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Effects of Technology and Business Networks on Firm Growth in a Tailor Cluster, Ethiopia

presentation at the Development Studies Association Annual Conference 2013. Effects of Technology and Business Networks on Firm Growth in a Tailor Cluster, Ethiopia. 16th November 2013 Ayako Ishiwata PhD Candidate Department of International Studies The University of Tokyo. １． Background.

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Effects of Technology and Business Networks on Firm Growth in a Tailor Cluster, Ethiopia

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  1. presentation at the Development Studies Association • Annual Conference 2013 Effects of Technology and Business Networks on Firm Growthin a Tailor Cluster, Ethiopia 16th November 2013 Ayako Ishiwata PhD Candidate Department of International Studies The University of Tokyo

  2. １．Background • Industrial Cluster: geographical concentration of related industries and institutions • Most of clusters in Sub-Saharan Africa are "survival clusters". • (Altenburg and Meyer-Stamer 1999, Yoshino 2011) • - micro and small enterprises • compete in low quality products at low cost • - Earnings are small and fragile • Yet, the clusters provide rare nonfarm income generation opportunities • Identifying ways to increase sales/income is vital for poverty alleviation in Sub-Saharan Africa

  3. 2. Research AreaAssela, Oromia, Ethiopia • 166 Km from Addis Ababa • 17.2 km2 • 76,000 people

  4. Locationof tailors Addis Ababa Food Market Bus Station • Approx. 260 tailors • within 0.05Km2 • 16% of tailors operating outside

  5. 3. Research Questions • What factors contribute to improvement in business performance (sales) in • a tailor cluster in rural Ethiopia? • Focusing on roles of • - technology (sewing skills and design • capability) and • - business networks • " How business networks affect increase in sales through technology improvement?"

  6. ４．Methodology • (1) Sample • 136 garment processing tailors • - firstly interviewed in 2011 and • - operated full time in 2012 and 2013 • (2) Data • - Interview in 2011, 2012, and 2013 • - sewing test in 2012 and 2013 • (3) Estimation Method • Three Stage Leased Square Regression (3SLS) and • Seemingly Unrelated Regression (SUR) • 1st stage: Instrumental variable for business network • 2nd stage: business network →　technology • 3rd stage: technology →　Sales

  7. 5. Description of the data • (2) Number of Workers • (1) Annual tailoring sales • excluding material costs • (Dependent Variable) • (converted with mean exchange rate on 30th August 2013, • 18.86345 Birr/$)

  8. (３)Technology Variables • 1) Speed • 2) Accuracy • 3) Other errors (thread tangle, • tension, etc) 56 firms (41%) • 4) Design capacity • (28 firms 21%) • Sewing Skill Index • tangle

  9. Performance in Sewing Skill Test • Total missed area (quality) • Sewing Time (efficiency) Sewing Skill Index →　Normalized average of log of above indicators x -1 (μ=0、σ=1)

  10. (4) Business Network • in-degree centrality: • Number of tailors which give some benefits (information, credit, sales order, procurement, etc.) to the Tailor A • in-closeness centrality: • Inverse of number of steps (d) for other tailors to reach the Tailor A • Tailor A • Tailor B • data (out-degree) • flow of collaboration • (in-degree)

  11. Indegree • Incloseness

  12. 6. Estimation Results (3SLS) 1: Sewing Skill Index

  13. 6. Estimation Results (3SLS) 2: Sewing Speed

  14. 6. Estimation Results 3 (3SLS): Sewing Quality

  15. ７. Results • Higher technology significantly increases sales, but its explanatory power is related more to efficiency (sewing speed) and innovation(design) rather than quality (sewing accuracy or other errors). • ⇒　Infers immaturity of consumers' preference • Centralities (directly and indirectly) in the business networks increase efficiency and innovationaspects of technology, but no effect on quality. • Longer operation years when it is controlled with age is insignificant in technology increase. • ⇒　Infers small learning effects • Rare available trainingopportunities are insignificant in technology improvement.

  16. ８．Conclusion • Illustrates characteristics of the survival clusters whose product quality does not respond to firm growth. • (Both consumers and tailors are not likely to be • conscious of the quality.) • →　do not match the global standards • vulnerable when the markets are developed • - competition with the global products • - mismatch with consumer's preference • once their purchasing power increases

  17. Policy Implications • Contents of trainings need to be reviewed. (technical - managerial) • Strengthening business networks seems immediate ＆ cost effective assistance to sustain livelihood of firms in a survival cluster. • Tailoring business is likely to shrink in the globalization process unless tailors are linked to more quality conscious consumers outside the cluster (external knowledge). • As a growth scenario, successful firms may diversify business after accumulating capital.

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