Investment firm to acquire mobile filtration technology provider Desotec

2017 ◽  
Vol 2017 (7) ◽  
pp. 2-3
Keyword(s):  
Investment Firm ◽  
Filtration Technology

Managing the Small Investment Firm (I)

1984 ◽  
Vol 1984 (1) ◽  
pp. 83-86, 89-95
Author(s):  
Frederick L. Muller
Keyword(s):  
Investment Firm

Ownership of the Investment Firm

2001 ◽  
Vol 2001 (6) ◽  
pp. 29-39 ◽  
Author(s):  
John H. Watts ◽  
Joachim Faber ◽  
Hilda Ochoa-Brillembourg ◽  
William J. Nutt
Keyword(s):  
Investment Firm

What is the Business with AI? Preparing Future Decision Makers and Leaders

2020 ◽  
Author(s):  
Helena S. Wisniewski
Keyword(s):  
Data Science ◽  
Decision Makers ◽  
Management Skills ◽  
Business Courses ◽  
College Of Business ◽  
College Of Engineering ◽  
Investment Firm ◽  
Business Curricula ◽  
The University ◽  
The Impact

With companies now recognizing how artificial intelligence (AI), digitalization, the internet of things (IoT), and data science affect value creation and the maintenance of a competitive advantage, their demand for talented individuals with both management skills and a strong understanding of technology will grow dramatically. There is a need to prepare and train our current and future decision makers and leaders to have an understanding of AI and data science, the significant impact these technologies are having on business, how to develop AI strategies, and the impact all of this will have on their employees’ roles. This paper discusses how business schools can fulfill this need by incorporating AI into their business curricula, not only as stand-alone courses but also integrated into traditional business sequences, and establishing interdisciplinary efforts and collaborative industry partnerships. This article describes how the College of Business and Public Policy (CBPP) at the University of Alaska Anchorage is implementing multiple approaches to meet these needs and prepare future leaders and decision makers. These approaches include a detailed description of CBPP’s first AI course and related student successes, the integration of AI into additional business courses such as entrepreneurship and GSCM, and the creation of an AI and Data Science Lab in partnership with the College of Engineering and an investment firm.

Synthesis of ceramic-based porous gradient structures for applications in energy conversion and related fields

2016 ◽  
Vol 09 (04) ◽  
pp. 1641001
Author(s):  
Thomas Graule ◽  
Paulina Ozog ◽  
Caroline Durif ◽  
Judit Wilkens-Heinecke ◽  
Dariusz Kata
Keyword(s):  
Energy Conversion ◽  
Biomedical Applications ◽  
Uv Curing ◽  
Pore Sizes ◽  
Environmental Friendly ◽  
Laminated Structures ◽  
Tailored Design ◽  
Filtration Technology

Porous, graded ceramic structures are of high relevance in the field of energy conversion as well as in catalysis, and additionally in filtration technology and in biomedical applications. Among different technologies for the tailored design for such structures we demonstrate here a new environmental friendly UV curing-based concept to prepare laminated structures with pore sizes ranging from a few microns up to 50 microns in diameter and with porosities ranging from 10% up to 75 vol.% porosity.

Investing in the Ugandan dairy sector

2021 ◽  
Vol 11 (2) ◽  
pp. 1-25
Author(s):  
Jorge Fernandez Vidal
Keyword(s):  
Value Chain ◽  
Dairy Farm ◽  
Market Demand ◽  
Content Type ◽  
Academic Level ◽  
Doing Business ◽  
The Right ◽  
Value Disciplines ◽  
Investment Firm ◽  
Agricultural Investments

Learning outcomes Industry analysis and market attractiveness: Understand how to analyse an industry, using the dairy sector in Uganda as an example and what makes a market attractive for incumbents or future entrants. Value disciplines: Understand and apply the different value disciplines companies can choose from to achieve market-leading positions. Business integration: Understand some of the key benefits of vertical integration and when it may or may not make sense to integrate. Doing business in Africa: Understand the specific generic challenges of doing business in Africa, particularly in the agricultural and manufacturing sectors. Generalisability of frameworks: Realise that the same frameworks that are used to analyse large firms and mature markets can be applied to smaller firms in less developed markets. Case overview/synopsis The case is set in the early months of 2020, as Bernd Schanzenbächer, founder and managing partner of EBG Capital (a Swiss investment firm that manages a multimillion global portfolio of agricultural investments), and his team are deciding whether to invest in a dairy farm in Uganda. The opportunity looks quite interesting and the EBG Capital team believes there is a good fit between the farm owners’ needs, its management team’s objectives and EBG Capital’s strengths and interests. However, the dairy market in Uganda faces many challenges and, while the market-demand fundamentals appear promising, the team wonders if it is the right time to invest. The issue for EBG Capital is to understand what makes the Ugandan dairy industry so challenging and to determine how to fix or mitigate some of the industry’s most pressing problems – given that it will be the firm’s first investment in the country – as well as for deciding where it makes sense to play in the broad value chain (i.e. only in milk production or also in milk processing). Complexity academic level Masters in Business Administration and Executive Education courses. Supplementary materials Teaching Notes are available for educators only. Please contact your library to gain login details or email [email protected] to request teaching notes. Subject code CSS 11: Strategy.

scholarly journals Distribusi Keruangan Penanaman Modal di Kabupaten Bantul

2020 ◽  
Vol 34 (1) ◽  
pp. 25
Author(s):  
Aprilia Prasmudika Sighita ◽  
Bambang Sriyanto Eko Prakoso
Keyword(s):  
Economic Growth ◽  
Spatial Distribution ◽  
Descriptive Analysis ◽  
Analytical Techniques ◽  
Nearest Neighbour ◽  
Investment Climate ◽  
R Value ◽  
Investment Firm ◽  
Neighbour Analysis ◽  
Selection Of

Kabupaten Bantul meraih prestasi tingkat nasional di tahun 2008 yakni memperoleh penghargaan dalam KPPOD Award. Penghargaan yang diperoleh menjadi awal yang baik bagi Kabupaten Bantul dalam memperbaiki iklim penanaman modal. Tujuan dari penelitian ini untuk mengidentifikasi dan menganalisis distribusi keruangan penanaman modal dan pengaruh karakteristik wilayah terhadap pemilihan lokasi penanaman modal. Teknik analisis yang digunakan adalah analisis deskriptif, analisis tetangga terdekat, dan analisis regresi berganda. Berdasarkan hasil kajian dapat disimpulkan bahwa distribusi keruangan penanaman modal di Kabupaten Bantul terdistribusi di 10 kecamatan, sedangkan 7 kecamatan lainnya belum menjadi destinasi penanaman modal. Untuk lokasi perusahaan penanaman modal membentuk pola dispersed atau merata dengan nilai R sebesar 5,920887 (R>1). Sebagian dari lokasi penanaman modal berada di tepi jalan raya. Pemilihan lokasi penanaman modal di Kabupaten Bantul dipengaruhi oleh faktor daya tarik karakteristik wilayah seperti pertumbuhan ekonomi dan jumlah objek wisata. Bantul Regency won the national award of KPPOD in 2008. That award was a good commencement to improve Bantul Regency’s investment climate. The aims of this research were to identify and analyse the spatial distribution of investment and the effect of regional characteristics on the selection of investment site. The analytical techniques used in the research are descriptive analysis, nearest neighbour analysis, and multiple regression analysis. Based on the analysis, it can be concluded that distribution of investment in Bantul Regency distributed in 10 sub-districts, while 7 others are not yet be destination of investment. For the location of investment firms forms a dispersed pattern with R value 5,920887 (R>1). Some investment firm are located on the edge of highway. The selection of investment sites in Bantul regency is affected by the attraction factors of the region characteristics such as economic growth and number of tourism objects.   

scholarly journals Fintech Predictive Modeling and Performance of Investment Firms in Kenya

Webology ◽  
2021 ◽  
Vol 18 (Special Issue 04) ◽  
pp. 1202-1212
Author(s):  
Elizabeth Ndichu Gitonga ◽  
Peter Wang’ombe Kariuki ◽  
Samuel Nduati Kariuki
Keyword(s):  
Predictive Modeling ◽  
Predictive Analytics ◽  
Machine Learning Techniques ◽  
Consumption Pattern ◽  
Mixed Method Research ◽  
Business Growth ◽  
Growth And Survival ◽  
Study Population ◽  
And Performance ◽  
Investment Firm

Predictive analytics is concerned with the prediction of future trends and outcomes. The approaches used to conduct predictive analytics can be classified into machine learning techniques and regression techniques. This study dteremined the influence of fintech predictive modeling on performance of investment firms in Kenya. The study population was 57 investment firms. The study employed mixed method research design by incorporating descriptive and explanatory research designs. Data was collected using questionnaires and an in-depth interview guide. Coefficient of fintech predictive modeling has a positive and significant effect on performance of investment firms. The study concluded that fintech predictive modeling allows investment firms to forecast business growth and customer behaviour chnages. It is important for an investment firm to be able to understand business growth by accurately forecasting future growth and survival. Moreover, it is of vital necessity to understand changes in customer buying/consumption behavior so as to develop products and services that suit their needs and preferences. As a result, predictive modeling is required to project future business growth and changes in customer consumption pattern.

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