scholarly journals Additive Manufacturing Cases and a Vision for a Predictive Analytics and Additive Manufacturing Based Maintenance Business Model

2020 ◽  
pp. 131-148
Author(s):  
Michele Urbani ◽  
Mikael Collan
Keyword(s):  
Additive Manufacturing ◽  
Business Model ◽  
Predictive Analytics

scholarly journals The width and scope of intelligence studies in business

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Klaus Solberg Soilen
Keyword(s):  
Data Mining ◽  
Economic Development ◽  
Additive Manufacturing ◽  
Business Intelligence ◽  
Predictive Analytics ◽  
Competitive Intelligence ◽  
Special Issue ◽  
Monitoring Process ◽  
Intelligence Studies ◽  
Simple Evaluation

If the last issue of JISIB was a special issue where the discipline was reflecting on itself, then this issues shows some of the width and scope of the field. The conceptual article by Nienaber and Sewdass presents a relatively new concept of workforce intelligence, and links it to competitive advantage by way of predictive analytics. The article by Solberg Søilen is an attempt to lay out a broad scientific agenda for the area of intelligence studies in business.Empirical findings come from a survey, but in the discussion the author argues for why the study should define itself as much broader than what the survey data implies, breaking out of the current dominating scientific paradigm. The article by Fourati-Jamoussi and Niamba is an updated evaluation of business intelligence tools, a frequently reoccurring topic. However, this time it is not a simple evaluation of existing software, but an evaluation by users to helpdesigners of business intelligence tools get the best efficiency out of a monitoring process. The article by Calof is an evaluation of government sponsored competitive intelligence for regional and sectoral economic development in Canada. The article concludes that it is possible tocalculate positive economic impacts from these activities. Rodríguez Salvador and Hernandez de Menéndez come back to a field that has become a specialty for Rodríguez Salvador: scientific and industrial intelligence based on scientometric patent analysis. This time she looks at bio-additive manufacturing using advanced data mining software and interviews with experts.

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.

Business Model for SMEs in the Field of Additive Manufacturing

2021 ◽  
Vol 396 (1) ◽  
pp. 2000291
Author(s):  
Andreea Cristina Costache ◽  
Gabriel Moagăr‐Poladian ◽  
Cristian Vasile Doicin
Keyword(s):  
Additive Manufacturing ◽  
Business Model

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.

scholarly journals Circular Business Models for Remanufacturing in the Electric Bicycle Industry

2021 ◽  
Vol 2 ◽  
Author(s):  
Carina Koop ◽  
Julian Grosse Erdmann ◽  
Jan Koller ◽  
Frank Döpper
Keyword(s):  
Additive Manufacturing ◽  
Business Model ◽  
Business Models ◽  
Spare Parts ◽  
Strong Increase ◽  
Bicycle Industry ◽  
Service Models ◽  
Electric Bicycle ◽  
Use Phase ◽  
Electric Bicycles

The rising popularity and strong increase in the number of electric bicycles make it necessary to consider the built-in resources as well as possible treatments after the use phase. The time lag between the purchase and the occurrence of relevant defects suggests significant increases in defective components. Especially the great dynamics of the market due to regular innovations, product renewals, and the lack of spare parts availability for older models make the long-term use by customers much more difficult than for conventional bicycles. Therefore, it is necessary to analyze circular business models for the electric bicycle market. In this way, the required structures for a sustainable electric bicycle industry can be created so that valuable materials do not go into disposal but undergo a new use phase. Based on the results of “AddRE-Mo–Value Preservation Scenarios for Urban Electromobility of Persons and Loads through Additive Manufacturing and Remanufacturing,” a research project funded by the German Federal Ministry of Education and Research, this paper addresses four circular business models, two sales models, and two service models. The guiding research interest of this paper is the combination of remanufacturing and additive manufacturing from a business model perspective, analyzing the extent to which additive remanufacturing can be considered a solution for electric bicycles' circularity. After describing the approach and methods used to develop these four circular business models the business models are described and analyzed using the Business Model Canvas. Based on this analysis, it is shown that the combination of remanufacturing and additive manufacturing can be applied to the electric bicycle market and be integrated into both sales and service models. The description of these business models will help managers design viable business models in the context of sustainable electric bicycles. It also shows that the individual partners within the value chain must collaborate more closely. In the electric bicycle industry, a single company will probably not be able to close the product cycle completely. Further research is needed to develop concepts of the business models and examine their practical feasibility in technical and organizational operations to achieve a circular economy.

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