Factors Predicting Singers’ Work Efficiency and Singers’ Singing Peak

Huang, Xuejie; Ang, Mei Foong

Factors Predicting Singers’ Work Efficiency and Singers’ Singing Peak

International Journal of Music Business Research

Volume 13 (2024): Issue 1 (April 2024)

By: Xuejie Huang and Mei Foong Ang

Open Access

|Mar 2024

Figures & Tables

The singing efficiency prediction model. RwT: rework times; SinD: singing duration; DR: dynamic range.

Mean RwT changed by SinD. RwT: rework times; SinD: singing duration.

Linear regression analysis examining the relationship between predictive variables and SinD_

Model Variables	B	S.E	β	95% CI		AIC	R²	∆R²

				LL	UL
Step 1						1,633.49	0.24^***	0.23
R	−0.601	0.097	−0.27^***	−0.075	−0.039
P	0.012	0.007	0.072^**	−0.936	−0.626
DR	−0.038	0.017	−0.09^**	−0.010	0.016
Pronun	−0.168	0.110	−0.06	−0.032	0.035
Vib	−0.001	0.000	−0.053	−0.429	0.099
Vqual	−0.087	0.140	−0.025	−0.001	0.000
Step 2						1,542.07	0.40^***	0.40
Intensity	−0.826	0.082	−0.44^***	−0.988	−0.664
Step 3						1,163.11	0.45^***	0.45
SinD	−0.057	0.009	−0.27^***	−0.075	−0.039

Mediation effect test of SinD_

Outcome variable	Predictive variable	R²	S.E	F	95% CI

					LL	UL
SinD	Intensity	0.036^***	0.46	14.15	0.82	2.61
RwT	Intensity	0.39^***	0.08	121.43	−1.11	−0.80
SinD	Intensity	0.39^***	0.01		−1.08	−0.04
RwT	Intensity	0.31^***	0.08	169.31	−1.22	−0.90

RwT correlated with the acoustic variables_

	R	SinD	Intensity	P	Pronun	DR	Vqual	Vib
RwT	−0.398^**	−0.384^**	−0.563^**	0.181^**	−0.116^*	−0.230^**	−0.059	−0.152^**
R		0.148^**	0.319^**	−0.092	0.027	0.178^**	0.003	−0.005
SinD			0.193^**	0.261^**	0.103^*	0.429^**	−0.098	0.101^*
Intensity				0.139^**	0.045	0.199^**	0.009	0.093
P					−0.041	−0.109^*	0.033	−0.069
Pronoun						0.019	−0.023	0.125^*
DR							−0.093	0.184^**
Vqual								0.058

Frequency of the acoustic best performance in each part of the song_

Duration	Variable

	RwT = 0	Intensity ³ 75	R = 6	P £ 50
Verse 1	12 (15.0%)	26 (32.5%)	30 (37.5%)	77 (96.25%)
Chorus 1	11 (13.75%)	28.75 (35.94%)	55 (68.75%)	78 (97.5%)
Verse 2	13 (16.25%)	11 (27.5%)	21 (52.5%)	38 (95.0%)
Chorus 2	40 (50.0%)	43 (53.75%)	51 (63.75%)	80 (100%)
Post-chorus	38 (47.5%)	45 (56.25%)	58 (72.5%)	79 (98.75%)
Outro	6 (30.0%)	8 (40.0%)	10 (25.0%)	18 (90.0%)

Mediation effect size of SinD_

Variable	Effect type	Coefficient	S.E	95% CI

				LL	UL
SinD	Total effect	−1.06^***	0.081	−1.22	−0.90
	Indirect effect	−0.11^***	0.034	−0.18	−0.04
	Direct effect	−0.95^***	0.078	−1.11	−0.80

DOI: https://doi.org/10.2478/ijmbr-2024-0004 | Journal eISSN: 2227-5789

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Language: English

Page range: 17 - 26

Submitted on: Nov 14, 2023

Accepted on: Jan 25, 2024

Published on: Mar 30, 2024

Published by: International Music Business Research Association (IMBRA)

In partnership with: Paradigm Publishing Services

Publication frequency: 2 issues per year

Keywords:

singer,

Related subjects:

Business and economics,

Business management,

Industries,

Entertainment industry, media, publishing companies,

Cultural management,

Social sciences,

Sociology,

Sociology of economy, organizations, and industry

© 2024 Xuejie Huang, Mei Foong Ang, published by International Music Business Research Association (IMBRA)
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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Factors Predicting Singers’ Work Efficiency and Singers’ Singing Peak

Figures & Tables

Figure 1.

Figure 2.

Figure 3.

Linear regression analysis examining the relationship between predictive variables and SinD_

Mediation effect test of SinD_

RwT correlated with the acoustic variables_

Frequency of the acoustic best performance in each part of the song_

Mediation effect size of SinD_

Paradigm

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