Esm 2.0

State of the Art and Future Potential of Experience Sampling Methods in Organizational Research

Bibliographic Data

ID17825969
AuthorsDaniel J Beal (0000-0003-4750-2430, Virginia Tech, corresponding author)
Year2015
Volume2
Issue1
Pages383-407
Publication date2015-01-26
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueAnnual Review of Organizational Psychology and Organizational Behavior (JOURNAL)
Journal identifiersISSN: 2327-0608 • E-ISSN: 2327-0616
PublisherAnnual Reviews (PUBLISHER • US)
DOI10.1146/annurev-orgpsych-032414-111335
OpenAlexW2106887764
LanguageEN
Citations received91
References cited117

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

Big data · Data mining · Data science · Experience sampling method · Behavioral Health and Interventions · Computer Science · Digital Mental Health Interventions · Mental Health Research Topics · Psychology · Social Psychology · Artificial Intelligence

Tools

Open DOISci-HubOpen Access