Review Article: 2024 Vol: 28 Issue: 3
Gaganpreet K Ahluwalia, Indira School of Business Studies: Indira ISBS PGDM
Karuna Joshi Gole, Jayawant Shikshan Prasarak Mandal, Pune
Rohan Das, Dr. D Y Patil Medical College, Navi Mumbai
Sadaf Karim, Allana Institute of Management Sciences, Pune
Samrat Ray, International Institute of Management Studies (IIMS) Pune
Sunil Kumar, Sai Balaji International Institute of Management Sciences, Pune
Kumar D, Sai Balaji International Institute of Management Sciences
Citation Information: Ahluwalia, K.G.., Joshi Gole, K., Das, R., Karim, S., Ray, S., Kumar, S., & Kumar, D. (2024). A study on demographic influences on changing consumption pattern of consumers towards indian cinema. Academy of Marketing Studies Journal, 28(3), 1-12.
Purpose: The Indian Cinema since independence has changed a lot. The change in consumption pattern towards Indian cinema is on account of change in technology, educational level, and increase in per capita income, digital connectivity etc. However, there are certain other demographic factors which have also influenced consumption pattern. Thus, under such situations, the researchers have tried to study the demographic influences such as age, gender, income and other variables on the consumption pattern. Design/Methodology/Approach: The research study is descriptive and analytical. The researchers have taken both primary and secondary data. The sampling design was non probability Judgmental sampling. The researchers have taken a survey of 108 respondents through questionnaire in order to know the changes in consumption patterns towards Indian Cinema. Originality/Value: First and foremost is that there are only few literatures regarding consumption patterns of Indian Cinema. The existing literatures have only considered limited dimensions of the subject. Thus the present study seems to explore various demographic features and its influence on changes in consumption pattern towards Indian cinema.
Age, Gender, Income, Cinema, Consumption.
The Indian Cinema industry has grown leaps and bound since independence especially post liberalization. The market size of Indian cinema was 172 billion rupees in 2022 and is estimated to increase to 228 billion rupees by 2025. This increase in market size has been on an account increase in per capita of the Indian population. India’s decent economic growth rate has increased the spending for entertainment services in India. The Indian population is now ready to spend for entertainment. There has been lot many changes in the overall consumption pattern of Indian consumers towards Indian Cinema driven by both demand and supply side forces. The economic growth backed by increased education level, digital technology and policy reforms has led to larger acceptance of Hollywood movies and movies of different regional languages in India. Under this scenario, the authors have tried to study the different factors responsible for changes in consumption pattern in general and demographic influences in particular.
Sheth (1977) in his research paper has studied the importance of demographics in consumer behavior. The author is of the view that ignoring demographic factors in consumer behavior is immature. None of the other social, economic models fully explain consumption behavior at the micro level. In contrast demographics, psychographic, life style and personality variables should be integrated in theories. Kevrekidis, et al. (2021) have studied the impact of demographic characteristics and consumer behaviour in the selection of retail pharmacies and over the counter medicine. The study is based on responses collected from 314 consumers through questionnaire. The various statistical tests used were Chi square test, one way Anova and Spearman’s correlation coefficient. The findings of the study show that respondents with lower educational level and retired consumers tend to make their purchase decisions through pharmacy. Product advertisement was found to be a significant factor influencing the purchase decisions through Over the Counter. Thus the researchers concluded that age, occupation and educational levels of consumers have significant effect on purchasing decisions through pharmacy or through over the counter. Nagaraj et al (2021) have studied factors influencing consumers decisions to subscribe Over the top (OTT) services. The study was based upon cross sectional descriptive study. The findings of the study show that five factors content, convenience, features, price and quality affected consumer’s decisions. The authors studied the impact of all these five factors along with demographics profiles of age, education, occupation using logistic regression analysis. Varshney et al. (2014) have studied the demographic profiles such as gender, age, occupation, city and its impact on internet/online activities. The authors have used K mean cluster and One way analysis of variance (ANOVA) have been used for a segmentation of internet users and online activities. The sample size considered for analysis was 204 and sampling design was convenience based sampling. The findings of the study show that gender does not have a significant influence on internet activities while age group, occupation, and tier have significant influence on the internet activities. The most important online activities were factored as online money transaction, leisure, social networking, wide exposure and yet to settle. Jadhav & Khanna (2017) have studied the different demographic features and their influence on online buying behavior among college students in Mumbai. The researchers have considered 10 demographic characteristics such as gender, education, age group, residential location, monthly household income, self monthly expenses, ownership of computer, internet connection, ownership of credit card and debit card. The size of the sample was 381 and the responses were collected through questionnaire. The sampling design was convenience sampling. The various statistical tests used were T test and one way Anova. The important finding of the study was that student’s ownership of debit card has significant influence on online shopping behavior of college going students. The gender of the respondents was not having significant difference on the attitudes of respondents towards online shopping. Kumar (2014) has studied the impact of demographic factors on consumer behavior towards four wheelers. The different demographic factors considered are age, sex, marital status, income, family background, education, occupation, family size, geographic factors and psychological factors. The study was based on a sample size of 1000 consumers. The statistical test used was Chi square test. The findings of the study show that the gender as a factor does not have significant relation with buying of the four wheelers from a particular dealer. Education has significant relation on the various facilities required in any four wheelers. However the paper fails to clearly justify the significance. Palomba (2020) has studied the influence of demographics, lifestyles and personalities on the movie consumption. The study is all about how consumer personality and lifestyle may help the marketers and advertisers in predicting movie frequency consumption across generations and platforms. The findings of the study show that for individual genres and platforms, certain measurements are more useful than others. However the limitation of the study is that it only considers the frequent movie watchers and not the casual and occasional. Hanchard et al. (2019) have focused on patterns of film consumptions. The authors have also tried to find out the significance of economic background and status on cultural consumption. The findings of the study show that social and economic factors are important predictors of cultural consumption besides other factors. The authors have used Latent Class Analysis (LCA) a subset of structural equation modeling. The various variables which statistically make larger contribution are education, age, location and income along with a positive perception of films and a negative perception of TV. The strongest predictor was education as respondents with higher education have preference for art house and foreign language films as compared to less educated. Horvath and Gyenge (2015) have focused on the consumption habits regarding movies. The study also focused on various factors influencing the respondents in watching movies at home. The various variables studied by the authors are attitude, sensation and perception, group dynamics and opinion leadership, changing technology etc. The authors have concluded that group dynamics and perception have a role in selecting movies. According to a report by Grandview research, the market size of global movies and entertainment industry was valued at USD 90.2 billion in 2021 and is expected to increase at the rate of 7.2% annually due to favourable demographics, changing consumption pattern, rise in disposable incomes and propensity to spend on leisure and entertainment. Martinez et al. (2011) in their study have focused on the Mexican film industry and its contribution in the global value chain. The basic objective of the study is to explore the feasibility of increasing its contribution to service exports and its participation in the global value chains. The authors concluded that Mexico has the capabilities for producing and showing films but also for offering services to foreign producers that are willing to film in Mexico or carry out post production activities. The authors have also focused on the greater incentives for attracting large foreign productions such as tax incentives, security, law and order etc. Turel (2008) has studied consumer behavior in context of motion picture industry. The different factors considered influencing consumer behavior are critical reviews, advertising genre, and the presence of a particular actor or director. The sample size of the study is 100 comprising of university students in the age group of 18-35 years. The findings of the study show that critical reviews are not significant variable in influencing consumer while word of mouth and film content are significant variables.
The researchers after reviewing different literatures on the subject failed to find research papers and other articles which fully describe the subject of study i.e. demographic influences on consumption pattern and that too with respect to Indian Cinema Industry. Thus to a larger extent it can be said that the subject of study is new and unique and it will be beneficial for the cinema industry so as to target a specific set of demographics influencing consumption pattern. The Producers of the films can get to know the changing requirements of the movie goers.
Objectives of the Study
1. To study the different factors influencing changes in consumption demand of Indian Cinema
2. To study the demographic influences on changing consumption pattern.
Type of Research Study, Sampling and Data Collection
The researchers have tried to take a survey of 108 respondents in Pune city, India through a structured questionnaire. The sampling design was non probability judgmental sampling. The research study was descriptive and analytical. The authors have relied on both primary and secondary data in order to have reliable and authentic results. The various demographic variables considered are gender, age, income level, occupation, education level, type of employment etc. The various demographic variables have been considered as independent variables while the various factors which determine changes in consumption pattern such as strong content, digital connectivity, diversity of movie, acceptability of Hollywood, Tamil, Telugu, Malayalam, social media and digital marketing activities, more open to watch movie with family have been considered as dependent variables. The various statistical tools such as Excel, SPSS 21, were used in order to derive the results. The researchers have used various statistical tests to derive the results such as one way Anova, Levene test etc.
Hypothesis Testing
H1: There is a significant difference in respondents’ consumption pattern towards cinema with respect to their gender.
H2: There is a significant difference in respondents’ perception about increase in diversity of films both in terms of subject and story with respect to their income level.
H3: There is a significant difference in respondents’ opinion about acceptability of Hollywood, Tamil, Telugu and Malayalam films with respect to their marital status.
H4: There is a significant difference in respondents’ perception about acceptability of Holly wood, Tamil, Telugu and Malayalam films with respect to their education level.
Proposed Research Framework
Data Analysis and Interpretation
Sample Characteristics
Levene Test for Homogeneity of Variances
Interpretation: One of the basic assumptions for the ANOVA test is that the variances of each comparison group are equal. This has been tested using the Levene statistic. In all the cases the significance value that is greater than .05. But we do not expect a significant result, since a significant result would suggest a real difference between variances.
In the above Tables 1 & 2, the significance value of the Levene statistic is more than 0.05 in all the cases. This is not a significant result, which means the requirement of homogeneity of variance has been met, and the ANOVA test or independent sample T test can be considered to be robust.
| Table 1 Descriptive Statistics | |||
| Demographic Variable | Categories | Frequency | Percent |
| Gender | Male | 67 | 62 |
| Female | 41 | 38 | |
| Age | 18-25 years | 29 | 26.9 |
| 26-41 years | 44 | 40.7 | |
| 42-60 years | 35 | 32.4 | |
| Annual Income | 0-5 lakh | 50 | 46.3 |
| 5-10 lakh | 15 | 13.9 | |
| 10-15 lakh | 19 | 17.6 | |
| 15 lakh and above | 24 | 22.2 | |
| Marital Status | Single | 59 | 54.6 |
| Married | 49 | 45.4 | |
| Educational Level | SSC | 0 | 0 |
| HSC | 1 | 9 | |
| Degree | 48 | 44.4 | |
| Post Graduate and above | 59 | 54.6 | |
| Nature of Employment | Salaried | 40 | 37 |
| Self Employed | 36 | 33.3 | |
| Contractual | 32 | 29.6 | |
| Table 2 Test of Homogeneity of Variances | |||||
| Levene Statistic | df1 | df2 | Sig. | Decisions & Interpretations | |
| The diversity of films has increased in terms of story and subject | .723 | 1 | 106 | .397 | .397>0.05, hence equal variances assumed |
| More open to watch movie of any subject with family | .643 | 1 | 106 | .425 | .425>0.05, hence equal variances assumed |
| Acceptability of Hollywood, Tamil, Telugu, Malayalam films have increased | 1.859 | 1 | 106 | .176 | .176>0.05, hence equal variances assumed |
| There is larger demand for strong content rather than established actors | 2.150 | 1 | 106 | .146 | .146>0.05, hence equal variances assumed |
| The spending for movie and other entertainment services has increased for Gen X and Gen Y | .106 | 1 | 106 | .745 | .745>0.05, hence equal variances assumed |
| The increase in number of multiplexes in Tier II and Tier III cities | .724 | 1 | 106 | .397 | .397>0.05, hence equal variances assumed |
| The rise of different platforms such as OTT | 1.799 | 1 | 106 | .183 | .183>0.05, hence equal variances assumed |
| Digital connectivity | .164 | 1 | 106 | .686 | .686>0.05, hence equal variances assumed |
| Social media and digital marketing activities | 1.081 | 1 | 106 | .301 | .301>0.05, hence equal variances assumed |
Independent variable: Nature of Employment
Interpretation: From the Table 3 above it can be seen that there is significant difference in the nature of employment (salaried, self employment and contractual) of respondents as far as one dependent variable is concerned i.e. more open to watch movie of any subject with family. Thus the null hypothesis is rejected. But in order to know the significance level of different groups, multiple comparisons has been done through post hoc test.
| Table 3 One Way Anova Test Statistics Anova | ||||||
| Sum of Squares | df | Mean Square | F | Sig. | ||
| The diversity of films has increased both in terms of story and subject | Between Groups | 1.077 | 2 | .538 | .719 | .489 |
| Within Groups | 78.581 | 105 | .748 | |||
| Total | 79.657 | 107 | ||||
| More open to watch movie of any subject with family | Between Groups | 9.066 | 2 | 4.533 | 5.249 | .007 |
| Within Groups | 90.674 | 105 | .864 | |||
| Total | 99.741 | 107 | ||||
| Acceptability of Hollywood, Tamil, Telugu, Malayalam films have increased | Between Groups | .561 | 2 | .280 | .473 | .624 |
| Within Groups | 62.208 | 105 | .592 | |||
| Total | 62.769 | 107 | ||||
| There is larger demand for strong content rather than established actors | Between Groups | 2.011 | 2 | 1.006 | 1.627 | .201 |
| Within Groups | 64.906 | 105 | .618 | |||
| Total | 66.917 | 107 | ||||
| The spending for movie and other entertainment services has increased for Gen X and Gen Y | Between Groups | 1.321 | 2 | .661 | 1.180 | .311 |
| Within Groups | 58.781 | 105 | .560 | |||
| Total | 60.102 | 107 | ||||
| The increase in number of multiplexes in Tier II and Tier III cities | Between Groups | 2.030 | 2 | 1.015 | 1.898 | .155 |
| Within Groups | 56.156 | 105 | .535 | |||
| Total | 58.185 | 107 | ||||
| The rise of different platforms such as OTT | Between Groups | 2.591 | 2 | 1.296 | 1.818 | .167 |
| Within Groups | 74.816 | 105 | .713 | |||
| Total | 77.407 | 107 | ||||
| Digital connectivity | Between Groups | .172 | 2 | .086 | .133 | .875 |
| Within Groups | 67.708 | 105 | .645 | |||
| Total | 67.880 | 107 | ||||
| Social media and digital marketing activities | Between Groups | 1.476 | 2 | .738 | 1.475 | .233 |
| Within Groups | 52.524 | 105 | .500 | |||
| Total | 54.000 | 107 | ||||
Interpretation: Considering the above Table 4, it can be seen that there is no statistically significant difference between salaried and contractual while there is statistically significant difference between salaried and self-employed respondents as far as their perception about changes in consumption pattern is concerned that is they are more open to watch movie of any subject with family.
| Table 4 Multiple Comparisons Employment | |||||||
| Tukey HSD | |||||||
| Dependent Variable | (I) Nature of employment | (J) Nature of employment | Mean Difference (I-J) | Std. Error | Sig. | 95% Confidence Interval | |
| Lower Bound | Upper Bound | ||||||
| More open to watch movie of any subject with family | Salaried | Self Emp. | .68889* | .21349 | .005 | .1813 | 1.1964 |
| contractual | .26875 | .22040 | .444 | -.2552 | .7927 | ||
| Self Employed | Salaried | -.68889* | .21349 | .005 | -1.1964 | -.1813 | |
| Contractual | -.42014 | .22577 | .155 | -.9569 | .1166 | ||
| Contractual | Salaried | -.26875 | .22040 | .444 | -.7927 | .2552 | |
| Self Emp. | .42014 | .22577 | .155 | -.1166 | .9569 | ||
| *.The mean difference is significant at the 0.05 level. | |||||||
Interpretation: From the Table 5 above it can be seen that there is significant difference in the annual income level of respondents as far as one dependent variable is concerned i.e. the diversity of films has increased both in terms of story and content. Thus the null hypothesis is rejected as the value of P (.036) is less than the level of significance (0.05). But in order to know the significance level of different groups, multiple comparisons has been done through post hoc test.
| Table 5 Independent Variable: Annual Income Level Anova | ||||||
| Sum of Squares | df | Mean Square | F | Sig. | ||
| The diversity of films has increased both in terms of story and subject | Between Groups | 6.234 | 3 | 2.078 | 2.944 | .036 |
| Within Groups | 73.423 | 104 | .706 | |||
| Total | 79.657 | 107 | ||||
| More open to watch movie of any subject with family | Between Groups | 6.787 | 3 | 2.262 | 2.531 | .061 |
| Within Groups | 92.953 | 104 | .894 | |||
| Total | 99.741 | 107 | ||||
| Acceptability of Hollywood, Tamil, Telugu, Malayalam films have increased | Between Groups | 4.350 | 3 | 1.450 | 2.581 | .057 |
| Within Groups | 58.419 | 104 | .562 | |||
| Total | 62.769 | 107 | ||||
| There is larger demand for strong content rather than established actors | Between Groups | 4.438 | 3 | 1.479 | 2.462 | .067 |
| Within Groups | 62.479 | 104 | .601 | |||
| Total | 66.917 | 107 | ||||
| The spending for movie and other entertainment services has increased for Gen X and Gen Y | Between Groups | 2.467 | 3 | .822 | 1.484 | .223 |
| Within Groups | 57.634 | 104 | .554 | |||
| Total | 60.102 | 107 | ||||
| The increase in number of multiplexes in Tier II and Tier III cities | Between Groups | .842 | 3 | .281 | .509 | .677 |
| Within Groups | 57.344 | 104 | .551 | |||
| Total | 58.185 | 107 | ||||
| The rise of different platforms such as OTT | Between Groups | .968 | 3 | .323 | .439 | .726 |
| Within Groups | 76.439 | 104 | .735 | |||
| Total | 77.407 | 107 | ||||
| Digital connectivity | Between Groups | .636 | 3 | .212 | .328 | .805 |
| Within Groups | 67.243 | 104 | .647 | |||
| Total | 67.880 | 107 | ||||
| Social media and digital marketing activities | Between Groups | .483 | 3 | .161 | .313 | .816 |
| Within Groups | 53.517 | 104 | .515 | |||
| Total | 54.000 | 107 | ||||
Interpretation: Considering the above Table 6, it can be seen that there is no statistically significant difference respondents earning 0-5 lakh and 10-15 lakh and 5-10 lakh while there is statistically significant difference between respondents earning 10-15 lakh and 15 lakh and above as far as their perception about changes in consumption pattern is concerned that is the diversity of films has increased both in terms of subject and content.
| Table 6 Multiple Comparisons Income Level | |||||||
| Tukey HSD | |||||||
| Dependent Variable | (I) Income Level | (J) Income Level | Mean Difference (I-J) | Std. Error | Sig. | 95% Confidence Interval | |
| Lower Bound | Upper Bound | ||||||
| The diversity of films has increased both in terms of story and subject | 0-5 lakh | 5-10 | .22250 | .24134 | .793 | -.4076 | .8526 |
| 10-15 | -.49789 | .22644 | .130 | -1.0892 | .0934 | ||
| 15 above | .18174 | .21170 | .826 | -.3710 | .7345 | ||
| 5-10 lakh | 0-5 | -.22250 | .24134 | .793 | -.8526 | .4076 | |
| 10-15 | -.72039 | .28510 | .062 | -1.4648 | .0240 | ||
| 15 above | -.04076 | .27353 | .999 | -.7550 | .6734 | ||
| 10-15 lakh | 0-5 | .49789 | .22644 | .130 | -.0934 | 1.0892 | |
| 5-10 | .72039 | .28510 | .062 | -.0240 | 1.4648 | ||
| 15 above | .67963 | .26049 | .050 | -.0005 | 1.3598 | ||
| 15 lakh & above | 0-5 | -.18174 | .21170 | .826 | -.7345 | .3710 | |
| 5-10 | .04076 | .27353 | .999 | -.6734 | .7550 | ||
| 10-15 | -.67963 | .26049 | .050 | -1.3598 | .0005 | ||
Interpretation: From the Table 7 above it can be seen that there is no significant difference in the age group of the respondents as far as any variable determining the consumption demand is concerned. Thus the results fail to reject the null hypothesis. Hence it can be said that age group of the respondents cannot significantly predict changes in consumption pattern.
| Table 7 Independent Variable: Age Anova | ||||||
| Sum of Squares | df | Mean Square | F | Sig. | ||
| The diversity of films has increased both in terms of story and subject | Between Groups | .119 | 2 | .060 | .079 | .924 |
| Within Groups | 79.538 | 105 | .758 | |||
| Total | 79.657 | 107 | ||||
| More open to watch movie of any subject with family | Between Groups | 1.045 | 2 | .523 | .556 | .575 |
| Within Groups | 98.696 | 105 | .940 | |||
| Total | 99.741 | 107 | ||||
| Acceptability of Hollywood, Tamil, Telugu, Malayalam films have increased | Between Groups | .377 | 2 | .188 | .317 | .729 |
| Within Groups | 62.392 | 105 | .594 | |||
| Total | 62.769 | 107 | ||||
| There is larger demand for strong content rather than established actors | Between Groups | .295 | 2 | .147 | .232 | .793 |
| Within Groups | 66.622 | 105 | .634 | |||
| Total | 66.917 | 107 | ||||
| The spending for movie and other entertainment services has increased for Gen X and Gen Y | Between Groups | 1.599 | 2 | .800 | 1.435 | .243 |
| Within Groups | 58.503 | 105 | .557 | |||
| Total | 60.102 | 107 | ||||
| The increase in number of multiplexes in Tier II and Tier III cities | Between Groups | .330 | 2 | .165 | .300 | .742 |
| Within Groups | 57.855 | 105 | .551 | |||
| Total | 58.185 | 107 | ||||
| The rise of different platforms such as OTT | Between Groups | 2.525 | 2 | 1.262 | 1.770 | .175 |
| Within Groups | 74.883 | 105 | .713 | |||
| Total | 77.407 | 107 | ||||
| Digital connectivity | Between Groups | 2.367 | 2 | 1.183 | 1.897 | .155 |
| Within Groups | 65.513 | 105 | .624 | |||
| Total | 67.880 | 107 | ||||
| Social media and digital marketing activities | Between Groups | 1.620 | 2 | .810 | 1.623 | .202 |
| Within Groups | 52.380 | 105 | .499 | |||
| Total | 54.000 | 107 | ||||
Interpretation: From the Table 8 above it can be seen that there is significant difference in the educational level of the (degree and post graduate and above) respondents as far as one dependent variable is concerned i.e. Acceptability of Hollywood, Tamil, Telugu, Malayalam films have increased. Thus the null hypothesis is rejected as the value of P (.036) is less than the level of significance (0.05). Since one of the category i.e. HSC has fewer respondents, hence Post Hoc and multiple comparisons cannot be performed across the groups.
| Table 8 Independent Variable: Educational Level (HSC/Degree/PG and above) Anova | ||||||
| Sum of Squares | df | Mean Square | F | Sig. | ||
| The diversity of films has increased both in terms of story and subject | Between Groups | .464 | 2 | .232 | .307 | .736 |
| Within Groups | 79.194 | 105 | .754 | |||
| Total | 79.657 | 107 | ||||
| More open to watch movie of any subject with family | Between Groups | .638 | 2 | .319 | .338 | .714 |
| Within Groups | 99.103 | 105 | .944 | |||
| Total | 99.741 | 107 | ||||
| Acceptability of Hollywood, Tamil, Telugu, Malayalam films have increased | Between Groups | 7.667 | 2 | 3.833 | 7.305 | .001 |
| Within Groups | 55.102 | 105 | .525 | |||
| Total | 62.769 | 107 | ||||
| There is larger demand for strong content rather than established actors | Between Groups | 1.522 | 2 | .761 | 1.222 | .299 |
| Within Groups | 65.394 | 105 | .623 | |||
| Total | 66.917 | 107 | ||||
| The spending for movie and other entertainment services has increased for Gen X and Gen Y | Between Groups | .757 | 2 | .379 | .670 | .514 |
| Within Groups | 59.345 | 105 | .565 | |||
| Total | 60.102 | 107 | ||||
| The increase in number of multiplexes in Tier II and Tier III cities | Between Groups | .296 | 2 | .148 | .269 | .765 |
| Within Groups | 57.889 | 105 | .551 | |||
| Total | 58.185 | 107 | ||||
| The rise of different platforms such as OTT | Between Groups | 1.559 | 2 | .779 | 1.079 | .344 |
| Within Groups | 75.849 | 105 | .722 | |||
| Total | 77.407 | 107 | ||||
| Digital connectivity | Between Groups | 2.932 | 2 | 1.466 | 2.370 | .098 |
| Within Groups | 64.948 | 105 | .619 | |||
| Total | 67.880 | 107 | ||||
| Social media and digital marketing activities | Between Groups | .151 | 2 | .076 | .147 | .863 |
| Within Groups | 53.849 | 105 | .513 | |||
| Total | 54.000 | 107 | ||||
One Way Anova Statistics
Interpretation: From the Table 9 above it can be seen that there is significant difference in the marital status of the respondents as far as its impact on various dependent variables are concerned. The value of P is less than the level of significance in case of variables such as digital connectivity, the rise of different platforms such as OTT, increase in spending for movie and other entertainment services by Gen X and Gen Y, increase in diversity of films in terms of subject and story, acceptability of Hollywood, Malyalam, Tamil and Telugu films. Hence the null hypothesis is rejected and hence it can be concluded that marital status can predict and influence all these variables.
| Table 9 Independent Variable: Marital Status Anova | ||||||
| Sum of Squares | df | Mean Square | F | Sig. | ||
| The diversity of films has increased both in terms of story and subject | Between Groups | 3.107 | 1 | 3.107 | 4.303 | .040 |
| Within Groups | 76.550 | 106 | .722 | |||
| Total | 79.657 | 107 | ||||
| More open to watch movie of any subject with family | Between Groups | 7.537 | 1 | 7.537 | 8.664 | .004 |
| Within Groups | 92.204 | 106 | .870 | |||
| Total | 99.741 | 107 | ||||
| Acceptability of Hollywood, Tamil, Telugu, Malayalam films have increased | Between Groups | 2.848 | 1 | 2.848 | 5.038 | .027 |
| Within Groups | 59.920 | 106 | .565 | |||
| Total | 62.769 | 107 | ||||
| There is larger demand for strong content rather than established actors | Between Groups | .260 | 1 | .260 | .414 | .521 |
| Within Groups | 66.657 | 106 | .629 | |||
| Total | 66.917 | 107 | ||||
| The spending for movie and other entertainment services has increased for Gen X and Gen Y | Between Groups | 2.740 | 1 | 2.740 | 5.064 | .026 |
| Within Groups | 57.361 | 106 | .541 | |||
| Total | 60.102 | 107 | ||||
| The increase in number of multiplexes in Tier II and Tier III cities | Between Groups | .497 | 1 | .497 | .914 | .341 |
| Within Groups | 57.688 | 106 | .544 | |||
| Total | 58.185 | 107 | ||||
| The rise of different platforms such as OTT | Between Groups | 3.464 | 1 | 3.464 | 4.966 | .028 |
| Within Groups | 73.943 | 106 | .698 | |||
| Total | 77.407 | 107 | ||||
| Digital connectivity | Between Groups | 5.388 | 1 | 5.388 | 9.139 | .003 |
| Within Groups | 62.492 | 106 | .590 | |||
| Total | 67.880 | 107 | ||||
| Social media and digital marketing activities | Between Groups | .598 | 1 | .598 | 1.186 | .279 |
| Within Groups | 53.402 | 106 | .504 | |||
| Total | 54.000 | 107 | ||||
One way Anova Statistics
Interpretation: From the Table 10 above it can be seen that there is significant difference in the Gender of the respondents as far as its impact on various dependent variables are concerned. The value of P is less than the level of significance in case of variables such as digital connectivity, more open to watch movie of any subject with family. Hence the null hypothesis is rejected and hence it can be concluded that there is significant difference in gender and its impact on the above dependent variables are concerned.
| Table 10 Independent Variable: Gender | ||||||
| Sum of Squares | df | Mean Square | F | Sig. | ||
| The diversity of films has increased both in terms of story and subject | Between Groups | .115 | 1 | .115 | .154 | .696 |
| Within Groups | 79.542 | 106 | .750 | |||
| Total | 79.657 | 107 | ||||
| More open to watch movie of any subject with family | Between Groups | 4.646 | 1 | 4.646 | 5.178 | .025 |
| Within Groups | 95.095 | 106 | .897 | |||
| Total | 99.741 | 107 | ||||
| Acceptability of Hollywood, Tamil, Telugu, Malayalam films have increased | Between Groups | .142 | 1 | .142 | .240 | .625 |
| Within Groups | 62.627 | 106 | .591 | |||
| Total | 62.769 | 107 | ||||
| There is larger demand for strong content rather than established actors | Between Groups | 1.038 | 1 | 1.038 | 1.671 | .199 |
| Within Groups | 65.878 | 106 | .621 | |||
| Total | 66.917 | 107 | ||||
| The spending for movie and other entertainment services has increased for Gen X and Gen Y | Between Groups | .003 | 1 | .003 | .005 | .944 |
| Within Groups | 60.099 | 106 | .567 | |||
| Total | 60.102 | 107 | ||||
| The increase in number of multiplexes in Tier II and Tier III cities | Between Groups | .018 | 1 | .018 | .034 | .855 |
| Within Groups | 58.167 | 106 | .549 | |||
| Total | 58.185 | 107 | ||||
| The rise of different platforms such as OTT | Between Groups | .617 | 1 | .617 | .852 | .358 |
| Within Groups | 76.790 | 106 | .724 | |||
| Total | 77.407 | 107 | ||||
| Digital connectivity | Between Groups | 2.628 | 1 | 2.628 | 4.269 | .041 |
| Within Groups | 65.252 | 106 | .616 | |||
| Total | 67.880 | 107 | ||||
| Social media and digital marketing activities | Between Groups | .983 | 1 | .983 | 1.965 | .164 |
| Within Groups | 53.017 | 106 | .500 | |||
| Total | 54.000 | 107 | ||||
Based on the above results, the authors can conclude that there is significance difference in the marital status of the respondents and different dependent variables which represent consumption pattern is concerned. As far as gender is concerned, it has larger influences on digital connectivity and more open to watch movie of any subject with family. There is no significant difference in the age group and the different variables representing consumption pattern is concerned.
Limitations of the Study
The study is based on limited sample and so generalizations may become difficult. The various statistical tests used have its own limitations. The authors have only considered limited dimensions of demographic profile and consumption demand. This can also serve as a scope for the future researchers to take the study further.
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Received: 12-Dec-2023, Manuscript No. AMSJ-23-14261; Editor assigned: 13-Dec-2023, PreQC No. AMSJ-23-14261(PQ); Reviewed: 29-Jan-2023, QC No. AMSJ-23-14261; Revised: 29-Feb-2024, Manuscript No. AMSJ-23-14261(R); Published: 15-Mar-2024