Proceedings of 21st International Business Research Conference

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Proceedings of 21st International Business Research Conference
10 - 11 June, 2013, Ryerson University, Toronto, Canada, ISBN: 978-1-922069-25-2
Applying the Extended Technology Acceptance Model to
Understand Online Purchase Behavior of Travelers
Robin Nunkoo*, T. D. Juwaheer** and Tekranee Rambhunjun***
This paper seeks to establish the relationships between travelers’
attitude, perceived ease of use, perceived usefulness, trust, perceived
risk and online purchase intention of tourism and travel related products
by using an extended technology acceptance model. Primary data were
collected using a self- structured questionnaire from 150 travelers
visiting Mauritius in 2012. Seven out of eight hypotheses tested were
supported. Perceived ease of use was not a significant predictor of
attitude towards online purchasing. The model can assist destination
marketing practitioners to better understand the online purchasing
behavior of travelers.
Field: Marketing
1. Introduction
The travel sector is rated among the top three product/ service categories purchased via
the Internet (Eric et.al, 2006). Use of the Internet is becoming a positive trend and an
important core competency for hospitality businesses due to the fact that travel related
services are among the fastest emergent areas for e-commerce (Yeh et al., 2005).
However, the dramatic development of commerce through the Internet has also brought
forth many new challenges. Risks arising from lack of human contact, lack of previous
experience could also impede on consumers’ trust in e-commerce. Trust is recognized
as a vital key for an e-vendor for customer retention (Reichheld and Schefter 2000).
The full potential of tourism e-commerce can only be achieved if the determinants of
travelers’ online purchase intent are known to researchers and practitioners. This
research extends the use of technology acceptance model (TAM) to investigate the
online purchase behavior of travelers by including perceived risks and trusts in the
model.
2. Literature Review: Technology Acceptance Model
According to Pavlou (2003), online purchase intention is defined as a situation where a
consumer is willing and intends to make online transactions. Online purchase intentions
are explained in part by the TAM (Davis 1989). The TAM model (Figure 1) constitutes of
two belief factors namely: perceived usefulness and perceived ease of use, which are
predictors of user attitude towards using technology. In turn, the latter influences
behavioral intentions. Perceived ease of use also influences perceived usefulness of
technology.
______________________________________________________________________
*Dr. Robin Nunkoo, Department of Management, University of Mauritius, E-mail: [email protected]
** Dr T.D Juwaheer, Department of Management, University of Mauritius, E-mail: [email protected]
*** Miss Tekranee Rambhunjun, MSc Marketing Management student, University of Mauritius,
E-mail: [email protected]
Proceedings of 21st International Business Research Conference
10 - 11 June, 2013, Ryerson University, Toronto, Canada, ISBN: 978-1-922069-25-2
Figure 1: Technology Acceptance Model
Perceived
Usefulness
Attitudes
towards
using
Behavioural
intention to
use
Actual
Usage
Perceived Ease
of Use
Source: Original Technology Acceptance Model (Davis 1989)
2.1 Perceived Usefulness
According to Davis et al., (1989), perceived usefulness (PU) can be explained as the
extent to which the consumer believes that using the system can increase his/ her
performance. From a perspective of e-commerce in tourism, perceived usefulness may
be defined as the prospective traveler’s subjective probability that using the Internet will
efficiently facilitate his/her purchasing tourism and travel service/product. Chen et al.,
(2002), Childers et al., (2001) and Heijden et al., (2001) found that perceived usefulness
affects attitudes towards online shopping. Other researchers (Heijden et al., 2001;
Koufaris, 2002; Pavlou, 2001) have also found that PU influences the purchase
intention of potential Internet shoppers. Thus:
H1: There is a direct positive relationship between perceived usefulness and attitude
towards online purchasing.
H2: There is a direct positive relationship between perceived usefulness and intention
towards online purchasing of tourism and travel related products.
2.2. Perceived Ease of Use
Perceived ease-of-use (PEOU) is defined as the degree to which a person believes that
using a particular system would be free from effort (Davis, 1989). Many researchers
(e.g. Aladwani, 2002; Moon & Kim, 2001) have studied the relationship between
perceived ease of use and perceived usefulness. Nonetheless the relationship remains
contradictory. Yet, past research on consumer adoption of online services found that
PEOU has been found to be an important antecedent of user’s adoption of new Web
technology in several studies (e.g., Chen, et al. 2002; Hong et al., 2008; Morris and
Dhillon, 1997; Pikkarainen, Pikkarainen, Karjaluoto, & Pahnila, 2004; Shin et al., 2009;
Taylor and Todd, 1995). Thus:
H3: There is a direct positive relationship between perceived ease of use of tourism and
travel related websites and perceived usefulness of the websites.
H4: There is a direct positive relationship between the perceived ease of use of tourism
and travel related websites and attitudes towards online purchasing.
Proceedings of 21st International Business Research Conference
10 - 11 June, 2013, Ryerson University, Toronto, Canada, ISBN: 978-1-922069-25-2
2.3. Trust in Travel Related Websites
According to Kolsaker and Payne (2002), trust is defined as the dimension of a
business relationship that determines the level to which each party feels they can rely
on the integrity of the promise offered by the other. Chen et al. (2002) hypothesized that
a consumer’s trust in a virtual store positively affects his/ her attitude toward using the
e-store. Jarvenpaa et al. (2000) also found that trust in the online store directly influence
attitude. Supported by the above literature, it can be hypothesized that:
H5: There is a direct positive relationship between the trust on tourism and travelrelated websites and attitudes towards online purchasing.
2.4. Perceived Risks
Perceived risk is defined as a consumer’s subjective perception of the possibility to
reach unexpected consequences (Dowling and Staelin, 1994). In this study, perceived
risk refers to the uncertainties associated with possible negative consequences of using
e-commerce for tourism and travel products. Trust and risk are essential in explaining ecommerce adoption, as uncertainty is present in the technology-driven environment
(Lee and Turban 2001; Pavlou 2003). Several studies show that perceived risk
negatively influences trust in a given website (e.g. Featherman, 2001; Pavlou, 2001).
Thus, the following hypothesis is proposed:
H6: There is a direct negative relationship between perceived risk and trust in tourism
and travel websites.
Perceived risks also impact on attitude towards online purchasing. Jarvenpaa et al.
(2000) showed attitude and risk perception affected consumer's attitudes toward an
online-store. However, a study of Brown et al., (2007) noted that even though perceived
risk is noted as an important barrier to e-commerce usage, it does not seem to stop
people from buying online travel services. Yet, Wu and Wang’s (2005) study
incorporated perceived risk into the TAM to evaluate consumers’ adoption of mobile
commerce, and revealed that potential risks of online transaction in process affect
consumers’ attitudes. Thus,
H7: There is a direct negative relationship between perceived risk and attitudes towards
online purchasing of tourism and travel related products.
2.5. Attitudes toward Online Purchasing
Attitude is defined as a consumer’s positive or negative feelings related to
accomplishing the purchasing behavior on the internet (Chiu et al., 2005). In the
context of this study, attitude is a traveler’s salient belief of whether the outcome of his/
her use of the internet for purchasing tourism and travel related products will be positive
or negative. Attitude is said to have a direct impact on intention. The original TAM model
(Davis, 1986), and the models of Taylor and Todd (1995) and Morris and Dillon (1997)
indicate that attitude exerts a positive effect on behavioral intention. This relationship
Proceedings of 21st International Business Research Conference
10 - 11 June, 2013, Ryerson University, Toronto, Canada, ISBN: 978-1-922069-25-2
has also been proven in general e-commerce studies (Bruner and Kumar, 2005).
Hence,
H8: There is a direct positive relationship between the attitudes and online purchase
intention of tourism and travel related products
3. Methodology
The survey research was based on a self- administered questionnaire originally
designed in English and translated in French. The study measured TAM construct
variables by using an adapted five-point Likert-type scale (1= strongly disagree to 5=
strongly agree) devised by Davis (1989) and Taylor and Todd (1995). The questionnaire
entailed items borrowed from literature which were slightly modified to suit the tourism
and travel context. The demographic profile of the respondents was also captured.
Data were collected from 150 travelers at different strategic tourism locations of
Mauritius during the months of June and July 2012. To ensure the reliability of the
scales, a reliability test was carried out and the Cronbach’s Alpha values (> 0.70) were
verified. Multiple regression analysis was used to evaluate the relationships between
the variables.
4. Findings
4.1 Sample Profile
The sample results revealed a well- balanced gender distribution with 76 males (50.7%)
and 74 females (49.3%). The age distribution was as follows: 53 respondents (35.3%)
were between 18- 27 years, 30 respondents (20.0%) were between 28-37 years, 32
respondents (21.3%) were between 38-47 years, 29 respondents (19.3%) were
between 48-57 years and 6 respondents (4.0%) were 58 years and above. As for the
marital status, the majority of the respondents were married accounting for 48.0% while
41.3% of the respondents were single and 10.7% of the respondents were divorced/
widowed. The nationality composition was as follows: 74 French (49.3%), 38 British
(25.3%), 11 Indian (7.3%), 10 German (6.7%), 5 South Africans (3.3%), 4 Australian
(2.7%), 3 Swiss (2.0%) and 5 were from other nationalities (3.5%). In terms of frequency
of visit, the majority was repeated visitors (60.0%) while 40.0% were first- time visitors.
4.2 Results of the Multiple Regression Analysis
Four multiple regression analyses were performed to test the hypotheses. Results from
Table 1 shows that Model 1 was a significant predictor of attitude towards online
purchase intention of tourism and travel products (F = 32.92; p < 0.001) and explained
48 % (R2 = 0.48) of variance in the dependent variable. This relatively moderate
percentage of explained variance is not surprising in tourism research given that attitude
is affected by a multiplicity of factors, not all accounted in this model. PEOU variable
did not significantly predict the dependent variable (β = - 0.066; t = - 0.863; p > 0.05).
The other variables entered, namely PU (β = 0.554; t = 7.654; p < 0.001); TRUST (β =
0.173; t = 2.347; p < 0.05); RISK (β = - 0.221; t = - 3.276; p < 0.001) showed
Proceedings of 21st International Business Research Conference
10 - 11 June, 2013, Ryerson University, Toronto, Canada, ISBN: 978-1-922069-25-2
independent predictive effects on attitude towards online purchasing of tourism and
travel products.
Table 1: Multiple Regression Analysis
Regression Models
b
t
p
Collinearity
diagnostic
VIF
Tolerance
Model Summary
Model 1: Predicting attitude towards online purchasing
PEOU
-0.066
-0.863 Not sig.
PU
0.554
7.654
< 0.001
TRUST
0.173
2.347
< 0.05
RISK
-0.221
-3.276 < 0.001
1.629
1.448
1.504
1.257
0.614
0.691
0.665
0.796
R = 0.48; adj. R = 0.46;
F = 32.92; p < 0.001
Model 2: Predicting online purchase intent
PU
0.284
4.295
ATTITUDE
0.568
8.580
< 0.001
< 0.001
1.622
1.622
0.617
0.617
R = .60; adj. R = .60; F =
111.661; p < 0.001
< 0.001
1.000
1.000
R = .54; adj. R = .29; F =
60.50; p < .001
Model 3: Predicting perceived usefulness
PEOU
0.539
7.778
-0.436
2
2
Model 4: Predicting perceived risks
TRUST
2
2
-5.900
< 0.001
1.000
1.000
2
2
2
2
R = .19; adj. R = .19; F =
34.81; p < .001
Model 2 was a significant predictor of online purchase intent of tourism and travel
products (F = 111.661; p < 0.001) and accounted for 60 % (R2 = 0.60) of variance in the
dependent variable. Results suggest that PU significantly predicted online purchase
intent of tourism and travel products (β = 0.284; t = 4.295; p < 0.001). Thus, there was
a significant positive relationship between PU and online purchase intent. Attitude also
significantly predicted online purchase intent of tourism and travel products (β = 0.568; t
= 8.580; p < 0.001). Hence, there was a significant positive relationship between
attitude towards tourism and travel related websites and online purchase intention of
tourism and travel products.
Results from the multiple regression analysis suggested that Model 3 was a significant
predictor of perceived usefulness of tourism and travel websites (F = 60.50; p < 0.001).
The model explained 29 % of variance in the dependent variable (R² = 0.290). PEOU
significantly predicted perceived usefulness of tourism and travel websites (β = 0.539; t
= 7.778; p < 0.001).
Model 4 significantly predicted the perceived risks associated with tourism and travel
websites (F = 34.81; p < 0.001) and explained around 19 % of variance in the
dependent variable (R² = 0.190). The results confirm the significant negative
relationship between perceived risks and trust associated with tourism and travel
websites (β = - 0.436; t = - 5.900; p < 0.001).
Proceedings of 21st International Business Research Conference
10 - 11 June, 2013, Ryerson University, Toronto, Canada, ISBN: 978-1-922069-25-2
5. Discussion
H1 which proposed a direct positive relationship between PU and attitude towards
online purchasing of tourism and travel products was supported. This indicated that the
more the travelers perceived the Internet to facilitate his/her purchase of tourism and
travel products, the more positive was their attitude towards these websites. These
findings are in line with the study of Chau and Hu (2001) who found perceived
usefulness to be a significant determinant of attitude. Carey and Day (2005) also found
a strong relationship between perceived usefulness and attitude. Based on the finding,
PU was the strongest predictor of attitude. This outcome yields the implication that PU
factor is of more concern to the travelers.
H2, postulating a positive direct relationship between PU and online purchase intention
of travelers was supported. This further explains that the more travelers perceived
his/her online purchase of tourism and travel products useful, the more likely he/she will
engage in online purchasing. This is echoed in the findings of Tan and Teo (2000) who
applied the TAM in e- banking and found that the greater the perceived usefulness of
using electronic banking services, the more likely electronic banking will be adopted.
H3 which proposed a direct positive relationship between PEOU and PU was supported
implying that tourism enterprises should make their websites more useful and usable.
To travelers, the degree to which the tourism and travel website is perceived to be easy
to use strongly influences their perceived usefulness of online purchasing. The causal
relationship of PEOU to PU is corroborated by Hubona and Blanton (1996). Morosan
and Jeong’s (2008) study findings also revealed that PEOU of hotel reservation
websites had a significant influence PU of the websites. Based on the result, both
constructs are concluded to be closely linked in part, this is due to the fact that a
traveler would inherently try to mould his/her perception of online purchasing based on
his/her experiences in engaging in online purchasing and the ease in which the task
was executed.
H4 which proposed a direct positive relationship between PEOU and attitude was not
supported. This finding corroborates the study of Chong et al. (2010) where it was
found that contrary to TAM, perceived ease of use was not significant. Although PEOU
was second to PU in importance concerning consumer attitude as per previously
documented studies, the results of the multiple regression revealed that it was not a
significant predictor of consumer attitude. This due to the fact that online shopping
systems have become easier to use and users have become more technically savvy,
variations in the perceived ease of use dimension are reduced. Likewise, the study was
conducted with travelers already had the online purchase experience. Therefore,
perceived ease of use was found to have no effect on their attitude.
H5 which predicted a direct relationship between trust and attitude towards online
purchasing was supported. Previous research has consistently argued that there is a
positive relationship between trust and attitude (e.g. Grazioli and Jarvenpaa 2000;
Macintosh and Lockshin 1997; Suh and Han 2003). Similarly, empirical evidence has
underlined the direct positive influence of trust on shopping attitude (Wu and Chen,
2005). This further explains that trust in tourism and travel website enables favorable
Proceedings of 21st International Business Research Conference
10 - 11 June, 2013, Ryerson University, Toronto, Canada, ISBN: 978-1-922069-25-2
attitudes since the website is perceived to be reliable and that no harmful consequences
will occur if travelers use it to carry out online purchasing of tourism and travel products.
H6 which proposed a direct negative relationship between trust and perceived risk was
supported implying that the more travelers perceive the websites to be trustworthy, the
lesser he/she will perceive the risk associated with online purchasing. The inverse
relationship between trust and perceived risk has been discussed by Kim et al. (2007)
who argue that trust negatively affects a consumer’s perceived risk in the online
transaction. However, Morgan and Hunt (1994) asserted that consumer’s perceived risk
is not related to trust. Yet, other scholars argue that consumer’s perceived risk in the
online marketplace can be reduced by trust or by raising security of web sites (Pavlou,
2003).
The result of this current study support H7 where perceived risk was found to have a
direct negative influence on attitudes towards online purchasing of tourism and travel
products. The online purchase of travel products has high levels of perceived risk, due
both to the shopping channel being used (Internet) (Cunnigham et al., 2005). Thus, the
risk factor associated with the tourism and travel websites can have an impact on
attitudes of travelers. The result also coincides with the studies of Shih (2004) and Van
der Heijden et al., (2003), who stated that prior research has shown that perceived risk
in e-commerce has a negative effect on attitude towards the behavior. Potential risks of
online transaction in process will affect travelers’ attitude of adopting it for instance,
finance loss, divulgence of personal information or lack of product quality warranty.
H8 which predicts a positive direct relationship between attitude of travelers towards
tourism and travel websites and online purchasing intention was accepted. This result
suggests that if the travelers’ attitude towards the website is positive, his/her behavior is
more likely to be optimistic. This finding is in line with that of Shu and Han (2003) who
empirically validated that behavioral intention is determined by the individual’s attitude.
Past research has also examined purchase intent and attitudes to purchasing online
(van der Heijden et al., 2003). According to the result, attitude would be favorable if
appropriate strategies are adopted to increase perceived usefulness and trust and
reduce perceived risks.
6. Conclusion
This particular study provides further evidence on the appropriateness of TAM to
measure the different dimensions of online purchase intent of travelers. The results
confirmed seven out of eight proposed hypotheses among which, perceived usefulness,
trusts and perceived risks have been found to be significant in influencing attitude to
online purchase of tourism and travel products. On the other hand, the result suggests
that perceived ease of use is not a significant predictor of attitude. Yet, perceived
usefulness impacts positively on online purchase intent of travelers and perceived ease
of use significantly influences perceived usefulness while trusts negatively impacts on
perceived risks associated with tourism and travel websites. This study has its
limitations since it does not cover potential travelers, who have never conducted any
online transaction but have the intention to engage in online purchase of tourism and
travel products. The study was also conducted in off- peak period. It is possible that
Proceedings of 21st International Business Research Conference
10 - 11 June, 2013, Ryerson University, Toronto, Canada, ISBN: 978-1-922069-25-2
different sample profile would be derived in summer (peak period). Despite these
limitations, this study is the first attempt in Mauritius to examine factors influencing
online purchase intent of travelers. Therefore, these limitations should be viewed as
opportunities for future research.
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