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1
TEM-21-1233.R3
The Impact of Technology and Change Management
on Value Proposition Innovation: An Iranian Study
Reihaneh Hajishirzi, Carlos J. Costa, and Manuela Aparicio
Abstract— Digital transformation is inevitable in today’s
business world. Applying digital technologies in business
processes creates innovative value propositions but causes
substantial changes to the organization. The main objective of
our research is to understand how technology and change
management affect value proposition innovation of organizations.
This study introduced a model that explains value proposition
innovation in Iranian companies considering three essential
factors of technology, change management, and environment
(industry pressure and government regulation). We evaluated
our model based on the data gathered by 220 organizational
leaders from different Iranian organizations, and statistically
validated our model. The results showed that technology and
change management significantly impact value proposition
innovation. Additionally, environment has a substantial effect on
change management and technology.
Index Terms—Change Management, Digital Transformation,
Environmental Pressure, Technology Adoption, Value
Proposition Innovation
I. INTRODUCTION
IGITAL transformation applies digital technologies in
every aspect of organizational processes to change
business models [1], [2] and value proposition [3]–[5]
– which is about creating and delivering value to customers
[6]. For example, using new technologies in the aviation
industry directly impacts on value proposition [7]; Blockchain
technology disrupts supply chain finance to solve the fraud
and non-trust issues in this market [8]; The Uber company as a
mobility service provider creates an innovative value
proposition by digital delivery [9]. However, technology is not
the only factor affecting the value proposition. Digital
technologies cause fundamental changes in culture, markets,
industries, and processes [10], [11]. Therefore, the leaders
“This work was supported in ADVANCE-CSG from the Fundação para
a Ciência and Tecnologia (FCT Portugal) through research grant number
UIDB/04521/2020, and we gratefully acknowledge the financial support from
FCT—Fundação para a Ciencia e Tecnologia, I.P. (Portugal), and national
funding through research grant UIDB/04152/2020—Centro de Investigação
em Gestão de Informação (MagIC).” (Corresponding author: Reihaneh
Hajishirzi).
R. Hajishirzi and C. J. Costa are with the Advance/ISEG (Lisbon School of
Economics & Management), Universidade de Lisboa, 1200-109 Lisbon,
Portugal. (e-mail: reihaneh.hajishirzi@aln.iseg.ulisboa.pt;
cjcosta@iseg.ulisboa.pt)
M. Aparicio is with NOVA Information Management School (NOVA
IMS), Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal (email:
mcosta@novaims.unl.pt)
have an essential role [12] to adapt the company to changes.
They should facilitate change management processes in
companies and remove obstacles [13] which needs clear
communication with employees [14]. However, to enhance
business values, changes in strategy and structure must be
controlled [15]. Importantly, all these are affected by the
environmental factors [16]–[19] including political, social,
industrial, and governmental pressures [20]. Environmental
regulation influences technology [21], green innovation [22]
and reliable infrastructure [23]. Furthermore, environmental
pressure has impact on management decisions on budgets,
costs, investments, and technologies [24].
In this study, we identify essential factors – including
technology, change management, and environment – that
affect value proposition innovation. Previous studies [1], [4],
[5], [7] have shown the correlations between some of these
factors (Table1), but a comprehensive study on how all these
factors are jointly correlated is required. This research focuses
on the Iranian market, which is located in a strategic
geographic location, but digital transformation is not mature
enough [25], and have not been studied much in the previous
literature [26].
We propose a new theoretical model, and we conduct an
empirical study at the organizational level and analyze the
collected data from 220 actual organizations to validate this
model. Accordingly, our research question is “what are the
determinants of value proposition innovation in Iranian
companies?” Our specific objectives are to understand:
1. What is the impact of technological dimension and
change management on value proposition innovation?
2. What is the impact of environmental dimension on
technological dimension and change management?
We empirically validate our model through a quantitative
Partial Least Squares/Structural Equation Modelling
(PLS/SEM) technique. Our findings reveal that environmental
dimension affects technological dimension and the change
management process in the organization. Moreover,
technological dimension and change management impact
value proposition innovation.
This study makes three main contributions: 1) It proposes a
theoretical model for digital transformation, change
management, environmental factor, and value proposition
innovation and validates the model by conducting an empirical
study; 2) It contributes to the existing literature on showing
D
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TEM-21-1233.R3
the impact of technology and change management on bringing
innovative values for the customers; 3) It enriches the scholars
on showing the impact of environment on change management
and the process of enabling technology in organizations.
This paper is organized as follows. The literature review is
presented in section 2. The conceptual model and hypotheses
are proposed in section 3, followed by how the empirical study
was conducted in section 4. Section 5 outlines the results and
discussion. Finally, the conclusion is provided in the last
section (6).
II. THE CURRENT STATE OF ART
2.1. Value proposition
The value proposition is expressed in a company’s business
model and is about creating and delivering value to customers
[6]. Traditional companies rarely change their value
proposition even if their products get updated [27]. According
to the theory of disruptive innovation [28], the new players in
the market disrupt the traditional companies by offering
convenience, accessibility, and cost-efficient products or
services. Therefore, successful companies need to create value
for their customers and differentiate their core competencies
by applying innovation opportunities [29]. Successful
companies use the business model canvas to clarify their value
proposition, key resources, activities, partners, customer
relationships, segments and channels, cost structures, and
revenue streams [30]. The companies should contribute
technology to their business models and improve the impact of
value proposition innovation on their performance [31], [32].
Furthermore, increasing product life cycle and changing
market demands affect value proposition innovation [7].
Moreover, companies gain distinct value propositions by
providing business transactions with external stakeholders,
and by strengthening the company to scale [5].
2.2. Change management
New technologies in organizations extend to structural
changes in products, services, processes, skills, and value
creation [33]. The successful implementation of digital
transformation in firms needs change management and focus
on individuals [15], [34], [35]. Hence, we summarize change
management theories to understand this concept better.
McKinsey's 7-S Framework analyzes companies' strategy,
structure, systems, shared values, styles, staff, and skills [36].
Kotter's theory emphasizes the role of leadership in change
management by combining the situation with a sense of
urgency, putting together a core alliance, defining a strategic
plan, getting everyone on the same page, removing
roadblocks, creating short-term victories, keeping the
momentum going and making permanent modifications [37].
Finally, a prior study shows a framework with essential factors
influencing successful change management, like the
importance of decisive leadership or resistance to change [38].
2.3. Theoretical background of technology adoption
Adopting new technologies has been extensively studied and
all are based on the Theory of Reasoned Action (TRA). This
theory is about the attitudes of individuals in a specific
situation [39]. For example, in technology acceptance, what
are employees' perceptions and attitudes [40]? Davis [41]
proposes a model based on the TRA and theoretically explains
why users might choose one type of technology. In this model,
a person's perceptions about the usefulness and ease of using
technologies are two essential factors in technology
acceptance [42], [43].
Technology, Organization, and Environment (TOE)
Framework extends TRA and represents three main aspects
that affect the technology acceptance process in firms [44]:
1)The technological dimension refers to all the technologies
used in a firm or those still not used [45]; 2)The organizational
dimension includes firm size, personnel attitudes toward
change, management support, and change management
processes in the organizations [46]; 3)The environmental
dimension covers the industry, partners, competitors,
regulations, and laws [17]. Our theoretical model in this work
uses some of the parameters in the TOE framework.
2.4. Importance and benefits of applying digital
transformation
The companies that use digital technologies to create
innovative business models gain more profits and bolster
margins. They should change the entire value chain from
suppliers, producers, and distributors [47]. Digital
transformation affects company performance, culture, sales,
and marketing processes [48]. Digital transformation changes
customer behavior and improves the customer experience.
Mobile applications, machine learning, automation, and many
other technologies allow customers to get what they need at
precisely the right time [49], [50]. In addition, Digital
transformation also increases employee experience and helps
the HR processes like compensation, performance
management, and job improvements [51].
Table 1 categorizes previous studies about digital
transformation mainly focusing on value proposition,
technological dimension, change management, and
environmental dimension.
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TEM-21-1233.R3
TABLE 1
PREVIOUS STUDIES ABOUT DIGITAL TRANSFORMATION FROM THE PERSPECTIVE OF VALUE PROPOSITION, TECHNOLOGY, CHANGE
MANAGEMENT, AND ENVIRONMENT
III. RESEARCH MODEL
In this study, we determined the factors that influence the
digital transformation process in Iranian companies and built a
theoretical model that study the relationships between these
factors. This section details the constructs, hypotheses, and
theoretical model.
Digital transformation is a process where digital technologies
disrupt companies. This makes company leaders implement
strategies to apply new technologies and manage changes in
business processes [61]. Successful implementation of digital
transformation and change management leads to innovation in
value proposition [27] and value networks. We integrated this
process with the TOE framework to propose our research model.
We selected the constructs related to technology and environment
from the TOE framework. In addition, we selected top
management support and change management from the
organizational dimension of the TOE framework. Finally, we
selected value proposition innovation as a result of applying
digital technologies in organizations from the digital
transformation process [61]. Our model constructs are:
Environmental Dimension, Industry Pressure [57], Government
Regulation [57], Technological Dimension, Technology Enabled
Assets [62], Compatibility [16], Complexity [16], Value
Proposition Innovation, New Offerings [63], New Channels [63],
New Customers [63], Change Management [15], and Top
Management Support [16]. Table 2 shows the definition of the
constructs.
Study
Description
Methodology
Studied variables
Value
proposition
Technology
Change
management
Environment
[33]
In this study, the authors present a framework for digital transformation with four dimensions:
the use of technologies, changes in value creation, structural changes, and financial aspects.
Literature Analysis, Case Study
*
*
*
[15]
This study investigates the relation of change management, digitalization, business performance,
and green development in Strategic Action Field Theory.
Survey, PLS/SEM
*
*
*
[7]
In this research, the drivers of business model innovation in the aviation industry are studied.
Qualitative, Inductive Theory
Building, Case Study
*
*
*
[4]
The authors propose a framework that analyze technological innovation and customer value
proposition.
Literature Review
*
*
[5]
The authors provide a definition of value proposition and identify features that make value
proposition unique.
Literature Review
*
*
*
[52]
They use the TOE framework to analyze the digital transformation adoption process in South
African retail organizations.
Case study
*
*
*
[53]
This research investigates 12 drivers of digital transformation in manufacturing.
Interviews, Qualitative
*
*
[54]
This study aims to understand how big organizations lead digital transformation process. In this
regard, some drivers of digital transformation in Sweden companies are investigated.
Qualitative, Inductive Approach,
Case Study
*
*
[55]
They propose the e-business adoption model based on diffusion of innovation theory and the
TOE framework.
Survey data from SIBIS, Interviews,
Quantitative
*
*
*
[56]
This study represents the elements that affect the process of e-business adoption in European
companies. They used the TOE framework and Iacouvo model of technology acceptance.
Survey, Factorial Analysis, Logistic
Regression
*
*
*
[57]
This study uses a research model based on the TOE framework and Diffusion of Innovation (DOI)
theory to investigate the adoption of e-business in ERP-enabled and non-enabled companies.
Survey, Factorial Analysis, Logistic
Regression
*
*
*
[58]
They study digital transformation adoption process in four large North American banks in 5 years.
Qualitative and Quantitative,
Visual Analytics
*
*
*
[16]
This paper studies the elements that influence leaders' decision to adopt cloud computing in the
UK using the TOE framework.
Survey, Principal Component
Analysis, Logistic Regression
*
*
*
[59]
This study integrates the TOE framework and DOI theory to find the adoption factors for mobile
applications.
Survey, Structural Equation
Modeling
*
*
*
[60]
This study proposes a model based on the TOE framework, DOI theory, and Iacouvo model to
explain e-business use among U.S. firms.
Survey, Factorial Analysis, Logistic
Regression
*
*
*
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TEM-21-1233.R3
TABLE 2
CONSTRUCT DEFINITIONS
Construct
Definition
Reference
Environmental Dimension
Industry Pressure
Deals with the competitors and partner pressures to increase
competitive advantages
[18]
Government Regulation
Corresponds to government strategies and pressures to force
and encourage companies to adopt digital transformation.
Technology Dimension
Technology Enabled Assets
Refers to cutting-edge technologies like social, mobile, analytics,
cloud computing and IoT (SMACIT) and AI, blockchain, VR, AR, 3-
D printing, etc.
[3]
Compatibility
It is the degree to which digital innovations fit with the current
business processes and organization values.
[64]
Complexity
Refers to the difficulty level of using digital technologies.
Value Proposition Innovation
New Offerings
Presents how companies offer new solutions to meet their
customers' needs.
[65]
New Channels
Deals with the new ways of delivering value to the customers.
[66]
New Customers
Corresponds to new customer groups or market segments to
whom the organization will offer the products/services.
[67]
Change Management
It is about serving the customers' needs by renewing organizational structures, capabilities, and direction.
[68]
Top Management Support
Deals with the role of leaders in affecting digital innovation processes in the organizations.
[69]
Figure 1 represents our proposed model. It shows that
environmental dimension, technology dimension, and change
management affect the innovation of value proposition. In
addition, environmental dimension affects technology
dimension and change management. Moreover, top
management support affects change management.
Fig. 1. Value proposition innovation model
The environmental dimension corresponds to partners' and
competitors' pressure and firms' interactions with the
government [19], [44]. Government regulation is one of the
critical aspects that organizations should consider nowadays;
It forces action to manage the government rules imposed [70].
The prior research shows that regulatory is a reflex of
environmental action [71]. Further, stakeholder pressures are
part of environmental strategies [72]. Based on previous
research, we believe the environmental dimension is a second-
order construct [73] demonstrated by industry pressure and
government regulation, and we hypothesize that:
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TEM-21-1233.R3
Hypothesis 1 (H1). The environmental dimension is a second-
order reflective construct that is composed of industry
pressure and government regulation.
Previous studies show that the environmental dimension
leads to technological changes in organizational processes,
products or services, and business models [21], [74]–[76]. The
organizations are forced to change in reply to their
environmental and industry pressures [77]. On the other hand,
the rapidly changing environment is an enabler of changes in
organizational policy making [24]. Moreover, governmental
regulations and laws affect change management [20]. Hence,
we hypothesize that:
Hypothesis 2a (H2a). The environmental dimension has a
positive impact on the technological dimension.
Hypothesis 2b (H2b). The environmental dimension has a
positive impact on change management.
Technology-enabled assets correspond to new digital
technologies like SMACIT (Social, Mobile, Analytics, Cloud
and Internet of Things) [3] and Artificial Intelligence,
Blockchain, Augmented Reality, Virtual Reality, 3D-printing
[78]. It is necessary to understand the type of technologies that
firms have already used. On the other hand, compatibility of
technology is crucial, and it is the degree to which digital
innovations fit with the current business processes and
organization values [64]. Another critical factor is the
complexity of technology, which refers to the difficulty level
of using digital technologies [64]. Thus, we consider the
technological dimension as a second-order construct
demonstrated by Technology-enabled assets, compatibility,
and complexity, and we hypothesize that:
Hypothesis 3 (H3). The technological dimension is a second-
order reflective construct composed of technology-enabled
assets, compatibility, and complexity.
A firm that uses technological innovation and business
model innovation maximizes its performance [31]. Business
model innovation has three dimensions: value proposition
innovation, value creation innovation, and value capture
innovation [63], [65], [79]. Prior studies show that technology
as an external factor affects the business model and value
proposition innovation, and it could be used as a catalyst for
developing new value propositions [7], [80]–[83]. Therefore,
we hypothesize that:
Hypothesis 4 (H4). The technological dimension has a
positive impact on value proposition innovation.
Value proposition innovation relates to innovative solutions
for clients that change the customer experience and bring new
clients. It also includes the method of offering new solutions
to the clients through new channels [63], [65], [83], [84].
Hence, we consider value proposition innovation as a second-
order construct demonstrated by new offerings, new channels,
and new customers, and we hypothesize that:
Hypothesis 5 (H5). Value proposition innovation is a second-
order reflective construct composed of new offerings, new
channels, and new customers.
Change management is about serving customers' needs by
renewing organizational structures, capabilities, and direction
[68]. Furthermore, in order to innovate the value proposition,
it needs to create new solutions for clients and offers through
new channels [63]. The prior research shows a negative effect
of business model innovation and value proposition innovation
on organizational inertia [85] that resist change management
process [86]. Therefore, we hypothesize that:
Hypothesis 6 (H6). Change management has a positive impact
on value proposition innovation.
Top management supports the business processes changes
by decreasing the degree of resistance to change of users [87]–
[90]. Furthermore, it affects technology adoption by changing
the culture and engaging employees in visions [13]. On the
other hand, the prior study shows that top management
support facilitates organizational inertia [85]. Hence, we
hypothesize that:
Hypothesis 7 (H7). Top management support has a positive
impact on change management.
IV. EMPIRICAL STUDY
We created a research instrument corresponding to the
measurement model (Appendix A) to survey a random sample
of Iranian organizations. Our measurement model is a
questionnaire consisting of two sections: 1) questions about
sample characteristics, 2) questions about construct
measurements. The respondents can select their answers on a
seven-point numerical scale (1- Strongly Disagree to 7-
Strongly agree).
We measured environmental dimension, technological
dimension, and value proposition innovation as latent
variables of the second-order reflective type hierarchical
component [91] (Figure 1). Environmental dimension
measures industry pressure and government regulation;
technological dimension measures technology-enabled assets,
compatibility, and complexity; Value proposition innovation
measures new offerings, new channels, and new customers;
Change management measures top management support.
Finally, we used technological dimension to measure the
effect of value proposition innovation.
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TEM-21-1233.R3
TABLE 3
DESCRIPTIVE STATISTICS OF RESPONDENT CHARACTERISTICS
Respondent characteristics
(n = 220)
Gender
Female
26
11.82%
Male
194
88.18%
Age
18-30
28
12.73%
31-40
115
52.27%
41-50
53
24.09%
51-60
20
9.09%
>60
4
1.82%
Organization characteristics
Age of the organization
<2
28
12.73%
2-5
45
20.45%
6-10
39
17.73%
11-20
53
24.09%
>20
55
25%
Industry
Charity/not for profit
0
0%
Construction/Property
8
3.64%
Consumer Packaged Goods
4
1.82%
Education
7
3.18%
Energy/Mining
21
9.55%
Entertainment/media
4
1.82%
Financial services
20
9.09%
Hospitality/Catering
0
0%
IT and technology
69
31.36%
Legal
1
0.45%
Manufacturing
26
11.82%
Pharmaceutical
10
4.54%
Private healthcare and services
4
1.82%
Professional/Business services
17
7.73%
Public sector (incl. local and central government)
13
5.91%
Retail
4
1.82%
Telecommunications
2
0.91%
Transport, distribution, and logistics
9
4.09%
Utilities
1
0.45%
We used our questionnaire and obtained 220 responses from
May to November 2021 at an organizational level. It means
that we got only one answer from one of the leaders of each
organization. The questionnaire was distributed via Google
form. Table 3 shows the respondents’ characteristics.
Respondents are from the range of small to large size
enterprises in different industries, including manufacturing,
services, and construction. Most of the respondents are male
(82.18%) and more than half of them are in the range of 31 to
40 years old (52.27%).
We used a quantitative, empirical methodology to analyze
the data using PLS/SEM technique [92], [93]. We used the
Smart PLS 3.0 tool [94] to evaluate and analyze the data.
V. RESULTS
This section presents the measurement model results and
analyzes the structural model results.
5.1. Measurement model assessment
We used the PLS algorithm to test if the constructs are
reliable or not. Table 4 represents the measurement model
results with different metrics including Outer Loading,
Composite Reliability, Cronbach’s Alpha, and Average
Variance Extracted (AVE). Outer loading indicates the
constructs’ weight, which should be over than 0.70 [95].
Composite Reliability higher than 0.70 indicates the internal
consistency of the variables [96]. Cronbach’s Alpha indicates
the internal consistency and should be over than 0.70 [97].
AVE indicates the constructs’ convergent validity and it
should be more than 0.5 [98].
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Our data analysis verifies that all the indicators are reliable
because all outer loadings are more significant than 0.723.
Moreover, all the constructs are consistent because they are
over 0.917. In our test, all Cronbach's Alpha measurements are
above 0.891 indicating the study is internally consistent. All
AVEs are over 0.636, indicating convergent validity.
TABLE 4
MEASUREMENT MODEL RESULTS
Construct
Items
Outer Loading
Composite
Reliability
Cronbach's Alpha
AVE
Discriminant Validity?
Technology Dimension
Technology
Enabled Assets1
0.828
0.940
0.928
0.636
Yes
Technology
Enabled Assets2
0.796
Technology
Enabled Assets3
0.781
Compatibility1
0.829
Compatibility2
0.818
Compatibility3
0.841
Complexity1
0.760
Complexity 2
0.755
Complexity 3
0.762
Environmental Dimension
Industry
Pressure1
0.853
0.917
0.891
0.650
Yes
Industry
Pressure2
0.847
Industry
Pressure3
0.767
Government
Regulation1
0.818
Government
Regulation2
0.819
Government
Regulation3
0.723
Top Management Support
Top Management
Support1
0.900
0.936
0.908
0.787
Yes
Top Management
Support2
0.941
Top Management
Support3
0.921
Top Management
Support4
0.7777
Change Management
Change
Management1
0.900
0.939
0.913
0.794
Yes
Change
Management2
0.904
Change
Management3
0.874
Change
Management4
0.885
Value Proposition
Innovation
New Offerings1
0.791
0.949
0.939
0.674
Yes
New Offerings2
0.806
New Offerings3
0.826
New Customers1
0.900
New Customers2
0.885
New Customers3
0.823
New Channels1
0.831
New Channels2
0.776
New Channels3
0.741
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5.2. Structural model assessment
For assessing the quality of the structural model, we ran the
PLS and bootstrapping algorithm with 5000 subsamples [99].
Figure 2 shows the structural model results. Table 5 describes
the hypotheses test results, and the results, indicating that our
proposed hypotheses in section 3 are all supported.
Fig. 2. Value proposition innovation model results. *Significant at p<0.05; **significant at p<0.01; ***significant at p<0.001.
We begin this section by reporting the R2, p-values, and β^
(Figure 2). We identify that seven hypotheses are supported
with large effects including H1 because environmental
dimension explains 85.2% of the variation in Industry pressure
(β^= 0.923, p<0.001), and explains 85.4% of the variation in
government regulation (β^= 0.924, p<0.001); H2a because
environmental dimension explains 61.3% of the variation in
technological dimension (β^= 0.783, p<0.001); H3 because
technological dimension explains 75.9% of the variation in
technology-enabled assets (β^= 0.871, p<0.001), and 83.2% of
the variation in compatibility (β^= 0.912, p<0.001), and 72.9%
of the variation in complexity (β^= 0.854, p<0.001); H5
because value proposition innovation explains 87.9% of the
variation in new channels (β^= 0.937, p<0.001), and 78.1% of
the variation in new offerings (β^= 0.884, p<0.001), and
75.5% of the variation in new customers (β^= 0.869,
p<0.001); H6 because change management explains 52.7% of
the variation in value proposition innovation (β^= 0.507,
p<0.001; H7 because top management support explains 56.1%
of the variation in change management (β^= 0.565, p<0.001).
Further, we identify that two hypotheses are supported with
medium effect including H2b because environmental
dimension explains 56.1% of the variation in change
management (β^= 0.224, p<0.05); and H4 because
technological dimension explains 52.7% of the variation in
value proposition innovation (β^= 0.275, p<0.001).
In addition, we report the F2 indicator to determine if a
construct has a substantive significance or not. For (F2>
0.350), the construct has a large effect, for (0.350 > F2 >
0.150), the construct has a medium effect, and for (0.150 > F2
> 0.020), the construct has a small effect [100]. The results
summarized in Table 5 shows that all the hypotheses are
positive and meaningful but with different effect sizes. H1,
H2a, H3, and H5 have large effects, but H6 and H7 have
medium effects, and H2b and H4 have small effects.
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TABLE 5
HYPOTHESIS TEST RESULTS
Hypothesis
Independent
Variable
Dependent Variable
F2
Effect
Size
p-
value
Findings
Conclusion
H1
Environmental
Dimension
Industry Pressure
5.759
Large
0.000
Positively & Statistically Significant
*** (β^= 0.923, p<0.001)
Supported with large
effect
Government
Regulation
5.865
Large
0.000
Positively & Statistically Significant
*** (β^= 0.924, p<0.001)
Supported with large
effect
H2a
Environmental
Dimension
Technological
Dimension
1.584
Large
0.000
Positively & Statistically Significant
*** (β^= 0.783, p<0.001)
Supported with large
effect
H2b
Environmental
Dimension
Change Management
0.049
Small
0.006
Positively & Statistically Significant
** (β^= 0.224, p<0.05)
Supported with
medium effect
H3
Technological
Dimension
Technology Enabled
Assets
3.154
Large
0.000
Positively & Statistically Significant
*** (β^= 0.871, p<0.001)
Supported with large
effect
Compatibility
4.965
Large
0.000
Positively & Statistically Significant
*** (β^= 0.912, p<0.001)
Supported with large
effect
Complexity
2.693
Large
0.000
Positively & Statistically Significant
*** (β^= 0.854, p<0.001)
Supported with large
effect
H4
Technological
Dimension
Value Proposition
Innovation
0.082
Small
0.000
Positively & Statistically Significant
** (β^= 0.275, p<0.001)
Supported with
medium effect
H5
Value Proposition
Innovation
New Offerings
3.560
Large
0.000
Positively & Statistically Significant
*** (β^= 0.884, p<0.001)
Supported with large
effect
New Channels
7.254
Large
0.000
Positively & Statistically Significant
*** (β^= 0.937, p<0.001)
Supported with large
effect
New Customers
3.076
Large
0.000
Positively & Statistically Significant
*** (β^= 0.869, p<0.001)
Supported with large
effect
H6
Change Management
Value Proposition
Innovation
0.278
Medium
0.000
Positively & Statistically Significant
*** (β^= 0.507, p<0.001)
Supported with large
effect
H7
Top Management
Support
Change Management
0.311
Medium
0.000
Positively & Statistically Significant
*** (β^= 0.565, p<0.001)
Supported with large
effect
5.3. Discussion
This study uses value proposition [28], [30], change
management [37], [38], and technology adoption [44], [45]
theories to propose a theoretical model for digital
transformation. In this model, we measured value proposition
innovation by the effects of technology and change
management. Moreover, we measured the effect of
environment on technology and change management.
The prior empirical work in digital transformation study
adopting specific technology including e-business [55]–[57],
[60], cloud computing [16] and mobile applications [59], and
they design their research based on technology adoption
theories including TOE, DOI, and Iacouvo model [56], [57],
[59]. Like previous research, we measured technology
dimension and confirm that it is a second-order reflective
construct of technology-enabled assets, compatibility, and
complexity (H3). In addition, our model integrates value
proposition and change management theories with technology
adoption theories which is supported with our empirical study.
For proposing the model, we selected the constructs and
designed their relationships based on some findings in prior
study. We evaluated environmental dimension and verified
that like previous studies [19], [70]–[72], it is a second-order
reflective construct of industry pressure and governmental
regulation (H1). The previous research suggest that
organizations need to add values to their business models
because of environmental pressure [53], which impacts
technology adoption [101]. Moreover, prior research show that
environment affects change management [20], [77]. Like
previous studies, we found that environment significantly
affect the technological dimension (H2a) and change
management process (H2b).
Regarding the technological dimension, we found that while
the organization's current technology assets and complexity
significantly affect value proposition innovation, the
compatibility of technology to company's business processes
2
TEM-21-1233.R3
is more critical (H4). This outcome validates the conclusion of
earlier study [55], [59].
The prior work show that top management has an essential
role in digital transformation, primarily by leading change and
reducing resistance to change [89], [90]. Similarly, in our
study, we observed that top management support influences
change management process (H7).
We assessed value proposition innovation and validated that
like previous studies [65], [83], [102], it is a second-order
reflective construct of new offerings, new channels and new
customers. Previous research show technology affects value
proposition innovation [7], [82] and organizations inertia
negatively affects the value proposition innovation [85].
Moreover, we observed that change management in the
organizational context turns out to be the most substantial
effect. Its impact is three times greater than the effect of using
technology in the firm (H6). It proves the findings of previous
researchers who deliberate that digital transformation is not
about technology but change [61], [103], [104].
6. CONCLUSIONS, IMPLICATIONS, AND FUTURE WORK
6.1. Conclusion
This study aims to understand the effect of technology and
change management on value proposition innovation and the
effect of environment on technology and change management.
For this reason, we proposed a model consists of
environmental dimension (industry pressure, government
regulation), technological dimension (technology enabled
assets, compatibility, complexity), value proposition
innovation (new offerings, new channels, new customers),
change management, and top management support. The
research model explains 53% of value proposition innovation
with the influences of technology dimension and change
management, but the main factor is change management with
more than three times effect. We found that environmental
dimension has more impact on technological dimension than
change management.
6.2. Theoretical implications
The theoretical implication of this study provides an
extension to the growing literature on digital transformation
and value proposition innovation through the lens of change
management and technology adoption theories. We also
conducted an empirical study to evaluate our model to
determine how value proposition innovation is explained by
change management and technology.
6.3. Practical Implications
As a practical implication, the findings expose the critical
role of change management in the digital transformation
process. It also reveals the significant impression of top
leaders on change management. Therefore, companies should
pay more attention to change management and leadership in
digital transformation instead of the technology itself.
Companies should improve their capabilities to manage
strategic changes in an ongoing process. C-suite leaders also
need to be aware of digital technologies' benefits and
encourage employees to use them.
In digital age, managers should understand that new
business models are built on digital technologies including big
data, analytics, cloud, blockchain, and artificial intelligence.
They should try to create consistency between current
organizational values and existing systems with new digital
technologies. In addition, managers need to take care of
competitive pressure and government regulation to apply
technology.
To gain value proposition innovation, organizations should
address new customer needs. They should develop more
innovative products and services in comparison with their
competitors. They also need to address unserved market
segments for their products and services. In addition, they
should use new distribution channels for their products and
services that bring more efficiency in their processes.
On the other hand, the governmental legislation should
support using technologies in the organizations and should be
transparent to support and protect organizations during their
digital transformation journey.
6.4. Future work
Eventually, it would be essential to understand the other
factors that lead to value proposition innovation, business
model renovation, and implementing digital transformation in
organizations for future work. Furthermore, new research for
analyzing the impact of digital transformation on sustainability
and vice versa is recommended.
ACKNOWLEDGMENT
The authors acknowledge financial support via ADVANCE-
CSG from the Fundação para a Ciência and Tecnologia (FCT
Portugal) through research grant number UIDB/04521/2020,
and we gratefully acknowledge the financial support from
FCT—Fundação para a Ciencia e Tecnologia, I.P.
(Portugal), and national funding through research grant
UIDB/04152/2020—Centro de Investigação em Gestão de
Informação (MagIC).
3
TEM-21-1233.R3
APPENDIX A. MEASUREMENT MODEL
Construct
Measurement Items
Authors
Technology-enabled assets
- Our firm is driving new business processes built on technologies such as big data, analytics, cloud,
mobile, and social media platforms.
- Our firm is integrating digital technologies such as social media, big data, analytics, cloud, and mobile
technologies to drive change.
- Our business operations are shifting toward using digital technologies such as big data, analytics, cloud,
mobile, and social media platforms.
[62]
Compatibility
- Digital technologies are consistent with current values and beliefs
- Digital technologies are compatible with managerial and operational needs
- Digital technologies are compatible with existing systems
[16]
Complexity
- Digital technologies are easy to integrate with existing processes
- Confidence levels in the adoption of digital technologies
- Digital technologies are easy to use and manageable
[16]
Top Management Support
-Top managers are aware of digital technologies' benefits.
-Top managers support adopting digital technology services.
-Top managers encourage employees to use digital technology services.
-Top management has adequate resources to adopt digital technology services
[16]
Change Management
- In our company, change management is recognized as part of our corporate culture.
-Our firm has the capability to manage strategic change in ongoing processes.
-Our managing directors/founders are constantly looking for innovation opportunities.
-In comparison with our competitors, our company has significantly more capability in change
management.
[15]
Government Regulation
-Legislation supports using digital technologies.
-Legislation about using digital technologies is transparent
-Firms are legally protected during purchase on the Internet.
[105]
Industry Pressure
-Business partners recommended the adoption of digital technologies.
-Business partners requested the adoption of digital technologies.
-The firm experienced competitive pressure to adopt digital technologies.
[105]
New Offerings
- We regularly address new, unmet customer needs.
- Our products or services are very innovative in relation to our competitors.
- Our products or services regularly solve customer needs, which competitors did not solve.
[63]
New Customers
-We regularly take opportunities that arise in new or growing markets
-We regularly address new, unserved market segments.
-We are constantly seeking new customer segments and markets for our products and services.
[63]
New Channels
-We regularly utilize new distribution channels for our products and services.
-Constant changes of our channels have led to improved efficiency of our channel functions
-We consistently change our portfolio of distribution channels.
[63]
REFERENCES
[1] T. Hess, C. Matt, A. Benlian, and F. Wiesboeck, “Options for
formulating a digital transformation strategy.,” Mis Quarterly
Executive, vol. 15, no. 2, Art. no. 2, 2016.
[2] M. Fitzgerald, N. Kruschwitz, D. Bonnet, and M. Welch,
“Embracing digital technology: a new strategic imperative.,”
MIT Sloan Manage, vol. 55, no. 2, Art. no. 2, 2014.
[3] I. M. Sebastian, J. W. Ross, C. Beath, M. Mocker, K. G.
Moloney, and N. O. Fonstad, “How Big Old Companies
Navigate Digital Transformation,” Mis Quarterly Executive,
vol. 16, no. 3, Art. no. 3, 2017.
[4] H. Mahdavizadeh, L. Falkengerg, and M. Stackhouse, “The
innovation value canvas: A guide to defining value
propositions and target customers for commercialization of
technological innovations,” International Journal of
Innovation Management, vol. 24, no. 3, 2019, doi: DOI:
10.1142/S1363919620500127.
[5] T. Bailetti, S. Tanev, and Ch. Keen, “What Makes Value
Propositions Distinct and Valuable to New Companies
Committed to Scale Rapidly?,” Technology Innovation
Management Review, vol. 10, no. 6, pp. 14–27, 2020, doi:
DOI: 10.22215/timreview/1365.
[6] H. Chesbrough and R. Rosenbloom, “The Role of the Business
Model in Capturing Value from Innovation: Evidence from
Xerox Corporation’s Technology Spin-Off Companies,”
Industrial and Corporate Change, vol. 11, no. 3, pp. 529–555,
2002, doi: DOI:10.1093/ICC/11.3.529.
2
TEM-21-1233.R3
[7] S. Schneider, P. Spieth, and T. Clauß, “Business model
innovation in the aviation industry,” International Journal of
Product Development, vol. 18, pp. 286–310, 2013.
[8] M. Du, Q. Chen, J. Xiao, H. Yang, and X. Ma, “Supply Chain
Finance Innovation Using Blockchain,” IEEE Transactions on
Engineering Management, vol. 67, no. 4, pp. 1045–1058,
2020, doi: doi: 10.1109/TEM.2020.2971858.
[9] J. J. Yun, X. Zhao, J. Wu, J. C. Yi, K. Park, and W. Y. Jung,
“Business Model, Open Innovation, and Sustainability in Car
Sharing Industry—Comparing Three Economies,”
sustainability, vol. 12, no. 5, p. 1883, 2020, doi:
doi:10.3390/su12051883.
[10] J. B. Hill, “Leading Through Digital Disruption,” Gartner,
2017.
[11] M. H. Ismail, M. Khater, and M. Zaki, “Digital Business
Transformation and Strategy: What Do We Know So Far?,”
Cambridge Service Alliance, 2017, doi: DOI:
10.13140/RG.2.2.36492.62086.
[12] L. Cortellazzao, E. Bruni, and R. Zampieri, “The Role of
Leadership in a Digitalized World: A Review,” Frontiers in
Psychology, vol. 10, p. 1938, 2019, doi: DOI:
10.3389/fpsyg.2019.01938.
[13] J. Stouten, D. M. Rousseau, and D. D. Cremer, “Successful
Organizational Change: Integrating the Management Practice
and Scholarly Literatures,” Academy of Management Annals,
vol. 12, no. 1, 2018, doi: DOI: 10.5465/annals.2016.0095.
[14] Ch. Riehl, Th. Koch, and B. Johannes, “The Importance of
Communicating Change. Identifying Predictors for Support
and Resistance towards Organizational Change Processes,”
Corporate Communications An International Journal, vol. 24,
no. 4, pp. 670–685, 2019, doi: https://doi.org/10.1108/CCIJ-
04-2019-0039.
[15] A. Irimiás and A. Mitev, “Change Management, Digital
Maturity, and Green Development: Are Successful Firms
Leveraging on Sustainability?,” Sustainability, vol. 12, no. 10,
2020, doi: https://doi.org/10.3390/su12104019.
[16] A. Gutierrez, E. Boukrami, and R. Lumsden, “Technological,
organisational and environmental factors influencing
managers’ decision to adopt cloud computing in the UK,”
Journal of Enterprise Information Management, vol. 28, no. 6,
Art. no. 6, 2015, doi: DOI: 10.1108/JEIM-01-2015-0001.
[17] J. N. Jere and N. Ngidi, “A technology, organisation and
environment framework analysis of information and
communication technology adoption by small and medium
enterprises in Pietermaritzburg,” South African Journal of
Information Management, vol. 22, no. 1, 2020, doi:
http://dx.doi.org/10.4102/sajim.v22i1.1166.
[18] E. Hoti, “The Technological, Organizational and
Environmental Framework of IS Innovation Adaption in Small
and Medium Enterprises. Evidence from Research over the
Last 10 Years,” International Journal of Business and
Management, vol. III, no. 4, pp. 1–14, 2015, doi: DOI:
10.20472/BM.2015.3.4.001.
[19] S. K. Lippert and Ch. Govindarajulu, “Technological,
Organizational, and Environmental Antecedents to Web
Services Adoption,” Communications of the IIMA, vol. 6, no.
1, 2006, [Online]. Available:
https://scholarworks.lib.csusb.edu/ciima/vol6/iss1/14?utm_sou
rce=scholarworks.lib.csusb.edu%2Fciima%2Fvol6%2Fiss1%2
F14&utm_medium=PDF&utm_campaign=PDFCoverPages
[20] M. A. Mdletye, J. Coetzee, and W. I. Ukpere, “Exploring the
Triggers of Transformational Change in the South African
Department of Correctional Services,” Mediterranean Journal
of Social Sciences, vol. 5, no. 10, 2014, doi:
Doi:10.5901/mjss.2014.v5n10p596.
[21] W. Li, H. Sun, D. Kh. Tran, and F. Taghizadeh-Hesary, “The
Impact of Environmental Regulation on Technological
Innovation of Resource-Based Industries,” Sustainability, vol.
12, no. 17, p. 6837, 2020, doi: doi:10.3390/su12176837.
[22] T. Lin, L. Wang, and J. Wu, “Environmental Regulations,
Green Technology Innovation, and High-Quality Economic
Development in China: Application of Mediation and
Threshold Effects,” Sustainability, vol. 14, no. 11, p. 6882,
2022, doi: https://doi.org/10.3390/su14116882.
[23] L. Nyaboe, N. Bitange, and O. Kennedy, “Technology and
government regulation: A conceptual perspective of
entrepreneurial orientation on creditworthiness of micro-
enterprises,” African Journal of Business Management, vol.
14, no. 3, pp. 93–100, 2020, doi: DOI:
10.5897/AJBM2019.8846.
[24] A. Blake, “The Impact of Our Changing Environment on the
Management Practices in Public Human Service
Organizations, Human Service Organizations,” Management,
Leadership & Governance, vol. 40, no. 2, pp. 89–91, 2016,
doi: DOI: 10.1080/23303131.2016.1165039.
[25] “Mashreq 2.0: Digital Transformation for Inclusive Growth
and Jobs,” World Bank, 2018.
[26] M. Bahaee, L. A. Perez-Batres, M. J. Pisani, V. N. Miller, and
M. Saremi, “Sustainable Development in Iran: An Exploratory
Study of University Students’ Attitudes and Knowledge about
Sustainable Development,” Corporate Social Responsibility
and Environmental Management, vol. 21, no. 3, Art. no. 3,
2014, doi: DOI: 10.1002/csr.1312.
[27] D. Rogers, The Digital Transformation Playbook: Rethink
Your Business for the Digital Age. Columbia Business School
Publishing, 2016.
[28] C. M. Christensen, The Innovator’s Dilemma : When New
Technologies Cause Great Firms to Fail. Harvard Business
Review Press, 1997.
[29] P. Drucker, Management: Task, Responsibilities, Practices,
Revised Edition. Routledge, 1974.
[30] A. Osterwalder and Y. Pigneur, Business Model Generation: A
Handbook for Visionaries, Game Changers, and Challengers.
John Wiley and Sons, 2010.
[31] H. Guo, J. Yang, and J. Han, “The Fit Between Value
Proposition Innovation and Technological Innovation in the
Digital Environment: Implications for the Performance of
Startups,” IEEE Transactions on Engineering Management,
vol. 68, no. 3, pp. 797–809, 2021, doi: DOI:
10.1109/TEM.2019.2918931.
[32] A. A. H. Khaddam, H. J. Irtaimeh, A. R. S. Al-Batanyeh, and
S. R. S. Al-Batanyeh, “The effect of business model
innovation on organization performance,” Management
Science Letters, vol. 11, pp. 1481–1488, 2021, doi:
http://dx.doi.org/10.5267/j.msl.2020.12.026.
3
TEM-21-1233.R3
[33] C. Matt, T. Hess, and A. Benlian, “Digital Transformation
Strategies,” Business & Information Systems Engineering, vol.
57, no. 5, Art. no. 5, 2015.
[34] A. Ancarani and C. Di Mauro, “Successful digital
transformations need a focus on the individual,” in
Digitalisierung im Einkauf, Springer Gabler, Wiesbaden,
2018, pp. 11–26.
[35] J. Jöhnk, “Managing Digital Transformation: Challenges and
Choices in Organizational Design and Decision-Making,”
University of Bayreuth, Bonn, 2020. [Online]. Available:
DOI: 10.15495/EPub_UBT_00004854
[36] R. H. Waterman and T. Peters, In search of excellence:
Lessons from America’s best-run companies. New York:
Harper & Row, 1982.
[37] J. P. Kotter, “Leading change: Why transformational efforts
fail.,” Harvard Business Review, vol. 73, no. 2, pp. 59–67,
1995.
[38] A. Errida and B. Lotfi, “The determinants of organizational
change management success: Literature review and case
study,” International Journal of Engineering Business
Management, vol. 13, pp. 1–15, 2021, doi:
10.1177/18479790211016273.
[39] M. Fishbein and I. Ajzen, “Belief, Attitude, Intention and
Behavior: an Introduction to Theory of Research,” Philosophy
and Rhetoric, vol. 10, no. 2, 1977.
[40] P. M. Silva and G. A. Dias, “Theories about Technology
Acceptance: Why the Users Accept or Reject the Information
Technology?,” Brazilian Journal of Information Science, vol.
1, no. 2, pp. 1981–1640, 2007.
[41] F. D. Davis, “Percieved usefulness, percieved ease of use, and
user acceptance of information technology.,” Mis Quarterly,
vol. 13, no. 3, pp. 319–340, 1989.
[42] W. W. Chin and P. A. Todd, “On the use, usefulness, and ease
of use of structural equation modeling in mis research.,” Mis
Quarterly, vol. 19, no. 2, pp. 237–246, 1995.
[43] K. Mathieson, “Predicting user intention:Comparing the
technology ac- ceptance model with the theory of planned
behavior.,” Information System Research, vol. 2, no. 3, pp.
173–191, 1991.
[44] L. G. Tornatzky and M. Fleischer, Processes of Technological
Innovation. Lexington Books, 1990.
[45] J. Baker, “The Technology–Organization–Environment
Framework,” in Information Systems Theory. Integrated
Series in Information Systems, vol. 28, Springer, 2012.
[Online]. Available: ttps://doi.org/10.1007/978-1-4419-6108-
2_12
[46] J. LL. Chong and K. Olesen, “A Technology-Organization-
Environment Perspective on Eco-effectiveness: A Meta-
analysis,” Australasian journal of information systems, vol.
21, 2017, doi: DOI: 10.3127/ajis.v21i0.1441.
[47] R. Ribeiro, “igital Transformation: The Evolution of the
Enterprise Value Chains,” 2020. doi: oi: 10.1007/978-981-15-
5856-6_29.
[48] K. Nikolskyy, “he Role of Information Technology in the
Business Sector,” International Journal of Science and
Research, vol. 3, no. 12, 2014.
[49] N. Behare, SH. Waghulkar, and S. Shah, “A Theoretical
Perspective on Customer Experience (CX) in Digital Business
Strategy,” 2018. doi:
http://dx.doi.org/10.1109/RICE.2018.8509079.
[50] S. A. Taylor, G. L. Hunter, A. H. Zadeh, D. Delpechitre, and J.
H. Lim, “Value propositions in a digitally transformed world,”
Industrial Marketing Management, vol. 87, pp. 256–263,
2020, doi: https://doi.org/10.1016/j.indmarman.2019.10.004.
[51] D. Cetindamar Kozanoglu and B. Abedin, “Understanding the
role of employees in digital transformation: conceptualization
of digital literacy of employees as a multi-dimensional
organizational affordance,” Journal of Enterprise Information
Management, 2020, doi: https://doi.org/10.1108/JEIM-01-
2020-0010.
[52] R. Van Dyk and J.-P. Van Belle, “Factors Influencing the
Intended Adoption of Digital Transformation: A South
African Case Study,” 2019, vol. 18, pp. 519–528. doi: DOI:
10.15439/2019F166.
[53] K. Liere-Netheler, S. Packmohr, and K. Vogelsang, “Drivers
of Digital Transformation in Manufacturing,” 2018, pp. 3926–
3935. doi: http://hdl.handle.net/10125/50381.
[54] J. Hyvönen, “Strategic leading of digital transformation in
large established companies – a multiple case-study,” Master’s
Thesis, Aalto University, 2018.
[55] K. Zhu, S. Dong, S. Xin Xu, and K. L. Kraemer, “Innovation
diffusion in global contexts: determinants of post-adoption
digital transformation of European companies,” European
Journal of Information Systems (, vol. 15, pp. 601–616, 2006,
doi: doi:10.1057/palgrave.ejis.3000650.
[56] T. Oliveira and M. R. O. Martins, “Understanding e-Business
Adoption Across Industries in European Countries,” Industrial
Management & Data Systems, vol. 110, no. 9, Art. no. 9,
2010, doi: 10.1108/02635571011087428.
[57] V. Ilin, J. Ivetić, and D. Simić, “Understanding the
determinants of e-business adoption in ERP-enabled firms and
non-ERP-enabled firms: A case study of the Western Balkan
Peninsula,” Technological Forecasting & Social Change, vol.
125, pp. 206–223, 2017.
[58] H. S. Pramanik, M. Kirtania, and A. K. Pani, “Essence of
digital transformation—Manifestations at large financial
institutions from North America,” Future Generation
Computer Systems, vol. 95, pp. 323–343, 2019, doi:
https://doi.org/10.1016/j.future.2018.12.003.
[59] C.-Y. Chiu, S. Chen, and C.-L. Chen, “An Integrated
Perspective of TOE Framework and Innovation Diffusion in
Broadband Mobile Applications Adoption by Enterprises,”
International Journal of Management, Economics and Social
Sciences, vol. 6, no. 1, Art. no. 1, 2017.
[60] P.-F. Hsu, K. L. Kraemer, and D. Dunkle, “Determinants of e-
business use in U.S. firms,” International Journal of
Electronic Commerce, vol. 10, no. 4, Art. no. 4, 2006, doi:
10.2753/JEC1086-4415100401.
[61] G. Vial, “Understanding digital transformation: A review and
a research agenda,” Journal of Strategic Information Systems,
vol. 28, pp. 118–144, 2019, doi:
https://doi.org/10.1016/j.jsis.2019.01.003.
[62] J. K. Nwankpa and Y. Roumani, “IT Capability and Digital
Transformation: A Firm Performance Perspective,” 2016.
[63] Th. Clauß, “Measuring Business Model Innovation:
Conceptualization, Scale Development and Proof of
4
TEM-21-1233.R3
Performance,” R&D Management, vol. 47, no. 3, pp. 385–403,
2017, doi: DOI: 10.1111/radm.12186.
[64] E. Rogers, Diffusion of Innovations, 5th ed. Free Press, 2003.
[65] M. W. Johnson, C. M. Christensen, and H. Kagermann,
“Reinventing Your Business Mode,” Harvard Business
Review, vol. 86, pp. 57–68, 2008.
[66] C. Baden-Fuller and V. Mangematin, “Business models: A
challenging agenda. Strategic Organization,” Strategic
Organization, vol. 11, pp. 418–427, 2013.
[67] A. Afuah, “Business Model Innovation: Concepts, Analysis,
and Cases,” New York: Routledge, 2014.
[68] J. W. Moran and B. K. Crightman, “Leading organizational
change,” The Career Development International, vol. 6, no. 2,
pp. 111–118, 2001, doi:
https://doi.org/10.1108/13620430110383438.
[69] D. S. Elenkov, W. Judge, and P. Wright, “Strategic Leadership
and Executives: An International Multi-Cluster Comparative
Study,” Strategic Management Journal, vol. 26, pp. 665–582,
2005, doi: 10.1002/smj.469.
[70] H. B. Magsi, T. S. Ong, J. A. Ho, and A. F. Sheikh Hassan,
“Organizational Culture and Environmental Performance,”
Sustainability, vol. 10, no. 8, 2018, doi:
https://doi.org/10.3390/su10082690.
[71] W. N. Davidson and D. L. Worrel, “Regulatory Pressure and
Environmental Management Infrastructure and Practices,”
Business & Society, vol. 40, no. 3, pp. 315–342, 2001, doi:
DOI: 10.1177/000765030104000305.
[72] L. Wang, W. Li, and L. Qi, “Stakeholder Pressures and
Corporate Environmental Strategies: A Meta-Analysis,”
Sustainability, vol. 12, no. 3, p. 1172, 2020, doi:
doi:10.3390/su12031172.
[73] M. Sarstedt, J. F. Hair, Ch. Jun-Hwa, J.-M. Becjer, and Ch. M.
Ringle, “How to specify, estimate, and validate higher-order
constructs in PLS-SEM,” Australasian Marketing Journal
(AMJ), vol. 27, no. 3, pp. 197–211, 2019, doi:
https://doi.org/10.1016/j.ausmj.2019.05.003.
[74] R. Kemp, “Technology and environmental policy: Innovation
effects of past policies and suggestions for improvement,”
OECD Publications, 2000.
[75] Y. Wang, “What impact does environmental regulation have
on technological innovation?,” in E3S Web of Conferece,
France, 2020. doi: DOI: 10.1051/e3sconf/202014502050.
[76] Y. Ji, J. Xue, and K. Zhong, “Does Environmental Regulation
Promote Industrial Green Technology Progress? Empirical
Evidence from China with a Heterogeneity Analysis,”
International journal of Environmental Research and Public
Health, vol. 19, no. 1, p. 484, 2022, doi:
https://doi.org/10.3390/ijerph19010484.
[77] A. C. Smith, D. M. Evans, and H. M. Westerbeek, “The
Examination of Change Management Using Qualitative
Methods: A Case Industry Approach,” The Qualitative Report,
vol. 10, no. 1, pp. 96–121, 2005, doi:
https://doi.org/10.46743/2160-3715/2005.1860.
[78] D. Ulas, “Digital Transformation Process and SMEs,” 2019,
vol. 158, pp. 662–671. doi:
https://doi.org/10.1016/j.procs.2019.09.101.
[79] D. J. Teece, “Business models and dynamic capabilities,”
Long Range Planning, vol. 51, no. 1, pp. 40–49, 2018.
[80] J. Häikiö and T. Koivumäki, “Exploring Digital Service
Innovation Process Through Value Creation,” Journal of
Innovation Management, vol. 4, no. 2, pp. 96–124, 2016.
[81] S. C. Voelpel, M. Leibold, and E. B. Tekie, “The wheel of
business model reinvention: how to reshape your business
model to leapfrog competitors.,” Journal of Change
Management, vol. 4, pp. 259–276, 2004.
[82] M. Wouters, “Customer Value Propositions in the Context of
Technology Commercialization,” International Journal of
Innovation Management, vol. 14, no. 6, pp. 1099–1127, 2010,
doi: https://doi.org/10.1142/S1363919610003021.
[83] C. Zott and R. Amit, “Business Model Innovation: Creating
Value In Times Of Change.,” Universia Business Review, pp.
108–121, 2009.
[84] M. Morris, M. Schindehutte, and J. Allen, “The entrepreneur’s
business model: Toward a unified perspective,” J. Bus. Res.,
vol. 58, no. 6, pp. 726–735, 2005.
[85] E. Moradi, S. M. Jafari, Z. M. Doorbash, and A. Mirzaei,
“Impact of organizational inertia on business model
innovation, open innovation and corporate performance,” Asia
Pacific Management Review, 2021, doi:
https://doi.org/10.1016/j.apmrv.2021.01.003.
[86] A. Majid, M. T. Abdullah, M. Yasir, and N. Tabassum,
“Organizational inertia and change portfolio: An analysis of
the organizational environment in developing countries,”
African Journal of Business Management, vol. 5, no. 2, pp.
383–388, 2011, doi: DOI: 10.5897/AJBM10.368.
[87] U. Kulkarni, J. A. Robles-Flores, and A. Popovič, “Business
Intelligence Capability: The Effect of Top Management and
the Mediating Roles of User Participation and Analytical
Decision Making Orientation,” Journal of the Association for
Information Systems, vol. 18, no. 7, pp. 516–541, 2017, doi:
DOI: 10.17705/1jais.00462.
[88] J. Lee and H.-Y. Joo, “The Impact of Top Management’s
Support on the Collaboration of Green Supply Chain
Participants and Environmental Performance,” Sustainability,
vol. 12, 2020, doi: doi:10.3390/su12219090.
[89] M. Werde, V. K. Velamuri, and T. Dauth, “Top managers in
the digital age: Exploring the role and practices of top
managers in firms’ digital transformation,” Managerial and
Decision Economics, vol. 41, no. 8, pp. 1549–1567, 2020, doi:
https://doi.org/10.1002/mde.3202.
[90] Sh. Gupta, “Organizational Barriers to Digital
Transformation,” KTH Industrial Engineering and
Management, STOCKHOLM, 2018.
[91] C. M. Ringle, M. Sarstedt, and D. Straub, “A critical look at
the use of PLS-SEM in MIS Quarterly.,” Mis Quarterly, vol.
36, no. 1, 2012.
[92] J. F. Hair, C. M. Ringle, and M. Sarstedt, “Partial least squares
structural equation modeling: rigorous applications, better
results and higher acceptance.,” Long. Range. Plan., vol. 46,
pp. 1–12, 2013.
[93] J. F. Hair, C. M. Ringle, and M. Sarstedt, “PLS-SEM: indeed a
silver bullet.,” J. Market. Theor. Pract., vol. 19, no. 2, pp.
139–152, 2011.
[94] C. M. Ringle, S. Wende, and A. Will, “SmartPLS 2.0.,”
Universtity of Hamburg, 2005, [Online]. Available:
http://www.smartpls.de
5
TEM-21-1233.R3
[95] W. W. Chin, B. L. Marcolin, and P. R. Newsted, “A partial
least squares latent variable modeling approach for measuring
interaction effects: Results from a Monte Carlo simulation
study and an electronic-mail emotion/adoption study,”
Information System Research, vol. 14, no. 2, pp. 189–217,
2003.
[96] J. Henseler, C. M. Ringle, and R. R. Sinkovics, “The Use of
Partial Least Squares Path Modeling in International
Marketing,” Advances in International Marketing, vol. 20, pp.
277–320, 2009.
[97] K. Taber, “The Use of Cronbach’s Alpha When Developing
and Reporting Research Instruments in Science Education,”
Research in Science Education, vol. 48, no. 1, pp. 1–24, 2018,
doi: 10.1007/s11165-016-9602-2.
[98] A. M. Farrel and J. M. Rudd, “Factor analysis and
discriminant validity: a brief review of some practical issues,”
in ANZMAC 2009 conference proceedings, 2009.
[99] A. Martinez-Ruiz and T. Aluja-Banet, “Toward the definition
of a structural equation model of patent value: PLS path
modeling with formative constucts,” Statistical Journal, vol.
7, no. 3, pp. 265–290, 2009.
[100] Carlos. J. Costa, E. Ferreira, F. Bento, and M. Aparicio,
“Enterprise resource planning adoption and satisfaction
determinants,” Computers in Human Behavior, vol. 63, pp.
659–671, 2016, doi:
http://dx.doi.org/10.1016/j.chb.2016.05.090.
[101] S. K. Yeng, A. Osman, Sh. N. Salahudin, S. Abdullah, Y. J.
Lim, and Ch. L. Sim, “Relative Advantage and Competitive
Pressure towards Implementation of E-commerce: Overview
of Small and Medium Enterprises (SMEs),” Procedia
Economics and Finance, vol. 35, no. 2016, pp. 434–443, 2016,
doi: https://doi.org/10.1016/S2212-5671(16)00054-X.
[102] Th. Clauss, “Measuring Business Model Innovation:
Conceptualization, Scale Development and Proof of
Performance,” R&D Management, vol. 47, no. 3, Art. no. 3,
2017, doi: DOI: 10.1111/radm.12186.
[103] Z. Van Veldhoven and J. Vanthienen, “Digital transformation
as an interaction-driven perspective between business, society,
and technology,” Electronic Markets, 2021, doi:
https://doi.org/10.1007/s12525-021-00464-5.
[104] P. Weill and S. L. woerner, What ’s your digital business
model? SIX QUESTIONS TO HELP YOU BUILD THE NEXT
GENERATION ENTERPRISE. Harvard Business Review
Press, 2018.
[105] V. Ilin, J. Ivetić, and D. Simić, “Understanding the
determinants of e-business adoption in ERP-enabled firms and
non-ERP-enabled firms: A case study of the Western Balkan
Peninsula,” Technological Forecasting & Social Change, vol.
125, pp. 206–223, 2017.
