From Claim Settlement to Claim Prevention - How Insurers Can Make Use of Predictive Analytics to Change their Business Model

2018 ◽  
pp. 211-214
Author(s):  
Bert F. Hölscher
Keyword(s):  
Business Model ◽  
Predictive Analytics

scholarly journals Big Data for the Sustainability of Healthcare Project Financing

2019 ◽  
Vol 11 (13) ◽  
pp. 3748 ◽  
Author(s):  
Roberto Moro Visconti ◽  
Donato Morea
Keyword(s):  
Big Data ◽  
Business Model ◽  
Predictive Analytics ◽  
Interdisciplinary Approach ◽  
Data Driven ◽  
Project Finance ◽  
Public And Private ◽  
Smart Healthcare ◽  
Economic Marginality ◽  
Sustainable Planning

This study aims to detect if and how big data can improve the quality and timeliness of information in infrastructural healthcare Project Finance (PF) investments, making them more sustainable, and increasing their overall efficiency. Interactions with telemedicine or disease management and prediction are promising but are still underexploited. However, given rising health expenditure and shrinking budgets, data-driven cost-cutting is inevitably required. An interdisciplinary approach combines complementary aspects concerning big data, healthcare information technology, and PF investments. The methodology is based on a business plan of a standard healthcare Public-Private Partnership (PPP) investment, compared with a big data-driven business model that incorporates predictive analytics in different scenarios. When Public and Private Partners interact through networking big data and interoperable databases, they boost value co-creation, improving Value for Money and reducing risk. Big data can also help by shortening supply chain steps, expanding economic marginality and easing the sustainable planning of smart healthcare investments. Flexibility, driven by timely big data feedbacks, contributes to reducing the intrinsic rigidity of long-termed PF healthcare investments. Healthcare is a highly networked and systemic industry, that can benefit from interacting with big data that provide timely feedbacks for continuous business model re-engineering, reducing the distance between forecasts and actual occurrences. Risk shrinks and sustainability is fostered, together with the bankability of the infrastructural investment.

scholarly journals Virtual Airport Hub—A New Business Model to Reduce GHG Emissions in Continental Air Transport

2021 ◽  
Vol 13 (9) ◽  
pp. 5076
Author(s):  
Wojciech Paprocki
Keyword(s):  
Energy Consumption ◽  
Business Model ◽  
Predictive Analytics ◽  
Ghg Emissions ◽  
Air Transport ◽  
Operational Capabilities ◽  
New Business ◽  
Innovative Solution ◽  
Regional Airports ◽  
The Eu

The virtual airport hub business model is an innovative solution supported by digital technologies; the implementation of which in continental air transport may lead to a reduction in energy consumption and to a reduction in greenhouse gas emissions. The prerequisites for the implementation of the described solution are as follows: striving to implement the GHG emission reduction strategy laid out in the Paris Agreement (2015) and the European Green Deal (2019) as well as the EU digitalization strategy (2020). The use of predictive analytics to identify the mobility needs of population and operational capabilities of the sector gives an opportunity to plan travel flows and to create an appropriate set of direct connections among regional airports every day. The results of the analysis of data from 2019 on the amount of energy consumption and GHG emissions indicate that in Europe, it would be possible to achieve reduce GHG emissions by 5% without reducing the number of passengers using air transport. The study was prepared after conducting literature studies, data analysis, and using the method of formulating scenarios. The proposed solution has the features of an innovative business model, the implementation of which allows for obtaining more favorable effects using already available resources.

scholarly journals Reviewing Literature on Digitalization, Business Model Innovation, and Sustainable Industry: Past Achievements and Future Promises

2019 ◽  
Vol 11 (2) ◽  
pp. 391 ◽  
Author(s):  
Vinit Parida ◽  
David Sjödin ◽  
Wiebke Reim
Keyword(s):  
Business Model ◽  
Data Exchange ◽  
Business Models ◽  
Predictive Analytics ◽  
Business Model Innovation ◽  
Research Field ◽  
Future Research ◽  
Special Issue ◽  
Value Capture ◽  
Industrial Companies

Digitalization is revolutionizing the way business is conducted within industrial value chains through the use of Internet of Things (IoT) technologies, intensive data exchange and predictive analytics. However, technological application on its own is not enough; profiting from digitalization requires business model innovation such as making the transition to advanced service business models. Yet, many research gaps remain in analyzing how industrial companies can leverage digitalization to transform their business models to achieve sustainability benefits. Specifically, challenges related to value creation, value delivery, and value capture components of business model innovation need further understanding as well as how alignment of these components drive sustainable industry initiatives. Thus, this special issue editorial attempts to take stock of the emerging research field through a literature review and providing a synthesis of special issue contributions. In doing so, we contribute by developing a framework that communicates and sets the direction for future research by linking digitalization, business model innovation, and sustainability in industrial settings.

Feature extraction and prediction of Dengue Outbreaks

2020 ◽  
pp. 216-222
Author(s):  
Kunal Parikh ◽  
Tanvi Makadia ◽  
Harshil Patel
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Developing Countries ◽  
Feature Extraction ◽  
Predictive Analytics ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Health Concerns ◽  
The World ◽  
Dengue Outbreaks

Dengue is unquestionably one of the biggest health concerns in India and for many other developing countries. Unfortunately, many people have lost their lives because of it. Every year, approximately 390 million dengue infections occur around the world among which 500,000 people are seriously infected and 25,000 people have died annually. Many factors could cause dengue such as temperature, humidity, precipitation, inadequate public health, and many others. In this paper, we are proposing a method to perform predictive analytics on dengue’s dataset using KNN: a machine-learning algorithm. This analysis would help in the prediction of future cases and we could save the lives of many.

Business Model Literature Overview

2014 ◽  
pp. 79-130 ◽  
Author(s):  
Ales Novak
Keyword(s):  
Business Model ◽  
Financial Reporting ◽  
Business Models ◽  
Potential Role ◽  
Financial Instruments ◽  
Business Logic ◽  
Literature Overview ◽  
Ifrs 9 ◽  
Definition Of

The term ?business model' has recently attracted increased attention in the context of financial reporting and was formally introduced into the IFRS literature when IFRS 9 Financial Instruments was published in November 2009. However, IFRS 9 did not fully define the term ‘business model'. Furthermore, the literature on business models is quite diverse. It has been conducted in largely isolated fashion; therefore, no generally accepted definition of ?business model' has emerged. Therefore, a better understanding of the notion itself should be developed before further investigating its potential role within financial reporting. The aim of this paper is to highlight some of the perceived key themes and to identify other bases for grouping/organizing the literature based on business models. The contributions this paper makes to the literature are twofold: first, it complements previous review papers on business models; second, it contains a clear position on the distinction between the notions of the business model and strategy, which many authors identify as a key element in better explaining and communicating the notion of the business model. In this author's opinion, the term ‘strategy' is a dynamic and forward-looking notion, a sort of directional roadmap for future courses of action, whereas, ‘business model' is a more static notion, reflecting the conceptualisation of the company's underlying core business logic. The conclusion contains the author's thoughts on the role of the business model in financial reporting.

Creating adaptive predictions for packaging-critical quality parameters using advanced analytics and machine learning

TAPPI Journal ◽  
2019 ◽  
Vol 18 (11) ◽  
pp. 679-689
Author(s):  
CYDNEY RECHTIN ◽  
CHITTA RANJAN ◽  
ANTHONY LEWIS ◽  
BETH ANN ZARKO
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Predictive Analytics ◽  
Paper Industry ◽  
Quality Parameters ◽  
Fast Change ◽  
The Face ◽  
Model Tuning ◽  
Reducing Costs ◽  
Time Critical

Packaging manufacturers are challenged to achieve consistent strength targets and maximize production while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning. The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under everchanging machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.

DISCIPLINA DE EMPREENDEDORISMO NA FORMAÇÃO DOS ALUNOS DE BIBLIOTECONOMIA E DOCUMENTAÇÃO DA UFS

2018 ◽  
Vol 1 (2) ◽  
pp. 189-195
Author(s):  
Marta Suzana Cabral Nunes ◽  
Augusto Cesar Vieira dos Santos ◽  
Sueli Maria Silva Pereira ◽  
Euder de Jesus Costa
Keyword(s):  
Business Model ◽  
Design Thinking ◽  
Business Model Canvas

Este trabalho visa apresentar a experiência da disciplina de Empreendedorismo na UFS como fator motivador do desenvolvimento de competências para o bibliotecário documentalista, onde participaram alunos do curso de Biblioteconomia e Documentação, dentre alunos de outros cursos. O tema do empreendedorismo tem sido debatido no campo profissional e apresenta-se como alternativa importante que permite aos profissionais desenvolver ações e estratégias inovadoras em sua atuação diária. Trata-se de um estudo que tem como principal mérito apresentar esse caso a fim de demonstrar que é possível, a partir de ações de extensão e da formação continuada, desenvolver competências empreendedoras nos futuros profissionais bibliotecários documentalistas, aplicando metodologias como o Ciclo de Aprendizagem Vivencial, o Business Model CANVAS, Design Thinking, e o Plano de Negócios. Ao todo participaram da disciplina 7 alunos do curso de Biblioteconomia e Documentação da UFS, que preencheram formulário eletrônico a fim de fornecer suas percepções sobre a aprendizagem obtida.

The Potential Of Blockchain Technology To Change International Mobile Roaming Business Model

2019 ◽  
Vol 5 (1) ◽  
pp. 15-22
Author(s):  
Ardian Thresnantia Atmaja
Keyword(s):  
Business Model ◽  
Current Situation ◽  
Business Value ◽  
Third Party ◽  
Fundamental Aspect ◽  
Clearing House ◽  
Blockchain Technology ◽  
Smart Contract ◽  
Target Architecture ◽  
Architecture Development

The key objectives of this paper is to propose a design implementation of blockchain based on smart contract which have potential to change international mobile roaming business model by eliminating third-party data clearing house (DCH). The analysis method used comparative analysis between current situation and target architecture of international mobile roaming business that commonly used by TOGAF Architecture Development Method. The purposed design of implementation has validated the business value by using Total Cost of Ownership (TCO) calculation. This paper applies the TOGAF approach in order to address architecture gap to evaluate by the enhancement capability that required from these three fundamental aspect which are Business, Technology and Information. With the blockchain smart contract solution able to eliminate the intermediaries Data Clearing House system, which impacted to the business model of international mobile roaming with no more intermediaries fee for call data record (CDR) processing and open up for online billing and settlement among parties. In conclusion the business value of blockchain implementation in the international mobile roaming has been measured using TCO comparison between current situation and target architecture that impacted cost reduction of operational platform is 19%. With this information and understanding the blockchain technology has significant benefit in the international mobile roaming business.

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