The Cost of Free: The Effects of “Wait-for-Free” Pricing Schemes on the Monetization of Serialized Digital Content

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Choi, Angela; Rhee, Ki-Eun; Yoon, Chamna; Oh, Wonseok

Abstract: Leveraging a combination of analytical frameworks and empirical assessments, th ... Expand

Abstract: Leveraging a combination of analytical frameworks and empirical assessments, this study investigates the effects of wait-for-free (WFF) pricing schemes on the monetization of serialized, digital entertainment content, which has become increasingly pervasive on online platforms. WFF pricing is a strategy in which consumers are given the option to either wait a certain amount of time to acquire digital content at no cost or pay to consume it immediately. We evaluate the extent to which habit formation and presentbiased preferences driven by the consumption of addictive stock affect individual consumers' willingness to wait (or pay) for content, which, in turn, determines the efficacy of WFF pricing. We also examine the conditions under which consumers switch from waiting for free content to instantaneously purchasing content. Our findings indicate that WFF pricing increases the sales of serialized digital content, generating new demand from customers who would otherwise forgo participation in the market. In addition, the pricing design effectively generates sustained profits in the long run. We found that most consumers who initiate a purchase either upon initial market entry or upon switching continue to purchase as new episodes become available. Moreover, the results indicate that as a user accumulates free episodes of a specific series, given extended waiting periods, the likelihood of their conversion from a wait-for-free customer to an instant-purchase customer increases. In particular, WFF pricing effectively augments the willingness to pay of low-valuation consumers as habit formation builds up through time with the free consumption of serialized content. One free episode can elevate the likelihood of consumer purchase by up to 13%. However, as the number of free episodes consumed goes beyond a threshold, the likelihood of conversion decreases. We conclude with a discussion of managerial implications that can help content providers monetize their serialized digital content products. Collapse

Topics: price management consumer behavior advertising management digital good customer satisfaction

Methods: mathematical model robustness check econometric modeling proportional hazards model survival analysis

Theories: behavioral economics

What is Digital about Digital Innovation? An Ontological Discussion of Digitality

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Fitz, Lukas; Scheeg, Jochen

Abstract: Digital" is a popular adjective for concepts related to electronic, computerize ... Expand

Abstract: Digital" is a popular adjective for concepts related to electronic, computerized or networked processes in current research and practice. From an ontological-theoretical perspective, the prevalence of digital things triggers the question, how Digitality itself could be conceptualized. This article studies the ontology of Digitality and consequently discusses Digital Innovation (DI) from a new perspective. First, literature on Digitality is analyzed. Based on the findings, an ontological conceptual framework of Digitality (OCFD) is proposed. It describes four layers of Digitality: physical foundations, virtuality, digital culture and world, and digital metaphysics. From a human perspective, requirements to grasp and embody Digitality are highlighted, as well as the expansion of reality. Finally, Digitality is discussed as a paradigm of DI and exemplary digital phenomena are projected onto the OCFD. This paper contributes to DI research and practice through theory-building towards a better understanding of ontological characteristics and practical implications of Digitality in DI. Collapse

Topics: database system digital good digital business ebook knowledge representation

Methods: literature study theory development ontological modelling

Referral Intention vs. Continuous Referral Intention: Incentive Mechanism in Multi-tasking Social Referral Programs

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Li, Xu; Jiang, Qiqi; Wang, Kanliang

Abstract: Social referral reward programs (SRRPs) aim to incentivize existing customers t ... Expand

Abstract: Social referral reward programs (SRRPs) aim to incentivize existing customers to recommend a product or service to others. Based on the reward threshold, we classify social referrals into two categories: singletasking social referral (SSR) and multi-tasking social referral (MSR). Considering that MSR involves multiple responders, we explore how to design an effective reward mechanism in this new context. Our primary interests in outcomes include users' willingness to recommend and their continuous referral intentions. Drawing from fairness theory and loss aversion theory, we propose three reward models based on the keeping percentage of rewards obtained, i.e., keep-it-all (KIA), discounted keep-it-all (DKIA), and all-or-nothing (AON). We designed an experiment to test the hypotheses regarding the effects of reward types on referral intention and continuous intention. This study will provide important implications for research and practice in designing an effective reward mechanism in MSR. Collapse

Topics: marketing management ebook electronic commerce

Methods: experiment statistical hypothesis test qualitative interview descriptive statistic theory development

Theories: loss aversion fairness theory

A critical assessment of consumer reviews: A hybrid NLP-based methodology

2022 | Decision Support Systems | Citations: 0

Authors: Biswas, Baidyanath; Sengupta, Pooja; Kumar, Ajay; Delen, Dursun; Gupta, Shivam

Abstract: Online reviews are integral to consumer decision-making while purchasing product ... Expand

Abstract: Online reviews are integral to consumer decision-making while purchasing products on an e-commerce platform. Extant literature has conclusively established the effects of various review and reviewer related predictors to­ wards perceived helpfulness. However, background research is limited in addressing the following problem: how can readers interpret the topical summary of many helpful reviews that explain multiple themes and consecutively focus in-depth? To fill this gap, we drew upon Shannon’s Entropy Theory and Dual Process Theory to propose a set of predictors using NLP and text mining to examine helpfulness. We created four predictors - review depth, review divergence, semantic entropy and keyword relevance to build our primary empirical models. We also reported interesting findings from the interaction effects of the reviewer’s credibility, age of review, and review divergence. We also validated the robustness of our results across different product categories and higher thresholds of help­ fulness votes. Our study contributes to the electronic commerce literature with relevant managerial and theo­ retical implications through these findings. Collapse

Topics: online review electronic commerce computer virus protection information retrieval digital media

Methods: natural language processing robustness check term frequency–inverse document frequency topic model moderation analysis

Theories: dual-system theory chaos theory mathematical theory of communication elaboration likelihood model

From free to fee: Monetizing digital content through expected utility-based recommender systems

2022 | Information & Management | Citations: 0

Authors: Lee, Dongwon; Nam, Kihwan; Han, Ingoo; Cho, Kanghyun

Abstract: This study proposes a novel framework for designing business rule analytics to a ... Expand

Abstract: This study proposes a novel framework for designing business rule analytics to assist businesses offering digital content in effectively converting free-only users (FOUs) into paying customers. Based on the theory of expected utility, we expand upon traditional frequency-driven rule analytics by integrating three business-relevant factors (target size, conversion profit, and conversion likelihood) into the process of generating recommendations for FOUs in digital content markets. The framework was tested using two different types of empirical analysis. We conducted a field experiment collaborating with a nationwide e-book store to determine how FOUs responded to the recommendations generated under the proposed framework. Furthermore, we analyzed over 5 million transactions collected from the e-book seller and a mobile application provider to examine the impact of customer segmentation on the effectiveness of our approach. Our findings suggest that business analytics derived from the utility-based mechanisms can significantly enhance digital content providers’ business performance. Collapse

Topics: ebook digital good mobile application recommender system analytical information system

Methods: experiment archival research field experiment descriptive statistic Bayesian analysis

Preferences for digital versus printed textbooks: Existing and emerging challenges

2022 | International Conference on Information Systems | Citations: 0

Authors: Levkov, Nikola

Abstract: ... Expand

Abstract: Collapse

Topics: database system digital good ebook innovation management user attitude

Methods: literature sample structured literature research

Significance of Task Significance in Online Marketplaces for Work

2022 | HICSS | Citations: 0

Authors: Ren, Yuqing; Curley, Shawn

Abstract: Online marketplaces for work like Amazon Mechanical Turk facilitate the sourcing ... Expand

Abstract: Online marketplaces for work like Amazon Mechanical Turk facilitate the sourcing of low expertise tasks in a fast and cost effective way. In this study, we explore the impact of task significance on work quality by informing workers of the purpose of the task and who benefits from it. Results from a laboratory experiment and a field experiment showed that perceived task significance improved work quality, but only for participants who recalled the purpose statement. In contrast, increasing monetary payment by 50% had no impact on work quality. A majority of participants who received the purpose statement were not able to recall it. Further analysis showed worker attributes such as English ability and personality traits influenced the likelihood of recall whereas rich media format had no effects. Overall, our work highlights the promise of task significance as a way to motivate online workers and the challenge of promoting task significance online. Collapse

Topics: intrinsic motivation personality Wikipedia electronic market ebook

Methods: ANOVA parametric test survey experiment data transformation

Theories: big five model

Conceptual Foundations on Debiasing for Machine Learning-Based Software

2022 | International Conference on Information Systems | Citations: 0

Authors: Schmitt, Anuschka; Walser, Maximilian; Fahse, Tobias

Abstract: Machine learning (ML)-based software's deployment has raised serious concerns a ... Expand

Abstract: Machine learning (ML)-based software's deployment has raised serious concerns about its pervasive and harmful consequences for users, business, and society inflicted through bias. While approaches to address bias are increasingly recognized and developed, our understanding of debiasing remains nascent. Research has yet to provide a comprehensive coverage of this vast growing field, much of which is not embedded in theoretical understanding. Conceptualizing and structuring the nature, effect, and implementation of debiasing instruments could provide necessary guidance for practitioners investing in debiasing efforts. We develop a taxonomy that classifies debiasing instrument characteristics into seven key dimensions. We evaluate and refine our taxonomy through nine experts and apply our taxonomy to three actual debiasing instruments, drawing lessons for the design and choice of appropriate instruments. Bridging the gaps between our conceptual understanding of debiasing for ML-based software and its organizational implementation, we discuss contributions and future research. Collapse

Topics: systems development new product development decision making system development method organizational context

Methods: qualitative interview structured literature research computational algorithm machine learning literature sample

The Digital Undertow: How the Corollary Effects of Digital Transformation Affect Industry Standards

2022 | Information Systems Research | Citations: 3

Authors: Scott, Susan; Orlikowski, Wanda

Abstract: Scholarship on digital transformation has centered on how waves of digitalizatio ... Expand

Abstract: Scholarship on digital transformation has centered on how waves of digitalization have moved through industries, producing strategic changes within and across firms and enabling new forms of value creation. In this paper, we argue that different but no less important processes of digital transformation are generated by the undertow produced by these waves. This digital undertow, a corollary effect of waves of digitalization, profoundly influences how firms operate by transforming the industry standards that coordinate and regulate their core business activities. Using a genealogical approach, we draw on findings from a longitudinal field study in book publishing to theorize the tensions and processes that constitute the digital undertow. We explain that, when waves of digitalization transform firms’ core activities, they unwittingly affect how industry standards correspond with materializations of the phenomena they structure, thus influencing how standards perform in practice. A significant outcome of recent waves of digitalization in the book industry is the loss in correspondence between industry standards and novel digital materializations of the book. This is producing what we refer to as digital displacement, a process that is engendering an existential challenge to the capacity of standards to effectively coordinate and regulate industry operations in the digital age. Collapse

Topics: digital transformation digital innovation ebook unintended consequence value creation

Methods: qualitative interview theory development archival research field study business process modeling

Recommendations and Cross-selling: Pricing Strategies when Personalizing Firms Cross-sell

2021 | Journal of Management Information Systems | Citations: 0

Authors: Ghoshal, Abhijeet; Mookerjee, Vijay S.; Sarkar, Sumit

Abstract: Recommender systems enable firms to target customers with products and services ... Expand

Abstract: Recommender systems enable firms to target customers with products and services that better match their needs, as well as cross-sell products and services. Considering these factors in markets with monopoly and duopoly, we investigate (i) How do pricing strategies differ when firms cross-sell versus when they do not cross-sell, and (ii) How do these pricing strategies change when a firm improves its recommender system? We find that cross-selling can enable a monopolist to subsidize its price for the focal products, while maximizing its profit. In a duopoly, the price set by the firm with the inferior system (low-type firm) is always lower when the firms cross-sell than when the firms do not cross-sell; however, that does not necessarily hold for the high-type firm. When the high-type firm improves its recommender system, the low-type firm may decrease its price when firms cross-sell, which does not happen when firms do not cross-sell. Collapse

Topics: recommender system duopoly price management IS effectiveness usability

Methods: experiment literature study