Alhamzah Alnoor – författare

Tourism is a huge economic driver for most countries, and for some parts of the world it is their main source of income. Despite this economic strength, tourism can be a fragile and volatile industry, as recent natural disasters and pandemics have shown. Regenerative tourism was founded on building better; with the philosophy that better tourism is possible, regenerative tourism emphasizes the innovative nature of resources, services, and systems.

The Role of Artificial Intelligence in Regenerative Tourism and Green Destinations takes the reader through the origins of regenerative tourism and how artificial intelligence can be utilised to develop and maintain green tourism. The chapter authors examine everything from marketing, data mapping, employment opportunities, cultural issues as well as what the future holds for tourism to give back to countries.

The interdisciplinary focus of this book appeals to researchers of tourism, economics, technology and sustainable development.

Tourism is a huge economic driver for most countries, and for some parts of the world it is their main source of income. Despite this economic strength, tourism can be a fragile and volatile industry, as recent natural disasters and pandemics have shown. Regenerative tourism was founded on building better; with the philosophy that better tourism is possible, regenerative tourism emphasizes the innovative nature of resources, services, and systems.

The Role of Artificial Intelligence in Regenerative Tourism and Green Destinations takes the reader through the origins of regenerative tourism and how artificial intelligence can be utilised to develop and maintain green tourism. The chapter authors examine everything from marketing, data mapping, employment opportunities, cultural issues as well as what the future holds for tourism to give back to countries.

The interdisciplinary focus of this book appeals to researchers of tourism, economics, technology and sustainable development.

This book explores current research trends in the context of the Metaverse’s impact on the tourism and marketing industries while delving into some case studies on education and finance. These trends are examined through various case studies utilizing distinct analytical methods. The chapters are expected to support scholars and postgraduate students in furthering their research in this field and in recognizing prospective advancements in the applications of the Metaverse.

This book addresses recent research trends concerning the role of the Metaverse in advancing the education and finance sectors from various perspectives. These trends are explored through multiple case studies employing diverse analytical approaches. The chapters aim to aid scholars and postgraduate students in pursuing future research in this domain and identifying potential developments in Metaverse applications.

This book explores current research trends in the context of the explainable artificial intelligence’s impact on the digital sustainability trend while delving into case studies on education, tourism, marketing, and finance. These trends are examined through various case studies utilizing distinct analytical methods. The chapters are expected to support scholars and postgraduate students in furthering their research in this field and in recognizing prospective advancements in the applications of artificial intelligence.

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.