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Community Organizations MDPI Online, Open Access Journals
MDPI Online, Open Access Journals
MDPI Online, Open Access Journals
Acronym
MDPI
Publishing Company
Phone number
+41 61 683 77 34

Location

St. Alban-Anlage 66
Basel
Basel-Stadt
Switzerland
Working languages
English

MDPI AG, a publisher of open-access scientific journals, was spun off from the Molecular Diversity Preservation International organization. It was formally registered by Shu-Kun Lin and Dietrich Rordorf in May 2010 in Basel, Switzerland, and maintains editorial offices in China, Spain and Serbia. MDPI relies primarily on article processing charges to cover the costs of editorial quality control and production of articles. Over 280 universities and institutes have joined the MDPI Institutional Open Access Program; authors from these organizations pay reduced article processing charges. MDPI is a member of the Committee on Publication Ethics, the International Association of Scientific, Technical, and Medical Publishers, and the Open Access Scholarly Publishers Association (OASPA).

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Resources

Displaying 751 - 755 of 1524

Perceived Social Norms and Agripreneurial Intention among Youths in Eastern DRC

Peer-reviewed publication
декабря, 2020
Congo

The Democratic Republic of the Congo (DRC) is a country with a high agricultural productivity potential; however, the agribusiness sector remains unattractive to youths. This study examined the extent to which perceived social norms and psychological capital affect youths’ intentions to pursue agribusiness opportunities in the Eastern DRC. Data was collected on a sample of 600 youths. We applied Partial Least Squares Structural Equation Modelling (PLS−SEM) in order to examine the relationship between the variables.

An ISM Approach for Managing Critical Stakeholder Issues Regarding Carbon Capture and Storage (CCS) Deployment in Developing Asian Countries

Peer-reviewed publication
декабря, 2020
Indonesia
Thailand
China
Philippines
Malaysia

Carbon capture and storage (CCS) technology deployment in developing Asian countries largely depends on public acceptance, which is highly dependent on the stakeholders involved in CCS. This paper illuminates how stakeholder issues could be strategically managed in the deployment of CCS, in a manner customized to such developing countries.

Analyzing Urban Public Policies of the City of Ensenada in Mexico Using an Attractive Land Footprint Agent-Based Model

Peer-reviewed publication
декабря, 2020
Global

The Urban Development Plan of the city of Ensenada, México (UDPE) states four major strategic projects, one of which mandates to “Acquire and enable new land reserves and expand opportunities for economic and social development.” This is of vital importance given the large number of vacant lots that perforates the urban surface in contrast to the physical limitations of growth demarcated by hill areas of a steep slope, which forces a sustainable use of the land.

Implementation of Fire Policies in Brazil: An Assessment of Fire Dynamics in Brazilian Savanna

Peer-reviewed publication
декабря, 2020
Global

In 2012, the Brazilian government implemented the Federal Brigades Program (FBP), a fire policy strategy to hire and train firefighters to combat wildfires. This study analyzed the impact of this program on fire behavior before (2008–2012) and after (2013–2017) its implementation in the Parque do Araguaia Indigenous Land, the largest indigenous territory with the highest occurrence of fires in the Brazilian tropical savanna.

Modeling and Prediction of Land Use Land Cover Change Dynamics Based on Land Change Modeler (LCM) in Nashe Watershed, Upper Blue Nile Basin, Ethiopia

Peer-reviewed publication
декабря, 2020
Ethiopia

Change of land use land cover (LULC) has been known globally as an essential driver of environmental change. Assessment of LULC change is the most precise method to comprehend the past land use, types of changes to be estimated, the forces and developments behind the changes. The aim of the study was to assess the temporal and spatial LULC dynamics of the past and to predict the future using Landsat images and LCM (Land Change Modeler) by considering the drivers of LULC dynamics.