1 Introduction

According to the Personal Cloud Market Research Report “Global Forecast till 2023,”Footnote 1 the Personal Cloud Market was valued at USD 14.51 billion in 2017 and is estimated to reach USD 125.92 billion by the end of 2023. The most popular cloud computing services among individuals are Microsoft’s OneDrive, Dropbox, Google Drive, Apple’s iCloud and Amazon Web Services. Some firms use a price strategy known as freemium, which consists of providing some online content for free, thus attracting customers and earning money from advertisements, and at the same time providing fee-based extra online content or features (Wagner et al. 2014). This strategy has led consumers to ask themselves why they should pay for cloud services. While companies may see the advantages of paying for cloud use (Gupta et al. 2013), individual consumers may be reluctant to do so; previous research has found that consumer willingness to pay for online content is relatively weak (Chyi 2012). Cloud services are one of the service contexts where the freemium strategy has increased in popularity, but little is known about which characteristics of cloud services increase payment likelihood (Yan and Wakefield 2018).

The communication strategy of some cloud service providers emphasizes greater storage space as the main factor encouraging users to pay for the service; other providers emphasize access to more online content. These strategies depend on the service’s aims; not all consumers use cloud services in the same way or for the same purposes, so they do not attach the same importance to cloud service offerings, and this segments the market. Recent research based on generational cohort theory has found that individuals from different generations show different concerns, motivations and behavior related to the use of information technologies, social and ethical values, and privacy and security concerns (Chen et al. 2017; Feng and Xie 2014; Miltgen and Peyrat-Guillard 2014; Moqbel et al. 2017). Although there is some disagreement about exactly how to categorize particular generations, researchers agree that the main generations are Generation Z, Millennials (or Generation Y), Generation X, Baby Boomers and the Silent Generation. Previous research has found that young adults are heavy users of online content services (Christofides et al. 2011), but it is inadvisable to focus only on this group of consumers. The digital immigrant generations are also important users of cloud services, although their motivations may be different from those of the digital natives. It is therefore important to use rigorous, representative data to establish the effects of age on the usefulness and value of cloud services and the managerial implications of these effects.

Research into online services, including personal cloud services, should consider privacy and security, as these are aspects that influence the adoption of these services (Ghaffari and Lagzian 2018; Hsu and Lin 2016; Lee 2016). Recent interest has focused on the effect of negative experiences on the protection behavior of different generations (Chen et al. 2016; Elhai et al. 2017). The protection behaviors examined include for example, use of fake names or changing of passwords. Research has suggested that some customers may be willing to pay a premium for security and privacy (Tsai et al. 2011; Schreiner and Hess 2015; Schreiner et al. 2013). In their freemium versions, some firms offer extra control and privacy and security features, thereby providing users with added value (Schreiner et al. 2013). However, little is known about the effect of negative privacy and security experiences on the decision to pay more for a service (with some exceptions: Tsai et al. 2011; Schreiner and Hess 2015; Schreiner et al. 2013). Evidence for differences between generations in terms of privacy and security concerns and protection behavior is also scarce (Halperin and Dror 2016), as most previous studies have focused on a single generation. Thus, the lack of evidence and the ambiguities surrounding generational differences make this fertile ground for additional research.

The aim of this paper is to examine whether age moderates the relationship between usefulness attributes of cloud services and payment for those services, and between past negative experiences and payment. To accomplish these objectives, a survey of 2840 users of cloud services is analyzed. The paper contributes to consumer behavior and information systems research by analyzing the differences in the usefulness attributes of cloud services that different age cohorts pay for. Apart from general attributes of cloud services (ubiquity, file sharing, data backup and storage space), the effect of previous negative experience related to security and privacy is also examined. The paper thus contributes to protection motivation research, which has so far focused on individuals’ reactions to negative privacy experiences. Previous research has also suggested a gap between intention and behavior, and the present study builds on this with an emphasis on actual payment behavior, allowing comparison with previous research focused on willingness to pay.

The next section of this paper discusses generational cohort theory, and Sect. 3 presents the model and hypotheses. Section 4 describes the methodology, and Sect. 5 gives the results, which are then discussed in Sect. 6. Section 7 concludes by highlighting the main theoretical and practical implications of this research, its limitations and suggestions for future lines of research.

2 Generational cohort theory

Age is a well-recognized factor that explains differences in consumer behavior in online content consumption and digital culture (Lee 2009; Yang et al. 2015; Zhitomirsky-Geffet and Blau 2016). Generational cohort theory suggests that people who have lived at the same period of time and have had similar experiences will exhibit similar values, attitudes and beliefs, and that they will differ in these from other generations (Strauss and Howe 1991). People are greatly influenced by external or environmental events, such as economic depression, wars and political events. Ultimately, such events will shape preferences, desires, attitudes and buying behavior. In the last decade, special attention has been paid to behavioral differences between generational cohorts (Hauk et al. 2018; Lissitsa and Kol 2016; Moore 2012; Zhitomirsky-Geffet and Blau 2016). This theory has been applied in different contexts, such as work research (Kuron et al. 2015; Liu et al. 2019), politics research (Milkman 2017) or business decisions (Hur et al. 2017; Mosquera et al. 2018; SivaKumar and Gunasekaran 2017). Although there is some variation in how generational cut-offs are defined, there is a consensus about the main generations: the Silent Generation, the Baby Boomers, Generation X, Millennials (or Generation Y) and Generation Z. Figure 1 illustrates these generations in terms of age cohorts.

Fig. 1
figure 1

Source: Dimock (2019). Defining generations: where Millennials end and Generation Z begins

Consumer generations by birth year and current age

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The Silent Generation lived during World War II. People from this generation are considered stable, loyal and hard-working (Pew Center Report 2010). Baby Boomers are considered as individualistic and as having strong ethical values, being active in the defense of human and workers’ rights (Strauss and Howe 1991). Generation X is highly educated with a strong interest in personal life and a lack of trust in institutions; people from this generation look for self-fulfillment and are highly individualistic (Yu and Miller 2005). This group lived through the birth of the internet (Pew Center Report 2010) and tends to humanize technologies (Reisenwitz and Iyer 2009). Millennials (or Generation Y) are the group that has attracted most attention from researchers. Millennials are the first generation to have worse lifelong economic and social prospects than their parents, with costs rising and job security decreasing (Cannon and Kendig 2018). They show less loyalty and feel more comfortable with the internet and technologies than older generations, and they are less risk averse than Generation X (Reisenwitz and Iyer 2009). Some researchers have examined this group in order to understand its preferences and behavior (Eastman et al. 2014; Liu et al. 2019; Moqbel et al. 2017; Purani et al. 2019; SivaKumar and Gunasekaran 2017), while others have compared Millennials with mature consumer behavior (Hur et al. 2017; Mosquera et al. 2018; Suh et al. 2017). In recent years, research has suggested that it is necessary to split this group, dividing it into younger and older Millennials (Bolton et al. 2013; Debevec et al. 2013; Garikapati et al. 2016; Schewe et al. 2013). Younger Millennials value autonomy in controlling their environment and are heavy consumers of social media, valuing the personalized service and instant communication it provides (Youn and Kim 2019). Compared to older Millennials, they are less concerned about politics, sustainability, saving or making mistakes in life (Debevec et al. 2013). The present study examines the differences in aspects of cloud services that each generational cohort finds valuable and that influence the likelihood that they will pay for these services.

3 Model and hypothesis development

In the context of digital services, perceived value is the most important factor that determines payment (Chu and Lu 2007; Hsiao 2011; Lu and Hsiao 2010). Research has found that usefulness and security concerns are the two main factors in the decision to adopt cloud services (Arpaci 2016; Ghaffari and Lagzian 2018; Hsu and Lin 2016; Lee 2016; Yang and Lin 2015). Although these aspects are considered as valuable characteristics of cloud services, a question remains as to their role in encouraging users to pay for those services. Table 1 summarizes the literature on willingness to pay and purchase intentions for cloud services. Yan and Wakefield (2018) concluded that perceived value is explained by ease of use, reliability and usefulness in terms of access. Similarly, Wang and Lin (2016) found that service quality, a construct that includes service access, trust, ease of navigation and reliability, is important in explaining payment for cloud services. It appears that payment for cloud services is explained mainly by their usefulness attributes, and that privacy and security concerns are two main drivers of cloud adoption (Hsu and Lin 2016). According to protection motivation theory, negative privacy and security experiences lead users to adopt protection strategies, but little is known about whether payment is one such protection strategy or about how negative experiences affect different generational cohorts.

Table 1 Summary of research on payment for digital services, 2004–2018
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3.1 Usefulness attributes of cloud storage services

The attributes that make cloud services valuable are ubiquity, data or file storage, access to greater resources (i.e., libraries of music, films, videos and e-books), ease of sharing files and documents, and protection and backup of information (Arpaci 2016; Burda and Teuteberg 2016; Koehler et al. 2010; Park and Kim 2014; Yoon and Kim 2007).

Previous research has suggested that one of the attractive aspects of cloud services is that they can be accessed anywhere and at any time, which increases their flexibility and consequently their usefulness (Arpaci 2016; Burda and Teuteberg 2016; Ion et al. 2011). Ubiquity can also lead users to switch from an incumbent technology to cloud services (Bhattacherjee and Park 2014) as a way of increasing perceived quality (Burda and Teuteberg 2015). Furthermore, users are willing to pay for on-demand movies and TV programs because of the greater convenience of these services (Goyanes 2014; King and King 2017; Koças and Akkan 2016). However, younger generations have grown up with digital devices (Kim and Huh 2007) and are used to having everything connected; they take it for granted that they can access their resources anywhere and at any time. As a result, they will not be willing to pay for ubiquity, as they regard this as an essential feature that should be free. However, individuals who have lived through the digital transition (digital immigrants) may perceive ubiquity as providing added value; because they have experienced the lack of ubiquity, they will value it more than younger consumers and will pay for this aspect of the technology. These considerations lead to the first hypothesis:

H1

Ubiquity will have a greater positive effect on cloud services payment for older generations than for younger Millennials.

Two further valuable features of cloud services are their capacity for data/file storage (Burda and Teuteberg 2016; Moqbel et al. 2017; Sharma and Singh 2012) and the access they provide to a greater number of resources, including libraries of music, movies, TV programs and e-books (Park and Kim 2014; Sharma et al. 2016). In addition to accessing these libraries, individual users can also form their own collections and share files with their peers (Lee et al. 2017). According to previous research, consumers are willing to pay for services that allow them to access, download, collect and share files (Weijters and Goedertier 2016). Compared to other generations, Millennials are more familiar with internet technology; they are heavy users of online content (Christofides, Muise and Desmarais 2011), and they prefer online streaming services for entertainment. Older generations may be more likely to use traditional media such as radio, newspapers or TV for information and for entertainment (Bondad-Brown, Rice and Pearce 2012). However, older generations, such as Generation X and Baby Boomers, will value more than Millennials the possibility of storing data or files that can be accessed anywhere. So, as users from the older generations become used to having these services, and owing to inertia, once they reach the limit of free data storage space, the need for additional storage space can lead them to pay. Service providers have taken advantage of this opportunity and developed “pay-as-you-go” models that offer limited free space and charge additional fees depending on the amount of space that users need (Schreiner et al. 2013; Schreiner and Hess 2015; Tsai et al. 2011). Therefore, the possibility of having greater amounts of storage space will be a more important aspect for older generations, whereas access to online libraries of music, films or TV services will be a more important reason for younger Millennials to pay. These considerations lead to the second and third hypotheses:

H2

Accessing larger amounts of storage space will have a greater effect on cloud services payment for older generations than for younger Millennials.

H3

Accessing more online resources will have a greater effect on cloud services payment for younger Millennials than for older generations.

Another reason that both individuals and firms use cloud services is to have backup systems against data loss (Rahumed et al. 2011; Zafar et al. 2017). Park and Kim (2014) suggested that use of cloud services can reduce the risk of data loss, as most service providers have a backup system to recover files. Companies may be concerned about the possibility of the service being destroyed or of hacker attack causing important data and information to be destroyed (Sharma and Singh 2012). Individual users may be worried about similar risks for personal computer use, and may likewise use cloud services to store information as a convenient backup system (Celesti et al. 2016). It has been noted that younger Millennials use cloud services for entertainment purposes instead of for data storage. Using cloud storage as protection against data loss is therefore relatively unimportant for them. However, older generations such as the Baby Boomers will be more concerned about security breaches (Chakraborty et al. 2016) and the consequences of those breaches, such as loss of or damage to personal information. We expect that older users will value cloud services as a convenient backup strategy more than younger users. These considerations lead to the fourth hypothesis:

H4

Data loss protection will have a greater effect on cloud services payment for older generations than for younger Millennials.

Another function of cloud services is ease of sharing files, documents and pictures. Sharing behavior is a social phenomenon that started with the growth of Web 2.0 technologies and has attracted the attention of researchers (Liou et al. 2016). These technologies created online platforms to promote collaboration and sharing of information and knowledge. The possibility of sharing files faster and more easily (Arpaci 2016; Yoon and Kim 2007) is one of the most important factors in business users continuing to use cloud services (Koehler et al. 2010) and is surpassed only by flexibility. Younger Millennials are digital natives, used to new technologies and generally able to use unfamiliar technologies with ease (Ng 2012). Ease of use is therefore less important in explaining their adoption of e-technologies (Lucia-Palacios et al. 2016; Shiau and Chau 2016); older generations, however, will attach greater importance to how easy it is to download and share files. Younger Millennials are used to sharing information and files in different ways (including via WhatsApp and social networks) and using different media devices. Sharing is a more important aspect for them than it is for older individuals. However, younger Millennials prefer to share documents via email instead of using cloud services, and their need for social recognition, interaction and immediate responses may cause them to prefer to share pictures through social networks than through cloud services (Hrastinski and Aghaee 2012; Oblinger and Oblinger 2005; Whiting and Williams 2013). Therefore, it is expected that ease of sharing in cloud services will be more important for older generations than for younger generations, which gives the fifth hypothesis:

H5

Ease of sharing files will have a greater effect on cloud services payment for older generations than for younger Millennials.

3.2 Privacy and security negative experiences

Data privacy and security among young people is a topic that has attracted the attention of academic research in the last decade (Chen et al. 2017; Feng and Xie 2014; Livingstone 2008; Miltgen and Peyrat-Guillard 2014; Moqbel et al. 2017; Moscardelli and Divine 2007; Youn 2009). Most of that research has focused on privacy protection or privacy concerns, with little attention paid to security concerns. Privacy concerns are related to the accessibility of data and users information by a third party. Privacy can be breached by a firm if a consumer’s personal information is collected without his/her knowledge or consent, and if his/her personal information is given to a third party without permission or used for any purpose not agreed (Phelps et al. 2000). Security concerns are related to the risks of being hacked and having information stolen, as well as to protection against viruses and spyware that can copy, damage or delete sensitive information. Previous studies have suggested that security and privacy breaches may have different impacts on user behavior (Miltgen and Peyrat-Guillard 2014).

Protection motivation theory (Rogers 1983) explains how individuals deal with risks, changing their attitudes and behaviors to protect themselves. Protection behavior depends on the perceived extent of the vulnerability and on the severity of the consequences of suffering a privacy or security breach. Severity depends on the immediacy of the event and on whether its negative consequences influence the user and/or other people in his/her environment. These issues have been a recent focus of internet research (Chen et al. 2017; Dinev and Hart 2004; Elhai et al. 2017; Feng and Xie 2014; Youn 2009). Studies have found positive associations among prior experience of being a victim of hacking, online privacy concerns and the adoption of privacy protection methods (Chen et al. 2017; Dinev and Hart 2004; Elhai et al. 2017). Researchers have proposed that having had an experience related to online privacy loss can help users understand their vulnerability and the serious consequences of such an event (Li 2008; Mohamed and Ahmad 2012), thus leading them to adopt protection behavior.

Different protection behaviors have been analyzed, including changing passwords, creating fake profiles and buying anti-spyware (Chen et al. 2016; Elhai et al. 2017; Lee et al. 2008). However, little is known about the influence of negative privacy or security experiences on the decision to pay extra for services (Mamonov and Benbunan-Fich 2015). Price can be used as a signal of better protection of security and privacy (Tsai et al. 2011; Schreiner et al. 2013). Schreiner and Hess (2015) found that, because subscribing to a premium version of a social network would provide more privacy and security control features, individuals might perceive privacy protection and trustworthiness as an additional value they would be willing to pay for. From a social contract perspective, one party involved in a contractual relationship must assume that the other will act responsibly to fulfill its promises (Okazaki et al. 2009). Therefore, someone who has been a victim of a security breach and has suffered the consequences is more likely to adopt protection behavior and, thus, more likely to pay a price premium for being protected.

Miltgen and Peyrat-Guillard (2014) showed that there is no consensus about which age group is more vulnerable or more concerned about privacy and security in online environments. Previous research has suggested that younger individuals are more concerned about privacy and security than older individuals (Bernstein 2015; Livingstone 2008; Moqbel et al. 2017; Moscardelli and Divine 2007; Wood 2013) because, as heavy internet users, they are more aware of the potential risks and more inclined to privacy protection behaviors (Moscardelli and Divine 2007). However, Chen et al. (2017) recently found that middle-aged individuals were more concerned about privacy, while younger adults declared themselves to be unconcerned about privacy. Despite this lack of consensus, it has been found that older adults tend to be less knowledgeable about internet security compared with younger users, as protection motivation depends on severity and vulnerability (Grimes et al. 2010); older users feel more vulnerable and are more likely to engage in protection behavior. Previous research has suggested that the information most commonly stolen in a security breach is credit card information (Chakraborty et al. 2016). This type of breach may have greater negative consequences for older users, which means that older generations are more concerned and more security-conscious (Chakraborty et al. 2016).

Misuse of private information is very often found among social networking firms. By sharing private and personal information on those sites, people run a greater risk of privacy invasion (Mohamed and Ahmad 2012). One of the main ways in which users fall victim to internet scams is through disclosure of private information online (Chen et al. 2017). Millennials are heavy users of social network sites (SNS), and they tend to disclose a lot of private information (Christofides, Muise and Desmarais 2011) compared to older users (Kezer et al. 2016). Among adolescents, the level of privacy concerns motivates coping behaviors to handle privacy risks (Rifon et al. 2005). For younger Millennials, privacy loss means identity theft and the misuse of profile data by third parties (e.g., phishing and other illegal or unethical activities). Van Schaik et al. (2017) found that university students rated identity theft as their most important concern because of its negative and severe consequences compared to other types of security breaches (such as virus infections). For them, privacy is more important than security. Security breaches are perceived as less risky, because they only affect the user’s computer, provoking the destruction of files. A privacy breach, in contrast, involves hackers being able to post inappropriate information, submit unwanted friend requests, add unwanted online contacts, and send offensive messages to online friends (Debatin et al. 2009; Sengupta and Chaudhuri 2011; Ybarra and Mitchell 2008). The consequences of such unauthorized use of online postings include relationship problems with family and friends, damage to personal image, and loss of social and other opportunities (Chen et al. 2016). Data breach may thus lead to relational conflicts with friends and may damage the victim’s reputation. For younger adults or younger Millennials who use SNS for social interaction, privacy loss may have a greater impact than a security breach, making them more likely to take action to protect their personal data. These considerations lead to the final hypotheses:

H6

Previous experience of privacy problems will have a greater effect on cloud services payment for younger Millennials than for cloud users from older generations.

H7

Previous experience of security problems will have a greater effect on cloud services payment for older generations than for younger Millennials.

Figure 2 shows the model to be tested.

Fig. 2
figure 2

Conceptual model to be tested and hypotheses

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4 Methodology

The data used for this study are taken from the Community Survey on ICT Usage in Households and Individuals carried out by the European Commission (Eurostat) in Spain during 2014. A computer assisted telephone interview (CATI) was used to obtain the responses, and the organization conducting the survey was the National Statistics Institute (www.ine.es). The participants ranged from 16 to 74 years of age, and the aim was to cover the whole country. The net sample size was 13,026 individuals, which represents an overall response rate of 75.7%. Of the respondents, 9309 reported that they had used the internet in the last 3 months (a filter for answering the questionnaire); of these, only 2840 were cloud users. The model will be tested using information provided by these cloud users.Footnote 2

An analysis of cloud storage services in Spain allows us to offer some figures about the price of these services at the time of the survey. Cloud storage services became fashionable in 2011 and, just 3 years later, the provider companies were involved in a price war to increase the number of clients. Most of them increased their offering of free storage space to create a customer base (Table 2). The prices charged by these providers were similar, except for the more expensive iCloud. All the providers charged for additional storage space, and some of them offered access to libraries of music, TV programs and movies.

Table 2 Monthly prices of cloud services in Spain, 2014.
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Common control factors, such as level of education, employment and gender, were taken into account, and we have controlled for the use of cloud services. We have also taken into account how individuals use cloud services, because there is a wide range of alternatives, covering saving and sharing documents, e-books, music files, videos and films.

4.1 Measurement of variables

The dependent variable, likelihood of payment, is measured through a binary variable that took the value 1 if the individual reported currently paying for cloud storage services and 0 otherwise. Dependent and independent variables were obtained from the European Commission questionnaire, which means that there was no possibility of being involved in the design of the questionnaire and no scales from previous research were used.

Individuals were asked the question: “What are the reasons for using internet storage space to save or share files?” For each reason, a dummy variable was created that took the value 1 if the answer was yes and 0 if it was no. The reasons proposed were as follows: using files from several devices or locations (Ubiquity); using more storage space (Storage space); protection against data loss (Data loss protection); sharing files with other people easily (Ease of sharing); and access to large libraries of music, TV programs and films (Access to greater online resources). Respondents were also asked the question: “When using storage space on the internet or file sharing services, have you ever experienced any of the following problems: disclosure of data to third parties due to security problems or breaches (Security problem), and/or the unauthorized use of personal information by a service provider (Privacy problem)?” The dummy variables took the value 1 if the individual said yes and 0 otherwise.

Age was included as a moderator variable and was measured as a categorical variable with eight categories: (1) up to 15 years old; (2) from 16 to 24 (younger Millennials); (3) 25 to 34 (older Millennials); (4) from 35 to 44, and (5) from 45 to 54 (both Generation X); (6) from 55 to 64, and (7) from 65 to 74 (both cohorts of Baby Boomers); and (8) 75 or older (the Silent Generation). Some control variables were included in the model. Gender was a dummy variable that took the value 1 for men and 0 for women. Employment type was measured using a categorical variable with four categories: employed, unemployed, student, and not in the labor force (retired or inactive). Internet usage was measured through the number of online activities the individual carried out. This variable ranged from 1 to 12 and included activities such as e-commerce, e-government, browsing for information, use of social media networks, e-banking and online gaming. Educational level was implemented by a categorical variable depending on whether the individual had completed primary, secondary or tertiary education. Finally, the type of use of cloud services was also included, using dummy variables to cover storing, collaborating and saving different types of files: music, videogames, films and documents.

4.2 Characteristics of the sample

Given the objectives of this research, it is especially interesting to examine the sample by age cohort. Most users were under 55, with the group aged between 35 and 44 being the most numerous (Table 3). There were no cloud users under 15 and few over 74, so these two cohorts are not considered in the following empirical analysis. Users older than 65 did not pay for cloud services, so age cohort (7) was deleted from the analysis, meaning that the oldest group in the analysis was the younger Baby Boomers group (55 to 64 years old). In the total sample, 6.06% of cloud users paid for these services. The payment percentage was similar between older Millennials and Generation X; it decreased for younger Millennials and increased for younger Baby Boomers. Privacy problems had been experienced by 4.82% of users and were more common for Generation X, age cohorts (4) and (5). Of the respondents, 4.93% had experienced security problems, with the highest percentages in the older generations, Generation X and young Baby Boomers, related to age cohorts (4) (5) and (6). Table 3 also shows the mean differences between younger Millennials and other generations. Significant differences were found in all aspects except for previous experience of security problems, indicating that nobody was free from this type of problem.

Table 3 Descriptive statistics by age cohort
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Women made up 47.78% of the sample; overall, 54.85% of respondents had received tertiary education and 62.8% were employed. More than half of the participants had high IT skills, and 44.29% said that their level of internet usage was medium-to-high. The main reasons participants gave for using cloud services were ease of sharing (70.14%) and ubiquity (65.04%), followed by larger storage space and data loss protection.

5 Results

The estimation was carried out using STATA 14 software. A probit regression was estimated. This regression was robust and with clustered errors based on age cohorts.Footnote 3 Table 4 shows the coefficients and the marginal effects for user payment for cloud services. Because we are interested in the direction of the main results, marginal effects were calculated only for the moderating effects in order to compare the different age cohorts with the cohort used as a base (age cohort (2), younger Millennials). Marginal effects allow us to calculate how much the (conditional) probability of the outcome variable changes when the value of a regressor changes, holding all other variables in the model at their means. The probit estimation for payment allows us to classify 94.5% of cases correctly.

Table 4 Results
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To determine whether the behavior of younger users differs from that of older users, we analyzed the margins of age cohort (2), related to younger Millennials, compared to age cohort (6),Footnote 4 related to younger Baby Boomers (see Tables 4 and 5). The effect of ubiquity on likelihood of payment became more positive as age increased, supporting H1. With respect to the possibility of using larger amounts of storage space, the oldest users (or younger Baby Boomers) found this less important than younger Millennials, and therefore H2 is not supported. The possibility of accessing greater resources and libraries of music, TV programs and films had a positive influence on the likelihood of payment. This influence was greater for younger Millennials than for older users (younger Baby Boomers), and so the results support H3. A positive and significant effect of data loss protection was found only for younger Baby Boomers; for the rest of users, this effect was negative, which supports H4. The effect of ease of sharing on likelihood of payment was greater for older users than for younger users, supporting H5. Compared to younger Millennials, experience of a security problem had a more positive effect for users aged 45 to 55 (older Generation X), but no differences were found with the Baby Boomers group; H7 is thus not supported. However, having been a victim of a privacy problem was more important for younger Millennials, which supports H6. A summary of which hypotheses are supported by the results can be seen in Fig. 3.

Table 5 Increase in payment likelihood for cloud characteristics compared to the youngest users (aged 16–24)
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Fig. 3
figure 3

Hypotheses supported and not supported by the results

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With respect to the control variables, compared to employed individuals, students were less likely to pay for cloud services. Furthermore, compared to those with only primary education, users with secondary education were more likely to pay. Entertainment use (e.g., e-books, music, videos, films and videogames) increased the likelihood of payment for cloud services, and the number of activities that were carried out on the internet also had a significant positive effect on payment.

6 Discussion

This paper examines the ability of usefulness attributes to explain differences between generational cohorts in likelihood of payment for cloud services. The effects of negative security and privacy experiences on likelihood of payment for a premium version (as a protection behavior) are also examined for each generational cohort.

The results suggest that generational cohort is an important element to consider in the analysis of payment for cloud services. Our findings indicate that the usefulness of particular features of those services depends on the generation users belong to, and they provide new evidence concerning differences in payment for cloud services depending on age, confirming the generational cohort theory. Our findings suggest that age is a core variable in online payment behavior. This contrasts with previous research, which has included age as a control variable only (Yan and Wakefield 2018).

In terms of usefulness attributes, ubiquity had a negative effect on payment for younger Millennials. This effect reduced as age increased, becoming positive for the two oldest groups: younger Baby Boomers and older Generation X. The effect of data loss protection on payment likelihood was highly variable: positive for younger Millennials, increasing for younger Baby Boomers, and decreasing for the other generations. Therefore, for the oldest group of users in the analysis (younger Baby Boomers), both ubiquity and data loss protection had a positive influence on the likelihood of paying for cloud services. These results are in line with previous research that suggests that older generations are digital immigrants (Kim and Huh 2007) compared to Millennials, who are digital natives, and that younger consumers do not value aspects such as flexibility and accessibility (Hsiao and Chen 2016) in their purchase intentions. For ease of sharing, a similar conclusion can be reached. This characteristic is important for prompting older users to continue to use an innovation (Salmon et al. 2017; Yang et al. 2015). According to our findings, it added value for younger Baby Boomers and older Generation X users, who were likely to pay for it, but not for younger or older Millennials. For ubiquity, the situation is similar, as the IT skills of digital natives mean that ease of use was not a characteristic that they valued. With respect to access to online resources such as TV programs, films and music, our results confirm that this is an aspect that led younger Millennials to pay for cloud services, in line with their avid consumption of cloud-based entertainment (Christofides et al. 2011; Kvavik and Caruso 2005). Contrary to our expectations, access to greater amounts of storage space had a more positive effect on payment for the youngest group (younger Millennials) than for the other groups, except for users aged 45–54 (older Generation X), for whom there were no significant difference from younger Millennials.

Previous negative experiences related to privacy or security were important aspects to consider, as previous research had indicated (Chen et al. 2017; Feng and Xie 2014; Ifinedo 2012). Having suffered security problems influenced likelihood of payment for all groups, but further analysis suggests that it had a stronger impact for older Generation X users (45 to 54 years old), which confirms previous research (Chakraborty et al. 2016). However, the impact of having been a victim of a privacy breach had a stronger effect on payment for younger Millennials, which confirms studies that have found that younger adults were more concerned about privacy than older individuals (Bernstein 2015; Moqbel et al. 2017; Moscardelli and Divine 2007) and, therefore, would pay extra for privacy protection. Our results are in line with the idea that young users are more exposed to risky online situations and that the consequences of suffering a privacy attack have a more immediate effect on their social environment than a security problem would. These differences between security and privacy for young adults confirm previous research about which types of internet problems are more important and how this depends on the immediacy and severity of the consequences. Our findings are therefore in line with previous research that suggests that younger users are more likely to react when the consequences of suffering a privacy or security problem are severe and immediate (Kahneman 2011; Van Schaik et al. 2017).

7 Conclusions and implications

This study has examined the antecedents of payment for cloud services in different age cohorts and contributes to the literature in three ways. First, this research provides new evidence about the differences between younger and older individuals in how they value the technological attributes of online services. This evidence allows us to suggest some implications for service providers that are considering adoption of a freemium price strategy (see below). Second, this research contributes new evidence on payment for cloud services over previous research (Burda and Teuteberg 2016; Wang and Lin 2016; Yan and Wakefield 2018) by examining additional factors, such as previous negative experience related to privacy or security concerns; it also offers evidence that paying a premium can be regarded as a protection behavior. These findings contribute not only to protection motivation theory but also to signaling theory. Additionally, as most previous studies have focused on just one generation (Halperin and Dror 2016), our results contribute new evidence about differences between generations in the effects and importance of privacy and security. Paying a premium may be understood by some users as a signal of additional promises made by the company regarding protection of data against security and privacy breaches. Finally, previous research has focused on privacy, tending to put security in the background or to include both these aspects in a single category. Our results provide new evidence that security and privacy breaches impact differently on users depending on their generation; this indicates that security and privacy should be analyzed separately.

Our results offer some implications for cloud service providers and entrepreneurs who are using a freemium strategy. In general, certain functional aspects can be highlighted to convert free customers into paying ones. Storage space and access to larger libraries of music, TV programs and films are the two factors that, together with having had a security problem, are relevant to users regardless of their age. However, the results suggest that this relevance is different for each generation of consumers, indicating that firms should define their target market in terms of generation and emphasize different characteristics depending on the generation being targeted. Some features that are irrelevant for younger Millennials are very important for Generation X and younger Baby Boomers. To attract younger paying users, all the aspects under study here are important, with the exception of ubiquity and ease of sharing. To attract paying customers among Generation X and younger Baby Boomers, however, these two aspects are the most important, together with data loss protection and security. This is of particular importance given that the current pricing strategies of cloud service providers are focused on the amounts of storage space they offer.

It should also be noted that younger Millennials are likely to pay a premium for greater control of privacy, whereas for older users, including younger Baby Boomers, greater control to increase security is what adds value and what they would pay for. Adoption of protection behavior will become more common among consumers as news breaks of big firms being hacked or sending private information to third parties without consent. Such events will increase the number of negative consumer experiences related to privacy and security, raise levels of consumer privacy and security concerns, and reduce consumer trust in protection privacy laws. Cloud service providers or other firms with a freemium strategy should therefore advertise the differences in privacy and security protocols between free and paid versions, thereby emphasizing the consequences of suffering a privacy or security breach. This would then allow them to offer the premium version as a solution or as a form of protective behavior. For the same purposes, trust in the firm should also be highlighted.

This study has a number of limitations, some of them related to the survey design and to variables that were omitted from the survey. For example, price and brand name were not introduced into the model, as that information was not included in the survey. The severity of this limitation is mitigated by the fact that, as discussed in the sample description, a recent price war had made cloud services very affordable and very similar among all service providers. A second limitation is that we analyzed the impact of negative experience on the payment of services without examining the possible mediation effects of privacy and security concerns or awareness. In terms of the measurement of the variables, a limitation is that dummy variables were used. The use of scales or categories for the variables under study would have provided more accurate information.

There are also a number of limitations that offer opportunities for further research to improve the generalizability and currency of the results. The lack of information about when negative experiences took place made it impossible to establish the immediacy of the problem. Further research could therefore include the time of the negative experience in order to examine the immediacy effect. Another avenue for future research relates to the different ways in which firms manage breaches and the extent to which users are satisfied with the solutions firms provide. In the present study, there is no information about levels of user satisfaction with cloud services, the brand image and trustworthiness of each provider, or the impact of these factors on the privacy and security control that users expect from the firm. One further limitation is that the data were collected when payment for cloud services was still in its infancy. A similar cross-sectional study could be carried out to provide up-to-date information now that cloud services have matured and paying for them is a widespread behavior. A longitudinal analysis would also shed light on the evolution of the importance of each functional attribute.