Ubiquitous tunes, virtuous archiving and catering for algorithms: the tethered affairs of people and music streaming services

Figures & data

Table 1. Demographics full sample and sub-samples (weighted).

	Full sample	Premium-user	Freemium/non-user
Gender
Male	51%	52%	49%
Female	49%	48%	51%
Age
Mean age/SD	47/17.5	39/14.4	56/16.1
Below 30 years	21%	32%	8%
30–49	26%	32%	19%
45–59	26%	26%	25%
60 years or older	28%	9%	48%
Education
Primary school	9%	7%	11%
Upper secondary school	58%	57%	60%
Higher education ≤ 4 years	19%	21%	17%
Higher education 4 years >	14%	15%	12%
Income before tax
Less than 299,999	23%	24%	23%
300,000–499,999	35%	31%	40%
500,000–699,999	21%	24%	17%
700,000–999,999	7%	8%	5%
1 million or more	2%	3%	2%
Don’t want to answer	12%	10%	13%

Note: Some variables do not add to 100% due to rounding. Income in NOK (1 NOK ≈ 0.12 USD).

Table 2. Factor loadings (N = 793).

	CV	AV	ArV	PV	CBI
CV: Convenience value (from Oyedele & Simpson, 2018)
I like that I can listen to whatever I want wherever I want	.92
I like that I can listen to whatever I want whenever I want	.87
With [MSS] the music I like is always available	.78
[MSS] are easy to use	.61
It’s easy to find the music I want to listen to	.61
It’s easy for me to learn to use [MSS]	.59
[MSS] includes all the music I want to listen to	.50
AV: Algorithmic value. Personalized recommendations often
help me discover music I’m not already familiar with		.82
include music I like		.80
include music I end up saving (for example in a playlist)		.77
help me expand my taste in music		.74
ArV: Archive value. It’s important for me to save music to
link music to a certain time or place			.84
make it easy to find music (…) to play in different situations			.71
create a sense of ownership to music that matters to me			.64
avoid losing track of music that matters to me			.51
PV: Price value. (from Venkatesh et al., 2012)
offer a good and economically favourable product for the price				.90
The subscription costs (from 99 NOK/month) is acceptable				.89
[MSS] provide good value for the money				.87
CBI: Cont. behav. intention (from Venkatesh et al., 2012)
I intend to use [MSS] often in the future					-.80
I want to use [MSS] more in the future					-.72
I will continue to use [MSS] in the future					-.64
Variance explained	35.29	11.19	8.25	7.17	4.77
Cronbach’s alpha	.87	.80	.75	.92	.86
M	4.3	3.5	3.5	3.9	4.0
SD	.57	.71	.78	.84	.77

Note: Coefficients below .2 suppressed. Factor loadings over .60 appear in bold. Wording of items condensed compared to survey. Music streaming services shortened to MSS in the table, but not in the questionnaire.

Table 3. Correlation coefficients.

	CV	PV	ArV	AV
Convenience value (CV)	1
Price value (PV)	.52^a	1
Archive value (ArV)	.32^a	.26^a	1
Algorithmic value (AV)	.37^a	.31^a	.41^a	1
Continued behavioural intention (CBI)	.55^a	.52^a	.43^a	.33^a

^aCorrelation is significant at the .01 level (two-tailed).

Table 4. Results from the hierarchical regression analysis.

	Dependent variable: continued behavioural intention
	b	SE B	β	p
Model 1
Constant	.959	.18		<.001
Convenience value	.43	.05	.34	<.001
Price value	.31	.03	.37	<.001
Model 2
Constant	.60	.18		<.001
Convenience value	.35	.05	.27	<.001
Price value	.29	.03	.34	<.001
Archive value	.23	.03	.23	<.001
Model 3
Constant	.52	.18		<.001
Convenience value	.33	.05	.26	<.001
Price value	.29	.03	.33	<.001
Archive value	.22	.03	.22	<.001
Algorithmic value	.05	.04	.05	.161

Note: R²=.38 for step 1 (p<.001); ΔR²=.05 for step 2 (p<.001); ΔR²=.002 for step 3 (p=.161).

Table 5. Interview participants (pseudonyms).

Participant	Age	Premium services	Freemium services
Kevin (m)	21	Spotify	Soundcloud, YouTube
Bård (m)	24	Spotify	YouTube
Richard (m)	25	Spotify	YouTube
Sara (f)	26		Spotify, YouTube
Ruth (f)	26	Spotify	YouTube
Annette (f)	27	Tidal	Spotify*
Erik (m)	27	Spotify, Tidal*	YouTube
Vilde (f)	31	Spotify	YouTube
Camilla (f)	31	Apple music, Spotify*, Tidal*	YouTube
Markus (m)	36	Spotify*	YouTube
Kristian (m)	36	Tidal, Spotify*	YouTube
Thomas (m)	43	Spotify	Soundcloud, YouTube
Morten (m)	46	Spotify
Lars (m)	49	Spotify, Apple music	Soundcloud, YouTube
Nina (f)	52	Spotify	YouTube
Heidi (f)	56	Spotify, Apple music*
Anne (f)	57		YouTube, Spotify*
Ingrid (f)	72	Apple music	YouTube, Spotify*

Note: Services marked with * refer to discontinued subscriptions or use.

Oyedele, A., & Simpson, P. M. (2018). Streaming apps: What consumers value. Journal of Retailing and Consumer Services, 41, 296–304. https://doi.org/https://doi.org/10.1016/j.jretconser.2017.04.006

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Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MS Quarterly, 36(1), 157–178. https://doi.org/https://doi.org/10.2307/41410412.

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