Abhaneri Festival

, 246

Advanced Commercial Vehicle Operation (ACVO)

, 50–51

Advanced Traveller Information Systems (ATIS)

, 50–51

Advanced Vehicle Control Systems (AVCS)

, 50–51

Aeroplanes

, 52

Agriculture

, 27–28

Airbnb

, 149

Airline companies

, 11

Alexa

, 162

Algae

, 197

Alibaba Tmall Genie

, 161–162

Alizarin

, 201

Allset

, 8

Alternative proteins

, 196–197

Amadeus

, 133

Amazon Echo

, 161–162

Amazon Web Services (AWS)

, 7–8

ANOVA analysis

, 89–90

Anthropomorphism

, 62

Antinatalists

, 232–233

Apple HomePod

, 161–162

Apple’s Siri

, 161–162

ARPANET

, 133–134

Artificial intelligence (AI)

, 4, 55, 62, 176–177

case study

, 13–14

in events

, 12–13

in hotels

, 6–7

in restaurants

, 7–8

in tourism

, 5–13

in transportation organisations

, 9–12

in travel organisations

, 9

Travel Planners

, 9

voice assistants

, 161–162

Artificial meat

, 197–200

food safety and transparency

, 199

nutraceuticals

, 198

personalised nutrition

, 198–199

plastic-free and smart packaging

, 200

Attitudes

, 63–64

Augmented reality (AR)

, 51, 116–117

technology in promotion of Dublin City

, 121

Authenticity

, 240–241

Author citation analysis

, 183

Automated temperature control systems

, 52

Automatic speech recognition (ASR)

, 161–162

Automation systems

, 176–177

Autonomous agents

, 5

Aviation, IoT in

, 52–53

Baneshwar Fair in Dungarpur

, 245

Bee Colony algorithm

, 44

Begpacking

, 212

Behavioural attitude

, 63–64

Behavioural intention

, 63–64

Beverage industries, IoT in

, 27–28

Big data

, 53, 104–105

Binder Jetting (BJ)

, 84

Bing

, 103

Bionic bars

, 53–54

BLive tour company

, 148–150

Blockchain technology

, 196

Bluetooth

, 26–27

Booking agents

, 101

Booking.com

, 108–109

BRE Hotels and Resorts

, 54

British Museum

, 105

Case study method

, 194–195

Catering industry in China

, 8

Chatbots

, 5, 9

Childfree

, 231–232

zones

, 233

Cloud-based smart restaurant management systems

, 7–8

Collaboration.Ai

, 13

Comprehensibility

, 241–242

Computer reservation systems (CRSs)

, 99

Computers

, 160

Consumer satisfaction

, 107

Conversational systems

, 5

Covid-19 pandemic

, 135, 178

Crickets

, 197

Cruise companies

, 53

Cruise industry, IoT in

, 53–54

Cruise lines

, 9–10

Curiosity

, 241–242

curiosity/interest behaviour

, 73

Customised food products for consumers

, 82

Cutting-edge technologies

, 99

Decision-making

, 4

Delta Airlines

, 12

Destination Integrated Computerised Information Reservation Management Systems (DICIRMS)

, 104

Destination management system (DMS)

, 104

Destinations

, 104

IoT technologies in

, 50–51

Digital Concierge Program

, 50–51

Digital food management

, 196

Digital storytelling

, 241–242

Digital systems

, 195

Digital technologies

, 195

Digital transformation

, 132–133

Digital voice assistants

, 161–162

Digitalisation

, 134, 194–195

Digital–physical hybrids

, 5–6

Digitisation of travel and tourism sector

, 102

Disney’s MagicBand

, 52

Document technique

, 180

Double Income No Kids (DINK)

, 232

e-Bike tours

, 148–149

E-destinations

, 104–105

E-hospitality

, 106–107

E-tourism

, 98

case of different countries

, 101

consumer satisfaction

, 107

E-destinations

, 104–105

E-hospitality

, 106–107

E-tours

, 104

E-TripAdvisor

, 103

4G/5G use

, 106

mobile technology adoption

, 105–106

multimedia technology

, 105

or digitisation of travel and tourism sector

, 102

OTAs

, 103–104

social media

, 106

tourism in India

, 100–101

trends

, 103

virtual museum

, 105

web-based

, 103

E-tours

, 104

E-TripAdvisor

, 103

EasyJet

, 54

Edible insects

, 197

Electric vehicles (EVs)

, 144

adoption

, 147

challenges

, 147–148

contributions

, 150–151

Electronic commerce

, 99–100

Electronic menus

, 195

Electronic Toll Collection Systems (ETC)

, 50–51

Empowering women

, 260

Enjoyment/satisfaction

, 73

Entomophagy

, 197

Environmentally friendly and sustainable technology

, 83

Events, AI in

, 12–13

Extended reality (XR)

, 116, 120–121

Face-to-Face Robots in Airports

, 9

Facebook

, 106, 133–134

Facial recognition technology

, 6

Family tourism

, 231–234

Female travellers

, 210

Festivals

, 240–241

Firms

, 177–178

Flightkeys

, 12

FlyZoo Hotel

, 6

Food industry

, 82

IoT in

, 27–28

Food management

, 196

Food production

, 194

Food safety

, 199

Food supply chain

, 34–36

Food waste

, 31

Forecasting tools

, 5

4G/5G use

, 106

Freestyle Cruising

, 53–54

Fused Deposition Modelling (FDM)

, 84

Galileo

, 133

Gastronomy industry

, 176, 194

case study

, 179

findings

, 180–186

methodology

, 179–180

service robots in

, 177–179

technology in

, 176–177

Gender equality

, 259–261

Gender-based discrimination

, 260

Gender-based risks

, 213

Generation PANK/PUNK

, 227

Global distribution systems (GDSs)

, 99, 103–104

Global tourism

, 99

Goa

BLive on

, 150

challenges of EV and e-bikes in

, 150

Goa Tourism Development Corporation (GTDC)

, 151

Google

, 103, 160–161

Google Assistant

, 162

Google Home

, 161–162

Google Scholar

, 180

Gothenburg, Sweden-Smart City

, 54

Grasshoppers

, 197

Gross domestic product (GDP)

, 100–101

Healthcare

, 27–28

Henn-na Hotel

, 7, 62

Hierarchical Code-Subcode Model

, 66

HoloLens

, 119

HoloTour

, 122

Hospitality

, 4, 194

IoT technologies in

, 51–52

Hotels, AI in

, 6–7

HTTP protocol

, 133–134

Human–computer interaction (HCI)

, 161

Human–robot interaction

, 65

Identity

, 240

iN2015 initiative

, 50–51

Independent samples T-test

, 88

India, tourism in

, 100–101, 107, 109

Influencers

, 132–133

Information and communication technologies (ICTs)

, 5, 55, 98, 117–118, 142

Information Technology (IT)

, 98, 147–148

Ink Jet Printing

, 84

Instagram

, 133–134

Institution citations network

, 185–186

Intelligent devices

, 50

Intelligent personal assistants

, 161–162

Intelligent tourism destinations

, 5

Intelligent virtual assistants

, 161–162

Internet Booking Portals

, 103

Internet of Everything (IoE)

, 55

Internet of Things (IoT)

, 11, 26–27, 50, 145, 160

analysis of data

, 29–30

in aviation

, 52–53

best practice sample

, 28

case study

, 31, 44, 54

in cruise industry

, 53–54

in food and beverage industries

, 27–28

food supply chain

, 34–36

IoT-based systems

, 26

material/method

, 28–29

results

, 30–31

sampling and data collection process

, 29

smart and sustainable agriculture

, 37–40

technologies in hospitality

, 51–52

technologies in tourism and destinations

, 50–51

waste management

, 41–43

Internet-based electronic commerce

, 99–100

Jawai Bandh

, 245–246

Jawai Leopard Safari

, 245–246

Journal citation analysis

, 184–185

Kaiser-Meyer-Olkin value (KMO value)

, 87–88

Keywords

, 186

Kitchen

, 27–28

Know your model (KYM)

, 84

Knowledge representation

, 4

Kolayat Festival and Fair, Bikaner

, 246

Language translation applications

, 5

Language-agnostic application

, 51

Layered Stack Modelling

, 84

Leiper’s model

, 142

Leopard tracking

, 245–246

Li-Fi

, 26–27

LinkedIn

, 133–134

Liquefied natural gas (LNG)

, 13–14

Louvre Museum

, 105

M-tourism

, 102

Machine learning (ML)

, 4

Matsya Utsav Alwar

, 245

MAXQDA 2020 qualitative data analysis programme

, 30, 66

Mealworms

, 197

Meaningful travel

, 211

Menus

, 195

Metaheuristic algorithms

, 4

#MeToo movement

, 214

Metropolitan Museum of Art

, 105

Microsoft

, 103

Mixed reality (MR)

, 116, 119–120

application in tourism

, 122

Mobile technology adoption

, 105–106

Mobility

, 142

Mosaic Netscape

, 133–134

Motivations

, 211

MSC Cruises

, 10

Multimedia technology

, 105

NADIA

, 52

Natural language processing (NLP)

, 161–162

Network speeds

, 98–99

New food structuring

, 83

New techs and trends in food

, 195–197

3D food printers

, 196

algae

, 197

alternative proteins

, 196–197

artificial meat

, 197–200

case study

, 200–201

digital food management

, 196

edible insects

, 197

restaurant digisation

, 195

NFC

, 26–27

tags

, 51

Non-traditional family tourism

, 233–234

Not Mothers (NoMos)

, 231

Nutraceuticals

, 198

Online reservation systems

, 103

Online tourist reviews

, 103

Online Travel Agencies (OTAs)

, 103–104

Open Data Trentino

, 51

Operations

, 148

Optimisation

, 4

Originality

, 241–242

Pay per view (PPV)

, 106

Peer-to-peer (P2P)

, 214

PepsiCo

, 83

Perceived ease of use

, 63–64

Perceived usefulness

, 63–64

Personalisation techniques

, 5

Personalised nutrition

, 198–199

Photo/video-taking

, 72

Pinterest

, 133–134

Planning

, 4

Plastic-free packaging

, 200

Population Matters (PM)

, 232–233

Printing with binder liquids

, 84

Production process

, 83

Professional aunts with no kids (PANK)

, 226

case study

, 227–231

characteristics

, 227

conceptual background

, 226–227

engagement guide

, 229

family tourism

, 231–234

principles

, 228

types

, 227

Professional uncles with no kids (PUNK)

, 226

case study

, 227–231

characteristics

, 227

conceptual background

, 226–227

family tourism

, 231–234

Professional women/men

, 226

PubMed

, 180

Pure digital systems

, 5–6

QR codes

, 51

QRC

, 26–27

Quantitative research method

, 87

Rabari’ people

, 245–246

Radio-frequency identification (RFID)

, 26–27, 200

Ramdevra Fair, Jaisalmer

, 246

Ranakpur Jawai Bandh Utsav

, 245–246

Reality technologies

, 116

augmented reality

, 116–117

case study

, 121–122

extended reality

, 120–121

mixed reality

, 119–120

virtual reality

, 117–119

Reasoning

, 4

Recommender systems

, 5

Regional fairs or festivals in Rajasthan

, 244–246

Regional festivals

, 240–241

Restaurants

, 176–177

AI in

, 7–8

digisation

, 195

Return on investment (ROI)

, 13

Robot chefs

, 177

Robotic technologies

, 176–177

Robots

, 5–6, 64, 178

Royal Caribbean Cruises

, 10–11, 13–14, 53

‘Sanbot Elf’ service robot

, 66

Scopus

, 180

Search engines

, 98–99

Second-chance tourism

, 120

Selective Laser Sintering (SLS)

, 84

Sensibility

, 241–242

Service robots

, 62–63, 176

case study

, 66–67

findings

, 67

in gastronomy industry

, 177–179

interview questions

, 67–71

methodology

, 66–67

observational findings

, 72–73

technology acceptance model

, 63–66

Single Income No Kids (SINK)

, 232

Small and medium-sized enterprises (SMEs)

, 99–100

Smart and sustainable agriculture

, 37–40

Smart apps

, 145

Smart Cruise Ecosystem (SCE)

, 55

Smart data

, 144–145

Smart governance and infrastructure

, 145

Smart machines

, 28

Smart mobility

, 142–143

adoption and promotion

, 145–146

case study

, 148–149

challenges

, 147–148

factors

, 147–148

historical developments

, 143

scope

, 143–145

uses

, 146–147

Smart packaging

, 200

Smart tourism

, 50–51, 136

Smart transport

, 144

Smartphones

, 160

Smithsonian National Museum of Natural History

, 105

Snapchat

, 133–134

Social change

, 210

Social media

, 106

channels

, 132

in tourism

, 133–134

Solo female travellers

case study

, 211–217

literature review on

, 210–211

story

, 211

studies

, 210–211, 214, 217

Solo tourists

, 216–217

Solo travel

, 256–258

Solo travellers

, 210

Solutions

, 194

Stakeholders

, 137

Starbucks

, 8

Stories

, 240–241

Storytelling

, 247

Subway Order Bot

, 8

Supply chain management

, 28, 44

Sustainability

, 197–198

Sustainable Development Goals (SDGs)

, 260

Sustainable tourism

, 241–242

Systematic literature reviews (SLRs)

, 28–29

Systematic searches

, 28–29

Tablet computers

, 7–8

Tacobot

, 8

Tanbo R-1

, 179

Tanbo R-2

, 179

Teachability

, 241–242

Technology

, 62, 98–99, 194

in gastronomy industry

, 176–177

Technology acceptance model

, 63–66

Telegram

, 133–134

Termites

, 197

Text-to-speech (TTS)

, 161–162

Thematic analysis

, 151

Theory of reasoned action

, 63–64

Three-dimension (3D)

advantages

, 82–83

case study

, 86–87

comparison

, 85

conceptual framework

, 82–83

findings

, 87–90

food printers

, 196

food printing technology

, 82

literature review

, 84–86

methods used in 3D food processing

, 83–84

printing technology

, 82

Touch Business

, 28

Tour operators

, 104

Tourism(see also Virtual tourism)

, 62, 98–99, 116, 142, 240

AI in

, 5–13

experiences

, 145

in India

, 100–101

IoT technologies in

, 50–51

marketing

, 109

social media in

, 133–134

virtuality in

, 133

Tourists

, 98

Transmedia revolution

, 243–244

Transmedia storytelling

, 240

objectives of study

, 243

potential

, 243–244

regional fairs or festivals in Rajasthan

, 244–246

relationship between regional festival storytelling and tourists’ visit or revisit intention

, 247

research methodology

, 243

review of literature

, 241–243

Transparency

, 199

Transport capacity

, 98–99

Transportation organisations

, 9–12

Travel blogs

, 214

Travel organisations, AI in

, 9

Travel service providers

, 132–133

Travel with nephews/nieces

, 226

TreSight

, 51

Tribal Kumbha Mela

, 245

TripAdvisor

, 149

Twitter

, 106, 133–134

Unified Theory of Acceptance and Use of Technology (UTAUT)

, 64–65

United Nations Development Programme (UNDP)

, 259–260

United Nations World Tourism Organization (UNWTO)

, 101

US Food and Drug Administration (FDA)

, 197–198

Vatican Museum

, 105

Vehicle tracking system

, 51

Vimeo

, 133–134

Virtual museum

, 105

Virtual reality (VR)

, 116–117, 119, 132

technologies

, 132–133

for visitors and tourism employees

, 121

Virtual tourism

, 132–133

case study

, 135–136

challenges

, 137

emergence of virtual tourism influencers

, 134–135

social media in tourism

, 133–134

virtuality in tourism

, 133

Virtual voice assistants

, 161–162

Virtualisation

, 133

Virtuality in tourism

, 133

Voice assistants

, 5

Voice command

, 160–161

Voice control

, 160–165

advantages

, 164–165

case study

, 167

in hospitality and tourism industry

, 163–164

Voice control devices (VCDs)

, 161–162

Voice recognition

advantages

, 164–165

in hospitality and tourism industry

, 163–164

technology

, 160–161

Voice search

, 160–161, 165, 167

case study

, 167

challenges and opportunities

, 166–167

in tourism industry

, 165–166

Voice-based digital assistants

, 161–162

Voice-controlled search (see Voice search)

Voice-enabled search (See Voice search)

Voice-enabled technology

, 8

Voluntary Human Extinction Movement (VHEMT)

, 232–233

Waste management

, 31, 41, 43

Wayfinder

, 53

Web of Science (WoS)

, 180

Web-based E-tourism

, 103

Websites

, 133–134

WhatsApp

, 133–134

Wi-Fi

, 26–27

Women solo travellers

, 258–259

base for gender equality

, 261–262

case study

, 261

World Wide Web

, 133–134

World-building

, 242–243

Wristband

, 53

Yahoo

, 103

YouTube

, 106, 133–134

Z generation

, 178

Z-wave technologies

, 26–27