Uncovering the barriers to customer over-the-top experience: an integrated approach Open Access

With the rise of the Internet as a dominant streaming medium and the rapid advancement of digital technologies, over-the-top (OTT) media platforms have transformed how consumers access, engage, and experience digital content. OTT service platforms, which deliver content directly to customers over the Internet without set-top boxes, have grown significantly (Rahe et al., 2021; Rahman and Arif, 2021). The OTT industry is expected to reach a valuation of USD 0.70 trillion in 2025 and is forecasted to grow to USD 1.47 trillion by 2030, reflecting a compound annual growth rate (CAGR) of 16.14% throughout the 2025–2030 period (Mordor Intelligence, 2025). Netflix, Amazon Prime, Disney+ Hotstar are the leading companies in this sector and hold a significant share of the market (Nafees et al., 2021). These platforms allow customers to move beyond traditional content consumption by using high-speed internet, affordable data plans, and smart devices (Nandukrishna and Sridevi, 2024).

OTT platforms allow users to access TV shows and movies on demand, customizing their viewing experience, thereby redefining customer experience in the entertainment industry. Owing to their personalized user experiences, convenience, and diverse range of content, these platforms are gaining popularity (Yoon and Kim, 2023). The evolution of OTT platforms, driven by technological advancements, convenience, and shifting customer preferences, has significantly transformed consumer behaviour (Polisetty et al., 2023). However, variations in user interests and attention spans have led to inconsistent content consumption patterns, influencing overall customer experience (Alsharif et al., 2021). Customer experience fundamentally reflects how consumers assess the treatment received from service providers. It is intricate and multifaceted, encompassing numerous touchpoints that contribute to a distinctive, memorable, and satisfying engagement journey (Kuppelwieser and Klaus, 2021). It encompasses the psychological, emotional, and cognitive connection between a company and its customers (Palmer, 2010). The perceptions and emotional responses of consumers toward online video creators who stream content over the internet is defined as the Customer Over-the-Top Experience (COTTE) (Kalra et al., 2024). Improved online customer experience encourages long-term adoption of a service (Lee et al., 2022) and is crucial to a business's success in the digital landscape (Carey, 2023). Building brand loyalty and achieving business success on OTT platforms requires a flawless, hassle-free, and engaging content experience (Ahmad et al., 2022). However, prior research on OTT context has primarily focused on understanding the drivers of user adoption, sustained usage, customer engagement, and willingness to pay, giving limited attention to understanding the barriers that hinder the COTTE.

The study is among the first to address the critical gap by identifying and analysing key barriers impeding COTTE, and it is positioned at the intersection of digital service management and customer experience research. Previous researchers have explored factors influencing user adoption and satisfaction in digital media environments; there is a paucity of comprehensive frameworks that systematically uncover, structure, and prioritize the multifaceted barriers impeding COTTE. For this purpose, the study employed an integrated method to identify and analyze the barriers to COTTE. First, barriers were identified through a systematic literature review and content analysis, and experts from both industry and academia further validated them. A systematic literature review (SLR) was undertaken to identify relevant studies, followed by a content analysis using first- and second-order coding to systematically derive and classify the key barriers impeding COTTE. Finally, by utilizing Interpretive Structural Modelling (ISM) and Fuzzy Matriced’ Impacts Croise's Multiplication Appliqu'ee an un Classement (Fuzzy MICMAC), the study examines the interrelationships among the identified barriers and classifies them based on their driving and dependence power, respectively. The findings of this study will guide academics, industry practitioners, and policymakers in prioritizing interventions that can drive superior customer experiences and foster sustainable competitive advantage in the rapidly evolving OTT landscape.

The structure of the paper is organized as follows: Section 2 presents a review of relevant literature and identifies the research gap. Section 3 explains the application of SLR, content analysis, ISM, and FMICMAC techniques used to examine the barriers influencing customer experience on OTT platforms. Section 4 outlines the results, followed by Section 5, which discusses the findings, contribution, and implications. Finally, Section 6 concludes the paper by highlighting insights, limitations, and directions for future research.

The concept of customer experience encompasses a broad spectrum of actions and emotional responses that emerge naturally throughout the customer journey, often emerging spontaneously in reaction to stimuli related to a product or service (Becker and Jaakkola, 2020). The overall customer experience represents a consumer's comprehensive and holistic interaction with a company, emphasizing the importance of the totality of connections that exist between the consumer and the organization (Harris et al., 2003). Each interaction with an online retailer elicits an internal and subjective response from the consumer (Gulfraz et al., 2022). OTT platforms refer to digital services that allow users to access video and audio content through internet-enabled devices (Palomba, 2022). According to the (FCC, 2013), OTT can be described as a video distribution service that delivers programming content to viewers over the Internet. The notion of online customer experience focuses on an individual's engagement with a particular online service, aiming to foster sustained usage and continued interaction with that service (Lee et al., 2022). Within the OTT context, customer experience evolves into a more specific construct termed COTTE, which captures users' perceptions, emotional responses, and behavioral tendencies during their engagement with streaming platforms (Kalra et al., 2024).

Despite the rapid growth and transformative potential of the OTT sector, achieving a seamless and satisfying customer experience remains a significant challenge for service providers. Indian OTT platform user penetration stands at only 4.6%, far below the global average of 16.2%. The difference highlights the necessity to identify the sector-specific barriers to COTTE in the given context (Statista, 2025). Moreover, individual preferences, fluctuating attention spans, and expectations for high-quality, personalized, and value-driven content further complicate the landscape (Chakraborty et al., 2023). Few studies have explored the barriers to customer experience in domains such as retail (Ghatak, 2024; Kamoonpuri and Sengar, 2023), food delivery applications (Kaur et al., 2021), and craftsmanship (Tarquini et al., 2022). Existing studies in the OTT context have focused on the factors leading to the adoption (Bhattacharyya et al., 2021; Dasgupta and Priya, 2019; Kakkar and Kakkar, 2018; Sharma and Kakkar, 2022; Shin et al., 2016), continuous usage (Yoon and Kim, 2023), customer engagement (Gupta and Singharia, 2021), willingness to pay (Kim et al., 2017; Nagaraj et al., 2021). Research focusing explicitly on the barriers to customer experience in OTT platforms is limited. A few studies have addressed barriers affecting OTT platform usage behaviour (Agarwal et al., 2023), adoption of OTT services (Polisetty et al., 2023) and continuance and discontinuance of OTT platforms (Nandukrishna and Sridevi, 2024).These fragmented views fail to provide a holistic understanding of the multi-dimensional barriers, such as technological, organizational, regulatory, and user-centric, that collectively shape customer experience on OTT platforms. Moreover, the interaction among these barriers and their relative influence may vary across contexts and industries. Hence, there remains a significant gap in the existing literature concerning the systematic identification and analysis of interrelated barriers that constrain customer experience on OTT platforms, especially in the context of India's rapidly evolving digital ecosystem.

The study employed an integrated methodology to identify and analyze the barriers to COTTE. In the initial phase, a systematic review of existing literature and a detailed content analysis were carried out to identify and categorize potential barriers, and further, it was validated and refined based on the experts' input. In the second phase, Interpretive Structural Modeling (ISM) was employed to explore the interrelationships among the identified barriers and to develop a hierarchical, multi-level structural framework. Finally, in the third phase, MICMAC analysis was performed to classify the barriers according to their driving and dependence power. The complete step-by-step research process is illustrated in Figure 1.

The initial stage comprised a systematic review of the literature and a content analysis aimed at identifying representative barriers to COTTE identified in the literature. Additionally, inputs were obtained from experts in academia and industry to validate the identified barriers in the given context. SLR was used to gather, examine, and synthesize existing knowledge, as well as identify what remains unknown, concerning a particular theme of interest (Briner et al., 2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al., 2009) were deployed to reduce selection bias and capture a diverse range of perspectives on barriers to COTTE. In terms of search strategy, the search string was defined as TITLE-ABS KEY, (“barrier*” OR “challenge*” OR “inhibitor*” OR “impediment*”) AND (“experience*” OR “viewer experience*”) AND (“over-the-top” OR “OTT” OR “over-the-top service” OR “streaming video” OR “video-on-demand”) AND (“technology”) and applied to titles, abstracts and keywords to include as much relevant research as possible within the field. Relevant articles were collected from the Scopus database to maintain a high level of rigor. The review protocol also outlined the inclusion and exclusion criteria for choosing articles. The inclusion criteria for the review were established as follows: (1) articles published in journals, (2) articles written in English, (3) articles addressing barriers of customer experience, (4) articles addressing barriers of OTT platforms, (5) articles addressing barriers of technology-related articles. Figure 2 illustrates the sequential stages of the review process developed in accordance with the PRISMA guidelines. In accordance with the defined review protocol, systematic database searches yielded a total of 261 articles. Of these, 189 were identified as journal publications, and 163 were written in English. During the selection of primary studies, articles were screened and analyzed based on their titles, abstracts, and keywords, resulting in 139 relevant papers. Subsequently, 92 articles met all five inclusion criteria and were retained as the final sample.

To identify the representative barriers influencing COTTE from the above shortlisted studies, a two-tiered approach of first- and second-order constructs was employed, where the second-order constructs represent a higher level of abstraction. The initially extracted first-order barriers, derived directly from the existing OTT literature, were found to be fragmented and loosely structured. To achieve greater conceptual coherence, these first-order barriers were systematically grouped into second-order constructs, enabling the identification of key themes and recurring patterns that shape customer experience on OTT platforms. This hierarchical categorization aligns with the methodological recommendations of Seuring and Gold (2012), White and Marsh (2006), ensuring both analytical rigor and comprehensiveness in capturing the multidimensional nature of barriers influencing COTTE.

Expert judgment was employed to validate the identified barriers from the existing literature. A total of 15 experts—seven from academia and eight from industry (please see Table 1)—were purposefully selected based on their expertise in marketing and customer experience or having over eight years of professional experience in the entertainment and customer service sectors. Experts evaluated and discussed eight potential barriers affecting COTTE through semi-structured interviews. Based on their collective assessment, eight major barriers were finalized using the principle that a barrier was retained if at least eight out of the fifteen experts identified it as a significant impediment to COTTE.

Warfield introduced ISM in 1974 (Warfield, 1974) to examine context-specific variables (Bhosale and Kant, 2016). A panel of experts determines variable associations, making this technique interpretative (Mathiyazhagan et al., 2013). With experts' input, the ISM technique transforms a complex structure into a hierarchical structural model with a visible and well-defined structure (Sage, 1977). This approach enables the structured development of a directed graph or network, visually representing the intricate contextual relationships among a given set of variables (Malone, 1975). Steps for developing an ISM-based model adopted in this study are based on the work of Warfield (1974), Sage (1977).

To establish the pairwise relationship among the barriers, responses were taken from the same 15 experts (Please see Table 1). ISM, an expert-driven methodology, is intended to develop a structural relationship rather than a statistical generalization. Hence, the interpretive quality of experts is more crucial than the sample size. Previous ISM base studies (Bhosale and Kant, 2016; Gokarn and Choudhary, 2021; Hu and Bi, 2025; Lima et al., 2025) have also used a limited sample (an expert panel of 8–20). Further, (VAXO) rotation was used to define the relationship between the barriers (i and j), representing barriers in rows and columns, respectively.

• V: Barrier i will help to achieve barrier j

• A: Barrier i will be achieved by barrier j

• X: Barrier i and j will help to achieve each other

• O: Barrier i and j are unrelated.

Based on these pairwise relationships, the SSIM table was developed for the eight barriers identified as COTTE barriers.

The SSIM is reformed into a binary matrix, called the initial reachability matrix. The symbols V, A, X, and O are converted into 1 and 0 as given below

1. If the entry in the cell (i, j) in the SSIM is V, then the cell (i, j) entry is converted into 1 and the cell (j, i) entry converted into 0 in the initial reachability matrix.

2. If the entry in the cell (i, j) in the SSIM is A, then the cell (i, j) entry is converted into 0, and the cell (j, i) entry is converted into 1 in the initial reachability matrix.

3. If the notation in the cell (i, j) in the SSIM is X, then the entry in both the cells (i, j) and (j, i) gets converted into 1 in the initial reachability matrix.

4. If the entry in the cell (i, j) in the SSIM is O, then the entry in both the cells (i, j) and (j, i) is converted into 0 in the initial reachability matrix.

The final reachability matrix of the barriers is obtained by incorporating the transitivity rule, which states that if a variable A influences B, and B influences the variable C, then A also influences C. Applying the transitivity rule, if a direct relationship exists between two barriers, an indirect link is established through other barriers that share a common relationship with both.

Using the final reachability matrix, the reachability set and antecedent set for each barrier were identified. The reachability set of a specific barrier includes the barrier itself, along with other barriers it may contribute to achieving. Conversely, the antecedent set comprises the barrier itself and other barriers that may aid in achieving it.

An ISM-based model is developed based on the final reachability matrix and the directed graph of the COTTE barriers. The conceptual inconsistency of the ISM-based model is checked, and necessary modifications are made.

Fuzzy MICMAC analysis is a sophisticated decision-making and analytical method that uses fuzzy logic and MICMAC. It is mostly used to investigate the interdependencies and consequences of numerous variables in complex systems to have a better understanding of their interactions (Hong et al., 2024). Fuzzy MICMAC is commonly used with ISM to improve performance. ISM defines factor structures, whereas fuzzy MICMAC shows their interdependencies. This combination enhances system dynamics understanding (Bashir et al., 2022). By categorizing barriers into dependent, independent, linkage, or autonomous clusters based on their influence and dependence, fuzzy MICMAC analysis helps unravel system complexities by providing a structured approach to understanding and addressing these barriers.

This section outlines the results derived from each method employed to achieve the stated objectives of the study. The findings from each approach are discussed below.

Eight key barriers relevant to the research problem were identified from the selected studies and are summarized in Table 2. A brief description of these eight barriers within the context of the problem is provided in the subsequent subsections.

Technological and infrastructural barriers refer to challenges related to limited access to hardware, software quality, and the overall planning and implementation needed to support digitalization (Iyanna et al., 2022). For rural OTT platforms, 82% of the population has not adopted them (Chacko, 2022). Poor internet access limits OTT viewers' entertainment experience. Technical constraints, including compatibility and system complexity, hinder online adoption (Loo et al., 2024), which can also hinder COTTE. Complex user interfaces, technological challenges, restricted search and navigation options, and poor curation and recommendation systems make it tougher for consumers to utilize the platform easily. Technology glitches typically hinder utilization, including setup, notification, and feature navigation errors. Technical problems include login issues, heavy tablets, and technical errors that slow chatbot performance (Kim et al., 2023), which means that technical errors cause the chatbot to respond more slowly, less reliably, or with poorer quality. Technological anxiety is a significant obstacle to chatbot adoption, stemming from users' fear and hesitation (Kwangsawad and Jattamart, 2022). These factors limit both adoption and user satisfaction, making them essential to address in the context of COTTE. Technology vulnerability refers to the fear of technological failures, including concerns about technological dependence and technology anxiety of OTT platforms (Polisetty et al., 2023).

Economic affordability barriers are impediments that hinder individuals from accessing products, services, or opportunities due to higher prices or financial limitations. The barrier of affordability is a difficulty with the Internet, connectivity, and technology costs, which may increase financial strain (Ali Alryalat et al., 2023; Loo et al., 2024). Previous studies have shown that the cost and effort involved in switching act as barriers, making users reluctant to change or adopt new services in areas such as internet banking (Zhou, 2018), online food delivery (Cheng et al., 2025), e-commerce (Ghazali et al., 2016), online hotel booking (Xue and Jo, 2024), online auctions (Li, 2015), and messaging applications (Schreiner and Hess, 2015). Since OTT platforms operate in a similar online environment, it can be inferred that switching costs and effort may also serve as barriers and making viewers reluctant to adopt new platforms, which affects COTTE. Perceived cost plays a significant role, as many users believe that subscribing to these services may not be worth the expense (Nandukrishna and Sridevi, 2024). The value barrier also affects adoption, with potential subscribers questioning whether the content and features justify the price (Polisetty et al., 2023). Additionally, the continuous increase in subscription fees makes it harder for users to afford multiple streaming services (Agarwal et al., 2023). Pricing plays an important role in influencing subscription decisions of OTT platforms (Kumar et al., 2025).These economic challenges discourage many from fully embracing OTT platforms.

Mental health issues include psychological conditions such as addiction disorders, stress, anxiety, and depression, which arise from overutilization of the internet, smartphones, and gaming. Internet gaming addiction (IGA) is often defined as an individual's inability to manage their internet usage, resulting in significant adverse consequences (Lin et al., 2015). Internet addiction (IA) is a broad concept that encompasses excessive involvement in various online activities, including gaming, social networking, chatting, gambling, video or movie streaming, compulsive shopping, and continuous browsing or information searching (Wölfling et al., 2019). It is characterized by a lack of control over internet use, eventually causing problems in mental health, social life, or work (Dong et al., 2012a). In 2024, India observed a 13% annual increase in the time spent on devices, marking the highest year-on-year growth among the top five countries in this category (Sanzgiri, 2025). As technology use grows and people rely more on social media for communication, social interactions decrease, leading to more mental health issues. Easy access, constant connectivity, and information overload can contribute to stress, anxiety, and depression (Scott et al., 2017). Previous studies have found that excessive digital consumption can result in addiction, stress, eye strain, and poor sleep quality (Aykutlu et al., 2024; Deivendran et al., 2025; Kayan, 2025; Nikolic et al., 2023). Consequently, it negatively impacts users' mental health, making many viewers aware of these effects and therefore inclined to limit their usage of OTT platforms.

A language barrier occurs when people are unable to communicate verbally due to the absence of a shared language. Localization goes beyond mere translation; it involves tailoring a message, product, or game to connect more effectively with different audiences (Xavier, 2024). Hence, a localisation barrier emerges when the company's message and offers do not meet the needs of a broad audience. The language barrier also restricts internet usage, as the majority of online content is in English (Lwoga and Chigona, 2019). A linguistic barrier impedes involvement in e-commerce, complicating individuals' ability to navigate online platforms, comprehend product information, and communicate successfully with sellers and customers in various languages (Al-Dmour et al., 2020). The lack of multilingual support and language limitations present significant barriers for chatbot adoption as well (Bansal et al., 2024; Rainey et al., 2023; Sezgin et al., 2024). Similarly, language can be a hurdle for viewers who watch OTT content but do not understand English. Moreover, there is a possibility of misleading or false information being shared, which could pose risks to viewers (Agarwal et al., 2023).

Socio-cultural barriers arise from differences in social origins, customs, beliefs, and behaviors. Cultural and social variety hinders information clarity, interpretation, and exchange (Soni, 2023). Lack of technical knowledge and awareness of e-commerce benefits (Abou-Shouk and Eraqi, 2015) and low perceived operational benefits and unwillingness to adopt these services are impediments to adoption (Ali Alryalat et al., 2023). These could also act as a barrier to COTTE. Online shoppers are impacted by social variables (Pentz et al., 2020), lack of understanding, cultural issues, and interest as barriers to social media use (Al-Busaidi et al., 2017). Lack of awareness, unethical work, and unpleasant customers also hinder OTT adoption (Agarwal et al., 2023). Unethical work refers to unethical work practices in the form of paying less, exploiting writers, etc. and unpleasant customers refers to other customers who are displeased or unhappy with OTT platforms. Viewers with a general aversion and pre-existing negative attitudes are more inclined to choose traditional entertainment over OTT. The image barrier, caused by stereotyping, slows innovation (Choudhary et al., 2024), which happens when people dislike the brand, industry, or innovation's adverse consequences (Lian and Yen, 2014). The tradition barrier emerges when an innovation disrupts or contradicts a user's cultural norms, with resistance intensifying as the level of conflict increases. These barriers significantly affect the adoption of OTT services (Polisetty et al., 2023) impacting the experience of OTT viewers.

A privacy and data security barrier refers to challenges, regulations, or limitations that prevent the effective protection, collection, or use of personal and sensitive data. Internet security primarily addresses the risks faced by consumers when using credit cards for online purchases, while payment fraud remains a significant threat to online merchants (Loo et al., 2024). Perceived risk refers to the uncertainty about future outcomes that may negatively impact individuals' purchasing decisions, highlighting the need for a secure payment method when ordering expensive products online. Fear of security risks in online transactions hinders its widespread adoption (Ndayizigamiye and Khoase, 2018). The lack of security and privacy in online transactions poses another challenge (Abou-Shouk and Eraqi, 2015). Perceived privacy risk is a key barrier to the adoption of OTT, as consumers worry about the misuse of their personal information. Users fear unauthorized access, data breaches, and misuse of personal information, making them hesitant to engage online (Alqahtani and Issa, 2018). In line with this, worries about privacy and security can disrupt the user experience on OTT platforms. Fear of data breaches, tracking, and unauthorized access may make viewers hesitant to engage with content or share personal information.

Trust and reliability barriers are characterized by a consumer's perceived lack of trust, which affects their decision to make an online purchase and is influenced by their perception (Sesar et al., 2024). Consumer trust is essential for internet users in electronic governance (Becker, 2005), social media (Salahshour et al., 2016) and voice assistants (Nallam et al., 2020). Trust is the expectation of receiving favorable or neutral outcomes based on the anticipated behaviour of another party in a situation where uncertainty exists (Bhattacharya et al., 1998). Likewise, a lack of trust and technological confidence can negatively affect COTTE. When customers value the advantages of a new technology, yet also express concerns about the potential risks involved in its use (Soopramanien, 2011). Ideological barriers hinder OTT adoption, as skeptical viewers doubt the success of OTT services (Polisetty et al., 2023). Insecurity also means doubting technology's dependability and functionality (Parasuraman, 2000). Insecurity increases uncertainty and decreases technology use (Kuo et al., 2013; Parasuraman and Colby, 2014). Users often face issues with inaccurate responses, which can be too vague, incorrect, or unsatisfactory, leading to more confusion than clarity. Inaccuracy and unreliability might also hinder COTTE.

The digital barrier is a phenomenon where an individual's success is determined by their engagement in the information revolution (Ling et al., 2020). Consumers with limited technological understanding or app experience may oppose a technology, creating a usage barrier (Polisetty et al., 2023). Lack of technology knowledge, expertise, and abilities hinders online learning, digital transformation (Akhter et al., 2022; Vuchkovski et al., 2023). Online and distant learning have struggled with skill insufficiency (Gan and Sun, 2022; Sumalinog, 2022). Likewise, in the context of OTT platforms, it can also pose a challenge for COTTE. Poor usability can create a hurdle that requires extra effort and determination to overcome (Chen and Thio, 2021). Perceived complexity is when a technology is seen as complicated, requiring more effort to use. As a result, if people find a technology difficult to use, they also view any tasks performed with it as challenging (Sullivan and Koh, 2019). Older persons' unwillingness to change and difficulties learning new skills hinder digital adoption (Xu et al., 2023). Lack of excitement, discomfort, preference for conventional technology, and cynicism or uncertainty about its performance can contribute to passive innovative resistance to new technologies. Resistance to digital transformation is people's reluctance, hesitancy, or rejection to adopting and integrating digital technology (Caputo et al., 2023). OTT users lack information to make purchasing decisions and evaluate service quality (Rudolph et al., 2004). Older audiences may prefer familiar genres such as sitcoms, dramas, and procedurals, which might be less common on OTT platforms (Mathevan, 2024).

Based on the results of the established contextual relationships among the identified barriers, an SSIM was constructed as presented in Table 3.

The initial reachability matrix and the final reachability matrix of the barriers are developed as shown in Tables 4 and 5, respectively.

In this study, all eight barriers reached their final levels after five iterations, as presented in Table 6. These five hierarchical levels serve as the foundation for constructing the ISM-based model.

The hierarchical model is constructed based on the final reachability matrix and the directed graph of COTTE barriers, as illustrated in Figure 3. In this model, the first-level barrier (Level I) is placed at the top of the digraph, followed by the second-level barriers positioned directly below it. Likewise, other barriers are arranged hierarchically according to their respective levels in the partitioning process until the bottom-level barrier (Level V) is placed at the lowest position in the digraph. This study's ISM model consists of five hierarchical levels, ranging from Level I to Level V.

Fuzzy MICMAC analysis uses fuzzy set theory (FST) to increase sensitivity over binary connections (0, 1) (Gorane and Kant, 2013). FMICMAC adds barrier interaction input. FMICMAC is more sensitive than conventional MICMAC analysis, but it is especially useful when identifying interaction possibilities would take extensive resources (Saxena et al., 1990). This analysis uses the initial reachability matrix to calculate the direct relationship matrix. Further, it is improved by incorporating the possibility of interactions between the barriers. Following conversion to a fuzzy direct relationship matrix, it becomes input for FMICMAC analysis. Fuzzy multiplication stabilizes matrices instead of Boolean multiplication.

A binary direct relationship matrix (BDRM) is constructed by analysing the direct relationships among barriers in the initial reachability matrix, as shown in Table 5. In this process, all non-zero values on the matrix's diagonal are converted to zero to form the BDRM, as presented in Table 7.

To enhance the analysis, the BDRM is further transformed into a fuzzy direct relationship matrix (FDRM) by incorporating the possibility of reachability rather than just direct reachability. For this, a scale ranging from 0 to 1, as shown in Table 5, is used. The relationship values between the two barriers are then updated based on inputs from academicians and industry experts. The resulting table is referred to as the fuzzy direct relationship matrix (FDRM), as presented in Table 8.

FDRM is the foundational matrix for finding fuzzy indirect COTTE barrier relationships. The FDRM is multiplied by itself to find indirect relationships (Nida et al., 2024). This multiplication uses fuzzy matrix multiplication (Kandasamy and Smarandache, 2007). Fuzzy matrix multiplication extends Boolean matrix multiplication by allowing for fuzzy values. In FST, the product of two fuzzy matrices results in another fuzzy matrix. Multiplication follows the rule:

The stabilized matrix (Table 9) shows the fuzzy indirect relationships between barriers.

Fuzzy MICMAC analysis grouped all eight barriers into different groups based on their contextual relationships. Driving power indicates a barrier's capacity to affect and intensify others, whereas dependence power indicates the extent to which others influence it. Based on their values, these eight barriers are grouped into autonomous, dependent, linkage, and independent categories. The driving power is determined by summing the rows in Table 9, while the dependence power is calculated by summing the columns. These values are plotted on a graph using dependence as the x-axis and driving power as the y-axis, as shown in Figure 4.

Eight relevant barriers were identified through a combination of literature review and expert consultations. The ISM technique was then applied to construct a structured hierarchical model illustrating the interrelationships among the identified barriers. Figure 3 shows that the technological and infrastructural barriers (B1) are at the highest level in this hierarchy, as they have strong driving power but low dependence power, making them the most important barrier. They have the potential to influence the remaining barriers like economic affordability barriers (B2), language and localization barriers (B4), and privacy and data security barriers (B6). These three barriers lead to the other barriers, such as mental health concerns (B3) and trust and reliability barriers (B7). Both these barriers, in return impact the socio-cultural barriers (B5). At the top of the ISM hierarchy are the digital barriers (B8), with the lowest driving power and maximum dependence power. All the remaining barriers affect digital barriers directly or indirectly.

These findings provide valuable insights for the OTT industry, highlighting key barriers that influence user experience and adoption. Among these, technological and infrastructural barriers stand out as the most significant, as they impact other barriers. Service providers must prioritize addressing technical issues such as system glitches, software bugs, and infrastructure-related shortcomings to ensure a seamless viewing experience. Additionally, the high cost of adopting new technology creates economic affordability barriers, making it difficult for some users to access OTT platforms. If content is not user-friendly or fails to adapt to diverse audiences, it leads to language and localization barriers, limiting engagement across different demographics. Moreover, privacy and data security barriers play a crucial role in user trust—when individuals feel unsafe using a platform, they hesitate to share sensitive information such as credit card details and personal data, further intensifying trust and reliability issues. A lack of confidence in platform security can cause users to fear potential data breaches or loss of vital information, reinforcing skepticism and reducing engagement. Meanwhile, excessive OTT usage, such as binge-watching, can contribute to addiction, anxiety, and other mental health concerns. When users begin to perceive these platforms as having a negative impact on their well-being, it fosters socio-cultural barriers, making them less inclined to engage with such services. The most dependent barrier among all is the digital barrier, which arises when users lack IT skills or awareness of the benefits of OTT services. Limited digital literacy can hinder individuals from effectively navigating these platforms, reducing their ability to fully engage with available content and services. Addressing these interconnected challenges is essential for enhancing user experience, building trust, and ensuring the continued growth of the OTT industry. To improve viewer satisfaction, OTT service providers must tackle these barriers and comprehend their interrelationships, as they greatly influence the overall consumer experience.

Fuzzy MICMAC analysis was used to categorize the eight barriers into different groups based on their contextual relationships. Based on this analysis, the eight barriers are categorized into four groups: autonomous barriers, dependent barriers, linkage barriers, and independent barriers.

Cluster I: Autonomous barriers. Barriers located in the first quadrant exhibit weak driving and dependence power and are referred to as autonomous barriers. When assessing COTTE barriers, no autonomous barriers are identified. These barriers are relatively isolated from the system, resulting in less impact. Their absence in this study suggests that all the considered barriers play a significant role within the system. OTT service providers cannot ignore all eight barriers while providing a seamless experience to viewers.

Cluster II: Dependent barriers. Barriers situated in the second quadrant possess weak driving power but strong dependence power and are classified as dependent barriers. The dependent barriers identified in quadrant II include mental health concerns (B3), socio-cultural barriers (B5), trust and reliability barriers (B7), and digital barriers (B8). Given their weak driving power and strong dependence power, service providers should thoroughly examine these barriers, as they hinder a seamless viewing experience.

Cluster III: Linkage barriers. The third quadrant of Figure 4 includes barriers with both strong driving and dependence power, referred to as linkage barriers. However, in this study, no barriers were identified as linkage barriers in quadrant III, meaning none exhibit both strong driving and dependence power. This suggests that all the barriers impacting COTTE in this study are stable in nature.

Cluster IV: Independent barriers. These barriers possess strong driving power but weak dependence power. Positioned in the fourth quadrant, they are referred to as independent barriers. In this study, barriers present in quadrant IV are technological and infrastructural barriers (B1), economic affordability barriers (B2), language and localization barriers (B4), and privacy and data security barriers (B6). These barriers possess strong driving power and weak dependence power, making them critical barriers. Service providers should make a strategy by considering these barriers to make the customer experience more comfortable and enjoyable. These barriers are also important as they influence all the dependent barriers, which are placed in the second quadrant. The OTT industry needs to explore diverse economic models beyond the conventional revenue sources of advertising and subscriptions to build a sustainable business (Mani, 2025).

This study includes both theoretical contributions and managerial implications.

The current study significantly contributes to the existing literature on customer experience in OTT platforms. First, the current study has significantly extended the scope of ongoing empirical studies of customer experience literature by identifying barriers to COTTE. Previous studies often emphasized service quality, personalization, or content richness, while this further adds insights on the inhibiting factors. This adds a new dimension to the existing customer experience literature by integrating negative determinants into the framework. Second, the present study extends existing literature by employing ISM to establish the interrelationships among identified barriers. By mapping the hierarchical interdependencies across economic, technological, psychological, and socio-cultural dimensions, the study offers a holistic theoretical understanding of the barriers to COTTE. It reflects that consumer experience in OTT is shaped by an ecosystem of structural, cultural, and individual-level barriers. Third, the current study makes a valuable contribution to the existing literature by the use of Fuzzy MICMAC, which results in the categorization that contributes to theoretical knowledge by classifying them into independent, dependent, and linkage barriers in the OTT context.

The study findings are valuable for different stakeholders, including practitioners, OTT service providers, and policymakers. First, as the technological and infrastructural barriers are the most significant, possessing strong driving power and influencing all other barriers, service providers could proactively address system glitches, software bugs, and infrastructure-related shortcomings to ensure a seamless and reliable viewing experience. Second, economic affordability barriers highlight the need for more inclusive pricing strategies. Managers could explore tiered subscription plans, ad-supported free versions, student discounts, and regional pricing to make OTT services accessible to a broader audience, especially in price-sensitive markets. Third, to overcome language and localization barriers, OTT service providers can ensure user-friendly content that is adapted to diverse audiences. This means investing in high-quality multi-language support (subtitles, dubbing), region-specific content, and designing user interfaces that are intuitive and localized for specific demographics to maximize engagement. Fourth, service providers could treat privacy and data security barriers as critical independent barriers that directly impact user trust and reliability. Management could implement robust security measures, clearly communicate data usage policies, and build transparent systems to reassure users about the safety of their sensitive personal information (like credit card details) to mitigate hesitancy in platform engagement. Fifth, since digital barriers have the highest dependence, managers could launch awareness campaigns or user-friendly tutorials to help less tech-savvy users navigate OTT platforms effectively. Simplified interfaces and AI-driven recommendations can improve accessibility and retention. Sixth, managers could recognize the potential negative effects of excessive screen time and binge-watching, i.e. mental health concerns. Introducing responsible-viewing features—like watch-time reminders or curated content for relaxation—can promote healthier viewing habits and strengthen the platform's reputation for user well-being. Seventh, trust and socio-cultural barriers indicate that platforms could maintain credibility through transparent operations, culturally sensitive content, and ethical advertising. Collaborating with local creators and respecting cultural norms can enhance emotional connection and brand acceptance. Lastly, the absence of linkage barriers suggests a stable barrier structure. Service providers could maintain this stability by focusing on the independent barriers, as they are the primary drivers. Continuously monitoring these key drivers ensures the overall system does not shift, which could introduce highly volatile linkage barriers.

This study develops a comprehensive framework by identifying and analysing key barriers that disrupt a smooth and effortless OTT viewing experience. After reviewing the existing literature, relevant barriers were identified. Further, ISM and fuzzy MICMAC techniques were applied to analyze and reveal the interconnections among them. In this effort, eight barriers to COTTE have been identified through SLR and content analysis. The ISM model (Figure 3) provides a hierarchical framework for service providers to prioritize actions and ensure a seamless experience. Meanwhile, fuzzy MICMAC analysis categorizes barriers into four distinct groups based on their driving and dependence power (Figure 4), offering insights for practitioners to understand the nature of viewer challenges. The study's findings will help service providers enhance customer experience and provide valuable academic insights into related issues.

This study has several limitations, which create opportunities for further investigation in the future. Firstly, the research involved 15 experts from academia and industry, which restricts its scope. Future studies could expand the expert pool by including additional stakeholders such as content creators, technology providers, and distributors to enhance exposure and credibility. Secondly, while conducting the systematic literature review and content analysis, some barriers may have been overlooked due to publication bias, database limitations, or the dynamic evolution of OTT platforms. Future research could expand the scope of database searches to include a broader range of studies for a more comprehensive analysis. Additionally, the model used in this study lacks statistical validation, so future studies could enhance its robustness and generalizability by employing statistical methods like confirmatory factor analysis (CFA) or structural equation modelling (SEM). Future research can employ CFA and SEM to empirically validate and strengthen the hierarchical framework derived from expert judgment. Specifically, CFA can be used to test the reliability and construct validity of the identified barriers, ensuring that the proposed dimensions of COTTE are statistically sound. Subsequently, SEM can be applied to examine the causal relationships among these barriers, thereby providing empirical confirmation of the hierarchical structure revealed through ISM and FMICMAC.