Structural Equation Modeling and Regression: Guidelines for Research Practice

Gefen, David; Straub, Detmar W.; Boudreau, Marie‐Claude

doi:10.17705/1cais.00407

Cited by 3,687 publications

(3,482 citation statements)

References 59 publications

Supporting

Mentioning

2,974

Contrasting

Unclassified

Order By: Relevance

“…In addition, we can use the second-generation statistical technique, namely structural equation modeling (SEM), when the sample size is above 200 (Hair et al 2006). SEM can examine multiple causal relationships simultaneously and have more rigorous analysis results (Gefen et al 2000). Second, this study only considers two types of channels: Internet and physical channels, and only analyze how channel characteristics influence the channel attitudes of multi-channel research shoppers.…”

Section: Resultsmentioning

confidence: 99%

Understanding multi-channel research shoppers: an analysis of Internet and physical channels

Wang

Lin

Tai

et al. 2015

Inf Syst E-Bus Manage

View full text Add to dashboard Cite

The purpose of this study is to analyze how channel characteristics influence the channel attitudes of multi-channel research shoppers. In addition, the study also considers consumers' complex shopping behaviors that involve using one channel for search and another for purchase simultaneously. Survey data were collected from 191 consumers with recent (i.e., in the last 3 months) multi-channel experiences. Qualified respondents had either searched in physical retail stores and purchased on the Internet or searched on the Internet and subsequently purchased in physical retail stores. The research hypotheses were examined using multiple regression analysis. The results show that customer perceptions of channel characteristics drive channel choice attitudes. Importantly, we find the significance of channel characteristics varies between the Internet and the physical channel. The research findings deepen our understanding of shopping behaviors in the multichannel context. Practitioners may use the findings to manage the characteristics of the complementary channels while also designing marketing programs to create positive consumer attitudes toward search and purchase.

show abstract

Section: Resultsmentioning

confidence: 99%

Understanding multi-channel research shoppers: an analysis of Internet and physical channels

Wang

Lin

Tai

et al. 2015

Inf Syst E-Bus Manage

View full text Add to dashboard Cite

show abstract

“…The study is exploratory in nature, the sample size (n ¼ 175) is less than the minimum recommended number of cases for covariance-based structural equation modeling methodologies such as LISREL, EQS, or AMOS, and it cannot be assumed that the data follows a normal distribution. Given these conditions, PLS is the most appropriate analytical tool [ChNe98;GeSB00]. Accordingly, PLS Graph version 3.0 was used to analyze the data and test the model.…”

Section: Resultsmentioning

confidence: 99%

“…A common method used to determine confidence intervals for the path coefficients is bootstrapping. This process involves taking repeated samples (with replacement) from the original data set, and using these samples to determine a t-value for each path coefficient [Chin98b;GeSB00]. Applying the associated bootstrap technique to this study, with the number of iterations set at 500, resulted in the significance levels shown in Figure 2.…”

Section: Resultsmentioning

confidence: 99%

Vendor capabilities and outsourcing success: A resource-based view

Goles

2003

Wirtschaftsinf

View full text Add to dashboard Cite

Grover et al. [GrCT94] were among the first to specifically identify the resourcebased view of the firm as a theoretical basis for linking outsourcing to a firm's gaps in IS resources and capabilities. Their results provide support for the hypothesis thatOutsourcing is a generally accepted method for fulfilling an organization's information systems (IS) needs. A prominent motive for outsourcing is a desire to increase the organization's access to high-quality information technology and expertise. There is, however, little research that examines the connection between vendor capabilities and customer satisfaction. This paper addresses that gap by using the resource-based view of the firm to investigate linkages between vendor capabilities, IS quality, and customer satisfaction. A survey was completed by managers of outsourcing customer firms. The results were analyzed using Partial Least Squares (PLS). The results indicate that customers evaluate a vendor primarily in terms of technological capabilities, followed by relationship management capabilities. The vendor's understanding of the customer's business was not considered to be significant. There is a significant connection between the vendor's capabilities and the quality of the IS function, which in turn was related to customer satisfaction.

show abstract

“…Bagozzi and Yi (1988) proposed confirmatory factor analysis evaluation criteria and both Anderson and Gerbing (1988) and Gefen et al (2000) recommended to assess data with model fit index for measurement model. The measurement model showed adequate fit: v 2 = 1087.775, df = 467, v 2 /df = 2.329, GFI = 0.915, AGFI = 0.898, RMSEA = 0.043, RMSR = 0.040, NFI = 0.932, CFI = 0.960 (see Table 1).…”

Section: Measurement Modelmentioning

confidence: 99%

Investigating information sharing behavior: the mediating roles of the desire to share information in virtual communities

Liou

Chih

Hsu

et al. 2015

Inf Syst E-Bus Manage

View full text Add to dashboard Cite

Social networking sites are built and designed to provide online services and a platform for people to social interacts and exchange information. This study used the social capital theory as a foundation to explore the social interaction factors and individual factors such as shared value, community identification, and information privacy concerns, and examine the mediating role of the desire to give information between trust on websites/members and information sharing behaviour in the proposed model. This research sample consists of seven hundred and twenty-seven members who have used the Facebook fan page for at least 6 months. This study adopted structural equation modeling to test the research hypotheses. The results of this study show that shared value, community identification, and information privacy concern directly influence trust on websites and members. Trust on websites and members directly influenced the desire to get/give information. Desire to give information directly influences information sharing behaviour. The desire to give information plays important mediating roles between trust on websites/members and information sharing behaviour. Finally, we provide conclusions and managerial implications of the findings.

show abstract

Structural Equation Modeling and Regression: Guidelines for Research Practice

Cited by 3,687 publications

References 59 publications

Understanding multi-channel research shoppers: an analysis of Internet and physical channels

Understanding multi-channel research shoppers: an analysis of Internet and physical channels

Vendor capabilities and outsourcing success: A resource-based view

Investigating information sharing behavior: the mediating roles of the desire to share information in virtual communities

Contact Info

Product

Resources

About