Rattan Governance: Actors' Motivation and Interest in Meme Division, Cameroon's Rattan Production and Transformation

The study examined rattan governance, focusing on the motivation and interests of actors in Meme Division, Cameroon's rattan production, and transformation. Both descriptive and explanatory designs were used. A multistage sampling technique was used. Primary and secondary sources of data were used. A sample size of 332 respondents was used. Structured questionnaires and observation were used to collect primary data. Secondary data sources included published and unpublished materials. Descriptive statistics were used for data analysis, and simple linear regression was used to test the hypothesis. Regression results for actors' interest and motivation in rattan production and transformation are 0.904 for production and 0.908 for transformation, both of which exceed the typical p-value of 0.05. Consequently, the beta coefficient indicates that the factors influencing production and transformation are positively correlated with actors' motivation and interest. Results revealed three typologies of actors (state actors, community-based actors, and civil society actors) involved in rattan production and transformation. Findings on determinants of actors’ motivation and interest in rattan production reveal favourable climate (24.4%), income generation (27.1%), cultural significance (37%), and cultural symbolism (28%) were influential motivating factors. Results on actors’ motivation and interest in rattan transformation indicate that climate change resilience (56%), adaptability (28.4%), social cooperation (39%), and traditional handicraft (40%) are some of the contributing factors. The study concludes that the government, non-governmental organizations, and community actors should develop policies aimed at promoting the growth of this sector, as rattan production and transformation are profitable activities in the Meme Division. Key Words: Meme Division, Motivation and Interest, Production, Rattan Governance, Transformation