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Binge Watching and Advertising
Abstract
How users consume media has shifted dramatically as viewers migrate from traditional broadcast channels toward online channels. Rather than following the schedule dictated by television networks and consuming one episode of a series each week, many viewers now engage in binge watching, which involves consuming several episodes of the same series in a condensed period of time. In this research, the authors decompose users' viewing behavior into (1) whether the user continues the viewing session after each episode viewed, (2) whether the next episode viewed is from the same or a different series, and (3) the time elapsed between sessions. Applying this modeling framework to data provided by Hulu.com, a popular online provider of broadcast and cable television shows, the authors examine the drivers of binge watching behavior, distinguishing between user-level traits and states determined by previously viewed content. The authors simultaneously investigate users' response to advertisements. Many online video providers support their services with advertising revenue; thus, understanding how users respond to advertisements and how advertising affects subsequent viewing is of paramount importance to both advertisers and online video providers. The results of the study reveal that advertising responsiveness differs between bingers and nonbingers and that it changes over the course of online viewing sessions. The authors discuss the implications of their results for advertisers and online video platforms.
... In recent years, various streaming media platforms and Internet entertainment services (e.g., Hulu and Netflix) have fundamentally altered the ways in which audiences watch, discuss, and consume media content. Today's audiences have been moving away from consuming traditional broadcast channels toward streaming online video content to gain more control over their media consumption (Lotz, 2014;Schweidal & Moe, 2016;Hayes & Chmielewski, 2022), and bingewatching has become increasingly popular among audience members. (e.g., Castro et al., 2021;Hayes & Chmielewski, 2022;Jenner, 2014;Panda & Pandey, 2017). ...
... Other than the factors mentioned above, there were also several other factors that may account for why people binge-watch, such as social recommendations (Schweidal & Moe, 2016). For example, recommendations by important others (e.g., friends, family members) may trigger individuals to engage in binge-watching of that particular media content. ...
... As shown in Table 2, individuals' motivations for binge-watching are composed of multiple variables adapted from U&G literature, including cultural inclusion (Steiner & Xu, 2020), enjoyment (Panda & Pandey, 2017), immersion (Sundar & Limperos, 2013), and easy accessibility to content (Schweidal & Moe, 2016). The items within each construct showed high multiple-item reliability (Cronbach's α > 0.70). ...
... The presence of consumer "eyeballs" on streaming media represents an attractive opportunity for advertisers, especially as these services allow for ad personalization due to the availability of rich data. As a result, advertising spending on streaming media services is expected to grow to $20 billion in 2020 from $4.7 billion in 2017 (eMarketer, 2018). 1 However, streaming media represents new challenges, especially as interruptions to the viewing experience via advertising detract from the viewers' feeling of being in control and can lead to decreased content consumption (Schweidel & Moe, 2016). In addition, platforms that provide these services need to balance the viewers' control of the consumption experience while delivering advertising commensurate with advertiser objectives. ...
... In order to do this, I first need to specify a temporal unit of consumption for a given viewer. I denote this unit as a viewer-session (in future, I use the term "session" to denote this unit) which is defined as a period of time spent by a viewer watching one TV show separated by 60 minutes or more of inactivity as in Schweidel and Moe (2016). ...
... The first metric, which I label "Bingeability," is based on the theory of "flow" (Ghani & Deshpande, 1994;Schweidel & Moe, 2016) as well as industry norms and captures the extent of viewer immersion in the content. In essence, this metric is based on a stylized count of complete and unique episodes of a TV show watched in a session. ...
The video streaming industry is growing rapidly, and consumers are increasingly using ad-supported streaming services. There are important questions related to the effect of ad schedules and video elements on viewer behavior that have not been adequately studied in the marketing literature. In my dissertation, I study these topics by applying causal and/or interpretable machine learning methods on behavioral data. In the first essay, “Finding the Sweet Spot: Ad Scheduling on Streaming Media”, I design an “optimal” ad schedule that balances the interest of the viewer (watching content) with that of the streaming platform (ad exposure). This is accomplished using a three-stage approach applied on a dataset of Hulu customers. In the first stage, I develop two metrics – Bingeability and Ad Tolerance – to capture the interplay between content consumption and ad exposure in a viewing session. Bingeability represents the number of completely viewed unique episodes of a show, while Ad Tolerance represents the willingness of a viewer to watch ads and subsequent content. In the second stage, I predict the value of the metrics for the next viewing session using the machine learning method – Extreme Gradient Boosting – while controlling for the non-randomness in ad delivery to a focal viewer using “instrumental variables” based on ad delivery patterns to other viewers. Using “feature importance analyses” and “partial dependence plots” I shed light on the importance and nature of the non-linear relationship with various feature sets, going beyond a purely black-box approach. Finally, in the third stage, I implement a novel constrained optimization procedure built around the causal predictions to provide an “optimal” ad-schedule for a viewer, while ensuring the level of ad exposure does not exceed her predicted Ad Tolerance. Under the optimized schedule, I find that “win-win” schedules are possible that allow for both an increase in content consumption and ad exposure. In the second essay, “Video Influencers: Unboxing the Mystique”, I study the relationship between advertising content in YouTube influencer videos (across text, audio and images) and marketing outcomes (views, interaction rates and sentiment). This is accomplished with the help of novel interpretable deep-learning architectures that avoid making a trade-off between predictive ability and interpretability. Specifically, I achieve high predictive performance by avoiding ex-ante feature engineering and achieve better interpretability by eliminating spurious relationships confounded by factors unassociated with “attention” paid to video elements. The attention mechanism in the Text and Audio models along with gradient maps in the Image model allow identification of video elements on which attention is paid while forming an association with an outcome. Such an ex-post analysis allows me to find statistically significant relationships between video elements and marketing outcomes that are supplemented by a significant increase in attention to video elements. By eliminating spurious relationships, I generate hypotheses that are more likely to have causal effects when tested in a field setting. For example, I find that mentioning a brand in the first 30 seconds of a video is on average associated with a significant increase in attention to the brand but a significant decrease in sentiment expressed towards the video. Overall, my dissertation provides solutions and identifies strategies that can improve the welfare of viewers, platform owners, influencers and brand partners. Policy makers also stand to gain from understanding the power exerted by different stakeholders over viewer behavior.
... They may ignore the content delivered by a long advertisement more than that of a short one [15] or block certain web advertisements, such as pop-ups, through a browser's add-on gadget [16]. Therefore, it is paramount for streaming providers to know how viewers respond to advertisements and analyze the relationship between watching hours and advertising frequency [17]. In addition, media platforms can reduce viewers' feelings of antipathy toward commercials by customizing advertisements according to their browsing history; however, emerging privacy concerns may decrease the subscription revenue [18,19]. ...
... Though our analytical result indicates that it depends on the threshold ̂ , we cannot construct a numeral experiment showing this outcome at the turning point because the advertisement demand drops to zero when the paid subscriptions are in the majority. Thus, when a channel has more free subscribers than paid ones, 17 we can anticipate that, as long as the two ad services can be reasonably differentiated, sharing more paid subscription revenue with streamers not only fuels their effort but also promotes sales of platform ads. According to business reports, both YouTube and Twitch share revenue from paid subscriptions with streamers and allow them to keep 70% and 50% of the revenue, respectively. ...
Video live streaming services have reached every corner of the world through the influence of COVID-19. In this study, the business model of a video live streaming platform is examined under a structure in which both a streamer and a platform provider simultaneously have an incentive alignment and a payoff conflict. On the one hand, the streaming platform relies on the efforts of streamers to strengthen its market share; on the other hand, streamers can employ influencer marketing to construct their own additional revenue from commercials, which can affect the sales from the advertisements operated by the platform. In addition, the platform provider can reward talented streamers for their remarkable performance by sharing the subscription revenue with them; however, the adoption of a built-in reward system is perplexing because the platform can levy a commission fee from the money donated to streamers. Combining these practical points, our results indicate that advertorials can still be largely expanded by streamers mastering marketing skills, even if there is high substitution in ad services. In addition, the practice of charging a commission fee from the built-in reward system but sharing the subscription revenue with outstanding streamers can benefit the streaming platform, and their donation loss will be compensated by a higher revenue-sharing ratio.
... On-demand media consumption has shifted dramatically in the past 20 years, transforming the landscape of consumer behaviour (Liu et al., 2018). The Internet has disposed of traditional barriers of content distribution and management, and the new emerging patterns of media consumption are often dubbed as 'binge watching,' where individuals are found to consume condensed media content over an extended period (Schweidel & Moe, 2016). Online video streaming companies such as Netflix, Hulu and Amazon Prime Video have seen a surge in their user base since the onset of the COVID-19 pandemic. ...
... Previous studies in online media consumption have made significant contributions towards unpacking the binge-watching phenomenon. For example, in their pioneering work, Schweidel and Moe (2016), closely inspected (and modelled) Hulu series consumption behaviour by mathematically incorporating user viewing behaviour (such as frequency, continuous viewing and series hopping) against viewing variables such as episode depth, season depth and season finale. Their findings indicate that viewers exhibit addictive consumption behaviour towards selected genres and the nature of the programme, and not necessarily the content providing platform. ...
The management literature has extensively studied viral marketing in the last decade; however, there is a lack of research in understanding network structures and the role of influencers within popular cultural consumption, such as on-demand digital media and binge-watching. In this article, we investigate the role of social media in popularising the East Asian dystopian cultural drama Squid Game. We studied this phenomenon by analysing social network structures, dynamics and influencer characteristics that transformed Squid Game into a popular global digital cultural consumption sensation. Stemming from the foundational theories of popular culture binge-watching, network theory and the social media echo chamber effect, we demonstrate how careful ‘seeding’ and ‘broadcasting’ behaviour adopted by Netflix and key influencers helped the ‘reciprocal merging’ of creative media content within the broader social media space. Our study found that 13,727 Twitter users were tweeting or mentioned on the day show was released. Our research findings further present the characteristic of individual group-based echo chambers and their role in value co-creation towards expanding the network boundary through e-WOM. This phenomenon led to the show’s unprecedented popularity amongst a global audience within a short period. Contributions of our work expand viral marketing and echo-chamber concepts into the binge-watching and popular digital culture realm, where the interplay between dramatized Asian and Western dystopian social norms provided the very fabric of user-led promotion and value co-creation.
... A more recent survey reports that more than 80% of consumers (ages 21-51 years old) view about seven episodes of a T.V. series in a single sitting [4]. Schweidel and Moe [8] show that consumers in the binge-watching state are more likely to continue watching the episodes from the same T.V. series on the Internet channels. However, it is still unclear how the users' content consumption decisions vary in different engagement states. ...
... Kim et al. [37] introduce a concept of mobile users' engagement and use the cognitive-affective-conative state framework to examine users' mobile engagement motivations. Schweidel and Moe [8] examine users' online viewing decisions and responses to the advertisement using a video streaming viewing data set. They find that users are more likely to bingewatching if they watch more episodes from a series in a session. ...
... Some authors proposed four different types of binge-watchers (i.e., recreational TV series viewers, regulated binge-watchers, avid binge-watchers, and unregulated binge-watchers; Flayelle et al., 2020); others differentiated high, medium, and low bingewatchers based on the number of episodes, duration, and frequency of viewing sessions (Sung et al., 2018); and still others distinguished between intentional and unintentional binge-watchers (Riddle et al., 2018). Additionally, even to assess binge-watching behavior, several proposals have been made: Some authors have suggested that both the number of consecutive episodes (e.g., Schweidel and Moe, 2016) and the viewing sessions' duration (e.g., Trouleau et al., 2016), should be considered when measuring binge-watching; others (Vaterlaus et al., 2019) define binge-watching as a problematic behavior when view sessions exceed 4 h; and still others do not identify a minimum duration (Schweidel and Moe, 2016;Sung et al., 2018;Sharma et al., 2019) or even suggest that setting a threshold represents a valueless approach (Flayelle et al., 2017). ...
... Some authors proposed four different types of binge-watchers (i.e., recreational TV series viewers, regulated binge-watchers, avid binge-watchers, and unregulated binge-watchers; Flayelle et al., 2020); others differentiated high, medium, and low bingewatchers based on the number of episodes, duration, and frequency of viewing sessions (Sung et al., 2018); and still others distinguished between intentional and unintentional binge-watchers (Riddle et al., 2018). Additionally, even to assess binge-watching behavior, several proposals have been made: Some authors have suggested that both the number of consecutive episodes (e.g., Schweidel and Moe, 2016) and the viewing sessions' duration (e.g., Trouleau et al., 2016), should be considered when measuring binge-watching; others (Vaterlaus et al., 2019) define binge-watching as a problematic behavior when view sessions exceed 4 h; and still others do not identify a minimum duration (Schweidel and Moe, 2016;Sung et al., 2018;Sharma et al., 2019) or even suggest that setting a threshold represents a valueless approach (Flayelle et al., 2017). ...
Nowadays, binge-watching (i.e., watching multiple episodes of a TV series in one session) has become a widespread practice of media consumption, raising concerns about its negative outcomes. Nevertheless, previous research has overlooked the underlying psychological mechanisms leading to binge-watching. In the present work, we investigated some of the psychological variables that could favor binge-watching tendencies in a sample of TV series viewers ( N = 196). To this aim, psychological determinants of problematic digital technologies usage (i.e., feelings of loneliness), as well as some of the mechanisms related to the enjoyment of media contents (i.e., escapism and the identification with media characters), were considered as predictors of the tendency to binge-watch. Results indicated that higher feelings of loneliness were associated with higher levels of problematic digital technologies usage. Additionally, direct and indirect effects showed that only escapism – out of the four dimensions measuring the problematic use of Internet-related technologies – predicted participants’ stronger identification with media characters, which in turn promoted greater binge-watching tendencies. Overall, we suggest that binge-watching could be interpreted as a coping strategy for media escapists, who enjoy TV series as a privileged online space in which the need to escape finds its fulfillment, allowing them to manage loneliness by identifying with a fictitious character.
... In testing how ad exposure affects consumer choice after consecutively consuming similar media, we build on research that found that TV advertisements can disrupt bingewatching behavior (Schweidel and Moe 2016). By manipulating whether the ads were perceived as similar to prior video consumption, we test the prediction that ads are less likely to disrupt the rabbit hole effect when they fall within the same category as prior media consumption. ...
... Lastly, this research has implications for advertisers. Prior research on binge-watching found that advertisements shown during a viewing session can reduce binge-watching behavior (Schweidel and Moe 2016). Expanding on this, we find that ads tend to disrupt the rabbit hole effect when they are unrelated to the shared category, but can perpetuate the rabbit hole when they fall within the shared category. ...
Consumers often become “stuck in a rabbit hole” when consuming media. They may watch several YouTube videos in the same category or view several artistic images on Instagram on the same theme, finding it difficult to stop. What contributes to this behavior, causing consumers to choose to consume additional media on a similar (vs. different) topic to what they just experienced? The authors examine a novel antecedent: the consecutive consumption of multiple similar media. After viewing multiple similar media consecutively, more consumers choose to view additional similar media over dissimilar media or complete a dissimilar activity entirely, even when the prior consumption pattern is externally induced. The rabbit hole effect occurs due to increased accessibility of the shared category—when a category is more accessible, people feel immersed in that category and anticipate that future options within that category will be more enjoyable. The authors identify three characteristics of media consumption that contribute to the rabbit hole effect by increasing category accessibility: similarity, repetition, and consecutiveness of prior media consumption. This research contributes to literature on technology, choice, and variety-seeking and offers implications for increasing (vs. slowing) similar consumption.
... Overall, the finding suggests the similar structural factors of VOD and social media use may contribute to adverse health outcomes for users, beyond the same problematic use tied to broadcast TV watching. This could be due to the structural differences between digital media interfaces and broadcast television (Schweidel & Moe, 2016). Broadcast television has clear structural breakpoints (i.e., organized schedules). ...
... These structures may provide scripted decision-points where audiences choose to keep watching, change the channel, or turn the TV off. Most VOD services, however, auto-play the next episode, and social media channels have adopted infinite scroll, considered a hallmark of "addictive" software design (Schweidel & Moe, 2016). These interfaces may encourage problematic watching in a way that negatively impacts sleep onset. ...
Media use appears to adversely affect sleep quality. Yet, findings remain inconsistent based on medium, duration, and manner of use. Given the recent, widespread rise in consumption of video-on-demand services and social media platforms, problematic use of these media has become of interest to media and sleep researchers. Although research has looked at the correlation between problematic media use and sleep, to date no studies have compared different media platforms to better understand the processes. To address this, we conducted a survey examining the relationships between both sleep quality and depression with problematic broadcast television, video-on-demand, and social media use. Results demonstrate problematic Internet-based media consumption, i.e., video-on-demand and social media use, is related to adverse sleep outcomes while broadcast television use, even when problematic, was not related to adverse sleep outcomes in our study. Similar results were found for depression. Implications for research and clinical practice are discussed.
... link: https://rb.gy/lv9zn9 4 olarak tanımlanır. Çoğu çalışma, 'oturum başına minimum bölüm sayısı' yaklaşımı (örn., Schweidel & Moe, 2016) veya 'görüntüleme oturumu uzunluğu' işlevselleştirmenin (örn., Trouleau et al., 2016) içinde yer alır. ...
ZET Bu çalışma, seri video içeriğinin aşırı izleme (binge-watching) deneyimiyle ilgili psikolojik kavramları inceledi. Sonuçlar, ulaşılan seviyede, nakillin izleyicilerin aşırı izleme deneyimlerine ve davranışlarına şekil vermedeki merkezi rolünü vurgulamaktadır. Nakil, aşırı izleme sıklığıyla pozitif bir ilişkiye sahiptir ve aşırı izleme seansının uzunluğunun parasosyal etkileşimlerin gelişimi üzerindeki etkisini (tam aracılık) ve aşırı izleme keyfi üzerindeki etkisini (kısmi aracılık) aracılık etmektedir. Akış deneyimleyebilme becerisi, bir aşırı izleme seansının uzunluğunu öngördüğü bulunmuştur. Diğer önemli ilişkiler de ortaya konmuştur. Çalışmanın teorik ve pratik çıkarımları, gelecekteki araştırmalar için öneriler ve aşırı izlemenin mevcut kavramsal görünümlerinin genişletme olasılığı tartışılmaktadır.
... Binge-watching India ranks first in the global index. It is a habit where people tend to watch entertaining or informative content for a long period called binge-watching [2]. It could be a television show. ...
Too much of anything is bad for health. In recent years we have been familiar with “Binge”. It may be in the case of eating, drinking, or watching movies. Generation Z is very much affected by this way of living. This habit comes from indulgence. These indulgences come mainly from heredity factors, psychological conditions, dieting, peer pressure, etc. Studies show that some important features can be shared, including personality and emotional features such as neuroticism and urgency. Excessive indulgence can lead to physical and mental breakdowns. Interpersonal psychotherapy (IPT) is an effective specialty treatment for different disorders that leads to a healthy life. A continuous effort to identify the consequences of binge behaviours will also aid the development of the research field. We have to build a society free from excessive indulgence.
... When asked about the most affect you most in the web series, 40.40% of the respondents agreed to like the cast, story and theme of the web series, while 30.50% agreed to like dialogues [22]. 20.60% agreed with abusive language and double meaning jokes and 8.50% of respondents agreed with sexual scene. ...
Nowadays, Web series and online streaming content are becoming the heart of
the youth. Web series are replacing television and have seen a boom in online
streaming and web series content produced in India. Many big companies like
Amazon, Netflix, SonyLiv, Hot star, and Eros Now have invested heavily in regional
content. Web series have gained popularity in India in the last few years because
they take us where television won't. Web series and online streaming allow their
audience to watch shows at their convenience.
This research paper analysis the psychosocial impact of web series and online
steaming content amongst youth on online platforms like YouTube, Amazon,
Netflix, SonyLiv, hot star, and Eros Now, and Torrent downloads. The researcher
also examined the perception of youth regarding the web series and online
streaming content. The questionnaire was used to gather information from the
respondents. The respondents were students studying in different Colleges and
Universities in Haryana, India.
... At the same time, it engages a person's various cognitive processes (perception, memory, attention, thinking). Both the emotions experienced by a person during binge-watching and cognitive processes that may result in excessive loss of control over the number of watched episodes (Schweidel and Moe, 2016;Granow et al., 2018;Flayelle et al., 2019;Flayelle, 2020). ...
... At the same time, it engages a person's various cognitive processes (perception, memory, attention, thinking). Both the emotions experienced by a person during binge-watching and cognitive processes that may result in excessive loss of control over the number of watched episodes (Schweidel and Moe, 2016;Granow et al., 2018;Flayelle et al., 2019;Flayelle, 2020). ...
... At the same time, it engages a person's various cognitive processes (perception, memory, attention, thinking). Both the emotions experienced by a person during binge-watching and cognitive processes that may result in excessive loss of control over the number of watched episodes (Schweidel and Moe, 2016;Granow et al., 2018;Flayelle et al., 2019;Flayelle, 2020). ...
... At the same time, it engages a person's various cognitive processes (perception, memory, attention, thinking). Both the emotions experienced by a person during binge-watching and cognitive processes that may result in excessive loss of control over the number of watched episodes (Schweidel and Moe, 2016;Granow et al., 2018;Flayelle et al., 2019;Flayelle, 2020). ...
This book examines the use of modern technologies in clinical psychological practice. It considers how we define attachment in an age where changes in technology and the COVID-19 pandemic have increased the prevalence of online contact in the process of diagnosis and psychological treatment.
Based on an attachment paradigm that is relatively unexplored, the book outlines how modern online contact influences mental health and development, along with the therapeutic relationship between client and professional. It discusses people’s relationships with new technologies, how relationships can be established using these technologies, and how these technologies affect professional relationships between psychologists and their clients, which they define as e-attachment. In the context of new technologies, the book draws on neurobiology and clinical psychology to consider mental health, social functioning, and emotional regulation.
Presenting both theory and examples from case studies, this cutting-edge book will be of great interest to researchers, academics, and post-graduate students in the fields of clinical psychology, psychotherapy, and mental health. Those also carrying out research into digital and online learning within the field of mental health will also benefit from this text.
Link: https://www.routledge.com/E-attachment-and-Online-Communication-The-Changing-Context-of-the-Clinical/Sitnik-Warchulska-Izydorczyk-Wajda/p/book/9781032116860
... TV watching also provides information value regardless of the education level of its audience (Battaggion & Vaglio, 2020). Traditional TV is now being challenged in terms of customer attraction and market leadership due to the advent of TV stations and channels, as well as the increase in the number and types of media (Ewing, 2013;Schweidel & Moe, 2016). However, 79.3% of Filipinos surf the Internet for social media (Mapa, 2020). ...
Television as a medium of marketing communication has a decreasing exposure rate among generation Z due to the increasing patronage on Internet-based communication. However, marketers could not fully shift into online platforms because of television’s high market reach attribute especially in the Philippines. Establishing awareness is a crucial work for unknown brands but repetition does not guarantee familiarity. A comparative analysis on the impact of energetic commercials on deactivating audiences was performed while this research aimed to identify the factors affecting Gen Z’s consumer perception towards television as an advertising medium. Data collection was done through survey questionnaires distributed to 385 respondents. Data were treated with statistical tools such as measures of central tendency, measures of variability and partial least square - structural equation modelling (PLS-SEM). The results revealed that Perceived Ease of Use is an insignificant variable to consumer perception. It was discovered that watching TV news, movies, series, and more is not usually preferred by consumers; they would rather stream online. However, Information Gratification is found to significantly influence consumer perception on TV as an advertising medium. Consumers get to know new products and brands when watching TV. The results of this study will mostly benefit advertising agencies because they will further understand the current perception of the generation on television advertising. Thus, more effective strategies concerning television advertising will be implemented. Keywords: TV, advertising, gen Z, consumer perception, perceived ease of use, perceived usefulness, information gratification
... A study revealed that a major portion of the people in America love to binge-watching and often finish a series less than a week. It is also found that people prefer and enjoy watching the multiple episodes of a series in a short span of time (Schweidel and Moe, 2016). ...
Information technology has changed the living style of people in the last few decades by its evolution and revolution. So, ‘digitalisation’ is considered as very imperative in human history especially after the ‘industrial revolution’. With the changing paradigm, digitalisation has provided enormous space for the entertainment of Individuals through the Over-the-Top (OTT) video platforms on their demand. In India, the significant growths of OTT platforms have been noticed during the last decade with an increasingly growing number of consumers. With such huge demand, a surge of consumers in India, the OTT became a commodity rather than a luxury. Further, the demands of consumers & internationalisation open up its OTT market for domestic as well as international players. The OTT players like Hotstar and Jio Cinema has expanded a stouter position, whereas global players like Netflix and Amazon Prime have also extended progressively their market share in India. According to one report, the Video on Demand (VoD) industry is still at its emerging stage but the entry of 40 VoD companies in a span of just three years indicates the popularity and demand of such industry. This huge demand has exposed the concept of ‘Binge Watching’ in India as this platform provides on-demand, anywhere access, without a commercial break and unlimited access. However, these growing OTT players and online content have faced many controversies and fought legal battles in India due to the lack of regulatory mechanisms. This paper explores the emergence & growth of OTT platforms with their recent trends in India. Further, the paper specifically focuses on the regulatory regime of OTT platforms since the beginning and its current scenario.
... That cultural reclamation is forcing a revolution within the TV industry (Lotz, 2014). Scholars note how binge-watching is disrupting norms of televisual advertising (Schweidel and Moe, 2016) as well as traditions of content production and distribution (Lotz, 2014: 8-11). Perks (2015) uses multiple methods to explore new consumption rituals of multimedia texts. ...
In this article, we explore how binge-watching culture and technology are changing the ways viewers understand and interact with television. We propose that the motives and rituals of binge-viewers can be used to expand uses and gratifications (U&G) theory. We conducted qualitative, semi-structured interviews to gather thick descriptions of why people binge-watch, how they binge-watch, and how they feel about binge-watching. The findings indicate that (1) viewers' primary motivations for binge-watching are catching up, relaxation, sense of completion, cultural inclusion, and improved viewing experience; (2) the portability and navigability of streaming video technology influence binge-watching rituals; and (3) viewers are ambivalent about their binge-watching. Based on the findings, we propose that a viewer attentiveness spectrum is a more accurate descriptor of contemporary TV watching than the passive/active dichotomy. We further argue that the changing motives and rituals of TV viewers can be used to bolster the quantitative surveys often employed in U&G research and to address the lingering criticisms of U&G theory.
... When asked about the most affect you most in the web series, 40.40% of the respondents agreed to like the cast, story and theme of the web series, while 30.50% agreed to like dialogues [22]. 20.60% agreed with abusive language and double meaning jokes and 8.50% of respondents agreed with sexual scene. ...
The Practice of Media Education and Media Research: A Review on Five Asian Countries
... Furthermore, some authors state that problematic binge-watching may even have certain similarities to substance or behavioural addictions (4,10,12,13). Prior research has shown that binge-watching is a highly engaging behaviour, meaning that it could lead to an increased loss of control over time (8,11,(13)(14)(15). Some studies have found that participants report experiencing various difficulties in attempting to reduce the time that they spend binge-watching TV series (8,16). ...
Recently, the question about the potentially problematic characteristics of binge-watching behaviours has been raised in the contemporary literature. Binge-watching is a highly popular behaviour that involves watching multiple episodes of TV series in one sitting. Studies show that binge-watching can be both an entertaining, but also a potentially problematic, behaviour. Therefore, this research aimed to answer the question about how impulsivity, difficulties in emotional regulation, and one's motivations around why they want to watch a TV series predict problematic binge-watching among a group of Polish young adults. The research group consisted of 645 participants. The following tools were then used to measure the study variables: the Impulsive Behaviour Scale, the Difficulties in Emotion Regulation Scale, the Viewing Motivation Scale, and the Questionnaire of Excessive Binge-watching. Furthermore, a regression analysis was performed on the responses to each measure in order to answer our research questions. Our results show that a lack of premeditation, impulse control difficulties, and having an escapist motivation are all significant predictors of problematic binge-watching behaviours. Furthermore, one's motivations around dealing with loneliness, their motivations around how to best spend their free time, as well as their informative and entertaining motivations were also found to be significant predictors of problematic binge-watching behaviours.
... The key aspect differentiating social live streams [1] from other popular media forms, such as TV or video on demand (Schweidel and Moe, 2016), is that the streaming and the consumption of content occur in real time. This allows for real-time social interactions between content creators (i.e. ...
Purpose – Social live-streaming services are an emerging form of social media that is gaining in popularity among researchers and practitioners. By facilitating real-time interactions be-tween video content creators (i.e., streamers) and viewers, live-streaming platforms provide an environment for novel engagement behaviors and monetization structures. In this research, the authors examine communication foci and styles as levers of streaming success. In doing so, they analyze their impact on viewers’ engagement with the stream.
Design/methodology/approach – This research draws on a unique dataset collected via a multi-wave questionnaire comprising viewers’ perceptions of a specific streamer’s communications and their actual behavior toward them. The authors analyze the proposed impact of communica-tion foci on viewing and donating behavior while considering the moderating role of communi-cation style using seemingly unrelated regressions.
Findings – The results show that communication foci represent a double-edged sword: commu-nity-focused communication drives viewership while reducing donations made to the streamer. In contrast, content-focused communication curbs viewing but drives donating.
Practical implications – Of specific interest for practitioners, the study demonstrates how streaming content providers (e.g., influencers) should adjust their communications to drive en-gagement in the context of synchronous social media such as social live-streaming services. Beyond that, this research identifies unique characteristics of engagement that can help manag-ers to improve their digital service offerings.
Originality/value – The authors highlight the need to distinguish between engagement behav-iors in asynchronous and synchronous social media. The proposed conceptualization sheds new light on success factors of social media in general and social live-streaming services specifical-ly. To maximize user engagement, content creators in synchronous social media must consider their communications’ focus (content or community) and style (utilitarian or hedonic).
Social Implications – Social live-streaming services provide an environment that offers unique opportunities for self-development and co-creation among social media users. By allowing for real-time interactions, these emerging social media services build on ephemeral content to pro-vide altered experiences for users.
Keywords: Live streaming services, Content creation, Content consumption, Engagement, Social media, Ephemeral content
... A new phenomenon that has been observed lately with the ongoing Covid Pandemic is binge watching. A broad definition of binge watching is consumption of multiple episodes of a TV series in a short period of time (Schweidel & Moe, 2016). The Digital Democracy Survey defines binge watching as "watching three or more episodes of a TV series in one sitting". ...
In recent times, video game live-streaming is rising with tremendous speed as a dominating form of live entertainment parallel to the growth of the gaming sector. The emergence of a new form of media led to the formation of internet services only for the live-streaming of video games. In the present paper, we study binge-watching and video game live streaming which shows that how streamers and spectators act based on their possible actions. Based on the reviews, authors were able to understand live-streamers behavior and channel surfing.
... The occurrence of anti-health form of binge-watching could be related to the new construction of narrative created by streaming platforms, characteristics of video on demand platforms, and individual psychological predispositions to development of problematic use of media (Alter, 2017;Grzegorzewska and Cierpiałkowska, 2018;Boca, 2019;Brand et al., 2019). Research has shown that binge-watching is an event that is very engaging both emotionally and cognitively, which may lead to loss of control over the number of watched episodes (Schweidel and Moe, 2016;Flayelle et al., 2017;Granow et al., 2018). The aforementioned loss of control is undoubtedly related to the production of series with a comprehensive narrative that keeps the viewer's attention (Alter, 2017). ...
In recent years, binge-watching becomes a highly popular way of spending free time. Even though binge-watching usually is related to entertainment, there are concerns about some negative and unhealthy outcomes of excessive form of this behavior. The study examined the predictive value of anxiety-depressive syndrome in explaining the symptoms of problematic binge-watching and the tendency to adopt a specific motivation to watch series. Research group consists of 645 Polish young adults. The State-Trait Anxiety Inventory, Depression Measurement Questionnaire, Viewing Motivation Scale, and Questionnaire of Excessive Binge-Watching were used in this study. The results of the path analysis show that anxiety-depressive syndrome and motivation to watch TV series are the significant factors in the manifestation of all symptoms of problematic binge-watching. Moreover, there is a significant relation between anxiety-depressive syndrome and motivation to watch TV series, which especially concerns escape motivation and motivation to deal with loneliness. Furthermore, motivation to deal with loneliness, escape motivation, and motivation to spend free time have mediating effect on the relationship between anxiety-depressive syndrome and problematic binge-watching. Results of this research show that there could be not only normative binge-watching behavior but also unhealthy and problematic form of this behavior.
... Eles podem ser classificados em: ao vivo, com transmissão em tempo real para os espectadores; e on-demand, em que o vídeo fica armazenado e os espectadores podem assistir ao conteúdo no momento em que julgarem melhor (Liu, Guo, & Liang, 2008;Shen, Luo, Zimmermann, & Vasilakos, 2011). Tal liberdade pode ter contribuído para que muitos considerassem o acesso aos VS tão importante quanto aos serviços de internet e de televisão paga (Lohmann & Frederiksen, 2018;Schweidel & Moe, 2016). Dessa forma, fica clara a importância de se realizar estudos sobre anúncios em VS. ...
The research was aimed at exploring whether there are gender differences in binge-watching patterns of urban-educated youth of Pakistan. Using the Uses and Gratification approach as the theoretical foundation of the research, the research investigated whether the motivations for binge-watching differed between males and females. The research also analyzed differences between genders on the negative impact of binge-watching. The methodology adopted for the research was the quantitative survey method. The purposive sample selected for the study comprised 300 male and female teenagers (13–19 years) who binge-watch online streamed content. The study’s findings revealed that Entertainment, Escape, and Excitement were the primary motivations of Pakistani teenagers to resort to binge-watching. However, it was found that Fear of Missing Out (FOMO) and Social Interaction were more important for females, while Excitement was deemed an important motivation by the males. Findings revealed that Sleep Disorder and Obesity were reported to be more of an issue than Depression and Productivity Issues. Furthermore, male binge-watchers reported a reduction in their Productivity, while female binge-watchers reported a disturbance in their sleeping patterns.
This paper explored the effects of binge-watching of Netflix on students at the Department of Theatre and Film Studies, University of Cape Coast, Ghana. It adopted the qualitative approach employing the phenomenology method. The selection of participants was done using purposive and snowball sampling. Recurring themes from data collection of semi-structured interviews with students were analysed. Findings indicated that most students gained some knowledge and others had sleeping disorders from binge-watching of Netflix. Also, other findings showed that students experienced some kind of academic disruptions and user self-satisfaction. It was obvious that some students enjoyed the picture quality and aesthetics of the visual elements. Further, others ended up draining their pockets by buying more data to binge-watch. It was concluded that controlling binge-watching of Netflix by individuals may be an alternative to prevent some consequences and addictions.
The new modes of television consumption point to the interest of binge-watching as the object of study. This paper builds an intensity index that classifies users into “irregular”, “regular” or “dedicated”. Methodologically, an inter-method sequence is applied, combining descriptive and multivariate statistical analyses, as well as discussion groups from which cleavages or discursive positions derive. The results of the research indicate that most of the University population are binge-watchers so the terms have changed and a new scale is necessary for identifying the level of engagement with binge-watching behaviour in the current. Almost 30% of the university population under study corresponds to the typical-ideal category of “dedicated” and 33% with the “regular”. The growth rate of the phenomenon is exponential between 2016-2019. The triggering motivations for binge-watching are primarily hedonic; its effects affect our moods especially in “dedicated” users. Two different types of viewing are clearly identified. The first is committed or prioritized viewing (with a high attention level, high dependence and sympathy with regards to the story and characters), and secondary or complimentary viewing. The study concludes that, in a pre-pandemic context of over-audiovisual fiction content (fictoxication), the ability to select and self-assess the media diet acquires the fundamental skill status in the socio-educational framework of the younger ones.
Temel ekonomik göstergelerin iktisadi faaliyetler üzerindeki etkisi, kuşkusuz medya endüstrisinde de söz konusudur. Mikro ve makro düzeyde ortaya çıkan bu etkiler, medya ekonomisi bağlamında medya birimlerini ve ekonomik göstergeleri bir araya getirmekte ve bugün, tüm dünyada insanların fikir ve düşünceleri üzerinde etkili olan, insanları eğlendiren ve bilgilendiren medyanın ekonomik tahlilini mümkün hâle
getirmektedir. Böylece alışılagelmiş ekonomi yazımı ile iletişimin önemli bir ögesi olan medya, ortak bir paydada buluşturulmaktadır.
Medya mecralarının üretmiş oldukları içeriklere ulaşmanın neredeyse ücretsiz olduğu günümüzde; reklam harcamaları, medyaları sübvanse etmekte ve medyalara finansal anlamda “can suyu” olmaktadır. İletişim ve dağıtım teknolojilerindeki gelişmeler, yıllar içerisinde, medyaları değişime ve dönüşüme uğratmış ve hatta yeni birimlerin ortaya çıkmasını sağlamıştır. Medya mecralarının ve iletişim sektörünün yıllar
içindeki değişimine en yakından tanıklık etmiş reklam değer zinciri de bu değişim ve dönüşüm ilişkilerine ayak uydurmayı başarmıştır.
2014 yılı ile birlikte “Netflix etkisi” olarak adlandırılan isteğe bağlı video ve beraberindeki isteğe bağlı ses hizmetlerinin, dijital medya vasıtası ile dünya genelinde geniş kullanım alanına kavuşmasıyla birlikte; kitle yoğunlaşmasının ve tüketici talebinin yönlendiği yeni medya mecrası internet olmuştur. Etkileşim, interaktiflik, aktif izleme ve dinleme eylemleri, binge-watching, yapay zekâ algoritmalı tavsiye sistemi ve navigasyonel tercih özgürlüğü ile internet medyası, zaman ve mekân sınırlarını ortadan kaldırarak medya içeriklerinin tüketimini; kişisel tercihler özeline ve topluluktan ziyade kişisel bir eyleme dönüştürmüştür. Bu dönüşüm silsilesini, potansiyel müşterilere ulaşmak ve başarılı satın alımları gerçekleştirmek isteyen reklamverenler de takip etmiş ve nihayetinde reklam harcamalarında da dolaylı ve doğrudan değişim başlamış; medyaların sorumlu olduğu harcamalar, birimler arasında farklılaşmıştır.
Anahtar kelimeler: Medya Ekonomisi, Reklam, Reklam Harcamaları, Dijital Medya, İsteğe Bağlı Hizmetler, İsteğe Bağlı Video, İsteğe Bağlı Ses.
Ao longo da última década, os serviços de streaming têm se popularizado ao
redor do mundo, disputando a atenção do público. No contexto da pandemia
da covid-19, essas plataformas registraram um aumento expressivo tanto no
número de assinaturas quanto na quantidade de horas de consumo de conteúdo audiovisual. Embora cada localidade tenha adotado medidas distintas para lidar com a circulação do vírus, a quarentena, o lockdown e o distanciamento social tornaram-se rotineiros em diversas cidades. Com as opções de lazer limitadas, o consumo de ficção seriada no streaming consolidou-se como uma das principais formas de entretenimento e o binge-watching intensificou-se (CORDEIRO et al., 2021). Neste capítulo, abordamos a prática em seu contexto histórico, a partir de seu impacto na espectatorialidade e na
própria construção narrativa da ficção seriada, destacando os desafios metodológicos para lidar com essa forma de fruição do conteúdo televisivo.
The authors develop an attribute-based mixed membership (ABMM) model of consumers’ preference for stock-keeping-units in store assortments. The model represents the underlying “topics of interest” that drive shopping behaviors as probability distributions over product attributes. It overcomes several limitations of Latent Dirichlet Allocation topic models and is particularly useful for preference predictions in large and frequently changing store assortments. They apply the proposed model to investigate topics driving browsing and purchase activities in an online deal marketplace of fashion products and how preference structures evolve over time. They find commonalities and differences in the topics that drive the browsing and purchase stages of online shopping processes. In general, browsing covers a broader range of product attributes than purchases. Consumers tend to browse products of premium positioning and/or deep discounts in the deal marketplace, but their purchases tend to gravitate toward products of lower tiers of original prices and modest depths of discounts. The authors illustrate how insights from the proposed model can be utilized to profile consumers based on their price preferences and to improve personalized product recommendations. They show that the model’s performance is particularly strong in predicting preferences for new products that are not in the existing assortment.
Human activities tend to burst at specific times, followed by long dormant periods. This study analyzes detailed trading records, as well as the demographic profiles of 486,049 customers from a major securities company and shows that an entropy measure of non-Poisson trading patterns has advantages over the canonical recency, frequency, and monetary value framework in the financial services sector. The LASSO logistic regression, the information gain metric in gradient boosting decision trees, and the relative importance method in neural networks all lend support to the conclusion that the clumpiness measure of trade clustering plays a significant role in explaining customers’ future churning. Furthermore, it appears that recently developed statistical learning techniques reduce churn prediction errors to a greater extent. A metric-based parsimonious RFMC approach coupled with machine learning techniques can be effectively used to better gauge customer lifetime value.
Psychotherapy is a treatment in which people get to know, discover and change themselves by working on mental healing mechanisms. Psychotherapy is the child of the 20th century and has been constantly developing, renewing and enriching for nearly a century. In this study, psychology’s view of cinema within the framework of the psychotherapy process, how cinema/series can be a borderline acting out defense, and how cinema can be a mediator function in overcoming the existential crisis and anxiety in which postmodern people fall are discussed through a psychotherapy case. Our main focus in the study is the case of “Samyeli", who has schizoid defenses and a diagnosis of quiet borderline made by a clinical evaluation within the framework of psychodynamic theories (Masterson Therapy). The psychotherapy process of this person took about 2 years. In the treatment of Samyeli, theoretical and technical Masterson therapy tools were used. When the therapy process was over, it was understood that this case contained a multifactorial diversity that could not be evaluated only with the dynamics of early infancy and childhood experience. It was seen that the case shed light on the existential and socio-psychological problems of the people of the age and even having very deep and rich dynamics in cinema-psychology. For these reasons, the therapy process of this person will be explained with the dynamics of Masterson theory and cinema/series issues will mostly be discussed as acting out defense in the case report. On the other hand, issues such as the relationship between cinema and psychotherapy, the positive psychological, existential and clinical effect mechanisms of cinema; how deterministic theories based on object-relations and existential theories inspired by continental philosophy and based on the criticism of modernity can be combined within the framework of complementarity and holism in understanding people and their problems are focused indirectly within the study.
Existing research treats sales performance as a series of discrete, independent events rather than a series of sales attempts with intertemporal spillover across these attempts. This research examines whether there are systematic short-term trends (“momentum”) in sales performance. To do so, the authors use the clumpiness approach to examine the existence of sales momentum in a high-frequency call-level data set obtained from two call centers of a large European firm. They further investigate the effect of positive (negative) momentum, or the positive (negative) deviation from the long-term expected performance on subsequent sales performance. Exploiting the differences in the social environment of the call centers, the authors find that the social working environment mitigates the harmful effect of negative momentum and sustains positive momentum. Further, they demonstrate that calls made midday, early-week, and late-week boost performance by mitigating the adverse effects of negative momentum. The findings suggest that monitoring sales performance can help managers detect momentum and use timely interventions to enhance sales productivity. Managers can also leverage momentum by creating a more social working environment to optimize overall salesperson performance.
People’s viewing experience has changed dramatically in recent years, with the rise of new viewing behaviours such as binge-watching and binge-racing made possible by the new media era. This study looks at how binge-watching affects several aspects of life (physical and psychological), correlating it to depression and loneliness, to test whether it affects them psychologically in a helpful way or drags them down to worse situations. Between December 2020 and April 2021, 234 participants completed an online survey that included four credible scales: the Center for Epidemiologic Studies Depression Scale, the Watching TV Series Motives Questionnaire, the Binge-watching Engagement and Symptoms Questionnaire and the UCLA Loneliness Scale (Version 3). Reaching out that most viewers watch alone and plan before entering the binge cycle, but not all of them could succeed in perceiving the impact of binge-watching left on them after ending their binging. The findings revealed that binge-watching is more prevalent among younger age. Additionally, there was a partial positive association between binge-watching and depression and loneliness. Furthermore, some TV viewing motives were positively associated with depression and loneliness.
Dijital platformların yayın hayatına başlaması ile birlikte eğlence endüstrilerinde büyük yapısal değişiklikler gerçekleşmiş ve buna paralel olarak video anlatılarının tüketilme şekilleri de farklılaşmış, yeni izleme biçimleri ortaya çıkmıştır. Seri izleme bu köklü yapısal değişikliklerin bir sonucudur. Her ne kadar üzerinde uzlaşılmış bir tanımı olmasa da bir dizinin en az üç bölümünü tek oturuşta ve oldukça kısa bir sürede izleme biçimine seri izleme adı verilmektedir. Hatta Netflix 2013 gibi erken bir dönemde seri izlemeyi yeni normal olarak ilan etmiştir ve 2013 yılından günümüze dünyanın farklı coğrafyalarında seri izleme, birçok izleyicinin deneyimlediği bir izleme biçimi haline gelmeye başlamıştır. Özellikle Y ve Z kuşağına mensup izleyiciler seri izleme tercihleri ile dikkat çekmektedir. Ancak seri izlemeyi gerçekleştiren öznelerin bu tercihlerinin altında yatan gerekçeler ve seri izleme motivasyonları üzerine sınırlı sayıda araştırmaya sahip, bilgi boşluklarının olduğu bir alandır. Dolayısıyla bu çalışma bireylerin seri izleme tercihlerini keşfetmek amacıyla gerçekleştirilen Kullanımlar Doyumlar yaklaşımı üzerine temellendirilmiş nitel bir araştırmadır.
The aim of the study is to discuss differences in defining the phenomenon of binge watching, and evolution of this process, considering research perspectives and problems explored by the authors. The in-depth literature analysis of 125 academic publications for the years 2014–2021 revealed the definition most often applied in the studies. Evolution of the interpretation of the binge watching term is also offered, related to increase of knowledge of motives, modes, and effects of binging, and finally, a proprietary definition of the phenomenon was proposed.
New technologies increasingly enable consumers to track their behaviors over time, making them more aware of their “streaks” – behaviors performed consecutively three or more times – than ever before. Our research explores how these logged streaks affect consumers’ decisions to engage in the same behavior subsequently. In seven studies, we find that intact streaks highlighted via behavioral logs increase consumers’ subsequent engagement in that behavior, relative to when broken streaks are highlighted. Importantly, this effect is independent of actual past behavior, and depends solely on how that behavior is represented within the log. This is because consumers consider maintaining a logged streak to be a meaningful goal in and of itself. In line with this theory, the effect of intact (vs. broken) logged streaks is amplified when consumers attribute a break in the streak to themselves rather than to external factors, and attenuated when consumers can “repair” a broken streak. Our research provides actionable insights for companies seeking to benefit from highlighting consumers’ streaks in various consequential domains (e.g., fitness, learning) without incurring a cost (e.g., reduced engagement or abandonment) when those streaks are broken.
Binge-watching via video websites has become a popular viewing behavior. Managers of such sites have attempted to launch related business strategies but have thus far failed. Theoretical guidance on the causal mechanisms that drive binge-watching behavior and effective business strategies is very limited. This study aims to fill this gap by constructing a psychological reaction model to explain how binge-watching behavior motivates consumers to purchase subsequent episodes of a program. We employ psychological reactance theory to model the psychological reaction process when binge-watching is stopped by a payment requirement. Based on a survey and two experimental studies, we confirm the causal relationship between binge-watching and program purchase, which provides an alternative understanding of binge-watching that conflicts with a previous finding whereby binge-watching behavior reduces paid subscriptions. We also confirm the significant difference in response to a payment requirement between binge- and non-binge-watching, and verify the boundary condition that distinguishes binge- and non-binge-watching behavior.
This study empirically validates the performance of stochastic customer base models in noncontract settings where the time at which a customer becomes dormant is not observable. We collaborate with a nationwide financial services company in Korea and analyze the complete transaction data of 373,031 retail customers from 2015 to 2018. We implement the following four buy-'til-you-die (BTYD) models: a) the original Pareto/NBD model, b) the Pareto/GGG model, c) the BG/CNBD-k model, and d) the MBG/CNBD-k model. The four BTYD models perform well in classifying active customers, with an area under the receiver operating characteristic curve of 0.82 ∼ 0.86 for each of the one-month, two-month, …, and twelve-month forecasting horizons. The results demonstrate that the BTYD framework can be used for customer base analysis as an instant heuristic approach that can complement existing customer relationship management tools.
Over-the-top video streaming (OTT) platforms, by their consummate artistry, are changing how people watch television. No past research has investigated the relationship between OTT streaming platforms' different uses and gratifications (U&G), subscription, and continuation intentions. Using the multi-method approach commonly used in uses and gratification research, i.e., semi-structured interviews and surveys, this study identified eight U&Gs for OTT use: convenient navigability, binge watching, entertainment, relaxation, social interaction, companionship, voyeurism, and information seeking. A comprehensive research model was developed based on the U& G theory and tested using Structural Equation Modelling (SEM) on cross-sectional data from 576 OTT users of different ages and gender from India. The result indicated that convenient navigability, binge watching, and relaxation U&G predict OTT subscription intentions, whereas convenient navigability, binge watching, and entertainment U&G predicts its continuation intentions
La irrupción de Netflix como productora de ficción televisiva cumplía cinco años en 2018. Un primer lustro marcado por la abundancia de acercamientos por parte de los estudiosos y por la asunción de que el famoso algoritmo que maneja la empresa, así como la minuciosa labor de etiquetar las series a través de categorías conceptuales con el fin de estar en mejor posición para juzgar lo que quiere su público, han llevado a una producción uniforme. En otras palabras, que la cultura del algoritmo deviene en productos muy similares que van repitiéndose una y otra vez para satisfacer al suscriptor. Tras dos años analizando los dramas producidos por Netflix bajo la etiqueta ‘Netflix Originals’ esa homogeneidad no se advierte en las formas de escribir y las estructuras manejadas. Por el contrario, lo que sí sorprende es que los guiones de la productora se asemejan más a los de una cadena en abierto que a los de una plataforma de pago.
La representación de la mujer en las narrativas de ficción ha evolucionado desde la primera ola del Feminismo. Dado que las ficciones no han roto todavía con los estereotipos de género, el presente trabajo plantea un análisis de los tres personajes femeninos de la serie de Netflix Bridgerton (Shondaland, 2020), a través de una metodología cualitativa que aplica la tabla de análisis de personajes femeninos propuesta por Mar Chicharro (2018, p. 95). Esta herramienta se basa en variables clave en la construcción de personajes desde el punto de vista narrativo, pero además incluye cuestiones descriptivas que ayudan a abordar su evolución, como es el arco de transformación. El objetivo es constatar el cambio del criterio representacional de la mujer en la ficción audiovisual, que pasa de objeto de deseo masculino a sujeto activo orientado a satisfacer la demanda del público femenino al que va dirigida. Finalmente se presentan los resultados, entre los que destacan la evolución del personaje principal, desde la figura de princesa de cuento de hadas a heroína de la acción, así como la multirepresentación de la figura femenina a través de tres generaciones, estrategia empleada con el objetivo de cubrir el conjunto de la audiencia femenina.
Streaming video (SV), such as YouTube, is a new media widely used nowadays. Nevertheless, there is a lack of knowledge about advertising in SV. In view of this, through a search in the rich depository of the Scopus database, this article presents the first integrative literature review about advertising in SV. Searching every article and conference paper related to the topic published until May 04, 2020, 59 studies were found and classified into two main topics: marketing studies (35), mostly focused on evaluating or exploring advertising in SV, and computational studies (24), focusing on the development of systems for the insertion of ads into SV. All knowledge present in these studies was summarized so that readers (both scholars and practitioners) could have easy access to the main contributions and information present in each study. Moreover, future research directions in six main themes are presented through a research agenda.
Binge-watching (BW) behavior has emerged rapidly in recent years. However, a comprehensive understanding of how BW is influenced and how it has changed is lacking. This study uses the valence framework to hypothesize the effects of positive valences (advantages) and negative valences (drawbacks) on consumers' tendency of BW through the mediating effects of consumer attitudes toward BW and tests the role played by consumers' self-control in the association between consumer attitudes toward BW and the tendency of BW. The results from the survey data analysis (N = 454) identify three negative valences (depression, loneliness, and social problems) and four positive valences (enjoyment, passing time, stress relief, and social interaction) that influence consumer attitudes toward BW. In addition, we confirm a U-shaped relationship between consumers' attitudes toward BW and the tendency of BW and find that consumers’ self-control has a moderating effect on this U-shaped association. Theoretically, we extend the valence theory into the study of BW behavior and investigate the specific positive and negative valences in this area. Practically, our findings could help broadcasters design strategies to promote BW.
Binge-watching or marathon watching is a new form of watching TV series/documentaries that has become widespread on a global scale as of 2013. With the developments in media and communication technologies, more and more viewers are watching more than one episode of a series through digital platforms more frequently by sparing longer periods of time. This situation creates some effects on the viewers. The purpose of this research was to identify the viewers' motivations behind binge-watching decisions and the effects of binge-watching on the viewers. For this purpose, data were collected using an in-depth interview method, one of the qualitative data collection methods, and analyzed with descriptive analysis method. As a result of the research, it was determined that the viewers' motivations for binge-watching were divided into two; individual and environmental factors. It was concluded that binge-watching caused some positive and negative feelings on the participants, that it oriented the participants towards individuality and isolation, and that this situation had some effects on family, social relations, work, and academic achievement.
As firms collect greater amounts of data about their customers from an ever broader set of " touchpoints, " a new set of methodological challenges arises. Companies often collect data from these various platforms at differing levels of aggregation, and it is not clear how to merge these data sources to draw meaningful inferences about customer-level behavior patterns. In this article, the authors provide a method that firms can use, based on readily available data, to gauge and monitor multiplatform media usage. The key innovation in the method is a Bayesian data-fusion approach that enables researchers to combine individual-level usage data (readily available for most digital platforms) with aggregated data on usage over time (typically available for traditional platforms). This method enables the authors to disentangle the intraday correlations between platforms (i.e., the usage of one platform vs. another on a given day) from longer-term correlations across users (i.e., heavy/light usage of multiple platforms over time). The authors conclude with a discussion of how this method can be used in a variety of marketing contexts for which data have become readily available, such as gauging the interplay between online and brick-and-mortar purchasing behavior.
Addiction creates an intertemporal link between a consumer’s past and present decisions, altering their responsiveness to price changes relative to nonaddictive products. We construct a dynamic model of rational addiction and endogenous consumption to investigate how consumers respond to policy interventions that aim to reduce purchases of cigarettes. We find that, on average, the category elasticity is about 35% higher when the model correctly accounts for addiction. However, some policies spur substitution from more expensive single packs to less expensive cartons of cigarettes, resulting in higher overall consumption for some consumers.
We discuss consumer engagement with a website, provide a systematic approach to examining the types of engagement produced by specific experiences, and show that engagement with the media context increases advertising effectiveness. Based on experiments using measurement scales involving eight different online experiences, we advance two types of engagement with online media — Personal and Social-Interactive Engagement. Our results show that both types are positively associated with advertising effectiveness. Moreover, Social-Interactive Engagement, which is more uniquely characteristic of the web as a medium, is shown to affect advertising after controlling for Personal Engagement. Our results offer online companies and advertisers new metrics and advertising strategies.
This article builds on job characteristics and optimal flow theory to describe the experience of individuals using computers in the workplace. A model was developed and tested with linear structural relationship modeling (LISREL) with data from 149 professionals employed in a variety of organizations. Flow, which is characterized by intense concentration and enjoyment, was found to be significantly linked with exploratory use behavior, which in turn was linked to extent of computer use. Flow was itself determined by the individual's sense of being in control and the level of challenge perceived in using computers. Perceived control was more important for individuals with high task-scope jobs, that is, jobs with high variety, identity, autonomy, and feedback. Challenge played a greater role for low task-scope individuals. Practical and theoretical implications of the model are discussed, and suggestions for further research are offered.
Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit organization founded in 1995 to build trusted digital archives for scholarship. We work with the scholarly community to preserve their work and the materials they rely upon, and to build a common research platform that promotes the discovery and use of these resources. For more information about JSTOR, please contact support@jstor.org. Individual viewing decisions have a direct impact on the media planning of television advertisers and, consequently, on the revenues of the major television networks. This paper represents an attempt to better understand these decisions. We use Nielsen people meter data to build a perceptual space for programs. That space is then used to develop models explaining viewers' decision to watch television and their choice of programming. The program-choice model is a clusterwise logit model which searches for segments with similar viewing preferences. A segment-level logit model is then used to model the on-off decision. These models can be used by advertisers and advertising agencies to understand the viewing audience better, and thus to help guide their advertising media placement decisions. The models can also help television networks design programs and program schedules that are more attractive to viewers (and thus advertisers).
The purpose of this study was to assess commonalities in binge eating and other problem behavior patterns in male and female college students, and in a group of women diagnosed as bulimic. Both males and females in the college student group reported a substantial frequency of eating an excessive amount of food in a relatively short period of time. A family history of substance abuse was significantly related to reported binge behavior for college females, but not for college males. Marked similarities were found among the college and clinical group women in the emotional antecedents and consequents of the eating binge, and in the foods consumed. The males reported a significantly greater proportion of positive affect after a binge episode. A general pattern of impulse-control problems was reported by a significant number of the clinically identified bulimic group.
Service churn and retention rates remain central as constructs in marketing activities, such as valuation of service subscribers and resource allocation. Although extant approaches have been proposed to relate service churn to external factors, such as reported satisfaction, marketing-mix activities, and so on, managers often face situations in which the only information available is the duration for which subscribers have had service. In such cases, can they forecast service churn and understand the contributing factors, which may allow for subsequent intervention? The authors propose a framework to examine factors that may underlie service retention in a contractual setting. Specifically, they use a model of retention that accounts for (1) duration dependence, (2) promotional effects, (3) subscriber heterogeneity, (4) cross-cohort effects, and (5) calendar-time effects (e.g., seasonality). Then, they apply the framework to subscription databases of seven services offered by a telecommunications provider, mirroring the format commonly used to forecast future service churn (and to make managerial decisions). Across all seven services, the inclusion of promotional effects always improves the forecast accuracy of retention behavior, whereas including cross-cohort effects does not significantly improve it. In five of the services, customer heterogeneity, calendar-time effects, and duration dependence also contribute to improved forecasts. The authors use these results to understand how the expected value of a subscription differs across model specifications. They find considerable variation across model specifications, indicating that model misspecification can affect resource allocation decisions and other marketing efforts that are important to a firm., The Wharton School, University of Pennsylvania. The authors express their appreciation to the anonymous firm that gra-ciously provided the data used herein.
A model for the prediction and explanation of individual television viewing choice is presented, incorporating considerations of utility, audience flow, and audience segmentation. The proposed model provides a quantifiably explicit theoretical explanation of television viewing choice, and its validation on large-sample network viewing data provides a baseline degree of accuracy against which the performance of future television viewing models may be compared. Of direct relevance to advertising agencies and the television networks is the suitability of the model for estimating the comparative impact of alternative programs on the audience size and composition of competing programs in the immediate and subsequent time slots.
We explore how Internet browsing behavior varies between mobile phones and personal computers. Smaller screen sizes on mobile phones increase the cost to the user of browsing for information. In addition, a wider range of offline locations for mobile Internet usage suggests that local activities are particularly important. Using data on user behavior at a (Twitter-like) microblogging service, we exploit exogenous variation in the ranking mechanism of posts to identify the ranking effects. We show that (1) ranking effects are higher on mobile phones suggesting higher search costs: links that appear at the top of the screen are especially likely to be clicked on mobile phones and (2) the benefit of browsing for geographically close matches is higher on mobile phones: stores located in close proximity to a user's home are much more likely to be clicked on mobile phones. Thus, the mobile Internet is somewhat less "Internet-like": search costs are higher and distance matters more. We speculate on how these changes may affect the future direction of Internet commerce.
This paper examines search across competing e-commerce sites. By analyzing panel data from over 10,000 Internet households and three commodity-like products (books, compact discs (CDs), and air travel services), we show that the amount of online search is actually quite limited. On average, households visit only 1.2 book sites, 1.3 CD sites, and 1.8 travel sites during a typical active month in each category. Using probabilistic models, we characterize search behavior at the individual level in terms of (1) depth of search, (2) dynamics of search, and (3) activity of search.
We model an individual's tendency to search as a logarithmic process, finding that shoppers search across very few sites in a given shopping month. We extend the logarithmic model of search to allow for time-varying dynamics that may cause the consumer to evolve and, perhaps, learn to search over time. We find that for two of the three product categories studied, search propensity does not change from month to month. However, in the third product category we find mild evidence of time-varying dynamics, where search decreases over time from already low levels. Finally, we model the level of a household's shopping activity and integrate it into our model of search. The results suggest that more-active online shoppers tend also to search across more sites. This consumer characteristic largely drives the dynamics of search that can easily be mistaken as increases from experience at the individual level.
Multiservice providers, such as telecommunication and financial service companies, can benefit from understanding how customers' service portfolios evolve over the course of their relationships. This can provide guidance for managerial issues such as customer valuation and predicting customers' future behavior, whether it is acquiring additional services, selectively dropping current services, or ending the relationship entirely. In this research, we develop a dynamic hidden Markov model to identify latent states that govern customers' affinity for the available services through which customers evolve. In addition, we incorporate and demonstrate the importance of separating two other sources of dynamics: portfolio inertia and service stickiness. We then examine the relationship between state membership and managerially relevant metrics, including customers' propensities for acquiring additional services or terminating the relationship, and customer lifetime value. Through a series of illustrative vignettes, we show that customers who have discarded a particular service may have an increased risk of canceling all services in the near future (as intuition would suggest) but also may be more prone to acquire more services, a provocative finding of interest to service providers. Our findings also emphasize the need to look beyond the previous period, as in much current research, and consider how customers have evolved over their entire relationship in order to predict their future actions.
This paper was accepted by Pradeep Chintagunta, marketing.
This research models the dynamics of customer relationships using typical transaction data. Our proposed model permits not only capturing the dynamics of customer relationships, but also incorporating the effect of the sequence of customer-firm encounters on the dynamics of customer relationships and the subsequent buying behavior. Our approach to modeling relationship dynamics is structurally different from existing approaches. Specifically, we construct and estimate a nonhomogeneous hidden Markov model to model the transitions among latent relationship states and effects on buying behavior. In the proposed model, the transitions between the states are a function of time-varying covariates such as customer-firm encounters that could have an enduring impact by shifting the customer to a different (unobservable) relationship state. The proposed model enables marketers to dynamically segment their customer base and to examine methods by which the firm can alter long-term buying behavior. We use a hierarchical Bayes approach to capture the unobserved heterogeneity across customers. We calibrate the model in the context of alumni relations using a longitudinal gift-giving data set. Using the proposed model, we probabilistically classify the alumni base into three relationship states and estimate the effect of alumni-university interactions, such as reunions, on the movement of alumni between these states. Additionally, we demonstrate improved prediction ability on a hold-out sample.
One reason consumers seek variety in product choices is to satisfy a need for stimulation. It is suggested that consumers may try to achieve an optimal level of stimulation by balancing the stimulation sought from product choice with the stimulation available from the choice context. Two laboratory experiments are conducted that show that causing changes in the choice context (thus increasing stimulation) decreases the amount of variety seeking subjects exhibit in product choices. Specifically, the results of the experiments suggest that consumers' needs for stimulation may be met by providing variety in a different product category or in other aspects of the choice context. A limiting condition to this finding is also examined. If positive affect is induced along with stimulation, then the reduction in variety-seeking behavior is mitigated. Copyright 1995 by the University of Chicago.
This study presents the evaluation of three dimensional traits of personality (Sensation Seeking, Anhedonia, Impulsivity) among 65 patients admitted in a psychiatric ward, with or without addictive behaviors. Our objective is to establish that these personality traits are commun to all addictive behaviors and to test the hypothesis that high scores on the three scales are linked to a greater probability of presenting with addictive behaviors. The two most frequent types of addiction were alcoholism and drug abuse. The subjects presenting with one or several addictive behaviors had higher average scores on the three scales. Our results printed in the same direction for the subjects having shown an addictive behavior in their past history. The risk to present with an addictive behavior increased with the total scores of these self-report questionnaires. There was a significant relationship between 3 sub-dimensions on the Sensation Seeking Scale and addictive behavior. Each time sub-scores of boredom susceptibility, disinhibition and thrill and adventure rise by one, the risk to present with an addictive behavior is multiplied by 1.4 for the first two and by 1.3 for the third one. Subjects with high scores on the anhedonia and impulsivity scales respectively show a risk multiplied by 1.6 and 3.3 of developing an addictive behavior. These results of this transverse study confirm the link between addiction behavior and these three personality traits.
We use the proportional hazard model (PHM) to study purchase-timing behavior of households in two product categories: laundry detergents and paper towels. The PHM decomposes a household's instantaneous probability of buying the product at a point of time into two components: the baseline hazard that captures the household's intrinsic purchase pattern over time and the covariate function that captures the effects of marketing variables on the household's purchase timing decision. We compare the continuous-time and discrete-time PHMs, where the latter explicitly accounts for households' shopping trips that do not involve purchase of the product. We find that the discrete-time PHM empirically outperforms the continuous-time PHM in terms of explaining the observed purchase outcomes. We compare five different parametric specifications of the baseline hazard, and find that the three-parameter expo-power specification outperforms the exponential, Erlang-2, Weibull, and log-logistic specifications. We use a cause specific, competing-risks PHM to distinguish between two types of purchase events that differ in terms of whether or not they were preceded by a shopping trip that involved purchase of the product. Such a cause-specific, competing-risks PHM is shown to outperform the traditional discrete-time PHM. We then estimate a nonparametric version of the PHM and find that it does not offer any additional insights compared to the parsimonious parametric PHM. Finally, we accommodate unobserved heterogeneity across households by allowing all of the parameters of the PHM to follow a discrete distribution across households whose locations and supports are nonparametrically estimated from the data. We find evidence for substantial unobserved heterogeneity in the data, both in the parameters of marketing variables and in the baseline hazards. This study will be a useful reference to researchers hoping to use the PHM to study event times.
This article applies different approaches to distinguish state dependence from unobserved heterogeneity and serial correlation and, hence, test for state dependence in consumer brand choices. First, we apply a simple method proposed by Chamberlain, which involves lagged exogenous variables only. Second, we also estimate a lagged-dependent-variable specification proposed by Wooldridge. Third, we use the estimation approach suggested by Wooldridge to estimate a model with both lagged dependent and exogenous variables to distinguish between the two different sources of choice dynamics, state dependence and lagged effects of the exogenous variables. Our analysis reveals that the best approach is to use models with both lagged dependent and exogenous variables. Our findings include strong evidence for state dependence in five out of the six product categories studied in this article.
In frequently-purchased-consumer-goods markets, consumer brand choices exhibit substantial persistence across purchase occasions. In this article, the author estimates a choice model that admits of both heterogeneity in preferences and true state dependence as sources of this persistence, using Nielsen scanner data on ketchup. He finds evidence for true state dependence in the choice process, even after controlling for a rich heterogeneity structure. Simulation of the model indicates that the long-term effect of a promotion-induced purchase on future purchase probabilities is positive but small.
Behavioral researchers use analysis of variance (ANOVA) tests of differences between treatment means or chi-square tests of differences between proportions to provide support for empirical hypotheses about consumer behavior. These tests are typically conducted on data from "between-subjects" experiments in which participants were randomly assigned to conditions. We show that, despite using internally valid experimental designs such as this, aggregation biases can arise in which the theoretically critical pattern holds in the aggregate even though it holds for no (or few) individuals. First, we show that crossover interactions -- often taken as strong evidence of moderating variables -- can arise from the aggregation of two or more segments that that do not exhibit such interactions when considered separately. Second, we show that certain context effects that have been reported for choice problems can result from the aggregation of two (or more) segments that do not exhibit these effect...
Advertising revenues have become a critical element in the business plans of most commercial Web sites. Despite extensive research on advertising in traditional media, managers and researchers face considerable uncertainty about its role in the online environment. The benefits offered by the medium notwithstanding, the lack of models to measure and predict advertising performance is a major deterrent to acceptance of the Web by mainstream advertisers. Presently, existing media models based on aggregate vehicle and advertising exposure are being adapted which underutilize the unique characteristics of the medium. What is required are methods that measure how consumers interact with advertising stimuli in ad-supported Web sites, going beyond mere counts of individual "eyeballs" attending to media. Given the enormous potential of this dynamic medium, academic investigation is sorely needed before cost implications and skepticism endanger the ability of the medium to generate and maintain ...
This paper addresses the role of marketing in hypermedia computer-mediated environments (CMEs). Our approach considers hypermedia CMEs to be large-scale (i.e. national or global) networked environments, of which the World Wide Web on the Internet is the first and current global implementation. We introduce marketers to this revolutionary new medium, propose a structural model of consumer behavior in a CME that incorporates the notion of flow, and examine the set of consequent testable research propositions and marketing implications that follow from the model. Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations 1) Introduction Firms communicate with their customers through various media. Traditionally, these media follow a passive one-to-many communication model whereby a firm reaches many current and potential customers, segmented or not, through marketing efforts that allow only limited forms of feedback on the part of the customer. For several years no...
Service churn and retention rates remain central as constructs in marketing activities, such as valuation of service subscribers and resource allocation. Although extant approaches have been proposed to relate service churn to external factors, such as reported satisfaction, marketing-mix activities, and so on, managers often face situations in which the only information available is the duration for which subscribers have had service. In such cases, can they forecast service churn and understand the contributing factors, which may allow for subsequent intervention? The authors propose a framework to examine factors that may underlie service retention in a contractual setting. Specifically, they use a model of retention that accounts for (1) duration dependence, (2) promotional effects, (3) subscriber heterogeneity, (4) cross-cohort effects, and (5) calendar-time effects (e.g., seasonality). Then, they apply the framework to subscription databases of seven services offered by a telecommunications provider, mirroring the format commonly used to forecast future service churn (and to make managerial decisions). Across all seven services, the inclusion of promotional effects always improves the forecast accuracy of retention behavior, whereas including cross-cohort effects does not significantly improve it. In five of the services, customer heterogeneity, calendar-time effects, and duration dependence also contribute to improved forecasts. The authors use these results to understand how the expected value of a subscription differs across model specifications. They find considerable variation across model specifications, indicating that model misspecification can affect resource allocation decisions and other marketing efforts that are important to a firm.
The authors develop an approach to market segmentation based on consumer response to marketing variables in both brand choice and category purchase incidence. The approach reveals segmentation as well as the nature of choice and incidence response for each segment. Brand choice and purchase incidence decisions are modeled at the segment level with the disaggregate multinomial logit and nested logit models; segment sizes are estimated simultaneously with the choice and incidence probabilities. Households are assigned to segments by using their posterior probabilities of segment membership based on their purchase histories. The procedure thereby permits an analysis of the demographic, purchase behavior, and brand preference characteristics of each response segment. The authors illustrate their approach with scanner panel data on the liquid laundry detergent category and find segmentation in price and promotion sensitivity for both brand choice and category purchase incidence. The results suggest that many households that switch brands on the basis of price and promotion do not also accelerate their category purchases and that households that accelerate purchases do not necessarily switch brands.
The authors address the role of marketing in hypermedia computer-mediated environments (CMEs). Their approach considers hypermedia CMEs to be large-scale (i.e., national or global) networked environments, of which the World Wide Web on the Internet is the first and current global implementation. They introduce marketers to this revolutionary new medium, propose a structural model of consumer navigation behavior in a CME that incorporates the notion of flow, and examine a series of research issues and marketing implications that follow from the model.
Patterns of television audience duplication (overlap of audiences between media vehicles) in the United States are found to be more complex than those in the United Kingdom. A new model of duplication is developed and shown to be better than previous estimates of the Viewing Law in describing television audience duplication in the U.S.
We explore how Internet browsing behavior varies between mobile phones and personal computers. Smaller screen sizes on mobile phones increase the cost to the user of browsing for information. In addition, a wider range of offline locations for mobile Internet usage suggests that local activities are particularly important. Using data on user behavior at a (Twitter-like) microblogging service, we exploit exogenous variation in the ranking mechanism of posts to identify the ranking effects. We show that (1) ranking effects are higher on mobile phones suggesting higher search costs: links that appear at the top of the screen are especially likely to be clicked on mobile phones and (2) the benefit of browsing for geographically close matches is higher on mobile phones: stores located in close proximity to a user's home are much more likely to be clicked on mobile phones. Thus, the mobile Internet is somewhat less “Internet-like”: search costs are higher and distance matters more. We speculate on how these changes may affect the future direction of Internet commerce.
Researchers and practitioners devote substantial effort to targeting banner advertisements to consumers, but they focus less effort on how to communicate with consumers once targeted. Morphing enables a website to learn, automatically and near optimally, which banner advertisements to serve to consumers to maximize click-through rates, brand consideration, and purchase likelihood. Banners are matched to consumers based on posterior probabilities of latent segment membership, which are identified from consumers' clickstreams.
This paper describes the first large-sample random-assignment field test of banner morphing—more than 100,000 consumers viewed more than 450,000 banners on CNET.com. On relevant Web pages, CNET's click-through rates almost doubled relative to control banners. We supplement the CNET field test with an experiment on an automotive information-and-recommendation website. The automotive experiment replaces automated learning with a longitudinal design that implements morph-to-segment matching. Banners matched to cognitive styles, as well as the stage of the consumer's buying process and body-type preference, significantly increase click-through rates, brand consideration, and purchase likelihood relative to a control. The CNET field test and automotive experiment demonstrate that matching banners to cognitive-style segments is feasible and provides significant benefits above and beyond traditional targeting. Improved banner effectiveness has strategic implications for allocations of budgets among media.
This article proposes that binge eating is motivated by a desire to escape from self-awareness. Binge eaters suffer from high standards and expectations, especially an acute sensitivity to the difficult (perceived) demands of others. When they fall short of these standards, they develop an aversive pattern of high self-awareness, characterized by unflattering views of self and concern over how they are perceived by others. These aversive self-perceptions are accompanied by emotional distress, which often includes anxiety and depression. To escape from this unpleasant state, binge eaters attempt the cognitive response of narrowing attention to the immediate stimulus environment and avoiding broadly meaningful thought. This narrowing of attention disengages normal inhibitions against eating and fosters an uncritical acceptance of irrational beliefs and thoughts. The escape model is capable of integrating much of the available evidence about binge eating.
This study examines the effects of Internet display advertising using cookie-level data from a field experiment at a financial tools provider. The experiment randomized assignment of cookies to treatment (firm ads) and control conditions (charity ads), enabling the authors to handle different sources of selection bias, including targeting algorithms and browsing behavior. They analyze display ad effects for users at different stages of the company's purchase funnel (i.e., nonvisitor, visitor, authenticated user, and converted customer) and find that display advertising positively affects visitation to the firm's website for users in most stages of the purchase funnel, but not for those who previously visited the site without creating an account. Using a binary logit model, the authors calculate marginal effects and elasticities by funnel stage and analyze the potential value of reallocating display ad impressions across users at different stages. Expected visits increase almost 10% when display ad impressions are partially reallocated from nonvisitors and visitors to authenticated users. The authors also show that results from the controlled experiment data differ significantly from those computed using standard correlational approaches.
When managers and researchers encounter a data set, they typically ask two key questions: (1) Which model (from a candidate set) should I use? And (2) if I use a particular model, when is it going to likely work well for my business goal? This research addresses those two questions and provides a rule, i.e., a decision tree, for data analysts to portend the "winning model" before having to fit any of them for longitudinal incidence data. We characterize data sets based on managerially relevant (and easy-to-compute) summary statistics, and we use classification techniques from machine learning to provide a decision tree that recommends when to use which model. By doing the "legwork" of obtaining this decision tree for model selection, we provide a time-saving tool to analysts. We illustrate this method for a common marketing problem (i.e., forecasting repeat purchasing incidence for a cohort of new customers) and demonstrate the method's ability to discriminate among an integrated family of a hidden Markov model (HMM) and its constrained variants. We observe a strong ability for data set characteristics to guide the choice of the most appropriate model, and we observe that some model features (e.g., the "back-and-forth" migration between latent states) are more important to accommodate than are others (e.g., the inclusion of an "off" state with no activity). We also demonstrate the method's broad potential by providing a general "recipe" for researchers to replicate this kind of model classification task in other managerial contexts (outside of repeat purchasing incidence data and the HMM framework).
Patterns of television audience duplication (overlap of audiences between media vehicles) in the United States are found to be more complex than those in the United Kingdom. A new model of duplication is developed and shown to be better than previous estimates of the Viewing Law in describing television audience duplication in the U.S.
In recent years, growing attention has been placed on the increasing pattern of ‘clumpy data’ in many empirical areas such as financial market microstructure, criminology and seismology, and digital media consumption to name just a few; but a well-defined and careful measurement of clumpiness has remained somewhat elusive. The related ‘hot hand’ effect has long been a widespread belief in sports, and has triggered a branch of interesting research which could shed some light on this domain. However, since many concerns have been raised about the low power of the existing ‘hot hand’ significance tests, we propose a new class of clumpiness measures which are shown to have higher statistical power in extensive simulations under a wide variety of statistical models for repeated outcomes. Finally, an empirical study is provided by using a unique dataset obtained from Hulu.com, an increasingly popular video streaming provider. Our results provide evidence that the ‘clumpiness phenomena’ is widely prevalent in digital content consumption, which supports the lore of ‘bingeability’ of online content believed to exist today.
Recent research has empirically characterized the buyer—seller relationship as dynamically evolving from one discrete state to another. Conventional wisdom would suggest that a customer in a higher relationship state that has a higher transaction value would also have greater lifetime value to the firm. However, recent evidence suggests that higher relationship states can be ephemeral. Hence, the link between transaction value and lifetime value is not obvious. In this study, we seek to understand, within a specific empirical context, (i) the relationship between a customer's transaction value and that customer's lifetime value and (ii) the relationship between the lifetime value of a customer and the optimal level of marketing activity that needs to be directed at that customer. To this end, we develop a trivariate Tobit hidden Markov model that allows for (a) transitions among relationship states, (b) possible synergies between the various products that the supplier firm offers, (c) endogeneity in marketing activity, (d) heterogeneity in model parameters, and (e) the presence of the nopurchase option. Our results reinforce recent findings by Schweidel et al. [Schweidel, D. A., E. T. Bradlow, P. S. Fader. 2011. Portfolio dynamics for customers of a multiservice provider. Management Sci. 57(3) 471—486] that higher relationship states can be short-lived. Importantly for the supplier firm, a customer in the highest relationship state in a given period does not yield the highest lifetime value to the firm. Hence, the relationship between transaction value (i.e., relationship state) and lifetime value can be nonmonotonic. At the same time, we also find a nonmonotonic relationship between the optimal expenditures that should be directed at a customer and that customer's lifetime value; i.e., the optimal level of marketing contacts is not the highest for customers with the highest lifetime value. Furthermore, we find that the optimal marketing expenditures for myopic agents are 14%—33% lower than the corresponding values for forward-looking agents. Therefore, not accounting for the long-term effects of marketing contacts would lead to suboptimal marketing budgets. Moreover, a comparison with the current marketing expenditures suggests that the current practice is closer to the myopic policy than to the forward-looking one.
An accurate television viewing choice model is an important tool for television executives and advertisers. The authors present a new viewing choice model, which differs from the traditional Rust-Alpert model in three ways: (1) It introduces a new show characteristic - the demographic characteristics of a show's cast; (2) it allows the preferences over the traditional show categories to be a function of both observable and unobservable individual characteristics; and (3) it allows the cost of switching among the viewing alternatives to vary across show types and individual characteristics. Cross-validated predictive testing shows that this model fits the data better than the Rust-Alpert model does. Furthermore, the authors demonstrate that network executives can improve ratings by using this model. The authors predict that by following their scheduling strategies (in particular, by broadcasting comedies after 10:00 P.M.), ABC, CBS, and NBC could have increased their average ratings by 12.9%, 7.5%, and 6.7%, respectively, on selected evenings.
Abstract The authors develop and estimate a model,of online buying using clickstream data from a Web site that sells cars. The model,predicts online buying,by linking the purchase,decision to what,visitors do and to what,they are exposed,while at the site. Predicting Internet buying poses several modeling,challenges. These include: (1) online buying,probabilities are usually low which can lead to a lack of predictive and explanatory power from models, (2) it is difficult to effectively account for what Web users do, and to what they are exposed, while browsing a site, and (3) because online stores reach a diverse user population across many competitive environments, models of online buying must account for the corresponding user heterogeneity. To overcome these hurdles, the authors decompose the user’s purchase process into the completion,of sequential,Nominal,User Tasks (nuts) and account,for heterogeneity,across visitors at the county,level. Three major,user tasks required to complete,a purchase,are: (1) completion of product configuration, (2) input of complete personal information, and (3) order confirmation,with provision of credit card data. These tasks are managerially,meaningful,and correspond,to considerable,visitor loss. Using a sequence,of binary probits estimated,through Bayesian methods, the authors model the visitor’s decision of whether or not to complete each task for the first time, given that the visitor has completed the previous tasks at least once. The propensity for completing,one task is also allowed to affect the propensity for completing subsequent,tasks. Results indicate that visitors’ browsing,experiences,and navigational,behavior,are pre- dictive of task completion for all decision levels. The use of interactive decision aids, the
The authors develop an approach to market segmentation based on consumer response to marketing variables in both brand choice and category purchase inci- dence. The approach reveals segmentation as v/ell as the nature of choice and incidence response for each segment. Brand choice and purchase incidence decisions are modeled at the segment level v/ith the disaggregate multinomial logit and nested logit models; segment sizes are estimated simultaneously with the choice and inci- dence probabilities. Households are assigned to segments by using their posterior probabilities of segment membership based on their purchase histories. The pro- cedure thereby permits an analysis of the demographic, purchase behavior, and brand preference characteristics of each response segment. The authors illustrate their approach with scanner panel data on the liquid laundry detergent category and find segmentation in price and promotion sensitivity for both brand choice and category purchase incidence. The results suggest that many households that switch brands on the basis of price and promotion do not also accelerate their category purchases and that households that accelerate purchases do not necessarily switch
The numerous associations between eating disorders and drug addictions--craving, preoccupation, compulsive use/behavior despite adverse consequences, denial of problem, use of substance to relieve negative affect with guilt following use, comorbidity, genetic links, high recidivism especially when exposed to cues or triggers, overeating and weight gain during early recovery from drug addiction, common neurobiological pathways, modification of drug reward by eating or starvation--suggest that binge eating disorders represent a drug-free auto-addiction for a significant subset of the addiction prone. In some it is a trigger leading to a drug or alcohol relapse, and in others it is an apparent result of alcohol or drug abstinence when food becomes a new drug of choice. In any case, food is a powerful mood altering substance that is repetitively and destructively used or restricted in eating disorders just as drugs are in substance use disorders. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Stand-alone marketing models are well-suited to deal with different behavioral features such as variation in transaction frequency (customer heterogeneity with latent classes), recency and attrition (“buy ‘till you die” models), and more general changes in customer transaction rates (hidden Markov models, HMMs). We unite these modeling approaches in a integrative framework as special cases or “children” of the HMM. We then selectively constrain the general model to assess the impact of each component on model performance. Instead of selecting latent-state models primarily using likelihood-based criteria, we favor a multi-faceted empirical evaluation using summaries of posterior predictive distributions; thus focusing model checking on managerially relevant features of the data, such as reach, frequency, and “streakiness.”We apply our methods to daily viewing incidence data from Hulu.com, a leading U.S. online streaming video provider. We find that increasing model complexity can improve some aspects of model performance (as expected) but worsen others in non-obvious ways. For instance, only models allowing back-and-forth movements among latent states can capture streakiness (a pattern of growing importance given the increasing availability of digital media data); but as a trade-off, these models still perform worse than their simpler counterparts in both forecasting and capturing other audience measurement criteria. Finally, using machine-learning classification techniques, customers are grouped based on similar model fit and features of their past consumption patterns. This allows researchers and managers to portend the “winning model” prior to having to fit the models for all customers. We discuss the generality of the methods and findings for different mixes of patterns of customer behavior.
This article highlights a large-scale field experiment conducted at an informational Web site where the timing of pop-up promotions being offered was varied. The experiment examines the Web user's reaction to the promotion in terms of (a) a direct response to the promotion (i.e., clickthrough) and (b) any indirect response in terms of the user's Web-site-exit behavior. Factors such as delay in offering the pop-up promotion and the page on which the pop-up appears are identified as variables that can be manipulated to enhance the individual's response.The context, or the page on which the popup promotion is offered, also is examined. Overall, this article suggests that characteristics of pop-up promotions, beyond just the message of the promotion, can be utilized to improve the consumer response.
We examine three sets of established behavioral hypotheses about consumers’ in‐store behavior using field data on grocery store shopping paths and purchases. Our results provide field evidence for the following empirical regularities. First, as consumers spend more time in the store, they become more purposeful—they are less likely to spend time on exploration and more likely to shop/buy. Second, consistent with “licensing” behavior, after purchasing virtue categories, consumers are more likely to shop at locations that carry vice categories. Third, the presence of other shoppers attracts consumers toward a store zone but reduces consumers’ tendency to shop there.
Click-through rates are still the de facto measure of Internet advertising effectiveness. Unfortunately, click-through rates have plummeted. This decline prompts two critical questions: (1) Why do banner ads seem to be ineffective and (2) what can advertisers do to improve their effectiveness? To address these questions, we utilized an eye-tracking device to investigate online surfers' attention to online advertising. Then we conducted a large-scale survey of Internet users' recall, recognition, and awareness of banner advertising. Our research suggests that the reason why click-through rates are low is that surfers actually avoid looking at banner ads during their online activities. This implies that the larger part of a surfer's processing of banners will probably be done at the pre-attentive level. If such is the case, click-through rate is an ineffective measure of banner ad performance. Our research also shows that banner ads do have an impact on traditional memory-based measure of effectiveness. Thus, we claim that advertisers should rely more on traditional brand equity measures such as brand awareness and advertising recall. Using such measures, we show that repetition affects unaided advertising recall, brand recognition, and brand awareness and that a banner's message influences both aided advertising recall and brand recognition.
In this study, we develop a multivariate generalization of the negative binomial distribution (NBD). This new model has potential application to situations where separate NBDs are correlated, such as for page views across multiple websites. In turn, our page view model is used to predict the audience for Internet advertising campaigns. For very large Internet advertising schedules, a simple approximation to the multivariate model is also derived. In a test of nearly 3,000 Internet advertising schedules, the two new models are compared with some proprietary and nonproprietary models previously used for Internet advertising and are shown to be significantly more accurate.
In this paper we develop a general class of dynamic brand choice models, called Lightning Bolt (LB) models, which are consistent with the theory of random utility maximization of consumer choice behavior. The underlying random utility process is Markov, and the inter-temporal evolution of the (utility-maximizing) brand choice process is also Markov. The models permit parsimonious parameterizations of the random utility process in brand choices with the resulting switching probabilities being functionally related to explanatory variables. The model allows for structural state dependence (feedback), habit persistence (inertia), and unobserved heterogeneity. The theoretical development shows that several well known stochastic brand choice models can be deduced from random utility maximization theory.
From a managerial perspective, the usefulness of the proposed model stems from its ability to separate out the effects of habits, state dependence and heterogeneity. Strong state dependence effects imply incentives for inducing trial of a brand (e.g., product sampling). In contrast with state dependence, a strong habit persistence effect may be indicative of buyer behavior where inducement of trial of a different brand may not be sufficient to maintain a (sustained) defection of the consumer from the habitually purchased brand to the trial brand. Failure to distinguish between these two effects has important implications. For example, a model that only accounts for state dependence effects would, in the presence of only habit persistence, incorrectly attribute it to state dependence. Based on this the manager could decide to embark on an expensive sampling program that might prove ineffective due to the absence of state dependence. It is also important to distinguish between the effects of unobserved heterogeneity and state dependence. In the absence of true state dependence, failing to account for unobservable variations across households (such as differences in price sensitivities), results in the temporally persistent unobservable elements showing up as state dependence in the model. Hence, a manager may incorrectly opt for sampling as the appropriate marketing action, whereas, a couponing or price promotion strategy should have been preferred.
We estimate the model parameters using the AC Nielsen household scanner panel data set on catsup purchases. Further, we investigate empirical techniques for overcoming the “initial conditions” problem that affects many dynamic models of brand choice. Through simulation analysis using the estimated parameters, we show that the calculated profitability of a promotion must take into account the multi-period impact due to state dependence. Further, we demonstrate how ignoring heterogeneity can result in spurious state dependence, thereby making marketing tactics such as product sampling appear far more attractive than they actually are. Specifically, the model that accounts only for habit persistence and state dependence effects predicts a share increase of 2.4% points through sampling for one of the brands in the empirical analysis. Once the effects of unobserved heterogeneity are accounted for, however, this number drops precipitously to 0.3%. While even this low number might fulfill the objectives of the brand manager, it ensures that expectations are not eight times that number.
It is important to note that this paper is a first attempt at analyzing the three fundamental dimensions of dynamic brand choice behavior. Our formulation represents a “reduced form” approach as opposed to a “structural” approach. Other limitations of the model include our focus on time-invariant choice sets. Extensions of the model to situations where choice sets vary over time are possible, but are difficult. Another limitation is the dependence on multivariate extreme value distributions. An alternative would be to use multivariate normal distributions, i.e., a probit-like structure which has certain useful properties. A comparison of the two approaches would be useful. Empirical extensions of the model to allow for higher-order processes and nested logit type model structures could also be fruitful. Explicitly incorporating variety-seeking behavior in the model would further enrich the theoretical framework proposed in this paper.
Some statistical methods developed recently in the biometrics and econometrics literature show great promise for improving the analysis of duration times in marketing. They incorporate the right censoring that is prevalent in duration times data, and can be used to make a wide variety of useful predictions. Both of these features make these methods preferable to the regression, logit, and discriminant analyses that marketers have typically used in analyzing durations.
This paper is intended to fulfill three objectives. First, we demonstrate how decision situations that involve durations differ from other marketing phenomena. Second, we show how standard modeling approaches to handle duration times can break down because of the peculiarities inherent in durations. It has been suggested in recent marketing articles that an alternative to these conventional procedures, i.e., hazard rate models and proportional hazard regression, can more effectively handle duration type data. Third, to investigate whether these proposed benefits are in fact delivered for marketing durations data, we estimate and validate both conventional and hazard rate models for household interpurchase times of saltine crackers. Our findings indicate the superiority of proportional hazard regression methods vis-à-vis common procedures in terms of stability and face validity of the estimates and in predictive accuracy.
The past few years have seen increasing interest in taking the notion of customer lifetime value (CLV) and extending it to value a customer base (with subsequent links to corporate valuation). The application of standard textbook discussions of CLV sees us performing such calculations using a single aggregate retention rate. However, at the cohort level, retention rates typically increase over time. We suggest that these observed dynamics are due, in large part, to a sorting effect in a heterogeneous population. We show that failing to recognize these dynamics yields a downward-biased estimate of the residual value of the customer base. We also explore the implications of failing to account for retention dynamics when computing retention elasticities, and find that the frequently reported estimates underestimate the true effect of increases in underlying retention rates in a heterogeneous world.