### Table 4: Firm-level evidence on the effects of new forms of work organisation on process, productivity and performance

2006

"... In PAGE 40: ... Having said so, taken together the available evidence nevertheless gives a fairly comprehensive, if still tentative, impression of the impacts of new forms for flexible work organisation on key performance parameters, and of the factors upon which success or failure of NWE implementation is contingent. Table4 lists some of the main findings of recent studies looking into the effects of new forms of work organisation on business performance. Early research was carried out almost exclusively in the USA, and often assessed a bundle of reorganisation measures including modern HR management, but also production-related measures such as total quality improvement and just-in-time production.... ..."

### Table #10 - Profiles of Firm-Level Assimilation

### Table 3 Firm-Level Inventory Model Parameter Estimates

"... In PAGE 25: ...32 3.3 Regression Estimates Table3 reports the results of the firm-level regression estimation for each of the three models at the company level (upper half) and division level (lower half). The first three columns report 10th, 50th (median), and 90th percentiles of the distributions of parameters and regression diag- nostic statistics.... In PAGE 26: ... Other indicates the percentage attributable to idiosyncratic variation within industry-size classes.33 The overall impression conveyed by Table3 is that the firm-level data generally do not support the linear-quadratic inventory model, regardless of the econometric methodology employed. In most respects, these firm-level estimates are consistent with prior results from regressions with aggregate data.... ..."

### Table 1: OLS Firm-Level Wage Regressions

"... In PAGE 11: ... Wage Inequality and Firm Performance In this section we present our results using pooled firm-level data for standardised blue- collar and white-collar wages. The basic specifications for standardised wages are contained in Table1 . Within-firm inequality (sigma) is entered in a quadratic form to allow for a non- linear relationship.... In PAGE 15: ... In order to see whether there is a long-term relationship between firm wage inequality and firm performance we focus the analysis on long-run firm-specific averages ( group- means ) of the interesting variables. These group-means regressions of the performance indicators use all variables which also entered the regressions of Table1 . To account for 17 Random effects models are rejected by a Hausman test in most cases, for some specifications a usual... In PAGE 16: ... It turns out that wage inequality has a significant impact on standardised wages of both white collar and blue collar workers with point estimates quantitatively much larger than in the case of within-firm effects. For white-collar workers the estimates imply a hump-shaped picture, just like that in the OLS regression of Table1 . This result remains qualitatively unchanged once we confine the analysis to observations where inequality indicators were calculated only for male employees (Table 4, Column 4).... In PAGE 16: ...oint is much later: at a value of firm wage inequality sigma of 0.28 in Table 3. This means, that for the most part of the empirical distribution of the inequality measure sigma, a positive dispersion-wage schedule can be observed. This result is again very similar to the OLS- regression in Table1 . If the firm inequality measure is based only on males, the results for blue-collar workers turn out to be less robust.... ..."

### Table 3 - continued Firm-level Logit Regression Results

"... In PAGE 11: ... Cash flow is not significant in that regression. In Panel B of Table3 , we estimate logit regressions in which the dependent variable takes a value of one for divesting firms and zero for discontinuing firms. The explanatory variables in the first regression are cash flow, capital expenditures, and leverage.... In PAGE 15: ... Our univariate results indicate that it is insignificantly higher. We now investigate whether adding liquidity to the multiple regressions of Table3 helps explain why, among firms that have similar fundamental reasons to divest, some firms divest a segment while others do not. Since liquidity is not a sufficient motive for divestiture, it is not surprising that liquidity is not significant in differentiating between comparison firms and divesting firms.... In PAGE 15: ... In fact, the liquidity variable is the only significant variable in these regressions. The liquidity variable is also significant if we add it to regressions (2) and (3) in Panel B of Table3 . Thus, unlike firm characteristics such as cash flow, capital expenditures, excess value, and leverage, liquidity can explain why some firms stop reporting a segment without divesting it while others stop reporting ... ..."

### Table 6 Descriptive Statistics: Firm-Level Data

### Table 7 Supply Relation Estimates: Firm-Level Data

"... In PAGE 22: ... We first report the results for the supply relation. As shown in Table7 , the supply-side estimates suggest the trust generally exercised little market power, but that it did raise prices for two short periods... ..."

### TABLE 2 Means (std. devs.) of Firm-Level Characteristics

### Table 3 - continued Firm-level Logit Regression Results

"... In PAGE 12: ... Cash flow is not significant in that regression. In Panel B of Table3 , we provide estimates of logit regressions where the dependent variable takes value one for divesting firms and zero for discontinuing firms. The explanatory variables in the first regression are cash flow, capital expenditures, and leverage.... In PAGE 16: ... Our univariate results indicate that it is insignificantly higher. We now investigate whether adding liquidity to the multiple regressions of Table3 helps explain whether a firm divests a segment. Liquidity should help explain why among firms, that have similar fundamental reasons to divest, some firms divest a segment while others do not.... In PAGE 17: ... In fact, the liquidity variable is the only significant variable in these regressions. The liquidity variable is also significant if we add it to regressions (2) and (3) of Panel B of Table3 . Thus, liquidity can explain what firm characteristics such as cash flow, capital expenditures, excess value, and leverage cannot, namely why some firms stop reporting a segment without divesting it while others stop reporting a segment and divest it.... ..."