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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Global Journal of Contemporary Research in Accounting, Auditing and Business Ethics (GJCRA) An Online International Research Journal (ISSN: 2311-3170)

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Dr. Elham Fariborzi, Computer /Information Technology/Educational Studies/Architectural Department,

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Dubai, United Arab Emirates.

Ms. Grace Kehinde Ojo, Faculty of Marketing,

Obafemi Awolowo University, Nigeria.

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Department of Marketing, Gdansk School of Banking,

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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. ___________________________________________________________________________




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,




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.




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.




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




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




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;




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.




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.

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