The Social Influence of Brand Community: Evidence from European Car Clubs

2005 ◽  
Vol 69 (3) ◽  
pp. 19-34 ◽  
Author(s):  
René Algesheimer ◽  
Utpal M. Dholakia ◽  
Andreas Herrmann
Keyword(s):  
Structural Equation Model ◽  
Structural Equation ◽  
Equation Model ◽  
Negative Consequences ◽  
Brand Community ◽  
Moderating Effects ◽  
Community Influence ◽  
Brand Knowledge ◽  
The Social ◽  
Community Pressure

The authors develop and estimate a conceptual model of how different aspects of customers’ relationships with the brand community influence their intentions and behaviors. The authors describe how identification with the brand community leads to positive consequences, such as greater community engagement, and negative consequences, such as normative community pressure and (ultimately) reactance. They examine the moderating effects of customers’ brand knowledge and the brand community's size and test their hypotheses by estimating a structural equation model with survey data from a sample of European car club members.

scholarly journals A structural equation model of cooperative member satisfaction and long-term commitment

2019 ◽  
Vol 22 (2) ◽  
pp. 247-263 ◽  
Author(s):  
Jasper Grashuis ◽  
Michael Lee Cook
Keyword(s):  
Structural Equation Model ◽  
Structural Equation ◽  
The United States ◽  
Equation Model ◽  
Negative Consequences ◽  
Term Survival ◽  
Farmer Cooperatives ◽  
Attitudes And Perceptions ◽  
Member Satisfaction

The organizational growth of farmer cooperatives is tied to increased heterogeneity in member attitudes and perceptions. To inform possible solutions, a better understanding of the complex interrelationships of member attitudes and perceptions is necessary. Using survey responses from 1,116 members of an organic marketing cooperative in the United States, this paper develops a structural equation model of six factors: organic lifestyle, mission support, participation, trust, satisfaction, and long-term commitment. The final model illustrates nine significant relationships, including satisfaction and long-term commitment. The result suggests the long-term survival or viability of farmer cooperatives is not only dependent on its financial performance but also the utility of its members. In terms of member attitudes and perceptions, trust and mission support may offer the best opportunities for farmer cooperatives to foster member satisfaction and thus address the negative consequences of heterogeneity.

scholarly journals The Relationship between Emotional Regulation and School Burnout: Structural Equation Model According to Dedication to Tutoring

2019 ◽  
Vol 16 (23) ◽  
pp. 4703 ◽  
Author(s):  
Ramón Chacón-Cuberos ◽  
Asunción Martínez-Martínez ◽  
Marina García-Garnica ◽  
María Dolores Pistón-Rodríguez ◽  
Jorge Expósito-López
Keyword(s):  
Structural Equation Model ◽  
Mental State ◽  
Emotional Regulation ◽  
Structural Equation ◽  
School Context ◽  
Equation Model ◽  
Negative Consequences ◽  
Expressive Suppression ◽  
Cross Sectional ◽  
School Burnout

School burnout constitutes a current phenomenon which generates diverse negative consequences in the personal and academic lives of students. Given this situation, it is necessary to develop actions that permit us to regulate this harmful mental state and that are administered from within the school context. A descriptive and cross-sectional study is presented that pursues the objective of examining a structural equation model which brings together burnout and emotional regulation. The model assumes that students receive tutoring at school in order to tackle these types of problems. For this, the sample constituted a total of 569 students from the province of Granada (men = 52.3% (n = 298); women = 47.7% (n = 271)). Mean age was reported as 10.39 ± 0.95 years and the School Burnout Inventory (BMI) and the Emotional Regulation Scale were utilized as the principal instruments. As main findings it was observed that students who received one hour of weekly tutoring showed a positive relationship between expressive suppression as a strategy of emotional regulation, cynicism, and exhaustion as consequences of school burnout. In the same way, a direct association existed between burnout-related exhaustion and cognitive repair. Given that significant relationships could not be observed between these variables in students who do not receive tutoring, higher use of emotional regulation was confirmed amongst tutored students when faced with this negative mental state.

The Structural Equation Model for Public Evaluation of the Transfer Efficiency of Rail Transit P&R Facilities

2013 ◽  
Vol 368-370 ◽  
pp. 2027-2033
Author(s):  
Xiao Nian Sun ◽  
Yuan Yuan Mai ◽  
Xian Guang Wang
Keyword(s):  
Structural Equation Model ◽  
Structural Equation ◽  
Social Equity ◽  
Service Level ◽  
Equation Model ◽  
Transfer Efficiency ◽  
Rail Transit ◽  
The Public ◽  
The Social ◽  
Public Evaluation

The public participation in evaluating the rail transit P&R facilities is beneficial for enhancing the objectivity of the evaluation and reflecting the social equity to the greatest degree, so that the decision-making can be more people-oriented. Based on the analysis of the P&R travelling features of sedan cars and the transfer facilities service level, this paper, from the perspective of the public evaluation, makes a structural equation model which shows the evaluation of sedan car travelers toward the transfer efficiency of rail transit P&R facilities and elaborates the identification, fitting, correction and applications of the model.

scholarly journals Tree-based Matching on Structural Equation Model Parameters

2021 ◽  
Author(s):  
Sarfaraz Serang ◽  
James Sears
Keyword(s):  
Social Sciences ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Treatment Effects ◽  
Equation Model ◽  
Causal Effects ◽  
Model Parameters ◽  
Simulation Studies ◽  
Proof Of Concept ◽  
The Social

Understanding causal effects of a treatment is often of interest in the social sciences. When treatments cannot be randomly assigned, researchers must ensure that treated and untreated participants are balanced on covariates before estimating treatment effects. Conventional practices are useful in matching such that treated and untreated participants have similar average values on their covariates. However, situations arise in which a researcher may instead want to match on model parameters. We propose an algorithm, Causal Mplus Trees, which uses decision trees to match on structural equation model parameters and estimates conditional average treatment effects in each node. We provide a proof of concept using two small simulation studies and demonstrate its application using COVID-19 data.

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