Methodological research on partial least squares structural equation modeling (PLS-SEM)
暂无分享,去创建一个
Wen-Lung Shiau | Gohar Feroz Khan | Marko Sarstedt | Christian M. Ringle | Joseph F. Hair | Joseph F. Hair | Martin P. Fritze | G. Khan | M. Sarstedt | C. Ringle | Wen-Lung Shiau
[1] H. Wold. A fix-point theorem with econometric background , 1966 .
[2] H. Wold. A fix-point theorem with econometric background , 1966 .
[3] Henry G. Small,et al. Co-citation in the scientific literature: A new measure of the relationship between two documents , 1973, J. Am. Soc. Inf. Sci..
[4] P. V. Marsden,et al. NETWORK DATA AND MEASUREMENT , 1990 .
[5] Steven B. Andrews,et al. Structural Holes: The Social Structure of Competition , 1995, The SAGE Encyclopedia of Research Design.
[6] Stanley Wasserman,et al. Social Network Analysis: Methods and Applications , 1994 .
[7] Andrew Parker,et al. Knowing What We Know: Supporting Knowledge Creation and Sharing in Social Networks , 2001 .
[8] R. Hanneman. Introduction to Social Network Methods , 2001 .
[9] A. Barabasi,et al. Evolution of the social network of scientific collaborations , 2001, cond-mat/0104162.
[10] David J. Ketchen,et al. AN ASSESSMENT OF THE USE OF STRUCTURAL EQUATION MODELING IN STRATEGIC MANAGEMENT RESEARCH , 2004 .
[11] Hong Xu,et al. Journal co-citation analysis of semiconductor literature , 2003, Scientometrics.
[12] Jon M. Kleinberg,et al. Bursty and Hierarchical Structure in Streams , 2002, Data Mining and Knowledge Discovery.
[13] K. Börner,et al. Mapping topics and topic bursts in PNAS , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[14] Gobinda G. Chowdhury,et al. Journal as Markers of Intellectual Space: Journal Co-Citation Analysis of Information Retrieval Area, 1987–1997 , 2004, Scientometrics.
[15] Johan Bollen,et al. Co-authorship networks in the digital library research community , 2005, Inf. Process. Manag..
[16] Michel Tenenhaus,et al. PLS path modeling , 2005, Comput. Stat. Data Anal..
[17] Vladimir Batagelj,et al. Exploratory Social Network Analysis with Pajek , 2005 .
[18] Jennifer Jie Xu,et al. The Social Identity of IS: Analyzing the Collaboration Network of the ICIS Conferences (1980-2005) , 2006, ICIS.
[19] Sheng-Hsun Hsu,et al. Robustness testing of PLS, LISREL, EQS and ANN-based SEM for measuring customer satisfaction , 2006 .
[20] Chaomei Chen,et al. Web site design with the patron in mind: A step-by-step guide for libraries , 2006 .
[21] Chaomei Chen,et al. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature , 2006, J. Assoc. Inf. Sci. Technol..
[22] Joachim Scholderer,et al. Was unterscheidet harte und weiche Strukturgleichungsmodelle nun wirklich , 2006 .
[23] Richard T. Vidgen,et al. What sort of community is the European Conference on Information Systems? A social network analysis 1993–2005 , 2007, Eur. J. Inf. Syst..
[24] M. Tenenhaus. Component-based Structural Equation Modelling , 2008 .
[25] Marko Sarstedt,et al. Heterogenität in varianzbasierter Strukturgleichungsmodellierung , 2008 .
[26] Siegfried P. Gudergan,et al. Confirmatory Tetrad Analysis in PLS Path Modeling , 2008 .
[27] W. Reinartz,et al. An Empirical Comparison of the Efficacy of Covariance-Based and Variance-Based SEM , 2009 .
[28] Yue Chen,et al. Towards an explanatory and computational theory of scientific discovery , 2009, J. Informetrics.
[29] Gaby Odekerken-Schröder,et al. Using PLS path modeling for assessing hierarchial construct models: guidelines and impirical illustration , 2009 .
[30] Ludo Waltman,et al. Software survey: VOSviewer, a computer program for bibliometric mapping , 2009, Scientometrics.
[31] Wynne W. Chin,et al. A Comparison of Approaches for the Analysis of Interaction Effects Between Latent Variables Using Partial Least Squares Path Modeling , 2010 .
[32] M. Sarstedt,et al. Treating unobserved heterogeneity in PLS path modeling: a comparison of FIMIX-PLS with different data analysis strategies , 2010 .
[33] Jörg Henseler,et al. On the convergence of the partial least squares path modeling algorithm , 2010, Comput. Stat..
[34] Anthony Randal McIntosh,et al. Partial Least Squares (PLS) methods for neuroimaging: A tutorial and review , 2011, NeuroImage.
[35] G. Mateos-Aparicio. Partial Least Squares (PLS) Methods: Origins, Evolution, and Application to Social Sciences , 2011 .
[36] Ingoo Han,et al. The Different Effects of Online Consumer Reviews on Consumers' Purchase Intentions Depending on Trust in Online Shopping Mall: An Advertising Perspective , 2011, Internet Res..
[37] Marko Sarstedt,et al. PLS-SEM: Indeed a Silver Bullet , 2011 .
[38] Katy Börner,et al. Mixed-indicators model for identifying emerging research areas , 2011, Scientometrics.
[39] Fujun Lai,et al. Using Partial Least Squares in Operations Management Research: A Practical Guideline and Summary of Past Research , 2012 .
[40] Martin Wetzels,et al. Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models , 2012 .
[41] Wynne W. Chin,et al. When Imprecise Statistical Statements Become Problematic: A Response to Goodhue, Lewis, and Thompson , 2012, MIS Q..
[42] William Lewis,et al. Does PLS Have Advantages for Small Sample Size or Non-Normal Data? , 2012, MIS Q..
[43] Edward E. Rigdon,et al. Rethinking Partial Least Squares Path Modeling: In Praise of Simple Methods , 2012 .
[44] Gohar Feroz Khan. Social media-based systems: an emerging area of information systems research and practice , 2012, Scientometrics.
[45] Marko Sarstedt,et al. The Use of Partial Least Squares Structural Equation Modeling in Strategic Management Research: A Review of Past Practices and Recommendations for Future Applications , 2012 .
[46] Jörg Henseler,et al. Analysing quadratic effects of formative constructs by means of variance-based structural equation modelling , 2012, Eur. J. Inf. Syst..
[47] Joseph F. Hair,et al. Partial Least Squares : The Better Approach to Structural Equation Modeling ? , 2012 .
[48] D. Straub,et al. Editor's comments: a critical look at the use of PLS-SEM in MIS quarterly , 2012 .
[49] Marko Sarstedt,et al. An assessment of the use of partial least squares structural equation modeling in marketing research , 2012 .
[50] Marko Sarstedt,et al. Editorial - Partial Least Squares Structural Equation Modeling: Rigorous Applications, Better Results and Higher Acceptance , 2013 .
[51] Gohar Feroz Khan,et al. The e-government research domain: A triple helix network analysis of collaboration at the regional, country, and institutional levels , 2013, Gov. Inf. Q..
[52] Mikko Rönkkö,et al. A Critical Examination of Common Beliefs About Partial Least Squares Path Modeling , 2013 .
[53] Marko Sarstedt,et al. Goodness-of-fit indices for partial least squares path modeling , 2013, Comput. Stat..
[54] D. Ketchen. A Primer on Partial Least Squares Structural Equation Modeling , 2013 .
[55] Gohar Feroz Khan,et al. An analysis of the information technology outsourcing domain: A social network and Triple helix approach , 2013, J. Assoc. Inf. Sci. Technol..
[56] Judith Molka-Danielsen,et al. Sympathy or strategy: social capital drivers for collaborative contributions to the IS community , 2013, Eur. J. Inf. Syst..
[57] Edward E. Rigdon,et al. Rethinking Partial Least Squares Path Modeling: Breaking Chains and Forging Ahead , 2014 .
[58] Jeffrey R. Edwards,et al. Reflections on Partial Least Squares Path Modeling , 2014 .
[59] Rudolf R. Sinkovics,et al. A Critical Look at the Use of SEM in International Business Research , 2014 .
[60] Marko Sarstedt,et al. Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers , 2014 .
[61] T. Dijkstra. PLS' Janus Face – Response to Professor Rigdon's ‘Rethinking Partial Least Squares Modeling: In Praise of Simple Methods’ , 2014 .
[62] Marko Sarstedt,et al. PLS-SEM: Looking Back and Moving Forward , 2014 .
[63] Joseph F. Hair,et al. On the Emancipation of PLS-SEM: A Commentary on Rigdon (2012) , 2014 .
[64] Detmar W. Straub,et al. Common Beliefs and Reality About PLS , 2014 .
[65] Peter M Bentler,et al. On Components, Latent Variables, PLS and Simple Methods: Reactions to Rigdon's Rethinking of PLS. , 2014, Long range planning.
[66] Marko Sarstedt,et al. Genetic algorithm segmentation in partial least squares structural equation modeling , 2013, OR Spectrum.
[67] Dirceu da Silva,et al. Modelagem de Equações Estruturais com Utilização do Smartpls , 2014 .
[68] Jörg Henseler,et al. Consistent Partial Least Squares Path Modeling , 2015, MIS Q..
[69] Jinyoung Min,et al. The distinct roles of dedication-based and constraint-based mechanisms in social networking sites , 2015, Internet Res..
[70] Daniel S. J. Costa,et al. Testing complex models with small sample sizes: A historical overview and empirical demonstration of what Partial Least Squares (PLS) can offer differential psychology , 2015 .
[71] Lutz Kaufmann,et al. A structured review of partial least squares in supply chain management research , 2015 .
[72] M. Sarstedt,et al. A new criterion for assessing discriminant validity in variance-based structural equation modeling , 2015 .
[73] Sung-Byung Yang,et al. The role of online product reviews on information adoption of new product development professionals , 2015, Internet Res..
[74] Marko Sarstedt,et al. Testing measurement invariance of composites using partial least squares , 2016 .
[75] Gohar Feroz Khan,et al. Knowledge Networks of the Information Technology Management Domain: A Social Network Analysis Approach , 2016, Commun. Assoc. Inf. Syst..
[76] Marko Sarstedt,et al. Gain more insight from your PLS-SEM results: The importance-performance map analysis , 2016, Ind. Manag. Data Syst..
[77] Edward E. Rigdon,et al. Choosing PLS path modeling as analytical method in European management research: A realist perspective , 2016 .
[78] Wei-Lun Chang,et al. Nurturing user creative performance in social media networks: An integration of habit of use with social capital and information exchange theories , 2016, Internet Res..
[79] Joseph F. Hair,et al. Estimation issues with PLS and CBSEM: Where the bias lies! ☆ , 2016 .
[80] Geoffrey S. Hubona,et al. Using PLS path modeling in new technology research: updated guidelines , 2016, Ind. Manag. Data Syst..
[81] J. Edwards,et al. Partial least squares path modeling: Time for some serious second thoughts , 2016 .
[82] Alexander Buhmann,et al. Advancing PR measurement and evaluation: Demonstrating the properties and assessment of variance-based structural equation models using an example study on corporate reputation , 2016 .
[83] Wen-Lung Shiau,et al. Understanding behavioral intention to use a cloud computing classroom: A multiple model comparison approach , 2016, Inf. Manag..
[84] Galit Shmueli,et al. The elephant in the room: Predictive performance of PLS models , 2016 .
[85] Mary Tate,et al. Assessing the predictive performance of structural equation model estimators , 2016 .
[86] Xiongfei Cao,et al. Exploring the influence of social media on employee work performance , 2016, Internet Res..
[87] Christian Nitzl,et al. The use of partial least squares structural equation modelling (PLS-SEM) in management accounting research: Directions for future theory development , 2016 .
[88] Christian Nitzl,et al. Mediation Analysis in Partial Least Squares Path Modeling: Helping Researchers Discuss More Sophisticated Models , 2016, Ind. Manag. Data Syst..
[89] Marko Sarstedt,et al. Segmentation of PLS path models by iterative reweighted regressions , 2015 .
[90] Edward E. Rigdon,et al. On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations , 2017 .
[91] Marko Sarstedt,et al. Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods , 2017, Journal of the Academy of Marketing Science.
[92] C. Jabbour,et al. Ethical awareness, ethical judgment, andwhistleblowing: A moderated mediation analysis , 2017 .
[93] J. Henseler. Bridging Design and Behavioral Research With Variance-Based Structural Equation Modeling , 2017 .
[94] Joseph F. Hair,et al. Partial Least Squares Structural Equation Modeling , 2021, Handbook of Market Research.
[95] Faizan Ali,et al. An Assessment of the Use of Partial Least Squares Structural Equation Modeling (PLS-SEM) in Hospitality Research , 2017 .
[96] Ned Kock. Going Beyond Composites: Conducting a Factor-Based PLS-SEM Analysis , 2017 .
[97] Florian Schuberth,et al. Ordinal Consistent Partial Least Squares , 2017 .
[98] Thurasamy Ramayah,et al. Determinants of cyberloafing: a comparative study of a public and private sector organization , 2017, Internet Res..
[99] Alain Yee-Loong Chong,et al. An updated and expanded assessment of PLS-SEM in information systems research , 2017, Ind. Manag. Data Syst..
[100] N. Avkiran. An in-depth discussion and illustration of partial least squares structural equation modeling in health care , 2018, Health care management science.
[101] Miguel I. Aguirre-Urreta,et al. Statistical Inference with PLSc Using Bootstrap Confidence Intervals , 2018, MIS Q..
[102] J. Henseler. Partial least squares path modeling: Quo vadis? , 2018, Quality & Quantity.
[103] Marko Sarstedt,et al. Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling , 2018, Journal of International Marketing.
[104] Martin P. Fritze,et al. From Goods to Services Consumption: A Social Network Analysis on Sharing Economy and Servitization Research , 2018 .
[105] Eldon Y. Li,et al. Marketing mix, customer value, and customer loyalty in social commerce: A stimulus-organism-response perspective , 2017, Internet Res..
[106] Jiabao Lin,et al. Understanding Chinese consumer engagement in social commerce: The roles of social support and swift guanxi , 2017, Internet Res..
[107] Ahmet Usakli,et al. Using partial least squares structural equation modeling in hospitality and tourism , 2018, International Journal of Contemporary Hospitality Management.
[108] Necmi K. Avkiran,et al. Rise of the Partial Least Squares Structural Equation Modeling: An Application in Banking , 2018 .
[109] Carlo Lauro,et al. Non-symmetrical composite-based path modeling , 2018, Adv. Data Anal. Classif..
[110] Marko Sarstedt,et al. Heuristics versus statistics in discriminant validity testing: a comparison of four procedures , 2019, Internet Res..
[111] Pratyush Nidhi Sharma,et al. PLS-Based Model Selection: The Role of Alternative Explanations in Information Systems Research , 2019, J. Assoc. Inf. Syst..
[112] S. Gudergan,et al. Partial least squares structural equation modeling in HRM research , 2020 .