An Empirical Study on K-Pop Livecast Concerts in Cinema: The Next Best Experience to a Real Live Concert?

Abstract

This study examines participants’ experiences of K-pop livecast concerts, a new phenomenon where audiences watch live-streamed online concerts together in cinemas. The study is in three stages—social media analysis, qualitative interview, and quantitative questionnaire survey—each generates knowledge on the experience in different dimensions. The first two stages lay the foundation for the final test of the service quality model, which illustrates the effect of service quality factors and artist attachment on satisfaction and repurchase intention. The results show that content quality, convenience, and physical interaction affect satisfaction, among which physical interaction has the strongest effect. Fandom is vital in determining repurchase intention regardless of satisfaction with the current livecast concert participation. This study predicts that livecast concerts will enjoy continuous popularity post-COVID-19 and provides practical insights into future strategies for operating and marketing livecast shows.

Keywords

K-pop livecast concert live-streaming concert service quality artist attachment physical interaction

Introduction

South Korean popular music, often called K-pop, emerged in the 1990s, gaining regional success around East Asia in the 2000s and global recognition beyond Asia in the Western market in the 2010s. The success of K-pop is due to (1) the high quality of its product: attractive physical appearance, globally fashionable pop music, and synchronized dance performances, (2) its effective circulation strategy via global social media tools, and (3) its vigorous fandom that consumes and deliberately re-creates and promotes their artists (Boman, 2019; Choi & Maliangkay, 2014; Jung & Shim, 2014; Oh & Park, 2013).

The live performance industry swiftly transitioned online during the COVID-19 pandemic, providing live-streaming for concerts. Due to its convenience and cost-effectiveness, watching live shows on one’s phone or computer remains a common practice throughout the K-pop industry post-COVID. On the other hand, people feel the loss of festivalization and embodied experience of an offline event that online streaming cannot provide (Luo et al., 2022; Shipman & Vogel, 2024). Thus, to improve online concert “liveness,” the industry and consumers are shifting live streams to public venues like cinemas and stadiums. This new phenomenon, named “K-pop livecast concerts” in this study, gathers audiences in public venues to watch an offline concert live stream together, organized by entertainment companies and self-organized by fans.

The concept “livecast,” borrowed from a similar practice in the classical music performance industry, is the combination of “livestream” (i.e., to stream a live event over the Internet) and “broadcast” (i.e., to send or transmit something, such as a program) through radio or television with an inherent sense of “making public” (King, 2018; Van Eeden, 2011). The counterpart in popular music performance had not emerged until recent years as an alternative revenue resource when the pandemic made world tours difficult. Without question, online concerts cannot replicate the irreplaceable experience of “liveness” of offline concerts. Thus, industry and consumers have been experimenting to make online concerts feel more “live” by bringing the streamed online concert into cinemas. In 2020 to 2021, fans in China self-organized group streaming events in cinemas for online concerts of NCT, BTS, etc., thanks to the region’s fast recovery from COVID-19’s first wave. In March 2022, BTS live broadcast their offline concert in Seoul to cinemas in 75 countries and regions worldwide. Other major artists such as “Seventeen,”“The Boyz,”“TXT,”“Twice,” and/or their fans have organized similar events. Beyond audio/video technological advances for online immersion, offline events’ physical and social interaction enhances enjoyment.

This study fills the gap in academic research on this newly emerged concert consumption. Although this study’s research interest derived from a response to COVID-19, this phenomenon is not a mere compromise in the era of travel restrictions and social distancing. Given global music distribution and live concert scarcity, livecast concerts offer a long-term alternative for live performance consumption. For example, in South Korea, even after the government lifted social distancing restrictions on live concerts, fans continued to welcome events such as the “Seventeen World Tour [Be The Sun] – Houston: Live Viewing” and “Boys Planet X CGV Final Live Show on the Theater.” The former event targeted domestic fans unable to see artists on lengthy overseas tours, leading to ticketing issues. This seating scarcity led to fans preferring the live debut of the latter group’s variety show in real-time rather than the recorded versions. These two examples summarize a livecast concert’s crucial characteristics that enable a livecast concert to continue to thrive in the post-COVID era: it stays real-time, overcomes distance, contains more audience, and maintains more liveness of the live event than online concerts streamed on a personal device.

Research Design

The study follows three stages. First, we conducted social media analysis of the videos filmed and uploaded by K-pop livecast concert participants to identify critical stages of the event and elements of participant behavior. Then, a qualitative study interviewing eight livecast concert participants explores how they perceive and articulate their experiences, motivations, values, etc. In this stage, we included a diverse range of similar experiences, such as watching recorded concert films in the cinema, to compare the level of liveness of these experiences. Finally, we surveyed those with experience in K-pop livecast concerts (real-time only) to examine the relationship between service quality factors, perceived value, satisfaction, and repurchase intention.

The study design of each of the three stages included a different approach to this new phenomenon. This study explores the subject by initially examining the subject’s video archive. We also ask participants guided open questions, minimizing bias resulting from the researcher’s preconceptions. After that, a quantitative modeling and testing stage investigates the broader applicability of insights acquired from qualitative analyses and converts them into a predictive model that can aid practical service management. Though each of the three stages generates knowledge regarding different dimensions of an experience, we used the knowledge gained in previous stages to improve the study design of later stages. The sequence of stages avoids the problem of indiscriminately applying unsuitable theoretical models to real-world phenomena. The following sections introduce each stage’s purpose, method, results, and discussion.

Stage 1: Social Media Analysis

Purpose

Stage 1 analyzed videos uploaded by participants on social media after attending K-pop livecast concerts. This analysis aimed to (1) provide a general understanding of K-pop livecast concerts and the event’s critical stages, (2) inform which stages of the experience are meaningful or valuable to the participant by identifying which parts they chose to record, edit, upload, and share on social media, and (3) identify potential interviewees for the study’s next stage.

Method

We selected three major social media sites or online video platforms as a sample pool: Bilibili (China), YouTube, and Twitter (global). We selected video works as follows: (1) videos under search words of major K-pop livecast concerts (“BTS Live Viewing,”“NCT Beyond Live Offline Gathering,” etc.) as subjects of the analysis, and (2) when we selected one video, we also examined relevant videos recommended by the platform’s algorithm. We repeated the above two steps until we reached theoretical saturation.

We collected basic information to analyze videos, such as the platform, artist, date, place, venue type (cinema, private cinema, etc.), audience size, official or fan-organized, video duration, and video structure. The researcher coded the participants’ behaviors in the video into categories, simultaneously and iteratively collecting and analyzing data (Bassett, 2010) by re-examining previously analyzed videos when adding new categories inspired by videos analyzed later. Altogether, the researchers analyzed 40 videos.

Stage 1 Results

Among the 40 videos analyzed, 31 were fan-organized events where fans negotiated block screenings with local cinemas to play official online live-streaming concert content originally provided via personal devices, with audience sizes ranging from 20 to 200+. Most happened in mainland China, as there have been no official events until now. Four were official livecast concerts ticketed by entertainment companies in contracted cinemas, and five were small-scale private gatherings among three to five close friends. Most clips are unedited or slightly edited with subtitles and comments.

The researchers observed selective uploading, with participants tending to upload clips with the highest excitement (e.g., lots of screaming) and group behaviors (e.g., chanting and cheering in unison with the lyrics, waving the cheering light sticks with the rhythm). The clips often included songs with special meaning to the fandom.

The researchers coded participants’ behaviors in the videos into the following categories: commenting on the concert with a nearby audience, screaming, chanting, cheering, waving light sticks, taking videos with a phone, answering the artists, and complaining about content editing quality and streaming quality. Two significant results are as follows.

Capture the Moment and Ease of Filming

Despite the artist’s physical absence, many still filmed the artist on the screen and the audience’s reactions. This pervasive filming shows participants are comfortable recording with their phones during livecast concerts, unlike offline concerts where filming is often restricted.

Audience’s Behaviors as a Kind of Performance

At livecast concerts, audiences did not just watch the screen; they also noted others’ reactions, reflected in the selective filming and uploading clips with captivating audience reactions. Furthermore, knowing that different audiences and clip viewers would watch their response, the audience sometimes reacted more dramatically or intentionally made interesting comments. In many situations, the audience replied to the artist in unison despite the artist’s physical absence. We regard this as a kind of collective self-performance. Audiences of small-scale events tended to feel more at ease and thus shared more comments.

Stage 1 Discussion

The critical stages and audience behaviors in a livecast concert identified from the social media analysis stage helped the researcher draft the interview guiding questions and questionnaire survey items in the following stages.

Stage 2: Qualitative Analysis: Interview

Purpose

The aim of the interview stage is (1) to understand the participants’ motivations, emotions, and behaviors in their experiences of K-pop livecast concerts, which are difficult to collect in a quantitative questionnaire survey, and (2) to inspire the generation and revision of survey items for the next stage, focusing on interaction and connectedness in livecast concerts.

Method

Sampling and Data Collection

We used judgmental sampling and the snowball method until reaching theoretical saturation for interviewee sampling (Hume et al., 2006). The selection criteria included: (1) The interviewee needs experience attending real-time livecast or recorded concerts. The latter helps understand livecast concert uniqueness. (2) To attain the best-randomized sample, we considered the diversity of artists and place of attendance. (3) We included events before, during, and after COVID-19 restrictive measures to capture the pandemic’s influence on participants’ expectations, consumption patterns, etc. Table 1 depicts the interviewees’ basic information.

Table 1.

Basic Information of Interviewees.

No.	Age	Artist	Type	Place	Price	Time	Audience size
M0 (self)	25–30	BTS, SHINee	Official, real-time, and concert film	Seoul, Korea	Unknown	2022	200
M1	25–30	NCT 127, SHINee	Fan-organized, real-time	Shanghai, China	15 USD (100 CNY)	2021	<100
M2	25–30	NCT 127	Fan-organized, real-time	Wuhan, China	10 USD (68 CNY)	2021	200
M3	18–24	Seventeen	Official, concert film	Davao, Philippines	15 USD (800)	2022	400
M4	18–24	Taemin (SHINee)	Official, concert film	Seoul, Korea	15 USD (19,000 KRW)	2019	<1,000
M5	25–30	BTS	Official, real-time	Seoul, Korea	21 USD (28,000 KRW)	2019	Unknown
M6	18–24	BTS	Official, concert film	Hong Kong, China	Unknown	2019	Unknown
M7	18–24	BTS	Official, concert film	Philadelphia, USA	15 USD	2019	30–40
M8	18–24	BTS	Official, real-time	Paris, France	20 USD (20 EUR)	2022	400
M9	18–24	BTS	Official, real-time	Montpellier, France	20 USD (20 EUR)	2022	100

We conducted interviews face-to-face, via online video call, or by online text exchange. We transcribed all face-to-face and Zoom call records into text transcripts and saved online text exchange records in their original form. All subjects completed an online form providing written informed consent before the interview. We anonymized identifying information to ensure participant safety and privacy.

Structure of Interview

We conducted semi-structured interviews that included open discussion and guided questions. The interviews began with a non-structured free discussion of the interviewee’s experience of the last K-pop livecast concert they attended. We invited interviewees to share videos or photos shot on-site to help them address the experience (Mencarelli, 2008). Following this, we asked more structured open questions on motivation, satisfaction, perceived value, and re-attend intention. Then, we collected recreational habits and demographic information and asked interviewees to assess the livecast concert’s “liveness” and identify contributing factors. We only addressed the theoretical construct of “liveness” and compared the livecast concerts to other types of live performances until the end of the interview, as an early introduction of the construct may have led the respondents to contemplate the experience in terms of the prescriptive binary of live/non-live (Reason, 2006, p. 221).

Stage 2 Results

The interview results revealed the existing audience’s motivations and potential audience’s characteristics. We coded the results into the following themes: (1) motivation, (2) preference for watching livecast in cinemas over watching on personal devices, (3) a convenient and easy-to-enter option to enjoy the concert, (4) the social need of “going with friends” and suitable price for inviting friends, and (5) greater interest in offline events after COVID-19.

Motivation

The most common motivation for attending a livecast concert is “not wanting to miss out on anything about the artist” (M3–M5, M7–M9). From a fan’s perspective, every content related to the artist is unique and thus becomes a must-see. Fans even regard each day of a concert series of several days as a new and memorable event. Age (M1) and level of fan attachment to the artist (M7) influence this motivation’s intensity. It also varies according to whether the livecast is real-time and non-repetitive (M6, M8–M9) or if the setlist is unique or only available on this day (M8). The one-off, perishable characteristic of arts and cultural services can explain this influence. Entertainment companies deliberately manipulate this psychology using an “in cinemas only” strategy, offering one concert day exclusively in cinemas and not on personal devices to attract online audiences to cinemas.

Participants reported that one could not compare the livecast experience to the experience at an authentic offline concert, making them anticipate original offline concerts even more (M3, M8). However, budget, schedule, and difficulty in ticketing prohibit attending offline concerts. Thus, livecast is a cost-effective yet compromising option with sometimes lower prices than online, but still retains much of the live performance vibe (M8–M9). Even if participants attended an offline concert day, watching a livecast concert was worth it. It allowed fans to watch another day of the concert series, a unique event they would not want to miss (M4, M5). Sometimes, the innovative form of livecast also serves as an attractive point (M7–M8).

To summarize, the livecast concert never competes with an offline concert for the audience. Yet, it may be an attractive second choice when offline concerts are not available or accessible.

Preference for Watching Livecast in Cinemas Over Watching on Personal Devices

While online streaming may be restricted on livecast event days to increase ticket sales, interviews indicated most preferred cinema livecasts over personal devices when both options were available (M1–M2, M4–M9). Some would still watch the online concert but preferred cinemas if livecasts were an option (M1, M7, M9). One respondent said that if not for the new livecast form, she would not watch the online concert because she has watched the same setlist online too many times (M8). This preference is due to the following aspects of a livecast concert.

• Cinema Facilities. The large screen, surround sound effects, and smooth internet connection make the experience more immersive and thus more satisfactory (M3–M7). However, when technical problems impacted the smooth live streaming at the cinema, it also constituted a dissatisfactory aspect (M2, M5–M6).

• The Lively Atmosphere of a Collective Event. Collective behaviors (e.g., waving light sticks, screaming, cheering, and chanting) create a livelier vibe. When seeing other audience members’ reactions, one’s mood may elevate at a livecast concert (M1, M5, M8–M9).

• Sense of Belonging. Many informants emphasized “being able to watch with fellow fans” as a key satisfaction factor in livecast concerts (M3, M4, M6), stressing the importance of shared experiences with like-minded fans.

The above indicates that the livecast concert has a strong potential to develop an audience from those who previously watched online shows on personal devices.

A Convenient and Easy-to-Enter Option to Enjoy the Concert

Although the livecast concert is a new service form, the interviews found that it does not create barriers to entry for newcomers.

• Trust and Familiarity with the Cinema Setting. Since the cinema is a popular recreational venue familiar to most people, trust in cinema facilities and familiarity with the cinema’s overall setting reduces worries about potential dissatisfactory encounters (M7, M9).

• Ticket Price. The price of a livecast concert is similar to or slightly higher than a regular movie ticket, which does not require too much deliberation about the purchase decision (M7–M9).

• Less Time and Effort. Compared to attending an offline concert, the livecast option saves time and effort in ticketing, transportation, and pre-event procedures (M5).

The convenience of going to a livecast concert may cater to audiences with relatively inflexible schedules (e.g., due to working hours), limited mobility (due to age), tight budgets, or those who prefer less complexity. Informants reported relevant evidence, such as observing women in their 50s (M0) and many office workers (M5) during livecast concerts. Audience distribution data on ticketing sites (Table 2) supports this speculation. Comparing the data of the same concert watched in cinemas and offline live venues, audiences in their 30s remain the largest buying group for cinemas. In contrast, those in their 40s and 50s prefer livecast concerts, while audiences under 30 choose offline concerts.

Table 2.

Audience Distribution Data: Livecast Versus Offline Concert.

Concert name	Type	Audience age
Concert name	Type	10–20	20–30	30–40	40–50	50+
BTS Permission to Dance on Stage—Seoul (2022)	Livecast	3.3	20	36.1	30.3	10.3
BTS Permission to Dance on Stage—Seoul (2022)	Offline	11.4	30.2	35.7	17.7	4.6
Love Yourself: Speak Yourself [The Final] (2019)	Livecast	3.7	30.2	34.5	27	4.8
Love Yourself: Speak Yourself [The Final] (2019)	Offline	27.1	35.9	25.3	10	1.5

Note. Audience distribution data are open data acquired from CGV and Interpark’s official site.

The Social Need of “Going With Friends” and Suitable Price for Inviting Friends

Six out of nine informants (M1–M3, M5–M6, M7–M8) went to the livecast concert with a personal friend. In addition, six out of nine (M1–M2, M4–M6, M8–M9) preferred a companion when participating in fandom gatherings or concerts, while only one preferred going alone. Some even regarded having a companion as a must, inviting a non-fan friend as a companion, or accompanying a friend even if they were not a fan (M1–M2). This finding shows that social needs are central to audience motivation to go to a livecast concert.

Meanwhile, the current price level of a livecast concert ticket is suitable for fans to invite non-fan companions to go with them. The ticket price of a livecast concert is similar, or slightly higher than a regular movie ticket, while predominantly lower than an offline concert (taking into consideration resale fees when ticketing is difficult). This approach may reduce the audience’s insecurity of going alone while attracting new audiences and increasing revenue.

Livecast Concerts in the Post-pandemic Era: Greater Interest in Offline Events After COVID-19

The informants’ testimonies suggest that the pandemic intensified their fear of missing out on events related to the artist, leading to patterns of revenge consumption (M4–M6). Audiences want more options within a reasonable budget and time from which to choose the most and varied content (as each day among a series of concerts is a different concert, even with a fixed setlist) rather than selecting between competitive options (online at home/online in cinemas/offline, real-time/recorded concert films), which presupposes that the audience can only go to one show. Moreover, the audience may be more interested in offline events after the long stay-at-home pandemic era (M2), making the livecast option a strong competitor for online concert audiences.

Therefore, the livecast concert could remain popular post-pandemic, not just as a temporary fix but as a preferred choice due to ongoing barriers like scheduling conflicts, tight budgets, and ticketing difficulties. Moreover, the draw of the communal atmosphere and interactions at livecast events may increase appeal in the post-pandemic era, attracting more online viewers.

Stage 2 Discussion

From the audience’s perspective, the livecast concert can serve as the “next best option” for an offline concert. However, it cannot substitute for the offline concert due to the non-reproducibility of an authentic offline experience with the artist “right here, right now.” Regardless, it might be better than online streaming because it is convenient and accessible while providing a livelier atmosphere and a sense of belonging than streaming online concerts on personal devices. From the service provider’s perspective, the reasonable price, accessibility, and lively atmosphere of the livecast concert may attract a wider audience and thus generate greater overall revenue. These interview results helped inform the survey items generation in the next stage.

Stage 3: Quantitative Analysis: Questionnaire Survey

Purpose

This stage developed the findings from the previous steps into questionnaire survey items and distributed the questionnaire to livecast concert participants. We used the collected data in quantitative analysis. The advantage of the questionnaire survey is in reaching a broader and more diverse group of participants. Thus, this stage tested whether findings from previous stages apply to the general participants of livecast concerts. It also conceptualizes qualitative insights into measurable factors and develops a predictive model of consumer repurchase for practical application in service design.

Conceptual Development and Hypotheses Development

Service Quality Model

Given their hybrid nature, we examined extant studies on online and offline live performances to find a model explaining consumer purchase behavior at livecast concerts. Hume et al. (2006) and Hume (2008) developed the core/peripheral service quality (SQ) model for performing arts. Hume suggests that consumers base their repurchase intention (RI) on core and peripheral SQ, highlighting the need for a strategic balance between the two in service design and delivery to maximize RI. Furthermore, perceived value (PV) and customer satisfaction (CS) mediate SQ’s influence on RI.

The present study adopted Hume’s SQ model for performing arts, considering it a well-tested model and a similar subject to this study. However, we made a few changes based on Hume’s original SQ model. Enlightened by previous literature and this study’s stages, we redesigned SQ factors, specifying four categories: content, convenience, technology, and interaction. We also added “artist attachment” as another independent variable. We extracted CS and PV as one factor in factor analysis and relabeled it as “consumer satisfaction.”Figure 1 illustrates this study’s research model.

Figure 1.

Proposed research model.

Consumer Satisfaction and Perceived Value

Consumer satisfaction (CS) measures how well service performance meets expectations, while perceived value (PV) reflects the benefits customers receive for the service’s price. The price includes money, time, and effort to participate in the activity. Previous research has found that PV has a positive and direct relationship with CS and that CS mediates the relationship between PV and RI (Hume, 2008).

In this study, though the survey asked about CS and PV items, in factor analysis, items under CS and PV load on one single factor. As previous studies suggest, CS and PV are complementary but distinct constructs, the main difference being that CS is an affective construct, while PV is cognitive (Eggert & Ulaga, 2002). However, as livecast concerts are recent and most participants have only attended once, we speculate they are unfamiliar with the service’s standards (price, time, effort), limiting their ability to assess costs and benefits. Also, participants in K-pop fandom-related activities are more likely to perceive experiences affectively. Therefore, participants likely have not distinguished cognitive and affective items but have treated all items as affective when answering the survey. This assumption is consistent with previous research that affective SQ is a stronger predictor of first-timers’ RI. In comparison, cognitive PV is the stronger predictor of repeat intent (Petrick & Backman, 2002). Based on this evidence, we only incorporated CS in the final model, considering all six items contributing to CS in livecast concert participation.

Repurchase Intention

RI reflects the individual’s decision to repurchase a service (Hume, 2008). This study split RI items into two categories—RI for livecast concerts of one’s favorite artist and other artists—to control for fandom influence. Also, considering participants might regard livecast concerts as a compromise when live concerts are unavailable, the survey explored their RI after lifting COVID-19 restrictions. Furthermore, pre-survey interviews reveal that participants see livecast concerts not as live concert substitutes but as alternatives to streaming concerts on devices, leading the survey to explore RI when self-streaming is an option. Thus, the study proposes the following primary hypotheses:

H₁: Service quality (SQ) factors positively affect consumer satisfaction (CS).

H₂: SQ factors positively affect repurchase intention (RI).

H₃: CS mediates the relationship between SQ factors and RI.

H₄: CS positively affects RI.

The following sections explain the conceptual development of each independent variable in detail.

Service Quality Factors

Hume et al. (2006) and Hume (2008) proposed that performance art is a special service, thus developing and validating a scale for measuring performing arts’ core and peripheral SQ. Core SQ refers to the quality of the act/show, while peripheral SQ measures physical evidence, service, and contact interactions. Studies on online live performance usually specify four SQ factors: content quality, convenience, interaction, and technology. Studies utilizing this model include S.-E. Kim and Kim (2021) on online musicals and S.-K. Kim and Limb (2020) on classic livestreaming performances. This study applies the core/peripheral division and the four SQ factors to livecast concerts, which bring online concert content to cinemas. Interview informants highlighted all four factors as crucial to their attitude toward livecast concerts, leading us to revise factor-based survey items to reflect livecast concerts’ unique characteristics.

Content Quality

Hume’s (2008) core SQ of a performance art experience refers to “the act (storyline) and actors, the theatre including the lighting, stage settings, audio and music” (p. 352). For online concerts, all mentioned elements are via Internet streaming service as video content, making “content quality” the core SQ factor, referring to the streamed video (content) quality. Unlike live performance arts viewed from a single angle, online concerts offer edited videos with multiple angles, significantly influencing the audience’s experience through angle selection. Considering this, the researchers added items measuring the quality of videography and editing (S.-E. Kim & Kim, 2021; S.-K. Kim & Limb, 2020). In the case of livecast concerts, as the video content streamed on screen is the same on personal devices, this study used the items of the “content quality” factor in online concerts.

H_1-1: Content quality positively affects consumer satisfaction (CS).

H_2-1: Content quality positively affects repurchase intention (RI).

H_3-1: CS mediates the relationship between content quality and RI.

Convenience (Offline Peripheral Quality)

Convenience, a peripheral SQ aspect offline, measures whether consumers easily navigate the whole service interaction, including ticketing, getting to the venue, and facility use before, during, and after the performance. Survey items asked about the quality of seating, cinema facilities, transportation, service personnel, ticketing, accessibility, and time consumption (Hong & Kim, 2020; Hume, 2008; S.-E. Kim & Kim, 2021; S.-K. Kim & Limb, 2020).

H_1-2: Convenience positively affects consumer satisfaction (CS).

H_2-2: Convenience positively affects repurchase intention (RI).

H_3-2: CS mediates the relationship between convenience and RI.

Technology (Online Peripheral Quality)

Technology, here referring to information technology (IT), is the online aspect of peripheral SQ. Researchers view technology—not a factor in offline performances—as crucial for online livestreams, focusing on Internet connectivity and audio–video quality (H. S. Kim, 2018; S.-E. Kim & Kim, 2021; S.-K. Kim & Limb, 2020). In livecast concerts, technology is key for smooth Internet streaming and high-quality cinema audio–video, offering a better experience than personal device streaming.

H_1-3: Technology positively affects consumer satisfaction (CS).

H_2-3: Technology positively affects repurchase intention (RI).

H_3-3: CS mediates the relationship between technology and RI.

Physical Interaction

Despite abundant theory on “liveness,” there is no empirical evidence on audience perception or measurement attempts. This interaction differs from interactions with service personnel in peripheral SQ. Interaction matters only for online and livecast performances, not real live ones, necessitating the reproduction of the connection felt at offline live performances. Online live performances reproduce interactions through special interactive segments or real-time chats on the livestream platform (S.-E. Kim & Kim, 2021; S.-K. Kim & Limb, 2020). However, livecast concerts lose livestream and device interactivity since audiences watch in cinemas. Therefore, being in a public venue like a cinema could recreate the live concert’s liveness and connectedness. Thus, this study’s main task is to identify which livecast concert elements replicate this interaction.

Studies in the COVID-19 era have primarily explored the “mediated liveness” in online concerts. For example, Park (2021) proposed evaluating “liveness” in three dimensions: temporal simultaneity, spatial co-presence, and audience. The real-time online concert in the COVID-19 era is a more “live” option than the recorded concert due to the additional “temporal simultaneity.” In addition, the livecast concert adds an “audience” for more liveness. Chie (2016a, 2016b) proposed that the unique “liveness” of livecast theater lies in four dimensions: real-time, spatial presence, vicarious live experience (seeing the live audience’s reactions), and audience interaction (sharing livecast theater experience among a livecast audience). Luo et al. (2022) highlighted the unique embodied experience of offline pop concerts, including emotional release, bodily presence, body sync, and immersion, guiding this study’s design to measure livecast concert interaction.

Based on the results from stages 1 (media analysis) and 2 (interview), we extracted “being able to scream, chant and sing along with other audiences,”“being able to see the reactions of other audiences and enjoy it,”“being able to exchange thoughts with friends sitting next to me,”“lighting stick synchronization,” and “feeling connected with the audience at the same cinema” as categories of a livecast concert’s interactive aspects.

H_1-4: Physical interaction positively affects consumer satisfaction (CS).

H_2-4: Physical interaction positively affects repurchase intent (RI).

H_3-4: CS mediates the relationship between physical interaction and RI.

Artist Attachment

Motivated by evidence and practicality, we included artist attachment as an independent factor that “serves to describe the strength of the target-specific emotional bond connecting the consumer with the human brand (i.e., idol)” (Huang et al., 2015, p. 1235). Many interviewees referred to the level of artist attachment to explain their or their companions’ livecast concert enjoyment. Also, adding this factor is important for gaining insights into future audience development of K-pop livecast concerts. Lower ticket prices for livecast concerts versus offline concerts may make purchasing easier for fans with weaker artist attachments, benefiting service providers’ revenue. Measuring the artist attachment’s link to CS and RI helps determine how audience development should address varying artist attachment levels.

This study adopted the “artist attachment” scale from Huang et al. (2015) with three indicators: separation distress, brand-self connection, and prominence. Previous studies have shown that higher attachment levels lead to higher human brand loyalty (Huang et al., 2015) and behavioral intentions such as purchasing related goods and visiting or recommending relevant tourist destinations (Wong & Lai, 2015; Yhee et al., 2021). Thus, this study hypothesizes that “artist attachment” will affect (re)purchase intentions toward livecast concerts.

H₅: Artist attachment positively affects consumer satisfaction (CS).

H₆: Artist attachment positively affects repurchase intention (RI).

H₇: CS mediates the relationship between artist attachment and RI.

Method

Sample and Data Collection

We collected responses from Chinese-speaking K-pop consumers who had participated in at least one livecast concert. Due to COVID-19 travel restrictions, we chose Chinese consumers because Chinese fans are among the most active groups rigorously organizing livecast events in different cities. Also, Chinese-speaking consumers were the most approachable group for the researcher.

Data collection was via a convenience sampling method from November 11, 2022, to April 19, 2023. We converted the questionnaire into an online form for easy distribution, opening the link on November 11 and sharing it via the researcher’s social media account and several fandom group chats. After collecting the first bundle of data until November 14, we set the questionnaire to a constant “open” mode and deliberately distributed it to participants of livecast concerts that happened after that date, including “The B-Road: 2022 The Boyz Fan Con” (December 3, 2022), “Le Sserafim Fan Meeting ‘Fearnada’ 2023 S/S” (March 20, 2023), “TXT World Tour Act Sweet Mirage. Act: Sweet Mirage” (March 25, 2023), and “Twice 5th World Tour ‘Ready To Be’” (April 15, 2023). This approach ensured that responses came from actual participants of livecast concerts. We distributed the questionnaire online via fan club influencer accounts and offline at the cinema; we collected 329 responses and applied quantitative analysis using SPSS Statistics Version 26.

Measures

We categorically collected basic information about experiences on livecast concerts, places, exclusivity, audience size, whether the participant went with a companion, and whether the organizer attended the livecast concert. We used a 5-point Likert scale to measure attachment, all SQ factors, CS, and RI on a scale from strongly disagree (1) to strongly agree (5). The questionnaire included demographic questions regarding gender, age, occupation, and personal monthly income.

Stage 3 Results

Basic Information and Demographic Profile

Table 3 shows the demographic profile of the respondents, the livecast concert participants. Among the 329 respondents, most were women (93.9%), 18 to 24 years old (83.6%), students (83.6%), with a personal monthly income under 3,000 CNY which is approximately USD 420 (64.1%). Most have watched a livecast concert only once (75.7%) and in China (76.9%), primarily available in cinemas and on personal devices (86.0%). Most respondents watched the livecast concert in an audience venue of 100 to 200 attendees (43.2%) with a friend (45.9%). Since most have watched in China, where no official service is available, most events are fan-organized (80.9%).

Table 3.

Basic Information of Questionnaire Survey Participants.

Variable	Value	N	%
Gender	Female	309	93.9
Gender	Male and other	20	6.1
Age	<18	18	5.5
	18–24	275	83.6
	≥25	36	10.9
Occupation	Student	275	83.6
Occupation	Non-student	54	16.4
Monthly income	<3,000 CNY	211	64.1
	3,000–5,000 CNY	39	11.9
	5,000–8,000 CNY	37	11.2
	>8,000 CNY	42	12.8
Experience	Watched once	249	75.7
Experience	Watched multiple times	80	24.3
Place	China	253	76.9
Place	Korea and other	76	23.1
Exclusivity	Concert available in cinema and on personal devices	283	86.0
Exclusivity	Concert available in cinema only	46	14.0
Audience size	<50	66	20.1
	50–100	63	19.1
	100–200	142	43.2
	>200	58	17.6
Companion	Alone	93	28.3
	With one friend	151	45.9
	With several friends	85	25.8
Organizer	Fan-organized	266	80.9
Organizer	Official and other	63	19.1
Frequency of going to concerts	0	149	45.3
	1–2	124	37.7
	≥3	56	17.0
Frequency of going to movies	0	88	26.7
	1–2	175	53.2
	≥3	66	20.1

Factor Analysis, Construct Validity and Reliability

We first conducted a exploratory factor analysis (EFA) on all survey items and extracted variables with eigenvalues >1.0 using the principal components method. We used the varimax rotation method since most previous studies also used the technique. We considered items with loading values above 0.6 on only one factor acceptable and removed items with all loading values under 0.6 or a load above 0.6 on more than one factor. We confirmed the partial correlation between variables with Kaiser–Meyer–Olkin (KMO) above 0.9 and Bartlett’s test of sphericity significance.

To validate the constructs, we performed a confirmatory factor analysis (CFA) using Mplus Version 8.3. The model fit indices indicated an acceptable fit with χ²/df = 859.217/413 = 2.08, CFI = 0.908, TLI = 0.896, and RMSEA = 0.057 (Browne & Cudeck, 1992; Schermelleh-Engel et al., 2003; Sharma et al., 2005). Standardized factor loadings in CFA were all significant and ranged above 0.6, indicating strong relationships between the items and their respective factors. The reliability of the factors was satisfactory, with all Cronbach’s alpha values in EFA above .7, AVE above .5, and CR above .6 in CFA (Fornell & Larcker, 1981). Table 4 shows the 31 items associated with each factor and the reliability measures. We calculated the means of the items under each variable and conducted correlation and regression analyses.

Table 4.

Factor Loadings and Composite Reliability.

Construct	Factor loading
Construct	EFA	CFA
Artist attachment (Cronbach’s alpha = .758, AVE = .647, CR = .843)
I would be very happy if I could meet them up close in person.	.886	.867
I hope their career on stage will be active for a long time.	.877	.901
I will miss them if I don’t see their content, social media feed, etc., for a long time.	.744	.615
Content quality (Cronbach’s alpha = .888, AVE = .639, CR = .898)
I am satisfied with the stage design, lighting, and special effects of the concert seen on the screen.	.786	.856
I am satisfied that through the intercut of shots, I can watch the stage performance from different angles.	.755	.825
I am satisfied that I can see the artist’s subtle expressions, movements, etc., through close-up shots.	.733	.808
I am satisfied with the flow, setlist, and special corners of the concert.	.723	.781
I am satisfied that when watching the concert in the cinema, there are special corners (such as VCR, interactive video, etc.) not seen by the live audience but are specially designed for the audience in the cinema.	.714	.719
Technology (Cronbach’s alpha = .772, AVE = .573, CR = .800)
The live streaming is smooth without network disconnection.	.839	.674
The video quality of the cinema screen is satisfying.	.760	.831
The audio quality of the concert at this cinema is good.	.719	.757
Convenience (Cronbach’s alpha = .899, AVE = .585, CR = .907)
The transportation or parking facilities around the cinema are convenient.	.826	.869
The environment around the entrance and exit of the theater, ticket box, restrooms, and dining spaces is good.	.750	.836
The theater staff or organizers are hospitable.	.736	.783
It is convenient to buy tickets or register before attending the event.	.684	.730
It is convenient to be able to attend the event at a place near where I live.	.665	.616
The seat in the cinema is comfortable and spacious.	.664	.762
It is convenient that going to the cinema does not need much preparation.	.651	.732
Physical interaction (Cronbach’s alpha = .797, AVE = .532, CR = .815)
I often share my feelings in real time with my friends sitting next to me.	.733	.558
Using new technologies, such as the flashing of light sticks along with the music, makes me feel more connected when watching the livecast concert.	.703	.608
I often scream, cheer, sing, etc., with the audience in the theater.	.624	.831
I can see the reaction of other audiences in the theater, and I enjoy that.	.604	.870
Consumer satisfaction (Cronbach’s alpha = .939, AVE = .729, CR = .942)
Watching a livecast concert in the cinema is a fun experience.	.807	.895
Considering what I got out of this experience, the physical and emotional effort that I paid was worth it.	.787	.880
I think it was worth the time it took to watch this concert live in the cinema.	.776	.841
I am generally satisfied with the experience of watching livecast concerts in the cinema.	.748	.843
I am happy to be able to watch the livecast concert with a group of people in the cinema.	.722	.858
I think it’s worth the money paid (including ticket price, transportation, etc.) to watch this concert live in the cinema.	.676	.804
Repurchase intention (Cronbach’s alpha = .812, AVE = .605, CR = .820)
Even if I can watch the livestream of the same concert on my portable devices at home, I am willing to choose to watch it in the cinema.	.752	.787
Even without the impact of the pandemic, I may watch livecast concerts in the cinema again for other reasons in the future.	.735	.869
I intend to watch the livecast concert of other artists/groups I like in the cinema.	.689	.664
Cumulative sums of squared loadings	72.035%
Kaiser-Meyer-Olkin measure of sampling adequacy	0.924
Bartlett’s test of sphericity, approx. chi-square	7,265.476 (df = 465, p < .001)

Note. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Correlation Analysis

We recoded all non-scale variables (demographics, basic information of livecast concert attended, and consumption patterns) into binary values to examine their potential relationship with SQ factors, CS, and RI (Table 5).

Table 5.

Control Variables.

Variable	Recoded values	N	%
Experience	0 = Watched once	249	75.7
Experience	1 = Watched multiple times	80	24.3
Place	0 = China (all events organized by fans)	253	76.9
Place	1 = Korea & Other	76	23.1
Exclusivity	0 = Both cinema & personal devices	283	86.0
Exclusivity	1 = Cinema only	46	14.0
Audience size	0 = below 100	129	39.2
Audience size	1 = 100 and above	200	60.8
Companion	0 = Alone	93	28.3
Companion	1 = With friends	236	71.1
Organizer	0 = Fan-organized	266	80.9
Organizer	1 = Official & Other	63	19.1
Gender	0 = Female	309	93.9
Gender	1 = Male & Other	20	6.1
Age	0 = Below 24	293	89.1
Age	1 = 25 and above	36	10.9
Occupation	0 = Student	275	83.6
Occupation	1 = Non-student	54	16.4
Monthly income	0 = Below 3,000 CNY	211	64.1
Monthly income	1 = 3,000 CNY and above	118	35.9
Frequency of going to offline concerts per year	0 = Never	149	45.3
Frequency of going to offline concerts per year	1 = More than once	180	54.7
Frequency of going to movies	0 = Never	88	26.7
Frequency of going to movies	1 = More than once	241	73.3
Frequency of going to performance arts	0 = Never	221	67.2
Frequency of going to performance arts	1 = More than once	108	32.8

Pearson’s correlation (Table 6) showed a statistically significant positive correlation between attachment, all SQ factors, CS, and RI, satisfying the prerequisite for linear regression. Based on the demographics, basic information of the livecast concert attended, and consumption pattern variables, we found a relationship between CS and/or RI and the following data: experience, place, audience size, organizer, age, income, and frequency of attending offline concerts. Therefore, we used this data as control variables in regression in the next step.

Table 6.

Pearson’s Correlation.

Variables	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20
14	−.058	−.001	.012	.131*	−.098	.013	.055	−.094	−.013	−.059	−.087	.024	−.014	1
15	−.112*	−.162**	.007	.065	.019	−.183**	.107	−.104	−.021	−.079	−.079	−.07	−.007	.419**	1
16	.128*	.026	.171**	−.040	.104	.007	−.018	−.106	−.094	.033	.155**	−.022	.05	.144**	.395**	1
17	−.014	−.087	.027	.077	.009	−.131*	.044	−.068	−.074	−.139*	−.04	−.055	.055	.343**	.582**	.522**	1
18	−.185**	−.244**	−.075	.02	.149**	−.304**	.033	−.111*	−.041	−.161**	−.088	−.062	.049	.352**	.541**	.305**	.536**	1
19	−.160**	−.246**	−.023	.08	.019	−.318**	.082	−.119*	−.046	−.184**	−.147**	−.027	−.077	.370**	.614**	.322**	.601**	.718**	1
20	−.078	−.180**	−.059	.18**	−.018	−.211**	.029	−.063	.016	−.150**	−.069	.08	.008	.425**	.556**	.269**	.492**	.587**	.693**	1

Note. Column/Row Headings Legend: 1 = Experience; 2 = Place; 3 = Exclusivity; 4 = Audience size; 5 = Companion; 6 = Organizer; 7 = Gender; 8 = Age; 9 = Occupation; 10 = Income; 11 = Frequency of concerts; 12 = Frequency of movies; 13 = Frequency of performing arts; 14 = Artist attachment; 15 = Content quality; 16 = Technology; 17 = Convenience; 18 = Interaction; 19 = Consumer satisfaction; 20 = Repurchase intention.

p < .05 (2-tailed). **p < .01 (2-tailed).

Hypotheses Testing

We used the Preacher and Hayes (2004, 2008) regression-based bootstrapping approach to test mediation effects (Demming et al., 2017) and the Hayes’ PROCESS macro model 4 in SPSS for simple mediation effects. Each independent variable is an X (predictor variable) and composes a simple mediation model with CS as M (mediator) and RI as Y (outcome variable). PROCESS macro outputs direct and indirect effects, covering all our hypotheses. We ran the macro with 5,000 bootstrap iterations, using RI as Y, CS as M, the independent variable as X, and other covariates. Table 7 lists the results.

Table 7.

Process Macro Results.

X (Predictor variable)	Direct effect of X on CS (a)	Direct effect of X on RI (c′)	Total effect of X on RI (c = ab + c′)	Indirect effect of X on RI (ab)
X (Predictor variable)	Std. Coeff.	Std. Coeff.	Std. Coeff.	Std. Coeff.	Boot. LLCI	Boot. ULCI
Experience	−0.0384	0.0716	0.0559
Place	0.0353	−0.0307	−0.0163
Audience size	0.0347	0.1209**	0.1350**
Organizer	−0.1383*	0.0091	−0.0471
Age	0.0071	0.0362	0.0391
Income	−0.0219	−0.0691	−0.0780
Freq_Concert	−0.0485	0.0634	0.0437
Content	0.2041**	0.1764**	0.2594***	0.0830^†	0.0264	0.1538
Convenience	0.2472***	−0.0225	0.0780	0.1005^†	0.0452	0.1710
Technology	0.0061	−0.0066	−0.0041	0.0025	−0.0342	0.0441
Physical interaction	0.3752***	0.1741**	0.3267***	0.1525^†	0.0749	0.2483
Artist attachment	0.0722	0.0954*	0.1247**	0.0294	−0.0203	0.0947
Effect of CS on RI (b)		0.4066***
F	40.1576***	24.1105***	20.1324***
R ²	.7771	.7062	.6582

p < .05. **p < .01. ***p < .001.

†

Significant (confidence interval does not include zero).

As per Table 7, the direct effect models show that among the control variables, “organizer” positively affects CS, and “audience size” positively affects RI. Among the independent variables, “content,”“convenience,” and “physical interaction” positively affect CS; “content,”“physical interaction,” and “artist attachment” positively impact RI.

Using Zhao et al. (2010) and Demming et al.’s (2017) mediation typology, the insignificant direct and total effects of “convenience” on RI indicate that “convenience” has no impact on RI despite a significant indirect effect. For “content” and “physical interaction,” total, direct, and indirect effects are significant with the same sign, suggesting complementary partial mediation. The direct effect model also shows that CS significantly positively affects RI (0.4066).

Table 8 lists all hypotheses testing results; Figure 2 presents all significant paths of the model for a clearer view of the relationship between variables.

Table 8.

Hypothesis Testing Results.

No.	Hypothesis	Result
H₁	SQ factors positively affect CS.	Partially supported
H_1-1	Content quality positively affects CS.	Supported
H_1-2	Convenience positively affects CS.	Supported
H_1-3	Technology positively affects CS.	Rejected
H_1-4	Physical interaction positively affects CS.	Supported
H₂	SQ factors positively affect RI.	Partially supported
H_2-1	Content quality positively affects RI.	Supported
H_2-2	Convenience positively affects RI.	Rejected
H_2-3	Technology positively affects RI.	Rejected
H_2-4	Physical interaction positively affects RI.	Supported
H₃	CS mediates the relationship between the SQ factors and RI.	Partially supported
H_3-1	CS mediates the relationship between content quality and RI.	Supported (partial mediation)
H_3-2	CS mediates the relationship between convenience and RI.	Rejected
H_3-3	CS mediates the relationship between technology and RI.	Rejected
H_3-4	CS mediates the relationship between physical interaction and RI.	Supported (partial mediation)
H₄	CS positively affects the RI.	Supported
H₅	Artist attachment positively affects CS.	Rejected
H₆	Artist attachment positively affects RI.	Supported
H₇	CS mediates the relationship between artist attachment and RI.	Rejected

Figure 2.

Model with significant path coefficients.

Stage 3 Discussion

Control Variables: Organizer and Audience Size

Among the control variables, “organizer” significantly affected satisfaction. Participants of fan-organized livecast concerts showed more satisfaction than those of official events. This finding may stem from participants feeling more comfortable at fandom-only events rather than at official ones, where etiquette is a concern. In addition, “audience size” significantly positively influenced RI, independent of other variables—the larger the audience size, the higher the RI. A larger audience size likely enhances the livecast’s appeal by creating a livelier atmosphere. Additionally, those attending large-audience events might be more open to public events, making them likelier to participate again.

Artist Attachment

Participants’ attachments to the artist do not influence livecast satisfaction but can directly lead to RI. Fans may purchase another livecast concert despite dissatisfaction, not wanting to miss unique artist-related activities. This finding aligns with the interview results.

SQ Factors That Influence Satisfaction

Livecast satisfaction hinges on concert quality, not on artist attachment or fandom. Specifically, “content,”“convenience,” and “physical interaction” positively affect livecast concert satisfaction. Among them, the coefficient of “physical interaction” is the highest (0.3752), almost twice the coefficient of “content” (0.2041) and “convenience” (0.2472). This result indicates that “physical interaction” is the most valued aspect of a livecast concert, aligning with interviewee testimonies that they appreciate livecast concerts’ lively atmosphere, sense of belonging, and social aspects. “Technology” (streaming connection, audio/video quality) does not affect satisfaction as hypothesized.

The SQ result differs from previous studies on purely online streaming concerts or musicals, where “technology” is an influential factor, and “convenience” and “content” typically outweigh “interaction” (S.-E. Kim & Kim, 2021; S.-K. Kim & Limb, 2020). This finding underscores the significance of in-person audience engagement that digital interactions through social media or platform functions cannot match in a purely online concert.

SQ Factors That Influence RI

Among the SQ factors, “content” and “physical interaction” positively influence RI, with “physical interaction” still the major influential factor (0.1741); satisfaction partially mediates both. Though “convenience” positively influences satisfaction, it does not lead to RI. In addition, “technology” does not lead to RI as hypothesized.

Practical Insights

The results provide practical insights for operating livecast concert services in the future. Improving SQ factors of livecast concert services can result in higher satisfaction with the event. However, when consumers consider whether to attend the next event, they still tend to decide based on how much they want to see the artist. Therefore, fandom is still the main target of livecast concerts. Livecast concerts can be the next best choice for fans who cannot secure an offline concert ticket due to limited seats.

From another perspective, the result also means that even if the participant does not show high attachment to the artist (not a “fan”), as long as service providers have guaranteed high service quality, they will still value the experience and will not be dissatisfied with this service. Even if these participants do not show high RI, they may participate as a companions and still enjoy the livecast concert. This finding aligns with the insight from interviews that livecast concerts may be an easy-to-enter option for a wider audience with lower attachment or fan loyalty. The entertainment industry may use this service to maximize revenue by attracting a wider audience, favoring lower prices and more convenience.

To enhance livecast concert quality, organizers should focus on fostering “physical interaction” to facilitate a lively atmosphere, making the event feel more like a fan gathering than a mere technical showcase.

Conclusion

Common Implications From the Three Stages of the Study

The main takeaway from this study’s three stages is that participants value physical presence and interaction in livecast K-pop concerts. This finding draws support from media analysis, interviewees’ accounts of a lively atmosphere, and data identifying “physical interaction” as a key satisfaction and RI influencer. Even when participants are not physically “there” in the same place as the artist, physically “being somewhere” with a group who shares the vibe is a more satisfactory option than watching on one’s device. Live streaming concerts in cinemas transform personal viewing into a social and group activity. A cinema-hosted livecast concert maintains valued concert behaviors found in authentic offline concerts, such as screaming, cheering, chanting, and waving light sticks together.

In addition, fandom significantly generates (re)purchase intention, with fans not wanting to miss any concert due to its unique nature—interviewees’ motives of wanting to witness everything about the artist support this finding. The quantitative result is that artist attachment directly leads to RI, and the quality of the content is an influential factor in satisfaction and RI.

The consumer behavior of wanting to see every concert also connects with the concept “fear of missing out (FoMO),” defined as an “uneasy and sometimes all-consuming feeling that you’re missing out – that your peers are doing, in the know about, or possession of more or something better than you” (Abel et al., 2016). FoMO relates to an individual’s intrinsic “inadequacy, irritability, anxiety & self-esteem,” magnified by social media (Abel et al., 2016).

Practical Insights on Future Strategy for Operating and Marketing Livecast Concerts

Livecast concerts, while not matching authentic offline concerts, serve as the “next best option” for fans. By partnering with cinemas, the entertainment industry can attract more audiences from previously online livestreaming concerts, boosting revenue.

There are two situations that the livecast option suits best in the post-COVID era. The first is the kind of one-time moment that fans must witness “right here” (if not with the artists, then at least with a group of like-minded participants) and “right now.” The “Boys Planet X Cgv Final Live Show on the Theater” is a successful case, marking the debut of a new idol group in a survival program’s final show. In this case, fans’ primary needs were to witness the moment in real-time, and being able to cheer for their favorite trainees in a group-viewing setting added to the joy of the experience.

Another situation is when the concerts target audiences from different locations, whether domestic for international fans or overseas for local fans, attending in person becomes challenging and costly. In this case, most fans would likely choose the livecast option, capturing the vibe of an offline concert while being more accessible than flying overseas to attend in person. “Seventeen World Tour [Be The Sun] – Houston: Live Viewing” and several fan-organized events in China are successful cases.

Methodological Contribution

This study diverged from traditional art management and business research by adopting a phenomenon-oriented, mixed-methods approach to explore a new, unstudied service. Qualitative analysis captured participants’ motivations and values through words and actions, exclusive to this method. The quantitative stage broadened the participant base, diversifying demographics, and consumption habits, allowing these results to confirm and generalize the qualitative results. Furthermore, the quantitative stage generated measurements and a model for future marketing research, offering intuitive insights into business and marketing strategies. This study’s qualitative and quantitative results validate each other, revealing valuable insights unique to each method. This study suggests the practicality of mixed methods in exploring a new business activity or an unknown market.

Limitations and Implications for Further Research

The study examined mostly fan-organized events and focused on Chinese-speaking participants for research efficiency. Future studies could explore livecast experiences in other regions, such as Japan, South Korea, and the United States, where cinemas offer these concerts collaboratively. The research primarily focused on fan-organized events since, at the time of the survey, fans predominantly organized livecast events. Additionally, contacting participants through fan clubs was easier than reaching individual attendees of official events. This restriction may potentially introduce bias in the results. Future studies could look at the official events organized by cinemas. Including a broader range of events organized by fans and official entities would provide a more comprehensive understanding of the livecast concert landscape.

We conducted this study during COVID-19, and the results predicted the continuous popularity of livecast concerts post-COVID-19. Future studies could look at the reality of livecast concerts in the post-COVID-19 era, analyze the actual operational strategies of livecast service providers, and compare with the results of this study.

As the first study on K-pop livecast concerts, this research outlines key factors influencing livecast concert purchases. Future studies could explore how specific factors drive purchase decisions, such as why fandom prompts repurchase regardless of current experience satisfaction or why K-pop livecast audiences overlook technological aspects. They might also measure and include the “fear of missing out” (FoMO) variable to determine how individual psychological traits contribute to purchasing artist events. We suggest that future studies apply diverse methodologies, like sociological or psychological approaches, to enrich our knowledge of livecast concerts and fandom psychology and liveness.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Approval

The Chung-Ang University Ethics Center approved the study (Approval number: 1041078-20230927-HR-269) on November 23, 2023.

ORCID iD

Seong-Joon Limb

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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