The Effect of Business Communication Skills on Business Performance Among SMEs in Tanzania: A Case of Songea Municipality.

a International Journal of Engineering, Business and Management (IJEBM)
ISSN: 2456-7817
[Vol-9, Issue-3, Jul-Sep, 2025]
Issue DOI: https://dx.doi.org/10.22161/ijebm.9.3
Article Issue DOI: https://dx.doi.org/10.22161/ijebm.9.3.8
Int. j. eng. bus. manag.
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The Effect of Business Communication Skills on Business
Performance Among SMEs in Tanzania: A Case of Songea
Municipality.
Msyangi M. Kuruchumila
Assistant Lecturer at Institute of Accountancy Arusha, Department of Business Management, Songea, Tanzania
Received: 18 Jul 2025; Received in revised form: 14 Aug 2025; Accepted: 18 Aug 2025; Available online: 21 Aug 2025
©2025 The Author(s). Published by AI Publications. This is an open-access article under the CC BY license
(https://creativecommons.org/licenses/by/4.0/)
Abstract— This study examines the effect of Business Communication Skills on Business Performance
Among SMEs in Tanzania: A Case of Songea Municipality. Thus, dependent variable is business
performance while independent variable is Business Communication Skills. The study used a cross-sectional
survey research design and mixed research approach. From population of 4,200 SMEs, sample size of 108
respondents (SMEs Owners) were used. Questionnaires and Interviews were used as methods of data
collection. The study employed descriptive statistical analysis and regression analysis for quantitative data
and content analysis for qualitative data. Findings of regression show that business communication skills
are statistically significant at the 1% level, with a positive coefficient of (β = 0.748). This suggests that a
one-unit improvement in business communication skills corresponds to a 7.48% increase in business
performance, assuming other factors remain constant (see Table 6). Overall, the findings conclude that
enhanced business communication skills contribute positively to the performance of SMEs. This study
suggested that, SME owners needed to invest in structured communication skills development programs. This
included targeted training in verbal, written, and digital communication, along with workshops on
interpersonal skills and active listening. SMEs should also establish clear internal communication channels
and protocols to guarantee the well-organized flow of information across all levels of the business.
Keywords— Business Communication Skills, Business Performance, SMEs
I. INTRODUCTION
Business growth is the outcome of efficiently combining
firm-specific resources, capabilities, and operational
routines. In the background of Tanzania, the growth of
Small and Medium Enterprises (SMEs) depends largely on
how well these enterprises utilize their resources such as
labor, capital, and knowledge to create products and
services that meet market needs (Fajarika,Trapsilawati, &
Sopha, 2024). Growth opportunities for SMEs are
associated to current production activities, yet they are also
influenced by environmental uncertainties such as
competition and fluctuating market conditions (Coad, 2009;
Hakkert & Kemp, 2016). For SMEs in Songea, these
uncertainties mean that owners must not only manage their
operations effectively but also adapt quickly to changing
conditions to sustain and enhance their performance.
Business environment in Songea, much like in other parts
of Tanzania, is dynamic and characterized by rapid changes
in technology, customer preferences, and regulatory
frameworks. This creates a strong need for SMEs to adopt
strategic management practices that guarantee they remain
competitive and resilient (Tsuma, 2013). Strategic
management involves setting clear long-term objectives,
aligning resources effectively, and adapting strategies to
external changes (Pandisha, Kombe & Kayunze, 2024).
Within this process, business communication skills play a
vigorous role. Effective communication facilitates
coordination of activities, sharing of ideas, and building of
strong relationships with both customers and employees.
For SMEs in Songea, clear and timely communication not
only reduces operational errors but also fosters teamwork
and customer loyalty, both of which are essential for

Kuruchumila The Effect of Business Communication Skills on Business Performance Among SMEs in Tanzania: A
Case of Songea Municipality
sustainable growth. Communication contribute a
noteworthy role in creating understanding and exciting
interest and desire to purchase a product/service. It
contributes to trademark parity by creating trademark
images and embedding the brand in the consumer's memory
(Nelson, Christopher, Teddy et al., 2022).
Effective communication skills are essential for
entrepreneurial success, as they enable entrepreneurs to
identify market opportunities, build networks for accessing
knowledge and resources, and apply negotiation and
persuasion techniques crucial in business relationships,
sales, and marketing (Wegulo et al., 2023). Despite this
acknowledged significance, many micro-firms still face
performance and growth limitations due to gaps in both
technical and soft skills (EmekaNwokeji, 2020). A major
constraint in this regard is inadequate communication
competence (Nasser et al., 2022). Previous research has
consistently linked communication skills to positive SME
outcomes such as business survival, profitability, export
performance, and job creation (Turyatemba et al., 2022).
The knowledge-based theory suggests that the ability of a
firm to create, share, and apply knowledge is a key
determinant of sustained competitive advantage. In
Songea’s SMEs, communication serves as the primary
channel for transferring both tacit and explicit knowledge
within the business and between the business and its
stakeholders (Penrose, 1959; Barney, 1991). For instance,
when SME owners communicate effectively with suppliers,
they negotiate better deals and ensure timely delivery of
inputs, which improves operational efficiency (Gamage,
2022). Similarly, clear communication with customers
helps in understanding their needs, addressing complaints
promptly, and building trust, all of which contribute to
improved business performance (Basiru, et al., 2025).
Despite significant contribution of SMEs play in Songea’s
local economy, contributing to job creation, poverty
reduction, and overall economic activity, numerous still
face challenges that hinder SMEs growth. These include
limited access to market information, inadequate business
management skills, poor communication channels, and a
lack of customer engagement strategies. Weak business
communication skills, in specific, lead to
misunderstandings, slow decision-making, and lost
business opportunities. While studies in other regions have
shown a strong positive link between communication and
SME performance, for instance Musiimenta and
Akampurira, (2024), Masecko and Kungu, (2020) and
Mutuku, et al., (2022); (Otoo, 2016), there is limited
empirical evidence from Songea Municipal Council. This
gap justifies the present study, which seeks to evaluate the
effect of business communication skills on the performance
of SMEs in Songea, with the aim of providing
recommendations that can strengthen their competitiveness
and long-term sustainability.
II. LITERATURE REVIEW
2.1 Theoretical Review
This study guided by knowledge-based theories, developed
by Penrose (1959) and later extended by Barney (1991) and
Conner (1991). According to Rommer (2001), knowledge
is a noteworthy driver of productivity in SMEs and the
economy at large. Skilled and knowledgeable employees
are more efficient at learning and applying new skills, which
allows them to boost productivity, efficiency, innovation,
and risk-taking capabilities within SMEs (Timmons, 1999).
This theory distinguishes between two forms of learning:
explorative learning, which takes place internally within the
SME through operations or experiments (Zagra, Neilsen, &
Bogner, 1999), and exploitative learning, which focuses on
external knowledge acquisition.
The knowledge-based theory is founded on numerous
assumptions. First, it suggests that knowledge is significant
resource for any firm. Unlike traditional economic theories
that prioritize tangible assets, this theory emphasizes
intellectual capital and specialized knowledge as key
resources (Ogutu, et al. 2023). It also highlights that
differences in knowledge across firms are a major
determinant of sustained competitive advantage
(Purnamawati, Jie, Hong & Yuniarta, 2022). Furthermore,
it assumes that knowledge-based resources are difficult to
replicate, yet they play a pivotal role in creating and
maintaining long-term competitiveness for a firm.
Regardless of its strengths, the theory has notable
limitations. Developing and maintaining a knowledge-
based system can be costly, requiring significant time,
effort, and financial investment (Purnamawati, Jie, Hong &
Yuniarta, 2022). This expense pose obstacle for SMEs,
particularly smaller ones. Moreover, such systems
inflexible, as they are frequently programmed with specific
rules that make adaptation to new or changing situations
challenging (Tajuddin, 2025). This firmness hinder SMEs
ability to respond effectively to dynamic market conditions.
In the background of entrepreneurship, learning by doing
plays a vital role in expanding knowledge. Education,
particularly entrepreneurial training, helps integrate skills,
attitudes, and behavior’s important for business success
(Middleton, 2010). A trained entrepreneur can make
rational decisions on market entry, product selection, and
pricing strategies. This theory, offers a valuable framework
for understanding the contribution of entrepreneurship
training in enhancing business performance. It underscores

the importance of knowledge acquisition and its influence
on improving personal abilities, making it applicable in
examining the relationship between entrepreneurship
business communication skills and SME performance in
Tanzania.
2.2 Empirical Review
This section presents the review related to influence of
business communication skills on business performance.
Business communication skills is a multi-dimension, and it
has been categorized differently such as, financial skills,
managerial skills, and creative thinking skills as soft skills.
Effective business communication skills build trust among
employees and enable business entity to attain its goals
(Jiang et al., 2020). Business communication can be either
vertical or horizontal allowing employess to exchange ideas
each other and it is divided into oral and written
communication skills (Otoo, 2016). The ability to
communicate ideas through verbal and non-verbal is very
essential in business set-ups because the continuity of new
entrants in the current competitive business environment
requires timely skills, which includes communication skills.
Thus, effective business communication skills must be
learned otherwise there should be barriers to accomplish the
set goals or objectives of the business entity. The existence
of any business depends on the positive impact of regular
customers, and to support and reinforce customer
relationship, effective business communication with
customers and other important stakeholders is very essential
for the prosperity of the business (Otoo, 2016). Excellent
communication is required within the entrepreneurship
practices (Penanula & Penanula, 2014).
Musiimenta and Akampurira, (2024) examine the influence
of communication skills on the entrepreneurial performance
of SMEs in Kyengera town council. Their investigation
used cross-sectional survey that targeted all formally
registered small business owners operating in Kyengera
Town Council. Findings of correlation between
communication skills and the performance of SMEs was
(r)= 0.650. Finding implies there was a high positive
relationship among the two variables since the p-value was
0.000 which was less than 0.01 (p < 0.01). This implied that
a positive change in communication skills outcomes in a
corresponding positive change in the performance of SMEs
in Kyengera Town Council. and vice versa. Likewise,
Mutuku, et al., (2022) from Kenya, examine the influence
of entrepreneurial skills on SMEs performance. Their
research used primary data collected from 20 SMEs. This
study used correlational survey design to collect data from
a sample of 20 respondents in order to establish the effect
of entrepreneurial skills on organizational performance.
Findings revealed that entrepreneurial communication skills
positive and statistically significant to influence SMEs
performance. The positive relationship among
entrepreneurial communication skills and performance of
SMEs means that, as entrepreneurial skills increase among
the SMEs in Nakuru city, their performance increases. It can
also be concluded that majority of the firms in Nakuru city
acknowledge the need for entrepreneurial skills in execution
of their daily activities. More so, communication and
entrepreneurial literacy skills are very paramount for good
performance of SMEs.
Moreover, Masecko and Kungu, (2020) from Kenya
investigated the influence of communication on the growth
of SMEs in Wakulima Market. Their study used a
descriptive survey research design and data collected form
576 SMEs. Regression findings show that, communication
had a positive significance influence on the growth of
SMEs. The study concluded that communication that is
transparent, open, effective communication in an
organization will create a sense of openness that builds trust
across employee levels. a group of employees in a room and
creating a plan for how the company interacts with
employees.
2.3 Conceptual Framework
Figure 1 display the conceptual framework that show the
relationship among the independent variables and the
dependent variables. In this study, dependent variables is
business performance which measured by indicators such as
profitability, productivity and innovation while independent
variables of business communication skills measured by
indicator such as collaboration and negotiating. This study
hypothesized that, business communication skills has
positively effect on SMEs business performance as
supported by Musiimenta and Akampurira, (2024);
Masecko and Kungu, (2020) and Mutuku, et al., (2022).

Fig.1: Conceptual Framework
Source: Researcher (2025)
III. METHODOLOGY
The current study examines the effect of business
communication skills on business performance among
SMEs in Tanzania, specifically study conducted at Songea
Municipality in Ruvuma Region. This paper employed
mixed approach (i.e. qualitative and quantitative approach).
In research design, the current study used a cross-sectional
research design where primary data from SMEs collection
at a single point in time at Songea Municipal Council.
Population of this study consisted a total of 4,200 SMEs as
reported by SIDO survey and preliminary reports from
TRA. From population of 4,200 SMEs, study used sample
size of 98 SMEs for quantitative data and a sample size of
10 participants for interview. In sample size selection, this
study used simple random and purposive sampling
technique to select 98 SMEs for quantitative data and 10 for
qualitative data. In data collection, study used
questionnaires and interview for collection of primary data.
Moreover, content analysis used to analyse qualitative data
collected by using interview which conducted with 15
participants while simple linear regression model used in
analysis of quantitative data. This study used simple linear
regression model due to single independent variable of
business communication skills. Thus, regression model
used to examine both magnitude and direction of influence
of business communication skills on business performance
among SMEs in Tanzania as showed in equation 1;
𝑌 = 𝛽0 + 𝛽1𝑖𝑋1 + µ𝑖 …………………………. (1)
Where, Y is dependent variable of business performance;
Β’s coefficient; µ is error term/residual; 𝑋1 is business
communication skills. In addition, this study tested the
several assumptions as recommended by Gauss-Markov
theorem where in statistics states that under certain
assumptions, the ordinary least squares (OLS) estimator for
the coefficients in a linear regression model is the best linear
unbiased estimator (BLUE). Those assumption included
linear in parameters; multicollinearity, heteroscedasticity,
autocorrelation and residual normality.
IV. FINDINGS
4.1 Finding of Descriptive Statistics
This section presents descriptive statistics of business
communication skills on business performance. Descriptive
statistics (mean, standard deviation values) of business
communication skills were computed. Results from Table
4.5 shows that, “I have a good understanding of the
collaborative tools and techniques introduced in the
business communication skills training” scored first with
mean 3.5918 and S.D of 1.4130. In addition, business
communication skills training increase ability to
communicate clearly and concisely in team collaborations
scored second with mean of 3.5714 and S.D of 1.4714.
Also, “there is an increase in the ability to build bond, trust
and long-term relationships in business negotiation” scored
second with mean value of 3.5612 and S.D of 1.4364. The
composite mean is 3.5408 implies that most of participants
agreed side based on each statement. Moreover, the
composite mean of Standard Deviation (SD) is 1.4375
which is below the composite mean and this indicates that
data were closely packed around the mean.

Table 2: Descriptive Statistics of Business Communication Skills
Statement Mean S. D
Business communication skills training enhance ability to employ
persuasive techniques during negotiations
3.4388 1.4292
Business communication skills training increase ability to communicate
clearly and concisely in team collaborations
3.5714 1.4714
There is an increase in the ability to build bond, trust and long-term
relationships in business negotiation
3.5612 1.4364
I have a good understanding of the collaborative tools and techniques
introduced in the business communication skills training
3.5918 1.4130
Composite mean 3.5408 1.4375
4.2 Regression Estimates
This part present finding of regression model that intended
to examine the influence of business communication skills
on business performance. Before presenting the main
results, the study first presents the model assumptions for
instance the normality test, heteroskedasticity,
multicollinearity, and autocorrelation.
4.2.1 Multicollinearity
This subsection presents the results of the Gauss–Markov
theorem assumption of Multicollinearity. Table 2 display
results of a collinearity test of business communication
skills. Collinearity refers to the degree of correlation
between predictor variables in a regression model. Findings
of Tolerance is 1.000, and a value close to 1 means very low
correlation with other predictors. Also, VIF is equal to 1.000
which means no multicollinearity at all. Multicollinearity
becomes a concern when VIF > 5 (moderate) or VIF > 10
(severe). Since there is only one independent variable in this
model, multicollinearity is mathematically impossible, so
VIF is exactly 1.000.
Table 2: Multicollinearity
Variable Tolerance VIF
Business Communication Skills 1.000 1.000
4.2.2 Heteroscedasticity
Heteroscedasticity in a regression analysis refers to a
condition where the variance of the dependent variable
differs across different levels of the independent variables.
This variance inconsistency complicates the analysis as
regression models typically assume equal variance across
all levels of the independent variables, a condition known
as homoscedasticity. Also, heteroscedasticity does not bias
coefficient estimates, it reduces their precision, affecting the
reliability of results. Correcting for heteroscedasticity is
crucial to ensure accurate regression analysis and valid
statistical inferences. In this investigation,
heteroscedasticity was identified using a scatter plot. If the
scatter plot displays a pattern, for instance, a curve, it
designates a violation of the assumptions of
homoscedasticity. Figure 1 shows an asymmetrical
structure, therefore there was no problem of
heteroscedasticity, and the variance of residual is constant
for all observations.
4.2.3 Residuals Normality
Figure 2 show histogram which designates that residuals
grouped around zero and formed a symmetric bell-shaped
curve. So, the residual is normally distributed. Also, Table
3 displays the results of normality tests for both
Kolmogorov-Smirnova and Shapiro-Wilk. Thus,
probability value for the Kolmogorov-Smirnova test is
0.200, and the p-value for the Shapiro-Wilk test is 0.768.
Generally, a probability value of less than 0.05 suggests that
the residual is not normally distributed. However, in this
case, the p-values are greater than 0.05, tell us that we
cannot reject the null hypothesis of normality at the 0.05
level of significance. A higher p-value (greater than the
typical significance level of 0.05) suggests that there is no
significant evidence to reject the null hypothesis that the
residuals follow a normal distribution. Therefore, the study
conclude that the standardized residuals of the regression
model are normally distributed.

Fig.1: Scatter Plot
Fig.1: Histogram
Table 3: Test for Normality
Kolmogorov-Smirnova
Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Unstandardized Residual .069 98 .200*
.997 98 .768
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction

4.2.4 Autocorrelation
Autocorrelation in regression model refers to a situation
where the error terms of a model are correlated with each
other (Akpan & Moffat, 2018). This problem occurs in both
time series and cross-sectional datasets, regularly due to
clustering or grouping within the data. The presence of
autocorrelation misrepresents regression outcomes, leading
to misleadingly significant coefficients, inflated t-statistics,
wrong correlations between variables, and unreliable
standard errors (Gujarati & Porter, 2009). Such distortions
compromise the validity of statistical inferences, making it
essential to detect and address autocorrelation in regression
models.
In this study, the Durbin–Watson (DW) test was employed
to detect the presence of autocorrelation. The DW statistic
ranges from 0 to 4, with values close to 0 indicating positive
autocorrelation, values near 4 suggesting negative
autocorrelation, and values around 2 implying minimal or
no autocorrelation. According to Wooldridge (2010), any
value falling significantly outside the expected range
indicates the presence of autocorrelation. In this study, the
DW statistic was 2.241, which is close to the ideal value of
2. This result, as shown in Table 4 of the model summary,
suggests that the model does not suffer from significant
autocorrelation, thereby supporting the reliability of the
regression estimates.
4.2.5 Model Summary
Table 4 outlines the outcomes obtained through a linear
regression analysis. The R indicates the correlation
coefficient representing the relationship among variables.
Correlation coefficient (R) of 0.733, tell us presence of a
positive and strong correlation between the independent
variables and outcome variable. Likewise, R Square stands
for coefficient of determination, which signifies the
proportion of variance in the outcome variable that can be
explained by the explanatory/independent variables. In this
case, the R Square is 0.538, representing that 53.3% of the
variation in "business performance" is explained by the
explanatory variables Business communication skills.
Table 4: Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson
1 .733a
.538 .533 .69749355 2.241
a. Predictors: (Constant), Business communication skills
b. Dependent Variable: Business Performance
4.2.6 Analysis of Variance (ANOVA)
This subsection presents the results of ANOVA. The
ANOVA table for a regression model with the dependent
variable of business performance and predictors business
communication skills are presented. Finding of F-value of
11.62 with probability value of 0.000 specifies that, overall
model is significant. The predictors (business
communication skills) explain a significant amount of
variance in SMEs' business performance. The low p-value
suggests that at least one of the predictors has a significant
impact on business performance. In conclusion, based on
this ANOVA table, there is strong evidence to suggest that
the business communication skills significantly influence
business performance.
Table 5: ANOVA
Model Sum of Squares df Mean Square F Sig.
1 Regression 54.304 1 54.304 111.621 .000b
Residual 46.704 96 .486
Total 101.007 97
a. Dependent Variable: Business Performance
b. Predictors: (Constant), Business communication skills
4.3 Regression Coefficients
This section presents the key findings of the study, which
aimed to examine the impact of business communication
skills on business performance. The results indicate that
business communication skills are statistically significant at
the 1% level, with a positive coefficient of (β = 0.748). This
suggests that a one-unit improvement in business
communication skills corresponds to a 7.48% increase in
business performance, assuming other factors remain
constant (see Table 6). Overall, the findings conclude that

enhanced business communication skills contribute
positively to the performance of SMEs. This conclusion
consistence with the idea that effective communication
supports SMEs coordinate operations more efficiently,
convey ideas clearly, strengthen relationships with
customers, and foster teamwork among employees. Clear
and timely communication also decreases
misinterpretations, increases decision-making, and
advances customer satisfaction, all of which contribute
directly to business growth. So, the statistical evidence
supports the conclusion that stronger business
communication skills are a important driver of SMEs’
improved performance.
Findings is supported by interview results, as reported by
Owner of a small manufacturing firm and Manager of a
retail SME
"In my small manufacturing business, clear communication
is everything. When I explain production schedules to my
team in simple terms, we avoid costly mistakes and save
time. Just last month, because everyone understood their
roles clearly, we finished an urgent order two days ahead
of schedule—and the client immediately placed a bigger
order." Participant 1
"Good communication keeps our customers coming back.
We make sure to explain product features and after-sales
services in a friendly, transparent way. For instance, when
a client bought our product, we gave clear instructions on
use and maintenance. She later referred three of her friends
to us, which increased our monthly sales." Participant 2
Findings consistence with Musiimenta and Akampurira,
(2024) from Kyengera town council who examined the
influence of communication skills on the entrepreneurial
performance of SMEs in Kyengera town council. Their
results show the presence of high positive relationship
among the communication skills and business performance
since the p-value was 0.000 which was less than 0.01 (p <
0.01). This implied that a positive change in communication
skills outcomes in a corresponding positive change in the
performance of SMEs in Kyengera Town Council. and vice
versa. Similarly, Mutuku, et al., (2022) from Kenya,
revealed that entrepreneurial communication skills positive
and statistically significant to influence SMEs performance.
The positive relationship among entrepreneurial
communication skills and performance of SMEs means
that, as entrepreneurial skills increase among the SMEs in
Nakuru city, their performance increases. Moreover,
Masecko and Kungu, (2020) from Kenya show that,
communication had a positive significance influence on the
growth of SMEs. The study concluded that communication
that is transparent, open, effective communication in an
organization will create a sense of openness that builds trust
across employee levels. a group of employees in a room and
creating a plan for how the company interacts with
employees.
From the viewpoint of the knowledge-based theory
(Penrose, 1959; Barney, 1991), communication is not
merely a transactional tool but a important mechanism for
making, sharing, and applying knowledge within business.
SMEs that develop strong communication skills are better
equipped to transfer tacit and explicit knowledge across
teams, align strategic goals, and respond swiftly to market
demands. This effective knowledge flow transforms
communication into a strategic resource that sustains
competitive advantage. So, the statistical evidence from this
study supports the theoretical premise that knowledge,
when proficiently shared and used through effective
communication serves as a vital driver of improved SME
business performance.
Table 6: Regression Coefficients
Model
Unstandardized Coefficients Standardized Coefficients
t Sig.
B Std. Error Beta
1 (Constant) .043 .070 .606 .546
Business communication
skills
.748 .071 .733 10.565 .000
a. Dependent Variable: Business Performance
V. CONCLUSION
This study concludes that, business communication skills
associated with increased business performance. This
strong and positive relationship suggests that
communication is not just an operational necessity but a
measurable driver of success in SMEs. Theoretically,
results consistence with the knowledge-based theory, which
highlights the role of knowledge creation, sharing, and
application as a source of sustained competitive advantage.
Effective communication facilitates the smooth transfer of
tacit and explicit knowledge within and outside the
organization. In SMEs, this means better coordination of

operations, clearer articulation of ideas, stronger customer
relationships, and more cohesive teamwork. These reduce
misunderstandings, speed up decision-making, and increase
customer satisfaction, all of which contribute directly to
better business performance.
RECOMMENDATIONS
This study suggested that, SME owners needed to invest in
structured communication skills development programs.
This included targeted training in verbal, written, and digital
communication, along with workshops on interpersonal
skills and active listening. SMEs should also establish clear
internal communication channels and protocols to
guarantee the well-organized flow of information across all
levels of the business. Also, fostering a culture that
encourages open dialogue, feedback, and knowledge
sharing can enhance both tacit and explicit knowledge
transfer, in line with the knowledge-based theory.
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