tiểu luận research about the influence of music content marketing on user satisfaction and intention to use in the metaverse

In conclusion, this research highlights the potential value of musiccontent marketing within the metaverse, as evidenced by the metaverse SPICE model.Keywords: metaverse; music content;

Introduction and Background

Important of research

The COVID-19 pandemic has fundamentally reshaped our lives, ushering in a

"contactless" era This has led to a surge in telecommunication, remote work, and virtual experiences The metaverse, a recently emerged platform powered by 5G, advanced graphics,and cutting-edge displays, presents a new paradigm for this era This technology offers a unique blend of virtual experiences and high connectivity, unbound by time and space.However, the metaverse is still in its early stages, and its effectiveness as a marketing tool remains largely unexplored This research aims to bridge this gap by investigating user satisfaction with music content in the metaverse By analyzing this data, we hope to understand the impact of music content marketing on consumer satisfaction and purchase intention within the metaverse This will provide valuable insights for content creators and marketers seeking to develop successful metaverse marketing strategies in the post-pandemic era.

Scope of research

This research focuses on “consumer satisfaction” and “purchase intention” This research is not limited to any type of music and using two questionnaires Vietnamese and English.

Considering the time and size of research, we use two factors (consumer satisfaction and purchase intention) in many experiences from quantitative research and literature review to build the framework and testing hypothesis.

The target audience is Vietnamese people, who use the metaverse, above 20 years old.

Research problem/question

In quantitative research, the result helps to answer the question: How does Music Content Marketing affect Consumer Satisfaction and Purchase Intention? Based on the result of quantitative research, in next step this research tries to answer these questions:

How does the SPICE Model for Music Content Marketing influence Consumer Satisfaction?

How does the SPICE Model for Music Content Marketing influence Purchase Intention?

Too long to read on your phone? Save to read later on your computer

Does Consumer Satisfaction formed by the Metaverse SPICE Model for MusicContent Marketing have a significant positive effect on Purchase Intention?

Aims and Objectives

This study’s aim is to provide a framework for content creators and marketers to verify the effectiveness of metaverse marketing.

This study’s objective is to examine the influence of the music content marketingSPICE model factors and Consumer satisfaction and purchase intentions in the metaverse through theoretical considerations and reviews of previous studies.

Literature review

Applicability of Existing Marketing Tools

Davis et al suggest that existing marketing tools used on traditional platforms can be adapted for the metaverse due to similarities in user behavior.

Marketing Strategies in the Post-COVID Era

Wamba et al analyze big data to demonstrate the suitability of "untact" marketing strategies for promoting performing arts and cultural content in the post-COVID era This finding aligns with the metaverse's potential for contactless experiences.

SPICE Factors for Metaverse Marketing

Studies by Yüksel et al., Lee et al., and You et al propose SPICE factors (Continuity, Presence, Interactivity, Customization, and Engagement) as crucial elements for effective marketing within the metaverse environment.

Music Content Marketing and Purchase Intention

Hampe and Schwabe explore the connection between music content marketing and purchase intention in live commerce settings, drawing on research by Lu and Chen This suggests a potential link between music marketing in the metaverse and user purchasing behavior.

Additional Factors Influencing User Behavior

Studies on consumer preferences highlight interoperability, simultaneity, and economic flow as important factors affecting user behavior in online environments, including purchase intention and continued use These factors may also hold relevance for the metaverse.

Liikkanen and Salovaara and Boroughf emphasize the significance of high-quality content in attracting and retaining subscribers on music platforms like YouTube This highlights the need for compelling music content within the metaverse to maximize the effectiveness of marketing strategies.

Research model and Hypothesis

H1 The metaverse SPICE model for music content marketing has a significant effect on consumer satisfaction.

H1-1 Continuity has a significant positive effect on Consumer satisfaction. H1-2 Sense of presence has a significant positive effect on Consumer satisfaction. H1-3 Interoperability has a significant positive effect on Consumer satisfaction. H1-4 Concurrence has a significant positive effect on Consumer satisfaction. H1-5 Economic flow has a significant positive effect on Consumer satisfaction. H2 The metaverse SPICE model for music content marketing has a significant effect on purchase intention.

H2-1 Continuity has a significant positive effect on purchase intention.

H2-2 Sense of presence has a significant positive effect on purchase intention.H2-3 Interoperability has a significant positive effect on purchase intention.H2-4 Concurrence has a significant positive effect on purchase intention.H2-5 Economic flow has a significantly positive effect on purchase intention.

H3 Consumer satisfaction formed by the metaverse SPICE model for music content marketing has a significant effect on purchase intention.

Methodology

Methodological considerations and assumptions

This research is quantitative research using questionnaires to collect the data. This research aims to find the relationship among components, so that descriptive research design is suitable with this aim.

The research adopts existing scales from the pertinent literature to analyze the relationship among components (table 1) The scales should produce an acceptable fit in a measurement model and have good psychometric properties as acceptable reliability and convergent and discriminant validity (Calder et al., 2009). This research uses the scales from previous research and has high reliability in other researches.

Table 1: Definition and method of measurement of components and dimensions

Components Definition Method of measurement

Seamlessness Seamlessness is a continuous connection between various experiences on a single platform, which means that even when a specific character is connected to a previous situation, it can continue the experience without disruption by retaining actions or experiences on the platform

3 indicators adopting from MinKyung, L., RakGun, H (5 April 2022)

Presence A sense of presence is a situation in which users can perceive it both spatially and socially, without any physical contact

Interoperability Interoperability is the property of interlocking data and information between the real world and the metaverse

Concurrence Concurrence is defined as an environment in which multiple users are simultaneously active and can have various experiences within 1 m.

Economy Flow Reflect the creation, transformation, exchange, transfer, or extinction of economic value; they involve changes in the volume, composition, or value of a unit's assets, liabilities, and net worth.

Purchase Intention Purchase Intention is the tendency of consumers to buy a brand or take actions related to purchases that are measured by the level of possibility of consumers to make purchases

Consumer satisfaction is the tendency to take action or respond to possibilities and thus measure satisfaction on the platform by the willingness of the user to continue using it or recommend it to others.

The research’ respondent answered all measurement items according to the 5 point likert scale (1- strongly disagree to 5- strongly agree) The questionnaire includes 22 indicators of 7 components, not including the indicators about respondents’ social demographics.

Sample considerations

Hair, J F., Black, W C., Babin, B J., Anderson, R E., & Tatham (2006) suggested that the size of the sample needs at least 5 times of indicators if usingMaximum Likelihood method Hoelter (1983) proposed a ‘critical sample size’ of

200 In other words, as a rule of thumb, any number above 200 is understood to provide sufficient statistical power for data analysis

(Hoe, 2008) This research contains 22 items, so that the size of the sample has at least 110 questionnaires This research collected 200 respondents, so that it is enough for analyzing.

Data collection and framework, and analytical considerations

Data of this research is collected through online surveys that avoid missing data errors The total sample size is 200 The majority of respondents fall into the 20-30 age group, comprising 47.5% of the sample, the 30-40 age group and older than 40 group account for 35.5% and 17.0% of the sample, respectively The sample is nearly evenly split between male and female respondents, with males representing 57% and females 43% The majority of respondents have a university education level accounting for 48.5% The majority of respondents whose employment status is already employed, accounting for 53.0% Finally, Most respondents have salaries from 10 million to 20 million VND, accounting for 42.0%.

Analysis

Descriptive statistics

Table 3 shows the frequency of 22 items of 7 factors in this research.

Table 3: The descriptive result of items

A1 It provides an experience with continuity 200 4.01 4.00 1.020

A3 The interest in music content increased due to the experience of the continuity element

B1 It provides an experience with a sense of reality

B2 The sense of reality is memorable 200 3.88 4.00 1.045

B3 Interest in music content has increased due to the experience of elements of presence

C1 It provides a working environment 200 4.07 4.00 0.998 C2 The interactive experience is interesting 200 3.86 4.00 1.047

C3 Interoperable experiences lead to fandom memberships, etc.

D2 The experience of simultaneity is memorable

D3 The experience of simultaneity has raised interest in music content

E1 It fits well with the elements of economic flow

E2 Economic flows can be linked to my actual economic factors

E3 It induces an actual economic action to purchase music content

F1 My interest in music content products has increased

F2 The possibility of purchasing musiccontent-related products has increased

F3 It convinces you to purchase the artist’s merchandise

G1 Sensitivity toward the artist rises 200 3.95 4.00 0.981

G2 I acquire a lot of information related to music content

G3 I want to participate in various events through experience

G4 It is becoming a standard for selecting music content

Cronbach’s Alpha

T-Test and Anova

H0: Gender has no effect on

Seamlessness/Presence/Interoperability/Concurrence/Economy Flow/Purchase Intention/Consumer Satisfaction

H1: Gender has an effect on

All variables: Sig > alpha = 0.05 → Failed to reject H0 → Accepted

H0 → Gender has no effect on

Seamlessness/Presence/Interoperability/Concurrence/Economy

Flow/Purchase Intention/Consumer Satisfaction

H0: Age has no effect on Seamlessness/Presence/Interoperability/Concurrence/Economy Flow/Purchase Intention/Consumer Satisfaction

H1: Age has an effect on

H0 → Age has no effect on

H0: Education level has no effect on Seamlessness/Presence/Interoperability/Concurrence/Economy Flow/Purchase Intention/Consumer Satisfaction

H1: Education level has an effect on

H0 → Education level has no effect on

H0: Employment status has no effect on Seamlessness/Presence/Interoperability/Concurrence/Economy Flow/Purchase Intention/Consumer Satisfaction

H1: Employment status has an effect on

H0 → Employment status has no effect on

H0: Average income has no effect on Seamlessness/Presence/Interoperability/Concurrence/Economy Flow/Purchase Intention/Consumer Satisfaction

H1: Average income has an effect on

H0 → Average income has no effect on

Regression Analysis

Table below shows the final result of testing hypothesis, all of hypotheses were tested by single linear regression.

Sup portedThe table shows that hypotheses H1-1 (b=0.297, p=0.000), H1-2 (0.549, p=0.000),H1-3 (b=0.399, p =0.000), H1-4 (b=0.630, p=0.000) and H1-5 (b=0.986, p =0.000) are accepted It means all Seamlessness, Presence, Interoperability, Concurrence and Economy

Flow affect customer satisfaction From this result, the research provides the mathematical function of Consumer satisfaction:

The table shows that hypotheses H2-1 (b=0.393, p =0.000), H2-2 (b=0.610, p=0.000), H2-3 (b=0.518,p=0.000), H2-4 (b=0.705, p=0.000) and H2-5 (b=0.690, p=0.000) are accepted It means all Seamlessness, Presence, Interoperability, Concurrence and Economy Flow lead to Purchase Intention From this result, the research provides the mathematical function of Purchase Intention

Thirdly, the research also shows the relationship between customer satisfaction and purchase intention According to the result, H3 (b=0.698, p=0.000) was supported, so we figured out the equation:

Purchase Intention = 1.218 + 0.681*Customer Satisfaction + ei

Finding and recommendation

Firstly, this research found that Consumer Satisfaction has a strong relationship with the dimension of Economy Flow because Economy Flow explains most of Consumer Satisfaction (R2 = 0.937 = 93.7%), other independent variables only explain little of dependent variables All independent variables have a positive impact on two dependent variables (Consumer Satisfaction and Purchase Intention).

Seamlessness: Users generally found the experience seamless (Means = 4.00). There's some variation in memorability (Means = 3.84) The impact on music content interest is moderate and varied (Means = 3.86).

Presence: Similar to seamlessness, users found the experience to have a moderate sense of reality (Means = 3.61) However, memorability of this aspect is higher (Means 3.88) The impact on music content interest seems positive but slightly higher than seamlessness (Means = 3.93).

Interoperability: Users felt the experience provided a working environment (Means

= 4.07) However, the interactive experience’s interestingness is moderate (Means = 3.86). There's a possibility that interoperability might lead to further engagement (Means = 3.87). Concurrency: The experience seems to achieve concurrency (Means = 4.07). Memorability of the simultaneous aspect is moderate (Means = 3.82) The impact on music content interest is positive (Means = 3.96).

Economy Flow: Users found it aligned with economic flow elements (Means = 3.95) and connectable to their economic factors (Mean 3.98) Moreover, users found that there is an actual economic action to purchase music content (Means = 3.88).

Purchase Intention: Users generally reported increased interest in music content and related products (Means = 4.00) The possibility of purchasing also increased (Means = 3.97). However, the element's influence on convincing users to buy merchandise seems moderate (Means = 3.81).

Consumer Satisfaction: Users reported increased artist sensitivity (Means = 3.95) and information gain (Means = 3.98) There's also a desire to participate in events due to the experience (Means = 3.88) Interestingly, the experience might be becoming a standard for music content selection (Means = 4.10).

This study identified several areas for further investigation to enhance user experience and marketing effectiveness in the metaverse music content Firstly, while users reported a positive experience, aspects like seamlessness and presence could be improved to create a more memorable experience Secondly, the data suggests a potential link between interoperability and user engagement, particularly for fan communities Further research could explore this connection to see if strengthening interoperability directly translates to increased fan loyalty and participation Additionally, the link between economic flow within the metaverse and user purchase intention requires further investigation Understanding how a more robust economic system might influence music content purchases will be crucial for optimizing monetization strategies Finally, although purchase intention for music content appears positive, A/B testing or other methods could be employed to refine the elements influencing merchandise purchases within the metaverse platform.

Compared to the reference research, which shows that all SPICE model factors have a strong impact on Customer Satisfaction and Purchase Intention, our research indicates that only Economy Flow affects these two dependent variables significantly and the rest of theSPICE model factors are moderate Furthermore, the research is only conducted in Vietnam;therefore, the results are applied only for Vietnamese people and it will require more investigation if taken globally.

Limitations

We find that this research has several drawbacks First and foremost, this research employs an online survey, posing challenges in monitoring respondents' behavior while completing it To address this issue, we seeked to gauge respondents' willingness to participate before providing them with a direct link via questionnaire

Secondly, we also have to deal with sampling bias as this survey may not reach a representative sample of the target population, it relies on individuals with internet access and willingness to participate, potentially excluding some certain demographics To deal with this matter, if we conduct this research again, we would utilize multiple channels for recruitment to reach a diverse amount of participants, including offline methods if feasible.

Last but not least, the inability to verify identity Definitely, online surveys lack the ability to verify the identity of respondents, which may lead to fraudulent or duplicate responses, compromising data accuracy To minimize this disadvantage, we would like to implement measures such as CAPTCHA or IP address tracking to minimize fraudulent or duplicate responses, or include screening questions to filter out respondents who do not meet eligibility criteria.

Appendices

Tiêu đề	Research about the Influence of Music Content Marketing on User Satisfaction and Intention to Use in the Metaverse
Tác giả	Le Vu Huong Giang, Vu Le Truc Linh, Nguyen Le Ngoc Diep, Nguyen Thi Ut, Nguyen Pham Cong Khang
Người hướng dẫn	Ph.D Truong Dinh Quoc Bao
Trường học	Da Nang University of Economics
Chuyên ngành	Marketing
Thể loại	Research
Năm xuất bản	2024
Thành phố	Da Nang

Định dạng
Số trang	30
Dung lượng	3,04 MB