Artificial Intelligence Big Data Travelling

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Artificial Intelligence Big Data Travelling Consumption Prediction

Author : Johnny Ch LOK
Publisher :
ISBN 13 : 9781983185939
Total Pages : 129 pages
Book Rating : 4.1/5 (859 download)

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Book Synopsis Artificial Intelligence Big Data Travelling Consumption Prediction by : Johnny Ch LOK

Download or read book Artificial Intelligence Big Data Travelling Consumption Prediction written by Johnny Ch LOK and published by . This book was released on 2018-06-16 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter twoHow can apply (AI) to provide travelling businesses with better-informed decisions ?I shall explain how (AI) big data gathering technology can provide travelling businesses with better-informed decisions to drive top-line growth, deliver meaningful experience for travelling customers and smooth their path along the travelling consumer journey. The widely understood definition of (AI) involves the ability of machines or computers to learn human thinking, reasoning and decision-making abilities. So, such as (AI) learning machine system can attempt to learn travelling consumer's travel destination or travel package thinking, judgement of their reasons why they choose to go to the destination to travel or why they choose to buy the travel package and learn how and why they make their past travelling decisions from their past travel big data gathering.A Narrative science study in 2015 year identified that (AI) was being used primarily in voice recognition, machine learning virtual assistants and decision support. This study also highlighted the many branches of (AI) and that techniques and their definition are used interchangeably. It is possible that (AI) can be used to gather big data , then to analyze to help travel businesses to predict travelling consumer travel destination and travel package choice behaviors. For example, one of the most common techniques is traveler machine learning, where algorithms are used to perform tasks by learning from the airline or travel agent whose past all travelers' travelling destination choice and travel package choice historical data. However, during 2017 year, search engines will begin to find what additional factors can influence past traveler personal travelling destination and travelling package travelling behavioral data into prediction of future travelling customer behavioral results, such as the online traveler (user's) history of travelling data searches, such as anywhere are the most popular travelling locations or travelling destinations and previously captures conservations.

Handbook of Research on Smart Technology Applications in the Tourism Industry

Author : Çeltek, Evrim
Publisher : IGI Global
ISBN 13 : 1799819906
Total Pages : 569 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Smart Technology Applications in the Tourism Industry by : Çeltek, Evrim

Download or read book Handbook of Research on Smart Technology Applications in the Tourism Industry written by Çeltek, Evrim and published by IGI Global. This book was released on 2020-01-17 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today’s modernized society, certain technologies have become more applicable within many professional fields and are much easier to implement. This includes the tourism industry, where smart technology has provided a range of new marketing possibilities including more effective sales tactics and delivering a more personalized customer experience. As the scope of business analytics continues to expand, professionals need research on the various applications of smart technology within the field of tourism. The Handbook of Research on Smart Technology Applications in the Tourism Industry is an essential reference source that discusses the use of intelligent systems in tourism as well as their influence on consumer relationships. Featuring research on topics such as digital advertising, wearable technology, and consumer behavior, this book is ideally designed for travel agents, tour developers, restaurateurs, hotel managers, tour directors, airlines, marketers, researchers, managers, hospitality professionals, policymakers, business strategists, researchers, academicians, and students seeking coverage on the use of smart technologies in tourism.

Artificial Intelligence Big Data Travelling Consumption: Prediction Story

Author : Johnny Ch Lok
Publisher : Independently Published
ISBN 13 : 9781799117001
Total Pages : 108 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Artificial Intelligence Big Data Travelling Consumption: Prediction Story by : Johnny Ch Lok

Download or read book Artificial Intelligence Big Data Travelling Consumption: Prediction Story written by Johnny Ch Lok and published by Independently Published. This book was released on 2019-03-08 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future travel consumption behaviorCan (AI) big data gathering tool predict traveller individual habitual behaviour, e.g. renting travel transportation tools ?Can (AI) big data gathering tool can predict past traveller destination and travelling package choice habit and it can be intended to predict of future traveller behavior to people are creatures of habits judgement of future anywhere travelling destination choice next year or next month or next half year destination prediction ? Many of human's everyday goal-directed behaviors are performed in a habitual fashion, the transportation made and route one takes to work, one's choice of breakfast. Habits are formed when using the some behavior frequently and a similar consistency in a similar context for the some purpose whether the individual past travel consumption model will be caused a habit to whom. e.g. choosing whom travel agent to buy air ticket or traveling package; choosing the same or similar countries' destinations to go to travel; choosing the business class or normal (general) class of quality airlines to catch planes. Does habitual rent traveling car tools use not lead to more resistance to change of travel mode? It has been argued that past behavior is the best predictor of future behavior to travel consumption. If individual traveler's past consumption behavior was always reasoned, then frequency of prior travel consumption behavior should only have an indirect link to the individual traveler's behavior. It seems that renting travel car tools to use is a habit example. So, a strong rent traveling car tools useful habit makes traveling mode choice. People with a strong renting of traveling car tools of habit should have low motivation to attend to gather any information about public transportation in their choice of travelling country for individual or family or friends members during their traveling journeys. Even when persuasive communication changes the traveler whose attitudes and intention, in the case of individual traveler or family travelers with a strong renting travel car tools habit. It is difficult to change whose travel behaviors to choose to catch public transportation in whose any trips in any countries. However, understanding of travel behavior and the reasons for choosing one mode of transportation over another. The arguments for rent traveling car tools to use, including convenience, speed, comfort and individual freedom and well known. Increasingly, psychological factors include such as, perceptions, identity, social norms and habit are being used to understand travel mode choice. Whether how many travel consumers will choose to rent traveling car tools during their trips in any countries. It is difficult to estimate the numbers. As the average level of renting travel car tools of dependence or attitudes to certain travel package policies from travel agents. Instead different people must be treated in different ways because who are motivated in different ways and who are motivated by different travel package policies ways from travel agents.In conclusion, the factors influence whose traveler's individual traveller destination choice behavior The factors include either who chooses to rent traveling car tools or who chooses to catch public transportation when who individual goes to travel in alone trip or family trip. It include influence mode choice factors, such as social psychology factor and marketing on segmentation factor both to influence whose transportation choice of behavior in whose trip. So, (AI) big data can be attempted to gather past traveller transportatin tool choice, rent travelling car tools choice or catching public transportation tools choice to predict where destinaton can provide what kind of transportation tool to attract many travellers to choose to go to the place to travel.

Advances in Artificial Intelligence, Big Data and Algorithms

Author : G. Grigoras
Publisher : IOS Press
ISBN 13 : 1643684450
Total Pages : 1224 pages
Book Rating : 4.6/5 (436 download)

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Book Synopsis Advances in Artificial Intelligence, Big Data and Algorithms by : G. Grigoras

Download or read book Advances in Artificial Intelligence, Big Data and Algorithms written by G. Grigoras and published by IOS Press. This book was released on 2023-12-19 with total page 1224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computers and automation have revolutionized the lives of most people in the last two decades, and terminology such as algorithms, big data and artificial intelligence have become part of our everyday discourse. This book presents the proceedings of CAIBDA 2023, the 3rd International Conference on Artificial Intelligence, Big Data and Algorithms, held from 16 - 18 June 2023 as a hybrid conference in Zhengzhou, China. The conference provided a platform for some 200 participants to discuss the theoretical and computational aspects of research in artificial intelligence, big data and algorithms, reviewing the present status and future perspectives of the field. A total of 362 submissions were received for the conference, of which 148 were accepted following a thorough double-blind peer review. Topics covered at the conference included artificial intelligence tools and applications; intelligent estimation and classification; representation formats for multimedia big data; high-performance computing; and mathematical and computer modeling, among others. The book provides a comprehensive overview of this fascinating field, exploring future scenarios and highlighting areas where new ideas have emerged over recent years. It will be of interest to all those whose work involves artificial intelligence, big data and algorithms.

Artificial Intelligence, Big Data, Algorithms and Industry 4.0 in Firms and Clusters

Author : Luciana Lazzeretti
Publisher : Taylor & Francis
ISBN 13 : 1040144306
Total Pages : 207 pages
Book Rating : 4.0/5 (41 download)

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Book Synopsis Artificial Intelligence, Big Data, Algorithms and Industry 4.0 in Firms and Clusters by : Luciana Lazzeretti

Download or read book Artificial Intelligence, Big Data, Algorithms and Industry 4.0 in Firms and Clusters written by Luciana Lazzeretti and published by Taylor & Francis. This book was released on 2024-10-04 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume offers a wide-ranging discussion on the interrelations among AI, algorithms, big data, and Industry 4.0 to understand the importance of these new paradigms for the development of firms, districts, clusters, cities, regions, and innovation. Drawing on theoretical, empirical, and qualitative studies and using local perspectives, the chapters in this book explore theoretical aspects of AI and its evolution in social sciences, focusing on industry 4.0, smart cities, big data, and other related topics. They examine the role of industrial robots in employment, productivity, and knowledge absorption in industrial districts. They also discuss innovation in the context of local production systems, AI ecosystems, and the growth and potential of the Metaverse. Taken together, the book offers insights to help understand the new dynamics generated by the advent of these technologies and how they may affect regions, cities, clusters, industries, and organizations, and identifies avenues for future research in the development of new trajectories for clusters and firms. This book will be a key resource for scholars and advanced students in the fields of economics, geography, architecture, planning, and management as well as for interdisciplinary researchers who want to learn more about the development of new technologies, the relevance of AI, Big Data and I4.0 for firms and in relation to their adoption in clusters. This book was originally published as a special issue of European Planning Studies.

Artificial Intelligence for Big Data

Author : Anand Deshpande
Publisher : Packt Publishing Ltd
ISBN 13 : 1788476018
Total Pages : 371 pages
Book Rating : 4.7/5 (884 download)

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Book Synopsis Artificial Intelligence for Big Data by : Anand Deshpande

Download or read book Artificial Intelligence for Big Data written by Anand Deshpande and published by Packt Publishing Ltd. This book was released on 2018-05-22 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.

Artificial Intelligence, Big Data, IOT and Block Chain in Healthcare: From Concepts to Applications

Author : Yousef Farhaoui
Publisher : Springer Nature
ISBN 13 : 3031650182
Total Pages : 581 pages
Book Rating : 4.0/5 (316 download)

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Book Synopsis Artificial Intelligence, Big Data, IOT and Block Chain in Healthcare: From Concepts to Applications by : Yousef Farhaoui

Download or read book Artificial Intelligence, Big Data, IOT and Block Chain in Healthcare: From Concepts to Applications written by Yousef Farhaoui and published by Springer Nature. This book was released on with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt:

How Artificial Intelligence Measures Traveller Needs

Author : Johnny Ch Lok
Publisher :
ISBN 13 : 9781710133691
Total Pages : 188 pages
Book Rating : 4.1/5 (336 download)

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Book Synopsis How Artificial Intelligence Measures Traveller Needs by : Johnny Ch Lok

Download or read book How Artificial Intelligence Measures Traveller Needs written by Johnny Ch Lok and published by . This book was released on 2019-11-21 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: I shall explain how (AI) big data gathering technology can provide travelling businesses with better-informed decisions to drive top-line growth, deliver meaningful experience for travelling customers and smooth their path along the travelling consumer journey. The widely understood definition of (AI) involves the ability of machines or computers to learn human thinking, reasoning and decision-making abilities. So, such as (AI) learning machine system can attempt to learn travelling consumer's travel destination or travel package thinking, judgement of their reasons why they choose to go to the destination to travel or why they choose to buy the travel package and learn how and why they make their past travelling decisions from their past travel big data gathering.A Narrative science study in 2015 year identified that (AI) was being used primarily in voice recognition, machine learning virtual assistants and decision support. This study also highlighted the many branches of (AI) and that techniques and their definition are used interchangeably. It is possible that (AI) can be used to gather big data, then to analyze to help travel businesses to predict travelling consumer travel destination and travel package choice behaviors. For example, one of the most common techniques is traveler machine learning, where algorithms are used to perform tasks by learning from the airline or travel agent whose past all travelers' travelling destination choice and travel package choice historical data. However, during 2017 year, search engines will begin to find what additional factors can influence past traveler personal travelling destination and travelling package travelling behavioral data into prediction of future travelling customer behavioral results, such as the online traveler (user's) history of travelling data searches, such as anywhere are the most popular travelling locations or travelling destinations and previously captures conservations. Artificial intelligence will use this past travelling destinations and travelling package information to power predictive search results, e.g. predictive future travelling consumer's choice behavioral processing for where will be their preferable travelling destination choice and how to design travelling package to satisfy future travelling clients' needs.

Artificial Intelligent Future Development

Author : Johnny Ch Lok
Publisher :
ISBN 13 : 9781082485527
Total Pages : 366 pages
Book Rating : 4.4/5 (855 download)

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Book Synopsis Artificial Intelligent Future Development by : Johnny Ch Lok

Download or read book Artificial Intelligent Future Development written by Johnny Ch Lok and published by . This book was released on 2019-07-25 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why does travelling market seem to similar to vehicle market which can apply (AI) learning tool to predict travellingconsumer behaviors?Artificial intelligence refers to complex in vehicle market and travelling entertainment market which is very seem to be applied to predict consumer behaviors.(AI) machine learning that posses the same characteristics of human intelligence and that have all our sense, all our reason and think just like human vehicle buyer who prefer vehicle purchase choice or travelling consumer who prefer travelling package or travelling destination and airline choice. Besides, machine learning is the practice of using algorithms to collect and examine data, learn from it, and then make a determination or prediction about something in the world. So, it can be attempted to gather data concerns that travelling consumer past travelling destination choice and air ticket price choice and different travelling package, e.g. high, middle, or low class hotel and foods supply and entertainment places choice in their past travelling journeys.The machine is " trained" using large amounts of data and algorithms that give it the ability to learn how to automatically perform a task with increasing accuracy. Otherwise, deep learning is primarily based on artificial neural networks inspired by our understanding of the biology of human's brains. Thus, (AI) big data can gather all these past traveler consumption behavioral choice data to make reference to analyze whether how many travelers will choose to go to the specific travelling destination in any time by the past traveler number record to different travelling destinations, then it can gather the past air ticket sale price to different destinations and past travelling package design to different destinations in order to analyze whether it is the cheap airline ticket price factor or attractive travelling package factor or attractive travelling entertainment etc. in order to predict which factor is the most potential influential factor to they choose to go to the destination to travel in different time within one year. Then, traveler agent or airline can collect these big data to judge how to design their package to attract travelers to go to anywhere to travel or what the main factor influence most of them to choose to visit the destination to travel.For example, travel agents or airlines can apply "Deep learning" breaks down tasks in ways that enables machines to assist them to predict when travelling consumer choice will be changed and why their travelling choice will change and how their travelling choice will change with increasingly complex tasks. So, such as why (AI) technology can be applied to predict how travelling consumer behavior changes to bring to judge whether anywhere will be many travelling consumers who will prefer to choose travelling hot destinations next year or next month. Then, travel agents and airlines can gather overall past travelling consumer data to analyze and conclude the more accurate prediction of different travelling destinations to the number of traveler. Then, they can choose how much air ticket price is more reasonable to charge to the travelling destination or how to design the travelling package which can bring more attractive to the prediction number of different travelling destination travelers in order to achieve to raise the different travelling destination number next year. Thus, (AI) big data machine learning can help airlines or travel agents to solve how to design any attractive travelling package challenge.

Artificial Intelligence Predicts Marketing Behavior

Author : Johnny Ch Lok
Publisher :
ISBN 13 :
Total Pages : 182 pages
Book Rating : 4.5/5 (851 download)

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Book Synopsis Artificial Intelligence Predicts Marketing Behavior by : Johnny Ch Lok

Download or read book Artificial Intelligence Predicts Marketing Behavior written by Johnny Ch Lok and published by . This book was released on 2020-12-22 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can apply (AI) to provide travelling businesses with better-informed decisions I shall explain how (AI) big data gathering technology can provide travelling businesses with better-informed decisions to drive top-line growth, deliver meaningful experience for travelling customers and smooth their path along the travelling consumer journey. The widely understood definition of (AI) involves the ability of machines or computers to learn human thinking, reasoning and decision-making abilities. So, such as (AI) learning machine system can attempt to learn travelling consumer's travel destination or travel package thinking, judgement of their reasons why they choose to go to the destination to travel or why they choose to buy the travel package and learn how and why they make their past travelling decisions from their past travel big data gathering.A Narrative science study in 2015 year identified that (AI) was being used primarily in voice recognition, machine learning virtual assistants and decision support. This study also highlighted the many branches of (AI) and that techniques and their definition are used interchangeably. It is possible that (AI) can be used to gather big data, then to analyze to help travel businesses to predict travelling consumer travel destination and travel package choice behaviors. For example, one of the most common techniques is traveler machine learning, where algorithms are used to perform tasks by learning from the airline or travel agent whose past all travelers' travelling destination choice and travel package choice historical data. However, during 2017 year, search engines will begin to find what additional factors can influence past traveler personal travelling destination and travelling package travelling behavioral data into prediction of future travelling customer behavioral results, such as the online traveler (user's) history of travelling data searches, such as anywhere are the most popular travelling locations or travelling destinations and previously captures conservations. Artificial intelligence will use this past travelling destinations and travelling package information to power predictive search results, e.g. predictive future travelling consumer's choice behavioral processing for where will be their preferable travelling destination choice and how to design travelling package to satisfy future travelling clients' needs.Predictive search will improve the quality of online travelling search results, and provide new insights into travelling consumers' travelling destination and package behavior and the moments which matter to them. Search will give recommendation into tailored how travelling consumer individual travelling destination choice in travelling decision making process. Several of the largest online platforms already use (AI) travelling machine learning to improve predictive travelling consumer behavioral search results. For example, Google's rank brain technology adds research by understanding the context in which the travelling consumer has entered it. Over time, rank brain will learn further from user behaviors Amazon's DSSTNE ( pronouned destiny) learns from shoppers' purchasing habits and consumption behavior to offer better product recommend actions, which Amazon can offer before a consumer has entered anything into the search bar. Such as (AI) big data can gather past online travelers' e-ticket purchase transactions to conclude that online traveler's travelling choice habits and online traveler consumption behavior to offer better travelling destinations and travelling package opinions to travel agents or airlines. However, this technology is not independent of human input. For example, Google engineers will periodically retain the rank brain system to improve the models it uses.

Learning Big Data Gathering to Predict Travel Industry Consumer Behavior

Author : Johnny Ch Lok
Publisher : Independently Published
ISBN 13 : 9781726860079
Total Pages : 380 pages
Book Rating : 4.8/5 (6 download)

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Book Synopsis Learning Big Data Gathering to Predict Travel Industry Consumer Behavior by : Johnny Ch Lok

Download or read book Learning Big Data Gathering to Predict Travel Industry Consumer Behavior written by Johnny Ch Lok and published by Independently Published. This book was released on 2018-10-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Challenges of artificial intelligence, algorithms technology and machine learning impact to consumption marketThe challenges of artificial intelligence, algorithms technology and machine learning impact to consumption market are similar to travelling entertainment consumption market. Markets have played a key role in providing individuals and businesses with the opportunity to gain from trade. If (AI) big data gather tool can predict how to change potential customer behavior in success. The challenges to consumers will face that the overall market consumption model will be dominated by the businessmen only. So, it is not fair or reasonable to consumers, because (AI) big data gather tool has controlled or dominated all consumers' minds and it has predicted how and why every kind of product or service consumer shopping model or consumption behaviors how will change.It will bring this questions: How can market designers learn the characteristics necessary to set optimal, or at least better, reserve prices after they had gather all data to conclude the analytical results of their consumers behaviors how will change? How can market designers better learn the environments of their markets?

Artificial Intelligence Big Data Gathering

Author : Johnny Ch Lok
Publisher : Independently Published
ISBN 13 : 9781082827891
Total Pages : 574 pages
Book Rating : 4.8/5 (278 download)

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Book Synopsis Artificial Intelligence Big Data Gathering by : Johnny Ch Lok

Download or read book Artificial Intelligence Big Data Gathering written by Johnny Ch Lok and published by Independently Published. This book was released on 2019-07-26 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can apply (AI) digital advertisement technology to help any national chain or restaurant to advertise to overseas traveller' mobile phones in order to let they know where is its location and food taste and price? Future one day, (AI) digital advertisement promotion channel can be applied to mobiles to let any countries' target travellers to know any national chain of restaurants to attract them to choose to visit their restaurants to consume easily.A global crisis in the advertising industry largely linked to the impact of the internet is transforming the business models of media industries, the content they create and distribute, and the audiences who consume that contents. Such as consumers can use whose mobiles to find where the chain of restaurants are located and meal and drink prices and meal and drink types and restaurant opening and closing time etc. information for the national chain of restaurants from internet advertising when who leave at home conveniently. The opportunity to mobile advertising for a national chain of restaurants, it can expand its national chain of restaurants brand to different countries visitors and instead of its self country visitors to let them to know whether where its chain of restaurants can provide what kinds of food or drink to serve to them to eat before they prepare to go to any one of the national chain of restaurants immediately. Hence, when visitors travel to its country, it will be more easy to let them to remember where any one of the national chain restaurants are located in the nation when who enter the national chain restaurants website or enter yahoo website to type" national chain restaurants" word, then who can seek any one of the national chain restaurants from whose mobiles easily.

The Evolution of Yield Management in the Airline Industry

Author : Ben Vinod
Publisher : Springer Nature
ISBN 13 : 3030704246
Total Pages : 417 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis The Evolution of Yield Management in the Airline Industry by : Ben Vinod

Download or read book The Evolution of Yield Management in the Airline Industry written by Ben Vinod and published by Springer Nature. This book was released on 2021-05-28 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book chronicles airline revenue management from its early origins to the last frontier. Since its inception revenue management has now become an integral part of the airline business process for competitive advantage. The field has progressed from inventory control of the base fare, to managing bundles of base fare and air ancillaries, to the precise inventory control at the individual seat level. The author provides an end-to-end view of pricing and revenue management in the airline industry covering airline pricing, advances in revenue management, availability, and air shopping, offer management and product distribution, agency revenue management, impact of revenue management across airline planning and operations, and emerging technologies is travel. The target audience of this book is practitioners who want to understand the basics and have an end-to-end view of revenue management.

AI and Big Data’s Potential for Disruptive Innovation

Author : Strydom, Moses
Publisher : IGI Global
ISBN 13 : 1522596895
Total Pages : 405 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis AI and Big Data’s Potential for Disruptive Innovation by : Strydom, Moses

Download or read book AI and Big Data’s Potential for Disruptive Innovation written by Strydom, Moses and published by IGI Global. This book was released on 2019-09-27 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.

The Role of Artificial Intelligence in Regenerative Tourism and Green Destinations

Author : Alhamzah Alnoor
Publisher : Emerald Group Publishing
ISBN 13 : 1837537488
Total Pages : 438 pages
Book Rating : 4.8/5 (375 download)

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Book Synopsis The Role of Artificial Intelligence in Regenerative Tourism and Green Destinations by : Alhamzah Alnoor

Download or read book The Role of Artificial Intelligence in Regenerative Tourism and Green Destinations written by Alhamzah Alnoor and published by Emerald Group Publishing. This book was released on 2024-07-09 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume takes the reader through the origins of regenerative tourism and how artificial intelligence can be utilised to develop and maintain green tourism. Chapters examine everything from marketing, data mapping, employment opportunities, cultural issues as well as what the future holds for tourism to give back to countries.

Handbook of e-Tourism

Author : Zheng Xiang
Publisher : Springer Nature
ISBN 13 : 3030486524
Total Pages : 1976 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Handbook of e-Tourism by : Zheng Xiang

Download or read book Handbook of e-Tourism written by Zheng Xiang and published by Springer Nature. This book was released on 2022-09-01 with total page 1976 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook provides an authoritative and truly comprehensive overview both of the diverse applications of information and communication technologies (ICTs) within the travel and tourism industry and of e-tourism as a field of scientific inquiry that has grown and matured beyond recognition. Leading experts from around the world describe cutting-edge ideas and developments, present key concepts and theories, and discuss the full range of research methods. The coverage accordingly encompasses everything from big data and analytics to psychology, user behavior, online marketing, supply chain and operations management, smart business networks, policy and regulatory issues – and much, much more. The goal is to provide an outstanding reference that summarizes and synthesizes current knowledge and establishes the theoretical and methodological foundations for further study of the role of ICTs in travel and tourism. The handbook will meet the needs of researchers and students in various disciplines as well as industry professionals. As with all volumes in Springer’s Major Reference Works program, readers will benefit from access to a continually updated online version.

Artificial Intelligence Brings Social Influences

Author : Johnny Ch Lok
Publisher : Independently Published
ISBN 13 :
Total Pages : 198 pages
Book Rating : 4.7/5 (284 download)

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Book Synopsis Artificial Intelligence Brings Social Influences by : Johnny Ch Lok

Download or read book Artificial Intelligence Brings Social Influences written by Johnny Ch Lok and published by Independently Published. This book was released on 2021-03-25 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to apply (AI) big data to predict individual traveler's behavioral intention of choosing a travel destination? Understanding why people travel and what factors influence their behavioral intention of choosing a travel destination is beneficial to tourism planning and marketing. In general, an individual's choice of a travel destination into two forces. The first force is the push factor that pushes an individual away from home and attempt to develop a general desire to go somewhere, without specifying where that may be. The other force is the pull factor that pull an individual toward in destination, due to a region-specific or perceived attractiveness of a destination. The respective push and pull factors illustrate that people travel because who are pushed by whose internal motives and pulled by external forced of a destination. However, the decision making process leading to the choice of a travel destination is a very complex process. For example, a Taiwanese traveler who might either choose new travel destination of Hong Kong or another old travel Asia destinations again or who also might choose any one of Western country, as a new travel destination. The travel agents can predict where who will have intention to choose to travel from whose past behavior and attitude, subjective and perceived behavioral control model. When (AI) big data gather past every country traveler number who chose to go to which countries to travel in order to judge where destinations will be the country travelers' travelling choice destinations in the future.The factors influence where is the traveler choice, include personal safety, scenic beauty, cultural interest, climate changing, transportation tools, friendliness of local people, price of trip, trip package service in hotels and restaurants, quality and variety of food and shopping facilities and services etc. needs. So, whose factors will influence where is the individual travel's choice. It seems every traveler whose choice of travel process, will include past behavior. e.g. travelling experience, travelling habit, then to choose the best seasoned travelling action to satisfy whose travel needs. This process is the individual traveler's psychological choice process, who must need time to gather information to compare concerning of different travel packages, destination scene, climate change, transportation tools available to the destination, air ticket price etc. these factors, then to judge where is the best right destination to travel in the right time. Hence, (AI) big data can gather past different countries' climate changing data, transportation tool changing data, destination scene environment changing etc. different data to give opinions to travelling businesses whether any country's these above factors will influence about how many traveler number will be increase or decrease in the future.2.3Why can expectation, motivation and attitude factor influence travelling behavior?Social psychology is concerned with gaining insight into the psychological of socially relevant behaviors and the processes. For instance, on a global level bad influence to global warming, it influences some countries extreme cold or hot bad climate changing occurrence, then it ought influence some travelers' behavioral decision to change their mind to choose some countries to go to travel at the moment which do not occur extreme hot or cold climate ( temperature). e.g. above than 40 degree in summer or below than 0 degree in winter. Due to the extreme climate changing environment in the countries, it will cause them to feel uncomfortable to play during their trips. So, the global warming causes to climate changing factor will influence the numbers of travel consumption to be reduced possibly.