Digital transformation in project-based manufacturing: Developing the ISA-95 model for vertical integration

2022 ◽  
pp. 108413
Author(s):  
Lütfi Apilioğulları
Keyword(s):  
Vertical Integration ◽  
Digital Transformation

HIMSS Impact18: Leading Digital Transformation und Big Data in Medicine

2018 ◽  
Vol 23 (09) ◽  
pp. 25-25
Author(s):  
Sabine Schützmann
Keyword(s):  
Big Data ◽  
Digital Transformation

Am 17. und 18. Oktober findet im Hasso-Plattner-Institut (HPI) in Potsdam zum zweiten Mal die HIMSS Impact statt: Ein englischsprachiges Symposium, welches aktuelle Trends im Gesundheitswesen, digitale Strategien und jüngste Forschungserkenntnisse beleuchtet.

An old friend is better than two new ones? Approaches to market research in the context of digital transformation for the antitrust laws enforcement

2020 ◽  
pp. 37-55 ◽  
Author(s):  
A. E. Shastitko ◽  
O. A. Markova
Keyword(s):  
Business Models ◽  
Rapid Development ◽  
Digital Transformation ◽  
Market Definition ◽  
Type I ◽  
Type Ii ◽  
Digital Platforms ◽  
Advantages And Disadvantages ◽  
Pass Through ◽  
Type Ii Errors

Digital transformation has led to changes in business models of traditional players in the existing markets. What is more, new entrants and new markets appeared, in particular platforms and multisided markets. The emergence and rapid development of platforms are caused primarily by the existence of so called indirect network externalities. Regarding to this, a question arises of whether the existing instruments of competition law enforcement and market analysis are still relevant when analyzing markets with digital platforms? This paper aims at discussing advantages and disadvantages of using various tools to define markets with platforms. In particular, we define the features of the SSNIP test when being applyed to markets with platforms. Furthermore, we analyze adjustment in tests for platform market definition in terms of possible type I and type II errors. All in all, it turns out that to reduce the likelihood of type I and type II errors while applying market definition technique to markets with platforms one should consider the type of platform analyzed: transaction platforms without pass-through and non-transaction matching platforms should be tackled as players in a multisided market, whereas non-transaction platforms should be analyzed as players in several interrelated markets. However, if the platform is allowed to adjust prices, there emerges additional challenge that the regulator and companies may manipulate the results of SSNIP test by applying different models of competition.

Assessing the size of agricultural holdings

2020 ◽  
pp. 105-116
Author(s):  
N. I. Shagaida
Keyword(s):  
Russian Federation ◽  
Vertical Integration ◽  
Total Revenue ◽  
Large Share ◽  
State Support ◽  
The Russian Federation ◽  
Agricultural Organizations ◽  
Business Entities ◽  
To Receive

The article clarifies the concept of “agricultural holding”, using an approach to assessing the size on the basis of the total revenue of all agricultural organizations within the agricultural holding. It has been revealed that only 100 of the total number of agricultural holdings that were identified can be attributed to large business entities. They comprise about 3% of agricultural organizations in the country, while their share in the proceeds is about 37%. A large share of agricultural holdings — large business subjects under the control of Russian entities operate in one, and under the control of foreign legal entities — in three or more regions of the Russian Federation. Vertical integration within the framework of large agricultural holdings with different schemes for including the stages of processing and sale of products produced in their agricultural organizations allows them to receive advantages. Strengthening the role of large business entities in agriculture puts on the agenda the issue of differentiating approaches to taxation and state support in agriculture, depending on the size of the companies’ agricultural businesses.

Imperatives of innovation policy implementation in the concept of digital transformation

2020 ◽  
Author(s):  
A.A. Yuryeva ◽  
◽  
A.A. Stepanov ◽  
I. Pshekhotska ◽  
Ya. Sobon' ◽  
...  
Keyword(s):  
Policy Implementation ◽  
Innovation Policy ◽  
Digital Transformation

Монография посвящена исследованию проблемы современных императивов реализации инновационной политики в условиях цифровизации как установки на эффективное управление и активизацию инновационного поведения и деятельности. Особое внимание уделено организационно-управленческим, гуманистическим, культурно-историческим, профессионально-кадровым и иным императивам, формирующим потенциальные возможности, открывающие новые перспективы эффективного инновационного развития на основе перехода к новой модели построения и функционирования организации. Императивы нацелены на освоение приемов стандартов взаимодействия субъектов-участников в процессе реализации инновационной политики, которые позволяют эффективно и организованно справляться с возникающими проблемами. Монография рассчитана на профессорско-преподавательский состав университетов, других высших учебных заведений, докторантов, аспирантов, магистрантов, студентов, изучающих проблемы управления реализацией инновационной политики в цифровой экономике.

An insight into Case Management and Challenges in Veteran Suicide Prevention

2020 ◽  
pp. 14-25
Author(s):  
Tamara Green
Keyword(s):  
Case Management ◽  
Suicide Prevention ◽  
Suicide Risk ◽  
Digital Transformation ◽  
Prevention Science ◽  
Historical Records ◽  
Military Members ◽  
Prediction And Control ◽  
And Control ◽  
Insight Into

Much of the literature, policies, programs, and investment has been made on mental health, case management, and suicide prevention of veterans. The Australian “veteran community is facing a suicide epidemic for the reasons that are extremely complex and beyond the scope of those currently dealing with them.” (Menz, D: 2019). Only limited work has considered the digital transformation of loosely and manual-based historical records and no enablement of Artificial Intelligence (A.I) and machine learning to suicide risk prediction and control for serving military members and veterans to date. This paper presents issues and challenges in suicide prevention and management of veterans, from the standing of policymakers to stakeholders, campaigners of veteran suicide prevention, science and big data, and an opportunity for the digital transformation of case management.

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