Artificial Neural Networks and Structural Equation Modeling (eBook)
IX, 341 Seiten
Springer Nature Singapore (Verlag)
978-981-19-6509-8 (ISBN)
This book goes into a detailed investigation of adapting artificial neural network (ANN) and structural equation modeling (SEM) techniques in marketing and consumer research. The aim of using a dual-stage SEM and ANN approach is to obtain linear and non-compensated relationships because the ANN method captures non-compensated relationships based on the black box technology of artificial intelligence. Hence, the ANN approach validates the results of the SEM method. In addition, such the novel emerging approach increases the validity of the prediction by determining the importance of the variables. Consequently, the number of studies using SEM-ANN has increased, but the different types of study cases that show customization of different processes in ANNs method combination with SEM are still unknown, and this aspect will be affecting to the generation results. Thus, there is a need for further investigation in marketing and consumer research. This book bridges the significant gap in this research area.
The adoption of SEM and ANN techniques in social commerce and consumer research is massive all over the world. Such an expansion has generated more need to learn how to capture linear and non-compensatory relationships in such area. This book would be a valuable reading companion mainly for business and management students in higher academic organizations, professionals, policy-makers, and planners in the field of marketing. This book would also be appreciated by researchers who are keenly interested in social commerce and consumer research.
Alhamzah Alnoor is a professional administrator with ten years of experience in organizational studies, social commerce, internship programs, multi-criteria decision analysis, leadership and innovation, strategic planning, and technology acceptance models. Successfully achieved several projects during my career with impactful business values. Creative, flexible, motivated with active optimism and belief in diversity and inclusion. He is a reviewer for many journals. He published many papers in different and high-impact journals. He is a senior lecturer at the Southern Technical University, Management Technical College. He received his M.B.A. from the University of Basrah, Iraq. He received his Ph.D. from the School of Management, Universiti Sains Malaysia, Malaysia.
Khaw Khai Wah is a senior lecturer in the School of Management, Universiti Sains Malaysia. He holds a Ph.D. in statistical quality control from Universiti Sains Malaysia. He is a coordinator of the Business Analytics Program in the School of Management, USM. His areas of research are in advanced analytics and statistical quality/process control. He has featured in prominent international publications. His efforts and excellence have been acknowledged and awarded at several dignified platforms. He is actively involved in conducting training in statistics and visualization. Prior to his academic career, he worked in a renowned US multinational company as a data analytics team leader.
Azizul Hassan is a member of the Tourism Consultants Network of the UK Tourism Society. Hassan's areas of research interest are technology-supported marketing for tourism and hospitality, immersive technology application in the tourism and hospitality industry, and technology-influenced marketing suggestions for sustainable tourism and hospitality industry in developing countries. Hassan authored over 100 articles and book chapters in leading tourism outlets. He is also part of the editorial team of 20 book projects from Routledge, Springer, CAB International and Emerald Group Publishing Limited. Hassan is a regular reviewer of Tourism Management, Journal of Hospitality and Tourism Management, Tourism Analysis, the International Journal of Human Resource Management, Journal of Ecotourism, Journal of Business Research, eReview of Tourism Research (eRTR), International Interdisciplinary Business-Economics Advancement Journal, International Journal of Tourism Cities, Heliyon, Technology in Society, Anatolia, Journal of King Saud University - Computer and Information Sciences, and Tourism Recreation Research.
This book goes into a detailed investigation of adapting artificial neural network (ANN) and structural equation modeling (SEM) techniques in marketing and consumer research. The aim of using a dual-stage SEM and ANN approach is to obtain linear and non-compensated relationships because the ANN method captures non-compensated relationships based on the black box technology of artificial intelligence. Hence, the ANN approach validates the results of the SEM method. In addition, such the novel emerging approach increases the validity of the prediction by determining the importance of the variables. Consequently, the number of studies using SEM-ANN has increased, but the different types of study cases that show customization of different processes in ANNs method combination with SEM are still unknown, and this aspect will be affecting to the generation results. Thus, there is a need for further investigation in marketing and consumer research. This book bridges the significant gap in this research area. The adoption of SEM and ANN techniques in social commerce and consumer research is massive all over the world. Such an expansion has generated more need to learn how to capture linear and non-compensatory relationships in such area. This book would be a valuable reading companion mainly for business and management students in higher academic organizations, professionals, policy-makers, and planners in the field of marketing. This book would also be appreciated by researchers who are keenly interested in social commerce and consumer research.
| Erscheint lt. Verlag | 19.11.2022 |
|---|---|
| Zusatzinfo | IX, 341 p. 18 illus., 8 illus. in color. |
| Sprache | englisch |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Wirtschaft ► Betriebswirtschaft / Management ► Marketing / Vertrieb | |
| Schlagworte | Artificial neural network for consumer research • Social commerce and technology • Structural equation modelling for consumer research • sustainability • Technology acceptance in marketing and consumer research |
| ISBN-10 | 981-19-6509-9 / 9811965099 |
| ISBN-13 | 978-981-19-6509-8 / 9789811965098 |
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