Using conjoint analysis for a value estimation of the consumption attributes of online performances

Bo-Hyun, Baek Article Using conjoint analysis for a value estimation of the consumption attributes of online performances Cogent Business & Management Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Bo-Hyun, Baek (2023) : Using conjoint analysis for a value estimation of the consumption attributes of online performances, Cogent Business & Management, ISSN 2331-1975, Taylor & Francis, Abingdon, Vol. 10, Iss. 3, pp. 1-16, https://doi.org/10.1080/23311975.2023.2264563 This Version is available at: https://hdl.handle.net/10419/294667 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Submit your article to this journal Article views: 367 View related articles View Crossmark data MARKETING | RESEARCH ARTICLE Using conjoint analysis for a value estimation of the consumption attributes of online performances Baek Bo-Hyun 1 * Abstract: Since online performances are new service, consumer confusion is occurring due to the absence of a product composition strategy. Therefore, this study derived the major attributes of online performance and estimates the value of each consumption attribute. As a result, it was found that the optimal combination of online performance products transmits the genre of “ballad” from the “video streaming platform” to “no audience,” and provides “online merchandising” as an additional service. Furthermore, market segmentation using cluster analysis yielded three groups with significant differences, and optimal-performance products are proposed for each type of audience Subjects: Korean Studies; Music; Theatre & Performance Studies; Cultural Studies Keywords: online performance; popular music; conjoint analysis; market segmentation, K-Pop 1. Introduction Since COVID-19, the scope of performing arts has been expanded from offline to online. Traditionally, a performance is a field art in which the performer and the audience interact in the same time and space (Osipovich, 2006). However, a high probability of contact between the performer and the audience during a performance makes individuals vulnerable to infectious diseases in pandemic circumstances. Therefore, on-site performances were canceled or postponed worldwide, and online performances emerged as a new alternative to revitalize the popular music industry (Swarbrick et al., 2021). Online performances are digital content-transmitting performance videos via online platforms involving no direct contact between performers and audiences. The production costs of online performances are lower than the expenses required for offline concerts, and performance agencies bear a lower risk of uncertain earnings. Online performances are also highly profitable because there is no space—time constraint, and they can accommodate unlimited audience numbers (Kim & Na, 2020). Additionally, attractive content can be planned through the application of new technologies such as holograms and extended reality (XR), attracting potential audiences in greater numbers by increasing access to performances (De la Vega et al., 2020). However, business personnel working in the popular music industry cannot prepare a specific marketing strategy for online performances because of the rapid digital transformation. Popular music performances generate revenue by offering a collective experience through face-to-face Bo-Hyun, Cogent Business & Management (2023), 10: 2264563 https://doi.org/10.1080/23311975.2023.2264563 Page 1 of 16 Received: 26 February 2023 Accepted: 25 September 2023 *Corresponding author: Baek BoHyun, Department of Entertainment & Arts Management, Korea Soongsil Cyber University 369, Seoul, Republic of Korea E-mail: [email protected] Reviewing editor: Osikhuemhe Okwilagwe, Marketing, Strategy and Innovation, Bournemouth University Faculty of Management: Bournemouth University Business School, UK Additional information is available at the end of the article © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. encounters between performers and audiences. Their conversion into non-interfacing performances requires the delivery of experiences and values beyond simple video streaming. However, online performance products are being experimentally constructed and are causing consumer confusion because of the paucity of research on types of major transmission platforms, forms of additional services, and the presence or absence of audiences (Baek, 2022). For example, strong competition to establish platforms exists because online performance fees represent around 40% of ticket prices. Therefore, unified streaming platforms are not available for every concert, and some performances even appear simultaneously on multiple platforms. In addition, unlike offline concerts that only sell tickets, online concert products are sold in conjunction with a wide variety of additional services, such as light sticks and unreleased videos. Therefore, serious consumer confusion results because the range of ticket pricing is too wide. Therefore, it is necessary to research the marketing strategies regarding the composition and sales of online performance products for the growth of the popular music industry. The research objective is to derive consumer preference attributes for online performances and to propose marketing strategies by segmenting the market. For this purpose, this study seeks to develop the attributes and attribute levels of online performances through expert and consumer surveys based on a literature study and applies the conjoint methodology to examine the utility of each attribute affecting the consumption of online performances. In addition, the present study was aimed at categorizing audience characteristics through market segmentation and proposing marketing strategies for online performances optimized for each group. 2. Literature review Traditionally, performances have been addressed in the limited context of offline shows, and studies related to online performances are relatively scant because this concept emerged due to the COVID-19 pandemic. The research on online performances can be classified broadly into the following three categories: substitution—complementation relationship studies, business model case analyses, and empirical investigations of audience experience. First, studies on substitution—complementation relationships may be summarized as follows. Bakhshi and Throsby (2014) and Bakhshi and Whitby (2014) conducted a semi-field experiment addressing live performances to examine whether online performances reduced the attendance of theater-going audiences. They found a positive relationship between the ratios of online and theater ticket reservations and thus rejected the possibility of reduced audience attendance. King (2018) reported a positive correlation between the number of online and offline performances and thus rejected the possibility of audience detraction. Most existing studies have deduced a positive outlook on the relationship between the two performance type (De la Vega et al., 2020; Kim, 2017). Second, the business model case analysis studies may be outlined as follows. Mueser and Vlachos (2018) classified and conceptualized online performance services in terms of aesthetics, consumption, and social dimensions. In addition, Kim and Na (2020) suggested a method of improving the profitability of the online performance business through a case analysis of the Seoul Arts Center in Korea. These studies are significant because they analyzed the current state of the online performance industry but are limited because they merely conducted case analyses without applying verification procedures. Third, empirical studies of the audience experiences of online performance are as follows. Swarbrick et al. (2021) reported that audience immersion increased when the artist mentioned COVID-19 during the performance or when a sad song was played. However, the online concert format (live or recorded) was not found to affect the viewing experience. Furthermore, Onderdijk et al. (2021) experimental study used different settings for the voting element, viewing device, and platform type to identify the composition of online performances Bo-Hyun, Cogent Business & Management (2023), 10: 2264563 https://doi.org/10.1080/23311975.2023.2264563 Page 2 of 16 that increased social connection and sense of presence. It found no effect of the voting element but discovered a difference in psychological experience of the audience depending on the viewing device and platform type. To summarize previous studies related to online performances, varied case studies have been conducted based on the prospect that the online—offline performance industry would coevolve. In addition, diverse experimental studies have been conducted recently to maximize the viewing experience of consumers. These studies have experimented with the use of discrete variables, such as voting elements, viewing devices, platform types, and transmission formats. The limitation that the interaction between selection-related properties cannot be identified is presented in this context (Rao, 2014). Therefore, the attributes and attribute levels that online performance consumers consider important when selecting content must be derived, and based on them, a conjoint analysis must be conducted targeting respondents experienced in watching online performances. Thus far, studies that derived the preferred attributes of offline performances have been conducted by Gang and Jin (2015), Park and Petrick (2016), Kim et al. (2018), and Ryu (2020). However, the selection-related attributes of offline performances are expected to significantly differ from those of online performances, which form the scope of the present study. 3. Methods This study used a mixed research design that sequentially applies qualitative and quantitative research methods. First, in the qualitative research stage, open-ended survey was conducted on 20 consumers and 10 experts, respectively. In the quantitative research stage, 324 consumers were surveyed on the main attributes and attribute levels of the confirmed online performance. The consumer groups that conducted open and closed surveys consisted of different respondents. 3.1. Selection of attributes and attribute levels This study was aimed at deriving the selection-related attributes and attribute levels of online performance products. To this end, it conducted an open-ended survey on the major attributes that affected the consumption of performances with 20 consumers who had watched online performances. As a result of the consumer survey, nine major selection-related attributes were derived, some of which were not suitable for conjoint analysis. There were items that require vector models to be applied (e.g. image quality, ticket price) or items that are expected to be of absolute high utility (e.g. artist casting). Next, 10 experts were interviewed to select the key attributes to be used for the study because respondents find it difficult to rank too many attributes as the number of survey questions increases. Such difficulties could decrease the reliability of the research results (Green & Srinivasan, 1990; Green et al., 2004). Experts were selected on the basis of the criteria they had accrued over more than 10 years of experience in the popular music industry and were proficient in planning, producing, and distributing online performances. The interviews were conducted from 8 May to 30 May 2022. In sum, the four attributes most agreed upon by 10 experts were derived. The selection-related attributes and attribute levels for online performances were finalized to include genre (dance, ballad, or trot), audience (no audience or with an audience), and merchandising (online merchandising or offline merchandising) as shown in Table 1. 3.2. Questionnaire composition This study utilized the full profile method to present respondents with 36 (3 × 3 × 2 × 2) virtual online performance profiles created using the four stated attributes. A fractional factorial design was utilized because sequencing all profiles could distort consumer responses. To this end, the orthogonal design method was employed to reduce the number of stimuli to a feasible level while Bo-Hyun, Cogent Business & Management (2023), 10: 2264563 https://doi.org/10.1080/23311975.2023.2264563 Page 3 of 16 maintaining a state precluding interaction between attributes (Cattin & Wittink, 1982). SPSS 26 was used to exclude unrealistic profiles or to omit profiles with duplicated attribute combinations. Ultimately, nine product profiles were constructed as presented in Table 2. 3.3. Investigation and analysis methods The survey subjects were individuals experienced in watching popular music online performances, and convenience sampling was used for their selection. In this study, questionnaires were distributed to 324 people, and all collected responses were used for analysis. SPSS 26.0 was deployed to analyze the consumer response data. First, a frequency analysis was performed to analyze the demographic characteristics of the sample and the online performance consumption behavior. The suitability of the conjoint model used in this study was then verified using Pearson’s R and Kendall’s tau. The importance of the attributes as reported by each respondent and the part-worths and utility for each attribute level were derived through conjoint analysis. Table 1. Attributes and attribute levels for online performances Attributes Attribute level Explanation Genre Dance Music genres with fast rhythms and addictive melodies comprising dance, vocals, and rap Ballad Music genre with slow rhythms and lyrical melodies Trot A music genre comprising quadruple meter patterns and simple melodies Platform Video streaming platform Streaming sites that offer diverse paid and non-paid videos (e.g., YouTube, Netflix) Agency platforms An online arena developed and operated by agencies for communication between their artists and the artist’s fandom (e.g., Weverse for Hive Entertainment) Online concert platforms Sites that operate exclusively to stream online concerts (e.g., Beyond Live) Audience Without an audience Online performances without audiences: these performance videos do not include applause, cheers, and viewing behaviors of audiences With an audience Video adaptations of offline performances for live audiences: such performance videos include applause, cheers, and viewing behaviors of audiences Merchandising Online merchandising Digital merchandising is available for online download and collection (e.g., AR photo exhibitions, unreleased videos, unreleased photos) Offline merchandising Merchandising in the form of collectible products (e.g., light sticks, key rings, t-shirts, masks) Bo-Hyun, Cogent Business & Management (2023), 10: 2264563 https://doi.org/10.1080/23311975.2023.2264563 Page 4 of 16 Next, a non-hierarchical k-means cluster analysis was performed on the constant value estimated from the conjoint analysis and the utility values for 11 attribute levels to derive clusters with significant differences. Finally, cross-analysis was conducted to check whether there were differences in demographic characteristics, offline concert consumption patterns, and online performance viewing experience according to the previously derived clusters. 4. Results 4.1. Demographic characteristics The gender ratio of respondents was similar, with 168 males (51.9%) and 156 females (48.1%). An even age distribution was noted in the study sample: 23 respondents were in their teens (7.1%), 71 were in their 20s (21.9%), 80 were in their 30s (34.7%), 55 were in their 40s (16.7%), 54 were in their 50s (16.7%), 41 were in their 60s and older (12.7%). In terms of occupation of the study sample, office workers were represented by 134 individuals, and this group accounted for the largest proportion (41.4%) of respondents, followed by 51 students (15.7%), 43 housewives (13.3%), 34 self-employed workers (10.5%), 25 professional workers (7.7%), 16 individuals with other occupations (4.9%), 12 part-timers (3.7%), and nine civil servants (2.8%). 4.2. Conjoint analysis result Conjoint analysis was conducted with all 324 respondents, and the obtained results are shown in Table 3. Among the four attributes of online performance products, genre was the most important (53.725%), followed by platform (21.610%), audience (14.233%), and merchandising (10.422%). Regarding the part-worth of the attribute levels for each attribute, for genre, ballad was the highest at 0.726, followed by dance at 0.583. Trot was the lowest at − 1.310. Currently, the most active online concert productions involve the genre of dance, which includes idols. Nonetheless, this study found a higher part-worth for ballads. This outcome may be attributed to the evenly Table 2. Final product profile Card Attribute level Card Attribute level Card 1 Trot Card 2 Trot Agency platform Online concert platforms No audience No audience Online merchandising Offline merchandising Card 3 Ballad Card 4 Ballad Video streaming platform Online concert platforms No audience With audience Offline merchandising Online merchandising Card 5 Ballad Card 6 Dance-pop Agency platform Online concert platforms No audience No audience Online merchandising Online merchandising Card 7 Dance-pop Card 8 Trot Video streaming platform Video streaming platform No audience With audience Online merchandising Online merchandising Card 9 Dance-pop Agency platform With audience Offline merchandising Bo-Hyun, Cogent Business & Management (2023), 10: 2264563 https://doi.org/10.1080/23311975.2023.2264563 Page 5 of 16 distributed age distribution of the study’s respondents, who ranged from teenagers to people in their 60s and older. Conversely, people in their teens and 20s constitute the main consumption age group for idol performances. For platforms, video streaming and online concert sites showed similarly high values of 0.228 and 0.217, respectively. Agency platforms exhibited low part-worth at − 0.445. Video streaming platforms, including YouTube and Netflix, denote representative media platforms on which users can view a variety of video content as well as online performances. Hence, viewers display a superior utilization and awareness of these platforms. In addition, such platforms offer discrete advantages, such as systematic fees, and prevent overloads during simultaneous connections by building large-capacity servers and owning distributed technology. However, live subtitles for each language, a chat function with artists, a multi-view selection function, light stick Bluetooth functions, and other services required for online concert viewing are installed on the online concert-only platforms (Song, 2021). It appears that the part-worth of the online concert platforms was as high as that of video streaming platforms for this reason. A low partial value would have been assigned for agency platforms developed and operated by specific groups because of the conversion costs arising from the difficulties of viewing performances delivered by artists from other agencies (Baek, 2022). For the audience parameter, the part-worth of performances without an audience was high at 0.135, and the part-worth of concerts with an audience was − 0.135. This result aligns with the outcomes reported by Hong and Kim (2021), Swarbrick et al. (2021), Onderdijk et al. (2021), and Baek (2022), where they have suggested that viewers find it difficult to focus on performances with audiences because of the audible applause, cheers, singalongs, or fan chants from the live audience. Further, performances with audiences were much consumed because such videos were filmed for archiving before COVID-19 and were released at the early stages of social distancing. Producers have found it impossible to attract audiences recently. Therefore, most performances are currently broadcast online without audiences, and respondents are now familiarized with performances without audiences. The measure of the element of merchandising revealed that the part-worth of online merchandising was high at 0.038, and the part-worth of offline merchandising was − 0.038. Merchandisingbased sales account for a large percentage of revenue in the popular music performance market. Limited amounts of merchandising products were sold on the days when offline concerts were Table 3. Part-worth and utility of online performance attribute level Attribute Attribute level Part-worth (A) Importance (B) Utility (C=A*B) Genre Dance 0.583 53.725 0.313 Ballad 0.726 0.390 Trot −1.310 −0.704 Platform Video streaming platform 0.228 21.610 0.049 Agency platform −0.445 −0.096 Online concert platforms 0.217 0.047 Audience No audience 0.1355 14.223 0.019 With audience −0.135 −0.019 Merchandising Online merchandising 0.038 10.442 0.004 Offline merchandising −0.038 −0.004 Bo-Hyun, Cogent Business & Management (2023), 10: 2264563 https://doi.org/10.1080/23311975.2023.2264563 Page 6 of 16 held and primarily comprised light sticks, keyrings, pouches, and other such goods (Nurunnisha et al., 2021). However, wallpapers, unreleased photographs and videos, and emoticons have appeared as merchandise sold during online performances, increasing the influence of the online merchandising market (Jeong & Kim, 2020). Therefore, the preference for online merchandising is adjudged higher than the inclination for offline merchandising. The study also verified the suitability of the applied conjoint model. Pearson’s R denotes the correlation value between the utility denominations obtained from an estimated model and the profile rank, and the larger this value the higher the explanatory power of the model (Hauser & Rao, 2004). Kendall’s Tau is a value indicating the correlation between the rank obtained by evaluating the profile with the developed model and the rank actually marked by the respondent (Rao, 2014). The data are deemed unreliable if this value is negative. The analyses performed for this study revealed Pearson’s R-value of 0.995 (p < 0.000) and Kendall’s Tau value of 0.944 (p < 0.000), confirming the model’s suitability. Finally, utility was calculated using the part-worth of each attribute and attribute level to derive the optimal product conditions for the delivery of online performance to consumers. This analysis disclosed that viewers of online performances on video streaming platforms most preferred the transmission of ballad performances without audiences and favored the distribution of online merchandising. 4.3. Market segmentation using cluster analysis The importance of an attribute on selecting online performances varies by individual. Therefore, a k-means cluster analysis was performed for this study using the utility values of individual selection-related attributes derived from conjoint analysis as variables. K-means is a representative cluster analysis method that sets the object that best expresses the characteristics of the group and forms a cluster in a way that includes one object close to it (Lee, 2015). In conclusion, three clusters with significant differences were derived. The findings revealed that all three groups considered the attribute of genre to be paramount, followed by platform, audience, and merchandising. Table 4 displays the attribute positions assigned by each group and the partworth of the attribute level. Pearson’s R was 0.9 or higher, confirming the model suitability apropos all groups. Group 1 comprised 96 people and accounted for 29.62% of the total market. Group 1 exhibited a high preference for the trot genre at 1.191, online concert platform at 0.517, performances without audiences at 0.536, and offline merchandising at 0.208. Group 1 was deemed the group desiring to immerse itself in listening to music and watching videos because unlike the other groups, they favored online concert platforms without audiences. Group 2 included 91 people and represented 28.08% of the total market. Group 2 was highly inclined toward ballads at 2.421, video streaming platforms at 0.601, performances without audiences at 0.044, and online merchandising at 0.195. Just as Group 1, Group 2 fancied performances without audiences, but it was more inclined toward video streaming platforms. In addition, this group favored online merchandising. Group 3 encompassed 137 people and accounted for 42.28% of the total market. Group 3 displayed a high preference for the dance genre at 2.579, video streaming platform at 0.388, performances with audiences at 0.086, and online merchandising at 0.106. Just as Group 2, Group 3 preferred the video streaming platform, but it was the only group attracted to performances with audiences. This group was also partial to online merchandising. The demographic characteristics and viewing frequencies of the segmented markets were analyzed to identify the characteristics of each group with more clarity. Table 5 presents these results. Bo-Hyun, Cogent Business & Management (2023), 10: 2264563 https://doi.org/10.1080/23311975.2023.2264563 Page 7 of 16 A low percentage of Group 2 members belonged to fandoms, and 38.5% of them considered the cast as a consumption determinant, a figure lower than that of members of Groups 1 and 3. Additionally, this group evaluated performance (15.4%) and price discounts (11%) as more important than the other groups did. It is thus presumed that this group represents viewers who like to consume inexpensive performances with good reviews, as well as varied events, rather than watch performances by specific artists as fans. Therefore, if Group 1 were to be served as the main customer group, it would be effective to cast artists well-liked by all genders and ages and recognized for their singing abilities and qualities as artists. Varied event planning is also suggested. Third, Group 3 signified youth in their teens and 30s and was composed mainly of students and office workers. This group reported overwhelmingly high fandom membership and activity rate. Therefore, promoting online performances on fandom platforms operated by entertainment companies (such as Hive’s Weverse) along with social media marketing would exert maximal impact on this cohort. In addition, the members of Group 3 were highly price-sensitive because they were in their teens and 20s. Therefore, it would be effective to subdivide the merchandising into diverse products across various price spectrums. Finally, Group 3 preferred performances with audiences and indicated that online performances would be enhanced through interactions between artists and audiences. People who experience a sense of belonging and interaction tend to cooperate and bond more than those who do not (Kurtin et al., 2019). Therefore, online concerts are not events where they can merely watch performances or listen to music. Rather, such events tend to become meeting places for the members of Group 3, at which they can communicate with the artists and other audience members. Therefore, a service strategy that promotes interaction is mandated when online performances target Group 3. Based on these characteristics, in this study, Group 3 is defined as artist-oriented groups. Despite the usual considerable distance between the audience and the stage at offline performances, physical proximity exists because audiences and the artists exist in the same space and time. However, the same cannot be said of online performances. Therefore, a make-believe strategy that can replace this sense of physical distance with a sense of psychological distance is needed. For example, self-camera content from artists, video call tickets, backstage introductions, and other such tactics, may be deployed. Virtual settings can also be introduced, for instance, a housewarming or a dating situation. Further, online performances with audiences could be effectively and continuously produced even after the pandemic so that online and offline performances can both be simultaneously promoted. 5. Conclusions While the performance sector of the popular music industry faced a significant crisis due to COVID19, this segment is achieving symbolic results of business expansion through online performances. Therefore, this study examined the important attributes influencing audience decisions in choosing online performances for viewing. In so doing, it aimed to describe an optimal product and to recommend marketing strategies by analyzing the characteristics of each consumer group. The results of the conjoint analysis revealed that audiences evinced a substantial and sequential genre preference for ballads, dances, and trots. The video streaming platform was most preferred because the respondents could view online performances, as well as other types of audiovisual content, in the largest numbers. This preference was followed by online concert and agency platforms. Performances with no audiences were favored more than performances with audiences were, and online merchandising goods were desired over offline products. In sum, the viewers of online performances generally preferred ballad performances without audiences on video streaming platforms, along with the distribution of online goods. Bo-Hyun, Cogent Business & Management (2023), 10: 2264563 https://doi.org/10.1080/23311975.2023.2264563 Page 14 of 16 The market segmentation analysis confirmed the efficacy of offering online performances without audiences on Internet-based concert platforms with offline goods for older and high-income viewer groups (Group 1). The offering of online goods along with performances without audiences delivered on video streaming platforms was found effective for middle-income viewer groups (Group 2) in their 20s and 40s who liked ballads. Finally, young and low-income viewers (Group 3) like dance and would opt for online performances with audiences delivered via video streaming platforms along with digital merchandising goods. It was hence confirmed that discrete consumer segments consuming online performances favored different product attributes and genres. This study offers the following implications. Since online performances represent a relatively new service. Hence, no study has yet investigated preference attributes. According to previous studies, audiences have various needs and preferences in consuming onsite performing arts (Kim et al., 2018). Therefore, it is of academic significance to identify the characteristics of online performances and develop the optimal product composition for each group of audiences. The results of this study help to understand the various choices that consumers make when selecting online performances. However, this study entails the following limitations. There are many genres of popular music, but this study limited its genre-based ambit to trot, ballad, and dance. The market status and consumer characteristics differ for every music genre. Future studies should posit specific marketing strategies for each genre by studying audience experiences and product attributes. Further, this study could not establish a comprehensively diverse list of attributes and attribute levels for online performances because it would be difficult for respondents to evaluate their preferences if the number of product profiles was increased. Therefore, it is necessary for the prospective research initiatives to contemplate attributes and attribute levels not addressed in this study. Also, this study has a limitation in that it used the convenience sampling method. In subsequent studies, a valid sampling method should be used. Finally, since there is no conjoint study on online performances, the results of previous studies and analysis could not be compared and interpreted. Author details Baek Bo-Hyun 1 E-mail: [email protected] ORCID ID: http://orcid.org/0000-0001-9527-3199 1 Department of Entertainment & Arts Management, Korea Soongsil Cyber University, Seoul, Republic of Korea. Disclosure statement No potential conflict of interest was reported by the author(s). Citation information Cite this article as: Using conjoint analysis for a value estimation of the consumption attributes of online performances, Baek Bo-Hyun, Cogent Business & Management (2023), 10: 2264563. References Baek, B. (2022). A study on strategies to revitalize the popular music industry ecosystem using online performances [PhD Diss]. Chung-Ang University. Bakhshi, H., & Throsby, D. (2014). Digital complements or substitutes? A quasi-field experiment from the Royal National Theatre. Journal of Cultural Economics, 38 (1), 1–8. https://doi.org/10.1007/s10824-013-9201-2 Bakhshi, H., & Whitby, A. (2014). Estimating the impact of live simulcast on theatre attendance: An application to London’s national theatre. National Endowment for Science Technology and the Arts. Byun, S. (2017). A study on the determinants of active seniors in media markets. Journal of Industrial Economics & Business, 30(4), 1525–1544. https://doi. org/10.22558/jieb.2017.08.30.4.1525 Cattin, P., & Wittink, D. R. (1982). Commercial use of conjoint analysis: A survey. Journal of Marketing, 46(3), 44–53. https://doi.org/10.1177/002224298204600308 Colbert, F. (2003). Entrepreneurship and leadership in marketing the arts. International Journal of Arts Management, 6(1), 30–39. De la Vega, P., Suarez-Fernández, S., Boto-García, D., & Prieto-Rodríguez, J. (2020). Playing a play: Online and live performing arts consumers profiles and the role of supply constraints. Journal of Cultural Economics, 44(3), 425–450. https://doi.org/10.1007/s10824-019-09367-y Gang, H., & Jin, H. (2015). Analysis of consumer preferences for content provision and promotion of creative musicals. Journal of Consumption Culture, 18(2), 169–185. https://doi.org/10.17053/jcc.2015.18.2.008 Green, P. E., Krieger, A. M., & Wind, Y. (2004). Thirty years of conjoint analysis: Reflections and prospects. In Intern ational series in quantitative marketing Hauser international series in quantitative marketing (pp. 117–139). Springer. https://doi.org/10.1007/978-0-387-28692-1_6 Green, P. E., & Srinivasan, V. (1990). Conjoint analysis in marketing: New developments with implications for research and practice. Journal of Marketing, 54(4), 3–19. https://doi.org/10.1177/002224299005400402 Hauser, J. R., & Rao, V. R. (2004). Conjoint analysis, related modeling, and applications. In International series in quantitative marketing (pp. 141–168). Springer. https://doi.org/10.1007/978-0-387-28692-1_7 Hong, H., & Kim, K. (2021). User experience study of online concerts – focusing on KPOP online concert case. Journal of Digital Convergence, 19(1), 349–354. Jeong, S., & Kim, S. (2020). A study on ways to expand performance merchandising revenue using online Bo-Hyun, Cogent Business & Management (2023), 10: 2264563 https://doi.org/10.1080/23311975.2023.2264563 Page 15 of 16 platformsfocused on comparison of sales cases of goods and MD. Kim, H. (2017). Strategies for increasing audiences in performance broadcast video: Suggesting strategic task through productivity analysis, audience research, and qualitative discussion [PhD Diss.]. Sungkyunkwan University. Kim, S., Chung, J. Y., Petrick, J., & Park, J. W. (2018). Determination of preferred performing arts tourism products using conjoint analysis. Journal of Vacation Marketing, 24(1), 44–61. https://doi.org/10.1177/ 1356766716679484 Kim, G., & Na, Y. (2020). A study on how to activate online performances through sac on screen business analysis. The Journal of the Korea Contents Association, 20(8), 114–127. Kim, J., & Park, S. (2021). Life history, analysis, and cultural art marketing plan for seniors’ cultural and artistic experiences. Geriatric Education Research, 7 (1), 105–123. King, T. (2018). Streaming from stage to screen: Its place in the cultural marketplace and the implication for UK arts policy. International Journal of Cultural Policy, 24(2), 220–235. https://doi.org/10.1080/10286632. 2016.1150270 Kurtin, K. S., O’Brien, N. F., Roy, D., & Dam, L. (2019). Parasocial relationships with musicians. Journal of Social Media in Society, 8(2), 30–50. Lee, H. (2015). Research methodology by professor HoonYoung Lee. Crbooks. Mueser, D., & Vlachos, P. (2018). Almost like being there? A conceptualisation of live-streaming theatre. International Journal of Event & Festival Management, 9(2), 183–203. https://doi.org/10.1108/ IJEFM-05-2018-0030 Nurunnisha, G. A., Setiawan, D. W., Wijayanti, F., & Sinaga, O. (2021). The effect of product, distribution, and digital marketing toward female’s purchase intention (case study: Bts album on Weverse shop). Review of International Geographical Education Online, 11(7), 3429–3440. Onderdijk, K. E., Swarbrick, D., Van Kerrebroeck, B., Mantei, M., Vuoskoski, J. K., Maes, P.-J., & Leman, M. (2021). Livestream experiments: The role of COVID-19, agency, presence, and social context in facilitating social connectedness. Frontiers in Psychology, 12, 647929. https://doi.org/10.3389/ fpsyg.2021.647929 Osipovich, D. (2006). What is a theatrical performance? The Journal of Aesthetics & Art Criticism, 64(4), 461–470. https://doi.org/10.1111/j.1540-594X.2006. 00224.x Park, C., & Petrick, J. F. (2016). Developing the optimal Korean performing arts tourism product for Japanese tourists. Travel and Tourism Research Association, 16, 1–7. https://scholarworks.umass.edu/ttra/2010/Visual/16/ Rao, V. R. (2014). Applied conjoint analysis. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-54087753-0 Ryu, G. (2020). Development of an optimal performance product model for revitalization of cultural and artistic performances. Productivity Research, 38, 131– 138. https://doi.org/10.36345/KACST.2020.38.1.016 Song, M. (2021). A study on the business model of a fan community platform Weverse. International Journal of Advanced Smart Convergence, 10(4), 172–182. Swarbrick, D., Seibt, B., Grinspun, N., & Vuoskoski, J. K. (2021). Corona concerts: The effect of virtual concert characteristics on social connection and Kama Muta. Frontiers in Psychology, 12, 648448. https://doi.org/ 10.3389/fpsyg.2021.648448 Vandenberg, F., Berghman, M., & Schaap, J. (2021). The ‘lonely raver’: Music livestreams during COVID-19 as a hotline to collective consciousness? European Societies, 23(Suppl 1), S141–S152. https://doi.org/10. 1080/14616696.2020.1818271 Willis, K., & Snowball, J. (2009). Investigating how the attributes of live theatre productions influence consumption choices using conjoint analysis: The example of the national arts festival, South Africa. Journal of Cultural Economics, 33, 167–183. https:// doi.org/10.1007/s10824-009-9097-z Bo-Hyun, Cogent Business & Management (2023), 10: 2264563 https://doi.org/10.1080/23311975.2023.2264563 Page 16 of 16