Abstract
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 cityMethod – 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 – The proposed model could help city planners to formulate a good strategy mix for the intended use(rs) of an intelligent waste management system.
Highlights
Smart citiesInternational Telecommunication Union (ITU) describes a smart sustainable city is an innovative city that uses ICTs and other means to improve quality of life, the efficiency of urban operation, services provision, and competitiveness while ensuring that it meets the needs of present and future generations concerning economic, social and environmental aspects (ITU, 2014)
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 technology acceptance model (TAM) model; and readiness provided by the technology readiness index (TRI) model
For instance:(i) whereas TRI antecedents may correlate to diffusion of innovation (DoI) constructs, their combination does not take into account the mediating factors such as psychometrics characterization of users' behavioral intentions, (ii)a study by Pires et al (2011) found out that combining TRI and TAM led to only 3% increase in the intention to use technology, a study by Godoe and Johansen (2012), found out that only optimism and innovativeness significantly affected perceived ease of use and perceived usefulness when TAM and TRIare combined, (iii) DOI variables of complexity and relative advantage are overlapping with TAM variables of perceived ease of use and perceived usefulness respectively (Carter &Bélanger, 2005) their combination may not provide a good prediction of adoption and use of technology
Summary
International Telecommunication Union (ITU) describes a smart sustainable city is an innovative city that uses ICTs and other means to improve quality of life, the efficiency of urban operation, services provision, and competitiveness while ensuring that it meets the needs of present and future generations concerning economic, social and environmental aspects (ITU, 2014). Waleed et al (2019) integrated DoI and TAM to evaluate students attitude towards MOOCs learning management system and recommended that system developers, designers and procurers should cautiously study the needs of students and confirm that the chosen system successfully meet their expectation since the MOOCs system features significantly affected user adoption; Lee (2009) combined TAM with theory of planned behavior to understand the perceived risks and benefits in adoption of internet banking and found out that perceived ease of use, perceived usefulness, attitude, subjective norm and perceived behavioral control are the important determinants of online banking adoption; Moon and Young-Gul (2001) introduced a newer variable “playfulness” in working with TAM to study acceptance of world wide web ( www) and found out that perception of playfulness influenced users ’ attitude towards using the www and should be a consideration in designing future www systems by providing more concentration, curiosity and enjoyment Despite this wide use, TAM may not measure a user’s readiness. The integration of the three models sought to solve the weaknesses of each model when applied independently or a combination of two models by focusing on innovation (DoI), perceptions (TAM), and readiness (TRI)
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