Giants with Feet of Clay? An Inquiry into User Payment Patterns for Subscription Video-on-Demand Services

Abstract

Subscription video-on-demand platforms such as Netflix and HBO Max are being increasingly challenged by the widespread practice of sharing accounts with individuals outside the household. Platforms face a massive loss of revenue due to the opportunistic behavior of many users who enjoy content without paying anything or paying only a part of the required subscription fees. This study explores which factors influence platform users to pay all, part, or none of the subscription fees. Using a cross-sectional survey from Spain, various demographic, attitudinal, and behavioral factors were identified as predictors of the patterns of full, partial, and non-payment. The findings may help platform managers tailor some interventions to monetize a larger number of actual users by deterring the opportunistic payment patterns without discouraging the full payment pattern.

1. Introduction

Subscription video-on-demand (SVOD) has greatly disrupted how users consume movies, series, and other video content. In exchange for fees that are generally considered most convenient (Palomba 2020), SVOD subscribers are empowered to watch a wide variety of video content whenever, wherever, and however they desire. Unsurprisingly, the number of subscriptions has seen remarkable growth globally (Wayne and Castro 2021), and SVOD has steadily taken audiences away from well-established distribution channels, such as cinemas, DVD/Blu-ray, and TV networks (Schauerte et al. 2021; Weinberg et al. 2021). The explosive growth of the SVOD market has encouraged the entry of major competitors in recent years: Apple TV+ and Disney+ in 2019, HBO Max and Peacock in 2020, Discovery+ and Paramount+ in 2021, and SkyShowtime in 2022. Soon after, the market began to show some signs of maturity, such as a slowdown in the growth of new subscriptions and an acceleration in the growth of cancellations (Chakraborty et al. 2023; Wang 2022).

In addition to growing rivalry, SVOD players face two major threats: the ease with which the public can enjoy content from pirated video sources and can use SVOD accounts without paying the required fees. Regarding the piracy threat, the direct release of film content on SVOD has made high-quality copies available almost immediately on unauthorized sites, which has ushered in a new age of piracy (De Kosnik 2020; Sharma et al. 2023). Moreover, in the last decade, the most common form of piracy has shifted from that of downloading large files in P2P networks to simpler direct viewing on streaming sites: in 2021, P2P and streaming contributed 11% and 79%, respectively, to global piracy (Alliance for Creativity and Entertainment 2022). Concerning the threat of unpaid fees, subscribers can give their login credentials to individuals living in other households (e.g., relatives, friends, and acquaintances), who can then make unauthorized use of all account content. When the SVOD market was growing rapidly, providers tacitly allowed this practice and even considered it beneficial to their business because (a) temporary sharing could serve as a test before subscription and (b) rigorous user authentication could encourage viewing the same content on illegal streaming websites (Kelly 2022; Loh 2019). Nevertheless, SVOD account sharing creates large gaps between the number of subscribers and the number of actual users: for example, Netflix acknowledged that globally almost a third of the households consuming its content did not actually have the required subscription (Nguyen 2022). The subscriber-user gap has prompted more and more industry insiders to stress (a) the importance of considering the unauthorized use of SVOD accounts as a new form of piracy and (b) the need to implement more rigorous methods of user authentication (Gardner 2019).

In an increasingly competitive market, SVOD players have a growing need for subscription revenues to provide a solid source of funding, regardless of whether such revenues account for most sales (e.g., HBO Max) or whether there are significant additional revenues from advertising (e.g., Hulu) or cross-selling (e.g., Amazon Prime) (Hadida et al. 2021; Kübler et al. 2021). However, subscription revenues are a relatively fragile source of funding over which SVOD players have limited control because the actual payment of fees ultimately relies on the goodwill of users. In this complex situation, it is important to understand which factors motivate SVOD users in their decisions to pay the required fees. Although there have been calls to investigate this issue (Schauerte et al. 2021; Guo 2022), we have found no peer-reviewed studies on which individual factors influence SVOD payment patterns.

Our study examines not only the paid and unpaid patterns but also the shared payment pattern, which is a common behavior with its own predictors and practical implications. This paper is an initial exploration of how these three patterns are influenced by various demographic, attitudinal, and behavioral factors. These factors and their measures were not specifically defined by us but directly collected from the secondary data source used (a nationally representative cross-sectional survey in Spain). The Literature Review section discusses how the influence of such factors can be understood by considering social cognitive theory, previous evidence related to digital piracy, and our own intuitions. As detailed in the Methodology section, logistic regression models were constructed to identify the influential factors of each pattern and assess their effect sizes. Among other findings reported in the Results section, the sense of duty was a positive predictor of the full payment pattern, household size was a negative predictor of the shared payment pattern, and unpaid movie downloading was a positive predictor of the non-payment pattern. The Managerial Implications section discusses how the predictors identified might help SVOD managers to tailor their interventions to monetize a larger number of actual users. Remarkably, this study examines SVOD payment patterns across platforms simultaneously and analyses various attitudinal and behavioral factors that providers do not usually collect from their subscribers.

2. Literature Review

In exchange for a monthly/annual fee, SVOD services typically allow subscribers (a) to obtain unlimited access to a wide selection of self-administered video content including original and exclusive titles, (b) to create multiple user profiles for the household members, (c) to simultaneously stream on multiple devices such as televisions, computers, tablets, and game consoles, and (d) to download their favorite content and play it offline anytime and anywhere. In addition, it is easy for users to contract, cancel, and restart their subscriptions.

Although not authorized by SVOD services, subscribers can easily share their login credentials with individuals from other households, who may then access the same selection of video content under the same viewing conditions. In turn, non-subscription users may or may not provide financial compensation to the corresponding subscribers. All of this means that actual SVOD users may have essentially three payment patterns for the services enjoyed: pay the full subscription, share the subscription fee, and pay nothing. Note that the same consumer can use different payment patterns for different SVOD services.

As a first step to understanding this phenomenon, we aim to explore which individual factors may influence the decision to pay all, part, or none of the corresponding subscriptions. Such individual factors can be tentatively understood under the umbrella of social cognitive theory, which Lowry et al. (2017) found to be the most efficient theoretical framework for the predictors of digital piracy identified in previous studies. However, it is worth noting that unauthorized SVOD use and digital piracy are partly similar and partly different. On the one hand, both behaviors consistently refer to the unauthorized use of digital content without providing the required compensation to copyright holders. On the other hand, the two phenomena show marked differences: first, there is a relatively strong (poor) social awareness of the illegitimacy of digital piracy (unauthorized SVOD use); second, digital piracy basically boils down to the dilemma of paying or not paying, while unauthorized SVOD use also covers the intermediate decision to pay only a part of the required fee.

Social cognitive theory posits that individuals’ behaviors are the result of dynamic and reciprocal interactions of personal, behavioral, and environmental factors (Bandura 1986). This theory encompasses five sets of factors that help predict digital piracy (Lowry et al. 2017): outcome expectancies, which are the anticipated consequences that individuals consider when determining whether digital piracy is worth committing (e.g., the benefit of saving money and the risk of legal repercussions); social learning, or the process by which social influences, social environment, and derived norms affect individuals’ willingness to encourage or discourage digital piracy (e.g., perceived ethicality shaped by societal values and imitation of the peers’ piracy practices); self-efficacy, which refers to the level of individuals’ confidence in their ability to successfully engage in piracy and control the desired outcomes (e.g., proficiency in obtaining pirated content and ability to avoid malware); moral disengagement, or the process by which individuals suspend or ignore their own judgment to commit piracy that they judge to be wrong, unethical, or immoral, regardless of their reasons for such a judgment (e.g., trivialization of the harm to copyright holders and minimization of one’s own responsibility); and environmental and other factors, which are the external conditions and personal characteristics that may facilitate or hinder the practice of digital piracy (e.g., internet connection quality and individual demographics).

Although the potential predictors of unauthorized SVOD use are quite numerous and varied, we are compelled to focus on the factors available in the secondary data used in this study. Specifically, 21 individual factors are examined, after being classified for convenience into three relatively homogeneous groups: six demographic factors, seven attitude-related factors, and eight behavior-related factors. The discussion of the possible influence of each factor is based on the social cognitive theory framework, the available evidence in the digital piracy field, and our intuitive understanding.

2.1. Demographic Factors

Consistent with social cognitive theory (Lowry et al. 2017), several individual demographics could influence unauthorized SVOD use in a way that is analogous to how they have been found to affect digital piracy.

The potential influence of gender is rather uncertain due to both the lack of theoretical justification and the existence of mixed evidence of its influence on digital piracy, with some studies showing a higher incidence in males than in females (Bhattacharjee et al. 2003; Coyle et al. 2009) and other studies finding no significant differences (Al-Rafee and Cronan 2006; van der Byl and Van Belle 2008). In contrast, the influence of age seems rather more likely for two reasons. Firstly, compared to older individuals, younger ones are more inclined to share passwords for their personal computers (Byrne et al. 2016) and social networks (Bevan 2018; Whitty et al. 2015), an inclination associated with a lower concern for information privacy and sharing-related risks (Byrne et al. 2016; Steijn et al. 2016). Secondly, younger individuals show a greater willingness to download copyrighted material without paying (Coyle et al. 2009; Al-Rafee and Cronan 2006). Thus, it would be reasonable to find that age is negatively related to decisions to share SVOD accounts and to pay part or nothing of the corresponding subscription fees.

The potential roles played by education and household income are suggested by intuitive arguments and empirical results. Intuitively, higher levels of education may help raise awareness of the importance of fairly compensating the content creators, while households with higher income levels are more able to pay the full fees for SVOD services. Empirically, a willingness to pay for using online digital content was found to be directly related to education (Fetscherin and Lattemann 2007) and household income (Coyle et al. 2009). Thus, it would be unsurprising to find a positive influence of education and household income on full payment for SVOD services.

Another promising demographic is household size or number of people living in the household. There is anecdotal evidence that SVOD users living in small-sized households share unused available user profiles with non-cohabitants in exchange for monetary compensation (Loh 2019). On the contrary, households with more residents than available user profiles are less likely to share their SVOD accounts. It is thus reasonable to expect that household size negatively influences the sharing of SVOD usage and payment.

Our demographic analysis also includes municipality size, despite having found neither reason nor evidence for its possible influence.

2.2. Attitudinal Factors

The SVOD full payment pattern could be positively influenced by four attitude-related factors (sense of duty, online privacy concern, attitude toward novelty, and attitude toward quality), whereas SVOD payment sharing could be positively influenced by three different ones (interest in collaborative consumption, preference for teamwork, and level of cosmopolitanism).

The sense of duty can prevent or inhibit the process of moral disengagement by which some individuals self-justify the acceptability of their piracy activities (Shang et al. 2008). This self-justification involves the neutralization of self-blame by disregarding or minimizing the violation of a personal duty and the negative impact on third parties (Lowry et al. 2017; Bandura 2002). The neutralization of the personal duty to compensate copyright holders increases willingness to engage in digital piracy (Higgins et al. 2008; Siponen et al. 2012). It is thus not surprising that a sense of duty has been found to reduce the likelihood of engaging in digital piracy (van Rooij et al. 2017), and that a similar pattern can be found with respect to unauthorized SVOD use.

Online privacy concern can fuel the expectation that piracy will jeopardize the security of personal information. In fact, engagement in digital piracy decreases with the increase in the perceived risk of personal information becoming accessible to others (Jeong et al. 2012). In the case of SVOD use, the risk comes from sharing the account password with the consequent possibility that non-cohabitants could track the account viewing history, obtain bank details, change contracted conditions, etc. Interestingly, there is anecdotal evidence that individuals more concerned about privacy and security are more reluctant to share their SVOD accounts (Sailaja and Fowler 2022). Thus, individuals with more online privacy concern will be more likely to follow an SVOD full payment pattern, which will free them from having to share the account.

Attitudes toward both novelty and quality can improve the willingness to compensate copyright holders to minimize the expectation of a lowering of artistic standards due to the losses from digital piracy and unauthorized SVOD use. Consistent with the relationship between the attitude toward novelty and the willingness to pay for copyrighted creative works (Hsu and Shiue 2008; Redondo and Charron 2013), users with a more positive attitude toward novelty might feel more compelled to properly compensate the creators of SVOD content. Considering that quality sensitivity is related to the willingness to financially contribute to digital content quality (Kim et al. 2017; Lee et al. 2019), SVOD users with a more positive attitude toward quality might be more prone to compensate providers to preserve content standards.

The interest in collaborative consumption, preference for teamwork, and level of cosmopolitanism could help build the self-efficacy required to share the use and cost of SVOD accounts. Despite sharing the same theoretical framework (Bandura 1986; Lowry et al. 2017), engaging in digital piracy primarily requires self-efficacy in technical skills (e.g., knowing how to use piracy software and how to find download sites), while engaging in SVOD sharing primarily requires self-efficacy in interpersonal skills (e.g., establishing a trusting relationship between sharers and resolving possible conflicts). The influence of technical skills on digital piracy has been observed (Cronan and Al-Rafee 2008; Sahni and Gupta 2019), but the influence of interpersonal skills on SVOD sharing remains unexplored. Even without prior evidence, there are good reasons to speculate on the possible influence of the three factors studied. Firstly, since collaborative consumption is about consumers sharing resources (e.g., car sharing and peer-to-peer accommodation), users more interested in collaborative consumption could be more inclined to share the use and cost of SVOD accounts. Secondly, as teamwork is based on interaction and cooperation with others to efficiently manage work and non-work activities, individuals with a greater preference for teamwork may be more likely to enjoy the mutual benefit of sharing the use and cost of SVOD accounts. Thirdly, considering that cosmopolitan individuals have more online interaction and collaboration with people from other countries/cultures, the level of cosmopolitanism could influence the likelihood of sharing the use and cost of SVOD accounts.

2.3. Behavioral Factors

The entry of new competitors is an environmental change that highlights the number of SVOD services used as one of the most potentially influential factors in users’ payment patterns. Consumers are of course attracted by the growing range of SVOD providers, each with exclusive content, but are also turned off by the high cost of subscribing to all or many of them (Loh 2019). In order to enjoy a greater number of SVOD services, consumers might agree among themselves to share the use and cost of multiple subscriptions.

Price sensitivity shapes users’ financial expectations when deciding whether or not to pay for copyrighted content (Jacobs et al. 2012; LaRose and Kim 2007). Intuitively, a negative relationship between price sensitivity and a willingness to pay copyright fees can be expected. Indeed, there is evidence that less price-sensitive users are more likely to pay for their movie downloads (Redondo and Charron 2013), while more price-sensitive ones are more likely to consume pirated movie content (Ho and Weinberg 2011). Similarly, less (more) price-sensitive SVOD users might be more inclined to pay the full subscription (to pay anything at all).

Past piracy behavior has a positive effect on the current intention to engage in digital piracy (Cronan and Al-Rafee 2008), an effect that has been attributed to both habituation (Ajzen 2002) and moral disengagement (Garbharran and Thatcher 2011). If individuals have engaged in digital piracy, it is likely that they have previously invoked the moral disengagement mechanism and that they currently require less moral disengagement to justify the same behavior (Garbharran and Thatcher 2011). Similarly, individuals who have engaged in unpaid movie downloading might reasonably require less moral disengagement to justify an unpaid use of SVOD content. Thus, unpaid movie downloading is a promising candidate for influencing the pattern of unpaid SVOD use.

Individuals who are more motivated by self-interested reasons are more likely to use moral disengagement mechanisms to justify the acceptability of their antisocial behaviors (Kish-Gephart et al. 2014). Conversely, individuals who participate in charity and community activities show that they put the interests of others before their own interests, which is contrary to the practice of benefiting oneself from free content at the expense of the legitimate benefit of creators. Thus, charity and community participation could influence the willingness to give fair compensation to the creators of SVOD content consumed.

Finally, we include four factors whose influence on SVOD payment patterns is difficult to specify a priori: binge-watching behavior, which is a frequent practice among the most enthusiastic SVOD users; frequency of cinema attendance, which shows the fondness for watching movies in the most traditional way; level of video-on-demand (VOD) use, which reveals the extent to which the self-administered consumption of video content is preferred; and level of internet use, which indicates the extent to which the internet is used in ordinary activities. Within the framework of social cognitive theory, these four factors can be classified as environmental factors that can act as enablers or inhibitors of the willingness to pay for SVOD content.

3. Methodology

3.1. Data

The data were obtained from AIMC Marcas, a secondary source of information that numerous mass media and advertising agencies in Spain use to manage their media content and advertising campaigns. AIMC Marcas is an annual survey that, since its inception in 2003, has consisted of interviewing about 10,000 individuals living in Spain, aged 14 years or older. This survey includes a wide variety of questions about attitudes and exposure to mass media, purchasing and consumption habits, values and lifestyles, leisure-related attitudes and behaviors, etc. The survey is managed by AIMC (Asociación para la Investigación de Medios de Comunicación), an independent and non-profit organization that represents many stakeholders from the Spanish media and advertising industries. In turn, the execution of the questionnaire, fieldwork, and data processing is delegated to the Kantar TNS company.

The data used in this study (Redondo and Serrano 2023) were drawn from the 2018 survey. Of those interviewed in that year, 87% came from Kantar TNS regular panelists, who had been selected through a purposive sampling method aimed at reflecting the Spanish population in terms of region, municipality, gender, age, household income, family role, and household size; and 13% came from another AIMC survey (Estudio General de Medios), from participants who had been selected through a random route procedure. The fieldwork was carried out in three waves between May and December. The self-administered questionnaire could be completed either in a hard-copy format (delivered and returned by mail) or online (option chosen by one third of the participants). Participation was encouraged by offering 50 euros in cash or an equivalent gift from a catalogue to the participants who adequately responded to the questionnaire. From the 10,789 completed questionnaires received, 332 had to be excluded for incorrect completion. Thus, the final sample consisted of 10,457 subjects, whose basic demographics are shown in

Table 1. Demographic distribution of the data.

Demographic	Categories	AIMC Data (N = 10,457)	SVOD Users (N = 1420)
Gender	Male	45.5%	50.2%
	Female	54.5%	49.8%
Age	14–18	3.5%	3.7%
	19–30	12.4%	21.7%
	31–40	11.8%	19.2%
	41–50	21.9%	26.7%
	51–60	22.5%	18.2%
	61–70	15.3%	8.0%
	71 or older	12.6%	2.5%
Education	Less than primary	1.3%	0.1%
	Primary	7.7%	2.0%
	Secondary	54.1%	46.1%
	Tertiary	31.7%	43.3%
	Postgraduate	5.2%	8.5%
Household income (euros)	Less than 745	4.5%	1.2%
	745–1312	15.5%	8.0%
	1313–1602	11.9%	7.7%
	1603–2145	27.7%	26.7%
	2146–2451	14.9%	17.5%
	2452–3005	18.9%	28.8%
	More than 3005	6.5%	10.2%
Household size (persons)	1	9.0%	5.9%
	2	30.7%	24.6%
	3	24.8%	27.8%
	4	28.4%	32.9%
	5 or more	7.1%	8.8%
Municipality size (inhabitants)	Less than 2001	5.2%	2.8%
	2001–5000	6.3%	3.8%
	5001–10,000	7.3%	5.7%
	10,001–50,000	25.1%	25.4%
	50,001–200,000	22.9%	23.7%
	200,001–500,000	12.6%	10.9%
	More than 500,000	20.6%	27.7%

.

3.2. Variable Description

Regarding the dependent variables, participants were asked if they used (a) any SVOD platform for which they and/or other household members paid the full subscription (a pattern measuring all-payers); (b) any SVOD platform for which they and/or other household members shared the subscription fee with people from other households (partial payers); and (c) any SVOD platform for which neither they nor any other member of the household paid anything at all (non-payers). Each of these patterns was coded 1 if applicable and 0 otherwise. Note that the three dependent variables were not mutually exclusive because the same participant could have used a certain pattern for one SVOD platform and a different pattern for another.

Concerning the independent variables, the attitude toward novelty, attitude toward quality, level of cosmopolitanism, price sensitivity, level of VOD use, and level of internet use were computed by averaging four items (Appendix A), with each item rated on a 5-point Likert scale (from −2 = completely disagree, to 2 = completely agree). Six other independent variables were measured with one item on the same Likert scale: sense of duty, with “It’s more important to do your duty than to live just to enjoy yourself”; online privacy concern, with “I’m concerned about the security of the personal information I put on the internet”; interest in collaborative consumption, with “I’m interested in new collaborative consumption practices”; preference for teamwork, with “I prefer to work in a team rather than on my own”; charity and community participation, with “I actively participate in charity and community activities”; and binge-watching behavior, with “I like to binge-watch the TV series I have previously downloaded or recorded”. The remaining independent variables were measured as follows: the number of SVOD services was calculated by counting how many of the 13 SVOD services listed in the questionnaire (Appendix A) had been used by the respondent in the last 12 months; unpaid movie downloading was coded 1 if the respondent had downloaded any movie, TV show, or program without paying in the last 12 months, and 0 otherwise; and the frequency of cinema attendance was measured with an 8-category ordinal scale (from 0 = never, to 7 = twice or more per week).

3.3. Statistical Analysis

Preliminarily, the reliability of multi-item measures was assessed by Cronbach’s alpha coefficients, which indicated sufficient internal consistency when exceeding the recommended value of 0.7 (Hair et al. 2018).

For each dependent variable, a binary logistic regression model was built to identify the influential factors and assess their effect sizes. Note that constructing a multinomial logistic regression model would have been inappropriate because the three payment patterns were not mutually exclusive. The three models were built using a forward stepwise selection procedure, which is appropriate for exploratory research and consists of iteratively adding and removing candidate factors until there are no remaining candidate factors that provide an improvement in the model fit (Hair et al. 2018).

The coefficients resulting from each logistic regression model are statistically robust and easily interpretable: (a) the sign of the B coefficient shows the direction of the relationship between the predictor and the dependent variable; (b) the Wald statistic tests the significance of the estimated B coefficient; and (c) the value of Exp(B) indicates the magnitude of the effect—that is, (Exp(B) − 1) × 100 equals the percentage change in odds resulting from a unit increase in the predictor (Hair et al. 2018).

All statistical analyses were performed with SPSS for Windows (version 26, IBM SPSS, Armonk, NY, USA, 2019), and the significance level was set at p < 0.05.

4. Results

A total of 1420 participants reported being SVOD users, who, compared to the entire AIMC sample, showed demographics associated with lower age levels, higher education and income levels, and larger municipality and household sizes (Table 1). Among the SVOD users, 766 reported following a pattern of all-payers, 347 a pattern of partial payers, and 350 a pattern of non-payers. Since a total of only 1463 patterns were reported by the 1420 users, the combination of different patterns was found to be a rather rare practice.

Regarding the reliability of the multi-item scales, Cronbach’s alpha equaled 0.72 for the attitude toward novelty, 0.70 for the attitude toward quality, 0.71 for the level of cosmopolitanism, 0.71 for price sensitivity, 0.79 for the level of VOD use, and 0.85 for the level of internet use, all values indicating acceptable levels of internal consistency.

Concerning the model for all-payers (

Table 2. Binomial logistic regression for all-payers.

Predictors Included in the Model	B	Std. Error	Wald	df	Sig.	Exp(B)
Age	0.02	0.00	12.59	1	p < 0.01	1.02
Household size	0.14	0.05	7.68	1	p < 0.01	1.15
Sense of duty	0.12	0.06	3.83	1	p < 0.05	1.12
Interest in collaborative consumption	0.15	0.07	5.47	1	p < 0.05	0.86
Number of SVOD services	0.15	0.07	4.65	1	p < 0.05	1.16
Price sensitivity	−0.26	0.09	8.85	1	p < 0.01	0.77
Charity and community participation	0.14	0.05	7.82	1	p < 0.01	1.15
Level of VOD use	0.16	0.07	5.48	1	p < 0.05	1.17
Constant	−0.82	0.27	9.59	1	p < 0.01	0.44

), 8 of the 21 candidate factors were identified as predictors, either in one direction or the other. On the one hand, the full payment pattern was negatively affected by price sensitivity and the interest in collaborative consumption, which produced odds ratio reductions of 23% and 14%, respectively. On the other hand, this pattern was positively affected by the level of VOD use (17% increase in odds), number of SVOD services (16%), household size (15%), charity and community participation (15%), sense of duty (12%), and age (2%).

The model for partial payers identified four influencing factors (

Table 3. Binomial logistic regression for partial payers.

Predictors Included in the Model	B	Std. Error	Wald	df	Sig.	Exp(B)
Age	−0.02	0.01	10.92	1	p < 0.01	0.98
Household size	−0.16	0.06	7.47	1	p < 0.01	0.85
Level of cosmopolitanism	0.20	0.09	5.08	1	p < 0.05	1.22
Number of SVOD services	0.28	0.07	14.15	1	p < 0.01	1.31
Constant	−0.72	0.30	5.64	1	p < 0.05	0.49

). The number of SVOD services and level of cosmopolitanism had positive effects with odds increases of 31% and 22%, respectively. Contrarily, household size and age had negative effects, with odds reductions of 15% and 2%, respectively.

The model for non-payers identified two positive and four negative influencing factors (

Table 4. Binomial logistic regression for non-payers.

Predictors Included in the Model	B	Std. Error	Wald	df	Sig.	Exp(B)
Number of SVOD services	−0.35	0.09	13.99	1	p < 0.01	0.71
Price sensitivity	0.33	0.10	10.90	1	p < 0.01	1.39
Unpaid movie download	0.33	0.14	5.57	1	p < 0.05	1.39
Charity and community participation	−0.13	0.06	4.71	1	p < 0.05	0.88
Frequency of cinema attendance	−0.09	0.05	3.94	1	p < 0.05	0.91
Level of VOD use	−0.31	0.08	17.15	1	p < 0.01	0.73
Constant	−0.64	0.18	11.93	1	p < 0.01	0.53

). Price sensitivity and unpaid movie downloading were strong positive predictors, both producing an increase of 39% in odds. In turn, negative effects were found for the number of SVOD services (29% reduction in odds), level of VOD use (27%), charity and community participation (12%), and frequency of cinema attendance (9%).

5. Discussion

Among all the reported payment patterns (1463), almost half (347 partial payers and 350 non-payers) corresponded to unauthorized behaviors in which users benefited from SVOD services but paid only a portion or none of the subscription fees. This observation suggests that SVOD providers are losing a substantial part of their potential revenue and that monetizing all actual users poses a critical but complex challenge, as discussed in the Managerial Implications section.

Another remarkable finding is that very few users combined different payment patterns; that is, almost all users consistently had the same payment pattern across the different SVOD platforms used. This observed consistency suggests that drivers of payment patterns be studied by focusing more on individual-related factors than on SVOD service-related factors.

The model for all-payers identified six drivers consistent with our expectations: those who paid the full subscription (a) were less price sensitive, (b) were less interested in collaborative consumption, (c) lived in more crowded households, (d) participated more in charity and community activities, (e) had a greater sense of duty, and (f) were older. Note that price sensitivity (Redondo and Charron 2013), sense of duty (van Rooij et al. 2017), and age (Coyle et al. 2009; Al-Rafee and Cronan 2006) have been found to play analogous roles in predicting the rejection of digital piracy, whereas to our knowledge the findings on collaborative consumption, household size, and community participation have never been reported. Contrary to our expectations, the number of SVOD services was positively related to all-payers, meaning that these individuals took on the high cost of multiple subscriptions without taking advantage of the ease of sharing accounts and expenses with other users. However, all things considered, this finding can be tentatively explained by these individuals’ low interest in prices and high interest in avoiding collaborative consumption and in complying with standards of duty and selflessness. It should also be noted that future studies may find the expected negative relationship when data incorporating the recent entries of SVOD services are analyzed. Furthermore, the level of VOD use, whose effect was unpredictable to us, turned out to be a positive driver of the full payment pattern. As a possible explanation, we suggest that users more inclined to view self-administered video content could better justify full payment because they perceive a comparative advantage over broadcast schedule-based video services.

The four predictors included in the model for partial payers were largely consistent with expected relationships: The probability of sharing payment increased as users (a) consumed a greater number of SVOD services, (b) had a higher level of cosmopolitanism, (c) lived in less crowded households, and (d) were younger. The result regarding household size confirms some preliminary evidence on SVOD sharing (Loh 2019), the result regarding age is analogous to the reported evidence on password sharing (Bevan 2018; Byrne et al. 2016), and the findings on the number of SVOD services and level of cosmopolitanism seem to be reported for the first time.

The model for non-payers showed, as expected, that these individuals were (a) more price sensitive, (b) more active in unpaid movie downloads, and (c) less involved in charity and community activities. However, unexpectedly, non-payers were also characterized by consuming fewer SVOD services, which could occur because these users might be getting their desired video content through unpaid downloads. In addition, the level of VOD use and frequency of cinema attendance had unanticipated negative effects, suggesting that non-payers were less involved in film viewing in both self-administered and theatrical formats. Note that all the predictors of non-payers appear to be first reported here, although there was evidence on the effect of price sensitivity on digital piracy (Ho and Weinberg 2011).

Six factors did not produce the expected effects. Firstly, education, attitude toward novelty, and attitude toward quality did not encourage payment for viewed SVOD, despite their previously reported impact on payment for downloaded digital content (Fetscherin and Lattemann 2007; Redondo and Charron 2013). This finding suggests that SVOD account sharing, compared to peer-to-peer file sharing, may be perceived as not obviously detrimental to the support and development of creative works. Household income also did not encourage payment for SVOD services, which could be explained by the fact that subscription fees are low enough that most households can afford them. In addition, online privacy concern did not prevent the sharing of SVOD accounts, which could mean that users involved in this practice are not sufficiently aware of its risks. Finally, the preference for teamwork did not encourage the sharing of SVOD accounts, which could simply indicate an insufficient connection between them.

6. Managerial Implications

With demand growth slowing and new competitors entering the market, SVOD providers face the difficult challenge of monetizing as many as possible of the numerous users who consume SVOD content either for free or at a reduced price. However, the real challenge encompasses both maintaining the current revenues from all-payers and achieving the potentially generated revenues from partial payers and non-payers, which are two very different groups: There are high expectations for partial payers, who already pay a part of the subscription and thus show an undoubted fondness for the service; but expectations are low for non-payers, who pay nothing and who show little fondness for movies, significant involvement in unpaid movie downloads, and a low sensitivity to others’ rights. It is therefore advisable for SVOD providers to focus more on monetizing partial payers than non-payers.

In order to restrict the sharing of SVOD accounts with non-cohabitants, providers could impose authentication with a fingerprint or a code received via SMS/email, registration of a limited number of devices to accounts, limiting the number of concurrent sessions, etc. However, these restrictions can be double-edged swords because, while they are likely to reduce unauthorized account sharing, they could also affect the loyalty of all-payers whose viewing experience is disrupted. Furthermore, explaining the reasons justifying the restrictions could also produce mixed effects: all-payers would easily understand such reasons due to their heightened sense of justice and selflessness but might think that they are being punished for the wrongdoing of others. In particular, the limitation of the number of concurrent sessions could be easily misperceived by all-payers, for whom household size is a positive influential factor and on whom a restriction on concurrent use by their family members would be burdensome. Interestingly, Netflix has just started requiring users to authenticate when accessing from an unusual location, which hampers account sharing with residents of other locations but also annoys subscribers who travel or spend a few days in second homes. Netflix has also started to facilitate the regularization of non-subscribing users by reducing its basic fees and enabling the transfer of a profile from an existing account to a new one. Unfortunately, Netflix will most likely not make public whether and to what extent these various decisions succeed in increasing its number of subscribers and total income.

A major effort should be directed at preventing partial payers from sharing payment and use of SVOD accounts among themselves. Importantly, partial payers do not manifest the standards of justice and selflessness of full payers but neither are they characterized by downloading movies without paying as are non-payers. It then would not be surprising that some partial payers just lend and borrow SVOD account credentials similar to those who lend and borrow books with friends and family. These individuals should be warned that their seemingly innocuous practice is a clear breach of the terms of use accepted by subscribers—that is, an unauthorized practice with harmful effects on SVOD providers. It would be highly advisable for SVOD providers to jointly promote this awareness because (a) all of them are harmed by the sharing of SVOD accounts, (b) SVOD sharers are likely to be more receptive to messages coming simultaneously from shared services, and (c) observed payment patterns are generally consistent—that is, they hardly vary among the SVOD providers. Understandably, partial payers who are more aware of the unfairness of SVOD sharing might be more receptive to lower-priced ad-supported subscription tiers, which would allow SVOD providers to generate subscription revenues from these users, as well as earn additional revenues from the ads shown to them. In fact, a growing number of SVOD platforms have started to offer ad-supported subscription options (Kweon and Kweon 2021), but no scholarly study has yet been published on the impact of this practice on the actual revenues of providers (Zhou et al. 2023).

In order to prevent the non-payment pattern, it is not advisable to try to directly dissuade non-payers, who are unlikely to accept the duty to fairly compensate SVOD providers. However, it is quite advisable to indirectly prevent subscribers from revealing their credentials to third parties. In this sense, providers could encourage subscribers to be aware of the privacy and security risks associated with the transfer of access credentials: Recipients of credentials (initially received from subscribers or subsequently from other recipients with or without subscribers’ consent) could access viewing history and personal and banking data, change such data and contracted conditions, etc.

Finally, as SVOD account sharing is not prevented by novelty and quality sensitivity, SVOD providers are advised to jointly promote the need to fairly compensate creators in order to recover their investments and maintain enough funding to undertake new projects with high levels of creativity and quality.

7. Limitations

The most important limitation was the cross-sectional nature of the data, which provided a static representation of a dynamic phenomenon: SVOD usage and payment patterns are affected by market and environmental changes and are easily modifiable because subscribers can contract, cancel, and restart their accounts at any time. After the period surveyed here, an important market change was the entry of several platforms, which probably caused an increase in the shared payment pattern linked to the increase in the number of platforms used. Additionally, an important environmental change occurred in the form of the COVID-19 pandemic lockdowns, which caused reported increases in the number of SVOD subscribers (Vlassis 2021) and also likely increases in platform account sharing.

Another notable limitation was the use of a secondary data source, which did not allow us to include ad hoc questions. The predetermined questions allowed for measuring a large number of potentially influential factors, but many others have been excluded in this analysis. This does not seem relevant for demographics but might be quite relevant for attitudinal and behavioral factors. As examples, we suggest (a) in the attitudinal domain, how users ethically evaluate password sharing and unpaid consumption, and how these patterns are affected by the opinions of relatives, friends, and colleagues; and (b) in the behavioral domain, what motivates users to share or not share certain goods/services online/offline and to undertake or not undertake unpaid consumption of digital products. In addition, we did not have the possibility of measuring the variables with the desired level of detail. For example, the partial payers variable does not distinguish various situations that are relevant to the phenomenon studied: sharing with one, several, or many people; contributing a small, medium, or large part of the subscription fee; and using or not using specialized sharing websites such as Together Price. Another example is that the variables of all-payers and partial payers do not determine whether the SVOD user has personally paid all/part of the subscription fee or whether someone else in the household has paid. It would also have been interesting to know how the SVOD user contributed to deciding the corresponding payment pattern.

The self-reported nature of the data was also a limitation because the reported information could contain inaccuracies and errors that respondents may have made either intentionally or unintentionally. It is worth noting that questions about SVOD payment patterns might have been sensitive for some respondents, who might then have avoided reporting acts that they or their peers considered inappropriate.

8. Future Research Directions

After this initial exploration of SVOD payment pattern predictors, future studies are recommended to examine the phenomenon in greater breadth and depth. In this regard, we suggest (a) analyzing other countries to increase representativeness and discover possible cultural/geographic differences; (b) examining new factors that facilitate the identification of predictors that remain unknown; (c) performing dynamic analyses to measure the influence of market and environmental changes; and (d) making more detailed measurements of the variables so that all relevant situations are well represented.

Furthermore, we strongly recommend conducting experiments to measure how different actions could improve the monetization of the users who do not pay the full subscription. Such actions might include restrictions on account sharing (user authentication, device registration, etc.), explanations for such restrictions, subscription facilitations (basic fee reduction, transfer of profiles to new accounts, etc.), and awareness campaigns (about privacy/security risks, appropriate creator compensation, etc.). Testing actions with different degrees of intensity could provide valuable practical implications for SVOD providers. It would be important to distinguish the effects on the three segments analyzed here (all-payers, partial payers, and non-payers) and to include a new group: those who stop using the service due to potential boomerang effects. Certain factors potentially influencing users’ responses (perception of unfairness, psychological reactance, etc.) might also be included. Finally, the interactive effects of different actions with the drivers already identified (limitation of concurrent sessions with household size, awareness of the sharing problem with number of SVOD services, etc.) might be analyzed.

9. Conclusions

Several reasons prompt SVOD managers to work more actively on monetizing users who do not pay the subscription fees required. Firstly, the SVOD market is entering a maturation phase, with slowing growth and increasing competition, all of which threaten revenue sustainability. Secondly, the high prevalence of unauthorized payment patterns means a massive loss of revenue for SVOD providers, who now are encouraged to react more actively than in the past. Thirdly, this study’s findings provide some insights that may help in the difficult task of deterring unauthorized payment patterns without discouraging the appropriate payment pattern. Such findings suggest that SVOD providers (a) focus on monetizing partial payers rather than non-payers; (b) work together to foster awareness that SVOD account sharing is an unauthorized practice with harmful effects on providers; (c) encourage subscribers to become aware of the privacy and security risks associated with sharing access credentials; and (d) promote fair compensation for creators to obtain enough funding to develop new projects with high levels of quality and creativity. Although some progress has been made thus far, research on this topic is still in its infancy. It is becoming urgent to examine how consumers react to efforts aimed at increasing end-user monetization. We suggest that this topic be investigated across all SVOD providers, and the results be published for the benefit of the entire industry.