Introduction
This investigation aims to uncover the scope of Generation Z's engagement with digital museum offerings. It examines how digital and cultural capital influence a group's consumption behaviours related to digital museum services. Additionally, the study explores the effects of various sociodemographic and attitudinal factors rigorously controlling for the interplay of cultural and digital capitals with socioeconomic and demographic variables – including gender, age, educational attainment, and the size of the place of living. In other words, this study aims to explore Generation Z’s demand for digital museums. Ultimately, our research seeks to unravel some intrinsic motivations and obstacles that shape Generation Z’s attitudes toward digital museum services.In the rapidly evolving digital landscape, many sectors, including cultural and creative industries, face significant transformation. Museums, central to heritage preservation and dissemination, typically navigate these changes. The shift towards digital management and engagement goes beyond technological adaptation, signifying a fundamental change in how culture is accessed, interpreted, and experienced, especially among younger demographics, such as Generation Z.
The cultural participation of Generation Z as a specific age cohort has not been addressed in the literature yet (Russo, 2023). Even less so when considering their engagement with digital museums, whose fluidity has yet to result in a consolidated definition. For the purposes of this analysis, we interpret the digital museum as a service provided by museums and delivered in digital form. Traditionally, socio-demographic factors, such as education (O’Hagan, 2017), age (Ateca-Amestoy 2020), gender (Muñiz et al., 2014), and the size of the population of the place of living (Brook, 2016), alongside capital (Sullivan, 2007), have consistently been identified as determinants of general cultural participation. This observation extends to patterns of physical museums (Falk and Katz-Gerro, 2015). Education, income, gender, and both individual and household cultural capital have recurrently emerged as the most influential factors (Falk and Katz-Gerro, 2015; Suárez-Fernández, 2020), while the impact of other socio-demographics remains less defined (Muñiz et al., 2014; Evans, 2016).
For Generation Z, the dimensions of cultural engagement may undergo a redefinition as traditional metrics are complemented by digital milestones and shared online experiences (Bertacchini et al., 2014). This shift prompts a reconsideration of the determinants of participation when it comes to digital museums. Unlike many other cultural consumptions, digital museum services and collections primarily function as (pure) public goods, being both non-excludable and non-rivalrous. Notably, they are provided to consumers at virtually no additional cost, diminishing the traditional influence of income as a determinant. The elimination of shadow costs, such as travel expenses (Borgonovi, 2004), further contributes to this shift. The same applies to the virtually universal access and pervasive daily access to the internet among younger cohorts (European Commission, 2020). This widespread connectivity has the potential to diminish geographical disparities, such as those between urban and rural areas. Consequently, the significance of other determinants in the participation process could be amplified, emphasising the evolving landscape of cultural engagement for Generation Z.
A survey instrument was designed to gather data on the frequency and quality of Generation Z's interactions with the offerings of digital museums. Based on the concept of capitals as influential propensities and abilities (Bourdeau, 1983; Butklova, 2020; Throsby, 2020), the instrument aims to establish the nature of connections between digital museum interactions and broader sociodemographic and capital variables of participants. A total of 700 surveys were analysed.
We construct the Digital Museum Engagement Score (DMES) which reflects Generation Z’s demand for digital museums services. The DMES is based on the stated frequency of consumption of eight different services provided online by museums in the twelve months prior to the survey.
We analyse the DMES based on the respondents’ dual capital profile: cultural and digital. Cultural capital of participants is measured two-fold. First, respondents take part in a short game that requires art history knowledge. The game involves engaging with three memes, which represent a form of the reuse of digital art collections, followed by answering one trivia question for each meme. Second, to gauge broader cultural engagement beyond digital museums, the study quantifies participants' cultural activities, leveraging the concept of cultural omnivorousness as a proxy for cultural capital (Peterson, 1992; Peterson and Kern, 1996). To evaluate digital capital, our study implements a two-fold approach. Firstly, the accumulation of digital resources is gauged by tallying the number of digital devices participants own (Willekens and Lievens, 2014). This provides a straightforward metric of their access to digital tools. Secondly, digital competencies are assessed through participants’ responses to a bespoke series of nine true/false statements. These statements are crafted to determine the extent of each participant's digital skills (European Commission, 2017; Ragnedda et al., 2019). Affirmative answers are indicative of competency in the specific digital skill queried and contribute to the cumulative Digital Competency Score (DCS). The survey extended beyond digital and cultural capital to include a variety of questions concerning participants’ digital cultural activities and the value they ascribe to various online museum features. It also explored their pre-pandemic cultural engagement, attitudes toward art expressed in digital media, and the perceived barriers to accessing physical cultural venues. This comprehensive inquiry aimed to illuminate the broader cultural engagement and preferences of Generation Z.
To analyse the impact of digital and cultural capitals, along with other selected independent variables, on the demand for digital museum services, we employ econometric tools. Initially, through simple linear regression, we explain variations in the DMES, which is incorporated into the model as a continuous variable approximating the number of respondents' interactions with various digital museum services. Apart from two independent variables related to cultural capital and two to digital capital, we include attitudinal variables, such as those related to intrinsic motivation to consume art. Additionally, we integrate sociodemographic variables and other control variables constructed from follow-up questions. For the robustness check, we try various model specifications. To address potential differences in the demand for various types of digital museum services, we disaggregate the DMES and further control for the impact of the same independent variables on binary participation, indicating whether respondents engaged or did not engage in each digital activity separately. For this analysis, we employ the multivariate probit, a popular method for modelling correlated binary data. Finally, we check whether the demand can be better understood when clustering digital activities according to the utilitarian versus experiential use of technology, the solo versus collective nature of the activities, the weight of nature or nurture, as motivational drivers offering deeper insights into the use of digital museum services.

Main takeaway and results:
Our results seem to point that both digital and cultural capital are significant predictors of the demand for digital museum services. Cultural omnivorousness and art knowledge positively impact the DMES, whereas digital competences prove to be stronger predictors than the accumulation of digital devices.
Detailed results indicate that engaging in an additional type of cultural activity corresponds to a 1.2-point increase in DMES. High cultural capital is associated with a 3.1-point increase in DMES. Each additional reported digital competence, as measured by the DCS, results in approximately a 1-point increase in DMES.
Interestingly, respondents from the EU exhibit a 2.4-point increase in DMES compared to those from non-member states. However, caution is needed due to the underrepresentation of respondents from non-member states. Traditional motivations for physical museum visits, rooted in education and inspiration, are mirrored in the digital realm. Youngsters facing challenges reaching physical museums score almost 8 points higher on the DMES, emphasising the role of digital museums in overcoming geographical barriers.
Interestingly, a knowledge gap among respondents concerning digital museums translates to a significantly reduced DMES, indicating a communication gap between institutions and Generation Z. Furthermore, while socio-demographic factors do not directly impact DMES, they remain predictors of cultural and digital capitals. City dwellers indicate more devices and higher digital competencies. Males report slightly fewer devices but show no difference in competencies. Females outscore males in omnivorousness but not in art knowledge.
Our analysis reveals that the factors driving demand for different digital museum activities do not vary significantly when examined independently. This suggests either the need for a more comprehensive understanding as digital museum engagement grows or the emergence of nuanced preferences as Generation Z becomes more accustomed to digital museum offerings.
In summary, our exploration of Generation Z's interaction with digital museums reveals key predictors of engagement. Both digital and cultural capital strongly influence demand, with cultural omnivorousness and art knowledge positively shaping the Digital Museum Engagement Score (DMES). Notably, digital competences outweigh the impact of device accumulation. The increased engagement in EU regions suggests that EU cultural policies indeed favor cultural participation. Nevertheless, this study emphasises the role of digital museums in overcoming geographical barriers related to the access of physical ones. Moreover, we have identified a knowledge gap between digital museums and the Generation Z, suggesting a need for refined communication strategies.

(Please note that we enclose the essential bibliography as Tables/Figures1)