developed within the project with the aim to allow for the first time to address in an
integrated way the problem of global knowledge access, seamless data exchanges,
and reuse between aquaculture companies and its related stakeholders. The tools
have been developed through the cooperation of different experts (computer scientists, biologists, economists, sociologists, etc.) with the intention to give new
instruments to policy makers and scientists for supporting their research and wellinformed decisions.
The technology developed allows (a) companies to improve efficiency, increase
profitability, and do business in a sustainable, environmentally friendly way,
enabling them to convert their operation data into knowledge and actionable results;
(b) researchers access datasets concerning the practices and performance of aquaculture producers, generating new knowledge and evaluating the practical indicators
of aqua-farming performance; (c) governments and environmental agencies to
evaluate the current situation and define policies; (d) SMEs and academic institutes
to provide training for executives and decision-makers on the sector; and
(e) investors to efficiently take decisions using, for instance, multifactor evaluation
approaches. The delivering of these technologies has been completed through a
continuous development process in which (i) detailed needs for related capacitybuilding instruments are collected and verified, (ii) service and data offerings are
delivered, and (c) results and effectiveness of the instruments are validated.
Integrated production models developed within the scope of the project try to
fulfill the basic demand of incorporating all the possible factors that are vital for
global sustainable development within the process of productivity-potential. The
methodology proposed and the type of models that have been developed are easily
applicable to several different domains such as agriculture, food production, industry, etc. Integrated production models are developed for the aquaculture sector, in
order to (1) assess and conceptualize the social, economic, and environmental
impacts of climate change, over the same time period; (2) gather intelligence and
data that will assist decision-making plagued with uncertainty, (3) foster innovation,
and (4) strengthen the transition towards a Blue Economy by incorporating specific
socio- and techno-economic factors. Sustainability indicators within a socio-,
techno-, and ecological context are utilized in order to examine and record developments over a specific time period and assist in producing qualitative and quantitative data, within a much larger system that includes consumers and the chain of
production.
This chapter provides a brief overview of the VREs developed within the
BlueBRIDGE project with focus on aquaculture. Section 6.2 discusses VRES for
aquaculture. Section 6.3 reviews the socio-economic extensions of the production
models developed. Section 6.4 briefly presents the option to run and examine
alternative future production scenarios. Last section concludes.
6 Techno- and Socio-economic Models of Production with Application to. . .
97
integrated way the problem of global knowledge access, seamless data exchanges,
and reuse between aquaculture companies and its related stakeholders. The tools
have been developed through the cooperation of different experts (computer scientists, biologists, economists, sociologists, etc.) with the intention to give new
instruments to policy makers and scientists for supporting their research and wellinformed decisions.
The technology developed allows (a) companies to improve efficiency, increase
profitability, and do business in a sustainable, environmentally friendly way,
enabling them to convert their operation data into knowledge and actionable results;
(b) researchers access datasets concerning the practices and performance of aquaculture producers, generating new knowledge and evaluating the practical indicators
of aqua-farming performance; (c) governments and environmental agencies to
evaluate the current situation and define policies; (d) SMEs and academic institutes
to provide training for executives and decision-makers on the sector; and
(e) investors to efficiently take decisions using, for instance, multifactor evaluation
approaches. The delivering of these technologies has been completed through a
continuous development process in which (i) detailed needs for related capacitybuilding instruments are collected and verified, (ii) service and data offerings are
delivered, and (c) results and effectiveness of the instruments are validated.
Integrated production models developed within the scope of the project try to
fulfill the basic demand of incorporating all the possible factors that are vital for
global sustainable development within the process of productivity-potential. The
methodology proposed and the type of models that have been developed are easily
applicable to several different domains such as agriculture, food production, industry, etc. Integrated production models are developed for the aquaculture sector, in
order to (1) assess and conceptualize the social, economic, and environmental
impacts of climate change, over the same time period; (2) gather intelligence and
data that will assist decision-making plagued with uncertainty, (3) foster innovation,
and (4) strengthen the transition towards a Blue Economy by incorporating specific
socio- and techno-economic factors. Sustainability indicators within a socio-,
techno-, and ecological context are utilized in order to examine and record developments over a specific time period and assist in producing qualitative and quantitative data, within a much larger system that includes consumers and the chain of
production.
This chapter provides a brief overview of the VREs developed within the
BlueBRIDGE project with focus on aquaculture. Section 6.2 discusses VRES for
aquaculture. Section 6.3 reviews the socio-economic extensions of the production
models developed. Section 6.4 briefly presents the option to run and examine
alternative future production scenarios. Last section concludes.
6 Techno- and Socio-economic Models of Production with Application to. . .
97