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This study examines articles related to tourist decision making, especially with respect to cognitive biases, published in the Journal of Travel Research, Annals of Tourism Research, and Tourism Management over the past 10 years (from January 2008 to September 2018). Tourists do not always make rational choices due to the influence of behavioral factors, such as dispositions and emotions. According to the study of judgment and decision making, cognitive biases are the main underlying causes of suboptimal decisions. Through a systematic analysis, this study reveals the prevalence and influence of common biases at different stages of travel, such as pre-trip, on-site, and post-trip. This study also summarizes implications for tourism management and proposes areas of potential research contributions.
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A Systematic Review of Cognitive Biases in Tourist Decisions 1
A research paper submitted to 2
Tourism Management Journal 3
4
Walanchalee Wattanacharoensil *
5
6
Tourism and Hospitality Management Division, 7
Mahidol University International College 8
999 Bhuthamonthon Sai 4, Salaya, Nakhon Pathom, Thailand 73170 9
Phone: (66) 2700 5000 Ext. 4416 10
E-mail: walanchale.wat@mahidol.ac.th 11
12
Dolchai La-ornual 13
Business Administration Division, 14
Mahidol University International College 15
999 Bhuthamonthon Sai 4, Salaya, Nakhon Pathom, Thailand 73170 16
Phone: (66) 2700 5000 Ext. 4448 17
E-mail: dolchai.lar@mahidol.ac.th 18
19
20
*Corresponding Author 21
___________________________________________________________________________ 22
This version of the submitted review paper is for consideration of Tourism Management Journal 23
The paper is accepted in June 2019 24
25
26
27
28
A Systematic Review of Cognitive Biases in Tourist Decisions 29
Abstract 30
This study examines articles related to tourist decision making, especially with respect to cognitive 31
biases, published in the Journal of Travel Research, Annals of Tourism Research, and Tourism 32
Management over the past 10 years (from January 2008 to September 2018). Tourists do not always 33
make rational choices due to the influence of behavioral factors, such as dispositions and emotions. 34
According to the study of judgment and decision making, cognitive biases are the main underlying 35
causes of suboptimal decisions. Through a systematic analysis, this study reveals the prevalence and 36
influence of common biases at different stages of travel, such as pre-trip, on-site, and post-trip. This 37
study also summarizes implications for tourism management and proposes areas of potential research 38
contributions. 39
Keywords: cognitive biases, decision making, tourists 40
1. Introduction 41
Tourist decision making has been a popular research topic in the past decade (Sirakaya & Woodside, 42
2005; Decrop & Kozak, 2009; Smallman & Moore, 2010). People make various choices in their 43
journeys, from trip preparation to their return. Accordingly, previous research has attempted to 44
explain, predict, and understand the tourist decision-making process. 45
Most relevant studies are based on the traditional economic discipline (i.e., utility theory), which 46
assumes that tourists maximize their satisfaction in making travel decisions by selecting the best 47
alternative. Under this view, people often base their decisions on rationality, logic, and complex 48
reasoning (McCabe, Li, & Chen, 2016; Gretzel, 2011; Pearce & Packer, 2013). Other studies explain 49
tourist decisions through psychological theories, such as the theory of planned behavior, which 50
hypothesizes that a person acts through reasoning (Fishbein & Ajzen, 1975, as cited in McCabe, Li, 51
& Chen, 2016), and rational choice theory, which postulates that choices are hierarchically selected 52
until the final decision is derived (Hauser & Wernerfelt, 1990; Howard & Sheth, 1969; Roberts & 53
Lattin, 1991, as cited in Vermeulen & Seegers, 2009). Tourist decisions are presumed to rely on 54
cognitive processing, and comprehensive decision-making process occurs before the final purchase 55
(McCabe et al., 2016). 56
These perceptions have been dominating tourist decision-making research for many years (Gretzel, 57
2011; McCabe et al., 2016). Tourist approaches provide insights into the process through the input-58
output or causal mechanism (where decision outcomes or purchase intentions are the results of 59
various input attributes). New claims have also been emerging in recent years, positing that 60
traditional theories neglect affective or emotional factors, intuitive reasoning, adaptive characters, 61
and spontaneous acts (Decrop, 2010). These issues influence actual decisions and should not be 62
omitted from the analysis of tourist decision-making process. 63
Tourists, as humans, can be irrational decision-makers. Various travel products and services require 64
travelers to commit to advance purchases for future consumption, which can further affect the 65
optimality of tourist decisions. Time delays influence how tourists construe decisions (Trope & 66
Liberman, 2010) and perceive decision attributes. Human cognitive limitations also make tourists 67
emotional and subjective (Gladwell, 2005; Bazerman & Moore, 2009). Thus, systematic decision-68
making deviations from rationality may arise (Albar & Jetter, 2009), leading to poor consumer 69
choices. These findings illustrate that tourist decisions are more complex than original thoughts. 70
Recent literature reports that tourists have a limited memory that may impede their decision-making 71
process. During searches, they are exposed to massive information that can cause cognitive overload
72
(Park & Nicolau, 2015). These limitations can drive tourists to rely more on trust and intuitive 73
perceptions than on logical reasoning (Correia, Kozak, & Tao, 2014). 74
Research on cognitive biases in tourist decisions is arguably still in its infancy. Despite various studies 75
on decision making in the tourism context, incidents and prognoses of cognitive biases with regard to 76
their types and stages where they arise are still abstruse. To ameliorate this situation, a systematic 77
investigation is necessary. The present study focuses on the most frequent bias types and the stages in 78
which cognitive biases occur. The authors review relevant articles in three forefront tourism journals 79
published within 10 years from January 2008 to September 2018. The Journal of Travel Research 80
(JTR), Annals of Tourism Research (ATR), and Tourism Management (TM) are the top three leading 81
tourism journals according to the Web of Science’s Journal Impact Factor (JTR: 4.564, ATR: 3.194, 82
and TM: 4.707), posing influential roles in tourism knowledge. 83
This study aims to answer the following questions. 84
1) Based on the current stage of literature on cognitive biases in key tourism literature, what are the 85
general characteristics of the existing articles? 86
2) What are the most frequent bias types found in the tourist decision-making context? 87
3) How can cognitive biases occur in different tourism stages, starting from destination choice to 88
post-visit experience? 89
This paper is organized in the following manner. Section 2 discusses the background literature 90
regarding decision making and cognitive biases. Section 3 provides the methodology of the review 91
process. Sections 4, 5 and 6 present the findings and discussions regarding the types and stages that 92
cognitive biases manifest in tourism literature. Section 7 concludes with a summary of implications on 93
tourism management and potential future research areas. 94
2. Background literature 95
2.1 Normative, descriptive, and prescriptive decision making 96
Decision science is an academic field that can be classified into the study of normative, descriptive, 97
and prescriptive decisions (Steele & Orri, 2015). Normative decision-making studies indicate how 98
people should decide to maximize their objectives. This is close to that of game theory in economics, 99
which focuses on the interactions between agents and the best action that each one takes (Myerson, 100
1991). By contrast, descriptive decision making is concerned with how people make decisions, which 101
may deviate from norms of optimality or rationality (MacCrimmon, 1968; Slovic, Fischhoff, & 102
Lichtenstein, 1977). As a consequence of the discrepancy of normative and descriptive decisions, 103
prescriptive decision making relates to practical applications of “nudging” people to make good 104
decisions. The interactions among normative, descriptive, and prescriptive decision making, 105
especially through experimental findings, have led to a good understanding of human decision-making 106
processes (Anand, 1993; Keren & Wagenaar, 1985). Most tourism studies examine issues related to 107
descriptive or behavioral decision making, i.e. how tourists decide from available or given choices. 108
Among normative, descriptive, and prescriptive areas of decision science, the most extensively 109
researched category is decision under uncertainty, which is founded on mathematical and statistical 110
concepts of probability. In this paradigm, people must commit to an action before an outcome is 111
realized. For example, people must decide how many shares of a particular stock to buy, which may 112
eventually result in either a profit or a loss. In decision under uncertainty, calculating the expected 113
value to evaluate such a prospect is traditionally accepted in the field of economics and finance 114
(Schoemaker, 1982). Many theoretical studies focus on this area, especially from a normative 115
perspective. For example, Neumann and Morgenstern (1953) axiomatized the influential model of 116
expected utility. However, descriptive-oriented studies have indicated that people do not always 117
behave rationally. The most prominent works are by Maurice Allais (1953) and Daniel Ellsberg 118
(1961) who proposed the paradoxes or decisions which violate normative assumptions. In addition, 119
prospect theory (Kahneman & Tversky, 1979) is widely accepted as a plausible model of descriptive 120
choice. 121
Another widely investigated category is that of intertemporal choices or decisions that involve the 122
element of time (Frederick & Loewenstein, 2002). A typical situation is when people decide between 123
two alternative prospects with varying time delays, such as to spend a particular amount of earnings 124
today or to save and consume it (with interest) in the future. Decision uncertainty and intertemporal 125
choice are applicable to tourism because many products and services require payment before the 126
actual consumption, such as airplane flights. In addition, tourists often report varying experiences for 127
the same products and services, such as hotel stays. 128
2.2 Bounded rationality, heuristics, and tourist decision making 129
Literature on decision making, including that related to tourism, has traditionally developed with a 130
strong linkage to economics, thus these studies are often based on the rational choice paradigm. In this 131
setting, classical (expected) utility theory (von Neumann & Morgenstern, 1947, as cited in Thaler, 132
2015) is used to explain tourist decision making (Albar & Jetter, 2009; Decrop, 2010; Pearce & 133
Packer, 2010; Gretzel, 2011). Existing tourism studies on this topic assume that tourists make rational 134
decisions following a logic of reasons and order (Sirakaya & Woodside, 2005). Goldstein (2011, as 135
cited in Pearce and Packer, 2013) found that the nature of decision making and its process is 136
considerably affected by the presentation of problems. Tourists are not always rational and can make 137
biased decisions. Irrational decisions occur when tourists violate the principles of rationality and 138
select options that do not reflect their true preferences (Brown, 2007). Keys and Schwartz (2007) 139
revealed the three principles of rationality: i) dominance (the option that never results in an outcome 140
worse than others should be the preferred option), ii) variance (information should be understood and 141
must weigh the same regardless of its presentation), and iii) sunk cost (irreversible consequences 142
should be ignored when making considerations for the future). 143
Simon (1972) introduced the “bounded rationality” concept, which states that although an individual 144
makes a rational choice, (s)he may lack important information that can help define a problem or 145
determine a relevant criterion. Time and cost constraints likewise limit the quantity and quality of 146
available information. These factors explain why an individual cannot always assume a fully rational 147
model because his/her rationality is bounded by cognitive limitation (Bazerman & Moore, 2009; 148
Thaler, 2015). 149
In addition, individuals must deal with a tremendous amount of available information. Heuristics or 150
mental shortcuts may be employed to save time but can cause cognitive biases (Tversky & Kahneman, 151
1974). Payne, Bettman, and Johnson (1993) discovered that decision makers must normally find rules, 152
which are adaptively based on a given situation (e.g., time pressure or the number of available 153
options). However, heuristics do not always lead to undesirable results. Certain types such as 154
elimination by aspects (Tversky, 1972), allow individuals to make choices on the basis of systematic 155
reduction. In this case, people base their decisions on the most desirable attributes to reduce the 156
complexity in decision making. Such heuristics can become functional, especially when they yield 157
consistent choices. Effective heuristics can be established by determining the degree to which 158
achieving a predetermined objective is allowed (Merlo, Lukas, & Whitwell, 2008). 159
To conclude, irrational decisions are a result of the limited ability of humans to arrive at the optimal 160
solution, which may be caused by time and cost constraints, limited cognitive capacity, and 161
incomplete or overloaded information. People cannot often maximize the utility of all possible choices 162
(Cahyanto et al., 2016). Instead, individuals make good decisions that are good enough, rather than 163
optimal (Simon, 1957, as cited in Smallman & Moore, 2010; Bazerman & Moore, 2015). Such 164
situations are common in tourism, especially regarding tourist decisions. For example, in choosing 165
places to visit, most tourists cannot afford the time and effort to evaluate the details of all possible 166
alternatives without resorting to certain heuristics. 167
3. Methodology 168
This study systematically reviewed all articles on tourist decision making that were published in JTR, 169
ATR, and TM between January 2008 and September 2018. Two main processes were performed 170
before the systematic review, namely, article collection and article screening. 171
3.1 Article collection 172
In the initial step, different sets of keywords were used to identify articles on cognitive biases in 173
tourist decisions. After several attempts, the two authors agreed upon the set of {tourist, traveler, 174
“decision making,” cognitive, bias}. 175
The three journals yielded 269 articles (148, 27, and 94 articles in JTR, ATR, and TM, respectively). 176
The articles were then collected and recorded in a spreadsheet to facilitate categorization and prepare 177
for data screening. Information regarding article titles, authors, year, affiliations, countries, and 178
abstracts was also noted. 179
3.2 Article screening 180
All of the 269 articles were screened through two parallel actions: 1) examining the abstract of each 181
article and 2) inspecting the context surrounding each of the specified keywords in the body of each 182
article. This process confirmed whether the article is related to cognitive biases in tourist decisions. 183
During the screening process, the two researchers agreed upon the evaluative judgment by assigning 184
each article to one of the following categories. 185
Category 1: articles in which at least one cognitive bias type(s) is explicitly stated within the 186
body. 187
Category 2: articles that can be inferred as related to cognitive biases but specify no bias type. 188
Category 3: articles that are not related to cognitive biases in tourist decisions. 189
In this study, only Category 1 was selected for the main analysis. The 269 articles were reviewed and 190
coded, and the results were jointly cross-checked to confirm the categorization. The inter-coding 191
reliability between the two researchers was 85%. Articles that received different codes, particularly 1 192
versus 2 and 1 versus 3, were further discussed and investigated before confirming their 193
categorization. The last step was a reference search, and a total of 37 articles were selected for the 194
review. 195
196
197
Figure 1. Article selection and screening 198
4. Preliminary analysis 199
The past 10 years, from January 2008 to September 2018, has seen an increase in the number of 200
studies on cognitive biases in tourist decisions, especially between 2016 and 2018. For each journal, 201
the number of articles rose from zero to three papers each year between 2008 and 2015 to five to nine 202
papers between 2016 and 2018. Among the 37 articles, 14, 6, and 17 papers were published in JTR, 203
ATR, and TR, respectively (See Table 1). In addition, cognitive biases assumed a central role in 23 204
papers and a supporting role in the remaining 14 papers. (A central role means that a cognitive bias 205
type is one of the key topics in the study, whereas a supporting role means that a bias is used for 206
explanatory purpose.). See Table 2. 207
208
Table 1. Article distribution in JTR, ATR, and TR from 2008 to 2018 209
Year
JTR
ATR
TM
Total
Accumulated
Total
2008
0
0
2009
1
1
2
2
2010
1
1
2
4
2011
1
1
5
2012
3
3
8
2013
1
1
2
10
2014
1
1
11
2015
1
1
1
3
14
2016
2
2
5
9
23
2017
0
1
4
5
28
2018
6
1
2
9
37
Total
14
6
17
37
210
Table 2. Roles of cognitive bias in the selected studies 211
212
The 37 selected studies applied three types of research methods. Thirty-four papers adopted a 213
quantitative analysis, two were conceptual reviews, and one performed a qualitative analysis. For 214
articles in which cognitive bias posed a central role, only the quantitative method was used. Among 215
the 34 quantitative studies, the experimental design was the most frequently used method (13 articles, 216
56.5%), followed by surveys using questionnaires (6 articles, 26.1%). The prevalence of experimental 217
design is in line with the nature of cognitive bias studies in the field of judgment and decision making. 218
Furthermore, the quantitative studies performed common statistical analyses, including structural 219
equation modeling, regression analysis, t-test, and ANOVA. 220
Table 3. Research methods employed in the selected studies 221
Methods All
articles
Cognitive bias as a
central
role
Percentage
(only articles with
central role)
Quantitative analysis
The analysis of the quantitative survey (not the
experiment)
9
6
26.1%
Mathematical equation
4
3
13%
Experimental design
17
13
56.5%
Quantitative analysis on textual data
4
1
4.3%
Qualitative analysis
Discourse analysis
1
Review article
Conceptual review
2
37
23
100%
222
Table 4. Studies by regions and countries 223
Total studies by
region
North America
Europe
The Middle
East
Africa
Asia
Oceania
n=57
n = 22
n = 11
n=1
n=3
n=12
n=8
(100%)
(39%)
(19%)
(2%)
(5%)
(21%)
(14%)
Countries
The United States
(21)
The United
Kingdom (4)
Israel (1)
South
Africa
(3)
People
Republic of
China (5)
Australia (5)
Canada (1)
Norway (2)
Spain (2)
Republic of
China (3)
New Zealand
(3)
Greece (1)
Hong Kong
SAR (2)
Roles of cognitive biases
JTR
ATR
TM
Sum
Cognitive biases as a central role of the study
11
3
9
23
Cognitive biases as a supporting role of the study
3
3
8
14
Total
14
6
17
37
Switzerland (1)
Russia (1)
Republic of
Korea (2)
224
The 37 selected articles classified by regions and countries reveal that research related to cognitive 225
biases in tourist decisions has been conducted across the globe. Most studies were from North 226
America (39%), followed by Asia (21%) and Europe (19%). North American and Asian papers have 227
predominantly used quantitative research methods (mainly experimental design and questionnaire 228
survey). By contrast, studies in the European continent, mainly from Spain and the United Kingdom, 229
have employed mathematical modeling (See Table 4). 230
Moreover, from the selected 37 articles, 24 cognitive biases were observed with different frequencies. 231
The highest frequency was heuristics, which appeared in six articles (12.24%), followed by social 232
bias and stereotype in five articles (10.2%). Framing effect and cognitive dissonance each appeared in 233
four articles (8.16%). In addition, anchoring and negativity bias were each referred to in three articles 234
(6.12%). Six of the bias types were mentioned in two articles (4.08%), and 12 of the bias types 235
appeared in one article (2.04%). See Table 5 below. 236
Table 5. Distribution of bias in the selected articles 237
No.
Bias types
Number
Percentage
1
Heuristics
6
12.24
2
Social bias and stereotype
5
10.20
3
Framing effect
4
8.16
4
Cognitive dissonance
4
8.16
5
Anchoring
3
6.12
6
Negativity bias
3
6.12
7
Loss aversion
2
4.08
8
Positivity bias
2
4.08
9
Primacy effect
2
4.08
10
Bias on memory (Recall bias)
2
4.08
11
Time perspective bias
2
4.08
12
Confirmation bias
2
4.08
13
Halo effect
1
2.04
14
Cognitive miser
1
2.04
15 Decoy effect 1 2.04
16
Priming effect
1
2.04
17
Impact bias
1
2.04
18
Subconscious bias
1
2.04
19
Cognitive bias (no specific)
1
2.04
20
Sunk cost effect
1
2.04
21
Present bias
1
2.04
22
Availability bias
1
2.04
23
Conjunction fallacy
1
2.04
24
Scope insensitivity
1
2.04
Total biases
49
100.00
238
Table 6. Detail explanation of each bias type 239
Bias types
Bias explanations
Selected article
Heuristics ... or rules of thumb, are the cognitive tools we use to simplify the decision making process
(Bazerman & Moore, 2009)
Tanford & Kim (2018); Tanford, Choi and Joe
(2018); Park & Nicolau (2015); Castelltort, &
Mader (2010); Xiang, Du, Ma, & Fan (2017);
Tan, Lv, Lui, & Gusoy (2018)
Social bias
…prejudicial attitudes toward particular groups, races, sexes, or religions, including the
conscious or unconscious expression of these attitudes in writing, speaking, etc. Stepchenkova & Shichkova (2018); Gkritzall,
Gritzalls, & Stavrou (2018)
Stereotype .. when a person has certain characteristics about another person, thing or place without
having actual information
Chen, Lin, & Petrick (2013); Castelltort, &
Mader (2010); Berdychevsky, Gibson, & Bell
(2016)
Framing effect …the situation when choices being made are influenced by the way they are framed.
Framing effect occurs when changing perspective influences evaluation of outcomes
Tanford, Choi and Joe (2018); Sparks &
Browning (2011); Kapuscinski, & Richards
(2016); Zhang et al. (2018)
Cognitive
dissonance
...
the situations when attitudes, beliefs or behaviours of a person are not aligned and could
create conflict and he or she can react in the irrational way in order to maintain the
consonance (McLeod, 2018).
Tanford & Montgomery (2015); Park and Jang
(2013); Park and Jang (2014); Tseng (2017)
Anchoring …the tendency to anchor a decision at an initial value and fail to adjust sufficiently to reach
the true value
Book, Tanford, & Chen (2016); Tanford, Choi,
& Joe (2018); Higham, Ellis, & Maclaurin
(2018);
Negativity bias
...
things of a more negative nature have a greater effect on one's psychological state and
processes than neutral or positive things
Tanford & Kim (2018); Park & Nicolau (2015);
Zhang, Zhang, & Yang (2016)
Loss aversion
…changes from reference points may be valued differently depending on whether they are
gains or losses and people tend to avoid potential loss and leading them to make irrational
decision
Nicolau (2012); Nguyen (2016)
Positivity bias
…a pervasive tendency for people, especially those with high self-esteem, to rate positive
traits as being more true
Ouyang, Gursoy, & Sharma (2017); Xiang, Du,
Ma, & Fan (2017)
Primacy effect
… recalling or seeing primary (last) information presented better than information presented
later on (before)
Ert & Fleischer (2016); Sparks & Browning
(2011)
Bias on memory
(Recall bias)
… bias which occurred when people remember past events that easily spring out into their
memories but don’t usually have a complete or accurate picture of what happened
Lee & Kyle (2012); Smith et al. (2015)
Time perspective
bias
…refers to the relative focus and valence a person assigns to past, present, and future time
frames.
Kah, Lee, & Lee (2016); Lu et al. (2016b)
Confirmation
bias
…the tendency to interpret new evidence as confirmation of one's existing beliefs or
theories.
Chi, Ouyang, & Xu (2018);
Higham, Ellis, & Maclaurin (2018)
Halo effect
… when a person making an initial evaluation of another person, place, or thing based on
the assumption of ambiguous information
Kneesel, Baloglu, & Millar (2010)
Cognitive miser
… a social psychology theory that suggests that humans, valuing their mental processing
resources, find different ways to save time and effort when negotiating the social world
Tanford, Baloglu, & Erdem (2012)
Decoy effect
…(or attraction effect) is the phenomenon that consumers will tend to have a specific
change in preference between two options when they are presented with a third option that
is asymmetrically dominated
Kim, Kim, Lee, Kim, & Hyde (2018)
Priming effect
…how ideas prompt other ideas later on without an individual’s conscious awareness
Thai &Yuksel (2017)
Impact bias
…tendency that people overestimate the intensity and duration of their emotional reactions
to future
events
Larsen, Brun, & Ogaard, (2009)
Subconscious bias
…while individuals are likely to respond better to human cues, they are unlikely to be aware
of what has occurred, or why they feel more favorable towards the message they have just
seen
Letheren, Martin, & Jin (2017)
Cognitive bias
a systematic pattern of deviation from norm or rationality in judgment
Tan, Lv, Lui, & Gusoy (2018)
Sunk cost effect
…when a person is more likely to continue with a project if he or she has already invested a
lot of money, time, or effort in it, even when continuing is not the best thing to do
Park and Jang (2014)
Present bias
…tendency of people to give stronger weight to payoffs that are close to present time when
considering trade-offs between two future moments.
Nguyen (2016)
Availability bias
…the estimation of frequency or probability by the ease with which instances or
associations could be brought to mind.
Higham, Ellis, & Maclaurin (2018)
Probabilistic
reasoning and
conjunction
fallacy
…individuals exhibit a bias toward overestimating the probability of conjunctive events and
underestimating the probability of disjunctive events Higham, Ellis, & Maclaurin (2018)
Scope
insensitivity
…the amount that a person is willing to pay for purchasing moral satisfaction (e.g.
donation) is relatively insensitive to the actual nature and extent of harm to be ameliorated
Higham, Ellis, & Maclaurin (2018)
240
241
Sources [excluding the selected articles]: Bazerman and Moore (2009); Haselton, Nettle & Andrews(2005); Heshmart (2015); Huber, Payne, and Puto(1982); 242
McLeod (2018); Oxford Reference (2018, 2019); O'Donoghue & Rabin (1999); Tversky and Kahneman (1973); Tversky and Kahneman (1974); Tversky and 243
Kahneman (1981); Social bias (n.d.); Wilson & Gilbert (2005); World Heritage Encyclopedia (2019); Zimbardo & Boyd (1999). 244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
5. Keywords frequently related to the most common cognitive biases 259
Frequent keywords related to the most common types of cognitive biases were examined. 260
Specifically, the qualitative analysis tool of the NVivo 11 software was employed to identify the 261
word influence via word cloud, a visual tool to indicate dominant keywords. Figures 2 and 3 262
illustrate the four most commonly found biases, namely, [A] heuristic, [B] social bias and 263
stereotype, [C] framing effect, and [D] cognitive dissonance. The biases are likewise explained in 264
relation to the related keywords in the figure. 265
266
267
268
269
270
271
272
273
274
275
Figure 2. Word clouds of keywords on [A] heuristic and [B] social bias and stereotype 276
Heuristics, or mental shortcuts, are simple principles that enable individuals to decide and assess 277
values efficiently under uncertain and intricate conditions (Tversky & Kahneman, 1974). 278
Heuristics can cause cognitive bias when the application of automatic mental processing leads to 279
inconsistent choices (Brown, 2007). Derived from keywords found in the literature, possible 280
heuristic cues can help tourists make decisions but also distort rational decisions. The predominant 281
keywords related to heuristics are “destination image” (see Article 22 from Appendix 1) and 282
“online reviews” [11, 16, 35, and 37]. Online reviews are valuable information sources that affect 283
customer pre-purchase evaluations and decisions (Book et al., 2016). However, the reviews pose as 284
heuristics because their valences (positive or negative) enable tourists to decide quickly. Negative 285
reviews are expected to activate heuristic processing as voicing unfavorable attitudes can attract 286
attention (Kanouse & Hanson, 1987). “Destination image” is another heuristic cue for destination 287
choice. When faced with several destinations, tourists can reduce the number of considerations or 288
available choices due to the limitation of their cognitive ability (Miller, 1956, as cited in Decrop, 289
2010). The perception toward a destination image helps tourists reduce destination choices in the 290
available set. 291
Social bias and stereotype is a common bias in tourism that occurs from prejudicial attitudes 292
toward certain groups or races. The keywords related to these cognitive bias types surround the 293
ideas of “destination image” [5, 12, 22], “gender in tourism” [29], “advertising” [10, 29], and 294
“country or national conflicts” [10]. A message derived from advertising can form a stereotype 295
toward a destination image. Moreover, country or national conflicts may lead to an unfavorable 296
image of a country in conflict. Stereotype also applies to the role of gender (male versus female), 297
such as perceptions on solo female travelers. 298
299
Figure 3. Word clouds of keywords [C] framing effect and [D] cognitive dissonance 300
Framing effect refers to the situation when choices being made are influenced by their manner of 301
presentation (Tversky & Kahneman, 1981). The keywords related to the framing effect in tourism 302
studies are “price anchoring” [13], “online review” [23], “media” [28], and “destination image” 303
[36]. 304
Tanford, Choi, and Joe (2018) [13] argued that framing principles can explain the influence of 305
tourist budget on price evaluations. Perceived high or low budget framing may influence how 306
people view hotel pricing strategies and may affect purchase decisions (Wu & Cheng, 2011). 307
Review framing (what is read first: positive or negative review) can influence consumer choice. 308
Sparks and Browning (2011) [23] found that positively framed reviews result in a more favorable 309
booking intention than negatively framed reviews. Moreover, news media can frame audience 310
perception on destination risk [28] and how destination image is perceived [38]. The “gain-framed 311
condition” (97% of the visitors are satisfied when visiting a destination) receives a higher image 312
perception than the “loss-framed condition” (only 3% of the visitors are dissatisfied when visiting 313
a destination). This factor provides an important implication on how the advertising message about 314
a destination can be framed to attract the interest and trust of tourists. 315
Cognitive dissonance refers to the situation when people’s attitudes, beliefs, or behaviors are not 316
aligned and create conflicts in a way that such people react irrationally to maintain consonance. 317
When people encounter cognitive dissonance, they react in one of the following three ways: 1) 318
change beliefs; 2) change actions; and 3) change perceptions of action (rationalize the action). The 319
last option can lead to irrational decision making when people reconcile their conflicting beliefs 320
(Investopedia, 2018). 321
The keywords that are most related to cognitive dissonance revolve in the concepts of “social 322
influence” [6], “perceived regret” [24], “seller rating” [32], and “sunk-cost effect” [25]. In the 323
tourism context, cognitive dissonance occurs when individuals’ purchase decision is affected by 324
factors that lead to distortion or regret in their decision choice. These factors include the social 325
influence on the selected choice or from several available choices. Regret can arise when 326
customers consider the favorable qualities of the options they did not choose, causing dissonance 327
(Festinger, 1957, as cited in Landmark, 1987). For example, article [32] investigated how seller 328
ratings can reduce post-purchase regret. 329
As previously discussed, the context surrounding the four most common cognitive bias types 330
varies. The next section further scrutinizes all of the bias types with respect to their manifestations 331
in different tourism stages. 332
6. Cognitive biases with respect to different tourism stages 333
Within the selected 37 articles, different types of cognitive biases occur in distinct tourism stages, 334
namely, [1] pre-trip, [2] on-site, and [3] post-trip. In this study, [1] is classified into three sub-stages: 335
[1.1] evaluating destination choice, [1.2] evaluating tourism product rating, and [1.3] evaluating 336
tourism product choice. 337
Six types of cognitive biases occur during [1.1] and appear in nine articles (18.4%). Five cognitive 338
bias types occur during [1.2], appearing in nine articles (18.4%). The largest number of bias types, 339
nine, is recorded in [1.3] and appear in 14 articles (32.7%). Two bias types are found in [2], appearing 340
in two articles and accounting for 4.1%. Only one bias type exists in the two articles for [3], 341
accounting for 4.1%. The last categories [4], which refer to the tourism articles in which the travel 342
stage cannot be identified, comprise 10 types of bias in six articles, accounting for 22.5%. 343
Each stage is elaborated in the next section. The details of the key bias types observed in the three 344
tourism stages and three sub-stages are illustrated in Figures 4 and 5. 345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
Figure 4. Types of cognitive bias found in each stage of the selected articles (the number in brackets 361
[] indicates the number of articles) 362
363
Figure 5. Cognitive biases in each tourism stage 364
6.1 Pre-trip experience 365
6.1.1 Destination choice 366
Tourist decision making on a destination choice relies on choice set theory, which is borrowed from 367
marketing and consumer behavior disciplines (Hastak & Mitra, 1996; Howard, 1977). At this stage, 368
tourists apply a mental process and consider possible places to travel. Certain rules can be applied so 369
that tourists can make certain comparisons and work out their preference order among alternatives (Li, 370
McCabe, & Song, 2017). Choice set theory proposes that several destinations are included in the 371
consideration (or evoked) set before the final choice is made (Decrop, 2010). 372
At the stage of destination selection, six types of cognitive biases are observed to affect the destination 373
choice. The key bias types are heuristics, halo effect, framing effect, stereotype, social bias, and 374
subconscious bias. 375
In this stage, destination image is the key variable that is often addressed as a heuristic cue (mental 376
shortcut) before tourists make a final decision. Destination image can be influenced by many factors, 377
from news media to marketing promotional campaigns. The perception of destination image through 378
news media or advertising likewise links to framing effect. This bias can arise from watching news 379
and seeing promotional materials. The framing of media context (e.g., positively, negatively, or 380
neutral) can affect how tourists perceive a destination (Kapuscinski & Richards, 2016; Zhang et al., 381
2018). Halo effect refers to character judgments of an object that can be influenced by its overall 382
impression. Such an effect is another bias type that is likewise found at this stage. Tourists pose a 383
positive judgment toward a destination because they have a positive view, resulting from the 384
positively framed marketing. Thus, such marketing affects the final judgment of how tourists perceive 385
a destination choice (Kneesel, Baloglu, & Millar, 2010). 386
International tourist perception toward a destination is likewise influenced by social bias and 387
stereotype, referring to the positive and negative tourist perceptions about the destination. Chen, Lin, 388
and Patrick (2012) explained that tourists can have a negative stereotype if their home country has a 389
record of conflict with other countries, resulting in the formation of a negatively biased country and 390
destination image. This negative stereotype is similarly witnessed when the destination country is 391
viewed as the out-group on the basis of the constant political, economic, diplomatic, or military 392
conflicts (Stepchenkova & Shichkova, 2019). 393
Moreover, subconscious bias occurs when people respond to the marketing communication message 394
of a destination or to human cues without knowing the reasons. Letheren, Martin, and Jin (2017) 395
reported that people with high anthropomorphic tendency (tendency to humanize non-human 396
agents/objects) can develop a positive destination attitude when exposed to a personified 397
advertisement, rather than a concrete or plain text. 398
These biases can result in the distorted image perception of a destination. Destination image acts as a 399
heuristic clue and plays a crucial role in destination choice (Fu, Yeh, and Xiang, 2016). Therefore, 400
such biases affect tourist perceptions toward a destination. With its likely inclusion in the 401
consideration choice (or evoked) set, the destination is therefore involved in the final choice. 402
6.1.2 Tourism product rating 403
After destination choice, tourists further search for information related to tourism product choices, 404
such as accommodations, flights, or destination packages. A growing reliance on the Internet, an 405
information source for decision making, is witnessed in the digital era (Sparks & Browning, 2011). As 406
a result, tourists are bombarded with online information when making purchase decisions (Book, 407
Tanford, & Chen, 2015). Therefore, online reviews and/or ratings are often consulted to enhance 408
confidence before making decisions. Online reviews and ratings have a powerful influence on 409
consumer purchase decisions (Sparks & Browning, 2011; Tanford & Kim, 2018). At this stage, 410
cognitive biases can arise while assessing such information. The key bias types involved in this stage 411
are heuristic, negativity bias, positivity bias, framing effect, and primacy effect. 412
Online ratings and reviews are considered heuristic cues that enable tourists to form quick judgments 413
on available choices before making decisions (Tanford & Kim, 2018). Negativity bias occurs when 414
tourists consult reviews displayed on user-generated content websites before making choices, 415
especially in product-judgment contexts (Maheswaran & Sternthal, 1990). Accordingly, a negative 416
input has a greater effect on attitudinal and behavioral expressions than a positive input (Cacioppo & 417
Bernston, 1994). Moreover, negative reviews present greater impact than positive reviews (Book, 418
Tanford, & Chen, 2015; Chen & Lurie, 2013; Park and Nicolau, 2015; Tanford & Kim, 2018). These 419
factors support the study of Ito, Larsen, Smith, and Cacioppo (1998), who argued that negative bias 420
largely occurs during information and choice evaluation. On the contrary, negative cues evoke an 421
emotional reaction, causing people to weigh them more heavily than positive cues (Taylor, 1991). 422
423
Framing effect can occur when travelers read review information. Sparks and Browning (2011) 424
claimed that framing reviews (negative or positive information) can influence tourist destination 425
choice. Consumers are influenced by early negative information, especially when the overall set of 426
reviews is negative. Nevertheless, if the reviews are positively framed and when used together with 427
numerical rating details, then booking intentions and trust can increase. Moreover, the sequence of 428
reviews and ratings indicates the bias of primacy effect as travelers are influenced by early negative 429
information (negative reviews come first). Reviewed comments that users receive first have a greater 430
impact on the formed impression than those received in a later period (Park & Nicolau, 2015; Sparks 431
& Browning, 2011). 432
433
6.1.3 Tourism product choice 434
After assessment, tourists must decide on tourism products. In this stage, instant price, discount, 435
purchase risk, and willingness to pay are the few key variables that affect tourist decisions. In tourism 436
product choice, the maximum number of biases is observed, and these biases revolve around tourist 437
perceptions of available choices and prices before making decisions. Cognitive bias types found in 438
this stage include heuristics, cognitive miser, price anchoring, framing effect, loss aversion, 439
primacy/recency effect, decoy effect, priming effect, and cognitive dissonance. These bias types can be 440
categorized into three groups. 441
Biases related to price and discount 442
The online travel booking environment involves multiple cues that may encourage consumers to use 443
System 1 or automatic processing and apply judgmental heuristics to simplify the decision process 444
(Tversky & Kahneman, 1974). Tanford, Baloglu, and Erdem (2012) addressed that discount is 445
perceived as a heuristic cue. When the discount is large, consumers simply assume that the discounted 446
product is a good deal. Price difference influences the attributions of trust, price fairness, and purchase 447
intentions (Grewal, Marmorstein, & Sharma 1996; Hardesty and Bearden, 2003). When the discount 448
is small, the perceptions of trust and fairness are influenced by other factors, such as information 449
transparency, which can affect purchase decisions (Grewal, Hardesty, & Iyer 2004). The idea of 450
heuristics supports the cognitive miser principle (Fiske & Taylor, 1991), which theorizes that people 451
limit the amount of cognitive effort they must exert to reach decisions (Tanford, Baloglu, & Erdem, 452
2012). 453
Price anchoring and framing effect are the two other bias types related to tourist decision making on 454
price. Anchoring refers to the tendency to anchor a decision at an initial value and the failure to 455
sufficiently adjust to reach the true value (Tversky & Kahneman, 1974). Anchoring effect can occur 456
on price in the sense that compared with low-anchor advertising prices, high-anchor advertising prices 457
(up to a certain amount) increase potential customers’ willingness to pay more (Tanford, Choi, & Joe, 458
2018). Moreover, a relationship exists between price anchoring and framing effect. Framing can 459
influence tourists’ mental budgeting goal (high- or low-framed budget). Therefore, framing can 460
impact tourist response to price anchors when purchasing products online (Wu & Cheng 2011). 461
However, the effect of price anchoring decreases when tourists’ budget goal is incompatible with a 462
high price anchor but is not evidenced on a low-price anchor (Book, Tanford, & Chen, 2016; Tanford, 463
Choi, & Joe, 2018). 464
Loss aversion is relevant to pricing. Evidence of loss aversion implies that changes from the reference 465
point may be valued differently depending on whether such changes are gains or losses. People 466
become more sensitive to losses relative to their reference point than to gains (Nicolau, 2012). Nicolau 467
(2008) revealed that tourists react more strongly to price increases than to price decreases relative to 468
the reference price, thus representing evidence in favor of loss aversion. 469
Biases related to the positioning of online tourism products 470
In this concept, primacy/recency effect exists when the tourism product position (such as hotel 471
accommodations) affects the likelihood of selection. The bias occurs from the fact that hotels listed at 472
the top (primacy) and bottom (recency) are more likely selected than those listed in the middle (Ert & 473
Fleischer, 2016). 474
With regard to selecting and rejecting options, decoy effect can occur when a new alternative is added 475
into a choice set, thereby increasing the existing options (Huber, Payne, & Puto, 1982; Kim et al., 476
2018). If the decoy makes the target appear as a middle option in the choice set, then the preference 477
increase of the target represents the compromise effect (Pechtl, 2009). Decoy effect breaks the basic 478
economic assumption, which states that the attractiveness of one alternative is independent of the 479
remaining alternatives in the choice set (Schoemaker, 1982). Therefore, decoy effect creates bias in 480
decision making. 481
Biases related to information overload 482
Tourists are exposed to information overload during product selection. Priming effect is the cognitive 483
bias observed in the marketing area and is used as a technique to help promote sales. This effect 484
involves how ideas prompt other ideas without individuals’ conscious awareness. Thai and Yuksel 485
(2017) showed its evidence in tourism by using the priming effect to boost self-confidence and reduce 486
the choice overload effect. In addition, bounded rationality limits individuals’ cognitive abilities for 487
analyzing and comprehending online information (Lu et al., 2016a). Moreover, cognitive dissonance 488
is observed in situations involving choice overload and when customers perceive regrets after making 489
decisions. Perceived regret can be a sense of disappointment or sadness due to the choice individuals 490
make or do not make (Simonson, 1992). Park and Jang (2013) suggested that when tourists are 491
exposed to less than 22 choices, tourists who made a decision have less regret than those who did not. 492
However, when more than 22 choices are given, the choice group feels more regret than the “no-493
choice” group. The choice group may question whether the foregone alternatives are better than the 494
chosen one, leading to the perceived regret of making choices. Therefore, cognitive dissonance occurs 495
as a result of decision making. 496
6.2 On-site and post-trip experiences 497
Cognitive biases in on-site experiences are few. Two types of cognitive bias are investigated during 498
the retail/shopping experience, namely, loss aversion and present bias. Nguyen (2016) investigated 499
the link among loss aversion, present bias, and traveling expenditure patterns. The result reveals that 500
tourists with high loss aversion and high present bias likely overspend. However, the role of group 501
identity is regarded as a de-biasing factor, supporting the fact that individuals behave in accordance 502
with the standard economic models when making decisions in groups. 503
Post-trip biases are influenced by the recall of emotion after tourists return home. The memory of 504
emotional experience is reconstructed on the basis of past experiences and current beliefs (Aaker, 505
Drolet, & Griffin 2008; Levine 1997). Thus, the active reconstructive process provides an opportunity 506
for different cognitive and motivational biases to come into play (Watson & Spence 2007). Robinson 507
and Clore (2002) stated that the bias of retrospective emotions is attributed to individuals’ capacity to 508
remember and integrate subtle distinctions in expressing their experiences when they report bygone 509
emotions. Consequently, individuals provide a biased account of their emotions when recalling past 510
emotional experiences (Thomas & Diener, 1990). Lee and Kyle (2012) directly referred to the 511
memory recall of emotion and addressed the potential of recall inaccuracy (recall bias) by 512
investigating these two stages of emotions during and after tourists experience festival events. Their 513
findings support the notion that memories of emotions are inaccurate reflections of actual emotions. 514
On the contrary, Smith et al. (2015) supported the point that recall bias arises when tourists are asked 515
for their post-experience perceptions because recall is often shaped or distorted by events following 516
the trip. 517
6.3 Others 518
Other key articles relate to cognitive bias but cannot be included in the three stages of tourist 519
experience. These articles pose as either conceptual papers that state contents related to irrational 520
tourist decision making or empirical papers in which the context and phenomenon do not occur within 521
the three tourism stages. 522
Smallman and Moore (2009) stated that tourist decision-making processes are complex and involve 523
considerable sub-decisions. Although their article proposes the process view of tourist decision 524
making, aspects of prospect theory (Kahneman & Tversky, 1979), regret theory (Loomes & Sugden, 525
1982), heuristics, and bounded rationality (Simon, 1972) are mentioned to point out that the rationality 526
of tourists may not always follow the classical economic concept. Moreover, tourists may become 527
irrational given the contextual facts, perceptions, or evaluative judgments of relatively high-risk 528
decisions. 529
Higham, Ellis, and Maclaurin (2018) discussed the aspect of carbon emission in air travel and the 530
problem of cognitive biases that lead to unsuccessful effects. Various bias types cause irrational 531
decisions when tourists fly and trade off the risk of accelerating global warming. Such bias types 532
include availability bias (when asked to judge relative risks, people rely on their ability to remember 533
instances of the harms in question, and carbon emission risk and global warming still seem far away), 534
confirmation bias (when frequent air travelers rely on information that supports their decision to fly), 535
probabilistic reasoning and conjunction fallacy (the undependable ability of travelers to estimate the 536
real risk posed by global warming and hence may underestimate the cost of their own individual acts 537
of air travel onto themselves), price anchoring (how airlines place the low-framed anchor on the 538
carbon offset payment), and scope insensitivity (the amount that people are willing to pay is relatively 539
insensitive to the actual nature and extent of harm to be ameliorated). 540
Time perspective bias plays an important role in travel motivation (Lu et al., 2016b). Whether people 541
have a present-time or future-time perspective affects their motivation to travel. Different 542
psychological distances (e.g., temporal, social, or spatial) can make individuals construe objects 543
differently and hence affect their preferences on such objects attributes (Liberman, Trope, & 544
Wakslak, 2007). Kah, Lee, and Lee (2016) addressed the effect of construal level theory (CLT) on 545
temporal and spatial distances. CLT explains that an increased temporal distance highlights the 546
desirability-related aspects of intended actions, whereas a short temporal distance emphasizes the 547
feasibility-related aspects of intended actions (Trope & Liberman, 2003). Therefore, bias on the 548
perception toward the selected object’s attributes may arise. Moreover, a marketing implication 549
explains that if a prospective customer plans a purchase in the distant future, then a marketer should 550
emphasize factors that enhance consumption desirability. Conversely, if a prospective customer is 551
planning an immediate purchase, then a marketer must emphasize factors that enhance purchase 552
feasibility. 553
554
7. Conclusion, implications, and future research 555
556
This study conducts a systematic literature review on cognitive biases in tourist decision making from 557
three leading journals, JTR, ATR and TM. Tourists are revealed to make irrational decisions during 558
the three tourism stages. In addition, bias types that affect certain areas of managerial implications are 559
disclosed. Most of the selected articles provide insights for tourism and hospitality audiences 560
regarding potential tourist biases. Moreover, the selected articles provide implications and 561
recommendations that relate to the following three aspects of the tourism industry. 562
1) Implications/recommendations on tourism management 563
For the environmental concern on air travel, the “nudge” strategy can be applied with 564
regulatory impositions during the pre-trip stage to enhance tourists’ consciousness of their 565
impact on carbon emission, which can lead to the change in tourists’ behaviors toward carbon 566
offsetting. 567
To lessen the prejudgment toward a destination, destination marketing organizations can 568
reinforce the destination’s positive attributes and implement ways to manage its negative 569
attributes, thus reducing potential tourist social biases or stereotypes. 570
To reduce recall bias that can affect tourists’ intention to return, emotional experience must be 571
designed in a way that leaves them a positive feeling before a trip ends because incidents 572
occurring toward the end of the trip can greatly affect post-trip recall (Smith et al., 2015). 573
2) Implications on marketing, social media, and pricing 574
To market tourism products (e.g., hotels, restaurants, airlines, attractions), service providers 575
can improvise the framing of marketing messages, display tourism products in a way that 576
helps lessen customer information (choice) overload, and/or manage the product sequence 577
that appears on the tourism website. 578
To manage social media and online comments, tourism service providers can focus on means 579
to handle negative review contents and monitor review sequences to reduce the negativity bias 580
of potential customers toward the business. 581
To set the product price for pricing strategy, service providers may consider the anchoring 582
effect and set an appropriate starting price as a referencing point in relation to customers583
willingness to pay. How customers relate the set price with mental budgeting and review 584
comments before making decision should likewise be considered. 585
586
3) Policy implications 587
Public and non-profit organizations can develop policies on the basis of prevalent biases to 588
protect consumers and ensure producers’ efficient resource utilization. 589
Similarly, the findings infer that companies can use behavioral data to build descriptive models that 590
can increase the opportunity to generate additional revenue from the appropriate target market and 591
enhance consumer satisfaction. At the same time, consumers should learn the possible biases in 592
decision making that can lead to low satisfaction of travel experience. 593
The selected articles also indicate that the effect of cognitive biases vary from a trivial to a large 594
degree as tourists’ irrational decision making can affect individual to society levels. These irrational 595
decisions include decision making based on the process of product choices (e.g., choosing 596
accommodation, willingness to pay, and reading reviews before making decisions) or the post 597
“memory recall of emotion” of trips that affect future destination choices. Although these decisions 598
can cause individualsdeviation from the optimum choice, such decisions can still pose mild 599
consequences. However, certain irrational decisions occurring collectively can pose harm and have a 600
negative effect on a society. The impact of this scale can be significant, such that it may require the 601
policy level to provide a structural guideline or nudge behaviors. For example, an individual judgment 602
on a destination that is influenced by social bias or a certain negative or positive stereotype can bring 603
about collective social conflicts. Tourists’ collective purchase decision on environmental policy-604
related issues may not help lessen the global environment problem caused by air travel. Therefore, 605
investigating the possibility that cognitive biases can occur in the tourism context can help lay out 606
wide and deep perspectives for audiences to enhance bias awareness on such notions. 607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
Figure 6. Underresearched areas and existing research contributions 624
Further recommendations for future studies are also addressed. The selected cognitive bias studies on 625
tourism focus on an individual decision making, rather than a group decision, which can play a part in 626
decision choice. For instance, family members influence each other’s choices. Among the selected 627
articles, only one article mentioned a group decision in on-site experience. Therefore, further research 628
on group decision making and how such decisions influence cognitive biases is recommended. 629
In addition, this study discloses that most bias types occur during the pre-trip experience, especially 630
when tourists decide on product choices. Many elements of cognitive biases can be explored in the 631
tourism context. For instance, during the “post-trip stage,” an in-depth understanding about biases of 632
emotional recall is necessary because recalling products and experiences affects future decisions. 633
Tourism products are perceived as experiential products and are related to emotion and its memory 634
recall. Articles that discuss recall bias are limited. A similar urge for additional cognitive bias studies 635
also includes “on-site experience, but addressing specific bias types under this stage is quite 636
challenging. Considering the nature of the tourism industry, various tourist choices (e.g., event 637
festivals, adventurous tours, sightseeing, and shopping), site activities (choosing one activity over the 638
others), and topics related to cognitive bias types are under-examined and need further exploration and 639
investigation. 640
Moreover, cognitive biases do not always have to be negative or flawed (i.e., leading to suboptimal or 641
irrational choices) because cognitive biases may be important for human survival. From the 642
evolutionary perspective, cognitive bias is an important design feature for natural adaptation 643
(Haselton, Nettle, & Andrews, 2005). For example, cognitive load reduction through heuristics 644
enables individuals/tourists to quickly decide and optimize valuable resources in time-limited 645
situations (e.g., vacations). Thus, rather than seeing cognitive biases as flaw factors, further research 646
can explore and unearth the positive viewpoints that indicate the benefits of such biases in the tourism 647
industry. 648
This study also has limitations. The three selected journals exclude cognitive bias papers from other 649
tourism journals. This limited selection hinders the opportunity to fully capture cognitive bias studies 650
from a wide threshold. Future research may include a wide range of tourism journals that discuss the 651
cognitive bias phenomenon in the tourism and hospitality contexts. Through a qualitative systematic 652
analysis, this research may limit its power of generalizability on the data and content found through a 653
quantitative meta-analysis. Moreover, aspects of cognitive biases in tourist decision making are under-654
examined. Nevertheless, this study still serves as a solid starting point that allows tourism academics 655
and practitioners to focus their research directions toward crucial issues. 656
…………………………………………………………………………………………………………… 657
Declarations of interest: None 658
…………………………………………………………………………………………………………… 659
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Appendix 1. The selected articles on cognitive biases in the tourism context
No.
Author/Year
Article
Type of bias
mentioned in the
article
Relating Bias contents from the article
Central/
Supporting
role (C/S)
Tourism
Stage
Journal of Travel Research (JTR)
1
Kneesel,
Baloglu, &
Millar (2010)
Gaming Destination
Images: Implications
for Branding
Halo effect
The authors suggested that “Well-known destination brands are
associated with high awareness and familiarity, more positive
overall images, and more affective descriptions, which might
create a halo effect on evaluations of cognitive attributes,
visitation intention, and word of mouth.
S
Destination
choice
selection
2
Nicolau (2012)
Asymmetric Tourist
Response to Price:
Loss Aversion
Segmentation
Loss aversion
The author looks into the heterogeneity in loss aversion which is
a prominent psychological human trait that causes asymmetric
price reactions. The objective of the study is to detect how
dispersed loss aversion is in tourism and to observe whether
different degrees of loss aversion can lead to the different
loss-aversionbased segments.
C
Destination
choice
selection
3
Lee & Kyle
(2012)
Recollection
Consistency of
Festival Consumption
Emotions
Recall bias
The authors investigated the variation in visitors’ recall of their
emotional experiences at festivals over time. The results
demonstrate that respondents reported a higher intensity of
positive emotions but reported a consistent intensity of neutral
and negative emotions when asked to evaluate their emotions
on-site during their festival visit.
C
Post-trip
experience
4
Tanford,
Baloglu, &
Erdem (2012)
Travel Packaging on
the Internet: The
Impact of Pricing
Information and
Perceived Value on
Consumer Choice
Cognitive miser
In the study, the authors apply principles of decision heuristics
and the cognitive miser principle to online travel package
purchases.
C
Tourism
product
choice
selection
5
Chen, Lin, &
Petrick (2013)
Social Biases of
Destination
Perceptions
Stereotype
The study proposes that the process of international stereotyping
might be triggered when two countries have conflicts, resulting in
the formation of negatively biased country and destination images.
The results show that individuals who have higher identification
with their own country (guest country) might possess poorer
evaluations of the host country and that biased perceptions are
C
Destination
choice
selection
No.
Author/Year
Article
Type of bias
mentioned in the
article
Relating Bias contents from the article
Central/
Supporting
role (C/S)
Tourism
Stage
fairly solid in that they might not be dispelled after actual visitation.
6
Tanford &
Montgomery
(2015)
The Effects of
Social Influence and
Cognitive Dissonance
on Travel Purchase
Decisions
Cognitive
dissonance
The study investigates the cognitive dissonance in hotel choice on
guests with pro-environmental attitudes and hotel choices. Subjects
with strong pro-environmental attitudes experienced dissonance
when making a non-green choice on the hotel selection.
Consistent with dissonance theory predictions, guests sought
out more favorable information about the resort when they
experienced dissonance.
C
Tourism
product
choice
selection
7
Ert & Fleischer
(2016)
Mere Position Effect
in Booking Hotels
Online
Primacy effect
The study investigated the position effect in online hotel booking
and found that the hotels that were listed at the top (primacy
effect) and bottom (recency effect) of the list were more likely
to be chosen than those listed in the middle. The study found
items on the first screen, the last item on the were more
likely to be selected.
C
Tourism
product
choice
selection
8
Book, Tanford,
& Chen (2016)
Understanding the
Impact of Negative
and Positive Traveler
Reviews: Social
Influence and Price
Anchoring Effects
Price anchoring
The study investigates how social influence (both in the form of
negative or positive traveller reviews) influences the price and
willingness to pay. Results indicate that no amount of price
reduction was sufficient to offset the impact of unanimously
negative reviews, although an extreme price reduction influenced
decisions when negative reviews were not unanimous. Price
anchoring occurred for positive reviews, such that a higher
reference price increased willingness to pay.
C
Tourism
product
choice
selection
9
Higham, Ellis,
& Maclaurin
(2018)
Tourist Aviation
Emissions: A Problem
of Collective Action
Availability bias;
Confirmation bias;
Anchoring;
Conjunction
fallacy;
Scope insensitivity
The study uses decision-making theory on heuristic and cognitive
biases to explore why individuals have been generally unwilling or
unable to act upon the threats of unconstrained and accelerating
emissions associated with air travel and threaten everyone’s well-
being. A number of cognitive biases listed in the left column are
used to explain why an individual uses the irrational decision
making to response to the problem.
C
Other
10
Stepchenkova,
Su, &
Shichkova
(2018)
Marketing to Tourists
from Unfriendly
Countries: Should We
Even Try?
Social bias
The study focuses on how tourists respond to marketing materials
in a situation where the destination country and the source market
country are engaged in constant political, economic, diplomatic,
and/or military conflict. The notion of social bias (in-group/out-
group) has been addressed to indicate the perception of people on
the two conflicted nations.
S
Destination
choice
selection
No.
Author/Year
Article
Type of bias
mentioned in the
article
Relating Bias contents from the article
Central/
Supporting
role (C/S)
Tourism
Stage
11
Tanford & Kim
(2018)
Risk versus Reward:
When Will
Travelers Go the
Distance?
Heuristic/prospect
theory
Negativity bias
In this study, prospect theory and judgmental heuristics are
employed as a theoretical foundation for the prediction of tourists
purchase decision based on the online review and location. When
both resorts had neutral reviews, location was the main determinant
of lodging choice. The findings suggest that locational superiority
can be offset by negative reviews, whereas locational inferiority
can be overcome by maintaining good reviews online.
C
Tourism
product
review and
rating
12
Gkritzali,
Gritzalis, &
Stavrou (2018)
Is Xenios Zeus Still
Alive? Destination
Image of Athens in
the Years of
Recession
Social bias
This study examines the evolution of the destination image of
Athens from 2005 to 2015. The findings reveal that the destination
image of Athens is partially shared by individuals residing inside
and outside Greece, and that non-Greek residents have more
favourable perceptions toward the destination. The findings suggest
that the perceptions on the affective image of Athens are not overall
consistent but only partially shared between Greek and non-Greek
residents, being socially biased. Therefore, the findings confirm the
subjective character of destination image.
S
Destination
choice
selection
13
Tanford, Choi,
& Joe (2018)
The Influence of
Pricing Strategies on
Willingness to Pay for
ccommodations:
Anchoring, Framing,
and Metric
Compatibility
Anchoring effect
Framing effect
Heuristics
The study uses experimental methods to test the effects of price
anchors, framing, and metric compatibility (price per night versus
the mental total budget) on willingness to pay for a Spring Break
vacation. Travel providers advertise low prices to attract customers,
which can decrease willingness to pay through anchoring effects.
Customers often approach purchases with a budget goal, which can
influence price interpretation due to framing effects. A high anchor
increases willingness to pay compared to a low anchor. Anchoring
effects are reduced when the budget goal is incompatible with a
high anchor but not a low anchor. The findings can be attributed to
dual processing systems and asymmetry effects.
C
Tourism
product
choice
selection
14
Kim, Kim, Lee,
Kim, & Hyde
(2018)
The Influence of
Decision Task on the
Magnitude of Decoy
and Compromise
Effects in a Travel
Decision
Decoy effect
This research assesses the effects of choice alternatives on the
travel destination decisions of travelers. The decoy effect, which is
the phenomenon where consumers tend to change their preferences
between the two choices when presented with the third choice and
caused the bias in decision choices, was tested through a series of
scenario-based experiments.
C
Tourism
product
choice
selection
Annals of Tourism Research (ATR)
15
Smallman &
Process studies of
-
Mentioned about heuristic in tourist decision making, the factor of
S
Other
No.
Author/Year
Article
Type of bias
mentioned in the
article
Relating Bias contents from the article
Central/
Supporting
role (C/S)
Tourism
Stage
Moore (2009)
tourists
bounded rationality and the need to incorporate prospect theory and
regret theory into the understanding.
16
Park & Nicolau
(2015)
Asymmetric effects of
online consumer
reviews
Heuristics
Negativity bias
Star ratings in online reviews are a critical heuristic element of the
perceived evaluation of online consumer information. The results of
this study show that people perceive extreme ratings (positive or
negative) as more useful and enjoyable than moderate ratings.
Negativity bias was mentioned to be the tendency for a unit of
activation to bring about a greater change in output by the negative
motivational system compared with the positive motivational
system.
C
Tourism
product
review and
rating
17
Lu, Gursoy &
Lu (2016)
Antecedents and
outcomes of
consumers’confusion
in the online tourism
domain
Bounded
rationality
The paper proposes a research model examining the antecedents
and outcomes of online tourism information confusion faced by
consumers. Bounded rationality was mentioned as a cause that
limits individuals’ cognitive abilities for analysing and
comprehending the incoming stimuli which affect the possibility of
tourists’ confusion when a tourist is searching and processing
online information.
S
Tourism
product
choice
selection
18
Kah, Lee, &
Lee (2016)
Spatialtemporal
distances in travel
intentionbehavior
Time perspective
bias and construal
level Theory
(CLT)
The study investigates non-travelers’ behavior, focusing on the
influence of spatial and temporal distances on decisions not to
travel and their effects on the gap between travel intention and
actual behavior. The study also employed the concept of Construal
Level Theory (CLT) which explains the different attributes being
focused by the individual based on how they are construed both the
spatial and temporal dimensions.
C
Other
19
Thai &Yuksel
(2017)
Too many
destinations to visit:
Tourists’ dilemma?
Priming effect
In this study, the priming effect is recommended to promote the
sales techniques. Boosting participants’ self-confidence by priming
them to believe that they were experts will help reduce the
information overload effect as literature supports the relation
between self-confidence and expertise. As self-confidence
attenuates choice overload effects, high self-confidence can be
conveniently integrated into sales communications by travel
advisors online or in face-to-face interactions with clients.
S
Tourism
product
choice
selection
20
Chi, Ouyang,
& Xu (2018)
Changing perceptions
and reasoning
process: Comparison
Confirmation bias
The study incorporates the positive confirmation bias theory to
explain residents’ changing perceptions toward a mega-event.
Under the confirmation bias, individuals tend to search evidence to
C
Other
No.
Author/Year
Article
Type of bias
mentioned in the
article
Relating Bias contents from the article
Central/
Supporting
role (C/S)
Tourism
Stage
of residents’ pre- and
post-event attitudes
confirm their initial judgments. This fundamental reasoning
tendency for humans is expected to impose significant effects on
residents’ perceptions of event impacts, as well as their responses to
the government and the event per se. The findings support
confirmation bias and clearly demonstrate that residents’ trust in
government(s), attachment to the event, perceptions of the event’s
impacts and ultimate support to the event have changed in a
predictable manner over time. Individuals’ direct experience with
the event alters the associations between their cognitive/affective
evaluations and attitudes towards the event
Tourism Management (TM)
21
Larsen, Brun,
& Ogaard,
(2009)
What tourists worry
about Construction
of a scale measuring
tourist worries.
Impact bias
This paper explores the concept of tourist worry. The cognitive bias
is found in the tourist samples who seem to underestimate the level
of worrying. Impact bias is mentioned when the authors explained
the tendency of tourists to overestimate the intensity of future
emotions.
S
Destination
choice
selection
22
Castelltort, &
Mader (2010)
Press media coverage
effects on destinations
A Monetary Public
Value (MPV)
analysis.
Stereotyping,
Heuristics
The present study examines the extent, source and nature of
reporting about Spain as a tourist destination among Swiss German
language newspapers by using the Monetary Publicity Value
(MPV). In regards to cognitive biases, media coverage is mentioned
by scholars to be a stereotype and consumers are imperfectly
informed and consume more bad news stories than good ones.
News media has impact to the destination image which is
mentioned to be a heuristic factor.
S
Destination
choice
selection
23
Sparks &
Browning
(2011)
The impact of online
reviews on hotel
booking intentions
and perception of
trust.
Framing effect,
Primacy effect
The study explores the role of factors that influence perceptions of
trust and consumer choice. Consumers seem to be more influenced
by early information, especially when the overall set of reviews is
negative, indicating primacy effect, meaning information is
presented before has some influence on shaping evaluation.
Positively framed information (framing effect) together with
numerical rating details influences both booking intentions and
consumer trust.
C
Tourism
product
review and
rating
24
Park and Jang
(2013)
Confused by too many
choices? Choice
overload in tourism.
Cognitive
dissonance
Choice overload phenomenon exists in tourism products. The study
results showed that having more than 22 choices increased the
likelihood of making ‘no choice,’ regardless of destination type.
S
Tourism
product
choice
No.
Author/Year
Article
Type of bias
mentioned in the
article
Relating Bias contents from the article
Central/
Supporting
role (C/S)
Tourism
Stage
When fewer than 22 choices were provided, participants who made
a choice perceived less regret than those who made ‘no choice’.
However, the opposite results were found when tourists were
provided with too many choices. Perceived regret is the negatively
and cognitively determined emotion that can arise after a tourist
starts to consider the favourable qualities of other options which
could cause cognitive dissonance and the feelings of regret
eventually.
selection
25
Park and Jang
(2014)
Sunk costs and travel
cancellation: Focusing
on temporal cost.
Sunk cost effect
Cognitive
dissonance
The study aims to understand the effects of temporal sunk costs on
potential travelers’ cancellation intentions in addition to monetary
sunk costs. Theoretically, sunk cost is associated with cognitive
dissonance theory as once a subject is induced to expend effort on a
challenging task, they will evaluate the value upward and will
increase willingness to expend further resources on the task
compared to the resources that would be allocated by a subject not
having made a prior effort investment. The results of this study
suggested the possibility that temporal costs can be converted into
monetary costs, but the conversion relationship may not be linear
and that travelers' intentions to cancel a travel product decreased as
the temporal and monetary sunk costs increased. Repeat visitors'
intentions to cancel their reservations are more influenced by
temporal sunk costs than first-time visitors.
C
Tourism
product
choice
selection
26
Smith et al.
(2015)
Tracking destination
image across the trip
experience with
smartphone
technology.
Recall bias
This study is to examine changes to tourists' image of a destination
throughout a trip experience by examining a group of Canadian
student travelers to Peru. Through the use of Blackberry
technology, students were asked to record images and experience in
the five stages namely pre-trip, upon arrival, halfway, departure,
and post-trip. The results show that destination image evolves
throughout their trip and can be affected by certain incidents. Bias
of recall was mentioned to explain that incidents which happened
close to the end of the trip seemed to have a greater effect on the
post-trip recall scores than those that occurred during earlier parts.
S
Post-trip
experience
27
Lu et al.
(2016b)
Do perceptions of
time affect outbound-
travel motivations and
Temporal thinking
bias/time
perspective bias
The study investigates Chinese seniors' outbound-travel motivation
and intention with particular reference to time perspective since
how people conceptualise time, indicating time-perspective bias,
C
Other
No.
Author/Year
Article
Type of bias
mentioned in the
article
Relating Bias contents from the article
Central/
Supporting
role (C/S)
Tourism
Stage
intention? An
investigation among
Chinese seniors.
can play a critical role in their travel intention. The findings showed
that present-time perspective and future-time perspective were
directly related to travel motivation, and that the associations
between present and future perspectives and travel intention were
fully mediated by travel motivation.
28
Kapuscinski, &
Richards
(2016)
News framing effects
on destination risk
perception.
Framing effect
The study takes the framing effects theory and existing knowledge
of perceived risk in tourism in order to seek to understand whether
different media frames concerning hazards influence tourists'
judgment of risk as news coverage of hazards is often commented
to be of critical importance to individuals' perceived risk associated
with tourist destinations. The findings showed that the use of risk
amplifying frame and risk attenuating frame result in higher and
lower ratings of risk respectively. Moreover, tourist psychographic
characteristics were found to moderate the influence of news
frames on perceived risk.
C
Destination
choice
selection
29
Berdychevsky,
Gibson, & Bell
(2016)
“Girlfriend getaway”
as a contested term:
Discourse analysis.
Stereotype
The study explores the meanings associated with the “girlfriend
getaway” term, using discourse analysis to understand the ways
women build significance, activities, identities, relationships,
politics, connections, and sign systems and knowledge with respect
to it. The analysis revealed that “girlfriend getaway” is a term with
contested and polysemous meanings. While some women found it
to be adequate, accurate, cute, and reflective of their all-female
tourist experiences, others described it as stereotypical,
narrow/claustrophobic, “pink,” inadequate, and unreflective of their
experiences. At times, the same symbolic meanings attracted some
women but alienated others. This gives implication to tourism
marketers to identify and engage with different strands within their
female clientele to ensure that their strategies appropriately respond
to various preferences and lifestyles.
S
Other
30
Zhang, Zhang,
& Yang (2016)
The power of expert
identity: How
website-recognized
expert reviews
influence travelers’
online rating behavior.
Negativity bias
The study explores the effects of some prominent reviews on
subsequent consumer behavior. Customers tend to see negative
reviews and information to be more values for them. Voicing less
favourable attitudes tends to attract attention (Kanouse & Hanson,
1987), therefore, ordinary users on the website may be prone to
negative bias from the negative reviews they have read, particularly
C
Tourism
product
review and
rating
No.
Author/Year
Article
Type of bias
mentioned in the
article
Relating Bias contents from the article
Central/
Supporting
role (C/S)
Tourism
Stage
if those negative reviews come from experts.
31
Nguyen (2016)
Linking loss aversion
and present bias with
overspending
behavior of tourists:
Insights from a lab-in-
the-field experiment.
Loss aversion
Present bias
The study explores how behavioural factors influence the
probability of overspending among outbound leisure travellers, by
applying the concept of loss aversion and present bias. The study
explores the link between the measured preferences to
overspending behaviour. The findings reveal a link between loss
aversion, present bias and traveling expenditure patterns: outbound
tourists with high loss aversion and high present bias are more
likely to overspend. The study also highlights the role of group
identity in de-biasing. Specifically, individuals are more likely to
behave according to standard economic models when making
decisions in groups.
C
On-site
experience
32
Tseng (2017)
Why do online
tourists need sellers’
ratings? Exploration
of the factors affecting
regretful tourist e-
satisfaction.
Cognitive
dissonance
The study responds to the research questions: are higher tendency-
to-regret (TTR) tourists more likely to experience post-purchase
cognitive dissonance than lower TTR tourists after online
purchases? And how does post-purchase cognitive dissonance
(PCD) influence the relationship between tourists' tendency-to-
regret and e-satisfaction? The results indicate that the influence of
regretful personality on e-satisfaction was fully mediated via post-
purchase cognitive dissonance. The effect of valid sellers' ratings
on raising regretful tourist e-satisfaction was also confirmed.
C
Tourism
product
choice
selection
33
Ouyang,
Gursoy, &
Sharma (2017)
Role of trust,
emotions and event
attachment on
residents' attitudes
toward tourism
Positive bias
This study examines the effects of residents' trust in government
and their emotions toward an event on their perceptions of potential
impacts and their support. Findings indicate that residents' support
is a function of both cognitive and affective assessment of
perceived impacts. Trust in government influences directly
residents' support and indirectly through perceived impacts and
experienced emotions toward an event. Moreover, findings further
suggest that those residents with high level of event attachment
pose more positive bias towards perceptions of impacts.
S
Other
34
Letheren,
Martin, & Jin
(2017)
Effects of
personification and
anthropomorphic
tendency on
destination attitude
Subconscious bias
The study examines how individual differences in anthropomorphic
tendency (the tendency to humanize non-human agents/objects)
influence how people respond to destination marketing
communications. The study specifically examined whether
individual-level anthropomorphic tendency and text-personification
S
Destination
choice
selection
No.
Author/Year
Article
Type of bias
mentioned in the
article
Relating Bias contents from the article
Central/
Supporting
role (C/S)
Tourism
Stage
and travel intentions
of destination marketing communications interact to influence
destination attitude and travel intentions. The process of
anthropomorphism is mentioned to be mindless or subconscious
bias, indicating that while individuals are likely to respond better to
human cues, they are unlikely to be aware of what has occurred, or
why they feel more favorable towards the message they have just
seen. Results from a study revealed that destination attitude and
travel intentions were most favorable for people with high levels of
anthropomorphic tendency and who were exposed to personified
tourism messages.
35
Xiang, Du, Ma,
& Fan (2017)
A comparative
analysis of major
online review
platforms:
Implications for social
media analytics in
hospitality and
tourism
Positivity bias
Heuristic
The study applies the text analytics with the review data from the
three data sources of three major online review platforms, namely
TripAdvisor, Expedia, and Yelp to examine information quality (in
terms of their linguistic characteristics, semantic features,
sentiment, rating, usefulness as well as the relationships between
these features) related to online reviews about the entire hotel
population in Manhattan, New York City. The findings show that
there are huge discrepancies in the representation of the hotel
industry on these platforms. Different types of cognitive biases
relating to the review data on the social media were mentioned
namely availability bias, positivity bias and heuristic.
S
Tourism
product
review and
rating
36
Zhang et al.
(2018)
Message framing and
regulatory focus
effects on destination
image formation
Framing effect
This study examines the impacts of attribute framing effects of
destination advertising messages on travellers destination image
perceptions and visit intentions, by utilising attribute framing and
regulatory focus fit theories. This study also examines the
mediating role of cognitive fluency and emotional state on attribute
framing effects on destination image formation and visit intentions.
Findings indicate that framing of marketing messages exerts
significant influences on consumers' decision making and
destination selection process. Consumers under gain-framed
message condition tend to have higher destination image
perceptions compared to those under loss-framed message
conditions. A match between attribute framing and regulatory focus
results in formation of better destination image perceptions
compared to mismatch.
C
Destination
choice
selection
No.
Author/Year
Article
Type of bias
mentioned in the
article
Relating Bias contents from the article
Central/
Supporting
role (C/S)
Tourism
Stage
37
Tan, Lv, Lui, &
Gusoy (2018)
Evaluation nudge:
Effect of evaluation
mode of online
customer reviews on
consumers’
preferences
Cognitive bias
Heuristic
The study utilises two experimental designs to examines the
relationship between evaluation mode of online reviews and
evaluators' preferences and decision-making for tourism products
by applying an “evaluation nudge”. The consumers' preferences for
tourism products are dependent on whether the online information
about alternative products is presented jointly (joint evaluation
mode) or separately (separate evaluation mode). Cognitive bias was
founded in the case of making decision in isolation as some
negative attributes were being ignored. Hence, the information
processing mode is found to mediate the impact of evaluation mode
on preference for restaurant alternatives. For the hotel choices, the
study reveals the different impacts of evaluation mode on
preference for hotel alternatives resulting from negative valence of
customers’ reviews.
C
Tourism
product
choice
selection
(stronger
emphasis)
&
Tourism
product
review and
rating
... Research by experimental psychologists has shown that people rely on heuristic cues when making judgements about uncertain outcomes, which can lead to severe biases (Tversky and Kahneman, 1974;Gilovich et al., 2002; Frontiers in Psychology | www.frontiersin.org for a review of the cognitive biases in tourists' decision-making, see Wattanacharoensil and La-ornual, 2019). ...
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Based on the factors of the Theory of Planned Behaviour (TPB), the Health Belief Model (HBM), and the DOSPERT scale, used to measure general risk-taking behaviour, a combined model has been developed for investigating tourists' intentions to implement protective measures against the coronavirus disease 2019 (COVID-19). The purpose of the study is to formulate a model that Swiss tourism practitioners can use to understand tourists' decision-making regarding the acceptance and proper implementation of non-pharmaceutical interventions (NPIs). A large-scale cross-sectional population study that is representative for the Swiss population has been designed to validate the model (N = 1,683; 39% response rate). In our empirical investigation, a simple regression analysis is used to detect significant factors and their strength. Our empirical findings show that the significant effects can be ordered regarding descending effect size from severity (HBM), attitude (TPB), perceived behavioural control (TPB), subjective norm (TPB), self-efficacy (HBM), and perceived barriers (HBM) to susceptibility (HBM). Based on this information, intervention strategies and corresponding protective measures were linked to the social-psychological factors based on an expert workshop. Low-cost interventions for tourists (less time, less money, and more comfort), such as the free provision of accessories (free mask and sanitizers) or free testing (at cable cars), can increase the perceived behavioural control and lower the perceived barriers and thus increase the acceptance of this protective measure.
... utility theory) and psychology (e.g. planned behaviour theory) to explain the tourism decision-making process (Wattanacharoensil & La-ornual, 2019). However, tourism decision-making varies among different types of tourists. ...
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Although the number of studies on sport tourism has increased in recent years, there is a shortage of systematic reviews. This study meta-analytically investigated 40 correlation matrices on the determinants that affect the decision-making of sport tourists from the articles published in sport and tourism journals. By conducting a comprehensive meta-analysis, this paper revealed that the decision-making determinants of sport tourists include nostalgia, attitude, motivation, behavioural intention, event quality, destination image, tourist satisfaction, perceived value, future intention, destination loyalty, and place attachment. The correlations among these determinants were integrated into a framework with 16 hypotheses tested. This paper is the first meta-analysis of the determinants that affect the decision-making of sport tourists, thus providing implications for future research and sport tourism marketing and planning. ARTICLE HISTORY
... Tourist decision making has been dominated by a rational paradigm based on utility theory, which postulates that tourists are rational decision makers who try to maximize utility through logical reasoning (McCabe, Li, & Chen, 2016;Sirakaya & Woodside, 2005). However, tourists as human beings are not always rational (Wattanacharoensil & La-ornual, 2019). Dual-system theories indicate two distinctive but complementary processes behind decision making: System 1 is rapid, intuitive, heuristic and affect-driven, which generates intuitive responses, while System 2 is slow, rational, analytic and reflective, which involves deliberate considerations (Kahneman, 2011). ...
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Searching for inspiration, or travel ideas, is part of the dreaming phase, positioned at the start of the travel process. Yet the ontological and epistemological understanding of inspiration in travel is still in infancy. Based on the inspiration literature in psychology and marketing, this study conceptualizes travel inspiration as a moti-vational state that drives a prospective tourist to bring newly obtained travel ideas into realization. By explaining the two distinct states, inspired-by and inspired-to, this note further proposes that inspiration can provide a potential shortcut in tourist decision making. The destination choice scenario is used to illustrate the shortcut. Travel inspiration can help researchers explore the neglected dreaming phase and irrational aspects of tourists' decision making. Tourism marketers can inspire prospective tourists by serendipitously suggesting lesser-known attractions and novel experiences, thereby allowing for a seamless experience from inspiration to booking.
... This systematic literature review follows the structured approach which is well recognised in the areas of management, transportation, and travel research (e.g., Khalaj et al., 2020;Papavasileiou and Tzouvanas, 2020;Wattanacharoensil and La-ornual, 2019). The systematic literature review is an explicit, reproducible, and structured evaluation of the existing literature related to one or more research questions in a specific field of knowledge (Tranfield et al., 2003). ...
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In light of the Micromobility Sharing Systems (MSS) boom, specifically bike and scooter sharing, related academic studies have grown accordingly in the last few years. However, contributions are scattered, particularly regarding the knowledge about the user of these systems. This article provides a systematic review of the studied factors influencing MSS user behaviour and offers insights for future research. An inclusive search of the Web of Science and Scopus databases was performed to identify related literature. The final analysis included 203 articles that met the eligibility criteria. The findings were organised into three main groups that aggregate 25 factors influencing MSS user behavioural responses: (i) temporal, spatial and weather-related factors, (ii) system-related factors and (iii) user-related factors. The review uncovered several neglected factors, as well as theoretical and methodological gaps in the literature. Based on that, the study suggests directions for future studies including researching the emotional influences and outcomes of MSS use, considering environmental beliefs and behaviours in the MSS context, examining negative behaviours and negative assessments of MSS use, and consolidating the use of theoretical frameworks.
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While human actions are the outcome of both personal and contextual forces, existing pro-environmental behavior (PEB) studies have predominantly focused on the former, leaving contextual drivers rarely examined. Urban areas attract large numbers of tourists, yet tourist PEB studies have primarily focused on nature-based and lodging settings, leaving PEBs in urban settings under-evaluated. In the current study, we seek to develop and validate a scale measuring the pro-environmental contextual force that affects urban tourists’ PEBs. Adopting mixed-method approaches, this paper involves three studies. This paper contributes the first measurement instrument for pro-environmental contextual force, tests its role, and extends the theory of planned behavior. This paper also provides practical implications for PEB interventions at tourism destinations.
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Purpose This paper aims to provide an assessment of tourism promotion in tourist destinations and airports (TPTDs) and to organize and classify the literature on tourism promotion, with the aim of staging the importance of this topic and encouraging future research in the projection of tourism and marketing sectors. Design/methodology/approach The paper uses the Social Sciences Citation Index (SSCI) database to analyze the bibliometric in TPTDs topic from 2000 to 2021. Additionally, the paper also uses the visualization of similarities (VOS) viewer software to map graphically the bibliographic material. The graphical analysis uses bibliographic coupling, co-citation, citation and co-occurrence of keywords. Findings This study provides an amended new definition of tourism promotion, which is the efficient management of a destination’s resources and strategic plans by destination marketing organizations (DMOs) to adapt the tourism supply to market trends and will empower tourists to visit such destinations. Furthermore, results also show a new paradigm applied to TPTDs topic and classified in five first-order research streams. Digital and mobile marketing, infrastructure, branding, quality, accessibility and information factors about a specific destination which are mostly demanded by tourists are considered as an important means of promotion for the tourism industry. Originality/value The contribution of this study is important to identify new challenges and opportunities for researchers, DMOs, airport and airlines operators and stakeholders, as disentangling existing contradictions and applying new theoretical framework to make better future decisions by researchers and organizations to provide higher quality to new research in the context of the TPTDs.
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Domestic tourism is increasingly being propagated as a primer for the global tourism industry’s resuscitation in the era of COVID-19. However, in light of the COVID-19 pandemic, the challenge for African tourism destinations such as South Africa is predicting domestic tourists’ behavioral and demand responses. The article explores the mediating effect of perceived risk on the nexus between South African domestic tourists’ push and pull travel motives. Data were generated via a self-administered online survey and analyzed primarily utilizing factor and mediation analyses. From the sample (n = 427), the study identifies the heterogeneity in the push–pull travel motives nexus. Moreover, the findings also establish the susceptibility of experiential escape-seeking tourists to the negative mediating influence of COVID-19-induced perceived physical risk on their likelihood of engaging in leisure-oriented domestic tourism activity. The results also point to potential cognitive bias and subjective preference towards domestic tourism, potentially signaling a crisis-induced shift in tourist behavior. The managerial implications are also discussed.
Conference Paper
Full-text available
از یک سو، مسكن یکی از نیازهای اساسی انسان است که از جنبه‌هاي مختلفی، اعم از اقتصادی، اجتماعی و روانی و جسمی بر زندگي وی تاثیرگذار است. از سوی دیگر، عواملی مانند عدم قطعیت، احتمال، ابهام و پیچیدگی، عمل انتخاب را برای فرد دشوار می‌سازند و می‌توانند سوگیری‌های شناختی را در وی ایجاد کنند. بنابراین، تصمیم‌گیری برای انتخاب مسکن مناسب از اهمیت بسیاری برخوردار است. علیرغم تحقیقات خارجی و داخلی که در حوزه سوگیری‌های شناختی صورت گرفته است، تحقیقات داخلی اندکی به سوگیری‌های شناختی در سرمایه‌گذاران پرداخته‌اند و تاکنون هیچ پژوهشی، سوگیری‌های شناختی در خریداران مسکن را مورد بررسی قرار نداده است. هدف از این پژوهش، شناسايي سوگيري‌هاي شناختی تاثيرگذار بر تصميم‌گيري خریداران ایرانی در انتخاب مسکن و رتبه‌بندي سوگيري‌هاي شناختی خریداران ایرانی می‌باشد. این پژوهش از نظر هدف کاربردي و از نظر ماهیت و گردآوري داده‌ها توصیفی زمینه‌یاب است. جامعه آماري این پژوهش شامل خریداران ایرانی مسکن می‌باشد. روش نمونه‌گیری که در این پژوهش مورد استفاده قرار گرفته است، روش نمونه‌گیري در دسترس می‌باشد. گردآوري داده‌ها در این پژوهش از طریق مطالعات کتابخانه‌اي و پرسشنامه آنلاین انجام شده است. برای تجزیه و تحلیل داده‌ها (150=n) از شاخص‌های فراوانی استفاده شد و توسط نرم‌افزار SPSS انجام گرفت. نتایج این تحقیق نشان داد که 9 سوگیری شناختی بر تصميم‌گيري خریداران ایرانی در انتخاب مسکن تاثيرگذار است. این سوگیری‌های شناختی به ترتیب عبارتند از: رویدادهای اخیر، قابليت دسترسي، حسابداری ذهنی، ابهام‌گريزي، اتكاء و تعديل، اعتماد بيش از حد، رویدادگرایی، ناهماهنگي شناختي و نمایندگی.
Conference Paper
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On the one hand, housing is one of the basic human needs that affect her/his life in various aspects, including economic, social, psychological, and physical. On the other hand, uncertainty, probability, ambiguity, and complexity make a choice difficult for the individual and can create cognitive biases. Therefore, deciding to choose the proper housing is very important. Despite foreign and domestic research in the field of cognitive biases, domestic research has addressed little of the cognitive biases in investors, and so far, no research has examined cognitive biases in home buyers. This study aims to identify the cognitive biases that affect the decision of Iranian buyers in choosing to house and rank the cognitive biases of Iranian buyers. This research is descriptive in applied purpose and nature and descriptive data collection. The statistical population of this study includes Iranian housing buyers. The sampling method used in this research is the sampling method available. Data collection in this study was done through library studies and online questionnaires. Frequency indices were used to analyze the data (n = 150) and were performed by SPSS software. The results of this study showed that nine cognitive biases affect the decision of Iranian buyers in choosing a housing. These cognitive biases include recency, availability, mental accounting, ambiguity aversion, anchoring, overconfidence, hindsight, cognitive dissonance, and representativeness.
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Tour experiences often comprise sequences of episodes, yet little is known in tourism research on how two common situational factors might alter individuals' evaluation of such multi-episode experiences: hedonic trend (i.e., the order of such episodes) and perceived time pressure (i.e., individuals' perception of limited available time). Two studies (i.e., an online experiment on a multi-city tour and a field experiment in a multi-site archaeological park) examine the interaction between these two factors by showing that individuals exhibit better evaluative responses (i.e., liking and revisit intention) to multi-episode tour experiences when such experiences have an ascending hedonic trend (i.e., their constituting episodes unfold in an increasing attractiveness order) rather than a descending one (i.e., the same episodes unfold in the opposite order). Importantly, individuals' perception of time pressure reverses this tendency. Our findings carry theoretical and managerial implications on how to design multi-episode tour experiences.
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Building upon Prospect Theory and Hyperbolic Time Discounting models, we explore how behavioral factors influence the probability of overspending among outbound leisure travelers. We construct our data in two steps. First, we collect demographics and travel-related variables from a random sample of 314 Singaporean tourists across different age groups and income levels. Second, we conduct a field experiment to measure their risk and time preferences, specifically loss aversion and present bias. We then explore the link between the measured preferences to overspending behavior. The findings reveal an interesting link between loss aversion, present bias and traveling expenditure patterns: outbound tourists with high loss aversion and high present bias are more likely to overspend. Finally, our study also highlights the role of group identity in de-biasing. Specifically, individuals are more likely to behave according to standard economic models when making decisions in groups.
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This research assesses the effects of choice alternatives on the travel destination decisions of travelers. The decoy effect involves the addition of a new inferior alternative into a choice set, thereby increasing the choice of an existing option. Meanwhile, the compromise effect involves the addition of a new alternative into a choice set that increases selection of an existing option with nonextreme attributes, and decreases selection of options with extreme attributes. In this study, a series of scenario-based experiments is performed to determine if the decoy and compromise effects influence travel destination decisions. Results show that the decoy effect is stronger in a choice (vs. rejection) task, whereas the compromise effect is stronger in a rejection (vs. choice) task when deciding travel destinations.
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While transportation currently accounts for 23% of total global energy-related CO2 emissions, transport emissions are projected to double by 2050, driven significantly by continued high growth in global passenger demand for air travel. Addressing high growth in aviation emissions is critical to climate stabilization. Currently we rely on individual decisions to forego air travel as the means of reducing these high-risk emissions. In this paper we argue that encouraging voluntary responses to such risks cannot succeed because of the nature of human reason and the structure of the problem itself. We use decision-making theory to explore why individuals have been generally unwilling or unable to act upon these risks, and collective action theory to illustrate the futility of relying on uncoordinated actors in such cases. Participation in the high-carbon air travel regime is a social convention, and transition from social conventions requires coordination among players. Our theoretical discussions lead us to conclude that it is our moral duty to promote coordinated collective action, via national or global policy mechanisms, to address tourist aviation emissions. We offer various avenues of future research to advance this moral duty.
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This study examines the effects of residents' trust in government and their emotions toward an event on their perceptions of potential impacts and their support. This study also examines the moderating role of event attachment on the strength of relationships between residents' trust in government and their impacts perceptions, emotional responses, and as well as their support based on social exchange theory and cognitive appraisal theory. Findings clearly indicate that residents' support is a function of both cognitive and affective assessment of perceived impacts. Trust in government influences directly residents' support and indirectly through perceived impacts and experienced emotions toward an event. Findings further suggest that level of event attachment moderates the effects of trust on residents’ perceptions of impacts, their emotions, as well as on their support.
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This study examines the evolution of the city of Athens’ destination image from 2005 to 2015, in order to exploit the impact of the recent economic recession on individual perceptions. It uses advanced web content mining to analyze Tripadvisor messages that were posted in Athens Travel Forum. The findings show that the image of Athens has remained positive, facing a significant, but short-term, shift during the first years of the crisis. The findings also reveal that the destination image of Athens is only partially shared by people residing inside and outside Greece, and that non-Greek residents have more favorable perceptions towards the destination. The study expands understanding on destination image literature by demonstrating the normative nature of destination images, which - once established - can be particularly resistant to change, even during long term crises.
Article
This research examined how individual differences in anthropomorphic tendency (the tendency to humanize non-human agents/objects) influence how people respond to destination marketing communications. Specifically, this study examined whether individual-level anthropomorphic tendency and text-personification of destination marketing communications interact to influence destination attitude and travel intentions. Results from a study involving 210 Australian participants revealed that destination attitude and travel intentions were most favorable for people with high levels of anthropomorphic tendency and who were exposed to personified tourism messages. These findings indicate that text-personification represents a new communication tactic for tourism – particularly for target consumers who are high in anthropomorphic tendency – and one that can humanize the destination leading to more favorable attitudes and higher intentions to travel. This effect is mediated by positive emotions. People with high anthropomorphic tendency who are exposed to a personified advertisement feel more positive emotions, which lead to positive tourism outcomes.