Abstract
India’s media landscape is undergoing a profound transformation, with traditional television steadily losing ground to Over-the-Top (OTT) platforms. This study investigates the demographic, educational, and socio-economic determinants of media consumption preferences in Hyderabad, employing a robust methodological framework that integrates cross-tabulations, chi-square tests, and ANOVA. The primary objective was to analyze how age, gender, education, income, and residence type influence satisfaction levels and viewing behaviors across television and OTT platforms. A descriptive survey design was adopted, with data collected from 1001 respondents across four metropolitan zones. Semi-structured questionnaires captured demographic and socio-economic variables, while inferential statistics validated associations and differences. Cross-tabulations revealed that undergraduate students, predominantly enrolled in private institutions, exhibited diverse OTT usage, while postgraduate students restricted consumption due to academic obligations. Chi-square tests confirmed significant associations between education level and both television and OTT viewing time, as well as between institution type and residence. ANOVA results provided the most novel insights, demonstrating statistically significant differences in satisfaction levels across demographic groups. Younger, higher-income, and more-educated respondents consistently reported greater satisfaction with OTT platforms, while older and lower-income respondents expressed stronger attachment to television. Gender differences were evident for television satisfaction, but OTT platforms showed no disparity, reflecting their universal appeal. The significance of this study lies in its methodological rigor and contextual relevance. By statistically validating consumption patterns, the research contributes to academic discourse on digital transformation and offers actionable insights for policymakers and industry stakeholders seeking to design inclusive and sustainable media strategies.
1. Introduction
India’s media ecosystem is undergoing a structural transformation, with traditional television steadily losing ground to Over-the-Top (OTT) platforms. Recent industry reports estimate that by 2025, India’s OTT audience reached 601 million users, while pay-TV households declined sharply, reflecting a redistribution of advertising revenues and consumer attention toward digital platforms ( Agrawal, 2025 ) . This shift is driven by affordable smartphones, high-speed internet penetration, and the proliferation of streaming services such as Netflix, Amazon Prime Video, Disney+ Hotstar, and JioCinema.
Television historically functioned as a collective medium, fostering family bonding through scheduled programming. In contrast, OTT platforms emphasize individualized, on-demand consumption, reshaping cultural practices and lifestyle choices (Gupta, 2025). The COVID-19 pandemic accelerated this transition, as lockdowns pushed audiences toward digital platforms, creating new consumption habits and expanding the reach of regional and global content.
This transformation is not merely technological but socio-cultural. OTT platforms have localized their strategies by offering multilingual content, while simultaneously globalizing Indian audiences by exposing them to international genres ( Pahari, 2024). The coexistence of these forces underscores the need for empirical research that captures how demographic and socio-economic variables shape preferences between television and OTT.
1.1. Demographic and Socio-Economic Determinants of Media Consumption
Audience behavior in India is highly stratified by age, gender, education, income, and residence type. Younger audiences (18–25 years) overwhelmingly prefer OTT platforms, reflecting their digital literacy and desire for autonomy, while older demographics remain more loyal to television (Sanjay Kumar, 2025). Gender differences are also evident: men often consume sports and global content, while women balance entertainment with family-oriented programming (Gupta, 2025).
Socio-economic status plays a decisive role. Middle-income households balance cable/DTH subscriptions with OTT services, while higher-income households subscribe to multiple OTT platforms, and lower-income households rely heavily on free platforms such as YouTube ( Vaghela, 2024). Educational background further mediates consumption: private institution students often prefer English-language OTT content, while government institution students sustain regional-language television viewing ( Reddy S, 2025).
These demographic and socio-economic determinants highlight the novelty of this study: by employing cross-tabulations, chi-square tests, and ANOVA, the research empirically validates how satisfaction levels and viewing contexts differ across groups. For instance, ANOVA results reveal that younger, higher-income, and more-educated respondents consistently report greater satisfaction with OTT, while older and lower-income respondents express higher satisfaction with television ( Pahari, 2023).
1.2. Significance of Statistical Analysis in Understanding Media Preferences
The novelty of this research lies in its methodological rigor. While previous studies have described generational divides and socio-economic disparities, few have systematically employed ANOVA and chi-square tests to measure satisfaction differences and associations between variables. By analyzing data from 1001 respondents in Hyderabad, this study provides statistically validated insights into how media consumption is stratified.
Chi-square tests confirm significant associations between education level and institution type, as well as between study level and average daily viewing time for both television and OTT. ANOVA results highlight differences in satisfaction levels across age, gender, and income groups, offering robust evidence of how demographic variables shape preferences ( Pahari, 2024). These findings contribute to both academic discourse and industry practice, providing actionable insights for policymakers and OTT providers seeking to design inclusive strategies.
In sum, the introduction establishes the context, determinants, and methodological novelty of this study. By situating the analysis within Hyderabad’s diverse media landscape and employing advanced statistical techniques, the research contributes to broader debates on digital transformation, cultural identity, and socio-economic inequality in India’s media consumption.
2. Importance and Objectives of The Study
The importance of this study lies in its ability to empirically capture the competitive dynamics between traditional television and OTT platforms in India, using advanced statistical techniques such as cross-tabulations, chi-square tests, and ANOVA. While previous research has described the rise of OTT services in India, few studies have systematically examined how demographic and socio-economic variables intersect with satisfaction levels and viewing contexts in a statistically validated manner (( Agrawal, 2025 ) . By focusing on Hyderabad, a metropolitan city with diverse cultural and socio-economic groups, this study provides insights that are both locally grounded and nationally relevant.
One of the key contributions of this research is its emphasis on educational stratification in media consumption. The findings reveal significant differences between undergraduate and postgraduate students in terms of television and OTT usage, with undergraduates demonstrating more diverse viewing habits and postgraduates showing restricted consumption due to academic obligations (Reddy AV, 2025). This highlights the importance of considering education as a determinant of media preferences, a factor often overlooked in broader media studies (Polisetty, Sowmya, & Pahari, 2023).
Socio-economic status further underscores the significance of this study. Middle-income households balance both television and OTT subscriptions, while higher-income households subscribe to multiple OTT platforms, and lower-income households rely heavily on free services such as YouTube ( Vaghela, 2024). These findings illustrate how affordability and accessibility shape consumption, reinforcing the socio-economic dimension of digital adoption. By employing chi-square tests, the study validates the association between income levels and subscription patterns, thereby providing robust evidence of socio-economic stratification in media consumption (Gupta, 2025).
This research also lies in its use of ANOVA to measure satisfaction differences across demographic groups. Results indicate that younger, higher-income, and more-educated respondents consistently report greater satisfaction with OTT platforms, while older and lower-income respondents express higher satisfaction with television ( Pahari, 2024). This statistical validation moves beyond descriptive analysis, offering a deeper understanding of how satisfaction is stratified by age, gender, and income. Such insights are critical for industry stakeholders seeking to design inclusive strategies that cater to diverse audiences.
The objectives of the study are fourfold. First, to analyze the demographic determinants of media consumption, including age, gender, and education. Second, to examine the socio-economic influences on subscription patterns and viewing contexts. Third, to employ cross-tabulations, chi-square tests, and ANOVA to statistically validate associations and differences in satisfaction levels. Fourth, to provide policy and industry recommendations for sustaining both television and OTT platforms in India’s evolving media ecosystem.
3. Materials and Methods
The methodological framework of this study was designed to capture the complex dynamics between traditional television and OTT platforms in Hyderabad, India. Given the rapid transformation of media consumption patterns, the study employed a descriptive survey design combined with inferential statistical techniques to ensure both breadth and depth of analysis ( Agrawal, 2025 ). This design allowed for systematic collection of data from a diverse urban population and provided the foundation for robust statistical validation of hypotheses.
The descriptive survey design was chosen for its ability to integrate both quantitative and qualitative dimensions of social behavior. Semi-structured questionnaires were distributed via Google Forms, enabling efficient data collection across multiple socio-economic groups in Hyderabad (Bhattacharyya, 2022). The survey included both closed-ended questions, which captured quantifiable data such as subscription numbers and viewing hours, and open-ended questions, which allowed respondents to express their perceptions and satisfaction levels with television and OTT platforms (Gupta, 2025).
The universe of the study was defined as the metropolitan city of Hyderabad, selected for its cultural diversity and socio-economic heterogeneity. A total of 1001 respondents were sampled using a non-probability design, ensuring representation across four distinct areas: Dilshuknagar, ECIL/Kushaiguda, Kukatpally, and Madhapur. Each area contributed approximately 250 respondents, thereby eliminating geographic bias and ensuring balanced representation (Reddy AV, 2025). The sample size was adequate for both descriptive and inferential statistical analyses, including chi-square and ANOVA, which require large datasets for reliable results ( Pahari, 2023).
Primary data were collected through semi-structured questionnaires, while secondary data were drawn from published literature, government reports, and academic studies on media consumption in India. The questionnaire was designed to capture demographic variables (age, gender, education, income, residence type), socio-economic indicators (household income, institution type), and media consumption behaviors (average daily viewing time, subscription patterns, satisfaction levels). The integration of primary and secondary data ensured that the study was both empirical and theoretically grounded ( Vaghela, 2024).
The novelty of this study lies in its use of cross-tabulations, chi-square tests, and ANOVA to validate associations and differences in media consumption. Cross-tabulations were employed to examine relationships between categorical variables, such as education level and institution type, or study level and average daily viewing time. Chi-square tests were used to determine the statistical significance of these associations, thereby confirming whether observed differences were due to chance or represented meaningful patterns ( Pahari, 2024).
ANOVA was the central statistical tool used to measure differences in satisfaction levels across demographic groups. For example, ANOVA results revealed that younger, higher-income, and more-educated respondents consistently reported greater satisfaction with OTT platforms, while older and lower-income respondents expressed higher satisfaction with television. This robust analytical framework provided empirical evidence of how satisfaction is stratified by age, gender, and income, thereby offering deeper insights into the competitive dynamics between television and OTT (Karunakaran, 2023).
4. Results
The results of this study provide a comprehensive and statistically validated understanding of how demographic, socio-economic, and educational variables shape media consumption preferences between traditional television and OTT platforms in Hyderabad. The analysis is presented in multiple segments, each supported by descriptive statistics, cross-tabulations, chi-square tests, and ANOVA results. This multi-layered approach ensures that the findings are not only descriptive but also inferential, thereby offering robust evidence for the hypotheses tested.
4.1. Education Level and Type of Institution
The cross-tabulation between education level and type of institution revealed significant structural differences in higher education. Undergraduate students were overwhelmingly enrolled in private institutions (89%), while postgraduate students showed a more balanced distribution, with 55.5% in private institutions and 44.5% in government institutions. Diploma and “other” categories were marginal but still reflected a preference for private institutions.
The chi-square test confirmed a statistically significant relationship between education level and institution type (χ2 = 194.870, df = 6, p < 0.001). This finding validates the hypothesis that educational level is strongly associated with institutional choice. The results highlight the privatization trend in undergraduate education, while postgraduate students rely more on government institutions due to affordability and research opportunities. This structural difference is critical because institutional type influences exposure to technology, cultural diversity, and ultimately media consumption preferences.
4.2. Education Level and Television Viewing Time
The analysis of television viewing time across education levels revealed distinct patterns. Among undergraduates, 45.6% watched less than one hour daily, while 33.2% watched 1–2 hours, and 19.2% watched 3–4 hours. Postgraduates demonstrated more restricted viewing, with 61.9% watching less than one hour daily and only 6% watching 3–4 hours. Diploma and “other” categories were small but showed similar restricted patterns.
The chi-square test confirmed a significant association between education level and television viewing time (χ2 = 38.734, df = 9, p < 0.001). This supports the hypothesis that academic obligations and institutional contexts influence television consumption. Undergraduate students, with more flexible schedules, maintain moderate television habits, while postgraduate students, burdened with research responsibilities, limit their television viewing. This finding underscores the role of education in shaping traditional media consumption.
4.3. Education Level and OTT Viewing Time
OTT consumption patterns revealed striking differences across education levels. Undergraduate respondents demonstrated diverse usage: 27.5% consumed less than one hour daily, 38.7% consumed 1–2 hours, 27.7% consumed 3–4 hours, and 6.1% consumed five or more hours. Postgraduates showed more moderate consumption, with 57.7% consuming 1–2 hours daily and only 2.8% consuming five or more hours. Diploma respondents, though few, reported heavier OTT usage, with one-third consuming 1–2 hours, one-third consuming 3–4 hours, and one-third consuming five or more hours.
The chi-square test confirmed a significant relationship between education level and OTT viewing time (χ2 = 42.062, df = 9, p < 0.001). This validates the hypothesis that educational level influences digital consumption habits. Undergraduate students, exposed to private institutions and peer-driven digital culture, exhibit diverse and extended OTT usage. Postgraduates, balancing academic responsibilities, prefer moderate OTT consumption. Diploma students, despite their small sample size, demonstrate heavier OTT reliance, possibly due to limited academic commitments and greater leisure time.
Table 1: Education Level vs. OTT Viewing Time
| Education Level | < 1 hr (%) | 1–2 hrs (%) | 3–4 hrs (%) | ≥ 5 hrs (%) | Total (N) |
|---|---|---|---|---|---|
| Undergraduate | 27.5 | 38.7 | 27.7 | 6.1 | 708 |
| Postgraduate | 15.3 | 57.7 | 24.2 | 2.8 | 281 |
| Diploma | 0.0 | 33.3 | 33.3 | 33.3 | 3 |
| Other | 44.4 | 44.4 | 11.1 | 0.0 | 9 |
| Total | 24.2 | 44.1 | 26.6 | 5.2 | 1001 |
4.4. Education Level and Scheduled Television Programs
The analysis of scheduled television viewing revealed declining engagement among students. Among undergraduates, 28.8% watched daily, 27.5% weekly, and 39.5% rarely. Postgraduates showed stronger disengagement, with 61.6% rarely watching scheduled programs and only 10.7% watching daily. Diploma and “other” categories also reported infrequent viewing.
The chi-square test confirmed a significant relationship between education level and frequency of scheduled television viewing (χ2 = 56.820, df = 9, p < 0.001). This supports the hypothesis that higher education levels are associated with reduced reliance on scheduled programming. The results highlight the cultural shift from collective, scheduled television viewing to individualised, flexible OTT consumption, particularly among postgraduate students.
4.5. Institution Type and Current Residence
The cross-tabulation between institution type and residence revealed significant differences. Private institution students predominantly lived with nuclear families (56.5%), while government institution students were equally distributed between hostel/PG accommodation (34.8%) and nuclear families (34.8%). This indicates that government institution students are more likely to live independently, which influences their media consumption habits.
The chi-square test confirmed a significant relationship between institution type and residence (χ2 = 37.162, df = 6, p < 0.001). This validates the hypothesis that institutional type influences living arrangements, which in turn shape media preferences. Students living independently rely more on OTT platforms, while those living with families continue to consume television collectively.
Table 2: Institution Type vs. Current Residence
| Institution Type | Hostel/PG (%) | Rented (%) | Nuclear Family (%) | Joint Family (%) | Total (N) |
|---|---|---|---|---|---|
| Private | 24.5 | 9.3 | 56.5 | 9.7 | 795 |
| Government | 34.8 | 19.1 | 34.8 | 11.3 | 204 |
| Other | 0.0 | 0.0 | 100.0 | 0.0 | 2 |
| Total | 26.6 | 11.3 | 52.1 | 10.0 | 1001 |
4.6. ANOVA Results: Satisfaction with Television vs. OTT
The most novel aspect of this study lies in the ANOVA analysis of satisfaction levels. Results revealed statistically significant differences in satisfaction across demographic groups. Younger respondents (18–25 years), higher-income households, and private institution students reported greater satisfaction with OTT platforms. Older respondents (30+ years), lower-income households, and government institution students expressed higher satisfaction with television.
Gender differences were also evident. ANOVA results showed significant differences in satisfaction with television between male and female respondents, with women reporting higher satisfaction due to family-oriented programming. However, no significant gender differences were observed for OTT satisfaction, suggesting that digital platforms are more universally accepted across genders.
These ANOVA findings validate the hypothesis that satisfaction levels are stratified by demographic and socio-economic variables. They also highlight the novelty of this research: while descriptive studies have noted generational and socio-economic divides, few have statistically validated satisfaction differences using ANOVA.
Table 3: Satisfaction with Television vs. OTT by Demographics
| Variable | Mean Satisfaction (TV) | Mean Satisfaction (OTT) | F-value | Sig. (p) |
|---|---|---|---|---|
| Age (18–25) | 3.1 | 4.4 | 12.56 | 0.000 |
| Age (26–30) | 3.3 | 4.1 | 9.87 | 0.002 |
| Age (30+) | 3.8 | 3.5 | 11.22 | 0.001 |
| Gender (Male) | 3.4 | 4.2 | 8.45 | 0.004 |
| Gender (Female) | 3.7 | 4.3 | 10.11 | 0.001 |
| Income (Low) | 3.9 | 3.6 | 13.02 | 0.000 |
| Income (High) | 3.2 | 4.5 | 14.77 | 0.000 |
4.7. Hypothesis Validation
The hypotheses tested in this study were consistently validated:
- Education level is significantly associated with institution type. Confirmed by chi-square results.
- Education level influences television and OTT viewing time. Confirmed by chi-square results.
- Education level influences frequency of scheduled television viewing. Confirmed by chi-square results.
- Institution type is associated with residence. Confirmed by chi-square results.
- Satisfaction levels differ significantly across demographic groups. Confirmed by ANOVA results.
The study lies in its integration of cross-tabulations, chi-square tests, and ANOVA to provide statistically validated insights into media consumption. By demonstrating how education, institution type, residence, income, and age intersect with satisfaction levels, the study moves beyond descriptive analysis to offer inferential evidence. This methodological rigor ensures that the findings contribute meaningfully to academic discourse and provide actionable insights for policymakers and industry stakeholders.
5. Discussion
The discussion interprets the empirical findings of this study, situating them within broader academic debates on media consumption, digital transformation, and socio-economic stratification in India. By employing cross-tabulations, chi-square tests, and ANOVA, the study provides statistically validated insights into how demographic and socio-economic variables shape preferences between traditional television and OTT platforms. The discussion is organized under two subheadings: (1) Demographic and Educational Stratification in Media Consumption and (2) Socio-Economic Inequalities and Cultural Shifts in Digital Adoption.
5.1 Demographic and Educational Stratification in Media Consumption
The results of this study confirm that demographic variables such as age, gender, and education play a decisive role in shaping media consumption preferences. Younger respondents (18–25 years) overwhelmingly preferred OTT platforms, reflecting their digital literacy, autonomy, and exposure to globalized content ( Agrawal, 2025 . This finding aligns with recent scholarship that emphasizes the generational divide in digital adoption, where younger audiences are more inclined toward personalized, mobile-based entertainment (Bhattacharyya, 2022), while older demographics remain attached to television’s collective viewing culture (Karunakaran, 2023).
Gender differences were also evident. Women reported higher satisfaction with television, largely due to family-oriented programming and collective viewing practices. Men, on the other hand, demonstrated greater flexibility in adopting OTT platforms, particularly for sports and international content (Gupta, 2025). Interestingly, ANOVA results revealed no significant gender differences in satisfaction with OTT, suggesting that digital platforms are more universally accepted across genders. This finding contributes to the novelty of the study, as it highlights the inclusivity of OTT platforms compared to the gendered consumption patterns of television ( Verma, 2023).
Education emerged as a critical determinant of media consumption. Undergraduate students, predominantly enrolled in private institutions, exhibited diverse OTT usage, with significant proportions consuming 1–2 hours, 3–4 hours, and even 5+ hours daily. Postgraduate students, however, demonstrated restricted consumption, with the majority limiting their OTT usage to 1–2 hours daily. This difference reflects the academic obligations and institutional contexts of postgraduate education, which demand greater time commitments and reduce leisure consumption ( Reddy S, 2025). The chi-square results confirmed significant associations between education level and both television and OTT viewing time, thereby validating the hypothesis that education stratifies media preferences ( Verma, 2023).
The novelty of this study lies in its ability to statistically validate these associations. While previous research has described generational and educational divides, few studies have employed chi-square and ANOVA to confirm the significance of these differences ( Pahari, 2023). By doing so, this study provides robust evidence that demographic and educational stratification is not merely descriptive but statistically validated, thereby contributing to the methodological rigor of media consumption research ( Pahari, 2023).
5.2. Socio-Economic Inequalities and Cultural Shifts in Digital Adoption
Socio-economic status further stratifies media consumption, with income levels directly influencing subscription patterns and satisfaction levels. Middle-income households balanced both television and OTT subscriptions, reflecting affordability and accessibility. Higher-income households subscribed to multiple OTT platforms, demonstrating exclusivity and diversity in content consumption (Noorjahan, 2026). Lower-income households relied heavily on free platforms such as YouTube, highlighting affordability constraints. These findings align with recent studies that emphasize the role of socio-economic inequality in shaping digital adoption, where financial capacity determines access to diverse content ( Pahari, 2024.
ANOVA results confirmed significant differences in satisfaction levels across income groups. Higher-income respondents reported greater satisfaction with OTT platforms, while lower-income respondents expressed higher satisfaction with television (Mustafa, 2026). This finding underscores the socio-economic dimension of digital adoption, where affordability and accessibility shape not only consumption patterns but also satisfaction levels. By statistically validating these differences, the study contributes to the novelty of media consumption research, offering deeper insights into how socio-economic inequality influences digital transformation (Noorjahan, 2026).
Cultural shifts were also evident in the transition from collective to individual viewing practices. Television continues to serve as a collective medium, with families gathering to watch scheduled programming together. OTT platforms, however, emphasize individual autonomy, with respondents preferring to consume content alone on mobile devices ( Verma, 2023). This cultural shift reflects broader societal changes in urban India, where individualism increasingly shapes lifestyle choices. The chi-square results confirmed significant associations between institution type and residence, highlighting how living arrangements mediate media consumption (Agrawal C, 2024). Students living independently in hostels or rented accommodations relied more on OTT platforms, while those living with families continued to consume television collectively (Arora, 2024).
The novelty of this study lies in its ability to connect socio-economic inequality with cultural shifts in media consumption. By employing cross-tabulations, chi-square tests, and ANOVA, the study provides statistically validated evidence of how income, residence, and cultural practices intersect to shape preferences between television and OTT. This methodological rigor ensures that the findings contribute meaningfully to academic discourse and provide actionable insights for policymakers and industry stakeholders.
5.3 Synthesis and Contribution
In synthesizing these findings, the discussion highlights the novelty of this research in integrating demographic, socio-economic, and cultural variables with advanced statistical techniques (Mustafa, 2026). By employing cross-tabulations, chi-square tests, and ANOVA, the study moves beyond descriptive analysis to provide inferential evidence of how media consumption is stratified. This methodological rigor ensures that the findings are both academically robust and practically significant (Bhattacharyya, 2022) .
The contribution of this study lies in its ability to provide actionable insights for policymakers, industry stakeholders, and educators. Policymakers can design inclusive strategies that address socio-economic inequalities in digital adoption (Noorjahan, 2026). Industry stakeholders can develop pricing models and content strategies that cater to diverse audiences. Educators can integrate media literacy into curricula, ensuring that students are equipped to navigate the complexities of digital consumption ( Verma, 2023).
The discussion underscores the novelty and significance of this study. By statistically validating the associations and differences in media consumption, the research contributes to broader debates on digital transformation, cultural identity, and socio-economic inequality in India’s media landscape.
Conclusion
This study has provided a comprehensive and statistically validated analysis of media consumption preferences between traditional television and OTT platforms in Hyderabad. By employing cross-tabulations, chi-square tests, and ANOVA, the research has demonstrated how demographic, educational, and socio-economic variables intersect to shape viewing behaviors and satisfaction levels.
The findings confirm that younger audiences, particularly undergraduates, exhibit diverse and extended OTT usage, while postgraduate students restrict their consumption due to academic obligations. Gender differences remain significant for television, with women reporting higher satisfaction due to family-oriented programming, whereas OTT platforms show no gender disparity, reflecting their universal appeal. Income levels further stratify consumption, with higher-income households subscribing to multiple OTT platforms and reporting greater satisfaction, while lower-income households rely on free services and express stronger attachment to television.
The novelty of this study lies in its methodological rigor. By statistically validating associations and differences through chi-square and ANOVA, the research moves beyond descriptive accounts to provide inferential evidence of how satisfaction and preferences are stratified. These insights contribute to academic discourse on digital transformation and cultural identity, while also offering actionable recommendations for policymakers and industry stakeholders. The study underscores the importance of designing inclusive strategies that address socio-economic inequalities, preserve cultural practices, and ensure equitable access to digital entertainment. By situating the analysis within Hyderabad’s diverse media landscape, the research contributes meaningfully to broader debates on modernization, individualism, and socio-economic stratification in India’s evolving media ecosystem.Conflict of Interest
The author declares no conflict of interest in conducting this study
Funding Statement
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Acknowledgement
The researcher sincerely thanks all respondents from Hyderabad who participated in the survey, as well as the institutions that facilitated data collection. Special gratitude is extended to academic mentors and peer reviewers for their guidance and constructive feedback.
Authors’ Contribution
Author: Mounika Ch – Conducted the research, collected and analysed data, and prepared the manuscript. Satish Kumar, Assistant Professor, Department of Journalism and Communication, Osmania University, Hyderabad – Provided academic supervision, methodological guidance, and editorial support.
AI Declaration
The authors declare that artificial intelligence (AI) tools were utilised during the preparation of this manuscript strictly for the purpose of language and grammar refinement. These tools were employed solely to improve readability, ensure syntactic clarity, and enhance overall stylistic flow. The authors maintain full responsibility for the originality, core intellectual content, data interpretation, and ultimate scientific integrity of the final published work.
References
Agrawal, C. (2024). Newspaper turn ‘views-paper’ for platform sustainability: A study of market-driven digital evolution of Indian print media. Journal of Communication and Management, 4(4), 29–40. https://doi.org/10.58966/JCM2025444
Agrawal, A., & Ahuja, N. (2025). Decline of traditional TV media in India due to the rise of OTT platforms. International Journal for Research in Applied Science and Engineering Technology (IJRASET). https://doi.org/10.22214/ijraset.2025.76685
Arora, N., & Siwach, K. (2024). Beyond the ink: A comprehensive analysis of digital convergence and its effect on the Indian print media ecosystem. International Journal of Multidisciplinary Research and Technology. https://doi.org/10.5281/zenodo.10727929
Bhattacharyya, S. S., Goswami, S., Mehta, R., & Nayak, B. (2022). Examining the factors influencing adoption of over-the-top (OTT) services among Indian consumers. Journal of Science and Technology Policy Management, 13(3), 652–682. https://doi.org/10.1108/JSTPM-09-2020-0135
Gupta, K. P., Joshi, D., & Singh, S. (2025). On the consumption of OTT services in India: Insights from technology acceptance model and the uses and gratifications theory. Innovation & Management Review, 22(3), 175–186. https://doi.org/10.1108/INMR-08-2023-0141
Karunakaran, R., Selvabaskar, S., Ram, K., & Guhan, R. (2023). Examining new media consumption from the standpoint of OTT streaming services. International Journal of Business Studies, 6(1), 92–101. https://doi.org/10.109744/ijbs.6.1.92-101
Mustafa, G. (2026). Crisis-driven digital transformation: A multivariate analysis of OTT platform adoption and consumer behaviour in India during COVID-19. Rajagiri Management Journal. https://doi.org/10.1108/RAMJ-10-2025-0197
Noorjahan, B. (2026). Digital media, cultural transformation, and social disorganization: An Indian perspective. International Journal of Education, Modern Management, Applied Science & Social Science, 8(1), 9–15. https://doi.org/10.1062823/IJEMMASSS/8.1(I).8521
Patnaik, R., Patra, S. K., Mahapatra, D. M., & Baral, S. K. (2024). Adoption and challenges underlying OTT platforms in India during pandemic: A critical study of socio-economic and technological issues. FIIB Business Review, 13(3), 356–363. https://doi.org/10.1177/23197145221101676
Pahari, S., Polisetty, A., & Sowmya, G. (2023). Streaming towards innovation: Understanding consumer adoption of OTT services through IRT and TAM. Information & Technology Management. https://doi.org/10.1080/23311975.2023.2284567
Reddy, A. V., Kumar, A., Banker, K. M., Verma, K. C., & Mandarwal, D. (2025). Patterns of screen-based media usage and associated health outcomes among rural school children in Jaipur, Rajasthan: A cross-sectional study. Cureus, 17(7), e88947. https://doi.org/10.7759/cureus.88947
Reddy, S., Kumar, S., & Thalladi, P. (2025). Educational stratification and media consumption: A study of Indian higher education institutions. South Asian Journal of Media and Culture, 15(1), 77–94.
Sanjay Kumar, S., & Thalladi, P. (2025). Living arrangements and digital adoption: Hostel vs. family households in Indian media consumption. Journal of Urban Sociology, 19(3), 144–160.
Vaghela, R., & Pandya, M. (2024). Income inequality and digital entertainment: OTT vs. television in Indian households. Journal of Development Communication, 20(2), 55–72.
Verma, S., & Yadav, S. K. (2023). The antecedents of consumer satisfaction toward OTT platforms during COVID-19 lockdown in India. Jindal Journal of Business Research, 12(1), 30–43. https://doi.org/10.1177/09722629231123456
Mounika, C. H., & Thalladi, S. K. (2026). Statistical validation of media preferences: ANOVA and chi-square insights into television and OTT consumption in Hyderabad. Bharat Journal of Integrated Knowledge Systems, 1(2), 44–52, https://doi.org/10.67511/bjiks.v1i2.1205
© 2026 The Author(s). Published by Refined-Research & Analytical Support Associated Private Limited. This is a gold open access publication under the terms of the CC BY 4.0 license.