Extending Technology Acceptance Model to Predict Innovation in Micro and Small Food Manufacturing Enterprises in Kenya

Abstract

Food processing is one of the manufacturing sectors that is propagated to feed the steady growing population and other current economic development challenges such as poverty, job supply, healthy lifestyles, globalization and competitive entrepreneurship in food value chain. How food processing innovations are affected by Micro and Small Entrepreneurs’ (MSEs’) perceived ease of use, perceived usefulness and attitude towards acceptance behaviour are the research questions this study addresses. The Technology Acceptance Model (TAM) is used as a base model to produce a causal model representing a network of relationships among the study constructs. Mixed research methods were used to collect data from 132 MSEs manufacturing food in Busia and Nairobi Counties on Likert Scale questionnaires and interview schedules. The Cronbach’s alpha found an excellent internal consistency of 0.97 reliability. Due to weak information management system of agro-food processors in Busia county, snowballing sampling techniques was used and fisher sampling techniques formula at standard normal deviate of 1.96 on Nairobi County Government given its numerous food manufacturing enterprises. Data analysis by Logit model showed that at wald(1) = 41.475, p= .000, sig < .05, 2 tailed, the three of Davis predictors (“ease of use,” “usefulness” and Behavioural intention to use) significantly influenced food innovations. Behavioural intention to adopt technology scored highest n=129(97.7%) followed by perceived technology to be useful n=109(82.6%) and ease of use n=102 (77.3%) last. The study recommends that county governments should facilitate technology permeation among MSEs through appropriate policies and programmes and establish agro-industrial “silicon valley,” and agro-export zones that would link MSE products to global agricultural value chains.