Periodicity analysis and a model structure for consumer behavior on hotel online search interest in the US

2017 ◽  
Vol 29 (5) ◽  
pp. 1486-1500 ◽  
Author(s):  
Juan Liu ◽  
Xue Li ◽  
Ya Guo
Keyword(s):  
Consumer Behavior ◽  
Least Squares ◽  
Nonlinear Least Squares ◽  
Model Parameters ◽  
Model Structure ◽  
Online Search ◽  
Content Type ◽  
The Usa ◽  
Frequency Components ◽  
Least Squares Algorithm

Purpose This paper aims to analyze and model consumer behavior on hotel online search interest in the USA. Design/methodology/approach Discrete Fourier transform was used to analyze the periodicity of hotel search behavior in the USA by using Google Trends data. Based on the obtained frequency components, a model structure was proposed to describe the search interest. A separable nonlinear least squares algorithm was developed to fit the data. Findings It was found that the major dynamics of the search interest was composed of nine frequency components. The developed separable nonlinear least squares algorithm significantly reduced the number of model parameters that needed to be estimated. The fitting results indicated that the model structure could fit the data well (average error 0.575 per cent). Practical implications Knowledge of consumer behavior on online search is critical to marketing decision because search engine has become an important tool for customers to find hotels. This work is thus very useful to marketing strategy. Originality/value This research is the first work on analyzing and modeling consumer behavior on hotel online search interest.

scholarly journals Quantifying soil hydraulic properties and their uncertainties by modified GLUE method

2017 ◽  
Vol 31 (3) ◽  
pp. 433-445
Author(s):  
Yifan Yan ◽  
Jianli Liu ◽  
Jiabao Zhang ◽  
Xiaopeng Li ◽  
Yongchao Zhao
Keyword(s):  
Confidence Interval ◽  
Least Squares ◽  
Water Content ◽  
Soil Water ◽  
Nonlinear Least Squares ◽  
Uncertainty Estimation ◽  
Model Parameters ◽  
Retention Curve ◽  
Least Squares Algorithm ◽  
Soil Hydraulic

AbstractNonlinear least squares algorithm is commonly used to fit the evaporation experiment data and to obtain the ‘optimal’ soil hydraulic model parameters. But the major defects of nonlinear least squares algorithm include non-uniqueness of the solution to inverse problems and its inability to quantify uncertainties associated with the simulation model. In this study, it is clarified by applying retention curve and a modified generalised likelihood uncertainty estimation method to model calibration. Results show that nonlinear least squares gives good fits to soil water retention curve and unsaturated water conductivity based on data observed by Wind method. And meanwhile, the application of generalised likelihood uncertainty estimation clearly demonstrates that a much wider range of parameters can fit the observations well. Using the ‘optimal’ solution to predict soil water content and conductivity is very risky. Whereas, 95% confidence interval generated by generalised likelihood uncertainty estimation quantifies well the uncertainty of the observed data. With a decrease of water content, the maximum of nash and sutcliffe value generated by generalised likelihood uncertainty estimation performs better and better than the counterpart of nonlinear least squares. 95% confidence interval quantifies well the uncertainties and provides preliminary sensitivities of parameters.

Integrating Parameter Estimation Solutions From the Time and Time-Scale Domains

2009 ◽  
Author(s):  
James R. McCusker ◽  
Kourosh Danai
Keyword(s):  
Parameter Estimation ◽  
Least Squares ◽  
Time Scale ◽  
Prediction Error ◽  
Nonlinear Least Squares ◽  
Integrated Approach ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Single Model ◽  
Iterative Estimation

A method of parameter estimation was recently introduced that separately estimates each parameter of the dynamic model [1]. In this method, regions coined as parameter signatures, are identified in the time-scale domain wherein the prediction error can be attributed to the error of a single model parameter. Based on these single-parameter associations, individual model parameters can then be estimated for iterative estimation. Relative to nonlinear least squares, the proposed Parameter Signature Isolation Method (PARSIM) has two distinct attributes. One attribute of PARSIM is to leave the estimation of a parameter dormant when a parameter signature cannot be extracted for it. Another attribute is independence from the contour of the prediction error. The first attribute could cause erroneous parameter estimates, when the parameters are not adapted continually. The second attribute, on the other hand, can provide a safeguard against local minima entrapments. These attributes motivate integrating PARSIM with a method, like nonlinear least-squares, that is less prone to dormancy of parameter estimates. The paper demonstrates the merit of the proposed integrated approach in application to a difficult estimation problem.

When the owl of Minerva flew at dusk: marketing in Greater Germany, 1918‐1939

2009 ◽  
Vol 21 (1) ◽  
pp. 92-104 ◽  
Author(s):  
Ronald A. Fullerton
Keyword(s):  
Consumer Behavior ◽  
Design Methodology ◽  
Cross Cultural ◽  
Economic Conditions ◽  
German Language ◽  
Economic Changes ◽  
Content Type ◽  
The World ◽  
Peripheral Position ◽  
The Usa

PurposeDuring the 1920s and into the 1930s, German‐language work on consumer behavior led the world; for example, segmentation was clearly discussed from the late 1920s. The purpose of this paper is to show how marketing thought in Germany and Austria reached a peak even as the environmental substructure that sustained it was being seriously eroded by political and economic changes that forever consigned it to a peripheral position upon the world stage.Design/methodology/approachThe design of the study is a critical historical one relying heavily upon documents produced during the period discussed. Statements are weighed and evaluated.FindingsThe paper finds that very impressive, at times world‐leading, work was being done in the 1920s and early 1930s, particularly in the areas of segmentation and what would later become known as consumer behavior. Much of what later became known as Motivation Research, or example, was pioneered in Germany and Austria before 1934.Research limitations/ implicationsThe primary implication is that a great deal of marketing thought developed outside the USA, sometimes drawing upon US marketing thought, in other cases developing completely independently. A second implication is that marketing thought can be weakened by political and economic conditions, as Germany and Austria painfully experienced.Originality/valueThis is the first study to explore historical German and Austrian marketing thought in a cross‐cultural manner, comparing and contrasting them with thought developed elsewhere.

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