Performance Factors of Czech Companies Identified Using Statistical Pattern Recognition: Interpretation of Results

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Performance Factors of Czech Companies Identified Using Statistical Pattern Recognition: Interpretation of Results

Appendix A 1. Results

In the further text, m denotes mean of the dependent variable and p denotes p-value. To remind to the reader, dependent variable is measured as return on assets and growth of assets between 2004-2010 (up to two missing values accepted), standardised into z-scores and summed up. Therefore, the higher m, the better performance of a company or a subsample.

Because the standardisation was carried out for each year individually, the mean corporate financial performance of the full sample is not zero, but it is m = 0.267 (standard deviation 0.976).

Descriptive statistics of the sample can be found in the following two tables. Second column shows frequencies, which are more important for categorical variables. Fourth to eight columns give appropriate values of corporate financial performance in subsets defined by these categorical variables. This is quite important when assessing first- and second-order relationships with CFP in further text. Zero-order relationships to CFP are analysed in the main text of the paper.

Table 4: Descriptive statistics: CFP in subsets defined by categorical independent variables

Variable N

Mean Median Std.

deviation Min. Max.

Valid Missing

Cost Leadership 81 5 0.10 0.17 0.92 -2.37 2.93

Differentiation 103 5 0.14 0.09 0.97 -2.99 2.71

Cost Focus 66 2 0.26 0.22 0.85 -1.95 1.90

Differentiation Focus 103 7 0.46 0.36 1.04 -3.01 3.62

Focus Yes 169 9 0.38 0.31 0.97 -3.01 3.62

Focus No 184 10 0.13 0.12 0.95 -2.99 2.93

Cost strategies 147 7 0.17 0.17 0.89 -2.37 2.93

Differentiation strategies 206 12 0.30 0.15 1.02 -3.01 3.62

FDI No 254 13 0.31 0.17 0.97 -2.37 3.62

FDI Yes 96 6 0.21 0.17 0.93 -3.01 2.07

Export No 89 5 0.45 0.34 1.00 -2.34 3.54

Export Yes 290 15 0.18 0.09 0.98 -3.01 3.62

Source: Author’s calculations.

The next table gives descriptive statistics of scale variables. Zero-order relationships to CFP are analysed in the main text of the paper.

Table 5: Descriptive statistics: dependent and independent scale variables

Variable N

Mean Median Std.

dev. Min. Max.

Valid Miss.

Corporate financial performance 411 21 0.27 0.16 0.98 -3.01 3.62 Share of Top Management

Performance Pay on total remuneration

368 64 34.39 33.30 20.02 0.00 100.00

2/12 Share of Workers’ Performance

Pay on total remuneration 368 64 26.73 23.55 17.87 0.00 100.00 Source: Author’s calculations.

Finally, before we proceed to the analyses of higher-order relationships, following table gives associations among the independent variables. Given their mostly categorical nature, Cramer´s V was chosen as the association coefficient. Share of Top Management Performance Pay on Total Remuneration and Share of Workers’ Performance Pay on Total Remuneration were recoded into below average and above average categories for this purpose. The only exception is correlation between these two variables, which was computed as Spearman´s rho using the original values. The associations (correlations) found are generally weak, if any at all.

Table 6: Zero-order relationships among the independent variables

St ra te gy (G en er ic ) St ra te gy (F oc us Y es /N o) St ra te gy (Cos t vs . D iff. ) FD I (Y es /N o) E xpor t (Y es /N o) T op M an age m ent Pe rform an ce P ay W ork er s’ Pe rform an ce P ay

Strategy (Generic)

Cramer´s V 1.00

Sig. (2-tailed)

N 372

Strategy (Focus Yes/No)

Cramer´s V 1.00 1.00

Sig. (2-tailed)

N 372 372

Strategy (Cost vs. Diff.)

Cramer´s V 1.00 1.00 1.00

Sig. (2-tailed)

N 372 372 372

FDI (Yes/No)

Cramer´s V 0.16

0.11

0.05 1.00

Sig. (2-tailed) .048 .055 .355

N 315 315 315 369

Export (Yes/No)

Cramer´s V 0.19

0.16

0.06 0.18

1.00

Sig. (2-tailed) .005 .002 .269 .001

N 346 346 346 342 399

Top Management Performance Pay (below average/above average)

Cramer´s V 0.08 0.05 0.06 0.14

0.06 1.00 Sig. (2-tailed) .532 .365 .289 .015 .297

N 320 320 320 313 345 368

Workers’ Performance Pay (below average/above average)

Cramer´s V 0.05 0.05 0.01 0.11

0.16

0.23

1.00 Sig. (2-tailed) .854 .409 .930 .059 .003 .000

N 318 318 318 316 345 357 368

Source: Author’s calculations.

a

Spearman´s correlation coefficient between the original values of these variables (before recoding into below average/above average.

*

denotes p-value <0.1,

denotes p-value <0.05,

denotes p-value <0.01.

3/12 1.1. FDI

The CFP without FDI (m = 0.31) is slightly higher than the sample average, whereas CFP with FDI (m = 0.21) is slightly lower than the average. This difference, however, is not statistically significant.

When dividing the sample according to the Strategy pursued, one can observe a totally opposite trend among companies pursuing the Cost Leadership strategy, where the companies without FDI are considerably less efficient (m = -0.10, N = 59) than the companies with FDI (m = 0.44, N = 9). Again, the difference is not statistically significant because of the low and uneven number of observations. In companies pursuing other strategies, the direction of the effect of FDI is the same as in the whole sample. Companies are distributed more evenly among the strategies and based on the presence of FDI, but only for businesses pursuing the Differentiation Focus strategy the difference between the companies without FDI (m = 0.67, N = 63) and with FDI (m = 0.16, N = 24) is large enough to be statistically significant (p = 0.05). Further analyses show (see below) that the businesses using the Cost Leadership strategy are among the least efficient, while the businesses using the Differentiation Focus strategy are among the most efficient. Furthermore, the businesses pursuing the Focus strategies that lack FDI are significantly more efficient (m = 0.54, N = 10) than those with FDI (m = 0.21, N = 43). Given the number of observations, the difference can be considered statistically significant (p = 0.06). Dividing the companies into those pursuing Differentiation strategies and Cost strategies changes the effect of FDI as follows. Differentiation strategies magnifies the effect of FDI, therefore companies pursuing Differentiation strategies without FDI have higher CFP (m = 0.41, N = 126) than those in the full sample and companies with FDI have lower CFP (m = 0.13, N = 46). Cost strategies reverse the effect of FDI and companies without FDI are underperforming (m = 0.13, N = 98) and companies with FDI are rather average (0.31 N = 28). These effects are however not statistically significant.

When dividing the sample according to whether or not the companies export, only a minimum of enterprises where FDI is present, do not export (N = 8). This division does not alter the shape of the effect of FDI on the CFP in any way; only if combining the aspect of Export and Strategy pursued, the previously observed difference between the companies that use the Cost Leadership strategy without FDI and with FDI, which was not statistically significant, is stronger and statistically significant (p = 0.02) in exporting companies. It is important that exporting companies without FDI pursuing the Cost Leadership strategy are less efficient (m

= -0.12, N = 35) than those with FDI (m = 0.62, N = 8), which is an opposite trend than in the rest of the sample. In the other subsets created by combining the strategy aspects (Focus Yes/No, Cost/Differentiation) and Export, the shape of the relationship between FDI and CFP is again similar to the situation when only the strategy aspect is used, but with one exception:

a small number (N = 8) of non-exporting companies with FDI does not allow an assessment of them.

The effort to motivate top management and workers through performance pay changes the

effect of FDI on CFP in companies with above-average share of performance pay on the total

remuneration. If the share of performance pay is below average, the effect of FDI on CFP is

similar to the one found in the full sample. If the share of performance pay is above average,

the effect of FDI is reversed for both top management and workers, resulting in companies

without FDI having slightly lower CFP than companies with FDI.

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Table 7: Effect of FDI on mean CFP in subsets defined by chosen variables Strategy

Cost Leadership Differentiation Cost Focus Differentiation Focus FDI No

Yes

0.10 (59) 0.44 (9)

0.15 (63) 0.09 (22)

0.34 (39) 0.26 (19)

0.67 (63)*

0.16 (24)*

Strategy Both focused

strategies Both not-focused

strategies Both differentiation

strategies Both cost strategies FDI No

Yes

0.54 (102)*

0.21 (43)*

0.07 (122) 0.19 (31)

0.41 (126) 0.13 (46)

0.13 (98) 0.32 (28) Export

No Yes

FDI No Yes

0.45 (66) 0.45 (8)

0.24 (174) 0.16 (76) Share of Top Management

Performance Pay on total remuneration

Share of Workers’ Performance Pay on total remuneration

Below average Above average Below average Above average FDI No

Yes

0.37 (102) 0.14 (49)

0.29 (114) 0.35 (30)

0.28 (125) 0.03 (53)

0.43 (94) 0.50 (26) Source: Author’s calculations.

Values represent mean CFP in the given subset. Moderators are in columns. Number of observations in brackets. * denotes two-tailed p-value <0.1.

1.2. Export

The share of Export shows a relationship to CFP only if measured as Yes/No (p = 0.03). The number of completely non-exporting companies is 89 from 376, for which these data are available. The average CFP of non-exporting companies (m = 0.45) is significantly higher than the average CFP of exporting companies (m = 0.18).

When dividing the sample based on the presence of FDI, the differences between exporting and non-exporting companies are very similar as in the entire sample. Thus, FDI neither questions the effect of the variable Export on CFP, nor modifies this effect in any way.

The Strategy pursued changes the effect of Export on CFP only for companies using the Differentiation and Cost Focus strategies. If companies pursue the Differentiation strategy and Export, their CFP is much worse than average. Without exporting the CFP while using this strategy is the same as in the full sample (p = 0.06). When pursuing the Cost Focus strategy, no differences between non-exporting and exporting companies are observed. Because the differences between exporting and non-exporting companies are similar for the remaining two strategies, as in the full sample, one can say that a variable Strategy does not question the effect of the variable Export on CFP either, but modifies this effect.

When classifying companies into those with and without the Focus strategies, or companies pursuing the Cost and Differentiation strategies, differences similar to those observed at the level of the four generic strategies emerge (see above). The effect of Export on CFP does not differ between subsets with and without the Focus strategies, or compared to the full sample.

The effect of Export on CFP is statistically significant in both the categories (p = 0.10 and p = 0.08). For businesses with the Cost strategies, the difference between exporting and non- exporting companies decreases; on the contrary, for companies with the Differentiation strategies the difference increases and is statistically significant (p = 0.02).

When dividing the sample depending on the presence of FDI and the Strategy pursued, one

cannot assess the effect of Export on CFP in the group of companies with FDI, because only 8

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businesses with FDI do not export. For companies without FDI, the effect of Export on CFP remains approximately the same as for using only the aspect of Strategy pursued. The effect of Export on CFP changes to the opposite only for companies pursuing the Cost Focus strategy and exporting companies without FDI become significantly more efficient (m = 0.32, N = 30) than the non-exporting ones in this subset (m = 0.15, N = 6) as well as the exporting ones in the entire sample (m = 0.18, N = 290).

When dividing the sample depending on the presence of FDI and the Strategy pursued of Focus Yes/No, the small number (N = 8) of non-exporting companies with FDI does not allow an assessment of them. For companies without FDI, the effects of variable Focus Yes/No and Export add up, so both non-exporting and exporting companies without FDI pursuing the Focus strategies perform better than companies pursuing the Focus strategies in general, all companies without FDI in general, as well as all companies in the full sample. In the opposite direction of the effects, the same holds true for companies without FDI that do not pursue the Focus strategies; no matter if they are exporting or non-exporting, their CFP is lower than the CFP of companies without FDI in general, companies that do not pursue the Focus strategy in general or all companies in the full sample.

When dividing the sample depending on the presence of FDI and the pursued Strategy of Cost/Differentiation, the small number (N = 8) of non-exporting companies with FDI does not allow an assessment of them. For businesses without FDI, the effects of Export on CFP in the groups of companies pursuing the strategies of Cost and Differentiation are identical with the effects of Export on CFP without taking into account the presence of FDI.

The effort to motivate top management and workers through performance pay does not significantly change the effect of Export on CFP.

Table 8: Effect of Export on mean CFP in subsets defined by chosen variables Strategy

Cost Leadership Differentiation Cost Focus Differentiation Focus Export No

Yes

0.22 (28) 0.04 (50)

0.47 (24)*

0.07 (72)*

0.22 (8) 0.22 (51)

0.86 (17)*

0.34 (78)*

Strategy Both focused

strategies Both not-focused

strategies Both differentiation

strategies Both cost strategies Export No

Yes

0.66 (25)*

0.29 (129)*

0.34 (52)*

0.05 (122)*

0.63 (41)**

0.21 (150)**

0.22 (36) 0.13 (101) FDI

No Yes

Export No Yes

0.45 (66) 0.24 (174)

0.45 (8) 0.16 (76) Share of Top Management

Performance Pay on total remuneration

Share of Workers’ Performance Pay on total remuneration

Below average Above average Below average Above average Export No

Yes

0.35 (43) 0.20 (118)

0.52 (35)*

0.19 (130)*

0.32 (36) 0.15 (162)

0.54 (41)*

0.24 (87)*

Source: Author’s calculations.

Values represent mean CFP in the given subset. Moderators are in columns. Number of observations

in brackets. * denotes two-tailed p-value <0.1, ** denotes two-tailed p-value <0.05.

6/12 1.3. Top Management Performance Pay

Top Management Performance Pay does not affect CFP at the zero-order level. Partial correlations do not reveal any relationship with CFP either. Conversely, examining the variables moderating the correlation between Top Management Performance Pay and CFP shows that Top Management Performance Pay affects CFP, but only in certain groups of businesses. Moreover, the effects in these groups vary significantly. The division of the sample based on the presence of FDI, Export and pursuing the Focus Yes/No strategies does not change the effects of Top Management Performance Pay. However, the effects occur in the companies pursuing both of the Cost strategies (r

= -0.14, p = 0.10, N = 126), which probably results from a stronger effect in the companies pursuing the Cost Focus strategy (r

= -0.30, p = 0.03, N = 55). Even a stronger effect appears when dividing the sample using the aspect of Strategy and Export at the same time. Top Management Performance Pay affects CFP in a relatively strong and positive way in non-exporting companies pursuing the Differentiation strategy (r

= 0.40, p = 0.08, N = 21) and in a strong and negative way in non- exporting companies pursuing the Cost Focus strategy (r

= -0.75, p = 0.08, N = 6). The relationship is slightly weaker and of the same direction in exporting companies pursuing the Cost Focus strategy (r

= -0.26, p = 0.09, N = 43). Similarly, this relationship is weaker and positive in exporting companies pursuing the Differentiation Focus strategy (r

= 0.20, p = 0.11, N = 67), and the effect is the same in non-exporting companies pursuing the Differentiation strategy.

Table 9: Correlations of Share of Top Management Performance Pay with CFP in subsets defined by chosen variables

Strategy Cost

Leadership Differentiation Cost Focus Differentiation Focus Share of Top Management

Performance Pay -0.01 (71) 0.05 (81) -0.30 (55)** 0.09 (88) Strategy

Both focused strategies

Both not- focused strategies

Both differentiation

strategies

Both cost strategies Share of Top Management

Performance Pay -0.07 (143) 0.03 (159) 0.06 (176) -0.14 (126)*

Share of Workers’ Performance Pay

Below average Above average Share of Top Management

Performance Pay -0.08 (203) 0.04 (209)

FDI Export

No Yes No Yes

Share of Top Management

Performance Pay -0.07 (216) 0.12 (79) 0.03 (78) -0.02 (248) Source: Author’s calculations.

Values represent Spearman´s rho. Moderators are in columns. Number of observations in brackets. *

denotes two-tailed p-value <0.1, ** denotes two-tailed p-value <0.05.

7/12 1.4. Workers’ Performance Pay

Workers’ Performance Pay does not affect CFP at the zero-order level. When examining partial correlations, no relationship with CFP was revealed either. Conversely, when examining the variables moderating the correlation between Workers’ Performance Pay and CFP, Workers’ Performance Pay affects CFP, but only in certain groups of companies. This effect applies primarily to companies that do not pursue the Focus strategies (r

= 0.16, p = 0.05, N = 157), companies pursuing both of the Differentiation strategies (r

= 0.13, p = 0.10, N = 175), and companies that do not export at all (r

= 0.21, p = 0.07, N = 77). Combining these criteria, the effects of Workers’ Performance Pay on CFP become stronger. The power of the relationship reaches even r

= 0.55 (p = 0.01, N = 21) in non-exporting companies pursuing the Differentiation strategy. Exporting companies using this strategy seem to show negative, but statistically insignificant effects of Workers’ Performance Pay. The examined relationship also applies more strongly in non-exporting companies that do not pursue the Focus strategies (r

= 0.37, p = 0.01, N = 44) and in companies with FDI that do not pursue the Focus strategies (r

= 0.41, p = 0.03, N = 23).

Table 10: Correlations of Share of Workers’ Performance Pay with CFP in subsets defined by chosen variables

Strategy Cost

Leadership Differentiation Cost Focus Differentiation Focus Share of Workers’

Performance Pay 0.14 (71) 0.16 (86) -0.06 (54) 0.08 (89)

Strategy Both focused

strategies

Both not- focused strategies

Both differentiation

strategies

Both cost strategies Share of Workers’

Performance Pay 0.03 (143) 0.16 (157)** 0.13 (175)* 0.06 (125) Share of Top Management

Performance Pay

Below average Above average Share of Workers’

Performance Pay 0.05 (166) 0.17** (171)

FDI Export

No Yes No Yes

Share of Workers’

Performance Pay 0.09 (219) 0.08 (79) 0.21 (77)* -0.03 (249) Source: Author’s calculations.

Values represent Spearman´s rho. Moderators are in columns. Number of observations in brackets. * denotes two-tailed p-value <0.1, ** denotes two-tailed p-value <0.05.

1.5. Strategy

Concerning the strategies, businesses pursuing the Differentiation Focus strategy show the

highest CFP (m = 0.46). Companies with the Cost Focus strategy (m = 0.26), and companies

with the Differentiation strategy (m = 0.14) follow. Companies using the Cost Leadership

strategy report the lowest CFP (m = 0.10). Differences are statistically significant between the

strategies of Cost Leadership and Differentiation Focus (p = 0.07) and between the strategies

of Differentiation and Differentiation Focus (p = 0.10). The difference between the two Cost

strategies (m = 0.17) and the two Differentiation strategies (m = 0.3) is not statistically

significant, but the difference between the businesses with the Focus strategies that have

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higher average CFP (m = 0.38) than the companies without the Focus strategies that have lower average CFP (m = 0.13) is statistically significant (p = 0.01).

When dividing the sample depending on the presence of FDI in a company, companies without FDI show the same order of success rates of strategies as the entire sample. However, CFP is now lower (m = -0.10) for companies without FDI pursuing the Cost Leadership strategy than in the whole sample (m = 0.10), almost the same for companies using the Differentiation strategy, and higher for companies using the other strategies than in the whole sample: Cost Focus (m = 0.34) and Differentiation Focus (m = 0.67). The differences between the strategies of Differentiation Focus and Cost Leadership (p = 0.01) as well as between Differentiation Focus and Differentiation (p = 0. 02) are still statistically significant. One can see that the presence of FDI helps the companies pursuing Cost Leadership strategy to become the most successful (m = 0.44) while the presence of FDI rather hurts the companies pursuing other strategies, namely the Differentiation Focus strategy, which is most hurt compared to the CFP of all companies pursuing this strategy (m = 0.16 vs. m = 0.46).

However, the differences in CFP among the strategies pursued by companies with FDI are not statistically significant. Also, the differences in the CFP of companies with the Focus strategies and without these strategies remain substantively and statistically significant (p = 0.01) only for businesses without FDI, whereas they are eliminated for companies with FDI, and similar findings apply to pursuing strategies of Cost and Differentiation (p = 0.03 for businesses without FDI). Hence, the FDI variable modifies the effect of the pursued Strategy on CFP. A stringent conclusion is that this effect is true only in companies without FDI, or one can assume that the low number of observations in these categories (N = 8-24) causes the insufficient p-value for the significance of differences in strategies pursued by companies with FDI.

When dividing the sample based on the aspect of Export, the differences among the individual strategies cease to be statistically significant, unlike in the entire sample. Such a finding is generally a reason for interpreting that the zero-order relationship between Strategy and CFP is only apparent and that Export explains the variability of CFP instead. However, closer examination shows that this conclusion may not be true. In the group of exporting companies (N = 251), the order of strategies does not change depending on their success; their average success rates are only lower than in the whole sample, and the differences are slightly smaller.

The statistical insignificance of the differences among these averages is probably caused by low numbers of observations (N = 50-78): in general, the smaller the substantive differences are, the greater sample is needed for evaluating the differences as statistically significant.

Another option to explain the statistical insignificance would be significant variability in the observed values; however, standard deviation in the entire sample is similar to standard deviation for exporting companies. The differences between the companies pursuing the Focus strategies and others also remain similar as in the full sample, and this difference is statistically significant (frequencies in these two groups are obviously higher than the frequencies in groups when divided into the four strategies).

Again, in non-exporting companies (N = 77) the differences among the success rates of the

four generic strategies are not statistically significant, but the numbers of observations are

even lower here (N = 8-28). Substantive differences are primarily between the Cost and

Differentiation strategies; this difference is statistically significant considering the low

number of observations (p = 0.08). While the strategies of non-exporting companies focusing

on low cost are similarly successful (m = 0.22) as the strategies of exporting companies (m =

0.13), Differentiation strategies are considerably more successful in non-exporting companies

(m = 0.63) than in exporting ones (m = 0.21). Therefore, the decision not to export turns out

to be successful for businesses pursuing the Differentiation strategies.

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When combining the aspects of Export and FDI, the small number (N = 8) of non-exporting companies with FDI does not allow an assessment of them. Non-exporting companies without FDI have a lower success rate of the Cost strategies and a greater success rate of the Differentiation strategies, which is in line with the zero-order impact of the Export aspect.

The differences are statistically significant (p = 0.08). Thus, the modifying effect of Export is stronger here than the effect of FDI. In the group of exporting companies without FDI, performances of the strategies are very similar to those in the full sample. The Focus strategies are slightly more successful than in the full sample, which is again in line with the impact of Export, which outweighs the effect of FDI. The differences among the performances of the strategies in exporting companies without FDI are also statistically significant (p = 0.01). An obvious effect of FDI on the relationship between the Strategies pursued and CFP is in exporting companies with FDI where – for example when controlling only for the impact of FDI – the Cost Leadership strategy has significantly higher performance compared to the full sample, performance of the Cost Focus strategy remains unchanged, but both the Differentiation strategies have lower performance (significantly lower for Differentiation Focus). Thus, the effect of the presence of FDI clearly predominates here over the effect of the Export aspect. The differences among the performances of the individual strategies are not statistically significant, but the small number of observations (N

= 8-22) might be again the reason.

Share of Top Management Performance Pay changes the success of different strategies as follows: companies with below average Share of Top Management Performance Pay pursuing Cost Leadership (m = - 0.06) and Differentiation Focus (m = 0.35) strategies are worse off than companies with the same strategies in full sample, whereas companies pursuing Differentiation (m = 0.23) and Cost Focus (m = 0.57) strategies are better off. Companies with above average Share of Top Management Performance Pay achieve different results:

Cost Leadership (m = 0.23) strategy pays off better, while Cost Focus (m = 0.06) does not and Differentiation (m = 0.12) and Differentiation Focus (m = 0.48) are about the same as in the full sample. Effect of Strategy measured as both Focused and both Not Focused is a little stronger among companies with below average and a little weaker among companies with above average Share of Top Management Performance Pay on total remuneration. Effect of Strategy measured as Both Differentiation and Both Cost is a little weaker in both categories (below average/above average).

If the Share of Workers’ Performance Pay is below average, companies pursuing Cost Leadership (m = -0.12), Differentiation (m = 0. 04) and Differentiation Focus (m = 0.36) are worse off than companies pursuing the same strategies in the full sample. Only companies pursuing Cost Focus strategy (m = 0.37) are better off. If the Share of Workers’ Performance pay is above average, all companies are better off, regardless of their strategy. Effect of Strategy measured as both Focused and both Not Focused is a little stronger among companies with below average and about the same among companies with above average Share of Workers’ Performance Pay on total remuneration. Effect of Strategy measured as Both Differentiation and Both Cost is about the same among companies with below average Share of Workers’ Performance Pay and a little weaker among companies with above average Share of Workers’ Performance Pay.

The Strategy pursued shows no relationship to Top Management Performance Pay and

Worker Performance Pay. Conversely, the individual strategies and dividing the strategies to

Focus Yes/No are significantly associated with the presence of FDI and Export. Companies

with foreign capital are less likely to focus on the Cost Leadership strategies as they prefer the

Cost Focus strategies (p = 0.05), which also further implies their frequent choice of the Focus

strategies (p = 0.06). Similarly, exporting companies more often pursue the Cost Focus

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strategy as well as the Differentiation Focus strategy (p = 0.01), which therefore implies their frequent choice of the Focus strategies (p = 0.01).

Table 11: Effect of generic Strategy on mean CFP in subsets defined by chosen variables

FDI Export

No Yes No Yes

Strategy

Cost Leadership Differentiation Cost Focus

Differentiation Focus

-0.01 (59)

0.15 (63)

0.34 (39) 0.67 (63)

0.44 (9) 0.09 (22) 0.26 (19) 0.16 (24)

0.22 (28) 0.47 (24) 0.22 (8) 0.86 (17)

0.04 (50) 0.07 (72) 0.22 (51) 0.34 (78) Share of Top Management

Performance Pay on total remuneration

Share of Workers’

Performance Pay on total remuneration Below

average

Above average

Below average

Above average

Strategy

Cost Leadership Differentiation Cost Focus

Differentiation Focus

-0.06 (36)

0.23 (39) 0.57 (30)

0.35 (45)

0.23 (35) 0.12 (49) 0.06 (25) 0.48 (43)

-0.12 (43)

0.04 (48) 0.37 (33)

0.36 (54)

0.32 (28) 0.21 (38) 0.37 (21) 0.60 (35) Source: Author’s calculations.

Values represent mean CFP in the given subset. Moderators are in columns. Number of observations in brackets.

denote differences between subsets significant at p-value at least 0.1 (two-tailed).

Table 12: Effect of Strategy (Focus yes/no) on mean CFP in subsets defined by chosen variables

FDI Export

No Yes No Yes

Strategy Both Focused Both Not Focused

0.54 (102)***

0.07 (122)***

0.21 (43) 0.19 (31)

0.66 (25) 0.34 (52)

0.29 (129)*

0.05 (122)*

Share of Top Management Performance Pay on total

remuneration

Share of Workers’

Performance Pay on total remuneration Below

average

Above average

Below average

Above average Strategy Both Focused

Both Not Focused

0.44 (75)**

0.09 (75)**

0.32 (68) 0.17 (84)

0.36 (87)***

-0.04 (91)***

0.51 (56) 0.25 (66) Source: Author’s calculations.

Values represent mean CFP in the given subset. Moderators are in columns. Number of observations in brackets. * denotes two-tailed p-value <0.1, ** denotes two-tailed p-value <0.05, *** denotes two- tailed p-value <0.01.

Table 13: Effect of Strategy (Differentiation/Cost) on mean CFP in subsets defined by chosen variables

FDI Export

No Yes No Yes

Strategy Both Differentiation Both Cost

0.41 (126)**

0.13 (98)**

0.13 (46) 0.32 (28)

0.63 (41)*

0.22 (36)*

0.21 (150) 0.13 (101) Share of Top Management

Performance Pay on total remuneration

Share of Workers’

Performance Pay on total remuneration Below

average

Above average

Below average

Above

average

11/12 Strategy Both Differentiation

Both Cost

0.30 (84) 0.23 (66)

0.29 (92) 0.16 (60)

0.21 (102) 0.09 (76)

0.39 (73) 0.34 (49) Source: Author’s calculations.

Values represent mean CFP in the given subset. Moderators are in columns. Number of observations in brackets. * denotes two-tailed p-value <0.1, ** denotes two-tailed p-value <0.05.

1.6. Summary of moderating effects

The tables bellow show effects of variables in rows on CFP in subsets defined by variables in columns compared to the effect in the full sample. Therefore, if the effect in the full sample is for example weak negative and in a specific subset weak positive, the table shows ↑↑, meaning the effect in the subset is distinctively more positive than in the full sample. Cells containing sign ↔ mean that there was no moderating effect of the variable in column, in other words the effect in subset is approximately the same as in the full sample. A concrete example is the effect of pursuing Cost Leadership strategy. Companies with this strategy experience higher CFP if they are owned by a foreign entity (m = 0.44) than if they are domestically owned (m = 0.10). This is distinctively different from the effect of FDI in the full sample (m = 0.31 in companies without FDI and 0.21 in companies with FDI).

Table 14: Summary of moderating effects first part

Ful l s am pl e effe ct

Strategy Strategies Strategies FDI Export TMPP WPP

Cos t L ea de rs hi p D iffe re nt ia ti on Cos t F oc us D iffe re nt ia ti on F oc us Bot h foc us ed Bot h not -foc us ed Bot h D iff ere nt ia tion Bot h Cos t No Y es No Y es Be low a ve ra ge A bove a ve ra ge Be low a ve ra ge A bove a ve ra ge

FDI ↓ ↑↑ ↔ ↔ ↓↓ ↓↓ ↑↑ ↓ ↑↑ n/a n/a ↑ ↔ ↔ ↑ ↓ ↑

Export ↓ ↔ ↓ ↑ ↓↓ ↓ ↔ ↓ ↔ ↔ ↔ n/a n/a ↑ ↔ ↑ ↔

TMPP ↔ ↔ ↔ ↓↓ ↑ ↔ ↔ ↔ ↓ ↔ ↑ ↔ ↔ n/a n/a ↔ ↔

WPP ↔ ↔ ↑ ↓ ↔ ↔ ↑ ↔ ↔ ↔ ↔ ↑ ↓ ↔ ↑ n/a n/a

Source: Author’s calculations.

↑ The effect in the subset is more positive than in the full sample.

↑↑ The effect in the subset is distinctively more positive than in the full sample.

↓ The effect in the subset is more negative than in the full sample.

↓↓ The effect in the subset is distinctively more negative than in the full sample.

↔ The effect in the subset is about the same as in the full sample.

TMPP stands for the Share of Top Management Performance Pay on total remuneration

WPP stands for the Share of Workers´ Performance Pay on total remuneration

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Table 15: Summary of moderating effects second part (Strategies)

Ful l s am pl e effe ct FDI Export TMPP WPP

No Y es No Y es Be low a ve ra ge A bove a ve ra ge Be low a ve ra ge A bove a ve ra ge

Cost Leadership ↓ ↓ ↑↑ ↑ ↔ ↓ ↑ ↓↓ ↑↑

Differentiation ↓ ↔ ↓ ↑↑ ↔ ↑ ↔ ↓ ↑

Cost Focus ↔ ↑ ↔ ↔ ↔ ↑↑ ↓↓ ↑ ↑

Differentiation Focus ↑ ↑↑ ↓↓ ↑↑ ↓ ↓ ↔ ↓ ↑

Both Focused ↑ ↑ ↓↓ ↑↑ ↓ ↔ ↔ ↔ ↑

Both Not Focused ↓ ↓ ↔ ↑↑ ↓ ↔ ↔ ↓↓ ↓

Both Differentiation ↔ ↑ ↓↓ ↑↑ ↓ ↔ ↔ ↓ ↑

Both Cost ↓ ↔ ↑ ↔ ↔ ↔ ↔ ↓ ↑↑

Source: Author’s calculations.

↑ The effect in the subset is more positive than in the full sample.

↑↑ The effect in the subset is distinctively more positive than in the full sample.

↓ The effect in the subset is more negative than in the full sample.

↓↓ The effect in the subset is distinctively more negative than in the full sample.

↔ The effect in the subset is about the same as in the full sample.

TMPP stands for the Share of Top Management Performance Pay on total remuneration

WPP stands for the Share of Workers´ Performance Pay on total remuneration