Structural Equation Modeling in Information Systems Research Using Partial Least Squares
By Nils Urbach, Frederik Ahlemann. 2010
1,954 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/e50c0dd248bca04f1768903acb92aaa2f3b6e058
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- Jun-Hwa (Jacky) Cheah
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Citations in the corpus
- E-learning success determinants: Brazilian empirical study (2017, unknown): “As all the AVEs are above 0.500, requirements are met (Barclay, Higgins, & Thompson, 1995; Fornell & Larcker, 1981; Hair, Hult, Ringle, & Sarstedt, 2014; Urbach & Ahlemann, 2010).”
- Why do small and medium enterprises use social media marketing and what is the impact: Empirical insights from India (2020, background): “Since the results show that the lowest values of CR and AVE of each construct are greater than their lowest acceptable values which are 0.6 for CR (Urbach and Ahlemann, 2010) and 0.5 for AVE (Gefen & Straub, 2005; Hair et al., 2010), it is confirmed that the identification of constructs is valid.”
- Self-Efficacy, Work Engagement, and Job Satisfaction Among Teaching Assistants in Hong Kong’s Inclusive Education (2020, methodology): “PLSSEM can be applied to the analysis of non-normally distributed data, does not demand a large sample size, and serves the purposes of exploratory study rather than theory testing (Urbach & Ahlemann, 2010).”
- Sampling weight adjustments in partial least squares structural equation modeling: guidelines and illustrations (2020, background): “…main area of application is in business research, particularly information systems (Cheah et al., 2019; Hair et al., 2017a; Ringle et al., 2012; Roldán & Sánchez-Franco, 2012; Shiau & Chau, 2016; Urbach & Ahlemann, 2010) and marketing (Hair et al., 2012; Hair et al., 2017c; Henseler et al., 2009).”
- Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust (2016, unknown): “This approach has been used as the investigated phenomenon is new and the research aims at generation of theory rather than con fi rmation a theory (Urbach & Ahlemann, 2010). furthermore, a PLS approach does not require a normal distribution, as opposed to covariance-based approaches, which requires…”
- Using Partial Least Squares Structural Equation Modeling in Tourism Research (2016, background): “…in business research, including marketing (e.g., Hair, Ringle, and Sarstedt 2011), strategic management (e.g., Hair et al. 2012a; Hulland 1999), and MIS (e.g., Ringle, Sarstedt, and Straub 2012; Urbrach and Ahlemann 2010), corresponding assessments of PLS-SEM in tourism are still limited.”
- Customer experiences in the age of artificial intelligence (2020, unknown): “In addition, composite reliability and Cronbach Alpha values were above the threshold value of 0.7 (Urbach & Ahlemann, 2010).”
- A model of acceptance of augmented-reality interactive technology: the moderating role of cognitive innovativeness (2014, background): “6, PLS analysis of the integrated ARIT acceptance model explains 69 % of the variance in sustainable relationship behavior toward using ARIT, which exceeds the substantial value of 67 % for R 2 proposed by previous studies [12,76].”
- The impact of customer experience and perceived value on sustainable social relationship in blogs: An empirical study (2015, methodology): “PLS is superior to covariance-based SEM for the following four reasons (Chin, 1998; Chin and Newsted, 1999; Urbach and Ahlemann, 2010).”
- ASSESSING REFLECTIVE MODELS IN MARKETING RESEARCH: A COMPARISON BETWEEN PLS AND PLSc ESTIMATES (2018, background): “It is however mandatory that R2 values should be high enough for the model to achieve a minimum level of explanatory power (Urbach & Ahlemann 2010).”
- Factors Affecting Students’ Attitude toward Mathematics: A Structural Equation Modeling Approach (2017, methodology): “It tests whether the items do not unintentionally measure something else (Urbach & Ahlemann, 2010) which can be determined with Fornell-Lacker’s method (Fornell & Lacker, 1981).”