Author: Arif Wibowo & Setyabudi Indartono The Role of Consumer Self-Efficacy on the Effect of ...

12 Pages·2017·0.65 MB·English

by  Professor Richard Chinomona

The Role of Consumer Self-Efficacy on the Effect of Demographics Background on
Impulse Behavior

Arif Wibowo & Setyabudi Indartono
Universitas Negeri Yogyakarta, Indonesia

ABSTRACT

This study adopted a motivation theory to explore the antecedents of impulse buying behaviour.
Different customers’ demographic backgrounds are believed to affect their impulse buying.
However, there has been no general consensus among researchers on this phenomenon. This study
investigates the effects of consumers’ demographic backgrounds and their self-efficacy on
impulsive buying behaviors. The results show demographic backgrounds affect self-efficacy
differently which subequently affects customer impulse behavior. Implications and suggestions for
future research are discussed.

KEYWORDS: Demographics Background, Impulse buying, Consumers’ Self-Efficacy.

Address Correspondence to: Setyabudi Indartono, Universitas Negeri Yogyakarta, Indonesia.
Email: [email protected]

Journal of Business Sciences (JBS)
Volume 1, Issue 1, pp. 73-84
(ISSN: 2521-5302)
June 2017

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Author: Arif Wibowo & Setyabudi Indartono
1.0. INTRODUCTION
In dynamic markets, the multiplicity of alternative brands causes confusion in the customers when
making purchasing decisions. From the dynamic behavior point of views (Schalk & Freese, 1997;
White, 2008, Chen, & Indartono, 2011), people may change their behavior as a result of contingent
factors – that is, the short-term opportunities experienced in the environment (Perish,
Cadwallader, and Busch, 2008). Being directed by their needs, customers can respond to external
offerings defensively, reactively, or protectively to avoid actions such as blaming (Ashforthand
Lee, 1990). Thus, their behavior might change accordingly when they feel unfairly treated
(Hochwarter, Witt and Kacmar, 2000; Valle and Perewe, 2000). In their quest to satisfy their needs,
consumers tend to be rational in order to use their limited resources and hence, achieve the
maximum possible levels of satisfaction. Thus, consumers precisely set their goals as a basis for
the alternative-selection process (Saleh, 2012). However, consumers are sometimes unaware of
the deals that are available. They do not have any intention of owning a particular deal prior
exposure to the promotions. Consumers may be pressured into making a purchase without careful
considerations. This may challenge customers to ensure survival in the long run rather than become
just another fad. The customers play a significant role in the delivery and consumption of many
types of services and products. Wu & Chen (2000) argue that people become disenchanted with
certain products due to changes in their habits, age, and income. Hence they are likely to make a
repurchase of a product or prefer to exhibit an impulse buying.

Researchers found that impulse buying is affected by various antecedents. For instance,
involvement and positive emotion were found to have positive effects on impulse buying behavior
(Joo Park, Young Kim, & Forney, 2006). Thus, salespersons try to segment their customer based
on their background characteristics. Market segmentation can be used by minor players in the
market to gain a foothold in a particular niche; i.e.by identifying an opportunity not directly
concentrated on by the brand or market leaders (e.g. Ecover washing-up liquid or Tie Rack).
However, even market leaders, whether Burtons or Sainsbury, use market segmentation profitably
and effectively (Dibb & Simkin, 1991). Different groups of people behave differently in various
social situations and take on different roles. Each group inhabits different social roles and perceives
unique societal expectations and attitudes. For example, some scholars are of the view that, only
people from specific age groups or one gender develop purchase intentions. These scholars assert
that, for instance, women seem more concerned about maintaining relationships, whereas men like
to maintain autonomous interactions. Role theory, therefore, would predict that female consumers
are keen to preserve relationships with their service provider and that the variations in customer
satisfaction are more likely to affect the loyalty levels of male consumers. (Walsh, Evanschitzky,
& Wunderlich, 2008). Furthermore, impulse buying has been approached from different
psychological perspectives with each perspective highlighting different constructs or mechanisms.

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This might, therefore, explain the disparities in consumer behaviour - such as personality,
emotions, identity concerns, cognitive processes, self-control, or psychopathology
(Verplanken&Sato, 2011). Perhaps too, these disparities can also explain the behavioural shift and
their self-efficacy intentions. Hsu & Chiu (2004) found that the self-efficacy of customers is
potentially an important factor that explains their decisions. Self-efficacy can, therefore, strengthen
the relationship between customers’ background and their impulse buying systematically. Greater
self-efficacy can be expected to promote more confidence in their ability to decide their buying
behaviors. Accordingly, the links between various customers’ backgrounds and their hedonic
buying are not equal. This study attempts to investigate the role of custumers self-efficacy and its
effect on customers’ demographic background and impulse Behavior. It is expected that the
findings of this study will potentially contribute towards new insights on how the dynamic
behaviors of customers lead to different buying behaviour.

2.0. LITERATURE REVIEWS AND HYPOTHESIS
2.1. Impulse buying
Impulse buying tendency refers to the degree to which an individual is likely to make unintended,
immediate, and unreflective purchases (e.g. impulse purchases)” (Weun, Jones, and Beatty, 1998).
Impulse buying occurs with an emotional conflict between actually concluded and previously
planned purchases (Weinberg and Gottwald, 1982). There are various psychological motivations
for impulse buying that people might experience in shopping (Rook, 1987). A visual encounter
with a product or a promotional incentive can motivate the sudden urge to buy. However, impulse
buying behavior does not always come from direct visual encouragement. Sometimes, without any
reason or stimulation, people are suddenly motivated to shop. Among various product categories,
apparel has been the main target for impulse buying. According to Bellenger and Korgaonkar
(1980), when consumers shop in a large department store, 50 percent of impulse purchases were
for apparel, where impulse purchases range from 27 percent to 62 percent of the total sales.

Impulse buying tendency has been conceptualized as a personal trait (e.g. Dholakia, 2000; Murray,
1938) that influences consistent responses to environmental stimuli (Kassarjian, 1971). Traits
represent pre-dispositional attributes of personality that refers to a person’s unique psychological
make-up. People tend to exhibit steady personal traits and behave consistently across different
situations. Impulsive individuals may have difficulties in restricting their own behaviors and make
frequent and consistent impulse purchases in several different shopping contexts (Murray, 1938).
A theoretical model of impulse buying developed by Beatty and Ferrell (1998) presented impulse
buying tendency as a trait. The consumption impulse formation and enactment (CIFE) model
developed by Dholakia (2000) also considered the impulse buying tendency as a personal trait that
contributes to the formation of the consumption impulse. The impulse buying tendency as a
consumer trait then may be positively related to the actual impulse buying. Rook and Fisher (1995)
also mentioned that consumers who rate high on the impulsivity trait buy things on impulse more
frequently than do others.

There are various findings on different customer backgrounds’ buying decision. Even previous
research has demonstrated that females are more likely to plan their purchases than males. Wells,
Farley, & Armstrong (2007) found that female consumers illustrated the highest incidence of
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Author: Arif Wibowo & Setyabudi Indartono
planned purchasing rather than male. Brito, Soares, Almeida, Monte, & Byvoet (2015) more
mature men were more likely to show different preferences than their female counterparts. The
people with low income were more likely to do impulsive buying for economic reasons rather than
for hedonic one (Tendai, & Crispen, 2009). Accordingly, the current study, therefore, proposes
that:
Hypothesis 1: Various customer backgrounds’ promote different effect on impulse buying.

2.2. Customer Self-Efficacy
Self-efficacy is a core concept in social cognition theory. It refers to people’s judgments of their
capabilities to organize and execute courses of action required to attain designated types of
performances. It is concerned not with the skills one has, but with judgments of what one can do
with whatever skills one possesses (Bandura, 1986). Self-efficacy regulates human behavior by
motivating effort and a persistent desire to complete tasks so that it enables one to surmount
difficulties in the face of challenges and failures. Customers who have more confidence in their
abilities tend to exert more effort to perform a particular behavior, persist longer in order to
overcome obstacles, and set more challenging goals than those who have less confidence in their
abilities (McKee, Simmers, & Licata, 2006). Moreso, customers with better self-efficacy are noted
to choose to perform more challenging tasks and they stick to them. Because self-efficacy is
originally developed through social learning processes, it leads to more productive goal setting.
Thus, self-efficacy perceptions affect the chosen goal level (Gist, 1987). More importantly,
because self-efficacy judgments are positively related to outcome expectations, the stronger
customer self-efficacy beliefs are, the more likely they are to achieve the desired outcome (Pereay
Monsuwé, Dellaert, & deRuyter, 2004). Outcome expectations pertain to the perception of possible
consequences of their actions (Bandura, 1986), which refers to the positive or negative
consequences of specific actions.Hence, They with greater self-efficacy have more confidence to
decide their buying behaviors. Self-efficacy is the belief that one has the capability to perform a
particular behavior. It is plausible that self-efficacy exerts a positive influence on decisions about
what behaviors to undertake and the effort exerted and persistence in attempting those behaviors
(McKee, et al, 2006). According to social cognition theory, people are self-organizing, self-
reflective, and self-regulative in that they make judgments about themselves on the basis of their
own behavior (Luszczynska, Scholz, &Schwarzer, 2005). Based on the discussion
aforementioned, the following hypotheses are proposed:
Hypothesis 2: Customer Self-Efficacy effect impulse buying.
Hypothesis 3: Customer Self-Efficacy mediates the effect of customer backgrounds’ on
impulse buying.

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Figure 1 Model of Research

3.0. METHOD
This study sample was generating by simple random sampling of Carrefour Hypermarkets’
customers. The result of data collection shows that 1101 respondents out of 1500 completed the
survey, therefore representing an overall 73.4% response rate. The average age for respondents
was approximately 24 years old and 9.1% of the respondents were married. 23.6% respondents
held a graduate degree and 34% of respondents were male, while 44.6% of them earn less than 4
million rupiahs a month.
3.1. Measurement development
Items were either developed by the authors or obtained from previous research. After a review of
wording, content, and so forth, 6 item sets were retained for inclusion in the instrument. Responses
were made on a 5-point Likert-type scale with scale anchors ranging from 1 (strongly disagree) to
5 (strongly agree).
3.2. Dependent variables
Impulse Behavior was measured using 4 items taken from Verplanken, & Herabadi, (2001). The
question asked to the participants were “I usually do not think carefully before I buy something
from this buying, Before I buy something, I make sure I consider very carefully whether I need it
(reverse question), Sometimes I cannot suppress the feeling of wanting to buy something, and I
can become very excited if I see something I would like to buy”.
Mediator variable
Customer Self- Efficacy was measured using 2 items taken from Pavlou & Fygenson, (2006). The
questions asked of the participants were “If I wanted to, I would be able to get this product within
the next 30 days” and “If I wanted to, I am confident I could get this product within the next 30
days”. A Five-point Likert-type scale was also used.
3.3. Demographics variable
This study also incorporates demographic variables suggested by Hochwater et al. (2000) (i.e.,
gender, marital status, and education level).
4.0. RESULTS
4.1. Instrument validation
Confirmatory factor analysis (CFA) was adopted to test for the quality and adequacy of the
measurement model. In accordance with the two-step procedure suggested by Anderson and
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Author: Arif Wibowo & Setyabudi Indartono
Gerbing (1988), prior to testing the hypotheses, confirmatory factor analysis (CFA) was performed
to examine reliability, convergent and discriminates validity of the multi-item construct measures.
Initial specification search led to the deletion of some of the items in the constructs scale in order
to provide the acceptable fit.

Table 1: Loading factor of construct
CSE IB
IB1 -
IB2 0.424
IB3 0.620
IB4 0.675
CSE1 0.847
CSE2 0.817

Confirmatory factor analysis (CFA) is adopted to test for the quality and adequacy by investigating
reliability, convergent and divergent validity (Anderson andGarbing, 1988). This study assessed
reliability jointly for all items of a construct by computing the composite reliability and average
variance extracted (Steenkamp and van Trijp 1991). Cronbach’s value is the most widely used
criteria to measure the reliability of the items for each construct (Cronbach’s, 1991).The
Cronbach’s value of construct is shown in Table 2. A result of correlation values greater than 0.85,
however, tells us that the two constructs overlap greatly and they are likely to be measuring the
same thing. Therefore, the results shown in Table 2 demonstrated adequate unidimensionality of
constructs

Table 2: Mean, Standard Deviation, Correlation values and Cronbach 
Maen SD 1 2 3 4 5 6
1 Gender 1.55 .505
2 Education 3.81 1.161 -.032
3 Marital 1.77 .522 .079* -.118**
4 Income 1.44 .854 -.190** .350** -.249**
5 Age 3.65 .723 .130** -.086* .095** -.045 0.580
6 Customer Self Efficacy 3.41 .973 -.048 .003 .002 .035 .298** 0.859
** Correlation is significant at the 0.01 level (2-tailed).
Bold values are Cronbach 

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Convergent validity is determined by the reliability of each construct and the averages variance
extracted (AVE) of each construct. Variance extracted is not only the average percentage of
variation explained among the items but also a summary measure of convergence among a set of
items representing a latent construct. Variance extracted is computed as the total of all squared
standardized factor loadings divided by the number of items. In other words, it is the average
squared factor loading. Fornell and Larcker (1981) suggested that average variance extracted of
0.5 or higher than squared multiple correlations are good. AVE values exceed the .50 shown in
Table 3. Table 4 shows AVE exceeding correlations in all squared multiple correlations. Therefore,
the indicator variables of this study have a good discriminant validity.
Table 3 Convergent Validity and Reliability
Mean SD Item-total α Value Loading CR AVE
IB2 .303 0.424
IB3 3.66 .7236 .421 0.58 0.620 0.599 0.340
IB4 .454 0.675
CSE1 754 0.847
3.42 .9732 0.859 0.818 0.692
CSE2 754 0.817

Discriminant validity describes the degree to which the operationalization is not similar to
(diverges from) other operationalizations that it theoretically should not be similar to. A successful
evaluation of discriminant validity shows that a test of a concept is not highly correlated with other
tests designed to measure theoretically different concepts. It is possible to calculate the extent to
which the two scales overlap by using the following formula where r is a correlation between x
xy
and y, r is the reliability of x, and r is the reliability of y:
xx yy
r
xy
r .r
xx yy
Table 4: Mediation Regression Analysis
Step 1 Step 2
Gender 0.118*** 0.132***
Education -0.086* -0.082*
Marital .017 .007
Income .049 .038
Age -0.108* -0.115**

Customer Self-Efficacy 0.292***
R2 .040 .125
R3 .040 0.09

Table 4 shows that gender, education background, and age have varying effects on impulse buying.
Female consumers promote higher hedonic behavior rather than male consumers. Higher
education background and elder customers are likely to reject the impulse buying. However, the
marital status and different income do not have a significant effect on impulse buying. Hence,
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Author: Arif Wibowo & Setyabudi Indartono
hypothesis 1 is partially accepted. Customer self-efficacy significantly affect impulse buying, and
thus the second hypothesis is accepted. Hypothesis 3 sought that self-efficacy plays a role on the
customer demographics background on hedonic behavior. However, the result shows that self-
efficacy is significantly influenced by educational background of costumers and consequently
affect impulse buying. Whereas customer self-efficacy does not play a significant role on the
different of customers’, gender, marital status, income, and age on their hedonic behavior. Hence,
Hypothesis 3 is partially supported.
5.0. DISCUSSION
Drawing from the research findings, it can be noted that self-efficacy is influenced in a significant
way by the education background of the costumers – and consequently influences impulse buying.
It is believed that custumers with better educational background are able to improve their financial
management behavior (Perry & Morris, 2005). This therefore, will enable them to achieve more
appropriate levels of spending and saving. In turn, this is expected to induce consumers’ hedonic
behaviour. It can therefore, be argued that self-efficacy is likely to lead to customers’ self control
(Sultan, Joireman, & Sprott, 2011). In the same vein, customers with self-efficacy are able to
control or override their thoughts, emotions, urges, and behavior on impulse buying.
6.0. LIMITATION AND SUGGESTION
Notwithstanding these contributions, this study has its limitations. This study allows us to rule out
the influence of the gender, educational background, and customer age on impulse buying and the
role of self-efficacy on the customer educational background and on impulse buying. However, it
is an open question as to whether these results can be applied to different and broader coverage of
research context. Although self-efficacy was found to influence the relationship between
educational background of costumers and impulse buying. Thus, it is also imperative that other
psychological attachment variables can be utilised to develop an expanded conceptual model for
subsequent empirical test.

Perhaps too, a longitudinal study on the impact of self-efficacy on impulsive buying and
repurchase intention might shed new insights. Measurement equivalence is now more than ever a
general concern in organizational studies. It is not only examined in cross-cultural, but also in
comparisons of participants with different levels of the market, in experimental versus control
groups, and in comparisons between sales and customer exchange. Hence, examining the
equivalence approach as the extended procedure (Cheung, 1999, 2008) solves the standardization
problem by performing a systematic comparison of all pairs of factor loadings across groups. The
sub-conditions of workplace spirituality on social and profit sales and different customers’ values
should become future attractive investigations. Perhaps too, it might be expected to yield
significant impact on future buying intention.

7.0. REFERENCES

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