UDC: 379.8 JEL: Z330
tourists' Locus of control impact on destination brands online reviews: destination employees' efficiency as a mediator
M. I. Saleh
St. Petersburg State University,
7-9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation
For citation: Saleh M. I. 2021. Tourists' locus of control impact on destination brands online reviews: Destination employees' efficiency as a mediator. Vestnik of Saint Petersburg University. Management 20 (4): 539-558. https://doi.org/10.21638/11701/spbu08.2021.403
Tourist behavior is crucial when studying tourists' reviews. Fleeting but powerful, greedy behavior drives tourists to exaggerate negativity while reviewing tourism destination brands. To date, however, the current studies on tourism have not considered the role of greed to harm destination reputations. To address the issue, this study relies on locus of control theory as one of critical theories that treat consumer behavior. The study investigates the correlation between tourists' locus of control and their review of tourism destinations in terms of the employees' efficiency at destinations. The study uses a distributed survey among 230 frequent travelers using STATA software to analyze regressions for data analysis and mediation analysis. The study uses different measurement scales with 17 items to ensure the reliability and validity of the research. The results revealed that tourists who attribute the holiday success to their choices of destinations, provide positive reviews of those destinations and do not exaggerate negative feedback in the reviews. The study also shows that employees' efficiency at the destination plays a crucial role as a mediator between tourists' locus of control and their reviews. Theoretical and managerial implications are discussed.
Keywords: greedy behavior, tourist behavior, locus of control, exaggerated reviews, word of mouth, employees' efficiency, tourists' reviews, brand attachment.
introduction
Tourism suppliers such as hotels, travel agencies, and resorts usually attract tourists to their destinations [Orth et al., 2012] because tourists are vital for the host destinations in boosting revenues and creating thousands of jobs [Jackson, 2019]. Therefore, tourism service providers tend to study the factors influencing tourists' behavior at tourism destinations to remain to attract numerous tourists [Orth et al., 2012]. Social media and online reviews are among the most crucial factors influencing tourist behavior as consumers toward tourism destinations [Lam, So, 2013]. The spread of social media has led to a significant dependence on online reviews for making decisions to visit and/or evaluate tourism destinations [Kapoor et al., 2021]. Empirically, an analysis of consumer reviews online found that 88% of consumers consider online reviews to be personal
© St. Petersburg State University, 2021
recommendations [Hlee et al., 2021] because users follow these reviews to get more information about services or products. Online reviews (OR) provide consumers with the flexibility and convenient information to evaluate and interpret potential services they would like to use [Sun et al., 2021]. Online reviews depend mainly on electronic word of mouth (e-WOM), which refers to any textual statements that describe prior experiences to potential consumers [Williams, Ferdinand, Bustard, 2019; Zhu et al., 2020]. These textual statements consider personal cautioning to use specific services [Banerjee, Chua, 2021] or personal recommendations to use services [Kapoor et al., 2021].
Therefore, online reviews could affect purchasing behavior and destinations' reputation [Sun et al., 2021]. However, online reviews have no credibility because exaggerated e-WOM on social media has become a norm among millennials, so they share fake vacation photos to satiate their dark traits [Kapoor et al., 2021]. Exaggeration in e-WOM refers to consumers over-reviewing events or explaining places or services as more dangerous than the true [Banerjee, Chua, 2021]. So, tourists as consumers may exaggerate their reviews about experiences at these destinations [Kapoor et al., 2021]. These exaggerations in online reviews can damage the destination's reputation and decrease revenues [Zhu et al., 2020].
One of the reasons for exaggeration is the feeling of greed [Crusius, Thierhoff, Lange, 2021] because greedy people respond strongly to outperforming others with negative and overacting responses, which may harm other people's experiences or service providers' reputation [Helzer, Rosenzweig, 2020]. This harm occurs because greedy individuals tend to make more prejudiced and selfish decisions than others [Crusius, Thierhoff, Lange, 2021]. They want to gain more experience without satisfaction [Krekels, Pan-delaere, 2015]. So, greedy individuals communicate with strong negative emotional responses because they do not have enough self-confidence [Mussel, Hewig, 2016; Helzer, Rosenzweig, 2020] with a high probability to ascribe events' outcomes to external causes by an external locus of control (LOC) [Jiang et al., 2020]. Locus of control or locus of causality theory provides conceptual and experimental evidence of how tourists attribute their reactions to people or events [Orth et al., 2012; Jackson, 2019]. For instance, people with an internal LOC are more likely to attribute events outcomes to themselves more than others (dispositional attribution) [Karkoulian, Srour, Sinan, 2016]. Whereas people with an external LOC are more likely to ascribe events' outcomes to external causes, such as social circumstances, powerful others, and chances [Hwang, Choe, Kim, 2020; Dunn, Jensen, Ralston, 2021].
One of the crucial factors affecting a tourist's LOC is employee efficiency and behavior [Jackson, 2019]. Positive employee behavior helps achieve the consumers' expectations about their self-confidence in the service encounter process [Wallace, de Cherna-tony, Buil, 2013; Neira, Vazquez, 2014]. Likewise, services without positive behavior will not satisfy customer needs because building consumer self-confidence requires positive employee behavior [Balmer, 2001]. Thus, employees' positive performance helps service providers preserve consumer self-confidence and self-control [Wallace, de Chernatony, Buil, 2013], leading consumers to attribute the service successes to themselves with an
internal LOC [Su, Gong, Huang, 2020]. In contrast, negative employees' behavior influences tourists to exaggerate their reviews with greedy behavior because they feel low self-confidence and attribute service failure to external causes with an external LOC (situational attribution) [Neira, Vazquez, 2014].
Notwithstanding the significant influence of employee efficiency on tourists' LOC, and the influences of LOC on tourists' satisfaction [Jackson, 2019], no previous study examines the tourists' locus of causality impacts on tourists' online reviews with the presence of employees' efficiency as a mediator. Therefore, this study aims to contribute with a new theoretical and empirical framework to investigate the correlation between tourists' locus of control on reviewing tourism destinations through employee efficiency at destinations.
The first part of the study highlights a theoretical framework under four subcat-egories: destination branding, locus of control, exaggerative reviews, and employee efficiency. The second one provides a methodology. The third part presents results and discussion and the fourth one introduces the research conclusion, provides theoretical contribution and practical implications.
theoretical framework
Destination branding. The destination is a combination of products, amenities, and services [Alexander, Teller, Wood, 2020] that establish tourists' experience before, during, and post-visit the destinations [Ruiz-Real, Uribe-Toril, Gázquez-Abad, 2020]. Tourism researchers have emphasized branding as an essential marketing element to create positive perceptions to tourists about the destinations [Chi, Huang, Nguyen, 2020] because branding services help distinguish services from others [Ruiz-Real, Uribe-Toril, Gázquez-Abad, 2020].
The importance of branding in distinguishing services from others leads tourism managers to build destination brands [Alexander, Teller, Wood, 2020] because the evolution of communication technologies enabled travelers to know more about tourist services, destinations' cultures, and heritages [Jiménez-Barreto et al., 2020]. So, destination branding helps tourism managers to distinguish their tourism destination and compete with other destinations to gain revenues and provide tourists with memorable experiences at destinations [Orth et al., 2012; Ruiz-Real, Uribe-Toril, Gázquez-Abad, 2020]. Tourism service providers find it challenging to control these services and amenities at tourism destinations because of the complexity of destination branding unexpected events [Alexander, Teller, Wood, 2020].
Tourism service providers find it challenging to control these services and amenities at tourism destinations because of unexpected events (e.g., weather) [Hankinson, 2004]. Also, the probability of experiencing service failure at destination brands is more than with other brands because of the sensitivity of tourism services [Hankin-son, 2004; Orth et al., 2012; Chi, Huang, Nguyen, 2020]. These challenges lead tourism researchers to study tourists' interpretations and judgments of their destinations' expe-
riences [Jackson, 2019]. Therefore, tourism researchers such as M. Jackson [Jackson, 2019] and L. Fong with coauthors [Fong, Lam, Law, 2017] have mentioned that locus of control theory is crucial for understanding tourist judgments and interpretations of destination events.
Locus of control. Locus of control is a crucial dimension of attribution theory which mainly asserts that people make causal inferences based on their' subjective evaluations of different events [Chang, 2008; Kim, Choi, 2018]. Locus of control significantly impacts behavioral regulations that affect individuals' interpretations [Cleveland, Kalamas, Laroche, 2012]. There are two types of individuals' LOC; the first one is internal LOC, or, in another term (an internal attribution), which considers that individuals attribute events outcome to themselves than others [Jackson, 2019; Dunn, Jensen, Ralston, 2021]. In contrast, the external LOC or, in another term (an external attribution) considers that individuals attribute events outcome to external causes than themselves such as service providers' inefficiency or luck [Hampson, Gong, Xie, 2021].
Individuals who attribute events to external causes stimulate confusion when making decisions [Hwang, Choe, Kim, 2020] because it sometimes influences contradictory sentiments when producing ideas to make decisions [Dunn, Jensen, Ralston, 2021]. In contrast, favorable outcomes are more likely to be attributed internally with an internal locus of control [Harris et al., 2006]. When individuals attribute events internally, they are more stable than attribute events to external causes [Galvin et al., 2018]. Thus, people who attribute events internally are more likely to raise their self-confidence by ascribing harmful incidents, not to themselves but external causes [Galvin et al., 2018; Jackson, 2019; Helzer, Rosenzweig, 2020]. They ascribe events to external causes to avoid self-attribution bias [Kelley, Michela, 1980; Harvey et al., 2014] and are more likely to speed negative reviews if they encounter negative experiences [Harvey et al., 2014; Baker, Kim, 2019; Hlee et al., 2021]. In an experiment by [Harris, Fisk, Sysalova, 2016], they have clarified that individuals who are most likely to ascribe events to others (external LOC) performed a significantly higher time to spread negative e-WOM, with greedy behavior [Jiang et al., 2020].
Greedy behavior and exaggerative reviews. Scholars have distinguished greedy behavior into two aspects. The first aspect is the positive side of greed which refers to the positivity of greed in promoting competition and innovation to earn more advantages than other individuals or companies [Carnevale, Carson, Huang, 2021]. Greedy personalities can work hard to earn more rewards or experience many journeys to have many experiences [Zeelenberg et al., 2020].
The second aspect is the negative aspect which indicates the desire to earn more without satisfaction [Helzer, Rosenzweig, 2020]. In most cases, when individuals attribute events to external causes, the probability of greedy behavior toward events is higher [Jiang et al., 2020] because a strong passion identifies greed individuals for gaining experiences in services without satisfaction (here, tourists at tourism destinations) [Sekhar, Uppal, Shukla, 2020; Crusius, Thierhoff, Lange, 2021]. Greedy people are aligned with goods or products and associated with excessive desires such as suc-
cess to achieve a point of view or approve the wrong speech on the right path [Razen, Stefan, 2019].
Thus, greed leads to a selfish and less cooperative attitude; empirically, there is a high positive correlation between greed and low empathy, contempt, lack of close connection with others, rebellion, excitement seeking, exploitation, and empowerment through cruelty [Mussel, Hewig, 2016]. Consequently, greed causes a hostile essence because individuals wish to over-collect benefits and use dark attribution techniques to harm others [Razen, Stefan, 2019]. Thus, greedy people seek self-gratification and self-admiration (narcissism); this leads to sadism and hatred towards destinations or individuals who provoke this hatred when showing better experiences than other people [Sekhar, Uppal, Shukla, 2020]. In an experiment by M. Razen and M. Stefan [Razen, Stefan, 2019] to detect whether greed is an outcome of competitions to show off a person's ability to gain more than others. The results indicated that greedy people increase the frequency of comments in online reviews to prove that they are more accurate than others, even if they are not correct. For instance, "the resorts services were awesome, and employees were helpful, however I would need more upgrading services". In such comments where we can find it in the tourism review platforms, we can also find the replies of service providers that "we provide the services regarding your payments' amount".
Therefore, the service providers behave in a "value of money" tendency. But greedy tourists behave that they want more even if they pay less. This leads to fake comments with difficulties discovering lies in e-WOM compared with WOM because face-to-face contact may contain deceptive signals such as increased unconscious tremors or anxiety to catch greedy people [Kapoor et al., 2021]. The internet environment is free of these things, making it a more fertile area for deception by greedy personalities [Jia, 2020].
Thus, greedy personalities will attribute service externally with blame behavior [Neira, Vazquez, 2014; Jiang et al., 2020], leading to unethical judgments based on service acquisitiveness without satisfaction. Moreover, the individuals with greedy personalities influence negligence in reviewing or lack of care about the post-truth. So, greedy people tend to lie to improve their social image, so they freely exaggerate to acquire striving-like behavior among their peers even if the service providers are efficient [Kapoor et al., 2021].
Thus, if tourists have greedy behavior, they enormously like to attribute events to external causes and may exaggerate negative word-of-mouth on social media with complex language to service providers [Baker, Kim, 2019], which may increase fake reviews [Kapoor et al., 2021]. Fake online reviews are deliberately written to reflect authenticity but trick the reader [Baker, Kim, 2019]. So, illegally skewed consumer reviews disrupt prevailing conduct codes by damaging companies' reputations [Hlee et al., 2021]. That is why there is suspicion of fraudulent manipulation of reviews by many consumers in the tourism industry and the hospitality industry [Guo, Barnes, Jia, 2017]. Given that greedy individuals are more likely to attribute events externally with negative word of mouth to gravitate the ultimate benefits from service providers. Therefore, we can hypothesize the
contradictory action that individuals who attribute events internally are more likely to spread positive online reviews and avoid greedy behavior.
Therefore, we can hypothesize that:
Hypothesis H1. Tourists who are more likely to attribute events to themselves — internal LOC — are more likely to spread positive reviews about tourism destinations than those who have — external LOC.
Moreover, when a tourists attribute events to themselves and positively review the destination, this internal attribution assembles their self-identity, introduces themselves to others, and judges destination events [Jackson, 2019]. This influences tourists' motivations to positively interpret service providers' [Kaplan et al., 2010]. These favorable judgments and attribution toward events lead to positive emotions to destination image [Konecnik, Gartner, 2007] and satisfaction [Beerli, Martin, 2004] with tourism destination brands [Chi et al., 2020] by building an attachment and loyalty with that destination brands [Orth et al., 2012]. Destination attachment (DA) is the strength of emotionally connecting oneself with the destination [Grisaffe, Nguyen, 2011]. It leads to spreading positive word-of-mouth and revisiting tourism destinations [Stylos et al., 2016]. Consequently, destination attachment positively influences stable attribution and minimizes destination switching [Kaplan et al., 2010; Ruiz-Real, Uribe-Toril, Gazquez-Abad, 2020]. Hence, this helps increase stable revenues to tourism destination brands [Jimenez-Bar-reto et al., 2020; Grisaffe, Nguyen, 2011]. Therefore, we can hypothesize that:
Hypothesis H2. Internal attributions with (internal locus of control) influence tourists to attach to destinations.
Self-employees' efficiency (EE) (mediator). Tourists who have a high level of confidence organize their trip with a high expectation that they will receive a positive experience all the time [Jackson, 2019]. Unfortunately, experiencing perfect service is inevitable [Swanson, Kelley, 2001; Jackson, 2019]. In most cases, tourists may receive inadequate services in tourism destination brands [Beerli, Martin, 2004; Ruiz-Real, Uribe-Toril, Gazquez-Abad, 2020]. Service failure may occur because of failure to match consumers' (here tourists) preferences [Mccoll-Kennedy, Sparks, 2003], but the most common reason for the service failure is the employees' inefficiency [Yeh, 2013]. On the one hand, tourism employees' efficiency refers to the sense of positive actions and high productivity to provide high-quality tourism services during tourists' holidays [Fang, Zhang, Li, 2020]. There is substantial research supporting that tourism employees play a dominant role in maintaining tourists' satisfaction by helping them matching their expectations [Suhartanto et al., 2018]. On the other hand, employee's inefficiency during tourists' holidays leads to destructive behavior from employees to consumers [Suhartanto et al., 2018], which lead tourists to negatively attribute their holidays to tourism service providers [Fang, Zhang, Li, 2020], and spread negative e-word of mouth [Jackson, 2019]. Tourists use e-WOM more than WOM to express their experiences [Orth et al., 2012]. Tourists post online reviews to retell and criticize their travel experiences; reviews on websites could be five scale-points or textual explanations [Jia,
2020] to dedicate the level of satisfaction or dissatisfaction with the tourism services at destinations. Thus, travelers use the information obtained by e-WOM to identify service components, advantages, and disadvantages and predict service trends [Li, Tung, Law, 2017]. Thus, in employees' inefficiency (vs employees' efficiency), tourists who experience inadequate services are more likely to have different attributions toward service providers [Neira, Vazquez, 2014] before the judgments and/or spread WOM about various events at destinations [Jackson, 2019]. Therefore, we can hypothesize that:
Hypothesis H3. Employees' efficiency mediates the tourists' locus of control and positive destination online reviews.
The following figure explains the relationship between all suggested hypotheses (Figure 1).
Figure 1. The study conceptual framework
The Figure 1 indicates that when tourists attribute the events' outcomes to themselves, they are more likely to spread online positive WOM and attach to the destination. However, this internal attribution outcome with the presence of employees' efficiency could differ.
The study uses a quantitative methodology to test the suggested conceptual framework using the multiple regression formula regarding the previous assumptions. The results are supposed to help fathom the essence behind tourists' attribution toward different events in the tourism destinations.
methodology
The study uses quantitative analysis with STATA software to test the hypothesis with analyzing (respondent profiles, mediation, and regression analysis for data analysis). The questionnaire was distributed through online tourism groups on Facebook (e.g., travel experience, and travel secret club), mainly frequent travelers who have visited the Red Sea resorts/hotels in Egypt. As for filling out the questionnaires, the respondents filed the survey online because of the COVID-19 pandemic and social distance requirements. A total of 230 surveys were distributed to Egyptian tourists who have visited Red Sea resorts for leisure activities. The number of valid surveys after collecting them was 230, with a response rate of 84%. The participants were asked to determine their gender, age, and educational background in the socio-demographic part of the survey, and all these variables were coded as a typical variable (Table 1).
Table 1. The respondents' profile
Demographic item Code Number Percentage, %
Gender Male 1 92 40
Female 2 138 60
Age 20-30 1 184 80
31-40 2 16 6.7
41-50 3 30 13.3
Educational background High school or general educational development 1 16 6.7
Associate degree 2 85 36.9
Bachelor's degree 3 107 46.7
Master's degree 4 22 9.7
In this study, the number of female participants is 60% compared to 40% for males. The participants also differed in ages, but most participants were between 20 and 30 years old with 80%. The highest percentage of the youth age is because young tourists primarily engage in leisure activities. Participants' educational background mostly associate degree with 36.9% and bachelor's degree with 46.7%.
Regarding reliability and the study validity, the scale's samples contain 17 elements that help measure and test the study hypothesis (Table 2).
Table 2. The study measurement scale
Construct Item Source (adapted from) Description Code
1 Locus of control My holiday experiences' events in Red Sea resort are outcomes of my trip preparation [Jackson, 2019; Toti, Diallo, Huaman-Ramirez, 2021] Tourist locus of control: here, tourists attributing their experiences' events to themselves more than others with an internal LOC LOC
I can pretty much determine what will happen during my journey to the Red Sea resort
My holiday experience' events in the Red Sea resort are outcomes of my ability to enjoy every moment
I am usually able to protect my interests during my journey in the Red Sea resort
2 Destination attachment I miss the destination when I am not there [Orth et al., 2012; Deb, Lomo-David, 2021] Destination attachment: here, tourists consider that they belong to the destination with a high attachment level DA
I know the destination very well
I defend the destination when somebody criticizes it
I feel secure in this destination
3 Online reviews I have recommended this destination to lots of people on the Internet [Orth et al., 2012; Jia, 2020; Deb, Lomo-David, 2021] Online reviews: the tourists recognize that this place has good quality to spread positive electronic word of mouth about the destination rather than exaggerate their reviews OR
I "talk up" about the destination to my friends on the Internet
I try to spread the good word about the destination in general on the Internet
I have recommended this destination to lots of people on the Internet
4 Employees' efficiencies Efficient staff [Harris et al., 2006; Chau, Yan, 2021] Employees' efficiencies: here, the tourist recognizes that employees play a crucial role in facilitating the itinerary elements EE
Caring staff
Polite staff
Friendly staff
Helpful staff
The calculations of Composite Reliability (CR), Average Variance Extracted (AVE), and Cronbach alpha use conventional threshold criteria (0.7) for CR and Cronbach's alpha; as for AVE, it is suggested to be from 0.5 to 0.8 according to [Hair et al., 2016]. The results showed that Cronbach alpha was higher than 0.07, and CR was between 0.80 and 0.90. AVE for constructs is between 0.6 and 0.7, proving that the structure has high internal reliability of all elements [Golafshani, 2003]. Regarding the validity: convergent viability can be estimated using correlation coefficients for the 17 items. The successful evaluation of converging validity demonstrates that testing concepts are closely related to other experiments designed in theory to measure the same ideas or that the correlation between items is high [Stober, 2001]. The correlation coefficients for items are related to the primary constructs it meant to be measured with high correlation and significance according to ¿-value (Table 3). Consequently, the measures significantly differentiate structures, indicating that the factors represent structures with a convergent validity.
results and discussion
To test the hypotheses H1, H2, and H3, the study computed the mean average of all constructs in an excel sheet, then uploaded it on STATA software to test the regressions. The results show that the correlation between the average mean of LOC and the average mean of OR is statistically significant withp < 0.05 and (^ = 0.50, ¿-value = 5.1) (Table 3).
Table 3. Hypothesis analysis results
Hypothesis Relationship ß f-value p-value Hypothesis status
Hypothesis H1 LOC-OR 0.50 5.14*** 0.000 Supported
Hypothesis H2 LOC-DA 0.35 3.26*** 0.001 Supported
LOC-OR (without the EE presence) 0.50 5.14*** 0.000 Supported
LOC-^ OR (with the EE presence) 0.42 4.48*** 0.000 Supported
Hypothesis H3 LOC-EE 0.30 2.62*** 0.009 Supported
EE-OR 0.25 3.35*** 0.001 Supported
LOC-EE-OR (indirect effects) 0.08 2.07** 0.030 Supported
Notes: 1) 6 — standardized path; 2) *— p < 0.05; p < 0.01; p < 0.001. 548 Вестник СПбГУ. Менеджмент. 2021. Т. 20. Вып. 4
Thus, with a one-unit increase in attributing experiences' events with an internal LOC, the probability of increasing positive reviews about the destination will be 50%. The result refers to the fact that when tourists internally attribute experiences' events with an internal LOC, this encourages them to positively review the destination with low greedy behavior [Banerjee, Chua, 2021]. This, in turn, eliminates the deception of greed behavior when exaggerating the reviews toward services [Zeelenberg et al., 2020]. This, in turn, influences tourists to spread positive word of mouth about destinations rather than fake reviews [Lam, So, 2013].
Moreover, the correlation between the average mean of LOC and the average mean of DA is statistically significant with p < 0.05 (P = 0.35, ¿-value = 3.2). So, with a one-unit increase in tourists' locus of control, the destination attachment will be increase by 35%. This result explains that tourists who internally attribute experiences' events with an internal LOC are more likely to ascribe the event causes to self-internal success [Jiang et al., 2020]. This eliminates ascribing causes to external causes with low self-attribution bias. Thus, it leads to positive emotions toward events, then positive feelings toward destinations [Jackson, 2019]. These positive feelings influence tourist attachment with tourism destination brands [Orth et al., 2012].
As for hypothesis H3, the study follows the R. Baron and D. Kenny [Baron, Kenny, 1986] mediation mechanism and applies mediation sensitivity analysis. Thus, mediation analysis comprises three sets of the average mean of the following regressions: IV (independent variable) ■ DV (dependent variable), IV ■ M (mediator), and IV + M ■ DV, as mentioned in table 3. The following three equations will clarify more precisely how does the mechanism of the mediation.
OR = p0 + p1(LOC) + e1. (1)
Here the first equation refers to testing the overall effect of LOC on OR (without considering mediation EE) when the average mean of online reviews is the DV, and the average mean of LOC is the IV; the results refer that this relationship is statistically significant with p < 0.05 (P = 0.50, ¿-value = 5.1).
EE = y0 + Y1 (LOC) + e2. (2)
The second equation refers to testing the direct effect of the average mean of LOC as IV on the average mean of EE as DV; the results refer that this relationship is statistically significant with p < 0.05 (P = 0.30). So, every unit increases in attributing events internally with an internal LOC, this could encourage service providers to enhance their efficiency by 30%; this occurs because individuals with a high LOC are considered to have sufficient information and experiences that could help employees to enhance their work efficiency [Kelley, Michela, 1980].
OR = p~ 0 + P"1 (LOC) + 81 (EE) + s3. (3)
In the third equation, DV is the average mean of OR (online reviews), the IV is the average mean of LOC (locus of control), and the average mean of EE (employees' efficiency) is the hypothesized mediator variable that is supposed to transmit the causal effect between LOC and OR.
As Figure 2 illustrates, the standardized regression coefficient is statistically significant between LOC on OR (with the presence of EE) (P = 0.42, p < 0.05) and standardized regression coefficient between EE on OR (P = 0.25,p < 0.05) is also statistically significant.
Figure 2. The hypotheses test for the study
Therefore, the standardized indirect effect was (0.30) *(0.25) = (P = 0.08) which is also statistically significant with p < 0.05. Thus, with a high level of efficiency of the service provider at destinations, the probability that tourists who internally attribute experiences' events with an internal LOC will spread more positive word of mouth [Park et al., 2010] and avoid any exaggerative reviews about the destination is around 9%. This reflects those employees at destinations could affect tourists' trip itineraries [Chau, Yan, 2021]. Here, tourists who have high expectations about destinations with an internal LOC (vs. external LOC) could be influences by employee's behavior [Jackson, 2019]. This, in turn, may affect tourists' reviews about destinations if tourists' expectations match the reality (vs. not) because of employee's efficiency (vs. inefficiency) at destinations.
As mentioned, when tourists have the probability of ascribing the service success to themselves, they are more likely to have attachment and spread positive e-WOM. However, the gap in the direct effect of regression coefficient between LOC to OR (0.50) and LOC to OR with EE presence (0.42) reveals a crucial fact: "tourists' external LOC". Tourists' external LOC clarifies that tourists are affected by external factors that could lead tourists to attribute the events' outcome to the tourism service providers [Kelley, Michela, 1980]. When tourists attribute tourism events outcomes to external causes, this
could be for two reasons [Jackson, 2019]: the service providers are too helpful or have inefficiency. In both cases, tourists are more likely to be affected by the external factors that lead them to eliminate (vs. not) their internal attribution effects on OR. This, in turn, leads to the indirect impacts for the Internal LOC on the OR.
According to Gauss-Markov theorem assumptions, when the mediator is treated as exogenous, this means that the correlation between the factors which affect the mediator (EE) and factors that affect the outcome (OR) will be zero [Harville, 1976]. Thus, the study also uses sensitivity analysis because when EE is treated as endogenous according to equation (2) (EE = y0 + y1 (LOC) + s2) and then as exogenous in equation (3) (OR = 0 + p~1 (LOC) + 81 (EE) + s3), there will be a relationship between EE and the error term. Thus, the study tends to clarify how sensitive the mediation effect's estimate will depend on the correlation between the EE as a mediator and the error term. Figure 3 shows that the estimated mediation effect correspondingly (Average Causal Mediated Effect — ACME) to each parameter row's value (the correlation between the factors that influence the employees' efficiency and the factor that affects online reviews).
ACME(P)
1 ----------------------------------------------------------------
-1 _
-1 -0.5 0 0.5 1
Sensitivity parameter: p
Figure 3. Mediation sensitivity graph Note: confirmation interval — 95%.
Here, the graph line indicates that the mediation effect is positive in most parameter low levels; when the sensitivity parameter equals 0, the mediation is (0.10) with the correlations between factors that affect EE and OR. Therefore, employees' efficiency is crucial to preserving an increasing online positive review of tourism destination brands.
conclusion
Tourism suppliers tend to maintain tourists' attachment to destination brands because tourists are vital for the host destinations to gain revenues [Jackson, 2019]. This led tourism destination managers to pay more attention to the tourists' online reviews as an essential dimension to fathom the essence behind tourists' interpretations about their destinations [Lam, So, 2013]. Also, destination managers want to avoid exaggerated, greedy reviews, which may harm the destination's reputation [Banerjee, Chua, 2021]. Hence, this study focuses on studying tourists' locus of control theory to predict tourists' reviews toward destinations. Locus of control theory is one of the crucial theories investigating how individuals believe that they can control their judgments and interpretations toward different events [Jackson, 2019]. Thus, this study addresses LOC theory to understand tourists' variations in reviews toward destination events through a crucial mediator: employees' efficiency at destinations. Employees' efficiency at destinations plays a vital role in online tourist reviews [Chau, Yan, 2021].
Employees' efficiency help achieve the consumers' expectations about their self-confidence in the service encounter process [Wallace, de Chernatony, Buil, 2013]. Therefore, the current study examines tourists' internal LOC impacts on tourists' online reviews through employees' efficiency at destinations. The study uses quantitative analysis by surveying 180 Egyptian tourists engaged in leisure activities in the Red Sea. The results reveal that tourists who attribute experiences' events with an internal LOC are more likely to positively review destinations with a strong attachment. The study also shows that employees' efficiency plays a crucial role in mediating tourists' locus of control and tourists' reviews. Thus, with a high level of efficiency of the service provider at destinations (vs. low), the probability that tourists attribute experiences with an internal LOC will spread more positive word of mouth and avoid any exaggerative reviews about the destination.
Therefore, this study has a manifold theoretical contribution and practical implications. As for theoretical contribution, On the one hand, the study expands previous studies of destination marketing in the tourism field, so this study adds to [Alexander, Teller, Wood, 2020; Chi, Huang, Nguyen, 2020; Jiménez-Barreto et al., 2020; Ruiz-Real, Uribe-Toril, Gázquez-Abad, 2020] by providing a locus of control as a crucial new construct that affects tourist interpretation toward tourism destination brands. Besides, this study contributes to the tourism literature by providing empirical evidence of how employees' efficiency mediates the relationship between destination brands' online reviews and tourists' locus of control. Besides, this study broadens the numerous electronic WOM studies in destination marketing literature by a crucial physiological factor: the greedy attitude that can destroy positive e-WOM and online reviews.
On the other hand, this study responds to [Kapoor et al., 2021] to study and explore the motivations that lead a person to exaggerate reviews online. This could negatively or positively affect destination tourism by exaggerating online reviews. Thus, this study examines these calls and provides empirical evidence that internal LOC could mitigate
greedy behavior to tourism destination brands and marketing through a crucial mediator: employee efficiency.
The study provides prominent insights to mitigate the greedy tourist's behavior that can sabotage tourism destinations by exaggerating online reviews, especially for leisure destination managers as an outcome of the study respondents. Leisure destination managers should follow TripAdvisor's popular tips to respond to negative reviews rather than positive ones. These tips include insights about "when" and "how" tourism managers could respond to the negative comments by highlighting their priority on staff efficiency. So, destination managers should focus on these statements, clarify any hostile actions from employees, and take reasonable efforts to recover these problems.
Moreover, leisure destination managers could use the twelve algorithms proposed by [Zhu et al., 2020] to explain why and how destinations prioritize their response strategies; mainly, managers have to use these algorithms to respond firstly to the reviews about staff efficiency. These algorithms can provide tourism managers with prominent tools to predict the significance of incoming tourists' reviews. Tourism managers also are recommended to hire professionally trained employees to respond to these greedy reviews. They can spot these fake reviews and then react to them by providing visual evidence of the staff's efficiency. Visual evidence instead of transcripts increases the response's reliability, especially in the tourism industry [Guo, Barnes, Jia, 2017].
Besides, leisure destination managers should identify where tourists pay more attention to consider prior tourists' reviews before making travel decisions. According to [Guo, Barnes, Jia, 2017], tourists concentrate on appraising reviews about room experiences and service quality over cleanliness, location, and value for money. Therefore, tourism managers have to increase the training budget for room service staff and front office staff who work directly with tourists. This will help other tourists to neglect these greedy reviews and support destinations' performance with self-confidence. This reflects that feeling confident about the destination increases the positive locus of control and satisfaction with employees' efficiency [Jackson, 2019]. Employees' efficiency is a mediator between LOC and online reviews; hence, it would be reasonable for destination managers to launch frequent training and professional workshops to improve self-behavior proficiency for the staff who work directly with tourists, as recommended by [Wallace, de Chernatony, Buil, 2013]. Thus, destination managers need to develop professional human resource management systems that minimize negative legislations at work and maximize the positive effects of the human resource management system on employee perception (e.g., Incentives and Recognition) [Mccoll-Kennedy, Sparks, 2003].
This study has some limitations. First, locus of control is one of the three dimensions of attribution theory (controllability, stability, and locus of control). Therefore, future studies are recommended to study the other dimensions (stability and controllability) with their impacts on tourists' online reviews. Second, this study focuses on leisure destinations in Egypt and Egyptian tourists as study samples. Therefore, future studies are recommended to study different nationalities and tourism destination types
and measure how tourists' LOC could affect tourists' WOM (e.g., culture, sport, etc.). Additionally, the study treats the independent variable construct mainly with tourists' internal LOC. Future research is recommended to treat external LOC as an independent variable. All constructs' mean averages were rounded to the nearest integer at the coding stage in the coding process. The reason behind that is the averages are almost biased to integer without numeric fractions. However, the study was supposed to replicate the study with a complete structure model to test all variable load factors on the latent variable — constructs — and test the relations. Therefore, the next studies should use path structure model analysis rather than mean averages to study tourists' attribution toward different events in tourism destinations.
Acknowledgments
The researcher would like to thank Karina A. Bogatyreva, Associate Professor of Strategic and International Management Department, Director of the Center for Entrepreneurship, GSOM SPbSU, for her supportive, most generous, and thoughtful efforts to help the researcher in his studies.
References
Alexander A., Teller C., Wood S. 2020. Augmenting the urban place brand — On the relationship between markets and town and city centers. Journal of Business Research 116 (August): 642-654. Baker M. A., Kim K. 2019. Value destruction in exaggerated online reviews: The effects of emotion, language, and trustworthiness. International Journal of Contemporary Hospitality Management 31 (4): 1956-1976.
Balmer J. M. T. 2001. Corporate identity, corporate branding and corporate marketing — Seeing
through the fog. European Journal of Marketing 35 (3): 248-291. Banerjee S., Chua A. Y. 2021. Calling out fake online reviews through robust epistemic belief. Information & Management 58 (3): 103445. Baron R. M., Kenny D. A. 1986. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 51 (6): 1173.
Beerli A., Martín J. D. 2004. Tourists' characteristics and the perceived image of tourist destinations: A quantitative analysis — A case study of Lanzarote, Spain. Tourism Management 25 (5): 623-636. Carnevale J. B., Carson J. E., Huang L. 2021. Greedy for thee or greedy for me? A contingency model of positive and negative reactions to leader greed. Journal of Business Research 132 (August): 897-905.
Chang J. C. 2008. Tourists' satisfaction judgments: An investigation of emotion, equity, and attribution. Journal of Hospitality & Tourism Research 32 (1): 108-134. Chau S., Yan L. 2021. Destination hospitality indicators. Journal of Destination Marketing & Management 19 (March): 100537. Chi H. K., Huang K. C., Nguyen H. M. 2020. Elements of destination brand equity and destination familiarity regarding travel intention. Journal of Retailing and Consumer Services 52 (January): 101728.
Cleveland M., Kalamas M., Laroche M. 2012. "It's not easy being green": Exploring green creeds, green
deeds, and internal environmental locus of control. Psychology & Marketing29 (5): 293-305. Crusius J., Thierhoff J., Lange J. 2021. Dispositional greed predicts benign and malicious envy. Personality and Individual Differences 168 (January 2021): 110361.
Deb M., Lomo-David E. 2021. Determinants of word of mouth intention for a World Heritage Site: The case of the Sun Temple in India. Journal of Destination Marketing & Management 19 (March): 100533.
Dunn B., Jensen, M. L., Ralston R. 2021. Attribution of Responsibility after Failures within Platform Ecosystems. Journal of Management Information Systems 38 (2): 546-570.
Fang S., Zhang C., Li Y. 2020. Physical attractiveness of service employees and customer engagement in tourism industry. Annals of Tourism Research 80 (January): 102756.
Fong L. H. N., Lam L. W., Law R. 2017. How locus of control shapes intention to reuse mobile apps for making hotel reservations: Evidence from Chinese consumers. Tourism Management 61 (August): 331-342.
Galvin B. M., Rande A. E., Collins B. J., Johnson R. E. 2018. Changing the focus of locus (of control): A targeted review of the locus of control literature and agenda for future research. Journal of Organizational Behavior 39 (7): 820-833.
Golafshani N. 2003. Understanding reliability and validity in qualitative research. The Qualitative Report 8 (4): 597-607.
Grisaffe D. B., Nguyen H. P. 2011. Antecedents of emotional attachment to brands. Journal of Business Research 64 (10): 1052-1059.
Guo Y., Barnes S. J., Jia Q. 2017. Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation. Tourism Management 59 (April): 467-483.
Hair J. F., Jr., Hult G. T. M., Ringle C., Sarstedt M. 2016. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications.
Hampson D. P., Gong S., Xie Y. 2021. How consumer confidence affects price conscious behavior: The roles of financial vulnerability and locus of control. Journal of Business Research 132 (August): 693-704.
Hankinson G. 2004. Relational network brands: Towards a conceptual model of place brands. Journal of Vacation Marketing 10 (2): 109-121.
Harris K. E., Grewal D., Mohr L. A., Bernhardt K. L. 2006. Consumer responses to service recovery strategies: The moderating role of online versus offline environment. Journal of Business Research 59 (4): 425-431.
Harris L. C., Fisk R. P., Sysalova H. 2016. Exposing Pinocchio customers: Investigating exaggerated service stories. Journal of Service Management 27 (2): 63-90.
Harvey P., Madison K., Martinko M., Crook T. R., Crook T. A. 2014. Attribution theory in the organizational sciences: The road traveled and the path ahead. Academy of Management Perspectives 28 (2): 128-146.
Harville D. 1976. Extension of the Gauss-Markov theorem to include the estimation of random effects. The Annals of Statistics 4 (2): 384-395.
Helzer E. G., Rosenzweig E. 2020. Examining the role of harm-to-others in lay perceptions of greed. Organizational Behavior and Human Decision Processes 160 (September): 106-114.
Hlee S., Lee H., Koo C., Chung N. 2021. Fake reviews or not: Exploring the relationship between time trend and online restaurant reviews. Telematics and Informatics 59 (June): 101560.
Hwang J., Choe J. Y. J., Kim J. J. 2020. Strategy for enhancing the image of edible insect restaurants: Focus on internal environmental locus of control. Journal of Hospitality and Tourism Management 45 (December): 48-57.
Jackson M. 2019. Utilizing attribution theory to develop new insights into tourism experiences. Journal of Hospitality and Tourism Management 38 (March): 176-183.
Jia S. S. 2020. Motivation and satisfaction of Chinese and US tourists in restaurants: A cross-cultural text mining of online reviews. Tourism Management 78 (June): 104071.
Jiang X., Hu X., Liu Z., Sun X., Xue G. 2020. Greed as an adaptation to anomie: The mediating role of belief in a zero-sum game and the buffering effect of internal locus of control. Personality and Individual Differences 152 (January): 109566.
Jimenez-Barreto J., Rubio N., Campo S., Molinillo S. 2020. Linking the online destination brand experience and brand credibility with tourists' behavioral intentions toward a destination. Tourism Management 79 (August): 104101.
Kaplan M. D., Yurt O., Guneri B., Kurtulus K. 2010. Branding places: Applying brand personality concept to cities. European Journal of Marketing44 (9): 1286-1304.
Kapoor P. S., Balaji M. S., Maity M., Jain N. K. 2021. Why consumers exaggerate in online reviews? Moral disengagement and dark personality traits. Journal of Retailing and Consumer Services 60 (May): 102496.
Karkoulian S., Srour J., Sinan T. 2016. A gender perspective on work-life balance, perceived stress, and locus of control. Journal of Business Research 69 (11): 4918-4923.
Kelley H. H., Michela J. L. 1980. Attribution theory and research. Annual Review of Psychology 31 (1): 457-501.
Kim S., Choi S. M. 2018. Congruence effects in post-crisis CSR communication: The mediating role of attribution of corporate motives. Journal of Business Ethics 153 (2): 447-463.
Konecnik M., Gartner W. C. 2007. Customer-based brand equity for a destination. Annals of Tourism Research 34 (2): 400-421.
Krekels G., Pandelaere M. 2015. Dispositional greed. Personality and Individual Differences 74 (February): 225-230.
Lam D., So A. 2013. Do happy tourists spread more word-of-mouth? The mediating role of life satisfaction. Annals of Tourism Research 43 (October): 646-650.
Li N., Tung V., Law R. 2017. A fuzzy comprehensive evaluation algorithm for analyzing electronic word-of-mouth. Asia Pacific Journal of Tourism Research 22 (6): 592-603.
Mccoll-Kennedy J. R., Sparks B. A. 2003. Application of fairness theory to service failures and service recovery. Journal of Service Research 5 (3): 251-266.
Mussel P., Hewig J. 2016. The life and times of individuals scoring high and low on dispositional greed. Journal of Research in Personality 64 (October): 52-60.
Neira C. V., Vazquez V. R. 2014. Intentionality attributions and humiliation: The impact on customer behavior. European Journal of Marketing 48 (5): 10-11.
Orth U. R., Stockl A., Veale R., Brouard J., Cavicchi A., Faraoni M., Larreina M., Lecat B., Olsen J., Rodriguez-Santos C., Santini C., Wilson D. 2012. Using attribution theory to explain tourists' attachments to place-based brands. Journal of Business Research 65 (9): 1321-1327.
Park C. W., Macinnis D. J., Priester J., Eisingerich A. B., Iacobucci D. 2010. Brand attachment and brand attitude strength: Conceptual and empirical differentiation of two critical brand equity drivers. Journal of Marketing74 (6): 1-17.
Razen M., Stefan M. 2019. Greed: Taking a deadly sin to the lab. Journal of Behavioral and Experimental Economics 81 (August): 164-171.
Ruiz-Real J. L., Uribe-Toril J., Gazquez-Abad J. C. 2020. Destination branding: Opportunities and new challenges. Journal of Destination Marketing & Management 17 (September): 100453.
Sekhar S., Uppal N., Shukla A. 2020. Dispositional greed and its dark allies: An investigation among prospective managers. Personality and Individual Differences 162 (August): 110005.
Stober J. 2001. The Social Desirability Scale-17 (SDS-17): Convergent validity, discriminant validity, and relationship with age. European Journal of Psychological Assessment 17 (3): 222.
Stylos N., Vassiliadis C. A., Bellou V., Andronikidis A. 2016. Destination images, holistic images and personal normative beliefs: Predictors of intention to revisit a destination. Tourism Management 53 (April): 40-60.
Su L., Gong Q., Huang Y. 2020. How do destination social responsibility strategies affect tourists' intention to visit? An attribution theory perspective. Journal of Retailing and Consumer Services 54 (May): 102023.
Suhartanto D., Dean D., Nansuri R., Triyuni N. N. 2018. The link between tourism involvement and service performance: Evidence from frontline retail employees. Journal of Business Research 83 (February): 130-137.
Sun M., Chen J., Tian Y., Yan Y. 2021. The impact of online reviews in the presence of customer returns. International Journal of Production Economics 232 (February): 107929. Swanson S. R., Kelley S. W. 2001. Service recovery attributions and word-of-mouth intentions. European Journal of Marketing 35 (2): 194-211. Toti J. F., Diallo M. F., Huaman-Ramirez R. 2021. Ethical sensitivity in consumers' decision-making: The mediating and moderating role of internal locus of control. Journal of Business Research 131 (July): 168-182.
Wallace E., de Chernatony L., Buil I. 2013. Building bank brands: How leadership behavior influences
employee commitment. Journal of Business Research 66 (2): 165-171. Williams N. L., Ferdinand N., Bustard J. 2019. From WOM to aWOM — The evolution of unpaid
influence: A perspective article. Tourism Review 75 (1): 314-318. Yeh C. M. 2013. Tourism involvement, work engagement and job satisfaction among frontline hotel
employees. Annals of Tourism Research 42 (July): 214-239. Zeelenberg M., Seuntjens T. G., van de Ven N., Breugelmans S. M. 2020. When enough is not enough: Overearning as a manifestation of dispositional greed. Personality and Individual Differences 165 (October): 110155.
Zhu J. J., Chang Y. C., Ku C. H., Li S. Y., Chen C. J. 2020. Online critical review classification in response strategy and service provider rating: Algorithms from heuristic processing, sentiment analysis to deep learning. Journal of Business Research 129 (May): 860-877.
Received: June 7, 2021 Accepted: September 20, 2021
Contact information
Mahmoud Ibraheam Saleh — Postgraduate Student; st084542@gsom.spbu.ru
воздействие локусл контроля туристов на онлАйн-отзывы о туристических направлениях: медиационный эффект качества работы сотрудников
М. И. Салех
Санкт-Петербургский государственный университет,
Российская Федерация, 199034, Санкт-Петербург, Университетская наб., 7-9
Для цитирования: Saleh M. I. 2021. Tourists' locus of control impact on destination brands online reviews: Destination employees' efficiency as a mediator. Вестник Санкт-Петербургского университета. Менеджмент 20 (4): 539-558. https://doi.org/10.21638/11701/spbu08.2021.403
Особенности поведения туристов во многом определяют их подход к написанию отзывов о туристических направлениях. Чрезмерная требовательность побуждает их преувеличивать негативные эмоции при оценке брендов туристических направлений. Однако в современных исследованиях такой тип поведения и его роль в нанесении ущерба репутации направлений еще не установлены. В основе исследования лежит теория локуса контроля как одна из важнейших теорий оценки потребительского поведения. В работе рассматривается связь между локусом контроля туристов и их оценкой туристических направлений с учетом эффективности сотрудников курорта. Эмпирические данные получены в результате опроса 230 активных путешественников с использованием устоявшихся и
апробированных шкал для измерения переменных. Установлено, что туристы, которые приписывают успешность поездки своему выбору и хорошей подготовке к путешествию, положительно отзываются о направлениях, а не преувеличенно критичны по отношению к ним. Продемонстрировано, что эффективность сотрудников курорта играет важную роль в качестве медиатора между локусом контроля туристов и риторикой их отзывов. Ключевые слова: чрезмерная требовательность, туристическое поведение, локус контроля, преувеличенные отзывы, сарафанное радио, эффективность сотрудников, отзывы туристов, привязанность к бренду.
Статья поступила в редакцию 7 июня 2021 г. Статья рекомендована к печати 20 сентября 2021 г.
Контактная информация
Салех Махмуд Ибрагим — аспирант; st084542@gsom.spbu.ru