Edinburgh Napier University

  In 2017, 2 billion mobile and smart phones were manufactured but only 15% were collected back. Although realistically not 100% could be collected back, there is scope for improvement.
To further close the loop for a circular economy, mobile and smart phone collection rates need to increase. A Theory of Endowed Behaviour extends the Theory of Planned Behaviour to shed a new light on small electronics end-of-use behaviours among young adults, using mobile and smart phones within the UK Higher Education as a case study. An exploratory mixed method was developed to identify and then confirm relevant end-of-use decision factors for these devices.
Using concepts from Behavioural Economics, the Endowment Effect has been measured on owners’ current mobile devices. Students consistently overvalued their phone second-hand monetary value. This overvaluation was in turn correlated to daily screen time. The more time users spent daily using their device, the higher the overvaluation.
Screen time was not only a proxy to the Endowment Effect but as well to the quantity of devices stored away. Respondents with higher screen time had more devices in storage. Certain devices were stockpiled for a specific backup purpose, but others were hoarded for a lack of better alternatives. Screen time can be used as proxy to both the Endowment Effect and the quantity of devices stored away.
Mobile and smart phones Distinct Urban Mines (DUM) are expressed not only by the quantity of devices and their nature but also the reasons they have been stored away. Behavioural economics associated to DUM exploitation have been theoretically explored in two conference papers and one journal article. Devices stored away by stockpilers can be assimilated to a ‘safety stock' that is not exploitable and devices kept by hoarders to an ‘exploitable stock.’ From a DUM of 3.4 million devices in the UK Higher Education system, it was estimated that approximately 1 million are exploitable. Some caution should be made as the extrapolation is made to give a sense of the potential available but the sample is biased towards male and overseas students.
To access this DUM, it is suggested to integrate screen time as a behavioural factor used as a proxy for the Endowment effect and hoarding behaviour. While difficult at this stage to estimate a clear improvement in modelling screen time and the endowment effect, the aim is to provide additional insights into the barriers leading to stockpiling small e-waste. To counter the Endowment Effect, it is proposed to improve existing collection systems using use Choice Architecture and non-monetary incentives.