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Session Overview
14-05: Paula Dootson
Saturday, 20/Jul/2019:
4:45pm - 5:10pm

Seminar Room 2-5

Chair: Paula Dootson

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Stealing from Robots in Service Roles

Authors: Paula Dootson (Queensland University of Technology, Australia), Kate Letheren (Queensland University of Technology, Australia)

Consumers increasingly use technology to make their everyday lives more efficient, including how they engage with and experience services. Yet, with the introduction of these technologies into the marketplace, we also observe new ways consumers can cheat, lie, steal, or misuse the technologies for their own benefit. These are all examples of deviant consumer behaviour (DCB), behaviour that violates laws, policies, or accepted norms of conduct (Daunt & Harris, 2012; Dootson et al., 2017). DCB can be directed towards an organisation’s employees (e.g. verbal abuse), merchandise (e.g. theft), financial assets (e.g. all types of fraud), physical or electronic premises (e.g. vandalism; computer virus), or other consumers (e.g. jumping queues; hostility). For instance, theft at the self-checkout is a billion-dollar problem around the globe (Mortimer & Dootson, 2017; Taylor, 2016). With businesses increasing rates of self-service technology adoption, new modes of deterrence need to be explored.

While the reasons to introduce technologies into the servicescape are, for the most part, economically compelling, there is little consideration in literature and practice for the unintended consequences of DCB. These could include damage to the technology, misuse, cost of reprogramming, or cost of shrinkage linked to use of the technology. DCB impacts whether the organisation can realise the full potential of the technology they invest in.

Past research demonstrates humans are the greatest defence against DCB for two reasons: they increase the perceived likelihood of being caught and punished (Greer & Daunt, 2015), and they can engender empathy (Jenni & Loewenstein, 1997) from a possible deviant consumer. Humans are thus able to trigger both cognitive and affective responses in consumers to deter DCB. So, if humans are the greatest defence against deviance then what happens when we replace them with technology? Can the same cognitive and affective inhibitors – risk of detection/punishment and empathy – still be triggered when no human is present?

This research draws on criminology, psychology, marketing, and human-computer interaction. Three studies were conducted across Australia and the United States, in the financial services context. The findings demonstrated consumer propensity to steal from technology varies based on the perceived humanness of the technology. Participants were more likely to steal from an ATM than a robot, but were more likely to steal from a robot than a human. The relationship between perceived humanness and DCB is mediated by participant’s empathy towards the technology, such that higher empathy strengthens the negative relationship between perceived humanness and DCB. Preliminary findings, however, do not find perceptions of risk (probability of being caught and punished) to mediate the perceived humanness and DCB relationship.

Theoretical and practical implications are presented for the development of technology to reduce instances of DCB, while still offering customers efficient service delivery.

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