Mendonça Silva, Ferreira Moutinho, and Paço: Examining the relationships between Entrepreneurship, Intrapreneurship, and e-Commerce.
Evidence from Iberian and Scandinavian Countries
Resumen
Digitisation is a phenomenon that inevitably affects companies and economies. Consequently, the virtual market seems an excellent alternative for aspiring entrepreneurs. Recent statistics precisely point to accelerated growth of e-commerce. Indeed, this and entrepreneurship are business tools that allow a new dynamic in the market. However, recent research has barely explored the relationship between entrepreneurship and e-commerce, so this study contributes to the literature by filling the gap.
In light of the above, this study has used several indicators from two groups of countries, namely Scandinavia, in broad terms (Denmark, Sweden, Norway and Finland), and Iberia (Portugal and Spain) from the years 2012 to 2020. The Panel Corrected Standard Errors models have been used for the econometric treatment of the data. The findings confirm the bidirectional causality between entrepreneurship and e-commerce. In addition, from a widerperspective of entrepreneurship, the paper also reveals that intrapreneurship based on Research and Development (R&D) is an e-commerce driver. Therefore, this study opens up a new discussion and provides relevant support for the theoretical framework and a valuable contribution to the scarce literature on the relationship between entrepreneurship and e-commerce.
E-commerce is currently at its pinnacle, spurred by recent events such as the COVID-19
pandemic . Nevertheless, more challenges will come; for instance, the Russia-Ukraine conflict
will reshape international trade and force global value chains to be reconsidered
. Implementing the 5G Internet of Things will clearly provide opportunities and changes
, what with more and more users connecting and spending longer online , indicating that the current virtual environment offers several business opportunities
and challenges.
In this respect, e-commerce, which consists of commercial transactions performed electronically
on the Internet , is a relevant field of research for the economy and companies. In general, the
latter are aware of its importance in contemporary business, as it is a sales channel
open 24 hours a day, 7 days a week without any geographical limitations . Therefore, the Internet offers consumers a great deal of information at lower prices,
facilitating their purchases. At the same time, suppliers have many more opportunities
to benefit from economies of scale to reduce production costs , with indicators confirming this combination of interests. Thus, according to the
Statistical Office of the European Union [Eurostat] , from 2011 to 2020, the percentage of companies that performed e-sales in this region
increased (from 16% in 2011 to 22% in 2020). Likewise, business turnover generated
from e-sales rose, in this case by 6 percentage points (from 14% in 2011 to 20% in
2020). Hence, e-commerce has a net market expansion effect .
However, despite the rapid growth of digital market, studies on drivers of e-commerce
remain limited and so do those focusing on the link between entrepreneurship and digital (Steininger,
2019) in spite of the fact that e-commerce is considered to be a source of resilience
in the context of entrepreneurship . Hence, there is a need for knowledge of the relationship between entrepreneurship
and e-commerce to be broadened. Taking this into consideration, this paper aims to
create a new talking point and improve upon existing knowledge, examining the causal
relationships between e-commerce and entrepreneurship, including intrapreneurship,
one of its sub-concepts.
From a pragmatic perspective, entrepreneurship is the ability to create, develop and
manage a new venture . However, entrepreneurial production can arise in a broad range of contexts as events
that create value in a stream of changing circumstances . In other words, value creation is the basic principle of entrepreneurship . Intrapreneurship, in contrast, is a driver or an internal force that searches for
opportunities to innovate and develop entrepreneurship within organisations ; . Specifically, it refers to the company's ability to react quickly and innovatively
to internal and external changes , for instance, by way of new business ventures innovativeness, the development of
new products or services, the renewal of key ideas and proactiveness .
Therefore, entrepreneurship and digital have dominated economic development recently
and will continue to play an important role for years to come . Intrapreneurship is a driver of change in companies , which can lead to their becoming involved in e-commerce.. Moreover, intrapreneurial
capabilities are important to an organisation's success, especially during turbulent
periods of uncertainty , as was the case when the analysis of this study was performed. This paper zooms
in on two European regions, Scandinavia, in its broad sense (Denmark, Sweden, Norway
and Finland) and Iberia (Portugal and Spain) between 2012 and 2020. These regions
are culturally diverse and have different perspectives on e-commerce growth. According to , an annual global average growth rate of 6% for e-commerce is predicted between 2021-2025.
For Scandinavia, a growth equal to or greater than the global average of 6% is expected,
with Finland and Sweden seeing annual growth forecasts of 7% and Norway with rates
similar to the aforementioned global average, while Denmark will be at 5%, i.e., below
the global average. For the Iberian region, it is predicted to be equal to or less
than the 6% global average, with Spain being at said rate while in Portugal it will
more likely be 5%.
There is a lack of general understanding regarding these factors (entrepreneurship,
intrapreneurship) in e-commerce in recent literature, but this study aims to fill
the gap. In particular, it intends to explore whether e-commerce influences entrepreneurial
activities or vice versa. In addition, this dynamic between entrepreneurship and e-commerce
raises the possibility of analysing whether the relationship between these two quantities
is bidirectional.
2. LITERATURE REVIEW
2.1. The relationship between entrepreneurship and e-commerce
Business managers consider e-commerce a source of competitive advantage because it
provides a cost-effective way to access any customer globally and compete internationally
. It also allows small and medium-sized companies to compete in a similar fashion
to large ones ; . As start-ups naturally face many challenges, e-commerce can be a competitive force
, the digitalisation of products or services helping new ventures create value, for
instance . Entrepreneurs can use e-commerce tools, take risks, look for new business opportunities
and create new products or services, responding effectively to business challenges
in a constantly changing world in real time as a consequence . Therefore, the digitisation of products and services can increase the potential
for ventures to be rapidly scaled . In practice, digital works for entrepreneurs as a facilitator and mediator of their
business operations, providing tools and channels, mediated by digital technology
in order to access customers, as e-commerce does . Entrepreneurial companies use e-commerce to increase operational efficiency in
terms of sales growth . This means that e-commerce is growing exponentially and attracting more and more
entrepreneurs who are familiar with the potential benefits of this business tool.
To perform this study, “enterprises with e-commerce sales of at least 1% turnover”
is the e-commerce indicator from Eurostat which has been adopted. To enrich the analysis,
the two entrepreneurship indicators from Eurostat, namely “Birth rate of companies”
and “Survival rate 3 of companies,” have also been included. For entrepreneurship,
the relationship between emerging and surviving companies is an important detail to
consider in e-commerce because entrepreneurial persistence affects its performance
. Generally, it is considered a robust strategy by newly created ventures to adopt
e-commerce as it helps them beat their competitors and generate profits . The entrepreneur's journey unfolds via various ventures and stages of development,
with failures and restarts . Thus, the strategic timing of e-commerce adoption is critical because it can affect
performance measures .
With this in mind, the discussion of the literature suggests that entrepreneurship
can influence e-commerce, awakening the following hypotheses:
H1. Entrepreneurship based on the creation of new ventures positively influences the
adoption of e-commerce.
H2. Entrepreneurship based on surviving ventures positively influences the adoption
of e-commerce.
The aforementioned literature suggests that e-commerce is an output, but some studies
also point to its being a driver of entrepreneurship. Indeed, the Internet promotes
entrepreneurship mainly because it eases entrepreneurs’ access to information . Likewise, the development of e-commerce significantly increases the number of new
start-ups entering the market while the number of companies exiting is reduced . The prosperity of e-commerce has created multiple opportunities for aspiring entrepreneurs
to seize , among which are the fact that it has no geographical limitations, the operational
and implementation costs are significantly lower and more precise segmentation can
be made . Therefore, e-commerce simplifies new business development, positively affecting
the annual rate of business evolution for SMEs and micro businesses , alluring micro-entrepreneurs.
The discussion of the literature also suggests that e-commerce can influence entrepreneurship,
leading to the following hypotheses:
H3. The adoption of e-commerce positively influences entrepreneurship based on the
creation of new ventures.
H4. The adoption of e-commerce positively influences entrepreneurship based on surviving
ventures.
2.2. The relationship between intrapreneurship and e-commerce
Intrapreneurial initiatives can promote digital transformation ; because these actions can contribute to generating organisational newness if said
automated technology is taken advantage of . Similarly, have highlighted the importance of taking risks and developing certain capabilities
(intrapreneurial behaviour) related to e-commerce; digitisation has allowed for new
intrapreneurship opportunities with the development of e-commerce businesses.
Therefore, the study has used the R&D indicator and Global Innovation Index for intrapreneurship.
It is argued that knowledge derived from R&D investments is, in practice, an internal
force that searches for opportunities to innovate and develop internet entrepreneurship.
The field of intrapreneurship is generally related to R&D functions and innovation is a natural factor of intrapreneurship for organisations .
Taking all of the above into account, the discussion of the literature suggests that
intrapreneurship can influence e-commerce, allowing the formulation of the following
hypotheses:
H5. Intrapreneurship based on R&D positively influences the adoption of e-commerce.
H6. Intrapreneurship based on innovation positively influences the adoption of e-commerce.
3. METHODOLOGY
3.1. Data and variables
The main objective of this study is to analyse entrepreneurship and intrapreneurship
as antecedents of e-commerce, so e-commerce will be the dependent variable. However,
a bidirectional analysis between e-commerce and entrepreneurship will also be applied
in the study.
As presented in the literature review, the explanatory variables related to entrepreneurship
are (i) Birth rate and (ii) Survival rate 3 of companies. The explanatory variables
related to intrapreneurship are (iii) R&D expenditure and (iv) Global Innovation Index.
The descriptions of the variables, their acronyms, their units of measurement and
their sources are shown in Table 1.
Table 1Data and definition of variables
Variable
Acronym
Definition
Source
e-commerce
ECOM
Enterprises with e-commerce sales of at least 1% turnover. All enterprises without
financial sector (10 or more employees and self-employed workers)
Eurostat
Entrepreneurship based on the creation of new ventures
ENV
The number of enterprise births in reference period (t) divided by the number of enterprises
active in t.
Eurostat
Entrepreneurship based on surviving ventures
ESV
The number of enterprises in reference period (t) newly born in t-3 having survived
to t, divided by the number of enterprise births in t-3.
Eurostat
Intrapreneurship based on R&D
IR&D
Research and experimental development (R&D) comprises creative work undertaken on
a systematic basis to increase the stock of knowledge, including that of humans, culture
and society, and the use of this stock of knowledge to devise new applications. R&D
expenditure includes all expenditure for R&D performed in the business enterprise
sector (BERD) in the national territory during a given period, regardless of the source
of funds. R&D expenditure in BERD is shown as a percentage of GDP (R&D intensity).
Eurostat
Intrapreneurship based on innovation
IINOV
The index comprises around 80 indicators, including measures on each economy's political
environment, education, infrastructure and knowledge creation.
Wipo
This paper focuses on two European regions, Scandinavia in broad terms (Denmark, Sweden,
Norway, and Finland) and Iberia (Portugal and Spain). Therefore, the study has collected
data for each indicator for the years 2012 to 2020 for the the abovementioned countries.
To analyse the hypotheses proposed in the literature review, the following equations
have been applied:
(1)
where 𝐸𝐶𝑖𝑡is e-commerce, 𝑋𝑘𝑖𝑡 is the vector of the 𝑘 explanatory variables (Birth rate; Survival rate 3 of companies;
R&D expenditure; Global Innovation Index) and 𝜇𝑖𝑡 is the error term, 𝑖 representing a specific country and 𝑡 indicating the year.
However, the literature review also suggests that there is bidirectionality in the
relationship between e-commerce and entrepreneurship, based on Survival rate 3 of
companies and Birth rate of companies. Thus, the study includes two models represented
by Equations 2 and 3:
(2)
where 𝐵𝑅𝑖𝑡 is Birth rate of companies, 𝑋𝑘𝑖𝑡 is the vector of the 𝑘 explanatory variables (e-commerce; Survival rate 3 of companies;
R&D expenditure; Global Innovation Index) and 𝜇𝑖𝑡 is the error term, 𝑖 representing
a specific country and 𝑡 referring to the year.
(3)
where 𝑆𝑉𝑖𝑡 is Survival rate 3 of companies, 𝑋𝑘𝑖𝑡 is the vector of the 𝑘 explanatory variables (e-commerce, Birth rate of companies;
R&D expenditure; Global Innovation Index) and 𝜇𝑖𝑡 is the error term, 𝑖 referring to a specific country and 𝑡 indicating the year.
3.2. Econometric approach
This study has used Panel Corrected Standard Errors (PCSE) models. However, to justify
these econometric models to the detriment of conventional and/or robust models of
fixed and random effects, it is essential to check for the presence of what are known
as cross-dependence, heteroscedasticity and autocorrelation problems. Consequently,
and tests have been used to assess the presence of sectional dependence. To check for
the existence of heteroscedasticity problems, this study has used the Modified Waldtest
. As for whether there is autocorrelation, the test has been employed.
After conducting diagnostic tests for the existence of autocorrelation, heteroscedasticity
and contemporary correlation problems, these can be solved by using PCSE models, among
others. In this study, econometrically, to estimate equations (1), (2) and (3),we have used the PCSE models developed by . Namely, Feasible Generalized Least Squares (FGLS); a contemporaneous correlation
PCSE model [CORR(IND)]; a PCSE estimator with the option for first-order serial correlation
(AR1); Parks (PSAR), a first-order autocorrelation with a coefficient of the AR(1)
process specific to each panel; Hetonly (ar1) (HET-AR1), a PCSE estimator with the
options for both heteroscedasticity and first-order serial correlation; finally, we
have used Hetonly (HET), a PCSE estimator, which specifies that the disturbances are
assumed to be heteroscedastic.
The PCSE estimator is suitable for short-sized panels because it considers finite
sample bias while producing panel-corrected standard errors, allowing for heteroscedasticity
and correlation within analysis panels . Recent empirical studies have used the PCSE estimator because it offers a good
fit and very robust estimates for studies with similar characteristics to this one
; ; .
The three models, or equations, have been estimated using statistical software for
data science (known as Stata) where the PCSE estimators have been calculated with
the econometric methods and estimators associated by CORR(IND), FGLS, PSAR, HET-AR1
and HET, thus allowing the robustness of the regression results to be tested.
The CORR (IND) estimation specifies that there is no autocorrelation, while the FGLS
estimator is conditioned to any autocorrelation of the estimated parameters. AR1 states
that there is no autocorrelation between the panels and adds that the coefficients
of the AR1 process are common to all panels with the same coefficient for all countries.
PSAR (1) is similar to AR1 but considers that the coefficients of the first-order
autocorrelation process are particular to each panel. HET-AR1 regards the errors as
heteroscedastic and the coefficients of the first-order autocorrelation process as
common for all countries. At the same time, the HET estimator assumes a perturbation
variance common to all observations .
4. EMPIRICAL RESULTS
In the first stage, we have performed diagnostic tests whose results are presented
in Table 2, and relate them to the estimation of fixed effects, since the observations of the
sample of this study refer to a specific set of countries. There is significant statistical
evidence for the existence of the cross-section dependence problem but only from the
Frees test and Equations 1 and 2. Next, heteroscedasticity has been shown to predominate in the three equations proposed,
while the first-order autocorrelation problem only appears in the estimation of Equation 2.
Table 2Diagnostic tests
Pesaran Test
Frees Test
Modified Wald Test (χ²)
Wooldridge Test
Statistical and significant evidence
1st equation
Null hypothesis not rejected
Null hypothesis rejected
Null hypothesis rejected
Null hypothesis not rejected
Cross-Section dependency Heteroscedasticity
2nd equation
Null hypothesis not rejected
Null hypothesis rejected
Null hypothesis rejected
Null hypothesis rejected
Cross-Section dependency Heteroscedasticity Autocorrelation (AR 1)
3rd equation
Null hypothesis not rejected
Null hypothesis not rejected
Null hypothesis rejected
Null hypothesis not rejected
Heteroscedasticity
According to the results presented in Table 2, the diagnostic tests report that they must be selected for the interpretation of
the estimation results of the 1st proposed econometric relation and only the contemporaneous correlation estimator
(CORR (IND)) and the estimator with the option for heteroscedasticity (HET). Table 3, below, presents the PCSE regression estimates, considering e-commerce to be a dependent
variable whose coefficients have identical values and signals.
Table 3PCSE results for 1st equation
DEPENDENT VARIABLE
E-COMMERCE
INDEPENDENTVARIABLES
CORR (IND)
FGLS
PSAR
HET-AR1
HET
Entrepreneurship based on the creation of new ventures
0.3972971
0.2691969**
0.5303297
0.7641218*
0.3972971
Entrepreneurship based on surviving ventures
0.6725205***
0.5309511***
0.5186054***
0.4782816***
0.6725205***
Intrapreneurship based on R&D
0.1374575**
0.1272493***
0.2975227***
0.2761219**
0.1374575**
Intrapreneurship based on innovation
-0.7169127
0.462933
0.8999118
0.9280401
-0.7169127
Constant
-21.74833*
-13.73156***
-25.24183**
-23.85123**
-21.74833*
R2
0.4667
0.5236
0.5720
0.4667
Observations
60
60
60
60
60
[i] Note: *, ** and *** represent the values being statistically significant at 90%, 95%
and 99% respectively. FGLS - Feasible Generalized Least Squares; CORR(IND) – Contemporaneous
correlation PCSE model; AR1 - PCSE estimator with the option for first-order serial
correlation; PSAR1 - first-order autocorrelation with a coefficient of the AR1 process
specific to each panel; HET-AR1 - PCSE estimator with the options for both heteroscedasticity
and first-order serial correlation.
The grey columns represent the values of the estimators considered in the empirical
analysis. The other estimators are presented only from an informal perspective.
The results shown in Table 3, from the CORR (IND) and HET models, reveal that the explanatory variable Entrepreneurship
based on surviving ventures has a positive and statistically significant effect on
e-commerce with a 1% level of significance and the variable Intrapreneurship based
on R&D has a positive and statistically significant effect on e-commerce with a 5%
level of significance. However, the variables Entrepreneurship based on the creation
of new ventures and Intrapreneurship based on innovation do not significantly influence
e-commerce. Therefore, H2 and H5 are statistically supported whereas H1 and H6 are
not.
Table 4 presents the PCSE regression estimates considering Birth rate of companies as a dependent
variable. The main explanatory variables are e-Commerce, Survival rate 3 of companies,
R&D expenditure and Global Innovation Index. In Entrepreneurship, Survival rate 3
of companies has a negative and significant influence on Birth rate of companies in
all methods selected according to the results of diagnostic tests, where the study
finds the problems of cross-section dependency, heteroscedasticity and autocorrelation
first order. Moreover, the variable Intrapreneurship based on R&D shows a negative
and significant effect according to results of FGLS and HET estimators at a 1% level
of significance. Nonetheless, Intrapreneurship based on innovation has a negative
and significant effect on Entrepreneurship based on Birth rate of companies only with
the FGLS estimator. e-Commerce shows a positive and statistically significant impact
on Entrepreneurship based on Birth rate of companies at a 1% and a 5% level of significance,
according to FGLS, PSAR and HET-AR1 estimators. Comparing the results presented in
Tables 3 and 4 and recognising that there is consensus on the estimation results PCSE under Estimator
with the options for heteroscedasticity (HET-AR1), the results show that there is
a bidirectional sense between the variables Entrepreneurship based on Birth rate of
companies and e-Commerce. Therefore, it can be said that H3 is supported. Moreover,
with H1+H3 supported statistically at the estimator level (HET-AR1), it raises a hypothesis
of bidirectionality between H1 and H3.
Table 4PCSE results for 2nd Equation
DEPENDENT VARIABLE
ENTREPRENEURSHIP BASED ON BIRTH RATE OF COMPANIES
INDEPENDENTVARIABLES
CORR (IND)
FGLS
PSAR
HET-AR1
HET
Entrepreneurship based on surviving ventures
-0.2001396***
-0.2006392***
-0.1113756**
-0.1374425***
-0.2001396**
Intrapreneurship based on R&D
-0.1493402***
-0.1452031***
-0.0621713
-0.0451342
-0.1493402***
Intrapreneurship based on innovation
0.471561
0.3812352**
-0.014056
-0.9186213
0.471561
e-Commerce
0.0643778
0.069592***
0.0882707**
0.0722575**
0.0643778
Constant
26.59717***
26.36188***
16.43217***
18.88665***
26.59717***
R2
0.5773
0.8060
0.6593
0.5773
Observations
60
60
60
60
60
[i] Note: *, ** and *** represent the values being statistically significant at 90%, 95%
and 99% respectively.
The grey columns represent the values of the estimators considered in the empirical
analysis. The other estimator is presented only in an informal perspective.
Table 5 presents the PCSE regression estimates considering Survival rate 3 of companies as
a dependent variable. For entrepreneurship, Birth rate of companies has a negative
and significant influence on Survival rate 3 of companies in all methods. Regarding
intrapreneurship, R&D expenditure as an influence on Survival rate 3 of companies
is not significant in any of the methods. According to diagnostic tests, the Global
Innovation Index emerges as a significant driver of Survival rate 3 of companies with
significance in both methods.
Comparing the results presented in Tables 3 and 5, it has been taken into consideration that there is consensus on the estimation results
PCSE under estimator with the options for the Contemporaneous correlation CORR (IND)
and heteroscedasticity (HET) PCSE estimators. The scores show that significant statistical
bidirectional causality exists at the 1 % level of significance for both variables
and the relationship proposed is confirmed, so e-Commerce also influences Survival
rate 3 of companies and vice versa. Therefore, it can be said that H4 is supported.
Moreover, with H2+H4 supported statistically, it raises a hypothesis of bidirectionality
between H2 and H4.
Table 5PCSE results for 3rd Equation
DEPENDENT VARIABLE
ENTREPRENEURSHIP BASED ON SURVIVAL RATE 3 OF COMPANIES
INDEPENDENTVARIABLES
CORR (IND)
FGLS
PSAR
HET-AR1
HET
ENV
-0.487117***
-0.5039063***
-0.7125641***
-0.6570531**
-0.487117***
IR&D
0.0240619
0.0232215
-0.0220903
-0.0032314
0.0240619
IINOV
5.390891***
5.537408***
4.818595***
4.368772***
5.390891***
ECOM
0.2652322***
0.2399772***
0.3042625***
0.3240187***
0.2652322***
Constant
43.10689***
44.23486***
47.59907***
45.92557***
43.10689***
R2
0.7979
0.9595
0.8428
0.7979
Observations
60
60
60
60
60
[i] Note: *, ** and *** represent the values being statistically significant at 90%, 95%
and 99% respectively.
The grey columns represent the values of the estimators considered in the empirical
analysis. The other estimators are presented only from an informal perspective.
5. DISCUSSION AND CONCLUDING REMARKS
Some challenges arise after analysing and validating the research hypotheses by applying
the three econometric relations proposed, when e-commerce, entrepreneurship based
on the creation of new ventures and entrepreneurship based on surviving ventures are
considered for Scandinavia (Denmark, Sweden, Norway, and Finland) and Iberia (Portugal
and Spain). The findings show biderectionality and unidirectionality between these
same quantities, as shown in Figure 1.
Therefore, the results reveal a mutual influence between e-commerce and entrepreneurship.
One upside of the former is that it can be a competitive force for entrepreneurs . Given that entrepreneurial processes see failures and restarts , e-commerce adoption is critical for entrepreneurial performance , which can be done by entering new markets for instance . In addition, it promotes entrepreneurship because it facilitates entrepreneurs’
access to information and generates multiple opportunities that potential entrepreneurs can seize .
Figure 1.Bidirectionality of Entrepreneurship and eCommerce
In terms of intrapreneurship, the results highlight its role based on R&D as an e-commerce
driver, which paves the way for future investigations. R&D will probably be an efficient
intrapreneurial process to generate organisational newness if it takes advantage of
digital technology . R&D helps to understand the internal and external environment and create solutions.
Among the benefits is the possibility of reducing errors and creating effective strategies.
The results on the bidirectionality between e-commerce and entrepreneurship partially
corroborate findings on e-commerce that state that it is a competitive and value-creating
output for entrepreneurs ; ; , while at the same time said results agree with studies that propose that e-commerce
is an input or entrepreneurial source and generator of opportunity for new ventures
; ; . Therefore, this paper offers a complementary link between different views present
in the literature on the relationship between entrepreneurship and e-commerce. The
findings that e-commerce influences Survival rate 3 of companies and vice versa also
highlight the results of other studies ; ; that suggest e-commerce as a source of resilience for entrepreneurs; entrepreneurship
is not a single act but a process marked by successes, failures and beginnings . Bearing this in mind, e-commerce can work as a tool to combat the volatility and
adversities of the entrepreneurial process. Finally, R&D-based intrapreneurship as
a driver of e-commerce also backs up the intrinsic relationship between R&D functions
and intrapreneurship . Studies highlight intrapreneurial initiatives as drivers of digital transformation
; , thus opening up new opportunities for intrapreneurship .
However, the most relevant aspect of the study is that it opens up the debate about
the effects on the directional sense between entrepreneurship and e-commerce. The
bidirectional evidence found should be studied more in depth with a larger number
of European countries and in more recent periods which cover the COVID-19 pandemic.
During this time, the digital transition processes in e-commerce have implied changes
and adjustments in entrepreneurial behaviour, representing an important step forward
in research on this topic.
Hence, entrepreneurial styles of working increasingly gain recognition as fundamental
vehicles in order for the entire value-added chain to be fostered, as well as the
sustainable development of e-commerce via the technological changes of the digital
transition process for all economic activities. Consequently, there are knowledge
gains in technological innovation and digitalisation in e-commerce, with potential
gains in digital transition periods, particularly for Europe.
Based on the results, this study recommends that public policies promote professional
knowledge in entrepreneurship and e-commerce at the same time as creating legal, social
and economic conditions for organisations to explore the opportunities generated by
the combination of entrepreneurship and e-commerce; one advantage of following this
advice is that it strengthens digital technology, making broadband access more efficient,
and creates the logistical infrastructure to support entrepreneurship and e-commerce,
as well as lines of financing and consultancy services to support venture activities.
This is in addition to the specific legal requirements that promote e-commerce in
a fair and agile way.
A new decade has already started, marked by digitalisation, where there are new challenges
to undertake and opportunities for growth. Small entrepreneurial projects in a digital
era could become economically viable with high growth potential. Those who do not
adapt will miss out on more and more opportunities than ever.. Seeking to keep up-to-date
will be fundamental in the dynamic field of entrepreneurship and e-commerce.
6. LIMITATIONS AND FUTURE RESEARCH
This study has used an e-commerce indicator that only comprises omnichannel businesses
(enterprises with e-commerce sales of at least 1% turnover). Thus, it would be interesting
for a comparative study between e-commerce and brick-and-mortar companies to be performed.
This paper generates insights into the significant effect of entrepreneurship on sustainability
and digitalisation in e-commerce, particularly in Iberian and Scandinavian countries.
As for limitations, the following aspects have been identified: firstly, the drivers
of the impact of e-commerce on entrepreneurship and vice versa in other European countries
have not been tested, meaning that potential differences in terms of the levels of
the above-mentioned business tools in and between the nation states are unknown, having
solely focused on the Iberian and Northeastern countries; secondly, the number of
years covered in the sample is rather limited.
Regarding future research, it may be of interest to consider the significant increase
in the number of observations, namely the panel with a range of countries and the
notable rise in the number of years. There could be other estimation options for the
relationships proposed in this study, such as the application of dynamic models that
may make a contribution and show other statistical evidence between the quantities
and other types of results, including higher levels of reliability. Finally, according
to more recent studies of entrepreneurship, digital transition and e-commerce, the
inclusion of other variables is recommended, employing the models and equations proposed
in this study. Such examples may be (i) the number of Internet users in a particular
country per 100 inhabitants, (ii) the percentage of total early-stage entrepreneurial
activity (TEA) businesses that are active in technology sectors (high and medium),
(iii) the percentage of TEA businesses founded because of incentives for start-ups,
(iv) the percentage of TEA businesses using new technology that are less than 5 years
old on average, and (v) innovation capability, normalised to 0-100 (higher capability),
among others.
Author contribution
Conceptualization PMS, A.P.; Data Curation PMS, VFM; Methodology PMS, VFM; Visualization
PMS, VFM, AP; Software PMS, VFM; Formal analysis PMS; Validation VFM, AP; Writing
Original Draft PMS; Writing- Reviewing and Editing VFN, AP
Acknowledgments
The authors wish to thank Centre for Social and Organizational Studies (CEOS) and
NECE- Research Center in Business Sciences
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