Strategic management: An Eastern Cape construction SME case study

Small and Medium-size Enterprises (SMEs) fulfil an important role in the long-term growth and development of the economy of the country. The development and growth of construction SMEs are important for all countries, as a strong SME base has the capacity to produce a high-quality infrastructure for the country. However, research has revealed the high failure rate of small businesses within the first five years of their existence in South Africa. In addition, research also indicated that lack of long-term planning and lack of strategic thinking are major contributing factors to the failure of most SMEs. For instance, despite the considerable growth in the industry in the past decade due to government’s considerable infrastructural spending occasioned by the 2010 FIFA World Cup, the majority of construction SMEs failed to use the opportunities gained in this period to develop into established construction entities. This study investigates how strategic management can be applied to address the problems faced by construction SMEs, and to explore techniques and tools of strategic management that can make a significant contribution to their growth and development. The research findings, based on a literature review and a qualitative research approach, suggest that, although many construction SMEs perform poorly, some have the potential to grow and develop into more established entities by proactively managing their firms strategically. In addition, the findings indicate that SMEs that practise strategic management perform better, and that there are many advantages for SMEs that adopt strategic management principles at the organisational level

Group Medical Visits for the Management of Chronic Pain

Improvements of possible practical significance were seen for various clinical measures in studies of group treatment sessions for patients with back pain, arthritis, and rheumatic disease. However, studies on group treatment for patients with nonspecific pain are lacking, especially in the primary care setting. (Strength of Recommendation: B)

Accurate determination of breed origin of alleles in a simulated smallholder crossbred dairy cattle population

Background Accurate assignment of breed origin of alleles at a heterozygote locus may help to introduce a resilient or adaptive haplotype in crossbreeding. In this study, we developed and tested a method to assign breed of origin for individual alleles in crossbred dairy cattle. After generations of mating within and between local breeds as well as the importation of exotic bulls, five rounds of selected crossbred cows were simulated to mimic a dairy breeding programme in the low- and middle-income countries (LMICs). In each round of selection, the alleles of those crossbred animals were phased and assigned to their breed of origin (being either local or exotic).Results Across all core lengths and modes of phasing (with offset or no), the average percentage of alleles correctly assigned a breed origin was 95.76%, with only 1.39% incorrectly assigned and 2.85% missing or unassigned. On consensus, the average percentage of alleles correctly assigned a breed origin was 93.21%, with only 0.46% incorrectly assigned and 6.33% missing or unassigned. This high proportion of alleles correctly assigned a breed origin resulted in a high core-based mean accuracy of 0.99 and a very high consensus-based mean accuracy of 1.00. The algorithm’s assignment yield and accuracy were affected by the choice of threshold levels for the best match of assignments. The threshold level had the opposite effect on assignment yield and assignment accuracy. A less stringent threshold generated higher assignment yields and lower assignment accuracy.Conclusions We developed an algorithm that accurately assigns a breed origin to alleles of crossbred animals designed to represent breeding programmes in the LMICs. The developed algorithm is straightforward in its application and does not require prior knowledge of pedigree, which makes it more relevant and applicable in LMICs breeding programmes

Genomic evaluations using data recorded on smallholder dairy farms in low- to middle-income countries

Breeding has increased genetic gain for dairy cattle in advanced economies but has had limited success in improving dairy cattle in low- to middle-income countries (LMIC). Genetic evaluations are a central component of delivering genetic gain, because they separate the genetic and environmental effects of animals' phenotypes. Genetic evaluations have been successful in advanced economies because of large data sets and strong genetic connectedness, provided by the widespread use of artificial insemination (AI) and accurate recording of pedigree information. In smallholder dairy production systems of many LMICs, the limited use of AI and small herd sizes results in a data structure with insufficient genetic connectedness between herds to facilitate genetic evaluations based on pedigree. Genomic information keeps track of shared haplotypes rather than shared relatives captured by pedigree records. Therefore, genomic information could capture “hidden” genetic relationships, that are not captured by pedigree information, to strengthen genetic connectedness in LMIC smallholder dairy data sets. This study's objective was to use simulation to quantify the power of genomic information to enable genetic evaluation using LMIC smallholder dairy data sets. The results from this study show that (1) genetic evaluations using genomic information were more accurate than those using pedigree information in populations with a high effective population size and weak genetic connectedness; and (2) genetic evaluations modeling herd as a random effect had higher or equal accuracy than those modeling herd as a fixed effect. This demonstrates the potential of genomic information to be an enabling technology in LMIC smallholder dairy production systems by facilitating genetic evaluations with in situ records collected from herds of ≤4 cows. The establishment of routine genomic evaluations could allow the development of LMIC breeding programs comprising an informal set of nucleus animals distributed across many small herds within the target environment. These nucleus animals could be used for genetic evaluation, and the best animals could be disseminated to participating smallholder dairy farms. Together, this could increase the productivity, profitability, and sustainability of LMIC smallholder dairy production systems