Development of a diffusion model for agro-technologies innovation for research and development organisations in Tanzania

Abstract

Research and development (R&D) organisations in Tanzania use old systematic design models that focus on the mere agro-technologies prototypes development, instead of innovation of agro-technology for diffusion. A serious gap exists in the incorporation of the agro-technologies diffusion factors in design models in R&D organisations in Tanzania. The twin valley of technology death describes the technology development failures based on business vision disregard. Technology prototypes or services are developed, though are not linked to business setup, and that they don‟t get ripe to earn money through commercial sales. This study identified that there is no customised model for agro-technology diffusion in research and development organisations in Tanzania. Structured questionnaires, interview with R&D organisation staffs and stakeholders and observation of activities in these R&D organisations were used to collect data from sources identified. Literatures on engineering design, technology development for diffusion and various models for innovation were studied. The factors that were linked with agro-technology were identified and their related variables and hence the model was developed, that proved to be useful in guiding technology developers in ensuring the good final diffusion of technologies to above 95% significant level. Regression analysis and system dynamic model development and analysis were used to organise identified factors into agro-technology innovation diffusion model. The model was calibrated and validated using data collected from various R&D organisations in Tanzania between the year 2011and 2013. Factors that were included in the model are: relevance of needs identification, need identification, interpretation of variable into design specification, agro-technology validation process, agro-technology information generation and proper agro-technology packaging and agro-technology development stages importance. These factors were found to affect agro-technology diffusion at a rate between 10 and 65%. It was noted that the development of technology for diffusion is more than the prototype development. By using the model with its useriii interface provides guidance to agro-technology developers that the control of innovation diffusion is above 95% confidence interval. However further work to improve the model especially on time adjustment and other socioeconomic factors like human resource requirement, fixed capital and R&D organisation rationalisation in Tanzania that has to be done