2.1. Consumer Buying Stages
One of the major areas of consumer behavior theory and research has been the focus on consumer buying stages. It is recognized that people go through an ordered, sequential set of steps and decision-making when buying products and services. Several models have been proposed of buying process stages and those by Howard and Sheth in their book [15
]. The Theory of Buyer Behavior, and the Engel, Kollat, and Blackwell [16
] consumer decision model from their book, Consumer Behavior, are among the most popularly cited. The Howard-Sheth model identified sequential buying process stages as being need recognition, search for information (internal and external), evaluation of alternatives, purchase, post-purchase evaluation, and divestment [15
]. Authors in tourism have made slight changes to this model, including adding consumption (actual travel and destination experiences) after purchase and replacing divestment with the remembering and sharing of travel experiences [17
Engel, Kollat, and Blackwell [16
] proposed the EKB consumer decision model, which includes inputs, information processing, decision-making process, decision variables, and external factors. The EKB model is similar to the Howard-Sheth model in the decision-making part. Only a few studies in tourism and hospitality have so far applied the EKB model [18
]. Osei and Abenyin applied the EKB model to identify the use and influence of social media across all stages of travel decision-making for trips to Ghana in West Africa [20
]. Dimitriou and AbouElgheit used EKB as a base in a conceptual paper, proposing a five-stage decision-making model for Generation Z travelers in the context of social media and mobile technologies [18
]. Han, Zhang, and Wang (2020) also used EKB as a base in a study of online ticket reservation systems in China [19
These models of consumer buying stage processes are widely accepted; however, it is noteworthy that most were developed in the pre-Internet era and buying behavior has significantly changed since then. Before describing these changes, the next section of the literature review considers the research on travel planning and consumption processes.
2.2. Travel Planning and Consumption Processes
Travel planning and consumption can be considered as a distinctive type of consumer buying. There has been a considerable volume of research on how people plan travel trips and consume the products and services of the hospitality and tourism sector. Woodside and King put forward a complex purchase consumption system for leisure travelers comprised of 19 steps in three stages: (1) thinking and planning actions prior and during travel; (2) specific decisions and actions; and (3) trip event-specific and trip-global evaluations and conations [21
]. Choi et al. depicted a hierarchical and sequential structure of the travel planning process consisting of vacation sub-decisions (departure date, travel budget, length of trip, travel mode, accommodation, attractions, and activities), information sources (various websites, travel agents and tour operators, WoM, guidebooks, TV and magazines), and decision steps and stages (planning initiation, destination choice, booking and purchase, and onsite stay) [22
The traditional view of just three stages (pre-, during-, and post-travel) has been challenged both by academic researchers [18
] and practitioners [23
]. Dimitriou and AbouElgheit outlined five steps in the decision-making process: (1) inspiration; (2) need for social recognition; (3) planning, search, and evaluation; (4) booking; and (5) post-booking evaluations [18
]. From a practitioner viewpoint, Team Tourism Consulting identified four stages when travelers use online information—dreaming, enthusing, and informing; planning, selecting, and booking; visiting and enjoying; and repeating, recommending, and recollecting [24
]. The Dentsu approach is discussed later in reviewing the AISAS model [23
A consensus has, therefore, developed that there are more than three stages in the decision process since the Internet took hold of markets. A cycle of travel behavior can now be divided into the triggering of intention, seeking travel information, booking products, using products during travel, and sharing personal experiences after trips. People may develop travel intentions because of friends sharing or advertising. Before departure, they search for information and products on travel platforms and make purchases. During travel, they also search for information on itineraries, attractions and activities, transportation, and restaurants through online platforms to make trip experiences more enjoyable. After returning home, they share experiences with friends or netizens [25
]. These functions are all greatly facilitated by online travel platforms of various types and that is the next topic in this literature review.
2.3. Online Travel Booking and Sales
Online information and travel platforms have revolutionized how people plan, book, and enjoy travel experiences. Due to ICT advancement and the popularity of the Internet, consumer purchase behaviors have changed. Compared with the traditional channels of tourism distribution, the advantages of the Internet lie in information richness, and convenience of booking and purchasing [3
]. Tourists are now more dependent on the Internet for information search, planning, and purchasing travel products and services [1
]. In addition, this is making independent travel options more popular. According to the Taiwan Ministry of Transportation and Communications, most Taiwanese tourists (90.1%) plan their own travel itineraries and travel by themselves (87.9%) rather than in organized tour groups [30
]. Independent travelers make use of social media across the entire travel process [20
]. It is now very common for travelers to search, organize, and share travel experiences through various online tools such as blogs, social media sharing sites, chat, and social knowledge sharing sites [28
]. These platforms provide individual control and greater autonomy. Using them, allows travelers to move around at their own pace, planning individualized itineraries, and have more in-depth experiences of life at destinations thereby better appreciating local cultures and lifestyles, while promoting more self-learning and personal growth. These benefits created through autonomous behavior can result in higher levels of company and destination brand belief and post-trip satisfaction and loyalty [28
In addition, online travel agencies (OTAs) and other online tourism suppliers have the (big) data to be sensitive to changes in customer needs and market trends, and thus can update and develop new products to suit the market [33
]. When a company is able to present its new products to the market faster than its competitors, it can increase sales volume and market share, and achieve greater profitability, productivity, and effectiveness [35
]. With rapid socioeconomic changes and digital development, innovative and precise promotions help change customer purchasing behaviors and improve an organization’s competitive advantage [37
]. The widespread use of mobile communications and social media has completely changed the way consumers live and how organizations conduct marketing [39
]. One of these changes has been the emergence of content marketing and co-creation.
2.7. The AIDMA and AISAS Models
AIDA was the first hierarchy of effects model in marketing. It was followed by AIDMA (Attention-Interest-Desire-Memory-Action) proposed by Hall, which was the predecessor of the AISAS (Attention-Interest-Search-Action-Share) model [55
]. Due to the growing impact of Internet technology on consumer behavior, Dentsu observed that the way consumers receive marketing information was being influenced. They were no longer just passively receiving information; now they were actively seeking it. Dentsu proposed the AISAS model to better characterize consumer behavior in the Internet era [23
]. A Japanese advertising company noticed that the mode for consumers to get marketing information had changed from just receiving to actively looking for materials. The new AISAS model was proposed and considered to be more suitable than the traditional AIDA or AIDMA models for explaining consumption behavior in the Internet era. Some research studies have been done based on the AISAS model [56
]. However, it has been used in very few studies related to tourism and hospitality [62
] and investigations of online travel consumption behavior are also scarce.
Chen & Huang integrated S-O-R (Stimulus-Organism-Response) into AISAS to reflect the role of eWoM [64
]. The major difference between AISAS and AIDMA lies in search and sharing. With the Internet, consumers readily search for information about the products or services they want and are more willing to share online purchasing experiences. The conceptual difference between AISAS and AIDMA lies in the change in advertising, which has switched from consumer persuasion to information interactions. This is caused by communication environment changes; the rise and stature of the Internet make it an inseparable part of consumers’ daily lives. All necessary information is available there; they are no longer limited to television, broadcasting, newspapers, and magazines [27
]. Moreover, consumers have transformed from information receivers to active information seekers and even interact with those who publish information [65
]. The popularity of mobile devices is one of the catalysts for this transformation. Mobile devices have changed lifestyles and have become a new communication media channel, which enables consumers to choose the information they want to receive anytime and anywhere. Consequently, advertising can also work by interacting with consumers, not through informing and persuasion [66
]. When consumers see advertisements for a brand or company via television, newspapers, and magazines, they become interested in the products and search for more relevant information. The traditional way of advertising involves impressing consumers with ads to promote purchase. However, it is more convenient and easier for consumers to search for information on the Internet and they can find more detailed product and service information by themselves. The behavior of searching for products and services often accidentally leads to the possibility of other products being purchased. Therefore, compared with traditional forms of marketing, the active search for information is more effective in promoting actual purchases. Information search has become an important part of consumer behavior as it combines information with user experiences and enables consumers to use the Internet to easily communicate with each other. This is often a determinant of the WoM for a product or service [67
Due to the rapid flow of information, not only do brands communicate with consumers but consumers themselves have become part of advertising. When describing consumer decision-making behavior, Dentsu replaced “desire” and “memory” in the AIDMA model with “search” and “share” because they were more applicable to the Internet generations. In the AISAS model, a product or an advertisement attracts attention and the information is used to maintain consumer interest in the product. However, the difference lies in the driving force of the Internet, which enables consumers to adapt from passive recipients into active seekers of information. When their search is completed, consumers take “action” to make purchases. Having used the products or services, they begin to “share” their first-hand user experiences with others in the form of eWoM. The emergence of eWoM is not only a source of information for potential consumers but also starts the next round of attention and search. Compared with the AIDMA model, AISAS emphasizes the process of search and sharing, which fully embodies the media usage habits and consumer behaviors of the Internet generations. In addition, the search and sharing behaviors are effective in increasing purchase frequency [68
]. Abdurrahim, Najib, and Djohar explored the influence of destination marketing organization (DMO) social media on tourist choices of destinations based on the AISAS model [62
]. Their research analyzed whether DMO social media promotions attracted the attention and interest of tourists to pique their desire to search for relevant information about destinations. They also investigated the impact of information seeking on tourist decision-making and whether visiting destinations influenced the sharing of experiences.
Consumers now increasingly look for their ideal products and services via online search. The information they find not only includes those published by companies and destinations about certain brands, but also feedback and comments, both positive and negative, uploaded by consumers who have already used them. The persuasiveness of reviews and comments is almost equal to or more influential to the advertising of companies and destinations [31
]. Having made purchases, consumers share their own experiences and suggestions with others, which triggers the next cycle of search [70
When consumers experience a series of psychological changes caused by external incentives and internal needs, their attention is drawn to certain products or services. This may generate interest, search for relevant information, and decisions on whether to purchase products or services [71
] and then make the actual purchase. Shim, Eastlick, and Lotz explored the relationship between search intent and purchase intentions [72
]. This revealed that the intention to search for product attributes online was a determinant of purchase intention. Searching for information and booking products are two stages before travel [73
]. Lee, Qu, and Kim studied the online shopping behavior of travelers, expanded the theory of reasoned action (TRA) with search intent and purchase intention, and emphasized the importance of information search as a prerequisite for travel decision-making [74
]. Chen and Huang established the model of Online Word-of-Mouth Marketing (OWoM) based on AISAS, which was represented as attention → interest → search → action → share → OWoM [64
]. Lin and Chen expanded the AISAS model by adding sociality, exploring the effect of an AR (augmented reality) wedding invitation app [75
]. The results demonstrated positive relationships between attention and interest, interest and search, search and sociality, sociality and behavior, and behavior and sharing. Hendriyani et al. used the AISAS model to analyze the online consumer behavior of Twitter users and found that there were positive relationships between attention and interest, interest and search, and search and behavior [56
]. Cheah, Ting, Cham, and Memon applied AISAS to compare the effect of celebrity-endorsed advertising and selfie promotion and found that the AISAS model with selfie promotion produced better predictive ability while attention had a positive impact on interest, interest on search, search on behavior, and behavior on sharing [76
]. Therefore, the following hypotheses were proposed:
Hypotheses 1 (H1).
Attention has a positive effect on interest.
Hypotheses 2a (H2a).
Interest has a positive effect on search before travel.
Hypotheses 2b (H2b).
Interest has a positive effect on search during travel.
Hypotheses 3a (H3a).
Search before travel has a positive impact on action.
Hypotheses 3b (H3b).
Search during travel has a positive effect on action.
Hypotheses 4 (H4).
Action has a positive impact on post-travel sharing.
There are also nonlinear effects in the AISAS model in addition to the linear ones. Hendriyani et al. (2013) found that attention had significant positive effects on search, attention on action, attention on sharing, interest on search, interest on sharing, and search on sharing [56
]. Cheah et al. found that attention had a significant positive effect on search, interest on behavior, and search on sharing [76
]. Abdurrahim, Najib, and Djohar determined that: (1) social media had a positive impact on attention, interest, and search; (2) attention had a positive effect on sharing; (3) action had a positive impact on sharing; and (4) interest had no significant impact on action [62
]. Kono proposed that sharing one’s own experience or suggestions with others after using certain products triggers the information search of other people, which is the beginning of another round of the tourism cycle [70
]. Therefore, the following hypotheses were proposed:
Hypotheses 5 (H5).
Attention has a positive effect on search before travel.
Hypotheses 6 (H6).
Attention has a positive effect on search during travel.
Hypotheses 7 (H7).
Interest has a positive effect on action.
Hypotheses 8a (H8a).
Search before travel has a positive impact on sharing after travel.
Hypotheses 8b (H8b).
Search during travel has a positive impact on sharing after travel.
Hypotheses 9 (H9).
Post-travel sharing has a positive effect on attention.
Independent travelers may develop deeper understandings through their travel experiences, thus achieving self-affirmation and growth. They have a high degree of autonomy and flexibility in travel planning in terms of transportation, accommodation, and recreational activities [77
]. Independent travel is more autonomous and flexible [79
] and authentic experiences are considered to be the charm of travel [80
Loker-Murphy explored the motivations of backpackers when traveling in Australia, which were divided into four types: escape/relaxation, society/stimulation, self-development, and pursuing a sense of achievement [81
]. Elsrud (2001) suggested that backpackers love traveling freely and start in-depth traveling along their planned routes when they can, hoping to deeply explore local areas through their own perspectives and realizing their own desires and needs [82
]. This implies that independent travelers can achieve learning and growth goals in the process of traveling. Loker-Murphy and Pearce discovered that backpackers prioritize getting to know others, independent organization, flexible itineraries, and long travel times [84
]. Murphy emphasized the pursuit of pleasant travel experiences and the importance of interpersonal interaction with other tourists by sharing their new experiences [85
]. Moreover, life growth and change brought about by traveling are also considered as characteristics of independent travelers [80
]. Chen found that for the The Net Generation who seek innovation, change, and customization, travel platforms provide them with great autonomy where they can fully control travel pace, plan itineraries, experience local life, and understand local culture more deeply, and even learn and grow on journeys [32
]. Therefore, the following hypotheses were proposed:
Hypotheses 10 (H10).
Learning and growth have a positive impact on post-travel sharing.
Hypotheses 11 (H11).
Search before travel has a positive impact on learning and growth.
Hypotheses 12 (H12).
Search during travel has a positive effect on learning and growth.
Hypotheses 13 (H13).
Action exerts a positive effect on learning and growth.
This research explored the online travel consumption behavior of the Net Generation based on the AISAS model along with the introduction of the variable of learning and growth from the perspective of independent travel. The results are thought to contribute to theory and practice. They potentially enrich marketing theories related to online business by integrating the AISAS model with information search behaviors across the entire trip process. From a practical viewpoint, the findings identify key factors influencing the purchasing and sharing behavior after travel which in turn stimulates attention and leads to a new cycle of the AISAS model. This should be valuable for companies and destinations in adopting appropriate marketing strategies and delivering needed information, which enhances customer engagement and builds loyalty. The conceptual research model and hypotheses are shown in Figure 1