Understanding the structure of risk belief systems concerning drone delivery: A network analysis

Xun Zhu, Timothy J. Pasch and Aaron Bergstrom

Technology in Society, 2020, vol. 62, issue C

Abstract: While e-commerce industries envision drones as a promising solution to the challenges associated with last-mile logistics of product delivery, there is increasing public concern over the risks of these airborne innovations. A growing number of studies seek to gauge the public's risk beliefs about drone delivery and inform policy development before its widespread uptake. Complicating these efforts is the fact that beliefs are interconnected and embedded in a cognitive system. This article argues that public outcomes are not based on atomized and isolated beliefs about risks involved in drone delivery, but instead emerge from the patterns in the relationships among these expressed beliefs. However, little is known about the structural characteristics of risk belief systems related to drone delivery, and the implications for risk communication and management. In an effort to fill this void, we conducted a network analysis of risk beliefs about drone delivery based on nationally representative data (N = 1465). The results revealed structural connections among 11 risk beliefs and explored structural variations in the risk belief system between people with different attitudes toward drone delivery. The simulation results showed that risk-mitigating messages instigated greater changes to the public's risk perceptions when they targeted structurally central, as opposed to peripheral, risk beliefs. The reported evidence adds new insights into how risks about drone delivery are configured in the public consciousness, and provides guidance into how practitioners may mobilize structural leverage to optimize the effectiveness and efficiency of risk communication strategies.

Keywords: Risk perceptions; Belief system; Drones; Network analysis; Risk communication (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:62:y:2020:i:c:s0160791x1930613x

DOI: 10.1016/j.techsoc.2020.101262

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