scholarly journals Towards a Model of Automation Adoption

Author(s):  
Ian McCandliss ◽  
Kevin Zish ◽  
J. Malcolm McCurry ◽  
J. Gregory Trafton

This study examines the impact of prior experience on the adoption of automation in a supervisory control task. Automation is typically implemented as a means of reducing a person’s effort or involvement in a task. When automation is first introduced in a new product, the experience on the yet-to-be automated task is variable. Some users have experience with the task prior to the automation while others have little to no prior experience. Automation adoption between levels of experience was investigated in a mixed design study. One group was trained to use a manual version of a task before learning of an automated version. A second group was only trained to use the automated version of the task. The results of this study indicate that both training and experience are needed before users can make robust predictions about future automation adoption.

2019 ◽  
Vol 13 (4) ◽  
pp. 295-309 ◽  
Author(s):  
Mary Cummings ◽  
Lixiao Huang ◽  
Haibei Zhu ◽  
Daniel Finkelstein ◽  
Ran Wei

A common assumption across many industries is that inserting advanced autonomy can often replace humans for low-level tasks, with cost reduction benefits. However, humans are often only partially replaced and moved into a supervisory capacity with reduced training. It is not clear how this shift from human to automation control and subsequent training reduction influences human performance, errors, and a tendency toward automation bias. To this end, a study was conducted to determine whether adding autonomy and skipping skill-based training could influence performance in a supervisory control task. In the human-in-the-loop experiment, operators performed unmanned aerial vehicle (UAV) search tasks with varying degrees of autonomy and training. At the lowest level of autonomy, operators searched images and, at the highest level, an automated target recognition algorithm presented its best estimate of a possible target, occasionally incorrectly. Results were mixed, with search time not affected by skill-based training. However, novices with skill-based training and automated target search misclassified more targets, suggesting a propensity toward automation bias. More experienced operators had significantly fewer misclassifications when the autonomy erred. A descriptive machine learning model in the form of a hidden Markov model also provided new insights for improved training protocols and interventional technologies.


2012 ◽  
Vol 6 (1) ◽  
pp. 57-87 ◽  
Author(s):  
Dietrich Manzey ◽  
Juliane Reichenbach ◽  
Linda Onnasch

Two experiments are reported that investigate to what extent performance consequences of automated aids are dependent on the distribution of functions between human and automation and on the experience an operator has with an aid. In the first experiment, performance consequences of three automated aids for the support of a supervisory control task were compared. Aids differed in degree of automation (DOA). Compared with a manual control condition, primary and secondary task performance improved and subjective workload decreased with automation support, with effects dependent on DOA. Performance costs include return-to-manual performance issues that emerged for the most highly automated aid and effects of complacency and automation bias, respectively, which emerged independent of DOA. The second experiment specifically addresses how automation bias develops over time and how this development is affected by prior experience with the system. Results show that automation failures entail stronger effects than positive experience (reliably working aid). Furthermore, results suggest that commission errors in interaction with automated aids can depend on three sorts of automation bias effects: (a) withdrawal of attention in terms of incomplete cross-checking of information, (b) active discounting of contradictory system information, and (c) inattentive processing of contradictory information analog to a “looking-but-not-seeing” effect.


Author(s):  
Jeeyun Oh ◽  
Mun-Young Chung ◽  
Sangyong Han

Despite of the popularity of interactive movie trailers, rigorous research on one of the most apparent features of these interfaces – the level of user control – has been scarce. This study explored the effects of user control on users’ immersion and enjoyment of the movie trailers, moderated by the content type. We conducted a 2 (high user control versus low user control) × 2 (drama film trailer versus documentary film trailer) mixed-design factorial experiment. The results showed that the level of user control over movie trailer interfaces decreased users’ immersion when the trailer had an element of traditional story structure, such as a drama film trailer. Participants in the high user control condition answered that they were less fascinated with, absorbed in, focused on, mentally involved with, and emotionally affected by the movie trailer than participants in the low user control condition only with the drama movie trailer. The negative effects of user control on the level of immersion for the drama trailer translated into users’ enjoyment. The impact of user control over interfaces on immersion and enjoyment varies depending on the nature of the media content, which suggests a possible trade-off between the level of user control and entertainment outcomes.


2011 ◽  
Author(s):  
Daniel Gartenberg ◽  
Malcolm McCurry ◽  
Greg Trafton

2021 ◽  
pp. 108602662199006
Author(s):  
Peter Tashman ◽  
Svetlana Flankova ◽  
Marc van Essen ◽  
Valentina Marano

We meta-analyze research on why firms join voluntary environmental programs (VEPs) to assess the impact of program stringency, or the extent to which they have rigorous, enforceable standards on these decisions. Stringency creates trade-offs for firms by affecting programs’ effectiveness, legitimacy, and adoption costs. Most research considers singular programs and lacks cross program variation needed to analyze program stringency’s impact. Our meta-analysis addresses this by sampling 127 studies and 23 VEPs. We begin by identifying common institutional and resource-based drivers of participation in the literature, and then analyze how program stringency moderates their impacts. Our results suggest that strictly governed VEPs encourage participation among highly visible and profitable firms, and discourage it when informal institutional pressures are higher, and firms have prior experience with other VEPs or quality management standards. We demonstrate that VEP stringency has nuanced effects on firm participation based on the institutional and resource-based factors facing them.


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