Acceptance of Online vs. Traditional Travel Agencies

Anatolia An International Journal of Tourism and Hospitality Research

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Acceptance of Online vs. Traditional Travel Agencies THOMAS MAYR & ANDREAS H. ZINS To cite this article: THOMAS MAYR & ANDREAS H. ZINS (2009) Acceptance of Online vs. Traditional Travel Agencies, Anatolia, 20:1, 164-177, DOI: 10.1080/13032917.2009.10518902 To link to this article: http://dx.doi.org/10.1080/13032917.2009.10518902

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Acceptance of Online vs. Traditional Travel Agencies THOMAS MAYR'. ANDREAS H. ZINS 2 1 Institute for Tourism and Leisure Studies, University of Economics and Business, Augasse 2-6, A- 1090 Vienna, Austria.

E-mail: Thomas.mayr({:rwu-wieu.ac.at 2

Institute for Tourism and Leisure Studies, University of Economics and Business, Augasse 2-6, A- 1090 Vienna, Austria. E-mail: Andreas ..:ius(fPu'u-wien.ac.at

ABSTRACT

Previous research focused primarily on discovering factors affecting either the benefits and service quality of traditional travel agencies or those of online booking facilities. This study tries to broaden the scope by investi-. gating multiple distribution channel options. It considers different concepts covered by the SERVQUAL instrument, the technology acceptance model, thee-service quality approach and price perceptions as potential value drivers for different travel distribution channels. 58 different perceptual and attitudinal criteria were finally used and condensed into eleven value driving dimensions. These evaluative dimensions were applied together with a set of personal characteristics to discriminate between five different traveller segments defined a priori by their past booking behaviour. Overall, socalled store characteristics seem to dominate the explanation of differences in channel preferences. More favourable price perceptions are attributed to online agencies which is one of the outstanding perspectives of the strongest discriminant function described as 'online euphorism-scepticism'.

KEY WORDS

Travel agents Leisure travel Booking behaviour

ARTICLE HISTORY

Submitted : 10 February 2009 Resubmitted : 01 April 2009 Acce1>ted: 06 April2009

INTRODUCTION

In leisure travel online booking increased enormously due to several factors: e.g. as low cost carriers sell directly and solely on the internet, airline companies operate their own booking websites, and effective online agents appeared. As a result, travel booking behaviour has dramatically changed in the last years, especially among countries with well-developed infrastructure for marketing activities over the internet. For the European online travel market a continuous growth to almost EUR 77 billion in 2011 is forecast (Forrester Research 2006). Differing views prevail regarding the impact of the internet on and the future of traditional travel agents. While earlier studies mentioned a (partly) dis-

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Anatolia: An International Journal of Tourism and Hospitality Research


Thomas Mayr- Andreas H. Zins

intermediation of traditional travel agents (Sheldon 1997) more recent ones reported that travellers still rely on them (Bennett and Buhalis 2003; Buhalis 2003). Main reasons for this loyalty are the high value of face-to-face contact, personal and competent counselling, and avoiding high search costs. Thus, a better understanding what factors affect a traveller's preference of online and traditional travel agents is important for the travel service industry to improve their service standards (Zhang et al. 2006). In line with this claim the aim of the present paper is to shed light on the important characteristics of traditional and online travel agencies including service expectations, price and value for money evaluations, and attitudes towards traditional and online travel agencies. In particular, this study extends the current research by contrasting different segments among the travelling population and by considering related streams of research such as the SERVQUAL approach, the technology acceptance model (TAM), the electronic service quality model (eSQ), the Service Value paradigm, and price satisfaction models. LITERATURE REVIEW

The supply chain within the tourism industry has changed mainly due to the diffusion of new technologies. As a result, the trend from facilitation of information exchange and reservations to a much more sophisticated mechanism of adding value and providing service is apparent (Law, Leung and Wong 2004). However, limited research has been conducted in this area. In the field of traditional travel agencies some papers try to explain overall quality or customer satisfaction by service expectations and/or perceptions of travel agencies. Lam and Zhang (1999) examined 26 service aspects which had been generated with reference to the original SERVQUAL instrument and adapted through industry input. They identified two factors with the highest gap scores: reliability and responsiveness or assurance which had the strongest influence on overall satisfaction (R2 adj.= .51). In contrast, Bigne et. al (2003) made an effort to explain overall quality for travel agencies with a more generic, yet adapted SERVQUAL instrument using a performance-only measurement. They revealed only reliability as a significant explanatory dimension. However, responsiveness and assurance had relatively high, though insignificant correlations. A third contribution in this field did not link directly to the SERVQUAL paradigm but referred to expectations (such as past experiences, image, communication, and tangibles) as the key drivers for satisfaction (R 2 adj. = .79) and loyalty (Rodriguez del Bosque, San Martin and Collado 2006). They argued that perceived services tend to be assimilated towards the expected service levels. In taking the insights from both, the first and the third study seriously managers would be recommended to raise expectations very high irrespective to the performance of the particular travel agency. Ignoring this conceptual weakness still inherent in this kind of measurement, SERVQUAL based or related approaches are running short in considering price and other customer contributions to acquire a particular service for explaining outcome evaluations in a comprehensive way. Volume 20 •

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Acceptance of Online vs. Traditional Travel Agencies

As searching, planning and booking online requires the travellers' willingness to accept new technologies, the often cited theoretical framework of technology acceptance called TAM (Davis 1989) helps to explain the user's intention of using the information technology. A study of Zhang eta!. (2006) used the TAM approach to explain functions of e-travel agencies. In their view search capability, rich destination information, multimedia presentation, availability of online communities, and a wider range of choices are very useful features of online travel agencies that would fall close to the notion of perceived usefulness and should lead to the prospective users' intention to use online travel agencies. Features like 'easy and simple' search, and a feeling of 'being in control' fall close to the notion of perceived ease of use and should lead to the intention of using online travel agencies. In addition, Cho and Agrusa (2006) tested a model of users' attitudes towards online travel agencies and e-satisfaction. Their model included external variables such as information, price, product/service, convenience, technology/usability, brand name, promotional and entertainment factors. A former criticism about research in information systems was the ignorance of the human interaction aspect (Li 1997). Recent studies considered this human interaction aspect and included e-service quality measures (Zeithaml, Parasuraman and Malhotra 2000; Parasuraman, Zeithaml and Malhotra 2005). However, it is assumed that there is probably not a single specific scale that can be used to measure service quality across different industries (Santos 2003). Broadly defined, perceived value is a comparison of what a consumer 'gets' with what a consumer' gives' for the attainment of a product or service (Parasuraman, Zeithaml and Berry 1988; Petrick 2002). A fundamental study of perceived value of a service showed that perceived quality leads to perceived value, which leads to purchase intentions (Parasuraman, Zeithaml and Berry 1988; Zeithaml1988). Furthermore, consumers who perceive that they received 'value for money' are more satisfied than consumers who do not. Petrick (2002) conceptualized perceived value of a service as a five-dimensional construct consisting of behavioural price, monetary price, emotional response, quality, and reputation. Low price is seen as one of the most important characteristics of online travel agents (Anckar and Walden 2001; Ah Keng, Tang and Chose 2003; Zhang et a!. 2006). The more information consumers have on prices of the vendor (e.g. on complex fee structures or differentiated prices) the higher their confidence in the superiority of the offer will be (Matzler, Renzi and Rothenberger 2005). According to their approach additional perceptual constructs such as price information, price confidence, and price fairness explain influences on price satisfaction and loyalty which can be helpful to get a deeper insight into travellers' price perceptions. In general, online customers expect a lower price than in the traditional marketplace (Cho and Agrusa 2006). Arguments for using an online agent may be convenience, control, lower prices, easier access to information about the destination, comparable prices and information access 24x7 (Anckar and Walden 2001; Bennett and Buhalis 2003;

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Law, Leung and Wong 2004; Zhang et al. 2006). Reasons for planning and booking with a traditional agent may be the personal advisory service, their competent staff, personal counselling in planning and arranging complex trips and the support network in case of need during the trip (Anckar and Walden 2001). Hudson et al. (2001) stated that a traditional travel agent often has tremendous amount of influence on consumer's decision making and therefore booking a more complex trip with multiple layovers might be faster and easier with a traditional agent than online. Lang (2000) asked for reasons for not booking online and found out that security issues, a lack of confidence in technology use, a lack of personal service and the loyalty to the traditional travel agent were the most important ones. Card, Chien and Cole (2003) indicated that face-to-face services lower risks involved in travel planning and booking. The explanations for the differences between online buyers and non-buyers in the literature remain controversial so far. Donthu and Garcia (1999) found out that online buyers are older, have a higher income, are more convenience seekers, innovative, impulsive, variety seekers and less risk averse than nononline buyers are. Card, Chien and Cole (2003) challenged some of these explanations by analysing and explaining the booking preferences of TTRA (Travel and Tourism Association) members. Their conclusion that store characteristics, such as time saving, price, reduced risk, product variety, or customer service factors do not contribute to discriminate between shoppers and non-shoppers seems to have only limited validity. Zhang et al. (2006) asked students about their online booking behaviour. Their findings support the assumption that store characteristics play an important role. Law, Leung and Wong (2004) recommended further research investigating particularly the non-Internet users' perceptions of online booking options. Considering the insights of the research areas discussed above this study tries to identify those value driving factors which discriminate most between online and traditional travel agency preferences. Thus, this research tries to achieve a better understanding what service propositions are essential for traditional agents to compete with online agents. Hence, the following research questions are put forward: Are socio-demographic and travel behaviour characteristics responsible for different travel planning and booking preferences? (RQ 1) Do online bookers emphasize other service areas of traditional travel agencies compared to conventional bookers? (RQ 2) Are attitudes towards online travel agencies pertinent to different booking preferences? (RQ 3) Are price and value-for-money perceptions responsible for the diminishing loyalty for traditional travel agencies? (RQ 4) Which of the aforementioned factors- value drivers versus personal characteristics- contribute most to the explanation of differences in booking preferences? (RQ 5)

METHODOLOGY Addressing the previous research questions it seemed necessary to consider both perspectives: perceived advantages and disadvantages of online travel Volume 20 •

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booking and those perceived of traditional or conventional booking activities. In addition, a sample of the average travel population was deemed more appropriate compared to taking either industry experts (Card, Chien and Cole 2003) or students (Zhang et Al. 2006) to achieve unbiased validity. By contrasting segments which are based on past booking behaviour differences in attitudes and channel benefit perceptions can be conceived as the underlying driving forces. It was essential to generate a sample of the travelling population (in this case for Austria) with the following characteristics: either online booking experiences or abstinence from internet access and/or from booking travel services online. For this purpose elementary characteristics about the respondent's internet access, internet usage, usage frequency, usage purposes, and selfperceived internet expertise were integrated in the study together with basic socio-demographic and travel behavior variables. To achieve a representative profile of the travelling population their booking and internet behaviour was taken into account. To ascertain these structural characteristics in the sample two steps had been taken: 1. The email addresses of a large travel agency were used to announce this study (web-based questionnaire for internet users, June 2006). 2. An additional random telephone sample was generated to invite people to participate in this study (paper-andpencil mail questionnaire for non-internet users, April to May 2006). The data for this study were gathered in June to August 2006. DISCUSSION OF FINDINGS

The further analyses are based on a sample of 715 respondents representative for a national European population (here: Austria) travelling international including internet users and non-users. Booking behaviour for the last leisure trip and past online booking experience for travel components are combined to define five segments with a varying degree of distribution channel preferences (see Table 1). 1. 70% of the respondents told that they did already book over the internet a complete travel or parts thereof in the past while 30% did not. 2. 40% reported that they booked their last holiday trip with a traditional travel agency, 22% over the internet and 31% directly with the service provider. Combining both criteria, five booking segments emerged. (Note: Their shares are not representative for the whole travel population since the assembled sample is not proportionate to that.). 22% of the respondents reported having already booked a trip or parts of a trip online in the past while the most recent holiday trip was booked with a traditional travel agency. A slightly smaller share of 18% did it the same way, however, without any previous online travel booking experience. The largest segment in this sample (29%) has previous online booking experience while the majority organized their last trip via the internet. The remaining two segments represent those independent travellers organizing their last trip without internet booking and travel agencies. The larger part (20%) has already some previous online booking experience while 11% (the last segment) has not.

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Table 1. Profile of the Travel Distribution Channel Se~ments


Chi 2 - or F-Iest

Switcher

Travel Agency

Online

Segment share

22%

18%

29%

20%

11%

Gender Female Male

67% 33%

64% 36%

60% 40%

54% 46%

58% 42%

Age 15-24 25-44 45-64 65+

6% 46% 46% 2%

11% 43% 37% 9%

10% 53% 33% 4%

15% 55% 24% 6%

22% 38% 29% 11%

Education Secondary Bakkalaureat University

38% 39% 23%

51% 37% 12%

34% 42% 24%

23% 50% 27%

49% 35% 16%

Internet experience in years

6.5a)

6.1b)

6.9C)

7.3a) b)

5.oa) c)

Perceived internet expert

28%

32%

46%

48%

32%