Adoption Conceptual Model for Intelligent Waste Management in Smart Cities: Theoretical Review - Ajwang, Stephen Oloo; Abila, James Onyango; Tejero-Dakay, Irish (International Journal of Computing Sciences Research, 2020)
Purpose –Adoption of technologies in waste management in developing countries has largely lagged leading to poor waste collection and disposal exposing the city dwellers to health hazards and points of extortion. The delay has been occasioned by several technology adoption inhibitors. This paper, therefore, proposes am integration of three adoption models:  diffusion of innovation (DoI), technology acceptance model (TAM) and technology readiness index (TRI) models towards enhancing understanding of the factors that may influence acceptance and use of smart waste management system in a smart city Method – This paper critically reviewed the available literature on DoI, TAM, and TRI models and highlighted the challenges of applying each model and thereafter, proposed an integrated model based on the strength exhibited by each model. Results –Despite the wide use of DoI, TAM, and TRI models, the models have weaknesses when applied independently for intelligent waste management. For instance: DoI focuses on innovation rather than information technology, does not support participatory adoption of technology, and lacks psychometrics characterization of users' behavioral intentions; TAM may not measure user’s readiness and deals with perception to use technology rather than the actual use; TRI presupposes that users must be well equipped with the required infrastructure, skills, beliefs, and attitude to use technology. The integrated model may solve these weaknesses by drawing from the strength of each model while focusing on innovation (DoI), perceptions (TAM) and readiness (TRI) Conclusion – The model may enhance the adoption of the waste management system by focusing on(i) the innovation covered byDoImodel and (ii) the intended users; characterized by both perceptions through the TAM model; and readiness provided by the TRI model.  Recommendations – The study recommends the actual application of the model to test the hypothesis adduced that integrating the models would enhance the adoption and use of intelligent systems for waste management in smart cities.  Practical Implications – T he proposed model could help city planners to formulate a good strategy mix for the intended use(rs) of an intelligent waste management system.