scholarly journals The Possibilities of Open-Cast Mining in Landscape Parks in Poland—A Case Study

Resources ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 122
Author(s):  
Alicja Kot-Niewiadomska ◽  
Agnieszka Pawłowska
Keyword(s):  
Nature Conservation ◽  
National Parks ◽  
Cultural Landscape ◽  
Buffer Zones ◽  
Open Cast Mining ◽  
The Social ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Social Licence To Operate

Landscape parks are one of the most important tools for nature conservation in Europe. Cultural landscape protection, coupled in particular with rural tradition of land use plays a very important role. A common feature of these popular protected areas is the fact that they are established legally, in accordance with the principle of sustainable development. Activities carried out in the landscape parks are not entirely subservient to nature conservation. This makes them different from national parks and natural reserves. In Poland, landscape parks together with their buffer zones cover more than 13% of the country’s territory, which frequently causes conflicts among mining entrepreneurs and limits their activities. Mining in landscape parks in Poland is not forbidden by domestic law; however, detailed guidelines in this respect are determined by the assembly of a given province. Additionally, the process of applying for an extraction licence could be burdened with the threat of social protests, which may result in extending it by many years, and because of which a project may fail to be completed. Optimal solutions to these obstacles are already proposed by “Czatkowice” Limestone Mine (Małopolska Province). This case study presents an efficient practice of a smooth and effective decision-making process of obtaining a new mining licence in a landscape park. It also outlines certain aspects of the social licence to operate (SLO) as well as some appropriate methods of acting in complicated environments and spatial conditions.

Designing a Business Analytics Culture in Organizations in India

2021 ◽  
pp. 670-678
Author(s):  
Tanushri Banerjee ◽  
Arindam Banerjee
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Data Organization ◽  
Business Analytics ◽  
Domain Specific ◽  
Consumer Lending ◽  
Effective Decision ◽  
Effective Decision Making

There are several challenges faced by decision makers while deploying Business Analytics in their organization. There may not be one resolution approach that is suitable for creating a Business Analytics culture in all organizations. However, it is easy to perceive that most India-based organizations may have similar issues of data organization that may be impeding their progression in the field of Analytics. Based on their research, the authors have proposed a framework for adoption of Analytics in Indian firms in their book “Weaving Analytics for Effective Decision Making” by SAGE. They propose to use that model for explaining certain domain specific adoption of Business Analytics in organizations in India. They have used a case study of a Global Bank which is in the process of establishing its consumer lending USA operations, an offshore captive operation, in India to describe the process of building an Analytics team in an organization in India. Data processed using R has been added as screenshots for supporting the findings.

A descriptive case study of effective decision-making of a local government organization in the United States of America

2020 ◽  
Vol 16 (3) ◽  
pp. 279-297
Author(s):  
Jennifer Capler
Keyword(s):  
United States ◽  
Decision Making ◽  
Local Government ◽  
United States Of America ◽  
The United States ◽  
Content Type ◽  
Government Organizations ◽  
Effective Decision ◽  
Effective Decision Making

PurposeThis article details a qualitative descriptive case study of affective factors of effective decision-making of one local government organization in the United States of America. The specific problem was that many elected American local government representatives lack effective decision-making strategies. This research focus indicated a lack of qualitative research on the real-world experience of factors that were taken into consideration during decision-making within American local government organizations.Design/methodology/approachUsing a local government organization in southwest Illinois, elected representatives were interviewed and observed. The interviews and observations surfaced how the representatives made decisions. Data were analyzed using manual coding and theming to determine themes and patterns.FindingsThe results produced six themes about factors, including emotional intelligence, which impacted decision-making. They are: (1) remembering the past, (2) communication and respect, (3) spurring economic growth and development, (4) fairness, (5) recognizing and removing emotions and bias and (6) accountability.Research limitations/implicationsBeing a single case study, this research is limited in generalization. The research was limited to the identification of current, real-world experience of elected local government representatives.Practical implicationsThe findings of this research can be used to create more effective decision-making practices for local government organizations of similar size.Originality/valueThis is the first study to review, in-depth, the decision-making and emotional intelligence factors of local government organizations in the United States of America. The conceptual background, discussion, implications to local government organizations, limitations and recommendations for future studies are discussed.

The Making of a National Park: Ruins of Nature and History in Northern Dobrudja

2017 ◽  
Vol 31 (3) ◽  
pp. 596-614
Author(s):  
Calin Cotoi
Keyword(s):  
Nature Conservation ◽  
Political Ecology ◽  
National Parks ◽  
National Park ◽  
Conservation Areas ◽  
Analytical Potential ◽  
The Social ◽  
Social Construction Of Nature ◽  
Critical Discourses ◽  
Gain Access

After 1990, nature conservation areas multiplied all over Central and Eastern Europe. National parks came into being as part of a dramatically changing society, economy, and culture. Scholarly efforts to understand national parks rely either on arguments about the social construction of nature or on political ecology. In this article, I attempt to point to the analytical potential of the literature on ruins for expanding studies carried out in both theoretical traditions. I draw from fieldwork in nature conservation areas in southeastern Romania to explore how actors gain access to critical discourses and complex ways of narrating and enrolling the landscapes. The mechanisms that counterpoise safeguarding and development are analyzed as parts of a longue durée articulation of ruination and modernization.

scholarly journals Urban Vitality Evaluation and Spatial Correlation Research: A Case Study from Shanghai, China

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1195
Author(s):  
Jiangang Shi ◽  
Wei Miao ◽  
Hongyun Si ◽  
Ting Liu
Keyword(s):  
Spatial Distribution ◽  
Urban Development ◽  
Central Area ◽  
Spatial Distribution Characteristics ◽  
Primary Driver ◽  
Effective Decision ◽  
Development Evaluation ◽  
Effective Decision Making ◽  
The City

Urban vitality is the primary driver of urban development. However, assessing urban vitality has always been a challenge. This paper builds on the research framework of sustainable development evaluation and selects evaluation indicators from the three systems of urban operation: economy, society, and environment. The deviation maximization (DM) method is used to evaluate urban vitality. Shanghai is then used as a case study for evaluation, and the comprehensive index of urban vitality is calculated for the city from 2010 to 2019. The evaluation results indicate that the urban vitality of Shanghai experienced a significant upward trend over ten years (2010–2019), which shows that the urban competitiveness of Shanghai is constantly strengthening. Next, the study focuses on the administrative region of Shanghai, to calculate the regional vitality level of Shanghai from 2010 to 2019 and to explore its spatial distribution characteristics. Then, a spatial autocorrelation analysis is used to explore the mechanism that affects the spatial distribution of urban vitality. The results demonstrate that the urban vitality in Shanghai shows a significant positive correlation in space. Moreover, there is a “High–High” gathering area, which includes Huangpu, Xuhui, Hongkou, and Changning in central area of Shanghai. This research provides a theoretical reference to support effective decision-making with respect to high-quality urban development.

scholarly journals Decision-Making Enhancement in a Big Data Environment: Application of the K-Means Algorithm to Mixed Data

2019 ◽  
Vol 9 (4) ◽  
pp. 293-302
Author(s):  
Oded Koren ◽  
Carina Antonia Hallin ◽  
Nir Perel ◽  
Dror Bendet
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Mixed Data ◽  
Systems Research ◽  
Information Systems Research ◽  
Effective Decision ◽  
Data Ecosystem ◽  
Effective Decision Making ◽  
Business Requirements

Abstract Big data research has become an important discipline in information systems research. However, the flood of data being generated on the Internet is increasingly unstructured and non-numeric in the form of images and texts. Thus, research indicates that there is an increasing need to develop more efficient algorithms for treating mixed data in big data for effective decision making. In this paper, we apply the classical K-means algorithm to both numeric and categorical attributes in big data platforms. We first present an algorithm that handles the problem of mixed data. We then use big data platforms to implement the algorithm, demonstrating its functionalities by applying the algorithm in a detailed case study. This provides us with a solid basis for performing more targeted profiling for decision making and research using big data. Consequently, the decision makers will be able to treat mixed data, numerical and categorical data, to explain and predict phenomena in the big data ecosystem. Our research includes a detailed end-to-end case study that presents an implementation of the suggested procedure. This demonstrates its capabilities and the advantages that allow it to improve the decision-making process by targeting organizations’ business requirements to a specific cluster[s]/profiles[s] based on the enhancement outcomes.

Events in Tweets: Graph Based Techniques

2020 ◽  
Vol 13 ◽  
Author(s):  
Abhaya Kumar Pradhan ◽  
Hrushikesha Mohanty ◽  
Rajendra Prasad Lal
Keyword(s):  
Event Detection ◽  
Social Networking Sites ◽  
Research Problem ◽  
Critical Survey ◽  
User Interactions ◽  
Detection Techniques ◽  
The Social ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Structural Semantics

Introduction: Mining Twitter streaming posts (i.e. tweets) to find events or the topics of interest has become a hot research problem. In the last decade, researchers have come up with various techniques like bag-of-words techniques, statistical methods, graph-based techniques, topic modelling approaches, NLP and ontology-based approaches, machine learning and deep learning methods for detecting events from tweets. Among these techniques, the graph-based technique is efficient in capturing the latent structural semantics in the tweet content by modelling word co-occurrence relationships as a graph and able to capture the activity dynamics by modelling the user-tweet and user-user interactions. Discussion: This article presents an overview of different event detection techniques and their methodologies. Specifically, this paper focuses on graph-based event detection techniques in Twitter and presents a critical survey on these techniques, their evaluation methodologies and datasets used. Further, some challenges in the area of event detection in Twitter along with future directions of research are presented. Conclusion: A Microblogging services and online social networking sites like Twitter provides a massive amount of valuable information on real-world happenings. There is a need for mining this information, which will help in understanding the social interest and effective decision making on various emergencies. However, event detection techniques need to be efficient in terms of time and memory and accurate for processing such voluminous, noisy and fastarriving information from Twitter.

scholarly journals Optimization of Density of Sugar Beet (Beta vulgaris L.) Production Quotas by Pointwise Geostatistic Methods

2005 ◽  
pp. 46-50
Author(s):  
Ildikó Nagy ◽  
János Tamás
Keyword(s):  
Decision Making ◽  
Boundary Condition ◽  
Sugar Beet ◽  
Regional Distribution ◽  
Buffer Zones ◽  
Effective Decision ◽  
Gis Environment ◽  
Effective Decision Making ◽  
Processing Solution ◽  
Standard Deviational Ellipse

The regional distribution of the Hungarian sugar beet production quotas was developed by the conventional concurrency relationships. In our research we analyzed 320 sectors of 9 factories with geostatistic methods in a GIS environment. The applied researches of spatial mean, spatial deviation, deviational ellipse have been introduced by us in this speciality. We used two different methods in our optimization inquiries, where the spatial segment of the standard deviational ellipse was based on a more robust preliminary data processing solution, and this is why it is a less parametricable method. The inquiry of the spatial buffer zones in production sectors ensures an obvious optimization possibility. We considered the supply route distances in both cases as a modeling boundary condition. Our results show that we introduced an effective decision making method to the occurent replanning of the production sectors with the pointwise density inquiries and the geometric analogy that was fitted to it.

Sign in / Sign up

Export Citation Format

Share Document