Antecedents of tourist trip planning autonomy: The moderating effects of a global economic crisis

Abstract

With national data from tourists who reside in Spain, this article researches antecedents of tourist autonomy in trip planning, including both tourists’ characteristics and details of their trips. The results indicate positive relationships of tourists’ educational background and their travel experience with autonomy but negative relationships of trip length with autonomy. These data from Spain also highlight the role of the last global economic crisis, revealing its moderating influence on the relationships among several of the antecedent factors and autonomy. These results in turn have relevant managerial implications for tourism operators.

Keywords

economic crisis tourists’ characteristics trip characteristics trip planning autonomy

Introduction

Modern technology provides tourists with alternative trip planning tools (Mokhtarian et al., 2006), so they can readily perform tasks that traditionally were reserved for professional agents. In particular, travellers increasingly use the Internet to find travel information and book and pay for tourism services (IET, 2007–2012; IPK International, 2015), with concomitant reductions in their use of traditional, physical intermediaries (European Commission, 2016). This independent planning behaviour by tourists – who gather information, book and pay for their trips on their own, without relying on conventional travel intermediaries – constitutes autonomy in trip planning (Fernández-Herrero et al., 2018).

Performed mainly online, such autonomy represents a critical phenomenon for the tourism market. In particular, several characteristics linked to the autonomy phenomenon in tourism make it worthy of attention: (1) It is a global and growing trend in the tourism market; (2) It is thus necessarily transforming the way tourism providers approach tourists.

First, nowadays Internet is the basic source of tourist information worldwide (IPK International, 2015, 2019), European travellers specifically use the Internet extensively to obtain information and plan their holidays. In particular, an estimated 66% of travellers (representing a 13% increase since 2011) use online information sources, whereas only 13% rely on physical travel agencies (a decrease of 10% since 2011) (European Commission, 2016). Consider Spain as an example: Nearly three-quarters (71.3%) of Spanish tourists depend on the Internet to make their travel arrangements, nearly 100% more than 10 years ago. When it comes to actual bookings, 60.2% of Spanish tourists turn to the Internet, and 62.1% visit Internet sites to make transportation arrangements, whereas only 8.6% use in-person contacts, and 14% call travel intermediaries on the telephone to make travel arrangements (INE, 2016a). Although currently traditional tourism agents coexist with autonomous tourists, the continued development of the Internet and its widespread use for planning trips suggests that the returns on such efforts will continue to diminish. In turn, understanding the levers of tourists’ trip planning autonomy represents a pressing demand for tourism marketers and managers.

Second, autonomy in trip planning changes effective marketing strategies for tourism products and destinations when the target market increasingly consists of competent, autonomous consumers. They can easily access information about tourism products or services, including prices, and as a consequence, offers and prices are more transparent. Globally, 81% of tourists consult a review website, such as TripAdvisor, before booking; 75% of tourists leave reviews on review sites (Travelport, 2017). The proliferation of reviews in turn gives firms novel insights into client perceptions, while also providing a channel to respond directly to clients’ comments. Due to these shifts, physical travel agents have largely lost their function, and tourism providers and intermediaries confront the clear need to revise their approaches if they hope to provide valued contributions to tourism supply chains.

Thus, due to the relevance of the phenomenon and the consequences for tourism operators, studying its antecedents is of interest for the industry. In this regard, prior research on tourists’ trip planning behaviour indicates some links between the tourists’ sociodemographic profiles and their trip planning behaviours (Bansal and Eiselt, 2004; Bargeman and van der Poel, 2006; Kuo et al., 2011). For example, personal characteristics might determine the amount and type of information a tourist requires in the three phases of trip planning (i.e. information search, booking and paying; Hyde, 2008). In particular, it appears that a higher educational level relates to more complex planning processes (Van Loon and Rouwendal, 2013), and previous travel experience facilitates autonomy (Bargeman and van der Poel, 2006; Li et al., 2008). Other factors, beyond individual traits, have also been examined, such as the vacation type (Hyde, 2008) or the number of tourist services included in the vacation (Beldona et al., 2005; Haynes, 2009; Park and Jang, 2013). Overall, research shows that more complex holidays (e.g. big vacations, more services booked) require more information before tourists will make booking decisions. But no research has specifically integrated potential antecedents of autonomy related to both tourists’ characteristics and trip features.

Complementarily, in addition to recognising that the use of the Internet provides a basis for explaining autonomy, these links likely reflect the influence of the intense 2008 global economic crisis. Economic crises disrupt tourist activity, leading to decreased tourism expenditures and fewer international trips in the immediate term (Alegre et al., 2013; Antonakakis et al., 2015; Guizzardi and Mazzocchi, 2010; INE, 2017), as well as long-term effects such as stronger desires to economise or tendencies to flit from one offer to another (Flatters and Willmott, 2009). As a consequence, economic crises generally create an even more difficult competitive environment in the tourism industry and, shedding light on how crises influence tourist behaviour (and particularly their autonomy), may be especially valuable to the industry.

Finally, although the concept of autonomy is key for the tourism sector, we have little evidence of research to date, being even scarcer when it refers to its antecedents. In particular, we have not found any research that analyses this topic in the context of the economic crisis, so decisive in the Spanish case.

Thus, with the recognition that tourists’ behaviour is increasingly autonomous, and that the economic crisis represents a critical consideration, this study pursues two main research objectives:

To identify potential antecedents of autonomy in trip planning, related to tourists’ characteristics (educational background, travel experience) and trip characteristics (trip length, service complexity).

To analyse the moderating role of the economic crisis in the relationships between the antecedent factors and autonomy in trip planning.

In the next section, we present our hypotheses, derived from a review of prior literature, together with a proposed model. Then we outline the findings, from which we draw several conclusions and management implications, along with suggestions for further research.

Literature review and hypotheses

We review prior literature and establish our hypotheses according to four relevant topics: autonomy in trip planning, the characteristics of tourists, the characteristics of the trip and the potential moderating role of the global economic crisis.

Autonomy in trip planning

Empowered by the widespread use of the Internet, tourists are now showing increasingly independent behaviour in the travel preparation phase, searching for information, making reservations and paying for it by themselves.

As a human behaviour, autonomy can be explained from a psychological point of view: Autonomy of the individual can be understood as an innate and universal psychological need that must be satisfied in all cultures to be optimally healthy (theory of self-determination) (Deci and Ryan, 2012), which implies the organic desire to organise one’s own experience and behaviour (Deci, 1980; Ryan and Connell, 1989; Sheldon and Elliot, 1999).

Autonomy can also be related to the concept of self-efficacy that reflects ‘beliefs in one’s abilities to organise and execute the courses of action necessary to produce the given achievements’ (Bandura, 1997: 3; Luszczynska et al., 2005). Greater autonomy implies a higher level of self-confidence in one’s abilities, better use of technology, better problem-solving and, finally, better results and higher levels of personal satisfaction from the most optimal selection made by oneself (Bandura, 2010; Deci and Ryan, 2000; Gómez et al., 2007; Hung and Petrick, 2012; Igbaria and Iivari, 1995; Kim et al., 2011; Luszczynska et al., 2005).

In some specific environments, experiences of autonomy are necessary to enjoy the activity, to experience spontaneous pleasure as long as the activity was self-organised and the task appropriately challenging (Deci and Ryan, 2012), and it also constitutes an important behavioural feature that can affect people’s approaches to leisure or travel planning (Hung and Petrick, 2012; Walker et al., 2007).

In tourism, autonomy is closely related to the Internet: The latter’s progressive expansion and accessibility enables tourists to organise the trip, especially as regards planning; and the more self-efficient the people are, the more they use the Internet autonomously for their travel arrangements (Bansal and Eiselt, 2004; Hyde, 2008; Steinbauer and Werthner, 2007).

Although tourists combine physical and traditional agents with autonomous behaviour for the organisation of travel (Steinbauer and Werthner, 2007), they need to resort less and less to them at the planning stage (Law et al., 2004; Maurer, 2003). Different arguments support the widespread use of the Internet in travel planning: The Internet is a comfortable and convenient channel (Heung, 2003) that helps reduce the risk of buying thanks to customer feedback and vendor responses that provide clear indicators of quality of service (Melo et al., 2017). This gives access to infomediary channels that compare and classify offers, reducing search costs (Kim et al., 2011; Nieto et al., 2014), offering the possibility of enjoying the navigation process through the different web pages as part of the tourist experience (Belver-Delgado et al., 2020; Teichmann and Zins, 2009), and a means, finally, with which the tourist is increasingly familiar, providing a sense of security to customers in their handling of travel arrangements.

All of this reduces the use of physical agents and increases the autonomous behaviour of the tourist in travel planning, based on the use of the Internet: The Internet is already the most used means by Europeans to plan vacations, with year-on-year growth percentages observed from the beginning of the 21st century to the present (European Commission, 2016; INE, 2016a, 2019; IPK International, 2015).

Tourists’ characteristics

Tourists’ sociodemographic profiles influence on their travel behaviour: The individual characteristics of tourists determine their choices and attitudes towards travel (Amaro and Duarte, 2013; Bansal and Eiselt, 2004; Bargeman and van der Poel, 2006; Cheung et al., 2005; Kuo et al., 2011). This influence is also confirmed in the online context where the different individual attitudes towards online shopping depend on the particular profile of the consumer (Bansal and Eiselt, 2004; Bargeman and van der Poel, 2006; Cetina et al., 2012; Cheung et al., 2005; Díaz et al., 2017; Kuo et al., 2011; Moon and Kim 2001; Sam and Chatwin, 2015; Torkzadeh and Dhillon, 2002). In particular, in this research two tourist characteristics are examined: educational background and travel experience.

Educational background

Particularly, educational levels may prompt specific travel behaviours; more education tends to increase people’s skills and abilities, so consumers with more education are apt to visit general and travel websites more often and have more positive attitudes towards the Internet (Morrisonn et al., 2001). Moreover, education may allow people to select holiday destinations that require more complex planning processes, so they increase their ability for and likelihood to travel internationally (Van Loon and Rouwendal, 2013), and they can gain exposure to culturally diverse and unique products (e.g. culinary tourism, López-Guzmán and Sánchez-Cañizares, 2012).

We can expect that the higher the tourists’ educational level, the easier it becomes for them to be successful in performing autonomously; therefore, tourists with strong educational backgrounds should be able to perform autonomously and with greater efficiency. We thus predict:

H1: Tourists’ educational background has a positive impact on tourists’ trip planning autonomy.

Travel experience

Past travel experience influences tourist behaviour (Horner and Swarbrooke, 2007; Solomon, 2017). When a tourist has visited more destinations, he or she likely gains greater familiarity with travelling in general.

When a tourist is involved in a trip planning process, the set of alternative solutions that are usually considered is limited, since the tourist is not aware of all of them or the information is difficult to process, resorting firstly to the ‘evoked set’ (Woodside and Ronkainen, 1980: 7). When the information contained in the evoked set is not enough, the tourist has to extend his or her search. In this regard, if the tourist is a frequent traveller, that is, if he or she has previous experience, he has a wealth of information that the inexperienced tourist does not have (Crotts, 2000). Thus, faced with planning a particular trip, the most expert will probably perform a more selective, shorter search based on their previous experience (Solomon, 2017). Besides, for the more experienced tourists, any trip planning will probably be easier, requiring less effort. That is, experience with travelling influences not just selection processes themselves but also the extent to which these processes appear more or less difficult (Bargeman and van der Poel, 2006; Gursoy and McCleary, 2004; Li et al., 2008).

Consequently, with greater tourism experience, consumers can act more autonomously and, by doing so, they are more apt to obtain favourable outcomes. In particular, it becomes easier to make holiday choices, including information searches, booking and payment. This ease should help more experienced tourists make more appropriate trip and tourism selections, often using less effort or time. Such a planning process likely feels more satisfactory, which may enhance the trip experience overall, as well as producing a better fit with the tourist’s preferences. Because experienced tourists probably manage their autonomy more efficiently, we predict that greater familiarity with travelling overall has positive influence on autonomy. Formally,

H2: Travel experience has a positive impact on tourists’ trip planning autonomy.

Trip characteristics

Trip length

Trip length refers to the duration of the vacation. A longer trip is associated with higher risk, which affects decision-making processes. Three rationales offer support to this relationship among trip length and risk.

Firstly, it is expected that a longer trip will involve a higher investment. And, when trip expenditures increase, the perceived risk increases as well. When travel expenses increase, tourists require more security for their investment or make more service demands (Amaro and Duarte, 2013; Beritelli et al., 2007; Coenders et al., 2016; Hiransomboon, 2012; Kim et al., 2005).

Secondly, a longer trip means that the consequences of a bad decision will be suffered for a longer time, provided that the vacation is longer. In contrast, if the trip is short, the days of ruined vacation are not that many. Thus, this potentially longer negative experience is associated with higher risk, which the tourist will try to avoid (Beritelli et al., 2007; Kim et al., 2005; Law et al., 2004).

Thirdly, particularly for the Spanish setting, longer trips are usually linked to the main vacation of the year, which is usually taken in summer, when many companies close completely or reduce their activity drastically, because of extremely hot weather and cultural reasons. A greater importance of the holiday is also associated to a higher risk (Aguiló and Rosselló, 2012; Law et al., 2004).

In summary, negative consequences of a poor choice increase as trip length increases (Kim et al., 2005). Thus, the amount of information needed (and length of the information search process) varies according to trip length, being more demanding when the trip is longer and, consequently, the decision involves higher risk. For example, regarding payment decisions, while some transactions demand exhaustive information; others only require basic transactional information. Differences in information needed or processing time also influence which distribution channel tourists prefer (Law et al., 2004). For example, for shorter and cheaper stays at a nearby tourist site, tourists are more likely to make their accommodation decision by themselves and make the reservation autonomously (Hiransomboon, 2012). In contrast, when the trip is long, the risk is also high, tourists more frequently reduce their Internet use and rely more on professional tourism agents (Amaro and Duarte, 2013; Beritelli et al., 2007; Coenders et al., 2016; Hiransomboon, 2012; Kim et al., 2005).

Thus, although one might think that longer trips would imply a greater effort in searching for information (also on the Internet) in order to get a lower price, these trips’ association with risk would incline the balance towards the third-party travel agent, in order to minimise risk. That is, tourists prefer to use the Internet for trips that they perceive to involve low risk and low uncertainty (Beritelli et al., 2007; Law et al., 2004). The threat of losing more money, suffering negative consequences for longer, and/or ruin the main holidays, is assumed to increase when the trip is longer. Accordingly, tourists would exhibit different degrees of autonomy in trip planning depending on trip length. Thus, we hypothesise,

H3: Trip length has a negative impact on tourists’ trip planning autonomy.

Service complexity

Pretrip decision-making involves choices for accommodation and/or transportation (Decrop and Snelders, 2005; Jeng and Fesenmaier, 2002). Different behaviour patterns mark trip planning, depending on the type of tourism services required, in general (Cetina et al., 2012; Coenders et al., 2016) and specifically in an online environment (Cheung et al., 2005; Díaz et al., 2017; Torkzadeh and Dhillon, 2002). In particular, tourists are prone to perceive different degrees of complexity in the services they need for the trip, which in turn determines the amount and type of information they require, as well as their willingness to book through a particular channel (Hyde, 2008; Kotler et al., 2015; Solomon, 2017). Complementarily, the level of complexity related to the trip also influences paying behaviour. When the elements that must be purchased are perceived as more complex, potential buyers usually demand more information from providers to make their paying decisions (Beldona et al., 2005).

If the service is familiar, the tourist likely can find all the necessary information and make the reservation autonomously. More unknown, unusual tourist services instead increase uncertainty and do not offer enough previous experience to facilitate choices, so tourists demand more information before making purchase decisions (Beldona et al., 2005). After resorting to internal information, if it is not sufficient or there is not enough experience, the tourist turns to external sources such as family and friends, brochures, travel agencies, or the Internet (Crotts, 2000; Hawkins et al., 1995).

Tourists’ behavioural patterns in trip planning thus reflect their different needs for information, based on their perceived levels of difficulty and risk, and their desire for security, depending on the type of services they need to purchase. If the services are less familiar or more complex, tourists are prone to mistrusting their own capacity and turn to reliable distribution channels to gain confidence. Suitable planning arrangements are more difficult when accommodation and transport are complex, so we anticipate a negative relationship between service complexity and autonomy. Formally,

H4: Service complexity, in terms of the type of accommodation and the type of transport, has a negative impact on tourists’ trip planning autonomy.

The economic crisis

A crisis climate triggers economisation; people are less inclined to consume. During such periods, the tourism industry faces a difficult competitive environment, marked by fewer customers, greater price sensitivity and shorter stays. Tourists’ preferences and attitudes shift during economic crises (Scott et al., 2013), in such a way that they adopt economising approaches, seek to save and alter their planning and travel strategies (Bronner and De Hoog, 2012). Although cost-cutting strategies vary regionally, people generally take fewer vacations, reduce the lengths of their stays, choose cheaper accommodations and means of transport, travel closer to home and change their vacation dates or destinations (Bronner and De Hoog, 2011; Campos-Soria et al., 2015; Eugenio-Martín and Campos-Soria, 2014).

They also tend to use the Internet rather than consulting travel agents (European Commission, 2016; IET, 2007–2012; López-Bonilla and López-Bonilla, 2008), because they can economise on travel spending by making their own arrangements (Aguiló and Rosselló, 2012). The Internet dramatically broadens tourists’ range of alternatives and provides consumers with offers tailored to their needs (Bakos, 1997, 1998; Buhalis and Law, 2008) minimising search costs in different degrees according to factors such as prior knowledge of the product or the profile of each tourist (education, age, etc.) (Solomon, 2017). Consumers’ trust dispositions also change (Kim et al., 2008; Martin and Woodside, 2011), such that their confidence drops, due to the influences of dire media reports and the general decline in their disposal income.

In this regard, using the recent global economic crisis as an example, data show that in Europe in 2008, for the first time, the proportion of holiday trips booked online surpassed those booked offline; in 2009, despite an overall reduction in the number of trips compared with 2008, those booked through the Internet increased by 11% and booking of essential travel rose by 20% (IPK International, 2010). These trends reflect the benefits that the Internet offers, by helping tourists develop economising strategies to get the best outcomes at the lowest prices. As an economic crisis unfolds, tourists attempt even more actively to find better prices and performance by becoming more autonomous in their information-seeking and booking behaviours. Some of this behaviour likely persists after the crisis too, because tourists’ preferences, attitudes and behaviours already have changed. By using the Internet, tourists lose access to the expertise of travel agents (López-Bonilla and López-Bonilla, 2008), but the abundance of reviews, information tips and deals make up for this loss and strike a clear path towards the final choice.

Economic crises, therefore, create a context that influences tourist behaviour, and it is expected that the effects on autonomy of different traits of the tourist profile or of the trip profile become accentuated.

Regarding specific tourist characteristics, such as education, well-educated people tend to access the Internet more (ONTSI, 2018), so they should have stronger online search skills. Internet-savvy tourists can take full advantages of special offers and low-cost opportunities using the Internet; in response, tourism providers increasingly turn to low-price strategies, such as online-only offers that provide discounts to end customers while also eliminating sales commissions and distribution charges, by shortening the value chain (Buhalis and Law, 2008). In times of crisis, providers can be expected to increase this strategy that, in turn, could be more profitable for the more skilled tourist. That is, they can better leverage the benefits of the Internet and, for example, find deals more easily. They also perform such operations more efficiently, which should encourage their autonomous trip planning.

Besides, economic crises drive learning processes and prompt even more efficient behaviour, which together with highly accessible technological conveniences such as the Internet, apps and mobile devices lead to even more efficient and autonomous behaviour (Bodosca et al., 2014). It is assumed that these learning processes are especially relevant for the more educated people. Thus, we expect the crises to accentuate the effect of education on autonomy.

Regarding tourist past travel experience, we know that it implies greater familiarity with the preplanning process, a greater likelihood of achieving a good fit and more positive disconfirmation of expectations. As for educated tourists, an economic crisis accentuates the need to get the most at the lowest price, so efficient, autonomous trip planning, without the help of tourism intermediaries, emerges as an even more appealing consumer choice. Thus, we expect the crisis to accentuate the effect of travel experience on autonomy.

Furthermore, for every tourist, an economic crisis requires consumers to minimise their purchase risk, such that it is important for tourists to make good choices. During economic crises, tourists especially want to ensure that their vacations are satisfactory, because they may be limited to taking only one holiday. Tourists reduce their spending, and each expense also becomes more important, and the need to make a good decision becomes more pertinent. In turn, risk perceptions increase, and consumers’ trust dispositions in others (e.g. travel agents) likely diminish (Kim et al., 2008). There is a greater need for security (Simon, 2009). Therefore, we expect the crisis to accentuate the effect of both education and travel experience on autonomy.

However, due to the need to minimise risk and uncertainty, especially powerful in a crisis climate, when tourists’ budgets are probably limited, for those trips for which the duration is longer or service complexity is higher, tourists are expected to seek to extend their information processing before making a decision, and they might behave in a less autonomous way. Thus, we expect that a crisis would accentuate the effects of trip length and services complexity on autonomy. That is, the expected negative effect of trip length and services complexity would escalate.

Therefore, we posit:

H5: Economic crises moderate the relationship between educational background and tourists’ trip planning autonomy, such that this positive relationship intensifies during economic crises.

H6: Economic crises moderate the relationship between travel experience and tourists’ trip planning autonomy, such that this positive relationship intensifies during economic crises.

H7: Economic crises moderate the relationship between trip length and tourists’ trip planning autonomy, such that the negative relationship intensifies during economic crises.

H8: Economic crises moderate the relationship between service complexity and tourists’ trip planning autonomy, such that the negative relationship intensifies during economic crises.

We summarise our proposed model, which integrates these hypotheses, in Figure 1.

Figure 1.

General model.

Methodology

Data collection

The data for this research came from an annual survey of Spanish tourists’ behaviour, known as FAMILITUR, for 2006–2011. This survey, conducted by the Institute of Tourism Studies of the Government of Spain, gathers data about trips taken by Spanish residents. A nationwide statistical reference, it has been collected since 1996.

Beyond the availability of these official data, we chose Spain as our study setting for two key reasons. First, Spain attracts substantial numbers of tourists, both internationally (second in the world in receipts and arrivals in 2017; World Tourism Organization, 2018) and nationally, and more than 11% of its gross domestic product (GDP) comes from tourism (in 2015; INE, 2016b). In line with global trends, Spanish tourists increasingly rely on the Internet to conduct trip planning, but some people still use physical intermediaries (INE, 2016a), so it represents a relevant context for studying tourists’ behaviour. Second, Spain was strongly affected by the international economic crisis of 2008, with adverse evolution in its main macroeconomic indicators from 2008 to 2011 (the end of our study period), including a sharp decline in GDP and sharp rise in unemployment to historic heights (INE, 2014, 2017).

For this study, we gather six waves of the same original database, for the years 2006–2011; when aggregated, they comprise 765,165 entries, each of which refers to a particular trip taken by the 66,173 households represented by the combined sample. To estimate our proposed general model (Figure 1), we conduct the analyses on a subsample of 20,121 entries, representing 6738 households, for which the observations assessed satisfaction and also involved accommodation and transport being booked simultaneously. With these criteria, we ensure a clear focus on trips involving complex arrangements, in that they demand booking decisions for two key dimensions of trip planning, transport and accommodation, and thus better reflect the criteria for our intended analysis.

Measures

We define the variables in Table 1. As established in the general model (Figure 1), our purpose is to identify antecedents of autonomy in trip planning, related to tourist and trip characteristics and then to study the moderating role of the economic crisis in these relationships.

Using a reliable and rigorous data source, we developed our own measures tailored to the purpose of our research from available information.

Considering the relevance of the Internet as a facilitator of autonomous behaviour, we measure autonomy through the ordinal variable Internet usage intensity, on an ordinal scale from 0 to 4, reflecting the intensity in the use of Internet for trip planning: whether the participant used the Internet to seek information, book and/or pay for the basic tourist services, accommodation and transport, and if he did these actions for one or for both elements. Although this scale was developed by the authors, taking into account available information, the measure of the intensity in the use of the Internet in order to explain the behaviour of tourists in trip planning has been used previously (e.g., Coenders et al., 2016; Kim et al., 2015; MacKay and Vogt, 2012).

We organised the predicted antecedents into four blocks: tourist educational background, tourist travel experience, trip length and service complexity. The first two refer to the household level, which is the context in which most travel decisions take place. Educational background indicates if someone in the household has a university education; travel experience measures the number of destinations visited during the study period. Among the trip characteristics, we measured the duration of the trip, according to the number of overnight stays of each trip and which tourist services have been booked, in terms of the type of accommodation and transportation. In this regard, we consider more complex the less common options chosen by Spanish tourists on accommodation and means of transport: accommodation other than a hotel, and means of transport other than a plane.

To register the onset and escalation of the crisis in Spain, we use three dichotomous variables, one of them reflects the period before the crisis (P1, 2006–2007); the second one reflects the start of the crisis (P2, 2008–2009) and the third period is meant to reflect the built-up crisis period (P3, 2010–2011).

With these variables, we test the potential moderating effect of the economic crisis on the four relationships of the antecedents with trip planning autonomy. All the variables reflect the same analysis period, 2006–2011, which corresponds to the six FAMILITUR surveys for these years. Table 1 contains a more detailed description, and Table 2 provides the descriptive statistics.

Table 1.

Variable definitions.

Description	Measurement
Internet usage intensity	0–4 scale, reflecting the use of the Internet for information, booking and payment of accommodation and transport, such that 0 = does not use the Internet 1 = only uses the Internet for information on one of the travel elements 2 = uses the Internet for information on both travel elements OR books/pays for one travel element 3 = uses the Internet for information on one of the travel elements AND books/pays for the other travel element 4 = uses the Internet to book and pay for both travel elements
Educational background	0 = no university-educated household members 1 = at least one university-educated household member
Travel experience	Maximum number of destinations visited by at least one household member during the period under analysis
Trip length	Number of nights/overnight stays at destination
Type of accommodation	0 = hotel 1 = other accommodation
Means of transport	0 = airline 1 = other means of transport
Time period	Three dummies: Period 2006–2007 (P1) Period 2008–2009 (P2) Period 2010–2011 (P3)

Table 2.

Descriptive statistics (N = 20,121).

Variables	Mean or %	Minimum	Maximum	Standard deviation
Internet usage intensity
Does not use the Internet	65.1%	0.00	4.00	1.64985
Internet for information on one of the travel elements	2.2%
Internet for information on both travel elements OR books/pays for one travel element	9.4%
Internet for information on one of the travel elements AND books/pays for the other travel element	2.1%
Internet to book and pay for both travel elements	21.2%
Educational background
No University degree	48%	0.00	1.00	0.49960
University degree	52%	0.00	1.00	0.49960
Travel experience	1.4715	1.00	8.00	0.79561
Trip length	7.6996	1.00	122.00	4.67507
Type of accommodation
Hotel	94.1%	0.00	1.00	0.23655
Others	5.9%	0.00	1.00	0.23655
Means of transport
Airline	72.8%	0.00	1.00	0.44488
Others	27.2%	0.00	1.00	0.44488
Time period
Period 2006–2007 (P1)	31.6%	0.00	2.00	0.82665
Period 2008–2009 (P2)	31.4%
Period 2010–2011 (P3)	37%

These data contained in Table 2 reflect how the Internet users for trip planning mostly use it to make the complete reservation, the two main elements of the trip. It is also revealed that the experience with various travel destinations is low: 1.5 destinations per year are visited on average. Data also show a high use of hotels and flights compared to other accommodation services or means of transport, which is surely in relation to other data that this table shows, such as the mean trip length, near 7.7 overnight stays.

Analysis and results

In Figure 1, we predict causal relationships between antecedents related to tourist characteristics and trip characteristics and trip planning autonomy, as well as a potential moderating effect of the economic crisis. To test these proposed relationships, we employed an ordered logit approach and used the SPSS v23 software. The dependent variable is an ordinal variable that measures the extent to which tourists use the Internet to plan a trip (Internet usage intensity). In particular, for the analyses, we ran three ordered logit models (see Table 3) so as to:

Test for direct relationships of the main independent variables, or antecedent factors (educational background, travel experience, trip length, type of accommodation and means of transport), with autonomy as the dependent variable (Internet usage intensity).

Add the potential direct relationship of crisis escalation (time period) with the dependent variable.

Add the potential moderating effect of crisis escalation to the main causal relationships between the antecedents and autonomy.

In terms of direct effects, the results in Table 3 (regression a) indicate a positive direct effect of education on autonomy, in support of H1. We also confirm a direct positive effect of travel experience on autonomy, in support of H2. The direct negative relationship between trip length and autonomy predicted by H3 is confirmed too.

Table 3.

Ordered logit model results (dependent variable: autonomy, N = 20,121).

Variables	Regression a	Regression b	Regression c
Educational background	0.709***	0.689***	0.610***
Travel experience	0.093***	0.118***	0.091***
Trip length	−0.024***	−0.024***	−0.025***
Type of accommodation	0.623***	0.542***	0.377***
Means of transport	−0.585***	−0.594***	−0.792***
Period 2008–2009 (P2)		0.401***	−0.050
Period 2010–2011 (P3)		0.740***	0.755***
Educational background × P2			0.261***
Educational background × P3			0.015
Travel experience × P2			0.094**
Travel experience × P3			−0.028
Trip length × P2			0.012
Trip length × P3			−0.008
Type of accommodation × P2			−0.029
Type of accommodation × P3			0.315**
Means of transport × P2			0.265***
Means of transport × P3			0.260***
Sig	0.000	0.000	0.000

Note: For time period, the baseline (reference) category is the one excluded from the regression. The effects of the categories that enter the regression represent the added effect, beyond that of the excluded category.

**p < 0.05.

***p < 0.01.

Regarding H4, we find the predicted direct negative relationship between service complexity and autonomy when service complexity is measured by transport; when it is measured by the type of accommodation, we find a positive effect, contrary to what we predicted, so we find partial support for H4.

The results (regression b) also show a direct, positive and significant effect of the periods associated with the crisis, P2 (2008–2009) and P3 (2010–2011), on autonomy. Although this relationship is not the central object of our research and, therefore, is not hypothesised, it reflects progressive growth in autonomy as the crisis worsens, as expected.

With regard to the moderating effect of the economic crisis (regression c), we find that the relationship between tourist education and autonomy is positively moderated by the economic crisis, significantly positive for period P2 (2008–2009), confirming H5. However, it is not verified for P3 (2010–2011), which implies that the moderating effect of the crisis on education–autonomy is not revealed beyond the P2 period, perhaps because, after 2 years of crisis, the possibility of further improving efficiency through education is not likely.

We also find support for H6. Results reveal a positive and significant moderating effect of economic crisis on the relationship between travel experience and autonomy for period P2 (2008–2009), the period of crisis explosion in Spain. But, similarly to the previous hypothesis, H5, the moderating effect of the crisis on the experience–autonomy relationship is not significant for P3 (2010–2011); therefore, it seems that, in the same way as in education, the improvement of the positive effects derived from experience reaches its maximum point in the initial period of crisis.

The negative moderating effect on the relationship between trip length and autonomy is not confirmed, thus H7 is not supported, not finding any significant moderating effect of the crisis period on this relationship.

Finally, the results indicate a positive moderating effect of the economic crisis on the relationship of service complexity with autonomy, both when measured by the type of accommodation and by the means of transportation, thus H8 is not supported because the resulting sign for the moderating effect is not the hypothesised one. For type of accommodation, the positive moderating effect is only found for the P3 period (2010–2011), the period of the most intense crisis, accentuating the unexpected effect found for H4, so that the lower autonomy linked to the hotel reservation, compared to other options, is accentuated in the 2010–2011 period. The effect for means of transport is positive and significant both for P2 (2008–2009) and P3 (2010–2011), reflecting that the crisis positively influences, contrary to expectations, the autonomous behaviour linked to non-airplane means of transport, that is, to the less common and, thus, more complex options. It seems that the crisis causes the search for savings to exceed the perceived risk linked to complexity.

Conclusions and implications

Current markets reveal widespread use of the Internet for trip planning. The tourism industry must gain a clear comprehension of this phenomenon if it is to manage and optimise its response. This study contributes to that effort by identifying some antecedents of tourists’ trip planning autonomy.

In particular, we show that certain characteristics enhance trip planning autonomy: The most educated and most experienced tourists plan their trips by themselves, reflecting their travel knowledge or skills. We also find differences in autonomy, depending on the trip characteristics, including its length, and the type of accommodations or means of transport. When perceptions of risk or uncertainty increase, tourists tend to be more conservative in choosing the distribution channel, relying less on their own autonomy.

Specifically, if the vacation has a longer duration, tourists are less likely to use the Internet, to avoid ruining a greater number of leisure days. Similarly, a greater number of overnight stays probably implies higher trip expenditures, which at the same time reinforces the avoidance of autonomy despite the potential benefits that would derive from finding a lower price on the Internet; that is, as investments increase, tourists appear to stop planning their trip autonomously to avoid ruining the whole investment. It seems that, at a certain point, the cost–benefit balance generated by the perceived risk linked to the duration of the trip tilts the choice between autonomy and professional third party, favouring the choice of a professional agent. In this regard, the findings related to the trip length’s positive effects on autonomy constitute a particularly important contribution in that, to the best of our knowledge, almost no research has explicitly and empirically analysed this relationship (trip length–autonomy); with the work of Coenders et al. (2016) being an exception, which also found support for it. In contrast, research pertinent to the topic has often just relied on the link between perceived risk and the use of the Internet, as well as on the identification of some characteristics that would affect the risk perceptions and thus the use of the Internet (e.g. Amaro and Duarte, 2013; Beritelli et al., 2007; Hiransomboon, 2012). Although most research related to the topic of autonomy does not deal directly with trip length, based on this previous literature and on the trip length concept, our study establishes several rationales that associate higher risk to longer trips, before formulating the hypothesis stating the negative effect of trip length on autonomy in trip planning.

Furthermore, the most common transportation method in our sample is a flight (booked in advance), which involves greater use of the Internet than other, less common alternatives. In addition, the unexpectedly positive relationship between service complexity and autonomy, measured by the type of accommodation (hotel vs. others), probably reflects a more intense use of tourist packages and travel agencies (and less use of the Internet) associated in particular with hotel bookings, especially in the analysed sample (i.e. trips for which accommodation and transport were booked in advance).

Finally, the economic crisis enhances or intensifies some tourist behaviours. It potentiates autonomy, such that as the economic crisis progresses, tourists become more autonomous, using the Internet to find the most efficient tourism solutions. This economic crisis also intensifies the relationships of some antecedents with autonomy, namely, education, or travel experience. During economic crises, certain skills, such as the efficient use of the Internet, and specific feelings, such as the need for security or to minimise the risk, become accentuated. However, the direct negative effect of the duration of the trip on autonomy is not reinforced by the context of the crisis. Perhaps because for the longest trips the need to reduce cost, often reflected by searching on the Internet (especially in a crisis context), coupled with the increasingly potentiated skills for using the Internet, may be counteracting the need for security. Therefore, the expected greater use of a professional agent to reduce the risk associated with long trips may be progressively counteracted as the crisis evolves.

These findings offer insights for managing and marketing tourism offerings successfully. First, the tourism industry should optimise online offerings, to address the differences in tourists’ skills, abilities and experience. To support their autonomy, the tourism industry should make using the Internet easy for everyone, with tools such as search engine optimisation, so that regardless of their education or experience, tourists can plan travel autonomously. In turn, tourism operators should recognise that more experienced and more educated travellers can better manage autonomous trip planning, such that they likely achieve better purchase outcomes. For many consumers, modern travel is a need instead of a luxury, so they have grown far more familiar with and informed about tourism options. The resulting trend implies that consumers may enjoy improved tourism outcomes as they engage in more independent, autonomous trip planning. Such a context implies the likely benefits and rewards for tourism providers and destinations if they invest in enhancing their online presence to stimulate positive outcomes.

Second, as consumers progressively become more skilled and experienced with trip planning, tourism agents should enable greater adaptation and personalised content. To compete, providers need to gather complete, updated information about their customers, including how they process information and how and why they buy. Operators thus should develop systems to capture market information that they can analyse and apply to develop better solutions for customer ‘experts’. They might track individual customer preferences and offer customised options that reflect their past behaviour, then present travel packages in dynamic formats to allow these expert customers to choose the services that best meet their individual needs.

Third, tourism agents should provide more information and more guarantees for trips that evoke higher perceptions of risk and uncertainty. For example, when planning trips for long stays, or when tourists choose new tourism services, it is a priori more difficult for them to behave autonomously. Operators seeking to promote new products or destinations on the Internet, focused on popular holidays, or that offer less common tourism services, should acknowledge this greater risk associated with autonomous trip planning and therefore provide additional, clear quality information. Moreover, providers should supply enough guarantees (e.g. insurance, clear refund policies) to mitigate risk perceptions, while also ensuring the security of all electronic transactions. This is even more important for long-haul destinations, generally linked to longer stays, which will have to reinforce further their efforts to minimise the associated perception of risk in order to be chosen by the tourist.

Fourth, in a related implication, traditional tourism intermediaries could benefit specifically from needs for advice or security when tourists must make particularly complex decisions. In these cases, tourists might combine online and offline services and agencies, depending on the nature of their consumption. Traditional agencies could take advantage of their expertise and boost their market positions by acting as trip consultants that specialise in more complicated trips or aiding less skilled or experienced tourists.

In particular, longer vacations (often linked to more complicated trips) might constitute a specific gap for specialisation of professional tourism intermediaries, online and offline.

Fifth, tourism providers should realise that the economic crisis intensified consumers’ economising efforts, including their autonomous trip planning. To find the best prices, customers conduct multiple queries, online and offline, before completing the booking. Prices are more transparent, and customers can easily compare various alternatives. Tourism providers should work to guarantee the best available rates on their websites and ensure that their offers are adaptable, meeting different needs at different prices. Such flexibility results in time and money savings for tourists. They also should be aware that a crisis generates a tendency for mistrust. Accordingly, providers should ensure ever more transparency in their proposals (services, prices, timing) and safety in their transactions.

Our findings from Spain should be of interest to the global tourism industry, which was greatly affected by the 2008 economic crisis. But there also are some limitations to our research. First, the national database we used is rigorous in its data collection standards, but it determined the measures that we could apply. Thus, although we had access to a massive data set that benefits population representativeness, scientifically well-developed measures would have been desirable for greater rigorousness. Some dimensions and concepts have been approximated by available variables (proxy measures) instead of using more appropriate measures based on explicit and direct questioning. For example, instead of a categorical measure built from the secondary data set, a multiple-item perceptual measure for autonomy would have favoured a more precise concept measure without restricting the analysis options. Second, the conditions that we required at the outset of our analysis – so we considered only cases in which tourists booked both accommodation and transport – restricted our study to the most complex scenarios, thus ignoring other possible scenarios.

Further research could investigate differences between regions or countries related to these identified antecedent factors. Researchers also might study the antecedents of autonomy according to different, specific agents on the Internet (e.g. online travel agent, infomediary) or the specific function required (e.g. information search, booking, payment). Moreover, further exploration of the relationship between trip length and trip planning autonomy might provide interesting outcomes (e.g. potentially different effects for trips of standard duration versus trips of non-common duration for which no packaged tours are offered). Finally, the topics involved in this research could be studied based on scientifically developed measures, opening new opportunities for analysis.

Footnotes

Acknowledgements

The authors thank the Institute of Tourism Studies of the Government of Spain for facilitating the database used to accomplish this study.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Milagros Fernández-Herrero

Rosa María Hernández-Maestro

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