User's Delay Perception and Tolerance in Human-Computer Interaction

Abstract

This paper focuses on user's delay perception and tolerance in a simulated computer supported cooperative work (a special case of HCI) environment, as well as the non-technological factors affecting user's delay tolerance. Five factors (gender, Type-A personality, task-type, difficulty level and time delay) were investigated by a mixed 2 (male vs. female, between-group) X 2 (object search vs. budget calculation, within-group) X 2 (hard vs. easy, within-group) factorial experimental design. Type-A personality and time delay were nested in gender and treatment respectively. Results showed that users could estimate 2–6 second delay accurately, but would underestimate shorter delays (<2 seconds) and overestimate longer delays (>6 seconds). MANOVA analysis indicated that task-type, difficulty level and time delay were major factors affecting user's delay tolerance. We also found some important interaction effects between independent variables. The findings suggest that users can adjust their delay tolerance based on the context information such as task-type and difficulty level.

Delays and User Performance in Human-Computer-Network Interaction Tasks

“…Perceived delay at the 120-s delay level was significantly longer than 120 s, t(89) = 1.846, p < .05). These latter findings are in contrast to Vierodt's law (Wang, 2002;Wang et al, 2002;Woodrow, 1951). This might be an important finding for delay perception laws, as will be addressed later in the General Discussion.…”

“…Detailed results of the preliminary studies have been presented elsewhere (Wang, 2002;Wang, Caldwell, & Zhang, 2002); the next section provides a brief summary of important outcomes of those studies and their influence on the design of the U.S. studies.…”

Back to normal? Impact of temporally increasing network disturbances on QoE

“…Usually, they tend to overestimate durations of less than 2 seconds, accurately estimate durations between 2 to 6 seconds, and underestimate durations when delays are above 6 seconds. This law was further confirmed by an experimental study [21]. Similarly, the exponential interdependency of QoE and QoS was presented with the term IQX hypothesis by Fiedler et al [9], which stated that, if the QoE is very high, a slight disturbance will decrease QoE strongly.…”

Bird’s-Eye View Provided in Real-time via Drone Improves Spatial Perception for Team Sports

“…The image from the drone was transmitted to the Moverio smart glasses via the smartphone using Bluetooth at 15.0 fps. Latency, which was less than 200 ms when the drone was 40.0 m above the field and less than 130 ms when it was on the ground, was sufficiently small that the participants did not perceive a time lag 19 . Also, the field of view of the camera was 85.0, and is sufficient to capture all the field which would be used for this experiment.…”