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An Empirical Study of Factors that Influence the Willingness to Pay for Online News Manuel Goyanes Published online: 11 Feb 2014.

To cite this article: Manuel Goyanes (2014) An Empirical Study of Factors that Influence the Willingness to Pay for Online News, Journalism Practice, 8:6, 742-757, DOI: 10.1080/17512786.2014.882056 To link to this article: http://dx.doi.org/10.1080/17512786.2014.882056

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AN EMPIRICAL STUDY OF FACTORS THAT INFLUENCE THE WILLINGNESS TO PAY FOR ONLINE NEWS

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Manuel Goyanes

Drawing on the theory of the economics of information, this study sheds light on the factors that influence willingness to pay for online news, using a telephone survey of 570 US (from the Pew Research Center) adults selected at random. Results of the logistic regression analysis revealed relationships between paying intent and predictor variables such as demographics (age and income), purchase of other digital products (online movies or TV content, software programs, eBooks and applications) and media use (Twitter). However, independent variables such as gender (demographics), video games and music files (purchase of other digital products) were not statistically significant. Future research on the economics of news may take into account these findings focused on studying paying intent. KEYWORDS business model; online news; online newspaper; paid for contents; revenue model; willingness to pay

Introduction The internet has become a well-established and dominant medium for news consumption and delivery. According to the Pew Research Center (2013a), online was the only category of news that showed growth, following the rapid spread of digital platforms. By some accounts, about 39 per cent of Americans accessed news online or from a mobile device on a daily basis (34 per cent in 2010). If other online digital news sources are included, the share of people who got news on an average day rises to 50 per cent. For many traditional newspapers, this rapid digital growth has coincided with a decline in print (Sylvie and Witherspoon 2002; Thurman and Herbert 2007; Küng, Picard, and Towse 2008). In this switching context, the profitability issue still troubles the online publishing industry as no business models seem to generate reliable revenue streams for online news services (Chyi 2005; Nel 2010). In 2005 (Mensing and Rejfek 2005), advertising was seen as the major source of significant future income for American editors, while a 2009 survey of newspaper executives showed that nearly 60 per cent of respondents were considering paid content strategies. This was a dramatic change, considering that 90 per cent of the responding papers did not charge for content, and only 3 per cent had a subscription-only site at the time of the survey (American Press Institute 2009). The reasons for this strategic shift were based on the inefficiency of free business models and advertising support to monetise the content production sustainably (Perez-Latre 2007; Clemons 2009). The problem for online newspapers was—and is—not the size of the digital advertising market, which is growing far more rapidly than the rest of the advertising market (World Association of Newspapers 2012), but their composition. Online newspapers are tiny players in a market dominated Journalism Practice, 2014 Vol. 8, No. 6, 742–757, http://dx.doi.org/10.1080/17512786.2014.882056 © 2014 Taylor & Francis

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by large technology companies (Google, Amazon, Yahoo, etc.), where the top five account for 64 per cent of all US digital advertising spending in 2012 (Pew Research Center 2013a). This economic uncertainty has led to many news organisations charging for content (Ihlström and Palmer 2002; Stahl, Schäfer, and Maass 2004). According to the Pew Research Center (2013a), digital pay plans are being adopted at 450 of the country’s 1380 dailies and appear to be working not just in major US news organisations (like The New York Times) but also at small and mid-sized papers (Mitchell 2013). However, the newspaper industry’s efforts to refinance its production through paid content clash with readers’ stated unwillingness to pay for digital goods (Chyi and Sylvie 2009; Bleyen and Van Hove 2007). As BCG (2009) suggested, the maximum amount of money people are willing to pay for online news is very modest, around $5 a month, while only 2 per cent would be prepared to pay for unrestricted access to a website they currently use regularly if a paywall was introduced (KPMG 2010). The tablet is not the solution, either, since a large majority of those who have not paid directly for news on their tablet remain reluctant to do so, even if that was the only way to get news from their favourite sources (Pew Research Center 2011). The underlying reason why people are unwilling to pay for online news reflects its lack of value (Goyanes 2013a) and the expansion of a culture of free (Castells 2006; NietoTamargo 2001; Miguel de Bustos 2010) since the birth of the internet. Online news has become a commodity (Picard 2009b): its creation is cheap and undifferentiated, average journalists share the same skills sets and the same approaches to stories, they seek out the same sources, ask similar questions and produce relatively similar stories. Furthermore, more and more competition from outside and inside the journalism profession provides news and information (Campos 2010). In this climate, some media scholars suggested that content must be free unless it is very specialised (López 2010) or unless the reader cannot find the same content on a free website (Nel 2010). However, offering relevant content for the reader’s life based on personalisation (Micó-Sanz and González-Molina 2010) and exclusivity (Thurman and Herbert 2007), enhancing documentation in order to improve the journalistic product (Marcos-Recio et al. 2008) and focusing on hyper-local coverage (Foremski 2009) would increase willingness to pay (WTP) for online news. In this economic situation, an important question for the future of news organisations arises: which factors influence the WTP for online news? This issue is important for several reasons. First, it would help media managers to gain a better understanding of customers’ purchasing behaviour as well as the creation of well-stratified market segments where paying intent for online news is stronger. Therefore, it would drive online newspapers that are developing paid content strategies to a better firm performance, since the greater the knowledge of clients’ purchasing behaviour and profiles, the better the adequacy and creation of content adapted to customers’ needs and wants. However, despite the importance of this issue, limited empirical and academic researchers have focused especially and deeply on WTP for online news. Most recent studies on economics of newspapers analyse differences between business models (Thurman and Herbert 2007; Nel 2010, etc.) with special emphasis on the viability of multiple revenue models (Steinbock 2000; Chyi 2005), in order to partially shed light on the issue of WTP. Other media research has explored small, per-article payments in the newspaper industry (Graybeal and Hayes 2011) or payment intentions across channels (Chyi 2012), or empirically examined whether multi-platform news consumption is a reality and the extent to which people own, use and enjoy multiple electronic devices

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(Chyi and Chadha 2011). Still, there is a lack of studies which empirically analyse factors that influence WTP for online news. Therefore, to evaluate the viability of paid content strategies through any business model, an empirical examination of online users’ response to paid content is essential. This paper addresses this gap by analysing potential predictors [demographic variables (age, gender and income), media use (measured with Twitter) and purchase of other digital products (music, online movies or TV content, eBooks, applications (apps), video games and software programs)] of WTP for online news highlighted by previous research on media economics/management and marketing, on the basis of an enquiry conducted by the Pew Research Center in 2010. By using a logistic regression analysis to study all these key independent factors, four main results emerged: (1) younger people are more likely to pay for online news than older people; (2) people who have purchased software programs, online movies or TV content, apps for tablets or smartphones, and eBook files are more likely to pay for online news; (3) people with a higher income are more willing to pay for online news than users with a lower income; and (4) users who have a moderate use of Twitter (at least once a week) are more willing to pay for online news than those who have never used Twitter.

Theoretical Framework Different Revenue Models There is some consensus that most newspapers going online have yet to find a business strategy with which they are completely comfortable (Picard 2009a; Goyanes 2013b); in fact, most adopt a highly experimental approach (Chyi and Sylvie 2001). The failure of many of them to implement paid content strategies has led media researchers (Goyanes 2013b, Perez-Latre 2007) to conclude that generating multiple revenue sources in the digital environment is more appropriate than depending to a large extent on only one (like advertising). Academic research clearly shows that advertising alone cannot provide sustainable profits and charging for content will likely be an essential part of an effective business model in the future (Sylvie and Chyi 2007). Recent market research in the United States shows that newspapers took in roughly $11 in print revenue for every $1 they attracted online (Pew Research Center 2012). Thus, even though total digital advertising revenues rose 19 per cent on average in the last full year (Pew Research Center 2011), that did not come anywhere close to making up for the dollars lost as a result of a 9 per cent decline in print advertising. The displacement ratio in the sample was a loss of dollars by about 7:1. Despite the fact that a great number of online newspapers have implemented different business models based on paid content strategies (metered model, paywall, virtual kiosks, etc.) as well as different revenue models (subscriptions, pay per view, advertising, etc.) and packaging formulas (PDFs) across different channels (smartphone, tablet and PC), only a few have improved their economic performance (Filloux 2011). In most cases, this kind of organisation was financial or economic newspapers based on exclusivity and specialisation such as The Wall Street Journal or the Financial Times. Nevertheless, as Thurman and Herbert (2007) have pointed out, these organisations seem to be the exception rather than the norm and “will continue to be the two who charge most and have the highest walled gardens”.

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In recent years, the business model concept has been the focus of substantial attention from both academics and practitioners. If in general management studies there is a lack of consensus about what a business model is (Shafer, Smith, and Linder 2005; Casadesus-Masanell and Ricart 2009; Zott, Amitt, and Massa 2011), this fact could be extended to media economics or media management studies. Despite the overall increase in literature on online newspapers’ business models, researchers frequently adopt idiosyncratic conceptualisations that fit the purposes of their studies but which are difficult to reconcile with each other. The literature is developing in silos, according to the phenomena of interest to the respective researchers (Zott, Amitt, and Massa 2011). The main areas of interest are (1) the application of the business model theory developed by management academia in order to understand and conceptualise online newspapers’ business models (Thurman and Herbert 2007; Nel 2010; Graybeal and Hayes 2011) and (2) the configuration and conceptualisation of business models as practically developed by online newspapers (Picard 2009a; Chyi 2012; Goyanes 2012). A business model defines the way a company generates value (value creation) and how it captures some of this value as profit (value capture) (Teece 2010). In this sense, a business model represents the “business logic” (Casadesus-Masanell and Ricart 2010) or according to Peter Drucker (1994), it provides answers to the following research questions: “Who is the customer and what does the customer value?” and “What is the underlying economic logic that explains how we can deliver value to customers at an appropriate cost?” For Timmers (1998), a business model refers to an integrated system consisting of products, services and information flows, including all participants, their roles, their potential benefits, and the corresponding profit sources and ways. Christoph Zott and Raphael Amit (2007) contend that the business model is the focus of innovation, and is the decisive source for enterprises to create value for themselves, suppliers, partners and customers. Alexander Osterwalder, Yves Pigneur, and Christopher Tucci (2005) posit that the business model is a conceptual tool that contains a large number of commercial elements and inter-relationships, so as to clarify the business logic of a particular entity. In summary, the business model can be generally defined as an integrated solution that enables a business to (1) form a high-efficiency operation system with unique core competitiveness and (2) achieve sustained profitability goals by providing products and services that maximise the customers’ value. From a theoretical point of view, the first step when it comes to differentiating between business models for online newspapers is the revenue model, i.e. the customer is involved in an economic transaction. Based on the paid versus free dichotomy, the internet allows for different business models: the free business model (based on free access to information and advertising support); paywall (based on charging for access and admitting different revenue models such as subscription or pay-per-view, which includes pay per day/week or read article, following the micropayments model implemented by iTunes); freemium (online newspapers give away certain content for free, with other content behind a paywall); the metered model (allows free access to a certain number of articles in a given period of time, and once this amount is exceeded, the newspaper invites the reader to subscribe to one of the multiples packages); donations; digital kiosks (simulate offline news-stands, thus exporting the traditional newspaper to the digital environment), etc.

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Willingness to Pay for Online News Consumers’ WTP has been widely studied in economics and marketing research for decades. However, little empirical evidence has shed light on WTP for digital media goods (Schwer and Daneshvary 1995; Chyi and Lasorsa 2002) and, specifically, for online newspapers (Chyi 2005; Chyi 2012). This study addresses this gap by systematically analysing potential predictors of WTP for online news highlighted by previous research on media economics/management and marketing on the basis of an enquiry conducted by the Pew Research Center in 2010. WTP refers to the maximum amount one is willing to pay for a product, which is the inevitable outcome and ultimate measure of competition (McDowell 2011). Since the majority of online newspapers are for free (PWC 2009), in many cases the willingness to pay for information could be much higher than the price of the online newspaper (that is zero), producing, therefore, a clear customer surplus. In this sense, online news has been characterised by a demand curve at the price of zero, whereas if the price increases even by a single cent, demand drops to zero. Because substitutes for online news are available, cross-price elasticity is high, so the free-to-fee switch envisioned by media outlets could cause a drop in quantity because the substitution effect would be triggered (Chyi 2005). Market researchers have found little evidence suggesting that users are ready to pay for online news (Dou 2004). Chyi developed an empirical study in 2005 in which the results were clear and demonstrated in 2012, while incorporating a multi-platform approach. These studies show that the types of online content that consumers are most likely to pay for are, to a large extent, the same kinds they normally pay for offline, but only one in 50 (2 per cent) would be prepared to pay for unrestricted access to a website they currently use regularly if a paywall were introduced (KPMG 2010). The reason that consumers may be unwilling to pay for online news can be multifold. It may be a matter of customary belief (Miguel de Bustos 2010), or it may be related to the methods of payment or their availability (Zhang and Nguyen 2004). It may also be due to the format and platform delivered (Chyi 2012). In any case, it is critical to understand these consumer opinions towards charged online newspapers and related determining factors. An understanding of these opinions and factors would help news organisations to assess and predict the behaviour of their online customers. Consequently, it may also help to choose appropriate business models and design appropriate revenuegeneration methods for online consumers. Previous researchers have used regression methods to explain different factors that empirically predict WTP for online news (Schwer and Daneshvary 1995; Chyi and Lasorsa 2002). In the vast majority, demographics (such as age, gender or income) were taken into account as independent variables. For example, Chyi (2005), based on Schwer and Daneshvary’s (1995) statistical approach for studying the WTP for public broadcasting services, developed an empirical analysis to study the viability of the subscription model to online newspapers. The results clearly showed age to be the only significant demographic variable (and it was negative). The same author in 2012 evaluated users’ paying intent for different newspaper formats. Age and, to a lesser extent, gender had an influence on the likelihood of paying for Web and apps, but no demographic variables predicted a paying intent for print newspapers. Therefore, building on previous research, this study examines whether demographics affect paying intent for online news, addressing the following research question:

WILLINGNESS TO PAY

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RQ1: How do age, gender and income influence WTP for online news?

Empirical studies have demonstrated that the online services customers are more willing to pay for are those used frequently and those that are important to a customer (Zhang and Nguyen 2004). However, as most users believe close substitutes for general-interest online news are available, cross-price elasticity is high (Picard 2012). Therefore, according to Chyi (2005: 133), “unless every alternative news product increases the price at the same time, switching from free to fee can only trigger the substitution effect, which would result in a huge decline in the quantity demanded”. In addition, the habit of traditionally perceiving online newspapers as free (Miguel de Bustos 2010) implies great difficulty in convincing a customer to pay for them. The substitution effects in media were a traditional issue in media economics. It is a popular belief that the internet displaces traditional media (Van der Wurff 2011), although the alternative argument that the internet forces traditional media into new niches, perhaps even increasing total media consumption, can also be heard (Dutta-Bergman 2004). In 2000 Stempel, Hargrove, and Bernt (2000) examined the impact of internet use on television, radio, newspaper and magazine use, and found internet users more likely to be newspaper readers and radio news listeners. Chyi and Lasorsa (2002), aiming to investigate the public’s response to local, regional and national newspapers’ print and online editions, demonstrated the simultaneous use of the print and online editions, suggesting that to some extent print and online products complemented each other. An empirical analysis conducted by Dutta-Bergman (2004) found users that seek content in online media seek similar content in other news media, too, and as Leung and Wei (1999) noted, newspaper reading is positively related to TV news viewing among Hong Kong students. Finally, according to Chyi (2005), more time spent on reading traditional newspapers was associated with higher paying intent for online news. All these studies investigated the relation, in terms of use, of different media systems (internet, traditional newspapers, online newspapers, radio and TV) or the relation between traditional media use and WTP for information. Methodologically, they defined media in general terms, neglecting new media technologies that enable and extend our ability to communicate, such as platforms like Twitter, in their empirical analysis. As a result, little empirical evidence from the media economics perspective sheds light on the relation of Twitter use (media use) on WTP for online news, despite the fact that the average Twitter user is two to three times more likely to visit a news website than the average person (Farhi 2009), and taking into account that this platform is an essential mechanism for news organisations to distribute breaking news quickly and concisely. Consequently, this study tries to address this gap by asking the following research question: RQ2: How does media use [social networking (measured with Twitter)] influence WTP for online news?

Consumer decision making has long been of interest to academics and practitioners. Previous research on attribute theory suggests that a product is composed of several attributes and consumers attach value to these attributes. The model assumes that consumer choice is based on maximising utility (which is often operationalised as satisfaction) from the product attributes subject to a budget constraint. This theory allows researchers to examine consumer attitudes towards not just one product, but a group of products that are preference alternatives (Bass and Talarzyk 1972). Therefore,

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understanding consumer preferences for attributes that distinguish between products can help in defining the best positioning and marketing mix for a particular product. Previous research on marketing and media economics has traditionally used conjoint analysis methods to examine how potential consumers assign relative importance to different attributes that make up a product or service (Carroll and Green 1995). Putzke, Schoder, and Fischbach (2010), for example, examine consumer acceptance of an individualised newspaper, suggesting that consumers are generally willing to devote effort to customising their news, while Chyi (2012), aiming to analyse the relative importance of format and price when people choose between different news packages, concluded that the Web-only edition received a negative utility value, indicating that it is the least preferred level, and the combined format (both print and Web) is the most preferred. In terms of price, results showed that it (ranging from $5–20) has a much greater influence on preference over newspaper format. These studies, among others, have analysed different attributes of one product (online newspapers) and their influence on customer purchasing behaviour. However, the influence of the purchasing of different digital products (such as music and eBook files, software programs, etc.) on WTP for online news remains unclear. This analysis is important for several reasons. First, it contributes to a better understanding of customer profiles as well as actual behaviour in the newspaper industry. Second, and most importantly, it has significant managerial implications since the analysis points out which digital products have a positive or negative impact on customers’ paying intent for online news. Therefore, this study examines the following research question: RQ3: How does the purchase of different digital products (music, online movies or TV content, eBooks, apps, video games and software programs) influence WTP for online news?

Method Data were collected from the datasets of the Pew Internet & American Life Project. The survey data reported in the research come from telephone interviews with a representative sample of 570 adults living in the continental United States. Telephone interviews were conducted in English and over the phone (both landline and mobile) by Princeton Data Source from October 28 to November 1, 2010, to investigate the general public’s response to WTP for online news. The model constructed in this research is based on a binomial logistic regression and analyses the probability of paying for online news as a dependent variable. The logistic regression tests the probability of a dichotomous event happening, in this case engaging in a purchasing activity. The predicted proportion of activities follows the logistic model of lnP/(1 − Pi) = βXi, where Pi is the probability of purchasing or downloading online news, newspapers or a special report.

Variables and Measurements Dependent variable. WTP for online news was measured as a categorical and dichotomous variable and coded as 1 = Yes, I’ve paid to access online or to download a newspaper, journal article or special report and 0 = No, I’ve never paid to access online or to download a newspaper, journal article or special report.

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WILLINGNESS TO PAY Independent variables. All independent variables regarding previous purchase of digital products were categorical and dichotomous variables coded as 1 = Yes, I’ve paid to access online or to download… (applications, music, software files, etc.) and 0 = No, I’ve never paid to access online or to download… (Example of question: “Have you ever paid to access or to download music, applications, software, computer games, etc.?”). Gender was coded as a categorical and dichotomous variable where 1 = Male and 2 = Female. Twitter use was coded as a categorical and polytomous variable where 1 = Yes, I have used Twitter at least once a day (heavy usage), 2 = Yes, I have used Twitter at least once a week (moderate usage), 3 = I’ve never used Twitter. Income (per year) was coded as a categorical and polytomous variable where 1 = Less than $10,000, 2 = $10,000 to under $20,000, 3 = $20,000 to under $30,000, 4 = $30,000 to under $40,000, 5 = $40,000 to under $50,000, 6 = $50,000 to under $75,000, 7 = $75,000 to under $100,000, 8 = $100,000 to under $150,000 and 9 = $150,000 or over. Finally, age was coded as a continuous variable.

Results Descriptive Analysis The sample of 570 US residents included slightly more women (54.9 per cent, N = 313) than men (45.1 per cent, N = 257) with an age range between 18 and 88 (mean = 47.75, SD = 16.90). Most respondents have never used Twitter (82.1 per cent, N = 468; have used Twitter at least once a day (heavy Twitter use): 11.4 per cent, N = 65; have used Twitter at least once a week (moderate Twitter use): 6.5 per cent, N = 37). Software programs are the digital products which people were most willing to pay for (33.3 per cent, N = 190), followed by music (32.1 per cent, N = 183), apps for smartphones or tablets (19.5 per cent, N = 111), newspapers, journal articles or special reports (18.9 per cent, N = 108), video games (17.7 per cent, N = 101), videos, online movies or TV content (15.3 per cent, N = 87) and eBooks (9.5 per cent, N = 54).

WTP for Online News: Logistic Regression Analysis Results of the logistic regression analysis revealed the relation between paying intent and predictor variables (p < 0.05) such as demographics (age and income), purchase of other digital products (online movies or TV content, eBooks, software programs and apps) and media use (Twitter) (see Table 1). However, independent variables such as gender (demographics), video games and music files (purchase of other digital products) were not statistically significant. The first model accounted for 6 or 4 per cent of the variance in paying intent (Nagelkerke R2 = 0.068; Cox and Snell R2 = 0.042). The second model accounted for 9 or 5 per cent of the variance in paying intent (Nagelkerke R2 = 0.091; Cox and Snell R2 = 0.056). The third model accounted for 24 or 15 per cent of the variance in paying intent (Nagelkerke R2 = 0.247; Cox and Snell R2 = 0.152), therefore suggesting considerable explanatory power. The classification table predicts 82.8 per cent of the cases (error of 17.2 per cent). With regard to the first research question, the influence of demographic variables on WTP for online news, gender, age and income were entered on the first step of the analysis. Results of the logistic regression showed a statistically significant association (p < 0.05) with age1 (negative) and income, but not with gender. Therefore, the probability of paying for online news (β = −0.021; p < 0.05) was higher in young users. In other words,

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MANUEL GOYANES TABLE 1 Logistic regression analysis of predictors of paying intent

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β Gender (1) Age Income (1) Income (2) Income (3) Income (4) Income (5) Income (6) Income (7) Income (8) Twitter (1) Twitter (2) Music Videos/TV content eBook Video games Software Apps Nagelkerke R2 Cox & Snell R2 −2 Log likelihood No. of observations Chi-square

Model 1

−0.086 −0.021* −2.650* −1.697** −1.320** −1.451** −1.173* −0.785* −0.399 −0.605

0.068 0.042 522.976 570 24.587**

Model 2

Exp(β)

β

0.917 0.979 0.071 0.183 0.267 0.234 0.310 0.456 0.671 0.546

−0.082 −0.002 −2.600* −1.678** −1.213* −1.449** −1.217* −0.718 −0.329 −0.567 0.552 1.069**

0.091 0.056 514.478 570 33.086**

Model 3

Exp(β)

β

0.921 0.998 0.074 0.187 0.297 0235 0.296 0.488 0.720 0.567 1.737 2.913

−0.032 0.014 −2.183* −1.496* −0.689 −0.995 −1.055* −0.565 −0.111 −0.663 0.427 1.081* 0.472 0.876** 1.162** −0.102 0.551* 0.633* 0.247 0.152 453.334 570 94.230**

Exp(β) 0.969 1.014 0.113 0.224 0.502 0.370 0.348 0.568 0.895 0.515 1.533 2.949 1.603 2.401 3.196 0.903 1.734 1.883

The constant in the three models is statistically significant. The last category (in categorical variables) is taken as a reference. *p < 0.05, **p < 0.01.

paying intent for online news increases when age decreases (if age is reduced by one year, then the probability of paying for online news increases by [0.979 ex] 2.1 per cent). Previous empirical research (Chyi 2005) provides support for this association, so findings are entirely contrasted and warranted. The reasons young users are more likely to pay for online news are multi-fold. It could be due to the fact that younger people are more wired than older ones (Pew Research Center 2013a). But especially, it could be due to the extensive penetration of tablets and smartphones (whose owners are dramatically more likely to buy news than those using desktops and laptops) among the American youth (Pew Research Center 2013b). In any case, what this research presents in answering this question is a new and favourable scenario for news organisations: despite the constant decline of young readers in the traditional newspaper industry in the United States (Edmonds, Guskin, and Rosenstiel 2011), the internet presents a great opportunity for media managers to attract and convince them, since it is the market segment that is most likely to pay for information. In addition, the logistic regression showed income as a statistically significant variable. People whose annual income was less than $10,000 (p < 0.05; β = −2.650; 0.071 ex), $10,000 to under $20,000 (p < 0.05; β = −1.697; 0.183 ex), $20,000 to under $30,000 (p < 0.05; β = −1.320; 0.267 ex), $30,000 to under $40,000 (p < 0.05; β = −1.451; 0.234 ex), $40,000 to under $50,000 (p < 0.05; β = −1.173; 0.310 ex), $50,000 to under $75,000

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(p < 0.05; β = −0.785; 0.456 ex), were less likely to pay for online news than those whose income was over $150,000 [we cannot observe significant differences between the seventh ($75,000 to under $100,000) and eighth ($100,000 to under $150,000) categories with respect to the ninth (over $150,000)]. Therefore, people with a higher income are, obviously, more willing to pay for online news than people with a lower income.2 The second research question asked whether media use (measured with Twitter) would predict paying intent. Twitter use was entered at the second step of the logistic regression analysis. In addition to income (the first five categories), Twitter use was also a significant predictor of paying intent. Hence, users who engage in moderate use of Twitter (at least weekly) were more likely (p < 0.05; β = 1.069; 2.913 ex) to pay for online news than users who have never used Twitter (there are no significant differences between nonTwitter users and heavy Twitter users in relation to willingness to pay for online news). In this regard, moderate use of Twitter (at least once a week) means that people use it occasionally and, therefore, are less involved in social media activities than daily users of Twitter. Generally, the most active market segment in Twitter is young people, since the penetration of this platform among older people is much lower (and we already see what the effect of age is on WTP for online news). Empirical studies suggest that people who use Twitter routinely (everyday) are two to three times more likely to visit a news website than the average person, although this does not mean they are more willing to pay for online news, as this research found. Moreover, taking into account the general perception of social networking platforms as free, uncensored and uncharged scenarios, it could be that this perception of “apparent free culture” (Nieto-Tamargo 2001) has a negative impact on WTP for online news. Furthermore, it could be that some people who use Twitter every day employ this social network as an alternative to paid online news, for example by subscribing to Twitter feeds from the main news agencies (so they do not see the point of paying for information). The third research question asked whether the purchase of different digital products (music, online movies or TV content, eBooks, apps, video games and software programs) influences WTP for online news. Of the six variables introduced in the third step of the logistic regression, four of them (eBooks, online movies or TV content, apps and software programs) were statistically significant (p < 0.05) and positive. Therefore, people who had paid for all of these different digital products were actually more, not less, likely to pay for online news than people who declared they had never paid for them. By positive importance, people who are most likely to pay for online news are those who have already paid for eBook files (p < 0.05; β = 1.162; 3.196 ex), followed by online movies or TV content (p < 0.05; β = 0.876; 2.401 ex), apps for tablets or smartphones (p < 0.05; β = 0.633; 1.883 ex) and, finally, software programs (p < 0.05; β = 0.551; 1.734 ex). Hence, the digital product purchase that implies the least probability of user paying intent for online news (so the digital product which has the least probability of paying intent) is the purchase of software programs. A reasonable explanation for this positive impact could be rooted in the uses and gratifications theory (UGT). UGT acknowledges individual use and choice and that different people can use the same medium for different purposes (Roy 2009). It attempts to explain the gratifications consumers seek in a particular medium and their perceptions of and affinity for that medium and its content (Ruggiero 2000). According to Katz and Blumler (1973), the most frequently found motives for using traditional media (television, radio and newspapers) are diversion (the need to escape

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personal problems and the need for emotional release); personal relationship (the need for companionship and help in social interaction); personal identity (the need for selfunderstanding and reassurance of one’s role in society); and surveillance (the need for information about factors that might affect or help one). However, since the birth of the internet, new technologies and electronic devices enable and extend our ability to communicate and entertain, thereby establishing a new and disruptive scenario. In this regard, digital products whose main value proposition consists in providing culture and entertainment (online movies or TV content and eBook files) and solutions (apps and software programs) have a positive impact on paying intent for online news, i.e. on products that provide information. Therefore, it would be an ideal opportunity for academics to shed light on the possible associations between different digital products under the theoretical lens of UGT and its influence on WTP for online news. This is important because it would help news organisations to differentiate between customers’ profiles as well as create well-stratified market segments that have a positive (or negative) impact on WTP for online news.

Discussion The objectives of online news organisations with paid content strategies on the internet, unlike the online news organisations with free business models, is not only to convince the customer to pay for the product, but also to retain customers on a long-term basis in order to create a sustainable base of economic income to maintain the business. As such, this results in a dual approach, involving both methods of subscriber recruitment and retention. However, the newspaper industry’s effort to finance its production through paid content collides with the stated unwillingness to pay for digital goods on the readers’ side. Most online news organisations’ customer recruitment and retention strategies are based on the creation and adaptation of complementary services. However, depending on the online newspaper, developing these services varies, from the creation of a community platform with benefits for its members, or through services oriented towards the reader via the personalisation of information, entertainment or cultural offers. All these complementary services try to create a community that (based on its editorial offering and on extra services of value) remains loyal to the brand through a direct relationship with the customer. Therefore, the main value proposition of online news organisations becomes not only the production (of information) but also the delivery of services designed to satisfy the client, whether through additional services, interaction, content personalisation, or cultural or entertainment offers. Future companies of the online newspaper industry will not be organisations that depend (only) on content, but (also) on the exclusive (complementary) services they offer. The study shows that online users were more likely to pay for those digital products whose main value proposition consists of providing entertainment (music) and solutions (software and apps), but less likely to pay for those providing knowledge (such as an online newspaper). In this respect, software programs were the digital product people were most willing to pay for, while online news came in fourth (behind music and apps for tablets and smartphones). This approach reinforces the idea that online news organisations need to go a step beyond the classical production of information when implementing paid content strategies. News organisations have to provide content, but

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also leisure, entertainment and cultural services (through complementary services) according to their understanding of the readers’ demands and needs. Despite the fact that software programs were the products people were most willing to pay for (N = 190), the logistic regression clearly showed this variable to be the one (belonging to the different digital products set) that has less influence on WTP for online news (among the significant variables). In this sense, the purchase of different digital products such as eBooks, online videos (or TV content) and apps had a positive impact on WTP for online news. However, variables such as purchasing of video games and music files were not statistically significant. These findings clearly have significant managerial implications, since consumer behaviour understanding helps online markets to focus and target customers by segmentation, predict customers’ purchasing behaviour and generate more profit through online channels (Bidgoli 2004). From the newspaper industry’s perspective, understanding determinants and factors of paying intent for online news is crucial to the functioning and sustainability of online newspapers with paid content strategies in this new era of competition from outside and inside the journalism profession. Furthermore, as this research clearly shows, customers are more willing to pay for products that provide entertainment and solutions, and the logistic regression analysis shows the significant impact of this kind of product on WTP. Therefore, it is now time for online news organisations to develop new partnerships or strategic alliances with entertainment companies with the aim of creating and sharing new (complementary) services based on leisure, culture, entertainment, etc. In addition, this study has found demographic variables such as age (negative) and income to be significant predictors of paying intent. It is not surprising that younger users were more likely to pay for online news than older users, the same way users with a higher income were more likely to pay for online news compared to users whose annual income is less than $75,000 (in the first model). Future research on the economics of news may take into account these findings focused on studying paying intent. Finally, with regard to media use, Twitter usage predicts paying intent: users who engage in moderate use of Twitter (at least weekly) had a higher probability of WTP for online news than those who have never used Twitter (there are no significant differences between non-Twitter users and heavy Twitter users in relation to WTP for online news). Therefore, Twitter users who use the social network occasionally or sporadically are actually more likely to pay for online news. This is interesting for media managers since we can infer from the results a great extension of the culture of free among heavy Twitter users. Hence, it is necessary and appropriate that news organisations consider Twitter not only a mechanism to distribute breaking news quickly and concisely, but also a marketing and interactive platform with which they can convince new customers to pay for their content through innovative marketing and advertising campaigns.

ACKNOWLEDGEMENTS The author gratefully thanks the two anonymous reviewers of this paper for their useful feedback.

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NOTES 1.

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2.

However, age dropped out as a significant predictor of WTP for online news when media use (model 2: p = 0.831; β = −0.002; 0.998 ex) and purchase of other digital products (model 3: p = 0.095; β = 0.014; 1.014 ex) entered the equation. Our empirical results differ on this point from Chyi’s (2005) analysis. The author entered income at the fourth step of the hierarchical regression analysis and found this variable was not a significant predictor of WTP for online news in a Hong Kong sample (N = 853). However, the beta was negative, and simple correlation analysis also revealed a significant negative relation between income and paying intent (r = −0.13; p < 0.05). In other words, people with a higher income were actually less, not more, willing to pay for online news.

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Manuel Goyanes, Department of Journalism and Mass Communication, Universidad Carlos III de Madrid, Spain. E-mail: [email protected]; manuel.goyanes@ gmail.com

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