A Multisensor Person-Centered Approach to Understand the Role of Daily Activities in Job ...
summary
Uses sensor data from 603 information workers (Tesserae) and multimodal streams—wearables smartphones bluetooth social media—to cluster day-level activity and combine that with personality clusters into four “organizational personas.” Applies classical clustering and regression tests and finds activity context independently explains job outcomes, with activity having equal or larger effect than personality on organizational citizenship behavior and significant effects on task proficiency and deviance. The strongest-performing persona shows fewer location visits batched phone-use shorter desk sessions longer sleep, suggesting actionable, malleable activity features relate to better performance.
AI-written summary · about
related talks
06mPerson-Centered Predictions of Psychological Constructs with Social Media Contextualized by ...
19mData-driven Personas: Constructing Archetypal Users with Clickstreams and User Telemetry
42mData-Driven Personas
32mIdentifying playstyles in football through spatial networks
05mInterview with Alex Willcock
08mThe Consistency of Gamification User Types: A Study on the Change of Preferences over Time
01h 04mTake Control of the Data of You
29mUser Motivation: Refining Customer Segments with Location