Functional Value in Breeding Integrated to the Vegetables Value Chain as Part of Decision Making

2020 ◽  
pp. 51-65
Author(s):  
C. Jana ◽  
G. Saavedra ◽  
N. Calabrese ◽  
J. P. Martinez ◽  
S. Vargas ◽  
...  
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Functional Value

scholarly journals Multi-criteria decision-making model for supporting manufacturing settlements location in Africa after COVID-19

2021 ◽  
Vol 13 ◽  
pp. 184797902110233
Author(s):  
Stefania Bait ◽  
Serena Marino Lauria ◽  
Massimiliano M. Schiraldi
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Multinational Enterprises ◽  
Value Added ◽  
Plant Performance ◽  
Multi Criteria Decision Making ◽  
African Countries ◽  
Analytic Hierarchy ◽  
Location Selection ◽  
Decision Making Model

The COVID-19 emergency is affecting manufacturing industries all over the world. Notably, it has generated several issues in the products’ supply and the global value chain in African countries. Besides this, Africa’s manufacturing value-added rate grew only 1.5 since 2018, and the foreign direct investment (FDI) from multinational enterprises (MNEs) remains very low due to high-risk factors. Most of these factors are linked to a non-optimized location selection that can adversely affect plant performance. For these reasons, supporting decision-makers in selecting the suitable country location in Africa is crucial, both for contributing to countries’ growth and companies’ performance. This research aims at presenting a comprehensive multi-criteria decision-making model (MCDM) to be used by MNEs to evaluate the best countries to develop new manufacturing settlements, highlighting the criteria that COVID-19 has impacted. Thus, it has affected countries’ performance, impacting the plant location selection choices. A combination of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods have also been used for comparative analysis. The criteria used in the proposed approach have been validated with a panel of MNEs experts.

scholarly journals Building the Sun4Cast System: Improvements in Solar Power Forecasting

2018 ◽  
Vol 99 (1) ◽  
pp. 121-136 ◽  
Author(s):  
Sue Ellen Haupt ◽  
Branko Kosović ◽  
Tara Jensen ◽  
Jeffrey K. Lazo ◽  
Jared A. Lee ◽  
...  
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Solar Irradiance ◽  
Collaborative Design ◽  
Solar Power ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Solar Array ◽  
Solar Power Forecasting ◽  
Power Forecasting

Abstract As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from the public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers. The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, which forms the basis of the system beyond about 6 h. For short-range (0–6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short- to midterm irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. This paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.

scholarly journals Strategic Decision-Making In the Emerging Field Of E-commerce

2011 ◽  
Vol 14 (2) ◽  
Author(s):  
Rodney Oudan
Keyword(s):  
Decision Making ◽  
Electronic Commerce ◽  
Value Chain ◽  
Theoretical Background ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Value Chains ◽  
Competitive Strategies ◽  
Knowledge Based ◽  
Doing Business

Electronic commerce is changing the traditional way of doing business and furthermore the growth of the Internet is creating new opportunities for business.  This paper discusses how the nature of electronic commerce affects strategic decision-making. First, some features of electronic commerce are identified that distinguish it from traditional business - new markets and knowledge-based competition.  This is followed by a review of literature on the theoretical background of e-commerce an academic consideration on what are e-commerce strategies.  This paper then introduces some of the most common strategic tools used in decision –making, concepts for creating competitive advantage and value chains. Porter’s Value Chain Theory, Five Forces Model is examined in the emerging world of e-commerce, as well as generic competitive strategies.

Prozess-Empowerment durch Handlungsempfehlungen/Recommondation-based process empowerment. Edge-AI architecture for the prediction of quality features

2020 ◽  
Vol 110 (06) ◽  
pp. 363-367
Author(s):  
Tobias Kaufmann ◽  
Soumen Ganguly ◽  
Daniel Trauth ◽  
Wolfgang Maas ◽  
Thomas Bergs
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Sustainable Production ◽  
Decision Making Process ◽  
Industrial Products ◽  
Recommendations For Action ◽  
Machine Operators ◽  
Pass Through ◽  
Processing Steps ◽  
Quality Features

Industrielle Güter durchlaufen eine Vielzahl von Bearbeitungsschritten, während der Bauteilwert sich entlang dieser Wertschöpfungskette steigert. Eine robuste und Edge-KI-basierte Vorhersage von Prozessergebnissen befähigt Maschinenbediener durch abgeleitete Handlungsempfehlungen aktiv bei ihrer Entscheidungsfindung. Dies ermöglicht nicht nur eine vorausschauend effiziente, sondern auch eine nachhaltige Produktion.   Industrial products pass through a multitude of processing steps, and their value is increased along this value chain. With a resilient and edge-ai-based prediction of process results, machine operators are significantly empowered in their decision-making process through recommendations for action. This enables not only a foresighted and efficient but also a sustainable production.

Innovation Platforms

2018 ◽  
pp. 72-95
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Business Model ◽  
Value Chain ◽  
Analytical Techniques ◽  
Human Interaction ◽  
Business Relationship ◽  
Potential Relationship ◽  
Relationship Of ◽  
Cross Fertilization

Data and analytics is the heart of a digital business platform. Today, big data (BD) becomes useful when it enriches decision making that is enhanced by application of analytical techniques and some element of human interaction. With the merging of data and information vs. knowledge and intelligence, this chapter investigates an opportunity for cross-fertilization between BD and the field of digital business with related disciplines. Primary BD and analytics platform is a set of business capabilities. This chapter aims to investigate the potential relationship of BD and analytics platform and digital business platform. In doing so, it develops a BD value chain framework, BD business model pattern (BDBMP) with related levels of BD maturity improvement. This framework could be used to find answers on the basic BD and digital business relationship questions.

AHP-Driven Knowledge Leakage Risk Assessment Model

2020 ◽  
pp. 218-237 ◽  
Author(s):  
Haley Wing Chi Tsang ◽  
Wing Bun Lee ◽  
Eric Tsui
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Intellectual Capital ◽  
Value Chain ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Analytic Hierarchy ◽  
Job Knowledge ◽  
Knowledge Leakage ◽  
Hierarchy Process

Intellectual Capital (IC) is becoming more widely understood by the academic and business communities, especially its important role in value creation of an organization. However, few people are aware that IC, if not managed properly, may also pose threats, sometime serious, to an organization. Knowledge leakage from an organization, for example, may come about when an experienced employee leaves for another job. Knowledge leakage is pervasive throughout an organization but is seldom noticed until the consequence is felt. This intellectual capital risk has to be systematically and effectively identified, assessed and controlled in the whole value chain of an organization. An AHP (Analytic Hierarchy Process) based multi-dimensional decision making and assessment model is developed to determine knowledge leakage risk in an organization.

It’s (just) Chemistry, Stupid! Or Not?

2015 ◽  
Vol 6 (3) ◽  
pp. 423-425
Author(s):  
Justo Corti Varela
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Institutional Dynamics ◽  
Eu Legislation ◽  
Risks And Benefits ◽  
Modern Biotechnology ◽  
National Attitudes ◽  
The Relationship ◽  
Food Value ◽  
The Eu

This section aims to update readers on decisions related to marketing products of modern biotechnology (e.g., GMOs, animal clones) at EU level and on national measures concerning their production. Special attention is devoted to problems of competence between Member States and the EU in regulating biotechnology issues; the institutional dynamics of decision making regarding products derived frommodern biotechnology; the relationship between the EFSA and the EU institutions on green biotech-related issues; the evolution of EU regulatory framework and of national attitudes towards the risks and benefits of biotechnology derived products and their production. This section will also delve into the interaction between the EU legislation and WTO law regarding advances in the application of biotechnology within the agri–food value chain.

Decision making in the cod industry based on recording and analysis of value chain data

2010 ◽  
Vol 99 (2) ◽  
pp. 151-158 ◽  
Author(s):  
Sveinn Margeirsson ◽  
Birgir Hrafnkelsson ◽  
Guðmundur R. Jónsson ◽  
Páll Jensson ◽  
Sigurjón Arason
Keyword(s):  
Decision Making ◽  
Value Chain

scholarly journals Application of the Fuzzy Optimal Model in the Selection of the Startup Hub

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xinman Zhu ◽  
Jie Dai ◽  
Haoran Wei ◽  
Debing Yang ◽  
Weilun Huang ◽  
...  
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Nominal Group Technique ◽  
Nominal Group ◽  
Order Preference ◽  
The Difference ◽  
Topsis Approach ◽  
Textile Factory ◽  
Hierarchy Process

This paper integrates nominal group technique (NGT), analytical hierarchy process (AHP), and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) approach, and a case study has been used to demonstrate the fuzzy optimal selection model. From a literature review on the startup hub and the interviews conducted with officials and experts, the selection criteria are (1) convenience—promoted by the city’s entrepreneurial policies or its traffic infrastructure; (2) potentiality—promoted by a regional network or value chain of startups. Lastly, the best idle land resulted in this case study with equal decision-making power using the fuzzy method is Taipei Jianguo Brewery, and the difference of decision-making power might make the best idle land to be Wanbao Textile Factory.

Biotechnology

2010 ◽  
Vol 1 (1) ◽  
pp. 63-71
Author(s):  
Justo Corti Varela
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Institutional Dynamics ◽  
Eu Legislation ◽  
Risks And Benefits ◽  
Modern Biotechnology ◽  
National Attitudes ◽  
The Relationship ◽  
Food Value ◽  
The Eu

This section aims to update readers on decisions related to marketing products of modern biotechnology (e.g., GMOs, animal clones) at EU level and on national measures concerning their production. Special attention is devoted to problems of competence between Member States and the EU in regulating biotechnology issues; the institutional dynamics of decision making regarding products derived from modern biotechnology; the relationship between the EFSA and the EU institutions on green biotech-related issues; the evolution of EU regulatory framework and of national attitudes towards the risks and benefits of biotechnology derived products and their production. This section will also delve into the interaction between the EU legislation and WTO law regarding advances in the application of biotechnology within the agri-food value chain.

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