184
EU SMEs and E-Business Innovation
relations with citizens, businesses and other arms
of government. These technologies can serve a
variety of different ends: better delivery of govern-
ment services to citizens, improved interactions
with business and industry, citizen empowerment
WKURXJKDFFHVVWRLQIRUPDWLRQRUPRUHHI¿FLHQW
JRYHUQPHQWPDQDJHPHQW7KHUHVXOWLQJEHQH¿WV
can be less corruption, increased transparency,
greater convenience, revenue growth, and/or cost
reductions (World Bank, 2002).
Innovation: The process of innovation is
divided into the following broad activities:
• Agenda setting: general organisational
problems create a perceived need for
change;
• Matching: an organisational problem is
¿WWHGZLWKDQLQQRYDWLRQ
• 5HGH¿QLQJ5HVWUXFWXULQJ the innovation
LVPRGL¿HGWR¿WWKHRUJDQLVDWLRQDQGLW
alters the organisational structure(s);
• Clarifying: the relationship between the
organisation and the innovation is clearly
GH¿QHGDQG
•
Routinising: the innovation loses its identity
as it becomes an ongoing element in the
organisation’s activities (Rogers, 1995).
EU: European Union.
ICT: Information and Communication Tech-

nologies.
IS (Information Systems): An information
V \VW H P K D VE H H Q G H VF U L E H G D V ³DV\V W H P W R F RO OHF W  
process, store, transmit, and display information”
(Avison & Wood-Harper, 1990, p. 3).
SMEs (Small- and Medium-Sized Enter-
prises): In February 1996, the European Union
DGRSWHGDVLQJOHGH¿QLWLRQRI60(VWREHDSSOLHG
across all EU programmes and proposals dating
from December 31, 1997. The communication
recommended that member states, the European
Investment Bank and the European Investment
)X Q G D G R S W W K H G H ¿ Q L W L R Q V  +RZHYH UW KHF RP PX-
Q LF D W L R Q S H U P LW V W K H X V H RIORZ H U W K U H V K ROG¿J X U H V  
if desired. The European Union recommended
GH¿QLWLRQIRUD³PLFUR´EXVLQHVVLVWKDWLWPXVW
KDYHDPD[LPXPRIQLQHHPSOR\HHV$³VPDOO´
business must satisfy the following criteria:
• A maximum number of 49 employees;
• A maximum annual turnover of 7 million
euros;
• A maximum annual balance sheet total of
5 million euros; and
• The maximum of 25% owned by one, or
jointly by several, enterprise(s) not satisfy-
ing the same criteria.
7KH(8UHFRPPHQGDWLRQVWDWHVWKDWD³PH-
dium-sized” business must satisfy the following
criteria:
• A maximum number of 249 employees;

• A maximum annual turnover of 40 million
euros;
• A maximum annual balance sheet total of
27 million euros; and
• The maximum of 25% owned by one, or
jointly by several, enterprise(s) not satisfy-
ing the same criteria.
This work was previously published in Encyclopedia of E-Commerce, E-Government, and Mobile Commerce, edited by M.
Khosrow-Pour, pp. 464-471, copyright 2006 by Information Science Reference (an imprint of IGI Global).
185
Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.
Chapter 1.13
Environmental Drivers of
E-Business Strategies
Among SMEs
Alessandro Arbore
Bocconi University, Italy
Andrea Ordanini
Bocconi University, Italy
ABSTRACT
In front of traditional interpretations of the digital
JDSEDVHGRQHQGRJHQRXVFRQGLWLRQVRIWKH¿UPV
this chapter intends to emphasize the importance
that some external pressures may have on the e-
business strategy of small and medium enterprises
(SMEs). The environmental factors analyzed here
are market position, competitive intensity, and
institutional pressures. SMEs have been grouped
according to their level of e-business involvement,
in relation to the number of e-business solutions

adopted so far. Three layers are proposed: ex-
cluded, tentative, and integrated e-business SMEs.
A multinomial logistic regression was used to
predict these strategies. A general conclusion is
that different models seem to explain exclusion
DQGLQYROYHPHQW6SHFL¿FDOO\WZRIDFWRUVDPRQJ
those analyzed reveal to be more suitable in ex-
plaining e-business exclusion. They are the size
of a SME and a lack of institutional pressures to
adopt. On the other hand, e-business involvement
seems to be primarily prompted by a selective
competitive environment and not by imitative
behaviors, as in the previous case.
INTRODUCTION
In this chapter, our general attention is on the
adoption and diffusion of e-business solutions
among small and medium enterprises (SMEs).
0RUHVSHFL¿FDOO\RXULQWHUHVWLVIRFXVHGRQVRPH
external factors that may affect this process, since
we are persuaded that external forces are espe-
cially important within small organizations, while
186
Environmental Drivers of E-Business Strategies Among SMEs
largely understated by the literature. We will try
to analyze whether these factors do relate to the
e-business involvement of an SME.
E-business is an umbrella term referring to
a wide variety of Internet-based management
solutions. The solutions considered here are:
interactive Web sites, e-commerce platforms,

e-procurement systems, customer relationship
management systems, and telework.
BACKGROUND: SMES AND
EXTERNAL FACTORS AFFECTING
E-BUSINESS
Many researches explain the adoption of e-
business solutions in terms of endogenous fac-
tors, that is variables which are internal to the
organization. Among these factors, different
typologies of variables are recursive: the level of
¿QDQFLDOUHVRXUFHVDEOHWRDIIHFWDQ\LQYHVWPHQW
GHFLVLRQWKHPDQDJHULDOFXOWXUHLQÀXHQFLQJWKH
propensity to innovate; and the organizational
readiness, which is relevant for the integration of
new technologies (for a review, see Lee, Runge,
%DHN&RQYHUVHO\WKHSRWHQWLDOLQÀX-
ence of exogenous pressures have been largely
understated. Within this handbook, a review of
internal factors is out of the scope of the current
chapter. Instead, our goal is to deepen our un-
derstanding about the following environmental
drivers: market position, competitive intensity,
and institutional pressures.
When focusing on SMEs, environmental
elements must be considered as especially im-
portant because of the high dependency of these
organizations from the context: SMEs appear
more sensible to external pressures, in terms of
ERWKFRPSHWLWLYHDQGVRFLDO³UXOHVRIWKHJDPH´
(Fink, 1998). Therefore, important explanatory

factors of adoption strategies shall be easily found
by studying the environment where SMEs play,
rather than focusing only on internal conditions.
Above all, since e-business is basically considered
DQLQVWUXPHQWWRLPSURYH¿UP¶VFRPSHWLWLYHQHVV
(Amit & Zott, 2000), we could expect that the
competitive features of the arena where SMEs
play require special attention.
Starting from the current literature, then, the
environmental forces analyzed in this work are:
(1) the level of perceived competition (Kuan &
Chau, 2001; Riemschneider, Harrison, & Mykytn,
2003); (2) the pressure to be considered technology
savvy (Iacovou, Benbasat, & Dexter, 1995; Zhu,
Kremer, & Xu, 2003); and (3) the competitive
position occupied in the marketplace (Daniel &
Grimshaw, 2002; Lal, 1999).
2XUFKDSWHUZLOOEULHÀ\UHYLHZWKHWKHRUHWLFDO
antecedents for each of these factors and then we
will provide a set of hypotheses.
Competitive Intensity
According to the well known industrial organiza-
tion framework (Andrews, 1971; Porter, 1985), it
can be observed that an increasing competitive
intensity worsens the balance between opportuni-
WLHVDQGWKUHDWVUHTXLULQJ¿UPVWRDGRSWPRUHLQ-
QRYDWLYHVWUDWHJLHVWRVXUYLYHDQGPDNHSUR¿WV
Within this view, Gatignon and Robertson
(1989) found that competitive pressure in the
adopter industry has a positive impact on adoption

of information and communication technologies.
In the same way, Thong and Yap (1995) found
that the CEO attitude towards new technologies
adoption is positively correlated with the degree
of competition faced in the market. Similarly,
Premkumar and Roberts (1999) demonstrated that
the degree of competitive rivalry in the adopter’s
industry affects the rate of adoption of digital
technologies.
Also adopting the more recent resource-based
approach (Barney, 1991; Peteraf, 1993), it could
be observed that the strength of competition in
the factor markets reduces the power of isolating
mechanisms sustaining the competitive edge,
thus requiring continuous innovation strategies.
Within these contexts, innovations lead to re-
187
Environmental Drivers of E-Business Strategies Among SMEs
source substitution phenomenon, acting as basic
conditions for rent seeking (Malerba & Orsenigo,
1997). Especially here, e-business solutions may
contribute to the development of dynamic capabili-
ties sustaining long-term competitive advantages
(Teece, Pisano, & Shuen, 1997). This discussion
OHDGVWRIRUPXODWHRXU¿UVWK\SRWKHVLV
Hp1: The degree of perceived competition
increases the intensity of e-business strategy
among SMEs.
Institutional Pressures and
Technology Legitimacy

$FFRUGLQJWRWKHLQVWLWXWLRQDOWKHRULHVD¿UP¶V
behavior has to be coherent with norms and social
rules requested by their environment (Di Maggio
& Powell, 1983; North, 1990).
&RQVLVWHQWO\LQRUGHUWRJDLQDFFHVVWRVSHFL¿F
resources, to collaborative networks, or to strategic
DOOLDQFHVD¿UPPLJKWEHVXEMHFWWROHJLWLPDF\
assessment by other social agents (competitors,
partners, and other stakeholders). The require-
ments may be very selective especially for SMEs,
since they are not usually perceived as legitimate
players due to their lack of resources and capabili-
ties (Grewal, Comer, & Metha, 2001).
Although for SMEs the last decision maker is
generally the owner-manager, the pressure that
she feels from other stakeholders (e.g., employ-
ees, customers, suppliers) remains an important
determinant of technology adoption. Harrison,
Mykytyn, and Riemenschneider (1997) found
that similar unwritten norms, maintained by
SHHUVDQGVRFLHW\VWURQJO\LQÀXHQFHWKHLQWHQ-
tion to adopt information technologies in small
businesses. Along the same line, Lee et al. (2001)
posit that SMEs’ managers hear about the relative
advantages of digital technologies largely from the
trade press, their friends, business competitors,
and peer-social interactions.
This would create selective contexts, where it
is important to be perceived as technology savvy
and where e-business strategies may be driven,

among the other things, by a relational need to
be reputed as innovative and technology savvy.
This leads to our second hypothesis:
Hp2: The need for a technology legitimacy
increase the intensity of e-business adoption
among SMEs.
Market Position
Given a certain level of competitive rivalry, a lead-
ing market
position
1
may reveal better resources to
exploit the potential of the new technologies. This,
in turn, would be a further driver for e-business
intensity. Moreover, early e-business adoption
might be interpreted as a pre-emptive strategy
of the leader. From this point of view, the leader
ZRXOG IHHO DQ H[WHUQDO SUHVVXUH WR EH WKH ¿UVW
mover, in order not to loose its supremacy.
From a theoretical point of view, there is a
general consensus on the fact that the adoption of
information technologies, by itself, has a marginal
GLUHFWHIIHFWRQ¿UPSHUIRUPDQFHZKLOHVLJQL¿-
cant impacts emerge only when such technologies
are combined and integrated with other distinctive
competencies (see, among the others, Clemons &
Row, 1991; Mata, Fuerst, & Barney, 1995; Powell
& Dent-Micallef, 1997).
A possible implication is that e-business solu-
tions, like other ICTs, would have greater power

in consolidating leading positions rather than
reduce competitive gaps: the instrumental nature
of technology makes e-business strategies viable
RQO\ ZKHQ WKHUH DUH VRPH ³EXVLQHVV VWUDWHJ\´
beyond them, thus suggesting that technology
FDQQRW¿[DÀDZSURFHVVE\LWVHOIEXWLWLVDEOH
WR LPSURYH HYHQ VLJQL¿FDQWO\ DQ HVWDEOLVKHG
process (Carr, 2001).
,QRWKHUZRUGVWKHUHLVD³VWUDWHJLFQHFHVVLW\
hypothesis” supporting the adoption of ICT tech-
nologies, and it is more likely that this necessity is
SUHVHQWDPRQJ¿UPVZLWKDVROLGPDUNHWSRVLWLRQ
(Clemons & Row, 1991).
Following these considerations, SMEs feeling
in a leading market position would be more likely
188
Environmental Drivers of E-Business Strategies Among SMEs
WRDGRSWQHZWHFKQRORJLHVWKDQ³PDUJLQDO´FRP-
petitors, which would prefer to exploit existing
knowledge and capabilities rather than exploring
new possibilities (Leonard-Barton, 1992).
Hp3: Being in a leading market position
increases the intensity of e-business among
SMEs.
METHODOLOGY
Sampling and Collecting
The analysis is based on a survey of Italian
SMEs. In this case, Italy can be considered as a
PHDQLQJIXO¿HOGWRLQYHVWLJDWHLVVXHVUHODWHGWR
SMEs, given the high number of small organiza-

W LR Q V L Q P R V W RI W K H L Q G X V W U L H V  $ U D Q G R P V W U D W L ¿ H G 
sample of 1,000 SMEs was selected, respecting
the breakdown of SMEs among manufacturing
DQGVHUYLFHLQGXVWULHVH[FOXGLQJ¿UPVZLWKOHVV
than 50 employees, considered as very small, and
with more than 500 employees, considered as
large organizations. Data was collected through a
TXHVWLRQQDLUHDQG¿UPVZHUHFRQWDFWHGE\SKRQH
using the CATI technique during the period No-
vember/December, 2003.
$GUDIWRIWKHTXHVWLRQQDLUHZDV¿UVWWHVWHG
RQDUDQGRPVDPSOHRI60(V7KH¿QDOYHU-
VLRQZDV PR GL¿HGDFF RUGLQJO\,QRUGH UWRUH GXFH
potential response bias, a unique key informant
was chosen: the CEO was selected as the most
appropriate respondent. In answering the entire
T X H V W L R Q Q D L U H   ¿ U P V E H F D P H W K H D F W X D O V D P S O H 
of this study.
Variables
The dependent variable of our model is the inten-
sity of e-business adoption among SMEs. More
SUHFLVHO\ZHPHDVXUH³HEXVLQHVVLQWHQVLW\´DV
a multinomial variable (EBUSINT) with three
possible levels:
• 0, for SMEs which do not implement any
kind of e-business strategy, and thus ex-
cluded from e-business trajectories (EX-
CLUDED)
• 1, for SMEs which tried to implement one
e-business strategy among the following: in-

teractive Web site, e-commerce, e-procure-
ment, customer relationship management,
DQGWHOHZRUN7KLVJURXSRI¿UPVZLOOEH
called TENTATIVE
• 2, for SMEs that integrated more than one
e-business solutions in their processes, and
for which e-business could be seen as a
normal practice (INTEGRATED)
0 applications -
EXCLUDED;
26,1%
1 application =
TENTATIVE;
30,3%
2 or more
applications =
INTEGRATED;
43,6%
Figure 1. The number of e-business solutions adopted by Italian SMEs
Source: I-LAB, Bocconi University
189
Environmental Drivers of E-Business Strategies Among SMEs
The intensity of competition perceived by
a SME YDULDEOH ³&203(7,7,21´ KDV EHHQ
PHDVXUHGWKURXJKD¿YHSRLQWVOLNHUWW\SHVFDOH
(1= I completely disagree; 5 = I totally agree) for
WKHIROORZLQJVHQWHQFH³,QWKHPDUNHWZKHUHZH
play, competition is extremely strong.”
The intensity of technology legitimacy pres-
VXUH SHUFHLYHGE\D60( ³7(&+/(*,7,0´

KDVEHHQ PHDVXUHG WKURXJKD¿YHSRLQWOLNHUW
type scale (1= I completely disagree; 5 = I totally
DJUHHIRUWKHIROORZLQJVHQWHQFH³*LYHQWKH
market where we play, it is important for us to
be considered as technology savvy.”
The relative market position has been measured
WKURXJKDGXPP\YDULDEOH³/($'(56+,3´
DVWKHDQVZHUWRWKHIROORZLQJVHQWHQFH³:LWKLQ
\RXUVSHFL¿FVHJPHQWRUQLFKHGRHV\RXU¿UP
feel to be in a leading market position?” (1 =
yes; 0 = no).
6LQFHWKHUDQJHRI¿UPV¶VL]HLQRXUVDPSOHLV
remarkable (from 50 to 250 employees), and since
EXVLQHVVVL]HDOUHDG\SURYHGWREHDVLJQL¿FDQW
discriminator between IT adopters and non-adopt-
ers among SMEs (Fink, 1998), we controlled
IRUVL]HHIIHFWVYDULDEOH³6,=(´7R WKDWHQG
we used the natural logarithm of the number of
employees, considering that the probability to
adopt an innovation increases with size, but at
decreasing rates.
Last, we recognize that service sectors—for
their intangible nature—may be more conducive
of e-business strategy than manufacturing (Luck-
ing-Reilly & Spulber, 2001). The dichotomous
YDULDEOH ³6(59,&(´   PDQXIDFWXULQJ  
service), then, is used to control for this industry
VSHFL¿FLW\
The Analytical Model
Multinomial logistic regression (MLR) is useful

for sit uations in which you wa nt to be able to cla s-
sify subjects based on values of a set of predictor
variables. This type of regression is similar to
logistic regression, but it is more general because
it can be applied when the dependent variable is
not restricted to two categories.
Since we modeled our dependent variable as a
multinomial variable with three levels (excluded,
tentative, integrated), we applied the MLR proce-
dure, which is essentially an extension of binary
logistic regression to a polytomous multinomial
(Agresti, 1999).
The method basically proceeds by compar-
ing the effect of factors and covariates on the
SRVVLELOLW\RIEHLQJLQHDFKRI³n-1” categories
LQRXUFDVHWKH³H[FOXGHG´DQGWKH³LQWHJUDWHG´
categories) compared with the baseline category
³n”LQRXUFDVHWKH³WHQWDWLYH´FDWHJRU\
7KLVLVFRQFHSWXDOO\HTXLYDOHQWWR¿WWLQJ³Q´
separate binary logistic models, comparing cat-
egory 1 with category n, category 2 with n, and
so on. Practically, the software usually estimates
a simultaneous model which is more statistically
sophisticated where, for each independent vari-
DEOHZH KDYH³n-1” parameter estimates, each
estimating the effect of a one-unit change in this
v a r i a b l e o n t h e l o g o d d s o f b e i n g i n c a t e g o r y r a t h e r
than in the baseline category (Long, 1997). In few
terms, for each case, there will be n-1 predicted
logits, one for each category relative to the refer-

ence or baseline category (Menard, 2002).
It could be noted that, when multiple classes
of the dependent variable can be ranked, as for
our case, ordinal logistic regression is sometimes
preferred to multinomial logistic regression. Our
choice to adopt MLR is due to the fact that our
sample does not fully satisfy the test of parallel
lines, which is mandatory to adopt the ordinary
logistic regression (Menard). Moreover, MLR
allows comparing the effects of independent
variables (i.e., the drivers of e-business) across
different categories of dependent variables, which
is one important feature of our model. In any cases,
when the ordered logit model is run adopting a logit
as a link function, outcomes are largely similar to
those obtainable through the multinomial logistic
regression (Pampel, 2000).
190
Environmental Drivers of E-Business Strategies Among SMEs
FINDINGS
7DEOHVKRZVWKH¿UVWRXWFRPHRIWKHSUHGLFWLYH
model for the adoption of e-business solutions
DPRQJ60(V7KHUHIHUHQFHFDWHJRU\LV³WHQWD-
WLYH´WKDWLV¿UPVWKDWDGRSWHGRQHEXWRQO\RQH
e-business solution.
7KH RYHUDOO PRGHO ¿WWLQJ PHDVXUHV DUH DOO
satisfactory.
2
We can focus, then, to parameter
estimates and discuss our previous hypotheses.

7KH¿QGLQJVDUHUHSRUWHGEHORZ
  7 K H V L ] H R I D 6 0 ( D S S H D U V W R E H D VLJ Q L ¿ F D Q W 
variable in explaining the leap from being
³H[FOXGHG´ WR EHFRPH ³WHQWDWLYH´ EXW LW
GRHVQRWDSSHDUDVVLJQL¿FDQWLQH[SODLQLQJ
DIXUWKHUOHDSWKHRQHIURPEHLQJ³WHQWDWLYH´
WREHFRPHDQ³LQWHJUDWHG´HEXVLQHVV¿UP
More precisely, a one unit increase in the
natural logarithm of the number of employee
of a SME (that is, an increase of about 170%
in its size), reduces the odds ratio of being an
³H[FOXGHG´¿UP²LQVWHDGRIEHLQJDWOHDVW
D³WHQWDWLYH´RQH²E\
Excluded SME
(no ebusiness
solutions)
Tentative SME
(just 1 ebus iness
solution)
Involved S ME
(2 or more
ebusiness solutions)
SIZE**
SIZE
2. The lack of competition would not prove to
EHDVLJQL¿FDQWIDFWRULQH[SODLQLQJHEXVL-
ness exclusion for a SME; on the contrary,
the level of perceived competition appears
VLJ Q L ¿FDQWLQH[SODLQLQJWKHOHD SIURP³ WHQ -
WDWLYH´HEXVLQHVVWR³LQWHJUDWHG´HEXVLQHVV

7KLVUHVXOWZRXOGFRQ¿UPRXU¿UVWK\SRWK-
esis: the degree of perceived competition
does affect the involvement in e-business
strategies, even if it does not explain e-busi-
ness exclusion tout court. More precisely,
DRQHSRLQWLQFUHDVHLQWKH¿YHSRLQWVFDOH
measuring the level of perceived competi-
tion increases the odds ratio of being an
³LQWHJUDWHG´ HEXVLQHVV 60(²LQVWHDG RI
EHLQJMXVW³WHQWDWLYH´²E\
Excluded SME
(no ebusiness
solutions)
Tentative SME
(just 1 ebus iness
solution)
Involved S ME
(2 or more
ebusiness solutions)
Competition**
Competition
3. Low environmental pressures for being
WHFKQRORJ\VDYY\SURYHWREHDVLJQL¿FDQW
factor in explaining part of the e-business
H[FOXVLRQRID60(EXWQRWDVLJQL¿FDQWIDF-
WRULQH[SODLQLQJWKHOHDSIURPEHLQJ³WHQWD-
WLYH´WREHFRPHDQ³LQWHJUDWHG´HEXVLQHVV
¿UP $FFRUGLQJO\WKH VHFRQG K\SRWKHVLV
ZRXOGEHFRQ¿UPHGE\RXUHYLGHQFHEXW
only in explaining e-business exclusion vs.

DGRSWLRQ7KLVVDPSOHGLGQRWFRQ¿UPDQ\
role of technology legitimacy requirements
in explaining different level of e-business
adoption. More precisely, a one point in-
FUHDVHLQWKH¿YHSRLQWVFDOHPHDVXULQJWKH
intensity of this pressure reduces the odds
UDWLRRIEHLQJDQ³H[FOXGHG´¿UPLQVWHDGRI
EHLQJDWOHDVW³WHQWDWLYH´E\
Excluded SME
(no ebusiness
solutions)
Tentative SME
(just 1 ebus ines s
solution)
Involved S ME
(2 or more
ebusiness solutions)
Need for tech. legitimacy*** Need for tech. legitimacy
4. A (self-stated) leading market position is
KLJKO\ VLJQL¿FDQW RQO\ LQ H[SODLQLQJ WKH
OHDS IURP EHLQJ MXVW ³WHQWDWLYH´ WR EH DQ
³LQWHJUDWHG´ HEXVLQHVV ¿UP 60(V LQ
a leading market position (or feeling so)
more than double the odds ratio of being
³LQYROYHG´LQHEXVLQHVV ,QFRQ¿UPDWLRQRI
our third hypothesis, then, it seems possible
to conclude that a strong market position is
positively related to higher levels of e-busi-
ness involvement. More precisely, when an
SME feels to be in a leading market posi-

WLRQWKHRGGVUDWLRRIEHLQJDQ³LQWHJUDWHG´
191
Environmental Drivers of E-Business Strategies Among SMEs
Model -2 Log Likelihood Chi-Square df Sig.
Intercept Only
762,955
Final
717,061 45,895 10 0,000
Cox and Snell
0,115
Nagelkerke
0,130
McFadden
0,057
Effect
-2 Log Likelihood
of Reduced Model Chi-Square df Sig.
Intercept
717,061 0,000 0 .
SIZE
723,692 6,631 2
0,036
TECHLEGITIM
725,818 8,758 2
0,013
COMPETITION
721,911 4,851 2
0,088
SERVICES
724,123 7,063 2

0,029
LEADERSHIP
730,237 13,176 2
0,001
The chi-square statistic is the difference in -2 log-likelihoods between the final model and a reduced model.
The reduced model is formed by omitting an effect from the final model.
The null hypothesis is that all parameters of that effect are 0.
This reduced model is equivalent to the final model because omitting the effect does not increase the degrees of freedom.
EXCLUDED TENTATIVE INTEGRATED
Percent
Correct
EXCLUDED
36 14 48 36,7%
TENTATIVE
17 26 71 22,8%
INTEGRATED
22 18 124 75,6%
Overall
Percentage
19,9% 15,4% 64,6%
49,5%
Model Fitting Information
Pseudo R-Square
Likelihood Ratio Tests
Classification
Observed
Predicted
Lower
Bound
Upper

Bound
Intercept
2,947 1,012 8,476 1 0,004 . . .
SIZE
-0,418 0,170 5,999 1
0,014
0,659 0,472 0,920
TECHLEGITIM
-0,324 0,121 7,141 1
0,008
0,723 0,570 0,917
COMPETITION
0,029 0,135 0,045 1 0,831 1,029 0,791 1,339
SERVICES
-0,417 0,335 1,551 1 0,213 0,659 0,342 1,270
LEADERSHIP
0,057 0,301 0,035 1 0,851 1,058 0,587 1,907
Intercept
-0,478 0,903 0,280 1 0,596 . . .
SIZE
-0,093 0,143 0,423 1 0,515 0,911 0,689 1,205
TECHLEGITIM
-0,043 0,112 0,146 1 0,702 0,958 0,770 1,193
COMPETITION
0,250 0,125 3,983 1
0,046
1,284 1,004 1,642
SERVICES
0,381 0,276 1,901 1 0,168 1,463 0,852 2,513
LEADERSHIP

0,818 0,258 10,078 1
0,002
2,266 1,367 3,754
Wald df
EXCLUDED
INTEGRATED
Si
g
.Exp
(
B
)
95% Confidence
B Std. Error
Parameter Estimates
7DEOH0XOWLQRPLDOORJLVWLFUHJUHVVLRQPRGHO¿WWLQJ
Table 2. Multinomial logistic regression: parameter estimates*
* TENTATIVE is the reference category
192
Environmental Drivers of E-Business Strategies Among SMEs
e-business SME—instead of being just
³WHQWDWLYH´²LQFUHDVHVE\
Excluded SME
(no ebusiness
solutions)
Tentative SME
(just 1 ebus ines s
solution)
Involved S ME
(2 or more

ebusiness solutions)
Market leader Market leader***
Finally, the role of the industry (namely, ser-
vices vs. manufacturing) was controlled by the
GLFKRWRPRXVYDULDEOH³VHUYLFHV´(YHQLIWKHOLW-
erature already proved the relevance of this factor,
our sample produced a Wald statistics below the
OHYHORIVLJQL¿FDQFHIRUERWKWKHFRQWUDVWV
³WHQWDWLYH´YV³H[FOXGHG´DQG³WHQWDWLYH´YV³LQ-
tegrated”). Considering the two contrasts together,
however, the F
2
test on the difference between
the full model deviance and the baseline model
GHYLDQFHVKRZVDQRYHUDOOVLJQL¿FDQFHDWWKH
level. The estimates indicate that belonging to a
service sector, instead of a manufacturing one,
ZRXOGUHGXFHWKHRGGVUDWLRRIEHLQJ³H[FOXGHG´
by 34%. Similarly, belonging to a service sector
ZRXOG LQFUHDVH WKH SUREDELOLW\ RI EHLQJ ³LQWH-
JUDWHG´LQVWHDGRIMXVW³WHQWDWLYH´E\
IMPLICATIONS AND CONCLUSIONS
7KHYHU\¿UVWFRQFOXVLRQWKDWLVSRVVLEOHWRGUDZ
out is that different factors seem to explain the
nonadoption of e-business solutions and different
levels of e-business involvement. The analysis, in
RW K H U ZRUG V  F R Q ¿ U P V W KHRSS R U W X Q L W \ W R NH H S W K H 
two issues as separated: e-business exclusion and
e-business involvement appear, at least partially,
to be different phenomena that require different

theoretical reasoning and modeling.
:LWKVSHFL¿FUHJDUGWRRXUVWXG\WZRIDFWRUV
among those analyzed reveal to be more suitable
in explaining e-business exclusion of some SMEs
(but not to explain different levels of e-business
adoption). They are the size of a SME and a lack
of institutional pressures/inputs to adopt the in-
novations in point (see hypothesis two).
Excluded SME
(no ebusiness
solutions)
Size
Lack of institutional pres sures
to a dopt e bus ines s
This means that:
1. When the adoption of e-business is just
sporadic, almost casual (tentative, as said),
this is generally because such an adoption
roots mainly in imitating behaviors or ex-
ternal pressures, and less in the culture of
innovation or in the search of competitive
advantages.
 ,WLVDOVRFRQ¿UPHGWKDWWKHODFNRIDGHTXDWH
resources (tangibles and intangibles, as
approximated by the variable size), may
completely impair the adoption of any e-
business solution, something well-known
to the literature of innovations. SMEs in
similar conditions need the special attention
of e-business supporting policies, keeping

in mind that pushing adoption, by itself, is
QRWHQRXJKWROHWD¿UPHQMR\WKHEHQH¿WV
of e-business.
The study, then, provides insights on e-busi-
ness involvement, that is, on a further step to
EHFRPH¿UPVGHYHORSLQJPRUHHEXVLQHVVLQWH-
grated opportunities.
Leading
market p osition
Selec tive competitive
environment
Involved SME
(more
ebusiness solutions)
 ,QWHUHVWLQJO\DQGVLJQL¿FDQWO\WKLVOHDSLV
prompted by a selective competitive envi-
ronment, and not by imitative or induced
behaviors, as for the previous, tentative
step
193
Environmental Drivers of E-Business Strategies Among SMEs
2. An integrated e-business involvement, here,
seems to be a requirement and an opportu-
nity to remain competitive. Not by chance,
LQIDFWWKHVH¿UPVDUHWKHOHDGLQJRQHV
feeling the necessity to stay on the edge.
Competition, then, would create the right
conditions for driving the adoption of integrated
e-business solutions among SMEs. Procompeti-
tive policies, accordingly, would result in effective

DQGHI¿FLHQWSURGLJLWDOL]DWLRQSROLFLHVDVZHOO
The results also lead to a related consideration:
W R G D \ ¿ U P V I D F L Q J O R Z O H YHO V RI F R P S H W LW L R Q R U O RZ 
environmental pressures can still afford a low (or
nought) e-business involvement and innovation.
But how many arenas will have the fortune of
maintaining a similar structure in the next future?
The evidence tells us that these happy gardens
are rarer and rarer, also because of technologi-
cal changes. The management, here, should ask
whether they are getting ready for the upcoming
challenges or whether, instead, they are exposing
WKHLU¿UPVWRVRPHULVN\HEXVLQHVVUXQXS
Among the limitations of this study, it must be
noted that a possible response bias exists. In fact,
¿UPVZLWKDKLJKHUHEXVLQHVVLQYROYHPHQWPLJKW
be more inclined to answer the questionnaire.
However, while this would bias the percentage
of e-business adopters (statistical frequencies in
Table 1), it should not bias the relationships that
we discussed in this chapter.
Finally, as a suggestion for future research,
the implications emerged in this study might be
integrated by the analysis of further factors, both
endogenous and exogenous, separately for e-busi-
ness adoption and e-business involvement.
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