ArticlePDF Available
CATCHWORD
Monetizing Online Content: Digital Paywall Design
and Configuration
Robert Rußell Benedikt Berger Lucas Stich Thomas Hess Martin Spann
Received: 6 April 2019 / Accepted: 6 January 2020 / Published online: 12 February 2020
The Author(s) 2020
Keywords Digital paywalls Online content
Monetization Revenue models Pricing
1 Introduction
The media industry was among the first affected by digi-
tization, because digital technologies have changed content
production, distribution, and consumption profoundly.
Most media companies have suffered revenue losses, being
unable to adapt their monetization strategies to the rapidly
changing media consumption patterns of their recipients.
Additionally, advertising revenues have proven to be a less
reliable revenue source in online than in offline media
markets. Consequently, a major obstacle to the content
providers’ successful digital transformation is the estab-
lishment of sustainable revenue streams (Chyi 2012). The
market for music and video content reveals a trend toward
direct monetization, with subscription-based streaming
services such as Spotify or Netflix showing increasing
revenues. However, other media markets, including the
market for news content, still struggle to monetize their
content online (PricewaterhouseCoopers 2019). After
extensive experimentation with various monetization
approaches and several failed attempts, more and more
news content providers adopt digital paywalls to counter
the impending market trends. While the term digital pay-
wall is commonly used in the context of news content, the
functionality of this instrument to govern consumers’
access to online content is also important for other media
products such as music, videos, or games. However, a
standard digital paywall does not exist. Owing to the wide
range of and new developments in configuration options,
the limited experience with digital paywalls in practice,
and a lack of research on this topic, it is still unclear which
factors determine the optimal design of a digital paywall.
The process of establishing a viable business model for
online content is complex and remains a challenge for
media companies. Content providers seek to maximize
direct revenue by selling content and indirect revenue
through advertising (i.e., a two-sided market), while
simultaneously considering cannibalization and spillover
effects on their traditional formats. Whereas news content
providers usually rely on both revenue sources for their
printed editions, most of them initially offered their online
editions free of charge and only monetized them indirectly
through advertising. Although online advertising revenue
has been growing steadily, this growth has not been suffi-
cient to compensate for the revenue losses from offline
sources such as print subscriptions or advertising. The
small margins in online advertising are mainly due to the
intensified competition in the digital channel, driven by
Accepted after two revisions by Ulrich Frank.
R. Rußell (&)B. Berger T. Hess
Institute for Information Systems and New Media, Ludwig-
Maximilians-Universita
¨tMu
¨nchen, Ludwigstr. 28,
80539 Munich, Germany
e-mail: russell@bwl.lmu.de
B. Berger
e-mail: benedikt.berger@bwl.lmu.de
T. Hess
e-mail: thess@bwl.lmu
L. Stich M. Spann
Institute of Electronic Commerce and Digital Markets, Ludwig-
Maximilians-Universita
¨tMu
¨nchen, Ludwigstr. 28,
80539 Munich, Germany
e-mail: stich@bwl.lmu.de
M. Spann
e-mail: spann@bwl.lmu.de
123
Bus Inf Syst Eng 62(3):253–260 (2020)
https://doi.org/10.1007/s12599-020-00632-5
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
news aggregators, social media networks, and efficiently
designed ad exchange platforms. Additionally, the classi-
fieds market, which news content providers traditionally
owned, has almost entirely moved toward online platforms
such as Craigslist, Indeed, or Facebook.
Therefore, content providers try to increase their direct
revenues in order to build a stable revenue stream mainly
by means of digital paywalls. For example, German market
data on the digital news publishing market from 2014 to
2018 confirm that direct sales revenues show a much
stronger growth (112 million to 359 million) than
advertising revenues (238 million to 325 million)
(PricewaterhouseCoopers 2019). Promising additional
revenue, digital paywalls could also stall the cannibaliza-
tion of offline editions by free digital editions. Addition-
ally, these instruments could increase the value of the
website’s individual users for advertisers. However,
besides the ongoing competition with free content alter-
natives on the Internet, consumers show a general lack of
willingness to pay for online content compared to the
physical equivalent, which makes the pricing of access to
online content an uncertain endeavor (Berger et al. 2015).
Furthermore, pricing online content can decrease viewer-
ship and drive down online advertising revenue (e.g.,
Chiou and Tucker 2013). Therefore, content providers must
configure their paywall solutions carefully to improve their
content monetization. Hence, content providers have to
understand implementation and configuration possibilities
to establish a viable revenue model in the digital economy.
In this catchword article, we introduce digital paywalls
as an instrument to address the content monetization issue.
We differentiate between paywall systems and paywall
solutions to account for both the technological and eco-
nomic aspects of digital paywalls. A paywall system allows
for mediating the access to content by distinguishing
between users who have paid for the access and those who
have not. We describe the overarching design of paywall
systems with related modules in a stylized content provi-
ders’ IT architecture (Sect. 2). Building on the paywall
system, content providers can configure various paywall
solutions to monetize their online content. Accordingly, a
paywall solution is the combination of specific economic
configuration parameters, namely access restriction options
and pricing options (see Sect. 3). In addition, the use of
Machine Learning (ML) provides new opportunities and
challenges when configuring paywall solutions, which we
debate (see Sect. 4). In conclusion, we summarize existing
knowledge on digital paywalls, and propose directions for
future research. Overall, IS research on digital paywalls is
still sparse, with several economic and technological
aspects being unexplored. The IS discipline can contribute
by addressing the challenges regarding the design of the
paywall’s system architecture, as well as the configuration
possibilities of paywall solutions and their economic
impact on content providers’ direct (sales) and indirect
(advertising) revenue streams across online and offline
channels.
2 Technological Functionality of Paywall Systems
The system architecture of media companies commonly
consists of a content management system (CMS), a cus-
tomer relationship management (CRM) system, an enter-
prise resource planning (ERP) system, and a website or
application software.
1
Within the CMS, an editorial system
provides functions to plan, create, and change content,
while a content repository system provides functions to
store and retrieve content, and a publication system trans-
forms content into different output formats. The CRM
system documents historical customer data and provides
functions to manage customer relationships. Lastly, the
ERP system with integrated media sales enables the
administration and consolidation of customer and transac-
tional data.
Based on existing systems and their application pro-
gramming interfaces, content providers can integrate pay-
wall systems in their system architecture that are either
dependent or independent and either integrated or adjacent
to the CMS (see Fig. 1). The grey-shaded modules repre-
sent the core systems, which are independent of a content
provider’s attempt to restrict access to online content. The
black modules are the essential components of a paywall
system, namely (1) access control management, (2) sub-
scription and access policy management, and (3) user
interface.
The main functionalities of the access control man-
agement (ACM) module are to identify individual users on
the website (i.e., authentication) and to implement the
decision whether they are permitted or not to access
requested content (i.e., authorization). Initially, a user
requests access to a specific content unit on the website.
The ACM module uses technologies like cookies or Java-
Script to track and identify the individual user by collecting
a number of available identification parameters (Pa-
padopoulos et al. 2019). If the user is eligible to access the
content, a server delivers the content page and access is
granted. Otherwise, the ACM module directs the user to a
login page to verify the user’s credentials. In the case of a
successful verification, the authorized user can access the
requested content. However, if the verification is not
1
We focus on core systems and do not consider the adjacent systems
and modules, such as the specifics of advertising technologies, data
warehouses, or data interfaces.
123
254 R. Rußell et al.: Monetizing Online Content: Digital Paywall Design and Configuration, Bus Inf Syst Eng 62(3):253–260 (2020)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
successful, the ACM module blocks the access to the
requested content until the user is authorized.
The subscription and access policy management (SAPM)
module manages the ACM module’s operations by setting up
the access restriction and pricing rules (see Sect. 3). An
interface to the CMS is necessary, if the access to specific
content units is supposed to be restricted. The access
restriction and pricing rules can be orchestrated by humans
or automated by algorithms based on various data sources
(see Sect. 4). Accordingly, an interface to the content pro-
viders’ accessible data sources is required to define the rules
and subsequently provide relevant information to the ACM.
The payment interface is a commonly integrated submodule
of the SAPM, which provides different payment methods or
links to payment service providers. The payment interface
exchanges subscriber and transactional data with the CRM
system and the ERP system.
The user interface facilitates a frictionless user experi-
ence of the internal processes of the paywall system (e.g., a
paywall page with login and registration options; a self-
service-area to update personal data and contracts).
The implementation of a paywall system provides con-
tent providers with new opportunities to leverage data, for
example anonymous data from non-paying users and per-
sonalized data from registered users. Content providers
could track the entire customer journey on their website,
from the first visit to the actual selection of subscription
options and re-purchase behavior. However, these oppor-
tunities produce new challenges. To use the data intelli-
gently, content providers need to store, link, and integrate
the data streams in a central database, and manage addi-
tional information accordingly. In addition, content provi-
ders need to operate website analytics tools to adapt the
configuration of a paywall solution according to user
activity. Based on the paywall system, content providers
can configure paywall solutions to monetize their content.
In the next section, we present the fundamental configu-
ration parameters of paywall solutions.
3 Configuration of Paywall Solutions
Once content providers have established the technological
capabilities to restrict access to their content, they can
subsequently configure the access restriction and pricing
rules in the SAPM module of the paywall system. Online
content is an information good which consumers need to
experience in order to evaluate their expected benefits and
costs (Lopes and Galletta 2006; Shapiro and Varian 1998).
Accordingly, content providers follow different strategies
to offer either free content, paid content, or a combination
of the two. Additionally, the cost structure of digital
information goods with a high fixed cost but almost zero
variable cost for distribution raises challenges regarding
what is priced (i.e., paying per use of the content, per
period, or offering bundles with the offline edition) and
how to set prices (i.e., based on costs or other metrics such
as consumers’ perceived value). Building on the literature
on revenue models (e.g., Veit et al. 2014) and pricing
models (e.g., Skiera et al. 2005), we present a framework to
classify paywall solutions by their most relevant economic
configuration parameters, namely access restriction options
and pricing options (see Fig. 2).
Whereas access restriction options specify the mecha-
nism to access content (see Sect. 3.1), pricing options
define how the access to this content is priced (see
Sect. 3.2). By selecting at least one option on each of the
two layers, paywall solutions can be classified according to
their respective functions.
3.1 Access Restriction Options
Overall, we distinguish between three access restriction
options, which follow different rules to decide whether a
user can access the requested content or not.
First, content providers can place a donation request on
their website whenever a user accesses the content. This
mechanism does not restrict the access to content but asks
Content Management
System
Customer Relationship
Management System
Enterprise Resource
Planning System
Website /
Application Software
User Interface
Paywall System
User
Core Systems
Access Control Management
Subscription & Access Policy
Management
Ad Tec h
Fig. 1 Stylized content
providers’ system architecture
with an integrated paywall
system
123
R. Rußell et al.: Monetizing Online Content: Digital Paywall Design and Configuration, Bus Inf Syst Eng 62(3):253–260 (2020) 255
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
users for a voluntary payment. This can be either a request
at the end of the free content consumption or a permanent
display ad on the website. Content providers who follow a
donation strategy may believe that their content on the
website needs to be open and accessible to anyone (Reuters
Institute 2018). A widely used economic pricing mecha-
nism for voluntary payments is called ‘Pay What You
Want’. This mechanism asks consumers to pay any price
they like, including zero (Schmidt et al. 2014). Examples
of media companies who successfully follow this strategy
are The Guardian and Wikipedia.
Second, content providers can implement a soft access
restriction, which allows at least some free content on the
website. This access restriction rule is based on a freemium
model, which simultaneously offers a limited free version
(i.e., free content) and a premium version with additional
benefits such as functionality or higher quality (i.e., paid
content) (Anderson 2009). By providing two versions of
the content, the media companies are able to differentiate
prices between consumers with heterogeneous valuations
for content (Lambrecht and Misra 2017). Theory distin-
guishes between price differentiation with and without self-
selection. In price differentiation without self-selection, the
seller divides buyers into different groups, offering varying
prices for each group (e.g., discounts for students). In
contrast, in price differentiation with self-selection, the
seller offers the same product in different versions at dif-
ferent prices, and allows consumers to decide which offer
suits them. The second mechanism is closely related to the
soft access restriction of a paywall solution, in which
content providers offer free content and let consumers
decide if they are willing to pay for the content behind the
paywall. The soft access restriction can further distinguish
whether or not the access restriction depends on the indi-
vidual usage behavior of consumers on the website, that is
a usage-dependent or usage-independent access restriction.
In a usage-dependent access restriction, content provi-
ders give consumers the freedom to choose their preferred
free content within a pre-defined allowance. Therefore,
news publishers have no control over what content
individual consumers actually consume (Halbheer et al.
2014). Accordingly, the access restriction rule is dependent
on the individual usage (i.e., browsing behavior) of con-
sumers on the website. The access restriction rule can be
based on the quantity of requested contents’ access (e.g., a
certain number of news articles or movies per month), or
the time a consumer spends on browsing the website’s
content (e.g., a certain duration of free content consump-
tion per day), before a payment for the unlimited access is
required (Chiou and Tucker 2013; Wilkinson 2013). An
example of a usage-dependent access restriction is The
New York Times’s ‘metered’ paywall, which allows free
access to a certain number of news articles per month.
In contrast, the usage-independent access restriction
limits the access to content by offering a pre-defined set of
free content, which is independent of the individual usage
of consumers. However, the consumption behavior of
consumers on the website can indirectly affect the selection
of free content, because the differentiation between free
and paid content is often determined by the content pro-
viders’ purported value of content for the audiences (Olsen
and Solvoll 2018). With this access restriction option,
content providers are able to manipulate the free content
strategically, that is they can decide what content to offer
for sampling (Halbheer et al. 2014). Widely used classifi-
cation rules to differentiate between free and paid content
are based on the breadth of offered free content (e.g.,
access restriction to specific genres), the objective quality
of free content (e.g., production costs; resolution of con-
tent; exclusiveness of content itself), or consumers’ pref-
erences (e.g., cumulative demand for specific content;
temporal access restrictions) (Aral and Dhillon 2017;
Chiou and Tucker 2013; Li et al. 2019; Oh et al. 2016). An
example of a usage-independent access restriction is the
French news publisher Le Monde, which offers specific
content (e.g., exclusive news articles) as paid content.
Third, content providers can place a hard access
restriction on their website to restrict the access to the
entire content by solely offering paid content. In this
option, consumers cannot access any content without
Access
Restriction Options
Pricing Options
Hard
(Paid Content)
Pay-per-use Pay-per-period
Donation
(Free Content)
Soft
(Free & Paid Content)
Usage-
independent
Usage-
dependent
Fig. 2 Core configuration parameters of a paywall solution
123
256 R. Rußell et al.: Monetizing Online Content: Digital Paywall Design and Configuration, Bus Inf Syst Eng 62(3):253–260 (2020)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
certain content-related restrictions. However, content pro-
viders usually allow consumers to access teasers of their
content free of charge (e.g., first paragraphs of a news
article). The Times, for example, launched a hard paywall
on their news website in 2010, believing that their quality
content is worth paying for.
A paywall solution requires a certain rule to restrict
access to the content providers’ online content (see Fig. 2).
The execution of access restriction rules can be based on a
variety of content and user data. Particularly, the soft
access restriction rules can be combined in the configura-
tion of paywall solutions. Optimizing the access restriction
rules based on data-driven decisions (e.g., consumers’
usage patterns) using ML is becoming increasingly
important (see Sect. 4). Besides the core access restriction
rules, content providers can differentiate their free and paid
content by additional features, such as refraining from
advertising in the paid content, device specific access
restrictions, or free access via referrers such as social
media platforms. Moreover, many content providers offer a
free trial access to the entire content and allow consumers
to bypass the access restriction options for a certain period.
3.2 Pricing Options
The pricing options of a paywall solution define how the
access to the media companies’ content is priced. More
specifically, these rules determine the quantity of content
units (e.g., the number of articles, songs, movies) that users
can access with a payment, as well as the duration of the
access period. We analyze the overarching pricing decision
that content providers face when intending to monetize
their online content. For this purpose, we focus on the
pricing rules related to the configuration of a paywall
solution.
Essentially, we differentiate between pay-per-use, that is
a usage-dependent tariff, and pay-per-period, namely a
usage-independent tariff or flat-rate. In theory, rational
consumers are expected to choose the tariff that will
maximize consumer surplus conditional on their beliefs
about individual usage, namely the quantity of content they
are going to consume. However, several studies show that
consumers prefer a pay-per-period to a pay-per-use
mechanism even though their resulting surplus is lower
(Lambrecht and Skiera 2006). The pay-per-use mechanism
requires users to pay a small fee, a micropayment, for each
unit of paid content they want to consume. An advantage of
this pricing mechanism for consumers is that they exclu-
sively pay for content that interest them. For content pro-
viders, these micropayments have the advantage that the
users’ entry barrier is much lower compared to higher,
usage-independent pricing mechanisms. In contrast, the
pay-per-period mechanism allows consumers to access an
unlimited quantity of content units in a pre-defined period.
Hence, it provides consumers with a flat-rate for a specific
period. The advantages of this pricing mechanism com-
pared to micropayments are the higher comfort of a single
payment for the user and the improved revenue pre-
dictability for content providers. The pay-per-period
mechanism can be differentiated into a single payment for
a pre-defined period, and a subscription, which is an
agreement for a recurring payment over a pre-defined
contract duration. Content providers often reward loyal
subscribers who opt for longer contract durations with
discounts on the recurring payments. Many content provi-
ders use a mixed pricing option, that is a pay-per-use and a
pay-per-period option to maximize direct revenue from
online content by exploiting consumers’ heterogeneous
valuations.
4 Use of Machine Learning in Paywall Solution
Configurations
Digital paywall systems’ functionalities can be enhanced
by ML to adjust and combine the solution’s configuration
parameters based on various data points. Hereby, digital
paywalls allow content providers (1) to individualize
access restriction and pricing options based on users’
behavior on the website and (2) to identify improved
classification schemes with respect to whether specific
content should be free or paid content. Specifically, ML
allows varying access restriction and pricing rules by rec-
ognizing patterns in user behavior data over time. The ML
model first needs to be trained with historical data.
Accordingly, the model learns about differences in data
patterns between objects (e.g., users, content units) which
reveal certain reactions (e.g., user conversion), and objects
which do not reveal the examined reactions. Based on these
patterns, the model can determine the optimal paywall
configuration for a specific user. The users’ interaction with
the paywall then serves as a basis for the ongoing
improvement of the paywall configuration. Figure 3
depicts a stylized workflow from data extraction and stor-
age to model training and the adaptive digital paywall.
Apart from data analytics competencies, a fundamental
requirement for using ML in optimizing digital paywall
configurations is a solid data infrastructure to extract and
synchronize various data streams such as anonymous vis-
itor data, personalized data from registered users and cus-
tomers, content data, and additional contextual data.
In the following, we describe three applications of ML
to transform static paywalls configured by humans into
dynamic paywalls configured by algorithms. First, content
providers can model users’ conversion probability score
based on behavioral data (e.g., visit recency and
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R. Rußell et al.: Monetizing Online Content: Digital Paywall Design and Configuration, Bus Inf Syst Eng 62(3):253–260 (2020) 257
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
frequency). The model learns about (individual) user’s
content consumption and conversion patterns and dynam-
ically adapts the paywall solution’s configuration (e.g.,
quantity of free content units). Second, content providers
can use ML models to identify which content is most
suitable as free or paid content. A content value score can
be predicted by content-related metrics, such as the con-
tent’s theme, and usage related-metrics, such as stickiness
(i.e., the duration a user reads the specific content). The
model could identify content that drives conversions and
classify it accordingly. Third, paywall systems can simul-
taneously optimize content classification and the individ-
ualization of the paywall solution’s configuration.
Additionally, content providers could feed ML algorithms
with contextual data, such as the time of the day or external
events (e.g., elections). The result can be a dynamically
adjusting digital paywall solution, which presents different
(free and paid) content to individual users or segments.
Besides the individualization of the paywall solution’s
configuration and classification of the content providers’
offer, ML can also be used to optimize communication
strategies (e.g., personalized newsletters), to engage cus-
tomers by improving the audience’s website experience
(e.g., personalized front-page), and to support content
creation (e.g., reporting emerging topics). However,
increasing the use of ML and automation by means of
artificial intelligence can also have negative consequences.
First, by managing ML models as ‘black boxes’, content
providers delegate control to algorithms. Content providers
increase the risk of filter bubbles if they allow algorithms to
decide which content is displayed to a specific audience.
Second, content providers face challenges with regulations
such as the General Data Protection Regulation (GDPR) or
the ePrivacy Regulation, which prohibit cookie-based
tracking of users without their explicit consent. From the
consumer’s perspective, identifying the usage of personal
data (e.g., by product recommendations) could lead to
intensified perceptions of privacy concerns, subsequently
increasing the probability of website abandonment by
consumers.
5 Prior Research and Avenues for Future Work
Digital paywall research has its origins in business model
research on the monetization of online content (e.g., Cle-
mons 2009) and optimal content strategies (e.g., Fan et al.
2007).
One research stream analytically studies when media
companies can benefit from offering free content, paid
content, or both. Fan et al. (2007) conclude that media
companies should offer paid content if the content quality
is high and access costs are low. In addition, Halbheer et al.
(2014) show that advertising effectiveness can determine
the optimal content monetization strategy. Another
research stream looks empirically at the consequences of a
paywall introduction. Most studies leverage quasi-experi-
mental settings of paywall introductions and find a negative
impact on website traffic (Aral and Dhillon 2017; Chiou
and Tucker 2013; Cook and Attari 2012; Pauwels and
Weiss 2008) and word of mouth activities (Oh et al. 2016).
In contrast, charging for access to online content not only
provides direct revenue but also protects own paid channels
from self-cannibalization (Pattabhiramaiah et al. 2019) and
Anonymous
visitor data
Personalized
user &
customer data
Content
data
Other
contextual
data
Model
Paywall System
(SAPM Module)
Access restriction rules
Pricing rules
•…
Data Extraction &
Storage
(Machine Learning)
Algorithm
Adaptive
Digital Paywall
Feedback based on user behavior
Training data Scoring results
(e.g., conversion
propensity score)
Fig. 3 Stylized workflow of using machine learning in configuring paywall solutions
123
258 R. Rußell et al.: Monetizing Online Content: Digital Paywall Design and Configuration, Bus Inf Syst Eng 62(3):253–260 (2020)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
enhances control over the substitutive effects of cross-
channel demand (Aral and Dhillon 2017).
Although initial paywall research has been conducted,
very little is known about the impact of paywall solution’s
configuration on user behavior. According to Aral and
Dhillon (2017), a decrease in the quantity and an increase
in the breadth of free content can increase the probability
of a non-paying user becoming a subscriber. Furthermore,
Lambrecht and Misra (2017) show that it can be optimal
for media companies to offer more free content during
periods of high demand. To the best of our knowledge,
only Davoudi et al. (2018) investigate the effect of adaptive
paywall solutions by modeling the restriction rule execu-
tion based on users’ costs and the utilities of articles. They
show that the adaptive mechanism can outperform static
mechanisms by applying the proposed method on a real
data set of a Canadian news publisher.
Future research should advance our understanding of
digital business models for content providers and of the
role of IT in developing and managing content monetiza-
tion strategies. Subsequently, we outline three promising
directions for future research.
The impact of paywall solution’s configuration on
consumer behavior in pre-conversion (acquisition) and
post-conversion stages (engagement and retention)
Researchers could empirically examine this relation-
ship by conducting experiments or analyzing secondary
data obtained from content providers. Additionally,
research could focus on important and relevant mod-
erators and mediators of this relationship, for instance
by examining content, consumers, markets, and addi-
tional paywall characteristics to generate insights on
optimal paywall configurations.
The effect of online content monetization strategies
across media products and their online and offline
channels While studies in the context of news content
exist, IS research could examine the applicability of
digital paywalls beyond this type of content. For
example, the German video streaming platform Joyn
recently implemented a usage-independent access
restriction for specific serials and movies on their
website. Additionally, IS research could focus on
content providers’ multi-channel activities, as well as
on bundling the offerings of one company or between
companies, which aim to increase the value of the
content providers’ paid content. Moreover, platform
characteristics of media companies’ websites need to be
further examined to optimize content monetization
strategies within this multi-sided market.
The impact of technological innovations and their
applicability on paywall systems and resulting paywall
solutions’ configuration Current trends in ML or
blockchain technology influence digital paywalls by
providing new system functionalities and related archi-
tecture designs. Recent general developments in the
media industry include the personalization and recom-
mendation of content, as well as the automation of
content creation (Newman 2019). Accordingly, ques-
tions arise regarding consumers’ attitudes toward auto-
mated processes, privacy concerns based on content
providers’ data usage, and threats to freedom of opinion
and the content providers’ role of informing the public
(e.g., filter bubbles) as consequences of the use of ML.
Insights into these topics can assist content providers to
better prepare themselves for their future in the digital
economy. Owing to its interdisciplinary foundations, the IS
discipline is particularly well positioned to advance this
field of research. The paid content market is growing and in
this process continuously bringing forward innovative
approaches to solve the content providers’ monetization
dilemma. In this relatively young research area of IS, the
BISE community could set new ground rules for strategies
to sell media products based on digital paywall approaches.
Acknowledgement Open Access funding provided by Projekt
DEAL.
Open Access This article is licensed under a Creative Commons
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... Kinerja model bisnis berlangganan media cukup beragam. Ada tiga opsi pembatasan konten yang biasanya diterapkan oleh media online berlangganan, yaitu donasi, soft paywall dan hard paywall (Rußell et al., 2020). Opsi donasi biasanya diambil oleh penyedia konten yang meyakini bahwa seluruh konten di situsnya harus disajikan secara terbuka agar dapat diakses oleh semua orang. ...
... Hal ini seperti yang diterapkan oleh surat kabar The Times yang menerapkan hard paywall di situsnya sejak 2010, karena mereka meyakini bahwa kualitas jurnalismenya patut untuk dibayar. (Rußell et al., 2020). ...
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... According to Rußell et al. (2020), there are three major paywall solutions to monetize online content directly: Firstly, donation-based models (free content). Secondly, soft paywall models (free and paid content), which are often referred to as freemium models, can be either usage dependent (a time or metered paywall) or usage independent (specific content is restricted for paid access). ...
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... Coupled with the [40] cited administrator control to delete user's posts, a future experiment could be created to explore whether the missing posts prior to August 9, 2022 were from one of these Gettr moderation avenues. Furthermore, inclusion of access control lists and public/private settings does set the platform up for tiers of communication to happen, much like paywalls for online content [35]. When Gettr does decide to implement code around the acl and/or vis fields, research could and should be done to evaluate the way communication is monetized on the platform. ...
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... It is also important to remark that the traditional paywall-model is not a polar opposite of the personalization-based revenue model. Quite the contrary, in fact: personalization is easier and likely more effective for subscribers whose personal data can be also correlated with "anonymous" visitor data (Rußell et al. 2020). Although personalization offers some advantages to consumers, such as potential relevance of the news stories displayed, they are also increasingly aware of the privacy risks, and feel that social media advertising, in particular, is mostly irrelevant, annoying, and unethical (Baglione and Tucci 2019;Brinson et al. 2018). ...
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Declining advertising revenue and print copy sales have propelled extensive paywall experiments in local newspapers to generate new revenue and fund local journalism. The success of these experiments is ultimately depending on whether or not they deliver the value that customers require. This article studies local newspapers’ potential to build successful paywalls by conducting a two-sided analysis of paywall value propositions and local news audiences’ responses to these value propositions. Drawing on mixed methods – in-depth interviews with 20 newspaper managers and a national survey (N = 1586) among local newspaper audiences – our study identifies a major gap between intended value of paywalls and customer value perception and behavior. These are misalignments between the intended attractiveness of paywalled content and audience attitude toward this content, and misalignments between access to paywalled content and use. Local newspapers’ offerings are particularly misaligned with younger, lower income and lower news interest customers. When these groups hit a paywall, they most likely bounce off.
Conference Paper
Many online news agencies utilize the paywall mechanism to increase reader subscriptions. This method offers a non-subscribed reader a fixed number of free articles in a period of time (e.g., a month), and then directs the user to the subscription page for further reading. We argue that there is no direct relationship between the number of paywalls presented to readers and the number of subscriptions, and that this artificial barrier, if not used well, may disengage potential subscribers and thus may not well serve its purpose of increasing revenue. Moreover, the current paywall mechanism neither considers the user browsing history nor the potential articles which the user may visit in the future. Thus, it treats all readers equally and does not consider the potential of a reader in becoming a subscriber. In this paper, we propose an adaptive paywall mechanism to balance the benefit of showing an article against that of displaying the paywall (i.e., terminating the session). We first define the notion of cost and utility that are used to define an objective function for optimal paywall decision making. Then, we model the problem as a stochastic sequential decision process. Finally, we propose an efficient policy function for paywall decision making. The experimental results on a real dataset from a major newspaper in Canada show that the proposed model outperforms the traditional paywall mechanism as well as the other baselines.
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Many online content providers aim to compensate for a loss in advertising revenues by charging consumers for access to content. However, such a choice is not straightforward because subscription fees typically deter customers, and a resulting decline in viewership further reduces advertising revenues. This research examines whether firms that offer both free and paid content can benefit from adjusting the amount of content offered for free. We find that firms should offer more free—and not paid—content in periods of high demand. We motivate theoretically that this policy, which we term “countercyclical offering,” may be optimal for firms when consumers are heterogeneous in their valuation of online content and this heterogeneity varies over time. Using unique data from an online content provider, we then provide empirical evidence that firms indeed engage in countercyclical offering and increase the share of free content in periods of high demand. This paper was accepted by Matthew Shum, marketing.
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Information goods providers such as print newspapers are experimenting with different pricing models for their online content. Despite research on the topic, it is still not clear how information pricing strategy influences word-of-mouth (WOM) via social media, which has become a dominant channel for raising awareness about a newspaper's articles and attracting new visitors to its website. Using The New York Times' paywall rollout as a natural experiment, our study examines how the implementation of paywall by a firm (i.e., a shift from "free" to "for-a-fee") influences the pattern and effectiveness of online WOM in social media. Our results indicate that implementing a paywall (i.e., charging for content that was earlier available for free) has a disproportionate impact on WOM for popular and niche articles, creating a longer tail in the WOM (i.e., content sharing) distribution. Further, we find that the impact of WOM on the NYT's website traffic weakens significantly after the introduction of a paywall. These results show that a paywall has implications for product and promotion strategies. The study offers novel and important implications for the theory and practice of strategic use of social media and paywall.
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While consumption of content in offline formats continues to decline, many providers are still struggling to monetize their content online, because consumers’ willingness to pay (WTP) for content in online formats is low. The availability of free content on the Internet is often considered the primary reason for this issue. However, we hold that the lower WTP is also related to a lower appraisal of online formats per se. Using a conjoint analysis and the example of newspaper subscriptions, we explore differences in consumer preferences and WTP between offline and online formats. Our results show that after price, format is the second-most important attribute of a newspaper subscription. While consumers still prefer the printed newspaper to any online format, WTP differs across online formats and is strongly associated with device ownership. Our study provides a novel understanding of the previously neglected factor content format and its importance for content providers.
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Almost all attempts to date to monetize Internet applications targeted at individuals have focused on natural extensions of traditional media or traditional retailing. Most are either some form of consumer-focused advertising or of consumer-focused e-commerce. And yet the Net is far more powerful than traditional media on one hand, and far more liberating and thus inappropriate as an alternative to traditional media on the other. There are numerous potential online business models that are not based on advertising. This paper explores several such areas and divides them into two basic categories, those that sell some product, experience, content, or service and earn revenues from the sale, and those that provide access to consumers and charge for access. It further divides each of these major categories into subcategories, and for each subcategory reviews current experience, places it in the context of the relevant literature in competitive strategy, and uses that theory to make predictions. The paper concludes with strategic recommendations for corporations as well as with suggestions for further research.