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Yohanes, Farah Margaretha Leon and Yvonne Augustine Sudibyo.
(2021) Analysis of the Influence of Dynamic Capabilities on Company
Performance Mediated by Competitive Advantage. Journal Eduvest.
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Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
p- ISSN 2775-3735 e-ISSN 2775-3727
ANALYSIS OF THE INFLUENCE OF DYNAMIC CAPABILITIES ON
COMPANY PERFORMANCE MEDIATED BY COMPETITIVE
ADVANTAGE
Yohanes, Farah Margaretha Leon and Yvonne Augustine Sudibyo
Doctorate Program in Strategic Management - Faculty of Economics and Business
Universitas Trisakti
E-mail: [email protected], [email protected],
[email protected]
ARTICLE INFO ABSTRACT
Received:
September, 26
th
2021
Revised:
October, 11
st
2021
Approved:
October, 13
rd
2021
This research has a purpose to find out how the influence of
Dynamic Capabilities, either directly or indirectly on Company
Performance through Competitive advantage as a mediating
variable. Design / methodology / approach – data collection
in the form of distributing questionnaires to collect a sample
of 309 manufacturing companies in Indonesia. In any case, to
analyze the data, the analytical method used is the Structural
Equation Model (SEM) to assign the phenomenon and the
tool used is AMOS 22. The result of this research is that
Dynamic Capabilities, affect the upgrade in Competitive
Advantage significantly and positively. Dynamic Capabilities,
affect the positive and significant upgrade in Company
Performance. Competitive Advantage affects the Company's
performance improvement positively and significantly. The
mediating influence of Competitive advantage upgrades the
influence of Dynamic Capabilities, on improving Company
Performance. Practical implications – this research has shown
that Dynamic Capabilities have affected Company
Performance through the practice of Competitive Advantage.
In any case, This research describes that the company's
performance is influenced by different competitive priorities
Yohanes, Farah Margaretha Leon and Yvonne Augustine Sudibyo
Analysis of the Influence of Dynamic Capabilities on Company Performance Mediated
by Competitive Advantage 1008
as well as internal capabilities and external capabilities.
Originality / value - This research analyzes sustainable
innovation predicated on dynamic capabilities in
manufacturing companies in Indonesia, by collecting
managers' perceptions of modification in the external
environment that affect the adaptation and alignment of the
company's maneuver, which has an impact on the applied
business model.
KEYWORDS
Dynamic Capabilities, Competitive Advantage and Company
Performance
This work is licensed under a Creative Commons
Attribution-ShareAlike 4.0 International
INTRODUCTION
Competition in the market generates business cycles that force companies to
reshape business models. There is no definite definition that explains the business model
(Zott, Amit, & Massa, 2011), although Amit & Zott (2012) define a business model as a
system of corporate activities of interdependent and interdependent components that
parallel markets require. Business model innovations are small or large modification
made to the business model by organizations with the goals of surviving in the market
and to gain a competitive advantage. Research by Schneider & Spieth (2013) explains the
sense of challenging old business methods. Business model innovation is a relentless
endeavor for senior leaders, but they can apply business model innovation techniques to
capture the competitive advantage organizations seek.
The application of technology-predicated technology for the manufacturing
sector does not mean that the manufacturing industry sector is free from economic
challenges. The processing industry is currently in the fourth industrial development stage
known as Industry 4.0 after experiencing three waves of industrial development, namely
the first analog processing industry revolution in the 19th century; the second digital
industrial revolution in 1937; and the third Internet-predicated industrial revolution in
1969 (Zhengmao Li, 2018).
The rapid development of technology in the digital era requires companies to
always follow modification dynamically. Companies will strive to implement the
strategies they have set so achieve goals and gain competitive advantage. Competitive
advantage is notable for every company, because it assigns the success or failure of a
business (Sudibyo, 2019). In an effort to generate competitive advantage, companies
need to utilize all of their resources optimally in accordance with their business concept
(Sudibyo, 2019).
Previous research have verified the fine affect among innovation 7and aggressive
gain due to the fact the capacity of such innovation lets in organizations to advantage
flexibility in leveraging vital assets from commercial enterprise companions and running
throughout barriers thereby developing aggressive gain for the company (Liu & Yang,
2019). However, unlike other opinions, there are many differences of opinion on the
various facets of innovation and competitive advantage. Previous researches have
highlighted that innovation can lead to an unbalanced outflow of firm-specific assets,
dependence on external capabilities of network partners and opportunistic behavior in
dealing with appropriate resources to innovate (Yang, Nguyen, & Le, 2018).
Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
1009 http://eduvest.greenvest.co.id
The influence between competitive advantage and dynamic capabilities with
company performance as the guidance of the strategies applied by the company has not
been analyzed and tested empirically predicated on extensive surveys. Previous research
has placed the influence of dynamic capabilities on firm performance (Nakos, Dimitratos,
& Elbanna, 2019). The same research conducted by Peng, Peng, dan Chang (2018) proves
that dynamic capabilities have a positive influence on company performance. Liu, Song,
dan Blake (2018) conducted research of 250 glass production companies in Taiwan and
found that capability partially mediates competitive advantage on company performance.
However, additionally they recommend that agencies ought to position extra attempt in
extra dynamic agencies in growing and preserving their community shape to seize outside
assets as a driving force of business enterprise agility. In contrast, what has been
accomplished formerly argues that aggressive benefit because the quantity to which an
organisation produces, disseminates and responds to the enterprise version that the
business enterprise applies (Kohli, 2017), is considered to be influenced by the
organization's ability to develop business models.
However, this view is different from the research of Braun, Latham, dan
Cannatelli (2019) which states that a business model approach will not help an
organization outperform its competitors. In the same way, maneuver by itself does not
guarantee the continuation and safeguard of long-term customer value. To our
knowledge, this influence has not been studied extensively, and therefore empirical
testing is needed. In any case, the influence of dynamic capabilities on company
performance through competitive advantage has not yet developed. Therefore, further
research on the influence between these variables is needed for manufacturing companies.
The dynamic change in the company's environment demands a critical maneuver
in achieving competitive advantage through continuous innovation, which is becoming
more notable given that modification in Rapid technology encourages companies to
implement strategies more influenceively and faster (Teece, 2018). Therefore, this
research identifies the impact of decisions related to the formation or adoption on
competitive advantage as a research gap to address research gaps that place maneuver as
a rational and/or cognitive decision-making process.
Several previous researches that support this research are the influence of
dynamic capability variables on competitive advantage Fainshmidt, Wenger, Pezeshkan,
& Mallon (2019), the influence of business model variables on competitive advantage
Chen, Wang, dan Qu (2020), the influence of sustainability innovation variables on
competitive advantage Amjad, Fawad, Frederic, Farooq, dan Saddam (2019); Arsawan et
al. (2020); dan Marques, Maffini, Schoproni, Kamila, dan Paula (2019) and the influence
of competitive advantage on firm performance (Efrat, Hughes, Nemkova, Souchon, & Sy-
Changcoe, 2018).
Predicated on the outcame of previous researches that have been described above,
there is still no research that involves the simultaneous influence of Dynamic Capability
on Company Performance and the role of Competitive Advantage as a mediating variable.
In any case, this research will continue the research recommendions of Hermundsdottir &
Aspelund (2020) which states that there are still not many who have researched
competitive advantage through simultaneous development and exploration in the
manufacturing industry on company performance. Therefore, this research will shows the
influence of Dynamic Capabilities on the Performance of Manufacturing Companies
through competitive advantage. Despite the broad research interest in understanding
business models, many interesting questions about business models remain unanswered
(Purkayastha & Sharma, 2016).
Yohanes, Farah Margaretha Leon and Yvonne Augustine Sudibyo
Analysis of the Influence of Dynamic Capabilities on Company Performance Mediated
by Competitive Advantage 1010
Research unearths that the enterprise version is the maximum critical indicator in
reaching aggressive benefit and influences the enterprise's overall performance,
researches at the purpose for enterprise overall performance of the selection of enterprise
version is not often studied (Wahyono, 2018).
The outcame of this research are suppossed to present additional knowledge for
domestic and international companies regarding the impact of Dynamic Capabilities and
Competitive Advantage on Company Performance. Predicated on the literature discussed
above, it is suppossed to present a role for managerial in this research so upgrade
managerial awareness in the development of business model innovation which is an
notable component for sustainability and longevity. Businesses struggle to maintain their
innovative capacity, and their understanding of the driving forces behind innovation can
strengthen competitive advantage. The research of value chain management is still
relatively limited when it comes to empirical research and case researches (Moura &
Salori, 2020), especially on the theme of dynamic capabilities. Therefore, this research
upgrades knowledge in the field of management, internal and external partners as well as
processes and structures of manufacturing companies, for sustainable product
development. This research targets to present leadership insights from the business of
manufacturing companies that apply innovative business models in the face of very
dynamic business competition.
RESEARCH METHOD
This research is research in which the object and scope include competitive
advantage on the performance of manufacturing companies in Indonesia and the variables
that include Dynamic Capabilities. This research was designed using a mix method,
which is a combination of descriptive qualitative and quantitative analysis which includes
data collection to test hypotheses or answer questions about the latest status of research
subjects. Quantitative data was collected through a list of questions in surveys and
interviews. The data will be processed using Structure Equation Model (SEM) analysis
and hypothesis testing with Amos cross sectional data for manufacturing companies. This
type of research is quantitative research that emphasizes distributing questionnaires to
respondents, namely the Board of Directors, Chief Executive Officer, Chief Technology
Officer, Chief Operation Officer, Country Manager, Executive General Manager, General
Manager and Senior Manager of selected companies who are believed to have sufficient
knowledge both about the company's maneuver and company business processes by using
a Likert scale of interval standard (1-6).
RESULT AND DISCUSSION
A. Validity and Reliability Test
1. Validity Test Outcame
Validity test is done by correlating the answer score of each question item with the
number of variable scores. The correlation technique used is the Pearson Product Moment
correlation technique according to the ordinal data measuring scale. Numbers that are
used as a comparison to see whether an item is valid or not.
The outcame of the validity test of the Dynamic Capability (X1) variable can be
known predicated on the following table:
Table 1 Outcame of the Dynamic Capabilities Variable Validity Test (X1)
Variable
Dimention
r count
r Table
Description
Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
1011 http://eduvest.greenvest.co.id
Dynamic
Capabilities
(X1)
Sensing
Capabilities
0.737
0.500
Validation
0.837
0.500
Validation
0.723
0.500
Validation
0.728
0.500
Validation
0.701
0.500
Validation
0.714
0.500
Validation
Learning
Capabilities
0.701
0.500
Validation
0.731
0.500
Validation
0.706
0.500
Validation
0.830
0.500
Validation
Intergrating
Capabilities
0.726
0.500
Validation
0.756
0.500
Validation
0.744
0.500
Validation
0.750
0.500
Validation
0.718
0.500
Validation
0.708
0.500
Validation
Source: Primary Data Processing Outcame, 2021
Because the correlation number obtained from the questions on the Dynamic
Capability Variable (X1) is above 0.5, the questions are decided to be significant and
have good validity.
The outcame of the validity test of the Competitive Advantage variable (Y1) are
known predicated on the following table:
Table 2 Outcame of the Validity Test for Competitive Advantage Variables (Y1)
Variable
Dimention
Indikator
Statement
r count
r Table
Description
Competitive
advantage
(Y1)
Competitive
Maneuver
Y1.1
0.851
0.500
Validation
Y1.2
0.826
0.500
Validation
Y1.3
0.846
0.500
Validation
Y1.4
0.846
0.500
Validation
Y1.5
0.814
0.500
Validation
Y1.6
0.801
0.500
Validation
Yohanes, Farah Margaretha Leon and Yvonne Augustine Sudibyo
Analysis of the Influence of Dynamic Capabilities on Company Performance Mediated
by Competitive Advantage 1012
Y1.7
0.833
0.500
Validation
Source: Primary Data Processing Outcame, 2021
Because the correlation number obtained from the questions on the Competitive
Advantage Variable (Y1) is above 0.5, the questions are decided to be significant and
have good validity. The outcame of the validity test of the Company's Business
Performance variable (Y2) are known predicated on the following table:
Table 3 Validity Test Outcame of Company Business Performance Variables (Y2)
Variable
Dimention
Indikator
Statement
r-
count
r Table
Description
Company
performance
(Y2)
Reduced costs
Y2.1
0.806
0.500
Validation
Y2.2
0.773
0.500
Validation
Y2.3
0.701
0.500
Validation
Non-financial
Assets
Y2.4
0.811
0.500
Validation
Y2.5
0.859
0.500
Validation
Y2.6
0.796
0.500
Validation
Y2.7
0.700
0.500
Validation
Source: Primary Data Processing Outcame, 2021
Due to the correlation number obtained from the questions on the Company's
Business Performance Variable (Y2) which is above the number 0.5, the questions are
decided to be significant and have good validity.
2. Reliability Test
Reliability test is used to see the stability or consistency of the standard outcame. A
measuring instrument is said to be reliable if it is used repeatedly on one object to
produce the same outcame. The reliability technique used is the reliability of the
consistency between the authors' items using the Cronbach Alpha test. The following are
the outcame of the research instrument reliability test on the research variables.
Table 4 Reliability Test Outcame of Research Variables
No.
Variable
Cronbach Alpha value
Description
1
Dynamic Capability (X1)
0.943
Reliable
2
Competitive Advantage (Y1)
0.924
Reliable
3
Company Performance (Y2)
0.891
Reliable
Source: Primary Data Processing Outcame, 2021
Predicated on the calculation of the reliability test that the researchers did. It was
found that all research variables had a Cronbach alpha reliability coefficient value above
0.5. This means that the instrument has reliable outcame, so this instrument or
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questionnaire is a reliable and consistent instrument so that it can be used for further
analysis.
3. Structural Equation Modeling (SEM) Test
a. Standard Model Test (Standard Model)
The stage in the SEM analysis technique is the standard model stage. The standard
model is used to measure the dimensions that make up a factor. The estimation technique
used in the SEM calculation is by using the maximum likelihood. However, before
forming a full SEM model, it will first be tested on the factors that make up each variable.
The test will be carried out by looking at the outcame of the standardized regression
weight in the Amos v.23.0 output table. If there is an estimate or loading factor value
from indicators that have a value of less than 0.5, then the indicator cannot describe the
construct and cannot be included in the next calculation.
1) Exogenous Construct Standard Model
The standard model test outcame for exogenous constructs can be seen through the
loading factor coefficient values of each indicator which are presented in the following
table.
Table 5 Exogenous Construct Standard Model
Latent
Variable
Manifest
variable
λ
λ
2
E
CR
VE
Dynamic
Capabilities
X1.1
0.939
0.882
0.118
0.948
0.858
X1.2
0.914
0.835
0.165
X1.3
0.925
0.856
0.144
Note: λ= loading factor value, e=error, CR=composite reliability, VE=variance
extracted
Source: Primary Data Processing Outcame, 2021
The table above recommends that the loading factor (λ) cost for every occur
variable is more than 0.five. This way that everyoccur variable is said legitimate in
forming an endogenous assemble. Then the CR (assemble reliability) cost have to be
above 0.7 and the VE (variance extracted) have to be above 0.five has been fulfilled in
order that it is able to be concluded that the endogenous assemble has excellent assemble
validity and reliability.
Figure 1 Exogenous Construct Standard Model
1) Endogenous Construct Standard Model
The size version take a look at influences for endogenous constructs may be visible
thru the loading aspect coefficient values of every indicator which might be presentd 6in
the subsequent table:
Yohanes, Farah Margaretha Leon and Yvonne Augustine Sudibyo
Analysis of the Influence of Dynamic Capabilities on Company Performance Mediated
by Competitive Advantage 1014
Table 6 Endogenous Construct Standard Model
Latent Variable
Manifest
variable
λ
λ
2
E
CR
VE
Competitive
advantage
Y1.1
0.816
0.666
0.334
0.852
0.658
Y1.2
0.794
0.630
0.370
Y1.3
0.823
0.677
0.323
Y1.4
0.821
0.674
0.326
Y1.5
0.781
0.610
0.390
Y1.6
0.759
0.576
0.424
Y1.7
0.802
0.643
0.357
Note: =load factor value, e=error, CR=composite reliability, VE=variance
extracted
Source: Primary Data Processing Outcame, 2021
The table above shows that the loading factor (λ) value for each manifest variable
is greater than 0.5. This means that each manifest variable is declared valid in forming an
endogenous construct. Then the CR (construct reliability) value must be above 0.7 and
the VE (variance extracted) must be above 0.5 has been fulfilled so that it can be
concluded that the endogenous construct has good construct validity and reliability.
Figure 2 Endogenous Construct Standard Model
b. Structural Model
As previously explained, this research applies Structural Equation Modeling (SEM)
analysis as an effort to test the hypothesis. The theoretical version on this examine has
been defined in a framework in which the researches version goals to look at the have an
impact on among the hypothesized variables.
In the SEM analysis, there are techniques of the use of the enter information
matrix, specifically the variance/covariance matrix and the correlation matrix. This
analysis will use the covariance matrix input for further estimation. The preference of
enter with a covariance matrix is due to the fact the covariance matrix has the gain of
supplying legitimate comparisons among unique populations or samples, that is every
now and then now no longer viable while the usage of a correlation matrix model.
1) Model Feasibility Test (Goodness of Fit Model)
Goodness of fit criteria from the structural equation model above are presented in
the following table:
Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
1015 http://eduvest.greenvest.co.id
Table 7 Goodness of Fit Testing Research Model
GOF
Acceptable Match Level
Model
Index
Explanation
Chi-square
chi-square ≤2df (good fit), 2df < chi-square ≤3df (marginal fit)
1.578
Good Fit
P-value
P ≥ 0.05
0.000
Good Less
GFI
GFI ≥ 0.9 (good fit), 0.8 ≤ GFI ≤ 0.9 (marginal fit)
0.932
Good Fit
RMR
RMR ≤ 0.05
0.016
Good Fit
RMSEA
0.05 < RMSEA ≤ 0.08 (good fit), 0.08 < RMSEA ≤1 (marginal fit)
0.043
Good Fit
TLI
TLI ≥ 0.9 (good fit), 0.8 ≤ TLI≤0.9 (marginal fit)
0.988
Good Fit
NFI
NFI ≥ 0.9 (good fit), 0.8 ≤ NFI ≤ 0.9 (marginal fit)
0.967
Good Fit
AGFI
AGF I≥ 0.9 (good fit), 0.8 ≤ AGFI ≤ 0.9 (marginal fit)
0.907
Good Fit
RFI
RFI ≥ 0.9 (good fit), 0.8 ≥ RFI ≤ 0.9 (marginal fit)
0.960
Good Fit
CFI
CFI ≥ 0.9 (good fit), 0.8 ≤ CFI ≤0.9 (marginal fit)
0.987
Good Fit
Source: Wijanto, 2007
The goodness of fit model recapitulation table shows that in general the goodness
of fit model is good fit, although there is still 1 indicator that has GOF with bad fit
criteria. This is because the indicator is very sensitive to the large number of research
samples.
1) Hypothesis Testing
The next goal in structural model analysis is to estimate the influence parameters
between variables, which will also prove the research hypothesis. The following is a
recapitulation of the parameter estimation outcame from the SEM analysis that has been
carried out as presented in the following table:
Table 8 SEM Test Recapitulation
Variable
Estimate
SE
T-stat
t-table
p-value
Description
KD
→
KK
0.475
0.046
9.137
1.96
***
Significant
KD
→
KBP
0.293
0.047
4.968
1.96
***
Significant
KK
→
KBP
0.298
0.073
3.712
1.96
***
Significant
Source: Output Amos v.23.0, 2021
Note:
KD = Dynamic Capability
KK = Competitive Advantage
KBP = Company Performance
Predicated on the coefficient values in the table above, the outcame of hypothesis
testing can be explained as follows:
1. Dynamic Capabilities affect Competitive Advantage
The tested hypotheses are:
H0: Dynamic Capabilities have no influence on Competitive Advantage
H1: Dynamic Capabilities have an influence on Competitive Advantage
The significant test outcame for hypothesis 1 prove that there is a positive
influence of Dynamic Capability on Competitive Advantage as indicated by p value =
*** or < 0.05, then H0 is rejected. This means that the Dynamic Capability variable has a
positive and significant influence on Competitive Advantage, so hypothesis 1 is accepted.
2. Competitive Advantage affects Company Performance
The tested hypotheses are:
H0: Competitive Advantage has no influence on Company Performance
H1: Competitive Advantage has an influence on Company Performance
The outcame of the significant test on hypothesis 2 prove that there is a positive
influence of Competitive Advantage on Company Performance as indicated by p value =
Yohanes, Farah Margaretha Leon and Yvonne Augustine Sudibyo
Analysis of the Influence of Dynamic Capabilities on Company Performance Mediated
by Competitive Advantage 1016
*** or < 0.05, then H0 is rejected. This means that the Competitive Advantage variable
has a positive and significant influence on the Company's Performance, so hypothesis 4 is
accepted.
3. Dynamic Capabilities affect the Company's Performance
The tested hypotheses are:
H0: Dynamic Capabilities have no influence on Company Performance
H1: Dynamic Capabilities have an influence on Company Performance
The outcame of the significant test on hypothesis 3 prove that there is a positive
influence of Dynamic Capability on Company Performance as indicated by p value = ***
or < 0.05, then H0 is rejected. This means that the Dynamic Capability variable has a
positive and significant influence on the Company's performance, so hypothesis 3 is
accepted.
B. Discussion of Research Outcame
The findings of statistical analysis were carried out in the form of descriptive
analysis and differential analysis through the Structural Equation Modeling approach.
This have a look at goals to research the function of the have an influence on of
Competitive Advantage in enhancing Company Performance. The function of the have an
influence on of Competitive Advantage in moderating among Dynamic Capabilities, with
Company Performance is the principal goal of the dialogue of this research.
Inferential analysis was carried out predicated on the outcame of statistical
significance test processing using the CR value that connected the latent variables to one
another. The influence between latent variables is considered significant if the calculated
p value > the absolute value of 0.05 (with = 5%).
1. Influence of Dynamic Capability with Competitive Advantage (Hypothesis
Accepted)
The significant test outcame for hypothesis 1 prove that there is a positive
influence of Dynamic Capability on Competitive Advantage as indicated by p value =
*** or < 0.05. The outcame of this research support the outcame of the research of
Martelo et al. (2013) show that added value for customers depends on the company's
resources and capabilities. According to Jeng and Pak (2014), competitive advantage will
motivate companies to use existing resources more efficiently and create or acquire new
resources.
Huang et al. (2012), dynamic capabilities will enable companies to create new
products and processes that enable companies to respond to changing market conditions.
Hsu and Wang (2012) argue that dynamic capabilities can upgrade competitive advantage
in a rapidly changing environment through optimal use of resources.
According to research Li and Liu (2014) have identified the same key role for
dynamic capabilities in maintaining competitive advantage. This research shows that the
dynamic capability context influences the differentiation guidance of firms by stimulating
experimentation and the development of unique resources in creating competitive
advantage (Nandakumar et al., 2010). Regardless of competitors' access to the same
external resources, dynamic capabilities present the basis for a continuous search for
uniqueness that builds differentiation and deters further imitation. On the other hand,
companies can achieve a low-cost guidance through dynamic capabilities, which build
greater efficiency and adaptability to a changing environment (Fainshmidt et al., 2019).
Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
1017 http://eduvest.greenvest.co.id
2. Influence of Dynamic Capability with Company Performance (Hypothesis
Accepted)
The outcame of the significant test on hypothesis 3 prove that there is a positive
influence of Dynamic Capability on Company Performance as indicated by p value = ***
or < 0.05. The outcame of this research support the outcame of research by Brettel et al.
(2012) pointed out the need to clarify some issues related to business models and their
relation to firm performance so build a strong and reliable theory about the relationship
between these constructs. Considering this research for further investigation, while it is
clear that there is a large body of literature clgoalsing that business models can be a
source of competitive advantage (Markides & Charitou, 2004) and therefore influence
firm performance (Aspara et al., 2010), firms recognize that the significant contribution
Incorporating business model investigations as a basis for classifying firms and how this
affects firm performance, or, in other words, the influence of different types of Business
Models on firm performance, is minimal (Zott & Amit, 2008). There is evidence, to the
contrary, as recommended by Brettel et al. (2012), that company performance is related to
the share of value taken by companies that have adopted certain business models. Such
themes then need to be investigated in an effort to donate to the current theoretical debate
about business models and their relation to firm performance, as well as to present
entrepreneurs with valuable recommendations to improve the competitiveness of their
firms.
3. Influence of Competitive Advantage on Company Performance (Hypothesis
Accepted)
The outcame of the significant test on hypothesis 2 prove that there is a positive
influence of Competitive Advantage on Company Performance as indicated by p value =
*** or < 0.05. The outcame of this research support the research outcame of
Ghasemzadeh, Nazari, Mandana, & Gholamhossein (2019) recommending that
companies need to establish a value system together, including activities that stimulate
open communication, new opinions and ideas to achieve sustainable innovation.
Furthermore, internal innovation instruction helps organizational members to send a
message to company employees that their new ideas are appreciated. When a culture of
innovation permeates, employees are free to express their ideas and try new methods to
donate to organizational performance.
This is understanding with the outcame of research by Tadros and Magnan (2019)
which revealed that companies that care about the environment will be more accepted by
the community. That is, the company will enjoy long-term viability and profitability if it
is supported by innovation. Innovation as a tool to improve performance by carrying out a
continuous innovation process that can improve characteristic and save costs in business.
As a result of implementing innovation in the production process, the organization will be
in a good condition to improve its functions and procedures (Hashi & Stojčić, 2013).
CONCLUSION
From the outcame of this research, in general, Dynamic Capabilities have an
influence in improving Company Performance with the existence of Excellence and with
eight accepted hypotheses. Competitive Advantage plays a very notable role as a
mediation in increasing the influence of Dynamic Capabilities, on Company
Performance. There is a positive and significant influence of Dynamic Capability on
Competitive Advantage. The dimension of Dynamic Capability with the most dominant
influence is on the dimension of environmental observation. This shows that improving
Yohanes, Farah Margaretha Leon and Yvonne Augustine Sudibyo
Analysis of the Influence of Dynamic Capabilities on Company Performance Mediated
by Competitive Advantage 1018
the characteristic of Dynamic Capability, especially in the environmental observation
dimension, will result in an upgrade in Competitive Advantage.
There is a positive and significant influence of Dynamic Capability on Company
Performance. The size of Dynamic Capability with the maximum dominant has an
influence on is at the size of environmental commentary. This shows that enhancing the
best of Dynamic Capabilities, particularly withinside the environmental commentary size,
will bring about growing the Company's Performance. There is a tremendous and
substantial impact of Competitive Advantage on Company Performance. The size of
Competitive Advantage with the maximum dominant has an influence on is at the size of
operational efficiency. This indicates that enhancing the best of Competitive Advantage,
particularly withinside the dimensions of operational efficiency, will bring about growing
the Company's Performance.
REFERENCES
Amit, Raphael, & Zott, Christoph. (2012). Creating value through business model
innovation. MIT Slogan Management Review, 53, 41–49.
Amjad, Iqbal, Fawad, Latif, Frederic, Marimon, Farooq, Sahibzada Umar, & Saddam,
Hussain. (2019). From Knowledge Management to Organizational Performance:
Modelling the Mediating Role of Innovation and Intellectual Capital in Higher
Education. Journal of Enterprise Information Management, 32(1), 36–59.
https://doi.org/10.1108/JEIM-04-2018-0083
Arsawan, I.Wayan Edi, Koval, Viktor, Rajiani, Ismi, Rustiarini, Ni Wayan, Supartha,
Wayan Gede, & Suryantini, Ni Putu Santi. (2020). Leveraging Knowledge Sharing
and Innovation Culture into SMEs Sustainable Competitive Advantage.
International Journal of Productivity and Performance Management.
Banker, Rajiv, Mashruwala, Raj, & Tripathy, Arindam. (2014). Does a Differentiation
Strategy Lead to More Sustainable Financial Performance than a Cost Leadership
Strategy? Management Decision, 52, 872–896. https://doi.org/10.1108/MD-05-
2013-0282
Braun, Michael, Latham, Scott, & Cannatelli, Benedetto. (2019). Strategy and Business
Models: Why Winning Companies Need Both. Journal of Business Strategy, 40(5).
Chen, Jin, Wang, Luyao, & Qu, Guannan. (2020). Explicating The Business Model From
A Knowledge-Based View: Nature, Structure, Imitability And Competitive
Advantage Erosion. Journal of Knowledge Management, 25(1).
Efrat, Kalanit, Hughes, Paul, Nemkova, Ekaterina, Souchon, Anne L., & Sy-Changcoe,
Joseph. (2018). Leveraging of Dynamic Export Capabilities for Competitive
Advantage and Performance Consequences: Evidence From China. Journal of
Business Research, 84, 114–124.
Fainshmidt, Stav, Wenger, Lucas, Pezeshkan, Amir, & Mallon, Mark. (2019). When do
Dynamic Capabilities Lead to Competitive Advantage? The Importance of Strategic
Fit. Journal of Management Studies, 55, 758–787.
https://doi.org/10.1111/joms.12415
Harrison, Jeffrey S., Bosse, Douglas A., & Phillips, Robert A. (2010). Managing for
Stakeholders, Stakeholder Utility Functions, and Competitive Advantage. Strategic
Management Journal, 31(1), 58–74.
Hashi, Iraj, & Stojčić, Nebojša. (2013). The Impact of Innovation Activities on Firm
Performance Using a Multistage Model: Evidence From The Community
Innovation Survey 4. Research Policy, 42(2), 353–366.
https://doi.org/https://doi.org/10.1016/j.respol.2012.09.011
Hermundsdottir, Fanny, & Aspelund, Arild. (2020). Sustainability innovations and firm
Eduvest – Journal of Universal Studies
Volume 1 Number 10, October 2021
1019 http://eduvest.greenvest.co.id
competitiveness: A review. Journal of Cleaner Production, 124715.
Hoskisson, Robert E., Wright, Mike, Filatotchev, Igor, & Peng, Mike W. (2012).
Emerging Multinationals from Mid‐Range Economies: The Influence of Institutions
and Factor Markets. Journal of Management Studies, 50(7), 1295–1321.
Jeng, Don Jyh Fu, & Pak, Artur. (2014). The Variable Effects of Dynamic Capability by
Firm Size: The Interaction of Innovation and Marketing Capabilities in Competitive
Industries. International Entrepreneurship and Management Journal, 12(1).
https://doi.org/10.1007/s11365-014-0330-7
Kohli, Ajay K. (2017). Market Orientation in a Digital World. Global Business Review,
18(3), 1–3.
Li, Da yuan, & Liu, Juan. (2014). Dynamic Capabilities, Environmental Dynamism, and
Competitive Advantage: Evidence from China. Journal of Business Research, 67(1),
2793–2799. https://doi.org/https://doi.org/10.1016/j.jbusres.2012.08.007
Li, Zhengmao. (2018). Telecommunication 4.0: Reinvention of the Communication
Network. Singapore: Springer.
Liu, Anyu, Song, Haiyan, & Blake, Adam. (2018). Modelling Productivity Shocks And
Economic Growth Using The Bayesian Dynamic Stochastic General Equilibrium
Approach. International Journal of Contemporary Hospitality Management, 30(11).
Liu, Hsian Ming, & Yang, Hsin Feng. (2019). Network Resources Meet Organizational
Agility: Creating an Idiosyncratic Competitive Advantage for Smes. Management
Decision, 58. https://doi.org/10.1108/MD-10-2017-1061
Marques, Kneipp Jordana, Maffini, Gomes Clandia, Schoproni, Bichueti Roberto,
Kamila, Frizzo, & Paula, Perlin Ana. (2019). Sustainable Innovation practices and
Their Relationship With The Performance of Industrial Companies. Revista de
Gestão, 26(2), 94–111. https://doi.org/10.1108/REGE-01-2018-0005
McGrath, Rita Gunther. (2013). Transient Advantage. Harvard Business Review, 91(6),
62–70.
Nakos, George, Dimitratos, Pavlos, & Elbanna, Said. (2019). The Mediating Role of
Alliances in The International Market Orientation–Performance Relationship Of
SMEs. International Business Review, 28(3), 603–612.
https://doi.org/https://doi.org/10.1016/j.ibusrev.2018.12.005
Peng, Michael Yao Ping, Peng, Yen Chun, & Chang, Chen Chieh. (2018). The Effect of
Organizational Strategy Orientation on Network Relationships. Proceedings of the
2018 International Conference on E-Business and Mobile Commerce, 30–33.
https://doi.org/https://doi.org/10.1145/3230467.3230473
Purkayastha, Anish, & Sharma, Sunil. (2016). Gaining Competitive Advantage Through
The Right Business Model: Analysis Based on Case Studies. Journal of Strategy
and Management, 9(2).
Schneider, Sabrina, & Spieth, Patrick. (2013). Business Model Innovation: Towards An
Integrated Future Research Agenda. International Journal of Innovation
Management, 17(1), 671–696. https://doi.org/10.1142/S136391961340001X
Sudibyo, Yvonne Augustine. (2019). The Adoption of Environmental Consciousness and
Environmental Leadership as driver of Competitive Advantage. OIDA International
Journal of Sustainable Development, 12(9), 25–34.
Teece, David J. (2018). Business Models and Dynamic Capabilities. Long Range
Planning, 51(1), 40–49. https://doi.org/https://doi.org/10.1016/j.lrp.2017.06.007
Wahyono. (2018). Business Model Innovation: A Review And Research Agenda. Journal
of Indian Business Research, 11(4). https://doi.org/10.1108/JIBR-12-2017-0251
Yohanes, Farah Margaretha Leon and Yvonne Augustine Sudibyo
Analysis of the Influence of Dynamic Capabilities on Company Performance Mediated
by Competitive Advantage 1020
Yang, Zhi, Nguyen, Van Thithuy, & Le, Phong Ba. (2018). Knowledge Sharing Serves as
a Mediator Between Collaborative Culture and Innovation Capability: an Empirical
Research. Journal of Business & Industrial Marketing, 33(7).
Zhou, Steven S., Zhou, Abby J., Feng, Junzheng, & Jiang, Shisong. (2019). Dynamic
Capabilities and Organizational Performance: The Mediating Role of Innovation.
Journal of Management & Organization, 25(5), 731–747. https://doi.org/DOI:
10.1017/jmo.2017.20
Zott, Christoph, Amit, Raphael, & Massa, Lorenzo. (2011). The business model: recent
developments and future research. Journal of Management, 37(4), 1019–1042.
https://doi.org/10.1177/0149206311406265