The competitive environment is an external impact factor that can be examined using Michael Porter's strategy. In this resource, locate Porter's three generic strategies impacting a firm's performance. Create a chart, and then choose one of the brands you have examined in the branding section. Apply these options to each brand and conclude which is the best match. To apply the concepts to real scenarios in brand management, complete the exercises in the boxes. Use your notebook to create 2-3 sentence answers to the challenge questions. You must refer back to key concepts in the resource and charts when included.
Porter's generic strategies are applicable in the competitive environment; we have tested the competing environment of respondent firms. Table 3 shows the data for the competitive environment in which respondent firms operate. In the questions presented in Table 3, the participants had five scales to present their competing environment from 1 - not at all competing environment to 5 - extremely competing environment. From this table, it can be seen that the highest assessment by the respondent firms has taken the ascertainment "products/services are similar in the market" which is evaluated on average with 4.39 from 5 that was the maximal evaluation, while the lower evaluation has taken ascertainment "a small number of firms are dominant in the market" on average with 2.63 by 5 that was the maximal evaluation. By these results, the answer is found for the first research question: Are the respondent firms operating in the competitive industry? So, the environment where the respondent firms operate is a competitive environment, and these results provide the needed conditions to go further with hypotheses testing that derives by the third section of this study (Table 4).
Table 3 Firm's responses for competing environment.
Study of environment variables |
Minimum |
Maximum |
Mean |
Std. deviation |
---|---|---|---|---|
A small number of firms are dominant in the market |
1 |
5 |
2.63 |
1.775 |
Products/services are similar in the market |
1 |
5 |
4.29 |
1.151 |
A large number of firms offer similar products/services |
1 |
5 |
4.26 |
1.144 |
In our industry, there is a decrease in requirement |
1 |
5 |
3.48 |
1.617 |
Obstacles to get out of market are high |
1 |
5 |
3.03 |
1.367 |
Study variables |
Minimum |
Maximum |
Mean |
Std. deviation |
---|---|---|---|---|
LCS |
2 |
5 |
3.91 |
0.713 |
DS |
3 |
5 |
4.29 |
0.776 |
FS |
1 |
5 |
3.75 |
0.770 |
FP |
2 |
5 |
3.81 |
0.991 |
Descriptive data are minimum, maximum, mean, and standard deviation, for all independent variables and dependent variable that are part of this research.
A "Cronbach's alpha" test was used to evaluate the reliability of the factors as suggested by Nunnally. Cronbach's alpha can be considered an adequate index of the inter-item consistency reliability of independent and dependent variables. Nunnally suggests that constructs should have reliability values 0.7 or greater. Table 5 shows the relationship between the items that are measured, deliberately to see which factors have the highest relationship, and that can be represented by a single variable. The reliabilities for each of the four constructs were adequate since the Cronbach's alpha values for each were significantly greater than the prescribed 0.7 threshold. So, in this study the values varied from 0.734 (focus strategy) to 0.894 (firm performance), showing that the instruments are sufficiently reliable. Variables LCS2, LCS4, FS1, and FS3 are moved from further analyses because they have reliability value lower than (< 0.7). In order to see which factors are included within each Porter's generic strategy, which enables us to test the hypotheses of this research paper, Cronbach's alpha test is performed for reliability (Table 5).
Table 5 Statistical highlights - Cronbach's alpha test for reliability
Low-cost strategy |
Differentiation strategy |
Focus strategy |
Firm performance |
||||
---|---|---|---|---|---|---|---|
Cronbach's alpha test for reliability |
|||||||
0.760 |
0.779 |
0.734 |
0.894 |
||||
Remaining items with loading values > 0.7 |
|||||||
LCS1 |
0.767 |
DS1 |
0.750 |
FS1 |
0.754 |
PS1 |
0.866 |
LSC2 |
0.564x |
DS2 |
0.750 |
FS2 |
0.621x |
PS2 |
0.871 |
LCS3 |
0.715 |
DS3 |
0.700 |
FS3 |
0.619x |
PS3 |
0.880 |
LCS4 |
0.597x |
DS4 |
0.771 |
PS4 |
0.873 |
||
LCS5 |
0.767 |
DS5 |
0.793 |
PS5 |
0.875 |
||
LCS6 |
0.712 |
DS6 |
0.765 |
PS6 |
0.889 |
||
DS7 |
0.712 |
Variables |
Correlations |
LCS |
DS |
FS |
FP |
---|---|---|---|---|---|
LCS |
Pearson's correlation |
1 |
|||
Sig. (two-tailed) |
|||||
DS |
Pearson's correlation |
0.233* |
1 |
||
Sig. (two-tailed) |
0.074 |
||||
FS |
Pearson's correlation |
0.527*** |
0.119 |
1 |
|
Sig. (two-tailed) |
0.000 |
0.355 |
|||
FP |
Pearson's correlation |
0.499*** |
0.337*** |
0.433*** |
1 |
Sig. (two-tailed) |
0.000 |
0.007 |
0.000 |
Table 7 Regression analysis of dependent variable "Firm performance," n = 113.
Model |
R2 |
ΔR2 |
β |
b |
S.E |
F |
t |
p |
---|---|---|---|---|---|---|---|---|
0.671 |
0.632 |
9.976 |
||||||
(Constant) |
0.448 |
0.800 |
0.560 |
0.038 |
||||
LCS |
0.245 |
0.312 |
0.141 |
2.207 |
0.031 |
|||
DS |
0.312 |
0.439 |
0.182 |
2.410 |
0.019 |
|||
FS |
0.246 |
0.315 |
0.163 |
1.934 |
0.028 |