American Express Global Business Travel

, 99

Antico Palazzo dei Vescovi

, 156

Assessment of changes in company’s ratings and rankings over time (ARR)

, 221–222

Assessment of Web Convergence (AWC)

, 222

Attitudes

, 216–217

Attributes

, 216–217

Benefits

, 216–217

Big Data

, 82–83

Big Data Analytics (BDA)

, 73–74

Big Five Model

, 34

Brand

, 93

alignment in tourism studies

, 222

associations

, 216

communication

, 226–227

equity

, 216–217

identity

, 214, 216, 218

image

, 216–218

loyalty

, 93

management

, 153

reputation

, 214–215

Brand association coverage (BAC)

, 224–225

Brandsome. fi

, 168

Bridging management via 4. 0 technology

, 114–116

Carlson Wagonlit Travel (CWT)

, 99

Carrying capacity

, 201–202

Case study of museums

, 154

Catastrophic losses

, 113

Cognitive alignment

, 225–226

Cognitive disalignment

, 226

Communication

, 92, 176–177

of spa enterprises on social networks

, 183–185

of spa enterprises on website

, 179–183

Comparison with industry competitors (CIC)

, 221–222

Compass Airlines

, 116–117

Constituent Likelihood Automatic Word Tagging System (CLAWS4)

, 224

Consumer behavior

, 30

shift and impact on online reputation management

, 136–138

Consumer brand associations alignment (CBAA)

, 224–225

emerging effects of combining indicators

, 225–227

Consumer brand associations matching (CBAM)

, 224–225

Consumer brand knowledge

, 216

Consumption

, 6–7

Conversation Prism 5. 0

, 13

Coronavirus pandemic

, 117

Corporate reputation

and effects on companies

, 53–56

of tourism companies

, 58–59

COVID-19

changes in tourists’ behavior

, 133–136

economy impact

, 132–133

pandemic

, 52

pandemic on reading reviews

, 138–145

and tourism

, 132–138

Credibility

, 12–13

Cultural heritage

, 152

Data analysis

, 60, 169

Data collection

, 59–60, 168–169

Data limitations

, 169

Data overview

, 203–204

Decision-making process

, 31

Density of visitors

, 201–202

Destination

, 9

choice

, 118–121

hygiene and safety

, 136

managers

, 73–74

Destination management companies (DMC)

, 94, 99

Determination of publication reach and readership (DPR)

, 221–222

Digital channels

, 52

Digital entrepreneurial ecosystem (DEE)

, 79–80

and dynamic capabilities

, 80–81

Digital marketing

, 112

Digital technology

, 79–80

Digital-based research proposal

, 223–225

Digitalization

, 80–81, 159

Directly via messages (DM)

, 184

Distribution chain, tourism intermediaries and role in

, 94–99

Distribution channels

, 136

Dynamic capabilities theory

, 80–81

Economy and tourism

, 132–133

Electronic word-of-mouth (eWOM)

, 4, 13–14, 29–30, 52, 93, 165, 168

factors influencing contribution of eWOM and motivation

, 41–43

and impact on consumer behavior in tourism

, 34–41

methodology

, 30–31

prevalent characteristics of examined eWOM studies

, 31–34

results

, 31–43

Empowerment

, 76–78

Entrepreneurs

, 78–79

Entrepreneurship

and digital technology

, 79–80

in tourism

, 78–79

European Union Directive (EU Directive)

, 95–96

Evaluations

, 219–221

Expedia

, 32

Facebook

, 100, 168, 183

Fake reviews

, 15

Finland, social media usage in

, 167–168

Finnish DMOs

, 168

Flybe Airlines

, 116–117

Frequency of responses

, 11

Friendly relationship

, 122

Functional quality

, 7

Global Distribution Systems (GDS)

, 97

Google

, 100

Healthcare services

, 122

Hierarchy of Effects model (HOE model)

, 55–56

Holidays

, 95

Horizontal cognitive alignment

, 226

Hospitality

, 112, 115, 164

hospitality 4.0

, 123

social media in

, 164–165

Hotel’s reputation measurement model (HREPM)

, 221–222

Identification of the reputation landscape (IRL)

, 221–222

Image

, 92

Increasing reputational scores (IRS)

, 221–222

Industry 4.0

, 112

adoption of 4.0 technologies

, 122–123

findings

, 118–123

literature review

, 114–117

pre-and post-coronavirus and tourism

, 123–124

research methodology

, 117–118

technologies

, 113

Information Acquisition Model (IAM)

, 34

Information Communication Technologies (ICTs)

, 97, 214

Innovation

, 159

Instagram

, 100, 168, 184

Institut National d’histoire de l’art (INHA)

, 156

Institut national du Patrimoine (INP)

, 156

Intermediaries

companies

, 92

different platforms for reputation from intermediaries’ perspective

, 100–101

roles of intermediaries in online reputation creation in tourism ecosystem

, 101–104

specifics of online reputation management of

, 104–105

Internet

, 77

Internet marketing communication

, 177

data and methods

, 178–179

literature review

, 176–178

results

, 179–189

Interpretivism

, 117

Joint topic/sentiment model (JST model)

, 60

Latent Dirichlet Allocation (LDA)

, 60

Latent semantic analysis

, 60

Length of response

, 11

Linguistic clues

, 14–15

Linked Travel Arrangement

, 95–96

Manipulation strategies

, 14–15

Mass customization

, 115

Mass media

, 6

Media relations

, 6

Meeting/Incentives/Conventions–Congresses/Events–Exhibitions (MICE)

, 99

Metric analysis

, 203–204

Museums

, 152

literature review

, 153–154

management

, 208–209

method

, 154–155

results

, 155–159

Negative online reviews

, 10

Netnography

, 218

Offline brand studies

, 217–218

Online Brand Reputation (OBR)

, 214–216

measurements

, 225–227

in tourism studies

, 219–222

Online corporate reputation

, 56–58

Online evaluations

, 5–6

Online reputation (see also Corporate reputation)

, 165, 214

and empowerment

, 76–78

importance of online reputation in tourism

, 7–9

issues

, 3–7

strategies in online reputation management and factors influencing effectiveness

, 9–15

Online reputation management (ORM)

, 73–76, 93, 112–113, 176, 221

consumer behavior shift and impact on

, 136–138

different platforms for reputation from intermediaries’ perspective

, 100–101

roles of intermediaries in online reputation creation in tourism ecosystem

, 101–104

specifics of online reputation management of intermediaries

, 104–105

technologies and

, 82–83

tools

, 176

tourism companies’ reputation

, 92–94

tourism intermediaries and role in distribution chain

, 94–99

Online reviews

, 10

contributors

, 5–6

Online travel agencies (OTA)

, 52, 97–98

Overcrowding in tourist destinations

, 201–202

Overpopulated destinations, avoidance of

, 136

Overtourism

, 136

Package Travel

, 95–96

Palazzo Buontalenti

, 156

Palazzo de’ Rossi

, 155–156

Palazzo Sozzifanti (see Palazzo Buontalenti)

Participation

, 6–7

Perceived credibility

, 12–13

Perceived quality

, 7

Pistoia Museums

, 154–156

Positive online reviews

, 10

Positive reviews

, 75–76

Post-COVID tourism

, 116–117, 123–124

Pre-COVID tourism

, 116–117, 123–124

Principal Component Analysis (PCA)

, 204

Production

, 6–7

Professional congress organizers (PCO)

, 94, 99

Public relations (PR)

, 6

Reliability

, 121

Reputation

, 4–6, 92–93, 152, 214

management

, 74–75, 92–93, 153

strategies and tools to improve

, 156–159

Reputators

, 215–216

Retweet (RT)

, 199

Review of ranking methodologies (RRM)

, 221–222

Reviews

, 29–30, 179, 183, 219, 221

Risk management

, 134

San Salvatore Church of 979

, 156

Sentiment analysis

, 198–199

Sentiment analysis scores (SAS)

, 203–204

Service delivery

, 134–135

Service quality

, 7

Shelter-in-place orders

, 116–117

Slovakia, importance and management of reviews in online reputation of selected spa enterprises in

, 185–189

Small museums (SMs)

, 152–154

platforms

, 154

Snapchat

, 168

Social distance rules

, 116–117

Social listening

, 7

Social media

, 6–7, 164, 214–215

companies

, 93

issues of social media use in travel planning process

, 166

marketing

, 165

research design

, 168–169

research findings

, 169–171

tools

, 13

in tourism and hospitality

, 164–165

usage in Finland

, 167–168

Spa tourism enterprises

, 176–178

Spearman correlation coefficient

, 139

Speed of responses

, 11

Strategic planning

, 121–122

Technical quality

, 7

Thematic analysis

, 118

Tour operators

, 95–97

Tourism

, 73

entrepreneurship in

, 78–79

flow management

, 200

implication, limitation, and suggestion for future research

, 84

importance of online reputation in

, 7–9

intermediaries and role in distribution chain

, 94–99

online reputation and empowerment

, 76–78

online reputation management

, 75–76

reputation management

, 74–75

social media in

, 164–165

Tourism 4.0 technologies

, 123

Tourism academics

, 202

Tourism businesses

, 81

Tourism companies reputation

, 92–94

aim and methodology

, 94

Tourism destination

, 29–31, 112

managers

, 83

Tourist pressure

, 198

influence of tourism pressure on online reputation of destinations

, 200–201

Tourists-based proximity preferences

, 114

Tourists’ behavior, changes in

, 133–136

Trans States Airlines

, 116–117

Transportation patterns

, 135

Travel

, 95

agent/agency

, 98

decision process

, 166

issues of social media use in travel planning process

, 166

restrictions

, 116–117

Travel management company (TMC)

, 95, 99

Travelers’ behavior

, 52

findings

, 60–64

limitations and future research

, 66–67

managerial implications

, 66

methodology

, 59–60

research questions

, 59

theoretical background

, 53–59

theoretical contribution

, 65–66

TripAdvisor

, 14–15, 32, 93, 100–103

Twitter

, 199

Twitter Vigilance tool

, 203–204

Uffizi Gallery

, 198

data overview and metric analysis

, 203–204

literature review and hypotheses development

, 200–203

verification of hypotheses

, 204–208

User-generated content (UGC)

, 6–7, 13, 56–57, 75, 165, 198–199, 217–218

initiatives

, 77

Vertical cognitive alignment

, 226

Virgin Airlines

, 116–117

Visitor satisfaction and destinations’ online reputations

, 202–203

Visitors engagement

, 152

Web 2.0 technology

, 5–6, 75–76

Word-of-mouth (WOM)

, 4–5, 55–56, 214–215

Xenophobia

, 116–117

Yelp

, 32, 93

You-Tube

, 168, 184–185