Supplemental Material for Meta-Analytic Structural Equation Modeling With Moderating Effects on SEM Parameters

2019 ◽  
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Moderating Effects

Parenting quality, adversity, and conduct problems in adolescence: Testing process-oriented models of resilience

1993 ◽  
Vol 5 (4) ◽  
pp. 663-682 ◽  
Author(s):  
Scott D. Gest ◽  
Jennifer Neemann ◽  
Jon J. Hubbard ◽  
Ann S. Masten ◽  
Auke Tellegen
Keyword(s):  
Structural Equation Modeling ◽  
Conduct Problems ◽  
Structural Equation ◽  
Extended Family ◽  
Equation Modeling ◽  
Childhood And Adolescence ◽  
Moderating Effects ◽  
Negative Effects ◽  
Effective Parenting ◽  
Parenting Quality

AbstractStructural equation modeling was used (a) to determine the extent to which parent-related and non-parent-related adversity were associated with increases in conduct problems between childhood and adolescence and (b) to evaluate the possible preventive, compensatory, and moderating effects of parenting quality in this regard. Subjects were 180 boys and girls from the Project Competence longitudinal study of adversity, competence, and resilience (Garmezy & Tellegen, 1984). Conduct problems, parenting quality, and socioeconomic status were assessed when subjects were in the third through sixth grades, and adversity and conduct problems were assessed again 7 years later. Results were consistent with the view that parentrelated adversity experienced between the two assessment times was associated with a small increase in conduct problems. Adversity involving siblings, extended family, and friends was not associated with changes in conduct. Effective parenting was associated with less parent-related adversity during adolescence. Effective parenting, however, did not directly compensate for the negative effects of adversity; nor did it moderate the effects of adversity. Structural equation modeling was helpful in testing for several of these effects simultaneously. Short-term longitudinal studies with baseline measures, more frequent assessments, and adequate sample size are necessary to clarify the processes suggested by these results.

Promote the price promotion

2014 ◽  
Vol 26 (7) ◽  
pp. 1065-1082 ◽  
Author(s):  
Hui-Chun Huang ◽  
Ya-Ting Chang ◽  
Che-Yi Yeh ◽  
Chung-Wei Liao
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Purchase Intentions ◽  
Equation Modeling ◽  
Moderating Effects ◽  
Price Promotions ◽  
Content Type ◽  
Chain Stores ◽  
Moderating Role

Purpose – The authors empirically evaluated the effect of price promotions on customer quality evaluations and repeat-purchase intentions in coffee chain stores. The moderating role of customer characteristics in this process was also investigated. Design/methodology/approach – Consumers in 12 coffee chain stores were surveyed and 488 usable questionnaires were obtained. Relationships in the test model were examined using structural equation modeling techniques. A multiple-group solution was used to test the moderating effects of consumer characteristics. Findings – The results of structural equation modeling analyses suggested that price-promotion activities at Starbucks in Taiwan had a favorable effect on customer quality evaluations and positively influenced repeat-purchase intentions. The moderating effects of consumer characteristics were partially supported. Whereas sex showed no significant moderating effect, consumption frequency did demonstrate a moderating effect. Practical implications – The results indicate that existing customers may see price promotions at Starbucks in Taiwan as a reward or incentive, and thus lead to an increase in favorable evaluations. The findings provide a new perspective that may encourage those involved in the marketing of coffee chain stores to manage price promotions in a more strategic manner by considering customer characteristics. Originality/value – The effects of price promotions on brand evaluation remain controversial and may vary among product categories. Additionally, most studies regarding price promotions have used an experimental approach, and few studies of price promotions in the coffee industry have been reported. The study is among the first to empirically examine the effects of price promotions and the moderating role of consumer characteristics in the process at coffee chain stores.

Brand involvement in retaining customers despite dissatisfaction

2013 ◽  
Vol 41 (4) ◽  
pp. 643-650 ◽  
Author(s):  
Yih-Chearng Shiue ◽  
Lisa Shih-Hua Li
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Theory And Practice ◽  
Equation Modeling ◽  
Moderating Effects ◽  
Shopping Experience ◽  
Brand Involvement ◽  
Negative Messages

In this study, we investigated the importance of brand involvement in retaining dissatisfied customers. We surveyed 377 customers dissatisfied with their shopping experience on the Lativ shopping website because of its dishonesty, and then analyzed the data using structural equation modeling. The results revealed that brand involvement had moderating effects that improved the possibility of repatronage in the presence of many negative messages. This fits with previous studies in which it was shown that inertia had no influence on customers, and clarifies our understanding of the importance of brand involvement as a buffer that decreases customer exit intentions following organizational failures. Finally, the findings contribute to theory and practice in relation to our investigation of the factors of consumers' intentions reflected in their dissatisfied responses, and the role of brand involvement in repatronage.

scholarly journals The Effect of Airport Self-Service Characteristics on Passengers’ Perceived Value, Satisfaction, and Behavioral Intention: Based on the SOR Model

2019 ◽  
Vol 11 (19) ◽  
pp. 5352 ◽  
Author(s):  
Jong-Hyeon Kim ◽  
Jin-Woo Park
Keyword(s):  
Structural Equation Modeling ◽  
Waiting Time ◽  
Behavioral Intention ◽  
Structural Equation ◽  
Equation Modeling ◽  
Moderating Effects ◽  
Service Characteristics ◽  
International Airport ◽  
Perceived Values ◽  
Self Service

This paper analyzes the effects of airport self-service characteristics on behavioral intention through the perceived values and satisfaction in passengers based on the Stimulus-Organism-Response (SOR) model. For this purpose, a survey was conducted with passengers having used self-service technologies (SSTs) at Incheon International Airport. A total of 400 questionnaires were then analyzed using structural equation modeling. Four SST factors—functionality, enjoyment, customization, and convenience—were found to have significant effects on behavioral intention through the perceived values and customer satisfaction. As for the moderating effects of self-efficacy and waiting time, significant differences were found in the effects of the airport self-service characteristics. The results of this study are expected to be useful as basic data to aid strategies to develop and improve SSTs at Incheon International Airport.

Antecedents of Loyalty Towards Online Retailers

2014 ◽  
Vol 12 (4) ◽  
pp. 32-45
Author(s):  
Soma Sur
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Integrated Model ◽  
Equation Modeling ◽  
Moderating Effects ◽  
Theoretical Understanding ◽  
General Lack ◽  
Online Retailers

E-tailing has had a phenomenal growth in the last few years but still great potential remains unused because of consumers' general lack of trust in online retailers. The purpose of this study is to develop and test an integrated model to understand the role of satisfaction and trust in building e-loyalty. It further explores the moderating effects of shopping levels on antecedents of trust, satisfaction and loyalty toward an Internet retailer. The study has used structural equation modeling to reveal the nature of relational influences of these constructs on loyalty. The moderating effects of the levels of shopping are observed as the price/value had a stronger effect on e-satisfaction for light shoppers, while e-trust had a stronger effect on e-satisfaction for heavy shoppers. This study not only advances our theoretical understanding but also helps practitioners to formulate strategies to convert light shoppers to heavy and loyal ones.

scholarly journals ESTIMATING MODERATING EFFECTS IN PLS-SEM AND PLSc-SEM: INTERACTION TERM GENERATION*DATA TREATMENT

2018 ◽  
Vol 2 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Jan-Michael Becker ◽  
Christian M. Ringle ◽  
Marko Sarstedt
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Treatment Options ◽  
Equation Modeling ◽  
Moderating Effects ◽  
Parameter Recovery ◽  
Data Treatment ◽  
Interaction Terms ◽  
Interaction Term ◽  
The Impact

When estimating moderating effects in partial least squares structural equation modeling (PLSSEM), researchers can choose from a variety of approaches to model the influence of a moderator on a relationship between two constructs by generating different interaction terms. While prior research has evaluated the efficacy of these approaches in the context of PLS-SEM, the impact of different data treatment options on their performance in the context of standard PLS-SEM and consistent PLS-SEM (PLSc-SEM) is as yet unexplored. Our simulation study addresses these limitations and explores if the choice of approach and data treatment option has a pronounced impact on the methods’ parameter recovery. An empirical application substantiates these findings. Based on our results, we offer recommendations for researchers wishing to estimate moderating effects by means of PLS-SEM and PLSc-SEM.

Using Data Labels to Discover Moderating Effects in PLS-Based Structural Equation Modeling

2016 ◽  
pp. 1298-1311
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Moderating Effects ◽  
Model Driven ◽  
Correlation Analyses ◽  
Using Data

PLS-based structural equation modeling is extensively used in e-collaboration research, as well as in many other fields of research. Two main types of exploratory analyses are frequently employed in the context of PLS-based structural equation modeling: covariance (or correlation) analyses, where the covariances (or correlations) among all variables are inspected; and model-driven exploratory analyses, where one or more variations of theory-supported models are built and adjusted associations among variables are inspected. These analyses, while useful, provide limited insights about the possible presence of moderating effects. We discuss a general approach through which researchers can employ data labels, implemented as symbols that are displayed together with legends on graphs, to uncover moderating relationships among variables. The discussion is illustrated with the software WarpPLS version 4.0. While the approach is illustrated in the context of e-collaboration research, it arguably applies to any field where PLS-based structural equation modeling can be used.

The Role Of Word Of Mouth’s Value Co-Creation On The Achievement Of Sustainability

2021 ◽  
Vol 4 (2) ◽  
pp. 846-866
Author(s):  
Yud Buana
Keyword(s):  
Corporate Social Responsibility ◽  
Structural Equation Modeling ◽  
Structural Equation ◽  
Word Of Mouth ◽  
Social Economic ◽  
Equation Modeling ◽  
Moderating Effects ◽  
Main Factors ◽  
Corporate Social

Consumers who buy their products through e-commerce are beginning to pay attention to a company's corporate social responsibility (CSR) status. Due to technological advancements, information became more transparent. Based on this phenomenon, research is required to determine the extent to which word-of-mouth consumers collaborate to increase value in order to achieve sustainability. In this study, the achievements are examined from the perspective of co-creation on the word of mouth aspect, with dimensions of three main factors, namely, social, economic, and environmental. The hypothesis of this study was tested using structural equation modeling (SEM), which includes an assessment of the segments of the related pathways. A total of 297 Indonesians who have completed at least 20 transactions in e-commerce, expressed concern about three important aspects of sustainability: people, profit, and the planet. This finding demonstrates the importance of co-creation of word-of-mouth value in achieving sustainability. Further research into the moderating effects of more detailed aspects of the supporting ecosystem could be conducted in the future.

Using Data Labels to Discover Moderating Effects in PLS-Based Structural Equation Modeling

2014 ◽  
Vol 10 (4) ◽  
pp. 1-16 ◽  
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
Moderating Effects ◽  
Model Driven ◽  
Correlation Analyses ◽  
Using Data

PLS-based structural equation modeling is extensively used in e-collaboration research, as well as in many other fields of research. Two main types of exploratory analyses are frequently employed in the context of PLS-based structural equation modeling: covariance (or correlation) analyses, where the covariances (or correlations) among all variables are inspected; and model-driven exploratory analyses, where one or more variations of theory-supported models are built and adjusted associations among variables are inspected. These analyses, while useful, provide limited insights about the possible presence of moderating effects. We discuss a general approach through which researchers can employ data labels, implemented as symbols that are displayed together with legends on graphs, to uncover moderating relationships among variables. The discussion is illustrated with the software WarpPLS version 4.0. While the approach is illustrated in the context of e-collaboration research, it arguably applies to any field where PLS-based structural equation modeling can be used.

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