Acceptance of restrictions and safety measures

, 95, 97–99

ADAPTAR programme

, 250

Adaptive capacity

, 55

Adventure tourism

, 52

Air transport strategy

, 161

Ajzen’s theory

, 228–229

Akaike information criterion

, 149

Armação dos Búzios

, 68–69

Artificial intelligence (AI)

, 144

Asset pricing risk

, 122

literature review

, 123–125

method

, 126–131

results

, 132–136

Association of Turkish Travel Agencies (TURSAB)

, 39

Avian influenza

, 13–22

Aviation sector in Turkey

, 40

Banco do Brasil, National Bank for Economic and Social Development (BNDES)

, 75–76

Biases

, 125

Brand love

, 228

limitations

, 238

literature review

, 229–231

methodology

, 232

results

, 233–235

Brands

, 228

Brazil

, 68, 70–72

Brazilian tourism

access, services and tourist attractions restrictions

, 74–75

analysis

, 78–79

campaign support to minimize sector losses

, 77–78

economic and financial measures

, 75–77

map

, 68

methodological procedures

, 71–72

mobility of people

, 74

normative acts

, 72–78

public policies in tourism, intergovernmental coordination and government functions

, 69–71

Brazilian Tourism Institute

, 77

Celebrities

, 195–197

Celebrity WOM

, 194–195, 199

Chikungunya fever

, 231

China–Pakistan Economic Corridor (CPEC)

, 54

Cholera

, 231

‘Clean and Safe’ seal

, 250

Climate change

, 37

Community resilience

, 55

Conditional volatility

, 130

Conscious Tourism Seal

, 77

Content analysis procedures

, 216–217, 233, 235

Coordination

, 70

Corporate bond portfolio ETF

, 135

Corporate social responsibility (CSR)

, 212–213, 215

COVID-19

, 107–108, 142, 158, 174–175, 193

destination marketing during

, 215–216

destination strategies for recovery and resilience in

, 4–5

impacts in economy and finance

, 4

and importance of communication during crisis

, 194–195

outbreak

, 122

pandemic

, 2–3, 11–12, 30–31, 50–51, 72, 84, 212, 245

and risk perception in tourism

, 197–198

in Russian Federation

, 109

tourism crisis management in Southern European countries

, 248–251

and tourism industry management

, 57–60

tourism promotion during

, 230–231

tourists and residents perceptions regarding

, 3

Credibility

, 199

Crisis

, 29–30, 158–159

and disaster management

, 246

in Turkey

, 31–33

Cultural heritage

, 38

Cultural tourism

, 51

Daily life and travelling

, 117–118

Dengue

, 13, 22, 231

Destination brand love

, 228

Destination image

, 193–194, 213, 215

interpretation of content and destination image scale matrix

, 218–219

Destination management/marketing organizations (DMOs)

, 212

in destination marketing

, 212–213

promotional campaigns

, 233

Destination marketing

, 212–213, 228

during COVID-19 pandemic

, 215–216

DMOs in

, 212–213

Destination(s)

, 230

resilience

, 247

social responsibility strategy

, 222

strategies for recovery and resilience in COVID-19 context

, 4–5

Dexamethasone

, 12

Disease outbreak

, 10

Droughts

, 38

Earthquakes

, 38

Ebola virus disease

, 13, 22, 231

Economic collapse

, 143

Economic Commission for Latin America and the Caribbean (ECLAC)

, 177

Economic policy

, 143

Economic policy uncertainty (EPU)

, 142

indexes calculation and studies

, 144–146

Economic recession

, 29–30

Ecotourism

, 37–38, 52

Ecuador

, 158

characterization of sector

, 162–163

literature review

, 159–162

methodology

, 163–165

results

, 165–168

Ehsas programme

, 58

Electronic word of mouth (eWoM)

, 56, 196

Environmental crises

, 37–38

Environmental disasters

, 29–30, 175

Epidemic preparedness index (EPI index)

, 145, 148

Epidemics

, 8

impacting tourism in twenty-first century

, 12–13, 22–23

Estimation methods

, 178–179

European equity portfolio ETF

, 135

European Union (EU)

, 30, 87, 248–249

Expertise/knowledge, level of

, 199

Factor analysis

, 130

Familiarity

, 199

Federal

, 70

Federalism

, 70

Federation

, 70

Filtered probabilities

, 147

Flightradar24 website

, 173–174

Floods

, 38

Gandhara Civilization

, 51

Generalized autoregressive conditional heteroskedasticity (GARCH)

, 130, 142–143

Geopolitical disasters

, 175

Geopolitical instabilities

, 35–37

Geopolitical uncertainty (GEOU)

, 143

Global crisis

, 30

Global economic crisis

, 34–35

Global EPU index (GEPU index)

, 145

Globalization of tourism industry

, 1

Government functions

, 69–71

Government intervention

, 135

Government response

, 122

Government Response Tracker (GRT)

, 124, 126, 130

‘Greece from Home’ platform

, 249

Green stimulus project

, 54

Gross domestic product (GDP)

, 87, 145, 174–175, 248

Guarantor function

, 71

Gurdwaras

, 51–52

H1N1 virus

, 11

H1N2 flu pandemic

, 10

H2N2 virus

, 11

H3N2 virus

, 11

Hannan–Quinn information criteria

, 149–150

Harappan Civilization

, 51

Health risks

, 8, 85, 197

in tourism

, 8–9

Health-related crises

, 23, 38, 40

Health-related outbreaks

, 108

Herding behaviour

, 125

Heritage tourism

, 51

Heritage tourists

, 51

Higher Education Commission (HEC)

, 54–55

Home bias

, 125

Horizontal coordination

, 79

‘Host destinations’ residents

, 159

Hotel Association of Turkey (TUROB)

, 39

Human immunodeficiency virus (HIV)

, 231

Individual investors

, 125, 135–136

Individual resilience

, 247

Indus Valley Civilization

, 51

Influenza

, 231

Institutional investors

, 124–125, 135–136

Instituto Brasileiro de Geografia e Estatístíca (IBGE)

, 68

Intangible heritage

, 51

Interaction effect

, 122

Intergovernmental coordination

, 69, 71

International migration

, 36

International travel

, 23

Kaiser-Meyer-Olkin measure

, 131

Karakoram 2 (K-2)

, 52

Katherine Flood in Australia

, 38

Leisure and recreation stocks

, 143

data processing and high volatility regime smoothed probability estimation

, 146–148

economic policy uncertainty indexes calculation and studies

, 144–146

methodology

, 146–150

results

, 148–150

Malaria

, 231

Markov-switching models

, 143

Marmara (İzmit) earthquake (1999)

, 38

Mean-variance concept

, 123

Measles

, 231

Meningitis

, 231

Mexican tourist income

, 174–175

Mexico

, 174–175

data and variable transformation

, 178

estimation methods

, 178–179

implications

, 182–185

literature review

, 175–177

methodology

, 177–179

model specification by economic activity

, 178

results

, 179–182

Middle East respiratory syndrome coronavirus (MERS-CoV)

, 13, 22, 231

Ministério do Turismo (MTur)

, 69, 78

Mobility

, 161

Mughal Empire

, 51

National Confederation of Commerce, Services, Goods and Tourism (CNC)

, 68

National Institute of Statistics and Geography (INEGI)

, 178

Natural disasters

, 38

News media

, 195

News sentiment

, 142

No-Objection Certificates (NOCs)

, 56

Non-believers

, 51

North American Industrial Classification System (NAICS)

, 177, 185

Option volatility risk

, 135

Ordinary least squares (OLS)

, 148

Organisation for Economic Co-operation and Development (OECD)

, 177, 231–232

Organizational resilience

, 247

Outbreaks impacting tourism in twenty-first century

, 12–13, 22–23

Pakistan Hotels and Restaurants Act (1976), The

, 54–55

Pakistan Tourism Development Corporation (PTDC)

, 56

Pakistan Tourist Guides Act (1976), The

, 54–55

Pakistan’s tourism industry

, 50

categories and forms

, 51–52

COVID-19 and tourism industry management

, 57–60

rise of

, 55–57

struggling

, 52–55

Pandemic(s)

, 2–3, 8–10, 29–30, 85, 99

in history

, 10–11

impacting tourism in twenty-first century

, 12–13, 22–23

Paraty

, 76–77

Perceived risk

, 230

Physical risks

, 9

Poliomyelitis

, 231

Political conflicts

, 29–30

Portugal

, 194, 212

channels

, 202

country of origin

, 199–202

limitations

, 205

methodology

, 198–199

results

, 199–204

theme

, 202–204

theoretical background

, 194–198

Positive Word of Mouth (pWOM)

, 4, 193–194

Product Input Matrix (PIM)

, 164

Prospects

, 173–174

Public policy

, 70–71

in tourism

, 69–71

Purchasing Power Parity (PPP)

, 145

Quintana Roo

, 182

Recovery communication

, 216

Refinitiv global leisure and recreation stock index (RGLR)

, 143

Regional Economic Analysis Laboratory of the National Autonomous University of Mexico (LabREG-UNAM)

, 177, 179

Religious tourism

, 51

Residents

, 88

Resilience

, 49–50, 55

building resilience in Southern European countries

, 251–254

in tourism

, 246–248

Resilient destination

, 251

Restart project

, 76–77

Rio de Janeiro

, 68–69

Risk perception

, 85, 108–109, 197

in tourism

, 197–198

in travel

, 1

Risk(s)

, 211, 8–9, 122

risk-reduction strategy

, 193–194

Russia

, 109

Russian Federation

basic results

, 110–112

COVID-19 in

, 109

findings

, 110–113

key results

, 112–113

methodology

, 109–110

Russian residents

, 3

Safety

, 215, 85, 197, 230, 237–238

communication

, 195

on vacation and leisure

, 108–109

Safety perceptions

in daily life and future plans

, 93, 95–97

data analysis

, 89–90

data collection

, 88–89

literature review

, 85–86

methodology

, 87–90

research setting

, 87–88

results

, 90–97

survey instrument design

, 88

in tourism activities practicing

, 91–93

to travel inside and outside country

, 90–91

Scenario method

, 158–159

Seasonal autoregressive integrated moving average models (SARIMA models)

, 177

Sense of community

, 229–230

Severe acute respiratory syndrome (SARS)

, 1–2, 31–32, 38–39, 84, 108

Severe acute respiratory syndrome coronavirus (SARS-COV)

, 11–13, 22

SARS-CoV-1

, 231

SARS-COV-2

, 11–12, 68, 142, 158, 173–174, 215–216

Social disasters

, 175

Social distancing measures

, 158

Social media

, 195

Social resilience

, 55

Southern European countries

, 244

literature review

, 244–248

methodology

, 248

Spanish flu

, 10

Spanish Tourist Quality Institute (ICTE)

, 251

Spatial weights matrix

, 178

Stock markets

, 123

Surprise effect

, 122, 131–132

COVID-19

, 131

sensitivity

, 135–136

Sustainability of tourism

, 55

Swine influenza

, 13–22

Tangible heritage

, 51

Technological incidents or failures

, 32

Territorial and Urban Property Tax (IPTU)

, 76–77

Terrorism

, 29–30

Theory of Planned Behaviour (TPB)

, 228–229

Three-factor model

, 123

Tourism

, 1, 68, 84–85, 108, 159–160, 230, 244

challenges for future in

, 23–24

health risks in

, 8–9

industry

, 8, 30, 122

industry

, 161

market

, 228

marketing

, 212

in Mexico

, 174, 182

promotion during COVID-19 pandemic

, 230–231

resilience

, 244

sector in Turkey

, 29–32

tourism-dependent communities

, 55

vulnerability

, 50

Tourism Coordination Board

, 56

Tourism crises

and disaster management

, 244–246

and governments policies and measures in COVID-19 context

, 3

Tourism-led growth hypothesis (TLGH)

, 174

Tourist Assistance Centre

, 77

Tourists

, 8–9

destinations

, 159

and residents perceptions regarding COVID-19 pandemic

, 3

Trade policy uncertainty (TPU)

, 144

Travel Agencies Act (1976), The

, 54–55

Travel and Tourism Competitiveness Index (T&TC Index)

, 56–57

Travel risk perception

, 90

Travelling and coronavirus

, 118–119

#TuPodes national campaign

, 254

Turkey

, 30

crises and tourism sector in

, 31–33

findings

, 33–40

limitations and future research

, 42

literature review

, 31–32

purpose and method of study

, 32

tourism sector in

, 30–31

Uncertainty

, 142

United Nations Conference on Trade and Development (UNCTAD)

, 176–177

United Nations World Tourism Organization (UNWTO)

, 57–58

US dollars (USD)

, 145

US economic policy uncertainty index

, 4

US markets

, 143

US stock market volatility index (USVI)

, 145

Value-at-risk concept

, 123

Vertical coordination

, 79

Virus outbreaks

, 8, 85

VIX

, 142–143, 149–150

Volatility

, 124

spillovers

, 143

Vstoxx

, 130–131

Vulnerability

, 49–50, 55

Word cloud analysis

, 220–221, 235

Word of Mouth (WOM)

, 194–195, 197–198

World Economic Forum

, 175

World Health Organization (WHO)

, 11–13, 22, 59–60, 84, 158, 193

Yellow fever

, 231

Zika virus

, 1–2, 13, 22, 231