decision is desirable. Human decisions don’t actually process information in such a rational way. Kahneman and Tversky
(1979) contends that people value gains and losses differently, that is, decision base is put more interest on perceived gains
rather than perceived losses. For example, when people were given to equal choices, one explained as possible gains and the
other as possible losses, people responds to the former even though the result is same in the end. Losses have more
emotional impact that an equivalent amount of gains. Rather, value should be treated as a function in two arguments: this
function is a representation of the difference in utility (amount of value or sacrifice) that is achieved as a result of a certain
amount of gain or loss. Interesting is that everyone would have a different value function that serves as a reference point and
the magnitude of the change (positive or negative) from that reference point (Kahneman and Tversky, 1979; Gupta and Kim,
2010).
According to prospect theory, customers maximize the value of the choice and decision making under conditions of
uncertainty. Furthermore, people put more favorable efforts on positive outcomes under a condition of certain than positive
outcomes under a condition of probable. This effect can be explained as people tend to choose smaller but certain gains
rather than larger but probable gains (Gupta and Kim, 2012).
Mental accounting theory contends that individuals divide their current and future assets (e.g., stock, options, and real
estate) into separate, and which generate a disposition effect (Thaler, 1980). The importance of this theory can help why
investors choose their money as ‘safety (risk-averse)’, or ‘high-risk (risk-loving)’ in investing into separate accounts. Mental
accounting theory considers compound outcomes, in contrast prospect theory is defined over single, unidimensional out-
come. Since social media usage decisions could be affected by more than one decision factor (such as relations, risk, conve-
nience), mental accounting theory seems better fit for social media usage decision making, individuals evaluate, first,
potential transactions, second, approve and disapprove of each potential transaction. The first stage is a judgment process
while the second is a decision process (Thaler, 2008). For evaluating potential transactions, Thaler (2008) proposed two types
of utility: acquisition utility and transactions utility. Acquisition utility is the value of the goods received compared to the
spending, the latter relies on solely on the perceived merits of the ‘‘deal’’ (Thaler, 2008). For making usage decisions, users
make decisions to maximize their total utility with reference to the mental account. In social media information searching,
the ultimate use of social media information searching behavior would be same. Acquisition utility may, however, be
N. Chung, C. Koo / Telematics and Informatics 32 (2015) 215–229 219
different as cost may vary between different online search channels, therefore, this study identifies only transaction utility
and total utility, not acquisition utility.
2.3. Social media for travel information searches
Social media can generally be regarded as Internet-based applications that carry consumer-generated content encom-
passing media impressions created by consumers, typically informed by relevant experience, and archived or shared online
for easy access by other impressionable consumers’’ (Xiang and Gretzel, 2010, p. 180). In our study, social media may be
explained as a group of Internet-based applications that exist on the Web 2.0 platform and enable Internet users from all
over the world to share ideas, thoughts, experiences, perspectives, information, and forge relationships (Chan and Guillet,
2011; Sigala et al., 2012). Furthermore, we classify social media use in this study as a combination of self-presentation
(self-disclosure) and social presence (media richness) dimensions, as represented in Table 3.
Social media provide an environment that facilitates users’ interaction and their search for services. Hence, the number of
people who perceive that they are benefiting from social media is increasing dramatically. We, therefore, studied the role of
search engines in travelers’ of the Internet and adapted the online travel information search behavior from Xiang and Gretzel
(2010)’s study. The key components of social media usage for travel information search are categorized as followings: (1) the
online traveler who is engaged in personal and trip-related needs; (2) the online tourism domain that is providing
informational entities among individual consumers through means of social media rather than the hypertextual nature of
the Internet search; (3) the search engine that determines the representation of the tourism domain which are related to
the design of interface features, search result rankings, metadata, and paid links that influences the travelers’ perception
and decision making (Xiang and Gretzel, 2010).
Traditionally, tourists have consulted travel magazines, newspapers, and books to retrieve the information they need.
Over the last 15 years, however, these traditional media sources have been replaced by Internet websites that provide travel
information and allow users to share their experiences. During the pre-travel phase, travelers typically perform extensive
travel information searches and make online bookings, and during the post-travel phase, they share their experiences of their
travel activities, services, and products (Jeng and Fesenmaier, 2002; Vogt and Fesenmaier, 1998). Here we need to define
information search that can explain information on various products and services sought by a traveler during a trip, vs.
‘information posting,’ which is defined as a simple rating, comments, photos, or videos of a product or service during the trip
found in social media (Sigala et al., 2012). Web 2.0 allows the tourism industry to change the ways in which they tradition-
ally conduct their internal and external business operations, with travelers as more proactive information providers who
relay their travel experiences (e.g., travelers as co-creators; travelers as co-distributors) beyond just information processing
(Sigala et al., 2012).
Many travel-related firms have started to integrate the growing number of social media available through smart devices,
which provide an increasing diversity of travel-related services, such as looking up destination for tourist activities through
travel information searches. Therefore, it is critical to understand changes in technologies and travelers’ behaviors that
impact the creation, distribution, and accessibility of travel information (Werthner and Klein, 1999; Xiang and Gretzel,
2010).
Today, social media has evolved into a multitude of different social network services (e.g., Instagram.com, Four-
square.com) that allow people from various locations to form relationships or share their travel-related experiences by post-
ing photos and videos (Parra-López et al., 2011). This information can be very useful to potential travelers and can be
searched at their convenience. Tourism related social media applications on smart-devices can serve as tools for finding
more travel information, with search engines providing direct access to information (Xiang and Gretzel, 2010). If a traveler
wants to read about someone else’s experiences in and around a certain destination, the traveler will attempt to search for
information and interact with other social media users. Therefore, travelers can find real-time information among network
members, and the providers of that information receive gratitude from users all over the world. Although their importance
and value have been noted, there has yet to be a study conducted on empirical social media usage for travel information
search. While the perceived value theory can explain a traveler’s evaluation of a new IS for searching travel information,
our study extends the concept to understand travelers’ use behavior regarding this new technology.