LEADER 03623nam 22006255 450 001 9911021973303321 005 20250828130149.0 010 $a3-032-01055-1 024 7 $a10.1007/978-3-032-01055-1 035 $a(MiAaPQ)EBC32274029 035 $a(Au-PeEL)EBL32274029 035 $a(CKB)40430610500041 035 $a(DE-He213)978-3-032-01055-1 035 $a(EXLCZ)9940430610500041 100 $a20250828d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPartial Least Squares Structural Equation Modeling and Complementary Methods in Business Research /$fby XinYing Chew, Abbas Gatea Atiyah, Alhamzah Alnoor, Sammar Abbas, Yousif Raad Muhsen, Gül Erkol Bayram 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (272 pages) 225 1 $aInformation Systems Engineering and Management,$x3004-9598 ;$v67 311 08$a3-032-01054-3 327 $aPartial Least Squares Structural Equation Modeling -- PLSbSEM Path Model Estimation -- Overview of ANN Analysis -- Business Research Applications in SEM ANN Analysis -- Opportunity for ANN Analysis -- Artificial Neural Network and Theories -- Hybrid SEM and ANN Approach -- Fuzzy set Qualitative Comparative Analysis FsQCA -- Outline of ANFIS Analysis -- Multi Criteria Decision Making -- Machine Learning in Business Research -- Application of Multi Criteria Decision Making Methods. 330 $aThis book offers a practical and accessible guide to Partial Least Squares Structural Equation Modeling (PLS-SEM) in business research, while addressing its limitations by integrating complementary methods such as artificial neural networks (ANN), fuzzy-set qualitative comparative analysis (fsQCA), and multi-criteria decision-making (MCDM). It supports early-career researchers, postgraduate students, and practitioners in navigating complex models, predictive analytics, and latent construct measurement. By focusing on emerging business issues like digital transformation, metaverse, and sustainability, this book delivers clear, applied insights. Readers gain not only foundational knowledge of PLS-SEM but also strategies for enhancing research rigor, prediction, and decision-making using hybrid approaches. This is a timely and essential resource for scholars aiming to advance their methodological toolkit for impactful and actionable business research. 410 0$aInformation Systems Engineering and Management,$x3004-9598 ;$v67 606 $aComputational intelligence 606 $aBusiness mathematics 606 $aEngineering$xData processing 606 $aComputational Intelligence 606 $aBusiness Mathematics 606 $aData Engineering 615 0$aComputational intelligence. 615 0$aBusiness mathematics. 615 0$aEngineering$xData processing. 615 14$aComputational Intelligence. 615 24$aBusiness Mathematics. 615 24$aData Engineering. 676 $a006.3 700 $aChew$b XinYing$01845345 701 $aGatea Atiyah$b Abbas$01845346 701 $aAlnoor$b Alhamzah$01586455 701 $aAbbas$b Sammar$01845347 701 $aMuhsen$b Yousif Raad$01743668 701 $aBayram$b Gül Erkol$01743667 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911021973303321 996 $aPartial Least Squares Structural Equation Modeling and Complementary Methods in Business Research$94429204 997 $aUNINA