International Journal of Knowledge Management

Volume 18 • Issue 1

The Role of Marketing Knowledge

Management in Enhancing Digital Financial
Innovation in Commercial Banks:
Empirical Study
Hani H. Al-dmour, The Univeristy of Jordan, Jordan
Futon Alsfour, The University of Jordan, Jordan
Rand Al-Dmour, The University of Jordan, Jordan
Noor Majid Saifan, Al Ahliyya Amman University, Jordan

ABSTRACT

This study examines the role of marketing knowledge management (assets and capabilities) in
enhancing digital financial innovation through the moderating role of employees’ demographic
characteristics (age, education, experience, and position) in commercial banks operating in Jordan. To
accomplish this aim, a conceptual framework based on knowledge-based theory and literature review
was developed. A total of 336 responses to a questionnaire survey were collected from the managers
and employees working on commercial banks operating in Jordan. The empirical findings revealed
that marketing knowledge management capabilities positively and significantly affect digital financial
innovation. The findings also support the moderating effect of only two demographic characteristics:
of employee education and position on the relationship between marketing knowledge management
and digital financial innovation in commercial banks in Jordan.

Keywords
Business Performance, Digital Financial Innovation, Marketing Knowledge Management

INTRODUCTION

Applying knowledge efficiently and correctly will help organizations increase their competitive
advantage. Facilitating marketing knowledge depends on the presence o knowledge management
capabilities (Masa’deh, et al., 2019). These capabilities assist in creating knowledge by integrating/
combining different resources and activities that positively affect competitive advantage (Lungu,
2019). In the business environment context, products, marketplaces, technologies, consumers, rivals,
protocols and even communities transform hastily towards knowledge management. They manage,
store, and use knowledge and data they have collected overages since they deem knowledge an enabler
and intangible asset to organizational success. Also, knowledge serves innovation and sustainable
competitive advantages (Fidel et al., 2016). Therefore, management and marketing scholars today
appreciate the ability to create and employ knowledge to be the essential source of a firm’s better

DOI: 10.4018/IJKM.291094 *Corresponding Author

This article published as an Open Access article distributed under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and production in any medium,
provided the author of the original work and original publication source are properly credited.

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Volume 18 • Issue 1

performance (Abualoush et al., 2018; Muddaha et al., 2018). Knowledge brings awareness and
expertise as cornerstones for economic interests.
As a result, strategic knowledge should be valued as a treasured resource for organizations
regardless of the sector and the business in which they operate (Fomani and Sherani, 2012). In addition
to the agreed-on benefits, marketing studies agree that marketing knowledge mirrors both explicit and
tacit knowledge. It involves strategies with rivals, collaborations, tactics and customer relationships.
Furthermore, it indicates the learned lessons from earlier marketing experiences to be employed when
developing new products or services while retaining existing customers’ relationships (Foumani and
Chirani, 2012). Thus, this knowledge ought to be effectively managed (Kermally, 2019). As another
side of the discussion, because of its significance, innovation has resulted in various perspectives and
led to the introduction of multiple typologies (Chesbrough, 2010). Innovation is considered a crucial
factor in wealth creation and organizational competitiveness since it is now outdated to compete based
only on financial capital or based on copying others (Efrat et al., 2017).
Marketing knowledge management and competitive advantage are significantly related to each
other. This relationship is practically beneficial for business organizations. It is argued that this
relationship’s importance emanates from the fact that organizing knowledge empowers employees in
organizations to enhance their performance in accomplishing their tasks and performing their activities
(Ritala et al., 2018; Abualous, et al., 2018). Competency and incremental innovation indicate a solution
to reduce sustainable development pressure. Additionally, they develop new capabilities to remove
any unwanted business practices and capture business value successfully (Massa and Tucci, 2013;
Foumani and Chirani, 2012). On the one hand, merging between innovation and existing business
settings is hard to be achieved (Massa and Tucci, 2013; Chesbrough, 2010). On the other hand, as
any innovation effort’s success is not only the accountability of the innovativeness/actor, the role
of social and business contexts needs to be improved and systemic at all levels (Massa and Tucci,
2013; Foumani and Chirani, 2012). Despite the growing recognition of the importance of marketing
knowledge management contribution to the promotion of innovation, most of the existing studies have
not made clear guidance on unique knowledge processes believed to have the most significant effects
(Bueno et al., 2008; Rahimi et al., 2018). Further, research on the interaction between knowledge
management and innovation is highly needed (Andreeva and Kianto, 2011; Dahiyat, 2015)
Greater use of technology in banks is allusive to an industry leveraging KM and is ideal for
this study. Banks have realized the crucial role of knowledge management in gaining an edge in this
competitive field. On the other hand, disruptive innovation holds potential in empowering the bank
industry to face unprecedented challenges reflected in the decline of the value provided to clients
and shareholders through innovative delivery services/technologies that replace outdated ones. These
innovations are neither imitative nor incremental; however, existing services/ technologies should be
substituted by ones with more benefits; namely, those that are more valuable, more accessible and
more affordable, thereby making them available for much larger segments of customers which might
be previously ignored by current competitors (Bolen et al., 2009; Wessel and Christensen, 2012).
Despite the growing body of literature examining knowledge management practices in the
banking context, including processes, functions and best practices in KM and the effect of KM on
digital financial innovation (e.g., Mciver et al., 2017), the authors of this research noted a lack of
empirical studies that examined and validated the impact of marketing knowledge management (assets
and capabilities) on digital financial innovation via the moderating role of managers’ demographic
characteristics (age, sex, education, experience and position) in the context of commercial banking
business in Jordan. In general, banking sectors are operating in a dynamic environment at the national
and global levels. Consequently, they endeavour to improve their services and administration work
by innovative and high-quality products and services to gain a leading position in the market. This
research is expected to help bank managers develop new policies and give more considerable attention
to marketing knowledge management (assets and capabilities) and digital financial innovation to
enhance competitive advantages.

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LITERATURE REVIEW

Marketing Knowledge Management in Banking Sector

Marketing knowledge management is part of the knowledge the company possesses and utilizes in its
strategies and operations. According to literature, the concept of marketing knowledge management
is purely a subset of knowledge management. Researchers defined this concept in terms of other
dimensions and concepts in business management. For example, Leposky et al. (2017) defined it as
the integration of information. Moreover, Morgan (2012) defined marketing knowledge management
as the knowledge resources shared by marketing departments. Akroush and Al-Mohammad (2010)
stated that marketing knowledge management is “a discipline that involves the recognition and
analysis of obtainable and required marketing-related knowledge assets and capabilities and the
ensuing, planning and control of actions to develop both marketing assets and capabilities to fulfil
organizational objectives”. Marketing knowledge management also refers to that specific scope of
knowledge related to organizational marketing processes (Fang et al., 2010). On the other hand, other
researchers relate marketing knowledge management to the efforts towards analyzing the trends of
the market to understand social aspects, customer behaviors and cultural aspects, and develop brands,
products, and different marketing activities (Fang et al., 2010). Hanvanich et al. (2003) argued that
with the increasing importance of marketing in today’s trade, modern organizations need marketing
knowledge management as a significant source of competitive success.
A marketing process consists of different actions and activities according to responsibilities and
purposes. For instance, a marketing mix includes various activities designed for the development
and management of an organization. Other events are designed to develop, disseminate, and utilise
marketing information (Ellis, 2010). However, more developed, and advanced activities are used
to implement marketing philosophy and other marketing approaches (Falahati et al., 2013). Some
activities are also designed to make marketing philosophy and marketing methods operational
throughout the organization. Such a variety of marketing activities requires the existence and
optimization of relevant assets and growth abilities of MKM to achieve organizational goals. Faraji
(2011) argued that if financial firms are moving slower than their surroundings, they are subject to
collapse. Business managers need to manage marketing knowledge and information to make the
necessary decisions. Such management leads to a decrease in errors and duplication and increases
problem-solving and decision-making speed. This will reduce costs and lead to more effective
relationships and better services provided to customers and achieve employee satisfaction. On the
other hand, it should be noted that in today’s economy, the interest of banks and the banking industry
in improved technology has intensified competition among banks and meanwhile, banks are successful
and have excellent performance (Liebl, 2015). An organization’s marketing assets and capabilities
have been described as a significant determinant of business performance and are a potential source
of achieving competitive advantage:

(1) Built-in marketing assets are these assets acquired by the organization over time. Examples of
built-in marketing assets are the organization’s name and image, which may drive customers’
purchasing decisions, achieve better satisfaction levels, and improve loyalty (Falahati et al., 2013).
Growing sales’ volume increases market share. Investment in developing an organization’s name
and brand image should undeniably influence its competitive situation in the market, thereby
positively impacting its performance (Fang et al., 2010).
(2) Invested-in marketing assets refer to assets expected to be developed through investments
extended by the organization. This concept is defined as “the existing assets observing substantial
investment, or new assets being invested-in” (Akroush and Al-Mohammad, 2010; Morgan,
2012). Owning built-in marketing assets overtime is based on the businesses needed to invest in
developing old assets and acquiring new ones which are the “invested-in marketing assets”. In
other words, even though most of an organization’s assets can be built-in, continuous investment

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is needed to develop them to competitively deal with changes in the market environment (Akroush
and Al-Mohammad, 2010).
(3) Internal marketing capabilities are viewed as the internal processes associated with providing
value-added products and services that meet competitive requirements. Internal marketing
capabilities induce functional integration, finances, strategic management, marketing management
and ongoing operations’ management (Akroush, 2006). Internal marketing capabilities have a
positive impact on business performance. These capabilities provide organizational skills and
distribute high-quality products and services that will positively impact customer satisfaction,
improve their loyalty and improve organizational performance (Morgan, 2012; Akroush and
Al-Mohammad, 2010).
(4) External marketing capabilities are defined as “the external processes concerned with
understanding the organization’s external environment with all its factors”. Examples of external
marketing capabilities are opponents, customers, service suppliers and distributors. Organizations
must carry out a comprehensive analysis of the macro-industry characteristics through analyzing
and understanding all the relevant dimensions (Morgan, 2012).

Digital Financial Innovation

Mansur et al. (2018) defined organizational innovation as the competitive advantage obtained from
qualified human resources, where marketing knowledge enables organizations to compete based on
quality and innovation. Crossan and Apaydin (2010) argued that innovation is the “production and
adoption, assimilation and exploitation of value-added novelty in economic and social spheres; renewal
and enlargement of products, services and markets; development of new methods of production; and
establishment of new management systems. It is both a process and an outcome.” Organizations tend
to expand their innovative actions to leverage their performance and profitability. Such expansion
needs different strategies, such as managing knowledge within the organization and using such
knowledge in their different operations. In other words, innovation is associated with introducing
new techniques, methods, techniques, or processes into the production chain to provide remarkable
benefits and advantages to customers in terms of products and services (Oliva and Kotabe 2019). When
financial innovation mentioned in the broad sense, it is evident that it encompasses establishing new
financial institutions, technologies, instruments and tools, processes, products, and services. Examples
are online banking, phone banking and different information and communication technology (ICT)
applications (Edwards-Schachter, 2018). Gomber et al. (2017) argued that the term digital finance
innovation includes a wide variety of novel financial software programs, businesses, products, and
services to enable customers to interact and communicate with financial institutions more quickly
and more efficiently. Something similar was stated by Korir et al. (2015) who indicated that digital
financial innovation has to do with introducing new instruments and tools to be utilized by financial
institutions to raise their level of effectiveness and efficiency in terms of the services offered by these
institutions to their customers.
Digital finance covers a wide range of financial fields. Examples are payments, remittances,
savings and investments, personal financial management, trade, and invoice finance. Digital financial
innovative services can be made available to large firms, SMEs, and individuals. According to Klapper
et al. (2016), digital financial innovation also encompasses diverse financial processes, such as capital
market activities, banking system connectivity, credit scoring, asset securitization, risk management
and trade processing. It also extends to cover other financial processes, like middle- and back-office
reporting, customer service, collections, and recovery and compliance with the so-called Anti-
Money Laundering-Know Your Customer (AML-KYC). It can be argued that financial institutions,
particularly banks, have improved their performance and profitability, relying on financial innovation
(Scott et al., 2017). Banking has witnessed a real revolution in performed financial transactions, as
stated by Yin and Zhengzheng (2010), who found out that Chinese commercial banks have remarkably

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enhanced their financial operations by utilizing digital financial innovation. It was revealed that the
Tunisian banking industry has benefited from the positive, significant relationship between return
on assets (ROA) and financial product innovation, Mabrouk and Mamoghli, (2016). In this study,
digital financial innovations can be grouped as new products: subprime mortgages or services,
internet banking and others. Digital financial services (DFSs) are significant financial resolutions
for cultivating financial inclusion (Buckley and Malady, 2015; Akhisar et al., 2015). Digital financial
are provided to the underprivileged using advanced skills, digital platforms, and electronic money
models (Scott et al., 2017; David-West et al., 2018; Nguena, 2019).

Marketing Knowledge Management and Digital Financial Innovation

Several scholars have widely discussed the relationship between knowledge management and
technological innovation (e.g., Kör and Maden, 2013; Waribugo et al., 2016; Talat, 2018). Most
researchers have agreed that innovation depends heavily on the knowledge and the way of managing
it. Today, knowledge management becomes an essential managerial task that helps organizations in
shaping a sound innovation strategy. Knowledge management has been recognized as a tool to help an
organization identify gaps in knowledge and provide ways to fill up these gaps to aid organizational
innovation (Akram, 2011). Through knowledge management, managers can use pre-programmed
models based on integrative knowledge of past experiences and ask for updated information while
considering alternative solutions and stimulating innovative proposals. Al Rubaiee et al. (2015)
conducted a study that aimed at developing a better understanding of the relationships between
organizational performance, organizational innovation, and knowledge management processes
in the context of telecommunication and information technology industry in Amman. The study
was exploratory and quantitative. The results of the study revealed a positive and robust impact of
knowledge management processes on organizational innovation.
To achieve successful MKM implementation and technological innovation, organizations need to
determine the role of the employees’ characteristics; however, studies that empirically and specifically
examined the impact of employees’ demographic characteristics on the relationship between marketing
knowledge management (capabilities and assets) and product innovation have rarely been available.
Harem and Al-Saae’d (2006) indicated that knowledge management practices were influenced by their
characteristics (age, experience, education position). Al-Dmour et al. (2020) argued that managers’
attitudes toward knowledge management are influenced by their experience and position factors. Also,
Ababneh’s study (2008) showed that knowledge management has a strong positive correlation with
organizational innovation and that employees’ demographic variables significantly impact practising
each KM dimension. However, other studies showed that age, education, and position do not affect
knowledge management behaviour, (e.g., Ismail 2006; Ojha 2005; and Watson & Hewett 2006).

Research Model and Hypotheses

The major elements of this research are established based on preceding literature, either theoretically
or empirically. Indeed, this study used variables that are common in knowledge management
literature. Figure 1 represents a study model that shows the independent variables within the
construct of marketing knowledge management capabilities and the dependent variable (digital
financial innovation), and the proposed relationship between them. The current research considers
four independent variables within marketing knowledge management capabilities and one dependent
variable (digital financial innovation). Further, marketing knowledge management capabilities include
built-in marketing assets, invested-in marketing assets, internal marketing capabilities and external
marketing capabilities. (Muddaha et al., 2018; Akroush and Al-Mohammad, 2010) and digital financial
innovation. This research is based on knowledge-based theory (Grant, 1996) and financial innovation
(Silber 1993). The knowledge-based theory assumes that knowledge as an intangible asset resource is
an essential strength whose proper utilization could go a long way in offering long-term sustainable

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Figure 1.

competitiveness. An essential aspect of this theory is that the primary source of competitiveness is
applying knowledge and not just in possession of knowledge.
On the other hand, financial innovation theory viewed that improving corporate performance is
the critical factor for financial institutions to engage in digital financial innovation through service
delivery efficiency (Silber, 1993). Innovation harnesses the ICT capabilities to create new banking
services and new media for offering services. Theoretical background and knowledge-based theory
and the relevant literature on marketing knowledge management and digital financial innovation were
reviewed and integrated to develop a model to guide this study.
Based on the study model and the study questions, the following hypotheses are formulated in
the Jordanian environment business context:

Ho1: There is no significant impact of marketing knowledge management capabilities (built-in

marketing assets, invested-in marketing assets, internal marketing capabilities and external
marketing capabilities) on digital financial innovation in Jordanian commercial banks.
Ho 2. Employees’ demographic variables (age, education, experience, and position) do not significantly
moderate the relationship between marketing knowledge management capabilities and digital
financial innovation.

RESEARCH METHODOLOGY

The research employs a quantitative method with an exploratory and descriptive design. A survey
questionnaire was employed to collect data to confirm the conceptual research model and investigate
the research hypotheses. This research’s target population consisted of all the banks operating in the
Jordanian market registered at the Association of Banks in Jordan up to 2019. 13 commercial banks
are operating in Jordan, and all agreed to participate in this study. The participants (i.e., the sample)
in this research were specified as all marketing managers and employees at banks’ headquarters and
branch working for those banks. The researchers distributed a total of 602 surveys using both online
and paper-based questionnaires. The number of the returned instruments was 492. After eliminating
any incomplete or improperly filled questionnaires, the valid usable questionnaires for further analysis
were 336 (55.8% of the total), which is a decent rate in comparison with the lengthy approvals and

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authorization processes followed by the researchers to distribute and share the survey questionnaire
to the targeted bankers.
The questionnaire’s content (measures) was mainly selected and adopted from relevant previous
studies. The independent variables: “components of marketing knowledge management” were
measured using a 5-point scale developed by Akroush and Al-Mohammad (2010), Davoudi et al.
(2018) and Prifti and Alimehmeti (2017). The dependent variable “Digital financial innovation”
was measured using a 5-point scale developed by Girniene (2013), Ramona-Diana and Bolisani
(2016), Kör and Maden (2012). For construct validation, the questionnaire content was modified
to the practice of Jordanian business culture context based on a pilot study and feedback from five
professional academic staff members in this filed.

Respondents’ Demographic Profile

In this study, 57% of the respondents were males and 33% in the age group between 40 and 49. About
75% of the respondents have a bachelor’s degree in education, and 39% have an experience of fewer
than ten years, while about 47% of them were acting as divisional/branch level managers in Jordanian’s
commercial banks. Table (1) summarizes the demographic characteristics of the respondents.

Descriptive Analysis

Table 1. The demographic characteristics of the respondents

Characteristics Category Frequency Per

cent (%)
Age 24- 29 years 84 25
30-39 years 95 28
40-49 years 110 33
50 years and above 47 14
Education Secondary and 27 08
diploma
Bachelor’s degree 254 75
Graduate degree (MA 57 17
or PhD)
Experience Less than 10 years 132 39
11-15 years 121 36
16 years and above 83 25
Position Divisional /branch 157 47
manager
Head of department/ 99 29
executive
Chief officer/lower 80 24
level

The mean, standard deviation, level of importance, skewness, and kurtosis were calculated for all the
measurements to illustrate the extent of the significance of variables to the sampled respondents. The
descriptive statistics offered in Table 2 pointed to a positive disposition towards the items measured.
The mean values indicate a narrow spread around the mean. Also, most items’ mean values were

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greater than the midpoint (3) and ranged from 4.30 to 4.38. The level of every item was calculated
by the following method: (highest point in Likert scale - lowest point in Likert scale) / number of
levels used = (5-1) / 5 = 0.80, where (1-1.80) indicating “very low”, (1.81-2.60) indicating “low”,
(2.61-3.40) indicating “moderate”, (3.41-4.20) indicating “high” and (4.21-5) indicating “very high”.

Table 2. Means and standard deviations

Standard Level of Skewness Kurtosis

Constructs Mean
Deviation importance
Marketing Knowledge Management Capabilities
Built-in 4.38 0.591 87.6% -1.806 5.090
marketing assets
Invested-in 4.34 0.575 86.8% -1.774 5.280
marketing assets
Internal 4.32 0.572 86.4% -1.501 4.682
marketing
capabilities
External 4.33 0.611 86.6% -1.402 3.364
marketing
capabilities
All 4.34 0.534 86.8% -1.697 5.661
Digital 4.30 0.551 86.0% -1.565 4.631
Financial
Innovation

After that, the items were being ordered by their means (Sekaran,2003). After careful assessment
using skewness and kurtosis, the data was generally distributed for normality test. Indeed, skewness
and kurtosis indicated normal distribution, since most of the values were inside the adequate range
for normality (i.e., -1.0 to +1.0) for skewness and less than 10 for kurtosis (Hair et al., 2010).

DATA ANALYSIS

The Exploratory Factor Analysis (EFA)

The aim of using the exploratory factor analysis is to reduce the number of variables in each MKM
(i.e., Built-in marketing assets, Invested-in marketing assets; Internal marketing capabilities and
external marketing capabilities) to facilitate further regression analysis. PCA is also deemed suitable
for overcoming multicollinearity problems. In this study, data was cheeked to determine whether it
is appropriate for factor analysis. The factor analysis findings have been tested using eigenvalues,
interpretability, and internal consistency, as suggested by Hair et al., (2010). Items having eigenvalues
above (1) and factor loadings under (0.40) have been determined.
Thereby, items having a weak or no relationship to each other are ignored (Hair et al., 2010). In this
study, marketing knowledge management was measured using (29) items, as presented in Table 4. An
inspection of the correlation matrix indicates that all the correlations were above the acceptable level
of 0.40. Subsequent KMO and Bartlett’s test resulted in a significant level of probability (P>0.000)
and a high KMO statistic of (0.794), confirming that all the factor analysis could be carried out, as
(79.0%) of the variance in the data can be explained by this construct, as presented in Table.3.

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Table 3. KMO and Bartlett’s test

KMO and Bartlett’s Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0. 893
Approx. Chi-Square 856.038
Bartlett’s Test of Sphericity DF 314
Sig. 0.000

Table 4. Total variance explained

Component/ Factor Rotation Sums of Squared Loadings

Eigenvalue % of Variance Cumulative %
1 5.152 23.713 23.713
2 2.604 19.681 43.394
3 1.159 14.785 58.179
4 1.231 11.932 70.111

The exploratory factor analysis results in Table (5) indicate that four factors could be extracted
from the variables of marketing knowledge management. The first factor, which accounts for (23.713
of the variance with loadings ranging from 0.61 to 0.83, can be identified as a “Built-in marketing
assets” factor. The second factor, which explains 19.681% of the variance with loadings ranging
from 0.63 to 0.79, can be labelled as “Invested in marketing assets” factor and the third one, which
accounts for (14.785%) of the variance can be named as “Internal marketing capabilities” factor.
Furthermore, the last one is called “external marketing capabilities” which accounts for (11.932)
The combination of these factors accounts for (70.111%) of the total variance in the questionnaire data
as can be shown in Table (5). In statistics, multicollinearity is a phenomenon in multiple regression
analysis; it arises if there is a high correlation coefficient (positive or negative) between two or more
independent variables.
Multicollinearity can be assessed by the most widely used measures: Tolerance and Variance
Inflation Factor (VIF), which is the proportion of variance in the independent variable that is not
explained by its relationships with the other independent variables. Hair et al. (2012) stated that the
minimum cut-off value for tolerance is typically (0.10); a tolerance value less than 0.10 should be
investigated further. On the other hand, the Variance Inflation Factor (VIF) determines how much the
variance of regression coefficients is inflated by multicollinearity problems, noting that (VIF) value is
favorable when being less than five and in more relaxed criteria when being less than 10 (Hair et al.,
2010). From this perspective, the multicollinearity test for the four factors (Built-in marketing assets,
Invested-in marketing assets; Internal marketing capabilities and external marketing capabilities)
was accomplished, where all (VIF) values were less than five and less than 10), while tolerance
values were more than (0.10). Consequently, there is no collinearity within the collected data, which
reinforced the model by avoiding having interchangeable beta values between independent variables
and indicates that there was no bias.

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Table 5. Main factors underlying the knowledge management process

Code Items (variables) Loadings Cronbach’s

Alpha

Factor 1 Built-in Marketing Assets 0.760

BM3 Developing new banking products. 0.658
BM5 Developing customer service quality. 0.615
BM2 Developing a customer service relationship. 0.712
BM1 Building a strong brand image of the bank. 0.839
BM8 Developing bank promotion and customer education. 0.707
BM6 Improving the banking channel of distribution. 0.744
BM7 Building employees’ skills, capabilities, and knowledge. 0.663
BM4 Building technological abilities, e.g., information 0.719
technology.
Factor 2: Invested in Marketing Assets 0.831
IM3 Strategic marketing planning. 0.699
IM5 Market segmentation. 0.645
IM6 Building reputation or image. 0.709
IM2 Service quality. 0.630
IM1 Technological processes. 0.764
IM4 Service delivery process activities. 0.795
IM8 Market place and customer knowledge. 0.749
IM7 Serving customers and handling their complaints. 0.730
Factor 3: Internal Marketing Capabilities 0.856
CM1 Integrated marketing programs. 0.704
CM4 Innovating and developing new banking services. 0.741
CM5 Superior pricing capabilities. 0.729
CM6 Marketing communication capabilities. 0.585
CM4 Distribution capabilities. 0.740
CM2 Superior skills, abilities, and knowledge of marketing and
0.721
technical specialists.
Factor 4: External Marketing Capabilities 0.891
EC1 Understanding of customer wants and needs. 0.697
EC3 Creating, sustaining, and enhancing relationships with the
0.757
firm’s customers, financial institutions, etc.
EC2 Conducting a comprehensive analysis of the external
0.808
business environment.
EC5 Analyze information to anticipate market requirements 0.778
EC6 Matching the bank’s distinguished competencies with
0.715
external opportunities in the marketplace.
EC4 Identifying lead strategic activities. 0.619

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HYPOTHESES TESTING

This part of the study focuses on testing the study hypotheses, which were developed to assess
the relationships between independent and dependent variables. Multiple regression was used to
accept or reject the research hypotheses. Two regression analyses were performed to determine the
relationships between the independent variables and the dependent variable and the effect of the
moderator. Interaction testing can show the moderator effect (Hair et al., 2010). A moderator is a
variable that strengthens or weakens the relationship between dependent and independent variables.
Statistically, moderation is an interaction between the independent and moderator variables on the
relationship with the dependent variable (Hair et al., 2010).
Multiple regressions enable to test the effect of many different factors (independent variables)
on a particular outcome (dependent variable) at the same time. In the beginning, this study used the
model summary, which consists of “coefficient of determination (R2)” to measure how much that
independent variables (Built-in marketing assets, Invested-in marketing assets; Internal marketing
capabilities and external marketing capabilities) can justify from the problem in the dependent variable
(Digital financial innovation). R2 falls between 0 and 1. Higher values of R2 improved the regression
model fit with the observations. Furthermore, analysis of variance (ANOVA) was used to assess the
model fit and its overall significance to test the hypotheses (Ho1 and Ho2).

The First Hypothesis

Ho1: There is no significant impact of marketing knowledge management capabilities (built-in
marketing assets, invested-in marketing assets, internal marketing capabilities and external marketing
capabilities) on digital financial innovation in Jordanian commercial banks.
After conducting a multiple regression test to examine the correlation, the relationship between
the variables (R) is 0.751, which means a significant relationship between the four main factors of
marketing knowledge management and digital financial innovation. The R2 value indicates that the
four factors (Built-in marketing assets, Invested-in marketing assets; Internal marketing capabilities
and external marketing capabilities) are responsible for about 56% of the change in commercial
banks’ level of innovation.

Table 6. Model summary

Std. The ANOVA

Model R R Square Adjusted R Square errorof the Sum of Df Mean F Sig.
Estimate Squares Square
1 0.751a 0.564 0.549 0.36751 23.477 3 9.188 5634 0.000

a. Predctors: (constant) Built-in marketing assets, Invested-in marketing assets; Internal marketing capabilities and
external marketing capabilities

By implementing the level of significance (0.05) to reject or accept the first hypothesis; the
F- value for the collected primary data was 9.188, which is significant at the level of p<0.05 (sig. =
0.000). It means that there is a statistically significant relationship between the marketing knowledge
management functions (Built-in marketing assets, Invested-in marketing assets; Internal marketing
capabilities and external marketing capabilities) on digital financial innovation. Table 7started with
an estimation of beta for each independent variable. It gives a measure of the contribution of each
variable to the model. Clearly, a large value shows that a unit change in the independent variable has
a large effect on the dependent variable; internal marketing capabilities represented the highest beta

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values, which was 0.462. Therefore, internal marketing capabilities have the highest contributions
in the research model.

Table 7. Coefficients for variables

Coefficients
Model Unstandardized Standardized T Sig.
Coefficients Coefficients
Beta Std. Beta
Error
(Constant) 2.143 0.232 11.087 0.000
Built-in 0.161 0.042 0.213 4.177 0.000
marketing assets
Internal 0.311 0.046 0.462 6.876 0.000
marketing
capabilities
11
Invested 0.242 0.036 0.154 4.354 0.000
in marketing
assets
External 0.101 0.031 0.099 2.180 0.031
marketing
capabilities
a. Dependent variable: Digitals financial innovation

The second part of Table 7 demonstrates T and sig. Values, which give a rough indication of the
relationship of each independent variable with the dependent variable. For instance, a big absolute (T)
value and a small (p) value indicate that a predictor variable has a large effect on the criterion variable.

The Second Hypothesis

Ho 2. Employees’ demographic variables (age, education, experience, and position) do not significantly
moderate the relationship between marketing knowledge management capabilities and digital
financial innovation.

Moderators are variables that can modify the relationship directly between independent and dependent
variables. Hierarchal regression analysis was performed to examine the moderation effect of the
respondents’ demographic characteristics (age, education, and experience and position) on the
relationship between the independent variables and the dependent variable. It shows that: R square =
75.3 means that 75.3% of the dependent variable variation is explained by the independent variables
and p = 000 <0.01 which is very significant, implying that the model is adequate. Table 8 shows
respondents’ demographic characteristics (age, education, experience, and position) as moderators for
the relationship between marketing knowledge management and digital financial innovation. Based on
the results, only two respondents’’ demographic characteristics; position and education were positively
significant (p £ 0.05) as moderators with R square change of 0.016 and 0.020, respectively. However,
age and experience were found insignificant as moderators in the relationship between marketing
knowledge management and digital financial innovation. Therefore, Ho 2 is partially accepted. This
result implies that respondents’’ education and position factors could improve the prediction level (the

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Volume 18 • Issue 1

rate of explanation) of the relationship between MKM and digital financial innovation. The explanation
power has increased from 0.751to 0.778, with the existence of these two demographic factors.

Table 8. Hierarchical regression results of the effects of respondents’ demographic characteristics as moderators

Selected Model 1 Model 2 Model3 Model 4 Model 5

variable
MKM 0.751a*** .
management
Age 0.761b. **
Position 0.767c***
Experience 0.770d***
Education 0.778e***
R Square 0.5647 0.579 0.588 0592 0.605
Adjusted R 0.525 0.527 0.529 0.539 0.578
Square
R Square 0.003 0.018 0.016 0.007
change
F sig. change 43.111 1.222 3.298 1.058 16.344**
Sig. 0.000*** 0.344 0.031 0.142 0.0221*
*p £0 .05 **;p £0 .01; ***p £ .001

DISCUSSION, CONTRIBUTIONS, AND IMPLICATIONS

This study aims to explore the effect of marketing knowledge management (Built-in marketing assets,
Invested-in marketing assets; Internal marketing capabilities and external marketing capabilities) upon
digital financial innovation via the moderating role of bank employees’ demographic characteristics
(age, education, experience and position) in commercial banks operating in Jordan. Testing the
research hypotheses has led to results and conclusions compared with previous general findings and
observations. Three factors were extracted from the 29 items of marketing knowledge managements,
which were: (1) Built-in marketing assets, (2) Invested-in marketing assets; (3) Internal marketing
capabilities and (4) external marketing capabilities and subsequently used to answer the research
questions by using multiple regression analysis. This result is consistent with previous research (e.g.,
Akorash, 2006; Fahy et al.; Morgan, 2012; Tnorbi and El-Den, (2017).
This study’s first objective is to explore to which extent commercial banks operating in Jordan
are employing marketing management: assets and capabilities to enhance digital financial innovation.
The findings indicate that the extent of investing in marketing knowledge management of (1) Built-in
marketing assets, (2) Invested-in marketing assets; (3) Internal marketing capabilities and (4) external
marketing capabilities by commercial banks operating in Jordan are considered acceptable ((i.e., 86%
or 4.34, Table 2), since their mean is more than the mean of the scale, which is 3 (mean of the scale
= Σ Degrees of the scale 1+2+3+4+5/ 5 = 3.00). It appears that commercial banks in Jordan are
fully aware of the importance of using marketing knowledge management.
The second objective of the study was to examine and validate the impact of marketing knowledge
management capabilities and digital financial innovation in Jordanian commercial banks. The analysis
provides empirical evidence regarding marketing knowledge management’s effect on digital financial
innovation (hypotheses H1)). The results for this hypothesis significantly and positively supported the
linkage between marketing knowledge management and digital financial innovation (Rezaee and Jafari

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2015; Alrubaiee et al. 2015, Byukusenge et al. 2016, Nawab et al. 2015, Nowacki, and Bachnik, (016;
Al-Dmour et al., 2020). This could be attributed to the fact that information technology is used and
that there is some form of knowledge being acquired and distributed by commercial banks operating
in Jordan. In today’s banking industry environment characterized by rapid and continuous changes,
empirically analyzing marketing knowledge management capabilities and innovation concepts is
critical because of these concepts’ importance in creating competitive advantages.
The third objective was to examine the effect of bank employees’ demographic characteristics
(age, education, experience, and position) as a moderating factor in the relationship between marketing
knowledge management and digital financial innovation. The study’s findings indicate that only two
employees’ demographic characteristics; education and position play essential roles as moderating
factors in the relationship between marketing knowledge management capabilities and level of digital
financial innovation in commercial banks of Jordan, while age, experience does not. This result
implies that employees with higher education and position positively improve the relationship between
marketing knowledge management capabilities and digital financial innovation in commercial banks
in Jordan, while age and experience were insignificant. This result is supported by previous studies,
such as Al-Dmour et al. (2020).
This study fills the literature gap regarding a comprehensive understanding of the relationships
between marketing knowledge management (assets and capabilities), and digital financial innovation.
Also, it contributes to the literature and knowledge-based theory and fanatical innovation theory by
empirically analyzing the relationship between marketing knowledge management capabilities and
digital financial innovation. Through managing knowledge virtually, commercial banks can improve
digital financial innovation. Therefore, marketing knowledge management (MKM): assets and
capabilities (built-in marketing assets, invested-in marketing assets, internal marketing capabilities)
are external marketing capabilities been considered sufficient means of enhancing digital financial
innovation.
The study also significantly contributes to supporting knowledge-based theory and financial
innovation theory by supporting the links between marketing knowledge management (assets and
capabilities) and digital financial innovation via the moderating effect of the banks’ employees’
demographic characteristics their education and position. Based on the research findings, the
study concludes that marketing knowledge management (assets and capabilities) plays a vital
role in enhancing commercial banks’ digital financial innovation in Jordan. Marketing knowledge
management capabilities could be viewed as an essential attribute to increase innovation. Therefore,
marketing managers of commercial banks in Jordan should understand and focus on their available
marketing assets and capabilities as significant components of any effort to manage such a critical
knowledge scope. They should also use and manage their knowledge marketing management assets
and capabilities more efficiently and be more technology innovation-oriented, which will improve
their competitive advantages.
Marketing knowledge management (MKM): assets and capabilities should be integrated and
combined to enhance commercial banks’ digital financial innovation. Managers of commercial
banks in Jordan should improve marketing knowledge assets and capabilities in their organizations.
They should apply intellectual capital development and knowledge dissemination to a greater extent
because of their strong influence on digital financial innovation. The managers of commercial banks
in Jordan should integrate and fully utilize knowledge management to develop and enhance digital
financial innovation’s effectiveness in their organizations. Hence, managers in commercial banks
need to recognize the importance of practical knowledge management practices to enhance their
level of digital financial innovation. Furthermore, in similar countries, the commercial banking
sector can use this study’s outcomes to understand better the practices of knowledge management
in banks and the skills acquired by or existing in individuals working in the organization. The study
findings are also helpful to cultivate a knowledge-oriented environment. Banks should consider
promoting a culture of practising knowledge management among their managers and employees by

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motivating and training them to promote innovation. Because this study has a cultural context, it
is recommended for future studies to be extended on other types of service sectors. Therefore, we
could see the differences between marketing knowledge management capabilities on innovation on
new entry companies and a new environment. Therefore, further research is needed to be conducted
in other business environments to improve reliability and validity.

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Hani H. Al-Dmour’s background is in international marketing and his particular research interests surround the export
marketing behavior and services marketing. He completed university education and received bachelor’s degree
Business Management from the University of Jordan in 1983 and MBA degree from the University of Edinburgh in
1986. In 1985, he gained his Ph.D. degree from the University of Sheffield in export marketing behaviour in 1993.

Futon Alsfour has her MBA from the University of Jordan.

Rand Al-Dmour is an assistant professor at Management Information System Department, School of Business at
the University of Jordan. She holds a bachelor’s degree in Management Information System and MBA/Management
Degree from the University of Jordan. She also has a PhD degree from Brunel university, London, UK in 2012. Her
current research interest is in the area of information system, innovation, human resources information system,
management information system. Apart of her work, she has been published in reputable journals including IJBR,
IJMSBS, EJBM, ESJ, IJMS.

Noor Majid Saifan is a lecturer in Al Ahliyya Amman University.

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