Beyond the “substitution effect”: the impact of digital experience quality on future cultural participation

Figures & data

Table 1. Descriptive statistics.

Demographics^1
Age	20-34	35-54	55-74	75+	No info
	7.4%	29.3%	51.4%	10.1%	1.7%
Ethnicity	White	Ethnic minorities
	94.6%	2.5%			3.0%
Disability	Yes	No
	13.4%	83.3%			3.4%
Index of multiple deprivation (IMD)	Q1-Q3	Q4-Q7	Q8-Q10
	36.5%	25.6%	6.7%		31.1%
Vulnerability to Covid	Yes	No
	17.9%	76.3%			5.9%
Income change	Reduced	No change
	18.3%	76.8%			4.9%
Characteristics of previous and current online experience
Previous engagement with online culture	First time	Only since closure	Before and since		No info
	21.1%	45.1%	33.8%
Previous in-person visit to venue	Yes	No
	72.1%	27.9%
Form of access^2	Live stream	On-demand	Other
	31.0%	50.2%	18.8%
Cost	Free	Less than £10	£10-£20	More than £20
	12.8%	12.0%	51.8%	14.3%	9.1%
Device	Smartphone/ tablet	Smart TV or connected to TV	Computer	Other
	16.7%	33.1%	47.7%	2.5%
Party	Alone	One other person	Two or more people
	37.2%	34.5%	20.2%		8.1%

¹ To retain as much information as possible, cases with partially missing demographic information were kept and a new category of ‘no info’ was created for the analysis.

² The "Other" category was analysed and found to have little impact on the overall results, so it was kept in the main analysis.

Table 2. IDE quality indicators and associated dimensions from the literature.

Survey indicator	Range	Quality dimension
V1 How did your experience compare with how you thought it would be?	1: Much worse; 5: Much better	Risk (e.g. Radbourne et al., 2009)
V2 How easy or difficult did you find it to watch or take part in the online experience?	1: Very difficult; 5: Very easy	Consumer factors (E.g. Mueser & Vlachos, 2018), communicative dimension (E.g. Boerner et al., 2010; Swarbrick et al., 2021)
V3 What rating would you give the online experience in terms of value for money?	1: Very poor value; 5: Excellent value	Consumer factors (E.g. Mueser & Vlachos, 2018), risk (e.g. Radbourne et al., 2009)
V4 I hardly noticed the time passing	1: Strongly disagree; 5: Strongly agree	Emotional dimension (E.g. Eversmann, 2004; Boerner et al., 2010; Chan & Au, 2017)
V5 I felt lively and enthusiastic	1: Strongly disagree; 5: Strongly agree	Emotional dimension (E.g. Eversmann, 2004; Boerner et al., 2010; Chan & Au, 2017)
V6 I found aspects of the performance very moving	1: Strongly disagree; 5: Strongly agree	Perceptual dimension (E.g. Eversmann, 2004; Boerner et al., 2010; Chan & Au, 2017)
V7 How would you rate the quality of the artistic content?	1: Very poor; 5: Excellent	Presentation/rigour (E.g. Bunting & Knell, 2014)

Figure 1. Mean and standard deviation for quality indicators.

Figure 2. Mean quality index by demographics including 95% confidence interval for the mean. One-way ANOVA comparison is statistically significant for age (F-test = 5.741, p-value = 0.000).

Figure 3. Mean quality index by characteristics of previous and current online experience including 95% confidence interval for the mean. One-way ANOVA comparison is statistically significant for previous online attendance (F-test = 3890.672, p-value = 0.000), type of experience and (F-test = 2043.312, p-value = 0.011) device use (F-test = 7.155, p-value = 0.000).

Figure 4. Mean quality indicator by Previous engagement with online culture. One-way ANOVA comparison is statistically significant for V1 (F-test = 13.623, p-value = 0.000), V2 (F-test = 4.552, p-value = 0.011), V4 (F-test = 17.751, p-value = 0.001), V5 (F-test = 4.469, p-value = 0.012) and V7 (F-test = 8.753, p-value = 0.011).

Figure 5. Mean quality index by future intentions for in-person and online participation including 95% confidence interval for the mean. One-way ANOVA comparison is statistically significant for future in-person attendance (F-test = 11855.351, p-value = 0.000), and future online participation (F-test = 60.001, p-value = 0.000).

Figure 6. Distribution of future in-person attendance by terminal nodes.

Figure 7. Distribution of future in-person attendance by terminal nodes.

Figure A1. Exhaustive CHAID tree for future in person attendance to cultural organisation.

Figure A2. Exhaustive CHAID tree for future online participation in arts and culture.

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