Assessing the predictive performance of structural equation model estimators

Evermann, Jöerg; Tate, Mary

doi:10.1016/j.jbusres.2016.03.050

Cited by 187 publications

(119 citation statements)

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“…The latter aspect allows PLS-SEM to become a useful method for predictive modeling. Publications such as Evermann and Tate (2016) and Becker et al (2013) follow Rigdon's (2012Rigdon's ( , 2014 call to further develop PLS-SEM into this direction and thereby to emancipate itself from CB-SEM (Sarstedt et al, 2014a, b). Furthermore, PLS-SEM is better suited to explain complex models or relationships (Fornell, 1982;Wold, 1985).…”

Section: Introductionmentioning

confidence: 99%

A critical look at the use of SEM in international business research

Richter

Sinkovics

Ringle

et al. 2016

International Marketing Review

433

278

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. Christopher SchlägelFaculty of Economics and Management, Otto von Guericke University Magdeburg, Magdeburg, Gemany Abstract Purpose -Structural equation modeling (SEM) has been widely used to examine complex research models in international business and marketing research. While the covariance-based SEM (CB-SEM) approach is dominant, the authors argue that the field's dynamic nature and the sometimes early stage of theory development more often require a partial least squares SEM (PLS-SEM) approach. The purpose of this paper is to critically review the application of SEM techniques in the field. Design/methodology/approach -The authors searched six journals with an international business (and marketing) focus (Management International Review, Journal of International Business Studies, Journal of International Management, International Marketing Review, Journal of World Business, International Business Review) from 1990 to 2013. The authors reviewed all articles that apply SEM, analyzed their research objectives and methodology choices, and assessed whether the PLS-SEM papers followed the best practices outlined in the past. Findings -Of the articles, 379 utilized CB-SEM and 45 PLS-SEM. The reasons for using PLS-SEM referred largely to sampling and data measurement issues and did not sufficiently build on the procedure's benefits that stem from its design for predictive and exploratory purposes. Thus, the procedure's key benefits, which might be fruitful for the theorizing process, are not being fully exploited. Furthermore, authors need to better follow best practices to truly advance theory building. Research limitations/implications -The authors examined a subset of journals in the field and did not include general management journals that publish international business and The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/0265-1335.htm marketing-related studies. Fur-thermore, the authors found only limited use of PLS-SEM in the journals the authors considered relevant to the study. Originality/value -The study contributes to the literature by providing researchers seeking to adopt SEM as an analytical method with pra...

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Section: Introductionmentioning

confidence: 99%

A critical look at the use of SEM in international business research

Richter

Sinkovics

Ringle

et al. 2016

International Marketing Review

433

278

View full text Add to dashboard Cite

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“…Otherwise, unlike covariance-based modeling, it works with formative, reflective and single-item constructs (Hair et al, 2014;Peng & Lai, 2012;Richter, Sinkovics, Ringle, & Schlägel, 2016). The sample size required for performing PLS-SEM must follow the 10-times rule, that is, 10 times the largest number of structural paths directed to a latent variable in the structural model (Evermann & Tate, 2016;Hair et al, 2014;Richter et al, 2016). Given such criteria, the minimum sample required for our model would be 70 valid responses, which was surpassed by our data collection (n=149).…”

Section: Methodsmentioning

confidence: 99%

“…Following Streukens and Leroi-Werelds (2016) recommendations, we adopted 10,000 bootstrap samples (J=10,000) with bias-corrected and accelerated (BCa) confidence intervals. We also assessed the predictive relevance of the model though a blindfolding procedure, adopting an omission distance of seven (D=7), in accordance with previously recommended parameters (Chin, 2010;Evermann & Tate, 2016).…”

Section: Methodsmentioning

confidence: 99%

“…For our model, we adopted a consistent number of bootstrap samples (J=10,000) for improving the level of accuracy of the estimations (Streukens & Leroi-Werelds, 2016). We assessed the explained variance (R²) and StoneGeisser test (Q²>0) through blindfolding procedure (omission distance D=7) for evaluating the predictive power of the structural model (Figure 2), as well as path coefficient (β), effect size (f²), confidence intervals, t-value and p-value of each path (Table 4) in order to support or refute our hypotheses and assess their explanatory power (Chin, 2010;Evermann & Tate, 2016;Peng & Lai, 2012;Richter et al, 2016 Regarding variance explained (R²) we adopted the cut-off value of 0.10, with values between 0.19 and 0.33 considered weak explanation, values between 0.33 and 0.67 considered moderate explanation, and values higher than 0.67 considered strong explanation (Peng & Lai, 2012;Streukens & LeroiWerelds, 2016). The model presented significant explanation and predictive power for the degree of internationalization (R²=0.41; p<0.001 and Q²=0.35) and risk perception (R²=0.26; p<0.01 and Q²=0.15).…”

Section: Structural Modelmentioning

confidence: 99%

See 1 more Smart Citation

Exploring Risk Perception and Degree of Internationalization of Brazilian Small-and-Medium Enterprises

Bonfim

Silva

Prado

et al. 2018

BAR, Braz. Adm. Rev.

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This research investigates managerial risk perception regarding internationalization of small and medium-sized enterprises in the Brazilian context. We examine how managers' perception of risk influences firms' degrees of internationalization. Likewise, we assessed how risk perception is influenced by managers' cognitive traits, such as tolerance for ambiguity and cognitive style. We provided empirical evidence for the relationships we proposed through a partial least squares structural equation model with data gathered from a survey of 149 SMEs from the State of Paraná, Brazil. Our results suggest that managers' tolerance for ambiguity is only significant for explaining risk perception for the managers with a preference for a deliberative style. Still, the research suggests that the Brazilian SMEs in our sample presented a higher degree of internationalization even when their managers perceived higher levels of risk.

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“…Structural equation model (SEM) is an important branch of the area of applied statistics. It is widely used in different research areas, such as sociology, management science, behavioral science and econometrics [46][47][48][49]. This method has the following advantages: handling multiple dependent variables at the same time; robustness to the observational error between the dependent and independent variables; and allowing the existence of latent variable that consist of multiple observation indexes when the latent variables are hard to measure.…”

Section: Evaluation Of Sustainable Urbanizationmentioning

confidence: 99%

A Novel Approach for Assessing the Performance of Sustainable Urbanization Based on Structural Equation Modeling: A China Case Study

et al. 2016

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Abstract:The rapid urbanization process has brought problems to China, such as traffic congestion, air pollution, water pollution and resources scarcity. Sustainable urbanization is commonly appreciated as an effective way to promote the sustainable development. The proper understanding of the sustainable urbanization performance is critical to provide governments with support in making urban development strategies and policies for guiding the sustainable development. This paper utilizes the method of Structural equation modeling (SEM) to establish an assessment model for measuring sustainable urbanization performance. Four unobserved endogenous variables, economic variable, social variable, environment variable and resource variable, and 21 observed endogenous variables comprise the SEM model. A case study of the 31 provinces in China demonstrates the validity of the SEM model and the analysis results indicated that the assessment model could help make more effective policies and strategies for improving urban sustainability by recognizing the statue of sustainable urbanization.

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Assessing the predictive performance of structural equation model estimators

Cited by 187 publications

References 28 publications

A critical look at the use of SEM in international business research

A critical look at the use of SEM in international business research

Exploring Risk Perception and Degree of Internationalization of Brazilian Small-and-Medium Enterprises

A Novel Approach for Assessing the Performance of Sustainable Urbanization Based on Structural Equation Modeling: A China Case Study

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