Performance impacts of mobile carbon footprint calculators in South Africa

Modernization and advancement in technology have contributed towards the increased use of mobile phones in South Africa. The increased demand for services and energy has resulted in the increase in generation of electricity to meet the country's need. Consequently, South Africa now possesses the highest greenhouse gas (GHG) emission per capita relative to other developing countries. Conservation organizations in South Africa argue that the first step towards reducing carbon footprint is through its measurement. In spite of the high penetration of mobile phones and the alarming GHG emission, there is hardly any research to investigate the fit and performance impacts of mobile carbon footprint calculators in South Africa. In fulfilment of this gap, the rationale of this study was to (1) investigate factors that are suitable to determine the fit of mobile technology for carbon footprint tasks, (2) adopt an existing model from the vast base of theories and models on technology usage and impact, (3) test the research model based on a South African sample within a mobile technology and carbon footprint context in order to determine the performance impacts on individual carbon footprint tasks. Sample data were collected, through a survey instrument, and was analysed quantitatively. Partial Least Square Structural Equation Modeling (PLS-SEM) analysis was used to evaluate the study's outer and the inner model. The study revealed that only task-technology fit was the cause of performance impacts on individual carbon footprint tasks. In addition, there was no significant difference in the estimation and offsetting of carbon footprint between the users and non-users of mobile technology. In conclusion, this study established that performance impacts on individual carbon footprint tasks are only determined by the fit of the mobile technology. The insignificant difference between users and non users of carbon calculators, in performance impacts on carbon footprint tasks, was an unexpected result but yet relevant to practitioners. Further implications to practice and theory are outlined in conclusion to this study.

Grantor dc:publisher.institution

Department of Information Systems

Year dc:date.issued

2017

Author dc:creator

• Munetsi, Martin

Advisor dc:contributor.advisor

• Kyobe, Michael

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/25406

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/25406