<table><caption>Table A1
Mean values of performance proxies for the eight groups defined according to their SEM model-based scores on animal welfare performance (AW), environmental performance (ENV) and economic performance (ECO).</caption><thead><tr><th></th><th></th><th>Group 1</th><th>Group 2</th><th>Group 3</th><th>Group 4</th><th>Group 5</th><th>Group 6</th><th>Group 7</th><th>Group 8</th></tr></thead><tbody><tr><td rowspan="5">Model scores</td><td>Group definition</td><td>AW &gt; median<br>ENV &gt; median<br>ECO &gt; median</td><td>AW &gt; median<br>ENV &lt; median<br>ECO &gt; median</td><td>AW &gt; median<br>ENV &gt; median<br>ECO &lt; median</td><td>AW &gt; median<br>ENV &lt; median<br>ECO &lt; median</td><td>AW &lt; median<br>ENV &gt; median<br>ECO &gt; median</td><td>AW &lt; median<br>ENV &lt; median<br>ECO &gt; median</td><td>AW &lt; median<br>ENV &gt; median<br>ECO &lt; median</td><td>AW &lt; median<br>ENV &lt; median<br>ECO &lt; median</td></tr><tr><td>Number of farms</td><td>287</td><td>93</td><td>133</td><td>131</td><td>118</td><td>146</td><td>106</td><td>275</td></tr><tr><td>AW quantile</td><td>26.8 (13.7) a</td><td>34.5 (13.1) b</td><td>31.5 (13.8) ab</td><td>32.1 (14.8) ab</td><td>73.5 (13.2) c</td><td>79.7 (13.4) de</td><td>76.4 (14) cd</td><td>84.3 (13.7) e</td></tr><tr><td>ENV quantile</td><td>27.4 (13.8) a</td><td>75.6 (13.9) b</td><td>31.8 (12.9) a</td><td>76.6 (14.4) b</td><td>31 (14.5) a</td><td>80.6 (13.7) bc</td><td>33.4 (15) a</td><td>82.7 (13.8) c</td></tr><tr><td>ECO quantile</td><td>26.2 (14.2) a</td><td>32.5 (13.1) ab</td><td>75.3 (12.8) c</td><td>81.1 (14) d</td><td>29.9 (14.1) a</td><td>35.9 (12.4) b</td><td>78.9 (14.2) cd</td><td>82.1 (14.4) d</td></tr><tr><td rowspan="3">AW-<br>Good feeding<br>Good housing</td><td>Adjusted cow weight after calving (kg)<sup>1</sup></td><td>740 (68) a</td><td>761 (71) a</td><td>757 (87) a</td><td>753 (80) a</td><td>743 (79) a</td><td>757 (76) a</td><td>738 (84) a</td><td>754 (70) a</td></tr><tr><td>Gross liveweight production (kg per LU)</td><td>320 (51) a</td><td>330 (61) a</td><td>336 (52) a</td><td>333 (69) a</td><td>338 (62) a</td><td>346 (80) a</td><td>343 (86) a</td><td>348 (87) a</td></tr><tr><td>Mean building costs (€/LU)<sup>1</sup></td><td>82.7 (62.4) a</td><td>63.1 (38) a</td><td>90.8 (95.6) a</td><td>81.6 (56.1) a</td><td>72.5 (44.7) a</td><td>62.8 (42.9) a</td><td>68.1 (43.8) a</td><td>70.2 (55.9) a</td></tr><tr><td rowspan="5">AW-<br>Good health</td><td>Calf mortality (%)<sup>1</sup></td><td>5.88 (3.21) a</td><td>6.22 (3.19) a</td><td>6.36 (3.2) a</td><td>5.72 (3.07) a</td><td>9.23 (4.08) b</td><td>8.87 (4.7) b</td><td>10.2 (5) b</td><td>10.2 (5.2) b</td></tr><tr><td>Other-category mortality (%)<sup>1</sup></td><td>0.483 (0.798) a</td><td>0.463 (0.868) ab</td><td>0.577 (0.915) abc</td><td>0.42 (0.734) a</td><td>1.15 (1.72) abc</td><td>1.08 (2.03) bc</td><td>1.33 (1.89) bc</td><td>1.38 (2.07) c</td></tr><tr><td>Pregnancy rate (%)<sup>1</sup></td><td>93.7 (5.4) ab</td><td>92.7 (5.5) abc</td><td>92.3 (6.5) abc</td><td>94 (5.6) a</td><td>89.9 (11) bc</td><td>91.4 (7.1) bc</td><td>90.6 (8.6) abc</td><td>89.8 (9) c</td></tr><tr><td>Mean calving interval (days)</td><td>378 (14) a</td><td>379 (16) a</td><td>377 (13) a</td><td>381 (19) a</td><td>381 (18) a</td><td>380 (19) a</td><td>377 (41) a</td><td>384 (29) a</td></tr><tr><td>Rate of 400-day-plus calving intervals (%)</td><td>18.9 (11.6) a</td><td>18.6 (12.7) a</td><td>18.6 (12.9) a</td><td>20.7 (13.8) a</td><td>19.3 (11.7) a</td><td>20.7 (16.7) a</td><td>19.9 (11.9) a</td><td>21.3 (14.1) a</td></tr><tr><td rowspan="3">AW-Appropriate<br>behaviour</td><td>Dystocia rate (%)</td><td>4.06 (9.2) a</td><td>3.09 (3.97) a</td><td>4.25 (4.46) a</td><td>3.94 (4.58) a</td><td>2.99 (3.97) a</td><td>3.48 (4.98) a</td><td>3.73 (4.24) a</td><td>4.24 (5.68) a</td></tr><tr><td>Abortion rate (%)</td><td>0.427 (0.946) a</td><td>0.655 (1.294) a</td><td>0.499 (1.058) a</td><td>0.379 (0.807) a</td><td>0.505 (1.227) a</td><td>0.555 (1.123) a</td><td>0.426 (1.22) a</td><td>0.346 (0.999) a</td></tr><tr><td>Estimated amount of feed grazed out of<br>total forage offered (%)<sup>1,2</sup></td><td>63.5 (6.5) a</td><td>62 (6.5) a</td><td>62.6 (7) a</td><td>61.5 (8) a</td><td>51 (11.2) b</td><td>45.4 (12.6) cd</td><td>49.2 (12.1) bc</td><td>43.1 (14) d</td></tr><tr><td rowspan="5">ENV</td><td>Pesticide index per ha forage area<sup>1</sup></td><td>0.023 (0.032) a</td><td>0.088 (0.064) b</td><td>0.026 (0.034) a</td><td>0.079 (0.091) b</td><td>0.029 (0.033) a</td><td>0.112 (0.118) b</td><td>0.023 (0.035) a</td><td>0.136 (0.148) b</td></tr><tr><td>Fertiliser index per ha forage area</td><td>0.335 (0.244) a</td><td>0.639 (0.326) b</td><td>0.314 (0.237) a</td><td>0.817 (0.56) b</td><td>0.31 (0.225) a</td><td>0.694 (0.406) b</td><td>0.338 (0.327) a</td><td>0.736 (0.465) b</td></tr><tr><td>Nitrogen balance (kg N/100 kg<br>liveweight)<sup>1</sup></td><td>7.87 (3.59) a</td><td>17.7 (10.2) b</td><td>8.76 (3.6) a</td><td>18.2 (7.9) b</td><td>7.88 (3.53) a</td><td>17.7 (8) b</td><td>8.57 (4.45) a</td><td>18 (7.6) b</td></tr><tr><td>Energy consumption (MJ/100 kg<br>liveweight)<sup>1</sup></td><td>2060 (460) a</td><td>3250 (2140) b</td><td>2180 (430) a</td><td>3100 (850) b</td><td>2200 (600) ac</td><td>3340 (3180) b</td><td>2340 (480) c</td><td>3320 (1650) b</td></tr><tr><td>Permanent grassland per UAA (%)</td><td>64.2 (25.2) a</td><td>49.6 (21.4) bc</td><td>61.6 (26.1) ab</td><td>44 (26.6) c</td><td>50.4 (26.2) bc</td><td>41.2 (23.3) cd</td><td>51 (25.5) c</td><td>36.7 (20.3) d</td></tr><tr><td rowspan="5">ECO</td><td>Gross operating surplus ratioed to total<br>revenue (%)<sup>1</sup></td><td>40.3 (6) a</td><td>37.8 (5.4) ab</td><td>27.7 (5.2) c</td><td>25.3 (6.3) de</td><td>38.5 (5.4) ab</td><td>37 (5.1) b</td><td>27.3 (6.2) cd</td><td>24.1 (7.1) e</td></tr><tr><td>Gross operating surplus (€/AWU)</td><td>57,100 (21400) a</td><td>65,600 (28400) a</td><td>47,200 (16500) b</td><td>48,300 (19000) b</td><td>59,000 (22400) a</td><td>62,800 (24900) a</td><td>48,800 (20000) b</td><td>44,000 (18500) b</td></tr><tr><td>Farm income (€/farmer)</td><td>27,800 (20500) a</td><td>38,100 (29500) a</td><td>15,300 (15600) b</td><td>14,000 (22000) b</td><td>30,400 (22100) a</td><td>35,200 (24900) a</td><td>18,600 (19300) b</td><td>13,500 (21100) b</td></tr><tr><td>Cash income (€/farmer)</td><td>36,400 (22600) a</td><td>45,300 (27500) a</td><td>21,100 (16000) bc</td><td>19,400 (24300) bc</td><td>37,500 (24800) a</td><td>41,800 (24200) a</td><td>22,100 (18400) b</td><td>17,200 (24000) c</td></tr><tr><td>Debt-to-asset ratio (%)<sup>1</sup></td><td>27.4 (15.4) a</td><td>29.4 (12.8) a</td><td>41.3 (18.6) b</td><td>43.1 (18.5) b</td><td>28.4 (14.2) a</td><td>32.6 (14.3) a</td><td>48.9 (20.7) b</td><td>43.1 (22.9) b</td></tr><tr><td></td><td>Capital intensity (€/AWU)</td><td>125,100 (48900) a</td><td>152,900 (61100) ab</td><td>134,200 (48200) ab</td><td>154,200 (48100) b</td><td>133,300 (49900) ab</td><td>148,500 (54600) ab</td><td>145,200 (52600) ab</td><td>145,700 (49600) ab</td></tr></tbody></table>

<footnote n="1">1 Variables used in the structural equation model.</footnote>

<footnote n="2">2 Variables used in the logit models. a,b,c: values within a row with no common letter differ significantly (Wilcox-test: p ≤ 0.10). Standard deviations in brackets.</footnote>
<table><caption>**Table A1**
Mean values of performance proxies for the eight groups defined according to their SEM model-based scores on animal welfare performance (AW), environmental performance (ENV) and economic performance (ECO).</caption><thead><tr><th></th><th>Group definition</th><th>Group 1</th><th>Group 2</th><th>Group 3</th><th>Group 4</th><th>Group 5</th><th>Group 6</th><th>Group 7</th><th>Group 8</th></tr></thead><tbody><tr><td rowspan="4">Model scores</td><td>Number of farms</td><td>AW &gt; median<br>ENV &gt; median<br>ECO &gt; median</td><td>AW &gt; median<br>ENV &lt; median<br>ECO &gt; median</td><td>AW &gt; median<br>ENV &gt; median<br>ECO &lt; median</td><td>AW &gt; median<br>ENV &lt; median<br>ECO &lt; median</td><td>AW &lt; median<br>ENV &gt; median<br>ECO &gt; median</td><td>AW &lt; median<br>ENV &lt; median<br>ECO &gt; median</td><td>AW &lt; median<br>ENV &gt; median<br>ECO &lt; median</td><td>AW &lt; median<br>ENV &lt; median<br>ECO &lt; median</td></tr><tr><td>AW quantile</td><td>26.8 (13.7) a</td><td>34.5 (13.1) b</td><td>31.5 (13.8) ab</td><td>32.1 (14.8) ab</td><td>73.5 (13.2) c</td><td>79.7 (13.4) de</td><td>76.4 (14) cd</td><td>84.3 (13.7) e</td></tr><tr><td>ENV quantile</td><td>27.4 (13.8) a</td><td>75.6 (13.9) b</td><td>31.8 (12.9) a</td><td>76.6 (14.4) b</td><td>31 (14.5) a</td><td>80.6 (13.7) bc</td><td>33.4 (15) a</td><td>82.7 (13.8) c</td></tr><tr><td>ECO quantile</td><td>26.2 (14.2) a</td><td>32.5 (13.1) ab</td><td>75.3 (12.8) c</td><td>81.1 (14) d</td><td>29.9 (14.1) a</td><td>35.9 (12.4) b</td><td>78.9 (14.2) cd</td><td>82.1 (14.4) d</td></tr><tr><td>AW-<br>Good feeding</td><td>Adjusted cow weight after calving (kg)<sup>1</sup></td><td>740 (68) a</td><td>761 (71) a</td><td>757 (87) a</td><td>753 (80) a</td><td>743 (79) a</td><td>757 (76) a</td><td>738 (84) a</td><td>754 (70) a</td></tr><tr><td rowspan="2">AW-<br>Good housing</td><td>Gross liveweight production (kg per LU)</td><td>320 (51) a</td><td>330 (61) a</td><td>336 (52) a</td><td>333 (69) a</td><td>338 (62) a</td><td>346 (80) a</td><td>343 (86) a</td><td>348 (87) a</td></tr><tr><td>Mean building costs (€/LU)<sup>1</sup></td><td>82.7 (62.4) a</td><td>63.1 (38) a</td><td>90.8 (95.6) a</td><td>81.6 (56.1) a</td><td>72.5 (44.7) a</td><td>62.8 (42.9) a</td><td>68.1 (43.8) a</td><td>70.2 (55.9) a</td></tr><tr><td>AW-<br>Good health</td><td>Calf mortality (%)<sup>1</sup></td><td>5.88 (3.21) a</td><td>6.22 (3.19) a</td><td>6.36 (3.2) a</td><td>5.72 (3.07) a</td><td>9.23 (4.08) b</td><td>8.87 (4.7) b</td><td>10.2 (5) b</td><td>10.2 (5.2) b</td></tr><tr><td rowspan="5">AW-Appropriate<br>behaviour</td><td>Other-category mortality (%)<sup>1</sup></td><td>0.483 (0.798) a</td><td>0.463 (0.868) ab</td><td>0.577 (0.915) abc</td><td>0.42 (0.734) a</td><td>1.15 (1.72) abc</td><td>1.08 (2.03) bc</td><td>1.33 (1.89) bc</td><td>1.38 (2.07) c</td></tr><tr><td>Pregnancy rate (%)<sup>1</sup></td><td>93.7 (5.4) ab</td><td>92.7 (5.5) abc</td><td>92.3 (6.5) abc</td><td>94 (5.6) a</td><td>89.9 (11) bc</td><td>91.4 (7.1) bc</td><td>90.6 (8.6) abc</td><td>89.8 (9) c</td></tr><tr><td>Mean calving interval (days)</td><td>378 (14) a</td><td>379 (16) a</td><td>377 (13) a</td><td>381 (19) a</td><td>381 (18) a</td><td>380 (19) a</td><td>377 (41) a</td><td>384 (29) a</td></tr><tr><td>Rate of 400-day-plus calving intervals (%)</td><td>18.9 (11.6) a</td><td>18.6 (12.7) a</td><td>18.6 (12.9) a</td><td>20.7 (13.8) a</td><td>19.3 (11.7) a</td><td>20.7 (16.7) a</td><td>19.9 (11.9) a</td><td>21.3 (14.1) a</td></tr><tr><td>Abortion rate (%)</td><td>4.06 (9.2) a</td><td>3.09 (3.97) a</td><td>4.25 (4.46) a</td><td>3.94 (4.58) a</td><td>2.99 (3.97) a</td><td>3.48 (4.98) a</td><td>3.73 (4.24) a</td><td>4.24 (5.68) a</td></tr><tr><td rowspan="2">ENV</td><td>Estimated amount of feed grazed out of total forage offered (%)<sup>1,2</sup></td><td>63.5 (6.5) a</td><td>62 (6.5) a</td><td>62.6 (7) a</td><td>61.5 (8) a</td><td>51 (11.2) b</td><td>45.4 (12.6) cd</td><td>49.2 (12.1) bc</td><td>43.1 (14) d</td></tr><tr><td>Pesticide index per ha forage area<sup>1</sup></td><td>0.023 (0.032) a</td><td>0.088 (0.064) b</td><td>0.026 (0.034) a</td><td>0.079 (0.091) b</td><td>0.029 (0.033) a</td><td>0.112 (0.118) b</td><td>0.023 (0.035) a</td><td>0.136 (0.148) b</td></tr><tr><td rowspan="5">ECO</td><td>Fertiliser index per ha forage area</td><td>0.335 (0.244) a</td><td>0.639 (0.326) b</td><td>0.314 (0.237) a</td><td>0.817 (0.56) b</td><td>0.31 (0.225) a</td><td>0.694 (0.406) b</td><td>0.338 (0.327) a</td><td>0.736 (0.465) b</td></tr><tr><td>Nitrogen balance (kg N/100 kg liveweight)<sup>1</sup></td><td>7.87 (3.59) a</td><td>17.7 (10.2) b</td><td>8.76 (3.6) a</td><td>18.2 (7.9) b</td><td>7.88 (3.53) a</td><td>17.7 (8) b</td><td>8.57 (4.45) a</td><td>18 (7.6) b</td></tr><tr><td>Energy consumption (MJ/100 kg liveweight)<sup>1</sup></td><td>2060 (460) a</td><td>3250 (2140) b</td><td>2180 (430) a</td><td>3100 (850) b</td><td>2200 (600) ac</td><td>3340 (3180) b</td><td>2340 (480) c</td><td>3320 (1650) b</td></tr><tr><td>Permanent grassland per UAA (%)</td><td>64.2 (25.2) a</td><td>49.6 (21.4) bc</td><td>61.6 (26.1) ab</td><td>44 (26.6) c</td><td>50.4 (26.2) bc</td><td>41.2 (23.3) cd</td><td>51 (25.5) c</td><td>36.7 (20.3) d</td></tr><tr><td>Gross operating surplus ratioed to total revenue (%)<sup>1</sup></td><td>40.3 (6) a</td><td>37.8 (5.4) ab</td><td>27.7 (5.2) c</td><td>25.3 (6.3) de</td><td>38.5 (5.4) ab</td><td>37 (5.1) b</td><td>27.3 (6.2) cd</td><td>24.1 (7.1) e</td></tr><tr><td rowspan="5">AW-<br>Good housing</td><td>Gross operating surplus (€/AWU)</td><td>57,100 (21400) a</td><td>65,600 (28400) a</td><td>47,200 (16500) b</td><td>48,300 (19000) b</td><td>59,000 (22400) a</td><td>62,800 (24900) a</td><td>48,800 (20000) b</td><td>44,000 (18500) b</td></tr><tr><td>Farm income (€/farmer)</td><td>27,800 (20500) a</td><td>38,100 (29500) a</td><td>15,300 (15600) b</td><td>14,000 (22000) b</td><td>30,400 (22100) a</td><td>35,200 (24900) a</td><td>18,600 (19300) b</td><td>13,500 (21100) b</td></tr><tr><td>Cash income (€/farmer)</td><td>36,400 (22600) a</td><td>45,300 (27500) a</td><td>21,100 (16000) bc</td><td>19,400 (24300) bc</td><td>37,500 (24800) a</td><td>41,800 (24200) a</td><td>22,100 (18400) b</td><td>17,200 (24000) c</td></tr><tr><td>Debt-to-asset ratio (%)<sup>1</sup></td><td>27.4 (15.4) a</td><td>29.4 (12.8) a</td><td>41.3 (18.6) b</td><td>43.1 (18.5) b</td><td>28.4 (14.2) a</td><td>32.6 (14.3) a</td><td>48.9 (20.7) b</td><td>43.1 (22.9) b</td></tr><tr><td>Capital intensity (€/AWU)</td><td>125,100 (48900) a</td><td>152,900 (61100) ab</td><td>134,200 (48200) ab</td><td>154,200 (48100) b</td><td>133,300 (49900) ab</td><td>148,500 (54600) ab</td><td>145,200 (52600) ab</td><td>145,700 (49600) ab</td></tr></tbody></table>

<footnote n="1">1 Variables used in the structural equation model.</footnote>

<footnote n="2">2 Variables used in the logit models. a,b,c: values within a row with no common letter differ significantly (Wilcox-test: p ≤ 0.10). Standard deviations in brackets.</footnote>
<caption>Table A2</caption>

Mean values of practices, proxies for farmer expertise and farm characteristics for eight groups defined according to their score based on the SEM model.

<table><thead><tr><th></th><th></th><th>Group 1</th><th>Group 2</th><th>Group 3</th><th>Group 4</th><th>Group 5</th><th>Group 6</th><th>Group 7</th><th>Group 8</th></tr></thead><tbody><tr><td rowspan="5">Feed</td><td>Estimated amount of feed grazed out of total forage offered (%)<sup>1,2</sup></td><td>63.5 (6.5) a</td><td>62 (6.5) a</td><td>62.6 (7) a</td><td>61.5 (8) a</td><td>51 (11.2) b</td><td>45.4 (12.6) cd</td><td>49.2 (12.1) bc</td><td>43.1 (14) d</td></tr><tr><td>Amount of corn feed out of total forage offered (%)<sup>2</sup></td><td>2.87 (4.78) a</td><td>10.3 (7.2) bc</td><td>3.49 (4.91) a</td><td>7.14 (7.45) bd</td><td>5.06 (7.64) a</td><td>10.8 (9.2) b</td><td>5.45 (7.7) ad</td><td>14.9 (11.9) c</td></tr><tr><td>Amount of silage feed out of total forage offered (%)<sup>2</sup></td><td>3.59 (5.99) a</td><td>4.63 (5.97) a</td><td>5.1 (6.35) a</td><td>4.81 (6.07) a</td><td>5.43 (7.71) a</td><td>8.6 (9.42) a</td><td>4.97 (7.72) a</td><td>7.44 (8.83) a</td></tr><tr><td>Amount of wrapped haylage out of total forage offered (%)</td><td>7.89 (6.68) a</td><td>6.42 (7.57) a</td><td>8.23 (7.45) a</td><td>6.68 (7.56) a</td><td>9.11 (8.34) a</td><td>9.53 (10.49) a</td><td>10 (10.2) a</td><td>7.46 (9.91) a</td></tr><tr><td>Amount of hay feed out of total forage offered (%)</td><td>20.4 (9.2) abc</td><td>13.9 (7.7) d</td><td>18.2 (9.2) abd</td><td>16.1 (9.9) d</td><td>26.5 (13.8) c</td><td>21.1 (14.7) abc</td><td>24.1 (15) ac</td><td>19.5 (13.8) bd</td></tr><tr><td rowspan="8">Herd management</td><td>Amount of straw feed out of total forage offered (%)</td><td>1.11 (1.99) a</td><td>1.68 (3.83) a</td><td>1.38 (2.61) a</td><td>2.14 (3.84) a</td><td>1.49 (3.19) a</td><td>2.07 (5.3) a</td><td>2.49 (5.23) a</td><td>2.95 (5.88) a</td></tr><tr><td>Amount of concentrate feed out of total ration (%)</td><td>8.38 (3.52) a</td><td>10.7 (3.4) bc</td><td>9.64 (3.64) ab</td><td>11.9 (4.9) c</td><td>9.55 (4.8) ab</td><td>12.8 (6) cd</td><td>10.8 (5) bc</td><td>13.9 (5.8) d</td></tr><tr><td>Renewal rate (%)<sup>2</sup></td><td>22.1 (5.9) a</td><td>23.7 (6.6) a</td><td>23.9 (5.7) a</td><td>23.7 (6.7) a</td><td>23.5 (6.8) a</td><td>24 (7.7) a</td><td>24 (6.7) a</td><td>24.4 (6.7) a</td></tr><tr><td>Mean age at first calving (months)<sup>2</sup></td><td>35.2 (1.6) a</td><td>35 (2.5) a</td><td>34.6 (2.1) a</td><td>34.6 (2.2) a</td><td>35 (2.4) a</td><td>34.8 (3.1) a</td><td>34.2 (2.9) a</td><td>34.7 (2.8) a</td></tr><tr><td>Rate of calving before 30 months (%)</td><td>6.01 (15.9) a</td><td>3.8 (13.71) a</td><td>10.6 (22.5) a</td><td>11.1 (25.9) a</td><td>8.94 (20.94) a</td><td>13.7 (27.9) a</td><td>15.1 (26.6) a</td><td>10.6 (24.4) a</td></tr><tr><td>Calving in Jan-Feb (%)</td><td>22.7 (19.3) a</td><td>18.2 (17.3) ab</td><td>20.8 (21.1) ab</td><td>15.6 (16.2) ab</td><td>15.3 (14.3) b</td><td>16.4 (17) ab</td><td>18.3 (20) ab</td><td>13.5 (13.6) b</td></tr><tr><td>Calving in Mar-Apr (%)<sup>2</sup></td><td>16.3 (15.2) a</td><td>12.3 (16) a</td><td>14.2 (13.5) a</td><td>11.5 (13.1) a</td><td>14.3 (15.1) a</td><td>12.4 (12.2) a</td><td>14.6 (16.5) a</td><td>14.4 (15.2) a</td></tr><tr><td>Calving in May-Jun (%)</td><td>4.14 (6.24) a</td><td>4.2 (6.19) a</td><td>4.22 (9.3) a</td><td>5.66 (8.97) a</td><td>4.72 (6.52) a</td><td>6.08 (8.14) a</td><td>4.33 (7.26) a</td><td>7 (9.46) a</td></tr><tr><td rowspan="10">Revenue, subsidies, sales</td><td>Calving in Jul-Aug (%)</td><td>5.11 (10.48) a</td><td>9.52 (16.59) abc</td><td>8.15 (16.12) ab</td><td>7.49 (11.75) ab</td><td>8.83 (15.86) b</td><td>15.1 (17.4) d</td><td>8.6 (12.47) abcd</td><td>13.4 (18.4) cd</td></tr><tr><td>Calving in Sep-Oct (%)</td><td>22.2 (26.7) a</td><td>27.3 (26.7) ab</td><td>22.3 (24.7) ab</td><td>27.4 (24.9) ab</td><td>28.2 (27.2) ab</td><td>30.3 (24.7) b</td><td>30.9 (28.4) ab</td><td>31.1 (24.9) b</td></tr><tr><td>Calving in Nov-Dec (%)</td><td>29.6 (25.4) ab</td><td>28.4 (24.9) ab</td><td>30.4 (27.9) ab</td><td>32.3 (24.7) a</td><td>28.7 (24.7) ab</td><td>19.6 (20.7) b</td><td>23.3 (21.5) ab</td><td>20.6 (20) b</td></tr><tr><td>Beef revenue ratioed to total revenue (%)</td><td>55.7 (10.8) a</td><td>54.9 (13.7) a</td><td>57.3 (10.3) a</td><td>48.7 (17.5) a</td><td>54.8 (13.8) a</td><td>54.9 (16.7) a</td><td>54.1 (13.5) a</td><td>53.7 (16.1) a</td></tr><tr><td>Crop revenue ratioed to total revenue (%)<sup>2</sup></td><td>6.26 (12.39) a</td><td>14.3 (17.7) bc</td><td>6.76 (11.13) ab</td><td>20.7 (21.8) c</td><td>10.2 (16.5) abc</td><td>14.6 (19.5) bc</td><td>12.2 (17.1) abc</td><td>16.3 (18.3) c</td></tr><tr><td>Subsidies ratioed to total revenue (%)</td><td>34.2 (9.8) a</td><td>26.1 (8) bc</td><td>31.7 (7.9) a</td><td>25.9 (8.8) bc</td><td>31.2 (8.9) a</td><td>25.8 (8.9) bc</td><td>29.1 (9.2) ab</td><td>25.1 (8) c</td></tr><tr><td>Sales of calves (%)<sup>2</sup></td><td>6.83 (16.66) a</td><td>13 (27.1) a</td><td>3.58 (6.81) a</td><td>6.89 (17.81) a</td><td>8.42 (19.62) a</td><td>12.5 (25.6) a</td><td>7.4 (17.21) a</td><td>9.45 (20.88) a</td></tr><tr><td>Sales of weanlings for fattening (%)<sup>2</sup></td><td>32.8 (27.4) a</td><td>27 (26.8) ab</td><td>27.4 (26.8) a</td><td>32.5 (27.3) a</td><td>26.4 (26.9) ab</td><td>20.3 (26.2) ab</td><td>23.3 (25.3) ab</td><td>19 (25.2) b</td></tr><tr><td>Sales of older weanlings for fattening (%)<sup>2</sup></td><td>17.1 (24.6) a</td><td>6.82 (16.22) ab</td><td>15.4 (21.8) a</td><td>9.26 (18.34) ab</td><td>12.7 (22.7) a</td><td>5.04 (13.16) b</td><td>7.75 (15.98) ab</td><td>5.1 (14) b</td></tr><tr><td>Sales of heifers and young bulls for fattening (%)<sup>2</sup></td><td>3.05 (10.45) a</td><td>1.02 (3.57) a</td><td>1.77 (5.44) a</td><td>0.935 (3.415) a</td><td>1.79 (4.9) a</td><td>0.484 (2.269) a</td><td>1.32 (4.73) a</td><td>0.79 (3.176) a</td></tr><tr><td>Sales of animals for slaughter excl. Calves and cull cows (%)</td><td>14.5 (20.5) a</td><td>25.1 (25.4) bc</td><td>23.5 (25.6) ab</td><td>22.1 (26.3) ab</td><td>22.9 (25.1) ab</td><td>32.6 (29.2) bc</td><td>30.6 (29.4) bc</td><td>37.9 (31.5) c</td></tr><tr><td>Sales of cull cows (%)</td><td>19.6 (8.3) a</td><td>21.5 (7.3) ab</td><td>22.1 (8.9) ab</td><td>21.5 (9.1) ab</td><td>23.5 (8.4) ab</td><td>24 (9.1) ab</td><td>24 (8.5) b</td><td>23.9 (9.8) b</td></tr><tr><td>Sales of breeder stock (%)<sup>2</sup></td><td>6.16 (10.62) ab</td><td>5.63 (8.32) ab</td><td>6.34 (10.83) a</td><td>6.7 (10.96) ab</td><td>4.26 (7.97) ab</td><td>5.1 (9.66) ab</td><td>5.66 (9.24) ab</td><td>3.87 (8.62) b</td></tr><tr><td rowspan="7">Farmer expertise</td><td>Work experience (years)<sup>2</sup></td><td>23.6 (9.8) a</td><td>21.1 (9.5) a</td><td>20.3 (9.4) a</td><td>19.2 (9.4) a</td><td>23.9 (10.4) a</td><td>23.3 (11.8) a</td><td>20.3 (9.7) a</td><td>23.2 (10.6) a</td></tr><tr><td>Feed costs (€/100 kg liveweight)<sup>2</sup></td><td>59.4 (20) a</td><td>79.1 (43.5) bc</td><td>63.9 (19.8) ab</td><td>85.1 (28.6) cd</td><td>58.8 (22.1) a</td><td>80.4 (26.6) cd</td><td>67.9 (24.6) ab</td><td>91.8 (36.2) d</td></tr><tr><td>Numerical productivity (%)<sup>2</sup></td><td>90.4 (6) a</td><td>89.8 (6.6) a</td><td>89.2 (7.3) a</td><td>90.9 (6.5) a</td><td>84.2 (10.5) b</td><td>85.1 (8.1) b</td><td>84.4 (10.3) b</td><td>83.1 (10) b</td></tr><tr><td>Utilised agricultural area (UAA) (ha)</td><td>155 (75) a</td><td>172 (77) a</td><td>183 (87) a</td><td>180 (75) a</td><td>168 (67) a</td><td>167 (76) a</td><td>172 (77) a</td><td>165 (80) a</td></tr><tr><td>Livestock units (LU)<sup>2</sup></td><td>151 (68) a</td><td>170 (76) a</td><td>168 (71) a</td><td>154 (67) a</td><td>151 (64) a</td><td>175 (93) a</td><td>161 (81) a</td><td>163 (79) a</td></tr><tr><td>Annual work units (AWU)</td><td>1.78 (0.69) a</td><td>1.87 (0.69) a</td><td>1.82 (0.59) a</td><td>1.8 (0.65) a</td><td>1.85 (0.75) a</td><td>2.04 (0.73) a</td><td>1.77 (0.7) a</td><td>1.88 (0.79) a</td></tr><tr><td>LU per AWU</td><td>90.1 (34.3) a</td><td>94.6 (34) a</td><td>95.9 (33.6) a</td><td>89.8 (33.5) a</td><td>87.6 (34.3) a</td><td>87.2 (33.9) a</td><td>93.7 (34.3) a</td><td>89.7 (33.4) a</td></tr><tr><td rowspan="3">Farm characteristics</td><td>Stocking rate</td><td>1.24 (0.35) a</td><td>1.54 (0.41) bcd</td><td>1.21 (0.29) a</td><td>1.55 (0.52) bc</td><td>1.24 (0.34) a</td><td>1.69 (0.58) bd</td><td>1.48 (1.05) ac</td><td>1.97 (1.36) d</td></tr><tr><td>Feed protein self-sufficiency (%)</td><td>90.8 (5.2) a</td><td>85.1 (7.5) bc</td><td>89.4 (5.2) a</td><td>83.9 (7.3) b</td><td>89.4 (7.1) a</td><td>82.3 (11) bd</td><td>86.2 (12.4) ac</td><td>78.6 (13.4) d</td></tr><tr><td>Feed energy self-sufficiency (%)</td><td>93.4 (4.4) a</td><td>90.3 (6.6) bc</td><td>92.2 (4.4) ab</td><td>89.3 (6.5) bc</td><td>91.8 (7.4) a</td><td>87.9 (10.4) bc</td><td>89.3 (11.1) ab</td><td>85.3 (12.8) c</td></tr></tbody></table>

<footnote n="1">1 Variables used in the structural equation model.</footnote>

<footnote n="2">2 Variables used in the logit models. a,b,c: values within a row with no common letter differ significantly (Wilcox-test: p ≤ 0.10). Standard deviations in brackets.</footnote>
<caption>Table A2</caption>

Mean values of practices, proxies for farmer expertise and farm characteristics for eight groups defined according to their score based on the SEM model.

<table><thead><tr><th></th><th></th><th>Group 1</th><th>Group 2</th><th>Group 3</th><th>Group 4</th><th>Group 5</th><th>Group 6</th><th>Group 7</th><th>Group 8</th></tr></thead><tbody><tr><td rowspan="5">Feed</td><td>Estimated amount of feed grazed out of total forage offered (%)<sup>1,2</sup></td><td>63.5 (6.5) a</td><td>62 (6.5) a</td><td>62.6 (7) a</td><td>61.5 (8) a</td><td>51 (11.2) b</td><td>45.4 (12.6) cd</td><td>49.2 (12.1) bc</td><td>43.1 (14) d</td></tr><tr><td>Amount of corn feed out of total forage offered (%)<sup>2</sup></td><td>2.87 (4.78) a</td><td>10.3 (7.2) bc</td><td>3.49 (4.91) a</td><td>7.14 (7.45) bd</td><td>5.06 (7.64) a</td><td>10.8 (9.2) b</td><td>5.45 (7.7) ad</td><td>14.9 (11.9) c</td></tr><tr><td>Amount of silage feed out of total forage offered (%)<sup>2</sup></td><td>3.59 (5.99) a</td><td>4.63 (5.97) a</td><td>5.1 (6.35) a</td><td>4.81 (6.07) a</td><td>5.43 (7.71) a</td><td>8.6 (9.42) a</td><td>4.97 (7.72) a</td><td>7.44 (8.83) a</td></tr><tr><td>Amount of wrapped haylage out of total forage offered (%)</td><td>7.89 (6.68) a</td><td>6.42 (7.57) a</td><td>8.23 (7.45) a</td><td>6.68 (7.56) a</td><td>9.11 (8.34) a</td><td>9.53 (10.49) a</td><td>10 (10.2) a</td><td>7.46 (9.91) a</td></tr><tr><td>Amount of hay feed out of total forage offered (%)</td><td>20.4 (9.2) abc</td><td>13.9 (7.7) d</td><td>18.2 (9.2) abd</td><td>16.1 (9.9) d</td><td>26.5 (13.8) c</td><td>21.1 (14.7) abc</td><td>24.1 (15) ac</td><td>19.5 (13.8) bd</td></tr><tr><td rowspan="10">Herd management</td><td>Amount of straw feed out of total forage offered (%)</td><td>1.11 (1.99) a</td><td>1.68 (3.83) a</td><td>1.38 (2.61) a</td><td>2.14 (3.84) a</td><td>1.49 (3.19) a</td><td>2.07 (5.3) a</td><td>2.49 (5.23) a</td><td>2.95 (5.88) a</td></tr><tr><td>Amount of concentrate feed out of total ration (%)</td><td>8.38 (3.52) a</td><td>10.7 (3.4) bc</td><td>9.64 (3.64) ab</td><td>11.9 (4.9) c</td><td>9.55 (4.8) ab</td><td>12.8 (6) cd</td><td>10.8 (5) bc</td><td>13.9 (5.8) d</td></tr><tr><td>Renewal rate (%)<sup>2</sup></td><td>22.1 (5.9) a</td><td>23.7 (6.6) a</td><td>23.9 (5.7) a</td><td>23.7 (6.7) a</td><td>23.5 (6.8) a</td><td>24 (7.7) a</td><td>24 (6.7) a</td><td>24.4 (6.7) a</td></tr><tr><td>Mean age at first calving (months)<sup>2</sup></td><td>35.2 (1.6) a</td><td>35 (2.5) a</td><td>34.6 (2.1) a</td><td>34.6 (2.2) a</td><td>35 (2.4) a</td><td>34.8 (3.1) a</td><td>34.2 (2.9) a</td><td>34.7 (2.8) a</td></tr><tr><td>Rate of calving before 30 months (%)</td><td>6.01 (15.9) a</td><td>3.8 (13.71) a</td><td>10.6 (22.5) a</td><td>11.1 (25.9) a</td><td>8.94 (20.94) a</td><td>13.7 (27.9) a</td><td>15.1 (26.6) a</td><td>10.6 (24.4) a</td></tr><tr><td>Calving in Jan-Feb (%)</td><td>22.7 (19.3) a</td><td>18.2 (17.3) ab</td><td>20.8 (21.1) ab</td><td>15.6 (16.2) ab</td><td>15.3 (14.3) b</td><td>16.4 (17) ab</td><td>18.3 (20) ab</td><td>13.5 (13.6) b</td></tr><tr><td>Calving in Mar-Apr (%)<sup>2</sup></td><td>16.3 (15.2) a</td><td>12.3 (16) a</td><td>14.2 (13.5) a</td><td>11.5 (13.1) a</td><td>14.3 (15.1) a</td><td>12.4 (12.2) a</td><td>14.6 (16.5) a</td><td>14.4 (15.2) a</td></tr><tr><td>Calving in May-Jun (%)</td><td>4.14 (6.24) a</td><td>4.2 (6.19) a</td><td>4.22 (9.3) a</td><td>5.66 (8.97) a</td><td>4.72 (6.52) a</td><td>6.08 (8.14) a</td><td>4.33 (7.26) a</td><td>7 (9.46) a</td></tr><tr><td>Calving in Jul-Aug (%)</td><td>5.11 (10.48) a</td><td>9.52 (16.59) abc</td><td>8.15 (16.12) ab</td><td>7.49 (11.75) ab</td><td>8.83 (15.86) b</td><td>15.1 (17.4) d</td><td>8.6 (12.47) abcd</td><td>13.4 (18.4) cd</td></tr><tr><td>Calving in Sep-Oct (%)</td><td>22.2 (26.7) a</td><td>27.3 (26.7) ab</td><td>22.3 (24.7) ab</td><td>27.4 (24.9) ab</td><td>28.2 (27.2) ab</td><td>30.3 (24.7) b</td><td>30.9 (28.4) ab</td><td>31.1 (24.9) b</td></tr><tr><td>Calving in Nov-Dec (%)</td><td>29.6 (25.4) ab</td><td>28.4 (24.9) ab</td><td>30.4 (27.9) ab</td><td>32.3 (24.7) a</td><td>28.7 (24.7) ab</td><td>19.6 (20.7) b</td><td>23.3 (21.5) ab</td><td>20.6 (20) b</td></tr><tr><td rowspan="10">Revenue, subsidies, sales</td><td>Beef revenue ratioed to total revenue (%)</td><td>55.7 (10.8) a</td><td>54.9 (13.7) a</td><td>57.3 (10.3) a</td><td>48.7 (17.5) a</td><td>54.8 (13.8) a</td><td>54.9 (16.7) a</td><td>54.1 (13.5) a</td><td>53.7 (16.1) a</td></tr><tr><td>Crop revenue ratioed to total revenue (%)<sup>2</sup></td><td>6.26 (12.39) a</td><td>14.3 (17.7) bc</td><td>6.76 (11.13) ab</td><td>20.7 (21.8) c</td><td>10.2 (16.5) abc</td><td>14.6 (19.5) bc</td><td>12.2 (17.1) abc</td><td>16.3 (18.3) c</td></tr><tr><td>Subsidies ratioed to total revenue (%)</td><td>34.2 (9.8) a</td><td>26.1 (8) bc</td><td>31.7 (7.9) a</td><td>25.9 (8.8) bc</td><td>31.2 (8.9) a</td><td>25.8 (8.9) bc</td><td>29.1 (9.2) ab</td><td>25.1 (8) c</td></tr><tr><td>Sales of calves (%)<sup>2</sup></td><td>6.83 (16.66) a</td><td>13 (27.1) a</td><td>3.58 (6.81) a</td><td>6.89 (17.81) a</td><td>8.42 (19.62) a</td><td>12.5 (25.6) a</td><td>7.4 (17.21) a</td><td>9.45 (20.88) a</td></tr><tr><td>Sales of weanlings for fattening (%)<sup>2</sup></td><td>32.8 (27.4) a</td><td>27 (26.8) ab</td><td>27.4 (26.8) a</td><td>32.5 (27.3) a</td><td>26.4 (26.9) ab</td><td>20.3 (26.2) ab</td><td>23.3 (25.3) ab</td><td>19 (25.2) b</td></tr><tr><td>Sales of older weanlings for fattening (%)<sup>2</sup></td><td>17.1 (24.6) a</td><td>6.82 (16.22) ab</td><td>15.4 (21.8) a</td><td>9.26 (18.34) ab</td><td>12.7 (22.7) a</td><td>5.04 (13.16) b</td><td>7.75 (15.98) ab</td><td>5.1 (14) b</td></tr><tr><td>Sales of heifers and young bulls for fattening (%)<sup>2</sup></td><td>3.05 (10.45) a</td><td>1.02 (3.57) a</td><td>1.77 (5.44) a</td><td>0.935 (3.415) a</td><td>1.79 (4.9) a</td><td>0.484 (2.269) a</td><td>1.32 (4.73) a</td><td>0.79 (3.176) a</td></tr><tr><td>Sales of animals for slaughter excl. Calves and cull cows (%)</td><td>14.5 (20.5) a</td><td>25.1 (25.4) bc</td><td>23.5 (25.6) ab</td><td>22.1 (26.3) ab</td><td>22.9 (25.1) ab</td><td>32.6 (29.2) bc</td><td>30.6 (29.4) bc</td><td>37.9 (31.5) c</td></tr><tr><td>Sales of cull cows (%)</td><td>19.6 (8.3) a</td><td>21.5 (7.3) ab</td><td>22.1 (8.9) ab</td><td>21.5 (9.1) ab</td><td>23.5 (8.4) ab</td><td>24 (9.1) ab</td><td>24 (8.5) b</td><td>23.9 (9.8) b</td></tr><tr><td>Sales of breeder stock (%)<sup>2</sup></td><td>6.16 (10.62) ab</td><td>5.63 (8.32) ab</td><td>6.34 (10.83) a</td><td>6.7 (10.96) ab</td><td>4.26 (7.97) ab</td><td>5.1 (9.66) ab</td><td>5.66 (9.24) ab</td><td>3.87 (8.62) b</td></tr><tr><td rowspan="10">Farmer expertise</td><td>Work experience (years)<sup>2</sup></td><td>23.6 (9.8) a</td><td>21.1 (9.5) a</td><td>20.3 (9.4) a</td><td>19.2 (9.4) a</td><td>23.9 (10.4) a</td><td>23.3 (11.8) a</td><td>20.3 (9.7) a</td><td>23.2 (10.6) a</td></tr><tr><td>Feed costs (€/100 kg liveweight)<sup>2</sup></td><td>59.4 (20) a</td><td>79.1 (43.5) bc</td><td>63.9 (19.8) ab</td><td>85.1 (28.6) cd</td><td>58.8 (22.1) a</td><td>80.4 (26.6) cd</td><td>67.9 (24.6) ab</td><td>91.8 (36.2) d</td></tr><tr><td>Numerical productivity (%)<sup>2</sup></td><td>90.4 (6) a</td><td>89.8 (6.6) a</td><td>89.2 (7.3) a</td><td>90.9 (6.5) a</td><td>84.2 (10.5) b</td><td>85.1 (8.1) b</td><td>84.4 (10.3) b</td><td>83.1 (10) b</td></tr><tr><td>Utilised agricultural area (UAA) (ha)</td><td>155 (75) a</td><td>172 (77) a</td><td>183 (87) a</td><td>180 (75) a</td><td>168 (67) a</td><td>167 (76) a</td><td>172 (77) a</td><td>165 (80) a</td></tr><tr><td>Livestock units (LU)<sup>2</sup></td><td>151 (68) a</td><td>170 (76) a</td><td>168 (71) a</td><td>154 (67) a</td><td>151 (64) a</td><td>175 (93) a</td><td>161 (81) a</td><td>163 (79) a</td></tr><tr><td>Annual work units (AWU)</td><td>1.78 (0.69) a</td><td>1.87 (0.69) a</td><td>1.82 (0.59) a</td><td>1.8 (0.65) a</td><td>1.85 (0.75) a</td><td>2.04 (0.73) a</td><td>1.77 (0.7) a</td><td>1.88 (0.79) a</td></tr><tr><td>LU per AWU</td><td>90.1 (34.3) a</td><td>94.6 (34) a</td><td>95.9 (33.6) a</td><td>89.8 (33.5) a</td><td>87.6 (34.3) a</td><td>87.2 (33.9) a</td><td>93.7 (34.3) a</td><td>89.7 (33.4) a</td></tr><tr><td>Stocking rate</td><td>1.24 (0.35) a</td><td>1.54 (0.41) bcd</td><td>1.21 (0.29) a</td><td>1.55 (0.52) bc</td><td>1.24 (0.34) a</td><td>1.69 (0.58) bd</td><td>1.48 (1.05) ac</td><td>1.97 (1.36) d</td></tr><tr><td>Feed protein self-sufficiency (%)</td><td>90.8 (5.2) a</td><td>85.1 (7.5) bc</td><td>89.4 (5.2) a</td><td>83.9 (7.3) b</td><td>89.4 (7.1) a</td><td>82.3 (11) bd</td><td>86.2 (12.4) ac</td><td>78.6 (13.4) d</td></tr><tr><td>Feed energy self-sufficiency (%)</td><td>93.4 (4.4) a</td><td>90.3 (6.6) bc</td><td>92.2 (4.4) ab</td><td>89.3 (6.5) bc</td><td>91.8 (7.4) a</td><td>87.9 (10.4) bc</td><td>89.3 (11.1) ab</td><td>85.3 (12.8) c</td></tr></tbody></table>

<footnote n="1">1 Variables used in the structural equation model.</footnote>

<footnote n="2">2 Variables used in the logit models. a,b,c: values within a row with no common letter differ significantly (Wilcoxon-test: p ≤ 0.10). Standard deviations in brackets.</footnote>
Appendix B

<table><caption>**Table B1**
Correlation matrix between practices and other explanatory variables.</caption><thead><tr><th></th><th></th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th><th>12</th><th>13</th><th>14</th><th>15</th><th>16</th><th>17</th><th>18</th><th>19</th></tr></thead><tbody><tr><td rowspan="8">Feed</td><td>Estimated amount of feed grazed out of total fodder offered (%) <sup>1)</sup></td><td>1</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of corn silage feed out of total fodder offered (%) <sup>2)</sup></td><td>2</td><td>-0.32</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of grass silage feed out of total fodder offered (%) <sup>2)</sup></td><td>3</td><td>-0.15</td><td>0.17</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of wrapped hayage feed out of total fodder offered (%)</td><td>4</td><td>-0.17</td><td>-0.21</td><td>-0.39</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of hay feed out of total fodder offered (%)</td><td>5</td><td>-0.33</td><td>-0.36</td><td>-0.19</td><td>-0.10</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of straw feed out of total fodder offered (%)</td><td>6</td><td>-0.25</td><td>0.04</td><td>-0.14</td><td>0.08</td><td>-0.25</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of concentrate feed out of total ration (%)</td><td>7</td><td>-0.36</td><td>0.18</td><td>0.17</td><td>0.08</td><td>0.01</td><td>0.18</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="10">Herd management</td><td>Renewal rate (%) <sup>3)</sup></td><td>8</td><td>-0.05</td><td>0.11</td><td>0.04</td><td>-0.06</td><td>-0.19</td><td>0.14</td><td>0.04</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Meanage at first calving (months) <sup>2)</sup></td><td>9</td><td>0.04</td><td>-0.11</td><td>-0.11</td><td>0.02</td><td>0.10</td><td>0.05</td><td>-0.08</td><td>-0.19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Rate of calving before 30 months (%)</td><td>10</td><td>-0.07</td><td>0.11</td><td>0.08</td><td>-0.01</td><td>-0.05</td><td>-0.04</td><td>0.08</td><td>0.10</td><td>-0.54</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in Jan-Feb (%)</td><td>11</td><td>0.15</td><td>-0.10</td><td>-0.01</td><td>-0.10</td><td>0.02</td><td>0.02</td><td>-0.06</td><td>-0.13</td><td>0.08</td><td>-0.08</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in Mar-Apr (%) (2)</td><td>12</td><td>0.00</td><td>-0.08</td><td>-0.14</td><td>-0.10</td><td>0.15</td><td>0.08</td><td>-0.12</td><td>-0.17</td><td>0.12</td><td>-0.09</td><td>0.24</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in May-Jun (%)</td><td>13</td><td>-0.13</td><td>0.05</td><td>-0.10</td><td>-0.06</td><td>0.21</td><td>-0.06</td><td>0.02</td><td>-0.29</td><td>0.10</td><td>-0.01</td><td>-0.07</td><td>0.40</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in Jul-Aug (%)</td><td>14</td><td>-0.19</td><td>0.22</td><td>0.10</td><td>0.12</td><td>-0.04</td><td>-0.09</td><td>0.08</td><td>-0.05</td><td>-0.13</td><td>0.11</td><td>-0.27</td><td>-0.12</td><td>0.06</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in Sep-Oct (%)</td><td>15</td><td>-0.11</td><td>0.07</td><td>0.07</td><td>0.14</td><td>-0.11</td><td>-0.04</td><td>0.07</td><td>0.22</td><td>-0.13</td><td>0.11</td><td>-0.57</td><td>-0.46</td><td>-0.24</td><td>0.04</td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in Nov-Dec (%)</td><td>16</td><td>-0.18</td><td>-0.12</td><td>-0.02</td><td>-0.08</td><td>-0.04</td><td>0.06</td><td>-0.01</td><td>0.09</td><td>0.06</td><td>-0.08</td><td>-0.06</td><td>-0.35</td><td>-0.31</td><td>-0.44</td><td>-0.33</td><td></td><td></td><td></td></tr><tr><td rowspan="10">Revenue, subsidies, sales</td><td>Crop revenue allocated to total revenue (%) <sup>3)</sup></td><td>17</td><td>-0.14</td><td>0.08</td><td>-0.16</td><td>0.03</td><td>-0.11</td><td>0.39</td><td>0.07</td><td>0.20</td><td>0.00</td><td>0.02</td><td>-0.10</td><td>-0.07</td><td>-0.07</td><td>-0.20</td><td>0.05</td><td>0.21</td><td></td></tr><tr><td>Subsidies ratioed to total revenue (%)</td><td>18</td><td>0.19</td><td>-0.42</td><td>-0.12</td><td>0.03</td><td>0.39</td><td>-0.27</td><td>-0.30</td><td>-0.33</td><td>0.15</td><td>-0.13</td><td>0.17</td><td>0.17</td><td>0.08</td><td>-0.04</td><td>-0.13</td><td>-0.08</td><td>-0.55</td></tr><tr><td>Sales of calves (%)</td><td>19</td><td>-0.12</td><td>-0.13</td><td>0.06</td><td>0.01</td><td>0.26</td><td>-0.13</td><td>0.09</td><td>-0.28</td><td>0.07</td><td>-0.07</td><td>-0.06</td><td>0.10</td><td>0.31</td><td>0.12</td><td>-0.04</td><td>-0.16</td><td>-0.12</td><td>0.08</td></tr><tr><td>Sales of weanings for fattening (%) <sup>2)</sup></td><td>20</td><td>0.13</td><td>-0.24</td><td>-0.23</td><td>0.09</td><td>0.19</td><td>-0.01</td><td>-0.22</td><td>-0.09</td><td>0.06</td><td>-0.07</td><td>0.06</td><td>0.05</td><td>-0.13</td><td>-0.01</td><td>0.06</td><td>0.11</td><td>0.29</td><td>-0.20</td></tr><tr><td>Sales of older weanings for fattening (%) <sup>2)</sup></td><td>21</td><td>0.25</td><td>-0.12</td><td>-0.03</td><td>0.02</td><td>-0.02</td><td>-0.13</td><td>-0.13</td><td>-0.16</td><td>0.04</td><td>-0.07</td><td>0.11</td><td>0.04</td><td>-0.08</td><td>-0.06</td><td>-0.09</td><td>0.07</td><td>-0.14</td><td>0.17</td><td>-0.17</td></tr><tr><td>Sales of heifers and young bulls for fattening (%) <sup>2)</sup></td><td>22</td><td>0.11</td><td>-0.03</td><td>-0.08</td><td>0.05</td><td>0.07</td><td>-0.05</td><td>-0.07</td><td>-0.05</td><td>0.05</td><td>-0.04</td><td>0.03</td><td>0.19</td><td>0.02</td><td>-0.06</td><td>-0.09</td><td>0.00</td><td>-0.09</td><td>0.12</td><td>-0.07</td></tr><tr><td>Sales of animals for slaughter excluding calves and cull cows (%)</td><td>23</td><td>-0.20</td><td>0.48</td><td>0.22</td><td>-0.09</td><td>-0.34</td><td>0.17</td><td>0.31</td><td>0.21</td><td>-0.11</td><td>0.14</td><td>-0.02</td><td>-0.15</td><td>-0.14</td><td>0.12</td><td>0.07</td><td>0.00</td><td>0.08</td><td>-0.43</td><td>-0.27</td></tr><tr><td>Sales of breeder stock (%) <sup>2)</sup></td><td>24</td><td>0.02</td><td>-0.17</td><td>-0.05</td><td>0.07</td><td>0.08</td><td>-0.02</td><td>-0.09</td><td>0.01</td><td>-0.04</td><td>0.02</td><td>0.06</td><td>0.00</td><td>-0.06</td><td>-0.06</td><td>0.00</td><td>0.02</td><td>-0.07</td><td>0.12</td><td>-0.07</td></tr><tr><td>Sales of cull cows (%)</td><td>25</td><td>-0.04</td><td>0.13</td><td>0.11</td><td>-0.04</td><td>-0.16</td><td>0.06</td><td>0.02</td><td>0.50</td><td>-0.12</td><td>0.10</td><td>-0.12</td><td>-0.15</td><td>-0.17</td><td>-0.01</td><td>0.17</td><td>0.06</td><td>0.17</td><td>-0.30</td><td>-0.23</td></tr><tr><td rowspan="3">Farmer expertise</td><td>Work experience (years) <sup>2)</sup></td><td>26</td><td>-0.02</td><td>-0.02</td><td>-0.02</td><td>-0.01</td><td>0.07</td><td>-0.03</td><td>0.09</td><td>-0.02</td><td>0.03</td><td>0.02</td><td>0.00</td><td>-0.06</td><td>-0.02</td><td>-0.04</td><td>-0.02</td><td>0.04</td><td>0.03</td><td>0.02</td><td>-0.10</td></tr><tr><td>Feed costs (100 kg liveweight) <sup>2)</sup></td><td>27</td><td>-0.29</td><td>0.08</td><td>-0.02</td><td>0.10</td><td>0.11</td><td>0.10</td><td>0.45</td><td>-0.12</td><td>0.05</td><td>-0.01</td><td>-0.09</td><td>0.01</td><td>0.24</td><td>0.13</td><td>0.03</td><td>-0.13</td><td>0.15</td><td>-0.13</td><td>0.27</td></tr><tr><td>Numerical productivity (%) <sup>2)</sup></td><td>28</td><td>0.11</td><td>-0.09</td><td>0.06</td><td>0.07</td><td>-0.05</td><td>0.00</td><td>-0.06</td><td>-0.08</td><td>-0.07</td><td>0.02</td><td>0.06</td><td>-0.10</td><td>-0.14</td><td>0.02</td><td>0.01</td><td>0.05</td><td>-0.08</td><td>0.06</td><td>-0.02</td></tr><tr><td rowspan="10">Farm characteristics</td><td>Utilised agricultural area (UAA) (ha)</td><td>29</td><td>0.11</td><td>0.02</td><td>0.07</td><td>-0.04</td><td>-0.14</td><td>0.03</td><td>0.07</td><td>0.19</td><td>0.01</td><td>-0.03</td><td>0.07</td><td>-0.12</td><td>-0.15</td><td>-0.19</td><td>-0.03</td><td>0.22</td><td>0.32</td><td>-0.21</td><td>-0.26</td></tr><tr><td>Livestock units (LU) <sup>2)</sup></td><td>30</td><td>0.09</td><td>0.27</td><td>0.22</td><td>-0.10</td><td>-0.29</td><td>0.07</td><td>0.13</td><td>0.18</td><td>-0.05</td><td>0.04</td><td>0.11</td><td>-0.09</td><td>-0.12</td><td>0.05</td><td>-0.01</td><td>-0.01</td><td>-0.19</td><td>-0.20</td><td>-0.24</td></tr><tr><td>Annual work units (AWU)</td><td>31</td><td>-0.03</td><td>0.10</td><td>0.11</td><td>-0.04</td><td>-0.10</td><td>0.02</td><td>0.13</td><td>0.13</td><td>-0.04</td><td>0.02</td><td>0.06</td><td>-0.10</td><td>-0.07</td><td>0.03</td><td>0.03</td><td>-0.01</td><td>0.05</td><td>-0.06</td><td>-0.03</td></tr><tr><td>LU per AWU</td><td>32</td><td>0.16</td><td>0.20</td><td>0.14</td><td>-0.08</td><td>-0.24</td><td>-0.01</td><td>0.11</td><td>0.11</td><td>-0.01</td><td>0.02</td><td>0.04</td><td>-0.10</td><td>-0.10</td><td>0.03</td><td>0.04</td><td>-0.01</td><td>0.05</td><td>-0.17</td><td>-0.29</td></tr><tr><td>Stocking rate</td><td>33</td><td>-0.29</td><td>0.53</td><td>0.04</td><td>-0.12</td><td>-0.36</td><td>0.36</td><td>0.22</td><td>0.16</td><td>-0.09</td><td>0.08</td><td>-0.06</td><td>-0.02</td><td>0.02</td><td>0.15</td><td>0.04</td><td>-0.10</td><td>0.25</td><td>-0.47</td><td>-0.09</td></tr><tr><td>Feed protein self-sufficiency (%)</td><td>34</td><td>0.41</td><td>-0.32</td><td>0.00</td><td>-0.04</td><td>0.19</td><td>-0.40</td><td>-0.53</td><td>-0.14</td><td>0.03</td><td>-0.04</td><td>0.05</td><td>0.06</td><td>-0.02</td><td>-0.02</td><td>0.00</td><td>-0.05</td><td>-0.05</td><td>0.04</td><td>-0.22</td></tr><tr><td>Feed energetic self-sufficiency (%)</td><td>35</td><td>0.38</td><td>-0.13</td><td>0.07</td><td>-0.08</td><td>0.13</td><td>-0.45</td><td>-0.41</td><td>-0.15</td><td>-0.02</td><td>-0.02</td><td>0.08</td><td>0.05</td><td>-0.06</td><td>-0.06</td><td>0.00</td><td>-0.05</td><td>0.07</td><td>-0.24</td><td>0.29</td></tr><tr><td>Breed <sup>2)</sup></td><td>36</td><td>0.00</td><td>-0.06</td><td>0.03</td><td>0.11</td><td>0.08</td><td>-0.10</td><td>-0.12</td><td>-0.22</td><td>-0.06</td><td>0.04</td><td>-0.16</td><td>0.04</td><td>0.00</td><td>-0.02</td><td>0.20</td><td>0.15</td><td>-0.12</td><td>-0.16</td><td>0.20</td></tr><tr><td>Organic farming</td><td>37</td><td>-0.02</td><td>-0.36</td><td>-0.05</td><td>-0.03</td><td>0.23</td><td>-0.01</td><td>-0.44</td><td>0.19</td><td>0.07</td><td>-0.08</td><td>-0.02</td><td>0.13</td><td>0.06</td><td>-0.08</td><td>0.03</td><td>-0.09</td><td>-0.02</td><td>-0.19</td><td>0.17</td></tr><tr><td rowspan="2">Control variables</td><td>Year <sup>2)</sup></td><td>38</td><td>0.00</td><td>-0.02</td><td>0.00</td><td>0.11</td><td>-0.05</td><td>-0.01</td><td>-0.05</td><td>0.01</td><td>-0.02</td><td>0.08</td><td>0.00</td><td>-0.02</td><td>0.00</td><td>0.03</td><td>-0.01</td><td>0.07</td><td>-0.11</td><td>0.01</td></tr><tr><td>Less-favoured area (LFA) <sup>2)</sup></td><td>39</td><td>-0.17</td><td>0.26</td><td>-0.05</td><td>0.01</td><td>-0.19</td><td>0.31</td><td>-0.09</td><td>0.08</td><td>-0.15</td><td>0.18</td><td>-0.15</td><td>0.00</td><td>0.01</td><td>0.17</td><td>-0.13</td><td>-0.14</td><td>0.14</td><td>-0.22</td><td>0.01</td></tr><tr><td rowspan="10">Farmer expertise</td><td>Sales of weanings for fattening (%) <sup>3)</sup></td><td>20</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sales of older weanings for fattening (%) <sup>2)</sup></td><td>21</td><td>-0.25</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sales of heifers and young bulls for fattening (%) <sup>2)</sup></td><td>22</td><td>-0.04</td><td>0.07</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sales of animals for slaughter excl. calves and cull cows (%)</td><td>23</td><td>-0.60</td><td>-0.26</td><td>-0.11</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sales of breeder stock (%) <sup>2)</sup></td><td>24</td><td>0.07</td><td>-0.11</td><td>-0.04</td><td>-0.20</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sales of cull cows (%)</td><td>25</td><td>-0.13</td><td>-0.10</td><td>-0.07</td><td>0.14</td><td>-0.27</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Work experience (years) <sup>2)</sup></td><td>26</td><td>0.06</td><td>0.08</td><td>0.05</td><td>-0.01</td><td>-0.04</td><td>-0.02</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Feed costs (100 kg liveweight) <sup>2)</sup></td><td>27</td><td>0.05</td><td>-0.09</td><td>-0.09</td><td>-0.08</td><td>-0.01</td><td>-0.05</td><td>0.04</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Numerical productivity (%) <sup>2)</sup></td><td>28</td><td>0.09</td><td>-0.03</td><td>-0.08</td><td>0.15</td><td>-0.19</td><td>-0.03</td><td>-0.05</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="10">Farm characteristics</td><td>Utilised agricultural area (UAA) (ha)</td><td>29</td><td>-0.07</td><td>0.10</td><td>-0.03</td><td>0.15</td><td>-0.10</td><td>0.20</td><td>0.06</td><td>-0.09</td><td>-0.05</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Livestock units (LU) <sup>2)</sup></td><td>30</td><td>-0.25</td><td>0.08</td><td>0.01</td><td>0.35</td><td>-0.09</td><td>0.17</td><td>0.04</td><td>-0.10</td><td>-0.03</td><td>0.66</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Annual work units (AWU)</td><td>31</td><td>-0.10</td><td>-0.08</td><td>-0.05</td><td>0.14</td><td>0.05</td><td>0.06</td><td>0.09</td><td>0.00</td><td>0.02</td><td>0.55</td><td>0.59</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>LU per AWU</td><td>32</td><td>-0.19</td><td>0.19</td><td>0.05</td><td>0.27</td><td>-0.14</td><td>0.15</td><td>-0.06</td><td>-0.15</td><td>-0.05</td><td>0.21</td><td>0.54</td><td>-0.30</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Stocking rate</td><td>33</td><td>-0.22</td><td>-0.17</td><td>-0.05</td><td>0.46</td><td>-0.08</td><td>0.00</td><td>0.04</td><td>0.18</td><td>-0.12</td><td>-0.13</td><td>0.16</td><td>0.06</td><td>0.09</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Feed protein self-sufficiency (%)</td><td>34</td><td>0.13</td><td>0.17</td><td>0.06</td><td>-0.36</td><td>0.06</td><td>-0.05</td><td>-0.05</td><td>-0.50</td><td>0.12</td><td>0.01</td><td>-0.12</td><td>-0.08</td><td>-0.04</td><td>-0.60</td><td></td><td></td><td></td><td></td></tr><tr><td>Feed energetic self-sufficiency (%)</td><td>35</td><td>0.07</td><td>0.16</td><td>0.06</td><td>-0.26</td><td>0.03</td><td>-0.04</td><td>-0.05</td><td>-0.44</td><td>0.11</td><td>0.03</td><td>-0.04</td><td>-0.02</td><td>-0.02</td><td>-0.52</td><td>0.93</td><td></td><td></td><td></td></tr><tr><td>Breed <sup>2)</sup></td><td>36</td><td>-0.11</td><td>0.08</td><td>-0.02</td><td>0.04</td><td>0.10</td><td>-0.19</td><td>-0.02</td><td>-0.09</td><td>0.15</td><td>-0.16</td><td>-0.09</td><td>-0.04</td><td>-0.03</td><td>-0.07</td><td>0.17</td><td>0.15</td><td></td><td></td></tr><tr><td>Organic farming</td><td>37</td><td>0.04</td><td>-0.31</td><td>-0.20</td><td>-0.12</td><td>0.16</td><td>0.15</td><td>-0.31</td><td>-0.50</td><td>-0.08</td><td>-0.07</td><td>-0.27</td><td>-0.01</td><td>-0.29</td><td>-0.40</td><td>0.56</td><td>0.45</td><td>-0.05</td><td></td></tr><tr><td rowspan="2">Control variables</td><td>Year <sup>2)</sup></td><td>38</td><td>-0.07</td><td>0.07</td><td>-0.04</td><td>-0.01</td><td>0.01</td><td>0.08</td><td>0.07</td><td>0.07</td><td>0.03</td><td>0.08</td><td>0.02</td><td>0.01</td><td>0.01</td><td>-0.07</td><td>0.01</td><td>0.00</td><td>0.01</td><td>0.00</td><td></td></tr><tr><td>Less-favoured area (LFA) <sup>2)</sup></td><td>39</td><td>0.03</td><td>-0.18</td><td>-0.15</td><td>0.11</td><td>0.04</td><td>0.00</td><td>-0.09</td><td>-0.01</td><td>0.01</td><td>-0.31</td><td>-0.17</td><td>-0.17</td><td>-0.04</td><td>0.51</td><td>-0.24</td><td>-0.25</td><td>-0.01</td><td>-0.02</td><td>-0.09</td></tr></tbody></table>

<footnote n="1">¹Variables used in structural equation model, ²Variables used in logit models</footnote>

<footnote n="1">¹Variables used in structural equation model, (2) Variables used in logit models.</footnote>

<footnote n="2">²Variables used in logit models.</footnote>
Appendix B

<table><caption>Table B1
Correlation matrix between practices and other explanatory variables.</caption><thead><tr><th></th><th></th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th><th>12</th><th>13</th><th>14</th><th>15</th><th>16</th><th>17</th><th>18</th><th>19</th></tr></thead><tbody><tr><td rowspan="8">Feed</td><td>Estimated amount of feed grazed out of total fodder offered (%) <sup>1</sup></td><td>1</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of corn silage feed out of total fodder offered (%) <sup>2</sup></td><td>2</td><td>-0.32</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of grass silage feed out of total fodder offered (%) <sup>2</sup></td><td>3</td><td>-0.15</td><td>0.17</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of wrapped hayage feed out of total fodder offered (%)</td><td>4</td><td>-0.17</td><td>-0.21</td><td>-0.39</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of hay feed out of total fodder offered (%)</td><td>5</td><td>-0.33</td><td>-0.36</td><td>-0.19</td><td>-0.10</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of straw feed out of total fodder offered (%)</td><td>6</td><td>-0.25</td><td>0.04</td><td>-0.14</td><td>0.08</td><td>-0.25</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Amount of concentrate feed out of total ration (%)</td><td>7</td><td>-0.36</td><td>0.18</td><td>0.17</td><td>0.08</td><td>0.01</td><td>0.18</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="10">Herd management</td><td>Renewal rate (%) <sup>3</sup></td><td>8</td><td>-0.05</td><td>0.11</td><td>0.04</td><td>-0.06</td><td>-0.19</td><td>0.14</td><td>0.04</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Meanage at first calving (months) <sup>3</sup></td><td>9</td><td>0.04</td><td>-0.11</td><td>-0.11</td><td>0.02</td><td>0.10</td><td>0.05</td><td>-0.08</td><td>-0.19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Rate of calving before or 30 months (%)</td><td>10</td><td>-0.07</td><td>0.11</td><td>0.08</td><td>-0.01</td><td>-0.05</td><td>-0.04</td><td>0.08</td><td>0.10</td><td>-0.54</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in Jan-Feb (%)</td><td>11</td><td>0.15</td><td>-0.10</td><td>-0.01</td><td>-0.10</td><td>0.02</td><td>0.02</td><td>-0.06</td><td>-0.13</td><td>0.08</td><td>-0.08</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in Mar-Apr (%) (2)</td><td>12</td><td>0.00</td><td>-0.08</td><td>-0.14</td><td>-0.10</td><td>0.15</td><td>0.08</td><td>-0.12</td><td>-0.17</td><td>0.12</td><td>-0.09</td><td>0.24</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in May-Jun (%)</td><td>13</td><td>-0.13</td><td>0.05</td><td>-0.10</td><td>-0.06</td><td>0.21</td><td>-0.06</td><td>0.02</td><td>-0.29</td><td>0.10</td><td>-0.01</td><td>-0.07</td><td>0.40</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in Jul-Aug (%)</td><td>14</td><td>-0.19</td><td>0.22</td><td>0.10</td><td>0.12</td><td>-0.04</td><td>-0.09</td><td>0.08</td><td>-0.05</td><td>-0.13</td><td>0.11</td><td>-0.27</td><td>-0.12</td><td>0.06</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in Sep-Oct (%)</td><td>15</td><td>-0.11</td><td>0.07</td><td>0.07</td><td>0.14</td><td>-0.11</td><td>-0.04</td><td>0.07</td><td>0.22</td><td>-0.13</td><td>0.11</td><td>-0.57</td><td>-0.46</td><td>-0.24</td><td>0.04</td><td></td><td></td><td></td><td></td></tr><tr><td>Calving in Nov-Dec (%)</td><td>16</td><td>-0.18</td><td>-0.12</td><td>-0.02</td><td>-0.08</td><td>-0.04</td><td>0.06</td><td>-0.01</td><td>0.09</td><td>0.06</td><td>-0.08</td><td>-0.06</td><td>-0.35</td><td>-0.31</td><td>-0.44</td><td>-0.33</td><td></td><td></td><td></td></tr><tr><td rowspan="10">Revenue, subsidies, sales</td><td>Crop revenue allocated to total revenue (%) <sup>3</sup></td><td>17</td><td>-0.14</td><td>0.08</td><td>-0.16</td><td>0.03</td><td>-0.11</td><td>0.39</td><td>0.07</td><td>0.20</td><td>0.00</td><td>0.02</td><td>-0.10</td><td>-0.07</td><td>-0.07</td><td>-0.20</td><td>0.05</td><td>0.21</td><td></td></tr><tr><td>Subsidies ratioed to total revenue (%)</td><td>18</td><td>0.19</td><td>-0.42</td><td>-0.12</td><td>0.03</td><td>0.39</td><td>-0.27</td><td>-0.30</td><td>-0.33</td><td>0.15</td><td>-0.13</td><td>0.17</td><td>0.17</td><td>0.08</td><td>-0.04</td><td>-0.13</td><td>-0.08</td><td>-0.55</td></tr><tr><td>Sales of calves (%)</td><td>19</td><td>-0.12</td><td>-0.13</td><td>0.06</td><td>0.01</td><td>0.26</td><td>-0.13</td><td>0.09</td><td>-0.28</td><td>0.07</td><td>-0.07</td><td>-0.06</td><td>0.10</td><td>0.31</td><td>0.12</td><td>-0.04</td><td>-0.16</td><td>-0.12</td><td>0.08</td></tr><tr><td>Sales of weanings for fattening (%) <sup>2</sup></td><td>20</td><td>0.13</td><td>-0.24</td><td>-0.23</td><td>0.09</td><td>0.19</td><td>-0.01</td><td>-0.22</td><td>-0.09</td><td>0.06</td><td>-0.07</td><td>0.06</td><td>0.05</td><td>-0.13</td><td>-0.01</td><td>0.06</td><td>0.11</td><td>0.29</td><td>-0.20</td></tr><tr><td>Sales of older weanings for fattening (%) <sup>2</sup></td><td>21</td><td>0.25</td><td>-0.12</td><td>-0.03</td><td>0.02</td><td>-0.02</td><td>-0.13</td><td>-0.13</td><td>-0.16</td><td>0.04</td><td>-0.07</td><td>0.11</td><td>0.04</td><td>-0.08</td><td>-0.06</td><td>-0.09</td><td>0.07</td><td>-0.14</td><td>0.17</td></tr><tr><td>Sales of heifers and young bulls for fattening (%) <sup>2</sup></td><td>22</td><td>0.11</td><td>-0.03</td><td>-0.08</td><td>0.05</td><td>0.07</td><td>-0.05</td><td>-0.07</td><td>-0.05</td><td>0.05</td><td>-0.04</td><td>0.03</td><td>0.19</td><td>0.02</td><td>-0.06</td><td>-0.09</td><td>0.00</td><td>-0.09</td><td>0.12</td></tr><tr><td>Sales of animals for slaughter excluding calves and cull cows (%)</td><td>23</td><td>-0.20</td><td>0.48</td><td>0.22</td><td>-0.09</td><td>-0.34</td><td>0.17</td><td>0.31</td><td>0.21</td><td>-0.11</td><td>0.14</td><td>-0.02</td><td>-0.15</td><td>-0.14</td><td>0.12</td><td>0.07</td><td>0.00</td><td>0.08</td><td>-0.43</td></tr><tr><td>Sales of breeder stock (%) <sup>3</sup></td><td>24</td><td>0.02</td><td>-0.17</td><td>-0.05</td><td>0.07</td><td>0.08</td><td>-0.02</td><td>-0.09</td><td>0.01</td><td>-0.04</td><td>0.02</td><td>0.06</td><td>0.00</td><td>-0.06</td><td>-0.06</td><td>0.00</td><td>0.02</td><td>-0.07</td><td>0.12</td></tr><tr><td>Sales of cull cows (%)</td><td>25</td><td>-0.04</td><td>0.13</td><td>0.11</td><td>-0.04</td><td>-0.16</td><td>0.06</td><td>0.02</td><td>0.50</td><td>-0.12</td><td>0.10</td><td>-0.12</td><td>-0.15</td><td>-0.17</td><td>-0.01</td><td>0.17</td><td>0.06</td><td>0.17</td><td>-0.30</td></tr><tr><td rowspan="4">Farmer expertise</td><td>Work experience (years) <sup>3</sup></td><td>26</td><td>-0.02</td><td>-0.02</td><td>-0.02</td><td>-0.01</td><td>0.07</td><td>-0.03</td><td>0.09</td><td>-0.02</td><td>0.03</td><td>0.02</td><td>0.00</td><td>-0.06</td><td>-0.02</td><td>-0.04</td><td>-0.02</td><td>0.04</td><td>0.03</td><td>0.02</td></tr><tr><td>Feed costs (100 kg liveweight) <sup>3</sup></td><td>27</td><td>-0.29</td><td>0.08</td><td>-0.02</td><td>0.10</td><td>0.11</td><td>0.10</td><td>0.45</td><td>-0.12</td><td>0.05</td><td>-0.01</td><td>-0.09</td><td>0.01</td><td>0.24</td><td>0.13</td><td>0.03</td><td>-0.13</td><td>-0.15</td><td>0.27</td></tr><tr><td>Numerical productivity (%) <sup>3</sup></td><td>28</td><td>0.11</td><td>-0.09</td><td>0.06</td><td>0.07</td><td>-0.05</td><td>0.00</td><td>-0.06</td><td>-0.08</td><td>-0.07</td><td>0.02</td><td>0.06</td><td>-0.10</td><td>-0.14</td><td>0.02</td><td>0.01</td><td>0.05</td><td>-0.08</td><td>0.06</td></tr><tr><td>Far characteristics</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="10">Farm</td><td>Utilised agricultural area (UAA) (ha)</td><td>28</td><td>0.11</td><td>0.02</td><td>0.07</td><td>-0.04</td><td>-0.14</td><td>0.03</td><td>0.07</td><td>0.19</td><td>0.01</td><td>-0.03</td><td>0.07</td><td>-0.12</td><td>-0.15</td><td>-0.19</td><td>-0.03</td><td>0.22</td><td>0.32</td><td>-0.21</td></tr><tr><td>Livestock units (LU) <sup>3</sup></td><td>30</td><td>0.09</td><td>0.27</td><td>0.22</td><td>-0.10</td><td>-0.29</td><td>0.07</td><td>0.13</td><td>0.18</td><td>-0.05</td><td>0.04</td><td>0.11</td><td>-0.09</td><td>-0.12</td><td>0.05</td><td>-0.01</td><td>-0.01</td><td>-0.19</td><td>-0.20</td></tr><tr><td>Annual work units (AWU)</td><td>31</td><td>-0.03</td><td>0.10</td><td>0.11</td><td>-0.04</td><td>-0.10</td><td>0.02</td><td>0.13</td><td>0.13</td><td>-0.04</td><td>0.02</td><td>0.06</td><td>-0.10</td><td>-0.07</td><td>0.03</td><td>0.03</td><td>-0.01</td><td>0.05</td><td>-0.06</td></tr><tr><td>LU per AWU</td><td>32</td><td>0.16</td><td>0.20</td><td>0.14</td><td>-0.08</td><td>-0.24</td><td>-0.01</td><td>0.11</td><td>0.11</td><td>-0.01</td><td>0.02</td><td>0.04</td><td>-0.10</td><td>-0.10</td><td>0.03</td><td>0.04</td><td>-0.01</td><td>-0.05</td><td>-0.03</td></tr><tr><td>Stocking rate</td><td>33</td><td>-0.29</td><td>0.53</td><td>0.04</td><td>-0.12</td><td>-0.36</td><td>0.36</td><td>0.22</td><td>0.16</td><td>-0.09</td><td>0.08</td><td>-0.06</td><td>-0.02</td><td>0.02</td><td>0.15</td><td>0.04</td><td>-0.10</td><td>0.25</td><td>-0.47</td></tr><tr><td>Feed protein self-sufficiency (%)</td><td>34</td><td>0.41</td><td>-0.32</td><td>0.00</td><td>-0.04</td><td>0.19</td><td>-0.40</td><td>-0.53</td><td>-0.14</td><td>0.03</td><td>-0.04</td><td>0.05</td><td>0.06</td><td>-0.02</td><td>-0.02</td><td>0.00</td><td>-0.05</td><td>-0.22</td><td>0.38</td></tr><tr><td>Feed energetic self-sufficiency (%)</td><td>35</td><td>0.38</td><td>-0.13</td><td>0.07</td><td>-0.08</td><td>0.13</td><td>-0.45</td><td>-0.41</td><td>-0.15</td><td>-0.02</td><td>-0.02</td><td>0.08</td><td>0.05</td><td>0.00</td><td>-0.05</td><td>-0.07</td><td>0.02</td><td>-0.24</td><td>0.29</td></tr><tr><td>Breed <sup>3</sup></td><td>36</td><td>0.00</td><td>-0.06</td><td>0.03</td><td>0.11</td><td>0.08</td><td>-0.10</td><td>-0.12</td><td>-0.22</td><td>-0.06</td><td>0.04</td><td>-0.16</td><td>-0.06</td><td>-0.06</td><td>0.20</td><td>0.15</td><td>-0.12</td><td>-0.16</td><td>0.20</td></tr><tr><td>Organic farming</td><td>37</td><td>-0.02</td><td>-0.36</td><td>-0.05</td><td>-0.03</td><td>0.23</td><td>-0.01</td><td>-0.44</td><td>0.19</td><td>0.07</td><td>-0.08</td><td>-0.02</td><td>0.13</td><td>0.06</td><td>-0.08</td><td>0.03</td><td>-0.09</td><td>-0.02</td><td>0.19</td></tr><tr><td rowspan="2">Control variables</td><td>Year <sup>3</sup></td><td>38</td><td>0.00</td><td>-0.02</td><td>0.00</td><td>0.11</td><td>-0.05</td><td>-0.01</td><td>-0.05</td><td>0.01</td><td>-0.02</td><td>0.08</td><td>-0.02</td><td>0.00</td><td>0.03</td><td>-0.01</td><td>0.07</td><td>-0.11</td><td>0.01</td></tr><tr><td>Less-favoured area (LFA) <sup>3</sup></td><td>39</td><td>-0.17</td><td>0.26</td><td>-0.05</td><td>0.01</td><td>-0.19</td><td>0.31</td><td>-0.09</td><td>0.08</td><td>-0.15</td><td>0.18</td><td>-0.15</td><td>0.00</td><td>0.01</td><td>0.17</td><td>0.13</td><td>-0.14</td><td>0.14</td><td>-0.22</td></tr><tr><td rowspan="10">Farmer expertise</td><td>Sales of weanings for fattening (%) <sup>3</sup></td><td>20</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sales of older weanings for fattening (%) <sup>3</sup></td><td>21</td><td>-0.25</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sales of heifers and young bulls for fattening (%) <sup>3</sup></td><td>22</td><td>-0.04</td><td>0.07</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sales of animals for slaughter excl. calves and cull cows (%)</td><td>23</td><td>-0.60</td><td>-0.26</td><td>-0.11</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sales of breeder stock (%) <sup>3</sup></td><td>24</td><td>0.07</td><td>-0.11</td><td>-0.04</td><td>-0.20</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sales of cull cows (%)</td><td>25</td><td>-0.13</td><td>-0.10</td><td>-0.07</td><td>0.14</td><td>-0.27</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Work experience (years) <sup>3</sup></td><td>26</td><td>0.06</td><td>0.08</td><td>0.05</td><td>-0.01</td><td>-0.04</td><td>-0.02</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Feed costs (100 kg liveweight) <sup>3</sup></td><td>27</td><td>0.05</td><td>-0.09</td><td>-0.09</td><td>-0.08</td><td>-0.01</td><td>-0.05</td><td>0.04</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Numerical productivity (%) <sup>3</sup></td><td>28</td><td>0.09</td><td>-0.03</td><td>-0.08</td><td>0.15</td><td>-0.19</td><td>-0.03</td><td>-0.05</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="10">Farm characteristics</td><td>Utilised agricultural area (UAA) (ha)</td><td>29</td><td>-0.07</td><td>0.10</td><td>-0.03</td><td>0.15</td><td>-0.10</td><td>0.20</td><td>0.06</td><td>-0.09</td><td>-0.05</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Livestock units (LU) <sup>3</sup></td><td>30</td><td>-0.25</td><td>0.08</td><td>0.01</td><td>0.35</td><td>-0.09</td><td>0.17</td><td>0.04</td><td>-0.10</td><td>-0.03</td><td>0.66</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Annual work units (AWU)</td><td>31</td><td>-0.10</td><td>-0.08</td><td>-0.05</td><td>0.14</td><td>0.05</td><td>0.06</td><td>0.09</td><td>0.00</td><td>0.02</td><td>0.55</td><td>0.59</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>LU per AWU</td><td>32</td><td>-0.19</td><td>0.19</td><td>0.05</td><td>0.27</td><td>-0.14</td><td>0.15</td><td>-0.06</td><td>-0.15</td><td>-0.05</td><td>0.21</td><td>0.54</td><td>-0.30</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Stocking rate</td><td>33</td><td>-0.22</td><td>-0.17</td><td>-0.05</td><td>0.46</td><td>-0.08</td><td>0.00</td><td>0.04</td><td>0.18</td><td>-0.12</td><td>-0.13</td><td>0.16</td><td>0.06</td><td>0.09</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Feed protein self-sufficiency (%)</td><td>34</td><td>0.13</td><td>0.17</td><td>0.06</td><td>-0.36</td><td>0.06</td><td>-0.05</td><td>-0.05</td><td>-0.50</td><td>0.12</td><td>0.01</td><td>-0.12</td><td>-0.08</td><td>-0.04</td><td>-0.60</td><td></td><td></td><td></td></tr><tr><td>Feed energetic self-sufficiency (%)</td><td>35</td><td>0.07</td><td>0.16</td><td>0.06</td><td>-0.26</td><td>0.03</td><td>-0.04</td><td>-0.05</td><td>-0.44</td><td>0.11</td><td>0.03</td><td>-0.04</td><td>-0.02</td><td>-0.02</td><td>-0.52</td><td>0.93</td><td></td><td></td></tr><tr><td>Breed <sup>3</sup></td><td>36</td><td>-0.11</td><td>0.08</td><td>-0.02</td><td>0.04</td><td>0.10</td><td>-0.19</td><td>-0.02</td><td>-0.09</td><td>0.15</td><td>-0.16</td><td>-0.09</td><td>-0.04</td><td>-0.03</td><td>-0.07</td><td>0.17</td><td>0.15</td><td></td></tr><tr><td>Organic farming</td><td>37</td><td>0.04</td><td>-0.31</td><td>-0.20</td><td>-0.12</td><td>0.16</td><td>0.15</td><td>-0.31</td><td>-0.50</td><td>-0.08</td><td>-0.07</td><td>-0.27</td><td>-0.01</td><td>-0.29</td><td>-0.40</td><td>0.56</td><td>0.45</td><td>-0.05</td></tr><tr><td rowspan="2">Control variables</td><td>Year <sup>3</sup></td><td>38</td><td>-0.07</td><td>0.07</td><td>-0.04</td><td>-0.01</td><td>0.01</td><td>0.08</td><td>0.07</td><td>0.07</td><td>0.03</td><td>0.08</td><td>0.02</td><td>0.01</td><td>0.01</td><td>-0.07</td><td>0.01</td><td>0.00</td><td>0.01</td><td>0.00</td></tr><tr><td>Less-favoured area (LFA) <sup>3</sup></td><td>39</td><td>0.03</td><td>-0.18</td><td>-0.15</td><td>0.11</td><td>0.04</td><td>0.00</td><td>-0.09</td><td>-0.01</td><td>0.01</td><td>-0.31</td><td>-0.17</td><td>-0.17</td><td>-0.04</td><td>0.51</td><td>-0.24</td><td>-0.25</td><td>-0.01</td><td>-0.02</td></tr></tbody></table>

<footnote n="1">¹Variables used in structural equation model, ²Variables used in logit models.</footnote>

<footnote n="1">¹Variables used in structural equation model, (2) Variables used in logit models.</footnote>

<footnote n="2">²Variables used in logit models.</footnote>
<caption>**Table B2**</caption>

Comparison of mean values for animal welfare performance (AW) proxies between the Multiperforming group (performing well on all dimensions), other groups performing well on AW (AW+ groups), and groups performing poorly on AW (AW- groups), based on the panel-data logit model.

<table><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="4">Panel-data logit model</th></tr><tr><th colspan="2">Multiperforming Group</th><th rowspan="2">Other AW+ groups</th><th rowspan="2">AW- groups</th></tr><tr><th></th><th></th><th>True positives</th><th>False negatives</th></tr></thead><tbody><tr><td rowspan="3">Good feeding</td><td>Number of farms</td><td>171</td><td>116</td><td>357</td><td>645</td></tr><tr><td>AW quantile</td><td>22 (12.4) a</td><td>34 (12.2) b</td><td>32.5 (14) b</td><td>80 (14.2) c</td></tr><tr><td>Adjusted cow weight after calving (kg)<sup>1</sup></td><td>734 (71) a</td><td>748 (64) a</td><td>756 (80) a</td><td>750 (76) a</td></tr><tr><td rowspan="2">Good housing</td><td>Gross liveweight production (kg/LU)</td><td>313 (48) a</td><td>329 (55) ab</td><td>333 (61) b</td><td>345 (81) b</td></tr><tr><td>Mean building costs (€/LU)<sup>1</sup></td><td>85.3 (71.8) a</td><td>78.9 (45.3) a</td><td>80.2 (70.9) a</td><td>68.6 (49.3) a</td></tr><tr><td rowspan="2">Good health</td><td>Calf mortality (%)<sup>1</sup></td><td>5.74 (3.41) a</td><td>6.08 (2.9) a</td><td>6.09 (3.15) a</td><td>9.71 (4.89) b</td></tr><tr><td>Other-category mortality (%)<sup>1</sup></td><td>0.447 (0.773) a</td><td>0.537 (0.833) a</td><td>0.49 (0.841) a</td><td>1.26 (1.97) b</td></tr><tr><td></td><td>Pregnancy rate (%)<sup>1</sup></td><td>94.3 (4.9) a</td><td>92.9 (6.1) ab</td><td>93 (6) a</td><td>90.3 (8.9) b</td></tr><tr><td></td><td>Mean calving interval (days)</td><td>377 (13) a</td><td>379 (15) a</td><td>379 (16) a</td><td>382 (28) a</td></tr><tr><td></td><td>Rate of 400-day-plus calving intervals (%)</td><td>18.9 (11.7) a</td><td>19 (11.5) a</td><td>19.4 (13.1) a</td><td>20.6 (13.9) a</td></tr><tr><td></td><td>Dystocia rate (%)</td><td>3.78 (8.51) a</td><td>4.48 (10.16) a</td><td>3.83 (4.39) a</td><td>3.76 (5.03) a</td></tr><tr><td></td><td>Abortion rate (%)</td><td>0.322 (0.809) a</td><td>0.582 (1.104) a</td><td>0.496 (1.047) a</td><td>0.436 (1.11) a</td></tr><tr><td>Appropriate behaviour</td><td>Estimated amount of feed grazed out of total forage offered (%)<sup>1,2</sup></td><td>65.2 (6.5) a</td><td>61 (5.7) b</td><td>62.1 (7.2) b</td><td>46.1 (13.3) c</td></tr></tbody></table>

<caption>**Table B3**</caption>

Comparison of mean values for environmental performance (ENV) proxies between the Multiperforming group (performing well on all dimensions), other groups performing well on ENV (ENV + groups), and groups performing poorly on ENV (ENV - groups), based on the panel-data logit model.

<table><thead><tr><th rowspan="2"></th><th colspan="4">Panel-data logit model</th></tr><tr><th colspan="2">Multiperforming Group</th><th rowspan="2">Other ENV+ groups</th><th rowspan="2">ENV- groups</th></tr><tr><th></th><th>True positives</th><th>False negatives</th></tr></thead><tbody><tr><td>Number of farms</td><td>171</td><td>116</td><td>357</td><td>645</td></tr><tr><td>ENV quantile</td><td>23.3 (13.1) a</td><td>33.5 (12.7) b</td><td>32 (14.1) b</td><td>80 (14.2) c</td></tr><tr><td>Pesticide index per ha forage area<sup>1</sup></td><td>0.02 (0.029) a</td><td>0.027 (0.036) a</td><td>0.026 (0.034) a</td><td>0.112 (0.124) b</td></tr><tr><td>Fertiliser index per ha forage area</td><td>0.292 (0.21) a</td><td>0.398 (0.276) b</td><td>0.32 (0.263) ab</td><td>0.729 (0.459) c</td></tr><tr><td>Nitrogen balance (kg N/100 kg liveweight)<sup>1</sup></td><td>7.09 (3.37) a</td><td>9.01 (3.6) b</td><td>8.41 (3.86) b</td><td>17.9 (8.1) c</td></tr><tr><td>Energy consumption (MJ/100 kg liveweight)<sup>1</sup></td><td>1920 (400) a</td><td>2260 (480) b</td><td>2240 (510) b</td><td>3270 (2060) c</td></tr><tr><td>Permanent grassland per UAA (%)</td><td>66.8 (23.9) a</td><td>60.3 (26.6) b</td><td>54.8 (26.4) b</td><td>41.1 (23) c</td></tr></tbody></table>

<caption>**Table B4**</caption>

Comparison of mean values for economic performance (ECO) indicators between the Multiperforming group (performing well on all dimensions), other groups performing well on ECO (ECO + groups), and groups performing poorly on ECO (ECO - groups), based on the panel-data logit model.

<table><thead><tr><th rowspan="2"></th><th colspan="4">Panel-data logit model</th></tr><tr><th colspan="2">Multiperforming Group</th><th rowspan="2">Other ECO+ groups</th><th rowspan="2">ECO- groups</th></tr><tr><th></th><th>True positives</th><th>False negatives</th></tr></thead><tbody><tr><td>Number of farms</td><td>171</td><td>116</td><td>357</td><td>645</td></tr><tr><td>ECO quantile</td><td>22.7 (13.2) a</td><td>31.2 (14.2) b</td><td>33 (13.4) b</td><td>80 (14.2) c</td></tr><tr><td>Gross operating surplus ratioed to total revenue (%)<sup>1</sup></td><td>42 (6) a</td><td>37.9 (5.2) b</td><td>37.7 (5.3) b</td><td>25.6 (6.6) c</td></tr><tr><td>Gross operating surplus (€/AWU)</td><td>55,200 (19300) a</td><td>59,800 (24100) b</td><td>62,300 (25100) b</td><td>46,300 (18500) c</td></tr><tr><td>Farm income (€/farmer)</td><td>26,900 (17800) a</td><td>29,100 (24100) a</td><td>34,300 (25400) b</td><td>14,800 (20000) c</td></tr><tr><td>Cash income (€/farmer)</td><td>35,100 (17800) a</td><td>38,400 (28300) a</td><td>41,300 (25400) a</td><td>19,300 (21800) b</td></tr><tr><td>Debt-to-asset ratio (%)<sup>1</sup></td><td>27.1 (16.3) a</td><td>27.9 (14) a</td><td>30.4 (14) a</td><td>43.7 (21) b</td></tr><tr><td>Capital intensity (€/AWU)</td><td>115,300 (42600) a</td><td>139,500 (54000) b</td><td>144,600 (55300) b</td><td>145,000 (49800) b</td></tr></tbody></table>

<footnote n="1">¹ Variables used in the structural equation model.</footnote>

<footnote n="2">² Variables used in the logit models. a,b,c: values within a row with no common letter differ significantly (Wilcox-test: $p \le 0.10$). Standard deviations in brackets.</footnote>

<footnote n="1">¹ Variables used in the structural equation model. a,b,c: values within a row with no common letter differ significantly (Wilcox-test: $p \le 0.10$). Standard deviations in brackets.</footnote>

<footnote n="1">¹ Variables used in the structural equation model. a,b,c: values within a row with no common letter differ significantly (Wilcox-test: $p \le 0.10$). Standard deviations in brackets.</footnote>
<caption>**Table B2**</caption>

Comparison of mean values for animal welfare performance (AW) proxies between the Multiperforming group (performing well on all dimensions), other groups performing well on AW (AW+ groups), and groups performing poorly on AW (AW- groups), based on the panel-data logit model.

<table><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="4">Panel-data logit model</th></tr><tr><th colspan="2">Multiperforming Group</th><th rowspan="2">Other AW+ groups</th><th rowspan="2">AW- groups</th></tr><tr><th></th><th></th><th>True positives</th><th>False negatives</th></tr></thead><tbody><tr><td rowspan="3">Good feeding</td><td>Number of farms</td><td>171</td><td>116</td><td>357</td><td>645</td></tr><tr><td>AW quantile</td><td>22 (12.4) a</td><td>34 (12.2) b</td><td>32.5 (14) b</td><td>80 (14.2) c</td></tr><tr><td>Adjusted cow weight after calving (kg)<sup>1</sup></td><td>734 (71) a</td><td>748 (64) a</td><td>756 (80) a</td><td>750 (76) a</td></tr><tr><td rowspan="2">Good housing</td><td>Gross liveweight production (kg/LU)</td><td>313 (48) a</td><td>329 (55) ab</td><td>333 (61) b</td><td>345 (81) b</td></tr><tr><td>Mean building costs (€/LU)<sup>1</sup></td><td>85.3 (71.8) a</td><td>78.9 (45.3) a</td><td>80.2 (70.9) a</td><td>68.6 (49.3) a</td></tr><tr><td rowspan="2">Good health</td><td>Calf mortality (%)<sup>1</sup></td><td>5.74 (3.41) a</td><td>6.08 (2.9) a</td><td>6.09 (3.15) a</td><td>9.71 (4.89) b</td></tr><tr><td>Other-category mortality (%)<sup>1</sup></td><td>0.447 (0.773) a</td><td>0.537 (0.833) a</td><td>0.49 (0.841) a</td><td>1.26 (1.97) b</td></tr><tr><td rowspan="5">Appropriate behaviour</td><td>Pregnancy rate (%)<sup>1</sup></td><td>94.3 (4.9) a</td><td>92.9 (6.1) ab</td><td>93 (6) a</td><td>90.3 (8.9) b</td></tr><tr><td>Mean calving interval (days)</td><td>377 (13) a</td><td>379 (15) a</td><td>379 (16) a</td><td>382 (28) a</td></tr><tr><td>Rate of 400-day-plus calving intervals (%)</td><td>18.9 (11.7) a</td><td>19 (11.5) a</td><td>19.4 (13.1) a</td><td>20.6 (13.9) a</td></tr><tr><td>Dystocia rate (%)</td><td>3.78 (8.51) a</td><td>4.48 (10.16) a</td><td>3.83 (4.39) a</td><td>3.76 (5.03) a</td></tr><tr><td>Abortion rate (%)</td><td>0.322 (0.809) a</td><td>0.582 (1.104) a</td><td>0.496 (1.047) a</td><td>0.436 (1.11) a</td></tr><tr><td></td><td>Estimated amount of feed grazed out of total forage offered (%)<sup>1,2</sup></td><td>65.2 (6.5) a</td><td>61 (5.7) b</td><td>62.1 (7.2) b</td><td>46.1 (13.3) c</td></tr></tbody></table>

<caption>**Table B3**</caption>

Comparison of mean values for environmental performance (ENV) proxies between the Multiperforming group (performing well on all dimensions), other groups performing well on ENV (ENV + groups), and groups performing poorly on ENV (ENV - groups), based on the panel-data logit model.

<table><thead><tr><th rowspan="2"></th><th colspan="4">Panel-data logit model</th></tr><tr><th colspan="2">Multiperforming Group</th><th rowspan="2">Other ENV+ groups</th><th rowspan="2">ENV- groups</th></tr><tr><th></th><th>True positives</th><th>False negatives</th></tr></thead><tbody><tr><td>Number of farms</td><td>171</td><td>116</td><td>357</td><td>645</td></tr><tr><td>ENV quantile</td><td>23.3 (13.1) a</td><td>33.5 (12.7) b</td><td>32 (14.1) b</td><td>80 (14.2) c</td></tr><tr><td>Pesticide index per ha forage area<sup>1</sup></td><td>0.02 (0.029) a</td><td>0.027 (0.036) a</td><td>0.026 (0.034) a</td><td>0.112 (0.124) b</td></tr><tr><td>Fertiliser index per ha forage area</td><td>0.292 (0.21) a</td><td>0.398 (0.276) b</td><td>0.32 (0.263) ab</td><td>0.729 (0.459) c</td></tr><tr><td>Nitrogen balance (kg N/100 kg liveweight)<sup>1</sup></td><td>7.09 (3.37) a</td><td>9.01 (3.6) b</td><td>8.41 (3.86) b</td><td>17.9 (8.1) c</td></tr><tr><td>Energy consumption (MJ/100 kg liveweight)<sup>1</sup></td><td>1920 (400) a</td><td>2260 (480) b</td><td>2240 (510) b</td><td>3270 (2060) c</td></tr><tr><td>Permanent grassland per UAA (%)</td><td>66.8 (23.9) a</td><td>60.3 (26.6) b</td><td>54.8 (26.4) b</td><td>41.1 (23) c</td></tr></tbody></table>

<caption>**Table B4**</caption>

Comparison of mean values for economic performance (ECO) indicators between the Multiperforming group (performing well on all dimensions), other groups performing well on ECO (ECO + groups), and groups performing poorly on ECO (ECO - groups), based on the panel-data logit model.

<table><thead><tr><th rowspan="2"></th><th colspan="4">Panel-data logit model</th></tr><tr><th colspan="2">Multiperforming Group</th><th rowspan="2">Other ECO+ groups</th><th rowspan="2">ECO- groups</th></tr><tr><th></th><th>True positives</th><th>False negatives</th></tr></thead><tbody><tr><td>Number of farms</td><td>171</td><td>116</td><td>357</td><td>645</td></tr><tr><td>ECO quantile</td><td>22.7 (13.2) a</td><td>31.2 (14.2) b</td><td>33 (13.4) b</td><td>80 (14.2) c</td></tr><tr><td>Gross operating surplus ratioed to total revenue (%)<sup>1</sup></td><td>42 (6) a</td><td>37.9 (5.2) b</td><td>37.7 (5.3) b</td><td>25.6 (6.6) c</td></tr><tr><td>Gross operating surplus (€/AWU)</td><td>55,200 (19300) a</td><td>59,800 (24100) b</td><td>62,300 (25100) b</td><td>46,300 (18500) c</td></tr><tr><td>Farm income (€/farmer)</td><td>26,900 (17800) a</td><td>29,100 (24100) a</td><td>34,300 (25400) b</td><td>14,800 (20000) c</td></tr><tr><td>Cash income (€/farmer)</td><td>35,100 (17800) a</td><td>38,400 (28300) a</td><td>41,300 (25400) a</td><td>19,300 (21800) b</td></tr><tr><td>Debt-to-asset ratio (%)<sup>1</sup></td><td>27.1 (16.3) a</td><td>27.9 (14) a</td><td>30.4 (14) a</td><td>43.7 (21) b</td></tr><tr><td>Capital intensity (€/AWU)</td><td>115,300 (42600) a</td><td>139,500 (54000) b</td><td>144,600 (55300) b</td><td>145,000 (49800) b</td></tr></tbody></table>

<footnote n="1">¹ Variables used in the structural equation model.</footnote>

<footnote n="2">² Variables used in the logit models. a,b,c: values within a row with no common letter differ significantly (Wilcox-test: $p \le 0.10$). Standard deviations in brackets.</footnote>

<footnote n="1">¹ Variables used in the structural equation model. a,b,c: values within a row with no common letter differ significantly (Wilcox-test: $p \le 0.10$). Standard deviations in brackets.</footnote>

<footnote n="1">¹ Variables used in the structural equation model. a,b,c: values within a row with no common letter differ significantly (Wilcox-test: $p \le 0.10$). Standard deviations in brackets.</footnote>
<caption>Table B5</caption>

Contribution and significance of farm practices and other explanatory variables in two logit models assessing the probabilities of belonging to the Multiperforming group.

<table><thead><tr><th rowspan="2"></th><th rowspan="2">Variable</th><th>Panel-data logit<sup>1</sup></th><th>Standard logit<sup>2</sup></th></tr><tr><th>Coefficient</th><th>Coefficient</th></tr></thead><tbody><tr><td rowspan="3">Feed</td><td>Estimated amount of feed grazed out of total forage offered (%)</td><td>0.140*** (-0.018)</td><td>0.117*** (-0.0134)</td></tr><tr><td>Amount of corn silage feed out of total forage offered (%)</td><td>-0.0796*** (-0.0277)</td><td>-0.0596*** (-0.0196)</td></tr><tr><td>Amount of grass silage feed out of total forage offered (%)</td><td>-0.0146 (-0.0226)</td><td>-0.0231 (-0.0154)</td></tr><tr><td rowspan="2">Herd management</td><td>Renewal rate (%)</td><td>-0.00373 (-0.0239)</td><td>-0.00398 (-0.0175)</td></tr><tr><td>Mean age at first calving (months)</td><td>0.1 (-0.0745)</td><td>0.105** (-0.0508)</td></tr><tr><td rowspan="3">Revenue/sales</td><td>Calving in March-April (%)</td><td>0.0137 (-0.00965)</td><td>0.009 (-0.00668)</td></tr><tr><td>Crop revenue ratioed to total revenue (%)</td><td>-0.0221* (-0.0113)</td><td>-0.0192** (-0.00796)</td></tr><tr><td>Sales of calves (%)</td><td>0.00684 (-0.00834)</td><td>0.00348 (-0.00625)</td></tr><tr><td rowspan="3">Farmer expertise</td><td>Sales of animals for slaughter excluding calves and cull cows (%)</td><td>-0.0155** (-0.00707)</td><td>-0.0152*** (-0.00485)</td></tr><tr><td>Sales of breeder stock (%)</td><td>-0.0221 (-0.015)</td><td>-0.0167 (-0.0103)</td></tr><tr><td>Work experience (years)</td><td>0.0358** (-0.0146)</td><td>0.0305*** (-0.00987)</td></tr><tr><td rowspan="3">Farm characteristics</td><td>Numerical productivity (%)</td><td>0.131*** (-0.0204)</td><td>0.105*** (-0.014)</td></tr><tr><td>Feed costs (€/100 kg liveweight)</td><td>-0.0543*** (-0.00781)</td><td>-0.0437*** (-0.00527)</td></tr><tr><td>Livestock units (LU)</td><td>-0.00296 (-0.00253)</td><td>-0.00136 (-0.00156)</td></tr><tr><td rowspan="10">Control variables</td><td>Breed = AUBRAC (base)</td><td></td><td></td></tr><tr><td>Breed = BLONDE D'AQUITAINE</td><td>-2.973** (-1.19)</td><td>-2.290*** (-0.838)</td></tr><tr><td>Breed = CHAROLAIS</td><td>-2.043** (-0.99)</td><td>-1.608** (-0.647)</td></tr><tr><td>Breed = GASCON</td><td>1.768 (-1.977)</td><td>1.259 (-1.156)</td></tr><tr><td>Breed = LIMOUSIN</td><td>-1.766* (-0.956)</td><td>-1.325** (-0.617)</td></tr><tr><td>Breed = PARTHENAISE</td><td>-0.14 (-1.835)</td><td>0.0468 (-1.195)</td></tr><tr><td>Breed = SALERS</td><td>-1.223 (-1.037)</td><td>-0.954 (-0.666)</td></tr><tr><td>Year = 2016 (base)</td><td></td><td></td></tr><tr><td>Year = 2017</td><td>0.472 (-0.364)</td><td>0.35 (-0.324)</td></tr><tr><td>Year = 2018</td><td>-0.342 (-0.394)</td><td>-0.184 (-0.327)</td></tr><tr><td>Year = 2019</td><td>-0.795** (-0.4)</td><td>-0.548 (-0.337)</td></tr><tr><td>Year = 2020</td><td>-0.474 (-0.398)</td><td>-0.218 (-0.345)</td></tr><tr><td>Year = 2021</td><td>-0.307 (-0.386)</td><td>-0.178 (-0.345)</td></tr><tr><td>Year = 2022</td><td>0.333 (-0.41)</td><td>0.3 (-0.363)</td></tr><tr><td>Less-favoured area (LFA) = Plain (base)</td><td></td><td></td></tr><tr><td>LFA = Simple disadvantaged area</td><td>1.704*** (-0.445)</td><td>1.274*** (-0.327)</td></tr><tr><td>LFA = High-mountain</td><td>-1.817 (-1.751)</td><td>-1.478 (-1.053)</td></tr><tr><td>LFA = Mountain</td><td>1.934*** (-0.588)</td><td>1.494*** (-0.396)</td></tr><tr><td>LFA = Piedmont</td><td>1.634** (-0.682)</td><td>1.405*** (-0.434)</td></tr><tr><td>Constant</td><td>-20.43*** (-3.916)</td><td>-17.52*** (-2.728)</td></tr><tr><td>Observations</td><td>1289</td><td>1289</td></tr><tr><td>Farms</td><td>254</td><td></td></tr></tbody></table>

*** p < 0.01, ** p < 0.05, * p < 0.1.

¹ Model accounting for the panel structure of the data and for unobserved heterogeneity.

² Model considering farm-year observations as independent.

## References

Adamie, B.A., Hansson, H., 2022. Rationalising inefficiency in dairy production: evidence from an over-time approach. Eur. Rev. Agric. Econ. 49, 433–471. https://doi.org/10.1093/erae/jbaa034.

Adamie, B.A., Uehleke, R., Hansson, H., Mußhoff, O., Hüttel, S., 2022. Dairy cow welfare measures: can production economic data help? Sustainable Production and Consumption 32, 296–305. https://doi.org/10.1016/j.spc.2022.04.032.

Agabriel, J., Bastien, D., Benoit, M., Brouard, S., Devun, J., D'Hour, P., Farrié, J.-P., Leclerc, M.-C., Pottier, E., 2014. Guide de l'alimentation du troupeau bovin allaitant: vaches, veaux et génisses de renouvellement. Les incontournables. Institut de l'élevage, Paris.

Agreste, 2019. Réseau d'information comptable agricole, RICA [WWW Document]. URL https://agreste.agriculture.gouv.fr/agreste-saiku/?plugin=true&query=query/open/RICA_METRO#query/open/RICA_METRO (accessed 3.20.24).

Agreste, 2023. Réseau d'information comptable agricole. RICA [WWW Document]. URL https://agreste.agriculture.gouv.fr/agreste-saiku/?plugin=true&query=query/open/RICA_METRO_SOC2017#query/open/RICA_METRO_SOC2017 (accessed 12.20.23).

Barnes, A., Hansson, H., Billaudet, L., Leduc, G., Tasevska, G.M., Ryan, M., Thompson, B., Toma, L., Duvaleix-Tréguer, S., Tzouramani, I., 2022. European farmer perspectives and their adoption of ecological practices. EuroChoices 21, 5–12. https://doi.org/10.1111/1746-692X.12371.

Benoit, M., Mottet, A., 2023. Energy scarcity and rising cost: towards a paradigm shift for livestock. Agr. Syst. 205, 103585 https://doi.org/10.1016/j.agsy.2022.103585.

Boissy, A., Manteuffel, G., Jensen, M.B., Moe, R.O., Spruijt, B., Keeling, L.J., Winckler, C., Forkman, B., Dimitrov, I., Langbein, J., Bakken, M., Veissier, I., Aubert, A., 2007. Assessment of positive emotions in animals to improve their welfare. Physiol. Behav. 92, 375–397. https://doi.org/10.1016/j.physbeh.2007.02.003.

Botreau, R., Veissier, I., Butterworth, A., Bracke, M., Keeling, L., 2007. Definition of criteria for overall assessment of animal welfare. Animal Welfare 16, 225–228.

Bovins Croissance, 2020. Résultats 2020 des élevages bovins viande suivis par Bovins Croissance.

Brennan, M., Hennessy, T., Dillon, E., 2021. Embedding animal welfare in sustainability assessment: an indicator approach. Irish Journal of Agricultural and Food Research 60. https://doi.org/10.15212/ijafr-2020-0133.

Cameron, A.C., Trivedi, P.K., 2022. Microeconometrics Using Stata, Second ed. Stata Press, College Station.

Charroin, T., Ferrand, M., 2010. Elaboration d'un jeu de coefficients pour analyser les coûts de structure d'une exploitation. In: Application aux charges de mécanisation des systèmes de polyculture-élevage. Presented at the Rencontres Recherches Ruminants (3R), pp. 413–416.

Citepa, 2022. Inventaire des émissions de polluants atmosphériques et de gaz à effet de serre en France - Format Secten (No. 2071sec / 2022).

Coignard, M., Guatteo, R., Veissier, I., Lehébel, A., Hoogveld, C., Mounier, L., Bareille, N., 2014. Does milk yield reflect the level of welfare in dairy herds? Vet. J. 199, 184–187. https://doi.org/10.1016/j.tvjl.2013.10.011.

Collick, D., Ward, W., Dobson, H., 1989. Associations between types of lameness and fertility. Vet. Rec. 125, 103–106. https://doi.org/10.1136/vr.125.5.103.

Cordier, C., Sailley, M., Courtonne, J.-Y., Duflot, B., Cadudal, F., Perrot, C., Brion, A., Baumont, R., 2020. Quantifier les matières premières utilisées par l'alimentation animale en France et segmenter les flux jusqu'aux filières consommatrices.

Dahl, M.O., De Vries, A., Galvão, K.N., Maunsell, F.P., Risco, C.A., Hernandez, J.A., 2020. Combined effect of mastitis and parity on pregnancy loss in lactating Holstein cows. Theriogenology 143, 57–63. https://doi.org/10.1016/j.theriogenology.2019.12.002.

Davidova, S., Latruffe, L., 2007. Relationships between technical efficiency and financial management for Czech Republic farms. J Agricultural Economics 58, 269–288. https://doi.org/10.1111/j.1477-9552.2007.00109.x.

Davidova, S., Hostiou, N., Alebaki, M., Bailey, A., Bakucs, Z., Duval, J., Gouta, P., Henderson, S., Jacquot, A., Jeanneaux, P., Jendrzejewski, B., Kilcline, K., Konstantideli, V., Kostov, P., Latruffe, L., Schaller, L., Van Ruymbeke, K., Védrine, L., Veslot, J., Vranken, L., Walder, P., 2022. What does ecological farming mean for farm labour? EuroChoices 21, 21–26. https://doi.org/10.1111/1746-692X.12366.
<caption>Table B5</caption>

Contribution and significance of farm practices and other explanatory variables in two logit models assessing the probabilities of belonging to the Multiperforming group.

<table><thead><tr><th rowspan="2">Variable</th><th rowspan="2"></th><th>Panel-data logit<sup>1</sup></th><th>Standard logit<sup>2</sup></th></tr><tr><th>Coefficient</th><th>Coefficient</th></tr></thead><tbody><tr><td rowspan="3">Feed</td><td>Estimated amount of feed grazed out of total forage offered (%)</td><td>0.140*** (-0.018)</td><td>0.117*** (-0.0134)</td></tr><tr><td>Amount of corn silage feed out of total forage offered (%)</td><td>-0.0796*** (-0.0277)</td><td>-0.0596*** (-0.0196)</td></tr><tr><td>Amount of grass silage feed out of total forage offered (%)</td><td>-0.0146 (-0.0226)</td><td>-0.0231 (-0.0154)</td></tr><tr><td rowspan="2">Herd management</td><td>Renewal rate (%)</td><td>-0.00373 (-0.0239)</td><td>-0.00398 (-0.0175)</td></tr><tr><td>Mean age at first calving (months)</td><td>0.1 (-0.0745)</td><td>0.105** (-0.0508)</td></tr><tr><td rowspan="4">Revenue/sales</td><td>Calving in March-April (%)</td><td>0.0137 (-0.00965)</td><td>0.009 (-0.00668)</td></tr><tr><td>Crop revenue ratioed to total revenue (%)</td><td>-0.0221* (-0.0113)</td><td>-0.0192** (-0.00796)</td></tr><tr><td>Sales of calves (%)</td><td>0.00684 (-0.00834)</td><td>0.00348 (-0.00625)</td></tr><tr><td>Sales of animals for slaughter excluding calves and cull cows (%)</td><td>-0.0155** (-0.00707)</td><td>-0.0152*** (-0.00485)</td></tr><tr><td rowspan="3">Farmer expertise</td><td>Sales of breeder stock (%)</td><td>-0.0221 (-0.015)</td><td>-0.0167 (-0.0103)</td></tr><tr><td>Work experience (years)</td><td>0.0358** (-0.0146)</td><td>0.0305*** (-0.00987)</td></tr><tr><td>Numerical productivity (%)</td><td>0.131*** (-0.0204)</td><td>0.105*** (-0.014)</td></tr><tr><td rowspan="5">Farm characteristics</td><td>Feed costs (€/100 kg liveweight)</td><td>-0.0543*** (-0.00781)</td><td>-0.0437*** (-0.00527)</td></tr><tr><td>Livestock units (LU)</td><td>-0.00296 (-0.00253)</td><td>-0.00136 (-0.00156)</td></tr><tr><td>Breed = AUBRAC (base)</td><td></td><td></td></tr><tr><td>Breed = BLONDE D'AQUITAINE</td><td>-2.973** (-1.19)</td><td>-2.290*** (-0.838)</td></tr><tr><td>Breed = CHAROLAIS</td><td>-2.043** (-0.99)</td><td>-1.608** (-0.647)</td></tr><tr><td rowspan="5">Control variables</td><td>Breed = GASCON</td><td>1.768 (-1.977)</td><td>1.259 (-1.156)</td></tr><tr><td>Breed = LIMOUSIN</td><td>-1.766* (-0.956)</td><td>-1.325** (-0.617)</td></tr><tr><td>Breed = PARTHENAISE</td><td>-0.14 (-1.835)</td><td>0.0468 (-1.195)</td></tr><tr><td>Breed = SALERS</td><td>-1.223 (-1.037)</td><td>-0.954 (-0.666)</td></tr><tr><td>Year = 2016 (base)</td><td></td><td></td></tr><tr><td>Year = 2017</td><td>0.472 (-0.364)</td><td>0.35 (-0.324)</td></tr><tr><td>Year = 2018</td><td>-0.342 (-0.394)</td><td>-0.184 (-0.327)</td></tr><tr><td>Year = 2019</td><td>-0.795** (-0.4)</td><td>-0.548 (-0.337)</td></tr><tr><td>Year = 2020</td><td>-0.474 (-0.398)</td><td>-0.218 (-0.345)</td></tr><tr><td>Year = 2021</td><td>-0.307 (-0.386)</td><td>-0.178 (-0.345)</td></tr><tr><td>Year = 2022</td><td>0.333 (-0.41)</td><td>0.3 (-0.363)</td></tr><tr><td>Less-favoured area (LFA) = Plain (base)</td><td></td><td></td></tr><tr><td>LFA = Simple disadvantaged area</td><td>1.704*** (-0.445)</td><td>1.274*** (-0.327)</td></tr><tr><td>LFA = High-mountain</td><td>-1.817 (-1.751)</td><td>-1.478 (-1.053)</td></tr><tr><td>LFA = Mountain</td><td>1.934*** (-0.588)</td><td>1.494*** (-0.396)</td></tr><tr><td>LFA = Piedmont</td><td>1.634** (-0.682)</td><td>1.405*** (-0.434)</td></tr><tr><td>Constant</td><td>-20.43*** (-3.916)</td><td>-17.52*** (-2.728)</td></tr><tr><td>Observations</td><td>1289</td><td>1289</td></tr><tr><td>Farms</td><td>254</td><td></td></tr></tbody></table>

## References

Adamie, B.A., Hansson, H., 2022. Rationalising inefficiency in dairy production: evidence from an over-time approach. Eur. Rev. Agric. Econ. 49, 433–471. https://doi.org/10.1093/erae/jbaa034.

Adamie, B.A., Uehleke, R., Hansson, H., Mußhoff, O., Hüttel, S., 2022. Dairy cow welfare measures: can production economic data help? Sustainable Production and Consumption 32, 296–305. https://doi.org/10.1016/j.spc.2022.04.032.

Agabriel, J., Bastien, D., Benoit, M., Brouard, S., Devun, J., D'Hour, P., Farrié, J.-P., Leclerc, M.-C., Pottier, E., 2014. Guide de l'alimentation du troupeau bovin allaitant: vaches, veaux et génisses de renouvellement. Les incontournables. Institut de l'élevage, Paris.

Agreste, 2019. Réseau d'information comptable agricole, RICA [WWW Document]. URL https://agreste.agriculture.gouv.fr/agreste-saiku/?plugin=true&query=query/open/RICA_METRO#query/open/RICA_METRO (accessed 3.20.24).

Agreste, 2023. Réseau d'information comptable agricole. RICA [WWW Document]. URL https://agreste.agriculture.gouv.fr/agreste-saiku/?plugin=true&query=query/open/RICA_METRO_SOC2017#query/open/RICA_METRO_SOC2017 (accessed 12.20.23).

Barnes, A., Hansson, H., Billaudet, L., Leduc, G., Tasevska, G.M., Ryan, M., Thompson, B., Toma, L., Duvaleix-Tréguer, S., Tzouramani, I., 2022. European farmer perspectives and their adoption of ecological practices. EuroChoices 21, 5–12. https://doi.org/10.1111/1746-692X.12371.

Benoit, M., Mottet, A., 2023. Energy scarcity and rising cost: towards a paradigm shift for livestock. Agr. Syst. 205, 103585 https://doi.org/10.1016/j.agsy.2022.103585.

Boissy, A., Manteuffel, G., Jensen, M.B., Moe, R.O., Spruijt, B., Keeling, L.J., Winckler, C., Forkman, B., Dimitrov, I., Langbein, J., Bakken, M., Veissier, I., Aubert, A., 2007. Assessment of positive emotions in animals to improve their welfare. Physiol. Behav. 92, 375–397. https://doi.org/10.1016/j.physbeh.2007.02.003.

Botreau, R., Veissier, I., Butterworth, A., Bracke, M., Keeling, L., 2007. Definition of criteria for overall assessment of animal welfare. Animal Welfare 16, 225–228.

Bovins Croissance, 2020. Résultats 2020 des élevages bovins viande suivis par Bovins Croissance.

Brennan, M., Hennessy, T., Dillon, E., 2021. Embedding animal welfare in sustainability assessment: an indicator approach. Irish Journal of Agricultural and Food Research 60. https://doi.org/10.15212/ijafr-2020-0133.

Cameron, A.C., Trivedi, P.K., 2022. Microeconometrics Using Stata, Second ed. Stata Press, College Station.

Charroin, T., Ferrand, M., 2010. Elaboration d'un jeu de coefficients pour analyser les coûts de structure d'une exploitation. In: Application aux charges de mécanisation des systèmes de polyculture-élevage. Presented at the Rencontres Recherches Ruminants (3R), pp. 413–416.

Citepa, 2022. Inventaire des émissions de polluants atmosphériques et de gaz à effet de serre en France - Format Secten (No. 2071sec / 2022).

Coignard, M., Guatteo, R., Veissier, I., Lehébel, A., Hoogveld, C., Mounier, L., Bareille, N., 2014. Does milk yield reflect the level of welfare in dairy herds? Vet. J. 199, 184–187. https://doi.org/10.1016/j.tvjl.2013.10.011.

Collick, D., Ward, W., Dobson, H., 1989. Associations between types of lameness and fertility. Vet. Rec. 125, 103–106. https://doi.org/10.1136/vr.125.5.103.

Cordier, C., Sailley, M., Courtonne, J.-Y., Duflot, B., Cadudal, F., Perrot, C., Brion, A., Baumont, R., 2020. Quantifier les matières premières utilisées par l'alimentation animale en France et segmenter les flux jusqu'aux filières consommatrices.

Dahl, M.O., De Vries, A., Galvão, K.N., Maunsell, F.P., Risco, C.A., Hernandez, J.A., 2020. Combined effect of mastitis and parity on pregnancy loss in lactating Holstein cows. Theriogenology 143, 57–63. https://doi.org/10.1016/j.theriogenology.2019.12.002.

Davidova, S., Latruffe, L., 2007. Relationships between technical efficiency and financial management for Czech Republic farms. J Agricultural Economics 58, 269–288. https://doi.org/10.1111/j.1477-9552.2007.00109.x.

Davidova, S., Hostiou, N., Alebaki, M., Bailey, A., Bakucs, Z., Duval, J., Gouta, P., Henderson, S., Jacquot, A., Jeanneaux, P., Jendrzejewski, B., Kilcline, K., Konstantideli, V., Kostov, P., Latruffe, L., Schaller, L., Van Ruymbeke, K., Védrine, L., Veslot, J., Vranken, L., Walder, P., 2022. What does ecological farming mean for farm labour? EuroChoices 21, 21–26. https://doi.org/10.1111/1746-692X.12366.

<footnote>*** p < 0.01, ** p < 0.05, * p < 0.1.</footnote>

<footnote n="1">¹ Model accounting for the panel structure of the data and for unobserved heterogeneity.</footnote>

<footnote n="2">² Model considering farm-year observations as independent.</footnote>
de Vries, M., Bokkers, E.A.M., Dijkstra, T., van Schaik, G., de Boer, I.J.M., 2011. Invited review: associations between variables of routine herd data and dairy cattle welfare indicators. J. Dairy Sci. 94, 3213–3228. https://doi.org/10.3168/jds.2011-4169.

Doreau, M., Farruggia, A., Veysset, P., 2018. Aménités et impacts sur l'environnement des exploitations françaises élevant des bovins pour la viande. INRA Prod. Anim. 30, 165–178. https://doi.org/10.20870/productions-animales.2017.30.2.2242.

Dubrulle, J., Cochet, H., Chotteau, P., 2023. Soixante-dix ans d'accroissement de la productivité physique du travail en élevage bovin allaitant : le cas du bassin charolais. Economierurale 87–109. https://doi.org/10.4000/economierurale.12111.

EFSA, 2012. Scientific opinion on the welfare of cattle kept for beef production and the welfare in intensive calf farming systems. EFSA J. https://doi.org/10.2903/j.efsa.2012.2669.

EFSA Panel on Animal Health and Welfare (AHAW), Nielsen, S.S., Alvarez, J., Bicout, D. J., Calistri, P., Canali, E., Drewe, J.A., Garin-Bastuji, B., Gonzales Rojas, J.L., Gortázar Schmidt, C., Michel, V., Miranda Chueca, M.Á., Padalino, B., Pasquali, P., Roberts, H.C., Spoolder, H., Stahl, K., Velarde, A., Viltrop, A., Winckler, C., Earley, B., Edwards, S., Faucitano, L., Marti, S., de La Lama, G.C.M., Costa, L.N., Thomsen, P.T., Ashe, S., Mur, L., Van der Stede, Y., Herskin, M., 2022. Welfare of cattle during transport. EFS2 20. https://doi.org/10.2903/j.efsa.2022.7442.

European Commission, 2015. Special Eurobarometer 442: Attitudes of Europeans towards Animal Welfare, Directorate General for Health and Food Safety. TNS Political&Social. ed. Publications Office, Luxembourg.

European Commission, 2022. State of the Union 2022 Letter of Intent.

European Commission, 2023. State of the Union Address by President von der Leyen.

Faucitano, L., 2018. Preslaughter handling practices and their effects on animal welfare and pork quality. J. Anim. Sci. 96, 728–738. https://doi.org/10.1093/jas/skx064.

Fayard, D., 2013. De L'Art d'Engraisser Les Bovins Dans Le Berceau De La Charolaise. Anthropozoologica 48, 137–151. https://doi.org/10.5252/az2013n1a8.

Fischer, C., Schornberg, S., 2007. Assessing the competitiveness situation of EU food and drink manufacturing industries: an index-based approach. Agribusiness 23, 473–495. https://doi.org/10.1002/agr.20139.

Gautam, G., Nakao, T., Koike, K., Long, S.T., Yusuf, M., Ranasinghe, R.M.S.B.K., Hayashi, A., 2010. Spontaneous recovery or persistence of postpartum endometritis and risk factors for its pratiquance in Holstein cows. Theriogenology 73, 168–179. https://doi.org/10.1016/j.theriogenology.2009.08.010.

Godfray, H.C.J., Beddington, J.R., Crute, I.R., Haddad, L., Lawrence, D., Muir, J.F., Pretty, J., Robinson, S., Thomas, S.M., Toulmin, C., 2010. Food security: the challenge of feeding 9 billion people. Science 327, 812–818. https://doi.org/10.1126/science.1185383.

Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., Ray, S., 2021. Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook, Classroom Companion. Business Springer International Publishing, Cham. https://doi.org/10.1007/978-3-030-85019-7.

Hemsworth, P.H., Coleman, G.J., Barnett, J.L., Borg, S., 2000. Relationships between human-animal interactions and productivity of commercial dairy cows. J. Anim. Sci. 78, 2821. https://doi.org/10.2527/2000.78112821x.

Henningsen, A., Czekaj, T.G., Forkman, B., Lund, M., Nielsen, A.S., 2018. The relationship between animal welfare and economic performance at farm level: A quantitative study of Danish pig producers. J. Agric. Econ. 69, 142–162. https://doi.org/10.1111/1477-9552.12228.

Institut de l'Elevage et Chambres d'Agriculture, 2014. Inosys-Réseaux d'Elevage 2014-2020. In: Une plateforme collective pour la connaissance et l'innovation dans les systèmes d'élevage d'herbivores. Idole Paris, 12.

Interbev, 2022. Lancement d'une nouvelle application digitale pour la réalisation du diagnostic BoviWell en élevage [WWW Document]. URL. https://www.interbev.fr/space-presse/lancement-dune-nouvelle-application-digitale-pour-la-realisation-du-diagnostic-boviwell-en-elevage/.

IPCC, 2006. In: Eggleston, H.S., Buendia, L., Miwa, K., Ngara, T., Tanabe, K. (Eds.), 2006 IPCC guidelines for national greenhouse gas inventories. Prepared by the National Greenhouse Gas Inventories Programme. Institute for Global Environmental Strategies, Hayama, Japan.

IPCC, 2023. Summary for policymakers. In: Core Writing Team, Lee, H., Romero, J. (Eds.), Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland. https://doi.org/10.59327/IPCC/AR6-9789291691647.001.

Jiang, Y., Lee, M.-L.T., He, X., Rosner, B., Yan, J., 2020. Wilcoxon rank-based tests for clustered data with R package clusrank. J. Stat. Soft. 96 https://doi.org/10.18637/jss.v096.i06.

Krug, C., Haskell, M.J., Nunes, T., Stilwell, G., 2015. Creating a model to detect dairy cattle farms with poor welfare using a national database. Prev. Vet. Med. 122, 280–286. https://doi.org/10.1016/j.prevetmed.2015.10.014.

Lahémade, T., 2022. Témoignage de Philippe Aumeunier: "Vélages de fin d'hiver et taurillons maigres, des besoins du troupeau calés sur le cycle de l'herbe." Projet CAP PROTEINES - Témoignages d'éleveurs.

Larue, A., Moreau, S., Agabriel, J., Devun, J., Farrie, J.P., Renon, J., Brunschwig, G., Manneville, V., 2012. Bilan production-environnement de deux systèmes bovins allaitants contrastés. Presented at the Rencontres Recherches Ruminants.

Latruffe, L., 2009. Competitiveness, productivity and efficiency in the agricultural and agri-food sectors: definition, measurement, results, and suggestions for future

research. In: Report for the Organisation for Economic Co-operation and Development (OECD), 81.

Mandrekar, J.N., 2010. Receiver operating characteristic curve in diagnostic test assessment. J. Thorac. Oncol. 5, 1315–1316. https://doi.org/10.1097/JTO.b013e3181ec173d.

Maslow, A.H., 1943. A theory of human motivation. Psychol. Rev. 50, 370–396.

Matthews, L.R., Cameron, C., Sheahan, A.J., Kolver, E.S., Roche, J.R., 2012. Associations among dairy cow body condition and welfare-associated behavioral traits. J. Dairy Sci. 95, 2595–2601. https://doi.org/10.3168/jds.2011-4889.

McCaughey, W.P., Cliplef, R.L., 1996. Carcass and organoleptic characteristics of meat from steers grazed on alfalfa/grass pastures and finished on grain. Can. J. Anim. Sci. 76, 149–152. https://doi.org/10.4141/cjas96-021.

Minviel, J.J., Spiläinen, T., Latruffe, L., Bravo-Ureta, B.E., 2023. Impact of public subsidies on persistent and transient technical efficiency: evidence from French mixed crop-livestock farms. Appl. Econ. 1–16 https://doi.org/10.1080/00036846.2023.2281289.

Mounier, L., Marie, M., Lensink, B.J., 2007. Facteurs déterminants du bien-être des ruminants en élevage. INRA Prod. Anim. 20, 65–72. https://doi.org/10.20870/productions-animales.2007.20.1.3437.

Normand, J., Gruffat, D., 2023. L'engraissement des bovins avec des rations à base d'herbe améliore la qualité nutritionnelle des acides gras de leur viande. Cahiers de Nutrition et de Diététique 58, 53–69. https://doi.org/10.1016/j.cnd.2022.07.004.

Nyman, A.-K., Lindberg, A., Sandgren, C.H., 2011. Can pre-collected register data be used to identify dairy herds with good cattle welfare? Acta Vet. Scand. 53, S8. https://doi.org/10.1186/1751-0147-53-S1-S8.

Ofner, E., Amon, T., Amon, B., Lins, M., Boxberger, J., 2002. Precision of the Tgi 35 L Austrian Animal Needs Index for on-Farm Assessment of Animal Welfare (with Special Regard to the Tgi 35 L for Fattening Pigs), 24, p. 5.

Olsen, J.V., Andersen, H.M.-L., Kristensen, T., Schlægelberger, S.V., Udesen, F., Christensen, T., Sandøe, P., 2023. Multidimensional sustainability assessment of pig production systems at herd level - the case of Denmark. Livest. Sci. 270, 105208 https://doi.org/10.1016/j.livsci.2023.105208.

Petit, M., Agabriel, J., 1993. Etat corporel des vaches allaitantes Charolaises : signification, utilisation pratique et relations avec la reproduction. INRA Prod. Anim. 6, 311–318. https://doi.org/10.20870/productions-animales.1993.6.5.4212.

R Core Team, 2022. R: A Language and Environment for Statistical Computing.

Rega, C., Thompson, B., Niedermayr, A., Desjeux, Y., Kantelhardt, J., D'Alberto, R., Gouta, P., Konstantidelli, V., Schaller, L., Latruffe, L., Parachini, M.L., 2022. Uptake of ecological farming practices by EU farms: A pan-European typology. EuroChoices 21, 64–71. https://doi.org/10.1111/1746-692X.12368.

Roche, J.R., Friggens, N.C., Kay, J.K., Fisher, M.W., Stafford, K.J., Berry, D.P., 2009. Invited review: body condition score and its association with dairy cow productivity, health, and welfare. J. Dairy Sci. 92, 5769–5801. https://doi.org/10.3168/jds.2009-2431.

Sandgren, C., Lindberg, A., Keeling, L., 2009. Using a national dairy database to identify herds with poor welfare. Anim. Welf. 18, 523–532.

Schulte, H.D., Armbrecht, L., Bürger, R., Gauly, M., Musshoff, O., Hüttel, S., 2018. Let the cows graze: an empirical investigation on the trade-off between efficiency and farm animal welfare in milk production. Land Use Policy 79, 375–385. https://doi.org/10.1016/j.landusepol.2018.07.005.

StataCorp, 2021. Stata/MP.

Struijk, P.C., Kuyper, T.W., 2017. Sustainable intensification in agriculture: the richer shade of green. A review. Agron. Sustain. Dev. 37, 39. https://doi.org/10.1007/s13593-017-0445-7.

Tilman, D., Cassman, K.G., Matson, P.A., Naylor, R., Polasky, S., 2002. Agricultural sustainability and intensive production practices. Nature 418, 671–677. https://doi.org/10.1038/nature01014.

Tinitana-Bayas, R., Sanjuán, N., Jiménez, E.S., Lainez, M., Estellés, F., 2024. Assessing the environmental impacts of beef production chains integrating grazing and landless systems. Animal 18, 101059. https://doi.org/10.1016/j.animal.2023.101059.

van Calker, K.J., Berentsen, P.B.M., Romero, C., Giesen, G.W.J., Huirne, R.B.M., 2006. Development and application of a multi-attribute sustainability function for Dutch dairy farming systems. Ecol. Econ. 57, 640–658. https://doi.org/10.1016/j.ecolecon.2005.05.016.

Veysset, P., Lherm, M., Bébin, D., Roulenc, M., 2014. Mixed crop-livestock farming systems: a sustainable way to produce beef? Commercial farms results, questions and perspectives. Animal 8, 1218–1228. https://doi.org/10.1017/S1751731114000378.

Veysset, P., Lherm, M., Roulenc, M., Troquier, C., Bébin, D., 2015. Productivity and technical efficiency of suckler beef production systems: trends for the period 1990 to 2012. Animal 9, 2050–2059. https://doi.org/10.1017/S1751731115002013.

Vissers, L.S.M., Saatkamp, H.W., Oude Lansink, A.G.J.M., 2021. Analysis of synergies and trade-offs between animal welfare, ammonia emission, particulate matter emission and antibiotic use in Dutch broiler production systems. Agr. Syst. 189, 103070 https://doi.org/10.1016/j.agsy.2021.103070.

Welfare Quality, 2009. Welfare Quality Assessment Protocol for Cattle. Welfare Quality® Consortium, Lelystad, Netherlands.

Zhu, L., Schneider, K., Oude Lansink, A., 2023. Economic, environmental, and social inefficiency assessment of Dutch dairy farms based on the dynamic by-production model. Eur. J. Oper. Res. 311, 1134–1145. https://doi.org/10.1016/j.ejor.2023.05.032.
de Vries, M., Bokkers, E.A.M., Dijkstra, T., van Schaik, G., de Boer, I.J.M., 2011. Invited review: associations between variables of routine herd data and dairy cattle welfare indicators. J. Dairy Sci. 94, 3213–3228. https://doi.org/10.3168/jds.2011-4169.

Doreau, M., Farruggia, A., Veysset, P., 2018. Aménités et impacts sur l'environnement des exploitations françaises élevant des bovins pour la viande. INRA Prod. Anim. 30, 165–178. https://doi.org/10.20870/productions-animales.2017.30.2.2242.

Dubrulle, J., Cochet, H., Chotteau, P., 2023. Soixante-dix ans d'accroissement de la productivité physique du travail en élevage bovin allaitant : le cas du bassin charolais. Economierurale 87–109. https://doi.org/10.4000/economierurale.12111.

EFSA, 2012. Scientific opinion on the welfare of cattle kept for beef production and the welfare in intensive calf farming systems. EFSA J. https://doi.org/10.2903/j.efsa.2012.2669.

EFSA Panel on Animal Health and Welfare (AHAW), Nielsen, S.S., Alvarez, J., Bicout, D. J., Calistri, P., Canali, E., Drewe, J.A., Garin-Bastuji, B., Gonzales Rojas, J.L., Gortázar Schmidt, C., Michel, V., Miranda Chueca, M.Á., Padalino, B., Pasquali, P., Roberts, H.C., Spoolder, H., Stahl, K., Velarde, A., Viltrop, A., Winckler, C., Earley, B., Edwards, S., Faucitano, L., Marti, S., de La Lama, G.C.M., Costa, L.N., Thomsen, P.T., Ashe, S., Mur, L., Van der Stede, Y., Herskin, M., 2022. Welfare of cattle during transport. EFS2 20. https://doi.org/10.2903/j.efsa.2022.7442.

European Commission, 2015. Special Eurobarometer 442: Attitudes of Europeans towards Animal Welfare, Directorate General for Health and Food Safety. TNS Political&Social. ed. Publications Office, Luxembourg.

European Commission, 2022. State of the Union 2022 Letter of Intent.

European Commission, 2023. State of the Union Address by President von der Leyen.

Faucitano, L., 2018. Preslaughter handling practices and their effects on animal welfare and pork quality. J. Anim. Sci. 96, 728–738. https://doi.org/10.1093/jas/skx064.

Fayard, D., 2013. De L'Art d'Engraisser Les Bovins Dans Le Berceau De La Charolaise. Anthropozoologica 48, 137–151. https://doi.org/10.5252/az2013n1a8.

Fischer, C., Schornberg, S., 2007. Assessing the competitiveness situation of EU food and drink manufacturing industries: an index-based approach. Agribusiness 23, 473–495. https://doi.org/10.1002/agr.20139.

Gautam, G., Nakao, T., Koike, K., Long, S.T., Yusuf, M., Ranasinghe, R.M.S.B.K., Hayashi, A., 2010. Spontaneous recovery or persistence of postpartum endometritis and risk factors for its persistence in Holstein cows. Theriogenology 73, 168–179. https://doi.org/10.1016/j.theriogenology.2009.08.010.

Godfray, H.C.J., Beddington, J.R., Crute, I.R., Haddad, L., Lawrence, D., Muir, J.F., Pretty, J., Robinson, S., Thomas, S.M., Toulmin, C., 2010. Food security: the challenge of feeding 9 billion people. Science 327, 812–818. https://doi.org/10.1126/science.1185383.

Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., Ray, S., 2021. Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook, Classroom Companion. Business. Springer International Publishing, Cham. https://doi.org/10.1007/978-3-030-85019-7.

Hemsworth, P.H., Coleman, G.J., Barnett, J.L., Borg, S., 2000. Relationships between human-animal interactions and productivity of commercial dairy cows. J. Anim. Sci. 78, 2821. https://doi.org/10.2527/2000.78112821x.

Henningsen, A., Czekaj, T.G., Forkman, B., Lund, M., Nielsen, A.S., 2018. The relationship between animal welfare and economic performance at farm level: A quantitative study of Danish pig producers. J. Agric. Econ. 69, 142–162. https://doi.org/10.1111/1477-9552.12228.

Institut de l'Elevage et Chambres d'Agriculture, 2014. Inosys-Réseaux d'Elevage 2014-2020. In: Une plateforme collective pour la connaissance et l'innovation dans les systèmes d'élevage d'herbivores. Idole Paris, 12.

Interbev, 2022. Lancement d'une nouvelle application digitale pour la réalisation du diagnostic BoviWell en élevage [WWW Document]. URL. https://www.interbev.fr/space-presse/lancement-dune-nouvelle-application-digitale-pour-la-realisation-du-diagnostic-boviwell-en-elevage/.

IPCC, 2006. In: Eggleston, H.S., Buendia, L., Miwa, K., Ngara, T., Tanabe, K. (Eds.), 2006 IPCC guidelines for national greenhouse gas inventories. Prepared by the National Greenhouse Gas Inventories Programme. Institute for Global Environmental Strategies, Hayama, Japan.

IPCC, 2023. Summary for policymakers. In: Core Writing Team, Lee, H., Romero, J. (Eds.), Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland. https://doi.org/10.59327/IPCC/AR6-9789291691647.001.

Jiang, Y., Lee, M.-L.T., He, X., Rosner, B., Yan, J., 2020. Wilcoxon rank-based tests for clustered data with R package clusrank. J. Stat. Soft. 96 https://doi.org/10.18637/jss.v096.i06.

Krug, C., Haskell, M.J., Nunes, T., Stilwell, G., 2015. Creating a model to detect dairy cattle farms with poor welfare using a national database. Prev. Vet. Med. 122, 280–286. https://doi.org/10.1016/j.prevetmed.2015.10.014.

Lahémade, T., 2022. Témoignage de Philippe Aumeunier: "Vélages de fin d'hiver et taurillons maigres, des besoins du troupeau calés sur le cycle de l'herbe." Projet CAP PROTEINES - Témoignages d'éleveurs.

Larue, A., Moreau, S., Agabriel, J., Devun, J., Farrie, J.P., Renon, J., Brunschwig, G., Manneville, V., 2012. Bilan production-environnement de deux systèmes bovins allaitants contrastés. Presented at the Rencontres Recherches Ruminants.

Latruffe, L., 2009. Competitiveness, productivity and efficiency in the agricultural and agri-food sectors: definition, measurement, results, and suggestions for future

research. In: Report for the Organisation for Economic Co-operation and Development (OECD), 81.

Mandrekar, J.N., 2010. Receiver operating characteristic curve in diagnostic test assessment. J. Thorac. Oncol. 5, 1315–1316. https://doi.org/10.1097/JTO.b013e3181ec173d.

Maslow, A.H., 1943. A theory of human motivation. Psychol. Rev. 50, 370–396.

Matthews, L.R., Cameron, C., Sheahan, A.J., Kolver, E.S., Roche, J.R., 2012. Associations among dairy cow body condition and welfare-associated behavioral traits. J. Dairy Sci. 95, 2595–2601. https://doi.org/10.3168/jds.2011-4889.

McCaughey, W.P., Cliplef, R.L., 1996. Carcass and organoleptic characteristics of meat from steers grazed on alfalfa/grass pastures and finished on grain. Can. J. Anim. Sci. 76, 149–152. https://doi.org/10.4141/cjas96-021.

Minviel, J.J., Spiläinen, T., Latruffe, L., Bravo-Ureta, B.E., 2023. Impact of public subsidies on persistent and transient technical efficiency: evidence from French mixed crop-livestock farms. Appl. Econ. 1–16 https://doi.org/10.1080/00036846.2023.2281289.

Mounier, L., Marie, M., Lensink, B.J., 2007. Facteurs déterminants du bien-être des ruminants en élevage. INRA Prod. Anim. 20, 65–72. https://doi.org/10.20870/productions-animales.2007.20.1.3437.

Normand, J., Gruffat, D., 2023. L'engraissement des bovins avec des rations à base d'herbe améliore la qualité nutritionnelle des acides gras de leur viande. Cahiers de Nutrition et de Diététique 58, 53–69. https://doi.org/10.1016/j.cnd.2022.07.004.

Nyman, A.-K., Lindberg, A., Sandgren, C.H., 2011. Can pre-collected register data be used to identify dairy herds with good cattle welfare? Acta Vet. Scand. 53, S8. https://doi.org/10.1186/1751-0147-53-S1-S8.

Ofner, E., Amon, T., Amon, B., Lins, M., Boxberger, J., 2002. Precision of the Tgi 35 L Austrian Animal Needs Index for on-Farm Assessment of Animal Welfare (with Special Regard to the Tgi 35 L for Fattening Pigs), 24, p. 5.

Olsen, J.V., Andersen, H.M.-L., Kristensen, T., Schlægelberger, S.V., Udesen, F., Christensen, T., Sandøe, P., 2023. Multidimensional sustainability assessment of pig production systems at herd level - the case of Denmark. Livest. Sci. 270, 105208 https://doi.org/10.1016/j.livsci.2023.105208.

Petit, M., Agabriel, J., 1993. Etat corporel des vaches allaitantes Charolaises : signification, utilisation pratique et relations avec la reproduction. INRA Prod. Anim. 6, 311–318. https://doi.org/10.20870/productions-animales.1993.6.5.4212.

R Core Team, 2022. R: A Language and Environment for Statistical Computing. Rega, C., Thompson, B., Niedermayr, A., Desjeux, Y., Kantelhardt, J., D'Alberto, R., Gouta, P., Konstantidelli, V., Schaller, L., Latruffe, L., Parachini, M.L., 2022. Uptake of ecological farming practices by EU farms: A pan-European typology. EuroChoices 21, 64–71. https://doi.org/10.1111/1746-692X.12368.

Roche, J.R., Friggens, N.C., Kay, J.K., Fisher, M.W., Stafford, K.J., Berry, D.P., 2009. Invited review: body condition score and its association with dairy cow productivity, health, and welfare. J. Dairy Sci. 92, 5769–5801. https://doi.org/10.3168/jds.2009-2431.

Sandgren, C., Lindberg, A., Keeling, L., 2009. Using a national dairy database to identify herds with poor welfare. Anim. Welf. 18, 523–532.

Schulte, H.D., Armbricht, L., Bürger, R., Gauly, M., Musshoff, O., Hüttel, S., 2018. Let the cows graze: an empirical investigation on the trade-off between efficiency and farm animal welfare in milk production. Land Use Policy 79, 375–385. https://doi.org/10.1016/j.landusepol.2018.07.005.

StataCorp, 2021. Stata/MP.

Struijk, P.C., Kuyper, T.W., 2017. Sustainable intensification in agriculture: the richer shade of green. A review. Agron. Sustain. Dev. 37, 39. https://doi.org/10.1007/s13593-017-0445-7.

Tilman, D., Cassman, K.G., Matson, P.A., Naylor, R., Polasky, S., 2002. Agricultural sustainability and intensive production practices. Nature 418, 671–677. https://doi.org/10.1038/nature01014.

Tinitana-Bayas, R., Sanjuán, N., Jiménez, E.S., Lainez, M., Estellés, F., 2024. Assessing the environmental impacts of beef production chains integrating grazing and landless systems. Animal 18, 101059. https://doi.org/10.1016/j.animal.2023.101059.

van Calker, K.J., Berentsen, P.B.M., Romero, C., Giesen, G.W.J., Huirne, R.B.M., 2006. Development and application of a multi-attribute sustainability function for Dutch dairy farming systems. Ecol. Econ. 57, 640–658. https://doi.org/10.1016/j.ecolecon.2005.05.016.

Veysset, P., Lherm, M., Bébin, D., Roulenc, M., 2014. Mixed crop-livestock farming systems: a sustainable way to produce beef? Commercial farms results, questions and perspectives. Animal 8, 1218–1228. https://doi.org/10.1017/S1751731114000378.

Veysset, P., Lherm, M., Roulenc, M., Troquier, C., Bébin, D., 2015. Productivity and technical efficiency of suckler beef production systems: trends for the period 1990 to 2012. Animal 9, 2050–2059. https://doi.org/10.1017/S1751731115002013.

Vissers, L.S.M., Saatkamp, H.W., Oude Lansink, A.G.J.M., 2021. Analysis of synergies and trade-offs between animal welfare, ammonia emission, particulate matter emission and antibiotic use in Dutch broiler production systems. Agr. Syst. 189, 103070 https://doi.org/10.1016/j.agsy.2021.103070.

Welfare Quality, 2009. Welfare Quality Assessment Protocol for Cattle. Welfare Quality® Consortium, Lelystad, Netherlands.

Zhu, L., Schneider, K., Oude Lansink, A., 2023. Economic, environmental, and social inefficiency assessment of Dutch dairy farms based on the dynamic by-production model. Eur. J. Oper. Res. 311, 1134–1145. https://doi.org/10.1016/j.ejor.2023.05.032.