The impact of ‘black swan’ on consumer behavior

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Global Journal of Emerging Trends in e-business, Marketing and Consumer Psychology
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2016 Volume: 1 Issue. 1

Global Journal of Contemporary Research in Accounting, Auditing and Business Ethics (GJCRA)
An Online International Research Journal (ISSN: 2311-3170)
2016 Volume: 1 Issue.1
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The British University in Dubai,
Dubai, United Arab Emirates.
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Obafemi Awolowo University,
Nigeria.
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Department of Marketing,
Gdansk School of Banking,
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Global Journal of Emerging Trends in e-Business, Marketing and Consumer Psychology (GJETeMCP)
2016 Vol: 1 Issue: 1
351
The Impact of ‘Black Swan’ on Consumer Behavior:
A Logarithmic Approach
Abdulla S. Alhamad,
Graduate school of Management,
Multimedia University, Malaysia.
Abdelbaset Queiri,
Graduate school of Management,
Multimedia University, Malaysia.
_____________________________________________________________________
Abstract
This study is logarithmically approaching the impact of Black Swan event on the different types
of consumer behavior, namely, the expected purchasing decision, the influenced purchasing
decision and the unexpected purchasing decision. This logical model illustrates how people
react towards the event by examining the impact of Black Swan on the three aforementioned
types of consumer behavior and how likely such consumer behavior will be changing in the
event of organizational intervention at right or bad time. It was mathematically proven with
the aid of mathematical solution that the Black Swan event alters the consumer behavior only
if the organization can interfere at the right time. Then, a favorable outcome can benefit those
organization through influencing consumer behavior.
___________________________________________________________________________

352
1. Introduction
Our life is full of positive and negative events. However, these events are not regarded the
same. Taleb (2007) differentiates the event that requires our attention, in terms of its rarity to
the extent that it is an ‘outlier’ that falls outside the regular expectation; it has an extreme impact
and retrospective predictability. This type of event, indeed, is highly improbable and carries a
significant implication to different stakeholders.
The Black Swan incidents over the years, had a tremendous impact on restructuring and
reforming policies in different fields, in an attempt to avoid the potential future negative impact
of Black Swan and to reap the benefits of it through learning.
For instance, post the 9/11 incident, U.S government had imposed strict security measures
and enforced different acts, in response to future threat of terrorist attacks. Furthermore, the
incident of Black Monday (stock market crash) which occurred in 1987, has resulted in the
introduction of trading curbs and circuit breakers to prevent the market from panic selling, as a
result of investors’ sentiment and the available information. While some of Black Swans
resulted in negative impacts, such events increase our learning and knowledge and assists in
putting effective strategies to avoid future complication.
Since then, this concept became one of the most researched trends in so many practical and
academicals researches and studies , as in (Taylor, & Williams, 2008; Anthony, Catanach, &
Ragatz, 2010; Mowbray,2010; Green, 2011; Hausmann, & Rigobon, 2011; Illgner, Platt, &
Taylor, 2011; Shrader, 2011; Correa, 2012; Broaddus, 2013; Theron, Pretorius, & Chan2014).
One major implication of Black Swan is the impact that it has on consumer behavior.
Basically, consumer learning is formed through long processes; once learning is formed, it
appears to others in the form of behavior.
There are two perspectives about learning. From a psychological perspective, “learning refers
to a relatively permanent change in behavior which comes with experience” (Solomon,
Bamossy & Askegaard, 1999).
From the marketing point of view, “consumer learning is the process by which individuals
acquire the purchase and consumption knowledge and the experience they apply to future
related behavior” (Schiffman, Bednall, Cass, Paladino, Ward & Kanuk, 2008).
According to Hawkins, & Mothersbaugh, 2010) consumer behavior arises due to the interaction
of external and internal influences that shapes personal concepts. Collectively, these factors and
personal concepts guide the consumer behavior towards particular purchasing decision.
In the event of negative Black Swan, consumer reacts in destructive, random and
unanticipated manner. Black Swan events forced consumer into extraordinary learning
experience. The events occur unexpectedly, carrying out massive impact that disturbs the
course of organizational and economic success (Taleb, 2007; Asia-Pacific Housing Journal,

353
2010; Grant, 2013).
This unpredictable nature of the event forces people to gain an unexpected, sudden and
unforgettable experience that remind and get stored in people’s long-term memory,
transforming this living experience into permanent change in people’s learning and
consequently, their behavior (Solomon, Bamossy & Askegaard, 1999; Schiffman, Bednall,
Cass, Paladino, Ward & Kanuk, 2008).
The impact of Black Swan events on the course of economy is inevitable; companies and
organizations must understand the key elements to successfully managing the black sawn event
(Grant, 2013). Indeed, people’s reactions toward Black Swan events that are different in nature,
share the same key characteristics. After the famous attacks of the 9/11 on U.S, people reacted
immediately and aggressively (History, 2010). Furthermore, as in the case of Bahrain that
occurred on 14 February 2011, the community (unconsciously) and for a period of time (the
early stages of the event) fall under the influence of anonymous Twitter account users. It was
not because these accounts belong to political leaders or well-known figures within the
community. Simply, these Twitter users were the first to provide information and guidance to
the information seekers. The integrity of the provided information did not matter at that time.
In these types of situations people simply do not care whether the provided information is true
or not, what mattered was that someone (anonymous Twitter users) were reacting and
answering all questions regarding the situation, providing guidance padded with instructions to
their followers, telling them how to deal with the situation. This need of guidance and
information that has always associated with Black Swan events is key elements that
organizations can benefit from it.
Taken collectively, this study aims to assess the impact of Black Swan event on three
different types of consumer behavior, namely: the previous purchasing decision, the influenced
purchasing decision and the unexpected purchasing decision. Such impact is assessed using
algorithmic logic gates proposed under different scenarios (inputs). These inputs are the
occurrence of Black Swan event and the intervention of marketers (organizations) at right or
bad time.
In short, the proposed logic gate will provide sound mathematical justification on how Black
Swan event likely to affect the three aforementioned types of consumer behavior, during no
marketers’ intervention (organization) or with their intervention at bad or right time.
2. Logical Framework
In the case of “Black Swan” event occurrence, influencing consumer reaction is interfering
with the process of “consumer learning”; this interference will direct the final purchase decision
toward the influencer best interest.

354
This framework idea is based on the study interpretation on how people obtain their
information about the situation during the occurrence of a “Black Swan” event. In the very
early stage of a “Black Swan” event, people search for information, guidance and instructions,
to tell them how to react toward the event. By studying and examining different “Black Swan”
events this study found that the first information, guidance, and instruction provider is the one
who obtains more followers (especially in social media) and credibility, in other words the first
initiator obtains the largest bulk of followers (potential customers), however, what matters here
is choosing the right moment to intervene using proper types of inputs. The following
framework shows the logic of this assumption using logical gates compilation to form the
algorithms.
Formulating the framework using logical gates is to achieve two objectives, first is to make
it possible for this framework to be used as a hardware device or to translate it easily to a
software that can be integrated within any decision support system using any computer
language, second is to open a window on the possibilities and the benefits that business studies
can gain when scholars are thinking outside the box, using uncommon solutions to explain or
maybe solve a business dilemma. Science is full of opportunities and unlimited ways to create
solutions, the only thing stopping us from making the best out of it, is us, humans are only
focusing on what they already know, this makes what we don’t know a lost opportunity (Taleb,
2007).
The framework is designed as an electronic circuit using logical gates; these gates will help
calculate all the logical possible odds that if occurred at the right time will help decision maker’s
to make the right decision and to take the necessary actions to direct consumers reaction and
eventually changing “consumer learning” toward their best interest.
Influencing consumer learning become possible because of the established IT public
infrastructure (Internet), therefore, social media is the best tool (at this time) for marketers to
use as the primary tool to change the existing “consumer learning”, this study observes that
firms who used Facebook and Twitter during the February 14, 2011 events in the Kingdom of
Bahrain was very successful (unintentionally) to obtain the largest bulk of new consumers who
managed (unconsciously) to changed their learning, whoever, some firms have failed to do so
by using the same tools, what determine the difference between failures and success is the
timing.
The following framework will prove that timing is the critical factor when marketers are
dealing with “consumer learning”, moreover, if this framework (logical gates circuit) integrated
within any marketing DSS (Decision Support System) it will determine the most appropriate
time to which marketers can engage to influence “consumer learning” direction. Figure 1 below
shows the purchase decision probabilities during the occurrence of a “Black Swan” event.

355
The framework shown in figure (1) above, explains the probabilities of the different
purchase decisions that consumers may take in case of the occurrence of a “Black Swan” event.
The logical framework shown in figure (2) above, was designed as electronic circuit using
logical gates, this type of circuits are usually used to create solutions for physical dilemmas to
provide reliable and logical solutions that can be implemented in real live situations.
3. Logical Framework Description
The framework have three inputs and three possible outputs, the first input (UNOP) is the
“Black Swan” event, this framework is recognized it as (unexpected opportunity) instead of a
disaster, (UNOP) is not controllable by the marketers or the organizations. The other two inputs
represent the marketers (organizations) intervention to influence the “consumer reaction”,
(IRR) represent the marketers (organizations) engagement to influence “consumer reaction” at
the right time, (IRB) represent the marketers (organizations) engagement to influence
“consumer reaction” at bad time. The three outputs represent the final purchase decision that
consumers may have as a reaction to the inputs, depending on the inputs combination. Before
the February 14, 2011 events in the Kingdom of Bahrain, “consumer behavior” was stable and
predictable; this is represented in the first output (EPD) the existing purchase decision that is
based on the existing “consumer learning” and the existing overall “consumer behavior”. The
second output (IPD) is the target to be achieved with this framework, this output represent the
influenced purchased decision. To achieve this target, the odds must be in favor of the marketers
and organizations. The third and the last output is the unexpected purchase decision (UNPD),
this is the most unwanted “purchase decision” in any market, this will create a new “consumer
learning” that maybe permanent in some cases which will eventually resulting in creating a new
unprepared for “consumer behavior”. This concept was adapted from consumer animosity
Figure (2)
Logical Framework
Influencing Purchase
Decision
Figure (1)
Purchase Decision
Probabilities

356
studies (Riefler, & Diamantopoulos, 2007; Harmeling, Magnusson, and Singh, 2015).
Influencing purchase decision toward an unexpected purchase decision in an imitating to the
famous story of Samson the mighty when he pulled the temple supporting pillars to kill his
enemies, which he was successful, however, Samson died as well.
The empirical conceptual framework is using three logical gats as follow:
i. Not gate.
This gate work as a reverser or a converter, when the input is 0, the output is 1, when the input
is 1, the output is 0.
Input Output
0 1
1 0
Table 1: shows the NOT gate inputs & outputs
ii. AND gate.
This gate need at least two inputs, the AND gate output will not be active if one of the inputs
is passive, in other words, the output is 0 as long one of the inputs is 0.
Input I Input II Output
0 0 0
0 1 0
1 0 0
1 1 1
Table 2: AND gate inputs & outputs
iii. EX-OR gate.
The EX- OR gate output is active when only one of the inputs is
active. Incase of two active inputs the output is 0.
Input I Input II Output
0 0 0
0 1 1
1 0 1
1 1 0

357
4. Solving the Framework Algorithms
This algorithms are simulating the possible logical situations the case of “Black Swan” event
occurrence, therefore, some of the inputs will be excluded for two reasons, first we need to
calculate for the possible reactions during a “Black Swan” event, second some of the proposed
situations cannot happen in reality. Table (4) below shows the possible situations
(probabilities).
Table 3: shows the EX-OR gate inputs & outputs
Inputs Table
UNOP ILR IRB
0 0 0
1 0 0
0 1 0
1 1 0
0 0 1
1 0 1
0 1 1
1 1 1
Table 4: shows the real Situations possible inputs
The situations in RED were excluded. However the first situation is solved to prove the integrity
of the framework.
i. The first situation represents the market in its normal status, without a “Black Swan” event
and without any attempt to influence “consumer learning”.
Inputs:
UNOP = 0, ILR = 0, ILB = 0
Outputs:
EPD = not (UNOP and ILR) = 1
IPD = ILB xor (not EPD) = 0 xor 0 = 0
UEPD = (not IPD) and UNOP = 1 and 0 = 0
Explanation:
In the normal market situation, without any attempt to influence “consumer learning”, the
purchase decision reflect the expected “consumer behavior” from this market consumers in that
situation. This result is the logical output that we are expecting, thus, the integrity of the
framework has been proved.
In the following part only the possible logical situations during the occurrence of a “Black
Swan” event will be solved, in order to find the best combination of inputs, that we can achieve
our objective with.
ii. In this logical situation, marketers and organizations was taken by surprise by the occurrence
of the “Black Swan” event. Marketers and organizations were not ready to deal with the event;

358
the decision was to sit back and wait to see the results and the implication from the event on
the market situation.
Inputs:
UNOP = 1, ILR = 0, ILB = 0
Outputs:
Explanation:
From the results it can be seen that in case of the occurrence of a “Black Swan” event, and
organizations were not ready to take action, the impact of the event will change the consumers
“purchase decision”, generating new “consumer behavior” as a reaction to the event
occurrence, some of the consumers will continue with their existing “purchase decision”, others
will show a new and unexpected “consumer behavior” resulting for unexpected purchase
decision.
iii. The second logical situation is when marketers and organizations are ready for interfere in
case of the occurrence of the event, to influence “consumer learning” toward their best interest.
Inputs:
UNOP = 1, ILR = 1, ILB = 0
Outputs:
Explanation:
The results shows that incase of the occurrence of a “Black Swan” event, and the marketers and
organizations were ready to interfere to influence “consumer learning” at the right time (using
the proper tools1
), the output will be directing consumers purchase decision and creating a new
“consumer behavior” that serve their best interest. This situation cannot be generalized on the
whole market; the only beneficiary from this interference is the organization that imposed
influence.
iv. The third logically possible situation for this dilemma is when the decision of interference
was taking in a bad timing or too late to impose influence on “consumer learning”.
Inputs:
UNOP = 1, ILR = 0, ILB = 1
1 Marketers and organizations must identify the proper tools of interference according to the general
environment, for example, 20 years ago social network did not exists, however, for the time being these networks
could be consider as the best appropriate tool for implementing this conceptual framework.

359
Outputs:
Explanation:
The interference in bad time have the same results on the organization as doing nothing, except
of one thing, the exception is that the organization may lose more of its market share than the
first logical situation, in case someone else was ready to interfere at the right time.
5. Conclusion
We cannot move around Black Swan event like it did not happen, its occurrence will disturb
the course of life. Organizations should be prepared for these events, and we should not
consider it as destructive event. Black Swan event may become our unexpected opportunity if
we were prepared for it, its occurrence could be profitable or at least it will pass without hurting
the stakeholders. These events could be the best opportunity to gain new costumers and
transferring them into permanent consumers, or at least temporally benefiting from the event
rather than losing because of it. Solutions may not exist within our knowledge; one must
consider other options to find solutions.
6. Recommendations
There are extreme rareness in researches and studies on the link between Black Swan events
and human behavior. It is recommended that social scientists and scholars should consider the
power imposed by Black Swan events on human behavior and especially on consumer
behavior.
Empirical approaching methods could be the best solution for these studies. For consumer
animosity studies researchers may consider new theories while formulating their hypotheses,
such as “Hysteresis effects” on consumer behavior.
References
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Kansas.
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