Revenue Model Research Articles

Optimal revenue model for Q&A platforms: Paid or free viewership?

Optimal sizing and control of a grid-connected battery in a stacked revenue model including an energy community

Against the backdrop of the development of informationisation in Chinese society, traditional newspaper groups are facing profound changes brought about by media convergence. With the rapid development of mobile Internet and new media, the traditional advertising revenue model and the circulation of paper newspapers have declined sharply, forcing newspaper groups to accelerate digital transformation. Taking Henan Daily Newspaper Group as an example, this study, based on semi-structured interviews, provides an in-depth analysis of the three core challenges faced by traditional newspaper groups in the context of media convergence, namely, the loss of readers, the decline in advertising revenue and the plight of outdated organisational structure. The results of the study show that the traditional newspaper industry has greater difficulties in technological integration, especially in the construction of digital platforms, the application of content production tools and the shortage of technological talents. The rigidity of organisational structure and the lack of cross-departmental collaboration also severely constrain the efficiency of innovation and the pace of transformation. In addition, with the decline of traditional advertising revenues, newspaper groups have made slow progress in content payment, IP realisation and diversified revenue exploration. To address these challenges, the study proposes strategies to enhance the competitiveness of traditional newspaper groups through technological innovation, organisational structure optimisation and the establishment of diversified revenue models. In the future, newspaper groups need to accelerate the pace of technological innovation, implement more flexible organisational management models, and actively explore new revenue sources in order to maintain sustainable development in the new media environment.

This study explores the impact of gaming motivations on user satisfaction through the mediating factor of user addiction in online gaming. ‎Immersion, achievement, escapism, socialization, competition, cognition, and earning, seven motivational factors used as independent ‎factors and analyzed. These factors were used as a first order construct and were studied under a second order construct motivational factor ‎a second order construct. Data were collected using snowball sampling techniques from 272 online gamers, and mediation analysis was ‎performed to test the proposed model. The findings reveal that while motivational factors were directly influencing satisfaction, addiction ‎acts as a mediating mechanism that reinforces this impact. Through Rationality Addiction Theory, the outcomes suggest that players ‎integrate addictive engagement as part of their satisfaction-maximization. The research further highlights wider economic and policy ‎implications, specifically the role of motivational factors in industrial revenue models and the need for sensible gaming structures to balance ‎user satisfaction and societal well-being‎.

Purpose Although the broader consequences of interest rate liberalization (IRL) have been widely studied, few studies have systematically explored its impact on the income structure of commercial banks. This study aims to examine this gap by examining the effects of IRL on the income structure of 243 Chinese banks over 2005–2023. Design/methodology/approach Using panel data and fixed-effects regression models with robustness tests, heterogeneity analysis and mediation analysis. Findings The results confirm that IRL has materially increased the proportion of non-interest income in Chinese commercial banks. These effects are heterogeneous across bank types, with joint-stock and city commercial banks exhibiting the most pronounced responses. The results also demonstrate that net interest margin is a key mediator in this relationship, supporting the “margin compression–innovation compensation” hypothesis. Originality/value This study contributes to the existing literature by providing empirical evidence of structural shifts in bank revenue models and offers insights into the broader implications of IRL in the evolution of the Chinese banking sector.

ABSTRACT Purpose This study explores the reasons for the unrealised potential of digital agro-advisory services in developing countries by analysing the difficulties encountered by advisory service providers who are digitalising their services. Design/Methodology/Approach We used a multidimensional model of service innovation to examine the changes that occurred in the advisory system as it underwent digitalisation and the manner in which a Burkinabe farmer organisation and their partners coped with these transformations. This model includes six dimensions that can be transformed during the service innovation process: the service concept, interactions with users, the partner network, the revenue model, the organisational delivery system, and the technological delivery system. Findings This study shows that the farmer organisation did not anticipate the multiple transformations implied by the digitalisation process. This had detrimental effects for the farmer organisation, including the disruption of its day-to-day activities, difficulties in ensuring the economic viability of the new digital advisory service, and an evolution of the advisory approach towards top-down supervision. Practical Implications This article highlights six dynamic capabilities that are essential for advisory service providers to successfully manage the development of a digital farm advisory service. Theoretical Implications Using a holistic model of service innovation is instrumental in comprehending the failures encountered by organisations developing digital agro-advisory services. Originality/Value This article adopts a new perspective to understand the failures of digital advisory services: the capabilities of advisory providers to holistically manage the digitalisation of their service.

With the rapid development of the digital economy, the industrial utilization of digital copyrights, a core asset and production factor, has become a key driving force behind innovation and economic growth in the cultural content industry. This paper analyzes the key characteristics of the current industrial utilization of digital copyrights in China and focuses on presenting prospects for future collaboration between the Korean and Chinese digital copyright industries. This study compares and analyzes three leading companies in web novel copyright, music copyright, and social e-commerce: Yuewen Group, Tencent Music Entertainment Group, and ByteDance Group. This analysis focuses on four aspects: content, revenue model, technical support, and industry structure. Based on this analysis, the study explores the characteristics of China's digital copyright industry and proposes future collaboration strategies for the two industries.

In an increasingly competitive global market, where industries from consumer electronics to digital content face saturation and margin pressures, companies are compelled to adopt innovative strategies to increase market share and profitability. These measures—both profitability and market share—are important predictors of corporate competitiveness, which is reflected not only in strategic foresight of resource allocation but also in operational efficiency. Through strategic leverage and integrated market financial governance, Xiaomi and Bilibili—two industry disruptors in hardware manufacturing and digital content, respectively—have grown exponentially and provided replicable frameworks for enterprises operating in complicated ecosystems, according to this paper. Xiaomi's dominance in the EV sector is an example of ecosystem-driven diversification. Xiaomi took advantage of the current IoT user base (more than 700 million connected devices) by the SU7 sedan that was launched in 2024, which reduced the cost of customer acquisition by 40% in comparison to that of conventional automakers. Concurrently, its asset–light manufacturing model—partnering with the BAIC Group for production while retaining R&D control—lowered capital expenditure by 60%, boosting its operating margin to 18.7% in Q3 2024. Conversely, BiliBili demonstrates community-powered monetization. Transitioning from a niche anime platform to a PUGC (professional user-generated content) hub, the number of monthly active users (MAUs) increased from 150 million in 2020 to 368 million in 2024. By implementing a “dual-engine” revenue model—advertising (45% of 2023 revenue) + premium subscriptions (30%)—it achieved 22% year-on-year profit growth while maintaining a 78% user retention rate through gamified loyalty programs (e.g., “Coin System” for content rewards).

Bill C-18, Canada's Online News Act, has sparked significant debate. It mandates tech giants like Google and Meta to compensate Canadian news outlets for using their content, aiming to support the declining news industry. Proponents argue it will correct revenue imbalances caused by digital platforms, ensuring fair compensation for media. However, critics, including tech companies, claim it's based on flawed premises, asserting that the bill won't resolve the industry's issues and could lead to censorship and reduced news access. This essay argues that Bill C-18 is ineffective, failing to address the fundamental challenges of the Canadian news industry's outdated business model. It also contends that the bill disproportionately benefits large media corporations and could hinder innovation, further entrenching the dominance of a few major players in the industry. Ultimately, the essay suggests that a more effective approach would involve adapting to digital media's realities, moving away from traditional revenue models to ensure the industry's sustainability.

A key practical problem in the financial performance (FP) of metaverse organizations in the United Stats of America (USA) is the massive investment losses faced by leading firms like Meta Platforms. Meta’s Reality Labs, which drives its metaverse initiatives, reported a $17.7 billion operating loss in 2024 despite generating $2.1 billion in revenue. Since 2020, the division has accumulated over $50 billion in losses. These financial struggles highlight concerns regarding corporate governance in metaverse firms. Poor governance structures, lack of accountability in investment decisions, and uncertain revenue models are key factors that challenge sustainable FP. Stronger governance frameworks could help optimize spending, improve investor confidence, and drive profitability in this evolving sector. Therefore, the primary objective of this study is to investigate the influence of corporate governance elements like board size, board independence, number of board meetings, audit quality and audit committee on the FP of metaverse organizations in the USA. DataStream database and annual reports were used to extract data regarding board size, board independence, number of board meetings, audit quality and audit committee, FP and technological innovation. The current study employed a sample size of 40 metaverse companies in the USA from 2014 to 2023. Results of the study proved the positive contribution of corporate governance and technological innovation to the FP of metaverse companies in USA.

In late 2023, the Writers Guild of America (WGA) and the Screen Actors Guild-American Federation of Television and Radio Artists (SAG-AFTRA) simultaneously struck against the Alliance of Motion Picture and Television Producers (AMPTP), the first dual strike since the 1960s. While several factors drove these strikes, this study focuses on residuals, particularly for streaming services. Streaming platforms like Netflix undermine traditional revenue models and residual pay structures, driving new union requests. To understand this conflict, and what it means for entertainment labor, we conducted an inductive thematic analysis of relevant news coverage collected over thirty days during the overlapping strikes. While much coverage was favorable toward the strikes, reporting often emphasized comparative negotiations and above-the-line workers, overlooking structural inequities such as background actors’ exclusion from residuals. We argue this framing contributes to the marginalization of wage laborers in SAG-AFTRA, reinforcing existing disparities in labor representation within the industry.

The promotion of local renewable energy consumption and stable power gird (the latter is referred to as PG) operation have emerged as the primary objectives of power system reform. The integration of multiple microgrids with distinct characteristics through the utilization of shared energy storage (the following is referred to as SES) facilitates coordinated operation. This approach enables the balancing of energy across temporal and spatial domains, contributing to the overall reliability and security of the energy network. The proposed model outlines a methodology for the coordinated operation of multiple microgrids and SES, with a focus on asymmetric price negotiation. Initially, cost and revenue models for microgrids and SES power plants are established. Secondly, an asymmetric pricing method based on the magnitude of each entity’s energy contribution is proposed. A profit optimization model is also established. The model can be decomposed into two distinct subproblems: the maximization of overall profit and the negotiation of transaction prices. The model can be solved by employing the alternating direction method of multipliers (ADMM). Finally, a series of case studies were conducted for the purpose of validating the operation optimization model that was previously constructed. These studies demonstrate that the model enhances collective operational efficiency by 44.69%, with each entity’s efficiency increasing by at least 12%. At the same time, cooperative benefits are distributed fairly according to each entity’s energy contribution.

The Metaverse is attracting significant investment and promises to transform value creation and business competitiveness. While Small and Medium-Sized Enterprises (SMEs) are exploring its use to overcome resource limitations and enhance operations, its role in facilitating internationalization remains unclear. This study fills a research gap by investigating how the Metaverse can support SMEs in overcoming internationalization challenges through value creation, capture, and delivery. A Metaverse-based framework was developed and validated using a three-round Delphi approach with international business professionals and Metaverse specialists. This study confirmed that the Metaverse offers SMEs distinct opportunities to enhance value creation, capture, and delivery in the internationalization process. In value creation, it supports broader product offerings (e.g. digital twins), improved efficiency, and co-creation through superior knowledge management and deeper insights into consumer preferences. For value capture, the Metaverse enables access to new revenue models, demand forecasting through simulation, and better resource utilization, helping SMEs overcome regulatory and cultural barriers. In terms of value delivery, immersive interactions and real-time communication facilitate international collaboration, improve customer engagement, and extend global market reach. Overall, the Metaverse helps SMEs address internationalization challenges linked to firm size, resource constraints, and market complexity, ultimately strengthening their competitive advantage in international contexts.

This study addresses the critical challenge of advancing tax revenue forecasting models to effectively handle distinctive data gaps and inherent fluctuations in tax revenue data. These challenges are evident in Lampung Province, Indonesia, where limited temporal granularity and non-linear variability hinder accurate fiscal planning. Despite advancements in statistical, machine learning, and hybrid approaches, existing models often fall short in simultaneously managing these challenges. A hybrid model integrating random forest regressors for data interpolation and Long Short-Term Memory for capturing complex temporal patterns was proposed. The model was evaluated, achieving an R² of 0.86, root mean squared error (RMSE) of 9.65 billion, and mean absolute percentage error (MAPE) of 3.49%. Although the model has limitations in generalizing to unseen data, the results demonstrate that it outperforms existing forecasting models regarding accuracy and reliability. Integrating random forest regressors and long short-term memory delivers a tailored solution to the complexities of tax revenue forecasting, contributing to fiscal forecasting and setting a foundation for further exploration into hybrid approaches.

This article examines the revolutionary impact of artificial intelligence on television advertising monetization. It explores how AI technologies are creating new pathways for converting viewer engagement into direct purchases, thereby reshaping traditional advertising revenue models. The convergence of AI and television has fundamentally transformed the traditional awareness-based advertising paradigm into an interactive commerce ecosystem where entertainment, advertising, and e-commerce boundaries blur. By investigating the technical foundations, implementation models, economic impacts, and consumer behavior factors that drive this transformation, the article provides a comprehensive framework for understanding how AI-driven shoppable TV is creating value for stakeholders across the television ecosystem while simultaneously reshaping viewer experiences and expectations.

Economic diversification is a critical strategy for achieving sustainable development, particularly in resource-dependent economies that face vulnerabilities linked to volatile commodity prices and environmental degradation. By broadening the economic base—through investment in sectors such as technology, renewable energy, agriculture, and services—countries can reduce their reliance on singular industries, thereby fostering resilience against market fluctuations. This research investigates the interplay between economic diversification strategies and sustainable development in Oman, focusing on the objectives outlined in Oman Vision 2040. With an emphasis on transitioning from an oil-dependent economy to a diversified economic framework, the study employs a quantitative approach in which data from 402 respondents are analyzed through a structured questionnaire. Key dimensions of economic diversification, including production, trade, and revenue, are examined for their respective impacts on sustainable development outcomes. The findings reveal significant positive correlations between the independent variables and the dependent variable, underscoring that effective diversification in production enhances trade and revenue generation, thereby contributing to greater economic resilience. Notably, the results indicate that diversified trade partnerships and increased nonoil production are critical for mitigating the risks associated with fluctuating oil prices. Furthermore, the analysis emphasizes the importance of a balanced revenue model, highlighting the need to expand government revenue sources beyond oil. This research contributes to the understanding of how strategic economic diversification can facilitate sustainable development in resource-rich contexts. The implications of these findings are pertinent for policymakers aiming to achieve the ambitious targets set forth in Oman Vision 2040. By prioritizing initiatives that enhance economic diversification, Oman can advance toward a more sustainable and resilient economy equipped to navigate future challenges.

The purpose of this paper is to study the crop planting strategy of a rural village in North China from 2024 to 2030 to cope with market fluctuations and uncertainty of planting risks. Firstly, a dynamic linear programming model is constructed and combined with Gaussian white noise to simulate random fluctuations, and Lingo software is used to solve the optimization model of crop revenue under the consideration of uncertainty. Then, on the one hand, we analyze the substitutability and complementarity between crops by introducing Spearman's correlation coefficient; on the other hand, we conduct regression analysis on the expected sales volume and sales price, planting cost, introduce the correlation coefficient to correct the existing model, and finally, we use Monte Carlo simulation to generate virtual data to solve the corrected model. The results of the study show that under the dynamic model that takes uncertainty into account, the total planting return in the village is 3,268,000 yuan, the total planting return is adjusted to 3,185,000 yuan after introducing the correlation constraint, and the total return of the grain category is increased by substituting sweet potatoes with pumpkins. This study provides a decision-making framework for agricultural planting strategies that consider economy and risk control, which is of realization significance for rural revitalization and agricultural modernization.

This article provides an in-depth analysis of gambling taxation systems in European Union countries, considering fiscal, legal, and social aspects. The authors defined the purpose of the study as identifying the main approaches to gambling taxation in the European Union countries, analyzing their impact on economic stability, regulatory efficiency and social security, as well as developing proposals for adapting Ukrainian fiscal policy in the field of gambling to European standards in the face of modern challenges. The authors examine the specific features of taxation across various European jurisdictions, including revenue-based taxation and gross gaming revenue (GGR) models, as well as issues related to the taxation of gambling winnings and the structure of licensing fees. Recent fiscal strategies in Italy, Slovakia, Romania, Estonia, Bulgaria, Slovenia, Czech Republic, Latvia, Lithuania and other EU states are analyzed, revealing a general trend toward increased government oversight, higher tax burdens, and intensified efforts to combat illegal gambling operators. Particular attention is paid to the social risks associated with the expansion of the gambling sector, especially the rise of gambling addiction, which increases the risk of player criminalization, debt accumulation, social maladaptation, and vulnerability to criminal exploitation. The study also explores state intervention tools aimed at reducing social harm, such as access restrictions, self-exclusion mechanisms, and stricter regulation of gambling advertising. Emphasis is placed on the role of digital technologies in monitoring the gambling sector and tracking financial flow. Furthermore, the article highlights a shift from traditional tax models toward adaptive systems that respond to the dynamics of online gambling and the growing need for international cooperation to prevent tax base erosion. Based on this analysis, the authors propose recommendations for aligning Ukraine’s gambling taxation policy with European standards to ensure both effective budget revenues and protection of citizens from the negative consequences of gambling under conditions of economic instability and wartime.

This paper examines how decentralized retail and last-mile delivery can transform public service delivery in developing economies, using the Punjab Sahulat Bazaars Authority (PSBA) as a case study. As a statutory institution in Pakistan, PSBA demonstrates how legislative empowerment, strategic leadership, and operational innovation enable scalable, subsidy-free access to essential goods. Employing a qualitative documentary and data-driven approach, the study evaluates PSBA’s legal framework, revenue model, logistics infrastructure, and market impact. Key initiatives include 105 tehsil-level bazaars, over 85,000 home deliveries, mobile bazaars, GPS-enabled digital logistics, solar-powered markets, and women-inclusive vendor policies. These interventions support 21,000 direct jobs and 126,000 dependents while delivering price relief of up to 35% below market rates. The findings position PSBA as a replicable, citizen-focused, and technologically integrated governance model with broad relevance for public sector innovation in emerging economies.

Purpose This study aims to develop and validate a scale measuring Digital Business Model Innovation (DBMI) within organisations. The goal is to provide a reliable and comprehensive tool for assessing the extent of DBMI in practice. Design/methodology/approach The paper follows a rigorous scale development process, which includes item generation, scale development, and purification. Validity and reliability tests were conducted using survey data from two sample sets of 485 and 459 SMEs in India. Findings The study identifies a multidimensional conceptualisation of DBMI, consisting of Value Proposition Innovation, Revenue Model Innovation, Customer Engagement Innovation, Operational Model Innovation, Ecosystem and Partnership Innovation, Organisational Innovation, and Technological Innovation. The developed scale demonstrates strong convergent and discriminant validity, confirming its usefulness as a measurement tool. Research limitations/implications This study advances the understanding of DBMI by providing a solid conceptual framework and a reliable measurement scale. However, the cross-sectional design limits the ability to establish causal relationships, suggesting the need for longitudinal studies to explore the long-term effects of DBMI. Practical implications Practitioners can use the scale to assess their organisation’s DBMI level, benchmark against industry peers, and identify areas for improvement. The scale’s multidimensional nature enables the design of targeted interventions and more efficient resource allocation for successful DBMI. Social implications A higher DBMI level can enhance organisational efficiency, customer satisfaction, and value creation, contributing to broader societal benefits such as economic growth, job creation, and innovation. Originality/value This study contributes to the literature by developing a reliable measurement scale and offering a comprehensive conceptualisation of DBMI. The mixed-methods approach, combining quantitative and qualitative data, strengthens the findings and provides valuable insights for scholars, practitioners, and policymakers interested in DBMI.