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<p>This study investigates the operational efficiency of actors within Kenya’s cage tilapia value chain governance using Data Envelopment Analysis (DEA) and Transaction Cost Analysis (TCA) framework. The analysis of 560 participants across six value chain segments reveals a hierarchical governance structure dominated by traders (45.18%) and consumers (30.18%), with primary producers (11.79%) and processors (5%) holding smaller shares. Efficiency scores highlight significant variations: consumers demonstrate the highest efficiency (mean score of 0.824), followed by support enterprises (0.782) and input suppliers (0.754). Processors and producers exhibit moderate efficiency levels (0.583 and 0.589 respectively), while traders show the lowest efficiency (0.463) despite their market dominance. Transaction costs vary widely across actors, with producers (Ksh. 272,455) and input suppliers (Ksh. 206,045) facing the highest costs. The regression analysis reveals that transaction costs positively correlate with efficiency (<i>p</i> &lt; 0.01), while government regulatory frameworks and demographic factors significantly influence performance. To enhance value chain efficiency, targeted interventions in processing and trading are recommended, including investments in technology, infrastructure and policy measures to reduce transaction costs through improved supply chain management.</p>

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Value chain governance and operational efficiency of cage tilapia value chain in the riparian counties of Kenya’s Lake Victoria

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月16日

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  • Martin Abwao,
  • Hillary Bett,
  • Edith Gathungu

摘要

This study investigates the operational efficiency of actors within Kenya’s cage tilapia value chain governance using Data Envelopment Analysis (DEA) and Transaction Cost Analysis (TCA) framework. The analysis of 560 participants across six value chain segments reveals a hierarchical governance structure dominated by traders (45.18%) and consumers (30.18%), with primary producers (11.79%) and processors (5%) holding smaller shares. Efficiency scores highlight significant variations: consumers demonstrate the highest efficiency (mean score of 0.824), followed by support enterprises (0.782) and input suppliers (0.754). Processors and producers exhibit moderate efficiency levels (0.583 and 0.589 respectively), while traders show the lowest efficiency (0.463) despite their market dominance. Transaction costs vary widely across actors, with producers (Ksh. 272,455) and input suppliers (Ksh. 206,045) facing the highest costs. The regression analysis reveals that transaction costs positively correlate with efficiency (p < 0.01), while government regulatory frameworks and demographic factors significantly influence performance. To enhance value chain efficiency, targeted interventions in processing and trading are recommended, including investments in technology, infrastructure and policy measures to reduce transaction costs through improved supply chain management.