Match!

Dual cognitive pathways to voice quality: Frequent voicers improvise, infrequent voicers elaborate

Published on Feb 27, 2019in PLOS ONE2.78
· DOI :10.1371/journal.pone.0212608
Inge Wolsink1
Estimated H-index: 1
,
Deanne N. Den Hartog45
Estimated H-index: 45
+ 1 AuthorsIlja G. Sligte13
Estimated H-index: 13
View in Source
Abstract
We investigate the involvement of Working Memory Capacity (WMC, the cognitive resource necessary for controlled elaborate thinking) in voice behavior (speaking up with suggestions, problems, and opinions to change the organization). While scholars assume voice requires elaborate thinking, some empirical evidence suggests voice might be more automatic. To explain this discrepancy, we distinguish between voice quantity (frequency of voice) and voice quality (novelty and value of voiced information) and propose that WMC is important for voice quality, but less for voice quantity. Furthermore, we propose that frequent voicers rely less on WMC to reach high voice quality than people who voice rarely. To test our ideas, we conducted three studies: a between-participant lab-study, a within-participant experiment, and a multi-source field-study. All studies supported our expectation that voice quantity is unrelated to WMC, and that voice quality is positively related to WMC, but only for those who rarely voice. This indicates that the decision to voice (quantity) might be more automatic and intuitive than often assumed, whereas its value to the organization (quality), relies more on the degree of cognitive elaboration of the voicer. It also suggests that frequent and infrequent voicers use distinct cognitive pathways to voice high-quality information: frequent voicers improvise, while infrequent voicers elaborate.
Figures & Tables
  • References (84)
  • Citations (1)
References84
Newest
#1Valerio Capraro (Middlesex University)H-Index: 18
24 CitationsSource
#1Valerio Capraro (Middlesex University)H-Index: 18
#2Brice Corgnet (EMLYON Business School)H-Index: 12
Last.Roberto Hernán-González (University of Nottingham)H-Index: 5
view all 4 authors...
18 CitationsSource
#1Diana I. Tamir (Princeton University)H-Index: 14
#2Mark Thornton (Harvard University)H-Index: 11
Last.Jason P. Mitchell (Harvard University)H-Index: 42
view all 4 authors...
42 CitationsSource
#1David G. Rand (Yale University)H-Index: 45
#2Victoria L. Brescoll (Yale University)H-Index: 22
Last.Hélène Barcelo (Mathematical Sciences Research Institute)H-Index: 5
view all 5 authors...
109 CitationsSource
#1Mathias Benedek (University of Graz)H-Index: 34
#2Emanuel Jauk (University of Graz)H-Index: 18
Last.Aljoscha C. Neubauer (University of Graz)H-Index: 49
view all 5 authors...
171 CitationsSource
66 CitationsSource
#1Elizabeth Wolfe Morrison (NYU: New York University)H-Index: 27
232 CitationsSource
#1Timothy D. Maynes (SUNY: State University of New York System)H-Index: 4
#2Philip M. Podsakoff (College of Business Administration)H-Index: 55
114 CitationsSource
#1Adam M. Grant (UPenn: University of Pennsylvania)H-Index: 47
108 CitationsSource
#1James R. Detert (SPbU: Saint Petersburg State University)H-Index: 19
#2Ethan R. Burris (University of Texas at Austin)H-Index: 14
Last.Sean R. Martin (SPbU: Saint Petersburg State University)H-Index: 6
view all 4 authors...
69 CitationsSource
Cited By1
Newest
Source