Feedback, even positive feedback, can reduce performance.
Listening is transformational. See a Harvard Business Review paper.
Feedforward, with listening, could substitute feedback.
Kluger, A. N. (2021, August). Exposing the underlying assumptions of listeners, listening researchers, and listening trainers. The 1st Israeli Listening Research Conference, Ono Academic College, Ramat Gan, Israel. http://dx.doi.org/10.23668/psycharchives.5054.
Kluger, A. N. (2015, April). Listening: Why should you and why should you not? Symposium presented at the 30th Annual Conference of the Society for Industrial and Organizational Psychology, Philadelphia, PA.
SLIDES from the SIOP 2015 conference:
An introduction (Slides 1-9) and "The Hidden Power of Listening: Meta-Analyses"
"If You Listen to Me, I Will Change My Attitude" by Guy Itzchakov
"Listener Effects on Psychological Safety – Attenuated by Avoidance-Attachment Style" by Dotan R. Castro
"Listening Up the Status Hierarchy: Unpacking the Social Status implications of Listening" by Anat Hurwitz.
Bouskila-Yam, O., & Kluger, A., N. (2011). The Facilitating Listening Scale (FLS). Paper presented at the 1st Israel Organizational Behavior Conference, Tel Aviv, Israel.
Kluger, A. N., & Bouskila-Yam, O. (in press). Facilitating Listening Scale: (Bouskila-Yam & Kluger, 2011, December). In D. L. Worthington & G. D. Bodie (Eds.), The sourcebook of listening research: Methodology and measures. West Sussex, UK: Wiley-Blackwell.
R Codes for Dyadic Data Analysis
A companion to
Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic data analysis. York: Guilford Press.
Converting data structures: Individual to Dyad, Dyad to Individual, and Individual to Pairwise
Computing intra-class correlation with confidence interval for Table 2.1
Table 3.3 -- example different from book
SEM for dyads with indistinguishable members
Table 6.1 Equality of variances
Table 6.2 Equality of correlations
Table 6.3 Latent variable correlations
Table 6.4 Omnibus test of distinguishability Correlations pairwise method (p. 138)
Table 7.1 Mimic APIM with MLM results obtained with SPSS in Table 7.3
Figure 7.2 Estimate indistinguishable APIM with SEM
Figure 7.3 Estimate distinguishable APIM (with SEM)
Table 8.4 Univariate SRM
Table 8.9 Bivariate SRM
Table 9.1 Family SRM
p. 292 Blog. One with many reciprocal design -- indistinguishable
p. 292 One with many reciprocal design -- indistinguishable with MLM
p. 293 One with many reciprocal design -- with SEM For R-based web applications, see Randi Garcia and Dave Kenny's Dyadic Data Analysis 2018 Workshop
Table 11.4 Social network analysis