Collaborative Playlists around the World: A Cross‑Cultural User Study

2.1 Social practices around music

Music acts as a social agent that helps reinforce existing relationships and establish new ones (DeNora, 2000; Hargreaves and North, 1999), as it can “increase social cohesion and strengthen inter‑individual attachments” (Koelsch, 2013, p. 204).

Characteristics of music can act as social indicators: Musical tastes are used to express and infer personality traits (Lonsdale and North, 2011; North and Hargreaves, 1999; Rentfrow and Gosling, 2003; Rentfrow et al., 2009) and can influence impression formation even in online settings. Music fandoms, or having one’s music taste centered around specific musicians, are increasingly prominent on social media (Kang et al., 2019). Taking nonverbal online actions (Park et al., 2021b) for certain artists may suggest ideological (e.g., political) alignment, as could participating in fandom activities such as activism (Park et al., 2021a).

Discussing and sharing music are also common social music activities that express identity and communicate affection (Brown and Sellen, 2006; Cunningham, 2019; O’Hara and Brown, 2006). In social music recommendation, underlying relationships can be so important that they sometimes override other factors in assessing the value of a recommendation (Lee et al., 2019). In fact, music recommended through interpersonal channels embodies greater diversity, novelty, and serendipity than system recommendations (Kim et al., 2020).

Music co‑listening has been found to advance conversation about music (Lee and Price, 2015), helping to form or strengthen relationships and sometimes making a deep and lasting impact (Lee et al., 2019). As with many social music activities, co‑listening has also come to take place over virtual platforms (Vandenberg et al., 2020). Yet, co‑listening engagement can be limited by feature design gaps, suggesting a need for improved tools to support these kinds of activities (Stewart et al., 2018).

2.2 Collaborative music playlists (CPS)

Social music engagement now includes curation of collaborative playlists (CPs) on streaming platforms. Central to our present work is a seminal study by Park et al. (2019) that characterized usage and perception of CPs. They introduced the CP Framework, which delineated three purposes and two connotations surrounding CP usage. Practical purposes relate to the context of consumption, the playlist content (type of music), or the intrinsic enjoyment of creating a CP. Cognitive purposes relate to discovery—of new music as well as collaborators’ tastes and consumption patterns. Finally, Social purposes relate to sharing as well as strengthening ties (bonding) through CPs. The two connotations are Utility, referring to reducing effort through collaboration, and Orientation, denoting a stated directionality—i.e., that a CP or its curation will benefit oneself or named others. The authors also assessed social connection through music more broadly, finding that CP users, compared with non‑users, reported more sustained connections with others through music.

More recently, an analysis of reported CP usage patterns (Park and Kaneshiro, 2021) and an investigation into important and desired aspects of CPs in support of user needs (Park and Kaneshiro, 2022)—both involving CP users from the United States—reinforced the three purposes of the CP Framework and highlighted users’ desire for CPs to be actively contributed to and engaged with. Relating to this, comfort levels of interacting with a CP interface resembling a commercial platform have been found to differ according to the action (i.e., adding, deleting, and reordering songs), the initiator of the CP, and the original contributor of a song (Park and Lee, 2021). Recent work by Park et al. (2022b) highlights changes in motivations and behaviors around CP usage during the coronavirus disease 2019 (COVID‑19) pandemic. In all, CPs are found to serve user needs relevant to personal playlist usage, such as music discovery (Schedl et al., 2018), but converging evidence also indicates that social factors unique to co‑curation influence multiple aspects of CP usage and perceived success.

2.3 MIR and HCI studies of music, location, and culture

Music is a cultural product that reflects the history, tradition, and societal context of its origin. MIR researchers have long aimed to characterize music listeners on the basis of geographical or cultural affinity (Lee et al., 2005). Across multiple studies, Hu and Lee found that differences in music mood perception aligned with cultural backgrounds of American, Chinese, and Korean listeners (Hu and Lee, 2012; Hu and Lee, 2016; Lee and Hu, 2014). In 2014, Jun et al. (2014) devised a map construction based on across‑locale music consumption patterns using Twitter’s Streaming API, while Moore et al. (2014) derived culture‑ and language‑based clusters from an embedding analysis of music‑related tweets. Expanding on Moore’s work, Pichl et al. (2017) identified clusters of Spotify users that revealed music preference correlations between certain cultures as well as country‑specific and cross‑country patterns of music listening. Other recent studies have taken big‑data approaches: Liu et al. (2018) analyzed 10 billion music‑listening records of users in 18 countries and found that music preference similarities could be explained by cultural similarities, while Way et al. (2020) used 5.5 years of all streaming data on Spotify to explore music listener preferences for local versus global content, finding greater preference for local music among early Spotify adopters. Finally, Knees et al. (2022) replicated findings around a Korean sample’s interpersonal relationships in music recommendation (Kim et al., 2020) with a European sample (see § 2.1).

MIR researchers have examined geographical and cultural considerations of datasets used in content‑based analyses. A longitudinal project from 2011 to 2017 on multiculturalism led by Serra (2011) explored music unique to five distinct cultures of the world: Hindustani (North India), Carnatic (South India), Turkish makam (Turkey), Arab‑Andalusian (Maghreb), and Beijing Opera (China). Recognizing the influence of cultural background on content and perception of music, researchers questioned whether computational models constructed from music of one culture (particularly Western in origin) could be applicable to music of another (Wu and Xie, 2008). Models were constructed and evaluated with multiple cross‑cultural music datasets, such as British–American versus Chinese (Hu and Yang, 2017), Hindi versus Western (Patra et al., 2018), and Brazilian versus British–American (de Sousa et al., 2016). Evaluation campaigns also initiated tasks involving music of different cultures, e.g., mood and genre classification of Kpop songs in the Music Information Retrieval Evaluation eXchange (MIREX; Lee et al., 2013; Hu et al., 2014). Culture is now highlighted as one aspect of diversity that should be considered in the design of music recommendation systems (Porcaro et al., 2019).

HCI studies also examine these factors with implications for broader system design. Kayan et al. (2006) posited that tool design for cross‑cultural instant messaging should consider cultural differences. Boer and Abubakar (2014) found that, across four cultures, music listening strengthened ties among families and peer groups; similarly, Litt et al. (2020) found that friends, family, and shared activities consistently facilitated interactions across the United States, India, and Japan. Recent work by Park et al. (2022a) presented design implications around similarities and differences in music‑sharing behavior in South Korea and the United States.

Together, these diverse lines of research frame the current study of CP perceptions and usage across different contexts.

3.1 Ethics statement

Ethics approval for the research was obtained from each involved institution (one institution per location).

3.2 Scope

We investigated four cultures, enabling the study of differing norms and practices surrounding music co‑consumption across cultures: Hong Kong (HK), South Korea (KR), Quebec (QC),³ and the United States (US). Each culture was considered to have a distinct societal context (e.g., dominant and accessible music services, language, and social norms), as “language, time, and place are important in determining the difference between one and another culture” (Triandis, 2001, p. 908). This set includes two North American (QC and US) and two Asian (HK and KR) sites, which could enable “Western” and “Eastern” distinctions to emerge (Hofstede, 1984). We also accounted for a balance of national (KR and US) and subnational (HK and QC) entities in each continent. To ensure proper study design and data analysis, at least one author had expert familiarity with each culture—they originated from and/or resided long‑term (more than a decade) in the location, were fluent in the language and cultural customs, and had conducted user studies with the respective cultural sample.

3.3 Survey

Basing our survey design on the survey by Park et al. (2019) enabled direct comparison of findings. Accordingly, the US and QC samples could potentially provide more detailed insights into usage and perception of CPs in North America, the primary demographic of that previous work. For the current study, participants in the US completed the survey in its original, English‑language form; survey questions for participants in HK, KR, and QC were presented in Chinese (traditional), Korean, and French, respectively, translated from English by native‑speaking researchers. Survey questions with translations are included in Supplementary Material §S1. The questions analyzed here represent part of a larger survey.

3.4 Participants and sampling

Participants were recruited through various channels, including online music groups, music classes, and flyers as deemed appropriate by the research team. Eligible participants were 18 years of age or older, lived in the respective location, spoke the language of the respective survey, and used music streaming services. As in Park et al. (2019), participants were not required to be CP users specifically; this enabled collection of non‑users’ perceptions for comparison with current users. After completing the survey, participants could enter a raffle conducted separately for each location; each raffle had a 10% chance of winning the location’s and currency’s equivalent of a $10 USD gift card. Data were collected between March 2019 and February 2020, reflecting perceptions and experiences prior to the COVID‑19 pandemic. All data were anonymized at the time of data collection.

In this exploratory work, our objective was to glean rich insights into areas that had not yet been researched rather than to obtain generalizable findings. As such, the study used small, non‑probabilistic samples— specifically, a non‑proportional quota sampling method comprising four different categories—and a minimum number of participants was recruited for each category, without considering the population size of the strata (Singh, 2007).

Across cultures, a total of $N=262$ participants completed the survey; demographics are reported in Table 1.⁴ Participants used a variety of streaming platforms to listen to, discover, share, and co‑curate music (Supplementary Figure SF1). Overall, Spotify was used most across HK, QC, and US, followed by YouTube Music and Apple Music; in KR, Melon Music and YouTube Music were used most.⁵

3.5 Analysis

4.1 CP usage varies by culture

We assessed whether CP usage group membership— user ($U$), interested non‑user ($N_i$), and uninterested non‑user ($N_n$)—differed significantly by culture. As suggested by Table 1, the differences were significant (${\chi }^2(6)=35.31$, $p=3.76\text{e-}06$). Normalized residuals of the contingency table indicated that the chi‑squared statistic was driven primarily by comparatively high $U$ in the US (accounting for 50.58% of the ${\chi }^2$ score), followed by low $U$ in QC (8.91%), low $N_i$ in the US (8.87%), and low $N_n$ in the US (8.80%).

4.2 All cultures report CP framework categories (RQ1)

The CP Framework (Park et al., 2019) delineates three categories of CP purpose (Practical, Cognitive, and Social) and two categories of connotation (Utility and Orientation) based on free‑text reports of experienced or perceived CP purposes (§2.2). In the present study, we collected responses to the same originating questions from $U$ and $N_i$ participants and found all five CP Framework categories were implicated in the responses from each culture with no new categories emerging (Table 3).

4.3 Impacts of CP usage

4.3.2 Principal dimensions of CP outcomes indicate benefits to utility and music experience

A per‑culture PCA analysis of responses to the above questions revealed consistent principal dimensions across cultures, implicating eight of the 10 CP outcomes (outcomes listed in Table 4 caption; see Methods). A subsequent PCA computed over data pooled across cultures for these eight outcomes revealed two principal dimensions, labeled as benefits to Utility ($alpha=0.78$ across Q2c, Q2d, and Q2e) and to Music Experience ($alpha=0.75$ across Q2a, Q2b, Q2g, Q2h, and Q2j). Together, these dimensions explained 59% of the variance in the data. Quantitative analysis of results shown in Figure 1 indicate that, for Music Experience, responses vary significantly according to CP user group ($F=16.94$, $p<0.001$) but not culture. Utility responses varied according to both CP usage ($F=7.99$, $p<0.001$) and culture ($F=5.80$, $p<0.001$).

Figure 1

4.3.3 Broader social connection through music varies by culture and CP usage

To understand broader ramifications of CP usage, we assessed participants’ views on social connection through music (Figure 2). As shown in Table 5, all linear models were at least marginally significant (all $F\ge 1.99$, all $p_{FDR}\le 0.081$, four comparisons). As for whether CP usage impacts perception of social connection through music, inspection of CP user groups pooled across cultures suggests monotonically increasing agreement from $U$ to $N_i$ to $N_n$ for questions on perceived decline in connection (Q3a and Q3c), and monotonically decreasing agreement for questions on music facilitating connection (Q3b and Q3d). Quantitatively, for personally feeling that music helps them connect with others (Q3b), $U$ responses were marginally significantly higher than $N_i$ ($t=1.87$, $p_{FDR}=0.63$, three comparisons here and following) and significantly higher than $N_n$ ($t=3.38$, $p_{FDR}=0.0030$); $N_i$ was also marginally significantly higher than $N_n$ ($t=2.09$, $p_{FDR}=0.059$). Additionally, $N_n$ agreement that connecting through music has declined personally (Q3a) was significantly higher than $U$ ($t=2.87$, $p_{FDR}=0.014$), and significantly lower than both $U$ ($t=3.55$, $p_{FDR}=0.0016$) and $N_i$ ($t=2.65$, $p_{FDR}=0.014$) for agreeing that, in general, music helps people connect with others (Q3d). (Marginally) significant main effects of culture pointed to higher agreement from HK participants that connections through music have declined personally and generally ($t\ge 2.00$, $p_{FDR}\le 0.095$, six comparisons per sub‑question), and from US participants that, personally, music helps them connect with others (Q3b: $t\ge 2.30$, $p_{FDR}=0.069$).

Figure 2

Table 5

Ordinal responses on broader social connection through music (user $U$; interested non‑user $N_i$; uninterested non‑user $N_n$). Participants reported their level of agreement, on a scale of 1 to 5, to the following statements: (Q3a) “In my case, personally, connecting with others through music has declined,” (Q3b) “In my case, personally, music has helped to connect with others,” (Q3c) “In general, connecting with others through music has declined,” and (Q3d) “In general, music has helped people connect with others.” We report overall model output, significance of individual predictors, and significance from follow‑up pairwise t‑tests ($\ast \ast$ $p<0.05$; $\ast$ $0.5\le p<0.1$).

		CP usage					Culture
	Model	Predictor		U	Ni	Nn	Predictor		HK	KR	QC	US
Q3a	$F(5,256)=3.29$,	$F(2,256)=3.08$,	Means	2.42	2.69	2.98	$F(3,256)=2.51$,	Means	3.03	2.60	2.66	2.48
	$p_{FDR}=0.013$	$p=0.047$	$N_n>$	$\ast \ast$			$p=0.059$	HK $>$		$\ast \ast$	$\ast$	$\ast \ast$
Q3b	$F(5,256)=3.32$,	$F(2,256)=4.13$,	Means	4.02	3.76	3.38	$F(3,256)=1.57$,	Means	3.72	3.55	3.61	4.03
	$p_{FDR}=0.013$	$p=0.017$	$U>$		$\ast$	$\ast \ast$	$p=0.20$	US $>$		$\ast$	$\ast$
			$N_i>$			$\ast$
Q3c	$F(5,256)=1.99$,	$F(2,256)=0.012$,	Means	2.64	2.67	2.69	$F(3,256)=3.29$,	Means	2.99	2.45	2.66	2.57
	$p_{FDR}=0.081$	$p=0.99$					$p=0.021$	HK $>$		$\ast \ast$		$\ast$
Q3d	$F(5,256)=3.10$,	$F(2,256)=4.52$,	Means	4.29	4.14	3.82	$F(3,256)=1.22$,	Means	4.00	4.02	4.08	4.30
	$p_{FDR}=0.013$	$p=0.012$	$N_n<$	$\ast \ast$	$\ast \ast$		$p=0.30$

5.1 CP engagement varies across cultures

We observed the greatest percentage of CP usage among US participants at 51%, comparable to pre‑pandemic findings from Park et al. (2019) involving mostly US participants. In contrast, HK, KR, and QC showed lower engagement with CPs (Table 1). The lower CP activity in KR may be explained by the lack of CP functionalities in widely used music services and lack of access to Spotify—the most dominant platform used to engage in CPs overall—at the time of data collection.⁵

In HK and QC, however, Spotify—and hence the function of CPs—was available, yet percentages of $U$ in these two samples were low. Prior studies investigating collaborative work suggest this could be related to cultural factors. For instance, HK residents consider their society to be one that promotes harmony (Ho and Chan, 2009); avoidance behaviors such as “steer[ing] away from confrontation” have been observed in collaborative writing among HK students (Bremner et al., 2014, p. 159), and such aversions toward modifications might extend to the context of CPs as well, especially given some CP actions may be highly uncomfortable (e.g., perceived as being judgmental or confrontational), as found in Park and Lee (2021). Alternatively, features for social interaction may not be adequately compelling or known to users to encourage usage, suggesting a need for strategic positioning and ancillary features to support engagement with CPs. As for QC, it is known to produce and consume its own music (Piroth, 2022) that “primarily exists in an internal cultural space [...] undefined outside the borders of the province” (Jones, 2001). Prioritizing local music, often played ubiquitously via the radio, could be a reason for low CP engagement. Other reasons could be related to QC’s Spotify user behavior. Most QC respondents noted using Facebook to share music, even among Spotify users. Spotify users in QC may have not had as much time to get used to the platform to use more advanced features such as CPs (Spotify launched in the US in 2011 and Canada in 2014).⁷ Possibly, the lower market penetration rate of Spotify in QC caused Spotify users to maintain existing practices of sharing music; music sharers in Park et al. (2022a) often turned to YouTube and social media to share music, as not everyone they wanted to share with had a Spotify account. These are merely a few possible explanations; future studies should investigate underlying reasons and specific perspectives surrounding CP usage.

5.2 Unpacking cultural similarities and differences in CP framework categories

Consistent with previous findings by Park et al. (2019), US $U$ mentioned the Practical and Social categories more than US $N_i$ (Table 3). While more recent US‑centric work since the start of COVID‑19 highlights additional, broader categories motivating CP usage such as “relieving pressure” and “nostalgia” (Park et al., 2022b), all responses in the present sample could be categorized into at least one existing CP Framework category; no new categories emerged. Thus, for the present sample, the CP Framework generalized to cultures beyond the US.

Overall, while $U$ and $N_i$ participants from the four cultures reported or expected engagement with CPs for all three purposes, the varied proportions of these purposes highlight differing levels of motives for engaging with CPs:

Practical. Playlists can be curated around various musical themes or listening contexts (Hagen, 2015). In HK, QC, and US samples, substantially more $U$ than $N_i$ mentioned Practical purposes involving social events (e.g., road trips and private parties at homes), similar to previous findings (Park et al., 2019; Park and Kaneshiro, 2021). In contrast, KR $U$ mentioned Practical purposes significantly less than $N_i$. Across KR responses, mentions of social events did not emerge, though more intrinsic aspects did (e.g., enjoyment of music [KR44‑$N_i$] in §4.2.1). This may be explained by differing social settings for music co‑curation and co‑consumption in KR, where music is reportedly shared often through group chats and social media (Park et al., 2022a), and rarely through social events; house parties are not common (Song, 2014), and more popular activities such as karaoke may not necessitate CPs.

Cognitive. Discovering music and others’ musical tastes are considered pleasurable activities (Hakansson et al., 2007; Liu and Reimer, 2008). While such Cognitive purposes were not the predominant reasons for $U$ to engage with CPs in the present sample, Cognitive was the most‑implicated purpose across cultures for $N_i$. This suggests that past findings from a primarily North American sample (Park et al., 2019) may generalize to other cultures; the emphasis on Cognitive purposes from $N_i$ may reflect non‑users projecting music‑discovery benefits, offered by streaming services’ recommender systems in the context of personal consumption, to the CP context. Moreover, $N_i$ mentioned Cognitive purposes more than $U$ across all four cultures ($U$ mentioned the other purposes more often; Table 3). This suggests that $U$ might have shared music with people who already have similar tastes or hesitated to add music that might not be familiar to others, thereby curbing Cognitive benefits. This discrepancy between $N_i$ and $U$ warrants further research.

Social. In‑person interactions serve as the oldest and potentially richest means of communicating (Baym et al., 2004; Berger and Luckmann, 1966). Meaningful social connections can also be established and maintained virtually (Olsson, 2009), including through co‑curation of CPs (Park and Kaneshiro, 2021; Park et al., 2022b). KR and US respondents gave similar proportions of Social mentions (more for $U$ than $N_i$, Table 3), which exceeded those from HK and QC respondents. KR and US participants frequently expressed a desire to share music and to bond, as music sharers in these samples have also been found to do (Park et al., 2022a). For them, CPs facilitated better understanding of their collaborators and emotional connections, as found in prior work (Park and Kaneshiro, 2021). Kim et al. (2011) also found similar motives behind the usage of social network sites for KR and US users, though those in KR put greater emphasis on supporting existing social relationships, while those in the US emphasized entertainment.

Moreover, desire for validation—a distinct reason for sharing music among US and KR participants (Park et al., 2022a)—also emerged as a motivation for CP usage, for example, “I’d feel proud/pleased if they all listened to the songs I selected”/“제가 선택한 노래를 다들 들어주면 뿌듯할 것 같습니다” (KR49‑$N_i$). This also illustrates CPs’ potential use for taste performance, which is closely tied to impression management (Goffman, 1959). Social media are known to be used for taste performance as an expression of prestige (Laplante et al., 2017; Liu, 2007; Papacharissi, 2012), with users selectively self‑presenting to “appear attractive, successful, or savvy to others” when deciding what music to share (Johnson and Ranzini, 2018, p. 156); this could be an underlying reason for KR56‑$U$ comparing CPs and social media (§4.2.1).

In contrast to KR and US, QC and HK had fewer Social mentions, especially from $U$. French Canadians’ higher susceptibility to interpersonal and value‑expressive influences (i.e., the influence of others’ values, attitudes, and behavior) compared with English‑speaking counterparts in consumer behavior (Mourali et al., 2005) could be one explanation. This susceptibility could lead to greater wariness of being judged on music preferences, resulting in a reluctance to use CPs. Similar discomforts were reported by the aforementioned HK students around collaborative writing (Bremner et al., 2014) (§ 5.1). Among US CP users, deleting and reordering songs in CPs has been found to be highly uncomfortable (Park and Lee, 2021); future studies could determine whether this discomfort is greater for HK and QC users.

Utility. We found similar percentages of Utility reports from $U$ and $N_i$ in HK and KR (15–20%), while there was surprisingly little to no mention of Utility from US and QC $N_i$. From US $U$, Utility mentions reflected direct experience with CPs—many $U$ noted saving time and effort when creating CPs for social events. This notable departure from previous findings—in which Utility was reported more by $N_i$ than $U$ in a predominantly North American sample (Park et al., 2019)—calls for further research on Utility aspects of CP usage with a larger sample.

Orientation. Reports of Orientation varied by culture, and responses implicated benefits to self more than others. Contrary to reports of “other”‑focused reasons for sharing music (Park et al., 2022a), we found no sample that displayed greater for‑others orientation of CP engagement as an act of service.

5.3 Not all non‑users are the same: $N_i$ versus $N_n$

Unlike Park et al. (2019), who reported differences in CP outcomes and social music perceptions between users and non‑users without differentiating non‑users on the basis of interest in CPs, we have further separated $N_i$ and $N_n$. In doing so, we have found that non‑users’ interest, or lack thereof, in CPs corresponded to significantly different expectations for outcomes.

Unsurprisingly, $N_n$ participants had more neutral or negative outlooks on CP outcomes, whereas $N_i$ participants showed more openness and positive associations. Interested non‑users felt CPs could be a “fun process,” could “broaden” one’s range of music, could provide a “window into” what their family was listening to, and could aid them in “recommending music to others” (§ 4.2.1); in fact, they collectively mentioned all CP purposes. Meanwhile, $N_n$ generally did not see utilitarian benefits of CPs. They may feel that existing tools such as personal playlists—a popular way of finding experts or others with similar tastes and consuming their music (Lee, 2009; i.e., Cognitive purpose)—are sufficient for their music goals. They also aligned more with the “music recluse” persona, who is not compelled to discuss listening habits with others and may avoid social functions of music platforms altogether (Lee and Price, 2015). KR $N_n$, however, recognized the Utility benefits of CPs to the same extent as $U$ and $N_i$. This aligns with prior work showing that South Koreans have more positive perceptions (e.g., greater novelty) of music received from others than of system recommendations (Kim et al., 2020)— therefore perceiving greater Utility from human recommendations. Appreciation for Melon Music—a popular Korean streaming platform that enables users to “[browse] and [bookmark] other users’ playlists”—and using these playlists “as a tool for expanding the horizon of music experiences” (Lee, 2009, p. 500) also suggest that KR $N_n$ may embody the “music recluse” persona less, which is further supported by findings that music listeners in KR desired more validation of their music taste than those in the US (Park et al., 2022a).

In contrast, $N_i$ approached or leveled with expectations of $U$ on CP outcomes, even exceeding $U$’s perceptions of Music Experience in the US and KR. This could imply $N_i$’s greater openness toward music consumption habits being changed with CPs,⁸ as supported by their high agreement that appreciation for CP functionality would increase with CP usage. Overall, $N_i$’s optimism toward CPs presents an opportunity for platforms to engage users through such functions.

5.4 CP motivation, engagement, and outcomes are not geographically aligned

Across locales explored, there were more similarities overall between HK and QC (sub‑national), and between KR and the US (national). Despite being from different continents, we found HK and QC showed similarities in outcomes of Music Experience and Utility (§4.3.2) as well as relatively low CP adoption even with Spotify being available in both locations. On the other hand, similarities around dominant purposes for and outcomes derived from CP engagement were observed between KR and US.

Other, more influential culture‑specific music factors should be considered in better understanding the similarities and differences observed in this study. One example is the market size and velocity of music market growth in the locales. The digital music market in KR is “thriving” with an annual growth rate of total music revenue at 10%, similar to that of the US at 11%, and “innovative platforms integrating K‑pop and advanced technology to cater to diverse consumer preferences”.⁹

Another factor may be the music scene in the location. The Kpop idol culture is prevalent in KR, with fandoms primarily listening to singular artists or groups. Playlists are often shared within fandoms to strategically support an artist (e.g., increasing streaming count; Lee and Nguyen, 2020), hence collaboration around CPs for Cognitive purposes may be less necessary. Personality and music preferences (Rentfrow and Gosling, 2003), and hence behaviors within locations and cultures as an extension, may also evolve to become more or less similar. Recent KR–US convergences¹⁰ in music engagement—suggested by increasing popularity of KR artists in the US, US music in KR charts, and KR–US musician collaborations—could be more dominant factors. These may have contributed to recently reported music‑related KR‑US similarities: Listeners in the US were shown to be more similar to those in KR than to those in China with regard to music mood judgment (Lee and Hu, 2014), and factors of music sharing were similar in KR and the US (Park et al., 2022a). Similarly, whether QC’s cultural specificities—such as music primarily from their own culture in their charts (Piroth, 2008)—are a point of alignment with HK could also be studied further to understand commonalities between these two cultures. In sum, our findings highlight that while existing cultural frameworks (e.g., “West versus East” (Diaper and Lindgaard, 2008; Hofstede, 1996)) may have merit, they may pose an oversimplification and may not be applicable in the context of CPs.