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Antecedents and consequences of apparel involvement
Antecedents and consequences of apparel involvement

... However, little work has focused thoroughly on apparel involvement. There were several studies that used the concept of apparel involvement in relation to other consumer behavior variables. However, these studies simply borrowed previous perspectives and measures by merely attaching the concept of p ...
Real business cycles: A Reader
Real business cycles: A Reader

... G.King and Charles I.Plosser for “Real Business Cycles and the Test of the Adelmans” in Journal of Monetary Economics, vol. 33:2, April 1989, pp. 405–438. Louisiana State University Press and James E.Hartley, Kevin D.Salyer and Steven M.Sheffrin for “Calibration and Real Business Cycle Models: An Un ...
Resilience
Resilience

... • How are different transport modes affected? Are existing public transport systems able to step into the breach? If not, which investments are necessary to prepare public transport for possible new challenges? • Which new opportunities and challenges will arise for electric mobility as well as neig ...
New Measures of Clumpiness for Incidence Data Yao Zhang Eric T. Bradlow
New Measures of Clumpiness for Incidence Data Yao Zhang Eric T. Bradlow

... interest and never come back, or just simply have become “inactive” for a period of time and return. Once he returns, it is very likely that he would make a lot of purchases again. As a result, a nice/valid measure of clumpiness adds a new building block to profiling customers by which companies ar ...
Learning Latent Sentiment Scopes for Entity
Learning Latent Sentiment Scopes for Entity

... complete sentence, while they do not overlap with one another. However, the sentiment scopes are not explicitly annotated in the training data. We thus need to build models that can automatically learn such latent information from the data. As we will see later, with the above assumptions on the pro ...
A Joint Model of Usage and Churn in Contractual
A Joint Model of Usage and Churn in Contractual

... (e.g., work travel means fewer visits to the gym in a given week), it is easy to think of a common factor (e.g., commitment) affecting both decisions. As a consequence, if we want to understand and predict customer usage and renewal behaviors, we should model them jointly. Another common characteri ...
PDF
PDF

... over 95% had eaten these nuts in the previous twelve months. The number of pecan purchases during the previous six months for each respondent is used as the dependent variable in the model. Pecan purchasers averaged approximately three purchases during the survey period. We label respondents who did ...
Research article
Research article

... extended this notion of hierarchy (temporal sequence) by shifting focus to a set of core constructs: attention, affect, memory, and desirability. These core constructs can affect advertising success independently or in combination (Haley and Baldinger 2000; Morwitz, Steckel, and Gupta 2007; Walker a ...
Bank of England working paper no.58
Bank of England working paper no.58

... utility of consumption. Equation (4) determines how consumers trade off consumption and leisure and states that the marginal rate of substitution between them equals the real wage rate. Under standard assumptions on the utility function (4) suggests that increases in the real wage should bring forth ...
Some Applications of Data Mining Tools in Database Marketing
Some Applications of Data Mining Tools in Database Marketing

... CART analysis, when the misclassification rate for Logit regression is a parametric appr"ach which is well understood and widely used in csregorical EC is 18.38%, the rate is about 26% for non-EC. When the misclassification rate for EC is 11.6%, data analysis for its simplicity and be:rer performanc ...
Predicting Advertising Success Beyond Traditional Measures: New
Predicting Advertising Success Beyond Traditional Measures: New

... equity. Because popular brands tend to have higher premea­ sure scores, it is important to account for this bias before making any judgments about shifts in desirability. Walker and Dubitsky (1994) propose a method by which change scores are normalized by using a baseline predicted average result (P ...
chapter one - Covenant University Repository
chapter one - Covenant University Repository

... structurally heavily parameterized and essentially static. In addition, they cannot handle uncertainties and intertemporal features. This thesis will contribute to quantitative macroeconomic assessment of the Nigerian economy based on the characterization and analyses of business cycles in a Dynamic ...
Analyses of Online Advertising Performance Using
Analyses of Online Advertising Performance Using

... 2. Categorize digital marketing channels based on the analysis. 3. Propose an attribution modeling approach and key metrics that best fit the industry based on the given datasets. Due to the nature of the problem, a set of hypotheses, which will be reviewed during the analysis, must be set to suppor ...
Cluster Analysis
Cluster Analysis

... distance measures. Compare the results across measures to determine the stability of the solutions. 2. Use different methods of clustering and compare the results. 3. Split the data randomly into halves. Perform clustering separately on each half. Compare cluster centroids across the two subsamples. ...
Asymmetric preference formation in willingness to pay estimates in
Asymmetric preference formation in willingness to pay estimates in

... random taste heterogeneity. This shows that by accounting for APS, modellers can reduce the impact of the unobserved part of utility on model results. In this paper, we look at a different issue that falls within the general field of attribute processing strategies, namely whether there are asymmetr ...
Elements of a Decision Analysis
Elements of a Decision Analysis

... Bidding for a Government Contract at SciTools • The value model in this example is straightforward but in other examples it is often complex – If SciTools decides right now not to bid, then its monetary values is $0 - no gain, no loss – If they make a bid and are underbid by a competitor, then they ...
APPLICATION OF NIR SPECTROSCOPY FOR WHISKY
APPLICATION OF NIR SPECTROSCOPY FOR WHISKY

... figure 1B [Inon et al. 2006]. The spectral range between 6000-5660 cm-1 corresponds to the first overtone of the C-H stretching vibrations in CH3 and CH2 group. The spectral range between 4580-4200 cm-1 corresponds to the combination of CH vibrations [Workman 1996]. NIR spectra of the same types of ...
here
here

... than variance shared between the LV's. If this is true for the target LV and all the other LV's, this suggests the discriminant validity of the target LV. Unfortunately, experience suggests that AVE in LV Interactions and Quadratics is typically low, frequently less than 50%. For example, while the ...
Selecting Peer Institutions with Cluster Analysis
Selecting Peer Institutions with Cluster Analysis

... The appropriate clustering algorithm and parameter settings (including values such as the distance function, density threshold or the number of expected clusters) depend on the individual data set and intended use of the results. Cluster analysis is an iterative process of knowledge discovery and op ...
estimating latent variable interactions and quadratics
estimating latent variable interactions and quadratics

... This technique is popular in the substantive literatures, and is a preferred technique in some situations. Jaccard, Turissi and Wan (1990) state that subgroup analysis may be appropriate when the model could be structurally different for different subgroups of subjects. They also point out that an i ...
Incorporating Competitor Data into CRM
Incorporating Competitor Data into CRM

... public-policy motivated findings suggest detailing and sampling serve primarily an informative role. Using a fixed-effects model, physician-specific effects are considered by Mizik and Jacobson (2004). The authors also include lagged prescriptions to allow for physician preferences to persist over t ...
Estimating Supply Elasticity for Disaggregated Paper Products: A
Estimating Supply Elasticity for Disaggregated Paper Products: A

... regression that estimates, in the present case, how market price changes are influenced by demand. To identify these effects, economic variables that are highly correlated with product demand are regressed against output price. Predicted price values from this first-stage regression are then used in ...
Assessment of the precision of an analytical technique
Assessment of the precision of an analytical technique

... total variance by hand (using Excel): this will be helpful to understand the relationship between these variances and the different "Mean Squares" given by Excel i.e. the Between Mean Square (BMS) (“entre groupes” in French ) and the Within Mean Square (WMS) (“à l'intérieur du groupe” in French). It ...
PDF
PDF

... because an individual’s characteristics are invariant among a set of choices. In an econometric sense this means that the effect of individual characteristics are not identifiable in the probability of choosing commodities. In essence, the model parameters are the same for each sampled individual im ...
Download paper (PDF)
Download paper (PDF)

... stream reflects not only the importance of new products, but also the role of diffusion research in helping managers to better plan their entry strategy, target the right consumer, and anticipate demand so as to formulate an efficient and effective promotion, production, and distribution strategy. A ...
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Sensitivity analysis

Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be apportioned to different sources of uncertainty in its inputs. A related practice is uncertainty analysis, which has a greater focus on uncertainty quantification and propagation of uncertainty. Ideally, uncertainty and sensitivity analysis should be run in tandem.The process of recalculating outcomes under alternative assumptions to determine the impact of variable under analysis Sensitivity analysis can be useful for a range of purposes, including Testing the robustness of the results of a model or system in the presence of uncertainty. Increased understanding of the relationships between input and output variables in a system or model. Uncertainty reduction: identifying model inputs that cause significant uncertainty in the output and should therefore be the focus of attention if the robustness is to be increased (perhaps by further research). Searching for errors in the model (by encountering unexpected relationships between inputs and outputs). Model simplification – fixing model inputs that have no effect on the output, or identifying and removing redundant parts of the model structure. Enhancing communication from modelers to decision makers (e.g. by making recommendations more credible, understandable, compelling or persuasive). Finding regions in the space of input factors for which the model output is either maximum or minimum or meets some optimum criterion (see optimization and Monte Carlo filtering). In case of calibrating models with large number of parameters, a primary sensitivity test can ease the calibration stage by focusing on the sensitive parameters. Not knowing the sensitivity of parameters can result in time being uselessly spent on non-sensitive ones.Taking an example from economics, in any budgeting process there are always variables that are uncertain. Future tax rates, interest rates, inflation rates, headcount, operating expenses and other variables may not be known with great precision. Sensitivity analysis answers the question, ""if these variables deviate from expectations, what will the effect be (on the business, model, system, or whatever is being analyzed), and which variables are causing the largest deviations?""
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