scholarly journals The Effect of Marketing Mix upon The Consumer’s Decision Making to Buy a Product at PT. Griya Pagelaran Bogor,

2018 ◽  
Vol 3 (1) ◽  
pp. 59
Author(s):  
Sumardjono Jono ◽  
Heni Ardila
Keyword(s):  
Decision Making ◽  
Structural Equation Modeling ◽  
Maximum Likelihood ◽  
Analytical Method ◽  
Structural Equation ◽  
Price Level ◽  
Marketing Mix ◽  
Equation Modeling ◽  
Significance Level ◽  
Level Of Significance

The purpose of this study is to determine and prove whether the variablesof the marketing mix significantly has influenced the consumer’s decision making tobuy the product at PT. Griya Pagelaran Bogor. The population of this study are thenumber of unknown sampling determination using Maximum Likelihood estimationmethod by taking samples of consumers who their needs has met with theresearcher requirement as many as 150 respondents. The analytical method hasused is Structural Equation Modeling (SEM) using AMOS 21 program. The result ofthe research shows that 1) Product Variables have a significance level of 0.05 whichis 1,965 > 1,96 and value (p) probability 0,49 ≤ 0.05. Then Ha is accepted andsignificant effect. 2) Variable Price level of significance 0.05 is 2.023 > 1.96 and hasa probability of 0.43 which is below 0.05. And the value (p) probability ≤ 0.05 then Hais accepted and significant effect. 3) Place Variables significance level of 0.05 is2.251 > 1.96 and has a probability of 0.24 which is below 0.05. And the value (p)probability ≤ 0.05 then Ha is accepted and significant effect. 4) Promotion Variables0.05 level of significance is 3.435 > 1.96 and has a probability in accordance with therecommended. And the value (p) probability ≤ 0.05 then Ha accepted and significanteffect.

THE EFFECT OF MARKETING MIX UPON THE CONSUMER’S DECISION MAKING TO BUY A PRODUCT AT PT GRIYA PAGELARAN BOGOR

2018 ◽  
Vol 3 (01) ◽  
pp. 59
Author(s):  
Sumardjono Jono ◽  
Heni Ardila
Keyword(s):  
Decision Making ◽  
Structural Equation ◽  
Price Level ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Marketing Mix ◽  
Equation Modeling ◽  
Significance Level ◽  
Level Of Significance ◽  
Maximum Likelihood Estimation Method

The purpose of this study is to determine and prove whether the variables of  the marketing mix significantly has influenced  the consumer’s decision making to buy the product at PT. Griya Pagelaran Bogor. The population of this study are the number of unknown sampling determination using Maximum Likelihood estimation method by taking samples of consumers who their needs has met with the researcher requirement as many as 150 respondents. The analytical method has used is Structural Equation Modeling (SEM) using AMOS 21 program. The result of the research shows that 1) Product Variables have a significance level of 0.05 which is 1,965 > 1,96 and value (p) probability 0,49 ≤ 0.05. Then Ha is accepted and significant effect. 2) Variable Price level of significance 0.05 is 2.023 > 1.96 and has a probability of 0.43 which is below 0.05. And the value (p) probability ≤ 0.05 then Ha is accepted and significant effect. 3) Place Variables significance level of 0.05 is 2.251 > 1.96 and has a probability of 0.24 which  is below 0.05. And the value (p) probability ≤ 0.05 then Ha is accepted and significant effect. 4) Promotion Variables 0.05 level of significance is 3.435 > 1.96 and has a probability in accordance with the recommended. And the value (p) probability ≤ 0.05 then Ha accepted and significant effect.Keywords: Marketing Mix, Consumer Purchase Decision, SEM

Challenges in Nonlinear Structural Equation Modeling

Methodology ◽  
2007 ◽  
Vol 3 (3) ◽  
pp. 100-114 ◽  
Author(s):  
Polina Dimitruk ◽  
Karin Schermelleh-Engel ◽  
Augustin Kelava ◽  
Helfried Moosbrugger
Keyword(s):  
Structural Equation Modeling ◽  
Maximum Likelihood ◽  
Structural Equation ◽  
Nonlinear Effects ◽  
Structural Equations ◽  
Estimation Methods ◽  
Equation Modeling ◽  
Parameter Estimates ◽  
Nonlinear Structural ◽  
Nonlinear Structural Equation

Abstract. Challenges in evaluating nonlinear effects in multiple regression analyses include reliability, validity, multicollinearity, and dichotomization of continuous variables. While reliability and validity issues are solved by employing nonlinear structural equation modeling, multicollinearity remains a problem which may even be aggravated when using latent variable approaches. Further challenges of nonlinear latent analyses comprise the distribution of latent product terms, a problem especially relevant for approaches using maximum likelihood estimation methods based on multivariate normally distributed variables, and unbiased estimates of nonlinear effects under multicollinearity. The only methods that explicitly take the nonnormality of nonlinear latent models into account are latent moderated structural equations (LMS) and quasi-maximum likelihood (QML). In a small simulation study both methods yielded unbiased parameter estimates and correct estimates of standard errors for inferential statistics. The advantages and limitations of nonlinear structural equation modeling are discussed.

Study on the Integrated Method of SEM and DEMATEL

2014 ◽  
Vol 926-930 ◽  
pp. 3722-3727
Author(s):  
Wei Meng
Keyword(s):  
Decision Making ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Model Fitting ◽  
Assessment Model ◽  
Model Specification ◽  
Equation Modeling ◽  
Model Assessment ◽  
Integrated Method ◽  
Model Modification

This paper compares Structural Equation Modeling and Decision Making Trial and Evaluation Laboratory. Structural Equation Modeling and Decision Making Trial and Evaluation Laboratory are all methods to study factors’ structure problem. Some steps of the two methods can completely replace each other and complement each other. This paper puts forward an integrated method of Structural Equation Modeling and Decision Making Trial and Evaluation Laboratory that includes competing model specification, model fitting, model assessment, model modification and result explain.

scholarly journals EMPOWERING LEADERSHIP DAN KINERJA PEGAWAI: SEBUAH STUDI EMPIRIS PADA DISTRIK X KABUPATEN MAYBRAT

2021 ◽  
Vol 6 (2) ◽  
pp. 149-156
Author(s):  
Reijeng Tabara ◽  
Niar Azriya ◽  
Uswatul Mardliyah
Keyword(s):  
Structural Equation Modeling ◽  
Least Squares ◽  
Significant Influence ◽  
Structural Equation ◽  
Employee Performance ◽  
Equation Modeling ◽  
Empowering Leadership ◽  
Significance Level ◽  
A Value ◽  
West Papua

The purpose of this study is to determine the influence of Empowering Leadership on the performance Employees of District X Maybrat Regency. The study used Partial Least Squares (PLS) with Structural Equation Modeling (SEM) techniques to analyze 45 employees. The results showed there was a positive and significant influence between Empowering Leadership on employee performance with a value TStatistic greater than Tsabel (Tstatistic 31,692 1,679 Ttabel) at a significance level of 5% (0.05). The results of this study indicate that the higher Empowering Leadership that the organization has, the more it will improve the performance of Employees in District X Maybrat regency of West Papua

scholarly journals Estimasi Parameter Structural Equation Modeling Terhadap Kepuasan Pelanggan Layanan Telekomunikasi Menggunakan Metode Maximum Likelihood

2020 ◽  
Vol 1 (1) ◽  
pp. 48
Author(s):  
Dwicahyo Ramadhan Priyatna ◽  
Raupong Raupong ◽  
La Podje Talangko
Keyword(s):  
Structural Equation Modeling ◽  
Maximum Likelihood ◽  
Customer Satisfaction ◽  
Natural Science ◽  
Latent Variables ◽  
Structural Equation ◽  
Sampling Technique ◽  
Likelihood Method ◽  
Equation Modeling ◽  
Students Satisfaction

Structural Equation Modeling is a statistical technique that is able to analyze the pattern of simultan linear relationships between indicator variables and latent variables. In this study using structural equation modeling to analyze the relationship between perceived quality, perceived value, perceived bestscore, and customer satisfaction. The purpose of this study is to obtain the result parameter model estimation of structural equation modeling using maximum likelihood method and to obtain the level of students satisfaction from faculty of Mathematics and Natural Science Hasanuddin University toward Tri operator. Data collected by distributing questionnaire. Collecting sample in this study using Proporsional Random Sampling technique. To measure the level of students satisfaction from faculty of Mathematics and Natural Science Hasanuddin University toward Tri operator, the model chosen is the model used to measure Indonesian Customer Satisfaction Indeks. From the result of this study obtained in the amount of 92,04% with very satisfied criteria level of students satisfaction from faculty of Mathematics and Natural Science Hasanuddin University toward Tri operator with very satisfied criteria.

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