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Value proposition

About: Value proposition is a research topic. Over the lifetime, 3582 publications have been published within this topic receiving 88855 citations.


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Journal ArticleDOI
TL;DR: The 5G Exchange (5GEx) concept is introduced, and facilitates the provisioning of multi-operator 5G services by means of inter-operator management and orchestration of virtualized network, compute, and storage resources.
Abstract: Foreseen 5G verticals hold the promise of being true value-added services, hence bringing significant income to their respective providers. However, the nature of these verticals are very demanding in terms of both economic and technical requirements, such as multi-operator cooperation, end-to-end quality assurance, and the unified orchestration of network and cloud resources. Existing systems fall short of satisfying these requirements, but emerging network softwarization and resource virtualization technologies, such as SDN and NFV, show promise for being key enablers in this context. In this article, we introduce the 5G Exchange (5GEx) concept that builds on SDN and NFV, and facilitates the provisioning of multi-operator 5G services by means of inter-operator management and orchestration of virtualized network, compute, and storage resources. We present potential 5GEx use cases, conceptual architecture, and value proposition. We also outline open research questions on how to exchange information in such a coopetitive environment, and provide an outlook on the impact of 5GEx on a network service provider's business and operation.

27 citations

Proceedings ArticleDOI
01 Aug 2019
TL;DR: In this article, the authors present the quantitative approaches like statistical hypothesis testing and analysis of regression using convenient random sampling for better analyzing the impacts of fintech on conventional banking industry in Indonesia.
Abstract: Disruptive innovation related modern information systems has recently altered the ways the companies do their businesses and it has positive impacts to those that are willing to adapt to it. The fast development of fintech startups on creating payment gateway and peer-to-peer (P2P) lending applications is one of examples for the modern disruptive innovations affecting to traditional financial business. The problem arises when the digital disruption affects the bank’s business models due to change in customer trends with additional impacts to conventional companies. This paper presents the quantitative approaches like statistical hypothesis testing and analysis of regression using convenient random sampling for better analyzing the impacts of fintech on conventional banking industry in Indonesia. A number of important and realistic variables, such as customer satisfaction, net promotion score, promotion, ease of use, etc., were considered in this research in order to find a variety of the value propositions that dominantly influence to the adoption of fintech or banking products. The results show that the banks have been disrupted by the payment fintech since the emergence of fintech companies in around 2015, mainly due to superior value propositions, like promotion with standardized beta value of 0.349 and wide range of merchants with 0.153, respectively. In addition, the fintech startups have digital strategies on adopting a customer-centric mindset and developing a product that gives their customer a high customer satisfaction. However, in the current time, P2P fintechs do not have that significant disruption to the banks, mainly due to the fact that the customers consider more on safety reasons.

27 citations

Journal ArticleDOI
TL;DR: It is concluded that mobile computing is a new and unstable technology that potentially can change much about how organizations work and executives must learn to recognize a variety of options for the future and manage these effectively and dynamically while keeping a close eye on the value proposition.
Abstract: New mobile devices, combined with content digitization, promise the creation of a vast global communications network that will have enormous and far-reaching impacts on how we work and live. Who will benefit from this technology, where its real opportunities lie, and how it will impact our organizations and our personal lives is not yet clear. We know that changes will occur and that these impacts will likely vary by firm, industry, and segment of society. What we don’t know is how and when these changes will happen. This uncertainty leaves business with the challenge of navigating between the opportunities presented by the new capabilities offered by mobile technology and the risks of being in the wrong place at the wrong time as their business ecosystem alters. This paper is a tutorial for both the IS practitioner and the IS academic. It presents the issues faced in applying wireless technology in business and suggests areas in which research might be fruitful. It concludes that mobile computing is a new and unstable technology that potentially can change much about how organizations work. However, the uncertainty surrounding mobile computing can make decision-making a challenge for many senior executives who would like to see a clear business case for their investment. Unfortunately, this goal is not always possible. Instead, executives must learn to recognize a variety of options for the future and manage these effectively and dynamically while keeping a close eye on the value proposition.

27 citations

Journal ArticleDOI
TL;DR: In this paper, the authors propose a literature review based on keywords analysis to analyze the issues addressed in the circular business model innovation (CMBI) by categorizing them as core, emerging/phantom, trendy or intermittent.
Abstract: Ongoing economic, social and environmental developments have forced the production system to undertake a profound transformation, shifting from a linear to a circular model. The transformation towards a circular economy poses significant challenges for established companies, in many cases requiring a strong modification of their current business models, start-ups and new ventures. Firms need to completely rethink their value proposition, modifying how the product or service is produced, delivered to the customers and disposed of. As a result, interest in business model innovation with a view to a circular system has increased significantly over the last five years, leading to a flourishing literature production. Although several literature reviews have been published on the topic of the circular business model, few of them include the innovation dimension. Moreover, the time horizon covered by the previous reviews extends to 2019 and in one case to 2020. Since 2020 saw a 135% increase in scientific production compared to the previous year, it is necessary to update the prior works, taking into account the new contributions. Our paper aims to bridge this gap by proposing a literature review based on keywords analysis. In this way, it is possible to analyze the issues addressed in the circular business model innovation (CMBI) by categorizing them as core, emerging/phantom, trendy or intermittent. This analysis is particularly suitable for identifying future research directions as signaled by the emerging themes.

27 citations

Journal ArticleDOI
TL;DR: This work outlines how data-driven business models redefine the value network, alter the roles of individual actors as cocreators of value, lead to the emergence of new data- driven value propositions, as well as novel revenue and cost models.
Abstract: Purpose The purpose of this study is to identify, analyze and explain the ethical implications that can result from the datafication of service. Design/methodology/approach This study uses a midrange theorizing approach to integrate currently disconnected perspectives on technology-enabled service, data-driven business models, data ethics and business ethics to introduce a novel analytical framework centered on data-driven business models as the general metatheoretical unit of analysis. The authors then contextualize the framework using data-intensive insurance services. Findings The resulting midrange theory offers new insights into how using machine learning, AI and big data sets can lead to unethical implications. Centered around 13 ethical challenges, this work outlines how data-driven business models redefine the value network, alter the roles of individual actors as cocreators of value, lead to the emergence of new data-driven value propositions, as well as novel revenue and cost models. Practical implications Future research based on the framework can help guide practitioners to implement and use advanced analytics more effectively and ethically. Originality/value At a time when future technological developments related to AI, machine learning or other forms of advanced data analytics are unpredictable, this study instigates a critical and timely discourse within the service research community about the ethical implications that can arise from the datafication of service by introducing much-needed theory and terminology.

27 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
2023194
2022426
2021307
2020300
2019308