Browsing by Author "Nkamisa, Lwando"

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    Assessing the competitive performance of smallholder wool growers in the South African wool industry
    (2020-03) Nkamisa, Lwando; Van Rooyen, Johan; Gerwel, Heinrich; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Agricultural Economics.
    ENGLISH ABSTRACT: The South African wool value chain has potential to increase its production levels from the current 50 million kg to 75 million kg per annum without negatively affecting the wool prices, according to De Beer (2018). That would create 12 500 jobs and contribute an additional R1.5 billion Rand to the agribusiness GDP. However, to achieve such a mammoth task, it must increase the number of wool sheep from 23 million to 50 million. Even though commercial farmers are the backbone of the South African wool industry, they cannot tackle such a gigantic task alone. Thus, smallholder wool growers (SWGs) need to take their rightful place within the industry and assist the sector in fulfilling its potential. Conversely, the lingering question is, how can that be done? It is from this question that the broad objective of this study was derived, which was to analyse the competitiveness of SWGs in the former Transkei and Ciskei and assess the factors affecting their competitive performance. The specific research questions were: How is the small wool grower's competitiveness defined and measured? Are SWGs competitive? What strategies are needed to promote competitive performance for SWGs? In order to answer these questions, the study adopted the Delphi sampling procedure and the five-step competitiveness analytical framework (Esterhuizen 2006; Van Rooyen et al. 2011; Ndou, 2012; Jafta, 2014; Abei, 2017; Dlikilili; Sibulali, 2018 and Barr, 2019). The first step of the framework was to define competitiveness. Duly, the study adopted Van Rooyen's (2008) definition. Van Rooyen defined competitiveness as "the ability of a sector, industry, firm or farm to compete by trading their products within the global environment while earning at least the opportunity cost of returns on resources employed." Therefore, the competitiveness of SWGs is their ability to compete in the wool industry, while at least breaking even on the existing trade dynamics. The second step was to measure competitiveness. Although, scholars usually measure competitiveness at the macro-level instead of the meso- or micro-level (Bahta & Molope, 2014). This phenomenon is due to lack of reliable data sources. Nevertheless, this study made us of data from the Cape Wool SA. The aforementioned organisation has been keeping records of SWGs data since 1997 and is under the reporting supervision of International Wool Trade Organisation (IWTO). Consequently, the research measured the competitive performance of SWGs with the RCA (Revealed Trade Advantage) from the Cape Wool SA (1997-2018). However, to measure the SWGs competitiveness, the study modified the RCA formula. Moreover, for the broader SA wool value both RCA and RTA (Relative Trade Advantage) from FAO-STAT (1961-2017), ITC Trade Map (2001-2018). Furthermore, the RTA and RCA values of the SA wool value chain competitors such as Australia, New Zealand and Argentina were also measured. The third RTA and RCA measurements were for the different wool categories traded in the SA wool value chain. The results revealed that the South African wool value chain continued to compete competitively, even when compared to its major competitors. It is only behind Australia and New Zealand. For example, Australia's RTA in 2018 was 55.91 and 24.48 for New Zealand, while SA's was 21.11. Unfortunately, the results for the SWGs were not as straight forward, as the analysis showed that their competitive performance had improved significantly over the last 2 decades but at much slower rate than expected. Even though the subsector can be defined as marginally competitive from the start of the 21st century, fortunes started to improve in 2016, as the SWGs RCA values increase. For example, in 2001 the RCA value was 0.03 but in 2018 it had improved to 1.60. In order to assess the factors that helped improve the competitive performance of SWG's, the study analysed the survey results in the third step. The survey had 45 respondents, from the whole wool value chain. Starting with 23 SWGs, followed by seven extension officers, six wool buyers, five shed leaders and four wool brokers. The SWG's come from both the former Transkei and Ciskei region. The first analysis done was the cluster analysis, which allowed the study to divide the respondents into 3 Clusters. Cluster 1 was constituted by the SWG's, Cluster 2 by the brokers, buyers and extension officers and the third Cluster was made up of the general industry. The Cluster analysis results showed that there was consensus in the views of the respondent. For example, Cluster 1 indicated that 86% the questions asked to them enhanced competitive performance, while the second Cluster cited 59%, and the general industry's average was 65%. The last step of the framework was to develop a strategic plan for the industry. However, to make such a plan. The study had first to analyse each of the six determinants separately, and then to administer the PCA and Cronbach's alpha tests. The PCA provided the study with correlated variables from the data set, while the Cronbach's alpha test, measured the internal consistency. The Cronbach's alpha test showed that the data set had a high internal consistency as the alpha value was 0.725. The last part of the analysis was to take the 16 identified factors in step 5. That is the smallholder wool-growers strategic plan for competitive performance. Accordingly, the smallholder wool growers' competitive performance strategic plan was created with both enhancing and constraining factors from the Cronbach's analysis. The plan included innovative approaches to improve access to finance, improving the quality and flow of information and creative ways of dealing with the challenge of communal tenure and provision of primary inputs.