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ESM 2.0: State of the Art and Future Potential of Experience Sampling Methods in Organizational Research
Open accessAbstract
The use of experience sampling methods (ESM) and related techniques has exploded in organizational research. The goals of this review are to provide a focused perspective on the state of the art in using ESM and set the stage for what ESM will look like in the years to come. First, I provide a conceptually based discussion of exactly what is and what is not ESM. Next, I discuss the more advantageous elements of ESM that have surfaced from the range of disciplines that enjoy its use (e.g., reduced memory and methods biases), followed by the inevitable challenges that have sometimes limited its utility (e.g., issues with repeated assessment, missing data, and internal validity). Finally, I discuss three innovations of ESM (e.g., trait assessment, expansion to higher levels of analysis, and connection to big data) that seem likely to ensure its continued and expanded influence as a common tool for examining not only within-person psychological processes at work, but higher levels of analysis as well.
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“Utilizing ESM allows researchers to protect against common method bias usually associated with crosssectional survey designs and memory bias where followers have to recall specific behaviors (Beal, 2015).”
From Servant Leadership: A systematic review and call for future research (2019) · cites this paper as Beal, 2015
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“Researchers typically employee ESM to survey participants regularly (i.e.every few hours up to daily) across 1 to 2 weeks (Beal, 2015).”
From Servant Leadership: A systematic review and call for future research (2019) · cites this paper as Beal, 2015
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Metadata
- Authors
- Beal, D. J.
- Affiliations
- Virginia Tech (US)
- Corresponding author
- Beal, Daniel J.
- ORCID
- Beal, Daniel J.
- Venue
- Annual Review of Organizational Psychology and Organizational Behavior
- Publisher
- Annual Reviews
- Published
- 2015-04-10
- Volume
- 2
- Issue
- 1
- Pages
- 383-407
- ISSN
- 2327-0608 (ISSN-L)
- 2327-0616
- OpenAlex
- W2106887764
- Cited by
- 436
- References
- 129
- Citations by year
- 2026: 49 · 2025: 63 · 2024: 50 · 2023: 36 · 2022: 52 · 2021: 51 · 2020: 36 · 2019: 37 · 2018: 24 · 2017: 18 · 2016: 12 · 2015: 4
- FWCI
- 2.51
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Annual Review of Organizational Psychology and Organizational Behavior (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Job Satisfaction and Organizational Behavior
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Workplace Health and Well-being
- Keywords
- ecological momentary assessment, within-person processes, memory bias, methodological bias, repeated assessment, missing data, internal validity, trait assessment, big data, work psychology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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