2. Oman (Seban, 2019). In Malaysia, FinTech is supported by the government. Malaysian
banks are assisted by Bank Negara Malaysia and as a result, most of the banks have
embraced FinTech and other digital tools required by such financial institutions to devise a
digital platform for their consumers (Hui Ho et al., 2019). Malaysia is a hub of Islamic finance
but still ahead towards FinTech. Islamic banks in Malaysia have adopted advanced
technology support in the South East Asian region (Shaikh et al., 2018). On the same note,
there are limited studies that have mapped out acceptance of Islamic FinTech either on
empirical or non-empirical grounds as suggested by lack of literature (Milian et al., 2019;
Acar and Çıtak, 2019; Breidbach et al., 2019). Figure 1 best defines FinTech’s concept
transformation into the global Islamic economy context of Islamic FinTech. According to
Miskam et al. (2019) “FinTech promises to reshape the Islamic financial landscape by
improving processes’ efficiencies, cost-effectiveness, increased distribution, Sharīʿah
compliance and financial inclusion” (p. 223).
In relation to press, FinTech appears to be hype or a “buzz word” as Milian et al. (2019)
asserts that FinTech is an integral part of the “information technology (IT)”, “innovation”
(technology centres, capital outlay, etc) and “financial industry”. Furthermore, “derived from
contracting the words finances and technology, the term FinTech first arose in the scientific
literature in 1972” (Milian et al., 2019). Furthermore, the vice-chair of “Manufacturers
Hanover Trust”, Abraham Leon Bettinger, phrased FinTech as; “an acronym, which stands
for financial technology, combining bank expertise with modern management science
techniques and the computer” (Bettinger, 1972, p. 62).
Figure 1 Mapping the Islamic FinTech ecosystem
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3. Moreover, there are various versions of its spelling, which are fin-tech, Fin-Tech or FinTech
(Milian et al., 2019). In the case of the current research, the term is spelled as FinTech
throughout the paper. FinTech adoption is currently considered by various Islamic Finance
services providers to mention few, namely, Saudi Arabia, the UAE, Malaysia, Bahrain,
Brunei, Indonesia, Oman and others.
As stated earlier FinTech adoption in the Islamic banking context is still at the infancy stage
and in terms of acceptability on tenets of Shariah this topic is gaining popularity among the
Shariah scholars and practitioners. Going by this, it can be further asserted that FinTech
adoption and acceptability becomes the focus for its main role in terms of acceptance.
This study intends to provide empirical evidence and test technology acceptance model
(TAM) as a baseline theory by review of previous literature and studies if any that contribute
to the factors, which are influential towards FinTech adoption.
This study aims to add to the body of the knowledge on the FinTech services, which may be
offered and or is currently offered and practiced by Islamic banks. Going by this, the
current research emphasis more on the FinTech’s acceptance in Malaysia.
Malaysia is considered a big market for Sharīʿah-compliant products. To the best of
authors’ knowledge, there are a few empirical studies conducted on factors responsible for
the acceptance of Islamic FinTech. Furthermore, the current study will incorporate the
variables, which are consumer innovativeness (CI) and self-efficacy in the framework of
TAM along with other variables, which are perceived ease of use (PEOU), perceived
usefulness (PU) and subjective norms (SN).
Furthermore, the aforementioned factors will be investigated in search of determinants that
are responsible for Islamic FinTech services usage in Malaysia in the quest to cover the
research gap. Previous studies on usage behaviour conducted an investigation using a
theory of Planned Behaviour (TPB), diffusion of Innovation (DOI) theory, the decomposed
theory of planned behaviour (DTPB) and theory of interpersonal behaviour but there is no
study that validated and tested such theories in the context of Islamic FinTech services.
Therefore, this research will fill in the gap by using TAM as a baseline model to investigate
the adoption of FinTech services offered by Islamic banks.
Hence, the research paper will be beneficial for the Islamic bank policymakers,
practitioners, managers and academicians. Further, it will enhance the scope of significant
factors responsible for the adoption of FinTech.
Literature review
Product receptivity of Islamic banking services
Islamic banking is in existence for more than three-decades-long periods, but its
acceptance in terms of market acceptance is relatively lower when compared to
conventional banks (Ahmad and Haron, 2002).
Further, Ahmad and Haron (2002) contend that the majority of respondents consider that
Islamic banks are unable to promote and market their products, which are available to them
in the market. On the same note, it is argued by Haque et al. (2009) that the majority of their
respondents who were Malaysian were unaware of the Islamic banking services and
products.
Looking at the broad picture, if there is no intended level of technology usage or service
acceptance then the product or system cannot be implemented successfully (Amoako-
Gyampah, 2007). In other words, it can be said that the acceptance of a particular product
or intention towards a system is reflected by a system usage.
Furthermore, if targeted customers are not enthusiast to accept the new system or the new
arrangement in a product per se, then the organisation will have a blur vision on the benefits
VOL. 22 NO. 3 2020 jFORESIGHT j PAGE 369
4. that the new offered system may bring (Davis and Venkatesh, 1996). In the author’s opinion,
considering the paradigm of products being introduced and made available for current
consumers of Islamic banks, it is still implicit whether customers will embrace these services
and products or not. Having said that, acceptance of Islamic banks’ products and services
are contingent upon the consumers’ eagerness and willingness to espouse it.
Technology acceptance model
In a bid to ascertain the acceptance of an individual to accept Islamic FinTech services,
there is a need for theoretical support. For the purpose of determining the factors that have
an impact on Islamic FinTech services, this study extends the TAM. Davis (1989) modified
the theory of reasoned action and put forward TAM, which is from a domain of Information
systems and is a cognitive model and shares similarity with the theory of reasoned action
(Fishbein and Ajzen, 1975).
In light of the fact, TAM goes beyond the previously stated models and extends the
aforesaid models, slotting in the variables, namely, PEOU and perceived usefulness that
impact behaviour resulting in the negative or positive outcome towards behaviour intention
leading to usage determination (Davis, 1989). Afterwards, Davis (1989) suggested after
experimenting the previous model of TAM to omit attitude construct from the original TAM
model. Hence, supporting the prediction of behaviour intention only by two original
constructs, which are PEOU and PU as robust determinants towards intention prediction.
To be specific intentions are reflected by PEOU and PU in TAM (Davis, 1989). Moreover,
TAM is considered by many researchers as a model that can provide an understanding of
complex human behaviour and extend the further analysis of the factors that shape this
behaviour towards the acceptance of specific systems. Similarly, TAM remained successful
in developing a variety of user acceptance in the Information systems domain. Going by this
there were many modifications applied to the original TAM model to mention few; including
the work by Venkatesh and Davis (2000), Chau and Hu (2001). In the context of this study,
TAM is tested to predict Islamic FinTech’s acceptance and authors have extended the
original TAM model. The extended TAM model can be seen in Figure 2.
Figure 2 Research framework
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5. Hypotheses development
Consumer innovativeness
Rogers and Shoemaker (1983, p. 27) define CI as “the degree to which an individual is
relatively earlier in adopting an innovation than other members of his system”. According to
Rogers innovations are diffused and that innovations have been communicated via a
communicative channel over a certain time frame among particular individuals within the
social system. Other scholars explain CI as “the predisposition to buy new and different
products and brands rather than remain with previous choices and consumption patterns”.
Moreover, those users or patrons who are Innovative will incline to gather thoughts or
concepts and further evidence with regards to product innovation (innovative).
Consequently, who could be early adopters of such product with innovation (Rogers, 2003).
On the same note, it is worth mentioning that there exists scarce literature on CI and Islamic
FinTech service adoption. There are studies with significant findings in relation to CI to be a
key predictor (Lassar et al., 2005; Yi et al., 2006; Lee et al., 2007). All these studies find CI
as a predictor for customers’ adoption and acceptance of certain systems. For instance,
starting with Lee et al. (2007) where authors find that customers’ intention to travel may
change with regards to innovativeness level and in a similar vein, the study also tested CI
moderated the attitude towards search and purchase intention. Going by this, another study
by Yi et al. (2006) discovers that CI is a factor of characteristics of innovation, which are
“PU, perceived compatibility and PEOU”. Agarwal and Prasad (1998) in a similar territory of
IT drawn upon an extension to the model based on DOI theory and introduced a new
moderator, that is, “personal innovations of information technology”, that marks the
difference between the domain-specific innovation and global innovation. Yet the moderator
has been partially exhibited and it has drawn a substantial impact on the association
between compatibility and the intention towards innovation and compatibility. This study
finds CI to influence the intention of a user towards the “World Wide Web”.
Based on the aforementioned studies it can be hypothesised that as follows:
H1. There is a direct relationship between CI and acceptance of Islamic FinTech
services.
Subjective norms
Subjective norm pertains to one’s insights related to social build pressures’ expecting an
individual to perform certain behaviour (Fishbein and Ajzen, 1975). As stated earlier, the
construct of the subjective norm was theorised as far back as TRA by Fishbein and Ajzen
(1975). Subjective norm is figured in a variety of contexts such as the adoption of technology
and others. Furthermore, this construct is asserted as noteworthy by a number of researchers
(Taib et al., 2008; Lada et al., 2009; Amin et al., 2013). Taib et al. (2008) examines the
influence of subjective norm and intention and reports SN to affect the behavioural intention of
postgraduate student’s acceptance for Islamic housing. To emphasise the importance of halal
products as a rapidly growing market force, a work by Lada et al. (2009) that applies TRA
reports SN to have a direct influence on attitude for the consumption of the halal product.
Correspondingly, Amin et al. (2013) findings lead to the conclusion that subjective norm is
directly related to the Islamic housing products’ adoption.
Thus,
H2. There is a direct relationship between SN and acceptance of Islamic FinTech services.
Perceived ease of use
As stated in the earlier section that concerning with TAM, the attitude becomes the outcome
variable measured by PEOU, which is a transformed form of perceived complexity.
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6. Chen et al. (2002) argue that complexity to be taken as opposite to PEOU in the constructs
associated with TAM. Consequently, it is, therefore evident that more or less TAM to some
degree underscores the conceptual groundings of DOI theory. As far as innovation is
concerned, complexity is viewed as a usability-related factor, Sonnenwald et al. (2001),
which negatively affects the PEOU. Davis (1989) suggests that PEOU as “the degree to
which a person believes that using a particular system would be free from efforts” (p. 320).
There exists empirical work to confirm the relationship between behavioural intention and
PEOU. To mention few (Amin et al., 2014; Ramayah et al., 2005; Kleijnen et al., 2004;
Ramayah et al., 2003). Starting with the prime study by Amin et al. (2014) on the online waqf
(holding property) determinants of acceptance among individuals. The study reports that
PEOU is one of the motivators that influence individuals when making a decision to
participate in online waqf. On the same token, Chin and Ibrahim (2005) conduct a study in
the context of Malaysia to investigate factors that drive intention for e-bill payment among
the students and discover that there exists a relationship between intention for e-bill
payment and PEOU. Kleijnen et al. (2004) investigates the finance via wireless among
Netherlanders and explores the influence of PEOU on intention. Hence, the findings
suggest that PEOU variable influences the intention of those who are willing to participate in
wireless financing. On the same note, while investigating drivers of the internet use
Ramayah et al. (2003) find that PEOU is significantly related to internet use initially. Hence, it
can, therefore, be hypothesised that as follows:
H3. There is a direct relationship between PEOU and acceptance of Islamic FinTech
services.
Self-efficacy
Self-efficacy speaks to a person’s self-belief in the capacity to direct behaviour and it is
defined as “a person’s judgement of their capabilities to organise and execute courses of
action required to attain designated types of performances”. “It is concerned not with the
skills one has but with the judgement of what one can do with whatever skills an individual
possesses” (Bandura, 1986, p. 391). In regard to the present study, it is more likely
expected that users with higher self-efficacy (i.e. self-belief) most likely tend to accept
Islamic FinTech. The effect of self-efficacy is reported in numerous empirical studies.
Investigating consumers’ intention to accept diminishing partnership home finance Shaikh
et al. (2018) discovered self-efficacy to be one of the significant factors to influence
intention. Examining students’ intention to use a computing resource centre, Taylor and
Todd (1995a) find that both self-efficacy and resource-based facilitating conditions are
significant determinants of predictors of behavioural control. The same result is also
reported in Taylor and Todd (1995b). Bhattacherjee’s (2000) empirical examination of
individuals’ underlying motivation to accept electronic brokerage technology among e-
brokerage users resulted in a significant effect of one’s self-confidence in skills to perform
the intended behaviour (i.e. self-efficacy).
Thus,
H4. There is a direct relationship between self-efficacy and acceptance of Islamic
FinTech services.
Perceived usefulness
Results of Karahanna and Straub (1999) suggests that in the process before adoption, both
mechanisms of instrumentality, which is PU or relative advantage and non-instrumentality
values affecting attitude; nonetheless, once the experience is gained in post-adoption, only
image and mechanism values affect attitude. Although the renowned TAM is grounded on
different theoretical underpinnings from TRA and DOI theory, similarities in the main
constructs are recognised. For the case in a point, as stated previously, the relative
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7. advantage construct of DOI is used interchangeably often with PU. Chen et al. (2002)
findings of an online survey conducted to examine internet users’ intention to online
shopping demonstrate that a high degree of PU leads to an additional favourable attitude
towards shopping online. In the same vein, investigating the effect of trust on technology
usage, Suh and Han (2002) findings based on investigation of the effect, which trust may
have on customers’ willingness to accept internet banking suggest that PU construct
measures up to statistical significance with a positive impact on attitude towards using the
technology. According to Amin et al. (2014), PU affects the intentions of online waqf
participants. Based on the aforementioned studies it can be hypothesised that as follows:
H5. There is a direct relationship between PU and acceptance of Islamic FinTech
services.
Research framework
Proposed research model
The framework for this study, which is acceptance for Islamic FinTech services is developed
based on the adapted constructs from TAM by Davis (1989) and additional constructs of CI
along with the self-efficacy variable as shown in Figure 2. In a similar vein, TAM is widely used
in the area of Information communication technology (Shih and Fang, 2004).
In the author’s decision to choose between the theories of behaviour, TAM is considered
after drawing upon a comparison between the models of TRA, TPB, DTPB and TAM. What
TAM, TPB and DTPB have in common is that all of these theories have been derived from
TRA. DTPB and TPB were not the choices because of their failure to give an explanation of
how an individual believe in performing a particular behaviour and the means by which he
gets involved in such behaviour (Taylor and Todd, 1995c).
As stated earlier this study is grounded on the technology acceptance model. The model is
modified with TAM original constructs, which are PEOU and PU. Two additional variables
are incorporated and integrated into model including CI construct and self-efficacy. The
model of TAM is not tested previously in the context of Islamic FinTech. This study is pioneer
work that breaks the ground and becomes first to extend the technology acceptance model
in this context on empirical grounds. Furthermore, a construct of CI and self-efficacy are yet
to be tested in the Islamic FinTech context.
The research framework for this study is shown in Figure 2.
Research method
Subjects
The data for this study was gathered from users of Islamic banks located in Klang Valley. A
total of 250 questionnaires were distributed and 213 were returned and 8 questionnaires
were incomplete. Therefore, only 205 were usable for the analysis, making 82.0 per cent
response rate. Hence, based on the previous studies said the response rate is ample for the
analysis. Convenience sampling was applied to represent the population. In Table I
respondents’ demographic details are shown.
Measures
This study uses the constructs from the previous studies, which are to be incorporated in
the FinTech domain. For PEOU and PU, the items are adopted from Khalil (2005) and
Amin et al. (2014). Similarly, subjective norm’s items are adopted from Gopi and Ramayah
(2007) and for CI items, Goldsmith and Hofacker’s (1991) scale was used. While the
determinant of self-efficacy in this study is adopted from the past study by Khalil (2005).
VOL. 22 NO. 3 2020 jFORESIGHT j PAGE 373
8. All the constructs’ items used in this study are adopted after modification so as to be
accommodated with the Islamic FinTech domain. The Likert scale with five-points was used
within the range of 1-5 with 1-represent “strongly disagree” and 5-represent “strongly
agree”. All these items mentioned earlier were placed in the questionnaire in section two
while the first section contained the demographics, namely, gender, age, job status and
education level, respectively.
Results
Data analysis
In the context of this study structural equation modelling (SEM) is used for the analysis of
data using Amos (v. 21). Further SEM is a confirmatory approach in the current study is
suitable because it is covariance-based and it being a confirmatory approach (Hair et al.,
2010). According to Hair et al. (2010), SEM is advantageous because of its ability to
simultaneously testing the measurement and path model. Further, the model of TAM has
been largely validated in applied and validated in many studies. Thus, there is strong
theoretical support to specify our model.
Measurement model
The model fit in this study was assessed by opting maximum likelihood estimation using a
comparative fit index (CFI). Compared to other fit indices researchers have suggested CFI
preferred model fit index (Hair et al., 2010). The minimum threshold for CFI is 0.90 but more
is better (Hair et al., 2010). Figure 3 portrays the initial measurement model. As Figure 3
shows that to determine either the variables measured the hypothesised latent variable
reliably. The confirmatory factor analysis was initiated. These latent variables were freely
allowed to intercorrelate with no causal order attribution. This is the stage where it is advised
to cover the problem with the measurement model if any. Furthermore, convergent validity
was examined on the basis of criterion. Whereby indicators estimated pattern coefficiently is
significant on its posited underlying construct factor.
Validity measures
Moreover, construct validity comprises of convergent and discriminant validity. The latter is
investigated by average variance extracted (AVE) square root for each (diagonal) inter-
Table I Frequency statistics
Demographic information Frequency (%)
Education
Under-graduate 122 60.0
Post-graduate 83 40.0
Age
20-30 102 50.0
31-40 60 29.0
31 and above 43 21.0
Gender
Male 94 46.0
Female 111 54.0
Job status
Full-time 164 80.0
Part-time 41 20.0
Source: Primary data
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9. factor correlations. As suggested by Field (2005) minimum threshold value of 0.60 is
surpassed by the factor loadings to attain convergent validity. Furthermore, the AVE is also
indicating the value over the minimum threshold of 0.50 and above 0.75 for composite
reliability (Hair et al., 2010). In addition, the value of AVE above 0.50 indicates that there
exists ideal convergent validity. It is also discovered that for internal consistency
measurement the threshold of 0.70 value by Cronbach’s alpha, which surpassed and thus
guided by Nunnaly and Bernstein (1994) internal consistency is gained.
Furthermore, for examining (square of AVE) for discriminant validity testing shown in
Table II, the inter-factor correlation construct. It is evident that the value of correlations is less
than all the diagonal values (square root of AVE). Hence, there exists enough discriminant
validity. The results indicate that discriminant and convergent validity is attained.
Figure 3 Measurement model
VOL. 22 NO. 3 2020 jFORESIGHT j PAGE 375
10. Table III mentions the indices that were produced, namely, (x2 ¼ 1,088.347, df = 284, x2/
df (x2/df) ratio 3.832, GFI= 0.902, CFI = 0.925, TLI = 0.914, SRMR= 0.0406, Pclose fit =
0.000 and RMSEA = 0.068. With the exception of the x2
-statistics (which is sensitive to large
samples), the fit indices uniformly pointed a good fitting model. According to the results, it is
indicated that the acceptable goodness-of-fit model. The value of GFI, TLI and CFI meet the
minimum threshold of 0.90. Furthermore, as suggested by Hair et al. (2010) value of RMSEA
also achieves the minimum threshold of RMSEA value < 0.08.
Figure 4 shows the structural model and the result finds squared multiple correlations (R2
)
value of 0.68. Identifying that CI, PEOU, SN, self-efficacy and PU collectively contribute to
65 per cent variance of acceptance towards Islamic FinTech. Further, to find the strength of
the relationship between endogenous and exogenous variables.
Table II also depicts that the CFI value surpasses the minimum threshold of 0.90, whereas
the RMSEA value for the model is 0.068, which is representing a valid model fit based upon
the recommendation of Hair et al. (2010).
Table IV depicts results between the independent variables i.e. CI, PEOU, SN, PU and self-
efficacy towards acceptance of Islamic FinTech. The result for CI indicates that it has a
significant positive impact on Islamic FinTech acceptance (b = 0.376, r < 0.001). Hence,
H1 is supported.
Further, the findings indicate that PEOU has a significant positive influence on the
acceptance of Islamic FinTech (b = 0.154, r < 0.001). Thus, H3 is supported. The results
also find that PU has a significant positive impact on Islamic FinTech acceptance (b =
0.224, r < 0.001). Therefore, H5 is supported as well. On the contrary, SN does not turn out
to be a significant positive predictor, which is (b = 0.105, r > 0.05).
Therefore, H2 is not supported. Moreover, self-efficacy also has no significant effect on the
acceptance of Islamic FinTech services. Meaning that both the variables SN and self-
efficacy are not significantly related to alpha level 0.05 resulting in H2 and H4 to be
rejected.
Thus, H1, H3 and H5 are supported and H2 and H4 are rejected.
Table III Fit indices of model
CMIN/DF GFI AGFI CFI RMSEA PCLOSE IFI TLI SRMR
3.832 0.902 0.854 0.925 0.068 0.000 0.925 0.914 0.0406
Notes: SE = self-efficacy; SN = subjective norms; PU = perceived usefulness; PEOU = perceived
ease of use; CI = consumer innovativeness; AIFT = acceptance of Islamic FinTech services
Source: Primary data
Table II Reliability and validity testing of the measurement model
Construct CR AVE MSV ASV CI PEOU AIFT SE PU SN
CI 0.851 0.589 0.564 0.484 0.767
PEOU 0.903 0.699 0.438 0.400 0.607 0.836
AIFT 0.891 0.620 0.564 0.472 0.751 0.638 0.788
SE 0.844 0.580 0.554 0.448 0.715 0.592 0.657 0.762
PU 0.890 0.619 0.554 0.517 0.744 0.660 0.728 0.744 0.787
SN 0.867 0.619 0.511 0.438 0.651 0.662 0.652 0.626 0.715 0.787
Notes: SE = self-efficacy; SN = subjective norms; PU = perceived usefulness; PEOU = perceived
ease of use; CI = consumer innovativeness; AIFT = acceptance of Islamic FinTech services
Source: Primary data
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11. Figure 4 Structural model
Table IV Regression weights for hypotheses testing
Weights of regression b SE C.R. P result
H1 AIFT / CI 0.376 0.059 6.038
Supported
H2 AIFT / SN 0.105 0.051 1.938 0.053 Not supported
H3 AIFT / PEOU 0.154 0.054 3.256 0.001
Supported
H4 AIFT / SE 0.064 0.057 1.128 0.259 Not supported
H5 AIFT / PU 0.224 0.076 3.358
Supported
Notes:
Significant at p 0.05,
significant at 0.01,
significant at 0.001; SE = self-efficacy; SN =
subjective norms; PU = perceived usefulness; PEOU = perceived ease of use; CI = consumer
innovativeness; AIFT = acceptance of Islamic FinTech services
Source: Primary data
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12. Conclusion and implication
The purpose of the current study is to examine Malaysian’s acceptance for Islamic FinTech,
which is offered by the service providers in the country and determinants influential for
making an individual use (Islamic FinTech) FinTech based on principles of Shariah. In terms
of theoretical implication, this work contributes to theoretical framework development.
Further, the proposed framework can be applied in behaviour studies, which are carried out
to determine the acceptance of an individual for digital products, as well as Shariah-based
services and products.
Furthermore, this study adds to a new relationship between CI and Islamic FinTech
acceptance. From the theoretical standpoint, this research introduces a model based on
TAM and incorporates a new variable, which is CI that enriches the literature on Islamic
FinTech. The research framework is based on TAM, which is a pioneering effort to use the
aforesaid theory in the context of Islamic FinTech acceptance.
Hence, this study makes an effort to contribute to the scarce literature on Islamic FinTech on
empirical grounds particularly, using TAM modified framework in the setting of Islamic
Finance is an effort to improve the predictivity of acceptance factors.
The effects of the factors in the Islamic home financing setting are particularly sparse.
Literature suggests that there are limited studies on the Islamic FinTech acceptance,
therefore, current work is an effort towards proposing factors responsible for Islamic
FinTech acceptance. All the variables used in this study may be able to better explain one’s
acceptance such as PEOU, CI and PU. It is suggested by the findings that among all the
determinants for Islamic FinTech acceptance, CI is the most influential one as presented in
Table IV. TAM theory was effective in the Islamic FinTech’s acceptance prediction.
Extricating the specific determinants that affect Islamic FinTech including consumers’
innovativeness, PEOU and PU offer a vibrant understanding of the association among
factors and definite effects that these factors have on acceptance. Hence, the findings of
this research turn out to be pertinent to practitioners.
The previous sections mentioned the results of the hypotheses. Moreover, brief implications
may be described. Starting with CI, it is found that CI, impact Islamic FinTech’s acceptance
significantly. Hence, it is, therefore, important for policymakers to look into how can new
technology-driven platforms are used by their consumers. On the same token, bank
managers may require to know their consumers who may be able to participate with new
innovative products to estimate the demand for such innovative products formulated using
FinTech platform. Concerned with subjective norm (SN) in the current study SN does not
influence Islamic FinTech acceptance. Thus, it opens another floor for discussion. On the
same note, self-efficacy does not directly affect Islamic FinTech acceptance. While PEOU
significantly influences Islamic FinTech acceptance. PU also affects FinTech acceptance
significantly. Taking into consideration, results of this study it is expected of policymakers
and managers of Islamic banks to look into factors, which significantly influence Islamic
FinTech acceptance, namely, CI, PEOU and PU. These factors may be considered as a
prime reason for an individual to accept Islamic FinTech services as they are predicting 65
per cent of the variance. Hence, there may also be other factors responsible for Islamic
FinTech prediction. In that current research fills the research gap by contributing factors
responsible for Islamic FinTech acceptance and extends the technology acceptance model
as a baseline model.
Furthermore, current research alike others have limitations in terms of the sampling method
used and only covers a part of Klang Valley. Further studies need to be conducted in other
regions as well with a large population. Moreover, there might be other factors responsible
for Islamic FinTech acceptance, and therefore, this work is limited in terms of applicability of
accepted theories as it is drawn upon by TAM. For this reason, future studies may also use
PAGE 378 jFORESIGHT jVOL. 22 NO. 3 2020
13. other related theories including but not limited to a unified theory of acceptance and use of
technology (UTAUT1 and UTAUT 2).
Even though FinTech is at the infancy stage in Malaysia and there are already few banks
that have implemented FinTech platform. Furthermore, the authors suggest that to get
Islamic Fintech’s support among users of Islamic bank there might be some changes
needed in terms of policymaking. Policymakers of the Islamic bank may also need to
accommodate factors of the current study to invite their customers to use the services of
Islamic FinTech.
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Author Affiliations
Imran Mehboob Shaikh is Heads Department of Management Science, Mohammad Ali
Jinnah University, Karachi, Pakistan and Faculty of Business Administration and Social
Sciences, University of Malaya, Malaya, Malaysia.
Muhammad Asif Qureshi is based at Mohammad Ali Jinnah University, Karachi, Pakistan.
Kamaruzaman Noordin is based at the University of Malaya, Kuala Lumpur, Malaysia.
Junaid Mehboob Shaikh is based at the University of South Australia, Adelaide, Australia.
Arman Khan is based at the Department of Business Administration, Shaheed Benazir
Bhutto University Shaheed Benazirabad, Shaheed Benazirbad, Pakistan.
Muhammad Saeed Shahbaz is based at the Department of Management Sciences,
Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Karachi, Pakistan.
Corresponding author
Imran Mehboob Shaikh can be contacted at: imranims800@gmail.com
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16. Appendix 1
Table AI Standardised regression weights
Item Estimate
PEOU4 / PEOU 0.749
PEOU3 / PEOU 0.822
PEOU2 / PEOU 0.892
PEOU1 / PEOU 0.875
PU1 / PU 0.712
PU2 / PU 0.790
PU3 / PU 0.820
PU4 / PU 0.817
PU5 / PU 0.790
AIFT1 / AIFT 0.718
AIFT2 / AIFT 0.811
AIFT3 / AIFT 0.829
AIFT4 / AIFT 0.775
AIFT5 / AIFT 0.800
CI1 / CI 0.790
CI2 / CI 0.779
CI3 / CI 0.764
CI4 / CI 0.735
SN1 / SN 0.781
SN2 / SN 0.757
SN3 / SN 0.819
SN4 / SN 0.790
SE1 / S 0.841
SE2 / S 0.819
SE3 / S 0.793
SE4 / S 0.560
Source: Primary data
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