The extent that certain dairy farmer attitudes and behaviors are associated with farm business profitability

Drivers linking farmers' decision-making with farm performance: A systematic review and future research agenda

A strong aptitude for making sound decisions on a farm is closely linked to favorable farm outcomes, and this finding has been observed across diverse types of farm businesses and geographic locations. Traditionally, research in farm management has addressed the drivers of decision-making and performance as separate entities; however, this article presents novel evidence on the relationship between farmers' decision-making and farm performance. We also examine this association in various contexts of farm decision-making, spanning the past decade. Our comprehensive review encompasses 24 empirical studies conducted in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The analysis focuses on research topics, performance measures, and methodological perspectives. The findings reveal seven key research topics: farmers' management capacity; the influence of management and farm structure; farmers' emotional attachment to their businesses; personal aspects, farm characteristics, and institutional settings; the significance of farm recordkeeping; joint decisions in farm decision-making processes; and rational inefficiencies in farm decisions. Most studies employed conventional farm performance measures, including financial indicators, technical efficiency, and productivity indicators. Existing studies have predominantly used quantitative methodologies. We also identified research gaps and provide suggestions for future investigations in this field. Our results underscore the pivotal role of decision-making ability in shaping farmers' managerial capacity and, consequently, farm performance.

Modeling the profitability of investing in cooling systems in dairy farms under several intensities of heat stress in the Mediterranean

Heat stress (HS) in dairy cows affects dry matter intake, milk yield, reproduction, and culling rate. Cooling systems (CS) may partially revert these effects, but their profitability depends on the price of milk and effectiveness and cost of the CS. Because these effects may interact over time, stochastic dynamic models are useful tools to evaluate the effects of HS and the profitability of CS. Several HS intensity scenarios, from 1,000 to 31,000 temperature and humidity index load (THI_Load, units/yr), were simulated in a stochastic dynamic dairy herd simulator, with 3 milk prices (€0.28, €0.32, and €0.36/L) and 2 initial investment costs in fans and sprinklers (€100 and €200/cow). The HS and CS scenarios simulated were modeled as a function of the THI_Load to predict the technical and economic performance in 21 selected locations of the Mediterranean. The THI_Load mean of the 21 selected locations was 12,530 (ranging from 6,908 to 31,424). Heat stress reduced milk yield in a range of 346 to 1,696 L/cow per year, feeding costs in a range of €63 to €266/cow per year, and pregnancy rate in a range of 1.0 to 3.0%/yr and increased culling rates in a range of 5.7 to 16.4%/yr compared with the control scenario. The implementation of CS increased milk yield in a range from 173 to 859 L/cow per year, feeding cost in a range from €26 to €139/cow per year, and pregnancy rate in a range from 0.1 to 1.0%/yr and reduced culling rate in a range from 1.0 to 3.9%/yr compared with HS scenarios. When the THI_Load was ≤6,300, the implementation of CS was never profitable, from 6,300 to 11,000 was dependent on milk price and CS cost, and over 11,000 was consistently profitable. The Δnet margin (€/cow per year) for CS at an initial investment cost of €100/cow ranged from -9 to 239 and at an initial investment cost of €200/cow ranged from -24 to 225. The profitability of CS depends on the THI_Load, milk price, and CS cost.