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The Influence of Firms Entrepreneurial Orientation,
Age and Size on Information systems use and Competitive Advantage:
Empirical Evidence from Developing Countries
1.Introduction
Entrepreneurial orientation (EO) is gaining popularity among firms operating in a dynamic environment, particularly SMEs. With
increased competition, business firms are changing from the early stable roles, processes and structures which were useful in
planning, production and service delivery. Earlier on, with such a stable environment, it was possible to follow business andproduct life cycles, but with the current changes, dynamic competition pays more. Thus, entrepreneurial inclination has thepotential to replace the obsolete business models or change the firms position on the entrepreneurial orientation continuum from
conservative to entrepreneurial firms (Covin et al., 2006).
Firms entrepreneurial orientation is related to the first mover advantage whereby firms take advantage of emerging opportunities,which normally results in a positive influence on performance (Wiklund, 1999; Covin & Slevin, 1991). The emerging
opportunities could include, among others, the use of state-of-the art technologies, in particular ICTs. This kind of initiativesinvolve risk-taking and resource commitment that have a potential downside (Rauch et al., 2009). With a number of ICT platforms
that prevail, differences in performance among firm is most likely a function of their orientation and willingness to take risk,
innovate and leverage on the information systems (IS) potential. This suggests that exploiting the value offered by information
systems is contingent on among others, the enterprising tendency of the firm. This bet on the fact that availability of IS resourcesin a particular firm is worthless unless exploited intelligibility.
Previous studies operationalized entrepreneurial orientation using three dimensions, which are; risk-taking propensity,innovativeness and proactiveness (see Yusof et al., 2007; Gurol & Atsan, 2006; Miller, 1983). According to Rauch et al. (2009),
risk taking involves taking daring actions by venturing into unknown, borrowing and/or committing significant resources toventure in uncertain environment, while, innovativeness involves being creative and experimenting by introducing new
products/services and technological leadership. Proactiveness is seen as an opportunity-seeking and a forward-looking propensity,characterized by the introduction of new products/services ahead of competitors.
There has been a lot of discussion on the dimensions of EO which usually show high inter-correlation (Rauch et al., 2009,Lumpkin & Dess, 1996). As a result, most of the studies combine these dimensions into a single factor. However, in this study,
entrepreneurial orientation is measured by using two dimensions, which are innovativeness and risk-taking propensity at firmlevel. Lumpkin and Dess (1996) argue that, even though factors mostly associated with entrepreneurial orientation (autonomy,
innovativeness, proactiveness and competitive aggressiveness) are important, a firms success that is based on its entrepreneurialorientation may be achieved when only some of these factors are operating.
Elly Tumsifu
PhD, Business Administration
University of Dar es Salaam Business School, Tanzania
Abstract:
The study investigates the influence of firms entrepreneurial orientation, age and size on information system resources,
firms capabilities and competitive advantage. A confirmatory factor analysis is used to validate a model and test the
hypothesized relationships using 217 cases from small and medium tourism enterprises in Tanzania. Findings show that,
conservative firms rely on the state of the art ICT platforms in order to compete. Ceteris peribus entrepreneurial firms
industriously compete using basic IS platforms. Findings demonstrate further that, regardless of their size, extant and
entrant firms could compete on an equal footing using IS. Entrepreneurship has the potential to overcome tendency of
acquiring and accumulating ICT resources among small firms with diminutive performance improvement in developing
countries.
ISSN 2277-5846
THE INTERNATIONAL JOURNAL OF MANAGEMENT
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Firms under study and the nature of the business in question imply a dynamic and rapid changing business environment. In orderto benefit from entrepreneurial orientation, firms operating in such dynamic environment need to seek out new opportunities
(Rauch et al., 2009) and innovate frequently while taking risks in their product-market strategies (Miller & Friesen, 1982). Thus,
risk taking propensity and innovativeness are deemed relevant in measuring firm performance in relation to entrepreneurialorientation in general and information systems studies in particular. The choice of the two dimensions reflects the perspective
from which the study is undertaken as suggested by Lumpkin and Dess (1996). The use of each of the dimensions is contingent on
external and internal factors, and the industry or business environment. As such, the relationship between entrepreneurialorientation and performance is context specific and their dimensions may vary independently in a given context. The metrics forinnovativeness and risk-taking propensity from a firm perspective are feasible, but proactiveness could require sophisticatedmetrics that include customers assessments of new products and services, thus limiting the choice to the two former variables.
Similarly, since most of the time new and unfolding information technologies leave behind (are ahead of) business innovations,proactiveness is left to have little influence in such a scenario.
In most of the previous studies, the use of information systems (IS) has been associated with firms entrepreneurial characteristics,size and age. When contrasting small and large firms for instance, Vanyushyn (2006) argues that the former can be entrepreneurial
and outrun the latter when it comes to innovating with technologies. Moreover, Lumpkin and Dess (1996) propound that, for both
start-up and existing firms, entrepreneurship carried on in pursuit of business opportunities spurs business expansion,
technological progress and wealth creation. On the downside, small firms when compared with large firms may lack the financial
resources and management capabilities necessary for innovative action. With respect to IS use, SMEs have been associated withconstraints such as lack of financial resources, lack of in-house expertise, and short range of management perspective (Delone,
1998; Lees, 1987). These insights suggest that, entrepreneurial orientation, size, and age of the firm have an influence on thedevelopment, and deployments of IS. Eventually, these factors have an impact on the competitive advantage enjoyed by a
particular firm. Moreover, variations in terms of IS adoption and use between small firms of varying sizes, and along firms
entrepreneurial orientation continuum, are evident (Alpar & Reeves, 1990; Dholakia & Kshetri, 2004). The preceding discussionsuggest that entrepreneurial inclination could be vital especially when a need exist of replacing static business models with more
dynamic ones. The age and size of the firm could have far-reaching effect on the IS resources, the IS-human resources and thecapabilities of the firm. Small firm characteristics such as size, age and entrepreneurial tendencies could shape IS resources
acquisition and use as well as firms capabilities and consequently their competitive position. Therefore, the need exist to studythese factors in a more integrated and coherent manner in order to ascertain their effects.
In the study context, where generally Africans portray strong patriarchy structures, power distance and traditionalism (Krauss et
al., 2005), entrepreneurial orientation could be taken to imply a positive way of thinking about new ideas pertaining to products,services, administration or technological processes. According to West and Farr (1990), new ideas are not necessarily absolutenovelties but could be new to the relevant group, market and environment and thus context. This implies that firm performance is
not only subject to the technological advances, but also to how these technologies are implemented and used in a given context
The purpose of this study was to investigate the relationship between information systems resources (IS resources and human IS
resources), firms capabilities and competitive advantage considering the firms entrepreneurial orientation, age and size.
2.Methodology
Survey techniques were used in this study to collect data from 217 small and medium tourism enterprises (SMTEs) in Tanzania
(Babbie, 1992). As suggested by Ostgaard and Birley (1996) assessing the performance of a firm with less than two years inbusiness is illogical. Similarly, studying firm performance is seen as a relative concept which connotes assessment of continuous
firm performance (Fahy, 2000), and thus only SMETs with three years or more in business were considered. The population under
study considered SMTEs from Dar es Salaam, Moshi, Arusha, and Unguja, which account for more than 85% of all tourism
enterprises in Tanzania (URT, 2007). The choice of the regions was purely on the density of tourism activities and enterprises perse (Olomi, 2001; URT, 2007). Since the aim of the study was to draw statistical inferences from the data, thus probabilitysampling was used in obtaining the firms (Saunders et al., 2007). Lumpkin and Dess (1996) posit that, firm level approach is
consistent with classical economics in which an individual entrepreneur is regarded as a firm. The unit of analysis for this study
was thus a firm in which owner/managers were involved in the study
2.1.The Study Constructs
The model of the study hypothesize the relationship between IS use and performance through a subset of constructs as shown inTable 1.
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Latent /factor/construct
Variables
Manifest /indicator/ observed
Variables
Source/References
based on
Firm Competitive advantage
(COMPETITIVEADV )
Sales growth(SaleGr) Rivard et al, (2006);
Ravichandran andLertwongsatien,
(2005); Bhatt and
Grover,(2005); Covinet al.,(2006)
Market growth (MarkGr)
Firm growth (FirmGr)
Financial performance(FinLiq)Market share
Firm Capabilities
(CAPABILITIES)
Operational efficiency(Opertn) Rivard et al, 2006;
Ravichandran andLertwongsatien, 2005
Market efficiency (Mrkt)
Integrity efficiency (Intgeff)
Innovation efficiency (Inoeff)
Firm IS Resources (ISRES) Computing platform meeting current
business needs, and link suppliers,customers, and firm(ISfcs), IS flexibility
(ISflex), Service provider(Internet andweb hosting services)(ITServs)
Bhatt and Grover,
2005; Ravichandranand Lertwongsatien,
2005Thong, 2001, Attewell,
1992
Developed based on
pilot studyFirm Human IS resources
competences (ISHR)
Managerial IS skills(ISMgt) Ravichandran and
Lertwongsatien, 2005;
Bhatt and Grover, 2005Thong, 2001, Attewell,
1992
IS Business skills and experience(ISbus)
Industry knowledge andexperience(ISind)
Reliable IS knowledge source hired
(ISexp)
Entrepreneurial Orientation Innovativeness(Inno) Al-Qirim , 2005;
Thong and Yap,1995,Lumpkin and Dess,
(1996);Miller, (1983),Covin et al.,(2006);
Miller and Friesen,(1982)
Risk Propensity (Risk)
Firm Factors (Not Latent) Firm SizeRavichandran and
Lertwongsatien,(2005); Covin et al.
(2006)
Age of the firm
Table 1: The Constructs Of The Model
The relationship between variables is through five latent variables ( Figure 1), namely firm ISHR, ISRES, firm capabilities,
entrepreneurial orientation and firm competitive advantage, measured by a number of manifest variables. The model has also ageand size being measured directly. The bold and faded arrows represent different assumptions on what influences IS use and firm
performance. The bold arrows represent the basic study assumption that firm competitive advantage is a function of its ISHR and
ISRES through various capabilities. On the other hand the faded arrows represent the assumptions that firm competitive advantage
is not only contingent on its ISHR and ISRES but also that these variables could be shaped by the entrepreneurial orientation ofthe firm and its age and size.
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Figure 1: Latent Variables Of The Study Model; Their Relationships
2.2.Reliability And Validity
The internal consistency of the variables was assessed using Cronbachs alpha (Cooper & Schindler, 2003). Table 2 summarisesthe Cronbachs alpha coefficients obtained. The findings shows that that the items used measure what they are purported to
measure (Tabachnick & Fidell, 2007; Hair et al,. 2003).
Construct Manifest Variable1 No. ofItems
Cronbachs AlphaCoefficient
ISRES ISfcs, ISflex, ITserv 3 0.891
ISHR ISind, ISexp, ISmgt, 3 0.767
ENTREPRENEURIAL Inno, Risk 2 0.760
CAPABILITIES Mrkt, Opertn 2 0.637
COMPETITIVEADV Finliq, SaleGr, MarkGr,
FirmGr
4 0.715
Table 2: Cronbachs Alpha Values
Convergent validity was assessed throughout the analysis of the competing models as presented in the ensuing section. Themeasurement models show that factor loading were greater than 0.55, except one which is acceptable2 for research use (Falk and
Miller 1992).
3.Competing Model Analysis
A five-factor model was analysed using AMOS 15. The analysis followed the competing models analysis strategy (Hair, 2007;Ullman, 2007; Nielsen et al., 2007; Joreskog & Sorbom, 1993 Nielsen & Host 2007) which allowed for comparison between
models at each run by looking at the fit indices. As shown in the ensuing section series of six models were generated andanalysed. The values of the goodness of fit indices are presented in each model and a summary table that compare the models.
3.1.The Effect Of Age Of The Firm
Findings as shown in Figure 2 indicate that the model with Age has (five) indices that meet the criterion for data fit. These are
RMSEA, Chi-square, CMIN/DF, the GFI, AGFI, IFI and RMSEA.
1 Variables presented are those with significant coefficient values in the model.
2The item loading poorly is retained in the model to allow for alternative analysis. As suggested by MacCallum & Austin (2000)
and Straub et al.(2004) a single item in a measurement model which load weakly does not present a problem in the validity of the
model
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3.6.The Effect Of Age, Entrepreneurial Orientation, And Size
When size was added to the preceding model, the goodness-of fit indices obtained could not meet the proposed values of a good
model fit. Only the RMSEA and normed2
values have the recommended values see Figure 8 below.
Figure 7: Basic Model _Age, Entrepreneurial Orientation And Size
Table 3 below provide comparison for the models in terms of the fit indices. The basic model_age was the best one in terms of thenumber of indices (6) that graduated the minimum cut-off points. This was followed by the Basic Model_Entrepreneurial _Age.
The latter has the best indices in terms of the magnitude of the values compared with the Basic Model_Entrepreneurial though all
have four indices. So our discussion will be mainly on these two models.
S/N Model name 2,DF
probability
CMIN/DF
AGFI
CFI
GFI
IFL
RMSEA
Noindices
passed
1 Basic model_Age 2
118.739(99df) p= .086
1.199 0.906 0.931 0.900 0.030 6
2 Basic
Model_Size
2
144.015(100df) p = .003
1.440 0.917 0.045 3
3 Basic Model_Size& Age
2
170.204(114df) p=.001
1.493 0.907 0.048 3
4 BasicModel_Entrepren
eurial
2
234.983(114df) p=.000
2.061 0.909 0.911 0.070 4
5 Basic
Model_Entrepreneurial & Age
2
245.228(129df) p=.000
1.901 0.913 0.915 0.065 4
6 Basic Model_Entrepreneurial,
Age & Size
2
321.787(146df) p=.000
2.204 0.075 2
Table 3: Models Fit Comparison Summarized
3.7.Assessment Of The Measurement Models
The discussion of the measurement model considers only two models with the best-fit indices. A summary of the validity andreliability for both the measurement (indicator variables) and path coefficients has been provided in Table 4 below. The validity
and reliability of the best models are thus compared with the de facto standards to ascertain the validity and reliability of the
models (Straub et al., 2004; Tabachnick & Fidell, 2007; Nelson & Ghods, 1998).
IS RES.87
ITserv
e7
IS HR
.55
CAPABILITIES
.55
ISexp
e3
.54
ISmgt
e2
res1
Chi_square= 321.787(146 df)
p=.000
RMSEA= .075CMIN/DF = 2.204
.01
ISbus
e1
.12
.93
COMPETITIVE ADV
.39
MarkGr
e12
.37
Mrkt
e16
.34
Opertn
e15
.44
FirmGr
e13
.27
SaleGr
e10
res2
.74
.48
ISflex
e6
.28
FinLiq
e9
.92
ISfcs
e5
.61
.58
.52 .63
.67
.01
Intgef
e14
.48
ISind
e4
.69
.53
.08
.69
.93
.35
.61
.14
.73
.96.97
.03
Inoeff
e17
.18Size
.00
Age .03
.30
ENTREPRENEURIAL
.75
Risk
e19
.86
.66
Inno
e18
.81
.31
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Validity
component
Technique
used
Heuristic/de
facto
standards
Study model validation
Basic model_Age Basic Model
Entrepreneurial &
Age
Discriminantvalidity CFA as used
in SEM
GFI>.90,NFI>.90,
AGFI>80,insignificant2
and
significant t-values for item
loadings
CMIN/DF=1.901,2
118.739 (99df) p=.086,
AGFI=0.906,
GFI=0.931,IFL=0.900,RMSEA=0.030,
t-values aresignificant3
CMIN/DF=1.199,CFI= .931, IFI=.915,
RMSEA=.065t-values for factor
loading are
significant,
Convergent
validity
CFA as used
in SEM
GFI>.90,
NFI>.90,AGFI> .80,
CMIN/DF=1.901,2
118.739 (99df) p=.086,
AGFI=0.906,GFI=0.931,IFL=0.900,
RMSEA=0.030,t-values are significant
CMIN/DF=1.199,
CFI= .931, IFI=.915,RMSEA=.065
t-values for factorloading are
significant,
Reliability(InternalConsistency)
Cronbachs Cronbachs should be
above .60 or
.70
Cronbachs valuesare above .60
Cronbachs valuesare above .60
Content validity LiteratureReview,
Expert panels
Higher degreeof consensus
Study instrumentreviewed and consider
experts opinion, pilottested
Study instrumentreviewed and consider
experts opinion, pilottested
Nomologicalvalidity
SEM Standardizepath
coefficients
All standardizedcoefficients have
significant values
greater than 0.2
Paths coefficients forISHR and
ENTREPRENEURIA
L to CAPABILITIESand
COMPETITIVEADV
have significantvalues greater than0.2 ,
Predictive validity SEM Explained
variances in the
.40 range orabove are
desired
Variance explained for
capabilities is .56 and
for the competitiveadvantage is .88
Variance explained
for capabilities is .55
and for thecompetitive advantage
is. 93
Table 4: Study Models Validation4
3.8.The Measurement Model For The Model With Age
Standardized path coefficients between measured variables and factors (Table 5), show that all path coefficients betweenmeasured (manifest) variables and latent (unobserved) variables in the model are significant p < 0.05, except for integrity
efficiency Intgeff and innovation efficiency inoeff. Second, the observed variables with significant probabilities have positive
standardized regression weights greater than 0.56, only the ISbus had a value of 0.284 (Straub et al., 2004). Most of the factorloadings explaining the measurement model are adequate and thus show that the research constructs are reliable (Rivard et al.,
2006).
3Significant t-values are associated with C.R > 1.96, in our study models all factors loadings have significant t- values. Note that
age is not considered here since it is a direct measure and not a factor.4 See (Straub et al., 2004; Tabachnick & Fidell, 2007; Nelson and Ghods, 1998; Hoe, 2008) for the heuristic/de factostandards in
relation to SEM.
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Estimate S.E C.R P Standardized
Regression Weights
CAPABILITIES
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Estimate S.E. C.R. P Estimate
CAPABILITIES
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expected performance improvement. Better performance resulting from IS use occurs when firms consider innovating beyond
technological diffusion to include process, products and services as well as the users of the technology (Lumpkin & Dess, 1996).Risk-taking dimension of firms using IS could be associated with the transformation undertaken as firms attempt to migrate to a
more IS business environment. This may involve the application of systems which integrate customer information, IS platforms
that provide support to customers, and end-to-end processing. This is a deal of both IT and human resource requirements, andchanging existing configurations. While these are important aspects in competing through technology, the managers risk-taking
propensity play a major role in shaping these frontiers. Thus, SMEs that are ready to take risks towards this end are more likely to
perform better than those that are risk averse. This may require firms to effectively scope the inherent risks (Bharadwaj, 2000)associated with infrastructure investments and technology trends.Firms which take chances in uncertain decision-making contexts are ready to invest their resources in opportunities with the
possibility of costly failure. This is an important aspect which could be a source of difference in the successful development and
deployment of IS, even for small firms with meager resources. Although small firms are known to be flexible towards innovationand technology, they might have difficulties in taking risks concerning new technologies. As both low and very high risk taking
propensity are not favourable in respect of calculated risk taking, owner-managers in the position of taking such a calculated riskare more likely to have an impact on IS use and firm performance.
4.2.The Effect Of The Firms Age
The study investigated whether the firms age influenced its competitive advantage through its capabilities and resources. From
the findings of this study, age contributed to the best model, where it has a significant correlation with ISHR. These findingssuggest that various ISHR capabilities are positively correlated to firm age. These competences of the firm have an element of
time, i.e. they take time to develop and mainly through learning by doing (Barney, 2001). Thus, age of the firm influences varioushuman IS resources rather than directly influencing market and operational efficiencies. Ravichandran and Lertwongsatien (2005)claim that, on average, it takes four to six years to develop a mature systems delivery process, when firms systematically
implement software.This could be explained by the fact that the presence of customized computer applications and increasinglythe open source and standard solutions makes it possible for even newly founded firms to acquire basic computing platform.
However, by their nature the SMEs in this study require a basic computing platform in an onset of the business to be able to runtheir activities. This suggests that IS use among extant and new entrant firms is not restricted. Rao et al. (2003) acknowledge that,
it is not necessary for a firm to always start with simple applications but can always assume any position in the developmentrange. This gives leeway to even young firms to enjoy the benefits of IS given the experience and knowledge they bring in or start
with the business.
4.3.Size Of The FirmsThe size of the firm as measured by the number of employees could not be accounted for by any of the two models.
Balasubramanian and Lee (2008) acknowledged a contradiction with regard to the size of the firm and innovation, as Schumpeter
(1934) had two apparently contradictory views. While entrepreneurs seem most likely to innovate, contradicts the assertion that
large firms with some degree of monopoly power are also most likely to innovate. These findings seem to suggest that the
frequently unfolding innovations related to IS are undifferentiated between firms of varying sizes. Technological improvementsincremental as they are do not necessarily prohibit small or large firms from acquiring and making use of them. Neither do theyfavour large and established firms at the expense of the small firms.
5.Conclusion
In both scenarios, the findings demonstrate that ISHR significantly influence the performance of a firm in which age of the firm
favours the development of ISHR. However, the size of the firm has no influence whatsoever on competitive advantage. What
differs between the two is the quality of ISRES. Whereas for conservative SMTEs, ISRES significantly influence firm capabilitiesand competitive advantage, this extent is less pronounced when SMTEs are entrepreneurial. Entrepreneurial SMTEs couldcompete using basic IS resources and in that case do not necessarily depend on the state-of-the-art technologies or an
accumulation of IS resources. They only need ICT infrastructure as a source of value which provide the necessary IS platform to
compete through. The tendency for majority of the users of ICT in Africa tend to automate and upgrade or change their facilitieseach time a new release is made available. This attitude does not necessarily translate into better performance. We argue that been
industrious with ICT use pays more than just acquiring every released new version.
These calls for policies that create a conducive operating environment, encouraging small firms to use IS and embraces anentrepreneurial culture that leads to greater business competency, improved performance and sustained competitive advantage.Policy priorities should be on entrepreneurial tendencies as they pave the way for better use of IS resources.
The findings have far-reaching implications for owner managers entrepreneurial inclination. Whereas entrepreneurial tendenciescould lead to better performance through basic IS resources, the opposite is true for conservative managers. There is a need formanagers to inspire innovativeness and risk-taking propensity within the firm. Such aspects have the potential to result in above-
normal performance. Entrepreneurial orientation (EO), particularly being more innovative in deploying basic ISRES incombination with the right ISHR, has the potential to overcome IS infrastructural over-dependence and thus provide firms with
the required capabilities and competitive advantage, which is most desirable for SMEs in developing economies.
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