The role of cognitive factors in consumers’ perceived value and subscription intention of video streaming platforms: a systematic literature review

Abstract

This study reviews the literature to determine how cognitive factors affect consumers’ value perception and video streaming platform subscription intentions. This study analyses 20 Scopus and Web of Science peer-reviewed articles to examine the complex relationship between cognitive factors, perceived value and users’ decision-making. The cognitive factors perceived quality, content relevance, variety, enjoyment, cost-benefit ratio, and personalization help explain how users value video streaming platforms. Analyzing these factors can reveal the complex mechanisms that influence users’ platform subscriptions. This has practical implications for industry professionals. The research shows that technical dependability, tailored content suggestions, a variety of content, emotionally engaging content, clear benefit communication, and adaptable experiences shape users’ value perceptions. The above implications are especially relevant in dynamic digital environments influenced by the global pandemic and technological advances. This study also advances consumer behavior theory. This study applies existing models and frameworks to video streaming platforms, adding to the literature. The findings of this study enhance perceived value theory, technology adoption models, personalization theories, and engagement frameworks. These findings improve our understanding of digital user behavior. The study’s narrow focus on cognitive factors and self-reported data are limitations, but it provides valuable insights. These limitations allow future research to explore unexplored areas and use new methods.

Keywords:

• Systematic literature review
• subscription intention
• video streaming platform
• cognitive factor
• perceived value

REVIEWING EDITOR:

• Len Tiu Wright, De Montfort University Faculty of Business and Law, United Kingdom of Great Britain and Northern Ireland

SUBJECTS:

• Cognitive Psychology
• Media & Communications
• Marketing
• Consumer Behaviour

1. Introduction

The digital revolution has transformed many aspects of human life, including media and entertainment consumption (Moll, 2023). Video streaming platforms have become a significant player in the digital transformation of entertainment (Pencarelli, 2020). These platforms offer a wide range of multimedia content, including films, TV shows, documentaries, and original series, at users’ discretion and preferences. Video streaming services have disrupted media consumption patterns and become part of millions of people’s daily routines (Mavale & Singh, 2020). Rapid growth and widespread adoption of video streaming platforms have made the industry a billion-dollar global market (Sundaravel & Elangovan, 2020). This growth has caused a proliferation of providers competing for users’ attention and industry competition. In the highly competitive streaming industry, Netflix, Amazon Prime Video, Disney+, Hulu, and others stand out (McCarthy, 2022). Further, the global COVID-19 pandemic and rapid 5G technology implementation have complicated these platforms’ operations (Siriwardhana et al., 2020). Industry giants compete fiercely to attract and retain loyal customers. Service providers must understand the cognitive factors influencing consumers’ value perceptions and platform subscriptions in a dynamic market. This pursuit is crucial to these providers’ long-term success and growth.

The current study examines the complex relationship between cognitive factors, consumers’ value perception and intention to subscribe the video streaming platforms. It is important to understand the psychological mechanisms that influence video streaming users’ decisions. Therefore, the question arises that what cognitive factors strongly influence consumers’ value perception and intention to subscribe to video streaming platforms? This study investigates the cognitive factors that shape people’s views, preferences, and motivations regarding video streaming platforms.

It’s important to note that the literature on this topic is fragmented, with inconsistent findings. Many studies have examined cognitive aspects like perceived quality, ease of use, enjoyment, and information processing. In contrast, some studies have detachedly analyzed individual platforms (Wu & Gao, 2020). Limited research on the cognitive mechanisms underlying users’ experiences and decision-making processes across video streaming services leaves a gap in our understanding of this complex phenomenon (Liedtka, 2018). New content delivery models, personalized recommendation systems, and interface designs have emerged to accommodate changing consumer preferences as the digital landscape rapidly evolves. However, scarce literature exists regarding the effect of these advances on the consumers’ cognitive mechanisms and decision-making process, particularly in video streaming platforms. Therefore, there is need for a thorough investigation and examination of literature regarding this topic is required.

This study examines literature to combine and integrate current knowledge on cognitive factors’ effects on consumers’ value perception and video streaming platform subscriptions. We use a comprehensive methodology to identify patterns, develop theoretical frameworks, and analyze empirical data to understand users’ complex cognitive processes when using platforms.

This study has both theoretical and practical contributions. The study will not only be limited to growth or profitability but will also cover the subscription intention of video streaming platforms. In the theoretical contribution, future research can benefit from cognitive factor and perceived value to subscription intention which is one of the most important research areas in the domain of consumer perception (Menon, 2022). Overall, make the study a novel contribution towards the body of knowledge. In practical contribution, the professional significance of this research to the video streaming industry and marketing practitioners will help analyze the most important factors for creating, upgrading and maintaining video streaming services.

2. Methods

The systematic literature review was conducted regarding the role of cognitive factors in consumers’ perceived value and subscription intention of video streaming platforms. The systematic review was conducted following the reporting checklist of preferred reporting items for systematic review and meta-analysis (PRISMA; Liberati et al., 2009; Pahlevan-Sharif et al., 2019). To create the main dataset, a protocol was developed in advance to document the search terms, databases, analysis method, and screening criteria. The search was conducted on the Web of Science (WoS) and Scopus. These two databases have the ability to become the leading databases in the systematic literature review because they have the following advantages: advanced search function, comprehensiveness (indexing more than 5000 publishers), article quality control, and multidisciplinary attention, which are used for systematic review of social science research (Gusenbauer & Haddaway, 2019; Martín-Martín et al., 2018; Shaffril et al., 2020).

The article had to meet three pre-defined Eligibility Criteria. First, the article had to be full-length and published in English with the final stage in publication, with no limitations to years and disciplines. The second criterion for the selection of the papers was that the article had to be peer-reviewed journal articles. Other sources of publications like conference papers or reviews, note or book chapters, editorials, and data papers were excluded to ensure the study’s accurate representation and unbiased findings (Weng et al., 2010). Thus, all other publications, such as research notes, editors’ comments, readers’ comments, and book reviews were excluded. The final criterion based on the research question was articles should be from the consumer perspective and include cognitive factors or consumer perception of subscription intention of video streaming platforms.

The existing studies have recommended a five-step review process (Sarja et al., 2021; Yong et al., 2019). The first is to specify the time horizon. The current study duration was selected no time limited. The second step was the selection of a database. The current study includes two well-known databases containing high-quality scientific journal articles such as Scopus and Web of Science. The citations from the identified articles were traced. Among the 1246 publications (628 publications in Scopus, 618 publications in Web of Science) identified, only those empirical studies related to what factors influence subscription intention in video streaming platforms were selected for analysis. The literature search was carried out on 20st Aug 2023. The third step was the identification of keywords. The literature suggests engaging more than one researcher in finalizing the keywords. Therefore, the current study’s authors were included in the keyword selection.

Papers within the scope of consideration have been thoroughly screened, and papers related to platform perspective, ecosystem perspective, content creator perspective, and related papers have been discarded because they do not conform to the scope of research. PRISMA provides a flow diagram showing the different steps of the study selection (i.e. identification, screening, eligibility, and included) and the number of studies identified number of excluded studies in each step, and the number of included studies (Figure 1).

Figure 1. The PRISMA flow diagram.

Finally, all full-text articles investigating factors that influence consumers’ subscriptions to video streaming platforms are shared by the author. The research objectives, research background, research methodology and methods, analysis units, research objectives, theories, variables, assumptions, and research limitations are extracted from the selected papers and recorded in excel and coded for subsequent descriptive analysis.

Further, articles from well-regarded publishers were selected. After implementing the exclusion criteria, 20 studies were considered for this study. Lastly, an Excel sheet was prepared, including all studies. Figure 1 presents a detailed overview of the methodology.

3. Result

The researchers reviewed all the articles thoroughly and attempted to identify the cognitive factors strongly influence consumers’ value perception and intention to subscribe to video streaming platforms. The review results suggested six key factors: perceived quality, perceived content relevance, perceived variety, perceived enjoyment, perceived cost-benefit ratio and perceived personalization. Most studies have attempted to present new insights regarding the definition of video streaming platforms or OTT platforms.

“OTT platforms are services that stream audio-visual content over the internet which their subscribers can view using various devices.” (Chakraborty et al., 2023). In all the reviewed papers, various definitions and terms of video streaming platforms or OTT platforms have been widely observed. Some scholars believe that video streaming services as Subscription based Video on Demand (SVoD) services, which creators provide unlimited access to their video content libraries for a monthly or annual subscription. The business models of most video streaming platforms are based on subscription models and research on consumer subscription behavior (Nagaraj et al., 2021). Other scholars’ research also focuses on Live streaming platforms. At present, live broadcast is also concerned, but many live broadcasts are not based on subscription mode, and their consumer behavior is also based on online purchase (Liao et al., 2022). Through systematic review, my study learned about the definition and consumption mode of video streaming platform. In conclusion, due to the rapid development of technology, there is no consensus on the definition of video streaming platform at this stage. The definition is expanding, and the business model is changing. So in this specific research area, we should do more research on it. Table 1 presents the definition of video streaming platforms or OTT platforms based on different authors.

Table 1. A summary of the definitions.

Authors	Definitions
Chakraborty et al. (2023)	OTT platforms are services that stream audio-visual content over the internet which their subscribers can view using various devices.
Yoelianto and Tjhin (2022)	OTT is defined as “Premium” content services that are channeled through internet media by traditional broadcast operators and content production houses.
Zahara et al. (2022)	Streaming service is a service that allows users to watch movies or TV shows online through TV, mobile device, computer without downloading them from the internet. Streaming services is also recognized as Over the Top(OTT) service, defined as “content, a service or an application that is provided to the end user over the public internet”
Guo, (2022)	Not mention
Camilleri and Falzon, (2021)	Not mention
Nagaraj et al. (2021)	OTT commercial video service, also known as Subscription based Video-on-Demand (SVoD) services are content aggregators (now creators even) which provide unlimited access to their video content libraries for a monthly or yearly subscription.
Madanaguli et al. (2021)	OTT as “the dissemination of services such as voice, video and data, through the Internet such that the mobile network or Internet service is not controlled by the OTT service provider.”
Sardanelli et al. (2019)	Not mention
Walsh and Singh (2022)	Not mention
Kwak et al. (2021)	Not mention
Liao et al. (2022)	Live streaming refers to the technology of leisure, entertainment or communication that broadcasts instant images/video on the Internet with the rise of online audio and video platforms in the modern society.
Kuscu-Ozbudak (2021)	Not mention
Tsai (2023)	Massive amounts of media can be streamed in segments through the compression of large files in what is known as video on demand (VOD)
Kwon et al. (2021)	Over-the-top (OTT) services, which provide streaming media through all devices in online setting
Redondo and Serrano (2023)	Not mention
Lim (2022)	Online streaming platforms allow consumers to access on-demand online content for television shows, movies, and various streaming media.
Liu et al. (2023)	Not mention
Kim and Kim (2020)	Not mention
Koul et al. (2021)	OTT (over-the-top) refers to the contents, services and applications intended for end users and accessible through open internet.
Talwar et al. (2023)	Not mention

3.1. Consumer cognitive factors

3.1.1. Perceived quality

Perceived quality in video streaming platforms includes users’ subjective assessments of the content’s technical and aesthetic qualities and the platform’s overall experience (Fotis, 2015). Users evaluate quality based on video resolution, audio clarity, buffering, and seamless playback (Bhargava et al., 2019). A consistently high-definition content platform and the mitigation of technical glitches and slow loading times shape users’ quality perceptions.

Users judge quality based on content and production values (Mackiewicz & Yeats, 2014). Cinematography, visual effects, sound design, and acting are examples. High-quality, well-crafted content enhances the immersive experience and gives users a sense of satisfaction that their subscription is providing them with high-quality content (Paulauskas et al., 2023). Technical performance, defined as the absence of unexpected system crashes or long buffering periods, is crucial to maintaining users’ engagement and fostering a positive relationship with the platform.

Platforms that prioritize high-quality content delivery build trust and professionalism. This significantly affects users’ value perceptions. Platform reliability and quality experience strongly influence users’ value perception and subscription intention (Guo, 2022). Thus, prioritizing technically superior content and a seamless viewing experience shapes users’ value perception and subscription intention.

3.1.2. Perceived content relevance

The extent to which content offerings match users’ preferences, interests, and viewing patterns determines content relevance (Barragáns-Martínez et al., 2010). The platform’s ability to accommodate a variety of user tastes and preferences affects their perceived value and subscription rate. Users want a comprehensive platform with a wide range of genres, languages, and themes to find content that suits their tastes (Hosey et al., 2019).

Personalized content recommendations boost content relevance beyond measure (Kim et al., 2007). Platforms use algorithms to recommend content based on users’ historical viewing patterns, ratings, and interactions, creating a highly customized user experience (Kim et al., 2007). Personalization improves user engagement and satisfaction. Tailoring options increases the likelihood of meeting user preferences. This increased personalization improves user engagement and satisfaction. Thus, users feel more understood by the platform about their preferences and principles, increasing their relevance and intrinsic value (Kee & Yazdanifard, 2015). Users’ expectations of new and engaging content affect their perception of content relevance. New content across genres on platforms boosts users’ curiosity and exploration (Kee & Yazdanifard, 2015). A diverse content library and personalized recommendations help users perceive a platform as offering many relevant options. This affects users’ value perception and platform subscription intentions.

3.1.3. Perceived variety

The concept of perceived variety refers to users’ subjective perception of the platform’s content diversity (Tu et al., 2021). A platform can reach a wider audience with diverse preferences by offering a variety of content genres, formats, and types (Moring, 2007). Diverse content caters to user preferences and facilitates communal viewing among households or social groups (Huang et al., 2020).

Diverse content reduces monotony and helps find content for different emotions. People often want different entertainment experiences. For instance, a person may prefer a thought-provoking documentary one day and lighthearted comedy the next. This tendency to switch genres and themes in audiovisual content consumption warrants study (Bolander & Locher, 2014). Platforms that accommodate such variability create a sense of inclusivity by acknowledging and addressing diverse interests. Unique and exclusive content also boosts perceived diversity. Exclusive shows, films, and original series increase the streaming service’s perceived value by enticing users. The perception of exclusivity shapes users’ perceived variety and improves their experience, increasing their intention to subscribe.

3.1.4. Perceived enjoyment

The emotional engagement and satisfaction users get from content and platform experience determines their enjoyment (See-To et al., 2012). Content that evokes positive emotions, grabs attention, and provides escapism improves users’ enjoyment (See-To et al., 2012). Engaging narratives, relatable characters, and well-crafted storylines affect user immersion and emotional connection. These elements improve the user experience and strengthen the user-content connection (Coker et al., 2017). Captivating narratives draw users into the story, immersing them in the virtual world. Relatable characters allow users to connect with virtual personas’ struggles, emotions, and motivations (Miller et al., 2023). The careful construction of storylines ensures a compelling narrative.

The consistent delivery of user-preferred content is key to platform enjoyment. Engaging and entertaining content is essential to building positive user associations with a platform. Positive reinforcement boosts people’s perception of value, making them believe their subscription always pays off. The dynamic relationship between perceived enjoyment and social interaction is important (Kim et al., 2013). Stumbling upon content that becomes a topic of discussion among friends, family, or online communities increases pleasure (Kim et al., 2013). The platform’s ability to create shared experiences boosts enjoyment and deepens engagement.

Perceived enjoyment goes beyond superficial amusement. Instead, it’s the emotional satisfaction and deep connection users feel with the content and platform (Hill, 2010). Positive emotions and sustained user engagement on platforms increase perceived enjoyment. This greatly increases value perception and subscription intent.

3.1.5. Perceived cost-benefit ratio

The perceived cost-benefit ratio measures users’ value versus subscription cost. In this study, participants cognitively evaluate the platform’s potential benefits (Lin et al., 2020). This assessment compares to the financial and non-financial costs of subscribing to said platform (Lin et al., 2020). The cognitive factor in question affects users’ value perception and subscription intention. Users value platforms for more than just content. The unique features, user-friendly interface, tailored suggestions, and 24/7 content access all add up to perceived benefits (Chung et al., 2021). Users value the accessibility of a large content repository, eliminating the need for additional purchases or rentals.

To influence the perceived cost-benefit ratio, strategies must manipulate people’s perceptions of a decision or action’s costs and benefits. This requires a thorough understanding of the factors that shape such perceptions and Platforms must establish clear and concise communication channels that explain the benefits of subscribing to engage and retain subscribers (Merkhofer, 2012). Platforms can improve user satisfaction and experience by doing so. Transparency helps users understand their subscription fee (Wan et al., 2019). Tiered pricing plans or free trials allow users to directly experience the benefits before subscribing, reducing uncertainty and shaping their value perception. Platforms that offer significant benefits that exceed subscription fees create a compelling value proposition thanks to efficient cost-benefit management (Nichol, 2001). The perception of receiving more value for the cost influences users’ attitudes towards a platform and their likelihood of subscribing.

3.1.6. Perceived personalization

Perceived personalization is users’ subjective assessment of the platform’s ability to meet their needs and habits (Mulvenna et al., 2000). Platforms can create personalized experiences that resonate with users at a deep level in the data-driven age (Mulvenna et al., 2000). The cognitive factor strongly influences users’ platform engagement and connection. Personalization occurs in content recommendations and curated playlists. Users feel platform comprehension and alignment with their tastes when content suggestions match their historical viewing patterns and preferences (Jeon et al., 2023). Providing tailored content that matches user preferences reduces cognitive load when searching for relevant information, increasing user engagement.

Personalization includes content curation and interface customization. The integration of platforms that allow users to personalize profiles, create watchlists, and configure preferences increases ownership and connection. Users feel the platform meets their needs and preferences, increasing their value and intention to subscribe. Continuously refined artificial intelligence (AI)-powered algorithms in content recommendation and personalization strategies increase user engagement and loyalty (Gregory et al., 2021). The platform’s perceived value as a companion that adapts to users’ preferences increases the likelihood of long-term subscription commitment.

Thus, perceived quality, content relevance, variety, enjoyment, cost-benefit ratio, and personalization are the key cognitive factors that affect users’ value perceptions and video streaming platform subscriptions (Wang et al., 2013). By understanding and strategically addressing each factor, platforms can create a compelling value proposition that matches user preferences and encourages long-term subscriber engagement and loyalty. Digital entertainment platforms must optimize cognitive factors to succeed in a competitive and changing market.

3.2. Journal outlets, research objective and publication year

The majority of the research pertaining to subscription behavior on video streaming platforms, as examined in this study, was disseminated through UK and European academic journals. Specifically, 10 journals based in the United Kingdom, one journal in the Netherlands, and one journal in Spain, one journal in Germany and 2 journals in Switzerland were the primary outlets for publication. Furthermore, a total of 4 scholarly articles were published in Asian academic journals, comprising two publications from South Korea, one from Pakistan, and one from China. A solitary article was published in a journal based in the United States. The chosen articles in this study were discovered to be non-specific to any particular discipline and were published across various channels, including consumer behavior, information systems, psychology, and marketing (refer to Table 2). The primary focus of this research pertains to the various factors that influence individuals’ intentions to subscribe to Video Streaming Platforms (VSPs), repurchase Over-The-Top (OTT) platforms, or continue their subscriptions to VSPs. Additionally, the study aims to examine individuals’ intentions to utilize online streaming technologies and adopt Subscription-Based Video on Demand (SVOD) streaming services. Moreover, there has been a notable increase in the publication of articles pertaining to the subscription behavior of video streaming platforms in Scopus and WoS databases in recent years. Specifically, 4 articles were published in 2023, 6 articles were published in 2022, 8 articles in 2021, 1 article in 2020 and one article in 2019. This indicates that there is a growing body of research on the subscription behavior of video streaming platforms, and the academic community is showing an increasing interest in this area of study.

Table 2. Summary of reviewed articles.

Authors	Title	Year	Journal outlet/country	Theoretical foundation	Research approach	Method of data collection	Data processing and analysis	Survey instrument	Sample size
Chakraborty D., Siddiqui M., Siddiqui A., Paul J., Dash G., Mas F.D.	Watching is valuable: Consumer views – Content consumption on OTT platforms	2022	Journal of Retailing and Consumer Services (UK)	Theory of consumption values	Quantitative	Non-Probability sampling, convenience sampling	SPSS (ver.26) AMOS.	Online survey	1309 responses
Yoelianto F., Tjhin V.U.	SOCIAL ISOLATION, A NEW VARIABLE AFFECTING BEHAVIORAL INTENTION TO USE SUBSCRIPTION VIDEO ON DEMAND	2022	Journal of Theoretical and Applied Information Technology (Pakistan)	Modified Unified theory of adoption and the use of technology (UTAUT)	Quantitative	Probability sampling method, simple random sampling type	Structural Equation Modeling (SEM) method through the SmartPLS (Partial Least Square) application.	Online survey	140 users
Zahara N., Wulandari N.C., Kairupan J.H., Hidayat Z.	What drives Indonesians Subscribe and Push the Distribution of Disney + Hotstar?	2022	Journal of Distribution Science (South Korea)	Marketing Mix	Quantitative()	Non-Probability sampling,purposive sampling	Structural Equation Modeling (SEM) method with WarpPLS	Online survey	316 respondents
Guo M.	The Impacts of Service Quality, Perceived Value, and Social Influences on Video Streaming Service Subscription	2022	JMM International Journal on Media Management (UK)	Technology acceptance model (TAM), value-based adoption model (VAM), innovation diffusion theory, and planned behavior theory	Quantitative	Not mention	Multiple regression analysis	Online survey	834 online video streaming users in the U.S
Camilleri M.A., Falzon L.	Understanding motivations to use online streaming services: integrating the technology acceptance model (TAM) and the uses and gratifications theory (UGT)	2021	Spanish Journal of Marketing – ESIC (Spain)	Technology acceptance model (TAM) and uses and gratifications theory (UGT)	Quantitative	Not mention	Structural equations partial least squares	Online survey	491 Higher education students in a Southern European university
Nagaraj S., Singh S., Yasa V.R.	Factors affecting consumers’ willingness to subscribe to over-the-top (OTT) video streaming services in India	2021	Technology in Society(UK)	Not mention	Quantitative	Non-Probability sampling,snowball sampling technique	SPSS	Online survey	468 responses
Arun T.M., Singh S., Khan S.J., Akram M.U., Chauhan C.	Just One More Episode: Exploring Consumer Motivations for Adoption of Streaming Services	2021	Asia Pacific Journal of Information Systems (South Korea)	Unified Theory of Acceptance and Use of Technology (UTAUT2) model	Quantitative	Not mention	Structural Equation Model (SEM)	Online survey	337 Indian respondents(consumers with diverse backgrounds in three biggest metropolitan cities of India - Delhi, Mumbai and Bangalore)
Sardanelli D., Vollero A., Siano A., Bottoni G.	Lowering the pirate flag: a TPB study of the factors influencing the intention to pay for movie streaming services	2019	Electronic Commerce Research(US)	Theory of planned behavior	Quantitative	Not mention	Structural equation modeling	Online survey	453 respondents
Walsh, Philip; Singh, Ranjita	Determinants of Millennial behaviour towards current and future use of video streaming services	2021	YOUNG CONSUMERS (UK)	Technology acceptance model, perceived values and social identity theory	Quantitative	Non-Probability sampling, convenience sampling	Factor analysis and multiple regression	Survey	292 university undergraduates
Kwak, Kyu Tae; Oh, Chae Ju; Lee, Sang Woo	Who uses paid over-the-top services and why? Cross-national comparisons of consumer demographics and values	2021	Telecommunications Policy (UK)	Value theory	Quantitative	Not mention	Tobit model and Seemingly Unrelated Estimation (SUE) method	Online survey	Survey responses from 1400 OTT service users (200 people per country) in their 20s–70s were collected.
Liao, Shu-Hsien; Widowati, Retno; Puttong, Pimchanok	Data mining analytics investigate Facebook Live stream users’ behaviors and business models: The evidence from Thailand	2022	Entertainment Computing (Netherlands)	Not mention	Quantitative	Data mining analytic methods	IBM SPSS Modeler	Online survey	3354 questionnaires were returned in this study
Kuscu-Ozbudak, Seda	The role of subtitling on Netflix: an audience study	2021	Perspectives:Studies in Translation Theory and Practice (UK)	Not mention	Qualitative	Purposive sampling	Thematic analysis	Interview, Focus group interview	9 users of Turkish millennials about Netflix
Tsai L.L.	A deeper understanding of switching intention and the perceptions of non-subscribers	2023	Information Technology and People (UK)	Theory of population migration,Push-pull-mooring (PPM) theory	Quantitative	Not mention	Partial least squares multi-group analysis (PLS-MGA)	Online questionnaire surveys	446 free users were collected from Facebook and Line
Kwon Y.; Park J.; Son J.-Y.	Accurately or accidentally? Recommendation agent and search experience in over-the-top (OTT) services	2021	Internet Research(UK)	Not mention	Quantitative	Not mention	SEMPLS	online survey	212 paid Netflix subscribers in Korea
Redondo I.; Serrano D.	Giants with Feet of Clay? An Inquiry into User Payment Patterns for Subscription Video-on-Demand Services	2023	Administrative Sciences (Switzerland)	Social cognitive theory	Quantitative	Not mention	Multinomial logistic regression model	Cross-sectional survey from Spain	1420 participants of SVOD users
Lim C.T.N.	Assessing the Consumption Pattern and Expenditure of Media Streaming Platforms in the Philippines	2022	Review of Integrative Business and Economics Research(China)	The uses and gratifications (U&G) theory, Technology Acceptance Model (TAM)	Quantitative	Descriptive methods of analysis-Simple random sampling technique	Not mention	Online questionnaire surveys	855 users, 703 of whom are media streaming subscribers.
Liu L.; Jin B.; Shi Y.; Hu L.; Yang J.; Mi C.	Motivating Subscription of Video-on-Demand in Mainland China: A Push-Pull-Mooring Perspective	2023	Communications in Computer and Information Science (Germany)	Push-pull-mooring theory	Quantitative	Not mention	SmartPLS, PLS-SEM	Online survey	167 respondents
Kim Y.; Kim B.	Selection attributes of innovative digital platform-based subscription services: A Case of South Korea	2020	Journal of Open Innovation: Technology, Market, and Complexity (Switzerland)	Not mention	Quantitative	Not mention	SPSS, AMOS	Online survey	434 subscription service users in Korea
Koul, S; Ambekar, SS; Hudnurkar, M	Determination and ranking of factors that are important in selecting an over-the-top video platform service among millennial consumers	2021	INTERNATIONAL JOURNAL OF INNOVATION SCIENCE(UK)	Not mention	Quantitative	Purposive sampling	SPSS	Online survey	409 qualifified
Talwar, S; Kaur, P; Kumar, S; Laroche, M; Dhir, A	Caged, helpless but not bored: consumption values derived from over-the-top platforms during pandemic	2023	INFORMATION TECHNOLOGY & PEOPLE (UK)	Theory of consumption value (TCV)	Mixed-method approach	Snowball sampling method	Content analysis of qualitative data, CB-SEM	Interviews; online survey	Interviews of 12 current OTT platform users；Survey of 371 existing users;

3.3. Research approach, method of data collection and survey instrument

As shown in Table 2, quantitative methods are used in all 18 empirical articles, one article used qualitative and one article used mixed method. In the method of data collection: 2 articles use probability sampling method, simple random sampling type. 7 articles use Non-Probability sampling, including convenience sampling (2), purposive sampling (3), snowball sampling technique (2). One article use data mining analytic methods. 10 articles do not mention about detailed method of data collection. In survey instrument, 16 articles use online survey, 1 article use survey, one article used cross-sectional survey, one article used focus group interview, one article used Interviews and online survey. Different analysis methods are used to study consumer subscription behavior or intention of video streaming platforms. Five articles use Structural Equation Modeling (SEM) method through the SmartPLS (Partial Least Square) application. One article uses Structural Equation Modeling (SEM) method with WarpPLS. Another three articles use Structural Equation Modeling (SEM). Besides, five articles use SPSS. And 4 articles use multiple regression. Only one article uses Tobit model and Seemingly Unrelated Estimation (SUE) method. And one article use content analysis, another one use thematic analysis. According to my research, different scholars have used different quantitative research methods and data collection methods for the research of subscription intention or subscription behavior of video streaming platforms, which provides reference for future research. In addition, only 1 qualitative research method was used in the study. Whether the future research can be more comprehensive in terms of research methods has attracted the attention of scholars (Camilleri & Falzon, 2021). This finding reveals that the present state of research on subscription intention emphasis on theory testing (quantitative studies) rather than theory building (qualitative studies). And in future research, for subscription behavior in video streaming platform, it should focus on quantitative studies. In particular, different method of data collection and survey instrument should be applied in future.

3.4. Research context and unit of analysis

The articles included in this systematic review primarily examine the various factors that influence individuals’ subscription intentions or behaviors towards video streaming platforms. The research context pertains to the examination of video streaming platforms across various countries and regions. Specifically, the focus is on Asia, including India (3), Indonesia (2), and Thailand (1); Europe, encompassing the UK (1) and Italy (1); and North America, consisting of Canada (1) and the US (1) (Table 3). Additionally, another article explores the context of video streaming platforms with diverse national backgrounds, namely Britain, China, France, Germany, Japan, South Korea, and the United States. The units of analysis in each article are the individuals who utilize the aforementioned video streaming platforms. Out of the total number of articles, nine of them pertain to individuals who utilize more than two video streaming platforms. In future research endeavors, it is imperative to broaden the scope of investigation pertaining to video streaming platforms by examining subscription intention or behavior across diverse countries and cultural contexts. Historical research has predominantly concentrated on developed nations. However, there has been a shift in focus towards emerging economies in recent times. In subsequent investigations, it is imperative to allocate greater attention towards the subscription intention and behavior of emerging economies. Additionally, the inclusion of users across multiple platforms will be expanded. Furthermore, it would be beneficial to conduct comparative analyses among various platforms for future research purposes.

Table 3. Research context and unit of analysis.

Authors	Title	Context	Analysis units
Chakraborty D., Siddiqui M., Siddiqui A., Paul J., Dash G., Mas F.D.	Watching is valuable: Consumer views – Content consumption on OTT platforms	OTT platforms in India	Consumers of Over-the-top (OTT) platforms in India from different city
Yoelianto F., Tjhin V.U.	SOCIAL ISOLATION, A NEW VARIABLE AFFECTING BEHAVIORAL INTENTION TO USE SUBSCRIPTION VIDEO ON DEMAND	Streaming services / video on demand / over the top media services in Indonesia	Users of SVOD services in Indonesia
Zahara N., Wulandari N.C., Kairupan J.H., Hidayat Z.	What drives Indonesians Subscribe and Push the Distribution of Disney + Hotstar?	Disney + Hotstar in Indonesia.	Users who have ever known about Disney + Hotstar in Indonesia
Guo M.	The Impacts of Service Quality, Perceived Value, and Social Influences on Video Streaming Service Subscription	Online video streaming services in the U.S	Online video streaming users in the U.S
Camilleri M.A., Falzon L.	Understanding motivations to use online streaming services: integrating the technology acceptance model (TAM) and the uses and gratifications theory (UGT)	Motivation of use online streaming technologies in UK	Users to use online streaming technologies in UK
Nagaraj S., Singh S., Yasa V.R.	Factors affecting consumers’ willingness to subscribe to over-the-top (OTT) video streaming services in India	Indian OTT service market	Consumers of Over-the-top (OTT) platforms in India
Arun T.M., Singh S., Khan S.J., Akram M.U., Chauhan C.	Just One More Episode: Exploring Consumer Motivations for Adoption of Streaming Services	Two models of streaming services, standalone streaming services and bundled streaming services in India	Consumers of SVOD in India
Sardanelli D., Vollero A., Siano A., Bottoni G.	Lowering the pirate flag: a TPB study of the factors influencing the intention to pay for movie streaming services	Online movie streaming services in Italy	Italian Internet users that are virtually willing to subscribe a streaming on-demand service
Walsh, Philip; Singh, Ranjita	Determinants of Millennial behaviour towards current and future use of video streaming services	Video streaming applications in Canada	Millennial’s users of video streaming services
Kwak, Kyu Tae; Oh, Chae Ju; Lee, Sang Woo	Who uses paid over-the-top services and why? Cross-national comparisons of consumer demographics and values	Paid content streaming, or over-the-top (OTT) media services in Britain, China, France, Germany, Japan, South Korea, and the United States	Consumers of over-the-top (OTT) media services in Britain, China, France, Germany, Japan, South Korea, and the United States
Liao, Shu-Hsien; Widowati, Retno; Puttong, Pimchanok	Data mining analytics investigate Facebook Live stream users’ behaviors and business models: The evidence from Thailand	FB Live in Thailand	Consumers of FB Live in Thailand
Kuscu-Ozbudak, Seda	The role of subtitling on Netflix: an audience study	Netflix in Turkey	Users of Turkish millennials about Netflix
Tsai L.L.	A deeper understanding of switching intention and the perceptions of non-subscribers	Free-to-paid switching behavior in OTT platform in Taiwan, China	Free users were collected from Facebook and Line
Kwon Y.; Park J.; Son J.-Y.	Accurately or accidentally? Recommendation agent and search experience in over-the-top (OTT) services	Subscribers’ continuous subscription behavior over-the-top (OTT) services in Korea	Paid Netflix subscribers in Korea
Redondo I.; Serrano D.	Giants with Feet of Clay? An Inquiry into User Payment Patterns for Subscription Video-on-Demand Services	Subscription Video-on-Demand Services in Spain.	SVOD users in Spain
Lim C.T.N.	Assessing the Consumption Pattern and Expenditure of Media Streaming Platforms in the Philippines	Consumption Pattern and Expenditure of Media Streaming Platforms in the Philippines	Users of media streaming platforms
Liu L.; Jin B.; Shi Y.; Hu L.; Yang J.; Mi C.	Motivating Subscription of Video-on-Demand in Mainland China: A Push-Pull-Mooring Perspective	Subscription of Video-on-Demand in Mainland China	Users of video streaming platfomrs in mainland China.
Kim Y.; Kim B.	Selection attributes of innovative digital platform-based subscription services: A Case of South Korea	Innovative Digital Platform-Based Subscription Services in Korea	Subscription service users in Korea
Koul, S; Ambekar, SS; Hudnurkar, M	Determination and ranking of factors that are important in selecting an over-the-top video platform service among millennial consumers	Selecting an over-the-top video platform in India.	Participants within the age group of 18–34 from Tier I and Tier II cities, who were having or had at least one OTT platform subscription.
Talwar, S; Kaur, P; Kumar, S; Laroche, M; Dhir, A	Caged, helpless but not bored: consumption values derived from over-the-top platforms during pandemic	Subscription behavior in OTT service providers in India	Interviews of current OTT platform users; Survey of existing users

3.5. Theory

In the articles that were chosen for analysis, we have identified four distinct categories of theoretical frameworks that were employed in quantitative research studies, with a total sample size of 20 articles. The categorization of the research pertaining to two theoretical chains is presented in the main categories, with further division of research within each theoretical chain into distinct categories as presented in Figure 2. The theoretical foundation of the study was not adequately delineated in a particular article. The first primary category, which pertains to research on the adoption and dissemination of technology, is a well-established area of study within the literature on information systems (IS). The present research incorporates several theoretical frameworks that have been widely used in the field of technology adoption and usage. These include the Unified Theory of Adoption and the Use of Technology (UTAUT) proposed by Venkatesh, Morris, Davis, and Davis in 2003 (n = 1), the Unified Theory of Acceptance and Use of Technology (UTAUT2) model developed by Venkatesh et al. in 2012 (n = 1), the Technology Acceptance Model (TAM) introduced by Davis in 1989 and further expanded by Davis, Bagozzi The Technology Acceptance Theory (TAT) is a commonly employed framework for forecasting the level of acceptance exhibited by users towards technology systems. The theory of technology can be traced back to the theory of reasoned action (TRA). Ajzen (1991) also credits attitude, subjective norms, and perceived behavioral control for the development of Planned Behavior Theory (TPB). We then created the Technology Acceptance Model (TAM) to assess information system technology user behavior. Venkatesh et al. (2003) expanded the TAM and TAM2 models to create the unified theory of technology acceptance and use (UTAUT). According to Venkatesh et al. (2012) and Madanaguli et al. (2021), the UTAUT2 model expanded by adding three constructs. Recent research has examined how cognitive factors affect video streaming platform subscription intentions and behaviors. Technology acceptance models, which provide a framework for studying this relationship, have spurred this research. Thus, scholars have been able to broaden their studies and investigate the factors that affect subscription intentions and behaviors. Studies have linked consumer value, social cognition, uses and gratifications, and behavior. The study used several theoretical frameworks. Three references mentioned Sheth et al.’s (1991) Theory of Consumption Values (TCV). A citation also mentioned Kim, Chan, and Gupta’s (2007) Value-Based Adoption Model (VAM). Katz et al. (1973) used and Gratifications Theory (UGT) and Tajfel and Turner used Social Identity Theory were both cited. Product and service characteristics, emotional, and situational factors all affect perceived value. Thus, these studies evaluate perceived value from multiple perspectives (Aguiar, 2017). A scholarly article examined how the marketing mix affects video streaming platform subscription intentions and behaviors. The author used Kotler, Wong, Saunders, and Armstrong’s (2005) marketing mix theory. This discovery suggests that subscription behavior research lacks conceptual advances like integrated perspectives, multiple theories, and interdisciplinary approaches. Thus, future research should broaden this line of inquiry’s theoretical scope by incorporating multiple theories, particularly in information technology, social psychology, marketing, and media studies.

Figure 2. The theoretical foundation of the studies reviewed.

3.6 Variables

Repurchase intention, SVOD behavior intention, willingness to pay, willingness to continue and subscribe to video streaming services, intention to use, SI, and behavioral intention were the dependent variables. Consumer behavior included paid OTT service usage changes. This study found that most articles focused on consumer behavior intention rather than behavior. There is lack of a standard name and definition for the dependent variable in consumer behavior intention for video streaming platforms. Each article’s dependent variable nomenclature and conceptualization (Table 3) inspired this study. This research should use "subscription intention" instead of "subscription model" to determine video streaming consumer behavior (Camilleri & Falzon, 2021). Differences of opinion among scholars. Video streaming platforms could incorporate consumer behavior intention in future research.

Table 4 lists consumer, video, and platform variables as research framework categories. Many factors affect consumer variables. Consumer values include convenience, money, emotions, functions, social, epistemic, and conditional. Trust, social influence, corona fear, social isolation, perceived value, perceived risk, ritualized use, instrument use, habit, hedonic motivation, perceived subjective norms, attitude, moral judgement, identity salience, warm relationship with others (WRO), sense of belonging (SOB), self-respect (SER), self-fulfillment (SEF), fun and enjoyment in life (FEL), and sense of accomplishment (SOA). The theory of consumer value explains how five perceived values influence product or service use. Two viewpoints compare value. Utility and economic theory are the first area, while utility and hedonic perceptions are the second. Many studies (Karjaluoto et al., 2021; Kaur et al., 2021; Talwar et al., 2020) have used the second approach to study consumer product and service selection based on values, emotional, conditional, perceived, functional, and social values (Chakraborty et al., 2023). Chakraborty et al. (2022) found that trust mediates the relationship between Convention, Monetary, Emotional, Functional, and OTT platform repurchase intention. The Millennium generation uses video streaming for social and emotional reasons, say Walsh and Singh (2022). Guo (2022) examined how perceived benefit—enjoyment and controllability—affects consumers’ video streaming service use and subscription. Guo’s study suggests perceived benefits affect consumer behavior (Guo, 2022). Yoelianto and Tjhin (2022) examined behavioral intention using social influence and coronavirus fear. Social influence did not significantly improve behavioral intention, according to Yoelianto and Tjhin (2022). Social influence is how much significant others affect a person’s thoughts, attitudes, and actions. Guo (2022) predicts that social influence, particularly normative pressure from social norms, will affect consumers’ subscription-based video streaming service use. The empirical study by Madanaguli et al. (2021) examined social impact and SVOD customer adoption. Social impact increased consumers’ SVOD adoption (Madanaguli et al., 2021). Yoelianto and Tjhin (2022) studied SVOD use and social isolation. Habit is how automatic people think video streaming platforms are (Yoelianto & Tjhin, 2022). According to Madanaguli et al. (2021), consumers’ habits affect their SVOD adoption intentions. Hedonic motivation is video streaming platform enjoyment. Hedonic motivation affects consumers’ SVOD adoption intentions, according to Madanaguli et al. (2021). In their empirical study, Sardanelli et al. (2019) examine movie streaming service payment intention factors. Attitudes, participating products, moral judgements, and past behavior frequency most explained this intention (Sardanelli et al., 2019). Kwak et al. (2021) found that a desire to form warm relationships, have fun, achieve self-fulfillment, and feel accomplished directly influences the use of paid over-the-top (OTT) services.

Table 4. The dependent variables, independent variables mediator and moderater of the studies reviewed.

Authors	Title	Dependent variables	Independent variables	Mediator	Moderater
Chakraborty D., Siddiqui M., Siddiqui A., Paul J., Dash G., Mas F.D.	Watching is valuable: Consumer views – Content consumption on OTT platforms	Repurchase Intention	Functional Values, Social values, Emotional values, Epistemic Values, Conditional Values	Trust	Age, Gender, Hoursehold Size
Yoelianto F., Tjhin V.U.	Social Isolation, A New Variable Affecting Behavioral Intention To Use Subscription Video On Demand	Behavior intention to use SVOD	Effort Expectancy, Social Influence, Facilitating Condition, Price Value, Content, Social Isolation		Corona Fear
Zahara N., Wulandari N.C., Kairupan J.H., Hidayat Z.	What drives Indonesians Subscribe and Push the Distribution of Disney + Hotstar?	Willingness to Pay	Brand Relationship, Decisive subscription price, Content, Brand Awareness, eWOM
Guo M.	The Impacts of Service Quality, Perceived Value, and Social Influences on Video Streaming Service Subscription	Willingness to continue and subscribe to video streaming services	Service quality, Perceived benefits, Social influences
Camilleri M.A., Falzon L.	Understanding motivations to use online streaming services: integrating the technology acceptance model (TAM) and the uses and gratifications theory (UGT)	Intention to use	Perceived ease of use, perceived usefulness, Ritualized use, Instrument use
Nagaraj S., Singh S., Yasa V.R.	Factors affecting consumers’ willingness to subscribe to over-the-top (OTT) video streaming services in India	Not mention	Not mention
Arun T.M., Singh S., Khan S.J., Akram M.U., Chauhan C.	Just One More Episode: Exploring Consumer Motivations for Adoption of Streaming Services	SVOD behavioral intention	Price Value, Habit, Hedonic Motivation, Facilitating Conditions, Social Influence, Effort Expectancy, Performance Expectancy
Sardanelli D., Vollero A., Siano A., Bottoni G.	Lowering the pirate flag: a TPB study of the factors influencing the intention to pay for movie streaming services	Subscription intention (SI)	Perceived subjective norms about digital piracy (SN), Involvement with the movie category (INV), Frequency of past behavior (FPB)	Perceived risk in online buying (RISK), Attitude toward the subscription of movie streaming services (ATT), Moral judgement about the illegal acquisition of movies (MORAL)
Walsh, Philip; Singh, Ranjita	Determinants of Millennial behaviour towards current and future use of video streaming services	Behavioural intent; Hours of use	Ease of use, Convenience value, Monetary value, Emotional value, Social value; Mediator: Identity salience
Kwak, Kyu Tae; Oh, Chae Ju; Lee, Sang Woo	Who uses paid over-the-top services and why? Cross-national comparisons of consumer demographics and values	Changes in the usage of paid OTT services	Warm relationship with others (WRO), Sense of Belonging (SOB), Self-respect (SER), Self-fulfillment (SEF), Fun & enjoyment in Life (FEL), Sense of accomplishment (SOA)
Liao, Shu-Hsien; Widowati, Retno; Puttong, Pimchanok	Data mining analytics investigate Facebook Live stream users’ behaviors and business models: The evidence from Thailand	Not mention	Cluster-1 :K-pop boy group;Cluster-2:Student bloggers group;Cluster-3:Fanfiction group
Kuscu-Ozbudak, Seda	The role of subtitling on Netflix: an audience study	Reasons for Netflix subscription	Content-oriented reasons
Tsai L.L.	A deeper understanding of switching intention and the perceptions of non-subscribers	Switching intention of non-subscribers	Perceived intrusiveness, alternative attractiveness, Habit; Perceived convenience, perceived enjoyment		Habit
Kwon Y.; Park J.; Son J.-Y.	Accurately or accidentally? Recommendation agent and search experience in over-the-top (OTT) services	Intention to continue a subscription	Perceived diagnosticity and perceived serendipity	Decision satisfaction
Redondo I.; Serrano D.	Giants with Feet of Clay? An Inquiry into User Payment Patterns for Subscription Video-on-Demand Services	Users pay for the full subscription fee; Users share the subscription fee; Users pay anything at all	The attitude toward novelty, attitude toward quality, level of cosmopolitanism, price sensitivity, level of VOD use, and level of internet use
Lim C.T.N.	Assessing the Consumption Pattern and Expenditure of Media Streaming Platforms in the Philippines	Actual Use	Self presentation, social connection,Entertainment,Irritation,Accesibility, Extent list of content, Perceived ease of use, Price competiveness, Convenience, Minimal storage requirements.Mediator:Behavior intention to use
Liu L.; Jin B.; Shi Y.; Hu L.; Yang J.; Mi C.	Motivating Subscription of Video-on-Demand in Mainland China: A Push-Pull-Mooring Perspective	Subscription Behavior	Fush factors: Time Cost, Functional Deprivation, Pull factors: Non-substitutability, Perceived Enjoyment, Mooring factors: Consumer Devotion, Price Cost.	Intention to subscribe
Kim Y.; Kim B.	Selection attributes of innovative digital platform-based subscription services: A Case of South Korea	Continuous use intentions	Selection attributes of subscription services: content superiority, service differentiation.
Koul, S; Ambekar, SS; Hudnurkar, M	Determination and ranking of factors that are important in selecting an over-the-top video platform service among millennial consumers	Decision-making of a consumer while opting for an OTT service platform	Subscription fee, Wide content range, Exclusive and original content, Live entertainment/sports, Trending content, Favorite content, Platform’s appeal and features, Local language content, A good marketing strategy
Talwar, S; Kaur, P; Kumar, S; Laroche, M; Dhir, A	Caged, helpless but not bored: consumption values derived from over-the-top platforms during pandemic	Continued intentions to use	Conditional value (CV), Functional value quality (FVQ), Epistemic value (EPV), Social value (SV)	Functional value price (FVP), Emotional value (EMV);	Premium subscription purchased following the onset of the pandemic;Increased viewing time following the onset of the pandemic.

Key video variables are price and content. Venkatesh et al. (2012) define prices as goods and services’ financial costs. In streaming platforms, it’s video value. Madanaguli et al. (2021) and Yoelianto and Tjhin (2022) found that consumers are more likely to buy online video content if it’s affordable. Content-based subscriptions drive video streaming platforms. Content boosts video streaming customer subscriptions, according to several studies.

Platform variables include effort, facilitating condition, performance, brand relationship, decisive subscription price, brand awareness, eWOM, service quality, and usability. The UTAUT2 model states that effort, facilitating condition, and performance expectancy affect behavioral intention, according to Venkatesh et al. (2012). Yoelianto and Tjhin (2022) and Arun et al. (2021) found that effort expectancy and facilitation conditions significantly impact SVOD use. Performance expectancy was key to Arun et al.’s (2021) study. Zahara et al. (2022) examined how brand relationship, decisive subscription price, brand awareness, and eWOM affect Disney + Hotstar purchases. Customers evaluate video streaming platforms’ service quality. Guo (2022) proposed a six-dimensional streaming media service evaluation framework. These dimensions are system reliability, content quality, customer service, access, search, and recommender system quality. Guo (2022) examined how video streaming service reliability affects consumer subscription behavior. According to Venkatesh et al. (2003), technology’s perceived usefulness and ease of use affect use intentions. Online streaming technologies’ ease of use and perceived usefulness positively and significantly affect people’s intentions to use video streaming platforms, according to Camilleri and Falzon (2021).

This discovery shows that subscription behavior research and video streaming platform dependent variable naming and definition are inconsistent. Future research must resolve these issues. The study divides variables into consumer, video, and platform themes. Future research should expand theme-related variables in this domain. This requires multifaceted and multidimensional investigations to understand video streaming platform subscription behavior. The creation of new research questions and frameworks advances this field’s knowledge. To understand video streaming platform subscription behavior, future research should combine consumer, video, and platform variables.

4. Discussion

A systematic literature review on the role of cognitive factors in consumers’ perceived value and subscription intention of video streaming platform filled the research gap. The focus was on cognitive factors that influence consumers’ platform subscriptions. The literature suggests six key factors: perceived quality, content relevance, variety, enjoyment, cost-benefit ratio, and personalization. These cognitive factors influence video streaming platform subscriptions. The combination of utilitarian value (price and quality), hedonic value (enjoyment and pleasure), cognitive value (novelty and curiosity), and conditional value (discounts and promotions) increased the intention to repurchase on the OTT platform. The OTT platform can tailor content to consumer values. Marketers prioritize trust-building to build customer loyalty and keep existing users using the company’s products. The findings can inform government OTT policy (Chakraborty et al., 2022). Guo (2022) found three predictors of consumer subscriptions. Video streaming media quality, value, and social impact are among these factors. The study found that the five factors within these three dimensions are crucial. This study examines what makes consumers keep and subscribe to online video streaming services. It examines how service system reliability, perceived compatibility, enjoyment, controllability, and regulatory pressure (social norms) affect consumers’ willingness to use these services. In practice, industry professionals can use multidimensional scales to monitor customer service quality. Video streaming services allow users to watch a variety of content at their convenience with flexible scheduling and viewing modes. Thus, these services improve video streaming. Enhancing hedonic benefits may affect value perception and behavior (Guo, 2022). Madanaguli et al. (2021) found that bundled service unit price value may outweigh content quality and habit. Given the power of social influence, SVOD providers should actively pursue content licensing agreements to grow their user base. Additionally, the SVOD platform must invest in marketing to promote its content and attract nonusers. All six variables in the Unified Theory of User Acceptance and Use of Technology 2 (UTAUT2) model affect SVOD adoption. Gender moderation studies show that women use Subscription Video-On-Demand (SVOD) services more than they do hedonistically. Habitual behavior, cost, and convenience explain this preference for SVOD services. The study suggests that service providers should prioritize pricing strategies and offer cheaper options for young customers with low price awareness. Kwak et al. (2021) examined how values and psychological traits affect paid over-the-top (OTT) service use. Our comprehensive transnational analysis found that user attributes and values affect OTT service use differently across cultures. This study shows that consumer value influences paid over-the-top (OTT) service adoption and use. In addition, user income appears to have a similar effect on OTT service payment across countries.

Yoelianto and Tjhin (2022) found a positive and statistically significant relationship between SVOD platforms’ content quantity and quality and customers’ behavioral intention to use them. SVOD service providers can improve content quality and quantity by partnering with other production companies to create exclusive content for their platforms. SVOD service providers can also analyze customer preference data to improve operations. If the government implements social distancing policies, companies can customize customer packages. Unique pricing structures or discounts can do this. Social isolation significantly affects SVOD use intentions (Yoelianto & Tjhin, 2022). Zahara et al. (2022) found that brand relationship, price, content, and brand awareness increase Indonesian consumers’ willingness to pay for Disney + Hotstar. Disney+, Hotstar, and other streaming services use social media to maximize reach and engagement. These platforms also offer cheap, high-quality films (Zahara et al., 2022). Nagaraj et al. (2021) investigated what drives SVoD subscriptions. This research helps understand consumers’ needs in this area. Thus, video quality and home viewing experience affect cable TV subscription retention among these consumers. SVoD services are appealing because they allow viewers to watch their favorite shows anytime (Nagaraj et al., 2021).

Sardanelli et al. (2019) found that online shopping attitudes strongly influence purchase behavior. Products appear to have affected both direct and indirect movie streaming service subscription intentions. The normative framework around digital piracy helps people subscribe. The present study found that price does not affect item use. Sardanelli et al. (2019) found that identity saliency affects video stream use.

4.1. Implication of the study

This study has practical implications for video streaming platforms and digital entertainment professionals. The result found cognitive factors like perceived quality, content relevance, variety, enjoyment, cost-benefit ratio, and personalization can inform strategic choices to improve user experiences and subscription intentions.

Video streaming platforms can increase the content quality to subscription - film scripts, cinematography, visual effects, sound design and performances. In addition, the marketers of video streaming platform should improve the reliability and quality experience to increase the perceived value of viewers, finally it will solve the problems of increasing subscription intention in video streaming platforms, especially in the context of developing countries. While video streaming platforms in developing countries are growing rapidly, the quality and diversity of video content are not being effectively addressed, which limits the growth of viewers’ subscription intentions. Optimizing playback continuity and reducing technical interruptions greatly affect users’ quality perception. Personalized content recommendations and customizable interfaces may increase platform engagement. Algorithms that adapt to user preferences can boost engagement and subscription duration. Platforms that emphasize diverse content across genres and themes can appeal to more people, increasing their perceived value. Exclusive content diversifies offerings, attracting subscribers seeking unique content. Create content that makes users feel good about the platform. Delivering content that matches users’ preferences can boost satisfaction and loyalty. Effectively communicating subscription plan benefits versus costs can reduce ambiguity and increase perceived value. Tiered pricing or free trials can help users understand the value proposition.

The findings of this study contribute to the theoretical understanding of digital entertainment consumer behavior. In particular, they improve and expand existing models and frameworks. This study clarifies the cognitive factors that affect consumers’ value perceptions of video streaming platforms, improving perceived value theory. The widely accepted factors provide complex value evaluations. Technology adoption models can emphasize cognitive factors’ effects on users’ digital platform adoption and interaction. Understanding these factors helps explain user adoption. The research supports personalization and engagement theories by showing that personalization strengthens users’ platform affiliations. The findings emphasize the importance of active participation-focused content. This research also helps us understand digital entertainment user behavior by revealing how cognitive factors affect subscription decisions. This information adds to digital media and subscription-based service consumption literature.

In summary, the study’s theoretical contributions help us understand digital entertainment consumer behavior and its practical implications help industry strategies optimize user experiences. Using cognitive factors, professionals can increase the perceived value of their platforms, encouraging user participation and loyalty.

4.2. Limitations

The study examines how cognitive factors affect consumers’ value perception and intention to subscribe to video streaming platforms. This study provides valuable insights. It is important to recognize constraints that may limit the extent and relevance of these results.

The study emphasizes perceived quality, content relevance, variety, enjoyment, cost-benefit ratio, and personalization. This method yields important user decision-making insights. It is important to recognize that consumer behavior is a complex interaction of cognitive and contextual factors. Social influence, brand loyalty, and perceived risk may influence subscription decisions. Future research may add these dimensions to better understand the complex cognitive processes involved.

Participant subjectivity and memory retrieval can bias self-reported data, a common consumer behavior research method. Self-reporting provides insights into participants’ thoughts, emotions, and perceptions but may not accurately represent their cognitive processes. Thus, future studies may include behavioral or physiological indicators to improve cognitive factor assessments’ objectivity. Triangulation of multiple data sources would strengthen and verify research results. Consider how the study’s sample composition may affect its applicability to a larger population. The findings may not apply to more diverse populations due to cultural or demographic bias. Future research must prioritize inclusivity by including a more diverse range of participants that adequately represent various cultural backgrounds because cultural nuances strongly influence consumer perceptions and behaviors. This approach would provide a broader view of cognitive factors in different contexts. The study’s focus on specific platforms may introduce platform-specific biases, influencing the findings. Different video streaming platforms have different content libraries, interfaces, and features that can affect cognitive responses. Future research may use a comparative methodology to understand the phenomenon across multiple platforms. This approach would help identify shared characteristics and cognitive factor differences across platforms, deepening research understanding. A promising future research direction is the interaction between cognitive factors and external influences like culture and rapid digital advancements. Longitudinal studies of users’ cognitive factors and subscription intentions can reveal the complex dynamics of changing preferences and behaviors. The temporal perspective can help researchers and industry practitioners adapt to changing consumer preferences. Video streaming platforms must understand and strategically use these cognitive factors to improve value perceptions and subscriber engagement. Scholars can improve our understanding of consumer behavior in the dynamic context of digital entertainment by acknowledging and examining its limitations and exploring future research avenues.

5. Conclusions

In conclusion, this study examined the complex interaction of cognitive variables that affect consumers’ value perception and video streaming platform subscription intentions. The cognitive factors perceived quality, content relevance, variety, enjoyment, cost-benefit ratio, and personalization explain user decision-making. This study’s comprehensive literature review revealed how these factors collectively affect users’ perceptions and preferences.

The findings have major implications for industry professionals developing compelling value propositions and improving user engagement. Platforms can meet changing user expectations by prioritizing technical reliability, tailored content suggestions, a wide range of offerings, emotionally engaging content, clear benefits communication, and customizable experiences. These implications are especially important in the dynamic digital environment of the global pandemic and rapid technological progress.

This study also advances consumer behavior theory by incorporating video streaming platforms into current models. The findings improve our understanding of perceived value theory, technology adoption models, personalization theories, and engagement frameworks. This study illuminates cognitive factors’ complex effects on users’ decision-making in the digital age, expanding the theoretical framework for user behavior.

It is important to acknowledge this study’s limitations, such as its narrow focus on cognitive factors and its use of self-reported data. However, these constraints offer opportunities for future research to uncover untapped areas and use novel methods. This study examines cognitive factors to explain users’ complex decision-making processes on dynamic video streaming platforms. This research helps industry practitioners and researchers improve their digital entertainment knowledge and methods by connecting theoretical concepts with practical applications. The evolving digital landscape ensures that this study’s findings remain relevant and useful in navigating consumer preferences and subscription intentions.

Authors’ Contribution

The authors confirm contribution to the paper as follows: study conception and design: Tong Wu, Nan Jiang; data collection, analysis and interpretation of results: Tong Wu, Mobai Chen; draft manuscript preparation: Tong Wu, Thivashini B Jaya Kumar. All authors reviewed the results and approved the final version of the manuscript.

Disclosure statement

The authors declare that there is no conflict of interest.

Data availability

The data that support the findings of this study are available upon request from the corresponding author.

Additional information

Notes on contributors

Tong Wu

Tong Wu is studying PHD in business at Taylor University, Malaysia. Presently she is a lecturer in Film Market Teaching and Research Center, at the department of media management, Qingdao Film Academy, China. Her several research articles published in various international journals and journals in China. She presented several research papers at international conferences held in US, Malaysia, and China. And she completed two research projects from the Ministry of Education in China. Besides, her current research interests include media management, film marketing, film production, consumer behavior, new media management, international film industry, and the international film and television trade. ORCID: 0000-0002-9354-3543.

Nan Jiang

Dr. Nan Jiang (PhD, Derby UK) is an associate professor at the School of Management and Marketing, Faculty of Business and Law, Taylor’s University, Malaysia. Nan has 12 years of working experience in tertiary education and has a track record of teaching, research, and administrative profile. Her journal publication is in the areas of internationalization of higher education, data mining, social media marketing, consumer behaviour, and game addiction. She is the project leader and co-researcher for several international and national grants. Orcid: 0000-0002-4410-6283.

Thivashini B. Jaya Kumar

Dr. Thivashini B Jaya Kumar (PhD, Taylor’s University) is a Lecturer at the School of Management & Marketing, Taylors Business School, Taylor’s University, Malaysia. She was awarded Bachelor of Business from Victoria University, Australia and Master’s in management from Taylors University. She holds a PhD in Business (Marketing) with a research interest in service marketing, consumer behavior, international business, higher education and entrepreneurship. ORCID: 0000-0002-3265-3191.

Mobai Chen

Dr. Mobai Chen (PhD, Limkokwing University of Creative Technology, Malaysia; Postdoctor, Shandong University, China.) is an associate professor, and the dean of the Department of Film and Animation in Qingdao University of Science and Technology, China. His research areas are film and animation studies, and film marketing. ORCID: 0009-0001-3188-0368.