1 16th November 2013 Ayako Ishiwata PhD Candidate Department of International Studies The University of Tokyo presentation at the Development Studies Association Annual Conference 2013 Effects of Technology and Business Networks on Firm Growth in a Tailor Cluster, Ethiopia
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1 16th November 2013 Ayako Ishiwata PhD Candidate Department of International Studies The University of Tokyo presentation at the Development Studies Association.
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16th November 2013Ayako Ishiwata
PhD CandidateDepartment of International Studies
The University of Tokyo
presentation at the Development Studies AssociationAnnual Conference 2013
Effects of Technology and Business Networks on Firm Growth
in a Tailor Cluster, Ethiopia
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Industrial Cluster: geographical concentration of related industries and institutions
1. Background
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 fragileYet, the clusters provide rare nonfarm income generation opportunities
Identifying ways to increase sales/income is vital for poverty alleviation in Sub-Saharan Africa
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2. Research Area Assela, Oromia, Ethiopia
166 Km from Addis Ababa
17.2 km2
76,000 people
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Location of tailors
Food Market
Addis AbabaBus Station
Approx. 260 tailors within 0.05Km2
16% of tailors operating outside
3. Research Questions
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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?"
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
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(1) Annual tailoring sales excluding material costs (Dependent Variable)
5. Description of the data
Mean 21,993 Birr ($1165)Std. Dev.
55,900 Birr ($2963)
Min 800 Birr ($42)Median 13,830 Birr ($733)Max 648,000 Birr($34352)(converted with mean exchange rate on 30th August 2013, 18.86345 Birr/$)
Ln No of co-owners 2.59*** 2.55***2nd Stage (Dependent variable: Sewing Quality)
Ln Indegree+1 -0.05
Ln In-closeness + 0.01 -0.01
Ln Age -0.40** -0.43**
Female -0.09 -0.06
Training -0.16 -0.171st Stage*** Ln Indegree or Ln In- closeness in 2012
0.76*** 0.62***
6. Estimation Results 3 (3SLS): Sewing Quality
7 . Results
I. 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
II. Centralities (directly and indirectly) in the business networks increase efficiency and innovation aspects of technology, but no effect on quality.
III. Longer operation years when it is controlled with age is insignificant in technology increase.
⇒ Infers small learning effects
IV. Rare available training opportunities are insignificant in technology improvement.
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8. Conclusion
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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
Policy Implications
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I. Contents of trainings need to be reviewed. (technical - managerial)
II. Strengthening business networks seems immediate & cost effective assistance to sustain livelihood of firms in a survival cluster.
III. Tailoring business is likely to shrink in the globalization process unless tailors are linked to more quality conscious consumers outside the cluster (external knowledge).
IV. As a growth scenario, successful firms may diversify business after accumulating capital.