revenue model
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2021 ◽  
Vol 16 (7) ◽  
pp. 2981-3002
Author(s):  
Ya-Wen Lin ◽  
Tsung-Xian Lin ◽  
Cheng-Kiang Farn

The long-standing economic model is one where customers receive and pay for goods and services. However, in today’s modern network economy, why are vendors willing to provide free services and goods to free-riders at an apparent loss? The objective of this study is to provide a theoretical framework explaining why free network services emerge and how they work. This study adopted the multi-case study method, summarized 28 types of revenue model patterns from 51 indicative free network services, and inferred the causes for the antecedent conditions of each revenue model with Qualitative Comparative Analysis (QCA), in order to confirm the causal relationship between the various antecedent conditions, configurations, and revenue models as conclusive evidence. In addition, this study established seven conditional propositions via their links with related theories, which were taken as the basis for providing in-depth explanations of the revenue model of the free network service, and expanded the demonstration of the original network economy.


Author(s):  
Jessica E. Galarraga ◽  
Derek DeLia ◽  
Jim Huang ◽  
Cynthia Woodcock ◽  
Rollin J. Fairbanks ◽  
...  

Author(s):  
Zhen Li ◽  
Qi Liao

We are experiencing the worst years of ransomware attacks with continuing news reports on high-profile ransomware attacks on organizations such as hospitals, schools, government agencies and private businesses. Recently a few ransomware attackers have gone beyond simply encrypting files and waiting for ransom. They threaten to release the data if the victims refuse their ransom request. In this paper, we propose a hypothetical new revenue model for the ransomware, i.e., selling the stolen data rather than publishing the data for free. Through a game-theoretical analysis between attackers and victims, we contribute a novel model to understand the critical decision variables for the proposed data-selling ransomware (which we refer as "ransomware 2.0") that sells data as well as demands ransom. We compare the role of reputation and the profitability of the data-selling ransomware with traditional ransomware ("ransomware 1.0") that demands ransom only and the data-threat ransomware ("ransomware 1.5") that demands ransom with the threat of releasing data for no compliance. Both theoretical modeling and simulation studies suggest that in general both ransomware 2.0 and 1.5 are more profitable than ransomware 1.0, while ransomware 2.0 is always more profitable than ransomware 1.5. Notably, common defensive measures that may work to eliminate the financial incentives of ransomware 1.0 may not work on ransomware 2.0, in particular the data backup practice and the never-pay-ransom strategy. Our findings also suggest that the uncertainties created by this new revenue model may affect attackers' reputation and users' willingness-to-pay, therefore, ransomware 2.0 may not always increase the profitability of attackers. Another finding of the study suggests that reputation maximization is critical in ransomware 1.0 and 1.5, but not in ransomware 2.0, where attackers could manipulate reputation for profit maximization.


2021 ◽  
Vol 5 (1) ◽  
pp. 42-73
Author(s):  
Larysa Hlinenko ◽  
◽  
Yurii Daynovskyy ◽  

The aim of the article. Internet of Things (IoT) technologies deeply affect business development and, as a consequence, business models (BMs) as a way of doing business by its actors. Conventional firm-centric e-business models are not always good for the IoT due to its ecosystem nature; implementing innovative models faces a number of challenges. It is a BMC (Business Model Canvas) template that is mainly used to create business models at enterprise level. Modified in accordance with the specifics of IoT, BMC templates overcome the limitations of the classical BMC and provide interrelated BMC solutions for the different layers of the IoT architecture. However, all of these templates, when modelling value propositions, focus only on the current state of consumer needs. The models ignore the interdependencies between the allowable attribute values of the certain BMC blocks, in particular between key resources, value proposition and revenue model. The article aims to analyse the IoT business models based on BMC, to identify the effective values of individual components of the BMC and the expediency of combining them within a particular BM and to specify means of taking into account the changing state of consumer needs in the formation of the BMC components. Analyses results. The IoT outlines a paradigm relying on a continuous set of things which interact with forming a worldwide dynamic network. The functionality of the IoT device sets the technological constraints and perspectives for value propositions and revenue generation modesl. The analysis of the proposed variants of IoT BMC and their successful implementation cases provided for clarification and generalisation of effective value propositions consistent with IoT specificity. For each of these value propositions the compatible revenue models and required functions of IoT devices were identified. In accordance with the proposed sophisticated classification of the IoT device functionalities, the valid types of IoT devices as a key resource for the realisation of a particular value proposition were identified. The formation of the BM should start from developing the concept of value offered to the consumer. To be effective the creation of the value proposition should be preceded by the identification of the consumer need and the state of its satisfaction by existing means. This state can be the following one: the need exists, but is not recognized by consumers and is not satisfied by existing means at all; the need exists and is identified by consumers but is not satisfied by existing means at all; the need is clear to consumers but is not fully satisfied by existing means. In the first two cases, the value proposition should ensure meeting the need at a minimum sufficient level. In case the means of satisfying the need exist, it is necessary to assess the current state of satisfying the need and to determine the extent to which the proposed IoT solution would change this state. The lines of development of needs and means of their satisfaction, adapted to the specifics of the particular need and IoT at large, are proposed to be used for assessing the state of need satisfaction. Specificity of IoT requires supplementing the set of lines of development of needs and satisfaction means with the lines launched by IoT possibilities. Several such lines, in particular, the line of increasing the consumer's awareness and the line of increasing the ideality of the final need satisfaction, have been proposed. A matrix of need parameters has been developed to simplify the consideration of the content and state of need in the formation of value and revenue models. Conclusions and directions for further research. The importance of taking into account the characteristics of needs in value proposition design makes it necessary to identify "Needs" as a distinct BMC component described by a set of specific attributes. The values of these attributes, together with the resources of the participants, provide the basis for the value proposition content and affect the choice of the revenue model. Setting the attribute values requires determining the current and expected state of needs and the means of meeting them on relevant lines of development, the further elaboration and parameterisation of which, taking into account the specificity of IoT, is the subject of further research. The result of the digital service provided by the IoT device appears to be a key innovative element of the IoT value proposition. That suggests the separating the "IoT contribution" element in the "Value proposition" component of the BMC or introducing it as a BMC component to reflect the relevant digital service. The content of the service will determine the functionality of the IoT device and the IT infrastructure requirements. When defining the value proposition, the real change in the state of all the components of the IoT ecosystem causing changes in the prioritisation of individual needs should also be considered. Clarifying the concept of the value proposition, the needs it satisfies and the specific "IoT component" of value creates the basis for identifying consumer segments and the ways of interacting with them. Compatibility and effectiveness of the joint use of specific value propositions and revenue models as well as compliance of the value proposition content, cost and promotion to the target consumer demands should be also considered when specifying the blocks of BMC. The BMC is to be built for each of the ioT ecosystem partners. The present research recommendations refer mainly to developers and manufacturers of IoT devices and service providers; the construction of the BMC for other IoT system key players (platform providers/providers, system integrators and marketplace providers), as well as the problem of these models coordination, should be the subjects of separate research. Keywords: Internet of Things (IoT), business model, Business Model Canvas (BMC), value proposition, revenue model


2021 ◽  
Vol 13 (4) ◽  
pp. 1740
Author(s):  
Cheng Che ◽  
Xiaoguang Zhang ◽  
Yi Chen ◽  
Liangyan Zhao ◽  
Zhihong Zhang

By establishing a two-level symbiotic supply chain system consisting of one supplier and one manufacturer, we use Stackelberg method to analyze the optimal price and revenue model of supplier and manufacturer in the symbiotic supply chain under two power structures in which the supplier and manufacturer are dominant respectively, and analyze the influence of the degree of symbiosis and power structure on the model. Through comparative analysis, we find that: There is a relationship between the income level and the degree of symbiosis in the symbiotic supply chain. The change of power structure will affect the relative benefits of suppliers and manufacturers in the symbiotic supply chain. The manufacturer’s expected unit product revenue will affect the supply chain revenue when the manufacturer is dominant. Finally, the sensitivity analysis of relevant parameters is carried out through an example analysis, and the validity of the conclusion is verified. This paper has a guiding significance for the behavior of enterprises in the cogeneration supply chain.


Author(s):  
Ruhi Bhardwaj ◽  
Namrata Sandhu

From a humble beginning in 2013, OYO is today the world's second-largest hospitality chain of franchised and leased hotels, living spaces, and homes. OYO has a global presence with large-scale operations in many countries. This case outlines OYO's complicated growth journey from a rapidly growing startup to an ethically maligned business venture. It also underscores OYO's business and revenue model, work culture, and growth strategies. It also provides a sneak peek about the major problems faced by OYO and how OYO should cope with these challenges.


2020 ◽  
Author(s):  
Martin Eve ◽  
Frances Pinter

We outline the work of a university press, with assistance from the COPIM Project (Community-led Open Publication Infrastructures for Monographs), in building an innovative revenue model to fund open access monographs at a traditional publisher. Building on library journal subscription models (eg: OLH) and on Knowledge Unlatched's approach to monograph funding, we present a sustainable OA publishing model that gives members exclusive access to a backlist, with the revenue then used to make the frontlist openly accessible. The model can be emulated by other scholarly presses who wish to take advantage of the opportunities that open access publishing affords. Supporting information: Led by Dr Frances Pinter (Publishing Advisor, & founder of Knowledge Unlatched) and Professor Martin Paul Eve (OLH, Birkbeck & COPIM) the case study explores an innovative revenue model that will transition new titles at a well-known publisher to a viable open-access model. COPIM is an international partnership of researchers, universities, librarians, publishers and infrastructure providers working on bringing about a new OA publishing ecosystem. Their remit is to build a revenue infrastructure, and examine production workflows and metadata, experimental publishing and archiving. The project is working with colleagues across the sector to document existing and potential ways of funding open-access monographs and is consulting with academics, publishers, libraries, funders, and policy makers. The publisher case study aims to initiate and document a ‘working model’ as the next step in creating a practical toolkit and roadmap for other publishers.


2020 ◽  
Vol 12 (16) ◽  
pp. 6635
Author(s):  
Katarína Remeňová ◽  
Jakub Kintler ◽  
Nadežda Jankelová

Since revenue streams provide financial stability for business development, companies are tasked with conducting an individual revenue model, that ensures their healthy and sustainable growth. Therefore, it is important to take into account the manner of creating revenues. This initiative relates to the revenue generation mechanism which describes how revenue is generated from the offer. Our research aims to find out whether the number of revenue streams (scope of the revenue model) and other financial and production indicators can predict the amount of revenue, as well as which factors can predict the scope of the revenue model. Concurrently we have focused on analyzing the sources of revenue streams and have selected key business variables in the wine producing industry. This sector had been selected as there is a significant difference between revenue streams based on manufacturing and those based on tourism activities. This concept was created by using theoretical knowledge about the value, pricing and segmentation. The goal of our research article was to design the General Concept of the Revenue Model and to identify variables with a strong influence on it. Results of the multiple linear regression analysis confirmed the significant influence of particular predictors on the scope of the revenue model, whereby the model explains up to 80% of the variance.


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