Assessment of the economic and socio-territorial sustainability of cow milk production systems around coastal cities of West Africa: A case study in Benin

This study investigated antimicrobial resistance (AMR) in commensal Escherichia coli from Ethiopian dairy farms and assessed associations with farm-level antimicrobial use (AMU). A cross-sectional study was conducted in six districts across intensive, semi-intensive, and extensive dairy systems. Eighty-three farms were selected using stratified sampling, and 1149 cattle and environmental samples (faeces, udder milk, bulk tank milk, and udder, bucket and floor swabs) were collected. E. coli was isolated using standard methods, and 310 isolates were tested for susceptibility to nine antimicrobials using the Bauer-Kirby disk diffusion method. Multidrug resistance (MDR) and multiple antibiotic resistance index (MARI) were calculated. Associations among AMU, production system, and location with AMR/MARI were assessed using mixed-effects regression models. Oxytetracycline (80%) and penicillin-streptomycin (73%) were the most used antimicrobials. Penstrep use was significantly higher in central districts, whereas oxytetracycline use was lower in intensive systems. Resistance to more than one antimicrobial was detected in 89% of isolates, with high rates for tetracycline (65%), streptomycin (56%), and sulfisoxazole (43%). MDR was observed in 46.5% of the isolates. Intensive systems and sulphonamide use were statistically associated with higher odds of quinolone resistance, whereas oxytetracycline use was associated with aminoglycoside resistance. Farms in central Ethiopia had substantially higher odds of resistance to antifolates. MARI values were significantly higher in central districts and on farms using penicillin and sulphonamides. AMR in E. coli is widespread in Ethiopian dairy farms, with AMU strongly associated with MDR. Targeted interventions are urgently needed to mitigate AMR and safeguard public health.

Lower serum IgG concentrations in Montbéliarde neonatal: A comparative study on breed-specific passive transfer success.

Milk's complex biochemistry, high water activity, and nutritional content make it an ideal environment for microbial growth and reproduction. This study evaluated the quality of raw cow's milk, including physicochemical composition and bacteriological load, among dairy value chain operators in Mekelle City. A cross-sectional study design was conducted from December 2023 to June 2024, using 120 raw milk samples (Dairy farm, 80; Vendors, 20; Cafeteria, 20). Laboratory investigations, including physicochemical properties of raw cow milk were evaluated using the Lactoscan milk analyzer. The bacteriological assessments were employed to assess the total bacteriological load and total coliform count at the Microbiology Laboratory of Mekelle University College of Veterinary Science. The milk samples from dairy value chain participants were found with an average fat, protein, lactose, SNF, freezing point, density, and ash, 4.58 ± 0.94%, 3.08 ± 0.27%, 4.58 ± 0.47%, 8.44 ± 0.685%, -0.5395 ± 0.05C0°C, 1.029 ± 0.0029g/cm³, 0.67 ± 0.061%, respectively. The overall bacterial and coliform counts were 7.23 log10 CFU/mL and 4.5 log10 CFU/mL, (Mean ± S.d) respectively. The primary factors recorded affecting the quality of raw cow milk include limited awareness, poor hygienic standards, a shortage of clean water, inadequate cooling facilities, a lack of quality control systems, and the absence of a payment system based on quality. In this study, milk samples from cafeterias showed the highest mean value bacterial load, followed by vendors, whereas samples from dairy producers had the lowest mean value bacterial load. Therefore, the microbial quality of raw cow milk in the study area was low, and needs awareness creation.

ABSTRACT Dairy farming is faced with environmental, social and economic sustainability challenges, which call for the uptake of more sustainable farming practices. Policy schemes involving public and private sectors can support the uptake of more sustainable farming practices through the provision of incentives to farmers if designed appropriately. However, empirical research in designing such policy schemes is scarce. This paper examines dairy farmers’ preferences for policy attributes in environmental compensation schemes for more grass‐based feeding systems. Using data from a discrete choice experiment in Sweden and a hybrid latent class model, we find that while size of financial compensation matters, farmers’ likelihood of participation in grass‐based feeding schemes is also driven by how the financial compensation is designed and by non‐financial attributes of the policy schemes. Notably, we find three distinct groups of farmers who differ in their likelihood of participating and exhibit heterogeneous preferences for schemes with private versus public sector‐led implementation mode, and direct subsidy payment versus consumer price premium and tax relief. Furthermore, findings demonstrate that behavioral factors, including farmer attitudes toward different forms of compensation and risk aversion, partly explain the observed heterogeneous preferences. Overall, our findings highlight the need to accommodate preference heterogeneity in policy design to improve participation, especially in settings where the transition to more grass‐based feeding is challenging for farmers.

ABSTRACT Farmers' adoption of climate change mitigation practices is crucial for reducing greenhouse gas (GHG) emissions from food production. One major source of these emissions is chemical fertilizer application. Introducing clover into grassland can mitigate emissions by reducing the need for chemical fertilizers. In this study, we conduct an information experiment with over 300 Irish dairy farmers to examine how information impacts their beliefs about clover adoption, and how this in turn influences subsequent intentions. Methodologically, we contribute to the literature by combining qualitative (i.e., open‐ended questions) and quantitative (i.e., point estimates) belief elicitation measures in our experimental design. This approach provides more detailed insights into farmers' beliefs, as it captures top‐of‐mind concerns without priming responses. Our qualitative belief elicitation reveals that after exposure to the information treatments, while most farmers did not change their opinions, some shifted from concerns such as ‘ bloat ’ and ‘ difficult ’ to terms like ‘ reduction ’ and ‘ possible ’. Our quantitative measures show that farmers underestimated clover's potential to reduce chemical fertilizer use. This finding is key for policymakers, as similar underestimations may apply to other GHG mitigation practices. Importantly, we provide causal evidence that information could reduce misperceptions. This highlights the need for strategies that positively shift beliefs to encourage more widespread uptake of climate change mitigation practices. Nonetheless, there was no meaningful impact of the updated beliefs on intentions, which underlines the complexity of adoption decisions.

Financial analysis of a dairy farm in the state of Rio Grande do Sul in 2022

Effect of trace mineral injection during the dry period on the occurrence of clinical mastitis in the first 30 days post-partum in dairy cows.

Background: Keeping in view the majority population under marginal and small category, dairy enterprise is considered as one of the major agri-allied sectors. It has capability to improve economics of rural households and hence hunger, poverty and sustainability. Using cutting-edge statistical techniques, this study assesses the productivity, resource allocation and economic efficiency of dairy farms in four significant bovine-rearing states in India. Methods: Four hundred farms (smallholder, family-operated and semi-commercial) in Uttar Pradesh, Maharashtra, Punjab and Andhra Pradesh were selected using stratified simple random sampling. Data envelopment analysis (DEA), principal component analysis (PCA), cluster analysis and stochastic frontier analysis (SFA) were used to analyze the data. Result: Findings indicate notable typological and geographical variations in profitability, input use and efficiency. Due to input misallocation and a lesser adoption of technology, smallholder farms fell behind semi-commercial farms in terms of technical and economic efficiency. Input access, customized extension services and best-practice scaling are highlighted in policy proposals. Additionally, the results provide solid benchmarks and practical advice for policy development and farm improvement.

Background: The study is motivated by the persistent low productivity of dairy cattle farming in Bogor Regency, specifically within the Kawasan Usaha Peternakan (KUNAK), which has been further aggravated by the Foot and Mouth Disease (FMD) outbreak and inefficient input management in the area. The sector faces significant challenges, including the dominance of smallholder farms with poor feed management, shrinking land for forage, and heavy reliance on imports, all of which weaken local farmers’ bargaining power.Purpose: This study aimed to analyze the factors influencing milk production, technical efficiency, and farm profitability in KUNAK. It seeks to evaluate how effectively farmers manage inputs, such as cattle and feed, to maximize output and determine the financial feasibility of these operations post-FMD.Design/methodology/approach: Data were collected from 67 purposively sampled farmers in Cibungbulang and Pamijahan (January–April 2025) who owned cows in their second or third lactation. This study utilized a stochastic frontier translog production function estimated via Maximum Likelihood Estimation (MLE) to measure technical efficiency, alongside a revenue-cost (R/C) ratio analysis for profitability.Findings/Result: MLE results indicated that lactating cows (0.656), concentrate (0.193), and tofu dregs (0.159) significantly affected milk yield. Conversely, labor's negative elasticity (-0.083) reflects severe overutilization. The farms operate under increasing returns to scale, with a high mean technical efficiency of 0.868. Efficiency improves with farmer age but declines as the number of family dependents increases. While economically feasible (R/C ratio=1.10), operations face tight profit margins of Rp207,951 per head per month.Conclusion: Although smallholder dairy farming in the KUNAK cluster demonstrates high technical efficiency (0.868), this operational mastery does not translate into proportional economic welfare due to low market pricing and high input costs. Policy interventions must target labor reallocation and cooperative pricing reforms to bridge the gap between technical proficiency and economic sustainability.Originality/value (State of the art): This study contributes a post-FMD analysis of smallholder dairy clusters, revealing a critical disconnect where high technical efficiency does not guarantee economic welfare due to external market and institutional failures. Keywords: dairy cattle, production function, profitability, stochastic frontier, technical efficiency

Milk cells are mirrors of mammary health and immune responses in dairy cows. However, their specific physiological or pathological significance in cows with high somatic cell count (SCC) remains poorly understood. Dysregulation of milk cell physiology may contribute to inflammatory responses and impact mammary health and milk production. By investigating the composition and function of milk cells in high and low SCC cows, our study aimed to identify SCC-associated biological processes in the mammary gland. Sixteen animals were divided as two groups, SCC-h group (n = 8, milk SCC > 200 × 103/mL) and SCC-l group (n = 8, milk SCC < 100 × 103/mL). The milk performance traits of dairy cows were assessed, and RNA sequencing of milk cells was conducted. Metabolomic analysis was performed to identify 'find-me' signals associated with efferocytosis. The expression patterns of genes involved in apoptotic and non-apoptotic cell death, actin remodelling and efferocytosis were analysed. The protein levels of inflammatory and anti-inflammatory genes and nuclear receptors were determined. The immune microenvironment in milk cells was also dissected to understand the dysregulation in high SCC cows. The results showed increased expressions of key genes associated with apoptosis, necroptosis and pyroptosis in the high SCC group. However, the 'find-me' signals and 'eat-me' signals in the high SCC group were reduced compared with the low SCC group. Therefore, the protein levels of IL-1β and nuclear factor kappa B subunit 1 (NFκB1) levels were increased, whereas the protein level of peroxisome proliferator-activated receptor γ (PPARγ) was decreased in high SCC group. These results demonstrated an enhanced pro-inflammatory signalling and altered immune microenvironment of milk cells in high SCC group. The high SCC group showed higher proportions of various types of immune cells, including dendritic cell, neutrophil and CD8+ T cell, indicating a pro-inflammatory immune microenvironment. Our study highlights the dysregulation of efferocytosis and immune microenvironment in milk cells of high SCC cows, potentially contributing to chronic inflammation and impaired mammary gland health. Reviving proper efferocytic function and rebalancing the immune microenvironment are essential for enhancing disease management and improving dairy cow welfare and productivity. Understanding the significance of milk cells in udder health can facilitate targeted interventions to optimise milk production and maintain mammary health in dairy farming.

Bovine raw milk with high bacterial and somatic cell counts (SCC) may affect food safety and market competitiveness in the dairy sector. This study investigated how a structured hygiene intervention protocol affects milk quality and safety on Albanian dairy farms. From August 2024 to March 2025, five dairy farms of an average herd size of 22.6±2.25 (standard error) were visited bimonthly. Before and after a thorough hygiene intervention, bulk tank milk was tested for total plate count (TPC), SCC, antibiotic residues, Clostridium spp. spore count, and California Mastitis Test (CMT) screening test. The intervention resulted in substantial decreases in microbial load on the majority of farms (p<0.05). The average log10 reduction in TPC varied from -0.89 to 2.40, with 80% of farms exhibiting improved hygienic conditions. As a result of monthly CMT monitoring, SCC levels consistently adhered to European Union regulatory limits (<5.6 log10 cfu/mL) across all farms during the study period. A robust positive correlation was identified between log10 SCC and log10 TPC (r=0.66, p<0.05). Analysis of variance established that CMT sum scores were a highly significant predictor of both log10SCC (F=31.45, p<0.05) and log10 TPC (F=9.82, p<0.05). β-lactams were identified in only one farm (1 out of 35 milk samples in total, 2.9%). Implementing targeted on-farm ten-step hygiene protocols can significantly diminish microbial contamination in raw milk. A significant correlation was observed between SCC and TPC, highlighting the importance of good hygiene practices. This study provides a scalable model for improving milk quality in small-scale dairy production systems.

Introduction Climate-smart livestock (CSL) practices have the potential to boost food production while improving the resilience and environmental sustainability of agricultural systems in sub-Saharan Africa. However, their adoption rates in the region remain low. Focusing on Uganda as a case study, multivariate Probit and Tobit regression models were applied to determine the factors influencing the adoption of CSL practices by dairy farmers. Methods Data were collected from 626 cattle-keeping households located in southwestern, central and eastern Uganda. The Adoption and Diffusion Outcome Prediction Tool (ADOPT) was used to predict the peak adoption levels and the number of years to reach these for CSL practices. The CSL practices identified and considered were forage cultivation, artificial insemination, routine vaccination and planting trees. Results and Discussion The results showed that 37%, 14%, 45% and 19% of cattle-keeping households grew forage, used artificial insemination, carried out routine vaccination and planted trees respectively. Forage cultivation, artificial insemination use and planting trees were positively and significantly influenced by access to credit and keeping farm records. Use of artificial insemination was associated with higher milk revenues. The household head’s education level significantly influenced both the area allocated to forage cultivation and the number of trees planted. Households that allocated a large portion of their land to grazing cattle were less likely to grow forage and use artificial insemination. The number of trees planted was positively and significantly influenced by the age of the household head, household size, keeping farm records, access to credit and total adult equivalent (total number of working hours among adults per household). Forage cultivation and use of artificial insemination were practiced interdependently, pointing to the existence of complementarities and synergies between these two practices. The complementarities and synergies between both practices should be explored for increased adoption. Conclusion CSL practices should be introduced as a package of practices rather than as stand-alone practices, as their complementarities can enhance adoption. Development programs and policies should focus on improving access to credit, while investing in capacity building for record keeping, to increase the likelihood for adoption and intensification of CSL in the region.

Objective: To identify the presence of Chlamydia sp. in the municipality of Coatepec, Veracruz, Mexico Design/methodology/approach: A total of 60 animals from five dairy goat farms were included, comprising 57 females and three males of varying ages and breed phenotypes. Samples were obtained via vaginal and preputial swabs and placed in sterile conical tubes. Endpoint PCR was performed for the detection of the ompA VD2 gene with an amplification of 576 bp. Statistical analysis was conducted using the chi-square test for prevalence and a 2x2 contingency table for the analysis of risk factors. Results: An overall prevalence of 5.0% was obtained from the samples collected, with three females (5.26%) aged 48 months-old (6.1%), and 36 months (12.5%) months-old. A 6.8% of positive samples belonged to the alpine and saanen breed phenotypes; however, no risk factor attributable to the variables found was identified (p&gt;0.05). Limitations on study/implications: The study has a small sample size and reduced UPP, which may limit the representativeness of the results, which may underestimate the true prevalence of the agent. Findings/conclusions: The presence of Chlamydia sp. in goats in the central region of the state of Veracruz has been confirmed, highlighting the usefulness of PCR as a diagnostic tool. These results underscore the need to expand health surveillance and strengthen prevention measures in goat production systems.

Abstract New Zealand dairy farmers rely on industry-supported genetic indices in the National Breeding Objective, including Breeding Worth, Production Worth, and Lactation Worth to guide selection and culling. Animals without pedigree or genomic data receive low-reliability breed-average values, limiting early decisions. We developed phenotype-based “New Zealand Entry Evaluations” (NZEE) that predict BW, PW and LW from early-lactation records. First-lactation heifers (n = 60; Friesian, Jersey, or dual-purpose [Norwegian Red/Fleckvieh]) in a spring-calving pasture herd were recorded at ~100 days in milk for milk volume, fat, protein and somatic cell count; mature liveweight breeding value (BVW) was used as a body-size proxy. Multiple regression models predicted NZEEBW, NZEEPW, NZEELW, FATBV and PROTBV without pedigree or genomic inputs; breed-group means were compared by one-way ANOVA. NZEE predictions correlated strongly with industry indices (r = 0.87 for LW, 0.82 for BW, 0.75 for PW), explaining 55–78% of variation. NZEEBW aligned more closely with measured milk solids than pedigree-based BW. Breed effects were significant for fat and protein breeding values (Friesian vs Jersey; P &lt; 0.05) but not for NZEEBW, NZEEPW or NZEELW (P &gt; 0.05). These models enable earlier ranking of non-pedigreed heifers using routinely collected on-farm data. Information © The Authors 2026

Dairy manure contains bacterial and viral pathogens that can infect livestock and humans. These pathogens present a risk of airborne transport when bioaerosols are generated from land-applied manure. The transport range and distribution of fecal bioaerosols around dairy farms could be studied using microbial source tracking (MST) markers and bovine enteric viruses, but their applicability and limitations have not been studied for this purpose. This study investigated the distribution of ruminant-specific MST markers and bovine enteric viruses in air samples from a working dairy farm (Jun 2024-Jan 2025) and assessed their recovery using the InnovaPrep Cub ACD-210 air sampler. Markers included ruminant Bacteroides, Bacteroidales-like CowM3, the bacterial 16S rRNA gene, five bovine-specific enteric viruses, and two bacteriophages (MS2 and phiX174). Sampling locations included indoor, naturally and mechanically ventilated livestock barns and outdoor control locations. Bacterial MST markers were detected more frequently than bovine enteric viruses, on 19/19 sample dates versus 7/19 sample dates, and ruminant Bacteroides occurred at a higher concentration than CowM3, for example, at mean concentrations of 262,803 genomic copies/m3 versus 7,853 genomic copies/m3 in the naturally ventilated barn. Bacteriophages were never detected. The Cub recovered higher concentrations of bacterial markers than comparison gelatin filter button samplers, by average factors of 6.3-21.0. Recovery of viruses by the Cub appeared comparable to button samplers. Results inform the development of bioaerosol sampling strategies on dairy farms, which could be used for biomonitoring during outbreaks and understanding endemic spread of infectious disease on and between livestock farms.IMPORTANCEHighly pathogenic avian influenza (HPAI) is a pressing health concern for the dairy industry, and recent advances have highlighted a need to understand its distribution in fecal bioaerosols on and around dairy farms. Microbial source tracking (MST) markers and bovine enteric viruses could be key tools in advancing this line of research, but their application and limitations with respect to air sampling have not been well-studied. This study assessed the distribution of bacterial MST markers and bovine enteric viruses on a working HPAI-free dairy farm. The results provide a basis for selecting among several competing markers and sampling technologies and highlight areas where additional development is needed to formulate effective bioaerosol sampling strategies for dairy farms.

Addressing the issue of high mastitis incidence in cows is critically important for Russian agriculture as it directly impacts the national food security, the economic efficiency of the agro-industrial complex, and the veterinary well-being of dairy farming. Kholmogory cows, one of the oldest domestic dairy breeds, are well-adapted to harsh climates, undemanding in their feeding requirements, and quite sturdy, which makes them a popular subject of marker-assisted selection. This article describes the incidence of mastitis in Kholmogory breed cows at an agricultural breeding enterprise in the Arkhangelsk Region. A comprehensive study of lectin (MBL1) genotypes linked the incidence of mastitis with MBL1 genotypes. The MBL1C allele of the lectin gene dominated in the cattle sample with a frequency of 54.1% while the frequency of the MBL1T allele was 45.9%. Out of 524 cows, 349 contracted mastitis one or more times during the entire observation period, accounting for 66.6% of the herd. The highest incidence of mastitis among the animals with MBL1 genotypes belonged to the group with the MBL1TT genotype – 72.4% (76 / 105 cows). A total of 1,197 cases of mastitis was recorded in the herd during the observation period. The largest number of mastitis cases (628) was registered in the animals with the MBL1TC genotype, which constituted 52.5% of the total number of mastitis cases in the entire sample. The average number of mastitis cases in cows with different MBL1 genotypes increased from the first to the third and subsequent lactations. The gene for mannose-binding lectin (MBL) requires further study and could serve as a genetic marker for cow resistance to udder diseases. Furthermore, the practical application of this research enables the development of a reliable and timely epizootiological herd modeling.

This study investigated the occurrence of antibiotic-resistantShigellaspp. within a dairy farm environment by examining 200 samples collected from cattle (milk, faeces), environmental sources (drinking water, dairy wastewater, milking machine swabs), and human handlers. Shigellaspp. was detected in 8.5% of samples, with the highest occurrence in dairy wastewater (52.94%) and feces (35.29%). S. flexneri was the predominant species identified, while S. dysenteriae and S. sonnei were less frequent. Notably, no Shigella spp. were found in milk or handler swabs. High antibiotic resistance was observed, with complete resistance to ampicillin (100%), followed by tetracycline (82.4%) and cefoxitin (58.8%). Conversely, isolates were largely susceptible to meropenem (94.1%), ampicillin-sulbactam (94.1%), and cefepime (88.2%). Multidrug resistance (MDR) was common, affecting 70.6% of isolates. Phenotypic tests confirmed extended-spectrum β-lactamase (ESBL) production in ten isolates and AmpC production in eight cefoxitin-resistant isolates. The multiple antibiotic resistance (MAR) index was ≥ 0.2 in 94.1% of isolates. Genotypic analysis revealed a high prevalence of tetracycline resistance genes (tetA, tetB; 70.5%), plasmid-mediated quinolone resistance genes (qnrS, qnrB; 58.8%), and blaAmpC gene (52.9%). ESBL genes (blaTEM-1, blaSHV-1, blaCTX-M-9) were present in 17.6% of isolates, while the trimethoprim resistance gene (dfrA17) was detected in 5.8%. Chi-square analysis confirmed significant differences in prevalence, resistance profiles, and gene distribution (p < 0.05). These findings highlight the occurrence of multidrug-resistant Shigella spp. within the dairy farm ecosystem, underscoring their potential role in the dissemination of antibiotic resistance and posing an emerging public-health concern.

Purpose This study investigates economies of scale and the minimum economically viable production scale within Brazilian dairy farming, focusing on the milk production stabilization period from 2014 to 2024. Design/methodology/approach Econometric models, specifically the Translog (TL) cost function, were applied to estimate cost elasticities of an unbalanced panel data from 1,213 participating dairy farms. Findings Findings indicate that all analyzed farms operated under economies of scale (increasing returns), with no observed trend towards convergence to the optimal production scale. A consistent increase in average production costs was identified over the period, raising the minimum break-even scale from 849 to 1,145 liters per day. While most farms in the sample exceeded this viability threshold, comparisons with official census data suggest that the average Brazilian dairy farm operates below the required scale. The analysis also revealed a moderate and statistically significant positive relationship between milk price and production volume. Research limitations/implications Despite limitations regarding sample representativeness, this study provides crucial insights for understanding the dynamics of economic sustainability in the dairy sector and for developing public policies and business strategies. Social implications The high proportion of dairy farms operating below the minimum viable scale, particularly those outside specialized programs, suggests potential threats to rural livelihoods and small-scale producers’ long-term survival. Public policies are crucial to mitigate the social and economic disparities resulting from increased production costs and the challenge of achieving scale economies, ensuring a more equitable and sustainable development of the dairy sector and preventing rural exodus. Originality/value This study offers novel insights by dynamically analyzing economies of scale in Brazilian dairy farming during a unique period of production stabilization, addressing research gaps often overlooked in studies focusing solely on expansion phases. The application of a flexible TL cost function with panel data from a large, diverse sample provides a nuanced understanding of scale elasticities and break-even points.

This study aims to assess the current state of human resource recruitment in Mongolia’s dairy farming sector and to examine how key employee-related factors—professional knowledge, professional experience, professional skills, communication, and attitude—affect organizational management effectiveness. These dimensions were selected as they represent critical components of employee competence and behavioral performance that directly influence recruitment quality and managerial outcomes. The research adopts a quantitative approach, employing hypothesis testing and statistical techniques including reliability analysis, correlation analysis, and path analysis. Data were collected from employees working in dairy farm enterprises, and the proposed model evaluates the relationship between the selected variables and organizational management effectiveness. The findings reveal that professional competence has a statistically significant and positive impact on organizational management. Among the examined factors, professional experience and professional knowledge demonstrate strong effects, while communication and attitude play a crucial role in shaping workplace interactions and employee performance. Professional skills are also found to contribute meaningfully to task execution and overall management efficiency. The results suggest that these factors collectively enhance both individual and team performance within organizations. This study contributes to the literature by providing empirical evidence from the dairy farming sector in Mongolia, a relatively underexplored context in human resource management research. The findings offer practical implications for improving recruitment strategies by emphasizing competence-based selection and the integration of behavioral attributes such as communication and attitude. Strengthening these dimensions is essential for enhancing organizational effectiveness and ensuring long-term sustainability in the sector.