Local And Virtual Alliances As A
Supplemental Contributor To Firm Performance
Sarit J. Levy ¹, Aaron D. Joyal ²
¹ University of Miami ,
USA , ² University of Memphis , USA
ABSTRACT:
The degree of participation of local alliances defines formal and informal relationships designed to share the knowledge base of a particular region. Local alliances have played an unprecedented role in firm performance in the past. A firm's involvement with those alliances can often be a measurable component to overall success (Levy, 2011). Today, the inclusion of virtual alliances may often serve as a supplement to the facilitation of relationships and support networks.
Keywords: Local alliances, Virtual alliances, Firm performance
Introduction
The access to relationships often serves as an entry way for new product introduction (Acs et al., 1994). The knowledge spillover when engaged in a business or personal relationship with a party in the same or similar industry can often encourage innovative activity. This notion that a reciprocal relationship amongst alliances exists has been demonstrated amongst firms in similar geographic locations. The localization of the relationship and the strength of the tie is what ultimately encourages this knowledge spillover (Levy, 2011). Yet, today the communication barrier of support networks has extended far beyond the geographically bounded region into the virtual universe. This research embodies the significance of local alliances on firm performance with a new perspective on the inclusion of virtual relationships in future firm success.
Theoretical Background
The theoretical underpinning of the aforementioned research stems from the knowledge based theory (Decarolis & Deeds, 1999). Knowledge generation is seen as source for superior performance. Moreover, the knowledge that flows within the organization is seen as a constant flow. In order to achieve this flow, access to knowledge generators such as; educational institutions, research labs, suppliers, partners, and so forth must be a part of the foundation for decision making and organizational action. These generators are seen as an entrepreneurial support system whereby the encouragement of the relationship fosters innovative activity.
While the spatial context of the firm plays a role on corporate performance (Delios & Beamish, 1999), it is the strength of the tie (Sternberg & Litzenberger, 2004) and commonality amongst the relationships that formulate a clustering, allowing the potential for growth of the firm. The research within this article demonstrates the dependence on alliances in a spatially concentrated area. However, the need for supplemental alliances and resources is demonstrated by an increase dependency on virtual alliances.
Conceptual Foundation And Data
The conceptual foundation for this research is proposed in the theoretical
background of the knowledge based theory.
An internet survey assessing firm performance of senior managers and executives
in the professional business and technology service sector in
Herein, the hypotheses are identified:
H1: Senior management of professional business and technology service firms in the NAICS 541 category view accessibility to alliances as a prime component of a successful firm.
H2: As the number of alliances increases for professional business and technology firms in the NAICS541 category so does the performance outcome of that firm.
The literature has argued that senior management has generally viewed alliances as a very important contributor to success (Boasson et al., 2005). The propensity to engage in alliance networks will encourage knowledge spillover, and contribute to a business model of high performing and innovative firms.
Findings
And Descriptive Analysis
At the descriptive level, the survey findings
display a high level of importance on local alliance building as a key to
success. It is important to note that
these findings relate to local alliances, which is perceived as an important
value for the localization of a professional business or technology service
firm. However, there is some evidence
that virtual alliances also play a contributory role. The notion that virtual alliances can be
considered a proponent for local success or virtual success of a firm is of
significant value in that it can be explored further in future research.
The mean percentage of alliances each firm in
South Florida indicated they have is roughly 76.6% and of those alliances 81.7%
of them are located in
Table
1: Firms With Alliances
|
Q2 Firms with Alliances |
Descriptive and Frequencies |
Q3 Number of Alliances in |
Descriptive Statistics |
|
Mean |
8.8 |
Mean |
43% |
|
Median |
3.0 |
Median |
15% |
|
Number of Cases |
|
Number of Cases |
|
|
Don't have alliances |
53 |
Don't have alliances |
49 |
|
Percent having alliances |
76.6% |
Percent having alliances in |
81.7% |
|
Total No. of Cases |
73 |
Total No. of Cases |
30 |
Table two illustrates that respondents find particular alliances significant to their overall success. It is clear that business partners are ranked the highest in terms of importance of alliance with a percentage of importance of 93.1%. Professional associations as well as complementary business are also highly valuable as their percentage of importance is ranked second and third consecutively with a percentage of 86.5% and 81%.
Table
2: Importance Of
|
Q5 |
Important (Top 3 categories) |
Not Important (Bottom 2 categories) |
|
Research institutions |
54.8% |
46.2% |
|
Universities & Colleges |
39.1% |
61.9% |
|
Supplier Partnerships |
78.8% |
21.2% |
|
Business Partners |
93.1% |
7.9% |
|
Professional Associations |
86.5% |
13.5% |
|
Complementary Business |
81.0% |
19.0% |
Table 2 is based on a Likert type 5-point scale ranging from Not Important (1) to Very Important (5)
In addition to determining the importance of alliances, the type of
alliances was examined. Business
partners were seemingly the most important alliance in that the firms in
Table 3: Types Of Alliances
|
Q4 |
Research Institutions |
Universities
& Colleges |
Supplier Partnerships |
Business Partners |
Professional Associations |
Complementary Business |
|
% of Firms In
each category |
4.2% |
19.2% |
33.4% |
44.1% |
43.5% |
42.8% |
|
Total Number of
Cases |
72 |
73 |
72 |
72 |
73 |
72 |
One of the significant elements of the research
illustrated the importance of the strength of alliances within each category as
it pertained to entrepreneurial success (refer to table 4). Although all the
categories were important in terms of choosing a location for a business,
access to business partners, suppliers, and professional associations were the
strongest networks that encourage alliance building. A
Table
4: Importance Of Strength Of
|
Q5 |
Research Institutions |
Universities
& Colleges |
Supplier Partnerships |
Business Partners |
Professional Associations |
Complementary Business |
|
Mean |
2.1 |
2.7 |
3.5 |
4.1 |
3.7 |
3.5 |
|
Not Important
(bottom two categories) |
46.2% |
61.9% |
21.2% |
7.9% |
13.5% |
19.0% |
|
Important (top
3 categories) |
54.8% |
39.1% |
78.8% |
93.1% |
86.5% |
81.0% |
|
Number of Cases |
21 |
26 |
33 |
38 |
37 |
42 |
Table Four is based on a Likert type 5-point scale ranging from Not Important (1) to Very Important (5)
Table
5: Inter-Correlations (Kendal Tau-B) Between The Importance Of Specific Types
Of Alliances
Q5A Q5B Q5C Q5D Q5E Q5F Q5A Universities 1.00 .67* -.07 .14 .04 .26 Q5B Research Institutions 1.00 .04 .12 .24 .36 Q5C Business Partners 1.00 .21 .34* .36* Q5D Professional Associations 1.00 .11 .27 Q5E Suppliers 1.00 .27 Q5F 1.00 * Represents correlations that are
significant at the 95% level of confidence or higher * Represents correlations that are
significant at the 95% level of confidence or higher
The usefulness of alliances with research
institutions, universities, business partners, and so forth is empirically
confirmed in the descriptive analysis.
It is clear that the tables provide strong evidence for alliance
building and clustering in the
The emergence of other types of alliances, such as
distant alliances and virtual alliances also can have significant impact in
decision making processes within an organization. When the firm has access to these
supplemental knowledge generators, there is a reaffirmation that they are
contributory to the overall success of the firm. Although they are secondary to local factors,
firms in the sample acknowledged that they have virtual alliances and their
significance. 21.1% percent of the firms
sampled indicate that they have virtual alliances (refer to table 6).
Table
6: Firms Having Virtual Alliances
|
Q6 |
Virtual
Alliances |
No. of Firms |
|
Percent with
Virtual Alliances |
21.1% |
16 |
|
Total Cases |
|
76 |
The importance of these virtual alliances among
those firms that acknowledge that they have virtual alliances also plays a role
in admitting that the common practice of going to the local supply house or
neighbor for business advice has changed.
While the localization of a business' immediate economy is communal, the
dialog that is now being reached virtually helps to enhance the innovative
environment through knowledge spillover.
This is not to say that the local firm will no longer be a source of
stimulation for practical operations, but the ability to access additional
knowledge resources may play a deciding factor in business decisions. Table seven illustrates that 43.8% of the
firms sampled feel that their virtual alliances are of significance to their
entrepreneurial effort.
Table
7: Importance Of Virtual
|
Q7 If
established virtual alliances, how important To
entrepreneurial effort? |
Virtual
Alliances |
No. of Firms |
|
Not at all
important |
6.3% |
1 |
|
Somewhat
Important |
31.3% |
5 |
|
Important |
43.8% |
7 |
|
Very Important |
18.8% |
3 |
Structural
Equation Modeling
The second phase of the analysis concentrates on
structural equation methodologies to determine the effects of a firm’s adoption
of traditional alliances coupled with the significance of virtual alliances as
it impacts organizational performance.
As previously stated, the research determines both the accessibility to
alliances and the impact of alliances on firm success.
H1: Senior management
of professional business and technology service firms in the NAICS 541 category
view accessibility to alliances as a prime component of a successful firm.
H2: As the number of
alliances increases for professional business and technology firms in the
NAICS541 category so does the performance outcome of that firm.
A two-step approach for modeling (Anderson &
Gerbing, 1988) was utilized in this procedure.
Firstly, an adequate measurement model was established and later tested
for adequacy of fit (refer to figure 1).
Figure
1: Measurement Model
Figure two indicates a model with path coefficients. Note that the path coefficients are not
correlation coefficients. In this case,
the model demonstrates a statistically significant path relating to the
establishment of traditional alliances to business performance. As the number of traditional alliances
increase, a firm gradually increases its’ performance. The meaning of the path coefficient (e.g.,
0.803 in figure 2) is that as the number of strategic alliances is increased by
one standard deviation from its mean, business performance is expected to
increase by 0.803 of its own standard deviation from its own mean (Bullmore et
al., 2000). The data was screened for
skewness, kurtosis, and possible outliers to avoid any violations of the
assumptions identified.
Figure
2: Model With Path Coefficients
Once the measurement in the model was defined, the
hypotheses were then tested. When
tested, the first hypothesis test confirmed the significance of alliances has a
positive impact on the establishment of alliances. Moreover, the second test confirmed that the
number of strategic alliances is positively related to performance in firms. As discussed below, the model was supported
by various fit indices. Table eight
indicates a significant relationship between traditional alliances and virtual
alliances and business performance outcomes with a t-value of >2.00, and
p<0.05.
Table
8: Hypotheses Test Results
|
Path |
Coefficient |
Standard |
t-Value |
Two Tailed |
|
H1:
Significance of Alliances → Strategic Alliances |
0.503 |
0.066 |
7.621 |
< 0.0001 |
|
H2: Strategic
Alliances → Organizational Performance |
0.803 |
0.092 |
8.730 |
< 0.0001 |
|
Note: df
= 25 |
|
|
|
|
|
|
|
|
|
|
The analyses also provided evidence of model fit.
With respect to commonly accepted fit statistics, all are suggestive of a
well-fitting model. The χ2
test for goodness of fit measures how well our model fits our set of
observations. In other words, a measure
of goodness of fit summarizes the discrepancy between the observed values and
the expected values with regard to the postulated model. Bollen and Long (1993) explain that for
models with 75 to 200 cases, the χ2 test provides for a
reasonable measure of fit. The
significance of the χ2 test for goodness of fit value is
determined by examining the χ2 statistic (here, χ2
= 30.779), the predetermined alpha level of significance (α = 0.05), and
the degrees of freedom of the model (here, df
= 25). Given these values (and a
critical value of the χ2 statistic of 37.653) for a model with
25 degrees of freedom (Hill & Lewicki, 2007), the null hypothesis indicating
that business performance is independent of the establishment of alliances and
that neither the proximity to resources nor organizational culture have an
impact on the establishment of alliances.
Moreover, in table nine an examination of the fit
model is done using the comparative fit index (CFI). The CFI compares the fit of the model we
developed to the fit of a null model, in which the variables are assumed to be
uncorrelated. With values exceeding
0.930 (Byrne, 1994), it is considered to be an acceptable fit, and the current
model is deemed to be a better model than the null. In this case, the CFI was 0.968 implying that
the model fits the data collected better than the null. This challenges the original notion that
local alliances are the only acceptable form of alliances to achieve firm
performance. The CFI indicates that the
presence of virtual alliances is significant in predicting and influencing firm
performance.
Lastly, the root mean square of approximation
(RMSEA) and the standardized root mean square residual (SRMR) were also
examined. The RMSEA had a measurement of
0.033 indicating a good fit, according to MacCullum et al. (1996). The SRMR also ranges from zero to 1.0, with
well fitting models attainable at 0.05 (Byrne, 1998). The aforementioned model has a SRMR of 0.035,
which again indicates a good model fit.
Table
9: Model Fit Indices
|
Fit Statistic |
Value |
|
χ2 |
30.779 |
|
CFI |
0.968 |
|
RMSEA |
0.033 |
|
SRMR |
0.035 |
Conclusively, the significance of alliances is a
positive predictor of the establishment of alliances and the establishment of
alliances is a positive predictor of firm performance. This conclusion is based upon the adequate
fit of our model to the data and the significance of the t-Values associated
with the path coefficients demonstrated in table nine. Thus, the two hypotheses of this study are
supported and the model is valid.
Implications
Of The Research
Although this study was geared toward the acknowledgement
of local alliances as a contributing factor to entrepreneurial and innovative
development., the research suggests that there are different types of alliances
and knowledge generators that encourage spillover. The analyses clearly demonstrate the need for
alliances in organizational decision making, and ultimately firm
performance. However, the studies’ mere
glimpse into types of alliances shows the inclusion of virtual alliances as a
supplemental knowledge generator, and possible contributor to nurturing an
innovative culture within an organization.
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About the Authors:
Dr. Sarit J. Levy has been in the
academic and business environments for many years. She holds a Ph.D. in
Business Administration from Touro University International, as well as a M.S.
in management engineering and computer science from
Dr. Sarit J. Levy, Department of Marketing,
University of Miami, School of Business Administration, 5250 University Drive,
501 Kosar Epstein Bldg, Coral Gables, Fl 33124-6554; Email: slevy@bus.miami.edu
Mr. Aaron Joyal is a Canadian born
academic, and is currently completing his doctorate at the
Aaron D. Joyal, 426 Fogleman College of Business and Economics, University of Memphis, 3675 Central Avenue, Memphis, TN 38152; Email: adjoyal@memphis.edu
.