kernels of these digraphs. Graphs are particularly well suited for studying circularity, and we provide some general means for verifying that circular or apparently circular extensions are conservative. Traditional syntactic means of ensuring conservativity, like definitional extensions or positive occurrences guaranteeing exsitence of fixed points, emerge as special cases.

scholarly journals Flexible models for overdispersed and underdispersed count data

2021 ◽  
Author(s):  
Dexter Cahoy ◽  
Elvira Di Nardo ◽  
Federico Polito
Keyword(s):  
Poisson Distribution ◽  
Count Data ◽  
Hypergeometric Functions ◽  
Natural Generalization ◽  
Model Parameters ◽  
Probability Models ◽  
Limiting Behavior ◽  
Poisson Models ◽  
Special Cases ◽  
Flexible Models

AbstractWithin the framework of probability models for overdispersed count data, we propose the generalized fractional Poisson distribution (gfPd), which is a natural generalization of the fractional Poisson distribution (fPd), and the standard Poisson distribution. We derive some properties of gfPd and more specifically we study moments, limiting behavior and other features of fPd. The skewness suggests that fPd can be left-skewed, right-skewed or symmetric; this makes the model flexible and appealing in practice. We apply the model to real big count data and estimate the model parameters using maximum likelihood. Then, we turn to the very general class of weighted Poisson distributions (WPD’s) to allow both overdispersion and underdispersion. Similarly to Kemp’s generalized hypergeometric probability distribution, which is based on hypergeometric functions, we analyze a class of WPD’s related to a generalization of Mittag–Leffler functions. The proposed class of distributions includes the well-known COM-Poisson and the hyper-Poisson models. We characterize conditions on the parameters allowing for overdispersion and underdispersion, and analyze two special cases of interest which have not yet appeared in the literature.

Application of two approaches to model chlorine residuals in Severn Trent Water Ltd (STW) distribution systems

1997 ◽  
Vol 36 (5) ◽  
pp. 317-324 ◽  
Author(s):  
M.J. Rodriguez ◽  
J.R. West ◽  
J. Powell ◽  
J.B. Sérodes
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Treatment Plant ◽  
Residual Chlorine ◽  
Ann Model ◽  
Order Model ◽  
First Order ◽  
Chlorine Decay ◽  
Artificial Neural Network Ann ◽  
Key Parameter

Increasingly, those who work in the field of drinking water have demonstrated an interest in developing models for evolution of water quality from the treatment plant to the consumer's tap. To date, most of the modelling efforts have been focused on residual chlorine as a key parameter of quality within distribution systems. This paper presents the application of a conventional approach, the first order model, and the application of an emergent modelling approach, an artificial neural network (ANN) model, to simulate residual chlorine in a Severn Trent Water Ltd (U.K.) distribution system. The application of the first order model depends on the adequate estimation of the chlorine decay coefficient and the travel time within the system. The success of an ANN model depends on the use of representative data about factors which affect chlorine evolution in the system. Results demonstrate that ANN has a promising capacity for learning the dynamics of chlorine decay. The development of an ANN appears to be justifiable for disinfection control purposes, in cases when parameter estimation within the first order model is imprecise or difficult to obtain.

Representation of symmetric probability models

1969 ◽  
Vol 34 (2) ◽  
pp. 183-193 ◽  
Author(s):  
Peter H. Krauss
Keyword(s):  
Mathematical Theory ◽  
Preceding Paper ◽  
Probability Logic ◽  
Probability Models ◽  
Additional Material ◽  
First Order ◽  
Order Probability ◽  
Joint Publication

This paper is a sequel to the joint publication of Scott and Krauss [8] in which the first aspects of a mathematical theory are developed which might be called “First Order Probability Logic”. No attempt will be made to present this additional material in a self-contained form. We will use the same notation and terminology as introduced and explained in Scott and Krauss [8], and we will frequently refer to the theorems stated and proved in the preceding paper.

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