Fragmented Moments, Balanced Choices: How Do People Make Use of Their Waiting Time?
Abstract
1 Introduction
2 Related Work
2.1 Time Usage Studies
2.2 Gap Time Between Scheduled Events
2.3 Waiting Time as an Underexplored yet Ubiquitous Format of Gap Time
3 Method
3.1 Participants
ID | Gender | Age | Employment | Work time | Work place | ESM reports |
---|---|---|---|---|---|---|
P01 | Male | 28 | Full-time | 9 a.m. to 5 p.m. | Hybrid | 34 |
P02 | Male | 36 | Full-time | 9 a.m. to 5 p.m. | Hybrid | 33 |
P03 | Female | 48 | Full-time | Rotating shifts | Hybrid | 38 |
P04 | Female | 33 | Full-time | 9 a.m. to 5 p.m. | On-site | 42 |
P05 | Female | 41 | Full-time | 9 a.m. to 5 p.m. | Remote | 42 |
P06 | Female | 42 | Part-time | As required | Hybrid | 29 |
P07 | Male | 32 | Full-time | Rotating shifts | On-site | 43 |
P08 | Female | 46 | Full-time | 9 a.m. to 5 p.m. | On-site | 42 |
P09 | Female | 32 | Part-time | Rotating shifts | Remote | 41 |
P10 | Female | 43 | Full-time | 9 a.m. to 5 p.m. | On-site | 32 |
P11 | Female | 50 | Freelance | As required | Remote | 45 |
P12 | Female | 34 | Full-time | 9 a.m. to 5 p.m. | On-site | 47 |
P13 | Female | 31 | Full-time | Rotating shifts | On-site | 45 |
P14 | Male | 32 | Full-time | 9 a.m. to 5 p.m. | On-site | 50 |
P15 | Male | 25 | Full-time | Rotating shifts | Hybrid | 43 |
P16 | Male | 34 | Freelance | Rotating shifts | On-site | 43 |
P17 | Female | 55 | Full-time | 9 a.m. to 5 p.m. | Hybrid | 75 |
P18 | Female | 60 | Full-time | 9 a.m. to 5 p.m. | Remote | 50 |
P19 | Female | 61 | Full-time | As required | Hybrid | 31 |
P20 | Female | 53 | Full-time | 9 a.m. to 5 p.m. | On-site | 25 |
P21 | Male | 52 | Full-time | 9 a.m. to 5 p.m. | Remote | 42 |
3.2 Mobile app for data collection
3.3 Procedure
3.4 Data Analysis
4 Results
4.1 RQ1: What Do People Do While Waiting?
4.2 RQ2: How Do Situational Factors Affect People’s Waiting Time Activities?
Productive vs. Leisure | Maintenance vs. Leisure | |||||||
---|---|---|---|---|---|---|---|---|
Variable | B | SE B | t | p | B | SE B | t | p |
(Intercept) | -0.74 | 0.29 | -2.56 | .01 | -0.83 | 0.28 | -3.02 | .001 |
Computer | 1.55 | 0.24 | 6.51 | <.001 | -0.09 | 0.24 | -0.37 | .35 |
Phone | 0.16 | 0.51 | 0.32 | .37 | -0.69 | 0.38 | -1.80 | .04 |
Workplace | 0.79 | 0.33 | 2.42 | .01 | 0.35 | 0.45 | 0.76 | .22 |
Home | -0.23 | 0.27 | -0.85 | .20 | 1.08 | 0.25 | 4.33 | <.001 |
Lunchtime | 0.71 | 0.26 | 2.71 | .003 | 0.86 | 0.28 | 3.04 | .001 |
Duration | 0.00 | 0.00 | 1.05 | .15 | 0.01 | 0.01 | 1.18 | .12 |
*Bold font indicates statistical significance. |
5 Discussion
5.1 Leisure Activities as the Most Performed Waiting Time Activities
5.2 Maintenance Activities as One Substantial Component of Waiting Time Activities
5.3 Implications for the Management of Waiting Time
5.4 Limitations and Directions for Future Studies
Attributes \ Method | ESM | Shadowing | Wearable cameras | Survey | Passive tracking |
---|---|---|---|---|---|
Recording situational factors | Yes | Yes | No | No | Yes |
Recognizing physical activities | Yes | Yes | Yes | Yes | Limited |
Identifying waiting from first-person accounts | Yes | No | No | Yes | No |
Being intrusive | No | Yes | Yes | No | No |
Raising privacy concerns | No | Yes | Yes | No | Yes |
Inducing self-report bias | Yes | No | No | Yes | No |
Requiring effort from participants | Yes | No | No | Yes | No |
Number of participants commonly involved | Small | Small | Small | Large | Medium |
Representative example of this kind | This study | [9] | [54] | [45] | [24] |
6 Conclusion
Acknowledgments
A Distribution of Waiting Time Duration
B Categories of Waiting Time Activities
Category | Sub-category | Example | Duration% |
---|---|---|---|
Leisure | Watching TV, movie, or video | "watching TV" | 13.4% |
Socializing | "catch up with friends at table" | 8.3% | |
Social media | "scrolling facebook" | 7.5% | |
Reading for leisure | "reading news" | 7.0% | |
Listening to music or podcast | "listening to music, listening to a podcast " | 5.1% | |
Games | "play Disney emoji" | 3.7% | |
Text messages | "checking messages" | 2.9% | |
Relaxing or resting | "relaxing, stretching" | 2.3% | |
Physical activity | "treadmill, cycling" | 2.2% | |
Phonecall | "talking to my friend on the phone" | 1.5% | |
Browsing internet | "on the internet" | 1.4% | |
Using my phone | "scrolling on phone" | 1.0% | |
Religious practices | "church services" | 0.5% | |
Time with pets | "played withy pets outside" | 0.5% | |
Art | "played piano" | 0.1% | |
Subtotal | \ | 57.4% | |
Productive | "checking emails" | 11.0% | |
Work | "work" | 10.8% | |
Study | "recitation" | 0.6% | |
Planning & Preparing | "made a list" | 0.2% | |
Subtotal | \ | 22.5% | |
Maintenance | Personal care | "shower" | 6.5% |
Housework | "washing dishes" | 5.6% | |
Food & drink preparing | "made a salad" | 2.3% | |
Other maintenance | "clean my glasses" | 1.4% | |
Shopping | "ordered some things online" | 1.3% | |
Subtotal | \ | 17.1% | |
No purpose | Doing nothing | "nothing, wait" | 1.7% |
Looking around | "looking out of the window" | 0.7% | |
Standing or sitting | "just standing" | 0.6% | |
Subtotal | \ | 3.0% | |
All activities | Grand total | \ | 100.0% |
C Waiting Time Activities at Different Locations
D Logistic Regression Results with Log-Transformed Duration
Productive vs. Leisure | Maintenance vs. Leisure | |||||||
---|---|---|---|---|---|---|---|---|
Variable | B | SE B | t | p | B | SE B | t | p |
(Intercept) | -1.08 | 0.40 | -2.68 | .004 | -0.97 | 0.39 | -2.47 | .01 |
Computer | 1.54 | 0.25 | 6.20 | <.001 | -0.08 | 0.24 | -0.34 | .37 |
Phone | 0.19 | 0.50 | 0.37 | .36 | -0.68 | 0.39 | -1.75 | .04 |
Workplace | 0.77 | 0.34 | 2.29 | .01 | 0.37 | 0.46 | 0.79 | .22 |
Home | -0.23 | 0.27 | -0.84 | .20 | 1.10 | 0.26 | 4.28 | <.001 |
Lunchtime | 0.72 | 0.26 | 2.72 | .003 | 0.85 | 0.28 | 3.02 | .001 |
Log-Transformed Duration | 0.13 | 0.11 | 1.16 | .12 | 0.06 | 0.10 | 0.56 | .29 |
*Bold font indicates statistical significance. |
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