scholarly journals Optimization of the System of Monitoring the Effectiveness of Venture Investments

2019 ◽  
Vol 8 (4) ◽  
pp. 2145-2150
Keyword(s):  
Research And Development ◽  
Venture Capital ◽  
Private Equity ◽  
Numerical Data ◽  
Advanced Manufacturing Technologies ◽  
Innovative Products ◽  
Venture Capital Firms ◽  
Manufacturing Technologies ◽  
High Level ◽  
The Impact

The paper discusses real examples of venture capital firms that have reached a high level, as well as start-ups that have not yet managed to become mature companies. The paper presents statistical data on venture investments in the form of tables and graphs for clarity and simplification of the perception of numerical data. The process of evaluating venture capital enterprises is described, which allows you to decide to invest money in a project or abandon such a decision. In the course of the research, scientific, comprehensive literature, periodical informational publications, and Internet resources of various types were used: websites of venture funds, Internet blogs of famous business angels, research articles on venture investment. The choice of diverse literature made it possible to approach the questions of research critically, which helped to ensure an independent assessment. Besides, scientific calculations were used from related fields - marketing, economic psychology, management, which allowed us to consider the topic from different angles, illuminating the subject and object of research from new perspectives. The economic and mathematical model for assessing the impact of venture network actors on the commercialization of innovative products at the regional level consists of the following indicators: advanced manufacturing technologies used; volume of innovative goods, works, services; the number of personnel engaged in research and development; grant of patents; amount of investment; domestic current expenditure on research and development; share of investments in 1 private equity and venture capital fund; share of expenses of the first organization for research and development.

scholarly journals Connectivity as a Design Feature for Industry 4.0 Production Equipment: Application for the Development of an In-Line Metrology System

2021 ◽  
Vol 11 (3) ◽  
pp. 1312
Author(s):  
Ana Pamela Castro-Martin ◽  
Horacio Ahuett-Garza ◽  
Darío Guamán-Lozada ◽  
Maria F. Márquez-Alderete ◽  
Pedro D. Urbina Coronado ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Design Feature ◽  
Production Equipment ◽  
Smart Manufacturing ◽  
Process Data ◽  
Industrial Sectors ◽  
Advanced Manufacturing Technologies ◽  
Manufacturing Technologies ◽  
Equipment Application ◽  
The Impact

Industry 4.0 (I4.0) is built upon the capabilities of Internet of Things technologies that facilitate the recollection and processing of data. Originally conceived to improve the performance of manufacturing facilities, the field of application for I4.0 has expanded to reach most industrial sectors. To make the best use of the capabilities of I4.0, machine architectures and design paradigms have had to evolve. This is particularly important as the development of certain advanced manufacturing technologies has been passed from large companies to their subsidiaries and suppliers from around the world. This work discusses how design methodologies, such as those based on functional analysis, can incorporate new functions to enhance the architecture of machines. In particular, the article discusses how connectivity facilitates the development of smart manufacturing capabilities through the incorporation of I4.0 principles and resources that in turn improve the computing capacity available to machine controls and edge devices. These concepts are applied to the development of an in-line metrology station for automotive components. The impact on the design of the machine, particularly on the conception of the control, is analyzed. The resulting machine architecture allows for measurement of critical features of all parts as they are processed at the manufacturing floor, a critical operation in smart factories. Finally, this article discusses how the I4.0 infrastructure can be used to collect and process data to obtain useful information about the process.

The Politics of the Sharing Economy

2020 ◽  
pp. 21-36
Author(s):  
David Murillo
Keyword(s):  
Venture Capital ◽  
Business Model ◽  
Private Equity ◽  
Sharing Economy ◽  
Moving Target ◽  
Definition Of ◽  
The Impact ◽  
Platform Economy ◽  
Academic Debate

The current academic debate on the sharing economy (SE) seems to embrace three main discussions: its definition, its effects, and the role of regulation. A neglected topic here seems to be analyzing the specific implications of the changing nature of these firms boosted by private equity and venture capital. As the author points out, we need to analyze not only the impact of a changing business model but, specifically, how stakeholders, cities, and regulators should approach this moving target now called SE. In the following sections the author departs from a traditional definition of the sharing economy to start building the case for treating the SE at large as an epiphenomenon of the platform economy, and as a temporary condition based on a moveable business model. The chapter closes by introducing the regulatory hurdles that come associated with the previous and mapping out its different futures.

scholarly journals Private equity and venture capital in South Africa: A comparison of project financing decisions

2013 ◽  
Vol 16 (3) ◽  
pp. 258-278 ◽  
Author(s):  
David Portmann ◽  
Chipo Mlambo
Keyword(s):  
South Africa ◽  
Venture Capital ◽  
Private Equity ◽  
Venture Capitalists ◽  
Project Financing ◽  
Financing Decisions ◽  
Start Up ◽  
Risk Appetite ◽  
Investment Opportunities ◽  
Venture Capital Firms

This paper investigates the manner in which private equity and venture capital firms in South Africa assess investment opportunities. The analysis was facilitated using a survey containing both Likert-scale and open-ended questions. The key findings show that both private equity and venture capital firms rate the entrepreneur or management team higher than any other criterion or consideration. Private equity firms, however, emphasise financial criteria more than venture capitalists do. There is also an observable shift in the investment activities away from start-up funding, towards later-stage deals. Risk appetite has also declined post the financial crisis.

Shared memory multiprocessor support for functional array processing in SAC

2005 ◽  
Vol 15 (3) ◽  
pp. 353-401 ◽  
Author(s):  
CLEMENS GRELCK
Keyword(s):  
Shared Memory ◽  
Array Processing ◽  
Numerical Data ◽  
Parallel Execution ◽  
Real Performance ◽  
Execution Model ◽  
Series Of Experiments ◽  
High Level ◽  
Performance Gains ◽  
The Impact

Classical application domains of parallel computing are dominated by processing large arrays of numerical data. Whereas most functional languages focus on lists and trees rather than on arrays, SAC is tailor-made in design and in implementation for efficient high-level array processing. Advanced compiler optimizations yield performance levels that are often competitive with low-level imperative implementations. Based on SAC, we develop compilation techniques and runtime system support for the compiler-directed parallel execution of high-level functional array processing code on shared memory architectures. Competitive sequential performance gives us the opportunity to exploit the conceptual advantages of the functional paradigm for achieving real performance gains with respect to existing imperative implementations, not only in comparison with uniprocessor runtimes. While the design of SAC facilitates parallelization, the particular challenge of high sequential performance is that realization of satisfying speedups through parallelization becomes substantially more difficult. We present an initial compilation scheme and multi-threaded execution model, which we step-wise refine to reduce organizational overhead and to improve parallel performance. We close with a detailed analysis of the impact of certain design decisions on runtime performance, based on a series of experiments.

Technical Know-How for Modeling of a Geological Environment: Part 2—Geological Modeling

2010 ◽  
Author(s):  
Toshiyuki Matsuoka ◽  
Kenji Amano ◽  
Hideaki Osawa ◽  
Takeshi Semba
Keyword(s):  
Research And Development ◽  
Research Laboratory ◽  
Site Characterization ◽  
Initial Surface ◽  
Geological Environment ◽  
Know How ◽  
Environment Model ◽  
High Level ◽  
Underground Research Laboratory ◽  
The Impact

It is important for site characterization projects to manage the decision-making process with transparency and traceability and to transfer the technical know-how developed and accumulated during the research and development to the implementing phase as well as to future generations. The modeling of a geological environment supports efforts to clarify the degree of understanding regarding that geological environment, including uncertainty. Evaluation of the impact of uncertainties in a geological environment model is important to identify and prioritize key issues for further investigations. Therefore, a plan for site characterization should be made based on the results of the modeling. The aim of this study is to support the planning of initial surface-based site characterization based on the technical know-how accumulated from the Mizunami Underground Research Laboratory Project and the Horonobe Underground Research Laboratory Project. These projects are broad scientific studies of the deep geological environment that are a basis for research and development for the geological disposal of high-level radioactive wastes. In this study, the work-flow followed in developing the geological model, one of the geological environment models, and the related technical know-how acquired from literature data have been summarized.

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