Assessing the competitive performance of smallholder wool growers in the South African wool industry

Thesis (MAgricAdmin)--Stellenbosch University, 2020.

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.

AFRIKAANSE OPSOMMING: Die Suid-Afrikaanse wol waardeketting het potensiaal om sy produksie vlakke van die huidige 50 000 000 kg tot 75 000 000 kg per jaar te verhoog sonder om die wolpryse negatief te beïnvloed, volgens de Beer (2018). Dit sal 12 500 werksgeleenthede skep en 'n bykomende R 1.5 miljard rand tot die agri-besigheid bydra. Om so 'n reuse taak te bereik, moet dit egter die aantal wolskape van 23 000 000 tot 50 000 000 verhoog. Alhoewel kommersiële boere die ruggraat van die Suid-Afrikaanse wolbedryf is, kan hulle nie so 'n reuse taak alleen aanpak nie. Die kleinboere moet dus hul regmatige plek binne die bedryf neem en die sektor bystaan om sy potensiaal te verwesenlik. Aan die ander kant, die voortslepende vraag is, hoe kan dit gedoen word? Dit is uit hierdie vraag dat die breë doelwit van hierdie studie afgelei is, wat die mededingendheid van kleinboere in die voormalige Transkei en Ciskei ontleed en die faktore wat hul mededingende prestasie beïnvloed, assesseer. Die spesifieke navorsing vrae was: Hoe word die kleinboere se mededingendheid gedefinieer en gemeet? Is kleinboere mededingend? Watter strategieë is nodig om mededingende prestasie vir kleinboere te bevorder? Ten einde hierdie vrae te beantwoord, het die studie die Delphi-steekproef prosedure en die vyf-stap-kompeterende analitiese raamwerk (Esterhuizen 2006; Van Rooyen et al. 2011; Ndou, 2012; Jafta, 2014; Abei, 2017; Dlikilili 2018; Sibulali, 2018 en Barr, 2019). Die eerste stap van die raamwerk was om mededingendheid te definieer. Die studie het behoorlik van Rooyen (2008) definisie aanvaar. Van Rooyen het mededingendheid gedefinieer as "die vermoë van 'n sektor, bedryf, firma of plaas om te kompeteer deur hul produkte binne die wêreld omgewing te verhandel, terwyl ten minste die geleentheid koste van die opbrengs op hulpbronne in diens verdien." Dus, die mededingendheid van kleinboere is hul vermoë om te kompeteer in die wolbedryf, terwyl hulle ten minste gelyk breek selfs op die bestaande handel dinamika. Die tweede stap was om mededingendheid te meet. Geleerdes meet gewoonlik mededingendheid op die makro-vlak in plaas van die meso- of mikrovlak (Bahta & Molope, 2014). Hierdie verskynsel is te wyte aan 'n gebrek aan betroubare data bronne. Nietemin het hierdie studie ons van data van die Cape Wool SA gemaak. Die voorgenoemde organisasie hou al sedert 1997 rekords van kleinboere data en is onder die verslag toesig van Internasionale Wol Handel Organisasie (IWHO). Gevolglik het die navorsing die mededingende prestasie van kleinboere met die OHV (Onthulde Handel Voordeel) van die Cape Wool SA (1997-2018) gemeet. Om die kleinboere mededingendheid te meet, het die studie die "formule" verander. Verder, vir die breër SA wol waarde is beide die OHV sowel as RHV (Relatiewe Handelsvoordeel) van die FAO-staat (1961-2017), ITC-Handelskaart (2001-2018) gebruik. Die RHV en OHV waardes van die SA wol waardeketting mededingers soos Australië, Nieu-Seeland en Argentinië is ook gemeet. Die derde OHV en RHV waardes was vir die verskillende wol kategorieë wat in die SA wol waardeketting verhandel is. Die resultate het getoon dat die Suid-Afrikaanse wol waardeketting steeds kompeterend meeding, selfs in vergelyking met sy groot mededingers. Dit is net agter Australië en Nieu-Seeland. Byvoorbeeld, Australië se RHV in 2018 was 55,91 en 24,48 vir Nieu-Seeland, terwyl SA se 21,11 was. Ongelukkig was die resultate vir die kleinboere nie so duidelik nie, aangesien die analise getoon het dat hul mededingende prestasie beduidend oor die laaste 2 dekades verbeter het, maar teen baie stadiger tempo as wat verwag is. Alhoewel die Subsektor as marginaal mededingend van die begin van die 21ste eeu gedefinieer kan word , het hulle in 2016 begin verbeter, aangesien die kleinboere se OHV toeneem. Byvoorbeeld, in 2001 was die OHV-waarde 0,03, maar in 2018 dit het verbeter tot 1,60. Ten einde die faktore wat gehelp het om die mededingende prestasie van kleinboere se te evalueer, die studie ontleed die opname resultate in die derde stap. Die opname het 45 respondente vanuit die hele wol waardeketting ingesluit. Eerstens met 23 kleinboere, gevolg deur sewe uitbreidings beamptes, ses wolkopers, vyf skuur leiers en vier wolmakelaars. Die kleinboere kom van beide die voormalige Transkei en Ciskei-streek. Die eerste analise wat gedoen is, was die “Cluster Analysis”, wat die studie toegelaat het om die respondente in 3 klusters te verdeel. Cluster 1 is saamgestel deur die kleinboere, Cluster 2 deur die makelaars, kopers en voorligtingsbeamptes en die derde kluster is saamgestel uit die algemene bedryf. Die “Cluster Analysis” resultate het getoon dat daar konsensus in die sienings van die respondent was. Cluster 1 het byvoorbeeld aangedui dat 86% die vrae wat vir hulle 'n verbeterde mededingende prestasie gevra het, terwyl die tweede kluster 59% aangehaal het, en die algemene bedryf se gemiddelde was 65%. Die laaste stap van die raamwerk was om 'n strategiese plan vir die bedryf te ontwikkel. Die studie moes egter eers elkeen van die ses faktore afsonderlik ontleed, en dan die PCA en Cronbach se alfa toetse administreer. Die PCA het die studie gekorreleer met veranderlikes uit die data stel, terwyl die Cronbach se Alpha Toets, die interne konsekwentheid gemeet het. Die Cronbach se alfa-toets het getoon dat die datastel 'n hoë interne konsekwentheid gehad het, aangesien die Alpha-waarde 0,725 was. Die laaste deel van die analise was om die 16 geïdentifiseerde faktore in stap 5 te neem. Dit is die kleinboere wol-produsente strategiese plan vir mededingende prestasie. Gevolglik is die kleinboere wol produsente se mededingende prestasie strategiese plan geskep met beide die verbetering en baie faktore van die Cronbach se analise. Die plan het innoverende benaderings ingesluit om toegang tot finansiering te verbeter, die verbetering van die gehalte en vloei van inligting en kreatiewe maniere om die uitdaging van gemeenskaplike ampstermyn en voorsiening van primêre insette te hanteer.

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