Impact of Social Media on Consumer Behaviour

Abstract

The goal of this paper is to research empirically the role of social media in consumers' decision-making process for complex purchases-those characterised by significant brand differences, high consumer involvement and risk, and which are expensive and infrequent. The model uses the information search, alternative evaluation, and purchase decision stages from the classical EBM model. A quantitative survey investigates up to what degree experiences are altered by the use of social media. Results show that social media usage influences consumer satisfaction in the stages of information search and alternative evaluation, with satisfaction getting amplified as the consumer moves along the process towards the final purchase decision and post-purchase evaluation. The research was done among internet-savvy consumers in South-East Asia, and only considered purchases that were actually made by consumers, not including searches that were abandoned.

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Int. J. Information and Decision Sciences, Vol. X, No. Y, xxxx 1
Copyright © The Author(s) 2018. Published by Inderscience Publishers Ltd. This is an Open Access Article
distributed under the CC BY license. (http://creativecommons.org/licenses/by/4.0/)
Impact of social media on consumer behaviour
Duangruthai Voramontri*
George Herbert Walker School of Business and Technology,
Webster University,
Bangkok, Thailand
Email: duangruthai@gmail.com
*Corresponding author
Leslie Klieb
George Herbert Walker School of Business and Technology,
Webster University,
Bangkok, Thailand
Email: kliebl@webster.ac.th
Abstract: The goal of this paper is to research empirically the role of social
media in consumers’ decision-making process for complex purchases – those
characterised by significant brand differences, high consumer involvement and
risk, and which are expensive and infrequent. The model uses the information
search, alternative evaluation, and purchase decision stages from the classical
EBM model. A quantitative survey investigates up to what degree experiences
are altered by the use of social media. Results show that social media usage
influences consumer satisfaction in the stages of information search and
alternative evaluation, with satisfaction getting amplified as the consumer
moves along the process towards the final purchase decision and post-purchase
evaluation. The research was done among internet-savvy consumers in
South-East Asia, and only considered purchases that were actually made by
consumers, not including searches that were abandoned.
Keywords: social media; consumer decision-making; EBM model; EKB
model; information search; complex purchase; online consumer behaviour;
consumer satisfaction.
Reference to this paper should be made as follows: Voramontri, D. and
Klieb, L. (xxxx) ‘Impact of social media on consumer behaviour’, Int. J.
Information and Decision Sciences, Vol. X, No. Y, pp.000–000.
Biographical notes: Duangruthai Voramontri graduated in Economics from
the University of Madras in India, and earned an MBA from Webster
University, Thailand. Her research interests include consumer behaviour,
decision-making and behavioural economics.
Leslie Klieb earned his PhD in Theoretical Physics from the State University of
Groningen, the Netherlands. After some post-doctoral work in physics at the
Racah Institute of Physics of the Hebrew University, Jerusalem, Israel, and
elsewhere, he taught computer science in the USA. His interest in statistical
analysis led him to quantitative business research. He has been a supervisor of
DBA candidates at the Grenoble School of Management, France, and taught
online complexity science and statistics in the PhD Doctoral Program for a
business degree of the University of Liverpool in Association with Laureate,
Inc. He is currently a Lecturer at Webster University Thailand.

2 D. Voramontri and L. Klieb
1 Introduction
In this paper, a study is made of the decision process of consumers for complex
purchases, with a special emphasis on how this process is influenced by possible use of
social media. Complex buying behaviour in this context refers to expensive infrequent
purchases with high consumer involvement, significant brand differences, and high risk.
Social media is a relatively recent phenomenon. Over the last decade, the World
Wide Web has seen a proliferation of user-driven web technologies such as blogs, social
networks and media sharing platforms. Collectively called social media, these
technologies have enabled the growth of user-generated content, a global community, and
the publishing of consumer opinions (Smith, 2009). This movement now dominates the
way we use the web and has given rise to popular platforms like Facebook, YouTube,
Instagram and Twitter, where people connect, produce and share content.
The social media revolution has led to new ways of seeking and obtaining
information on the multitude of products and services in the market. It has enabled
consumers to connect and discuss brands with each other quickly and easily (Powers
et al., 2012). Consumer opinions on products and services are now increasingly
dominated by strangers in digital spaces, which in turn influence opinions in the offline
space (Smith, 2009). Social media have empowered consumers, as marketers have no
power over the content, timing or frequency of online conversations among consumers
(Mangold and Faulds, 2009).
The use of social media by consumers is anxiously followed by marketers, but not
much is known about how it influences the consumers’ decision-making. Many studies
focus on consumer behaviour in the online shopping environment, but without
consideration of the effects of the internet on the different phases of consumers’ decision
process (Darley et al., 2010). This research explores how the presence and abundance of
these new information sources is influencing the decision process of consumers for
complex purchases.
The classical EBM model (Engel et al., 1990) is chosen to study the consumers’
decision process due to its simplicity and versatility. The model consists of five stages:
need recognition, information search, alternative evaluation, purchase decision, and
post-purchase evaluation. The research seeks to ascertain the relevance of the model in
the context of social media usage.
A quantitative survey was used to retroactively attempt to explore aspects of the
phases in the decision process. A total of 158 participants completed the survey, and their
responses were used to analyse the decision-making process of their complex purchase
instances.
2 Literature review
2.1 History and classification of social media
The creation of social networking sites like MySpace in 2003 and Facebook in 2004 led
to the popularity of the term ‘social media’. The term ‘Web 2.0’ was also first used
around this time to describe the new use of the internet as a platform where content is no
longer created and published by individuals, but is continuously modified by many users
in a participatory and collaborative manner (Kaplan and Haenlein, 2010). Web 2.0 led to

Impact of social media on consumer behaviour 3
the introduction of collaborative projects, Wikis and interactive blogs; thus facilitating
the creation of user networks, and the flow of ideas, information and knowledge among
users (Constantinides, 2014).
User generated content (UGC) refers to media content that is publicly available and
created by end-users (Kaplan and Haenlein, 2010) and, according to OECD (2007), it
should have been created outside professional routines, without a commercial market
context. The latter refers to the content creator; the topic of the UGC can be (and often is)
a commercial product or service regarding which the discussants volunteer their opinions.
From these concepts of Web 2.0 and UGC, social media can be defined as a group of
internet-based applications that build on the ideological and technological foundations of
Web 2.0 and that allow the creation and exchange of UGC (Kaplan and Haenlein, 2010).
Social media can be categorised into: collaborative projects (Wikipedia, blogs), content
communities (YouTube), social networking (Facebook), virtual game worlds (World of
Warcraft), and virtual social worlds (Second Life) (Kaplan and Haenlein, 2010).
Nowadays, e-commerce and professional review sites also accommodate UGC, for
instance, Amazon and dpreview.com.
2.2 Social media as electronic word-of-mouth
The concept of word-of-mouth (WOM), introduced in the 1950s, has been revitalised by
the internet. According to Arndt (1967), WOM is a “person-to-person communication
between a receiver and a communicator whom the receiver perceives as non-commercial
regarding a brand, product, or service.”
WOM is a primary source of information for consumer buying decisions, shaping
attitudes, perceptions and expectations of brands, products and services (Kimmel and
Kitchen, 2014), and impacting all phases of consumer decision-making: from product
awareness to selection and post-purchase evaluation.
WOM has gained new prominence today as a result of greater inter-connectedness of
people on social media (Kimmel and Kitchen, 2014). Online or electronic word-of-mouth
(eWOM) is a form of WOM where internet users provide reviews and ratings to all kinds
of products, brands and services on review sites (Bronner and Hoog, 2010). It is defined
as “any positive or negative statements made by potential, actual, or former customers
about a product or company, which is made available to a multitude of people and
institutions via the Internet” (Hennig-Thurau et al., 2004). Electronic WOM can be
disseminated in many ways, on social media platforms or the comments sections on
e-commerce sites; and the information disseminated is rarely available through
company-led marketing communications.
Content generated by internet users, who are also consumers, is generally perceived
to be independent of commercial influences (Bronner and Hoog, 2010). This trust makes
consumers go to forums, blogs and other unbiased social media sources to gather
information for purchase decisions (Powers et al., 2012).
2.3 Variations in purchase decision behaviour
Kotler and Armstrong (2014) classified buying behaviour along two axes: high or low
consumer involvement, and significant or few brand differences. The four types of
purchase behaviour they discerned are summarised in Table 1.

4 D. Voramontri and L. Klieb
Table 1 Types of purchase behaviour
Purchase behaviour Characteristics Examples
High consumer involvement Car
Significant brand differences
Expensive
Infrequent
Complex buying
High risk
Laptop
High consumer involvement Carpet
Few brand differences
Expensive
Infrequent
High risk
Dissonance-reducing
Price sensitive
Furniture
Low customer involvement Household goods
Little brand difference
Habitual buying
Frequent or repeat purchases
Groceries
Low customer involvement Cookies
Significant brand differences
Variety-seeking buying
Brand switching for variety
Restaurant
Source: Kotler and Armstrong (2014)
Complex buying involves high risk, and hence information gathering and evaluation of
product choices assume greater importance. It differs from dissonance-reducing
behaviour, also high risk, in that there are significant brand differences, and would have
the consumer passing through all stages of the decision process. Therefore, this research
focuses on complex buying situations where the influence of social media is presumed to
be most visible.
2.4 Consumer buyer behaviour
There are many ways to model consumer behaviour, depending on the goal of the
research, but a useful method is the decision-process approach which studies the events
that precede and follow a purchase, and that explains the way decisions are made
(Karimi, 2013). Consumer decision-making could be defined as the “behaviour patterns
of consumers, that precede, determine and follow on the decision process for the
acquisition of need satisfying products, ideas or services” (Du Plessis et al., 1991).
Consumer models have ranged in their complexity, with the simplest ones including the
economic model (where consumers follow the principle of maximum utility and spend
minimum amount for maximum gains), the psychological model (based on Maslow’s
hierarchy of needs, where individuals are motivated by their strongest needs), the
Pavlovian learning model (behaviour brought about by practice, learning and experience),
and sociological model (buying influenced by society or social norms). Towards the end
of the 1960s, several complex models were developed, for instance Nicosia (1966), Engel

Impact of social media on consumer behaviour 5
et al. (1978) and Howard and Sheth (1969). These three models are sometimes referred to
as the ‘grand models’ of consumer behaviour.
The Nicosia (1966) model had four fields of actions in the decision process:
consumer attitude-formation, information search and evaluation, the act of purchase, and
post-consumption feedback. The Howard and Sheth (1969) model also had four sets of
variables: inputs (stimuli); perceptual and learning constructs; outputs (consumer
behaviour, purchase decision); and external variables (social, psychological and
marketing factors). The EKB model, later renamed EBM (Engel et al., 1990), has four
parts: information input, information processing, decision stages, and decision process
variables. The decision process of consumers consists of five sequential phases: need
recognition, search for information, alternative evaluation, purchase (choice), and
outcomes (post-purchase), which are each influenced by individual characteristics,
environmental influences and psychological processes.
The three grand models captured the stages of the purchase process but differed in
their emphasis on different variables and their presentation. However, they were
criticised as being too complex, with many poorly defined variables, vague and complex
interrelationships, and lack of empirical support (Karimi, 2013). As a reaction, in the
1970s–1980s, simpler models like the theory of planned behaviour (TPB) by Ajzen, and
the Bettman model were introduced. The TPB does not address the decision process,
while the Bettman model illustrates the process as a decision tree governed by how
consumers process external information under the constraint of limited information
processing.
2.5 The classical or traditional purchase model
While the grand models were overreaching, they contained a view of the decision process
that was concise, plausible, and in agreement with the work of Herbert Simon on
decision-making (Simon, 1960). The classical model simplified the grand models by
eliminating the numerous variables and their interrelations, and focusing only on the five
decision stages of problem recognition, information search, alternative evaluation,
purchase decision and post-purchase behaviour. Often referred to as the EKB model or
EBM model, this has been one of the most well-known and commonly-used standard
model in consumer behaviour research (Karimi et al., 2015).
Figure 1 Stages of the EBM model and Simon’s model (see online version for colours)
In the realm of decision science, Simon’s model is considered a pioneering
decision-making model since 1960. He broke down decision-making into the three stages

6 D. Voramontri and L. Klieb
of intelligence, design and choice. The intelligence phase involves the classification of
the problem, and the gathering and processing of information. During the second phase of
design activity, alternatives are generated and evaluated; and in the final choice phase, an
alternative is chosen. When compared with the classical model, Simon’s intelligence
phase is a combination of the first two stages: need recognition and information search.
The design phase is the third stage of alternative evaluation, while the choice phase
coincides with the purchase decision stage.
The five stages of the classical model are described in the following paragraphs.
Stage 0 – need recognition
Need recognition is the first stage of the buyer decision-process. Internal stimuli (like
hunger) or external stimuli (e.g., advertisements) make the consumer realise that there is
a difference between their current state and their desired state (Kotler and Armstrong,
2014). This is generally regarded as the trigger that initiates a purchase decision process,
and is the precursor of all subsequent consumer-initiated activities such as information
search, evaluation and purchase. Choices that establish a need for a purchase may depend
on many varied individual characteristics. With the many complicated drivers, this stage
is sufficiently different from the later stages, and is hence not considered in this study.
Stage 1 – information search
Following need recognition, a consumer undertakes a ‘search’ into memory to determine
if enough is known about the available options to make a choice. If internal knowledge is
not sufficient, an external search is required to supplement existing knowledge. Complex
buying with its infrequency will involve a greater amount and intensity of search.
External search is typically undertaken through personal sources (e.g., friends and
family), commercial sources (e.g., advertisements and salespeople), and public media
sources (e.g., newspapers, magazines, television, and internet). User reviews on websites
like Amazon.com or TripAdvisor are seen as providing a more complete and reliable
product assessment (Kotler and Armstrong, 2014). Search continues until enough
information of sufficient quality is gathered, but can be constrained by the availability
and quantity of information. While low availability certainly limits decision-making, too
much information also hinders good decisions due to limits on the consumers’
information processing capabilities. Social media adds a new element to information
search, and its influences are therefore the main subject of this study.
Stage 2 – evaluation of alternatives
Once information has been collected, the consumer uses it to evaluate and assess the
alternative product choices to arrive at a purchase decision. The alternative evaluation
and information search stages, though presented separately, are intricately intertwined
during decision-making, and consumers often move back and forth between the two.
Alternative evaluation involves the selection of choice alternatives and evaluative
criteria. Once determined, the performance of the considered choices are compared along
the salient criteria, and finally, decision rules are applied to narrow down the alternatives
to make a final selection. This stage leads to the formation of beliefs, attitudes and
intentions, leading to the subsequent stage of purchase.

Impact of social media on consumer behaviour 7
Stage 3 – purchase decision
Purchase decision refers to the final choice or selection made regarding which product to
buy. The act of purchase is the last major stage, with the consumer deciding on what to
buy, where to buy, and how to pay. Purchase is a function of intentions, environmental
influences and individual situations. Some of the influences that can affect the purchase
action include the time available for decision-making, information availability and the
retail environment. The attitude of family and friends, and unanticipated circumstances
such as product availability (size, colour) and stock-outs may also force a re-evaluation
(Kotler and Armstrong, 2014).
Stage 4 – post-purchase behaviour
In the post-purchase stage, consumers evaluate the product’s performance based on
expectations, and reach a state of satisfaction or dissatisfaction. The expectation
confirmation theory (Oliver, 1977) explains post-purchase satisfaction as a function of
expectations, perceived performance, and confirmation (or disconfirmation) of beliefs.
Outcomes are compared against expectations in a subjective evaluation, which takes one
of three different forms: positive disconfirmation or satisfaction (performance is better
than expected); simple confirmation or neutral response (performance equals
expectations); and negative disconfirmation or dissatisfaction (performance is worse than
expected). Consumers who invest a lot of time, effort and money into a purchase may
experience cognitive dissonance on whether a right decision was made (Kotler and
Armstrong, 2014). This makes the consumer search for supportive information to reduce
the dissonance, by either positively confirming the choice made, or concluding that it was
an unwise decision.
Consumer satisfaction is a result of experiences during all stages of the purchase
process, as the outcome in one stage affects the experiences in the other stages (Karimi,
2013). Many studies on consumer satisfaction focus only on satisfaction with the final
choice and outcome, and ignore satisfaction with the decision-making process. Both
concepts have different underlying dimensions, but together make a significant impact on
consumers’ overall satisfaction (Karimi, 2013). Hence, it is important to analyse the
entire decision process.
2.6 Decision-making styles – satisficing and maximising
First introduced by Simon (1960), decision-making style is the tendency to maximise or
satisfice a decision. According to Schwartz et al. (2002), “maximisers desire the best
possible result; satisficers desire a result that is good enough to meet some criterion.”
Maximisers spend more time and effort to search and evaluate options to choose the best
possible one with the highest utility; on the other hand, satisficers search and evaluate
products only until they find one good enough to meet some criterion or pass their
acceptability threshold (Schwartz et al., 2002). Decision-making style has been proven to
affect the intensity of the decision process in terms of duration and the number of
alternatives and criteria considered, with maximisers undergoing more intensive
processes compared to satisficers (Karimi et al., 2015). This work attempts to see if social
media use affects consumers with different decision styles differently.

8 D. Voramontri and L. Klieb
2.7 Impact of the internet on consumer decisions
The enhanced variety and amount of information online has improved the ability of
consumers to make better consumption choices (Aksoy and Cooil, 2006), and has opened
up new opportunities for information search because of low search costs (Jepsen, 2007).
Results on search engines are now often dominated by user content and opinions (Smith,
2009).
The impact of the internet varies on the various stages of decision-making. Initially,
the internet supported only the information search stage (Karimi, 2013), but recent trends
in social media, online decision aids and recommender systems have extended the
internet’s influencing role to all the decision stages.
For online decision-making quality, besides time costs and the cognitive costs of
acquiring and processing information, other influencing factors include perceived risk,
product knowledge and trust. Internet or web skills have also assumed importance: the
higher the amount of internet use by consumers, the more likely they will use it for
decision-making (Jepsen, 2007). According to Punj (2012), the essential difference in
decision quality between offline and online settings can be attributed to the technology
available online, including access to the varied sources of information and decision aids,
which have the potential to help consumers make better quality decisions.
2.8 Impact of social media on consumer decisions
Several authors have recently studied the influence of social media on consumer
behaviour, although generally not from the point of view of the decision process (e.g.,
Xie and Lee, 2015; Chu and Kim, 2011). Consumers use social media for the benefit of
immediate access to information at their convenience (Mangold and Faulds, 2009),
helping them to decide what to buy or to know more about new products or brands, when
and where they want (Powers et al., 2012). Examples are given by Goh et al. (2013) and
Xiang and Gretzel (2010). Online consumer reviews have been shown to have a causal
impact on product choice and purchase behaviour by consumers (Yayli and Bayram,
2012).
Social media has brought on a ‘participatory culture’ where users network with other
like-minded individuals to engage in an unending loop of sharing information,
monitoring updates, and requesting opinions and ratings on all kinds of products, services
and activities (Ashman et al., 2015). The quality of online product reviews, characterised
by perceived informativeness and persuasiveness, together with the perceived quantity of
reviews, are found to have a significant positive influence on consumers’ purchase
intentions (Zhou et al., 2013; Zhang et al., 2014). Social media is perceived as a more
trustworthy source of information when compared to corporate communications and
advertisements. According to Constantinides (2014), there is a general feeling of mistrust
towards mainstream media. Therefore, consumers are turning away from traditional
media such as television, magazines, and newspapers as sources to guide their purchases
(Mangold and Faulds, 2009).
Information overload is a key issue in online decision-making. Social media with its
sheer amount of information have led consumers to a state of analysis paralysis, making
it difficult to navigate all the available information (Powers et al., 2012). Due to bounded
rationality (Simon, 1960; Thaler and Mullainathan, 2008), there is a limit to the amount

Impact of social media on consumer behaviour 9
of information that can be processed by individuals, and it is not feasible to evaluate all
choice alternatives in depth (Karimi, 2013).
2.9 Conclusions about the literature
There is no doubt that social media are now important sources of information for
consumers in their purchase decision-making, especially in instances of complex buying
behaviour. More and more people are turning to consumer opinions online due to the ease
of access, low cost, and the wide availability of information. Peer recommendations on
social media are viewed as an eWOM and as more trustable sources of information when
compared to advertisements and other marketer-generated information.
3 Research model
The classical model is chosen to study the influence of social media on complex buying
decisions due to its simplicity and versatility. Of the five stages, the first stage of need
recognition is not considered, as it is often not amenable to the kind of retrospective
survey used in the other stages. Therefore, this paper focuses on the decision process of
consumers who made an actual purchase after they judged a personal, situational,
psychological, or social need for a certain product or service as large enough.
The research model is depicted in Figure 2, showing the stages the consumers go
through, independent of the use of social media or not. Each stage has certain similar
attributes, indicated in the ellipse. The aim is to research the relationship of the stages,
that is, the influence of the information search stage on the evaluation of alternatives; the
influence of alternative evaluation on purchase decision; and the influence of the decision
stage on post-purchase outcome. The decision process is analysed with respect to the use
or non-use of social media.
3.1 Research hypotheses
Based on the literature and the presented model, the following hypotheses are proposed
for the research (Tables 2–6):
Table 2 Hypotheses regarding the decision-making model
Decision-making model hypotheses (DM)
DM1 There is a significant relationship between satisfaction in the first stage of information
search and satisfaction in the second stage of alternative evaluation.
DM2 There is a significant relationship between satisfaction in the first stage of information
search and satisfaction in the third stage of purchase decision.
DM3 There is a significant relationship between satisfaction in the second stage of alternative
evaluation and satisfaction in the third stage of purchase decision.
DM4 There is a significant relationship between satisfaction in the first stage of purchase
decision and the post-purchase satisfaction.
DM5 There is a significant relationship between satisfaction in the third stage of purchase
decision and the post-purchase satisfaction.

10 D. Voramontri and L. Klieb
Table 3 Hypotheses regarding social media usage
Social media usage hypotheses (SM)
SM1 There is a significant positive association between the use of social media and the
satisfaction in the first stage of information search.
SM2 There is a significant positive association between the use of social media and the
satisfaction in the second stage of alternative evaluation.
SM3 There is a significant positive association between the use of social media and the
satisfaction in the third stage of purchase decision.
SM4 There is a significant positive association between the use of social media and the
post-purchase satisfaction.
SM5 The social media group spends on average significantly less time on the three
decision-making stages when compared to the no social media group.
SM6 The social media group expends on average significantly less effort on the three
decision-making stages when compared to the no social media group.
SM7 The social media group finds it on average easier to search for information and evaluate
alternatives, when compared to the no social media group.
Table 4 Hypotheses regarding satisficing/maximising
Satisficing/maximising hypotheses (SatMax)
SatMax1 There is a significant positive association between maximising tendencies and the
amount of time and effort spent in the three stages of decision-making.
SatMax2 There is a significant positive association between satisficing tendencies and the
satisfaction in the first stage of information search.
SatMax3 There is a significant positive association between satisficing tendencies and the
satisfaction in the second stage of alternative evaluation.
SatMax4 There is a significant positive association between satisficing tendencies and the
satisfaction in the third stage of purchase decision.
SatMax5 There is a significant positive association between satisficing tendencies and the
post-purchase satisfaction.
Table 5 Hypotheses regarding internet and social media usage skills
Internet and social media skills hypotheses (I)
I1 Consumers who are proficient in internet usage are on average significantly more likely to
use social media for their purchase decision-making.
I2 Consumers who are proficient in internet usage are on average significantly more likely to
have higher satisfaction with the decision-making stages.
Table 6 Hypotheses regarding the quality and quantity of information on social media
Quality and quantity of information on social media (QQ)
QQ1 Higher perceived quality of information on social media is associated with higher
satisfaction with decision-making stages.
QQ2 Greater perceived quantity of information available on social media is associated with
higher satisfaction with decision-making stages.

Impact of social media on consumer behaviour 11
Figure 2 Research model (see online version for colours)
4 Methodology
Retrospective questioning through a questionnaire survey was chosen for the study. The
research focuses on complex purchases that require extended problem solving, where
social media is more likely to be utilised. To focus on complex buying, respondents were
asked in the survey to think of a recent purchase situation involving extended problem
solving, such as the purchase of a computer, a mobile phone, a camera, or a vacation
package, and to recall the search activities undertaken during decision-making.
Respondents were then asked whether or not they had used social media in their
decision-making. Those answering ‘no’ were marked as the ‘no social media group’.
Those answering ‘yes’ were further asked to specify how much social media helped
them. If social media contributed 30% or less towards their decision-making, and they
had to seek out other information sources, the respondents were marked as the ‘no social
media group’. The rest were all classified as the ‘social media group’. Both groups were
directed to basically the same questions customised according to their media sources
(social media or other). The questions measured the same concepts in the different
contexts, and differed only very little in their wording.
As indicated previously, the need recognition stage is not considered; therefore,
information search is named here the first stage, alternative evaluation the second stage,
and purchase decision as the third stage. The post-purchase stage is regarded as the
outcome of these three stages.
Consumer decision quality has no objective measurement and is difficult to
operationalise. The approach to measuring decision quality can be objective or subjective
(Aksoy and Cooil, 2006). Subjective measures are evaluations of the decision-maker,
capturing what is most important to the individual with respect to the decision. Survey
questions were designed to measure the subjective evaluations of the respondents
regarding the quality of the stages, in order to study the effectiveness of their
decision-making.
According to Grant et al. (2007), search behaviour is influenced by information
source utility, personal factors and product factors. Information source utility is measured

12 D. Voramontri and L. Klieb
here through the attributes of accuracy and reliability of information. For personal
factors, besides the basic questions like age and gender, respondents were asked about
their internet usage habits (time spent on internet per day, proficiency in using social
media, and participation in online discussions). Product factors are not considered as the
research focuses on complex purchases.
To operationalise the three stages of information search, alternative evaluation and
purchase decision, measurements included easiness, time, effort, enjoyment and
satisfaction. Questions on anxiety, trust, and confidence were included to indirectly
measure the perception of risk in the purchase, as it is linked to the degree of search
(Kotler and Armstrong, 2014). Consumers’ emotional experiences differ for the different
stages, with varying levels of emotions like anxiety, joy, trust and confidence felt during
each stage (Powers et al., 2012). Questions to measure the satisficing and maximising
tendencies of respondents were taken from Schwartz et al. (2002), with their wordings
slightly adjusted to make them more in tune with the times. The Likert-scale questions
were similarly framed for all the three stages. Additionally, questions were formulated to
measure the ‘herd behaviour’ tendencies of the respondents through the importance
placed on the opinions of family and friends, and of other people. Information quality and
quantity are among factors that affect decision quality and were measured for social
media users. At the end of each stage, respondents were asked about their satisfaction
with, and their quality ratings for, the stage. For the final post-purchase evaluation, the
survey asked about the overall satisfaction with the purchase, and the perceived quality of
the product or service purchased.
The survey was conducted through an online questionnaire created with the Qualtrics
survey tool in two languages: English and Thai. Convenience sampling with snowballing
(requested forwarding) was used to distribute the online questionnaire through e-mails,
messaging applications (WhatsApp and LINE), and social media channels (Facebook and
Twitter). Respondents who could not be reached through these channels were personally
contacted and asked to fill out the questionnaire on a tablet computer.
5 Results
5.1 Descriptives and univariate variables
A total of 158 respondents completed the survey, 90% from Thailand, N = 104 in English
and N = 54 in Thai. Of these 158 respondents, 129 reported using social media and 29 did
not use social media at all in their decision-making. The relatively high usage of social
media in purchase decisions in Thailand has been reported before (Goodrich and De
Mooij, 2013). As indicated in the methodology chapter, respondents for whom the use of
social media did not make any noteworthy contribution towards their decision-making
(less than 30% helpful) were regarded as the ‘no social media group’, since they
primarily used other media sources. Of the 129 social media users, 16 were below this
threshold and were automatically placed in the ‘no social media group’, bringing the total
of this group to N = 45, and the ‘social media group’ to N = 113. Further, N = 107 for
females and N = 51 for males. The age distribution of the respondents was concentrated
in the 33–37 years range and the over 48 years range.

Impact of social media on consumer behaviour 13
Table 7 Number of respondents in the ‘social media group’ and ‘no social media group’
Frequency Percent Valid percent
Social media group 113 71.5 71.5
No social media group 45 28.5 28.5
Valid
Total 158 100.0 100.0
Most respondents spent between 1–2 hours or 3–4 hours per day on the internet for
personal use. Most had basic to advanced proficiency in using social media for reading
messages (93%), but only 39% contributed to online discussions by providing product
reviews or feedback. Users in this survey have self-reported more participation than the
90-9-1 internet rule would suggest. According to the rule, which is popular among
internet marketing researchers, 90% of users only read (lurkers), 9% edit or contribute to
existing postings (contributors), and only 1% create new content (super-users) (Nielsen,
2006).
Figure 3 Word cloud of popular products considered by survey respondents (see online version
for colours)
The questionnaire asked respondents to consider a recent substantial purchase that
involved extended decision-making. Products commonly considered were mobile phones
(11.4%), hotel packages (7.6%), cars (4.4%), and cameras (3.8%).
Among users of social media, 61% found the quality of information matching their
expectations, and 26% found it better than expected. Only 13% reported that the
information was worse than their expectations. As for the quantity of information on
social media, 44% indicated that it matched their needs, 36% indicated it was more than
needed, while 20% felt that the information was less than their needs.

14 D. Voramontri and L. Klieb
5.2 Differences between the ‘social media group’ and ‘no social media group’
The significant differences between the social media group and the no social media group
are summarised in Table 8, as found by applying a t-test with a confidence level α of
0.05.
Table 8 Comparison between ‘social media group’ and ‘no social media group’
No. Variable factors Significant
difference Inferences
1 Age Yes Younger respondents more likely to make
purchase decisions with the use of social media
2 Average hours per day on
internet Yes Those who spent more time on the internet
more likely to use social media for purchase
decision-making.
3 Proficiency in reading
social media messages Yes Active users of social media are more likely to
use it in purchase decision-making.
4 Participating in online
forums and discussions Yes Active participants in social media are more
likely to use it in purchase decisions.
Yes (1, 2) 5 Easiness or convenience in
the use of media No (3)
Social media users found it easier to search
information (stage 1) and evaluate options
(stage 2) compared with no social media group;
however, easiness was same for both groups in
the purchase decision stage (stage 3).
6 Decision-making stages
being easier than expected Yes Social media users found the decision-making
process in all three stages to be easier than
expectations.
7 Time taken during the
decision-making stages No Social media did not reduce time taken for
decision-making, relative to non-social media
sources.
8 Effort spent during the
decision-making stages No Social media did not reduce effort during
decision-making, relative to non-social media
sources.
9 Fun and enjoyment during
decision-making Yes Social media users had more fun and
enjoyment during all three stages.
10 Anxiety during
decision-making No Social media users and non-users were equally
anxious in all three stages.
Yes (1, 2)
11 Importance of other
people’s opinion No (3)
Social media users placed more importance on
other people’s opinions while searching
information (stage 1) and evaluating options
(stage 2) compared to the no social media
group. But for final decision-making (stage 3),
both groups placed an equal emphasis on other
people’s opinions.
Yes (1) 12 Importance of friends’ and
family’s opinions No (2, 3)
Social media users placed more importance on
the opinions of family and friends while
searching for information (stage 1); but for
evaluating options (stage 2) and making the
final decision (stage 3), both groups placed an
equal emphasis on the opinions of family and
friends.

Impact of social media on consumer behaviour 15
Table 8 Comparison between social media group and no social media group (continued)
No. Variable factors Significant
difference Inferences
13 Information accuracy and
reliability Yes Social media users found information more
accurate and reliable, in all three stages.
No (1, 2) 14 Trust on information
Yes (3)
Trust in information was equal for both groups
during the first two stages, but in the third stage
of purchase decision, social media users had a
greater trust in information than non-users.
15 Confidence in using
information Yes Social media users felt more confident in using
the information that they found, across all three
stages.
16 Satisfaction with the media
in the three stages Yes Social media users indicated higher satisfaction
with their media, relative to non-users, in all
three stages.
17 Rating of the three stages Yes Social media users gave higher satisfaction
ratings relative to non-users, across all three
stages.
18 Post-purchase satisfaction No Social media users and non-users were equally
satisfied with their purchases.
19 Frequency of complex
decision-making No No difference between social media users and
non-users.
20 Frequency of going
through a decision process
that does not result in
purchase
No No difference between social media users and
non-users.
5.3 Correlations
In this section, some of the salient correlations between variables are reported. The
correlations between satisfaction with a stage and proficiency in reading messages on
social media were significant for stages 2 and 3, but not for stage 1 (Table 9). The
correlations of the ratings of the stages with the same variable were significant for all
three stages. Correlations with the variable about participation in social media were
similar, but also significant in stage 1. Therefore, rating of a stage and satisfaction
increases in general with increasing social media use.
The hedonistic aspect of search (fun or enjoyment) was positively correlated with
higher satisfaction in each of the three stages and the post-purchase stage (Table 10).
Note that the fun in the search stage, where social media makes the most difference,
does not translate into higher satisfaction with the purchase decision. This foreshadows
one of the conclusions of this work: while social media has a definite influence on the
subjective feelings about the decision process in the first two stages, its influence on
satisfaction in the post-purchase stage is minimal.
Social media users who found the quality of information as better than expected had
greater satisfaction in the three stages (Table 11). The final post-purchase satisfaction
was also correlated with a higher than expected quality of information on social media.
Those who found the quantity of information on social media to be greater than
expectations also reported higher satisfaction, which would seem to contradict the

16 D. Voramontri and L. Klieb
literature in that information overload did not have any negative effect on
decision-making.
Table 9 Correlations between satisfaction and ratings of the stages with proficiency in social
media
Correlations
How proficient do you
consider yourself in
reading messages on
social media
websites?
Do you participate
in online forums or
in giving product
reviews or feedback
on the internet?
Pearson correlation 0.123 0.210** Stage 1 – satisfaction
Sig. (2-tailed) 0.123 0.008
Pearson correlation 0.286** 0.232** Stage 1 – rating
Sig. (2-tailed) < 0.0005 0.003
Pearson correlation 0.206** 0.188* Stage 2 – satisfaction
Sig. (2-tailed) 0.009 0.018
Pearson correlation 0.274** 0.217** Stage 2 – rating
Sig. (2-tailed) < 0.0005 0.006
Pearson correlation 0.287** 0.281** Stage 3 – satisfaction
Sig. (2-tailed) < 0.0005 0.000
Pearson correlation 0.292** 0.189* Stage 3 – rating
Sig. (2-tailed) < 0.0005 0.017
Notes: *Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at
the 0.01 level (2-tailed). N = 158.
Table 10 Correlations between enjoyment and satisfaction in the three stages
Correlations
Searching for
information was
fun and exciting.
I enjoyed
comparing the
different
alternatives.
I enjoyed
deciding which
product (or
service) to buy.
Pearson
correlation 0.465** 0.409** 0.361** Stage 1
satisfaction
Sig. (2-tailed) < 0.0005 < 0.0005 < 0.0005
Pearson
correlation 0.340** 0.516** 0.384** Stage 2
satisfaction
Sig. (2-tailed) < 0.0005 < 0.0005 < 0.0005
Pearson
correlation 0.405** 0.492** 0.438** Stage 3
satisfaction
Sig. (2-tailed) < 0.0005 < 0.0005 < 0.0005
Pearson
correlation 0.160* 0.345** 0.408** Satisfaction
with purchase
Sig. (2-tailed) 0.044 < 0.0005 < 0.0005
Notes: **Correlation is significant at the 0.01 level (2-tailed). N = 158.

Impact of social media on consumer behaviour 17
Table 11 Correlations of quality and quantity of social media information with satisfaction
Correlations
The quality of the
information that I
collected by using
social media was:
The quantity of the
information that I
collected by using
social media was:
Pearson correlation 0.489** 0.519** Stage 1 satisfaction
Sig. (2-tailed) < 0.0005 < 0.0005
Pearson correlation 0.467** 0.420** Stage 2 satisfaction
Sig. (2-tailed) < 0.0005 < 0.0005
Pearson correlation 0.316** 0.421** Stage 3 satisfaction
Sig. (2-tailed) < 0.0005 < 0.0005
Pearson correlation 0.312** 0.184* Satisfied with
purchase Sig. (2-tailed) < 0.0005 0.037
Notes: **Correlation is significant at the 0.01 level (2-tailed). N = 129.
5.4 Regression analysis
The questionnaire included items for the characteristics of the stages, such as easiness,
time, effort, anxiety, herd behaviour (opinions of family, friends, and others), accuracy,
trust, and confidence. These were used as independent variables. Quality of the stages
was measured by satisfaction with the use of social media or other sources
(‘satisfaction’), and by the overall rating of the stages (‘rating’). Satisfaction was found to
be more representative of the stage quality and hence used as the dependent variable.
Regression stage 1 – information search
Taking the satisfaction in stage 1 as the dependent variable, and the other variables
(demographics, internet usage, social media yes/no, maximising/satisficing or MvS) as
independents, a backward regression analysis was performed. The ANOVA output for
the final model after removal of unnecessary predictors shows that not all linear
coefficients are zero with p < 0.0005. R2 = 0.499, fairly high, and the adjusted
R2 = 0.465, showing a sufficient number of cases per independent. Many independents
were predictive, as indicated in Table 12.
Table 12 Regression: first stage – information search
Stage 1 – coefficients
Standardised
coefficients
Beta t Sig.
(Constant) 2.882 0.005
MvS 1). When I watch television, I often check other
channels to see if something better is playing. 0.149 2.428 0.016
MvS 2). Going to watch a movie is really difficult, I’m
always struggling to pick the best one. –0.128 –2.067 0.040

18 D. Voramontri and L. Klieb
Table 12 Regression: first stage – information search (continued)
Stage 1 – coefficients
MvS 3). No matter what I do, I have the highest standards
for myself. –0.127 –2.067 0.040
Social media: yes/no –0.183 –2.825 0.005
Stage 1 – it was easy to find relevant information on the
product (or service). 0.219 3.144 0.002
Stage 1 – finding relevant information took a lot of time. 0.275 3.407 0.001
Stage 1 – finding relevant information took a lot of effort. –0.165 –2.076 0.040
Stage 1 – searching for information was fun and exciting. 0.226 3.301 0.001
Stage 1 – seeking and collecting information was easier than
I expected. 0.241 3.343 0.001
Stage 1 – I have confidence in using the information that I
found. 0.172 2.690 0.008
Satisfaction with information search is increased by satisficing (MvS 1–3) and by aspects
of the search process that are higher scoring or easier with social media. However, each
independent contributes relatively little. The negative coefficient of social media
indicates that those who did not use social media reported lesser satisfaction.
Table 13 Regression: second stage – alternative evaluation
Stage 2 – coefficients
Standardised
coefficients
Beta t Sig.
(Constant) 3.363 0.001
How many hours per day on average do you use the internet
for personal reasons? –0.112 –2.070 0.040
Social media: yes/no –0.165 –2.846 0.005
Stage 1 satisfaction 0.376 5.994 0.000
Stage 2 – evaluating and comparing the various options
took a lot of time. –0.215 –3.047 0.003
Stage 2 – evaluating and comparing the various options
took a lot of effort. 0.166 2.349 0.020
Stage 2 – I enjoyed comparing the different alternatives. 0.213 3.409 0.001
Stage 2 – I trust the information I obtained to evaluate and
compare the different options. 0.212 2.230 0.027
Stage 2 – I felt confident while evaluating the different
alternatives available. 0.168 1.997 0.048
Regression stage 2 – alternative evaluation
For the regression analysis of stage 2, the dependent variable was also satisfaction, while
the independents were the other stage variables like in stage 1. Besides these, the
satisfaction in stage 1 was also taken as an independent. A backward regression was
performed and variables that were not contributing were removed. The ANOVA-test

Impact of social media on consumer behaviour 19
gave p < 0.0005. R2 = 0.627, adjusted R2 = 0.599, which is higher than the R2 of the first
stage. Significant predictors of satisfaction in the second stage and their coefficients are
listed in Table 13.
The largest predictor of stage 2 satisfaction is the satisfaction reported in the previous
stage. Further, enjoyment, effort, trust and confidence are significant predictors.
Satisficing plays no role in this stage, as can be expected from its character.
Regression stage 3 – purchase decision
Regression analysis for the third stage was also run with its satisfaction as the dependent,
while the independents included the other stage variables, and the satisfaction in the
previous two stages. Variables that were not contributing were removed through
backward regression. ANOVA was p < 0.0005. R2 = 0.643, adjusted R2 = 0.629, which is
higher than those of both the previous stages.
Significant predictors of satisfaction and their coefficients are indicated in Table 14.
Like the second stage, satisficing/maximising of the respondents no longer had an effect.
However, unlike the first two stages, the use of social media no longer had a significant
effect. Significant predictors included the effort (negative), perceived accuracy and
reliability of information, and confidence in making the purchase decision.
Summary of the regression analysis
The use of social media in decision-making led to greater satisfaction in the information
search and evaluation stages but made no significant difference in the stage of purchase
decision. In other words, the level of satisfaction reported by respondents in their
purchase decision stage was the same irrespective of whether they used social media or
not. However, satisfaction reported in the first two stages were significant predictors of
satisfaction in the third stage, showing that satisfaction gets amplified as consumers move
along the decision-making process.
Table 14 Regression: third stage – purchase decision
Stage 3 – coefficients
Standardised
coefficients
Beta t Sig.
(Constant) 3.146 0.002
How proficient do you consider yourself in reading
messages on social media websites? 0.121 2.414 0.017
Stage 1 satisfaction 0.231 3.668 < 0.0005
Stage 2 satisfaction 0.402 6.077 < 0.0005
Stage 3 – it took me a lot of effort to reach a purchase
decision. –0.153 –3.055 0.003
Stage 3 – accurate and reliable information helped me
make my purchase decision. 0.204 3.681 < 0.0005
Stage 3 – I felt confident when making my purchase
decision. 0.147 2.549 0.012

20 D. Voramontri and L. Klieb
The influence of the satisficing/maximising variables in the first stage indicates that
maximisers were likely to have lesser satisfaction with their information search than
satisficers. This is a confirmation of Simon’s theory of satisficing in which optimising by
consumers is not possible under bounded rationality due to the sheer amount of
information in the market. Maximisers desire the best possible result and are more prone
than satisficers to be less satisfied with their decisions.
To conclude, the significant predictors of satisfaction in the three stages are listed in
Table 15.
Table 15 Summary of the regression analysis of the three stages
No. Dependent variable Significant predictors
1 Stage 1 satisfaction Social media, satisficing, time, effort, enjoyment,
easiness, confidence
2 Stage 2 satisfaction Social media, enjoyment, time, effort, trust,
confidence, stage 1 satisfaction
3 Stage 3 satisfaction Effort, confidence, accuracy and reliability, stage 1
satisfaction, stage 2 satisfaction
The Hayes PROCESS macro for SPSS
The best tool to analyse a general overall network model would be structural equation
modelling. Unfortunately, the large number of cases needed was impossible to achieve in
this research. However, Hayes model 6 template (Hayes, 2012), a macro for SPSS, fitted
the network structure and was therefore used to analyse the impact of the use or non-use
of social media (independent variable) on the purchase satisfaction (dependent), taking
the satisfaction in the three decision stages as the mediators. This led to the following
network model (Figure 4).
Figure 4 Hayes PROCESS network model of the research (see online version for colours)

Impact of social media on consumer behaviour 21
There were no covariates used. Significant coefficients (p < 0.05) are marked with an
asterisk (*), while the dotted arrows have p > 0.05. The total effect model has a low
R2 = 0.0219, p = 0.0635, which is consistent with no practical influence from the use of
social media. The total effect of the use of social media for decision-making on the final
outcome of purchase satisfaction, through the mediating decision stages, is –0.1827,
p = 0.0635, which indicates slightly lower satisfaction when social media is not used. The
estimate of the low influence of social media is robust, as indicated by the correlation
coefficient of –0.148 between the use of social media and post-purchase satisfaction, at a
two-tailed significance of 0.063.
One possible cause for the low total effect of the model could be post-purchase
cognitive dissonance, leading to effort justification or trivialisation. In other words, most
consumers expressed high satisfaction with their purchases, even though they reportedly
experienced less satisfaction during the initial stages of their decision-making. Also,
when mediation processes become complex, the direct effect size from the initial
independent variable to the outcome tends to get smaller because of additional links in
the chain, affected by competing causes and random factors (Shrout and Bolger, 2002).
To exclude the factor of dissonance resolution, the macro was run again with
satisfaction in stage 3 as the final dependent. The coefficients are (obviously) the same as
in the first model. However, R2 = 0.1535, p < 0.0005. The coefficient of the independent
variable (use of social media) is now higher, –0.4492, p < 0.0005, indicating that the use
of social media leads to a higher satisfaction through the first two stages on the third
stage of purchase decision.
5.5 Research hypotheses
Table 16 lists the hypotheses of the research with the applied statistical tests and the
results (whether supported or not).
Table 16 Results of the hypotheses testing
Hypothesis Test Result
Decision-making model
DM1 There is a significant relationship between satisfaction
in the first stage of information search and satisfaction
in the second stage of alternative evaluation.
Regression,
PROCESS Supported
DM2 There is a significant relationship between satisfaction
in the first stage of information search and satisfaction
in the third stage of purchase decision.
Regression,
PROCESS Supported
DM3 There is a significant relationship between satisfaction
in the second stage of alternative evaluation and
satisfaction in the third stage of purchase decision.
Regression,
PROCESS Supported
DM4 There is a significant relationship between satisfaction
in the first stage of purchase decision and the post-
purchase satisfaction.
PROCESS Not
supported
DM5 There is a significant relationship between satisfaction
in the third stage of purchase decision and the
post-purchase satisfaction.
PROCESS Supported

22 D. Voramontri and L. Klieb
Table 16 Results of the hypotheses testing (continued)
Hypothesis Test Result
Social media
SM1 There is a significant positive association between the
use of social media and the satisfaction in the first
stage of information search.
Regression,
PROCESS Supported
SM2 There is a significant positive association between the
use of social media and the satisfaction in the second
stage of alternative evaluation.
Regression,
PROCESS Supported
SM3 There is a significant positive association between the
use of social media and the satisfaction in the third
stage of purchase decision.
Regression,
PROCESS Not
supported
SM4 There is a significant positive association between the
use of social media and the post-purchase satisfaction. PROCESS Not
supported
SM5 The social media group spends on average
significantly less time on the three decision-making
stages when compared to the no social media group.
T-test,
regression Not
supported
SM6 The social media group expends on average
significantly less effort on the three decision-making
stages when compared to the no social media group.
T-test,
regression Not
supported
SM7 The social media group finds it on average easier to
search for information and evaluate alternatives, when
compared to the no social media group.
T-test,
regression supported
Satisficing/maximising
SatMax1 There is a significant positive association between
maximising tendencies and the amount of time and
effort spent in the three stages of decision-making.
Correlations Not
supported
SatMax2 There is a significant positive association between
satisficing tendencies and the satisfaction in the first
stage of information search.
Regression Supported
SatMax3 There is a significant positive association between
satisficing tendencies and the satisfaction in the
second stage of alternative evaluation.
Regression Not
supported
Satmax4 There is a significant positive association between
satisficing tendencies and the satisfaction in the third
stage of purchase decision.
Regression Not
supported
SatMax5 There is a significant positive association between
satisficing tendencies and the post-purchase
satisfaction.
Regression,
PROCESS Not
supported
Internet usage skills
I1 Consumers who are proficient in internet usage are on
average significantly more likely to use social media
for their purchase decision-making.
Correlations Supported
I2 Consumers who are proficient in internet usage are on
average significantly more likely to have higher
satisfaction with the decision-making stages.
Correlations Supported

Impact of social media on consumer behaviour 23
Table 16 Results of the hypotheses testing (continued)
Hypothesis Test Result
Quality and quantity of information on social media
QQ1 Higher perceived quality of information on social
media is associated with higher satisfaction with
decision-making stages.
Correlations Supported
QQ2 Greater perceived quantity of information available
on social media is associated with higher satisfaction
with decision-making stages.
Correlations Supported
6 Conclusions
A key issue for marketers currently is to understand how digital and social media are
used in the purchase decision process (Powers et al., 2012), their influence on buyer
behaviour, and their role as a marketing tool. The results overall show that the classical
model of decision-making is valid in describing the decision process of consumers in this
social media age. Stage characteristics positively associated with higher consumer
satisfaction are easiness, enjoyment, trust and confidence. Those who enjoyed the
decision-making process had greater satisfaction in the three stages and the final
purchase. High trust and confidence led to greater satisfaction with the stages and the
purchase. Satisficers were more satisfied with their information search, while maximisers
had lower satisfaction.
Social media users found decision-making to be easier and enjoyed the process more,
when compared to those who used other information sources. They also had greater
confidence and satisfaction during the process. Those who perceived the information on
social media to be of higher quality and greater quantity than expectations were more
satisfied overall. This suggests that information overload did not reduce consumer
satisfaction with social media.
Finally, the study shows that the use of social media improved satisfaction for
consumers during the initial stages of information search and alternative evaluation but
did not help much in improving satisfaction in the purchase decision stage, nor in the
post-purchase evaluation. Many consumers are just as satisfied to reach their purchase
decisions in the traditional physical stores after having conducted their search and
evaluation online; which means that brick-and-mortar shops have not yet lost their
significance.
Social media has enabled marketers to access and monitor consumer opinions on a
continual instant basis by listening-in and participating in online conversations, and
observing what people are discussing in blogs, forums and online communities
(Constantinides, 2014). With such vast information freely available on social media, it is
up to businesses to harness it positively to improve their product offerings, their customer
relationship management, and their profitability.

24 D. Voramontri and L. Klieb
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