### Table 4: Differences between financial and auction markets.

2005

"... In PAGE 6: ... Pricing Options While the conceptual definition of an option is the same whether referring to financial or auction markets, there are three fundamental differences between the two markets that make existing option-pricing models inappropriate for pricing options used in auction markets. Table4 lists these critical differences. Market structure Equity markets are characterized as double auctions, in which interested buyers and sellers both submit bids.... ..."

### Table 2 - Determinants of Commitments in Financial Services:

"... In PAGE 22: ...parentheses). Table2 represents estimations using the unionisation and inflation variability measures whereas Table 3 includes the Freedom House index and the quality of prudential regulation variable instead. 23 We also checked whether our results are robust with respect to the construction of the liberalisation indices or the estimation technique, and whether they are driven by a few influential observations.... In PAGE 22: ... The results in both Tables 2 and 3 confirm the relevance of our model to explaining financial services commitments in banking and (to a somewhat lesser degree) in securities services trade. As to our hypothesis on the role of workers and unionisation, we find that countries that are characterised by a high degree of unionisation had a greater propensity to commit to financial sector liberalisation ( Table2 , columns (1) through (5)). On the other hand, the alternative proxy of democracy represented by the Freedom House index did not prove significant (Table 3).... In PAGE 22: ... Lending-deposit spreads which are used as a proxy for the financial sector apos;s mark-up have a positive sign for some specifications, suggesting that the effect of bank monopoly power on workers apos; pressure for liberalisation dominates incumbents apos; resistance. However, if we look at securities services, this result no longer holds ( Table2 , column (4)), and if we replace the standard deviation of inflation by the prudential regulation variable (Table 3, column (3)), the markup has a significantly negative effect on financial sector liberalisation. The latter result is most likely due to the fact that the lending spread is highly correlated with 23 Due to limited data availability, the number of observations falls to 25 in the second set of estimations.... In PAGE 23: ... The potential for exchanging market access commitments in future negotiations, especially for countries whose exports face high barriers abroad, was apparently a motive to withhold market access commitments in banking services. The Cairns group members and the textile/clothing exporters constrained by quotas under the former Multi Fibre Agreement have indeed committed to less liberalisation than otherwise expected ( Table2 , column (1) and Table 3, column (1) and (2)). However, robustness tests show that the significance of the outcome for the Cairns groups variable (8 observations in total) depends somewhat on one observation (Chile).... In PAGE 23: ... As an alternative test of the hypothesis that countries withheld commitments in the hope of a future exchange of market access, we used the export share of the textiles/clothes and agricultural sector, respectively. However, neither variable showed a significant influence on any estimation outcome (hence only represented in Table2 , column (2)). Note also the difference in th e overall model fit between the estimation which includes the bargaining coalition dummies and the one which includes the export share variables.... In PAGE 24: ...membership in either the Cairns group or in the textile exporters apos; group, the model apos;s fit can be substantially improved ( Table2 , column (5)).25 As to other control variables, the negative sign of inflation indicates that countries with an unstable macroeconomic environment were reluctant to commit to financial sector liberalisation.... In PAGE 24: ... The presence of foreigners in the banking sector proves highly correlated for the degree of banking services commitments, while the trade openness variable is not significant in any estimation and therefore only included for illustrative purposes in columns (1) and (4) of Table 2. Finally, column (3) of Table2 demonstrates that a more parsimonious specification neither substantially alters the coefficients of the remaining regressors nor reduces the fit of the regression. 5.... ..."

### Table 1. Exploratory data analysis of the financial ratios

1997

"... In PAGE 5: ... This broad group was introduced into a regression model with the aim of obtaining a first approxima- tion on the explanatory capacity of each ratio. In this way Pina (1989) selected the nine ratios which appear in Table1 . The first three are liquidity ratios, whilst the fourth measures the self-financing capacity of the bank.... In PAGE 6: ... We have used a procedure based on Tchebyschev inequality, which has allowed us to identify five companies as outliers (banks 14, 17, 24, 47 and 57 of Appendix A). In order to complete the study of the classifying power of each variable, a univariate analysis was carried out, the results of which appear in Table1 . For each financial ratio, the univariate statistics test for the equality of the means of the two groups.... In PAGE 8: ... Finally, the box plots also give us some idea of the form and symmetry of the distribution, albeit incomplete, so that we have applied a normality test, namely that of Kolmogorov Smirnov. As can be seen in Table1 , in five of the nine ratios analysed, specifically ratios 4, 5, 6, 7 and 8, the normality hypothesis has been rejected. 3.... ..."

Cited by 2

### Table 1 Accelerated DDM with Robin Transmission Conditions with Overlapping Subdomains Acceleration Parameters

"... In PAGE 11: ... 8 Choosing the Parameter Cycle and the Overlap The convergence of our domain decomposition iteration for the mixed nite element method for the model problem considered herein can be signi cantly accelerated both by choosing a variable parameter cycle and by overlapping the domains. The result of combining the two concepts is illustrated for a very simple choice of the parameter cycle in Table1 below; no great e ort was made to optimize this choice, though sample calculations did indicate that basing the cycle on annihilating the lower frequency components of the error led to quite e cient iterations. Table 2 extracts the choices from Table 1 that give minimal work requirements for N=50 and N=100 associated with given overlaps; the case of no overlap does lead to convergence, but the number of iterations required to reduce the error by a factor of 10?6 is about ve times that required with an overlap from x = ?h to x = h, thereby indicating clearly that a small overlap is necessary to obtain a work estimate anywhere reasonably close to optimal.... In PAGE 11: ... The result of combining the two concepts is illustrated for a very simple choice of the parameter cycle in Table 1 below; no great e ort was made to optimize this choice, though sample calculations did indicate that basing the cycle on annihilating the lower frequency components of the error led to quite e cient iterations. Table 2 extracts the choices from Table1 that give minimal work requirements for N=50 and N=100 associated with given overlaps; the case of no overlap does lead to convergence, but the number of iterations required to reduce the error by a factor of 10?6 is about ve times that required with an overlap from x = ?h to x = h, thereby indicating clearly that a small overlap is necessary to obtain a work estimate anywhere reasonably close to optimal. For N=50, the best choice based on these iteration parameters is given by using a single cycle of length three combined with an overlap from x = ?3h to x = 3h, while the best choice for N=100 is given by using a single cycle of length four combined with overlap from x = ?4h to x = 4h.... ..."

Cited by 1

### Table 1 Accelerated DDM with Robin Transmission Conditions with Overlapping Subdomains Acceleration Parameters

"... In PAGE 11: ... 8 Choosing the Parameter Cycle and the Overlap The convergence of our domain decomposition iteration for the mixed nite element method for the model problem considered herein can be signi cantly accelerated both by choosing a variable parameter cycle and by overlapping the domains. The result of combining the two concepts is illustrated for a very simple choice of the parameter cycle in Table1 below; no great e ort was made to optimize this choice, though sample calculations did indicate that basing the cycle on annihilating the lower frequency components of the error led to quite e cient iterations. Table 2 extracts the choices from Table 1 that give minimal work requirements for N=50 and N=100 associated with given overlaps; the case of no overlap does lead to convergence, but the number of iterations required to reduce the error by a factor of 10?6 is about ve times that required with an overlap from x = ?h to x = h, thereby indicating clearly that a small overlap is necessary to obtain a work estimate anywhere reasonably close to optimal.... In PAGE 11: ... The result of combining the two concepts is illustrated for a very simple choice of the parameter cycle in Table 1 below; no great e ort was made to optimize this choice, though sample calculations did indicate that basing the cycle on annihilating the lower frequency components of the error led to quite e cient iterations. Table 2 extracts the choices from Table1 that give minimal work requirements for N=50 and N=100 associated with given overlaps; the case of no overlap does lead to convergence, but the number of iterations required to reduce the error by a factor of 10?6 is about ve times that required with an overlap from x = ?h to x = h, thereby indicating clearly that a small overlap is necessary to obtain a work estimate anywhere reasonably close to optimal. For N=50, the best choice based on these iteration parameters is given by using a single cycle of length three combined with an overlap from x = ?3h to x = 3h, while the best choice for N=100 is given by using a single cycle of length four combined with overlap from x = ?4h to x = 4h.... ..."

Cited by 1

### Table 5 . Firm Size, Process Performance, Process Variation, and Financial Performance

1998

"... In PAGE 31: ... Process variation is defined as the variation in performance across the eleven individual process performance scores for each bank. The fundamental question addressed in Frei et al (1997) is which is more important for a bank, to do a few things well and, hence, to do other things not so well, or to provide a reasonably consistent set of service delivery processes to the customer? What ultimately matters, occasional excellence or consistency? To address this question, the model from Table 4 was expanded to include process variation, as shown in Table5 . As can be 2 The previous study does not argue that consistently poor performance is a good strategy but rather evidence is presented in terms of an analytical model and empirical data that suggests that if there is an additional resource to be invested in a firm, then the investment should go to improving consistency rather than in moving a single... ..."

### Table 1 Other vehicle choice models that have used similar attributes Article Attribute

in studies of

### Table 1: Financial information and ratios used in prior studies

"... In PAGE 2: ...raditional Financial Distress Models ....................................3 Table1 : Financial information and ratios used in prior studies .... In PAGE 7: ... The financial ratios analyzed in FAK encompass the set of ratios found to be the best financial distress predictors in prior studies. The ratios used by FAK and prior studies are compared in Table1 . At the bottom of Table 1, prior study ratios not analyzed in FAK are listed.... In PAGE 7: ... The ratios used by FAK and prior studies are compared in Table 1. At the bottom of Table1 , prior study ratios not analyzed in FAK are listed. Each of these ratios has a FAK counterpart which provides similar information.... ..."

### Table 5. Impact of IT and Dynamic Capabilities on Firm Financial Performance

"... In PAGE 24: ... We regressed the firm-level financial measures against dependent variables such as IT usage, the dynamic capabilities of effectiveness and efficiency, and organizational and process variables. Our regression results are shown in Table5 . In a manner similar to our approach described in the previous section, the odd-numbered columns denote results where we regressed the relevant financial performance measure in year t (FPt) against the dynamic capabilities, firm control variables, and past firm performance in year t-1 represented by Fin.... In PAGE 25: ... To compare the two models, we once again compare the R2 values of the mediation and direct models. Clearly, the F-test results in Table5 show that the incremental direct impact of IT on firm performance is not statistically significant. These results confirm that the impact of IT on firm performance is mediated through effectiveness and efficiency, but through firm-level data.... ..."

### Table 6 . The Effect of Good and Consistent Processes on Financial Performance

1998

"... In PAGE 32: ... Using these dummy variables instead of the continuous measures, the question of which matter more (in terms of financial performance) continuous processes or good processes could be addressed. By comparing the coefficients on good and consistent processes in Table6 , it was found that the coefficient on consistent is significantly greater than the coefficient on good . This analysis reinforced the analytical model presented in Frei et al (1997) by showing that when analyzing the relation between the process measures and firm performance, there tends to be a stronger financial return for banks with consistent processes than for banks with good processes.... ..."